diff --git a/GECS/components/c_health.gd b/GECS/components/c_health.gd new file mode 100644 index 0000000..55b798c --- /dev/null +++ b/GECS/components/c_health.gd @@ -0,0 +1,9 @@ +class_name C_Health +extends Component + +@export var current: float = 100.0 +@export var maximum: float = 100.0 + +func _init(max_health: float = 100.0): + maximum = max_health + current = max_health diff --git a/GECS/components/c_health.gd.uid b/GECS/components/c_health.gd.uid new file mode 100644 index 0000000..8443f14 --- /dev/null +++ b/GECS/components/c_health.gd.uid @@ -0,0 +1 @@ +uid://bg653v2p104l1 diff --git a/GECS/components/c_spawn_point.gd b/GECS/components/c_spawn_point.gd new file mode 100644 index 0000000..b9588d5 --- /dev/null +++ b/GECS/components/c_spawn_point.gd @@ -0,0 +1,15 @@ +class_name C_SpawnPoint +extends Component + +@export var spawn_prefab: PackedScene +@export var spawn_frequency: float = 1 +var spawn_cooldown: float = 0 + +func _init(): + pass + +func should_spawn() -> bool: + return spawn_cooldown < 0 + +func start_spawn_cooldown() -> void: + spawn_cooldown = spawn_frequency diff --git a/GECS/components/c_spawn_point.gd.uid b/GECS/components/c_spawn_point.gd.uid new file mode 100644 index 0000000..ed91f28 --- /dev/null +++ b/GECS/components/c_spawn_point.gd.uid @@ -0,0 +1 @@ +uid://cmflg422miab6 diff --git a/GECS/components/c_transform.gd b/GECS/components/c_transform.gd new file mode 100644 index 0000000..2f9c209 --- /dev/null +++ b/GECS/components/c_transform.gd @@ -0,0 +1,7 @@ +class_name C_Transform +extends Component + +@export var position: Vector3 = Vector3.ZERO + +func _init(pos: Vector3 = Vector3.ZERO): + position = pos diff --git a/GECS/components/c_transform.gd.uid b/GECS/components/c_transform.gd.uid new file mode 100644 index 0000000..35c0f4b --- /dev/null +++ b/GECS/components/c_transform.gd.uid @@ -0,0 +1 @@ +uid://c4ihfoefv2vwd diff --git a/GECS/components/c_velocity.gd b/GECS/components/c_velocity.gd new file mode 100644 index 0000000..7d1b698 --- /dev/null +++ b/GECS/components/c_velocity.gd @@ -0,0 +1,7 @@ +class_name C_Velocity +extends Component + +@export var velocity: Vector3 = Vector3.ZERO + +func _init(vel: Vector3 = Vector3.ZERO): + velocity = vel diff --git a/GECS/components/c_velocity.gd.uid b/GECS/components/c_velocity.gd.uid new file mode 100644 index 0000000..b864f65 --- /dev/null +++ b/GECS/components/c_velocity.gd.uid @@ -0,0 +1 @@ +uid://cnqotfu7xgxwa diff --git a/GECS/entities/BasicEnemy/BasicEnemy.tscn b/GECS/entities/BasicEnemy/BasicEnemy.tscn new file mode 100644 index 0000000..8316627 --- /dev/null +++ b/GECS/entities/BasicEnemy/BasicEnemy.tscn @@ -0,0 +1,36 @@ +[gd_scene load_steps=11 format=3 uid="uid://bct6stmj0qyp2"] + +[ext_resource type="Script" uid="uid://ci3kmg1eck6gb" path="res://GECS/entities/BasicEnemy/e_basic_enemy.gd" id="1_h3v2l"] +[ext_resource type="Script" uid="uid://b6k13gc2m4e5s" path="res://addons/gecs/ecs/component.gd" id="2_gsgoc"] +[ext_resource type="Script" uid="uid://bg653v2p104l1" path="res://GECS/components/c_health.gd" id="3_unr0g"] +[ext_resource type="Script" uid="uid://c4ihfoefv2vwd" path="res://GECS/components/c_transform.gd" id="4_07lse"] +[ext_resource type="Script" uid="uid://cnqotfu7xgxwa" path="res://GECS/components/c_velocity.gd" id="5_vhe2b"] + +[sub_resource type="Resource" id="Resource_vas4o"] +script = ExtResource("3_unr0g") +metadata/_custom_type_script = "uid://bg653v2p104l1" + +[sub_resource type="Resource" id="Resource_yuljp"] +script = ExtResource("4_07lse") +metadata/_custom_type_script = "uid://c4ihfoefv2vwd" + +[sub_resource type="Resource" id="Resource_6hf1n"] +script = ExtResource("5_vhe2b") +velocity = Vector3(2, 0, 0) +metadata/_custom_type_script = "uid://cnqotfu7xgxwa" + +[sub_resource type="CapsuleShape3D" id="CapsuleShape3D_ocib1"] + +[sub_resource type="CapsuleMesh" id="CapsuleMesh_4ju8b"] + +[node name="BasicEnemy" type="CharacterBody3D"] +script = ExtResource("1_h3v2l") +component_resources = Array[ExtResource("2_gsgoc")]([SubResource("Resource_vas4o"), SubResource("Resource_yuljp"), SubResource("Resource_6hf1n")]) + +[node name="CollisionShape3D" type="CollisionShape3D" parent="."] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0) +shape = SubResource("CapsuleShape3D_ocib1") + +[node name="MeshInstance3D" type="MeshInstance3D" parent="."] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0) +mesh = SubResource("CapsuleMesh_4ju8b") diff --git a/GECS/entities/BasicEnemy/e_basic_enemy.gd b/GECS/entities/BasicEnemy/e_basic_enemy.gd new file mode 100644 index 0000000..6dc0f4b --- /dev/null +++ b/GECS/entities/BasicEnemy/e_basic_enemy.gd @@ -0,0 +1,10 @@ +@tool +class_name BasicEnemy +extends Entity + + +func on_ready(): + # Sync the entity's scene position to the Transform component + if has_component(C_Transform): + var c_trs = get_component(C_Transform) as C_Transform + self.global_position = c_trs.position diff --git a/GECS/entities/BasicEnemy/e_basic_enemy.gd.uid b/GECS/entities/BasicEnemy/e_basic_enemy.gd.uid new file mode 100644 index 0000000..f105100 --- /dev/null +++ b/GECS/entities/BasicEnemy/e_basic_enemy.gd.uid @@ -0,0 +1 @@ +uid://ci3kmg1eck6gb diff --git a/GECS/entities/Spawner/SpawnPoint.tscn b/GECS/entities/Spawner/SpawnPoint.tscn new file mode 100644 index 0000000..40d196c --- /dev/null +++ b/GECS/entities/Spawner/SpawnPoint.tscn @@ -0,0 +1,25 @@ +[gd_scene load_steps=7 format=3 uid="uid://d0075ch03hfri"] + +[ext_resource type="Script" uid="uid://ckqlc1tqyh7gm" path="res://GECS/entities/Spawner/e_spawn_point.gd" id="1_sp3sh"] +[ext_resource type="Script" uid="uid://b6k13gc2m4e5s" path="res://addons/gecs/ecs/component.gd" id="2_ksqpe"] +[ext_resource type="Script" uid="uid://cmflg422miab6" path="res://GECS/components/c_spawn_point.gd" id="3_ksqpe"] +[ext_resource type="PackedScene" uid="uid://bct6stmj0qyp2" path="res://GECS/entities/BasicEnemy/BasicEnemy.tscn" id="4_2ixog"] + +[sub_resource type="Resource" id="Resource_dgltp"] +script = ExtResource("3_ksqpe") +spawn_prefab = ExtResource("4_2ixog") +metadata/_custom_type_script = "uid://cmflg422miab6" + +[sub_resource type="SphereShape3D" id="SphereShape3D_sp3sh"] + +[node name="SpawnPoint" type="CharacterBody3D"] +collision_layer = 0 +collision_mask = 0 +motion_mode = 1 +script = ExtResource("1_sp3sh") +component_resources = Array[ExtResource("2_ksqpe")]([SubResource("Resource_dgltp")]) + +[node name="Marker3D" type="Marker3D" parent="."] + +[node name="CollisionShape3D" type="CollisionShape3D" parent="."] +shape = SubResource("SphereShape3D_sp3sh") diff --git a/GECS/entities/Spawner/e_spawn_point.gd b/GECS/entities/Spawner/e_spawn_point.gd new file mode 100644 index 0000000..99ba754 --- /dev/null +++ b/GECS/entities/Spawner/e_spawn_point.gd @@ -0,0 +1,14 @@ +@tool +class_name E_SpawnPoint +extends Entity + +@export var spawn_prefab: PackedScene +@export var spawn_frequency: float = -1 + +func on_ready(): + if has_component(C_SpawnPoint): + var c_spawn_point = get_component(C_SpawnPoint) as C_SpawnPoint + if spawn_prefab != null && spawn_prefab.can_instantiate(): + c_spawn_point.spawn_prefab = spawn_prefab + if spawn_frequency > 0: + c_spawn_point.spawn_frequency = spawn_frequency diff --git a/GECS/entities/Spawner/e_spawn_point.gd.uid b/GECS/entities/Spawner/e_spawn_point.gd.uid new file mode 100644 index 0000000..1d7bf7b --- /dev/null +++ b/GECS/entities/Spawner/e_spawn_point.gd.uid @@ -0,0 +1 @@ +uid://ckqlc1tqyh7gm diff --git a/GECS/systems/default_systems.tscn b/GECS/systems/default_systems.tscn new file mode 100644 index 0000000..cf6164f --- /dev/null +++ b/GECS/systems/default_systems.tscn @@ -0,0 +1,25 @@ +[gd_scene load_steps=4 format=3 uid="uid://b2v1bngfh5te"] + +[ext_resource type="Script" uid="uid://b3vi2ingux88g" path="res://addons/gecs/lib/system_group.gd" id="1_sk1vy"] +[ext_resource type="Script" uid="uid://dpglt5gt5ijrn" path="res://GECS/systems/s_movement.gd" id="2_aqda8"] +[ext_resource type="Script" uid="uid://cb2kev6dsctfu" path="res://GECS/systems/s_spawner.gd" id="2_hdbau"] + +[node name="Systems" type="Node"] + +[node name="gameplay" type="Node" parent="."] +script = ExtResource("1_sk1vy") +metadata/_custom_type_script = "uid://b3vi2ingux88g" + +[node name="SpawnSystem" type="Node" parent="gameplay"] +script = ExtResource("2_hdbau") +group = &"gameplay" +metadata/_custom_type_script = "uid://cb2kev6dsctfu" + +[node name="physics" type="Node" parent="."] +script = ExtResource("1_sk1vy") +metadata/_custom_type_script = "uid://b3vi2ingux88g" + +[node name="MovementSystem" type="Node" parent="physics"] +script = ExtResource("2_aqda8") +group = &"physics" +metadata/_custom_type_script = "uid://dpglt5gt5ijrn" diff --git a/GECS/systems/s_movement.gd b/GECS/systems/s_movement.gd new file mode 100644 index 0000000..cf5e599 --- /dev/null +++ b/GECS/systems/s_movement.gd @@ -0,0 +1,25 @@ +class_name MovementSystem +extends System + +func query(): + # Find all entities that have both transform and velocity + return q.with_all([C_Velocity]) + +func process(entities: Array[Entity], _components: Array, delta: float): + for entity in entities: + var c_velocity = entity.get_component(C_Velocity) as C_Velocity + + if entity.velocity.length() == 0: + entity.velocity = c_velocity.velocity + + # Add the gravity. + if not entity.is_on_floor(): + entity.velocity += entity.get_gravity() * delta + + # Bounce off screen edges (simple example) + if entity.global_position.x > 10 && entity.velocity.x > 0: + entity.velocity = -c_velocity.velocity + if entity.global_position.x < -10 && entity.velocity.x < 0: + entity.velocity = c_velocity.velocity + + entity.move_and_slide() diff --git a/GECS/systems/s_movement.gd.uid b/GECS/systems/s_movement.gd.uid new file mode 100644 index 0000000..a1eff13 --- /dev/null +++ b/GECS/systems/s_movement.gd.uid @@ -0,0 +1 @@ +uid://dpglt5gt5ijrn diff --git a/GECS/systems/s_spawner.gd b/GECS/systems/s_spawner.gd new file mode 100644 index 0000000..22bec3f --- /dev/null +++ b/GECS/systems/s_spawner.gd @@ -0,0 +1,21 @@ +class_name SpawnSystem +extends System + +func query(): + # Find all entities that have both transform and velocity + return q.with_all([C_SpawnPoint]).enabled() + +func process(entities: Array[Entity], _components: Array, delta: float): + for entity in entities: + var spawn_point = entity.get_component(C_SpawnPoint) as C_SpawnPoint + + if not spawn_point.should_spawn(): + spawn_point.spawn_cooldown -= delta + continue + + var spawned = spawn_point.spawn_prefab.instantiate() as Entity + get_tree().current_scene.add_child(spawned) + ECS.world.add_entity(spawned) + + spawned.global_position = entity.global_position + spawn_point.start_spawn_cooldown() diff --git a/GECS/systems/s_spawner.gd.uid b/GECS/systems/s_spawner.gd.uid new file mode 100644 index 0000000..08342af --- /dev/null +++ b/GECS/systems/s_spawner.gd.uid @@ -0,0 +1 @@ +uid://cb2kev6dsctfu diff --git a/addons/debug_menu/LICENSE.md b/addons/debug_menu/LICENSE.md new file mode 100644 index 0000000..54fc020 --- /dev/null +++ b/addons/debug_menu/LICENSE.md @@ -0,0 +1,21 @@ +# MIT License + +Copyright © 2023-present Hugo Locurcio and contributors + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/addons/debug_menu/debug_menu.gd b/addons/debug_menu/debug_menu.gd new file mode 100644 index 0000000..f99a5c6 --- /dev/null +++ b/addons/debug_menu/debug_menu.gd @@ -0,0 +1,482 @@ +extends CanvasLayer + +@export var fps: Label +@export var num_entities: Label +@export var frame_time: Label +@export var frame_number: Label +@export var frame_history_total_avg: Label +@export var frame_history_total_min: Label +@export var frame_history_total_max: Label +@export var frame_history_total_last: Label +@export var frame_history_cpu_avg: Label +@export var frame_history_cpu_min: Label +@export var frame_history_cpu_max: Label +@export var frame_history_cpu_last: Label +@export var frame_history_gpu_avg: Label +@export var frame_history_gpu_min: Label +@export var frame_history_gpu_max: Label +@export var frame_history_gpu_last: Label +@export var fps_graph: Panel +@export var total_graph: Panel +@export var cpu_graph: Panel +@export var gpu_graph: Panel +@export var information: Label +@export var settings: Label + +## The number of frames to keep in history for graph drawing and best/worst calculations. +## Currently, this also affects how FPS is measured. +const HISTORY_NUM_FRAMES = 150 + +const GRAPH_SIZE = Vector2(150, 25) +const GRAPH_MIN_FPS = 10 +const GRAPH_MAX_FPS = 160 +const GRAPH_MIN_FRAMETIME = 1.0 / GRAPH_MIN_FPS +const GRAPH_MAX_FRAMETIME = 1.0 / GRAPH_MAX_FPS + +## Debug menu display style. +enum Style { + HIDDEN, ## Debug menu is hidden. + VISIBLE_COMPACT, ## Debug menu is visible, with only the FPS, FPS cap (if any) and time taken to render the last frame. + VISIBLE_DETAILED, ## Debug menu is visible with full information, including graphs. + MAX, ## Represents the size of the Style enum. +} + +## The style to use when drawing the debug menu. +var style := Style.HIDDEN: + set(value): + style = value + match style: + Style.HIDDEN: + visible = false + Style.VISIBLE_COMPACT, Style.VISIBLE_DETAILED: + visible = true + frame_number.visible = style == Style.VISIBLE_DETAILED + $DebugMenu/VBoxContainer/FrameTimeHistory.visible = style == Style.VISIBLE_DETAILED + $DebugMenu/VBoxContainer/FPSGraph.visible = style == Style.VISIBLE_DETAILED + $DebugMenu/VBoxContainer/TotalGraph.visible = style == Style.VISIBLE_DETAILED + $DebugMenu/VBoxContainer/CPUGraph.visible = style == Style.VISIBLE_DETAILED + $DebugMenu/VBoxContainer/GPUGraph.visible = style == Style.VISIBLE_DETAILED + information.visible = style == Style.VISIBLE_DETAILED + settings.visible = style == Style.VISIBLE_DETAILED + +# Value of `Time.get_ticks_usec()` on the previous frame. +var last_tick := 0 + +var thread := Thread.new() + +## Returns the sum of all values of an array (use as a parameter to `Array.reduce()`). +var sum_func := func avg(accum: float, number: float) -> float: return accum + number + +# History of the last `HISTORY_NUM_FRAMES` rendered frames. +var frame_history_total: Array[float] = [] +var frame_history_cpu: Array[float] = [] +var frame_history_gpu: Array[float] = [] +var fps_history: Array[float] = [] # Only used for graphs. + +var frametime_avg := GRAPH_MIN_FRAMETIME +var frametime_cpu_avg := GRAPH_MAX_FRAMETIME +var frametime_gpu_avg := GRAPH_MIN_FRAMETIME +var frames_per_second := float(GRAPH_MIN_FPS) +var frame_time_gradient := Gradient.new() + +func _init() -> void: + # This must be done here instead of `_ready()` to avoid having `visibility_changed` be emitted immediately. + visible = false + + if not InputMap.has_action("cycle_debug_menu"): + # Create default input action if no user-defined override exists. + # We can't do it in the editor plugin's activation code as it doesn't seem to work there. + InputMap.add_action("cycle_debug_menu") + var event := InputEventKey.new() + event.keycode = KEY_F3 + InputMap.action_add_event("cycle_debug_menu", event) + + +func _ready() -> void: + fps_graph.draw.connect(_fps_graph_draw) + total_graph.draw.connect(_total_graph_draw) + cpu_graph.draw.connect(_cpu_graph_draw) + gpu_graph.draw.connect(_gpu_graph_draw) + + fps_history.resize(HISTORY_NUM_FRAMES) + frame_history_total.resize(HISTORY_NUM_FRAMES) + frame_history_cpu.resize(HISTORY_NUM_FRAMES) + frame_history_gpu.resize(HISTORY_NUM_FRAMES) + + # NOTE: Both FPS and frametimes are colored following FPS logic + # (red = 10 FPS, yellow = 60 FPS, green = 110 FPS, cyan = 160 FPS). + # This makes the color gradient non-linear. + # Colors are taken from . + frame_time_gradient.set_color(0, Color8(239, 68, 68)) # red-500 + frame_time_gradient.set_color(1, Color8(56, 189, 248)) # light-blue-400 + frame_time_gradient.add_point(0.3333, Color8(250, 204, 21)) # yellow-400 + frame_time_gradient.add_point(0.6667, Color8(128, 226, 95)) # 50-50 mix of lime-400 and green-400 + + get_viewport().size_changed.connect(update_settings_label) + + # Display loading text while information is being queried, + # in case the user toggles the full debug menu just after starting the project. + information.text = "Loading hardware information...\n\n " + settings.text = "Loading project information..." + thread.start( + func(): + # Disable thread safety checks as they interfere with this add-on. + # This only affects this particular thread, not other thread instances in the project. + # See for details. + # Use a Callable so that this can be ignored on Godot 4.0 without causing a script error + # (thread safety checks were added in Godot 4.1). + if Engine.get_version_info()["hex"] >= 0x040100: + Callable(Thread, "set_thread_safety_checks_enabled").call(false) + + # Enable required time measurements to display CPU/GPU frame time information. + # These lines are time-consuming operations, so run them in a separate thread. + RenderingServer.viewport_set_measure_render_time(get_viewport().get_viewport_rid(), true) + update_information_label() + update_settings_label() + ) + + +func _input(event: InputEvent) -> void: + if event.is_action_pressed("cycle_debug_menu"): + style = wrapi(style + 1, 0, Style.MAX) as Style + + +func _exit_tree() -> void: + thread.wait_to_finish() + + +## Update hardware information label (this can change at runtime based on window +## size and graphics settings). This is only called when the window is resized. +## To update when graphics settings are changed, the function must be called manually +## using `DebugMenu.update_settings_label()`. +func update_settings_label() -> void: + settings.text = "" + if ProjectSettings.has_setting("application/config/version"): + settings.text += "Project Version: %s\n" % ProjectSettings.get_setting("application/config/version") + + var rendering_method := str(ProjectSettings.get_setting_with_override("rendering/renderer/rendering_method")) + var rendering_method_string := rendering_method + match rendering_method: + "forward_plus": + rendering_method_string = "Forward+" + "mobile": + rendering_method_string = "Forward Mobile" + "gl_compatibility": + rendering_method_string = "Compatibility" + settings.text += "Rendering Method: %s\n" % rendering_method_string + + var viewport := get_viewport() + + # The size of the viewport rendering, which determines which resolution 3D is rendered at. + var viewport_render_size := Vector2i() + + if viewport.content_scale_mode == Window.CONTENT_SCALE_MODE_VIEWPORT: + viewport_render_size = viewport.get_visible_rect().size + settings.text += "Viewport: %d×%d, Window: %d×%d\n" % [viewport.get_visible_rect().size.x, viewport.get_visible_rect().size.y, viewport.size.x, viewport.size.y] + else: + # Window size matches viewport size. + viewport_render_size = viewport.size + settings.text += "Viewport: %d×%d\n" % [viewport.size.x, viewport.size.y] + + # Display 3D settings only if relevant. + if viewport.get_camera_3d(): + var scaling_3d_mode_string := "(unknown)" + match viewport.scaling_3d_mode: + Viewport.SCALING_3D_MODE_BILINEAR: + scaling_3d_mode_string = "Bilinear" + Viewport.SCALING_3D_MODE_FSR: + scaling_3d_mode_string = "FSR 1.0" + Viewport.SCALING_3D_MODE_FSR2: + scaling_3d_mode_string = "FSR 2.2" + + var antialiasing_3d_string := "" + if viewport.scaling_3d_mode == Viewport.SCALING_3D_MODE_FSR2: + # The FSR2 scaling mode includes its own temporal antialiasing implementation. + antialiasing_3d_string += (" + " if not antialiasing_3d_string.is_empty() else "") + "FSR 2.2" + if viewport.scaling_3d_mode != Viewport.SCALING_3D_MODE_FSR2 and viewport.use_taa: + # Godot's own TAA is ignored when using FSR2 scaling mode, as FSR2 provides its own TAA implementation. + antialiasing_3d_string += (" + " if not antialiasing_3d_string.is_empty() else "") + "TAA" + if viewport.msaa_3d >= Viewport.MSAA_2X: + antialiasing_3d_string += (" + " if not antialiasing_3d_string.is_empty() else "") + "%d× MSAA" % pow(2, viewport.msaa_3d) + if viewport.screen_space_aa == Viewport.SCREEN_SPACE_AA_FXAA: + antialiasing_3d_string += (" + " if not antialiasing_3d_string.is_empty() else "") + "FXAA" + + settings.text += "3D scale (%s): %d%% = %d×%d" % [ + scaling_3d_mode_string, + viewport.scaling_3d_scale * 100, + viewport_render_size.x * viewport.scaling_3d_scale, + viewport_render_size.y * viewport.scaling_3d_scale, + ] + + if not antialiasing_3d_string.is_empty(): + settings.text += "\n3D Antialiasing: %s" % antialiasing_3d_string + + var environment := viewport.get_camera_3d().get_world_3d().environment + if environment: + if environment.ssr_enabled: + settings.text += "\nSSR: %d Steps" % environment.ssr_max_steps + + if environment.ssao_enabled: + settings.text += "\nSSAO: On" + if environment.ssil_enabled: + settings.text += "\nSSIL: On" + + if environment.sdfgi_enabled: + settings.text += "\nSDFGI: %d Cascades" % environment.sdfgi_cascades + + if environment.glow_enabled: + settings.text += "\nGlow: On" + + if environment.volumetric_fog_enabled: + settings.text += "\nVolumetric Fog: On" + var antialiasing_2d_string := "" + if viewport.msaa_2d >= Viewport.MSAA_2X: + antialiasing_2d_string = "%d× MSAA" % pow(2, viewport.msaa_2d) + + if not antialiasing_2d_string.is_empty(): + settings.text += "\n2D Antialiasing: %s" % antialiasing_2d_string + + +## Update hardware/software information label (this never changes at runtime). +func update_information_label() -> void: + var adapter_string := "" + # Make "NVIDIA Corporation" and "NVIDIA" be considered identical (required when using OpenGL to avoid redundancy). + if RenderingServer.get_video_adapter_vendor().trim_suffix(" Corporation") in RenderingServer.get_video_adapter_name(): + # Avoid repeating vendor name before adapter name. + # Trim redundant suffix sometimes reported by NVIDIA graphics cards when using OpenGL. + adapter_string = RenderingServer.get_video_adapter_name().trim_suffix("/PCIe/SSE2") + else: + adapter_string = RenderingServer.get_video_adapter_vendor() + " - " + RenderingServer.get_video_adapter_name().trim_suffix("/PCIe/SSE2") + + # Graphics driver version information isn't always availble. + var driver_info := OS.get_video_adapter_driver_info() + var driver_info_string := "" + if driver_info.size() >= 2: + driver_info_string = driver_info[1] + else: + driver_info_string = "(unknown)" + + var release_string := "" + if OS.has_feature("editor"): + # Editor build (implies `debug`). + release_string = "editor" + elif OS.has_feature("debug"): + # Debug export template build. + release_string = "debug" + else: + # Release export template build. + release_string = "release" + + var rendering_method := str(ProjectSettings.get_setting_with_override("rendering/renderer/rendering_method")) + var rendering_driver := str(ProjectSettings.get_setting_with_override("rendering/rendering_device/driver")) + var graphics_api_string := rendering_driver + if rendering_method != "gl_compatibility": + if rendering_driver == "d3d12": + graphics_api_string = "Direct3D 12" + elif rendering_driver == "metal": + graphics_api_string = "Metal" + elif rendering_driver == "vulkan": + if OS.has_feature("macos") or OS.has_feature("ios"): + graphics_api_string = "Vulkan via MoltenVK" + else: + graphics_api_string = "Vulkan" + else: + if rendering_driver == "opengl3_angle": + graphics_api_string = "OpenGL via ANGLE" + elif OS.has_feature("mobile") or rendering_driver == "opengl3_es": + graphics_api_string = "OpenGL ES" + elif OS.has_feature("web"): + graphics_api_string = "WebGL" + elif rendering_driver == "opengl3": + graphics_api_string = "OpenGL" + + information.text = ( + "%s, %d threads\n" % [OS.get_processor_name().replace("(R)", "").replace("(TM)", ""), OS.get_processor_count()] + +"%s %s (%s %s), %s %s\n" % [OS.get_name(), "64-bit" if OS.has_feature("64") else "32-bit", release_string, "double" if OS.has_feature("double") else "single", graphics_api_string, RenderingServer.get_video_adapter_api_version()] + +"%s, %s" % [adapter_string, driver_info_string] + ) + + +func _fps_graph_draw() -> void: + var fps_polyline := PackedVector2Array() + fps_polyline.resize(HISTORY_NUM_FRAMES) + for fps_index in fps_history.size(): + fps_polyline[fps_index] = Vector2( + remap(fps_index, 0, fps_history.size(), 0, GRAPH_SIZE.x), + remap(clampf(fps_history[fps_index], GRAPH_MIN_FPS, GRAPH_MAX_FPS), GRAPH_MIN_FPS, GRAPH_MAX_FPS, GRAPH_SIZE.y, 0.0) + ) + # Don't use antialiasing to speed up line drawing, but use a width that scales with + # viewport scale to keep the line easily readable on hiDPI displays. + fps_graph.draw_polyline(fps_polyline, frame_time_gradient.sample(remap(frames_per_second, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)), 1.0) + + +func _total_graph_draw() -> void: + var total_polyline := PackedVector2Array() + total_polyline.resize(HISTORY_NUM_FRAMES) + for total_index in frame_history_total.size(): + total_polyline[total_index] = Vector2( + remap(total_index, 0, frame_history_total.size(), 0, GRAPH_SIZE.x), + remap(clampf(frame_history_total[total_index], GRAPH_MIN_FPS, GRAPH_MAX_FPS), GRAPH_MIN_FPS, GRAPH_MAX_FPS, GRAPH_SIZE.y, 0.0) + ) + # Don't use antialiasing to speed up line drawing, but use a width that scales with + # viewport scale to keep the line easily readable on hiDPI displays. + total_graph.draw_polyline(total_polyline, frame_time_gradient.sample(remap(1000.0 / frametime_avg, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)), 1.0) + + +func _cpu_graph_draw() -> void: + var cpu_polyline := PackedVector2Array() + cpu_polyline.resize(HISTORY_NUM_FRAMES) + for cpu_index in frame_history_cpu.size(): + cpu_polyline[cpu_index] = Vector2( + remap(cpu_index, 0, frame_history_cpu.size(), 0, GRAPH_SIZE.x), + remap(clampf(frame_history_cpu[cpu_index], GRAPH_MIN_FPS, GRAPH_MAX_FPS), GRAPH_MIN_FPS, GRAPH_MAX_FPS, GRAPH_SIZE.y, 0.0) + ) + # Don't use antialiasing to speed up line drawing, but use a width that scales with + # viewport scale to keep the line easily readable on hiDPI displays. + cpu_graph.draw_polyline(cpu_polyline, frame_time_gradient.sample(remap(1000.0 / frametime_cpu_avg, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)), 1.0) + + +func _gpu_graph_draw() -> void: + var gpu_polyline := PackedVector2Array() + gpu_polyline.resize(HISTORY_NUM_FRAMES) + for gpu_index in frame_history_gpu.size(): + gpu_polyline[gpu_index] = Vector2( + remap(gpu_index, 0, frame_history_gpu.size(), 0, GRAPH_SIZE.x), + remap(clampf(frame_history_gpu[gpu_index], GRAPH_MIN_FPS, GRAPH_MAX_FPS), GRAPH_MIN_FPS, GRAPH_MAX_FPS, GRAPH_SIZE.y, 0.0) + ) + # Don't use antialiasing to speed up line drawing, but use a width that scales with + # viewport scale to keep the line easily readable on hiDPI displays. + gpu_graph.draw_polyline(gpu_polyline, frame_time_gradient.sample(remap(1000.0 / frametime_gpu_avg, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)), 1.0) + + +func _process(_delta: float) -> void: + if visible: + fps_graph.queue_redraw() + total_graph.queue_redraw() + cpu_graph.queue_redraw() + gpu_graph.queue_redraw() + + # Difference between the last two rendered frames in milliseconds. + var frametime := (Time.get_ticks_usec() - last_tick) * 0.001 + + frame_history_total.push_back(frametime) + if frame_history_total.size() > HISTORY_NUM_FRAMES: + frame_history_total.pop_front() + + # Frametimes are colored following FPS logic (red = 10 FPS, yellow = 60 FPS, green = 110 FPS, cyan = 160 FPS). + # This makes the color gradient non-linear. + frametime_avg = frame_history_total.reduce(sum_func) / frame_history_total.size() + frame_history_total_avg.text = str(frametime_avg).pad_decimals(2) + frame_history_total_avg.modulate = frame_time_gradient.sample(remap(1000.0 / frametime_avg, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)) + + var frametime_min: float = frame_history_total.min() + frame_history_total_min.text = str(frametime_min).pad_decimals(2) + frame_history_total_min.modulate = frame_time_gradient.sample(remap(1000.0 / frametime_min, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)) + + var frametime_max: float = frame_history_total.max() + frame_history_total_max.text = str(frametime_max).pad_decimals(2) + frame_history_total_max.modulate = frame_time_gradient.sample(remap(1000.0 / frametime_max, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)) + + frame_history_total_last.text = str(frametime).pad_decimals(2) + frame_history_total_last.modulate = frame_time_gradient.sample(remap(1000.0 / frametime, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)) + + var viewport_rid := get_viewport().get_viewport_rid() + var frametime_cpu := RenderingServer.viewport_get_measured_render_time_cpu(viewport_rid) + RenderingServer.get_frame_setup_time_cpu() + frame_history_cpu.push_back(frametime_cpu) + if frame_history_cpu.size() > HISTORY_NUM_FRAMES: + frame_history_cpu.pop_front() + + frametime_cpu_avg = frame_history_cpu.reduce(sum_func) / frame_history_cpu.size() + frame_history_cpu_avg.text = str(frametime_cpu_avg).pad_decimals(2) + frame_history_cpu_avg.modulate = frame_time_gradient.sample(remap(1000.0 / frametime_cpu_avg, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)) + + var frametime_cpu_min: float = frame_history_cpu.min() + frame_history_cpu_min.text = str(frametime_cpu_min).pad_decimals(2) + frame_history_cpu_min.modulate = frame_time_gradient.sample(remap(1000.0 / frametime_cpu_min, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)) + + var frametime_cpu_max: float = frame_history_cpu.max() + frame_history_cpu_max.text = str(frametime_cpu_max).pad_decimals(2) + frame_history_cpu_max.modulate = frame_time_gradient.sample(remap(1000.0 / frametime_cpu_max, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)) + + frame_history_cpu_last.text = str(frametime_cpu).pad_decimals(2) + frame_history_cpu_last.modulate = frame_time_gradient.sample(remap(1000.0 / frametime_cpu, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)) + + var frametime_gpu := RenderingServer.viewport_get_measured_render_time_gpu(viewport_rid) + frame_history_gpu.push_back(frametime_gpu) + if frame_history_gpu.size() > HISTORY_NUM_FRAMES: + frame_history_gpu.pop_front() + + frametime_gpu_avg = frame_history_gpu.reduce(sum_func) / frame_history_gpu.size() + frame_history_gpu_avg.text = str(frametime_gpu_avg).pad_decimals(2) + frame_history_gpu_avg.modulate = frame_time_gradient.sample(remap(1000.0 / frametime_gpu_avg, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)) + + var frametime_gpu_min: float = frame_history_gpu.min() + frame_history_gpu_min.text = str(frametime_gpu_min).pad_decimals(2) + frame_history_gpu_min.modulate = frame_time_gradient.sample(remap(1000.0 / frametime_gpu_min, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)) + + var frametime_gpu_max: float = frame_history_gpu.max() + frame_history_gpu_max.text = str(frametime_gpu_max).pad_decimals(2) + frame_history_gpu_max.modulate = frame_time_gradient.sample(remap(1000.0 / frametime_gpu_max, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)) + + frame_history_gpu_last.text = str(frametime_gpu).pad_decimals(2) + frame_history_gpu_last.modulate = frame_time_gradient.sample(remap(1000.0 / frametime_gpu, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)) + + frames_per_second = 1000.0 / frametime_avg + fps_history.push_back(frames_per_second) + if fps_history.size() > HISTORY_NUM_FRAMES: + fps_history.pop_front() + + fps.text = str(floor(frames_per_second)) + " FPS" + var frame_time_color := frame_time_gradient.sample(remap(frames_per_second, GRAPH_MIN_FPS, GRAPH_MAX_FPS, 0.0, 1.0)) + fps.modulate = frame_time_color + + num_entities.text = "Entities: " + str(ECS.world.entities.size()) + + frame_time.text = str(frametime).pad_decimals(2) + " mspf" + frame_time.modulate = frame_time_color + + var vsync_string := "" + match DisplayServer.window_get_vsync_mode(): + DisplayServer.VSYNC_ENABLED: + vsync_string = "V-Sync" + DisplayServer.VSYNC_ADAPTIVE: + vsync_string = "Adaptive V-Sync" + DisplayServer.VSYNC_MAILBOX: + vsync_string = "Mailbox V-Sync" + + if Engine.max_fps > 0 or OS.low_processor_usage_mode: + # Display FPS cap determined by `Engine.max_fps` or low-processor usage mode sleep duration + # (the lowest FPS cap is used). + var low_processor_max_fps := roundi(1000000.0 / OS.low_processor_usage_mode_sleep_usec) + var fps_cap := low_processor_max_fps + if Engine.max_fps > 0: + fps_cap = mini(Engine.max_fps, low_processor_max_fps) + frame_time.text += " (cap: " + str(fps_cap) + " FPS" + + if not vsync_string.is_empty(): + frame_time.text += " + " + vsync_string + + frame_time.text += ")" + else: + if not vsync_string.is_empty(): + frame_time.text += " (" + vsync_string + ")" + + frame_number.text = "Frame: " + str(Engine.get_frames_drawn()) + + last_tick = Time.get_ticks_usec() + + +func _on_visibility_changed() -> void: + if visible: + # Reset graphs to prevent them from looking strange before `HISTORY_NUM_FRAMES` frames + # have been drawn. + var frametime_last := (Time.get_ticks_usec() - last_tick) * 0.001 + fps_history.resize(HISTORY_NUM_FRAMES) + fps_history.fill(1000.0 / frametime_last) + frame_history_total.resize(HISTORY_NUM_FRAMES) + frame_history_total.fill(frametime_last) + frame_history_cpu.resize(HISTORY_NUM_FRAMES) + var viewport_rid := get_viewport().get_viewport_rid() + frame_history_cpu.fill(RenderingServer.viewport_get_measured_render_time_cpu(viewport_rid) + RenderingServer.get_frame_setup_time_cpu()) + frame_history_gpu.resize(HISTORY_NUM_FRAMES) + frame_history_gpu.fill(RenderingServer.viewport_get_measured_render_time_gpu(viewport_rid)) diff --git a/addons/debug_menu/debug_menu.gd.uid b/addons/debug_menu/debug_menu.gd.uid new file mode 100644 index 0000000..c5783fe --- /dev/null +++ b/addons/debug_menu/debug_menu.gd.uid @@ -0,0 +1 @@ +uid://datrr7iu7jc62 diff --git a/addons/debug_menu/debug_menu.tscn b/addons/debug_menu/debug_menu.tscn new file mode 100644 index 0000000..f83c882 --- /dev/null +++ b/addons/debug_menu/debug_menu.tscn @@ -0,0 +1,412 @@ +[gd_scene load_steps=3 format=3 uid="uid://cggqb75a8w8r"] + +[ext_resource type="Script" uid="uid://datrr7iu7jc62" path="res://addons/debug_menu/debug_menu.gd" id="1_p440y"] + +[sub_resource type="StyleBoxFlat" id="StyleBoxFlat_ki0n8"] +bg_color = Color(0, 0, 0, 0.25098) + +[node name="CanvasLayer" type="CanvasLayer" node_paths=PackedStringArray("fps", "num_entities", "frame_time", "frame_number", "frame_history_total_avg", "frame_history_total_min", "frame_history_total_max", "frame_history_total_last", "frame_history_cpu_avg", "frame_history_cpu_min", "frame_history_cpu_max", "frame_history_cpu_last", "frame_history_gpu_avg", "frame_history_gpu_min", "frame_history_gpu_max", "frame_history_gpu_last", "fps_graph", "total_graph", "cpu_graph", "gpu_graph", "information", "settings")] +layer = 128 +script = ExtResource("1_p440y") +fps = NodePath("DebugMenu/VBoxContainer/FPS") +num_entities = NodePath("DebugMenu/VBoxContainer/NumEntities") +frame_time = NodePath("DebugMenu/VBoxContainer/FrameTime") +frame_number = NodePath("DebugMenu/VBoxContainer/FrameNumber") +frame_history_total_avg = NodePath("DebugMenu/VBoxContainer/FrameTimeHistory/TotalAvg") +frame_history_total_min = NodePath("DebugMenu/VBoxContainer/FrameTimeHistory/TotalMin") +frame_history_total_max = NodePath("DebugMenu/VBoxContainer/FrameTimeHistory/TotalMax") +frame_history_total_last = NodePath("DebugMenu/VBoxContainer/FrameTimeHistory/TotalLast") +frame_history_cpu_avg = NodePath("DebugMenu/VBoxContainer/FrameTimeHistory/CPUAvg") +frame_history_cpu_min = NodePath("DebugMenu/VBoxContainer/FrameTimeHistory/CPUMin") +frame_history_cpu_max = NodePath("DebugMenu/VBoxContainer/FrameTimeHistory/CPUMax") +frame_history_cpu_last = NodePath("DebugMenu/VBoxContainer/FrameTimeHistory/CPULast") +frame_history_gpu_avg = NodePath("DebugMenu/VBoxContainer/FrameTimeHistory/GPUAvg") +frame_history_gpu_min = NodePath("DebugMenu/VBoxContainer/FrameTimeHistory/GPUMin") +frame_history_gpu_max = NodePath("DebugMenu/VBoxContainer/FrameTimeHistory/GPUMax") +frame_history_gpu_last = NodePath("DebugMenu/VBoxContainer/FrameTimeHistory/GPULast") +fps_graph = NodePath("DebugMenu/VBoxContainer/FPSGraph/Graph") +total_graph = NodePath("DebugMenu/VBoxContainer/TotalGraph/Graph") +cpu_graph = NodePath("DebugMenu/VBoxContainer/CPUGraph/Graph") +gpu_graph = NodePath("DebugMenu/VBoxContainer/GPUGraph/Graph") +information = NodePath("DebugMenu/VBoxContainer/Information") +settings = NodePath("DebugMenu/VBoxContainer/Settings") + +[node name="DebugMenu" type="Control" parent="."] +custom_minimum_size = Vector2(400, 400) +layout_mode = 3 +anchors_preset = 1 +anchor_left = 1.0 +anchor_right = 1.0 +offset_left = -416.0 +offset_top = 8.0 +offset_right = -16.0 +offset_bottom = 408.0 +grow_horizontal = 0 +size_flags_horizontal = 8 +size_flags_vertical = 4 +mouse_filter = 2 + +[node name="VBoxContainer" type="VBoxContainer" parent="DebugMenu"] +layout_mode = 1 +anchors_preset = 1 +anchor_left = 1.0 +anchor_right = 1.0 +offset_left = -300.0 +offset_bottom = 374.0 +grow_horizontal = 0 +mouse_filter = 2 +theme_override_constants/separation = 0 + +[node name="FPS" type="Label" parent="DebugMenu/VBoxContainer"] +modulate = Color(0, 1, 0, 1) +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/line_spacing = 0 +theme_override_constants/outline_size = 5 +theme_override_font_sizes/font_size = 18 +text = "60 FPS" +horizontal_alignment = 2 + +[node name="NumEntities" type="Label" parent="DebugMenu/VBoxContainer"] +modulate = Color(0, 1, 0, 1) +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/line_spacing = 0 +theme_override_constants/outline_size = 5 +theme_override_font_sizes/font_size = 18 +text = "0 Ents" +horizontal_alignment = 2 + +[node name="FrameTime" type="Label" parent="DebugMenu/VBoxContainer"] +modulate = Color(0, 1, 0, 1) +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "16.67 mspf (cap: 123 FPS + Adaptive V-Sync)" +horizontal_alignment = 2 + +[node name="FrameNumber" type="Label" parent="DebugMenu/VBoxContainer"] +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "Frame: 1234" +horizontal_alignment = 2 + +[node name="FrameTimeHistory" type="GridContainer" parent="DebugMenu/VBoxContainer"] +layout_mode = 2 +size_flags_horizontal = 8 +mouse_filter = 2 +theme_override_constants/h_separation = 0 +theme_override_constants/v_separation = 0 +columns = 5 + +[node name="Spacer" type="Control" parent="DebugMenu/VBoxContainer/FrameTimeHistory"] +custom_minimum_size = Vector2(60, 0) +layout_mode = 2 +mouse_filter = 2 + +[node name="AvgHeader" type="Label" parent="DebugMenu/VBoxContainer/FrameTimeHistory"] +custom_minimum_size = Vector2(50, 0) +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "Average" +horizontal_alignment = 2 + +[node name="MinHeader" type="Label" parent="DebugMenu/VBoxContainer/FrameTimeHistory"] +custom_minimum_size = Vector2(50, 0) +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "Best" +horizontal_alignment = 2 + +[node name="MaxHeader" type="Label" parent="DebugMenu/VBoxContainer/FrameTimeHistory"] +custom_minimum_size = Vector2(50, 0) +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "Worst" +horizontal_alignment = 2 + +[node name="LastHeader" type="Label" parent="DebugMenu/VBoxContainer/FrameTimeHistory"] +custom_minimum_size = Vector2(50, 0) +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "Last" +horizontal_alignment = 2 + +[node name="TotalHeader" type="Label" parent="DebugMenu/VBoxContainer/FrameTimeHistory"] +custom_minimum_size = Vector2(50, 0) +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "Total:" +horizontal_alignment = 2 + +[node name="TotalAvg" type="Label" parent="DebugMenu/VBoxContainer/FrameTimeHistory"] +modulate = Color(0, 1, 0, 1) +custom_minimum_size = Vector2(50, 0) +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "123.45" +horizontal_alignment = 2 + +[node name="TotalMin" type="Label" parent="DebugMenu/VBoxContainer/FrameTimeHistory"] +modulate = Color(0, 1, 0, 1) +custom_minimum_size = Vector2(50, 0) +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "123.45" +horizontal_alignment = 2 + +[node name="TotalMax" type="Label" parent="DebugMenu/VBoxContainer/FrameTimeHistory"] +modulate = Color(0, 1, 0, 1) +custom_minimum_size = Vector2(50, 0) +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "123.45" +horizontal_alignment = 2 + +[node name="TotalLast" type="Label" parent="DebugMenu/VBoxContainer/FrameTimeHistory"] +modulate = Color(0, 1, 0, 1) +custom_minimum_size = Vector2(50, 0) +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "123.45" +horizontal_alignment = 2 + +[node name="CPUHeader" type="Label" parent="DebugMenu/VBoxContainer/FrameTimeHistory"] +custom_minimum_size = Vector2(50, 0) +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "CPU:" +horizontal_alignment = 2 + +[node name="CPUAvg" type="Label" parent="DebugMenu/VBoxContainer/FrameTimeHistory"] +modulate = Color(0, 1, 0, 1) +custom_minimum_size = Vector2(50, 0) +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "123.45" +horizontal_alignment = 2 + +[node name="CPUMin" type="Label" parent="DebugMenu/VBoxContainer/FrameTimeHistory"] +modulate = Color(0, 1, 0, 1) +custom_minimum_size = Vector2(50, 0) +layout_mode = 2 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "12.34" +horizontal_alignment = 2 + +[node name="CPUMax" type="Label" parent="DebugMenu/VBoxContainer/FrameTimeHistory"] +modulate = Color(0, 1, 0, 1) +custom_minimum_size = Vector2(50, 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+mouse_filter = 2 +theme_override_styles/panel = SubResource("StyleBoxFlat_ki0n8") + +[node name="TotalGraph" type="HBoxContainer" parent="DebugMenu/VBoxContainer"] +layout_mode = 2 +mouse_filter = 2 +alignment = 2 + +[node name="Title" type="Label" parent="DebugMenu/VBoxContainer/TotalGraph"] +custom_minimum_size = Vector2(0, 27) +layout_mode = 2 +size_flags_horizontal = 8 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "Total: ↓" +vertical_alignment = 1 + +[node name="Graph" type="Panel" parent="DebugMenu/VBoxContainer/TotalGraph"] +custom_minimum_size = Vector2(150, 25) +layout_mode = 2 +size_flags_vertical = 0 +mouse_filter = 2 +theme_override_styles/panel = SubResource("StyleBoxFlat_ki0n8") + +[node name="CPUGraph" type="HBoxContainer" parent="DebugMenu/VBoxContainer"] +layout_mode = 2 +mouse_filter = 2 +alignment = 2 + +[node name="Title" type="Label" parent="DebugMenu/VBoxContainer/CPUGraph"] +custom_minimum_size = Vector2(0, 27) +layout_mode = 2 +size_flags_horizontal = 8 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = "CPU: ↓" +vertical_alignment = 1 + +[node name="Graph" type="Panel" parent="DebugMenu/VBoxContainer/CPUGraph"] +custom_minimum_size = Vector2(150, 25) +layout_mode = 2 +size_flags_vertical = 0 +mouse_filter = 2 +theme_override_styles/panel = SubResource("StyleBoxFlat_ki0n8") + +[node name="GPUGraph" type="HBoxContainer" parent="DebugMenu/VBoxContainer"] +layout_mode = 2 +mouse_filter = 2 +alignment = 2 + +[node name="Title" type="Label" parent="DebugMenu/VBoxContainer/GPUGraph"] +custom_minimum_size = Vector2(0, 27) +layout_mode = 2 +size_flags_horizontal = 8 +theme_override_colors/font_outline_color = Color(0, 0, 0, 1) +theme_override_constants/outline_size = 3 +theme_override_font_sizes/font_size = 12 +text = 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"Project Version: 1.2.3 +Rendering Method: Forward+ +Window: 1234×567, Viewport: 1234×567 +3D Scale (FSR 1.0): 100% = 1234×567 +3D Antialiasing: TAA + 2× MSAA + FXAA +SSR: 123 Steps +SSAO: On +SSIL: On +SDFGI: 1 Cascades +Glow: On +Volumetric Fog: On +2D Antialiasing: 2× MSAA" +horizontal_alignment = 2 + +[connection signal="visibility_changed" from="." to="." method="_on_visibility_changed"] diff --git a/addons/debug_menu/plugin.cfg b/addons/debug_menu/plugin.cfg new file mode 100644 index 0000000..54100f7 --- /dev/null +++ b/addons/debug_menu/plugin.cfg @@ -0,0 +1,7 @@ +[plugin] + +name="Debug Menu" +description="In-game debug menu displaying performance metrics and hardware information" +author="Calinou" +version="1.2.0" +script="plugin.gd" diff --git a/addons/debug_menu/plugin.gd b/addons/debug_menu/plugin.gd new file mode 100644 index 0000000..5ec132e --- /dev/null +++ b/addons/debug_menu/plugin.gd @@ -0,0 +1,29 @@ +@tool +extends EditorPlugin + +func _enter_tree() -> void: + add_autoload_singleton("DebugMenu", "res://addons/debug_menu/debug_menu.tscn") + + # FIXME: This appears to do nothing. +# if not ProjectSettings.has_setting("application/config/version"): +# ProjectSettings.set_setting("application/config/version", "1.0.0") +# +# ProjectSettings.set_initial_value("application/config/version", "1.0.0") +# ProjectSettings.add_property_info({ +# name = "application/config/version", +# type = TYPE_STRING, +# }) +# +# if not InputMap.has_action("cycle_debug_menu"): +# InputMap.add_action("cycle_debug_menu") +# var event := InputEventKey.new() +# event.keycode = KEY_F3 +# InputMap.action_add_event("cycle_debug_menu", event) +# +# ProjectSettings.save() + + +func _exit_tree() -> void: + remove_autoload_singleton("DebugMenu") + # Don't remove the project setting's value and input map action, + # as the plugin may be re-enabled in the future. diff --git a/addons/debug_menu/plugin.gd.uid b/addons/debug_menu/plugin.gd.uid new file mode 100644 index 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granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/addons/gdUnit4/bin/GdUnitCmdTool.gd b/addons/gdUnit4/bin/GdUnitCmdTool.gd new file mode 100644 index 0000000..cae9138 --- /dev/null +++ b/addons/gdUnit4/bin/GdUnitCmdTool.gd @@ -0,0 +1,21 @@ +#!/usr/bin/env -S godot -s +extends SceneTree + + +var _cli_runner: GdUnitTestCIRunner + + +func _initialize() -> void: + DisplayServer.window_set_mode(DisplayServer.WINDOW_MODE_MINIMIZED) + _cli_runner = GdUnitTestCIRunner.new() + root.add_child(_cli_runner) + + +# do not use print statements on _finalize it results in random crashes +func _finalize() -> void: + queue_delete(_cli_runner) + if OS.is_stdout_verbose(): + prints("Finallize ..") + prints("-Orphan nodes report-----------------------") + Window.print_orphan_nodes() + prints("Finallize .. done") diff --git a/addons/gdUnit4/bin/GdUnitCmdTool.gd.uid b/addons/gdUnit4/bin/GdUnitCmdTool.gd.uid new file mode 100644 index 0000000..b83c97f --- /dev/null +++ b/addons/gdUnit4/bin/GdUnitCmdTool.gd.uid @@ -0,0 +1 @@ +uid://chdvqgrairx2r diff --git a/addons/gdUnit4/bin/GdUnitCopyLog.gd b/addons/gdUnit4/bin/GdUnitCopyLog.gd new file mode 100644 index 0000000..8b22805 --- /dev/null +++ b/addons/gdUnit4/bin/GdUnitCopyLog.gd @@ -0,0 +1,167 @@ +#!/usr/bin/env -S godot -s +extends MainLoop + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") + +# gdlint: disable=max-line-length +const LOG_FRAME_TEMPLATE = """ + + + + + + Godot Logging + + + + +
+${content} +
+ + +""" + +const NO_LOG_MESSAGE = """ +

No logging available!

+
+

In order for logging to take place, you must activate the Activate file logging option in the project settings.

+

You can enable the logging under: +Project Settings > Debug > File Logging > Enable File Logging in the project settings.

+""" + +#warning-ignore-all:return_value_discarded +var _cmd_options := CmdOptions.new([ + CmdOption.new( + "-rd, --report-directory", + "-rd ", + "Specifies the output directory in which the reports are to be written. The default is res://reports/.", + TYPE_STRING, + true + ) + ]) + + +var _report_root_path: String +var _current_report_path: String +var _debug_cmd_args := PackedStringArray() + + +func _init() -> void: + set_report_directory(GdUnitFileAccess.current_dir() + "reports") + set_current_report_path() + + +func _process(_delta: float) -> bool: + # check if reports exists + if not reports_available(): + prints("no reports found") + return true + + # only process if godot logging is enabled + if not GdUnitSettings.is_log_enabled(): + write_report(NO_LOG_MESSAGE, "") + return true + + # parse possible custom report path, + var cmd_parser := CmdArgumentParser.new(_cmd_options, "GdUnitCmdTool.gd") + # ignore erros and exit quitly + if cmd_parser.parse(get_cmdline_args(), true).is_error(): + return true + CmdCommandHandler.new(_cmd_options).register_cb("-rd", set_report_directory) + + var godot_log_file := scan_latest_godot_log() + var result := read_log_file_content(godot_log_file) + if result.is_error(): + write_report(result.error_message(), godot_log_file) + return true + write_report(result.value_as_string(), godot_log_file) + return true + + +func set_current_report_path() -> void: + # scan for latest report directory + var iteration := GdUnitFileAccess.find_last_path_index( + _report_root_path, GdUnitConstants.REPORT_DIR_PREFIX + ) + _current_report_path = "%s/%s%d" % [_report_root_path, GdUnitConstants.REPORT_DIR_PREFIX, iteration] + + +func set_report_directory(path: String) -> void: + _report_root_path = path + + +func get_log_report_html() -> String: + return _current_report_path + "/godot_report_log.html" + + +func reports_available() -> bool: + return DirAccess.dir_exists_absolute(_report_root_path) + + +func scan_latest_godot_log() -> String: + var path := GdUnitSettings.get_log_path().get_base_dir() + var files_sorted := Array() + for file in GdUnitFileAccess.scan_dir(path): + var file_name := "%s/%s" % [path, file] + files_sorted.append(file_name) + # sort by name, the name contains the timestamp so we sort at the end by timestamp + files_sorted.sort() + return files_sorted.back() + + +func read_log_file_content(log_file: String) -> GdUnitResult: + var file := FileAccess.open(log_file, FileAccess.READ) + if file == null: + return GdUnitResult.error( + "Can't find log file '%s'. Error: %s" + % [log_file, error_string(FileAccess.get_open_error())] + ) + var content := "
" + file.get_as_text()
+	# patch out console format codes
+	for color_index in range(0, 256):
+		var to_replace := "[38;5;%dm" % color_index
+		content = content.replace(to_replace, "")
+	content += "
" + content = content\ + .replace("", "")\ + .replace(GdUnitCSIMessageWriter.CSI_BOLD, "")\ + .replace(GdUnitCSIMessageWriter.CSI_ITALIC, "")\ + .replace(GdUnitCSIMessageWriter.CSI_UNDERLINE, "") + return GdUnitResult.success(content) + + +func write_report(content: String, godot_log_file: String) -> GdUnitResult: + var file := FileAccess.open(get_log_report_html(), FileAccess.WRITE) + if file == null: + return GdUnitResult.error( + "Can't open to write '%s'. Error: %s" + % [get_log_report_html(), error_string(FileAccess.get_open_error())] + ) + var report_html := LOG_FRAME_TEMPLATE.replace("${content}", content) + file.store_string(report_html) + _update_index_html(godot_log_file) + return GdUnitResult.success(file) + + +func _update_index_html(godot_log_file: String) -> void: + var index_path := "%s/index.html" % _current_report_path + var index_file := FileAccess.open(index_path, FileAccess.READ_WRITE) + if index_file == null: + push_error( + "Can't add log path '%s' to `%s`. Error: %s" + % [godot_log_file, index_path, error_string(FileAccess.get_open_error())] + ) + return + var content := index_file.get_as_text()\ + .replace("${log_report}", get_log_report_html())\ + .replace("${godot_log_file}", godot_log_file) + # overide it + index_file.seek(0) + index_file.store_string(content) + + +func get_cmdline_args() -> PackedStringArray: + if _debug_cmd_args.is_empty(): + return OS.get_cmdline_args() + return _debug_cmd_args diff --git a/addons/gdUnit4/bin/GdUnitCopyLog.gd.uid b/addons/gdUnit4/bin/GdUnitCopyLog.gd.uid new file mode 100644 index 0000000..c08b3dd --- /dev/null +++ b/addons/gdUnit4/bin/GdUnitCopyLog.gd.uid @@ -0,0 +1 @@ +uid://cca26e4thsgr2 diff --git a/addons/gdUnit4/plugin.cfg b/addons/gdUnit4/plugin.cfg new file mode 100644 index 0000000..6f73418 --- /dev/null +++ b/addons/gdUnit4/plugin.cfg @@ -0,0 +1,7 @@ +[plugin] + +name="gdUnit4" +description="Unit Testing Framework for Godot Scripts" +author="Mike Schulze" +version="6.0.0" +script="plugin.gd" diff --git a/addons/gdUnit4/plugin.gd b/addons/gdUnit4/plugin.gd new file mode 100644 index 0000000..822c4d5 --- /dev/null +++ b/addons/gdUnit4/plugin.gd @@ -0,0 +1,110 @@ +@tool +extends EditorPlugin + +# We need to define manually the slot id's, to be downwards compatible +const CONTEXT_SLOT_FILESYSTEM: int = 1 # EditorContextMenuPlugin.CONTEXT_SLOT_FILESYSTEM +const CONTEXT_SLOT_SCRIPT_EDITOR: int = 2 # EditorContextMenuPlugin.CONTEXT_SLOT_SCRIPT_EDITOR + +var _gd_inspector: Control +var _gd_console: Control +var _gd_filesystem_context_menu: Variant +var _gd_scripteditor_context_menu: Variant + + +func _enter_tree() -> void: + + var inferred_declaration: int = ProjectSettings.get_setting("debug/gdscript/warnings/inferred_declaration") + var exclude_addons: bool = ProjectSettings.get_setting("debug/gdscript/warnings/exclude_addons") + if !exclude_addons and inferred_declaration != 0: + printerr("GdUnit4: 'inferred_declaration' is set to Warning/Error!") + printerr("GdUnit4 is not 'inferred_declaration' save, you have to excluded addons (debug/gdscript/warnings/exclude_addons)") + printerr("Loading GdUnit4 Plugin failed.") + return + + if check_running_in_test_env(): + @warning_ignore("return_value_discarded") + GdUnitCSIMessageWriter.new().prints_warning("It was recognized that GdUnit4 is running in a test environment, therefore the GdUnit4 plugin will not be executed!") + return + + if Engine.get_version_info().hex < 0x40500: + prints("This GdUnit4 plugin version '%s' requires Godot version '4.5' or higher to run." % GdUnit4Version.current()) + return + GdUnitSettings.setup() + # Install the GdUnit Inspector + _gd_inspector = (load("res://addons/gdUnit4/src/ui/GdUnitInspector.tscn") as PackedScene).instantiate() + _add_context_menus() + add_control_to_dock(EditorPlugin.DOCK_SLOT_LEFT_UR, _gd_inspector) + # Install the GdUnit Console + _gd_console = (load("res://addons/gdUnit4/src/ui/GdUnitConsole.tscn") as PackedScene).instantiate() + var control: Control = add_control_to_bottom_panel(_gd_console, "gdUnitConsole") + @warning_ignore("unsafe_method_access") + await _gd_console.setup_update_notification(control) + if GdUnit4CSharpApiLoader.is_api_loaded(): + prints("GdUnit4Net version '%s' loaded." % GdUnit4CSharpApiLoader.version()) + else: + prints("No GdUnit4Net found.") + # Connect to be notified for script changes to be able to discover new tests + GdUnitTestDiscoverGuard.instance() + @warning_ignore("return_value_discarded") + resource_saved.connect(_on_resource_saved) + prints("Loading GdUnit4 Plugin success") + + +func _exit_tree() -> void: + if check_running_in_test_env(): + return + if is_instance_valid(_gd_inspector): + remove_control_from_docks(_gd_inspector) + _gd_inspector.free() + _remove_context_menus() + if is_instance_valid(_gd_console): + remove_control_from_bottom_panel(_gd_console) + _gd_console.free() + var gdUnitTools: GDScript = load("res://addons/gdUnit4/src/core/GdUnitTools.gd") + @warning_ignore("unsafe_method_access") + gdUnitTools.dispose_all(true) + prints("Unload GdUnit4 Plugin success") + + +func check_running_in_test_env() -> bool: + var args: PackedStringArray = OS.get_cmdline_args() + args.append_array(OS.get_cmdline_user_args()) + return DisplayServer.get_name() == "headless" or args.has("--selftest") or args.has("--add") or args.has("-a") or args.has("--quit-after") or args.has("--import") + + +func _add_context_menus() -> void: + if Engine.get_version_info().hex >= 0x40400: + # With Godot 4.4 we have to use the 'add_context_menu_plugin' to register editor context menus + _gd_filesystem_context_menu = _preload_gdx_script("res://addons/gdUnit4/src/ui/menu/EditorFileSystemContextMenuHandlerV44.gdx") + call_deferred("add_context_menu_plugin", CONTEXT_SLOT_FILESYSTEM, _gd_filesystem_context_menu) + # the CONTEXT_SLOT_SCRIPT_EDITOR is adding to the script panel instead of script editor see https://github.com/godotengine/godot/pull/100556 + #_gd_scripteditor_context_menu = _preload("res://addons/gdUnit4/src/ui/menu/ScriptEditorContextMenuHandlerV44.gdx") + #call_deferred("add_context_menu_plugin", CONTEXT_SLOT_SCRIPT_EDITOR, _gd_scripteditor_context_menu) + # so we use the old hacky way to add the context menu + _gd_inspector.add_child(preload("res://addons/gdUnit4/src/ui/menu/ScriptEditorContextMenuHandler.gd").new()) + else: + # TODO Delete it if the minimum requirement for the plugin is set to Godot 4.4. + _gd_inspector.add_child(preload("res://addons/gdUnit4/src/ui/menu/EditorFileSystemContextMenuHandler.gd").new()) + _gd_inspector.add_child(preload("res://addons/gdUnit4/src/ui/menu/ScriptEditorContextMenuHandler.gd").new()) + + +func _remove_context_menus() -> void: + if is_instance_valid(_gd_filesystem_context_menu): + call_deferred("remove_context_menu_plugin", _gd_filesystem_context_menu) + if is_instance_valid(_gd_scripteditor_context_menu): + call_deferred("remove_context_menu_plugin", _gd_scripteditor_context_menu) + + +func _preload_gdx_script(script_path: String) -> Variant: + var script: GDScript = GDScript.new() + script.source_code = GdUnitFileAccess.resource_as_string(script_path) + script.take_over_path(script_path) + var err :Error = script.reload() + if err != OK: + push_error("Can't create context menu %s, error: %s" % [script_path, error_string(err)]) + return script.new() + + +func _on_resource_saved(resource: Resource) -> void: + if resource is Script: + await GdUnitTestDiscoverGuard.instance().discover(resource as Script) diff --git a/addons/gdUnit4/plugin.gd.uid b/addons/gdUnit4/plugin.gd.uid new file mode 100644 index 0000000..1d7d106 --- /dev/null +++ b/addons/gdUnit4/plugin.gd.uid @@ -0,0 +1 @@ +uid://ddael08u8cd37 diff --git a/addons/gdUnit4/runtest.cmd b/addons/gdUnit4/runtest.cmd new file mode 100644 index 0000000..ad5da4d --- /dev/null +++ b/addons/gdUnit4/runtest.cmd @@ -0,0 +1,62 @@ +@echo off +setlocal enabledelayedexpansion + +:: Initialize variables +set "godot_binary=" +set "filtered_args=" + +:: Process all arguments +set "i=0" +:parse_args +if "%~1"=="" goto end_parse_args + +if "%~1"=="--godot_binary" ( + set "godot_binary=%~2" + shift + shift +) else ( + set "filtered_args=!filtered_args! %~1" + shift +) +goto parse_args +:end_parse_args + +:: If --godot_binary wasn't provided, fallback to environment variable +if "!godot_binary!"=="" ( + set "godot_binary=%GODOT_BIN%" +) + +:: Check if we have a godot_binary value from any source +if "!godot_binary!"=="" ( + echo Godot binary path is not specified. + echo Please either: + echo - Set the environment variable: set GODOT_BIN=C:\path\to\godot.exe + echo - Or use the --godot_binary argument: --godot_binary C:\path\to\godot.exe + exit /b 1 +) + +:: Check if the Godot binary exists +if not exist "!godot_binary!" ( + echo Error: The specified Godot binary '!godot_binary!' does not exist. + exit /b 1 +) + +:: Get Godot version and check if it's a mono build +for /f "tokens=*" %%i in ('"!godot_binary!" --version') do set GODOT_VERSION=%%i +echo !GODOT_VERSION! | findstr /I "mono" >nul +if !errorlevel! equ 0 ( + echo Godot .NET detected + echo Compiling c# classes ... Please Wait + dotnet build --debug + echo done !errorlevel! +) + +:: Run the tests with the filtered arguments +"!godot_binary!" --path . -s -d res://addons/gdUnit4/bin/GdUnitCmdTool.gd !filtered_args! +set exit_code=%ERRORLEVEL% +echo Run tests ends with %exit_code% + +:: Run the copy log command +"!godot_binary!" --headless --path . --quiet -s res://addons/gdUnit4/bin/GdUnitCopyLog.gd !filtered_args! > nul +set exit_code2=%ERRORLEVEL% +exit /b %exit_code% diff --git a/addons/gdUnit4/runtest.sh b/addons/gdUnit4/runtest.sh new file mode 100644 index 0000000..f0269ef --- /dev/null +++ b/addons/gdUnit4/runtest.sh @@ -0,0 +1,62 @@ +#!/bin/bash + +# Check for command-line argument +godot_binary="" +filtered_args="" + +# Process all arguments with a more compatible approach +while [ $# -gt 0 ]; do + if [ "$1" = "--godot_binary" ] && [ $# -gt 1 ]; then + # Get the next argument as the value + godot_binary="$2" + shift 2 + else + # Keep non-godot_binary arguments for passing to Godot + filtered_args="$filtered_args $1" + shift + fi +done + +# If --godot_binary wasn't provided, fallback to environment variable +if [ -z "$godot_binary" ]; then + godot_binary="$GODOT_BIN" +fi + +# Check if we have a godot_binary value from any source +if [ -z "$godot_binary" ]; then + echo "Godot binary path is not specified." + echo "Please either:" + echo " - Set the environment variable: export GODOT_BIN=/path/to/godot" + echo " - Or use the --godot_binary argument: --godot_binary /path/to/godot" + exit 1 +fi + +# Check if the Godot binary exists and is executable +if [ ! -f "$godot_binary" ]; then + echo "Error: The specified Godot binary '$godot_binary' does not exist." + exit 1 +fi + +if [ ! -x "$godot_binary" ]; then + echo "Error: The specified Godot binary '$godot_binary' is not executable." + exit 1 +fi + +# Get Godot version and check if it's a .NET build +GODOT_VERSION=$("$godot_binary" --version) +if echo "$GODOT_VERSION" | grep -i "mono" > /dev/null; then + echo "Godot .NET detected" + echo "Compiling c# classes ... Please Wait" + dotnet build --debug + echo "done $?" +fi + +# Run the tests with the filtered arguments +"$godot_binary" --path . -s -d res://addons/gdUnit4/bin/GdUnitCmdTool.gd $filtered_args +exit_code=$? +echo "Run tests ends with $exit_code" + +# Run the copy log command +"$godot_binary" --headless --path . --quiet -s res://addons/gdUnit4/bin/GdUnitCopyLog.gd $filtered_args > /dev/null +exit_code2=$? +exit $exit_code diff --git a/addons/gdUnit4/src/Comparator.gd b/addons/gdUnit4/src/Comparator.gd new file mode 100644 index 0000000..096088a --- /dev/null +++ b/addons/gdUnit4/src/Comparator.gd @@ -0,0 +1,12 @@ +class_name Comparator +extends Resource + +enum { + EQUAL, + LESS_THAN, + LESS_EQUAL, + GREATER_THAN, + GREATER_EQUAL, + BETWEEN_EQUAL, + NOT_BETWEEN_EQUAL, +} diff --git a/addons/gdUnit4/src/Comparator.gd.uid b/addons/gdUnit4/src/Comparator.gd.uid new file mode 100644 index 0000000..de2e00c --- /dev/null +++ b/addons/gdUnit4/src/Comparator.gd.uid @@ -0,0 +1 @@ +uid://diowb66hireor diff --git a/addons/gdUnit4/src/Fuzzers.gd b/addons/gdUnit4/src/Fuzzers.gd new file mode 100644 index 0000000..f61ba6e --- /dev/null +++ b/addons/gdUnit4/src/Fuzzers.gd @@ -0,0 +1,34 @@ +## A fuzzer implementation to provide default implementation +class_name Fuzzers +extends Resource + + +## Generates an random string with min/max length and given charset +static func rand_str(min_length: int, max_length :int, charset := StringFuzzer.DEFAULT_CHARSET) -> Fuzzer: + return StringFuzzer.new(min_length, max_length, charset) + + +## Generates an random integer in a range form to +static func rangei(from: int, to: int) -> Fuzzer: + return IntFuzzer.new(from, to) + +## Generates a randon float within in a given range +static func rangef(from: float, to: float) -> Fuzzer: + return FloatFuzzer.new(from, to) + +## Generates an random Vector2 in a range form to +static func rangev2(from: Vector2, to: Vector2) -> Fuzzer: + return Vector2Fuzzer.new(from, to) + + +## Generates an random Vector3 in a range form to +static func rangev3(from: Vector3, to: Vector3) -> Fuzzer: + return Vector3Fuzzer.new(from, to) + +## Generates an integer in a range form to that can be divided exactly by 2 +static func eveni(from: int, to: int) -> Fuzzer: + return IntFuzzer.new(from, to, IntFuzzer.EVEN) + +## Generates an integer in a range form to that cannot be divided exactly by 2 +static func oddi(from: int, to: int) -> Fuzzer: + return IntFuzzer.new(from, to, IntFuzzer.ODD) diff --git a/addons/gdUnit4/src/Fuzzers.gd.uid b/addons/gdUnit4/src/Fuzzers.gd.uid new file mode 100644 index 0000000..b11ddee --- /dev/null +++ b/addons/gdUnit4/src/Fuzzers.gd.uid @@ -0,0 +1 @@ +uid://b5k74b3q0djbr diff --git a/addons/gdUnit4/src/GdUnitArrayAssert.gd b/addons/gdUnit4/src/GdUnitArrayAssert.gd new file mode 100644 index 0000000..eeb7ca6 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitArrayAssert.gd @@ -0,0 +1,122 @@ +## An Assertion Tool to verify array values +@abstract class_name GdUnitArrayAssert +extends GdUnitAssert + + +## Verifies that the current value is null. +@abstract func is_null() -> GdUnitArrayAssert + + +## Verifies that the current value is not null. +@abstract func is_not_null() -> GdUnitArrayAssert + + +## Verifies that the current Array is equal to the given one. +@abstract func is_equal(...expected: Array) -> GdUnitArrayAssert + + +## Verifies that the current Array is equal to the given one, ignoring case considerations. +@abstract func is_equal_ignoring_case(...expected: Array) -> GdUnitArrayAssert + + +## Verifies that the current Array is not equal to the given one. +@abstract func is_not_equal(...expected: Array) -> GdUnitArrayAssert + + +## Verifies that the current Array is not equal to the given one, ignoring case considerations. +@abstract func is_not_equal_ignoring_case(...expected: Array) -> GdUnitArrayAssert + + +## Overrides the default failure message by given custom message. +@abstract func override_failure_message(message: String) -> GdUnitArrayAssert + + +## Appends a custom message to the failure message. +@abstract func append_failure_message(message: String) -> GdUnitArrayAssert + + +## Verifies that the current Array is empty, it has a size of 0. +@abstract func is_empty() -> GdUnitArrayAssert + + +## Verifies that the current Array is not empty, it has a size of minimum 1. +@abstract func is_not_empty() -> GdUnitArrayAssert + + +## Verifies that the current Array is the same. [br] +## Compares the current by object reference equals +@abstract func is_same(expected: Variant) -> GdUnitArrayAssert + + +## Verifies that the current Array is NOT the same. [br] +## Compares the current by object reference equals +@abstract func is_not_same(expected: Variant) -> GdUnitArrayAssert + + +## Verifies that the current Array has a size of given value. +@abstract func has_size(expectd: int) -> GdUnitArrayAssert + + +## Verifies that the current Array contains the given values, in any order.[br] +## The values are compared by deep parameter comparision, for object reference compare you have to use [method contains_same] +@abstract func contains(...expected: Array) -> GdUnitArrayAssert + + +## Verifies that the current Array contains exactly only the given values and nothing else, in same order.[br] +## The values are compared by deep parameter comparision, for object reference compare you have to use [method contains_same_exactly] +@abstract func contains_exactly(...expected: Array) -> GdUnitArrayAssert + + +## Verifies that the current Array contains exactly only the given values and nothing else, in any order.[br] +## The values are compared by deep parameter comparision, for object reference compare you have to use [method contains_same_exactly_in_any_order] +@abstract func contains_exactly_in_any_order(...expected: Array) -> GdUnitArrayAssert + + +## Verifies that the current Array contains the given values, in any order.[br] +## The values are compared by object reference, for deep parameter comparision use [method contains] +@abstract func contains_same(...expected: Array) -> GdUnitArrayAssert + + +## Verifies that the current Array contains exactly only the given values and nothing else, in same order.[br] +## The values are compared by object reference, for deep parameter comparision use [method contains_exactly] +@abstract func contains_same_exactly(...expected: Array) -> GdUnitArrayAssert + + +## Verifies that the current Array contains exactly only the given values and nothing else, in any order.[br] +## The values are compared by object reference, for deep parameter comparision use [method contains_exactly_in_any_order] +@abstract func contains_same_exactly_in_any_order(...expected: Array) -> GdUnitArrayAssert + + +## Verifies that the current Array do NOT contains the given values, in any order.[br] +## The values are compared by deep parameter comparision, for object reference compare you have to use [method not_contains_same] +## [b]Example:[/b] +## [codeblock] +## # will succeed +## assert_array([1, 2, 3, 4, 5]).not_contains(6) +## # will fail +## assert_array([1, 2, 3, 4, 5]).not_contains(2, 6) +## [/codeblock] +@abstract func not_contains(...expected: Array) -> GdUnitArrayAssert + + +## Verifies that the current Array do NOT contains the given values, in any order.[br] +## The values are compared by object reference, for deep parameter comparision use [method not_contains] +## [b]Example:[/b] +## [codeblock] +## # will succeed +## assert_array([1, 2, 3, 4, 5]).not_contains(6) +## # will fail +## assert_array([1, 2, 3, 4, 5]).not_contains(2, 6) +## [/codeblock] +@abstract func not_contains_same(...expected: Array) -> GdUnitArrayAssert + + +## Extracts all values by given function name and optional arguments into a new ArrayAssert. +## If the elements not accessible by `func_name` the value is converted to `"n.a"`, expecting null values +@abstract func extract(func_name: String, ...func_args: Array) -> GdUnitArrayAssert + + +## Extracts all values by given extractor's into a new ArrayAssert. +## If the elements not extractable than the value is converted to `"n.a"`, expecting null values +## -- The argument type is Array[GdUnitValueExtractor] +@abstract func extractv(...extractors: Array) -> GdUnitArrayAssert diff --git a/addons/gdUnit4/src/GdUnitArrayAssert.gd.uid b/addons/gdUnit4/src/GdUnitArrayAssert.gd.uid new file mode 100644 index 0000000..c523c27 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitArrayAssert.gd.uid @@ -0,0 +1 @@ +uid://b7jtmrldpoyys diff --git a/addons/gdUnit4/src/GdUnitAssert.gd b/addons/gdUnit4/src/GdUnitAssert.gd new file mode 100644 index 0000000..41382d9 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitAssert.gd @@ -0,0 +1,47 @@ +## Base interface of all GdUnit asserts +@abstract class_name GdUnitAssert +extends RefCounted + + +## Verifies that the current value is null. +@abstract func is_null() -> GdUnitAssert + + +## Verifies that the current value is not null. +@abstract func is_not_null() -> GdUnitAssert + + +## Verifies that the current value is equal to expected one. +@abstract func is_equal(expected: Variant) -> GdUnitAssert + + +## Verifies that the current value is not equal to expected one. +@abstract func is_not_equal(expected: Variant) -> GdUnitAssert + + +## Overrides the default failure message by given custom message.[br] +## This function allows you to replace the automatically generated failure message with a more specific +## or user-friendly message that better describes the test failure context.[br] +## Usage: +## [codeblock] +## # Override with custom context-specific message +## func test_player_inventory(): +## assert_that(player.get_item_count("sword"))\ +## .override_failure_message("Player should have exactly one sword")\ +## .is_equal(1) +## [/codeblock] +@abstract func override_failure_message(message: String) -> GdUnitAssert + + +## Appends a custom message to the failure message.[br] +## This can be used to add additional information to the generated failure message +## while keeping the original assertion details for better debugging context.[br] +## Usage: +## [codeblock] +## # Add context to existing failure message +## func test_player_health(): +## assert_that(player.health)\ +## .append_failure_message("Player was damaged by: %s" % last_damage_source)\ +## .is_greater(0) +## [/codeblock] +@abstract func append_failure_message(message: String) -> GdUnitAssert diff --git a/addons/gdUnit4/src/GdUnitAssert.gd.uid b/addons/gdUnit4/src/GdUnitAssert.gd.uid new file mode 100644 index 0000000..705ed5f --- /dev/null +++ b/addons/gdUnit4/src/GdUnitAssert.gd.uid @@ -0,0 +1 @@ +uid://b8ypyyuevakpd diff --git a/addons/gdUnit4/src/GdUnitAwaiter.gd b/addons/gdUnit4/src/GdUnitAwaiter.gd new file mode 100644 index 0000000..51385e8 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitAwaiter.gd @@ -0,0 +1,72 @@ +class_name GdUnitAwaiter +extends RefCounted + + +# Waits for a specified signal in an interval of 50ms sent from the , and terminates with an error after the specified timeout has elapsed. +# source: the object from which the signal is emitted +# signal_name: signal name +# args: the expected signal arguments as an array +# timeout: the timeout in ms, default is set to 2000ms +func await_signal_on(source :Object, signal_name :String, args :Array = [], timeout_millis :int = 2000) -> Variant: + # fail fast if the given source instance invalid + var assert_that := GdUnitAssertImpl.new(signal_name) + var line_number := GdUnitAssertions.get_line_number() + if not is_instance_valid(source): + @warning_ignore("return_value_discarded") + assert_that.report_error(GdAssertMessages.error_await_signal_on_invalid_instance(source, signal_name, args), line_number) + return await (Engine.get_main_loop() as SceneTree).process_frame + # fail fast if the given source instance invalid + if not is_instance_valid(source): + @warning_ignore("return_value_discarded") + assert_that.report_error(GdAssertMessages.error_await_signal_on_invalid_instance(source, signal_name, args), line_number) + return await await_idle_frame() + var awaiter := GdUnitSignalAwaiter.new(timeout_millis) + var value :Variant = await awaiter.on_signal(source, signal_name, args) + if awaiter.is_interrupted(): + var failure := "await_signal_on(%s, %s) timed out after %sms" % [signal_name, args, timeout_millis] + @warning_ignore("return_value_discarded") + assert_that.report_error(failure, line_number) + return value + + +# Waits for a specified signal sent from the between idle frames and aborts with an error after the specified timeout has elapsed +# source: the object from which the signal is emitted +# signal_name: signal name +# args: the expected signal arguments as an array +# timeout: the timeout in ms, default is set to 2000ms +func await_signal_idle_frames(source :Object, signal_name :String, args :Array = [], timeout_millis :int = 2000) -> Variant: + var line_number := GdUnitAssertions.get_line_number() + # fail fast if the given source instance invalid + if not is_instance_valid(source): + @warning_ignore("return_value_discarded") + GdUnitAssertImpl.new(signal_name)\ + .report_error(GdAssertMessages.error_await_signal_on_invalid_instance(source, signal_name, args), line_number) + return await await_idle_frame() + var awaiter := GdUnitSignalAwaiter.new(timeout_millis, true) + var value :Variant = await awaiter.on_signal(source, signal_name, args) + if awaiter.is_interrupted(): + var failure := "await_signal_idle_frames(%s, %s) timed out after %sms" % [signal_name, args, timeout_millis] + @warning_ignore("return_value_discarded") + GdUnitAssertImpl.new(signal_name).report_error(failure, line_number) + return value + + +# Waits for for a given amount of milliseconds +# example: +# # waits for 100ms +# await GdUnitAwaiter.await_millis(myNode, 100).completed +# use this waiter and not `await get_tree().create_timer().timeout to prevent errors when a test case is timed out +func await_millis(milliSec :int) -> void: + var timer :Timer = Timer.new() + timer.set_name("gdunit_await_millis_timer_%d" % timer.get_instance_id()) + (Engine.get_main_loop() as SceneTree).root.add_child(timer) + timer.add_to_group("GdUnitTimers") + timer.set_one_shot(true) + timer.start(milliSec / 1000.0) + await timer.timeout + timer.queue_free() + + +# Waits until the next idle frame +func await_idle_frame() -> void: + await (Engine.get_main_loop() as SceneTree).process_frame diff --git a/addons/gdUnit4/src/GdUnitAwaiter.gd.uid b/addons/gdUnit4/src/GdUnitAwaiter.gd.uid new file mode 100644 index 0000000..15a199d --- /dev/null +++ b/addons/gdUnit4/src/GdUnitAwaiter.gd.uid @@ -0,0 +1 @@ +uid://cmpgcgbf1v3he diff --git a/addons/gdUnit4/src/GdUnitBoolAssert.gd b/addons/gdUnit4/src/GdUnitBoolAssert.gd new file mode 100644 index 0000000..714f8fc --- /dev/null +++ b/addons/gdUnit4/src/GdUnitBoolAssert.gd @@ -0,0 +1,35 @@ +## An Assertion Tool to verify boolean values +@abstract class_name GdUnitBoolAssert +extends GdUnitAssert + + +## Verifies that the current value is null. +@abstract func is_null() -> GdUnitBoolAssert + + +## Verifies that the current value is not null. +@abstract func is_not_null() -> GdUnitBoolAssert + + +## Verifies that the current value is equal to the given one. +@abstract func is_equal(expected: Variant) -> GdUnitBoolAssert + + +## Verifies that the current value is not equal to the given one. +@abstract func is_not_equal(expected: Variant) -> GdUnitBoolAssert + + +## Overrides the default failure message by given custom message. +@abstract func override_failure_message(message: String) -> GdUnitBoolAssert + + +## Appends a custom message to the failure message. +@abstract func append_failure_message(message: String) -> GdUnitBoolAssert + + +## Verifies that the current value is true. +@abstract func is_true() -> GdUnitBoolAssert + + +## Verifies that the current value is false. +@abstract func is_false() -> GdUnitBoolAssert diff --git a/addons/gdUnit4/src/GdUnitBoolAssert.gd.uid b/addons/gdUnit4/src/GdUnitBoolAssert.gd.uid new file mode 100644 index 0000000..717b097 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitBoolAssert.gd.uid @@ -0,0 +1 @@ +uid://caidddxgb3yj diff --git a/addons/gdUnit4/src/GdUnitConstants.gd b/addons/gdUnit4/src/GdUnitConstants.gd new file mode 100644 index 0000000..e43c75a --- /dev/null +++ b/addons/gdUnit4/src/GdUnitConstants.gd @@ -0,0 +1,10 @@ +class_name GdUnitConstants +extends RefCounted + +const NO_ARG :Variant = "<--null-->" + +const EXPECT_ASSERT_REPORT_FAILURES := "expect_assert_report_failures" + +## The maximum number of report history files to store +const DEFAULT_REPORT_HISTORY_COUNT = 20 +const REPORT_DIR_PREFIX = "report_" diff --git a/addons/gdUnit4/src/GdUnitConstants.gd.uid b/addons/gdUnit4/src/GdUnitConstants.gd.uid new file mode 100644 index 0000000..d8c7d57 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitConstants.gd.uid @@ -0,0 +1 @@ +uid://dgclscvuh5v84 diff --git a/addons/gdUnit4/src/GdUnitDictionaryAssert.gd b/addons/gdUnit4/src/GdUnitDictionaryAssert.gd new file mode 100644 index 0000000..45cc62a --- /dev/null +++ b/addons/gdUnit4/src/GdUnitDictionaryAssert.gd @@ -0,0 +1,79 @@ +## An Assertion Tool to verify dictionary +@abstract class_name GdUnitDictionaryAssert +extends GdUnitAssert + + +## Verifies that the current value is null. +@abstract func is_null() -> GdUnitDictionaryAssert + + +## Verifies that the current value is not null. +@abstract func is_not_null() -> GdUnitDictionaryAssert + + +## Verifies that the current dictionary is equal to the given one, ignoring order. +@abstract func is_equal(expected: Variant) -> GdUnitDictionaryAssert + + +## Verifies that the current dictionary is not equal to the given one, ignoring order. +@abstract func is_not_equal(expected: Variant) -> GdUnitDictionaryAssert + + +## Overrides the default failure message by given custom message. +@abstract func override_failure_message(message: String) -> GdUnitDictionaryAssert + + +## Appends a custom message to the failure message. +@abstract func append_failure_message(message: String) -> GdUnitDictionaryAssert + + +## Verifies that the current dictionary is empty, it has a size of 0. +@abstract func is_empty() -> GdUnitDictionaryAssert + + +## Verifies that the current dictionary is not empty, it has a size of minimum 1. +@abstract func is_not_empty() -> GdUnitDictionaryAssert + + +## Verifies that the current dictionary is the same. [br] +## Compares the current by object reference equals +@abstract func is_same(expected: Variant) -> GdUnitDictionaryAssert + + +## Verifies that the current dictionary is NOT the same. [br] +## Compares the current by object reference equals +@abstract func is_not_same(expected: Variant) -> GdUnitDictionaryAssert + + +## Verifies that the current dictionary has a size of given value. +@abstract func has_size(expected: int) -> GdUnitDictionaryAssert + + +## Verifies that the current dictionary contains the given key(s).[br] +## The keys are compared by deep parameter comparision, for object reference compare you have to use [method contains_same_keys] +@abstract func contains_keys(...expected: Array) -> GdUnitDictionaryAssert + + +## Verifies that the current dictionary contains the given key and value.[br] +## The key and value are compared by deep parameter comparision, for object reference compare you have to use [method contains_same_key_value] +@abstract func contains_key_value(key: Variant, value: Variant) -> GdUnitDictionaryAssert + + +## Verifies that the current dictionary not contains the given key(s).[br] +## The keys are compared by deep parameter comparision, for object reference compare you have to use [method not_contains_same_keys] +@abstract func not_contains_keys(...expected: Array) -> GdUnitDictionaryAssert + + +## Verifies that the current dictionary contains the given key(s).[br] +## The keys are compared by object reference, for deep parameter comparision use [method contains_keys] +@abstract func contains_same_keys(expected: Array) -> GdUnitDictionaryAssert + + +## Verifies that the current dictionary contains the given key and value.[br] +## The key and value are compared by object reference, for deep parameter comparision use [method contains_key_value] +@abstract func contains_same_key_value(key: Variant, value: Variant) -> GdUnitDictionaryAssert + + +## Verifies that the current dictionary not contains the given key(s). +## The keys are compared by object reference, for deep parameter comparision use [method not_contains_keys] +@abstract func not_contains_same_keys(...expected: Array) -> GdUnitDictionaryAssert diff --git a/addons/gdUnit4/src/GdUnitDictionaryAssert.gd.uid b/addons/gdUnit4/src/GdUnitDictionaryAssert.gd.uid new file mode 100644 index 0000000..c6f6a8c --- /dev/null +++ b/addons/gdUnit4/src/GdUnitDictionaryAssert.gd.uid @@ -0,0 +1 @@ +uid://bu6473b8ymdyh diff --git a/addons/gdUnit4/src/GdUnitFailureAssert.gd b/addons/gdUnit4/src/GdUnitFailureAssert.gd new file mode 100644 index 0000000..6fec191 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitFailureAssert.gd @@ -0,0 +1,52 @@ +## An assertion tool to verify GDUnit asserts. +## This assert is for internal use only, to verify that failed asserts work as expected. +@abstract class_name GdUnitFailureAssert +extends GdUnitAssert + + +## Verifies that the current value is null. +@abstract func is_null() -> GdUnitFailureAssert + + +## Verifies that the current value is not null. +@abstract func is_not_null() -> GdUnitFailureAssert + + +## Verifies that the current value is equal to the given one. +@abstract func is_equal(expected: Variant) -> GdUnitFailureAssert + + +## Verifies that the current value is not equal to expected one. +@abstract func is_not_equal(expected: Variant) -> GdUnitFailureAssert + + +## Overrides the default failure message by given custom message. +@abstract func override_failure_message(message: String) -> GdUnitFailureAssert + + +## Appends a custom message to the failure message. +@abstract func append_failure_message(message: String) -> GdUnitFailureAssert + + +## Verifies if the executed assert was successful +@abstract func is_success() -> GdUnitFailureAssert + + +## Verifies if the executed assert has failed +@abstract func is_failed() -> GdUnitFailureAssert + + +## Verifies the failure line is equal to expected one. +@abstract func has_line(expected: int) -> GdUnitFailureAssert + + +## Verifies the failure message is equal to expected one. +@abstract func has_message(expected: String) -> GdUnitFailureAssert + + +## Verifies that the failure message starts with the expected message. +@abstract func starts_with_message(expected: String) -> GdUnitFailureAssert + + +## Verifies that the failure message contains the expected message. +@abstract func contains_message(expected: String) -> GdUnitFailureAssert diff --git a/addons/gdUnit4/src/GdUnitFailureAssert.gd.uid b/addons/gdUnit4/src/GdUnitFailureAssert.gd.uid new file mode 100644 index 0000000..7147890 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitFailureAssert.gd.uid @@ -0,0 +1 @@ +uid://c2itwjhst3f1j diff --git a/addons/gdUnit4/src/GdUnitFileAssert.gd b/addons/gdUnit4/src/GdUnitFileAssert.gd new file mode 100644 index 0000000..771da90 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitFileAssert.gd @@ -0,0 +1,38 @@ +@abstract class_name GdUnitFileAssert +extends GdUnitAssert + + +## Verifies that the current value is null. +@abstract func is_null() -> GdUnitFileAssert + + +## Verifies that the current value is not null. +@abstract func is_not_null() -> GdUnitFileAssert + + +## Verifies that the current value is equal to the given one. +@abstract func is_equal(expected: Variant) -> GdUnitFileAssert + + +## Verifies that the current value is not equal to expected one. +@abstract func is_not_equal(expected: Variant) -> GdUnitFileAssert + + +## Overrides the default failure message by given custom message. +@abstract func override_failure_message(message: String) -> GdUnitFileAssert + + +## Appends a custom message to the failure message. +@abstract func append_failure_message(message: String) -> GdUnitFileAssert + + +@abstract func is_file() -> GdUnitFileAssert + + +@abstract func exists() -> GdUnitFileAssert + + +@abstract func is_script() -> GdUnitFileAssert + + +@abstract func contains_exactly(expected_rows :Array) -> GdUnitFileAssert diff --git a/addons/gdUnit4/src/GdUnitFileAssert.gd.uid b/addons/gdUnit4/src/GdUnitFileAssert.gd.uid new file mode 100644 index 0000000..f0b5b93 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitFileAssert.gd.uid @@ -0,0 +1 @@ +uid://dw44nkyt05u6h diff --git a/addons/gdUnit4/src/GdUnitFloatAssert.gd b/addons/gdUnit4/src/GdUnitFloatAssert.gd new file mode 100644 index 0000000..2695ab0 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitFloatAssert.gd @@ -0,0 +1,75 @@ +## An Assertion Tool to verify float values +@abstract class_name GdUnitFloatAssert +extends GdUnitAssert + + +## Verifies that the current value is null. +@abstract func is_null() -> GdUnitFloatAssert + + +## Verifies that the current value is not null. +@abstract func is_not_null() -> GdUnitFloatAssert + + +## Verifies that the current value is equal to the given one. +@abstract func is_equal(expected: Variant) -> GdUnitFloatAssert + + +## Verifies that the current value is not equal to expected one. +@abstract func is_not_equal(expected: Variant) -> GdUnitFloatAssert + + +## Verifies that the current and expected value are approximately equal. +@abstract func is_equal_approx(expected: float, approx: float) -> GdUnitFloatAssert + + +## Overrides the default failure message by given custom message. +@abstract func override_failure_message(message: String) -> GdUnitFloatAssert + + +## Appends a custom message to the failure message. +@abstract func append_failure_message(message: String) -> GdUnitFloatAssert + + +## Verifies that the current value is less than the given one. +@abstract func is_less(expected: float) -> GdUnitFloatAssert + + +## Verifies that the current value is less than or equal the given one. +@abstract func is_less_equal(expected: float) -> GdUnitFloatAssert + + +## Verifies that the current value is greater than the given one. +@abstract func is_greater(expected: float) -> GdUnitFloatAssert + + +## Verifies that the current value is greater than or equal the given one. +@abstract func is_greater_equal(expected: float) -> GdUnitFloatAssert + + +## Verifies that the current value is negative. +@abstract func is_negative() -> GdUnitFloatAssert + + +## Verifies that the current value is not negative. +@abstract func is_not_negative() -> GdUnitFloatAssert + + +## Verifies that the current value is equal to zero. +@abstract func is_zero() -> GdUnitFloatAssert + + +## Verifies that the current value is not equal to zero. +@abstract func is_not_zero() -> GdUnitFloatAssert + + +## Verifies that the current value is in the given set of values. +@abstract func is_in(expected: Array) -> GdUnitFloatAssert + + +## Verifies that the current value is not in the given set of values. +@abstract func is_not_in(expected: Array) -> GdUnitFloatAssert + + +## Verifies that the current value is between the given boundaries (inclusive). +@abstract func is_between(from: float, to: float) -> GdUnitFloatAssert diff --git a/addons/gdUnit4/src/GdUnitFloatAssert.gd.uid b/addons/gdUnit4/src/GdUnitFloatAssert.gd.uid new file mode 100644 index 0000000..99fd8b2 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitFloatAssert.gd.uid @@ -0,0 +1 @@ +uid://x57gp00db8lb diff --git a/addons/gdUnit4/src/GdUnitFuncAssert.gd b/addons/gdUnit4/src/GdUnitFuncAssert.gd new file mode 100644 index 0000000..e8a49c5 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitFuncAssert.gd @@ -0,0 +1,42 @@ +## An Assertion Tool to verify function callback values +@abstract class_name GdUnitFuncAssert +extends GdUnitAssert + + +## Verifies that the current value is null. +@abstract func is_null() -> GdUnitFuncAssert + + +## Verifies that the current value is not null. +@abstract func is_not_null() -> GdUnitFuncAssert + + +## Verifies that the current value is equal to the given one. +@abstract func is_equal(expected: Variant) -> GdUnitFuncAssert + + +## Verifies that the current value is not equal to expected one. +@abstract func is_not_equal(expected: Variant) -> GdUnitFuncAssert + + +## Overrides the default failure message by given custom message. +@abstract func override_failure_message(message: String) -> GdUnitFuncAssert + + +## Appends a custom message to the failure message. +@abstract func append_failure_message(message: String) -> GdUnitFuncAssert + + +## Verifies that the current value is true. +@abstract func is_true() -> GdUnitFuncAssert + + +## Verifies that the current value is false. +@abstract func is_false() -> GdUnitFuncAssert + + +## Sets the timeout in ms to wait the function returnd the expected value, if the time over a failure is emitted.[br] +## e.g.[br] +## do wait until 5s the function `is_state` is returns 10 [br] +## [code]assert_func(instance, "is_state").wait_until(5000).is_equal(10)[/code] +@abstract func wait_until(timeout: int) -> GdUnitFuncAssert diff --git a/addons/gdUnit4/src/GdUnitFuncAssert.gd.uid b/addons/gdUnit4/src/GdUnitFuncAssert.gd.uid new file mode 100644 index 0000000..62bd282 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitFuncAssert.gd.uid @@ -0,0 +1 @@ +uid://dq7qrmge6m2ug diff --git a/addons/gdUnit4/src/GdUnitGodotErrorAssert.gd b/addons/gdUnit4/src/GdUnitGodotErrorAssert.gd new file mode 100644 index 0000000..01711f9 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitGodotErrorAssert.gd @@ -0,0 +1,59 @@ +## An assertion tool to verify for Godot runtime errors like assert() and push notifications like push_error(). +@abstract class_name GdUnitGodotErrorAssert +extends GdUnitAssert + + +## Verifies that the current value is null. +@abstract func is_null() -> GdUnitGodotErrorAssert + + +## Verifies that the current value is not null. +@abstract func is_not_null() -> GdUnitGodotErrorAssert + + +## Verifies that the current value is equal to the given one. +@abstract func is_equal(expected: Variant) -> GdUnitGodotErrorAssert + + +## Verifies that the current value is not equal to expected one. +@abstract func is_not_equal(expected: Variant) -> GdUnitGodotErrorAssert + + +## Overrides the default failure message by given custom message. +@abstract func override_failure_message(message: String) -> GdUnitGodotErrorAssert + + +## Appends a custom message to the failure message. +@abstract func append_failure_message(message: String) -> GdUnitGodotErrorAssert + + +## Verifies if the executed code runs without any runtime errors +## Usage: +## [codeblock] +## await assert_error().is_success() +## [/codeblock] +@abstract func is_success() -> GdUnitGodotErrorAssert + + +## Verifies if the executed code runs into a runtime error +## Usage: +## [codeblock] +## await assert_error().is_runtime_error() +## [/codeblock] +@abstract func is_runtime_error(expected_error: Variant) -> GdUnitGodotErrorAssert + + +## Verifies if the executed code has a push_warning() used +## Usage: +## [codeblock] +## await assert_error().is_push_warning() +## [/codeblock] +@abstract func is_push_warning(expected_warning: Variant) -> GdUnitGodotErrorAssert + + +## Verifies if the executed code has a push_error() used +## Usage: +## [codeblock] +## await assert_error().is_push_error() +## [/codeblock] +@abstract func is_push_error(expected_error: Variant) -> GdUnitGodotErrorAssert diff --git a/addons/gdUnit4/src/GdUnitGodotErrorAssert.gd.uid b/addons/gdUnit4/src/GdUnitGodotErrorAssert.gd.uid new file mode 100644 index 0000000..f1b4e44 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitGodotErrorAssert.gd.uid @@ -0,0 +1 @@ +uid://bv0opv8h54qk0 diff --git a/addons/gdUnit4/src/GdUnitIntAssert.gd b/addons/gdUnit4/src/GdUnitIntAssert.gd new file mode 100644 index 0000000..05eb922 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitIntAssert.gd @@ -0,0 +1,79 @@ +## An Assertion Tool to verify integer values +@abstract class_name GdUnitIntAssert +extends GdUnitAssert + + +## Verifies that the current value is null. +@abstract func is_null() -> GdUnitIntAssert + + +## Verifies that the current value is not null. +@abstract func is_not_null() -> GdUnitIntAssert + + +## Verifies that the current value is equal to the given one. +@abstract func is_equal(expected: Variant) -> GdUnitIntAssert + + +## Verifies that the current value is not equal to expected one. +@abstract func is_not_equal(expected: Variant) -> GdUnitIntAssert + + +## Overrides the default failure message by given custom message. +@abstract func override_failure_message(message: String) -> GdUnitIntAssert + + +## Appends a custom message to the failure message. +@abstract func append_failure_message(message: String) -> GdUnitIntAssert + + +## Verifies that the current value is less than the given one. +@abstract func is_less(expected: int) -> GdUnitIntAssert + + +## Verifies that the current value is less than or equal the given one. +@abstract func is_less_equal(expected: int) -> GdUnitIntAssert + + +## Verifies that the current value is greater than the given one. +@abstract func is_greater(expected: int) -> GdUnitIntAssert + + +## Verifies that the current value is greater than or equal the given one. +@abstract func is_greater_equal(expected: int) -> GdUnitIntAssert + + +## Verifies that the current value is even. +@abstract func is_even() -> GdUnitIntAssert + + +## Verifies that the current value is odd. +@abstract func is_odd() -> GdUnitIntAssert + + +## Verifies that the current value is negative. +@abstract func is_negative() -> GdUnitIntAssert + + +## Verifies that the current value is not negative. +@abstract func is_not_negative() -> GdUnitIntAssert + + +## Verifies that the current value is equal to zero. +@abstract func is_zero() -> GdUnitIntAssert + + +## Verifies that the current value is not equal to zero. +@abstract func is_not_zero() -> GdUnitIntAssert + + +## Verifies that the current value is in the given set of values. +@abstract func is_in(expected: Array) -> GdUnitIntAssert + + +## Verifies that the current value is not in the given set of values. +@abstract func is_not_in(expected: Array) -> GdUnitIntAssert + + +## Verifies that the current value is between the given boundaries (inclusive). +@abstract func is_between(from: int, to: int) -> GdUnitIntAssert diff --git a/addons/gdUnit4/src/GdUnitIntAssert.gd.uid b/addons/gdUnit4/src/GdUnitIntAssert.gd.uid new file mode 100644 index 0000000..9f8fa4f --- /dev/null +++ b/addons/gdUnit4/src/GdUnitIntAssert.gd.uid @@ -0,0 +1 @@ +uid://b56cu45wqwctd diff --git a/addons/gdUnit4/src/GdUnitObjectAssert.gd b/addons/gdUnit4/src/GdUnitObjectAssert.gd new file mode 100644 index 0000000..9d7e76e --- /dev/null +++ b/addons/gdUnit4/src/GdUnitObjectAssert.gd @@ -0,0 +1,51 @@ +## An Assertion Tool to verify Object values +@abstract class_name GdUnitObjectAssert +extends GdUnitAssert + + +## Verifies that the current value is null. +@abstract func is_null() -> GdUnitObjectAssert + + +## Verifies that the current value is not null. +@abstract func is_not_null() -> GdUnitObjectAssert + + +## Verifies that the current value is equal to the given one. +@abstract func is_equal(expected: Variant) -> GdUnitObjectAssert + + +## Verifies that the current value is not equal to expected one. +@abstract func is_not_equal(expected: Variant) -> GdUnitObjectAssert + + +## Overrides the default failure message by given custom message. +@abstract func override_failure_message(message: String) -> GdUnitObjectAssert + + +## Appends a custom message to the failure message. +@abstract func append_failure_message(message: String) -> GdUnitObjectAssert + + +## Verifies that the current object is the same as the given one. +@abstract func is_same(expected: Variant) -> GdUnitObjectAssert + + +## Verifies that the current object is not the same as the given one. +@abstract func is_not_same(expected: Variant) -> GdUnitObjectAssert + + +## Verifies that the current object is an instance of the given type. +@abstract func is_instanceof(type: Variant) -> GdUnitObjectAssert + + +## Verifies that the current object is not an instance of the given type. +@abstract func is_not_instanceof(type: Variant) -> GdUnitObjectAssert + + +## Checks whether the current object inherits from the specified type. +@abstract func is_inheriting(type: Variant) -> GdUnitObjectAssert + + +## Checks whether the current object does NOT inherit from the specified type. +@abstract func is_not_inheriting(type: Variant) -> GdUnitObjectAssert diff --git a/addons/gdUnit4/src/GdUnitObjectAssert.gd.uid b/addons/gdUnit4/src/GdUnitObjectAssert.gd.uid new file mode 100644 index 0000000..898c244 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitObjectAssert.gd.uid @@ -0,0 +1 @@ +uid://huu1od8c2rtu diff --git a/addons/gdUnit4/src/GdUnitResultAssert.gd b/addons/gdUnit4/src/GdUnitResultAssert.gd new file mode 100644 index 0000000..01eb880 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitResultAssert.gd @@ -0,0 +1,51 @@ +## An Assertion Tool to verify Results +@abstract class_name GdUnitResultAssert +extends GdUnitAssert + + +## Verifies that the current value is null. +@abstract func is_null() -> GdUnitResultAssert + + +## Verifies that the current value is not null. +@abstract func is_not_null() -> GdUnitResultAssert + + +## Verifies that the current value is equal to the given one. +@abstract func is_equal(expected: Variant) -> GdUnitResultAssert + + +## Verifies that the current value is not equal to expected one. +@abstract func is_not_equal(expected: Variant) -> GdUnitResultAssert + + +## Overrides the default failure message by given custom message. +@abstract func override_failure_message(message: String) -> GdUnitResultAssert + + +## Appends a custom message to the failure message. +@abstract func append_failure_message(message: String) -> GdUnitResultAssert + + +## Verifies that the result is ends up with empty +@abstract func is_empty() -> GdUnitResultAssert + + +## Verifies that the result is ends up with success +@abstract func is_success() -> GdUnitResultAssert + + +## Verifies that the result is ends up with warning +@abstract func is_warning() -> GdUnitResultAssert + + +## Verifies that the result is ends up with error +@abstract func is_error() -> GdUnitResultAssert + + +## Verifies that the result contains the given message +@abstract func contains_message(expected: String) -> GdUnitResultAssert + + +## Verifies that the result contains the given value +@abstract func is_value(expected: Variant) -> GdUnitResultAssert diff --git a/addons/gdUnit4/src/GdUnitResultAssert.gd.uid b/addons/gdUnit4/src/GdUnitResultAssert.gd.uid new file mode 100644 index 0000000..c6a4607 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitResultAssert.gd.uid @@ -0,0 +1 @@ +uid://b0xr5fcj2q42p diff --git a/addons/gdUnit4/src/GdUnitSceneRunner.gd b/addons/gdUnit4/src/GdUnitSceneRunner.gd new file mode 100644 index 0000000..6b11918 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitSceneRunner.gd @@ -0,0 +1,325 @@ +## The Scene Runner is a tool used for simulating interactions on a scene. +## With this tool, you can simulate input events such as keyboard or mouse input and/or simulate scene processing over a certain number of frames. +## This tool is typically used for integration testing a scene. +@abstract class_name GdUnitSceneRunner +extends RefCounted + + +## Simulates that an action has been pressed.[br] +## [member action] : the action e.g. [code]"ui_up"[/code][br] +## [member event_index] : [url=https://docs.godotengine.org/en/4.4/classes/class_inputeventaction.html#class-inputeventaction-property-event-index]default=-1[/url][br] +@abstract func simulate_action_pressed(action: String, event_index := -1) -> GdUnitSceneRunner + + +## Simulates that an action is pressed.[br] +## [member action] : the action e.g. [code]"ui_up"[/code][br] +## [member event_index] : [url=https://docs.godotengine.org/en/4.4/classes/class_inputeventaction.html#class-inputeventaction-property-event-index]default=-1[/url][br] +@abstract func simulate_action_press(action: String, event_index := -1) -> GdUnitSceneRunner + + +## Simulates that an action has been released.[br] +## [member action] : the action e.g. [code]"ui_up"[/code][br] +## [member event_index] : [url=https://docs.godotengine.org/en/4.4/classes/class_inputeventaction.html#class-inputeventaction-property-event-index]default=-1[/url][br] +@abstract func simulate_action_release(action: String, event_index := -1) -> GdUnitSceneRunner + + +## Simulates that a key has been pressed.[br] +## [member key_code] : the key code e.g. [constant KEY_ENTER][br] +## [member shift_pressed] : false by default set to true if simmulate shift is press[br] +## [member ctrl_pressed] : false by default set to true if simmulate control is press[br] +## [codeblock] +## func test_key_presssed(): +## var runner = scene_runner("res://scenes/simple_scene.tscn") +## await runner.simulate_key_pressed(KEY_SPACE) +## [/codeblock] +@abstract func simulate_key_pressed(key_code: int, shift_pressed := false, ctrl_pressed := false) -> GdUnitSceneRunner + + +## Simulates that a key is pressed.[br] +## [member key_code] : the key code e.g. [constant KEY_ENTER][br] +## [member shift_pressed] : false by default set to true if simmulate shift is press[br] +## [member ctrl_pressed] : false by default set to true if simmulate control is press[br] +@abstract func simulate_key_press(key_code: int, shift_pressed := false, ctrl_pressed := false) -> GdUnitSceneRunner + + +## Simulates that a key has been released.[br] +## [member key_code] : the key code e.g. [constant KEY_ENTER][br] +## [member shift_pressed] : false by default set to true if simmulate shift is press[br] +## [member ctrl_pressed] : false by default set to true if simmulate control is press[br] +@abstract func simulate_key_release(key_code: int, shift_pressed := false, ctrl_pressed := false) -> GdUnitSceneRunner + + +## Sets the mouse position to the specified vector, provided in pixels and relative to an origin at the upper left corner of the currently focused Window Manager game window.[br] +## [member position] : The absolute position in pixels as Vector2 +@abstract func set_mouse_position(position: Vector2) -> GdUnitSceneRunner + + +## Returns the mouse's position in this Viewport using the coordinate system of this Viewport. +@abstract func get_mouse_position() -> Vector2 + + +## Gets the current global mouse position of the current window +@abstract func get_global_mouse_position() -> Vector2 + + +## Simulates a mouse moved to final position.[br] +## [member position] : The final mouse position +@abstract func simulate_mouse_move(position: Vector2) -> GdUnitSceneRunner + + +## Simulates a mouse move to the relative coordinates (offset).[br] +## [color=yellow]You must use [b]await[/b] to wait until the simulated mouse movement is complete.[/color][br] +## [br] +## [member relative] : The relative position, indicating the mouse position offset.[br] +## [member time] : The time to move the mouse by the relative position in seconds (default is 1 second).[br] +## [member trans_type] : Sets the type of transition used (default is TRANS_LINEAR).[br] +## [codeblock] +## func test_move_mouse(): +## var runner = scene_runner("res://scenes/simple_scene.tscn") +## await runner.simulate_mouse_move_relative(Vector2(100,100)) +## [/codeblock] +@abstract func simulate_mouse_move_relative(relative: Vector2, time: float = 1.0, trans_type: Tween.TransitionType = Tween.TRANS_LINEAR) -> GdUnitSceneRunner + + +## Simulates a mouse move to the absolute coordinates.[br] +## [color=yellow]You must use [b]await[/b] to wait until the simulated mouse movement is complete.[/color][br] +## [br] +## [member position] : The final position of the mouse.[br] +## [member time] : The time to move the mouse to the final position in seconds (default is 1 second).[br] +## [member trans_type] : Sets the type of transition used (default is TRANS_LINEAR).[br] +## [codeblock] +## func test_move_mouse(): +## var runner = scene_runner("res://scenes/simple_scene.tscn") +## await runner.simulate_mouse_move_absolute(Vector2(100,100)) +## [/codeblock] +@abstract func simulate_mouse_move_absolute(position: Vector2, time: float = 1.0, trans_type: Tween.TransitionType = Tween.TRANS_LINEAR) -> GdUnitSceneRunner + + +## Simulates a mouse button pressed.[br] +## [member button_index] : The mouse button identifier, one of the [enum MouseButton] or button wheel constants. +## [member double_click] : Set to true to simulate a double-click +@abstract func simulate_mouse_button_pressed(button_index: MouseButton, double_click := false) -> GdUnitSceneRunner + + +## Simulates a mouse button press (holding)[br] +## [member button_index] : The mouse button identifier, one of the [enum MouseButton] or button wheel constants. +## [member double_click] : Set to true to simulate a double-click +@abstract func simulate_mouse_button_press(button_index: MouseButton, double_click := false) -> GdUnitSceneRunner + + +## Simulates a mouse button released.[br] +## [member button_index] : The mouse button identifier, one of the [enum MouseButton] or button wheel constants. +@abstract func simulate_mouse_button_release(button_index: MouseButton) -> GdUnitSceneRunner + + +## Simulates a screen touch is pressed.[br] +## [member index] : The touch index in the case of a multi-touch event.[br] +## [member position] : The position to touch the screen.[br] +## [member double_tap] : If true, the touch's state is a double tab. +@abstract func simulate_screen_touch_pressed(index: int, position: Vector2, double_tap := false) -> GdUnitSceneRunner + + +## Simulates a screen touch press without releasing it immediately, effectively simulating a "hold" action.[br] +## [member index] : The touch index in the case of a multi-touch event.[br] +## [member position] : The position to touch the screen.[br] +## [member double_tap] : If true, the touch's state is a double tab. +@abstract func simulate_screen_touch_press(index: int, position: Vector2, double_tap := false) -> GdUnitSceneRunner + + +## Simulates a screen touch is released.[br] +## [member index] : The touch index in the case of a multi-touch event.[br] +## [member double_tap] : If true, the touch's state is a double tab. +@abstract func simulate_screen_touch_release(index: int, double_tap := false) -> GdUnitSceneRunner + + +## Simulates a touch drag and drop event to a relative position.[br] +## [color=yellow]You must use [b]await[/b] to wait until the simulated drag&drop is complete.[/color][br] +## [br] +## [member index] : The touch index in the case of a multi-touch event.[br] +## [member relative] : The relative position, indicating the drag&drop position offset.[br] +## [member time] : The time to move to the relative position in seconds (default is 1 second).[br] +## [member trans_type] : Sets the type of transition used (default is TRANS_LINEAR).[br] +## [codeblock] +## func test_touch_drag_drop(): +## var runner = scene_runner("res://scenes/simple_scene.tscn") +## # start drag at position 50,50 +## runner.simulate_screen_touch_drag_begin(1, Vector2(50, 50)) +## # and drop it at final at 150,50 relative (50,50 + 100,0) +## await runner.simulate_screen_touch_drag_relative(1, Vector2(100,0)) +## [/codeblock] +@abstract func simulate_screen_touch_drag_relative(index: int, relative: Vector2, time: float = 1.0, trans_type: Tween.TransitionType = Tween.TRANS_LINEAR) -> GdUnitSceneRunner + + +## Simulates a touch screen drop to the absolute coordinates (offset).[br] +## [color=yellow]You must use [b]await[/b] to wait until the simulated drop is complete.[/color][br] +## [br] +## [member index] : The touch index in the case of a multi-touch event.[br] +## [member position] : The final position, indicating the drop position.[br] +## [member time] : The time to move to the final position in seconds (default is 1 second).[br] +## [member trans_type] : Sets the type of transition used (default is TRANS_LINEAR).[br] +## [codeblock] +## func test_touch_drag_drop(): +## var runner = scene_runner("res://scenes/simple_scene.tscn") +## # start drag at position 50,50 +## runner.simulate_screen_touch_drag_begin(1, Vector2(50, 50)) +## # and drop it at 100,50 +## await runner.simulate_screen_touch_drag_absolute(1, Vector2(100,50)) +## [/codeblock] +@abstract func simulate_screen_touch_drag_absolute(index: int, position: Vector2, time: float = 1.0, trans_type: Tween.TransitionType = Tween.TRANS_LINEAR) -> GdUnitSceneRunner + + +## Simulates a complete drag and drop event from one position to another.[br] +## This is ideal for testing complex drag-and-drop scenarios that require a specific start and end position.[br] +## [color=yellow]You must use [b]await[/b] to wait until the simulated drop is complete.[/color][br] +## [br] +## [member index] : The touch index in the case of a multi-touch event.[br] +## [member position] : The drag start position, indicating the drag position.[br] +## [member drop_position] : The drop position, indicating the drop position.[br] +## [member time] : The time to move to the final position in seconds (default is 1 second).[br] +## [member trans_type] : Sets the type of transition used (default is TRANS_LINEAR).[br] +## [codeblock] +## func test_touch_drag_drop(): +## var runner = scene_runner("res://scenes/simple_scene.tscn") +## # start drag at position 50,50 and drop it at 100,50 +## await runner.simulate_screen_touch_drag_drop(1, Vector2(50, 50), Vector2(100,50)) +## [/codeblock] +@abstract func simulate_screen_touch_drag_drop(index: int, position: Vector2, drop_position: Vector2, time: float = 1.0, trans_type: Tween.TransitionType = Tween.TRANS_LINEAR) -> GdUnitSceneRunner + + +## Simulates a touch screen drag event to given position.[br] +## [member index] : The touch index in the case of a multi-touch event.[br] +## [member position] : The drag start position, indicating the drag position.[br] +@abstract func simulate_screen_touch_drag(index: int, position: Vector2) -> GdUnitSceneRunner + + +## Returns the actual position of the touchscreen drag position by given index. +## [member index] : The touch index in the case of a multi-touch event.[br] +@abstract func get_screen_touch_drag_position(index: int) -> Vector2 + + +## Sets how fast or slow the scene simulation is processed (clock ticks versus the real).[br] +## It defaults to 1.0. A value of 2.0 means the game moves twice as fast as real life, +## whilst a value of 0.5 means the game moves at half the regular speed. +## [member time_factor] : A float representing the simulation speed.[br] +## - Default is 1.0, meaning the simulation runs at normal speed.[br] +## - A value of 2.0 means the simulation runs twice as fast as real time.[br] +## - A value of 0.5 means the simulation runs at half the regular speed.[br] +@abstract func set_time_factor(time_factor: float = 1.0) -> GdUnitSceneRunner + + +## Simulates scene processing for a certain number of frames.[br] +## [member frames] : amount of frames to process[br] +## [member delta_milli] : the time delta between a frame in milliseconds +@abstract func simulate_frames(frames: int, delta_milli: int = -1) -> GdUnitSceneRunner + + +## Simulates scene processing until the given signal is emitted by the scene.[br] +## [member signal_name] : the signal to stop the simulation[br] +## [member args] : optional signal arguments to be matched for stop[br] +@abstract func simulate_until_signal(signal_name: String, ...args: Array) -> GdUnitSceneRunner + + +## Simulates scene processing until the given signal is emitted by the given object.[br] +## [member source] : the object that should emit the signal[br] +## [member signal_name] : the signal to stop the simulation[br] +## [member args] : optional signal arguments to be matched for stop +@abstract func simulate_until_object_signal(source: Object, signal_name: String, ...args: Array) -> GdUnitSceneRunner + + +## Waits for all input events to be processed by flushing any buffered input events +## and then awaiting a full cycle of both the process and physics frames.[br] +## [br] +## This is typically used to ensure that any simulated or queued inputs are fully +## processed before proceeding with the next steps in the scene.[br] +## It's essential for reliable input simulation or when synchronizing logic based +## on inputs.[br] +## +## Usage Example: +## [codeblock] +## await await_input_processed() # Ensure all inputs are processed before continuing +## [/codeblock] +@abstract func await_input_processed() -> void + + +## The await_func function pauses execution until a specified function in the scene returns a value.[br] +## It returns a [GdUnitFuncAssert], which provides a suite of assertion methods to verify the returned value.[br] +## [member func_name] : The name of the function to wait for.[br] +## [member args] : Optional function arguments +## [br] +## Usage Example: +## [codeblock] +## # Waits for 'calculate_score' function and verifies the result is equal to 100. +## await_func("calculate_score").is_equal(100) +## [/codeblock] +@abstract func await_func(func_name: String, ...args: Array) -> GdUnitFuncAssert + + +## The await_func_on function extends the functionality of await_func by allowing you to specify a source node within the scene.[br] +## It waits for a specified function on that node to return a value and returns a [GdUnitFuncAssert] object for assertions.[br] +## [member source] : The object where implements the function.[br] +## [member func_name] : The name of the function to wait for.[br] +## [member args] : optional function arguments +## [br] +## Usage Example: +## [codeblock] +## # Waits for 'calculate_score' function and verifies the result is equal to 100. +## var my_instance := ScoreCalculator.new() +## await_func(my_instance, "calculate_score").is_equal(100) +## [/codeblock] +@abstract func await_func_on(source: Object, func_name: String, ...args: Array) -> GdUnitFuncAssert + + +## Waits for the specified signal to be emitted by the scene. If the signal is not emitted within the given timeout, the operation fails.[br] +## [member signal_name] : The name of the signal to wait for[br] +## [member args] : The signal arguments as an array[br] +## [member timeout] : The maximum duration (in milliseconds) to wait for the signal to be emitted before failing +@abstract func await_signal(signal_name: String, args := [], timeout := 2000 ) -> void + + +## Waits for the specified signal to be emitted by a particular source node. If the signal is not emitted within the given timeout, the operation fails.[br] +## [member source] : the object from which the signal is emitted[br] +## [member signal_name] : The name of the signal to wait for[br] +## [member args] : The signal arguments as an array[br] +## [member timeout] : tThe maximum duration (in milliseconds) to wait for the signal to be emitted before failing +@abstract func await_signal_on(source: Object, signal_name: String, args := [], timeout := 2000 ) -> void + + +## Restores the scene window to a windowed mode and brings it to the foreground.[br] +## This ensures that the scene is visible and active during testing, making it easier to observe and interact with. +@abstract func move_window_to_foreground() -> GdUnitSceneRunner + + +## Minimizes the scene window to a windowed mode and brings it to the background.[br] +## This ensures that the scene is hidden during testing. +@abstract func move_window_to_background() -> GdUnitSceneRunner + + +## Return the current value of the property with the name .[br] +## [member name] : name of property[br] +## [member return] : the value of the property +@abstract func get_property(name: String) -> Variant + + +## Set the value of the property with the name .[br] +## [member name] : name of property[br] +## [member value] : value of property[br] +## [member return] : true|false depending on valid property name. +@abstract func set_property(name: String, value: Variant) -> bool + + +## executes the function specified by in the scene and returns the result.[br] +## [member name] : the name of the function to execute[br] +## [member args] : optional function arguments[br] +## [member return] : the function result +@abstract func invoke(name: String, ...args: Array) -> Variant + + +## Searches for the specified node with the name in the current scene and returns it, otherwise null.[br] +## [member name] : the name of the node to find[br] +## [member recursive] : enables/disables seraching recursive[br] +## [member return] : the node if find otherwise null +@abstract func find_child(name: String, recursive: bool = true, owned: bool = false) -> Node + + +## Access to current running scene +@abstract func scene() -> Node diff --git a/addons/gdUnit4/src/GdUnitSceneRunner.gd.uid b/addons/gdUnit4/src/GdUnitSceneRunner.gd.uid new file mode 100644 index 0000000..f981d08 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitSceneRunner.gd.uid @@ -0,0 +1 @@ +uid://2q5oityuhdkr diff --git a/addons/gdUnit4/src/GdUnitSignalAssert.gd b/addons/gdUnit4/src/GdUnitSignalAssert.gd new file mode 100644 index 0000000..bb975e8 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitSignalAssert.gd @@ -0,0 +1,46 @@ +## An Assertion Tool to verify for emitted signals until a waiting time +@abstract class_name GdUnitSignalAssert +extends GdUnitAssert + + +## Verifies that the current value is null. +@abstract func is_null() -> GdUnitSignalAssert + + +## Verifies that the current value is not null. +@abstract func is_not_null() -> GdUnitSignalAssert + + +## Verifies that the current value is equal to the given one. +@abstract func is_equal(expected: Variant) -> GdUnitSignalAssert + + +## Verifies that the current value is not equal to expected one. +@abstract func is_not_equal(expected: Variant) -> GdUnitSignalAssert + + +## Overrides the default failure message by given custom message. +@abstract func override_failure_message(message: String) -> GdUnitSignalAssert + + +## Appends a custom message to the failure message. +@abstract func append_failure_message(message: String) -> GdUnitSignalAssert + + +## Verifies that given signal is emitted until waiting time +@abstract func is_emitted(name: String, args := []) -> GdUnitSignalAssert + + +## Verifies that given signal is NOT emitted until waiting time +@abstract func is_not_emitted(name: String, args := []) -> GdUnitSignalAssert + + +## Verifies the signal exists checked the emitter +@abstract func is_signal_exists(name: String) -> GdUnitSignalAssert + + +## Sets the assert signal timeout in ms, if the time over a failure is reported.[br] +## e.g.[br] +## do wait until 5s the instance has emitted the signal `signal_a`[br] +## [code]assert_signal(instance).wait_until(5000).is_emitted("signal_a")[/code] +@abstract func wait_until(timeout: int) -> GdUnitSignalAssert diff --git a/addons/gdUnit4/src/GdUnitSignalAssert.gd.uid b/addons/gdUnit4/src/GdUnitSignalAssert.gd.uid new file mode 100644 index 0000000..0aa56c3 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitSignalAssert.gd.uid @@ -0,0 +1 @@ +uid://mbxuu2iwaq2 diff --git a/addons/gdUnit4/src/GdUnitStringAssert.gd b/addons/gdUnit4/src/GdUnitStringAssert.gd new file mode 100644 index 0000000..2de698b --- /dev/null +++ b/addons/gdUnit4/src/GdUnitStringAssert.gd @@ -0,0 +1,71 @@ +## An Assertion Tool to verify String values +@abstract class_name GdUnitStringAssert +extends GdUnitAssert + + +## Verifies that the current value is null. +@abstract func is_null() -> GdUnitStringAssert + + +## Verifies that the current value is not null. +@abstract func is_not_null() -> GdUnitStringAssert + + +## Verifies that the current value is equal to the given one. +@abstract func is_equal(expected: Variant) -> GdUnitStringAssert + + +## Verifies that the current String is equal to the given one, ignoring case considerations. +@abstract func is_equal_ignoring_case(expected: Variant) -> GdUnitStringAssert + + +## Verifies that the current value is not equal to expected one. +@abstract func is_not_equal(expected: Variant) -> GdUnitStringAssert + + +## Verifies that the current String is not equal to the given one, ignoring case considerations. +@abstract func is_not_equal_ignoring_case(expected: Variant) -> GdUnitStringAssert + + +## Overrides the default failure message by given custom message. +@abstract func override_failure_message(message: String) -> GdUnitStringAssert + + +## Appends a custom message to the failure message. +@abstract func append_failure_message(message: String) -> GdUnitStringAssert + + +## Verifies that the current String is empty, it has a length of 0. +@abstract func is_empty() -> GdUnitStringAssert + + +## Verifies that the current String is not empty, it has a length of minimum 1. +@abstract func is_not_empty() -> GdUnitStringAssert + + +## Verifies that the current String contains the given String. +@abstract func contains(expected: String) -> GdUnitStringAssert + + +## Verifies that the current String does not contain the given String. +@abstract func not_contains(expected: String) -> GdUnitStringAssert + + +## Verifies that the current String does not contain the given String, ignoring case considerations. +@abstract func contains_ignoring_case(expected: String) -> GdUnitStringAssert + + +## Verifies that the current String does not contain the given String, ignoring case considerations. +@abstract func not_contains_ignoring_case(expected: String) -> GdUnitStringAssert + + +## Verifies that the current String starts with the given prefix. +@abstract func starts_with(expected: String) -> GdUnitStringAssert + + +## Verifies that the current String ends with the given suffix. +@abstract func ends_with(expected: String) -> GdUnitStringAssert + + +## Verifies that the current String has the expected length by used comparator. +@abstract func has_length(length: int, comparator: int = Comparator.EQUAL) -> GdUnitStringAssert diff --git a/addons/gdUnit4/src/GdUnitStringAssert.gd.uid b/addons/gdUnit4/src/GdUnitStringAssert.gd.uid new file mode 100644 index 0000000..98b83c8 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitStringAssert.gd.uid @@ -0,0 +1 @@ +uid://haccmssdxpsq diff --git a/addons/gdUnit4/src/GdUnitTestSuite.gd b/addons/gdUnit4/src/GdUnitTestSuite.gd new file mode 100644 index 0000000..e69c7a8 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitTestSuite.gd @@ -0,0 +1,691 @@ +## The main class for all GdUnit test suites[br] +## This class is the main class to implement your unit tests[br] +## You have to extend and implement your test cases as described[br] +## e.g MyTests.gd [br] +## [codeblock] +## extends GdUnitTestSuite +## # testcase +## func test_case_a(): +## assert_that("value").is_equal("value") +## [/codeblock] +## @tutorial: https://mikeschulze.github.io/gdUnit4/faq/test-suite/ + +@icon("res://addons/gdUnit4/src/ui/settings/logo.png") +class_name GdUnitTestSuite +extends Node + +const NO_ARG :Variant = GdUnitConstants.NO_ARG + +### internal runtime variables that must not be overwritten!!! +@warning_ignore("unused_private_class_variable") +var __is_skipped := false +@warning_ignore("unused_private_class_variable") +var __skip_reason :String = "Unknow." +var __active_test_case :String +var __awaiter := __gdunit_awaiter() + + +### We now load all used asserts and tool scripts into the cache according to the principle of "lazy loading" +### in order to noticeably reduce the loading time of the test suite. +# We go this hard way to increase the loading performance to avoid reparsing all the used scripts +# for more detailed info -> https://github.com/godotengine/godot/issues/67400 +func __lazy_load(script_path :String) -> GDScript: + return GdUnitAssertions.__lazy_load(script_path) + + +func __gdunit_assert() -> GDScript: + return __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitAssertImpl.gd") + + +func __gdunit_tools() -> GDScript: + return __lazy_load("res://addons/gdUnit4/src/core/GdUnitTools.gd") + + +func __gdunit_file_access() -> GDScript: + return __lazy_load("res://addons/gdUnit4/src/core/GdUnitFileAccess.gd") + + +func __gdunit_awaiter() -> Object: + return __lazy_load("res://addons/gdUnit4/src/GdUnitAwaiter.gd").new() + + +func __gdunit_argument_matchers() -> GDScript: + return __lazy_load("res://addons/gdUnit4/src/matchers/GdUnitArgumentMatchers.gd") + + +func __gdunit_object_interactions() -> GDScript: + return __lazy_load("res://addons/gdUnit4/src/doubler/GdUnitObjectInteractions.gd") + + +## This function is called before a test suite starts[br] +## You can overwrite to prepare test data or initalizize necessary variables +func before() -> void: + pass + + +## This function is called at least when a test suite is finished[br] +## You can overwrite to cleanup data created during test running +func after() -> void: + pass + + +## This function is called before a test case starts[br] +## You can overwrite to prepare test case specific data +func before_test() -> void: + pass + + +## This function is called after the test case is finished[br] +## You can overwrite to cleanup your test case specific data +func after_test() -> void: + pass + + +func is_failure(_expected_failure :String = NO_ARG) -> bool: + return Engine.get_meta("GD_TEST_FAILURE") if Engine.has_meta("GD_TEST_FAILURE") else false + + +func set_active_test_case(test_case :String) -> void: + __active_test_case = test_case + + +# === Tools ==================================================================== +# Mapps Godot error number to a readable error message. See at ERROR +# https://docs.godotengine.org/de/stable/classes/class_@globalscope.html#enum-globalscope-error +func error_as_string(error_number :int) -> String: + return error_string(error_number) + + +## A litle helper to auto freeing your created objects after test execution +func auto_free(obj :Variant) -> Variant: + var execution_context := GdUnitThreadManager.get_current_context().get_execution_context() + + assert(execution_context != null, "INTERNAL ERROR: The current execution_context is null! Please report this as bug.") + return execution_context.register_auto_free(obj) + + +@warning_ignore("native_method_override") +func add_child(node :Node, force_readable_name := false, internal := Node.INTERNAL_MODE_DISABLED) -> void: + super.add_child(node, force_readable_name, internal) + var execution_context := GdUnitThreadManager.get_current_context().get_execution_context() + if execution_context != null: + execution_context.orphan_monitor_start() + + +## Discard the error message triggered by a timeout (interruption).[br] +## By default, an interrupted test is reported as an error.[br] +## This function allows you to change the message to Success when an interrupted error is reported. +func discard_error_interupted_by_timeout() -> void: + @warning_ignore("unsafe_method_access") + __gdunit_tools().register_expect_interupted_by_timeout(self, __active_test_case) + + +## Creates a new directory under the temporary directory *user://tmp*[br] +## Useful for storing data during test execution. [br] +## The directory is automatically deleted after test suite execution +func create_temp_dir(relative_path :String) -> String: + @warning_ignore("unsafe_method_access") + return __gdunit_file_access().create_temp_dir(relative_path) + + +## Deletes the temporary base directory[br] +## Is called automatically after each execution of the test suite +func clean_temp_dir() -> void: + @warning_ignore("unsafe_method_access") + __gdunit_file_access().clear_tmp() + + +## Creates a new file under the temporary directory *user://tmp* + [br] +## with given name and given file (default = File.WRITE)[br] +## If success the returned File is automatically closed after the execution of the test suite +func create_temp_file(relative_path :String, file_name :String, mode := FileAccess.WRITE) -> FileAccess: + @warning_ignore("unsafe_method_access") + return __gdunit_file_access().create_temp_file(relative_path, file_name, mode) + + +## Reads a resource by given path into a PackedStringArray. +func resource_as_array(resource_path :String) -> PackedStringArray: + @warning_ignore("unsafe_method_access") + return __gdunit_file_access().resource_as_array(resource_path) + + +## Reads a resource by given path and returned the content as String. +func resource_as_string(resource_path :String) -> String: + @warning_ignore("unsafe_method_access") + return __gdunit_file_access().resource_as_string(resource_path) + + +## Reads a resource by given path and return Variand translated by str_to_var +func resource_as_var(resource_path :String) -> Variant: + @warning_ignore("unsafe_method_access", "unsafe_cast") + return str_to_var(__gdunit_file_access().resource_as_string(resource_path) as String) + + +## Waits for given signal to be emitted by until a specified timeout to fail[br] +## source: the object from which the signal is emitted[br] +## signal_name: signal name[br] +## args: the expected signal arguments as an array[br] +## timeout: the timeout in ms, default is set to 2000ms +func await_signal_on(source :Object, signal_name :String, args :Array = [], timeout :int = 2000) -> Variant: + @warning_ignore("unsafe_method_access") + return await __awaiter.await_signal_on(source, signal_name, args, timeout) + + +## Waits until the next idle frame +func await_idle_frame() -> void: + @warning_ignore("unsafe_method_access") + await __awaiter.await_idle_frame() + + +## Waits for a given amount of milliseconds[br] +## example:[br] +## [codeblock] +## # waits for 100ms +## await await_millis(myNode, 100).completed +## [/codeblock][br] +## use this waiter and not `await get_tree().create_timer().timeout to prevent errors when a test case is timed out +func await_millis(timeout :int) -> void: + @warning_ignore("unsafe_method_access") + await __awaiter.await_millis(timeout) + + +## Creates a new scene runner to allow simulate interactions checked a scene.[br] +## The runner will manage the scene instance and release after the runner is released[br] +## example:[br] +## [codeblock] +## # creates a runner by using a instanciated scene +## var scene = load("res://foo/my_scne.tscn").instantiate() +## var runner := scene_runner(scene) +## +## # or simply creates a runner by using the scene resource path +## var runner := scene_runner("res://foo/my_scne.tscn") +## [/codeblock] +func scene_runner(scene :Variant, verbose := false) -> GdUnitSceneRunner: + return auto_free(__lazy_load("res://addons/gdUnit4/src/core/GdUnitSceneRunnerImpl.gd").new(scene, verbose)) + + +# === Mocking & Spy =========================================================== + +## do return a default value for primitive types or null +const RETURN_DEFAULTS = GdUnitMock.RETURN_DEFAULTS +## do call the real implementation +const CALL_REAL_FUNC = GdUnitMock.CALL_REAL_FUNC +## do return a default value for primitive types and a fully mocked value for Object types +## builds full deep mocked object +const RETURN_DEEP_STUB = GdUnitMock.RETURN_DEEP_STUB + + +## Creates a mock for given class name +func mock(clazz :Variant, mock_mode := RETURN_DEFAULTS) -> Variant: + @warning_ignore("unsafe_method_access") + return __lazy_load("res://addons/gdUnit4/src/mocking/GdUnitMockBuilder.gd").build(clazz, mock_mode) + + +## Creates a spy checked given object instance +func spy(instance :Variant) -> Variant: + @warning_ignore("unsafe_method_access") + return __lazy_load("res://addons/gdUnit4/src/spy/GdUnitSpyBuilder.gd").build(instance) + + +## Configures a return value for the specified function and used arguments.[br] +## [b]Example: +## [codeblock] +## # overrides the return value of myMock.is_selected() to false +## do_return(false).on(myMock).is_selected() +## [/codeblock] +func do_return(value :Variant) -> GdUnitMock: + return GdUnitMock.new(value) + + +## Verifies certain behavior happened at least once or exact number of times +func verify(obj :Variant, times := 1) -> Variant: + @warning_ignore("unsafe_method_access") + return __gdunit_object_interactions().verify(obj, times) + + +## Verifies no interactions is happen checked this mock or spy +func verify_no_interactions(obj :Variant) -> GdUnitAssert: + @warning_ignore("unsafe_method_access") + return __gdunit_object_interactions().verify_no_interactions(obj) + + +## Verifies the given mock or spy has any unverified interaction. +func verify_no_more_interactions(obj :Variant) -> GdUnitAssert: + @warning_ignore("unsafe_method_access") + return __gdunit_object_interactions().verify_no_more_interactions(obj) + + +## Resets the saved function call counters checked a mock or spy +func reset(obj :Variant) -> void: + @warning_ignore("unsafe_method_access") + __gdunit_object_interactions().reset(obj) + + +## Starts monitoring the specified source to collect all transmitted signals.[br] +## The collected signals can then be checked with 'assert_signal'.[br] +## By default, the specified source is automatically released when the test ends. +## You can control this behavior by setting auto_free to false if you do not want the source to be automatically freed.[br] +## Usage: +## [codeblock] +## var emitter := monitor_signals(MyEmitter.new()) +## # call the function to send the signal +## emitter.do_it() +## # verify the signial is emitted +## await assert_signal(emitter).is_emitted('my_signal') +## [/codeblock] +func monitor_signals(source :Object, _auto_free := true) -> Object: + @warning_ignore("unsafe_method_access") + __lazy_load("res://addons/gdUnit4/src/core/thread/GdUnitThreadManager.gd")\ + .get_current_context()\ + .get_signal_collector()\ + .register_emitter(source) + return auto_free(source) if _auto_free else source + + +# === Argument matchers ======================================================== +## Argument matcher to match any argument +func any() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().any() + + +## Argument matcher to match any boolean value +func any_bool() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_BOOL) + + +## Argument matcher to match any integer value +func any_int() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_INT) + + +## Argument matcher to match any float value +func any_float() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_FLOAT) + + +## Argument matcher to match any String value +func any_string() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_STRING) + + +## Argument matcher to match any Color value +func any_color() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_COLOR) + + +## Argument matcher to match any Vector typed value +func any_vector() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_types([ + TYPE_VECTOR2, + TYPE_VECTOR2I, + TYPE_VECTOR3, + TYPE_VECTOR3I, + TYPE_VECTOR4, + TYPE_VECTOR4I, + ]) + + +## Argument matcher to match any Vector2 value +func any_vector2() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_VECTOR2) + + +## Argument matcher to match any Vector2i value +func any_vector2i() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_VECTOR2I) + + +## Argument matcher to match any Vector3 value +func any_vector3() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_VECTOR3) + + +## Argument matcher to match any Vector3i value +func any_vector3i() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_VECTOR3I) + + +## Argument matcher to match any Vector4 value +func any_vector4() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_VECTOR4) + + +## Argument matcher to match any Vector4i value +func any_vector4i() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_VECTOR4I) + + +## Argument matcher to match any Rect2 value +func any_rect2() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_RECT2) + + +## Argument matcher to match any Plane value +func any_plane() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_PLANE) + + +## Argument matcher to match any Quaternion value +func any_quat() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_QUATERNION) + + +## Argument matcher to match any AABB value +func any_aabb() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_AABB) + + +## Argument matcher to match any Basis value +func any_basis() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_BASIS) + + +## Argument matcher to match any Transform2D value +func any_transform_2d() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_TRANSFORM2D) + + +## Argument matcher to match any Transform3D value +func any_transform_3d() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_TRANSFORM3D) + + +## Argument matcher to match any NodePath value +func any_node_path() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_NODE_PATH) + + +## Argument matcher to match any RID value +func any_rid() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_RID) + + +## Argument matcher to match any Object value +func any_object() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_OBJECT) + + +## Argument matcher to match any Dictionary value +func any_dictionary() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_DICTIONARY) + + +## Argument matcher to match any Array value +func any_array() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_ARRAY) + + +## Argument matcher to match any PackedByteArray value +func any_packed_byte_array() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_PACKED_BYTE_ARRAY) + + +## Argument matcher to match any PackedInt32Array value +func any_packed_int32_array() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_PACKED_INT32_ARRAY) + + +## Argument matcher to match any PackedInt64Array value +func any_packed_int64_array() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_PACKED_INT64_ARRAY) + + +## Argument matcher to match any PackedFloat32Array value +func any_packed_float32_array() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_PACKED_FLOAT32_ARRAY) + + +## Argument matcher to match any PackedFloat64Array value +func any_packed_float64_array() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_PACKED_FLOAT64_ARRAY) + + +## Argument matcher to match any PackedStringArray value +func any_packed_string_array() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_PACKED_STRING_ARRAY) + + +## Argument matcher to match any PackedVector2Array value +func any_packed_vector2_array() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_PACKED_VECTOR2_ARRAY) + + +## Argument matcher to match any PackedVector3Array value +func any_packed_vector3_array() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_PACKED_VECTOR3_ARRAY) + + +## Argument matcher to match any PackedColorArray value +func any_packed_color_array() -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().by_type(TYPE_PACKED_COLOR_ARRAY) + + +## Argument matcher to match any instance of given class +func any_class(clazz :Object) -> GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + return __gdunit_argument_matchers().any_class(clazz) + + +# === value extract utils ====================================================== +## Builds an extractor by given function name and optional arguments +func extr(func_name :String, args := Array()) -> GdUnitValueExtractor: + return __lazy_load("res://addons/gdUnit4/src/extractors/GdUnitFuncValueExtractor.gd").new(func_name, args) + + +## Constructs a tuple by given arguments +func tuple(arg0 :Variant, + arg1 :Variant=NO_ARG, + arg2 :Variant=NO_ARG, + arg3 :Variant=NO_ARG, + arg4 :Variant=NO_ARG, + arg5 :Variant=NO_ARG, + arg6 :Variant=NO_ARG, + arg7 :Variant=NO_ARG, + arg8 :Variant=NO_ARG, + arg9 :Variant=NO_ARG) -> GdUnitTuple: + return GdUnitTuple.new(arg0, arg1, arg2, arg3, arg4, arg5, arg6, arg7, arg8, arg9) + + +# === Asserts ================================================================== + +## The common assertion tool to verify values. +## It checks the given value by type to fit to the best assert +func assert_that(current :Variant) -> GdUnitAssert: + match typeof(current): + TYPE_BOOL: + return assert_bool(current) + TYPE_INT: + return assert_int(current) + TYPE_FLOAT: + return assert_float(current) + TYPE_STRING: + return assert_str(current) + TYPE_VECTOR2, TYPE_VECTOR2I, TYPE_VECTOR3, TYPE_VECTOR3I, TYPE_VECTOR4, TYPE_VECTOR4I: + return assert_vector(current, false) + TYPE_DICTIONARY: + return assert_dict(current) + TYPE_ARRAY, TYPE_PACKED_BYTE_ARRAY, TYPE_PACKED_INT32_ARRAY, TYPE_PACKED_INT64_ARRAY,\ + TYPE_PACKED_FLOAT32_ARRAY, TYPE_PACKED_FLOAT64_ARRAY, TYPE_PACKED_STRING_ARRAY,\ + TYPE_PACKED_VECTOR2_ARRAY, TYPE_PACKED_VECTOR3_ARRAY, TYPE_PACKED_COLOR_ARRAY: + return assert_array(current, false) + TYPE_OBJECT, TYPE_NIL: + return assert_object(current) + _: + return __gdunit_assert().new(current) + + +## An assertion tool to verify boolean values. +func assert_bool(current :Variant) -> GdUnitBoolAssert: + return __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitBoolAssertImpl.gd").new(current) + + +## An assertion tool to verify String values. +func assert_str(current :Variant) -> GdUnitStringAssert: + return __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitStringAssertImpl.gd").new(current) + + +## An assertion tool to verify integer values. +func assert_int(current :Variant) -> GdUnitIntAssert: + return __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitIntAssertImpl.gd").new(current) + + +## An assertion tool to verify float values. +func assert_float(current :Variant) -> GdUnitFloatAssert: + return __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitFloatAssertImpl.gd").new(current) + + +## An assertion tool to verify Vector values.[br] +## This assertion supports all vector types.[br] +## Usage: +## [codeblock] +## assert_vector(Vector2(1.2, 1.000001)).is_equal(Vector2(1.2, 1.000001)) +## [/codeblock] +func assert_vector(current :Variant, type_check := true) -> GdUnitVectorAssert: + return __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitVectorAssertImpl.gd").new(current, type_check) + + +## An assertion tool to verify arrays. +func assert_array(current :Variant, type_check := true) -> GdUnitArrayAssert: + return __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitArrayAssertImpl.gd").new(current, type_check) + + +## An assertion tool to verify dictionaries. +func assert_dict(current :Variant) -> GdUnitDictionaryAssert: + return __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitDictionaryAssertImpl.gd").new(current) + + +## An assertion tool to verify FileAccess. +func assert_file(current :Variant) -> GdUnitFileAssert: + return __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitFileAssertImpl.gd").new(current) + + +## An assertion tool to verify Objects. +func assert_object(current :Variant) -> GdUnitObjectAssert: + return __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitObjectAssertImpl.gd").new(current) + + +func assert_result(current :Variant) -> GdUnitResultAssert: + return __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitResultAssertImpl.gd").new(current) + + +## An assertion tool that waits until a certain time for an expected function return value +func assert_func(instance :Object, func_name :String, args := Array()) -> GdUnitFuncAssert: + return __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitFuncAssertImpl.gd").new(instance, func_name, args) + + +## An assertion tool to verify for emitted signals until a certain time. +func assert_signal(instance :Object) -> GdUnitSignalAssert: + return __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitSignalAssertImpl.gd").new(instance) + + +## An assertion tool to test for failing assertions.[br] +## This assert is only designed for internal use to verify failing asserts working as expected.[br] +## Usage: +## [codeblock] +## assert_failure(func(): assert_bool(true).is_not_equal(true)) \ +## .has_message("Expecting:\n 'true'\n not equal to\n 'true'") +## [/codeblock] +func assert_failure(assertion :Callable) -> GdUnitFailureAssert: + @warning_ignore("unsafe_method_access") + return __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitFailureAssertImpl.gd").new().execute(assertion) + + +## An assertion tool to test for failing assertions.[br] +## This assert is only designed for internal use to verify failing asserts working as expected.[br] +## Usage: +## [codeblock] +## await assert_failure_await(func(): assert_bool(true).is_not_equal(true)) \ +## .has_message("Expecting:\n 'true'\n not equal to\n 'true'") +## [/codeblock] +func assert_failure_await(assertion :Callable) -> GdUnitFailureAssert: + @warning_ignore("unsafe_method_access") + return await __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitFailureAssertImpl.gd").new().execute_and_await(assertion) + + +## An assertion tool to verify Godot errors.[br] +## You can use to verify certain Godot errors like failing assertions, push_error, push_warn.[br] +## Usage: +## [codeblock] +## # tests no error occurred during execution of the code +## await assert_error(func (): return 0 )\ +## .is_success() +## +## # tests a push_error('test error') occured during execution of the code +## await assert_error(func (): push_error('test error') )\ +## .is_push_error('test error') +## [/codeblock] +func assert_error(current :Callable) -> GdUnitGodotErrorAssert: + return __lazy_load("res://addons/gdUnit4/src/asserts/GdUnitGodotErrorAssertImpl.gd").new(current) + + +## Explicitly fails the current test indicating that the feature is not yet implemented.[br] +## This function is useful during development when you want to write test cases before implementing the actual functionality.[br] +## It provides a clear indication that the test failure is expected because the feature is still under development.[br] +## Usage: +## [codeblock] +## # Test for a feature that will be implemented later +## func test_advanced_ai_behavior(): +## assert_not_yet_implemented() +## +## [/codeblock] +func assert_not_yet_implemented() -> void: + @warning_ignore("unsafe_method_access") + __gdunit_assert().new(null).do_fail() + + +## Explicitly fails the current test with a custom error message.[br] +## This function reports an error but does not terminate test execution automatically.[br] +## You must use 'return' after calling fail() to stop the test since GDScript has no exception support.[br] +## Useful for complex conditional testing scenarios where standard assertions are insufficient.[br] +## Usage: +## [codeblock] +## # Fail test when conditions are not met +## if !custom_check(player): +## fail("Player should be alive but has %d health" % player.health) +## return +## +## # Continue with test if conditions pass +## assert_that(player.health).is_greater(0) +## [/codeblock] +func fail(message: String) -> void: + @warning_ignore("unsafe_method_access") + __gdunit_assert().new(null).report_error(message) + + +# --- internal stuff do not override!!! +func ResourcePath() -> String: + return get_script().resource_path diff --git a/addons/gdUnit4/src/GdUnitTestSuite.gd.uid b/addons/gdUnit4/src/GdUnitTestSuite.gd.uid new file mode 100644 index 0000000..56827eb --- /dev/null +++ b/addons/gdUnit4/src/GdUnitTestSuite.gd.uid @@ -0,0 +1 @@ +uid://bvnw1dvfilyp3 diff --git a/addons/gdUnit4/src/GdUnitTuple.gd b/addons/gdUnit4/src/GdUnitTuple.gd new file mode 100644 index 0000000..6c91002 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitTuple.gd @@ -0,0 +1,28 @@ +## A tuple implementation to hold two or many values +class_name GdUnitTuple +extends RefCounted + +const NO_ARG :Variant = GdUnitConstants.NO_ARG + +var __values :Array = Array() + + +func _init(arg0:Variant, + arg1 :Variant=NO_ARG, + arg2 :Variant=NO_ARG, + arg3 :Variant=NO_ARG, + arg4 :Variant=NO_ARG, + arg5 :Variant=NO_ARG, + arg6 :Variant=NO_ARG, + arg7 :Variant=NO_ARG, + arg8 :Variant=NO_ARG, + arg9 :Variant=NO_ARG) -> void: + __values = GdArrayTools.filter_value([arg0,arg1,arg2,arg3,arg4,arg5,arg6,arg7,arg8,arg9], NO_ARG) + + +func values() -> Array: + return __values + + +func _to_string() -> String: + return "tuple(%s)" % str(__values) diff --git a/addons/gdUnit4/src/GdUnitTuple.gd.uid b/addons/gdUnit4/src/GdUnitTuple.gd.uid new file mode 100644 index 0000000..69d664d --- /dev/null +++ b/addons/gdUnit4/src/GdUnitTuple.gd.uid @@ -0,0 +1 @@ +uid://3biuc1g6112i diff --git a/addons/gdUnit4/src/GdUnitValueExtractor.gd b/addons/gdUnit4/src/GdUnitValueExtractor.gd new file mode 100644 index 0000000..1a34445 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitValueExtractor.gd @@ -0,0 +1,9 @@ +## This is the base interface for value extraction +class_name GdUnitValueExtractor +extends RefCounted + + +## Extracts a value by given implementation +func extract_value(value :Variant) -> Variant: + push_error("Uninplemented func 'extract_value'") + return value diff --git a/addons/gdUnit4/src/GdUnitValueExtractor.gd.uid b/addons/gdUnit4/src/GdUnitValueExtractor.gd.uid new file mode 100644 index 0000000..55f837f --- /dev/null +++ b/addons/gdUnit4/src/GdUnitValueExtractor.gd.uid @@ -0,0 +1 @@ +uid://bldih0qi4d5k4 diff --git a/addons/gdUnit4/src/GdUnitVectorAssert.gd b/addons/gdUnit4/src/GdUnitVectorAssert.gd new file mode 100644 index 0000000..c186cba --- /dev/null +++ b/addons/gdUnit4/src/GdUnitVectorAssert.gd @@ -0,0 +1,55 @@ +## An Assertion Tool to verify Vector values +@abstract class_name GdUnitVectorAssert +extends GdUnitAssert + + +## Verifies that the current value is null. +@abstract func is_null() -> GdUnitVectorAssert + + +## Verifies that the current value is not null. +@abstract func is_not_null() -> GdUnitVectorAssert + + +## Verifies that the current value is equal to the given one. +@abstract func is_equal(expected: Variant) -> GdUnitVectorAssert + + +## Verifies that the current value is not equal to expected one. +@abstract func is_not_equal(expected: Variant) -> GdUnitVectorAssert + + +## Verifies that the current and expected value are approximately equal. +@abstract func is_equal_approx(expected: Variant, approx: Variant) -> GdUnitVectorAssert + + +## Overrides the default failure message by given custom message. +@abstract func override_failure_message(message: String) -> GdUnitVectorAssert + + +## Appends a custom message to the failure message. +@abstract func append_failure_message(message: String) -> GdUnitVectorAssert + + +## Verifies that the current value is less than the given one. +@abstract func is_less(expected: Variant) -> GdUnitVectorAssert + + +## Verifies that the current value is less than or equal the given one. +@abstract func is_less_equal(expected: Variant) -> GdUnitVectorAssert + + +## Verifies that the current value is greater than the given one. +@abstract func is_greater(expected: Variant) -> GdUnitVectorAssert + + +## Verifies that the current value is greater than or equal the given one. +@abstract func is_greater_equal(expected: Variant) -> GdUnitVectorAssert + + +## Verifies that the current value is between the given boundaries (inclusive). +@abstract func is_between(from: Variant, to: Variant) -> GdUnitVectorAssert + + +## Verifies that the current value is not between the given boundaries (inclusive). +@abstract func is_not_between(from: Variant, to: Variant) -> GdUnitVectorAssert diff --git a/addons/gdUnit4/src/GdUnitVectorAssert.gd.uid b/addons/gdUnit4/src/GdUnitVectorAssert.gd.uid new file mode 100644 index 0000000..06e3de3 --- /dev/null +++ b/addons/gdUnit4/src/GdUnitVectorAssert.gd.uid @@ -0,0 +1 @@ +uid://bqqs7cg70gaw2 diff --git a/addons/gdUnit4/src/asserts/CallBackValueProvider.gd b/addons/gdUnit4/src/asserts/CallBackValueProvider.gd new file mode 100644 index 0000000..6be4b3e --- /dev/null +++ b/addons/gdUnit4/src/asserts/CallBackValueProvider.gd @@ -0,0 +1,25 @@ +# a value provider unsing a callback to get `next` value from a certain function +class_name CallBackValueProvider +extends ValueProvider + +var _cb :Callable +var _args :Array + + +func _init(instance :Object, func_name :String, args :Array = Array(), force_error := true) -> void: + _cb = Callable(instance, func_name); + _args = args + if force_error and not _cb.is_valid(): + push_error("Can't find function '%s' checked instance %s" % [func_name, instance]) + + +func get_value() -> Variant: + if not _cb.is_valid(): + return null + if _args.is_empty(): + return await _cb.call() + return await _cb.callv(_args) + + +func dispose() -> void: + _cb = Callable() diff --git a/addons/gdUnit4/src/asserts/CallBackValueProvider.gd.uid b/addons/gdUnit4/src/asserts/CallBackValueProvider.gd.uid new file mode 100644 index 0000000..e3f973b --- /dev/null +++ b/addons/gdUnit4/src/asserts/CallBackValueProvider.gd.uid @@ -0,0 +1 @@ +uid://cxwhijm17t4gi diff --git a/addons/gdUnit4/src/asserts/DefaultValueProvider.gd b/addons/gdUnit4/src/asserts/DefaultValueProvider.gd new file mode 100644 index 0000000..2f828fa --- /dev/null +++ b/addons/gdUnit4/src/asserts/DefaultValueProvider.gd @@ -0,0 +1,13 @@ +# default value provider, simple returns the initial value +class_name DefaultValueProvider +extends ValueProvider + +var _value: Variant + + +func _init(value: Variant) -> void: + _value = value + + +func get_value() -> Variant: + return _value diff --git a/addons/gdUnit4/src/asserts/DefaultValueProvider.gd.uid b/addons/gdUnit4/src/asserts/DefaultValueProvider.gd.uid new file mode 100644 index 0000000..8e37302 --- /dev/null +++ b/addons/gdUnit4/src/asserts/DefaultValueProvider.gd.uid @@ -0,0 +1 @@ +uid://c8rypp0tibdrq diff --git a/addons/gdUnit4/src/asserts/GdAssertMessages.gd b/addons/gdUnit4/src/asserts/GdAssertMessages.gd new file mode 100644 index 0000000..abc135a --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdAssertMessages.gd @@ -0,0 +1,692 @@ +class_name GdAssertMessages +extends Resource + +const WARN_COLOR = "#EFF883" +const ERROR_COLOR = "#CD5C5C" +const VALUE_COLOR = "#1E90FF" +const SUB_COLOR := Color(1, 0, 0, .3) +const ADD_COLOR := Color(0, 1, 0, .3) + + +# Dictionary of control characters and their readable representations +const CONTROL_CHARS = { + "\n": "", # Line Feed + "\r": "", # Carriage Return + "\t": "", # Tab + "\b": "", # Backspace + "\f": "", # Form Feed + "\v": "", # Vertical Tab + "\a": "", # Bell + "": "" # Escape +} + + +static func format_dict(value :Variant) -> String: + if not value is Dictionary: + return str(value) + + var dict_value: Dictionary = value + if dict_value.is_empty(): + return "{ }" + var as_rows := var_to_str(value).split("\n") + for index in range( 1, as_rows.size()-1): + as_rows[index] = " " + as_rows[index] + as_rows[-1] = " " + as_rows[-1] + return "\n".join(as_rows) + + +# improved version of InputEvent as text +static func input_event_as_text(event :InputEvent) -> String: + var text := "" + if event is InputEventKey: + var key_event := event as InputEventKey + text += "InputEventKey : key='%s', pressed=%s, keycode=%d, physical_keycode=%s" % [ + event.as_text(), key_event.pressed, key_event.keycode, key_event.physical_keycode] + else: + text += event.as_text() + if event is InputEventMouse: + var mouse_event := event as InputEventMouse + text += ", global_position %s" % mouse_event.global_position + if event is InputEventWithModifiers: + var mouse_event := event as InputEventWithModifiers + text += ", shift=%s, alt=%s, control=%s, meta=%s, command=%s" % [ + mouse_event.shift_pressed, + mouse_event.alt_pressed, + mouse_event.ctrl_pressed, + mouse_event.meta_pressed, + mouse_event.command_or_control_autoremap] + return text + + +static func _colored_string_div(characters: String) -> String: + return colored_array_div(characters.to_utf32_buffer().to_int32_array()) + + +static func colored_array_div(characters: PackedInt32Array) -> String: + if characters.is_empty(): + return "" + var result := PackedInt32Array() + var index := 0 + var missing_chars := PackedInt32Array() + var additional_chars := PackedInt32Array() + + while index < characters.size(): + var character := characters[index] + match character: + GdDiffTool.DIV_ADD: + index += 1 + @warning_ignore("return_value_discarded") + additional_chars.append(characters[index]) + GdDiffTool.DIV_SUB: + index += 1 + @warning_ignore("return_value_discarded") + missing_chars.append(characters[index]) + _: + if not missing_chars.is_empty(): + result.append_array(format_chars(missing_chars, SUB_COLOR)) + missing_chars = PackedInt32Array() + if not additional_chars.is_empty(): + result.append_array(format_chars(additional_chars, ADD_COLOR)) + additional_chars = PackedInt32Array() + @warning_ignore("return_value_discarded") + result.append(character) + index += 1 + + result.append_array(format_chars(missing_chars, SUB_COLOR)) + result.append_array(format_chars(additional_chars, ADD_COLOR)) + return result.to_byte_array().get_string_from_utf32() + + +static func _typed_value(value :Variant) -> String: + return GdDefaultValueDecoder.decode(value) + + +static func _warning(error :String) -> String: + return "[color=%s]%s[/color]" % [WARN_COLOR, error] + + +static func _error(error :String) -> String: + return "[color=%s]%s[/color]" % [ERROR_COLOR, error] + + +static func _nerror(number :Variant) -> String: + match typeof(number): + TYPE_INT: + return "[color=%s]%d[/color]" % [ERROR_COLOR, number] + TYPE_FLOAT: + return "[color=%s]%f[/color]" % [ERROR_COLOR, number] + _: + return "[color=%s]%s[/color]" % [ERROR_COLOR, str(number)] + + +static func _colored_value(value :Variant) -> String: + match typeof(value): + TYPE_STRING, TYPE_STRING_NAME: + return "'[color=%s]%s[/color]'" % [VALUE_COLOR, _colored_string_div(str(value))] + TYPE_INT: + return "'[color=%s]%d[/color]'" % [VALUE_COLOR, value] + TYPE_FLOAT: + return "'[color=%s]%s[/color]'" % [VALUE_COLOR, _typed_value(value)] + TYPE_COLOR: + return "'[color=%s]%s[/color]'" % [VALUE_COLOR, _typed_value(value)] + TYPE_OBJECT: + if value == null: + return "'[color=%s][/color]'" % [VALUE_COLOR] + if value is InputEvent: + var ie: InputEvent = value + return "[color=%s]<%s>[/color]" % [VALUE_COLOR, input_event_as_text(ie)] + var obj_value: Object = value + if obj_value.has_method("_to_string"): + return "[color=%s]<%s>[/color]" % [VALUE_COLOR, str(value)] + return "[color=%s]<%s>[/color]" % [VALUE_COLOR, obj_value.get_class()] + TYPE_DICTIONARY: + return "'[color=%s]%s[/color]'" % [VALUE_COLOR, format_dict(value)] + _: + if GdArrayTools.is_array_type(value): + return "'[color=%s]%s[/color]'" % [VALUE_COLOR, _typed_value(value)] + return "'[color=%s]%s[/color]'" % [VALUE_COLOR, value] + + + +static func _index_report_as_table(index_reports :Array) -> String: + var table := "[table=3]$cells[/table]" + var header := "[cell][right][b]$text[/b][/right]\t[/cell]" + var cell := "[cell][right]$text[/right]\t[/cell]" + var cells := header.replace("$text", "Index") + header.replace("$text", "Current") + header.replace("$text", "Expected") + for report :Variant in index_reports: + var index :String = str(report["index"]) + var current :String = str(report["current"]) + var expected :String = str(report["expected"]) + cells += cell.replace("$text", index) + cell.replace("$text", current) + cell.replace("$text", expected) + return table.replace("$cells", cells) + + +static func orphan_detected_on_suite_setup(count :int) -> String: + return "%s\n Detected <%d> orphan nodes during test suite setup stage! [b]Check before() and after()![/b]" % [ + _warning("WARNING:"), count] + + +static func orphan_detected_on_test_setup(count :int) -> String: + return "%s\n Detected <%d> orphan nodes during test setup! [b]Check before_test() and after_test()![/b]" % [ + _warning("WARNING:"), count] + + +static func orphan_detected_on_test(count :int) -> String: + return "%s\n Detected <%d> orphan nodes during test execution!" % [ + _warning("WARNING:"), count] + + +static func fuzzer_interuped(iterations: int, error: String) -> String: + return "%s %s %s\n %s" % [ + _error("Found an error after"), + _colored_value(iterations + 1), + _error("test iterations"), + error] + + +static func test_timeout(timeout :int) -> String: + return "%s\n %s" % [_error("Timeout !"), _colored_value("Test timed out after %s" % LocalTime.elapsed(timeout))] + + +# gdlint:disable = mixed-tabs-and-spaces +static func test_suite_skipped(hint :String, skip_count :int) -> String: + return """ + %s + Skipped %s tests + Reason: %s + """.dedent().trim_prefix("\n")\ + % [_error("The Entire test-suite is skipped!"), _colored_value(skip_count), _colored_value(hint)] + + +static func test_skipped(hint :String) -> String: + return """ + %s + Reason: %s + """.dedent().trim_prefix("\n")\ + % [_error("This test is skipped!"), _colored_value(hint)] + + +static func error_not_implemented() -> String: + return _error("Test not implemented!") + + +static func error_is_null(current :Variant) -> String: + return "%s %s but was %s" % [_error("Expecting:"), _colored_value(null), _colored_value(current)] + + +static func error_is_not_null() -> String: + return "%s %s" % [_error("Expecting: not to be"), _colored_value(null)] + + +static func error_equal(current :Variant, expected :Variant, index_reports :Array = []) -> String: + var report := """ + %s + %s + but was + %s""".dedent().trim_prefix("\n") % [_error("Expecting:"), _colored_value(expected), _colored_value(current)] + if not index_reports.is_empty(): + report += "\n\n%s\n%s" % [_error("Differences found:"), _index_report_as_table(index_reports)] + return report + + +static func error_not_equal(current :Variant, expected :Variant) -> String: + return "%s\n %s\n not equal to\n %s" % [_error("Expecting:"), _colored_value(expected), _colored_value(current)] + + +static func error_not_equal_case_insensetiv(current :Variant, expected :Variant) -> String: + return "%s\n %s\n not equal to (case insensitiv)\n %s" % [ + _error("Expecting:"), _colored_value(expected), _colored_value(current)] + + +static func error_is_empty(current :Variant) -> String: + return "%s\n must be empty but was\n %s" % [_error("Expecting:"), _colored_value(current)] + + +static func error_is_not_empty() -> String: + return "%s\n must not be empty" % [_error("Expecting:")] + + +static func error_is_same(current :Variant, expected :Variant) -> String: + return "%s\n %s\n to refer to the same object\n %s" % [_error("Expecting:"), _colored_value(expected), _colored_value(current)] + + +@warning_ignore("unused_parameter") +static func error_not_same(_current :Variant, expected :Variant) -> String: + return "%s\n %s" % [_error("Expecting not same:"), _colored_value(expected)] + + +static func error_not_same_error(current :Variant, expected :Variant) -> String: + return "%s\n %s\n but was\n %s" % [_error("Expecting error message:"), _colored_value(expected), _colored_value(current)] + + +static func error_is_instanceof(current: GdUnitResult, expected :GdUnitResult) -> String: + return "%s\n %s\n But it was %s" % [_error("Expected instance of:"),\ + _colored_value(expected.or_else(null)), _colored_value(current.or_else(null))] + + +# -- Boolean Assert specific messages ----------------------------------------------------- +static func error_is_true(current :Variant) -> String: + return "%s %s but is %s" % [_error("Expecting:"), _colored_value(true), _colored_value(current)] + + +static func error_is_false(current :Variant) -> String: + return "%s %s but is %s" % [_error("Expecting:"), _colored_value(false), _colored_value(current)] + + +# - Integer/Float Assert specific messages ----------------------------------------------------- + +static func error_is_even(current :Variant) -> String: + return "%s\n %s must be even" % [_error("Expecting:"), _colored_value(current)] + + +static func error_is_odd(current :Variant) -> String: + return "%s\n %s must be odd" % [_error("Expecting:"), _colored_value(current)] + + +static func error_is_negative(current :Variant) -> String: + return "%s\n %s be negative" % [_error("Expecting:"), _colored_value(current)] + + +static func error_is_not_negative(current :Variant) -> String: + return "%s\n %s be not negative" % [_error("Expecting:"), _colored_value(current)] + + +static func error_is_zero(current :Variant) -> String: + return "%s\n equal to 0 but is %s" % [_error("Expecting:"), _colored_value(current)] + + +static func error_is_not_zero() -> String: + return "%s\n not equal to 0" % [_error("Expecting:")] + + +static func error_is_wrong_type(current_type :Variant.Type, expected_type :Variant.Type) -> String: + return "%s\n Expecting type %s but is %s" % [ + _error("Unexpected type comparison:"), + _colored_value(GdObjects.type_as_string(current_type)), + _colored_value(GdObjects.type_as_string(expected_type))] + + +static func error_is_value(operation :int, current :Variant, expected :Variant, expected2 :Variant = null) -> String: + match operation: + Comparator.EQUAL: + return "%s\n %s but was '%s'" % [_error("Expecting:"), _colored_value(expected), _nerror(current)] + Comparator.LESS_THAN: + return "%s\n %s but was '%s'" % [_error("Expecting to be less than:"), _colored_value(expected), _nerror(current)] + Comparator.LESS_EQUAL: + return "%s\n %s but was '%s'" % [_error("Expecting to be less than or equal:"), _colored_value(expected), _nerror(current)] + Comparator.GREATER_THAN: + return "%s\n %s but was '%s'" % [_error("Expecting to be greater than:"), _colored_value(expected), _nerror(current)] + Comparator.GREATER_EQUAL: + return "%s\n %s but was '%s'" % [_error("Expecting to be greater than or equal:"), _colored_value(expected), _nerror(current)] + Comparator.BETWEEN_EQUAL: + return "%s\n %s\n in range between\n %s <> %s" % [ + _error("Expecting:"), _colored_value(current), _colored_value(expected), _colored_value(expected2)] + Comparator.NOT_BETWEEN_EQUAL: + return "%s\n %s\n not in range between\n %s <> %s" % [ + _error("Expecting:"), _colored_value(current), _colored_value(expected), _colored_value(expected2)] + return "TODO create expected message" + + +static func error_is_in(current :Variant, expected :Array) -> String: + return "%s\n %s\n is in\n %s" % [_error("Expecting:"), _colored_value(current), _colored_value(str(expected))] + + +static func error_is_not_in(current :Variant, expected :Array) -> String: + return "%s\n %s\n is not in\n %s" % [_error("Expecting:"), _colored_value(current), _colored_value(str(expected))] + + +# - StringAssert --------------------------------------------------------------------------------- +static func error_equal_ignoring_case(current :Variant, expected :Variant) -> String: + return "%s\n %s\n but was\n %s (ignoring case)" % [_error("Expecting:"), _colored_value(expected), _colored_value(current)] + + +static func error_contains(current :Variant, expected :Variant) -> String: + return "%s\n %s\n do contains\n %s" % [_error("Expecting:"), _colored_value(current), _colored_value(expected)] + + +static func error_not_contains(current :Variant, expected :Variant) -> String: + return "%s\n %s\n not do contain\n %s" % [_error("Expecting:"), _colored_value(current), _colored_value(expected)] + + +static func error_contains_ignoring_case(current :Variant, expected :Variant) -> String: + return "%s\n %s\n contains\n %s\n (ignoring case)" % [_error("Expecting:"), _colored_value(current), _colored_value(expected)] + + +static func error_not_contains_ignoring_case(current :Variant, expected :Variant) -> String: + return "%s\n %s\n not do contains\n %s\n (ignoring case)" % [_error("Expecting:"), _colored_value(current), _colored_value(expected)] + + +static func error_starts_with(current :Variant, expected :Variant) -> String: + return "%s\n %s\n to start with\n %s" % [_error("Expecting:"), _colored_value(current), _colored_value(expected)] + + +static func error_ends_with(current :Variant, expected :Variant) -> String: + return "%s\n %s\n to end with\n %s" % [_error("Expecting:"), _colored_value(current), _colored_value(expected)] + + +static func error_has_length(current :Variant, expected: int, compare_operator :int) -> String: + @warning_ignore("unsafe_method_access") + var current_length :Variant = current.length() if current != null else null + match compare_operator: + Comparator.EQUAL: + return "%s\n %s but was '%s' in\n %s" % [ + _error("Expecting size:"), _colored_value(expected), _nerror(current_length), _colored_value(current)] + Comparator.LESS_THAN: + return "%s\n %s but was '%s' in\n %s" % [ + _error("Expecting size to be less than:"), _colored_value(expected), _nerror(current_length), _colored_value(current)] + Comparator.LESS_EQUAL: + return "%s\n %s but was '%s' in\n %s" % [ + _error("Expecting size to be less than or equal:"), _colored_value(expected), + _nerror(current_length), _colored_value(current)] + Comparator.GREATER_THAN: + return "%s\n %s but was '%s' in\n %s" % [ + _error("Expecting size to be greater than:"), _colored_value(expected), + _nerror(current_length), _colored_value(current)] + Comparator.GREATER_EQUAL: + return "%s\n %s but was '%s' in\n %s" % [ + _error("Expecting size to be greater than or equal:"), _colored_value(expected), + _nerror(current_length), _colored_value(current)] + return "TODO create expected message" + + +# - ArrayAssert specific messgaes --------------------------------------------------- + +static func error_arr_contains(current: Variant, expected: Variant, not_expect: Variant, not_found: Variant, by_reference: bool) -> String: + var failure_message := "Expecting contains SAME elements:" if by_reference else "Expecting contains elements:" + var error := "%s\n %s\n do contains (in any order)\n %s" % [ + _error(failure_message), _colored_value(current), _colored_value(expected)] + if not is_empty(not_expect): + error += "\nbut some elements where not expected:\n %s" % _colored_value(not_expect) + if not is_empty(not_found): + var prefix := "but" if is_empty(not_expect) else "and" + error += "\n%s could not find elements:\n %s" % [prefix, _colored_value(not_found)] + return error + + +static func error_arr_contains_exactly( + current: Variant, + expected: Variant, + not_expect: Variant, + not_found: Variant, compare_mode: GdObjects.COMPARE_MODE) -> String: + var failure_message := ( + "Expecting contains exactly elements:" if compare_mode == GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST + else "Expecting contains SAME exactly elements:" + ) + if is_empty(not_expect) and is_empty(not_found): + var arr_current: Array = current + var arr_expected: Array = expected + var diff := _find_first_diff(arr_current, arr_expected) + return "%s\n %s\n do contains (in same order)\n %s\n but has different order %s" % [ + _error(failure_message), _colored_value(current), _colored_value(expected), diff] + + var error := "%s\n %s\n do contains (in same order)\n %s" % [ + _error(failure_message), _colored_value(current), _colored_value(expected)] + if not is_empty(not_expect): + error += "\nbut some elements where not expected:\n %s" % _colored_value(not_expect) + if not is_empty(not_found): + var prefix := "but" if is_empty(not_expect) else "and" + error += "\n%s could not find elements:\n %s" % [prefix, _colored_value(not_found)] + return error + + +static func error_arr_contains_exactly_in_any_order( + current: Variant, + expected: Variant, + not_expect: Variant, + not_found: Variant, + compare_mode: GdObjects.COMPARE_MODE) -> String: + + var failure_message := ( + "Expecting contains exactly elements:" if compare_mode == GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST + else "Expecting contains SAME exactly elements:" + ) + var error := "%s\n %s\n do contains exactly (in any order)\n %s" % [ + _error(failure_message), _colored_value(current), _colored_value(expected)] + if not is_empty(not_expect): + error += "\nbut some elements where not expected:\n %s" % _colored_value(not_expect) + if not is_empty(not_found): + var prefix := "but" if is_empty(not_expect) else "and" + error += "\n%s could not find elements:\n %s" % [prefix, _colored_value(not_found)] + return error + + +static func error_arr_not_contains(current: Variant, expected: Variant, found: Variant, compare_mode: GdObjects.COMPARE_MODE) -> String: + var failure_message := "Expecting:" if compare_mode == GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST else "Expecting SAME:" + var error := "%s\n %s\n do not contains\n %s" % [ + _error(failure_message), _colored_value(current), _colored_value(expected)] + if not is_empty(found): + error += "\n but found elements:\n %s" % _colored_value(found) + return error + + +# - DictionaryAssert specific messages ---------------------------------------------- +static func error_contains_keys(current :Array, expected :Array, keys_not_found :Array, compare_mode :GdObjects.COMPARE_MODE) -> String: + var failure := ( + "Expecting contains keys:" if compare_mode == GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST + else "Expecting contains SAME keys:" + ) + return "%s\n %s\n to contains:\n %s\n but can't find key's:\n %s" % [ + _error(failure), _colored_value(current), _colored_value(expected), _colored_value(keys_not_found)] + + +static func error_not_contains_keys(current :Array, expected :Array, keys_not_found :Array, compare_mode :GdObjects.COMPARE_MODE) -> String: + var failure := ( + "Expecting NOT contains keys:" if compare_mode == GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST + else "Expecting NOT contains SAME keys" + ) + return "%s\n %s\n do not contains:\n %s\n but contains key's:\n %s" % [ + _error(failure), _colored_value(current), _colored_value(expected), _colored_value(keys_not_found)] + + +static func error_contains_key_value(key :Variant, value :Variant, current_value :Variant, compare_mode :GdObjects.COMPARE_MODE) -> String: + var failure := ( + "Expecting contains key and value:" if compare_mode == GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST + else "Expecting contains SAME key and value:" + ) + return "%s\n %s : %s\n but contains\n %s : %s" % [ + _error(failure), _colored_value(key), _colored_value(value), _colored_value(key), _colored_value(current_value)] + + +# - ResultAssert specific errors ---------------------------------------------------- +static func error_result_is_empty(current :GdUnitResult) -> String: + return _result_error_message(current, GdUnitResult.EMPTY) + + +static func error_result_is_success(current :GdUnitResult) -> String: + return _result_error_message(current, GdUnitResult.SUCCESS) + + +static func error_result_is_warning(current :GdUnitResult) -> String: + return _result_error_message(current, GdUnitResult.WARN) + + +static func error_result_is_error(current :GdUnitResult) -> String: + return _result_error_message(current, GdUnitResult.ERROR) + + +static func error_result_has_message(current :String, expected :String) -> String: + return "%s\n %s\n but was\n %s." % [_error("Expecting:"), _colored_value(expected), _colored_value(current)] + + +static func error_result_has_message_on_success(expected :String) -> String: + return "%s\n %s\n but the GdUnitResult is a success." % [_error("Expecting:"), _colored_value(expected)] + + +static func error_result_is_value(current :Variant, expected :Variant) -> String: + return "%s\n %s\n but was\n %s." % [_error("Expecting to contain same value:"), _colored_value(expected), _colored_value(current)] + + +static func _result_error_message(current :GdUnitResult, expected_type :int) -> String: + if current == null: + return _error("Expecting the result must be a %s but was ." % result_type(expected_type)) + if current.is_success(): + return _error("Expecting the result must be a %s but was SUCCESS." % result_type(expected_type)) + var error := "Expecting the result must be a %s but was %s:" % [result_type(expected_type), result_type(current._state)] + return "%s\n %s" % [_error(error), _colored_value(result_message(current))] + + +static func error_interrupted(func_name :String, expected :Variant, elapsed :String) -> String: + func_name = humanized(func_name) + if expected == null: + return "%s %s but timed out after %s" % [_error("Expected:"), func_name, elapsed] + return "%s %s %s but timed out after %s" % [_error("Expected:"), func_name, _colored_value(expected), elapsed] + + +static func error_wait_signal(signal_name :String, args :Array, elapsed :String) -> String: + if args.is_empty(): + return "%s %s but timed out after %s" % [ + _error("Expecting emit signal:"), _colored_value(signal_name + "()"), elapsed] + return "%s %s but timed out after %s" % [ + _error("Expecting emit signal:"), _colored_value(signal_name + "(" + str(args) + ")"), elapsed] + + +static func error_signal_emitted(signal_name :String, args :Array, elapsed :String) -> String: + if args.is_empty(): + return "%s %s but is emitted after %s" % [ + _error("Expecting do not emit signal:"), _colored_value(signal_name + "()"), elapsed] + return "%s %s but is emitted after %s" % [ + _error("Expecting do not emit signal:"), _colored_value(signal_name + "(" + str(args) + ")"), elapsed] + + +static func error_await_signal_on_invalid_instance(source :Variant, signal_name :String, args :Array) -> String: + return "%s\n await_signal_on(%s, %s, %s)" % [ + _error("Invalid source! Can't await on signal:"), _colored_value(source), signal_name, args] + + +static func result_type(type :int) -> String: + match type: + GdUnitResult.SUCCESS: return "SUCCESS" + GdUnitResult.WARN: return "WARNING" + GdUnitResult.ERROR: return "ERROR" + GdUnitResult.EMPTY: return "EMPTY" + return "UNKNOWN" + + +static func result_message(result :GdUnitResult) -> String: + match result._state: + GdUnitResult.SUCCESS: return "" + GdUnitResult.WARN: return result.warn_message() + GdUnitResult.ERROR: return result.error_message() + GdUnitResult.EMPTY: return "" + return "UNKNOWN" +# ----------------------------------------------------------------------------------- + +# - Spy|Mock specific errors ---------------------------------------------------- +static func error_no_more_interactions(summary :Dictionary) -> String: + var interactions := PackedStringArray() + for args :Array in summary.keys(): + var times :int = summary[args] + @warning_ignore("return_value_discarded") + interactions.append(_format_arguments(args, times)) + return "%s\n%s\n%s" % [_error("Expecting no more interactions!"), _error("But found interactions on:"), "\n".join(interactions)] + + +static func error_validate_interactions(current_interactions: Dictionary, expected_interactions: Dictionary) -> String: + var collected_interactions := PackedStringArray() + for args: Array in current_interactions.keys(): + var times: int = current_interactions[args] + @warning_ignore("return_value_discarded") + collected_interactions.append(_format_arguments(args, times)) + + var arguments: Array = expected_interactions.keys()[0] + var interactions: int = expected_interactions.values()[0] + var expected_interaction := _format_arguments(arguments, interactions) + return "%s\n%s\n%s\n%s" % [ + _error("Expecting interaction on:"), expected_interaction, _error("But found interactions on:"), "\n".join(collected_interactions)] + + +static func _format_arguments(args :Array, times :int) -> String: + var fname :String = args[0] + var fargs := args.slice(1) as Array + var typed_args := _to_typed_args(fargs) + var fsignature := _colored_value("%s(%s)" % [fname, ", ".join(typed_args)]) + return " %s %d time's" % [fsignature, times] + + +static func _to_typed_args(args :Array) -> PackedStringArray: + var typed := PackedStringArray() + for arg :Variant in args: + @warning_ignore("return_value_discarded") + typed.append(_format_arg(arg) + " :" + GdObjects.type_as_string(typeof(arg))) + return typed + + +static func _format_arg(arg :Variant) -> String: + if arg is InputEvent: + var ie: InputEvent = arg + return input_event_as_text(ie) + return str(arg) + + +static func _find_first_diff(left :Array, right :Array) -> String: + for index in left.size(): + var l :Variant = left[index] + var r :Variant = "" if index >= right.size() else right[index] + if not GdObjects.equals(l, r): + return "at position %s\n '%s' vs '%s'" % [_colored_value(index), _typed_value(l), _typed_value(r)] + return "" + + +static func error_has_size(current :Variant, expected: int) -> String: + @warning_ignore("unsafe_method_access") + var current_size :Variant = null if current == null else current.size() + return "%s\n %s\n but was\n %s" % [_error("Expecting size:"), _colored_value(expected), _colored_value(current_size)] + + +static func error_contains_exactly(current: Array, expected: Array) -> String: + return "%s\n %s\n but was\n %s" % [_error("Expecting exactly equal:"), _colored_value(expected), _colored_value(current)] + + +static func format_chars(characters: PackedInt32Array, type: Color) -> PackedInt32Array: + if characters.size() == 0:# or characters[0] == 10: + return characters + + # Replace each control character with its readable form + var formatted_text := characters.to_byte_array().get_string_from_utf32() + for control_char: String in CONTROL_CHARS: + var replace_text: String = CONTROL_CHARS[control_char] + formatted_text = formatted_text.replace(control_char, replace_text) + + # Handle special ASCII control characters (0x00-0x1F, 0x7F) + var ascii_text := "" + for i in formatted_text.length(): + var character := formatted_text[i] + var code := character.unicode_at(0) + if code < 0x20 and not CONTROL_CHARS.has(character): # Control characters not handled above + ascii_text += "<0x%02X>" % code + elif code == 0x7F: # DEL character + ascii_text += "" + else: + ascii_text += character + + var message := "[bgcolor=#%s][color=white]%s[/color][/bgcolor]" % [ + type.to_html(), + ascii_text + ] + + var result := PackedInt32Array() + result.append_array(message.to_utf32_buffer().to_int32_array()) + return result + + +static func format_invalid(value :String) -> String: + return "[bgcolor=#%s][color=with]%s[/color][/bgcolor]" % [SUB_COLOR.to_html(), value] + + +static func humanized(value :String) -> String: + return value.replace("_", " ") + + +static func build_failure_message(failure :String, additional_failure_message: String, custom_failure_message: String) -> String: + var message := failure if custom_failure_message.is_empty() else custom_failure_message + if additional_failure_message.is_empty(): + return message + return """ + %s + [color=LIME_GREEN][b]Additional info:[/b][/color] + %s""".dedent().trim_prefix("\n") % [message, additional_failure_message] + + +static func is_empty(value: Variant) -> bool: + var arry_value: Array = value + return arry_value != null and arry_value.is_empty() diff --git a/addons/gdUnit4/src/asserts/GdAssertMessages.gd.uid b/addons/gdUnit4/src/asserts/GdAssertMessages.gd.uid new file mode 100644 index 0000000..417dbfd --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdAssertMessages.gd.uid @@ -0,0 +1 @@ +uid://vy15s8xjek4s diff --git a/addons/gdUnit4/src/asserts/GdAssertReports.gd b/addons/gdUnit4/src/asserts/GdAssertReports.gd new file mode 100644 index 0000000..06b72ed --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdAssertReports.gd @@ -0,0 +1,54 @@ +class_name GdAssertReports +extends RefCounted + +const LAST_ERROR = "last_assert_error_message" +const LAST_ERROR_LINE = "last_assert_error_line" + + +static func report_success() -> void: + GdUnitSignals.instance().gdunit_set_test_failed.emit(false) + GdAssertReports.set_last_error_line_number(-1) + Engine.remove_meta(LAST_ERROR) + + +static func report_warning(message :String, line_number :int) -> void: + GdUnitSignals.instance().gdunit_set_test_failed.emit(false) + send_report(GdUnitReport.new().create(GdUnitReport.WARN, line_number, message)) + + +static func report_error(message:String, line_number :int) -> void: + GdUnitSignals.instance().gdunit_set_test_failed.emit(true) + GdAssertReports.set_last_error_line_number(line_number) + Engine.set_meta(LAST_ERROR, message) + # if we expect to fail we handle as success test + if _do_expect_assert_failing(): + return + send_report(GdUnitReport.new().create(GdUnitReport.FAILURE, line_number, message)) + + +static func reset_last_error_line_number() -> void: + Engine.remove_meta(LAST_ERROR_LINE) + + +static func set_last_error_line_number(line_number :int) -> void: + Engine.set_meta(LAST_ERROR_LINE, line_number) + + +static func get_last_error_line_number() -> int: + if Engine.has_meta(LAST_ERROR_LINE): + return Engine.get_meta(LAST_ERROR_LINE) + return -1 + + +static func _do_expect_assert_failing() -> bool: + if Engine.has_meta(GdUnitConstants.EXPECT_ASSERT_REPORT_FAILURES): + return Engine.get_meta(GdUnitConstants.EXPECT_ASSERT_REPORT_FAILURES) + return false + + +static func current_failure() -> String: + return Engine.get_meta(LAST_ERROR) + + +static func send_report(report :GdUnitReport) -> void: + GdUnitThreadManager.get_current_context().get_execution_context().add_report(report) diff --git a/addons/gdUnit4/src/asserts/GdAssertReports.gd.uid b/addons/gdUnit4/src/asserts/GdAssertReports.gd.uid new file mode 100644 index 0000000..08ca207 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdAssertReports.gd.uid @@ -0,0 +1 @@ +uid://6vkjauii7gha diff --git a/addons/gdUnit4/src/asserts/GdUnitArrayAssertImpl.gd b/addons/gdUnit4/src/asserts/GdUnitArrayAssertImpl.gd new file mode 100644 index 0000000..9643cfa --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitArrayAssertImpl.gd @@ -0,0 +1,433 @@ +class_name GdUnitArrayAssertImpl +extends GdUnitArrayAssert + + +var _base: GdUnitAssertImpl +var _current_value_provider: ValueProvider +var _type_check: bool + + +func _init(current: Variant, type_check := true) -> void: + _type_check = type_check + _current_value_provider = DefaultValueProvider.new(current) + _base = GdUnitAssertImpl.new(current) + # save the actual assert instance on the current thread context + GdUnitThreadManager.get_current_context().set_assert(self) + if not _validate_value_type(current): + @warning_ignore("return_value_discarded") + report_error("GdUnitArrayAssert inital error, unexpected type <%s>" % GdObjects.typeof_as_string(current)) + + +func _notification(event: int) -> void: + if event == NOTIFICATION_PREDELETE: + if _base != null: + _base.notification(event) + _base = null + + +func report_success() -> GdUnitArrayAssert: + @warning_ignore("return_value_discarded") + _base.report_success() + return self + + +func report_error(error: String) -> GdUnitArrayAssert: + @warning_ignore("return_value_discarded") + _base.report_error(error) + return self + + +func failure_message() -> String: + return _base.failure_message() + + +func override_failure_message(message: String) -> GdUnitArrayAssert: + @warning_ignore("return_value_discarded") + _base.override_failure_message(message) + return self + + +func append_failure_message(message: String) -> GdUnitArrayAssert: + @warning_ignore("return_value_discarded") + _base.append_failure_message(message) + return self + + +func _validate_value_type(value: Variant) -> bool: + return value == null or GdArrayTools.is_array_type(value) + + +func get_current_value() -> Variant: + return _current_value_provider.get_value() + + +func max_length(left: Variant, right: Variant) -> int: + var ls := str(left).length() + var rs := str(right).length() + return rs if ls < rs else ls + + +# gdlint: disable=function-name +func _toPackedStringArray(value: Variant) -> PackedStringArray: + if GdArrayTools.is_array_type(value): + @warning_ignore("unsafe_cast") + return PackedStringArray(value as Array) + return PackedStringArray([str(value)]) + + +func _array_equals_div(current: Variant, expected: Variant, case_sensitive: bool = false) -> Array[Array]: + var current_value := _toPackedStringArray(current) + var expected_value := _toPackedStringArray(expected) + var index_report := Array() + for index in current_value.size(): + var c := current_value[index] + if index < expected_value.size(): + var e := expected_value[index] + if not GdObjects.equals(c, e, case_sensitive): + var length := max_length(c, e) + current_value[index] = GdAssertMessages.format_invalid(c.lpad(length)) + expected_value[index] = e.lpad(length) + index_report.push_back({"index": index, "current": c, "expected": e}) + else: + current_value[index] = GdAssertMessages.format_invalid(c) + index_report.push_back({"index": index, "current": c, "expected": ""}) + + for index in range(current_value.size(), expected_value.size()): + var value := expected_value[index] + expected_value[index] = GdAssertMessages.format_invalid(value) + index_report.push_back({"index": index, "current": "", "expected": value}) + return [current_value, expected_value, index_report] + + +func _array_div(compare_mode: GdObjects.COMPARE_MODE, left: Array[Variant], right: Array[Variant], _same_order := false) -> Array[Variant]: + var not_expect := left.duplicate(true) + var not_found := right.duplicate(true) + for index_c in left.size(): + var c: Variant = left[index_c] + for index_e in right.size(): + var e: Variant = right[index_e] + if GdObjects.equals(c, e, false, compare_mode): + GdArrayTools.erase_value(not_expect, e) + GdArrayTools.erase_value(not_found, c) + break + return [not_expect, not_found] + + +func _contains(expected: Array, compare_mode: GdObjects.COMPARE_MODE) -> GdUnitArrayAssert: + var by_reference := compare_mode == GdObjects.COMPARE_MODE.OBJECT_REFERENCE + var current_value: Variant = get_current_value() + var expected_value: Variant = _extract_variadic_value(expected) + if not _validate_value_type(expected_value): + return report_error("ERROR: expected value: <%s>\n is not a Array Type!" % GdObjects.typeof_as_string(expected_value)) + + if current_value == null: + return report_error(GdAssertMessages.error_arr_contains(current_value, expected_value, [], expected_value, by_reference)) + @warning_ignore("unsafe_cast") + var diffs := _array_div(compare_mode, current_value as Array[Variant], expected_value as Array[Variant]) + #var not_expect := diffs[0] as Array + var not_found: Array = diffs[1] + if not not_found.is_empty(): + return report_error(GdAssertMessages.error_arr_contains(current_value, expected_value, [], not_found, by_reference)) + return report_success() + + +func _contains_exactly(expected: Array, compare_mode: GdObjects.COMPARE_MODE) -> GdUnitArrayAssert: + var current_value: Variant = get_current_value() + var expected_value: Variant = _extract_variadic_value(expected) + if not _validate_value_type(expected_value): + return report_error("ERROR: expected value: <%s>\n is not a Array Type!" % GdObjects.typeof_as_string(expected_value)) + + if current_value == null: + return report_error(GdAssertMessages.error_arr_contains_exactly(null, expected_value, [], expected_value, compare_mode)) + # has same content in same order + if _is_equal(current_value, expected_value, false, compare_mode): + return report_success() + # check has same elements but in different order + if _is_equals_sorted(current_value, expected_value, false, compare_mode): + return report_error(GdAssertMessages.error_arr_contains_exactly(current_value, expected_value, [], [], compare_mode)) + # find the difference + @warning_ignore("unsafe_cast") + var diffs := _array_div(compare_mode, + current_value as Array[Variant], + expected_value as Array[Variant], + GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST) + var not_expect: Array[Variant] = diffs[0] + var not_found: Array[Variant] = diffs[1] + return report_error(GdAssertMessages.error_arr_contains_exactly(current_value, expected_value, not_expect, not_found, compare_mode)) + + +func _contains_exactly_in_any_order(expected: Array, compare_mode: GdObjects.COMPARE_MODE) -> GdUnitArrayAssert: + var current_value: Variant = get_current_value() + var expected_value: Variant = _extract_variadic_value(expected) + if not _validate_value_type(expected_value): + return report_error("ERROR: expected value: <%s>\n is not a Array Type!" % GdObjects.typeof_as_string(expected_value)) + + if current_value == null: + return report_error(GdAssertMessages.error_arr_contains_exactly_in_any_order(current_value, expected_value, [], expected_value, compare_mode)) + # find the difference + @warning_ignore("unsafe_cast") + var diffs := _array_div(compare_mode, current_value as Array[Variant], expected_value as Array[Variant], false) + var not_expect: Array[Variant] = diffs[0] + var not_found: Array[Variant] = diffs[1] + if not_expect.is_empty() and not_found.is_empty(): + return report_success() + return report_error(GdAssertMessages.error_arr_contains_exactly_in_any_order(current_value, expected_value, not_expect, not_found, compare_mode)) + + +func _not_contains(expected: Array, compare_mode: GdObjects.COMPARE_MODE) -> GdUnitArrayAssert: + var current_value: Variant = get_current_value() + var expected_value: Variant = _extract_variadic_value(expected) + if not _validate_value_type(expected_value): + return report_error("ERROR: expected value: <%s>\n is not a Array Type!" % GdObjects.typeof_as_string(expected_value)) + if current_value == null: + return report_error(GdAssertMessages.error_arr_contains_exactly_in_any_order(current_value, expected_value, [], expected_value, compare_mode)) + @warning_ignore("unsafe_cast") + var diffs := _array_div(compare_mode, current_value as Array[Variant], expected_value as Array[Variant]) + var found: Array[Variant] = diffs[0] + @warning_ignore("unsafe_cast") + if found.size() == (current_value as Array).size(): + return report_success() + @warning_ignore("unsafe_cast") + var diffs2 := _array_div(compare_mode, expected_value as Array[Variant], diffs[1] as Array[Variant]) + return report_error(GdAssertMessages.error_arr_not_contains(current_value, expected_value, diffs2[0], compare_mode)) + + +func is_null() -> GdUnitArrayAssert: + @warning_ignore("return_value_discarded") + _base.is_null() + return self + + +func is_not_null() -> GdUnitArrayAssert: + @warning_ignore("return_value_discarded") + _base.is_not_null() + return self + + +func is_equal(...expected: Array) -> GdUnitArrayAssert: + var current_value: Variant = get_current_value() + var expected_value: Variant= _extract_variadic_value(expected) + if not _validate_value_type(expected_value): + return report_error("ERROR: expected value: <%s>\n is not a Array Type!" % GdObjects.typeof_as_string(expected_value)) + if current_value == null and expected_value != null: + return report_error(GdAssertMessages.error_equal(null, expected_value)) + + if not _is_equal(current_value, expected_value): + var diff := _array_equals_div(current_value, expected_value) + var expected_as_list := GdArrayTools.as_string(diff[0], false) + var current_as_list := GdArrayTools.as_string(diff[1], false) + var index_report: Array = diff[2] + return report_error(GdAssertMessages.error_equal(expected_as_list, current_as_list, index_report)) + return report_success() + + +# Verifies that the current Array is equal to the given one, ignoring case considerations. +func is_equal_ignoring_case(...expected: Array) -> GdUnitArrayAssert: + var current_value: Variant = get_current_value() + var expected_value: Variant = _extract_variadic_value(expected) + if not _validate_value_type(expected_value): + return report_error("ERROR: expected value: <%s>\n is not a Array Type!" % GdObjects.typeof_as_string(expected_value)) + if current_value == null and expected_value != null: + @warning_ignore("unsafe_cast") + return report_error(GdAssertMessages.error_equal(null, GdArrayTools.as_string(expected_value))) + + if not _is_equal(current_value, expected_value, true): + @warning_ignore("unsafe_cast") + var diff := _array_equals_div(current_value, expected_value, true) + var expected_as_list := GdArrayTools.as_string(diff[0]) + var current_as_list := GdArrayTools.as_string(diff[1]) + var index_report: Array = diff[2] + return report_error(GdAssertMessages.error_equal(expected_as_list, current_as_list, index_report)) + return report_success() + + +func is_not_equal(...expected: Array) -> GdUnitArrayAssert: + var current_value: Variant = get_current_value() + var expected_value: Variant = _extract_variadic_value(expected) + if not _validate_value_type(expected_value): + return report_error("ERROR: expected value: <%s>\n is not a Array Type!" % GdObjects.typeof_as_string(expected_value)) + + if _is_equal(current_value, expected_value): + return report_error(GdAssertMessages.error_not_equal(current_value, expected_value)) + return report_success() + + +func is_not_equal_ignoring_case(...expected: Array) -> GdUnitArrayAssert: + var current_value: Variant = get_current_value() + var expected_value: Variant = _extract_variadic_value(expected) + if not _validate_value_type(expected_value): + return report_error("ERROR: expected value: <%s>\n is not a Array Type!" % GdObjects.typeof_as_string(expected_value)) + + if _is_equal(current_value, expected_value, true): + @warning_ignore("unsafe_cast") + var c := GdArrayTools.as_string(current_value as Array) + @warning_ignore("unsafe_cast") + var e := GdArrayTools.as_string(expected_value) + return report_error(GdAssertMessages.error_not_equal_case_insensetiv(c, e)) + return report_success() + + +func is_empty() -> GdUnitArrayAssert: + var current_value: Variant = get_current_value() + @warning_ignore("unsafe_cast") + if current_value == null or (current_value as Array).size() > 0: + return report_error(GdAssertMessages.error_is_empty(current_value)) + return report_success() + + +func is_not_empty() -> GdUnitArrayAssert: + var current_value: Variant = get_current_value() + @warning_ignore("unsafe_cast") + if current_value != null and (current_value as Array).size() == 0: + return report_error(GdAssertMessages.error_is_not_empty()) + return report_success() + + +@warning_ignore("unused_parameter", "shadowed_global_identifier") +func is_same(expected: Variant) -> GdUnitArrayAssert: + if not _validate_value_type(expected): + return report_error("ERROR: expected value: <%s>\n is not a Array Type!" % GdObjects.typeof_as_string(expected)) + var current: Variant = get_current_value() + if not is_same(current, expected): + @warning_ignore("return_value_discarded") + report_error(GdAssertMessages.error_is_same(current, expected)) + return self + + +func is_not_same(expected: Variant) -> GdUnitArrayAssert: + if not _validate_value_type(expected): + return report_error("ERROR: expected value: <%s>\n is not a Array Type!" % GdObjects.typeof_as_string(expected)) + var current: Variant = get_current_value() + if is_same(current, expected): + @warning_ignore("return_value_discarded") + report_error(GdAssertMessages.error_not_same(current, expected)) + return self + + +func has_size(expected: int) -> GdUnitArrayAssert: + var current_value: Variant = get_current_value() + @warning_ignore("unsafe_cast") + if current_value == null or (current_value as Array).size() != expected: + return report_error(GdAssertMessages.error_has_size(current_value, expected)) + return report_success() + + +func contains(...expected: Array) -> GdUnitArrayAssert: + return _contains(expected, GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST) + + +func contains_exactly(...expected: Array) -> GdUnitArrayAssert: + return _contains_exactly(expected, GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST) + + +func contains_exactly_in_any_order(...expected: Array) -> GdUnitArrayAssert: + return _contains_exactly_in_any_order(expected, GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST) + + +func contains_same(...expected: Array) -> GdUnitArrayAssert: + return _contains(expected, GdObjects.COMPARE_MODE.OBJECT_REFERENCE) + + +func contains_same_exactly(...expected: Array) -> GdUnitArrayAssert: + return _contains_exactly(expected, GdObjects.COMPARE_MODE.OBJECT_REFERENCE) + + +func contains_same_exactly_in_any_order(...expected: Array) -> GdUnitArrayAssert: + return _contains_exactly_in_any_order(expected, GdObjects.COMPARE_MODE.OBJECT_REFERENCE) + + +func not_contains(...expected: Array) -> GdUnitArrayAssert: + return _not_contains(expected, GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST) + + +func not_contains_same(...expected: Array) -> GdUnitArrayAssert: + return _not_contains(expected, GdObjects.COMPARE_MODE.OBJECT_REFERENCE) + + +func is_instanceof(expected: Variant) -> GdUnitAssert: + @warning_ignore("unsafe_method_access") + _base.is_instanceof(expected) + return self + + +func extract(func_name: String, ...func_args: Array) -> GdUnitArrayAssert: + var extracted_elements := Array() + var args: Array = _extract_variadic_value(func_args) + var extractor := GdUnitFuncValueExtractor.new(func_name, args) + var current: Variant = get_current_value() + if current == null: + _current_value_provider = DefaultValueProvider.new(null) + else: + for element: Variant in current: + extracted_elements.append(extractor.extract_value(element)) + _current_value_provider = DefaultValueProvider.new(extracted_elements) + return self + + +func extractv(...extractors: Array) -> GdUnitArrayAssert: + var extracted_elements := Array() + var current: Variant = get_current_value() + if current == null: + _current_value_provider = DefaultValueProvider.new(null) + else: + for element: Variant in current: + var ev: Array[Variant] = [ + GdUnitTuple.NO_ARG, + GdUnitTuple.NO_ARG, + GdUnitTuple.NO_ARG, + GdUnitTuple.NO_ARG, + GdUnitTuple.NO_ARG, + GdUnitTuple.NO_ARG, + GdUnitTuple.NO_ARG, + GdUnitTuple.NO_ARG, + GdUnitTuple.NO_ARG, + GdUnitTuple.NO_ARG + ] + + for index: int in extractors.size(): + var extractor: GdUnitValueExtractor = extractors[index] + ev[index] = extractor.extract_value(element) + if extractors.size() > 1: + extracted_elements.append(GdUnitTuple.new(ev[0], ev[1], ev[2], ev[3], ev[4], ev[5], ev[6], ev[7], ev[8], ev[9])) + else: + extracted_elements.append(ev[0]) + _current_value_provider = DefaultValueProvider.new(extracted_elements) + return self + + +## Small helper to support the old expected arguments as single array and variadic arguments +func _extract_variadic_value(values: Variant) -> Variant: + @warning_ignore("unsafe_method_access") + if values != null and values.size() == 1 and GdArrayTools.is_array_type(values[0]): + return values[0] + return values + + +@warning_ignore("incompatible_ternary") +func _is_equal( + left: Variant, + right: Variant, + case_sensitive := false, + compare_mode := GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST) -> bool: + + @warning_ignore("unsafe_cast") + return GdObjects.equals( + (left as Array) if GdArrayTools.is_array_type(left) else left, + (right as Array) if GdArrayTools.is_array_type(right) else right, + case_sensitive, + compare_mode + ) + + +func _is_equals_sorted( + left: Variant, + right: Variant, + case_sensitive := false, + compare_mode := GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST) -> bool: + + @warning_ignore("unsafe_cast") + return GdObjects.equals_sorted( + left as Array, + right as Array, + case_sensitive, + compare_mode) diff --git a/addons/gdUnit4/src/asserts/GdUnitArrayAssertImpl.gd.uid b/addons/gdUnit4/src/asserts/GdUnitArrayAssertImpl.gd.uid new file mode 100644 index 0000000..fedb207 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitArrayAssertImpl.gd.uid @@ -0,0 +1 @@ +uid://ltwqaslcmub0 diff --git a/addons/gdUnit4/src/asserts/GdUnitAssertImpl.gd b/addons/gdUnit4/src/asserts/GdUnitAssertImpl.gd new file mode 100644 index 0000000..9f578c4 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitAssertImpl.gd @@ -0,0 +1,80 @@ +class_name GdUnitAssertImpl +extends GdUnitAssert + + +var _current :Variant +var _current_failure_message :String = "" +var _custom_failure_message :String = "" +var _additional_failure_message: String = "" + + +func _init(current :Variant) -> void: + _current = current + # save the actual assert instance on the current thread context + GdUnitThreadManager.get_current_context().set_assert(self) + GdAssertReports.reset_last_error_line_number() + + + +func failure_message() -> String: + return _current_failure_message + + +func current_value() -> Variant: + return _current + + +func report_success() -> GdUnitAssert: + GdAssertReports.report_success() + return self + + +func report_error(failure :String, failure_line_number: int = -1) -> GdUnitAssert: + var line_number := failure_line_number if failure_line_number != -1 else GdUnitAssertions.get_line_number() + GdAssertReports.set_last_error_line_number(line_number) + _current_failure_message = GdAssertMessages.build_failure_message(failure, _additional_failure_message, _custom_failure_message) + GdAssertReports.report_error(_current_failure_message, line_number) + Engine.set_meta("GD_TEST_FAILURE", true) + return self + + +func do_fail() -> GdUnitAssert: + return report_error(GdAssertMessages.error_not_implemented()) + + +func override_failure_message(message: String) -> GdUnitAssert: + _custom_failure_message = message + return self + + +func append_failure_message(message: String) -> GdUnitAssert: + _additional_failure_message = message + return self + + +func is_null() -> GdUnitAssert: + var current :Variant = current_value() + if current != null: + return report_error(GdAssertMessages.error_is_null(current)) + return report_success() + + +func is_not_null() -> GdUnitAssert: + var current :Variant = current_value() + if current == null: + return report_error(GdAssertMessages.error_is_not_null()) + return report_success() + + +func is_equal(expected: Variant) -> GdUnitAssert: + var current: Variant = current_value() + if not GdObjects.equals(current, expected): + return report_error(GdAssertMessages.error_equal(current, expected)) + return report_success() + + +func is_not_equal(expected: Variant) -> GdUnitAssert: + var current: Variant = current_value() + if GdObjects.equals(current, expected): + return report_error(GdAssertMessages.error_not_equal(current, expected)) + return report_success() diff --git a/addons/gdUnit4/src/asserts/GdUnitAssertImpl.gd.uid b/addons/gdUnit4/src/asserts/GdUnitAssertImpl.gd.uid new file mode 100644 index 0000000..7651f2e --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitAssertImpl.gd.uid @@ -0,0 +1 @@ +uid://bs5xosk58gxia diff --git a/addons/gdUnit4/src/asserts/GdUnitAssertions.gd b/addons/gdUnit4/src/asserts/GdUnitAssertions.gd new file mode 100644 index 0000000..a5b53c1 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitAssertions.gd @@ -0,0 +1,68 @@ +# Preloads all GdUnit assertions +class_name GdUnitAssertions +extends RefCounted + + +@warning_ignore("return_value_discarded") +func _init() -> void: + # preload all gdunit assertions to speedup testsuite loading time + # gdlint:disable=private-method-call + @warning_ignore_start("return_value_discarded") + GdUnitAssertions.__lazy_load("res://addons/gdUnit4/src/asserts/GdUnitAssertImpl.gd") + GdUnitAssertions.__lazy_load("res://addons/gdUnit4/src/asserts/GdUnitBoolAssertImpl.gd") + GdUnitAssertions.__lazy_load("res://addons/gdUnit4/src/asserts/GdUnitStringAssertImpl.gd") + GdUnitAssertions.__lazy_load("res://addons/gdUnit4/src/asserts/GdUnitIntAssertImpl.gd") + GdUnitAssertions.__lazy_load("res://addons/gdUnit4/src/asserts/GdUnitFloatAssertImpl.gd") + GdUnitAssertions.__lazy_load("res://addons/gdUnit4/src/asserts/GdUnitVectorAssertImpl.gd") + GdUnitAssertions.__lazy_load("res://addons/gdUnit4/src/asserts/GdUnitArrayAssertImpl.gd") + GdUnitAssertions.__lazy_load("res://addons/gdUnit4/src/asserts/GdUnitDictionaryAssertImpl.gd") + GdUnitAssertions.__lazy_load("res://addons/gdUnit4/src/asserts/GdUnitFileAssertImpl.gd") + GdUnitAssertions.__lazy_load("res://addons/gdUnit4/src/asserts/GdUnitObjectAssertImpl.gd") + GdUnitAssertions.__lazy_load("res://addons/gdUnit4/src/asserts/GdUnitResultAssertImpl.gd") + GdUnitAssertions.__lazy_load("res://addons/gdUnit4/src/asserts/GdUnitFuncAssertImpl.gd") + GdUnitAssertions.__lazy_load("res://addons/gdUnit4/src/asserts/GdUnitSignalAssertImpl.gd") + GdUnitAssertions.__lazy_load("res://addons/gdUnit4/src/asserts/GdUnitFailureAssertImpl.gd") + GdUnitAssertions.__lazy_load("res://addons/gdUnit4/src/asserts/GdUnitGodotErrorAssertImpl.gd") + @warning_ignore_restore("return_value_discarded") + + +### We now load all used asserts and tool scripts into the cache according to the principle of "lazy loading" +### in order to noticeably reduce the loading time of the test suite. +# We go this hard way to increase the loading performance to avoid reparsing all the used scripts +# for more detailed info -> https://github.com/godotengine/godot/issues/67400 +# gdlint:disable=function-name +static func __lazy_load(script_path :String) -> GDScript: + return ResourceLoader.load(script_path, "GDScript", ResourceLoader.CACHE_MODE_REUSE) + + +static func validate_value_type(value :Variant, type :Variant.Type) -> bool: + return value == null or typeof(value) == type + + +# Scans the current stack trace for the root cause to extract the line number +static func get_line_number() -> int: + var stack_trace := get_stack() + if stack_trace == null or stack_trace.is_empty(): + return -1 + for index in stack_trace.size(): + var stack_info :Dictionary = stack_trace[index] + var function :String = stack_info.get("function") + # we catch helper asserts to skip over to return the correct line number + if function.begins_with("assert_"): + continue + if function.begins_with("test_"): + return stack_info.get("line") + var source :String = stack_info.get("source") + if source.is_empty() \ + or source.begins_with("user://") \ + or source.ends_with("GdUnitAssert.gd") \ + or source.ends_with("GdUnitAssertions.gd") \ + or source.ends_with("AssertImpl.gd") \ + or source.ends_with("GdUnitTestSuite.gd") \ + or source.ends_with("GdUnitSceneRunnerImpl.gd") \ + or source.ends_with("GdUnitObjectInteractions.gd") \ + or source.ends_with("GdUnitObjectInteractionsVerifier.gd") \ + or source.ends_with("GdUnitAwaiter.gd"): + continue + return stack_info.get("line") + return -1 diff --git a/addons/gdUnit4/src/asserts/GdUnitAssertions.gd.uid b/addons/gdUnit4/src/asserts/GdUnitAssertions.gd.uid new file mode 100644 index 0000000..fb3ccbf --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitAssertions.gd.uid @@ -0,0 +1 @@ +uid://cs8lnu7bwdr3x diff --git a/addons/gdUnit4/src/asserts/GdUnitBoolAssertImpl.gd b/addons/gdUnit4/src/asserts/GdUnitBoolAssertImpl.gd new file mode 100644 index 0000000..2fc0ce4 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitBoolAssertImpl.gd @@ -0,0 +1,87 @@ +extends GdUnitBoolAssert + +var _base: GdUnitAssertImpl + + +func _init(current :Variant) -> void: + _base = GdUnitAssertImpl.new(current) + # save the actual assert instance on the current thread context + GdUnitThreadManager.get_current_context().set_assert(self) + if not GdUnitAssertions.validate_value_type(current, TYPE_BOOL): + @warning_ignore("return_value_discarded") + report_error("GdUnitBoolAssert inital error, unexpected type <%s>" % GdObjects.typeof_as_string(current)) + + +func _notification(event :int) -> void: + if event == NOTIFICATION_PREDELETE: + if _base != null: + _base.notification(event) + _base = null + + +func current_value() -> Variant: + return _base.current_value() + + +func report_success() -> GdUnitBoolAssert: + @warning_ignore("return_value_discarded") + _base.report_success() + return self + + +func report_error(error :String) -> GdUnitBoolAssert: + @warning_ignore("return_value_discarded") + _base.report_error(error) + return self + + +func failure_message() -> String: + return _base.failure_message() + + +func override_failure_message(message: String) -> GdUnitBoolAssert: + @warning_ignore("return_value_discarded") + _base.override_failure_message(message) + return self + + +func append_failure_message(message: String) -> GdUnitBoolAssert: + @warning_ignore("return_value_discarded") + _base.append_failure_message(message) + return self + + +func is_null() -> GdUnitBoolAssert: + @warning_ignore("return_value_discarded") + _base.is_null() + return self + + +func is_not_null() -> GdUnitBoolAssert: + @warning_ignore("return_value_discarded") + _base.is_not_null() + return self + + +func is_equal(expected: Variant) -> GdUnitBoolAssert: + @warning_ignore("return_value_discarded") + _base.is_equal(expected) + return self + + +func is_not_equal(expected: Variant) -> GdUnitBoolAssert: + @warning_ignore("return_value_discarded") + _base.is_not_equal(expected) + return self + + +func is_true() -> GdUnitBoolAssert: + if current_value() != true: + return report_error(GdAssertMessages.error_is_true(current_value())) + return report_success() + + +func is_false() -> GdUnitBoolAssert: + if current_value() == true || current_value() == null: + return report_error(GdAssertMessages.error_is_false(current_value())) + return report_success() diff --git a/addons/gdUnit4/src/asserts/GdUnitBoolAssertImpl.gd.uid b/addons/gdUnit4/src/asserts/GdUnitBoolAssertImpl.gd.uid new file mode 100644 index 0000000..82e2de7 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitBoolAssertImpl.gd.uid @@ -0,0 +1 @@ +uid://ul5ajqk7fu8g diff --git a/addons/gdUnit4/src/asserts/GdUnitDictionaryAssertImpl.gd b/addons/gdUnit4/src/asserts/GdUnitDictionaryAssertImpl.gd new file mode 100644 index 0000000..6d62dcf --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitDictionaryAssertImpl.gd @@ -0,0 +1,206 @@ +extends GdUnitDictionaryAssert + +var _base: GdUnitAssertImpl + + +func _init(current :Variant) -> void: + _base = GdUnitAssertImpl.new(current) + # save the actual assert instance on the current thread context + GdUnitThreadManager.get_current_context().set_assert(self) + if not GdUnitAssertions.validate_value_type(current, TYPE_DICTIONARY): + @warning_ignore("return_value_discarded") + report_error("GdUnitDictionaryAssert inital error, unexpected type <%s>" % GdObjects.typeof_as_string(current)) + + +func _notification(event :int) -> void: + if event == NOTIFICATION_PREDELETE: + if _base != null: + _base.notification(event) + _base = null + + +func report_success() -> GdUnitDictionaryAssert: + @warning_ignore("return_value_discarded") + _base.report_success() + return self + + +func report_error(error :String) -> GdUnitDictionaryAssert: + @warning_ignore("return_value_discarded") + _base.report_error(error) + return self + + +func failure_message() -> String: + return _base.failure_message() + + +func override_failure_message(message: String) -> GdUnitDictionaryAssert: + @warning_ignore("return_value_discarded") + _base.override_failure_message(message) + return self + + +func append_failure_message(message: String) -> GdUnitDictionaryAssert: + @warning_ignore("return_value_discarded") + _base.append_failure_message(message) + return self + + +func current_value() -> Variant: + return _base.current_value() + + +func is_null() -> GdUnitDictionaryAssert: + @warning_ignore("return_value_discarded") + _base.is_null() + return self + + +func is_not_null() -> GdUnitDictionaryAssert: + @warning_ignore("return_value_discarded") + _base.is_not_null() + return self + + +func is_equal(expected: Variant) -> GdUnitDictionaryAssert: + var current :Variant = current_value() + if current == null: + return report_error(GdAssertMessages.error_equal(null, GdAssertMessages.format_dict(expected))) + if not GdObjects.equals(current, expected): + var c := GdAssertMessages.format_dict(current) + var e := GdAssertMessages.format_dict(expected) + return report_error(GdAssertMessages.error_equal(c, e)) + return report_success() + + +func is_not_equal(expected: Variant) -> GdUnitDictionaryAssert: + var current: Variant = current_value() + if GdObjects.equals(current, expected): + return report_error(GdAssertMessages.error_not_equal(current, expected)) + return report_success() + + +@warning_ignore("unused_parameter", "shadowed_global_identifier") +func is_same(expected :Variant) -> GdUnitDictionaryAssert: + var current :Variant = current_value() + if current == null: + return report_error(GdAssertMessages.error_equal(null, GdAssertMessages.format_dict(expected))) + if not is_same(current, expected): + var c := GdAssertMessages.format_dict(current) + var e := GdAssertMessages.format_dict(expected) + return report_error(GdAssertMessages.error_is_same(c, e)) + return report_success() + + +@warning_ignore("unused_parameter", "shadowed_global_identifier") +func is_not_same(expected :Variant) -> GdUnitDictionaryAssert: + var current :Variant = current_value() + if is_same(current, expected): + return report_error(GdAssertMessages.error_not_same(current, expected)) + return report_success() + + +func is_empty() -> GdUnitDictionaryAssert: + var current :Variant = current_value() + @warning_ignore("unsafe_cast") + if current == null or not (current as Dictionary).is_empty(): + return report_error(GdAssertMessages.error_is_empty(current)) + return report_success() + + +func is_not_empty() -> GdUnitDictionaryAssert: + var current :Variant = current_value() + @warning_ignore("unsafe_cast") + if current == null or (current as Dictionary).is_empty(): + return report_error(GdAssertMessages.error_is_not_empty()) + return report_success() + + +func has_size(expected: int) -> GdUnitDictionaryAssert: + var current :Variant = current_value() + if current == null: + return report_error(GdAssertMessages.error_is_not_null()) + @warning_ignore("unsafe_cast") + if (current as Dictionary).size() != expected: + return report_error(GdAssertMessages.error_has_size(current, expected)) + return report_success() + + +func _contains_keys(expected: Array, compare_mode: GdObjects.COMPARE_MODE) -> GdUnitDictionaryAssert: + var current :Variant = current_value() + var expected_value: Array = _extract_variadic_value(expected) + if current == null: + return report_error(GdAssertMessages.error_is_not_null()) + # find expected keys + @warning_ignore("unsafe_cast") + var keys_not_found :Array = expected_value.filter(_filter_by_key.bind((current as Dictionary).keys(), compare_mode)) + if not keys_not_found.is_empty(): + @warning_ignore("unsafe_cast") + return report_error(GdAssertMessages.error_contains_keys((current as Dictionary).keys() as Array, expected_value, keys_not_found, compare_mode)) + return report_success() + + +func _contains_key_value(key :Variant, value :Variant, compare_mode :GdObjects.COMPARE_MODE) -> GdUnitDictionaryAssert: + var current :Variant = current_value() + var expected := [key] + if current == null: + return report_error(GdAssertMessages.error_is_not_null()) + var dict_current: Dictionary = current + var keys_not_found :Array = expected.filter(_filter_by_key.bind(dict_current.keys(), compare_mode)) + if not keys_not_found.is_empty(): + return report_error(GdAssertMessages.error_contains_keys(dict_current.keys() as Array, expected, keys_not_found, compare_mode)) + if not GdObjects.equals(dict_current[key], value, false, compare_mode): + return report_error(GdAssertMessages.error_contains_key_value(key, value, dict_current[key], compare_mode)) + return report_success() + + +func _not_contains_keys(expected: Array, compare_mode: GdObjects.COMPARE_MODE) -> GdUnitDictionaryAssert: + var current :Variant = current_value() + var expected_value: Array = _extract_variadic_value(expected) + if current == null: + return report_error(GdAssertMessages.error_is_not_null()) + var dict_current: Dictionary = current + var keys_found :Array = dict_current.keys().filter(_filter_by_key.bind(expected_value, compare_mode, true)) + if not keys_found.is_empty(): + return report_error(GdAssertMessages.error_not_contains_keys(dict_current.keys() as Array, expected_value, keys_found, compare_mode)) + return report_success() + + +func contains_keys(...expected: Array) -> GdUnitDictionaryAssert: + return _contains_keys(expected, GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST) + + +func contains_key_value(key :Variant, value :Variant) -> GdUnitDictionaryAssert: + return _contains_key_value(key, value, GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST) + + +func not_contains_keys(...expected: Array) -> GdUnitDictionaryAssert: + return _not_contains_keys(expected, GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST) + + +func contains_same_keys(expected :Array) -> GdUnitDictionaryAssert: + return _contains_keys(expected, GdObjects.COMPARE_MODE.OBJECT_REFERENCE) + + +func contains_same_key_value(key :Variant, value :Variant) -> GdUnitDictionaryAssert: + return _contains_key_value(key, value, GdObjects.COMPARE_MODE.OBJECT_REFERENCE) + + +func not_contains_same_keys(...expected: Array) -> GdUnitDictionaryAssert: + return _not_contains_keys(expected, GdObjects.COMPARE_MODE.OBJECT_REFERENCE) + + +func _filter_by_key(element :Variant, values :Array, compare_mode :GdObjects.COMPARE_MODE, is_not :bool = false) -> bool: + for key :Variant in values: + if GdObjects.equals(key, element, false, compare_mode): + return is_not + return !is_not + + +## Small helper to support the old expected arguments as single array and variadic arguments +func _extract_variadic_value(values: Variant) -> Variant: + @warning_ignore("unsafe_method_access") + if values != null and values.size() == 1 and GdArrayTools.is_array_type(values[0]): + return values[0] + return values diff --git a/addons/gdUnit4/src/asserts/GdUnitDictionaryAssertImpl.gd.uid b/addons/gdUnit4/src/asserts/GdUnitDictionaryAssertImpl.gd.uid new file mode 100644 index 0000000..0a65290 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitDictionaryAssertImpl.gd.uid @@ -0,0 +1 @@ +uid://b2xhkirk7f76x diff --git a/addons/gdUnit4/src/asserts/GdUnitFailureAssertImpl.gd b/addons/gdUnit4/src/asserts/GdUnitFailureAssertImpl.gd new file mode 100644 index 0000000..198624c --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitFailureAssertImpl.gd @@ -0,0 +1,136 @@ +extends GdUnitFailureAssert + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") + +var _is_failed := false +var _failure_message: String +var _current_failure_message := "" +var _custom_failure_message := "" +var _additional_failure_message := "" + + +func _set_do_expect_fail(enabled :bool = true) -> void: + Engine.set_meta(GdUnitConstants.EXPECT_ASSERT_REPORT_FAILURES, enabled) + + +func execute_and_await(assertion :Callable, do_await := true) -> GdUnitFailureAssert: + # do not report any failure from the original assertion we want to test + _set_do_expect_fail(true) + var thread_context := GdUnitThreadManager.get_current_context() + thread_context.set_assert(null) + @warning_ignore("return_value_discarded") + GdUnitSignals.instance().gdunit_set_test_failed.connect(_on_test_failed) + # execute the given assertion as callable + if do_await: + await assertion.call() + else: + assertion.call() + _set_do_expect_fail(false) + # get the assert instance from current tread context + var current_assert := thread_context.get_assert() + if not is_instance_of(current_assert, GdUnitAssert): + _is_failed = true + _failure_message = "Invalid Callable! It must be a callable of 'GdUnitAssert'" + return self + @warning_ignore("unsafe_method_access") + _failure_message = current_assert.failure_message() + return self + + +func execute(assertion :Callable) -> GdUnitFailureAssert: + @warning_ignore("return_value_discarded") + execute_and_await(assertion, false) + return self + + +func _on_test_failed(value :bool) -> void: + _is_failed = value + + +func is_equal(_expected: Variant) -> GdUnitFailureAssert: + return _report_error("Not implemented") + + +func is_not_equal(_expected: Variant) -> GdUnitFailureAssert: + return _report_error("Not implemented") + + +func is_null() -> GdUnitFailureAssert: + return _report_error("Not implemented") + + +func is_not_null() -> GdUnitFailureAssert: + return _report_error("Not implemented") + + +func override_failure_message(message: String) -> GdUnitFailureAssert: + _custom_failure_message = message + return self + + +func append_failure_message(message: String) -> GdUnitFailureAssert: + _additional_failure_message = message + return self + + +func is_success() -> GdUnitFailureAssert: + if _is_failed: + return _report_error("Expect: assertion ends successfully.") + return self + + +func is_failed() -> GdUnitFailureAssert: + if not _is_failed: + return _report_error("Expect: assertion fails.") + return self + + +func has_line(expected :int) -> GdUnitFailureAssert: + var current := GdAssertReports.get_last_error_line_number() + if current != expected: + return _report_error("Expect: to failed on line '%d'\n but was '%d'." % [expected, current]) + return self + + +func has_message(expected :String) -> GdUnitFailureAssert: + @warning_ignore("return_value_discarded") + is_failed() + var expected_error := GdUnitTools.normalize_text(GdUnitTools.richtext_normalize(expected)) + var current_error := GdUnitTools.normalize_text(GdUnitTools.richtext_normalize(_failure_message)) + if current_error != expected_error: + var diffs := GdDiffTool.string_diff(current_error, expected_error) + var current := GdAssertMessages.colored_array_div(diffs[1]) + return _report_error(GdAssertMessages.error_not_same_error(current, expected_error)) + return self + + +func contains_message(expected :String) -> GdUnitFailureAssert: + var expected_error := GdUnitTools.normalize_text(expected) + var current_error := GdUnitTools.normalize_text(GdUnitTools.richtext_normalize(_failure_message)) + if not current_error.contains(expected_error): + var diffs := GdDiffTool.string_diff(current_error, expected_error) + var current := GdAssertMessages.colored_array_div(diffs[1]) + return _report_error(GdAssertMessages.error_not_same_error(current, expected_error)) + return self + + +func starts_with_message(expected :String) -> GdUnitFailureAssert: + var expected_error := GdUnitTools.normalize_text(expected) + var current_error := GdUnitTools.normalize_text(GdUnitTools.richtext_normalize(_failure_message)) + if current_error.find(expected_error) != 0: + var diffs := GdDiffTool.string_diff(current_error, expected_error) + var current := GdAssertMessages.colored_array_div(diffs[1]) + return _report_error(GdAssertMessages.error_not_same_error(current, expected_error)) + return self + + +func _report_error(error_message :String, failure_line_number: int = -1) -> GdUnitAssert: + var line_number := failure_line_number if failure_line_number != -1 else GdUnitAssertions.get_line_number() + _current_failure_message = GdAssertMessages.build_failure_message(error_message, _additional_failure_message, _custom_failure_message) + GdAssertReports.report_error(_current_failure_message, line_number) + return self + + +func _report_success() -> GdUnitFailureAssert: + GdAssertReports.report_success() + return self diff --git a/addons/gdUnit4/src/asserts/GdUnitFailureAssertImpl.gd.uid b/addons/gdUnit4/src/asserts/GdUnitFailureAssertImpl.gd.uid new file mode 100644 index 0000000..e7fa11f --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitFailureAssertImpl.gd.uid @@ -0,0 +1 @@ +uid://bte1ip8x1fse7 diff --git a/addons/gdUnit4/src/asserts/GdUnitFileAssertImpl.gd b/addons/gdUnit4/src/asserts/GdUnitFileAssertImpl.gd new file mode 100644 index 0000000..c4f9570 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitFileAssertImpl.gd @@ -0,0 +1,116 @@ +extends GdUnitFileAssert + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") + +var _base: GdUnitAssertImpl + + +func _init(current :Variant) -> void: + _base = GdUnitAssertImpl.new(current) + # save the actual assert instance on the current thread context + GdUnitThreadManager.get_current_context().set_assert(self) + if not GdUnitAssertions.validate_value_type(current, TYPE_STRING): + @warning_ignore("return_value_discarded") + report_error("GdUnitFileAssert inital error, unexpected type <%s>" % GdObjects.typeof_as_string(current)) + + +func _notification(event :int) -> void: + if event == NOTIFICATION_PREDELETE: + if _base != null: + _base.notification(event) + _base = null + + +func current_value() -> String: + return _base.current_value() + + +func report_success() -> GdUnitFileAssert: + @warning_ignore("return_value_discarded") + _base.report_success() + return self + + +func report_error(error :String) -> GdUnitFileAssert: + @warning_ignore("return_value_discarded") + _base.report_error(error) + return self + + +func failure_message() -> String: + return _base.failure_message() + + +func override_failure_message(message: String) -> GdUnitFileAssert: + @warning_ignore("return_value_discarded") + _base.override_failure_message(message) + return self + + +func append_failure_message(message: String) -> GdUnitFileAssert: + @warning_ignore("return_value_discarded") + _base.append_failure_message(message) + return self + + +func is_null() -> GdUnitFileAssert: + @warning_ignore("return_value_discarded") + _base.is_null() + return self + + +func is_not_null() -> GdUnitFileAssert: + @warning_ignore("return_value_discarded") + _base.is_not_null() + return self + + +func is_equal(expected: Variant) -> GdUnitFileAssert: + @warning_ignore("return_value_discarded") + _base.is_equal(expected) + return self + + +func is_not_equal(expected: Variant) -> GdUnitFileAssert: + @warning_ignore("return_value_discarded") + _base.is_not_equal(expected) + return self + + +func is_file() -> GdUnitFileAssert: + var current := current_value() + if FileAccess.open(current, FileAccess.READ) == null: + return report_error("Is not a file '%s', error code %s" % [current, FileAccess.get_open_error()]) + return report_success() + + +func exists() -> GdUnitFileAssert: + var current := current_value() + if not FileAccess.file_exists(current): + return report_error("The file '%s' not exists" %current) + return report_success() + + +func is_script() -> GdUnitFileAssert: + var current := current_value() + if FileAccess.open(current, FileAccess.READ) == null: + return report_error("Can't acces the file '%s'! Error code %s" % [current, FileAccess.get_open_error()]) + + var script := load(current) + if not script is GDScript: + return report_error("The file '%s' is not a GdScript" % current) + return report_success() + + +func contains_exactly(expected_rows: Array) -> GdUnitFileAssert: + var current := current_value() + if FileAccess.open(current, FileAccess.READ) == null: + return report_error("Can't acces the file '%s'! Error code %s" % [current, FileAccess.get_open_error()]) + + var script: GDScript = load(current) + if script is GDScript: + var source_code := GdScriptParser.to_unix_format(script.source_code) + var rows := Array(source_code.split("\n")) + @warning_ignore("return_value_discarded") + GdUnitArrayAssertImpl.new(rows).contains_exactly(expected_rows) + return self diff --git a/addons/gdUnit4/src/asserts/GdUnitFileAssertImpl.gd.uid b/addons/gdUnit4/src/asserts/GdUnitFileAssertImpl.gd.uid new file mode 100644 index 0000000..1dd66cd --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitFileAssertImpl.gd.uid @@ -0,0 +1 @@ +uid://ceaoc5gsdw5iw diff --git a/addons/gdUnit4/src/asserts/GdUnitFloatAssertImpl.gd b/addons/gdUnit4/src/asserts/GdUnitFloatAssertImpl.gd new file mode 100644 index 0000000..83d7e05 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitFloatAssertImpl.gd @@ -0,0 +1,159 @@ +extends GdUnitFloatAssert + +var _base: GdUnitAssertImpl + + +func _init(current :Variant) -> void: + _base = GdUnitAssertImpl.new(current) + # save the actual assert instance on the current thread context + GdUnitThreadManager.get_current_context().set_assert(self) + if not GdUnitAssertions.validate_value_type(current, TYPE_FLOAT): + @warning_ignore("return_value_discarded") + report_error("GdUnitFloatAssert inital error, unexpected type <%s>" % GdObjects.typeof_as_string(current)) + + +func _notification(event :int) -> void: + if event == NOTIFICATION_PREDELETE: + if _base != null: + _base.notification(event) + _base = null + + +func current_value() -> Variant: + return _base.current_value() + + +func report_success() -> GdUnitFloatAssert: + @warning_ignore("return_value_discarded") + _base.report_success() + return self + + +func report_error(error :String) -> GdUnitFloatAssert: + @warning_ignore("return_value_discarded") + _base.report_error(error) + return self + + +func failure_message() -> String: + return _base.failure_message() + + +func override_failure_message(message: String) -> GdUnitFloatAssert: + @warning_ignore("return_value_discarded") + _base.override_failure_message(message) + return self + + +func append_failure_message(message: String) -> GdUnitFloatAssert: + @warning_ignore("return_value_discarded") + _base.append_failure_message(message) + return self + + +func is_null() -> GdUnitFloatAssert: + @warning_ignore("return_value_discarded") + _base.is_null() + return self + + +func is_not_null() -> GdUnitFloatAssert: + @warning_ignore("return_value_discarded") + _base.is_not_null() + return self + + +func is_equal(expected: Variant) -> GdUnitFloatAssert: + @warning_ignore("return_value_discarded") + _base.is_equal(expected) + return self + + +func is_not_equal(expected: Variant) -> GdUnitFloatAssert: + @warning_ignore("return_value_discarded") + _base.is_not_equal(expected) + return self + + +@warning_ignore("shadowed_global_identifier") +func is_equal_approx(expected :float, approx :float) -> GdUnitFloatAssert: + return is_between(expected-approx, expected+approx) + + +func is_less(expected :float) -> GdUnitFloatAssert: + var current :Variant = current_value() + if current == null or current >= expected: + return report_error(GdAssertMessages.error_is_value(Comparator.LESS_THAN, current, expected)) + return report_success() + + +func is_less_equal(expected :float) -> GdUnitFloatAssert: + var current :Variant = current_value() + if current == null or current > expected: + return report_error(GdAssertMessages.error_is_value(Comparator.LESS_EQUAL, current, expected)) + return report_success() + + +func is_greater(expected :float) -> GdUnitFloatAssert: + var current :Variant = current_value() + if current == null or current <= expected: + return report_error(GdAssertMessages.error_is_value(Comparator.GREATER_THAN, current, expected)) + return report_success() + + +func is_greater_equal(expected :float) -> GdUnitFloatAssert: + var current :Variant = current_value() + if current == null or current < expected: + return report_error(GdAssertMessages.error_is_value(Comparator.GREATER_EQUAL, current, expected)) + return report_success() + + +func is_negative() -> GdUnitFloatAssert: + var current :Variant = current_value() + if current == null or current >= 0.0: + return report_error(GdAssertMessages.error_is_negative(current)) + return report_success() + + +func is_not_negative() -> GdUnitFloatAssert: + var current :Variant = current_value() + if current == null or current < 0.0: + return report_error(GdAssertMessages.error_is_not_negative(current)) + return report_success() + + +func is_zero() -> GdUnitFloatAssert: + var current :Variant = current_value() + @warning_ignore("unsafe_cast") + if current == null or not is_equal_approx(0.00000000, current as float): + return report_error(GdAssertMessages.error_is_zero(current)) + return report_success() + + +func is_not_zero() -> GdUnitFloatAssert: + var current :Variant = current_value() + @warning_ignore("unsafe_cast") + if current == null or is_equal_approx(0.00000000, current as float): + return report_error(GdAssertMessages.error_is_not_zero()) + return report_success() + + +func is_in(expected :Array) -> GdUnitFloatAssert: + var current :Variant = current_value() + if not expected.has(current): + return report_error(GdAssertMessages.error_is_in(current, expected)) + return report_success() + + +func is_not_in(expected :Array) -> GdUnitFloatAssert: + var current :Variant = current_value() + if expected.has(current): + return report_error(GdAssertMessages.error_is_not_in(current, expected)) + return report_success() + + +func is_between(from :float, to :float) -> GdUnitFloatAssert: + var current :Variant = current_value() + if current == null or current < from or current > to: + return report_error(GdAssertMessages.error_is_value(Comparator.BETWEEN_EQUAL, current, from, to)) + return report_success() diff --git a/addons/gdUnit4/src/asserts/GdUnitFloatAssertImpl.gd.uid b/addons/gdUnit4/src/asserts/GdUnitFloatAssertImpl.gd.uid new file mode 100644 index 0000000..b679fe0 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitFloatAssertImpl.gd.uid @@ -0,0 +1 @@ +uid://dv7lqw52d0wab diff --git a/addons/gdUnit4/src/asserts/GdUnitFuncAssertImpl.gd b/addons/gdUnit4/src/asserts/GdUnitFuncAssertImpl.gd new file mode 100644 index 0000000..c38acf0 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitFuncAssertImpl.gd @@ -0,0 +1,177 @@ +extends GdUnitFuncAssert + + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") +const DEFAULT_TIMEOUT := 2000 + + +var _current_value_provider :ValueProvider +var _current_failure_message :String = "" +var _custom_failure_message :String = "" +var _additional_failure_message: String = "" +var _line_number := -1 +var _timeout := DEFAULT_TIMEOUT +var _interrupted := false +var _sleep_timer :Timer = null + + +func _init(instance :Object, func_name :String, args := Array()) -> void: + _line_number = GdUnitAssertions.get_line_number() + GdAssertReports.reset_last_error_line_number() + # save the actual assert instance on the current thread context + GdUnitThreadManager.get_current_context().set_assert(self) + # verify at first the function name exists + if not instance.has_method(func_name): + @warning_ignore("return_value_discarded") + report_error("The function '%s' do not exists checked instance '%s'." % [func_name, instance]) + _interrupted = true + else: + _current_value_provider = CallBackValueProvider.new(instance, func_name, args) + + +func _notification(what :int) -> void: + if what == NOTIFICATION_PREDELETE: + _interrupted = true + var main_node :Node = (Engine.get_main_loop() as SceneTree).root + if is_instance_valid(_current_value_provider): + _current_value_provider.dispose() + _current_value_provider = null + if is_instance_valid(_sleep_timer): + _sleep_timer.set_wait_time(0.0001) + _sleep_timer.stop() + main_node.remove_child(_sleep_timer) + _sleep_timer.free() + _sleep_timer = null + + +func report_success() -> GdUnitFuncAssert: + GdAssertReports.report_success() + return self + + +func report_error(failure :String) -> GdUnitFuncAssert: + _current_failure_message = GdAssertMessages.build_failure_message(failure, _additional_failure_message, _custom_failure_message) + GdAssertReports.report_error(_current_failure_message, _line_number) + return self + + +func failure_message() -> String: + return _current_failure_message + + +func override_failure_message(message: String) -> GdUnitFuncAssert: + _custom_failure_message = message + return self + + +func append_failure_message(message: String) -> GdUnitFuncAssert: + _additional_failure_message = message + return self + + +func wait_until(timeout := 2000) -> GdUnitFuncAssert: + if timeout <= 0: + push_warning("Invalid timeout param, alloed timeouts must be grater than 0. Use default timeout instead") + _timeout = DEFAULT_TIMEOUT + else: + _timeout = timeout + return self + + +func is_null() -> GdUnitFuncAssert: + await _validate_callback(cb_is_null) + return self + + +func is_not_null() -> GdUnitFuncAssert: + await _validate_callback(cb_is_not_null) + return self + + +func is_false() -> GdUnitFuncAssert: + await _validate_callback(cb_is_false) + return self + + +func is_true() -> GdUnitFuncAssert: + await _validate_callback(cb_is_true) + return self + + +func is_equal(expected: Variant) -> GdUnitFuncAssert: + await _validate_callback(cb_is_equal, expected) + return self + + +func is_not_equal(expected: Variant) -> GdUnitFuncAssert: + await _validate_callback(cb_is_not_equal, expected) + return self + + +# we need actually to define this Callable as functions otherwise we results into leaked scripts here +# this is actually a Godot bug and needs this kind of workaround +func cb_is_null(c :Variant, _e :Variant) -> bool: return c == null +func cb_is_not_null(c :Variant, _e :Variant) -> bool: return c != null +func cb_is_false(c :Variant, _e :Variant) -> bool: return c == false +func cb_is_true(c :Variant, _e :Variant) -> bool: return c == true +func cb_is_equal(c :Variant, e :Variant) -> bool: return GdObjects.equals(c,e) +func cb_is_not_equal(c :Variant, e :Variant) -> bool: return not GdObjects.equals(c, e) + + +func do_interrupt() -> void: + _interrupted = true + + +func _validate_callback(predicate :Callable, expected :Variant = null) -> void: + if _interrupted: + return + GdUnitMemoryObserver.guard_instance(self) + var time_scale := Engine.get_time_scale() + var timer := Timer.new() + timer.set_name("gdunit_funcassert_interrupt_timer_%d" % timer.get_instance_id()) + var scene_tree := Engine.get_main_loop() as SceneTree + scene_tree.root.add_child(timer) + timer.add_to_group("GdUnitTimers") + @warning_ignore("return_value_discarded") + timer.timeout.connect(do_interrupt, CONNECT_DEFERRED) + timer.set_one_shot(true) + timer.start((_timeout/1000.0)*time_scale) + _sleep_timer = Timer.new() + _sleep_timer.set_name("gdunit_funcassert_sleep_timer_%d" % _sleep_timer.get_instance_id() ) + scene_tree.root.add_child(_sleep_timer) + + while true: + var current :Variant = await next_current_value() + # is interupted or predicate success + if _interrupted or predicate.call(current, expected): + break + if is_instance_valid(_sleep_timer): + _sleep_timer.start(0.05) + await _sleep_timer.timeout + + _sleep_timer.stop() + await scene_tree.process_frame + if _interrupted: + # https://github.com/godotengine/godot/issues/73052 + #var predicate_name = predicate.get_method() + var predicate_name :String = str(predicate).split('::')[1] + @warning_ignore("return_value_discarded") + report_error(GdAssertMessages.error_interrupted( + predicate_name.strip_edges().trim_prefix("cb_"), + expected, + LocalTime.elapsed(_timeout) + ) + ) + else: + @warning_ignore("return_value_discarded") + report_success() + _sleep_timer.free() + timer.free() + GdUnitMemoryObserver.unguard_instance(self) + + +func next_current_value() -> Variant: + @warning_ignore("redundant_await") + if is_instance_valid(_current_value_provider): + return await _current_value_provider.get_value() + return "invalid value" diff --git a/addons/gdUnit4/src/asserts/GdUnitFuncAssertImpl.gd.uid b/addons/gdUnit4/src/asserts/GdUnitFuncAssertImpl.gd.uid new file mode 100644 index 0000000..75c6173 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitFuncAssertImpl.gd.uid @@ -0,0 +1 @@ +uid://dhs4rkw88l0vq diff --git a/addons/gdUnit4/src/asserts/GdUnitGodotErrorAssertImpl.gd b/addons/gdUnit4/src/asserts/GdUnitGodotErrorAssertImpl.gd new file mode 100644 index 0000000..fc010db --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitGodotErrorAssertImpl.gd @@ -0,0 +1,141 @@ +extends GdUnitGodotErrorAssert + +var _current_failure_message := "" +var _custom_failure_message := "" +var _additional_failure_message := "" +var _callable: Callable + + +func _init(callable: Callable) -> void: + # save the actual assert instance on the current thread context + GdUnitThreadManager.get_current_context().set_assert(self) + GdAssertReports.reset_last_error_line_number() + _callable = callable + + +func _execute() -> Array[ErrorLogEntry]: + # execute the given code and monitor for runtime errors + if _callable == null or not _callable.is_valid(): + @warning_ignore("return_value_discarded") + _report_error("Invalid Callable '%s'" % _callable) + else: + await _callable.call() + return await _error_monitor().scan(true) + + +func _error_monitor() -> GodotGdErrorMonitor: + return GdUnitThreadManager.get_current_context().get_execution_context().error_monitor + + +func failure_message() -> String: + return _current_failure_message + + +func _report_success() -> GdUnitAssert: + GdAssertReports.report_success() + return self + + +func _report_error(error_message: String, failure_line_number: int = -1) -> GdUnitAssert: + var line_number := failure_line_number if failure_line_number != -1 else GdUnitAssertions.get_line_number() + _current_failure_message = GdAssertMessages.build_failure_message(error_message, _additional_failure_message, _custom_failure_message) + GdAssertReports.report_error(_current_failure_message, line_number) + return self + + +func _has_log_entry(log_entries: Array[ErrorLogEntry], type: ErrorLogEntry.TYPE, error: Variant) -> bool: + for entry in log_entries: + if entry._type == type and GdObjects.equals(entry._message, error): + # Erase the log entry we already handled it by this assertion, otherwise it will report at twice + _error_monitor().erase_log_entry(entry) + return true + return false + + +func _to_list(log_entries: Array[ErrorLogEntry]) -> String: + if log_entries.is_empty(): + return "no errors" + if log_entries.size() == 1: + return log_entries[0]._message + var value := "" + for entry in log_entries: + value += "'%s'\n" % entry._message + return value + + +func is_null() -> GdUnitGodotErrorAssert: + return _report_error("Not implemented") + + +func is_not_null() -> GdUnitGodotErrorAssert: + return _report_error("Not implemented") + + +func is_equal(_expected: Variant) -> GdUnitGodotErrorAssert: + return _report_error("Not implemented") + + +func is_not_equal(_expected: Variant) -> GdUnitGodotErrorAssert: + return _report_error("Not implemented") + + +func override_failure_message(message: String) -> GdUnitGodotErrorAssert: + _custom_failure_message = message + return self + + +func append_failure_message(message: String) -> GdUnitGodotErrorAssert: + _additional_failure_message = message + return self + + +func is_success() -> GdUnitGodotErrorAssert: + var log_entries := await _execute() + if log_entries.is_empty(): + return _report_success() + return _report_error(""" + Expecting: no error's are ocured. + but found: '%s' + """.dedent().trim_prefix("\n") % _to_list(log_entries)) + + +func is_runtime_error(expected_error: Variant) -> GdUnitGodotErrorAssert: + var result := GdUnitArgumentMatchers.is_variant_string_matching(expected_error) + if result.is_error(): + return _report_error(result.error_message()) + var log_entries := await _execute() + if _has_log_entry(log_entries, ErrorLogEntry.TYPE.SCRIPT_ERROR, expected_error): + return _report_success() + return _report_error(""" + Expecting: a runtime error is triggered. + message: '%s' + found: %s + """.dedent().trim_prefix("\n") % [expected_error, _to_list(log_entries)]) + + +func is_push_warning(expected_warning: Variant) -> GdUnitGodotErrorAssert: + var result := GdUnitArgumentMatchers.is_variant_string_matching(expected_warning) + if result.is_error(): + return _report_error(result.error_message()) + var log_entries := await _execute() + if _has_log_entry(log_entries, ErrorLogEntry.TYPE.PUSH_WARNING, expected_warning): + return _report_success() + return _report_error(""" + Expecting: push_warning() is called. + message: '%s' + found: %s + """.dedent().trim_prefix("\n") % [expected_warning, _to_list(log_entries)]) + + +func is_push_error(expected_error: Variant) -> GdUnitGodotErrorAssert: + var result := GdUnitArgumentMatchers.is_variant_string_matching(expected_error) + if result.is_error(): + return _report_error(result.error_message()) + var log_entries := await _execute() + if _has_log_entry(log_entries, ErrorLogEntry.TYPE.PUSH_ERROR, expected_error): + return _report_success() + return _report_error(""" + Expecting: push_error() is called. + message: '%s' + found: %s + """.dedent().trim_prefix("\n") % [expected_error, _to_list(log_entries)]) diff --git a/addons/gdUnit4/src/asserts/GdUnitGodotErrorAssertImpl.gd.uid b/addons/gdUnit4/src/asserts/GdUnitGodotErrorAssertImpl.gd.uid new file mode 100644 index 0000000..32571e3 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitGodotErrorAssertImpl.gd.uid @@ -0,0 +1 @@ +uid://bbokpm06helow diff --git a/addons/gdUnit4/src/asserts/GdUnitIntAssertImpl.gd b/addons/gdUnit4/src/asserts/GdUnitIntAssertImpl.gd new file mode 100644 index 0000000..bdee249 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitIntAssertImpl.gd @@ -0,0 +1,166 @@ +extends GdUnitIntAssert + +var _base: GdUnitAssertImpl + + +func _init(current :Variant) -> void: + _base = GdUnitAssertImpl.new(current) + # save the actual assert instance on the current thread context + GdUnitThreadManager.get_current_context().set_assert(self) + if not GdUnitAssertions.validate_value_type(current, TYPE_INT): + @warning_ignore("return_value_discarded") + report_error("GdUnitIntAssert inital error, unexpected type <%s>" % GdObjects.typeof_as_string(current)) + + +func _notification(event :int) -> void: + if event == NOTIFICATION_PREDELETE: + if _base != null: + _base.notification(event) + _base = null + + +func current_value() -> Variant: + return _base.current_value() + + +func report_success() -> GdUnitIntAssert: + @warning_ignore("return_value_discarded") + _base.report_success() + return self + + +func report_error(error :String) -> GdUnitIntAssert: + @warning_ignore("return_value_discarded") + _base.report_error(error) + return self + + +func failure_message() -> String: + return _base.failure_message() + + +func override_failure_message(message: String) -> GdUnitIntAssert: + @warning_ignore("return_value_discarded") + _base.override_failure_message(message) + return self + + +func append_failure_message(message: String) -> GdUnitIntAssert: + @warning_ignore("return_value_discarded") + _base.append_failure_message(message) + return self + + +func is_null() -> GdUnitIntAssert: + @warning_ignore("return_value_discarded") + _base.is_null() + return self + + +func is_not_null() -> GdUnitIntAssert: + @warning_ignore("return_value_discarded") + _base.is_not_null() + return self + + +func is_equal(expected: Variant) -> GdUnitIntAssert: + @warning_ignore("return_value_discarded") + _base.is_equal(expected) + return self + + +func is_not_equal(expected: Variant) -> GdUnitIntAssert: + @warning_ignore("return_value_discarded") + _base.is_not_equal(expected) + return self + + +func is_less(expected :int) -> GdUnitIntAssert: + var current :Variant = current_value() + if current == null or current >= expected: + return report_error(GdAssertMessages.error_is_value(Comparator.LESS_THAN, current, expected)) + return report_success() + + +func is_less_equal(expected :int) -> GdUnitIntAssert: + var current :Variant = current_value() + if current == null or current > expected: + return report_error(GdAssertMessages.error_is_value(Comparator.LESS_EQUAL, current, expected)) + return report_success() + + +func is_greater(expected :int) -> GdUnitIntAssert: + var current :Variant = current_value() + if current == null or current <= expected: + return report_error(GdAssertMessages.error_is_value(Comparator.GREATER_THAN, current, expected)) + return report_success() + + +func is_greater_equal(expected :int) -> GdUnitIntAssert: + var current :Variant = current_value() + if current == null or current < expected: + return report_error(GdAssertMessages.error_is_value(Comparator.GREATER_EQUAL, current, expected)) + return report_success() + + +func is_even() -> GdUnitIntAssert: + var current :Variant = current_value() + if current == null or current % 2 != 0: + return report_error(GdAssertMessages.error_is_even(current)) + return report_success() + + +func is_odd() -> GdUnitIntAssert: + var current :Variant = current_value() + if current == null or current % 2 == 0: + return report_error(GdAssertMessages.error_is_odd(current)) + return report_success() + + +func is_negative() -> GdUnitIntAssert: + var current :Variant = current_value() + if current == null or current >= 0: + return report_error(GdAssertMessages.error_is_negative(current)) + return report_success() + + +func is_not_negative() -> GdUnitIntAssert: + var current :Variant = current_value() + if current == null or current < 0: + return report_error(GdAssertMessages.error_is_not_negative(current)) + return report_success() + + +func is_zero() -> GdUnitIntAssert: + var current :Variant = current_value() + if current != 0: + return report_error(GdAssertMessages.error_is_zero(current)) + return report_success() + + +func is_not_zero() -> GdUnitIntAssert: + var current :Variant= current_value() + if current == 0: + return report_error(GdAssertMessages.error_is_not_zero()) + return report_success() + + +func is_in(expected :Array) -> GdUnitIntAssert: + var current :Variant = current_value() + if not expected.has(current): + return report_error(GdAssertMessages.error_is_in(current, expected)) + return report_success() + + +func is_not_in(expected :Array) -> GdUnitIntAssert: + var current :Variant = current_value() + if expected.has(current): + return report_error(GdAssertMessages.error_is_not_in(current, expected)) + return report_success() + + +func is_between(from :int, to :int) -> GdUnitIntAssert: + var current :Variant = current_value() + if current == null or current < from or current > to: + return report_error(GdAssertMessages.error_is_value(Comparator.BETWEEN_EQUAL, current, from, to)) + return report_success() diff --git a/addons/gdUnit4/src/asserts/GdUnitIntAssertImpl.gd.uid b/addons/gdUnit4/src/asserts/GdUnitIntAssertImpl.gd.uid new file mode 100644 index 0000000..c41b177 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitIntAssertImpl.gd.uid @@ -0,0 +1 @@ +uid://detx7vuayqooh diff --git a/addons/gdUnit4/src/asserts/GdUnitObjectAssertImpl.gd b/addons/gdUnit4/src/asserts/GdUnitObjectAssertImpl.gd new file mode 100644 index 0000000..955e1ef --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitObjectAssertImpl.gd @@ -0,0 +1,166 @@ +extends GdUnitObjectAssert + +var _base: GdUnitAssertImpl + + +func _init(current: Variant) -> void: + _base = GdUnitAssertImpl.new(current) + # save the actual assert instance on the current thread context + GdUnitThreadManager.get_current_context().set_assert(self) + if (current != null + and (GdUnitAssertions.validate_value_type(current, TYPE_BOOL) + or GdUnitAssertions.validate_value_type(current, TYPE_INT) + or GdUnitAssertions.validate_value_type(current, TYPE_FLOAT) + or GdUnitAssertions.validate_value_type(current, TYPE_STRING))): + @warning_ignore("return_value_discarded") + report_error("GdUnitObjectAssert inital error, unexpected type <%s>" % GdObjects.typeof_as_string(current)) + + +func _notification(event: int) -> void: + if event == NOTIFICATION_PREDELETE: + if _base != null: + _base.notification(event) + _base = null + + +func current_value() -> Variant: + return _base.current_value() + + +func report_success() -> GdUnitObjectAssert: + @warning_ignore("return_value_discarded") + _base.report_success() + return self + + +func report_error(error: String) -> GdUnitObjectAssert: + @warning_ignore("return_value_discarded") + _base.report_error(error) + return self + + +func failure_message() -> String: + return _base.failure_message() + + +func override_failure_message(message: String) -> GdUnitObjectAssert: + @warning_ignore("return_value_discarded") + _base.override_failure_message(message) + return self + + +func append_failure_message(message: String) -> GdUnitObjectAssert: + @warning_ignore("return_value_discarded") + _base.append_failure_message(message) + return self + + +func is_equal(expected: Variant) -> GdUnitObjectAssert: + @warning_ignore("return_value_discarded") + _base.is_equal(expected) + return self + + +func is_not_equal(expected: Variant) -> GdUnitObjectAssert: + @warning_ignore("return_value_discarded") + _base.is_not_equal(expected) + return self + + +func is_null() -> GdUnitObjectAssert: + @warning_ignore("return_value_discarded") + _base.is_null() + return self + + +func is_not_null() -> GdUnitObjectAssert: + @warning_ignore("return_value_discarded") + _base.is_not_null() + return self + + +@warning_ignore("shadowed_global_identifier") +func is_same(expected: Variant) -> GdUnitObjectAssert: + var current: Variant = current_value() + if not is_same(current, expected): + return report_error(GdAssertMessages.error_is_same(current, expected)) + return report_success() + + +func is_not_same(expected: Variant) -> GdUnitObjectAssert: + var current: Variant = current_value() + if is_same(current, expected): + return report_error(GdAssertMessages.error_not_same(current, expected)) + return report_success() + + +func is_instanceof(type: Variant) -> GdUnitObjectAssert: + var current: Variant = current_value() + if current == null or not is_instance_of(current, type): + var result_expected := GdObjects.extract_class_name(type) + var result_current := GdObjects.extract_class_name(current) + return report_error(GdAssertMessages.error_is_instanceof(result_current, result_expected)) + return report_success() + + +func is_not_instanceof(type: Variant) -> GdUnitObjectAssert: + var current: Variant = current_value() + if is_instance_of(current, type): + var result := GdObjects.extract_class_name(type) + if result.is_success(): + return report_error("Expected not be a instance of <%s>" % str(result.value())) + + push_error("Internal ERROR: %s" % result.error_message()) + return self + return report_success() + + +## Checks whether the current object inherits from the specified type. +func is_inheriting(type: Variant) -> GdUnitObjectAssert: + var current: Variant = current_value() + if not is_instance_of(current, TYPE_OBJECT): + return report_error("Expected '%s' to inherit from at least Object." % str(current)) + var result := _inherits(current, type) + if result.is_success(): + return report_success() + return report_error(result.error_message()) + + +## Checks whether the current object does NOT inherit from the specified type. +func is_not_inheriting(type: Variant) -> GdUnitObjectAssert: + var current: Variant = current_value() + if not is_instance_of(current, TYPE_OBJECT): + return report_error("Expected '%s' to inherit from at least Object." % str(current)) + var result := _inherits(current, type) + if result.is_success(): + return report_error("Expected type to not inherit from <%s>" % _extract_class_type(type)) + return report_success() + + +func _inherits(current: Variant, type: Variant) -> GdUnitResult: + var type_as_string := _extract_class_type(type) + if type_as_string == "Object": + return GdUnitResult.success("") + + var obj: Object = current + for p in obj.get_property_list(): + var clazz_name :String = p["name"] + if p["usage"] == PROPERTY_USAGE_CATEGORY and clazz_name == p["hint_string"] and clazz_name == type_as_string: + return GdUnitResult.success("") + var script: Script = obj.get_script() + if script != null: + while script != null: + var result := GdObjects.extract_class_name(script) + if result.is_success() and result.value() == type_as_string: + return GdUnitResult.success("") + script = script.get_base_script() + return GdUnitResult.error("Expected type to inherit from <%s>" % type_as_string) + + +func _extract_class_type(type: Variant) -> String: + if type is String: + return type + var result := GdObjects.extract_class_name(type) + if result.is_error(): + return "" + return result.value() diff --git a/addons/gdUnit4/src/asserts/GdUnitObjectAssertImpl.gd.uid b/addons/gdUnit4/src/asserts/GdUnitObjectAssertImpl.gd.uid new file mode 100644 index 0000000..44b5e0f --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitObjectAssertImpl.gd.uid @@ -0,0 +1 @@ +uid://bst3r5k8f6evn diff --git a/addons/gdUnit4/src/asserts/GdUnitResultAssertImpl.gd b/addons/gdUnit4/src/asserts/GdUnitResultAssertImpl.gd new file mode 100644 index 0000000..98a6768 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitResultAssertImpl.gd @@ -0,0 +1,128 @@ +extends GdUnitResultAssert + +var _base: GdUnitAssertImpl + + +func _init(current :Variant) -> void: + _base = GdUnitAssertImpl.new(current) + # save the actual assert instance on the current thread context + GdUnitThreadManager.get_current_context().set_assert(self) + if not validate_value_type(current): + @warning_ignore("return_value_discarded") + report_error("GdUnitResultAssert inital error, unexpected type <%s>" % GdObjects.typeof_as_string(current)) + + +func _notification(event :int) -> void: + if event == NOTIFICATION_PREDELETE: + if _base != null: + _base.notification(event) + _base = null + + +func validate_value_type(value :Variant) -> bool: + return value == null or value is GdUnitResult + + +func current_value() -> GdUnitResult: + return _base.current_value() + + +func report_success() -> GdUnitResultAssert: + @warning_ignore("return_value_discarded") + _base.report_success() + return self + + +func report_error(error :String) -> GdUnitResultAssert: + @warning_ignore("return_value_discarded") + _base.report_error(error) + return self + + +func failure_message() -> String: + return _base.failure_message() + + +func override_failure_message(message: String) -> GdUnitResultAssert: + @warning_ignore("return_value_discarded") + _base.override_failure_message(message) + return self + + +func append_failure_message(message: String) -> GdUnitResultAssert: + @warning_ignore("return_value_discarded") + _base.append_failure_message(message) + return self + + +func is_null() -> GdUnitResultAssert: + @warning_ignore("return_value_discarded") + _base.is_null() + return self + + +func is_not_null() -> GdUnitResultAssert: + @warning_ignore("return_value_discarded") + _base.is_not_null() + return self + + +func is_equal(expected: Variant) -> GdUnitResultAssert: + return is_value(expected) + + +func is_not_equal(expected: Variant) -> GdUnitResultAssert: + var result := current_value() + var value :Variant = null if result == null else result.value() + if GdObjects.equals(value, expected): + return report_error(GdAssertMessages.error_not_equal(value, expected)) + return report_success() + + +func is_empty() -> GdUnitResultAssert: + var result := current_value() + if result == null or not result.is_empty(): + return report_error(GdAssertMessages.error_result_is_empty(result)) + return report_success() + + +func is_success() -> GdUnitResultAssert: + var result := current_value() + if result == null or not result.is_success(): + return report_error(GdAssertMessages.error_result_is_success(result)) + return report_success() + + +func is_warning() -> GdUnitResultAssert: + var result := current_value() + if result == null or not result.is_warn(): + return report_error(GdAssertMessages.error_result_is_warning(result)) + return report_success() + + +func is_error() -> GdUnitResultAssert: + var result := current_value() + if result == null or not result.is_error(): + return report_error(GdAssertMessages.error_result_is_error(result)) + return report_success() + + +func contains_message(expected :String) -> GdUnitResultAssert: + var result := current_value() + if result == null: + return report_error(GdAssertMessages.error_result_has_message("", expected)) + if result.is_success(): + return report_error(GdAssertMessages.error_result_has_message_on_success(expected)) + if result.is_error() and result.error_message() != expected: + return report_error(GdAssertMessages.error_result_has_message(result.error_message(), expected)) + if result.is_warn() and result.warn_message() != expected: + return report_error(GdAssertMessages.error_result_has_message(result.warn_message(), expected)) + return report_success() + + +func is_value(expected: Variant) -> GdUnitResultAssert: + var result := current_value() + var value :Variant = null if result == null else result.value() + if not GdObjects.equals(value, expected): + return report_error(GdAssertMessages.error_result_is_value(value, expected)) + return report_success() diff --git a/addons/gdUnit4/src/asserts/GdUnitResultAssertImpl.gd.uid b/addons/gdUnit4/src/asserts/GdUnitResultAssertImpl.gd.uid new file mode 100644 index 0000000..35f4090 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitResultAssertImpl.gd.uid @@ -0,0 +1 @@ +uid://cwnck5nc2l32s diff --git a/addons/gdUnit4/src/asserts/GdUnitSignalAssertImpl.gd b/addons/gdUnit4/src/asserts/GdUnitSignalAssertImpl.gd new file mode 100644 index 0000000..6f5878c --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitSignalAssertImpl.gd @@ -0,0 +1,143 @@ +extends GdUnitSignalAssert + +const DEFAULT_TIMEOUT := 2000 + +var _signal_collector :GdUnitSignalCollector +var _emitter :Object +var _current_failure_message :String = "" +var _custom_failure_message :String = "" +var _additional_failure_message: String = "" +var _line_number := -1 +var _timeout := DEFAULT_TIMEOUT +var _interrupted := false + + +func _init(emitter :Object) -> void: + # save the actual assert instance on the current thread context + var context := GdUnitThreadManager.get_current_context() + context.set_assert(self) + _signal_collector = context.get_signal_collector() + _line_number = GdUnitAssertions.get_line_number() + _emitter = emitter + GdAssertReports.reset_last_error_line_number() + + +func _notification(what :int) -> void: + if what == NOTIFICATION_PREDELETE: + _interrupted = true + if is_instance_valid(_emitter): + _signal_collector.unregister_emitter(_emitter) + _emitter = null + + +func report_success() -> GdUnitAssert: + GdAssertReports.report_success() + return self + + +func report_warning(message :String) -> GdUnitAssert: + GdAssertReports.report_warning(message, GdUnitAssertions.get_line_number()) + return self + + +func report_error(failure :String) -> GdUnitAssert: + _current_failure_message = GdAssertMessages.build_failure_message(failure, _additional_failure_message, _custom_failure_message) + GdAssertReports.report_error(_current_failure_message, _line_number) + return self + + +func failure_message() -> String: + return _current_failure_message + + +func override_failure_message(message: String) -> GdUnitSignalAssert: + _custom_failure_message = message + return self + + +func append_failure_message(message: String) -> GdUnitSignalAssert: + _additional_failure_message = message + return self + + +func wait_until(timeout := 2000) -> GdUnitSignalAssert: + if timeout <= 0: + @warning_ignore("return_value_discarded") + report_warning("Invalid timeout parameter, allowed timeouts must be greater than 0, use default timeout instead!") + _timeout = DEFAULT_TIMEOUT + else: + _timeout = timeout + return self + + +func is_null() -> GdUnitSignalAssert: + if _emitter != null: + return report_error(GdAssertMessages.error_is_null(_emitter)) + return report_success() + + +func is_not_null() -> GdUnitSignalAssert: + if _emitter == null: + return report_error(GdAssertMessages.error_is_not_null()) + return report_success() + + +func is_equal(_expected: Variant) -> GdUnitSignalAssert: + return report_error("Not implemented") + + +func is_not_equal(_expected: Variant) -> GdUnitSignalAssert: + return report_error("Not implemented") + + +# Verifies the signal exists checked the emitter +func is_signal_exists(signal_name :String) -> GdUnitSignalAssert: + if not _emitter.has_signal(signal_name): + @warning_ignore("return_value_discarded") + report_error("The signal '%s' not exists checked object '%s'." % [signal_name, _emitter.get_class()]) + return self + + +# Verifies that given signal is emitted until waiting time +func is_emitted(name :String, args := []) -> GdUnitSignalAssert: + _line_number = GdUnitAssertions.get_line_number() + return await _wail_until_signal(name, args, false) + + +# Verifies that given signal is NOT emitted until waiting time +func is_not_emitted(name :String, args := []) -> GdUnitSignalAssert: + _line_number = GdUnitAssertions.get_line_number() + return await _wail_until_signal(name, args, true) + + +func _wail_until_signal(signal_name :String, expected_args :Array, expect_not_emitted: bool) -> GdUnitSignalAssert: + if _emitter == null: + return report_error("Can't wait for signal checked a NULL object.") + # first verify the signal is defined + if not _emitter.has_signal(signal_name): + return report_error("Can't wait for non-existion signal '%s' checked object '%s'." % [signal_name,_emitter.get_class()]) + _signal_collector.register_emitter(_emitter) + var time_scale := Engine.get_time_scale() + var timer := Timer.new() + (Engine.get_main_loop() as SceneTree).root.add_child(timer) + timer.add_to_group("GdUnitTimers") + timer.set_one_shot(true) + @warning_ignore("return_value_discarded") + timer.timeout.connect(func on_timeout() -> void: _interrupted = true) + timer.start((_timeout/1000.0)*time_scale) + var is_signal_emitted := false + while not _interrupted and not is_signal_emitted: + await (Engine.get_main_loop() as SceneTree).process_frame + if is_instance_valid(_emitter): + is_signal_emitted = _signal_collector.match(_emitter, signal_name, expected_args) + if is_signal_emitted and expect_not_emitted: + @warning_ignore("return_value_discarded") + report_error(GdAssertMessages.error_signal_emitted(signal_name, expected_args, LocalTime.elapsed(int(_timeout-timer.time_left*1000)))) + + if _interrupted and not expect_not_emitted: + @warning_ignore("return_value_discarded") + report_error(GdAssertMessages.error_wait_signal(signal_name, expected_args, LocalTime.elapsed(_timeout))) + timer.free() + if is_instance_valid(_emitter): + _signal_collector.reset_received_signals(_emitter, signal_name, expected_args) + return self diff --git a/addons/gdUnit4/src/asserts/GdUnitSignalAssertImpl.gd.uid b/addons/gdUnit4/src/asserts/GdUnitSignalAssertImpl.gd.uid new file mode 100644 index 0000000..2aa68e7 --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitSignalAssertImpl.gd.uid @@ -0,0 +1 @@ +uid://bube5lu6sl3d1 diff --git a/addons/gdUnit4/src/asserts/GdUnitStringAssertImpl.gd b/addons/gdUnit4/src/asserts/GdUnitStringAssertImpl.gd new file mode 100644 index 0000000..cb49c9c --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitStringAssertImpl.gd @@ -0,0 +1,194 @@ +extends GdUnitStringAssert + +var _base: GdUnitAssertImpl + + +func _init(current :Variant) -> void: + _base = GdUnitAssertImpl.new(current) + # save the actual assert instance on the current thread context + GdUnitThreadManager.get_current_context().set_assert(self) + if current != null and typeof(current) != TYPE_STRING and typeof(current) != TYPE_STRING_NAME: + @warning_ignore("return_value_discarded") + report_error("GdUnitStringAssert inital error, unexpected type <%s>" % GdObjects.typeof_as_string(current)) + + +func _notification(event :int) -> void: + if event == NOTIFICATION_PREDELETE: + if _base != null: + _base.notification(event) + _base = null + + +func failure_message() -> String: + return _base.failure_message() + + +func current_value() -> Variant: + return _base.current_value() + + +func report_success() -> GdUnitStringAssert: + @warning_ignore("return_value_discarded") + _base.report_success() + return self + + +func report_error(error :String) -> GdUnitStringAssert: + @warning_ignore("return_value_discarded") + _base.report_error(error) + return self + + +func override_failure_message(message: String) -> GdUnitStringAssert: + @warning_ignore("return_value_discarded") + _base.override_failure_message(message) + return self + + +func append_failure_message(message: String) -> GdUnitStringAssert: + @warning_ignore("return_value_discarded") + _base.append_failure_message(message) + return self + + +func is_null() -> GdUnitStringAssert: + @warning_ignore("return_value_discarded") + _base.is_null() + return self + + +func is_not_null() -> GdUnitStringAssert: + @warning_ignore("return_value_discarded") + _base.is_not_null() + return self + + +func is_equal(expected: Variant) -> GdUnitStringAssert: + var current: Variant = current_value() + if current == null: + return report_error(GdAssertMessages.error_equal(current, expected)) + if not GdObjects.equals(current, expected): + var diffs := GdDiffTool.string_diff(current, expected) + var formatted_current := GdAssertMessages.colored_array_div(diffs[1]) + return report_error(GdAssertMessages.error_equal(formatted_current, expected)) + return report_success() + + +func is_equal_ignoring_case(expected :Variant) -> GdUnitStringAssert: + var current :Variant = current_value() + if current == null: + return report_error(GdAssertMessages.error_equal_ignoring_case(current, expected)) + if not GdObjects.equals(str(current), expected, true): + var diffs := GdDiffTool.string_diff(current, expected) + var formatted_current := GdAssertMessages.colored_array_div(diffs[1]) + return report_error(GdAssertMessages.error_equal_ignoring_case(formatted_current, expected)) + return report_success() + + +func is_not_equal(expected: Variant) -> GdUnitStringAssert: + var current: Variant = current_value() + if GdObjects.equals(current, expected): + return report_error(GdAssertMessages.error_not_equal(current, expected)) + return report_success() + + +func is_not_equal_ignoring_case(expected :Variant) -> GdUnitStringAssert: + var current :Variant = current_value() + if GdObjects.equals(current, expected, true): + return report_error(GdAssertMessages.error_not_equal(current, expected)) + return report_success() + + +func is_empty() -> GdUnitStringAssert: + var current :Variant = current_value() + @warning_ignore("unsafe_cast") + if current == null or not (current as String).is_empty(): + return report_error(GdAssertMessages.error_is_empty(current)) + return report_success() + + +func is_not_empty() -> GdUnitStringAssert: + var current :Variant = current_value() + @warning_ignore("unsafe_cast") + if current == null or (current as String).is_empty(): + return report_error(GdAssertMessages.error_is_not_empty()) + return report_success() + + +func contains(expected :String) -> GdUnitStringAssert: + var current :Variant = current_value() + @warning_ignore("unsafe_cast") + if current == null or (current as String).find(expected) == -1: + return report_error(GdAssertMessages.error_contains(current, expected)) + return report_success() + + +func not_contains(expected :String) -> GdUnitStringAssert: + var current :Variant = current_value() + @warning_ignore("unsafe_cast") + if current != null and (current as String).find(expected) != -1: + return report_error(GdAssertMessages.error_not_contains(current, expected)) + return report_success() + + +func contains_ignoring_case(expected :String) -> GdUnitStringAssert: + var current :Variant = current_value() + @warning_ignore("unsafe_cast") + if current == null or (current as String).findn(expected) == -1: + return report_error(GdAssertMessages.error_contains_ignoring_case(current, expected)) + return report_success() + + +func not_contains_ignoring_case(expected :String) -> GdUnitStringAssert: + var current :Variant = current_value() + @warning_ignore("unsafe_cast") + if current != null and (current as String).findn(expected) != -1: + return report_error(GdAssertMessages.error_not_contains_ignoring_case(current, expected)) + return report_success() + + +func starts_with(expected :String) -> GdUnitStringAssert: + var current :Variant = current_value() + @warning_ignore("unsafe_cast") + if current == null or (current as String).find(expected) != 0: + return report_error(GdAssertMessages.error_starts_with(current, expected)) + return report_success() + + +func ends_with(expected :String) -> GdUnitStringAssert: + var current :Variant = current_value() + if current == null: + return report_error(GdAssertMessages.error_ends_with(current, expected)) + @warning_ignore("unsafe_cast") + var find :int = (current as String).length() - expected.length() + @warning_ignore("unsafe_cast") + if (current as String).rfind(expected) != find: + return report_error(GdAssertMessages.error_ends_with(current, expected)) + return report_success() + + +# gdlint:disable=max-returns +func has_length(expected :int, comparator := Comparator.EQUAL) -> GdUnitStringAssert: + var current :Variant = current_value() + if current == null: + return report_error(GdAssertMessages.error_has_length(current, expected, comparator)) + var str_current: String = current + match comparator: + Comparator.EQUAL: + if str_current.length() != expected: + return report_error(GdAssertMessages.error_has_length(str_current, expected, comparator)) + Comparator.LESS_THAN: + if str_current.length() >= expected: + return report_error(GdAssertMessages.error_has_length(str_current, expected, comparator)) + Comparator.LESS_EQUAL: + if str_current.length() > expected: + return report_error(GdAssertMessages.error_has_length(str_current, expected, comparator)) + Comparator.GREATER_THAN: + if str_current.length() <= expected: + return report_error(GdAssertMessages.error_has_length(str_current, expected, comparator)) + Comparator.GREATER_EQUAL: + if str_current.length() < expected: + return report_error(GdAssertMessages.error_has_length(str_current, expected, comparator)) + _: + return report_error("Comparator '%d' not implemented!" % comparator) + return report_success() diff --git a/addons/gdUnit4/src/asserts/GdUnitStringAssertImpl.gd.uid b/addons/gdUnit4/src/asserts/GdUnitStringAssertImpl.gd.uid new file mode 100644 index 0000000..eba7bfb --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitStringAssertImpl.gd.uid @@ -0,0 +1 @@ +uid://dwodh1yw0gyaw diff --git a/addons/gdUnit4/src/asserts/GdUnitVectorAssertImpl.gd b/addons/gdUnit4/src/asserts/GdUnitVectorAssertImpl.gd new file mode 100644 index 0000000..fbc031a --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitVectorAssertImpl.gd @@ -0,0 +1,187 @@ +extends GdUnitVectorAssert + +var _base: GdUnitAssertImpl +var _current_type: int +var _type_check: bool + +func _init(current: Variant, type_check := true) -> void: + _type_check = type_check + _base = GdUnitAssertImpl.new(current) + # save the actual assert instance on the current thread context + GdUnitThreadManager.get_current_context().set_assert(self) + if not _validate_value_type(current): + @warning_ignore("return_value_discarded") + report_error("GdUnitVectorAssert error, the type <%s> is not supported." % GdObjects.typeof_as_string(current)) + _current_type = typeof(current) + + +func _notification(event :int) -> void: + if event == NOTIFICATION_PREDELETE: + if _base != null: + _base.notification(event) + _base = null + + +func _validate_value_type(value :Variant) -> bool: + return ( + value == null + or typeof(value) in [ + TYPE_VECTOR2, + TYPE_VECTOR2I, + TYPE_VECTOR3, + TYPE_VECTOR3I, + TYPE_VECTOR4, + TYPE_VECTOR4I + ] + ) + + +func _validate_is_vector_type(value :Variant) -> bool: + var type := typeof(value) + if type == _current_type or _current_type == TYPE_NIL: + return true + @warning_ignore("return_value_discarded") + report_error(GdAssertMessages.error_is_wrong_type(_current_type, type)) + return false + + +func current_value() -> Variant: + return _base.current_value() + + +func report_success() -> GdUnitVectorAssert: + @warning_ignore("return_value_discarded") + _base.report_success() + return self + + +func report_error(error :String) -> GdUnitVectorAssert: + @warning_ignore("return_value_discarded") + _base.report_error(error) + return self + + +func failure_message() -> String: + return _base.failure_message() + + +func override_failure_message(message: String) -> GdUnitVectorAssert: + @warning_ignore("return_value_discarded") + _base.override_failure_message(message) + return self + + +func append_failure_message(message :String) -> GdUnitVectorAssert: + @warning_ignore("return_value_discarded") + _base.append_failure_message(message) + return self + + +func is_null() -> GdUnitVectorAssert: + @warning_ignore("return_value_discarded") + _base.is_null() + return self + + +func is_not_null() -> GdUnitVectorAssert: + @warning_ignore("return_value_discarded") + _base.is_not_null() + return self + + +func is_equal(expected: Variant) -> GdUnitVectorAssert: + if _type_check and not _validate_is_vector_type(expected): + return self + @warning_ignore("return_value_discarded") + _base.is_equal(expected) + return self + + +func is_not_equal(expected: Variant) -> GdUnitVectorAssert: + if _type_check and not _validate_is_vector_type(expected): + return self + @warning_ignore("return_value_discarded") + _base.is_not_equal(expected) + return self + + +@warning_ignore("shadowed_global_identifier") +func is_equal_approx(expected :Variant, approx :Variant) -> GdUnitVectorAssert: + if not _validate_is_vector_type(expected) or not _validate_is_vector_type(approx): + return self + var current :Variant = current_value() + var from :Variant = expected - approx + var to :Variant = expected + approx + if current == null or (not _is_equal_approx(current, from, to)): + return report_error(GdAssertMessages.error_is_value(Comparator.BETWEEN_EQUAL, current, from, to)) + return report_success() + + +func _is_equal_approx(current :Variant, from :Variant, to :Variant) -> bool: + match typeof(current): + TYPE_VECTOR2, TYPE_VECTOR2I: + return ((current.x >= from.x and current.y >= from.y) + and (current.x <= to.x and current.y <= to.y)) + TYPE_VECTOR3, TYPE_VECTOR3I: + return ((current.x >= from.x and current.y >= from.y and current.z >= from.z) + and (current.x <= to.x and current.y <= to.y and current.z <= to.z)) + TYPE_VECTOR4, TYPE_VECTOR4I: + return ((current.x >= from.x and current.y >= from.y and current.z >= from.z and current.w >= from.w) + and (current.x <= to.x and current.y <= to.y and current.z <= to.z and current.w <= to.w)) + _: + push_error("Missing implementation '_is_equal_approx' for vector type %s" % typeof(current)) + return false + + +func is_less(expected :Variant) -> GdUnitVectorAssert: + if not _validate_is_vector_type(expected): + return self + var current :Variant = current_value() + if current == null or current >= expected: + return report_error(GdAssertMessages.error_is_value(Comparator.LESS_THAN, current, expected)) + return report_success() + + +func is_less_equal(expected :Variant) -> GdUnitVectorAssert: + if not _validate_is_vector_type(expected): + return self + var current :Variant = current_value() + if current == null or current > expected: + return report_error(GdAssertMessages.error_is_value(Comparator.LESS_EQUAL, current, expected)) + return report_success() + + +func is_greater(expected :Variant) -> GdUnitVectorAssert: + if not _validate_is_vector_type(expected): + return self + var current :Variant = current_value() + if current == null or current <= expected: + return report_error(GdAssertMessages.error_is_value(Comparator.GREATER_THAN, current, expected)) + return report_success() + + +func is_greater_equal(expected :Variant) -> GdUnitVectorAssert: + if not _validate_is_vector_type(expected): + return self + var current :Variant = current_value() + if current == null or current < expected: + return report_error(GdAssertMessages.error_is_value(Comparator.GREATER_EQUAL, current, expected)) + return report_success() + + +func is_between(from :Variant, to :Variant) -> GdUnitVectorAssert: + if not _validate_is_vector_type(from) or not _validate_is_vector_type(to): + return self + var current :Variant = current_value() + if current == null or not (current >= from and current <= to): + return report_error(GdAssertMessages.error_is_value(Comparator.BETWEEN_EQUAL, current, from, to)) + return report_success() + + +func is_not_between(from :Variant, to :Variant) -> GdUnitVectorAssert: + if not _validate_is_vector_type(from) or not _validate_is_vector_type(to): + return self + var current :Variant = current_value() + if (current != null and current >= from and current <= to): + return report_error(GdAssertMessages.error_is_value(Comparator.NOT_BETWEEN_EQUAL, current, from, to)) + return report_success() diff --git a/addons/gdUnit4/src/asserts/GdUnitVectorAssertImpl.gd.uid b/addons/gdUnit4/src/asserts/GdUnitVectorAssertImpl.gd.uid new file mode 100644 index 0000000..6ca735c --- /dev/null +++ b/addons/gdUnit4/src/asserts/GdUnitVectorAssertImpl.gd.uid @@ -0,0 +1 @@ +uid://dxyx0rdumvvu8 diff --git a/addons/gdUnit4/src/asserts/ValueProvider.gd b/addons/gdUnit4/src/asserts/ValueProvider.gd new file mode 100644 index 0000000..be01f70 --- /dev/null +++ b/addons/gdUnit4/src/asserts/ValueProvider.gd @@ -0,0 +1,10 @@ +# base interface for assert value provider +class_name ValueProvider +extends RefCounted + +func get_value() -> Variant: + return null + + +func dispose() -> void: + pass diff --git a/addons/gdUnit4/src/asserts/ValueProvider.gd.uid b/addons/gdUnit4/src/asserts/ValueProvider.gd.uid new file mode 100644 index 0000000..5eee73b --- /dev/null +++ b/addons/gdUnit4/src/asserts/ValueProvider.gd.uid @@ -0,0 +1 @@ +uid://bct18w8cw1xxd diff --git a/addons/gdUnit4/src/cmd/CmdArgumentParser.gd b/addons/gdUnit4/src/cmd/CmdArgumentParser.gd new file mode 100644 index 0000000..aa02319 --- /dev/null +++ b/addons/gdUnit4/src/cmd/CmdArgumentParser.gd @@ -0,0 +1,62 @@ +class_name CmdArgumentParser +extends RefCounted + +var _options :CmdOptions +var _tool_name :String +var _parsed_commands :Dictionary = Dictionary() + + +func _init(p_options :CmdOptions, p_tool_name :String) -> void: + _options = p_options + _tool_name = p_tool_name + + +func parse(args :Array, ignore_unknown_cmd := false) -> GdUnitResult: + _parsed_commands.clear() + + # parse until first program argument + while not args.is_empty(): + var arg :String = args.pop_front() + if arg.find(_tool_name) != -1: + break + + if args.is_empty(): + return GdUnitResult.empty() + + # now parse all arguments + while not args.is_empty(): + var cmd :String = args.pop_front() + var option := _options.get_option(cmd) + + if option: + if _parse_cmd_arguments(option, args) == -1: + return GdUnitResult.error("The '%s' command requires an argument!" % option.short_command()) + elif not ignore_unknown_cmd: + return GdUnitResult.error("Unknown '%s' command!" % cmd) + return GdUnitResult.success(_parsed_commands.values()) + + +func options() -> CmdOptions: + return _options + + +func _parse_cmd_arguments(option: CmdOption, args: Array) -> int: + var command_name := option.short_command() + var command: CmdCommand = _parsed_commands.get(command_name, CmdCommand.new(command_name)) + + if option.has_argument(): + if not option.is_argument_optional() and args.is_empty(): + return -1 + if _is_next_value_argument(args): + var value: String = args.pop_front() + command.add_argument(value) + elif not option.is_argument_optional(): + return -1 + _parsed_commands[command_name] = command + return 0 + + +func _is_next_value_argument(args: PackedStringArray) -> bool: + if args.is_empty(): + return false + return _options.get_option(args[0]) == null diff --git a/addons/gdUnit4/src/cmd/CmdArgumentParser.gd.uid b/addons/gdUnit4/src/cmd/CmdArgumentParser.gd.uid new file mode 100644 index 0000000..6b3ebf9 --- /dev/null +++ b/addons/gdUnit4/src/cmd/CmdArgumentParser.gd.uid @@ -0,0 +1 @@ +uid://c2b2qn3d88c3v diff --git a/addons/gdUnit4/src/cmd/CmdCommand.gd b/addons/gdUnit4/src/cmd/CmdCommand.gd new file mode 100644 index 0000000..92e8c1f --- /dev/null +++ b/addons/gdUnit4/src/cmd/CmdCommand.gd @@ -0,0 +1,27 @@ +class_name CmdCommand +extends RefCounted + +var _name: String +var _arguments: PackedStringArray + + +func _init(p_name :String, p_arguments := []) -> void: + _name = p_name + _arguments = PackedStringArray(p_arguments) + + +func name() -> String: + return _name + + +func arguments() -> PackedStringArray: + return _arguments + + +func add_argument(arg :String) -> void: + @warning_ignore("return_value_discarded") + _arguments.append(arg) + + +func _to_string() -> String: + return "%s:%s" % [_name, ", ".join(_arguments)] diff --git a/addons/gdUnit4/src/cmd/CmdCommand.gd.uid b/addons/gdUnit4/src/cmd/CmdCommand.gd.uid new file mode 100644 index 0000000..b6f1a31 --- /dev/null +++ b/addons/gdUnit4/src/cmd/CmdCommand.gd.uid @@ -0,0 +1 @@ +uid://8ufljsi4mj40 diff --git a/addons/gdUnit4/src/cmd/CmdCommandHandler.gd b/addons/gdUnit4/src/cmd/CmdCommandHandler.gd new file mode 100644 index 0000000..2a7ed55 --- /dev/null +++ b/addons/gdUnit4/src/cmd/CmdCommandHandler.gd @@ -0,0 +1,136 @@ +class_name CmdCommandHandler +extends RefCounted + +const CB_SINGLE_ARG = 0 +const CB_MULTI_ARGS = 1 +const NO_CB := Callable() + +var _cmd_options :CmdOptions +# holds the command callbacks by key::String and value: [, ]:Array +# Dictionary[String, Array[Callback] +var _command_cbs :Dictionary + + + +func _init(cmd_options: CmdOptions) -> void: + _cmd_options = cmd_options + + +# register a callback function for given command +# cmd_name short name of the command +# fr_arg a funcref to a function with a single argument +func register_cb(cmd_name: String, cb: Callable) -> CmdCommandHandler: + var registered_cb: Array = _command_cbs.get(cmd_name, [NO_CB, NO_CB]) + if registered_cb[CB_SINGLE_ARG]: + push_error("A function for command '%s' is already registered!" % cmd_name) + return self + + if not _validate_cb_signature(cb, TYPE_STRING): + push_error( + ("The callback '%s:%s' for command '%s' has invalid function signature. " + +"The callback signature must be 'func name(value: PackedStringArray)'") + % [cb.get_object().get_class(), cb.get_method(), cmd_name]) + return null + + registered_cb[CB_SINGLE_ARG] = cb + _command_cbs[cmd_name] = registered_cb + return self + + +# register a callback function for given command +# cb a funcref to a function with a variable number of arguments but expects all parameters to be passed via a single Array. +func register_cbv(cmd_name: String, cb: Callable) -> CmdCommandHandler: + var registered_cb: Array = _command_cbs.get(cmd_name, [NO_CB, NO_CB]) + if registered_cb[CB_MULTI_ARGS]: + push_error("A function for command '%s' is already registered!" % cmd_name) + return self + + if not _validate_cb_signature(cb, TYPE_PACKED_STRING_ARRAY): + push_error( + ("The callback '%s:%s' for command '%s' has invalid function signature. " + +"The callback signature must be 'func name(value: PackedStringArray)'") + % [cb.get_object().get_class(), cb.get_method(), cmd_name]) + return null + + registered_cb[CB_MULTI_ARGS] = cb + _command_cbs[cmd_name] = registered_cb + return self + + +func _validate() -> GdUnitResult: + var errors := PackedStringArray() + # Dictionary[StringName, String] + var registered_cbs := Dictionary() + + for cmd_name in _command_cbs.keys() as Array[String]: + var cb: Callable = (_command_cbs[cmd_name][CB_SINGLE_ARG] + if _command_cbs[cmd_name][CB_SINGLE_ARG] + else _command_cbs[cmd_name][CB_MULTI_ARGS]) + if cb != NO_CB and not cb.is_valid(): + @warning_ignore("return_value_discarded") + errors.append("Invalid function reference for command '%s', Check the function reference!" % cmd_name) + if _cmd_options.get_option(cmd_name) == null: + @warning_ignore("return_value_discarded") + errors.append("The command '%s' is unknown, verify your CmdOptions!" % cmd_name) + # verify for multiple registered command callbacks + if cb != NO_CB: + var cb_method := cb.get_method() + if registered_cbs.has(cb_method): + var already_registered_cmd :String = registered_cbs[cb_method] + @warning_ignore("return_value_discarded") + errors.append("The function reference '%s' already registerd for command '%s'!" % [cb_method, already_registered_cmd]) + else: + registered_cbs[cb_method] = cmd_name + if errors.is_empty(): + return GdUnitResult.success(true) + return GdUnitResult.error("\n".join(errors)) + + +func execute(commands: Array[CmdCommand]) -> GdUnitResult: + var result := _validate() + if result.is_error(): + return result + for cmd in commands: + var cmd_name := cmd.name() + if _command_cbs.has(cmd_name): + var cb_s: Callable = _command_cbs.get(cmd_name)[CB_SINGLE_ARG] + var arguments := cmd.arguments() + var cmd_option := _cmd_options.get_option(cmd_name) + + if arguments.is_empty(): + cb_s.call() + elif arguments.size() > 1: + var cb_m: Callable = _command_cbs.get(cmd_name)[CB_MULTI_ARGS] + cb_m.call(arguments) + else: + if cmd_option.type() == TYPE_BOOL: + cb_s.call(true if arguments[0] == "true" else false) + else: + cb_s.call(arguments[0]) + + return GdUnitResult.success(true) + + +func _validate_cb_signature(cb: Callable, arg_type: int) -> bool: + for m in cb.get_object().get_method_list(): + if m["name"] == cb.get_method(): + @warning_ignore("unsafe_cast") + return _validate_func_arguments(m["args"] as Array, arg_type) + return true + + +func _validate_func_arguments(arguments: Array, arg_type: int) -> bool: + # validate we have a single argument + if arguments.size() > 1: + return false + # a cb with no arguments is also valid + if arguments.size() == 0: + return true + # validate argument type + var arg: Dictionary = arguments[0] + @warning_ignore("unsafe_cast") + if arg["usage"] as int == PROPERTY_USAGE_NIL_IS_VARIANT: + return true + if arg["type"] != arg_type: + return false + return true diff --git a/addons/gdUnit4/src/cmd/CmdCommandHandler.gd.uid b/addons/gdUnit4/src/cmd/CmdCommandHandler.gd.uid new file mode 100644 index 0000000..ecebe9f --- /dev/null +++ b/addons/gdUnit4/src/cmd/CmdCommandHandler.gd.uid @@ -0,0 +1 @@ +uid://d0b2bvfg8av2f diff --git a/addons/gdUnit4/src/cmd/CmdOption.gd b/addons/gdUnit4/src/cmd/CmdOption.gd new file mode 100644 index 0000000..a4982de --- /dev/null +++ b/addons/gdUnit4/src/cmd/CmdOption.gd @@ -0,0 +1,61 @@ +class_name CmdOption +extends RefCounted + + +var _commands :PackedStringArray +var _help :String +var _description :String +var _type :int +var _arg_optional :bool = false + + +# constructs a command option by given arguments +# commands : a string with comma separated list of available commands begining with the short form +# help: a help text show howto use +# description: a full description of the command +# type: the argument type +# arg_optional: defines of the argument optional +func _init(p_commands :String, p_help :String, p_description :String, p_type :int = TYPE_NIL, p_arg_optional :bool = false) -> void: + _commands = p_commands.replace(" ", "").replace("\t", "").split(",") + _help = p_help + _description = p_description + _type = p_type + _arg_optional = p_arg_optional + + +func commands() -> PackedStringArray: + return _commands + + +func short_command() -> String: + return _commands[0] + + +func help() -> String: + return _help + + +func description() -> String: + return _description + + +func type() -> int: + return _type + + +func is_argument_optional() -> bool: + return _arg_optional + + +func has_argument() -> bool: + return _type != TYPE_NIL + + +func describe() -> String: + if help().is_empty(): + return " %-32s %s \n" % [commands(), description()] + return " %-32s %s \n %-32s %s\n" % [commands(), description(), "", help()] + + +func _to_string() -> String: + return describe() diff --git a/addons/gdUnit4/src/cmd/CmdOption.gd.uid b/addons/gdUnit4/src/cmd/CmdOption.gd.uid new file mode 100644 index 0000000..b9304ca --- /dev/null +++ b/addons/gdUnit4/src/cmd/CmdOption.gd.uid @@ -0,0 +1 @@ +uid://hps2c4og40yu diff --git a/addons/gdUnit4/src/cmd/CmdOptions.gd b/addons/gdUnit4/src/cmd/CmdOptions.gd new file mode 100644 index 0000000..c610529 --- /dev/null +++ b/addons/gdUnit4/src/cmd/CmdOptions.gd @@ -0,0 +1,31 @@ +class_name CmdOptions +extends RefCounted + + +var _default_options :Array[CmdOption] +var _advanced_options :Array[CmdOption] + + +func _init(p_options :Array[CmdOption] = [], p_advanced_options :Array[CmdOption] = []) -> void: + # default help options + _default_options = p_options + _advanced_options = p_advanced_options + + +func default_options() -> Array[CmdOption]: + return _default_options + + +func advanced_options() -> Array[CmdOption]: + return _advanced_options + + +func options() -> Array[CmdOption]: + return default_options() + advanced_options() + + +func get_option(cmd :String) -> CmdOption: + for option in options(): + if Array(option.commands()).has(cmd): + return option + return null diff --git a/addons/gdUnit4/src/cmd/CmdOptions.gd.uid b/addons/gdUnit4/src/cmd/CmdOptions.gd.uid new file mode 100644 index 0000000..37d5dc6 --- /dev/null +++ b/addons/gdUnit4/src/cmd/CmdOptions.gd.uid @@ -0,0 +1 @@ +uid://b28ifyiobyc3b diff --git a/addons/gdUnit4/src/core/GdArrayTools.gd b/addons/gdUnit4/src/core/GdArrayTools.gd new file mode 100644 index 0000000..74f0e17 --- /dev/null +++ b/addons/gdUnit4/src/core/GdArrayTools.gd @@ -0,0 +1,127 @@ +## Small helper tool to work with Godot Arrays +class_name GdArrayTools +extends RefCounted + + +const max_elements := 32 +const ARRAY_TYPES := [ + TYPE_ARRAY, + TYPE_PACKED_BYTE_ARRAY, + TYPE_PACKED_INT32_ARRAY, + TYPE_PACKED_INT64_ARRAY, + TYPE_PACKED_FLOAT32_ARRAY, + TYPE_PACKED_FLOAT64_ARRAY, + TYPE_PACKED_STRING_ARRAY, + TYPE_PACKED_VECTOR2_ARRAY, + TYPE_PACKED_VECTOR3_ARRAY, + TYPE_PACKED_VECTOR4_ARRAY, + TYPE_PACKED_COLOR_ARRAY +] + + +static func is_array_type(value: Variant) -> bool: + return is_type_array(typeof(value)) + + +static func is_type_array(type :int) -> bool: + return type in ARRAY_TYPES + + +## Filters an array by given value[br] +## If the given value not an array it returns null, will remove all occurence of given value. +static func filter_value(array: Variant, value: Variant) -> Variant: + if not is_array_type(array): + return null + + @warning_ignore("unsafe_method_access") + var filtered_array: Variant = array.duplicate() + @warning_ignore("unsafe_method_access") + var index: int = filtered_array.find(value) + while index != -1: + @warning_ignore("unsafe_method_access") + filtered_array.remove_at(index) + @warning_ignore("unsafe_method_access") + index = filtered_array.find(value) + return filtered_array + + +## Groups an array by a custom key selector +## The function should take an item and return the group key +static func group_by(array: Array, key_selector: Callable) -> Dictionary: + var result := {} + + for item: Variant in array: + var group_key: Variant = key_selector.call(item) + var values: Array = result.get_or_add(group_key, []) + values.append(item) + + return result + + +## Erases a value from given array by using equals(l,r) to find the element to erase +static func erase_value(array :Array, value :Variant) -> void: + for element :Variant in array: + if GdObjects.equals(element, value): + array.erase(element) + + +## Scans for the array build in type on a untyped array[br] +## Returns the buildin type by scan all values and returns the type if all values has the same type. +## If the values has different types TYPE_VARIANT is returend +static func scan_typed(array :Array) -> int: + if array.is_empty(): + return TYPE_NIL + var actual_type := GdObjects.TYPE_VARIANT + for value :Variant in array: + var current_type := typeof(value) + if not actual_type in [GdObjects.TYPE_VARIANT, current_type]: + return GdObjects.TYPE_VARIANT + actual_type = current_type + return actual_type + + +## Converts given array into a string presentation.[br] +## This function is different to the original Godot str() implementation. +## The string presentaion contains fullquallified typed informations. +##[br] +## Examples: +## [codeblock] +## # will result in PackedString(["a", "b"]) +## GdArrayTools.as_string(PackedStringArray("a", "b")) +## # will result in PackedString(["a", "b"]) +## GdArrayTools.as_string(PackedColorArray(Color.RED, COLOR.GREEN)) +## [/codeblock] +static func as_string(elements: Variant, encode_value := true) -> String: + var delemiter := ", " + if elements == null: + return "" + @warning_ignore("unsafe_cast") + if (elements as Array).is_empty(): + return "" + var prefix := _typeof_as_string(elements) if encode_value else "" + var formatted := "" + var index := 0 + for element :Variant in elements: + if max_elements != -1 and index > max_elements: + return prefix + "[" + formatted + delemiter + "...]" + if formatted.length() > 0 : + formatted += delemiter + formatted += GdDefaultValueDecoder.decode(element) if encode_value else str(element) + index += 1 + return prefix + "[" + formatted + "]" + + +static func has_same_content(current: Array, other: Array) -> bool: + if current.size() != other.size(): return false + for element: Variant in current: + if not other.has(element): return false + if current.count(element) != other.count(element): return false + return true + + +static func _typeof_as_string(value :Variant) -> String: + var type := typeof(value) + # for untyped array we retun empty string + if type == TYPE_ARRAY: + return "" + return GdObjects.typeof_as_string(value) diff --git a/addons/gdUnit4/src/core/GdArrayTools.gd.uid b/addons/gdUnit4/src/core/GdArrayTools.gd.uid new file mode 100644 index 0000000..3bd11b4 --- /dev/null +++ b/addons/gdUnit4/src/core/GdArrayTools.gd.uid @@ -0,0 +1 @@ +uid://dja3iem04c17x diff --git a/addons/gdUnit4/src/core/GdDiffTool.gd b/addons/gdUnit4/src/core/GdDiffTool.gd new file mode 100644 index 0000000..5131df7 --- /dev/null +++ b/addons/gdUnit4/src/core/GdDiffTool.gd @@ -0,0 +1,224 @@ +# Myers' Diff Algorithm implementation +# Based on "An O(ND) Difference Algorithm and Its Variations" by Eugene W. Myers +class_name GdDiffTool +extends RefCounted + + +const DIV_ADD :int = 214 +const DIV_SUB :int = 215 + + +class Edit: + enum Type { EQUAL, INSERT, DELETE } + var type: Type + var character: int + + func _init(t: Type, chr: int) -> void: + type = t + character = chr + + +# Main entry point - returns [ldiff, rdiff] +static func string_diff(left: Variant, right: Variant) -> Array[PackedInt32Array]: + var lb := PackedInt32Array() if left == null else str(left).to_utf32_buffer().to_int32_array() + var rb := PackedInt32Array() if right == null else str(right).to_utf32_buffer().to_int32_array() + + # Early exit for identical strings + if lb == rb: + return [lb.duplicate(), rb.duplicate()] + + var edits := _myers_diff(lb, rb) + return _edits_to_diff_format(edits) + + +# Core Myers' algorithm +static func _myers_diff(a: PackedInt32Array, b: PackedInt32Array) -> Array[Edit]: + var n := a.size() + var m := b.size() + var max_d := n + m + + # V array stores the furthest reaching x coordinate for each k-line + # We need indices from -max_d to max_d, so we offset by max_d + var v := PackedInt32Array() + v.resize(2 * max_d + 1) + v.fill(-1) + v[max_d + 1] = 0 # k=1 starts at x=0 + + var trace := [] # Store V arrays for each d to backtrack later + + # Find the edit distance + for d in range(0, max_d + 1): + # Store current V for backtracking + trace.append(v.duplicate()) + + for k in range(-d, d + 1, 2): + var k_offset := k + max_d + + # Decide whether to move down or right + var x: int + if k == -d or (k != d and v[k_offset - 1] < v[k_offset + 1]): + x = v[k_offset + 1] # Move down (insert from b) + else: + x = v[k_offset - 1] + 1 # Move right (delete from a) + + var y := x - k + + # Follow diagonal as far as possible (matching characters) + while x < n and y < m and a[x] == b[y]: + x += 1 + y += 1 + + v[k_offset] = x + + # Check if we've reached the end + if x >= n and y >= m: + return _backtrack(a, b, trace, d, max_d) + + # Should never reach here for valid inputs + return [] + + +# Backtrack through the edit graph to build the edit script +static func _backtrack(a: PackedInt32Array, b: PackedInt32Array, trace: Array, d: int, max_d: int) -> Array[Edit]: + var edits: Array[Edit] = [] + var x := a.size() + var y := b.size() + + # Walk backwards through each d value + for depth in range(d, -1, -1): + var v: PackedInt32Array = trace[depth] + var k := x - y + var k_offset := k + max_d + + # Determine previous k + var prev_k: int + if k == -depth or (k != depth and v[k_offset - 1] < v[k_offset + 1]): + prev_k = k + 1 + else: + prev_k = k - 1 + + var prev_k_offset := prev_k + max_d + var prev_x := v[prev_k_offset] + var prev_y := prev_x - prev_k + + # Extract diagonal (equal) characters + while x > prev_x and y > prev_y: + x -= 1 + y -= 1 + #var char_array := PackedInt32Array([a[x]]) + edits.insert(0, Edit.new(Edit.Type.EQUAL, a[x])) + + # Record the edit operation + if depth > 0: + if x == prev_x: + # Insert from b + y -= 1 + #var char_array := PackedInt32Array([b[y]]) + edits.insert(0, Edit.new(Edit.Type.INSERT, b[y])) + else: + # Delete from a + x -= 1 + #var char_array := PackedInt32Array([a[x]]) + edits.insert(0, Edit.new(Edit.Type.DELETE, a[x])) + + return edits + + +# Convert edit script to the DIV_ADD/DIV_SUB format +static func _edits_to_diff_format(edits: Array[Edit]) -> Array[PackedInt32Array]: + var ldiff := PackedInt32Array() + var rdiff := PackedInt32Array() + + for edit in edits: + match edit.type: + Edit.Type.EQUAL: + ldiff.append(edit.character) + rdiff.append(edit.character) + Edit.Type.INSERT: + ldiff.append(DIV_ADD) + ldiff.append(edit.character) + rdiff.append(DIV_SUB) + rdiff.append(edit.character) + Edit.Type.DELETE: + ldiff.append(DIV_SUB) + ldiff.append(edit.character) + rdiff.append(DIV_ADD) + rdiff.append(edit.character) + + return [ldiff, rdiff] + + +# prototype +static func longestCommonSubsequence(text1 :String, text2 :String) -> PackedStringArray: + var text1Words := text1.split(" ") + var text2Words := text2.split(" ") + var text1WordCount := text1Words.size() + var text2WordCount := text2Words.size() + var solutionMatrix := Array() + for i in text1WordCount+1: + var ar := Array() + for n in text2WordCount+1: + ar.append(0) + solutionMatrix.append(ar) + + for i in range(text1WordCount-1, 0, -1): + for j in range(text2WordCount-1, 0, -1): + if text1Words[i] == text2Words[j]: + solutionMatrix[i][j] = solutionMatrix[i + 1][j + 1] + 1; + else: + solutionMatrix[i][j] = max(solutionMatrix[i + 1][j], solutionMatrix[i][j + 1]); + + var i := 0 + var j := 0 + var lcsResultList := PackedStringArray(); + while (i < text1WordCount && j < text2WordCount): + if text1Words[i] == text2Words[j]: + @warning_ignore("return_value_discarded") + lcsResultList.append(text2Words[j]) + i += 1 + j += 1 + else: if (solutionMatrix[i + 1][j] >= solutionMatrix[i][j + 1]): + i += 1 + else: + j += 1 + return lcsResultList + + +static func markTextDifferences(text1 :String, text2 :String, lcsList :PackedStringArray, insertColor :Color, deleteColor:Color) -> String: + var stringBuffer := "" + if text1 == null and lcsList == null: + return stringBuffer + + var text1Words := text1.split(" ") + var text2Words := text2.split(" ") + var i := 0 + var j := 0 + var word1LastIndex := 0 + var word2LastIndex := 0 + for k in lcsList.size(): + while i < text1Words.size() and j < text2Words.size(): + if text1Words[i] == lcsList[k] and text2Words[j] == lcsList[k]: + stringBuffer += "" + lcsList[k] + " " + word1LastIndex = i + 1 + word2LastIndex = j + 1 + i = text1Words.size() + j = text2Words.size() + + else: if text1Words[i] != lcsList[k]: + while i < text1Words.size() and text1Words[i] != lcsList[k]: + stringBuffer += "" + text1Words[i] + " " + i += 1 + else: if text2Words[j] != lcsList[k]: + while j < text2Words.size() and text2Words[j] != lcsList[k]: + stringBuffer += "" + text2Words[j] + " " + j += 1 + i = word1LastIndex + j = word2LastIndex + + while word1LastIndex < text1Words.size(): + stringBuffer += "" + text1Words[word1LastIndex] + " " + word1LastIndex += 1 + while word2LastIndex < text2Words.size(): + stringBuffer += "" + text2Words[word2LastIndex] + " " + word2LastIndex += 1 + return stringBuffer diff --git a/addons/gdUnit4/src/core/GdDiffTool.gd.uid b/addons/gdUnit4/src/core/GdDiffTool.gd.uid new file mode 100644 index 0000000..46d5d82 --- /dev/null +++ b/addons/gdUnit4/src/core/GdDiffTool.gd.uid @@ -0,0 +1 @@ +uid://c7anyxojp1a63 diff --git a/addons/gdUnit4/src/core/GdObjects.gd b/addons/gdUnit4/src/core/GdObjects.gd new file mode 100644 index 0000000..4fec24e --- /dev/null +++ b/addons/gdUnit4/src/core/GdObjects.gd @@ -0,0 +1,719 @@ +# This is a helper class to compare two objects by equals +class_name GdObjects +extends Resource + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") + + +# introduced with Godot 4.3.beta1 +const TYPE_VOID = 1000 +const TYPE_VARARG = 1001 +const TYPE_VARIANT = 1002 +const TYPE_FUNC = 1003 +const TYPE_FUZZER = 1004 +# missing Godot types +const TYPE_NODE = 2001 +const TYPE_CONTROL = 2002 +const TYPE_CANVAS = 2003 +const TYPE_ENUM = 2004 + + +const TYPE_AS_STRING_MAPPINGS := { + TYPE_NIL: "null", + TYPE_BOOL: "bool", + TYPE_INT: "int", + TYPE_FLOAT: "float", + TYPE_STRING: "String", + TYPE_VECTOR2: "Vector2", + TYPE_VECTOR2I: "Vector2i", + TYPE_RECT2: "Rect2", + TYPE_RECT2I: "Rect2i", + TYPE_VECTOR3: "Vector3", + TYPE_VECTOR3I: "Vector3i", + TYPE_TRANSFORM2D: "Transform2D", + TYPE_VECTOR4: "Vector4", + TYPE_VECTOR4I: "Vector4i", + TYPE_PLANE: "Plane", + TYPE_QUATERNION: "Quaternion", + TYPE_AABB: "AABB", + TYPE_BASIS: "Basis", + TYPE_TRANSFORM3D: "Transform3D", + TYPE_PROJECTION: "Projection", + TYPE_COLOR: "Color", + TYPE_STRING_NAME: "StringName", + TYPE_NODE_PATH: "NodePath", + TYPE_RID: "RID", + TYPE_OBJECT: "Object", + TYPE_CALLABLE: "Callable", + TYPE_SIGNAL: "Signal", + TYPE_DICTIONARY: "Dictionary", + TYPE_ARRAY: "Array", + TYPE_PACKED_BYTE_ARRAY: "PackedByteArray", + TYPE_PACKED_INT32_ARRAY: "PackedInt32Array", + TYPE_PACKED_INT64_ARRAY: "PackedInt64Array", + TYPE_PACKED_FLOAT32_ARRAY: "PackedFloat32Array", + TYPE_PACKED_FLOAT64_ARRAY: "PackedFloat64Array", + TYPE_PACKED_STRING_ARRAY: "PackedStringArray", + TYPE_PACKED_VECTOR2_ARRAY: "PackedVector2Array", + TYPE_PACKED_VECTOR3_ARRAY: "PackedVector3Array", + TYPE_PACKED_VECTOR4_ARRAY: "PackedVector4Array", + TYPE_PACKED_COLOR_ARRAY: "PackedColorArray", + TYPE_VOID: "void", + TYPE_VARARG: "VarArg", + TYPE_FUNC: "Func", + TYPE_FUZZER: "Fuzzer", + TYPE_VARIANT: "Variant" +} + + +const NOTIFICATION_AS_STRING_MAPPINGS := { + TYPE_OBJECT: { + Object.NOTIFICATION_POSTINITIALIZE : "POSTINITIALIZE", + Object.NOTIFICATION_PREDELETE: "PREDELETE", + EditorSettings.NOTIFICATION_EDITOR_SETTINGS_CHANGED: "EDITOR_SETTINGS_CHANGED", + }, + TYPE_NODE: { + Node.NOTIFICATION_ENTER_TREE : "ENTER_TREE", + Node.NOTIFICATION_EXIT_TREE: "EXIT_TREE", + Node.NOTIFICATION_CHILD_ORDER_CHANGED: "CHILD_ORDER_CHANGED", + Node.NOTIFICATION_READY: "READY", + Node.NOTIFICATION_PAUSED: "PAUSED", + Node.NOTIFICATION_UNPAUSED: "UNPAUSED", + Node.NOTIFICATION_PHYSICS_PROCESS: "PHYSICS_PROCESS", + Node.NOTIFICATION_PROCESS: "PROCESS", + Node.NOTIFICATION_PARENTED: "PARENTED", + Node.NOTIFICATION_UNPARENTED: "UNPARENTED", + Node.NOTIFICATION_SCENE_INSTANTIATED: "INSTANCED", + Node.NOTIFICATION_DRAG_BEGIN: "DRAG_BEGIN", + Node.NOTIFICATION_DRAG_END: "DRAG_END", + Node.NOTIFICATION_PATH_RENAMED: "PATH_CHANGED", + Node.NOTIFICATION_INTERNAL_PROCESS: "INTERNAL_PROCESS", + Node.NOTIFICATION_INTERNAL_PHYSICS_PROCESS: "INTERNAL_PHYSICS_PROCESS", + Node.NOTIFICATION_POST_ENTER_TREE: "POST_ENTER_TREE", + Node.NOTIFICATION_WM_MOUSE_ENTER: "WM_MOUSE_ENTER", + Node.NOTIFICATION_WM_MOUSE_EXIT: "WM_MOUSE_EXIT", + Node.NOTIFICATION_APPLICATION_FOCUS_IN: "WM_FOCUS_IN", + Node.NOTIFICATION_APPLICATION_FOCUS_OUT: "WM_FOCUS_OUT", + #Node.NOTIFICATION_WM_QUIT_REQUEST: "WM_QUIT_REQUEST", + Node.NOTIFICATION_WM_GO_BACK_REQUEST: "WM_GO_BACK_REQUEST", + Node.NOTIFICATION_WM_WINDOW_FOCUS_OUT: "WM_UNFOCUS_REQUEST", + Node.NOTIFICATION_OS_MEMORY_WARNING: "OS_MEMORY_WARNING", + Node.NOTIFICATION_TRANSLATION_CHANGED: "TRANSLATION_CHANGED", + Node.NOTIFICATION_WM_ABOUT: "WM_ABOUT", + Node.NOTIFICATION_CRASH: "CRASH", + Node.NOTIFICATION_OS_IME_UPDATE: "OS_IME_UPDATE", + Node.NOTIFICATION_APPLICATION_RESUMED: "APP_RESUMED", + Node.NOTIFICATION_APPLICATION_PAUSED: "APP_PAUSED", + Node3D.NOTIFICATION_TRANSFORM_CHANGED: "TRANSFORM_CHANGED", + Node3D.NOTIFICATION_ENTER_WORLD: "ENTER_WORLD", + Node3D.NOTIFICATION_EXIT_WORLD: "EXIT_WORLD", + Node3D.NOTIFICATION_VISIBILITY_CHANGED: "VISIBILITY_CHANGED", + Skeleton3D.NOTIFICATION_UPDATE_SKELETON: "UPDATE_SKELETON", + CanvasItem.NOTIFICATION_DRAW: "DRAW", + CanvasItem.NOTIFICATION_VISIBILITY_CHANGED: "VISIBILITY_CHANGED", + CanvasItem.NOTIFICATION_ENTER_CANVAS: "ENTER_CANVAS", + CanvasItem.NOTIFICATION_EXIT_CANVAS: "EXIT_CANVAS", + #Popup.NOTIFICATION_POST_POPUP: "POST_POPUP", + #Popup.NOTIFICATION_POPUP_HIDE: "POPUP_HIDE", + }, + TYPE_CONTROL : { + Object.NOTIFICATION_PREDELETE: "PREDELETE", + Container.NOTIFICATION_SORT_CHILDREN: "SORT_CHILDREN", + Control.NOTIFICATION_RESIZED: "RESIZED", + Control.NOTIFICATION_MOUSE_ENTER: "MOUSE_ENTER", + Control.NOTIFICATION_MOUSE_EXIT: "MOUSE_EXIT", + Control.NOTIFICATION_FOCUS_ENTER: "FOCUS_ENTER", + Control.NOTIFICATION_FOCUS_EXIT: "FOCUS_EXIT", + Control.NOTIFICATION_THEME_CHANGED: "THEME_CHANGED", + #Control.NOTIFICATION_MODAL_CLOSE: "MODAL_CLOSE", + Control.NOTIFICATION_SCROLL_BEGIN: "SCROLL_BEGIN", + Control.NOTIFICATION_SCROLL_END: "SCROLL_END", + } +} + + +enum COMPARE_MODE { + OBJECT_REFERENCE, + PARAMETER_DEEP_TEST +} + + +# prototype of better object to dictionary +static func obj2dict(obj: Object, hashed_objects := Dictionary()) -> Dictionary: + if obj == null: + return {} + var clazz_name := obj.get_class() + var dict := Dictionary() + var clazz_path := "" + + if is_instance_valid(obj) and obj.get_script() != null: + var script: Script = obj.get_script() + # handle build-in scripts + if script.resource_path != null and script.resource_path.contains(".tscn"): + var path_elements := script.resource_path.split(".tscn") + clazz_name = path_elements[0].get_file() + clazz_path = script.resource_path + else: + var d := inst_to_dict(obj) + clazz_path = d["@path"] + if d["@subpath"] != NodePath(""): + clazz_name = d["@subpath"] + dict["@inner_class"] = true + else: + clazz_name = clazz_path.get_file().replace(".gd", "") + dict["@path"] = clazz_path + + for property in obj.get_property_list(): + var property_name :String = property["name"] + var property_type :int = property["type"] + var property_value :Variant = obj.get(property_name) + if property_value is GDScript or property_value is Callable or property_value is RegEx: + continue + if (property["usage"] & PROPERTY_USAGE_SCRIPT_VARIABLE|PROPERTY_USAGE_DEFAULT + and not property["usage"] & PROPERTY_USAGE_CATEGORY + and not property["usage"] == 0): + if property_type == TYPE_OBJECT: + # prevent recursion + if hashed_objects.has(obj): + dict[property_name] = str(property_value) + continue + hashed_objects[obj] = true + @warning_ignore("unsafe_cast") + dict[property_name] = obj2dict(property_value as Object, hashed_objects) + else: + dict[property_name] = property_value + if obj is Node: + var childrens :Array = (obj as Node).get_children() + dict["childrens"] = childrens.map(func (child :Object) -> Dictionary: return obj2dict(child, hashed_objects)) + if obj is TreeItem: + var childrens :Array = (obj as TreeItem).get_children() + dict["childrens"] = childrens.map(func (child :Object) -> Dictionary: return obj2dict(child, hashed_objects)) + + return {"%s" % clazz_name : dict} + + +static func equals(obj_a :Variant, obj_b :Variant, case_sensitive :bool = false, compare_mode :COMPARE_MODE = COMPARE_MODE.PARAMETER_DEEP_TEST) -> bool: + return _equals(obj_a, obj_b, case_sensitive, compare_mode, [], 0) + + +static func equals_sorted(obj_a: Array[Variant], obj_b: Array[Variant], case_sensitive: bool = false, compare_mode: COMPARE_MODE = COMPARE_MODE.PARAMETER_DEEP_TEST) -> bool: + var a: Array[Variant] = obj_a.duplicate() + var b: Array[Variant] = obj_b.duplicate() + a.sort() + b.sort() + return equals(a, b, case_sensitive, compare_mode) + + +static func _equals(obj_a :Variant, obj_b :Variant, case_sensitive :bool, compare_mode :COMPARE_MODE, deep_stack :Array, stack_depth :int ) -> bool: + var type_a := typeof(obj_a) + var type_b := typeof(obj_b) + if stack_depth > 32: + prints("stack_depth", stack_depth, deep_stack) + push_error("GdUnit equals has max stack deep reached!") + return false + + # use argument matcher if requested + if is_instance_valid(obj_a) and obj_a is GdUnitArgumentMatcher: + @warning_ignore("unsafe_cast") + return (obj_a as GdUnitArgumentMatcher).is_match(obj_b) + if is_instance_valid(obj_b) and obj_b is GdUnitArgumentMatcher: + @warning_ignore("unsafe_cast") + return (obj_b as GdUnitArgumentMatcher).is_match(obj_a) + + stack_depth += 1 + # fast fail is different types + if not _is_type_equivalent(type_a, type_b): + return false + # is same instance + if obj_a == obj_b: + return true + # handle null values + if obj_a == null and obj_b != null: + return false + if obj_b == null and obj_a != null: + return false + + match type_a: + TYPE_OBJECT: + if deep_stack.has(obj_a) or deep_stack.has(obj_b): + return true + deep_stack.append(obj_a) + deep_stack.append(obj_b) + if compare_mode == COMPARE_MODE.PARAMETER_DEEP_TEST: + # fail fast + if not is_instance_valid(obj_a) or not is_instance_valid(obj_b): + return false + @warning_ignore("unsafe_method_access") + if obj_a.get_class() != obj_b.get_class(): + return false + @warning_ignore("unsafe_cast") + var a := obj2dict(obj_a as Object) + @warning_ignore("unsafe_cast") + var b := obj2dict(obj_b as Object) + return _equals(a, b, case_sensitive, compare_mode, deep_stack, stack_depth) + return obj_a == obj_b + + TYPE_ARRAY: + @warning_ignore("unsafe_method_access") + if obj_a.size() != obj_b.size(): + return false + @warning_ignore("unsafe_method_access") + for index :int in obj_a.size(): + if not _equals(obj_a[index], obj_b[index], case_sensitive, compare_mode, deep_stack, stack_depth): + return false + return true + + TYPE_DICTIONARY: + @warning_ignore("unsafe_method_access") + if obj_a.size() != obj_b.size(): + return false + @warning_ignore("unsafe_method_access") + for key :Variant in obj_a.keys(): + @warning_ignore("unsafe_method_access") + var value_a :Variant = obj_a[key] if obj_a.has(key) else null + @warning_ignore("unsafe_method_access") + var value_b :Variant = obj_b[key] if obj_b.has(key) else null + if not _equals(value_a, value_b, case_sensitive, compare_mode, deep_stack, stack_depth): + return false + return true + + TYPE_STRING: + if case_sensitive: + @warning_ignore("unsafe_method_access") + return obj_a.to_lower() == obj_b.to_lower() + else: + return obj_a == obj_b + return obj_a == obj_b + + +@warning_ignore("shadowed_variable_base_class") +static func notification_as_string(instance :Variant, notification :int) -> String: + var error := "Unknown notification: '%s' at instance: %s" % [notification, instance] + if instance is Node and NOTIFICATION_AS_STRING_MAPPINGS[TYPE_NODE].has(notification): + return NOTIFICATION_AS_STRING_MAPPINGS[TYPE_NODE].get(notification, error) + if instance is Control and NOTIFICATION_AS_STRING_MAPPINGS[TYPE_CONTROL].has(notification): + return NOTIFICATION_AS_STRING_MAPPINGS[TYPE_CONTROL].get(notification, error) + return NOTIFICATION_AS_STRING_MAPPINGS[TYPE_OBJECT].get(notification, error) + + +static func string_to_type(value :String) -> int: + for type :int in TYPE_AS_STRING_MAPPINGS.keys(): + if TYPE_AS_STRING_MAPPINGS.get(type) == value: + return type + return TYPE_NIL + + +static func to_camel_case(value :String) -> String: + var p := to_pascal_case(value) + if not p.is_empty(): + p[0] = p[0].to_lower() + return p + + +static func to_pascal_case(value :String) -> String: + return value.capitalize().replace(" ", "") + + +@warning_ignore("return_value_discarded") +static func to_snake_case(value :String) -> String: + var result := PackedStringArray() + for ch in value: + var lower_ch := ch.to_lower() + if ch != lower_ch and result.size() > 1: + result.append('_') + result.append(lower_ch) + return ''.join(result) + + +static func is_snake_case(value :String) -> bool: + for ch in value: + if ch == '_': + continue + if ch == ch.to_upper(): + return false + return true + + +static func type_as_string(type :int) -> String: + if type < TYPE_MAX: + return type_string(type) + return TYPE_AS_STRING_MAPPINGS.get(type, "Variant") + + +static func typeof_as_string(value :Variant) -> String: + return TYPE_AS_STRING_MAPPINGS.get(typeof(value), "Unknown type") + + +static func all_types() -> PackedInt32Array: + return PackedInt32Array(TYPE_AS_STRING_MAPPINGS.keys()) + + +static func string_as_typeof(type_name :String) -> int: + var type :Variant = TYPE_AS_STRING_MAPPINGS.find_key(type_name) + return type if type != null else TYPE_VARIANT + + +static func is_primitive_type(value :Variant) -> bool: + return typeof(value) in [TYPE_BOOL, TYPE_STRING, TYPE_STRING_NAME, TYPE_INT, TYPE_FLOAT] + + +static func _is_type_equivalent(type_a :int, type_b :int) -> bool: + # don't test for TYPE_STRING_NAME equivalenz + if type_a == TYPE_STRING_NAME or type_b == TYPE_STRING_NAME: + return true + if GdUnitSettings.is_strict_number_type_compare(): + return type_a == type_b + return ( + (type_a == TYPE_FLOAT and type_b == TYPE_INT) + or (type_a == TYPE_INT and type_b == TYPE_FLOAT) + or type_a == type_b) + + +static func is_engine_type(value :Variant) -> bool: + if value is GDScript or value is ScriptExtension: + return false + var obj: Object = value + if is_instance_valid(obj) and obj.has_method("is_class"): + return obj.is_class("GDScriptNativeClass") + return false + + +static func is_type(value :Variant) -> bool: + # is an build-in type + if typeof(value) != TYPE_OBJECT: + return false + # is a engine class type + if is_engine_type(value): + return true + # is a custom class type + @warning_ignore("unsafe_cast") + if value is GDScript and (value as GDScript).can_instantiate(): + return true + return false + + +static func _is_same(left :Variant, right :Variant) -> bool: + var left_type := -1 if left == null else typeof(left) + var right_type := -1 if right == null else typeof(right) + + # if typ different can't be the same + if left_type != right_type: + return false + if left_type == TYPE_OBJECT and right_type == TYPE_OBJECT: + @warning_ignore("unsafe_cast") + return (left as Object).get_instance_id() == (right as Object).get_instance_id() + return equals(left, right) + + +static func is_object(value :Variant) -> bool: + return typeof(value) == TYPE_OBJECT + + +static func is_script(value :Variant) -> bool: + return is_object(value) and value is Script + + +static func is_native_class(value :Variant) -> bool: + return is_object(value) and is_engine_type(value) + + +static func is_scene(value :Variant) -> bool: + return is_object(value) and value is PackedScene + + +static func is_scene_resource_path(value :Variant) -> bool: + @warning_ignore("unsafe_cast") + return value is String and (value as String).ends_with(".tscn") + + +static func is_singleton(value: Variant) -> bool: + if not is_instance_valid(value) or is_native_class(value): + return false + for name in Engine.get_singleton_list(): + @warning_ignore("unsafe_cast") + if (value as Object).is_class(name): + return true + return false + + +static func is_instance(value :Variant) -> bool: + if not is_instance_valid(value) or is_native_class(value): + return false + @warning_ignore("unsafe_cast") + if is_script(value) and (value as Script).get_instance_base_type() == "": + return true + if is_scene(value): + return true + @warning_ignore("unsafe_cast") + return not (value as Object).has_method('new') and not (value as Object).has_method('instance') + + +# only object form type Node and attached filename +static func is_instance_scene(instance :Variant) -> bool: + if instance is Node: + var node: Node = instance + return node.get_scene_file_path() != null and not node.get_scene_file_path().is_empty() + return false + + +static func can_be_instantiate(obj :Variant) -> bool: + if not obj or is_engine_type(obj): + return false + @warning_ignore("unsafe_cast") + return (obj as Object).has_method("new") + + +static func create_instance(clazz :Variant) -> GdUnitResult: + match typeof(clazz): + TYPE_OBJECT: + # test is given clazz already an instance + if is_instance(clazz): + return GdUnitResult.success(clazz) + @warning_ignore("unsafe_method_access") + return GdUnitResult.success(clazz.new()) + TYPE_STRING: + var clazz_name: String = clazz + if ClassDB.class_exists(clazz_name): + if Engine.has_singleton(clazz_name): + return GdUnitResult.error("Not allowed to create a instance for singelton '%s'." % clazz_name) + if not ClassDB.can_instantiate(clazz_name): + return GdUnitResult.error("Can't instance Engine class '%s'." % clazz_name) + return GdUnitResult.success(ClassDB.instantiate(clazz_name)) + else: + var clazz_path :String = extract_class_path(clazz_name)[0] + if not FileAccess.file_exists(clazz_path): + return GdUnitResult.error("Class '%s' not found." % clazz_name) + var script: GDScript = load(clazz_path) + if script != null: + return GdUnitResult.success(script.new()) + else: + return GdUnitResult.error("Can't create instance for '%s'." % clazz_name) + return GdUnitResult.error("Can't create instance for class '%s'." % str(clazz)) + + +## We do dispose 'GDScriptFunctionState' in a kacky style because the class is not visible anymore +static func dispose_function_state(func_state: Variant) -> void: + if func_state != null and str(func_state).contains("GDScriptFunctionState"): + @warning_ignore("unsafe_method_access") + func_state.completed.emit() + + +@warning_ignore("return_value_discarded") +static func extract_class_path(clazz :Variant) -> PackedStringArray: + var clazz_path := PackedStringArray() + if clazz is String: + @warning_ignore("unsafe_cast") + clazz_path.append(clazz as String) + return clazz_path + if is_instance(clazz): + # is instance a script instance? + var script: GDScript = clazz.script + if script != null: + return extract_class_path(script) + return clazz_path + + if clazz is GDScript: + var script: GDScript = clazz + if not script.resource_path.is_empty(): + clazz_path.append(script.resource_path) + return clazz_path + # if not found we go the expensive way and extract the path form the script by creating an instance + var arg_list := build_function_default_arguments(script, "_init") + var instance: Object = script.callv("new", arg_list) + var clazz_info := inst_to_dict(instance) + GdUnitTools.free_instance(instance) + @warning_ignore("unsafe_cast") + clazz_path.append(clazz_info["@path"] as String) + if clazz_info.has("@subpath"): + var sub_path :String = clazz_info["@subpath"] + if not sub_path.is_empty(): + var sub_paths := sub_path.split("/") + clazz_path += sub_paths + return clazz_path + return clazz_path + + +static func extract_class_name_from_class_path(clazz_path :PackedStringArray) -> String: + var base_clazz := clazz_path[0] + # return original class name if engine class + if ClassDB.class_exists(base_clazz): + return base_clazz + var clazz_name := to_pascal_case(base_clazz.get_basename().get_file()) + for path_index in range(1, clazz_path.size()): + clazz_name += "." + clazz_path[path_index] + return clazz_name + + +static func extract_class_name(clazz :Variant) -> GdUnitResult: + if clazz == null: + return GdUnitResult.error("Can't extract class name form a null value.") + + if is_instance(clazz): + # is instance a script instance? + var script: GDScript = clazz.script + if script != null: + return extract_class_name(script) + @warning_ignore("unsafe_cast") + return GdUnitResult.success((clazz as Object).get_class()) + + # extract name form full qualified class path + if clazz is String: + var clazz_name: String = clazz + if ClassDB.class_exists(clazz_name): + return GdUnitResult.success(clazz_name) + var source_script :GDScript = load(clazz_name) + clazz_name = GdScriptParser.new().get_class_name(source_script) + return GdUnitResult.success(to_pascal_case(clazz_name)) + + if is_primitive_type(clazz): + return GdUnitResult.error("Can't extract class name for an primitive '%s'" % type_as_string(typeof(clazz))) + + if is_script(clazz): + @warning_ignore("unsafe_cast") + if (clazz as Script).resource_path.is_empty(): + var class_path := extract_class_name_from_class_path(extract_class_path(clazz)) + return GdUnitResult.success(class_path); + return extract_class_name(clazz.resource_path) + + # need to create an instance for a class typ the extract the class name + @warning_ignore("unsafe_method_access") + var instance :Variant = clazz.new() + if instance == null: + return GdUnitResult.error("Can't create a instance for class '%s'" % str(clazz)) + var result := extract_class_name(instance) + @warning_ignore("return_value_discarded") + GdUnitTools.free_instance(instance) + return result + + +static func extract_inner_clazz_names(clazz_name :String, script_path :PackedStringArray) -> PackedStringArray: + var inner_classes := PackedStringArray() + + if ClassDB.class_exists(clazz_name): + return inner_classes + var script :GDScript = load(script_path[0]) + var map := script.get_script_constant_map() + for key :String in map.keys(): + var value :Variant = map.get(key) + if value is GDScript: + var class_path := extract_class_path(value) + @warning_ignore("return_value_discarded") + inner_classes.append(class_path[1]) + return inner_classes + + +static func extract_class_functions(clazz_name :String, script_path :PackedStringArray) -> Array: + if ClassDB.class_get_method_list(clazz_name): + return ClassDB.class_get_method_list(clazz_name) + + if not FileAccess.file_exists(script_path[0]): + return Array() + var script :GDScript = load(script_path[0]) + if script is GDScript: + # if inner class on class path we have to load the script from the script_constant_map + if script_path.size() == 2 and script_path[1] != "": + var inner_classes := script_path[1] + var map := script.get_script_constant_map() + script = map[inner_classes] + var clazz_functions :Array = script.get_method_list() + var base_clazz :String = script.get_instance_base_type() + if base_clazz: + return extract_class_functions(base_clazz, script_path) + return clazz_functions + return Array() + + +# scans all registert script classes for given +# if the class is public in the global space than return true otherwise false +# public class means the script class is defined by 'class_name ' +static func is_public_script_class(clazz_name :String) -> bool: + var script_classes:Array[Dictionary] = ProjectSettings.get_global_class_list() + for class_info in script_classes: + if class_info.has("class"): + if class_info["class"] == clazz_name: + return true + return false + + +static func build_function_default_arguments(script :GDScript, func_name :String) -> Array: + var arg_list := Array() + for func_sig in script.get_script_method_list(): + if func_sig["name"] == func_name: + var args :Array[Dictionary] = func_sig["args"] + for arg in args: + var value_type :int = arg["type"] + var default_value :Variant = default_value_by_type(value_type) + arg_list.append(default_value) + return arg_list + return arg_list + + +static func default_value_by_type(type :int) -> Variant: + assert(type < TYPE_MAX) + assert(type >= 0) + + match type: + TYPE_NIL: return null + TYPE_BOOL: return false + TYPE_INT: return 0 + TYPE_FLOAT: return 0.0 + TYPE_STRING: return "" + TYPE_VECTOR2: return Vector2.ZERO + TYPE_VECTOR2I: return Vector2i.ZERO + TYPE_VECTOR3: return Vector3.ZERO + TYPE_VECTOR3I: return Vector3i.ZERO + TYPE_VECTOR4: return Vector4.ZERO + TYPE_VECTOR4I: return Vector4i.ZERO + TYPE_RECT2: return Rect2() + TYPE_RECT2I: return Rect2i() + TYPE_TRANSFORM2D: return Transform2D() + TYPE_PLANE: return Plane() + TYPE_QUATERNION: return Quaternion() + TYPE_AABB: return AABB() + TYPE_BASIS: return Basis() + TYPE_TRANSFORM3D: return Transform3D() + TYPE_COLOR: return Color() + TYPE_NODE_PATH: return NodePath() + TYPE_RID: return RID() + TYPE_OBJECT: return null + TYPE_CALLABLE: return Callable() + TYPE_ARRAY: return [] + TYPE_DICTIONARY: return {} + TYPE_PACKED_BYTE_ARRAY: return PackedByteArray() + TYPE_PACKED_COLOR_ARRAY: return PackedColorArray() + TYPE_PACKED_INT32_ARRAY: return PackedInt32Array() + TYPE_PACKED_INT64_ARRAY: return PackedInt64Array() + TYPE_PACKED_FLOAT32_ARRAY: return PackedFloat32Array() + TYPE_PACKED_FLOAT64_ARRAY: return PackedFloat64Array() + TYPE_PACKED_STRING_ARRAY: return PackedStringArray() + TYPE_PACKED_VECTOR2_ARRAY: return PackedVector2Array() + TYPE_PACKED_VECTOR3_ARRAY: return PackedVector3Array() + + push_error("Can't determine a default value for type: '%s', Please create a Bug issue and attach the stacktrace please." % type) + return null + + +static func find_nodes_by_class(root: Node, cls: String, recursive: bool = false) -> Array[Node]: + if not recursive: + return _find_nodes_by_class_no_rec(root, cls) + return _find_nodes_by_class(root, cls) + + +static func _find_nodes_by_class_no_rec(parent: Node, cls: String) -> Array[Node]: + var result :Array[Node] = [] + for ch in parent.get_children(): + if ch.get_class() == cls: + result.append(ch) + return result + + +static func _find_nodes_by_class(root: Node, cls: String) -> Array[Node]: + var result :Array[Node] = [] + var stack :Array[Node] = [root] + while stack: + var node :Node = stack.pop_back() + if node.get_class() == cls: + result.append(node) + for ch in node.get_children(): + stack.push_back(ch) + return result diff --git a/addons/gdUnit4/src/core/GdObjects.gd.uid b/addons/gdUnit4/src/core/GdObjects.gd.uid new file mode 100644 index 0000000..6247a07 --- /dev/null +++ b/addons/gdUnit4/src/core/GdObjects.gd.uid @@ -0,0 +1 @@ +uid://hc2odn3d2lov diff --git a/addons/gdUnit4/src/core/GdUnit4Version.gd b/addons/gdUnit4/src/core/GdUnit4Version.gd new file mode 100644 index 0000000..777eb92 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnit4Version.gd @@ -0,0 +1,61 @@ +class_name GdUnit4Version +extends RefCounted + +const VERSION_PATTERN = "[center][color=#9887c4]gd[/color][color=#7a57d6]Unit[/color][color=#9887c4]4[/color] [color=#9887c4]${version}[/color][/center]" + +var _major :int +var _minor :int +var _patch :int + + +func _init(major :int, minor :int, patch :int) -> void: + _major = major + _minor = minor + _patch = patch + + +static func parse(value :String) -> GdUnit4Version: + var regex := RegEx.new() + @warning_ignore("return_value_discarded") + regex.compile("[a-zA-Z:,-]+") + var cleaned := regex.sub(value, "", true) + var parts := cleaned.split(".") + var major := parts[0].to_int() + var minor := parts[1].to_int() + var patch := parts[2].to_int() if parts.size() > 2 else 0 + return GdUnit4Version.new(major, minor, patch) + + +static func current() -> GdUnit4Version: + var config := ConfigFile.new() + @warning_ignore("return_value_discarded") + config.load('addons/gdUnit4/plugin.cfg') + @warning_ignore("unsafe_cast") + return parse(config.get_value('plugin', 'version') as String) + + +func equals(other :GdUnit4Version) -> bool: + return _major == other._major and _minor == other._minor and _patch == other._patch + + +func is_greater(other :GdUnit4Version) -> bool: + if _major > other._major: + return true + if _major == other._major and _minor > other._minor: + return true + return _major == other._major and _minor == other._minor and _patch > other._patch + + +static func init_version_label(label :Control) -> void: + var config := ConfigFile.new() + @warning_ignore("return_value_discarded") + config.load('addons/gdUnit4/plugin.cfg') + var version :String = config.get_value('plugin', 'version') + if label is RichTextLabel: + (label as RichTextLabel).text = VERSION_PATTERN.replace('${version}', version) + else: + (label as Label).text = "gdUnit4 " + version + + +func _to_string() -> String: + return "v%d.%d.%d" % [_major, _minor, _patch] diff --git a/addons/gdUnit4/src/core/GdUnit4Version.gd.uid b/addons/gdUnit4/src/core/GdUnit4Version.gd.uid new file mode 100644 index 0000000..58f2e33 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnit4Version.gd.uid @@ -0,0 +1 @@ +uid://crrvklhb1vxj4 diff --git a/addons/gdUnit4/src/core/GdUnitFileAccess.gd b/addons/gdUnit4/src/core/GdUnitFileAccess.gd new file mode 100644 index 0000000..f6db5b4 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitFileAccess.gd @@ -0,0 +1,232 @@ +class_name GdUnitFileAccess +extends RefCounted + +const GDUNIT_TEMP := "user://tmp" + + +static func current_dir() -> String: + return ProjectSettings.globalize_path("res://") + + +static func clear_tmp() -> void: + delete_directory(GDUNIT_TEMP) + + +# Creates a new file under +static func create_temp_file(relative_path :String, file_name :String, mode := FileAccess.WRITE) -> FileAccess: + var file_path := create_temp_dir(relative_path) + "/" + file_name + var file := FileAccess.open(file_path, mode) + if file == null: + push_error("Error creating temporary file at: %s, %s" % [file_path, error_string(FileAccess.get_open_error())]) + return file + + +static func temp_dir() -> String: + if not DirAccess.dir_exists_absolute(GDUNIT_TEMP): + @warning_ignore("return_value_discarded") + DirAccess.make_dir_recursive_absolute(GDUNIT_TEMP) + return GDUNIT_TEMP + + +static func create_temp_dir(folder_name :String) -> String: + var new_folder := temp_dir() + "/" + folder_name + if not DirAccess.dir_exists_absolute(new_folder): + @warning_ignore("return_value_discarded") + DirAccess.make_dir_recursive_absolute(new_folder) + return new_folder + + +static func copy_file(from_file :String, to_dir :String) -> GdUnitResult: + var dir := DirAccess.open(to_dir) + if dir != null: + var to_file := to_dir + "/" + from_file.get_file() + prints("Copy %s to %s" % [from_file, to_file]) + var error := dir.copy(from_file, to_file) + if error != OK: + return GdUnitResult.error("Can't copy file form '%s' to '%s'. Error: '%s'" % [from_file, to_file, error_string(error)]) + return GdUnitResult.success(to_file) + return GdUnitResult.error("Directory not found: " + to_dir) + + +static func copy_directory(from_dir :String, to_dir :String, recursive :bool = false) -> bool: + if not DirAccess.dir_exists_absolute(from_dir): + push_error("Source directory not found '%s'" % from_dir) + return false + + # check if destination exists + if not DirAccess.dir_exists_absolute(to_dir): + # create it + var err := DirAccess.make_dir_recursive_absolute(to_dir) + if err != OK: + push_error("Can't create directory '%s'. Error: %s" % [to_dir, error_string(err)]) + return false + var source_dir := DirAccess.open(from_dir) + var dest_dir := DirAccess.open(to_dir) + if source_dir != null: + @warning_ignore("return_value_discarded") + source_dir.list_dir_begin() + var next := "." + + while next != "": + next = source_dir.get_next() + if next == "" or next == "." or next == "..": + continue + var source := source_dir.get_current_dir() + "/" + next + var dest := dest_dir.get_current_dir() + "/" + next + if source_dir.current_is_dir(): + if recursive: + @warning_ignore("return_value_discarded") + copy_directory(source + "/", dest, recursive) + continue + var err := source_dir.copy(source, dest) + if err != OK: + push_error("Error checked copy file '%s' to '%s'" % [source, dest]) + return false + + return true + else: + push_error("Directory not found: " + from_dir) + return false + + +static func delete_directory(path :String, only_content := false) -> void: + var dir := DirAccess.open(path) + if dir != null: + dir.include_hidden = true + @warning_ignore("return_value_discarded") + dir.list_dir_begin() + var file_name := "." + while file_name != "": + file_name = dir.get_next() + if file_name.is_empty() or file_name == "." or file_name == "..": + continue + var next := path + "/" +file_name + if dir.current_is_dir(): + delete_directory(next) + else: + # delete file + var err := dir.remove(next) + if err: + push_error("Delete %s failed: %s" % [next, error_string(err)]) + if not only_content: + var err := dir.remove(path) + if err: + push_error("Delete %s failed: %s" % [path, error_string(err)]) + + +static func delete_path_index_lower_equals_than(path :String, prefix :String, index :int) -> int: + var dir := DirAccess.open(path) + if dir == null: + return 0 + var deleted := 0 + @warning_ignore("return_value_discarded") + dir.list_dir_begin() + var next := "." + while next != "": + next = dir.get_next() + if next.is_empty() or next == "." or next == "..": + continue + if next.begins_with(prefix): + var current_index := next.split("_")[1].to_int() + if current_index <= index: + deleted += 1 + delete_directory(path + "/" + next) + return deleted + + +# scans given path for sub directories by given prefix and returns the highest index numer +# e.g. +static func find_last_path_index(path :String, prefix :String) -> int: + var dir := DirAccess.open(path) + if dir == null: + return 0 + var last_iteration := 0 + @warning_ignore("return_value_discarded") + dir.list_dir_begin() + var next := "." + while next != "": + next = dir.get_next() + if next.is_empty() or next == "." or next == "..": + continue + if next.begins_with(prefix): + var iteration := next.split("_")[1].to_int() + if iteration > last_iteration: + last_iteration = iteration + return last_iteration + + +static func as_resource_path(value: String) -> String: + if value.begins_with("res://"): + return value + return "res://" + value.trim_prefix("//").trim_prefix("/").trim_suffix("/") + + +static func scan_dir(path :String) -> PackedStringArray: + var dir := DirAccess.open(path) + if dir == null or not dir.dir_exists(path): + return PackedStringArray() + var content := PackedStringArray() + dir.include_hidden = true + @warning_ignore("return_value_discarded") + dir.list_dir_begin() + var next := "." + while next != "": + next = dir.get_next() + if next.is_empty() or next == "." or next == "..": + continue + @warning_ignore("return_value_discarded") + content.append(next) + return content + + +static func resource_as_array(resource_path :String) -> PackedStringArray: + var file := FileAccess.open(resource_path, FileAccess.READ) + if file == null: + push_error("ERROR: Can't read resource '%s'. %s" % [resource_path, error_string(FileAccess.get_open_error())]) + return PackedStringArray() + var file_content := PackedStringArray() + while not file.eof_reached(): + @warning_ignore("return_value_discarded") + file_content.append(file.get_line()) + return file_content + + +static func resource_as_string(resource_path :String) -> String: + var file := FileAccess.open(resource_path, FileAccess.READ) + if file == null: + push_error("ERROR: Can't read resource '%s'. %s" % [resource_path, error_string(FileAccess.get_open_error())]) + return "" + return file.get_as_text(true) + + +static func make_qualified_path(path :String) -> String: + if path.begins_with("res://"): + return path + if path.begins_with("//"): + return path.replace("//", "res://") + if path.begins_with("/"): + return "res:/" + path + return path + + +static func extract_zip(zip_package :String, dest_path :String) -> GdUnitResult: + var zip: ZIPReader = ZIPReader.new() + var err := zip.open(zip_package) + if err != OK: + return GdUnitResult.error("Extracting `%s` failed! Please collect the error log and report this. Error Code: %s" % [zip_package, err]) + var zip_entries: PackedStringArray = zip.get_files() + # Get base path and step over archive folder + var archive_path := zip_entries[0] + zip_entries.remove_at(0) + + for zip_entry in zip_entries: + var new_file_path: String = dest_path + "/" + zip_entry.replace(archive_path, "") + if zip_entry.ends_with("/"): + @warning_ignore("return_value_discarded") + DirAccess.make_dir_recursive_absolute(new_file_path) + continue + var file: FileAccess = FileAccess.open(new_file_path, FileAccess.WRITE) + file.store_buffer(zip.read_file(zip_entry)) + @warning_ignore("return_value_discarded") + zip.close() + return GdUnitResult.success(dest_path) diff --git a/addons/gdUnit4/src/core/GdUnitFileAccess.gd.uid b/addons/gdUnit4/src/core/GdUnitFileAccess.gd.uid new file mode 100644 index 0000000..816e497 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitFileAccess.gd.uid @@ -0,0 +1 @@ +uid://07p3yf11755u diff --git a/addons/gdUnit4/src/core/GdUnitProperty.gd b/addons/gdUnit4/src/core/GdUnitProperty.gd new file mode 100644 index 0000000..3d050b1 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitProperty.gd @@ -0,0 +1,81 @@ +class_name GdUnitProperty +extends RefCounted + + +var _name :String +var _help :String +var _type :int +var _value :Variant +var _value_set :PackedStringArray +var _default :Variant + + +func _init(p_name :String, p_type :int, p_value :Variant, p_default_value :Variant, p_help :="", p_value_set := PackedStringArray()) -> void: + _name = p_name + _type = p_type + _value = p_value + _value_set = p_value_set + _default = p_default_value + _help = p_help + + +func name() -> String: + return _name + + +func type() -> int: + return _type + + +func value() -> Variant: + return _value + + +func int_value() -> int: + return _value + +func value_as_string() -> String: + return _value + + +func value_set() -> PackedStringArray: + return _value_set + + +func is_selectable_value() -> bool: + return not _value_set.is_empty() + + +func set_value(p_value: Variant) -> void: + match _type: + TYPE_STRING: + _value = str(p_value) + TYPE_BOOL: + _value = type_convert(p_value, TYPE_BOOL) + TYPE_INT: + _value = type_convert(p_value, TYPE_INT) + TYPE_FLOAT: + _value = type_convert(p_value, TYPE_FLOAT) + TYPE_DICTIONARY: + _value = type_convert(p_value, TYPE_DICTIONARY) + _: + _value = p_value + + +func default() -> Variant: + return _default + + +func category() -> String: + var elements := _name.split("/") + if elements.size() > 3: + return elements[2] + return "" + + +func help() -> String: + return _help + + +func _to_string() -> String: + return "%-64s %-10s %-10s (%s) help:%s set:%s" % [name(), type(), value(), default(), help(), _value_set] diff --git a/addons/gdUnit4/src/core/GdUnitProperty.gd.uid b/addons/gdUnit4/src/core/GdUnitProperty.gd.uid new file mode 100644 index 0000000..0fb8309 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitProperty.gd.uid @@ -0,0 +1 @@ +uid://blsgr6udd4asq diff --git a/addons/gdUnit4/src/core/GdUnitResult.gd b/addons/gdUnit4/src/core/GdUnitResult.gd new file mode 100644 index 0000000..42392a5 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitResult.gd @@ -0,0 +1,109 @@ +class_name GdUnitResult +extends RefCounted + +enum { + SUCCESS, + WARN, + ERROR, + EMPTY +} + +var _state: int +var _warn_message := "" +var _error_message := "" +var _value :Variant = null + + +static func empty() -> GdUnitResult: + var result := GdUnitResult.new() + result._state = EMPTY + return result + + +static func success(p_value: Variant = "") -> GdUnitResult: + assert(p_value != null, "The value must not be NULL") + var result := GdUnitResult.new() + result._value = p_value + result._state = SUCCESS + return result + + +static func warn(p_warn_message: String, p_value: Variant = null) -> GdUnitResult: + assert(not p_warn_message.is_empty()) #,"The message must not be empty") + var result := GdUnitResult.new() + result._value = p_value + result._warn_message = p_warn_message + result._state = WARN + return result + + +static func error(p_error_message: String) -> GdUnitResult: + assert(not p_error_message.is_empty(), "The message must not be empty") + var result := GdUnitResult.new() + result._value = null + result._error_message = p_error_message + result._state = ERROR + return result + + +func is_success() -> bool: + return _state == SUCCESS + + +func is_warn() -> bool: + return _state == WARN + + +func is_error() -> bool: + return _state == ERROR + + +func is_empty() -> bool: + return _state == EMPTY + + +func value() -> Variant: + return _value + + +func value_as_string() -> String: + return _value + + +func or_else(p_value: Variant) -> Variant: + if not is_success(): + return p_value + return value() + + +func error_message() -> String: + return _error_message + + +func warn_message() -> String: + return _warn_message + + +func _to_string() -> String: + return str(GdUnitResult.serialize(self)) + + +static func serialize(result: GdUnitResult) -> Dictionary: + if result == null: + push_error("Can't serialize a Null object from type GdUnitResult") + return { + "state" : result._state, + "value" : var_to_str(result._value), + "warn_msg" : result._warn_message, + "err_msg" : result._error_message + } + + +static func deserialize(config: Dictionary) -> GdUnitResult: + var result := GdUnitResult.new() + var cfg_value: String = config.get("value", "") + result._value = str_to_var(cfg_value) + result._warn_message = config.get("warn_msg", null) + result._error_message = config.get("err_msg", null) + result._state = config.get("state") + return result diff --git a/addons/gdUnit4/src/core/GdUnitResult.gd.uid b/addons/gdUnit4/src/core/GdUnitResult.gd.uid new file mode 100644 index 0000000..eb36c08 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitResult.gd.uid @@ -0,0 +1 @@ +uid://dldi7wm4cqk13 diff --git a/addons/gdUnit4/src/core/GdUnitRunnerConfig.gd b/addons/gdUnit4/src/core/GdUnitRunnerConfig.gd new file mode 100644 index 0000000..9f36354 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitRunnerConfig.gd @@ -0,0 +1,126 @@ +class_name GdUnitRunnerConfig +extends Resource + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") + +const CONFIG_VERSION = "5.0" +const VERSION = "version" +const TESTS = "tests" +const SERVER_PORT = "server_port" +const EXIT_FAIL_FAST = "exit_on_first_fail" + +const CONFIG_FILE = "res://addons/gdUnit4/GdUnitRunner.cfg" + +var _config := { + VERSION : CONFIG_VERSION, + # a set of directories or testsuite paths as key and a optional set of testcases as values + + TESTS : Array([], TYPE_OBJECT, "RefCounted", GdUnitTestCase), + + # the port of running test server for this session + SERVER_PORT : -1 + } + + +func version() -> String: + return _config[VERSION] + + +func clear() -> GdUnitRunnerConfig: + _config[TESTS] = Array([], TYPE_OBJECT, "RefCounted", GdUnitTestCase) + return self + + +func set_server_port(port: int) -> GdUnitRunnerConfig: + _config[SERVER_PORT] = port + return self + + +func server_port() -> int: + return _config.get(SERVER_PORT, -1) + + +func add_test_cases(tests: Array[GdUnitTestCase]) -> GdUnitRunnerConfig: + test_cases().append_array(tests) + return self + + +func test_cases() -> Array[GdUnitTestCase]: + return _config.get(TESTS, []) + + +func save_config(path: String = CONFIG_FILE) -> GdUnitResult: + var file := FileAccess.open(path, FileAccess.WRITE) + if file == null: + var error := FileAccess.get_open_error() + return GdUnitResult.error("Can't write test runner configuration '%s'! %s" % [path, error_string(error)]) + + var to_save := { + VERSION : CONFIG_VERSION, + SERVER_PORT : _config.get(SERVER_PORT), + TESTS : Array() + } + + var tests: Array = to_save.get(TESTS) + for test in test_cases(): + tests.append(inst_to_dict(test)) + file.store_string(JSON.stringify(to_save, "\t")) + return GdUnitResult.success(path) + + +func load_config(path: String = CONFIG_FILE) -> GdUnitResult: + if not FileAccess.file_exists(path): + return GdUnitResult.warn("Can't find test runner configuration '%s'! Please select a test to run." % path) + var file := FileAccess.open(path, FileAccess.READ) + if file == null: + var error := FileAccess.get_open_error() + return GdUnitResult.error("Can't load test runner configuration '%s'! ERROR: %s." % [path, error_string(error)]) + var content := file.get_as_text() + if not content.is_empty() and content[0] == '{': + # Parse as json + var test_json_conv := JSON.new() + var error := test_json_conv.parse(content) + if error != OK: + return GdUnitResult.error("The runner configuration '%s' is invalid! The format is changed please delete it manually and start a new test run." % path) + var config: Dictionary = test_json_conv.get_data() + if not config.has(VERSION): + return GdUnitResult.error("The runner configuration '%s' is invalid! The format is changed please delete it manually and start a new test run." % path) + + var default: Array[Dictionary] = Array([], TYPE_DICTIONARY, "", null) + var tests_as_json: Array = config.get(TESTS, default) + _config = config + _config[TESTS] = convert_test_json_to_test_cases(tests_as_json) + + + fix_value_types() + return GdUnitResult.success(path) + + +func convert_test_json_to_test_cases(jsons: Array) -> Array[GdUnitTestCase]: + if jsons.is_empty(): + return [] + var tests := jsons.map(func(d: Dictionary) -> GdUnitTestCase: + var test: GdUnitTestCase = dict_to_inst(d) + # we need o covert manually to the corect type becaus JSON do not handle typed values + test.guid = GdUnitGUID.new(str(d["guid"])) + test.attribute_index = test.attribute_index as int + test.line_number = test.line_number as int + return test + ) + return Array(tests, TYPE_OBJECT, "RefCounted", GdUnitTestCase) + + +func fix_value_types() -> void: + # fix float value to int json stores all numbers as float + var server_port_: int = _config.get(SERVER_PORT, -1) + _config[SERVER_PORT] = server_port_ + + +func convert_Array_to_PackedStringArray(data: Dictionary) -> void: + for key in data.keys() as Array[String]: + var values :Array = data[key] + data[key] = PackedStringArray(values) + + +func _to_string() -> String: + return str(_config) diff --git a/addons/gdUnit4/src/core/GdUnitRunnerConfig.gd.uid b/addons/gdUnit4/src/core/GdUnitRunnerConfig.gd.uid new file mode 100644 index 0000000..11a5b57 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitRunnerConfig.gd.uid @@ -0,0 +1 @@ +uid://cu2erwwch03o8 diff --git a/addons/gdUnit4/src/core/GdUnitSceneRunnerImpl.gd b/addons/gdUnit4/src/core/GdUnitSceneRunnerImpl.gd new file mode 100644 index 0000000..f271853 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitSceneRunnerImpl.gd @@ -0,0 +1,622 @@ +# This class provides a runner for scense to simulate interactions like keyboard or mouse +class_name GdUnitSceneRunnerImpl +extends GdUnitSceneRunner + + +var GdUnitFuncAssertImpl: GDScript = ResourceLoader.load("res://addons/gdUnit4/src/asserts/GdUnitFuncAssertImpl.gd", "GDScript", ResourceLoader.CACHE_MODE_REUSE) + + +# mapping of mouse buttons and his masks +const MAP_MOUSE_BUTTON_MASKS := { + MOUSE_BUTTON_LEFT : MOUSE_BUTTON_MASK_LEFT, + MOUSE_BUTTON_RIGHT : MOUSE_BUTTON_MASK_RIGHT, + MOUSE_BUTTON_MIDDLE : MOUSE_BUTTON_MASK_MIDDLE, + # https://github.com/godotengine/godot/issues/73632 + MOUSE_BUTTON_WHEEL_UP : 1 << (MOUSE_BUTTON_WHEEL_UP - 1), + MOUSE_BUTTON_WHEEL_DOWN : 1 << (MOUSE_BUTTON_WHEEL_DOWN - 1), + MOUSE_BUTTON_XBUTTON1 : MOUSE_BUTTON_MASK_MB_XBUTTON1, + MOUSE_BUTTON_XBUTTON2 : MOUSE_BUTTON_MASK_MB_XBUTTON2, +} + +var _is_disposed := false +var _current_scene: Node = null +var _awaiter: GdUnitAwaiter = GdUnitAwaiter.new() +var _verbose: bool +var _simulate_start_time: LocalTime +var _last_input_event: InputEvent = null +var _mouse_button_on_press := [] +var _key_on_press := [] +var _action_on_press := [] +var _curent_mouse_position: Vector2 +# holds the touch position for each touch index +# { index: int = position: Vector2} +var _current_touch_position: Dictionary = {} +# holds the curretn touch drag position +var _current_touch_drag_position: Vector2 = Vector2.ZERO + +# time factor settings +var _time_factor := 1.0 +var _saved_iterations_per_second: float +var _scene_auto_free := false + + +func _init(p_scene: Variant, p_verbose: bool, p_hide_push_errors := false) -> void: + _verbose = p_verbose + _saved_iterations_per_second = Engine.get_physics_ticks_per_second() + @warning_ignore("return_value_discarded") + set_time_factor(1) + # handle scene loading by resource path + if typeof(p_scene) == TYPE_STRING: + @warning_ignore("unsafe_cast") + if !ResourceLoader.exists(p_scene as String): + if not p_hide_push_errors: + push_error("GdUnitSceneRunner: Can't load scene by given resource path: '%s'. The resource does not exists." % p_scene) + return + if !str(p_scene).ends_with(".tscn") and !str(p_scene).ends_with(".scn") and !str(p_scene).begins_with("uid://"): + if not p_hide_push_errors: + push_error("GdUnitSceneRunner: The given resource: '%s'. is not a scene." % p_scene) + return + @warning_ignore("unsafe_cast") + _current_scene = (load(p_scene as String) as PackedScene).instantiate() + _scene_auto_free = true + else: + # verify we have a node instance + if not p_scene is Node: + if not p_hide_push_errors: + push_error("GdUnitSceneRunner: The given instance '%s' is not a Node." % p_scene) + return + _current_scene = p_scene + if _current_scene == null: + if not p_hide_push_errors: + push_error("GdUnitSceneRunner: Scene must be not null!") + return + + _scene_tree().root.add_child(_current_scene) + # do finally reset all open input events when the scene is removed + @warning_ignore("return_value_discarded") + _scene_tree().root.child_exiting_tree.connect(func f(child :Node) -> void: + if child == _current_scene: + # we need to disable the processing to avoid input flush buffer errors + _current_scene.process_mode = Node.PROCESS_MODE_DISABLED + _reset_input_to_default() + ) + _simulate_start_time = LocalTime.now() + # we need to set inital a valid window otherwise the warp_mouse() is not handled + move_window_to_foreground() + + # set inital mouse pos to 0,0 + var max_iteration_to_wait := 0 + while get_global_mouse_position() != Vector2.ZERO and max_iteration_to_wait < 100: + Input.warp_mouse(Vector2.ZERO) + max_iteration_to_wait += 1 + + +func _notification(what: int) -> void: + if what == NOTIFICATION_PREDELETE and is_instance_valid(self): + # reset time factor to normal + __deactivate_time_factor() + if is_instance_valid(_current_scene): + move_window_to_background() + _scene_tree().root.remove_child(_current_scene) + # do only free scenes instanciated by this runner + if _scene_auto_free: + _current_scene.free() + _is_disposed = true + _current_scene = null + + +func _scene_tree() -> SceneTree: + return Engine.get_main_loop() as SceneTree + + +func await_input_processed() -> void: + if scene() != null and scene().process_mode != Node.PROCESS_MODE_DISABLED: + Input.flush_buffered_events() + await (Engine.get_main_loop() as SceneTree).process_frame + await (Engine.get_main_loop() as SceneTree).physics_frame + + +@warning_ignore("return_value_discarded") +func simulate_action_pressed(action: String, event_index := -1) -> GdUnitSceneRunner: + simulate_action_press(action, event_index) + simulate_action_release(action, event_index) + return self + + +func simulate_action_press(action: String, event_index := -1) -> GdUnitSceneRunner: + __print_current_focus() + var event := InputEventAction.new() + event.pressed = true + event.action = action + event.event_index = event_index + _action_on_press.append(action) + return _handle_input_event(event) + + +func simulate_action_release(action: String, event_index := -1) -> GdUnitSceneRunner: + __print_current_focus() + var event := InputEventAction.new() + event.pressed = false + event.action = action + event.event_index = event_index + _action_on_press.erase(action) + return _handle_input_event(event) + + +@warning_ignore("return_value_discarded") +func simulate_key_pressed(key_code: int, shift_pressed := false, ctrl_pressed := false) -> GdUnitSceneRunner: + simulate_key_press(key_code, shift_pressed, ctrl_pressed) + await _scene_tree().process_frame + simulate_key_release(key_code, shift_pressed, ctrl_pressed) + return self + + +func simulate_key_press(key_code: int, shift_pressed := false, ctrl_pressed := false) -> GdUnitSceneRunner: + __print_current_focus() + var event := InputEventKey.new() + event.pressed = true + event.keycode = key_code as Key + event.physical_keycode = key_code as Key + event.unicode = key_code + event.alt_pressed = key_code == KEY_ALT + event.shift_pressed = shift_pressed or key_code == KEY_SHIFT + event.ctrl_pressed = ctrl_pressed or key_code == KEY_CTRL + _apply_input_modifiers(event) + _key_on_press.append(key_code) + return _handle_input_event(event) + + +func simulate_key_release(key_code: int, shift_pressed := false, ctrl_pressed := false) -> GdUnitSceneRunner: + __print_current_focus() + var event := InputEventKey.new() + event.pressed = false + event.keycode = key_code as Key + event.physical_keycode = key_code as Key + event.unicode = key_code + event.alt_pressed = key_code == KEY_ALT + event.shift_pressed = shift_pressed or key_code == KEY_SHIFT + event.ctrl_pressed = ctrl_pressed or key_code == KEY_CTRL + _apply_input_modifiers(event) + _key_on_press.erase(key_code) + return _handle_input_event(event) + + +func set_mouse_position(pos: Vector2) -> GdUnitSceneRunner: + var event := InputEventMouseMotion.new() + event.position = pos + event.global_position = get_global_mouse_position() + _apply_input_modifiers(event) + return _handle_input_event(event) + + +func get_mouse_position() -> Vector2: + if _last_input_event is InputEventMouse: + return (_last_input_event as InputEventMouse).position + var current_scene := scene() + if current_scene != null: + return current_scene.get_viewport().get_mouse_position() + return Vector2.ZERO + + +func get_global_mouse_position() -> Vector2: + return (Engine.get_main_loop() as SceneTree).root.get_mouse_position() + + +func simulate_mouse_move(position: Vector2) -> GdUnitSceneRunner: + var event := InputEventMouseMotion.new() + event.position = position + event.relative = position - get_mouse_position() + event.global_position = get_global_mouse_position() + _apply_input_mouse_mask(event) + _apply_input_modifiers(event) + return _handle_input_event(event) + + +@warning_ignore("return_value_discarded") +func simulate_mouse_move_relative(relative: Vector2, time: float = 1.0, trans_type: Tween.TransitionType = Tween.TRANS_LINEAR) -> GdUnitSceneRunner: + var tween := _scene_tree().create_tween() + _curent_mouse_position = get_mouse_position() + var final_position := _curent_mouse_position + relative + tween.tween_property(self, "_curent_mouse_position", final_position, time).set_trans(trans_type) + tween.play() + + while not get_mouse_position().is_equal_approx(final_position): + simulate_mouse_move(_curent_mouse_position) + await _scene_tree().process_frame + return self + + +@warning_ignore("return_value_discarded") +func simulate_mouse_move_absolute(position: Vector2, time: float = 1.0, trans_type: Tween.TransitionType = Tween.TRANS_LINEAR) -> GdUnitSceneRunner: + var tween := _scene_tree().create_tween() + _curent_mouse_position = get_mouse_position() + tween.tween_property(self, "_curent_mouse_position", position, time).set_trans(trans_type) + tween.play() + + while not get_mouse_position().is_equal_approx(position): + simulate_mouse_move(_curent_mouse_position) + await _scene_tree().process_frame + return self + + +@warning_ignore("return_value_discarded") +func simulate_mouse_button_pressed(button_index: MouseButton, double_click := false) -> GdUnitSceneRunner: + simulate_mouse_button_press(button_index, double_click) + simulate_mouse_button_release(button_index) + return self + + +func simulate_mouse_button_press(button_index: MouseButton, double_click := false) -> GdUnitSceneRunner: + var event := InputEventMouseButton.new() + event.button_index = button_index + event.pressed = true + event.double_click = double_click + _apply_input_mouse_position(event) + _apply_input_mouse_mask(event) + _apply_input_modifiers(event) + _mouse_button_on_press.append(button_index) + return _handle_input_event(event) + + +func simulate_mouse_button_release(button_index: MouseButton) -> GdUnitSceneRunner: + var event := InputEventMouseButton.new() + event.button_index = button_index + event.pressed = false + _apply_input_mouse_position(event) + _apply_input_mouse_mask(event) + _apply_input_modifiers(event) + _mouse_button_on_press.erase(button_index) + return _handle_input_event(event) + + +@warning_ignore("return_value_discarded") +func simulate_screen_touch_pressed(index: int, position: Vector2, double_tap := false) -> GdUnitSceneRunner: + simulate_screen_touch_press(index, position, double_tap) + simulate_screen_touch_release(index) + return self + + +@warning_ignore("return_value_discarded") +func simulate_screen_touch_press(index: int, position: Vector2, double_tap := false) -> GdUnitSceneRunner: + if is_emulate_mouse_from_touch(): + # we need to simulate in addition to the touch the mouse events + set_mouse_position(position) + simulate_mouse_button_press(MOUSE_BUTTON_LEFT) + # push touch press event at position + var event := InputEventScreenTouch.new() + event.window_id = scene().get_window().get_window_id() + event.index = index + event.position = position + event.double_tap = double_tap + event.pressed = true + _current_scene.get_viewport().push_input(event) + # save current drag position by index + _current_touch_position[index] = position + return self + + +@warning_ignore("return_value_discarded") +func simulate_screen_touch_release(index: int, double_tap := false) -> GdUnitSceneRunner: + if is_emulate_mouse_from_touch(): + # we need to simulate in addition to the touch the mouse events + simulate_mouse_button_release(MOUSE_BUTTON_LEFT) + # push touch release event at position + var event := InputEventScreenTouch.new() + event.window_id = scene().get_window().get_window_id() + event.index = index + event.position = get_screen_touch_drag_position(index) + event.pressed = false + event.double_tap = (_last_input_event as InputEventScreenTouch).double_tap if _last_input_event is InputEventScreenTouch else double_tap + _current_scene.get_viewport().push_input(event) + return self + + +func simulate_screen_touch_drag_relative(index: int, relative: Vector2, time: float = 1.0, trans_type: Tween.TransitionType = Tween.TRANS_LINEAR) -> GdUnitSceneRunner: + var current_position: Vector2 = _current_touch_position[index] + return await _do_touch_drag_at(index, current_position + relative, time, trans_type) + + +func simulate_screen_touch_drag_absolute(index: int, position: Vector2, time: float = 1.0, trans_type: Tween.TransitionType = Tween.TRANS_LINEAR) -> GdUnitSceneRunner: + return await _do_touch_drag_at(index, position, time, trans_type) + + +@warning_ignore("return_value_discarded") +func simulate_screen_touch_drag_drop(index: int, position: Vector2, drop_position: Vector2, time: float = 1.0, trans_type: Tween.TransitionType = Tween.TRANS_LINEAR) -> GdUnitSceneRunner: + simulate_screen_touch_press(index, position) + return await _do_touch_drag_at(index, drop_position, time, trans_type) + + +@warning_ignore("return_value_discarded") +func simulate_screen_touch_drag(index: int, position: Vector2) -> GdUnitSceneRunner: + if is_emulate_mouse_from_touch(): + simulate_mouse_move(position) + var event := InputEventScreenDrag.new() + event.window_id = scene().get_window().get_window_id() + event.index = index + event.position = position + event.relative = _get_screen_touch_drag_position_or_default(index, position) - position + event.velocity = event.relative / _scene_tree().root.get_process_delta_time() + event.pressure = 1.0 + _current_touch_position[index] = position + _current_scene.get_viewport().push_input(event) + return self + + +func get_screen_touch_drag_position(index: int) -> Vector2: + if _current_touch_position.has(index): + return _current_touch_position[index] + push_error("No touch drag position for index '%d' is set!" % index) + return Vector2.ZERO + + +func is_emulate_mouse_from_touch() -> bool: + return ProjectSettings.get_setting("input_devices/pointing/emulate_mouse_from_touch", true) + + +func _get_screen_touch_drag_position_or_default(index: int, default_position: Vector2) -> Vector2: + if _current_touch_position.has(index): + return _current_touch_position[index] + return default_position + + +@warning_ignore("return_value_discarded") +func _do_touch_drag_at(index: int, drag_position: Vector2, time: float, trans_type: Tween.TransitionType) -> GdUnitSceneRunner: + # start draging + var event := InputEventScreenDrag.new() + event.window_id = scene().get_window().get_window_id() + event.index = index + event.position = get_screen_touch_drag_position(index) + event.pressure = 1.0 + _current_touch_drag_position = event.position + + var tween := _scene_tree().create_tween() + tween.tween_property(self, "_current_touch_drag_position", drag_position, time).set_trans(trans_type) + tween.play() + + while not _current_touch_drag_position.is_equal_approx(drag_position): + if is_emulate_mouse_from_touch(): + # we need to simulate in addition to the drag the mouse move events + simulate_mouse_move(event.position) + # send touche drag event to new position + event.relative = _current_touch_drag_position - event.position + event.velocity = event.relative / _scene_tree().root.get_process_delta_time() + event.position = _current_touch_drag_position + _current_scene.get_viewport().push_input(event) + await _scene_tree().process_frame + + # finaly drop it + if is_emulate_mouse_from_touch(): + simulate_mouse_move(drag_position) + simulate_mouse_button_release(MOUSE_BUTTON_LEFT) + var touch_drop_event := InputEventScreenTouch.new() + touch_drop_event.window_id = event.window_id + touch_drop_event.index = event.index + touch_drop_event.position = drag_position + touch_drop_event.pressed = false + _current_scene.get_viewport().push_input(touch_drop_event) + await _scene_tree().process_frame + return self + + +func set_time_factor(time_factor: float = 1.0) -> GdUnitSceneRunner: + _time_factor = min(9.0, time_factor) + __activate_time_factor() + __print("set time factor: %f" % _time_factor) + __print("set physics physics_ticks_per_second: %d" % (_saved_iterations_per_second*_time_factor)) + return self + + +func simulate_frames(frames: int, delta_milli: int = -1) -> GdUnitSceneRunner: + var time_shift_frames :int = max(1, frames / _time_factor) + for frame in time_shift_frames: + if delta_milli == -1: + await _scene_tree().process_frame + else: + await _scene_tree().create_timer(delta_milli * 0.001).timeout + return self + + +func simulate_until_signal(signal_name: String, ...args: Array) -> GdUnitSceneRunner: + await _awaiter.await_signal_idle_frames(scene(), signal_name, args, 10000) + return self + + +func simulate_until_object_signal(source: Object, signal_name: String, ...args: Array) -> GdUnitSceneRunner: + await _awaiter.await_signal_idle_frames(source, signal_name, args, 10000) + return self + + +func await_func(func_name: String, ...args: Array) -> GdUnitFuncAssert: + return GdUnitFuncAssertImpl.new(scene(), func_name, args) + + +func await_func_on(instance: Object, func_name: String, ...args: Array) -> GdUnitFuncAssert: + return GdUnitFuncAssertImpl.new(instance, func_name, args) + + +func await_signal(signal_name: String, args := [], timeout := 2000 ) -> void: + await _awaiter.await_signal_on(scene(), signal_name, args, timeout) + + +func await_signal_on(source: Object, signal_name: String, args := [], timeout := 2000 ) -> void: + await _awaiter.await_signal_on(source, signal_name, args, timeout) + + +func move_window_to_foreground() -> GdUnitSceneRunner: + if not Engine.is_embedded_in_editor(): + DisplayServer.window_set_mode(DisplayServer.WINDOW_MODE_WINDOWED) + DisplayServer.window_move_to_foreground() + return self + + +func move_window_to_background() -> GdUnitSceneRunner: + if not Engine.is_embedded_in_editor(): + DisplayServer.window_set_mode(DisplayServer.WINDOW_MODE_WINDOWED) + DisplayServer.window_set_mode(DisplayServer.WINDOW_MODE_MINIMIZED) + return self + + +func _property_exists(name: String) -> bool: + return scene().get_property_list().any(func(properties :Dictionary) -> bool: return properties["name"] == name) + + +func get_property(name: String) -> Variant: + if not _property_exists(name): + return "The property '%s' not exist checked loaded scene." % name + return scene().get(name) + + +func set_property(name: String, value: Variant) -> bool: + if not _property_exists(name): + push_error("The property named '%s' cannot be set, it does not exist!" % name) + return false; + scene().set(name, value) + return true + + +func invoke(name: String, ...args: Array) -> Variant: + if scene().has_method(name): + return await scene().callv(name, args) + return "The method '%s' not exist checked loaded scene." % name + + +func find_child(name: String, recursive: bool = true, owned: bool = false) -> Node: + return scene().find_child(name, recursive, owned) + + +func _scene_name() -> String: + var scene_script :GDScript = scene().get_script() + var scene_name :String = scene().get_name() + if not scene_script: + return scene_name + if not scene_name.begins_with("@"): + return scene_name + return scene_script.resource_name.get_basename() + + +func __activate_time_factor() -> void: + Engine.set_time_scale(_time_factor) + Engine.set_physics_ticks_per_second((_saved_iterations_per_second * _time_factor) as int) + + +func __deactivate_time_factor() -> void: + Engine.set_time_scale(1) + Engine.set_physics_ticks_per_second(_saved_iterations_per_second as int) + + +# copy over current active modifiers +func _apply_input_modifiers(event: InputEvent) -> void: + if _last_input_event is InputEventWithModifiers and event is InputEventWithModifiers: + var last_input_event := _last_input_event as InputEventWithModifiers + var _event := event as InputEventWithModifiers + _event.meta_pressed = _event.meta_pressed or last_input_event.meta_pressed + _event.alt_pressed = _event.alt_pressed or last_input_event.alt_pressed + _event.shift_pressed = _event.shift_pressed or last_input_event.shift_pressed + _event.ctrl_pressed = _event.ctrl_pressed or last_input_event.ctrl_pressed + # this line results into reset the control_pressed state!!! + #event.command_or_control_autoremap = event.command_or_control_autoremap or _last_input_event.command_or_control_autoremap + + +# copy over current active mouse mask and combine with curren mask +func _apply_input_mouse_mask(event: InputEvent) -> void: + # first apply last mask + if _last_input_event is InputEventMouse and event is InputEventMouse: + (event as InputEventMouse).button_mask |= (_last_input_event as InputEventMouse).button_mask + if event is InputEventMouseButton: + var _event := event as InputEventMouseButton + var button_mask :int = MAP_MOUSE_BUTTON_MASKS.get(_event.get_button_index(), 0) + if _event.is_pressed(): + _event.button_mask |= button_mask + else: + _event.button_mask ^= button_mask + + +# copy over last mouse position if need +func _apply_input_mouse_position(event: InputEvent) -> void: + if _last_input_event is InputEventMouse and event is InputEventMouseButton: + (event as InputEventMouseButton).position = (_last_input_event as InputEventMouse).position + + +## handle input action via Input modifieres +func _handle_actions(event: InputEventAction) -> bool: + if not InputMap.event_is_action(event, event.action, true): + return false + __print(" process action %s (%s) <- %s" % [scene(), _scene_name(), event.as_text()]) + if event.is_pressed(): + Input.action_press(event.action, event.get_strength()) + else: + Input.action_release(event.action) + return true + + +# for handling read https://docs.godotengine.org/en/stable/tutorials/inputs/inputevent.html?highlight=inputevent#how-does-it-work +@warning_ignore("return_value_discarded") +func _handle_input_event(event: InputEvent) -> GdUnitSceneRunner: + if event is InputEventMouse: + Input.warp_mouse((event as InputEventMouse).position as Vector2) + Input.parse_input_event(event) + + if event is InputEventAction: + _handle_actions(event as InputEventAction) + + var current_scene := scene() + if is_instance_valid(current_scene): + # do not flush events if node processing disabled otherwise we run into errors at tree removed + if _current_scene.process_mode != Node.PROCESS_MODE_DISABLED: + Input.flush_buffered_events() + __print(" process event %s (%s) <- %s" % [current_scene, _scene_name(), event.as_text()]) + if(current_scene.has_method("_gui_input")): + (current_scene as Control)._gui_input(event) + if(current_scene.has_method("_unhandled_input")): + current_scene._unhandled_input(event) + current_scene.get_viewport().set_input_as_handled() + + # save last input event needs to be merged with next InputEventMouseButton + _last_input_event = event + return self + + +@warning_ignore("return_value_discarded") +func _reset_input_to_default() -> void: + # reset all mouse button to inital state if need + for m_button :int in _mouse_button_on_press.duplicate(): + if Input.is_mouse_button_pressed(m_button): + simulate_mouse_button_release(m_button) + _mouse_button_on_press.clear() + + for key_scancode :int in _key_on_press.duplicate(): + if Input.is_key_pressed(key_scancode): + simulate_key_release(key_scancode) + _key_on_press.clear() + + for action :String in _action_on_press.duplicate(): + if Input.is_action_pressed(action): + simulate_action_release(action) + _action_on_press.clear() + + if is_instance_valid(_current_scene) and _current_scene.process_mode != Node.PROCESS_MODE_DISABLED: + Input.flush_buffered_events() + _last_input_event = null + + +func __print(message: String) -> void: + if _verbose: + prints(message) + + +func __print_current_focus() -> void: + if not _verbose: + return + var focused_node := scene().get_viewport().gui_get_focus_owner() + if focused_node: + prints(" focus checked %s" % focused_node) + else: + prints(" no focus set") + + +func scene() -> Node: + if is_instance_valid(_current_scene): + return _current_scene + if not _is_disposed: + push_error("The current scene instance is not valid anymore! check your test is valid. e.g. check for missing awaits.") + return null diff --git a/addons/gdUnit4/src/core/GdUnitSceneRunnerImpl.gd.uid b/addons/gdUnit4/src/core/GdUnitSceneRunnerImpl.gd.uid new file mode 100644 index 0000000..b38834c --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitSceneRunnerImpl.gd.uid @@ -0,0 +1 @@ +uid://de2y23dh4aepm diff --git a/addons/gdUnit4/src/core/GdUnitSettings.gd b/addons/gdUnit4/src/core/GdUnitSettings.gd new file mode 100644 index 0000000..f6bff12 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitSettings.gd @@ -0,0 +1,435 @@ +@tool +class_name GdUnitSettings +extends RefCounted + + +const MAIN_CATEGORY = "gdunit4" +# Common Settings +const COMMON_SETTINGS = MAIN_CATEGORY + "/settings" + +const GROUP_COMMON = COMMON_SETTINGS + "/common" +const UPDATE_NOTIFICATION_ENABLED = GROUP_COMMON + "/update_notification_enabled" +const SERVER_TIMEOUT = GROUP_COMMON + "/server_connection_timeout_minutes" + +const GROUP_HOOKS = MAIN_CATEGORY + "/hooks" +const SESSION_HOOKS = GROUP_HOOKS + "/session_hooks" + +const GROUP_TEST = COMMON_SETTINGS + "/test" +const TEST_TIMEOUT = GROUP_TEST + "/test_timeout_seconds" +const TEST_LOOKUP_FOLDER = GROUP_TEST + "/test_lookup_folder" +const TEST_SUITE_NAMING_CONVENTION = GROUP_TEST + "/test_suite_naming_convention" +const TEST_DISCOVER_ENABLED = GROUP_TEST + "/test_discovery" +const TEST_FLAKY_CHECK = GROUP_TEST + "/flaky_check_enable" +const TEST_FLAKY_MAX_RETRIES = GROUP_TEST + "/flaky_max_retries" + + +# Report Setiings +const REPORT_SETTINGS = MAIN_CATEGORY + "/report" +const GROUP_GODOT = REPORT_SETTINGS + "/godot" +const REPORT_PUSH_ERRORS = GROUP_GODOT + "/push_error" +const REPORT_SCRIPT_ERRORS = GROUP_GODOT + "/script_error" +const REPORT_ORPHANS = REPORT_SETTINGS + "/verbose_orphans" +const GROUP_ASSERT = REPORT_SETTINGS + "/assert" +const REPORT_ASSERT_WARNINGS = GROUP_ASSERT + "/verbose_warnings" +const REPORT_ASSERT_ERRORS = GROUP_ASSERT + "/verbose_errors" +const REPORT_ASSERT_STRICT_NUMBER_TYPE_COMPARE = GROUP_ASSERT + "/strict_number_type_compare" + +# Godot debug stdout/logging settings +const CATEGORY_LOGGING := "debug/file_logging/" +const STDOUT_ENABLE_TO_FILE = CATEGORY_LOGGING + "enable_file_logging" +const STDOUT_WITE_TO_FILE = CATEGORY_LOGGING + "log_path" + + +# GdUnit Templates +const TEMPLATES = MAIN_CATEGORY + "/templates" +const TEMPLATES_TS = TEMPLATES + "/testsuite" +const TEMPLATE_TS_GD = TEMPLATES_TS + "/GDScript" +const TEMPLATE_TS_CS = TEMPLATES_TS + "/CSharpScript" + + +# UI Setiings +const UI_SETTINGS = MAIN_CATEGORY + "/ui" +const GROUP_UI_INSPECTOR = UI_SETTINGS + "/inspector" +const INSPECTOR_NODE_COLLAPSE = GROUP_UI_INSPECTOR + "/node_collapse" +const INSPECTOR_TREE_VIEW_MODE = GROUP_UI_INSPECTOR + "/tree_view_mode" +const INSPECTOR_TREE_SORT_MODE = GROUP_UI_INSPECTOR + "/tree_sort_mode" + + +# Shortcut Setiings +const SHORTCUT_SETTINGS = MAIN_CATEGORY + "/Shortcuts" +const GROUP_SHORTCUT_INSPECTOR = SHORTCUT_SETTINGS + "/inspector" +const SHORTCUT_INSPECTOR_RERUN_TEST = GROUP_SHORTCUT_INSPECTOR + "/rerun_test" +const SHORTCUT_INSPECTOR_RERUN_TEST_DEBUG = GROUP_SHORTCUT_INSPECTOR + "/rerun_test_debug" +const SHORTCUT_INSPECTOR_RUN_TEST_OVERALL = GROUP_SHORTCUT_INSPECTOR + "/run_test_overall" +const SHORTCUT_INSPECTOR_RUN_TEST_STOP = GROUP_SHORTCUT_INSPECTOR + "/run_test_stop" + +const GROUP_SHORTCUT_EDITOR = SHORTCUT_SETTINGS + "/editor" +const SHORTCUT_EDITOR_RUN_TEST = GROUP_SHORTCUT_EDITOR + "/run_test" +const SHORTCUT_EDITOR_RUN_TEST_DEBUG = GROUP_SHORTCUT_EDITOR + "/run_test_debug" +const SHORTCUT_EDITOR_CREATE_TEST = GROUP_SHORTCUT_EDITOR + "/create_test" + +const GROUP_SHORTCUT_FILESYSTEM = SHORTCUT_SETTINGS + "/filesystem" +const SHORTCUT_FILESYSTEM_RUN_TEST = GROUP_SHORTCUT_FILESYSTEM + "/run_test" +const SHORTCUT_FILESYSTEM_RUN_TEST_DEBUG = GROUP_SHORTCUT_FILESYSTEM + "/run_test_debug" + + +# Toolbar Setiings +const GROUP_UI_TOOLBAR = UI_SETTINGS + "/toolbar" +const INSPECTOR_TOOLBAR_BUTTON_RUN_OVERALL = GROUP_UI_TOOLBAR + "/run_overall" + +# Feature flags +const GROUP_FEATURE = MAIN_CATEGORY + "/feature" + + +# defaults +# server connection timeout in minutes +const DEFAULT_SERVER_TIMEOUT :int = 30 +# test case runtime timeout in seconds +const DEFAULT_TEST_TIMEOUT :int = 60*5 +# the folder to create new test-suites +const DEFAULT_TEST_LOOKUP_FOLDER := "test" + +# help texts +const HELP_TEST_LOOKUP_FOLDER := "Subfolder where test suites are located (or empty to use source folder directly)" + +enum NAMING_CONVENTIONS { + AUTO_DETECT, + SNAKE_CASE, + PASCAL_CASE, +} + + +const _VALUE_SET_SEPARATOR = "\f" # ASCII Form-feed character (AKA page break) + + +static func setup() -> void: + create_property_if_need(UPDATE_NOTIFICATION_ENABLED, true, "Show notification if new gdUnit4 version is found") + # test settings + create_property_if_need(SERVER_TIMEOUT, DEFAULT_SERVER_TIMEOUT, "Server connection timeout in minutes") + create_property_if_need(TEST_TIMEOUT, DEFAULT_TEST_TIMEOUT, "Test case runtime timeout in seconds") + create_property_if_need(TEST_LOOKUP_FOLDER, DEFAULT_TEST_LOOKUP_FOLDER, HELP_TEST_LOOKUP_FOLDER) + create_property_if_need(TEST_SUITE_NAMING_CONVENTION, NAMING_CONVENTIONS.AUTO_DETECT, "Naming convention to use when generating testsuites", NAMING_CONVENTIONS.keys()) + create_property_if_need(TEST_DISCOVER_ENABLED, false, "Automatically detect new tests in test lookup folders at runtime") + create_property_if_need(TEST_FLAKY_CHECK, false, "Rerun tests on failure and mark them as FLAKY") + create_property_if_need(TEST_FLAKY_MAX_RETRIES, 3, "Sets the number of retries for rerunning a flaky test") + # report settings + create_property_if_need(REPORT_PUSH_ERRORS, false, "Report push_error() as failure") + create_property_if_need(REPORT_SCRIPT_ERRORS, true, "Report script errors as failure") + create_property_if_need(REPORT_ORPHANS, true, "Report orphaned nodes after tests finish") + create_property_if_need(REPORT_ASSERT_ERRORS, true, "Report assertion failures as errors") + create_property_if_need(REPORT_ASSERT_WARNINGS, true, "Report assertion failures as warnings") + create_property_if_need(REPORT_ASSERT_STRICT_NUMBER_TYPE_COMPARE, true, "Compare number values strictly by type (real vs int)") + # inspector + create_property_if_need(INSPECTOR_NODE_COLLAPSE, true, + "Close testsuite node after a successful test run.") + create_property_if_need(INSPECTOR_TREE_VIEW_MODE, GdUnitInspectorTreeConstants.TREE_VIEW_MODE.TREE, + "Inspector panel presentation mode", GdUnitInspectorTreeConstants.TREE_VIEW_MODE.keys()) + create_property_if_need(INSPECTOR_TREE_SORT_MODE, GdUnitInspectorTreeConstants.SORT_MODE.UNSORTED, + "Inspector panel sorting mode", GdUnitInspectorTreeConstants.SORT_MODE.keys()) + create_property_if_need(INSPECTOR_TOOLBAR_BUTTON_RUN_OVERALL, false, + "Show 'Run overall Tests' button in the inspector toolbar") + create_property_if_need(TEMPLATE_TS_GD, GdUnitTestSuiteTemplate.default_GD_template(), "Test suite template to use") + create_shortcut_properties_if_need() + create_property_if_need(SESSION_HOOKS, {} as Dictionary[String,bool]) + migrate_properties() + + +static func migrate_properties() -> void: + var TEST_ROOT_FOLDER := "gdunit4/settings/test/test_root_folder" + if get_property(TEST_ROOT_FOLDER) != null: + migrate_property(TEST_ROOT_FOLDER,\ + TEST_LOOKUP_FOLDER,\ + DEFAULT_TEST_LOOKUP_FOLDER,\ + HELP_TEST_LOOKUP_FOLDER,\ + func(value :Variant) -> String: return DEFAULT_TEST_LOOKUP_FOLDER if value == null else value) + + +static func create_shortcut_properties_if_need() -> void: + # inspector + create_property_if_need(SHORTCUT_INSPECTOR_RERUN_TEST, GdUnitShortcut.default_keys(GdUnitShortcut.ShortCut.RERUN_TESTS), "Rerun the most recently executed tests") + create_property_if_need(SHORTCUT_INSPECTOR_RERUN_TEST_DEBUG, GdUnitShortcut.default_keys(GdUnitShortcut.ShortCut.RERUN_TESTS_DEBUG), "Rerun the most recently executed tests (Debug mode)") + create_property_if_need(SHORTCUT_INSPECTOR_RUN_TEST_OVERALL, GdUnitShortcut.default_keys(GdUnitShortcut.ShortCut.RUN_TESTS_OVERALL), "Runs all tests (Debug mode)") + create_property_if_need(SHORTCUT_INSPECTOR_RUN_TEST_STOP, GdUnitShortcut.default_keys(GdUnitShortcut.ShortCut.STOP_TEST_RUN), "Stop the current test execution") + # script editor + create_property_if_need(SHORTCUT_EDITOR_RUN_TEST, GdUnitShortcut.default_keys(GdUnitShortcut.ShortCut.RUN_TESTCASE), "Run the currently selected test") + create_property_if_need(SHORTCUT_EDITOR_RUN_TEST_DEBUG, GdUnitShortcut.default_keys(GdUnitShortcut.ShortCut.RUN_TESTCASE_DEBUG), "Run the currently selected test (Debug mode).") + create_property_if_need(SHORTCUT_EDITOR_CREATE_TEST, GdUnitShortcut.default_keys(GdUnitShortcut.ShortCut.CREATE_TEST), "Create a new test case for the currently selected function") + # filesystem + create_property_if_need(SHORTCUT_FILESYSTEM_RUN_TEST, GdUnitShortcut.default_keys(GdUnitShortcut.ShortCut.NONE), "Run all test suites in the selected folder or file") + create_property_if_need(SHORTCUT_FILESYSTEM_RUN_TEST_DEBUG, GdUnitShortcut.default_keys(GdUnitShortcut.ShortCut.NONE), "Run all test suites in the selected folder or file (Debug)") + + +static func create_property_if_need(name :String, default :Variant, help :="", value_set := PackedStringArray()) -> void: + if not ProjectSettings.has_setting(name): + #prints("GdUnit4: Set inital settings '%s' to '%s'." % [name, str(default)]) + ProjectSettings.set_setting(name, default) + + ProjectSettings.set_initial_value(name, default) + help = help if value_set.is_empty() else "%s%s%s" % [help, _VALUE_SET_SEPARATOR, value_set] + set_help(name, default, help) + + +static func set_help(property_name :String, value :Variant, help :String) -> void: + ProjectSettings.add_property_info({ + "name": property_name, + "type": typeof(value), + "hint": PROPERTY_HINT_TYPE_STRING, + "hint_string": help + }) + + +static func get_setting(name :String, default :Variant) -> Variant: + if ProjectSettings.has_setting(name): + return ProjectSettings.get_setting(name) + return default + + +static func is_update_notification_enabled() -> bool: + if ProjectSettings.has_setting(UPDATE_NOTIFICATION_ENABLED): + return ProjectSettings.get_setting(UPDATE_NOTIFICATION_ENABLED) + return false + + +static func set_update_notification(enable :bool) -> void: + ProjectSettings.set_setting(UPDATE_NOTIFICATION_ENABLED, enable) + @warning_ignore("return_value_discarded") + ProjectSettings.save() + + +static func get_log_path() -> String: + return ProjectSettings.get_setting(STDOUT_WITE_TO_FILE) + + +static func set_log_path(path :String) -> void: + ProjectSettings.set_setting(STDOUT_ENABLE_TO_FILE, true) + ProjectSettings.set_setting(STDOUT_WITE_TO_FILE, path) + @warning_ignore("return_value_discarded") + ProjectSettings.save() + + +static func get_session_hooks() -> Dictionary[String, bool]: + var property := get_property(SESSION_HOOKS) + if property == null: + return {} + var hooks: Dictionary[String, bool] = property.value() + return hooks + + +static func set_session_hooks(hooks: Dictionary[String, bool]) -> void: + var property := get_property(SESSION_HOOKS) + property.set_value(hooks) + update_property(property) + + +static func set_inspector_tree_sort_mode(sort_mode: GdUnitInspectorTreeConstants.SORT_MODE) -> void: + var property := get_property(INSPECTOR_TREE_SORT_MODE) + property.set_value(sort_mode) + update_property(property) + + +static func get_inspector_tree_sort_mode() -> GdUnitInspectorTreeConstants.SORT_MODE: + var property := get_property(INSPECTOR_TREE_SORT_MODE) + return property.value() if property != null else GdUnitInspectorTreeConstants.SORT_MODE.UNSORTED + + +static func set_inspector_tree_view_mode(tree_view_mode: GdUnitInspectorTreeConstants.TREE_VIEW_MODE) -> void: + var property := get_property(INSPECTOR_TREE_VIEW_MODE) + property.set_value(tree_view_mode) + update_property(property) + + +static func get_inspector_tree_view_mode() -> GdUnitInspectorTreeConstants.TREE_VIEW_MODE: + var property := get_property(INSPECTOR_TREE_VIEW_MODE) + return property.value() if property != null else GdUnitInspectorTreeConstants.TREE_VIEW_MODE.TREE + + +# the configured server connection timeout in ms +static func server_timeout() -> int: + return get_setting(SERVER_TIMEOUT, DEFAULT_SERVER_TIMEOUT) * 60 * 1000 + + +# the configured test case timeout in ms +static func test_timeout() -> int: + return get_setting(TEST_TIMEOUT, DEFAULT_TEST_TIMEOUT) * 1000 + + +# the root folder to store/generate test-suites +static func test_root_folder() -> String: + return get_setting(TEST_LOOKUP_FOLDER, DEFAULT_TEST_LOOKUP_FOLDER) + + +static func is_verbose_assert_warnings() -> bool: + return get_setting(REPORT_ASSERT_WARNINGS, true) + + +static func is_verbose_assert_errors() -> bool: + return get_setting(REPORT_ASSERT_ERRORS, true) + + +static func is_verbose_orphans() -> bool: + return get_setting(REPORT_ORPHANS, true) + + +static func is_strict_number_type_compare() -> bool: + return get_setting(REPORT_ASSERT_STRICT_NUMBER_TYPE_COMPARE, true) + + +static func is_report_push_errors() -> bool: + return get_setting(REPORT_PUSH_ERRORS, false) + + +static func is_report_script_errors() -> bool: + return get_setting(REPORT_SCRIPT_ERRORS, true) + + +static func is_inspector_node_collapse() -> bool: + return get_setting(INSPECTOR_NODE_COLLAPSE, true) + + +static func is_inspector_toolbar_button_show() -> bool: + return get_setting(INSPECTOR_TOOLBAR_BUTTON_RUN_OVERALL, true) + + +static func is_test_discover_enabled() -> bool: + return get_setting(TEST_DISCOVER_ENABLED, false) + + +static func is_test_flaky_check_enabled() -> bool: + return get_setting(TEST_FLAKY_CHECK, false) + + +static func is_feature_enabled(feature: String) -> bool: + return get_setting(feature, false) + + +static func get_flaky_max_retries() -> int: + return get_setting(TEST_FLAKY_MAX_RETRIES, 3) + + +static func set_test_discover_enabled(enable :bool) -> void: + var property := get_property(TEST_DISCOVER_ENABLED) + property.set_value(enable) + update_property(property) + + +static func is_log_enabled() -> bool: + return ProjectSettings.get_setting(STDOUT_ENABLE_TO_FILE) + + +static func list_settings(category: String) -> Array[GdUnitProperty]: + var settings: Array[GdUnitProperty] = [] + for property in ProjectSettings.get_property_list(): + var property_name :String = property["name"] + if property_name.begins_with(category): + settings.append(build_property(property_name, property)) + return settings + + +static func extract_value_set_from_help(value :String) -> PackedStringArray: + var split_value := value.split(_VALUE_SET_SEPARATOR) + if not split_value.size() > 1: + return PackedStringArray() + + var regex := RegEx.new() + @warning_ignore("return_value_discarded") + regex.compile("\\[(.+)\\]") + var matches := regex.search_all(split_value[1]) + if matches.is_empty(): + return PackedStringArray() + var values: String = matches[0].get_string(1) + return values.replacen(" ", "").replacen("\"", "").split(",", false) + + +static func extract_help_text(value :String) -> String: + return value.split(_VALUE_SET_SEPARATOR)[0] + + +static func update_property(property :GdUnitProperty) -> Variant: + var current_value :Variant = ProjectSettings.get_setting(property.name()) + if current_value != property.value(): + var error :Variant = validate_property_value(property) + if error != null: + return error + ProjectSettings.set_setting(property.name(), property.value()) + GdUnitSignals.instance().gdunit_settings_changed.emit(property) + _save_settings() + return null + + +static func reset_property(property :GdUnitProperty) -> void: + ProjectSettings.set_setting(property.name(), property.default()) + GdUnitSignals.instance().gdunit_settings_changed.emit(property) + _save_settings() + + +static func validate_property_value(property :GdUnitProperty) -> Variant: + match property.name(): + TEST_LOOKUP_FOLDER: + return validate_lookup_folder(property.value_as_string()) + _: return null + + +static func validate_lookup_folder(value :String) -> Variant: + if value.is_empty() or value == "/": + return null + if value.contains("res:"): + return "Test Lookup Folder: do not allowed to contains 'res://'" + if not value.is_valid_filename(): + return "Test Lookup Folder: contains invalid characters! e.g (: / \\ ? * \" | % < >)" + return null + + +static func save_property(name :String, value :Variant) -> void: + ProjectSettings.set_setting(name, value) + _save_settings() + + +static func _save_settings() -> void: + var err := ProjectSettings.save() + if err != OK: + push_error("Save GdUnit4 settings failed : %s" % error_string(err)) + return + + +static func has_property(name :String) -> bool: + return ProjectSettings.get_property_list().any(func(property :Dictionary) -> bool: return property["name"] == name) + + +static func get_property(name :String) -> GdUnitProperty: + for property in ProjectSettings.get_property_list(): + var property_name :String = property["name"] + if property_name == name: + return build_property(name, property) + return null + + +static func build_property(property_name: String, property: Dictionary) -> GdUnitProperty: + var value: Variant = ProjectSettings.get_setting(property_name) + var value_type: int = property["type"] + var default: Variant = ProjectSettings.property_get_revert(property_name) + var help: String = property["hint_string"] + var value_set := extract_value_set_from_help(help) + return GdUnitProperty.new(property_name, value_type, value, default, extract_help_text(help), value_set) + + +static func migrate_property(old_property :String, new_property :String, default_value :Variant, help :String, converter := Callable()) -> void: + var property := get_property(old_property) + if property == null: + prints("Migration not possible, property '%s' not found" % old_property) + return + var value :Variant = converter.call(property.value()) if converter.is_valid() else property.value() + ProjectSettings.set_setting(new_property, value) + ProjectSettings.set_initial_value(new_property, default_value) + set_help(new_property, value, help) + ProjectSettings.clear(old_property) + prints("Successfully migrated property '%s' -> '%s' value: %s" % [old_property, new_property, value]) + + +static func dump_to_tmp() -> void: + @warning_ignore("return_value_discarded") + ProjectSettings.save_custom("user://project_settings.godot") + + +static func restore_dump_from_tmp() -> void: + @warning_ignore("return_value_discarded") + DirAccess.copy_absolute("user://project_settings.godot", "res://project.godot") diff --git a/addons/gdUnit4/src/core/GdUnitSettings.gd.uid b/addons/gdUnit4/src/core/GdUnitSettings.gd.uid new file mode 100644 index 0000000..6b7b577 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitSettings.gd.uid @@ -0,0 +1 @@ +uid://dk7bm1nqf5bf6 diff --git a/addons/gdUnit4/src/core/GdUnitSignalAwaiter.gd b/addons/gdUnit4/src/core/GdUnitSignalAwaiter.gd new file mode 100644 index 0000000..528e133 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitSignalAwaiter.gd @@ -0,0 +1,81 @@ +class_name GdUnitSignalAwaiter +extends RefCounted + +signal signal_emitted(action :Variant) + +const NO_ARG :Variant = GdUnitConstants.NO_ARG + +var _wait_on_idle_frame := false +var _interrupted := false +var _time_left :float = 0 +var _timeout_millis :int + + +func _init(timeout_millis :int, wait_on_idle_frame := false) -> void: + _timeout_millis = timeout_millis + _wait_on_idle_frame = wait_on_idle_frame + + +func _on_signal_emmited( + arg0 :Variant = NO_ARG, + arg1 :Variant = NO_ARG, + arg2 :Variant = NO_ARG, + arg3 :Variant = NO_ARG, + arg4 :Variant = NO_ARG, + arg5 :Variant = NO_ARG, + arg6 :Variant = NO_ARG, + arg7 :Variant = NO_ARG, + arg8 :Variant = NO_ARG, + arg9 :Variant = NO_ARG) -> void: + var signal_args :Variant = GdArrayTools.filter_value([arg0,arg1,arg2,arg3,arg4,arg5,arg6,arg7,arg8,arg9], NO_ARG) + signal_emitted.emit(signal_args) + + +func is_interrupted() -> bool: + return _interrupted + + +func elapsed_time() -> float: + return _time_left + + +func on_signal(source :Object, signal_name :String, expected_signal_args :Array) -> Variant: + # register checked signal to wait for + @warning_ignore("return_value_discarded") + source.connect(signal_name, _on_signal_emmited) + # install timeout timer + var scene_tree := Engine.get_main_loop() as SceneTree + var timer := Timer.new() + scene_tree.root.add_child(timer) + timer.add_to_group("GdUnitTimers") + timer.set_one_shot(true) + @warning_ignore("return_value_discarded") + timer.timeout.connect(_do_interrupt, CONNECT_DEFERRED) + timer.start(_timeout_millis * 0.001 * Engine.get_time_scale()) + + # holds the emited value + var value :Variant + # wait for signal is emitted or a timeout is happen + while true: + value = await signal_emitted + if _interrupted: + break + if not (value is Array): + value = [value] + if expected_signal_args.size() == 0 or GdObjects.equals(value, expected_signal_args): + break + await scene_tree.process_frame + + source.disconnect(signal_name, _on_signal_emmited) + _time_left = timer.time_left + timer.queue_free() + await scene_tree.process_frame + @warning_ignore("unsafe_cast") + if value is Array and (value as Array).size() == 1: + return value[0] + return value + + +func _do_interrupt() -> void: + _interrupted = true + signal_emitted.emit(null) diff --git a/addons/gdUnit4/src/core/GdUnitSignalAwaiter.gd.uid b/addons/gdUnit4/src/core/GdUnitSignalAwaiter.gd.uid new file mode 100644 index 0000000..6a3dbe2 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitSignalAwaiter.gd.uid @@ -0,0 +1 @@ +uid://ca8mcf88y78r7 diff --git a/addons/gdUnit4/src/core/GdUnitSignalCollector.gd b/addons/gdUnit4/src/core/GdUnitSignalCollector.gd new file mode 100644 index 0000000..d03cc8e --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitSignalCollector.gd @@ -0,0 +1,124 @@ +# It connects to all signals of given emitter and collects received signals and arguments +# The collected signals are cleand finally when the emitter is freed. +class_name GdUnitSignalCollector +extends RefCounted + +const NO_ARG :Variant = GdUnitConstants.NO_ARG +const SIGNAL_BLACK_LIST = []#["tree_exiting", "tree_exited", "child_exiting_tree"] + +# { +# emitter : { +# signal_name : [signal_args], +# ... +# } +# } +var _collected_signals :Dictionary = {} + + +func clear() -> void: + for emitter :Object in _collected_signals.keys(): + if is_instance_valid(emitter): + unregister_emitter(emitter) + + +# connect to all possible signals defined by the emitter +# prepares the signal collection to store received signals and arguments +func register_emitter(emitter :Object) -> void: + if is_instance_valid(emitter): + # check emitter is already registerd + if _collected_signals.has(emitter): + return + _collected_signals[emitter] = Dictionary() + # connect to 'tree_exiting' of the emitter to finally release all acquired resources/connections. + if emitter is Node and !(emitter as Node).tree_exiting.is_connected(unregister_emitter): + (emitter as Node).tree_exiting.connect(unregister_emitter.bind(emitter)) + # connect to all signals of the emitter we want to collect + for signal_def in emitter.get_signal_list(): + var signal_name :String = signal_def["name"] + # set inital collected to empty + if not is_signal_collecting(emitter, signal_name): + _collected_signals[emitter][signal_name] = Array() + if SIGNAL_BLACK_LIST.find(signal_name) != -1: + continue + if !emitter.is_connected(signal_name, _on_signal_emmited): + var err := emitter.connect(signal_name, _on_signal_emmited.bind(emitter, signal_name)) + if err != OK: + push_error("Can't connect to signal %s on %s. Error: %s" % [signal_name, emitter, error_string(err)]) + + +# unregister all acquired resources/connections, otherwise it ends up in orphans +# is called when the emitter is removed from the parent +func unregister_emitter(emitter :Object) -> void: + if is_instance_valid(emitter): + for signal_def in emitter.get_signal_list(): + var signal_name :String = signal_def["name"] + if emitter.is_connected(signal_name, _on_signal_emmited): + emitter.disconnect(signal_name, _on_signal_emmited.bind(emitter, signal_name)) + @warning_ignore("return_value_discarded") + _collected_signals.erase(emitter) + + +# receives the signal from the emitter with all emitted signal arguments and additional the emitter and signal_name as last two arguements +func _on_signal_emmited( + arg0 :Variant= NO_ARG, + arg1 :Variant= NO_ARG, + arg2 :Variant= NO_ARG, + arg3 :Variant= NO_ARG, + arg4 :Variant= NO_ARG, + arg5 :Variant= NO_ARG, + arg6 :Variant= NO_ARG, + arg7 :Variant= NO_ARG, + arg8 :Variant= NO_ARG, + arg9 :Variant= NO_ARG, + arg10 :Variant= NO_ARG, + arg11 :Variant= NO_ARG) -> void: + var signal_args :Array = GdArrayTools.filter_value([arg0,arg1,arg2,arg3,arg4,arg5,arg6,arg7,arg8,arg9,arg10,arg11], NO_ARG) + # extract the emitter and signal_name from the last two arguments (see line 61 where is added) + var signal_name :String = signal_args.pop_back() + var emitter :Object = signal_args.pop_back() + #prints("_on_signal_emmited:", emitter, signal_name, signal_args) + if is_signal_collecting(emitter, signal_name): + @warning_ignore("unsafe_cast") + (_collected_signals[emitter][signal_name] as Array).append(signal_args) + + +func reset_received_signals(emitter: Object, signal_name: String, signal_args: Array) -> void: + #_debug_signal_list("before claer"); + if _collected_signals.has(emitter): + var signals_by_emitter :Dictionary = _collected_signals[emitter] + if signals_by_emitter.has(signal_name): + var received_args: Array = _collected_signals[emitter][signal_name] + # We iterate backwarts over to received_args to remove matching args. + # This will avoid array corruption see comment on `erase` otherwise we need a timeconsuming duplicate before + for arg_pos: int in range(received_args.size()-1, -1, -1): + var arg: Variant = received_args[arg_pos] + if GdObjects.equals(arg, signal_args): + received_args.remove_at(arg_pos) + #_debug_signal_list("after claer"); + + +func is_signal_collecting(emitter: Object, signal_name: String) -> bool: + @warning_ignore("unsafe_cast") + return _collected_signals.has(emitter) and (_collected_signals[emitter] as Dictionary).has(signal_name) + + +func match(emitter :Object, signal_name :String, args :Array) -> bool: + #prints("match", signal_name, _collected_signals[emitter][signal_name]); + if _collected_signals.is_empty() or not _collected_signals.has(emitter): + return false + for received_args :Variant in _collected_signals[emitter][signal_name]: + #prints("testing", signal_name, received_args, "vs", args) + if GdObjects.equals(received_args, args): + return true + return false + + +func _debug_signal_list(message :String) -> void: + prints("-----", message, "-------") + prints("senders {") + for emitter :Object in _collected_signals: + prints("\t", emitter) + for signal_name :String in _collected_signals[emitter]: + var args :Variant = _collected_signals[emitter][signal_name] + prints("\t\t", signal_name, args) + prints("}") diff --git a/addons/gdUnit4/src/core/GdUnitSignalCollector.gd.uid b/addons/gdUnit4/src/core/GdUnitSignalCollector.gd.uid new file mode 100644 index 0000000..516bad9 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitSignalCollector.gd.uid @@ -0,0 +1 @@ +uid://egq48khdrto7 diff --git a/addons/gdUnit4/src/core/GdUnitSignals.gd b/addons/gdUnit4/src/core/GdUnitSignals.gd new file mode 100644 index 0000000..53aafe9 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitSignals.gd @@ -0,0 +1,118 @@ +class_name GdUnitSignals +extends RefCounted +## Singleton class that handles GdUnit's signal communication.[br] +## [br] +## This class manages all signals used to communicate test events, discovery, and status changes.[br] +## It uses a singleton pattern stored in Engine metadata to ensure a single instance.[br] +## [br] +## Signals are grouped by purpose:[br] +## - Client connection handling[br] +## - Test execution events[br] +## - Test discovery events[br] +## - Settings and status updates[br] +## [br] +## Example usage:[br] +## [codeblock] +## # Connect to test discovery +## GdUnitSignals.instance().gdunit_test_discovered.connect(self._on_test_discovered) +## +## # Emit test event +## GdUnitSignals.instance().gdunit_event.emit(test_event) +## [/codeblock] + + +## Emitted when a client connects to the GdUnit server.[br] +## [param client_id] The ID of the connected client. +@warning_ignore("unused_signal") +signal gdunit_client_connected(client_id: int) + + +## Emitted when a client disconnects from the GdUnit server.[br] +## [param client_id] The ID of the disconnected client. +@warning_ignore("unused_signal") +signal gdunit_client_disconnected(client_id: int) + + +## Emitted when a client terminates unexpectedly. +@warning_ignore("unused_signal") +signal gdunit_client_terminated() + + +## Emitted when a test execution event occurs.[br] +## [param event] The test event containing details about test execution. +@warning_ignore("unused_signal") +signal gdunit_event(event: GdUnitEvent) + + +## Emitted for test debug events during execution.[br] +## [param event] The debug event containing test execution details. +@warning_ignore("unused_signal") +signal gdunit_event_debug(event: GdUnitEvent) + + +## Emitted to broadcast a general message.[br] +## [param message] The message to broadcast. +@warning_ignore("unused_signal") +signal gdunit_message(message: String) + + +## Emitted to update test failure status.[br] +## [param is_failed] Whether the test has failed. +@warning_ignore("unused_signal") +signal gdunit_set_test_failed(is_failed: bool) + + +## Emitted when a GdUnit setting changes.[br] +## [param property] The property that was changed. +@warning_ignore("unused_signal") +signal gdunit_settings_changed(property: GdUnitProperty) + +## Called when a new test case is discovered during the discovery process. +## Custom implementations should connect to this signal and store the discovered test case as needed.[br] +## [param test_case] The discovered test case instance to be processed. +@warning_ignore("unused_signal") +signal gdunit_test_discover_added(test_case: GdUnitTestCase) + + +## Emitted when a test case is deleted.[br] +## [param test_case] The test case that was deleted. +@warning_ignore("unused_signal") +signal gdunit_test_discover_deleted(test_case: GdUnitTestCase) + + +## Emitted when a test case is modified.[br] +## [param test_case] The test case that was modified. +@warning_ignore("unused_signal") +signal gdunit_test_discover_modified(test_case: GdUnitTestCase) + + +const META_KEY := "GdUnitSignals" + + +## Returns the singleton instance of GdUnitSignals.[br] +## Creates a new instance if none exists.[br] +## [br] +## Returns: The GdUnitSignals singleton instance. +static func instance() -> GdUnitSignals: + if Engine.has_meta(META_KEY): + return Engine.get_meta(META_KEY) + var instance_ := GdUnitSignals.new() + Engine.set_meta(META_KEY, instance_) + return instance_ + + +## Cleans up the singleton instance and disconnects all signals.[br] +## [br] +## Should be called when GdUnit is shutting down or needs to reset.[br] +## Ensures proper cleanup of signal connections and resources. +static func dispose() -> void: + var signals := instance() + # cleanup connected signals + for signal_ in signals.get_signal_list(): + @warning_ignore("unsafe_cast") + for connection in signals.get_signal_connection_list(signal_["name"] as StringName): + var _signal: Signal = connection["signal"] + var _callable: Callable = connection["callable"] + _signal.disconnect(_callable) + signals = null + Engine.remove_meta(META_KEY) diff --git a/addons/gdUnit4/src/core/GdUnitSignals.gd.uid b/addons/gdUnit4/src/core/GdUnitSignals.gd.uid new file mode 100644 index 0000000..e0ae50e --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitSignals.gd.uid @@ -0,0 +1 @@ +uid://cual5ybsgqkkr diff --git a/addons/gdUnit4/src/core/GdUnitSingleton.gd b/addons/gdUnit4/src/core/GdUnitSingleton.gd new file mode 100644 index 0000000..b8e08cc --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitSingleton.gd @@ -0,0 +1,56 @@ +################################################################################ +# Provides access to a global accessible singleton +# +# This is a workarount to the existing auto load singleton because of some bugs +# around plugin handling +################################################################################ +class_name GdUnitSingleton +extends Object + + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") +const MEATA_KEY := "GdUnitSingletons" + + +static func instance(name: String, clazz: Callable) -> Variant: + if Engine.has_meta(name): + return Engine.get_meta(name) + var singleton: Variant = clazz.call() + if is_instance_of(singleton, RefCounted): + @warning_ignore("unsafe_cast") + push_error("Invalid singleton implementation detected for '%s' is `%s`!" % [name, (singleton as RefCounted).get_class()]) + return + + Engine.set_meta(name, singleton) + GdUnitTools.prints_verbose("Register singleton '%s:%s'" % [name, singleton]) + var singletons: PackedStringArray = Engine.get_meta(MEATA_KEY, PackedStringArray()) + @warning_ignore("return_value_discarded") + singletons.append(name) + Engine.set_meta(MEATA_KEY, singletons) + return singleton + + +static func unregister(p_singleton: String, use_call_deferred: bool = false) -> void: + var singletons: PackedStringArray = Engine.get_meta(MEATA_KEY, PackedStringArray()) + if singletons.has(p_singleton): + GdUnitTools.prints_verbose("\n Unregister singleton '%s'" % p_singleton); + var index := singletons.find(p_singleton) + singletons.remove_at(index) + var instance_: Object = Engine.get_meta(p_singleton) + GdUnitTools.prints_verbose(" Free singleton instance '%s:%s'" % [p_singleton, instance_]) + @warning_ignore("return_value_discarded") + GdUnitTools.free_instance(instance_, use_call_deferred) + Engine.remove_meta(p_singleton) + GdUnitTools.prints_verbose(" Successfully freed '%s'" % p_singleton) + Engine.set_meta(MEATA_KEY, singletons) + + +static func dispose(use_call_deferred: bool = false) -> void: + # use a copy because unregister is modify the singletons array + var singletons: PackedStringArray = Engine.get_meta(MEATA_KEY, PackedStringArray()) + GdUnitTools.prints_verbose("----------------------------------------------------------------") + GdUnitTools.prints_verbose("Cleanup singletons %s" % singletons) + for singleton in PackedStringArray(singletons): + unregister(singleton, use_call_deferred) + Engine.remove_meta(MEATA_KEY) + GdUnitTools.prints_verbose("----------------------------------------------------------------") diff --git a/addons/gdUnit4/src/core/GdUnitSingleton.gd.uid b/addons/gdUnit4/src/core/GdUnitSingleton.gd.uid new file mode 100644 index 0000000..0285311 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitSingleton.gd.uid @@ -0,0 +1 @@ +uid://b06vn4t0dkoa5 diff --git a/addons/gdUnit4/src/core/GdUnitTestResourceLoader.gd b/addons/gdUnit4/src/core/GdUnitTestResourceLoader.gd new file mode 100644 index 0000000..33b80e2 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitTestResourceLoader.gd @@ -0,0 +1,97 @@ +class_name GdUnitTestResourceLoader +extends RefCounted + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") + +enum { + GD_SUITE, + CS_SUITE +} + + +static func load_test_suite(resource_path: String, script_type := GD_SUITE) -> Node: + match script_type: + GD_SUITE: + return load_test_suite_gd(resource_path) + CS_SUITE: + return load_test_suite_cs(resource_path) + assert("type '%s' is not implemented" % script_type) + return null + + +static func load_tests(resource_path: String) -> Dictionary: + var script := load_gd_script(resource_path) + var discovered_tests := {} + GdUnitTestDiscoverer.discover_tests(script, func(test: GdUnitTestCase) -> void: + discovered_tests[test.display_name] = test + ) + + return discovered_tests + + +static func load_test_suite_gd(resource_path: String) -> GdUnitTestSuite: + var script := load_gd_script(resource_path) + var discovered_tests: Array[GdUnitTestCase] = [] + GdUnitTestDiscoverer.discover_tests(script, func(test: GdUnitTestCase) -> void: + discovered_tests.append(test) + ) + # complete test suite wiht parsed test cases + return GdUnitTestSuiteScanner.new().load_suite(script, discovered_tests) + + +static func load_test_suite_cs(resource_path: String) -> Node: + if not GdUnit4CSharpApiLoader.is_api_loaded(): + return null + var script :Script = ClassDB.instantiate("CSharpScript") + script.source_code = GdUnitFileAccess.resource_as_string(resource_path) + script.resource_path = resource_path + script.reload() + return null + + +static func load_cs_script(resource_path: String, debug_write := false) -> Script: + if not GdUnit4CSharpApiLoader.is_api_loaded(): + return null + var script :Script = ClassDB.instantiate("CSharpScript") + script.source_code = GdUnitFileAccess.resource_as_string(resource_path) + var script_resource_path := resource_path.replace(resource_path.get_extension(), "cs") + if debug_write: + script_resource_path = GdUnitFileAccess.create_temp_dir("test") + "/%s" % script_resource_path.get_file() + print_debug("save resource:", script_resource_path) + DirAccess.remove_absolute(script_resource_path) + var err := ResourceSaver.save(script, script_resource_path) + if err != OK: + print_debug("Can't save debug resource",script_resource_path, "Error:", error_string(err)) + script.take_over_path(script_resource_path) + else: + script.take_over_path(resource_path) + script.reload() + return script + + +static func load_gd_script(resource_path: String, debug_write := false) -> GDScript: + # grap current level + var unsafe_method_access: Variant = ProjectSettings.get_setting("debug/gdscript/warnings/unsafe_method_access") + # disable and load the script + ProjectSettings.set_setting("debug/gdscript/warnings/unsafe_method_access", 0) + + var script := GDScript.new() + script.source_code = GdUnitFileAccess.resource_as_string(resource_path) + var script_resource_path := resource_path.replace(resource_path.get_extension(), "gd") + if debug_write: + script_resource_path = script_resource_path.replace("res://", GdUnitFileAccess.temp_dir() + "/") + #print_debug("save resource: ", script_resource_path) + DirAccess.remove_absolute(script_resource_path) + DirAccess.make_dir_recursive_absolute(script_resource_path.get_base_dir()) + var err := ResourceSaver.save(script, script_resource_path, ResourceSaver.FLAG_REPLACE_SUBRESOURCE_PATHS) + if err != OK: + print_debug("Can't save debug resource", script_resource_path, "Error:", error_string(err)) + script.take_over_path(script_resource_path) + else: + script.take_over_path(resource_path) + var error := script.reload() + if error != OK: + push_error("Errors on loading script %s. Error: %s" % [resource_path, error_string(error)]) + ProjectSettings.set_setting("debug/gdscript/warnings/unsafe_method_access", unsafe_method_access) + return script + #@warning_ignore("unsafe_cast") diff --git a/addons/gdUnit4/src/core/GdUnitTestResourceLoader.gd.uid b/addons/gdUnit4/src/core/GdUnitTestResourceLoader.gd.uid new file mode 100644 index 0000000..6b9538a --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitTestResourceLoader.gd.uid @@ -0,0 +1 @@ +uid://cywd5x07nj5bk diff --git a/addons/gdUnit4/src/core/GdUnitTestSuiteBuilder.gd b/addons/gdUnit4/src/core/GdUnitTestSuiteBuilder.gd new file mode 100644 index 0000000..97a49b0 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitTestSuiteBuilder.gd @@ -0,0 +1,20 @@ +class_name GdUnitTestSuiteBuilder +extends RefCounted + + +static func create(source :Script, line_number :int) -> GdUnitResult: + var test_suite_path := GdUnitTestSuiteScanner.resolve_test_suite_path(source.resource_path, GdUnitSettings.test_root_folder()) + # we need to save and close the testsuite and source if is current opened before modify + @warning_ignore("return_value_discarded") + ScriptEditorControls.save_an_open_script(source.resource_path) + @warning_ignore("return_value_discarded") + ScriptEditorControls.save_an_open_script(test_suite_path, true) + if source.get_class() == "CSharpScript": + return GdUnit4CSharpApiLoader.create_test_suite(source.resource_path, line_number+1, test_suite_path) + var parser := GdScriptParser.new() + var lines := source.source_code.split("\n") + var current_line := lines[line_number] + var func_name := parser.parse_func_name(current_line) + if func_name.is_empty(): + return GdUnitResult.error("No function found at line: %d." % line_number) + return GdUnitTestSuiteScanner.create_test_case(test_suite_path, func_name, source.resource_path) diff --git a/addons/gdUnit4/src/core/GdUnitTestSuiteBuilder.gd.uid b/addons/gdUnit4/src/core/GdUnitTestSuiteBuilder.gd.uid new file mode 100644 index 0000000..bae663b --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitTestSuiteBuilder.gd.uid @@ -0,0 +1 @@ +uid://dgqbjtlkjt6cq diff --git a/addons/gdUnit4/src/core/GdUnitTestSuiteScanner.gd b/addons/gdUnit4/src/core/GdUnitTestSuiteScanner.gd new file mode 100644 index 0000000..cc4dbff --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitTestSuiteScanner.gd @@ -0,0 +1,397 @@ +class_name GdUnitTestSuiteScanner +extends RefCounted + +const TEST_FUNC_TEMPLATE =""" + +func test_${func_name}() -> void: + # remove this line and complete your test + assert_not_yet_implemented() +""" + + +# we exclude the gdunit source directorys by default +const exclude_scan_directories = [ + "res://addons/gdUnit4/bin", + "res://addons/gdUnit4/src", + "res://reports"] + + +const ARGUMENT_TIMEOUT := "timeout" +const ARGUMENT_SKIP := "do_skip" +const ARGUMENT_SKIP_REASON := "skip_reason" +const ARGUMENT_PARAMETER_SET := "test_parameters" + + +var _script_parser := GdScriptParser.new() +var _included_resources: PackedStringArray = [] +var _excluded_resources: PackedStringArray = [] +var _expression_runner := GdUnitExpressionRunner.new() +var _regex_extends_clazz_name := RegEx.create_from_string("extends[\\s]+([\\S]+)") + + +func prescan_testsuite_classes() -> void: + # scan and cache extends GdUnitTestSuite by class name an resource paths + var script_classes: Array[Dictionary] = ProjectSettings.get_global_class_list() + for script_meta in script_classes: + var base_class: String = script_meta["base"] + var resource_path: String = script_meta["path"] + if base_class == "GdUnitTestSuite": + @warning_ignore("return_value_discarded") + _included_resources.append(resource_path) + elif ClassDB.class_exists(base_class): + @warning_ignore("return_value_discarded") + _excluded_resources.append(resource_path) + + +func scan(resource_path: String) -> Array[Script]: + prescan_testsuite_classes() + # if single testsuite requested + if FileAccess.file_exists(resource_path): + var test_suite := _load_is_test_suite(resource_path) + if test_suite != null: + return [test_suite] + return [] + return scan_directory(resource_path) + + +func scan_directory(resource_path: String) -> Array[Script]: + prescan_testsuite_classes() + # We use the global cache to fast scan for test suites. + if _excluded_resources.has(resource_path): + return [] + + var base_dir := DirAccess.open(resource_path) + if base_dir == null: + prints("Given directory or file does not exists:", resource_path) + return [] + + prints("Scanning for test suites in:", resource_path) + return _scan_test_suites_scripts(base_dir, []) + + +func _scan_test_suites_scripts(dir: DirAccess, collected_suites: Array[Script]) -> Array[Script]: + if exclude_scan_directories.has(dir.get_current_dir()): + return collected_suites + var err := dir.list_dir_begin() + if err != OK: + push_error("Error on scanning directory %s" % dir.get_current_dir(), error_string(err)) + return collected_suites + var file_name := dir.get_next() + while file_name != "": + var resource_path := GdUnitTestSuiteScanner._file(dir, file_name) + if dir.current_is_dir(): + var sub_dir := DirAccess.open(resource_path) + if sub_dir != null: + @warning_ignore("return_value_discarded") + _scan_test_suites_scripts(sub_dir, collected_suites) + else: + var time := LocalTime.now() + var test_suite := _load_is_test_suite(resource_path) + if test_suite: + collected_suites.append(test_suite) + if OS.is_stdout_verbose() and time.elapsed_since_ms() > 300: + push_warning("Scanning of test-suite '%s' took more than 300ms: " % resource_path, time.elapsed_since()) + file_name = dir.get_next() + return collected_suites + + +static func _file(dir: DirAccess, file_name: String) -> String: + var current_dir := dir.get_current_dir() + if current_dir.ends_with("/"): + return current_dir + file_name + return current_dir + "/" + file_name + + +func _load_is_test_suite(resource_path: String) -> Script: + if not GdUnitTestSuiteScanner._is_script_format_supported(resource_path): + return null + + # We use the global cache to fast scan for test suites. + if _excluded_resources.has(resource_path): + return null + # Check in the global class cache whether the GdUnitTestSuite class has been extended. + if _included_resources.has(resource_path): + return GdUnitTestSuiteScanner.load_with_disabled_warnings(resource_path) + + # Otherwise we need to scan manual, we need to exclude classes where direct extends form Godot classes + # the resource loader can fail to load e.g. plugin classes with do preload other scripts + #var extends_from := get_extends_classname(resource_path) + # If not extends is defined or extends from a Godot class + #if extends_from.is_empty() or ClassDB.class_exists(extends_from): + # return null + # Finally, we need to load the class to determine it is a test suite + var script := GdUnitTestSuiteScanner.load_with_disabled_warnings(resource_path) + if not is_test_suite(script): + return null + return script + + +func load_suite(script: GDScript, tests: Array[GdUnitTestCase]) -> GdUnitTestSuite: + var test_suite: GdUnitTestSuite = script.new() + var first_test: GdUnitTestCase = tests.front() + test_suite.set_name(first_test.suite_name) + + # We need to group first all parameterized tests together to load the parameter set once + var grouped_by_test := GdArrayTools.group_by(tests, func(test: GdUnitTestCase) -> String: + return test.test_name + ) + # Extract function descriptors + var test_names: PackedStringArray = grouped_by_test.keys() + test_names.append("before") + var function_descriptors := _script_parser.get_function_descriptors(script, test_names) + + # Convert to test + for fd in function_descriptors: + if fd.name() == "before": + _handle_test_suite_arguments(test_suite, script, fd) + continue + + # Build test attributes from test method + var test_attribute := _build_test_attribute(script, fd) + # Create test from descriptor and given attributes + var test_group: Array = grouped_by_test[fd.name()] + for test: GdUnitTestCase in test_group: + # We need a copy, because of mutable state + var attribute: TestCaseAttribute = test_attribute.clone() + test_suite.add_child(_TestCase.new(test, attribute, fd)) + return test_suite + + +func _build_test_attribute(script: GDScript, fd: GdFunctionDescriptor) -> TestCaseAttribute: + var collected_unknown_aruments := PackedStringArray() + var attribute := TestCaseAttribute.new() + + # Collect test attributes + for arg: GdFunctionArgument in fd.args(): + if arg.type() == GdObjects.TYPE_FUZZER: + attribute.fuzzers.append(arg) + else: + match arg.name(): + ARGUMENT_TIMEOUT: + attribute.timeout = type_convert(arg.default(), TYPE_INT) + ARGUMENT_SKIP: + var result: Variant = _expression_runner.execute(script, arg.plain_value()) + if result is bool: + attribute.is_skipped = result + else: + push_error("Test expression '%s' cannot be evaluated because it is not of type bool!" % arg.plain_value()) + ARGUMENT_SKIP_REASON: + attribute.skip_reason = arg.plain_value() + Fuzzer.ARGUMENT_ITERATIONS: + attribute.fuzzer_iterations = type_convert(arg.default(), TYPE_INT) + Fuzzer.ARGUMENT_SEED: + attribute.test_seed = type_convert(arg.default(), TYPE_INT) + ARGUMENT_PARAMETER_SET: + collected_unknown_aruments.clear() + pass + _: + collected_unknown_aruments.append(arg.name()) + + # Verify for unknown arguments + if not collected_unknown_aruments.is_empty(): + attribute.is_skipped = true + attribute.skip_reason = "Unknown test case argument's %s found." % collected_unknown_aruments + + return attribute + + +# We load the test suites with disabled unsafe_method_access to avoid spamming loading errors +# `unsafe_method_access` will happen when using `assert_that` +static func load_with_disabled_warnings(resource_path: String) -> Script: + # grap current level + var unsafe_method_access: Variant = ProjectSettings.get_setting("debug/gdscript/warnings/unsafe_method_access") + + # disable and load the script + ProjectSettings.set_setting("debug/gdscript/warnings/unsafe_method_access", 0) + + var script: Script = ( + GdUnitTestResourceLoader.load_gd_script(resource_path) if resource_path.ends_with("resource") + else ResourceLoader.load(resource_path)) + + # restore + ProjectSettings.set_setting("debug/gdscript/warnings/unsafe_method_access", unsafe_method_access) + return script + + +static func is_test_suite(script: Script) -> bool: + if script is GDScript: + var stack := [script] + while not stack.is_empty(): + var current: Script = stack.pop_front() + var base: Script = current.get_base_script() + if base != null: + if base.resource_path.find("GdUnitTestSuite") != -1: + return true + stack.push_back(base) + elif script != null and script.get_class() == "CSharpScript": + return true + return false + + +static func _is_script_format_supported(resource_path: String) -> bool: + var ext := resource_path.get_extension() + return ext == "gd" or ext == "cs" + + +static func parse_test_suite_name(script: Script) -> String: + return script.resource_path.get_file().replace(".gd", "") + + +func _handle_test_suite_arguments(test_suite: GdUnitTestSuite, script: GDScript, fd: GdFunctionDescriptor) -> void: + for arg in fd.args(): + match arg.name(): + ARGUMENT_SKIP: + var result: Variant = _expression_runner.execute(script, arg.plain_value()) + if result is bool: + test_suite.__is_skipped = result + else: + push_error("Test expression '%s' cannot be evaluated because it is not of type bool!" % arg.plain_value()) + ARGUMENT_SKIP_REASON: + test_suite.__skip_reason = arg.plain_value() + _: + push_error("Unsuported argument `%s` found on before() at '%s'!" % [arg.name(), script.resource_path]) + + +# converts given file name by configured naming convention +static func _to_naming_convention(file_name: String) -> String: + var nc :int = GdUnitSettings.get_setting(GdUnitSettings.TEST_SUITE_NAMING_CONVENTION, 0) + match nc: + GdUnitSettings.NAMING_CONVENTIONS.AUTO_DETECT: + if GdObjects.is_snake_case(file_name): + return GdObjects.to_snake_case(file_name + "Test") + return GdObjects.to_pascal_case(file_name + "Test") + GdUnitSettings.NAMING_CONVENTIONS.SNAKE_CASE: + return GdObjects.to_snake_case(file_name + "Test") + GdUnitSettings.NAMING_CONVENTIONS.PASCAL_CASE: + return GdObjects.to_pascal_case(file_name + "Test") + push_error("Unexpected case") + return "--" + + +static func resolve_test_suite_path(source_script_path: String, test_root_folder: String = "test") -> String: + var file_name := source_script_path.get_basename().get_file() + var suite_name := _to_naming_convention(file_name) + if test_root_folder.is_empty() or test_root_folder == "/": + return source_script_path.replace(file_name, suite_name) + + # is user tmp + if source_script_path.begins_with("user://tmp"): + return normalize_path(source_script_path.replace("user://tmp", "user://tmp/" + test_root_folder)).replace(file_name, suite_name) + + # at first look up is the script under a "src" folder located + var test_suite_path: String + var src_folder := source_script_path.find("/src/") + if src_folder != -1: + test_suite_path = source_script_path.replace("/src/", "/"+test_root_folder+"/") + else: + var paths := source_script_path.split("/", false) + # is a plugin script? + if paths[1] == "addons": + test_suite_path = "%s//addons/%s/%s" % [paths[0], paths[2], test_root_folder] + # rebuild plugin path + for index in range(3, paths.size()): + test_suite_path += "/" + paths[index] + else: + test_suite_path = paths[0] + "//" + test_root_folder + for index in range(1, paths.size()): + test_suite_path += "/" + paths[index] + return normalize_path(test_suite_path).replace(file_name, suite_name) + + +static func normalize_path(path: String) -> String: + return path.replace("///", "/") + + +static func create_test_suite(test_suite_path: String, source_path: String) -> GdUnitResult: + # create directory if not exists + if not DirAccess.dir_exists_absolute(test_suite_path.get_base_dir()): + var error_ := DirAccess.make_dir_recursive_absolute(test_suite_path.get_base_dir()) + if error_ != OK: + return GdUnitResult.error("Can't create directoy at: %s. Error code %s" % [test_suite_path.get_base_dir(), error_]) + var script := GDScript.new() + script.source_code = GdUnitTestSuiteTemplate.build_template(source_path) + var error := ResourceSaver.save(script, test_suite_path) + if error != OK: + return GdUnitResult.error("Can't create test suite at: %s. Error code %s" % [test_suite_path, error]) + return GdUnitResult.success(test_suite_path) + + +static func get_test_case_line_number(resource_path: String, func_name: String) -> int: + var file := FileAccess.open(resource_path, FileAccess.READ) + if file != null: + var line_number := 0 + while not file.eof_reached(): + var row := file.get_line() + line_number += 1 + # ignore comments and empty lines and not test functions + if row.begins_with("#") || row.length() == 0 || row.find("func test_") == -1: + continue + # abort if test case name found + if row.find("func") != -1 and row.find("test_" + func_name) != -1: + return line_number + return -1 + + +func get_extends_classname(resource_path: String) -> String: + var file := FileAccess.open(resource_path, FileAccess.READ) + if file != null: + while not file.eof_reached(): + var row := file.get_line() + # skip comments and empty lines + if row.begins_with("#") || row.length() == 0: + continue + # Stop at first function + if row.contains("func"): + return "" + var result := _regex_extends_clazz_name.search(row) + if result != null: + return result.get_string(1) + return "" + + +static func add_test_case(resource_path: String, func_name: String) -> GdUnitResult: + var script := load_with_disabled_warnings(resource_path) + # count all exiting lines and add two as space to add new test case + var line_number := count_lines(script) + 2 + var func_body := TEST_FUNC_TEMPLATE.replace("${func_name}", func_name) + if Engine.is_editor_hint(): + var settings := EditorInterface.get_editor_settings() + var ident_type :int = settings.get_setting("text_editor/behavior/indent/type") + var ident_size :int = settings.get_setting("text_editor/behavior/indent/size") + if ident_type == 1: + func_body = func_body.replace(" ", "".lpad(ident_size, " ")) + script.source_code += func_body + var error := ResourceSaver.save(script, resource_path) + if error != OK: + return GdUnitResult.error("Can't add test case at: %s to '%s'. Error code %s" % [func_name, resource_path, error]) + return GdUnitResult.success({ "path" : resource_path, "line" : line_number}) + + +static func count_lines(script: Script) -> int: + return script.source_code.split("\n").size() + + +static func test_suite_exists(test_suite_path: String) -> bool: + return FileAccess.file_exists(test_suite_path) + + +static func test_case_exists(test_suite_path :String, func_name :String) -> bool: + if not test_suite_exists(test_suite_path): + return false + var script := load_with_disabled_warnings(test_suite_path) + for f in script.get_script_method_list(): + if f["name"] == "test_" + func_name: + return true + return false + + +static func create_test_case(test_suite_path: String, func_name: String, source_script_path: String) -> GdUnitResult: + if test_case_exists(test_suite_path, func_name): + var line_number := get_test_case_line_number(test_suite_path, func_name) + return GdUnitResult.success({ "path" : test_suite_path, "line" : line_number}) + + if not test_suite_exists(test_suite_path): + var result := create_test_suite(test_suite_path, source_script_path) + if result.is_error(): + return result + return add_test_case(test_suite_path, func_name) diff --git a/addons/gdUnit4/src/core/GdUnitTestSuiteScanner.gd.uid b/addons/gdUnit4/src/core/GdUnitTestSuiteScanner.gd.uid new file mode 100644 index 0000000..a51e208 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitTestSuiteScanner.gd.uid @@ -0,0 +1 @@ +uid://0rglpdu4cghb diff --git a/addons/gdUnit4/src/core/GdUnitTools.gd b/addons/gdUnit4/src/core/GdUnitTools.gd new file mode 100644 index 0000000..0742896 --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitTools.gd @@ -0,0 +1,144 @@ +extends RefCounted + + +static var _richtext_normalize: RegEx + + +static func normalize_text(text :String) -> String: + return text.replace("\r", ""); + + +static func richtext_normalize(input :String) -> String: + if _richtext_normalize == null: + _richtext_normalize = to_regex("\\[/?(b|color|bgcolor|right|table|cell).*?\\]") + return _richtext_normalize.sub(input, "", true).replace("\r", "") + + +static func to_regex(pattern :String) -> RegEx: + var regex := RegEx.new() + var err := regex.compile(pattern) + if err != OK: + push_error("Can't compiling regx '%s'.\n ERROR: %s" % [pattern, error_string(err)]) + return regex + + +static func prints_verbose(message :String) -> void: + if OS.is_stdout_verbose(): + prints(message) + + +static func free_instance(instance :Variant, use_call_deferred :bool = false, is_stdout_verbose := false) -> bool: + if instance is Array: + var as_array: Array = instance + for element: Variant in as_array: + @warning_ignore("return_value_discarded") + free_instance(element) + as_array.clear() + return true + # do not free an already freed instance + if not is_instance_valid(instance): + return false + # do not free a class refernece + @warning_ignore("unsafe_cast") + if typeof(instance) == TYPE_OBJECT and (instance as Object).is_class("GDScriptNativeClass"): + return false + if is_stdout_verbose: + print_verbose("GdUnit4:gc():free instance ", instance) + @warning_ignore("unsafe_cast") + release_double(instance as Object) + if instance is RefCounted: + @warning_ignore("unsafe_cast") + (instance as RefCounted).notification(Object.NOTIFICATION_PREDELETE) + # If scene runner freed we explicit await all inputs are processed + if instance is GdUnitSceneRunnerImpl: + @warning_ignore("unsafe_cast") + await (instance as GdUnitSceneRunnerImpl).await_input_processed() + return true + else: + if instance is Timer: + var timer: Timer = instance + timer.stop() + if use_call_deferred: + timer.call_deferred("free") + else: + timer.free() + await (Engine.get_main_loop() as SceneTree).process_frame + return true + + @warning_ignore("unsafe_cast") + if instance is Node and (instance as Node).get_parent() != null: + var node: Node = instance + if is_stdout_verbose: + print_verbose("GdUnit4:gc():remove node from parent ", node.get_parent(), node) + if use_call_deferred: + node.get_parent().remove_child.call_deferred(node) + #instance.call_deferred("set_owner", null) + else: + node.get_parent().remove_child(node) + if is_stdout_verbose: + print_verbose("GdUnit4:gc():freeing `free()` the instance ", instance) + if use_call_deferred: + @warning_ignore("unsafe_cast") + (instance as Object).call_deferred("free") + else: + @warning_ignore("unsafe_cast") + (instance as Object).free() + return !is_instance_valid(instance) + + +static func _release_connections(instance :Object) -> void: + if is_instance_valid(instance): + # disconnect from all connected signals to force freeing, otherwise it ends up in orphans + for connection in instance.get_incoming_connections(): + var signal_ :Signal = connection["signal"] + var callable_ :Callable = connection["callable"] + #prints(instance, connection) + #prints("signal", signal_.get_name(), signal_.get_object()) + #prints("callable", callable_.get_object()) + if instance.has_signal(signal_.get_name()) and instance.is_connected(signal_.get_name(), callable_): + #prints("disconnect signal", signal_.get_name(), callable_) + instance.disconnect(signal_.get_name(), callable_) + release_timers() + + +static func release_timers() -> void: + # we go the new way to hold all gdunit timers in group 'GdUnitTimers' + var scene_tree := Engine.get_main_loop() as SceneTree + if scene_tree.root == null: + return + for node :Node in scene_tree.root.get_children(): + if is_instance_valid(node) and node.is_in_group("GdUnitTimers"): + if is_instance_valid(node): + scene_tree.root.remove_child.call_deferred(node) + (node as Timer).stop() + node.queue_free() + + +# the finally cleaup unfreed resources and singletons +static func dispose_all(use_call_deferred :bool = false) -> void: + release_timers() + GdUnitSingleton.dispose(use_call_deferred) + GdUnitSignals.dispose() + + +# if instance an mock or spy we need manually freeing the self reference +static func release_double(instance :Object) -> void: + if instance.has_method("__release_double"): + instance.call("__release_double") + + + +static func find_test_case(test_suite: Node, test_case_name: String, index := -1) -> _TestCase: + for test_case: _TestCase in test_suite.get_children(): + if test_case.test_name() == test_case_name: + if index != -1: + if test_case._test_case.attribute_index != index: + continue + return test_case + return null + + +static func register_expect_interupted_by_timeout(test_suite: Node, test_case_name: String) -> void: + var test_case := find_test_case(test_suite, test_case_name) + if test_case: + test_case.expect_to_interupt() diff --git a/addons/gdUnit4/src/core/GdUnitTools.gd.uid b/addons/gdUnit4/src/core/GdUnitTools.gd.uid new file mode 100644 index 0000000..1d8e44e --- /dev/null +++ b/addons/gdUnit4/src/core/GdUnitTools.gd.uid @@ -0,0 +1 @@ +uid://dgw6lp43m1uxa diff --git a/addons/gdUnit4/src/core/GodotVersionFixures.gd b/addons/gdUnit4/src/core/GodotVersionFixures.gd new file mode 100644 index 0000000..5299325 --- /dev/null +++ b/addons/gdUnit4/src/core/GodotVersionFixures.gd @@ -0,0 +1,11 @@ +## This service class contains helpers to wrap Godot functions and handle them carefully depending on the current Godot version +class_name GodotVersionFixures +extends RefCounted + + +# handle global_position fixed by https://github.com/godotengine/godot/pull/88473 +static func set_event_global_position(event: InputEventMouseMotion, global_position: Vector2) -> void: + if Engine.get_version_info().hex >= 0x40202 or Engine.get_version_info().hex == 0x40104: + event.global_position = event.position + else: + event.global_position = global_position diff --git a/addons/gdUnit4/src/core/GodotVersionFixures.gd.uid b/addons/gdUnit4/src/core/GodotVersionFixures.gd.uid new file mode 100644 index 0000000..1224819 --- /dev/null +++ b/addons/gdUnit4/src/core/GodotVersionFixures.gd.uid @@ -0,0 +1 @@ +uid://ctcxd1l26q2ow diff --git a/addons/gdUnit4/src/core/LocalTime.gd b/addons/gdUnit4/src/core/LocalTime.gd new file mode 100644 index 0000000..fabaaf6 --- /dev/null +++ b/addons/gdUnit4/src/core/LocalTime.gd @@ -0,0 +1,114 @@ +# This class provides Date/Time functionallity to Godot +class_name LocalTime +extends Resource + +enum TimeUnit { + DEFAULT = 0, + MILLIS = 1, + SECOND = 2, + MINUTE = 3, + HOUR = 4, + DAY = 5, + MONTH = 6, + YEAR = 7 +} + +const SECONDS_PER_MINUTE:int = 60 +const MINUTES_PER_HOUR:int = 60 +const HOURS_PER_DAY:int = 24 +const MILLIS_PER_SECOND:int = 1000 +const MILLIS_PER_MINUTE:int = MILLIS_PER_SECOND * SECONDS_PER_MINUTE +const MILLIS_PER_HOUR:int = MILLIS_PER_MINUTE * MINUTES_PER_HOUR + +var _time :int +var _hour :int +var _minute :int +var _second :int +var _millisecond :int + + +static func now() -> LocalTime: + return LocalTime.new(_get_system_time_msecs()) + + +static func of_unix_time(time_ms :int) -> LocalTime: + return LocalTime.new(time_ms) + + +static func local_time(hours :int, minutes :int, seconds :int, milliseconds :int) -> LocalTime: + return LocalTime.new(MILLIS_PER_HOUR * hours\ + + MILLIS_PER_MINUTE * minutes\ + + MILLIS_PER_SECOND * seconds\ + + milliseconds) + + +func elapsed_since() -> String: + return LocalTime.elapsed(LocalTime._get_system_time_msecs() - _time) + + +func elapsed_since_ms() -> int: + return LocalTime._get_system_time_msecs() - _time + + +func plus(time_unit :TimeUnit, value :int) -> LocalTime: + var addValue:int = 0 + match time_unit: + TimeUnit.MILLIS: + addValue = value + TimeUnit.SECOND: + addValue = value * MILLIS_PER_SECOND + TimeUnit.MINUTE: + addValue = value * MILLIS_PER_MINUTE + TimeUnit.HOUR: + addValue = value * MILLIS_PER_HOUR + @warning_ignore("return_value_discarded") + _init(_time + addValue) + return self + + +static func elapsed(p_time_ms :int) -> String: + var local_time_ := LocalTime.new(p_time_ms) + if local_time_._hour > 0: + return "%dh %dmin %ds %dms" % [local_time_._hour, local_time_._minute, local_time_._second, local_time_._millisecond] + if local_time_._minute > 0: + return "%dmin %ds %dms" % [local_time_._minute, local_time_._second, local_time_._millisecond] + if local_time_._second > 0: + return "%ds %dms" % [local_time_._second, local_time_._millisecond] + return "%dms" % local_time_._millisecond + + +# create from epoch timestamp in ms +func _init(time: int) -> void: + _time = time + @warning_ignore("integer_division") + _hour = (time / MILLIS_PER_HOUR) % 24 + @warning_ignore("integer_division") + _minute = (time / MILLIS_PER_MINUTE) % 60 + @warning_ignore("integer_division") + _second = (time / MILLIS_PER_SECOND) % 60 + _millisecond = time % 1000 + + +func hour() -> int: + return _hour + + +func minute() -> int: + return _minute + + +func second() -> int: + return _second + + +func millis() -> int: + return _millisecond + + +func _to_string() -> String: + return "%02d:%02d:%02d.%03d" % [_hour, _minute, _second, _millisecond] + + +# wraper to old OS.get_system_time_msecs() function +static func _get_system_time_msecs() -> int: + return Time.get_unix_time_from_system() * 1000 as int diff --git a/addons/gdUnit4/src/core/LocalTime.gd.uid b/addons/gdUnit4/src/core/LocalTime.gd.uid new file mode 100644 index 0000000..0b32717 --- /dev/null +++ b/addons/gdUnit4/src/core/LocalTime.gd.uid @@ -0,0 +1 @@ +uid://dpsbsdwgrdw6t diff --git a/addons/gdUnit4/src/core/_TestCase.gd b/addons/gdUnit4/src/core/_TestCase.gd new file mode 100644 index 0000000..58409e7 --- /dev/null +++ b/addons/gdUnit4/src/core/_TestCase.gd @@ -0,0 +1,243 @@ +class_name _TestCase +extends Node + +signal completed() + + +var _test_case: GdUnitTestCase +var _attribute: TestCaseAttribute +var _current_iteration: int = -1 +var _expect_to_interupt := false +var _timer: Timer +var _interupted: bool = false +var _failed := false +var _parameter_set_resolver: GdUnitTestParameterSetResolver +var _is_disposed := false +var _func_state: Variant + + +func _init(test_case: GdUnitTestCase, attribute: TestCaseAttribute, fd: GdFunctionDescriptor) -> void: + _test_case = test_case + _attribute = attribute + set_function_descriptor(fd) + + +func execute(p_test_parameter := Array(), p_iteration := 0) -> void: + _failure_received(false) + _current_iteration = p_iteration - 1 + if _current_iteration == - 1: + _set_failure_handler() + set_timeout() + + if is_parameterized(): + execute_parameterized() + elif not p_test_parameter.is_empty(): + update_fuzzers(p_test_parameter, p_iteration) + _execute_test_case(test_name(), p_test_parameter) + else: + _execute_test_case(test_name(), []) + await completed + + +func execute_parameterized() -> void: + _failure_received(false) + set_timeout() + + # Resolve parameter set at runtime to include runtime variables + var test_parameters := await _resolve_test_parameters(_test_case.attribute_index) + if test_parameters.is_empty(): + return + + await _execute_test_case(test_name(), test_parameters) + + +func _resolve_test_parameters(attribute_index: int) -> Array: + var result := _parameter_set_resolver.load_parameter_sets(get_parent()) + if result.is_error(): + do_skip(true, result.error_message()) + await (Engine.get_main_loop() as SceneTree).process_frame + completed.emit() + return [] + + # validate the parameter set + var parameter_sets: Array = result.value() + result = _parameter_set_resolver.validate(parameter_sets, attribute_index) + if result.is_error(): + do_skip(true, result.error_message()) + await (Engine.get_main_loop() as SceneTree).process_frame + completed.emit() + return [] + + @warning_ignore("unsafe_method_access") + var test_parameters: Array = parameter_sets[attribute_index].duplicate() + # We need here to add a empty array to override the `test_parameters` to prevent initial "default" parameters from being used. + # This prevents objects in the argument list from being unnecessarily re-instantiated. + test_parameters.append([]) + + return test_parameters + + +func dispose() -> void: + if _is_disposed: + return + _is_disposed = true + Engine.remove_meta("GD_TEST_FAILURE") + stop_timer() + _remove_failure_handler() + _attribute.fuzzers.clear() + + +@warning_ignore("shadowed_variable_base_class", "redundant_await") +func _execute_test_case(name: String, test_parameter: Array) -> void: + # save the function state like GDScriptFunctionState to dispose at test timeout to prevent orphan state + _func_state = get_parent().callv(name, test_parameter) + await _func_state + # needs at least on await otherwise it breaks the awaiting chain + await (Engine.get_main_loop() as SceneTree).process_frame + completed.emit() + + +func update_fuzzers(input_values: Array, iteration: int) -> void: + for fuzzer :Variant in input_values: + if fuzzer is Fuzzer: + fuzzer._iteration_index = iteration + 1 + + +func set_timeout() -> void: + if is_instance_valid(_timer): + return + var time: float = _attribute.timeout / 1000.0 + _timer = Timer.new() + add_child(_timer) + _timer.set_name("gdunit_test_case_timer_%d" % _timer.get_instance_id()) + @warning_ignore("return_value_discarded") + _timer.timeout.connect(do_interrupt, CONNECT_DEFERRED) + _timer.set_one_shot(true) + _timer.set_wait_time(time) + _timer.set_autostart(false) + _timer.start() + + +func do_interrupt() -> void: + _interupted = true + # We need to dispose manually the function state here + GdObjects.dispose_function_state(_func_state) + if not is_expect_interupted(): + var execution_context:= GdUnitThreadManager.get_current_context().get_execution_context() + if is_fuzzed(): + execution_context.add_report(GdUnitReport.new()\ + .create(GdUnitReport.INTERUPTED, line_number(), GdAssertMessages.fuzzer_interuped(_current_iteration, "timedout"))) + else: + execution_context.add_report(GdUnitReport.new()\ + .create(GdUnitReport.INTERUPTED, line_number(), GdAssertMessages.test_timeout(_attribute.timeout))) + completed.emit() + + +func _set_failure_handler() -> void: + if not GdUnitSignals.instance().gdunit_set_test_failed.is_connected(_failure_received): + @warning_ignore("return_value_discarded") + GdUnitSignals.instance().gdunit_set_test_failed.connect(_failure_received) + + +func _remove_failure_handler() -> void: + if GdUnitSignals.instance().gdunit_set_test_failed.is_connected(_failure_received): + GdUnitSignals.instance().gdunit_set_test_failed.disconnect(_failure_received) + + +func _failure_received(is_failed: bool) -> void: + # is already failed? + if _failed: + return + _failed = is_failed + Engine.set_meta("GD_TEST_FAILURE", is_failed) + + +func stop_timer() -> void: + # finish outstanding timeouts + if is_instance_valid(_timer): + _timer.stop() + _timer.call_deferred("free") + _timer = null + + +func expect_to_interupt() -> void: + _expect_to_interupt = true + + +func is_interupted() -> bool: + return _interupted + + +func is_expect_interupted() -> bool: + return _expect_to_interupt + + +func is_parameterized() -> bool: + return _parameter_set_resolver.is_parameterized() + + +func is_skipped() -> bool: + return _attribute.is_skipped + + +func skip_info() -> String: + return _attribute.skip_reason + + +func id() -> GdUnitGUID: + return _test_case.guid + + +func test_name() -> String: + return _test_case.test_name + + +@warning_ignore("native_method_override") +func get_name() -> StringName: + return _test_case.test_name + + +func line_number() -> int: + return _test_case.line_number + + +func iterations() -> int: + return _attribute.fuzzer_iterations + + +func seed_value() -> int: + return _attribute.test_seed + + +func is_fuzzed() -> bool: + return not _attribute.fuzzers.is_empty() + + +func fuzzer_arguments() -> Array[GdFunctionArgument]: + return _attribute.fuzzers + + +func script_path() -> String: + return _test_case.source_file + + +func ResourcePath() -> String: + return _test_case.source_file + + +func generate_seed() -> void: + if _attribute.test_seed != -1: + seed(_attribute.test_seed) + + +func do_skip(skipped: bool, reason: String="") -> void: + _attribute.is_skipped = skipped + _attribute.skip_reason = reason + + +func set_function_descriptor(fd: GdFunctionDescriptor) -> void: + _parameter_set_resolver = GdUnitTestParameterSetResolver.new(fd) + + +func _to_string() -> String: + return "%s :%d (%dms)" % [get_name(), _test_case.line_number, _attribute.timeout] diff --git a/addons/gdUnit4/src/core/_TestCase.gd.uid b/addons/gdUnit4/src/core/_TestCase.gd.uid new file mode 100644 index 0000000..773c5e4 --- /dev/null +++ b/addons/gdUnit4/src/core/_TestCase.gd.uid @@ -0,0 +1 @@ +uid://bk3ollgp8yni5 diff --git a/addons/gdUnit4/src/core/assets/touch-button.png b/addons/gdUnit4/src/core/assets/touch-button.png new file mode 100644 index 0000000..23f46ef Binary files /dev/null and b/addons/gdUnit4/src/core/assets/touch-button.png differ diff --git a/addons/gdUnit4/src/core/assets/touch-button.png.import b/addons/gdUnit4/src/core/assets/touch-button.png.import new file mode 100644 index 0000000..e02f2b7 --- /dev/null +++ b/addons/gdUnit4/src/core/assets/touch-button.png.import @@ -0,0 +1,40 @@ +[remap] + +importer="texture" +type="CompressedTexture2D" +uid="uid://covtcq4g27io3" +path="res://.godot/imported/touch-button.png-2fff40c8520d8e97a57db1b2b043f641.ctex" +metadata={ +"vram_texture": false +} + +[deps] + +source_file="res://addons/gdUnit4/src/core/assets/touch-button.png" +dest_files=["res://.godot/imported/touch-button.png-2fff40c8520d8e97a57db1b2b043f641.ctex"] + +[params] + +compress/mode=0 +compress/high_quality=false +compress/lossy_quality=0.7 +compress/uastc_level=0 +compress/rdo_quality_loss=0.0 +compress/hdr_compression=1 +compress/normal_map=0 +compress/channel_pack=0 +mipmaps/generate=false +mipmaps/limit=-1 +roughness/mode=0 +roughness/src_normal="" +process/channel_remap/red=0 +process/channel_remap/green=1 +process/channel_remap/blue=2 +process/channel_remap/alpha=3 +process/fix_alpha_border=true +process/premult_alpha=false +process/normal_map_invert_y=false +process/hdr_as_srgb=false +process/hdr_clamp_exposure=false +process/size_limit=0 +detect_3d/compress_to=1 diff --git a/addons/gdUnit4/src/core/attributes/TestCaseAttribute.gd b/addons/gdUnit4/src/core/attributes/TestCaseAttribute.gd new file mode 100644 index 0000000..cf7a2b9 --- /dev/null +++ b/addons/gdUnit4/src/core/attributes/TestCaseAttribute.gd @@ -0,0 +1,76 @@ +class_name TestCaseAttribute +extends Resource +## Holds configuration and metadata for individual test cases.[br] +## [br] +## This class defines test behaviors and properties such as:[br] +## - Test timeouts[br] +## - Skip conditions[br] +## - Fuzzing parameters[br] +## - Random seed values[br] + + +## When set, no specific timeout value is configured and test will use the [code]test_timeout[/code][br] +## value from [GdUnitSettings]. +const DEFAULT_TIMEOUT := -1 + + +## The maximum time in milliseconds for test completion.[br] +## The test fails if execution exceeds this duration.[br] +## [br] +## When set to [constant DEFAULT_TIMEOUT], uses the value from [method GdUnitSettings.test_timeout]. +var timeout: int = DEFAULT_TIMEOUT: + set(value): + timeout = value + get: + if timeout == DEFAULT_TIMEOUT: + # get the default timeout from the settings + timeout = GdUnitSettings.test_timeout() + return timeout + + +## The seed used for random number generation in the test.[br] +## Ensures reproducible results for randomized test scenarios.[br] +## A value of -1 indicates no specific seed is set. +var test_seed: int = -1 + + +## Controls whether this test should be skipped during execution.[br] +## Useful for temporarily disabling tests without removing them. +var is_skipped := false + + +## Documents why the test is being skipped.[br] +## [br] +## Should explain the reason for skipping and ideally include:[br] +## - Why the test was disabled[br] +## - Under what conditions it should be re-enabled[br] +## - Any related issues or tickets +var skip_reason := "Unknown" + + +## Number of iterations to run when using fuzzers.[br] +## [br] +## Fuzzers generate random test data to help find edge cases.[br] +## Higher values provide better coverage but increase test duration. +var fuzzer_iterations: int = Fuzzer.ITERATION_DEFAULT_COUNT + + +## Array of fuzzer configurations for test parameters.[br] +## [br] +## Each [GdFunctionArgument] defines how random test data[br] +## should be generated for a particular parameter. +var fuzzers: Array[GdFunctionArgument] = [] + + +# There is a bug in `duplicate` see https://github.com/godotengine/godot/issues/98644 +# we need in addition to overwrite default values with the source values +@warning_ignore("native_method_override") +func clone() -> Resource: + var copy: TestCaseAttribute = TestCaseAttribute.new() + copy.timeout = timeout + copy.test_seed = test_seed + copy.is_skipped = is_skipped + copy.skip_reason = skip_reason + copy.fuzzer_iterations = fuzzer_iterations + copy.fuzzers = fuzzers.duplicate() + return copy diff --git a/addons/gdUnit4/src/core/attributes/TestCaseAttribute.gd.uid b/addons/gdUnit4/src/core/attributes/TestCaseAttribute.gd.uid new file mode 100644 index 0000000..5dd6c11 --- /dev/null +++ b/addons/gdUnit4/src/core/attributes/TestCaseAttribute.gd.uid @@ -0,0 +1 @@ +uid://bw0mu8xsmkv7 diff --git a/addons/gdUnit4/src/core/command/GdUnitCommand.gd b/addons/gdUnit4/src/core/command/GdUnitCommand.gd new file mode 100644 index 0000000..659b6a3 --- /dev/null +++ b/addons/gdUnit4/src/core/command/GdUnitCommand.gd @@ -0,0 +1,41 @@ +class_name GdUnitCommand +extends RefCounted + + +func _init(p_name :String, p_is_enabled: Callable, p_runnable: Callable, p_shortcut :GdUnitShortcut.ShortCut = GdUnitShortcut.ShortCut.NONE) -> void: + assert(p_name != null, "(%s) missing parameter 'name'" % p_name) + assert(p_is_enabled != null, "(%s) missing parameter 'is_enabled'" % p_name) + assert(p_runnable != null, "(%s) missing parameter 'runnable'" % p_name) + assert(p_shortcut != null, "(%s) missing parameter 'shortcut'" % p_name) + self.name = p_name + self.is_enabled = p_is_enabled + self.shortcut = p_shortcut + self.runnable = p_runnable + + +var name: String: + set(value): + name = value + get: + return name + + +var shortcut: GdUnitShortcut.ShortCut: + set(value): + shortcut = value + get: + return shortcut + + +var is_enabled: Callable: + set(value): + is_enabled = value + get: + return is_enabled + + +var runnable: Callable: + set(value): + runnable = value + get: + return runnable diff --git a/addons/gdUnit4/src/core/command/GdUnitCommand.gd.uid b/addons/gdUnit4/src/core/command/GdUnitCommand.gd.uid new file mode 100644 index 0000000..324e572 --- /dev/null +++ b/addons/gdUnit4/src/core/command/GdUnitCommand.gd.uid @@ -0,0 +1 @@ +uid://b6jqo0obi0tqw diff --git a/addons/gdUnit4/src/core/command/GdUnitCommandHandler.gd b/addons/gdUnit4/src/core/command/GdUnitCommandHandler.gd new file mode 100644 index 0000000..c8130cc --- /dev/null +++ b/addons/gdUnit4/src/core/command/GdUnitCommandHandler.gd @@ -0,0 +1,429 @@ +class_name GdUnitCommandHandler +extends Object + +signal gdunit_runner_start() +signal gdunit_runner_stop(client_id :int) + + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") + +const CMD_RUN_OVERALL = "Debug Overall TestSuites" +const CMD_RUN_TESTCASE = "Run TestCases" +const CMD_RUN_TESTCASE_DEBUG = "Run TestCases (Debug)" +const CMD_RUN_TESTSUITE = "Run TestSuites" +const CMD_RUN_TESTSUITE_DEBUG = "Run TestSuites (Debug)" +const CMD_RERUN_TESTS = "ReRun Tests" +const CMD_RERUN_TESTS_DEBUG = "ReRun Tests (Debug)" +const CMD_STOP_TEST_RUN = "Stop Test Run" +const CMD_CREATE_TESTCASE = "Create TestCase" + +const SETTINGS_SHORTCUT_MAPPING := { + "N/A" : GdUnitShortcut.ShortCut.NONE, + GdUnitSettings.SHORTCUT_INSPECTOR_RERUN_TEST : GdUnitShortcut.ShortCut.RERUN_TESTS, + GdUnitSettings.SHORTCUT_INSPECTOR_RERUN_TEST_DEBUG : GdUnitShortcut.ShortCut.RERUN_TESTS_DEBUG, + GdUnitSettings.SHORTCUT_INSPECTOR_RUN_TEST_OVERALL : GdUnitShortcut.ShortCut.RUN_TESTS_OVERALL, + GdUnitSettings.SHORTCUT_INSPECTOR_RUN_TEST_STOP : GdUnitShortcut.ShortCut.STOP_TEST_RUN, + GdUnitSettings.SHORTCUT_EDITOR_RUN_TEST : GdUnitShortcut.ShortCut.RUN_TESTCASE, + GdUnitSettings.SHORTCUT_EDITOR_RUN_TEST_DEBUG : GdUnitShortcut.ShortCut.RUN_TESTCASE_DEBUG, + GdUnitSettings.SHORTCUT_EDITOR_CREATE_TEST : GdUnitShortcut.ShortCut.CREATE_TEST, + GdUnitSettings.SHORTCUT_FILESYSTEM_RUN_TEST : GdUnitShortcut.ShortCut.RUN_TESTSUITE, + GdUnitSettings.SHORTCUT_FILESYSTEM_RUN_TEST_DEBUG : GdUnitShortcut.ShortCut.RUN_TESTSUITE_DEBUG +} + +# the current test runner config +var _runner_config := GdUnitRunnerConfig.new() + +# holds the current connected gdUnit runner client id +var _client_id: int +# if no debug mode we have an process id +var _current_runner_process_id: int = 0 +# hold is current an test running +var _is_running: bool = false +# holds if the current running tests started in debug mode +var _running_debug_mode: bool + +var _commands := {} +var _shortcuts := {} + + +static func instance() -> GdUnitCommandHandler: + return GdUnitSingleton.instance("GdUnitCommandHandler", func() -> GdUnitCommandHandler: return GdUnitCommandHandler.new()) + + +@warning_ignore("return_value_discarded") +func _init() -> void: + assert_shortcut_mappings(SETTINGS_SHORTCUT_MAPPING) + + GdUnitSignals.instance().gdunit_event.connect(_on_event) + GdUnitSignals.instance().gdunit_client_connected.connect(_on_client_connected) + GdUnitSignals.instance().gdunit_client_disconnected.connect(_on_client_disconnected) + GdUnitSignals.instance().gdunit_settings_changed.connect(_on_settings_changed) + # preload previous test execution + @warning_ignore("return_value_discarded") + _runner_config.load_config() + + init_shortcuts() + var is_running := func(_script :Script) -> bool: return _is_running + var is_not_running := func(_script :Script) -> bool: return !_is_running + register_command(GdUnitCommand.new(CMD_RUN_OVERALL, is_not_running, cmd_run_overall.bind(true), GdUnitShortcut.ShortCut.RUN_TESTS_OVERALL)) + register_command(GdUnitCommand.new(CMD_RUN_TESTCASE, is_not_running, cmd_editor_run_test.bind(false), GdUnitShortcut.ShortCut.RUN_TESTCASE)) + register_command(GdUnitCommand.new(CMD_RUN_TESTCASE_DEBUG, is_not_running, cmd_editor_run_test.bind(true), GdUnitShortcut.ShortCut.RUN_TESTCASE_DEBUG)) + register_command(GdUnitCommand.new(CMD_RUN_TESTSUITE, is_not_running, cmd_run_test_suites.bind(false), GdUnitShortcut.ShortCut.RUN_TESTSUITE)) + register_command(GdUnitCommand.new(CMD_RUN_TESTSUITE_DEBUG, is_not_running, cmd_run_test_suites.bind(true), GdUnitShortcut.ShortCut.RUN_TESTSUITE_DEBUG)) + register_command(GdUnitCommand.new(CMD_RERUN_TESTS, is_not_running, cmd_run.bind(false), GdUnitShortcut.ShortCut.RERUN_TESTS)) + register_command(GdUnitCommand.new(CMD_RERUN_TESTS_DEBUG, is_not_running, cmd_run.bind(true), GdUnitShortcut.ShortCut.RERUN_TESTS_DEBUG)) + register_command(GdUnitCommand.new(CMD_CREATE_TESTCASE, is_not_running, cmd_create_test, GdUnitShortcut.ShortCut.CREATE_TEST)) + register_command(GdUnitCommand.new(CMD_STOP_TEST_RUN, is_running, cmd_stop.bind(_client_id), GdUnitShortcut.ShortCut.STOP_TEST_RUN)) + + # schedule discover tests if enabled and running inside the editor + if Engine.is_editor_hint() and GdUnitSettings.is_test_discover_enabled(): + var timer :SceneTreeTimer = (Engine.get_main_loop() as SceneTree).create_timer(5) + @warning_ignore("return_value_discarded") + timer.timeout.connect(cmd_discover_tests) + + +func _notification(what: int) -> void: + if what == NOTIFICATION_PREDELETE: + _commands.clear() + _shortcuts.clear() + + +func _do_process() -> void: + check_test_run_stopped_manually() + + +# is checking if the user has press the editor stop scene +func check_test_run_stopped_manually() -> void: + if is_test_running_but_stop_pressed(): + if GdUnitSettings.is_verbose_assert_warnings(): + push_warning("Test Runner scene was stopped manually, force stopping the current test run!") + cmd_stop(_client_id) + + +func is_test_running_but_stop_pressed() -> bool: + return _running_debug_mode and _is_running and not EditorInterface.is_playing_scene() + + +func assert_shortcut_mappings(mappings: Dictionary) -> void: + for shortcut: int in GdUnitShortcut.ShortCut.values(): + assert(mappings.values().has(shortcut), "missing settings mapping for shortcut '%s'!" % GdUnitShortcut.ShortCut.keys()[shortcut]) + + +func init_shortcuts() -> void: + for shortcut: int in GdUnitShortcut.ShortCut.values(): + if shortcut == GdUnitShortcut.ShortCut.NONE: + continue + var property_name: String = SETTINGS_SHORTCUT_MAPPING.find_key(shortcut) + var property := GdUnitSettings.get_property(property_name) + var keys := GdUnitShortcut.default_keys(shortcut) + if property != null: + keys = property.value() + var inputEvent := create_shortcut_input_even(keys) + register_shortcut(shortcut, inputEvent) + + +func create_shortcut_input_even(key_codes: PackedInt32Array) -> InputEventKey: + var inputEvent := InputEventKey.new() + inputEvent.pressed = true + for key_code in key_codes: + match key_code: + KEY_ALT: + inputEvent.alt_pressed = true + KEY_SHIFT: + inputEvent.shift_pressed = true + KEY_CTRL: + inputEvent.ctrl_pressed = true + _: + inputEvent.keycode = key_code as Key + inputEvent.physical_keycode = key_code as Key + return inputEvent + + +func register_shortcut(p_shortcut: GdUnitShortcut.ShortCut, p_input_event: InputEvent) -> void: + GdUnitTools.prints_verbose("register shortcut: '%s' to '%s'" % [GdUnitShortcut.ShortCut.keys()[p_shortcut], p_input_event.as_text()]) + var shortcut := Shortcut.new() + shortcut.set_events([p_input_event]) + var command_name := get_shortcut_command(p_shortcut) + _shortcuts[p_shortcut] = GdUnitShortcutAction.new(p_shortcut, shortcut, command_name) + + +func get_shortcut(shortcut_type: GdUnitShortcut.ShortCut) -> Shortcut: + return get_shortcut_action(shortcut_type).shortcut + + +func get_shortcut_action(shortcut_type: GdUnitShortcut.ShortCut) -> GdUnitShortcutAction: + return _shortcuts.get(shortcut_type) + + +func get_shortcut_command(p_shortcut: GdUnitShortcut.ShortCut) -> String: + return GdUnitShortcut.CommandMapping.get(p_shortcut, "unknown command") + + +func register_command(p_command: GdUnitCommand) -> void: + _commands[p_command.name] = p_command + + +func command(cmd_name: String) -> GdUnitCommand: + return _commands.get(cmd_name) + + +func cmd_run_test_suites(scripts: Array[Script], debug: bool, rerun := false) -> void: + # Update test discovery + GdUnitSignals.instance().gdunit_event.emit(GdUnitEventTestDiscoverStart.new()) + var tests_to_execute: Array[GdUnitTestCase] = [] + for script in scripts: + GdUnitTestDiscoverer.discover_tests(script, func(test_case: GdUnitTestCase) -> void: + tests_to_execute.append(test_case) + GdUnitTestDiscoverSink.discover(test_case) + ) + GdUnitSignals.instance().gdunit_event.emit(GdUnitEventTestDiscoverEnd.new(0, 0)) + GdUnitTestDiscoverer.console_log_discover_results(tests_to_execute) + + # create new runner runner_config for fresh run otherwise use saved one + if not rerun: + var result := _runner_config.clear()\ + .add_test_cases(tests_to_execute)\ + .save_config() + if result.is_error(): + push_error(result.error_message()) + return + cmd_run(debug) + + +func cmd_run_test_case(script: Script, test_case: String, test_param_index: int, debug: bool, rerun := false) -> void: + # Update test discovery + var tests_to_execute: Array[GdUnitTestCase] = [] + GdUnitSignals.instance().gdunit_event.emit(GdUnitEventTestDiscoverStart.new()) + GdUnitTestDiscoverer.discover_tests(script, func(test: GdUnitTestCase) -> void: + # We filter for a single test + if test.test_name == test_case: + # We only add selected parameterized test to the execution list + if test_param_index == -1: + tests_to_execute.append(test) + elif test.attribute_index == test_param_index: + tests_to_execute.append(test) + GdUnitTestDiscoverSink.discover(test) + ) + GdUnitSignals.instance().gdunit_event.emit(GdUnitEventTestDiscoverEnd.new(0, 0)) + GdUnitTestDiscoverer.console_log_discover_results(tests_to_execute) + + # create new runner config for fresh run otherwise use saved one + if not rerun: + var result := _runner_config.clear()\ + .add_test_cases(tests_to_execute)\ + .save_config() + if result.is_error(): + push_error(result.error_message()) + return + cmd_run(debug) + + +func cmd_run_tests(tests_to_execute: Array[GdUnitTestCase], debug: bool) -> void: + # Save tests to runner config before execute + var result := _runner_config.clear()\ + .add_test_cases(tests_to_execute)\ + .save_config() + if result.is_error(): + push_error(result.error_message()) + return + cmd_run(debug) + + +func cmd_run_overall(debug: bool) -> void: + var tests_to_execute := await GdUnitTestDiscoverer.run() + var result := _runner_config.clear()\ + .add_test_cases(tests_to_execute)\ + .save_config() + if result.is_error(): + push_error(result.error_message()) + return + cmd_run(debug) + + +func cmd_run(debug: bool) -> void: + # don't start is already running + if _is_running: + return + + # save current selected excution config + var server_port: int = Engine.get_meta("gdunit_server_port") + var result := _runner_config.set_server_port(server_port).save_config() + if result.is_error(): + push_error(result.error_message()) + return + # before start we have to save all changes + ScriptEditorControls.save_all_open_script() + gdunit_runner_start.emit() + _current_runner_process_id = -1 + _running_debug_mode = debug + if debug: + run_debug_mode() + else: + run_release_mode() + + +func cmd_stop(client_id: int) -> void: + # don't stop if is already stopped + if not _is_running: + return + _is_running = false + gdunit_runner_stop.emit(client_id) + if _running_debug_mode: + EditorInterface.stop_playing_scene() + elif _current_runner_process_id > 0: + if OS.is_process_running(_current_runner_process_id): + var result := OS.kill(_current_runner_process_id) + if result != OK: + push_error("ERROR checked stopping GdUnit Test Runner. error code: %s" % result) + _current_runner_process_id = -1 + + +func cmd_editor_run_test(debug: bool) -> void: + if is_active_script_editor(): + var cursor_line := active_base_editor().get_caret_line() + #run test case? + var regex := RegEx.new() + @warning_ignore("return_value_discarded") + regex.compile("(^func[ ,\t])(test_[a-zA-Z0-9_]*)") + var result := regex.search(active_base_editor().get_line(cursor_line)) + if result: + var func_name := result.get_string(2).strip_edges() + if func_name.begins_with("test_"): + cmd_run_test_case(active_script(), func_name, -1, debug) + return + # otherwise run the full test suite + var selected_test_suites: Array[Script] = [active_script()] + cmd_run_test_suites(selected_test_suites, debug) + + +func cmd_create_test() -> void: + if not is_active_script_editor(): + return + var cursor_line := active_base_editor().get_caret_line() + var result := GdUnitTestSuiteBuilder.create(active_script(), cursor_line) + if result.is_error(): + # show error dialog + push_error("Failed to create test case: %s" % result.error_message()) + return + var info: Dictionary = result.value() + var script_path: String = info.get("path") + var script_line: int = info.get("line") + ScriptEditorControls.edit_script(script_path, script_line) + + +func cmd_discover_tests() -> void: + await GdUnitTestDiscoverer.run() + + +static func scan_all_test_directories(root: String) -> PackedStringArray: + var base_directory := "res://" + # If the test root folder is configured as blank, "/", or "res://", use the root folder as described in the settings panel + if root.is_empty() or root == "/" or root == base_directory: + return [base_directory] + return scan_test_directories(base_directory, root, []) + + +static func scan_test_directories(base_directory: String, test_directory: String, test_suite_paths: PackedStringArray) -> PackedStringArray: + print_verbose("Scannning for test directory '%s' at %s" % [test_directory, base_directory]) + for directory in DirAccess.get_directories_at(base_directory): + if directory.begins_with("."): + continue + var current_directory := normalize_path(base_directory + "/" + directory) + if GdUnitTestSuiteScanner.exclude_scan_directories.has(current_directory): + continue + if match_test_directory(directory, test_directory): + @warning_ignore("return_value_discarded") + test_suite_paths.append(current_directory) + else: + @warning_ignore("return_value_discarded") + scan_test_directories(current_directory, test_directory, test_suite_paths) + return test_suite_paths + + +static func normalize_path(path: String) -> String: + return path.replace("///", "//") + + +static func match_test_directory(directory: String, test_directory: String) -> bool: + return directory == test_directory or test_directory.is_empty() or test_directory == "/" or test_directory == "res://" + + +func run_debug_mode() -> void: + EditorInterface.play_custom_scene("res://addons/gdUnit4/src/core/runners/GdUnitTestRunner.tscn") + _is_running = true + + +func run_release_mode() -> void: + var arguments := Array() + if OS.is_stdout_verbose(): + arguments.append("--verbose") + arguments.append("--no-window") + arguments.append("--path") + arguments.append(ProjectSettings.globalize_path("res://")) + arguments.append("res://addons/gdUnit4/src/core/runners/GdUnitTestRunner.tscn") + _current_runner_process_id = OS.create_process(OS.get_executable_path(), arguments, false); + _is_running = true + + +func is_active_script_editor() -> bool: + return EditorInterface.get_script_editor().get_current_editor() != null + + +func active_base_editor() -> TextEdit: + return EditorInterface.get_script_editor().get_current_editor().get_base_editor() + + +func active_script() -> Script: + return EditorInterface.get_script_editor().get_current_script() + + + +################################################################################ +# signals handles +################################################################################ +func _on_event(event: GdUnitEvent) -> void: + if event.type() == GdUnitEvent.SESSION_CLOSE: + cmd_stop(_client_id) + + +func _on_stop_pressed() -> void: + cmd_stop(_client_id) + + +func _on_run_pressed(debug := false) -> void: + cmd_run(debug) + + +func _on_run_overall_pressed(_debug := false) -> void: + cmd_run_overall(true) + + +func _on_settings_changed(property: GdUnitProperty) -> void: + if SETTINGS_SHORTCUT_MAPPING.has(property.name()): + var shortcut :GdUnitShortcut.ShortCut = SETTINGS_SHORTCUT_MAPPING.get(property.name()) + var value: PackedInt32Array = property.value() + var input_event := create_shortcut_input_even(value) + prints("Shortcut changed: '%s' to '%s'" % [GdUnitShortcut.ShortCut.keys()[shortcut], input_event.as_text()]) + var action := get_shortcut_action(shortcut) + if action != null: + action.update_shortcut(input_event) + else: + register_shortcut(shortcut, input_event) + if property.name() == GdUnitSettings.TEST_DISCOVER_ENABLED: + var timer :SceneTreeTimer = (Engine.get_main_loop() as SceneTree).create_timer(3) + @warning_ignore("return_value_discarded") + timer.timeout.connect(cmd_discover_tests) + + +################################################################################ +# Network stuff +################################################################################ +func _on_client_connected(client_id: int) -> void: + _client_id = client_id + + +func _on_client_disconnected(client_id: int) -> void: + # only stops is not in debug mode running and the current client + if not _running_debug_mode and _client_id == client_id: + cmd_stop(client_id) + _client_id = -1 diff --git a/addons/gdUnit4/src/core/command/GdUnitCommandHandler.gd.uid b/addons/gdUnit4/src/core/command/GdUnitCommandHandler.gd.uid new file mode 100644 index 0000000..e285622 --- /dev/null +++ b/addons/gdUnit4/src/core/command/GdUnitCommandHandler.gd.uid @@ -0,0 +1 @@ +uid://dq7gchyc2bw6h diff --git a/addons/gdUnit4/src/core/command/GdUnitShortcut.gd b/addons/gdUnit4/src/core/command/GdUnitShortcut.gd new file mode 100644 index 0000000..4a8aa29 --- /dev/null +++ b/addons/gdUnit4/src/core/command/GdUnitShortcut.gd @@ -0,0 +1,66 @@ +class_name GdUnitShortcut +extends RefCounted + + +enum ShortCut { + NONE, + RUN_TESTS_OVERALL, + RUN_TESTCASE, + RUN_TESTCASE_DEBUG, + RUN_TESTSUITE, + RUN_TESTSUITE_DEBUG, + RERUN_TESTS, + RERUN_TESTS_DEBUG, + STOP_TEST_RUN, + CREATE_TEST, +} + + +const CommandMapping = { + ShortCut.RUN_TESTS_OVERALL: GdUnitCommandHandler.CMD_RUN_OVERALL, + ShortCut.RUN_TESTCASE: GdUnitCommandHandler.CMD_RUN_TESTCASE, + ShortCut.RUN_TESTCASE_DEBUG: GdUnitCommandHandler.CMD_RUN_TESTCASE_DEBUG, + ShortCut.RUN_TESTSUITE: GdUnitCommandHandler.CMD_RUN_TESTSUITE, + ShortCut.RUN_TESTSUITE_DEBUG: GdUnitCommandHandler.CMD_RUN_TESTSUITE_DEBUG, + ShortCut.RERUN_TESTS: GdUnitCommandHandler.CMD_RERUN_TESTS, + ShortCut.RERUN_TESTS_DEBUG: GdUnitCommandHandler.CMD_RERUN_TESTS_DEBUG, + ShortCut.STOP_TEST_RUN: GdUnitCommandHandler.CMD_STOP_TEST_RUN, + ShortCut.CREATE_TEST: GdUnitCommandHandler.CMD_CREATE_TESTCASE, +} + + +const DEFAULTS_MACOS := { + ShortCut.NONE : [], + ShortCut.RUN_TESTCASE : [Key.KEY_META, Key.KEY_ALT, Key.KEY_F5], + ShortCut.RUN_TESTCASE_DEBUG : [Key.KEY_META, Key.KEY_ALT, Key.KEY_F6], + ShortCut.RUN_TESTSUITE : [Key.KEY_META, Key.KEY_ALT, Key.KEY_F5], + ShortCut.RUN_TESTSUITE_DEBUG : [Key.KEY_META, Key.KEY_ALT, Key.KEY_F6], + ShortCut.RUN_TESTS_OVERALL : [Key.KEY_META, Key.KEY_F7], + ShortCut.STOP_TEST_RUN : [Key.KEY_META, Key.KEY_F8], + ShortCut.RERUN_TESTS : [Key.KEY_META, Key.KEY_F5], + ShortCut.RERUN_TESTS_DEBUG : [Key.KEY_META, Key.KEY_F6], + ShortCut.CREATE_TEST : [Key.KEY_META, Key.KEY_ALT, Key.KEY_F10], +} + +const DEFAULTS_WINDOWS := { + ShortCut.NONE : [], + ShortCut.RUN_TESTCASE : [Key.KEY_CTRL, Key.KEY_ALT, Key.KEY_F5], + ShortCut.RUN_TESTCASE_DEBUG : [Key.KEY_CTRL,Key.KEY_ALT, Key.KEY_F6], + ShortCut.RUN_TESTSUITE : [Key.KEY_CTRL, Key.KEY_ALT, Key.KEY_F5], + ShortCut.RUN_TESTSUITE_DEBUG : [Key.KEY_CTRL,Key.KEY_ALT, Key.KEY_F6], + ShortCut.RUN_TESTS_OVERALL : [Key.KEY_CTRL, Key.KEY_F7], + ShortCut.STOP_TEST_RUN : [Key.KEY_CTRL, Key.KEY_F8], + ShortCut.RERUN_TESTS : [Key.KEY_CTRL, Key.KEY_F5], + ShortCut.RERUN_TESTS_DEBUG : [Key.KEY_CTRL, Key.KEY_F6], + ShortCut.CREATE_TEST : [Key.KEY_CTRL, Key.KEY_ALT, Key.KEY_F10], +} + + +static func default_keys(shortcut :ShortCut) -> PackedInt32Array: + match OS.get_name().to_lower(): + 'windows': + return DEFAULTS_WINDOWS[shortcut] + 'macos': + return DEFAULTS_MACOS[shortcut] + _: + return DEFAULTS_WINDOWS[shortcut] diff --git a/addons/gdUnit4/src/core/command/GdUnitShortcut.gd.uid b/addons/gdUnit4/src/core/command/GdUnitShortcut.gd.uid new file mode 100644 index 0000000..bada408 --- /dev/null +++ b/addons/gdUnit4/src/core/command/GdUnitShortcut.gd.uid @@ -0,0 +1 @@ +uid://clxc017i3aoyy diff --git a/addons/gdUnit4/src/core/command/GdUnitShortcutAction.gd b/addons/gdUnit4/src/core/command/GdUnitShortcutAction.gd new file mode 100644 index 0000000..c49e83e --- /dev/null +++ b/addons/gdUnit4/src/core/command/GdUnitShortcutAction.gd @@ -0,0 +1,40 @@ +class_name GdUnitShortcutAction +extends RefCounted + + +func _init(p_type :GdUnitShortcut.ShortCut, p_shortcut :Shortcut, p_command :String) -> void: + assert(p_type != null, "missing parameter 'type'") + assert(p_shortcut != null, "missing parameter 'shortcut'") + assert(p_command != null, "missing parameter 'command'") + self.type = p_type + self.shortcut = p_shortcut + self.command = p_command + + +var type: GdUnitShortcut.ShortCut: + set(value): + type = value + get: + return type + + +var shortcut: Shortcut: + set(value): + shortcut = value + get: + return shortcut + + +var command: String: + set(value): + command = value + get: + return command + + +func update_shortcut(input_event: InputEventKey) -> void: + shortcut.set_events([input_event]) + + +func _to_string() -> String: + return "GdUnitShortcutAction: %s (%s) -> %s" % [GdUnitShortcut.ShortCut.keys()[type], shortcut.get_as_text(), command] diff --git a/addons/gdUnit4/src/core/command/GdUnitShortcutAction.gd.uid b/addons/gdUnit4/src/core/command/GdUnitShortcutAction.gd.uid new file mode 100644 index 0000000..80a5d46 --- /dev/null +++ b/addons/gdUnit4/src/core/command/GdUnitShortcutAction.gd.uid @@ -0,0 +1 @@ +uid://d3yxmr84geinm diff --git a/addons/gdUnit4/src/core/discovery/GdUnitGUID.gd b/addons/gdUnit4/src/core/discovery/GdUnitGUID.gd new file mode 100644 index 0000000..00332f9 --- /dev/null +++ b/addons/gdUnit4/src/core/discovery/GdUnitGUID.gd @@ -0,0 +1,46 @@ +## A class representing a globally unique identifier for GdUnit test elements. +## Uses random values to generate unique identifiers that can be used +## to track and reference test cases and suites across the test framework. +class_name GdUnitGUID +extends RefCounted + + +## The internal string representation of the GUID. +## Generated using Godot's ResourceUID system when no existing GUID is provided. +var _guid: String + + +## Creates a new GUID instance. +## If no GUID is provided, generates a new one using Godot's ResourceUID system. +func _init(from_guid: String = "") -> void: + if from_guid.is_empty(): + _guid = _generate_guid() + else: + _guid = from_guid + + +## Compares this GUID with another for equality. +## Returns true if both GUIDs represent the same unique identifier. +func equals(other: GdUnitGUID) -> bool: + return other._guid == _guid + + +## Generates a custom GUID using random bytes.[br] +## The format uses 16 random bytes encoded to hex and formatted with hyphens. +static func _generate_guid() -> String: + # Pre-allocate array with exact size needed + var bytes := PackedByteArray() + bytes.resize(16) + + # Fill with random bytes + for i in range(16): + bytes[i] = randi() % 256 + + bytes[6] = (bytes[6] & 0x0f) | 0x40 + bytes[8] = (bytes[8] & 0x3f) | 0x80 + + return bytes.hex_encode().insert(8, "-").insert(16, "-").insert(24, "-") + + +func _to_string() -> String: + return _guid diff --git a/addons/gdUnit4/src/core/discovery/GdUnitGUID.gd.uid b/addons/gdUnit4/src/core/discovery/GdUnitGUID.gd.uid new file mode 100644 index 0000000..76326ed --- /dev/null +++ b/addons/gdUnit4/src/core/discovery/GdUnitGUID.gd.uid @@ -0,0 +1 @@ +uid://badb6bi2hc0i5 diff --git a/addons/gdUnit4/src/core/discovery/GdUnitTestCase.gd b/addons/gdUnit4/src/core/discovery/GdUnitTestCase.gd new file mode 100644 index 0000000..766f9ea --- /dev/null +++ b/addons/gdUnit4/src/core/discovery/GdUnitTestCase.gd @@ -0,0 +1,125 @@ +## GdUnitTestCase +## A class representing a single test case in GdUnit4. +## This class is used as a data container to hold all relevant information about a test case, +## including its location, dependencies, and metadata for test discovery and execution. + +class_name GdUnitTestCase +extends RefCounted + +## A unique identifier for the test case. Used to track and reference specific test instances. +var guid := GdUnitGUID.new() + +## The resource path to the test suite +var suite_resource_path: String + +## The name of the test method/function. Should start with "test_" prefix. +var test_name: String + +## The class name of the test suite containing this test case. +var suite_name: String + +## The fully qualified name of the test case following C# namespace pattern: +## Constructed from the folder path (where folders are dot-separated), the test suite name, and the test case name. +## All parts are joined by dots: {folder1.folder2.folder3}.{suite_name}.{test_name} +var fully_qualified_name: String + +var display_name: String + +## Index tracking test attributes for ordered execution. Default is 0. +## Higher values indicate later execution in the test sequence. +var attribute_index: int + +## Flag indicating if this test requires the Godot runtime environment. +## Tests requiring runtime cannot be executed in isolation. +var require_godot_runtime: bool = true + +## The path to the source file containing this test case. +## Used for test discovery and execution. +var source_file: String + +## Optional holds the assembly location for C# tests +var assembly_location: String = "" + +## The line number where the test case is defined in the source file. +## Used for navigation and error reporting. +var line_number: int = -1 + +## Additional metadata about the test case, such as: +## - tags: Array[String] - Test categories/tags for filtering +## - timeout: int - Maximum execution time in milliseconds +## - skip: bool - Whether the test should be skipped +## - dependencies: Array[String] - Required test dependencies +var metadata: Dictionary = {} + + +static func from_dict(dict: Dictionary) -> GdUnitTestCase: + var test := GdUnitTestCase.new() + test.guid = GdUnitGUID.new(str(dict["guid"])) + test.suite_resource_path = dict["suite_resource_path"] if dict.has("suite_resource_path") else dict["source_file"] + test.suite_name = dict["managed_type"] + test.test_name = dict["test_name"] + test.display_name = dict["simple_name"] + test.fully_qualified_name = dict["fully_qualified_name"] + test.attribute_index = dict["attribute_index"] + test.source_file = dict["source_file"] + test.line_number = dict["line_number"] + test.require_godot_runtime = dict["require_godot_runtime"] + test.assembly_location = dict["assembly_location"] + return test + + +static func to_dict(test: GdUnitTestCase) -> Dictionary: + return { + "guid": test.guid._guid, + "suite_resource_path": test.suite_resource_path, + "managed_type": test.suite_name, + "test_name" : test.test_name, + "simple_name" : test.display_name, + "fully_qualified_name" : test.fully_qualified_name, + "attribute_index" : test.attribute_index, + "source_file" : test.source_file, + "line_number" : test.line_number, + "require_godot_runtime" : test.require_godot_runtime, + "assembly_location" : test.assembly_location + } + + +static func from(_suite_resource_path: String, _source_file: String, _line_number: int, _test_name: String, _attribute_index := -1, _test_parameters := "") -> GdUnitTestCase: + if(_source_file == null or _source_file.is_empty()): + prints(_test_name) + + assert(_test_name != null and not _test_name.is_empty(), "Precondition: The parameter 'test_name' is not set") + assert(_source_file != null and not _source_file.is_empty(), "Precondition: The parameter 'source_file' is not set") + + var test := GdUnitTestCase.new() + test.suite_resource_path = _suite_resource_path + test.test_name = _test_name + test.source_file = _source_file + test.line_number = _line_number + test.attribute_index = _attribute_index + test._build_suite_name() + test._build_display_name(_test_parameters) + test._build_fully_qualified_name(_suite_resource_path) + return test + + +func _build_suite_name() -> void: + suite_name = source_file.get_file().get_basename() + assert(suite_name != null and not suite_name.is_empty(), "Precondition: The parameter 'suite_name' can't be resolved") + + +func _build_display_name(_test_parameters: String) -> void: + if attribute_index == -1: + display_name = test_name + else: + display_name = "%s:%d (%s)" % [test_name, attribute_index, _test_parameters.trim_prefix("[").trim_suffix("]").replace('"', "'")] + + +func _build_fully_qualified_name(_resource_path: String) -> void: + var name_space := _resource_path.trim_prefix("res://").trim_suffix(".gd").trim_suffix(".cs").replace("/", ".") + + if attribute_index == -1: + fully_qualified_name = "%s.%s" % [name_space, test_name] + else: + fully_qualified_name = "%s.%s.%s" % [name_space, test_name, display_name] + assert(fully_qualified_name != null and not fully_qualified_name.is_empty(), "Precondition: The parameter 'fully_qualified_name' can't be resolved") diff --git a/addons/gdUnit4/src/core/discovery/GdUnitTestCase.gd.uid b/addons/gdUnit4/src/core/discovery/GdUnitTestCase.gd.uid new file mode 100644 index 0000000..978acb9 --- /dev/null +++ b/addons/gdUnit4/src/core/discovery/GdUnitTestCase.gd.uid @@ -0,0 +1 @@ +uid://bwjtnx6u41kt8 diff --git a/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverGuard.gd b/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverGuard.gd new file mode 100644 index 0000000..6af8255 --- /dev/null +++ b/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverGuard.gd @@ -0,0 +1,323 @@ +## Guards and tracks test case changes during test discovery and file modifications.[br] +## [br] +## This guard maintains a cache of discovered tests to track changes between test runs and during[br] +## file modifications. It is optimized for performance using simple but effective test identity checks.[br] +## [br] +## Test Change Detection:[br] +## - Moved tests: The test implementation remains at a different line number[br] +## - Renamed tests: The test line position remains but the test name changed[br] +## - Deleted tests: A previously discovered test was removed[br] +## - Added tests: A new test was discovered[br] +## [br] +## Cache Management:[br] +## - Maintains test identity through unique GdUnitTestCase GUIDs[br] +## - Maps source files to their discovered test cases[br] +## - Tracks only essential metadata (line numbers, names) to minimize memory use[br] +## [br] +## Change Detection Strategy:[br] +## The guard uses a lightweight approach by comparing only line numbers and test names.[br] +## This avoids expensive operations like test content parsing or similarity checks.[br] +## [br] +## Event Handling:[br] +## - Emits events on test changes through GdUnitSignals[br] +## - Synchronizes cache with test discovery events[br] +## - Notifies UI about test changes[br] +## [br] +## Example usage:[br] +## [codeblock] +## # Create guard for tracking test changes +## var guard := GdUnitTestDiscoverGuard.new() +## +## # Connect to test discovery events +## GdUnitSignals.instance().gdunit_test_discovered.connect(guard.sync_test_added) +## +## # Discover tests and track changes +## await guard.discover(test_script) +## [/codeblock] +class_name GdUnitTestDiscoverGuard +extends Object + + + +static func instance() -> GdUnitTestDiscoverGuard: + return GdUnitSingleton.instance("GdUnitTestDiscoverGuard", func() -> GdUnitTestDiscoverGuard: + return GdUnitTestDiscoverGuard.new() + ) + + +## Maps source files to their discovered test cases.[br] +## [br] +## Key: Test suite source file path[br] +## Value: Array of [class GdUnitTestCase] instances +var _discover_cache := {} + + +## Tracks discovered test changes for debug purposes.[br] +## [br] +## Available in debug mode only. Contains dictionaries:[br] +## - changed_tests: Tests that were moved or renamed[br] +## - deleted_tests: Tests that were removed[br] +## - added_tests: New tests that were discovered +var _discovered_changes := {} + + +## Controls test change debug tracking.[br] +## [br] +## When true, maintains _discovered_changes for debugging.[br] +## Used primarily in tests to verify change detection. +var _is_debug := false + + +## Creates a new guard instance.[br] +## [br] +## [param is_debug] When true, enables change tracking for debugging. +func _init(is_debug := false) -> void: + _is_debug = is_debug + # Register for discovery events to sync the cache + @warning_ignore("return_value_discarded") + GdUnitSignals.instance().gdunit_test_discover_added.connect(sync_test_added) + GdUnitSignals.instance().gdunit_test_discover_deleted.connect(sync_test_deleted) + GdUnitSignals.instance().gdunit_test_discover_modified.connect(sync_test_modified) + GdUnitSignals.instance().gdunit_event.connect(handle_discover_events) + + +## Adds a discovered test to the cache.[br] +## [br] +## [param test_case] The test case to add to the cache. +func sync_test_added(test_case: GdUnitTestCase) -> void: + var test_cases: Array[GdUnitTestCase] = _discover_cache.get_or_add(test_case.source_file, Array([], TYPE_OBJECT, "RefCounted", GdUnitTestCase)) + test_cases.append(test_case) + + +## Removes a test from the cache.[br] +## [br] +## [param test_case] The test case to remove from the cache. +func sync_test_deleted(test_case: GdUnitTestCase) -> void: + var test_cases: Array[GdUnitTestCase] = _discover_cache.get_or_add(test_case.source_file, Array([], TYPE_OBJECT, "RefCounted", GdUnitTestCase)) + test_cases.erase(test_case) + + +## Updates a test from the cache.[br] +## [br] +## [param test_case] The test case to update from the cache. +func sync_test_modified(changed_test: GdUnitTestCase) -> void: + var test_cases: Array[GdUnitTestCase] = _discover_cache.get_or_add(changed_test.source_file, Array([], TYPE_OBJECT, "RefCounted", GdUnitTestCase)) + for test in test_cases: + if test.guid == changed_test.guid: + test.test_name = changed_test.test_name + test.display_name = changed_test.display_name + test.line_number = changed_test.line_number + break + + +## Handles test discovery events.[br] +## [br] +## Resets the cache when a new discovery starts.[br] +## [param event] The discovery event to handle. +func handle_discover_events(event: GdUnitEvent) -> void: + # reset the cache on fresh discovery + if event.type() == GdUnitEvent.DISCOVER_START: + _discover_cache = {} + + +## Registers a callback for discovered tests.[br] +## [br] +## Default sink writes to [class GdUnitTestDiscoverSink]. +static func default_discover_sink(test_case: GdUnitTestCase) -> void: + GdUnitTestDiscoverSink.discover(test_case) + + +## Finds a test case by its unique identifier.[br] +## [br] +## Searches through all cached test cases across all test suites[br] +## to find a test with the matching GUID.[br] +## [br] +## [param id] The GUID of the test to find[br] +## Returns the matching test case or null if not found. +func find_test_by_id(id: GdUnitGUID) -> GdUnitTestCase: + for test_sets: Array[GdUnitTestCase] in _discover_cache.values(): + for test in test_sets: + if test.guid.equals(id): + return test + + return null + + +func get_discovered_tests() -> Array[GdUnitTestCase]: + var discovered_tests: Array[GdUnitTestCase] = [] + for test_sets: Array[GdUnitTestCase] in _discover_cache.values(): + discovered_tests.append_array(test_sets) + return discovered_tests + + +## Discovers tests in a script and tracks changes.[br] +## [br] +## Handles both GDScript and C# test suites.[br] +## The guard maintains test identity through changes.[br] +## [br] +## [param script] The test script to analyze[br] +## [param discover_sink] Optional callback for test discovery events +func discover(script: Script, discover_sink: Callable = default_discover_sink) -> void: + # Verify the script has no errors before run test discovery + var result := script.reload(true) + if result != OK: + return + + if _is_debug: + _discovered_changes["changed_tests"] = Array([], TYPE_OBJECT, "RefCounted", GdUnitTestCase) + _discovered_changes["deleted_tests"] = Array([], TYPE_OBJECT, "RefCounted", GdUnitTestCase) + _discovered_changes["added_tests"] = Array([], TYPE_OBJECT, "RefCounted", GdUnitTestCase) + + if GdUnitTestSuiteScanner.is_test_suite(script): + # for cs scripts we need to recomplie before discover new tests + if script.get_class() == "CSharpScript": + await rebuild_project(script) + + # rediscover all tests + var source_file := script.resource_path + var discovered_tests: Array[GdUnitTestCase] = [] + + GdUnitTestDiscoverer.discover_tests(script, func(test_case: GdUnitTestCase) -> void: + discovered_tests.append(test_case) + ) + + # The suite is never discovered, we add all discovered tests + if not _discover_cache.has(source_file): + for test_case in discovered_tests: + discover_sink.call(test_case) + return + + sync_moved_tests(source_file, discovered_tests) + sync_renamed_tests(source_file, discovered_tests) + sync_deleted_tests(source_file, discovered_tests) + sync_added_tests(source_file, discovered_tests, discover_sink) + + +## Synchronizes moved tests between discover cycles.[br] +## [br] +## A test is considered moved when:[br] +## - It has the same name[br] +## - But a different line number[br] +## [br] +## [param source_file] suite source path[br] +## [param discovered_tests] Newly discovered tests +func sync_moved_tests(source_file: String, discovered_tests: Array[GdUnitTestCase]) -> void: + @warning_ignore("unsafe_method_access") + var cache: Array[GdUnitTestCase] = _discover_cache.get(source_file).duplicate() + for discovered_test in discovered_tests: + # lookup in cache + var original_tests: Array[GdUnitTestCase] = cache.filter(is_test_moved.bind(discovered_test)) + for test in original_tests: + # update the line_number + var line_number_before := test.line_number + test.line_number = discovered_test.line_number + GdUnitSignals.instance().gdunit_test_discover_modified.emit(test) + if _is_debug: + prints("-> moved test id:%s %s: line:(%d -> %d)" % [test.guid, test.display_name, line_number_before, test.line_number]) + @warning_ignore("unsafe_method_access") + _discovered_changes.get_or_add("changed_tests", Array([], TYPE_OBJECT, "RefCounted", GdUnitTestCase)).append(test) + + +## Synchronizes renamed tests between discover cycles.[br] +## [br] +## A test is considered renamed when:[br] +## - It has the same line number[br] +## - But a different name[br] +## [br] +## [param source_file] suite source path[br] +## [param discovered_tests] Newly discovered tests +func sync_renamed_tests(source_file: String, discovered_tests: Array[GdUnitTestCase]) -> void: + @warning_ignore("unsafe_method_access") + var cache: Array[GdUnitTestCase] = _discover_cache.get(source_file).duplicate() + for discovered_test in discovered_tests: + # lookup in cache + var original_tests: Array[GdUnitTestCase] = cache.filter(is_test_renamed.bind(discovered_test)) + for test in original_tests: + # update the renaming names + var original_display_name := test.display_name + test.test_name = discovered_test.test_name + test.display_name = discovered_test.display_name + GdUnitSignals.instance().gdunit_test_discover_modified.emit(test) + if _is_debug: + prints("-> renamed test id:%s %s -> %s" % [test.guid, original_display_name, test.display_name]) + @warning_ignore("unsafe_method_access") + _discovered_changes.get_or_add("changed_tests", Array([], TYPE_OBJECT, "RefCounted", GdUnitTestCase)).append(test) + + +## Synchronizes deleted tests between discover cycles.[br] +## [br] +## A test is considered deleted when:[br] +## - It exists in the cache[br] +## - But is not found in the newly discovered tests[br] +## [br] +## [param source_file] suite source path[br] +## [param discovered_tests] Newly discovered tests +func sync_deleted_tests(source_file: String, discovered_tests: Array[GdUnitTestCase]) -> void: + @warning_ignore("unsafe_method_access") + var cache: Array[GdUnitTestCase] = _discover_cache.get(source_file).duplicate() + # lookup in cache + for test in cache: + if not discovered_tests.any(test_equals.bind(test)): + GdUnitSignals.instance().gdunit_test_discover_deleted.emit(test) + if _is_debug: + prints("-> deleted test id:%s %s:%d" % [test.guid, test.display_name, test.line_number]) + @warning_ignore("unsafe_method_access") + _discovered_changes.get_or_add("deleted_tests", Array([], TYPE_OBJECT, "RefCounted", GdUnitTestCase)).append(test) + + +## Synchronizes newly added tests between discover cycles.[br] +## [br] +## A test is considered added when:[br] +## - It exists in the newly discovered tests[br] +## - But is not found in the cache[br] +## [br] +## [param source_file] suite source path[br] +## [param discovered_tests] Newly discovered tests[br] +## [param discover_sink] Callback to handle newly discovered tests +func sync_added_tests(source_file: String, discovered_tests: Array[GdUnitTestCase], discover_sink: Callable) -> void: + @warning_ignore("unsafe_method_access") + var cache: Array[GdUnitTestCase] = _discover_cache.get(source_file).duplicate() + # lookup in cache + for test in discovered_tests: + if not cache.any(test_equals.bind(test)): + discover_sink.call(test) + if _is_debug: + prints("-> added test id:%s %s:%d" % [test.guid, test.display_name, test.line_number]) + @warning_ignore("unsafe_method_access") + _discovered_changes.get_or_add("added_tests", Array([], TYPE_OBJECT, "RefCounted", GdUnitTestCase)).append(test) + + +func is_test_renamed(left: GdUnitTestCase, right: GdUnitTestCase) -> bool: + return left.line_number == right.line_number and left.test_name != right.test_name + + +func is_test_moved(left: GdUnitTestCase, right: GdUnitTestCase) -> bool: + return left.line_number != right.line_number and left.test_name == right.test_name + + +func test_equals(left: GdUnitTestCase, right: GdUnitTestCase) -> bool: + return left.display_name == right.display_name + + +# do rebuild the entire project, there is actual no way to enforce the Godot engine itself to do this +func rebuild_project(script: Script) -> void: + var class_path := ProjectSettings.globalize_path(script.resource_path) + print_rich("[color=CORNFLOWER_BLUE]GdUnitTestDiscoverGuard: CSharpScript change detected on: '%s' [/color]" % class_path) + var scene_tree := Engine.get_main_loop() as SceneTree + await scene_tree.process_frame + + var output := [] + var exit_code := OS.execute("dotnet", ["--version"], output) + if exit_code == -1: + print_rich("[color=CORNFLOWER_BLUE]GdUnitTestDiscoverGuard:[/color] [color=RED]Rebuild the project failed.[/color]") + print_rich("[color=CORNFLOWER_BLUE]GdUnitTestDiscoverGuard:[/color] [color=RED]Can't find installed `dotnet`! Please check your environment is setup correctly.[/color]") + return + + print_rich("[color=CORNFLOWER_BLUE]GdUnitTestDiscoverGuard:[/color] [color=DEEP_SKY_BLUE]Found dotnet v%s[/color]" % str(output[0]).strip_edges()) + output.clear() + + exit_code = OS.execute("dotnet", ["build"], output) + print_rich("[color=CORNFLOWER_BLUE]GdUnitTestDiscoverGuard:[/color] [color=DEEP_SKY_BLUE]Rebuild the project ... [/color]") + for out: String in output: + print_rich("[color=DEEP_SKY_BLUE] %s" % out.strip_edges()) + await scene_tree.process_frame diff --git a/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverGuard.gd.uid b/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverGuard.gd.uid new file mode 100644 index 0000000..cad4a0d --- /dev/null +++ b/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverGuard.gd.uid @@ -0,0 +1 @@ +uid://c7ompeswepwdn diff --git a/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverSink.gd b/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverSink.gd new file mode 100644 index 0000000..5d0e5b6 --- /dev/null +++ b/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverSink.gd @@ -0,0 +1,13 @@ +## A static utility class that acts as a central sink for test case discovery events in GdUnit4. +## Instead of implementing custom sink classes, test discovery consumers should connect to +## the GdUnitSignals.gdunit_test_discovered signal to receive test case discoveries. +## This design allows for a more flexible and decoupled test discovery system. +class_name GdUnitTestDiscoverSink +extends RefCounted + + +## Emits a discovered test case through the GdUnitSignals system.[br] +## Sends the test case to all listeners connected to the gdunit_test_discovered signal.[br] +## [member test_case] The discovered test case to be broadcast to all connected listeners. +static func discover(test_case: GdUnitTestCase) -> void: + GdUnitSignals.instance().gdunit_test_discover_added.emit(test_case) diff --git a/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverSink.gd.uid b/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverSink.gd.uid new file mode 100644 index 0000000..c189fc6 --- /dev/null +++ b/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverSink.gd.uid @@ -0,0 +1 @@ +uid://cx6youvu7ogfb diff --git a/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverer.gd b/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverer.gd new file mode 100644 index 0000000..cbe4858 --- /dev/null +++ b/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverer.gd @@ -0,0 +1,136 @@ +class_name GdUnitTestDiscoverer +extends RefCounted + + +static func run() -> Array[GdUnitTestCase]: + console_log("Running test discovery ..") + await (Engine.get_main_loop() as SceneTree).process_frame + GdUnitSignals.instance().gdunit_event.emit(GdUnitEventTestDiscoverStart.new()) + + # We run the test discovery in an extra thread so that the main thread is not blocked + var t:= Thread.new() + @warning_ignore("return_value_discarded") + t.start(func () -> Array[GdUnitTestCase]: + # Loading previous test session + var runner_config := GdUnitRunnerConfig.new() + runner_config.load_config() + var recovered_tests := runner_config.test_cases() + var test_suite_directories :PackedStringArray = GdUnitCommandHandler.scan_all_test_directories(GdUnitSettings.test_root_folder()) + var scanner := GdUnitTestSuiteScanner.new() + + var collected_tests: Array[GdUnitTestCase] = [] + var collected_test_suites: Array[Script] = [] + # collect test suites + for test_suite_dir in test_suite_directories: + collected_test_suites.append_array(scanner.scan_directory(test_suite_dir)) + + # Do sync the main thread before emit the discovered test suites to the inspector + await (Engine.get_main_loop() as SceneTree).process_frame + for test_suites_script in collected_test_suites: + discover_tests(test_suites_script, func(test_case: GdUnitTestCase) -> void: + # Sync test uid from last test session + recover_test_guid(test_case, recovered_tests) + collected_tests.append(test_case) + GdUnitTestDiscoverSink.discover(test_case) + ) + + console_log_discover_results(collected_tests) + if !recovered_tests.is_empty(): + console_log("Recovered last test session successfully, %d tests restored." % recovered_tests.size(), true) + return collected_tests + ) + # wait unblocked to the tread is finished + while t.is_alive(): + await (Engine.get_main_loop() as SceneTree).process_frame + # needs finally to wait for finish + var test_to_execute: Array[GdUnitTestCase] = await t.wait_to_finish() + GdUnitSignals.instance().gdunit_event.emit(GdUnitEventTestDiscoverEnd.new(0, 0)) + return test_to_execute + + +## Restores the last test run session by loading the test run config file and rediscover the tests +static func restore_last_session() -> void: + if GdUnitSettings.is_test_discover_enabled(): + return + + var runner_config := GdUnitRunnerConfig.new() + var result := runner_config.load_config() + # Report possible config loading errors + if result.is_error(): + console_log("Recovery of the last test session failed: %s" % result.error_message(), true) + # If no config file found, skip test recovery + if result.is_warn(): + return + + # If no tests recorded, skip test recovery + var test_cases := runner_config.test_cases() + if test_cases.size() == 0: + return + + # We run the test session restoring in an extra thread so that the main thread is not blocked + var t:= Thread.new() + t.start(func () -> void: + # Do sync the main thread before emit the discovered test suites to the inspector + await (Engine.get_main_loop() as SceneTree).process_frame + console_log("Recovering last test session ..", true) + GdUnitSignals.instance().gdunit_event.emit(GdUnitEventTestDiscoverStart.new()) + for test_case in test_cases: + GdUnitTestDiscoverSink.discover(test_case) + GdUnitSignals.instance().gdunit_event.emit(GdUnitEventTestDiscoverEnd.new(0, 0)) + console_log("Recovered last test session successfully, %d tests restored." % test_cases.size(), true) + ) + t.wait_to_finish() + + +static func recover_test_guid(current: GdUnitTestCase, recovered_tests: Array[GdUnitTestCase]) -> void: + for recovered_test in recovered_tests: + if recovered_test.fully_qualified_name == current.fully_qualified_name: + current.guid = recovered_test.guid + + +static func console_log_discover_results(tests: Array[GdUnitTestCase]) -> void: + var grouped_by_suites := GdArrayTools.group_by(tests, func(test: GdUnitTestCase) -> String: + return test.source_file + ) + for suite_tests: Array in grouped_by_suites.values(): + var test_case: GdUnitTestCase = suite_tests[0] + console_log("Discover: TestSuite %s with %d tests found" % [test_case.source_file, suite_tests.size()]) + console_log("Discover tests done, %d TestSuites and total %d Tests found. " % [grouped_by_suites.size(), tests.size()]) + console_log("") + + +static func console_log(message: String, on_console := false) -> void: + prints(message) + if on_console: + GdUnitSignals.instance().gdunit_message.emit(message) + + +static func filter_tests(method: Dictionary) -> bool: + var method_name: String = method["name"] + return method_name.begins_with("test_") + + +static func default_discover_sink(test_case: GdUnitTestCase) -> void: + GdUnitTestDiscoverSink.discover(test_case) + + +static func discover_tests(source_script: Script, discover_sink := default_discover_sink) -> void: + if source_script is GDScript: + var test_names := source_script.get_script_method_list()\ + .filter(filter_tests)\ + .map(func(method: Dictionary) -> String: return method["name"]) + # no tests discovered? + if test_names.is_empty(): + return + + var parser := GdScriptParser.new() + var fds := parser.get_function_descriptors(source_script as GDScript, test_names) + for fd in fds: + var resolver := GdFunctionParameterSetResolver.new(fd) + for test_case in resolver.resolve_test_cases(source_script as GDScript): + discover_sink.call(test_case) + elif source_script.get_class() == "CSharpScript": + if not GdUnit4CSharpApiLoader.is_api_loaded(): + return + for test_case in GdUnit4CSharpApiLoader.discover_tests(source_script): + discover_sink.call(test_case) diff --git a/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverer.gd.uid b/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverer.gd.uid new file mode 100644 index 0000000..7a9d8eb --- /dev/null +++ b/addons/gdUnit4/src/core/discovery/GdUnitTestDiscoverer.gd.uid @@ -0,0 +1 @@ +uid://g7155gj4bdqv diff --git a/addons/gdUnit4/src/core/event/GdUnitEvent.gd b/addons/gdUnit4/src/core/event/GdUnitEvent.gd new file mode 100644 index 0000000..6bec105 --- /dev/null +++ b/addons/gdUnit4/src/core/event/GdUnitEvent.gd @@ -0,0 +1,206 @@ +class_name GdUnitEvent +extends Resource + +const WARNINGS = "warnings" +const FAILED = "failed" +const FLAKY = "flaky" +const ERRORS = "errors" +const SKIPPED = "skipped" +const ELAPSED_TIME = "elapsed_time" +const ORPHAN_NODES = "orphan_nodes" +const ERROR_COUNT = "error_count" +const FAILED_COUNT = "failed_count" +const SKIPPED_COUNT = "skipped_count" +const RETRY_COUNT = "retry_count" + +enum { + INIT, + STOP, + TESTSUITE_BEFORE, + TESTSUITE_AFTER, + TESTCASE_BEFORE, + TESTCASE_AFTER, + DISCOVER_START, + DISCOVER_END, + SESSION_START, + SESSION_CLOSE +} + +var _event_type: int +var _guid: GdUnitGUID +var _resource_path: String +var _suite_name: String +var _test_name: String +var _total_count: int = 0 +var _statistics := Dictionary() +var _reports: Array[GdUnitReport] = [] + + +func suite_before(p_resource_path: String, p_suite_name: String, p_total_count: int) -> GdUnitEvent: + _guid = GdUnitGUID.new() + _event_type = TESTSUITE_BEFORE + _resource_path = p_resource_path + _suite_name = p_suite_name + _test_name = "before" + _total_count = p_total_count + return self + + +func suite_after(p_resource_path: String, p_suite_name: String, p_statistics: Dictionary = {}, p_reports: Array[GdUnitReport] = []) -> GdUnitEvent: + _guid = GdUnitGUID.new() + _event_type = TESTSUITE_AFTER + _resource_path = p_resource_path + _suite_name = p_suite_name + _test_name = "after" + _statistics = p_statistics + _reports = p_reports + return self + + +func test_before(p_guid: GdUnitGUID) -> GdUnitEvent: + _event_type = TESTCASE_BEFORE + _guid = p_guid + return self + + +func test_after(p_guid: GdUnitGUID, p_statistics: Dictionary = {}, p_reports :Array[GdUnitReport] = []) -> GdUnitEvent: + _event_type = TESTCASE_AFTER + _guid = p_guid + _statistics = p_statistics + _reports = p_reports + return self + + +func type() -> int: + return _event_type + + +func guid() -> GdUnitGUID: + return _guid + + +func suite_name() -> String: + return _suite_name + + +func test_name() -> String: + return _test_name + + +func elapsed_time() -> int: + return _statistics.get(ELAPSED_TIME, 0) + + +func orphan_nodes() -> int: + return _statistics.get(ORPHAN_NODES, 0) + + +func statistic(p_type :String) -> int: + return _statistics.get(p_type, 0) + + +func total_count() -> int: + return _total_count + + +func success_count() -> int: + return total_count() - error_count() - failed_count() - skipped_count() + + +func error_count() -> int: + return _statistics.get(ERROR_COUNT, 0) + + +func failed_count() -> int: + return _statistics.get(FAILED_COUNT, 0) + + +func skipped_count() -> int: + return _statistics.get(SKIPPED_COUNT, 0) + + +func retry_count() -> int: + return _statistics.get(RETRY_COUNT, 0) + + +func resource_path() -> String: + return _resource_path + + +func is_success() -> bool: + return not is_failed() and not is_error() + + +func is_warning() -> bool: + return _statistics.get(WARNINGS, false) + + +func is_failed() -> bool: + return _statistics.get(FAILED, false) + + +func is_error() -> bool: + return _statistics.get(ERRORS, false) + + +func is_flaky() -> bool: + return _statistics.get(FLAKY, false) + + +func is_skipped() -> bool: + return _statistics.get(SKIPPED, false) + + +func reports() -> Array[GdUnitReport]: + return _reports + + +func _to_string() -> String: + return "Event: %s id:%s %s:%s, %s, %s" % [_event_type, _guid, _suite_name, _test_name, _statistics, _reports] + + +func serialize() -> Dictionary: + var serialized := { + "type" : _event_type, + "resource_path": _resource_path, + "suite_name" : _suite_name, + "test_name" : _test_name, + "total_count" : _total_count, + "statistics" : _statistics + } + if _guid != null: + serialized["guid"] = _guid._guid + serialized["reports"] = _serialize_TestReports() + return serialized + + +func deserialize(serialized: Dictionary) -> GdUnitEvent: + _event_type = serialized.get("type", null) + _guid = GdUnitGUID.new(str(serialized.get("guid", ""))) + _resource_path = serialized.get("resource_path", null) + _suite_name = serialized.get("suite_name", null) + _test_name = serialized.get("test_name", "unknown") + _total_count = serialized.get("total_count", 0) + _statistics = serialized.get("statistics", Dictionary()) + if serialized.has("reports"): + # needs this workaround to copy typed values in the array + var reports_to_deserializ :Array[Dictionary] = [] + @warning_ignore("unsafe_cast") + reports_to_deserializ.append_array(serialized.get("reports") as Array) + _reports = _deserialize_reports(reports_to_deserializ) + return self + + +func _serialize_TestReports() -> Array[Dictionary]: + var serialized_reports :Array[Dictionary] = [] + for report in _reports: + serialized_reports.append(report.serialize()) + return serialized_reports + + +func _deserialize_reports(p_reports: Array[Dictionary]) -> Array[GdUnitReport]: + var deserialized_reports :Array[GdUnitReport] = [] + for report in p_reports: + var test_report := GdUnitReport.new().deserialize(report) + deserialized_reports.append(test_report) + return deserialized_reports diff --git a/addons/gdUnit4/src/core/event/GdUnitEvent.gd.uid b/addons/gdUnit4/src/core/event/GdUnitEvent.gd.uid new file mode 100644 index 0000000..5005290 --- /dev/null +++ b/addons/gdUnit4/src/core/event/GdUnitEvent.gd.uid @@ -0,0 +1 @@ +uid://dsnehfo2jgdo7 diff --git a/addons/gdUnit4/src/core/event/GdUnitEventInit.gd b/addons/gdUnit4/src/core/event/GdUnitEventInit.gd new file mode 100644 index 0000000..774e7d4 --- /dev/null +++ b/addons/gdUnit4/src/core/event/GdUnitEventInit.gd @@ -0,0 +1,6 @@ +class_name GdUnitInit +extends GdUnitEvent + + +func _init() -> void: + _event_type = INIT diff --git a/addons/gdUnit4/src/core/event/GdUnitEventInit.gd.uid b/addons/gdUnit4/src/core/event/GdUnitEventInit.gd.uid new file mode 100644 index 0000000..7a9202b --- /dev/null +++ b/addons/gdUnit4/src/core/event/GdUnitEventInit.gd.uid @@ -0,0 +1 @@ +uid://c6dq5ga07rna6 diff --git a/addons/gdUnit4/src/core/event/GdUnitEventStop.gd b/addons/gdUnit4/src/core/event/GdUnitEventStop.gd new file mode 100644 index 0000000..d7a3c11 --- /dev/null +++ b/addons/gdUnit4/src/core/event/GdUnitEventStop.gd @@ -0,0 +1,6 @@ +class_name GdUnitStop +extends GdUnitEvent + + +func _init() -> void: + _event_type = STOP diff --git a/addons/gdUnit4/src/core/event/GdUnitEventStop.gd.uid b/addons/gdUnit4/src/core/event/GdUnitEventStop.gd.uid new file mode 100644 index 0000000..6e024ea --- /dev/null +++ b/addons/gdUnit4/src/core/event/GdUnitEventStop.gd.uid @@ -0,0 +1 @@ +uid://dbedmchp2o040 diff --git a/addons/gdUnit4/src/core/event/GdUnitEventTestDiscoverEnd.gd b/addons/gdUnit4/src/core/event/GdUnitEventTestDiscoverEnd.gd new file mode 100644 index 0000000..c6194ef --- /dev/null +++ b/addons/gdUnit4/src/core/event/GdUnitEventTestDiscoverEnd.gd @@ -0,0 +1,19 @@ +class_name GdUnitEventTestDiscoverEnd +extends GdUnitEvent + + +var _total_testsuites: int + + +func _init(testsuite_count: int, test_count: int) -> void: + _event_type = DISCOVER_END + _total_testsuites = testsuite_count + _total_count = test_count + + +func total_test_suites() -> int: + return _total_testsuites + + +func total_tests() -> int: + return _total_count diff --git a/addons/gdUnit4/src/core/event/GdUnitEventTestDiscoverEnd.gd.uid b/addons/gdUnit4/src/core/event/GdUnitEventTestDiscoverEnd.gd.uid new file mode 100644 index 0000000..1f546db --- /dev/null +++ b/addons/gdUnit4/src/core/event/GdUnitEventTestDiscoverEnd.gd.uid @@ -0,0 +1 @@ +uid://o01l4uax3r1b diff --git a/addons/gdUnit4/src/core/event/GdUnitEventTestDiscoverStart.gd b/addons/gdUnit4/src/core/event/GdUnitEventTestDiscoverStart.gd new file mode 100644 index 0000000..c7dd36f --- /dev/null +++ b/addons/gdUnit4/src/core/event/GdUnitEventTestDiscoverStart.gd @@ -0,0 +1,6 @@ +class_name GdUnitEventTestDiscoverStart +extends GdUnitEvent + + +func _init() -> void: + _event_type = DISCOVER_START diff --git a/addons/gdUnit4/src/core/event/GdUnitEventTestDiscoverStart.gd.uid b/addons/gdUnit4/src/core/event/GdUnitEventTestDiscoverStart.gd.uid new file mode 100644 index 0000000..e882260 --- /dev/null +++ b/addons/gdUnit4/src/core/event/GdUnitEventTestDiscoverStart.gd.uid @@ -0,0 +1 @@ +uid://opik40ogrfok diff --git a/addons/gdUnit4/src/core/event/GdUnitSessionClose.gd b/addons/gdUnit4/src/core/event/GdUnitSessionClose.gd new file mode 100644 index 0000000..52dab3f --- /dev/null +++ b/addons/gdUnit4/src/core/event/GdUnitSessionClose.gd @@ -0,0 +1,6 @@ +class_name GdUnitSessionClose +extends GdUnitEvent + + +func _init() -> void: + _event_type = SESSION_CLOSE diff --git a/addons/gdUnit4/src/core/event/GdUnitSessionClose.gd.uid b/addons/gdUnit4/src/core/event/GdUnitSessionClose.gd.uid new file mode 100644 index 0000000..a5e72b7 --- /dev/null +++ b/addons/gdUnit4/src/core/event/GdUnitSessionClose.gd.uid @@ -0,0 +1 @@ +uid://cuocq0rrl8s3u diff --git a/addons/gdUnit4/src/core/event/GdUnitSessionStart.gd b/addons/gdUnit4/src/core/event/GdUnitSessionStart.gd new file mode 100644 index 0000000..420ad53 --- /dev/null +++ b/addons/gdUnit4/src/core/event/GdUnitSessionStart.gd @@ -0,0 +1,6 @@ +class_name GdUnitSessionStart +extends GdUnitEvent + + +func _init() -> void: + _event_type = SESSION_START diff --git a/addons/gdUnit4/src/core/event/GdUnitSessionStart.gd.uid b/addons/gdUnit4/src/core/event/GdUnitSessionStart.gd.uid new file mode 100644 index 0000000..994b1e5 --- /dev/null +++ b/addons/gdUnit4/src/core/event/GdUnitSessionStart.gd.uid @@ -0,0 +1 @@ +uid://bjakxvhrhy8fy diff --git a/addons/gdUnit4/src/core/execution/GdUnitExecutionContext.gd b/addons/gdUnit4/src/core/execution/GdUnitExecutionContext.gd new file mode 100644 index 0000000..457fd67 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/GdUnitExecutionContext.gd @@ -0,0 +1,269 @@ +## The execution context +## It contains all the necessary information about the executed stage, such as memory observers, reports, orphan monitor +class_name GdUnitExecutionContext + +enum GC_ORPHANS_CHECK { + NONE, + SUITE_HOOK_AFTER, + TEST_HOOK_AFTER, + TEST_CASE +} + + +var _parent_context: GdUnitExecutionContext +var _sub_context: Array[GdUnitExecutionContext] = [] +var _orphan_monitor: GdUnitOrphanNodesMonitor +var _memory_observer: GdUnitMemoryObserver +var _report_collector: GdUnitTestReportCollector +var _timer: LocalTime +var _test_case_name: StringName +var _test_case_parameter_set: Array +var _name: String +var _test_execution_iteration: int = 0 +var _flaky_test_check := GdUnitSettings.is_test_flaky_check_enabled() +var _flaky_test_retries := GdUnitSettings.get_flaky_max_retries() +var _orphans := -1 + + +var error_monitor: GodotGdErrorMonitor = null: + get: + if _parent_context != null: + return _parent_context.error_monitor + if error_monitor == null: + error_monitor = GodotGdErrorMonitor.new() + return error_monitor + + +var test_suite: GdUnitTestSuite = null: + get: + if _parent_context != null: + return _parent_context.test_suite + return test_suite + + +var test_case: _TestCase = null: + get: + if test_case == null and _parent_context != null: + return _parent_context.test_case + return test_case + + +func _init(name: StringName, parent_context: GdUnitExecutionContext = null) -> void: + _name = name + _parent_context = parent_context + _timer = LocalTime.now() + _orphan_monitor = GdUnitOrphanNodesMonitor.new(name) + _orphan_monitor.start() + _memory_observer = GdUnitMemoryObserver.new() + _report_collector = GdUnitTestReportCollector.new() + if parent_context != null: + parent_context._sub_context.append(self) + + +func dispose() -> void: + _timer = null + _orphan_monitor = null + _report_collector = null + _memory_observer = null + _parent_context = null + test_suite = null + test_case = null + dispose_sub_contexts() + + +func dispose_sub_contexts() -> void: + for context in _sub_context: + context.dispose() + _sub_context.clear() + + +static func of(pe: GdUnitExecutionContext) -> GdUnitExecutionContext: + var context := GdUnitExecutionContext.new(pe._test_case_name, pe) + context._test_case_name = pe._test_case_name + context._test_execution_iteration = pe._test_execution_iteration + return context + + +static func of_test_suite(p_test_suite: GdUnitTestSuite) -> GdUnitExecutionContext: + assert(p_test_suite, "test_suite is null") + var context := GdUnitExecutionContext.new(p_test_suite.get_name()) + context.test_suite = p_test_suite + return context + + +static func of_test_case(pe: GdUnitExecutionContext, p_test_case: _TestCase) -> GdUnitExecutionContext: + assert(p_test_case, "test_case is null") + var context := GdUnitExecutionContext.new(p_test_case.get_name(), pe) + context.test_case = p_test_case + return context + + +static func of_parameterized_test(pe: GdUnitExecutionContext, test_case_name: String, test_case_parameter_set: Array) -> GdUnitExecutionContext: + var context := GdUnitExecutionContext.new(test_case_name, pe) + context._test_case_name = test_case_name + context._test_case_parameter_set = test_case_parameter_set + return context + + +func get_test_suite_path() -> String: + return test_suite.get_script().resource_path + + +func get_test_suite_name() -> StringName: + return test_suite.get_name() + + +func get_test_case_name() -> StringName: + if _test_case_name.is_empty(): + return test_case._test_case.display_name + return _test_case_name + + +func error_monitor_start() -> void: + error_monitor.start() + + +func error_monitor_stop() -> void: + await error_monitor.scan() + for error_report in error_monitor.to_reports(): + if error_report.is_error(): + _report_collector.push_back(error_report) + + +func orphan_monitor_start() -> void: + _orphan_monitor.start() + + +func orphan_monitor_stop() -> void: + _orphan_monitor.stop() + + +func add_report(report: GdUnitReport) -> GdUnitReport: + _report_collector.push_back(report) + return report + + +func reports() -> Array[GdUnitReport]: + return _report_collector.reports() + + +func collect_reports(recursive: bool) -> Array[GdUnitReport]: + if not recursive: + return reports() + + # we combine the reports of test_before(), test_after() and test() to be reported by `fire_test_ended` + # we strictly need to copy the reports before adding sub context reports to avoid manipulation of the current context + var current_reports := reports().duplicate() + for sub_context in _sub_context: + current_reports.append_array(sub_context.collect_reports(true)) + + return current_reports + + +func calculate_statistics(reports_: Array[GdUnitReport]) -> Dictionary: + var failed_count := GdUnitTestReportCollector.count_failures(reports_) + var error_count := GdUnitTestReportCollector.count_errors(reports_) + var warn_count := GdUnitTestReportCollector.count_warnings(reports_) + var skip_count := GdUnitTestReportCollector.count_skipped(reports_) + var is_failed := !is_success() + var orphan_count := _count_orphans() + var elapsed_time := _timer.elapsed_since_ms() + var retries := 1 if _parent_context == null else _sub_context.size() + # Mark as flaky if it is successful, but errors were counted + var is_flaky := retries > 1 and not is_failed + # In the case of a flakiness test, we do not report an error counter, as an unreliable test is considered successful + # after a certain number of repetitions. + if is_flaky: + failed_count = 0 + + return { + GdUnitEvent.RETRY_COUNT: retries, + GdUnitEvent.ELAPSED_TIME: elapsed_time, + GdUnitEvent.FAILED: is_failed, + GdUnitEvent.ERRORS: error_count > 0, + GdUnitEvent.WARNINGS: warn_count > 0, + GdUnitEvent.FLAKY: is_flaky, + GdUnitEvent.SKIPPED: skip_count > 0, + GdUnitEvent.FAILED_COUNT: failed_count, + GdUnitEvent.ERROR_COUNT: error_count, + GdUnitEvent.SKIPPED_COUNT: skip_count, + GdUnitEvent.ORPHAN_NODES: orphan_count, + } + + +func is_success() -> bool: + if _sub_context.is_empty(): + return not _report_collector.has_failures() + # we on test suite level? + if _parent_context == null: + return not _report_collector.has_failures() + + return _sub_context[-1].is_success() and not _report_collector.has_failures() + + +func is_skipped() -> bool: + return ( + _sub_context.any(func(c :GdUnitExecutionContext) -> bool: + return c.is_skipped()) + or test_case.is_skipped() if test_case != null else false + ) + + +func is_interupted() -> bool: + return false if test_case == null else test_case.is_interupted() + + +func _count_orphans() -> int: + if _orphans != -1: + return _orphans + + var orphans := 0 + for c in _sub_context: + if _orphan_monitor.orphan_nodes() != c._orphan_monitor.orphan_nodes(): + orphans += c._count_orphans() + + _orphans = _orphan_monitor.orphan_nodes() + if _orphan_monitor.orphan_nodes() != orphans: + _orphans -= orphans + + return _orphans + + +func sum(accum: int, number: int) -> int: + return accum + number + + +func retry_execution() -> bool: + var retry := _test_execution_iteration < 1 if not _flaky_test_check else _test_execution_iteration < _flaky_test_retries + if retry: + _test_execution_iteration += 1 + return retry + + +func register_auto_free(obj: Variant) -> Variant: + return _memory_observer.register_auto_free(obj) + + +## Runs the gdunit garbage collector to free registered object and handle orphan node reporting +func gc(gc_orphan_check: GC_ORPHANS_CHECK = GC_ORPHANS_CHECK.NONE) -> void: + # unreference last used assert form the test to prevent memory leaks + GdUnitThreadManager.get_current_context().clear_assert() + await _memory_observer.gc() + orphan_monitor_stop() + + var orphans := _count_orphans() + match(gc_orphan_check): + GC_ORPHANS_CHECK.SUITE_HOOK_AFTER: + if orphans > 0: + reports().push_front(GdUnitReport.new() \ + .create(GdUnitReport.WARN, 1, GdAssertMessages.orphan_detected_on_suite_setup(orphans))) + + GC_ORPHANS_CHECK.TEST_HOOK_AFTER: + if orphans > 0: + reports().push_front(GdUnitReport.new()\ + .create(GdUnitReport.WARN, 1, GdAssertMessages.orphan_detected_on_test_setup(orphans))) + + GC_ORPHANS_CHECK.TEST_CASE: + if orphans > 0: + reports().push_front(GdUnitReport.new()\ + .create(GdUnitReport.WARN, test_case.line_number(), GdAssertMessages.orphan_detected_on_test(orphans))) diff --git a/addons/gdUnit4/src/core/execution/GdUnitExecutionContext.gd.uid b/addons/gdUnit4/src/core/execution/GdUnitExecutionContext.gd.uid new file mode 100644 index 0000000..ad0f070 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/GdUnitExecutionContext.gd.uid @@ -0,0 +1 @@ +uid://d12y60lq2ehec diff --git a/addons/gdUnit4/src/core/execution/GdUnitMemoryObserver.gd b/addons/gdUnit4/src/core/execution/GdUnitMemoryObserver.gd new file mode 100644 index 0000000..dd03a31 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/GdUnitMemoryObserver.gd @@ -0,0 +1,135 @@ +## The memory watcher for objects that have been registered and are released when 'gc' is called. +class_name GdUnitMemoryObserver +extends RefCounted + +const TAG_OBSERVE_INSTANCE := "GdUnit4_observe_instance_" +const TAG_AUTO_FREE = "GdUnit4_marked_auto_free" +const GdUnitTools = preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") + + +var _store :Array[Variant] = [] +# enable for debugging purposes +var _is_stdout_verbose := false +const _show_debug := false + + +## Registration of an instance to be released when an execution phase is completed +func register_auto_free(obj :Variant) -> Variant: + if not is_instance_valid(obj): + return obj + # do not register on GDScriptNativeClass + @warning_ignore("unsafe_cast") + if typeof(obj) == TYPE_OBJECT and (obj as Object).is_class("GDScriptNativeClass") : + return obj + #if obj is GDScript or obj is ScriptExtension: + # return obj + if obj is MainLoop: + push_error("GdUnit4: Avoid to add mainloop to auto_free queue %s" % obj) + return + if _is_stdout_verbose: + print_verbose("GdUnit4:gc():register auto_free(%s)" % obj) + # only register pure objects + if obj is GdUnitSceneRunner: + _store.push_back(obj) + else: + _store.append(obj) + _tag_object(obj) + return obj + + +# to disable instance guard when run into issues. +static func _is_instance_guard_enabled() -> bool: + return false + + +static func debug_observe(name :String, obj :Object, indent :int = 0) -> void: + if not _show_debug: + return + var script :GDScript= obj if obj is GDScript else obj.get_script() + if script: + var base_script :GDScript = script.get_base_script() + @warning_ignore("unsafe_method_access") + prints("".lpad(indent, " "), name, obj, obj.get_class(), "reference_count:", obj.get_reference_count() if obj is RefCounted else 0, "script:", script, script.resource_path) + if base_script: + debug_observe("+", base_script, indent+1) + else: + @warning_ignore("unsafe_method_access") + prints(name, obj, obj.get_class(), obj.get_name()) + + +static func guard_instance(obj :Object) -> void: + if not _is_instance_guard_enabled(): + return + var tag := TAG_OBSERVE_INSTANCE + str(abs(obj.get_instance_id())) + if Engine.has_meta(tag): + return + debug_observe("Gard on instance", obj) + Engine.set_meta(tag, obj) + + +static func unguard_instance(obj :Object, verbose := true) -> void: + if not _is_instance_guard_enabled(): + return + var tag := TAG_OBSERVE_INSTANCE + str(abs(obj.get_instance_id())) + if verbose: + debug_observe("unguard instance", obj) + if Engine.has_meta(tag): + Engine.remove_meta(tag) + + +static func gc_guarded_instance(name :String, instance :Object) -> void: + if not _is_instance_guard_enabled(): + return + await (Engine.get_main_loop() as SceneTree).process_frame + unguard_instance(instance, false) + if is_instance_valid(instance) and instance is RefCounted: + # finally do this very hacky stuff + # we need to manually unreferece to avoid leaked scripts + # but still leaked GDScriptFunctionState exists + #var script :GDScript = instance.get_script() + #if script: + # var base_script :GDScript = script.get_base_script() + # if base_script: + # base_script.unreference() + debug_observe(name, instance) + (instance as RefCounted).unreference() + await (Engine.get_main_loop() as SceneTree).process_frame + + +static func gc_on_guarded_instances() -> void: + if not _is_instance_guard_enabled(): + return + for tag in Engine.get_meta_list(): + if tag.begins_with(TAG_OBSERVE_INSTANCE): + var instance :Object = Engine.get_meta(tag) + await gc_guarded_instance("Leaked instance detected:", instance) + await GdUnitTools.free_instance(instance, false) + + +# store the object into global store aswell to be verified by 'is_marked_auto_free' +func _tag_object(obj :Variant) -> void: + var tagged_object: Array = Engine.get_meta(TAG_AUTO_FREE, []) + tagged_object.append(obj) + Engine.set_meta(TAG_AUTO_FREE, tagged_object) + + +## Runs over all registered objects and releases them +func gc() -> void: + if _store.is_empty(): + return + # give engine time to free objects to process objects marked by queue_free() + await (Engine.get_main_loop() as SceneTree).process_frame + if _is_stdout_verbose: + print_verbose("GdUnit4:gc():running", " freeing %d objects .." % _store.size()) + var tagged_objects: Array = Engine.get_meta(TAG_AUTO_FREE, []) + while not _store.is_empty(): + var value :Variant = _store.pop_front() + tagged_objects.erase(value) + await GdUnitTools.free_instance(value, _is_stdout_verbose) + assert(_store.is_empty(), "The memory observer has still entries in the store!") + + +## Checks whether the specified object is registered for automatic release +static func is_marked_auto_free(obj: Variant) -> bool: + var tagged_objects: Array = Engine.get_meta(TAG_AUTO_FREE, []) + return tagged_objects.has(obj) diff --git a/addons/gdUnit4/src/core/execution/GdUnitMemoryObserver.gd.uid b/addons/gdUnit4/src/core/execution/GdUnitMemoryObserver.gd.uid new file mode 100644 index 0000000..4b3186a --- /dev/null +++ b/addons/gdUnit4/src/core/execution/GdUnitMemoryObserver.gd.uid @@ -0,0 +1 @@ +uid://bf4ooevpom8jp diff --git a/addons/gdUnit4/src/core/execution/GdUnitTestReportCollector.gd b/addons/gdUnit4/src/core/execution/GdUnitTestReportCollector.gd new file mode 100644 index 0000000..5f42d14 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/GdUnitTestReportCollector.gd @@ -0,0 +1,62 @@ +# Collects all reports seperated as warnings, failures and errors +class_name GdUnitTestReportCollector +extends RefCounted + + +var _reports :Array[GdUnitReport] = [] + + +static func __filter_is_error(report :GdUnitReport) -> bool: + return report.is_error() + + +static func __filter_is_failure(report :GdUnitReport) -> bool: + return report.is_failure() + + +static func __filter_is_warning(report :GdUnitReport) -> bool: + return report.is_warning() + + +static func __filter_is_skipped(report :GdUnitReport) -> bool: + return report.is_skipped() + + +static func count_failures(reports_: Array[GdUnitReport]) -> int: + return reports_.filter(__filter_is_failure).size() + + +static func count_errors(reports_: Array[GdUnitReport]) -> int: + return reports_.filter(__filter_is_error).size() + + +static func count_warnings(reports_: Array[GdUnitReport]) -> int: + return reports_.filter(__filter_is_warning).size() + + +static func count_skipped(reports_: Array[GdUnitReport]) -> int: + return reports_.filter(__filter_is_skipped).size() + + +func has_failures() -> bool: + return _reports.any(__filter_is_failure) + + +func has_errors() -> bool: + return _reports.any(__filter_is_error) + + +func has_warnings() -> bool: + return _reports.any(__filter_is_warning) + + +func has_skipped() -> bool: + return _reports.any(__filter_is_skipped) + + +func reports() -> Array[GdUnitReport]: + return _reports + + +func push_back(report :GdUnitReport) -> void: + _reports.push_back(report) diff --git a/addons/gdUnit4/src/core/execution/GdUnitTestReportCollector.gd.uid b/addons/gdUnit4/src/core/execution/GdUnitTestReportCollector.gd.uid new file mode 100644 index 0000000..4fb8def --- /dev/null +++ b/addons/gdUnit4/src/core/execution/GdUnitTestReportCollector.gd.uid @@ -0,0 +1 @@ +uid://csuxf3wljukmn diff --git a/addons/gdUnit4/src/core/execution/GdUnitTestSuiteExecutor.gd b/addons/gdUnit4/src/core/execution/GdUnitTestSuiteExecutor.gd new file mode 100644 index 0000000..e3fd510 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/GdUnitTestSuiteExecutor.gd @@ -0,0 +1,48 @@ +## The executor to run a test-suite +class_name GdUnitTestSuiteExecutor + + +# preload all asserts here +@warning_ignore("unused_private_class_variable") +var _assertions := GdUnitAssertions.new() +var _executeStage := GdUnitTestSuiteExecutionStage.new() +var _debug_mode : bool + +func _init(debug_mode :bool = false) -> void: + _executeStage.set_debug_mode(debug_mode) + _debug_mode = debug_mode + + +func execute(test_suite :GdUnitTestSuite) -> void: + var orphan_detection_enabled := GdUnitSettings.is_verbose_orphans() + if not orphan_detection_enabled: + prints("!!! Reporting orphan nodes is disabled. Please check GdUnit settings.") + + (Engine.get_main_loop() as SceneTree).root.call_deferred("add_child", test_suite) + await (Engine.get_main_loop() as SceneTree).process_frame + await _executeStage.execute(GdUnitExecutionContext.of_test_suite(test_suite)) + + +func run_and_wait(tests: Array[GdUnitTestCase]) -> void: + if !_debug_mode: + GdUnitSignals.instance().gdunit_event.emit(GdUnitInit.new()) + # first we group all tests by resource path + var grouped_by_suites := GdArrayTools.group_by(tests, func(test: GdUnitTestCase) -> String: + return test.suite_resource_path + ) + var scanner := GdUnitTestSuiteScanner.new() + for suite_path: String in grouped_by_suites.keys(): + @warning_ignore("unsafe_call_argument") + var suite_tests: Array[GdUnitTestCase] = Array(grouped_by_suites[suite_path], TYPE_OBJECT, "RefCounted", GdUnitTestCase) + var script := GdUnitTestSuiteScanner.load_with_disabled_warnings(suite_path) + if script.get_class() == "GDScript": + var test_suite := scanner.load_suite(script as GDScript, suite_tests) + await execute(test_suite) + else: + await GdUnit4CSharpApiLoader.execute(suite_tests) + if !_debug_mode: + GdUnitSignals.instance().gdunit_event.emit(GdUnitStop.new()) + + +func fail_fast(enabled :bool) -> void: + _executeStage.fail_fast(enabled) diff --git a/addons/gdUnit4/src/core/execution/GdUnitTestSuiteExecutor.gd.uid b/addons/gdUnit4/src/core/execution/GdUnitTestSuiteExecutor.gd.uid new file mode 100644 index 0000000..44c4c02 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/GdUnitTestSuiteExecutor.gd.uid @@ -0,0 +1 @@ +uid://cpnagercld5mi diff --git a/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseAfterStage.gd b/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseAfterStage.gd new file mode 100644 index 0000000..d3c6245 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseAfterStage.gd @@ -0,0 +1,22 @@ +## The test case shutdown hook implementation.[br] +## It executes the 'test_after()' block from the test-suite. +class_name GdUnitTestCaseAfterStage +extends IGdUnitExecutionStage + + +var _call_stage: bool + + +func _init(call_stage := true) -> void: + _call_stage = call_stage + + +func _execute(context: GdUnitExecutionContext) -> void: + var test_suite := context.test_suite + + if _call_stage: + @warning_ignore("redundant_await") + await test_suite.after_test() + + await context.gc(GdUnitExecutionContext.GC_ORPHANS_CHECK.TEST_HOOK_AFTER) + await context.error_monitor_stop() diff --git a/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseAfterStage.gd.uid b/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseAfterStage.gd.uid new file mode 100644 index 0000000..0475a8d --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseAfterStage.gd.uid @@ -0,0 +1 @@ +uid://deacd1mgnnwt5 diff --git a/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseBeforeStage.gd b/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseBeforeStage.gd new file mode 100644 index 0000000..4e04fad --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseBeforeStage.gd @@ -0,0 +1,19 @@ +## The test case startup hook implementation.[br] +## It executes the 'test_before()' block from the test-suite. +class_name GdUnitTestCaseBeforeStage +extends IGdUnitExecutionStage + +var _call_stage :bool + + +func _init(call_stage := true) -> void: + _call_stage = call_stage + + +func _execute(context :GdUnitExecutionContext) -> void: + var test_suite := context.test_suite + + if _call_stage: + @warning_ignore("redundant_await") + await test_suite.before_test() + context.error_monitor_start() diff --git a/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseBeforeStage.gd.uid b/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseBeforeStage.gd.uid new file mode 100644 index 0000000..c76af33 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseBeforeStage.gd.uid @@ -0,0 +1 @@ +uid://builxwwc0etwk diff --git a/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseExecutionStage.gd b/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseExecutionStage.gd new file mode 100644 index 0000000..12cc6fd --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseExecutionStage.gd @@ -0,0 +1,37 @@ +## The test case execution stage.[br] +class_name GdUnitTestCaseExecutionStage +extends IGdUnitExecutionStage + + +var _stage_single_test: IGdUnitExecutionStage = GdUnitTestCaseSingleExecutionStage.new() +var _stage_fuzzer_test: IGdUnitExecutionStage = GdUnitTestCaseFuzzedExecutionStage.new() + + +## Executes the test case 'test_()'.[br] +## It executes synchronized following stages[br] +## -> test_before() [br] +## -> test_case() [br] +## -> test_after() [br] +@warning_ignore("redundant_await") +func _execute(context :GdUnitExecutionContext) -> void: + var test_case := context.test_case + + context.error_monitor_start() + + if test_case.is_fuzzed(): + await _stage_fuzzer_test.execute(context) + else: + await _stage_single_test.execute(context) + + await context.gc() + await context.error_monitor_stop() + + # finally free the test instance + if is_instance_valid(context.test_case): + context.test_case.dispose() + + +func set_debug_mode(debug_mode :bool = false) -> void: + super.set_debug_mode(debug_mode) + _stage_single_test.set_debug_mode(debug_mode) + _stage_fuzzer_test.set_debug_mode(debug_mode) diff --git a/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseExecutionStage.gd.uid b/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseExecutionStage.gd.uid new file mode 100644 index 0000000..d970011 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/GdUnitTestCaseExecutionStage.gd.uid @@ -0,0 +1 @@ +uid://2loby2n2r1lu diff --git a/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteAfterStage.gd b/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteAfterStage.gd new file mode 100644 index 0000000..03bbd0f --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteAfterStage.gd @@ -0,0 +1,29 @@ +## The test suite shutdown hook implementation.[br] +## It executes the 'after()' block from the test-suite. +class_name GdUnitTestSuiteAfterStage +extends IGdUnitExecutionStage + + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") + + +func _execute(context :GdUnitExecutionContext) -> void: + var test_suite := context.test_suite + + @warning_ignore("redundant_await") + await test_suite.after() + await context.gc(GdUnitExecutionContext.GC_ORPHANS_CHECK.SUITE_HOOK_AFTER) + + var reports := context.collect_reports(false) + var statistics := context.calculate_statistics(reports) + fire_event(GdUnitEvent.new()\ + .suite_after(context.get_test_suite_path(),\ + test_suite.get_name(), + statistics, + reports)) + GdUnitFileAccess.clear_tmp() + # Guard that checks if all doubled (spy/mock) objects are released + await GdUnitClassDoubler.check_leaked_instances() + # we hide the scene/main window after runner is finished + if not Engine.is_embedded_in_editor(): + DisplayServer.window_set_mode(DisplayServer.WINDOW_MODE_MINIMIZED) diff --git a/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteAfterStage.gd.uid b/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteAfterStage.gd.uid new file mode 100644 index 0000000..ff393fd --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteAfterStage.gd.uid @@ -0,0 +1 @@ +uid://c16nrh5nfu16n diff --git a/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteBeforeStage.gd b/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteBeforeStage.gd new file mode 100644 index 0000000..e9fa718 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteBeforeStage.gd @@ -0,0 +1,14 @@ +## The test suite startup hook implementation.[br] +## It executes the 'before()' block from the test-suite. +class_name GdUnitTestSuiteBeforeStage +extends IGdUnitExecutionStage + + +func _execute(context :GdUnitExecutionContext) -> void: + var test_suite := context.test_suite + + fire_event(GdUnitEvent.new()\ + .suite_before(context.get_test_suite_path(), test_suite.get_name(), test_suite.get_child_count())) + + @warning_ignore("redundant_await") + await test_suite.before() diff --git a/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteBeforeStage.gd.uid b/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteBeforeStage.gd.uid new file mode 100644 index 0000000..30d2e62 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteBeforeStage.gd.uid @@ -0,0 +1 @@ +uid://ciwm6k04llsr diff --git a/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteExecutionStage.gd b/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteExecutionStage.gd new file mode 100644 index 0000000..ac921e0 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteExecutionStage.gd @@ -0,0 +1,147 @@ +## The test suite main execution stage.[br] +class_name GdUnitTestSuiteExecutionStage +extends IGdUnitExecutionStage + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") + +var _stage_before :IGdUnitExecutionStage = GdUnitTestSuiteBeforeStage.new() +var _stage_after :IGdUnitExecutionStage = GdUnitTestSuiteAfterStage.new() +var _stage_test :IGdUnitExecutionStage = GdUnitTestCaseExecutionStage.new() +var _fail_fast := false + + +## Executes all tests of an test suite.[br] +## It executes synchronized following stages[br] +## -> before() [br] +## -> run all test cases [br] +## -> after() [br] +func _execute(context :GdUnitExecutionContext) -> void: + if context.test_suite.__is_skipped: + await fire_test_suite_skipped(context) + else: + @warning_ignore("return_value_discarded") + GdUnitMemoryObserver.guard_instance(context.test_suite.__awaiter) + await _stage_before.execute(context) + for test_case_index in context.test_suite.get_child_count(): + # iterate only over test cases + var test_case := context.test_suite.get_child(test_case_index) as _TestCase + if not is_instance_valid(test_case): + continue + context.test_suite.set_active_test_case(test_case.test_name()) + await _stage_test.execute(GdUnitExecutionContext.of_test_case(context, test_case)) + # stop on first error or if fail fast is enabled + if _fail_fast and not context.is_success(): + break + if test_case.is_interupted(): + # it needs to go this hard way to kill the outstanding awaits of a test case when the test timed out + # we delete the current test suite where is execute the current test case to kill the function state + # and replace it by a clone without function state + context.test_suite = await clone_test_suite(context.test_suite) + await _stage_after.execute(context) + GdUnitMemoryObserver.unguard_instance(context.test_suite.__awaiter) + await (Engine.get_main_loop() as SceneTree).process_frame + context.test_suite.free() + context.dispose() + + +# clones a test suite and moves the test cases to new instance +func clone_test_suite(test_suite :GdUnitTestSuite) -> GdUnitTestSuite: + await (Engine.get_main_loop() as SceneTree).process_frame + dispose_timers(test_suite) + await GdUnitMemoryObserver.gc_guarded_instance("Manually free on awaiter", test_suite.__awaiter) + var parent := test_suite.get_parent() + var _test_suite := GdUnitTestSuite.new() + parent.remove_child(test_suite) + copy_properties(test_suite, _test_suite) + for child in test_suite.get_children(): + test_suite.remove_child(child) + _test_suite.add_child(child) + parent.add_child(_test_suite) + @warning_ignore("return_value_discarded") + GdUnitMemoryObserver.guard_instance(_test_suite.__awaiter) + # finally free current test suite instance + test_suite.free() + await (Engine.get_main_loop() as SceneTree).process_frame + return _test_suite + + +func dispose_timers(test_suite :GdUnitTestSuite) -> void: + GdUnitTools.release_timers() + for child in test_suite.get_children(): + if child is Timer: + (child as Timer).stop() + test_suite.remove_child(child) + child.free() + + +func copy_properties(source :Object, target :Object) -> void: + if not source is _TestCase and not source is GdUnitTestSuite: + return + for property in source.get_property_list(): + var property_name :String = property["name"] + if property_name == "__awaiter": + continue + target.set(property_name, source.get(property_name)) + + +func fire_test_suite_skipped(context :GdUnitExecutionContext) -> void: + var test_suite := context.test_suite + var skip_count := test_suite.get_child_count() + fire_event(GdUnitEvent.new()\ + .suite_before(context.get_test_suite_path(), test_suite.get_name(), skip_count)) + + + for test_case_index in context.test_suite.get_child_count(): + # iterate only over test cases + var test_case := context.test_suite.get_child(test_case_index) as _TestCase + if not is_instance_valid(test_case): + continue + var test_case_context := GdUnitExecutionContext.of_test_case(context, test_case) + fire_event(GdUnitEvent.new().test_before(test_case.id())) + # use skip count 0 because we counted it over the complete test suite + fire_test_skipped(test_case_context, 0) + + + var statistics := { + GdUnitEvent.ORPHAN_NODES: 0, + GdUnitEvent.ELAPSED_TIME: 0, + GdUnitEvent.WARNINGS: false, + GdUnitEvent.ERRORS: false, + GdUnitEvent.ERROR_COUNT: 0, + GdUnitEvent.FAILED: false, + GdUnitEvent.FAILED_COUNT: 0, + GdUnitEvent.SKIPPED_COUNT: skip_count, + GdUnitEvent.SKIPPED: true + } + var report := GdUnitReport.new().create(GdUnitReport.SKIPPED, -1, GdAssertMessages.test_suite_skipped(test_suite.__skip_reason, skip_count)) + fire_event(GdUnitEvent.new().suite_after(context.get_test_suite_path(), test_suite.get_name(), statistics, [report])) + await (Engine.get_main_loop() as SceneTree).process_frame + + +func fire_test_skipped(context: GdUnitExecutionContext, skip_count := 1) -> void: + var test_case := context.test_case + var statistics := { + GdUnitEvent.ORPHAN_NODES: 0, + GdUnitEvent.ELAPSED_TIME: 0, + GdUnitEvent.WARNINGS: false, + GdUnitEvent.ERRORS: false, + GdUnitEvent.ERROR_COUNT: 0, + GdUnitEvent.FAILED: false, + GdUnitEvent.FAILED_COUNT: 0, + GdUnitEvent.SKIPPED: true, + GdUnitEvent.SKIPPED_COUNT: skip_count, + } + var report := GdUnitReport.new() \ + .create(GdUnitReport.SKIPPED, test_case.line_number(), GdAssertMessages.test_skipped("Skipped from the entire test suite")) + fire_event(GdUnitEvent.new().test_after(test_case.id(), statistics, [report])) + + +func set_debug_mode(debug_mode :bool = false) -> void: + super.set_debug_mode(debug_mode) + _stage_before.set_debug_mode(debug_mode) + _stage_after.set_debug_mode(debug_mode) + _stage_test.set_debug_mode(debug_mode) + + +func fail_fast(enabled :bool) -> void: + _fail_fast = enabled diff --git a/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteExecutionStage.gd.uid b/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteExecutionStage.gd.uid new file mode 100644 index 0000000..4be3378 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/GdUnitTestSuiteExecutionStage.gd.uid @@ -0,0 +1 @@ +uid://dl5y1yq8my0h0 diff --git a/addons/gdUnit4/src/core/execution/stages/IGdUnitExecutionStage.gd b/addons/gdUnit4/src/core/execution/stages/IGdUnitExecutionStage.gd new file mode 100644 index 0000000..39de380 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/IGdUnitExecutionStage.gd @@ -0,0 +1,39 @@ +## The interface of execution stage.[br] +## An execution stage is defined as an encapsulated task that can execute 1-n substages covered by its own execution context.[br] +## Execution stage are always called synchronously. +class_name IGdUnitExecutionStage +extends RefCounted + +var _debug_mode := false + + +## Executes synchronized the implemented stage in its own execution context.[br] +## example:[br] +## [codeblock] +## # waits for 100ms +## await MyExecutionStage.new().execute() +## [/codeblock][br] +func execute(context :GdUnitExecutionContext) -> void: + GdUnitThreadManager.get_current_context().set_execution_context(context) + @warning_ignore("redundant_await") + await _execute(context) + + +## Sends the event to registered listeners +func fire_event(event :GdUnitEvent) -> void: + if _debug_mode: + GdUnitSignals.instance().gdunit_event_debug.emit(event) + else: + GdUnitSignals.instance().gdunit_event.emit(event) + + +## Internal testing stuff.[br] +## Sets the executor into debug mode to emit `GdUnitEvent` via signal `gdunit_event_debug` +func set_debug_mode(debug_mode :bool) -> void: + _debug_mode = debug_mode + + +## The execution phase to be carried out. +func _execute(_context :GdUnitExecutionContext) -> void: + @warning_ignore("assert_always_false") + assert(false, "The execution stage is not implemented") diff --git a/addons/gdUnit4/src/core/execution/stages/IGdUnitExecutionStage.gd.uid b/addons/gdUnit4/src/core/execution/stages/IGdUnitExecutionStage.gd.uid new file mode 100644 index 0000000..c7dbe1d --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/IGdUnitExecutionStage.gd.uid @@ -0,0 +1 @@ +uid://dggrqeqhhio6x diff --git a/addons/gdUnit4/src/core/execution/stages/fuzzed/GdUnitTestCaseFuzzedExecutionStage.gd b/addons/gdUnit4/src/core/execution/stages/fuzzed/GdUnitTestCaseFuzzedExecutionStage.gd new file mode 100644 index 0000000..73a7a66 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/fuzzed/GdUnitTestCaseFuzzedExecutionStage.gd @@ -0,0 +1,52 @@ +## The test case execution stage.[br] +class_name GdUnitTestCaseFuzzedExecutionStage +extends IGdUnitExecutionStage + +var _stage_before :IGdUnitExecutionStage = GdUnitTestCaseBeforeStage.new(false) +var _stage_after :IGdUnitExecutionStage = GdUnitTestCaseAfterStage.new(false) +var _stage_test :IGdUnitExecutionStage = GdUnitTestCaseFuzzedTestStage.new() + + +func _execute(context :GdUnitExecutionContext) -> void: + fire_event(GdUnitEvent.new().test_before(context.test_case.id())) + + while context.retry_execution(): + var test_context := GdUnitExecutionContext.of(context) + await _stage_before.execute(test_context) + if not context.test_case.is_skipped(): + await _stage_test.execute(GdUnitExecutionContext.of(test_context)) + await _stage_after.execute(test_context) + if test_context.is_success() or test_context.is_skipped() or test_context.is_interupted(): + break + + context.gc() + if context.is_skipped(): + fire_test_skipped(context) + else: + var reports: = context.collect_reports(true) + var statistics := context.calculate_statistics(reports) + fire_event(GdUnitEvent.new().test_after(context.test_case.id(), statistics, reports)) + +func set_debug_mode(debug_mode :bool = false) -> void: + super.set_debug_mode(debug_mode) + _stage_before.set_debug_mode(debug_mode) + _stage_after.set_debug_mode(debug_mode) + _stage_test.set_debug_mode(debug_mode) + + +func fire_test_skipped(context: GdUnitExecutionContext) -> void: + var test_case := context.test_case + var statistics := { + GdUnitEvent.ORPHAN_NODES: 0, + GdUnitEvent.ELAPSED_TIME: 0, + GdUnitEvent.WARNINGS: false, + GdUnitEvent.ERRORS: false, + GdUnitEvent.ERROR_COUNT: 0, + GdUnitEvent.FAILED: false, + GdUnitEvent.FAILED_COUNT: 0, + GdUnitEvent.SKIPPED: true, + GdUnitEvent.SKIPPED_COUNT: 1, + } + var report := GdUnitReport.new() \ + .create(GdUnitReport.SKIPPED, test_case.line_number(), GdAssertMessages.test_skipped(test_case.skip_info())) + fire_event(GdUnitEvent.new().test_after(test_case.id(), statistics, [report])) diff --git a/addons/gdUnit4/src/core/execution/stages/fuzzed/GdUnitTestCaseFuzzedExecutionStage.gd.uid b/addons/gdUnit4/src/core/execution/stages/fuzzed/GdUnitTestCaseFuzzedExecutionStage.gd.uid new file mode 100644 index 0000000..078ab3e --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/fuzzed/GdUnitTestCaseFuzzedExecutionStage.gd.uid @@ -0,0 +1 @@ +uid://ma4c3hq2rq4q diff --git a/addons/gdUnit4/src/core/execution/stages/fuzzed/GdUnitTestCaseFuzzedTestStage.gd b/addons/gdUnit4/src/core/execution/stages/fuzzed/GdUnitTestCaseFuzzedTestStage.gd new file mode 100644 index 0000000..62dda37 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/fuzzed/GdUnitTestCaseFuzzedTestStage.gd @@ -0,0 +1,55 @@ +## The fuzzed test case execution stage.[br] +class_name GdUnitTestCaseFuzzedTestStage +extends IGdUnitExecutionStage + +var _expression_runner := GdUnitExpressionRunner.new() + + +## Executes a test case with given fuzzers 'test_()' iterative.[br] +## It executes synchronized following stages[br] +## -> test_case() [br] +func _execute(context :GdUnitExecutionContext) -> void: + var test_suite := context.test_suite + var test_case := context.test_case + var fuzzers := create_fuzzers(test_suite, test_case) + + # guard on fuzzers + for fuzzer in fuzzers: + @warning_ignore("return_value_discarded") + GdUnitMemoryObserver.guard_instance(fuzzer) + + for iteration in test_case.iterations(): + @warning_ignore("redundant_await") + await test_suite.before_test() + await test_case.execute(fuzzers, iteration) + @warning_ignore("redundant_await") + await test_suite.after_test() + if test_case.is_interupted(): + break + # interrupt at first failure + var reports := context.reports() + if not reports.is_empty(): + var report :GdUnitReport = reports.pop_front() + reports.append(GdUnitReport.new() \ + .create(GdUnitReport.FAILURE, report.line_number(), GdAssertMessages.fuzzer_interuped(iteration, report.message()))) + break + await context.gc(GdUnitExecutionContext.GC_ORPHANS_CHECK.TEST_CASE) + + # unguard on fuzzers + if not test_case.is_interupted(): + for fuzzer in fuzzers: + GdUnitMemoryObserver.unguard_instance(fuzzer) + + +func create_fuzzers(test_suite :GdUnitTestSuite, test_case :_TestCase) -> Array[Fuzzer]: + if not test_case.is_fuzzed(): + return Array() + test_case.generate_seed() + var fuzzers :Array[Fuzzer] = [] + for fuzzer_arg in test_case.fuzzer_arguments(): + @warning_ignore("unsafe_cast") + var fuzzer := _expression_runner.to_fuzzer(test_suite.get_script() as GDScript, fuzzer_arg.plain_value() as String) + fuzzer._iteration_index = 0 + fuzzer._iteration_limit = test_case.iterations() + fuzzers.append(fuzzer) + return fuzzers diff --git a/addons/gdUnit4/src/core/execution/stages/fuzzed/GdUnitTestCaseFuzzedTestStage.gd.uid b/addons/gdUnit4/src/core/execution/stages/fuzzed/GdUnitTestCaseFuzzedTestStage.gd.uid new file mode 100644 index 0000000..7163348 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/fuzzed/GdUnitTestCaseFuzzedTestStage.gd.uid @@ -0,0 +1 @@ +uid://cg5mg83fplhoi diff --git a/addons/gdUnit4/src/core/execution/stages/single/GdUnitTestCaseSingleExecutionStage.gd b/addons/gdUnit4/src/core/execution/stages/single/GdUnitTestCaseSingleExecutionStage.gd new file mode 100644 index 0000000..70d687f --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/single/GdUnitTestCaseSingleExecutionStage.gd @@ -0,0 +1,53 @@ +## The test case execution stage.[br] +class_name GdUnitTestCaseSingleExecutionStage +extends IGdUnitExecutionStage + + +var _stage_before :IGdUnitExecutionStage = GdUnitTestCaseBeforeStage.new() +var _stage_after :IGdUnitExecutionStage = GdUnitTestCaseAfterStage.new() +var _stage_test :IGdUnitExecutionStage = GdUnitTestCaseSingleTestStage.new() + + +func _execute(context :GdUnitExecutionContext) -> void: + fire_event(GdUnitEvent.new().test_before(context.test_case.id())) + while context.retry_execution(): + var test_context := GdUnitExecutionContext.of(context) + await _stage_before.execute(test_context) + if not test_context.is_skipped(): + await _stage_test.execute(GdUnitExecutionContext.of(test_context)) + await _stage_after.execute(test_context) + if test_context.is_success() or test_context.is_skipped() or test_context.is_interupted(): + break + + context.gc() + if context.is_skipped(): + fire_test_skipped(context) + else: + var reports: = context.collect_reports(true) + var statistics := context.calculate_statistics(reports) + fire_event(GdUnitEvent.new().test_after(context.test_case.id(), statistics, reports)) + + +func set_debug_mode(debug_mode :bool = false) -> void: + super.set_debug_mode(debug_mode) + _stage_before.set_debug_mode(debug_mode) + _stage_after.set_debug_mode(debug_mode) + _stage_test.set_debug_mode(debug_mode) + + +func fire_test_skipped(context: GdUnitExecutionContext) -> void: + var test_case := context.test_case + var statistics := { + GdUnitEvent.ORPHAN_NODES: 0, + GdUnitEvent.ELAPSED_TIME: 0, + GdUnitEvent.WARNINGS: false, + GdUnitEvent.ERRORS: false, + GdUnitEvent.ERROR_COUNT: 0, + GdUnitEvent.FAILED: false, + GdUnitEvent.FAILED_COUNT: 0, + GdUnitEvent.SKIPPED: true, + GdUnitEvent.SKIPPED_COUNT: 1, + } + var report := GdUnitReport.new() \ + .create(GdUnitReport.SKIPPED, test_case.line_number(), GdAssertMessages.test_skipped(test_case.skip_info())) + fire_event(GdUnitEvent.new().test_after(test_case.id(), statistics, [report])) diff --git a/addons/gdUnit4/src/core/execution/stages/single/GdUnitTestCaseSingleExecutionStage.gd.uid b/addons/gdUnit4/src/core/execution/stages/single/GdUnitTestCaseSingleExecutionStage.gd.uid new file mode 100644 index 0000000..6123c3d --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/single/GdUnitTestCaseSingleExecutionStage.gd.uid @@ -0,0 +1 @@ +uid://ctt2ewnn65o8i diff --git a/addons/gdUnit4/src/core/execution/stages/single/GdUnitTestCaseSingleTestStage.gd b/addons/gdUnit4/src/core/execution/stages/single/GdUnitTestCaseSingleTestStage.gd new file mode 100644 index 0000000..9006b36 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/single/GdUnitTestCaseSingleTestStage.gd @@ -0,0 +1,11 @@ +## The single test case execution stage.[br] +class_name GdUnitTestCaseSingleTestStage +extends IGdUnitExecutionStage + + +## Executes a single test case 'test_()'.[br] +## It executes synchronized following stages[br] +## -> test_case() [br] +func _execute(context :GdUnitExecutionContext) -> void: + await context.test_case.execute() + await context.gc(GdUnitExecutionContext.GC_ORPHANS_CHECK.TEST_CASE) diff --git a/addons/gdUnit4/src/core/execution/stages/single/GdUnitTestCaseSingleTestStage.gd.uid b/addons/gdUnit4/src/core/execution/stages/single/GdUnitTestCaseSingleTestStage.gd.uid new file mode 100644 index 0000000..5193a03 --- /dev/null +++ b/addons/gdUnit4/src/core/execution/stages/single/GdUnitTestCaseSingleTestStage.gd.uid @@ -0,0 +1 @@ +uid://di38e7i5300v3 diff --git a/addons/gdUnit4/src/core/hooks/GdUnitBaseReporterTestSessionHook.gd b/addons/gdUnit4/src/core/hooks/GdUnitBaseReporterTestSessionHook.gd new file mode 100644 index 0000000..0f87ad1 --- /dev/null +++ b/addons/gdUnit4/src/core/hooks/GdUnitBaseReporterTestSessionHook.gd @@ -0,0 +1,78 @@ +class_name GdUnitBaseReporterTestSessionHook +extends GdUnitTestSessionHook + + +var test_session: GdUnitTestSession: + get: + return test_session + set(value): + # disconnect first possible connected listener + if test_session != null: + test_session.test_event.disconnect(_on_test_event) + # add listening to current session + test_session = value + if test_session != null: + test_session.test_event.connect(_on_test_event) + + +var _report_summary: GdUnitReportSummary +var _reporter: GdUnitTestReporter +var _report_writer: GdUnitReportWriter +var _report_converter: Callable + +func _init(report_writer: GdUnitReportWriter, hook_name: String, hook_description: String, report_converter: Callable) -> void: + super(hook_name, hook_description) + _reporter = GdUnitTestReporter.new() + _report_writer = report_writer + _report_converter = report_converter + + +func startup(session: GdUnitTestSession) -> GdUnitResult: + test_session = session + _report_summary = GdUnitReportSummary.new(_report_converter) + _reporter.init_summary() + + return GdUnitResult.success() + + +func shutdown(session: GdUnitTestSession) -> GdUnitResult: + var report_path := _report_writer.write(session.report_path, _report_summary) + session.send_message("Open {0} Report at: file://{1}".format([_report_writer.output_format(), report_path])) + + return GdUnitResult.success() + + +func _on_test_event(event: GdUnitEvent) -> void: + match event.type(): + GdUnitEvent.TESTSUITE_BEFORE: + _reporter.init_statistics() + _report_summary.add_testsuite_report(event.resource_path(), event.suite_name(), event.total_count()) + GdUnitEvent.TESTSUITE_AFTER: + var statistics := _reporter.build_test_suite_statisitcs(event) + _report_summary.update_testsuite_counters( + event.resource_path(), + _reporter.error_count(statistics), + _reporter.failed_count(statistics), + _reporter.orphan_nodes(statistics), + _reporter.skipped_count(statistics), + _reporter.flaky_count(statistics), + event.elapsed_time()) + _report_summary.add_testsuite_reports( + event.resource_path(), + event.reports() + ) + GdUnitEvent.TESTCASE_BEFORE: + var test := test_session.find_test_by_id(event.guid()) + _report_summary.add_testcase(test.source_file, test.suite_name, test.display_name) + GdUnitEvent.TESTCASE_AFTER: + _reporter.add_test_statistics(event) + var test := test_session.find_test_by_id(event.guid()) + _report_summary.set_counters(test.source_file, + test.display_name, + event.error_count(), + event.failed_count(), + event.orphan_nodes(), + event.is_skipped(), + event.is_flaky(), + event.elapsed_time()) + _report_summary.add_reports(test.source_file, test.display_name, event.reports()) diff --git a/addons/gdUnit4/src/core/hooks/GdUnitBaseReporterTestSessionHook.gd.uid b/addons/gdUnit4/src/core/hooks/GdUnitBaseReporterTestSessionHook.gd.uid new file mode 100644 index 0000000..dcea6ef --- /dev/null +++ b/addons/gdUnit4/src/core/hooks/GdUnitBaseReporterTestSessionHook.gd.uid @@ -0,0 +1 @@ +uid://bgi1xunfmp5kt diff --git a/addons/gdUnit4/src/core/hooks/GdUnitHtmlReporterTestSessionHook.gd b/addons/gdUnit4/src/core/hooks/GdUnitHtmlReporterTestSessionHook.gd new file mode 100644 index 0000000..4b8f390 --- /dev/null +++ b/addons/gdUnit4/src/core/hooks/GdUnitHtmlReporterTestSessionHook.gd @@ -0,0 +1,9 @@ +class_name GdUnitHtmlReporterTestSessionHook +extends GdUnitBaseReporterTestSessionHook + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") + + +func _init() -> void: + super(GdUnitHtmlReportWriter.new(), "GdUnitHtmlTestReporter", "The Html test reporting hook.", GdUnitTools.richtext_normalize) + set_meta("SYSTEM_HOOK", true) diff --git a/addons/gdUnit4/src/core/hooks/GdUnitHtmlReporterTestSessionHook.gd.uid b/addons/gdUnit4/src/core/hooks/GdUnitHtmlReporterTestSessionHook.gd.uid new file mode 100644 index 0000000..d721643 --- /dev/null +++ b/addons/gdUnit4/src/core/hooks/GdUnitHtmlReporterTestSessionHook.gd.uid @@ -0,0 +1 @@ +uid://cb5cnllfg3rbu diff --git a/addons/gdUnit4/src/core/hooks/GdUnitTestSessionHook.gd b/addons/gdUnit4/src/core/hooks/GdUnitTestSessionHook.gd new file mode 100644 index 0000000..23850e4 --- /dev/null +++ b/addons/gdUnit4/src/core/hooks/GdUnitTestSessionHook.gd @@ -0,0 +1,111 @@ +## @since GdUnit4 5.1.0 +## +## Base class for creating custom test session hooks in GdUnit4.[br] +## [br] +## [i]Test session hooks allow users to extend the GdUnit4 test framework by providing +## custom functionality that runs at specific points during the test execution lifecycle. +## This base class defines the interface that all test session hooks must implement.[/i] +## [br] +## [br] +## [b][u]Usage[/u][/b][br] +## 1. Create a new class that extends GdUnitTestSessionHook[br] +## 2. Override the required methods (startup, shutdown)[br] +## 3. Register your hook with the test engine (using the GdUnit4 settings dialog)[br] +## [br] +## [b][u]Example[/u][/b] +## [codeblock] +## class_name MyCustomTestHook +## extends GdUnitTestSessionHook +## +## func _init(): +## super("MyHook", "This is a description") +## +## func startup(session: GdUnitTestSession) -> GdUnitResult: +## session.send_message("Custom hook initialized") +## # Initialize resources, setup test environment, etc. +## return GdUnitResult.success() +## +## func shutdown(session: GdUnitTestSession) -> GdUnitResult: +## session.send_message("Custom hook cleanup completed") +## # Cleanup resources, generate reports, etc. +## return GdUnitResult.success() +## [/codeblock] +## +## [b][u]Hook Lifecycle[/u][/b][br] +## 1. [i][b]Registration[/b][/i]: Hooks are registered with the test engine via settings dialog[br] +## 2. [i][b]Priority Sorting[/b][/i]: Hooks are sorted by priority[br] +## 3. [i][b]Startup[/b][/i]: startup() is called before test execution begins, if it returns an error is shown in the console[br] +## 4. [i][b]Test Execution[/b][/i]: Tests run normally (only if all hooks started successfully)[br] +## 5. [i][b]Shutdown[/b][/i]: shutdown() is called after all tests complete, regardless of startup success[br] +## [br] +## [b][u]Priority System[/u][/b][br] +## The priority system allows controlling the execution order of multiple hooks.[br] +## - The order can be changed in the GdUnit4 settings dialog.[br] +## - The priority of system hooks cannot be changed and they cannot be deleted.[br] +## [br] +## [b][u]Session Access[/u][/b][br] +## +## Both [i]startup()[/i] and [i]shutdown()[/i] methods receive a [GdUnitTestSession] parameter that provides:[br] +## - Access to test cases being executed[br] +## - Event emission capabilities for test progress tracking[br] +## - Message sending functionality for logging and communication[br] +class_name GdUnitTestSessionHook +extends RefCounted + + +## The display name of this hook. +var name: String: + get: + return name + + +## A detailed description of what this hook does. +var description: String: + get: + return description + + +## Initializes a new test session hook. +## +## [param _name] The display name for this hook +## [param _description] A detailed description of the hook's functionality +func _init(_name: String, _description: String) -> void: + self.name = _name + self.description = _description + + +## Called when the test session starts up, before any tests are executed.[br] +## [br] +## [color=yellow][i]This method should be overridden to implement custom initialization logic[/i][/color][br] +## [br] +## such as:[br] +## - Setting up test databases or external services[br] +## - Initializing mock objects or test fixtures[br] +## - Configuring logging or reporting systems[br] +## - Preparing the test environment[br] +## - Subscribing to test events via the session[br] +## [br] +## [param session] The test session instance providing access to test data and communication[br] +## [b]return:[/b] [code]GdUnitResult.success()[/code] if initialization succeeds, or [code]GdUnitResult.error("error")[/code] with +## an error message if initialization fails. +func startup(_session: GdUnitTestSession) -> GdUnitResult: + return GdUnitResult.error("%s:startup is not implemented" % get_script().resource_path) + + +## Called when the test session shuts down, after all tests have completed.[br] +## [br] +## [color=yellow][i]This method should be overridden to implement custom cleanup logic[/i][/color][br] +## [br] +## such as:[br] +## - Cleaning up test databases or external services[br] +## - Generating test reports or artifacts[br] +## - Releasing resources allocated during startup[br] +## - Performing final validation or assertions[br] +## - Processing collected test events and data[br] +## [br] +## [param session] The test session instance providing access to test results and communication[br] +## [b]return:[/b] [code]GdUnitResult.success()[/code] if cleanup succeeds, or [code]GdUnitResult.error("error")[/code] with +## an error message if cleanup fails. Cleanup errors are typically logged +## but don't prevent the test engine from shutting down. +func shutdown(_session: GdUnitTestSession) -> GdUnitResult: + return GdUnitResult.error("%s:shutdown is not implemented" % get_script().resource_path) diff --git a/addons/gdUnit4/src/core/hooks/GdUnitTestSessionHook.gd.uid b/addons/gdUnit4/src/core/hooks/GdUnitTestSessionHook.gd.uid new file mode 100644 index 0000000..44d67c4 --- /dev/null +++ b/addons/gdUnit4/src/core/hooks/GdUnitTestSessionHook.gd.uid @@ -0,0 +1 @@ +uid://yqv0u1wv1t5n diff --git a/addons/gdUnit4/src/core/hooks/GdUnitTestSessionHookService.gd b/addons/gdUnit4/src/core/hooks/GdUnitTestSessionHookService.gd new file mode 100644 index 0000000..5a9bdcb --- /dev/null +++ b/addons/gdUnit4/src/core/hooks/GdUnitTestSessionHookService.gd @@ -0,0 +1,191 @@ +class_name GdUnitTestSessionHookService +extends Object + + +var enigne_hooks: Array[GdUnitTestSessionHook] = []: + get: + return enigne_hooks + set(value): + enigne_hooks.append(value) + + +var _save_settings: bool = false + + +static func instance() -> GdUnitTestSessionHookService: + return GdUnitSingleton.instance("GdUnitTestSessionHookService", func()->GdUnitTestSessionHookService: + GdUnitSignals.instance().gdunit_message.emit("Installing GdUnit4 session system hooks.") + var service := GdUnitTestSessionHookService.new() + # Register default system hooks here + service._save_settings = false + service.register(GdUnitHtmlReporterTestSessionHook.new()) + service.register(GdUnitXMLReporterTestSessionHook.new()) + service.load_hook_settings() + service._save_settings = true + return service + ) + + +static func contains_hook(current: GdUnitTestSessionHook, other: GdUnitTestSessionHook) -> bool: + return current.get_script().resource_path == other.get_script().resource_path + + +func find_custom(hook: GdUnitTestSessionHook) -> int: + for index in enigne_hooks.size(): + if contains_hook.call(enigne_hooks[index], hook): + return index + return -1 + + +func load_hook(hook_resourc_path: String) -> GdUnitResult: + if !FileAccess.file_exists(hook_resourc_path): + return GdUnitResult.error("The hook '%s' not exists." % hook_resourc_path) + var script: GDScript = load(hook_resourc_path) + if script.get_base_script() != GdUnitTestSessionHook: + return GdUnitResult.error("The hook '%s' must inhertit from 'GdUnitTestSessionHook'." % hook_resourc_path) + + return GdUnitResult.success(script.new()) + + +func enable_hook(hook: GdUnitTestSessionHook, enabled: bool) -> void: + _enable_hook(hook, enabled) + GdUnitSignals.instance().gdunit_message.emit("Session hook '{name}' {enabled}.".format({ + "name": hook.name, + "enabled": "enabled" if enabled else "disabled"}) + ) + save_hock_setttings() + + +func register(hook: GdUnitTestSessionHook, enabled: bool = true) -> GdUnitResult: + if find_custom(hook) != -1: + return GdUnitResult.error("A hook instance of '%s' is already registered." % hook.get_script().resource_path) + + _enable_hook(hook, enabled) + enigne_hooks.append(hook) + save_hock_setttings() + GdUnitSignals.instance().gdunit_message.emit("Session hook '%s' installed." % hook.name) + + return GdUnitResult.success() + + +func unregister(hook: GdUnitTestSessionHook) -> GdUnitResult: + var hook_index := find_custom(hook) + if hook_index == -1: + return GdUnitResult.error("The hook instance of '%s' is NOT registered." % hook.get_script().resource_path) + + enigne_hooks.remove_at(hook_index) + save_hock_setttings() + return GdUnitResult.success() + + +func move_before(hook: GdUnitTestSessionHook, before: GdUnitTestSessionHook) -> void: + var before_index := find_custom(before) + var hook_index := find_custom(hook) + + # Verify the hook to move is behind the hook to be moved + if before_index >= hook_index: + return + + enigne_hooks.remove_at(hook_index) + enigne_hooks.insert(before_index, hook) + save_hock_setttings() + + +func move_after(hook: GdUnitTestSessionHook, after: GdUnitTestSessionHook) -> void: + var after_index := find_custom(after) + var hook_index := find_custom(hook) + + # Verify the hook to move is before the hook to be moved + if after_index <= hook_index: + return + + enigne_hooks.remove_at(hook_index) + enigne_hooks.insert(after_index, hook) + save_hock_setttings() + + +func execute_startup(session: GdUnitTestSession) -> GdUnitResult: + return await execute("startup", session) + + +func execute_shutdown(session: GdUnitTestSession) -> GdUnitResult: + return await execute("shutdown", session, true) + + +func execute(hook_func: String, session: GdUnitTestSession, reverse := false) -> GdUnitResult: + var failed_hook_calls: Array[GdUnitResult] = [] + + for hook_index in enigne_hooks.size(): + var index := enigne_hooks.size()-hook_index-1 if reverse else hook_index + var hook: = enigne_hooks[index] + if not is_enabled(hook): + continue + if OS.is_stdout_verbose(): + GdUnitSignals.instance().gdunit_message.emit("Session hook '%s' > %s()" % [hook.name, hook_func]) + var result: GdUnitResult = await hook.call(hook_func, session) + if result == null: + failed_hook_calls.push_back(GdUnitResult.error("Result is null! Check '%s'" % hook.get_script().resource_path)) + elif result.is_error(): + failed_hook_calls.push_back(result) + + if failed_hook_calls.is_empty(): + return GdUnitResult.success() + + var errors := failed_hook_calls.map(func(result: GdUnitResult) -> String: + return "Hook call '%s' failed with error: '%s'" % [hook_func, result.error_message()] + ) + return GdUnitResult.error( "\n".join(errors)) + + +func save_hock_setttings() -> void: + if not _save_settings: + return + + var hooks_to_save: Dictionary[String, bool] = {} + for hook in enigne_hooks: + var enabled: bool = hook.get_meta("enabled") + hooks_to_save[hook.get_script().resource_path] = enabled + + GdUnitSettings.set_session_hooks(hooks_to_save) + + +func load_hook_settings() -> void: + var hooks_resource_paths := GdUnitSettings.get_session_hooks() + if hooks_resource_paths.is_empty(): + return + + for hock_path: String in hooks_resource_paths.keys(): + var enabled := hooks_resource_paths[hock_path] + + # Do not reinstall already installed hooks + var existing_hook: GdUnitTestSessionHook = enigne_hooks.filter(func(element: GdUnitTestSessionHook) -> bool: + return element.get_script().resource_path == hock_path + ).front() + # Applay enabled settings + if existing_hook != null: + _enable_hook(existing_hook, enabled) + continue + + # Load additional hooks + var result := load_hook(hock_path) + if result.is_error(): + push_error(result.error_message()) + continue + + GdUnitSignals.instance().gdunit_message.emit("Installing GdUnit4 session hooks.") + var hook: GdUnitTestSessionHook = result.value() + + result = register(hook, enabled) + if result.is_error(): + push_error(result.error_message()) + continue + + +static func is_enabled(hook: GdUnitTestSessionHook) -> bool: + if hook.has_meta("enabled"): + return hook.get_meta("enabled") + return true + + +func _enable_hook(hook: GdUnitTestSessionHook, enabled: bool) -> void: + hook.set_meta("enabled", enabled) diff --git a/addons/gdUnit4/src/core/hooks/GdUnitTestSessionHookService.gd.uid b/addons/gdUnit4/src/core/hooks/GdUnitTestSessionHookService.gd.uid new file mode 100644 index 0000000..39d9ab2 --- /dev/null +++ b/addons/gdUnit4/src/core/hooks/GdUnitTestSessionHookService.gd.uid @@ -0,0 +1 @@ +uid://cl0oj38pa505h diff --git a/addons/gdUnit4/src/core/hooks/GdUnitXMLReporterTestSessionHook.gd b/addons/gdUnit4/src/core/hooks/GdUnitXMLReporterTestSessionHook.gd new file mode 100644 index 0000000..94caef5 --- /dev/null +++ b/addons/gdUnit4/src/core/hooks/GdUnitXMLReporterTestSessionHook.gd @@ -0,0 +1,11 @@ +class_name GdUnitXMLReporterTestSessionHook +extends GdUnitBaseReporterTestSessionHook + + +func _init() -> void: + super(JUnitXmlReportWriter.new(), "GdUnitXMLTestReporter", "The JUnit XML test reporting hook.", convert_report_message) + set_meta("SYSTEM_HOOK", true) + + +func convert_report_message(value: String) -> String: + return value diff --git a/addons/gdUnit4/src/core/hooks/GdUnitXMLReporterTestSessionHook.gd.uid b/addons/gdUnit4/src/core/hooks/GdUnitXMLReporterTestSessionHook.gd.uid new file mode 100644 index 0000000..d686da2 --- /dev/null +++ b/addons/gdUnit4/src/core/hooks/GdUnitXMLReporterTestSessionHook.gd.uid @@ -0,0 +1 @@ +uid://dpkuec7sqkjwa diff --git a/addons/gdUnit4/src/core/parse/GdClassDescriptor.gd b/addons/gdUnit4/src/core/parse/GdClassDescriptor.gd new file mode 100644 index 0000000..fc83742 --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdClassDescriptor.gd @@ -0,0 +1,25 @@ +class_name GdClassDescriptor +extends RefCounted + + +var _name :String +var _is_inner_class :bool +var _functions :Array[GdFunctionDescriptor] + + +func _init(p_name :String, p_is_inner_class :bool, p_functions :Array[GdFunctionDescriptor]) -> void: + _name = p_name + _is_inner_class = p_is_inner_class + _functions = p_functions + + +func name() -> String: + return _name + + +func is_inner_class() -> bool: + return _is_inner_class + + +func functions() -> Array[GdFunctionDescriptor]: + return _functions diff --git a/addons/gdUnit4/src/core/parse/GdClassDescriptor.gd.uid b/addons/gdUnit4/src/core/parse/GdClassDescriptor.gd.uid new file mode 100644 index 0000000..b38604b --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdClassDescriptor.gd.uid @@ -0,0 +1 @@ +uid://ducxo0kxs4c4d diff --git a/addons/gdUnit4/src/core/parse/GdDefaultValueDecoder.gd b/addons/gdUnit4/src/core/parse/GdDefaultValueDecoder.gd new file mode 100644 index 0000000..f1b2244 --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdDefaultValueDecoder.gd @@ -0,0 +1,290 @@ +# holds all decodings for default values +class_name GdDefaultValueDecoder +extends GdUnitSingleton + + +@warning_ignore("unused_parameter") +var _decoders := { + TYPE_NIL: func(value :Variant) -> String: return "null", + TYPE_STRING: func(value :Variant) -> String: return '"%s"' % value, + TYPE_STRING_NAME: _on_type_StringName, + TYPE_BOOL: func(value :Variant) -> String: return str(value).to_lower(), + TYPE_FLOAT: func(value :Variant) -> String: return '%f' % value, + TYPE_COLOR: _on_type_Color, + TYPE_ARRAY: _on_type_Array.bind(TYPE_ARRAY), + TYPE_PACKED_BYTE_ARRAY: _on_type_Array.bind(TYPE_PACKED_BYTE_ARRAY), + TYPE_PACKED_STRING_ARRAY: _on_type_Array.bind(TYPE_PACKED_STRING_ARRAY), + TYPE_PACKED_FLOAT32_ARRAY: _on_type_Array.bind(TYPE_PACKED_FLOAT32_ARRAY), + TYPE_PACKED_FLOAT64_ARRAY: _on_type_Array.bind(TYPE_PACKED_FLOAT64_ARRAY), + TYPE_PACKED_INT32_ARRAY: _on_type_Array.bind(TYPE_PACKED_INT32_ARRAY), + TYPE_PACKED_INT64_ARRAY: _on_type_Array.bind(TYPE_PACKED_INT64_ARRAY), + TYPE_PACKED_COLOR_ARRAY: _on_type_Array.bind(TYPE_PACKED_COLOR_ARRAY), + TYPE_PACKED_VECTOR2_ARRAY: _on_type_Array.bind(TYPE_PACKED_VECTOR2_ARRAY), + TYPE_PACKED_VECTOR3_ARRAY: _on_type_Array.bind(TYPE_PACKED_VECTOR3_ARRAY), + TYPE_PACKED_VECTOR4_ARRAY: _on_type_Array.bind(TYPE_PACKED_VECTOR4_ARRAY), + TYPE_DICTIONARY: _on_type_Dictionary, + TYPE_RID: _on_type_RID, + TYPE_NODE_PATH: _on_type_NodePath, + TYPE_VECTOR2: _on_type_Vector.bind(TYPE_VECTOR2), + TYPE_VECTOR2I: _on_type_Vector.bind(TYPE_VECTOR2I), + TYPE_VECTOR3: _on_type_Vector.bind(TYPE_VECTOR3), + TYPE_VECTOR3I: _on_type_Vector.bind(TYPE_VECTOR3I), + TYPE_VECTOR4: _on_type_Vector.bind(TYPE_VECTOR4), + TYPE_VECTOR4I: _on_type_Vector.bind(TYPE_VECTOR4I), + TYPE_RECT2: _on_type_Rect2, + TYPE_RECT2I: _on_type_Rect2i, + TYPE_PLANE: _on_type_Plane, + TYPE_QUATERNION: _on_type_Quaternion, + TYPE_AABB: _on_type_AABB, + TYPE_BASIS: _on_type_Basis, + TYPE_CALLABLE: _on_type_Callable, + TYPE_SIGNAL: _on_type_Signal, + TYPE_TRANSFORM2D: _on_type_Transform2D, + TYPE_TRANSFORM3D: _on_type_Transform3D, + TYPE_PROJECTION: _on_type_Projection, + TYPE_OBJECT: _on_type_Object +} + +static func _regex(pattern: String) -> RegEx: + var regex := RegEx.new() + var err := regex.compile(pattern) + if err != OK: + push_error("error '%s' checked pattern '%s'" % [err, pattern]) + return null + return regex + + +func get_decoder(type: int) -> Callable: + return _decoders.get(type, func(value :Variant) -> String: return '%s' % value) + + +func _on_type_StringName(value: StringName) -> String: + if value.is_empty(): + return 'StringName()' + return 'StringName("%s")' % value + + +func _on_type_Object(value: Variant, _type: int) -> String: + return str(value) + + +func _on_type_Color(color: Color) -> String: + if color == Color.BLACK: + return "Color()" + return "Color%s" % color + + +func _on_type_NodePath(path: NodePath) -> String: + if path.is_empty(): + return 'NodePath()' + return 'NodePath("%s")' % path + + +func _on_type_Callable(_cb: Callable) -> String: + return 'Callable()' + + +func _on_type_Signal(_s: Signal) -> String: + return 'Signal()' + + +func _on_type_Dictionary(dict: Dictionary) -> String: + if dict.is_empty(): + return '{}' + return str(dict) + + +func _on_type_Array(value: Variant, type: int) -> String: + match type: + TYPE_ARRAY: + return str(value) + + TYPE_PACKED_COLOR_ARRAY: + var colors := PackedStringArray() + for color: Color in value: + @warning_ignore("return_value_discarded") + colors.append(_on_type_Color(color)) + if colors.is_empty(): + return "PackedColorArray()" + return "PackedColorArray([%s])" % ", ".join(colors) + + TYPE_PACKED_VECTOR2_ARRAY: + var vectors := PackedStringArray() + for vector: Vector2 in value: + @warning_ignore("return_value_discarded") + vectors.append(_on_type_Vector(vector, TYPE_VECTOR2)) + if vectors.is_empty(): + return "PackedVector2Array()" + return "PackedVector2Array([%s])" % ", ".join(vectors) + + TYPE_PACKED_VECTOR3_ARRAY: + var vectors := PackedStringArray() + for vector: Vector3 in value: + @warning_ignore("return_value_discarded") + vectors.append(_on_type_Vector(vector, TYPE_VECTOR3)) + if vectors.is_empty(): + return "PackedVector3Array()" + return "PackedVector3Array([%s])" % ", ".join(vectors) + + TYPE_PACKED_VECTOR4_ARRAY: + var vectors := PackedStringArray() + for vector: Vector4 in value: + @warning_ignore("return_value_discarded") + vectors.append(_on_type_Vector(vector, TYPE_VECTOR4)) + if vectors.is_empty(): + return "PackedVector4Array()" + return "PackedVector4Array([%s])" % ", ".join(vectors) + + TYPE_PACKED_STRING_ARRAY: + var values := PackedStringArray() + for v: String in value: + @warning_ignore("return_value_discarded") + values.append('"%s"' % v) + if values.is_empty(): + return "PackedStringArray()" + return "PackedStringArray([%s])" % ", ".join(values) + + TYPE_PACKED_BYTE_ARRAY,\ + TYPE_PACKED_FLOAT32_ARRAY,\ + TYPE_PACKED_FLOAT64_ARRAY,\ + TYPE_PACKED_INT32_ARRAY,\ + TYPE_PACKED_INT64_ARRAY: + var vectors := PackedStringArray() + for vector: Variant in value: + @warning_ignore("return_value_discarded") + vectors.append(str(vector)) + if vectors.is_empty(): + return GdObjects.type_as_string(type) + "()" + return "%s([%s])" % [GdObjects.type_as_string(type), ", ".join(vectors)] + return "unknown array type %d" % type + + +func _on_type_Vector(value: Variant, type: int) -> String: + + if typeof(value) != type: + push_error("Internal Error: type missmatch detected for value '%s', expects type %s" % [value, type_string(type)]) + return "" + + match type: + TYPE_VECTOR2: + if value == Vector2(): + return "Vector2()" + return "Vector2%s" % value + TYPE_VECTOR2I: + if value == Vector2i(): + return "Vector2i()" + return "Vector2i%s" % value + TYPE_VECTOR3: + if value == Vector3(): + return "Vector3()" + return "Vector3%s" % value + TYPE_VECTOR3I: + if value == Vector3i(): + return "Vector3i()" + return "Vector3i%s" % value + TYPE_VECTOR4: + if value == Vector4(): + return "Vector4()" + return "Vector4%s" % value + TYPE_VECTOR4I: + if value == Vector4i(): + return "Vector4i()" + return "Vector4i%s" % value + return "unknown vector type %d" % type + + +func _on_type_Transform2D(transform: Transform2D) -> String: + if transform == Transform2D(): + return "Transform2D()" + return "Transform2D(Vector2%s, Vector2%s, Vector2%s)" % [transform.x, transform.y, transform.origin] + + +func _on_type_Transform3D(transform: Transform3D) -> String: + if transform == Transform3D(): + return "Transform3D()" + return "Transform3D(Vector3%s, Vector3%s, Vector3%s, Vector3%s)" % [transform.basis.x, transform.basis.y, transform.basis.z, transform.origin] + + +func _on_type_Projection(projection: Projection) -> String: + return "Projection(Vector4%s, Vector4%s, Vector4%s, Vector4%s)" % [projection.x, projection.y, projection.z, projection.w] + + +@warning_ignore("unused_parameter") +func _on_type_RID(value: RID) -> String: + return "RID()" + + +func _on_type_Rect2(rect: Rect2) -> String: + if rect == Rect2(): + return "Rect2()" + return "Rect2(Vector2%s, Vector2%s)" % [rect.position, rect.size] + + +func _on_type_Rect2i(rect: Variant) -> String: + if rect == Rect2i(): + return "Rect2i()" + return "Rect2i(Vector2i%s, Vector2i%s)" % [rect.position, rect.size] + + +func _on_type_Plane(plane: Plane) -> String: + if plane == Plane(): + return "Plane()" + return "Plane(%d, %d, %d, %d)" % [plane.x, plane.y, plane.z, plane.d] + + +func _on_type_Quaternion(quaternion: Quaternion) -> String: + if quaternion == Quaternion(): + return "Quaternion()" + return "Quaternion(%d, %d, %d, %d)" % [quaternion.x, quaternion.y, quaternion.z, quaternion.w] + + +func _on_type_AABB(aabb: AABB) -> String: + if aabb == AABB(): + return "AABB()" + return "AABB(Vector3%s, Vector3%s)" % [aabb.position, aabb.size] + + +func _on_type_Basis(basis: Basis) -> String: + if basis == Basis(): + return "Basis()" + return "Basis(Vector3%s, Vector3%s, Vector3%s)" % [basis.x, basis.y, basis.z] + + +static func decode(value: Variant) -> String: + var type := typeof(value) + @warning_ignore("unsafe_cast") + if GdArrayTools.is_type_array(type) and (value as Array).is_empty(): + return "" + # For Variant types we need to determine the original type + if type == GdObjects.TYPE_VARIANT: + type = typeof(value) + var decoder := _get_value_decoder(type) + if decoder == null: + push_error("No value decoder registered for type '%d'! Please open a Bug issue at 'https://github.com/MikeSchulze/gdUnit4/issues/new/choose'." % type) + return "null" + if type == TYPE_OBJECT: + return decoder.call(value, type) + return decoder.call(value) + + +static func decode_typed(type: int, value: Variant) -> String: + if value == null: + return "null" + # For Variant types we need to determine the original type + if type == GdObjects.TYPE_VARIANT: + type = typeof(value) + var decoder := _get_value_decoder(type) + if decoder == null: + push_error("No value decoder registered for type '%d'! Please open a Bug issue at 'https://github.com/MikeSchulze/gdUnit4/issues/new/choose'." % type) + return "null" + if type == TYPE_OBJECT: + return decoder.call(value, type) + return decoder.call(value) + + +static func _get_value_decoder(type: int) -> Callable: + var decoder: GdDefaultValueDecoder = instance( + "GdUnitDefaultValueDecoders", + func() -> GdDefaultValueDecoder: + return GdDefaultValueDecoder.new()) + return decoder.get_decoder(type) diff --git a/addons/gdUnit4/src/core/parse/GdDefaultValueDecoder.gd.uid b/addons/gdUnit4/src/core/parse/GdDefaultValueDecoder.gd.uid new file mode 100644 index 0000000..1510f9d --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdDefaultValueDecoder.gd.uid @@ -0,0 +1 @@ +uid://bvq0bv1bg8m5f diff --git a/addons/gdUnit4/src/core/parse/GdFunctionArgument.gd b/addons/gdUnit4/src/core/parse/GdFunctionArgument.gd new file mode 100644 index 0000000..fdc1c43 --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdFunctionArgument.gd @@ -0,0 +1,208 @@ +class_name GdFunctionArgument +extends RefCounted + + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") +const UNDEFINED: String = "<-NO_ARG->" +const ARG_PARAMETERIZED_TEST := "test_parameters" + +static var _fuzzer_regex: RegEx +static var _cleanup_leading_spaces: RegEx +static var _fix_comma_space: RegEx + +var _name: String +var _type: int +var _type_hint: int +var _default_value: Variant +var _parameter_sets: PackedStringArray = [] + + +func _init(p_name: String, p_type: int, value: Variant = UNDEFINED, p_type_hint: int = TYPE_NIL) -> void: + _init_static_variables() + _name = p_name + _type = p_type + _type_hint = p_type_hint + if value != null and p_name == ARG_PARAMETERIZED_TEST: + _parameter_sets = _parse_parameter_set(str(value)) + _default_value = value + # is argument a fuzzer? + if _type == TYPE_OBJECT and _fuzzer_regex.search(_name): + _type = GdObjects.TYPE_FUZZER + + +func _init_static_variables() -> void: + if _fuzzer_regex == null: + _fuzzer_regex = GdUnitTools.to_regex("((?!(fuzzer_(seed|iterations)))fuzzer?\\w+)( ?+= ?+| ?+:= ?+| ?+:Fuzzer ?+= ?+|)") + _cleanup_leading_spaces = RegEx.create_from_string("(?m)^[ \t]+") + _fix_comma_space = RegEx.create_from_string(""", {0,}\t{0,}(?=(?:[^"]*"[^"]*")*[^"]*$)(?!\\s)""") + + +func name() -> String: + return _name + + +func default() -> Variant: + return type_convert(_default_value, _type) + + +func set_value(value: String) -> void: + # we onle need to apply default values for Objects, all others are provided by the method descriptor + if _type == GdObjects.TYPE_FUZZER: + _default_value = value + return + if _name == ARG_PARAMETERIZED_TEST: + _parameter_sets = _parse_parameter_set(value) + _default_value = value + return + + if _type == TYPE_NIL or _type == GdObjects.TYPE_VARIANT: + _type = _extract_value_type(value) + if _type == GdObjects.TYPE_VARIANT and _default_value == null: + _default_value = value + if _default_value == null: + match _type: + TYPE_DICTIONARY: + _default_value = as_dictionary(value) + TYPE_ARRAY: + _default_value = as_array(value) + GdObjects.TYPE_FUZZER: + _default_value = value + _: + _default_value = str_to_var(value) + # if converting fails assign the original value without converting + if _default_value == null and value != null: + _default_value = value + #prints("set default_value: ", _default_value, "with type %d" % _type, " from original: '%s'" % value) + + +func _extract_value_type(value: String) -> int: + if value != UNDEFINED: + if _fuzzer_regex.search(_name): + return GdObjects.TYPE_FUZZER + if value.rfind(")") == value.length()-1: + return GdObjects.TYPE_FUNC + return _type + + +func value_as_string() -> String: + if has_default(): + return GdDefaultValueDecoder.decode_typed(_type, _default_value) + return "" + + +func plain_value() -> Variant: + return _default_value + + +func type() -> int: + return _type + + +func type_hint() -> int: + return _type_hint + + +func has_default() -> bool: + return not is_same(_default_value, UNDEFINED) + + +func is_typed_array() -> bool: + return _type == TYPE_ARRAY and _type_hint != TYPE_NIL + + +func is_parameter_set() -> bool: + return _name == ARG_PARAMETERIZED_TEST + + +func parameter_sets() -> PackedStringArray: + return _parameter_sets + + +static func get_parameter_set(parameters :Array[GdFunctionArgument]) -> GdFunctionArgument: + for current in parameters: + if current != null and current.is_parameter_set(): + return current + return null + + +func _to_string() -> String: + var s := _name + if _type != TYPE_NIL: + s += ": " + GdObjects.type_as_string(_type) + if _type_hint != TYPE_NIL: + s += "[%s]" % GdObjects.type_as_string(_type_hint) + if has_default(): + s += "=" + value_as_string() + return s + + +func _parse_parameter_set(input :String) -> PackedStringArray: + if not input.contains("["): + return [] + + input = _cleanup_leading_spaces.sub(input, "", true) + input = input.replace("\n", "").strip_edges().trim_prefix("[").trim_suffix("]").trim_prefix("]") + var single_quote := false + var double_quote := false + var array_end := 0 + var current_index := 0 + var output :PackedStringArray = [] + var buf := input.to_utf8_buffer() + var collected_characters: = PackedByteArray() + var matched :bool = false + + for c in buf: + current_index += 1 + matched = current_index == buf.size() + @warning_ignore("return_value_discarded") + collected_characters.push_back(c) + + match c: + # ' ': ignore spaces between array elements + 32: if array_end == 0 and (not double_quote and not single_quote): + collected_characters.remove_at(collected_characters.size()-1) + # ',': step over array element seperator ',' + 44: if array_end == 0: + matched = true + collected_characters.remove_at(collected_characters.size()-1) + # '`': + 39: single_quote = !single_quote + # '"': + 34: if not single_quote: double_quote = !double_quote + # '[' + 91: if not double_quote and not single_quote: array_end +=1 # counts array open + # ']' + 93: if not double_quote and not single_quote: array_end -=1 # counts array closed + + # if array closed than collect the element + if matched: + var parameters := _fix_comma_space.sub(collected_characters.get_string_from_utf8(), ", ", true) + if not parameters.is_empty(): + @warning_ignore("return_value_discarded") + output.append(parameters) + collected_characters.clear() + matched = false + return output + + +## value converters + +func as_array(value: String) -> Array: + if value == "Array()" or value == "[]": + return [] + + if value.begins_with("Array("): + value = value.lstrip("Array(").rstrip(")") + if value.begins_with("["): + return str_to_var(value) + return [] + + +func as_dictionary(value: String) -> Dictionary: + if value == "Dictionary()": + return {} + if value.begins_with("Dictionary("): + value = value.lstrip("Dictionary(").rstrip(")") + if value.begins_with("{"): + return str_to_var(value) + return {} diff --git a/addons/gdUnit4/src/core/parse/GdFunctionArgument.gd.uid b/addons/gdUnit4/src/core/parse/GdFunctionArgument.gd.uid new file mode 100644 index 0000000..65c1e8d --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdFunctionArgument.gd.uid @@ -0,0 +1 @@ +uid://v7mgo6qqnmru diff --git a/addons/gdUnit4/src/core/parse/GdFunctionDescriptor.gd b/addons/gdUnit4/src/core/parse/GdFunctionDescriptor.gd new file mode 100644 index 0000000..acfada7 --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdFunctionDescriptor.gd @@ -0,0 +1,286 @@ +class_name GdFunctionDescriptor +extends RefCounted + +var _is_virtual :bool +var _is_static :bool +var _is_engine :bool +var _is_coroutine :bool +var _name :String +var _source_path: String +var _line_number :int +var _return_type :int +var _return_class :String +var _args : Array[GdFunctionArgument] +var _varargs :Array[GdFunctionArgument] + + + +static func create(p_name: String, p_source_path: String, p_source_line: int, p_return_type: int, p_args: Array[GdFunctionArgument] = []) -> GdFunctionDescriptor: + var fd := GdFunctionDescriptor.new(p_name, p_source_line, false, false, false, p_return_type, "", p_args) + fd.enrich_file_info(p_source_path, p_source_line) + return fd + +static func create_static(p_name: String, p_source_path: String, p_source_line: int, p_return_type: int, p_args: Array[GdFunctionArgument] = []) -> GdFunctionDescriptor: + var fd := GdFunctionDescriptor.new(p_name, p_source_line, false, true, false, p_return_type, "", p_args) + fd.enrich_file_info(p_source_path, p_source_line) + return fd + + +func _init(p_name :String, + p_line_number :int, + p_is_virtual :bool, + p_is_static :bool, + p_is_engine :bool, + p_return_type :int, + p_return_class :String, + p_args : Array[GdFunctionArgument], + p_varargs :Array[GdFunctionArgument] = []) -> void: + _name = p_name + _line_number = p_line_number + _return_type = p_return_type + _return_class = p_return_class + _is_virtual = p_is_virtual + _is_static = p_is_static + _is_engine = p_is_engine + _is_coroutine = false + _args = p_args + _varargs = p_varargs + + +func with_return_class(clazz_name: String) -> GdFunctionDescriptor: + _return_class = clazz_name + return self + + +func name() -> String: + return _name + + +func source_path() -> String: + return _source_path + + +func line_number() -> int: + return _line_number + + +func is_virtual() -> bool: + return _is_virtual + + +func is_static() -> bool: + return _is_static + + +func is_engine() -> bool: + return _is_engine + + +func is_vararg() -> bool: + return not _varargs.is_empty() + + +func is_coroutine() -> bool: + return _is_coroutine + + +func is_parameterized() -> bool: + for current in _args: + var arg :GdFunctionArgument = current + if arg.name() == GdFunctionArgument.ARG_PARAMETERIZED_TEST: + return true + return false + + +func is_private() -> bool: + return name().begins_with("_") and not is_virtual() + + +func return_type() -> int: + return _return_type + + +func return_type_as_string() -> String: + if return_type() == TYPE_NIL: + return "void" + if (return_type() == TYPE_OBJECT or return_type() == GdObjects.TYPE_ENUM) and not _return_class.is_empty(): + return _return_class + return GdObjects.type_as_string(return_type()) + + +func set_argument_value(arg_name: String, value: String) -> void: + var argument: GdFunctionArgument = _args.filter(func(arg: GdFunctionArgument) -> bool: + return arg.name() == arg_name + ).front() + if argument != null: + argument.set_value(value) + + +func enrich_arguments(arguments: Array[Dictionary]) -> void: + for arg_index: int in arguments.size(): + var arg: Dictionary = arguments[arg_index] + if arg["type"] != GdObjects.TYPE_VARARG: + var arg_name: String = arg["name"] + var arg_value: String = arg["value"] + set_argument_value(arg_name, arg_value) + + +func enrich_file_info(p_source_path: String, p_line_number: int) -> void: + _source_path = p_source_path + _line_number = p_line_number + + +func args() -> Array[GdFunctionArgument]: + return _args + + +func varargs() -> Array[GdFunctionArgument]: + return _varargs + + +func typed_args() -> String: + var collect := PackedStringArray() + for arg in args(): + @warning_ignore("return_value_discarded") + collect.push_back(arg._to_string()) + for arg in varargs(): + @warning_ignore("return_value_discarded") + collect.push_back(arg._to_string()) + return ", ".join(collect) + + +func _to_string() -> String: + var fsignature := "virtual " if is_virtual() else "" + if _return_type == TYPE_NIL: + return fsignature + "[Line:%s] func %s(%s):" % [line_number(), name(), typed_args()] + var func_template := fsignature + "[Line:%s] func %s(%s) -> %s:" + if is_static(): + func_template= "[Line:%s] static func %s(%s) -> %s:" + return func_template % [line_number(), name(), typed_args(), return_type_as_string()] + + +# extract function description given by Object.get_method_list() +static func extract_from(descriptor :Dictionary, is_engine_ := true) -> GdFunctionDescriptor: + var func_name: String = descriptor["name"] + var function_flags: int = descriptor["flags"] + var return_descriptor: Dictionary = descriptor["return"] + var clazz_name: String = return_descriptor["class_name"] + var is_virtual_: bool = function_flags & METHOD_FLAG_VIRTUAL + var is_static_: bool = function_flags & METHOD_FLAG_STATIC + var is_vararg_: bool = function_flags & METHOD_FLAG_VARARG + + return GdFunctionDescriptor.new( + func_name, + -1, + is_virtual_, + is_static_, + is_engine_, + _extract_return_type(return_descriptor), + clazz_name, + _extract_args(descriptor), + _build_varargs(is_vararg_) + ) + +# temporary exclude GlobalScope enums +const enum_fix := [ + "Side", + "Corner", + "Orientation", + "ClockDirection", + "HorizontalAlignment", + "VerticalAlignment", + "InlineAlignment", + "EulerOrder", + "Error", + "Key", + "MIDIMessage", + "MouseButton", + "MouseButtonMask", + "JoyButton", + "JoyAxis", + "PropertyHint", + "PropertyUsageFlags", + "MethodFlags", + "Variant.Type", + "Control.LayoutMode"] + + +static func _extract_return_type(return_info :Dictionary) -> int: + var type :int = return_info["type"] + var usage :int = return_info["usage"] + if type == TYPE_INT and usage & PROPERTY_USAGE_CLASS_IS_ENUM: + return GdObjects.TYPE_ENUM + if type == TYPE_NIL and usage & PROPERTY_USAGE_NIL_IS_VARIANT: + return GdObjects.TYPE_VARIANT + if type == TYPE_NIL and usage == 6: + return GdObjects.TYPE_VOID + return type + + +static func _extract_args(descriptor :Dictionary) -> Array[GdFunctionArgument]: + var args_ :Array[GdFunctionArgument] = [] + var arguments :Array = descriptor["args"] + var defaults :Array = descriptor["default_args"] + # iterate backwards because the default values are stored from right to left + while not arguments.is_empty(): + var arg :Dictionary = arguments.pop_back() + var arg_name := _argument_name(arg) + var arg_type := _argument_type(arg) + var arg_type_hint := _argument_hint(arg) + #var arg_class: StringName = arg["class_name"] + var default_value: Variant = GdFunctionArgument.UNDEFINED if defaults.is_empty() else defaults.pop_back() + args_.push_front(GdFunctionArgument.new(arg_name, arg_type, default_value, arg_type_hint)) + return args_ + + +static func _build_varargs(p_is_vararg :bool) -> Array[GdFunctionArgument]: + var varargs_ :Array[GdFunctionArgument] = [] + if not p_is_vararg: + return varargs_ + varargs_.push_back(GdFunctionArgument.new("varargs", GdObjects.TYPE_VARARG, '')) + return varargs_ + + +static func _argument_name(arg :Dictionary) -> String: + return arg["name"] + + +static func _argument_type(arg :Dictionary) -> int: + var type :int = arg["type"] + var usage :int = arg["usage"] + + if type == TYPE_OBJECT: + if arg["class_name"] == "Node": + return GdObjects.TYPE_NODE + if arg["class_name"] == "Fuzzer": + return GdObjects.TYPE_FUZZER + + # if the argument untyped we need to scan the assignef value type + if type == TYPE_NIL and usage == PROPERTY_USAGE_NIL_IS_VARIANT: + return GdObjects.TYPE_VARIANT + return type + + +static func _argument_hint(arg :Dictionary) -> int: + var hint :int = arg["hint"] + var hint_string :String = arg["hint_string"] + + match hint: + PROPERTY_HINT_ARRAY_TYPE: + return GdObjects.string_to_type(hint_string) + _: + return 0 + + +static func _argument_type_as_string(arg :Dictionary) -> String: + var type := _argument_type(arg) + match type: + TYPE_NIL: + return "" + TYPE_OBJECT: + var clazz_name :String = arg["class_name"] + if not clazz_name.is_empty(): + return clazz_name + return "" + _: + return GdObjects.type_as_string(type) diff --git a/addons/gdUnit4/src/core/parse/GdFunctionDescriptor.gd.uid b/addons/gdUnit4/src/core/parse/GdFunctionDescriptor.gd.uid new file mode 100644 index 0000000..7b8ebf3 --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdFunctionDescriptor.gd.uid @@ -0,0 +1 @@ +uid://d1s705d1jgmrc diff --git a/addons/gdUnit4/src/core/parse/GdFunctionParameterSetResolver.gd b/addons/gdUnit4/src/core/parse/GdFunctionParameterSetResolver.gd new file mode 100644 index 0000000..9c45e62 --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdFunctionParameterSetResolver.gd @@ -0,0 +1,188 @@ +class_name GdFunctionParameterSetResolver +extends RefCounted + +const CLASS_TEMPLATE = """ +class_name _ParameterExtractor extends '${clazz_path}' + +func __extract_test_parameters() -> Array: + return ${test_params} + +""" + +const EXCLUDE_PROPERTIES_TO_COPY = [ + "script", + "type", + "Node", + "_import_path"] + + +var _fd: GdFunctionDescriptor +var _static_sets_by_index := {} +var _is_static := true + +func _init(fd: GdFunctionDescriptor) -> void: + _fd = fd + + +func resolve_test_cases(script: GDScript) -> Array[GdUnitTestCase]: + if not is_parameterized(): + return [GdUnitTestCase.from(script.resource_path, _fd.source_path(), _fd.line_number(), _fd.name())] + return extract_test_cases_by_reflection(script) + + +func is_parameterized() -> bool: + return _fd.is_parameterized() + + +func is_parameter_sets_static() -> bool: + return _is_static + + +func is_parameter_set_static(index: int) -> bool: + return _is_static and _static_sets_by_index.get(index, false) + + +# validates the given arguments are complete and matches to required input fields of the test function +func validate(input_value_set: Array) -> String: + var input_arguments := _fd.args() + # check given parameter set with test case arguments + var expected_arg_count := input_arguments.size() - 1 + for input_values :Variant in input_value_set: + var parameter_set_index := input_value_set.find(input_values) + if input_values is Array: + var arr_values: Array = input_values + var current_arg_count := arr_values.size() + if current_arg_count != expected_arg_count: + return "\n The parameter set at index [%d] does not match the expected input parameters!\n The test case requires [%d] input parameters, but the set contains [%d]" % [parameter_set_index, expected_arg_count, current_arg_count] + var error := validate_parameter_types(input_arguments, arr_values, parameter_set_index) + if not error.is_empty(): + return error + else: + return "\n The parameter set at index [%d] does not match the expected input parameters!\n Expecting an array of input values." % parameter_set_index + return "" + + +static func validate_parameter_types(input_arguments: Array, input_values: Array, parameter_set_index: int) -> String: + for i in input_arguments.size(): + var input_param: GdFunctionArgument = input_arguments[i] + # only check the test input arguments + if input_param.is_parameter_set(): + continue + var input_param_type := input_param.type() + var input_value :Variant = input_values[i] + var input_value_type := typeof(input_value) + # input parameter is not typed or is Variant we skip the type test + if input_param_type == TYPE_NIL or input_param_type == GdObjects.TYPE_VARIANT: + continue + # is input type enum allow int values + if input_param_type == GdObjects.TYPE_VARIANT and input_value_type == TYPE_INT: + continue + # allow only equal types and object == null + if input_param_type == TYPE_OBJECT and input_value_type == TYPE_NIL: + continue + if input_param_type != input_value_type: + return "\n The parameter set at index [%d] does not match the expected input parameters!\n The value '%s' does not match the required input parameter <%s>." % [parameter_set_index, input_value, input_param] + return "" + + +func extract_test_cases_by_reflection(script: GDScript) -> Array[GdUnitTestCase]: + var source: Node = script.new() + source.queue_free() + + var fa := GdFunctionArgument.get_parameter_set(_fd.args()) + var parameter_sets := fa.parameter_sets() + # if no parameter set detected we need to resolve it by using reflection + if parameter_sets.size() == 0: + _is_static = false + return _extract_test_cases_by_reflection(source, script) + else: + var test_cases: Array[GdUnitTestCase] = [] + var property_names := _extract_property_names(source) + for parameter_set_index in parameter_sets.size(): + var parameter_set := parameter_sets[parameter_set_index] + _static_sets_by_index[parameter_set_index] = _is_static_parameter_set(parameter_set, property_names) + @warning_ignore("return_value_discarded") + test_cases.append(GdUnitTestCase.from(script.resource_path, _fd.source_path(), _fd.line_number(), _fd.name(), parameter_set_index, parameter_set)) + parameter_set_index += 1 + return test_cases + + +func _extract_property_names(source: Node) -> PackedStringArray: + return source.get_property_list()\ + .map(func(property :Dictionary) -> String: return property["name"])\ + .filter(func(property :String) -> bool: return !EXCLUDE_PROPERTIES_TO_COPY.has(property)) + + +# tests if the test property set contains an property reference by name, if not the parameter set holds only static values +func _is_static_parameter_set(parameters :String, property_names :PackedStringArray) -> bool: + for property_name in property_names: + if parameters.contains(property_name): + _is_static = false + return false + return true + + +func _extract_test_cases_by_reflection(source: Node, script: GDScript) -> Array[GdUnitTestCase]: + var parameter_sets := load_parameter_sets(source) + var test_cases: Array[GdUnitTestCase] = [] + for index in parameter_sets.size(): + var parameter_set := str(parameter_sets[index]) + @warning_ignore("return_value_discarded") + test_cases.append(GdUnitTestCase.from(script.resource_path, _fd.source_path(), _fd.line_number(), _fd.name(), index, parameter_set)) + return test_cases + + +# extracts the arguments from the given test case, using kind of reflection solution +# to restore the parameters from a string representation to real instance type +func load_parameter_sets(source: Node) -> Array: + var source_script: GDScript = source.get_script() + var parameter_arg := GdFunctionArgument.get_parameter_set(_fd.args()) + var source_code := CLASS_TEMPLATE \ + .replace("${clazz_path}", source_script.resource_path) \ + .replace("${test_params}", parameter_arg.value_as_string()) + var script := GDScript.new() + script.source_code = source_code + # enable this lines only for debuging + #script.resource_path = GdUnitFileAccess.create_temp_dir("parameter_extract") + "/%s__.gd" % test_case.get_name() + #DirAccess.remove_absolute(script.resource_path) + #ResourceSaver.save(script, script.resource_path) + var result := script.reload() + if result != OK: + push_error("Extracting test parameters failed! Script loading error: %s" % result) + return [] + var instance: Node = script.new() + GdFunctionParameterSetResolver.copy_properties(source, instance) + instance.queue_free() + var parameter_sets: Array = instance.call("__extract_test_parameters") + return fixure_typed_parameters(parameter_sets, _fd.args()) + + +func fixure_typed_parameters(parameter_sets: Array, arg_descriptors: Array[GdFunctionArgument]) -> Array: + for parameter_set_index in parameter_sets.size(): + var parameter_set: Array = parameter_sets[parameter_set_index] + # run over all function arguments + for parameter_index in parameter_set.size(): + var parameter :Variant = parameter_set[parameter_index] + var arg_descriptor: GdFunctionArgument = arg_descriptors[parameter_index] + if parameter is Array: + var as_array: Array = parameter + # we need to convert the untyped array to the expected typed version + if arg_descriptor.is_typed_array(): + parameter_set[parameter_index] = Array(as_array, arg_descriptor.type_hint(), "", null) + return parameter_sets + + +static func copy_properties(source: Object, dest: Object) -> void: + for property in source.get_property_list(): + var property_name :String = property["name"] + var property_value :Variant = source.get(property_name) + if EXCLUDE_PROPERTIES_TO_COPY.has(property_name): + continue + #if dest.get(property_name) == null: + # prints("|%s|" % property_name, source.get(property_name)) + + # check for invalid name property + if property_name == "name" and property_value == "": + dest.set(property_name, ""); + continue + dest.set(property_name, property_value) diff --git a/addons/gdUnit4/src/core/parse/GdFunctionParameterSetResolver.gd.uid b/addons/gdUnit4/src/core/parse/GdFunctionParameterSetResolver.gd.uid new file mode 100644 index 0000000..2e22fd5 --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdFunctionParameterSetResolver.gd.uid @@ -0,0 +1 @@ +uid://d3gni2yikju4m diff --git a/addons/gdUnit4/src/core/parse/GdScriptParser.gd b/addons/gdUnit4/src/core/parse/GdScriptParser.gd new file mode 100644 index 0000000..16f54cc --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdScriptParser.gd @@ -0,0 +1,786 @@ +class_name GdScriptParser +extends RefCounted + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") + +const TYPE_VOID = GdObjects.TYPE_VOID +const TYPE_VARIANT = GdObjects.TYPE_VARIANT +const TYPE_VARARG = GdObjects.TYPE_VARARG +const TYPE_FUNC = GdObjects.TYPE_FUNC +const TYPE_FUZZER = GdObjects.TYPE_FUZZER +const TYPE_ENUM = GdObjects.TYPE_ENUM + + +var TOKEN_NOT_MATCH := Token.new("") +var TOKEN_SPACE := SkippableToken.new(" ") +var TOKEN_TABULATOR := SkippableToken.new("\t") +var TOKEN_NEW_LINE := SkippableToken.new("\n") +var TOKEN_COMMENT := SkippableToken.new("#") +var TOKEN_CLASS_NAME := Token.new("class_name") +var TOKEN_INNER_CLASS := Token.new("class") +var TOKEN_EXTENDS := Token.new("extends") +var TOKEN_ENUM := Token.new("enum") +var TOKEN_FUNCTION_STATIC_DECLARATION := Token.new("static func") +var TOKEN_FUNCTION_DECLARATION := Token.new("func") +var TOKEN_FUNCTION := Token.new(".") +var TOKEN_FUNCTION_RETURN_TYPE := Token.new("->") +var TOKEN_FUNCTION_END := Token.new("):") +var TOKEN_ARGUMENT_ASIGNMENT := Token.new("=") +var TOKEN_ARGUMENT_TYPE_ASIGNMENT := Token.new(":=") +var TOKEN_ARGUMENT_FUZZER := FuzzerToken.new(GdUnitTools.to_regex("((?!(fuzzer_(seed|iterations)))fuzzer?\\w+)( ?+= ?+| ?+:= ?+| ?+:Fuzzer ?+= ?+|)")) +var TOKEN_ARGUMENT_TYPE := Token.new(":") +var TOKEN_ARGUMENT_VARIADIC := Token.new("...") +var TOKEN_ARGUMENT_SEPARATOR := Token.new(",") +var TOKEN_BRACKET_ROUND_OPEN := Token.new("(") +var TOKEN_BRACKET_ROUND_CLOSE := Token.new(")") +var TOKEN_BRACKET_SQUARE_OPEN := Token.new("[") +var TOKEN_BRACKET_SQUARE_CLOSE := Token.new("]") +var TOKEN_BRACKET_CURLY_OPEN := Token.new("{") +var TOKEN_BRACKET_CURLY_CLOSE := Token.new("}") + + + +var OPERATOR_ADD := Operator.new("+") +var OPERATOR_SUB := Operator.new("-") +var OPERATOR_MUL := Operator.new("*") +var OPERATOR_DIV := Operator.new("/") +var OPERATOR_REMAINDER := Operator.new("%") + +var TOKENS :Array[Token] = [ + TOKEN_SPACE, + TOKEN_TABULATOR, + TOKEN_NEW_LINE, + TOKEN_COMMENT, + TOKEN_BRACKET_ROUND_OPEN, + TOKEN_BRACKET_ROUND_CLOSE, + TOKEN_BRACKET_SQUARE_OPEN, + TOKEN_BRACKET_SQUARE_CLOSE, + TOKEN_BRACKET_CURLY_OPEN, + TOKEN_BRACKET_CURLY_CLOSE, + TOKEN_CLASS_NAME, + TOKEN_INNER_CLASS, + TOKEN_EXTENDS, + TOKEN_ENUM, + TOKEN_FUNCTION_STATIC_DECLARATION, + TOKEN_FUNCTION_DECLARATION, + TOKEN_ARGUMENT_FUZZER, + TOKEN_ARGUMENT_TYPE_ASIGNMENT, + TOKEN_ARGUMENT_ASIGNMENT, + TOKEN_ARGUMENT_TYPE, + TOKEN_ARGUMENT_VARIADIC, + TOKEN_FUNCTION, + TOKEN_ARGUMENT_SEPARATOR, + TOKEN_FUNCTION_RETURN_TYPE, + OPERATOR_ADD, + OPERATOR_SUB, + OPERATOR_MUL, + OPERATOR_DIV, + OPERATOR_REMAINDER, +] + +var _regex_clazz_name := GdUnitTools.to_regex("(class) ([a-zA-Z0-9_]+) (extends[a-zA-Z]+:)|(class) ([a-zA-Z0-9_]+)") +var _regex_func_name := GdUnitTools.to_regex("^(?:static\\s+)?func\\s+([\\w\\p{L}\\p{N}_]+)\\s*\\(") +var _regex_strip_comments := GdUnitTools.to_regex("^([^#\"']|'[^']*'|\"[^\"]*\")*\\K#.*") +var _scanned_inner_classes := PackedStringArray() +var _script_constants := {} +var _is_awaiting := GdUnitTools.to_regex("\\bawait\\s+(?![^\"]*\"[^\"]*$)(?!.*#.*await)") + + +static func to_unix_format(input :String) -> String: + return input.replace("\r\n", "\n") + + +class Token extends RefCounted: + var _token: String + var _consumed: int + var _is_operator: bool + var _regex :RegEx + + + func _init(p_token: String, p_is_operator := false, p_regex :RegEx = null) -> void: + _token = p_token + _is_operator = p_is_operator + _consumed = p_token.length() + _regex = p_regex + + func match(input: String, pos: int) -> bool: + if _regex: + var result := _regex.search(input, pos) + if result == null: + return false + _consumed = result.get_end() - result.get_start() + return pos == result.get_start() + return input.findn(_token, pos) == pos + + func is_operator() -> bool: + return _is_operator + + func is_inner_class() -> bool: + return _token == "class" + + func is_variable() -> bool: + return false + + func is_token(token_name :String) -> bool: + return _token == token_name + + func is_skippable() -> bool: + return false + + func _to_string() -> String: + return "Token{" + _token + "}" + + +class Operator extends Token: + func _init(value: String) -> void: + super(value, true) + + func _to_string() -> String: + return "OperatorToken{%s}" % [_token] + + +# A skippable token, is just a placeholder like space or tabs +class SkippableToken extends Token: + + func _init(p_token: String) -> void: + super(p_token) + + func is_skippable() -> bool: + return true + + +# Token to parse Fuzzers +class FuzzerToken extends Token: + var _name: String + + + func _init(regex: RegEx) -> void: + super("", false, regex) + + + func match(input: String, pos: int) -> bool: + if _regex: + var result := _regex.search(input, pos) + if result == null: + return false + _name = result.strings[1] + _consumed = result.get_end() - result.get_start() + return pos == result.get_start() + return input.findn(_token, pos) == pos + + + func name() -> String: + return _name + + + func type() -> int: + return GdObjects.TYPE_FUZZER + + + func _to_string() -> String: + return "FuzzerToken{%s: '%s'}" % [_name, _token] + + +# Token to parse function arguments +class Variable extends Token: + var _plain_value :String + var _typed_value :Variant + var _type :int = TYPE_NIL + + + func _init(p_value: String) -> void: + super(p_value) + _type = _scan_type(p_value) + _plain_value = p_value + _typed_value = _cast_to_type(p_value, _type) + + + func _scan_type(p_value: String) -> int: + if p_value.begins_with("\"") and p_value.ends_with("\""): + return TYPE_STRING + var type_ := GdObjects.string_to_type(p_value) + if type_ != TYPE_NIL: + return type_ + if p_value.is_valid_int(): + return TYPE_INT + if p_value.is_valid_float(): + return TYPE_FLOAT + if p_value.is_valid_hex_number(): + return TYPE_INT + return TYPE_OBJECT + + + func _cast_to_type(p_value :String, p_type: int) -> Variant: + match p_type: + TYPE_STRING: + return p_value#.substr(1, p_value.length() - 2) + TYPE_INT: + return p_value.to_int() + TYPE_FLOAT: + return p_value.to_float() + return p_value + + + func is_variable() -> bool: + return true + + + func type() -> int: + return _type + + + func value() -> Variant: + return _typed_value + + + func plain_value() -> String: + return _plain_value + + + func _to_string() -> String: + return "Variable{%s: %s : '%s'}" % [_plain_value, GdObjects.type_as_string(_type), _token] + + +class TokenInnerClass extends Token: + var _clazz_name :String + var _content := PackedStringArray() + + + static func _strip_leading_spaces(input :String) -> String: + var characters := input.to_utf8_buffer() + while not characters.is_empty(): + if characters[0] != 0x20: + break + characters.remove_at(0) + return characters.get_string_from_utf8() + + + static func _consumed_bytes(row :String) -> int: + return row.replace(" ", "").replace(" ", "").length() + + + func _init(clazz_name :String) -> void: + super("class") + _clazz_name = clazz_name + + + func is_class_name(clazz_name :String) -> bool: + return _clazz_name == clazz_name + + + func content() -> PackedStringArray: + return _content + + + func parse(source_rows :PackedStringArray, offset :int) -> void: + # add class signature + @warning_ignore("return_value_discarded") + _content.append(source_rows[offset]) + # parse class content + for row_index in range(offset+1, source_rows.size()): + # scan until next non tab + var source_row := source_rows[row_index] + var row := TokenInnerClass._strip_leading_spaces(source_row) + if row.is_empty() or row.begins_with("\t") or row.begins_with("#"): + # fold all line to left by removing leading tabs and spaces + if source_row.begins_with("\t"): + source_row = source_row.trim_prefix("\t") + # refomat invalid empty lines + if source_row.dedent().is_empty(): + @warning_ignore("return_value_discarded") + _content.append("") + else: + @warning_ignore("return_value_discarded") + _content.append(source_row) + continue + break + _consumed += TokenInnerClass._consumed_bytes("".join(_content)) + + + func _to_string() -> String: + return "TokenInnerClass{%s}" % [_clazz_name] + + + +func get_token(input :String, current_index :int) -> Token: + for t in TOKENS: + if t.match(input, current_index): + return t + return TOKEN_NOT_MATCH + + +func next_token(input: String, current_index: int, ignore_tokens :Array[Token] = []) -> Token: + var token := TOKEN_NOT_MATCH + for t :Token in TOKENS.filter(func(t :Token) -> bool: return not ignore_tokens.has(t)): + + if t.match(input, current_index): + token = t + break + if token == OPERATOR_SUB: + token = tokenize_value(input, current_index, token) + if token == TOKEN_INNER_CLASS: + token = tokenize_inner_class(input, current_index, token) + if token == TOKEN_NOT_MATCH: + return tokenize_value(input, current_index, token, ignore_tokens.has(TOKEN_FUNCTION)) + return token + + +func tokenize_value(input: String, current: int, token: Token, ignore_dots := false) -> Token: + var next := 0 + var current_token := "" + # test for '--', '+-', '*-', '/-', '%-', or at least '-x' + var test_for_sign := (token == null or token.is_operator()) and input[current] == "-" + while current + next < len(input): + var character := input[current + next] as String + # if first charater a sign + # or allowend charset + # or is a float value + if (test_for_sign and next==0) \ + or is_allowed_character(character) \ + or (character == "." and (ignore_dots or current_token.is_valid_int())): + current_token += character + next += 1 + continue + break + if current_token != "": + return Variable.new(current_token) + return TOKEN_NOT_MATCH + + +# const ALLOWED_CHARACTERS := "0123456789_abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ\"" +func is_allowed_character(input: String) -> bool: + var code_point := input.unicode_at(0) + # Unicode + if code_point > 127: + # This is a Unicode character (Chinese, Japanese, etc.) + return true + # ASCII digit 0-9 + if code_point >= 48 and code_point <= 57: + return true + # ASCII lowercase a-z + if code_point >= 97 and code_point <= 122: + return true + # ASCII uppercase A-Z + if code_point >= 65 and code_point <= 90: + return true + # underscore _ + if code_point == 95: + return true + # quotes '" + if code_point == 34 or code_point == 39: + return true + return false + + +func extract_clazz_name(value :String) -> String: + var result := _regex_clazz_name.search(value) + if result == null: + push_error("Can't extract class name from '%s'" % value) + return "" + if result.get_string(2).is_empty(): + return result.get_string(5) + else: + return result.get_string(2) + + +@warning_ignore("unused_parameter") +func tokenize_inner_class(source_code: String, current: int, token: Token) -> Token: + var clazz_name := extract_clazz_name(source_code.substr(current, 64)) + return TokenInnerClass.new(clazz_name) + + +func parse_return_token(input: String) -> Variable: + var index := input.rfind(TOKEN_FUNCTION_RETURN_TYPE._token) + if index == -1: + return TOKEN_NOT_MATCH + index += TOKEN_FUNCTION_RETURN_TYPE._consumed + # We scan for the return value exclusive '.' token because it could be referenced to a + # external or internal class e.g. 'func foo() -> InnerClass.Bar:' + var token := next_token(input, index, [TOKEN_FUNCTION]) + while !token.is_variable() and token != TOKEN_NOT_MATCH: + index += token._consumed + token = next_token(input, index, [TOKEN_FUNCTION]) + return token + + +func get_function_descriptors(script: GDScript, included_functions: PackedStringArray = []) -> Array[GdFunctionDescriptor]: + var fds: Array[GdFunctionDescriptor] = [] + for method_descriptor in script.get_script_method_list(): + var func_name: String = method_descriptor["name"] + if included_functions.is_empty() or func_name in included_functions: + # exclude type set/geters + if is_getter_or_setter(func_name): + continue + if not fds.any(func(fd: GdFunctionDescriptor) -> bool: return fd.name() == func_name): + fds.append(GdFunctionDescriptor.extract_from(method_descriptor, false)) + + # we need to enrich it by default arguments and line number by parsing the script + # the engine core functions has no valid methods to get this info + _prescan_script(script) + _enrich_function_descriptor(script, fds) + return fds + + +func is_getter_or_setter(func_name: String) -> bool: + return func_name.begins_with("@") and (func_name.ends_with("getter") or func_name.ends_with("setter")) + + +func _parse_function_arguments(input: String) -> Array[Dictionary]: + var arguments: Array[Dictionary] = [] + var current_index := 0 + var token: Token = null + var bracket := 0 + var in_function := false + + + while current_index < len(input): + token = next_token(input, current_index) + # fallback to not end in a endless loop + if token == TOKEN_NOT_MATCH: + var error : = """ + Parsing Error: Invalid token at pos %d found. + Please report this error! + source_code: + -------------------------------------------------------------- + %s + -------------------------------------------------------------- + """.dedent() % [current_index, input] + push_error(error) + current_index += 1 + continue + current_index += token._consumed + if token.is_skippable(): + continue + if token == TOKEN_BRACKET_ROUND_OPEN : + in_function = true + bracket += 1 + if token == TOKEN_BRACKET_ROUND_CLOSE: + bracket -= 1 + # if function end? + if in_function and bracket == 0: + return arguments + # is function + if token == TOKEN_FUNCTION_DECLARATION: + token = next_token(input, current_index) + current_index += token._consumed + continue + + # is value argument + if in_function: + var arg_value := "" + var current_argument := { + "name" : "", + "value" : GdFunctionArgument.UNDEFINED, + "type" : TYPE_VARIANT + } + + # parse type and default value + while current_index < len(input): + token = next_token(input, current_index) + current_index += token._consumed + if token.is_skippable(): + continue + + if token.is_variable() && current_argument["name"] == "": + arguments.append(current_argument) + current_argument["name"] = (token as Variable).plain_value() + continue + + match token: + # is fuzzer argument + TOKEN_ARGUMENT_FUZZER: + arg_value = _parse_end_function(input.substr(current_index), true) + current_index += arg_value.length() + current_argument["name"] = (token as FuzzerToken).name() + current_argument["value"] = arg_value.lstrip(" ") + current_argument["type"] = TYPE_FUZZER + arguments.append(current_argument) + continue + + TOKEN_ARGUMENT_VARIADIC: + current_argument["type"] = TYPE_VARARG + + TOKEN_ARGUMENT_TYPE: + token = next_token(input, current_index) + if token == TOKEN_SPACE: + current_index += token._consumed + token = next_token(input, current_index) + current_index += token._consumed + if current_argument["type"] != TYPE_VARARG: + current_argument["type"] = GdObjects.string_to_type((token as Variable).plain_value()) + + TOKEN_ARGUMENT_TYPE_ASIGNMENT: + arg_value = _parse_end_function(input.substr(current_index), true) + current_index += arg_value.length() + current_argument["value"] = arg_value.lstrip(" ") + TOKEN_ARGUMENT_ASIGNMENT: + token = next_token(input, current_index) + arg_value = _parse_end_function(input.substr(current_index), true) + current_index += arg_value.length() + current_argument["value"] = arg_value.lstrip(" ") + + TOKEN_BRACKET_SQUARE_OPEN: + bracket += 1 + TOKEN_BRACKET_CURLY_OPEN: + bracket += 1 + TOKEN_BRACKET_ROUND_OPEN : + bracket += 1 + # if value a function? + if bracket > 1: + # complete the argument value + var func_begin := input.substr(current_index-TOKEN_BRACKET_ROUND_OPEN ._consumed) + var func_body := _parse_end_function(func_begin) + arg_value += func_body + # fix parse index to end of value + current_index += func_body.length() - TOKEN_BRACKET_ROUND_OPEN ._consumed - TOKEN_BRACKET_ROUND_CLOSE._consumed + TOKEN_BRACKET_SQUARE_CLOSE: + bracket -= 1 + TOKEN_BRACKET_CURLY_CLOSE: + bracket -= 1 + TOKEN_BRACKET_ROUND_CLOSE: + bracket -= 1 + # end of function + if bracket == 0: + break + TOKEN_ARGUMENT_SEPARATOR: + if bracket <= 1: + # next argument + current_argument = { + "name" : "", + "value" : GdFunctionArgument.UNDEFINED, + "type" : GdObjects.TYPE_VARIANT + } + continue + return arguments + + +func _parse_end_function(input: String, remove_trailing_char := false) -> String: + # find end of function + var current_index := 0 + var bracket_count := 0 + var in_array := 0 + var in_dict := 0 + var end_of_func := false + + while current_index < len(input) and not end_of_func: + var character := input[current_index] + # step over strings + if character == "'" : + current_index = input.find("'", current_index+1) + 1 + if current_index == 0: + push_error("Parsing error on '%s', can't evaluate end of string." % input) + return "" + continue + if character == '"' : + # test for string blocks + if input.find('"""', current_index) == current_index: + current_index = input.find('"""', current_index+3) + 3 + else: + current_index = input.find('"', current_index+1) + 1 + if current_index == 0: + push_error("Parsing error on '%s', can't evaluate end of string." % input) + return "" + continue + + match character: + # count if inside an array + "[": in_array += 1 + "]": in_array -= 1 + # count if inside an dictionary + "{": in_dict += 1 + "}": in_dict -= 1 + # count if inside a function + "(": bracket_count += 1 + ")": + bracket_count -= 1 + if bracket_count < 0 and in_array <= 0 and in_dict <= 0: + end_of_func = true + ",": + if bracket_count == 0 and in_array == 0 and in_dict <= 0: + end_of_func = true + current_index += 1 + if remove_trailing_char: + # check if the parsed value ends with comma or end of doubled breaked + # `,` or `())` + var trailing_char := input[current_index-1] + if trailing_char == ',' or (bracket_count < 0 and trailing_char == ')'): + return input.substr(0, current_index-1) + return input.substr(0, current_index) + + +func extract_inner_class(source_rows: PackedStringArray, clazz_name :String) -> PackedStringArray: + for row_index in source_rows.size(): + var input := source_rows[row_index] + var token := next_token(input, 0) + if token.is_inner_class(): + @warning_ignore("unsafe_method_access") + if token.is_class_name(clazz_name): + @warning_ignore("unsafe_method_access") + token.parse(source_rows, row_index) + @warning_ignore("unsafe_method_access") + return token.content() + return PackedStringArray() + + +func extract_func_signature(rows: PackedStringArray, index: int) -> String: + var signature := "" + + for rowIndex in range(index, rows.size()): + var row := rows[rowIndex] + row = _regex_strip_comments.sub(row, "").strip_edges(false) + if row.is_empty(): + continue + signature += row + "\n" + if is_func_end(row): + return signature.strip_edges() + push_error("Can't fully extract function signature of '%s'" % rows[index]) + return "" + + +func get_class_name(script :GDScript) -> String: + var source_code := GdScriptParser.to_unix_format(script.source_code) + var source_rows := source_code.split("\n") + + for index :int in min(10, source_rows.size()): + var input := source_rows[index] + var token := next_token(input, 0) + if token == TOKEN_CLASS_NAME: + var current_index := token._consumed + token = next_token(input, current_index) + current_index += token._consumed + token = tokenize_value(input, current_index, token) + return (token as Variable).value() + # if no class_name found extract from file name + return GdObjects.to_pascal_case(script.resource_path.get_basename().get_file()) + + +func parse_func_name(input: String) -> String: + var result := _regex_func_name.search(input) + if result == null: + push_error("Can't extract function name from '%s'" % input) + return "" + return result.get_string(1) + + +## Enriches the function descriptor by line number and argument default values +## - enrich all function descriptors form current script up to all inherited scrips +func _enrich_function_descriptor(script: GDScript, fds: Array[GdFunctionDescriptor]) -> void: + var enriched_functions := {} # Use Dictionary for O(1) lookup instead of PackedStringArray + var script_to_scan := script + while script_to_scan != null: + # do not scan the test suite base class itself + if script_to_scan.resource_path == "res://addons/gdUnit4/src/GdUnitTestSuite.gd": + break + + var rows := script_to_scan.source_code.split("\n") + for rowIndex in rows.size(): + var input := rows[rowIndex] + # step over inner class functions + if input.begins_with("\t"): + continue + # skip comments and empty lines + if input.begins_with("#") or input.length() == 0: + continue + var token := next_token(input, 0) + if token != TOKEN_FUNCTION_STATIC_DECLARATION and token != TOKEN_FUNCTION_DECLARATION: + continue + + var function_name := parse_func_name(input) + # Skip if already enriched (from parent class scan) + if enriched_functions.has(function_name): + continue + + # Find matching function descriptor + var fd: GdFunctionDescriptor = null + for candidate in fds: + if candidate.name() == function_name: + fd = candidate + break + if fd == null: + continue + # Mark as enriched + enriched_functions[function_name] = true + var func_signature := extract_func_signature(rows, rowIndex) + var func_arguments := _parse_function_arguments(func_signature) + # enrich missing default values + fd.enrich_arguments(func_arguments) + fd.enrich_file_info(script_to_scan.resource_path, rowIndex + 1) + fd._is_coroutine = is_func_coroutine(rows, rowIndex) + # enrich return class name if not set + if fd.return_type() == TYPE_OBJECT and fd._return_class in ["", "Resource", "RefCounted"]: + var var_token := parse_return_token(func_signature) + if var_token != TOKEN_NOT_MATCH and var_token.type() == TYPE_OBJECT: + fd._return_class = _patch_inner_class_names(var_token.plain_value(), "") + # if the script ihnerits we need to scan this also + script_to_scan = script_to_scan.get_base_script() + + +func is_func_coroutine(rows :PackedStringArray, index :int) -> bool: + var is_coroutine := false + for rowIndex in range(index+1, rows.size()): + var input := rows[rowIndex].strip_edges() + # skip empty lines + if input.is_empty(): + continue + var token := next_token(input, 0) + # scan until next function + if token == TOKEN_FUNCTION_STATIC_DECLARATION or token == TOKEN_FUNCTION_DECLARATION: + break + + if _is_awaiting.search(input): + return true + return is_coroutine + + +func is_inner_class(clazz_path :PackedStringArray) -> bool: + return clazz_path.size() > 1 + + +func is_func_end(row :String) -> bool: + return row.strip_edges(false, true).ends_with(":") + + +func _patch_inner_class_names(clazz :String, clazz_name :String = "") -> String: + var inner_clazz_name := clazz.split(".")[0] + if _scanned_inner_classes.has(inner_clazz_name): + return inner_clazz_name + #var base_clazz := clazz_name.split(".")[0] + #return base_clazz + "." + clazz + if _script_constants.has(clazz): + return clazz_name + "." + clazz + return clazz + + +func _prescan_script(script: GDScript) -> void: + _script_constants = script.get_script_constant_map() + for key :String in _script_constants.keys(): + var value :Variant = _script_constants.get(key) + if value is GDScript: + @warning_ignore("return_value_discarded") + _scanned_inner_classes.append(key) + + +func parse(clazz_name :String, clazz_path :PackedStringArray) -> GdUnitResult: + if clazz_path.is_empty(): + return GdUnitResult.error("Invalid script path '%s'" % clazz_path) + var is_inner_class_ := is_inner_class(clazz_path) + var script :GDScript = load(clazz_path[0]) + _prescan_script(script) + + if is_inner_class_: + var inner_class_name := clazz_path[1] + if _scanned_inner_classes.has(inner_class_name): + # do load only on inner class source code and enrich the stored script instance + var source_code := _load_inner_class(script, inner_class_name) + script = _script_constants.get(inner_class_name) + script.source_code = source_code + var function_descriptors := get_function_descriptors(script) + var gd_class := GdClassDescriptor.new(clazz_name, is_inner_class_, function_descriptors) + return GdUnitResult.success(gd_class) + + +func _load_inner_class(script: GDScript, inner_clazz: String) -> String: + var source_rows := GdScriptParser.to_unix_format(script.source_code).split("\n") + # extract all inner class names + var inner_class_code := extract_inner_class(source_rows, inner_clazz) + return "\n".join(inner_class_code) diff --git a/addons/gdUnit4/src/core/parse/GdScriptParser.gd.uid b/addons/gdUnit4/src/core/parse/GdScriptParser.gd.uid new file mode 100644 index 0000000..58bd732 --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdScriptParser.gd.uid @@ -0,0 +1 @@ +uid://cxtbue2vt4k5j diff --git a/addons/gdUnit4/src/core/parse/GdUnitExpressionRunner.gd b/addons/gdUnit4/src/core/parse/GdUnitExpressionRunner.gd new file mode 100644 index 0000000..9faf830 --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdUnitExpressionRunner.gd @@ -0,0 +1,74 @@ +class_name GdUnitExpressionRunner +extends RefCounted + +const CLASS_TEMPLATE = """ +class_name _ExpressionRunner extends '${clazz_path}' + +func __run_expression() -> Variant: + return $expression + +""" + +var constructor_args_regex := RegEx.create_from_string("new\\((?.*)\\)") + + +func execute(src_script: GDScript, value: Variant) -> Variant: + if typeof(value) != TYPE_STRING: + return value + + var expression: String = value + var parameter_map := src_script.get_script_constant_map() + for key: String in parameter_map.keys(): + var parameter_value: Variant = parameter_map[key] + # check we need to construct from inner class + # we need to use the original class instance from the script_constant_map otherwise we run into a runtime error + if expression.begins_with(key + ".new") and parameter_value is GDScript: + var object: GDScript = parameter_value + var args := build_constructor_arguments(parameter_map, expression.substr(expression.find("new"))) + if args.is_empty(): + return object.new() + return object.callv("new", args) + + var script := GDScript.new() + var resource_path := "res://addons/gdUnit4/src/Fuzzers.gd" if src_script.resource_path.is_empty() else src_script.resource_path + script.source_code = CLASS_TEMPLATE.dedent()\ + .replace("${clazz_path}", resource_path)\ + .replace("$expression", expression) + #script.take_over_path(resource_path) + @warning_ignore("return_value_discarded") + script.reload(true) + var runner: Object = script.new() + if runner.has_method("queue_free"): + (runner as Node).queue_free() + @warning_ignore("unsafe_method_access") + return runner.__run_expression() + + +func build_constructor_arguments(parameter_map: Dictionary, expression: String) -> Array[Variant]: + var result := constructor_args_regex.search(expression) + var extracted_arguments := result.get_string("args").strip_edges() + if extracted_arguments.is_empty(): + return [] + var arguments :Array = extracted_arguments.split(",") + return arguments.map(func(argument: String) -> Variant: + var value := argument.strip_edges() + + # is argument an constant value + if parameter_map.has(value): + return parameter_map[value] + # is typed named value like Vector3.ONE + for type:int in GdObjects.TYPE_AS_STRING_MAPPINGS: + var type_as_string:String = GdObjects.TYPE_AS_STRING_MAPPINGS[type] + if value.begins_with(type_as_string): + return type_convert(value, type) + # is value a string + if value.begins_with("'") or value.begins_with('"'): + return value.trim_prefix("'").trim_suffix("'").trim_prefix('"').trim_suffix('"') + # fallback to default value converting + return str_to_var(value) + ) + + +func to_fuzzer(src_script: GDScript, expression: String) -> Fuzzer: + @warning_ignore("unsafe_cast") + return execute(src_script, expression) as Fuzzer diff --git a/addons/gdUnit4/src/core/parse/GdUnitExpressionRunner.gd.uid b/addons/gdUnit4/src/core/parse/GdUnitExpressionRunner.gd.uid new file mode 100644 index 0000000..a0bdef3 --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdUnitExpressionRunner.gd.uid @@ -0,0 +1 @@ +uid://r3oh5dgq8l7e diff --git a/addons/gdUnit4/src/core/parse/GdUnitTestParameterSetResolver.gd b/addons/gdUnit4/src/core/parse/GdUnitTestParameterSetResolver.gd new file mode 100644 index 0000000..527661d --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdUnitTestParameterSetResolver.gd @@ -0,0 +1,163 @@ +## @deprecated see GdFunctionParameterSetResolver +class_name GdUnitTestParameterSetResolver +extends RefCounted + +const CLASS_TEMPLATE = """ +class_name _ParameterExtractor extends '${clazz_path}' + +func __extract_test_parameters() -> Array: + return ${test_params} + +""" + +const EXCLUDE_PROPERTIES_TO_COPY = [ + "script", + "type", + "Node", + "_import_path"] + + +var _fd: GdFunctionDescriptor +var _static_sets_by_index := {} +var _is_static := true + +func _init(fd: GdFunctionDescriptor) -> void: + _fd = fd + + +func is_parameterized() -> bool: + return _fd.is_parameterized() + + +func is_parameter_sets_static() -> bool: + return _is_static + + +func is_parameter_set_static(index: int) -> bool: + return _is_static and _static_sets_by_index.get(index, false) + + +# validates the given arguments are complete and matches to required input fields of the test function +func validate(parameter_sets: Array, parameter_set_index: int) -> GdUnitResult: + if parameter_sets.size() < parameter_set_index: + return GdUnitResult.error("Internal error: the resolved paremeterset has invalid size.") + + var input_values: Array = parameter_sets[parameter_set_index] + if input_values == null: + return GdUnitResult.error("The parameter set '%s' must be an Array!" % parameter_sets[parameter_set_index]) + + # check given parameter set with test case arguments + var input_arguments := _fd.args() + var expected_arg_count := input_arguments.size() - 1 #(-1 we exclude the parameter set itself) + var current_arg_count := input_values.size() + if current_arg_count != expected_arg_count: + var arg_names := input_arguments\ + .filter(func(arg: GdFunctionArgument) -> bool: return not arg.is_parameter_set())\ + .map(func(arg: GdFunctionArgument) -> String: return str(arg)) + + return GdUnitResult.error(""" + The test data set at index (%d) does not match the expected test arguments: + test function: [color=snow]func test...(%s)[/color] + test input values: [color=snow]%s[/color] + """ + .dedent() % [parameter_set_index, ",".join(arg_names), input_values]) + return GdUnitTestParameterSetResolver.validate_parameter_types(input_arguments, input_values) + + +static func validate_parameter_types(input_arguments: Array[GdFunctionArgument], input_values: Array) -> GdUnitResult: + for i in input_arguments.size(): + var input_param: GdFunctionArgument = input_arguments[i] + # only check the test input arguments + if input_param.is_parameter_set(): + continue + var input_param_type := input_param.type() + var input_value :Variant = input_values[i] + var input_value_type := typeof(input_value) + # input parameter is not typed or is Variant we skip the type test + if input_param_type == TYPE_NIL or input_param_type == GdObjects.TYPE_VARIANT: + continue + # is input type enum allow int values + if input_param_type == GdObjects.TYPE_VARIANT and input_value_type == TYPE_INT: + continue + # allow only equal types and object == null + if input_param_type == TYPE_OBJECT and input_value_type == TYPE_NIL: + continue + if input_param_type != input_value_type: + return GdUnitResult.error(""" + The test data value does not match the expected input type! + input value: [color=snow]'%s', <%s>[/color] + expected argument: [color=snow]%s[/color] + """ + .dedent() % [input_value, type_string(input_value_type), str(input_param)]) + return GdUnitResult.success("No errors found.") + + +func _extract_property_names(node :Node) -> PackedStringArray: + return node.get_property_list()\ + .map(func(property :Dictionary) -> String: return property["name"])\ + .filter(func(property :String) -> bool: return !EXCLUDE_PROPERTIES_TO_COPY.has(property)) + + +# tests if the test property set contains an property reference by name, if not the parameter set holds only static values +func _is_static_parameter_set(parameters :String, property_names :PackedStringArray) -> bool: + for property_name in property_names: + if parameters.contains(property_name): + _is_static = false + return false + return true + + +# extracts the arguments from the given test case, using kind of reflection solution +# to restore the parameters from a string representation to real instance type +func load_parameter_sets(test_suite: Node) -> GdUnitResult: + var source_script: Script = test_suite.get_script() + var parameter_arg := GdFunctionArgument.get_parameter_set(_fd.args()) + var source_code := CLASS_TEMPLATE \ + .replace("${clazz_path}", source_script.resource_path) \ + .replace("${test_params}", parameter_arg.value_as_string()) + var script := GDScript.new() + script.source_code = source_code + # enable this lines only for debuging + #script.resource_path = GdUnitFileAccess.create_temp_dir("parameter_extract") + "/%s__.gd" % test_case.get_name() + #DirAccess.remove_absolute(script.resource_path) + #ResourceSaver.save(script, script.resource_path) + var result := script.reload() + if result != OK: + return GdUnitResult.error("Extracting test parameters failed! Script loading error: %s" % error_string(result)) + var instance :Object = script.new() + GdUnitTestParameterSetResolver.copy_properties(test_suite, instance) + (instance as Node).queue_free() + var parameter_sets: Array = instance.call("__extract_test_parameters") + fixure_typed_parameters(parameter_sets, _fd.args()) + return GdUnitResult.success(parameter_sets) + + +func fixure_typed_parameters(parameter_sets: Array, arg_descriptors: Array[GdFunctionArgument]) -> Array: + for parameter_set_index in parameter_sets.size(): + var parameter_set: Array = parameter_sets[parameter_set_index] + # run over all function arguments + for parameter_index in parameter_set.size(): + var parameter :Variant = parameter_set[parameter_index] + var arg_descriptor: GdFunctionArgument = arg_descriptors[parameter_index] + if parameter is Array: + var as_array: Array = parameter + # we need to convert the untyped array to the expected typed version + if arg_descriptor.is_typed_array(): + parameter_set[parameter_index] = Array(as_array, arg_descriptor.type_hint(), "", null) + return parameter_sets + + +static func copy_properties(source: Object, dest: Object) -> void: + for property in source.get_property_list(): + var property_name :String = property["name"] + var property_value :Variant = source.get(property_name) + if EXCLUDE_PROPERTIES_TO_COPY.has(property_name): + continue + #if dest.get(property_name) == null: + # prints("|%s|" % property_name, source.get(property_name)) + + # check for invalid name property + if property_name == "name" and property_value == "": + dest.set(property_name, ""); + continue + dest.set(property_name, property_value) diff --git a/addons/gdUnit4/src/core/parse/GdUnitTestParameterSetResolver.gd.uid b/addons/gdUnit4/src/core/parse/GdUnitTestParameterSetResolver.gd.uid new file mode 100644 index 0000000..b94cca2 --- /dev/null +++ b/addons/gdUnit4/src/core/parse/GdUnitTestParameterSetResolver.gd.uid @@ -0,0 +1 @@ +uid://c78bmaxb1a10u diff --git a/addons/gdUnit4/src/core/report/GdUnitReport.gd b/addons/gdUnit4/src/core/report/GdUnitReport.gd new file mode 100644 index 0000000..eb7ed2e --- /dev/null +++ b/addons/gdUnit4/src/core/report/GdUnitReport.gd @@ -0,0 +1,74 @@ +class_name GdUnitReport +extends Resource + +# report type +enum { + SUCCESS, + WARN, + FAILURE, + ORPHAN, + TERMINATED, + INTERUPTED, + ABORT, + SKIPPED, +} + +var _type :int +var _line_number :int +var _message :String + + +func create(p_type :int, p_line_number :int, p_message :String) -> GdUnitReport: + _type = p_type + _line_number = p_line_number + _message = p_message + return self + + +func type() -> int: + return _type + + +func line_number() -> int: + return _line_number + + +func message() -> String: + return _message + + +func is_skipped() -> bool: + return _type == SKIPPED + + +func is_warning() -> bool: + return _type == WARN + + +func is_failure() -> bool: + return _type == FAILURE + + +func is_error() -> bool: + return _type == TERMINATED or _type == INTERUPTED or _type == ABORT + + +func _to_string() -> String: + if _line_number == -1: + return "[color=green]line [/color][color=aqua]:[/color] %s" % [_message] + return "[color=green]line [/color][color=aqua]%d:[/color] %s" % [_line_number, _message] + + +func serialize() -> Dictionary: + return { + "type" :_type, + "line_number" :_line_number, + "message" :_message + } + + +func deserialize(serialized :Dictionary) -> GdUnitReport: + _type = serialized["type"] + _line_number = serialized["line_number"] + _message = serialized["message"] + return self diff --git a/addons/gdUnit4/src/core/report/GdUnitReport.gd.uid b/addons/gdUnit4/src/core/report/GdUnitReport.gd.uid new file mode 100644 index 0000000..d9d4f6e --- /dev/null +++ b/addons/gdUnit4/src/core/report/GdUnitReport.gd.uid @@ -0,0 +1 @@ +uid://cfaj8ju8e246m diff --git a/addons/gdUnit4/src/core/runners/GdUnitTestCIRunner.gd b/addons/gdUnit4/src/core/runners/GdUnitTestCIRunner.gd new file mode 100644 index 0000000..34dcfa3 --- /dev/null +++ b/addons/gdUnit4/src/core/runners/GdUnitTestCIRunner.gd @@ -0,0 +1,470 @@ +#warning-ignore-all:return_value_discarded +class_name GdUnitTestCIRunner +extends "res://addons/gdUnit4/src/core/runners/GdUnitTestSessionRunner.gd" +## Command line test runner implementation.[br] +## [br] +## This runner is designed for CI/CD pipelines and command line test execution.[br] +## Features:[br] +## - Command line options for test configuration[br] +## - HTML and JUnit report generation[br] +## - Console output with colored formatting[br] +## - Progress and error reporting[br] +## - Test history management[br] +## [br] +## Example usage:[br] +## [codeblock] +## # Run all tests in a directory +## runtest -a +## +## # Run specific test suite with ignored tests +## runtest -a -i +## [/codeblock] + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") + +var _console := GdUnitCSIMessageWriter.new() +var _console_reporter: GdUnitConsoleTestReporter +var _headless_mode_ignore := false +var _runner_config_file := "" +var _debug_cmd_args := PackedStringArray() +var _included_tests := PackedStringArray() +var _excluded_tests := PackedStringArray() + +## Command line options configuration +var _cmd_options := CmdOptions.new([ + CmdOption.new( + "-a, --add", + "-a ", + "Adds the given test suite or directory to the execution pipeline.", + TYPE_STRING + ), + CmdOption.new( + "-i, --ignore", + "-i ", + "Adds the given test suite or test case to the ignore list.", + TYPE_STRING + ), + CmdOption.new( + "-c, --continue", + "", + """By default GdUnit will abort checked first test failure to be fail fast, + instead of stop after first failure you can use this option to run the complete test set.""".dedent() + ), + CmdOption.new( + "-conf, --config", + "-conf [testconfiguration.cfg]", + "Run all tests by given test configuration. Default is 'GdUnitRunner.cfg'", + TYPE_STRING, + true + ), + CmdOption.new( + "-help", "", + "Shows this help message." + ), + CmdOption.new("--help-advanced", "", + "Shows advanced options." + ) + ], + [ + # advanced options + CmdOption.new( + "-rd, --report-directory", + "-rd ", + "Specifies the output directory in which the reports are to be written. The default is res://reports/.", + TYPE_STRING, + true + ), + CmdOption.new( + "-rc, --report-count", + "-rc ", + "Specifies how many reports are saved before they are deleted. The default is %s." % str(GdUnitConstants.DEFAULT_REPORT_HISTORY_COUNT), + TYPE_INT, + true + ), + #CmdOption.new("--list-suites", "--list-suites [directory]", "Lists all test suites located in the given directory.", TYPE_STRING), + #CmdOption.new("--describe-suite", "--describe-suite ", "Shows the description of selected test suite.", TYPE_STRING), + CmdOption.new( + "--info", "", + "Shows the GdUnit version info" + ), + CmdOption.new( + "--selftest", "", + "Runs the GdUnit self test" + ), + CmdOption.new( + "--ignoreHeadlessMode", + "--ignoreHeadlessMode", + "By default, running GdUnit4 in headless mode is not allowed. You can switch off the headless mode check by set this property." + ), + ]) + + +func _init() -> void: + super() + + +func _ready() -> void: + super() + # stop checked first test failure to fail fast + _executor.fail_fast(true) + _console_reporter = GdUnitConsoleTestReporter.new(_console, true) + GdUnitSignals.instance().gdunit_message.connect(_on_send_message) + + +func _notification(what: int) -> void: + super(what) + if what == NOTIFICATION_PREDELETE: + prints("Finallize .. done") + + +func init_runner() -> void: + init_gd_unit() + + +## Returns the exit code based on test results.[br] +## Maps test report status to process exit codes. +func get_exit_code() -> int: + return report_exit_code() + + +## Cleanup and quit the runner.[br] +## [br] +## [param code] The exit code to return. +func quit(code: int) -> void: + _state = EXIT + GdUnitTools.dispose_all() + await GdUnitMemoryObserver.gc_on_guarded_instances() + await super(code) + + +## Prints info message to console.[br] +## [br] +## [param message] The message to print.[br] +## [param color] Optional color for the message. +func console_info(message: String, color: Color = Color.WHITE) -> void: + _console.color(color).println_message(message) + + +## Prints error message to console.[br] +## [br] +## [param message] The error message to print. +func console_error(message: String) -> void: + _console.prints_error(message) + + +## Prints warning message to console.[br] +## [br] +## [param message] The warning message to print. +func console_warning(message: String) -> void: + _console.prints_warning(message) + + +## Sets the directory for test reports.[br] +## [br] +## [param path] The path where reports should be written. +func set_report_dir(path: String) -> void: + report_base_path = ProjectSettings.globalize_path(GdUnitFileAccess.make_qualified_path(path)) + console_info( + "Set write reports to %s" % report_base_path, + Color.DEEP_SKY_BLUE + ) + + +## Sets how many report files to keep.[br] +## [br] +## [param count] The number of reports to keep. +func set_report_count(count: String) -> void: + var report_count := count.to_int() + if report_count < 1: + console_error( + "Invalid report history count '%s' set back to default %d" + % [count, GdUnitConstants.DEFAULT_REPORT_HISTORY_COUNT] + ) + max_report_history = GdUnitConstants.DEFAULT_REPORT_HISTORY_COUNT + else: + console_info( + "Set report history count to %s" % count, + Color.DEEP_SKY_BLUE + ) + max_report_history = report_count + + +## Disables fail-fast mode to run all tests.[br] +## By default tests stop on first failure. +func disable_fail_fast() -> void: + console_info( + "Disabled fail fast!", + Color.DEEP_SKY_BLUE + ) + @warning_ignore("unsafe_method_access") + _executor.fail_fast(false) + + +func run_self_test() -> void: + console_info( + "Run GdUnit4 self tests.", + Color.DEEP_SKY_BLUE + ) + disable_fail_fast() + + + +## Shows GdUnit and Godot version information. +func show_version() -> void: + console_info( + "Godot %s" % Engine.get_version_info().get("string") as String, + Color.DARK_SALMON + ) + var config := ConfigFile.new() + config.load("addons/gdUnit4/plugin.cfg") + console_info( + "GdUnit4 %s" % config.get_value("plugin", "version") as String, + Color.DARK_SALMON + ) + quit(RETURN_SUCCESS) + + +## Ignores headless mode restrictions.[br] +## Allows tests to run in headless mode despite limitations. +func check_headless_mode() -> void: + _headless_mode_ignore = true + + +## Shows available command line options.[br] +## [br] +## [param show_advanced] Whether to show advanced options. +func show_options(show_advanced: bool = false) -> void: + console_info( + """ + Usage: + runtest -a + runtest -a -i + """.dedent(), + Color.DARK_SALMON + ) + console_info( + "-- Options ---------------------------------------------------------------------------------------", + Color.DARK_SALMON + ) + for option in _cmd_options.default_options(): + descripe_option(option) + if show_advanced: + console_info( + "-- Advanced options --------------------------------------------------------------------------", + Color.DARK_SALMON + ) + for option in _cmd_options.advanced_options(): + descripe_option(option) + + +## Describes a single command line option.[br] +## [br] +## [param cmd_option] The option to describe. +func descripe_option(cmd_option: CmdOption) -> void: + console_info( + " %-40s" % str(cmd_option.commands()), + Color.CORNFLOWER_BLUE + ) + console_info( + cmd_option.description(), + Color.LIGHT_GREEN + ) + if not cmd_option.help().is_empty(): + console_info( + "%-4s %s" % ["", cmd_option.help()], + Color.DARK_TURQUOISE + ) + console_info("") + + +## Loads test configuration from file.[br] +## [br] +## [param path] Path to the configuration file. +func load_test_config(path := GdUnitRunnerConfig.CONFIG_FILE) -> void: + console_info( + "Loading test configuration %s\n" % path, + Color.CORNFLOWER_BLUE + ) + _runner_config_file = path + _runner_config.load_config(path) + + +## Shows basic help and exits. +func show_help() -> void: + show_options() + quit(RETURN_SUCCESS) + + +## Shows advanced help and exits. +func show_advanced_help() -> void: + show_options(true) + quit(RETURN_SUCCESS) + + +## Gets command line arguments.[br] +## Returns debug args if set, otherwise actual command line args. +func get_cmdline_args() -> PackedStringArray: + if _debug_cmd_args.is_empty(): + return OS.get_cmdline_args() + return _debug_cmd_args + + +## Initializes the test runner and processes command line arguments. +func init_gd_unit() -> void: + console_info( + """ + -------------------------------------------------------------------------------------------------- + GdUnit4 Comandline Tool + --------------------------------------------------------------------------------------------------""".dedent(), + Color.DARK_SALMON + ) + + var cmd_parser := CmdArgumentParser.new(_cmd_options, "GdUnitCmdTool.gd") + var result := cmd_parser.parse(get_cmdline_args()) + if result.is_error(): + console_error(result.error_message()) + show_options() + console_error("Abnormal exit with %d" % RETURN_ERROR) + quit(RETURN_ERROR) + return + if result.is_empty(): + show_help() + return + # build runner config by given commands + var commands :Array[CmdCommand] = [] + @warning_ignore("unsafe_cast") + commands.append_array(result.value() as Array) + result = ( + CmdCommandHandler.new(_cmd_options) + .register_cb("-help", show_help) + .register_cb("--help-advanced", show_advanced_help) + .register_cb("-a", add_test_suite) + .register_cbv("-a", add_test_suites) + .register_cb("-i", skip_test_suite) + .register_cbv("-i", skip_test_suites) + .register_cb("-rd", set_report_dir) + .register_cb("-rc", set_report_count) + .register_cb("--selftest", run_self_test) + .register_cb("-c", disable_fail_fast) + .register_cb("-conf", load_test_config) + .register_cb("--info", show_version) + .register_cb("--ignoreHeadlessMode", check_headless_mode) + .execute(commands) + ) + if result.is_error(): + console_error(result.error_message()) + quit(RETURN_ERROR) + return + + if DisplayServer.get_name() == "headless": + if _headless_mode_ignore: + console_warning(""" + Headless mode is ignored by option '--ignoreHeadlessMode'" + + Please note that tests that use UI interaction do not work correctly in headless mode. + Godot 'InputEvents' are not transported by the Godot engine in headless mode and therefore + have no effect in the test! + """.dedent() + ) + else: + console_error(""" + Headless mode is not supported! + + Please note that tests that use UI interaction do not work correctly in headless mode. + Godot 'InputEvents' are not transported by the Godot engine in headless mode and therefore + have no effect in the test! + + You can run with '--ignoreHeadlessMode' to swtich off this check. + """.dedent() + ) + console_error( + "Abnormal exit with %d" % RETURN_ERROR_HEADLESS_NOT_SUPPORTED + ) + quit(RETURN_ERROR_HEADLESS_NOT_SUPPORTED) + return + + _test_cases = discover_tests() + if _test_cases.is_empty(): + console_info("No test cases found, abort test run!", Color.YELLOW) + console_info("Exit code: %d" % RETURN_SUCCESS, Color.DARK_SALMON) + quit(RETURN_SUCCESS) + return + _state = RUN + + +func discover_tests() -> Array[GdUnitTestCase]: + var gdunit_test_discover_added := GdUnitSignals.instance().gdunit_test_discover_added + + _test_cases = _runner_config.test_cases() + var scanner := GdUnitTestSuiteScanner.new() + for path in _included_tests: + var scripts := scanner.scan(path) + for script in scripts: + GdUnitTestDiscoverer.discover_tests(script, func(test: GdUnitTestCase) -> void: + if not is_skipped(test): + #_console.println_message("discoverd %s" % test.display_name) + _test_cases.append(test) + gdunit_test_discover_added.emit(test) + ) + + return _test_cases + + +func add_test_suite(path: String) -> void: + _included_tests.append(path) + + +func add_test_suites(paths: PackedStringArray) -> void: + _included_tests.append_array(paths) + + +func skip_test_suite(path: String) -> void: + _excluded_tests.append(path) + + +func skip_test_suites(paths: PackedStringArray) -> void: + _excluded_tests.append_array(paths) + + +func is_skipped(test: GdUnitTestCase) -> bool: + for skipped_info in _excluded_tests: + + # is suite skipped by full path or suite name + if skipped_info == test.suite_name or test.source_file.contains(skipped_info): + return true + var skip_file := skipped_info.replace("res://", "") + + # check for skipped single test + if not skip_file.contains(":"): + continue + var parts: PackedStringArray = skip_file.rsplit(":") + var skipped_suite := parts[0] + var skipped_test := parts[1] + # is suite skipped by full path or suite name + if (skipped_suite == test.suite_name or test.source_file.contains(skipped_suite)) and skipped_test == test.test_name: + return true + + return false + + +func _on_send_message(message: String) -> void: + _console.color(Color.CORNFLOWER_BLUE).println_message(message) + + +func _on_gdunit_event(event: GdUnitEvent) -> void: + match event.type(): + GdUnitEvent.SESSION_START: + _console_reporter.test_session = _test_session + GdUnitEvent.SESSION_CLOSE: + _console_reporter.test_session = null + + +func report_exit_code() -> int: + if _console_reporter.total_error_count() + _console_reporter.total_failure_count() > 0: + console_info("Exit code: %d" % RETURN_ERROR, Color.FIREBRICK) + return RETURN_ERROR + if _console_reporter.total_orphan_count() > 0: + console_info("Exit code: %d" % RETURN_WARNING, Color.GOLDENROD) + return RETURN_WARNING + console_info("Exit code: %d" % RETURN_SUCCESS, Color.DARK_SALMON) + return RETURN_SUCCESS diff --git a/addons/gdUnit4/src/core/runners/GdUnitTestCIRunner.gd.uid b/addons/gdUnit4/src/core/runners/GdUnitTestCIRunner.gd.uid new file mode 100644 index 0000000..ed659a6 --- /dev/null +++ b/addons/gdUnit4/src/core/runners/GdUnitTestCIRunner.gd.uid @@ -0,0 +1 @@ +uid://cu1hmt8duoa0j diff --git a/addons/gdUnit4/src/core/runners/GdUnitTestRunner.gd b/addons/gdUnit4/src/core/runners/GdUnitTestRunner.gd new file mode 100644 index 0000000..5af6c9b --- /dev/null +++ b/addons/gdUnit4/src/core/runners/GdUnitTestRunner.gd @@ -0,0 +1,87 @@ +extends "res://addons/gdUnit4/src/core/runners/GdUnitTestSessionRunner.gd" +## Runner implementation used by the editor UI.[br] +## [br] +## This runner connects to a GdUnit server via TCP to report test results.[br] +## Test results are reported in real-time and displayed in the editor UI.[br] +## [br] +## The runner uses an RPC message protocol to communicate status and events:[br] +## - Messages to report progress[br] +## - Events to report test results[br] + +## The TCP client used to connect to the GdUnit server +@onready var _client: GdUnitTcpClient = $GdUnitTcpClient +@onready var _version_label: Control = %Version + + +func _init() -> void: + super() + # We set the default max report history to 1 + max_report_history = 1 + + +func _ready() -> void: + super() + GdUnit4Version.init_version_label(_version_label) + + var config_result := _runner_config.load_config() + if config_result.is_error(): + push_error(config_result.error_message()) + _state = EXIT + return + @warning_ignore("return_value_discarded") + _client.connect("connection_failed", _on_connection_failed) + GdUnitSignals.instance().gdunit_message.connect(_on_send_message) + var result := _client.start("127.0.0.1", _runner_config.server_port()) + if result.is_error(): + push_error(result.error_message()) + return + + +## Cleanup and quit the runner.[br] +## [br] +## [param code] The exit code to return. +func quit(code: int) -> void: + if code != RETURN_SUCCESS: + _state = EXIT + await GdUnitMemoryObserver.gc_on_guarded_instances() + + +## Called when the TCP connection to the GdUnit server fails.[br] +## Stops the test execution.[br] +## [br] +## [param message] The error message describing the failure. +func _on_connection_failed(message: String) -> void: + prints("_on_connection_failed", message) + _state = STOP + + +## Initializes the test runner.[br] +## Waits for TCP client connection and then scans for test suites.[br] +## Reports the number of found test suites via TCP message. +func init_runner() -> void: + # wait until client is connected to the GdUnitServer + if _client.is_client_connected(): + await gdUnitInit() + _state = RUN + + +## Initializes the GdUnit framework.[br] +## Sends initial message about number of test suites. +func gdUnitInit() -> void: + #enable_manuall_polling() + _test_cases = _runner_config.test_cases() + await get_tree().process_frame + + +## Sends a message via TCP to the GdUnit server.[br] +## [br] +## [param message] The message to send. +func _on_send_message(message: String) -> void: + _client.send(RPCMessage.of(message)) + + +## Handles GdUnit events by sending them via TCP to the server.[br] +## [br] +## [param event] The event to send. +func _on_gdunit_event(event: GdUnitEvent) -> void: + _client.send(RPCGdUnitEvent.of(event)) diff --git a/addons/gdUnit4/src/core/runners/GdUnitTestRunner.gd.uid b/addons/gdUnit4/src/core/runners/GdUnitTestRunner.gd.uid new file mode 100644 index 0000000..156359c --- /dev/null +++ b/addons/gdUnit4/src/core/runners/GdUnitTestRunner.gd.uid @@ -0,0 +1 @@ +uid://bvlfmfgvqdlvr diff --git a/addons/gdUnit4/src/core/runners/GdUnitTestRunner.tscn b/addons/gdUnit4/src/core/runners/GdUnitTestRunner.tscn new file mode 100644 index 0000000..d4a1aae --- /dev/null +++ b/addons/gdUnit4/src/core/runners/GdUnitTestRunner.tscn @@ -0,0 +1,34 @@ +[gd_scene load_steps=3 format=3 uid="uid://belidlfknh74r"] + +[ext_resource type="Script" uid="uid://bvlfmfgvqdlvr" path="res://addons/gdUnit4/src/core/runners/GdUnitTestRunner.gd" id="1"] +[ext_resource type="Script" uid="uid://cuwwf10v6cxiy" path="res://addons/gdUnit4/src/network/GdUnitTcpClient.gd" id="2"] + +[node name="Control" type="Node"] +script = ExtResource("1") + +[node name="GdUnitTcpClient" type="Node" parent="."] +script = ExtResource("2") + +[node name="HBoxContainer" type="HBoxContainer" parent="."] +custom_minimum_size = Vector2(0, 24) +layout_direction = 2 +anchors_preset = 12 +anchor_top = 1.0 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 0 +size_flags_horizontal = 3 +size_flags_vertical = 10 +alignment = 2 + +[node name="Version" type="RichTextLabel" parent="HBoxContainer"] +unique_name_in_owner = true +custom_minimum_size = Vector2(128, 0) +layout_mode = 2 +size_flags_horizontal = 10 +bbcode_enabled = true +scroll_active = false +shortcut_keys_enabled = false +horizontal_alignment = 1 +justification_flags = 0 diff --git a/addons/gdUnit4/src/core/runners/GdUnitTestSession.gd b/addons/gdUnit4/src/core/runners/GdUnitTestSession.gd new file mode 100644 index 0000000..c789847 --- /dev/null +++ b/addons/gdUnit4/src/core/runners/GdUnitTestSession.gd @@ -0,0 +1,169 @@ +## +## @since GdUnit4 5.1.0 +## +## Represents a test execution session in GdUnit4.[br] +## [br] +## [i]A test session encapsulates a complete test execution cycle, managing the collection +## of test cases to be executed and providing communication channels for test events +## and messages. This class serves as the central coordination point for test execution +## and allows hooks and other components to interact with the running test session.[/i][br] +## [br] +## [b][u]Key Features[/u][/b][br] +## - [i][b]Test Case Management[/b][/i]: Maintains a collection of test cases to be executed[br] +## - [i][b]Event Broadcasting[/b][/i]: Forwards GdUnit events to session-specific listeners[br] +## - [i][b]Message Communication[/b][/i]: Provides a channel for sending messages during test execution[br] +## - [i][b]Hook Integration[/b][/i]: Passed to test session hooks for startup and shutdown operations[br] +## [br] +## [b][u]Usage in Test Hooks[/u][/b] +## [codeblock] +## func startup(session: GdUnitTestSession) -> GdUnitResult: +## # Access test cases +## print("Running %d test cases" % session.test_cases.size()) +## +## # Send status messages +## session.send_message("Custom hook initialized") +## +## # Listen for test events +## session.test_event.connect(_on_test_event) +## +## return GdUnitResult.success() +## +## func _on_test_event(event: GdUnitEvent) -> void: +## print("Test event received: %s" % event.type) +## [/codeblock] +## [br] +## [b][u]Event Flow[/u][/b][br] +## 1. Session is created with a collection of test cases[br] +## 2. Session connects to the global GdUnit event system[br] +## 3. During test execution, events are automatically forwarded to session listeners[br] +## 4. Hooks and other components can subscribe to session events[br] +## 5. Messages can be sent through the session for logging and communication[br] +class_name GdUnitTestSession +extends RefCounted + + +## Emitted when a test execution event occurs.[br] +## [br] +## [i]This signal forwards events from the global GdUnit event system to session-specific +## listeners. It allows hooks and other session components to react to test events +## without directly connecting to the global event system.[/i][br] +## [br] +## [u]Common event types include:[/u][br] +## - Test suite start/end events[br] +## - Test case start/end events[br] +## - Test assertion events[br] +## - Test failure/error events[br] +## +## [param event] The test event containing details about test execution, timing, and results +@warning_ignore("unused_signal") +signal test_event(event: GdUnitEvent) + + +## [b][color=red]@readonly: Should not be modified directly during test execution![/color][/b][br] +## Collection of test cases to be executed in this session.[br] +## [br] +## This array contains all the test cases that will be run during the session. +## Test hooks can access this collection to: +## - Get the total number of tests to be executed +## - Access individual test case metadata +## - Perform setup/teardown based on test case requirements +## - Generate reports or statistics about the test suite +## +## The collection is typically populated before session startup and remains +## constant during test execution. +var _test_cases : Array[GdUnitTestCase] = [] + + +## [b][color=red]@readonly: The report path should not be modified after session creation![/color][/b][br] +## The file system path where test reports for this session will be generated.[br] +## [br] +## [i]This property provides centralized access to the report output location, +## allowing test hooks, reporters, and other components to reference the same +## report path without coupling to specific reporter implementations.[/i][br] +## [br] +## [b][u]Common use cases include:[/u][/b][br] +## - Test hooks generating additional report files in the same directory[br] +## - Custom reporters creating supplementary output files[br] +## - Post-processing scripts that need to locate generated reports[br] +## - Cleanup operations that need to manage report artifacts[br] +## [br] +## [b][u]Example Usage:[/u][/b] +## [codeblock] +## # In a test hook +## func startup(session: GdUnitTestSession) -> GdUnitResult: +## var report_dir = session.report_path.get_base_dir() +## var custom_report = report_dir.path_join("custom_metrics.json") +## # Generate additional reports in the same location +## return GdUnitResult.success() +## +## func shutdown(session: GdUnitTestSession) -> GdUnitResult: +## session.send_message("Reports available at: " + session.report_path) +## return GdUnitResult.success() +## [/codeblock] +## [br] +## The path is set during session initialization and remains constant throughout +## the test execution lifecycle. +var report_path: String: + get: + return report_path + + +## Initializes the test session and sets up event forwarding.[br] +## [br] +## [i]This constructor automatically connects to the global GdUnit event system +## and forwards all events to the session's test_event signal. This allows +## session-specific components to listen for test events without managing +## global signal connections.[/i] +func _init(test_cases: Array[GdUnitTestCase], session_report_path: String) -> void: + # We build a copy to prevent a user is modifing the tests + _test_cases = test_cases.duplicate(true) + report_path = session_report_path + GdUnitSignals.instance().gdunit_event.connect(func(event: GdUnitEvent) -> void: + test_event.emit(event) + ) + + +## Finds a test case by its unique identifier.[br] +## [br] +## [i]Searches through all test cases to find a test with the matching GUID.[/i][br] +## [br] +## [param id] The GUID of the test to find[br] +## Returns the matching test case or null if not found. +func find_test_by_id(id: GdUnitGUID) -> GdUnitTestCase: + for test in _test_cases: + if test.guid.equals(id): + return test + + return null + + +## Sends a message through the GdUnit messaging system.[br] +## [br] +## [i]This method provides a convenient way for test hooks and other session +## components to send messages that will be handled by the GdUnit framework.[/i] +## [br][br] +## [b][u]Messages are typically used for:[/u][/b][br] +## - Status updates during test execution[br] +## - Progress reporting from test hooks[br] +## - Debug information and logging[br] +## - User notifications and alerts[br] +## [br] +## The message will be processed by the global GdUnit message system and +## may be displayed in the test runner UI, logged to files, or handled +## by other registered message handlers. +## [br] +## [b][u]Example Usage:[/u][/b] +## [codeblock] +## # In a test hook +## func startup(session: GdUnitTestSession) -> GdUnitResult: +## session.send_message("Database connection established") +## return GdUnitResult.success() +## +## func shutdown(session: GdUnitTestSession) -> GdUnitResult: +## session.send_message("Generated test report: report.html") +## return GdUnitResult.success() +## ``` +## [/codeblock] +## [param message] The message text to send through the GdUnit messaging system +func send_message(message: String) -> void: + GdUnitSignals.instance().gdunit_message.emit(message) diff --git a/addons/gdUnit4/src/core/runners/GdUnitTestSession.gd.uid b/addons/gdUnit4/src/core/runners/GdUnitTestSession.gd.uid new file mode 100644 index 0000000..b2d6f7e --- /dev/null +++ b/addons/gdUnit4/src/core/runners/GdUnitTestSession.gd.uid @@ -0,0 +1 @@ +uid://b226hbcdds6ol diff --git a/addons/gdUnit4/src/core/runners/GdUnitTestSessionRunner.gd b/addons/gdUnit4/src/core/runners/GdUnitTestSessionRunner.gd new file mode 100644 index 0000000..6551e08 --- /dev/null +++ b/addons/gdUnit4/src/core/runners/GdUnitTestSessionRunner.gd @@ -0,0 +1,180 @@ +extends Node +## The base test runner implementation.[br] +## [br] +## This class provides the core functionality to execute test suites with following features:[br] +## - Loading and initialization of test suites[br] +## - Executing test suites and managing test states[br] +## - Event dispatching and test reporting[br] +## - Support for headless mode[br] +## - Plugin version verification[br] +## [br] +## Supported by specialized runners:[br] +## - [b]GdUnitTestRunner[/b]: Used in the editor, connects via tcp to report test results[br] +## - [b]GdUnitCLRunner[/b]: A command line interface runner, writes test reports to file[br] +## The test runner runs checked default in fail-fast mode, it stops checked first test failure. + +## Overall test run status codes used by the runners +const RETURN_SUCCESS = 0 +const RETURN_ERROR = 100 +const RETURN_ERROR_HEADLESS_NOT_SUPPORTED = 103 +const RETURN_ERROR_GODOT_VERSION_NOT_SUPPORTED = 104 +const RETURN_WARNING = 101 + +## Specifies the Node name under which the runner is registered +const GDUNIT_RUNNER = "GdUnitRunner" + +## The current runner configuration +@warning_ignore("unused_private_class_variable") +var _runner_config := GdUnitRunnerConfig.new() + +## The test suite executor instance +var _executor: GdUnitTestSuiteExecutor +var _hooks : GdUnitTestSessionHookService + +## Current runner state +var _state := READY + +## Current tests to be processed +var _test_cases: Array[GdUnitTestCase] = [] + + +## Configured report base path (can be set on CI test runner) +var report_base_path: String = GdUnitFileAccess.current_dir() + "reports": + get: + return report_base_path + + +## Current session report path +var report_path: String: + get: + return "%s/%s%d" % [report_base_path, GdUnitConstants.REPORT_DIR_PREFIX, current_report_history_index] + + +## Current report history index, if max_report_history > 1 we scan for the next index over the existing reports +var current_report_history_index: int: + get: + if max_report_history > 1: + return GdUnitFileAccess.find_last_path_index(report_base_path, GdUnitConstants.REPORT_DIR_PREFIX) + 1 + else: + return 1 + + +## Controls how many report historys will be hold +var max_report_history: int = GdUnitConstants.DEFAULT_REPORT_HISTORY_COUNT: + get: + return max_report_history + set(value): + max_report_history = value + + +# holds the current test session context +var _test_session: GdUnitTestSession + +## Runner state machine +enum { + READY, + INIT, + RUN, + STOP, + EXIT +} + +func _init() -> void: + if OS.get_cmdline_args().size() == 1: + DisplayServer.window_set_title("GdUnit4 Runner (Debug Mode)") + else: + DisplayServer.window_set_title("GdUnit4 Runner (Release Mode)") + if not Engine.is_embedded_in_editor(): + # minimize scene window checked debug mode + DisplayServer.window_set_mode(DisplayServer.WINDOW_MODE_MINIMIZED) + # store current runner instance to engine meta data to can be access in as a singleton + Engine.set_meta(GDUNIT_RUNNER, self) + + +# Called when the node enters the scene tree for the first time. +func _ready() -> void: + if Engine.get_version_info().hex < 0x40300: + printerr("The GdUnit4 plugin requires Godot version 4.3 or higher to run.") + quit(RETURN_ERROR_GODOT_VERSION_NOT_SUPPORTED) + return + _executor = GdUnitTestSuiteExecutor.new() + + GdUnitSignals.instance().gdunit_event.connect(_on_gdunit_event) + _state = INIT + + +func _notification(what: int) -> void: + if what == NOTIFICATION_PREDELETE: + Engine.remove_meta(GDUNIT_RUNNER) + + +## Main test runner loop. Is called every frame to manage the test execution. +func _process(_delta: float) -> void: + match _state: + INIT: + await init_runner() + RUN: + _hooks = GdUnitTestSessionHookService.instance() + _test_session = GdUnitTestSession.new(_test_cases, report_path) + GdUnitSignals.instance().gdunit_event.emit(GdUnitSessionStart.new()) + # process next test suite + set_process(false) + var result := await _hooks.execute_startup(_test_session) + if result.is_error(): + push_error(result.error_message()) + await _executor.run_and_wait(_test_cases) + result = await _hooks.execute_shutdown(_test_session) + if result.is_error(): + push_error(result.error_message()) + _state = STOP + set_process(true) + GdUnitSignals.instance().gdunit_event.emit(GdUnitSessionClose.new()) + cleanup_report_history() + STOP: + _state = EXIT + # give the engine small amount time to finish the rpc + await get_tree().create_timer(0.1).timeout + await quit(get_exit_code()) + + +## Used by the inheriting runners to initialize test execution +func init_runner() -> void: + await get_tree().process_frame + + +func cleanup_report_history() -> int: + return GdUnitFileAccess.delete_path_index_lower_equals_than( + report_path.get_base_dir(), + GdUnitConstants.REPORT_DIR_PREFIX, + current_report_history_index-1-max_report_history) + + +## Returns the exit code when the test run is finished.[br] +## Abstract method to be implemented by the inheriting runners. +func get_exit_code() -> int: + return RETURN_SUCCESS + + +## Quits the test runner with given exit code. +func quit(code: int) -> void: + await get_tree().process_frame + await get_tree().physics_frame + get_tree().quit(code) + + +func prints_warning(message: String) -> void: + prints(message) + + +## Default event handler to process test events.[br] +## Should be overridden by concrete runner implementation. +@warning_ignore("unused_parameter") +func _on_gdunit_event(event: GdUnitEvent) -> void: + pass + + +## Event bridge from C# GdUnit4.ITestEventListener.cs[br] +## Used to handle test events from C# tests. +# gdlint: disable=function-name +func PublishEvent(data: Dictionary) -> void: + _on_gdunit_event(GdUnitEvent.new().deserialize(data)) diff --git a/addons/gdUnit4/src/core/runners/GdUnitTestSessionRunner.gd.uid b/addons/gdUnit4/src/core/runners/GdUnitTestSessionRunner.gd.uid new file mode 100644 index 0000000..b1d904f --- /dev/null +++ b/addons/gdUnit4/src/core/runners/GdUnitTestSessionRunner.gd.uid @@ -0,0 +1 @@ +uid://bgud3b065w5xk diff --git a/addons/gdUnit4/src/core/templates/test_suite/GdUnitTestSuiteDefaultTemplate.gd b/addons/gdUnit4/src/core/templates/test_suite/GdUnitTestSuiteDefaultTemplate.gd new file mode 100644 index 0000000..20325ac --- /dev/null +++ b/addons/gdUnit4/src/core/templates/test_suite/GdUnitTestSuiteDefaultTemplate.gd @@ -0,0 +1,36 @@ +class_name GdUnitTestSuiteDefaultTemplate +extends RefCounted + + +const DEFAULT_TEMP_TS_GD =""" + # GdUnit generated TestSuite + class_name ${suite_class_name} + extends GdUnitTestSuite + @warning_ignore('unused_parameter') + @warning_ignore('return_value_discarded') + + # TestSuite generated from + const __source: String = '${source_resource_path}' +""" + + +const DEFAULT_TEMP_TS_CS = """ + // GdUnit generated TestSuite + + using Godot; + using GdUnit4; + + namespace ${name_space} + { + using static Assertions; + using static Utils; + + [TestSuite] + public class ${suite_class_name} + { + // TestSuite generated from + private const string sourceClazzPath = "${source_resource_path}"; + + } + } +""" diff --git a/addons/gdUnit4/src/core/templates/test_suite/GdUnitTestSuiteDefaultTemplate.gd.uid b/addons/gdUnit4/src/core/templates/test_suite/GdUnitTestSuiteDefaultTemplate.gd.uid new file mode 100644 index 0000000..9943422 --- /dev/null +++ b/addons/gdUnit4/src/core/templates/test_suite/GdUnitTestSuiteDefaultTemplate.gd.uid @@ -0,0 +1 @@ +uid://baybufpxkapuj diff --git a/addons/gdUnit4/src/core/templates/test_suite/GdUnitTestSuiteTemplate.gd b/addons/gdUnit4/src/core/templates/test_suite/GdUnitTestSuiteTemplate.gd new file mode 100644 index 0000000..6fc282d --- /dev/null +++ b/addons/gdUnit4/src/core/templates/test_suite/GdUnitTestSuiteTemplate.gd @@ -0,0 +1,144 @@ +class_name GdUnitTestSuiteTemplate +extends RefCounted + +const TEMPLATE_ID_GD = 1000 +const TEMPLATE_ID_CS = 2000 + +const SUPPORTED_TAGS_GD = """ + GdScript Tags are replaced when the test-suite is created. + + # The class name of the test-suite, formed from the source script. + ${suite_class_name} + # is used to build the test suite class name + class_name ${suite_class_name} + extends GdUnitTestSuite + + + # The class name in pascal case, formed from the source script. + ${source_class} + # can be used to create the class e.g. for source 'MyClass' + var my_test_class := ${source_class}.new() + # will be result in + var my_test_class := MyClass.new() + + # The class as variable name in snake case, formed from the source script. + ${source_var} + # Can be used to build the variable name e.g. for source 'MyClass' + var ${source_var} := ${source_class}.new() + # will be result in + var my_class := MyClass.new() + + # The full resource path from which the file was created. + ${source_resource_path} + # Can be used to load the script in your test + var my_script := load(${source_resource_path}) + # will be result in + var my_script := load("res://folder/my_class.gd") +""" + +const SUPPORTED_TAGS_CS = """ + C# Tags are replaced when the test-suite is created. + + // The namespace name of the test-suite + ${name_space} + namespace ${name_space} + + // The class name of the test-suite, formed from the source class. + ${suite_class_name} + // is used to build the test suite class name + [TestSuite] + public class ${suite_class_name} + + // The class name formed from the source class. + ${source_class} + // can be used to create the class e.g. for source 'MyClass' + private string myTestClass = new ${source_class}(); + // will be result in + private string myTestClass = new MyClass(); + + // The class as variable name in camelCase, formed from the source class. + ${source_var} + // Can be used to build the variable name e.g. for source 'MyClass' + private object ${source_var} = new ${source_class}(); + // will be result in + private object myClass = new MyClass(); + + // The full resource path from which the file was created. + ${source_resource_path} + // Can be used to load the script in your test + private object myScript = GD.Load(${source_resource_path}); + // will be result in + private object myScript = GD.Load("res://folder/MyClass.cs"); +""" + +const TAG_TEST_SUITE_CLASS = "${suite_class_name}" +const TAG_SOURCE_CLASS_NAME = "${source_class}" +const TAG_SOURCE_CLASS_VARNAME = "${source_var}" +const TAG_SOURCE_RESOURCE_PATH = "${source_resource_path}" + + +static func default_GD_template() -> String: + return GdUnitTestSuiteDefaultTemplate.DEFAULT_TEMP_TS_GD.dedent().trim_prefix("\n") + + +static func default_CS_template() -> String: + return GdUnitTestSuiteDefaultTemplate.DEFAULT_TEMP_TS_CS.dedent().trim_prefix("\n") + + +static func build_template(source_path: String) -> String: + var clazz_name :String = GdObjects.to_pascal_case(GdObjects.extract_class_name(source_path).value_as_string()) + var template: String = GdUnitSettings.get_setting(GdUnitSettings.TEMPLATE_TS_GD, default_GD_template()) + + return template\ + .replace(TAG_TEST_SUITE_CLASS, clazz_name+"Test")\ + .replace(TAG_SOURCE_RESOURCE_PATH, source_path)\ + .replace(TAG_SOURCE_CLASS_NAME, clazz_name)\ + .replace(TAG_SOURCE_CLASS_VARNAME, GdObjects.to_snake_case(clazz_name)) + + +static func default_template(template_id :int) -> String: + if template_id != TEMPLATE_ID_GD and template_id != TEMPLATE_ID_CS: + push_error("Invalid template '%d' id! Cant load testsuite template" % template_id) + return "" + if template_id == TEMPLATE_ID_GD: + return default_GD_template() + return default_CS_template() + + +static func load_template(template_id :int) -> String: + if template_id != TEMPLATE_ID_GD and template_id != TEMPLATE_ID_CS: + push_error("Invalid template '%d' id! Cant load testsuite template" % template_id) + return "" + if template_id == TEMPLATE_ID_GD: + return GdUnitSettings.get_setting(GdUnitSettings.TEMPLATE_TS_GD, default_GD_template()) + return GdUnitSettings.get_setting(GdUnitSettings.TEMPLATE_TS_CS, default_CS_template()) + + +static func save_template(template_id :int, template :String) -> void: + if template_id != TEMPLATE_ID_GD and template_id != TEMPLATE_ID_CS: + push_error("Invalid template '%d' id! Cant load testsuite template" % template_id) + return + if template_id == TEMPLATE_ID_GD: + GdUnitSettings.save_property(GdUnitSettings.TEMPLATE_TS_GD, template.dedent().trim_prefix("\n")) + elif template_id == TEMPLATE_ID_CS: + GdUnitSettings.save_property(GdUnitSettings.TEMPLATE_TS_CS, template.dedent().trim_prefix("\n")) + + +static func reset_to_default(template_id :int) -> void: + if template_id != TEMPLATE_ID_GD and template_id != TEMPLATE_ID_CS: + push_error("Invalid template '%d' id! Cant load testsuite template" % template_id) + return + if template_id == TEMPLATE_ID_GD: + GdUnitSettings.save_property(GdUnitSettings.TEMPLATE_TS_GD, default_GD_template()) + else: + GdUnitSettings.save_property(GdUnitSettings.TEMPLATE_TS_CS, default_CS_template()) + + +static func load_tags(template_id :int) -> String: + if template_id != TEMPLATE_ID_GD and template_id != TEMPLATE_ID_CS: + push_error("Invalid template '%d' id! Cant load testsuite template" % template_id) + return "Error checked loading tags" + if template_id == TEMPLATE_ID_GD: + return SUPPORTED_TAGS_GD + else: + return SUPPORTED_TAGS_CS diff --git a/addons/gdUnit4/src/core/templates/test_suite/GdUnitTestSuiteTemplate.gd.uid b/addons/gdUnit4/src/core/templates/test_suite/GdUnitTestSuiteTemplate.gd.uid new file mode 100644 index 0000000..c1e03a4 --- /dev/null +++ b/addons/gdUnit4/src/core/templates/test_suite/GdUnitTestSuiteTemplate.gd.uid @@ -0,0 +1 @@ +uid://uoqauoy145rq diff --git a/addons/gdUnit4/src/core/thread/GdUnitThreadContext.gd b/addons/gdUnit4/src/core/thread/GdUnitThreadContext.gd new file mode 100644 index 0000000..f2b2672 --- /dev/null +++ b/addons/gdUnit4/src/core/thread/GdUnitThreadContext.gd @@ -0,0 +1,66 @@ +class_name GdUnitThreadContext +extends RefCounted + +var _thread :Thread +var _thread_name :String +var _thread_id :int +var _signal_collector :GdUnitSignalCollector +var _execution_context :GdUnitExecutionContext +var _asserts := [] + + +func _init(thread :Thread = null) -> void: + if thread != null: + _thread = thread + _thread_name = thread.get_meta("name") + _thread_id = thread.get_id() as int + else: + _thread_name = "main" + _thread_id = OS.get_main_thread_id() + _signal_collector = GdUnitSignalCollector.new() + + +func dispose() -> void: + clear_assert() + if is_instance_valid(_signal_collector): + _signal_collector.clear() + _signal_collector = null + _execution_context = null + _thread = null + + +func clear_assert() -> void: + _asserts.clear() + + +func set_assert(value :GdUnitAssert) -> void: + if value != null: + _asserts.append(value) + + +func get_assert() -> GdUnitAssert: + return null if _asserts.is_empty() else _asserts[-1] + + +func set_execution_context(context :GdUnitExecutionContext) -> void: + _execution_context = context + + +func get_execution_context() -> GdUnitExecutionContext: + return _execution_context + + +func get_execution_context_id() -> int: + return _execution_context.get_instance_id() + + +func get_signal_collector() -> GdUnitSignalCollector: + return _signal_collector + + +func thread_id() -> int: + return _thread_id + + +func _to_string() -> String: + return "ThreadContext <%s>: %s " % [_thread_name, _thread_id] diff --git a/addons/gdUnit4/src/core/thread/GdUnitThreadContext.gd.uid b/addons/gdUnit4/src/core/thread/GdUnitThreadContext.gd.uid new file mode 100644 index 0000000..ad1793d --- /dev/null +++ b/addons/gdUnit4/src/core/thread/GdUnitThreadContext.gd.uid @@ -0,0 +1 @@ +uid://bjlnokn0yw1qk diff --git a/addons/gdUnit4/src/core/thread/GdUnitThreadManager.gd b/addons/gdUnit4/src/core/thread/GdUnitThreadManager.gd new file mode 100644 index 0000000..31b1078 --- /dev/null +++ b/addons/gdUnit4/src/core/thread/GdUnitThreadManager.gd @@ -0,0 +1,64 @@ +## A manager to run new thread and crate a ThreadContext shared over the actual test run +class_name GdUnitThreadManager +extends Object + +## { = } +var _thread_context_by_id := {} +## holds the current thread id +var _current_thread_id :int = -1 + +func _init() -> void: + # add initail the main thread + _current_thread_id = OS.get_thread_caller_id() + _thread_context_by_id[OS.get_main_thread_id()] = GdUnitThreadContext.new() + + +static func instance() -> GdUnitThreadManager: + return GdUnitSingleton.instance("GdUnitThreadManager", func() -> GdUnitThreadManager: return GdUnitThreadManager.new()) + + +## Runs a new thread by given name and Callable.[br] +## A new GdUnitThreadContext is created, which is used for the actual test execution.[br] +## We need this custom implementation while this bug is not solved +## Godot issue https://github.com/godotengine/godot/issues/79637 +static func run(name :String, cb :Callable) -> Variant: + return await instance()._run(name, cb) + + +## Returns the current valid thread context +static func get_current_context() -> GdUnitThreadContext: + return instance()._get_current_context() + + +func _run(name :String, cb :Callable) -> Variant: + # we do this hack because of `OS.get_thread_caller_id()` not returns the current id + # when await process_frame is called inside the fread + var save_current_thread_id := _current_thread_id + var thread := Thread.new() + thread.set_meta("name", name) + @warning_ignore("return_value_discarded") + thread.start(cb) + _current_thread_id = thread.get_id() as int + _register_thread(thread, _current_thread_id) + var result :Variant = await thread.wait_to_finish() + _unregister_thread(_current_thread_id) + # restore original thread id + _current_thread_id = save_current_thread_id + return result + + +func _register_thread(thread :Thread, thread_id :int) -> void: + var context := GdUnitThreadContext.new(thread) + _thread_context_by_id[thread_id] = context + + +func _unregister_thread(thread_id :int) -> void: + var context: GdUnitThreadContext = _thread_context_by_id.get(thread_id) + if context: + @warning_ignore("return_value_discarded") + _thread_context_by_id.erase(thread_id) + context.dispose() + + +func _get_current_context() -> GdUnitThreadContext: + return _thread_context_by_id.get(_current_thread_id) diff --git a/addons/gdUnit4/src/core/thread/GdUnitThreadManager.gd.uid b/addons/gdUnit4/src/core/thread/GdUnitThreadManager.gd.uid new file mode 100644 index 0000000..9c362b2 --- /dev/null +++ b/addons/gdUnit4/src/core/thread/GdUnitThreadManager.gd.uid @@ -0,0 +1 @@ +uid://gkgkkauw35f6 diff --git a/addons/gdUnit4/src/core/writers/GdUnitCSIMessageWriter.gd b/addons/gdUnit4/src/core/writers/GdUnitCSIMessageWriter.gd new file mode 100644 index 0000000..be5d1e5 --- /dev/null +++ b/addons/gdUnit4/src/core/writers/GdUnitCSIMessageWriter.gd @@ -0,0 +1,227 @@ +@tool +class_name GdUnitCSIMessageWriter +extends GdUnitMessageWritter +## A message writer implementation using ANSI/CSI escape codes for console output.[br] +## [br] +## This writer provides formatted message output using CSI (Control Sequence Introducer) codes.[br] +## It supports:[br] +## - Color using RGB values[br] +## - Text styles (bold, italic, underline)[br] +## - Cursor positioning and text alignment[br] +## [br] +## Used primarily for console-based test execution and CI/CD environments. + + +enum { + COLOR_TABLE, + COLOR_RGB +} + +const CSI_BOLD = "" +const CSI_ITALIC = "" +const CSI_UNDERLINE = "" +const CSI_RESET = "" + +# Control Sequence Introducer +var _debug_show_color_codes := false +var _color_mode := COLOR_TABLE + +## Current cursor position in the line +var _current_pos := 0 + +# Pre-compiled regex patterns for tag matching +var _tag_regex: RegEx + + +## Constructs CSI style codes based on flags.[br] +## [br] +## [param flags] The style flags to apply (BOLD, ITALIC, UNDERLINE).[br] +## Returns the corresponding CSI codes. +func _apply_style_flags(flags: int) -> String: + var _style := "" + if flags & BOLD: + _style += CSI_BOLD + if flags & ITALIC: + _style += CSI_ITALIC + if flags & UNDERLINE: + _style += CSI_UNDERLINE + return _style + + +## Converts a color string (named or hex) to a Color object +func _parse_color(color_str: String) -> Color: + return Color.from_string(color_str.strip_edges().to_lower(), Color.WHITE) + + +## Generates CSI color code for foreground color +func _color_to_csi_fg(c: Color) -> String: + return "[38;2;%d;%d;%dm" % [c.r8 * c.a, c.g8 * c.a, c.b8 * c.a] + + +## Generates CSI color code for background color +func _color_to_csi_bg(c: Color) -> String: + return "[48;2;%d;%d;%dm" % [c.r8 * c.a, c.g8 * c.a, c.b8 * c.a] + + +func _init_regex_patterns() -> void: + if not _tag_regex: + _tag_regex = RegEx.new() + # Match all richtext tags: [tag], [tag=value], [/tag] + _tag_regex.compile(r"\[/?(?:color|bgcolor|b|i|u)(?:=[^\]]+)?\]") + + +func _extract_color_from_tag(tag: String, tag_assign: String) -> Color: + var tag_assign_length := tag_assign.length() + var color_value := tag.substr(tag_assign_length, tag.length() - tag_assign_length - 1) + return _parse_color(color_value) + + +## Optimized richtext to CSI conversion using regex and lookup processing +func _bbcode_tags_to_csi_codes(message: String) -> String: + _init_regex_patterns() + + var result := "" + var last_pos := 0 + var color_stack: Array[Color] = [] + var bgcolor_stack: Array[Color] = [] + + # Find all richtext tags + var matches := _tag_regex.search_all(message) + + for match in matches: + var start_pos := match.get_start() + var end_pos := match.get_end() + var tag := match.get_string(0) + + # Add text before this tag + result += message.substr(last_pos, start_pos - last_pos) + + # Process the tag + if tag.begins_with("[color="): + var fg_color := _extract_color_from_tag(tag, "[color=") + color_stack.push_back(fg_color) + result += _color_to_csi_fg(fg_color) + elif tag.begins_with("[bgcolor="): + var bg_color := _extract_color_from_tag(tag, "[bgcolor=") + bgcolor_stack.push_back(bg_color) + result += _color_to_csi_bg(bg_color) + elif tag == "[b]": + result += CSI_BOLD + elif tag == "[i]": + result += CSI_ITALIC + elif tag == "[u]": + result += CSI_UNDERLINE + elif tag == "[/color]": + result += CSI_RESET + if color_stack.size() > 0: + color_stack.pop_back() + # Restore remaining styles and colors + if color_stack.size() > 0: + result += _color_to_csi_fg(color_stack[-1]) + if bgcolor_stack.size() > 0: + result += _color_to_csi_bg(bgcolor_stack[-1]) + elif tag == "[/bgcolor]": + result += CSI_RESET + if bgcolor_stack.size() > 0: + bgcolor_stack.pop_back() + # Restore remaining styles and colors + if color_stack.size() > 0: + result += _color_to_csi_fg(color_stack[-1]) + if bgcolor_stack.size() > 0: + result += _color_to_csi_bg(bgcolor_stack[-1]) + elif tag in ["[/b]", "[/i]", "[/u]"]: + result += CSI_RESET + # Restore remaining colors after style reset + if color_stack.size() > 0: + result += _color_to_csi_fg(color_stack[-1]) + if bgcolor_stack.size() > 0: + result += _color_to_csi_bg(bgcolor_stack[-1]) + + last_pos = end_pos + + # Add remaining text after last tag + result += message.substr(last_pos) + + return result + + +## Implementation of basic message output with formatting. +func _print_message(_message: String, _color: Color, _indent: int, _flags: int) -> void: + var text := _bbcode_tags_to_csi_codes(_message) + var indent_text := "".lpad(_indent * 2) + var _style := _apply_style_flags(_flags) + printraw("%s[38;2;%d;%d;%dm%s%s" % [indent_text, _color.r8, _color.g8, _color.b8, _style, text] ) + _current_pos += _indent * 2 + text.length() + + +## Implementation of line-ending message output with formatting. +func _println_message(_message: String, _color: Color, _indent: int, _flags: int) -> void: + _print_message(_message, _color, _indent, _flags) + prints() + _current_pos = 0 + + +## Implementation of positioned message output with formatting. +func _print_at(_message: String, cursor_pos: int, _color: Color, _effect: Effect, _align: Align, _flags: int) -> void: + if _align == Align.RIGHT: + cursor_pos = cursor_pos - _message.length() + + if cursor_pos > _current_pos: + printraw("[%dG" % cursor_pos) # Move cursor to absolute position + else: + _message = " " + _message + + var _style := _apply_style_flags(_flags) + printraw("[38;2;%d;%d;%dm%s%s" % [_color.r8, _color.g8, _color.b8, _style, _message] ) + _current_pos = cursor_pos + _message.length() + + +## Writes a line break and returns self for chaining. +func new_line() -> GdUnitCSIMessageWriter: + prints() + return self + + +## Saves the current cursor position.[br] +## Returns self for chaining. +func save_cursor() -> GdUnitCSIMessageWriter: + printraw("") + return self + + +## Restores previously saved cursor position.[br] +## Returns self for chaining. +func restore_cursor() -> GdUnitCSIMessageWriter: + printraw("") + return self + + +## Clears screen content and resets cursor position. +func clear() -> void: + printraw("") # Clear screen and move cursor to home + _current_pos = 0 + + +## Debug method to display the available color table.[br] +## Shows both 6x6x6 color cube and RGB color modes. +@warning_ignore("return_value_discarded") +func _print_color_table() -> void: + color(Color.ANTIQUE_WHITE).println_message("Color Table 6x6x6") + _debug_show_color_codes = true + for green in range(0, 6): + for red in range(0, 6): + for blue in range(0, 6): + color(Color8(red*42, green*42, blue*42)).println_message("████████ ") + new_line() + new_line() + + color(Color.ANTIQUE_WHITE).println_message("Color Table RGB") + _color_mode = COLOR_RGB + for green in range(0, 6): + for red in range(0, 6): + for blue in range(0, 6): + color(Color8(red*42, green*42, blue*42)).println_message("████████ ") + new_line() + new_line() + _color_mode = COLOR_TABLE + _debug_show_color_codes = false diff --git a/addons/gdUnit4/src/core/writers/GdUnitCSIMessageWriter.gd.uid b/addons/gdUnit4/src/core/writers/GdUnitCSIMessageWriter.gd.uid new file mode 100644 index 0000000..6207e63 --- /dev/null +++ b/addons/gdUnit4/src/core/writers/GdUnitCSIMessageWriter.gd.uid @@ -0,0 +1 @@ +uid://bi11ifvk4kpiu diff --git a/addons/gdUnit4/src/core/writers/GdUnitMessageWriter.gd b/addons/gdUnit4/src/core/writers/GdUnitMessageWriter.gd new file mode 100644 index 0000000..2ae94a4 --- /dev/null +++ b/addons/gdUnit4/src/core/writers/GdUnitMessageWriter.gd @@ -0,0 +1,214 @@ +@tool +class_name GdUnitMessageWritter +extends RefCounted +## Base interface class for writing formatted messages to different outputs.[br] +## [br] +## This class defines the interface and common functionality for writing formatted messages.[br] +## It provides a fluent API for message formatting and supports different output targets.[br] +## [br] +## The class provides formatting options for:[br] +## - Text colors[br] +## - Text styles (bold, italic, underline)[br] +## - Text effects (e.g., wave)[br] +## - Text alignment[br] +## - Indentation[br] +## [br] +## Two concrete implementations are available:[br] +## - [GdUnitRichTextMessageWriter] writing to a [RichTextLabel][br] +## - [GdUnitCSIMessageWriter] writing to console using CSI codes[br] +## [br] +## Example usage:[br] +## [codeblock] +## writer.color(Color.RED).style(BOLD).println_message("Test failed!") +## writer.color(Color.GREEN).align(Align.RIGHT).print_at("Success", 80) +## [/codeblock] + + +## Text style flag for bold formatting +const BOLD = 0x1 +## Text style flag for italic formatting +const ITALIC = 0x2 +## Text style flag for underline formatting +const UNDERLINE = 0x4 + + +## Represents special text effects that can be applied to the output +enum Effect { + ## No special effect applied + NONE, + ## Applies a wave animation to the text + WAVE +} + + +## Controls text alignment at the specified cursor position +enum Align { + ## Aligns text to the left of the cursor position + LEFT, + ## Aligns text to the right of the cursor position, accounting for text length + RIGHT +} + + +## The current text color to be used for the next output operation +var _current_color := Color.WHITE + +## The current indentation level to be used for the next output operation.[br] +## Each level represents two spaces of indentation. +var _current_indent := 0 + +## The current text style flags (BOLD, ITALIC, UNDERLINE) to be used for the next output operation +var _current_flags := 0 + +## The current text alignment to be used for the next output operation +var _current_align := Align.LEFT + +## The current text effect to be used for the next output operation +var _current_effect := Effect.NONE + + +## Sets the text color for the next output operation.[br] +## [br] +## [param value] The color to be used for the text. +## Returns self for method chaining. +func color(value: Color) -> GdUnitMessageWritter: + _current_color = value + return self + + +## Sets the indentation level for the next output operation.[br] +## [br] +## [param value] The number of indentation levels, where each level equals two spaces. +## Returns self for method chaining. +func indent(value: int) -> GdUnitMessageWritter: + _current_indent = value + return self + + +## Sets text style flags for the next output operation.[br] +## [br] +## [param value] A combination of style flags (BOLD, ITALIC, UNDERLINE). +## Returns self for method chaining. +func style(value: int) -> GdUnitMessageWritter: + _current_flags = value + return self + + +## Sets text effect for the next output operation.[br] +## [br] +## [param value] The effect to apply to the text (NONE, WAVE). +## Returns self for method chaining. +func effect(value: Effect) -> GdUnitMessageWritter: + _current_effect = value + return self + + +## Sets text alignment for the next output operation.[br] +## [br] +## [param value] The alignment to use (LEFT, RIGHT). +## Returns self for method chaining. +func align(value: Align) -> GdUnitMessageWritter: + _current_align = value + return self + + +## Resets all formatting options to their default values.[br] +## [br] +## Defaults:[br] +## - color: Color.WHITE[br] +## - indent: 0[br] +## - flags: 0[br] +## - align: LEFT[br] +## - effect: NONE[br] +## Returns self for method chaining. +func reset() -> GdUnitMessageWritter: + _current_color = Color.WHITE + _current_indent = 0 + _current_flags = 0 + _current_align = Align.LEFT + _current_effect = Effect.NONE + return self + + +## Prints a warning message in golden color.[br] +## [br] +## [param message] The warning message to print. +func prints_warning(message: String) -> void: + color(Color.GOLDENROD).println_message(message) + + +## Prints an error message in crimson color.[br] +## [br] +## [param message] The error message to print. +func prints_error(message: String) -> void: + color(Color.CRIMSON).println_message(message) + + +## Prints a message with current formatting settings.[br] +## [br] +## [param message] The text to print. +func print_message(message: String) -> void: + _print_message(message, _current_color, _current_indent, _current_flags) + reset() + + +## Prints a message with current formatting settings followed by a newline.[br] +## [br] +## [param message] The text to print. +func println_message(message: String) -> void: + _println_message(message, _current_color, _current_indent, _current_flags) + reset() + + +## Prints a message at a specific column position with current formatting settings.[br] +## [br] +## [param message] The text to print.[br] +## [param cursor_pos] The column position where the text should start. +func print_at(message: String, cursor_pos: int) -> void: + _print_at(message, cursor_pos, _current_color, _current_effect, _current_align, _current_flags) + reset() + + +## Internal implementation of print_message.[br] +## [br] +## To be overridden by concrete formatters.[br] +## [br] +## [param message] The text to print.[br] +## [param color] The color to use.[br] +## [param indent] The indentation level.[br] +## [param flags] The style flags to apply. +func _print_message(_message: String, _color: Color, _indent: int, _flags: int) -> void: + pass + + +## Internal implementation of println_message.[br] +## [br] +## To be overridden by concrete formatters.[br] +## [br] +## [param message] The text to print.[br] +## [param color] The color to use.[br] +## [param indent] The indentation level.[br] +## [param flags] The style flags to apply. +func _println_message(_message: String, _color: Color, _indent: int, _flags: int) -> void: + pass + + +## Internal implementation of print_at.[br] +## [br] +## To be overridden by concrete formatters.[br] +## [br] +## [param message] The text to print.[br] +## [param cursor_pos] The column position.[br] +## [param color] The color to use.[br] +## [param effect] The effect to apply.[br] +## [param align] The text alignment.[br] +## [param flags] The style flags to apply. +func _print_at(_message: String, _cursor_pos: int, _color: Color, _effect: Effect, _align: Align, _flags: int) -> void: + pass + + +## Clears all output content.[br] +## [br] +## To be overridden by concrete formatters. +func clear() -> void: + pass diff --git a/addons/gdUnit4/src/core/writers/GdUnitMessageWriter.gd.uid b/addons/gdUnit4/src/core/writers/GdUnitMessageWriter.gd.uid new file mode 100644 index 0000000..bdc75ab --- /dev/null +++ b/addons/gdUnit4/src/core/writers/GdUnitMessageWriter.gd.uid @@ -0,0 +1 @@ +uid://7gshpv8p7axc diff --git a/addons/gdUnit4/src/core/writers/GdUnitRichTextMessageWriter.gd b/addons/gdUnit4/src/core/writers/GdUnitRichTextMessageWriter.gd new file mode 100644 index 0000000..64793bb --- /dev/null +++ b/addons/gdUnit4/src/core/writers/GdUnitRichTextMessageWriter.gd @@ -0,0 +1,115 @@ +@tool +class_name GdUnitRichTextMessageWriter +extends GdUnitMessageWritter +## A message writer implementation using [RichTextLabel] for the test report UI.[br] +## [br] +## This writer implementation writes formatted messages to a [RichTextLabel] using BBCode.[br] +## It supports:[br] +## - Text formatting using BBCode (bold, italic, underline)[br] +## - Text coloring using push colors[br] +## - Text indentation using push indent[br] +## - Text effects like wave[br] +## - Basic cursor positioning[br] +## [br] +## Used to format test reports in the editor UI. + + +## The [RichTextLabel] instance to write formatted messages +var _output: RichTextLabel + +## Tracks current position in characters from line start +var _current_pos := 0 + + +## Creates a new message writer for the given [RichTextLabel].[br] +## [br] +## [param output] The [RichTextLabel] used for output. +func _init(output: RichTextLabel) -> void: + _output = output + + +## Applies text style flags by wrapping text in BBCode tags.[br] +## [br] +## Available styles:[br] +## - BOLD: [b]text[/b][br] +## - ITALIC: [i]text[/i][br] +## - UNDERLINE: [u]text[/u][br] +## [br] +## [param message] The text to format.[br] +## [param flags] The text style flags to apply. +func _apply_flags(message: String, flags: int) -> String: + if flags & BOLD: + message = "[b]%s[/b]" % message + if flags & ITALIC: + message = "[i]%s[/i]" % message + if flags & UNDERLINE: + message = "[u]%s[/u]" % message + return message + + +## Writes a message with formatting.[br] +## [br] +## [param message] The text to write.[br] +## [param _color] The color to use.[br] +## [param _indent] The indentation level.[br] +## [param flags] The text style flags to apply. +func _print_message(message: String, _color: Color, _indent: int, flags: int) -> void: + for i in _indent: + _output.push_indent(1) + _output.push_color(_color) + message = _apply_flags(message, flags) + _output.append_text(message) + _output.pop() + for i in _indent: + _output.pop() + _current_pos += _indent * 2 + message.length() + + +## Writes a message with formatting followed by a line break.[br] +## [br] +## [param message] The text to write.[br] +## [param _color] The color to use.[br] +## [param _indent] The indentation level.[br] +## [param flags] The text style flags to apply. +func _println_message(message: String, _color: Color, _indent: int, flags: int) -> void: + _print_message(message, _color, _indent, flags) + _output.newline() + _current_pos = 0 + + +## Writes a message at a specific column position.[br] +## [br] +## [param message] The text to write.[br] +## [param cursor_pos] The column position from line start.[br] +## [param _color] The color to use.[br] +## [param _effect] The text effect to apply (e.g. wave).[br] +## [param _align] The text alignment (left or right).[br] +## [param flags] The text style flags to apply. +func _print_at(message: String, cursor_pos: int, _color: Color, _effect: Effect, _align: Align, flags: int) -> void: + if _align == Align.RIGHT: + cursor_pos = cursor_pos - message.length() + + var spaces := cursor_pos - _current_pos + if spaces > 0: + _output.append_text("".lpad(spaces)) + _current_pos += spaces + else: + _output.append_text(" ") + _current_pos += 1 + + _output.push_color(_color) + message = _apply_flags(message, flags) + match _effect: + Effect.NONE: + pass + Effect.WAVE: + message = "[wave]%s[/wave]" % message + _output.append_text(message) + _output.pop() + _current_pos += message.length() + + +## Clears all written content from the [RichTextLabel]. +func clear() -> void: + _output.clear() + _current_pos = 0 diff --git a/addons/gdUnit4/src/core/writers/GdUnitRichTextMessageWriter.gd.uid b/addons/gdUnit4/src/core/writers/GdUnitRichTextMessageWriter.gd.uid new file mode 100644 index 0000000..a1e8f98 --- /dev/null +++ b/addons/gdUnit4/src/core/writers/GdUnitRichTextMessageWriter.gd.uid @@ -0,0 +1 @@ +uid://cq5njkjk7o6j0 diff --git a/addons/gdUnit4/src/dotnet/GdUnit4CSharpApi.cs b/addons/gdUnit4/src/dotnet/GdUnit4CSharpApi.cs new file mode 100644 index 0000000..14a1355 --- /dev/null +++ b/addons/gdUnit4/src/dotnet/GdUnit4CSharpApi.cs @@ -0,0 +1,216 @@ +// Copyright (c) 2025 Mike Schulze +// MIT License - See LICENSE file in the repository root for full license text +#pragma warning disable IDE1006 +namespace gdUnit4.addons.gdUnit4.src.dotnet; +#pragma warning restore IDE1006 + +#if GDUNIT4NET_API_V5 +using System; +using System.Collections.Generic; +using System.Diagnostics; +using System.Linq; +using System.Threading; +using System.Threading.Tasks; + +using GdUnit4; +using GdUnit4.Api; + +using Godot; +using Godot.Collections; + +/// +/// The GdUnit4 GDScript - C# API wrapper. +/// +public partial class GdUnit4CSharpApi : GdUnit4NetApiGodotBridge +{ + /// + /// The signal to be emitted when the execution is completed. + /// + [Signal] +#pragma warning disable CA1711 + public delegate void ExecutionCompletedEventHandler(); +#pragma warning restore CA1711 + +#pragma warning disable CA2213, SA1201 + private CancellationTokenSource? executionCts; +#pragma warning restore CA2213, SA1201 + + /// + /// Indicates if the API loaded. + /// + /// Returns true if the API already loaded. + public static bool IsApiLoaded() + => true; + + /// + /// Runs test discovery on the given script. + /// + /// The script to be scanned. + /// The list of tests discovered as dictionary. + public static Array DiscoverTests(CSharpScript sourceScript) + { + try + { + // Get the list of test case descriptors from the API + var testCaseDescriptors = DiscoverTestsFromScript(sourceScript); + + // Convert each TestCaseDescriptor to a Dictionary + return testCaseDescriptors + .Select(descriptor => new Dictionary + { + ["guid"] = descriptor.Id.ToString(), + ["managed_type"] = descriptor.ManagedType, + ["test_name"] = descriptor.ManagedMethod, + ["source_file"] = sourceScript.ResourcePath, + ["line_number"] = descriptor.LineNumber, + ["attribute_index"] = descriptor.AttributeIndex, + ["require_godot_runtime"] = descriptor.RequireRunningGodotEngine, + ["code_file_path"] = descriptor.CodeFilePath ?? string.Empty, + ["simple_name"] = descriptor.SimpleName, + ["fully_qualified_name"] = descriptor.FullyQualifiedName, + ["assembly_location"] = descriptor.AssemblyPath + }) + .Aggregate(new Array(), (array, dict) => + { + array.Add(dict); + return array; + }); + } +#pragma warning disable CA1031 + catch (Exception e) +#pragma warning restore CA1031 + { + GD.PrintErr($"Error discovering tests: {e.Message}\n{e.StackTrace}"); +#pragma warning disable IDE0028 // Do not catch general exception types + return new Array(); +#pragma warning restore IDE0028 // Do not catch general exception types + } + } + + /// + public override void _Notification(int what) + { + if (what != NotificationPredelete) + return; + executionCts?.Dispose(); + executionCts = null; + } + + /// + /// Executes the tests and using the listener for reporting the results. + /// + /// A list of tests to be executed. + /// The listener to report the results. + public void ExecuteAsync(Array tests, Callable listener) + { + try + { + // Cancel any ongoing execution + executionCts?.Cancel(); + executionCts?.Dispose(); + + // Create new cancellation token source + executionCts = new CancellationTokenSource(); + + Debug.Assert(tests != null, nameof(tests) + " != null"); + var testSuiteNodes = new List { BuildTestSuiteNodeFrom(tests) }; + ExecuteAsync(testSuiteNodes, listener, executionCts.Token) + .GetAwaiter() + .OnCompleted(() => EmitSignal(SignalName.ExecutionCompleted)); + } +#pragma warning disable CA1031 + catch (Exception e) +#pragma warning restore CA1031 + { + GD.PrintErr($"Error executing tests: {e.Message}\n{e.StackTrace}"); + Task.Run(() => { }).GetAwaiter().OnCompleted(() => EmitSignal(SignalName.ExecutionCompleted)); + } + } + + /// + /// Will cancel the current test execution. + /// + public void CancelExecution() + { + try + { + executionCts?.Cancel(); + } +#pragma warning disable CA1031 + catch (Exception e) +#pragma warning restore CA1031 + { + GD.PrintErr($"Error cancelling execution: {e.Message}"); + } + } + + // Convert a set of Tests stored as Dictionaries to TestSuiteNode + // all tests are assigned to a single test suit + internal static TestSuiteNode BuildTestSuiteNodeFrom(Array tests) + { + if (tests.Count == 0) + throw new InvalidOperationException("Cant build 'TestSuiteNode' from an empty test set."); + + // Create a suite ID + var suiteId = Guid.NewGuid(); + var firstTest = tests[0]; + var managedType = firstTest["managed_type"].AsString(); + var assemblyLocation = firstTest["assembly_location"].AsString(); + var sourceFile = firstTest["source_file"].AsString(); + + // Create TestCaseNodes for each test in the suite + var testCaseNodes = tests + .Select(test => new TestCaseNode + { + Id = Guid.Parse(test["guid"].AsString()), + ParentId = suiteId, + ManagedMethod = test["test_name"].AsString(), + LineNumber = test["line_number"].AsInt32(), + AttributeIndex = test["attribute_index"].AsInt32(), + RequireRunningGodotEngine = test["require_godot_runtime"].AsBool() + }) + .ToList(); + + return new TestSuiteNode + { + Id = suiteId, + ParentId = Guid.Empty, + ManagedType = managedType, + AssemblyPath = assemblyLocation, + SourceFile = sourceFile, + Tests = testCaseNodes + }; + } +} +#else +using Godot; +using Godot.Collections; + +public partial class GdUnit4CSharpApi : RefCounted +{ + [Signal] + public delegate void ExecutionCompletedEventHandler(); + + public static bool IsApiLoaded() + { + GD.PushWarning("No `gdunit4.api` dependency found, check your project dependencies."); + return false; + } + + + public static string Version() + => "Unknown"; + + public static Array DiscoverTests(CSharpScript sourceScript) => new(); + + public void ExecuteAsync(Array tests, Callable listener) + { + } + + public static bool IsTestSuite(CSharpScript script) + => false; + + public static Dictionary CreateTestSuite(string sourcePath, int lineNumber, string testSuitePath) + => new(); +} +#endif diff --git a/addons/gdUnit4/src/dotnet/GdUnit4CSharpApi.cs.uid b/addons/gdUnit4/src/dotnet/GdUnit4CSharpApi.cs.uid new file mode 100644 index 0000000..b1d6468 --- /dev/null +++ b/addons/gdUnit4/src/dotnet/GdUnit4CSharpApi.cs.uid @@ -0,0 +1 @@ +uid://bxyytita82ppo diff --git a/addons/gdUnit4/src/dotnet/GdUnit4CSharpApiLoader.gd b/addons/gdUnit4/src/dotnet/GdUnit4CSharpApiLoader.gd new file mode 100644 index 0000000..3d8ba25 --- /dev/null +++ b/addons/gdUnit4/src/dotnet/GdUnit4CSharpApiLoader.gd @@ -0,0 +1,114 @@ +## GdUnit4CSharpApiLoader +## +## A bridge class that handles communication between GDScript and C# for the GdUnit4 testing framework. +## This loader acts as a compatibility layer to safely access the .NET API and ensure that calls +## only proceed when the .NET environment is properly configured and available. +## [br] +## The class handles: +## - Verification of .NET runtime availability +## - Loading the C# wrapper script +## - Checking for the GdUnit4Api assembly +## - Providing proxy methods to access GdUnit4 functionality in C# +@static_unload +class_name GdUnit4CSharpApiLoader +extends RefCounted + +## Cached reference to the loaded C# wrapper script +static var _gdUnit4NetWrapper: Script + +## Cached instance of the API (singleton pattern) +static var _api_instance: RefCounted + + +class TestEventListener extends RefCounted: + + func publish_event(event: Dictionary) -> void: + var test_event := GdUnitEvent.new().deserialize(event) + GdUnitSignals.instance().gdunit_event.emit(test_event) + +static var _test_event_listener := TestEventListener.new() + + +## Returns an instance of the GdUnit4CSharpApi wrapper.[br] +## @return Script: The loaded C# wrapper or null if .NET is not supported +static func instance() -> Script: + if not GdUnit4CSharpApiLoader.is_api_loaded(): + return null + + return _gdUnit4NetWrapper + + +## Returns or creates a single instance of the API [br] +## This improves performance by reusing the same object +static func api_instance() -> RefCounted: + if _api_instance == null and is_api_loaded(): + @warning_ignore("unsafe_method_access") + _api_instance = instance().new() + return _api_instance + + +static func is_engine_version_supported(engine_version: int = Engine.get_version_info().hex) -> bool: + return engine_version >= 0x40200 + + +## Checks if the .NET environment is properly configured and available.[br] +## @return bool: True if .NET is fully supported and the assembly is found +static func is_api_loaded() -> bool: + # If the wrapper is already loaded we don't need to check again + if _gdUnit4NetWrapper != null: + return true + + # First we check if this is a Godot .NET runtime instance + if not ClassDB.class_exists("CSharpScript") or not is_engine_version_supported(): + return false + # Second we check the C# project file exists + var assembly_name: String = ProjectSettings.get_setting("dotnet/project/assembly_name") + if assembly_name.is_empty() or not FileAccess.file_exists("res://%s.csproj" % assembly_name): + return false + + # Finally load the wrapper and check if the GdUnit4 assembly can be found + _gdUnit4NetWrapper = load("res://addons/gdUnit4/src/dotnet/GdUnit4CSharpApi.cs") + @warning_ignore("unsafe_method_access") + return _gdUnit4NetWrapper.call("IsApiLoaded") + + +## Returns the version of the GdUnit4 .NET assembly.[br] +## @return String: The version string or "unknown" if .NET is not supported +static func version() -> String: + if not GdUnit4CSharpApiLoader.is_api_loaded(): + return "unknown" + @warning_ignore("unsafe_method_access") + return instance().Version() + + +static func discover_tests(source_script: Script) -> Array[GdUnitTestCase]: + var tests: Array = _gdUnit4NetWrapper.call("DiscoverTests", source_script) + + return Array(tests.map(GdUnitTestCase.from_dict), TYPE_OBJECT, "RefCounted", GdUnitTestCase) + + +static func execute(tests: Array[GdUnitTestCase]) -> void: + var net_api := api_instance() + if net_api == null: + push_warning("Execute C# tests not supported!") + return + var tests_as_dict: Array[Dictionary] = Array(tests.map(GdUnitTestCase.to_dict), TYPE_DICTIONARY, "", null) + + net_api.call("ExecuteAsync", tests_as_dict, _test_event_listener.publish_event) + @warning_ignore("unsafe_property_access") + await net_api.ExecutionCompleted + + +static func create_test_suite(source_path: String, line_number: int, test_suite_path: String) -> GdUnitResult: + if not GdUnit4CSharpApiLoader.is_api_loaded(): + return GdUnitResult.error("Can't create test suite. No .NET support found.") + @warning_ignore("unsafe_method_access") + var result: Dictionary = instance().CreateTestSuite(source_path, line_number, test_suite_path) + if result.has("error"): + return GdUnitResult.error(str(result.get("error"))) + return GdUnitResult.success(result) + + +static func is_csharp_file(resource_path: String) -> bool: + var ext := resource_path.get_extension() + return ext == "cs" and GdUnit4CSharpApiLoader.is_api_loaded() diff --git a/addons/gdUnit4/src/dotnet/GdUnit4CSharpApiLoader.gd.uid b/addons/gdUnit4/src/dotnet/GdUnit4CSharpApiLoader.gd.uid new file mode 100644 index 0000000..50fb9c6 --- /dev/null +++ b/addons/gdUnit4/src/dotnet/GdUnit4CSharpApiLoader.gd.uid @@ -0,0 +1 @@ +uid://bt3wdbynm0djt diff --git a/addons/gdUnit4/src/doubler/CallableDoubler.gd b/addons/gdUnit4/src/doubler/CallableDoubler.gd new file mode 100644 index 0000000..1bc78a1 --- /dev/null +++ b/addons/gdUnit4/src/doubler/CallableDoubler.gd @@ -0,0 +1,156 @@ +## The helper class to allow to double Callable +## Is just a wrapper to the original callable with the same function signature. +## +## Due to interface conflicts between 'Callable' and 'Object', +## it is not possible to stub the 'call' and 'call_deferred' methods. +## +## The Callable interface and the Object class have overlapping method signatures, +## which causes conflicts when attempting to stub these methods. +## As a result, you cannot create stubs for 'call' and 'call_deferred' methods. + +class_name CallableDoubler + + +const doubler_script :Script = preload("res://addons/gdUnit4/src/doubler/CallableDoubler.gd") + +var _cb: Callable + + +func _init(cb: Callable) -> void: + assert(cb!=null, "Invalid argument must not be null") + _cb = cb + +## --- helpers ----------------------------------------------------------------------------------------------------------------------------- +static func map_func_name(method_info: Dictionary) -> String: + return method_info["name"] + + +## We do not want to double all functions based on Object for this class +## Is used on SpyBuilder to excluding functions to be doubled for Callable +static func excluded_functions() -> PackedStringArray: + return ClassDB.class_get_method_list("Object")\ + .map(CallableDoubler.map_func_name)\ + .filter(func (name: String) -> bool: + return !CallableDoubler.callable_functions().has(name)) + + +static func non_callable_functions(name: String) -> bool: + return ![ + # we allow "_init", is need to construct it, + "excluded_functions", + "non_callable_functions", + "callable_functions", + "map_func_name" + ].has(name) + + +## Returns the list of supported Callable functions +static func callable_functions() -> PackedStringArray: + var supported_functions :Array = doubler_script.get_script_method_list()\ + .map(CallableDoubler.map_func_name)\ + .filter(CallableDoubler.non_callable_functions) + # We manually add these functions that we cannot/may not overwrite in this class + supported_functions.append_array(["call_deferred", "callv"]) + return supported_functions + + +## ----------------------------------------------------------------------------------------------------------------------------------------- +## Callable functions stubing +## ----------------------------------------------------------------------------------------------------------------------------------------- + +func bind(...varargs: Array) -> Callable: + _cb = _cb.bindv(varargs) + return _cb + + +func bindv(caller_args: Array) -> Callable: + _cb = _cb.bindv(caller_args) + return _cb + + +@warning_ignore("native_method_override") +func call(...varargs: Array) -> Variant: + return _cb.callv(varargs) + + +# Is not supported, see class description +#func call_deferred(...varargs: Array) -> void: +# return _cb.call_deferred(varargs) + + +# Is not supported, see class description +#func callv(arguments: Array) -> Variant: +# return _cb.callv(arguments) + + +func get_bound_arguments() -> Array: + return _cb.get_bound_arguments() + + +func get_bound_arguments_count() -> int: + return _cb.get_bound_arguments_count() + + +func get_method() -> StringName: + return _cb.get_method() + + +func get_object() -> Object: + return _cb.get_object() + + +func get_object_id() -> int: + return _cb.get_object_id() + + +func hash() -> int: + return _cb.hash() + + +func is_custom() -> bool: + return _cb.is_custom() + + +func is_null() -> bool: + return _cb.is_null() + + +func is_standard() -> bool: + return _cb.is_standard() + + +func is_valid() -> bool: + return _cb.is_valid() + + +func rpc(...varargs: Array) -> void: + match varargs.size(): + 0: _cb.rpc() + 1: _cb.rpc(varargs[0]) + 2: _cb.rpc(varargs[0], varargs[1]) + 3: _cb.rpc(varargs[0], varargs[1], varargs[2]) + 4: _cb.rpc(varargs[0], varargs[1], varargs[2], varargs[3], varargs[4]) + 5: _cb.rpc(varargs[0], varargs[1], varargs[2], varargs[3], varargs[4], varargs[5]) + 6: _cb.rpc(varargs[0], varargs[1], varargs[2], varargs[3], varargs[4], varargs[5], varargs[6]) + 7: _cb.rpc(varargs[0], varargs[1], varargs[2], varargs[3], varargs[4], varargs[5], varargs[6], varargs[7]) + 8: _cb.rpc(varargs[0], varargs[1], varargs[2], varargs[3], varargs[4], varargs[5], varargs[6], varargs[7], varargs[8]) + 9: _cb.rpc(varargs[0], varargs[1], varargs[2], varargs[3], varargs[4], varargs[5], varargs[6], varargs[7], varargs[8], varargs[9]) + + +@warning_ignore("untyped_declaration") +func rpc_id(peer_id: int, ...varargs: Array) -> void: + match varargs.size(): + 0: _cb.rpc_id(peer_id ) + 1: _cb.rpc_id(peer_id, varargs[0]) + 2: _cb.rpc_id(peer_id, varargs[0], varargs[1]) + 3: _cb.rpc_id(peer_id, varargs[0], varargs[1], varargs[2]) + 4: _cb.rpc_id(peer_id, varargs[0], varargs[1], varargs[2], varargs[3], varargs[4]) + 5: _cb.rpc_id(peer_id, varargs[0], varargs[1], varargs[2], varargs[3], varargs[4], varargs[5]) + 6: _cb.rpc_id(peer_id, varargs[0], varargs[1], varargs[2], varargs[3], varargs[4], varargs[5], varargs[6]) + 7: _cb.rpc_id(peer_id, varargs[0], varargs[1], varargs[2], varargs[3], varargs[4], varargs[5], varargs[6], varargs[7]) + 8: _cb.rpc_id(peer_id, varargs[0], varargs[1], varargs[2], varargs[3], varargs[4], varargs[5], varargs[6], varargs[7], varargs[8]) + 9: _cb.rpc_id(peer_id, varargs[0], varargs[1], varargs[2], varargs[3], varargs[4], varargs[5], varargs[6], varargs[7], varargs[8], varargs[9]) + +func unbind(argcount: int) -> Callable: + _cb = _cb.unbind(argcount) + return _cb diff --git a/addons/gdUnit4/src/doubler/CallableDoubler.gd.uid b/addons/gdUnit4/src/doubler/CallableDoubler.gd.uid new file mode 100644 index 0000000..5804b95 --- /dev/null +++ b/addons/gdUnit4/src/doubler/CallableDoubler.gd.uid @@ -0,0 +1 @@ +uid://hueakrkyydfw diff --git a/addons/gdUnit4/src/doubler/GdFunctionDoubler.gd b/addons/gdUnit4/src/doubler/GdFunctionDoubler.gd new file mode 100644 index 0000000..d9459dc --- /dev/null +++ b/addons/gdUnit4/src/doubler/GdFunctionDoubler.gd @@ -0,0 +1,4 @@ +@abstract class_name GdFunctionDoubler +extends RefCounted + +@abstract func double(func_descriptor: GdFunctionDescriptor) -> PackedStringArray diff --git a/addons/gdUnit4/src/doubler/GdFunctionDoubler.gd.uid b/addons/gdUnit4/src/doubler/GdFunctionDoubler.gd.uid new file mode 100644 index 0000000..fda3699 --- /dev/null +++ b/addons/gdUnit4/src/doubler/GdFunctionDoubler.gd.uid @@ -0,0 +1 @@ +uid://c43psb036dyjs diff --git a/addons/gdUnit4/src/doubler/GdUnitClassDoubler.gd b/addons/gdUnit4/src/doubler/GdUnitClassDoubler.gd new file mode 100644 index 0000000..31aa06b --- /dev/null +++ b/addons/gdUnit4/src/doubler/GdUnitClassDoubler.gd @@ -0,0 +1,119 @@ +# A class doubler used to mock and spy checked implementations +class_name GdUnitClassDoubler +extends RefCounted + +const DOUBLER_INSTANCE_ID_PREFIX := "gdunit_doubler_instance_id_" +const EXCLUDE_VIRTUAL_FUNCTIONS = [ + # we have to exclude notifications because NOTIFICATION_PREDELETE is try + # to delete already freed spy/mock resources and will result in a conflict + "_notification", + "notification", + # https://github.com/godotengine/godot/issues/67461 + "get_name", + "get_path", + "duplicate", + ] +# define functions to be exclude when spy or mock checked a scene +const EXLCUDE_SCENE_FUNCTIONS = [ + # needs to exclude get/set script functions otherwise it endsup in recursive endless loop + "set_script", + "get_script", + # needs to exclude otherwise verify fails checked collection arguments checked calling to string + "_to_string", +] +const EXCLUDE_FUNCTIONS = ["new", "free", "get_instance_id", "get_tree"] + + +static func check_leaked_instances() -> void: + ## we check that all registered spy/mock instances are removed from the engine meta data + for key in Engine.get_meta_list(): + if key.begins_with(DOUBLER_INSTANCE_ID_PREFIX): + var instance: Variant = Engine.get_meta(key) + push_error("GdUnit internal error: an spy/mock instance '%s', class:'%s' is not removed from the engine and will lead in a leaked instance!" % [instance, instance.__SOURCE_CLASS]) + await (Engine.get_main_loop() as SceneTree).process_frame + + +# loads the doubler template +# class_info = { "class_name": <>, "class_path" : <>} +static func load_template(template: String, class_info: Dictionary) -> PackedStringArray: + var clazz_name: String = class_info.get("class_name") + var source_code := template\ + .replace("${source_class}", clazz_name)\ + # Replace template class_name DoubledClass with source class name + .replace("SourceClassName", clazz_name.replace(".", "_")) + var lines := GdScriptParser.to_unix_format(source_code).split("\n") + @warning_ignore("return_value_discarded") + lines.insert(1, extends_clazz(class_info)) + lines.insert(0, "@warning_ignore_start('unsafe_call_argument', 'shadowed_variable', 'untyped_declaration', 'native_method_override', 'int_as_enum_without_cast')") + return lines + + +static func extends_clazz(class_info: Dictionary) -> String: + var clazz_name: String = class_info.get("class_name") + var clazz_path: PackedStringArray = class_info.get("class_path", []) + # is inner class? + if clazz_path.size() > 1: + return "extends %s" % clazz_name + if clazz_path.size() == 1 and clazz_path[0].ends_with(".gd"): + return "extends '%s'" % clazz_path[0] + return "extends %s" % clazz_name + + +# double all functions of given instance +static func double_functions(instance: Object, clazz_name: String, clazz_path: PackedStringArray, func_doubler: GdFunctionDoubler, exclude_functions: Array) -> PackedStringArray: + var doubled_source := PackedStringArray() + var parser := GdScriptParser.new() + var exclude_override_functions := EXCLUDE_VIRTUAL_FUNCTIONS + EXCLUDE_FUNCTIONS + exclude_functions + var functions := Array() + + # double script functions + if not ClassDB.class_exists(clazz_name): + var result := parser.parse(clazz_name, clazz_path) + if result.is_error(): + push_error(result.error_message()) + return PackedStringArray() + var class_descriptor: GdClassDescriptor = result.value() + for func_descriptor in class_descriptor.functions(): + if instance != null and not instance.has_method(func_descriptor.name()): + #prints("no virtual func implemented",clazz_name, func_descriptor.name() ) + continue + if functions.has(func_descriptor.name()) or exclude_override_functions.has(func_descriptor.name()): + continue + doubled_source += func_doubler.double(func_descriptor) + functions.append(func_descriptor.name()) + + # double regular class functions + var clazz_functions := GdObjects.extract_class_functions(clazz_name, clazz_path) + for method: Dictionary in clazz_functions: + var func_descriptor := GdFunctionDescriptor.extract_from(method) + # exclude private core functions + if func_descriptor.is_private(): + continue + if functions.has(func_descriptor.name()) or exclude_override_functions.has(func_descriptor.name()): + continue + # GD-110: Hotfix do not double invalid engine functions + if is_invalid_method_descriptior(method): + #prints("'%s': invalid method descriptor found! %s" % [clazz_name, method]) + continue + # do not double on not implemented virtual functions + if instance != null and not instance.has_method(func_descriptor.name()): + #prints("no virtual func implemented",clazz_name, func_descriptor.name() ) + continue + functions.append(func_descriptor.name()) + doubled_source.append_array(func_doubler.double(func_descriptor)) + return doubled_source + + +# GD-110 +static func is_invalid_method_descriptior(method: Dictionary) -> bool: + var return_info: Dictionary = method["return"] + var type: int = return_info["type"] + var usage: int = return_info["usage"] + var clazz_name: String = return_info["class_name"] + # is method returning a type int with a given 'class_name' we have an enum + # and the PROPERTY_USAGE_CLASS_IS_ENUM must be set + if type == TYPE_INT and not clazz_name.is_empty() and not (usage & PROPERTY_USAGE_CLASS_IS_ENUM): + return true + if clazz_name == "Variant.Type": + return true + return false diff --git a/addons/gdUnit4/src/doubler/GdUnitClassDoubler.gd.uid b/addons/gdUnit4/src/doubler/GdUnitClassDoubler.gd.uid new file mode 100644 index 0000000..a42aa22 --- /dev/null +++ b/addons/gdUnit4/src/doubler/GdUnitClassDoubler.gd.uid @@ -0,0 +1 @@ +uid://dw5wdtn3pjyb7 diff --git a/addons/gdUnit4/src/doubler/GdUnitFunctionDoublerBuilder.gd b/addons/gdUnit4/src/doubler/GdUnitFunctionDoublerBuilder.gd new file mode 100644 index 0000000..a1a75f1 --- /dev/null +++ b/addons/gdUnit4/src/doubler/GdUnitFunctionDoublerBuilder.gd @@ -0,0 +1,336 @@ +class_name GdUnitFunctionDoublerBuilder +extends RefCounted + +const TYPE_VOID = GdObjects.TYPE_VOID +const TYPE_VARIANT = GdObjects.TYPE_VARIANT +const TYPE_VARARG = GdObjects.TYPE_VARARG +const TYPE_FUNC = GdObjects.TYPE_FUNC +const TYPE_FUZZER = GdObjects.TYPE_FUZZER +const TYPE_ENUM = GdObjects.TYPE_ENUM + +const DEFAULT_TYPED_RETURN_VALUES := { + TYPE_NIL: "null", + TYPE_BOOL: "false", + TYPE_INT: "0", + TYPE_FLOAT: "0.0", + TYPE_STRING: "\"\"", + TYPE_STRING_NAME: "&\"\"", + TYPE_VECTOR2: "Vector2.ZERO", + TYPE_VECTOR2I: "Vector2i.ZERO", + TYPE_RECT2: "Rect2()", + TYPE_RECT2I: "Rect2i()", + TYPE_VECTOR3: "Vector3.ZERO", + TYPE_VECTOR3I: "Vector3i.ZERO", + TYPE_VECTOR4: "Vector4.ZERO", + TYPE_VECTOR4I: "Vector4i.ZERO", + TYPE_TRANSFORM2D: "Transform2D()", + TYPE_PLANE: "Plane()", + TYPE_QUATERNION: "Quaternion()", + TYPE_AABB: "AABB()", + TYPE_BASIS: "Basis()", + TYPE_TRANSFORM3D: "Transform3D()", + TYPE_PROJECTION: "Projection()", + TYPE_COLOR: "Color()", + TYPE_NODE_PATH: "NodePath()", + TYPE_RID: "RID()", + TYPE_OBJECT: "null", + TYPE_CALLABLE: "Callable()", + TYPE_SIGNAL: "Signal()", + TYPE_DICTIONARY: "Dictionary()", + TYPE_ARRAY: "Array()", + TYPE_PACKED_BYTE_ARRAY: "PackedByteArray()", + TYPE_PACKED_INT32_ARRAY: "PackedInt32Array()", + TYPE_PACKED_INT64_ARRAY: "PackedInt64Array()", + TYPE_PACKED_FLOAT32_ARRAY: "PackedFloat32Array()", + TYPE_PACKED_FLOAT64_ARRAY: "PackedFloat64Array()", + TYPE_PACKED_STRING_ARRAY: "PackedStringArray()", + TYPE_PACKED_VECTOR2_ARRAY: "PackedVector2Array()", + TYPE_PACKED_VECTOR3_ARRAY: "PackedVector3Array()", + TYPE_PACKED_VECTOR4_ARRAY: "PackedVector4Array()", + TYPE_PACKED_COLOR_ARRAY: "PackedColorArray()", + GdObjects.TYPE_VARIANT: "null", + GdObjects.TYPE_ENUM: "0" +} + + +# @GlobalScript enums +# needs to manually map because of https://github.com/godotengine/godot/issues/73835 +const DEFAULT_ENUM_RETURN_VALUES = { + "Side" : "SIDE_LEFT", + "Corner" : "CORNER_TOP_LEFT", + "Orientation" : "HORIZONTAL", + "ClockDirection" : "CLOCKWISE", + "HorizontalAlignment" : "HORIZONTAL_ALIGNMENT_LEFT", + "VerticalAlignment" : "VERTICAL_ALIGNMENT_TOP", + "InlineAlignment" : "INLINE_ALIGNMENT_TOP_TO", + "EulerOrder" : "EULER_ORDER_XYZ", + "Key" : "KEY_NONE", + "KeyModifierMask" : "KEY_CODE_MASK", + "MouseButton" : "MOUSE_BUTTON_NONE", + "MouseButtonMask" : "MOUSE_BUTTON_MASK_LEFT", + "JoyButton" : "JOY_BUTTON_INVALID", + "JoyAxis" : "JOY_AXIS_INVALID", + "MIDIMessage" : "MIDI_MESSAGE_NONE", + "Error" : "OK", + "PropertyHint" : "PROPERTY_HINT_NONE", + "Variant.Type" : "TYPE_NIL", + "Vector2.Axis" : "Vector2.AXIS_X", + "Vector2i.Axis" : "Vector2i.AXIS_X", + "Vector3.Axis" : "Vector3.AXIS_X", + "Vector3i.Axis" : "Vector3i.AXIS_X", + "Vector4.Axis" : "Vector4.AXIS_X", + "Vector4i.Axis" : "Vector4i.AXIS_X", +} + + +static var def_constructor := """ + func _init({constructor_args}) -> void: + __init_doubler() + super({args}) + """.dedent() + + +static var def_verify_block := """ + # verify block + var __verifier := __get_verifier() + if __verifier != null: + if __verifier.is_verify_interactions(): + __verifier.verify_interactions("{func_name}", __args) + {default_return} + else: + __verifier.save_function_interaction("{func_name}", __args) + """.dedent().indent("\t").trim_suffix("\n") + + +static var def_prepare_block := """ + if __is_prepare_return_value(): + __save_function_return_value("{func_name}", __args) + {default_return} + """.dedent().indent("\t").trim_suffix("\n") + + +static var def_void_prepare_block := """ + if __is_prepare_return_value(): + push_error("Mocking functions with return type void is not allowed!") + return + """.dedent().indent("\t").trim_suffix("\n") + + +static var def_mock_return := """ + if __is_do_not_call_real_func("{func_name}", __args): + return __return_mock_value("{func_name}", __args, {default_return}) + """.dedent().indent("\t").trim_suffix("\n") + + +static var def_void_mock_return := """ + if __is_do_not_call_real_func("{func_name}", __args): + return + """.dedent().indent("\t").trim_suffix("\n") + + +var fd: GdFunctionDescriptor +var func_args: Array +var default_return: String +var verify_block: String = "" +var prepare_block: String = "" +var mock_return: String = "" + + +func _init(descriptor: GdFunctionDescriptor) -> void: + # verify all default types are covered + for type_key in TYPE_MAX: + if not DEFAULT_TYPED_RETURN_VALUES.has(type_key): + push_error("missing default definitions! Expexting %d bud is %d" % [DEFAULT_TYPED_RETURN_VALUES.size(), TYPE_MAX]) + prints("missing default definition for type", type_key) + assert(DEFAULT_TYPED_RETURN_VALUES.has(type_key), "Missing Type default definition!") + + fd = descriptor + func_args = argument_names() + default_return = default_return_value() + + +func build_func_signature() -> String: + var return_type := ":" if fd._return_type == TYPE_VARIANT else " -> %s:" % fd.return_type_as_string() + return "{static}func {func_name}({args}){return_type}".format({ + "static" : "static " if fd.is_static() else "", + "func_name": fd.name(), + "args": arguments_full_quilified(), + "return_type": return_type + }) + + +func arguments_full_quilified() -> String: + var collect := PackedStringArray() + for arg in fd.args(): + var name := argument_name(arg) + if arg.has_default(): + var signature := "{argument_name}{arg_typed}={arg_value}".format({ + "argument_name" : name, + "arg_typed" : ":"+GdObjects.type_as_string(arg.type()) if arg.type() == GdObjects.TYPE_VARIANT else "", + "arg_value" : arg.value_as_string() + }) + collect.push_back(signature) + else: + collect.push_back(name) + if fd.is_vararg(): + var arg_descriptor := fd.varargs()[0] + collect.push_back("...%s_: Array" % arg_descriptor.name()) + return ", ".join(collect) + + +func argument_name(arg: GdFunctionArgument) -> String: + return arg.name() + "_" + + +func argument_names() -> PackedStringArray: + return fd.args().map(argument_name) + + +func argument_default(arg :GdFunctionArgument) -> String: + return (arg.value_as_string() + if arg.has_default() + else DEFAULT_TYPED_RETURN_VALUES.get(arg.type(), "null")) + + +func build_constructor_arguments() -> String: + var arguments := PackedStringArray() + for arg in fd.args(): + var default_value := argument_default(arg) + var arg_signature := "{name}:{type}={default}".format({ + "name" : argument_name(arg), + "type" : "Variant" if default_value == "null" else "", + "default" : default_value + }) + arguments.append(arg_signature) + if fd.is_vararg(): + arguments.append("...varargs: Array") + return ", ".join(arguments) + + +func build_arguments() -> String: + return "\tvar __args := [{args}]{varargs}".format({ + "args" : ", ".join(func_args), + "varargs" : " + varargs_" if fd.is_vararg() else "" + }) + + +func build_super_calls() -> String: + if !fd.is_vararg(): + return 'super(%s)\n' % ", ".join(func_args) + + var match_block := "match varargs_.size():\n" + for index in range(0, 11): + match_block += '{index}: super({args})\n'.format({ + "index" : index, + "args" : ", ".join(func_args + build_vararg_list(index)) + }).indent("\t") + match_block += '_: push_error("To many varradic arguments.")\n'.indent("\t") + match_block += "return\n" if is_void_func() else "return %s\n" % default_return + return match_block + + +func build_vararg_list(count: int) -> Array: + var arg_list := [] + for index in count: + arg_list.append("varargs_[%d]" % index) + return arg_list + + +func default_return_value() -> String: + var return_type: Variant = fd.return_type() + if return_type == GdObjects.TYPE_ENUM: + var enum_class := fd._return_class + if DEFAULT_ENUM_RETURN_VALUES.has(enum_class): + return DEFAULT_ENUM_RETURN_VALUES.get(fd._return_class, "0") + + var enum_path := enum_class.split(".") + if enum_path.size() >= 2: + var keys := ClassDB.class_get_enum_constants(enum_path[0], enum_path[1]) + if not keys.is_empty(): + return "%s.%s" % [enum_path[0], keys[0]] + var enum_value: Variant = get_enum_default(enum_class) + if enum_value != null: + return str(enum_value) + # we need fallback for @GlobalScript enums, + return DEFAULT_ENUM_RETURN_VALUES.get(fd._return_class, "0") + return DEFAULT_TYPED_RETURN_VALUES.get(return_type, "invalid") + + +# Determine the enum default by reflection +func get_enum_default(value: String) -> Variant: + var script := GDScript.new() + script.source_code = """ + extends RefCounted + + static func get_enum_default() -> Variant: + return %s.values()[0] + + """.dedent() % value + var err := script.reload() + if err != OK: + push_error("Cant get enum values form '%s', %s" % [value, error_string(err)]) + return 0 + @warning_ignore("unsafe_method_access") + return script.new().call("get_enum_default") + + +func is_void_func() -> bool: + return fd.return_type() == TYPE_NIL or fd.return_type() == TYPE_VOID + + +func with_verify_block() -> GdUnitFunctionDoublerBuilder: + verify_block = def_verify_block.format({ + "func_name" : fd.name(), + "default_return" : "return" if is_void_func() else "return " + default_return + }) + return self + + +func with_prepare_block() -> GdUnitFunctionDoublerBuilder: + if fd.return_type() == TYPE_NIL or fd.return_type() == GdObjects.TYPE_VOID: + prepare_block = def_void_prepare_block + return self + + prepare_block = def_prepare_block.format({ + "func_name" : fd.name(), + "default_return" : "return" if is_void_func() else "return " + default_return + }) + return self + + +func with_mocked_return_value() -> GdUnitFunctionDoublerBuilder: + if is_void_func(): + mock_return = def_void_mock_return.format({ + "func_name" : fd.name(), + }) + else: + mock_return = def_mock_return.format({ + "func_name" : fd.name(), + "default_return" : '"no_arg"' if is_void_func() else default_return + }) + return self + + +func build() -> PackedStringArray: + if fd.name() == "_init": + return [def_constructor.format({ + "constructor_args" : build_constructor_arguments(), + "args" : ", ".join(func_args) + })] + + var func_body: PackedStringArray = [] + func_body.append(build_func_signature()) + func_body.append(build_arguments()) + if not prepare_block.is_empty(): + func_body.append(prepare_block) + func_body.append(verify_block) + if not mock_return.is_empty(): + func_body.append(mock_return) + func_body.append("") + var super_calls := build_super_calls() + if not is_void_func(): + super_calls = super_calls.replace("super(", "return super(" ) + if fd.is_coroutine(): + super_calls = super_calls.replace("super(", "await super(" ) + func_body.append(super_calls.indent("\t")) + return func_body diff --git a/addons/gdUnit4/src/doubler/GdUnitFunctionDoublerBuilder.gd.uid b/addons/gdUnit4/src/doubler/GdUnitFunctionDoublerBuilder.gd.uid new file mode 100644 index 0000000..4a6f520 --- /dev/null +++ b/addons/gdUnit4/src/doubler/GdUnitFunctionDoublerBuilder.gd.uid @@ -0,0 +1 @@ +uid://hjwlnynmbp8n diff --git a/addons/gdUnit4/src/doubler/GdUnitMockFunctionDoubler.gd b/addons/gdUnit4/src/doubler/GdUnitMockFunctionDoubler.gd new file mode 100644 index 0000000..d735bc5 --- /dev/null +++ b/addons/gdUnit4/src/doubler/GdUnitMockFunctionDoubler.gd @@ -0,0 +1,10 @@ +class_name GdUnitMockFunctionDoubler +extends GdFunctionDoubler + + +func double(func_descriptor: GdFunctionDescriptor) -> PackedStringArray: + return GdUnitFunctionDoublerBuilder.new(func_descriptor)\ + .with_prepare_block()\ + .with_verify_block()\ + .with_mocked_return_value()\ + .build() diff --git a/addons/gdUnit4/src/doubler/GdUnitMockFunctionDoubler.gd.uid b/addons/gdUnit4/src/doubler/GdUnitMockFunctionDoubler.gd.uid new file mode 100644 index 0000000..92950d6 --- /dev/null +++ b/addons/gdUnit4/src/doubler/GdUnitMockFunctionDoubler.gd.uid @@ -0,0 +1 @@ +uid://dxugiqwdcayp0 diff --git a/addons/gdUnit4/src/doubler/GdUnitObjectInteractions.gd b/addons/gdUnit4/src/doubler/GdUnitObjectInteractions.gd new file mode 100644 index 0000000..789eb32 --- /dev/null +++ b/addons/gdUnit4/src/doubler/GdUnitObjectInteractions.gd @@ -0,0 +1,53 @@ +class_name GdUnitObjectInteractions +extends RefCounted + + +static func verify(interaction_object: Object, interactions_times: int) -> Variant: + if not _is_mock_or_spy(interaction_object): + return interaction_object + + _get_verifier(interaction_object).do_verify_interactions(interactions_times) + return interaction_object + + +static func verify_no_interactions(interaction_object: Object) -> GdUnitAssert: + var assert_tool := GdUnitAssertImpl.new("") + if not _is_mock_or_spy(interaction_object): + return assert_tool.report_success() + + var summary := _get_verifier(interaction_object).verify_no_interactions() + if summary.is_empty(): + return assert_tool.report_success() + return assert_tool.report_error(GdAssertMessages.error_no_more_interactions(summary)) + + +static func verify_no_more_interactions(interaction_object: Object) -> GdUnitAssert: + var assert_tool := GdUnitAssertImpl.new("") + if not _is_mock_or_spy(interaction_object): + return assert_tool + + var summary := _get_verifier(interaction_object).verify_no_more_interactions() + if summary.is_empty(): + return assert_tool + return assert_tool.report_error(GdAssertMessages.error_no_more_interactions(summary)) + + +static func reset(interaction_object: Object) -> Object: + if not _is_mock_or_spy(interaction_object): + return interaction_object + + _get_verifier(interaction_object).reset_interactions() + return interaction_object + + +static func _is_mock_or_spy(instance: Object) -> bool: + if instance != null and instance.has_method("__get_verifier"): + return true + + push_error("Error: The given object '%s' is not a mock or spy instance!" % instance) + return false + + +static func _get_verifier(interaction_object: Object) -> GdUnitObjectInteractionsVerifier: + @warning_ignore("unsafe_method_access") + return interaction_object.__get_verifier() diff --git a/addons/gdUnit4/src/doubler/GdUnitObjectInteractions.gd.uid b/addons/gdUnit4/src/doubler/GdUnitObjectInteractions.gd.uid new file mode 100644 index 0000000..930a0f3 --- /dev/null +++ b/addons/gdUnit4/src/doubler/GdUnitObjectInteractions.gd.uid @@ -0,0 +1 @@ +uid://djn7jisfwlcn4 diff --git a/addons/gdUnit4/src/doubler/GdUnitObjectInteractionsVerifier.gd b/addons/gdUnit4/src/doubler/GdUnitObjectInteractionsVerifier.gd new file mode 100644 index 0000000..36aa978 --- /dev/null +++ b/addons/gdUnit4/src/doubler/GdUnitObjectInteractionsVerifier.gd @@ -0,0 +1,84 @@ +class_name GdUnitObjectInteractionsVerifier + +var expected_interactions: int = -1 +var saved_interactions := Dictionary() +var verified_interactions := Array() + + +func save_function_interaction(func_name: String, args :Array[Variant]) -> void: + var function_args := [func_name] + args + var matcher := GdUnitArgumentMatchers.to_matcher(function_args, true) + for index in saved_interactions.keys().size(): + var key: Variant = saved_interactions.keys()[index] + if matcher.is_match(key): + saved_interactions[key] += 1 + return + saved_interactions[function_args] = 1 + + +func is_verify_interactions() -> bool: + return expected_interactions != -1 + + +func do_verify_interactions(interactions_times: int = 1) -> void: + expected_interactions = interactions_times + + +func verify_interactions(func_name: String, args: Array[Variant]) -> void: + var summary := Dictionary() + var total_interactions := 0 + var function_args := [func_name] + args + var matcher := GdUnitArgumentMatchers.to_matcher(function_args, true) + for index in saved_interactions.keys().size(): + var key: Variant = saved_interactions.keys()[index] + if matcher.is_match(key): + var interactions: int = saved_interactions.get(key, 0) + total_interactions += interactions + summary[key] = interactions + # add as verified + verified_interactions.append(key) + + var assert_tool := GdUnitAssertImpl.new("") + if total_interactions != expected_interactions: + var __expected_summary := {function_args : expected_interactions} + var error_message: String + # if no interactions macht collect not verified interactions for failure report + if summary.is_empty(): + var __current_summary := verify_no_more_interactions() + error_message = GdAssertMessages.error_validate_interactions(__current_summary, __expected_summary) + else: + error_message = GdAssertMessages.error_validate_interactions(summary, __expected_summary) + @warning_ignore("return_value_discarded") + assert_tool.report_error(error_message) + else: + @warning_ignore("return_value_discarded") + assert_tool.report_success() + expected_interactions = -1 + + +func verify_no_interactions() -> Dictionary: + var summary := Dictionary() + if not saved_interactions.is_empty(): + for index in saved_interactions.keys().size(): + var func_call: Variant = saved_interactions.keys()[index] + summary[func_call] = saved_interactions[func_call] + return summary + + +func verify_no_more_interactions() -> Dictionary: + var summary := Dictionary() + var called_functions: Array[Variant] = saved_interactions.keys() + if called_functions != verified_interactions: + # collect the not verified functions + var called_but_not_verified := called_functions.duplicate() + for index in verified_interactions.size(): + called_but_not_verified.erase(verified_interactions[index]) + + for index in called_but_not_verified.size(): + var not_verified: Variant = called_but_not_verified[index] + summary[not_verified] = saved_interactions[not_verified] + return summary + + +func reset_interactions() -> void: + saved_interactions.clear() diff --git a/addons/gdUnit4/src/doubler/GdUnitObjectInteractionsVerifier.gd.uid b/addons/gdUnit4/src/doubler/GdUnitObjectInteractionsVerifier.gd.uid new file mode 100644 index 0000000..0ad8ede --- /dev/null +++ b/addons/gdUnit4/src/doubler/GdUnitObjectInteractionsVerifier.gd.uid @@ -0,0 +1 @@ +uid://cicc4xb1jan3w diff --git a/addons/gdUnit4/src/doubler/GdUnitSpyFunctionDoubler.gd b/addons/gdUnit4/src/doubler/GdUnitSpyFunctionDoubler.gd new file mode 100644 index 0000000..091241d --- /dev/null +++ b/addons/gdUnit4/src/doubler/GdUnitSpyFunctionDoubler.gd @@ -0,0 +1,8 @@ +class_name GdUnitSpyFunctionDoubler +extends GdFunctionDoubler + + +func double(func_descriptor: GdFunctionDescriptor) -> PackedStringArray: + return GdUnitFunctionDoublerBuilder.new(func_descriptor)\ + .with_verify_block()\ + .build() diff --git a/addons/gdUnit4/src/doubler/GdUnitSpyFunctionDoubler.gd.uid b/addons/gdUnit4/src/doubler/GdUnitSpyFunctionDoubler.gd.uid new file mode 100644 index 0000000..bf9eed3 --- /dev/null +++ b/addons/gdUnit4/src/doubler/GdUnitSpyFunctionDoubler.gd.uid @@ -0,0 +1 @@ +uid://cewvka7wc13ir diff --git a/addons/gdUnit4/src/extractors/GdUnitFuncValueExtractor.gd b/addons/gdUnit4/src/extractors/GdUnitFuncValueExtractor.gd new file mode 100644 index 0000000..124d3d4 --- /dev/null +++ b/addons/gdUnit4/src/extractors/GdUnitFuncValueExtractor.gd @@ -0,0 +1,73 @@ +# This class defines a value extractor by given function name and args +class_name GdUnitFuncValueExtractor +extends GdUnitValueExtractor + +var _func_names :PackedStringArray +var _args :Array + +func _init(func_name :String, p_args :Array) -> void: + _func_names = func_name.split(".") + _args = p_args + + +func func_names() -> PackedStringArray: + return _func_names + + +func args() -> Array: + return _args + + +# Extracts a value by given `func_name` and `args`, +# Allows to use a chained list of functions setarated ba a dot. +# e.g. "func_a.func_b.name" +# do calls instance.func_a().func_b().name() and returns finally the name +# If a function returns an array, all elements will by collected in a array +# e.g. "get_children.get_name" checked a node +# do calls node.get_children() for all childs get_name() and returns all names in an array +# +# if the value not a Object or not accesible be `func_name` the value is converted to `"n.a."` +# expecing null values +func extract_value(value: Variant) -> Variant: + if value == null: + return null + for func_name in func_names(): + if GdArrayTools.is_array_type(value): + var values := Array() + @warning_ignore("unsafe_cast") + for element: Variant in (value as Array): + values.append(_call_func(element, func_name)) + value = values + else: + value = _call_func(value, func_name) + var type := typeof(value) + if type == TYPE_STRING_NAME: + return str(value) + if type == TYPE_STRING and value == "n.a.": + return value + return value + + +func _call_func(value :Variant, func_name :String) -> Variant: + # for array types we need to call explicit by function name, using funcref is only supported for Objects + # TODO extend to all array functions + if GdArrayTools.is_array_type(value) and func_name == "empty": + @warning_ignore("unsafe_cast") + return (value as Array).is_empty() + + if is_instance_valid(value): + # extract from function + var obj_value: Object = value + if obj_value.has_method(func_name): + var extract := Callable(obj_value, func_name) + if extract.is_valid(): + return obj_value.call(func_name) if args().is_empty() else obj_value.callv(func_name, args()) + else: + # if no function exists than try to extract form parmeters + var parameter: Variant = obj_value.get(func_name) + if parameter != null: + return parameter + # nothing found than return 'n.a.' + if GdUnitSettings.is_verbose_assert_warnings(): + push_warning("Extracting value from element '%s' by func '%s' failed! Converting to \"n.a.\"" % [value, func_name]) + return "n.a." diff --git a/addons/gdUnit4/src/extractors/GdUnitFuncValueExtractor.gd.uid b/addons/gdUnit4/src/extractors/GdUnitFuncValueExtractor.gd.uid new file mode 100644 index 0000000..9d43f28 --- /dev/null +++ b/addons/gdUnit4/src/extractors/GdUnitFuncValueExtractor.gd.uid @@ -0,0 +1 @@ +uid://cs4qbmmqagkwq diff --git a/addons/gdUnit4/src/fuzzers/FloatFuzzer.gd b/addons/gdUnit4/src/fuzzers/FloatFuzzer.gd new file mode 100644 index 0000000..347513f --- /dev/null +++ b/addons/gdUnit4/src/fuzzers/FloatFuzzer.gd @@ -0,0 +1,13 @@ +class_name FloatFuzzer +extends Fuzzer + +var _from: float = 0 +var _to: float = 0 + +func _init(from: float, to: float) -> void: + assert(from <= to, "Invalid range!") + _from = from + _to = to + +func next_value() -> float: + return randf_range(_from, _to) diff --git a/addons/gdUnit4/src/fuzzers/FloatFuzzer.gd.uid b/addons/gdUnit4/src/fuzzers/FloatFuzzer.gd.uid new file mode 100644 index 0000000..ea25bff --- /dev/null +++ b/addons/gdUnit4/src/fuzzers/FloatFuzzer.gd.uid @@ -0,0 +1 @@ +uid://0jhbcw1c775s diff --git a/addons/gdUnit4/src/fuzzers/Fuzzer.gd b/addons/gdUnit4/src/fuzzers/Fuzzer.gd new file mode 100644 index 0000000..7cd6a58 --- /dev/null +++ b/addons/gdUnit4/src/fuzzers/Fuzzer.gd @@ -0,0 +1,39 @@ +# Base interface for fuzz testing +# https://en.wikipedia.org/wiki/Fuzzing +class_name Fuzzer +extends RefCounted +# To run a test with a specific fuzzer you have to add defailt argument checked your test case +# all arguments are optional [] +# syntax: +# func test_foo([fuzzer = ], [fuzzer_iterations=], [fuzzer_seed=]) +# example: +# # runs the test 'test_foo' 10 times with a random int value generated by the IntFuzzer +# func test_foo(fuzzer = Fuzzers.randomInt(), fuzzer_iterations=10) +# +# # runs the test 'test_foo2' 1000 times as default with a random seed='101010101' +# func test_foo2(fuzzer = Fuzzers.randomInt(), fuzzer_seed=101010101) + +const ITERATION_DEFAULT_COUNT = 1000 +const ARGUMENT_FUZZER_INSTANCE := "fuzzer" +const ARGUMENT_ITERATIONS := "fuzzer_iterations" +const ARGUMENT_SEED := "fuzzer_seed" + +var _iteration_index :int = 0 +var _iteration_limit :int = ITERATION_DEFAULT_COUNT + + +# generates the next fuzz value +# needs to be implement +func next_value() -> Variant: + push_error("Invalid vall. Fuzzer not implemented 'next_value()'") + return null + + +# returns the current iteration index +func iteration_index() -> int: + return _iteration_index + + +# returns the amount of iterations where the fuzzer will be run +func iteration_limit() -> int: + return _iteration_limit diff --git a/addons/gdUnit4/src/fuzzers/Fuzzer.gd.uid b/addons/gdUnit4/src/fuzzers/Fuzzer.gd.uid new file mode 100644 index 0000000..e51befd --- /dev/null +++ b/addons/gdUnit4/src/fuzzers/Fuzzer.gd.uid @@ -0,0 +1 @@ +uid://h8yqrfkorcbf diff --git a/addons/gdUnit4/src/fuzzers/IntFuzzer.gd b/addons/gdUnit4/src/fuzzers/IntFuzzer.gd new file mode 100644 index 0000000..064dc20 --- /dev/null +++ b/addons/gdUnit4/src/fuzzers/IntFuzzer.gd @@ -0,0 +1,32 @@ +class_name IntFuzzer +extends Fuzzer + +enum { + NORMAL, + EVEN, + ODD +} + +var _from :int = 0 +var _to : int = 0 +var _mode : int = NORMAL + + +func _init(from: int, to: int, mode :int = NORMAL) -> void: + assert(from <= to, "Invalid range!") + _from = from + _to = to + _mode = mode + + +func next_value() -> int: + var value := randi_range(_from, _to) + match _mode: + NORMAL: + return value + EVEN: + return int((value / 2.0) * 2) + ODD: + return int((value / 2.0) * 2 + 1) + _: + return value diff --git a/addons/gdUnit4/src/fuzzers/IntFuzzer.gd.uid b/addons/gdUnit4/src/fuzzers/IntFuzzer.gd.uid new file mode 100644 index 0000000..36398f3 --- /dev/null +++ b/addons/gdUnit4/src/fuzzers/IntFuzzer.gd.uid @@ -0,0 +1 @@ +uid://q2byxdj5myw4 diff --git a/addons/gdUnit4/src/fuzzers/StringFuzzer.gd b/addons/gdUnit4/src/fuzzers/StringFuzzer.gd new file mode 100644 index 0000000..ca165d3 --- /dev/null +++ b/addons/gdUnit4/src/fuzzers/StringFuzzer.gd @@ -0,0 +1,65 @@ +class_name StringFuzzer +extends Fuzzer + + +const DEFAULT_CHARSET = "a-zA-Z0-9+-_" + +var _min_length :int +var _max_length :int +var _charset :PackedByteArray + + +func _init(min_length :int, max_length :int, pattern :String = DEFAULT_CHARSET) -> void: + assert(min_length>0 and min_length < max_length) + assert(not null or not pattern.is_empty()) + _min_length = min_length + _max_length = max_length + _charset = StringFuzzer.extract_charset(pattern) + + +static func extract_charset(pattern :String) -> PackedByteArray: + var reg := RegEx.new() + if reg.compile(pattern) != OK: + push_error("Invalid pattern to generate Strings! Use e.g 'a-zA-Z0-9+-_'") + return PackedByteArray() + + var charset := Array() + var char_before := -1 + var index := 0 + while index < pattern.length(): + var char_current := pattern.unicode_at(index) + # - range token at first or last pos? + if char_current == 45 and (index == 0 or index == pattern.length()-1): + charset.append(char_current) + index += 1 + continue + index += 1 + # range starts + if char_current == 45 and char_before != -1: + var char_next := pattern.unicode_at(index) + var characters := build_chars(char_before, char_next) + for character in characters: + charset.append(character) + char_before = -1 + index += 1 + continue + char_before = char_current + charset.append(char_current) + return PackedByteArray(charset) + + +static func build_chars(from :int, to :int) -> Array[int]: + var characters :Array[int] = [] + for character in range(from+1, to+1): + characters.append(character) + return characters + + +func next_value() -> String: + var value := PackedByteArray() + var max_char := len(_charset) + var length :int = max(_min_length, randi() % _max_length) + for i in length: + @warning_ignore("return_value_discarded") + value.append(_charset[randi() % max_char]) + return value.get_string_from_utf8() diff --git a/addons/gdUnit4/src/fuzzers/StringFuzzer.gd.uid b/addons/gdUnit4/src/fuzzers/StringFuzzer.gd.uid new file mode 100644 index 0000000..1b25e2d --- /dev/null +++ b/addons/gdUnit4/src/fuzzers/StringFuzzer.gd.uid @@ -0,0 +1 @@ +uid://d2y06qra0pkfw diff --git a/addons/gdUnit4/src/fuzzers/Vector2Fuzzer.gd b/addons/gdUnit4/src/fuzzers/Vector2Fuzzer.gd new file mode 100644 index 0000000..855cf6a --- /dev/null +++ b/addons/gdUnit4/src/fuzzers/Vector2Fuzzer.gd @@ -0,0 +1,18 @@ +class_name Vector2Fuzzer +extends Fuzzer + + +var _from :Vector2 +var _to : Vector2 + + +func _init(from: Vector2, to: Vector2) -> void: + assert(from <= to, "Invalid range!") + _from = from + _to = to + + +func next_value() -> Vector2: + var x := randf_range(_from.x, _to.x) + var y := randf_range(_from.y, _to.y) + return Vector2(x, y) diff --git a/addons/gdUnit4/src/fuzzers/Vector2Fuzzer.gd.uid b/addons/gdUnit4/src/fuzzers/Vector2Fuzzer.gd.uid new file mode 100644 index 0000000..140b084 --- /dev/null +++ b/addons/gdUnit4/src/fuzzers/Vector2Fuzzer.gd.uid @@ -0,0 +1 @@ +uid://dbqcxolydo4yp diff --git a/addons/gdUnit4/src/fuzzers/Vector3Fuzzer.gd b/addons/gdUnit4/src/fuzzers/Vector3Fuzzer.gd new file mode 100644 index 0000000..c773ab5 --- /dev/null +++ b/addons/gdUnit4/src/fuzzers/Vector3Fuzzer.gd @@ -0,0 +1,19 @@ +class_name Vector3Fuzzer +extends Fuzzer + + +var _from :Vector3 +var _to : Vector3 + + +func _init(from: Vector3, to: Vector3) -> void: + assert(from <= to, "Invalid range!") + _from = from + _to = to + + +func next_value() -> Vector3: + var x := randf_range(_from.x, _to.x) + var y := randf_range(_from.y, _to.y) + var z := randf_range(_from.z, _to.z) + return Vector3(x, y, z) diff --git a/addons/gdUnit4/src/fuzzers/Vector3Fuzzer.gd.uid b/addons/gdUnit4/src/fuzzers/Vector3Fuzzer.gd.uid new file mode 100644 index 0000000..2a7aebd --- /dev/null +++ b/addons/gdUnit4/src/fuzzers/Vector3Fuzzer.gd.uid @@ -0,0 +1 @@ +uid://bfoo3wqvyi0dx diff --git a/addons/gdUnit4/src/matchers/AnyArgumentMatcher.gd b/addons/gdUnit4/src/matchers/AnyArgumentMatcher.gd new file mode 100644 index 0000000..bd50313 --- /dev/null +++ b/addons/gdUnit4/src/matchers/AnyArgumentMatcher.gd @@ -0,0 +1,11 @@ +class_name AnyArgumentMatcher +extends GdUnitArgumentMatcher + + +@warning_ignore("unused_parameter") +func is_match(value :Variant) -> bool: + return true + + +func _to_string() -> String: + return "any()" diff --git a/addons/gdUnit4/src/matchers/AnyArgumentMatcher.gd.uid b/addons/gdUnit4/src/matchers/AnyArgumentMatcher.gd.uid new file mode 100644 index 0000000..677dd65 --- /dev/null +++ b/addons/gdUnit4/src/matchers/AnyArgumentMatcher.gd.uid @@ -0,0 +1 @@ +uid://uygj574asu08 diff --git a/addons/gdUnit4/src/matchers/AnyBuildInTypeArgumentMatcher.gd b/addons/gdUnit4/src/matchers/AnyBuildInTypeArgumentMatcher.gd new file mode 100644 index 0000000..ba34431 --- /dev/null +++ b/addons/gdUnit4/src/matchers/AnyBuildInTypeArgumentMatcher.gd @@ -0,0 +1,50 @@ +class_name AnyBuildInTypeArgumentMatcher +extends GdUnitArgumentMatcher + +var _type : PackedInt32Array = [] + + +func _init(type :PackedInt32Array) -> void: + _type = type + + +func is_match(value :Variant) -> bool: + return _type.has(typeof(value)) + + +func _to_string() -> String: + match _type[0]: + TYPE_BOOL: return "any_bool()" + TYPE_STRING, TYPE_STRING_NAME: return "any_string()" + TYPE_INT: return "any_int()" + TYPE_FLOAT: return "any_float()" + TYPE_COLOR: return "any_color()" + TYPE_VECTOR2: return "any_vector2()" if _type.size() == 1 else "any_vector()" + TYPE_VECTOR2I: return "any_vector2i()" + TYPE_VECTOR3: return "any_vector3()" + TYPE_VECTOR3I: return "any_vector3i()" + TYPE_VECTOR4: return "any_vector4()" + TYPE_VECTOR4I: return "any_vector4i()" + TYPE_RECT2: return "any_rect2()" + TYPE_RECT2I: return "any_rect2i()" + TYPE_PLANE: return "any_plane()" + TYPE_QUATERNION: return "any_quat()" + TYPE_AABB: return "any_aabb()" + TYPE_BASIS: return "any_basis()" + TYPE_TRANSFORM2D: return "any_transform_2d()" + TYPE_TRANSFORM3D: return "any_transform_3d()" + TYPE_NODE_PATH: return "any_node_path()" + TYPE_RID: return "any_rid()" + TYPE_OBJECT: return "any_object()" + TYPE_DICTIONARY: return "any_dictionary()" + TYPE_ARRAY: return "any_array()" + TYPE_PACKED_BYTE_ARRAY: return "any_packed_byte_array()" + TYPE_PACKED_INT32_ARRAY: return "any_packed_int32_array()" + TYPE_PACKED_INT64_ARRAY: return "any_packed_int64_array()" + TYPE_PACKED_FLOAT32_ARRAY: return "any_packed_float32_array()" + TYPE_PACKED_FLOAT64_ARRAY: return "any_packed_float64_array()" + TYPE_PACKED_STRING_ARRAY: return "any_packed_string_array()" + TYPE_PACKED_VECTOR2_ARRAY: return "any_packed_vector2_array()" + TYPE_PACKED_VECTOR3_ARRAY: return "any_packed_vector3_array()" + TYPE_PACKED_COLOR_ARRAY: return "any_packed_color_array()" + _: return "any()" diff --git a/addons/gdUnit4/src/matchers/AnyBuildInTypeArgumentMatcher.gd.uid b/addons/gdUnit4/src/matchers/AnyBuildInTypeArgumentMatcher.gd.uid new file mode 100644 index 0000000..7e31f0f --- /dev/null +++ b/addons/gdUnit4/src/matchers/AnyBuildInTypeArgumentMatcher.gd.uid @@ -0,0 +1 @@ +uid://bnibcl33dinxu diff --git a/addons/gdUnit4/src/matchers/AnyClazzArgumentMatcher.gd b/addons/gdUnit4/src/matchers/AnyClazzArgumentMatcher.gd new file mode 100644 index 0000000..b5e3de3 --- /dev/null +++ b/addons/gdUnit4/src/matchers/AnyClazzArgumentMatcher.gd @@ -0,0 +1,32 @@ +class_name AnyClazzArgumentMatcher +extends GdUnitArgumentMatcher + +var _clazz :Object + + +func _init(clazz :Object) -> void: + _clazz = clazz + + +func is_match(value :Variant) -> bool: + if typeof(value) != TYPE_OBJECT: + return false + if is_instance_valid(value) and GdObjects.is_script(_clazz): + @warning_ignore("unsafe_cast") + return (value as Object).get_script() == _clazz + return is_instance_of(value, _clazz) + + +func _to_string() -> String: + if (_clazz as Object).is_class("GDScriptNativeClass"): + @warning_ignore("unsafe_method_access") + var instance :Object = _clazz.new() + var clazz_name := instance.get_class() + if not instance is RefCounted: + instance.free() + return "any_class(<"+clazz_name+">)"; + if _clazz is GDScript: + var result := GdObjects.extract_class_name(_clazz) + if result.is_success(): + return "any_class(<"+ result.value() + ">)" + return "any_class()" diff --git a/addons/gdUnit4/src/matchers/AnyClazzArgumentMatcher.gd.uid b/addons/gdUnit4/src/matchers/AnyClazzArgumentMatcher.gd.uid new file mode 100644 index 0000000..932a438 --- /dev/null +++ b/addons/gdUnit4/src/matchers/AnyClazzArgumentMatcher.gd.uid @@ -0,0 +1 @@ +uid://c5ajdbvbwgaqc diff --git a/addons/gdUnit4/src/matchers/ChainedArgumentMatcher.gd b/addons/gdUnit4/src/matchers/ChainedArgumentMatcher.gd new file mode 100644 index 0000000..f779bd7 --- /dev/null +++ b/addons/gdUnit4/src/matchers/ChainedArgumentMatcher.gd @@ -0,0 +1,22 @@ +class_name ChainedArgumentMatcher +extends GdUnitArgumentMatcher + +var _matchers :Array + + +func _init(matchers :Array) -> void: + _matchers = matchers + + +func is_match(arguments :Variant) -> bool: + var arg_array: Array = arguments + if arg_array == null or arg_array.size() != _matchers.size(): + return false + + for index in arg_array.size(): + var arg: Variant = arg_array[index] + var matcher: GdUnitArgumentMatcher = _matchers[index] + + if not matcher.is_match(arg): + return false + return true diff --git a/addons/gdUnit4/src/matchers/ChainedArgumentMatcher.gd.uid b/addons/gdUnit4/src/matchers/ChainedArgumentMatcher.gd.uid new file mode 100644 index 0000000..bae9682 --- /dev/null +++ b/addons/gdUnit4/src/matchers/ChainedArgumentMatcher.gd.uid @@ -0,0 +1 @@ +uid://b1ibvs7v00e11 diff --git a/addons/gdUnit4/src/matchers/EqualsArgumentMatcher.gd b/addons/gdUnit4/src/matchers/EqualsArgumentMatcher.gd new file mode 100644 index 0000000..2d387ed --- /dev/null +++ b/addons/gdUnit4/src/matchers/EqualsArgumentMatcher.gd @@ -0,0 +1,22 @@ +class_name EqualsArgumentMatcher +extends GdUnitArgumentMatcher + +var _current :Variant +var _auto_deep_check_mode :bool + + +func _init(current :Variant, auto_deep_check_mode := false) -> void: + _current = current + _auto_deep_check_mode = auto_deep_check_mode + + +func is_match(value :Variant) -> bool: + var case_sensitive_check := true + return GdObjects.equals(_current, value, case_sensitive_check, compare_mode(value)) + + +func compare_mode(value :Variant) -> GdObjects.COMPARE_MODE: + if _auto_deep_check_mode and is_instance_valid(value): + # we do deep check on all InputEvent's + return GdObjects.COMPARE_MODE.PARAMETER_DEEP_TEST if value is InputEvent else GdObjects.COMPARE_MODE.OBJECT_REFERENCE + return GdObjects.COMPARE_MODE.OBJECT_REFERENCE diff --git a/addons/gdUnit4/src/matchers/EqualsArgumentMatcher.gd.uid b/addons/gdUnit4/src/matchers/EqualsArgumentMatcher.gd.uid new file mode 100644 index 0000000..e1b8a40 --- /dev/null +++ b/addons/gdUnit4/src/matchers/EqualsArgumentMatcher.gd.uid @@ -0,0 +1 @@ +uid://3rv37uckbmsc diff --git a/addons/gdUnit4/src/matchers/GdUnitArgumentMatcher.gd b/addons/gdUnit4/src/matchers/GdUnitArgumentMatcher.gd new file mode 100644 index 0000000..d5adc4b --- /dev/null +++ b/addons/gdUnit4/src/matchers/GdUnitArgumentMatcher.gd @@ -0,0 +1,13 @@ +## The base class of all argument matchers +class_name GdUnitArgumentMatcher +extends RefCounted + + +@warning_ignore("unused_parameter") +func is_match(value: Variant) -> bool: + return true + + +func _to_string() -> String: + assert(false, "`_to_string()` Is not implemented!") + return "" diff --git a/addons/gdUnit4/src/matchers/GdUnitArgumentMatcher.gd.uid b/addons/gdUnit4/src/matchers/GdUnitArgumentMatcher.gd.uid new file mode 100644 index 0000000..cf581b0 --- /dev/null +++ b/addons/gdUnit4/src/matchers/GdUnitArgumentMatcher.gd.uid @@ -0,0 +1 @@ +uid://gnrw3gtrr080 diff --git a/addons/gdUnit4/src/matchers/GdUnitArgumentMatchers.gd b/addons/gdUnit4/src/matchers/GdUnitArgumentMatchers.gd new file mode 100644 index 0000000..6a70cc1 --- /dev/null +++ b/addons/gdUnit4/src/matchers/GdUnitArgumentMatchers.gd @@ -0,0 +1,42 @@ +class_name GdUnitArgumentMatchers +extends RefCounted + +const TYPE_ANY = TYPE_MAX + 100 + + +static func to_matcher(arguments: Array[Variant], auto_deep_check_mode := false) -> ChainedArgumentMatcher: + var matchers: Array[Variant] = [] + for arg: Variant in arguments: + # argument is already a matcher + if arg is GdUnitArgumentMatcher: + matchers.append(arg) + else: + # pass argument into equals matcher + matchers.append(EqualsArgumentMatcher.new(arg, auto_deep_check_mode)) + return ChainedArgumentMatcher.new(matchers) + + +static func any() -> GdUnitArgumentMatcher: + return AnyArgumentMatcher.new() + + +static func by_type(type: int) -> GdUnitArgumentMatcher: + return AnyBuildInTypeArgumentMatcher.new([type]) + + +static func by_types(types: PackedInt32Array) -> GdUnitArgumentMatcher: + return AnyBuildInTypeArgumentMatcher.new(types) + + +static func any_class(clazz: Object) -> GdUnitArgumentMatcher: + return AnyClazzArgumentMatcher.new(clazz) + + +static func is_variant_string_matching(value: Variant) -> GdUnitResult: + if value is String or value is StringName: + return GdUnitResult.success() + if value is GdUnitArgumentMatcher: + if str(value) == "any()" or str(value) == "any_string()": + return GdUnitResult.success() + return GdUnitResult.error("Only 'any()' and 'any_string()' argument matchers are allowed!") + return GdUnitResult.error("Only String or StringName types are allowed!") diff --git a/addons/gdUnit4/src/matchers/GdUnitArgumentMatchers.gd.uid b/addons/gdUnit4/src/matchers/GdUnitArgumentMatchers.gd.uid new file mode 100644 index 0000000..7daa6f8 --- /dev/null +++ b/addons/gdUnit4/src/matchers/GdUnitArgumentMatchers.gd.uid @@ -0,0 +1 @@ +uid://cq56qi8qdeljh diff --git a/addons/gdUnit4/src/mocking/GdUnitMock.gd b/addons/gdUnit4/src/mocking/GdUnitMock.gd new file mode 100644 index 0000000..c520d92 --- /dev/null +++ b/addons/gdUnit4/src/mocking/GdUnitMock.gd @@ -0,0 +1,45 @@ +class_name GdUnitMock +extends RefCounted + +## do call the real implementation +const CALL_REAL_FUNC = "CALL_REAL_FUNC" +## do return a default value for primitive types or null +const RETURN_DEFAULTS = "RETURN_DEFAULTS" +## do return a default value for primitive types and a fully mocked value for Object types +## builds full deep mocked object +const RETURN_DEEP_STUB = "RETURN_DEEP_STUB" + +var _value: Variant + + +func _init(value: Variant) -> void: + _value = value + + +## Selects the mock to work on, used in combination with [method GdUnitTestSuite.do_return][br] +## Example: +## [codeblock] +## do_return(false).on(myMock).is_selected() +## [/codeblock] +func on(obj: Variant) -> Variant: + if not GdUnitMock._is_mock_or_spy(obj, "__do_return"): + return obj + @warning_ignore("unsafe_method_access") + return obj.__do_return(_value) + + +## [color=yellow]`checked` is obsolete, use `on` instead [/color] +func checked(obj :Object) -> Object: + push_warning("Using a deprecated function 'checked' use `on` instead") + return on(obj) + + +static func _is_mock_or_spy(obj: Variant, func_sig: String) -> bool: + if obj is Object and not as_object(obj).has_method(func_sig): + push_error("Error: You try to use a non mock or spy!") + return false + return true + + +static func as_object(value: Variant) -> Object: + return value diff --git a/addons/gdUnit4/src/mocking/GdUnitMock.gd.uid b/addons/gdUnit4/src/mocking/GdUnitMock.gd.uid new file mode 100644 index 0000000..4306144 --- /dev/null +++ b/addons/gdUnit4/src/mocking/GdUnitMock.gd.uid @@ -0,0 +1 @@ +uid://d203bemd7f27p diff --git a/addons/gdUnit4/src/mocking/GdUnitMockBuilder.gd b/addons/gdUnit4/src/mocking/GdUnitMockBuilder.gd new file mode 100644 index 0000000..537e923 --- /dev/null +++ b/addons/gdUnit4/src/mocking/GdUnitMockBuilder.gd @@ -0,0 +1,186 @@ +class_name GdUnitMockBuilder +extends GdUnitClassDoubler + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") +const MOCK_TEMPLATE :GDScript = preload("res://addons/gdUnit4/src/mocking/GdUnitMockImpl.gd") + + +static func is_push_errors() -> bool: + return GdUnitSettings.is_report_push_errors() + + +static func build(clazz :Variant, mock_mode :String, debug_write := false) -> Variant: + var push_errors := is_push_errors() + if not is_mockable(clazz, push_errors): + return null + # mocking a scene? + if GdObjects.is_scene(clazz): + var packed_scene: PackedScene = clazz + return mock_on_scene(packed_scene, debug_write) + elif typeof(clazz) == TYPE_STRING and str(clazz).ends_with(".tscn"): + var packed_scene: PackedScene = load(str(clazz)) + return mock_on_scene(packed_scene, debug_write) + # mocking a script + var instance := create_instance(clazz) + if instance == null: + push_error("Can't create instance of class %s" % clazz) + var mock := mock_on_script(instance, clazz, [ "get_script"], debug_write) + if not instance is RefCounted: + instance.free() + if mock == null: + return null + var mock_instance: Object = mock.new() + @warning_ignore("unsafe_method_access") + mock_instance.__init(mock, mock_mode) + return register_auto_free(mock_instance) + + +static func create_instance(clazz: Variant) -> Object: + match typeof(clazz): + TYPE_OBJECT: + var obj: Object = clazz + if clazz is GDScript: + var script: GDScript = clazz + var args := GdObjects.build_function_default_arguments(script, "_init") + return script.callv("new", args) + elif obj.is_class("GDScriptNativeClass"): + @warning_ignore("unsafe_method_access") + return obj.new() + TYPE_STRING: + var clazz_name: String = clazz + if clazz_name.ends_with(".gd"): + var script: GDScript = load(clazz_name) + var args := GdObjects.build_function_default_arguments(script, "_init") + return script.callv("new", args) + elif ClassDB.can_instantiate(clazz_name): + return ClassDB.instantiate(clazz_name) + + push_error("Can't create a mock validation instance from class: `%s`" % clazz) + return null + + +static func mock_on_scene(scene: PackedScene, debug_write: bool) -> Variant: + var push_errors := is_push_errors() + if not scene.can_instantiate(): + if push_errors: + push_error("Can't instanciate scene '%s'" % scene.resource_path) + return null + var scene_instance := scene.instantiate() + # we can only mock checked a scene with attached script + var scene_script: Script = scene_instance.get_script() + if scene_script == null: + if push_errors: + push_error("Can't create a mockable instance for a scene without script '%s'" % scene.resource_path) + @warning_ignore("return_value_discarded") + GdUnitTools.free_instance(scene_instance) + return null + + var script_path := scene_script.get_path() + var mock := mock_on_script(scene_instance, script_path, GdUnitClassDoubler.EXLCUDE_SCENE_FUNCTIONS, debug_write) + if mock == null: + return null + scene_instance.set_script(mock) + @warning_ignore("unsafe_method_access") + scene_instance.__init(mock, GdUnitMock.CALL_REAL_FUNC) + return register_auto_free(scene_instance) + + +static func get_class_info(clazz :Variant) -> Dictionary: + var clazz_name :String = GdObjects.extract_class_name(clazz).value() + var clazz_path := GdObjects.extract_class_path(clazz) + return { + "class_name" : clazz_name, + "class_path" : clazz_path + } + + +static func mock_on_script(instance :Object, clazz :Variant, function_excludes :PackedStringArray, debug_write :bool) -> GDScript: + var function_doubler := GdUnitMockFunctionDoubler.new() + var class_info := get_class_info(clazz) + var clazz_name :String = class_info.get("class_name") + var clazz_path :PackedStringArray = class_info.get("class_path", [clazz_name]) + var mock_template := MOCK_TEMPLATE.source_code.format({ + "instance_id" : abs(instance.get_instance_id()), + "gdunit_source_class": clazz_name if clazz_path.is_empty() else clazz_path[0] + }) + var lines := load_template(mock_template, class_info) + lines += double_functions(instance, clazz_name, clazz_path, function_doubler, function_excludes) + # We disable warning/errors for inferred_declaration + if Engine.get_version_info().hex >= 0x40400: + lines.insert(0, '@warning_ignore_start("inferred_declaration")') + lines.append('@warning_ignore_restore("inferred_declaration")') + + var mock := GDScript.new() + mock.source_code = "\n".join(lines) + mock.resource_name = "Mock%s_%d.gd" % [clazz_name, Time.get_ticks_msec()] + mock.resource_path = "%s/%s" % [GdUnitFileAccess.create_temp_dir("mock"), mock.resource_name] + + if debug_write: + @warning_ignore("return_value_discarded") + DirAccess.remove_absolute(mock.resource_path) + @warning_ignore("return_value_discarded") + ResourceSaver.save(mock, mock.resource_path) + var error := mock.reload(true) + if error != OK: + push_error("Critical!!!, MockBuilder error, please contact the developer.") + return null + return mock + + +static func is_mockable(clazz :Variant, push_errors :bool=false) -> bool: + var clazz_type := typeof(clazz) + if clazz_type != TYPE_OBJECT and clazz_type != TYPE_STRING: + push_error("Invalid clazz type is used") + return false + # is PackedScene + if GdObjects.is_scene(clazz): + return true + if GdObjects.is_native_class(clazz): + return true + # verify class type + if GdObjects.is_object(clazz): + if GdObjects.is_instance(clazz): + if push_errors: + push_error("It is not allowed to mock an instance '%s', use class name instead, Read 'Mocker' documentation for details" % clazz) + return false + + if not GdObjects.can_be_instantiate(clazz): + if push_errors: + push_error("Can't create a mockable instance for class '%s'" % clazz) + return false + return true + # verify by class name checked registered classes + var clazz_name: String = clazz + if ClassDB.class_exists(clazz_name): + if Engine.has_singleton(clazz_name): + if push_errors: + push_error("Mocking a singelton class '%s' is not allowed! Read 'Mocker' documentation for details" % clazz_name) + return false + if not ClassDB.can_instantiate(clazz_name): + if push_errors: + push_error("Mocking class '%s' is not allowed it cannot be instantiated!" % clazz_name) + return false + # exclude classes where name starts with a underscore + if clazz_name.find("_") == 0: + if push_errors: + push_error("Can't create a mockable instance for protected class '%s'" % clazz_name) + return false + return true + # at least try to load as a script + var clazz_path := clazz_name + if not FileAccess.file_exists(clazz_path): + if push_errors: + push_error("'%s' cannot be mocked for the specified resource path, the resource does not exist" % clazz_name) + return false + # finally verify is a script resource + var resource := load(clazz_path) + if resource == null: + if push_errors: + push_error("'%s' cannot be mocked the script cannot be loaded." % clazz_name) + return false + # finally check is extending from script + return GdObjects.is_script(resource) or GdObjects.is_scene(resource) + + +static func register_auto_free(obj :Variant) -> Variant: + return GdUnitThreadManager.get_current_context().get_execution_context().register_auto_free(obj) diff --git a/addons/gdUnit4/src/mocking/GdUnitMockBuilder.gd.uid b/addons/gdUnit4/src/mocking/GdUnitMockBuilder.gd.uid new file mode 100644 index 0000000..f9e9e0b --- /dev/null +++ b/addons/gdUnit4/src/mocking/GdUnitMockBuilder.gd.uid @@ -0,0 +1 @@ +uid://qigtmgr1t6rw diff --git a/addons/gdUnit4/src/mocking/GdUnitMockImpl.gd b/addons/gdUnit4/src/mocking/GdUnitMockImpl.gd new file mode 100644 index 0000000..774ca3e --- /dev/null +++ b/addons/gdUnit4/src/mocking/GdUnitMockImpl.gd @@ -0,0 +1,143 @@ +class_name DoubledMockClassSourceClassName + +################################################################################ +# internal mocking stuff +################################################################################ + +const __INSTANCE_ID := "gdunit_doubler_instance_id_{instance_id}" + + +class GdUnitMockDoublerState: + const __SOURCE_CLASS := "{gdunit_source_class}" + + var excluded_methods := PackedStringArray() + var working_mode := GdUnitMock.RETURN_DEFAULTS + var is_prepare_return := false + var return_values := Dictionary() + var return_value: Variant = null + + + func _init(working_mode_ := GdUnitMock.RETURN_DEFAULTS) -> void: + working_mode = working_mode_ + + +var __mock_state := GdUnitMockDoublerState.new() +@warning_ignore("unused_private_class_variable") +var __verifier_instance := GdUnitObjectInteractionsVerifier.new() + + +func __init(__script: GDScript, mock_working_mode: String) -> void: + super.set_script(__script) + __init_doubler() + __mock_state.working_mode = mock_working_mode + + +static func __doubler_state() -> GdUnitMockDoublerState: + if Engine.has_meta(__INSTANCE_ID): + return Engine.get_meta(__INSTANCE_ID).__mock_state + return null + + +func __init_doubler() -> void: + Engine.set_meta(__INSTANCE_ID, self) + + +func _notification(what: int) -> void: + if what == NOTIFICATION_PREDELETE and Engine.has_meta(__INSTANCE_ID): + Engine.remove_meta(__INSTANCE_ID) + + +static func __get_verifier() -> GdUnitObjectInteractionsVerifier: + return Engine.get_meta(__INSTANCE_ID).__verifier_instance + + +static func __is_prepare_return_value() -> bool: + return __doubler_state().is_prepare_return + + +static func __sort_by_argument_matcher(__left_args: Array, __right_args: Array) -> bool: + for __index in __left_args.size(): + var __larg: Variant = __left_args[__index] + if __larg is GdUnitArgumentMatcher: + return false + return true + + +# we need to sort by matcher arguments so that they are all at the end of the list +static func __sort_dictionary(__unsorted_args: Dictionary) -> Dictionary: + # only need to sort if contains more than one entry + if __unsorted_args.size() <= 1: + return __unsorted_args + var __sorted_args: Array = __unsorted_args.keys() + __sorted_args.sort_custom(__sort_by_argument_matcher) + var __sorted_result := {} + for __index in __sorted_args.size(): + var key :Variant = __sorted_args[__index] + __sorted_result[key] = __unsorted_args[key] + return __sorted_result + + +static func __save_function_return_value(__func_name: String, __func_args: Array) -> void: + var doubler_state := __doubler_state() + var mocked_return_value_by_args: Dictionary = doubler_state.return_values.get(__func_name, {}) + + mocked_return_value_by_args[__func_args] = doubler_state.return_value + doubler_state.return_values[__func_name] = __sort_dictionary(mocked_return_value_by_args) + doubler_state.return_value = null + doubler_state.is_prepare_return = false + + +static func __is_mocked_args_match(__func_args: Array, __mocked_args: Array) -> bool: + var __is_matching := false + for __index in __mocked_args.size(): + var __fuction_args: Array = __mocked_args[__index] + if __func_args.size() != __fuction_args.size(): + continue + __is_matching = true + for __arg_index in __func_args.size(): + var __func_arg: Variant = __func_args[__arg_index] + var __mock_arg: Variant = __fuction_args[__arg_index] + if __mock_arg is GdUnitArgumentMatcher: + @warning_ignore("unsafe_method_access") + __is_matching = __is_matching and __mock_arg.is_match(__func_arg) + else: + __is_matching = __is_matching and typeof(__func_arg) == typeof(__mock_arg) and __func_arg == __mock_arg + if not __is_matching: + break + if __is_matching: + break + return __is_matching + + +static func __return_mock_value(__func_name: String, __func_args: Array, __default_return_value: Variant) -> Variant: + var doubler_state := __doubler_state() + if not doubler_state.return_values.has(__func_name): + return __default_return_value + @warning_ignore("unsafe_method_access") + var __mocked_args: Array = doubler_state.return_values.get(__func_name).keys() + for __index in __mocked_args.size(): + var __margs: Variant = __mocked_args[__index] + if __is_mocked_args_match(__func_args, [__margs]): + return doubler_state.return_values[__func_name][__margs] + return __default_return_value + + +static func __is_do_not_call_real_func(__func_name: String, __func_args := []) -> bool: + var doubler_state := __doubler_state() + var __is_call_real_func: bool = doubler_state.working_mode == GdUnitMock.CALL_REAL_FUNC and not doubler_state.excluded_methods.has(__func_name) + # do not call real funcions for mocked functions + if __is_call_real_func and doubler_state.return_values.has(__func_name): + @warning_ignore("unsafe_method_access") + var __mocked_args: Array = doubler_state.return_values.get(__func_name).keys() + return __is_mocked_args_match(__func_args, __mocked_args) + return !__is_call_real_func + + +func __exclude_method_call(exluded_methods: PackedStringArray) -> void: + __doubler_state().excluded_methods.append_array(exluded_methods) + + +func __do_return(mock_do_return_value: Variant) -> Object: + __doubler_state().return_value = mock_do_return_value + __doubler_state().is_prepare_return = true + return self diff --git a/addons/gdUnit4/src/mocking/GdUnitMockImpl.gd.uid b/addons/gdUnit4/src/mocking/GdUnitMockImpl.gd.uid new file mode 100644 index 0000000..ae08593 --- /dev/null +++ b/addons/gdUnit4/src/mocking/GdUnitMockImpl.gd.uid @@ -0,0 +1 @@ +uid://dvnoeofv8yv31 diff --git a/addons/gdUnit4/src/monitor/ErrorLogEntry.gd b/addons/gdUnit4/src/monitor/ErrorLogEntry.gd new file mode 100644 index 0000000..5ee1487 --- /dev/null +++ b/addons/gdUnit4/src/monitor/ErrorLogEntry.gd @@ -0,0 +1,72 @@ +extends RefCounted +class_name ErrorLogEntry + + +enum TYPE { + SCRIPT_ERROR, + PUSH_ERROR, + PUSH_WARNING +} + + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") + +const PATTERN_SCRIPT_ERROR := "USER SCRIPT ERROR:" +const PATTERN_PUSH_ERROR := "USER ERROR:" +const PATTERN_PUSH_WARNING := "USER WARNING:" +# With Godot 4.4 the pattern has changed +const PATTERN_4x4_SCRIPT_ERROR := "SCRIPT ERROR:" +const PATTERN_4x4_PUSH_ERROR := "ERROR:" +const PATTERN_4x4_PUSH_WARNING := "WARNING:" + +static var _regex_parse_error_line_number: RegEx + +var _type: TYPE +var _line: int +var _message: String +var _details: String + + +func _init(type: TYPE, line: int, message: String, details: String) -> void: + _type = type + _line = line + _message = message + _details = details + + +static func is_godot4x4() -> bool: + return Engine.get_version_info().hex >= 0x40400 + + +static func extract_push_warning(records: PackedStringArray, index: int) -> ErrorLogEntry: + var pattern := PATTERN_4x4_PUSH_WARNING if is_godot4x4() else PATTERN_PUSH_WARNING + return _extract(records, index, TYPE.PUSH_WARNING, pattern) + + +static func extract_push_error(records: PackedStringArray, index: int) -> ErrorLogEntry: + var pattern := PATTERN_4x4_PUSH_ERROR if is_godot4x4() else PATTERN_PUSH_ERROR + return _extract(records, index, TYPE.PUSH_ERROR, pattern) + + +static func extract_error(records: PackedStringArray, index: int) -> ErrorLogEntry: + var pattern := PATTERN_4x4_SCRIPT_ERROR if is_godot4x4() else PATTERN_SCRIPT_ERROR + return _extract(records, index, TYPE.SCRIPT_ERROR, pattern) + + +static func _extract(records: PackedStringArray, index: int, type: TYPE, pattern: String) -> ErrorLogEntry: + var message := records[index] + if message.begins_with(pattern): + var error := message.replace(pattern, "").strip_edges() + var details := records[index+1].strip_edges() + var line := _parse_error_line_number(details) + return ErrorLogEntry.new(type, line, error, details) + return null + + +static func _parse_error_line_number(record: String) -> int: + if _regex_parse_error_line_number == null: + _regex_parse_error_line_number = GdUnitTools.to_regex("at: .*res://.*:(\\d+)") + var matches := _regex_parse_error_line_number.search(record) + if matches != null: + return matches.get_string(1).to_int() + return -1 diff --git a/addons/gdUnit4/src/monitor/ErrorLogEntry.gd.uid b/addons/gdUnit4/src/monitor/ErrorLogEntry.gd.uid new file mode 100644 index 0000000..11192c6 --- /dev/null +++ b/addons/gdUnit4/src/monitor/ErrorLogEntry.gd.uid @@ -0,0 +1 @@ +uid://b0bhhahs622mb diff --git a/addons/gdUnit4/src/monitor/GdUnitMonitor.gd b/addons/gdUnit4/src/monitor/GdUnitMonitor.gd new file mode 100644 index 0000000..b6429ca --- /dev/null +++ b/addons/gdUnit4/src/monitor/GdUnitMonitor.gd @@ -0,0 +1,24 @@ +# GdUnit Monitoring Base Class +class_name GdUnitMonitor +extends RefCounted + +var _id :String + +# constructs new Monitor with given id +func _init(p_id :String) -> void: + _id = p_id + + +# Returns the id of the monitor to uniqe identify +func id() -> String: + return _id + + +# starts monitoring +func start() -> void: + pass + + +# stops monitoring +func stop() -> void: + pass diff --git a/addons/gdUnit4/src/monitor/GdUnitMonitor.gd.uid b/addons/gdUnit4/src/monitor/GdUnitMonitor.gd.uid new file mode 100644 index 0000000..70d788e --- /dev/null +++ b/addons/gdUnit4/src/monitor/GdUnitMonitor.gd.uid @@ -0,0 +1 @@ +uid://b627xg8ydggdk diff --git a/addons/gdUnit4/src/monitor/GdUnitOrphanNodesMonitor.gd b/addons/gdUnit4/src/monitor/GdUnitOrphanNodesMonitor.gd new file mode 100644 index 0000000..725dd1f --- /dev/null +++ b/addons/gdUnit4/src/monitor/GdUnitOrphanNodesMonitor.gd @@ -0,0 +1,27 @@ +class_name GdUnitOrphanNodesMonitor +extends GdUnitMonitor + +var _initial_count := 0 +var _orphan_count := 0 +var _orphan_detection_enabled :bool + + +func _init(name :String = "") -> void: + super("OrphanNodesMonitor:" + name) + _orphan_detection_enabled = GdUnitSettings.is_verbose_orphans() + + +func start() -> void: + _initial_count = _orphans() + + +func stop() -> void: + _orphan_count = max(0, _orphans() - _initial_count) + + +func _orphans() -> int: + return Performance.get_monitor(Performance.OBJECT_ORPHAN_NODE_COUNT) as int + + +func orphan_nodes() -> int: + return _orphan_count if _orphan_detection_enabled else 0 diff --git a/addons/gdUnit4/src/monitor/GdUnitOrphanNodesMonitor.gd.uid b/addons/gdUnit4/src/monitor/GdUnitOrphanNodesMonitor.gd.uid new file mode 100644 index 0000000..cf31b30 --- /dev/null +++ b/addons/gdUnit4/src/monitor/GdUnitOrphanNodesMonitor.gd.uid @@ -0,0 +1 @@ +uid://dn4kdg6d08wou diff --git a/addons/gdUnit4/src/monitor/GodotGdErrorMonitor.gd b/addons/gdUnit4/src/monitor/GodotGdErrorMonitor.gd new file mode 100644 index 0000000..b073705 --- /dev/null +++ b/addons/gdUnit4/src/monitor/GodotGdErrorMonitor.gd @@ -0,0 +1,100 @@ +class_name GodotGdErrorMonitor +extends GdUnitMonitor + +var _godot_log_file: String +var _eof: int +var _report_enabled := false +var _entries: Array[ErrorLogEntry] = [] + + +func _init() -> void: + super("GodotGdErrorMonitor") + _godot_log_file = GdUnitSettings.get_log_path() + _report_enabled = _is_reporting_enabled() + + +func start() -> void: + var file := FileAccess.open(_godot_log_file, FileAccess.READ) + if file: + file.seek_end(0) + _eof = file.get_length() + + +func stop() -> void: + pass + + +func to_reports() -> Array[GdUnitReport]: + var reports_: Array[GdUnitReport] = [] + if _report_enabled: + reports_.assign(_entries.map(_to_report)) + _entries.clear() + return reports_ + + +static func _to_report(errorLog: ErrorLogEntry) -> GdUnitReport: + var failure := "%s\n\t%s\n%s %s" % [ + GdAssertMessages._error("Godot Runtime Error !"), + GdAssertMessages._colored_value(errorLog._details), + GdAssertMessages._error("Error:"), + GdAssertMessages._colored_value(errorLog._message)] + return GdUnitReport.new().create(GdUnitReport.ABORT, errorLog._line, failure) + + +func scan(force_collect_reports := false) -> Array[ErrorLogEntry]: + await (Engine.get_main_loop() as SceneTree).process_frame + await (Engine.get_main_loop() as SceneTree).physics_frame + _entries.append_array(_collect_log_entries(force_collect_reports)) + return _entries + + +func erase_log_entry(entry: ErrorLogEntry) -> void: + _entries.erase(entry) + + +func collect_full_logs() -> PackedStringArray: + await (Engine.get_main_loop() as SceneTree).process_frame + await (Engine.get_main_loop() as SceneTree).physics_frame + + var file := FileAccess.open(_godot_log_file, FileAccess.READ) + file.seek(_eof) + var records := PackedStringArray() + while not file.eof_reached(): + @warning_ignore("return_value_discarded") + records.append(file.get_line()) + + return records + + +func _collect_log_entries(force_collect_reports: bool) -> Array[ErrorLogEntry]: + var file := FileAccess.open(_godot_log_file, FileAccess.READ) + file.seek(_eof) + var records := PackedStringArray() + while not file.eof_reached(): + @warning_ignore("return_value_discarded") + records.append(file.get_line()) + file.seek_end(0) + _eof = file.get_length() + var log_entries: Array[ErrorLogEntry]= [] + var is_report_errors := force_collect_reports or _is_report_push_errors() + var is_report_script_errors := force_collect_reports or _is_report_script_errors() + for index in records.size(): + if force_collect_reports: + log_entries.append(ErrorLogEntry.extract_push_warning(records, index)) + if is_report_errors: + log_entries.append(ErrorLogEntry.extract_push_error(records, index)) + if is_report_script_errors: + log_entries.append(ErrorLogEntry.extract_error(records, index)) + return log_entries.filter(func(value: ErrorLogEntry) -> bool: return value != null ) + + +func _is_reporting_enabled() -> bool: + return _is_report_script_errors() or _is_report_push_errors() + + +func _is_report_push_errors() -> bool: + return GdUnitSettings.is_report_push_errors() + + +func _is_report_script_errors() -> bool: + return GdUnitSettings.is_report_script_errors() diff --git a/addons/gdUnit4/src/monitor/GodotGdErrorMonitor.gd.uid b/addons/gdUnit4/src/monitor/GodotGdErrorMonitor.gd.uid new file mode 100644 index 0000000..7c91ffb --- /dev/null +++ b/addons/gdUnit4/src/monitor/GodotGdErrorMonitor.gd.uid @@ -0,0 +1 @@ +uid://p5rodklo3mqc diff --git a/addons/gdUnit4/src/network/GdUnitServer.gd b/addons/gdUnit4/src/network/GdUnitServer.gd new file mode 100644 index 0000000..6d878a0 --- /dev/null +++ b/addons/gdUnit4/src/network/GdUnitServer.gd @@ -0,0 +1,42 @@ +@tool +extends Node + +@onready var _server :GdUnitTcpServer = $TcpServer + + +@warning_ignore("return_value_discarded") +func _ready() -> void: + var result := _server.start() + if result.is_error(): + push_error(result.error_message()) + return + var server_port :int = result.value() + Engine.set_meta("gdunit_server_port", server_port) + _server.client_connected.connect(_on_client_connected) + _server.client_disconnected.connect(_on_client_disconnected) + _server.rpc_data.connect(_receive_rpc_data) + GdUnitCommandHandler.instance().gdunit_runner_stop.connect(_on_gdunit_runner_stop) + + +func _on_client_connected(client_id: int) -> void: + GdUnitSignals.instance().gdunit_client_connected.emit(client_id) + + +func _on_client_disconnected(client_id: int) -> void: + GdUnitSignals.instance().gdunit_client_disconnected.emit(client_id) + + +func _on_gdunit_runner_stop(client_id: int) -> void: + if _server: + _server.disconnect_client(client_id) + + +func _receive_rpc_data(p_rpc: RPC) -> void: + if p_rpc is RPCMessage: + var rpc_message: RPCMessage = p_rpc + GdUnitSignals.instance().gdunit_message.emit(rpc_message.message()) + return + if p_rpc is RPCGdUnitEvent: + var rpc_event: RPCGdUnitEvent = p_rpc + GdUnitSignals.instance().gdunit_event.emit(rpc_event.event()) + return diff --git a/addons/gdUnit4/src/network/GdUnitServer.gd.uid b/addons/gdUnit4/src/network/GdUnitServer.gd.uid new file mode 100644 index 0000000..b8f61b8 --- /dev/null +++ b/addons/gdUnit4/src/network/GdUnitServer.gd.uid @@ -0,0 +1 @@ +uid://cwutppvonjx3g diff --git a/addons/gdUnit4/src/network/GdUnitServer.tscn b/addons/gdUnit4/src/network/GdUnitServer.tscn new file mode 100644 index 0000000..2df17e6 --- /dev/null +++ b/addons/gdUnit4/src/network/GdUnitServer.tscn @@ -0,0 +1,10 @@ +[gd_scene load_steps=3 format=3 uid="uid://cn5mp3tmi2gb1"] + +[ext_resource type="Script" uid="uid://cwutppvonjx3g" path="res://addons/gdUnit4/src/network/GdUnitServer.gd" id="1"] +[ext_resource type="Script" uid="uid://4iftaidm3f35" path="res://addons/gdUnit4/src/network/GdUnitTcpServer.gd" id="2"] + +[node name="Control" type="Node"] +script = ExtResource("1") + +[node name="TcpServer" type="Node" parent="."] +script = ExtResource("2") diff --git a/addons/gdUnit4/src/network/GdUnitServerConstants.gd b/addons/gdUnit4/src/network/GdUnitServerConstants.gd new file mode 100644 index 0000000..d31eee7 --- /dev/null +++ b/addons/gdUnit4/src/network/GdUnitServerConstants.gd @@ -0,0 +1,6 @@ +class_name GdUnitServerConstants +extends RefCounted + +const DEFAULT_SERVER_START_RETRY_TIMES :int = 5 +const GD_TEST_SERVER_PORT :int = 31002 +const JSON_RESPONSE_DELIMITER :String = "<>" diff --git a/addons/gdUnit4/src/network/GdUnitServerConstants.gd.uid b/addons/gdUnit4/src/network/GdUnitServerConstants.gd.uid new file mode 100644 index 0000000..fee1c36 --- /dev/null +++ b/addons/gdUnit4/src/network/GdUnitServerConstants.gd.uid @@ -0,0 +1 @@ +uid://dkw3tyl5u5jq1 diff --git a/addons/gdUnit4/src/network/GdUnitTask.gd b/addons/gdUnit4/src/network/GdUnitTask.gd new file mode 100644 index 0000000..e0188a0 --- /dev/null +++ b/addons/gdUnit4/src/network/GdUnitTask.gd @@ -0,0 +1,25 @@ +class_name GdUnitTask +extends RefCounted + +const TASK_NAME = "task_name" +const TASK_ARGS = "task_args" + +var _task_name :String +var _fref :Callable + + +func _init(task_name :String,instance :Object,func_name :String) -> void: + _task_name = task_name + if not instance.has_method(func_name): + push_error("Can't create GdUnitTask, Invalid func name '%s' for instance '%s'" % [instance, func_name]) + _fref = Callable(instance, func_name) + + +func name() -> String: + return _task_name + + +func execute(args :Array) -> GdUnitResult: + if args.is_empty(): + return _fref.call() + return _fref.callv(args) diff --git a/addons/gdUnit4/src/network/GdUnitTask.gd.uid b/addons/gdUnit4/src/network/GdUnitTask.gd.uid new file mode 100644 index 0000000..96d8c79 --- /dev/null +++ b/addons/gdUnit4/src/network/GdUnitTask.gd.uid @@ -0,0 +1 @@ +uid://d0ky1wr7bfdsv diff --git a/addons/gdUnit4/src/network/GdUnitTcpClient.gd b/addons/gdUnit4/src/network/GdUnitTcpClient.gd new file mode 100644 index 0000000..2cf32a3 --- /dev/null +++ b/addons/gdUnit4/src/network/GdUnitTcpClient.gd @@ -0,0 +1,124 @@ +class_name GdUnitTcpClient +extends GdUnitTcpNode + +signal connection_succeeded(message: String) +signal connection_failed(message: String) + + +var _client_name: String +var _debug := false +var _host: String +var _port: int +var _client_id: int +var _connected: bool +var _stream: StreamPeerTCP + + +func _init(client_name := "GdUnit4 TCP Client", debug := false) -> void: + _client_name = client_name + _debug = debug + + +func _ready() -> void: + _connected = false + _stream = StreamPeerTCP.new() + #_stream.set_big_endian(true) + + +func stop() -> void: + console("Disconnecting from server") + if _stream != null: + rpc_send(_stream, RPCClientDisconnect.new().with_id(_client_id)) + if _stream != null: + _stream.disconnect_from_host() + _connected = false + + +func start(host: String, port: int) -> GdUnitResult: + _host = host + _port = port + if _connected: + return GdUnitResult.warn("Client already connected ... %s:%d" % [_host, _port]) + + # Connect client to server + if _stream.get_status() != StreamPeerTCP.STATUS_CONNECTED: + var err := _stream.connect_to_host(host, port) + #prints("connect_to_host", host, port, err) + if err != OK: + return GdUnitResult.error("GdUnit4: Can't establish client, error code: %s" % err) + return GdUnitResult.success("GdUnit4: Client connected checked port %d" % port) + + +func _process(_delta: float) -> void: + match _stream.get_status(): + StreamPeerTCP.STATUS_NONE: + return + + StreamPeerTCP.STATUS_CONNECTING: + set_process(false) + # wait until client is connected to server + for retry in 10: + @warning_ignore("return_value_discarded") + _stream.poll() + console("Waiting to connect ..") + if _stream.get_status() == StreamPeerTCP.STATUS_CONNECTING: + await get_tree().create_timer(0.500).timeout + if _stream.get_status() == StreamPeerTCP.STATUS_CONNECTED: + set_process(true) + return + set_process(true) + _stream.disconnect_from_host() + console("Connection failed") + connection_failed.emit("Connect to TCP Server %s:%d faild!" % [_host, _port]) + + StreamPeerTCP.STATUS_CONNECTED: + if not _connected: + var rpc_data :RPC = null + set_process(false) + while rpc_data == null: + await get_tree().create_timer(0.500).timeout + rpc_data = rpc_receive() + set_process(true) + _client_id = (rpc_data as RPCClientConnect).client_id() + console("Connected to Server: %d" % _client_id) + connection_succeeded.emit("Connect to TCP Server %s:%d success." % [_host, _port]) + _connected = true + process_rpc() + + StreamPeerTCP.STATUS_ERROR: + console("Connection failed") + _stream.disconnect_from_host() + connection_failed.emit("Connect to TCP Server %s:%d faild!" % [_host, _port]) + return + + +func is_client_connected() -> bool: + return _connected + + +func process_rpc() -> void: + if _stream.get_available_bytes() > 0: + var rpc_data := rpc_receive() + if rpc_data is RPCClientDisconnect: + stop() + + +func send(data: RPC) -> void: + rpc_send(_stream, data) + + +func rpc_receive() -> RPC: + return receive_packages(_stream).front() + + +func console(value: Variant) -> void: + if _debug: + print(_client_name, ": ", value) + + +func _on_connection_failed(message: String) -> void: + console("Connection faild by: " + message) + + +func _on_connection_succeeded(message: String) -> void: + console("Connected: " + message) diff --git a/addons/gdUnit4/src/network/GdUnitTcpClient.gd.uid b/addons/gdUnit4/src/network/GdUnitTcpClient.gd.uid new file mode 100644 index 0000000..73a1e5c --- /dev/null +++ b/addons/gdUnit4/src/network/GdUnitTcpClient.gd.uid @@ -0,0 +1 @@ +uid://cuwwf10v6cxiy diff --git a/addons/gdUnit4/src/network/GdUnitTcpNode.gd b/addons/gdUnit4/src/network/GdUnitTcpNode.gd new file mode 100644 index 0000000..156c764 --- /dev/null +++ b/addons/gdUnit4/src/network/GdUnitTcpNode.gd @@ -0,0 +1,73 @@ +class_name GdUnitTcpNode +extends Node + + +func rpc_send(stream: StreamPeerTCP, data: RPC) -> void: + var package_buffer := StreamPeerBuffer.new() + var buffer := data.serialize().to_utf16_buffer() + package_buffer.put_u32(0xDEADBEEF) + package_buffer.put_u32(buffer.size()) + var status_code := package_buffer.put_data(buffer) + if status_code != OK: + push_error("'rpc_send:' Can't put_data(), error: %s" % error_string(status_code)) + return + stream.put_data(package_buffer.data_array) + + +func receive_packages(stream: StreamPeerTCP, rpc_cb: Callable = noop) -> Array[RPC]: + var received_packages: Array[RPC] = [] + var package_buffer := StreamPeerBuffer.new() + if stream.get_status() != StreamPeerTCP.STATUS_CONNECTED: + return received_packages + + while stream.get_status() == StreamPeerTCP.STATUS_CONNECTED and stream.get_available_bytes() > 0: + var buffer := stream.get_data(8) + var status_code: int = buffer[0] + if status_code != OK: + push_error("'receive_packages:' Can't get_data(%d) for available_bytes, error: %s" + % [stream.get_available_bytes(), error_string(status_code)]) + return received_packages + + var data_package: PackedByteArray + package_buffer.data_array = buffer[1] + package_buffer.seek(0) + + if package_buffer.get_u32() == 0xDEADBEEF: + var size := package_buffer.get_u32() + if stream.get_status() != StreamPeerTCP.STATUS_CONNECTED: + return received_packages + if stream.get_available_bytes() < size: + prints("size check:", + package_buffer.get_size(), ":", + package_buffer.get_position(), + "to read:", + size, + "available size:", + stream.get_available_bytes()) + push_error("'receive_packages:' Can't receive data get_data(%d) for package, error: %s" % [size, error_string(status_code)]) + return received_packages + + buffer = stream.get_data(size) + package_buffer.data_array = buffer[1] + + var rpc_data := package_buffer.get_data(size) + status_code = rpc_data[0] + if status_code != OK: + push_error("'receive_packages:' Can't get_data(%d) for package, error: %s" % [size, error_string(status_code)]) + continue + data_package = rpc_data[1] + else: + data_package = buffer[1] + + var json := data_package.get_string_from_utf16() + if json.is_empty(): + push_warning("json is empty, can't process data") + continue + var data := RPC.deserialize(json) + received_packages.append(data) + rpc_cb.call(data) + return received_packages + + +static func noop(_rpc_data: RPC) -> void: + pass diff --git a/addons/gdUnit4/src/network/GdUnitTcpNode.gd.uid b/addons/gdUnit4/src/network/GdUnitTcpNode.gd.uid new file mode 100644 index 0000000..8043119 --- /dev/null +++ b/addons/gdUnit4/src/network/GdUnitTcpNode.gd.uid @@ -0,0 +1 @@ +uid://dbvfu7eapxtyo diff --git a/addons/gdUnit4/src/network/GdUnitTcpServer.gd b/addons/gdUnit4/src/network/GdUnitTcpServer.gd new file mode 100644 index 0000000..4687ac1 --- /dev/null +++ b/addons/gdUnit4/src/network/GdUnitTcpServer.gd @@ -0,0 +1,129 @@ +@tool +class_name GdUnitTcpServer +extends Node + +signal client_connected(client_id: int) +signal client_disconnected(client_id: int) +@warning_ignore("unused_signal") +signal rpc_data(rpc_data: RPC) + +var _server: TCPServer +var _server_name: String + +class TcpConnection extends GdUnitTcpNode: + var _id: int + var _stream: StreamPeerTCP + + + func _init(tcp_server: TCPServer) -> void: + _stream = tcp_server.take_connection() + #_stream.set_big_endian(true) + _id = _stream.get_instance_id() + rpc_send(_stream, RPCClientConnect.new().with_id(_id)) + + + func _ready() -> void: + server().client_connected.emit(_id) + + + func close() -> void: + if _stream != null and _stream.get_status() == StreamPeerTCP.STATUS_CONNECTED: + _stream.disconnect_from_host() + queue_free() + + + func id() -> int: + return _id + + + func server() -> GdUnitTcpServer: + return get_parent() + + + func _process(_delta: float) -> void: + if _stream == null or _stream.get_status() != StreamPeerTCP.STATUS_CONNECTED: + return + receive_packages(_stream, func(rpc_data: RPC) -> void: + server().rpc_data.emit(rpc_data) + # is client disconnecting we close the server after a timeout of 1 second + if rpc_data is RPCClientDisconnect: + close() + ) + + + func console(_value: Variant) -> void: + #print_debug("TCP Server: ", value) + pass + + +func _init(server_name := "GdUnit4 TCP Server") -> void: + _server_name = server_name + + +func _ready() -> void: + _server = TCPServer.new() + client_connected.connect(_on_client_connected) + client_disconnected.connect(_on_client_disconnected) + + +func _notification(what: int) -> void: + if what == NOTIFICATION_PREDELETE: + stop() + + +func start(server_port := GdUnitServerConstants.GD_TEST_SERVER_PORT) -> GdUnitResult: + var err := OK + for retry in GdUnitServerConstants.DEFAULT_SERVER_START_RETRY_TIMES: + err = _server.listen(server_port, "127.0.0.1") + if err != OK: + prints("GdUnit4: Can't establish server checked port: %d, Error: %s" % [server_port, error_string(err)]) + server_port += 1 + prints("GdUnit4: Retry (%d) ..." % retry) + else: + break + if err != OK: + if err == ERR_ALREADY_IN_USE: + return GdUnitResult.error("GdUnit4: Can't establish server, the server is already in use. Error: %s, " % error_string(err)) + return GdUnitResult.error("GdUnit4: Can't establish server. Error: %s." % error_string(err)) + console("Successfully started checked port: %d" % server_port) + return GdUnitResult.success(server_port) + + +func stop() -> void: + if _server: + _server.stop() + for connection in get_children(): + if connection is TcpConnection: + @warning_ignore("unsafe_method_access") + connection.close() + remove_child(connection) + _server = null + + +func disconnect_client(client_id: int) -> void: + client_disconnected.emit(client_id) + + +func _process(_delta: float) -> void: + if _server != null and not _server.is_listening(): + return + # check if connection is ready to be used + if _server != null and _server.is_connection_available(): + add_child(TcpConnection.new(_server)) + + +func _on_client_connected(client_id: int) -> void: + console("Client connected %d" % client_id) + + +func _on_client_disconnected(client_id: int) -> void: + for connection in get_children(): + @warning_ignore("unsafe_method_access") + if connection is TcpConnection and connection.id() == client_id: + @warning_ignore("unsafe_method_access") + connection.close() + remove_child(connection) + + +func console(value: Variant) -> void: + print(_server_name, ": ", value) diff --git a/addons/gdUnit4/src/network/GdUnitTcpServer.gd.uid b/addons/gdUnit4/src/network/GdUnitTcpServer.gd.uid new file mode 100644 index 0000000..7561c4d --- /dev/null +++ b/addons/gdUnit4/src/network/GdUnitTcpServer.gd.uid @@ -0,0 +1 @@ +uid://4iftaidm3f35 diff --git a/addons/gdUnit4/src/network/rpc/RPC.gd b/addons/gdUnit4/src/network/rpc/RPC.gd new file mode 100644 index 0000000..6569cb1 --- /dev/null +++ b/addons/gdUnit4/src/network/rpc/RPC.gd @@ -0,0 +1,37 @@ +class_name RPC +extends RefCounted + + +var _data: Dictionary = {} + + +func _init(obj: Object = null) -> void: + if obj != null: + if obj.has_method("serialize"): + _data = obj.call("serialize") + else: + _data = inst_to_dict(obj) + + +func get_data() -> Object: + return dict_to_inst(_data) + + +func serialize() -> String: + return JSON.stringify(inst_to_dict(self)) + + +# using untyped version see comments below +static func deserialize(json_value: String) -> Object: + var json := JSON.new() + var err := json.parse(json_value) + if err != OK: + push_error("Can't deserialize JSON, error at line %d:\n error: %s \n json: '%s'" + % [json.get_error_line(), json.get_error_message(), json_value]) + return null + var result: Dictionary = json.get_data() + if not typeof(result) == TYPE_DICTIONARY: + push_error("Can't deserialize JSON. Expecting dictionary, error at line %d:\n error: %s \n json: '%s'" + % [result.error_line, result.error_string, json_value]) + return null + return dict_to_inst(result) diff --git a/addons/gdUnit4/src/network/rpc/RPC.gd.uid b/addons/gdUnit4/src/network/rpc/RPC.gd.uid new file mode 100644 index 0000000..807b8ab --- /dev/null +++ b/addons/gdUnit4/src/network/rpc/RPC.gd.uid @@ -0,0 +1 @@ +uid://bxnb1dokwjvg diff --git a/addons/gdUnit4/src/network/rpc/RPCClientConnect.gd b/addons/gdUnit4/src/network/rpc/RPCClientConnect.gd new file mode 100644 index 0000000..6b494cf --- /dev/null +++ b/addons/gdUnit4/src/network/rpc/RPCClientConnect.gd @@ -0,0 +1,13 @@ +class_name RPCClientConnect +extends RPC + +var _client_id: int + + +func with_id(id: int) -> RPCClientConnect: + _client_id = id + return self + + +func client_id() -> int: + return _client_id diff --git a/addons/gdUnit4/src/network/rpc/RPCClientConnect.gd.uid b/addons/gdUnit4/src/network/rpc/RPCClientConnect.gd.uid new file mode 100644 index 0000000..12e7fda --- /dev/null +++ b/addons/gdUnit4/src/network/rpc/RPCClientConnect.gd.uid @@ -0,0 +1 @@ +uid://bohkbaqeiln13 diff --git a/addons/gdUnit4/src/network/rpc/RPCClientDisconnect.gd b/addons/gdUnit4/src/network/rpc/RPCClientDisconnect.gd new file mode 100644 index 0000000..7445b9d --- /dev/null +++ b/addons/gdUnit4/src/network/rpc/RPCClientDisconnect.gd @@ -0,0 +1,13 @@ +class_name RPCClientDisconnect +extends RPC + +var _client_id: int + + +func with_id(id: int) -> RPCClientDisconnect: + _client_id = id + return self + + +func client_id() -> int: + return _client_id diff --git a/addons/gdUnit4/src/network/rpc/RPCClientDisconnect.gd.uid b/addons/gdUnit4/src/network/rpc/RPCClientDisconnect.gd.uid new file mode 100644 index 0000000..4cc470b --- /dev/null +++ b/addons/gdUnit4/src/network/rpc/RPCClientDisconnect.gd.uid @@ -0,0 +1 @@ +uid://dnms5784bc0sf diff --git a/addons/gdUnit4/src/network/rpc/RPCGdUnitEvent.gd b/addons/gdUnit4/src/network/rpc/RPCGdUnitEvent.gd new file mode 100644 index 0000000..dbf55c6 --- /dev/null +++ b/addons/gdUnit4/src/network/rpc/RPCGdUnitEvent.gd @@ -0,0 +1,14 @@ +class_name RPCGdUnitEvent +extends RPC + + +static func of(p_event: GdUnitEvent) -> RPCGdUnitEvent: + return RPCGdUnitEvent.new(p_event) + + +func event() -> GdUnitEvent: + return GdUnitEvent.new().deserialize(_data) + + +func _to_string() -> String: + return "RPCGdUnitEvent: " + str(_data) diff --git a/addons/gdUnit4/src/network/rpc/RPCGdUnitEvent.gd.uid b/addons/gdUnit4/src/network/rpc/RPCGdUnitEvent.gd.uid new file mode 100644 index 0000000..f9952ca --- /dev/null +++ b/addons/gdUnit4/src/network/rpc/RPCGdUnitEvent.gd.uid @@ -0,0 +1 @@ +uid://4ac5xwyloyrp diff --git a/addons/gdUnit4/src/network/rpc/RPCMessage.gd b/addons/gdUnit4/src/network/rpc/RPCMessage.gd new file mode 100644 index 0000000..1db0470 --- /dev/null +++ b/addons/gdUnit4/src/network/rpc/RPCMessage.gd @@ -0,0 +1,18 @@ +class_name RPCMessage +extends RPC + +var _message: String + + +static func of(msg :String) -> RPCMessage: + var rpc := RPCMessage.new() + rpc._message = msg + return rpc + + +func message() -> String: + return _message + + +func _to_string() -> String: + return "RPCMessage: " + _message diff --git a/addons/gdUnit4/src/network/rpc/RPCMessage.gd.uid b/addons/gdUnit4/src/network/rpc/RPCMessage.gd.uid new file mode 100644 index 0000000..fdb9e18 --- /dev/null +++ b/addons/gdUnit4/src/network/rpc/RPCMessage.gd.uid @@ -0,0 +1 @@ +uid://ben2x831k6qts diff --git a/addons/gdUnit4/src/reporters/GdUnitReportSummary.gd b/addons/gdUnit4/src/reporters/GdUnitReportSummary.gd new file mode 100644 index 0000000..b55b964 --- /dev/null +++ b/addons/gdUnit4/src/reporters/GdUnitReportSummary.gd @@ -0,0 +1,202 @@ +class_name GdUnitReportSummary +extends RefCounted + +var _resource_path: String +var _name: String +var _test_count := 0 +var _failure_count := 0 +var _error_count := 0 +var _orphan_count := 0 +var _skipped_count := 0 +var _flaky_count := 0 +var _duration := 0 +var _reports: Array[GdUnitReportSummary] = [] +var _text_formatter: Callable + + +func _init(text_formatter: Callable) -> void: + _text_formatter = text_formatter + + +func name() -> String: + return _name + + +func path() -> String: + return _resource_path.get_base_dir().replace("res://", "") + + +func get_resource_path() -> String: + return _resource_path + + +func suite_count() -> int: + return _reports.size() + + +func suite_executed_count() -> int: + var executed := _reports.size() + for report in _reports: + if report.test_count() == report.skipped_count(): + executed -= 1 + return executed + + +func test_count() -> int: + var count := _test_count + for report in _reports: + count += report.test_count() + return count + + +func test_executed_count() -> int: + return test_count() - skipped_count() + + +func success_count() -> int: + return test_count() - error_count() - failure_count() - flaky_count() - skipped_count() + + +func error_count() -> int: + return _error_count + + +func failure_count() -> int: + return _failure_count + + +func skipped_count() -> int: + return _skipped_count + + +func flaky_count() -> int: + return _flaky_count + + +func orphan_count() -> int: + return _orphan_count + + +func duration() -> int: + return _duration + + +func get_reports() -> Array: + return _reports + + +func add_report(report: GdUnitReportSummary) -> void: + _reports.append(report) + + +func report_state() -> String: + return calculate_state(error_count(), failure_count(), orphan_count(), flaky_count(), skipped_count()) + + +func succes_rate() -> String: + return calculate_succes_rate(test_count(), error_count(), failure_count()) + + +@warning_ignore("shadowed_variable") +func add_testcase(resource_path: String, suite_name: String, test_name: String) -> void: + for report: GdUnitTestSuiteReport in _reports: + if report.get_resource_path() == resource_path: + var test_report := GdUnitTestCaseReport.new(resource_path, suite_name, test_name, _text_formatter) + report.add_or_create_test_report(test_report) + + +func add_reports( + p_resource_path: String, + p_test_name: String, + p_reports: Array[GdUnitReport]) -> void: + + for report:GdUnitTestSuiteReport in _reports: + if report.get_resource_path() == p_resource_path: + report.add_testcase_reports(p_test_name, p_reports) + + +func add_testsuite_report(p_resource_path: String, p_suite_name: String, p_test_count: int) -> void: + _reports.append(GdUnitTestSuiteReport.new(p_resource_path, p_suite_name, p_test_count, _text_formatter)) + + +func add_testsuite_reports( + p_resource_path: String, + p_reports: Array = []) -> void: + + for report:GdUnitTestSuiteReport in _reports: + if report.get_resource_path() == p_resource_path: + report.set_reports(p_reports) + + +func set_counters( + p_resource_path: String, + p_test_name: String, + p_error_count: int, + p_failure_count: int, + p_orphan_count: int, + p_is_skipped: bool, + p_is_flaky: bool, + p_duration: int) -> void: + + for report: GdUnitTestSuiteReport in _reports: + if report.get_resource_path() == p_resource_path: + report.set_testcase_counters(p_test_name, p_error_count, p_failure_count, p_orphan_count, + p_is_skipped, p_is_flaky, p_duration) + + +func update_testsuite_counters( + p_resource_path: String, + p_error_count: int, + p_failure_count: int, + p_orphan_count: int, + p_skipped_count: int, + p_flaky_count: int, + p_duration: int) -> void: + + for report:GdUnitTestSuiteReport in _reports: + if report.get_resource_path() == p_resource_path: + report._update_testsuite_counters(p_error_count, p_failure_count, p_orphan_count, p_skipped_count, p_flaky_count, p_duration) + _update_summary_counters(p_error_count, p_failure_count, p_orphan_count, p_skipped_count, p_flaky_count, 0) + + +func _update_summary_counters( + p_error_count: int, + p_failure_count: int, + p_orphan_count: int, + p_skipped_count: int, + p_flaky_count: int, + p_duration: int) -> void: + + _error_count += p_error_count + _failure_count += p_failure_count + _orphan_count += p_orphan_count + _skipped_count += p_skipped_count + _flaky_count += p_flaky_count + _duration += p_duration + + +func calculate_state(p_error_count :int, p_failure_count :int, p_orphan_count :int, p_flaky_count: int, p_skipped_count: int) -> String: + if p_error_count > 0: + return "ERROR" + if p_failure_count > 0: + return "FAILED" + if p_flaky_count > 0: + return "FLAKY" + if p_orphan_count > 0: + return "WARNING" + if p_skipped_count > 0: + return "SKIPPED" + return "PASSED" + + +func calculate_succes_rate(p_test_count :int, p_error_count :int, p_failure_count :int) -> String: + if p_failure_count == 0: + return "100%" + var count := p_test_count-p_failure_count-p_error_count + if count < 0: + return "0%" + return "%d" % (( 0 if count < 0 else count) * 100.0 / p_test_count) + "%" + + +func create_summary(_report_dir :String) -> String: + return "" diff --git a/addons/gdUnit4/src/reporters/GdUnitReportSummary.gd.uid b/addons/gdUnit4/src/reporters/GdUnitReportSummary.gd.uid new file mode 100644 index 0000000..5b33e8d --- /dev/null +++ b/addons/gdUnit4/src/reporters/GdUnitReportSummary.gd.uid @@ -0,0 +1 @@ +uid://6wmo4x2hl7lu diff --git a/addons/gdUnit4/src/reporters/GdUnitReportWriter.gd b/addons/gdUnit4/src/reporters/GdUnitReportWriter.gd new file mode 100644 index 0000000..bf4c96e --- /dev/null +++ b/addons/gdUnit4/src/reporters/GdUnitReportWriter.gd @@ -0,0 +1,12 @@ +class_name GdUnitReportWriter +extends RefCounted + + +func write(_report_path: String, _report: GdUnitReportSummary) -> String: + assert(false, "'write' is not implemented!") + return "" + + +func output_format() -> String: + assert(false, "'output_format' is not implemented!") + return "" diff --git a/addons/gdUnit4/src/reporters/GdUnitReportWriter.gd.uid b/addons/gdUnit4/src/reporters/GdUnitReportWriter.gd.uid new file mode 100644 index 0000000..3aa3e49 --- /dev/null +++ b/addons/gdUnit4/src/reporters/GdUnitReportWriter.gd.uid @@ -0,0 +1 @@ +uid://bukpyxufjfsky diff --git a/addons/gdUnit4/src/reporters/GdUnitTestCaseReport.gd b/addons/gdUnit4/src/reporters/GdUnitTestCaseReport.gd new file mode 100644 index 0000000..2801696 --- /dev/null +++ b/addons/gdUnit4/src/reporters/GdUnitTestCaseReport.gd @@ -0,0 +1,47 @@ +class_name GdUnitTestCaseReport +extends GdUnitReportSummary + + +var _suite_name: String +var _failure_reports: Array[GdUnitReport] = [] + + +func _init(p_resource_path: String, p_suite_name: String, p_test_name: String, text_formatter: Callable) -> void: + _resource_path = p_resource_path + _suite_name = p_suite_name + _name = p_test_name + _text_formatter = text_formatter + + +func suite_name() -> String: + return _suite_name + + +func failure_report() -> String: + var report_message := "" + for report in get_test_reports(): + report_message += _text_formatter.call(str(report)) + "\n" + return report_message + + +func add_testcase_reports(reports: Array[GdUnitReport]) -> void: + _failure_reports.append_array(reports) + + +func set_testcase_counters( + p_error_count: int, + p_failure_count: int, + p_orphan_count: int, + p_is_skipped: bool, + p_is_flaky: bool, + p_duration: int) -> void: + _error_count = p_error_count + _failure_count = p_failure_count + _orphan_count = p_orphan_count + _skipped_count = p_is_skipped + _flaky_count = p_is_flaky as int + _duration = p_duration + + +func get_test_reports() -> Array[GdUnitReport]: + return _failure_reports diff --git a/addons/gdUnit4/src/reporters/GdUnitTestCaseReport.gd.uid b/addons/gdUnit4/src/reporters/GdUnitTestCaseReport.gd.uid new file mode 100644 index 0000000..58426a2 --- /dev/null +++ b/addons/gdUnit4/src/reporters/GdUnitTestCaseReport.gd.uid @@ -0,0 +1 @@ +uid://cedf2tmgdo2fy diff --git a/addons/gdUnit4/src/reporters/GdUnitTestReporter.gd b/addons/gdUnit4/src/reporters/GdUnitTestReporter.gd new file mode 100644 index 0000000..46b8193 --- /dev/null +++ b/addons/gdUnit4/src/reporters/GdUnitTestReporter.gd @@ -0,0 +1,112 @@ +class_name GdUnitTestReporter +extends RefCounted + + +var _statistics := {} +var _summary := {} + + +func init_summary() -> void: + _summary["suite_count"] = 0 + _summary["total_count"] = 0 + _summary["error_count"] = 0 + _summary["failed_count"] = 0 + _summary["skipped_count"] = 0 + _summary["flaky_count"] = 0 + _summary["orphan_nodes"] = 0 + _summary["elapsed_time"] = 0 + + +func init_statistics() -> void: + _statistics.clear() + + +func add_test_statistics(event: GdUnitEvent) -> void: + _statistics[event.guid()] = { + "error_count" : event.error_count(), + "failed_count" : event.failed_count(), + "skipped_count" : event.skipped_count(), + "flaky_count" : event.is_flaky() as int, + "orphan_nodes" : event.orphan_nodes() + } + + +func build_test_suite_statisitcs(event: GdUnitEvent) -> Dictionary: + var statistic := { + "total_count" : _statistics.size(), + "error_count" : event.error_count(), + "failed_count" : event.failed_count(), + "skipped_count" : event.skipped_count(), + "flaky_count" : 0, + "orphan_nodes" : event.orphan_nodes() + } + _summary["suite_count"] += 1 + _summary["total_count"] += _statistics.size() + _summary["error_count"] += event.error_count() + _summary["failed_count"] += event.failed_count() + _summary["skipped_count"] += event.skipped_count() + _summary["orphan_nodes"] += event.orphan_nodes() + _summary["elapsed_time"] += event.elapsed_time() + + for key: String in ["error_count", "failed_count", "skipped_count", "flaky_count", "orphan_nodes"]: + var value: int = _statistics.values().reduce(get_value.bind(key), 0 ) + statistic[key] += value + _summary[key] += value + + return statistic + + +func get_value(acc: int, value: Dictionary, key: String) -> int: + return acc + value[key] + + +func processed_suite_count() -> int: + return _summary["suite_count"] + + +func total_test_count() -> int: + return _summary["total_count"] + + +func total_flaky_count() -> int: + return _summary["flaky_count"] + + +func total_error_count() -> int: + return _summary["error_count"] + + +func total_failure_count() -> int: + return _summary["failed_count"] + + +func total_skipped_count() -> int: + return _summary["skipped_count"] + + +func total_orphan_count() -> int: + return _summary["orphan_nodes"] + + +func elapsed_time() -> int: + return _summary["elapsed_time"] + + +func error_count(statistics: Dictionary) -> int: + return statistics["error_count"] + + +func failed_count(statistics: Dictionary) -> int: + return statistics["failed_count"] + + +func orphan_nodes(statistics: Dictionary) -> int: + return statistics["orphan_nodes"] + + +func skipped_count(statistics: Dictionary) -> int: + return statistics["skipped_count"] + + +func flaky_count(statistics: Dictionary) -> int: + return statistics["flaky_count"] diff --git a/addons/gdUnit4/src/reporters/GdUnitTestReporter.gd.uid b/addons/gdUnit4/src/reporters/GdUnitTestReporter.gd.uid new file mode 100644 index 0000000..693ff4d --- /dev/null +++ b/addons/gdUnit4/src/reporters/GdUnitTestReporter.gd.uid @@ -0,0 +1 @@ +uid://blvl4oan5rgx2 diff --git a/addons/gdUnit4/src/reporters/GdUnitTestSuiteReport.gd b/addons/gdUnit4/src/reporters/GdUnitTestSuiteReport.gd new file mode 100644 index 0000000..9be0682 --- /dev/null +++ b/addons/gdUnit4/src/reporters/GdUnitTestSuiteReport.gd @@ -0,0 +1,96 @@ +class_name GdUnitTestSuiteReport +extends GdUnitReportSummary + +var _time_stamp: int +var _failure_reports: Array[GdUnitReport] = [] + + +func _init(p_resource_path: String, p_name: String, p_test_count: int, text_formatter: Callable) -> void: + _resource_path = p_resource_path + _name = p_name + _test_count = p_test_count + _time_stamp = Time.get_unix_time_from_system() as int + _text_formatter = text_formatter + + +func failure_report() -> String: + var report_message := "" + for report in _failure_reports: + report_message += _text_formatter.call(str(report)) + return report_message + + +func set_duration(p_duration :int) -> void: + _duration = p_duration + + +func time_stamp() -> int: + return _time_stamp + + +func duration() -> int: + return _duration + + +func set_skipped(skipped :int) -> void: + _skipped_count += skipped + + +func set_orphans(orphans :int) -> void: + _orphan_count = orphans + + +func set_failed(count :int) -> void: + _failure_count += count + + +func set_reports(failure_reports :Array[GdUnitReport]) -> void: + _failure_reports = failure_reports + + +func add_or_create_test_report(test_report: GdUnitTestCaseReport) -> void: + _reports.append(test_report) + + +func _update_testsuite_counters( + p_error_count: int, + p_failure_count: int, + p_orphan_count: int, + p_skipped_count: int, + p_flaky_count: int, + p_duration: int) -> void: + _error_count += p_error_count + _failure_count += p_failure_count + _orphan_count += p_orphan_count + _skipped_count += p_skipped_count + _flaky_count += p_flaky_count + _duration += p_duration + + +func set_testcase_counters( + test_name: String, + p_error_count: int, + p_failure_count: int, + p_orphan_count: int, + p_is_skipped: bool, + p_is_flaky: bool, + p_duration: int) -> void: + if _reports.is_empty(): + return + var test_report: GdUnitTestCaseReport = _reports.filter(func (report: GdUnitTestCaseReport) -> bool: + return report.name() == test_name + ).back() + if test_report: + test_report.set_testcase_counters(p_error_count, p_failure_count, p_orphan_count, p_is_skipped, p_is_flaky, p_duration) + + +func add_testcase_reports(test_name: String, reports: Array[GdUnitReport]) -> void: + if reports.is_empty(): + return + # we lookup to latest matching report because of flaky tests could be retry the tests + # and resultis in multipe report entries with the same name + var test_report: GdUnitTestCaseReport = _reports.filter(func (report: GdUnitTestCaseReport) -> bool: + return report.name() == test_name + ).back() + if test_report: + test_report.add_testcase_reports(reports) diff --git a/addons/gdUnit4/src/reporters/GdUnitTestSuiteReport.gd.uid b/addons/gdUnit4/src/reporters/GdUnitTestSuiteReport.gd.uid new file mode 100644 index 0000000..e3ca4f2 --- /dev/null +++ b/addons/gdUnit4/src/reporters/GdUnitTestSuiteReport.gd.uid @@ -0,0 +1 @@ +uid://dean1teklh3rj diff --git a/addons/gdUnit4/src/reporters/console/GdUnitConsoleTestReporter.gd b/addons/gdUnit4/src/reporters/console/GdUnitConsoleTestReporter.gd new file mode 100644 index 0000000..8b54aac --- /dev/null +++ b/addons/gdUnit4/src/reporters/console/GdUnitConsoleTestReporter.gd @@ -0,0 +1,234 @@ +@tool +class_name GdUnitConsoleTestReporter + + +var test_session: GdUnitTestSession: + get: + return test_session + set(value): + # disconnect first possible connected listener + if test_session != null: + test_session.test_event.disconnect(on_gdunit_event) + # add listening to current session + test_session = value + if test_session != null: + test_session.test_event.connect(on_gdunit_event) + + +var _writer: GdUnitMessageWritter +var _reporter: GdUnitTestReporter = GdUnitTestReporter.new() +var _status_indent := 86 +var _detailed: bool +var _text_color: Color = Color.ANTIQUE_WHITE +var _function_color: Color = Color.ANTIQUE_WHITE +var _engine_type_color: Color = Color.ANTIQUE_WHITE + + +func _init(writer: GdUnitMessageWritter, detailed := false) -> void: + _writer = writer + _writer.clear() + _detailed = detailed + if _detailed: + _status_indent = 20 + init_colors() + + +func init_colors() -> void: + if Engine.is_editor_hint(): + var settings := EditorInterface.get_editor_settings() + _text_color = settings.get_setting("text_editor/theme/highlighting/text_color") + _function_color = settings.get_setting("text_editor/theme/highlighting/function_color") + _engine_type_color = settings.get_setting("text_editor/theme/highlighting/engine_type_color") + + +func clear() -> void: + _writer.clear() + + +func on_gdunit_event(event: GdUnitEvent) -> void: + match event.type(): + GdUnitEvent.INIT: + _reporter.init_summary() + + GdUnitEvent.STOP: + _print_summary() + println_message(build_executed_test_suite_msg(processed_suite_count(), processed_suite_count()), Color.DARK_SALMON) + println_message(build_executed_test_case_msg(total_test_count(), total_skipped_count()), Color.DARK_SALMON) + println_message("Total execution time: %s" % LocalTime.elapsed(elapsed_time()), Color.DARK_SALMON) + # We need finally to set the wave effect to enable the animations + _writer.effect(GdUnitMessageWritter.Effect.WAVE).print_at("", 0) + + GdUnitEvent.TESTSUITE_BEFORE: + _reporter.init_statistics() + print_message("Run Test Suite: ", Color.DARK_TURQUOISE) + println_message(event.resource_path(), _engine_type_color) + + GdUnitEvent.TESTSUITE_AFTER: + if not event.reports().is_empty(): + _writer.color(Color.DARK_SALMON)\ + .style(GdUnitMessageWritter.BOLD)\ + .println_message(event.suite_name()+":finalze") + _print_failure_report(event.reports()) + _print_statistics(_reporter.build_test_suite_statisitcs(event)) + _print_status(event) + println_message("") + if _detailed: + println_message("") + + GdUnitEvent.TESTCASE_BEFORE: + var test := test_session.find_test_by_id(event.guid()) + _print_test_path(test, event.guid()) + if _detailed: + _writer.color(Color.FOREST_GREEN).print_at("STARTED", _status_indent) + println_message("") + + GdUnitEvent.TESTCASE_AFTER: + _reporter.add_test_statistics(event) + if _detailed: + var test := test_session.find_test_by_id(event.guid()) + _print_test_path(test, event.guid()) + _print_status(event) + _print_failure_report(event.reports()) + if _detailed: + println_message("") + + +func _print_test_path(test: GdUnitTestCase, uid: GdUnitGUID) -> void: + if test == null: + prints_warning("Can't print full test info, the test by uid: '%s' was not discovered." % uid) + _writer.indent(1).color(_engine_type_color).print_message("Test ID: %s" % uid) + return + + var suite_name := test.source_file if _detailed else test.suite_name + _writer.indent(1).color(_engine_type_color).print_message(suite_name) + print_message(" > ") + print_message(test.display_name, _function_color) + + +func _print_status(event: GdUnitEvent) -> void: + if event.is_flaky() and event.is_success(): + var retries: int = event.statistic(GdUnitEvent.RETRY_COUNT) + _writer.color(Color.GREEN_YELLOW)\ + .style(GdUnitMessageWritter.ITALIC)\ + .print_at("FLAKY (%d retries)" % retries, _status_indent) + elif event.is_success(): + _writer.color(Color.FOREST_GREEN).print_at("PASSED", _status_indent) + elif event.is_skipped(): + _writer.color(Color.GOLDENROD).style(GdUnitMessageWritter.ITALIC).print_at("SKIPPED", _status_indent) + elif event.is_failed() or event.is_error(): + var retries :int = event.statistic(GdUnitEvent.RETRY_COUNT) + var message := "FAILED (retry %d)" % retries if retries > 1 else "FAILED" + _writer.color(Color.FIREBRICK)\ + .style(GdUnitMessageWritter.BOLD)\ + .effect(GdUnitMessageWritter.Effect.WAVE)\ + .print_at(message, _status_indent) + elif event.is_warning(): + _writer.color(Color.GOLDENROD)\ + .style(GdUnitMessageWritter.UNDERLINE)\ + .print_at("WARNING", _status_indent) + + println_message(" %s" % LocalTime.elapsed(event.elapsed_time()), Color.CORNFLOWER_BLUE) + + +func _print_failure_report(reports: Array[GdUnitReport]) -> void: + for report in reports: + if ( + report.is_failure() + or report.is_error() + or report.is_warning() + or report.is_skipped() + ): + _writer.indent(1)\ + .color(Color.DARK_TURQUOISE)\ + .style(GdUnitMessageWritter.BOLD | GdUnitMessageWritter.UNDERLINE)\ + .println_message("Report:") + var text := str(report) + for line in text.split("\n", false): + _writer.indent(2).color(Color.DARK_TURQUOISE).println_message(line) + + if not reports.is_empty(): + println_message("") + + +func _print_statistics(statistics: Dictionary) -> void: + print_message("Statistics:", Color.DODGER_BLUE) + print_message(" %d test cases | %d errors | %d failures | %d flaky | %d skipped | %d orphans |" %\ + [statistics["total_count"], + statistics["error_count"], + statistics["failed_count"], + statistics["flaky_count"], + statistics["skipped_count"], + statistics["orphan_nodes"]]) + + +func _print_summary() -> void: + print_message("Overall Summary:", Color.DODGER_BLUE) + _writer\ + .println_message(" %d test cases | %d errors | %d failures | %d flaky | %d skipped | %d orphans |" % [ + total_test_count(), + total_error_count(), + total_failure_count(), + total_flaky_count(), + total_skipped_count(), + total_orphan_count() + ]) + + +func build_executed_test_suite_msg(executed_count: int, total_count: int) -> String: + if executed_count == total_count: + return "Executed test suites: (%d/%d)" % [executed_count, total_count] + return "Executed test suites: (%d/%d), %d skipped" % [executed_count, total_count, (total_count - executed_count)] + + +func build_executed_test_case_msg(total_count: int, p_skipped_count: int) -> String: + if p_skipped_count == 0: + return "Executed test cases : (%d/%d)" % [total_count, total_count] + return "Executed test cases : (%d/%d), %d skipped" % [total_count-p_skipped_count, total_count, p_skipped_count] + + +func print_message(message: String, color: Color = _text_color) -> void: + _writer.color(color).print_message(message) + + +func println_message(message: String, color: Color = _text_color) -> void: + _writer.color(color).println_message(message) + + +func prints_warning(message: String) -> void: + _writer.prints_warning(message) + + +func prints_error(message: String) -> void: + _writer.prints_error(message) + + +func total_test_count() -> int: + return _reporter.total_test_count() + + +func total_error_count() -> int: + return _reporter.total_error_count() + + +func total_failure_count() -> int: + return _reporter.total_failure_count() + + +func total_flaky_count() -> int: + return _reporter.total_flaky_count() + + +func total_skipped_count() -> int: + return _reporter.total_skipped_count() + + +func total_orphan_count() -> int: + return _reporter.total_orphan_count() + + +func processed_suite_count() -> int: + return _reporter.processed_suite_count() + + +func elapsed_time() -> int: + return _reporter.elapsed_time() diff --git a/addons/gdUnit4/src/reporters/console/GdUnitConsoleTestReporter.gd.uid b/addons/gdUnit4/src/reporters/console/GdUnitConsoleTestReporter.gd.uid new file mode 100644 index 0000000..c985ce8 --- /dev/null +++ b/addons/gdUnit4/src/reporters/console/GdUnitConsoleTestReporter.gd.uid @@ -0,0 +1 @@ +uid://denttoej42p6v diff --git a/addons/gdUnit4/src/reporters/html/GdUnitByPathReport.gd b/addons/gdUnit4/src/reporters/html/GdUnitByPathReport.gd new file mode 100644 index 0000000..74b961b --- /dev/null +++ b/addons/gdUnit4/src/reporters/html/GdUnitByPathReport.gd @@ -0,0 +1,60 @@ +class_name GdUnitByPathReport +extends GdUnitReportSummary + + +func _init(p_path :String, report_summaries :Array[GdUnitReportSummary]) -> void: + _resource_path = p_path + _reports = report_summaries + + +# -> Dictionary[String, Array[GdUnitReportSummary]] +static func sort_reports_by_path(report_summaries :Array[GdUnitReportSummary]) -> Dictionary: + var by_path := Dictionary() + for report in report_summaries: + var suite_path :String = ProjectSettings.localize_path(report.path()) + var suite_report :Array[GdUnitReportSummary] = by_path.get(suite_path, [] as Array[GdUnitReportSummary]) + suite_report.append(report) + by_path[suite_path] = suite_report + return by_path + + +func path() -> String: + return _resource_path.replace("res://", "").trim_suffix("/") + + +func create_record(report_link :String) -> String: + return GdUnitHtmlPatterns.build(GdUnitHtmlPatterns.TABLE_RECORD_PATH, self, report_link) + + +func write(report_dir :String) -> String: + calculate_summary() + var template := GdUnitHtmlPatterns.load_template("res://addons/gdUnit4/src/reporters/html/template/folder_report.html") + var path_report := GdUnitHtmlPatterns.build(template, self, "") + path_report = apply_testsuite_reports(report_dir, path_report, _reports) + + var output_path := "%s/path/%s.html" % [report_dir, path().replace("/", ".")] + var dir := output_path.get_base_dir() + if not DirAccess.dir_exists_absolute(dir): + @warning_ignore("return_value_discarded") + DirAccess.make_dir_recursive_absolute(dir) + FileAccess.open(output_path, FileAccess.WRITE).store_string(path_report) + return output_path + + +func apply_testsuite_reports(report_dir :String, template :String, test_suite_reports :Array[GdUnitReportSummary]) -> String: + var table_records := PackedStringArray() + for report:GdUnitTestSuiteReport in test_suite_reports: + var report_link := GdUnitHtmlReportWriter.create_output_path(report_dir, report.path(), report.name()).replace(report_dir, "..") + @warning_ignore("return_value_discarded") + table_records.append(GdUnitHtmlPatterns.create_suite_record(report_link, report)) + return template.replace(GdUnitHtmlPatterns.TABLE_BY_TESTSUITES, "\n".join(table_records)) + + +func calculate_summary() -> void: + for report:GdUnitTestSuiteReport in get_reports(): + _error_count += report.error_count() + _failure_count += report.failure_count() + _orphan_count += report.orphan_count() + _skipped_count += report.skipped_count() + _flaky_count += report.flaky_count() + _duration += report.duration() diff --git a/addons/gdUnit4/src/reporters/html/GdUnitByPathReport.gd.uid b/addons/gdUnit4/src/reporters/html/GdUnitByPathReport.gd.uid new file mode 100644 index 0000000..91da22c --- /dev/null +++ b/addons/gdUnit4/src/reporters/html/GdUnitByPathReport.gd.uid @@ -0,0 +1 @@ +uid://bd3xfghiw30cc diff --git a/addons/gdUnit4/src/reporters/html/GdUnitHtmlPatterns.gd b/addons/gdUnit4/src/reporters/html/GdUnitHtmlPatterns.gd new file mode 100644 index 0000000..b8be904 --- /dev/null +++ b/addons/gdUnit4/src/reporters/html/GdUnitHtmlPatterns.gd @@ -0,0 +1,199 @@ +class_name GdUnitHtmlPatterns +extends RefCounted + +const TABLE_RECORD_TESTSUITE = """ + + ${testsuite_name} + ${report_state_label} + ${test_count} + ${skipped_count} + ${flaky_count} + ${failure_count} + ${orphan_count} + ${duration} + +
+
+
+
+
+
+
+
+ + +""" + +const TABLE_RECORD_PATH = """ + + ${path} + ${report_state_label} + ${test_count} + ${skipped_count} + ${flaky_count} + ${failure_count} + ${orphan_count} + ${duration} + +
+
+
+
+
+
+
+
+ + +""" + + +const TABLE_REPORT_TESTSUITE = """ + + TestSuite hooks + n/a + ${orphan_count} + ${duration} + +
+${failure-report}
+										
+ + +""" + + +const TABLE_RECORD_TESTCASE = """ + + ${testcase_name} + ${report_state_label} + ${skipped_count} + ${orphan_count} + ${duration} + +
+${failure-report}
+										
+ + +""" + +const CHARACTERS_TO_ENCODE := { + '<' : '<', + '>' : '>' +} + +const TABLE_BY_PATHS = "${report_table_paths}" +const TABLE_BY_TESTSUITES = "${report_table_testsuites}" +const TABLE_BY_TESTCASES = "${report_table_tests}" + +# the report state success, error, warning +const REPORT_STATE = "${report_state}" +const REPORT_STATE_LABEL = "${report_state_label}" +const PATH = "${path}" +const RESOURCE_PATH = "${resource_path}" +const TESTSUITE_COUNT = "${suite_count}" +const TESTCASE_COUNT = "${test_count}" +const FAILURE_COUNT = "${failure_count}" +const FLAKY_COUNT = "${flaky_count}" +const SKIPPED_COUNT = "${skipped_count}" +const ORPHAN_COUNT = "${orphan_count}" +const DURATION = "${duration}" +const FAILURE_REPORT = "${failure-report}" +const SUCCESS_PERCENT = "${success_percent}" + + +const QUICK_STATE_SKIPPED = "${skipped-percent}" +const QUICK_STATE_PASSED = "${passed-percent}" +const QUICK_STATE_FLAKY = "${flaky-percent}" +const QUICK_STATE_ERROR = "${error-percent}" +const QUICK_STATE_FAILED = "${failed-percent}" +const QUICK_STATE_WARNING = "${warning-percent}" + +const TESTSUITE_NAME = "${testsuite_name}" +const TESTCASE_NAME = "${testcase_name}" +const REPORT_LINK = "${report_link}" +const BREADCRUMP_PATH_LINK = "${breadcrumb_path_link}" +const BUILD_DATE = "${buid_date}" + + +static func current_date() -> String: + return Time.get_datetime_string_from_system(true, true) + + +static func build(template: String, report: GdUnitReportSummary, report_link: String) -> String: + return template\ + .replace(PATH, get_report_path(report))\ + .replace(BREADCRUMP_PATH_LINK, get_path_as_link(report))\ + .replace(RESOURCE_PATH, report.get_resource_path())\ + .replace(TESTSUITE_NAME, html_encoded(report.name()))\ + .replace(TESTSUITE_COUNT, str(report.suite_count()))\ + .replace(TESTCASE_COUNT, str(report.test_count()))\ + .replace(FAILURE_COUNT, str(report.error_count() + report.failure_count()))\ + .replace(FLAKY_COUNT, str(report.flaky_count()))\ + .replace(SKIPPED_COUNT, str(report.skipped_count()))\ + .replace(ORPHAN_COUNT, str(report.orphan_count()))\ + .replace(DURATION, LocalTime.elapsed(report.duration()))\ + .replace(SUCCESS_PERCENT, report.calculate_succes_rate(report.test_count(), report.error_count(), report.failure_count()))\ + .replace(REPORT_STATE, report.report_state().to_lower())\ + .replace(REPORT_STATE_LABEL, report.report_state())\ + .replace(QUICK_STATE_SKIPPED, calculate_percentage(report.test_count(), report.skipped_count()))\ + .replace(QUICK_STATE_PASSED, calculate_percentage(report.test_count(), report.success_count()))\ + .replace(QUICK_STATE_FLAKY, calculate_percentage(report.test_count(), report.flaky_count()))\ + .replace(QUICK_STATE_ERROR, calculate_percentage(report.test_count(), report.error_count()))\ + .replace(QUICK_STATE_FAILED, calculate_percentage(report.test_count(), report.failure_count()))\ + .replace(QUICK_STATE_WARNING, calculate_percentage(report.test_count(), 0))\ + .replace(REPORT_LINK, report_link)\ + .replace(BUILD_DATE, current_date()) + + +static func load_template(template_name :String) -> String: + return FileAccess.open(template_name, FileAccess.READ).get_as_text() + + +static func get_path_as_link(report: GdUnitReportSummary) -> String: + return "../path/%s.html" % report.path().replace("/", ".") + + +static func get_report_path(report: GdUnitReportSummary) -> String: + var path := report.path() + if path.is_empty(): + return "/" + return path + + +static func calculate_percentage(p_test_count: int, count: int) -> String: + if count <= 0: + return "0%" + return "%d" % (( 0 if count < 0 else count) * 100.0 / p_test_count) + "%" + + +static func html_encoded(value: String) -> String: + for key: String in CHARACTERS_TO_ENCODE.keys(): + @warning_ignore("unsafe_cast") + value = value.replace(key, CHARACTERS_TO_ENCODE[key] as String) + return value + + +static func create_suite_record(report_link: String, report: GdUnitTestSuiteReport) -> String: + return GdUnitHtmlPatterns.build(GdUnitHtmlPatterns.TABLE_RECORD_TESTSUITE, report, report_link) + + +static func create_test_failure_report(_report_dir :String, report: GdUnitTestCaseReport) -> String: + return GdUnitHtmlPatterns.TABLE_RECORD_TESTCASE\ + .replace(GdUnitHtmlPatterns.REPORT_STATE, report.report_state().to_lower())\ + .replace(GdUnitHtmlPatterns.REPORT_STATE_LABEL, report.report_state())\ + .replace(GdUnitHtmlPatterns.TESTCASE_NAME, report.name())\ + .replace(GdUnitHtmlPatterns.SKIPPED_COUNT, str(report.skipped_count()))\ + .replace(GdUnitHtmlPatterns.ORPHAN_COUNT, str(report.orphan_count()))\ + .replace(GdUnitHtmlPatterns.DURATION, LocalTime.elapsed(report._duration))\ + .replace(GdUnitHtmlPatterns.FAILURE_REPORT, report.failure_report()) + + +static func create_suite_failure_report(report: GdUnitTestSuiteReport) -> String: + return GdUnitHtmlPatterns.TABLE_REPORT_TESTSUITE\ + .replace(GdUnitHtmlPatterns.REPORT_STATE, report.report_state().to_lower())\ + .replace(GdUnitHtmlPatterns.REPORT_STATE_LABEL, report.report_state())\ + .replace(GdUnitHtmlPatterns.ORPHAN_COUNT, str(report.orphan_count()))\ + .replace(GdUnitHtmlPatterns.DURATION, LocalTime.elapsed(report._duration))\ + .replace(GdUnitHtmlPatterns.FAILURE_REPORT, report.failure_report()) diff --git a/addons/gdUnit4/src/reporters/html/GdUnitHtmlPatterns.gd.uid b/addons/gdUnit4/src/reporters/html/GdUnitHtmlPatterns.gd.uid new file mode 100644 index 0000000..793e33c --- /dev/null +++ b/addons/gdUnit4/src/reporters/html/GdUnitHtmlPatterns.gd.uid @@ -0,0 +1 @@ +uid://b30mtk4y1t610 diff --git a/addons/gdUnit4/src/reporters/html/GdUnitHtmlReportWriter.gd b/addons/gdUnit4/src/reporters/html/GdUnitHtmlReportWriter.gd new file mode 100644 index 0000000..a3d2bff --- /dev/null +++ b/addons/gdUnit4/src/reporters/html/GdUnitHtmlReportWriter.gd @@ -0,0 +1,72 @@ +class_name GdUnitHtmlReportWriter +extends GdUnitReportWriter + + +func output_format() -> String: + return "HTML" + + +func write(report_path: String, report: GdUnitReportSummary) -> String: + var template := GdUnitHtmlPatterns.load_template("res://addons/gdUnit4/src/reporters/html/template/index.html") + var to_write := GdUnitHtmlPatterns.build(template, report, "") + to_write = _apply_path_reports(report_path, to_write, report.get_reports()) + to_write = _apply_testsuite_reports(report_path, to_write, report.get_reports()) + # write report + DirAccess.make_dir_recursive_absolute(report_path) + var html_report_file := "%s/index.html" % report_path + FileAccess.open(html_report_file, FileAccess.WRITE).store_string(to_write) + @warning_ignore("return_value_discarded") + GdUnitFileAccess.copy_directory("res://addons/gdUnit4/src/reporters/html/template/css/", report_path + "/css") + return html_report_file + + +func _apply_path_reports(report_dir: String, template: String, report_summaries: Array) -> String: + #Dictionary[String, Array[GdUnitReportSummary]] + var path_report_mapping := GdUnitByPathReport.sort_reports_by_path(report_summaries) + var table_records := PackedStringArray() + var paths: Array[String] = [] + paths.append_array(path_report_mapping.keys()) + paths.sort() + for report_at_path in paths: + var reports: Array[GdUnitReportSummary] = path_report_mapping.get(report_at_path) + var report := GdUnitByPathReport.new(report_at_path, reports) + var report_link: String = report.write(report_dir).replace(report_dir, ".") + @warning_ignore("return_value_discarded") + table_records.append(report.create_record(report_link)) + return template.replace(GdUnitHtmlPatterns.TABLE_BY_PATHS, "\n".join(table_records)) + + +func _apply_testsuite_reports(report_dir: String, template: String, test_suite_reports: Array[GdUnitReportSummary]) -> String: + var table_records := PackedStringArray() + for report: GdUnitTestSuiteReport in test_suite_reports: + var report_link: String = _write(report_dir, report).replace(report_dir, ".") + @warning_ignore("return_value_discarded") + table_records.append(GdUnitHtmlPatterns.create_suite_record(report_link, report)) + return template.replace(GdUnitHtmlPatterns.TABLE_BY_TESTSUITES, "\n".join(table_records)) + + +func _write(report_dir :String, report: GdUnitTestSuiteReport) -> String: + var template := GdUnitHtmlPatterns.load_template("res://addons/gdUnit4/src/reporters/html/template/suite_report.html") + template = GdUnitHtmlPatterns.build(template, report, "") + + var report_output_path := create_output_path(report_dir, report.path(), report.name()) + var test_report_table := PackedStringArray() + if not report._failure_reports.is_empty(): + @warning_ignore("return_value_discarded") + test_report_table.append(GdUnitHtmlPatterns.create_suite_failure_report(report)) + for test_report: GdUnitTestCaseReport in report._reports: + @warning_ignore("return_value_discarded") + test_report_table.append(GdUnitHtmlPatterns.create_test_failure_report(report_output_path, test_report)) + + template = template.replace(GdUnitHtmlPatterns.TABLE_BY_TESTCASES, "\n".join(test_report_table)) + + var dir := report_output_path.get_base_dir() + if not DirAccess.dir_exists_absolute(dir): + @warning_ignore("return_value_discarded") + DirAccess.make_dir_recursive_absolute(dir) + FileAccess.open(report_output_path, FileAccess.WRITE).store_string(template) + return report_output_path + + +static func create_output_path(report_dir :String, path: String, name: String) -> String: + return "%s/test_suites/%s.%s.html" % [report_dir, path.replace("/", "."), name] diff --git a/addons/gdUnit4/src/reporters/html/GdUnitHtmlReportWriter.gd.uid b/addons/gdUnit4/src/reporters/html/GdUnitHtmlReportWriter.gd.uid new file mode 100644 index 0000000..ef50ca0 --- /dev/null +++ b/addons/gdUnit4/src/reporters/html/GdUnitHtmlReportWriter.gd.uid @@ -0,0 +1 @@ +uid://ts50qpft0jbg diff --git a/addons/gdUnit4/src/reporters/html/template/.gdignore b/addons/gdUnit4/src/reporters/html/template/.gdignore new file mode 100644 index 0000000..e69de29 diff --git a/addons/gdUnit4/src/reporters/html/template/css/breadcrumb.css b/addons/gdUnit4/src/reporters/html/template/css/breadcrumb.css new file mode 100644 index 0000000..17215ff --- /dev/null +++ b/addons/gdUnit4/src/reporters/html/template/css/breadcrumb.css @@ -0,0 +1,66 @@ +.breadcrumb { + display: flex; + border-radius: 6px; + overflow: hidden; + height: 45px; + z-index: 1; + background-color: #9d73eb; + margin-top: 0px; + margin-bottom: 10px; + box-shadow: 0 0 3px black; +} + +.breadcrumb a { + position: relative; + display: flex; + -ms-flex-positive: 1; + flex-grow: 1; + text-decoration: none; + margin: auto; + height: 100%; + color: white; +} + +.breadcrumb a:first-child { + padding-left: 5.2px; +} + +.breadcrumb a:last-child { + padding-right: 5.2px; +} + +.breadcrumb a:after { + content: ""; + position: absolute; + display: inline-block; + width: 45px; + height: 45px; + top: 0; + right: -20px; + background-color: #9d73eb; + border-top-right-radius: 5px; + transform: scale(0.707) rotate(45deg); + box-shadow: 2px -2px rgba(0, 0, 0, 0.25); + z-index: 1; +} + +.breadcrumb a:last-child:after { + content: none; +} + +.breadcrumb a.active, +.breadcrumb a:hover { + background: #b899f2; + color: white; + text-decoration: underline; +} + +.breadcrumb a.active:after, +.breadcrumb a:hover:after { + background: #b899f2; +} + +.breadcrumb span { + margin: inherit; + z-index: 2; +} diff --git a/addons/gdUnit4/src/reporters/html/template/css/logo.png b/addons/gdUnit4/src/reporters/html/template/css/logo.png new file mode 100644 index 0000000..12de79f Binary files /dev/null and b/addons/gdUnit4/src/reporters/html/template/css/logo.png differ diff --git a/addons/gdUnit4/src/reporters/html/template/css/styles.css b/addons/gdUnit4/src/reporters/html/template/css/styles.css new file mode 100644 index 0000000..e92d59b --- /dev/null +++ b/addons/gdUnit4/src/reporters/html/template/css/styles.css @@ -0,0 +1,475 @@ +html, +body { + display: flex; + flex-direction: column; + margin: 0; + padding: 0; + font-family: sans-serif; + background-color: white; + height: 100%; +} + +main { + flex-grow: 1; + overflow: auto; + margin: 0 10em; +} + + +header { + color: white; + padding: 1px; + position: relative; + background-image: linear-gradient(to bottom right, #8058e3, #9d73eb); +} + +.logo { + position: fixed; + top: 20px; + left: 20px; + display: flex; + align-items: center; + z-index: 1000; + filter: grayscale(1); + mix-blend-mode: plus-lighter; +} + +.logo img { + width: 64px; + height: 64px; +} + +.logo span { + font-size: 1.2em; + color: lightslategray; +} + +.report-container { + margin: 0 15em; + text-align: center; + margin-top: 60px; + flex-grow: 0; +} + +h1 { + margin: 0 0 20px 0; + font-size: 2.5em; + font-weight: normal; +} + +.summary { + display: inline-flex; + justify-content: center; + flex-wrap: nowrap; + margin-bottom: 20px; + align-items: baseline; + max-width: 960px; +} + +.summary-item { + flex: 1; + min-width: 80px; +} + +.label { + font-size: 1em; + flex-wrap: nowrap; +} + +.value { + font-size: 0.9em; + display: block; + padding-top: 10px; + color: lightgray; +} + +.success-rate { + padding-left: 40px; + display: flex; + flex-direction: column; + justify-content: center; + align-items: center; +} + +.check-icon { + background-color: #34c538; + color: white; + width: 48px; + height: 48px; + border-radius: 50%; + display: flex; + align-items: center; + justify-content: center; + font-size: 1.4em; +} + +.rate-text { + text-align: center; + flex-wrap: nowrap; +} + +.percentage { + font-size: 1.2em; + font-weight: bold; +} + + +nav { + padding: 20px 0px; + font-family: monospace; +} + +nav ul { + list-style-type: none; + padding: 0; + margin: 0; + display: flex; + justify-content: flex-start; + border-bottom: 1px solid lightgray; +} + +nav li { + cursor: pointer; + padding: 5px 20px; + font-size: 1.1em; + color: lightslategray; +} + +nav li.active { + color: darkslategray; + border-bottom: 1px solid darkslategray; + font-weight: bold; +} + +div#content { + height: calc(100vh - 400px); +} + + +table { + width: 100%; + height: 100%; + border-collapse: collapse; + overflow: hidden; +} + +thead th { + position: sticky; + top: 0; + background-color: white; + z-index: 1; + border-bottom: 2px solid #ddd; +} + +tbody { + display: block; + /* Limit the height of the table body */ + max-height: calc(100vh - 400px); + /* Enable scrolling on the table body */ + overflow-y: auto; +} + +thead, +tbody tr { + display: table; + width: 100%; + table-layout: fixed; +} + +tbody td { + overflow: hidden; +} + +/* Ensure scrollbar visibility */ +tbody::-webkit-scrollbar { + height: 4px; + width: 14px; +} + +tbody::-webkit-scrollbar-thumb { + background-color: #aaa6a6; + border-radius: 4px; +} + +tbody::-webkit-scrollbar-track { + background-color: #f1f1f1; +} + +th, +td { + font-size: .9em; + padding: 5px 0px; + border-bottom: 1px solid #eee; + color: lightslategrey; + text-align: left; + text-wrap: nowrap; + /* Default max and min width for all columns */ + max-width: 150px; + min-width: 80px; + width: 80px; +} + +th { + font-size: 1em; + font-weight: normal; + padding-top: 20px; + color: gray; + text-wrap: nowrap; +} + +.tab-report { + display: grid; + grid-template-columns: 100%; + margin-bottom: 20px; +} + +.tab-report-grid { + display: grid; + grid-template-columns: 70% 30%; + margin-bottom: 20px; +} + + +/* Specific styling for the first column (Testcase) */ +th:first-child, +td:first-child { + padding-left: 5px; + text-align: left; + /* Max width for the first column */ + min-width: 249px; + width: 250px; + /* Enable scrollbar if content exceeds max-width */ + white-space: nowrap; + overflow: auto; +} + +/* Scrollbar styles for first column */ +td:first-child { + overflow-x: auto; + text-overflow: initial; +} + +/* Scrollbar appearance */ +td:first-child::-webkit-scrollbar { + height: 6px; +} + +td:first-child::-webkit-scrollbar-thumb { + background-color: #888; + border-radius: 10px; +} + +td:first-child::-webkit-scrollbar-track { + background-color: #f1f1f1; +} + +/* Max width for Result column */ +th:nth-child(2), +td:nth-child(2) { + max-width: 140px; + min-width: 140px; + width: 140px; +} + +/* Max width for Quick Results column */ +th:nth-child(9), +td:nth-child(9) { + max-width: 140px; + min-width: 140px; + width: 140px; + padding-right: 10px; +} + +/* Background color for alternating groups */ +.group-bg-1 { + background-color: #f1f1f1; +} + +.group-bg-2 { + background-color: #e0e0e0; +} + +.grid-item { + overflow: auto; + padding-left: 20px; + color: lightslategrey; + max-height: calc(100vh - 350px); +} + +div.tab td.report-column, +th.report-column { + display: none; +} + +/* Result status styles */ +.status { + padding: 2px 40px; + border-radius: 6px; + color: black; + width: 40px; + display: flex; + align-content: center; + align-items: center; +} + +.status-bar { + display: flex; + border-radius: 8px; + overflow: hidden; + height: 20px; + flex-wrap: nowrap; + justify-content: space-evenly; +} + +.status-bar-column { + margin: -2px; + color: black; + display: flex; + align-content: center; + align-items: center; + transition: width 0.3s ease; +} + +.status-skipped { + background-color: #888888; +} + +.status-passed { + background-color: #63bb38; +} + +.status-error { + background-color: #fd1100; +} + +.status-failed { + background-color: #ed594f; +} + +.status-flaky { + background-color: #1d9a1f; +} + +.status-warning { + background-color: #fdda3f; +} + +div.tab tr:hover { + background-color: #d9e7fa; + box-shadow: 0 0 5px black; +} + +div.tab tr.selected { + background-color: #d9e7fa; +} + +div.report-column { + margin-top: 10px; + width: 100%; + text-align: left; +} + +.logging-container { + width: 100%; + height: 100%; +} + +div.godot-report-frame { + margin: 10px; + font-family: monospace; + height: 100%; + background-color: #eee; +} + +div.include-footer { + position: fixed; + bottom: 0; + width: 100%; + display: flex; +} + +footer { + position: static; + left: 0; + bottom: 0; + width: 100%; + white-space: nowrap; + color: lightgray; + font-size: 12px; + background-image: linear-gradient(to bottom right, #8058e3, #9d73eb); + display: flex; + justify-content: space-between; + align-items: center; +} + +footer p { + padding-left: 10em; +} + +footer .status-legend { + display: flex; + gap: 15px; + width: 500px; +} + +footer a { + color: lightgray; +} + +footer a:hover { + color: whitesmoke; +} + +footer a:visited { + color: whitesmoke; +} + +.status-legend-item { + display: flex; + align-items: center; + gap: 5px; +} + +.status-box { + width: 15px; + height: 15px; + border-radius: 3px; + display: inline-block; +} + +/* Normal link */ +a { + color: lightslategrey; +} + +/* Link when hovered */ +a:hover { + color: #9d73eb; +} + +/* Visited link */ +a:visited { + color: #8058e3; +} + +/* Active link (while being clicked) */ +a:active { + color: #8058e3; + /* Custom color when link is clicked */ +} + + +@media (max-width: 1024px) { + .summary { + flex-direction: column; + } + + nav ul { + flex-wrap: wrap; + } + + nav li { + margin-right: 10px; + margin-bottom: 5px; + } +} diff --git a/addons/gdUnit4/src/reporters/html/template/folder_report.html b/addons/gdUnit4/src/reporters/html/template/folder_report.html new file mode 100644 index 0000000..2cdca67 --- /dev/null +++ b/addons/gdUnit4/src/reporters/html/template/folder_report.html @@ -0,0 +1,122 @@ + + + + + + + + + GdUnit4 Testsuite + + + + + +
+ +
+

Report by Paths

+
+ ${resource_path} +
+
+
+ TestSuites + ${suite_count} +
+
+ Tests + ${test_count} +
+
+ Skipped + ${skipped_count} +
+
+ Flaky + ${flaky_count} +
+
+ Failures + ${failure_count} +
+
+ Orphans + ${orphan_count} +
+
+ Duration + ${duration} +
+
+
+
+ Success Rate + ${success_percent} +
+
+
+
+ +
+ +
+
+
+
+ + + + + + + + + + + + + + + + ${report_table_testsuites} + +
TestSuitesResultTestsSkippedFlakyFailuresOrphansDurationSuccess rate
+
+
+
+
+ +
+

Generated by GdUnit4 at ${buid_date}

+
+ + Skipped + + + Passed + + + Flaky + + + Warning + + + Failed + + + Error + +
+
+ + + diff --git a/addons/gdUnit4/src/reporters/html/template/index.html b/addons/gdUnit4/src/reporters/html/template/index.html new file mode 100644 index 0000000..342c8f2 --- /dev/null +++ b/addons/gdUnit4/src/reporters/html/template/index.html @@ -0,0 +1,164 @@ + + + + + + + GdUnit4 Report + + + + +
+ +
+

Summary Report

+
+
+ Test Suites + ${suite_count} +
+
+ Tests + ${test_count} +
+
+ Skipped + ${skipped_count} +
+
+ Flaky + ${flaky_count} +
+
+ Failures + ${failure_count} +
+
+ Orphans + ${orphan_count} +
+
+ Duration + ${duration} +
+
+
+
+ Success Rate + ${success_percent} +
+
+
+
+
+
+ +
+ +
+
+ +
+

Generated by GdUnit4 at ${buid_date}

+
+ + Skipped + + + Passed + + + Flaky + + + Warning + + + Failed + + + Error + +
+
+ + + + + diff --git a/addons/gdUnit4/src/reporters/html/template/suite_report.html b/addons/gdUnit4/src/reporters/html/template/suite_report.html new file mode 100644 index 0000000..4746841 --- /dev/null +++ b/addons/gdUnit4/src/reporters/html/template/suite_report.html @@ -0,0 +1,177 @@ + + + + + + + + + GdUnit4 Testsuite + + + + + + + + +
+ +
+

Testsuite Report

+
+ ${resource_path} +
+
+
+ Tests + ${test_count} +
+
+ Skipped + ${skipped_count} +
+
+ Flaky + ${flaky_count} +
+
+ Failures + ${failure_count} +
+
+ Orphans + ${orphan_count} +
+
+ Duration + ${duration} +
+
+
+
+ Success Rate + ${success_percent} +
+
+
+
+ +
+ +
+
+
+ + + + + + + + + + + + + ${report_table_tests} + +
TestcaseResultSkippedOrphansDurationReport
+
+
+

Failure Report

+
+
+
+
+ +
+

Generated by GdUnit4 at ${buid_date}

+
+ + Skipped + + + Passed + + + Flaky + + + Warning + + + Failed + + + Error + +
+
+ + + + + diff --git a/addons/gdUnit4/src/reporters/xml/JUnitXmlReportWriter.gd b/addons/gdUnit4/src/reporters/xml/JUnitXmlReportWriter.gd new file mode 100644 index 0000000..0b9674f --- /dev/null +++ b/addons/gdUnit4/src/reporters/xml/JUnitXmlReportWriter.gd @@ -0,0 +1,143 @@ +# This class implements the JUnit XML file format +# based checked https://github.com/windyroad/JUnit-Schema/blob/master/JUnit.xsd +class_name JUnitXmlReportWriter +extends GdUnitReportWriter + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") + +const ATTR_CLASSNAME := "classname" +const ATTR_ERRORS := "errors" +const ATTR_FAILURES := "failures" +const ATTR_HOST := "hostname" +const ATTR_ID := "id" +const ATTR_MESSAGE := "message" +const ATTR_NAME := "name" +const ATTR_PACKAGE := "package" +const ATTR_SKIPPED := "skipped" +const ATTR_FLAKY := "flaky" +const ATTR_TESTS := "tests" +const ATTR_TIME := "time" +const ATTR_TIMESTAMP := "timestamp" +const ATTR_TYPE := "type" + +const HEADER := '\n' + + +func output_format() -> String: + return "XML" + + +func write(report_path: String, report: GdUnitReportSummary) -> String: + var result_file: String = "%s/results.xml" % report_path + DirAccess.make_dir_recursive_absolute(report_path) + var file := FileAccess.open(result_file, FileAccess.WRITE) + if file == null: + push_warning("Can't saving the result to '%s'\n Error: %s" % [result_file, error_string(FileAccess.get_open_error())]) + else: + file.store_string(build_junit_report(report_path, report)) + return result_file + + +func build_junit_report(report_path: String, report: GdUnitReportSummary) -> String: + var iso8601_datetime := Time.get_date_string_from_system() + var test_suites := XmlElement.new("testsuites")\ + .attribute(ATTR_ID, iso8601_datetime)\ + .attribute(ATTR_NAME, report_path.get_file())\ + .attribute(ATTR_TESTS, report.test_count())\ + .attribute(ATTR_FAILURES, report.failure_count())\ + .attribute(ATTR_SKIPPED, report.skipped_count())\ + .attribute(ATTR_FLAKY, report.flaky_count())\ + .attribute(ATTR_TIME, JUnitXmlReportWriter.to_time(report.duration()))\ + .add_childs(build_test_suites(report)) + var as_string := test_suites.to_xml() + test_suites.dispose() + return HEADER + as_string + + +func build_test_suites(summary: GdUnitReportSummary) -> Array: + var test_suites: Array[XmlElement] = [] + for index in summary.get_reports().size(): + var suite_report :GdUnitTestSuiteReport = summary.get_reports()[index] + var iso8601_datetime := Time.get_datetime_string_from_unix_time(suite_report.time_stamp()) + test_suites.append(XmlElement.new("testsuite")\ + .attribute(ATTR_ID, index)\ + .attribute(ATTR_NAME, suite_report.name())\ + .attribute(ATTR_PACKAGE, suite_report.path())\ + .attribute(ATTR_TIMESTAMP, iso8601_datetime)\ + .attribute(ATTR_HOST, "localhost")\ + .attribute(ATTR_TESTS, suite_report.test_count())\ + .attribute(ATTR_FAILURES, suite_report.failure_count())\ + .attribute(ATTR_ERRORS, suite_report.error_count())\ + .attribute(ATTR_SKIPPED, suite_report.skipped_count())\ + .attribute(ATTR_FLAKY, suite_report.flaky_count())\ + .attribute(ATTR_TIME, JUnitXmlReportWriter.to_time(suite_report.duration()))\ + .add_childs(build_test_cases(suite_report))) + return test_suites + + +func build_test_cases(suite_report: GdUnitTestSuiteReport) -> Array: + var test_cases: Array[XmlElement] = [] + for index in suite_report.get_reports().size(): + var report :GdUnitTestCaseReport = suite_report.get_reports()[index] + test_cases.append( XmlElement.new("testcase")\ + .attribute(ATTR_NAME, JUnitXmlReportWriter.encode_xml(report.name()))\ + .attribute(ATTR_CLASSNAME, report.suite_name())\ + .attribute(ATTR_TIME, JUnitXmlReportWriter.to_time(report.duration()))\ + .add_childs(build_reports(report))) + return test_cases + + +func build_reports(test_report: GdUnitTestCaseReport) -> Array: + var failure_reports: Array[XmlElement] = [] + + for report: GdUnitReport in test_report.get_test_reports(): + if report.is_failure(): + failure_reports.append(XmlElement.new("failure")\ + .attribute(ATTR_MESSAGE, "FAILED: %s:%d" % [test_report.get_resource_path(), report.line_number()])\ + .attribute(ATTR_TYPE, JUnitXmlReportWriter.to_type(report.type()))\ + .text(convert_rtf_to_text(report.message()))) + elif report.is_error(): + failure_reports.append(XmlElement.new("error")\ + .attribute(ATTR_MESSAGE, "ERROR: %s:%d" % [test_report.get_resource_path(), report.line_number()])\ + .attribute(ATTR_TYPE, JUnitXmlReportWriter.to_type(report.type()))\ + .text(convert_rtf_to_text(report.message()))) + elif report.is_skipped(): + failure_reports.append(XmlElement.new("skipped")\ + .attribute(ATTR_MESSAGE, "SKIPPED: %s:%d" % [test_report.get_resource_path(), report.line_number()])\ + .text(convert_rtf_to_text(report.message()))) + return failure_reports + + +func convert_rtf_to_text(bbcode: String) -> String: + return GdUnitTools.richtext_normalize(bbcode) + + +static func to_type(type: int) -> String: + match type: + GdUnitReport.SUCCESS: + return "SUCCESS" + GdUnitReport.WARN: + return "WARN" + GdUnitReport.FAILURE: + return "FAILURE" + GdUnitReport.ORPHAN: + return "ORPHAN" + GdUnitReport.TERMINATED: + return "TERMINATED" + GdUnitReport.INTERUPTED: + return "INTERUPTED" + GdUnitReport.ABORT: + return "ABORT" + return "UNKNOWN" + + +static func to_time(duration: int) -> String: + return "%4.03f" % (duration / 1000.0) + + +static func encode_xml(value: String) -> String: + return value.xml_escape(true) + + +#static func to_ISO8601_datetime() -> String: + #return "%04d-%02d-%02dT%02d:%02d:%02d" % [date["year"], date["month"], date["day"], date["hour"], date["minute"], date["second"]] diff --git a/addons/gdUnit4/src/reporters/xml/JUnitXmlReportWriter.gd.uid b/addons/gdUnit4/src/reporters/xml/JUnitXmlReportWriter.gd.uid new file mode 100644 index 0000000..f061354 --- /dev/null +++ b/addons/gdUnit4/src/reporters/xml/JUnitXmlReportWriter.gd.uid @@ -0,0 +1 @@ +uid://dor7pwu8q0an7 diff --git a/addons/gdUnit4/src/reporters/xml/XmlElement.gd b/addons/gdUnit4/src/reporters/xml/XmlElement.gd new file mode 100644 index 0000000..86c7421 --- /dev/null +++ b/addons/gdUnit4/src/reporters/xml/XmlElement.gd @@ -0,0 +1,69 @@ +class_name XmlElement +extends RefCounted + +var _name :String +# Dictionary[String, String] +var _attributes :Dictionary = {} +var _childs :Array[XmlElement] = [] +var _parent :XmlElement = null +var _text :String = "" + + +func _init(name :String) -> void: + _name = name + + +func dispose() -> void: + for child in _childs: + child.dispose() + _childs.clear() + _attributes.clear() + _parent = null + + +func attribute(name :String, value :Variant) -> XmlElement: + _attributes[name] = str(value) + return self + + +func text(p_text :String) -> XmlElement: + _text = p_text if p_text.ends_with("\n") else p_text + "\n" + return self + + +func add_child(child :XmlElement) -> XmlElement: + _childs.append(child) + child._parent = self + return self + + +func add_childs(childs :Array[XmlElement]) -> XmlElement: + for child in childs: + @warning_ignore("return_value_discarded") + add_child(child) + return self + + +func indentation() -> String: + return "" if _parent == null else _parent.indentation() + " " + + +func to_xml() -> String: + var attributes := "" + for key in _attributes.keys() as Array[String]: + attributes += ' {attr}="{value}"'.format({"attr": key, "value": _attributes.get(key)}) + + var childs := "" + for child in _childs: + childs += child.to_xml() + + return "{_indentation}<{name}{attributes}>\n{childs}{text}{_indentation}\n"\ + .format({"name": _name, + "attributes": attributes, + "childs": childs, + "_indentation": indentation(), + "text": cdata(_text)}) + + +func cdata(p_text :String) -> String: + return "" if p_text.is_empty() else "\n".format({"text" : p_text}) diff --git a/addons/gdUnit4/src/reporters/xml/XmlElement.gd.uid b/addons/gdUnit4/src/reporters/xml/XmlElement.gd.uid new file mode 100644 index 0000000..07a512d --- /dev/null +++ b/addons/gdUnit4/src/reporters/xml/XmlElement.gd.uid @@ -0,0 +1 @@ +uid://7ccqb0s3a11f diff --git a/addons/gdUnit4/src/spy/GdUnitSpyBuilder.gd b/addons/gdUnit4/src/spy/GdUnitSpyBuilder.gd new file mode 100644 index 0000000..5d8b631 --- /dev/null +++ b/addons/gdUnit4/src/spy/GdUnitSpyBuilder.gd @@ -0,0 +1,154 @@ +class_name GdUnitSpyBuilder +extends GdUnitClassDoubler + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") +const SPY_TEMPLATE :GDScript = preload("res://addons/gdUnit4/src/spy/GdUnitSpyImpl.gd") +const EXCLUDE_PROPERTIES_TO_COPY = ["script", "type"] + + +static func build(to_spy: Variant, debug_write := false) -> Variant: + if GdObjects.is_singleton(to_spy): + @warning_ignore("unsafe_cast") + push_error("Spy on a Singleton is not allowed! '%s'" % (to_spy as Object).get_class()) + return null + + # if resource path load it before + if GdObjects.is_scene_resource_path(to_spy): + var scene_resource_path :String = to_spy + if not FileAccess.file_exists(scene_resource_path): + push_error("Can't build spy on scene '%s'! The given resource not exists!" % scene_resource_path) + return null + var scene_to_spy: PackedScene = load(scene_resource_path) + return spy_on_scene(scene_to_spy.instantiate() as Node, debug_write) + # spy checked PackedScene + if GdObjects.is_scene(to_spy): + var scene_to_spy: PackedScene = to_spy + return spy_on_scene(scene_to_spy.instantiate() as Node, debug_write) + # spy checked a scene instance + if GdObjects.is_instance_scene(to_spy): + @warning_ignore("unsafe_cast") + return spy_on_scene(to_spy as Node, debug_write) + + var excluded_functions := [] + if to_spy is Callable: + @warning_ignore("unsafe_cast") + to_spy = CallableDoubler.new(to_spy as Callable) + excluded_functions = CallableDoubler.excluded_functions() + + var spy := spy_on_script(to_spy, excluded_functions, debug_write) + if spy == null: + return null + var spy_instance: Object = spy.new() + @warning_ignore("unsafe_method_access") + # we do not call the original implementation for _ready and all input function, this is actualy done by the engine + spy_instance.__init(["_input", "_gui_input", "_input_event", "_unhandled_input"]) + @warning_ignore("unsafe_cast") + copy_properties(to_spy as Object, spy_instance) + @warning_ignore("return_value_discarded") + GdUnitObjectInteractions.reset(spy_instance) + return register_auto_free(spy_instance) + + +static func get_class_info(clazz :Variant) -> Dictionary: + var clazz_path := GdObjects.extract_class_path(clazz) + var clazz_name :String = GdObjects.extract_class_name(clazz).value() + return { + "class_name" : clazz_name, + "class_path" : clazz_path + } + + +static func spy_on_script(instance: Variant, function_excludes: PackedStringArray, debug_write: bool) -> GDScript: + if GdArrayTools.is_array_type(instance): + if GdUnitSettings.is_verbose_assert_errors(): + push_error("Can't build spy checked type '%s'! Spy checked Container Built-In Type not supported!" % type_string(typeof(instance))) + return null + var class_info := get_class_info(instance) + var clazz_name :String = class_info.get("class_name") + var clazz_path :PackedStringArray = class_info.get("class_path", [clazz_name]) + if not GdObjects.is_instance(instance): + if GdUnitSettings.is_verbose_assert_errors(): + push_error("Can't build spy for class type '%s'! Using an instance instead e.g. 'spy()'" % [clazz_name]) + return null + + @warning_ignore("unsafe_method_access") + var spy_template := SPY_TEMPLATE.source_code.format({ + "instance_id" : abs(instance.get_instance_id()), + "gdunit_source_class": clazz_name if clazz_path.is_empty() else clazz_path[0] + }) + @warning_ignore("unsafe_cast") + var lines := load_template(spy_template, class_info) + @warning_ignore("unsafe_cast") + lines += double_functions(instance as Object, clazz_name, clazz_path, GdUnitSpyFunctionDoubler.new(), function_excludes) + # We disable warning/errors for inferred_declaration + if Engine.get_version_info().hex >= 0x40400: + lines.insert(0, '@warning_ignore_start("inferred_declaration")') + lines.append('@warning_ignore_restore("inferred_declaration")') + + var spy := GDScript.new() + spy.source_code = "\n".join(lines) + spy.resource_name = "Spy%s.gd" % clazz_name + spy.resource_path = GdUnitFileAccess.create_temp_dir("spy") + "/Spy%s_%d.gd" % [clazz_name, Time.get_ticks_msec()] + + if debug_write: + @warning_ignore("return_value_discarded") + DirAccess.remove_absolute(spy.resource_path) + @warning_ignore("return_value_discarded") + ResourceSaver.save(spy, spy.resource_path) + var error := spy.reload(true) + if error != OK: + push_error("Unexpected Error!, SpyBuilder error, please contact the developer.") + return null + return spy + + +static func spy_on_scene(scene :Node, debug_write :bool) -> Object: + if scene.get_script() == null: + if GdUnitSettings.is_verbose_assert_errors(): + push_error("Can't create a spy checked a scene without script '%s'" % scene.get_scene_file_path()) + return null + # buils spy checked original script + @warning_ignore("unsafe_cast") + var scene_script :Object = (scene.get_script() as GDScript).new() + var spy := spy_on_script(scene_script, GdUnitClassDoubler.EXLCUDE_SCENE_FUNCTIONS, debug_write) + scene_script.free() + if spy == null: + return null + + # we need to restore the original script properties to apply after script exchange + var original_properties := {} + for p in scene.get_property_list(): + var property_name: String = p["name"] + var usage: int = p["usage"] + if (usage & PROPERTY_USAGE_SCRIPT_VARIABLE) == PROPERTY_USAGE_SCRIPT_VARIABLE: + original_properties[property_name] = scene.get(property_name) + + # exchage with spy + scene.set_script(spy) + # apply original script properties to the spy + for property_name: String in original_properties.keys(): + scene.set(property_name, original_properties[property_name]) + + @warning_ignore("unsafe_method_access") + scene.__init() + return register_auto_free(scene) + + +static func copy_properties(source :Object, dest :Object) -> void: + for property in source.get_property_list(): + var property_name :String = property["name"] + var property_value :Variant = source.get(property_name) + if EXCLUDE_PROPERTIES_TO_COPY.has(property_name): + continue + #if dest.get(property_name) == null: + # prints("|%s|" % property_name, source.get(property_name)) + + # check for invalid name property + if property_name == "name" and property_value == "": + dest.set(property_name, ""); + continue + dest.set(property_name, property_value) + + +static func register_auto_free(obj :Variant) -> Variant: + return GdUnitThreadManager.get_current_context().get_execution_context().register_auto_free(obj) diff --git a/addons/gdUnit4/src/spy/GdUnitSpyBuilder.gd.uid b/addons/gdUnit4/src/spy/GdUnitSpyBuilder.gd.uid new file mode 100644 index 0000000..ef81a22 --- /dev/null +++ b/addons/gdUnit4/src/spy/GdUnitSpyBuilder.gd.uid @@ -0,0 +1 @@ +uid://df5ntqpm07nwm diff --git a/addons/gdUnit4/src/spy/GdUnitSpyImpl.gd b/addons/gdUnit4/src/spy/GdUnitSpyImpl.gd new file mode 100644 index 0000000..e0bcaf2 --- /dev/null +++ b/addons/gdUnit4/src/spy/GdUnitSpyImpl.gd @@ -0,0 +1,46 @@ +class_name DoubledSpyClassSourceClassName + +const __INSTANCE_ID := "gdunit_doubler_instance_id_{instance_id}" + + +class GdUnitSpyDoublerState: + const __SOURCE_CLASS := "{gdunit_source_class}" + + var excluded_methods := PackedStringArray() + + func _init(excluded_methods__ := PackedStringArray()) -> void: + excluded_methods = excluded_methods__ + + +var __spy_state := GdUnitSpyDoublerState.new() +@warning_ignore("unused_private_class_variable") +var __verifier_instance := GdUnitObjectInteractionsVerifier.new() + + +func __init(__excluded_methods := PackedStringArray()) -> void: + __init_doubler() + __spy_state.excluded_methods = __excluded_methods + + +static func __doubler_state() -> GdUnitSpyDoublerState: + if Engine.has_meta(__INSTANCE_ID): + return Engine.get_meta(__INSTANCE_ID).__spy_state + return null + + +func __init_doubler() -> void: + Engine.set_meta(__INSTANCE_ID, self) + + +func _notification(what: int) -> void: + if what == NOTIFICATION_PREDELETE and Engine.has_meta(__INSTANCE_ID): + Engine.remove_meta(__INSTANCE_ID) + + +static func __get_verifier() -> GdUnitObjectInteractionsVerifier: + return Engine.get_meta(__INSTANCE_ID).__verifier_instance + + +static func __do_call_real_func(__func_name: String) -> bool: + @warning_ignore("unsafe_method_access") + return not __doubler_state().excluded_methods.has(__func_name) diff --git a/addons/gdUnit4/src/spy/GdUnitSpyImpl.gd.uid b/addons/gdUnit4/src/spy/GdUnitSpyImpl.gd.uid new file mode 100644 index 0000000..9b47f32 --- /dev/null +++ b/addons/gdUnit4/src/spy/GdUnitSpyImpl.gd.uid @@ -0,0 +1 @@ +uid://bhs2fvc0ku478 diff --git a/addons/gdUnit4/src/ui/GdUnitConsole.gd b/addons/gdUnit4/src/ui/GdUnitConsole.gd new file mode 100644 index 0000000..eb1e625 --- /dev/null +++ b/addons/gdUnit4/src/ui/GdUnitConsole.gd @@ -0,0 +1,91 @@ +@tool +extends Control + +const GdUnitUpdateClient = preload("res://addons/gdUnit4/src/update/GdUnitUpdateClient.gd") +const TITLE = "gdUnit4 ${version} Console" + +@onready var header := $VBoxContainer/Header +@onready var title: RichTextLabel = $VBoxContainer/Header/header_title +@onready var output: RichTextLabel = $VBoxContainer/Console/TextEdit + + +var _test_reporter: GdUnitConsoleTestReporter + + +@warning_ignore("return_value_discarded") +func _ready() -> void: + GdUnitFonts.init_fonts(output) + GdUnit4Version.init_version_label(title) + GdUnitSignals.instance().gdunit_event.connect(_on_gdunit_event) + GdUnitSignals.instance().gdunit_message.connect(_on_gdunit_message) + GdUnitSignals.instance().gdunit_client_connected.connect(_on_gdunit_client_connected) + GdUnitSignals.instance().gdunit_client_disconnected.connect(_on_gdunit_client_disconnected) + _test_reporter = GdUnitConsoleTestReporter.new(GdUnitRichTextMessageWriter.new(output)) + + +func _notification(what: int) -> void: + if what == EditorSettings.NOTIFICATION_EDITOR_SETTINGS_CHANGED: + _test_reporter.init_colors() + if what == NOTIFICATION_PREDELETE: + var instance := GdUnitSignals.instance() + if instance.gdunit_event.is_connected(_on_gdunit_event): + instance.gdunit_event.disconnect(_on_gdunit_event) + if instance.gdunit_message.is_connected(_on_gdunit_event): + instance.gdunit_message.disconnect(_on_gdunit_message) + if instance.gdunit_client_connected.is_connected(_on_gdunit_event): + instance.gdunit_client_connected.disconnect(_on_gdunit_client_connected) + if instance.gdunit_client_disconnected.is_connected(_on_gdunit_event): + instance.gdunit_client_disconnected.disconnect(_on_gdunit_client_disconnected) + + +func setup_update_notification(control: Button) -> void: + if not GdUnitSettings.is_update_notification_enabled(): + _test_reporter.println_message("The search for updates is deactivated.", Color.CORNFLOWER_BLUE) + return + + _test_reporter.print_message("Searching for updates... ", Color.CORNFLOWER_BLUE) + var update_client := GdUnitUpdateClient.new() + add_child(update_client) + var response :GdUnitUpdateClient.HttpResponse = await update_client.request_latest_version() + if response.status() != 200: + _test_reporter.println_message("Information cannot be retrieved from GitHub!", Color.INDIAN_RED) + _test_reporter.println_message("Error: %s" % response.response(), Color.INDIAN_RED) + return + var latest_version := update_client.extract_latest_version(response) + if not latest_version.is_greater(GdUnit4Version.current()): + _test_reporter.println_message("GdUnit4 is up-to-date.", Color.FOREST_GREEN) + return + + _test_reporter.println_message("A new update is available %s" % latest_version, Color.YELLOW) + _test_reporter.println_message("Open the GdUnit4 settings and check the update tab.", Color.YELLOW) + + control.icon = GdUnitUiTools.get_icon("Notification", Color.YELLOW) + var tween := create_tween() + tween.tween_property(control, "self_modulate", Color.VIOLET, .2).set_trans(Tween.TransitionType.TRANS_LINEAR) + tween.tween_property(control, "self_modulate", Color.YELLOW, .2).set_trans(Tween.TransitionType.TRANS_BOUNCE) + tween.parallel() + tween.tween_property(control, "scale", Vector2.ONE*1.05, .4).set_trans(Tween.TransitionType.TRANS_LINEAR) + tween.tween_property(control, "scale", Vector2.ONE, .4).set_trans(Tween.TransitionType.TRANS_BOUNCE) + tween.set_loops(-1) + tween.play() + + +func _on_gdunit_event(event: GdUnitEvent) -> void: + match event.type(): + GdUnitEvent.SESSION_START: + _test_reporter.test_session = GdUnitTestSession.new(GdUnitTestDiscoverGuard.instance().get_discovered_tests(), "") + GdUnitEvent.SESSION_CLOSE: + _test_reporter.test_session = null + + +func _on_gdunit_client_connected(client_id: int) -> void: + _test_reporter.clear() + _test_reporter.println_message("GdUnit Test Client connected with id: %d" % client_id, Color.hex(0x9887c4)) + + +func _on_gdunit_client_disconnected(client_id: int) -> void: + _test_reporter.println_message("GdUnit Test Client disconnected with id: %d" % client_id, Color.hex(0x9887c4)) + + +func _on_gdunit_message(message: String) -> void: + _test_reporter.println_message(message, Color.CORNFLOWER_BLUE) diff --git a/addons/gdUnit4/src/ui/GdUnitConsole.gd.uid b/addons/gdUnit4/src/ui/GdUnitConsole.gd.uid new file mode 100644 index 0000000..dc7062a --- /dev/null +++ b/addons/gdUnit4/src/ui/GdUnitConsole.gd.uid @@ -0,0 +1 @@ +uid://b3rlhmmvyunrm diff --git a/addons/gdUnit4/src/ui/GdUnitConsole.tscn b/addons/gdUnit4/src/ui/GdUnitConsole.tscn new file mode 100644 index 0000000..f35a503 --- /dev/null +++ b/addons/gdUnit4/src/ui/GdUnitConsole.tscn @@ -0,0 +1,1284 @@ +[gd_scene load_steps=24 format=4 uid="uid://dm0wvfyeew7vd"] + +[ext_resource type="Script" uid="uid://b3rlhmmvyunrm" path="res://addons/gdUnit4/src/ui/GdUnitConsole.gd" id="1"] + +[sub_resource type="Image" id="Image_p7eji"] +data = { +"data": 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") 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a8MxdQIMARj3spB5Y2UZlh1EecJQqRvrNV1r+sj3H8W9fOfmtkb2B5W3Y37Hkes863nsCK3lKoQB6PWt2klTvVNdL3FyWDXttiuaP8CMU+8n0OUcoqSBeT9uFFI13TVrXyIghHa3luKxMTbFv9pINa0C+a8mMlAM6GKHIcXN6HDVYVbHftuqE+i4JmWpPZq3qPm9doDKn78/7LzvviI3R3+I/y2J8q3LCu6UQQtE8B8Myjsd90FCfsnTNmZwxo3dfUewadDbPXYYOKbZVr3jmB4509NxNaFw20qITsCSG10iydfOYz6PYWqNNGjksz6fL5YB77RxvbN0uSvNU9WaH0pCptcr4hXPN8Xgz6KsdEvemVM6NsbCrpsaTLh+6oy39vHuQXDJYQEwMrRnFeOdA1LXsBBMj4p0YGMvs8K+dq4UjNdbUyiOiZYI7NvQUGLp0yPfaYeE3ZeL8Yjyw2BkRumxQEVhuBzCOAx4DFuZKKrdciE6PP/ukeGpePvVFq5sx4+fpXNd+JreOcJSPU+ZzJV7EFc2dOT9L5bvdkV+APlq4z3sGKVja3ZDMIdk1hNt8jY4hqlNGquJr8JpjQDvf/Y8FPXaFo6XQvCus3TRn9NSYk/IpmiZyiXZDxEMXDyYPHgzt5iQb5fSXM8AJRZox0hVHWxnA6HMIHOsIBaHhYMQxdyHzY3rF1phVMWUpBFoJgiEkFZuVOD5ipu5AHCl+JwFDca/hRMchZmtEbRiySrnbPUqUlfxOLyJ2R23FqdRwynXgQ8cmxDh5iW1wCG57Vmd5SIAurcAsOwEfMYSSIJBn0L0iXQZlmVrYRpqxoqyIRCPyDCaresR9jkGlgTJWsxsR0xh0pYNWWNIcabVWLkphzigwhtbaxbKaH+G7W7Yjb73+J311N32qYnUcabGZx34p63Jh9pRqKfGuVq5txPmwqTlKB8nU8MskWDnM4z5k3Pyfr6Tak2GFnVujuYOmv58joZj4cc6wsbDb5iI7B9D+wIwWr/MuWN6NpN0ygtqi3DjjvLt55Lsp0QgMzbgK0h3Exin5I199OwQHJ0Omg2ivKRnbprbVurFTwDZANx3BdmVRyV8MsOUx69wClgcwpHtoYM3BW5+Nv1LBWKM0y4VDtim1CEPtMDUaL2PnlmbWyRuMTqv9dBGk3hzcB88o+XdGjdGjndI67MUIpkwHNoIhpG4DAzZdd87S6OrOIovA+Gy6Xu3o0SsLZoKOdK4EF5U6Yke2ZBW1TNov7OsmnTTaRxNnp0IqAahEbTM6tk85Iskbh+oJNg5SDGLq6zGfw3uNMu6fIqMoxr79p7v6upYjHcG4/ACOXEG4Arg6Ls9RBxoYMpPtTaXz1MQiUMVUR9T10DkrfmWo+ax1e9+5lAElKUbRib8jNN6U91lFRsyQo8ZmhWYGtzcLcWQqTjHNrIOahxi5KmMD4hzTW36xNqybdG65TWuMcsHcWepV5ETpnFMol3w91DK9s3y7DjDUG5ctvdbKZEwKhqZciW5DLpEX93fZ3ss1jxUwcpiTN2NEonZtXAbwIrHlHkVvH4fejL4azahy8EpmUZ53Xu83pzjPeF3NW9Z39C4prIecfjOvpRw2OWdszYCCAQV/Cm1N1dBDyAyaa7oU+c0t3dBYM3WYN0rzqP6a3zwwM69MfyzMk+Aah2+e36GBsu91eluz5viB0my0A9b262ifdj5fLrGChOq/XDQd5yFAhBQFak6ix5gkNzBjxY4TN158BAkTSZYYSTK8IU+R5exZphx5ChQpVaHak+o1ekOzVu06devVZ9CwEWMmzfjGvEWP6hgOwdFwTBwHx8MJcCKc1AqrfdJ6G33DZlttt9Nue+1z0GFHHPNRAEsE4ADLDIxcCRMDxywcP3/My19z7/47LnP2BLSygf7ODRawgR0cwudvQAz0gXvRC0XQ0FfEc13zIZoX/BPPMdSIkEPLv1vgBkG1iwsiQEUcf+FeVarwuiZ+34NLA+UgINrwLaeT6VLvsrVU/sgpxctUIkU2AzkZqSYSYiJCRx0mcMA+fDxcu+3E0YiNhWlbsUViG2eAQRAR4MEBXqCaV7WhoqykqOC7r/I++eCdN3LWZWWkrUlJultM9NRuw92fqTYBlhc/a5+nnKEZrQNhCwMYj4ktLWDt+OLXyd4Ue+BteuyIwSE8EpewHrZBHmhQDxjUCwHqE0C/x20wQAkv3xnkE0O8YZgsI6wxSoIxYoyziI8ZfuUlfoL8hp8AI/xOPxO4+YMugjzhT+4TwsozOnh+xcQL2niJkVcYCKNjEi1TqJlGyQxyZmliDhE0z2Eowj5oAS60CAdaggUtswVagQJFQaC/BA/FPFzjbyrEKfIPX1nlA/+SI0GG/0iR5LmgwEkp/X8GKMESXxM+GtQRSzOqpHcCTdwn4Jnmd45mwukjLegueHgAaV53wCMs2tM938vwiBynbb3VO72HAiBdt3rhsgeARxpx+6tdfbq8fQSPrMNtW5/Nh5NJ2pE6b+192LeRnlzLkVpul3u3p5BWrdMoXI6wYwEgAOWrIVPCtmY7t/QrOtnmz+zMMa1dx9YzvdSzvdxr+XlsnzZZRUtIceJg4pR1Syc6sSed0vm6LlL13dLergS3hk2/KatfxlKGTFmy7bLbHnvtkyPXfgccdEiefAUKj+j9z6REqTLlKlSqctgRRx1zXLU6NWrVw9OfC/kzLj6ap3ZiLIPHL4/OqbE7Pa5BcNk559ysPbffTXmuvs754E/j9ddHxBUeEx9wacJPUnfh8XEVVweUibTInotxDP/wjuXlHM8reTUncjKv5VRe99gTTz3z3AsvvfLaG2+9894HH33y2RdfffPdDx06denWo1effgN++mUQgs3LgiySbJjhRhhplNHGGGschP7BLTnM2Dg+iv4PNiDxGWwzZVKMPMYlYizSguwnGweefarz+hxuCjOJrWRXHOR8mbMN3+q2FhoztTOdMpmtx91eanGWZWV42SfpmZ+FJGa8mWgmPwMgpG926bZwq7mzS6uBJudaXQ8429xtQpNI0jGE2ZyvR12iRPvsyFIys+L9XVkNtzW4/HzbpthctuEQpc2cJYIQMQRgzJVgOXQwdYmgBzolTvxroUjB4kgqPji7c9Fsdodk6z8ZZLiBKC1cT6ln1/PrRfXNq1nD3tjOfbKe9e3LXd7UvtnC1oIhTISLHEVkUac1V8VCpFFFl8sx535cGUowc1lNNvlUSkAZKAc9gEpQZU/2Qk211dn+Bjqluw2Bumm7fhineVm3/Tiv+3m/H0ZQDGd0hcki2CSHy+OnxrLZOzg6Obu4url78LjtKN4kljraepS4B0UKyAzLlWqtzmBsM3VY7z/pcveP+IMvZxaln9bj/taWJYFE2pEtWhYVE7cqISllTVoG+d6sRNbzTs4mf6C0eW8geH8dwTdwBnh0v/7/cT4oEE1Y0E8eOgoJRQSJHKRC5SE1htQ1gwzFl4n0CiSUsNfLzGTRK5JoVkccTzJpNWQt2bzJp3wfKrQdMqWUDeg5toKFgGKgxYbS0G0oG3BjQ3eiPPQA4FqIHkXFqFSb0OeVVVFVNT1d/Rx0oNrqaqixbTVdll/ujbbXUlvtdWjEZHXVU2/HjlKHGm7pRMuKNIzkrrmXls3NOyv58rF6MTeEl5Dh8jkwIqjHJMhhvEgML/yqFwt0FmJtiGh6+rASNVp0GDDOEawX/Yu6P5FbmOnkLo9w0j35WJAwEWIkyfCELtz0M4J/CrHaJjSQGrZsNlFWSb1U+lfwga8UiXYAmkqbDl3GzJizZM2eAykZF3KzzDbHQkstt1KaddbbZLMtdo7k7rkOyVd4kFsqhu2/rb4s5CD3mOkZmZhZWHlgc7g8vkCh1mgtVptvdW19Y3Nv//Do+IQoqkZ1w2K243p+EEY3t3f3f7F8nE9zFyEcFf7YdBbDpN7JP3dxw8PFj4xcRW6CSxyrKumTrCUipkefAZYpCQtWbNlx7OB4CFfabzNTilRzzbPYEsussMoaa22wUbqtttshY8MyG1VzngJF21Nqa3LVG2f825/18OcOYgcQGdjYOXAhlpHIFBYoFIklUplcBen0BqPJbHfAHC+IC4tLy1vbO++5/o6z84vLq2skYfnh8en55fXt/ePzX0YqqEEbvGkEzCelvDgFYrjIVU+B8N7bNNd5RbBRlw4+4fskUaoUFvmanQEoSni0l9IjFo1Ed2SAwcVSHrHlgJKoBFFmP7l5VLaQQaeFQosRTqoRWjfFTURaltI0ZK0qtQlNhf8wZbXjHGpv1adA9gj1ju7reLmdiJbiQVzsKX5WaPo4HUWaY8ki9s4o1SRikHaSyj6e5VPC99GYRpJZ2YgIbBNrg1q/1j+5awK6vT05+cTdSfHYBXIbLGERvyzJGhzXrY3xIL7b4oiMWNHckLu5cSVKUWWrT+8t181x3DSR7FMxlVC69VljhYZa5+NirhhwPvng0t5WDFR66vS+npsIW7cqdk6i5xT6rmDhPKwLmLqKpSZ0NKPrHq5OY+AMhhpqEQ2g0Ii21jknbeDsNvauYeUEYhcxcx1rN7DRgqN2XPyP1F1k2ncJCXAZc+AsxsA5TIAP7RDcgBvRYV0c8Eo7mp7+Aj01jHQwE2OlB0wdO4IT4maIF8VPmyA+YQxRBsQJSdIgTZksLnmqFClRJqJKkzoOTVq0CUDx6FKhT5cx/c9kwQTM2lta29o7wpForLOru6e3r39gcCg+PDI6Fu3ujNOhbIj7Zg1C5zrms4glLGc1a1lPOtvZEdtOl9+vmROxsDDzbLMzsJnpn/UZECFPRuynpBYVMM/H6k0WV7OyWPK/rHmnYXm77H6xnEwZnlcakVfL622NbO9sKGV5OnI/Y14khUhq46C16HkYLCixfrMIKdElDM2aTKnqDVW3KTV5vdp+w0awlZS20tHbbErZ3nL+yMN7p/WlIfB0pb25AqpSlA8q7o1SiuVqUfh5IcHZi5bKVrNw+rl8dYZ4RLBJg4Jne/5+qUCphV/N+Psf46HO684LcSu9PAxCfELXrCDQxNekEqZKTWtvXDAJ1llfZx2T0txba+FjUykNNLKhTD57uiGmMZ2pTjGPrc5of7sRdVVfw/PSLd0lluvOqLa3F+xrwGg22y3aHpXskp7dzV6dPe1PP+l3rZkWMdNc1UpWv+uvdgBLBofT/m0u3c6rKWN7Y5P4xvjWYHsmsMX++jLuzOUm3tuAQbrj0iuWVdqLQTbYXa4Y4rOv8M3VeRumxdafxgB3YFo51WyQh6JZBmpkKUZkqIqoNGydFN3I8sN2X5MSH7O98tGEjaUngOs/RRkqEFXqGeI0L8txAXmhlQCi3dfh/aTZ5qdH8/1i+G1oOJwHFt+MfB8A9GdjsTecyBu9JnvtBPiNyETonMwfd5cCcKmr8j6I9sOPPX/jpClw1AP9x0ERWZJCREXLxMHJKySlVrM+Ywy2frCARJACMkAB+HqCf30GGQQxfgOdvZw/sgxRVklo6FjBPAISatRrM9rY1nttlwCWg/TiG3+8V58eEvw/0fH55cl/Ry+nd/WmZ3r2e/72/Knyf5AAyXr+gN+T85Ub9eoQNVE91VIVfnpx4fGh/W5NifEotuVI6bz9soDR0RRnV3YLFyF2CLvCIcm58xAsREKNC7md5LxF0k/ImZ/mNn0AcH4F9FMYlpgKSHbuCziDcGvig94binuL1TKoQEGJUAloVRG76leBGPe1mLGMWKVGrURCgp2Lj0XPjrJyo3X9wvLyiRdLzC+NFgzsaZDSMJ/MLyI1AGOHkDX6NZWdS5iU8poCO6rxlnTVg9kbcTDZskOi3YBId5CkXrSQma1NzEah9xid1k5Qh5FmAp51DdYC283unUZCM3QGGlF9pmeAthR10GRo8TPRSc7acAuWaqehPl2RAuBTAxCMoYJVMRvh7TpC1j0WfaxfTZj6uotJYQhArQpWNFt2GKr9N/iDSfpiexzqCnBdOOZo9OW1PWsKl+0PW+Z0KcVnhhwxXI+kSRvfT09M3dNyVdpE+VqeHi/67WjC86cerMhpx9zubei+SmpwhedlS8RRbaAXOiRfLJbEOs/r2QAhhI/FNp6sBi3jDqpGWhFUnQoNcaPQ5nuW9KnEZ+QQecHw/IhME9lG+r5M5Qk5d89yvZKVXT7fYBOLfCGH3eiVa2a5ofAt/sF/enL3yOOS9pBfyiq0UDnRIUWT04FNrYbn/siIKOfFlY2SyFsj7HM5ey2wWh2KtxevoR2dZ0CdYnmtmizB1OfUgPmDO9YBIYwKuUcbW5rMy1QD2azbMY+Odnx3Hla1UtnsW/AhfMSbtLWjz5HMdL8WrXHccsKZaYF+JfOE1p/jjSuw9dOOmcLENAjy9eiz6E3MB+8FvwVT1tqnwVCyOmR63eVt5D7j1vfdjHz8x8fy/yT6OPT7/vNe8VR88+PRMhi/xSffvz10vfaa/HIevgjnoXxnlKcc2mmkcpH7JmsWsPF3/hGOl9ffe89+afme9+37sf3KvAG8YFGjpRyXtlLuzVJPVs61MshYO1BTSidlpYztfDoU0Xhke0fjnu5d24eGX36wnQdLze/75u0MX779kfk080nmnU/47P4uTuKkSrvSeeW3stBCFARCo4Xn3TR7mhbgFrpGV0peNu9S9pTSOitEtqSVUFkRizgSQr9LpkhoikUBxKui8QF/wTTI0W0GtkzpPSzTn2U/2Zyr0Pidjri+eCE9zaFlVpHKab5Cy7ipnuW6np5vcbRWmD1zRlpLrWoG2pP6VMBnurwW9wbph3kkXwoyv2QQv/kdTRji2KJORXBkAYSwYxxUG2KtCmMBCOg+ObGMKHItclW3ZPlTzJehklyQ+79fqLwbTHNRQvRSEWEqFaao1bxG2QNZj+h301ydRO8xeJ0oSCnctY6TOIldjpMuHR+dyv+PL9r3JXgBEOVHxj7E3wCvVU1TtaI5J0W9ncx+eppNI4zRaJBCDZmYJmRI1iJlF1j9thBMjJowfPzQ/4MOkim4MNqKAOpbtbm63ZCe9p16g7QuDwc1RqEOiISqyau5FV7XUN16J1P1Q/OwOv9Vfa7sa8jk+R946Hy+o1XrL4LRZrecrmH0NNusYymT30AAsoOURvKnNl41m15Xt8Mzg1RwauLRrRBO5sFZnDeM2TWJ39/NU8mZQwfKvsLp08neF1+042PwgqZG7BeIiPodyUd8aOl/cWlR5/ICdMVdCO9NlayZh3gvPUP8V5L7rEOKE1JyUsOIfxGmPtLDU8KFrqgWoX1ItlcKnKxcmABK0OZLGKRJbRsfR//nOHMQJiPAi/7QFtoAtD/RZ6OtIfqOROXlOY3AaDDU1LViAChmkOKTCs9iGS5qzeHOTFb4mV4sBnF7VuOQaJ/G0OzU16cj9BBTpkaiEPuQPMYWfCFh2/lsRhJDgWCJcFYYWusj/BdRVJAZGalyUlgoZLIABMxoeO0bgOw4c1shL2v/dsGom5miGJWbEgizeqkbCTKIVXzzsUl1A7KvgrYy1Bp6DFXpP5/HTISNoKt7sUauaxfd4TzGLOTLNh6AtqD+JV/KPNBYnADYxjmmc+lCOIpHlA1K5hLfn09LCxWazUszmaq/kTIWqVWM3/vE6Gk7yeOy46XjAn6nflL6YOP28Q7TDQWrH6qeEpZldw6cs8wzSWqemwmVjsNBG3qo87D5LVnZxi26W1fZpj5p7filmr3OHF5ufz5megn1y4UnIbjOMELYX0qg88xCggZawFwGOtvYk+datOUEqBJvoEqBu8yBId9XilEO7rRifmXL0qadfDtY4DbDQAXzUESwbKKqzOeQBkOv8bYkHkghhwFLYw/ysoC+3rIdOV/QSEKUkjJBO75Jm2klFfMa7PRKmu4ysfuCWh+xU+7RIrssKew3+14J412GgpoUMpgLpteszroQS4g7qbUusks3z7P/q7j7lZUNLuKYfpzBDVuPMZ2tudclJIu/jk5hXUFkfm9DLhmeSf4QxE74ANTshH3oYD92LMHlNrAdexmTUK1dXgtJPERcCUNQImv5gDWqhbPc29WNPpaVh3JP6idQCT/cnXA5OJS1LankA9GAeUxcoxTEO4RNY2KU6KPXENApkaPTiUdJr2TFba5wp7Upupk66BtxJ4qWN3IoAgsOYyWVrlhTFaI5/glhOt2dtV2bT68FdTxqxlBBlRrnaGgl0mX+GsKyOISxGh0ysztOtamxZ15kTkA7O0MNYagwkpv/jGs2i4GbmaYTblXlKeZBII5zPivBkRV3iFTyJdPY0UjCu+0RfYbzipt+3obTUe6zdd5WLyrHrpSswUYt1JHwlhbR5N2gY+zMRPAyLH5qyGtSIKmJBtJVfcPS9LMyQgPEHQDBmkJ7VheOSQwA3nHZHaJ9cSVsBHyjZ73Y73VyVfh4s0wbHSJoPBcfLwJqzqAC0WNh1hpgkxtM7V12V1uikqOfIQI5gy1bCQXPFdd8yH/t/VunYWomhfnfsq9WYuQnBzlW5J+pSk3r1hm+ArUnlabeRbfaeA3nDasKtB1KiGqVlWsIIAfSwAW6aJ2IV8k4jhVcls/y6Frbrw01YzkkT81iFqnGPf/7WRUiuCbkVTzlgfS/jartGe4BFemnlz6bx4w7zC1pMlSZfKSmEf5B6HD0+iqie23lXLzIVHMy8rZ9prta19Kt79Yk7BGa29AXv55YC8GQhF2cbdGMEMm+sNfdZ9FZFs7eo477xcT5RwbF+9Oo2f38teB9itI61qa9sHZXKLiSK4Ue3cIEL2+vj8lv/pi/h8q+nn5ttseV4IRqJdKCMC48J4b4b728bTxiLiMC5CQ+YOUPTT9zwPoZcIUn/fkNDxFa92uWtpONDO+t8k2KE/EEiYSPSiCtxd/h62NpJBySS+f1qfLlaYhfLT+d5Ws4W0bgnRUvKmwZIO/bpV0Sgs5/cwDzOlKuo3hA1opRsWXgZ5dboRavBNKrg1Zvfku7L94fr/++nVYgSRegVszryx3yC8OwaCJycnEe+D8/CvfcGKyf1D1C1s4/0wfqpoz85NrGVWZuS6cqqutr3xWDJagO54sId3A7hbjalxnz/iCYnrLZkzEd2SJ+/Pcs1HLTaQObdHmrGO/MZyZWBkCND91uZm+JE4pySF0/V7B0DfvQfR+SUxaYfZF2bFggnILKz8x5Ubp9U2N6nEqniIezis6BqysvLABr6Q6IzIpcLElYTgp0Imq6v1To5Yh5Rodclt7utGDF3lEpWk0Fzuwkjy/P53d/zd4/y9AKhfmQn/zAWT0VqlNvq3hNENJiYIv19dd2vvi9l65brLkqfxdsOQzI9/UC90/ZBzDQAmJbfjjBAzy5TCWpJ6D/F92OOT+sdgcgBk8jT4fB3o2JP0dHgKq/8JwxGIN28IAcS24ESUf/N7Y8CmVr7+5YFIMx6h+RstmFj0vpBY2MTrGCIVqMmt14ZT/fzeCW2TENH4tUmZJ1H9wa+9oQKS2/sOgJKxDXFZAyRZq4sjEAboWBhHS9SCorDf8Bb+PSV/QhdzWk/OiKNBa3DhSQzDJZaxgE5NCw6aEksa5pKri6yEkp3RW7GfIKFZvVJKeMlg2EAHV49awEnCjCDrA5Sr2mhQNzG5VYv0veP26gHAZ4pMol5BQP3pHTyFlBxm0zxebhWVXfeHJlheBtggG260Ccc4DajZnfcxljr+wtaCA5LUfUKAOw00nqyHZ+AegyxZA6plcGNphOSFnWjUQ7uwS3EhzV19ts+hNreEnx6CA/DXdiEIAIszfE0+POqn4S/maHCqbt3rHpMTZR42jyr8qllUcOuD6wSe6jVwhpNdWgbN44cKiQz2Kkz0kho/RnaWKZ21qiuVH0AuO3lDJvrNngKQrzf79dSU8iJmq2M94uKH9ZACLxAJJCiUnl97AkhoKurscaZ81A7NiTI3/KLr2x6xMG6sVpeKCazLrpTEOEHokUUa0mJF9jE4JokqBQtlMZr1XiCvPfCsfXcfNuUvKKV2OtyCSsDd4E/r6oqu1N3TGQpNmQ7Uqc5BSr8Q484TqA2EkW4hG+chA/3vnJz6K5MdOr3JLNBGuwPind21EhWuPsQtdYAY3IoblYI2oF88isFaAvEAKxHJQirdkiBHsrTF9ewA7aS23RbAfXFB0WYu1jnHg4q/xgAdiW5tCVg3wVZLdyG1uARBMY7XjIxpN8z6PrJAkF3+u5h242AMC1gfc1D6B1z+6Tl7eeHbOnF0JhCcHA7MiflO6C4qQYkybjMMknQHBN9JXeD2aZ2/oULrWBXdhDm4Tmj/Vg8S3OahzscnB9JrW+r6er4CqdBop1pdnMXmLLtjs1cARNu00pC6r6ag7yahAkx7FiFxSvtiyl+9E1w2jY+6TvHcoUJVcphDwikGufBT5QyHXyC5/LEiI4N2jfK1hNU0aW9E/xillbE08N4dIIaHc5Siu0L19pCjwayPQReQ57ul7Nz9Ke5uxROvjtolxEA44FDAZjTpRL3pzLvBJck7MMgmAr26e86SkFakx82qHQFIgeCeS70Quyp/VQcnjoRCBfeH77qk08ib4rovqyhr7YHeUv2iLcZOSb6AIm+JggW/kClaK8d857XFT2hoHOwZTYSxysSU+EOPMuMgr+uKeAtA7ulUYlotZ1cqyN7msJoRYlBG16p6S7ps0v4QmCHLv2WSemhgI+TNZiaY5bs4z+TiPfRq9xREyYvMLCAJxPUHXgdG010OiYwbWNtozOHIUpX7sm79qgK81kDo9mYkquKpSKRFwVy9r5IwQgc7xtDX89ku+tUqUew8DJDBtLMlfOcR6tUYijLjcasGpmP7TLQpm0ha1iU6gnoppx5rlRqbIMCcvLs6LpW+t6EZzKs1JM/O34e/M7ROmkYpeeBNrzSKV4iSt9AjwEskHKGcDqtK1/HU8bOeYQoNGWPYiXEiPI7IAgB9Bdez7Hs05rn7EN25zoNEdaCtbc3+f7Qvq+X59gqjkVCAFl5rhWLcSUXRQbZ8DY8sEy0edC+ndttzyZShkRZJ4LmBZBDHTm10mvqrxotf6l7pEJv4hvLjOBZqvY1D74Mqqq44CgtFN0M3jHyErkrFQeuyIBcgt3LmQKcdmApRXUzZq0bLStj2vaIa+ndWzMDBiIqxIKviEPGIpUUQNcK01KBNnHYJF7EacQ59e7sJMpquw+gaUVNtpyx2FwJ1h7fA/6oBJbmhO/Ky4KGWn3MQsbKlh0oguqZKtW3aV73AIAas7cN7aSVbt3mvule07e0cjus2gJNzdU5ab14k7z3ZJrktpbjDP3b40JxKK77ES5t1R2p+SRtFO6gaV7js2HLFhUOVYwI0tzaxtLTEJXOtzFVK/TkmbOsbLww6f4yVf0NFF/psZ7HYtWa/1HzOO4i0bOkF+nCjOQcJ9DK7SJ5uK4g9/lVGW35ox1E7l7KxBvaaYJnJ0WJZPZTsatsjBblpFv6gVOR5lghHLz2FFOvzmXaDQ7oGt9MZI7vtXSzLW21TBT4a3WraHfHbhogfQKlKXm+cXSwF4tkOpYJRIeBkNHa9FyVykxlddJrOovJs8W5aOWizTqNK2r2Pcqn6hUEAOeqfNYPOb9b2aVtDguNbhbxuD9xRAHehNdHV6/qL7GILwJS3LvLNa/yDJX1RScFhWa+1F//fA3icrlw2POkmjQ+rx8RfMXekeIfxACxY8WcKSVaXUCK31bCUbswAas13xuMvxs60bNcpGenaVaCLKkCuJpfUsTHyre9i1fZljMMmXh95hrErvf1F9wwXHHEJA6SzCJOwNQmt62TWRxgl8diq5/J7V5fCnaKY5xIUkNymi1B4MtD8mJvMC5RGPGaJHqRKLs6Se3lIzrgllyFJkhq/PjZuWSOpNoZ1f2exXl238OIod+Wn/8uunxjPJ2kkv+6hrDX0GF9VOblM4iSx2JxVuRQMeQw/5E+XDv6L3OvqGfiw94+IdGfPf/E6TQzheF633MrtfiE6LYlJKeRqocXjlGS+dnYv2rPVMSpicBSGmXg6KipuczO8Rql4QcnZ/ZcRYsRF6ta8VJRDGV1mMpRSi69dr0zAl0+vaqeE4tJLFC9vBm+60TPeT+byQui+Y3YJMHYvw9Ue/hu7ohgKjU+a5IfLnj4KIvOY1XT9Pbcdc5xAti7UajOSiTwuxYmVybCVz9m7cDDrXcePcRc1OzZeXgq9TbPt49kciP+KpS076bu8cjbOVw0WPuoT6tZKvtO49XtRIKeiDaMwYQg7vzqRC9ssMOUhrJr2AVG9DGXFpae9SRBj807+/jyqAC90CoqltkwxGut2lnQb4D09GiU8sd2wpxleK0te09kuHBnIUbef4PeSt5uuD/PzQ01NYIaF27Y6DJg5c50DXc0hZutZDlhGPu51TrAunhlKD4B0ykqofaUPagmSj2hEAECNtJGvBoCrW0xlk6qSEdYVj0fHlJp7hSE5QSaKTYRL2WcWnQblZbuS6FJkrwIF/KF2JZrv2wIPho5XN7zPWVyJQQXkubjhmR65uuY94x62hjJCpynwQGIKvk4UCd/O19EVrNwC2fuiUBdGtsaucBGoLvQb46zseuQ5uOa6E45t2G45Xazag1KUqL88/pqdbC+dC4GTVkQPfVgKESYC24AiR8qeFwx2xcAUo5NJ1fAQpoWUC8OGsdfDd8AkgamHZgKMihcWSb2HQ81g/cJpH/OEslZ5D+/n2IkXD1VQbPXOlsc8nBDsxPY8tADqTOnHk2g6g6B62E5pgjdlWh1dSZcK8yCTPFA3TRnzPhzR0jHt+IXOK+sNU+0nLtQ8H1piWJsmLROTDGnRQWJ0jP3CZb1DeToRkrXGFvuc2Bi3pDlLA6CJfSfrcERTi7TI9Yd607+DzkYLYln7+FPCLj9g1SR9EyYgVO7evO0dOsdGvS0vyQ510mQXNk/CUnlZiEQIzEw8OC5kYF2Y3m5X1MKBcKu1REuJFxtUJpk8yh1DaWNleQrLO5OzJzirb6vBbXsjIkJ4n39hDtlsOUTW+FO21ZdYbpm0t/bAMFuYFj3TNIAATDjX19qnh8KHamG7g1943/vXjc2RloMiIFV28Bx22YJykiJ7kBDRDdUE0pKZCN5ogDLG5ACOUcHE6qNsLQFWlokfzQXZsm9VFwCE2Zu6awprDB0rXpLtb1DXlnhXX7fLzXH4ISkm06ZMaKd/VUa4I48LFxt9WiuCODQTS7B/5GFdSYd6gz1dYvsSPBFx3KTuhxu1rFceiOBdMBYHfEIwGZCVdHobHq06BNwoqPRiwROUAOnM9wMQQX9fXK7EO2Iqoix+m/APzo5yP2Q+FaDJgGJn12YWQcOqbawnSH2BSR1NpVeJ97+xm0ndRSXghgaxt+ETNNjFvIiqEC/KkmCaLDtxtPzJ0wWTiKR4BJDB14S5im1ZFgXCNS+AEa2ZZ8NCEBV6KevY/seMEMC7aG+AwFNc5m5abQr5efMsuAXDf1AiOxUKh4CrGFhzrQw+3pMmbCTvmK/NjcBjCoyQbWA+O021ZNaJHrdS7zrgctiHnfRUoEMDSsRGFDT5MweGT5jFwjt5TRHOQwuqS2DVXUgHZtxFVHTH9O4mniL2ytam49wD38iUWxg2OiTnxhhggHSS5Kum4opkTLTTEBHoUhEFluRu0GHdnbqFhAFoVy1eTS5B7++vjVCOJ6Y5EKOVZ3pUu4KvOWcYM9gRSVDHruHbBTECYIQLY0ma5+pO7hUWW82yUCasVEQNbegNDorEG5fV2RnmTL/xQDN9FYLwp0ctB4JyDS0YTd2AxE0ZXUgXEll7DC1ritB2GEUrXQaAcN3ilJ0exvHLY8phnfMSNTQL9t4mnBKa0VeQ4uXazKnWHKXqNTLZZwxa0fFsj9MDufZ0STtu/EIGXPkrFU1IFQgBzQckRiw4rJM9zbvIF0N2OLxoKs2fbXIXYH0hswnburLNDBIPIt6a+7Lox/1wSEtCBhV9Z1i1iR1CIen5ANY7X3nrSJ650GmXl54AFCDWYQBxECUySiW6s4Le7J2hVCx5dgZsa6cgIdRe3COOILhUwzCceKgnHxm753kGGtlVENeMCQKymKL4ZdFVNhgqmVxsUPuEWDrlOnroFv+Lv/yTEel+sbjz6CEKHGB1dRiGRMNYCjcKUJWVaaikN0NBIsn5ep8tZnFhwRKOKXwRAUqbnOOwCVey9noa4v9j+IazUbJByuQdDWc8C4r+Vzg4C7QVMGy5WeD4CwyNwKtks5txQxmjUd+hRksGCN8e1dhWeAZxj3d3btBjgZvsO+Ncyv5crRRgGfXbbA6cEppo6sAYkYpO5a6wyHqDaGj0y6YSYE8IIcpraOvah6EJV7ZPUCDxE3b9e9M8peXi8vblCS7OJXg2ijmNY3xNvZNuR7SeveoHh+KNoNnPgC6g2KYpzHzfNYvOBRFbYnSAoLNz2mBd164WOZhHZsHswYdD3J6uc8SzRsEMuOx3TAoya+HpOJUcp2g/4EDptrh06viWLuvQqRpEghknG7ok8YWUrYQ7skQeCF3UVlV95+sk31F8nwLdEi4d/PqYq72tIZssEAwGcYDPAeYE2oOYh1S9KTRNdwIyKag62B21cMRV7NIeboICYHAX4A8RwnMCXn8q476P4NtcyZmD9h0hbaAUZy6t75/wAv/I0Xc7r8nyNwTL/F30xhnC4Vwqm0M0fOKhA/CCD4t4V0GbXizzuglroNEOT2fIgTv6E/wyaxHv75XYlqMmoN0ews+5DyHu0c7z84feSXri0TEAA1kAoW5gN+YoP48o7iwSITEILJEsDbWLLP1+AaSn5hOmONmAqjfDYLu5p9SgDUEC4cgdIRQmbyPgzKdDRnMjxoX63EW/N3CwyAH9B97yCoRegpjAllZr1YfO09txycqd0YWSHCBoyH4sDmVlSHUS8cPPJsHb3XfAarhB7jmA8m+LE0q25AAHMU1J9VaQHXwyByG5TDsHyT2xEYBtch165e+6+r/qMwjYH1jl4UJQF9zRMAlWGAr/jzd/QHXYFgyV97vwk1NyLFIEP59xPYDQotGFJKwTiVPF26YUAuAx4S77bIgWZGo6N4KlGAud1j0fUT8cYbwj0PV7IuyCOch7zv8m0b/y1/go+g0o2aWbwAOXTNS2zT5jP7/gGbCDscHHaNsJ4Elc2Ro4zXsdubywwoh00L5XvpTf3Q0hQ0mUdMk92EqJkqgxEkdnAW/rr03fFztM4iSYM6OkbCFhaIQIuijRGnRTAvFubOoAkxcXGdJOmbN9ZxHmOvKlfYUDI1N8+6VPG/ToWurDEGVKMK1ItNnAfla8z2ehtu91x8ux0kmvgI0XZ3r17bn7WCueKk7QYt3xBWZ/LKS7JHvIKxqxCk8gL9pDv1bRWOGaV9hZMj+ovkRjtG0hrMFEVuMXJ5m5ep/JZs7pWnyoGG7GnmScy+ieAba6sd3+0vN3riXWlfhMP9u5Y6INBfEf8n9oEkIzUEp9ZUSsZ6+HRnLx0EiAT66+PvAW7imYFndGHd6vuv1pMKAOU7JWBB8oQRWRTLB03gzsruCKx7SFnLkXPK4UN9zvqxDUh5QFHyHgdn9wNB/xgAtNw/ONBA4nD/CjxoSR2SPRkjRlHs+EnZUN9y5RfmzFrNIxkvj0S/SPjVUT5cAQFrMlcy5uDkcUCc6h7ouQyRU/Fgwqk4TTLNtWubrrWvbdG1AEsbw21NI2of53hQv8GI+Qf545e40ZfnyLjSBIHQUlJaQSAkgHW7LUG31eT32ixBr8Xsd1tvcBeBnNdA9n6Qsx94nZtsTnhkPPg4kf8yH5a5WpLpVGvCJRPAN/m8i/UyZ0s6gehdYhWMnDljh1XSlh1vKGCtQvFQoYThM+8iDiCX6Z7QlNTw4VNOyl9tf8H017UBM+0KiLox8DKddpNVOHYWVnJqB8loRwyC8GefeYxIwGXgew59M08HokwaTxeyu3ybnDbXW/hKPLNn/iYr8A1jwiqjvFEnhWk1bGpsQoZA1DWHPyoIjwlBnJa6ugn/Rzte59drYG1dytbFMDgnyoKViFmWZ3bRESbiNjkq41E4bXSxUDqKOeBR3TDcDZG/ZOZC0GMQ6daRjD/4w4TiIYFfjFWm4Py2iKsNNFYsdidm15l4Hb21E16M335K3GIOIKN6zChUKX59dZT9YNdmD4XH/7uJK6hjYT6zwkUiJmxwD/Q7yMqBdAM0WRw92ifgo5EMRBltncCKW4iQV91oQEwNTegQiOJzZK0RYx+qEXVurR38P9qRJ21W+8I9c+1RbR0loJb51S4O670beZsV1QJR/6cgq0IKQr8emr9u6/zMIa5bYDB5q3hAlNHVicy4iQi14ePs+voGdDLH7ZrMroP11SbBpT9LxaqwBc5J930+cc9xkxfkgjAHmqm2BysmSp3uSfJAJeLiFo9hzojbIKVXqdY+WnQjJgyxXZTBm97DjbnGCoU8qivTkJUNOtTQWI+MY9msY5lVVl2VVfLojysSVdiKDKvq+2HCnh0mX/Pzyzs7SQ6sokcCI/1STwrFHvZHxDpjVCGP6HTyaFRhhHUmGNJu0+mOarVmBOhqNte5ajKffkCyxQJuGEcc+KzU5PlzOtLK/MSTOw37dDSRepwG2qMsalwZKJt9jhJsT6VT9Ymw4vkjnmvMZow++T5O/C7nsVsj4azlif4DxmatrFrdWPT5hHET+/v/vjUz/ReW1ejJmvlhGaWQypRzuZyI29Ol8AJHpOz9tm67K8ObXR/8bfvNn3iQFx7gcA6q/yGTaUu4nBS9kaEWRbiNsCj/CZWKlvjKAiVcu8+hwTDBXtx+Gshg+nYnq17qGWy/noLjH/g7ZdNcMdf0ab7KZLMLUmIGa3l64fu1zBEe5jCpbKxStVZWMqXXQ2qS+tsqKlJ1Kaei/uBzZ4Eraq+Y341rvF3yx5Wk5R1PFiDlGtoSLncJQkTgJR1eCkWFfh7f9jCKPlSWjH7o+MVndYVsI4fHQq14esw6ey02hd2CmVucEoq3x80U+NgauS+kaizX+gbkzgqL7vvcai6v9q+rXrvFbX+A3+HfodLb4xaenX5fxrJxwBCTZWOzbYAhV1Mh1kTNZdqPtU0Wp7t/nXui3DADEqA62tA77+Ar8Rl2Vbguigl/rsno0akSKu6yzjkxgUpbIdZEzGZNtEKshuVOs9nkMsnkTpPJ7DQD+lxDTKEQ28MzSdlqcGjqEnA3aA4tNY3MHIWvxHcOD4XaBUbbKCmWsHu/6g+LIUNcoYrodKpoXKGDtQ4Y0v4AQZ9rITsMUHPlbrHIp6J3EzVtlkBo7Dw4GVtqeYrn+C0dMYLK6n+Y6eJOPKgrYzHfkxf8hYc6BWZnp9qSNHr5FR5b6SBCszcrZVKRoELvhoFqxlAlgcKGUvCKuc+GescscrW24jw6ZEdwvQ4J2w0Bp4Paeh8tFEZG6fUpDZ/pH/mTCb4h75bXCAwBK8QaMIEQNMkmwEX/wa4z+qr4H11lFzGYhWz6PAF/LuCeq4vLVFFDmVaoaDXC2rpKey/TYu1nV2P6VqecHl7m4vpGcTFXsldqs3fLkLjN89tAVKiB4jJNxGDQROMyLayBHToItms0/0E62AEcYvRWWEmfurWkgu3Weotp+2gIyVVndiZql6vT9Wv0qfYAafo6N/EB1+gODgjdnh6hzaVwP367we2JNdcGJD9mZtnsiFL5uZ6fFtA+qZLMeVWF6fUQZlGrUbPGgBnHD5lgw7oPQYacSinupYMUioJD/X2m7BkgyQ23RJLcZXckNVoJ3Lvss+wDhrtd6XboNU3pL0tPc0JoQ9AC2+FH+F3hLSoyVlaSOLF/AbhHkjRfa5qsmHfsRs+QwODVk/mZWiiTX57oGIzyo0JBOCCwmAOCsEBsBKrm6nVJNXepIBZL5GxwsbxrArOjcivE8bg2wBzZMa8/bcZnerilyD9Y2d6fGOHJyaH+sUGvNMCiV3BjSEjUQgNJTL7vh3uXy/QOxMZd+OLFTS6CBBEZOxScqgpZME/bcvPA368PnzQtEVQOchlnFD7EI5nN5PzBKNmz6od750mqrfn6v+Q/EcT8PasxMLEiOnq2MeiZon01swFP49MowemBoLlFYo/b+cs6+iMiDVTBcp+htGqBCQTDwERex6Z4Ym1La3LdpoqO9g0ViXWtLYm1G+Nt3vB4BBkMh+GBcUg4MgFBx0dwdNwgAqyuLAVX2XrtHnzMarQDnsCuR40tThUzdh7j/uZDvalxUjQ5BjJWqAVs350fPRHBVkLq8rkWmFJM68rWtpnwZN9qa03jBrhqQoWSGTuG8m67MG9qvNTlHyOH40YOFZ0gcAY1I3OsjRpGi1JCm4vawzonorOgGMTlhFhzItQgpWHz51xrUMUL/RClXvlmzmt0+k4G9RFg8k0w3O8j/8Z31ITi2BLzyMwefCW+Iz8SaRapoBti8sYfi0FXHl20fyM1mo7Xh+iVHQO4WxFOsw3qelrIrKj+2SCqKJLN3BaiC9UeqUgSVACrawvpJ83dtkhV31pLVc0Ga/XYqJqZuIBynwTtnug4kdvTL0fjJhYtQGc5Q2b5HkWF3Ox3GIywXS5KRy6WlhdRWceYjHMiRCsVxxI6p7laCsWBST3yVq12d3Sd6Ydt9y0NiZBB7vaIl2DkbzqpPLUXCwY2Os3uK/hKfFhfaoMjPdDbGdHy4dfc5SP06zZMB4L8DX7+VOJJc7dds/LI6fh2zFAYqPZTPg17/fymS/9METvZfJ2O2cTbiMN4duPoLwCTe77aoWrO4m2YtUMzbXmQHKo3SkXusMSMzbUbMeAGASe+9vYFBn+432RvB84xnCsK3atOQw/s0NZXwmNABzKeXY1CTYiCHG50ckbYuIgnMUaCwN0SOG6XckKU9Gi9n5TFrcLB7GHmKoXFvyEDrKTSW4ABnrFOZoyac3NQPtrvtqpq4o5O0BxeafnvxGS3Xp0MnbsgnPMtWxRjeC1Dd/+Uh7qFNmub1FZhF3L8FmvcvfJwkzeI5ypEVKYyuUIWszNkUks78ayWk0Pa4l8T83Wx6DUmFwZBBPA4Bxorsl07zT12T3DsMqzFPp5dpynvM3Kqf5SbafRzUF9qrMQR7oGMSS2XggxmpW1IpLE28ADPCL67WXlDrb6mVN5Vq+8Ds5m+CV3VeXldimYIr+zf7RgzdNRfO69Gz2ntrZ/w/82Oa/w6KBbuWWqsr5yucidNNOnQ+aMv3p7KqRLZo3jQ5lQc/Ienf6xkvX9kzZV3SijnOcxFU/Fp7UONDBrXZYXpUbOxB3G7x85x1oWoOYs7/gyGuoS2UAukTmhkPFxyaIrFO2IkNrp4sOm7TI7subsYU7VUF7cW2mHf12JyfjGFTqbADNBR+wXMj8ktysqYpZ1pjKwxUzN6OBST7vUzxrBZz70m/dYpd0bGQz18g7lV7MDN8Pcddar+c0i5JW7kHpCTlG0Gh6GuzjHIgp3TuK0ua6fbrhl/o2b8f4M7AroxJh/eNE3rdw1I3TEbtxzpHIgIjd4sb+Z/W9okJ3NHymo18foxuy2d0aXCUUHraL+O09pXP7iZR151RbJvuaEyPEMSrHDQhX6lj7vsg1ubuEYEs36F3xsRn0yjvyO47b8pfUpjmq2CwtRVwGRDuGrMVntb8w5bw4S0lOKb4mGY0hwkmJoqC8WGlFjCbO7HsiH5el9Pyezq/7ayVoi2th43y5TcWdpeWtJaSmgtGekk4LIdlyr8KqJ6pAqXWiP+NxTFjtpQzCxO4HvinGE+wGfkvHuADkc0Kt2P0yJ8aCcplstVMpa4tEd3SqXcZ9CfUipOa1Z1xUxKOoasBvWlieqGlHIztjvrxEnFOKtE5vgVLaIZewzSwKwRqvbFjB+kiHbdwjA/MCFrq/jJpBdBH8pHeu0w2jLOjPuWmP7OHLVLc+FMW7pqZDjYztfqkwKNSyXXxBQzJgMD8lHNnj9OYBSkxaTXxpOGXrrZNo5V5zA2oEpGdDvG9k/lqqQer6KKpDS3cxCnlrX31XF6928fFocYzM3S8pd+Wu7leDOCVjqV8DOmaW+mAXGrulY/ysuajs6zqvsffRmQ1BkcgcQcWaW/mSumWA5ymd6raFXZNW/Zcgq9QaPaBhJmuYo/ouhbzPFkvUkFUk7+u4jvS7Mf45nRX+PE0p0N/rIWosInMwhD1PXwbo6kUChSM1sgxsYGZBCE08vNFd1eqdEwX8jed+O6nKWKWOFhVaO/n7A7PZs5HviTuslzhE4hEYDv7lOsaLRHhDjHyz0pBPsyThPGqJjCAI1Oy67R/Vv+0yHw8BGz5ranVfTkiX0Y8flWSGHUa0+qIrPvbSqxsJznl5uUmJsrUW3GaJNFpipPOismR+I+zOl1mR2pWLSgoGjxd8IVzhy3Tspdxxf+CEi3Ez4jEe8TiPeJpDOAnJGsNP8548+ZZsma/34YejbB/GzohwnAwqyV+EpArfvlVVAIXwFtT/wzTeZyT5PlAbo/P9wFJVI7oJ9bLMtkOL5cFgD+wa3zq9KvjPcBtN8NsEUs6NKDzmmYhRQilgXmrwox8x595Pv/q9wtuONY2EwYSad1vxZeQ6YeAJ5tVuKGSBYzROyIR4gs2l6Q5yyfvd1Hz7/8a0Qxl7Nw1S0PRWQKG4CPQkb/ICiq1Xp8zTYDVIW6cz54ax6TsVIuaCeBu4CPdSqk9AybhjM8QJvds/z8SS+1Ah9rEE4oROzCslmVL5FpvLjE562TAsNr4FWxapGQFsL7N3w4f+TItwgU36VV4yvp4idMUu6Bh94LT3oLy2DCB8EC6iY2c0Qfa2TVCnreSHEhG/imEAWcXL20uK+gDJmluvzyyRzWCLoimP+idqPszqa8/Fi16IPSEdXb8wc4fHxZHWtrqxk3Z8+6weiWpXhVwsNhoG/ChZzmCVPyuj1Fpu6pnT9xaU/JWS2xCRE9bNZaki7gj0vrypkeIbeS3sBQi6LRpOsnNOAfocvp0wnLgTNZzi4qFRPwN6ymXoSU+C4UPBeGKQUy/DpQOW2GwsvG1bUKqKkSsJ6IxWnIUE0h4GG7lj3sWwJkMMaoShrT8I51PjY5nwOYzoZrPwjzK5QmZSpm6WCawqvNtIxefPepfCFn27YUOeey/kfjIRbpBY2xoz8b5Wx6TWGD1RzaxqlvvXPaHXm3tUqtuB61QDlw7gpcCSguVRZXlJRWFJc0Pz9Qd2fntMbrU/oWagtVnxpKIOuaR/nXzcRjoSbYqkKNJmjOQholGSsPGCHNp1oVrNMVjZkKFybVGrW7gq+B4kK1R2OAQ6eu+yqsJke8T+Ydtbup5uSUwdiJda0dtk56A11ph9AsD1BAi9af3xFYN2WgRgKkShkrPW/HJtTqtLaoWV1N66z1jlwM9lhdGp5TDndaXqHNfv6AcLqMeIZAPEMk7QcKVUue101AYCV3pX8lIEbwASs8OhSC+4wYD/dbfRZydH/ug9GmhohQ0WgziFgBXGTG0w72Vm9uTLsnj0FRKBnffpNs0CVr1XZhiEwpaNi6eg37pUK4qjY3SPfS+PYAbNA4TcBEpsy3hr11dUEDJUQW2urUuqTBAIWTEggdg7onpxurNx/oLbVqnCaNIQjb+F4aPTdYVQt4u3+N+uFjsTSgkDeFW1NDuI+v8xpWl0Wkz/CfWxzszGVquSrh7lORhSdkSh2oZ/SzmHF22Q+ReRagMjdQeun9Cs+DN6LOc7e5Vt+IkS5HazLwYBJiFnrVBgivldj0dTxzyKoV+ZymhQ+SQbglz7nwvsZjM0BBk07j8znjfi/wZ64mylW5NXVTEEMj9/Wja6q4Tyv8IbXKGeOqVWGuyqXRmuOPyuv5+5c2xfj7mjgIT612xniJP9xVnvcNTrH6R5EQVmNTwG+JVDGsUDHE6PQ7GAqEVlRsYYMXOeSLu5a+JtBFza7gOA82PbX604s/SAqD7/LeWDEEy1vDFq2gj1L23uwV7RxD2Os0VWMkGKDNXf3wvWfSwtAN3tntQ159TVKqlAd4GjcyCkHdPkgf8sPSgEyRsuPuzjE62DNo905qUBhCU3BQEKBSq4CGrKO+Rh8OnJGdy0Dl2ETP+PULVuYOc/dl7o3UrmrrGjw81nL0P4BA3uSPAS4HXIED6xwUOOmlH9mxcDpmI1Z4czbkouVjOsy/3gLstv4x8im0sXFS4xLx8uB8c5tUCt068h5bMhmK0usxusDrTwKFUzDX/JembFGhv6UGzjzu6gXYhceLQDuKG3nIG9foWo9QMl5vQ71WlTgUkhss9UZhZpvNTT5BKz3BpzLKF5SV/0stfwDsTzM6saA58Pczr/tpvKXd7iafoKMjWtdQxMWscpw1E5vOgqkshVAjADKKiaeh08Dsvlj0e+j7WBTr6erpxEZ1j+p29nT0dAGH/jCYdAadzjwdpA9iBoOeQf+ZiclQ1jv6LhmzpkT/Ow1TUf9W0gIGZCSbTjwnYGyVltA2ZvuIi9yASmRlTX8PnW4S3KaaQ582iwYkRe9/2Z7lBZeZRmR245AEvZfVFjF53L2sRZRyWYWJimpvG5DE4SqlhXz3WOd68WMFb9JsvotixqSwdlZo/+9QAXquUhMXPC2uNZ46bro5K/aCYJTa3vBz3yuvvXMtvIu62/H9ebYsI0+h96bEpNiWaLU08Jx1y3LpK/T+PDAsvflKiXNq8VUltM4cnIAyH0Kav3IczRpmCyxjzHXaI0YXDJkxDBLwQ0zOuYHbnx2CZQEVF38eZtz+q+E0g/Exg/71n+notZ9hzsTRNqeyZsKtfLyICUABzY60q8qEQpL8jGtEYaVkgfojIsVBBd9ncS/xYIVWFU2prIZqiT4mJNOH14IcbZtD0Mx3E+ttKZjlvS/RDWRxy81JNzffpdZ5Oh9sS00h6ppeYqs8zHxdRfxbUpM6lEXq8skp0NkMnSJvUNGlK5MdFqoXF/EA20Kd2rlBAlll7KTMxQpKBbiDL741pD0FqwP4rJiFtNzWkue8h07PrtE9XpRWqLpRKgwV86TIJuUY/zDnfJ6hVkE8B1C7qraOLtCkbUGfV78ySd2QVm1x7f3lpL1dxLtFrLMibtDKT7SKZ+7zSv0z84Rz/+XyQxTx3k9QZxBoTymySSSgPmt3NZbadnJlq7f8athpnMVaLJ0c1Amx3rncZvDkvMHpYYEvKcqPAXvDOZ6sUEhOI2Si6vbmE++jM4DwjFs/zX8PnZ75cnasPaJu/1FAY1irbf54/UJltHIFVNkeqpiMsI9ZtVZft8iDdfKsboh3Z9Z3qQ1/ZMs8PC4+niF3yUREaHSLe+Fc9zqn0qXUwXGWUplk611v/E54l0S8kfO6Fl7MRc9txO8BAjf/3SWTFrN8tUE/yblFnTCM1WUJ3bMF4R5u5zuriSPwy69maMMy7efacue391l6RCvXIHqd+1ZMcWETeevHM1aWM/LLyv7ObSB8ZjZNJN5oc20hei9Z5Kj0mlxJB44HZ86J5kfeV57kGmDEkDNsjDAq8yYbV6jT1Ss1qWa/cEkHSstyMCDM1cfFsNFczKVT7S3E0II3MXFxBet88AwCQcgZZ1b4LI/xO5P5O4NOYjHLAH5MjrPVLl2p8gNZUmlHWxdZRykIFCnrrpYoeusQbsYDf4lNHg4FZD2oAJqdJD6BdeHoEEsqC6Ok0qndw/59RvS5WvO5SPSDWvMDYBFT43y5S12syBZXqLFAy1RDyDtLcSGzEjfhjbf8WDNba6kX6r0qJifR62crNF3tp5a7Q3ypckAmG6dQzJHJBoA8BR9jHVGXYT/JqiDM2zRdH/dPVR8Zwt6cp1r4pOSf/rXSepDRwXtw0+Ns4uhN9VyTG4JPy1xVjIFMj18ns7DYQYXFKnl3WdjNVWZ/pHG2Clcmi8G/1Cqv2WzxWtQat8VMhE+6bc18s1fv7L4v5rSQvz0YjPO7w4o12Azwonhdyl2qrIK7MG/TTH2yZp410OmWUNFOhJ2NMjUGf5MYQ5pEeq+KkeDW+dkqvCHhcdencKtqnFQ6Tqm8OW4BuxXQehF09REKo86iZ6tFD9Go1hKOzpXErKPJlWoI15dOWO0h3GGoEbgLtJvb6X9KGQ/OvZSyOPGqMML9N8twRyK5ouVGWE92hrmTN8lguVL5kVr1kUKJKLo7qKnfV2+h06kk0sjwzZ4qYZNfXTJ8DaAdC1Z5ffTOhLPBk2xYoU5XrdKkWvz8rWmUnuWg6zB3H0ekbqG6EMEpepugiovlfdKimzK13V7hsn6uuhI4xRikczq4nALv26XtAVTlabV7mpaYumSc+L8E1v8K5REWqaZYK+a7uKy/nDyjycuTgKzrEaDFXukR0aDKZSGWRLb6roi+1EaHF8BjJOx9SCKu6O22MvL/QMsG5dg0X1dLF2IByXT6byyLHWaUMmgArbz06MmDpaqrOv/HX/ussMsYOssUIZrGbR2r1+3qC3QHp8TG9Y33u4VWkOERI3YEnE6lyhkFU5cvf/tgMenCmdOlX2cA5jG8LukulmeLK5VOrHlQj6+JpzOjuBSPFXvGx9P1zTUe88ReHzNhMlIStyhBm2D8CJoVzcvd4ZnpND5zhadp8fTgM6sqLVrmbsT8PQZLixOzNHXr/cE+vXVZuKzNvXozibNJ/BwGlCbwbpOx3ugJ1D96n6lLoEFksvxYZhI34a23nM40KFcMcIoiP5XCj4jrDGS0xj7ZS3bV9jrtpmas9xrLlUddFfP4VKtZfL8Y8CvUSa7Orc2nKyxVFhfeOF9bmV6hT7UHxTT3MYSTjrHMLl8v12rr5CAuHffu6oKg8s9at1eBWQyaX0QcV3A6kfa8jITw+S2fcWUKV0wINPKFcqW0Tky94SpduYeENQXCkRo/Jn6SOTCvsY2YzZY4dZiogVqndc/FzfiwBmQFFGgZmwjppTi46P7gsN8B6TIsifFe0dRo/DZXXVmtHCakdHQjDEIVdD2D0e+raB/X6THQE+tuaMbkY2YqS6EhKdhz/GV4dmr6+4BqQqTLqK1UwxVdSca0uV8KDTcnTPORsJACiuNxdCKUsxQ34cMS+dPlQHeVclGRtg5Cfa1zTdXmUfSkWZs080luKwb+QqJJtf5WRdDVJIV8Mh7zFtYtcxJf+VkW/Hl4LhThWWeyfykjPQQ5K4BJCbpqvt6rzc4ecg+6/M1ToVB4mupIZmqSO6zpvl7FqT3cyR+zeH46bDDtueXHWtg6qI5tceq9sFoQ7mbNUcLwABdBrj/lOtipVjtcOsUfRnxfJD6bCdIoNCpIn8nlzgDcZrrTrkkBU7PeaG+dA3clFxljnQH+qDTGzKIzIYu/XYTGmpVyn5DRxnlRAdn470p95Lldngx0facMkUgwmaJZImkEYomtXTXevBEaZbUaCzeu1rVN2oslxgWr/NFk2/PeRaf4AbHL1zBPU+sbzbe7NHS9e6P7wKrH9BBLi7kDClRw8hBHvVxU3rZpyfnfNAgHaewZzXCPBQpU84DXE3jThMqDiLZJZ7I2D9nq/TPUFzKrdrUTY8jZCmqdVRK5SyLgYoY1E7Su3EMdBRPitzIY6nKKHVimsFSKlV4lfX72Ef4LJuEslfIFmWEMCl4wvHwLUjfRGAvO0zzMrMVNeHa8tlP6yn4parHpOw3PXv7I72xma631Ar1TrtmQTItYc1+FEIeTqkR5xNyhgTzxhsWaCmSQ2WA1VNsgacvGaOObvUuGqWrVdk9inNSNdAnsXo1xcY/P7UzJyrjLJSk+kX1BnFBg4cZVutbJ27aDqfbnfYv3HspPw0go+587z8RMGaJznHe9yf2WUPaf4DXXa9yXyZSAkVUY2jHgtL8sSSi9lQ0rVanKVerKZr9oaxqjZ8JMvds1mu1wjOEMHaTXjczBsLERE1LQvXUxshh2G1ZTsqygcFpJ8ZjCghmAeTRcF4YJyBMZwlc7sXflBbooGrDPkWZ7G/O0+WOPs56tUj0FszI+gPOf/ZZ78Pz5B2zpoSofUxWuxxGkIRw0KXtFwl5Vl14o6tWWanognRtNTlVDn6IJUCyWNQ17ba9y/M/jrM1eWA06U+zxC28GJnzNnfIxi4WWXdnw6pdHgAmnnjity+wNJrO9olfpcU1XfpiZxlHhG5ZTO3GcecXramSr1RHmM7FQ4b46aRTQf6il2pZ9fA0S0VuDqZnKqKWHmjJo4yYh1bsEZm6zGJzubrbZ2Mx8V0pZtqKp5vg7pSUUWhsfujLg+duT5bIWUIq+XBdIlAHWCfFGh431/L6xxqRVNL75wMePiMPL05MVgfzrFHKOkMGeN04eL/3dRSggE99WyTqouWwDWnidrGlQhBNRlYCmS7/tGz7ARisYb+FZ6JeB4tLlqsjw4dESEcpRi/1la6EBxQjQkiHIZXR8sPNuFMPWazYQcP57Y5c1fz7ricocO0GEcHnla7M1MLB4juY6BN3TmB+v1Ws+Ux807mFOJ5OWM/cYs7AtCupNOniLSnnEYDwCHGWKAL+k75hXreSkbho0ayXSdRr1XulI8qqveGintxKcf2Z9HmE/pdzUYWwxvqdf8hKtiEIpoNEKKJQioLl/28hGlL96mS3/PsRSSOOMz8VrhnH36B/HmSqPUskerlgK/X8K5QWd/qIL+n/g0O45zlYrY+CbEjpBG4/cLyrNnLFibLmQJS2U7/jq59GkycTiPaQZz6JqndqvkpW+sfFVMPubMI2yp5RwqpwnBy4viEXmrz8rkTnlco1TK8sd9ptHgLT6wta9Wg5nAchayOVOBHNzVHKjT6MkAt+F3JvSI6YvodNNZeQd+xcu4ogEHJ5QSPz1dyT55CW2kh5hKpRRUAOrKE+PkfwcpVehVvvkipItbyzgfYz1s5w0GpcJZIyiWbezdW2OmKaS2iYu7qz+/40flljNQRG/ZPjV+SQplOKWjs5icmk0J1hGHCdRN1DqaOSfWaxMMq33QTFwbd7iohJWQYHqXKmqoEBZUrS48Vsgr9zud5tlIlypXPAtKLonLIUmjibbDG6jukx+wniUUkc2VLALXVthQC4TzxeV9Jn9ajU7+SGhgUfkJvjWuPC2hY/Lc51dntT5QXpMJP5GprXMdwyV8bu23U/TSPKJSxzF8wBTLAxQT5cYXzOangQFEplboeB+OF5VWo9pvNAaqqv0+usrg6GaSr+3tjKghr7XaO5BOtimVQsTp64rToXTVB9rsKR5alRGsWXOf/PzUgVuwHyYWVD6ZeHNdwbAv28jI9vsqkot4vTqDHpERJ1RyKfON6eVV0/tGZE7nQFmU8ov0cs7gLLxyjzZ2FLeAinbTT3MM7YYvx3uEnLpV0tGmHNyCYPCh7d+VWXWJn7TlRjcYrHgqYyLUDcMiljyCg6b+jtBBnwpgJs8VYHF+sYs2yTIUfrTkulM1XyFsqOlj3KcTr9EoXzIoH8FpJfrzahGa3EZFJjm2DFUozKa3Rq1CdOrnNr3zzm17ePpBhaL3D2JzKLHw1wWedKQkMU00JkVgMJ1xCjrBYVztdogRypPcUy6GpYRVpG+vZCz+EYpOB8m8q0VCgVnQ9lNbbqvlEQiMYlRQI7zjp0leAJBmMq4p+KHwY9+9Ggxsq9UaRB2Dkug9P4C1JVzntMhS32PzU/g/EQwfp07QuZnW+ZkMN4jlt3TObcoeGMKtQvddKHaq1Nl8zbMDlGW0nk+ESmtb30mgc9PPKQM/wbqcZYittI4+0HWAQ7NegF5Zvl7S5uJZc2lBGNxiR449UQxVXjlClcpizDk6jgIqdo/ynIWny1R+JR6rUeuYN46jCpXScbrMya+Tv2snHyPSvuXXP4PUBbWKyvrIV9dX9IPpkUm75RAq7uFaYk63Hq3iIMKtQafDlkznCz4hM2dv6xhUb5QTPwurGk0Y3a7zivjBgCJk53/NPD7VOjm4pKKUnX5zDLDNznDmJUdX2DcF2U0Eab+mllfTq5nk7cRbgLAeVQQLS6rf7xTL74TZCrkSeYXNEOLASrHNU6dqjQSsh0eTiwE+5PUIIPnFpdVHc39ClR6JGLOWrqa/Ayw3Y66e/FjwNS87lcLgmyHNmiwLH7rBE3m0k0Ka+fty7Uay8u9oeF7jHuoLRRDmpXnAaL0TMJtfQEkNi+8sut2LqE7bASq3B4xX7lewiTxiNM+n24gGjKS9INEuxkBdverVwnzJQ4dkbXUmJ2jCTewwIxxH9HYfDqB8P5dtXqWQDirnPaCWPYPjfpPGfGFkPh5ZRpt/M77/ddAsmM11u+O8H5bLLAmuID3vw9SinccyAJG9NOdLXNKOnmmNAqLw/Q3SYaO5Wcbq8/IDz4PSyQSRCxUPPc7Ad/VLiw/Jh3HVqW9qVRX0EEe8cHtzWeK5CGNHT4H0hubMvczusPFpdsJVHtMtVlV0kUv2HH5bd1OIDVrJZ6sFlP8iXQdZ2R6bGC4uklLdDyVqjt/YJmfdXwStPMeegokXRu30/76B46KzkuxVdQgQ8DHO04DOtOerJz8alvyuvt34Kdpf6xaRO3JG7b6jpNgNDjGUJOGro8KyU/us7mFmxYnS3zh1AxRsGqsUheUyQYy3SUoZwkAfFALvQp+HusWmdUjisltvo7Vjj7/TFYLbGrCyton/TVRgyUm7g5MbK9lFWeWqn6IuQ9T48SyZiplBom0EviqlGA02PsoSWjwUsHIV0AKWfqVZ1/aNsxY1VXm6KgBi/+eHk0x7nY8/lJe4cyX25TJPeBK03hm1PSRfWxWZoYqqHxrGHkxgfSESCXQ1Rb816asHaIiYPpls4pVhPIQPWcE2j2yzepSlYwbk5cfRPD64wAtlbJF2K6vTlzDGBXpOPy9ICZ5OGOvW+ZeSDngGNBsnCrZcfOOIRb2jTYwX/NlZg0+F/9m2DBmZfuX1imAGFWr2fl3LOarJ4uVykZkTwsKVXXHbBsIN5Jl3E8OaypN8xLRMOvUl4B058CckjRPeeMvG64McaNz+/FY/VUEgthLrAnAnaR9pONaT0ZDzJuFFc1UfGjNXJx9Ja1B2b+zBArvL8IpjO+U+2eFmQuz2jYsNGr9Tq6rrZL8Q4aWdaHXiB53tgkpe3FPNcoWyM1xl4BPtSjgb475S0GiNKHF3q0gqV9x2Lhvfzg3Q+VBN5/KtnUKzQt3SOITmWAlxvf4WAo1zjtFrhHdW/XRbEILtCgVswvOjB5t6YmMrrbPnn+fhD4Gzj2WkZkFwIMopd6N5o/Yoag2hWK9yy21+hRB+/10qs6GajQ2p05vwTSF9Pc9xYrxs9oSNviQEdqwXwe9PtEs3f0t+w5+3ysW++4Fs8KPSqADB6JLma/RqCcZjKtU6tW2SvImYVSliQk2vUxeKJqgGqmym57e3z/VY77qSQq/YSzl9twrrWS1uQmc+UoB8asCPuded9IUe+UsJW2jUG8Qifeo1PeBgVyLsyZB09cERzsM9Y3wEIhVGkbrBBr6lcHDIvRHjbB2bh8SPVMkeAIB3SSa03n/RagFqU1UILUW14v7XypY8PNMqD0/gjSTkQ6ya4zGmseg1WiQs9kyoykgNbK6JEVQHRhbHTwIwpUrbc8yR+NRmVKdwDjBe34JBfvEqKaOHFDKvGqWnlTkcj0odMKzLplA6pf778EXCqYzg+eJuH8A6YABakGtyGY0UnKjefwUrdIt5XtlOTm3lI0GX2g0csugjbYRDX9Ck6CGFsPb03tUd7isN2XFf4bwLpEF61TZEgZbVIx7rtK5TlVSJsqXcqdCpbDWWnYf7N+5Vlddkqb/S1YL4R88atDJKikVheQurOSABsIzM9Ymhsv9vMBtQ+uSCbTe5i54jtlBmcnIYNfC5RlbxGHbjtjA31GrKxogsqs9Na50yzp9LTKZ0WyxVFq5Szvd9Kx6uuRBSFxfpvENCJ0ejbaa7Hb/mu2yoTG/H43ZXNm/YhasUVHCZkcVitgztkYh53DYaoUKvqnTRRLL65Wo5jw0iYyYwfPc+5i2g/Qw4ZA7Ix4hyJY5gdHl3pDbzFlc5cmKeVyMzoSzbpiNX8rYUgH+lntCtiIqlTmkBMLWOeV2awVsfV912IMITtiOlteX00+LOIWurZHFs0Xfikqd2QoVD67eWegYHIlw1w6IR1LqyMb4M2sEcgUN2DX9GUmPx3o3KuhhvyAxR532qDySb8pLBRfZ5Dwz/7oRuyFXcmDrrg+DHMIBNgpwv9cw6jQlPmYR/CdKWvMe1T2I93d3uh0CGYM+govY3aCQwfiFVTh65rZ3jhC0n+kEoWfPavkWxGeLX3i2LZxPxgsjkD6isVhdBuH7+9/5gQuZgqhLfIFO3s2dM+nH/zRDh7U+A+UyZwJI5GcByxtsNpdKkt78f+JXlDHGnF5xgbE8XOXxNYGqNOCl3AcDfJ4mRvo/u7bu0e1nnWfo5Z+KeGT6MNB4410S7bcDLnKoGmGWwH8ipEkq3/TwqNYee+vKzFxe2SCyYgUuPDSDfbQn/1sFP1UUZV79+ZBzL4e9/smT/a33bwPKCl2L+G7p0wwi9yx6VDqP9mijm4zXsD01Aat3vBjJU1sxi9an+eEHn0ZrdqAarcNl03jUn7/nVH2ZgbwxnX2kh/GPTi6/5Ik2PP7jLuW3CP/QU2xe+6KN7VyweSyX275wUTuXnaIzWoFBpmqqDR3lFhCC2DN1WKvZjy5tWPK3079SiwIzOEIh/s1O0cQ7PIE6VV7wU3x05yiNi85mnRYRVmcJqsqynovLyo0C3lVqrqpqs5zKmp09+UUvFdJ/abPk2xOP7im9tGUtLjrcYYbX9SvE8aAjsdT8CTBTnsYHyv3LKhvVtSt59aD2xZsl0HVVNv99bVDnTif9gaqk21lR4cqSA19j/Xet+oxKuU+t+VSleBdwyKXglcdB48ue+XQ/tBvDfrePW0nkjEvgUQtzCxaVU/yMRp9R+86x5gfSVgrtBrHsBpXyPtAxfJf38yifzy0YevCxPW5SdUu4EkRD6snjp0dJM41YPNRtMtSb3I0TJQuqQCOOoVEdfrJPpxL6KZ/fQKeNb4S9CCNM3PYUsW0OQX2SSNua+abs5z4fW6RHDdT55krl1dGRka02VSWklaDWgua24O6PwtzlNLCMUv4RndwBlCRCyTEZfnm/mStlcF/flKoGFWGLv2Wwu5rVc4WW2Qhkda9dLMjXYncyEZL9RyP9BdLvlvf9Gt5YJtPq5IXT/huVzmOZ//yvHY3MNGgzXGDhc9SdaAGf9De+HIxVDn6gp2gP1tuooE3THI7mZnYZA3eq0Zoc5LG12x6pGrvV2hJezB8VsI8O6Llt+P+NOcwdEDRCiK42bR1Nt3imSkNpl79xyNJ68sfV+l6LQRWNyrXqfziUNeKSP37ziw4SM+mMLirnZjlxNvgFS37XpHfqVTLk/t13+IYaH/B9Q4D5rk9ffLxBY6vqlamnQJ37D1G3orRdnv/CXAezOlEdmXAxBLM/VOGyF1zunFffOi3aSCXvE3Bv0/Kjm6vSeQzXOxoZoix27wlqkx+YbwuO3/3JRujGx4SR70h58UKcceIuFsJIG4dYwLOh1d/GNGRH+noV5tKwJNHTgQnatLWfXjCiBHeFxVHV/yGj25TkwZN2UfYwrHA/A/tj3urr2iUm0Z2Rtor/hysTMxr+fkgj0nWPjeJb7dUr2ZDaafirKYh2xAmGr4fHet3FgLScER0G3J7CWIyYML8lJ2e8pclst9S3I/PYgdBCTpfT2owowPSlv0eWY1yV2pdQ91Cs4XnSeNzGpsPXbnzNfW7k+LjcAhaYyxu0TwBPsxmJwziMZ0e2MsH8M59N5tt63Emu+udNdescYd36ku+7QblTJo9v0doQnpmi3yO7fFqE+Ss3XaCznqbvQTOQLZeJnp5tSIu8ffWFzJwxs2A+Iys1+gtgLTM0u6c6L68pOBqxNXbB80B/bKNwUtAzJmAStz2pm/hicDtD1WyG7bUdtqlMxNRJjitVXrVt9KGq62EHq5KP1cUaIynd98Zy2YKjWsgkZUybPOvid0TKVBpVzXYb41p5uX3YsB7H+PYFXfgO7bl4Zkp2vXww55P4tnwBauv/0LDmguly4JPdydox3l6lz6ftx00CXAonOhN0PtfRidPcBFdEKbf70YLx7nIxz0u8/Kdcb4AmoQyBOge/PnQ+la8WHo2+NSLVclVIZfI34zQ0ldjzmcsavml1itU45s0/9vrZEjPpHk26SEhrL8/GV+KZ7jEXWGIv475y2LBjQFMyZ7lAPlSoqYMQVIqTabWs4ryy4F1tj8IlZmTjV0Xib2DMXz1J6TP0U2/PudJGUpsbwOnH832Vsi4hVoKgDCvbSqG9WUa8/l0AAQZmJPe+KKLd+nkvWrUfXGmai70OfewYyOBOz9OFDe9kMo4SSC+orFqu2lI1eBIrg6R2cNGQniJ2R6pbjWSrCb2Zs8Lz1DMwdYmuzMby/rm1TtcIznCmyn71KxxBUs/SfheCr006Mg3mOLlMVRw9zGNf/mdHz80xRPnSsbYmKzpJdxjM7Z6Ua78hf6NfxEMFWVk/tpcJC4op9PJymCF0V6L8Xl5UGUz3rbVWI5PZzdmE1aHMmMbTL8OiRj4L/kiNZPwDR/LGiZxsPl9LKQK3L2tv7JrvuIesv79CN3TgB1TIFh468BV7Nn0BAq7qQaNlNSvRUEJW/b9/UXPLiejpe/KMmq7Z9M0P61RepQk8S2CjLQKlWNfNt3ZT53XspgTOCv5MGH3OTyVlO35mBR/l5CCN6E2AHfB9Yp/lw4k2hPJg3g0DmMfoa8SmmGU4yX/VdRwirctQJjBzJG3fBUHbZ2xBghE0Jr86FrOk1RZ3pbhyPqzyRyJtBS6UazwQopUi6hy11qccNmzIPdHpa5ymiwanqo6mmxWGUqOuvTvUzvrI53MJ6i8DPlglDHWBc8J2p5hV589iAlDzCkoZmf0dS9SeLHXOClxtUe8vuXMofMP+6+SI/B2S7MCwl4ED3fpHmK6LJAKhzwvMSMoX9rDXwH5p4Rmc/dPK8toYH5YDi/KMFxiYx18dxf5W3eW3H6Hi5Qq5a9OEhtwWmTgU7tvwDyj6TkSAsuVqPtKVOXkeevA0+hWyueJoISOO9zSG0h3wMA1ezt6sLxoe5FpcUWedhfmEv8WZxmn6cvRhrmQEmBAJK0AwIRQmgJ8ggzfkK6QbKEkp0LIaKqiPJ6b5P8iJ8UdWgbS7bF/porE4cyIN0/ERE326XL6UTtvapVn+hLagaPSlyun9lZ6kU5q+ipl6YKd79Dy0MTurTSfzHGfhle0mmZP/Db7Cp+V+2yrUEj/MLI22Qaq4SsbDJe2jTP/koQ2EUQ1XM9hpKq1CdBzM5vGGgWVkACA3lPOI1120FknQez+9G9SFx7N7i0LcbPZLKlYZr6kyd+iZLXKTrotJisNi9MTRl64TmOTQYH2f34BzsusjdiP75EydSmbwoNMZO7iul/7kYJiJL2oXKT/dvXTb9h+HjpVuz0hNk2118PydxTtn6pVSvVczlbGzizJQgJ5zdlG2/1JW7ETNfGG7iPRP7Yml01/+y9HHheOzOMsEIuhDeY3abG+aYqtPzdUfz2zE9fjn3yYkSnC1gaVaMIDSZw+l3JLDxYni0tUlZW9SGfRfaBy5NMKUSyK0a+CnuK+ba3HXShRuCfjGa4OT9J7hm1oKBiKXMhmgGckb+2ESShGAIl1i2R9oTiDP2eTa9LWDRnqeaxtatLMQZ2dlrBDH0aHvaZWqsmr1a8awEXjszdJWRiDy6to1WIzddXRhbbrb8vgfAKBINnH5ScgPEuA/JQDFlmlQwUcsF/hJbztrdruoQo7IDQtmTpMFjh97+CrPTaN6T2nvCLBali7xna6zwaNSzXdS28Ko+79/2rPXC6opZHlxVmZ2ZkYGgJiddfG90tL3LmZlZ2QAJLNLUaMTV2v/EGFqNZvxCeKAXCTxZj8DlG8/pAhGPVvg+mYYCmsy1c4MfwBEITxEeSpmqRMh7k7TnD+GaVQ6S7NfMTym5yqlw4fwy272G51sSveV0cM7ITY3NwXZ1mWx1ALryjD7RwF47nAdjpDiT+UoX+VyXlMVmRDxxj+redy3aL2ylyQJM2MelnUBznv2a+6B2O5zZM/THppie/ar2xfl+3k8R3nSkTm6ri4YKtcfHhkz1xoLr3hrCpg0ShHE+qfOq7c0Xpf0/HR+Q0LxEm2ztbdSEpg1UrQWpamyTrjplUe+bEHw34TUh3TwEdxY61rz1TyH2gjSkHkOuJrrUNawj3CB0qnKzq5HScEHo/kgaZQG/svFfMrFvll/NJ3KykaMm/janzv6noPq2XJK64kViHrNAksGiPBqbnH5CMavA1mzf3rkeia2NZCUAQ1nlmw5VFQo1bnUGZNyQ7dbn1ZtkS+Y99KDIa6aYL55g332Aa6qt7OIqcaBXs9YMe9yhzPD+JrR/CQkkDCcw1lceHTWPVLpXsj15aJ82d7k7jJjJV/r3bZSuZgW9M1+2c0mJ3yt9UMm3vJe96yNxn9fkl5IoRTSaaMeMudqq/Gl/8Wln/mBDjd4aypDodpK77Ds4VhatcV78OXzOS5cqUU0Y59HQ7jTnrn+Cnz7GpG9Auj8eQHI99rqZYakg1kFp/g6T4O7tC6E/oVbLP8qFvtm/wH+V6HvvukdzXCFo8GnDPm/3XqF8BJIXtzz4JxsaN2QHPFezptdumHZYCoVT3zoX+Vi39LMAHwNlmAPLPrT5B38O8vHOrn+5IdLN9a3Jnb1t9Hwz/tviMbZALI2cmjBCyZZQufcjjBmIiBmSX9vv3zotJgmyUtVQ5bzSFr6eOhrW23mx0uf2hXAH+Xh+dO3NTeLjsP/Q/SzOObJmX15hNch/ze9ry9X+PsIxD3poziinP7Q4lBG3qmdv+vD7F+1w+VT+tQAeHm5G/R2puLP+ny6oj8O5aXdfbELZ7ShsRtyKR5xtG36MlWuJGUhvPAx6ZHkHnCFaS7SMLOZ0Ab5D0wcnndq58/6nRk/2jzE9SJVN+dRvkajKd9d3zfVityUYOiVQl0jk8Rw2ygn6/rhHfu8HqUXNKV8UbLMeP/AC4XMPmSmJNRBP7f2+ms7jvLP0+Xq1/B94txURgM1AUUcxujqP1YaNw1QguLSrDiYk4a3tyT2UyVEUVoB8HFHWj7G5rcHibdH0tVdHJ2MwvTZlIsLNdVc/KZJ17QRL5xpq6qOL80RZc2YEsg+B0pteJSb3tSpIF14Vkn31lIupnCO+joEvaFcKG6ptg7rhzS+hYbCC/tfhDZfER807GEur26vboveaWvncutWUR4ymbeolF8ZjF+B/rzmIU/D2ZcXB15v45wwHEXziEGdw2eG9373LX4/XXRPoDd4I7hKrWrHOmecYIzZY7EEu1AKoLxMG/Yvm033/YVA/IfKb12dUY2xhhmOAaerrtqFzm+l0CJJc8R1r6IL+3JiD+P4/i5vq/zv2hRP0jrkrpN8V+9h4xsWA+Rqd8bUEGo/zU0H7dV5THKafKGM64W3uA9cnOma21/IoG27SBKLUMGdqSgoNJwWi7sgTnpMBV6efWAt4S6dPukKvJdM2WfpPuoMV5SBlHUsgZMya7uXTnuaVvI4C1fe8pQLzWEdpIwYE5kCoOv987W6sNk6s9ffVVlw9cwPGVPlLrdMQQmQ7Pq5GEqiD9ZMDUxqwyh+ltmAFkBwKejJY6YIS+umEsXuqDFqDpfVW+sf3xQniwXAo6yKKhbUcvJOkwozHE1RT41/XKO9hAuVq6GgTzzYHCdx+k+FxHp9tvFNtmJO1L1+S7J8lhFv3ZN/bJZjPZW+7ptDPP60/qoOhsLOZn8nZn5ln5S1oqt4F4mIXS5Ay0jJk4v9Go2UDpGJr7DUlK8eu4NEm/v0Osi44Khr4qidIgn4/92ART9tjp4gXz8ik1UqYU5J4fmXJqrSLEFY6QxUGBT6nsN3EUKzhhfkFjeKwoSibK3ifP7IhR/Euc+pHK/QH8MULOnZj8cXZGfdq6XZ7JJHt1/ZBMQbx37gASvpKx8vNFlQaUwYFclRVKQFhxHus+JE38893z7p2IC9pIGsN6w/HSwI7LPuqa1JNOU+K+v8ovh1ZmyRZZzxE2D3jfqR//tKtlDPUPR6nZ5yGkh9GB2e4dibMTIN8I9bZzK3TLUsAI+iNsESMs0+OmiZydgyxTqffRwl5RIxbX/dXcbctgy4peIL16WSsVpPKFiXqIzUTq5f0OOhCZzKly6zWHplFZOGCiL+cH0yGa31BctkMpXHZ5KJ4D3TnJg0Geh9GBuR4QA+LcEaA/+sWBnIwuqDrjZP5uKFnhdDVsC6y70EvamCWEMjXrkikG0S+Ov3WnEBdtIy/Jz3afkpy0jny6Ix615p3lK3+SHgwXFcuIBcOO84311ygPVsgpsyszNs6SdVUpNfAaZB7w9eALVzu6YYQ4p/eRKUWQN0R4ztO3vsWPvZSf19b758tO3ckCdsW7NimWNdCJ98FQUYPGEDHuEbTf90xe58tDN0LQX8SSDacYZXbnE6LKIIOPObJ10yuK63PWEV1Aaq2tZvzaz1X7cB3wjGRPnB3ZVEqCbpxXzd1jqdS9eQ9lpsAb0RirJTwTOtIp+zSqYIqSCRxyXbmBEbUZ32V08ZAMoOwd4vYve7nd2HE4eBHndGNQNcpbp1TfQ78PcIfSNJG0zUUqBQKhwJpb0h7rU/JlMqUv6Cko9b9wnhRrWh3jl20iSAP8LZiZoXdIWpa10TJnuaiYRfvMTL1HRrRLYwM5XdkTDBNW3jmkYPTG312L2xOIJGERUsJFM0zNRvgGqa/4aRsKKqZBpQNmJ0X3vMX1XnYi7HY4he76/hm9L9FXGlAEYVq3YHjCqfpmKwuWcvuILFNbp1kMpngBSnTbN9AYdOg8c8LJThC+gMPgw4LiD8nOUjria5a5T6OLmXld0RNzmr28c39g1Ma3V1opbFvSnGWs/oyY7h1SpEKCzXslKwTm3zRytgLAYsqA3D3DqdHjpD9GfxwPxayhkq9TTF+OY4wvwR2FHqps7sxAFD+uIXnvaj7Xu9F28Dvy7DF+ELVx0XHcC2kPYjnoufqy7e9gJHX0o/DebwFBojAulFzlKMCb9aQYZqOisrlHR0/OaqHF2xuzDrWKA5C7aNHTXWduYxwCQgxV89CUpqoHL6+9Hn9OPTNkDz3mfnfQe7jnR5758HDo4QbxMDkm7jNvMdX9I7CjHBQt1d/Zt/ZP950vSp4ZIN8SfoSuhj0xEDUPoV/Bh5DMx2MBw9ckURdNfwRhyv2JFABV2hOxQYgm3XODyQde99Gn3SG073QT6bpXx+jmkaBN6NQHYhgDXDh6xHgMjLAVKKmnroKHVTZkzEgU9v95MqKcmHMOFqtDN8yMihkceuahH9ZORw3oUjGMunnKZSz1B0ep2ccm0SvJv4jUjJPLT02pY79e7mLamubd2qgjizZSugd1au0cil0FdqHBcdXwAkV7/kVmuAvxsZZyjw41IKP3z4us7kTYJ8KQPKVWXQHum/3kjylVc4Odl/1fx/0eu0TEBu4CFTbqEOnT/HyKakUPnvS6MYr3vZz0BJLDTKZDB/AqrAsJB3t/fJPl1/EAYSvezOLcK+QSv7dY4hiSe/owHrgWFetgrczLk5IKRCPq2z+itcb1dv5vO65Jy2aVmyvB3318zpZ+kkLP/hTuzIeOvEjImc/Jk7P3sHlKHsK4tQWm1FyS0K6SYvtINafhxomslZLuBnP1BUa9AfJzglxrG6ALzlm3nTtS4CgXv3rRUTOdTku9evIDSeB75YlYLdtqxhIXX4TJpc/0kgq421jCU78gAwX74QLLlFKXtItB2nlB8nlZCo0k4/dPh6huE1g/nxy6tyWTz3Q7K2Z90fVehutQPKxfyq0uJrKjTyTXB7rrDJ17JcszedlsEH6EVZihAXPxwCNbY+aWAZqvUtRdEM5YW0h3bepuwnhankq8fy+ftVhWgf8SXXGUrJN7ParZHhHA7P2fT01A5pfZitCXUcbjkG4gmR9nkTiMszDU4hb2XAvfIcv8ETCPRnl7l/fWsV51WXlD7JX/ClVuB8YoHDlgL/iv4Ju0Is4HnLZC3iXthAmfuX26u13xAqL95W4U+NP5fCL5d5yq7MZJeSXnEteNgCwSAAdAWvfvdosLsrvKKndT//ZoE7vy+1q4/1c6/jET7thdnND+jJFYE/wHB1fFA+BXzfgtC9QWXnssgHPhW66xXH81vwL4J+GArWONJKIijBuanjCwa3KhH8c3BXBNG17oLuSu57Qk8HAy86/Hecuz4h3vBJWD4l/0xsbL8zOO7fdZz7eeUOfDdZB7/bBo73aMD55Af878DKywneuJ6+hN+pgE877nWP56nMmH0nZ1zvb4PnHdIxPTHK0e83iP/JTQ5zfyjud0tDclIeX/eSRHz/N3Snz+F2siuep2ejO0cQyd0Lg/2/HwRP+248T03B8Dso432XF/MgAIYDALngnXkCWEBXXiHQiTMSm44iu90t2TJJRgarCYLMSC7guzngqc8bx9hhO7bpNLP92OaneO2SkRAYBiMAj4CIhIyCikaUGHESJLnngUdSpMmQJUeeAkVKlKlQBYp+tDrXroaCFTHj4fKT0R959vI2T8eLbVsB9WevhJO1POC3Iu6CfqbEw2rvNSU7o4n1kZXz1xXZHmjlOOchOPuwwa1ogVgr87QmOPuwL676A7BfmgSuiAXwYrOWxVxD8Vcb0sJ4tskrQunZq95yeFbmC7LvPqyXVUVUnW/1lOfbKi1tdhy1OqwDf9gMirfkPuqUz7kr5ii6rtX360H/2Wx+uSWd6gw3uS9kywswupBe4JnIs9N33YsyyNLdiWAv4/3+Md1e5rv0aIbCL4t55r558ene3WvXxkFj8d0gUpYf2l2uhZYb5loUUMT9Hsr2eVfJ+cnnZ0Wr9pdVWQGVsodl0bxSdrdszXmn7IpJpexOWdW5UrZSdq/sYll08EOd9VoWzbTcLTtPq347ZdXwrbJ/yIW1GC+PlYyd5JXS885Epg7welv0sc/BeTzSf6wd+GhtxoW9IIi7SA0BgNpVV6IBaoiJHYD5n881JoUxG8zACuhG5ll3f9Z6n6hpCX97sTPDs6XApq+sOu2MZzTrLKQzfHZ5YY6wTriCyHIfzqL0DJkpYnV6Z2Y74lB4EQyR5r4uD72GSxGWXpnSHFwiN5YRKlu7KnJTZu3S+4EtcGwCOIEHvNvNWM5RFSXxKe2JhflGU2YxGpKUaDkV3CJnT9Tu06RcfE8kycWoY7RMr2x3jmhKz/gOyrXLEz3h7WwLVR4uKgytaA7Ca8LftW/oBm5JkkoS/QgGvDvf56Jkx++93588G/r2epe0TatjTZts4qWy95P15ryyz3bP92j9mrNeZtS01Y11n9XssvlM+U56cv/T1J2ElOuwvxcAf5bBMvKtvPntcd40UMZ9hiOwM7CrMFB+IJejZeGiWWKdnTZhz86o5VRUUaspKWcnKbRmxhIM90ijadZKYN1nRAAkEXctffdznNZ/K6UfAcCj3x9yAICXV6WH+3v/Pa3bsDZuyBoADP+XFi79t/F+3zMPk153JbfvbmS9J/VIJXYy+L7WVNRziXkbGaw01htiUSJe2ZRXsbtfM7/XMsp7GrW9vB3wPv8d3znp7qSDsPc1856hS56jvAOpLaEucz2l13rVUr0Clwc0iPuxavHTUSuaOGe4YDtYzhzA7/Zk/Q2+o6g6AHE85x8l9jkM8InrnT8PifmuL/J6twLQdUaQvmHXG0C04ohXkUju7wBwdSaw0yexd23raGk3hoyJn1ktUBFIWQOY8AkWHgvrAfsWsc9jarWg2a00/VA++J7/IiWgy5rOSk9Ta5yR7lMkTyIXyJYSepXZqc3Me1BcfVAdSkYJOzP5WLUia6sWLo/qS+KegHAjWdKK7OReqsye0hsAjOO86syUAjhju605hgXgH/m684xz2gcucIosyqknhwrWUSdaaTVQXadSV5BLG9fqWrKPtxwcfQXg7+zyk8r5QdCGEpVvdDbTiiWLlk7JB9Y3hBHrZ4IfJwVaRz0WTuqCXtVyvI/cNwhoJCDEBcxbNOQzd3pp45UQWqaXkf2aMPaeaOetdNAkHCHqXfnaa/I80JTMlpNwnwxF5VrQYwFScor8iy4TYj9Ht2V4kLkGUhIyJTKrl56T9X1sPVGquq35N/Ja9CIn4glEtyfxtI1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") 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") 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2nftImTx/RGS7LM3aZfDSfJTunD3jAcGIXQzO6d2zjZ/nl7Nn/7bbOiR4S4tUfWsrRYqIFEkIAY+ABwJEiE9kIpPMeCY+k5mMydP79J5zJ90vtvtFBbIaK+HdIT2TBNxNOjXzfWvWmiUnpoQw01bV3aXaPTBAYE00eyTrfmbyJ/r+3YfI2tz/v/73d7sze3t3u7d3W+rtXq/fCl8opcs/XRD4R8pjo1h4LBGIUSyJgIktGtEYaxKFpKuJqIklTdE0U4bndfP/ktx7M+Y9514SdhgJS9mBJATIWGQtIGGswBZwoOJAa4fgwlUFrVo7BVe34uy0Wu3S3fVabdX2/77/Cq6O93+e3+u8beJf3r3nvuffnn73xH/EK0mTVExoKVDaUkpRGQwRH9uQDRjMMJ8gtsGEAfPh+dXWX7Yn/3vvT+fuzuxE7WxMx+7ERhS9Cy3SUqKCRRkJWAEYeSoYdacYaN+ZaN/dEL+2/gELu/3ezLztJHJZdll6l4gUEFoFCzAIK8FqjEZR7zwzz+iz6s688izQ+/eHcLoyZk1yuUtSsySdaBvpRLu2A58hPsSH+cD/H5VHdDz2yLDn0TFEh22YbPgj9pgPwTrP5Ov/x/MiY0zmTMbERG+iZ6q3qdrkv2eh/zHT75+F6CW9MsPGQGFb7aKheQchtXkYnl+bj7iK/967KLho+uCOO+iDO6LLQDAwUMDEBKvBKjDmnAHWUnvq5rSnc7rZs7f99G72/7eQzJyJAJWVXpNeUa9D0fhEJpM4AWosvWbyft/wtG9rlv37Y+rV9M/5M/M7txrYAnaXTKlUUEEBxcJA1DMS9OxTgTs9K+7aqPPCM/LCivOGp+n8gyaN3917dxeXtqnE60nj9aSqtKVQaItZi2mLDxhQdBsmYxuiGxOYwGDKpEUmSmH2/+ZLe10LGo1wBj0t6vJHatnXOY1mrfzXkM6BFZ35hSMcUC5wl+lXb/vKNH2Kpl2MLSEkY4SMuIxx7M3nX+2r6wwv9//7UMZYE/EwJWy9mzAB0j2APoa9vExG+R3rk5ttboolIQQInMn44lPddTBZzGoJXUSkfN/nRC5VLV3701/Zfl28sIuwwIIgGGQKpIItJ1IfJPsSCV36n6eV8yc5sd2d/96f3dmd2dnZnVkRvbs9l5wkl5O4QcQICUG1iIZgmiJtKRSrIKVoqSOlDlVoq8S28JCo+LgxuE6mxGIvPv7QrapfpT8xIExG4oSFNT1pmv9vGhGx0qadFVJOgVXo3FRdoELN/b81Y30IDNhq27lhOD18Px2OfvCSIM2yzYLzIdShTiLBLh26/ocUnQlhSbrf5NQStmkZOVwIIcT6lFLr+5DKYsovFUZ+jjLKaEBUrsl8LCO5iP1+7v3nv+tuUVX7k6BxYDAqmHOCSu4wFKAssbqf9xnMC2pf1oGYtVMpDRpWaZK2B+InvixQVCMnXCrKBv6+WcknHMJJsFGC90EmTudujFo5xK/2Y2ISisvefsTlmMcCjaFaIhRiVdOttVT6p0I/EFtTOsBsspuDBy4LRSRsq+wMlGm5DgfPN66F4lNwlUJKqi7rmqxuHQJPfNLuZmpiVVfEwj74SDnOzf30Tu3/YSwYjSTbSduL9PPxD9hs0m0i9wK+t9zYGjysdBkH7OwFQSLL6Te2aVKOMeOnc2AU9o1jjCEk8FS2b0amlWvleCS2RUSQikciNogH6Vl4GWoNHlE/QnTwPXTwZv9s9/Ojf519G63bXXWquvveKwkhhAADBgw2eJiZ97L3RduTHBIpCITIQQZj58l+G0L4+Fnv3/7/vbr6n+5zrm2uZKi+V65wDdW1JHjhytWsJdNp6uqu9ZripZRuUrj3yraCDbIElG3Ck2zolmRRT5ZNt4MAYUwtQ5kKqWOiUgfqBUm2qy1B05ZMJVNVD7sy9RJU90s/+b8yXeGbjtCRl/k5TMZ/MvyTWY6zPJv94R8OUx796ejzPP+XprnpgNHBiOVEqdSX0mww+Dm01irgmqz//bJ+ds90PYaQevsHS7PVBBeSnf3JEYQEYVHs7df9qrnceYS0vOpaSega0k+xe2aXngDfJkt0IfqYFrKMUX9PMiK5KDRKUViDRGisQwgNQbhsdoeaQBcSWap3V2i5W0r+X3jJ//mW9qZV3dMzA4ArAks5yptMyoEB5WykUMp1cs417xKvqt5btpnRjsFIAxIrEcv9R+Ca/33dqtfYZxqrRs98aQDIgJSj5He/nHFZYGyqMFSmIJXfN62kq0sOkZmCS9AJoZvunv/eTnJIGWCVqlu1o0mbErKNuAGlXS1dRDPaNQsRcMNjrao+rM7OGVz/xIPgLoUuVzyrViqF9qxNK74noKGIf8ijx/g/CVg/W19K97kzMnVn/MFfccuAhTJ3V7k0fvtc+NRqrfjpkBU+m+9sPvwSwIJx/P6nflLJ5TuN0BwewGRZX0pjFdFf9P7d7SiV5iwMy+Ged2fmucjeitJYAGOh4MnI2bD4/1+mVtuITIACKamLFNuweqWqcX6xozTO7paZ9/0fL+O/+BGJiEyQiARoMimKTNAmSBmQVMWPSGoiE5AOCLZBe1bVRlTXQmprAKmNqHZ2ObPaWLuc5SyWm5n/KlPr+n9ClBJFUY6sIuUE1UuCtLojKS+ApJ5zL8t6W9djxE+UnRFJqBMJggYSVTKQKGiAhGjnUuUGMsleV0q9bJvk2br3jMgCOyOyICMyChIiokAhIgC6IqJAV0QANCOzoJYtdw/t2Wz1tqs39k4v66zX4xwdyAI9WaiSX7HI9lOrZ9mOc7jP6TiX69xkeZZlvd17ai21t5+U2BK6Ct2OJyUre7t7+3R/gf3/AOGlFEJVZNW4AksgVk3Vu1hWLf9U/VQlUWnVTxV5XRtAF9eprKy3P1ElUJ86YP//y6+0b3rN7L3nHhFIpIAiWc2WejB8/twjC0ywapEgWwix5un33mMb8Uw8pstiyK5MZKKbAMguhfpf33PONXNTHnguEhURmWAnAP5qkKzuBf6v67fUox4OpBwOs3X56voMp5JVSre/WYrujOYKcfT84tXYSQik7T+7B///b1+ffap+98rrDzi7Kq8Y6F92N0kUfyIFZfNKPiBKEeFmbq9jRTrGyFMIF/oDqZJSQZAzwN+ESfsZ+ZeoyIR/a74vXem+X63hZTRTyuK1I3BstLA/RLNGAjAtT1+r/pXKndYDr71AMVo+SDGQab2goDYoRN0fVST6MTxU6+0/8esK7dolhxs2o72JXiQ0Y3NHNQdo/wPEqLL8qxVSDGF2xcvSFF9llPeAnuezZf9Sa9pxxykwWjpOTwPZjxesU2C42qnV6Oshw3+1vj6j7S8m1VSlUkt49vNFC5h+lEyl+xwbRd9y422pAkgmQNOz9xORT2hR91tAFrElgC5UZV/1yXZ0rG/h89vX11jhj2JmCvhzx5E3nbEquBpvF/7JyBDUESRE0jz6QSK8CvzMgiAB/9V6ewwXuBalE/3GX8itizoEcepUSTWZ2RoCqb27aOH/v/n2SUdPs0f4/QCcxQPY6/tkaa1B+TGSjO6c/BQD1CuITlVJll1u96NBQxDudtn9c3dYoKdf1nRT9UjGrZAIt0SpL84n9a3GiEP4IT7+DIWxOIOQHsl5geYv8sUGVig9KVJLUdfIWognL6l8nv35fr+V6hw01ve0clRaqXnD5ABSI/X+HZbHz/mTc337Zt7MKAywMj6C6CJrwhhB/SnedalKselS7q4qr6lu+Nr2/54JhpAc5wKiDxsRI6/0WJdQEQMj0cZAtLGaEqxA0WvF+1m7iFxs/nb14ftH1fy57wHMWplnhAUhCozLpVKmMu1cdK46l8Uvv0/Pb9q/cx+pAOkqNUqIfjbLZEnqidNsSlPapR7dpR4XYkbEiZg1RES/ua2owgd+OpuRdr3UgPIsa4UR7tCTOOmUK+3352ZkK2qSMMlHwRBEgoiIFCJFUVvUFoWIiIgUQbJSiIiEEERExA1SiLiuSBARCUFCkBBCCMEVkSCSDRIccUUKcUWKWufuPc7XcfI/36/l+ff9ff/vq42RhDvq0Y0qGpFhxktLjresqWOkI2sbacUGLF2d+Bq5HkYvKgN9wKvzASB6VzOLmqwCZCMSFCggUEBAQEBAoICAgECBAgICBQoICAgUEBDQRggYGBgYGBgYGDQwMDAwMBAQMBAQMDAwEBAw6H3ue6z1fVWFqH5815d+xZd9+Zd9xUdgBPbhBI7jBEbgOI7jOE7gOI7jBEEQOEEQBEEQJEkQFEmSFEWRFEXRFEVRNEPTNE0xNEMzNEPRNE3RNEXRNM3QNE3TDEMzzO69HvD1fy91btUEoEdNRZ+aPk3oiZsjR1qFAd6ktPP8u9n3rl5wxujEtwxxDck4xknUlGal2Rottlh6YquxIgqx0ooSAcGOAlIELNDVaMRK4pSe2f3asx+f9avOQ7rVv2CA/SDr/Z/l+J6363mu67q6rWDHSlfEAtjbKnZAQVlFWhNCCT2VFEKSSTIpkzrTk0zSJwn0717/tu9Vm2FBUiQ7DkYKbMqV3t///f+46d/3ktBOWX/G8nJKqtC1EzWpuIyaByhQ1+mHr2b6VaPXw9YA2mCFvj9nXBIlN0Fz+T+5t7l2oDIzlD659plaVbjWT7QGZ8gppodK4ohGsUBUVjSb3ew6+P8+/zjVfymx1wH53DW+/ktGSdv/XvMAkAYABcQ5SUMlE8URWpZBFpAtk2RZ3vj/h23+eew+J+E85yjbfkTkonRpZIMVmxhLMLGKSEeFUaiY/Svnoan2vUlH7j47bt97OS91//X2utz9gEv0abG73HK6UIJN2yQbKiVsB8iO4zhhA8WOHcskm8U4Gg1qUNJImtGMNDM23/H8o77zj8J14D/nlXNOfj6nP3QS6Jx0LtrSsYB2wy9r/ZIQ2IGMDQlkj/cy5tvDb2zPJcuyZFu2pe0hy7IlS7DnIc35/2eWGXP/rg3nHL7DzTXvEkJII60RAoRU6Gkk1EuAkNBM67ahu+BCd2m4tbX7dtvrtqV7vSv1VdtVLTOSRtKoznTNaKTZ7fOPU1Ny4gPO+2v9vYsPm4OlAwJurlvpCFLmKyVpOYBt0hhjhxyTDLIsS/oisHnjrTWb5IyMqur4qipC1QfmfQBQL5xuObOTAzx28f//pgTCcHFxMQzDcDAcDAfDwTBcXDy4GIZhGC5e/Pih/7xwehX4GDzAAhaDxWAwGDwMBgtYLGAJC/hx8eEzAgQAD8kUWrTR+W+QMCoRcNc4fI3nf9bEhgP7NSsgDMQ/B+MjQQcM4DM6hldEgmjoH9WxBdUmiFBl3JwViJSyDDQsiPtMFfYkOq5LZ5XS4+fstjNui3cWSYtU5al61ocJtbIOZdOBkTEH36q9/vNMWN2rmvyKh/9qk5f2FPE+dzj2xJm4og/0ub7anwYh5kFAvZC5iSYMFD5RnIFD1aM5Ux8dwLXAXXPrhumPWbGnbSZpTvNbW2mPz0RcoDBEM/Tk/E+ESUQUyg3HBBwe+Dy5NI8Vr0ysS2BML+kXw4QFAVPZUEwuKfxSKUvL3bcNOiRIlCpNhtr/xyL4bAhx6CBMOgAeygcKCcU6SruokOhtTQ1tQ+bJa0op1VDckUkOapJdaXZrIm5BkXJUPEwBheLgRbcfYUgDVBoU6dsVtvsCnR8pwhhthDeIRn5K8aQkqxaq7CKvbVjRQLF2LOmTv8DE4Z5uTVBXXh99GrzCT4rolDgfWORO6FVWm5RnlVYpplwBUacGGIjqCCwrQK0MBUZD9UpaxZPs8WvMMKO2mcZPPUFQ3UiUy7DK+K1kqWoJrWjq4KarxN7KZbuh87+IrunRj+H7AoqYE4uMZQ3MijVIsY3ZBXsOHGclz7oyqIfEpXhoCRKlSpNRZUayYFLzXm1j7G5xgjOPdhGi/cxbt98IV/Q9tzY666eDOXVA24P5gMayBmYV69hB6r5reiKoSJxfParJ3CUr9pgeWo7uiRnPSsTHRzvq7mc5FZ2IrunRj+E6IJjHgljWwKzm9KbsHJuwI+4FtU6cxUNLkChVmoxk7pIFjJrUshgk/D/wkeMxL4nSGY1ZCbPRmhWglFJKD9qAR6P3G9uPGo+dXBMA4IAuxBgwYDTrPjKqBAAAAAAwjrYw3Qw00TvPlEXjEgSnXYQoyQiUZbY+n8yvANbf7Ca6cyh/lhY2EabVRi23j8gy/5a6BaixOEMIBliWVYJF2Z9J4i+viQ4KuQPH41SzEHNxUHxv1WvBMplxMdY9g+L7JKuFCQabx/BYfKcyIw5UZ5I1tHHZySO4ztSGPyp56a8EH7ydxLBaaMDtrpz2c6PwjoB5SRlEYQS4EMIxTUeUZzBhBmVBs1kHOGzZPZV35ILPjXdqf3WCgvUSEUlucdEaJSToJ81kQ2VYNqY7WpFbJ6vM0Vm5hQpVWabYtjFdbmf5Lk44r6vzdHd36Qpv0ZXeKV/lPR+o9hFd54vy9b7yjR7EnwMqDOFuExgjAiIGE0SDyMAM8SDmAELKEWuwQGoSA2CkrhasDOdnVwE14v0M1i0DHEEzHf7hru3rdXtgFwCYuAZaBs9BjYXSuCjtdbRIkYN2IPDJz2MgGGSApwEpnzg/kCIY6ub4IMIRLugADVljBRyD3wVSWoEAIZBpZ0Jy4GpgR/KRCRDyc0KtRNei1fTvnSjLbntkH3bKtU+PPEf1y3fcKYsOL1h6eMMy9z2w3O+e+eXwtWJvvf8usfXJ2u+voMyoP5T7x38qD3/acDgWG88Q5AFUAyBEh5okJraJklItHTN1rFjZzIGTBu7cNZnE11YhwvwqQoQ2seLskDPV2Noxyyy7XXPNHjfc0OGWWzrdcUeXe+7Zuz6gcys75CE8gP0AyG8P4AAA7WKB7kobiuECB09oV9/a3NFuQIEjlfYgH7W7pT2GueVOr2HqSgx0+g6i4xZcAaAfjDO34DYAfTCGHsBLAAZS4ENl4BnV6I4RAw8Qa8ATTCqITdXwGj5lS0zGCUXOjYraBBpGPJkyM5ElG3r27Plz5CSACxdBqycMBPPmLcRCC4VaZZUwxdYI16JNtHa7xNljjwRdjkTixogOIzKgUNOxsWUiELKIiWWTkclBoeRSUcljRGsGHZ1ZrFiZzYmTOVy4mCtOvHmmmKZAulkWybdUcVRXLURV1dLQ/YRCjWFiG8cN3kKTmhBCDAQCSkoKQyIxKSiwqGmwGTPGZ8qUgBlrQrZsSTlzI+NlIoUAAVSCBVMLF85ArFiG0mXQyJJLa6ZZdOaax1yJMpbq1bPXoIGDLbZw1K6dk1NOcc7z9BbNBfCMWY0LVyIiHnkAbtE8Ac8kfdrk5hVueBebiilU0zB7RVvoX8WxsdLVU9zqYa1FK3s7dHJ0yGEejjrGy3EneDvtDL0LLvE1bFiAa24K9NxrofkFCz2q6tCGIZqAUCwVlXgGDCTQ00vky1fSRNtMJJttjnkzHVGgyNqYX8zE1UxmCQplBTNm8Uuxh2pPtxKKVELNUD0jFhr5qNNqi+3+mrz2N35MNMd2ZHdAmUKzsAQONsSy4gjVUeUBDQt/ceBoPCfoKIJ0y9GssoqBHfaE4caJjhGm+Ph0JCTMUCjmtIxZ0DFjNRthw5UrW5482QkRyl6ECI5ixHCSJImz5VZyUWSNCcpd5u2q24rddW8SrQ9qIJUeeRxVmwjAiA15REE3LpFFeGtXVNtb7u8oSa6+T6SXPATuDS6DZ7AGXuPdPEq+6m414A/jupqfJjo6BFMWXPOnztkNS9Y8VhuDYRugABMz0BJiew0ysLgM1rm3yBCdoCO0xeziM7Y6xwpxLWGTmuDqMgYSNU8ys6U6JkNrW7HKXK3O/ZVYq/9xxr4+xkXjLj/xkjNGKTTrGpwWXQr6rBkAsg/rMn6ijnuy56PVBi+8e30VB2EAHsIAd5gzd1eEqLi3uU0wsowYOvt8WVevjWxguppux28Ewf+C892AAH5VFeDKbwDvZ7+ERDn9X/iD+RdEp/ywKG5lYhz9fKpufwD18hEYMgkDkoZA1i0JDdF6EUxCkOUy6n+IodZ7WKA4/duQyFKmt/gR7+3plx8RRCSMCRgr3tcFVI249kgcp0r90MU+ybsV6FYBxYoNRCgi+QmUJ6kAvap1OVpCgCCzL5Uk3sh7hetyCbbrj2bi1hRtFp7Qj58t/8SNwroCFwXxvCOMApVXfKhUA/GhUGaEZIzL23vYRgB8oi4pq9njCkQyEEI2GhPdQnUr2RISUll0DXInvc9lCxTHKle9CJFlBixIogqpsrDuOV5gkgD2RsEyqWDa8q+5gTOkQQsGGWFcyMek0CcfL7Xp1/+PEZB0JO+Vyd2XnPjGRsk/5P9JWMP3+b/aOPw3nMRsDiD26D3+/EmD4Gk7rf4waXdSpoYeQJGk4mcwnjV16PlHaZr7ENWNEc4zoiGOukD6CAoAtIVqndgIUeBQMZ+GHJiaccsIiDRO3G2iq6SY9CUm1HKU/UJUSLCAm+PZLxVk+zHTNsVb+cT+FRjIp7xPiIV1ES2u5NZCpi9GSHwmv8CFHhFCSwuvRmpjRLzRHSZ/RNi/hKidmQHUVg0CSN0xt7QkEd1fl2zcTiGwYixCbo8l/fG1mzdvN7vaFKmr0hrFkgc1TuyyS3zCxBUNO6p52q8VKCxmhNfcB0uwVS09lkb1mEl3W0QsC0gSbFKVkhK/PSqjUNK/NhFoMiCT1FIjwfQwiBSG9FmL8FZJcC+3t5Dh+CrdL6goIr2FskSdWkLe9/BuSG+CXxgXb/Qj67EfP6cAaHmaGA6W7uq8oxLs9ItXVBKitbDkByRwTa04m1B1D1OzPEst+0s9YCsMEDyGQgVwkxWNqMCOJqMVfbmisMtmfa8ivGFB1vRJvXt23x8a6fabwhTb+MV43uvVaV5v8tec1N0CnvxhlVXBZMxZHV5FwBa1pggAtCIJ45z04SRbOyEZHqytGOktK/3+QuDx0Xwky+I6vzmcQd8DLhdCJte9WPVh3nMrt3cF3lOP2SEcfUIBzWxL7s46xu0mSUCTXxsoCBKVi1d+5BaBge7OGv1G6TrSUDbBEY0fiLuSHUlVVz6kWhNyH+pcM8DB10joGliPpu0jaiFgAlpylLtWnjyBB9lROvAyjK+JlVoIvuqcReaOjBtAFUAbJU1ySnEfYSHaewvT+AHBgO642yQ22fXrO/n3rvpc4979bRJSgcTdlB03wXZfLz90yHO4pzAN2sx/knKiGd79odzzd/ysLxcSF2ciPWIkb4KQrHGJSPJWKLuq/Dcdynaz4WF5tFDN2nnXjvP2GhasWDHEg1p8exXbv39SHA9VS7t8ozGkhYcTObVPLO9CruVD76OSUULRM2VsmM2oNMeo69M/DqqFr9M1tdIj35QU9wItBicmf+SDaMgU6zUWMp8SwmAlRkyKPTkzZJN4vjkVs5C6NcKHwN3zoRPOxBrDibRBQF6sY+3msNhCuNeqD9EzBBZvIVtR8hTgYWqJZ6UFVqIaDiuwL2xU14Vfd+AcioNHA7kVI/Qf3fiXxuVdrDhmLr0GFHG3uy/Z8RrEVIn6CHhSKuO0TLrxof00Xh87rBCcOBvYQKx0m/wz7cSGrDC9NnxMO7snk2CptrtzAiJTHz36peCAT3qyZqIkc3PX17r1rz9ikggcyLsUGBTSDn9GRbUS2415dVY4iEGqPfKpbMproj3n0fyBSB3QCkcfQeShHOqHylOq6AI02WV7SkCk++y+hB/T8cWcDWN8HqA9dUBuWV7zt5Pnw670vcpRw3z6SbthXRa3erya3fHTqsZ2G/R2zLOvhifd7XtNafVk75ahl7sYMT24trzHQUjbsQ6+jqUDZIlSnQdY8ZE3EJZgbYJ4XmIcEAW2U5vAVb4x6VfvCbauFmyb5A8e0w/p/1BeOwgsD69/fKTY9KP2FrOR+kLiClZKwpMSf0brRu29ivVZQUGTu/v/QOQIgFYuVhKinVaA9+K3iX9tRp7fjneeRosDP/bz12hO92lYas0uKUqdy44tKH0QXm4eFeQZisygOc3SgATYwoGjdoDK3kjWqC9bMg3vLPmUJrxqBgn1e/f0JwGX+Rrp3cLFyA/tyH3hjtt+k1WyBYzvKNPkAbOmDNg+eksP/PCqtWBLFKDa6lvB6B3iCGKHOuPSgmk1XsFhHeS6VdYszYJ7elENUvzOv3P4U+byGb168phxNeTDf175j3OJrJ1mNnse08mLidVwjIvAhjOGqtZyOx1SfJXFq8STWqu3EXfe2//RvMjNT0ymhusYMxZykx7BrNf2QWzt667FDQMcX9Ucj37nLe2lyC+mu+xuPyA0dYuPTsTV26dREW2WFAx3/XLs5buRqtq5zpEln3moVKghmDGlgPRf85IH9Nsry/byItrZlm7XYYsQldgYgOcF/fuoGagfU1S1Yi0k+Io/i5efaV6/K8GqeyoxIbauhaUHf7uIlIWz8oHWi8WDMw188WPweyZsrFXnEw9vBNz38uvt971MGePcufRlc2cCUHUCiO9NKzljGZ0RaF1/0hZo2OkmOqBTa/7ExZf/NDTmjwJw47HnCPS7PHdEzXfOxL4tnx5YgOQGOrlNGzadwid5rTEKMQ0/3T6c8dhVbpfsEv0UEmBTKONk4zCL12SoRS6AaxHSv8AtwcrysHXO02St3sSXnwPm2zL67cq8QyDqk+dsOID5ClfnVIBLnwTAYNYqpE0ciybj9GxvV04Uz8PpB+St/7HC+enOZ1N4joMddoPxj/fwHup8zvEb6Q0Ss7DgV/j4CyixJ0rM/yrxoUn+33496yEbk8kgDuheZOS0WN1Z+v23uUn7bLn3tTtFL5uXLjVCw2Ey/3ZSec5QNHrnu64e1uX+fzwL/Xhbrecc4zVx0grwq6O2XYuVfgfrjJ03bfCj1HuCxX6HyR7+zXh20ud59f+a5L9y3+JTywMsQ31dNFqHlsk/LkkTL0bXdz//tX5zc3//TfF0gfo9q/btpI6KO8G83NxAUnuDF1WQIeA0pmfKXZWX73iBNidBukUd44dv7Ye2/58WTvWZNxg0Tx5lw7oSv5+0ZO6v77H1mUq9vP0pAdse/EWGhEur+vdvjDUX27Zrd3uikr6Vl9d25feRBs/4X8MTwKYnz5v1jw4b77+S1aXn1qb6i5+KLPwPNYf3ui+I1g1RZB7rbzI55e+H0fgbZR25zPGGNKzvsUurYwq+arIMp8ZPRhF6fKtMIzxzZFmQvykH1WX2i+CaeeM21bFCwU8p6AQgQ1neCiQzG89/pgREyX8qgPMhgleEuX9wfK/ANP9nQpD7QtCXTsb0TIr0Uc7+uTbhpNb6bnboIwn/Zytvd1RIO1PrKLl9wKv0U6edPy2NnyBhZln5x/XrsxN2Iv/fEDb93w3//esKS3TdhNSbVKeV7Bv8Y1gIb5JR+2QPZUZOOK0PPAmb1xOVEmaJX4KAF/SkCImxoAkJ2lyDg4ReRf8EVAAjzb2nJOQKkU6xDB8pxmj3rmDVGDhRDejjleULWyhxaL6jFBL2WWgDm7/EoYr0lE4aoQbESzTSCqgpXhC9OtUsfrXR7U1Uqe5f7QGg8TYQMpcscUAEIYCex+gEBRWxOvFMKNr4emvafaFwkT1j+KHzRXVpGwqjjY+iyF6Dk7Af7Y4heVZdSbTRkq/o9F6QiSxdWKIDvT5RfUsZ4z71PA2PmluYxMty26N2j8yxkzsS5WM7/3RS+YbnkacG7TZwQGteTmETNVR9DS3N6XkfcqMtG9pelBUyKdGahk4LxmV2HWp3r9+ak1VP84b2uwTlSSclc563r9Lct3f/7WdPPeAxZYLNbk35Ff6okzHhl1hclwpb3hZahtjwAFTBp0OST8eGkXLL+ZPr5q2U/2EEmPicgtxVuf2dhNeCWdWB7mtOEtdKT+rUEU74Go5t0zARduMn9T5EaJDUJjkhlbBEyZyGMmralVNW3b6W0f7dj/QrCH5guBen+wacE/05R5t1wkljUIZjNZIJFg7tas2cyBFi9SyEkc7sqJZN6AO0+rZHBcLseh1jy/CNzWF9p/Fbo+9RAFbo2CDBzdncmOLUXuOZnuZ7kI8C0WL0Vp5d1ocQKZDy8Ywckh2Gv0dn0AQGZfVZR/ZytJUsE+J/gtsX5VlqvDluTkIhkBUgFKFo3zP8d202cUdGUmBQ96MKWxAIdaTru5IFP9JduL6CFnhGmLKZHejhiIQOaWP5qEJyBRNyDoBmModY5Mbs9BXa8FHPPNZmESBL9UoAWQ1FFTHMVghRs9FKhzWzx34pg5I6VXSMRchCKSGyflLIxyQ2+i+Bk6pFHJfv4C3MAJZ2oK6KupylffOJpCJYEimrM/MeLCpMekkdfMqOEwuh0GKpTr2DlrwWlTRK5cxCLZBMNHsrIxdRdDbbRoEVBTSPjUyTjsqWX2sp+Cx+an4F4klTSY4WbZGY+bzKI0N4bMOvwfMaU20NQe6NWra61ZSbyiN97Eofxony/ZEP4CaBedXFl8FC66VaWaOUSS95z7lIaj+kBILfe9N8YvJANBYL0fWgT1edgtkfxOPFbaiSdy0gqmxkadVGnme0IZUY53An41eAkLR7Uy4+bsd67HZfTT1p7UnWQT/Vub3hDzx1QtdJXpddgKILMoEgIrVx0QYaqe/Kd6hlwsK/09JPALk0oFJjAlfhTe51HOvTmnJTpckQRq3WI9fdJAVjTpUojTEptvxF963cPZs/GI2ec+SnyHRgNyWVtYCgLKovkRFTOJdvgmJHvUeX1BGjXrz4bQBUWavlnRQraBXH6I6PTWQg+t5M1KcvQbkyqZHqBSsNq+UWskfdJNLWjxQnrDxrH/05ZqKGeLJ8jyz5Psygb4Jw/vZfg95vK89LUYf3az/wX3x8HAUq/2krN2N6kd4ZEK4e0SuXm2IGKuPaSdRPHYOoQsH7YWIMa28gdmvlVe19jNUhONR3wEXPwdB8AURNVYetmJZJZhlCZPhohJnaaKIgNqk/S+u5FpVlEMufmTkKYAkgiL3muKiep+DMxJhby1mKk8E1dVliGNkHRVAbifQKdWGwN+GsmE45HWvepov6p1oXaiYTJ0Aea1iRx5SlcMnIYRqQTFKf/NpCRs+yo8pCoYm93MYWlz4GEcOjBRXS+Nv6vIiGXZ17xfIh9cCN+ezzmKwhbeUyUHTRnPYO9bx57d9QzXLFEhw/rzkC8aEDyPhkxKdJ/BWGnWKtWB4BXK3cuob4v1CAxCjs+6/1/z38nXUFSzkKN2HhUNb0eS9NSTscIHtETf0rlIyPF1rabIpgFUbrYAQX9RW2MVr1xp7XEc2yQGmgGGshnUBIP9qZUjHwjcabO+0X+K/OWXWabncErxRrB/wR5ayCMYGBhyvTv+/x559fBxpHKmnNyYhvgqRiWvFUbYt9ZpY7QAfBNduVhQ1dMcfwNtZyKOd0KY4rmZ2C4sxECMluxkmSU0tOkNqpz+ZczcCOd4SQWsdCT2HkxYjKGiHRAk3+hncflMjqPMBTPsuuPaam3ZweEOpwWLxf8IVlOsvOmaecgLgl5co7H5+OJeZbdAHxS+KfK0MXGtD0KqiINxCbL+OdLyIsx7xsttLQx0ay2rdFYxRlLqNrvoCE8KFtudcPCWqiieHUMJIy/ANJKxMCPKajNrswZifo7/DPz1PXS6yKKa/W6MBCVlzRpiHlpIkjMnnxqWSj8FFGPVjndewKFV99Fv1GXuPYQeGm493Ox+tB46thN5gNq/PY9PsOG3uEqmxCsYtxKpKt8i11m6RP/sbll5v1O/Vl9DYAlr+C7MeXrskVJ0HTDpzILIHQp33z3padWDl5hb5w+ZIJbtVVviv8brhgaLHrkRs0MjFCRlIR88BnCEGYUC5CT7XTq2Rk3uvJ+4hicCfcV5QY7mbXLI2+AiVW98EmJ3vOY6aq5mvmG5mmZYn9+Ut0NkWbLpR8y2DMk9WU5KZVYp6cHOQ2Pn+6aKGPm1pIX+PmNiuJJWxUMUU9mRIDHXfY2nMgsHbztMR9K16k5aepEuliXtZeaFHNq6SscqbllrfdcdaOgrGDZfhrtZ+ZWY7fCgV/s4676++QAhTKOlgGa/3pq482rtwdH3nqZoCcK9ZOUK/L4u0i5pQJb52tjkgr1OnJAZQoyQyZEVLJ4dijSuvKO6mGCYm/jMbTHb9/5gCR2OT2iBAIGpxs8thM2Bp4iS42gHcte9rbIdNwc2/qmRqT2dWGkREJH8Xu4pvBKFc/OwhzMwKyjt54snCg5N4wuawldyJlNCZvODWjAq/gmJqmY1jiyNYnxuTd75OQ/1HbfgysOJJjcuQasOHFtlEwUWmhEs758yf8aEcptkwJcfp9PHgF36fxkfS8gjsSvhQTbjZLouia6rjTo0HsN7wMbXf99KCu8FbsXktEPmG/2XZrjIQP4oLpZmJF9hz3lUYypCw39zbehA5bgsMfBQqNXuoHKQdhCSpjDubQDnpF61vtPeKKt+DVhIf9iQJYUvkgpnQSTIZPIHXLxPcNdmj5m+AJN9s/RLU7qzFfsebNtXkKJehxjBOZgVLNoYu3Jf571w5TmJ7F7EXrHaz1LESNtPcMrc2u24iCVNc5n58s6zTKYkGgBiDA53XcsYmPbZJOVvqottKElIXpBxS+ZhPvIAIrV3y9l1QaqsQMg4WbkkUCG8OyJYV2K3OblV8Q7NGtQqNyzM4eEpyIxYGWz4iyuGAwssosTv90p0KUkGXdt7aSrCAvpqWy99YOj0GzylnRntnHc937J6VjfKSnE5gq2FM7hVW/VQpLcSORgA+Avsb2lJ2MnVJk6qAFmNOmOsxnk5oe+Ekmas43KsvjZd7fegT62W5woDinFAdAmm2AI5Wac4fmx2g2zf/6+c22cdoQlpp37R+zGpLDB2oODypeTJ3oLy/9IqMSf57ev9r/jcRXWR18dGQyyrdwQijOfgOYduXbMqE33Ivqe4eur3WaeLgKXJCNvThHkc7MGPPANyAXgdn3aDqgRZPuDsEeJjGh2daemNEIlcB2royyhgMzeWcAU/4PtEEc8/2d7vJXrqkVYpaCANrcYXRhx5YU5P13PUCvAZJqH+xJqm1mEI08zcITolwoFFE5suEEQyraEHjqtDKD0J/2+LUosnIyICuhSWmQlj2cXEErXg8r00mZyANkM4Fg2TuaqY1eo/aLPhRnV6UoLFydPt4G3WYpNrsHbraxR8YqIW91dM3+u8DD3qmOiWKOMWnTvaksRPuffmYNjO13sfiEOa60OSzsusSwZWkTY5ihNKxVdodH2QqQs3GZhXN6I0Ndd2zCCIZPCzN+YjkzCFN2u6WdnaSeK+DeS14yp01amVXkmb0wHMwpQcKXi+xiVhUDVGYdnb7lSN/JLnwO5uhyLqX1ZNWWs2CaghpV5qJxB8eVCS347Yb6DAiK/KDNmX5e4qzH291Dxui8xNRm6dvveLBmZj4OGQ5gYOQ0+VZ5NYUO7obbD+mIz2O9zfS8h/u5D6yUlj58wwXznsdltt7m4kOYb3w3zw9RfCsuf23fODv7IZUg4n+6RM4gG+/Fj33njTZKX53u8L9/Y8EhHsxG7sMJLnF6csTL8Sbhe1hlzv2PCBYxP7ofWelshjsK0TkwSY4YrP3mpzjCcBFR9iQCOOsQvM1CgGCf7OU/l3ix4gmZ7PR3ksvlCkLBznNoZyXHgi8INaeQgr8U4ZjFKa7dbdn99OTrMfIm26fd0iPo1zU3Jv3MiEJfGBaSCc30/7y7nF6xN01lHK5LMIRztHlw0bfX2XTrz3mW2gdYsfiRfGsvS0v4rvSzPhipokU6Eto2WigVJ86fh7frXmDN1vH4Iaj5wu0Ty2O33lKpnBcVpjCzlhENgBQB+3l4OXLwCwbHK3I+oaLKpEIwAnMKRWxXfQHx9GvRebkNpvafuWF4JAo49fuZmh0mexOyE9i1atRtNkwdW9ffHjMFA/9NL2180gR2fcBwfMtnF9D9bqY+sfqVSnoOWRwAq9yL3/Ccc4IIjM+2C2e7a8naRVjq4K5aEcL0oWqhyYsGXB875Bosu4y+wDkO6QH+DWPA8sQxg+UQ9V7hZFE0WbQZP2fimXlvypjmiz7LW+sznmwhRvoCXJdMFPanrZ31HuzImDTP7CNGwfvEHHD5J5z+QP63pfdVN/7HDvlaG45EL6nsliHhPjk6E/O2rTg4Aubd4SGsvQhJs2beRF0Hc2kSKZZ4MC4XnKEYgkyDBlMviQgCZi8qOFPNBm1MdnyLoLF14fDWG/2Tw+0Ba7i65tTHDODoZKeyeL4/Xc3Qe5WWNuzsGo0I7uzWH/2EG4coKGdr+bXZ43h6mYo91jljxEqxyieWZ8jfjj3BYE9ksu7PSmluMuIh/duu84k9OSFGQOa4IdOC7I2RXwXw0aOXlaNqwissapbO4kBgoAN/IEsKIOqyt4UqznGDn2od3DU68p5eKfhx7aCeQLWACk2GZgLXyxplYUQaonH2zE14wtfdEISC+JhTZJy3etpwfND2XPMr6lDgyPXYuNe2HB5tnBsYTvqrBRZECVp6Y2TO9gGTYktfJBzJG5WVY6lqqCyBEoTdBVDCnJM14KVsTXaXjHktKmwF3JTk4UavpSMJP1shQaI72lEbzXsodqZ3zvSYi7aL3VJ6S/OKIw80l77QQhdPf5Q0YqYSP4uSMvfnmHEcUJR2UruLimRG8DWm6WIg4rpd1OI4vkrig97UR64aiD7pt5H9doxsr3Hvnkf43PnDdOCinqwruvx7VAxQnUj67eiTOV+WlFO79FJG7JrhAZb78tr1R8haHCGLKVj2mp6EGLvO6lWIxG5csVJtlLEfghbE1aFdkPQ62H3pnHQTtnL5IizsVjFpOoYTMxQCHIVi59XvISJy3y2OrS8w45i+T6FnTVIG7taz+4JhifU4OZ8zoSWlzaxHyw3pzLyOEJOS6jBxtjQOiz5gYNGM5NfjO1j8i39N0WWtYca3fuGBbrbgwW4jIjsLa5FkpvTLvMzkE6ldsL9eks5FX6AErmPsRzC1Fj7GAde7+bVCTDZGjlajkMyvA8tjuXa6/4qDmSB72dOmB8FD78MHRLHL07GrCMU04MW6tIGyg2jwrd26J/nLpr/XMCNnDE22pmMhZTdhhfMxuJzYotYY1ONzxGov8RELqqBGaU2ZhAoGrmvmICd8cnMGGwqprSu2WWdrbDbPplKWrRuSk1NNYtmenBNnQjAnjOfX47EJkzqb1jq3q9awpnAmCr+VpjAIBxN+YbvB5BnuuOnrMdu/vV3OIZtfojO07sycP02Y9uG1+Hpd5bSfqeh0cVrSxDcv8sML/UVK2egmcO3HuiqkWJ1EyMOh9qsneD1e6iV/MQf3eQJvoVCvRBG/svVjbrTntfRCqjVNto7Pdjv2mD7SVTcYKgM7FNkJQIKvGEnKYtlMsthuMMrcPWbhENJIu/mSsLrryu4TlMA2bLPYcPYoqVgVeB2SbjN7F176yITFT8O0p26ARxFcs1yu39TbV3dTATJjizmK/traQzVpi7MFS4G6G9DT2nKCtJudlZVjZWkFsaATK8AcYXt+KsCUCs66p68DIgfp/YnDLHj2UFz/wqyKFWzzGovlt4ugpaRMR1kFKkmERJvj2bGMMfY5y1KyeHxqujE5rNF7Dd2qmFu5F5OJuHkeaDVK8w3n6lyqGdOKYqQCzs6CCJYf12N/OJ+l2O7tRT1VpDhSrbJl5km8BrN13aEjFat629SUk0wrI924qtSY0s2KU4tzd6GQEEm3apq1RsmNzm1e4cTlNa8eP+3LTTA/UT9mxWTCnpJmn3d+knx753l7Ys7m+eQz0kcBfyJG39ZKSey0/vX4UmPc9LnVkvTr/5/rj68UPxtON7d/iZ8Bqp/Hb879eHxvTs7fD78/SnhV74oVyoQRchma77z/vKH1oKjOAUTfAjV5LyUrt3ySZ4vur8II6XvF/OzOhL8V7BqRo2Ojr3wJ0HvtwSfweUxBiQ7AdEDVBcQy4m4lI/Y6/OI2i76JEwn5xkwJjtt7fprLmNlSTn6WI1LpCKsQs88QB1hmmWB91H/fRKBkRiM+Z/7zM46jf5HdTuwNlPvw+zh11zU/InHxzHyK1fUd4VsI9bKh6l6DMF9Zg1tsdVhtuq6lhOhqhOvpmQNnPVzPQ2p0PrZ80siTEXw+rhmK5agNLI6KkylsOTso5kK1mNu2140T2cAbygshyPps4QKdDdVscIg5iCzweuhN1Gizg8O1nrqNPHYkNQTfcAbDVNyva+lcY01tLykm2XUsOBpDYZI9n6zDSyk2j3VOUpCc2UGaMo9XLDlxQoYvt4zHrvsU/djNWO+8xvoIrT3dN5+uNVGjT1QZ5V+h+XS/4fCE6OxLSKlrTmqzJljjduXe0MoqcxZn3fTTqo0Yq37GQcXY4s0OsFbtDFNqzNb3JlU8B7+RkoxCnEgL9E7M/DJekzJjjuEoxwBhl54vs1XwLlgQa2vrASe+q1qDX/BJBsMZI+f+i5447PfQQDnUBC7fNi1uucsxNAL4XArIsZxMWYlOBly6K9cDHZvvPkbca6V3cHaMebK3J1fN5Yp1vhhkv6SesAdhUwcY/jQKf9XTGG3o8CGSA2Bv21SVqrwTJ9DItPzqIC32WOXcz67b6CSdbRzPMAhPHDV6qZgUB5y78aXKETLpZQZdiyuOGyFH1wnJu939306/B286TUisZSU6WvjRT0efEHPtXFz0Wo0vXRkijffrdiJOmsNZTpA3C51Ndm6rXSZeHs/7vRqsHjcWAcX6wAGsdgSdYqN3eIuyrs6J2d0oFcSkzbmmrIvkfKbmu669dokR3oBfRC9c0IjCclWUdDjlaC5bemLiopej/8B9RipN6uH8qmrrmlRC+aaKlpur61g+qSvSE3JH3Sjlo2HOVvJ+i+YTjhUN5yy/CZ+v7zDBUFimw4ff++rDP0ZdZhQ7vDaKbYo3IloljAemM+JzyeaKxITJCNfhqqvsAGp+FsUe3R2CdpAeXZYYiIM10YLWRDtJzqnPwjXjWTctji170J3ufHrMxhd4Utxcx8kwQhwRie0boivmRm5i7DahpE/pyNNDeSabb39gAky3VK59GTn5HHxNc+Bu/BmSXJ8nFD298lt/8QcHPPsbVti1bLvuR9GjvSMXUd/JKr0apCiwdEm1U+D9Sf0WB18tdq9dLMm3e72+hrjrvYluYkk+OXwbMLtuIdXf4SI0KL0wrHS5/ZKqiEIl21osE77chl9wstlD1RYzBmzOgKcvqftedxfHEEGmdDtKiMMGolo0fuFMucLFRjpLOJNI9sk2K1dLWV2NY71vxo4rLdIpLu0Jx43OsP9S8lweyJ0kfkfH+LIcmvMlnX/Qgo1JExPTfHVnT+CiE0s7OVpztKpvtOiijj4VspIuR7fRX1IZDcEMpROLB/nFIan7D+lY1y996iZIebne8E2LjJD5sUAx2OYI5PPtlNuGb0Djjr4JkJEeQOkVOeTHEAbKhjr5wuEBAB/yvTDoso2scijCl65/y3G+gYYKV8lLGC3m1WRSNp1fCyfq4VNB+5azmV+LLx9yhn03Wy3Bb0wJH1hxmxS3wanjat19DUAm5jlZile2h3SmHjuIyY7evZPPNpprcAQJRR3tt1aJggqf+AY657ThdbAv9Z0/lzWMn7GrSavLNORGl7mFJdI1aAO68iQqArtKqcz6iB7ng/W6rsF/Kpb/hTPuqjWEafU/n9Mvete/nGWX4iVDgrht/Zg4nMR0ndx0vMpXQ+LIPXVSOIP4QT28uyPPrLu+tsi3nWcoOzf33nDi2UpliNVulduhHaeyIHjnTXBDeH/yln1AJHt9Ryrr8PWXVw1v7oulOWMEmY/D1ghzHpbT25FWo3ZjOR7mttMcnrofxaL55JQSvvYIqZfdjqPf8DBcTMswMIhPrlmLW7+tof8DOnZZzUL7AGaiC+VzVjJkYmMp4cCTHbSdFzWj1ZUTdQo/vSKAyfKng/VmUDF6XEu8jZiYkTLrONfrfAUpZObyjFVcYYXZDEZC3Xm6n33FoLskJhl6cnYLu5z+Cz72bemB4WS1BeMHMiiRaGFjuvYNdhMW1GKOyA/vbXbn0LkaM/CARVGA/s44KBDvIVwM0dWyPbJ190V938ZX4CM8M2TplQMdFKausrO74ZiaY3MFKzfPToTmrxsy2qapGseMkc5W6S3udE4oF+8XJTx7lZ6/U4o5g+WcBYhlXdXLNrpC+yopsSFgsojDdzD/p2V0LqY/9MHxtOG7j5UHLHX2rxyuMADAEjevt0gPKCE2whzYWpBTETPCXfITAPzK9D0LCSDCauocRHIiChLZSgzQVpA5I0bqDOa/CZMkqNornhirSOIIAD90EZZX4ad9b+1CwDRNCy+F+8Dphs06YCDlsHYg4E02Vp6wLJjlMGUEu1UFkGUYB1Mb0r8rE8rFWVGXwMfKPrqq5rhl0SVsJOZP/2jRIQTsXB3BuJxuxM4hgOwD0qOg6Qlg9QgcsKo29oJ7j6QSgYmAWodJmpQAWwZgdJDSIQATCJyR2N5V6VVGrmhnMQpqwBII+9Gj4mS9IpH0qDdResEBWA8XEy18GwZ+VObKW+wpjJ/i85Q7F/7SwGWs4cdmKslJl7FGxC8IztKjUdY2vlfNwe2wJQ6v+crLVjD1FzooCb9Qu5pZxUrSx4MfMYTH5fnYIaEdNM2zpNaL1lnUywfKuzdaLtUn+Eu0AvZu6Cu3htIfZEGsD+WC6bdg69hDhrSlKI0NdaTjzP+qPAKwAVetm2qgbAG2nD6tXvfAVOyQvdv/gV3KtpUT/tJqcZFdBHoBHIeZgEkD5V27nSFat1q2erKBvXMc9u/gwgb37T2Bwc587RMX7PrYHonthj814ChACIDt+FkT3YDN7Mtmx8/NCk65kZi1Uv7s68F8HK7Ahlnr5IVzu2/uuDymXXHIh//6qwGIWg+HAmy2bVvFLnK73ThWXvXrdeJL8cfOPz0GHGPu8ti/UvilfybScqAjKSabyamDcjQXOfBL/wrAIlBrd88h5OFV3YhQw1Bb6DQtpYLtAxB9SKV2TO3pzHB/7wEgx+Mu47JYj7Fo7zWETVg3+HLFJaTTLlYJD/9eRiv/z0rXFa5Ik6crQIstaoVK2gNKSiN6C44uBOBybchLqSSmhKGTU6tb6uNjMhrn+Xr9nN7vd0EfuN9vSaz4a+NxA4Y6HjGusMLr1XHOuUJduWv4JoRr2LM++MH1Zsh5/vbb53MFYIUIkS+UsrhrufsDjGlsNLbtju3MNCZOHLd+D6HcP3Dn+Zvn85eu6Zpt01i7SZrM2I67gHGHYEIXdz65swXQtsOwXq8fIYjT5lGBWh/on+YJQAuLKM8dtWHMMKxackCdQniqlCR9FprIVAXpAxhwAj5lcwVuGF0o1ZAGPTpOqJKFp1A+RWBBgaSKaSrq2+04qZoqeZ9dq8K7Le3wipnJ4TFpnytZeArlEwYLCiRVzLAKsMiq0N4TCJDUrjWANZoKqxs5qoKljqu76kCjeci/gQxfj2vN1JUj7/glwA68PYpexajx3u4hXZq7cTRgLDH6kPVD5F/0FQTWclXjZepYcpc+gDktvQ7Yi/hVzFoavvjOqGgGzqtxaOaOMb8M10uBVC63WAgv5k5C+yEDQcEIwgTSIBLTZJxnXwmA8Bl4g9pEWDE51DhePiAATYOAm4XREChUaau2QQI/zwlf9TSBiDyuQPcERcWllnrcDAzRLtXIZKPZCnaaakt+nN5ur4Pfs6oG5G4UfKqRPH/ufvTNMADzZjNgnn89pOUSyfcABAgXUTNqRV1KK42qRj2wHphITvkYYYBZJFoCv+1P60QQIIDjF/TP6dV658CBb358bV/blbySX5NfjxzpK9JXsZKxvsh3z55nkWd9kJ++yNfolSO9vvhVHchhHMk11xw5JWf9nNG/8k2ZPZHXtO6VRHZINHfHltRKvyR7spf6+HB+6vEbeXyka/xCnFv/7P1+xY+4TtvE/cI//Mv77f609L90F5IDKZFSZmbnxVPqB2m7PZLHiZxWXHFBLpz0DbmhkaRRlOZMnluSjBrMhluemSeMpYX8oNzJEThqkwWq4D5pUcm6t9huZWQyCUH7/6xh2i437qWgZtQ0GEqeUKynkcNhIZDktBuGzXaa3Tfeux2ZllUcFjVvD7s1bb/qQ9nGFLEYSGayNxg6mblYiqEIuRShCAVFBkEQstDl3KkbRlQXBGSZJBhMkNVJMjOYSTDQzLI1jfWFVvoiNE0p6CQYiqFpDIZOFEzoBfaC9YIEoSOWM2ufYFnIfdN04poc6WMIADHt+mi9Rj34vYqhJZ5noSiEQMgFGkFLqOIyA/w8snyV2o69smpAvWGmg5Ht9yi2YpnhS+n53Ra4A1sg/BTDGyOCdN1Zy23c01+8vLtfgWu+osRTbrJnCF2kg5bUhwgTv9TkQMmzhvvulxSIiRB9opOZPsnv45zjawBkh2l3P6jA/hAcOOx9W3SOmjaGBEwGLol+ONMWZ5o7WZPTZCR8pq10KBEygWRLkhFOkCxkJCZ4TQmM9JrESOcPlTxMBhgM49RzAgmQBgtDtrCwcLZwydZi40vky+Kou3bq1I/v4BunKBZCHYquFyGr6lk/TjoHz8qz7u/3fH+83+/d31MU32F8+ptD7UA0wLYpc/v4MDmrm5zEpJ/lUovJ4Fly63ycJSbfiNfga70+Xm8btGWf9kGzuQ+Odf44vf18nLzd5vssgIt07rtJbTyP0/shS7FXdNnXWXnc5vvj/xcqwMwjE1M0iRHdI8aebj3kiDXVWd9vYRNmNnl2pT+doRu2h+w42LnjmReHdRxZUHkPybD2rOwrTzuv3Y7X18X8yoYkG5KPir5X0qbi5XWJYQFPoGncSZJ8P5GzctyImpTMmvYfyuE0T8ebNpqU3G4cViVZNmWvVFLJmfKnodv/xK2b53H38e6PX6JyO1vAsstG+TIrTb4CGKb15Su+IvkNYDOzW9n1GHuuQAfYKZ1kAqYwyZ62Fp9Ma/ektFUt06aUljL6V+UvUmBYdenT56FT+r7Luu7SDV1tzcGodAel1yZL23fp59YB1k03oDes0a+lGM7our4b+tVqtWqTDvT9Cpjj/vHLZ24b5y7T5eumfCG58NWa3JXA6O7k+/S2+2ZNHt2GC7rkzIq+lNEzdWU9Jb2e7dL2vXZE++FDMkqSTEe1YSKZlLvSJqkkEyQFkgpI6rY9Rucn53egAsUIJpLN9sTwYe4mQFIj7nhKeF7BDX7DI5hko1AYUeDXKRT8BVD4ak05pDc3V/ev0CZLk8zK6ajLydt/7mQJk6++K105b8eowax7c1Uyb7nWW1HafoTTlpdFWfy4nub2yPEYgV3RbuD3Zs7uhAKfsJmmbnFtmULfbfPlXMKclW7iJe8fw1TRNE3b992CzGCnUbksmkGO0CXteQZJknRtKRkqXbulOpVd5L4KY9Q+bjllXXJSnq1Lko0/+MvvaPa6I7njjiQZD5s+3VKbbPq+e5rhGbzDZlSy6fsWeRbsoaH2W5skdpqvNjaj5eluj/ZC89FeLfvBlloH22tINjYoo7W2ZlR+2L8bzcaKiZ3DAROSydnI6JxxhOkgiqJXVOfCCHdG54VmD4onayRbFRyMQ48lc4QJXbJ3noSyCm8lojM6bdqCEQ3YvQuz0N6hKL6rAJLCKCe3dx6V8KTKOs8qFvCbU6NTVKwLYHgDVxkBFdzA7NTQFezB7PxMBw0AxYZiAm+7okmS4nyBAi5OMQGoY6spVNToFGckf0EWcHZ2SvLuzJnprjjANgCKIqm/waApinGgYDB17p3bkbOTR6T67dMxxgg1tv0cakhqVOqRTerGZ3Ar3R3qlPkBtY+nOJitIamxxj66JaLGGOMEVGeQ/0CRQ/PbqWmPWiadz81GWawqi31E8wbNo87Q9Kg9ydIMA7pk0QI1kex1LOtcJ79zJnAbGzg0zwGSHzMk29M86rzoOilvC1ulmdtkl7/SLJouyr7tn5vMCTOj8k/xGF/nXsk8hvmvHv4daX6ydTyDvKLj1PyOZlZOza+AbAMc7f+qD03z12aOcVnr5bhMy187nE6nBVyUDpMd5/noGIZ9d++cuktRHZUkO/1seQW5gJ3OIDt1/YH0ieTDakhql0hG7BQ2svshkmelrEeNT+uflExuPS1hWnyHF0hvIVtGklZp85GW+vLUZejabnjUMCTDGcN2UMpw3qL64VPp2rZtW0UhibZtuztI2rb14INV8vCQdJegk67vp+4yHy6/LefCgjpgYnJ+JUa6YscWyQY753BdLo/3z+geJx0Wd/gV6hsTHqeVv2MXo3IlZ5byrEt3Wv+8bvE3B9ymzKLjbjk0LEU7kYPWO5HdjJl3JHfkC86LcryUbrBR/p3z0v0MHcOut+TDh2RnybVXTkryzyJZZaO0yVU5tknu9EkmIKNyh0zKzuemC5Dko02QfLR8Ck2MyjI3fZ+MqguQZJ28KF8+Kd+eNOSP/5S86Pku0uE9w6cfSuEHkHWzwUqr93o+fW5XC148dlrzPNQylMdmN1tmOzSHZuWqM+RoBztAl8wh2V2fx0cu5fVTeNxtL2dw215xa6/K7PwVN72+ZnlHARZHxeR4wyfxhJ8ELlDwAlhICt/QuINX2IH/NgmAZ+5dARR0/DsopUMFPKNp7iDPaLygsG6IFDarNU1DpLAjz5hodjRXTaT2NIWfIGwJr+Vl86hct3PIwzDrNZfPG67KFRzBkXkjckbyBH7SfvI7vYG9/6vjDvPjUYtbal2LUxS/KYF96fb7DfZLs5qUfR3QbK09w758tWRfSgCWK3Nf+ozsNKfSg3lPk/GQdeau5jTFkINs4pSDKSs1phewmXq4rL8MvdV+x8auMuJJTZMBzkqyOhnN6mRp8p+WJv0cZf5J03x8GeBqN8uFpjWcfJJd257U5rw7TP6mvKs775bRb+dNr3j4OCttSAo5QnLctacTSJLkvPsEAYlUchQ5KUmSVIUtzTsh/4+GRNYyKkkyrJN51E4ZdkXZJfFsO6Vb7/RikuRMknxj0jdNmkbtNFUkyRGQJDcjSaaiK7tRKft2Uh6yUX7QTALINGKvrJN/5IxEJhX+90T+lRZ22r0KqXl+JpIk+bXhMirZHW2ntz3/f7DTQUmS5IJ3DkpyBvlsSZa7JclBTZK87krTJMn26F5FMsPcI8mkTL0yjZjylPOQP/f9kPN4P21Pr3k+l7kvyT6D49NNE46Q3Pxmf5112/50RLyjcUXkEbyCAh10UEGHKxhgERSYAF2BoYICHKBAuwcvDt5fTC2m7JIFabCSdHrJwELBLuPzugp+Q9u2Wqhc6HUHYSEFeGD0gJffMG3gadTen2aRrcn5nEP+PMb5vzKwQQtuyu7dCn4ABQXrggk8CltSIFljRcEbQJt8FvYgyQSSn6Ff9QDu/IDUYkiKIEGDhqTDUnX8jX15T5k7wCfFn3u7ZT1uF5KJMfMzRGXLlhdQe5uotY4vMmUWSIFROWBMSvLDRuXjb/gC2q37+Jmp6Vfb9+b8DR8nvSgpDMlcetsPmnqKPvkLaNu0F0zag0lHTKqYNIHDYUwjnFO6OIox1RKS5B8CGrZuVr4gKTp48h7zJ+Wq5GflWpXc4YuyV8t83OU5DRmUqVe7A2NN2LtNPwH8K0ALlwlJrlLK9GclJ+Wu8+5//EfNXf+45H/B27OexlF5zlnpuuTLn5bvTzjYlZ+s+Gf78Pzco6mwsX1tU6HCCY0k63csqLxjQZH8Ay9dTdghYYOREdMdNQKL4/LyjSZpcnU14WIkyXZ4YEvY++vp+wcw4q+goXN9qj/pdkVnRxnwBpdHRLk3x8Px+fPX47uSfFGSeQV/V35R3kDyGRSc6Ba66swcOLKMGpKp/l3XfXAATPVKsuCKm9jE/IixvL+7sscUZmVKaOZYYo6Y1vK3TJ/yBwt+ywW7PIIK9ucf84LxggtkyAGXCQuuaB4TMuAdg38zmE/Xn/FCO4OcMypbV8EZymp8iGgpWoqvokjmQHGHjuJl10JRPHAAiiKrZAZtfhj193/+zab5C0g6JKOQdJCcIVkEkhsvJIaWN31IpgySo0rTbGACGyhd6j7LPh2UklmUkopS8oymaR6Sr65kQSkpSSkPJXlTPkXNK78BzZFnOINyBv8Gkid//iCfIB3wwr4U+uSmsSMbbLFh4Ux1PoO+GeVpVSbwBmAC3T3slGSa9bbv0BwgWe3eHlWhI4Mj9t+Q3MV34y6WByRfHMaei5JMwJzBHkwATFlw0CXB+DqpWHj98Ausmz3eHv9b+u5Zb746eiR1n/0Z0xHNpr/gin1efv+vp0z6ru86hor+FX/s6dugLmhJV3dZ4AVHSJKZie0gXYx4YMQNyIuin3IupT9Mi5LhVorLZlHSYdTwaI1mcwgkyR+CJPmpayBJZoMkVbAGSZIkQ8A/CZyRJMM/Y8VDEoBnPCS5yy/WdFHJTskW6PfToVtUAZIzkLy/zkv7nokkyQSSpEV2CRONJkl+KMlFwCMA2+7SVIyle3hIkpxpIi1A3fWb8aCGvtX17XtMmMCBBt4jqq7/6m2XqUn+bWfzJFgDDnAGC5idv1swQcThqO2GMne7QjtLSbe99wroS8MMF8xTO+xnoOC3N/ATSuQ7j0q+05+VIwxLOD2DpMIBUCRgIhk/lA99MhlFTFBkqkU7e6VQRnc5jBvWPwEF3W1DKRxgOVzJw125zB1NO9zWBZxBsmmTl26WJOmnxitp0/p/BnSpSsGYs1KO4VeRbH+IJJPeE0qy1aVVfgUTKP8z2FQrSpvyOwTFUg+Vjb3homKCMpQ9bpc4ua0pyrAX63WSfAEUn0JyNc52MrqOruPNt9fNlYeHBJ0FHvj8DoW3JqV8KGVxCpbDmaOxLboPH3B0nJrGt70jFTiO1K4bo892hL5/2DTzy4C2q23bN2xDvfbcL2H//yXqknRD9asxHIsf8hB1t9qE45znwS8qmS8up0kP0bcTrpOSTEMclVnJZjgVP1i3xv1QDClJ1x1XYX8BTTOHXeh24eEBcEaSTLYHwzeyrgZs4AOrFGrajl2SU0g2TuV4QqcyxZNy5KwkyXUbrroBSZLUFetM5zZJcqxXnNEdlOSLUlGj/l27otRmic6gGSdsUvIHB23LOZFQjihskKygpdw9y+ntcugBMoOWyzso6K0OgSXtx2SrdvWkD8spHbahW9rkssSvW9EwXEK3aBP3x6pFfYIuk0at3d21kaT6vk9b0c8j2Z9aD6cl7LMy9zwqm+vzjNfbkCyj0h4mcvXtZb/hals9az8eUg7nmw3rUXVU2S3BLiRvz/ebO+0vVf2+vRTlYFdlsNZeajPawETfJ639zKSUUV3WHVRQsBZVyfqhPTtVSFpGZ3Iw4QqG8dP1E5Mz977No5Jpndkr18gouSjD8vIKzb4Ix2ZRUttk6DsLGs+a6NrdwH5xWJriz1OztIpce0w8W40JcqY6Bxw4LO1U2qRNptQlj3hRs9D7Ea8YnTku7Xcyj5Omi3Js1VGz8trhCcOxecd4uicYbkXdXkwkd5L3Y1Ps1rNSwR1Q/Hicok9Z5ex05qMVdWo+J5LVSWnSXq7WYLpT274r+4QDoM3uEro85InpBBz/aHdIkhwbDpavypX/VN7VH5SXXJ0NxajsG7b4CK7o+4IdkvMDDM60bdsdYZgrSbYmSc75cwZvapoC08zmUtu+pVgsCYdPOIPfSFWy3pD8jmXalLHVJkuTZKXudyqQnH0yxagXvfwMY9MnW0z41U/hk4elKXCJqN2uomman+rrZSontcXvaPu+u3TdMC1T2ycbJeuiMnS0bYoKSPZN5klmhTW7vkvWycrxBbxpwoSdQn8rCRMku4h2QzJRuAMKf+DQ3CJkSLp/UwajcoQl4XvrAAsuc3MEyVijsjTYt1fwG5jDPMkGSHaMSpLMYU+zuGSLZs6gW+hHn0mnZqpqkuQC0g4jFBybW3kBP4lBmV+QdbPHb2g9Mc3gAhwjBzgqyXIBPu59BKZ27ng0JCNQFEctmW+eMnZzwg9apgCH5gjJdlNbHWdbxztu14hvtfSlCxIUyKqO+klJxggwomkfOddxBSCj0j2DpEPyDqr1I/TatmKRAoWTa2flqK+bNUmSbnLJRmwuYPxQ9+vxb8ln4Qp2amckU0LzBP6ZsIG/AE6QJO10ziB5d2ipmKeiJL+qNWXlT8A30a8p3h38DLTJtku6IkkeYTcqfyjjOCqrHVEMf3p9/qqXkJzoomKoJGnvcINdipuSHyDprvC7AyaAQuuiUekmTOj7rI5fFpCdCrCAJH9V1rxOQ8p50AGn0BjJwrY2f8BWFR2SqVeSbyy4KFXJz4AP0zlAB0blB5xBNqFLuuQDYGO/gEa3heQMPoFTz4aJ5N/VNH9yrrLB8BONCki+2yrkNyUVQzFlpZxqs1M4A8mvIpkg2fZQveNp0YUmSZLz8pc3BycgVUmSsv6w3zYHVFBjP0et25GkEil0E0jCmonm07EzhayTOyTJPLp1YbIJZNa+hG9fPkAH++krQT0usuLpg11h1KvFTtoHmZ2wYJVsWv8CD/qoZHhHvfwjdzgE4Ng+6GjUfXpVl1Bg2gD3zQy+t/14NJnr9ZNRtNw0rcqibzqDx+nR7iAJLrOSTOA5otxUd93BSduP/SGrDilY7r8sSJKCisIELh+ApZP1veZPKerHyG7fptnsHoYkWUXjVU9wkvo5BBl9EuksAPoyt0lyXfbIdgDJazTeNGuR3gPlt+kTcIRPStrzEv8qJElOLyRJ0n46jHj6Ay1FlX5+UiMP8GcsMhFJki9wcSgl2QJzC+cLJHn9ApLf4Q4LJt8mCTyhWZovCgDgjH8FzedXpX3+rCRnPtNtld3L89ceB3In7QSelS9Akhn8oDFmFIqDO2bKs8OslJaZyyi//sdIM9qrmiYFbXKHAl+VJElmjvuRk15mNs5jkzPNs5J8xxW/I0XlDrMyKklywS7iCm6W5DN0UP+idKjtWlOUNUnSdXfYZUjgTfvCqLRgVFo4uw4bkqQCSOZpbg5H5hLnmxRWS41YwvqBKWA8/g4sMyRJst+1b9pi77vknKbc6q0OcSp6ao3hShaeZbdqR46bW2XM4fIK7pOnmZxfcEGfWhTma72+cj4Dp8+q4QhkThuLUofTONUBvlrr8Kwpj8pHndvtuCndLqx3SVfKF2jbdsA4ARIqxrbfIfnG4IBMVXtdlY/02mSi8IoafZsij28ZkrN+AxefYSrfyD5hGsvoR5IdM39/bZrroflJLyAHOGdu3RzbEaYr+/C89zYKKPA73s1ewwtTq+gwthXFP3HUdQHNTseQJFns5ucwYcJmWJR0YFQK0LbtEXxKCndIkvaqengByHpsFT8B+e+A/fRLvugBm/FsyRqRArD/Q/1ySA/6fj+AvmeYfeddP/X4odCaQzRPDS/ZepXV7sk0ef3Ml69wSox/4YAFn8AGuU9lOx6OztIcTkeSD8fj+GDe4aBllJ18ygy8TClM7qQhx+OzDtF5VO19MvUnN0Xn3H5az7RtO+xl2t4sTW7Y4wQOD/CNZv8GpeQXJe1IUpVNUXHeYWm7F+jnjjdQCPBAc5oh+TzpNFPaAEmyyVmZyE05uu2gfIJD6JK+z54n0Dm9HSeQ/AJ7aHa+bU/gV/EXNc0RSK6m4t3Bu96VrfbgH9p7QOZagGSd6QLKR3BUkk9EkmS/Ask610/g9OpI28IX9BO4woxrO+pDMtU2tdSozEW5Hpr4CD562DGNPWeY86HhBMSjb9vBNE5wcfsvx9AuY745mLSp91NtuynmGOMVqvUVzuASUUpukAQqqIBkEehB19VYQAUbmH4AwAU27jEaODSVBaYRoLuHZx2no1N732Fs12N2Nnhrrk8RbjsXpS8uoy6ePTDFMSXsw03jtsXTJSrz/aLs/VftnOcYS2yLNj8p7TmDM8A5Ox/BRKHGgmQAyTMe9g4dnJZN19S9QbMDyQ6y/dLjBxz0DY5NW2DEpAl2yly1zu5oCesG+m56AtlBRnQwFuZfkVFzsn5rE7ohGW0DG6U7KEflasNWG3t6GUtxBZWNIRktij4pRufu0I22HlVsQ7E9Rqc7bEtRPXffXWb2WTMGDnYMaXcqMiqdMmSdYouPynza93kodv6QXE0U681mZpLyctJxF2O37e1pi86ppzgVpT0fm+P+GhJzz/khU8zHUauDW2VRd7lR2R9Ee5Uzzcr+pCR9hgs4XS1G5Uil9GmOkFRlPzxKv40yykEdVHnDFMFZgaeMcth/WXRV3sFeudSldy5Nm7NfzbonsDwyJ6e4fOp1npQMY7fUwsIGGzSPynAv8Qs5KNdNs7KFpE2m6LzWptiJAbkt7XpIZuYTc5sMhwasZmf70/Y0q8qoiWTObi4xBsUTPqdwqpiym4Ikm/JY17br5oXVIWRlbM1jeYw4mPK1PxXN2jtTgTZ/0j/0quyQTOBC9vsR53+dYTjm5TxseQNnV6qS7JQkxyZJTroDVM90gSaPLBjlfPQUyWhejAYkQx6KjXJsHB222Fxq6LuDMl065zW/xwvUtq+McgYbipZuAj5FtvaS1ZX9h12r05WHdMklu/PvdMlDjjuerelSlSSSsnO4nJr3fLHk55ohuRvFHXqtUSh8T2T3p1cPE4VzQpeH/q5UQNLWUzPVF5BRedzXOEYkySUm/MfEm+1LTZIkc5d0D5xrTxF6aPu++x2t46FZbN66ZJ2sj8+LU5yxNHOpZc1h2VWKKce4hm58rmiapm1zm9yHLAk17QduT0bB+fEU27aYdIZuYuDflAtI8kozXCbsJyjJBfjov/mpttivg46QDHsV7wAc16Uj7Q1zO9Bd9A4/gEKSsZZRmI7c0VbHqWkLHRy18pqZ3Rl0T3+zUTLpkyUtMzDiI1g3e3xTkh3igenKxgbQUpagbSvOJc9KcvJz2dOtJnBVMoN/aWJyQJEh3eSSOcZflHXTj7BXss6sHLR3ZsA2WXWK7icOSnLzjHiG5hX6iqJtW7b4u9JBcjgeE9okBVftyAmSZAo7ZXjh7jC1irnWkkHyyk5/hKhIktu4m84LSfIn4BcHRg11mX+bVCTJTanjqKBgLTjAdMQV3fRJqXaABd1ZSQqS5G2NsEx5v0FlFQVmjcqqqIwNzyfNRUPyYj+pavsE3gHfPk/NGXR3eCRJPsHY3XD3T+0Wkp8l/65QUPT1M+CMOeHT7zABFE5O7aQ7xKp/sw6Mys+ADx0+ZwZlDl3SJfl+Us5LV+SOTFlJFpAs2Dt+hOTFmiRHBauDaqlT2y/uRTTWyQs8/oEJ3kNCLeAtTJhQSilNDqpHrYYcleELkmK6AIDkdyUJRthakorNf/CX0+L9ijMmVECyLTcRNaZThuQMSY6AJPlFJDczoqIvoIIOKiYiSbJhw0QyhVTl3cG5vCm50CRJsn93hXYkOcOnY6flGokUrpAk1RmkGlNWoCi6M5LslaV+TL/r4VdL2quG9Xq1/QgHhtSidFug8GXTkPSg678rm8+iGJJRuw9gLoxKBxzb+vmQ6RUA8yAkk9ab0PctV+BOjqrKvmnvcPn/VYgUfhzRTSDZQ9Z/QNoqig7J5V1J+yCzM6nQJ12XtH3X9dkoBWPokhusOqQAJMm0gp1N4DF7Rrwqr0r7BdiF5FEtwFrLxGwyNgYlM6sTcK/YOd72qyT5WJf2MTRGZXoCH9YNJEnhvIRkqyf4aKlt3+r7DlAUf+LBKRNJkvpzOGuTr5a8QI1JgaL4+OfI3JIk7WWJ34GC9fyqpLY5U1GdGSNymTK4CqjggetzSsWBJ1g0RLd7WNMEIEmWpoU/sGfnkiT5X54SyD8PSgK7hByabyCZwB2mP8IZnEF2qlChAnRIiqLt+51yg/b/SAEq+EFjugETQinJBmHXTutTYganCySBM/7A62eQTF0DFyWpqE4lUoDk2yBMh1Yi+QjIJAauRM753ev7M/4GagAcYdODG5yUFGVd1ptlnNxp1JvzsD/6pPQxXwOX/TnXjWR+bmelrjlkXbnQbJxJeyWPuCkt/P4CNkBps24O8G+WNy0R3WO0PUaQ/JNyhys4x04HJEdX8AJM4Ak4geZ8AioggTcDW3p75zkezust9oDM0zxUe9vG/YbpOPA91p5irzl2471V6tXO5tD3VvZPt6hsTmQbL5o59Gjb1sKhGfZZqWDiOTkjtktkSJ6a3Nusbx9Rl0RXVlnGgRNmBptXrLPO2KcAIzZYbVWHeCzTopfkgAXDTp3kqtxfq2oYNkq395NvZx3gaYja7g9Kdul5as718gRG5ei64+4KRvxJXdlfBiXZaet2Ysr+Ekl2KlDavHPFvrR5qEr6813kgDOaZkkYpsVB0jnAdwxJt1O4gt+Rzx660fqkKtv3Z3tD26aYE7pbj2ZraWWnI7idA7b2UVOYUFS+WpOqLHavvsb4yHBou7a6ZL6jbdvBpkvOF6UGqO4MUOBGZHXkyDv4PNnzCLTZumRpwPSsEaOn4AkWRhyu+AgqKJK8o47agumzAEnyg5iiW7sPyU69Mvd405BkxB2aWkalYDcqd6V2yVB0qH9Lcss0hTqqoE2u3U7JiyXlP25Q/PyKmr91ZDOCJEyA5Ax2iqTgTp+kpSBJjlckKNjpBFN28O5XO0xkUc5DBvZtzcDc1n0mpQBnMJUa3+AE7LQMMWf/LM7fAR/WkuQEMNmkI/bg7QvlkFVxhOTNPnteQ8v1VIp+wM/yqITpiJqzklSjQAWF1SEqBbOOSlqqMv/7b8XH1ylrAhORJGm59P6G6783f3FYrKIWn24CyRlIJmD6qU2+GaFPRk0x9AWb3l5Ay73ijzfIXROuesDGm9hYAgDm8nqGy/MweDhFePPJX5AzmJQ3IknyqGzi0MfeJH1juji0O8iIdzpaAGRBkD7CwFhgAoYPyiQhV0PUdmPvCe2nmLCZbbF22KDZeCGuGt4/mN8iQbqdwAtsaR5OJyQkyc6nxhz3VHdw1VWS6jrJEh4TqptC2Z8QnYoRFJUCJ3udbKMs1ve12i0rcDh3+/3S5DZOtchhis4O5ETpZhUKux59dsVN46bsZrBPQYE5KGpcytIe61lpd3oex1hEdyDbjiXiBh9xHI/lGBhGJf9XDZ98kmRWAeYfRt6VnPKoeRUF/mzr8M3UzjpTzk+ygfn2QzMeda2qtTmcdPs8N+u99k2xqM4aPtXloplDk4wj1q7WLhGnkNU0G07N06jM7fysJKfmzPniprMycbOs7APsswP7ZmyTeZmV6XnbdFXatBdlk7NyIk1Ws7rU6802zhE+7JUJE1k/3NZ+/AU5s9qXNhnh/ojOuT2xiWiTXXJ+OzZHHZs6Nfvm0HToimOtc3NTznji2NmX5glT/OpsxzItYTorTxq+b5pIagyS52VxCkwz7JBM4Dfdhz8qSc4kSfJJSVben7jiwnyhbdsOHLDYBXuSJCcx4pmqpLYLX1Dzf5ZK8qqm2VDszpOMnoJ1shrywEFr+wFGO7gtmtEmSB4upZRaNrBvUPihtsYxYXfHYFTatMWuKm80w275WbcaRuuTXcLN+KzGEVympsYYf8epTfL9Xdys0I4kHTZWVPqOpe3PpmneJywJnQPsCyxtkuy9CUpJPo6AtpSHhyQzGCpoKePRpiO9tqJ9TPgIqu3RTvWtXPIMySclP0g7jPBFTA6GIOmeQrHlDbyhZYpAj32u+A9pKcgvlg7JdhEuHyxWcSVSKDgqmYFUZe0AYMSFVdjwdX/k0KSqTS7WJEnmXPLOdmxbJKPqhbuyNFNC88JO0wnb7ODQdMaVZFvRF5wgSf4CuJtGfVu7336/gUckv7vdRedF+R1IkqOfLhP2cwMOGpJHu2jXDpWkHJWquIKYaJL2disCbGzT2+s/yZ8ccGXyi91mO88w9UryA5aVpYcbui7pkw+PJMlPV03A9GnWDfVQlYJPRTk1B+U7OQCS5JLwm3MGkjVhoglr9r+IZFZG7R8A1vgHnBLUP4p0yIoem5y4pT2ZgaD9CF7MOA8T7ixxO9Obg4s2NBv1NHHCKFAtt6m5fbYm8Ka7HtACJPnRx9AV/CsFwBOvWuOM1/wE7n8LMOuodbI0bfIHnpnX0CU3ZtiEyrPp8z9WNvpFGXaQZOqVMr8fNilqByOWpqK8AUiSM9gqAQdgmbRmziSLnnBV0gKsP5Zewzvg2ELyHUnWFWxgky+WwBVMkCjX6LjF8C6Ko8Z+gt4uLfwZYc0N0vV/x1ej/6DErXUXGDMTsKZcnS7NwOPcx6KJxAMwcjsvbXJWklM+Kpl0Whwu62nScVmPvZKvSp/zpJabdzotOZz/8yQ5j82oY142f77oAbcHbjZ1XO3sL+L0BaYyjNO1zEXHJrsiyTH2Xe76qLNyyoyFjdLRwbJkTUrzpq8B9k0B3u7o0BX9RbPyFcU/3WCDv1ibeb/H/AA7JL+tygvJxnDpLRlOjetEGSNJRZLMv+JwVF7VNJkTOkiGHJUr926JuEOH5PoKFChIRk1Pg5Ldtu/Kxt6RfAa4tBhDUrKxg5ILmEByueqe8wlSlR206cr+HVbNhVH5BfDhB6Sb3cYeJhRTT/FRSdLBBjIqBeMrdsoXwJsrmiT5oiTTDDmBJOv8LJKrOAB37jDlX7buaRQk7QFelWGyLwm3ApJ/MMhO3U4T11GFOiwwq8086lzUMio77bRQnYoakqcK2Y6SlD5Z2kSyC31S2z5JJH2yI4nkwxGSg4K5fapKypiDcq016/IEhox+JPkz0MWIFSmogGTVIQUrt7r3cd4NLK25y4eJ6guc9450sIsr35VZL5bV1XZInoFkZWMre3/2vow6l945K8m56Miqxr1f8YNX42nST4APaevxIFJI+xF5mvSDnwDNGSP6X0VylSmiFZJPQLMBgCQZT2EXlzCm/WHWpZvplmPWlpytXz/duxlH3z2HPCRT8DCOrh27S80Zcw3OvezlQ4b6TluzM/EOOhiWLs5dlhOVysCqZqfPuiovSuXB0ME+TU2ysakvQdEpFhWLFcPAXszxFQuelvZm38jP1haGQwPqqF3cOl1NsNMlDDelO/C0fMOotMn0j/xDSVeM11GP4GaNbmnOk85PHcNlf2mOMAwbf/pd3UEZ7tDsnX3bZ6tcMA7d5A6bUq1NnkRjSLrBqAxG5eAL+3IBF1xVwBwehq4rKjdY1TjHtAQH6B2gKkvTOr6AlnO4beDdJ0kuOM/NdMVnD3tl09NMNO2671rHDbyObuJmSdu2BQaQVOtH+E/Daxy1WVhHh6Sdanv7ohUuQFLVwVFg0j7PkOQdq6OS3McvcD0r69pd9cPSUsZzt/MU1HbCofnyBv5qmWZ8eEMAoAOHwSX75ghfD5ncvIbkMbbVhhEexawsTX9QhuHukSS/KJuclW6g+OhQm30JGLbZwZkkeaCipaKeloTGJvrpnEHya5f0xR1+05BkRHXsdFmUvkt70KrvlwXmPzty1PUL5dCns5IxIJmA6RfAh0kVZ7AdF/Dl2EwAhQIc8qgbFLcVSXJCkiRJ0rPzZFTaSifNXIt7/jc1TSVS6GflAkmyxpSVbVbK4a2+FmWffxHJLyIpPL3FMOK7rUIuUrEade5qTKcFkqSmePxkFG+5D8DHH0q65Pvl77lrgx503c9oyEfENOcn5AqHX+IAatSl6VZj+X7Jo1LmuOsOTvqseyR/GSG/KO1rEUWSdF1StcngSS/wpFzfQd3gIlv7lLDJIKk+02ApFN+uwnb8CyR3dI/LsTnBK9Kcj83YYpNIlmYCd2gZgfPzZ5C0lxNIkmQGSTok6447izp4g0Vb7SeoXRbYDCT75jMMU3Tats1mBm3b7mYNYzg1I+dmTdu2w/6ys88kGzbsj85h0mXA4artp8RS0ktVVnNH5VE5dMmbp+KmzAvpFIdnHcWhR93nRg53Lj0ei9PdfiVLedWTnrbmfPygPEJbj1pcSTHpETbq7wHJYUa1PVDgEIu23hM/6CDZDPaMpKBNfvZJVt3ZuyhVY1qVHNCBUSnyiCwgeYeekeQXJZMmkJyaHY54CRNIJudPdzyPmsDPMY5iOmx7jN0dkqrdgq5uh0uqKXVj1GaobZeH1/J0y6F4S7xEPavNTflGpYMOHsm27GfdlXx9tuT6Osb2rFq0miMbq23/bw9Lbmc7g/xWt8jofAS5qiqLW7p+RtM0E4UvHipJUn9FKusmGUuk72v7kI/gU3YwPFmTHiR7h/+BEdvenhx+oWmaKTt4geZ3YMb8YS9Iklk7p2/ZDrYkfP6Apfm62+M2AQ7Wz0MJByXJdx4HYG4nQLKLYpNBUvdeMcFOeYldcsZEFu0UjoAk+fRaFyA5g2IXTZIU2gezihq6gifRmOYdnB0YlW/okiTfgYLL1MMGNrBvhgaSRUk2sIFUpW3bO7ABpSS/ARU6mFWVm2/bXXHQ8g7ojAKWNA2c8jTGKrJoPY3KVGVOpRzLOGCvJ5uP2scwYCjetFFmVMyv75gw4QTzGJvmYYMfZAb5Z2Q7WHV2jlHW/QibrCw6KPM/AABf42GMBcAFNjas3TWclLXn0g6OoAxlVmZl6m7KV2XaYGPdTgtJzkSNSpLslXxfxogkc1UyJFvTgVHZqqJjJKGUZIvQ77Ta6+u8e1RGrUatbnHUVeeqGiP5kFzy2hkVHFRjPLb9cYx4TT8xUcjqHbc38AnNK3RqziNJTj0kGcMUTMfmog9JVhuQVLU1g2NCyzX8ULqWAr+dnwDQJklFm1Mt2voMWSe1+Myq0eeLRqUjSY3oDZmUrqiqyqiSa9jFNg/m0d99VrbKpFnDus2RNmeafVYOzWHS50hlAnRwsYz4WJRstNdhrVFX5bveP2nWdjdc9t919q3MkzY27fdF1FE7pUz9PDmOOh3bLA2tqWraz5cYT4dzGWM+jId1cu0wQtbJM/Zhckg2h2SdtKigk6xmdvtMrk07+fKc4x30++gclBOvljxpfrsORyteiz6CA3RnS5M3Nc0uJC3bDSy2cmgurQm09mrhclj1SZIpVHdUMk3A1qqWAfKuUTkvbWHoWPAnfBiS7tgm2Y8wt4eidNoNybDbxrXUV+SCf1de8YouD1XJ6FOvZyu02Z1AM4VslGRdleR885fyniKflGTaT2AxUB6VDkrJ3ka0bTuYKngXOzgXngDJiaawXTXNpwckVhnV5tnordOPkB+WR+2OOtF8QjMJR3B4QdrqWJpP3d4Vn40X0GSrjErZh/5n+KYkFcg6ueVqqSgldeit6CABkr9ZVkmS+wobe0bSxQiAy6osx7Yfkq2ZIn65KVewU6tW5Y4kqUqSX/GbjiDZKAdcsOntf/RSYDwlHMMG3uGAPsnBbjiDaQHdHW771cHKlJlU8Qb+U52maSCpvdtYLfhxVP4R+bSAbNT3q2N+UX4Hkqo1r8WTUfkPOoxWlSTp+JMD/gvyE/dnIfkvSlJDx1doktZVo/Jp0gRWfwNH1EpFkortdyA56KA8KSdl1r4qJ9Bko9wgSRbt2j5JjZ1wSdj7xTh5Lv5tS+nLuzXJYbITtFgTJpprx0gyu49+JOnPoDsw5CJgrrcAfPwsipNNBX9VknXeIVVpuedn8DMcT9/hT89oTPMGq2SjOb3pAU6x7QuuxuLhLf/KQ27Y+7RgVF4RJOvs+fWTvvH4i5IkXZdUVZSbm0Cpze77dcIfz5qVvBeNb3T9BB79BBnxR6DbDiD5Ez5webtaMoFfwqHJyrQsg7L97+UhEygFE9yQPIAkqe3PI0iSvv8lk+EATCTwDKjOWtbpk6T68wKSJLnAz5D3EuOgDiqSjV6soiSTdtZVQPJJ8qJnzXfxrGf1l8iTRjgoTCA5Y/z0ai2e9YLMIF1FURjFmCh80x2e8CjSSQpDB0nXJX2Snw4JVPDj+MFE1yU3+K4JkADcYWQ/UDmE5KDK4xjtAJURC0b29WkclRG2qLFLZt3S+bQtTJclWYrL/VPVRjUofXIsl6fe1VySY0fuR+mPQ7KX8/n4ZJdu7SXsDx6N5LaCYd8mZa8c2ZFlO1Esvs3TA8tFWX3b+rpeLnOzj+lhSScLIi0fLQcctX709o8L28W37fIxT8cv3Tp5NlTjOfT9UibHuYShw0HcXrvk+JlG8qikXt4eo7Kt2vTKxel2Wq+T5I403yBJEkmStBelyRH2lxPIR11AheP1IRqTywQo7qCZ3DFok2drntTdrFD9TjOapjnAro8MyUbZ6nfk7OeRUZk0JPu4KfuE/flwDH3SruYmSXJB+1PnFRsYbUpKjm2SyojL0+P+uM+Yp+kUjM4P8qjM4OzwUcnWTsiGpENysXXMVP42tsTXAgVAqvJx0BxW3zcMyTkrE5J3PPZovhYwzAm5K/9oVI67lpQy7ndv1iRzQ1rJOg9JhlJqm4dj+03MueRXiFzelDcHU4J/XTA84LKAWmsNkkI+T+rJNrEblbmW20q22XIm2dg2xIhWe+6Sx1c83WCJxv9IQ7IExQaSZJmUrF+hT7q5DINtR+Xfu1VF1yV9kq9TbfLVn5Sku4bGqPzAcAYZp0y7+Uj4UupJ+cXhcWS6lXL/lnWA86RvL8+qT2o2C5iAybftEUwznssJ+skKNfb2oPmu0xV8aJzBn5vkog/JlJVyvu8ODcccAcmCp4qXzIg1I8kEyRnWtVVcspJkVvZFF5okSZ61SWub5Jiwe8JFnJT8KpJ/8fD56fwBz0rL+XK+9j7VyZAj9MkCvlvLbZSM6M6oGRTogFP7YwHTFf5JeQE1lbY/aBowjfgZwnq1+XBXSHKBg3+Q2bnrAVudi7YEBaOSvbouuUHbITD83IzKv927z4wxlst/i/Q7SLIY32wd+6FPGH93z4d1bUcYkFSnbVvG3cOQJD9DYDMmzF8BH5bmjvNyVQUUKDB92Kjsj0BSddtAcga3rbtDUrUF+t1pgOSGqwNuVCyasNfwn+j+J/7zw5UMf0WENTciQ/9fyBbo58chVruHNfLFEoohmXcPfZJ0VxgHKlSoAKcNkkxAv3NOzyXGMzxsvv2EMZ3gozIgeQJDctBxVhZMvk2S8Xk4wb/aAQvaPjebE17DgSG7o1bqqmQ+l46DKieW5oIvmYN6xWefTFU5WDckc1Mc6Q/K9sOfLfJEPqqtINmyobjhG0i6g/LXWTpt0uchqfqo7LVTqIBkO9Zyal5xgokRO3Yc1LYpMuTyjmkBr58WmsKo5KAOG8+IDps86YofcgX7DVw/AKmLUoCK6txkxK/Or8BnaLag73+a7OaXtn/LcT3qbRjWo61T4XF1lOSK69H2WYdN6+t+ZcGnVay5ETnYZ1DQJV0yprugwJc/AfouOQPJAfZIpmFMnMFVmShMkHxS8oJn/AK734DT4k+nH6AhieQeitUxJHf/02Pp22Q1ncjb/ugfHzSri7rHLWS9as2Xw0X3kzOOSNo5YYJk1YFR+QF2AKoRKbT/oo3/RdngGJfomR1CVwiPULg5KhSeHc+XdoThaqGb4XRyhB1NYWKVXJmfT2oLM+WayolmWHwtSbc9FiXhY4rAJ3VJLcpFMSY6yXBq9lgdQ3mC8vwJf/mp++B4vPMmKiBZ0I4kS82HFAqvTXFs9lfMWmUK0/zIMfqEQZnhBSw60eD2j1yW37ImtYyooDXslTu6LRbtqwNG7OMCto7rU/IkG90QCmUa+XqGG/SMJC03zxLqr8io6QLOs2MChnxHgqQ/Z4KCZKMZp/oCWu7/+cPvjekvymfgDl799Al8A5ICoOCPXUhu+udcgas+gVVDk0ge75oAKphrL6igErmcE+y35wSHjUaebv0+KUw0ziPNhHORIy9trhkLJpSZKWeaCVOl6TBhsglM2JduP5VaL+0yFmUqykGJ4qB9KXPVXIp2X8NxvpayH3hRNgPZ9S/tsX2pV4w8z+XYDddwuSvlpIzhchxmMvdgOjl37mF5p22TZV8x4XR6/6wUExw8fHK7tTIqu5TqDB9Kn2aIZysY8mEf72kt5bn8Ahvlq6bhodw2JS05+XnSvk7HYx8Xy97v532iSPKERtU6r3k5i6eEZvWkN7LftGi91NownLQPrOcy1jDNHZbSo23bfRiSHJvl8GGfmvwa9+nNfqcaw06RJLmq0LZtNy2phCQ5VzK3R6Xv680aV60uSpN7LjG3B+WBnZ9Ve0zKOlnAi5pmfyYrO2WvrHPG3DmHPg9dsuuSTWldIW2eirP3ozdP6szdr5aqZH1VHltp86jT9oFkVKqekCSzS2Y46Bf/Ud/WiO6uFNcJF5/Rp5ac9aK3Q96rNf5PVrKrY8nk1Taw5Ec77OuPyddjs4uYkpJ2V4/JkkWZv/Ks5OIOdRhVFTheL8qhVYwfZAOeMaJ5QwOOx2GwrUsWtUeMyir5G7/jTj3jDs41b59vObNhRwO3L0pGDaBD8gjYoLnD1fDptei/a7ay48xV6XctH62gJUme8XBxUBTDLjrYF/+qQGZNEZzCMBx/7mWHJJKCn4gr2CkHpaA6+1twVJJsR2V40vBr0lwWdLOr8T9p7tDVK2co/OpoP6GW7c3hm5jApvu5nJU97EYlSX5xjMjtXdlWGDVMZzyz0+6sgWzP6DrmEt3aTMV93k0g6aAkK1JwxrDRBLIa5iRn8LsDzmAKfHj1vJZa7RyaLoywwQSS1PiibF6jsvGkS/IHNHJZZ3jgeJpwBe30te6XRsVc8vAEOpoGkkomJbPOSq6o3bphn2QC5nBGktx1cl+bc0rzUDVIktMP+AxtB5MmMFwAScX4zvH09kln1qVg7Bf8bFU+vk4n+PRymQBCz5ZmKpEzMiTTNOFZ6ZjzQAqz/8vhf2IZsk4mkFQlNSrJq7zmUSmX06AkqXSQ7N9cYd9nkJwhSbuDjJnmqhz+ZVS+8aHiWWe0TN0oFAphAAMDA3v9ld8D8ESSdF3hFr8eMkUyawNMf8afaAFqDMn3DApMMzLX0r6Av/otMoNhk4WfIHwEu1MASK55YYH739OBUZk+Ndkq96ghLUlyxLBXHnFWMqYMSbmPgmZ4ghxnf5pPAlb3kvBA+XmEVMwX+GQZclCOWADJI5JNSD7x2VnPfopiu5oFkusC+Wj5GTQ/MrCf6b1pqqWdXoFSJHy5AADuW1TEroN0YEWy7zGWBZ8bFUByVvJv9k9PNca78QPwYVpAaoyxrVDjKMY7kDfLHVqKWq74bYbPSta8ggnAqQskyQvu+nc1zdsZEyTTBkny153Nv+b8TyZQFMX7OCjr/KrkRdn0SqGYNpBkp//Xiits9EmMA8lvhq0B3GD6L/ELHAH0TOakmYWgyJ+Uf6IsqGCK789omAD4zkDb8uirqIexmzR2XdoypcPkHJ+XtthGp6JJ+uIRFuzO/z6eNB62tZYwK5VRqXNhVLpzMwkdbH0Vb8imHeEPoPtEXUiSH5B6+H7VLzJ23QSSv2PSlJVq7EblF+cXAD4aLkcl+UWZSs6JdUzgBptI8qFeSGosSls/DvmelH2ND5C5X5YYbhccj7kMyQ4h+XC917bPu664E0pJL23+hEwgM5hkz5H53wQkL3BIeGk7SM5IknYkWSIg+bl5iU6vqQCS/zk5rhvqjqdmGpXqxujUfMErDjSSeSiH6h4XUPxDc1WOQ7K5GfXe19D1d5qmWU7WaFZHS5OTRvpZJ6VAPwP98cd7myR5m4IkH4NOn6brkmR046cFeYrfqlJPnvL5RfkIXSR57ZIhadOyS0o+vjxfYny9Kcm7kkIBSKqqdQMWG3HAkE//BZiyNWNalTxD2o+D7cCnY+fjFyVsSIJ1AFpAgNlagAW/HAJJAtD1SdUbyjE7gyKZHC/e8PoKOliapIZk72wj65zbl3ZpOsmrQvpPhQwHkFmzfrOV7ZSAVygwOiQ5765KHpWsp0NGRfFl1va4xnD0hyWGLUd9Y5ru1Uq5ct7d9VSUmgbtdLU+D7Mmv9+bnl+P/sSld/UYX1LHrs67g/ULyYdajv48pmlx0/405Icq18xxt/rOqDw22TpnRhT9OSx1OZWcXJ/mrOTWPWRl75307exQMrxYQeW42+iSuCplx6tlY9OE6uSusUvu4OYV03FJzrRMSrpiQFbGyKivF/z0VLVfdif7YITN/FyUVzBgv7hpKcGIZlVW2Wc3x6sC7tQYThFwdpU8ftJpt/cpZ05Y5eBT3VMNOyXJTivv1zYbKsmf1BrWGz0CplKdklQlOdfmvERcyHCMaDMqJMmxeVUgyV4p9lCjQ9u23aQPk7L717ptYETbJjkzXiLTC9VVN7nT3Xl7g9Lm2Zql2Skt26w1zFWTatfxpiQpW3ulrTGXZDu/mpt00/Ks9qLCcVcYLkXHpm3bAruar6hzKaPCpwzLnCyZzgVUpY5JyX6LZPoYMGFWRqA+RG4h+YkMOSlJsi+nhC4PVUnL+fo6JZzbJM/3e46fd8fdEw67o39EsnDEfI7NpJRiUaqS/KTFlexUlbdxAxaapmmS5HYIuGuo4HPJSna3P3CHljIGj2xsBtPZ+zgK7VSBIxSAEVMvvxI99uGAAYwwZwftJ9rz6IngPn4oyhnMjMrfWsUdmC5nT8GNSFsTKuaZf1HmPV0FOiQDTwmMaJLJYUPtq8NN2a1uPeIISbeedaIpDEl2dxzBERxfwL9wnZqnJZOfLZdF6SRP9QkPLWXZT2B1ZA7vDjbKDF3yO5ObN1SUklebPqu06Q/K1SRJRnz6cPjv6SSFGt8c7kgKkqTe+BNwVJIUv5y73c1hOjRFnzz22cFfABvLEQVt8rujTVKw6i3QGb9qv5AkdAV/pD1kaeZmg6sm8r7+fIYLTfFLfldc1vjETnc0RgeT0h+UWe9VGDVMIGkZ8YxkpValruvkVnbKNCPZXUKMKIwytGclOV6Uux7e8TFGl3TFR2iTH2d0kyZwdodNnCNMJX/QTG7SM0VS9WNPCjbK7JMp+bwmjLDFO2CpJyXfKAdfjxgu3P1nDDkqQyWTkpZi/3HV6uhknZx0ncqkNnnkH9S+tweqIEmGbrQ+6doafdsewaj+rqzq8S/aOXlC+u6wd1GS9ycddy1vZYW9337rOkgmgMKif+WVEXflqn2JoUsGkuQMS+afYV/mZkhqPO2644K9ch787faoCZPm8g9yxccwGJX+oEwgqTqDqVeS7gY3nXfQ9X2HZH/0R5K9Szviz+I3MblPyjRBSX6FDv3ycrKk0yZDcnezPiofX6elflKm3OMGc4TdqMwsTfFFSVouC5CEgYtYMwV46bBXJkDyiMJd6aDijO5An+oMskNy2XvFxF4VE5EkeceYSjkw17J3PC0vZy0khWJoTuyrUvsYh2B6ADglXOAnW4UMjCQTJBUjYJiAeQIYOiTvaLLaOwPTBexhXxyflWR4zh1QyPq6XxmyTibwEw6AOSQUOKOvDxHT6SkAWHd9f9pNoNvlN3BWIGlvcNuqZh1pJF3yvUtGTW9K8AT5CKnKRkhV8vv/55u13L8D/8oD7IS+u/dW267gFzSkoH49ZK7XZ3D0he/KRpnAtpuyjsobUPf5sxT4GmOf36FpTO9op6yUSQt+vcAnpQUYWsofoUvavu+6Ljlj6jpIkqTrUpUuefwvk6pphY0dxdJRGQ3Jr5Z0XXKDs5LqLo8vjmlQynE3tEAyc9zlE1n1mV5gAklS9aInkFRAMn+D6356A38EunUDM5JXjBjHQSnHT0DSdckLeCxKciLb3lIwfHFQb6Bm8OvbzZI7+PjcKvhZXVbVuWZwN4Y7JFU/AQWfLTmjP4+qWJqJZm97YD3kO5aE6Z9Mg1JORZuEisBGuU6PEhImfvfvhxETJJf0wMN1taSpzrvy2aAbMIG5joNSKN4P6/WmgGsXG/Vg6KcPSBKAJFm0KBMgWXWgKLoumQBJ3//3pBpwgHUM811Nk580AZIW/ox/BGJNuBF5bZrkYBPYO7ygTRKYI/IPqKbZhD4XUvMRUvA30WztHYCnuWiXB9z7ICjJyb0hcrGEyw/XuZeF2lM4/5rCw5AkX61px6+vJcYJLcD2p50grIEKJvACE2klkiv0+DAGwAkmseZK5Ix/Be15QUiSzP44gyRJ5gceHvHwjAdcViWZtXXJ0nl3XljLo8NtLC6TSpIm/agou6yddprVTTpk7dS27U47vRXtdNBOT9m/7/VcQvIxc94fn8Fd8y6f2KnzYsmdnJW0XDtbJUmymv1cuZPstOBpJ0n2mWRSzfoRUEOSwy2RfLpW9TtnVJi0U8v2Z9akCzlj5bxZY52RaVSSXdzGg0Kq8rNlFmtmDUk3otla3e+UbLROCiMmDck8apeLstOsWnQeBeA8EGz1AjsdpgWTnlDbEUbbozIxMxRbHke9Qwdoq6fgfBQY8Y7bAicm/G1M/yd5M3M7sNNOqxOTJk1a0U3a6RnJUmvCSq3K3+wYsKWMc8IhzRHHdqCY9EakdMVE+wX30CVtfQJfIOn71cEzKrNqwxbLMetbbf4EVRlfyqAOSYf+cFUCXmk0tRWSZN0wZWUCJB1UDMk6qco2azsoU4ZkX3N+cVAZZky4wktmokOHrJP1BdYUfTJqulbN+luTrNNOWQFIDnWCLZLku2VT9Puvnoo57roD8suT8hlMWSnzqIlIktT4rGw+gKyTCdi3SfIFSIafRdKelzhq2iBJatlGBfAD4G7Kv2kjOSYl2VUoJx1xwILfgGZCkmQuMWYxcCPyCWyQpGYAdEN/m+o9q0m6pUcylXobYJ9z/s5usd2oqnxVstG3yB52HzxMF39pkqx3vwO7CCBZ8LSdzqctrrfXk+vTrE5nZXbH7hxHVUZdTt8aSXJatlMGp2V2kLzjFou2IYHlAyhzmfu0KTnNq1/EdTMbzNDsLIUkPaDYnhki/FGsIOHpuQHsJZI1jdNk4ww1kSzW3uAZkGfL5fZpfnp6FHBkVK6fdcaw0wnFVmmvbdJuSDJBklnZD1PbL21fGZF8gxGvsbTJT0pyQe74IHC8Y6vLMrOOfFEubk1Sr8x6oDj1+CMpkoIzJDkvIPOX9csJSW5HJTkoab4oSVqIor00rp7bHQDF/ghjrsfybN0EAbUir72QpL1sSpLsSlWZ2IfbOOu4KXN/1f4X5KLk6bBOkh85h/uPTyrZl2Z/tCSrJ6F4Cn0eLhtPcLDjQHCDQ7JkCujnUnJu191+wJSLksfNkkLBsuhDf6YpDMlTqb5te9OspOKf3WEem3VUZ98rB0wPSw5vF6j7++3LAoYOksH38dgUe46AJJl+VyeZ4WWBBeCfltMCknUyLfwHH5QzmLJOymsP+3o9g5uEGvg1pdh5j6SpOwiqSKVzTTd3tvoXy06QtyanS3vTE5yVu52g+Vnm2XbaHLhhCJJ9ts9jHw+bN3F16q6zQ5Jkq12Fsa96e7zw8qxrAKPy5LPcfeYdfEV/xAHn33XXVY8XJduzHpXxokfd9bJp4kldau886qpQ8bLprxkWLNo3bZviM1jKpsoM2013dbD1E/jPc+7wB/AdkNfvUoC7JnACzU5VGfmQWanNclElUjgAkuSuB3wWRXuB81kASTJXGHPGkQnLfIyYkC7cgcMNaa4Jt21C41GZtAPH5GAjKFCBocA+gkkFkjz7AuOoXOmKQPkaMJxnzwVs8suzL7AAydK0XNK2rzhZ8fL69miS7iDXC/TgeG1USsFvZJiWs1Lh1X52HnNPUGVy8ASWcv8xaklDDqvDqNOoYTDF0z2raizolJPuelzCvt2W/eEw9Jdp0PTGFyZsZKdNmblaoE8+5Ipk3yQF9xewl8rFaa/lxdvlI6KGmy0Y4TvNuX1GwTQ+SoyjFnSS1ZkI2mjbtvvXO7jU79qTHZKNssgj6C9UVaW2/RsbCkmSTO64gebZmqz3vGDCRPPedQpELoihK7Hel4tzWiIg+RjgRwsMszU0FxWKyh3mJOe56W/jvKI1hb9mhczgo5KP4DyOh6ZfY9Vfjwtu6OF1huQVn0ahnMHWkl3ODMqcVXhV1V4HbSx7nA8ZzkVJ3SGpAkmyb/sKBScjSXbqKooz2RbdjGbss4Pff/4SK0imaMU3yBHmlxLAqGzOvZJHf/8Aydz2GZW+z+pIWc5bqz/pZaTU/MDw54YTntrnUUnroiQL4KjpiB9wKqpKKaUkx+YMJB/RZPWrSPbNfNsgE5axhOVqLNf35zIRg/qduulnsnB3BWYqbNBIUPAj9Q+4h0UX7Gbq8TFoMDDgoXkwDiBJfTpDO2HWtGluaDDvhockedIDRQunI41t+VTQI+T+jIcskAXafsyHZvf9/Hugq4KrUlPCGLJYa8r7VZJUf1piBjfYwg3JsoJkAkl1qYKXJbTDQZn5snVJ6mY1OrCraCH0Th9gW2JgDl/JOGV73ouv4+cwxaFCHfvSsfecPAMDLR1j6ZjDNdSOpEtQIzbxBOu7JZmuytJDd4MH0iX5jJYHWu44/GFvHe+8c3OPr8pGuTxoJsIMqajuDMoZ7PKYvzpUp5IHQFMBJG80BbIc84zzx6o2+WSPszX5qfcrsg6HQ1WyKHlWUnADede//HQoyJOeM8Kfac5Ikp3AqkMuJNvehmNoC/oj68gRkjfh5YDOEG2HynnSqxUUzEpBwXnTYsEjowKS5O4QXFdSMK/95JDDuyrMyhzd5NCd9n2fk2eKbf+KgtMWe0vAUJUKXnXCNFNw9/WromDVPv1tyadrk2e4DqooJXulOgWPDr/HCzB9Jk2roFh6KPgUezsjSaYZfZ/24Ddfz2AgTN4vONemYktzAdQb6hkA9pplPGcl6yxILssdSa4XUBZIrhmUgvZTN2ICE5ihWTD5Nkl+a2iCLg9f29RM4fFxvZZrbHu0ge2YMF8HDplzZt9zIgdNHPdb2vMSk7J7vvc8ZQ3LUDKV4ys4qu1TN3fI4/O30O3RuCq1j+GuDKYjFjb7vCwO3fKk6XwHZzDFvD9FptDWTDL+7SNMPNN0I+6WdBZY3Ie8KwGW1dJkJ0wVw94VLTvgeAzDpHPJmZNhe8YAWkYcIUk+QrQmJEmWdEZjk0GyZWBfS+iSgSvYqU2+nkCz07SAS2iMyrcwYUIlOyVHSJYhD/2G7yCZSyZ/Vbob1B1PjDjbAr846SRzJFLAJ4bIDeZ1yWxoWs5/1dZzy6DAln29/a5koksogNOsJLtfzvsOKfi3zII/DVeYlGzWTVnnAnaaMtMvNiodJkFCxiNBJdzEHadTBjfRHiGZlGQ7KD8rW3tPWO/LYJuU2AOd9MBk1Wzt+TizMCrtacnlylFgs0sfz+0beUKo/K5KKkN0UI9+qjoqiVEpINk3LSN2o7Ib8RnaF417UwMK3pRDe/TwF+3Et11Hh4syK9lN66PbrMzbxa5LlOeiTZtc/HAPx7dVOUNR7KFekFwwbVGpvk1xWTxUQcpI8hHNZXkGzwlJcgFJUnBWVS76C9J61NvkuETnnBOaCpKqS0GSzHVJ+LIcAkmygGTelKRLVb4K4IwkOf8AbNCMVg0UhmdIBSSXFAVJUqig4KLyuI1dMivdoWyc7y9Fp1SLQ85d8pnz9npdahq7J0lyjPH61PtkikUZkr0zmJtHGv/0pyqnDN6oc5e0jjMYkndkSNq+67AL5bSO2mvBpMJOqErVuYwHI3qzsugC80VJkmSxlZ2yV9Ll8tAEkhck+Q74sBtg/WmG9mjj2N4PtTMq+2a+z7B/nF9+iOQOYEhqUf/wkOQdi05AUQEkdaUBW3uP+CluStul7dMtvst69H3sOTJpg83lAm2XoaDt09aAyb7jN7QTOIMPO31FZY9h8nWhrSNbVextr/2gCVs7g3FIw+moY4yH8S3GsBk+Z2ZqylnDyS/KPFnzfOGS0s0f1nb/4tqxe8iipHIN0MHZmZPz5NMWnGl2mbVitdNvuGo1gxfdsJ+arZ3YlJOzQZLLuUbHkXw/jB8O2SwpxhgB+aYU05cYX7E/UYvaZHccafppFHNT5MVNxy51lNUY45eI1dV5a/fh4t2/YZiX09qrPyj3Ab3LCorBdYY+I6+gLbCBN7quf0OzWvZO2iGZz1Pb787VOdlDUH9YyvECoSQcW22y2E7JGnYqlrYf0Yy6mAYYSt8flGycx4XurjQvehmTO9TpqJ+wJPyG7vGreiZI9qWAYtZ7Rq/ovWxd0j1mJP8szOENDB39fv30ZE2SxZWUm3LrbTrCGSxQkulI7UYYwB3sHfJN+cyHfAPJGlsy8YprUZLvIqt3tNYf6jPYIaHCBqNngpun4Awu4elvPoM6alu7TCTlte2v6ygFSSbs3T6ilDx5kmUSkJzcFTb2P921jCg1lqIkjzt/ASRBnRJW+8ZOOcAmbGCx6wxJ8gxam/b4VfQHZYPLvx5rl2lPsR6zZtCRR33Z7buinb4uS/cOyPij7ZcXJVnsHFMKSTbxJ+SCpunAqLT0JesXjftfwAlkpwUkn7QqPiK7EmGDo67dietlf/N2U8UdasUNPwFyyxS2wBzGtr2gWyAbvSpSfuDygKkqyaQk35AkF7BT95+wzZDg9btIrvpB1ROK5wnidC9cRQM3aS7rihFfsD4DPw307VY2vbJ8vv4He80Uf5aPuNQMyZ6m0cxbhmSxpmmaLU1/Rl3AouL4VVd7oHihmSBJOgoMv6DNJgt/ATweCnTrH20Dpkt2sJzxkP45IasOWQDJL8q0wcZays8BNpsqyr3Z9Bf4/ymNuuvsnHzMFHYft/1ThuSmTHj/Ch23CeCTUiCLfgY0mzo4+J9bJnATN2XCZ+Xlu5KfgIK8PPSs3N4hFfvm1NPcLdW7DXBDsrVPCevmDvp+3TxD368JV992Xf4LtQEO8PoMku/f+8MA3eoRLqdl8Mf5yxNI2jtsvqOUZIPQ78DhIpKsmWj2VmECfwOsmw7AAsms7JW9cklKc16Gcut4Kgc7bTFh9XWKjLooe+UX7JVZ2dWEvTKRVMBF15q9T2NS8u7bUck8dUblCMnnUpUNafsRTk1baD2hOsm+tyx4d8i2YspxRi3KmJRknwHJpBP2yleaivsWsS5gAleYb8Ajn4BMq7Jo1SEFT/4Z5/9IraFLrrAo/fQ/i2VTclVyVnJYlXSHTcmnz0pVXZWsc1Firvmzcg4XJet7Al+UjV2UzMOm5KJkl2pclTwpmbJzVdJeEiZl1rXus1IvNLy+5IyCUes8Vn1WrmXS5Hea26TYvStj378ri9jFd2XR/rk1b+KzMn3644ty9UcGl0iXxhcsbZ90xbSsSpLk2BR7JTnrs3JWsldSXalZqcpZyb5EsvtC2pFklwGGDMn+aGvz1nVcfEafOmBCksyrHorhMqEqS/OM35A/MCTrpO+XJ7zpj89KjVFJstEX5bt2CtdDvmN2yEd4gWc8PJY7jgsKqyPtTsl3ZZ18QnNRIvkQnMuHciUyldo8gnIGuwQFG2RS/lkh6+QC4N8t2quSpE0KBjLp2tf7bs4ln5HMUy3oCtp3TBEmkFT3XRna81n5rOxA8mlRLvulMSnnfWOUd8Be+dqtNujXxxNodvptXsCYlM9Kd4fVvtmYpmmvStK99dW37REkyfMrYDjrD5K8K2fQqsqir0iSX5UkIyMTyQkkVcEIG5sY8Z4G/q5MgAqSVCXrquTveAHwP4VmAqYvZLsY8AJ2y4Qk4JG/NRmVlvu/77Nv2tNpXSMKvypZHeGLMtUm45KJJEl9U5I5Ol+B5H9B6g1Un2y+AQXtBJokdQd/Rt//J/kMVwdOGyS5yn4Fy0Gj8TpEPsGFAokpCT9Rn+cQHNTUYr3XrL32GvNFKa5Vt7NIZvbaKYsruQKzTq4Uw8WhAsGsLM3DO2oGaZMCwMaqVBRabu/PbpX7dTva43XT1UanP+rx6kopSd1xDzQNJB1UHPF8fYBHf4ELTMD6w89AwQTukNSQQ5uSQAar5xkUfMtcaKZbjF/ABklyquXNw4Iaox9r7W3/hkxgY4VBS3Gany3A0wxJMmYH7UwUN1ilbdvZk1F5B6x2XWxVfVuYNIEXmLlgRJK7cVECm5Iw14QjJMn74kmyllzzy6UqpwE5Pme9o2nu3RjDd3JTHjU8rzQerXGVtm275HTZlCQnfYS7kjxdkSTn+zflzw/g3ZKX18dYlK5LdqOyG5VkN47KelOKcg1dl7xa1yVTVjq4+T67UemTDy+jDFRnNyobZ673JRf71zAx+dDMeLW7h+ewi/iiDyxAhxY/oAYOUIZoOC/LJ7bklzCHnhuIJ+qvbW+wHtIyotuNygHpUOMKfWUg9YRwzMw5UDXHFOcTJPkJ9F1Svx4CJnwKvXL98c0O/Dg3z7f7y8tLoOC9VXyEj0VZmr8Alh5+O83aZaUcXj0kkvMAFSoM/QiM8YIpHjZFF7CBx9zDsaQPJP1JTxFGYInY2gYWpUrTdI8iWzQ3JJuv35Ss89ftMkWUklYuS1bGcVRGNOdNSS6rHyrUXaNCl3619JAE6JcgXgjb7tb0J3A/kWkk61buBXX/IekK73h+xbo5NGtfjmtEfbSzMo9qp+Xm9zFhxFnp2N8F72C3H+ZHuPZMNKPz1OX0ULp25LkdMbZjzW6TMJcvempH7PaLYz0kh+NRJz+NyhiPprRbPytfL85TDy1TuXBMeGZSqnLUiOlNOZAkR60cfJIpfOT68O2fpvJvStuemqx2emoLDMWkN/yNy7Iakq4YlNFe8LCIUvKLEj8Due2P6Av+pgxkk9BSGLEB+l1RNktSd7c3IdnFLnns/nKOqGdA0n5zPj1dvlOzH/ouDExbxoL9knCDVcVOMqI1kfwrD9De4PJ/ucLBm0h+2qyi5j9Bh9E28AeQJMN0hKw5gonsBXCF6b/CTyv8gHRYd6AoBpw9un6dbPRTXUo/9jmN8/t37eL7Opd/zZtxbE90C8c2yZCsk9xBt9BXZ+j4JoorSeaNZNFZF0vGiNKO7Xkh6WDfLUm2zkSyaB8ZddB8I5nADsmVZH/x3heHPg/JOgca2UOh4MbG+jXFBFD4RjnE9AVjSChQ277g1xnc/5YTyVcgF5J1IEkKPwEFC86v4CYuogOw+SfGeU6XXOZp+JyLRssysK2aY7ePSx3Ol6fJmpe7N2x7O9jmsGKd6RIejHy8yEWZH0o2m61O7el8m23fR+a83K9zt97rbimZUnn2h3V/ce1GS3vpnJUbdusKNk4HI9q0O7BBwdJNmTP9Qzo6Wx2ZGFb2HR8jxfo874drXyZlf3TJczskE85KVc6WZLXT07bo67o5X/SozbRFbkqN4devepLd2CXleGUqRS/dmCLVdUWHuTstOI4lxhmjhozOTanHeFTO0Lyuq0Oxq03xc8TMocskwKxl7aaCcazFHrtDs6ifYx2XL2rqrvLE8XSaBvLHr9Fnuiivc7uE0ubidHZHi5fu6J5OYadKcmuTfaZ5yEbZheyKMmuvWr23DFDPWV2Rh2nJyrnXTi8PS5Lk2IzKYs903XDlbws0bZuP4LynSbLt7ZpjeeaHJJFkc6BoD5aklMTsaNu2O4P2fLXG7lzOR63Udj24thn5Y+HQ9TXZOgZ2SC5wQ56U/04HvFjTjKjAscTUXZVnbYojr7wgW7XZKTW6o3uUZXTmF539/KRhXqeEvQY6VzB0jGi2NrGobfN71qhcpa9KRuhnbUTati2AI3jPqHYAFDpINtMLeH8Ta5Jk3vToLqMao15pXtR+5h4wNf+iZBm1jfFqaetRbXWGiRfsnFEp8oPcwcsWlaWp8ZN98TAe6ksOd6VgZMS+ZO11KMqhTTJBcsVr2J3vC5rm/QjZYqJZ2v5PaCZSqMr5pDr/xE08JO9dwePgPFrJzKhM9XBPNhVQ2R+h9Kfwec00E81Aks8M1wmFonxRFhRJO+oy6hWvoPkJqVbRq0JyJTKAJN/segLJTvhJ7JB8chRMKoBNbYrvM0f+Re9qHBz7mtEX9Ksjn0rpsW72NGcmHHVqlgYF8o5Vknck0xi1WUKSiWTVPkpGDcnlYY13B0dIvuFcxpm2bYcKu1A29rsaOLZ4A5dRSWo7QrUT03Fp2eNRNHobNuSnqVOOy9Dbfp+l+aIXPPx39ndPGd0ZdNcvGGF7xs4l+6aD3eYpQMFFm0mHv1J25KKTMpdDJr27Nt3cUVFKVofR2fnMell0o0mSdCc32lpeaBrjiu1gG5zXu5I6yujwBK7YN7zAOFyPxpiU5BFJ27bZ+y7RIqnac39YkhdbJc+WTNnBBTb2vbPsRxRcwU6/fVXT5H/qv4kpY8KFbHvL7QW8getRkuSpJ31yGZXrqIQNPO78CdjrcVkUR51Vd4z4sSrvVWUgmW3o3h2cDh/UN7oYMSRbk2zGUTk1ff/e/GTvDpebXtipfccZ1F11brHG3YOHppvfdslPaWtnS7Ly7dhUunDYkyQ5RkHa7Ye6lGxsjy15jT4XLZZPpvkJsTQ75WPzgUXf5gfIRn/0U5PN8nX3ADmDzaE/xuOdAvyAE2h2uvyKOxR3mAAKzxr39VUZn/TpGJIk74BKJiX9qqLdR2djFd9BcoGdGGAgHJrzpI89OjDKQ3JjB6k6FCW5onZbYA7tFhsrHpXwpB78thiAyY4o8I3Hbw41kiTt9VY8GZVHEV3ybWpmpeAHoDkr2VvyzUYlnyw5Nqc8ashBGdr7giQ5L12R/MWGDpLdAj4qycnblnM9lOIduYIRttgOY2/J+FctqkidykfA0sPJoT822iS9OwxX7npDm2RpTspxedlFkuTrp3CgT/JPA94dhDVJxjeAGmNbN0hGJRUDSEjc4nFV+hFusuPZeJ5CJzjf4EQDG3+6sV/tUW8L62hxiKoWihEp+UOZtNMLrjEqWZ8FNjA/vQz2t4akm2zw6mk33Vy3P53hqUWS5A1Nm/WlOwJGm8Bn5b/gi5J817OQFOyQZAY70YO9ULDfs/7QT6CfnlskgzL7pw34CfKcSd7xHIBnJlAgk/LVYnTon7LnumPEFey0NM/slLPeLUl32xujSZJC/XJIFSTJEyTJgktVVfJT3n8aDEm2a1QWAwCXcg9J+Wz55PB3gexkg6J2unxnczsDXqaLNrjrQfHNKPrlimqVkZ1g2DxEYzqdrWLzOK7QN5iAnZK0lB+g/FyPur7aTnkDSfJAkswrkmtSsm9eoeGNSJLMIblp+Ay102fTpioFo6Qiw58MujI8GsE0I6Dc1PabMdo/gyR/AmqAcdP3fshD+fU6qmwH5YGKDZq5KC0janeHrxZoexT9O55/UQqmPutjpvAEPlxDl9xgyBckWXV4wAyEP189MMaD5gUXI8770eGHSD6+gilgYxvIFWO3vRxAtspfbdtbBZAMn5VkfxompT4pI0NZm9giPxHQ5g6/m2zCscnKFEeocpanMcePMR84ziWW8tBFyZsl+TPw7uAnQI5NOkhFKiD5M8wr7JVk9mRUtt2ORyU7XWmaplYHtFRcVhiQrI482cdT9I8GxaPxq38BRcKaK4RA5u4OSdbtGeqo3FGFZAJ34/oOzQQg2ShJ1utkjn0smoDVWL8DBevAWUnOA4yCsurKxi7oCpLUfV407o3K+351UJIJbLClmWcwWtIm8WqKWkrmSQAfLkXofzfCRadJGRclAzebz/bgenQfb31vu1EZAkLPs51hRPICu6qsm3qAvq+2uNXa7GkFNvlzdjjJ3ypDeTTkwxOzhJrPRChbk3wi4zf96J6OUrC6RWvSfFH+Dhz3HZKkoHu8YIlblkA7tbFTkFddADaWZK90yKz4A1PzxD8N8hcxosmvNE1zOTYd40Cy2B0qfRpJ8tBCEklt2/8FTA+wHeyT8i8xAlcA7QbsdE+Fy2okefHbwxQwDuSuCSzaUXTdj8GSZNb/Df9nNEiZofLPtrx+qej+CxhQFGfbOjy8f9zAyZOQJPM7+GJVkiw6KFcDfszxQ6Pyo/0+lW91sl+Ozf7nS6TgoKRLlg18P16xYPLJ9DGHJEmSnWYZp6nWKdap6k1PetL9f4Tdt1pHJMl+in6RSUmSZMEBByzojzhiweWIw4xxNyFXfz6YOdgeL5sdcJxw0JTxYVEyXdAX0zhwQFXuyoT7FJ8cFmxOEwqekd8ymoGl4ICfTyP2h9wpkmSnHZJnAEmXDR8NZlvwjsPW7uI6f4l5m3AFT6SAa9VJ2SJ3mCA5RxSXP9dntXW+ifzuJ2zRcn7Cu+/77l+VaZYl4QYLjuAKtsjuyRYsp+zKFcgNjYwJb8gDZYzWj/CCA1omh0PzuRyC5G+GAvf9+b1T5jc0+WHZxXjEATds2Krqvi6fxBXAFh92PuceF48k6z3OJEm/oLU5tl2MGM5OdX71JJcB+dCvKb5bYfpEmvaqnXKwZ6XdfHy+DMAcJi8WLZkrOOKATp1oGs2EJllv6M/gqgxNmYpONGfMAJPdSZKPaEmRR+TzWck66c/MHzw8TBOUZFmZTiUTSZLfROyGDMmED8s+C0j+LFKVkaRiVCeZezZMJGcg6SaQrD+2E5r2qtqeQVKVDirukCS/OlukY9hpgq2y2kFqD0zfb4Jpzp+aBz+U9QvY1rMCyQiXkj9gjzmT1P305SeQ6Q18AlU5YYqH6eTnI/6hbOKE33eUf/6vkWlkW2ufgQIFOvAvfPhkbNFskYV1PONm1VWmf9JSvOIvnd+U2rvH3najstA0mgmZkDc0NFskbfJA8wMASJJ9Mz1Dwye4Oofm3uCMyp8AcIWt5Wp4UVppJF+A5rr9Y8Be6wwM2CsVumNVUWkYlVR2QZd1e61a7RgTZDWRvPYUG3Y0lRM3+AgGXHzbjjCBZAtmAHd4vF6VL29INlvgunHHa5uHKV31NuH1Pzyu+52SR97/zfr1Bas+eW5y1oek6pt2S9WxPTJq1VZtlI8LfoBfX5LCCx9/OQ/4jl1UIsnVGs/xDsOrLahx/ffks4duJnn7aB1BTTFiuHQFVjvyNnj9hPt30zRjSZhLglzIdtS+1jJDkvwT/4k+kYwLOAOtFNTj9eyqUpf4omx/BTEcgT+ADRsmkglfP51hPuqiD8mtFkblVyWro861ZeCTkhteIlSo8F0TIPl/5l+1INlO4/CnvN3chuGhgw6eI7LaBjipg3c0aV9goungHXs92wvwAgdIEskFTmvOM9yV5AA5K0cYcITKuk+G5ATdsV0nddQWqrLO5600FZBs2hGOsOoQMM26OrTJplfKXwBH2FeHE5zB9lfY1kjCwJYmyZ/GAwETpLs2bf3Kji+xq30KgOE7UC4nV6qSlDL6lFLDurR1VFUqINl2I5S2/glQ2toe9GJwthfB0cOziNXHGO8iFhXPonEu+XQXdCefj2pnXfG9JHxVZvATPKnRuJ+i+2g0Kl4XIHkxGhfYf9VX7thz+MOz4NHO0HQXWCK7liT5DDenpWgpWnwyZ9H9iWb93TBTjue6k+8bIqfRTh/D84xsw3gQ38f6uTr6rHewOQV5LDN6Zq7P6xzn/pKh2MIcNrL9xbq+5+Appv0l3/AADxQrhuKQLBnAi0PSSfbboWpI0UF9DRSV3ag8UAzvaCnuYIpupGwHZQLJT/GJh0ckZ2gZ8S8rbKx10ai0FHXHER1FDRWm7w5nkCRJx7cvz/Zx8RRzBWecYF8H7YuyjeUFLdcY0zyQHw20FOt1p3hcHQtJ4Tdl9FyfcNQ04mYPmNuKwk5d8uwpvwNIklWHwL/tKGq7xpSV8xKSjVqKm6WyudgRmuGTg5Yi60Y7VtQSkQ2Mkz1QTABuJ3sioq04rnCG9C3/A8vnmJcGU3xVNgwfFky7hyRBSsjKOyVc3LRd2kxaXTbeopPVXnR9f5nfugqGgjcsU3zUjsmpWHT5BGMdXum3WNusRRWFvdIV720eiiHpkuSalb5Ikp+7F5KuSLpi35zQJH2BSq/pAHRBlwVN03TYmkH+EQAbPnzFP2CcHR4dfnv8/Przlx+/JY6///YT5denMLnkl+j82v3240P++NPptz8CTySod3zvlDk7aG3G9g+QbIoggeSs1SWsO1hmPjGWiE01JJBktQfJRzTN6GzHCd0Ekna/Kh0MeNEwq8/vIOmNyg6StECyAEhqFCSvlvPikjkCkl/QYDAqkJyRJKPjuD/yTbEOkh+GpH9HVywg2TyVDQq+TspOu6zru0DyaO92hhUkwJxJEkg6SDo6JFlD8md1gAQgSSqA5IhVkkCSdGzgE/UTc7EOkum/RCnpSptSsrgSe0qbU1FKm1KSTK7NLnU+q7Q5cqK0ybIvbaYjSsm8tCPJlyrjGPFuTZK2TbH4/An4jpQsruQOq1Ly+r6NsvkkCmY3kXX26kryRV/09knV54s6JIMyv+uTw6e1bed4fAtn9XmQpHazsl3sxbokn1ObvDlMuJG2TWd50yk6u/Io7EZl1JBLm23tFlBj251pvY5IbugnZapKl4dk0gR2Cguu8E1bNEu3ZWEd6/QB5/FzAU7kDCRnGVFTPG6QJMA+dE3O8OnZlf9W89/2Q/PfNpJPT26Vl889zCQ7Zs7smNkN3JSfphKmesiZnTZL22U7jOUIqxufVjYwZpczL2Dm9otlT56VTnK2pEYedWdjR7CEc7NbNIMVGdu/ofETjQpzWTiD7d8k/cwhjzqDn0F8fK27kaRNjayTM+17bNcNU1ZarhPY8VVXpjd8xOoM+ymrv4P9Z9axHUBSb6DGOIrNcgqn48K6idVYcYNfQJwZRFtx8sOQJoGNPcCfMXAzTNlMmY+OIZnVl5JkgW1Psm+mjnCDeYEyTWWBSVknR9gn7JKSnULBobnnf5ATFOAIv0MHoP4VkqrhWkByBqcFXBawXcBeSc7KGcxyBpc2Kb+BMi1g2GUqx4uyRF30lEnunEE/XUnOYF7Aq9IXlXVjhPFZTbOF0XallDjD3N7WqcSIDZruqH9RnmD2xLuD74IkOUbnDOqFLTC3bdsewRnY6bx0Z3AGp4TW8bR8F8n0jOQdUpVtb2fwArrkaQEfSbQp2uNChIvIstjcjhcDr0/brdRH4um6rTG6J1OJoLdbnVSGrc9qZ60U7UHt/l8rVpYXtEe1s07FJatnzMrez/qktBSORc+84rjWsJ5KqP2RaX9cvhYd9855IK9h3JgHf7iv2o86RmWJuOLyfAvSac0ZR9ovCSengxGbNinQcnyp/pCUYXeLAUZ4xqjkTHJWOp2yKxHDkStWdHft6Wdl0T4h1/eh4tvWJs0j6Iodks46zvMf9Ulf8Ft7ULRt2+2ehDY/e3gBr7mHW8Z0RGaMyrXovIAkkgDGqCRDsbT9HOZMYSolH2tX+BV5V76exogrTK5iQVXqcrQ3HK1JfdaXcASAqdDrR8DrZBUHw7/6i9I97b34r68A54Dktj+7MwBT5AA74Q0ZlNkxTaxjge+qduKyRJQP+QvgX37NGfh+VkCSdJ9s/0JbT9y1JdiNSkXhCEmSJPcAG5hU8e2oR1Uy9h9KbliaH1hPALiTJFua375RDhNgbyvZn3Js+4zKXL/aygepKc6/gtgwMZHmU1KogOQZ/CKS7z9SDH3ftmbxwOWc78C/iZi65K/Alr4FmA6oqzKmGPX9gj0k7CE5+7ZlVF8ekpyW9qajNfBV5+9eVtxBZ9++m5P47KYt2od2P8fDuPrxTDa7J3breLthhyftZB9gwsZyVXZ6PQwvZ+XaJn3Wb3HUOd0wHTajGJ0pYoc6rCQXZVN0O6K85PNPocv2DUXuYEORJKfivCoj+rld3SGP1mBPjQpllemGMxbtrWmaLAkt1xyxgWVTXmt9A+xwScgM4FSKb1u2gLRtW+3E4x8oOKqlYJoYdgm/opxBf0vw+6tDQZu0SDJW+p3eHHSSwpRL9pjVsgMkLSN+d8ACphO2QNf9AmfQ7DQB04J97pUEsL8HNxi8qRhVDUVlg64/kDf3RmIp5PI6oHbdcuQAFqvUJd9b5DsHxpjBQRs0SwWPbkru2wL+V1i4yyWvCkrdZVZ2HUny05OLMsqxO3OmeEjD2etFqfSlkU5n2V0d1fcpsmlU1tGtL2FKg9/0KYXTMmrYP1mGnSpduNNPL1eMsHfsfZjWhH+rzqgclCQ75Q6S5HTqPtiQWKYN+/LqYd48Z9/33VxrgbnF5VmYsOEx4QXbQ0FlHdtFLQUUTOnGk0OlTyObqkztdDGa8dfIOhZrCvpkzhR8ckibJDt1YFTGtCof2u3XDFDouqRPUlnH0GQadYUkOR2Ugg4qOuDQ/p/pQd8/rJFMapM/MIHHFyJJUnedyUml2yFJuRW1llKUj+WTgnWZ2BFIHpBxvwEzeIW91i7KRbkqG5tWZQbtBLpZ6WdlOiT9UUmf1MTWUo/X5hhmpdsp3aycxpRcPdoRZ07H5smaprW/L+j4vODmv4e9MvHiFscnzer75OhA1g/7bkUWLHSKXwt+aFrqIT/QH5jiGJ54UZ5Mc0S34OT7nbI0xXDS+yZ+6PeV23iFJzRTXK3ojh5tKFYnpYmtNtbOeuzf2avbKdOyPNQ07aExga7sQx6KJDldjzDFpXW7ZXBQZqWS/EreuIwnt/beW4cnJDlusy90kkttzn5u81CVnBNQqIBkVpJdXhz+NLV9TZguI6Ny1KznDAdNV22VJyVhi107MFWaK5Fvr2hmYJohgWQieQcvAMecnW93ZXV91XRkac5Zu03flWS96pCvNseYeXewOjSS7BJ0B3/jCGA3KtOr0tlU5a6m2bmRD0lyvzi8KQVJgrHLWRMZOJNsam4VMC0kyeJaO6VDvUC3GZV+qyzNDJJ0yZE7tEgyOka5waKbw+LbdgPfbmHRGQoqPO1v51WrijP4DpLWRamagG5ubwGj1XCD/LtSd2wX0J+Z35V1ui22WDRTTBdwhnnfJd8yI5KOOUOyANQUT3Vqksz/jmd4+Vua5j0pfLNVyFlJdVqu5akpbDCFnpGkXcRxWR0/iU1f6zDhCWy6hTCAb0iQ1M+HDMmoKd+NDnTdBAq0W2T3IeZR2E8/spBslcklSfbaZqXMIXnKJ1dwBh7ahw5WSLIAklWHQEXhcmpvOp00Oy4LSL4CyVSbjEsMXavrfgKS1At4CdgaJMMnkAnAncZn+2LTBpLs9F/o+1QDDjD8FfEJbs4ELjDpH/zBpo5005JVzI+l/7V5+xzB6H5M83ftK4zDfvffnzXTWmnT7t4HZ7Wb6CQ3pbR5fd2fQpt6x2g1JKss4ORnsA+zsrv6LKPqqrR3ntA0zUNyhaXFc1dJVjt/1XpYBxRarhOY78t97/iWUop36YcwMMIQ1tQ5zLT762HMLzUTXK+z65IOnrOqMqLbxaJFOS7tXYvokdVT2/cTSY1H9FbCPqGD/UWSJMcXXjmDDYQeYBqVfgrvHp5Ry6VNzuANObv5FyJ0/BctkA4WXaEBtsK6OXEGmUn+tolcjGc8bFe8ghtgN6LD+uQK1s/dEZJksZOSYDPqgL2uR1gy51PX7rVCFp3QrP9bxmiBUBNMFLXYowC48S9KB+ipWqt7PeoJO6bnpPUIWfxeqSrwHGOESeME6PZaPVVxatk/wI2M6B+NPCGfPQBfNCQbuwnrGwpvCX+tdhXRfk+S/7gVzCDBlJX1o4bbDODOvtbtRZNOLzWsLrG223FzPJN8s72eS3jCeRmRJNd9Y1ROuv79MkLyBEmy6pOs51Dx7RcSvyGVUZkZlRt0+zMctLpDl4eFxzPcoZQbh3azXqDFDXbK5QKzijtc4WZcyBnOADdoh36ntG3LFmkfoZ2+PffD2bjCnQzEAf8nS8Jk+jiHYVjzOcWDf32cZ78oXdYTPvN5Ua7z7WFJstE6j2gp5vPFPO5P1jSNTjKB35AJvOAOp9k2o5JKn9UE7D7PSp4zMNfSZlaSjDBNyl/dXEp1KIpiUPaZpG+z2WVLjrsJwxEbGD7sHBS/aF+Vvb7MxZNRafe4Khcl6bqkZwIkOWDV5x0+t3LQxIi7fTg3lmZPsWi+/0DyCxqyKGeh8PqAmeZqrSLdwa2MAdBrJmDaq1V5GNtdtD8y2OuTw4KfQJYu51N8TIVoF9AVadPYUpiYW94TgK7vkqSkKosm8A96TXte4tuobOCIGyTJMx5JkhzxVSTJktCq9RuGi5JcUGOMBUuJcRyowKkHdsKICrxwnFan7n/l11TwdkDDonP3At0wL5TxzePosVnkBRhx821eoMcSN2VC8ukBj2DKy58AU6v4GXjeb3rDxV7gHfDA7TsgF9ngBc6wdTWoOF8llhBrs/UyUh+5duK5yeBEZY9XPSrr5sS62aOcwQ+qncDlAZUzSXLc0IEXTBcwNCdgN+Hjy/Pz47E8fL/JvjrOq9rqmJyzXxdaJkDSVkdbHf2NKrUvOyYVRuRaUrtzDEiq8qHdKZsnPz6zU6YlQJdapr5VDIfmOEWnQ6LDubsoRz//LO1qf2VU9k7R50Hbtv1VD5cp7nONqahDkiTZ9d1lCt2bT2XEF+UAkKp0SIa9Fe3GJ+mQvAvvoDvrqCQYksp0SG5I5jImzSDJBJIuRuyVVP0H+atSUxw6RpIbJMnPYOjQIUlaQCZwaP4IeagN7o2mOQW79iuwajQF7U6TgCaEPMEk3+xTqD4jvXgZs56mkIdix6jgEnfZ+HRnVdjl/EQ+NCd9ViZwdKeoZNmQZFhW3G7BO8uGjxrRbxszq8eMpEAyaRLIOlk3J/CqJPdpw+8B22nBRllwhCT5BCABzNklvog5wU037UbljGKg2SQmYp4bbcuH/GGbS3iFZbhNOdj1HLKDBCRZ/3YcHg7kHWWvzFn0G7nz8vMbeMOttFdcH08Y0a8OV7whJa/IRSl4wZPnnPN+9sk8tslVmfd0e+T1sWdeq6ePax3f8wWY2yOYznfY7saGrqM/txP6o5KkTfrLMzKDNyTZRl3BTjkqye83BxRMRwA29gd+wERFBSQV1Zki+usRqjPIztNd4foO0xi/HtICrGO1e6hpcsZfQXfAuOts96e4+2RN8gfG3cSI2wlmyNmRTIvj3cMbmj8BF2voJpAMO0hy2+EGruAISXKEJPlGsZ8hSW6Oo/8cqAzZ5DyFIyRJpcwJ05YqUuZmY0nadXI95p3avVL6NI+QZG6TJ9WP+bHjMB7fl+7V2Y7nm+ZK05X9b0L9ewpMd7OUqe0HozJBsrUznizp4KjKDGVzWUBAVQF6x33J4HLHw8YlS7MTMoP8A0GSWzfPkCRPZbc9/3uQJFPEEZIEw8FuSOZc8sEuK8vQpzQAU0iSpGdrFZ/gEZJ8O+r6kr6F5O+YlX201mldbpCk5TYB/KfgF8KWJkmOmgrgTV3yPbpXtjBNxK9c6eh/UVqiCHvApDZL3WjaoX8KF6jdg0PfkyzEqVtPhbVZ18LMrLNjq62U+S2XZOZU9C9o1CDJF0kWxKu3MqtWdcWmhG72ZmmTuWoaLQidO+q8NCUJfUeDBOaS2rTT+hWGyZXaVZLPZQIcNL1rXjRiY0blW0o3pzh8AfkGFLSMaOc7OA+jUhbArLOSiy5N8kWXJnnElDhMdrPJWccnu4Aj38ilSV5ovl4iVMBEMs9UZ9+c23WVJMlnDGeu9EblFRPNhL0yvoj//qXZu2+idiNcEiYmDDeYVuXSJIUfvwF7kPSVZK/UJc8Y+1XJJ/pVzkoAG7d+aAs9kiSahwdl1SZJR9jSoAMeAY+saB8Ku0NSULsJkqxWK6si6T58SNp/BY1hyiExTPmeSQxT/jRCNlNzQqOf8gvb4YrBlP/qjJpckh9wtTwC3OzpFS66udOYHVwmwKhhzKOSu6EqeTnTNMYhKF3yUdcbmoxv+hmNBck3PjSPIleYIBl96m9nNOrvQLv9CGBUwAvm8qs1TfOXyRb7ftzQNJsFRnymaeRXwxlMStaBhLQZprfvHl/Lkd21i2L4CFJmuN6MULllFqjY6YZkFxVzODVjPDSFGdxXmr2jRofVTzdrTDD+UDYU1RK5vKgRmClwUX7T5e1pjtOtbdsSxWXZ1bkpKt3tCVWpJz0UKLQbkuNycqip8foS7kpdlO2GcVTSX87ojT1W+cXyghaSf1V8Lg6H5vqKGzABqUreYbGKYRdr4LuxHH5NbMKWoqO0hoKwuU6nbSCcsP/JqKYr/sefmwJ9wWVVKjguIOPnSX+FbjRIkpslzWnfGNWsHLRTOmx+5xZ/zWOoDV5/+7GM3xzlg2JB9feF6GoPyV6HEQRXhkhQxD+ko9+pPgg+F+zolfxRVyc3IdsSzJnR7rQFe8cbGnLQOtnroRv7Q35RvpZM2R4cWJXXtnhYPVCz/DuS6/pvYWVCBhpnoa+Huxa1o/44ynpodkdThqaBbocLbhBS5xi5Y6T2mZpsIcUZaHIlXWI/paxq4BdHf7KBrUvNgQ075YtSz5+mIPVHKF0WqHfXuvem+hzNFtHOh5xmQ7Y+WU1NvlIeiYxD8OBSpiHyrPbNXs/K5YhxSjKvmBaCoOfIX7rkYM0wBnjvkmPEc86jI9qxXcfHuz/ysdiv+XpHhlls5lax2vtk8vsZSXJlVPZtt1eqXkgGWyU5NHkEXzBi2pJy0KM1rukT/lP5+50kr3mSzRlPwdlyY6K5elgwYUKdFzTNRKEyYq7KkzXZh3uz/rBPOK1+tW+HpJ/zMELXt5Xko2/bAjdwx2I/yAWt4xMGo5Ikt6psFyTJDccbkkwOPtVx0RlJsmGiab+N7cD0BQo8wZDsVXBQflFaCioTzTSp+at9OTZwPBPp1hRnJMltUbLplQIkyZizsmuekKTiK7w79Gfnsiq70cHZSJIbdO0ZSfKf8bQoyUuPszrYTyBJdR+R5N/m8Jkx3y25oZtAgj19jX5zJkm+TboCm9JXB9xwdG/2fgpJkt8d8A5YckrZ37ZXSJIzkuQldh1UXN6VJFdIkuow5gtIDjoo/8AZSK5mxHcjqexaHkaSuyaa2XsFQPLNViGfkoVfLCy2gyckabnC2zAMhqSq4gn7TJIkSY758u95QpI3nBp4sy9w+KlkD69+wqwhVSkYP8VD7Z6RZHJ+hC65wouf5A5WtDt4/QBWl8mSqxKS/FGCDNRUid47SuKMySnb4ydv9vIkT/Io2V/ltuyTiT3xrDzLE8jEwb4izvv6dpe9tGOvrJO+eJb05jhPMOSd67qQNR6a6EJIemioBA1MUDuStHjgv0Gbj3Of1UkZXl1qFxL7ydLkK0SxjpWK7pvz25YB6JY0ZWBut8Acnv0yfDxTUqyf1znG59t6wXFsKjm2j+UTywk6WvE9WtFHFiqZy5MripP/jMXSc7eGn2BQNjZHeAIXmPUbMKkil2x0W4LG2vbTcGgmgl9g31uaXeg1fpPVfZlsoUfAZnWYQre3xc63CNicptAv2lWlAv+A+kU/2b6UupSqsZTnUlDMpUcz2lwu1jCXC0gyzQuQ+E329nh+KsSSi7smvEO2udMMJlz33ztDEtlevoYmDo82DB8upw1piT3m/Yeq8brQ/7OSsL5RAULzh9JvJyf/kKQzhSHLa+H7aOK/5lJOplsTp5WAqpzcRYAan47IqQEK2uRKI6jDjWI+cgKu/A3u6MIbtJwgzUUVm3i2QXNVuilejbG7qK7G9HK3ulmleVaxabdIPRtVn5Ql88OKzO2uHjXstgBz++725/LTLQlwcjhoSHaav7mH/icOSvLTbwCGY8NVEmzkJAiRzOCJM8oID/crFPvJ4Yx/B/0mD5b0m3y39Nt8aLbtFIFk2+6+QXlxavWWOHmH/eEaijp5S53ZjMkhKehSYwnJZ3+9gHN+8+fZJ9NKsY/Toe6yburzkimMaCb7gg9HJQGT91FtUvCzvftLLjmXcq2VUfnk79/Yiq2l6dv6D9tZ0Hr17zH+4EasxX+OCUfjlzD9tMGW3hPa90PFA5w9w+lK7s29WTNiIvnOhgtx/qp+11EJh3wvoCR9gunorvzOXP6F/e0HoIOOjRRZQaaj1hSmS5mW5Iqm3X7drzWs7N4Fk8PstMP1DXJIFPJOhqECzhWuS3Fgszbe6VAdvX7oOy0j3VI8KRy1xTQwWmzneUcpog2ub2y3cKgmoAfKNzZsl4IZIQ6kUu4aelnA3BLifFQoGxrMHf0CbTpAoIYi22SoOORK349mE7jTYdoAN9HrinwDNN2XHdeLQwKEzWmPxCL99TzpZbYNjxRNb2+ROrvBfZoScyejkOiOvItCS6qgDu0K/VoxNFkGJuAxOvmF4xKTgoVPkbJGP95g5icBrgAR+bdaMSS5rsP5VzeIqVk1/Yxp1Tn8JmANKHx1WMbH3OqsjVrbYZVq2x5tqtTS+BY3lZComXM4HFbu4bVTWVsq8RzGER/f36D2rKyd87B6xUKtauN+AZUgN7ZrOM9ftAQDnQrLTStrklJHEhewRBMAjwBJKGU2BxrlbKsExEVFpO23s3Hfxs0FICJI6KiW0hpSo1A45snmZIiQdxWuDSjKuVW5SCKp32CDMke0GuPNOWx0+9BstejL5j+PdEaQPSG9V+H+xlp5qDoAAzD3aoLhp60JOhlfVp6MWqwPAMPAYjh/vvEv7qHQv65FR8eDxt/LRCtwMeB4pVBcEs+U0zZBDvmmHW+N2yP2ft16xdRFZiVDwS0GzJIZeAW2rX9uqJjADAlUf2Up+ZDucrOi74W7B/ePVh2ZiqBhoC40i7QIfTwd6BRYsn4DRrb3jlbo2BZqcpd4o+9c1w9nfVgMDO2mOEmsS0dpyvHxJp1MKBPC++oRF0lE2DGgF7HLHENTPuiHjVuyzdqtQzpa9JZ0vtW95F5+sObFkvvlQ/EbP8Utx1NVURkeGl3S/1msue3bNeG2X93PgCTZXbHqoBB2FK+6ujZ/1wTRwlW98B77hM42Z+X4S4BfULjkK5GX3Te7rxNOYrE9/ETef9lc27urCdPV8Ve89xrfCxFWTvGv1Hx4KfQfoslNeXVvU/M6udepuSkfp+agved4AkXBOGm0FyX5AfjwpLyjzswzZUNSRpKzLoLiegf3DiSpAUrhALvu3N51WR3nJXoOS1m0YZ3LYC5ffyjPYmcfN/JwpmYjgbKNf2eams5D72GrvwrYtrbDEGxJels9tbYtTXdWtS3g5jvb3HQAKiUT3N4Ujr5LLhP/d7PnXkmyWcA0ftIG83wopuzgFClTPrnKBnflrIy6JeXDWwwwB3hVEtcX5GndYJXr7baoasMr0DMr+0MzArsDRVHSljYXVaXvki+X8MZtajac4ez+o1kSpv1OmfWi/CQlUpRQYkkoXZaECV/xd2vomnI5ks/IN/zF3vSOi9Fd4WmySEGIwPJYPNxpJinYJZqrFQ8rXmdAWJBlnGbMlyxjwUnp3Z8RUhLuGb5AXI7ZkyqDDnV8STQbkaV87tib1Lq26QQdkQ0l49dpR9Iia6NdtaJWJhgSw9Nc7eQBRo2ONHL87O7+nc0UkiwoOT53rO8IVv6hRPEHsjfld66fld+7fg+/dcwuPC9srZTarcrq/eLTJRUGg4hA2A9Hc/L1YJlBSYdtasEmbMCUua3pGIYw2u0E5DTYMYeA8OFd13Jtw7R5gNoBhfpTx3bFFtwZx1YNhCyoTZg/gBUCCyvIxFoZCBtp1dvEjPOM2trkSjDyDktDSIxp/3SOnc6jROKGkGraQVdGlOovM7xx8rqjVq5dDU+0gIT11dYKOMNaGVEh1+ad08TaymGwrsNQJ9iRRNZuW9SzknVafduEc6nnOo/Xg+5dbnEQJlfN+JjW9YCYLYcr/5v1AgWnOdr1jr3Ttx6hETWQf5X3P/nH8Vk6pHj5s89jQ9ZE4fzGhAZiTc3mS/Sx/SFbUtu8Two9Jzp31C06voQcVr2NDNHh1UP5772T/LaM4zIQXhA9XqGTRkzyxONjxKeqXOHhPNmWQ0clAyMxQvpS3pqDnXVj8nLmxG04KGj891kIM/zkkQlNT9AHbVrNsVayTGszm5tMzwp7ny2T1PFCfMtAq2+byl9acuIxb9CLeB4MaGg2q+6Ul/Xyfy4tMA33WtVMPSBnG0JhvcSVsT8NNFg6kxT7+oRHIvksxCehivYoVDMkYT84apb24ex6lzrxBVSyrGgZm3Kryi0zxmiT+fnIanUWbeBL59UMGE/4JfEnl1lhulzNpaVjO07ci4cCOJOXebflZM5TpLeZ+0gsmiUb6kAzmKiQ9FSTC0gXMKZXrFRt9ZKMh5uAUinDDA2bxaSgrUvRsOddatjZZYhZEVshNmUIg+bR3Ihqy3yWZdbOXbG7qO6xiiMnjwIdU1+sRUMFo6aAWN+kU10QT862cOS4u/V9yfLZtpJK9dDmiuLcrRUHcjYZxDlxFeR0cAl7/GoS/vwvx7mlAQv2laJ/JscETtADTEEgNMsEC24DfnhOEMR6Hks76mxd34R18uiB0F6SyM1oiuC4XUFxIR5/epq33w67hPhmcYQZGtvPOQ1p5vT4QFbTiC8zsouRt1JAhqSt4hy7g3rN79yv1m3AfFsBTrQShVkuo9BZLoowMMOfkgITDV0nA/2oXg7IRZnpC9ULL+ZXYLvlyqWQr4RYBzPl2VG/J3pBTXRlsjNhWrJMu0yLp+Ulf7tYMwm4zcN7Tl6tnGbyEL/h9aOV2nKh1q53l3own51dNTyI2un55rSsCcU/rFWrQdtOO2PJxys2D0CFnriACmeAU7nzf2Hxqk0RwelaJfGgT3sDEZggo9g0gJp8nHU78J5eK72s4X9vRjDglEuGZmqLQOrHILVmEBXO24djMkQBexofPTc9WHSXCtkkid6pnqVu1DkMDzpB98BofLNuNyioFG+3tw0dWR0G/lVrM5Wz38bm0pGRPF+N3tAenBTQ82iicBeZPF3INmUh8IofAGp4yR5fe2nZBrUXvPP/aJIhXQvhZu4hW3Db6m+AyWLNVIcUXchmWPJCVLd8SVeXkhIPuB+0Kb60HZio2xsyKgfjwuZc95tDYiY2cAl7tKc+BNVm3VnZocCLufRwQGIgFcaX2Dk+lYtwIKeArH10yspjQ/el6+FOzoGJHuiwRInc7C6EAvHE22vpfG3fete2pTNATS6dFR6eBnDZUulzF0ZvJvU9YJ+fUw591CJmv1yDZ2b//Kew10KG1GBkMvegrbaTVf0Ycg5pM96oOetAonWpnK7XoZw8wnVACjyA3eaL1m8U/zlCPBIWfnJKusWDAJlvopGyoqescJGH7rHgxDYGq+d4Yy9kljYWUvTArIxbH1ZssjKaxechGl/aj+ic1f+Vu4uaq2PZ/7XLnLDIPYz2C70z7Ih3yx791LUUVp+N7wTqFqGX1Ef0I8el5w++eRq69cILV9Dur9if3BJWLPnAKBpF2skcctrH3Avfrid/GmaOKbndhD87+OHvHZ7DOjF497w73tapu5v4fJDI2YmTO0nOkmsydI8+nx8VXPdlY1qSx4e5YDhSKhg33KWJu3s8p1ujjkrLW5NOIqvTK4MBoSw0XM0diwtasCDlii/jh9wZzlb6KFaSIVIhoRz12VaO9TCzokgdMMalvDzmxX9bfr58aV6xI0rfOCxR5+fUNKOz78p6pvvAIJmzohuTYVj1lfbjczhzLDQe/o0BeE3x8f2XxCRQubXpnOkhDgH67OOgXh+XPfz/wMnlU3sKV9ePVSfe+c5aeZiib7W564mRFZyPE7R9r8DKBBWRcarKfudS9YZbCrUfB1n3lEUPl3tKLlyZ7PmZjhYjYklKuKNAGhRV2t7tEO+7Ssm6JlfXXdVtXFZ6k/G5Hlrb/9+HYDc3PxtVWHGJpVd5geuFv3xJ8Y1cpqMxDqZRHivLZMz1OtafX/2UAlv8EajagpF64c/8vX3jslKf9tB+fY/eI6TQwx8MlGJbjeatMPwSz2n9SMKmHgWNkrGOHgyEleGhJjpsulGRROqrTw69cJM4msxleKeaHbf8E3LiejJSsY5nTJNrVKIzWCHQ0MGaSuKB0XSHQrfDKgndKfA8dccnEJHkW68wrvG31/yc8UvOyuPLMV2XJrtGamD82XuClHo8BMu9V6w4FuDZCPjgEn/Ex80g9OwBNdPz+Fjp84iKnpUEC9nv4L4T3eJ7S1jY1m0azso8k7mIFDNs51mq7kSuZBpwur7rT287aqrma2YT991/ua4HGxp4a9RHTkObPBod6fg0jWQbPSEXzp8ZwrzH4RAOapCiryOpDI4ltOxOBWFsLHa4LQwkGlIsp+JbH1kRgr6sLmdSmW1fpNup1yI194XHm9qFPe6snckrcfsufVTM9NakiX5L553Pw80Lex9+kxB+FOu/pS0gcVKAIBGXSOFNZiGU7uGuQro261yqFtm6NwPH9q44bkjamk/HoPUBFmT2bN+xaRvM168G6C2yPuDESxCiTip0mwaE/xnBW7ytXmby4K/cEz/TRJnUgTBXUVS36D+q6/zS6TwZ0IweqjR9N+LHheb3zjBpI+ymSbp1xRwkNVO27lK6bL8BrPlz+/OgDBOg6wdCjibhIin3nGwUHo5DrzK9K1+0jGL57k2sg1DoAZ5vJ2bQQiIBPc2jCNdvhuIgHYQEnXco5KUzUn8A25n/SKi+zm5qnvi1fEODPjghAHpik+VTfd3800y9POp74bVj35FNS5emeLGQu/6eHS2cTOGf34SB4Nx746ZicfpiW/osuBNXw9YjBt2duH4dy/3vX1qkqCkyBvLLK5kPxIrrvj2StDsdQDpeOMjyswzNa4/fnkxoCO8h1wrmjcTJWs/83vXi+0NYe+gjus0b/1C3Wh/2fVBc9BHVBwcdkj272rCend/IhqqH/fNZpytlRJutT2fq7zkIR5Wkw/7Pg+9clk8uTij+xqFk4CE+25L4YKAWZH7qVbsM92aZJyh4jrmla3uwJ+4s+zyf5k2C4Ie92lfXEw2e+qTOlhACJP7Dl14p3o0Xg4cx89yAvDb37B03swxCnC+Id1FXvX69O6q3QXib7+P36NGm6Gs+YyFxhHh+HHeejjmhQ7ItI08moFllodDYKguFt+WJCsmTERucUByTdffi7DJUnEonwHLGGfad+6qAxj99iwRvJzp7LGdRD3dG+Y6kXWpUisScW/X5FerpLuefKgUiQqZQW7Bz06z6U5iY1jE04iqb6n3zyoXtnsCs1/Q9YgpPwRSNcl5e28k3PXycg+CLWrhMXbXsHV7mjon98LWdASS2JzvZWJJhe6fhnjiAr75k0AYjiIwQvK0a3b5VsNLC9ntlDV3gZ8Qy6ZjRJcdqjd4vXa4uMEal4wRk5suRs8uOMfBYNbT35M25bdLrtIJ/z1hFC4SWrPaekoVzq9p6VukWw91iVZGfTZxhD1CbsMNV7+q+pMFHZk9bUdGfnOq8TXQfNOiSOusU1TMreP0UFaS6bQXZ+tXQv7M7gMOi44fbPQpN9E3Xm5ttrOQsBYfWsiNfK5rBGlQfAoapsjTD5cuX/W5wl2Rp1wqBWXW+RsX6h2b3fJ1YBoHFR83+q7COtdOyXUg9DplHk7qy9rLF0ehaPZp0+LSwWZ/LrBf9IQUO5Wa9lm/ZI33SW67ee25dxW635tbGavomcaByUDTQ5Tuj0cCONQdd6V0u7h3vw4Cj2emB8bp0RpXZbjz2S0U62p7sm1hKt9sy3SvwCOeAjozoBZMZLflvI/KdBbrNFailwXeq11s4uE3gK9khV8Z0729dbJDZ5/4lvbk53azyMIfgVCwA9+fOp+mfWzzpFfosuXrPUIULc3DOT5C79/vhY6C+49vV5p25C9/SBysYpm+KQjXCY5ATETz9AJufphQaLA1wPC/ajueEnqp+kW7b1Wj3SI+k9HnngRzFIMC+jhSlUL8rAYoWw8cHCvk6iGEqLUU84fPzH9sQiIxobMaAjd4bicmgOv+M0M5/m8CvfANGjXDOpxgvo8eQaa0w7Fe/TnXWH61GRoJQi63GOeHCiE0gT/jxsnvBY/M0LN1vCtRYozKDeT4OBTBMOlAoGsXG4jE+C6twNtKwJlYekSdcxyzHhIWOLnvj+MjJOiFeJ1vt1FrSNI33C0eK0/+dJwQHDpNgZK4Ys4lJ8ePphILEGP67KSQwZ8cpwtYyh1fPrDsUHpGDwCjDbTPNqPR37CzgL04zFiOvqz2KLV9t3cc2gqtKNCXj/ieF9kiYhahwaN9nB518VY8Yl9v9tIzuAcjRvbFZtkB4EXS3i5f4knhuPsl4QtI5fNud5D36AGL6tc7AeZY8vUQzLF8+DvRo4Bs1ShLSKm1nnmUWyaM314OSzxwC0oGnvk48coVoiWwaDA1KB6QCTXVYuA2/RLfBfhHvpu+Czqg81qikK7ASe2NRfkW47ea2NTqPKperDDZgjNEuQV6qlm2hxxrlMxmrMaolwCnF0kLS2NUp3j93z+pEmXaOhMCpFjxTJd1ZC3l6kMtBcQmHVw5/8pkq8j0J8bJJ05mTZeOj42Rdv3WxulichHIMA8Sh69i062OZe5vKG6sDwVdbCOZyt5OxN5uf6IlhZSFK4VpTutYMa3LVxmLNNG/dawax3oIDa2/mUwdYUCreicvUIR0ay5y6tj+082w0feaEFkyye9jApk3m8FB446od69XnbPSI6SISadqk1aPSMG3oIuJf3r86Ma24dWyd7eLMCxM4dKYHvy686JQePag8flV8uWSVp7eDsFXLlj99f7oh/RepMc6riVbzOU+1Fip57tHKpfHiQ7tAGqODILMJ75ooO8BMnQ5oTYVNcH3ErN7rsRO3zoBzSCZSThxDH714qogdJUkIbuUjk5V7NogxwxrRlo+8oXN+WE3PjlQDNE30+0lp3AJsoX3PBVGuAoxP67x+EHRJqZWaveC0WxoxLw7dZUOCi/Wr760l4JQ7CD9d2cdu5OlqeUT7M9lMRenRMG1TTDeVK/EcuutGueiRu6GvRx74V6RxlbZbL+ltSzb3+N2qLZZ0bZeSlhRLvL/6ir+4auN9until2wPxJh64oC9D+q3cZ6dgNmmqSI7vrTMGumYG8nijM1cQRLVnf8MN+46dnm/PWdyXKHx+WEMd3VSFBkflVntePC8q27DC433/rp9auHE3f20i0dHF9hLx2m76Z/Jqd8H9sfuv3Q3CDgv8cmnErXgbiOurzfhxfmZFb8eFIe4bFcG+yq5SmBFaP41f5t/zv4nDeO3auL5WKOH/3RxjZJcUqv3o1INVCbEb4mY1iqxJ+oIDQVa9bhSPSDnZA7x4H/FC/Ti8USlIPV75KtCLb9zOXa1tRBfj2cT5qaVL1n1cu0sEFdgzO5v024NnltF9bZcQxna9n6SJ7VF1Ur4wCMNWDPuuRgSR2zVLr/BcsSjgg3Us3xsWD4+6iMrFTUpNh5UxpWsoozgIv8WvznYM0kmbz1Niasec7bC0Yy0wxOTQcPjtFRBk9wOic87JI4dup7d92EfPN1tV0+KTTo0sZVtcIDwCxp32Aq7SDKwlpSDPmYT9to4DwI7e7AXqKUKV7bA07vxA/6VKzvgzw/pSeSVBv39fY3ygT07VJJWRKJKXXBFK8mlIiaFtsdv2oOy4J7vMLeyZAcAkyHDWZAld3AccO/tpDvdFvCsZA6HQPio0dFBDLYpFaLiocLlDd8tMV9E9h36aVnxNPrIudnInpenczKYKhGjpAz2YKGjL+UxNt0ZKAInHj+SGLo4b+ZyjULtj4m9P6JH8NfR8EFaUs4DPeARBZkdmT2odoj+VmcAJOVyYc+MntNjEHXqRpz2dP+HpxDNy2bOKSA6Nj/gZjFsP+v+f/0hDjrSDo7N6c8aFIBqMlfDNWpPtWmCPR3xURZh+oDVGQmM9UbT/Aki16OArC41T07doMRmGi+hbF8Oh5F1uvdkoqPnzvZ8356O5F/F0XxpMPW4hx7r1i7Jpv7YquSo/UNmM4mpN4/ZAtJgHunnNurN4TGgRYk/YT3T6D2DHWRzgTfxIvH54GRkDXwuD98dshsUsRtdip7fvAELiCqxguMo8esZjwoYsuc8qkAFA9JhBQ40hGDjWofvt0EVRqTCIJxI+xVnSLokkiPpYm3F7S84kwBV3S2SWNBUbErn86ZSuK7CBqsawBBVUsGvBk7jTNd1vpxnqbAY69I1v+EB74p87twgHf86ziQkDo1xsMiWLdYzC8wsjqICbkbG1UdOPkwZzPqrF0Ci2RsPJLQfdXeARJcOeNw4BSO8v7UTdm9igP3Z/SlP7q44tiCk+T0V3LDPQkLo+dE9z6MATZ/BCPicATWBAHzO/IpLeWWBi853WBF3sy8VFKIXiyEMTtWAu+TuWm6dEaDAndCMQnBDeN9xzRDclR0rDw254jllRrb5csglcy70KMKZOgR+5t7Y0tAweuZ1ikpmuUmwBVuFjZzbcvT/YTIX0D/hwcv/ojk9gqtKJxAHanB8ZE6Oo/cn4REO7DQtbT6I+JU+xAcffhWE15vCd3mfR4kSdvj2qx/8dQ1h/AgRv2eh5qEDlrKOZ4zXPsQHei+/7IQIfI8ao1hiBJhy7BANdcD7OfB0enKRG+L4uOlRPDa/l2Oqi7G7zQolUjs++IiULV7zA4ADNAwkDCJE1RLuFseBGBoumSCsSNZJOrk87xvuF2Z7YPwMGzARGC9tbUsB6GAsi377S5y3arlVHnkefukdzXZOWrZ6dHzCXH7YPejgD67WGk2trKw+bcZdflTcJBEfJniU2d58lIy0M3OyTlFychDRS1wOkV6FczZ0QgTK+h0j71GDtgfVdmDsL+Ro6X+TY7X6FurwxoUc4Dtrh52NQ9lYc/PLDnDkdQw0w8L+RtxxeWEz7Z/sNYEPEAkkhBgJYiRSQ1EgBbxI/nY722nWupBO/5FNaVeGhoyY2NmkD0f/b7+wBPYWgUAMtiKEAQrSQCyQBDuI019sVlMxI6BLWMbRcsCgjPl5flSNQJntA9/7KnFGR4xvAuXoKuZ+qRavqg+GKL7ppejKxJkNQzRk3HZZQUuQHbdKSkdWcCzcWnyrL0bOb0a9sL+3KOZegwwMnYe+4Q+N5NhCCleduVT7eC5CMoex2eSml3u5427kXKiwIV9V0od7sXSfftC99LH/Xcq6HpvuwsDL1TNvfJlNezKwSt7hqHyXno2ws4nbos0OHzeKtLfS/CRVMvdRQS8PCrQd+ItbFYz62NIrFR0c7pvQSd551zu2HjUsLp/+qldS6aUTIp2TSzYIvztoZiXrZ86nLFknW3UWh5lIDyF+OjrN4d6lw0nFd8LnUz5YdnfG6XZv4Z3cPydrWDwP8a0iq3ajE6ODFxvDCtlf9qzsNEvUsFU8AfDJQ9iJVkXH9F9w49sX5jViUPLeli+qlv7xpnl+iWV8tW6r72we1fXwPP9+vYL23hZH2P1/A8jCaRnscf8MP2JGk8T3cVTTpOAJz17rrPssn+Wkt97Y9UB3xx3semA1OTFPFuENHspzV5QOlqQlagE80OB9/bCbQyf8cgXi9CJDue//91iyGxIVWhw/iPQQaZRB+GnH0qglh+4jHxq00aHks3AtW7VI90mnZsBrOO+3dQXYp8cCwW7ivB9IvYABGuy451ZM35s6NHzSYa+r9/g18ZfZLK00vGmAww59PqXv2a0Fu6AsCflA1YkmrCSfmmfVoh9WHB7d6qcKi+V1vdNvhMjPGGORdfC19OyW86uj6/ZK8GKjXnV3KE3CaMDYN1PWs2bZMwFOLGr/5aI9f7+Fxzv9rgws/CjBZQg7hXu2y6bF4VJoX1pK64tDY/8GT0cMqcfGAL3rbbZv07ef9d8dzQuTwL6cRMh0Pbg+leHAX7Nlmr5rxPXenQzY2/xfbzlWfrimlrrX6n+azsuDsFFcpk1f/Qvl/275lzXcYeIvn8Qpzljb7aROdswq35+6/U/csXuhw10Hf9Psvy4vPnvMvBWKfB6GeFIRWNkuBeMZ3MZ1xTUOX0AKJX/sPKmubUjx7Qt90tfymfzgcaJzkdn7kfckDSBTRffG89eh83hz6gdp/xtbnXYjs5vd5fcqFSo2ye/q4Nfvuw6+JCfTSJpF3vjz1mUQv70oZTg5ariwEww2ThqbPw7sd/XXVXAJ5taqthVgeM+jJ8FZBI/jcgQ0K/jyEjDjYtq25SndAc4k/H4retR/Cje1917vdB4Vl8CX8BF8+AfszrTttPsnNieHB2u7QxiPDocdOnl6s5r96Pjx+5nz6a978Osvk+i/V/fOfvW2GjHLvads/tTJO1AgxiadmBHNW8Zc+VpwBL4u+4lqTgOV7S/f/jp3Q04PD1jKexaIrm9miYO3kkcvg/S3VP71ol4wcav+aGXD/zXi0kqeLi5QCNeX4KyF8JjyFUc4qbBQsGOAq/CPgb1R+Rr/G6VvrNJ4Ufqs+k/F8/iLgfsx/3r4NPgjNgzMZ036/0T2kbJC10zEPuf9ByP+uLD+qe/Z7/s3our8iKgLRPJCiQgADCxgM0UwAb+72Rllqs5PJbt0fx48nW36Xu6gRm+j2dO2YmretAcq/r1X0cnY9sJUxMk5ZPbgtr9nwrA/rhDw2O3tq02S/TFwR8cimmcnCjRINQVeQ2nU+25H8cBvGZDlFbzVOujOPktPwXPHJdMzOJMm7UIu0jHFiGat1lNL8unJ7a3/Wng97SvIzWlMGgcqP8yP74VTPzvoBPwNyKqtzdFeW5sTz7aTibX1VvRFx70a9r6I8DLvIq0F+byXIpp/7PT1YhXc1cwm3pMZ6/Dn7HgbvGTuH+7Xjkgh6Pybh9MraTTW3eK3dPDxWbrqqcSlcH/tvRN62cEZFqbmG3YuTrbBd72nMBNcGz42e7hufA0GX1J5mlBJLpST3BlnPkjZoyWrd2f0CMalnPA81RTgcJsIinv1tjeDLULr2dzPXTIsHkzb+vGJj3fRqPzf/HMvOPKf5+6hvEdG19+sdHZplr5ihmlX6i0vN//xVuF/RtEjL66pl9SJKEHUYI6vjWLRTON84YJ3YV5cVPf2mp4N+d19XtMhOxwnmY1RTNNlBQfe1wYYHjVmLaeaOPPXqc9qoWWfVHaqyFv9usMm/Fwdfi15lD0z2yxatLTdFX13dC7G76GuRrP33lqMfHZ9+/ZgJ/n7Mg42dFXmG/etuE4z7mwYsxHfiUXdQO/5v7ijVlfEdldK8bXOc/G3pqUWDt/RQ/S9Pskg0fqEzytskXo/elnmNveaF3MfO6uVmye5w2Ta/zd/L3NF0T+UuHTcjD071Xj/jpOtXpujzdkoiLIJuuLtq9cdoU7m2LJ8rXi8P6hYySqpdRqVNcBulx7q2gA2P15mZVVVv896SmLV0ilMbUhSWs0Nr8U2na6Wvtl7Xxr0LMuo/stL/6A39AXUyUfywSGbUT9M6rZHm0JVe7salSKnTTZRFS2ShgtgHrW8zR11xtzn9I2MgbzrnI8Yf8qzf+/3sNKfOPV9VCj2WZIcV/M+nb/mcU6TV3LA4T8h+4tjczf+fyX9cqN5Ku7U/96uPa+G+0Gvfy+qzX7t/cOfrYym8el0jyjNO6rszDHKVzV4S62TejYPzun8NG1pU86GnWhwfhgOVCoY3yd74eHlofv/qHWP6F1qlM6Uq7w1OT7NWJs6IpqHdQ/l+9loFXRIW/F3nWEoBkPRYivilPE0QZ3ze3wrhv79kRyfH4d2GVPyXAaidXpZg9ylYFE38UOSOTyoevzDBdiyse1J9V/lKf/dB7F+DP4XpzO+2J+es91a553e60FN02kP9D+fybkWtc9zN+m3AzG3Hu3rtI+OpK2ca9Oc3fgvKbtheJrSyzrl13U8++UmFfIw/L0SlsFZV5vns/XsZ1Px3UCfqoLvTpYJtamCF8lRsOQzH0GJOfdxdCrqv1XYT6N527zkRsX8/P1zKaaq3vvYZMzrVSveh/G7+SdN2ewTBln6cKqCKhKgh7qQ4BNJPaWUduriqptk7tYmblw5Xua57bobtvuWp+6U2NJhOo/xBqniaUGJfbjTOKuzUqn7rzH/UXZomzNpL3PuUpHll3UpGUPMspaauXz1rjuUMMSOslu+aRi3iuzZnq/PWqbxKJyug37yH1sM0+kB1nsy3yOUbgRy1STX1WTQW7g2WL1kalwGaStaAys7hzOtppeszfMY3ubel6w3fbbOaF75bFXwHd3SD6LdPw81TSKf38n1zL18qMFevXaxhWtntJxjWql63v7P+dHcG3lWBZ1BkuP/EX8U5pBMLm+fgj4XvwWa441d/PUg+51BFUgn385RJvIMsMDjge/eXw0jG+QlW+O39uYvkpAcStv39PAfdzjeKE7h29B3rqDUa2atHDn1TtjhtauVmXb835bvYOPQr+4rNK4NX37mMPzk8pLU/f6nGj5o2+/cVRry/Wo1YfQH/R9Vm6G10TL5od855ux2E7QL01/3LyBe97rgs+Klkg31Rrb2yMh+MdMptVDZ1iz+SXqIKagN0e3TaSvd92I7VTL++4uXvy00dXqqbFWig9N6l+6sD7++lhnmf8inyJNhfc5PyN+yT0cLn9fbH6Q74Tzgu0f8xIpGWS1V1fyfY1UC/3F/vYM7ZezqYP/g5B3b8VxncCa0nzfvbr3j4AftjK9fsOevYSEDZychrUsDPZ0BCc94909LFngPUvr2ciGox9on3c8fNCaPW3Goksmt19Qu/Mou9YkWp8iielF9huj4q5Pc9/KdWv6sb5x44XQuTclMaK9scLJIbkvv+dT8l+bCXLV5LZXm/cIWqbHTY6kkjlZ1Y7D3bJStztdLZuYDDzOt2jjQyF9wdQVSZzkKItV6bSdKUmmvR7l30oNPxQUf3scofHfz1LvV0Qunc+40+wf8NGcjabczJivn4KuW8UqFjU/7TOMFJCL+0jn53UnW219iaxzgnvn+seHnS9/yrwTb/Kli8y425rfaS5f1+U/EhZBGgs3eRYTcVuGYaPhvEvx9xPZ98G5mDU9349UEndxspG8NIPHgqiJ/P7XbB+uX5aL5QQHBlUBKgqXJ30OGNJwl4SUuwF4evzWNCWXwTgDftnly8NlTw/pTTLsvjGkNCzQFVGHy+OGr/q8MCVzxUPf+4vwt/MGD3a1ZfJT4S7Z9GFgwwrOUBFop3B06XI0pxzTu7/Ds6tPpYn7dejYJzputy5rdqx/X05ZKJqYs29VPrjbhw/IwTYF23dGoO6NlvMWPXqPZmzLm06b9xXZMu7Omm4+pg06g3+e4OHhhWumOi83x3u5jUIkyiJfwTpe3M190zubLhRTtyGs+87d0nAZPk1KRtZ/w3tcOFXpN5Rf1kJrM7/4LerKIdu78fI4xQB3X/ZrpN936pXNoPEr6zbaQ4Iqjdz6Ut0aP/PrpD+14+P7jKg41cwGrK/kV/lO26ePwm0Ys9vCs8/gsHsWv/fQK1lGrdnrznQFy03v5XPNgUG8r+5DauxDpkYTDqVYnrhbST0Z/wioSRarx9dn8sO6ww/YnQTHblLT7fbfDX4fecG/qL/evuaIoYznF8lpd2Kd08l/obaPX0Ys+k8YhLa7eREzFxtxo3fv3oH0j/K+lQxZcY8wlrfN0Eb+ZKsdqDD1SzP+3wMuowi9KHkCMOOFFRc8B86guFdYwxdmYPpyIaSrmRos/iSSPHFCCbPXfdvLgRV+0Z7FR+4zkoTCmyushkx3w4q1RHL45BjcZXWZFNgFT1Qu0XWoL//2Ep9ey8KN7U+++4XdFdOIb2t5n5fvbwfmsG+sjvudVqxJJwT58rdW3pl8FvJOWyKo5HlgvtfbZ1k8IZqztaOff+n2ObaLSHok76YOQPs6smDSs7DYOYedHW/+ZeZcxJVTxKKb+ifcsAxYxf9ruP5h1e4k3ZIL6aT5tnjXcBvzWR7n97nc0zRr/nMjB26/vubSBvOnkxvTsm4mdDn6n1dp0+W8Fu09PKl2b8MV97kW+SGOyOrG3Th8pGkx/etcmq2V68IypNeVZc8bxXAOk7cy2z3n6vPNjXPzNLs3PGqatL1+uBEaQFuj/FlQztbEWgMOB3C+fnjwcg/+uz1VYemZot3z32XWEZmI1M/b63/58yEZo8vsTdXeMVu9gdGaC1yBQrFO1cbs2dMtAhLGrDJLTE+CvybHjHSlP/HqTCY1Ttw+ErbVm3B7f3LGF5IBAbXAeoXy6y7qceamOJyRbVQJSVn49O7kdbe7rx8M7fnpjY7d18d6+9alJW0i99IICq1QiGto0PzmGPlGMHEsrzPSMJnnHh8/+l+v3j/8YwAbjaHXeOyHSmMg4H/XvDds+OZwvIeLqMebW79AuQjoCd/V1hNq0s2CLbm7pkDpPlyzPEBXB75NOoHXWMMdgPN824y1bTk7Jowua0rqaVQ46nDjAfx9FXx6enJrbrxw4d3ReWWqHDy1NxPOBVlFzKodGlEOgfK493r2RsLD+wCzitvb87Ja0wppMhOsq7GWozuswnYhHBz0+/ozbsT41synhZWn/pSFgQDULKXrxU7wts+fPmkVLCNxutYb4k5+pQs12IQZjUz6ZcZTluXbsFndQdyOiVMAu7LoE4/eaIdUNaPrWD0eHB9w+Ci54J4dSvC5PD47aXlhnx8LbgAsfr3My/tnluWjaL9RJThRuoqe/QexSIkDu/JWzhliQZvb9hAVrr5naekt7M6ZglViQHrjVnZiVwCT+16dT/7rwo9vPr5x2k4sx6kis4Xn6y3A/LGkAofjOzY2yj7HYAQACSoi1JU6HNfjCKTE/imIv9tV1dSvIl/2/1zSUqnwkLn048WnB/IOCDH9TqFu0Zu8/KSZLa98dyS+coGZm7k+pg3dZ6k3HUwbq3fzrWkGabGmYX0MtY137yFXD7Np3V/mDgPoxS2mPRBDASNxiQSj6Jv6hjey+wQemNjXEZqHxOrwigoeIot2oiIxJOPs7oVp4KFxUVhN/0xYI1jgpwoQAPympuEv6ruT7nNq2GTgI92/7PUqrWkQnVWlq1lJ6F1n5vZZP5arleDJJt1t5+OoYsmhcwUVAFuo+vtUL/gsEWW1NpFD4Bkn1KNnHpLIfzRrE0ZQsoThMCXEM5RP/IIU0NjcZXYDGHeVenf4qyr2MhxEiCQaQ3XDydkV0+4UlL/IWGBpEhIGzX4sNdteaxTEmZ+lwFmkvCvnN4KMHYWgymLhYP4aSbA099ZnYT8Vau1o1CHey+TsQwJ8FigMpI/PG+wF0TImOIr8Lv+Z5bckn7r6rg7NwAsB9gW0uZ0+7j0VAVVNRJBZY1j/vB+hiGZ1Pmw4oCav6wVOF4IufFoeQevfW9jq4VRI6mJnfNYXEtcAVORqYIJjTNVhjWniwNH+GXdiLPJ27KrmkYejRY9jC+R+Hf+/wZsvhEfyDSK+/SEqNMu9+Y4J8Go7BhoSgpwFziHkijSc9+tsnOaNA/dlXtWr8/aAlUcqBmMp897YVqwEDj6hRlYjTd3ePpt+XIjym5hCyMQEQuzogCePo6Ekz8axjeuAYRc1uy47RNLt9nOsh8ADq7fCdwGmE9EC7DaLJbaxRvJOBHE1YqSgeJZKxxScW5eyC2RCMGsSEdC1aW6NAV6u6xyH5YMeupXa1yuYblP8R62I1+sCuRIM0jau4DUbScmIXjIcSB6hKsTlrVWTMLNKnIJ3h2xPS+8JR3Y2q1uor8vQKla2M8C0W6q89RPjdwzfco03LEs8avR1tZ2B+olbAHh0oTRfDa+JMsFnTr13yCc4nfGvpQpTuJj2B5NXZs5vfv/dj/XhIym/cDJ+MkHbFZD0oF5Jpddy/92e/Zur/azh4dsf7p4LNAlryX7fSGRzM/VlvfjJMdw5tqjU6U3HyeP7JoQWqcADURCq2Wix6FL66jFU9mmzkhkgx8ZbzWJJEhgt2ptI8DXBAvV3ba5ezdtyJO4EJf+qVSPCt2OQr5Seb5g/fdPUR/uYvB0vhJI3wo/dyEoYptbaq7dHZuPkRvN86L5Psci0iVqPYR78+AshGkRkwe0VFg9JiAXEWi4u37Oq1D5rW5MdnMz6/iUIlmS7dZn1sAww+qAt3zlpTcbtgZovvVAdr9CJS+VuXtOh4qC1UYReXImdn6/SO/jjsGI+lXTMA3LZxIJZdzbEevLIbxUMINkbzGgKaAeOwpMUgydh297+aZ9PsBWx6ix9kokB8YyzKf0yOtMJ0YjEVWde83amHkuuG1eha4rGNapszxZAWK4WkxEtB0xJ+4OL+f/TwhXMdg3e9YKQI6HCKH751KZ0DFvnepS6CVFgapnWdU6MxdKro+FizoYmEqQC+6Yv90huv6nTaPLOgLq7dZyEqCFf3qV/JnTZiiIrnjbpfdoZQ0viBY8DftHTCPhBeGdTppi+MiIGT9++1RrB525wbUcBvJcorstuT1PRr87BRsMLegbM98tYnxstC1u+4ju0u49tvf+K8/SCE4di87G9M3LGD2nWlPNhLTO+bQCamkaWnxVw6doWEHnx2k7rdVfpjW9DZrcgiCP4uKnGcV5Sxp6dy92WnQ715jXzInC2rdqM+hdQSW7lG8bDgJNno509/6ab3XUv6vcduxyGiZd8v1C51lmToUNp2K3Uwj0vqEBmWN+KldjrwVZATzq5zc7fu9H62w0px23r/fnLmkOqbNSwnae4/3LRAktGoir7Q4AkG1kyLTotlq34tvHXbuhGDbK7E5SNc9s6KP5uc5HZay3KfJaU8AnhEnlv3uB7tSXdphj97CJiwDhBWWYcUeplaorMh1JMQd4ZbNfF73XmrF4uJ99W1KHn3/Jh5q5FyeEmWvkil9RPdpgSUUxFDroCSskkartot9lXsi0XHoeUn6LAkbb+YTEopBfQjCn059YApMj/yxpRDbzztfdMWLfwT4A2HCy/JprMoDkjfvg0Pk3G1zl04ZGGAutlV+oh7Ol8Ke8Z3zHpAfj8AIDOfnKkqZfRRMCrgQ8yotZZDLEX7U6wkN9JLhDnropDFvBRXcNba3G6rKzjaRHVjQTYPdiLqAhH8LMC/t9uVOhusD/kKoOe3cIwz5cf5nzXvizBHlk9yT6SUaIjyhFyO/qKNTrBUXPBFhO8sHCgybJGPedY96tFxJTYY/RNUfs/Hj6JJF3Z947dGHHmazNFO/cGExu7Vq+oycpdA/5fdx7LbZ+2ObcVSpJstqCmsQYYLJCpOWeLPpjj//oj+ZMWTc9w5Kkf7KbGNbsHnajz6dAOy0imAWvc5GovKe67SabzDGuzn/bKmdckqexILclD+UgMkpVBlQF0NncuwFmQJ+FfrNRg+avTVpe3v37iCwq2CXet0JB9mMOfXFHy79m3250UWwX4Vygb/UkYn69H1OahGsxTvC99//s9snPrOP4gSxruriovTo2pHyr2DHm9MynEURsCe5r+WH5Wnj9D+zvVNYe3hq8me2Y9H0+6X09a/gfM72/q2JuyzV17KaOknjM2HF5koLvwcflyqwQkx3mU+yVhWCwC1/8UmPfiMk6FycGTzhb5k2YYOGz9WbFuzGlNbR7StQRp2hDZ9AIiNdOFubKbXTub9m7FBUe0EpFK8jg6H/s+ycGzXdol4mRYEHoEiZkz73FPCKZrNmqOt84xpXdtzmhx/srhJ7E5WDX5oGU8EHK22yvmTNzn8H64C2WX3lj/jbPR7ZeZZH7LqtGwIxn/WZ+EN8nRuftBXC4oi/Xhvantwr8TRgZw0CoDpUsBQxPwE6ypz31udl5j1LTA9y2yPRPq5+dZEXDS3+yLg7GvqEaSvBChpiV9qGYD66/xGUxC9aayoeVIezsBJfNVrtPW5917quv6LPgv+yZvK1/aN90f1Ir+tOYDpYfH/WYHPi17ms3nw9OCmC7ylsgxuK9BLYT5VIriWK2rpsc0/e70fr/7h1RRKvh745Hr2tKKZL7MmkK9cE+kxJq7S5mQfeNy68jF0vrF0w2ZLPzFDmzQQ4+dNnv3t7nJ9hdeypVpehhbGTVk3ZxyiIwWab53USqvW2Wyl96k+eUX7nVVkD/LZLleHJTlS+7E2pd0hQvqbHubOZ1yQ37fzlvnb5TOy5d4eGzocRe9w8WumZP7cgLEOd5j0eULhnGg5vmV34vAUDJVXWS53fMG1HJ7RXLce44lugaX1xxUQh4b41ynKrwuUX9HVLi/4b+9Ss2rFZeriz3XoW8q9FsK/cALz5xmrI//yE04F/KNQPGX0r7BaUjybp/u2m/0h+6NFmdzyDmxGCznaU0lTc+3sL6GaKvSRkmYUN6ywxOhpkyO+jkvbVboBw1zxB/3ph/4htC1e+6keyUig0kPMJtkvy3WWe7aMNqTRQKnfsVVOzv5ewr/d+X1lDZ4V08NX4tu2nUNNbVKeGBzufAsPP7zbXK89vCHe5O+nZw7q3mEq3RhPtIKdc/zcQwuwbckWpsoCFVBFIq9IfzjoywsAQ7q5IJv+N6Szk0SfNIVbDZrDvRO1OR4efAPdH0WPMicDyd0YHLdYvgDp6l9D1cydT3Kj3l+QcLtEJCVbsvhc/N6ne4DuLwbi8sga7TXwzo3yVIGcKFeCqoMQDe47mIaGGIUkXvw8sqAmjsYutATzO7+93MOOWtBb5pr6Rh8z3TohrXOvK2ujPkZNxh4N+41LzYlq2uAumVgolQyurOUNV/igEN2gK/+2ox1IT6nsqEIlvybKkB/A+e6BVt1QDdu4//AgN2iP3cu67e28jyrs7Yo6d9ZCDJkP0Wc1L0cYdP8fHRrVbqyHn48sUNuhaqLphnfIA+ZRptJ0vTQvUV/ykGtjXpqMc1WdcdCNwXi3qc7yVJ32S3g9P5hpuapoc6VCbvfTDzG1Ltt7nmmc6uxb2X9Fm9RWVrgxUy90hiLSz52PoV4/WdHO7wnu0QxQ7JWf6o6MqjiGgVKxa/HGlllr/j+IlbMr8dBGb7mPwZSa3Oaj1tFDJwIc3+/YukIAw6kEvG9AH9649GvHXdujTwFpQ13ajRCtDYlK6XZOxzd9NLlKrBsX3sAA5wC42DxQNNC7yOaCowRANKhGUVnMmjLumJw3w8NRXyOHwyu31jLHUaHW/xE5ZH8vuaP9Ur+i2nlhmltVSMRzhvh1SM32rKmV+H9K9dlpR/rDq4OJPrTZ/L/13qY6m6Nt2udsFunlYzuxJthUwjiat3UmnYY3Z2WmEGpznxemU3lBSxfCVEV/VcYdB1CegDdVpzU4lju0uMIqPxqd3T4ndSvWpy2Qy0nxpWhwhJsnkQNsMx93x2NI9gsuXJ8flu+THwBiN0gRErabQFv+4mb45IndaI7NVPMuowyyEt9wjloTl4lHxBEkGnGtv/Kcd3icBsSN3EF9Y9M3rWJQMsYfuFvtT4/e4YB0lElf9CYJ3LMl20MattcH2REEHW1GrF9A7ExWmCq9G/SQNxGIzDy59bebp5tmeCgsXL809R/FDB8x2gxYdtWtpsjZ5GVBN2N2gVvRL7GMT5TqX7TFsBNiB+4+87rLum9dZ98W6ulSbaNj08vpnwvbTjeNIvVwEC3fGvPqd/zL9Wasj87QM9NPOhvvdKzR7vGprcAVPhQPWpVlp0018aOhO9i6Odgd8t63ydm0DJAi+hDw28q5qP118U4GKMCECMi+zA5Prd6ZPR3W/QQdP3q0G3LaDQQdXv3s1cmz8d5YbRPhOxb/ausHSDss0nY0umlgWt0t/a9TmNd/+vMFMpNEb1Lcp70kvsNblIpOFBxsS9JtvCuJB1NsyVu0iQ8N0bb87khK7JHrO/cbLY2hblElkjceGT8mBv+R/Wr477btxclV45Z6Wj9yUI9wqmZI5EdHBo2tO1jvAWdDWZk7J+rZE6hpQTHzo8z08625mw1/1KiqZB0F54675jYmHQbTZhcOBRs6nV2qkO//MoDYyS8O158PQ5X5s24COFm+vgz4HjtB8+yrUTMRGg1B1z60zSRu9EFSZzxdXYzVNnKov4ucmXPE1Nr32Cid+WJkaOQdpi8mzq8Ajwq8BN6+98axaSWdfZV8mW6cSEvKu2B0VcHwi6FZJsqDGh7Dgwi77sClUbLsBqqdQgsWnnMaSHq0T8lIx13rTEzt++eG2j7C21/KsVh7y+fVhAiowpoJhML8izmvqR07WLHL93OXVPfecGemmkkSnw5t5vfd7MxCc0Su97DHBWu77RSSUTnTk+H5CG8nSq3i1tjAuAPADbHga/O0qJDks9qiH7TgkvitufZPI7RVg2XMEgcxRgdINNT8vOgMZESeXPaoE9K4Gmz0J/Go7dvyArtc/YzPOAdzjocMdMHglZRL3JE7Q0BCNkw+zvSGKX452V/J8zdvWgkbJniQoxUMSdctzxSQS3K/TlME75ZYleB273TGH9Q4yf55j5+ASnxy5Z+LuaH2cHSuOaEijxwcKJzm4g/WFuSWyYyrynNjxiCwUOLrlweE02mbfB1Ul2QBZvF1JOFaKO8ZA1mctBW8z4XZqDPMnAQVzCsj9aPajg89SiDcwYUoe/ChfpJSb1RGRiFUL5UIQKCUH/r7vZU9g8jDeepKt4+tlkOrZTBwbd+rVOTj4JKU7C7OpF9Px1K8WtC/YoKk9PtydHCgYMHXquog2h9Eep3EzXLGkZKWT6lZC9KkEh+u24ZfoJWXpbWmiUpWKp0Iy1ZJyfF8UVYaS08oxNC7hUG7IEe3HZjVT4IMWTKjZjxERukYNSLdN6w0iVwlXgVndwX4dRRC7j6+twl/8LHfPsgoyTIKKMxEG/l8JIxcYnY/7G+lG9FJNvGxB87NTJdSnv64YceaaNlxZSUTVYfHs0ZN5xRQPi4d3J9S67vAuB0WaJIsAV5KJUFnlDH6bE41BFbjyby3nq4g+EkvxvHep4bgNCe6tutArFtQNz+WmRmkyL7k4uGTR3GY5jGsFNspvLJPwjEzcfNrITrXm6sW8k+SRU0VnetW3FgXfuXAXNTzjg1I7+cZjFmsdWyeF2zXxKYnqyygmldZ3T3LHgDdAyAY1xV5ClZsbnxzono9U4yRikwOfzzDL0HD/7Vq+3DaLbrVKGvUuUXEE6WeT7wu0qvu7p+PGldzjfAHi/fvWdz/9ZbMGKRE8riRP7pwI9UB/xn/chCr0yPRohaYmabkmkAqvgT93Kdr57rgFfvXmViQsEWxsds4y6fuoT/4FJkO/YuSpkPA2agZWJqt504k0zqLOvvGwx4LtA1DNfghTfA+EKW4UXQE4ZpO3Th6kz0x6bNuT58SVayKOi8d+bIuV/Zuwg6eeGGYfl9AsIbI4vBVXFBgh6dVXzwUSyeU5FwbH5SbTB3TukhtXuAkgzwUnFr9zfG3jJh43f3uQebmdL7xIfBS72ynGFdvzrU8FoagHKTkOtbtNY5i40Wlsh4sEjfJU6b7tGPgSHjrpy3jzUN0A/BeD3TcTeN3ePQdzEEi7nEvt5iG4Qpf42+tSKnAus/3aBjFZTNLz3VPmHXpGGHZwRbrTYDEd5BiKE/6dDbHj61ofp01LttldhyQriv3ggGLCtzoE8FTXtDRyTARZdracRhphM2kbW+nNIubxLWM5qEoM90gJhal+2mWNcQzdHEv2rhwPDn2+nD+9ID77Lv18PPBymZdLAi7klvIRnzMymAjXkKlMKi6cm8xYfvIoewgePFSN4h5Cbg4phrPbWkeZfySdOnb4G3XEDzEfFYttIVVo57zP+RSc/2S7/fUztKgruTkA7a8zlulMVtXobEsbcG+lfwW3YBgTvf7UHo+2rLXWuxzkYgDRPmgqnartuSnrJwaqkyvme1BW50dD+WFdpDX9VPZgE+BHVLdofPxxeoQTuap6d/avIuMdpBKPwnlEamVBJeVuBqPLKcKyWV034LVPdQiHIOAORf+qZTSKq3omWfxZdjlGygfJr8s7PKtgBhYJ/+ip5qjVCuSmTD3AGJ1Qr+lFWgn7gh0zVD0OuYz3rMxTR8gZ9ErZLUsq+7s278U5HxoPTBwKXsr18TgqlJYYfITm9MY1wPrVgBaHegOjG4Xn5jPLDY9yfnXJcsW20TTcVlibh54NjK3L049zS03ddTFYHwvw/l1GyLQAnoYqg599GASeGJSSOZI0/bAVF8y1mk9txm+Xf/DMZptjWkK8FOmHZ5kKCHVWaxZQNA+HTm6aGpd/IbgNSE9Je0kIFk6YhPF5/hHZNhuETBv4ANt6MAegVKQJDTrHlZsQd9gcqCjIejveO0N3RZLdIRoQMOdYZR4DnXknu/nPYfkJaDIpTrAhoQK28rBqLFiRk2rxvA0blVz+DfC+f+BH///XPFffVS+9PjH8qI4UmObJ6d4pIX0AqUlE1f2uv3jZ7Wo97b0YP9b+uo0r93OGgBzBZ7GvP/7uEk7zPFvlabk1QpIoSZ9xz4lZUHTW8XZPCKh1nKFi/BHJqMyubNZX/R8wj+5V7OfDpn+kk8x38OdgbpsU51cMm1zpKvvPoIHvlpL9riG+eIzqfVHN9WTI/s3rVo9Wb4wNsjE3ON4gUpPYBCRcOaX06xnDa0XSkFtoUN5ueMumvTrU6//e25KY/xeHNZzpWT82VhtvR2TDm3H6wU7cm93JjZC6Y8tXvpFqXqNMUl0V6MY/15zkafSk2Z6T/r4QF1+H4eHwkDGa49tJ+X0Ywuwi66sqgKpUKx9qruBYdv50QGxeamG3M58O6LYcH4XKxjULJjlbUKvateoVSegvUhfxZN55+kjyOb/hvjJjx6dqCntqT4PzAt2GMgW1KuFMHYWHMFZ97Ia1l/B8S3+GuJ+fOPCYQglnq5+XxU4QmqLYzHoSZ3KVT685YvNCLMKAUVYXNpH4S45etnNRrXH3qULOhhhFeUzkGX7yoj28xlVpiJh1Uh8VuFghitH2v8QiPUq/T6jZpBoLsnAcHTFspbLO901bbMpXdkXk76SpmWOtLkM10UWZF7UNlbMv7qtC5/5apjUGv4AGlrfYMHuoFaJ9ihFrHTVlm3HTHPebk4f805rZQYdhnpMXnTVerLCdMZP1dNkaWg8+lmbAG/F1CYYK7ZUy5IdVxhBW7LHdz6r0qBkVBs0kPFj5IghZdT6MNMNz5+NnVy1AQzM9QHLzT0dRBlEnTsOJNnvXrQwhPIsxJziSnQTRbDDhIlF5NBC0oyfhNQpjkMVy9sIdW/WpS+qqC8G8y0ji6erVHxDRxTQdTFYDshxyePvklFQdwmvvlqCaRP5SW8Ihc3DQa7obDBvd0mrnYgY9K856eYfQ1awJCOCSW8+3LCyZyQAg5YCc+d164T0WXwtm0hdmY2ZeqNbMPsuVdgyMF1FODgEuQbGtc4vCmm9x5s8c2Yf1ny0Td3WbW9Xq1qwrIOoMWnbRamSAOh3pQYMMyXUSGrbnd2EjakEVWlQ8kTF96ZQG5lSN/b8Zr9lkGdo7sYjLUeuyh8m+Zuvvm7VVlvBOK7LRu9p1b1dE6PLz8p3H3Lgw2kT+8Byjs9R5JHULLaiIN7rIFnpZ/mKrd5MKt+qh0Ts2j2zDHiJbcOY58SJGRmMAMxS+JMKZyXDoFHjh85ocQkG2130e50bwgCrYn5Mk0QCg1VSVnvhgo4S77uVPZ/hXtJ/sbmp9OPh2gzbaKPx8VHyhKBl74Lk6Xa5YBblu1R4ApyEaSWwLSq74pOgwh4QlHPmACHoMNfsggwCU6xPFBmYqZf0rYsYP3aqROOBt7roDoXN3BMN2eikobNl0XbIjXRNB9tuTr9m+/58vSZHqB7Zk2CvOE9te/eZTcJZfVQ0NGftx7JKzJwO9w9C1TxZkfcxtz2HqUWp1smxb3dYrlMA2/pZwz6jHtDoHiggzQ0kBq7DWwbIcUu47Z+efEGVTt+MZI/XRzXXQ+FphnUratzmoxY4YRN5O1/jJP32hlasHlkPeGndI6q1R8WaQvuPyQ8Njhzt2ybG0BTeXsxqOt3yMjeZJC/rr6oqrp0PFgqtQkipjHru0juSdNWC9ivqsC25ROhtMnrFYUzK/8HUQHNs7CBxz9BJOYboi3bl3dbPNYZK0zpBPHTMi7lsciNHLlFFPXf8Qlc5nabHJJbvMVN8WqjiYpwHkOTWdkbMyTNuLfCqRl3zWyghTLeJLchrfWapB4K7OoUo2+q75MiiTl0bzvYyxcS4C5sJTK6KayQrzYXmUwotDgbMqP6WgPffMy0ZbhnsbN/eWtAgIV2JBh5xus/6yUCBTsMTMdPd05APoEaSGYUiFRszqR3/NEi/W3MIIHPDqRA9324dxf0NNz3HtYlotSBQVCr/SVM7+ecQad3v97Huhrrhat8h7BsrvRdhkKs96QY5Lu21lLbbgIosOMf8xK1/gLOnWTgt0QytHJ28zFiyHL4BZ7r1opqNmpDP4WG9dhAGIw4x4C3DA6ZH47ln8nHUpgI7KZwX9GgLmtTveVhWNgbggxXOg9V2heRG5rWQUqGW4EdKUHk7PVWjbie+QBo7tb4pfDVPEL15bEjHfMlJgTUYr5GnTEmw79gCZXY/V0BHs10WkU4bnH8M9S3OJUxbravscfLDzEokEqRb45HbnHu7CBA5OVWX3TovfmtOxwuxD4iOkZi2TKZDHmUipapudUvqa25e06jS4wGU+XP587lrI7wrVMnGYAkYqbPDdyBCy4D0H87/5fPBFaV/oVf7FW6Qag6rF50VxWYrqT8Z0E+h2y15Ui6FS4JmbZoKibquWZg7JEjfJmcGjeJW4ObqzK1MyaY7NTYzYKcurEtRPyDQBYOFtmWcQ+S5BpLCt1gSJ1i0WVE9RZT10sY/Q3U5H7d0L87kmZuDF6bpCTI2x3IHEZqBDSDKqdm+cYxWMUl+OsQJgk19r5BQW0iaSz1c9SB3u7h+ioMYYaTu2LCy6BQ1HZGO8baFgNOhO8LeqKsEzPg5o5dr7gwjSwt+MShnFKUpxj8PvtWg6nFf8EKBOLlqBRi+ERJYTs1XunPt8tBIHGtOudMRPBpdsX4RqOLZWbZTOzYGfW6n8L64mbdQfCLi5v68lnOVj3i5UCxcTWaScVTpy7alD+JkON5EWeP79knkhC+ZKBEfnsakaPEIEHdUU0RZeqVAjXi+VD8Q+2mlu7h/PruwUlKiierG046azkhdqP7pCRAUKTA+fzwzC2VC13C4F/UhHli0hnbKuqOhdiJK54ctHSE8FbZDjT8tcHTtFwl56QWWneWQWnIaFc+Kdvgh+nEmuRi9HzI+FRy80dqtyUGc+ZsrL/357ifY9KaL+zOAqyXUv+ec2TRw8+OCO7+xrkkk1LOXtR4jbCW8AP1FkWspUx27a1otd4si2Fr8EX08gWJdsPom1/cxEqfMugdW88AV9Uvg0fdSmFlYH00R+ODB/4G41aAz/2GavtkPw+tiFWBsy/qoebrunWQ783OtwTaW94/pR+4iLeIZ5qbihlAfqVAbujDaWqy6ZjLWFVbDxgz3eIKAcKcU63yO08v1P3RVc6RPvQe5rMiV0lKvL7/fEWy/AcnQS7kk5RJCKx4yxi9VLmrDeJcH0SsI+oJDXSCrikwt39eEzyOkAp4RW10RtZ8B38IgMVWpyWMMk1c3uckTEEz4eMv71UGjVNWoPCUBi/MGZPn01CWuEJw7Fe6ZhkKkayOhNvAjw0Sz2JoMV4B+tykiOiPGq263m8HXea07Uq/xdOKBYyUtSbvQT5bXaR9yLWlwQE9mXSCARRdsjX85l/6rTq7Bxzj3vWNHPa9+UBy3kP1x/YjsFzgYdLHpjwrV5LubT4K/PPIeZZO89LJ16SeW79HuEirbaWO75XBzarkT4wi+9GkChptjJQwuNH1ZLMZlupiD6+Gk3d8D4IWtwl33cqN3oMae8ts0me0s1cZhap2PR0NW0+bwzzbgd+tlX4V0sqR9u3CvMtHPiEnMR2h5urkdT6RtEMuVIs2IvNxC974pbbVSJ92n8Lv1J9VYyp+jl8lLJ+9PgvOitubD1QOVg7TMeeRYjyNgRGEkl68WFUrgmoG7vl/C9pEUMdw7ov1EGEtlVJ6xFEGTg5lggC98lxO5GdUWszRl1rQRfXYUkmW4SWYVajntdvYmYO/DWpr52AKOjZYjpHT0WthmDYA1a+xIQgdWvOGQr/naCasHTw3T+G4L2d9t3orJcj659RBZpyuyjCUJVm7tk7VqyDVKo5O5nEf54LXfw5ld+LOc6tqwm/zju0rUzcQ6mBUDLF+esrAIS2FHXUEtq8YH+WNcVFyk5a44LK7AHcMTZmjbapa542wqhdVQzdRx1Lt7/FTJS9q/WfGDOy43G2fzlUNXxVk/yOh4Hy8/PIhHATS6FE3Dna+fu4rOi5JhN3/C7DWq32/qRXqFDg7Bhmw2sNL8XxsxaKO1+Jqqv+ubuY13UnrwykJ1/MBpZgfhWj414qneRJs77T39TjRJse4DvUPgB3SNaGnla1k72arNld1SCzNzV6SWYyfMUWPkW8g0ZTrv6JemHA5olEzMwvZJW6gi3DYJjme4lkuOuU8vUhI7sY36Ga9Au87rU/oaaWm3XGvQlLlgl8it9j/Sq+iZRcm5MPuS4X7KslS916vJYaM0tGJ1MmSVaZoTtJgxi08qtbXe3NBUodbd+03MdXEt9eGbEdlwcuk1lL4LR4HAsk9JLG7rVG0V8gNtmCayU2646U7PcdS9JFp7ht7D0AhKgzpSgbWCknvM2Myhnv4b16inMMP3CeyLlxTaMYU/xXTq5yDv7RPN3Jd3U8XuJNIaMlNCZ7gGQGjZlmLG94bZvKiktorLccD0nbm5XtcdPqwrlXeEQkEzvN1dMvCGFp/VkR4LluqHPuyDaR1rk2BbmRfN0hInNQKIzDworgzXPgSULUNgdnew3BG5LrkpkLpvz2l4KvaNWmuhKLyPqxmTXuWzWmaQnzJ1qGOQDfvXJOqNHvK2e12F8OpxPPxWIC0Hjmm/pk9NWxE3WzbQa/ZmNMKUJUgV45/X1nisRzK3gPBKrW+wXuln5+ybwYbvHBWK4rWDdmneiksZWRqzcEc98V0bOgwqArll0NNOHsoKIwM0LqWBPKKoPniJP2xXdrEuM6ojN4LLhTR2s2o8edmn78n1Wp0nmdd+ZHgdaAGnpUN7apLdz0NZIcIwTgW+956ngFLGXsEkEjLK47qvo81imA5jl3FHQmDSpR1MT3aazDTJU0RFUuv3feRXA2BFPuq5nQc77HdbNNURJX9JM+wX+4Hpwd640GAdDEU4WKuZcqOKKJU4y/Bayl4ZX78OfJswCgmTV7zd78XR/lHVlKS1nThw+2qRmQ/VRemRQJ/TNWW/p21NPOh5PS0DUX81Zrn3rex4dDotHoMt+wAmWHhz9eJK/zA2ngK/6Yqd7sMtJ+Visl2TsQYpqbgobWYzXWS3gnPjvS0XBYPP+MyOVdRTowJue0mLr+2Gzj6v8jwwEmWsdO2pZ2wbXv0MzcNazgxlRBjFT5oIleOhOKzeo9Za/OBRuN9Ho2SVy0n8bedBOHHZLoKD2jWiRzFwrG8/3sA6d+YfUrMqpcBpxsoJAPxdlgTD+Q4zoTrAVII+Fd0TRsi4qkYgbbKZWS5Nb+tiX/UuqL84mwqXVziIqmNEcxN5ywmtGnn6ZAtcoGBz1wh1coHmKVLqyo8M0Iblw2r7WM4cmO27EeXx1snqe/Mlgt+wu+lO6zdlIeUJ33xfpEuNfNqGDgjQE6DDBnCiw64ZcuH52t7FSsE8xaH6RX9xaoVmfknKSZaxznjphps+NpoWh1orLZaMoZpPqYC/LowrtrM1RZE0rRMHmtV1DTIsQ8BUZX+tikUqEvRJ9hQr0BS+1wgafb3c/S0wBgdhV8qMi4Od/jnQrWziZiRCP1UMope3FRIrbIW+g5vPNuT1gPmJ1Oc7AA4NJV78pk9LZpcHZ0ae2Il93AKwctqsllu0OWVRVoowHV4cdfiaBD1EPprUPfBIfW4bAbPPLFKqyZwrULnSmod20Nr07KAnoVTrrB/oQKDlFqreSQaQLBfKzB9h9MBK1RoNyQVCu6jZy3oVMiEclY1olDbQrh4VzsdUcw1kr1y7ALra8dh05lAecPKYwTDKdWYUHk8COIWEjAdFPmMrI06RMmyHjE/cjXz1oqtswxVGEagPS2BKqeDixoz0Y+uyjaYl2M+Q4H3VkU5+mTTQHeVIhwYcstPecn6uyuQgHNXBbvGb/X4Ae7F1tHUiqQyIqLFFSxWPlqZ/wfOUlSMzPKsSQBUiyKGx0Me4Uc2gbypkg6SuMdklydPOqhVoSRRwViPMxMdTHJDZcT0aVA1rnSIAyO6yTyMz/9rjAMjToMYMAEq+D/uRMbIdrwTlN+u9BDYulnPL9i24e+yj074r41I/LQsH93qN6vuqsnZmrULnqqAYUirnnn2731TIOmnlD6oorP2lFfHBBA72PBpLVgHbns+OcslTttU1IcXdNGUvs3nt4L62YvFjS1fAfUfrHzcQaOlmsvrKxA99FyR3CUFDeVgdGdXjQ0ofaplRTaaU3PNMlV+44rtDzBkUe8WGt/2su3Cj4WLK+h5V04nnpevtgTOcCVadtkcaWAZxuk3SQzPFkUWHIu9JkYG5Gq/5Vh+p6izWlzNCiXnUaCVmiaqK5OAnSL7zIvVATxoZZss1H/3zUm1+B0QdqMedqMVpqdfCbkEx+pnR+qzHZae4Egn2d3iSTgcm8lk/7jrmCf0ZMWrYLNk122xPfhv6VGJH306LhHTl+VYLaEOdVjRRYqQnhXWkSTROD0ILG9nJvpVj6wtPs1Q3k2HZZMUxQ5JjkobA78H6S0WF1M9H5ffXXDiTSLrbadPnNh4cG7djTdari/L7fuRxT2T8KC4sUFF2g7yYaCEi34EX30ReFZhlzETjuI1RwW+VbEI3VHjThzfDIBMr6Joda5CAVa40jqbr3ORWMNOau9h+GcCmolBH+2tIjJNWIN1NXN2Knne4MZsjO2/+4tNdoSgnK7wCf0nFJcVDHWlQlT5wkEIXzoe1s6PV+1M0CSlUOdV0YmtAPc3bD3x775KiSGp253V2LAb5ccvWXAqtC4lkxzK/mKJu3eLS6hQvNwykRdRKExlw7+tXJg9bpZjyOliHP5GiZU+6XrbPsW9ZKKrHdAZgpE8aTXxBMY8VNm7S2rN3ZbL/di2HL1egKN2jA6GC9XU06aQKvNN7iZyCpjPvCjoscDA+p9MlhalzGDLsLwjdpFSEkzPMavyGi/52wuPxpICqa/kQuIP0nHd/l8XtDp0PDTi5dRMjNo4OZAr4mHT29ZXiBC18PBqKSEpQI2/Mq/06JSk7ddc5Ywa+DZQ8E9qO0ShtdjHh6N8qIgUBFRJsRM03nwLYHgBuwTs1Fhir5QmN23Crk37Cqfrmqy/WD+o5B9uZieqS8KH9rRnSiQX2c4p8R49r6BAKVUk710WNson/jequeY8Trf+UbJvjZC1YMuts9ClzEXBPafwtxF+oQ8YKKDOArRjYD6bh0Bi5hCDIE1ZhBbUo+9fcVIf2afTS/xq1T4EUgAAnzU2vqSnz8Wu31+qsjQcifXGibczDZoKXcxpyBxCdWSp0jHsG3wPDCYyO1ybmEIJlis3tXTEGH7Qa8LTjgj47nQpNF/G9MGuNEkwnggF8zd7M+MkHgJUAoCIKURWNemExhICxJf05RbipQb4BO7CtWTK1Vl8pMy2Vc27xgxVjOqw0VvMqkw88Ci1epunBisn3vvN7m+FeFPFFaR8T97x52sl9ZwMLwVox4ny7HxW+aonbE+XhT/U7z/2FLqXTyfJAX/JCWUUoeCbqqptC5eRA3QdIwbTNNK2lhfUWGfYGk24ZYEChTU2pWAmO1O5mcLg19Ui/sjatPzTMos9KyUbAnA38iZNvaNdqx/K0W7wc/oDacQj5JC4AMVfOTQWcT3+UwJ4d01JtVA/UEquRP2fvDMCVkqLukwulwKvnglwBKSRrjBIoF99WrUy4UbgUX/rxhUhljQFLi8Dm+4OeR2cJGOXEUWoZV0NkMTNJHHCJoR0+J31AQ8LVJEFJkdqMn9m5g+X56crBIZNTrvjf6f35pgKWUz+ZxIhayonx1p1ElZPdutDnK5WnHF3LTO769fL3o7aYGQxXR4M0jYCpJYcMkRQjmqQcJ++nNQMcGdYn/eEkN9+u+B3bIxWs4CxcjDY9MgnE7aISU/hhZ0QQ8jEZ6QVUu/JSAX3RGTgQ9Df5dcY/GFWf4iMZja6ULzNnpzXJTqXVKAKmr+HFi5ce9TzAkc8/KVK1wWI29jVt9cvssiwf4yL4aSS/vnScLEh9zikloAtqWbI7nf2a9bPZxZUMNAkFpgZZBelxpcG6ws9i61AejRHx2yMx2fCSSKmQzN0LQGZTjUuhPHif241/eOrWUb3Z7PkV/y2y2IEbMmTJHcp4FN7OjPR2KtGidu1U/cNSLU/KupnbYbntvOsycyCgWHzGHj/Kd/5pO/At5z97X7egktQkfIwSESqAk/NTIr84ki9GHmqnlPIdTcmCo7B2X5d/v9U8p2CW5ApnTWa0zsPJ8LPWgWjFamp3Jod7iL2RjjIyGfit6Z9hsqSnKdEv+UqmYid+01xKmQesgSHHKxfII52VJQZlHg+F6XyWCNrmv2iL2ay4b0xNMLi8AnX6bIDQGj5AJzdDeJbtEsKZLP+O8Lliuwa0wIBRIAk1O3FxP99IJkNcKsE03vXSphKvusAPGXe3rN/HJKyylL7tC1s3e06/Y3tLrCZ7yC9TGhhspvb0E7lBaaHcoM0djSmwxwKF8OFhp3+nOF9quJwjU1uBc3/81D2w40x/OIBosIaKMEF3J8gkVPSpsbZKbb1ZnKn3cqEBojAPx3fKsPcSRDsLS0rQ22tkREGKu788N6YdkNOjplTvCba50Pop6rK/EjS43zEWs1Cwxl4n5Lu5X02l1GZyIaeUgWi8UTXyWvILbv/Vh/a5aagaxK7d8E9G25oAvTjgzcpwNQEmS29wpEDGxnNmhkHUEz7oG4gifknEbjwkKcMB8maA4NLYkFCZUr9BznQlhp3dFL27hxbXFl1nYX/bbJsNIdFqqV18PybY88lIOp4nYU4pfrMQcUqrr2oJHCwkChCLASmibEsBAAGvwiTBj7Ry/i7k/ySOUXoOMbW2wh3EIIEJHTvFBGC85ok0Spgl1PYER3zqrCGgqyI0WeRRiRUjyZkV8YwYx6HEnmo7x5FuntuILc4Mnh81D+ggdyK6AJvJQVWZqYQJu8mIl1ZeCwAURxPVQ5/7sqnfQniMtik4k/7PJwaLkVACRA1AEGVevCY+vmP7Ph0Jt83G6lm/L43yPZGfzv0PHbFgfu/fsJuXa2YjadAe97Br6qeAM4GGu+uBbLqM5sOCYLKNCfJwcaz01vo4hWTHvL2U8pt9VFyWO09Yz/EOZCDJ36GedmzoFcw2W+pTkvNtltuj9sjZMIf2ntEIfp8DODNLrQvfa45UZS7ASN8t1STI18NwWUqfF+fL7xAcinWSwbKGyiZIWwDAHAgh3EOIdBeQorz36F9IRN2rW80+pbPio7R0KpoKABM0PLKRj9Z/12EMUTwuAjOrKewQFM6ntycH6UMCCYeMnpMlb+E5+78TUUftdZm8WZz8z6A2HJ8g24a5sVa28Qpo/9fqj/N91euDfhgbC/zrlc6HcVY8Zm9z9cLI233x6B7WU4OA1yB9F6zx9YkVd7RRQKF/Z5Sq4GaR0B5CMCKm099z4ld79UwtG6DK2ASM33mY9ngjDLpovHYmXaZMpk9q9ernWhn2fI3hlHDBs1gvHGIhjAyRJ7+PX/fw42Ntv06G0bRZpPR+CoPMeLpKfl1FIrvCPdPFcbenz9K9sd5w+rE+lq5VBt0u3LBZT8qBWOzJXZG2f75ce4d1EiNBxrB27bG8XXMNeNzc+CmHJogBFJvxB2qLV6+7GWogPfC+LZJpqVQRNvBm6cPJOafA3zjdB5uZ8u6dWtWqMcK7JptnK6BUMhCckTmw5Zqs5rKog6nB1rsJe1d9H3oB4sldYh8xBmBvyh/OZh/j3AEDQxomGB8bFb3+OTW26w08sICyU5YtAa0wK7bpYYOe4y452GRQke4rLEDv1VHSGhdyH9vi0wMwICZXsy7lNDP/OVQKWRkUuFwI0cQ5M9xctc1cpyRLKRvSxEsSS9QyAQqspG8yB1FBe0gBFtyvHDeuMpgytpYd8LVjIlL8FZK5iTZcJHFvdBY14dQMyV024q/e6DwxvZZ6zDV0l3GIVzpWNBuy5m9cnmgAjiWVrNk+cPZ3kUFRTAsINJKVTSGr99gWQyx5edhYf1iCpg8TS0U1T7ZTEgpIeLo3t0lspvSI+dI4tZcZNUhcr0jxTova2THL/hzhrMtEoLUYva81d+P803T79RJp2XdyLbofIRcodc5rqO8g2engpFE06z2Ffw+HsbeWqRRwVWvs8NB9DsuL8ggMagiaM+5yNul5s8Rg3lRIl4THf/bpdlZXvrLM8z5fvLpsYLfO+dBeFPL1A0llwBTrI1Oyrr9FFZv9bFR6XFLTdH7lve23z48ezL6mK8w71TD5bw+WxCT/znnai0hkGeRTwtATtcOsX4X2XdELSGqURd9iXQ/rnSiB7dJVUeCxyWyDDz8Pnt/tqJYHzWrMRMT8dlYZqeyxZEal911Q+MEmHQlSWqig6HtaIJg0u0oqlDn4DEFouIcFpZ9rTyGCvSBpwrtu1Vs4Qa68AgNJIIjHJ3bBTY4zY+GqbU8MmffF5BnKyyDmFCxq3/d8cGIfVrPbn7gNc/nto9DbwAzyuLYJpB2x1ZlV24amd7cdZVrKk2CFAktFi7Qzs58Pq+1UkKmuClsHIURxsP/m2RQd60kXSJusqDGSDOhTNr1Hu2KFey8C/AXOmh2l+MwRseMRngDIEqdWVhfbF90lMu+Ki73pOh3SAFZpkrUGJthNl9AnQpdLuf+YtHcdd3qzv60BYJTuW764N63XUgp0Z+CjhsRBzfdab0NWc02q8/Jb5Z84IXNpEgbFi9x+AiW773XmnKw4mlpH4QtQcZAjd1iPJBx3rc1UMxKeQS0vQR3m8QNRUNvfZapIrC7qGzZs5XEXa1Nv5ukCSqiogQVgvpM1QqyWU0O6KGyLM5N1+e3EF1ivKaST2BTQlTURhPcF6WOskVNgWic2xoiALoY5pK+ZPw4yOTwxXkpcmtQ+VFTzIq/qB5vbzu7jRddbWWVMmCW0xzTVRFJA0m2BFnC2lO82QB4IvyASdmzeleDaSOEZ8OAksHHjVSbW5HSWO3+dtFvzb1s35Z5c9ok8syQ1W57R2530QgaoGTC3uyMaixMpEpRzDro5j0QzjzWADHZ+PmfLrAKMK3Ib+Y5Uh4lZeoQ2aOoKes7aRfPvAGU6yxFXVkUtWCqGav/EakRPjdWz+y0jstsgSoYYWrgolZtX66sWUHR9LAE7EFeg9yFJRjXFMqKlKaMkFldUuLCcqF64ukCT2qhXn0aaw1MzX2vPRjNpvC7EQZ8HCIByWgLCC0ADP6O6ciDRgGxD0DGMnYB8KwKABKD1xJAQDYe3bmgQ++218MaSbq9ynm9ADI56GeorVDRkFqwdriR5TI7plj+A3DAN3pvSaXk184ylimkb14lk/zADY2QjVWcEdGtu1KEa1utE07PoIfqKMN4CEbmFlOCPQqLryLEqOpRDnqgX+t1Sw/tb8FjZ6GB8S11WRSQyfByn9DAsxhp4I5AOaENaiJIZYhjcBWUV9Z9m/J+1camiLWEifG1xebEtM35V1tNnDLRpns3tOiZaDRqp9STs2L1lZ6IoeieilCZ06CcbDx97vWx/3TRkF1PYkTO3o54Gy1IIgnhh1pyoq4Zp6PykHNawW28PAOLQT3o0bIA8G9b/OLxVIzMibtnz9OaAKySzTXlZkqeEv+FKSsJ3V/pOB+QX5a6YSTqSd3xUe9zcbZp5E6UfHwH1C5/JXjdb6BF5ptLrax85FtNTZzIWyLG+x+0WqBZrVctrHpwXlKO6SHbu5aycStKoOr61Av16j6BPQK+8kmBdSWKSXQVhJ6PMmt0O1+OBokE9M6WZwgz9x0es0ZxYlEpflM1uhrpHJwxTeUOPrAxULaudFwZoYLVggiih4Nv2hVw4piGT2vcEtVyX2t2L9HJVAvL3rnjeZQtr3s0zGe+rSoubbzNUFjY9JWmC/Nod2vfE/WWIzd9Tbjy7GXVbIx+tyg7s1BkGBCT5+mTrifkU5TiwJ6lsSsuq+pnJHHKAH2pmseuXBgdp76ZSyB/YQekcECSbRCRrzciShumOk4ZDxVFlC+A8VazQ38lEU2yOcEYMwKCEKiAGc7LbjpL/93InU5dt9BWpW5wuDZPsKsz67Yg4IJ6j7dqWZS+y/QY3ajCOi7vPhBr6kFHJQJWR3gkqpi+Qt6P2/7kHOjVCZFnMeRGylhZwf8oqa7va4a+GgLmkNX3BBrmwb+R6G3uztB4GV4210F36DiOcxD7VMPfMRSU6Kfb37lic9w7GNo1HrtEuXJ8dHHgNz9rwd3JFFnX2D0EBG+z1OpzM9vIlqqPV5kamtd5WGo8oBaklbE2uZEBXb8S5yVaSi26TOicbdX60Ex2mwrVwMwZ1zwFGQFaR1HOXpIHfRtp4Wi4GzwDJJ8i2aRMSrDQ1+H4hnT0zuTc2kScPB/4nIJeijueB4z1g/3JwEPejmQcAi5658dUimbHmy5HzaoL0eSZ65CWSGIXuZh5YHqTp3JR4OrF6UfLkcj6NoJw19GoVPN+CoJY5eUaXQv92IadsUHL/ae8zP7Qf32wHRfKNVzSuGQq12xEkzLC8SZhP4e86LmKHm6OCkDuSu7GirFdCbWvJfRAlttevQNHmtHdbTFnJgbhLVdxLwqOlyrBMh1QkWt8M0TRgCix1uHgyGkLFUOXR3bFYZOwQsMfxW5aopNtnRh6XPm1S2IOVhxJAEayRa8mCT8Fl442opFH5KUvJekS8VTPfmjoUMO8mfEAiDnQDHpOgZd1gKGOR+Lj9CcGXUEeTJFLpan7WFUlL04pZXMB6ZhGy7/VN0BZJnQACDBzxBoJnzEx7Kp45soF8eY1NLBig8aNRhsb9lY99wH3GChZ3h7FoQ4nkOrA/7reGv1GSg6I1pWsH+y9bxKNLBoLJbZjMu4eJ1BHiEbIgCGp1KvkY6/ofxpn4InMvw6jlPUM4TLr3CGT/FoPbjwJIjfbDFhvblF4ZBlfGvyi+srrU70jR63oOSfwK2ajR7PH73F74jB1QVuEDtNfd9wntFxSTqQtFCxHH7vBc1Al8EHZG9J5cwAjvmzzfgoO5ULI8gPQdUwD1aSJ7UQUyKF3l3cNA7/2lvADaYbdnbrI2fulUWRO/aGMkDGHBGZDVKF977ASJLaQX2g8ILULAAsWQOy6cODR7cFP6E7wPdiMBv3fdkfTBu52jyuEgvw7fT3z6OYhKLfNLnjA/8BGqpwdDms6kPxBBxNE+SnYr+fSE/2BRlqxBvwXySMu4j4pcxctwbkbl3VrlNE4lcqe0f7u/Rm0Egw/RwkLTldsSp5FYiX5XJAJBaiZRfCZIBigqmFs2OL3da5WzGgr+/bnnps7j0M9c10vJXOdE2rCJS1vXCBNfVqGTsE1yXTkJJxRZrnrHkzXegKbblHKVjY18UMmTCg0nj0B5HDJNfh6Xvc2oe/puaMVogFltC1AB8rAAZXcFSt6HxhoID9EtowPJozEYXiJ/Zb03KjcCUf2JWNVFtc+OgGlP7A0ScKz2yymaiO2xjcnd6b3VnetS5vYf7zVDkIFRW83uMrFO0apGb7QgB2uIBPe2E0bMuZAcYVywV8Z8z12t1gbfDp27UOO6ta5Dnj5Jnk/NncOkI2Uzgt5sC/S/JFWUgzeQsXDNQ5p74DFRhJT5kOi6NXkNwig9aFc5J9GbJ7i7Cnut3DpqpyFV0cIgmHzqo5fb0X1rhG1qOecubBQJuuD2OqdkzbfcuajoDMX4TifcKfE02QrvxAFalA31YnkIMfWNA9NqkHP7H2h+Yz//pekmuTqSVEA44nPqfyXoEUw/R2JqJFo43T529DNwhRzcbsuMW6+lKYRPEw3ufMdJW3a1g9lReKyivwyYucWl1OyZRHYJFzJKwJ+zKEKL4/S5E92ZCK2Y/rEoRlgI8CW+puEh8g1Us0x7njWPbUWuvrV/cC3KJbmpZhfl6yDR94ywJr3Ut0QM0krYsQYio79DKJpJ47+huN2fdabYvMRfX0ct6xtlIlHrJXg/cY21ZeE7UCmK9GFLnROruAV9V/LWx01a7kAw3cDykiVPac1oKREpufZKtA9KsfDz2sRrKPctIIX5LBe14OT5HRT+HerzA9JRmLC/RfxmvCypf5DfJ57r3aXUB5ihkSRVH4Apvcqc1eoESn69OUph6KKl5X6MIg3B1MUvyjeUzcJqVkMKqQ7UsVGhZWXJwhuGJH6GvWA39sLK5iMKAltz6hXxRgxb/Tnjjd15cWaMqVPg1Xl99VyB1lZ5tEZuqjYoQYx0uUctfoYd4Q2QV3YWoZGNJ5O4UErFUdMwePEoHByvjfzh2dVmMtGLPUapUpZgPLFZWXRXeQdrcRzvZVUANHJbWnKtQSCDhAGM0RVPqt6otFTomeVxG+LCR3vCLJ/v+0mPigQzqwlVcPgf1wzUgS4MdOZCfSpieJtEnRTAB54nGt6bCgSAWsjhm813C/uUVEgrmgvlQhxYX+R76EqZZoi9XsBsT3v94K7ic+N6cWp6R6XPrS/e358fA15pTI5letBubiHOiJDtPHH1XtPi1JHx4v7xIYb1pgjjPoAYFa8YhFgEnP82Irlflp8R3BWgiGhRIMTlyVdKWUy6ixAT8bNXY9eiErPO1Q4MlQITgz5Ue8HL83Fd3ffQPd6HPAXyXjoT/TT1SZSSNXCRziS/lLIBmCob1kuoIUqRKwtI6TU+DWICNbK/Qnbu3vqIPwzxHh9f63PIqyI55UtDimSu11r3SQcjdjQ/ZqrZ652TVty7jA4qQwHV3xsbLQlFd05xqzAWVyG1NB8PxmdDffqjEDjQ1I/WLazKqRDvlPLmvubfbts4Ukud/wCASXwctzAvKMge4lcd51qWtVkMARmiHOy/yxpgN8piDSoq93qbSZfJsk+vbnc8Wxe2BR+sEVNQnMybVm99ImPYMiwpk9VXjsvYn1a51yaWDfe/XhOpTDX9q1pt6MxjyrfllAq8czgoBGDMgoBnRC4AEvaaP9xXlBjqCwLh9rTz0OdN76uS1SEne/wADRawVNfbGGjTdGtJkcDOWlz+Y2K8Z++ACEhnYUf3IbyBBcaiWYgv637jnsF5LBZtgUmMJrNYYtXqC2fzC0pYC9kBgLvAeiU1xY2PbcwD2WXcBKLLYN8UtiYpyGq0TEBXK8m+l8dhO41sHFkXlXtQ+BAsJO7v0BfU8IteHcJ72uop0z1J1jS+0XqqQBswrTyzjxXvw4UoT1D8bXIlxDkH3cW1+hKw90vvmr5dOFmY5Kzliz+9wcICNGK0T+wbEFUR1sce+/2YuPhIutxB/ypUJ3j5z01cN5UmuTPy/EpdpezUMYMrUJFakBGXNIqadKaNEo9c18/ZwAQ4dcYyczLqtAi+Zac2oBII1SVe18JzqbWvAsdPbkR7Xob0qheZUxRH3Os6sPGBusgliyMVq+ZYbWBGGqJoGzCJp7sjS90nTY2z/R68kP0yuB6o2yfuZUdY+665Fv8sUeq/HEztttfHVaelxewQCOMX8WeSoN4P43y0XC4XS39yQleCTCVQ5H76QZGoU7tAoelNyzsxdTlyYiiis+uDUS0RLslcAxB9NQ7/KuR8JlgYsM8b/uGJmRfAN7SfV4qf+wk8GGPLrMciRJraha0g40yrBoBpbWLlycx6sgvTjPFLF0TTF1+Bo11xNnJCJ63C6mn+QTmVyAXLdAWLaYwEcSLlG+evru4dqQyUixyWBJoM1R6zqQq5RXZKrvrmsJH2M9cWiE7dSLeNOeknQ2zX56c9MSQV9PJgJTQn/8aSUTII5RT3pkoO3mnvATqoRCqaZ9G9wmb0qX0pVb3SdC/zIKd4YLpEP5fPryzQhw+MamxxlrwCTSb6chEg+dvJae/y2pZoWnwYFnnj8I4PXmoMslc3SKRYACZPhIeBc7F6NqI3ffKWiu4JPiycOtpxTrV1Pjo4JcSR59tIhtppTsoFtjQ0BT3PvSdoIhwagJnsNxA79iFi/UN7ubip/VipC0G6QDI5I4Nf8iPogVrTNPSskOS9cwNoyDbjWeTuyult98d9wpCimrt5sQenQbjx7v6MlmDbMAPDvjxN59NT+tFZGnmNw0exIhD2KkkxFk/SwGvLbdatP9aIsB8gHlUz/ipPpCm1J10YE7y0N5AJ1JkK22BiRsQ9VvDgzXRmFa0Zx6IkCu9iROeLkLJLHS1xjUFY2OhbDVAWeAsSJCbLnIgo1elMiEdvH0Z9w8O2HW+rOoUVbifyJreRrmMFcjZzHvZrGYMjzoE3j8PkK2o8c5S+Keus5oIc/fYY85RzBgcZ7Zr+QXU/qy4qfTDabLgE0yaxnlFdhsZ0oHgnqEU0v6Gi6qzjQL0foowGODQytKRFJnzeEfjOYYEpQJatJV7OfN7bhBFkT/tlMkxER8Zhbjdaq765MiyM4uilywJf8k4k+CKWvLsGSsYFDP3OF8+/Ig+cd8WSPVrsHGHBR1PhtaXUC9jGNyzW0I5HMKbpJY0J+th2xNawUGjXp+4MCFooCwnGKE+qvTbNzg1baRhEWVzHUzt6JDTBwHJj/Cp1PSHHSNvjBDHA7Q6dmhMPF/ix/h3ILe/0oMrAa3bsEqZLitfxIzhrO/MPBWTa+/I02cgps6w2MHQ8DeMN+pQjnqehPXfcMEWtDrEEmiqtN0GIthGOyDeyzhEKirSBCRpuT12JZx0N6HSK8WXHLWthQKWwcQcXNf3bbhqW3KM9cvFKi5ttn5erbOgqcxWkTkkbMEczcTVGFWXMk7SXZsc7GlICAN8x3NnlW5tUtYJZ7oiKtHVZYai9CxBHYaUH+u1Rujelo7yrfBOMuVU6CLhwfkj5bL2nOo1pbkzGkNxp4UI4uEeVN2qmkXUlCiU7YNan/ZALUPMrURpMDR4b+E9JdJBBm16cBFXsV97gVpmNPsdoWnL78rin5V9RtaW3uXnjfqDBjeIXW+u7R7klbyi19Nr8dC46gZtNSlpH3V34D1HMs8pOO+eY9iPRx14yTY80qdcQXnNdfthdS4/RVg1e0IOzBVEe6hwvbRhuFILOJ7F0Fq2JT4go8JWRvX6ZS6KeUfdX1w0VncK0rcYOgMB4n64gHoTNb6JhzS6R7RJorJ5F+pE407n+J1Izkih7XLX1qhQ8dOa5KBNT3/d/1zcUlIAegYKWp4T+AA+No1LPLaRVQYvwJsOziEblGNI9en7yBIMsottVz4rKqgZiJcGSKHCoCJYOxECs/ibw36BrqibgsL0VdpIRXGWhns/oSuue25YjQF84ETz2eEZPeXzoSBlNsY4Zd04xlk4h9KKvv1AkdZEnABqqpvUUNHn7Dk573CwRaZ4AWn0RroDGTPkBJUSJ0der0X6tOJf2QuKmB+oJIUG4EKtIytN06edy1osgr3zSR6OT2EtIjVt3aK8MMOw12ECh2acIqhDsZzQd7CI9IjeZVTXKX+pzNOdiLCVgxRyiU2LHf/JtG4I+rhjmKJG4SFzTwI//xCPJYK+4GEVTMiSimcxR8hxLt05lKzejUNy+SESpOG2YIdc8CvnBNQn2WH1ZkPWuazqqLS/vZyx8crdp03oylv6WsENNeNxWhi33ipuqGpL5eXLvht4PXsdkn/3U/svDAPROFibnHF+h8o9ZAvfFSImynM50dtsBr8rKd1l51AfzTaZH9A4MD9lSEbMn/0XTSF560JPwqXZb9DcbXGkDLMrn4eNW0fEvaZIp5jN7eQ4gNs7glyLT0ORjT+EurOUVqt2Hm9zFJqPMB0FRfzsmIvHGZkMb/rOcSR5yOjOTF3AMKBYFflhyZQC1fpyhkAk2+2gDcJam7vQZUVtugIv7GtRGP3DSEfo7NX5jV0qJC2B4axXr2qfg0/yOMgO3fwOKAY/Ek4DV/fGPa6/JESPtjsaA40NMEHZRAcneYkVLInz7aQVNA1mF+Y6WNMnKp9RDazQs+GVuClZv2Eu/gnbOSOiOs6MXo1MDAvdrGQcZm3mZcF+/py4nC1GOkK8Myg11s6KYZCzKHkBaoDIvNgQeZ1b8Kt6n2syJr89ItZHLfwglRmoSJd2t8U7TSXImRcP6mSguhxUGAuc7zCfEtE6TxPFCHAW99+Cu/0Kce9sVu+gsxuYLgXl1u/X9Ok9E/CyZtlXLPWi46EeQU7LwF6wMa3uOn3v18QT1vU1hfe0TfFCi6SAdJ9P2G4V/XYX+J/8He50iU63CMBYt1yo3itdQKauJdVRsvCclJ0aOJzLW+a0ObSeNSslmBBSr49DqV5KevOCF3Txi8ujPYcPjqP/guKkNUqImOK2UiuJf8fNS6MNrTQ+Z6zhE5jiwCy9DSCDnJkqOWZI4S2kfh8aqxxGwyH8tCYITut3TdpE7F9+BovQtdjBSMNVYdcGqncGHHU4i4qDuZtc8Fpb+GP2zU46ZHG1q2c6F7mRNU7rmC3PL2KJp+Dz9GE2Uj2wvUSgIj7rhTY/DFvzOV8+LWstRkTihgCOFW8Y7c+pQfclYBLszQ1Wlf8Paul65try8ZgespkvHdvs0lvinSQZPvvtTGl//nzZDu2NMD08xYDHRONVYUv1n0HxCDkSUtpIAd6eEUkcxQeBCwyueEsHEQBCXTlJTxHSRL+EdKUFHXJAVh9GeqC4BRDS0kY6IOaCdvTgnO4lnrF7cXtqofLRE+X6D1vLNb26+V57VlRRRM8gSJZN7sToKzkr2R/g+SVMuwLeP97SY5tkgtW7myvGo7UATye2lCI1eqQFK/svAZcSh7fPYfhofInq7V1IHawaHpMwOX7LTwMgAOF/AV1VhzbSgG3WJmgu365OBc3v8a6OE8N/dvkPMINxk2m+Zh6l1G0UmPs3WZgU4naLfslmknYdwrzoy5s8jVCiAbfL8JONJmzHog1LMlYWVLL9ysAkj8PrshWOrUlhY8Rn/hcIziFIKVOWeKEA8jAc+oZnRTuKwwZGFEcqrGnn9bfxAXwrk1TfcmH+6hqJD2nCVJCFICyhBPIqllqWwEqdwxGadKJZEwjeasxCbBeCPRvLyBd1yEFuR+un4uCAh11Z62fpXcIXRij9nGgkSLGAfk/hI/aLuYvVKzUVm7x4i1zsbwpmroSMUx1mxd2Gb0/FkYlMegYdqajKOjzts8pI7AbRvMgXEGY3Paih9vH3d9Xdrreyd5b4E0FNXUml/qztKcHMFiZSuoUtflTpB2CRqwVqaMawKWJqvqthnVoW6hMGklb/3vHApnEcVT9bD7f4+FGfAwEpMjijEmUV2VY8ulIUgDagVTC0UbzaC2G9j1eM4F+q0WqgmScLgdaueXqfNrO/i7cUHba+W8p0+m1gfm+fqjY4rzKz1XeNbbajqPjJR/NdXIzElSMCw5tB7g028dcHtCsU+Ybvdfhczerz5KYrBiStzdIIz3bDQdplZwPueDEccfgAzdTjBf2gdz1T4R2S5lJ0L+osCYFiCEw7yiIYY5z1A8aogcW23saUNWiVew0mg7L2CP1rsQT3jz20yhDN2z4f4pDCWPjsspUtGFvgkHgcwley7+H7/y1rdRJEjuH3Tc+nD/iG4iQ9kXOoFJyKFnALsf+DoBLnLJBm4GCqEO5dlwr6r7fv065MOViPQ07krGOG1Eek854TDm5TrbdKn6QcgMbwvBYqsYTop427W0bcrsdPHNym3SxTKlnFftj/GV/LQdy/Ko3ysxve7rTjGAsbyhO/z5/VxtpXwZ9imrtXLIsfHMa42UkxUyXAKgsStNlihIsR9DRXWJInzQWxFLftUAnszlxNCXz+plmvJ7qsfdvyLz/zKInM+ejQ77G7FM1/nu4i9ppy7vvxfactETVsqiC1023JSOQofdYqVQC21UU4Wq6nqXhR3wboWhOFNloRj96ZeQCMlB8zT86qwkjv9vGGUGNyapPtDz/yltK0Fh98/qY83yfDg8kj76FtMiY7wnhcv0O1eNfH1xqMOONJSyq1u01D/RLkX9H9WNPHPOwRrV2oGXv+HSO3YK+kPKXd2C8c5qzvxkegeT86VS/imsgpA53SATGyrZSL4c1jwv5XkcoiVxUt/Ic43bnpCi64iC22UC2odjYAbae+Q13hyDxVBHV7KhY0vB+x1OLnEMHLb6Ncqkt5cJVPMBggmHMsmbCBwYvN9unKyY0Do77SoTTcEq4vo3woml7O1ljapWJVGwXAKpFV9hBQoxlfkwlbQAiMxVmDqvMBwpUh2WqHqLimLR64DlQHMoEFs++ubEE5+qma6A32rQ2I4KyLIFVSE0GzWLtV/pFhsKQ5BCYdFk8S0lhj6DTvlPgOKukFyheSznLy1l2nz9HndmkjpyB3XerBglgL3cSbgH56qaeHJpQOGsUnmAifbDNVUKfwZOa1+aT2Dn4WaJHjdYTLYdu2CbFOZeqI/1Ro88DsEPdsiI4qj6zPoywmvC05SkR1L1sMPyhPbb77r2+Ggvvfu8wBxln5wdpRqXpmL8Rf2EgnFBD8spAh9KhJuYutCMMhrB4Acd2TaRGuEjv0c//VVzN2EVmLV/IwPpHBQO1z7UekC2TXtVtrj4+XvpsybvArq8kpZB7hNehcWopZhyjetONMu9ewsL1SU5Q65V5S3q5RJksJHQrnd3rvlKRChfdBU3MyAyZxAnlMl2UDJ3J1+cLT0xFdbeY8d9NN51qKKug75qCLJnWsK9BQrsx/1kc6DnOBUOUSVPaWf+V1K4rkJp6cm0scDSk6It/YAGE/nFk46lWJ+T1479zVb47o8bDBiYymVe4Jdsjm/6WkiDMuQ3R/qtO4jC/KVeR2E+OSufOfiyZBXv9mE9hXve+vcFrE4HIOzGJSxnzSmq7qfkKvclhH1nOnAAfRv91W2vGdQIGHpEZNiQTa1XBZcSbTdDgQdbgCB7IGrwQkm+ngN8U0SzyMfGsLP8e8yKIPz59/Vg2BhpOzAPltyc2+//pUnpW3bk+Jd2SK8VCR5mGtn9WdHCekvpW0UdC5FaesuU77ZP03vrIef70UHbjBpwkAxQx/gGvaOdhKVZRyLCl6/nOCcBWCundFod7vum0TuKXEACxfV8Kh9k77mqqeZ3busp/4weo8Xi7gaFvxW2JaPQT4sKuE3C31fo6sOWQfc1LVatzehPkLg0XYz1zto3w53yt2brta6ALTKTBW6DhwXXC49xhD3z96GiviMVBgRks+WOKEG+n/yWd3GwLcGFIzapxgyWdiP0Fj3jEG9q1xDpr2NcExG+ZWo1eZa8JCCWLxw2TWq2PEgPQtnPEeZGmZhtYj8Q2c8bLuU3805ddjgU3K6/KBW/R30gO3sgGVXtrkHmBUDQvzJYuJMFV+GQ1Lwi2fPVqDD1rWCF5IH1hNDsdRaoDMlaYCQ28lBIGgPMSNeW0lZiC2gfSBEwbFsH0O4JNZ4RfVVUt5xqo8ds3QTdq7VcFDuTheVnJcWbfC5WgYLRhqxj46qK/XjA35YQn/2NkLgRdaA8qwsjG4v97Ep3JLB72SvJVf7bRWW/St1Lauj5BgIYxwjxBIFEBhWSzCeRId3dk1UfA5N2K5/SSP6NtRy81MobJsqLOkR6mu+cr+CYa3LhyNNWwLTOIIQLWq7QBdzcNRtfGqb6CEVBl/v/DwzQ3ALTud1S+nsNAGWJBsTBW2hmZHMuK+4wEOonnecPDUzG8K02xEI+9m0Z2FmWvhd8yghXa9lTwKOTstvd2568zDF7xddUBmHQDDXVcThN6oyF2luKvpRn9ZDYpVIFTZpxhuHGocxxSEcn1AGYCIuLUa1fKqz17vsgGg8oT1UUOMFtGOBaN3LG4c0QDjZfuQQrtz7/aVARLZvmQzR587BFUvUoXU1Ttv05Iv4kaBaV7BG3CjsyUnT9cca02t8E9zi1bC22ZTdbD2NvFHNIJtXpmNn6CVMnredZAQVMDwXv5fhLW1SSY/eNJALK9B729964s9hOaaGaLvZoY4yLxdtkg4tCXt8PnRYYjOtRLzbVc05iEJy1oGeJMGJy6Ow9dgzSC3x+XxHoNOyPUCpa6BkdFPO2Dzog3iW5errohkD8ixOdn0NL4hq14MVBgPCZ/iwMHiKQ3oaMRKMScuhkJOR+Gu5a4famtA9O8fKgcWjXxCYv7bm8SeDX0DAR146eGZclX5Ff7gl2JDAy1B9dYdSdzn35MkJ+ce3Lomb8Ksp8px83GWM8SH1lBGxlXsnvgtc+qmhHHwfpiv3MXOurC7bfWQMG5RyRQzcmLNe42U9IUQIkoaIgub4deYoPlkzIo9e2dBzTH9Su4JhHyihKhRQwkgWc/yn6zKkya+c587Frf8UVatY5xb3/0WFWuM/lT/rUucIpmW0GTQ2MuyT7Lf2LrAZDUn6B5H0Sw5J2JK5UKDnw//Lb3ZHdTCwqFC643nWOCWY684fNMr/c68z5ycur6VDq1nYAEx4UVBfJ6olPv8tsohUWsKGrUPQWYwvcIwWPD/AHlNIg1GcWwq+M+//aUFhpbprzRCfvFRJuTziM0CEPaAzlruAQPtg1u/cHLYzCb3rj0Vbyqea8a9WwvtbQ+TD1C5JQ1vkBU/PO3KMk960uE87eDTjJWpj91QlFn/v6cjArHsfNVnNA4jkvvcrKsIjr2h4StI6eUzkkyKLtVO9Sw++Hs21TwCHQKFvlMr7rfalv+/BD2GnyUEYWql3FbGA9hXGklyct1Tx1SZQxfeIZU9JUHNuPv9qSvkqrWcQayPMRyFpC7pSEvl93p9xYc6Mfo0D8kHESonGUouWTegCusRLbKPD0pTS+Xry89pbxZ/i1DsvZjUmYbm1UBCDyOSUETlz5a8qH9J4frvmYZDnT700zIpDAYSHWq5UzmUut7kCo7ePDFZCKi8PyMgX09vtiS7FMrBasxHWrYrUfp1owuYtWiAm5kdhZg0v4Q+7wujfC4pDEjJ+lY2fktbjTOhcDq2QKf0gyh2VtzDOLf2dFOghm1NwMO/kP9CgR+Rx6wrS/K8+90K4QyX7flDAKX58E5hjpEcdaSAzvGfrNYk0jYl5FMFyXdhLjeKDhI4hu5g/bKIMyJP8beX4m5JTp9c7ZU6dqa0t6QwQ0RAclFh6ek9MnrGgf0GhX88usYZM9Y+MHe6VrmaNYiIVzowRwUdDs2jyn8ZhVGzJkDTL1VWnGFT6SDTvcaBNXs8bdbMC35ZJQtQE4hMqDb6yiH2nFvYIdW6R9XcJZqFgYwjU2aGFLC2WqC8u3kZvZbBXNAmtz8ob8SCAcU7wEqN252HwSsdE5hMXO2zB94ryx2jI/Auv3vm4QOkRplt6oEFnROe8TBe3GJZsjoESoRXqtH5vmTaCG5g86EHD1Fp5921bfgoLC5nir3mFu60GyL9jRJy/U4fy4hcq+k+VWC2jGynZjwcozUB+/9c7PsJa1CxxxFYNsbCPSwTdAZWtkO/r9ZRPjOXu6nLzt9J/CttVQbWzWXuIa/TaRMTfyqYcpW8ZMicdkufbeys164hxyNBptNBnpZItck/rvKerL6wu7oB8GyqLdhjFslm9/LwuX0Ao9xv37sR8ZrGlm/BanHD5rD10/wnkDAt1lFYZNZ4OqdIaua366QeNgxOVR9gGtyYouLmIQb6+u+XuyfyaE5NBeM9LL9vrwDNYEHmNqKQqgEo6vkVBwrZfs7F775nIsaNKjcMkkuzH9AXj+ejD2GJwkyiAFkgVUIlopnhoz0PExUpKF2aME12fRCXLeu+DZFK7edG5m53bSrTiZ8mU7Stn/lA79beMzy65gXwhPZu6N1KjzlhWJEd4TTjDgjj4RrMiiibuWcJ3v7qZlXDO4Y1V1Cy2YH4qEsEz1E3TOyOprQV6DPM3ITX2b+BtscYYfXjFIAPEJw/uw7UmKWj0X88YTlmbSxY/oJYisaheC02mncgp9o9xBZu3waiKfF4WM/S/r7Y8wo6G8wdLKPjyAV7jWQkNdzaKZZ00xRsRfjart0a69Zi9E9t6DnAB6DIphpv0jXt68WP2mCt5gSiyETxQT4GEcjIVw81/fyW8niLgknzeuWof6RrJ/hJSUNQB4kfs1zi7eEloe3OdnObjSUOav9NZLOmkOnl7RC85JWSj8qVAEtUIbf+IQZs7LzM3qDvtY/xfGnK3bEPHBa2e2OwFgR0pqVy+JMLckRy/GNXPrePHeszXk5fzFbIV6Xx+q3xREFyLMG2Vei+d+FaAojfu4R+azdErfPrF6SN5sVFp31bSjHGSE4Lnk5hovuX3fYhyCjhhiJcsAYPosyu56H8kP5NQTLoQJfDa9ttAbGs320uuLFNr/3hHnjGCYEsn3A6VfKsl57Zs2JlIRXde7B/kACodHUEOSORds5XI2cHYvdXiVbY0fK2AdGRapPvk671FkArq2TY+IZS6rasx5es18hMucZI7IXIPyAnQG/W1tAiTO/owdhJl1hpB5xSQ88RkUqVg6eDShN/Lb7ja1exYnYlJ+PSUl+7JuhhIDPzYxPoVHmHtPZ5BDHKqIyQENQQGpYPUFFaAQpH0xXzOa8OfVqNkKYJvB23qwQpMIXJh8bYqvyjHXoV/Dwd0egVl9TMtnHuaqnbgp2V4+tqFTuycwUHXgE79wyyDY6PkRESZtKcq9Q/8S87780hB3RLPDMRyoOQ5Qk6SOlDylHDccgub0rrCKv4R/PsYXWKoF6CUmcRCT1WOyCF8D+M5sGY+Kouck1m25IPNHQq+FJxQAXYQd+hpW2mBolDtMNJx7Y9J7F1EwUsadDYSwZllFr7BYD3qMSazZgNurAyg1QTTHxkrc2VaSn1Uxa7RoqfPXm4Xod6tNIrxtLgplSwWkHfkwAIBDwqQULEqMnQJ24/XUJBp5y/YIEv+OqBh1DXliGFO1YjCujOEShgp8/yzaRF2+JytZcpFOPsP/3UrcpUA/GZHc+VQLnShT1EM6Ppc8glqhMoRwul3EfjdobociH/WPqYhYsB3OW1Y/actqNri7eDarqtg53JWB5k7u5d7ydRzye5RAfF+TkLPLshEAEGaDR1thbwSDoHUx8xHgwjJpuQETBixHXqrXp/evsLuKJJaX9oqzXOcPbichP3d9EiHC21KkTDTnZju0rYDOJT2y8CLuNHrTq018EvMFJ+HLlVup1FXNaFp5srg84h/Rh9S4i9RN79FY4VneH3oXndzfN8tMwBvAM1/QQ2O41NetJcuys2USNNlN/lDjw0uvQPSvoIzblvh4LKT+rhjQxf3FFASPc1cQIHl3tfea82TVi/JdqbXNRpJrfDhTJuqHUtNGfy9w2iuOnfrJ7pfXmuTFycUE8xWbbxb8ho0twyDX/q4tKtVCR8FH8HITQSJhnWeWcdHW+gTEQljySXr0FnHMkLzX4+ZTyi/u2e2l168BHz7To3m3ahn5mJdB0a5i55Fbufe+MWIrg92ivCLylBL7D9/zzM/rgf2V3ueCcy7x/eQ/O4q8/uZGdVDsdSNj8GIVDgNIyYzNaI5lfnaZbV+rFSTDKYOvWV65l3GK36eiJDR6PbJM3E8L1x4C38L4c/ahKrKISCCiycpPH2DOJcDlusHde19wfoS7Q6ic57Ek1r4Oh3fh9hxy5mPiXcsNvBJgIu7am53zsBHNqsIJQAT1h7lwdtQibOL3IRlEp/gHdhke8ezU5TM2mJXGHMVKekwR1Hj85F3/y2VzzbeV3b/4c8lZh8LaY3yMcWolRSCaOP0T3KFd63XzxGXDCjb/UOz7DWiLTB48sIUk4jNGWkDaJ00fMtfBTHg3arArCHvrkl4lobb7hnAiZdGJMxLYouiJ1NhYRTtvEzopOmVzCY64g19uFrCu1DbJYL9auakJ7Z6NvJon0cv+HLb1tnCoyRYE1V9O8M6PF7T9d0t2ty6N8j3ORaNC1PFPdRYlHpaNOeN5dEiFGWWnw49ytOBLlcK0sgiJBFAcfpFrQuI8QGMCvcroHPe90LfOil+kD6NzwF/w/YRz7+YAWtqu+PzvIFSJFObermwErNOqTmJd0Sd+fyK/58dzIz147rAC0sWKRdOw21hksqw8D+Q1xMS9ffelRtElzsTwsBw+9NPUI9Wllx5kEKwvVprXUwnXyvoHtGscdK0dX1secRD7Zgj8vgfTyAc4Jz/EB0w9eklREAvopN3YQo+GalXRH4dipia10zPOt1cb8Xr1fastFtyUPmedBkSpyncNnWUNpQt+BM07v3j5iKgi1sFbKUP0OpRIGsdyUjsdgtGfxfs7AobgSFjV/ZR3KsS1xN8YFbR18cCJ14uGb/HpaTQ4TN+fooQ8U2LKINlDuEUUa3dldQrEoo/FK8OCyaT0crjjAjwYCalJFzvF9A8E3Y/CKCcn8+zQJiLjurj0u79BfOT6a79SUuHWJFBDB2VqDyjRUSk/i4yyIXyRFFe1ml4ZloGedLz99JMWodc7enud0m+SnvuEOwhIu7sYX4xbDwuLMHORzQi8Cm/U3JZx5pe1tzMHTOIgjDm4AKN53kaIiGSebQgRgLhr5OWHzPwbvOOWPz2rzz0SXupcTPda7RVpjaCeITG2FtuMTYnWks/D3zB9IykKTPkD2w0NOAWtJpnbs6QTckQpKxIVJxpXrK57GVlEWGGxK7ZPKyw515nZNZyL7Xv1VyxVhlsbBZwKTUbIMdMrRr/MnmvlORU1eUDr2OozC/16zaR/37QU33luT9plWnlGrzgNtiLxEg1GYfGpYgHP45e48XGWg+9vvz25QitM+42x/XhsE1if4Tkh1/Up7nSw5zylJ7SITBS+l1XSBvCNvKy5tM17sP3RzFrixpxZ9w0RK1B0ER9pvC3sff6NGJhHXCvkXgq75q8Ipl5dySrsd0bK3wW9Ejb7kR3vKeXTy+zwKjQyKUyv2Fpnde3DEEOi99R5HD2+pzYCntXAj2FoHo5aZgb8aawWqLaXHSRY3sa0VOtM1k1BYGh/bqgFElkFHVvotHxf2rEfuFife0Cj1TAA6kPRrthmhPoB7tcZo/h6aMgp14zbZv6naAh4VREe9qz71vtoA83PsOSyJA/n3u0sJ/L0SpUS7j7X3vgwgGI5dtznuyRT+pebrdmpK8gIHzlrz+PS3m2wnSTac735Okmv5FcbzEB/x/BcAGbJG6/JPu8QvM0Mc649CgYSJWtaFpaVJkfKAfbj96R0hWeXoT1VMqjF9pq4V9zbWjaZXGUMjmC5Kv7BnQXZJeJ7nkoeM6CuOVnSCrKPmt9AplIbF8U7zzC75uqWa0lZcwhFTLY2YyUeQj+83UW0BFhfE21/CoQ2xMtfOThqUFwGF7A4V8jgAa61wkx2W8pxXe8yPFdA49ywyqLU89UMoezDIYRpWmkoyjcPlkFZu1iVV7s0j2jz1fzyFHakvXMuZHpK24IU8x/fyRx/u2nCfoueLoD5ybsE4rJn04Htg2dKtiI7BG25F8nPp3TKaTys+nMLMSkGQi5UHqET+9TOsi2EH+ulnadm6GYk0UQa+xgP9qU6NieaodmHnOlKqZzfZ3peCZPXUn3saS/7Lgttz6LqizuXxPeRWVDkk6U2Twjs7rRnqo8iKDO3hQnLdLIFsLvBeG2yccAbSLqEposWvoU20Wfi7viIvn20jlTkiDn4cbt6XCyQSSHmNp7xZJxuTO7xbrYg51LEiLR5PMj5pxeyTRl1tHpORmXsmdafbHqa78VpID37Kq6mDixn1NqkVDTvupVC2mtqvFAWWi1vbwEGzaMbrR6o5ANLat5/j+SkyF7GZoN3Zrv02dt2eUTZGle5MoBj3CzRjrLHnPvXE7P84hCsFMEAdtGrgDjrX4kkJS+IXQ1S2WRlN51g+QP2VyLaPslQqn2lTV0luZKLU4XZqOE1+FeDX6gugNmKkYeLf2NUPq/Da+hOr1jNslj2itNT7x7mhg4CyIwMA6+jf8gIK18Goxn5tHqzj+OzRjhNySkQM8yopn27XYW0oowPN+r5ERMMRQ3TmZvshQpWGcQg3rm6HB+o1wVPIbxmtKL95OwkFIEottmy0a/T2plMEjKUlP5nKGwP9HEGRFu/glbNqFKAtDVGCJrxVV9BU9+hn5uXA/Xdk6OppxbdwkZ7YzZm09+kmG+uCcafJdRV7QEi98r0jTaftdx/APCOKZ1L53nyWLoMhMsuSXnNXNYyyWczerJTMXKwcZpf3gDu/3Rn/B5LwUSwVmpDxvHngUcwqyWaa/2dC+Zqiz/KvQ7cKpJMyfoN1tUd3qNwmvkHZM1/ja3ji4LUdXXjjFEcx3mIl8J7B5Ycg6C1g8lkr2iyG9IcITsvCUyoScE8AP2q8s9lZvQ9iFaeLO9ZIDa9hgyebn8eElA7/DErbIt1ISoCPuLrEuDWRGjAcAUJzo3PVs+TGeW+tWVc6j8Y6QgGmQS0fWRWXHXL/6GDwhughII2aXcilNuYqQKYZBR9f9OGmrZ566TSNIktUivjNg7S115jFSTtyVlRVrUMG3SOIU9Db9pHP0lCfIvMkkqXUjVg0oeRhQnx9HGdYDGBhYYRyV+Nvw8kj5iZ5ir3rYH4wdZI7qLZwb/iIH1DED8ueHz5bamIKuwUYnk3aSJG5tQbOO1scdr79jvPlEJcYv13YAf/KSBMwICvvcPPchE3U6H8mtYB1ahUPtKJd5K0ravTySQB15bI7HlqhI8ECK7afSTGIlJjglOyp6N/o4Lchsiy9G7y+Ulkjk0Ju95yfEIetbauitPzuyHSnHTNUPdegnQir/dydnzkR/vF6gpF51uloiM+CdxGYxr3f36zqEFx0qrw9Jraf40eER+KYd4gBiF2aOv1WIl7RoVXTvOwomDd1AtTNvvCf2O+QGdHrDXa3LsQykeUD3fFnF/PT3rSwpVP4nslVjM4dkJPo2Jpu8yY6XIer7td/RPTFn/RN5HCPWRLkmtJeXJgPnr8fhnnGBHB2qN8xAfzf5fdIzmKkr5sIa2VIjWDTskLPyUAnNTIgDRuhD8FtVzXCj1xDutdeYs71h+yvvNO0RJTtTcgUWC6OW3EW0GnQb60+RloM/HUP93VwFjsuT/ucTbLBsnZWcWISWiKUL9TcGwcRngd4RA+up2Ktd/mCH/BD/BL4/1eOGjiIKwuOMzLG28ANI4fsGvJgzqBuhLFQ8O8sAtdUeOOevuCsg5RTgIhUb9sxYMIq4tsmxLMbSgLyBNZC645X2Iax5k4u8OBptk5jmr6UXucruu2b736pOgtF1EJcK6jZWLHlZP+2EwRpL7qpe9yRDOFkfnOas8o/fddlK4L1/YBi4LzzL44Y/KtvUg0THme+ijHi0+R5QdyxRSDdk7VMbEXhWz2fdiPHsOskhR0h6ZnHRfZdtRc3RcPn9dVoBsWQlDKoExJHrOjpnWd3gUE3tRjeOhCN/gdOROOKrCqmVAyLVKlbh9OYm037BmWYE8+RECHdyPHlj9v+YpR5M2ym1HDegaiCQX1Lo6lxcTCiaQ1VyjYBOLoSSBEF4Lm9yisIYtPbGWpcORjuq2oJ+Xn9e9DiCjZlGKbGPAY4SJv6aU2kmIyIsRu+Y4Yhp9TLxAT+pvlk+qF+H9rHhLor9TfVSBJ0P2Tju8xSUJwEs6cWNoYcgYdqxEsS66GjKzs7SNQKm4nI58P6x4zlwbP4Sp7bNgj3eBB3VQ72IllphniP8Jn4X68gWZvM6SrxcTLFJiwgK7lQBVDeJ55xkYxlpeQ+NZH+rx/vwYzhjNp/XPEVREkV4QQ3v5yTQVqZiWtSSF+Efk1aghomR5aXqbkC/L+vJyz0KstcQBNjJDndpy4nU8f9CcZvNTGRjVpd2yZohkL+KJmwUMO9G0j+u/XWOTxknwyruVMvfbYR1usp+5ltJXerK64GU+IMBPWNsVuU9F9yC4bsR4g3VEThS+3UMuyJMk2i4Oiq4iSWrJ6x67V2Onc6vJPa4bD2VDU3n0EGtT6KpgKMNFYzaJ6a+jAZ/9UGl8GYX9HVnkOTFTyfG5W5I8iwV3meoMY3Pq25C0FmcUoGB1wRYpndnoSbmSfjQZXFWmfp+lf663oWoLIdJaVvMzxKpyev96NYOpWDkVCFnyJOv3km5X/80yDeJZ7jTIQzh61Ruz/B48PauDWZvj79NNVUbe+MhvltQX8dquUJGGnLEP6eX/EVqPaT9KZMal2dwDTqxYm0saIvED4ZVmlURQraBr6hM3LNsswShms0uji7ebrpG0thmUvbSU2TdF1LBZFXzh9gwh3N8Cr7eh7cWqvNPTbXWSZoLt55NYi+ZnD/FGgkoNEHlJo7LDg0yS7LurCcBj3r6iMUNBn0Ph7Kq5wQB+kTdJL6/HeCozwtPj+d/cqIdsheuIwZdvhikDs40sdqJ52DNSL66xLv/0d8VxVNs2H36ZlXkw4GLh5fTUvnTppa5yeuiycsfR5l9e1lspRzYNkJ3mmUbUTSm5p0de7nFFr13i5OWpJOLFU63NcwZbYUwldyghGSm+x7fu5eTgXjlBs7D4tYW9MTQJrArEIXBbitE3Hn6Q2ddokbUtt9C5fNYYjQwBroaLqP0wF/vWIb1//MhVzzhj/Debh0HpdXnNnJep/r4EKfEWp8Z0lYpXB4+4YTx3dSXdyomd7Jood6fsetS2fPAo0KJzSnB4y4FXLTVUp3X00nso7o/XYs28rLPNeA+FFs94LuWXiDKSgybU09gJw3j48MrpFHL3cDFKjr5px0kX3sNsqel5m5uCLHXWl2/3nJitDvCZ/nR5sQpzZnzxrJabMEkjx0GszuTur7gHpDZBlbtVaP1tk/U35m9TbshISYZDjZx0OrjOp1jM9Jvgzpm0QT7i1Hra1i1Qk2SAt+2ZaGrNbbjWwJbtu2+8W8pKFOF1n/ordxrdTkjELpIJwOQBSXOh2yZuuJwaiPiXFYr+TcoA1gwvTOc0p1p1Qn//+j/mU/499k39DeQt/i/6hUpaSK69Ppm9jNx0gumXPPhbLemIFtNLe+MEHfiYov/6VGpLq7IJXZON6gpWVf4keUcYKow/ou9DA2+NuoVGi9iT6Sxa16vnaN4MNKmDPSJ0ZYbDarIW0HcA652DkaH2qEGl1b7rgfiG6Jd3P5jzNxnQ9i/fVNwyWo3W1wfb06Uu5CJrRhZm6HO15qC5wkEoTkQWenzDYH3gjeLR4Arr9H3IJ5yWVxyCvCE7HxCFtyM2JPXlBgyChXKQfiRFlTHACJc4H9wBFhwRXpTA8wIRXvZzZQW997XH+2TI3qtyhXdpW8uqZOU4SThYUQRO2rmqfkxe6PphPfcwEnVhmaL69ZJ8LH63gTX2Y6yGpXqQxKZZicrJSUXQqjbZsbmJFy+br1+xI7tZKRufE1/ASZo441RwleYyGHJKvccD3QKV0JVOU923s09N/9zgu75fsJT6KXYsuTTjuh3nIKyM7Vo7LzZ/YvBfNANtisrefELDp/WJXD5k/SMl/7fwFBcPBnZq9D160iltrFUOnxXo0in1X+ygK21tfNYTmLm5Vgf1v+gWimE7qqv/rSP7D2cYPUJogLPi+XF0eHl3bJZphg54uvT89/iV+GfPLfZ2nqfL84OkSj474O5ScT1Pr/T/4mXzK9yvfu0L/FEis+uD2VVKD81kMd57efBjP8oLVs66mpPkyPWnLm/LdnLlaTTsMP6A2gNdWt5TtVZ8Gqu/vaYtolZy9OT+sxapnB1v3Jifo8ap/A0q4+yoa29B1Pna9Nm/GwpAYT+EY/M5rZLVqj+vnc3w1z25VlQyNF2hG+yoEyzpr3gE0Tn9a+9+b+/bbUv0lX5xmSzTlUmT3Zfy4LPvy4fTzl8HWpRcznerV3Fk70XVr+mo0fALPYD8+q4kyaSuhvX+3US6dFxC3t1SJnO9NPZLEUnFi8bAS2bFEfHMNEpk17rRjSyhNo72foR/mEsFhZlPTE5jxW309/mg81Ba5j+lnHwj1Hzx56e8oO0PPjHXIj7wLiabg7m/1OJ5v7m8cogL+k8v7IuG7/0PnGS8q7R/R/qkfxGaj6NZ5JZGkuqBgjQPele9YOBuK+aMopfjtyaD3sSPwjtAgO4GntbRFpffW+Ds26LyXifd+JHCkqfJKeGxjct8tLdFB3AxWV6nS0XzqZAg4x/23wj4owdNbsW7kl/CXic7Q79VtOr/2Hu/Dg72Md6VSVNOjAPeB2lSacwrYbbB5/XRt1H66o5wRJoupdDuwUKRlQAP19lXzRkbUtIraDLDWESn/WR8cHbsn+4Wogz9N46211A7O+DHcsX5yp6p5Lw6n1yLb1xYjK9zmeyC2ZFm7bJ39X4Z5aTbo/FpyE01V7v61CxVJ/vk2v6ovxbZW1RE36LyBlUlW7O/9X/Xu4Fs6hgEDCvupo3PPG/Fi3oiTMv1YyGl5JX52b2rsLzTvZSE9T4euBbcDgyaelZ8cbXa+658eVUtj8Pjo/vhsLmf/OjxAZv96/QtGftmFOfSfaXnn1+jNk4uO6C4mKErv/F7r25mlaJK55e/LksZCvwbIuTQ32Ictb5WEkzaQIj64LxdfFyskS+WMpQihtG86Ndo4J9fkVLafCwT1PAOxe9rTD22so3cJXWvnud0Soin5v/Bpr+KdKfDEplyg6saVNV4EvLmaGf/p/Zsqges9wLdIDrq8tmENyToi6wknyoV2YqxQtQuAPqL3++Hu/Au4D1G43jNc2mV3bIDYCwevsTHxOG/aPRuauVJ66473bpHaIqv6ybB2W/FTc/27LB4WPH/LRbsmuFBbT0tmiwcVJ+JviHv/3j/1mlud9T0PZVspMDC7KLwHyqRVAQjgqaRDNEW3NDnMe/0bEbAmyu2XfUBFx0SNyj94GQK8ckPjGGn16b9xC6Dxb0JaMdjL8ys4rCg/4udakiRVwZyHFI+FSEsWMdUFnqnAnZjz+OPCzLHyMmp7U4pzByrlMJgiqxk4MvCLR1wWacTb7hNGEZvKUCE/x44MCmGq6lO9hvk6IwE4il3+c8A92Fbp8aOhDl3L4AZIHBBRLnLtbNH4/Z9b2//Epp3ypSW7jlPK5elVoxhzNCzTDTA7QSJM0FrMpXTVt4NXf55Aew0SYVSAKNkfSozSn+a25QEbeRwiizPQYuSZ9wIbtNtCd+oyLAqAWoi8cV9ix+MwRjlAmUL2k0q6yRJyEfN3bLeuFP8ITCl7U6nY6ZHcRaTpI3Ad5kjMDCipAtipNullJOvlBI4KDmfJMcDT5VAR9Q6MiAgEgnrgo5T+jnWovdMTxB0PF2pZPHk2cZdaQiHn0vJpniNdKYHVnAh45eJ0NBSwkoRbOj57Y4/3VaWn6pgwfezNzTPcca98kCBN1qSMeJcISzFaYdI49+ZX1iNxf5FyeTM6NkbKpURcO8its7FUjz/3V60o5MRIEp1zzSd0tJiUslSgi9ChSFwmFjMTGL5P9nwXk7c0mmtmmxaMeTSDF/wEJzZOBrdKNZ84w0ewjQTEu6S+7RGXRJduK2LkkFr/fklIonCBAeNuPYi9MJ4MzTNU/mH84jV67gTyeV/V5mQ87r0wqA6kSSl1hxL2OqyerlgzU63/Xs0ko27PB1nROE6C0PNbjAVJLAHvEa6iiy1TJVi6dd+rPKG/WzisSn1rVCGSROFW40ihWKwBaKm2Gbp2Vu7jczil4pzyDfieR99MubaYKVPWVomMQXSoh0iVQjLoUWehSReZOUFuWwLe/lnZI42HfJMINPj3wa7B5Ecy6jeFru+DkWrI7QJyFENyZ/VpdtlyO+MvVDySZO3Ph2Dt+djW5KF3vVg4KI797cpw5U7GG/DbCohaaGrU62pWDecjAtWi06cNfrFfYQeJPrMKT1flkWJQv3j7WEwIzsVvvtyd+qV3oqXLvmyu84k4YuiC2hyjiZPOG3EW+ZHQlCJDDnCu0oR4DHvXsEi3d7BImnjyuuA5pslZsgUoaD6AUW34mAPxWAuDRTHv/QyYPnpKjjEDBgnf/NurV9AOA8XGeO97j9l2Fj8Nn4xI30SANkuq5Kh6HyVARP7t7fGaZHqT4EQJl/f6P/r4cWrp5TvoQFMyCYUZPbc8vxxjnpsAIJv+WkG8Xvp2ce/WZhLL0LhrfxyCKjQgccSlN3km0zN7frJ7WgaqXNEEgHK5U+9MOKVilU1c4Dp692HX11/vvKC65yeGRcsjaigXvB5I5feeMBFIlVHq5YIOZIogNsuXMxmHOhAUDY1J1E8F1Qxn5LAe+TGNN3D1KMklz3f/JJRi6S3U95a9bHYdmCqa+04LzeQFXgVCFAqF+cLI5+L2uTzuUELtLea7Rss73GMBq+IPN5Qu5DvVv2b/GcOfml5UZZollFNPPM6/AewuVhtxD0jy11FrEdu5XebD/5Th58N1POb7pz0Vz7meoW4UXl/DzkGzOqL2q+GreVEbxPzO2+/zS9Zxf4rjkfxPKsDQb5JLrxbFdcyIIUA4SIaXQ/ofHz5vZiYPFzs1geTUIKMIfNGCVfwehNVBLnCHZtpybqDseBiInYUIuztOMZd2OCVh9lY4+a7RiCnBA4z/CHhdd5QYdS1DLH+O99mpAogNs1ZJGeo05Ln+eE/l3x3IKf4wQyw9XcwP+GQ6r+4ak/KJCK7E36LG/b8FHJnXCubTm05vG9X9Nhn3lzuDSXTElWORgnwNG+R5cLuHTjPWMQlQZhYA0I5HrU/tMjc62YwGbx0MMsx7sOaJMgJT1bmvOsJ0bmQ5bMaS2V1MogM9/FD0+ol4aVG9HhxCK2hO2/NISsUl6cmgx5M4e6Ml3W7R4IK/zF5aXWiNEedtd609gfd1C5cK0afhEc7rQGD1Pqx7UxTjujX/+/fVbDXWow+8wsljH1L+3TpcR4F19Xx1InatKGlnHnPFU6QtHE6CvJ3XKbQx/B18/dZxjncfHe8M9RYhR4ycOGTyN/Kc+m9aC/FfC9gVNyWR7l647J9wPRJDVUi6i+3Ggf1vSyW00P/CVwHfrjHDzDhKeSEukbHnSAXfrOnmx+9STtSSaEmieU+j/XoOKeXB4Rg3VvOXUBmcH8KbafvcYKWMz4oGfrmyX5oBq2lOR/77RpS2twybRdgOhnX8ZefNVx/WF4uHcJ10UxypKLm3TFJ5UlfTLD0Pyj4ZNTi+wi3fddna7N7/bronP0QB3ETr26PxO3U8vZL579LAl/+0NO9G46VXVVsbvJebPn77R8MDXXFBpXUnn/qTbyFpEBqeJgEB0NkVUL+sF8Nj2bWbJ7kPznh1g6zivBBpSMU0XJsuBpK30oE1gh3axzWMhDSDXS/qj50JXoWgbAA6mpcn23WNI2ECum2h/ZWOjO+bQCmn5xmMYS7Iktt/0TCZWTMgIsNKWQd8e57siiYdmt5Cz4aCmMIJF+tw3Y2ndIOfNaN+Y8ieTELBtTvtXNieGZ6ZZrXKrfpo7nTdvAv54rEjD6Ypo7COF43FfhFTpx911nc8QvWpbBcOyH7FbwPO49kjLyMMJy5y43KNlke07KAE2KHwL5rD6RenQFBc4Xy/Y7l2lz1SHu5bAjppt9J8+CZcVpsm4K+5LN3BCsq5vZWBP2eWlDrIadQ76uLFuU66hylZJKaq4vsi3blp9jfvBbis+R906k/r0m5ryjDe8MoYmed9jEKB0Ew0S5upzz+2GtNNjQHlz4PYq9JlK6h0TUFvLUREmK3ti0DmSx2sjJC3B65YRoh3wOZKyi807PmMEj1h0P9pPT7EdqsmPnAVCivsJUgvUVvrGWeGdhgp9WnQUQDiTt8x6OrR+wveaQnyOnewhtEckg4jt9L4ch/90HwW2hqEQyk03P4/jRmBltq0ESKy5ptMuq1VtXWuv5ezw92mO6/bu7jUo57UdBAt99A0hWLmFkFSPVNvtN0ihCBsRuD4eFluPqK8Id3/K0qoc31Fsz5BDvTy0wzdo5EPuOujA8kvQ7TsCGzZh1auPgNisqmnBWR83Fh5vN5JJtZLXti97Rcs7wffrAPDWD+ZtC6iGmeLGQSPNMbkccoe2rLODzpmzEKpLrZDvUoWt/R0xQC0jfSJ+WBW8J0LPeAGD2ls9pt48g/LUfa9LpPbwFXeb6gdutJCrMrWfJ7m+4/laCQT2EuLrXcArX9QUoPAF19dT2RPVx5is3c8OytkG4BzvElhLIXP/nJdYvpwBi/cfXpEjEGOuxayd8fyfVJU+ivbyat3LO4cSPSvZfeidv6IptQiw0hYzQk8JZv0GW+9uCk+EVXe/WH92cK8Fzn9qm4pBZe1nS4lhhVs9mOLk4KyyYq/N2NKao2ziAreUF+OJnp5nt6eioFaWaajsw7UUGnmQF/1nLMkgp5f25gKJ2MnslZ09yEpKv/knNr/eIcmSwZ7kW7q74L/upKN9g8eWqVkUKScKPjwJKaoNI3Kj7OkeJma5gOohwnzsNmcDl05O4lVfLz5yfqCxJUyVsX3tIfKbbC9Dpi5+Yo8ZJ/1b6lSqgfauz5Jk9lZSbrrtMeVar6VXjweESHOgqLInHh9YxChAeC+wpDAVxPWF8W4hyr9Gv6ADcPmBN/2ACuL/R8Iq6gZpxqM+XzN790JbPtESytXHRsicReungt2Dx17kywfDfxuT+3UgnEUI7Rkr+4dL0GtHgvZcklWGVPe2WFmjj0AegaJRnE3+Tb+vXANIc3Pr2KvoTeC9irdTxJUsuprZ8ehQJNPq76I5RcmfPXmJb9RMq8MUX2+OxAX9ovZp+ei5bJ66tAfmp66OewZAlLFBkh5OtZp3IUfMNqoC04yGIyTFSRAoXuS/UKYXvHDW8z+nE+aA/W5Vn/7vqk0kT6gQJU0DdGBD6k9lQD/wrwcpZGoJHZ6CiC/6Reh395G7STsZQkLC0v3ASHaz972r3arYgWI9U1MXWJgZoKC1U1mgh9ARaaB6bOR/jrk3Gjywj4tY4DpviOHkqIr+Jj3vJa+RvPD3XjcxFNcNRgNJJ1Gh1HCWvF3YUgCzdzciFttroWeAEHSLPNkNVWA34MEnqk0dK8+4zF7bpehWWg07gIKiAvnRKKT7132YKVYjGTFNcGN4TJVG5AY8RYRIRpZJ3HjQtJ1L5v20shFzTupQag+z4bGPPRyB4FdbuY1WxFQRmVja/4xgDbYebiMQQ9CO+zPscuhK+w2d0cBe2iBvYWXt9V429vzIlLg7u9qzgY6vAA60TgmP7wmGfOkzoZ+ngOnXUz95dHk1JX5PeYwmxDJ1Q5JDthhM/E1j2IJADf7b1kDP4bYtbTl+0tD0hd1A++63eey9MDBoVOeD2O9AjVH2VMEWSu97Q/+Zqn6VtJi3coByYF2AG5Ddt5vjMIn03bgGcRDbydhw7itKA510v0acaUWU58k0tsJg5DMRTV5nMp8KUl5XheHsFAQ8obprisUef4jZuLakrVWloZzWRUbuJwGGIFU9npK3l5WkH6zLEZf55Sv966L0Le0BH0mMe8qd/RCkn8KcXAycyP0c8XvsyT8lxHpvqdOU4AytNeiSjPNii5ecry0/BHQxjJlB8sIWHI/OAVDY1ApqERxP62yuix5nsDWok3tO62FLFxqz722azenncDDS2hCmv1FN4EzfOZGJyAsJwSQ19XejjK70958QqZW1rjmdEYHwmm/63lzKhUDP2DJRGlrcEAtFTZdramzzbVQrURqcKaLqDDvndRVjxt3enky1QLyGUcTZ5GsGdxwEfAvDXPp5QmGvKcnAK86gQAoMY9IeEPg+SHbJXV8wYvKY/acYfWS6Y7/ysZ+XH6SstIP3uVxHEx//AarC2BPRPx1DJYz+zlxJn6VTXAlY6OSEYU9T14cqpv2RuSW3HPdCNXN19g08Cad3RXFcNd28ZR0G5rtmf2nbgKbheDvBDYi1ZU4Wn4S5Oif6sB7m0LcfmgnH7KM7Fs6ZHraZq1wubR0UwGPkHtQn5RNsTAgx+ZqPC1cDCgjeUKcnbzUjeRyZhetlJKIt/87lPKcoycBAydfTKJWFNacJkpMkFFEsgx1hL9nfTAeaFNfuJImtEWWN2m/rJ4OoxE4fXLy7u17c/qMcPDvyXvtNRguJObtL1yVy17p6vRojM/MKvFpFm+aUzCLkKmy1JivuVYGMuH1JAAmMlTTkyXaNTrTkJh1isiey4BR9rmd8pMEEORfQcnAGpg0+7tiMC9ZUd3JEGzaRw/5bS/kBy13DMhl2NnC+iHB6XUqlJs9WlkGnEyIXWU9crelfFNPE2Uia4si990yn6fUK5rbKE3B+C7qCPa3Jv8w8eJcHrZlgwlf/tN63BJ4s7NT5mrRgmlemcfpcpJ4cxw+GlzEFTsWZ5KRDwd06JCeJVaK5kkKgwV3J1/tEaBTtLgjdssUckZsywhjus5ZqCeNJw9qvQeSZSmj+lNnw7F95t8RUqcK0dC+dL2KBdyCNUzLiVYS62zTckCK3RL/GHs8ZMgufxtxmGd/t0dHbZMXDvtxNXTUsbsduVS7cgebr60jofaAlMm+a459YMGuYXhUzaSytO4B8j+iFgKxUheRNC8sQiPIhsuqd2EjYub+RET5UYYvX1XacXU0BuO9bq8kgWFWRAG1xcMwgkFZR8HVfIzb+6aHMtpoWShrOMhvum1TN5M9O1hRDwd8T1iSFoy7INjx7/5fwnJD9mF9y0v75YPKrcSKD0Juy54w8+eVzk9XiGnAEF+EwgYVUmFXQx25Ck20IYvJSCv5gHmhd4APmTwyhG1W0T+jFQdLV2O8eT6W3rvWbw0xQRl9SjmZQwe7rDj8D6UDHgNwN7Joc4h2UIlLpv1mLNPgcn0GVUzv30A/LGtOMiIYTjSd7kB4SxV8FS/Ce9N+xeT8IKCKYPPknZHkvUrahBHl5TmsLp4SREKWnu2o5K8DvxSQwmyVMrNmHP+3qKW0AIxuPboVqa8aMo5rRjFOrHQ776UK2d3uQ/fpvo56bi8TPVA/m6tR6pAGfEQm3JzcDza9FJFgC7881Pqr5j+Qx/lp+REwhb/KQbL2ufnqcWoSvL72f6oVn53v+Npn02xxNhTj5TPOlsf3VNhnGp8AeHc8syeroJyy7ewIuDYsyB4pixZQ67BLfE2sqF+5FwqDAo2a/HIlhIqNURF1Zzoo9HciiDQni9UjSeMnl/u4o5JMzKt3LhWprtMQnPppLl3GKc8t3GnILsgI3HdWJXT6tnlLpEJVvr18uAowBNQe+75ytAtpq5Vc9rhA6NPM8RlBn6+pASLy+aJoceDZhmHvr5FKRTUIv5GGuKj2Gw2ZkKX4TdKc6rwFmk0qrJPIUClkW/+jVyfesredC2s1FKYsHiGludSUIyrQBvOLBRFj1U+4PIiEwsof5uTjGfba0IaMUDRwyor1y/ISP7WFNDd4ZSbaWhNvCfIPv3gbO0K3DQrfcjkO2JkR6BTBGX+sjEu93Ce2QYK7zYZDXja4gPqzjONBtPyo4i8JWGUM0+rEmmHXzdTOccykwSD17uA3Z0aL7pnYz/nOEbuDoefmrIK/Sd96ChBRXo1Hy/osp6z/UxmaF191YeD5DxLfVMf+KSflRMfJ7zjBqpxMlp5LK3pE8KtJqN0nJbs7HrZv316Q/LiJmOfThsaJ4MerefUQCVlaeUHjcr6tlsy01qVnyjkCRSXr1OYTO9e5Gvrm4nDNaixk6VPOqD4OSMSSWgu8oP+Wlt0RWO6k8sNgF4Ku7hh7NMM4gbx/vXoZ89uI0oMS3JdnYnkG4bXE3dbBQ7x+ND2exkDA1WGRvTCfUjtsGReDTou81xwzFfZekFtnnFDtOm24sZNBCLyvRdBmuzNICoamZQtLjA8IH4Lybf38HKMBYCsTEtG6KqV7334bnNgzblcmdVvgINBsFUQJApKvy0YEiVi87Y/ig+se95Jc8Z+LK2PL5z0PFRcYL4lo1Ftc7hhzIiIRniSEZpNGLAaAvoYx7fDpBYR+uAtYNnv0tz6lfRC+hYTTZ7Akli9oSOszAFU67mNBH00btl3cKtJB+c+oMu+gLCyYTCx8fOP8zXl+135DA/OOZHRayLKXiCzi9cUttpv0MJzS4AfjmKKlGCG8hLbXmG2C52Em9nL1tYYlrjb8/OKSUtplrb3HeGvApToe3gSZDhbnFwZoARXNjtnU6GmBiRf8YTYprhugcYmVCwynuFRnSbcFemyblQTzW17Z/WA9P+S1h4RRLLkW2IQ3pUEdzNtFdNJ10IaL0T2sqyd30wGQu1FqdLmoj5HSrafm2UFzbIgse4Vhvmg1GKQ/S/OVE3igy0dPSglCUVLAdTXdQ+tUyYAi+VIfgh/HthF4m3Y8T6Jk03RtKvpytYoroNzYEZWseFDbLJgvTT9B+rF3YEKOV17mf5/Ba4racyX9tTCX+WeaftqvtZGHcrSXlx2+CRyzLTU4uFOYK//i2Y32lcQSaXKtCxsU8XkwX+aZsO7SLsB71/2ubJJ2PBlVSGkDysFHYc1u0EPl5NAFzKYRMVSfHEsYQ0qFH5SWTJrnaXbnapWRSH9MZbPTuuecrWXfsfzGxRkKKQ6bTU9DkGUPElX7KRRFsNx997oO1SZxcYzuQtB3XwzKeXS0nN5X01U9MVx7NFKQAdWrscHlyXDdpntVlLkXkOcBj48yxtNFAwXgipNkvzTd/KYRtxu1GERf8qYbfkkMXqN2ijpgEgP8Gse2+3lIvKUCjRNkVANsmzeDH5oKTV64UbHKsNvAM034qx3nBOjXdPPpBeTL58iukz8Gbv/O/XmnZlu2ggStxfiurkwzm6neT7V8FjZSjQykpa8sQ8Sacp/GuPCd0dSd1NIz6SkDC5a3gmYoSr+wHeBRTrCuXJMCFS9iH4rsYFyaXVvteCOI+71HzvO/0V4qvR/3vpu2baWEHWkY1MQ3yxfGODaezmhG7ynywoEHewHb39vg/Lz2OBeHM2xFvLDqZk0/LD4TEl9E3eL8k0o3ZccX7gKNWiKq6wd6jXyBgjN5IZlKWtWbRkY4atNEPpPhSOKUFKHm94Z1C++YY2yvjIsqe5EsMZ5O8oF590+nRXTGwgol8R4ZhN595aJpyGycijP0iZVbYnVezKTf2IINGu8uaftSX2P8xFiv1DxGOI2+FGdfW8T+DNdK21jmoAQviimWCk+r0DeCNzHtsfWQtvVnYfaU0oTbUK1yxc/Jq0fwmMq/GL38ZjOCaJLhSxOdwObbBhr6iUwknplQRcc1o50VUQaO+c/fjIihQUqogWt5iUQdX6N9nFKudbnX3t8V/Y23OnRVSGzj0R0+4wHO6Y8f0fMcT+Qjpl1r/XmN1i4BnikD+OoKt9sing66JbrhhRfTVB2MWKWdJqVBA7TKLVKa8QXFBdF4biGCLCX36A6p7iN0Sby4iLJ91V3kpBQE2nSZvAgLzSxPhYBqTK6nJHN93KgJHxCJjJrP3KffWpJ34JUdgq+NRjcOrcUtoMb9k6UVchV8LexVDhaMslrzSjOg5I4UWWc8jls1VEusq9rI5mgWxxTCEr6ifwcLzzK6P6LgtuwZBRZA4qwFOBj7+0OVtfvBir3gLQuJYLfHFZyEKjiAZYyrisiCmm5qUPsWV7mxrSrWwkCKk02MxFIieRlQt7FXFOXKpKCvJRQVFxTonQX/s92tZ3i1qLCUen9bwkfR3CbdKqIh/E33769tyzSoNHjX+CHXC3N4no9yjIMIDf9RhmoVtWyT8KQM0Dnk/D8TLacREEO7SXMlJOQnJM0HOnCtaDx8s/n13CwXHOfcbK4YU1lOT9gzN0i+f6H0GLnX86YdsSF48dnJE5/JAedGG3n1m78CEhiPKgMo+V/ltLSXdM8t0l24TLWrXlaeuaGf99tKEPRFIq/0n90B50et08sfSGVX+wIQhAx4hn1kFqkeQFDiiZHH2vfdTPXt7NGVKHugCPDPUuHTxe2ENSzX1SMgvn9hSeU1Ux9nrwMdQmS3IlnVBs7tsih/U3hfHz4LM0TEBGcwFlBYUPsHy2uCQmnV/R34CsfhwRp+sxeKkZxZ7rNlyoZOB7P2diSpqQlvfoINUWt8fjelZY8y8xJJ6Ry1nktpIX2J6O8cYjapv1Q8zvvWJJZpZMgtju/E9ObO8iG+gBKTdPr9mL5x0BivdmN26cVc5KvmkkdpgE7l5idyfAjYZheglcxAjHiIJKVJPDagK1EyYgMycM89UY+CCWDjzM8CLkDv+UaTCXTJfm6+CGj8p8/dNzqhpb+bqp7JMEpB2xqfmScPR2zQO+i76UUoJ1CEhwxISr6wXLyMelmbtKzuEIzB7p8ctlVVuGx9bpZr+hsMHyo8A98Xkj0VywXuk8gcSRHg24jKwS6TNSRbvaOoJvfCspf428UznNQW7vPH7HaAAzwzpjCxX9XycPx3py4Cwnygd7rah4vXY9R2AvDgcTfR/eY1o/cpd3db9B93c7wYBX18bi3EZ58vHEe+cMaxeJJmXr63sXhRvmeDJmIiSnwI/KvUi+nWBT5qgCkfquDR7XCLc8qqY65tGb8XWiX6w9TdImOmN+IIg8yaYEjJPo2TcT1C9PPn1hn++jkLZVGfmj8oA6mHUrAIlMa7SnGMm3Vp9cMkqP9bEl3wQLUtXMLdJvoaeR2IWxmRej5RPym+PlwCFG2nSir0H2yrQUy65sYTc6a0O1oq3lgPDMTMk8T1tNXIScKhf5h1A51BCisne6GchpknPH0rbKNRFjzE6pdW63wazyI2cP+QjG+Gf3JY2fggM1f4BlBPSbICa2giPdztcbKPhC+r5yxXQZygnnwbNEjk4WIFl4tjReG+nxsVPf4S2RMGPukqTa2cthGC8GajwEvH79US1OroSCO9wVSqsVx/cvfgeH0zbMjBQowTQATwCeuG6FJ/c7Nl4BoQR0m+uIYtLxim7lrZ3mX98lcWn5f6IFQacnuNyYr9LH2xYDzZNl19F6lmxL7bFWF3SqQtEudaro3g8lzPcjKPZ8LxFT7iy1Ld0TBLTHAaAzp/dm7+j0HKWKHtFbaXXfMqzGk99tNDNnw9EQRrfEpW7UK4pH9PxbOfZpEstU6FgAvOVfhWRlBQYu+ds1nWIMvNZGPPzjdu11L8QaUqyyTgfTeybudYMTE/ut9wpMhXCSLjKGJWkbIW6NWJu2C5aiZUgjHF/fhINx/MK+u5mr7LK8I2k3svaB6ijRHO+S5Kst2KqlxRYSmn9olm0we1KdNyuaKooWuJ+xLXtcyayCKUS5uP11oPji8eUsuhiniL/LXctJOP5Mp9JTObSWVoTdPgDUpdm4CYFLqsWL81dUXYqbd/ppc9KhtwcrbP0kmYGIzG2Ok/879YqFz1tojbfkDob3jxlx8sTtx/nTnnRZ7ShormoLiyQ/vp4KjQL7Sdc5+y8eULpkZpPYhbBWD/iYumirotHPeFbdIGkL9oIMcLYcP6FYL/jSfMbConoEEXm8Ct1zkcDFqrwOWVds4Jw1ffG0o0L5R9ORXMRwhwrdQNFH4493n1MZ8Y8lyc+7D9sIyreIS1H/eI8VtYzqDPgGP0kpSk/ZNklIUoDeKb1gYIQCbTwDwHIYfMgY1qiKT61RAYSnx26ABG8jD0BWIlOm9WtosH6nsBsVuhlgROiAixBHW+wrYKVq8399Zj8IRwD3A196+6oXQJNmILIn+h/SEAuVJfPuTrX+RGcCEcJO8bCyQCqhrwAaQClnUX4fYHcPfW0uBLeCFVIazSckttFhWKeDlhUldGIoZPlhxVC1HA1uRAxD8cLyvvL93yGcUFuN1I2dpBo5H2XT1WGhc3b7UCUqknYPquDCnavqg2aNLNewTf2S7NnpWL4m+/GOigoKIZHAH0SZkIesllLiUXDmYRx6mV78TMabPsc7ovkhgSJ/24b6a+IPsFxIrOTob3eUgrNR5e/IxwlYRrw9ZkDy/BMUcX24MRuhTxp4b2EEX9BfNEF7xAtMXshX218/TwDDo+YbskS8jMExRZo5iLtRnC4C/d0DNKnb+QMLeCY7newJYFefiy50ZqZJYEPoPNHTMtSMrF9JTtb8k3JAYFtF8i4/grqQ+Y8Xin44cxPzefETxGMEGf1htq46rd/2OYYFXX04om6UsJOP8h9SlJsw/TVeG6Hkp4ISXmn4lQi21I97C7NNLDvRq9uLJIdfnVmJ7pDSSLyIAbCwO7AhS1ReoWwRWOb9OgMZrjT+KfF+S5VmPwq59KXnlEPmuJVHkhw9ib7Qnrm/LIeaVM68RMVCcmYIQA463UNqw3cq8MOjSJut9AMfeCdxJXbxCp1VU6AdR8wMucxKWqjlF/dtWtsSm/xeaNH8TWwRuJMGzX1lNfdDEEGDgYVdRqAYWXMK1idQsfZ0ObTm2Ux/SH9A0q6rbK5f1Ukpex4ANdBoWQTUZBLLCKM1v9GMowiJI8l4xlNMjPymcxOx6qjANz1H9Uj9ldJ5wXZQEK0NDeZDOABQF75QZBsiP6ULiDcCikxWVenzhut0lPQNynYi/6Vcef/lZQKnqG+QMo6OyxbQ0srmqbnHqn4N6qBF0/Hew27IQK8dR6wFAlCpflcH+bemG3lqt/Wm5juyEyh1XbbIvLjg3jhoFrk2QHuKXtiEVkpgQd/31XEdlxY+OxSYpTPevabSn2gMVSIq6mR9hqM+z7G0gQsIcrqpIRAwQ78Ws63Fkngaj2CGtl7Mu6KhS7ZlYJ4WWsFbPzh0A6czjgmvAWwN8vKWJtmxPpek+blcrXCt0HDJn0rqSJtk1D7JGZecnSwPwSaI2VFN4rJ5vPAoVpkFwW1Fg3Z1kQCgwhJ530Nw2FQRmFmjZKsRjq0/65fTMRTuz/8aCb/pxdVI8o873xPL4czNsMjN2gHkjhFxO92eua3BoYKv+Le8YV2gFly5sqdqFL67UNrsMoPTA4t7S6uFt+09Yyf3RSQbnhHhEA82RtwebJ2Lcb1jDbTNYBOVELZbwc0naQpOE1qmFZy+xFaxn1kIhF1rQnhXkBAIUJM48e+3FrmkGn6+XZkA9LmbLMmKpoMRwK2fYpF1zhrJWHn7k+KA3fdlNzWV9SGU1qzPpG6u0ux3Yr08YcNiSxX0dtcAnvLR3+gpvwIlZOv+Ywa14fOlV7KlB/g3JVD9jqCHl2oCIzVdFDLNOv7o4CPwXbgP/fPpfc4GBm+xxRmSi4QTEshRcLzIA7p48FxOIw73IhdVnEzBGoSfW+u57XH9luEnEr1Rhi9c/oD7AUP5Bw4/5srSdfLIeCpkmFEn3gY4g3qUY+cSBPd7nxaty2mImbG8fy3oEDY16DdYLv3zlDjeHOoynUmu0nX8D5Yajil0UVyMY3ze9FsNlzlNN94dlzUjemqlZp6k5HJk1wDZxvO56iDiOqEdfAORMazIbu0b27Sx6uX2b9W3dxsiiAw4DA2mnxeYhLvnQBiLLXlcdae2BO6LOJ+rZUauExZE6vIJ/VcxgUhdJwUEtvnlWdMHjTq7EKuYaVMaXBXz7ec2+lA1EaGZmz4ceC5nSfeHLcnNuVvNlXOPR+8F4kRV47nbfhW9Wq8QXlBY0tMUAkWYXbTnbRwKZM+4D/NBy6DC3LBa4A9Gk9YgZoXcYA7G1wqUzzRwbrHweVF4QflFqYOV/Aagzn3Fdka4z9WebcvyKeM42aPXTq2rxFiR8PLHbMY9rNUtkLDgN+OzjQf/AVkEMfVudhXOGsoVLZIqIRrtdkjNRxAL2bjcX3wnzvE0q4OEcVzumQa32Q0q1xhYaKuZMyC21Wi8SbldS3z7vABxfOAUxZyqnCJ1ePZZJPf1LhqI3k1PBK2Kqtw2QMhnUoMWXQitEjeQppqynhfYQlPDCUrhF7TD3N7G5skEf4TRK0uiA10R5vgZ3zQ1dnKiueV2ydsX+Wn/D0bnPxN/yGTMq6hlo1MRat56r1WV0aWg9AxE9hlDK87pZrONHfDsQjeCZJPUULwS63xTHX+OaXDagG8fizqjsNCHKLs8KRqE2XovKxVAqS+AKt83H/Nndn9qNEKS1JzWWf/EMchhKTcQx7PY3rk3Q3TuveK4z+Y8SIFNS1yCbopYXJIdh8T73uJaoBqo5W6I/1b7V8QqvsIbwfcJID7yxlh5YOILV4POMbGwGzDt8WIYJ4OC3F284ky1LP+y43chFuKFlP+GU2Sj3ku1JFt0q/+CQ0D/Sw4c+B2q3K/grkP2xYMA6axfpaBfht1Famps0ITORndUvFoK8RTiwD1WlJTp4NsjH9rjpmrJyv9VPByiWmligq14/TgQfz3wh3epdQCG38Sa8qxE+SX+j6vuWK2oAKbJFOw6VC+NDVLacx8Doy7UMMhIVe9WE2410vuQZX4g7Us159bbDVaAsxyn8Arp//8lb/5mnZrT3GfKG9IEWfc8O3XwXAP8ZbPUS0OC18eZwpNzvcW3Bq89pKV9GS9uFpY5ppchlj5deb5Hcl6YrqmQP4rb/hGtlB1NTfM/KGEe3VGF0P3LuTT1yHkRqprus0ru8j1cSciRtjdPASS3FuNQlOUifSrHA241E+6Cd/1Fu55RcHkaloXBbVBoy/97tDRQ3HJnVLKmS8imRnxEd34B3Gwsjlkj5cylhAkmu33ii4vtfSnsNQaLZfFhDNTwr7dhLXaD8BNHnOKeZ3HxwwP47vo7l8ZIbtq40A8GFlknjQAm/V9G0q4I8HuTIazbDITcW6K3xmYTa/0CT/qf8UDLpxylE3UkQIWuy3qRVbMua8hQtjEvDnPnS2sG1l9OWVD5tu6nS1Cdkded7M6EBTBt3B05yDSlvAJ7VTW51CGPYv3zc8cO6T5Vw4fljohzf83Hvd9zzDNQ4HmQYXgi5CsTcljlTpK1m0rbsr5eNpuJaq0YaIElzRKBoJyp6wm2nqKbYt6TaY8l8meW8N8s+AaFpSrvD8f5SuYdPLmczHiK3Zns/hqg2SNTzWLcsBhB+xYua4TN5Gq70RSafxUzwELf1Wy20GEXGoNdAFEnRpVIZczRv3ru+v/AW01FvWTcBK1+CWN9IypioE/RMOUh6E0iy5yRQODsfMsigynH9nMxZDy7LRslc36Eer+WqOQR7sxDH94FkcnsBp8kjJc3gqwg3/YTLR+LMpOT9TXcbmNRq/D7impZF9dlMQt8vmbxgji+/a4NWVeXEBedhtMs0uKqhSIpliye4w262awZpb81277Yvye4J/9Vc5DYyiGhvf4UR+I+pgU2UkT8Dhh5cJd78U2aOxVwkWLwwxH35bcCQCgUXkiBwpUqFCbn/ywmCDIukxqi3cDOac2+zd5IJ32iWbyXIhsFe7bsPOAoMdgGnd1FmjPixT8m8jo+Mr7TcYUbqAy0NaiLmE52WD82Oe+ASzX20ZDkH1zjnQxluGbSymFQwO6rVcSQFgrsQ77F4TP7jivNan2QDNheuioRk3LVcByoHXIbP1RkUyLEW0CUTGlNKCutZ6qXNWKRMxCF3PfWSlphHdywwEulAda9QIAM81e3SzllFfixE15xXGK25nBFuYV+RVcjNorIx0QVDyb6sWaplOyS6PJu2C8Qt+qN1S8oRPP17k7oXmQg7mU/IUW6yyjMWjst55drMfbID6cQQvo69XJzOqHg8fqJmZj0hng0+3dEiT3tp11hjbh6ba2iPpCDIufvnmbGjLRIwfI+nUeW7FNW3VPb2kub9GlPO3WKE4uAW48oxN2SdlJ182hqZNs3/WgNKh/BkvQpkqh5FePYyeM15iw0QXK3XUyv3uUR+Uu4TsA6y3nAGAJOjdOOVWlP7F5JVJz59uiuZaRT1LRvXKG9CYWJCeY6OwyfG+MS3rUfML1MWSUiRrD1Ir5J/Naa0XQe/Pcls45NppXxn4vE+Q2KDGFngW7Kyeac/RdG2Fs84ssN4PhjzGjRBOksn01nYvaFYwOhFOduywk1v/CyN+fbVxnZ2HeEGvVwbyb+Ar8KNYrsOA8UgzyhFKi2wT1CPLTUd76UP8oF+ATyAICFMDE6rGA14GAtn20n0/0hfBJIWmuBch8mGBGOYSvE3fDhSlz0XuDJeAvBZAbcxUg0A/ZK4AZ8z7I0awyij5INNIH3Q0IcwOlDezeWFZgvXOz9M8UNlfE4sZipDCZ/dP64ZB3QJRVwgXzcc6mSlv0jhNLwFLIWocqrRj8QgnBwqxCodTisMzReRZzmRa913SN2z5ryvuV+dpNXaL7NpjijKWixSqjrcvDfKhcKrR2+uhCDBqSmWOEHfT4fquwDEhjhdbwZMKOTEvhxOp2IZ+NwrPDuIXDXwChTBbZt8Ruy9/IywYFKenRSI0eT1VBBRcNKL8v1qq6t27dGXAb99sEdeXUkWu27g7esqbBF1fe9cb46cQ7bNX6TXlD3/0p+vr0QVW8Aoz8ZCt1bPVGrjI+VbQInnaHTm7/Zr0DwpJ8QZrtdztd8KD33uKMdmDV8g8gK5Rqu9jqEkc53rJvn+DbVwD8yK/0lbogCQm934+DeNP9C8JTyi2SSAEZsL0PS1ZlCHAigpFjQc3HGGMb+vT2wbxuQ1pneYCt4i1Lq49SXFbXdQGXp6rmWX/2gq9lIcm4XwZdCg8P1tzvc+/2Dy97gGLE6B8s9lJJFYCUXHVmDtF7GH8V2udSfCOD/+Rju2+uW3BPFXSUHBBOXmxgwvSLEFALRTf/mQeymJiqXZxCS1RX1XkKj+gKDn/dV7EsMbvhhmLkoyUdM4LXsc6HYz1oOFcfrwDshzkJQzx/QlKeaah074HsbZYYcq+EirNNxcDbtr5EcMijU5E+aUamQPtKhfNaYCV8SOmBOl8d5tSnJgbBAaQHwOeiPFWPaVc1YPkrKJ7uJhTPpstME7pBvvnobVoBHW7sFclPmd7IWyV52iABZFbBNL+Osg7xSU+jjughqAtR7naFyPM0HrIIBy+OC9QVy+BXDWjHJCaC/Liv0g42UeYoKg1B20bz6BseMio34q1dfOXP6e1tiBjmdn6zHs1KaWUt4XR/uc9+a/gkQZyz4M0GKYPREpEZLLNjc1b+erI7Ek63kGIgCK0BG+nVZp9IVhw90Mxi0/Muj3BKroUhPjN04kqEMsM8aiWJZ0RKzXvmLYn93JMblC5fRqc5KrmAiziM/lQ8bv0R8ZKuyzDue8b7jjgxtaEs+2qs2MKcC0uEWnhffJUVcdPsxTgz3q4FXNzyoaq1FY0/3N8pik9GnfZr1x/edM8ZOJwpFf3ONMQGZrtCaZASyZeCGbEmfPXT5hbj9VmGUiI3V9c98rYTwnku92JgpTc/JlS8mY/HQU9eRWrJAdyigOA7fvGuqy25jr+frHP+Bfy+8Fqw+ue3GvT8XrgMH8/7EpalVQFUkpcgPlnehkhVgnoWH+E498lLdLN3+J8jH7k589nlIdjQ/hZEhHldmxHkSyzmI02dz7zSQSrTr8i8dSYLEjicPxG7gZdH0MNd28DMHTLJFMAfzCFMg3m6nK84oHSg58D1nP7db2XyFAm89ySYm+RlcyiwuE/DK3qTTRtoYVC2Xe8JzKkRcR0sW74cbeAfDWGn06zFD/hRUfPb0lqduaqZPx5mp9oyQQg7hX/wRmuNpYwV2goqgF5/UmnxFyDxXdZ5hnQSk6e4lglU4Ay8zt/ph8WnPLBC+NyFoaDJn2TJ2FzhHfLWj6LYvuxT72iB3c0PqSoaYKgpFc/bpEcNvbve5wL1J5T0Y2G5bJaR658f9LDKuhgu/TDj5Rv8DyV3H69f08rtddWnThWAgSuZ4BZ4Be1+RpuWpFDaXl/U/LBxN3SJGTbJv5c6/XVjEx7aeu4GrcqnC3hKuHWfrkyn7eBBkXxYcAN2IqzF3uytHDhqZQZhxeB9wF7KsTrzY12KNtlA84nySjvfvIGg005kQ+cirMhHHk6tR2DMPa1kmZCdqXG5mjhVuqJUodsPdKbduhnogLgjoAU3ktbTe4WkUuZ0dTclD86cMHsD9u6T39pUJ3ca0FUsNZIwH5A4S4GWFNDK5qIcnj69HFJtja1xzn32J4S4/1dUqKdfLCPtSmSElVMuMTaKBuJJL3XB/nDK2TxjcNorb6j17WPKaEkMB6uyfqoQM8C+bCu8lgN6bh9ZD95P7rleB6S21qXZUFMmqLBDDiM8127bO6S+LsPZPS8pOWxpNdw4t4J8UIEq1iTVaCx572t/sx7lEbfDFhD/OAJGU1nHNDCbx6WWa1/Lo62YitVCMQEKE62yTs7SlB9O+QdXKQYvy86f9IQCH3hGMBjZ+IwlirNBXRmoc8mLEaXOcHQCGYmfS2L3RF6EZly+9CNcBWVLEAy1SRVwj1iIcam1LLztXXtiz3Y2RwN9ECXo+y5O9zpyxh4qGObPf1Rg45cLNFyII9SD7xCrKvoLfSju9+6/Q+mr+dYzCu7qZ2szKwpJXAdq5Aw8kdYHXRfYSm/tCkSvmi4W4n7yMonIkKJdSw/ZitxDw0o2QrW74WVzJrhPgkvT/sy7nzFCPqw6fX7RXUBSVqXn7tKv8kvxWfzMvyqKba84WsUC1slXnQVFsaQ/NHJGchCUNNFBhlbxpC4kh79LhE/8cXzFXQ9wysY1ul2jx7Zx5IwtaMddIYE6imm1rzvsPtLKqr/8hy9df1suVfgPLVQDlNXJFLXcwzSyJNDxqeWOSk2m3U7mSbGEMaB8hBGQpSmi21mtHAQJU51NOk74rt7oCB7RejTMikwvMtVsl4T+YwAHZh+wALK+UWQAEL3pOYKwo1in7n8SI/O0AbLwj8j0LqQDDb38Qi3ZyzlSadqV18jpxb8tvYQ+A5ywdH0wDcqzQTYfVtcp99Wqkm6wJeuIob/nlhCjAYsz2OtjFzCEcKAJIHqBnY+KbD0qBbtE5huaCB3rVr7qQm+AmkesIVQp/h/R+s4XwNYa/KQbGmqIV1JjKYkBah1fiuBlrFVGTPc8vs246wT3Ry2PX7Gh6yHo4jZaUENidjTXFGQ/atj5jBt0BywAzQCjc6xasrPOGEoXo4nCTEUuvak2E/2TDFHzjcUSqVfNgcPgT9A4V2BmYczW6oPzQiWIiSPxQ+stU0k8JXgCKh0y7f/KYog6vlBb+AP4BiYnAyws/B0JYPEkGaC9/G5+fsuShZF4yZiCkKKeL+tnN/u+VQhCidnwtwEFYQm1iW3ljwd2PivPustk9wIW6yUVvNp0lAFdVSn7DWcIqusnNMBCmIxqyzVxObShekUXQeThnRioj2HG1TIaBejeKZemanWu1FYjHpWOO3Uxi/RBcCc5oxwa9Tp9bLMHw86m3Tdill0dAVg8xkct0r8m101zfS3+Gy8mgr6PzXSNaWqh5SrRB2ROK4mj2UxfILKoiY6F/M+QF/QbuswBaqCXK+Na8dYOT9V6AIgT0UqV1zw8QWYZZZVnvN5JtwPOCImfO7JzxidGq3R2xVDkq1CWUrMv28+6LT3hPlXHiL6lmhQWhLo9v8SZEsHM8zEaMqU/QVh60WGYo1eVxGxvFTDfmLZJpjzZqOtEB018YMtrgpafZADvULBFYopheUlfJ5ws4utojiAQuc6yZAjG0z7VzwUTXncirqxScneZs0u6uqKZYUOZqNz5dS5Rz+RiFijA+aduYEOweSZ9T22kuAVtN14qj7RDqrjslJKIoRGeBDNYSivK8ZVyaFpqf59zQPe9cSsldAeRbmZANBDvV7JIgB/U8uKBmCFdnAmJG73rP0tliV6MzOsNshotb1xbNS6lhKb676Y/OmbGOE7JJDFF5QMbfHTNW+npSiPYOiIaC+keVGRyIh0dSe+1lXmPW4hTtVCAM7ZfXgbwoRz7sS8g7ZYD49nd4MN115UexGScZ7rKzRvbqKqV1gSYPHK8kt+Z3haqoQFFVyHz/bndlvAnsbH9wPc4aIr/jJ0keOQzlJrD/NdqhbStI5WZMWNm1ak6KBbmrczOGNyiAxx73bQprNzLY/ihQodufItibQfC+fQNLNfAKMHCHFdTm00ztRCxA132QVxRGy/pESQWdWKGZuiBNhXTmv5KCUsGaaE4OsXlzlTBP5Yyjv5aofD7cFM2g7u2Y3bDtME0jEprmthM4TTt5VXKDMF9yFZsvL8edlkpGKVlFIBBjIsKO3JMW3xDHjlFdYbiqLi19cYbl8kxLAGAwkP1Al5OU2RC4OPkfu9cyN3r44FuOomCYxun11rN31Se4Sk6CXE1ifmi+x+HNTqZ/PyWMk/GdJ6aO0L63UAVlZhhCQNtde7mC3MtsyvWPc4bAlJTkfC3kJGJylug5fBfk6RNV4y4SNf4aSFBncVPM1JDlJ19nO0o0k4YzLGm/r9AvuQCO8TWPhW8Fo5UJDl/5THlR7NlJfKJxy1m/jbzMwu+pgF0EfhuHNh+laCxIVIIYIudoZzf5NqxfovPnt3/tc31CIvAe3dxlpWKVz9eUA5/eOeY3HxLQd3Cc1tPAT/6uExHnldWMfxzx3rpeEzFs3TAwpn3T4Tt32Zep0NK/c/ButLpZXg7T7MPLwqWXHu1YAS2BVGg5Q++7QxmSZB5sVz5bQDCghbJnbSLy7fWBBe8mPyeiyGe4TNQ8SL5aVNDfDlta9MaahmN7tMwqhT/zb4SwHzpBCcFaYpNy77PeZ7GHlYdV0DLnN9J5R9P5uQxnYLKChln+WXI7m4i9z19CjV/dPSDyDTt1z1KLTLg6dd6FUm+zODCnK610B01G0hws4y9Ae3HTy1XAcYL+vLmBmohFqTK1mMG0RMqL6LXRZopfJG4HhME2mvnkCTC9u9JY9TSjmyppbxZKxoQC31+cuqKKnKhKu8hUA5YF04p5ZbJEwt+5ESE4VgQq6sYFB1wWpVESnDLo54d28U6uhNZiSPsQ8kxG1qoU+RW/89hP1sqdbUdrmSDEnrvIOLPAMsmlX6Wv/+N/ZqUQArJJ87bwlJUFquMiRalyo7hzEDYq3EpNInn3andh8391D3MHQm8SU8DOJslhOXX1NzSguMvnj7+cXcbgJVML++ePvyvW5/ZGHwCnUKUwvHHeykJ9grzj5ELm9VyTrXwF1zwvDkfAYradou5BmVTqA0hHWkon1KOdzsiqth2I4CPZxBKCRm2OBa0YMmwtnLWE5HnGvSi+nchSYge1tk8ZeW9PxPqYGyGaUnKhP8aPjuejDO98t3pRc1bVf+dko1PaIBsqQSq8p6L1B5cRVvx+FIvpNLGNcMDldqtHwCfW6HaFvQ6yhv2fzb4jBXyIjn0Y6i66K98/uymditFZIirFIQOUMtG8TqeddJDu+/yUrRUN1n1kyMCHWBPaFxaK2kUDTHIGegd4zDPQ8/1Me3deVICFdixILEybsDhlG3o9eO3o5Jex2Jeo0kLZT80lzFrro6D3x5xZuq53zASQ8zYxtlXtmSVOR/dHB6n71Zk/7Gf37pzyDSyeFSttQYUDp08cIe4/0X1lI+CRRgube1NMYrLwqUZ+lT0CUw5oOcfTuIWJPt+HHcaU6hQItnyk6w8OqezBPn38PnluSDYM9nyEHcYnQcMYIBImKRhSIg+OIxO20K6WiTpqk6RNcOzZj/7TaIu/2gF/ECzG/N/WHhb4ZneIavYzFnjNws1tTdrC1SnBd0dJeEHQRUd3OLGQtFuGybOE09jKUt6doiZr95CftWknd1oSwDv0jdQe/mV9/ioemhqNp3W/vVY2nf/UAPTJYlwJvaMkaXTt8TugpEjepR52KmVpSOu6Ia+o0nd63l/PH5vQbIq1NRfj5uCMID3WcJkUEYa9aCkv5SmLaeMCPhN0thw7H0xuLSywS0gnj3ZnZm/9CR8vgwmmUOFLJcjjzHPZVqnNti+tjPbRvtMJX/5hHjRuG/zImeZSgc1WeU/1SA8YVbCSBTeIyseZYIiimqRrqQjt9MDHrHj6lTC5WWeummMzjX8OOOo/71VyEmfrLS8Ai9YFRcGqcHGJSY+DYiwzkGqtTOQ61VVSrh6R8+gW9AK/5Aqd2HCavJu3SDvbmJAlfwn7CxsTV7YDtaxebh7GsbGqMcRvvpLmpPpNHn3gQgaaZ1NP6VIrBpuKyBYbh7jzOBFNuVBXs5oxAs+o6DaLJxNm5akqeIA87bF0e9qyteAvOMi6iPQVluTlR5lmhNOnY1DCrKKRjKLlvbvlUXl+xLQtxVncXZhjUveza0Ze7ATlgOr8WLKL8CeRVxnz9kli0bm2kZq1neLZzmO0HJTQKUUOXC5fFUocVPwYQ7wv8EM2qPzJtgEDGxVIV36J/0ifBOSASnPt9E87odJ3OdfHeLmYiHngqD/IdTBkAqZ3n6j0I0dLov2m0ZOJOoWL0XkmP+ssVgmdg7hi7xO7KzY2dIYwRRjaRLQTPRgeiBr934F00g7X4t0L4zc2EZ2Uih8rus2WBxaP6+1P9W7omD0FQb94w+XskuBDC+bKh5m2ca4z78vtqRzQYkMbPxch9LScZkwkV4WmhM7iDHYzqOn8kd6uYurSiL1q4eVf8iqn9OuP5XV3GWZ06MuWbaH3zMCcGbXTT8nrLL+apdKSBkfeH7TwUXaWdnu0+fTaUz0rXVtgKcHqsCrCxc93laFkoPNnGCFwmfW6YY/ZC+rfVGaxZfXpsWvyxi2TM1obyMr9sTGx3baS+iR9UPxLuutSkL7k50I+7PvPUyw2hMflpebr5Ak0cvsG45iM6TxJDdzfqhysrHGboT4TviZ0wKU74s3SNRo5bJbO593YYxevwjlRFoHG0uHZMRNcnW7HJjSK/Qb0rj0KdPN4b74MOJISjcvnfCVC/Djl7BszCYhlK0/CDa12LLcXIewiopdhmsTvZfl+iwI2o8tTZX0xgoppxPWN1dkFBlUxFERNwk8xOma9Fxon8kYJ6L2+I897Sw38QnQI8lB1eo+FTeY62FdR5HErT4OsWGJgPSw+bdJI5SMfMUntK5k0vWEh2pRB1avJD9aWrM6vmXjoX1EKIEXkoVAU+ZrrHdBrV3ADoc7fmC66CZAfnvqgHFQfXfnZpc9tN+pjg0g4EIONRrbse9xGW3FcDO8ArY5G8S7aIOP1HTu6T2Z+h81jWvelc8mU2wWd0acUtRSbtMf2NEvS0y+sFMB7Fxvn5taYq3H7Z2HqZ7f1sG+5wk1sdlQbNLMNOiCu930vHYrA/Ycyge/gTlbl8QPFlSXWtyCw43K0+OLPFIi3FBfWDRucDMPvOY/5Ms63HjZ4DgV1kY9GfQj3IJG4kyQay32vvg8WOMJs7lk7s727sf5jF4rOIYmJfLLDu7LdxCJfQmTR0/G+XCC1bxSPWcbMsiG/O/+BQ48zSYzX4LRb6B3+tFFuz9QG4BMCFgrW83eU87wG1ivzaCmcgrpwk3Sh+4N2Mp0xqxPOjYEpRFu7cq1YUwplHhLEme5QTuzFDGdp15bONxhwEG3Pjkb6tur7PPSBVfu5BCGiB7SApeqNvMp0oNjM4uUztk1hoR7DVnF1DMMN9MB5LbzH1f8uDSJEQA3EqwHMdQ/LZO8uVJGu6uZFr7eb8mXMeOirMxJ93RnsNhDeT9KdW2I9fpag59hCDFgdXvOdNM8iINOpLCY1y09snvldf0dubwhmzfw/k8lKrb/A14qXP/GHwHc9vfjOnpn2188HrW3knF2s7U4yi4OmioBaUW98m5aBIPl68Tqn5DICmlniT0nAMyEZ6meTurNZ3OVVYeDvqnp52J5UgmjN33++CklfKo0xKXsCf3z7tbuORmkZ/Saw9xfd7JFaN94ICWO4qOEzXeRoZ0GTCCfDf8LLPfJRMpURbP1MrAHPSkLYDdizRYo2x5trlYFdtyTYnPXYyhtaHWDtsUh4YmzMigaY+TcoysWZhn9QDgYCTqCYpPD+yZuueFGIGXlAXWHFySdeW+m2mKcBRdx6BhCLFJy5Za3Gvfnh3nVqRowb2nAz48gIbp0h5BK0RzwDzzJvZ33CiM2wPEWmMvzSAkZ/0kZSDQMIie7Z1dLc5UZ9Smx8h8U+2Y6EodCUfVAGypatB3FGsFdAxp/NxE+4IgmT7a5Cg5j2CJJAmPWJQNqKdxS++6SHQMDFSLT3POPHhJ1jN7JKt6tLDKhFDZrAE3WV+CPJpxS8W1eAXWRTqadFTDOrnbv6rYvNPNTGiy4CQNTOr+CyVs2D8K6/2LpFQ0XiDTwQBxN51cvezEaIiAGWSTtwa4zyDcsYLbjWD05BBjTTyD+FArxLD+mHB3HLySW/qCz9HCj9N+RgYbT9lnc/x6Q8KT4Rsx41DIWWgxP3971A4Zx455h237ZAzdffs3SVO8ZJNrXDGLGtDlbg/hW06GQ/Pf7vVRxLvH0dQYKTnhy8F6QgIwfxW7x+bxxWuo+tigC9xE8QfWfYREqVTT+jBJnERwN8JZ1fP0PS8HBGkO7cl3OiqWPIk7qIML8SbFkiNH+40+VWja9h8CgeDCJMvQni8zn/QsM3Flad3682nM70S9RJQVygXeEOYCk5dz4TiUP1tZ+Y9+TDsh21bnqMVWiRH1wO1FP0ueZM1Osyao8sCExHPox1GSjJdXVi5dHA8QZSEwNSWYxjcfn6hq0zFzKOjHvLkIVnlCwTbgVnvKzS4M3Zj/s3jc3AC7AGb0LKbCWvkiLthOtwH76w65tGuSdPV+hd0PUQCnzwpW9RB68Q7cMKN2SypId8s4RliX36ezjyyd5/rMqN2j4bFUhHMznga5GJ9fwpImIRohvUXUuHUOyBdtnHxXQs8t2bjGHPumdZgItwomnoR12VQvIkm7HI5qQ+L4TWQToxoLt12WVltvEQblFzpkZBzJp7H72XgOvYTdtj95ZBIxmeRzfWREJ7gkxOas5QX/K3oKVNMRnQ7sH7v8Ewk5tSwxJHvBTyM55n9pvtDUkdv7I9t6YWObse+yxwoNBgMovTD5M23T/x3KbshjGD5n4LhheXsLcIexuEbaUSLfNMdNbEYkQCjC/sc/50BscBdwM2cOWnfXHy/yc1nIgfvBD/VukT/Z4RlhdwV9Cv5KttlyvTZLKVOL8d88WSBvmEOCzi5WY82AlWRbddK7gIH8duXZtc7lutbAhHnDZx1ftnrdAcg9QTSK7wGWd8tv0xbgof/IvRvIpuvPuMtNrLkHXXa9GVB2ApPx6izuX0micZjVF9/UUnosHlte8BZvVJvlcXb4+oExhJ7ZHoh4TD7joqqcQNUQjF4t+jzEU5W2SsW4d9CgNuUALDKGqcqdd2oYagR0c1rmrLWsXFMTJhcg9AoxXYzC8/URdGnEbtJSlUaqqaulEikzoDNgSNZk0GMOf1zrgFIvAux4mbBOvMmmIROhXADKYFjdI6xcSPGiM7cBImgZX/n+0EkrDj73/ABtMsqBDizud8B/AUjjTGzDplU0XH0MkbP/Jvp8WhRXNqmKhiGxbtqkCZYDwU4MIePsxd9GAHrlooxYKMOxfcf+OJ/l8Y4QdsITTmMQ/5KRnxCS/QOV0n0pNk20N9sIKpHH2N4KlTiTQMiLjiSk5eJZBuTiriGD6uUUp7vQFEswqpEgNKy3N1G7ysK6/sI1DPFoTxyaL9D9uSU8wyl8JOdr4kkKidzeRyhXjcJ4tCIqzfSrLGfLBuHMWmBWa+j4kmpyFPPOv7mO9XFqgaOkjFHi5106+Wx3CWSSuQpboxF0Jq/zuBZ/bPsEAiUI5UgS3WQ6evAyvg+uBr0sz3czRYQFXZTwgJj/nCOyFO9wxv/bG7LScVCuG7/ZAShJlJZKUOxpC3dzx319tSfkHrTogDOI66JgndVowGftagJcqqOChEhY74SGDgVFbuUEFmRk1QWwlu/V2TRThnGGfOoQh5WZdbeyvP6rlHuHzzf1fVPA3EN8vB2J6rBcrgM5eZD8uYLF9R+McdqVXBF+pmROshm4zdNlJbk8eEygeIHP7pBElUv9TkVy3it+rTxOD9r9wJxnqwy2Lm4IwZzyvZFXgtovhRdJv2jnxlTvYVdQ1dMwZE5zsnzhhluIRB1sDJgEJtbdSZEhjCu+WotyX3A7/dFg7iolKgdvikI8yvXdASiPjOa90eUpek5qmFn/9Vkwhs/flQsGdbJoQAFZy2rC4Vf3FmFYb1nassZ5BLlNTKg4r1JDREDAtqfL9VSppczMSozflCz9mgRLl0TdnLi9FtG2W+TzYAN4u/H0MSS7mHuYtK1x3lW2BqTddH26AkiJ7Q6Lp6BBxfMjqUTV/dWGZyxc4Cfs+DcK3hkFUUONtIncZqsCRrCyizCQn/JJbdbwliEQmrokdHBO0Y4H8fDt2vHpnZjoiculQqW2xxyFHqS6VblLzt/JIOf9Jaeh91VbO0JrFc+0rpwPwzbOqq+1YZIrusFxHuqkneKuG4+/LTY81GCjpcFcNUYh+vl0zyMgr1URycU6zKBFd2NwfTxAL/7YP02S2G7wNribvysmZEHjRS1RYlyFBNFjkVpZ3bMVlY7EoH2CZJykfUwexhGw5KjwZD77FmS5d2J4CRqtgSJiBZSmJFhEHFUfsMpQN/lFiCwGZlxyGdufuZZJrhGMqgb382PBjpbyyMfhjPPfvkhfWGnBCGkxSyxB0hepYB4mDQwUfqZm35jym5IxDxOwndcyro+GsxDJ+sXfY9s7JDCPtd29bPVOZR0/i0cmsqi21xCnuqtfCzvdg9yhif3ygwFo8O50rxaPSVxO2CcazZbKUSf0K0MxfwWfb2deHkFkCXaCVdEVjiYTkvA6J5om0EOllD7Ed4em7TBeEo/Wa7KAYuU2T5sitrI2UhS4ers2D9XbZJN9P5YccHBEAPY5dsUmRguaVf1QS11GtvVv15Oer5EikJhvzKGhichNpWDWia7/fq+Ae4jT0xoxso7s9vFM+D2DlWpFLMcKDqJ1YXe9Jt0Il7zfEkZkK9pvmnhgCXV3Z6J78veyUDiaHT5zo34WTNTPUcns6ozbnUSkLB3Csg8hUJ5hUwnMp9fHpOmWqCopLanV2XO51+ZQzds53RKcaD4JIsetgvsvPTvmje7/bPB3fJTrNU6xjGW+M4aUZbwJ4ywJHkXhevGAE4xF6v5MJkh/2LiYTn05PM/rjQW6dFxyzePHdoV2YjUt5DGzv/dg97MCfZUQIKL9aiOxz3veERbkcQ1oTJD5xD3z3rxIKg5oVDS2EYFBIlWO+yz3Z84FCxqRP7f5g/oHE1LTOHBC4Jg8K+YCnY/lvNmV0wXs5eBWSfxQietgYa26dVn78wduvX64XeXhlGX3e4co63Pmo7Ls3PRozeJKusCOWd9cyT5sFFTT235geUjCewy6DYdwHyxwNnodSPl8LFrV/Meo+Oa/Xe87ia0qcJQ4Z5kdRK109Fjbjqpm5BEKXGzEEC184egysCQ6Ut58JOuS4aiSTDZpL2WG5+kHd8j8q9XqWq4RfEyyBV9sN67hvWJHSnbs+Nxnjw/kglxf5Lv00f0xkMEo8bR7OnJQ3dlyTpgoWMUxi3T0fbH7GgBpdEqLWi/L/o207be/z7g2qgkVEYLOyUaKmE0cow+7WSutXQKsMjkivNlc7qq528ht5JSHN8sP87EhSguemMd2kptJzOGGNF8/yLP1x16L6Y0T5Pahr2uKeVlz5uL8E7Jh9muAVq7rRLDcSbQw2a8HBVCKJGy+U94SJqRvyQhn5PxWY3nXrthl0UF0q5LdaQoklEr8uZK4ercOdNFZMxON8RRjeKiPDZTXaeOw1K2ufuHOO46agmQs/h3t8e4Wge5qSqEMW+EwoUjH43Payq+DheNR5uUu8Ju3waeRF/aEA+lPN6kXr4eyqIEgejklLtb0MIBm5SKsg7pZBuoW7t+py+GKF0E3DYKJwCTRsTcZAVkeDoSGmLLU8gZXWeD9D3ielDE/HRg3gQ7z8epeJVvjDfEbURPxCdp48/SXXf1X+WkyYgI1VEpr/bOZ2BRxmB66CrGwU8y2UHyvbO53BJkjvlVaHfPLACI6ykHCacKTQ27xIR47lNIPPSHVk7ZbRu9kgt8nf4CXztVmAPrITzJbpbR+dKT4KG58Nk98xcFkjcuBxSdWqvISUYJpDG/iVuZNlXCTQUdOTp+sKyQpNaQIe/vCkWnYDmb57UTF7sMJ4p1914d4ZDv2YoQMhORaTOEavwiWoO3dR6KKjwgL2jmU125wGLbQveLo8p91HDjbURjfRCTzs7v/eVeeCMhTNQoamAjDDlp+JA/1Pj5ztEbxVqLRj6jK532qiYEx0+FnnFXujLFoUl8r4tL6YVwp0hXjqUlydWvH+V64XPHRYS/ziaZXpS0xR0A+Y1Ht9Rsu8aTeRtEOe61CMNfhTUmno1aQ9wPOqbjz0gtvHOtx5j2+Z1J9E/x+AB0N2ToATEEo2XtBX++u3FEwXJxWLOGQoIFGVSyXLJjZh8gxLXAyo0rOt+WUzHZ7y+mkw+l+NSK1cW/StaVaSByNmu3oNYvTA9POe3mTnpJO6ofQqeu/JSws6lLWLYqUmwtd10WkncjbfQSZWYPEbc0Qzuz891Coinc64e8izxE+W9idqUYlCF/xfKznhYZkAqqZQ6SbDyYOc3RLD4Zpoae55qP8fsk41ypDkisNC/avIfNYrKMHM67KmIJEe4CC41gjd0AqUg6ah0V07s6UNwi0p5I38beWnNkORYEkC+2ShXIfQrwlNk9Ss5MDLIjdh1JDb/9PaWOWecMjp67rDaaqEB3x6JqD0FrKUjYA+CPQ3sEXqpL2uYga8kbkS809I7uFvG8Ul0I7yVh7UthJsqfSCf60jTIYiJ0mEdhfPu8FCqQEjF8Q3LQfUAwtq4lbDd+UMJsFYSAaV4pwx3U/AfiEydhHV3FiwWgIdydV1mSgSt7yl9lJOIifQCUK7vF7cM9Gq30vNwucvHkdwnywOmxTvigjT0bDvZoBLNA89/4CaVdLEb97CRPkfKzAHgpOX3VRL2OftEQYxXGUrjO6mquio7CPkm7qOVCakmUCr0ZreDb1xusKdXL+gvCi+UOvf5ptIPG6jkhoqQY5sRg9J9FyGKw/+ldG4nYFPNRvOfXmdqscoXsAKhyQx7kGiLXkopz2tjCH7qRO9T5BqRlzytLwaYNWD09C5YeNJVZu7zASNiv9l8Y3q02WYAGrVpGVnMCbHaWYxxvXnh/fbMX98t/Kyn8Yc2zh91Lbunf1XAiwvs+GZTasU3jh7SyXdp3rvOTLdWSYzrEaV2rYjwke0jiGuFHLpMQ9+AA2sF4ahGiofhL9svUBWCw2M4pqMzxkvUK+vOhG7itc9OD6dz2yQHM/9Dc/GKYAEhKwE9QE6Q5e/f6NGJwvzcUUaKmVkoc4QUeggdtavtjWZniPNclHK8HIUzoeRJiobCyIMibzIZsOb6LmRVf6N/zVVI9m7+mBhhHq8c8UXhSNG3PhdwZHCcCnYjwjZ7XBmV3EINBd0opz4YGlbFlyyrx6xMzxzwXlPArqcyfeCkBMAB2BDsckKTSDrlVLY27h/zhGAyTT0fogo1zr2PPht2dL6Jsv9nRD5h8XoY3SqmOwz6xfI1Ms5u146FaMTfdtCQBAqwJs5v8ClSwXfS0uiN58L8OxhETpGvpqLMBLqE4Im1P4uWW8tpAoRyepYt1WJ/BJzxHLnHDPZJXGp6hh6xkGCoyGcxqErsSkpFBLDXSxicoA/S+7jj89D+wfisD/sIilIM+rZk+Or9J8gu5o000JWD7C20AviH6aCOq0M5h9wgjdDXaIgkeuiI3u0OU7ILdIgMLny4c98+e/fKs8H+MBBiKsYjtstRkGwMfjU3VugXLMRfmydw/TORPHmYUgr9Y0pON1R9neKUuT0RHsFTK60ni/gXuuwlBsvsER0P/XPXwOdCJgG6R8kL9qWbC8j+2TIgOeSdhNrD2iceJEcp98ca1UbepSipJ2+1PtOt7n646TCmU04kfJ9ITU2c96s6pE9IwHi+5P5axKLuslFWFnWZHZzU/QutvCIG9TVXOZESEG4BGOXYl4utuao0ITONh3N4UI2X8TuV24ELU+dBJOYalUYOM6PUy/wtgXEyZEe1dhg85mLbm08lWp80yxLenBU2exnl1Jcd2BtH+rcoxqHo487pCU+9H70SvshGeevVLOR6giQH4jfbGPQZ2gQ/cvWaB/Ql9rMksdcYUVOd98gkRxeY1qdjcXytr0G4T7QrzBP4cXOziewCwzwDIRnz8g3pMFciXF1bcoLIsUPSbZPqnyt+C62tVFhXumEUcuveY3na/TTm2T4gwhFNvFw9l+txPt9U+rwtnDDHt0C9itzueWuyn0l5g2PM8+7CJffkGBqM2jvZflEHL/Lk4BAPMzaL/alARkHmzDYd0ufOgBkjY+Rh7v/c4pFzV+lR9jce+67rF3eiiRObZo/Ggc9wF90iUxr+Q8om1gEXPOFcUNPKIyvr5vD4tAtyWpnCTj3WO8AOj/b22soY0lt7KejZG0sGlzm0WfOKqLwp+W6ci6HUATCsKRBaH3S4hNgetSTh3cE1ObXfei/wz+HUZr3Gkb14kioZQTY6gEaB657BdT5NJmMolcJpfXL/e5X2ZTPjPYpoatar5oA3SjcTQzbExj+5M923wn+XpK1hHhSSDFKSxC7HAS0fsVNizIfkXqc7DorXpeSTxlKtPHTeSnBzLUUExay1EDERcu5Ipo7SSG6/7ONXtcn4TyEZpZQdxGrmmbAfNdSH/2t0JGIA/jKpdssjbGyIjbx3S+JnUdinbChUEwqgHseXjrtM4hHxBYkedEeEeIAfhppowv/QIkA5kk4mtrhavsBC13SCFglXJDz+azgrfzK6GbpxfhPKJfdtU1xcFhOtEt58E12NNcctw7+8KBBO5e0gO0EYpdPZpSKMl5EmzDQMTo/MLoT/0RKgzrlocs773kPsO0YexV01notU18j3J7RjGtwZUHgN6xN3WIrwePcF0O4vl98TCk1t/0ZrHIy/3C6WsmucVSb1gX1Rc8148/Kvh09DdwPo0VZZZyrCvD44sEjVPwC73gAJuGNvGOudWhp31XDe2xTm8zfUWgP/4gqaomBqfWC/3e5pwybhnOJwP3sQPGRAWoYrHSfl62rRGHMm39GSH0XkCRzUgune1GThEo6EtG+N4n8QSzE2bvbx17EYeSxlRzWmSMuwaEIbNDW3m0ZKLL7GXTKJb4Dv4POQ2XlfySGKVlS5M1hOYdTXIeaQSh0uDODJUcCrWOak1WEFtkvtye5EeY7EpUkE540ocAq15YEjfz8LboSO835NY3wPCgEtoq8j+tQ0/hVTC9kTOjF1wQOb/yKy6GHpvKmo/AbFMP9e7u7g12zx21XArlTQjO75AnaAXNZypWBWC2ToTwmEUw/bxLNax6DlUeOGHx2owmNPEzEVkLx5uhQVDDFX88Yzsz9Q80IZUfeYN7F2KrIpP1Uuvn0cR19FjBvKSFxt1jQN9742NRilq7ncC2TBr6GeMup8QMxYdgxJvEbKFMb3nfQLwECSN12Y4qNz0XXWBdO9Zdp28yRNToxiBF5/4jqRjogqha7qF+gZbdUX3E7EPl0ugnNDKEOGSe8IdgWumcuCq8Ea0KQYY897Z3Q/YNZuHfvvRV66AO0Kjx7qDwR7Cs+47LltAnpBStirc7+2t10YGmo1MfVdcAKDC6uC+zvOUACzy754fgPCt6rBm72OqozTLbH/pOx6ij9pQsqtlHAVwGDp8HBl0FjSwtX1uTPd1mBeFGJFfTmfprdUG4/d25fx9yuzpgeMTnX/gTNla+Q6bSZvma6ZKDcu42SBrNN8JAlxEu0x5QR78fpkKf0qvhXrdnBUMh/PCZIefBwSb1hzT9XGQ51/qc4MwHP1nBBwPuMlZy+sIBLkTRBC5/OPQLbog1F8NoNpLvesMGfMAc5Bo5KcAMOWlXN2ihA51BH5ZM+4Zsjd4jucpMJm8ikH4I+Rk9RqSxrIO1vsakMdDE8ZKmSp99xpQ8WX8K9FujkXz/cl6CQIAcrATPcxcAPerU7xjqKb786UwR0lqZTxTQAnUUwjxgjQoWMbaRzsVf8WgZwsrkrVm5P8zJaToegMc4MXt0kRaLx7dW6PJBcW245JBQR1VWJ8CS1cvAFfkB+bmE262and2pRDWvSOCbxv8Hrb6nsvFSdGbTez7eX1HYPHwEKwQFvuLZ6CnMPUeA38GS8IHKTw15pkH7ttLT2pKGZ3YCNZWgveGbo0eQzqUkSn99j5rGGpjhqgRgaz7w4Vwmx1Jdxbn+c+RFsidsk7lQ0zW2LtWIBIyl6uas68tm+3VsvAyjSiT67vuic1CegIb0s8DOv8bGHgjs4Ny8JE2UNdmY8XBJ54bf4DFzRBfj+Mw/lVE8NQD16VoghsxGodL40UVlGKzSEPgFtTA3Iq8SSyljiLEm3dtiMtajOgFGq/WHH6GZfM04RpdjxxPZCu0wlpvuGd2fibh3CttMAWIIz8fJFFWAFhsglarYscXmTN1a+ghHjzdd7Ha/o61DuO3r2BgU7+UxVSbMSXXJhVVrV8sC5ZJi1vcXktVCeeOBzfFmwx0TtowPMJ28vtCtuo5vd0hVqnc7sANujOaX7lT7Uo26vSxCTJmSJpPdRZgwmBVjyk8SGnVS7IeHt/2PjBKv5YrdTvCkOAxLUbJaB5n8QCA9tOKIRLjs/txLoiqYXxugAdWiE0msYqHCW0O3vVOzmn0ehwAjKsig/ApBc8eEt8MTJaidwjtVGFw/fJmd0c8bUsL930UvaWH3gHjuiF5xeX7NXuyGwBkxqofPFBXkWUvcAnCMHbxyLISTw8L7cVaShtvfjOmOzlg2tSgx6gQRXXBmiAysJno63h+2RXkyndGCg+MfvBEJb51oH7WviNwF2WwNrvGLloKkcYY8zJuYbJrvVRzAFSFKISsDuxf1iDBtXc6R2A48/uHWLMylVMnujGzmM6e0AmqgDXF0gej7xKGGD2KhGTiw6XoiC1XrSqb55dJWbH2flyauHsd6K5zuzbVmS+UUSVgjikZHgvPkFknHiKn0O88Mlv0mTsww5RDYmCXOWzHddlo7ROysG9WDg81OUIZn7KPkRkkyHrPPUY7yIJYSiIiElrO7tvf5jIn7nglduBJ0keJqkSaIbnpOOcDm+oOcpebM+fCyxQobsBs/MF+9g8f548OvHjksw5LhL88YhmbAywIe7GgwiI95QAgySmjZJD8RXsahUTt5ov/yF8aYRifJbuo7OUdGRWUeQpICdEQiL2g2/bv9JAz92D6ZJhIgsHgAWblAL9CwUM1gHvfRtHFRfYoEheaemxt5ylPBLXcvRAg3LVS3nfED31+gQqkTH8PwnnC8Gn1BHMLU0/PeyD/wcJBBUThtyvnPdsf2eTLdIpTKaRJVHGW7efGghOK42Ebji6Hooyi7uQXx4T4y6r7089RsNrCeU7RV3OkRSk86qPyEwIIIP/mArimafBTahL3ShgINirALgTES9/4fq0zmlZcASPmumXrwl7at/VDOGRv3XrDF4hLbfU4LGUuHbAN8uo1YgyHWdwY7VmvmtZ9B9yna16YTwKzYuODmwRjjggGo8uubavur2svXhwFpzJ0N0Tz7NQIdAN9JxwT/CCHHXEJBfb9W8CwjIlecdRDzIRXYL+IjL4LC4X3SuT7JVPuiQwizjt/2W4OdCWJj5YiDStFM6vaXeichRdFbxwemdyHsmDSx4p2JwVQwauOrO95KE+DbWb//1pXOFge+6sdTO8sdE1stgK+P8pH4iGV9UMv3qSL6eNX4jDx2wtYt0AKiwbIMMB5WroEAgv6cdz2XPauWCBz1pWouRK3XJjSPqd809JN+o2P5fKl3ZUzhV557SsZU1X+kqIi8SmMpPh4qe2WCsWMsFjTHBQXFOkv9U3hO5DupPw/vUhGeb7rRjahV9WZm1Xul/QNeve2diFb1HX19E59TQ2H7MDLB3o/H6Z+q2rwy78Jpx5dRZ2C1+l+kzoZDsKXhLr08m/Xac+kC5MhiJ4VNg5cHJwD4dxP20TCt0WVjgdynbDzQ5507PM4O946P6ur7b76eOtmEu6fQ9bq51MFl461lV0gMuzLntJfUuTwXQzlFdOvl/8TtaABZpd6hqW2cPf97uWrWnduACM2uGvrxmiiSQAMZs8TDO8ETVwHZ4F7FfAyQlMJ4FjcK+onj8a26F0zivO4/Rtw2ZCMWhL8Annf/a+NKPiupDL7Ljf99Y//cAIWXCU8ypOgyg36yThUaH7/mEpPapNdQ7oTBMzGPIo3Rk0GQkf/vrzLYgQL2q8jx9b1AcTAbsLLkjvqJM5xVDMcLY5JAol2iC8jWv6+Vd1Ja/kHo7kioiL46cxoOBpisnDTp7kZ+8mbit3IjLo7x/t1LMD3TV5zY/eAbO7D3ikRNfQJ+ZkLm+EuC2JcHQsinY+HaVNP3D2sE5gnu2oAKMom7tWU3qACFoLU2DZqUyOhTMv+CcI3O92ptZq2iVbeelt/04TMP9GB2axZ0P8fj7gtQ1NVBozR0NNg5yO/xB/THeyUL4CxCUz/418UFDQT8sVASA7n0Kjp7xEqJDlH8/2tud3aseF0Y8fKzTlHrycon7XX3CHdMCqXrrpxqfRJlNOrQOfJMjlN6QhlfOc3KzG0rs1t95Oanv+El/059npBJEjMeTi6TsC5VCs4OyP/TbjdOqR/5ejwmq1f4sTlI8SwDtmYFIJGo7BeoFkyGfMJeTII4Mh0IUN4qCkkujI+HnPVEZIrUjuRRdOB2A6JvjJE2rHGRY07rl2+imqoTh6pzXhJxMQEXYS0E1gsTYXbgPfLP08f0079UeemMM72Xzkg7GaCf3h+J/EP7MSolcKuxoFQqqWvVMHoWZPidjyXuC0fMeN0C3k+iTnN/IHJrTXrHc3Jkjykj6s390vXnY4b/1QyGESKXfGMfENQnI1mu8E1uWChx7IsOE98Lw4oP80lon5ytIsBLjUnRbaCfMPA6V3GsppUnAzmNuDkZJW91Q4qZEC05mbab3CsEIUXcLk/332TsHj2Viowqb0aeHqvsGmHdKNH8QA5UtbX4k8QLH7HQoLnoivUwG9+ackSmMhPMGl1lZFTAx8Bnpsu7YAoooIK+PaecX1W0Q6CjzVVp5XqkA6hPRIKeIRVT6AXHenyanYQrb6J23UJOvIeJbxmXp0P8/NmXQ+BbhFDjinrm5PcSQK4H279kjqcg44UNYrCD91sjQ3rPvwOHR7oHvIbGlwyFLjP+xZGooSbmQJhd8Xhmz0s3fPoJhzKjsXTqTpuhOWVk4XfDpDo+xfc3X54MOndjQEI30mNgUZTnwPpLcHdTLvDG48E7MNyQJoPFnDuUc/AgyEG90OWkYTsihrjocGCypgPcXyqn3fZv+w3LdIFxpvKdzAIduGnIMOdoFR0hlTXzxVc39PoIEwuJjnle1G71iMMEazMCnBL6zgS586pdBSTdISbclTAo7G9uM1EmFR+2AJaU1KOUP1VsvJpUakLU6clyEVHt3lrneTf9qvRzIa5ubnlw7txuI6Qwr2AJ5uHkv+L/E3OEv1p7RM3cxVJ0ZEGuPnPuYs982C9ONJzmRvOcreed7G93NBJ//vffMdiTOafqKQMB8RK8GZa5UuQkRCLE8MwCuRbvWni6ztkFQjCKxGMWs4LH0uHAckqyAw7pVknn0SfpyPPx79hcnLXmPKOMmPuDyCrf7ndF3mm1ApfHqVAyqXOflwY8vVa88i5JRz06uKS4FVF9CTAESMT6vETQQGEtkb+2Sj5OrNm3z6m7vU6+4851AqCTPZZr+SOZZ2fidIxWpeCyqx1RPVSXAJca1k8hQzXAYReXhfWZ0SF2QbWcTzmhfqh6ehJkGQvhR/Oo1g4JJF3T8pUFixSsaPh0qrWWzwLlcTN9OKEuvtyaHO7DiFshmNRPUisogHvPmHl0yQzR+mm9oswYTGvvULscCZzvqwLCkVgkMeCikeXxJU8qvu8xpV5F1uAhsQh4J2ZFA3MLH5jSxFWhk6D/HDHwYUDNMW30nt8a+vHum1Z0kgTA6eQLOBYiHfq0RUWPEPBlfIQGxLQHuVAd636A1mB0tVw2Maw55ZG6m4w4JD1LB5SVgOEt1zv+/ZNKzJyjBFRKa1IDmRdUjJyFBQGDit5svizof+T+YgYz3+8f7E2ysDlpwMcffQ60T7WZ8JXOmeTGLUs2F6JYj86X9CeXE56xLMOnWPVlirMtiOzIeTg/az0SF/j41HED6MiBudm2U6iH53Y1QkgraCVmPejp1kkjb7Q1pl3sJvj3DCFJJFkhVt61LmEcKVnu+QiRxGyylubIVIBGMCrW15gasBYKSttw4uSATeD7o+i36P9GCDbJxv4AGPY/T5kZyzoCDWYNCqMAtYaubhTHkl7OY0Te+RN3t6X3GS0Fzm9t80SUT6ZkBHMaizpNFh6wHf25b1h7vb5qQDo/S88pFkT7wXWHBfkO1H8y/l7HhliZmP3XV2Naeh4YMPhTHjrQZSWB4UrbAR1GLuogC8E8B95dGevN6nQiWS0HN8mukfg/DL3wNlThZFI1Nuy5USk/mI4QfOMmIWVEkO8EhE50p7a3uQXnPd+tkl+fJRhYkCXKdZsiErpTH6rmzqf495UEUPJ70RV7+HsMyT+ZQ6aSJoShaw0bLsufJideo878JrzGc4B75bGclAUlNkBz5zx9SbWnYWLLKo4j3El9WZClIE/P318Mhgku5VW6dXJHKsc7b8Idh5kFLjmoxGyl3/PUe8goqF6pPs6WFAOrY7Aw3VztopRiSvmGDLd626Acvl0CoddX6Alr9TKMlHGhxUIwVX2ijEjizYZXDSzICeUi33lQ6K0vr+kjauzJAkego/G5ytfKHdg3W3rzdqQEGjVgyw7yNGy/GSleVTCJzbtQ24XhY/PLH3/rVBzos0Viow46F/jk1Px3sur3+j6+THeLmQX1NmZWT+JHtRqgRGRl5zbOgqPBS3Iyls+RsZB3X7Z86ORKdkDCAGzBc+07qpCLvg2Gqfym4hIcb40bnBh/syC+sN1QUGPTLi/2EjSqrytD8o8TvXtTbrbfyCyzhZLx8SV6WOzmsNthHdwlzMUO0BgTiMFJrJ/R5OlGBbPUU4wcsXto67YvTx3gOfYmeoh3Cp4eI68NC6OczMr4ejLhN+ZQqbN3UVMsmy+xMZ0lGFH1ZbHXhbhDm6GqSmUIHAkAFoRz/ufxAH83R/Geyn0k6QwVntQuhGbyQp1XcqBWvrP/H4Ym0IaZBvQLq+ptVhLd1MiPMSmID1+6byUMGxdGfnZdkj7TO78vGokAXWDcc9aNVz8pR6b7StOZjmR1JrMY78ISQYPCLOHA5C8hxAHQ2+Zjt5qgKJgNM9eDM/4vx557UVTY0HHi+PwqPUoFyT+aIcVuK+8TnOcEnRSDTiyrpJ9HN2MRbwHOcfZNnBX5ZanR+ZB+mL5ks0R58doljBx4mBB8VkjXmIjMoat2+NM3NstccNpkG6QWAASdznnBpr9UjnDV0QgM7Xqw7h4s+S74qfTRBhBYLFeaBMmASLXPHOceoRcRw8jVDr2+oxtvzUMTQZ4Km2njHmRljdJoyiYmtA7epnE+FzCM+XeC41ItA75T9qdrXN3wMpT51mX2Xef6Q8PyLA977TJFo7h2YhQPVujJOaMzvukJ3hCCPU8MuhDOIKt7kM7M2DXmAPuElHg9SeFG1grFjVTHw+6Y5yTdDb3vxVsFAnUWXHdDqgwL0y8X3u6822qhfXZ/xhvnYBXKqRQ9LtlCocBGf1gX8Gb2VUCYlfn/aXIhaYbiLp8Kca6Z4YqolCRHtEdEuPcmNnfKW5dCaKiKd4/ySuDh1q7leBc7rEAWIpV/aEnfqpZbop7c8JLHKETXkt7i0tL/cqKnItaR9NGuA5wbnr8rI7j05o74nFOim/Ej197ZTRXruqdrtI9m3zAE72QCv26U9MN7m/VNaPBAsquMOQgv6nPfObFOJgFxX6uq/GXkrpdKHBOyeTWqpZKRV4YQn8p+LHopEOfeoFfxFuOPlyohBbarReriJRslA8ewD/zYn436JjPEtHelE2dEt3mrbcEYkL1BmUPlNRMoDgXlNMiLhnJehETn9blfg8g4wg6nsrLJG3ZByWfSmHrQLX6A34BRLSjFHQGKP5WG2XIM6HnLvoRnRWNdvFt86uC+ol7bKMxFTaeSsg5xRK5PthBiiT0p7bSVlBqK5uBLaXRWojU0TgtnZfjIc71Gvaujkj8sp/4h7mdJPaVrpvc6uYQMBQ0e541TlPqOWuS9yciTSTIXUi5vyTrw7fhn9o5adCCOt7mywQvpY6Hcp8H8EZfAMeTpmqAxVGvXKmbpFRFE1PiUoTnMT5srO8ZL76g720h4ymy4QF9lQTXhl0ySksBs5tkypHa/mUcJmWb22r8zb4LNr1k7iNNmSd8MG9O+RYytfnIz9jwYiKhsvR8uDeyNRRt76uRBfJo+lzN6AUCgPZjUwPjgv+i0k/RaGuwfEEOKTSKtVETVfW+21AqE58/nqNHfGXCre1tlH6oGgawH3nRZQn6If3tmM7vcwM8c3iiupXJUmc4OLCJIB8RCH5d2H2aXLmMGooOWMRt6Py2l2f1bBw9fJz9Ex7nU18qt6Bg+CBWqbQ+Gduq/kQaagQHhg7Ld2Jg7XxWbLdsyY78X4dRlBf8C+DO2LZtGZRyh8EC0pq5700pIf4GtYmwvX1vjc2RSnZ0L73iXZqWV2nhVSJ47ED0PbMQKBnQEFLpwFw9i8oy/JItf7EHnYyWjqgwfsJvH8DgSBxZlzeszgyX9AQyS5TYOaex+Gyr6tYdDhL+y93ylsUCZMmcjynm7XrsNaSYlDrlMDO6hOJRcSFbC+fgZFmFDsnivLvNJqiUqOMxDm90WQ0HOhWLH+caNJ7hUOMAJIE/6l/JzT3ivfGKhWEv9kLNDYvWD4NeN4nruELg94zRT8RbcDV3LbCiV1funHFbF3Kb9RDq7pl87OpiR55iZkCdkKOGUcIzTpmStZE3azPWfN75jtrhGPkinTu4vlv9Ls/2L1kB6u6cU2U/RptQo12XW0NkQCdG6DCVtSP5XmBZe0WF6vrIa3Vff0tTh1XmhV7xFy8C68SkjnHqnj4U5ypqKNHA4ssUJ1H3r5zjwyo0PtxINc9pUp0xcnO0ktQWD8tV3rXZJx/uyM7J4fQpxn873ASIo20fyVHgjp6HSXieDgx+oFuSeOmIGNM24Dnxz5TeRYmv0/hpeG5t6ukW5M6tsxkOxHOdA7yCX0UAJ/S7Mn5NmNOc/LnZvNhBNCZrTkeB6l2wuAfaY0J+uuZ0kBD2QJY2QeZDiXvpcr8Wnt8hkBpauWqlASltLE3pb8zqaFywll7grJGx8GgdgcgQrU8td7ALmivXKuSzzvx1TKHrCNvGidAuXtRkVufg6MMbmdXmCFKL85DI4N1AZvguHzI2ERG9FDle+gmRyTuJv0E0PaMB/MpO4t36nsBN3suxbjVzIAW0Vm47k1O2MikeN8u8oJ4xpJhKEPWwlHvuWDhEpnMqsjWAgSWpnGUJAtg5FD1ULxT0cfEdtheXygqo6zsIL8pdPZ4rkWg0WjRlXCB2L9E51FLVVvayXk6snoBQ+qAry+btSdeGD1kyvBHoxo2/oNJZH6KzdnEPrNqiRESCklpDkxs/B45NOIN/3RVVFpOPII6opVDgLnx7i9m5ncoUs8vlbuvUBqCyfATz0PnoNMAe4reUUqwsbpGxN+0+8L6h4m46pBT6JLkL+2M62ZSmW66n9zetKUqJL+yZSSJLnkxEurQGXCkTIfCC0aYRIsanrrzYvW7s1dRU8JFzLY55ZpHuDxyhDkKNT7pv6O/vdZ6NwtvJa65z+kMaW75I+bqQxlB+bsbEj9b+UPwe12oTrVO1JRbRF4eP+Mibx2yWYGv7q5hCQ0L+P3jPe4HtyH7SHYLPiaf59oNxSUamjXAex4JiOvMOvlUs2TtruRrNjqsGgo3dMl3Mpy6U88QzjdyZB9JFpWjILt4nUelIwbQGgDpU/7YWrx3+b3LLw73NkhGNi0TxcpLSue/I5Ms0XLFS1Krsfg3HdO9VYEhzzpUPu6qKJJB2q1Ju76LXIY7OvG+CcDEHXxPJKECk674JfevxsXAHl706msH5hwQAE3t5FIMZz9KaDIQ/XbEYmg9PBIY23OrcMTKL8tw6fnYavAVvlEh50FvSEGIMP1UASgV9TIJrVOPA6eq1DvARK2O0jvLBvLGGCyM9IfrIu99iriMr9tJ/HUr3soZ89RVPgMiLQ1XbLNhDlAY0wmtVNVfS9mDN5t8K4pZKHwEGV8SlDpALD1h2Lod6IjuOV5PzcLE6sgxObCBvkxu0JzQa3iIyB0f9lTMXpzw0MX5SZ2X3V51XFzg2vWX04gHohYopcVI0T6zMfuAhYqCzN7bLg3EdvOXqX4AquLnwZvreTKhmGTPyDmSTV6eMVxned+PFVkRmfvbBGajr9ZwcpQx/Nv7WEgwmqMsgczNBfzAD6AcXcTugoVbYKGzMypq+YMMdsIlB+UNxS3L+YXeg8JQ/ITnZBJBpV79h8uEJ8oXn44BL9g3Zxnmq5kTDRfSIafNdBqUf61SHnLg+Kd8buQz+GVSLjC6lZW2NxI/SPnui4L3TpeKrWmZmGrqn9Blj4hrC0S0yyjIcdR2F7vzRVdPBeqrLdrjVCXNTp9+5a7jg8n6E27YpvMBoHvf2DeGKuIGguvNsTqeWQnC7SUmCa86m+eD2jSjKwIFwHTHlMe9kAVfyguatdnnQk3LiR8e2XcWLoLQN+/Wy3Ozgp7rHNYtCeKRI86tKtJexYJf0quuRfbspLYqhznA4HIfsYRdfEI2gAbNKEyst5xk5pdjUwFlGNfnISgfYYYZ2Ne05PPyuqVRyHlLr1VL8hEk2bFKnFqoyD18EORkx3fuGOfK3gQT6qqD+Wc5gUyXPcwGqh5IidVrs5HeLpFtY2mo/TXOhK9QiBB1kHyChCbTI9I8waQu8SOcUTP0KQT+gA2Om+hMW8m7PltLRU5qqV8XUV1LjzDOfaAmGAuLttMnSwB5FYPqcwzLrllJmrDCFzE0Ko3ZA5xm1jmI3EqfJsOHknYEfN29T/4GHH5SHLDu4y9/QIpXuyAw/5MqNxx9SwTWiExa3tc8thFfnX0Z+ze/5Dyh2R1C04XBXNxMKiypXhAvpc6OxIiIS7UnC/Xf9m0PTaK9whQamJobqmS3abRcIjDfcvLPcw2cRf1pRpCVJIPeLK2SUnFZXOclRgw9hKuXvKr08vkKXlo3MCRV2hrG9nyVNtOFtbIz6Jgxzckroc7fnYRGwaao9nyvG1KIslL995+phRcPtOfbiIZ2HwSGA50TbnA+4D0Csy2Ks+XwSbx/9GKW73fL53M/ldv5uZs3WskV22D+xrxJ2wLCCQ9rqzJg0vt11mpM6o8MGBcH7L8V7yJRgozuiMl9GpW//QunfmrwyYBarqVLgzMR9Vyop+HH9PcFPXgk2/5uHGVch53WfMtoUZzFFzgk2A41o1wksJ6yNMqs154EAtl3YTh/fbvuEb6drgHkoTER3lgkr+prwMdPlag89wW1IidUjLirwnGbAmNx/xk4fauUrzf0UNHWInIwXddrlOpHCkBYuzLSWo3eeZnhzaz9HzTFruDHKl8g0mM/77sel2WIAPisLDZRdeVIEmn6qyp0sPtMYeqZ6ImYic8Lc1wP9I+XynsKYm7oG8/xYQs3gmex2Sr17WLNcCTKKlpRseaGZHtDoFYXijhmCF8e9KXmPUdrHpAQWX+HBZaKuXkdebVGcMVHUY7mMN8JU/s78DPfnoa6It6X4Aoau3/yYkTJO5Fw6kvfcyy1N2qpJMq1PuW43lwobg+VIedzJvPsPDNm9Ff8GAIivkCTA/YJo/Fbn0etB1Vr7h12OqfgdCxZi+h8TDvWrktjE3/mfTefA/aF14vdK6erWn8qYe09WTCf+i29kqvKHGJVMykfbI/0pkNEetn9zKBD+zDN4rUTDujX50CRdZ9d/KRNZQVb+ie4KBHwmpe7i52uPuTexYjX9Kp4ZaHeZKg6V08+mfJiw7HvhJFx3XLiP+ZXaZ+BU4ZViXe0QD0Vd8cweYumVS8sNHfPkOEf4ApJ+DHGzFMyjCT8B+LfLPoJ8flkNzwbMyxmWEz4rEGVjoyjHGEGraKMjo6TX8c5kPS31i8lJ8h8MY7JbWhmNt8cRP1kbst+qDahQlwmYiTEz28QxJWuZYnZlQD4XyQGkZXGgBGrcA0NxIh0irQX0M7dPTIrQqpVvZCbxkxjdea5b/QMcnHKaGXgYvIB52mvpHu2VGcdqKAYPl9LvIhMo1PH+vW/7XhdVptFxx50lcCTKxgRTwjRdkr3pL0jYqe6iG496f1IhgesKktuZzJjB3al83r9b64rsNigHipBO2BrfJFKlRrSDv6JtmJFbMI9jRlUQyPFO7W2CpsDHQ6ChgWi43B+cuARHA4JyJlS/14HDPhjpFzCc7Ei6XDRbMlgPdexlWxA95e9hegB05RRRZ7kwksxq9vSKf+TfUmGrW1+v3ug51ZQUtTSFezLPakkeIFRVUr6GMsd2KHQw5QUEvWUiaF5Af0u09Ve/79gxy1LwmZRKOBRlCHYuA2bN/8iBB/ZW8+ngvuMiNUtBjlysKIbYkRDxBxJHhLMrncKHIIQSRK0wr5CdQhsXRtghPOd9UQo9Zms+TvCRGvqJGX002v1bsBO5RmUMIFBr+xzOliEx3ExRrI3dClqzDdrEZBL3RW4Y9LHz2npkU7N4qvPNMtL+6VnhOJzbzpAq13yyBTPlfArzJOEefYTSoOB34KO0OOhMR4gMQMG0mmyOnreSnWPVINi/WPI5ybNoKYN490u2+LiIIEEwUIQRH1hUUS+cYzneS1r1/oIwKstH6u7pZqy5h1c7lUtZdO1r/G18xS+OVYW9VbJSTXq9Sj1suZFg1ffY5peS66B+gK+/LEYvJkKKYyfRwfvjVIU8ZPpX9rcnHwCEUDDdGIUQhfNp2W/+BZZPT0VOubdGQV99y8kJOMADVQCj1dW0HOkXVS4tufhi3ooIg7/G4taUvi8j8Vf+m/hRcePu6OPiDevgOxR/HtyDSCmulOSJGEKBo0V6LjP85JGha+WVkDnPWIHQveAZ7TYGGgMxyL52T4k4peIyNXZGGG1CchDSQtbYFb1mYi7gqYilL7/7LfALoDEmhwby4d3qJmDhG+SU07pCPc1gItPo/qKXgB4fv1E3tf3eIthZXmqJ2W8L5tSij0TWxjhSF21zSfOrSRq1dOpou7NBOVCQZbXYohVovKxHAeqvRQeLQGloZupo72sl3Vr5ur0hKJTXSFUhSrrRTMrn0V7m9APgmyOKKKxPaojE0UCJqm6ZLHRdzgQSRhWvmLu1sXRWoqXsyt+j+rspnUe31XOuDDm39GcSIe6XYuYfuX4p5bFOapRtV5Y4qNXXq9AqpZrRlzKsoSlEN2ccc8ipzI1UqeBk0C4/L0Ozelkt2cb5IYNQYQdFXGVC4Q9KfVHe4P9lazCpleiPs1ClWy8wOIvszyUnu5WDGV551YQeOEyR65mIq0w6ldtZnYsslD89AdfJ2uBExdUKsoTwlD2WPugG1i+tBytUGlkBg0mj73stL15kOfdXwq7oLO7mH5NdN/iLRkYHlJXdeT/mMw5PdX4Uc+yeXZ2K8wnLk5OLaRw1abK8IfqdBqxaVpnM66XOfFxHkktlOjR6i7hP9sdUL1hKm0QUebMVJUek9tamPvvqoQ8BVlN2tkn/2u2inw0IPiE0ZuQO7MVwiERSjkuOSwzYcjlgk+XOjLGVpycFCtkiu+lTx801KvZWNAG7Yr8SRyyl2Afddzim53/VChNwEfKQ3nrCftAdpWp3ktFQBia3IhMqhjD/TkNlfEw/dOT2vwLjqTrVCVTrcJetvAkt2qocaqHsQuwrAjWalWthvAVi8bTFoRzjEnQtpe7O/mTo1MmACzhPlRTXEboevIJhcOQkZ1juJL1XNqPt69cDWVTuoFaQLR+ujnOWYvtuvje9eABxqvtJv8wh4wt1pIYDwzk84/Btfnq9qc/Qb01X3YHxaLRmMplHIsbKOltDXzrdZDskr8RaVBw4Eyaqc8q7yb15aIOCkz+jphZnZ5ycsZvrYlkdOW7fxfIFAJpl5o6l8+CI/pSBXVnVXsOxYdzI7uClSlr5YMkK5aPM9+r6+Ejp4bLWPzCFQ6uLfHce+KvJyL8MNj/s2eCaege88jYF6GaGuMUwfDqlQLaKg7keelCv1pIJ2+w0mnjMpK6sOj3gP78tEU3poKzO9r73izfbXatrhw1BKbvpzJbidhS5dCXCP1l/21sKbIzzjpoXT0oIi8DDJendivN4NKksNqprfdQyo+ULu3VXZvsjLFLj2u7Ncguh+S/g8U+HjAdWhZIqtR1CZ5Jxdnn1OChglWpl5cQ6xMcSJXZkHlFSCEwE7b4Po1fBqeQyrbywQVoyU/OThT+AcmRQ8jgXigpT3O/y5qIWbcfY2ctYphQ12OOystdAF3j+hpjpkBFWVKUIhbteagTmBznMjMT7u2RMdb51zbiy80DcGKZZMwRlir7uv9Jzi5MYadFCSQUsof0QNJBAL4mTy+lzcQKY0ERLeQaNJeZZJHg/RhOC+hzhqAL0QA8JBNpkHGjzOoRtZx4M3HT5M25yEwwCUXnvnkVw1TCUEtaSUOGjdmlR0JmikMzyjU74MJ1PT9wFebEqd8o5JfytZR0MqumMGTKK4y9OSirROfX1lbr87sVOKmWLYmpQcW/dWmYrVT4p82MwpBDjp1DdidUc1QIqZapKQPtyk7WkTknYCb4EDIxqmsVZ+AluJ07bw/+qKXJsTi0gnZvhVxL2Vlgms3DW4fu6+k9ysZRm0nZVWewb0CQu+s0GBvuMhvtqm4FhhWtsa5OEk17LTphakeF8JQLF4nV8ur/r5YDh2oWNGMrNvieL+cXE5hJPmRFicDRgb+31HDsfxKcQdMfPNDzIF9+iRUOCfwEE+yITXcphRVMQXF5BXZuYkUNm7LdQ5ga5HTKhkMnlF4jGJzzwQNnRIh41RSjSY7TwJTyWst3BpQJSELIocyvQ4mTxgT3K4qSkR+gQZKMk3QPvEI5gaLxARwgFWV4gT6jCd6w7giPDbVofWxDPjy22VH5qeVV9SnMHIN6RP+0kYwt+ky8RAaHpY0NlG52C/k6at3YmyLi9R6aglhBPQ52j7/I1cK5+2ulxlz+mN9UKaMu/9T+N6bFbKj++PMrsJMvsrrdoTBRojnRjclz6DvFMsrTvMWgeA1+0PClZDdVEYCH070lJSqRN85e+hw0d8PakZXfXgIr4Fy8wjasqZs4n78vky+xFItN3huFWzW3neb2KZkPGd6N7KfIIfzGr5aTRJ3Nj4Vnq/5TuzrheFB6TVfMs0WxEBNRh4OEYJU8nQX6rgvQVIcUYRacYW1IxPeUxOs6df02ppLi/81aI3NrM2t8ntGID3Z0iwOESVZNAyS1SWu4zWU2w/+YDcZwwK0KEDDpCRFKP+qr7K7KIrjFX5M4NNYenb6Wi2v81S0HjCwjePHEj+6Cxbr0Lk9OvJ9zuA+w04BNWEe2l+4qzrAzI7d4u5WccECl0eSOBbDpMRS4dkbEVhLjx4PoF7Li7Z9SIeoRGpF/sp2qupa3ZoRdDHbUCXPPTKo51+U9BtmTFPdprUL0wGM9RoZVCFJbRToRtUDxTdc+esE0IpYQK88UDGR7dOdVBtRbGGxy5+It3NZKPOnKySny/lE21aZ/Pe2mNppXAIeUFydMJOFggMYTwQxpYnu5lhkRFj684S6FYpssti8vTrhXr0Mz023SnVQLi6yQRF0nBnxVtp96VFfp6feqXrL+uR/FsAtakJ6RDvxLcI7W9O5Yl3URsUg2HuH2OCZqQ6lDrOxVzcBCyJBQomHRssBATzWk9Js51eRJmPf44M5mProz1FW+JSs+V+oAHn3xLfA5d9EIrdkzeMjtTp6GRpERkXDgEfG95rL6cxZ1yagjeCEdi6xPqx14Zm0m0kX9vMwXFUe775isT3bFq45RcfqRB5QEnMgWag6oOuKA6hvJMpyYY6CtbxsNlqeiG36AZjeIuA48gdGjOjGlDQhgP5cqNNY+P2IqBs1lYaBo3cBXoSkklbbLLwA/cCyp+D3JTYeFHxMy6Z4u4KLjH++FQSypdFwNBa9TtDdhZ7aW5HuXN05OYrYHn4Jl1HeuC8qyha5dhe5LfBZ7PQtKa5ll+6RD+wsc0Haw/cdIL+dMVB8QezN3euREMLc4xdTWDVPHJ+rvAnGQTgVi79F+m3VVqf/sBu2K8Fr4oSjdMAOMRksOh2kaUIjoVS8fKhujredHEW/cG8Q+CUSujHI/B66o5m+oO8m/me7+yQKGcjoqC/7xzTu6c55dQUuek+UqjOMHIcO7HzkOEg+20VsGlLbzcjfTMb2MHtQBpKKL44RU5iwoeaXzJi7DIs/3vbJizGT2Oz06KXrA94YMalnQ/x9c3zcjIpHzWp1Fe2/0uBkwY/MnJW2eIABMvrJKLmDnsRxA/8vyRPQ3kYWHDvD5J5we6gfo8WOuL+U7bDKV7XM4+m2fy6qQ/fZCmaIzsFkEmxfut96eWD+4yCiCheqE4Pz49xv2Hp5iFCtVJs4TceHXja74RzdIKappQpr9vauuD3KggTNZQPJz6LeXI7q0/ZQ6hnh9vCzdco+NoEt3AiOOEHB1kMjIt4pXraNsSGjEkxtEbUyRnTBSIaTEv4zvcbYoCkzicz0UoJM9ljcFCNUIs8CUMfOBfz9NWbiGvM4Vo0sMdqKEzTg/HnTQ5lXIP7Qdyp+ZOkavsj4AFB79tJUHjzqU0H0p/UtGr4/7ZkkcvvoFLpcMkZB0GXb51lNCMfUz+qnEacjhGkfvWi6Exny/BZLjl7X1RZwb6+PAI2A5KNDrswRuBTYF25gQ5A6Lgn/8TakETOQMqJ9s0g2g2Odnn1sRKLISqJR6Qg0AW3JvlszJ4RYFjAOJ49FGqrHN6qV84TXdm0ZZu97vnKT9kGZgdJywaaPnSlpBDY5zFUGIBxyuJ4Qsl+Wpob3UunzPtGlJcd2z1nD0O+uiHYdu8T8V14Qr5W+RfYA63jJVSCdHg4hSubuKuQ+HAzHecIDecLh+qyfxC4L+BbwtyoneKGD707mJqE1wP0gU9NMeLUVd5sfZ/bL/A77AyGgvAw5hBQuxDzgs1Z+6u7/DYGLtBT2qOO0s8sSnBb67JmBeXZUxvlwEsNcLVO51nkbBV+SwGShYeo65CwQthyjHrfYfPD4kVs2XJIPWESxzl68zGaseYVfp/CchT5nNSLJDWTkOgmUPYUAC+Mt+s6VPSszkHx1UzVlXXzoz6dW9VL+DAfgwraiBPC8s6SZ8AUFrDzALzlnV/q+UPBx0GFDFf9genTjPR9vLuWNCXqkdvWr+Xb2HMyQs4KTxmK4PeSijIgDJKyjhlhvuaJ9Ts50g/4Lglt0X48pGDr8oGZeXhegdwpqrM96lhwHiCawxoS2yU1bgos65xpfX7KdHV51f8AETLwDI/I76rvTaOEMYKFS4fCTwgozAomcE2sFEnrFtWbtNt+T0ijvtr9biBNFH4Zlkhkkjp8/I65jv99FOLUPvoa8BUACO/zrmxqEpGJCOR0iE7qpWoMXXEK294hfRODz4IkDKCqG+H8l0G88PW/flcaie0izlqkhS8jZVS6zwTvIQSc0wCxiuihx3Xdaxy+vMBmTI7wMjhqn92BHEs5i+2MCOpuHuW2WOPpqCyMuyPwP3Uj0CQMHri35evt+gMxrmAulAbuBfnUBRPhou4N5yhiBX1VwoL3S2Iwif37/fBGtcPpcxRSSZeM0Qz4AMc69XJnpXQaS3NwtZUqPC1hZg8hFxgmjn9Q0G05t9A8INSYoyYUYqEcJ0uCGvyHA4gd2G8pqJjD5BrNlvlMCStEgxfSKc/KHyslXj/Wvv7Waxqy36RHLHLWd0b9qLsNknEtKjK8iy4eJwGPpgS8gXPYyFP2xylXA68Lnlhs1HrcfvL4wyjIuq/KmSQgCRrP9JFNYrJYtUJQu4TKaT+Mpk5EPYMnJ8t3LVpq2Axc491zCRcvT3WkWdajko/AYdgH9k7VAh/kb13xEV5VN2vRsgNSQYHtbExTfejK50l7JBTKBayZpGcv03Y3F4w2EfyVyE28eWAYTbDJVYO3BgNEXp5A9VY0AQ3fMzuND5qy7ZjsUE0RBeRJtIkVmxHFoWPKRJtsJjQi6En9M4Oo3prwT6ns7O/571IaZW7o9pMbF+nvrkX62TaEMD9Zfu6g1zhrMWqEG+CHsm2Tdi43G6wCpM5QVbbw/I12R72i2X/siYoh8JBzkgma9HY/ZVgy8Uqu2BhOllhyILczw7OVz/XjDIMbHn66Br1O4ofn5G5XX7aba+AIavKJEvZVcOqd1RoGjW5vwCxLkGz8MF3jkRwIXh0Djuctdx+ssH7XV+z3kt+SNl8zUmgolUJD/ijLweSSj3vHHD6k8ILUgpZpoUK/Zrrz1E01J+vaJQ/X7EjS283Ekfy7ZOCAxn21wo4hJDau0kiLdj8h0kEeWyFfqV5ezwV52OHvgm0LohT6E0TNMnJf7TAoAsvqk9WBwW6dME4DfC8+oQfGDLls0jI/8VwNHg9xFH8TmeRk9uLtatjLQBrhvLV3+FGArX03wbdMmgx9W4Zifan5XDDcqrc6s7dVssia/bE6uaigBSWCOKtCpLVPlkrfGL0Xn7X8CrbCIULurSXfkSzg06wugn/0FLB7pYH9PS7waDhzZygqG96BrQC5xWaNCdhEGEkByStB0KcfM+H2s8FzEDl2qbwtaKaP6FJWh/ZIhEfY0HQrP9b+/CHYgWVZa20uq+5j0JWSPRM5REAVStudZJsvXiti4i922CjeK33OJ4ssO1HZaFO3nzGLcuR91k+OPDyEYMmeOV9qeSmJkS/4/8qQ6fCIdm2iUo7dtmh5XAEQ3FVcjxyu7Qssy/H5gQOQzpDiY9J8AYx7yj2E7LKEd/RppryKZOgg7XS1Q9fFEN3Ke45i0+qOfXVMGTADJcfihbJoMRs+O0AvEhjxG8JhoWz5roYDX6x0Obo5ySa5T0UlT2VPedKO6Hbz9llUFONvCSQFFO0XloCDEtUmulkJstjstpF1jxMR56iJrJl6Z+WHuGbHp3v/jG/BL5UVBSLZkIMJf5g2gacpjYfBdOcfq4QnTBO/PKMUHDo9+jsJj716ByLLqH1dqnCcpix3qDC/A9TwjZP88h4+8tpdRRr50UlQaykInU63ATc/keRsp0P00/pUaIO+g9tp40eXfCRSg9umsMFvCw0K7FIHbgUZrFyku6uOeuVLw02UeXmVasTOzpFmibf2xaIQrTVzCl8Ksl54V1ZjUy/VG6CQ3sRxPUeOywMtw3bTqzAFStEwQbZnn9P3l/rmi+6wOCO0F+aUe9guC80T4rUCbiwVA9rM9RUdg3GzAgJh1REYb2alqdKvyD+LpLvOan43MV/0yHfJ+/vhPY6d4z54qXPnGSCLm9lqCUdIkqGZkHfbWaJDEThMZyWa8OGMUqTEokS03gWeWYr5XJizz+DnFqH6bXTLMryZlsexkS17/g2izwCf6dFcluNvfuHezORe65IS8ZzjdWKW5HaxlwslFkG1epGVnjG1gh3+eP4hZ1Rxxlq9lTzvKNJs+ZtlSyni5YcS9pJgzwyF2Z5XCaHVZACBGvqwvtSeJZbOMwGl6dRnZ8tFHsjQueZ0KVbnc0uekzu9zVaoCt80XKAzzhEG5Sauzck6vBlgh0030bFSd+XKRVXWyUSVrnMjcYPO25QQGQfCuNurkIOWwyNsUqvmNmi6IOP6hx2WHqkiYV/ivGGu7K8poFenZXXqJQWYsx3Ocrk7+0ug13ZinyQVHqKx4ysczLYZ1E+S1sxU0bek/nyWkFHTNS4f+4tT6JDdq/OpMsdDbVenSSazGhzB8uC/rLl9FG8PIQ9GJSKHmASVLInP/9sRr1eycfIyWS4ftSGI7pbns1Ywq8d2TuzwvTLIyvn0LtC+pRKg+GJNBGlmarAjQ44lrqC8YZ0+QvR0roJmtWmzMqoyOdww1tDXvnRogN4GcE88ybpW9Qx6Nlg8sDsJrG/B7dKOTJSaevLIyl9Dc99sGJJ62Xm5v3WoL4TC+t2UopvBlOOuyK67GBohx7vCyx+xWRZ/llw3RY2+k9o03icdUIrOWEWgOVcKy9uCjAP8JnQ9Ne/oL4NZ6/q0FHQiByhkxNLplznUhl7o3t95gAmPZmzvYar8rIcw5Rqu2+r68n98gYxEzOVn5+r52g0VzwnZz6zvBzXPS3lAmvAJVAV3/Lmj9iI1+7hI3sttKgWwIG/6Ip/TJtoL51PZPM/1oEaGsTFlUAz+sTx0J5aK2JHR7jWMDQqnP6zxXyCberkbcbW2ByYm2d5Z02Gqd8XlCsz05O4vc6pXG4XbTOl3sntAQFyMStZzE5Bqx8uPSbjoH/gIbteD2xVBoQDU7vhoR92e0ooU8nEeCZyNgZ7sHKJmJmDzhtGQ4rP+0KQ3gOSLWGXF1e0slQ+th2sNXNHQ1CVtgruK0UYV3u/LpGjkgm5BDYSoUq+2OH0jNWIQr4wyenmXvOvC5vjVhDP970LtjOfODmzua/u4VqzMBny798P9ijB9TTplYcWxranHNaRxdprL/yOXFRCtvu9MKn5Z2t371xYMKihS7DvQI8Psb7ZJ8ihhxBjV7eTalQxvI2wRyaWrNib8i1rjXRb9sjBv+3Oa6TH1s3hKw0Qq1svAGi199oBtALlNtGjsdOwJrpnCZ4HZnQQgi1dpzMeXI0dmdSe0uNWRhc/cJHVWNltsyrWVcbmdxb65C6TvLT3EDoXyUvy2aaQyDvGjTvd1ygWu7D+83XZOTZmY2Sxm2leZ2hWPZqsgmATTlrKoei4rl3NCi4+WtuTuHqJY+XYPw/5lZAK/W9xuZn5ylR+GUphbV1+i1VypzCYvTJUz/pHkjiyXsc5iTccXYUeGxsqMiyFLHOXtY1qoCqxmB4izoWsdh81ALJjaC6Zqcbl3F8kY3hs6OJBUqvT1UuJ4KXurilnMCtNZFnW76XurnoYGhQH7Mb6aIdNxtkcrOzpxYOcYbaF4ELP95j6aurMw/nz1cp/bKupynoniNKRUqkF2BuF9DvcWI5UkuC0YEB+apmem2jE6nnVsFcjENfjQ4/iLex6iVBxWBembCK1mNKjslYgKr49vq8k+7ymJ08QJ3DKG2M10xVqoT/wV/+UtgxXpGssXae9RBqS7zdJEk5uSLC4BFX6vF2ThsWVzv50MEH89WcuRzmE45SEZHB7MUCQwBorbUxVy7c6N6JCmC/Xhnk9pFHYLzXDuXk45MYKl/ueVRSvr9STtvx7GrCpa9WzO2He7XKevBXQbYLcft2AW1QJI0NYRISg9dl37PIeyw1De9ln3NfByCHHUKYk+NMzlqmzKHzN4nZ+r9UzTqZUQa/YlPKz1eOtmpzJoJQ+/Ee1em2Dn8yzYAu6OyF2LhwOF2+SPs34PXtx9sI3MH/0iXctr4E5TJoNJiXJncxG+r48Su3hKuP/IG0gM6BZuBMXBX324wjiE7Lir6d7VrV/P8DdPKJ4hpMZqw2rsGEb5AJwal9hZhQzOxkpxQs8XPzCHb/9bS0OXu7Xbn7lTy46tD6/wsNb3iyVFERqkXE//P94OnYRHMWZ55CeQ2h1LcGes1DFO86QsU0jNacfI83vA2kRF3eScffP9RnJzCrDVkxuW1P8TvCq3lmYjhai4j//xG35J2dBaUw+veo0jy/rEW1/ilBUKA9C3sRHZTuCZv/n2MMg1Tgh/QGJ2QLC4hUDZfEqRa/R2UipctLIgTP4oTCl8nrVCdDKzZn7C5dKIlw0Wq4KVdpN4fz/FVZqGiTqlheGk+Vy/fESja37MeGlkJ6VvG8/jo3anN3oINNEvaYocHsKbQi/yrUgEkZkmxRO9xiptBsUElEQlEu0CRDxrvY/gTHwTEKVWapUfec8v0vx6et0UxJ1BJu2zonXSYWJAfnULYVRWT1fxM7rlMfwv3MeANJnv2qf5iiwZ1GLthytxzD4Gb8OY8bn7FUAJtLYtRPlf9OYL2REnLpQIt24n4FFekj3T2o6mWoiNy28MNvRGSZVVReXUOuaHB7AP/qxuZH40vXFQ5DUiTKI+xdTauX8t/GI2R81QR0bcgFTJsgEWZlLP0Q+rbJ+I6lAhTtZIIhW79xT3TsMpP1Hk4ZCHTiNDW0sZLDi2jD1cYKySkUnIHRQRAXheoaq3V0tWA1vsopcDPQXzfXwjn3xJS/7qxxpYr5bouInPaXapT5ktNAaZcgW64u7rPrgfhjEg0FU4lp/IIR3TyrNg88yEfNs6iiHAgySDUPB6B6VVHPKaZkVpZwYAozeWsfYi2PU2i0PiX9Of3mz1Iuf5v3hfvUaeHc4vqgmv3ZzbBug41/tAw5AtiD2vAWwlcy7MXeqCpmpCEulRg7/nP8yfj3tXIPnqVm7gFUAyLq9H1Urqc8I5VjMPB+b29l3l1A5nIP+WbLRvA427VW/VBiQo++nbfrQ2TSjI0C3RiUFZnW5qbNKHsEJPPgFNDXZyXLkVBbZ3SS79wOQrubqjamB/YTF8Pn8ZD88btahwadjl/29j6TA5b5bb0DwkH0NBc8AU1ocXVEdH1m2txVZ2cEcUB+4XnOc/JnnDzfgecqTY7leOeIvrNB/V/VfCMnIDpxPa6XpclzmUvjDjfmAn0slGzwQYyI6izxjzyTi0ajUiGcqFskvnaijN4WeB90KcIopWoklg7IUgZTKCQHl8uP5TtLHz1MAwV0exS1WJvfduUyu5GP29nPVWCYN9mgpuISmAGkAxcWdwiqWN8nTfVzQsTn36kLRz3eCZjhow+K9h+G3dxUTk/AxSiwmFY9fgVwHA2lmpOT6wypH8OFgpA7gmn6beUUddkBcWaxo7D5VcK/4GunO7fKokeN1wuEXSVbN0/HhqnmAmeZrcAaBWcWE5EsaJ8DJO+9ctngfRetWv0Be5ZOY29Mfh6HuWytq1sCrLM63jqg9VvOrnrPMLk6V8JUnjxdF01F9ci1uybzpodb/sxj4IZAk96gGGXBHhgBYSx+GCZiByILXMr5NZ4etlN9FEFjh6Lbw65u4nRwUh6vJ3VVq4mnOgr+WYwYZy3pgN7HrnUkS1sEg2kAIGzAxUcY6u5+1ntTWMLYGeRdN7EYT6OLMYPYAHGxZquNU3TX2qA9RH1J0UFynz9K5eZ5xp2lk/lw9PkWITX2ekEzHM6VFbo4teTaQljK7WZUjQqgsn8Onbsvun9/jlb8lFeHJTwMOCvP9nRflIjVvCB/I+ga9WO/fyQ0jbiFmvC/MxzWD/zJ5lzpQ8IVxmxCuj9kRwJPIbUiG90RNDngTsMA4oAdJS9PM0aPQy3suy0q7bviSVeXc6UTvyKpSe7rpFJ6dbN/46S7Rb62Ng2IuNt+k99q+y/pj8dvageiXDNc8BZ+eMOeM3pqxsbk37rrbXng8yXE8fxa1IIwRGyrsqTZz8mhIx3KfsQ8G3v697+xSj5AnTbWJBv70p8jHUFLyO8c/IOST1Uae/YrxDE4ATyNEyLIOCa7b/FNQhQYpTJRp8kKW5fLLM/DgqqSD2uO6ko6VyPU/9eKmUOWff8r/XTK/3yxoBBxc0rPj/D9ZI+KR1191Xdisp8FmQiFKAxp3tfVwAuU5CSf5Wn+jp6LU2vpPp9zVCstjzOYa7VzaN3PvuCGqOR9R9Y2YS+XOLV1IxomlHGIgp2LybHVql88ZtKxqL+DZnzpuYHqvw6vhNheTpEhyRMNEH/aS+KvpvuFEXNwxfdFIlIChpNibTaV3JguJ9EX2PL4XOT87jyWf20iYw4IrFZdJ54KUeSozewYNi+BcNtubzuGuGNhfbwiCPJKvQmYgea5s8if5P+ZaXA4hP3lx9tmukveJO1EJOl5GhUGtf65Pm9+7lcLYU1112ekG9oPN8a4EC7PexooSVYmI6gTdDCjMhNeiXHr3LAQhAZRSQj0hZVD4I8OQkyIJ0wJbLnahwYmxiGSyUH6p7ouNQ//ihuD8khX4TrUwk/KkS6dvFo5KrnwwZwUNP9e/vHrVtQITJWN0drCNE2Mm6fYCs+OV98CwX3dqXU/JEiJ2gdY1MkZNUXQLOQIk4rCKPvuxSBvXYlbo9G+YBfTJy72YPMrOewptSPgxsnQMS8t1a9gMDsbHoBmjaM6274O6EXwImIlkTkniuWXlxr5OvimcnW9Sz8O2i3tfUNDK2IrN0J50mrBvxUgfOqS8EaDdOL8ocW6oJlfFZqed0q0PPC10XAzTYyAkocRezt4ENbC853PGvX/n4cOng71dwh9WZco6jbHZYizqJs8l8YVHmGJSEjlYI1+Kbk6snf12yXSnJ3TEzBA/ftZv1fobsZk9TZsUroxSG1KHulOCf5z1O/K8plA6FMc7AL3yVMFzYjXOyoZIx1Oyma6Y7fQleedXNNKg8bAUVnyCeKrq11A8RDCt9RvPhW8WGkA+ln9+R0r8Z/xQOR+eOVRWVCoFaFny+kL2H97VkbuWHpqWOglTGsgYwPiQ4XvHpaQwR+sx9Mu94VP+NZnTn2p3oEX7GpH7UQMz3M91KFFy5BNBcfQfn8nS1DmjwligrYLYSx3l2WHKOangb/NXPwR3zoxBNSWkNVvEaUNBShkwayeu1aI05isAyvFqYcnpjtlqEkfksYGF/gAZS1vyCGFmyuw791y2svCaaJWZYY0DIZtOjGPR/6UCpG7q6XcGExz6q1kH9olunZq3hWEibV+DJizxMC/5HconSZGPBvQsFnUzf/ZVDoIizz6u3YIzy7nI46QyjhqATSaGYAu+PFwTj3K/RD8EsG/suizSOcjV1BMMV34YG2fwnagTvOadqVauPfx2VoTa8DLzrwhVfQQCjEhb5mUSgzKKvjTdeXdsPYO8PujQNKDb5aRlavOz4XBVyEy/xgAT2CfyTDMBsMmm8d9jh4hIIIvJ5JA4gzTzEstw2tSdNpSsW/j1xwV2O5wn/J+XlaDtLjNtM4zvdMNSj4/7l76OWNa8tPbo4QC6C/xuFqrsN+4rdz/NDS0V8QIkfuLpqmao7xRSp6XBb/sjLpPgGmHBzTlemKX6XeYuO0frxhi+bCcNeQeNwok2zFBnVZzO1wwdiDRm2ZTzlZkOVqkNNySZ72Fhnsopt//euOH7L1iVzhbwSRWWQahJTHaasFIAQ+V6QKMrDsLI1RoZJvaWp84iaSf1Y+htOiZfsmFWYUdQg8tmBuK3eRtHYD2MJhiXvbR4OmG2wtLRSPs41DKzM5DnHLxc8UrIXG+AqicIZxzHAG2Noci37f30jfQSPwnRYQ5H3+b3oVy4/nqmtJaZxfEjcewf291Y1WiE4gl5E3/uo9lNfcjpofGt2P7EVZfKzd2qwDl79vsSrnywPEf+0r+Xnam4yeRrLWCgzUANW0Y+aYJRoXVGX3pF0ibkCcTt4GUBF8TzLBmdwwNmP4S6/i/n+xlWYtwbZ157lK4PjALTugXaJ05zKjyOpSX/1uZqmOOJ7BfUe+/NXgIDCRcR4HmkdCVeDIWQPyoM6WDUj+F0rkAnvq9VIxG4tze6AicNeQcYHa7HKDn+s0LrfAHEMODEZc2pIvCqUAui081zkZgPNZ3/pqvQ4DOeaowQkDj2lB8Rlt2980IsdpmbWmuCWEkkw5Oko8uD6ymGP7RdxUR09kHm7/tFWZNod5i+t/G6GRiteOhpTt6sWK0cJecKjq/mmSHI7pf2ZYWbx21ictcwqVjr359sX72Jkj0WT59XNGmSdH05sY6RgDRPd0zWBUuMgRepont3xNJ13UcnwPFtCjzfRMtNFYahI4e78HViEWUOuCmV/K4v35c8njMTvTNL2vaoaFPWg0SdCKW/AUZP2SwzezjMdv1C77oIUH/E8gJYhgh98dXmow1u5oe7eCkytRwwTO01wzAwAHcgnnmKTYVSuZ10FC63YFnL4ur0lMZFZMhp5zSr4PMBo8KSnqjqUOuv2Dphv3m8P8ZZMS+VYLS+LYL7h6MJ8a76RwJKu9/qHQM00af7DG7LMlskAt8E/SM5Oahj5dpOw6ELO+d5rtGjBMYJfUMt3v1lP2aVrBfdXjCklfr+K1qT6y0iFu54RkW6gXlz0TrUmZGRUmxOfoWEIthKmZUTG8yv0ItgoCsCz0V5oQzaIA+osvQ/xzF4jObvtT76MK0JnEGKNf3eyq7eQW6NLj6gNJ43v2mJF2dth3kQjaZ4eDZbAskKrM5Wbd0jj4LyIkka9ZprE30XrYyNNAkKKvA9FaqEpCL5M0cgHRg+Pq8QyB1RdIo/l+CBpwtCaDyxSXFPCi9KUAehzAFW8yEu7FA3sJ6PfzkH0jDzus96vP5L5slHfP76WTkVm65FTS+/H80GS5Hri2+dXAv6QGaqii78DUR0tS5pRvTn/dsQr8ZvyBu1zqLVHqQYg5aSvXITdBLx6pSwgPXV6D3v5qDDHmI1ONESpjr3CkI28oxFla+lbmirYKXwAH2vafx1/lXC5gi7BK9xcMh6nbCnhsjKZEsCU565+P9itZRGSBAQqNnh+mNKwoPPF3LBKwWwpnSmrVXTOJLv7dgg68yZE/sXMVWDoYcZ0HI9Bf7SVqbEr+NBJOVS3NNFRUI2XANjnzI4u+PpQGP+V6ef1peyEzA/vvQOGK+xQOTODgVpH55UrsJbDWoTvpefsVemmMTmNNFWzmTSStXQOicqlk1maGyx/tpaFAKG8IdoWo6vc73Znma8Iv1jaBcdL3HN17xkGCJA5+jt9LThjWBOI3sSmFdB4Ww47jx3vGwCO6cIwLPSHGtJEntnuI/Hrns3cPx8W3mIt4QHRJ0u2a5bcFGCYIwF4yyPNJdPw9xTaajrh9acH8VSAgCVL8HY01d+rXfOwhKLOKTjyjLrsWRQoDIB6mpj/5cjBGZqnKa9BRkUWbNjlcEFBhakkj7WyAuZsyXtbt8I1deJMrYx77n6hbVVqUqtjNxoMgSeEMko+f4Yl+bV6vymBFeP9ibS5L2hHTEwprNQyNhlvT/VBPLJ4qYQ/hb+VvvkI6w0EHafsl4FDW1iJRUjZnXNQao0jLC1jSKLzxCXBjcchIHGjVgnVijrzL1z997IawaTXGSi05B5nVwwvFDuBRnpCD49sO4vEpuiNOnRTEHrmJGnpzry56P7gCV8xlhNG2cJml2wZahdTbXyrZGvuQvbUcBOhlx3JFsjliPNvhf/kqKCanUtMgkXG3JQ142BHwNMwKUzgxRypONQUixWOvmTpmThRoZ+CGiiojUuk9LRdDGl5edfGu59cZl2ZMjCHv1DVZlpawZfZ8Mo1Tzo67ph2K7J5v5UfBy6XMQ91mUXlxH6ogby0/ai6Sh5mWUiwc6YGoyKAh39wMKfW62PL6o2PBTzORNsMTdTkQJd3dHAZdUpPNAr8UWwRFxk9jA2ots0aXcudLKnZcNqTiMgKPEXkHbHme37BwMLXBtw0l32eNJ2DMICSh1F6ywpVQxpZwbF30kHGrt3nQQx3r1cvYt9Nsh0hpEFeAyXUXsYzlPCcjFkhbn+Dex4iYwuJElSb8SAlJu5bv3rrrnlCfio2SD2C08VXhxlUuukwAJt6S3EBmTOMXzjIyD2Mv4oxB9iYtMe4oXl8hxXhUgyrru6G9jGVgvjdWKwajVgg+DE65TReZHU+3ma0EiJqwMvd5Vhb94y/XFkQvUfIsDuVL9jGz1lg8drHKMOAEPKSpOvLompKwqYEL36hpbQj0sisLBu8sj6dXP1A7bh/lM8kp65hk+BWdA1FczDMZp1yLHQuh5/hbMvUXFNrtYGvv4C8WfxmNojI3n/nJVJgu5+MZE3FifgSDQbBiOhMRLCo4uupE6k2Z1a/xIB3dv3x0D1axH4Nj3yYNmcGbJBAVHpBDqEOb3rtItw9SUxTHRc0QvngeUWCNfqFjLczjdfTkXCf4ZFUL4+o2bNRRDwOE6IQSkZwbaYh8IH55wamXbk6YALFqixXdBZiaJS+R60eKMqrKpOJaIhNydR/vBpDwNB65l3xlS4nmM/sllAvmah+GTX4lVcc4zao9/gzs1CLGGVavoolAKxAWkvPIjKRTfsAtiB0KFPYR51aOeCo+CymQP5Y6fo28y+fQ/d4n74F6O7SRNJuZ2R8PDDNhdsEAOEriGYiMKypduSUihsYhxf+OCR/dO25WYOm1qoIpX4WCbSraWAredWDM4soBjr49OMtMGcTwQCyUsJyZ/cMNRHhyGMSvMwI/pJwWJ2LWkFDVmednZvJ3abuEMyBRJaFlTJ57kOEa2Jap23uSFUxHwaqjgXLCPt/GqeOi39JZ6oZYcM6NLkWdbpG7LO+D38GsJ6YXZhmntUvG8nG3NJUutEGfLkYL9WOtcm2mvegTUNCxjDizt9OFQMQD3soAr52umgDbkufjpsirfsOdEPLxL5laieHL94xSGVaU770eBvUsE5irol7sMThVYYrgM4CHQRq3vKYXrIB+ULuxaxDMt4FwsyRzSn6LssGs1l0Uj5RyJEdOUS1uB+IUWwO9GlueMF1CsGW0gdmStERfaSju7tiLU7sV1tw3lK3OKyWXZf9xqA8nQzX6/dpxI6jDxWGoo4YQu49FVkQlk/VslDwipGlwSD8g5GVShJnocsu+loRl9tsTZ9EbXgmlhuruPJYnLQUX3SgeYKvHtuB8XxxaI9HPNQlrGkHADiAlxi9eQxRj9jYv3ecii2Zvj611Ho76EL9M9oPnnkZJIphyPHr1fdfdCE5QhxXEfflvqSVEN5+wojArTs9C0aXQXzY7loM0a58si7v2uH+624tWZ0ALAwxmBM4Z3rka0dl2hdUvVZJ1V/yracA23O1C7s1HUgsYggiq8btuJnkxVyvOPVQOsZH95FJoxGrKKnYuZRUskoVe+F3OKEZW9Dvaee6wgD3GVx1zo2I2GjJPAJXor8/JSFGBemIKLde0Aol+NzlQYdFcob6gN+RcZNhq/xmB0VF72wRZ/MA2YUpiOGtxN+Kymmc4ShbnLvw5n0pHSw6bCLDz/vpUA3Rro6tjQr8QxFWJ/Z80L28/jzdFQveRkVPtMLkScsf7qutrrXMW/U470OJd6ZkCsLmt4yMDSbgaoxsNc0BPtdXgHeFRhXJ8T3P8Z1+lXkZDjYUkt+eNi+mgTJKNywXEC67JhAfkh9BYMOFzL8runGd5rxXQBSu0pnyczHvIWasxrfk/kci4H6oLT3LUofzNfJ+StvV53LZH9jKjqUzcS1Om361ixy0IM4NXQ7W2PwWVeMGBT88ZL/MSOSOI4Lt9HTC3wsh84Ax3/7iVjd+qrReOsmRF5KofH2EyeujXcbrBxYlpXsEgxID2m9mOaM8iYrOvmvfM3EuzlJN3NzllGvRYANV9aRE/1dJroqAddRYrRXe/Dt3ncwauZGrLJbY5DFkTRiJmdi28YbNXmZQFIRvhiIhlSrxQ+usJGUEsKfRFsq9PCzH/zuxW8TRkFVOZawF+Jfi7i7i4K0cYhxZjN6e2N+Kv4yYCuAkRyI+y2QissWz3dv7kefnfwnMyL/8kU5tn11o0PwXy4nTb0egWIcrtzK0xqIcsaBG0oMCK9azGMpsQqzbJ+BQvib6xJYXolVXdsLqpQGP31o3RPcFN1ip4StWCTvyCagVKb0DhGete1RVRLq9gx0GwEYrvksxMYhhSvnjaLKK9f6bi+7f0H6qCX+JLnjXl+OjrZimAiPkqR+Eq+6VApEILbm8cSj0MCUmuWVszhsjGq7/D28HZMh8vci66+DY4F9TOSfTkbpHPvGdW0XLqY/6fHVU5emPllkhPyk2sj3pU5zxShsgMdjWDrUPtgiH3g3wraWRwa78lRzidj57ry4Dx6gKs/YnstFJf4DH/noZeKk1scNBvenEDt47BjVGp8AvqiU8cv+yxrtezyuKKpwL7L7P/6CIiLvlEv2qSp5zaub181vEgVlNrMTZfvMUn7DhPFAuCiKXMy3/CubKV2p/k7T42oD+Vj26MNA8bzvzUJR2saQ7vnIncAnhslNVfhJDLV264nAKZD/vY8HQfEFdCnLzpHFnIcWpzQtoRmv8IWWdFe5LWXmRoy3Z58imR3VEbuLUOMLfPWk8mmqmMFP+cKyEUe7d8N5K7Hnbi7O0zoc3Qzm22eNFnKumcyS94H7TdHxRx8l1dk/OnGdGKzufNrj6IXr0kFT+kTxLiBhNL3LyAA8Pvexcf2Sm1qOi6xYINXYTTaSI7BZ3gwYXKxH2xkSo4Wr36ARuvBdgbMzvzHRlAsUvaijh9uTzlI0hhhvj37O0Wu7VplQq9N8K1cwTOIZ6YdupduIJVNx4iYUWxJNVcghxItinIOpe0CE4IutSH4yRENKDgy/kgAZ5G1pWTq9AoYBjSKAG3vsGwhpnlMzHPtmA5jVH+PktaGVdMUmFodoFH5nTekSN2eRZJ2RyfeN8XuLxkOekE8o392g06lPXk/5rxkR5Y/CpEG9SJSyXe6c7UPwOmXNF1pf3CepasqhMeYYtUqydR+Xfwfrdq72+BxjNCg6TnbFkmAJUZV+XF3EzT08MmrUETsnJH510Oh3YPntyzK4q/w1yeCNZA6pXq9ptIjUDnEiMOMFGYZjrAKz92Mk2fJi9E5R17mDkLUuyTNGngydtY+nvukkP0mf39TJF8rZexMTxRVucC6zruHjPpILRd/WfiIBf+b3DO3cNb6VklAsRF+otRwc2lRDWTeGxQmqO9k3Dvgc21sdSgkrA7Yaf9WrTcv4OrHVzJuNeYGA3qLPLIQHmf+AW27HxUBVBsfJ6ZmQrUdXBbnhWu06ckiJaPFivrgV+itO03Ru1ZI6q/NLzgQeZIXlZhUOVSwmPVmNd76pjmQqdkaY669xWTJjfJkzOdnEZLv/GyTUSRLDLQXxXO7LiP5D40YUuFeVCqNX3T9aM7cGiELGewJeUpxE9/JcKSpmbb6zouQHnKN6ltM6NWCysbJDCsAYihb7z4zeN8m3E/xRlSuefzAoRpXDPZEr9uBRTUm2rvt3GsXzhebqZkssYAI8m7plMPrJAWG3BovWWsyAanQeozDenAjiWWBuvd2HmIjTPEEIJMHwSEEAkvBKodvOCdqHkH++rBzHymz90BXKrn6w5PkeSSEUN+i7Y/rP8E/ACZ7Ph+APoL6TIIpBvXZcc6rx6K2Y84K1LrUTIW8JFmnc43nHecNysaNzeC4DWFJQG/XMFUokAv9+9/neeMDE50fQVh7nEa8dg0X6RRvKiTcOIxBeTq6k8IMXf66Y4H2GJsiKQJ2Xe5z4dJ0caykLYBbVk0/ha7B80OJFvhnYiiz7MaQ4PThWMLyQZA0avstgth3wN1JRVBCwYTdctMaSBs3mhwOdrelwxbeZi5Nn1SGYuPdxfsucjWOuLEaDyOiZu2QrjEwgrTfrl/AoG2hEXTMxWxLkbqimZ7mp5fPr5Q0VpvF8K/FoU64rvZ7vBqDgwC/7gyuivnIDue0e6yp3lbqF4Z7jQa9FvRPEBp9oVYqJm3cKXE9t9f4DnQgCPBd0QlczPRWwzpITpCGszjNAfff4UwWjPYXz+IiFVDKdK95De/cWOBbMBIO+RAsMqb/xOO3YWcrDM/mrvnAUdGWNx0ejhbH9aUUNmWr45RLmnQH/KdIF45KxpoVp1nV0X28vlsoL6zM0M4lutUx6YB/1aKWrRvPPUZnxPn6qAatW9YzzxpXgkKpg4WQ1ZXd9oWOJZI1ar0ff2sbk9tntQZD6768WgvBw3+byunkdxViWBsx6TQTorv78OjdRbKcZY5RmgcEvYYz0b67RwcpiiW2SmE4bJPDZ0ZGDHB1ykLjt2aAThyJbTfkunafX172vYCMXhQGlZRaVaBES1sNw7qPDMKTaIxDL2Egv5z54QIX73xu5YtiPknx/yXWOKSzjwkpTJCabIhQL9juVCPAA6RvJQEhWVcaN8pqll9zfgXXvhWfGdKMMT/Ty543TeFMoFqPdHbHJi8PYlxG5oLCPzdkxY8aM6SJemWKdHJTfD4IF1V01AVvP3cywKFlNOtg1+gaGfTdbH8A2byHUmqkt8M05R0Maw+hlfMDMKJ9jVJ9dyGPV+RaymYyRUCfGNTEbL1KQxoyYsXERbZQsXy3d800JOUDMiL/0kZZhb4yuYl+U8klpOBl0CyH6NRdkpxPyOOpiKMsJC9xsJqjra5xXvlGcj/sPL49V7AxlDLEVTOW7Ovenp1qzX80DXmdJVr5Vyyd9XjBGx6DGpHNstrrZGAfg/qmP9dIikQ527Mz2X5X3R/NlqOutXTyrMW8WRXBEKl5t+ndlkCymh/F7GrviTDb+td6WhY+seIg8YqjqvH47RWEX0zUniH9dLaGYbJbLSMwDhsdKaRPWfHFoGufP98DUqVlaKdXGJjPmhWBHjFFHX6zHqf0oWYjqllz77o9MeMqPyFuA46IXdexFTiRborgZDLT6aC2Yyl1cnUKdQY8bSsgnesGWE9l5kDnRyP7oIHwlPcMBVxHFPHF7ToNlRrZPF/rTiX6tB73v5OOIfcn18tldhHAA4sw6aueLTZW6cXy0mdloW99WJ+lT0JWheZwlfWtTu+uH819ZJwPbJUUBKpBQnf1TGRanfy2F6XDI1NSgSzUWiJAIGesvzHWakO+1Wq+EMDq9DP04Cc9kPpGVYIUpn1kc1tsJeUznZE49v7PmF6yhGxaHewbB1RPhhbTR7tgujSR/5JgMDF1oyQGDpU8+BdcD06YiRcdDyBP4ViReXvS/ToD/QOD9LtmvmxLHqtFFqoyFYrDiSiEsKY1JmopUtwsfjZlxbj1VTNl/BYJYwo+9KtWWIvx0TuVzzfj/5gugem2VquT10c3l9BPxWem/Q4fzxfzUhhF7C5Y8ffBwi8KgMnIh2xOBxRD6If6LnhbGikpUcwujYljEEcLDK/WKogcgXvShuke2gYJiYupHiuEbOOkN9a+iKNO/kwZghg8ke+ejWL/1+dlsaF5UPZPWHpG9FFA1ck/4FKWVGZ8GhaxoOwNifsBL1wDHYCwm246U05xLv4akPcQlOebgb3ZrKrawK5ag/NTSo/JVLJRW6Ff/NOOKfa4Z9KEGIi6gIn7qc5CImKWlN4e1NIfg6oUGsqdq19cYl8HmwuwYxl/aNkkWUbaiQmiIWw54n1BKqoSGgv9aAnrpERH8VtV80xbAfoV4hCyyeWjvT6d5PAlm0xX+ZT5PbMxnHaj14Cpws9Laj8rM3Q++XHk/bPYdITsDqrDkJqOcq7AeBGMCUlhLghCTg4yGHUQqd4ucGHjBxl3bxKG6QoETc1WdtovEFvkX10imThvQ/BdbGRILxXy5+OGhKWmsTly6ebpp2gNllDA6ETBViXe/FcPJdoOK8JLLvL9mM5qb+pDE9ww3bwovUj95eO8m3LsoDw1wv2nb0I5+Lv05MAkuvxWRVWqb+z+EId8TMOww4PIpK0B+/poiRHmnHLGaJn2nzwVlcdoNkMUX17poL6lZViKp3uIlqx+d7qCqWWKyeW18gtj8WsSDtdSnM1wnRYpeRg4LeSkx9MWG5v5YK3QipSqwVv2EQX/W0ybAk1rHxEnpvjSPBlHG1KJ0m1nV1oqJ2MOaa+a2+bBoCMX2ZoV7jwqKO5CcrXzPXRfY3+HlxdFkXmYt5KE3D45VlB2DqXsfpRCt3dTlRZBT9kLcJHP/fs+8vLWy8X4AWVIPbO7QHlb46ajPHMCaeOqlUD1w76Oqz1awjbm6+sKz30oeGa3xaWooUE24LvIC7Bi18RqCcYd07abLRqbvu0vts5zeiH6ieYdDz/BvFs/IlNM8yAdjftlI3wH7+OMOiB57H8hlSX5Ps3OmVrhemz5X17efMyrRFFBMF8dFteWhvDZxI5OLqxcOZwRiumVs50UzyTnK9D+41WrD5mHB0g0ilGpwn+i0diOcqkXAnRy01knRPxZLZfKxB74S/te74yjPaDsJQ/QOPj+JcFsk44DDODkVHywiepuLvbq8JGIT2Z3ThNxZuYjz7SjlAZW008NAkdW5J9WzN9wQzCAuPwODmMCCvcpKOHl+hXMzV6DegYL8l6OOSYTli8yTV2NgLPzc4acVXtPfzeTzKZk3zVxPvdZpAxWZgCU7utaqYLPx35bzK59DANlFNJGSXadjvqWRpiTDlFb5ZvXPPqamJ+hlHZ1ln9W/qB9lVpgFVRoJctutVhZ1ci4WO5W+VTPhwH8ROzzpKi71IqOmvntr5b3NT1Fqp/vHTQgmes033W3WeTGOoT1x4d/LIOBNpFUd9KNyys1l8+JC2pz1s+thrKDQXNnuZ6tOmLCDm6MkPyJdyKYZZQUqr3LmxT3jbB+xdq64ORQlePLz2wjQs3Can3+PT1al01+nOiP+8d1/GhNOfF0Vmzo/bZhXBf8qNcwClr4KvEDY1Lg7YXrqtajjjytcR6redMSigeOvXxOeefiTbH4MGxTQetPqRQYml11iays2GbxPf5FXOvfTx7J8QxoNcWdvuXzkEhwsLWI5AO6dVscUYYvPusaQPwyYqdQkcENZdRJUo2aS3Zg/iyfVPilfNpYinbr8b+CYS2Pg6rrcUCZdD9ILNTB60P0HRkcRYl//gxcOFEAZfFzSdNNBifIv80+VvxR+ZeWKaifk3Rs8FbYmSlXpBEmc8X9uRMqpl11LnfInOV+iF6BQzOh9T+zlTHY95XLIKryja5PlWLdouhVdsY0xs15c6h/MeuEJseM2zhA5Trk0nyYRrg++zlaF9UwEZB86mYMo0LC8Vx07OKyh7NOQb8zwdUSrFyzZFKOXj/3HYaD8VAxrE80G/9JGBAzLdXbVyxmfHdeaQsuQJ6L5McA53B2Q8acwCyrKcCfyuOGR2dLZJ3QrPLhwno/FTeoae/geaXlCGtm9AXWzATxSCZNcIq1FGG+gth7fN74IU5vTn3cGb/Td6wdjr+navnM6u3ep6M6eC1P73Q/tySoVrtuuc1tVPF8eVK2JLCxuIHX50fom2CHJZFZbXEHq+NS4mc885li/jguTXpnAmg9P/aBA7TL92xZHoQB3D2bf/IcR0sels5Uv9bJT0XcQUKvSTsf0N//LWI6Dy4nJ/13/Kwh/erwaGtM6c2OyDF1pw3y7pqEv+K8bMnDAkR+e3zwJ3V4j/En+77Hip8PXJbd7sKCqDPLfacs02KEjZacdZhHdnSsP10r8hmUyoJbadZ33LbOAh+NneyPdiQXw2aWzUepuvw/t5L6Ieb50J21DWCEtQphBSKiarMXjBPmKlsjkE6S6mKb8bT3ttPM+3NOHrjmJ0bj1fmv6PlkvL+xDvFZg/e66VMTHSpN/yyPi80VhpWQtVytzHCVJirXuut142jrtlwLE60PaDoHDd9DJZRixvTWDud7GboFqrafigSPM2P2s6By2LrQ+a0MNHBtNzFPp/Inl4aMMsBnXnw9GbQalAfT9u+rFHGW1lau09/fU04x2oDdEIgu15OfL2nThQvxGPR5hQp3rspONJPWklEaq9mL0krMGhdWucaoqitL9CiNieciPz87vi2BymeX+b9Sh8cDln4npXeYr/gd2VL50zZMxX6LHjzXZq41HyJxns6fOXtu3uMbgvo3iEaUi9gB9crZvNBfyhWH+BeeZztVnZ1rcsnP2YBEEM3o32XL6Ch4upiokowPgn18PKSpkvN3wdCFtfZ8Z18+JQn86Uklf2CSqB+ccPjeJBXPUpLA9WIM0G3YK3abq58qPkgHrJMFdU9TdzXsyTdMwaPt6u6OTr0Bp2py02fRWUWG4ml5ZkRDJ8/Y5c9OXu7wrRGMR1MWLe+rvZvlEMRwzAZOPC915dmFXnX5nNf5aLViZlAYAHwtElWH5jq3gT6Bvl3LtvBE2rqzJWPkJxdTRkR9pF3a2YoeYgMZQ25If7lq73bdsCSnp5X86X+3NQ1SOelZeG2SiwITKbCttqL/jRnVv6w50ffkvTn2HO/tLMbZRuDg7LnnZUddu6bBy5W4bi3ancX8ac6/Noj76ef/OG9Qbsu892+jX7mw1XxtkD/0k88ODrMzm1NzZfYJn2zY5y7bxJYkKmQuZ7bJf2yJX08W1vhm2O0RXVdjidxW+JL/8ZY6XpMCr3/aRdB6BanhyI0Lso6fnnrgthq/oBV1dtumS+5vHOjRsYJFA3iLpV3HvZiNHRwpdCfA6s6QLid1gM9WUKmOhDpm3dTkIx4yPHgucuMHi1pPxxLrRFXTWT5Wi4iGZm7INax9q5YbYtHhXw9Pw0ybH5ZKbrVSnnkMRd392wIFmejAHMRtdnMHGsPUNznGwXIBB6knVPfmjD8LnvcEehUTcJ/uClOsVhGq2dBhDYihqbyfWBOZp8yAhg12v/eK3AMMAMLPsKnbUEIyDxARh7hj4a1w/QoQ7N0ys3/vEDcW4hxBLh57fVN+tEmo/lvLivU4DVCkWnDV2QiOz1ZChDwhLQnOeGGmJlPCYe19wdGXNL0AwWaxhVB14MyKVIKoXCQorJw41LzFWrjpx7oPNyyh09cwP4HR49+eji2SMFbEgTl2qZ1m8+OzX2xladmVhCLC8kw8rDh7xgef2F3S2AFadoR5JuIbXJVBU7WdQX1NpgUfSMD6+amAU5fRoH/hJLS/2Pgcl6Mvla1aoZCvE/Cja44uwDSGZVYkTfRpi3/eWp/5VfXSxd9W17OxtdVnKkzlgm373meDzx7qSuGydyawo4N649flLZaFs3kVokczHI+sDZqqLw9Jfy9H4RTeR4zCvhZpj6F7jI5cMCRYXQvPrJCaNfIxzv8q3Fbs/hZcOKPwIsQ5rMWN/8siv/UuKl3hYd2l3+7XChtTS2exT0oNE5KxxPnkTCs+ttDO9ZmrgbAsfuP9bXUwgfZnTpn0vfGaMgjBXoLq+4zwboZycOsoVtzK3nsMCXfhGnwA4+7Du0N1i2JiREMSfYjLz58+0Detq0y6biY679W+rDDUXjr9QxdNI1TbTYqKAGL5gY1eI+BOB+JTOgX0pipOZ5CM+n5lWqnSLNsMZKQhpMb/y+pl4gV1HIWwdnAxWX0Jpa9UYCNhA/Vs/auEXjWutNHDcN7HhrxViNioO5DV85r4ueSpF6OV8XeQpUESYlm6MGXx20dfX8y7jkj/1xNe8DVUnu1gPY0zDTj86rRI7GUXlJc0Bu24+bHxKurRkLTTCxOH36C1ja7CXXyW4nZ+tR/LhlK1KDlGAuBZxdYSmCJnrZk4wKjTmQKCnn5YjhNVaqeM6fCbxLi0uGULwbImfhflGJqJNMaaOltOq2Pn5thF6Fymb4hRp9H5bKM2VBtI8Zuzsg4B/u4JWzxtNkuWb/3BagvcHrpH8/IjWG+y90qCLD83ucCnrrNiPvV8nXGapnIGh20YttxPPUJMHPIzLbCUuX5Dka6u+k8T2SNbZbLZifHkq2T1l0H3eYbHkm3QzV1Jr8FCTEp/ApEFpxRAabYxyB1Ba+VXopsFK7QsRpS8I++QGAhL2UOA/UJex30iq6MuNwu3g3g93KIlasmPjHv2Q1/jcG2nuPCXuvn7JPnWghzLkp6HfsKTJNBAG8bKKsac4i08tgCawQwIOcV1bJnkZOtRHUZX5AZ8nBNprI3eHcy8GzzWQ74gzzSuxjd65EyInmFbZu/gMf6WLGhuXvN/JZiW6q14/G/HKlt2lgOkSt7CzevnaKGY0IDkgxev1h/ZwSeUTqUOyGCCY6Qd+W3I1zQlZxyjw/1Ml/33DDgW5WzKhkPB9irQxbuwt0znlpuRmimyVlc+bP2XpDotOUQn5vScd+u/XSbHHTpCJX19ObCLi3VL6tFV8fcnYG/9MBcppDoBLa5/5Ch4tYK4UzgOWrRVR8rw8du+G1qXtQcykflbO241eNyoKK8GKnh162PiHy0MU+CVBpZknDn89biZctVuRoscTuhMjJrqKPtLDy6Rl2Tz6a7ROc/r9YyxdUrFBId5hp3qbqtlLg2MvOURADPqsdIbWM3JmXgmAs82xp1sLtwrjXEE+0GzuSd+WpUwFJJEewpaPiOZJBo7RpS+o2w6XYZl0eQc9L/b/WaRUJ20CMgV3Z8y6bsXM1rb3zcxK4HJmATYgFS+C89xVCYtnhzF4Gq9N0GS6ByNdOOwkAXIGohnt4vZELGMHVXhkrkQaOViDqB7o7lo5bu5yOdFoE4osKGFcPguxAOuSY5lO1j8GfaFQMaZAzzHixijLMRLUtWyxLS2ren5Lr5kSAXB+xTuRPqBVlqGFmhQzgCaIyDg573nxE1rXAXZvHC/5l9kiX5BXIiNZRHmFRNBLTFLZJmIiV5lpXNpS09S87/BcP/9qb+NNjCVbXcuHT9kiYqK6tBwWh/X695nx7mXDXCntzdh8osoiadsGGd/i6fiHjhquzDJNuceoo82vi82mOw08bOUfyG++nSIgAi47tEkAzwgr3i0ZXeh1ttiFNtfJdhftCyMd6sgIle3kfvkO+hqJFvxurruKMjd0IQ+ebeQgLOZfN8pP/0a93up5XiTfUe4+fj5S3Uut+Sd8mt7pQfJ7VK9ASod5y8eWxZE0n1kOKCBpSJ31wx2ZadNyAlmfPS0PloZ7ton/MmpYZAweltXGHR7PruV3xMLf71ehmU6Up1RVFFXIlYRJ3BUZFqtB3j6FWokEoeXJxcr78I6nleoKHbrsjAXCdHhV38g8BE7he6NWTLedhaPioI5efZYHy6ByIHrS8w86vZLUmdlBErwXyv9oe+FKcJx48SNe+0o/kZAlB5Zq81/rRS87YdGlnDV7o5W36K1P8iuAir4qHvgoq5VPy4eOT0RQQMcJY4dEAwfy+tyjbnSXC+9ieGHg+VF6bbTShTzBwtJZHRuTU6iOQEFvxbW17gEzZ7TC+xiMjVQPUv9vW20phDRTgl8voAS9Pnq9sHk42KjTA7lO6rk/B1x48dSZ8hv+Wva4ioONWIQ6uyaVUnNPDN+u1+UZX8SUqv+FL/q/Qo4d2XAhQhLPIuR7b0MW7wB+0MaidMOLe9rQXKPPjrVEMaW55zvTZIusLuPh9mxTI6qVPtImYZkFScGfeBTOArF/eoHlMyyeKRFVcoeUsueG+8atyoYAdG8Pr9V66FD5bcpcBMAl6ZQzk5upVTLD11Gqo9Zq4Q+2eSQbc6GuAl73CGu+u/k9gsh/UtoF/X/ja4M3LuPSlvfkfxkhLipa2L8qkcP6yNIkzXAFAmyx8iw/vrw2xCPpX92s1P2VgZFf0qDI5Hl6Cv06LTPdJ4yrk/tz+sSuBzntqIP7ED8VU9sceFdL+DU1OfkMt42cuVqG3IstNX1PALcYLmRlUL884dtSjCBbGwf+GA5mG4Oybwr/gohQ5otNuyGB37JaYK7FlkcpxrFg+OICx6j/knM82rhmQddVYrrh5S5tL2ctqmWaPXJIbr3bPLfaHA1GqgYUwejREzqMmQQ5Tnjic/sOwmXyiveBC5J4rcOE5u6EFX2fLzhU9kevDacFMSpGN+9e3k+foZXh4dhmdbaT6aIwaxj3uGTdUUXJyLc94TZK9Z4r8GWA9h2HxDT7ayaJ+LnTkHgzHCgrzNys5E62bSN4CBJXcQcSm918bPX/MB3KUrQ7o5GHARaeSVC6iXdJB9ED9Moz1x4D2YUpFd54ED3ya4Nw71wUTaMsqrTmejp8nAAf/17JrojzpFwHxqvPI6HdWc/RJxTbC1HKGGx7IzKiPOjLzUusdXG0ZAv/0zZRltvBvQjs/p9k3T7H2Ix61QG4ZZnb5DzfbNrFfCXJS9r+Md9oQcTxFaRMibsw57Eu3u2fioCuZEEWZs7D4+lCsnQP1WZu4hzWOIAMJrqPt6cUoX2EqklpXLr1aw0tdjOlb1HMAJ6b57VthA8Hegafw+7of8B4uxXeRFlj699Sej9omthxZePe6JX1W301p3VZ61N/Qo2YY1+/pfU0CbwB4I5FV/wKh0WSBMiXXDlu2ODIFV2DjvVIdo5BHueuCeyqLoI+QpnIbM0xDmiZ6dPkmUYwNb71cIPWagHYLkwfjf7E0JqOECswLIpluPhIXNwdjuiiq72tbtub9WPRZe0i4+PiwFSsqVBCWQ/umBYkvujukb6VFdEg8YB/0lOB1proUs4zPUZ5Sg2LWScJr0t4TPKNgLgtLrz2dcBvmT9tbddtCPci6NeZatjGiMoH2g0GhqmOOP5HXaIhyuz79ZYtsTWlFmMeW2MUqGOCu0eF/2LfGLz3qmg78x1j7TqqQvZsx3eASVjN453hsHYdg2EhEZluBB6Ehgxo/LfPwIjuMh5lg9/yYSbkn+OY2PmMPwcA+7ggfE0XKidBU5LRl5jrCfkmjjy++jhOY+0mlxFYUZNuA+5cFVvQcav7V6ESoFGCNYw2xNIBRJBFoSs6SBUpe03dlU7tSFTCLanSrfAXT/RXdSX0D/0mjJIrfw7yvFfz/GJzILTR4ZsjjkqcYr3ifL8LuF1MOjUU6JstlQqcjABeiLXkz2Qw7gtB4I7pwgTrMvh1StleWNPN1IHiPUCpo2EpekLiDYk0kCUQLcRC4c4xX/eHJSiTorOhlTZCHrQSKw2YWvGlUVYO78rRXasEEdPMQUl9rwe3wzSmIUatRcYVpcPGUybWH6tqCw4/AsE4MXqOb+iMU0OqMDmInQRZFjBx0QEnOGE5M5aflqWkN5lj6ti0+ldJ1bCdwBGPRo2YD7iydxry9JZfjAxO84YAlMC0QwlsLHikjWiLrH6IIwpZrWy4ce6N4+Tld8IZPgY1VXUVbfGPjKcbGHprs8f9X4weKDPD5yA3bfDA5WL7ybO95iTUf9H7YoIUbURO8cdAxTfUeddgncggLjCkNcd/hWfS6Gko1DpQfy4rq9XmC5qa9ZsE5+afHPdtUDxZuv6KkO6l7EBnqkaDv6+wMumzPYS04kXRGG1ERWR90oL4X60mDCrLYAAMd6WAYaU1S4M8h/U3goY9T+NtdxUmxcmhNST4ZQMpQyYS9t9sEw8jqpDAobwlrSB6qNFFeiwuTEo0uBHAf0c22EJ98Ia5nOH6ouxWywAWsXjZ96YRgEdLU7s/ySU9xZv97NeND6vzSN2ogJgmF4N6fzARzzyj4gVEgVHJFuvkvfJWQhRNuavdfbnDe94oaiPFsYZ4wbzWiiRkh1qCem1MzxVbSrMpmztgDxINYjjufcHV6NO9erF9viTZg8iaHgE2rctJ2+valrbtVfN9XPdBebn0nlT0pMVfkExnRiSmMiafOVyVI6pqDKUPnWNMV099W1+4jop3IM03wqifyHU4St+KzMOkK3OqHq1HdBKHbqzqzyoD1FB3cLk7NPIPFp9Ez7scUF6mBCYb/NjR6u4pyJ0ovyWKPS7GfpQKnFqC/WkHF7Nit+AzNT9uPevTRYR/q5VhcNlopXf0nI9ppdBFRnQpWH9kV8uHx/LtIYoSzxvy9f4nejgmw3/+ogz8gta59lbdeTC12XTWoxlaMGXSxkkZpvv874vOxOfwMOzC2ZSCcCb26IfZ1Wxe40K1nZhEm2/njCC2IoKWd1cmX3zXX4P6XhoNBKd/Wr11efzK2u9DvslFzVVsQYvpXk9I6jFU5/5YczG2j//EBFFSzHNveav76CBGmyxpxjd5yA5VunLxJ7EvgpPiLoEZ/2gTxmmAj94jXDtcA0YrS830VwP8aF2H7LPD5bSOgO7KqXtgGsaqMa7/Y7c5Fw4a4yrMpYoh12R21nyKe/8q5Rd9N3KejEaDUqFZDil4RIdd5ugAe6Oc8OlO+wAklwbtDS6bmV18N/4qe1ZkoFsk+Z+YPXX0jwoHHzrouWShO+MBO0Zr7tl392De1l1L515Dyo+507dKf5s6WvMGNiU2zeIC0E7JLQWWa/6PW6/5oNZ8ugF8zaC0sGLuMYjkp6yBRwxenNm0coWicyafMNDT+lIpzUL75OApy1x9PDaLyJqsTqHI2VJpKhdRRIwr47Or38/hJg0vUtYex9wVtAk+wy7YeWKNC5iGXZ2BnOZfo3RKVCWL5ONi8m47gDVGYz4mLCyrsdTL/WFG19O1odUIrEbSu+G2TP7Gawjrdm8Acp0N8b/Tb3veu6IgYzk+uVsBKigIxf/FDn0129oy/p2uRM6Ali19t6vETcQ7NC/qFop9tQ6Dm08+WbVvtjBrx9e7iuIHLjNx3SxZzluypUrpsooLOrWY1WvZze6LeSKVDIIEWauwvwYaDHT+CqlPBPGuFi3kC2SCYi94B2iIIUkzAs4+XXr9DfZL8O59Lr2aFpZpttkMBS1FZtVijKW4nCDJQVjEi4eX+IbEf9hg5NJpFT2vEC7Mk5WlGb7roDrp9BgrC5bZ2pbptFsf7+fBCbcdEe5esnYORCcWFjDPGyhCBkVK5VdfeBmevB6ZPqPI9W4xm9SSnozwBUPpJ8O4LccUNSFSZhnqR4xLxiZvZqBJ470qDm9Ph4jyNwWcwyBRW4Yj1/x5b6JWlcw3m+ObqbDTy9A6fXgypil3IF/NAGqdkoSvAP3+BZOwKz7xHvMrut3U7cBYUxA6mvzhInWQ1QoTIsMX5mOFYFDRvo9Kzmlb6DFw5/PQLo+oyBhe+sd4gJlx82DdLhMdC1FMl8JCK8Sg3C538mvTdFYHhnUL/JHqWI4rDCyEpCKjyWqxFTTi3U0cr6VjtH1fXL6F7tPD/uU8mrCf3YSdKwK674psGjUOXx0a8LFdngraRg9ZbpJQkdqw3nc8t9nzSvb0lXgLRyIfGMfzVzvEZhe0HypPMm0QSxWRgjwt8yg06ITM6Fx2/Whjl3WoLtgQGK0f/O5J+aVXJrOfArcijhbhX15hZvaqVVzKCN+o6ODMsPZcyUmTv3FxdEuWyt8iWibplBv5tjpf6n7+UIPpcTEjGFdw/gk5wbgMlOLBg1r63uTCmJnqMlF52zjE3AP8BCJfXuhJ5i+5XJOpXimBCn0AoTlhpvF+aLtvs35m8dwcLp2kau2DNDNEM51QOVFGrL9Z4aOQZfLLQLBrtycoABrd282lGW0wXaJ/qFohZ304Xci0sBzI/WUtbfNvFfN/Cg1mSd7OHFsE1V+DRt668hJEmJGOwklo4NdxbpI57gVemI1F7O4XszXOieOtPBXViswVUxDnCfb2kYmjYY6aDjf+6Z2CAKYEKavc8nELA//8EjGIUzsFpCFqjx+Sms0qk8jY2vD6rIAysiWYRZDWkgjGPqaTvfLYNhrR/KBTIv7bnUFYT5uK79O0ZGxLDMsx2aQPM3qit0u4WycmOoS6hGwybCl3hpp/Rtak0057Bpi6f8FKhqdeKJda6foEc/HX8UGWGSqkpRG15SzC5ztaXqun/IJORjKEhX0cZXKBTDrT0DKpYhLgSG8uX8wCjg0pFixUhel+Rc4Qbtnn3lGuEovNTqpmBIVFl1Mv6qs879zNs+So3lT0j10xPSqXdgEaJ8bEyQpoKowo51GF57y5JSvJSuXkiC8Zae3upyKGpu2lR6TjS3sL01CzfjybZ9YgTIATWrwOgbANCKeXVyZnXn7uNU0GwXu361oQLefgs38prHX+6orM2F86z2wklaVWo0mN2T9JTFSTUs4HdUAnXqb61WFm2SBG7qvLkiTPyIImBH9m7v6P72jHFy511yygxGjjkOJXfjjN9ITsmVJXYYuCJkkPudtydB/fixoD/sDtQFb4RhLfVizlxWZtsTneo1gxvUj0/GhmcrkVdiAY953XpomA5MRICKLw/aJgN3kpu1la3Re9c/YgRmem/5FAaSQsSimpOLxhVeRwry0zbHqvfnIamd1jOvyOI1jH270RR2hywPLrw/bM/SvkDFjQSFSdL+zxsTf54P9U6PyddbJEp3m472Wkvr/mr6QOdmdlp9Hwiqws/5m5p5j6ZlR3E72bRJy4O0oI8HmDKR5Agqc2mqkv/pt5HOg/LfJPEjlFplXPgo5UcK9KBv8pEyyvOw4TI+6L6cQIvuUZSN5fIElECO9J1/GnaBcJ/Es54JL2wvJJfjYFq1AVLy8R7HH+fTT0Kg2oVvQeertJT4rJpWSfjRc+BiDxYXC19EhAD4DBuenYZC5y35/XZjdU3vdz7oSz6LPmNTCaPJd7SjJfgh/QDCBuNQp/yjm/95NVwpfrQ2bGv+Rr1K5YtJNbqr+AT0jjGZ1CzUWdeootubaSFF9cdfqscS3aalKgmt9duYSX7zNLE7E16wcM6A3Jik74Px/h5ijQxmerwAMIG9J9/Of8bpAE/ZRyIUw1RYc2I6ZHfmPHML60hG0vsr7E3LofioGuIKTqSAnxxI/Tx0Itu52OMes8mANr7meL5kDnGv14GxSYTqEZWQ7PXGyQRBx4xiQt4q+PLTFoksT915s4Ix8sfrnyG3E201lX7QH4VFgpViDZXgoR0vrkwEHMnlLi+sPcHvALxlPoxqRfb8ix9RB7pirlKidGAsI9nc9N6xat010dk+ID9r9Tb0NMYZhecs58c+csWVKv2ye8/u4X45/nq8SgZMKisTT+gQrxHHYAJ0Fe76vpzEAUAzEyPRzIRtElig6Vir0d2xC9kmBcimefC2ZIrY243HdVuLtQhbqK7lXAYZ7yxCh+vel2OpSv29MrUQdTS/8BPeqU4My4d0vIx6Ij6w+AphEubfEfAwBcsmm2bBhreQiF1kVLMUcVsGf1s/NqQyeTh1cjswif3t2ap+PLEjnT+ba62xLvyBBZ3SH5cT1Vx5ari3/OcHVLvV6JMPF39vR636drFyp8aWKF4YMuzQpv3ZiGP6q5KyWN2mej04ogahVq2vrLLZ3ZRdleN+8nG0hh/i0KnnU0Q9RUVycL599wXIkQH3Dk6+6MA/bdYFqH+sz0Y9624HC2o7UecVkdMK5SZ+MmAx5lA9mWNpgLV/Jg72pn40wfJYUfBW12vS1TgoiASIiA6WOMMsykn7uxB75RiGqWs/03d2vgfZFgxmxzDqOH96FriBvQlIfaNHDRnroTSCfhJ+u3glx4NJPcuGaC9joWEoxhi7dAojNGUqKN7a+U8D5jCh5PYrkd9DyNFKPSS8qv9hNunBRqW5xphrYR3YlZzuBjVi/oEKjI7+4o4S1TGYx9EXfllI28x3UPvVkjMPxB4mXFSwaJz37ny7J6Y41zRad0SZWdefp5aDIZHa+ry7Ww7+1Lw01WFrhbxjqaeMCuLrcFlg7nA/IeTjPa93+cGelBnZuxodomhXtQ1bRxHUAeEUQYTVM1xn7k9gum0PbVNGmX5QN+MabbY3SXZswKAOFbPXk1mVAIaqnqFtlkP5eeblrJCWmRGxh7iJRm5CLIlbCPs+FV/SZfDNGOEWjQwigyk4AJm94c9uAG/ZthKulMQiKgfijldQ8x9KhL3HRyGJZaMW4l/Ibs9BtF5UwK/hd9Tw/hvVm/vgecFFB928UQdl1U/zqfbgavpy5A5iZ0nOz/HFxoMu9AptP7/dOfxlIOlNN+9qk0YrSlUo3HnbhdB8YW7tBdJ4mb/Dh0O9Pg+LoWUHpTfnkTcywPakCXcIeL4tUXv23UMgjKOdnypT7i+DKYyV7abRLO+X4GPNaFxGCt059OzCHSqbzxv7WABM8gZg5q2BcZnTiW8ttEsRpoSjoDX66ojpubeZMxbkAfOIYmKSaRfhotR+XRci5z56+YFM523NqwUNKCXD9gWRbzfoMyMkaKbu1Z4OP/yGVxsZP/CAtqkP2lLVFpg/CuVEhKuZ+X9qgXGK6ruHxKNtM2YfpVRQX1/DG16B9vBIrjlEhNng/a+Knkaa96Fssb+NHLz3QL5kP9oKLzOsXmJkvk4VJ3i7B7Ows9oRt9maR/pDk7o5yXUfyvtCRky7IEdJjtooiPl/5TK4VpAddHNtdz44M0FHUe1oq07sijxNoHVAoq0DgSkOG/zjkRbcyDBXYCMaHmZEIpCMSnw4FfyPi1O+2Wibr12m0w+WR4jT7co/vLgTmzuxCfYvLKxFzmljgIZWuAZ9LFW5Jpkh/nONJY1Jx+uZMNrCr3TfssyISWevdsvmHW6J2kON5iVnhTqRnPvBoMtJKYrIfpdXMd6d5D1Mg2zv3CHOB0qVgXFmroYKm2X/eBvEUSHi97mL8SF1ivcOkbb/XalZbIWRitwZD1Dz/qguN/3/PtdI3hi90CoQxQ8ad7cCPwPZxTFNPzJ/ZjqZSlE5+ZIDreBD2WpGZt6UOw66AW0ApPOb0rQAeLb3wxHXjyBIN1sYGmKm2FQUR9IatejM2SoSF1eVyfFjrjRs1V4gBqMo2bF6yGXTeJtvfIwQxXmOy1JbtFOpdK6VOrGLQJD/I/xRS2dBjd/SsMtopn60oRwEmYYgI/ATG07EhaKgUE6h2qZQnF9r+ujWlUQdmRZ5ze3/ctRND6dcgOXY89TqLKVgSD1xnaIh2wcR6XT1aVuRcD5vndORhFvyWAazge0cX+N4MxlkQ3MfDgxYS7GiLpFJ8bf+hWrcvSFhOyvkxV80g5FWVN8MPD+2bzlVk/EgOQGfsDwlw/TrIGx5NWyhMiaIZMI5oJ4D9WL/0yfWwxRvZSRKz2k7l+0ZK6YjauRvrSTYpU1lc7VpTHzTf1Y5qQgQ3XN1Ju3ilkCvKTmUjkPtl4hf+fgv//C3x1B5bqRjxxUxYHg9yfpA6vO/wlUlLIgty0O2u1jKfSjakPFswrnbWdHEBzU4JvZbx+AK9Y1JNKVX35hMXHma84huQ/OZmlqe/K8JtLkViRTVur92rW8QSWJLR+Ud8+8sFaCeSNrT8xVMfOlR70qSc6BWXoNXujq2/GvkkZ5bNEF733jUgMnPZ+7Gzf1+rQz0/2oDrTcjSdzjUn3j8zxFrNL+Nvo7hIeau1DZIOTPe0ySZ6WCaOyckdTXb33a1eKNnU1RBsIC/nDLdRVKflxdY6R1/yJ8xDUeBj4lrtB7rtu/uv0ZatfOzl2BP+y7V+6vFUuB4lMcksWHwwJCl+NblOrU7ych2yPnJpn+jK/OsdrhO3girJk/DXW4HU/1EENYn+WGwbOpg9QDut0tD4P41mn/9ZTcD81B3XfqqLELP31j5fnjqTrU9J2FxgiTmf8vPxH9YJxv9bBj5m6Z0k5LG2QaP4T580usZjlhyvkcqwj69NiYg2L8XdhUSKC/G6WQgTc/cWl/v4YO+Z3Dr0jD589jjH3rUsKEV4YwmRDbXcTqugV4lVpKIQNAyWWU06RYCt5XZVYPSaXrwaGk5jwCuCTZ6Zy03i/teIKPTTyA8E+P4zljrBSi4x4Fa6tF9m/cS+DBbJesQI2vp8SYT6ZmMkn9oYV/G4Cgl5wWdQCi/R1pl6/Rq/OegFzwAoUyXyd68dOut0YdfU0Rk6p4CfTqvfxpM4rCqoHaUQx7L2lYi+LyXk5loxVlD0ozlPywn1db4LwqteuWZDgk8dk1WqDFlio9ba2PFN9KKSQcu3I6toyz9ET+VokDXw8cIA9bjXmP6FjqpsCzPTLq+qPh51kt8uSHaCRTJ7rCyHpT5yA7PiZu/6XaHVIlwFcxlRV5a8V6dTAOM1pkZCb9R7iKWXTTlfk7O4FWYO+vjacKhAnnvThdgO2u0J77S+u5KoL49ROi4zC9vGN7Nu9zz4WphrW3ULbeoSYWslK1BnZZLc9Ywe8/La2g6/UdzuUnEVuwTZG1t6kB5uXPnc07OhhfaVsvCevHJGn4C22F7mpu+6N1YRsH6+KG3shakBWzXqGlTVU/ziS64WoSq9nU4FdgpbYWcaxMY5+y0UXZS0fvUuoJhcHVjkwJJZbs9VJN6P7/++0OsxEfGD6gMkaDADNSfENRwNph1Yy27lXHUafKdAVHyk+01TSXbXRjxlij+D5BPj3i941qkshe74vseQjsxZMND9jLBEHlu9tiXDw1cOJRo8xVoZQ+wTPS8H1t84QkHYEd/jPb4BCg6UQgapT1fdxIgiyW32lt3lUWon10ot4V+87ECv3jYTmQZBTuvgvJ0IBKv/qwN1OLg0sBzKegEdZs0DjdKoqfQbrdH/rw9gLIZG67AA3Tjdk0zXFfceSPpXQhAM4Pibb3D4mcrmtKM+H4D5huXZ38m/4ib7102e5arBbz23ICd2Tp8hjEI6DgtPOEn8U7qhx52tf1qTUe6vMOWBui4KfmS7zip5BZ4ml6xjw3IJcJeTyrquuufhVZoOcT/iY3yXuWewJYh6CRK9+YjHfRuwD5Dl6fH9hzKoLcIJ0TWUZ1EWtNcX6ACV/J6jmjkuRCEsOpPqZwzMtU3E9j4VckXSQ4sgrqFtImfylXoPJkiuxEzOOvvvYlIe7yr6hvfdmCLhhArwppSD/1iKhzbJIXvBgHLuoWLf8/BaMNfhwS08R3FyWQZFji2hzhHuDK7LK3PA+Qzy/6RdiQ/DhJSuZWck/depG53YRvIUn57wBDSWg8J5T/H4+vVL04vQf7gHFyxl973Fz7TYKbDWHOGJSHb5Xplm+5RKmKDrWigfxBcXDR7fpMCS+yUZ8m/7dDUqmt/crWbHBvzfLF3wDA7GL/rRmSHEvK5ZlB/vqSZeunbPaTzTVr8Chk2sa7RryiCol1ul6G50R8TDmWFtqfy5s27Va5dBmlFjCnAxaa7JcfXzcfnohGoH88votbKFWXTydvWZ8JMfK2tBKQa/tdu+bzymIsiT2MKw0I5sHDDpwCk3Z01sA0RWw+vLHtZr/OuszzjZl4Nr6yjA/UHDihmPX38gdkFkdfabLpSSVxR5ipuMD8CeUA+5rt/Xpz05NpVNchh/OBRxQ+A010h+vMvMgmBF9yCEq07f7yeSI5H8GIyL7Hx3bEVuem56DTgwacirOD/PwVKYTny/9/ujXrFePeVrCmgTKBE6/gCwKR6v2j0fQjNNZXGVagNLv+Va4Lhl6XckkdbVbsc6949fES/SuMtUvkvn75kTshtdYB8+5HT7DfP+8wbq/e6IT06ilf4tJYdxb1s3f3Gu8QYVEWEP6MJWA9mZ8LJUjtny9tPfOrc7rKb5NB+87xD7rTPKaiDLYqVKPQ1dXd+cs49kBgdubFLonyRMYmjlnVq1K864lP+wQNwoo0Nb2C3qfHYll9mg1ToCwBwOLF7Fj0LjZfAQ/x9IwdHLkxrXe3sDVioSWO4pvBtVpO54MreAqWd9Ec+8nFqJqGoemjlj+3y+KmASf04rxoDLZ6BaAuFMGpv+VoBdpZ1wnuPKsLjpjTCbXUe/PB9OgbGprMv4IQDnDjf6HeI4+vZpKd9aLNaGb6SSX+ZB7S5+Bl5eghgmaChiSrenCEM7TL8Gtyr6akhQ/t/GEuOXSV4b1VueDxbpkSlcxJqWVrcsMOjuZGn/S4wcOcEJM7vrP0T5LjOtxoYMK0YfrmY3P2KugUNyAg5tLnkznc/q9h7Lm0nFztf7A9lhSwjKuOV4WOsN+CDg+54P1/Whn4gSJD18PqfF7ZkSLz77YjUcRP8jbXlUK7z8z0s/ox0KTxlrvxFZG9drmAL69Q8JduujLsv7f7dTmQCwQCDN0x4zwxtZN+MUtOAirsH8FQEk4XEoFRouSLIw2NhzY58xel4Mcdj2qXv/638T26Ne2eqhEQ+AaXGF9Emlq1P43tTxFEOeF5iIIj+YfdyJ86rV+dPpcGLxeyvNhWayaBwbFkyKgxLSgmwVY2X7TQwTZf/VLxNfcfVcStl8zz8kA6GOjWkiFC9srkOOL3zKpIrPeZQ4nOSQ1h24hvXKOwvbdzHl/QL328DEwDRnzRqda279NK1lNHpeWhv9YND+CZqbTJIa0VzKMFAWyWYBWq+625dMwoPwNZlBe+dCmdfptp9gHCBWT1PkNW2kfUj0gLRsANb7rR5lSRw1dPB3Yc5PDjnhTEMMilH5xwdOMrgUBVybUoFChzbpWUuKVtJ5PyfBbZLaD86c7eBuGPl1kduysltrv7TC9TFw8x6ExPTur6whHZ2QP1VpvzNnkYVH7aDUpenC/rUYApLqLqhxDu7LMA8i59LRtK36MG+8XU1nOckXduS6RFDV9lyDc7F5QmILTmKzSltbaMvBnRtJQq8696cDpf0tG/8AiiI+cnAv+YDRZpD/i2QRVzDPmxWXQyj6qkFldqzMvHNvW5mnsSxSwoNMiVx6TxRCWOb4MjJyoNxtgxyfMBtiXHrc2P9fQI8R7W8JExWkkLvFpx5HYzzEsozHocN7irpAiug4He4Nq1ZTY+WgmyLcYb2EmAo9oy3i5AO9hNpxlbyltCmOcPSY3bpz/sR5gSMKSTq0xOuuhBuHaJsobczuLMPnEBdyzZgo8ptVzyt/YSlat9BZmyrZtvMCsjU6PQPvfw+l7KNXO7m6MgdDv2LWM303X89UlImUvtblIOYN0mOLU2wS2h/D4/oT5vGU3yFymPfSUY3m5ovVBcj87FyUOdQMk58lpfxRYbX/jGZmw3nch3ekOd+kffgi+HAyCLjnOEDSiKQ4xbp7U8yZ5usMvHE6YRhlPc/t0riL470FCJk7HskaMFjaluYmr3GB3i3cz18A8Fo5h3Fk7UQKcFeIzM3aL6A/HeZTdM96j3Q7eH1yG0yv6iKiOXosUWpXmM3wQCkcwCbai/IkVn8eWBXuvZYkzjfrcfACWxlqcglgmWrcekj2C6sn1PWSEZgr8WaR8nM27UU6/AQKNNF8+qglp3bKnjeXaBAfFJ5lxV5c/ziP7OxsjX13OUYgn2rJksjp+SuUbUqXoid/vDPI2vRzGOd4mhO62z4M9mNkpW0mHVxLkVp0k3iTBVr/zYEsgpkTC6xxupNXV79u941lRoBEzMP9EvtuKa2jDzxt00B5eUY2kIjoKYHETGhTfI62aURzlkBjZeppqKuQirIqpXGlj76bAaQ98L+j117bgLoeVbYWnHI3ChPBSZ938TbpjiSekb00LY6/mj7JqCSKwu9z2AHz08Lv3+dmP/pwflLgzEPbB25N1VmnwSTMLEu3Z4Pd7SKUJSvntV9ZHyM/XsLa8XQK69pxcXNiGa++XTrjJLgjirdVN5b87DYAK83aXNCqS1r6/dZ0q+lnH993KkBRga6/krxk5A1bS0eizPTnncFuK7l+BtwGWB6tog2H9V2qxjXNz3xlzvwb0t95ugXFkPzvd3sQA5v3EfPdk3VnrCRAaotJHQxegQFZMdrRQg3ghZ1My0uM04OcqnSwUr5eDTeTD+Tn71F2NgVlVaMuY/sG6EfUMtHDHeTuHosLLO9Nr+s042LIS+zM+Nyfc43VPSR+EGG+lEsP+S1yEoKXj3GEW2awCM2RNnn3SB1ZDPHxz48KKKUh+VhXjIhbkWAJKksWAbSbklpLhw275OCVK0F9aCaHnhAAqtMlpMVQd/iMVZm7uyZ6h48FC9TV7neWpOvZBjxtfQY0c06+NQl4uAncxwjXSYkxSuiX1ZyHd03zbeiXHFVodeCCxiRNRB0ACs6UhfpMCBfibzceStaEp9cMa0I2N7KH3tcFS7bupy0cmJUwHg3cnTeV4czntxX3nUGSatYrXtgZAqmqx7IW5I75K7sC3U3w6JWXS8JMx8wnzln7CPjvLA0YfAjZ0yy4QT2cF+wbV9JkPz9DVeaIsdoaCU45PHk4Zt43FNj4vJ7ev9PkVcQTZQHSi34V6muDaTvzhPNdRxXvmf0JX4bVXnVvbqCAEWOeyeuFR7c3kYPMZ9qNiJioN5O6XMaUD5t1oQIl5Sq98epeMH3GRhnIErHAuMMb+c/sdynJ5spvEPQ6NXyD54LZ4ubKBiNysY2E24W0JNUP+W2SQmU3xhU8VinxQuRwfnK1hgjN3/+giYi56GTrhbCTjdPJMdRn/hCO7toGX66XzjxOS6fSy4PQPKPWV9bDWgdJ0fB30rYa51hlJeKtSc6b0DcV36DfSMU7LaWl7C0mb0ik+hQkirqY5Nh9zEzGEqbitPVfR4Odkiyy3MR8gE/6lpBrfYA7z3+/tw/72KhhfU7Kp700UI87ir7rwjEdznwI/6IRJF3r+oUBwYRT6OG5bjavh0bctAuXJvQ0r8GDbvz9GDMYwkD+o2om2me45E3Gcm8TSUnGcHD/tpxilYx+glw6eWULfnN2tXDVYam745hcd1WcRMhvp787sZwLdnCwJEo86QO2T6B8Cl0TiCHHHUgv3xq0/jEYOmwXjVAWX7Hj7Jip9xUG5g37ykcZb1WKvwQu/XWa6PW3gQZJD4pmlJPX1czPht4wycgJNhes72Z//JprBFapN3aj47CrcFOxtbL5OpvFSrYsXcE8BG1Ni4k9nAH5RkM7MIKnmZ2KIegT7QAYkZ7xCqU4B9qlpoyrIruq4US0+HWc+xQ7ejlW/gI8qlzjaXr0T3s6wQ77ZJR6+uP2biezkeMOX0l5f/ibGbxf1hsgl8N1T3zmVMyldH+H5YknSOdgtzHw33F9DBgNGQrSIiC6lLgu7U/gyw8I//XSLHxDQVXjaLoXnCDLnxk37vjDkd5z/+ZvkCU65EVcmJOdgtyIgNQDc8kECOVMq8gHrPPNvz16k0xqUzrTOi24S4nyU4ln9DO5dX5J+OMcXrbY+Ci1CGEcAguheK06FUCy71gYIx+lI0I4Xmy+VakSMM59U7fmlKMnZGSfCYGUXC1WonuQcT+FypMqGEQiDybdAaI9jRIfT7m/6zf/vhP/43I/CqmhzNg1yFZyKr1qN7rY2qQRA8vIJPFjo1V93YRh960auARN2fytirqXjr+/jcsRYeeRw6b4Ux9YQDIDYjuDkZMHw+f9b85BDDxsdA6P61oYTWjjtqtJWYm81Z3rsteGXSHDMOZinSyB7uumRRCBr1IAp7nSJ/QF5DQt4MBg+0EbjCrm+wPG88E0IoUDIRMGyd0V636WLY2qH8N2FsxmwGlvOcuXdDMw1PoUV/zvtgxdwtnZrbZc+een3/kIg9AUjm6ZIfG1IJY0bc1Vty3Zs9Pr6HtLyfhNtz/gzPk4JJmy2db7bd7j6cJ9cB43EoTxPkTH9/+ddRPqmbFnaVthfQytFGqPl0gXkjEVo3GujuwQ2rT6orpVKu/Q6qAVHh8a3XFkdEN712FZveZsFnioaF1fWRpRXY4FIbdF3XAitfy2DupVascrwkF+VZI/AGwATzpsR46Ojrrb3Ni6l+T8og49Xb3c+6SpQJ/P/pSO0u6wOAyjVHB04N2LwMFPjXWKoevoS6n3k2knpFNCSqPG1mR6ZgC+6bRL24TlnJ0mGnmShcpP9g2R1SDp8b2Ltjn/xdcj0XNlupvXO9gXLm5t6AsPJuH0nlrVfADBNjfxKs9gwFDFupc2Cf2kATN2cQmy+JQlHhiwxPPQ72AoF1HPGIHVRPvNlsPPeoymUToV6jDZ6cpwOyTqPP48FttcrdzEvlmZmF9LGQXbPnjDY5LtQ8sOLk4Ey/VetFoz3GMkodN5NYnNqTigExhil0e9klIUARRylYz8xNwgnz7WRucvICByE+q0Leg4F+CKTMESekzofosm0Pjz+JDb3lY0F3I9W13zbwM+ECCBzRM85nNQu1nhCrZOc+fr5ikzqVsv84gKD0ngIAxsP89PfifMm8NLdqCLm1ikvEkbG2TTaT5+haDRRGjEqKWMqdyqMBDvppm4E9w3Ps8teN9q0zJd4RZOtSxUGKyFG+dHDCzHC7lkKvHfSp2Wkw9kM8k80R5GDPAfCHNs4UjWlj1/pVtjUjOE67Ju94QbyM6WIdKBoEymnpw2jprEcy0QxFPRP4gnlKbPRzDprVx9ojt4kVK/FY3+cs0zqg2Zyqol9IrmP4HtdTyTMiQ85iBVCmflH3kSHugWzPX8KJoZmeejFDyNzmedB9Fr8KSzxGQjJQ+4x3o9wofnQFAz8yan9dUUvYIm2j3sARYUvjtc3Q8b4d+g+SYpmcIGzJDwUypzygQVxIHrAhdlfr1/gQ6deu/SuoN4kSGxbVm4weqqwkhfPd6u7DMVPajePbPlunBsHZ+qnsUXNd8ij9m6YVvAtWOKTMcmYPDfmEbniTdNlK1XZN2VYS8rDBz3TbQVnEdAcrukBD5/BRrC4tQdt4LzU/KXF/JiNy5OkR+NvDbQn9JYRU9GF6Mmw7XYxmPkdYiXjNbL9S9vv+oLnfacKIoEdeTTHOpP+15LLhasmzBR98NkGKprlsWfphrmZa1yAV15/n9pPm8wlw6lspOBFeZ4JSM66+xP1qjQfswuvjib+PzrNDXPX6z9Mx4XTiFa0HEC5HKXXrP12ZozE/y09mOJtu6owpyE8Mjj+u7peI8ddY7Hf74Y/vNRCMEdZGdQhuCoulftjx+xUYEiRs4s7wc11PlYYYj+cS+nionfWRohtZiUW7no+WiTkMSbbuhaYYcOY7+IjEEGNw0SEj4VlWt5GStaC4dQZW0xwmIWOKPumhLZQ7OSSYVZI5xxZF90f41x/mvrKeHKrl71VR4K5w8uZyRAFoa6bvRV8uw6IRBLBOHbUxofpKYsMG4wRxeIRfvFHE7j9wdEMQwonRgAJud+47Z+nCfqdpNepXH/MCJKIOUpiCnw/WJ2+UbDqPxATxqif2Y87WtlWIivRAOauEIhmW7zcQt2D3gN1vE+SkRJJLB7HgXBH5IOtlCAwudDECUkgt1kXsoVyI4CT5iyDMn2iUSQf2OXQcGPV/ieJ0bYTzF6l5EOftu/0HlwW+FQXep5XLmR0/qOuTbab44LTgC8JZZS9+cNuhLz6IRgNcprnPvdltnTsWKBMfGD7nX+3/G6TsVYVvjXt4ubw8Zlyz1g7m4VfpzBzL5UGHuDmCINDMg/VtEf5TfZobRmxAXNLpTF56nTMwWNyWlr7BQ9a/iZ6JKDDqnLUnessB5Pm7zWIv0dV5hNfY4wlX9K/mGizmf/9M0JRTU88+pNU11XcBpXIczIKZmyoLSM5qEbRysp6u7R+HEIxwi4tqREUMPnw387oDvUpudfNrXmIZRP3qPpQUqWYpmHhDTsFMGsrtB1Rs0x3gIULHp6unMe7McDc1Ag367wh0aEp5wJT8byU3Lq9mZa5OmN/t5lNId5Rs/x9IpuOKTHd0Nfjpm/cjEUNdZdlulb1vP5qEkfjTRSUuomyuiBG5QIjySUXSDBjqpYRmfp2f1G/u4RCzh8Bcpx7XHV1ld7bmz23UCnCyRAEAuN0WaZ+wV1LJNjti77b3/air/AgnUgrMRidLfEqFyKuCBKxcF0MXhEF3qHnZV+3k3/f4WnheXvaBnDQ+w/mt0dwB4+48eVd6DoyUvmP+qsUdc4n+i0BK3KZFnPRrMLdaRtx2TlAPJHcxWWRRRvh+W4yZ4hVZiVY/0PKd17yLfupVktA7/fmK9WKExKu7y2+Uv/f93lXK+PtsVcsjnzFLIJZYZ3NnaYduz7tI5gJH7UN+93yz59LVoDqiSuQU330Tpq4zIPiHky6Yk0gJGuGRAeVrgMy0rs5g3ygyGKwtsjyOLGMPA9xILByfiRsP0fr4JczsqSa5iiab3cJNcrsmhXb8DJmfQ54KX2UHdsvr30J1TxIVA8ccqci6gLvreF3V+tSfrylDAvJK4PGroLVZkfeCWxkfKR8YIUZDSCdwrOqSWZ9ZCLAS+IMoUHS8+zRxx+nGSo7yTBUV4dMOWI/DQdQl2/6O9nLKCr7O1PczNchZ2Cmy70ZJDUZic7LZlBcUPL0+I6LizAiTZ9QnyzKtNdc4+UOLImS0BzwnIMkhV/3raHx3MjMhSHKGkvp3D0ip+x9+Z8EGHQxRZQWcEi6T3R3/B6pS7buxHrPgeJyqUXiu7/p/+e+JdvyOFbec/cqAZrN02OBhP1Z4F9PKb0koKimyU+zIIQjTzZlju+qbhBLMvcLygz0H7zJ+445OoK5u6xRzGKliaa1lQwH9Edp/RFaLF8y5C+frjW1WMnLktJTjNt+D6FA2V7vLc+y4P2TqBXFbj1Z7foULP2uv8scdYLwUtRg5lMag5QYU780KYJDXvU3UJYBHhpHmMtvCyA1Cyn+ozX/KJqnwjpo035Jimr+F2KFvrs2oX/KLqVuFyqGpP4LWu5LhEkU/i8cO+JcY8Ug3L0H0ZIliOb81eZWkaV6crpoUG8DtaZPG0utUUbopUrDluytiwCnrdUKrsJ/gAvsYh1DacnpMWPFQ7ol9HTorLAZgo5d5GIzs7l0QgQniM37zNgmBEhZPtLOxwMRiCe3tH/wLKj/aAHqVzjHi0/5qlt1EPjuDSOUnc4QXTaXUQvxWnniGHT2D5pzn35OyAdkfLWT56m3qQ5vDMbdbrIVGUOYeNNUiH1DwGa2T6OL36nu6lX7LBTkTnztPf1kgT1ptvK0gRgXL+IwBXHMxv4serBZswOu+HUajA0vHsNtlvhE97dTAsYafWX11wGyQYj7PmAZThgEJCknEPWlalaHm082XRKEnjXqXyMYLjld+8+Y24KUNBByT7bUxxtX16Ki99jtLum/R3YuldlkzljogDFvIa4CCkiqpPdQ2651MCVDVNLixMQIKUyKXXoIl2Y9AYM/DKQ8E+XPPpF4mj+CS6UF/WeEN/9GgO3fMX915qjjgt/Uy1l6QXBwLoDGdo8r8O7nQoddo7/bIwWeHBIM6mMA9Y8VkO+9LKYHNtg8ZOGDGAq+xacth7yB01p/Slpu8cy4ObJ/9dVhQfr4nbsOULEKAQniL5kqTSBQhoiIQmcle+H6LxTFncx1e0Ho7nocXLeEXuEHvrypCCTTibz/YaXKnp2k30zaW6wXz14HmqJkl7l9lEHKzlYhR0S2XtMLzoSj2tycCyh/hg1aDN/WG3lBWL1VDGPdgyJ6talD6bXXjs+RAVAUS0rlDEIghd8pzmJDjyq/bNOGMWEqEsiq0rQXa99O5dw6xAMQem28SL7+utW6jSntEI+seZlRozafT3jIldu123dTqXyXbBlZqMUxfLV55q4VjIxuZBsNt5LO29fZHWyQIj3nr0arOgPZbDI38qNqCttPi4WBg+PIIJ4oxoTB0ylUdaBBkbpcaX2WXJLtYX4fw8Y7fyplA3tOcoJMjfU9dpDd5dddjTE2cC+nRR7snyTg4blGaCSKTg/S/AQ+UPHw7UtPvRKxU7RyViYeg5TKJPZhDmSvUmyhvblZpTkY0TpLbiFkZNPnzO89YYGB2HsHdJ6JpWaG9h4y9eN7mV20shu0s66SP3yDj3iIYtgm7mdO7bX29ypcbC8MAs/f9ZAEm+IOdK3VS9MyR9SlLnICZ6Zu51izxZkSaQ2CKzXs2B3MPUyFDo9lzS1lnU9KYd3gXxcfHY1Xq+U5jHpENn2tNszeskaNkOefMlcAjpU5A4s1kcY4Bdy6D2x+snZ0i9//STpN9HvNhml4qYsTifEo2fYeckGKiuVpNK14BQJbWd/4KfnnrWbQFNLoge6DZWfBdWcZHWS4jhz4kBxaNNLKYKQ10OHaIjwWNEGnCy2K+XqQ7ywcDjhtpxvxE3gbADC3UGuy7RSWoyR55DKQyAutMwlOe4boN80GBtVLA3GudrL3wDFWsjiIPBMdyc/WMCGFg9C8p2RDbfm7mdFlp8jeiG3l5chsn+pSHf1hF0IJOHwYUw/yoNof/mLyVhwTPhQ5zT9ALhq0qsl9Hg/DDeCsbLBwr5oGH7ddXPSKWbmN894s1Ei3Nhih5xzT9xm743VpwayX2NUTUYLHV5r2c1XDHoZ5piIXwKu5Z2wtVojlDwTObtCKQJ0IVXcTcSEIE4b9R3+2CZcGCtZuXXc4Na+AVNq5X8M92mvZ7w3eGRTFMrpmUpomBd52HVfhTxuRjKDzllHSJ2SY3AWgsVGPQOxclWnbNxgAhgET5r0h9qA+9RAp5qh9/G4AAFsPJkEUiL53Fvk1O0dIrHlM5U/Sh8sUbK4j8EG9m7Jjq89yi99DHKn/9iOgj+sNaZR27loT4V1lgqF0dmq0xf6hkQz/l39Hx11jDkLAzUOP27S2QF1EnxLrxFPwKLUJzqTvonyL2oDdUj7YohTKWjTk7PC8GcaS1qVEmtIt068FDMRAOWlJLvg34HO0KHOLLwYhhe6r2R5+4Nsz8wuYNvgrTwrz+w49HteUoHcOIzhsvGHzNlXrJ5Ihq63vuvcwgCl+hhZ4PBLDZP1gmAY9cAoxp2qxOD2g4lb05YcCVupwiNVRG6OB0gtJxZMzgJJSKeLeUqfct9zJYo7L9IrWeBTicGkAm9QfYmIRvKldt+SNSWpLYV1LOiI0HC/dgBdHJl9jDEkPJsw+kitIXGQG0PVaXuzj4p5N+H0tPvg0X2XJ+GLZ5os7iPp0WSM8pkIuWxIJm06hUEkdFo+XqeGyLBaW8KGp1J0zXxOFzbNIz2QolZhpU/72f+38WCx5lsJVKGRPCwMQ5LPELHwdf3FLofcXO05vc0yZpXm0BogFUvWppmRwfV8L5JTVzUFGZkiwHmth5Qq8ZnKVI6jM6nw4515EQi+IDS5werNAYT9OAbSIU5DAcsya9263RlMC797dm+NsZl9M+Wfir28y2aK6qPswf0aMKl37CteybnFDv1qUDsNDkZ9YgOm3CSvcLcMLjWOnXlv9C7OFTajDeCg3Rm3GQznmbjyfUNV8jiWOEsi+cFd7fHZSynf1a+/2AS8ogTLyTGfkUBW8jqMvcTHSIVmV7LAQvKd3peAVvMdJNMv5ERRT6Irceh3FnOxYblphvwAmuXRqWEG90t6dREh9yoU4P0D+NKiTyzNL2yzF8yRziLGdWE8nfRZHtaoTO5VT8dNH1sM5+s63aiEEuKMp4R+0vlZM8YxFabvQfMMozYvykT5jB9f/x6Hq8jcrRTauPpzlNfCvXHBBC3VwR725N0MPEGvQAaInks3LuY6aGOgZzMQIPsNlu0n9HlCPXFA4SAjavaSqpe4tZAwrrbxOaL+YoyAwcRRdrsyo9Lm311kdlK8DoaBLtIlWSbmSaxV3x7XqwGJ07pl4BZMtGm3buJvUEAFzi2pnlXdXUcM50HDQl1Kc5skYDUFzPt8hCrrR3h7SDbwVs6ot+nHQOt+ba2HKgyfaNrRdukQkifwHj0rXPCWRMqhDgnKd7CJLwqWM/ESTXFeB84dCvHnz9yi3Mqo/zTlhHYYwPS0LkUXeEKlD5JQKjzNB5YD6tTHAg+ayyxiluNXJnQiEBVNsKxjeoEHWb5kZg/Qu1Q9I355G7PEgFsPr+L2QVTXC51VPGCxRqNoGItWIC0i5neNnttXnPEiG4kNKB2pCJ2WLFMNt2VgmG/1fAuklKN+sFzvT8rMiynMtopNGnsBQ9Jp2IxoQwDIJIhdMsjO+tC4v2YeZ1GSX8/csJyBXLmd/YUJM8EU0Fn1xXHnxYiDPLvq/pF0sKG8CM0Ome7l3tS3N24gBs+7so72askmvzhLzwYM9HraaGzTLlOysVzY4pCItS4hRB4lt42EBRgivKdRfsSLITz3N8Cd12hhHkFQblQ3xhJlL9lIm+BYsoQLNDY6CvUMTBXQ7NknoZyOmrKDeUgcWPKOBo5SuAptTV95iUpnj41aQTWrchTWlDaKoDhd16lE85e2+XeLRBf+7IpkxZY+Lc51DBAiOkvpaoP88SZvSc1eaQAtG/0wruF7d4mBGNB4irU3AUh6+59xYlqq3mabnH/WnPHD6Zl4cszuFZh/E2tXN6GdUVJWKnZQXLQgNqfxKh9m1texlhws7wb1qNpH6zJI7nilq4gCac6hhLQQSKOomLVrdfQwt70qtZlPHSuDPsOUgCr3eB7bcJk12nbFA9Ad0LWBA73kYF3tS5jDdoSWcTVSYhiUHt+pUAESCrA0iMMGp26KE1hMm6buL65UB1eOW3ezeQVTGShrEF6CS7OrLUzMCCed6/2QM+sAlCNDDJzLNwvU4/Oxse9W9yRwIIBNuxrVVvpGgZV2668h2iNK6en6BykSyM3kPNbjWYqzcvkrc9eb1UgOQy+Y5dsQBg0wiCTcc5bztUxnfRR9QXIYDYM41ZsWnZEPp5oRXnSc1jI8YFlwUQv8k6ZUbbyDUB80XMy5RjDwNG0n45Nhou6I+AaT0oVi6ap0RfhUz6Nz7ayRGvJx+PQUBWHI5PeUjd+JGxNtztyrAdUxSitiZVNloKaTeyHv6mzP2aCezDTpdxJum5B6nGeijr6y8nGY2IUNHyuIS1P/GfEIOQp1oyG7wNecKZ5rbZX4IbjR9sZgCQVqTFR5lD5UW8QMS4awQoRorzDEO/BXKw932FBInhtxff3gn3g9w+vvywrjRx77RWAzjYkZ6VQHZexBCUy7LSCPn0YH8id0MiaLD0+N3cK5IJYyX64vhvW3KnmISueYY1D/juqvVxdCSUO89vEg4S7TLwu4XW2YdXi06Gvu51Gma5G0FgEeS/3S9ssvZuc6pZbiWGzeLgeZVlUvdM0APYr5IlgYll7wS9E9n2LU3L9K89Shl1O/piBhJHtcY2Ilrbj7SxptFtgxDts4TmhEy6yGqbjhIdsmcVnFie472mHLK4c2GEuK3G6YUfweEIxyn6rsUDqXQDijmme/Sc7t8dqGcMjJ7zeec7HMPgpxOoW6wlblySpeH6dSedJqpfjzF6JKtwxE03QoYYlmsKOLJ/OOzXrPlOPwBMBq6EGu4haWcSOHszqmBcSp09O1tY7BE2Mey08TRaA/5h4gtGhUtyGTYROjcobh42q+hsm8rE7UUU5qpq3zPQckExcwZrO8g+z53IoMTpxvimKTdaeGrZw5nKheH6dD5cyB/iwYzL0YHtIhZrgPNPQsrbahG+ncvf3wyF3A9J7prwDs1W4kYKQD5zt+PxDpIt5QDH6CkSU2sN2QKYOL+7B3bq1gBuYI2172qX7uMgvYIEzgKJYc1213fuXwB3P1OqBXeTE3AUU7T3DHdHJX5mbp9faTElNLLhHSY/pcYgYhTiV9fw1tVvgoQcA9Af/k8obLoLFRQ8sHL8UMLPpu3dXcekMDCtN2FwnuGLOXvfnBP9LHFid7M4OnJyGyIVJlMBZ7I00rIAo/iPl5XsCVZM6RZ8KAwyMbk/hgNnK/nVjlpxqSfGuU8X2PKEXs9U7NFrEI02j2V3+Z3TIRZGpEcdTxoFhf0MHXaAG5y0e5mwGTrQ22OOZR/GGhZYmmOAb94RkiOQNyc6GJbnDMGltQv4Fn+QZzpqBWAINX2Om8AyPCSM8AXfcdyDq5oXuG5XzhJSG+381e6pltiR5IAOA+jeqFOtwnVM+SCfTU1Znwut0ByNSpBXRphDCWAuvvR8UuBLfvDpV0BfDplZjrz0ahsaVf2aFkWG98PRs2uYMUa0VvPf3MWOfnvhvkim95uCNxLMAn60/0U9E41ieK71rDyfbCLbaZGQ3YbS//OIIo15kBIW0sgLUGnxm5AnKJc4qKl+9a883gWrGdM2BDLXuilYTn3hcSi7RjuP6dIiE0xf8ydXxaKbnp/m+V9vmz8OoYHFSVqzVIwhdU5Dia27HphTocywDXIlFZgrDGoer6ls/4sIWotnX+CbjWgqvDzllcKpjlQAxgXPN03Fw5x+hAutsSklnFeRH/Iro+cuhd8+r15oOrkg9scVd/qXtbSlXxKpsnNKHTV3YvqH6BlHMabKM9VL5K27kDFSsDCO3T36m5GYNK8p6DsSZPyWmelA/T/p3C7oChA+zAAnIl7euvAmrApwmYUoo1s7BTyNVmg/tcgHNAu0WY0pu2j0O5o/U6ygdRgM7ulgnIF3kGeW7DXZfv7FySd8yTxbQU3vpe165F6QB5Sx6eOfwF3dRMzI2clHVaxzrMVokjkFKkcGDimr7IoejY+ydgzuJcfW+ML00dq26Fg2Y9CrXtOs2u9Vwt2+tBOeYxTzOlU8zOeRybeuzUthxc3JlcIUjW+8PTzptYeMYb7hdXw4ZnTk3VoKibDXFmQsUKVFUNHTF4HpjELf7exwwollo0FVKFA76onLAQ5HBu7eI3ZdMWSe6KhiIJYfiqAX1apk4VjaxFxl0nYh1Mm6WcuMDQpsh7VJ9o1x7hZ2oC1Zg62F8lHXDfALuXFvWwfV884e86sRCyETfpM33edIpNCCwzIhh7MbD6YMr/Q71HAQ99S4M/xc2j/lmqQ3PZD/qGDwA/xDql+e5YZWaE2mlg5jJrMEotLknLBP9lBrKXH0Xa4Xnk0udgJGEdNullV/2ytonbzmVjYASVleckHdLEIuLNTPY7StZCzcQC+2QT6bv6VMKxqTTjqj6jFgDUZepJWLvutAoq3k3MVSIc04jlGac0HP2uGUZzPN6N6zulWkqZUvJONYGliXbL9GKiE0rh8PnDMNujduxPb7ihrtEePYLeTZhKmxuLdIn6UzmPvHHK1XEetvAqpFs+JaworZvQN5BNO/d0n0wX0HTv+fBUsEugyK4adWbTTbsI5FlPtXvFyjiPW+pZ6k083hQOlIsD4WAOXzeswMSKnVK62kIMtaNgfO/bSIFVE7TC3z0wP/x7zMpx4CO06moHiU6kL8cz5Y+JruFtCcgu0dJkkLI0p+uo/WeCnZ+4NsXChO4eYmL2BLNGgZb1BFsQgtQOYySUGFM8a6mz7TDWO62DM7WTc8WeZsh+4BvmdOmH/tU5afsBpuUhLaW7QiETxErnlBZOa5998P2BCWSUKJCIa7F5RqIIRtgeshR1jzdL8HlSc+MV9rdbQWX3zzk5VEUpJGSmEhc0Lbh7XgmXQcPU6/EH3Z3FYhEopvTQ7zLsFeaghBTxpu6jMs1Yo0U6OOYgag4KKJUpSZHm52vj4XD6OXtXlopceZNrJ5LgzQIiL6IWSc9Ycl10KR2+La6+ac8pL3oWwEbHjbLrlIMffH4S+NZ+Kd1RrjxU1hm/tUdiwtbQPCeXXyWxcfbOfUXABHRxLjgeuOZpO9As02eV4Ee3IDIhv2fBTr5C+K4XTLbX1xeD0BamK0Jh16XTgKnCwK9gwT4ZvMwhjL9S2Mx/SDnAGQvLaQeg6Dz9m4dn5xOKFxItsXt+isv3iMWx+3SdUp6kdse6wY1TZq8/8on2ers3qJzGTozfLTO0MOgz2Wmc+PFAABUf8zG4ZYsam2bLSGABDI8GNMU7XRXO4MDOvXJ3fa+fjdvVMG/e+OQnShORPqOA58sZuPmhc8b5ttEN1zyZ0ovYkv4iR1vg83yt3aTqeul5hbQA8C2kNz0K7JK0Hwa03cw/YOiyZeGGjQJog8s1R6zdmKWxhfVMzOXUca0is1CC9S1EnKS7xKO2G8FmLUAQuJRnmqqcNolzLKR+6vhLPKqoXHmxH96mZYaVgXSENoULe+tMbKauTGKOuGGtxQu41Oxu5VD+jApLA4kSEqxmqeJfnI15DtYQkMEUNhQPnDb7nMsvaE5dxZslzU0SkRGmQ+ID53JCx5uzWcxViYR/IWGyPCVq2MLrP2b0lq93EMQIBGbOE59+H3yJwUC+wsOxy/zRc5X9rZely6XH9eIo8qSza4eiL5t1KIA7apw1B8j/VqlP+EGoaCgNELZknhLoouuICaSk1wE1oBgvGMHanZ3i4KTGZfUd1v9GGtBarfwW0KcLBtqy0xTImsHpn9Fdl0l92sqLYFj0GIDGjZOmjvqxYvE5RWsXXmp4YSUS+CdyU4WsSx3q241hGBJCCiVc1aH5mGuVrMWFFBekGsQj36ugn3mmwO3o7xtPb4jRgCGfJrnO/dvKcV3Z+iWd5ORCpOWWjNp8euVDHk6Oy7X4puib2/jOnCKFuxn1sI8it0mqiTpy/C0+Lp11QId6GJKaNBoHHMGFnHIX6pqRehRkPywczCwczWIlq9/o5StO0kBG8y4dlmrju1j4cd1AuwCx3JEwFkYpka2gi1dMrW/EzPh07Wp+WNjMzxW8f0e7gtUUGaJGgainIh7Ecyu2sD60IfBpVTS8Yio3kWAHev5m0OY4+HQG0cV2vkswXh2HI3p9/LKUQ1nim2iahOaHBs1h2/2RSWZozqDVbjTsZz0fMPytQDeXGmtxii5hPh39Z9jycpT5Vt7Zl4cfnBOf1wIeH+/mwn/9cY7ZCJY2v7agxw3sfeEf/Bg5lSJYnWvqCGovkhRjzkcUoVWeRBJUYh4W8bIA5iY0b16Lg27hmr6A2QRgD47jS6/0E249YOk3FUUOTu0cFsRRpKCkXU5nXNo/P3ke9A+8K7edav9w1wajSX5+KaSM1TnXUqVjM58T5FP3r+QAJVQs+FB16iW6L2OKbEeoWFfwADdYlZ/nZz1ChAHvcuCXsRztXl/BXw4nX2eVnZ1Ss3mI9YTbGH3IRQagJRFWyTGMjS7lrr1jvbBBnmw4325SFZ//IobUPB9at9jNfneZs/wcqs2LsCyWzBRgLlE0nSYSM98E05l9h1HkTJiaZvYL9hDF9sd3dvcyuYXGfbHZUZFRqWJa6bJUxjs7lons6RCGrfGNo8khIGGpWEVR5kri3CXVvo2SOai56PHKnVEsBgwfXxEVcKlq9V+EVoTSC/KP1Jc5vErVIonKJhXtlfvJ+7NdOo7OIuUhCHmxsO9rUKXMEriMYGfjBvPNCudrQjM7xHC4iQ7k9OGjQ4Jenki8b8pgXZ2gZ4mTL2LA59RPkuEtMqajeUET04ys8tCWBX/cLlgAIPsfsBPKvuR/Ee706PTDzQiuMXfFAX2sjccMvwvdQjKCmYr3knrDLbOyJsgRb1Qr5gLNV7Fc+PiqkZeEmzi5FPNl3XbhVhV2c1k6Nf1mwv1thn0hj7efsYv5uuGBLsCOXMXSJmwInRXfht6eLut2dBB3htqwBde+FcEfKk67s8Jjh4IY4Xnuw236J/TZXVtquoD0L5fc3YK7GdHEdciPbVSA24QW2gx5ah66BdWENNWxDO74RryulOEl70s7JRhVvujif3VKz/BnnHpDbWjm4D/a7fEMd2skrQZsN/5OK7KtyNEJAouMMjbZMgj4iQxFN0I5sJJ8UEUzKL0zz0WWENYD5T3Ji8AIiXS8UgcwQpTVqZYpilNNxLFVq8xJYDIpZVS2HCM16RaJv7ybTN/nFQqsI/LEyHagJhjE6FO8Da5tkN/5vIZm2tnGMjaYGv+ClVQbGe0w39wV378kvZEgJH5QDnEA9YVaYTrG22ci8+5YERfRj2e8azT2yrj9J9rCtvGTJKKIvXsck47+KpQS0jqAoKNswlQj38K2iJuRd9frgFdLvLUVzR52vLmsrJEsl140kfPTR68VNGc+VQ0Gthw9hVERYQVbVfdgoQiR/Ldgp9NBiMjBNzGZdVJuj9cBqlNvUsvbz23goyOem/K8GEOysF1gdhezcJYNSVeU4TB0RAjkmcc75FsdeekwfDaWwqapHn6vCat2/VNb/mezU+GgYR0z/sM83enJ3mSnci8ZsQaOgpg65MuKAJEMaS64IU18JXxEzJRck0OqndeNy8oZKIXph+rhwswPwLlCSM4Uwy0SuA0X0/chmO1KpZ2jcXewJ1ELIAkt882wgLACrHpES1otO45DMFrDjMaaj7UTlZGoMr2H1UfQnX4Vu8I8mVgekfv1t/KPFhq04W9aFUsTLc2fGgG2PC+D3/adLX8XP6wrGShtYL3THJcHYKDTybxRGGr6xOTx9R60mS2U41bwG92dfG7ePTIVw4YSgd7OfUUsgDjadPkqdHVyWzkAz1Gtzb8KsVG+ajCqQpljsjcX8j/qkaBimq13BYBXaGk6qviXZQcVeFTwJw7cYOtCPZwamIKEaBXVhwfavol8gY99BJ9mdv3r3jTA2WBNlT5ODbsFf5Rlu6ih2k/5AUh3FYe7u+zG2ZLVBhh1+5Kc28ZJr1fRukz1mEd3196z1qHJ619VlzwaLcg3Rd0bdfhPYvbnYtwjCJZjtTZglMQyYnfH5FYMai+ReWDRoG57oHdh6e+qEBpO+aD/onyuzf1qxZQ9yqGLe/nZkDAQ0VD2xBmLjCT28TIwlP7e5dlTXDqxeughWXNkHH22lQjYJyMZeIDWpfgZ5C8erq19rmQE4Xj3v4wi1FddxVfjfxO7sz1PQ2RamMXSCn5Nwv4FzOznq1Db/4xMLOxZlq+kMOeCSMoGlsKXIZjJb51w52EqTgsoElXFgTm8R58zgvNogwbbCpdleuEPGcq+wBi260XsHWhKsOrnk/+FoZFghLlSXINermBH2r6pMpw+/qo9eRe1t8d/z3llqhEojj/HZvIMbXXeYhB3dXNpOnQzBLmF1yko+UehPh+UI1h912x5sggXHQfSQQw5JfJj5FKFRJAcvsBSp8tTqm+MTeK6m72f6uUvmQ+FLyXiSRBQt+isozIxajRbzBO6WXAmCI85nX9qBQmX3jythgVS+Yxw7tyni5dNHN3Tcwlucj2dCi4Ekbm9wYkC5EM8kiPUtxTpassySjgPpEqn7wKKy0onV1iPkxSmwEUaJum5TXoEwlmDZlsWLDRw6T+Z2inwmttkLM7YXJ9hj3eNU7rSQ2rtwXHxYCFmqiebBD/hjdWuI9X2AfFV/RoWZcRXY7NNN66hP9/gJWx1yjqEcVcYfGGhEPuJaovgZxq6QVSCckPqvaMsLixcdy5f8bFOctdxOTeRZL+49+D4oc1n8FBxZgvjoTCQP4ZmSAf15wlpbQvnQFpF1mEHkK+3QxGojloNCAHkn8EJd/gFdpEEExxsIxV/cIe7YWKCLWDifoPhdta8zy2k6DkV3W+41ESiZeFtHR0/dKbmjT4uoUjgIRicifJA4c9zVfDp19rjb01VVJqtWdB3IX/o7GNYeFjngqLJYzbHXENNWbKkrtLLdqyCfBTA9RAGJDrb/Jn9IJtGmaarHq7D0pA2ff3jISg0V1cnrOQAf3q0z8rwDQBHDntZOTkzRGsza+Oh/ilI43Lobso6KPj+s074rFBWR9Wr+kdFEguNwKAuRChjWwj/OyA0jagd2ovi/YjrOLTegXonP7M7CT5OBEE0invktUVgwFKQjXSSoLPLQv0iG9AxMgd5da0+03aE24hYmSSZtaTwQIukKcxdqtM7fSismp8h5Q2BLWAYry5xbJ7Cr/Vf8UcgDdYOT77MsDNQ2wh01zk43M8SaubvOl86kt2fbcMf3MiICPqCJkX5YIhtqcCG4RSiJysxmvK64V2mHqa/YBoIz2avABy7YASmlkeIXHPtXLXR+V93oQE1xVLGSSdv57gTYXHUxKh6v2oo3//hvF4vtmvCFsMuORONHwDG+MPCcV8886Jgjaf2WkPNB2Ot68ykokt7Xhmcvn3qZjAxXztD1uIf9ZozS+vzY8qa1qOaOx5/0XH0z2b5Bc4GzAuPx7unU3M9Y8IJ6YNW11fSA6UcUlTFp9ILNHWKPUGT4wfvXZ9w7lJyZwX4VFAnKQ4l3QFgbq5UCf9G4pLkVyL88RGVVo3D1Awrw7JK5ZvnkBNgc6FHl+yddGqgUPDZGdsJp5UiIIVFCvSZj/M+fYxLI9jwslHKtbynH59ePwyXqVJCi2nOjow61spBQwzr8ZLQ4WBA8MFG27DYFmt/g09T9kNc33k+TUeE4TbzgZMshSWjV3LDpFsv8+uXoYHOd6wFQC5+ouAigATdp0lLn28YuD/bYggiPMdSj6tsmvEdhHaQ2aAtqcrSeNx01w4En6eem6CFMuq286EGKWqkUkWM+YBZry+0Ytr/Epf33oZCoFbdQk2qXs4Olq1ubz05YG3588uZF+Sb73PBLmHrSeahDTBOrNwG3n2Vd0Dfx2Axx/jEGnHJRD/DJl9mOr52dxVEV694Yvz1nyfbTPQHNMXJj3ZluZM6/msXRx/WFh9nWhFLiNizKojWkfJ2SoXJ5dQHECXN5ahdaGflz9//+Hn2b3GgwpzcyDKfbmfPvnKV6ep6CJDbEJbGvEULG1erxa09A6F7k0c/ZueUMQgU23BUfFW6EF8qpDj9He+j0NnU/Lh6/9pxB3r1WRSq5CzuP6rxMUva0eGBl85EZW4fy3Fj7PdymuNWflx1F17aodjOrJ2tVFU3YG9t7IAky3Aoyzm7dvTvDSVNjlwPw5gzyvMiLH3KLQBHpMr10KaDNPhFw8p9G8TP4hW2SBSfh7StzRidFMn/jgxkMnX5TPYb88p4O7OGjsoLhdfUBa9NgUwDY3adE1nkF0S+3cwgDiwbT+NR2U+e12EXdT8zp8Xyly/lGup98W3mPy9r159O5nBi6fFmYunBWXDO+xTD6T0okk7fq8AtdclgHZ+PnCdw5Z5w/Y5/KRbBe1VVL1LocN1v1zIUeHYSBuKP1ToTcUtx0AoDdbqptcxo1Z+agNKUFl7ar8JDa90pL8Wbpy5Qin0BC7dyWxJ0avadUmUgW0WaZl2Xx4/2aFrOZqvLb4cDgTs3z0kvnKqFXPvotpO5O5sJV6I4tHD4evtPjw1Dg38mKAroYylurcvlijfBsjVa8MTtxqosTy/I/64yL2+px02M54PcNEePGRSpK1qBV8n/wbucQDYnBbi1Dqw9Wxza/czVzB5besFPu2+etBaMxffv55pvwStzZln3HnYYQVUYxqR+Hw0TH8psvQhbfqD7OwWtA4MSWGUxSP3HqTxYqK2gnUwXgaraOQX/+zUgydafZG/+RaObgNHZIqTi79it2ryBk7pWNQDMLYOPJQcxTdLHN+Z2OfGSwd2Tmmp1K1drOdEhLqyMiDZTcVL1Yye3KNfMXTtwr1DuQb6dPhOJ1Y8ZMDV7LI7ygPG2KjrEl2pWGiuY02WGDK3qpEjdn5p0u8r1wj6uvbeNXdiCLUyoKlIoAq27921CyKqkuh4zqfw6uRanv39Pq3UPh+X5jsmfRfkJJJV7rJGUiHg5uRArXSONsZpeHndqMQT+vhk+2bNl0rA60lLBD8SlaaT5l7n02sUQrkn6NPRcfTtRkckNnT4GRPEIzjMge9A9GoWdtV/vtdqmq9LUBisiuOaOZ6K+ms5OONxbYyaHsDrKMLAXwLNfUzBIczTL/O3OdTEb3NmN8Pjxl4dgn9WZRH791rVjYvlzl1SnlGPmtDh7bjm6/UFVVKLJ3u84CZidGgb1vT60Ksyyx26nh9Hr228hXlIE3sdShaScAQzHHTo8ebbNndxdsd3ILZrmq0KEf2kafoKtL3THAb/35PPGnk810aK5J8gG0Se979HhP8WvJ5WK0zWKg9N5XJf30dVE9Q1VYO1bsh/pABaWWjv8YXhLKD/7a7GyqHhmB5cqKJjExWXvFU18f5k6p6VazQMr7C2oEX56vU+fPD+J5ZVCBP+idt9mDSMW9a02yTZbtGGNl25PQAOny6DKcl5Jx6S9JW/hQsg7TBK7nxua3rb/ufhKztCeHBxzOAuaUF8QadAhOxxjxFfZN5FT53n1u3NIiByXORSwFnR+zz4drMW9sXSjKQUHyTaTmpsJ7MPSeAb45QKKpWUhAJ24U6O4uWgx/FHzhTgdMSfV2J4wmdrlz9LAI/4kOgZiXOfxh0uBSwTGsVSli7UnXdSqaktILuS1V3pdNzviifCNApYImtmdMi0MaELrP+tVIaZVH8rSnXOqoMwKFGsWL3VXHv8w9eJ2RvJqAFMvaqjjSx+qigilz1kwk6NcTFxH4+tdduYhn8toVeJgXmJ3rlbf1VXwiALj7zb0SZmKQqpA9xrXuIzxTb3zwMJPtRXZEqyNiwwe48FLBV1GXVr2GJfK5imrniF5/95H8HTkUWQkSCyu91VGJZtpGJUFO2t/C6YBmJ3p9QmXJDO/aLu0fmIw0M20Yht0suPKUanS+C9LpiaX+budpwQHkGfElO894z6IWcwVDXVtaQTLqWfvniR9cE8APOclanYUugUWsySK4p4NpnN77xxQZTg+SYfAIIMjBtixi7HA0xtfuHFJexG0QIjnP6+eeL/GzC6gxWHfq0GsYCXRVBHMOvsodIshlymHtStjekxmc50duHgSk509+OXfHM78dvje3UpMxZRdiiXG4KnznczJwGBILsbYyMp+Q4+hWJ6i8tIJIAzCxMA1yjjJOO5pT2kZADVs3qgMIrWC4h3nd62UhNaXjaP4HKtyYfwdrO1RoG3dYzYJ4Nl9Hqu7xKxckX48UpG7wv2oTcvernZLyDG4evG1iMAaFllySuV9aU2mUwwQTus6oke8rJYpu5TJfGJZaFqGQ+L5PoHokjhWdVgABfLzuDv7ewKmaA+Pg9hiXrpuLe02nf9FTjjDxMaQk+b7kbVi96Q+PqGcO0C21atL1iphJt+Pdcj+kNqL7Anq1kA2pT4l20jpXx6kyeYmmaIzG9dMH22lgnS+Jm0jGLSGysX/Cf5fNPNDRL1Y7RdOMgJoFxU4NblytklLQrKe9itmWv+54FDen8deK1km7kEtDl7Su523iGd4VP4dGyNFDFYljGG8U+ZM/Z6JCdlSOTAhoUhUqdL5sy6J57fkPHGrWsGNFoXmkmL31YZ4HbQiWOZ0RIysBFqrcbm+KGVpmbBIOn06bzxQByg0m9wIRr283Aivn8fJrDoOBVunTJKZpApMbwhS0kmE8R6Mk34MNdyeNmAns37RbN3QgH96iVr/Vn9YQEsJM8u1XPYhTkuZoNU9G7hTBcgDYxc+7I6DxwsZGVh8Um+lY+xn3TsFpe0CLjrCOhQ5Jkji18ZLDyn9206Luy3UN6Yta6Z2DEUAvjpLiAkAkkXMf9BEzx9/CZqq+2ukYNvc7vKkO4eV0fCFihD3FueFgBKgwQgMclc1l8JTuJ1Q7uRq1PLS+OnAmAle0ECFDFFC4jO2GvFWn+3sLNoBeuFdyXa11aShDNhCjasobE62tl1xW8R0ujjTcbjufuAkUj8YolMokyk2OdRqPYkfoaUp8jpASBFLES8GCTHtWph56+p5EbGwPdGtMwtEohG7aR5dVR5sxr6cNS9tYfYLBVZS6mnMVatthJx10TaLmdXyi/qmHheuSyGsUoXu9+BTb+I6UH4YkZLc6E7D5OrczGgRb7QHd9MWgBAKf6zuzzSE0eesHe9AbfJ0MWxLutevvWxPZFFfar6K8lRO/7vSNnz10L6KD0cNc3Yi0T5GSPfA14bzfR0zKwV7oJIIscYMWF2U3BcXoMuIFXBz0kn1cKBcLtKrFZMWbZ+Lp/Y8sGa4JXWSb/Ei3FKPJFclxcirPf8qNcbONZ3yPj42TySwD/Xa19koAjRy2CZxwsLdc+zz81zPkInYIsAancdP3d4BCr/JfITAnO4/ZxiQs7mt5K2XhTbekGdbge9IBQTG38GZ6ExGqVRw6aLtbzKz83380WvHNanvY01fxSNQbK/u+XRXgRuoQ139BZnTbFHADq5YhMv2WZ5O61i18bLc8dbNpvqWMBO5xO8xyjLBt8TJfi3K4o9VhLT4o77xnlOYZcQ3VIC30ZxbmNJ/uLxU9EPSzRfrAjE3n9z9O7OjozUVXgx+ndQgZbhIPURRd62IsBEuGb4uffpmEQxVG1wHBcKR5NpvN4Py90U7xUnGjVKoVmWUKL4iGMn1odQmzc4OC69mKSrVBR0thMn1yobzZRJG03oZHQHrO3iUc+HA8aiq0L9d7dPCsXWyMDu3WsWXhIj7Pa0y1FAnuTZmlwbkHjtQPQc2C4msLZqmsqcpzB95nxQOic/ZezhbbOF7wB03MCtdBple/CBTQ1uCO+RnR1stHiazZkd8YjjGzGE/o3XpeFoFcOdXT9Mjb4whmJ0VpY8Q0fkPNX+dxHEkjniHtWJr6ib5NLUzS1eNyCHdYm47qV5taYyO0UfnBk0sFFlfYvEI5oq+GZKp8P441VzhVv1AbdegDvy4+uJubGqmG4+Dzp5YP5nSJrcOGZx4TxmEhSWGk3I8OQp+pFHk4lO+I3Vj4L0wDqPb/HBP/+ZAsXtvd1RcOG0KROLOWc20VTZt8XA/wCJZVyrZYUaXNokbYu3zHxxDCLG5Xm3JtZFExk13KhGluCcYIZiXa4NMc4CNaMqJP8SNEBNVWf89wtIf1DA2mSaiNemmscwY6Gc2ZY9E++wQ11m0gCOQ5huNOpz8VItq2MSxe/2JFu3HazsvvWcvfctwQTOgJvYFE5WeNmeBojCRqi547Jhs4lITV+9Jz3t/kjv+F6NmDnavPylHcgnSD2NA6pOL00SqHTS/QSF80kBHUcwD0VsZYhguRp8OW4T1mbEhx2VuQXhX6HXF8bQCSBJDycKXfCoMU7RM62TMbAYLc6lSluHBqLSjRBNfRSAvP4OJAl9JbLhtG7EebLiTCmCuYli/6kORBLnpj+iM1KCu1MvBRTFarXnHuLBaxoWij+NwGk22eGPQCQYxat/2G6cYzM531pHqLeDRwo0ugrPjL3n5vfHs3Yt2/b76wt55Yvu7KdfoC/IQiyT53JsXjCYEwgmIJRuE4yHrL4/H34seRK6vh0RzdFQwi+mRYY1IpQag2gbz9oLyp8sTF+UiWjBcez+5KTAGRGhEkZMf80qaUVQxLwvmOAY/6OV9WlZWn+qh/YitFvyVue2Ypt42LWWrkIueor2iKw5R2Hhwdwr8g0aLqEIdcejHJGxdVvcwXRMJjdzg/ql2tv8uMtJr4BiGI0Y7YkxQEsef01VerhPjrFw2kOshLIPC+Gel7wl1yBDrKd68rWecXJKU0BNS1w8QTf9QitAp6k2nH8ZgXoGJt/LeCT6lnACqhL4PTRjbhI3S8B9B+pzg2SBGzI+P5EOKhH4cBM3sRvP2pCbIzkBALEsdRNXBz3XuRUaZO47XHhu3zPCSQgIw7kM/lQQBCiSZtVd8Xp3zTGkE/Y8NJ+smUTd5X8TAatGyHnivOcp38aVwhg+0ZI7f8srSYIzORk21Bac4movNqU7gKTXQrUs9TlcusTO3tZxl+/vSocKvbMFNs06qsSJHXJirj7j3/f420a48RWkaPNuAd66eEAW2SM5CPpUz5pz0HnNm6risVNIosejiWhZz1Q+cAvepjGDSL3y6xfBmcDU7TXda+mZwyVaLh4+a6Bfk2/btV/Z+HQ9rk3X8HFyB7wur2ZhkfuX2Sltn2g9rjhzgxfPOMVANC8tGwMuhkZDcESANqRmbMgI9x7mKzlg3JA9GMMPMyLqZGUSNlQ6uQkCX8wQHjzfzsGUOD7avoI01ZTTTVRR8+TpiME5VjcnoMh2R9TGVKpJbuoUzxQ5KjS+ZIVk1KSTKQ0aCY6zZrBXEGaIwD4Y84gWVIuE5s1FJF8Z3z1WgSrEquNNOGT+lC2uL2Pbv6WFrK61KUthqMeFKfG4LxJem1n6mtwRxeTxlckZrMcLcz3sPTINzwO3I2DT9fqFUpgMq7tOBT+DCPoz15yLyoQsXQCRPYErDgGpC5mkghW8HplbRGRiQ6yUnmefRtMCrjra+AWjwP20AUexFCt750lh+6GzKIFa/ieyRJu8MM5W2bZijWveXRwnZ/SuC7VPbYzZNpvGQtPeC3aP58jM14GcuohGAjUskrB+UM90lpkTQsx9yHgHCGCXOag2gcFCo5iaBoN3iz2q1oLjazCYwoWfM5qaOehrjeYNnT+P0zixS0OveoJ7TWoCROJ/2vH5QE/1J7N8rMQG0uMu3NBO1JxQMTcj4vM6qCsOqP3fiXuJayhFCjRqv4B8wi+FcJe6h+OIuQZOjs7fQYir+CnRdudmAoqy4vUUuw24SUhMXr6Aplx6Ezi7GWUQRbOYOddNsbVG92SQjPXVD62ABUm9/RxaaYZRbNnKOM375QYpvsuD03Zm0AF1+Ah2tvTFNbPttlGoEdJYLosojJBY/yHTYcR5sH3eMbp+8fKOzI4rvQo8zzAvkFNuwlXQZdSFpAack4cCzub5gYmFDdoCQJfLKzTuMXb0SSRbBUUB8IYVHF+7W6RAufwfaVREU1njHUOB14jVTvMQcKSKKlQWJWXiRAjb8GNVM6lYmCCnTZaYPJM/orx1yveeWWkdw75VJfzQmC4zTouijhihmhanL7T99HY4S3KlBOpfuzw0fSUs2t/ZH1R6S5LqtdqjQmJJ6dvrKgDOR6qQIClT2AwLL8d6UAXWqD/USo9JEq24zaOKv9gfBcLFFucXnpgO3865l0Rx1CX8Fg6W4j3ZlV/BS3m2UCQF7iLdE45G3A2PjQKklW86drxk/PZtBqeHMm9nXWcN78EdtP0pmySYBdkHShEOa4fKn/DkeVK4JW4kboTVGk9yKOhiFqu7KO+XuAsDWigLki59nCarmZYbsBNZ0xSlmGKpYZ6LxXJ5NwMjK3yp19YwpJjhBN4U8FSRHWSeL3N9+huXKGym+g60qrPBtw5Tq3QhZOU+58EzqIhFNehtQOeSKgmcaA8bTOnTcPKVBHBWHqjl7sSMhxPAJUkXxvDPUSSygXs/6x/jdDAj6AneRab1BwBowYio81SgdNMVyV7NPqYc6LTr1tZy3w+ZgyPtGzZaG8Z2Td8MUJXpcWb4uuFerCf47QF/eAoYTrP1mMiZLCBrFY3CjETl3NNei5OIpire3Bc1AfM/ZF/sRK+MVofZR7qmp2My9xU5+OI6k82UztjqepSuLARJ1zEjiwirpWfB1hDPTvngaiRgCAAptA4DryKgrUq3Xp4Mssgdxzv+2E/XEoXPHi5WRh/9A5oHKO5q/RXYv6GJkS9liKfLSrx3AB1eAmkYISXKAJs8EBFWmTEK8xcL62ZJ4I9sOq/JzMWohQ/utfdBO+dpSxYxTDLAiQDlzGoGvu3GyLcv8+cSfB+xMxAWXfw0485f0PYvlfNH7by6cC7YoLLavcRvDIMLOjBxmJFtN5F1ZOj0E46l8a4jbO8MhpN51SeiXQ7PSelqCsVt2nnH2+8aQ6zBwnrFTOmjLj33Foh+a1bNxPx0BKKiId9yl8YXZRHs6UhajcPKgRcXec38x4QfR546wVlr/HefvnlGVlJhuabCRosDzU3OzUDlQ+ZCw7O5/8cd3r3sI3QzXR7QusOkoDHLD+n01sKoNea0mdFyib+5UIiMZ/354W6jBoGw3F86n+VhOjaarb+bBmdzwXEKZnkkODWbqnpzy3JTPkm/IGJv1nroInQqgirVSteZSE5P5o2XLLW3RyA0zuDLXpY4JjdSJXyp4F85oh40BfK+FL4WjTziVUBzuVRAlzdptH9DYuuw98z4my6KJS9pH71aj02hTtt9zdMcuHxBwJSSHWW8v5FbBw6ZzEVdRP7+zJ9uN6Ev19jEDE44HT+9eml0Num+jNMaE9Z8bsv5XFE9LAYZqNyYTXl9YpaFZi68OLtAgalyUvVLWCUg75oxVxWPwb+5oWoVTfY2Kqd7ARV96pPTKm9uZzNdjX1nC+46eA+s+kGYdbJo7hLzX3JjiSuV4HuGWJqebDDmATRH77e7aIa//pBgRGc69WXQyD5ayBpC/jIZKdX61zOlvcvLPpfqDvFmy8XC7jzbOGksTlZTiqRF4anLPyReyK/DkKXeyIS7yNJALJGDsZMh71Ea1NqeI23A0wohOpfFezlZXQGTS+py1mfAhpur4FeGjtG3pHBFdqC+UTIr41FK093cMd1zR6rdhbonxXJeeUUt/xbBI40eiY38tBknsSjKsmnh/Uwwunw7UDpc1LydmQ4I85k8ZZFc25Z0jLewskR3Q1kJEs3lc6ykSqe7DUtRiq0xMrceXJIyc1JoPGG8Tc5G7VSwv5Lrhhqw13Kid5ZEKdYYIIip3g7x3QTeZzKkpWbpNiYYfqQS6vsFt0x019TIdiCxeRpKREo0EjTpo1KBq6R6ZjrRbFO/6JWY75l32BIiX7bqRG1vBsxwdhSyS4bB9hHDL4jJj00axVcf6726NU3paJDV+AwKnQfVUknimkYVorMGZTt52FoU130ZvMVVKtZEpQE/ekzYpVpqttdbXHae5IFgmoeTv54JktqgFBz2D3/fDxITFbHZjHS4hLqsd7ggsPHKXbfFtWKBi92OypE2GI+ll4pDbc6fqvqh2hJnyAHaiRCM0XZqEuHdx9DBA7tYx++zx4KDMdvw6R6L20iPoHUtmMGhHSdXbALkVWFGR1KNPBJJFvNAZJ3ucE59oVFn1oOTp0w+YlxFXGDWQ7Y+Rxkuuq0JTP+sWktxgu2PXC/HdLRpq6lm7BXUdKE9ypc+NHd8Y4YqCsVnGlVshq+qB+0ESk/sk/KwvFnTjseV3sly4YwUzZNmeEFZ+N+HADbUJBhVuHBgG9HxMqqzSluEcjWKxVEfVAOPHQgbL6g031yaMYk9Sf0hjo8Zl8m1B16H1mjHOTHZCi0CX50lOM/y4/cnXM3K7+zkJaQPJFdqN9cP3WI2TsCHAM6sPFLoj9Yq6bG0unuervC0WIgXIup3ox0gH5OoS1zfMMlAUR3UYQPhGbi9yLxG4v2XeuOmz3M1YmSSvZBR70RyXXQB7d6wkiVIBREpbDG0pGiCUdXCxxPg+W/8+e02XbUKpyl+I2qtbkSYHY0q0/GKulsHyfHYmOLCqcmORC7V105HN/fKzMj6/waI0eeP+Nhofc0VGNl8J6jXjfM4srjmV4zeXd0uO18HMzt+BMweow0tbetrB5SW6ZIbrSnPJhuWujyzIQ6dA/LNXVpMZvzCdjeFo+8ISnhTn56R8QtmFOnkqVp7dgK9Y80IZK8Tw2zfeqivbG/OIVZxqpStTb1gqE94auQTusMm6/f3oWOTgYYmHOWt6DtsdkoYytJfhWWN5WuF6vTG3Z1sb07G2NV3E5R0aaEPbaX54LdmJiOuoMVzRcZEeJaRWN0ZjRp/Zvf0roS6PvlnGpnlBma3ivtNPl1nQ2DisWlfKbPkfTptRW1MUVxAIvveaYmjfYe+b+rd8Fchn3ZczG3Y3uOFJSsPmbl9yqthE8xN2PtyXFMn/YHicszwkxWv32yLR4OZfEogUD5k6uzBBZhMJJ3U/iUHmjwJsmHU7JdeTlJopEr2TGq9okG9obmeroTGey68DC5oEVwitSiMMbLUUaUe4GHNW3CeNMsRX41DqxKGuh1QwSpNEhAVAF6ZCF7JoyxmbswbyJopiPYwK7X0AqQMtNDd3PpnP7am8MnBoeXPR5ebDwDzWc8v+QOFi7lqH5zQZW47SR/vbdRJdc8Hg0lNg0a4NUrH2r934ChLuyfG96y83KOoed1S1YztQ2k4dc9BM8Z59viTD9dcOOVUaO21q/CA6vTKy0ErZzpRGenp2aa3t2I3uWP/+89O2cc/cr+4ZDas4+3wi61bH1GhwloVuQroD9NsPVIludYTG25QrWfVklMfk9NGP09nGWtBubyJ3KhKEn49tr0us3RplOVtBAnr0JElKC/82CLDxNpbNZ29R8PwutIFMkFKINYU8iW8D8qPgin81Tm/YwnkTG3wBUsXtbfpOLj5xWvgKGIvjvn2mAZcvDr4PUTLWvsA18vNUmEcgG7cs8NYi58J+pE0clbfFpgo+JMjCn98Ka+rFwZWrvpssZky37i4P+s0LJm0CGmwO371EX2kbWOZ8JU+j4WaaHxlRGn+OBcwnQmZZl542VMW5YO0riEiSoIMfjbv0oSFwdGzTbn6EgfqPALhn8+wM/YviqD+71IIozgCatewTYg3Nz24MdR4XNaCr6s6SnC+t/Q4BIMJBS24LD8ZJgLkOkVOzn69zvWFscWivs3jcFm1zDNblZ8agEYc2LmdG51PdX3DlaAVIgcUtstCWMSiooX3T5YD+sfH5ffcpYgoqD/vnHz+oF6rwBl1VNYf5ESTwORNgMEbboxA2yHxN7UGWoYyD7IC6u2lD7ZrjchIvbf4CFigXZa8Yn7Ee26wTOtxpgS9yE/6ujDULEI0c6hrNtIcPW6GO0O2OIh8MetPUsFE0CtR2H1BfFqxsYeARqXG6w9QRSqvQOMNNHpcGsGAKjSzlmAy4K843N7KcsH7NXJpPIoYspxnbv5Fv4lOImo8Tb6QUq7l1XbPIr7QRfY5rRBmbxxQ7WbyUV8hBZOP26oEEtWzam8gXYHSlZlgBwYwEqokAC/HjTY6xjNMxvESGY1ze5ulObJqwL4SFB1NW6Y2whrZrRsBl/LSGzsrhEJdjvBGpzyAfC6zF6UkBb4DGTvSTJQDgmRKDJvsynNa4SohEASOMm3sd4WeeSs7nnmKCZW8RUvFJQ8HmTmH07Dtz9J256PcZd70eC+EJVydsx2BEF+xX6ECglUoKSt236UPNCKM8572n6FUyLIc3rOgBvYZLH30vr6jSbetqeo047kP/SRNVxnSMqFWZ3PK8aQrgCuwaLSVhzuDM7uizlfCYOD5ldFn+Fs1Qyoq1Zefvlg4Y5yse26Sk2TdfwklFAbtzmahj6u6AXe3TWeIvhE2ZlYrkHtkfKhyXQf+Hf7HTDvsphk/n3XQ93Y+PMdBcWOoYEZxxJvJ5BfCfxVu9xrU5XYyeVOOLn5fhKQszzYa7wPz5hd+YX4JyTjxFhCG8wLxoMa3t+HCJ/e0AB80TeAZ+jbiwI/mpmET0/Y3kXHTP+T1fdL+pQXSN/122Jp3h3LBE3wInum8VOLZHA1eRFyg9O8TwfCIVoUXMWQB08e16ykMIDG/wI2AmK59xWio4odS/KFvNNTBqIby0wuG2d3PRZUkCb86Je9taSoxOwrHTddFTd7r8MKyhHMr8SrnOqXi755a+pweCDQaPCJiTkfXrIbxOuGD177AMhiUSbnlQa8bcx4HLP9V6v/NBHsx50d1dDWEPICvMxsEgMt4133MGV1MWpmKMoxM4eUkWKkpTuj/iylnRLf/hCC2xGwrActKc8L6Ok8q+Im2rpzKy6XcUvNuYkSJZuk8Amizcg+nK4Tv3vCj6+1ZJpkTLv3SbW2c/Hj0F2WrLBYzlX7b+xUZl1fF46a7Gs/nTWxx2MtaB9EHITwCpBRpK4ap7rDyjoRxXep+iiCBsqZbQIRvO8Mrl5nU9AzL7uiyljOz7jo+dewJJMXzZLE8TEwya6sVvYy8lmRq6II9t7ptDIlOxaYsAdAC8kJAh9Cduhr77q0+JqZ4bnrJ1bpy4mEu3K58f6N/zq9T4AS44KOaG338LQ0wFPHe7701lrgoS1Qzb3dw836pxzWdEjRAD94fTk8tz/GgJsQW+I5OeZSc3Yuq8JCuccYFFLtggQ3cFNMOnjdPhdxlHquLudbF3tgwODFH/R7TOjVf3GcW/Wkykm+bHk6TJ0A8CRMnejVcDBWDH1XCi+euA6fBD6f1VeNzJ6E37gRFR+8gExSOFWoMrIra9rwoYmIvZn4o/J5czVpH9vs05Zx4bpekfmz7vKLiJDrLhu+zRHQVhNfhoC+9XQ5t1OD4SwCdLRiTe80geHP+Sc4eBJDw6fhc1LVo5V0IxDYyvDAEwbOPcbMWDuXIrOQ/xzC/0XSPx2zXEsVU+ASfRwINOGG3Ps8kxXRQWTgYLT+wy7HNw3PT2sn8Nw7f4ncV36Koyq7EJbWVDYmAeSF2abXqmJC8xcfF17KAsCErsfiBvgmBjXbWX5GJx6AmOfeSY7JhbPa+soTDQvnTB5ZKWF09H32q19jmVetxlh+aw7XPavH6kQAhiSY7RV1Hnfr0O8SrCzM8ch2cYIkJfIN5P9YO8pScE1s3QlpmgnAwStzQqPs+VfLWuW588k49Q2YTB6XsN777ML5Kr3JzzqAsbXPzfKnP5ZJb1ASuyLq5XscNcAQE3WIp6fimXadFLKzfDl8b+zY7zswlWkzXUT2VJciWGWPNdaryUb3ByBfVV2z7+0AbcxtKK0m2Z04i5yXoqadtW+PWZ34VYUBzx/uBxSBpSAuxvV9lejyRJv5X1F1lNxvu9dYqu/TKuhxQ18bIdHZgWJaQGnlvAqo7eTMuWC+iPLfbMS2NxTXAC/FieLcp8Z+UmpzvreXU99yQW7ds8g3zz3ajTZSiLnUqMuu8CGxqOydLHgnS+QGM3kE8JjERPpE4RQgG8XI25N30dlwOk7iR0iOYVSsHFmkUpVpf+xM8R2G/umqnFVtQyCjOo7ACrVXWDwK2X5jpo0yg77eanf69PCgmFZWHRxs2kQIsilttYgw+r3CwkQhDl8jJBcMoFoFjOu66WgNImCezQ4nMtDg/LKrQb2Md+Xg4Oss9qjbNV7kAVC16pGbfEoFBhlIqnsozBjnL5/PRGBRwl6Qeln3K3ymfxODf4LWEdH5AEap3DBbtc4EudhGQnS2BaKC8iKovfQ7dA+RhUCF/NhY7QT1jGRYDh7iwt4aTAT8vwlDw/+cmoHSyNHAl0xIe/Zq1zETmITtv+yrfuE2/czwxuN0Y28hbioC4YMitTl2HlP8fHjxw++eiULYEXCvrilSPnxxw9SEGQb/4e3aDa/Y0mxTjpJNrTMFOcydXeoznr87lros83DD/5hEpyWF9Wzsl4t1qJOZDLONQBI98cNxRwLDLIsjVT4k7QQ4TZsVVTdKEUOjS85WDcghI7wokyvaoh4gjJT/pfKM5StRYYX5MrVk7g8+yk+4P1889PWychuTZ/riW/40azvkve7KhKKrB32W7hgGBY8tWVqf2AAsfwnPfDxmAvIiRuiUmfIku+PL8s3R165GxQ6mZQzCYH/3/QclLstdl/bzjp6H8ouFbs9GxMhfUt7/zp3q1m9c/nj+JAU09JYdZdVWmzbhuqiCvlW7cOdTeXbmVODbDr+XXwlXGqQedXs/KlOrefhpZpfFO5NycAP6MisLECeQ2q4qyDgSxv17N3+3Uf/9xtpOp9qyI/tLZqE8wILclULvzn8l36r+E7fhUWEqsD0brk3uJvYeiO3gi2KD96rxG/b2zy/xIeKtDwwojaDg/eHJpLj2LcpwUrLm4VP+QNnrVil0MIRaVh0me9M1qQLBPgEW+Wt5Evf6CayjsWNj+a/6eNkmM5NWfIUgshHy4veNpYc8uyxckhd8sExlild1/lP27oDvqExna/qfv/HrpS/iAglMscXcynsCicFvp26IF4H787jyilHG3otAv22YCfI7K1ysPZ9r4sHCSi9EmUlH2zKIYJvzYX77xjEOiuSlqWSOVXYe7KY/to46SDNvMkWgX0HNEHIjS7AhpeoXD52U9sJqXNy9hK2ZqWFKn9X+A1VNRrJLX2bv46Dx16sQ5WXtE3XU1YcRWlxsZoZvJuPpeTBOFzk/FS3BUzTXtyiwG2HzLESmkCr56kdFs047TYBxVdOFcg2hh5+lIsE9xlDbZGZZN6SJzgxHnsXsPqL+3u1uzfH0iLyvoLIgjjnf4J3hvNJJ+TEKElTCrBfeQ3c/DhAQBOh//tdouUDc3JIGgmHbs3iOypFx/lfgUu0nLj9Uasm2uvB5en0JJzzUNV5MwaMerEkKhoT6AZFfoqGzcprrgm9WIzM3Lv08mpmwLBj2Wky7h+1LF+DTFVUQZdomhI+XXZ85eU/4i8bN/LLmVL2eZVabdUCFBa5tvcQHUGYhmHPrh0lQwpF7t5KVsorQWNlOWKR+YRn+JgZKdzgDMh/LQWNSMwRwP1M0XhJQU9r6cfy2BBxt4qF9t/oXDJJa6wZDi8z2zuVB3OsCKARFOMQogtMTUpHIGLci4opfteWv4ZuQTJVBWTh/CXZizZJzCEDB1evKGBthXDCryPgSL9HTUrryRO5NjwhCTAKZ/lluf/ThM0YbNFw46yUgKEuQVE0kbM0ao71cGODr96e2nLxXu9Zy8zaAB+rjtCycH9KtlDS8W7nCIEOtQhNTuxksy8Hzffs5U7AUw+ToLU/qEAgPMSOHmt5riYF7oyh8zHQt1kGDe8znpqhqdqwX24aQfjqL2B1GUD7CxTicuDTd6NAGilnsFmZyfFQEicAiU611QdXR7l+5L509ip+RfNCHHD/a4BbKOYOecWhnO6wlnps37PjjRH5t2Ts4SMRIirW8T/xgHaCMXK0e/CI8JOQ5idYxRrJ0OQlo2WqJ7AOVfnJKK59JyNTCg8CI5b/AlEQE8YE9aHcIlOM6lMwZ28rn6o5Nt+r9+gTeE0iPtCuCKDjqwQidbrXXa6u8FBQSE3qQAXRPUmCv5kh/ET7bdYrTw2or3Djmuxgo8s++gx1yKHxnQZRKskvPT76yoz7Dh+07kjzS9bgGS/zgHnk1T9pqLb3IMcDoP4oqGASL/k1VLq6viCnP2wpBS0nSrhKaZPjSnBQNzc1QI1357R1owOClBcTDVcgVqHMwQt3mKLlcnFJVFOI5PMM2x9dg9e/2zsStpmQVZemWcOwNNbMhMxD4Wlg73Vt8PPIyi4sAus36hbkSr9JtoF+r2kAOYjsocH673KgNlwtwf+/PgQQ7S49H54vtPuSIh5JNieLHwNFkK24uR6Fb1U2TcQsvAWPYD11M9dsltU2lo9TXKl1wnhJEt3IYwTy3F5Ph7mvM7wlDZuNkk9yGjS3kG3AmOVj2W0bNy9iEcP/NM+dZVxkGfKha2VdpR0DWpBjSO/6KkGD6YNsORdnVEMY+TbR1jelwpzMiFP2rx8Q8rTZtY2YDLDVD4PRlmFZfEivqmhcihE8O1yo2iNDALNi1zpVHJbDzb5PzmHyhkBVFeYTWPAWpbMzvY+RgTUSFiqnxMDSQVBIW9uajzvEijSuh7qlT/317IbtOLhNYtSZF1CJfu1Fe6tjz4UVLaju3l1emqw2Nna3/WEuOdiyzkmy02lxPe7l7QiSxwCdznXyHAm+qwv1cih13RGy4fMV6UYrouot6x4rv2pO5lKx1lGhmIRjW4fkxFrZ257sely4pSP0Sn2dRhpDtp/i6Otwf2UZxUC5Lo5Eu8jB+wGKS4ZiCH32p0+5NO/lUvwR4M/d2f/C1RoYuIJWmABSDhM0XYh1ZHgDICE47qaEQOBZI8FwCYJ7mr4yu9viC2ZGJNLxshh7VuJvGa5wVYGYot16vY5EZcvxYWrB9orATzgQarQQRx2Lt2RT3J2ut052xJpyj8tjeMTsnJr5K+JLtZOmRSwGGstP7O+BtNcySwCPCRHAST0BFYcNLin45lnmaDGFS+iYwaA8Mlm6L7MezMXXtBitfZuwzx9VbgqxGuLkrSKgTKx8M0Hjp4tzvGHkA7rXJkQLhLjTfr7VYM1b4cCeMTpzCs53dfHDSiPy68YShc99ELEOSwrQq7NPEuH7oJtdT8OKp8kC6JOHpk2eqYU+WH9j2sgWaihIR7pzJMetpcOxmueHaO+RIuqC657ycdIcPJ6Vu5e5gLoHPc3vNC6HP9w+7NVgmjo2aWYIyGH73iwz44uIlWjM8ECfwOuMxyFrrdQfPLeGoei62BfedDeb6xIq/MoDVyDjgHqbsdmf6RhPSpXtd6mtZP7vmwmNa4vvD18COczLOygTPCK+2q/ycEhn/+Y9++UI6JeOqThI8d+BgJY39ZraJkhUDpAszOd5QBqdL2+zmNdZjzOicHrh6yRkqA9Kf1aZkRJHZzPjujam3BLznQCBt/me1ICC4gNrF0+ZJhlp1lh4MWFsGEQboyP4BIpO9L9m9vi7zJgBLpiwpJitCg7aDtBWkO/EFe4TsDE4uW1ivav5kd5si5vExyFrN0vDKnGN/4FyYJAoAbDrF+ghrUSSE7G8f4X1+ujZpY27W3uQMrmRnYTNMRKwZ/bgKJTwR/3Rd61uFFGDpBcyqGl9BxojN83t+XqOpiQUYaC0JV/KDGKqi9THQH9x5uU5urbpkYE1i0dICcK68B4/YCGJHHZgFTGMO7KLHKO9XlfH0s5RW9sVXmGOJ1VLiPGDK2PxhEfFWWOhqZAzmOAfbmIMGMAxBBNxt/PpLRKIJNzvg/fX+GUzp5JzBCJo97Lps5Vgk7zzuWU/BI9e9+/J4sH6hMsCJybE+hLcL2TtXO/ANa2Wnlw40+8luNLcnw5Q/c4FJ7wK1eygd6+lzQ0OhsdfYh3SymYYSVXytD1UMeEZr1M6fuCUq24sFI+je2t5P8TdA7+nONEpRRZB0UipAMiFRQbwnpupBhDLTSv7+JnVEeKRDmseN0Bj6hYqTOvVpZZTTqjZX03+Fie80UDQ9pZV4cYOgR7HsQoo424/lLtaKE3z5bQi/ftWlVfFbqrAB14eaBKaIDPlYa68QApl4+CnC6ZYfjE0EobWpaooetk52p8rpdVDc5XEpDebo5hOeE0ScBXaWpQWybNab9ncs6knsOabbl/u+XgQWDcfCexj7qmw6pz8szObrJi7ZtDvyq0XN4/Mvyh5msgq6Kq/gZvI61bId84n2n6Jclj0mh8ktTMTsQd7iNGDQ7vpbFodUXp9tqMruavXRXXD3idGn7OSNL9+UgCVgN8invEzmdZXZPtEXdZqSz6ScFWmlqpyMlm0Ri+wX38DYKjKprT1RsTWW7iehBEL+8qDQe7HGLJLFXxbpmEV/Ji4u+SqnnzCnPMztNyffHW7rhRsawHlJivCd5txUvCfHy3oDl2DBMwBnTvckva2kNIBMoPr5HHFXCPsX3TueTbUwYPq4A4mvt0s0oqMvYnmXnTb/bCkIOIQkEoiB9nXI1/hl/CqAbL8eV6Ah+HGaEb9V0HXwyeg6Wt7JUQ/6bhEQAuF7DNl8mH37gfJWVeoehQtes0SxyctfHNQg9x3l677a24O2rwOJaYbDWYgLfieJXEAOXRHU4j8UdTOH0YBBQt4I3uz984A24l9bMlc+kj1bi+NUEhy2Ilj/VWAncYj1AIYuPZSLvrxS2a6X45BoW1K9065PzG+anlFKn17NbzzmBHz/VtNX/gDZMATMD5VcMkVb7bAsPR4U5mYzcH2D6bB2sbeVvCFW9jQPf3n9C/ubGqubXebOSAsiU6He7LFSxKnL8dsjRsbcsvBDi3CDWenegjx+eXzpIwqnKt8AkGMZx9RHI0bxnoIRvGpCeeIRgAqZwxHH5lyEbxT48myw4O+sBL3L5u1pynpckEq8jUvaSg4vwyqKokgc64Ui56iyYAmyImYeYHj2o+icgv9BzMss1MpgOXKeMJ981o2ztwtmPlE7A4wGJ5knJZL2v0FMD9BUghguuJx6BYynSB8aZQh3KTPKjLugX2x6pE1OHvU+D4k1a7YPHpAevO1Mu/pRsx+RDtYniJ1Jxn6XvAGNqcX5vleICZxdYOP+2NZQI7VcPhQJCY53yeS6QeYwQ4U9Rcg/3/3dD8oTebh2JvvCv22s9gHIycVUPT307Dv01ZmvWqN6WdEPVtn+XBkqCX5F7W1cGLFICENa29KTS4wLGtXrmupN5yBaRlnxpu4R2SRAQPDSdDsSq2lCQV99diwhluWjCh2d8AKC1QThU2qrYK4JToIBqbaIrRjNHT7/WzVnxlmktQMsp8yVy871BpkSc+lfnI5JMnn2hKie6nEN+aR0hL1L0Rj1zx9XLgsKam7qA9v5u5byHcxxJzvU/GSTAZqgq27QzDRSvrCRgnAJiyNREClREadK6pppp/2vln60k/U1M32nZuMJPpdoW5XeF28rhm9ps++SdDw5YSw0kF4GEMZ+aqmJBfLan9y7Q2F3taLtyeFjNmDXfBA9drbgaOTC/UgVDQcZDoX0gVjqG3XdEM31GpelBfOv53+35K4wkd2Hi795DV63/bpCfYR69YX2KcocsH6doOiGPs5usr21BXjXBGnbH1eGXuLXzF/y91QNSicTo3e7VB/4A+GPhz63zIqp0dby3qb3OUUSzbI5hvmTqxb3dIX8p3gxOghI1caMSpVdZi2y6nq033uOgOvbXLt9CRQAXULXGCSOdnBZpJRul90a2ynJf36l9vbP5IUA1OvVmeII+j6pQG7ju7+AzFFkWSasN1fAGQKha2inD7nbGTS1lonOfD8Crpn+m3yTjEL6TozjjkB/KPySF+tcC4n0eWM+Idf/MCQIaRKf0prTkkIm5E7yzKLGuEz6zRO4SSoHQ302si5WRwGV/uw0zteKVA/5n4kuuOz6FxYvBcmGT6HKmnqNxhCQm/6r3MxxT9m2BlhedUX5FGW9sVQ0YjKxyMNergQDSWTUhn9oP7DKfXg2DRtmyTCPnJbFGp45m2KdIjQQ0vJRuBLtVI9+cSz6/FTckwA03S4/oogr2DBMHzGTZxMFWh6fpRlUfXIxxWyHjGjPJK0JDD7Ox+M/3zGmlPASYJtLoa+Jj1IL+nSU5C4tQKjWzYcn/IUHGpeYozONdigOWBqOUhlCXjsqz0xgOg6PwuFt4/SiafHXl8B9Zhu43y73/EW834iOtONcN5UFoSx6u8H+I9KArVHsPv6SGLBjrIytjzcGgMRWjaj6+H2GJhdBIUqEKFXOx0qWXePdTjJhZHqeUc6Mu/yf09z7KxZBZMQIfv7pnbchKjOuEaCp37c5PTyWEUJfC4mWFY+wi+V+zc3Fhn/sWMfAchqTh2ddnpeBWgwzlVOwf1u+CiIqLuH0QTvPjdilaM9ttkF6pLSL+faTrHUrtwjdPjvzyaPT81Zs7Y0yfgkn4h+MUTBHvhHh+DhpN8YilB0T7cEmxiwN32XxgtAJ/ho7vqUU1H3xthQ6HTjsoXJseUlBdzPhNUPrydc+nIqtNNSmOvJ/Ciz6px5Gfa8xIFrcUee1PhReT+2qNV0/8nTVYq2/XHH6xq35Yu7D1kmlG7ZlBtnEEVYPOD7JflUzlN2d5d09PYH74mjkwj0aVe2Q9G5e5kFmbHSMS3VhmJaOojEfe+BWtJxvcfvDZURFYW7Ob9rLlOn+lpH0ye7dxvDuvw7A8v+JnktUyjkHv5P8sFL6XTY0qlrFw/lrmHxUCPbpB+3VMivPGjnLtYO9LdufnytVv17pf2b3KvFX7ogvJ+SjXTbufFr8thASoCw4L4Bu3L1GrvHig2IjHaKdGpAYxY1I5YidRHjyIQngAyP4wacMawyGbOrXXyF2GXBubQq05cY89w30h0fQhDNQhu+dBbmcGLxntRfR7bCAVvPRbC+glbKUWBY7J8fhUNvtQgPwQ/qTogX2rtzuDDFtz1XrnQ7gkOzBRtox7E+JFfXqWdfFjPHSeBiWc7DKFTIyhfe0dN2GrX3WakZT3Sla6/xsO3RAa7jogwCbarvv56fR0HXl+8eulK+5Y5WNLqNm017gwVXSxyduk8WM9DzwhKLrh79k4D1BAkQFhJo1Z2i8JJDzPZ69g58jsp3LTVRw6h3Yoqwzdifh1KPIweccpdGqB2wyCq841jFWQi86wSEHmUjq+dKQ2tPXAxCGe23C06Hb7eV5JfFst7XIqxzTSS262UohAxtSGwfulishpHyukSXUOAOY22XqE5FE1YZbNhwZ+CApUddGn5dV9FFXN4GJvMXdZid6orFvVSp5qhL6KOwW+2i5ZUWNyqNS1Z/P5ShTDv9R+Zh2cK+WpftBEWEqAvnxlYoIuoqE2RNm/IjMsfH/YDuk8b0njHOD1liHEcQp9ZMZp4PixN9bE3gqTO4b+KTLITgF/LBQUB7s6PHzWQfmItGpcP3bk7n+pvRATqljq3KsCMzx+XB1Nk3IGoER0gRp2nns5Pch7E2C3d8sZpcVYE6hHsFOUcG5nByTl5F6kClzocW0NtyR+jA5dvKshy5Ly7Wjx+NsP72yDPLsbmDKxGorFd8uxHUZJGO5rSctB/MKvf4NR0tj/rF3Qjrz16UW6Qv7SDTLe+rmEAvQmAalRnG0/HjC1DjWrjmQF4O2MK9qzhRBZB8UW0CMwzy4ya/Y1simdbruj8ZlnpEOY1tOLWazJMxlr5GmM1mT0c5+ktRqqIkV4sMUO7gzm1HjdpopndMuWrXUJFh6uwHmoV+botDyNcaafWAYWYTDpu+ugA7RG3gOUwD1W6j+AYeT6c6ZIteDEdshn0kW4wfj8Xo0f8AnSLwBTiSbkiBjqFgdymxK1Nf0K9Yw0HTe/6P/Wz0gfdL0/8fg6BdhYSwLJQkQYWrUSAC/E02DCcBJMexlVXP0rBLnyPr9mBf9Yp7cI5pW2AfHXLReUhHdgoNc8wJtfvpQOK2TOuKcMPDI+++uIxqRr6TVa4KqR6ZBFBbXQb1bHk6ydQnrbQ0qgil6FkHJxP/e6sLN9G76ZCp/7+2CtiKFT5UeYnEvE2BvyiQQ4AwiBol5J6t9pwjQfagWK7++F/ofOP2WhZL/7jp8rCG5NLAu/re8WR6j3WwhRLvpYZsQY6CRQ3x1VcqKIskFH7zEb+LxrwTSieBFwzkXhMez4hHtMnqv2QdYKBELDDyOaRI/SPGjJMqtzk1jXScByqvZi7Kzdb4bhEPZ07cVFU/+R/vPuU/tR28u7oFoo/45M2LKL1FLX8Ikc9rpkq7/StYd/Phx7BUKXoXfFgQ12LxM8+lY9AFmfcCIgh9WauwdSFHUPXZd2u4JxLbMfEjJtaLpt2wgmj6XJHeKEAOd8msQ9ukM8oeFhcas/0O8NejaYL2d+Hkmc1wjAe2Dg/SpderVlNFd7uhHUiuP9aIOAo47brliYMQJL7W/Gwpm9ZEpkL0O4iAJqQ2mRj+6v14pjwbZpzvebtRFUPbYNqLj4Y/rZk2KR6BUmTt+fv8ciXdB4a+V/oj0Mq95he6skzJBB3z2e5v6ASheo4V1dI/JW+Zimnwu1zo74MIqeVfZnpkalAjxP37OZFsKLlRSOXLY8Dl6E2X2NodsQ47j0QyTFU2herE667TfO534Srd5p4SygSVRmUBhzczeRJBlDzslnj7AeUKofBTgirMJ4C93UNu4qz4+J42tTwXRgDQVYKzVGnZsRw8pFUmWwdNa2gNVwJCu8jjbmrdyghm3+o91yLBqJUuXZZx3b+YLWTaY2jR0NyoAtL1arCq2/qjwILWe5Coy5IQeppZbac9MrtsKGPk6hf0gRGIFcYbqD1NdLwT9kJ7sqqEpx3soTFri7LSxvEH8u7rBtfVBGLgZpcza/kRE8YVmCE/aanPD9YPLltVY1gICxFF6WUClHp2Jw34h/YGgz6jPnSAapSbNVynddi+gnBArJiJr3xXjwVOrK0oI519y44OmXDxbrOXaEs/IE0Hyzfm0rTQ88vu8STlUn3ci4tGwHVG/T4zR9WbiWHwomnCA4yfB/ebiE7dYUwnwYQc6HmqQKXC/QotuqmXVmveHT9kAeCcTUvbDsT142CQL6wyqaDfxCPn8/qwAwDSfZE3OHM7Pxg3RUvmzwY5QXxKC5Wi4P9JGpihWLl1w6QljebN7DSbVem298krrPxSbRBuzDJSX9QhqYjrk787v3mPTwST1HMn1L/4HwMtOXwJ29+xuRkMO0zCIZNoYHIJRZZbTdLZjnaHdUu3nvME944+of8HTXgFgoTqMigC1iiuZTiW1ou3n0mglLH51Mj/hyD25FBks0iUoHIQhNRlWz9ASJhHTsABRHrSMppqdtmg356vAzCfJNhGrckHpnGItvDG2kxAgHtsTm/iIywCoKRCSoKOgGJpYh6OHwoQGe31x95C84FucP4KHp3AG5vgPdtGX5r2M/EoDa64hmXBxeub0bWkkgRP/Tmz8YR1RhMtUOGElGI0Aniqst5+UwQnyRHjMnrLmgeX3nhbIePFVXxzGVaPQwbe/sdBSf0YS9Mz2JmoT4yUgnW2x2T5EkW9YjpgczEIl2vP6LvN11iQyhQ/Y9rq8jyuroHJoBpzRFP8pfle3U0OHNlfWOaNYtNUt/Jkb8DpWw0FVfMt6CiHxRm3j9o/W768tmm/F/RUZIaiX5nmLycboNSY6emj7LXZs6g2sB8wNviTWTNlLvHU+6/GAeC0F3TSS7bnw5SiuNeCXfR8V70baUnHcEhv7XOc6YCoop8kOJ9kcbWnxV7gl33j6trWxK/IbfEyKilceb5eCUZobJXpeXr57t3SBIv/VYo8/2eoQvl0KduQpu/ZPC+Yd2F9Xir0gi87DlwZ84xuKYg7a+jhH71mqdJ03jNdESCh0vS+qsQ5Aee/xnI8wEjw7GVGqexBjweLBeVUeXEsVdn5F9uA7HdKdF5T+sDsLD1VZOiO1sQSfb3WGNx9vOccXFQddLdoq1uJMvwVS9BrjdsVfl+6vStguq99PZnltjH0vnCKhL6K6VA8J03uS4XF38aKd4nKkG8B2odIzQzPNFFSjbLTjOxgThctVx520qH1ZbXmzVotSiNVBnD7nF8wmcF71ppPyAfv66/p4QpHp94CouAgn/MoHCUROILYmQyJ/TYaKBX4hXzm8nfV0t0VNgOF3WIR332x7Rb9WquN/Ia6AZ9EDV6LVY444niGKYK9mSKE6y96aI5H3HD9mElTW7HoAfqv5W/EDr7necKg1/21Xe//kF24qBFdZ3pdEfDywL50zkAXMY7nahiiSgUcGJItagFOChviYCskPMv/DYZMxLYxwEaLV+dSgEpjZc5c4NBECbvSeYzJCnFqQpLN7VRlVkqbJDTJo4UZf845X50LTeMNufDAT9lQF8jTNf6uMTLd+4ezJGYhxlhfZRXrbHKaCkv12X1cGYTnQWHDMTvm5CBA36XXvW0R56A9CYFzjg/5AdU2pGnmJT+z2n+GQZOiZ5KKAniybkf6VUtXvh8JasCaBiKB3t2xwBqqlqfNuEbKJj+sczUqgxCGP5epRCDQXcxRaKSFWoaoHFFSAYiU5rNo1reK7ie51SOfdPnkzJ2Ijnw2xKhtnuiggHlUvIBdw25wLjLe2+jC15gwmplSgnFnXa6HMfaJoCGKTF8d/08yD+LNzPWnZ/F9OdN020JQX36BXhsdPYG0SgHXVM0pP61HGjo7jCP9Xbq3lsm7+AhKJpZ7xIxWPJo0v9uFe/LikdvJgyHQCGJbQ39OvnjF0ZeVFxY1Gdd1FzphUdEEu1wbJ93Joz81+S+UtqRITmNVb2y9ZuFFmargm5Qb4WmuuLVw9B544tIgqMHzwbl9gMtePL59splhP3DtiOc8F8Hc9Ad+zwMn6JVFYNP6rVHVUtTbU2WBxegCJWuzJ22SuwBixPOupmVAoPrCmWgMoXfAE4hcuLCTKM1XUgJmEMntCExkg6nizn3zVENe+KQaFdIZA0iTxNr29h/ma2BL4v6pAp20X8uvn6Ojac6BwwcCeLndyZV/ZvGzt7Ln1LoFK3zmnh/X7aavFLgq3yl4aNe/ETLRFWIMziTJamIHs5fiafsr6RDpNNo3J5N5CJxt0To9qPceJPXADG/mdI0z/LL3NP0Mj6nTbiLjsET5PAuyqRDkhpTNx0FpCpq91gFxVuOyHPexsiCj85xy+hrdeLwspMAmqBG2/KrHSp3J4rjEr5jBB2eAT8XXNQJg23GuYGulBEXTA8+aJajC+9sUTdVqkNfh32UKlMv0qHFkGcUX1aW8deXC3bHr5YioSjd8Tv3iOBsQUgnunO24WuY8VsQmVdljiEb5mG9Ikz4wVpEVOu8NRFMmIbzUzUrFxqRfDeFCJ7C2knD351VTVItPwBvAqJyoGNenXuDLSlOm7TyI5iYlxUPpVZWFSolgwQaMWdKLbcbJRKS5sOfaPtPuL+PqCtCNmsSTI7NgIKEqlmHg7ycqHQN064HKIKom8hWb85HgFunTjZlGuERmoRpyPzziNJ1poXI+HGYnKdSa6OYLDMhMewhQFOGmBL4soQhjNUA7xzDop7/yDsz2YfM4W6Yy7cStr/RLIK5F4NMBTZ07XEFSuJt8F3/0RB7lKjsdCRVjD0pbmWqC1agh/BvDc7lbwAOk/vQchJkBAwK2cBAsW5KMiFQcbDev+evZQeMzfpv6jJduLx3QVixqgF2Cj+vn2fcXE2NwkILNKyRiEttoXACxO49eJEUQBhwMdTS36ZqSanx2yzeWz2uGjS7c7Pxcugn0ff26+2y5XW5dwfEwu4WP1W9PZuXTSYkccCBsFq2C1nQh6zXIpXv3FAyEQdKcsR7JKn8NB5+2mPPVjPvcyeG7a9DrCTZjMe6dVfg0iF2FfQVnR+bjH/luS0yUTYs9wr/vHO2lsv1R7ywLz4ekdnKmeZ7YbIMG8LmAKxZGvbdmQsRBoBjnkBRg1/NzyZ2iudj6NBGwrswpl7+njRsqcdvQ9dPFWot3CMkyJPSMFKay3GB/W4xcIPTDiegjzZJaTSiiNPyulmum3657suIyFlDV6sKfPHVIbAzF+WdwzDJHv/e+YnZMUkP2gdtuY0UcGbn7zFH6533ztig70O8Kug8hxt/+jlv+UM0LFCalxPtNKaC+xuOFHRvqF/YZOLYpLaNV91CqGd1dCDATGYdM2BoMDqUmafw2mHYFm/GRIn1auZjD4+QG3SaA7Lxp6hh0zwUfD6LyDWTU19/DDohuI4LZSIxJrv61f6AMFLPECwbubCMfBf1GJ1p0QgMnw8GeUkgl91v0YNZ9c7lY2DSHlQ1ZkpQPAK2VaNcP7TRK5vIoIOZw8zREkBYBjZuqre0meQOltoiqzRPoxzGOzywUwWDv/8HxWl79pcBwQ1FRZMaUZWbTZ5zj1lOLS3oOrGtMFhDT/lNeK3WzysSKZr/Ec3TgD2zION0CWoRbOQU5DDYCwMBhzcF3QyzDFle9oQTtaujXE3WUxwhPQ/zYJYch7w0Bmwu3Z9ApQftpx3JCDol+5fXlgor8YXkID8aECm5A8PxeZvI1ES/EVKJIHIIAvkRP96FK1S+6ZpKywvfU+uqZfx6aIfp9AKUMCSPT4BFwaTEyXOMN1gdDUjTEU69cv7LrU/wG3GYXpqQ52LT1SrFxw7dZdNyLcRjD7Gtq29EmHbjmG17JoHBCU35WNMddT/DM9OtmMke4r6TTX2zgNi4eMtBhvCOpTBo92bBwp4/eAJQ58IWAZnPPCH8dxBGNPsFJVIdjVdez67igEepDGROVKdLL5IeYH5DZ8NfxIqcQTfqgLjRRzMhSUCWSS9xQWnLlB9FBdB36jntu5HNMNT3rlhPVvu63XDgcMYWmvYZAx3m6c26Qf7QLx31dsIs1DvaPYQZ8hdaJpgU5ubgq17xJ6unn3X9BcRQ8Xg562rMYZCuYda3d54/AN7aS0v2UKEM0V5EHWQs2XLp/juPXPWiRFbhzIjks8xKnhHmKo/hCy1jw1BKjdSE6JAPYVCRf0wlQb0PLqL07+xYySO4ZpVNpQiQrCVbUk7vYcKy6JEh6nbyRxSpvwzDKVPtuqF55JgxEIKGTkFzC+QEGT23z8Zwj2jC9+cZf4OtpNsGOZhn4xcEbIFsR03Ez4W0b77G5MXyjRXJGNPHyPQ9p/K4gAfUTRRgw7c9F/rS9NqjP+TvdDJ0zSb5APfdxz0e9LfPEnbFsSHKPz6iydVABASnIQUs9Rzowwjqv0WXdl1aJjkjvCfbpg0vVJoOpzz0x344q8wVLcbBwP9mc5PPpwySlZjc/Yo6ng2RL/rd9opjwwzjx5yHozZRVWJKytktNxCipuWfp95T3I5uHgBpIK+J71Zf680JsEOA9b8/qH5DGAB5oGmuMKbgBn9WKxHjT7ACisgGbuK56lNnSOSdOTKfRklaOfIjvi8qybwaImQsOr2/EkUjQluNuuZCvAGXLoqewYAiuX+aTicYV+RXeu8DvtwiZBKk9T14cQy+fMbrclaVU3gCgufw1dK6fiDkCdY2rxvtZEgKHj5LbfJeajCrte52PJnOO5oMcZLgDeBZCrNNtUObUsNYdK9KwqgD7d9INDdld2qWQWj/X3PS4jHy9ou0yPNbVMwOKp8h49itPhmDEg/o5vj25F7J19ujyWVznY8KbMDBHg+deORyT2H7Tu28FqO40E242l1tvhaIa9QMJVqIsKI6mOaUcOImbqRYP5qH/WFYuxCgnNnFkw+h5udgJi1c1iOzDpHwEf8vup2d1Hh4BfNyfl1NQj2CazEDHRpX0zWxFDGHs0NlIpS46fI/7QXi1antDcdkIekr3A0J16DlIZaZjgIf/p05CGvSD64wUQW04KdfItbSvXrg5Eo9H7Z1laqwW6Byyz/Ue1qtRwXy9QqtLGbo/cbAxJT28o7+uqGDOZ6bV2fo6Tw3xn2AsOezgwZh0BNpBVyl50GQd0GR+eX1qhJHyeWgdNe51Z5IHAsNKpmwxnEXAkkrXgkMTppVdQQc60n64HE7FW+l8BQGDM2RLYLilMhXihC3+IEB4SyzfhB1vuno4+PmXjbJ2RNKJ1R8ShjGsFJ2owmh2f1fR7HJR2AOQ/ogMJ6tzMD+e98KRyh+ocqM68THo0lsrUWFSr6hPHeMdoiB+Jt7mWm3rlDf1+4x0/R1tmPAK9ZI3mF0Xbnk01vVU9/dwB0Xgo8AfNBypTsD3N1xbfepr9W/7/cLHoiYDAWD66kWbV8o384dd6WcTXPZwwxdP6s7fvV2Z5+jeqXPdxj0XfAUfYM39yXK9qU6jkI/soUIr/KcHJvb3E2YVWAYeHecjiNf8s4op6i4Lv/IuyToRElFTCVcC8um36yH9oQTJHMjAHns+uMX9iQ1OHdxJP0V+a9oXPs/v6OdCkWLJ5a3eYZlirnKHGPjwIiBzWHpwzKWZyyqkSPldG9qzgkN9HyyZHuRvwPAZzF+wc2NWRG34I3uPbx9mzwLPCyP5bYhP53+iR+37ChOALprWPhTMJ5ecZ8Bv+wGjELhAf+6y0hf22WS0ii3ceGbeOctysxYaeKG9NiG+91pnn1F91DSyI7S5XFxYoxONbUnZ5Hnl1UmmCbqU8/1oWORkrJoptmAnKHYL/ve9EpckGoyNxt/A0nZW+RIPtWSCkmSlqasAZbX+tXu7QhDXyd1gjhlh8sOQOzn3+HqZ+fRJykvswq8ECjy/AXJn+G3kET0H6Iz/vJ4b63MZGWe/oO8Ajd+Rxkdr0UeG4AkInV80/9dn4rdAQ3qlEx2tSK4MA5WFWo1hX4rQRf9KvGL7baV2q/UOt7kB7j4LuXAg0CtOTlnPm//6vKJKzw3QHf4uaz9ArNKAI+KuiqclnHqFv4XoWnuhqHOEpe1yPEDOZ5w9WZpTaGJlVBNewHOPf7COuNVkzYfcHHSPd9M6Q3BgFFlpg17nkNwVBAE5TRKau82TuW0LN7PjxdiMFcY8QxYKofA4mX9E2LhtX4ksnKrbNk43cUzN4i+G9Y/YUi9zIPAnRQuCW2v9Z75wk4EPwCQheWgtKhS5AQQCCm0XIr8Y/JQzN1TOFI2UAJb9Ptz87l23NBuq1CgQec54XXxO4Z8rTdOAnSDJiiPnkG8PjrP/3vNuyTW1sRFSM54h9KoWA2M3ZUnuNsTqM+23/lQ9NjF65fOCEZgnWoMPnfMCwgU6CGcf9+HIfgwLjl9nYQ/7BqsSSVkmV5rni541wVQTMG4Jd75HnMqW48cTTq1lFYDt/mR9zb01GKLbxqZxxVpkvn7F1g+hEQEQY7W7GT4yKX1z1vEwGZmgmQpcgBXXStXCBKlrCQkSabcFgNXCmOIUmVFooKa1vVPtcYK1vrlvq7+CROKNCqsRjKeN0uS9QdmN6WPyMjGz08soV9zU8mJQr1Eh7BpoeIDbbSdrL1/iRpx1pXw5fTqwtzIT43+VyspB8XZ6MQypxbribJ2kPkgLIB4dF71OYpK+Cv6E+80PEVyOUkSN4xt53BuSRyFNhxwilQWL3+zvCAF4WkTQGro/mFzz+488e3uJKc7lhr+ge6J7cUuKO8shJ3zk3E6rojn6s/fLIPr6AH0SvCATEyvKBkxKj1UV+OIHyVeIUrDP4sDO5c/vft9rSWDV1PxzcOuL72xK7d+aqGLGvges4+F2DB9NsP93BLVscm/owM0zZmWMg6Ur7LpvNjW0sV2t6o8pn4kGSooFAq+Y4cCto02xnogCVXYiPTr3B8RTLckJr2CBlg1/ynxVh2XNlZjMeThmg/RsP4cIdsfXBsbfWk1RFRrMQV1vyo0l7Ej4vlHfVQDr+1906kpd2lz3MLdO6yK2IxzJquS/AEvzBOqgHskLaQ8gTB6yAqDdvdEk/NgvW+1oKvBDKQvq53hLqPMo5S5wLvTVAyEq9uATgHB69FGGKHnsO+9/iiD9XXWUK65cQG24iEgGQHm+iesHNKF5GQt6FlXDAupA7Ts0dGEBKf7JeQfcQgt6zifqYZVR85oyinr/7GxQ817+vrW3M2Rgse+xgUethbttRUhwOpzb+6xDVz++j1iQnrSjZuiY6ird21fXSvz1yxeARB0vysEinhsS06Y6h4G/xSBlaowJjN3hxw61kNTl/ktWvQbOIOvIhVid6FwNnH5goz8Yo5fW2alDW4+wEaRvdYetB/LD7KLutcZGbeWRD2cnBoww3IF6wk+GxV5m5lBrLDYm5cFg9TVf0d2Z8GWLsSFk53Dsxt8wdl6pbZpwl4yyiepUQOBfARMWhoEElbRUFJAAxl9BvCjbAh2z8CSSgyv5xCZ+NDPLkDzuk4NL1sQm24fHU637f1wLhW3RY43askh8RSBb5B+uI0PhqBPzs9eSrKqdk+8kwc6ROh+IYutTOzB/1COFk8x/VvVWTsAC5Ae3bCWcpl17lQef09w35QSZjibqsOsNg8TyiouRQelTB2DgUmzPDy8zu4bv1iGB6TRcdgkX30a8yrvDgeFt08LNNAOJJI6xl6DDzritdLJWwppRLC1UzmZYwsq5RjgruWWOGSTw/M4lQnQe5nUQM0BGzY1ivpGEhjVFMWywDbWHNe6mzLxxPl4xgwZHas+to3LMgxrxF/GCxC/poEHAWT0yUcQC87ye6T3yqQpVMIGlMexUB7E74H+2lYykynIRJpNYtyLimXjMz7gcQfol6kzpM5qcFPGa0Nh4laZyx7xesSO+c04hmv7Lcd2+Qp3v1P45/Q19mslCm+yWNRervStQfJWc/cETzOFJvcJuh3f36gZbHX+uodTKdyoaGQeOPjEYc/Og3S9IVNx7endwrOHWB3ZKbWJH6G1WPQmQ0tJ0Suzaj2RmqYSf5gHrxCUz/epIh9RzHI+AsBTuIG8uX2OCPxpPOT2RJ9rly15M7YBQ/JqY0M7L1f2xsUbQANbCP7ch18SWXG57lbiXY5/DN90RTZw3/9jKhxESuDs13xuDfV35J7RV0MNE+l6R7ecIDbhTGmCEu096AzT8api3MZ4+1Fn2QLudVeSYBl2QHTE1+hMDUVosOHHXR5up3YxaU51EYxUxUo8nXQzLLScStaB4Tn5TIqMx6S4Q2Q2tlNsO4l9BBbYZ/uE62xuIYNuYYd0c/h2QC0eyk0I9Mb+Qsznuf84CAL56Pdvh1GIS2TfKwqx+ztHUc8QoZnL/G17YUdHV/SwuK8vdORc/Vd4np0Vyc/09tWtYe8IDLGaecErxyGvNmBp72ulayPecBhQqRkXp3oiyPld1DH/FmCpFaMZEWkReyFTI+bhqYmjGCE/rKW4b5JdWQt7Ywi1OEK3BeD3A3tXcCOVM2xRLZBx57D5jdWhS1vvod5LlqmtWbWshkFyCiHDDXPF5VgZ0gbQZbqnfwKbp7mbtqu+bV1Fii08AcyMzJczfRYGTOc1X2c5TM3Ae3e6yVpwsreEV+Ri731Es4rapeszFhX9uH+XlXm3/BHmX09+q4h5x+mUEWUIcDW3qAwt9vz5Rkm+LxLt6YnYEbMc2ezH0jFBEGGsaVBxfFrcX8tMrnwoXGiI55wajJY15lBDulZs3vOlVdLdBG5v9a2bCcyqXsBd5hsshYE4xyaKO6zRGouCl7BF531Ng5LWPufUoMtdFhuyB1scXSMtBpUBzx336iBhKZyZwh0ET87L6roGfu3RfF3E21LyYqFXa7wfVlD+1PQu8QKRCFGVoyKBUhl+eZjaikM2OqS/uWnl1WTrbgYJHS5R4Smy0b5UeWBTtzznz0ykMeusyjsmB7s5um90SWO1IsIvdl9sEwGv3i+oNp6XLFNPFyM9LTm20JmGyKYJHOfF/AwrNE9ril5c0nid5PI7l+pQmbtye/VTkR1fG0G4bivhEmuuck44tUfj/kEQe9kolbsN7CPnlv6V3ozbLw2tRlgTBGf9qTbx7DqPb8HR0sV/qxSq0FKNUQkLx1424Xg7uf3N3UhCrNmhJExmuZlgICXCkAQuDYg/TuD+G74m42j0mXVqjlWcbyZvlS1bEdd9vPIlySvtgm+IQTqBPzmA5hP/NCh82HewgAZEwK1Vt4Dc7szvpoYxXWxKgp3ET1O9yIifSw0axSc3czr77cTwQwa7NgA1mXKQ+c7LXLRyv3vK5jtn0OBUqdRwMBmVxcSjNigKyAdm1TrhqAg5v7NdY+qVywFxvr28oUydjMPiFTaTFSxhBY8tB15w8ZniHai7Vk9YFvqGZb8gOsnIG2XbyituNM3hWtjIbe2ewnODmjFcZmkYIbVAnheViEMpr5DjvW91b/4hfj3pFKXFLW/1YCLEsEN/D7SmREMXrh+saoSmsh4VAjiSAGpXycneq8Z5t331XYCMNPwWq9FlvUObV00dGoredaOBgjRclU5Vr8tH/gYgIdlubh/PvBSICw2iwEGkx99RdIHxoHoA9pIWYO/OgEaSrx4WlVXAnPG6xUpIOHBIZoxyHPh6WqoFyOwG9quyX8JQSsrBtwxz+CMvA/YA+2tYwhGst/SRjxuZX9DxzhtrkfQp4YPN+fLT3GEMqeSMDImTJ6aBpEIp+x3PjvwGl1s0Ftgj7+EZoH2+Sr4VPmyuE0GzwcZpmKu7sdyfdFvo2VDA6yHEO7h22SGC/JMO5iwszcAJmC+9C1xnLEMEC0vhBEjWHjHU9gv8UNzQu/tjxV6TNSoZCzoCVQtzjHVFcuCnSPFD5mVd6UcUqa1C2E084eh4GVan10zIoLhjgPQCk0jN+px2+ON7d5mncUKC1Omo3OwYrJYuMBkHHsieakr84Uw5CS5GWUh1TRVNpIFE/CUVVfzbeX9uKQ44ao7bNqAlRuyRb/gkulltY6p46AqsE1zNGTcid85P7VwUNGNWFm0Sytq/DaS0HYK0wKm2UPtgpIdggfjoNLRWgCx773JH35+EtPOaxtbHbkeySHEsOnZRLnkCUC0urF2UAJ31Ez5MgMWTl53SlMisW6xQS6PTTRMxDR7QeVipWbr+k7jIAeNwjVaCDi5471TdJ468KKCHeFzpVSovUzUaib4etuIZPsDZMrVAJ2fuh8w0G4wPtod/S1kxf3jGDKlH1885kP3QeDlKWEy068bOjhsNzjoOopC3AmixvrfvWLaFEdiBjfh43Gg1yVkNG/UGY+eY5U3Kyc0hAV2sLmg3S9LV0RqjkzmRVYe716dEP3PMVE4KU2V5JDhIjhwNdx9WRv9CGrjqUiOY9NgedWSktYvR8iGbLm6uhglvBwNFQG8yvm3ujIGhy1zDRc0QhGHw91aUDrP7Wo1PGVf7uWmrn+LFXW+XpLNaM1t5y+wfg797wP7ewkdx43l92uccPWMkPgnTP3vkV3sA99MqFZMifuMzMlfAfUp0LELfZLtK1TQGvErY7Zl8h+vsNf2WBnQMOLr/F4UkChTxgCz13VK5Wt3HrcaXaI+knyoeu9A8/jf3HTYxGjT9I0hk9UVez4qWngva7iNLusYOxXucS0eD5a0TCyouP97PutkPIMtRiVmH3Vds0HeMBDP1Qvnx7yggGtJ966R+CC4O+VekzBg8V0EuHZhT8UbJVPsJPU7mUUeTM7J2A6I7f2mm/gjWPcekJRRt4Vwux6IDffd6AE5Nggrh9uyYyB0MZlj/Gm+NVw5z1zug0aTsP4eHYud3W1M3+tJn+mgI/AxdScSKUX/A6jQlDPRRsZNyYFxdqxbIWeG2Go90lQENSSDNhRBjLF+xC2qblmvAhaNNIDFpmd8Iw9XF6dHANu+mvpZ2LhkXxgqlij7YQ98fpFNxF6cEdOaVB2swgR+gyVJnFE4AuQiL/ZrN3GrhnFGHO3wtHQIF6apVZCqk2/hhHn+v52sxyLtdBeoAQCzdOXwshsaaDSYMzBR4bRo98OaaldvTp9g9KuONPJau8pwRYa024nPq58X0xAwelGq/V39nTupBNH8Um+pcJINHSD9vv752g9ZigE8BqNHGRRDGpMZnwqT1cVsjYwE6td6ptGjRbxgGhwD6iyTPNoBkWzC/ABA21xkaDSpojUuyNj2ehCWXRBvqaAqJeMbtfvk5y2YAINUNOBHKIy7B1aC5zLFd09WIC22KPob4ZnR49JGmFweWNt8rXgnH+BPT6GXK6NKdXU86huuexDc3lOrkNJL0ewXeEAsM360y5vO+mEy4X0liY3ChHbkFi5u8NiiBY8N19EpvhCVUzSHqpioR2u4OAgmdXTs71fLHUX5It4z+le0ngrrPqPZpAE0OIR4u6R1ijvRoOQiWN4vwdxdPPFwvxaq+vl8jvkPkeg+at8W7MKjDJSgMVxXwcK+X8EjLd4XJO3LAd8cRhRQA7PO6C8hTPNnabr6seQLnn3GLODdx8zxJ2s7hlh94iUHD2ho56Qq9ElQoiOf9oIV3hy2f81Mmv93ENiqrmFTqK+0tg8788tR+7bE7EJuw0etalQPyzsEgITRkPDyBFKKSNdU0N3IA1vqZ9PGSpsFBWrOWGBqhsk59tXi7eM3Lkh/h6CA9f2Y37ly4hEIU9xc189OukPEwFnfR936NPz6nYcUkLNB0UdTxSzYG35BoBYNEy56qW9pPncFFTX3CHLkf1e/+hIz03pHNwqgabwyRqlu3ma4HDIZ4sqRfzBvRzT0noigeWWmciFvzNY7ddj9/1+DjgxaJ+h4/KVhftC+lJ1vQ5Ga3jguItO/EvZNMus9NxSllE69CqHQARjvhKsavrxlmROfC/FMVoKcVjR3uIvtXTmKcYp6gWXXjrazcwVd46bm9tqdqSgQyzoR+1tQIKPByYTNGRzm1tuzdIedtlZORLeSVVYwc78GNVvYQgjn3gyHEbvyRmU+M31MJyjv0ior78qvu7oUhA1opQkW59aNRZq867sEB06y+cqz/YG4Q43sgVVOTvCdD9HU/4FjVgYKGb0PiUpRlwvARQ8v37PcYIRlVqwVSMuLOL0qSSD3/5owf8gfSCdMPfGJgL74Tik3gHgZdQU0KrIfWoQZRYvraOLDLv/TC/9o//LLAmr0M98vygifyErKIp7zQZK6bNWfExk1B1Y27zvTbpQnKde7ngfQgCrZKRn9xjkWmEL4LvU2eMHflySmInsphEpp8VtjqSLoceCZRfoMyyGXUQETLvGoBQQvTVWH4hzHn32Z2EzgDwGs6VGhXtRQ7KD+KLSmBjRyd2Jgdgk8direbllS/hQDJPq1O2xbnewJ2zDN2zb00X42YZMJlZUTRxu2SaX9rXLkdkbLRkoVZPoyqTZijGjFAl94E7flYLT/SWeiAJNgbnD6yPnrbNPg9hBulXGGnEWMOiGTUj9DL34vI0K382lc8SysBW3SJd26WNnMEAbRzFyDz9yqrSNkPsqFkYtYmav0IpQcvtKTQFhaDjXNMjPmJ6dQnUFL5N5E1tBajaDpbTZ+NNEWU5gxxidDNibXnx+eArDnUxEtIP2ZX/iuB7DAUGg+ojHrFW6T1QJGA5sPegmJeSLzumJWW0Ab0E/IyOFNqXZZt/9MYWgXacdiQ1gaRPvFqpICI0GXQtXcw15HyKBuypxPvT7Ec7wokJYnRK7DXwL5AhuGddK9f4WYFq0RcuYq1oVZX9V8rixGeX8S5mUPplcUjB9i01Afql/U8BB3MhPnVan0qYkStFbj5O9BfQ1hF16l+TmFaGaZIKPNA9yp96BXh8LIzw6Z+L9xQ5Dbv8p7TpL4itYRBbmxrc5+tb4TJi8BgdVBL8VcQyHOdgbwcv4B1DztLOKwfG/3qjUkA3AyGq4hpEELO7ZdlYlSElTyCVRHkYtLWEZhWfCAv1xf9LPSF4oCR18/uUOHHlaDXox/bw0xeXpovyFtEJqKGdNgyWuSDOtY8BnulD9PycrCZ/NjT0bQcubPbIZkb1rMAtLkjAbGtW/S9u24Jr3jz16ZlOymUjXr4Pr5TBlnnKQdSrEyXfHqCV/g8seVIZwF8sIHb6AqXJn+Pq9CEY4vsGsKvZ03hTVI71LoruGVopZ8sxFLwZo3VtlyWkZLMdwYTcgu1mw1BTXP7rvmTN5BQ9S9ixO4JE7uIflMI0JbLkt1ng+POQ2NvJIx2KOmSu8tCx/jsWLj7vdfxONe8vTRn1P1uP49S+L3tgR2BRL4NjIpQk0uIT2ZGtkHScxuR8F55+Bx2toxVyZOK6BzT/3aLGD4EVXeQgjfpPqDR11bgqWE5WuDKN1fbbgiPItbC8GZ/yqov+IauG8ex8MZe5ciE9Bkz+5fjUcTnHpf1SL8Nah0HSLKAXoILnjjjc3QjoKP+4vZToI3ev1Sug/gjzfEdMim6+yiVYKgvHH2e4odAJUlvdsYSlNH6MFPR807nyW/2cG0BV5q8fhBvZad/fFLB18W4Dfmr8gRm/uunvRjMjgj1xowkArfDHOR36o/dK5m8gNypZCxKchfl4DhryhThERSy/A/hhXVrsewS4hoJHUL2evEexoluLoyG3MB9K1xkVuW4feAP8cXYrUBJ0Q5t6Fjio7QnGn2UG19NKQZm9pXfijr++alA+sAiRa0l0WfD2N/4dMgxCF0G2sSnRCjZGq9h9mQ5Chd+6OetE/IUbK3QcNpJKwnr7jbideUZO7+sJcOEyFCEy2MPDpofkvrHS4mVgb5wHrMyqIi7Xi+Fe57lgjANny4klNqLp6TdW1OPt/vm7sqlMGPlTMbLKVQqcrDJwsEy9Nunv7tz+Y4+NkRJtv6rHsRjsyOzeXfwsYI6CGRGdtcFIv/K+2ZzYeu9OZp9OXUEBOCYN1Bs5rhiUcTolsL0xKaLcbZ0Yv+o0GBwaYAeSEfk1L3DfbHn39G8ObGFNgkBY0AQseW5sw2oaDCyF1aLU0X6vnhv8KRci/BV/5IqvELj49/DYV3N23fTx+20M4tqeexchMeBXX5GuP+1loPkteX8n3ZAAV85vhizqYodNDIEG6ZiUhIUA1rlOMpjepr3CDOX5EjKyNYX1bFlk5NVTscjNk0G/v1MS+G9NlKujzK3OeSTGMhmkgL3dtKLmbIWwCkW6m8xtNqCvLMdegBSVl5JekTk5ABnRawKKTtyNMFe2ak+pSrRyFfyKaevMQkeTm5ZXZOESjEmHGiKdPtw+bClxwRdZdBhDEMqXRgi6ZCRKIpGa4Wzm8tFzwje+TODd1lKJOH1BrSSLjDHRnTO6jytVHfCAwEt96B0IDEvBQoNm2EujwbWJvOZeZ3R2w4BOzX3CA6dkWli0p5fRKckSvxu9HBf04v+kPSAVv3JZaJbXgzLYXauha724ql7JyiBEq735fxsU937bXPI8Q33n+i67OXJH1Ev+wPp/BD2YwtP7B7Hx2FbVNIPD8IssVxxR+Zaj1jDuLh+K9wqqYmTLn+TnUSp8OVHtLBQpEw/kXKuLePsF+DynSQUgyLxg16u5O20gwSiG8gL7tZ6GgaicE7Qvteh3dFEEJ+F2wflG6eebQynTVAmmaz9wZ9zJjST1AQbZISHd0Hfl8dj+46nOyyHv5H3FrNmTiFj4r8s0SzVSGHiY+H2mmmMlkg3z1BITDRbnxKKymg5//UFPriEpdwJJUt1TzrWCt1yn9/ntDr03aaTgCtK3kJKE7XdPjkj9YSz27uAkF99K+Vyyg3YUR2S1vcM71iOuSyCz7iDTPQYrYrYDfxpBGzPVdvwaL5m5YilIDF9AKIkln+GCpc22ivWyDtK6P/F6+2E/Xagpco87uJedfFFUuEdGFfsOjlcVQDplF2i2tj0vJsF+SOPKIEV+3ljVx7epUXamUkm4RBZs2KWTGeRLNEfVen9QEqisXN4hocHkyj9dLS0mghbVCHjCygRZyvgj4YIxeVqYK1/f8BQJL5IFnPSffOChTer5C/8Aqe/Cs4i9swxDutZWI6cIgDwU7l2V3JlwnSMrcA/DlC1m790vYRdQOFmJxKNvRfAyOEBgws3L5WSvBvx2pHmoklg6FkYw0+18wpWHJkWBp8rgfKOOu726RG3FCdOZAkp5dqWPmiaSqqCzve9NeEyDC+BPSd4BD2l3bP0HGD8SPm/GVFchMaWpwK9kEn5urpI+slUHDCpPhSbRxFhd/UjduPOP1EPvuQ7KhLS/DwApdX4I6tjcitRicM9LeFqJGJHOHjRMTJVNM9dJS/K5BQJae71GZHGS+OdBNA4XDmcp3KcSDsj3SOtA2VusX4ptjjf1uuJy1hZnZC4/htVkrRiyKjknSygewZprGuSsEbBZsdurZ2RyxNihPFH7iINb+VJYeAHNwhrr6PClhRHeQO84ITJ5joVLAPqz1DM7Yxj8+kID4hPNb3qwqWqsFz6rOmnAvuxoNjP+Fz8pk0y/GibFhGS92xuRP1pHgOwx4qA8dn2bZId4+YRkdIyKNfG0q//olXouc12IFPgk8nz3qWzCs02Ykcrigl7eZOPuRjFMnrsKABeNNY4kk2PStFV9/yXnZXOyDP1IF6IqSErO7eXfIwDKWx1e4u8r5bYUBCwjolwAgI+nCL190HnK+uPP4FWZZNiXxZlbCSiWnS54IDYQ60WieONkMsGqWZDA2H0ssfagXRTpQsn61Jsnrlhtav5CS3f2k1nO9t3TTKSZBsl5wO7nPUlNWa4Z8sDwra5WmVdh9FaMhXyGLdy/teSOQ+gTl5PBD/xGLuonLrgINUViAuvPeVhBrgkW2VjMuHJzqkfH7kZLhW4os5PTwGwvf9sWds0o5Wh2RItGRE0G5s3Q1s2b+1GGYtAqxTZ5nrU50ZtoZ6M/gxK6PZ8VZd0TKaYispLrJaQsQHOlwqQR86Z/94DPbFheQInltALP0pIrRd13TicXsXW8ZjIp1FJz+/6yNWDUSgG+4wkU+n9FGsOdwzkWuKA4SIBRRGz6b2oAwQStzVvGJ8XLZQuEUe8mSda6Y+3vZ16cC8+BcZ/3awjc+1wv4J08Tq1bQSTLG6ROWeGixyvNA7t8elhb49q2udxlYCAGuZWDEfhBBCrImyylPFls6iGNR1XwpSa/3Y3dDdVdYK3Q0UYX3JSYEvn7makFuqWCQzTerUEqmzH/XUvTy18rkQ3IAkpOsyDEcn1J4goiCFf4E2GdASfFaM6PMHS234Qb+MyWrvZ8MP+utrfFF2VcCZSGlXZOHe4vlgUN2pazBja1os3XmMNI9kPj41vMAKznUv/vqWWNTgVx6sy6+KRZJnTKZCIKbZowsHNbfM+3TzPrkUiqFMHA0UrNCReH3rqC992hqLar+UAlhKS7J9c5TJ0FAjWrvIVV+/7Sqhph+cz3CzUXxOMJIeCJOGIKPw1RNPyiBwNUo+1l5J4XqyholrsQcQ7E3vPLCwRSdHCvfIKQFK9+DLomplLWEgjcwYBq+Rsrc1mH9nj3nAOuvi4PEUjVr/oU48PIB02NdyTH6BncrDqm+8KSzOounV78MSN3lXTkho4nLi7Z5/gxcuplDtcfJta6CgnAnOurko9WG0XYeRme7DyZdk6/8wIqNu46pShe6r2g3xwPjf8aY+nusQiCZCf0IDieUNAVg7KrUlGk5zx3letYcGAGYHST2fHMPOGvsakkFfwtLSwEhLuMkLOrHad8CxrLOadaeDj6827QE3hapXW+XBEd5X0TnuOxsF8IZGBPPCnLFZxGs9VNxXpVLx5RUUNZgcdHZ8w4xFoV+JjpeKrxMJrNYKCmyBoHwfg6uh0zAb4jUfgH7CBnOwIaksmnu4SKTv7f1lY0FxZ6crSn0NafY3K1YIbc0oqp+ZZVbuPh4MSXpUoKc1ioJFbYAG/KFKutcs94z3GTv5xVmaQx7I7sw+l5YHN81zYSUFX1BRf3QOgImfKXJ/+eTA4aA7I28UQZdxNtk89kguyPNIgf38T6ruDlOkGg8PVs7hZSxCql+u1yo1fvcq/wenhnW24HDIKkM3Lw5O8ifIF+icXmNRCbkcrR/kH0FhnL2I3tAjfnsR37200pkX446wxUNiJpgmxm8Ba50RSaKuU50fZ94zqclEk82TCm6pU6/S0DZVK6Gobzt3En5MbpaOggfsZttkrZVl4lAqGBMoBhQX+GV8gkuAayb51BApghhwDBd1n5ju3dHtr/25mZdAXwgEW/otHdh6ew0bOffC1bIUB4A6Vr5gVxUwmU+pkyZ/u72eKlrUy5MyL5VQeJ3QbdKzCBN+oWZBTLoUwjJQjBDR0kVdxlLbCWBKrLNrT6hffMMgJpPHyy9I6qb7+aJwBGHe6RA772Mx0kVqLMGpBMFbM944B2hoZDcljslivmPJ6vlhN9Gd93sy/wyW5h/AiKpKQfNEnoAeM0SSQhn6DnbH1RP0FIb25NzFBjDY+6pH9jnN9pxSS1AIV1GFNNNt4d6g5qIvkrVXTwiYgeLtYr44Ydxc5GyKyGfTQDfY6nZ9KQyray8oKdsUmwgzKAKNw8K8paJnzSESMIzXUI0rn5JKa4wficDKhnkgug0UvPVH2M0uyji68TwafIPciChOFAZa26EwBBNH3Rno69AKqi9g5DRSGMQ3TuZYk6Wr9YJISeP9foJMS7lBXH8Kd6j3hx+g8JJE94N1nsu0o/By/+dljvwCY3CLd10LfkPbZBdITXH7ZxXoRw+3y7HZ5RAX6NJxauF3TNbnI80tbj1kNqASWePgBk+6pups3mUPswy6z0MmTlpHyAWxId5teq6z0FFpJCmG7EeQ8HaIr4vhkPIdE7GwlVw36Hd6PD8Ivo9h/4wbp79Y1WArBPvxR5AywTJKaRjmt33ks74bviRw0yKJVj7k8VtymdWcLeelPyUSS7z/TK/9HUnJPio56u8jOKn0ADZSW4MufTtK7Khnvaa6RY3q1D49p7SgJD9ZmVYMhcBw9nc1DRoV50Bzh9lmX5A+cqtzuMsykZ05f31pPnAIE/gVhpQRvlZeZk6tcStfXEPT0ZU+RaEzjzid6IwN3J0zz9yUJ4GiYRbS8vlBn1VY39Zq34Wqo1H7TKAjhhP/TxHw9HHdLRh9GHPag5qD97qH/Qnw1R/by7NbVyqvintUh0U/hkv4SxNtPuls/njpjtc155vxo+iKSUkLfhNeuJEs7JRmmagM4eHKhm5AshduQ5fgbOIA7MW4i5oh4XejVN0CI74050pt35aAW07CD5FrxI+xgsGfHbyI/+407BOHwLBTqywqxMkc4RtmRl0grp6oeErvd1rC4/ov1RJylbWvE6odNcDPoBnFTSW8Q8D6gDAeuEi2arUEnBvp8sfhiZ0Fl9mdhP04ucJ8x9VeVOdu+jVbNkxto7MIXyk6ktnK6dCIqjLHlY7i6M5Mnxn6BJgicJZs69aAgKJPK/C8NC9V/kVfNKIRn9O9Im0VgHfpN3wZLFRNxIE5tuEsDYZx1mgJ6MV7cz/FALjPoxGTgQAFl5wmcTkLFyqSFW8elWYE/n0W/uDexFBp0i/LssH1FMpFcXTSlmPMaZcidnZxiqDc28vmxxkmDko0LrF314m/Jjy68ABQfCyNAh62haK3Ha2udP7cfxpUlulclkv195KacoxLnhC1SVGrD5RK90RaTS7GhHEq6akc4EA5zt2mWBcWTp8gA+1Mg6ya/A47x7ZKtVAAN06ydn+Lrt0vphqPqYi5DO9DD5cog3fYfZyphvbhJTTCJgWO7Nr581VenCm7PEhMBTgu6IiBZnv25GwrxYo8bP2U9/7wdz66Iy14Lhkl/Ulk0t8ZToumyRcJU/Str2W+Xj7MicFzDAJCU6PsoqRU6ZSpRD5fBIZBUJaKsp20ta+BK1QYcVQrqC7YtKWTyJHOWxsWsuQETsdAsKCg28I+N9zEx+KNIcEXxS4SqeARhWFql+usID3ehuzYo4iksn2wM7DnhT+RpqtK5YRygcJntdCMOhooO3Fj3USe5PQf5hFtj3qnhgjLmYgqr0X2AZ6hejUCgNqArmYAKBSXIDzC+RkiBK+sbjTDpA/ltxZlHpNuLLEhdw5HdO4Km0knETENZvBA8l4F1g50gOgWg4BVxQvZ5J2Ih2O6VayGkxT+W6bETKsTmkWZSbybye8WlYOpQrA97pzZpow/TNySAXKkQg+Kcy0xoWkA8Cjk2detQSPLGuaSjPCIMPm6VM2JMf+xeGLxwZKSXADTcs34/yXJn4th3dchlalGU1hLjTyIG9Ed5j7d8pTxm5VPZn4whr/3CckJbBD28wrdBkmqsM6ihUufvtiVRiAPCpse7fMdCvCi+XWZ8VHtPrqlS4v+qz3gyllXAvdEyKGrjrELgGHXF7AofzCkqYKXTXwRp0d1BPSRF3xzdjfWAL8122ynTDX1STiAmrsFk49hSmTLMYdaWiwUQK+qg6j7KyT1tslPTUTxdVY72vtmkVzEFTJep9KumoonbzPuzJgWthUneCE6xNgdm/JU4FSEG18+lwpMqtaZtYvKgQrO7jSU56NdVuhnbVbA+v72UGhJTUxB0WbZtYGnWYaguU7R5SisE87VCqsEsXhr6sad0337mRMMCl4RVyjAvJdnd7lGhWW86/dfjdzkNpFfQYOjF+erLuOW6K7FNb9gCo62dFbwJv0yWzJDVMSfYLqdJpvwwkgt3HSEjxXrevAmswMlAnez54idBmpoMMLkMfpKtww+b61INNRBDHAGxiVPF3Rq120rSekT+WQhyklNHzJduWMULgC1fQh7jp7eVOnGeXgfITSE1/+6Ibk2+0bCyKTq8hQ7U3ETfFim60aDNNNPw8dyT6dwBZvOP8yaRKCrLYl2TM2HV/AQpknbjQAGou47bSQbkYpqz2CENFzgw2HHtPgZ8O/EJhQPKJuaqi/v04lU+r2xBzOtwmiOiElLJuZgV4VM8ps325poex8LzA75lWQx4rV/MxRnaAm8eMMPf1szG6bXgc1eP2JgiR+3xzcLs1NlSGpKWh42k2CpTBFSCrQp3TWtXYmolqmJf5IHr5XWFUlH1LqIm35ve83NPekCmXa84kvoGNZ7ztQ256LQbXeUFLTNwPuiKB9Rsz3H78ZbrDjlEOVK7inUjD8L715Pds7endtUES4lL8qnvnZBYZVZPNxzpjLfa9ruVmofGmBHXP7NYoFT2kAfMJgjaoZd6N3VHa6P7jxmKoW5oZfWSdUjfdidwl2VK7JLuel7zeCCNdWKLf6K+Sp7UmxdZhFDYmwxcmU2SOkgezu+somw3E1pmDTgzMwlfoQnWYkYCEF9XoQ2bNfXwk9jcYf3JxqDjn3w8r8msxGhwrns6K4jTumvee/PZg/JGcVCvyk0y7g3S7vPHFRdHF7yVPR7/YMCOJbGimX5D+zTGxXwONWAU249DYdg8pIfcsIInMZHFto/A5cTBDv+lVlGCfhXOvKKAw21zKRNyd6WklBzygyrvOuyz8Z25dKLjRUM1sXIN0Lu+tljLpurMCwjbS2/fCh+1lqWMsFqZYoY+YJJVQMSVzP4m5RFE3NXSzangcaF6xB3zp9PFmhPzFwyO++qI/xml1z1cPmnsjXnSZ8FY+LCz9TfLMEdmnuBxFyvQMySKO2pXYJH6V4OIElnkLHQkFANda1RJ+bd0btySC78YpEwZSkIx7d3d3Sk/d9J8vZFc4cVsnWfeqh/bN94K7+5m9fwqU7AVOeQ9EYLsAZJr0Espm4D9vLeLjWbzYrZENl+Lk17IjzFOX9xRX7v3JKtaW6QMSZ6em4y9O7OsHYhjyQ8MlppfjNkR/YHXjaNnJy6qI7FmKVVi6zHILP9oPzpMZtYi+8EVfdLK78k4j4gh+ScTeO9Tpv+mRNZG/956pUFcnjEiXKdz6hHMw+l2PVJHbrYuekF2EsP8nZ3xDD0dQ8/Mn2RiQY/rTtKGwpKR1kO5P9e7rzLgY97A3jrrUdfgOyseEaoWeNN93I25sTXgWaXYptn5P3QNi3nvLG5iei5o5tCsZdkV6Zp09DEZCGx3HDyY+aRir5oD8JbN4zJ/1nxelDstMYx5HvYgHUBsdI74ojdZBy3cqx3WqthPN4pF7XyUt7J6tZTibe777pA6LftnAw31sdnaK7AyHdWakp3lLhHJFO373ZwwvBGPgXt+dDN2ObB1x3e1VxNWAzjs7kYJZg4yoGdy2jLM8ZGKYelDee+Pn59l78WoUw69bWdStyOpSmJEfq+5RaMBmEtU2xXBcDOMvqjaTZtzTiUvH1cCaB7zCG+7CfZf+dmBHuLQeNbyv614BcoUQ5lU+8uUohNcAEN5YC2TM0zIUkW8bN1d7ku/fh1XfHjxQ9RF3kX4WAAZMk42IfAdbqoLY2V7984UYV6WxHqdOyQAlS6z1gBYd81eNyY5xA7n8fDvnlKnbdPI65CuGM12P8mxtD6UfEVjETTjw25lqrar3YJ68vF5CSuz81oSDWlyqlCQTozy6kcE5s/7zc++a8s7uZNdjTLER1ml4kw4nI7B7Uclfk8l9rHoDP7fKGKZdZBb6K95shLGhf7M+gVCxYREZkIpKDnoVrk7XC2KN0rn347oy5FXqNYDsXGFerkayEkWnfaUUbpixpYtxoYOZj41aSXB7vWYOhgbCkCffoW4DIZatgllRr1AqJf0sOBhYHwbAY2sd44KzRV2GIAXKW4NuVi/SPMFQCFRloiffNZz6EbRuwQOnjXUJOwydU+OcnBMNVPtcmuQtqaMV1PojSi+XRYbrwtiPTG5AyuYlyt1LNZmWNyHJieaTDTPA1lLpF0NLkUq6+sUdBWyadN6+qyLchOC+6uwJ8e+U6AaRWg+/nhPzjlIhXO5R6yi8PLNXeUUSvo9IpJrw35358iwM310L2ems0Nysva63JD2n9CWQR7IdJtfJcAuIOC+WRFjL/i/TmDgajqFI92B8gr/Zs0hHrQKuiUCf/5IrQCAEPyuJlxKxAmc4+il+zaWmne8wXTxCmsFaILABxog5JhwdV1+EUe8V8fePS7LDVYYdPzgoDmHh7sjNn3ptDr/by0K7fkudfkK9kqCyDb9T7BlvqUHqujk/0JC/3aUHOPCTbBDAjFiucziJm8gRFynRgki2QZeJvc4emHMZda9zv9flyNvF6qTrgSLulEBrwYBNnhP8hg/cI9nYQ6C2PCRtaPFqElE0LB+FJsO0XJEHJ0TML9tVng80nrWIvSwZG1J5kyp305cT+Pgg9AoUQ+ZZgxp6zFY514bTdS5RI52LHAAj8kOPfK3UNCEvRKwkrkMDIwZEQ2o2rn1v17wtN9R6uKyAT5JCDQmZGtPCtV+MLTJCJhZIQ0JnvDH4uhDy5TS9Z045e11Ip4k6bAam6HLIgniZyKU4PjooApjXvONN7M+cCQYhUXxA+l5FaSnqvulbUuaTNQrGauikHIyOTeY/ROVF+5Wwwe/2EjqYz0wX0cgWUupSANG99a4I7uV1JhUcgBzI2/Zujp/sR3JMwpSy7dnSO3MKmQ39C+GijPYw/QIM0CUs9oxIOWkmetmE4M1M3L/93K8fXep3zR/ZgQhptheZU1B8tj9FeR5c0S+rOtJrF/8C/6prgz+LvVqWWN6smTGBonBctUfQa48/JSQrgs+GF0p80uXX+QOhEdqNxdrWy+cNjucjpDYLY3VT4+EbYHTt/n2Rmuiks+wH6+CL+Ns1i+ghQNF6MGPhe+mE55CgTnX9BLOaGAPTEBrOi/fsrKMIoLHfZUicvsPZyNi5In6hCWGuefAe+deWzklvLOKkwXJKko4YxVu+40JY5h0jxNkdJ1ruBVw5STeoyeI0znz1BZB9Ywjde7ou7wfIAQGeF1zPO5AEez9M7mmYG1EgczD33xYL3IDSWnq07oqchW5ALBo8+no1kR5eTypsO4XaF1CQIM7paa8FngaoFGzQvxKDhkcXk3I8B2Xri6Ry0KSgCNdM01ndHLPTovxtnZzH/GsSbI+W9stWG5NCL2zJ9l22q+DSwe7dnxFqRgbrhJERoJLGdHA0/W3F7Ald43N4y3zywSsJtx1Y+BesDVDPwThPZwXRKFbUeXxeqraCGuRDnhPrZDV48rgHMwq052KRTcnkeuMdxiRPP4F+tBuRBs9OxwS+RjybnJvQ1dCYL9Y7BaLNk7AJe4wCHcmNidUssWKA6qqN26OMQlhMvkFyAg2ir0E0eKJL6WGdlvhpN4xLz7yKA+QcKemPw/KdlS8c63TUmFuuaSSmKFnlPYd1NHg9o51jXDB/JBB793FG39Cph0z0qohzeIKORL/B5ZpuZzRZZXS51FJOzhO1PQ1wZ5OOCHpvK3TFp+zbRGDfN9bIDPTxZk9YMWslwBwb7MnmjjvGNaCy3vMECsMmiKKzu7AdyTZinV8Eq09wi6klicHfSW7jwe4bM3gZCTHvo9fdKtLK7+W5tUYutk9kBjTLRorG1CB3mqU9Z9qYOl5Em5c9edhpdnjqZzsrQ1d4vNKgVEgAG4jvtDrg2iAOyTFjceDY4wfQu3gAJvsV/gtY1FkJ5SfwHXB4FGkveZ8zsi2j7uwL0s7YJbfTNgQJ6Awp/HmUmaT0Y4C59Cua8TzoA20gAJGNKMNx2KpnVB6b26jr9oyUB63HW3xo+TfPYYdqIHNyFSQiUJFQAg7KyOQQhq2PQiYRymerAl2G1131JzbOwk4VBbQW9hMODBoXJqecEFK0vkt5QejtL0saROlUTloT7DqCjjyohhizGr9bDkZvIl7OerbGMK6QN+PI3yD94N2mnV3Nvy1F31v4bvO9gkbS950jVceYKwXMl/5R1ItjxZVffPW1RitlTQaDYR0GjDH7iHJKgGdkWl5cGg/oOmU7DShc7sAwAjhhm5+B6fq3csIUaRdB8HrAlkQz60wo0skj60D3BGvXx9gNHhBDVyfI2wPNNCro1g0ypJemdSRfEIURtWk93mPgZVBySaiYEcflBUnqUjvKnLqJCgFoYj2zGmgfTWJmhw5F7Uc18lGRllrfMw2Ab1n+7Hzd0vKb3pjL72x0BrqDasybngqfrsD4FPl10i2A1ccWWsJqgvqM98TXNXsLo9gnJ5vkMjX1+QlCm7qkX1xHQcitSt6Pu+mgcq0x95Fa14K/Bs4XVFwZTNIEjIPwFwzfzxD0S769GQ+VzzP4GzWr+ABfQ3chGp6BgVKh1tjn4DLVORQ84FFqQ9ldw1RfvNVK8r+1yCZ6Qy2HQziTnbaVpdIt1M/CXFKmsBbHR2vyqS+pY+9FKp8bpzVW6ez/sARD8WAeCoZPNkoUIHnzlFIszyhLF8275HrjfIvq8AtAh7PsdUyIRrIjSdzfVIoJIZRczGKSBpiSUKNEIhI/QbVkL3zlCFZuh1Nyg3+C/pN8fP2JOOTq6QNcGkchzGTaQtKgwfRkSOEsYRQn9ouxDOxPsGZj3B8UfsqU4dDGT5rWX+C7hIY1SJn5sckdLzqcwP7yrHaZffHv5dqWfokhnZQp87wkjKxW+/2V6skyTr4tAyC8/cs8zoyQFptzyCQBhmvbVKw2BAFLahmeiGfXvE1d+/ys3iTu6n5Z+8GknNAmI+AF3S7vQWrFtk/7joXMb1protwu/XeBgR0SIOhzDXKIUIYuCjOsNiuyheWHN3usLZCHkOxk7jUIn3gIoUyKrZU+Ek5HigywsDcgxnzj6pClvseuYMBsTalYAZAga3g651eUrX7T9CymrtDMTmIA2sPW3aKFmVrSonjEOMrYxCDfU6j7zmKIKGBhGEhJF7HiGmiDujgVgLMBKLMxOcZPOAnsVIm4WNxYHexp+CvOK2zjPXW6M5/V2uCW1xOtnldg69Ud5/iZYbYUMj8lnKS291HcVUUUt3jp+FrZkQSE9fnK+VF0FYVtEDTXWYenyginUORnB1NbZayXECBZasZvlnyVxvczQbmIlVYjRLU18K3L4HgBPxgh9B4jXmdv90c16KAewExgYi91jm7QYPBcm/HmxjdhZ738/PjLxnmxaAPQOv+l1LBi6eBHdr6x6fYkn+kIP+/x1k3WVPssqY8BwjW1deF8O/QmKM5Jv9JJeIiu5iFkhLsYLbSXdr5WXDaL/Xc6brIQUMxN+uiwPZRoadKV1E9EuteOZbfn1qxvq1AbunAZdYYuJUZYo9RJE1Q7imhtSkqIl2Jvv+cdqJ5QEb2XUfE6+jFpzmdX9EL0LR3zchDFe8KWXfQTC7LYar3iORj3mhcDguzW+0wrYLtP4UvvogxF9+tItEOwF1W33SK3ybbCEoRaofrxn7n8gK3+w8dF0Q6b4JrbhqGgnU3RqwiLJKWo3LUnZ9u/J3FMamlwg2EKhOD8BDrHa3k6tlq556XqOSRSfPgiu4M0fRYptvWXAuJDYBlMrTykCHVbg8jKOul3Ey2Wy/fcNdO+nHNkNEXCMWRIqg10dCdbLAwsFgxNrVauZxDHBDfoR8jKkgmtP32Hcd+0wT3Ymzdi2qm+YsFDEbMh/CptEOocrPqeoBhlWEjsnXSp87Asal3ywrvomgyIdPv9Rnhpe0OqSt76PlDkU2oTZ9cOLnWsNY8thfykp84x1pggGKb5tAbALhU9DzzTYjm5uLzMdY1ycvZqp4IyCfhkBQhXDA2JDgX7LeePMDTFMftG1nNXheK6t3gcQV2Z5z/Dycvuu1X5cDA0g2LM5TOlm5YTLi3exVuJyRc9rDSmzcxcWNXWV8e2yup5EEND3hhanYwUSEOmluJu/8eA+kcW0K5vkr5e9UGtmIGWHzoaUFUuNKgruP7DRYDpzAb7Z6kNpM20tM/Q4ydzL7VPk75l99yHuKC7jdOSZvGKNCrxMp6OGtSw9o4r0m6E19sugOr1lWWwiBz+CQdzhxC/5u0VP6bcoecRYK5eP6RGBxXQQEzjufw+ITuxHMnETDZ+YTH7Dj4coNB5qoA0c1q8Tb28u+4e5uxbyYz4O8GufZkdD3TEQWF1iTe9M2bFXaYXN/Jx4IhJ7q22jtr1WYuJ6Lvt3m60BMd2Q6k0Xdxv8ILDvfZe44QTpZqbaQqmVYsdWpAZZdfA1W2qdVqNzRH3IN8BFqmpNd44n1AuQECVG/SfxKTLNpM96LcIHDqQ1mx5nP5COH+xH7d1pjRKBHGVdbqMK0FIR5oGYMtMdnS8RsoZxmkk3vACgVNZtAHMGQUnJ0zhS/fVopwWWPwX477/ilvoGi6y82LIrUriiPVmUBje/O2Tb5zixnkX+toxYu6ap/ZZfSZMCQQktEkB59grYIUU69w0ZyfGWRZIe5xu9YulE/LCf9ZAIoSCrOu7Qpe3NV3gFSVDeWPlVJsxI5PW9BfTMDKfIoMHn+s59zw0TVavlvPkZDguWy175MI2UPHyPXGlmhutdkj1/q2nEa31IOe7WJsgHd5BRUZdGnBgGv7n3sjkeu87+jn1pJu5QKX7W046cGKZU3ktRqiL5Jzx9jr08T9tMh3Oyd2FQSfwHnPTyezO0pAK8k5zNC2lJV5IBTtsQ49ES9WmiEnsQVxiNxGEfamL0YEVWjphBmquBuYPpw0JTPlf6CrdveEUxEB7C8CmxXVd3YVQRhgx5mVhyfnaf8iIvMXXiOa/arm4gw2zy5r1aVloRPWI90+2y9OggKecyPiYiSHz0SQy84dcNxz57cZ5cgpQYc0PKQXxL0fvt4hfoQe4Det3ZW0Ajq7o7+5FCpm5xSy7b554MH4SewUq2ibQkaOOVE9h0cza3/89UUpsg3cW6woYq4hKP1KKZlXCzbnilP5tXF+BETagqCt1ATlZsLlNx8bsoCeEchQXZQb03DGigU7WQG7BvnaJJhc86Ic1dmJbcHNcxhq6rasEz4+iOtTWOEI084GfN/FbO3bS9/YqqTczmwUHCL22OnhTxGVepl5fHLdKJKkbfzYpSpl6pA3FpAJpSCGgsHVlw2PuQvoOfD5XOY0iB+qrGfD6MYBftWpO7HLeiu89esfzOTifimtimm5aAaggbQT29SOVTFbPq66/m1cWB9aqWW+aFxFays+a/BvihIhD+sN1KzpIVwZxha9pPP77sP8podmJBriI+WGQ1bM8tts8b/pD83zm5X5SG+GphjikGFTQL8Wq8vmnuVY5D6iu3i9gBWxAVN1d61oQUfwfPtr7iBQZfD6rNoEebTLpqh95Sh+Jai5M/wgd5q7EYE3hoH6wIaDc0cZMrAHKr9qr6I45MuKA+Z+6OFKd1JevM9IFejGXCdmw2/r9PanZoEkVMtFO6nk695X+ZuhT+SGKNKJgSzCZkj5Lf3vPo/PjacNOnlBbauSUIdJTgdmdGTbpUZRA+Vm1n1XAZdKNRJuRMPPt9tKeoXHSY/NJpCZSSdcEqaktLfo0Lr1zBUZsnzZItSV2tOkcCRhuQaAMNBQ8tCpe7oahrHVoOHvKANVneyG6K6msFbZtMvjo3F7vsuQeH3wBXL2j78utw2gy9v5C4Jp7Bs80aYrAXT1mdxMKkJFTf/ehR2/FB8mrJRyGaA0BVZkOijNDIL+N9i9cu/iNulJatbf3tC/uZ2JJ3e6tOWbFtptxAK/3yrmqh6xwKTikVB8+W+5/XcPeWHxdy7f6na3gCGvUiwk6CnLElp+gvycPSyhh0Ww/lTsAE9zYXW7lStTc16wjCLP1/hmrvMFewY6+fH73i3hxXpVo3OBv0jXXKBm+JmrIgb20fgUXF3Sl3Bbh23RwOM9J5Mgg/dKSWKXqL0/IzFMmiOPOrQMeLgqaTTvrN9N7Px+60MXyj5dvyjoxKFfdIOuUOIE90fYGFnsPv0IC0fe32vv4i5EJ95FBUTxQyn4Mh1C5SHOY7hYd4/VF7/yHc2/ipoHwPDslAfwwxLysu39dGa+Eojj0f/c654+FE88ZMostIk36WV5NaJnFg8q2jqUT+zQV0t68fJT03k5q2o/d6roZKf89hdzVP2oSx0QEIHhoskPi82An/PKiMMGkgLEoen9ZSYjy3bxgNgAUujXl/AVB5nSN8YnrYnf1JYgiUIaAFFqZegtQT5OjXsZ8VDGJuTqR4bcYyfjKymQh2FfTnkPqqLf6idLZluuZDAd2BxjFtBAObfL5jNctlHvkMe9KgZu+bJg7OjVUyPrZz4qfxWOfp6KXVRi1vL5wvP7MU/1T8aaCHpZN51pbtF3X8zlsMAA3lJFIElJvgHAr4ylrHQCqQjGotyJWcXTcVKO96KXdoeruaTjuX5xJIgNipYvu8lXw/Ul/KmMW/rJn/+u31iTBkYX1LC5ez4DRk/Kg273STTE+TsHay5sVbaY3cr4SsiTZR44qt37ye4k3FtvKeefuIZ8Va6QK9kHyZH4gJmgdgV3UgprDeFrvENx9rZFFIR2+jr4t7kH122AyRWvQC9m72q2jbFZm+BzDEWAIyEIT09IPGYJ/SmuaJ6Z19WYfxOguFxA2AeF8GV2EvYYHq6psA5hS8j7rUXKkVAGVzPC0pPNkfPCA4ELa6rAOFVV4+k2AlZpHj3+mNzU+tDXob/FaAw7QSAwysq1WdYiv/8F4FBQmgPhawyZHt1YXhhcdmunytZB8EgWzPnobz4NIfYCRh4ezaHLz+4KF8268MTcNboD+EdWll6/ljLpPiRJGmNHckK2Qfcxeg6dTWWmSu3ZFr1xFD50i2JUH78ntWmFggOEGVCXWlFwVW9xrrcz70Yi+bk4ua7g9gAXexBPExhRXV9KAt/7XCOohAL+RKXrnETnU7CHv+eA8ori5BKC+ATutuTtypousnOKY9Cr5v5aWv27P30f/Mlg0B9tmj0MX67XN8z26eYR0c45fEhXV0s94s1CL5KOI36GxKO5BAPQBhCA/xZPVwvdvpTyTWAwgt+CgoUU2jSM4GqHU6HA3CkiSXS8CHrIdOEf7WNUsDn3iFzCMwHZ5wxLJc2Te18tdShFSm60q/9AMhXkQKXbyuv0cXK4kWF0+MapUUnS4VfWNmSQldqFsvHRWLsDW9d3IxoRlzdmKI5Frb/qvHXxGHeAanrQwbi6ELsNQwfexiyOIwX7JcmAHqQI3Ey7ctc9ahOduirxVz7tovEL699syrZT9ExTgE4MVCxh0+pbbzwkOLMaobg2xOJVjwr+DJHk4cvmOsdAHQ/CX2vwEZtS/y+uZzgVRKrR5okxLdo+lkcEdw8g6soE1C632yM7f8nNYqSfCP/3G95UHL6qyPGEf3MGUDiYfbaLJlfrmSyBC9feIOkSXFXX4oVnOnzVsrtKnVpPuG/k/A2ehNk0vTla5ju6OQyUj9nA8/V634nXJT22aLrIJgZQ1jESVtHoDvb6fvBcjwvbioif6zHLaX1eNxwKAEaXpEEMEy54iTnQxzd5bSo3SpFG10hgoE4ek94luSxgPrbELrt/m2lUiXZpLyEh5K1vJ8RFozbZPlYJFGu2nGrH6m10zlJTP0g/sZSQpTjbdvOEn9kft3uFYEvqdhq5b3Ag60CAD7x2l9Tm5LsayMUgN7cPqUHVNiLLoQnvfBPSmjnOJ2ghie1HtS+WWqqm7r8D8OtBBvDudvvK3DLGjjiqrLRb7lxgfwoXxJLBeLPpuVPHWR6caop7QIdjCjHDLPA8SmNkXDw/z5WBOof7zXVpP8VM4PIiKtVPacDXf9VjpwIbR3/2kU3I3Jad24HRa2h6tbOS+6m3oyJX4e/+IgAt5ETknLuhxb6qS1zB+7R/OKa4cj6cP72fKFrSNBZwVyhA4u3v4Zaa4Flrqae9Ty90CPd/u3HrEKMTWp76GgB9is3kTmVcyhjrnqnO2rScSGn5pBORAOQ8k7n8zz3wFg3OvV8Z/epom7NpeHvjNaEyk5m7u00V1YMoWchbBEZKPYdORBF2AuatCHuLEZVdO3iiB/6AykMMpmxvbAf+BoGDLuhRMv36m2PGNsKwT+TIO+cx/+U6ZzMdpmqw2K9WDsby9LxZLpkEhQvNZyjYTPO63E01d4+s+Uq0oe7I9ujv5lX3e9Ppy2rTlwbFMrMmhEcN3zGPOkIquW8I7jvR6WDdnoYEdhcOoSX8aGZRh9KI82nwqDUoLnEoRFQp5TEPBaq8M0Y8dEiDbemFCF8G210zFolnpuNSnNc5DolPObdsbUN7WByEhM9Sb+PSDZZwkauxzpvl/WfqrsMKs5ZzmA1LwAdR6zzHrUDnzhry9UfVXucUVxcdXeVL0dAS5N/n++V0SwrvnJsZJS8lYemSuJnY29KHRezaPVBrKSbwhqFDngGBoHbxvB5PL3C8ra8VR2888RE0+CyV3XK6UfC5nymST/hsh4St+RVLDh8U9JL/scdiYMPeEqYKt0W73ywnEVOY5mM6RpxT0gt3xeqIp78ofbE4z4ZA1WL/DgJSI8weZgUaeqp73TO96/UGpRwLYsLeoOAtkBVjknuRB/jqNAhsSn4B7+or5wCjHL7VlHw/5ZoW7mB64M5AwcCalHzzibywWUaQmJlA++8AdlmhBBKbeTzPM1R1rbq96zZQt1eD52uLOPINV16c6A86UjgLzbk4OzlKWUIzFJ2etT497cddOHEi+n4nfr4CvDgVU6EXJiQkitFNJtVB953b3tFT2hYTy/NLzwnIonskIvzbJDHzHrvAvttlCZ56jwMnTmBljMS9thA5RFTk0SBywAyh6kukSDnXzCzPNHbu7LC6e3L2MbuAmN6bjHv8Xc6Csh6cTBJ3j9CLzZqYJ9cRAvV20QMZzcEWlJor9udl/VajYxafK1u6ssb2eqKzz1za2paNX3SLa2hdRWRLJJlFUA0pySUQpHn5PQ6T7El0wWeY87236p514vMJzrB3NE2Z2tU/4m9tgkKxf/W836Egr1mloc6CcO8zPPl6jcIXzubaoxhxGwpOjh9S38CFsTkovjq/L8iZzrg2hymYV6hkuwJ6gO1NMc84c5u5ddQdSuSXI5YoaaU4Edtd97M3kmXsgH0Eo1ughOpobmB7Z5CMOvi51JCTfO7QATaBdN7FxGXSKxgEJ7x7ix4VEIHtK4O8w2lDJ13XSU/W3V1+pqd/Cpy4SqT2w+JoUmzvf7ket1BXLdk6Va7DmvS6WANWXm7g+FeEEsUr25weQIG43QUo3C+ibdGsHWHfSpwsbTRS7Dhw4Dca7YP5FEW0TvE8oWVunwltnZ5ik6tc3VEeaPyDHTlOSHh89Hpt4agttasY0Ga05vxKjwG4f1YRqRfpGBdcSWuGuOU2XcS0uJx5+q4GzGPk2hZ3XN20buJjgQTqOO0NZGu0NDynjmOdscEHdT2oBb1LXireCrUKECUy7/JWosvEFAUQ5RGJ9QZESdEAp2a3jhZ4W1me7QzefMtfLjJaLaWhSjJ/z4tbL85l5eeZW8+pgy8yD5sLw0TmdtfwHIMiA0Lb+Gs0McajZu9GrqpZHOkN53aPw/SrS5n3B9sK1+w5ldFH1ZzKrdnWA0zrC9NU7pNQbuLyGtiTi8pROcMdxkcqc5VhQeV1BzucXweDu3c3DlYgdoH9PQfS2v3Azb4+07ra8TCljKMAmalpy+pWN49L6PGd3meLCX5/3pUIR10z6lyP+WlsIL+alyzBPHaOEQjtEGt+YA+1mTPb7AVeSpnZ1TQVqOEnrgYW3mDtGTCCQYmpVamhFv4ZcYHcCDEDAj+rQ2B2ZeEM67jfRVLveoGJb43VxH49jBya90OYZMTKHuPBoMzbcGntLhgf18iMC3ufln4CX4t9S8QRcDefblIOvsQMcInTjZNJmyf5W6tP+VMECjXke2Uab96bcjlZnuwqyTC0BaTyHMsp0gTgVL54FjCugviv1t/SObn9cgeICBFn6ypnvJWgmDr8LOxsY2j5lcUTbDDk5k4SXwZUA4e1jRsfZLI9eUPwAFk8t4TuUCc9zhs1en6S8A1sPre0t54zYXIs2V7iFd2B5XnUT4rEH99QtFl84h7y56XKzO5buYnxGgmlsWEgq3gNZtcL/gBqJLgbK9tQrSK/ZnWs5aaX/48LbjrceYMelYtSYkjm8YAIFWRLmw29c0jgvJ5VYvHmzw7wWnNmZQ/tLX82NAqkfpLuG8Sj8q974s+qoRBHAwKhamDO6M3Np3b62wTyKmp5wJ3U4T+cyfN05uK768myTWyKLzqSMfHM1Ww9wsyzVBAQ5/7TYFqLWP3u08ZBOxakCiW4EMLP6xA0bTcEO7FwIVFfq7w81JOZpeFFqjwcx5SUZCQMAl3Lt6gbq2MpB8SFsh3RaJf2keDkup5hGQQ4ED6kxYm81q12G7O64jj91jmcMceb8EWhk/S4TxQhRXmtmFNkHq8g3YgO/aN0ozL5/JxbjLhPYymYtGegSP9fH9FjClRJ5iqGlQpfuuJ+MuvjmdqnuPxlwnI6Z2eWLub3wdvHMfTmD4EnANguItaBFQ27sJXw9OV3lVWoK/DL7OTEmf8fhoRjyXTN0JbJvr4V1Gv4vVR0P3tYKDJM1rHPfJX+oryR+5bI1JTeJf93UBKjoDjHU8JMbHgrJ2ztQxBGt0hlzncIT/62FF5WLEQwFa2e2qTSD7KIo7jOoCmeIPH4HotLGJCcSejFEGfPYvvD9eeeBN2gQsQ5lRo3izKRHe03jKVqeS3sX9lh20giCkzl3b4X2xgr7mz/TRSjWuZQJQRGBUt/t8rC5S2haZ1K3u8uuE0xu6uuBz8+4skf3sqH8wWFQDn62a6u17Y39BB2SEyZ9/fL5lQ5BHWsAK0KKZgkkbIT1/ToDJURJdo0yUHlILC7CIixliBEVHcgmnyxr9XBhLN3ZRYQWr6BtSHWXstUElPB5v6F0iOFLd++CN656HDHA/kXG6yIOXm8oQz7JJWLwhcZMUPtUATnb02Q+2BAUbdOu53d+pRrRCgZCDusasYGjvmhmFcibST5QGwvxOE1zbKwOh7f1WSzUaMpc15xDbD2H6nJmO8Y4xvFm8BwsUP9VtDMPWqB9wVf4QE3qsteR9kWMxx/IrqZAz4j5swE5zwwUEdH+V93kabBO9/+93mvnU3+ErM/AQIFMikqN5SNsoNVO5EtdcrT5sf3PYTtuF6YJMTYKDDcJr6LYfp6NJXVJzR4/7/kCJOKb99bvtqUG7A1V4uAOjYydu9aXjw6D/iNf5FsuRwlDvlUbWn1E2rhfdC4qTSHJPreWiLv60bV+hbII5hO7/fkZ/MFK9NARTE5qb+/v+exI673suKwVmcCXf8TsKNVMQqzP8f/D37QtivjY1wcSrak523E3WJ6k1b/Elpm85HMFnUyTe6s2TgRTP7+3/f+Te15/0dvQOE5qKnPrSfSl5lZ+QYzrttgJBGZvkvlCu/QffgafCfSW+NE2pPQ/xN8D6aa0BtPmmUs80cos4ROwXGlBBdH1GdScpgeUC4K41UmnBcLrit9PNYJ/PrNLagQPY14icwUEUbq8g1IuX1UIk2xUPSD/6rJ29RZq5+dx3T7JfdvqTT+nZFLiyP4k2F87PRZr41cWCzF7SqZWv6+zn7k+31CGPK/8u+u5JNaqwRHSV2BPTROifvfq5WdwXfSz+kygmqggiH6s+BzzAZDuEMwpMc9+pbqz9Gh+EKsJd38mwkRO3kaO1aomMRW95vlOzyPwDGvj7V4Q1hTJZLLy1UNtgfRaQ1OkX1jbDTtxgjgnfyo2swlT3fH/Ssz59Wxo00BCk951qRrMKrJ+k7zGTfzjzwSSWi+pATJ1po640n3mcgYu+n5joAz05AXpnouhf12OoqYvbTprZYNj4D5GUAxJwRghARHt6lxw+cY725O0wH+veOpylGSWMxyGHitP8c+Y9QGuXo2iFeX816j0Yxfl2HSDB86cd0Dr1U3jpKAREIKg0TWD9CynY2nLq9mZDLx4ogXjofaqNgZBYE1GG5HaIAtb6qc8Jbv0eRPi2uXFXf6Sff6zmCanlXgAYtMP5LOzX//uVlrY4G7cSb5lK4YUUhcjXSqAgWdXylh5HxWYp51cx7HN19qzDVxnZN3eFUE7Km1Rhy+Gpr/NLFiUhCgAjS4M+xukLcPGz1ErDhTlLsKcn686dRL9PPF97aoZlL+birtr+zkcihJa3Bk5avTo15kF7pdYd3V9Qw2h2WTd/zofw+Hsaa3g+RqXqj584tr2ZH4/5os08/wMxTHL3fa6deLEnRuZrjyW31zmPHuP5aIRyQWmox4+tghCatbxxA3fIG0IY0vEedU3oy7bem/zE0w5mKu6Suseu2IX/tP73XV8xqxelvR+bRTIE7o3mhBBBEEcBQCNRyYwXyxjW1dnpMjl39jsEBXWBN+lZYz9INAyieMmZk5LJBBPizRdbCmS/JcsnJLESdngHOJeOALQRptGRTMz4ElY8SYYzaECikEo34EroN1kyFBEwaJfej3/g7uHC9bBzTUtiiHRxfl9DqOMezZf92v+jzbU8l2TUm/jk/U4qZqQzft4NPD6zKDoeqDkiGsgIS9qnNriAS1W5yzVXYWAAKkkrD0dkeBj3xH4jhOj5U4F49QUbcaKASw4lFbSJZRcJsTRJiKZHuGxkZgexPMy8suGrLpOoTO9pM1Pv8jRw/CG8rtFpVtX56Z/GtVk8sT+aPOp2KwUQ7NkwzHc+VFJ+zrfi1V2W87fGc49U2nea8Qh+QlPOH0JgIkm0p0SESxqiqaPu0ww3RUtdDp6mVefO34QFXC3tiJLfoTRdXURRha8pVUKv4Js/EMd2+cf67Ezazyn3mtlNwzc21THyocUoOmzkwo4ttPFWNGDRoQYZXNzhQ7V3Jyy02d4sQ5zeL9qpztVJJTXeW1LU/ABeiYIWzbuXO9eCbW+rDcWgFCdHGnRbYrdOS8vj/nnT7UI9szKvm3XNv+yAyLa9dEiptemZTiO29yk32Lf4S79denY66gkrnAqUB12tUr6MAd9QABSRimrkQCY53rgbE9ZAB4fZ5QYDTQ8WH4lI6Jsc/8bFVFrsrbrOAfXdQW4S2fANvFLEuGNnvkByxVe+H5ZFwWPbiNpXLJrRRQVw3M5VTvol0SjtEww8RZdlFiarKsj7fJ4976ARqeP7ZDxZn5wNWAbjSogcq50PsDAp32W3eagpnzbQcLvf+hY1MSsI5MiXuvcJKmXpH5WxwFoz0ZhnPbAGChcjY3AxKQ2WR+MvqqsJx8uPC3fOkGypvOzdu0mHxG5E+6hC1DdYO4D3/SSvKOGffNlTcWNJQkmhHidMzxW+kcaQDcP16aEyhsRfPZnG/PriNzF73TXRw52Yr1OITmhH2eEswQ6A2gDo57pyHzPACwkczOsXHf3+Bb82oguUSt4/MxLHTypPwLS28gQdzoTZU/VMsv5ePqx2oSVxCQxqYxpl/8NxAVFoV0KfKnCtoCGqQVEP2Li3S0huczfDyG2HMdABRxqlFtr13PykuVfDXa0XzlbLWVPoiXSU7lUXMcqxDsJ/U+2PHZqdGDjhIT7Y54T87dun1IDH008LYPujaYK13Fs98oPyMs35/b+yo0A7tGHeSDt1yF8+pjUPqlYDo+J2sZbMCyTCozhSuxqrJ7a9Z6/ytVsPs6/Nuv20VU/u2YuIvP0G8Ajj+A9fXqnDqXHOe5XHl5D7QBpFsFOcyZIEmpfiRAB07/FSeGG/xru5fpjdT/GvHRH7HLQ0NfxLgAduwM2Bdrs/YQMZ36EOaha3h//kruLrw23ghnjM7SqG8bItR97vjJqmQmo6PmByTNgVoOYRJxj9p+b+6L8GEMOz7bjlxMSJOLjZPIfUchvCyK1XqOAz+JoFu+nWC+OJWQBaKH7eI0qhjt6TO5nCMdumUeWksUsmhn44SHRKMKerkxoZ6vLh84PXi7FUqL8LLGJtKnihCk3y4N4XcYYVv6FdHBncF+Azi4B4kdYUUR/X8v6BYSZFv3LJNoH/l7Z8vSnjTNtbdex/E9IKsnLq7FEhBbnvabvAil2CKolmfIhNxRkeuJi1zZSvzVjIyiHpd1AgaSC5yDYFxqP4A1MMPpsP5FefOAoG1jYKPyr18r/g7u1EldYsiQUOyKDHAv6kITvOXJUcVc3OrJyaYU36XqrpuJggHldBSCFhODb488k8sFswAcWx1wsT+ANHD6PRcfArXQxRR5L6Bs+1/S1vvLI88gz+qDLwPAZqWY/0Z6wQn807+u+z3p3Gx4rsCvp1VvHX/rPA5jfpZ1/DtUa3olM/NmUR6yVXl9nl6XtvWaN95tIjpnQAVnOjkvrmYSf5ZTaD+LsEwwKX5V+JBqhoGsT6Hy0Ocsc+9cclU/ZoOxFf6MYYI/RUjadAvGcLl73nCDwDYXeqD0fvNz4bePVPS2rVbTtgmbs2zx6tFHQcAcmIspLBDvq334wCSB4bhgPL1jfLWi+6Ytdl2lpgbIyGGXGF6dQVhD6gb0w3ldpNV2vlapAmpIgIjTKkL7s+PwVWiRkozwRwgxkbk5ibU0ei/B+tZ1D2lxXeyQO1cNtqWYdl90xVmAnf6053y4HkztaxE7AYDYkKV0Uetst6iwM+6Qf/Gep/A4oaOWzkrP8VlIe8S3zgSjOvQTTofR8AVN9glpPW4d2tVjGpp9+ZI1XYXqiacVHm8frZC0zk9LiR218wa/qtv+en/l6TfSN2dttyRTXindT1RRhnsDodH9A+Vg+BdIWwlD67zbbVEgz1MyHTtx046137ZkxN3WfznTqbiy09DuAzaVOF8dq2tq8lKUh1q/mbroohjTI5lXbthnJY0f1C/MpLoTue1iin7LCDJyPoD53Vf5/cdGP64uDKqvSNhAxRtPHhnffZaiye+YZ1RSwt1F9ld38MoMCbUYKbCtR4NX3oNodCOYlW20i0D6nyjfy6TlDlbv4ROMfVxLO69eImy9jHvRx4BDtArXJmUWdbWL2tgoBZjxQYgYBgts+JT0pKHWynhMiSoh9ZeSnJP1Ia7BeDckXYnnrIq7PAWot05xXilGGrPzAR3I3t4vtgOKpB7VUarezaMtEJJXml1iu5O72zvbgFD8rfX1gpHpIFE/VUHjIG0PPVDQgHaNGZdKbteWcnI82s/J6wf3UuRpoKPEAg8qVVrvonJ0+teTTsJdyBU7+Fw2J99CitPprwfwpEjG6zPTyRX9sfyWDnWxulJkvlN8TIgdh2BZiB9KfeTyne4Jh2DAZ51fz+frtrYrMX8QDGzwNMnY0vpCC+ECcqTogCvY8XVY6Xzcxe9BCkhY4fuTPViVjoduvODhcwnUiwaFRyaxklFsQjaFXVYTP0fLphrLcUDr3i3e2t/6AVwlGmnF/GQdS+FWzYd+79+lUfY/IDOHJLMqneGAmAPXm8RVIsBfuVnxWbJS9eOP5dz0jaHIYeqJtcFaDDBPhaCF+r6aeXQpQ8qViNvWvZ7Qeilu/AKb/qOziNWfHC1xNu8jYbhg+wP7G/QqsoI8ugO4qhMcTdij0dh/0KKENN+qu6L27ILGWz5yxBzRxsJWuvhy3QYVauICtY+4MwwTNHj1TKCb13+LF601CAaY+MXpuF2r5fFTKhrhDo5vadEFaAjomc3IaDz7vnNpGMTS1M4CN33NoAGWonAHZuE4pN7FJDKLVX6+86N7S5RbWiCJJl7qRmKi6/5mrEG3J40b7LdjGYPP225OnYxeW9giTjoQI8ew9ILk550qbxtQnABolxCdQg8U6u9+7BDWQaj/yQiD+IJXwhKDVgNBc8keA4O7ycKtqTmtXmRk1BXfHCD4+Jl7Q2BEVQMwYI7mIbE5/QWWzPC5cIwVYoPoRt7Fda1jQknrf69flIJ9jE87k/73ve7y1nd0JyEMMn6A+WZ5mFfc9JdxQjorZ1HuMElsQGyLE0A/OD8HCK75PSNp8j15MfOsZUVOhS0P7sejPesvdtRNQlofYhyVSTuGiil1VFlKj/0aNvTl0Ngp9fOuWK5ZNbfNgv2Cj8ieTLsdCp6YVMTbjGfWpHDWZSRriLFfKF4lf4+K9R+KSy5YKoeVJRuzfqvRLuaQ/7j5T/59IGZ9hNmqvNUctHkVgJxkal5pc1/cUfPTJy1jMfJffm7Jm0EVmdmrr8jgq/iwQDwhWzf3XN2dM8dwtQ32hTfafFv08bJCyM3fCkPpGD7a184jtQkZHEK0rB0XTq4NrYBBGN7RAN3hN5IIySTtSQFSMdShHI223FH8JmifeukshThp2mFXkjw8c/LZtwpDiHEPs4uVn1wcvxNNzBrUuLpw+94s4SUlOgxxdx08j1UgL82y+NYKi4n05Q+i86znW8aCWcBO3tbYLwW5tyDqgSwpRPYn5nCJxdq5OwFTgU4RuanTk+T9HsasIdyHY7KUh3k3rKjBaq2QXrK+OeGQwUZqLCxadPZCpn6hIlyhsj7x3VAuGHqaVIK9tdhIF/IGJyrVnZOnfbmCaxxPLAIimvx4gQu3fd4hVzfCiFZ0jonECBBJ1gfMRZPdfHmYDAhJCZ9C166+JIzSjvA19r8Ce3b9Qq6wU4l4Pjh+kBHtgI5GDLHK8W8Oan54l2PSAZNAU15jxFAyP9zy5c+E3I8ZhsYJUvgnoijEM/yIdCd+iNO7OGRMHQgWmhJPq9rhY7KHyfdvIsqxSSLuE41sWSzER1kOZCAyrMe71NSeSvcdQ3eAnOwJ6RC3BjDoN/H/2noC10TDCBZx8brZ3OIeagyS9JMdEth4acFqGHBlQpj3Jnu7TSwUosG8BQecW1LNgODakZc8fksxOZInNwCG3xarDl7IJeOPZMd/R9+x4buG6/bM1CNp6mvqiBNcb3ZqVZC36G/N3so295YIHHn1Rzuc6x3T2/vTuvcwu6aOTdcYOaCPXi52l0N9iLc6lvTLzkoeGL4UmnHDU4lwCtsoAJbYQRjYegp1tiNaOuzWzZ8nCgrgWv58o9t5MPv7Z+dJ31FgCHLHvVNlPwoeRbKzoJB5i3yRDO81xwoph2tpRycct9FlIRs+F4lp3Iq5HdacFhadPt5k13pn/3Q7A7aS256d5LjA6/sBN2Tm+r4mbewONa6ederR6rTwihti6oP6Ej5UlNeo2x7UBX75DwtR9DMq9vuS/ZIZHFsql148aBUWd+Bt2FCf1ZrVDGkyGOto6ET13FjLFcChli/SlnW50Mm5HXYcTeHWnNJvT29RiG81QW7p4/nNcaZ87qsGgnciuw/Q7m494pczJ2R/IXaWsxSe7/GcCkMe5bDyHMYJWaK5b5y2qZx61JFcYrD2hLichR7aXyzKG6/LqfvTaNPX7flgYqj1wEQJgiFhjVFcLsNd497+079uHF7Wii6kQKlgUqm92SJTvXKV9v1qE2IIhTFLpi+nzYK8ng6t28mCgJwy2USTF48FY8ZPrziTl5Z9Wlh4NFRJfu2hcweTZOxMGhjREeoCDStUqgwlH7M7jvuB2LP2EmdinlcrPJOiNXKPLCgGs2zndWjAtNZXMUkx+HGAHHT0BZNHmE1b8fVR5mmbt/C+5HLTLbrpY/62RGzRNiVNHp+bLYqQwpA2/3SEtfBqXY9lDfK8jPKBgU7TKO6+gPjbDXNi6qPz+36pRnbe+fDlJSnrYJ7vLE6/PLj/LxXNuM+W3A7uGhZ6lzb+jHMEPbohSPWG9fI9I0nyzgUMW1Qccuuv4Ux0CueAKp0Vdagi0uC65XEZ6sXoT2OT7MMhYrKvwH+RGZuf82mO5MOifwyk0w4TKZ5p5rwickWSYBC+Vi++kNYP6CyXdnt6TcUqVk5F6OXDRW8DW48havwasRQfRXTZkLhnn37pUkjzrGtDgYB+NVVoYbA438rzf9oujzMg6pen6Z/ekfRvOyAgEMSRCzG7SmiRFnugZeG8Uav9+oarw+t6dbWIRpm9ngCm49VFP4orPv0IqWzZJJ8TNCNn8IACofDjX5yYIF1qeebYeF1ELZ2Yf3yprXyW99TwON+Y7licMK4XtldC5vLPeSomcq6gggv1cyDhSeXiRS+Hcm4urWxqA8rlh79AzZPTW9ptz/9lEyBlXkZvqdNDRWuuKR3RTht2+nA5a9AcZV1ZabFQ9tGg2B/4HVH2+2RwunoRgRDn6g7LjZSTkp3CzomnkY4QSlUYhZLqbQbF+aHtC6Yhs94U8pObB/rzuBNuFYralD36U2jiO6bK5QXq7lEMFhu5bIPhx1Fzt4DHOecDAQHUWcLs1qwEzm92ErfWzB2OR45Q7iv97ZctMZF3uzR5EUoUMMc8IeQ464pCp+x7/AXsCTxvJruR5MGudAp/NPS9i+1SssljvLWCR4hzqyPITiZMBZQWXD/DD8LHeeel3gUh8i5ul3zxywf/QNBAa+DxFtow3VCLNFtSaBGa6vYV2V0LbBM80pKD5obxTj124USVMhOCcZ8yhqGgYstqlC8Ytq/eR6C8T1gTwv3AyRY1OFxfyEZIXCbNTCZwDs20wbXRiBscaIl1bmWgcYkt7eO8Tec9B0q3om0ZG+cB/OTqfEqfIHJJrZn3m9pcZvmPgQ0fa3/LOGJBXZgMvVuvLP3tHk9nACew4AfiLLFFXxxzEqeGkiKb1pnJdTNZBiG2xa4O94F+1XnU5/refks2Cnk82694//dsn3pmwp41ENre9APy8vwQhEALgPVaNbvi/sA65ZG/JDvPuqFawa4OLREVnignhqgNycpPxUDGeN2iizqsm1CR+rXcAgiVSW+SYeytItMDuN1WVUb90OlI5I7m27/K+Zh4tJvRcdxCLSooLvf1vDqFavJ+SlULrxW9UXZN/cvpbUUOIyeZonJT5PwvGPCE26b4O8pyTnRrFQvnG0PFXVS+tptQUCpcNYi8ijJsHem3zElP8Nlm7WUqGCcRDfAaS3xzXQlEKLTWqoP9oZJ8qBbYKaZXzVz23HMGER4EQZu3Nkq36uJXuoK6NYuDOls4y6iq1lin2HRU6KR5xMkBdQPIvOpb79Y0fOvPb2yUU91K7tpJeCjsiWQvEwqOF0e/DH+ZSoGCgskWTLN5/14L2UeGFY4a+WNuy/bBaeRVr1MYHo9C63KXohv4E37rRjY4Mub7g2/oO37Tm5twu0uv+f3LiRCZnff5KdTE/mnIjzpHZoG+WNDH02s+p62+pa+3+M9BoSRI3yvzr9uu6ONwnrHcTdbYVp5vzUx1NLDoPlrhj6ueocvdgr/R1FYckXZfkSn4Sg1v2VQXBEqKHYO1mSYVxgURLjKgShqKR7exsumeV7T/UazdgELwOSjAPCvzjb/cOTptg3oXRBxwHfLDDOaT3ZWD0uRmkzJYUDeLmR358y0DHSim8qT1B3ma4weTfEbfUhFrF6n4a+r9QCDi8DKTEsKIMPy89bm/Y8n/R9gwrxRhh6q3zvpCDGzSzRI0WqSXQ2AxqQrOH8h2DKxwJ2xtC+eq1Z6S7NsPfN9NpBuAIAlp28nX2z3pLwQVNprxyvGRLNM/sBlTEyU7ZCELCGYYVTfyfoLabB8Db2Wt5LtnYbajeDYsJLMSzdmYG9FNpqzZwkR6T2k4NNGjKVqJi1T6TwL1e3sZsa0m/oIg9vbSymEKJ+YX+T06KJMYtLqgFmAUUV1i4WNxjkX15VR33s90mxAemY3nKfqPKclyDHTW/JdE6B9fit5Wu4FSlVRucKqTOxoPI9kw2bFOKzALPxAAJFSAK1QL07bf9UHpssGCHRfr+VElieGuq+o20ODHjnByCY/2z6zfP1feVD5jC0tFq2MP7X+6BTJzEsmMu+6qi6IYb9LyyE4IdWF8rO3XhpL6t0k+ONKezoijuIMy+YJDSNa4BCIxtBTaTLSciop87P/cthGVFyfVsvF0PNyntvpzVSlKcwZBZ0QyWUf39rx4Zx6XNPTt5Eci+AsSRM7CF5Pl17l5TH6Nay8oF1I28+cAZmE/Kfb4jJaATXuJwZHGMbIFnmeel/YfsWl8eZrXPegYPl9OkoHcscxrbotWqEZV5OCl+fNU6QsTXEwY8zEpzm713qYPfngajuzdOi/8KrRiCZqgcf6HwAFQrDljwl2EOHskNoU2XiSgkQxZlvLcmUOy5NpbII2VSaS2OVtQXzZIbvaxRCd2tXeuWiaXY7wikMSUNtNHpJOJ3X0Yng2XmZWPQTIUb5PRelp+37Alc1yVW0fEndzB2/4kg8c6w2T4lpOrEn7lHTZ5bLlYf5njz+cVfu6HpFjQJTINexGFbZZLATqjUijobVhko9SBXmvjWlzMmO6zzM5odEZ3lebCOYtS792FbJREANXf442Sa1aH1ugBB2i/23lNINiGKdSmeSbJpJo4y/SKnrPLik1Ksl9+WhlJ9Q539FJlwfvTiC4aPsOpV8DbzHG7ZvPXfVHb186pf3GzX6Cu8wz+JJ9oa8lw6bsIoD4oef1d76E/C7Gk9TyMwcYrgQnOr8k3B2QBfdiQwnE1GdATOxSz4ubZckp+WGeNFPDWD45NKIVL8v57S3hT7nmADqHLinySh7KBuhyngVlfy76EkPxzQ2xwFD2xIMfmuEYaXCazAO0t0iPMple3LP95A1fvyJsZ2t57W+oLy2exA59Ew8DUeMuYsJD7WkR30oDBqBHfSWW623usybcF3AGFK/AuCEgwQxWfciI3rSd5R/0whIyW+YqkOM4EGChLsFKCkcltbAvRWTBYhc1y1B3Hm0ri3onKuPFghx2CYf5TY9b4C5jcG/wqVjnogbbGOtT6v/diTnT/2tBi8lo6oKqgx8iG6ULiSU4wPXe/YHIFVSGhGSB9xPO+snBAm8HzQSovLkCb8Y50WhVdwgEXVPNxQ7y5+UxyF2afHOjwbCVIdCiECi26ZbdpaoE2z5tynMJTekNnzRcOrmE3MNpHai4FqSI8hpLKI7APAGGww9fa4SafILQk7JYuRYSbjjDemmep/lVPXBrZCb6S9qkfVcGIdfyfJwzkNEaMBgV9Nn6Jl0rtxWrHLQdaGnbFsr8u1QuZbUZkGnNzfLJB+ERdR4/krxgMNE+Jo4SomJMtE18Z/TeYbiwnFREOwP+TEEcX7m+8eFjXDTp4UR6dwHSuvk5bYQiwgxRBL504zBPmi+SaHqFug9HJ07lyENjjFeuCo271RCHaD/NKrb8RK0B01b1dp+sgo6OjQvBhC7cSyNmQWeXcIrXegskJeWe371StZz/Rf9rNUrz/WPuTPgeSvKl/J8uy+AZYJy0gaiqFI0FTAWA7OKkegJFRAHt90Id43BmFPHpvPWDqMikAIKkbJsH1qITT6/A+JL/Vm7ZpwPVQ37Mz/j7hAp0z3Fp86s9ryt5abPdwFui+5XLjeyNK/G5iw7qvvcuaJBk67JkV0rmAwJCjcLaCAucAqk9R9Z4oB4wJt31tRux50Zl5LAc06ef+mq+89UbXcBKvRDx9LXQOEsjDukJRT+x7I7HJzjYwkx1TdbrYp9Jek7aK+wnj+rJcweeT4Z1IrPNb9rtRve6ODWg6tX70GO+tcHaZmvnLy5dJ+T56iBo65Q7mmpLSz6NBaV3530hm/OTGQVXSzwSrW/ibJCf7qXLu67uXA0LYSIbk1a3K+nWDdcJIim/qc5ykJfBFJRQKbs/ORtWRuBhYjaI7Gt2u0rDsXYtm6urMXTfQJdQqJ2osVsN+XD0Xm+SkZcvG39dfBeo2L/iWkHAJuQ+73qPC196zAuX9706TsU0nBl59VoFxcXve4oluUYLRF4V9PP9cednj8pzdrdGY9pSnFGn2aBDuoAFxWRzbVdreDKnNpjJaaSJq2N5kkDb8PJwnYQkChWYG6eAeLErNYr6GfLOslthd2TzXZBY290YILbB/8S51483ls7S2CNQuDwgKMexgHIskEUtLPi9OS22sN8NMF9Q8uEgalpPN7Tbb/DZVKWseUpJQvqyQ5dLdQYuqivnGJfaDp1eQWYTGwgaoTH2mi5Zn7GFruxqXvd0aublPmYeGk5AEQn/1GJcXjrW2UrvEFNob4SREbsF6HA6UZ6PefERfmU2NWhUXKhC9DSDBoNHh/m3lvcdGsRPJfKGrZK3sDgHjdEaaozrj8PVD/WOEm8sNANxIjmjKDFkNBKFzyn5DjOqCtiyxas+PCfX9deDjdtmRKqsz6rF/u5N6aZTLtjkwrFv5JrAPeNLxLMu88UWyykTLE+veUhESp3w14+cgvqCplIHNaVfuDOYT8Zg0xOIzzFWcpQX2vl0HRN2v7W+w8XoY4oh9V7hEprEBG9IxRqFT3eyS/5SAK2vKuZgm1FeHksNcfIZOtwFcFskmPQy+ey52jvPcBGADX6jWyNMyEzGi7ZN6cHvtLyD+gY/SVSozJCyvF3NPIoytySo3D4LsqTsLfzwiSCFeaTvYmBLunh7s/ijLxxqX5VKWdq9yZFxq3ADrebgtgV37itcQLPDDj5DwqyEJyjceN+aCjhKbx6TsrIHtN+SZMoEOnq4Z9bKq563NEQHJgU9+IYPqYyVEo1DRp0TZFgv/AfMbHmIDAr4liKpqpra2tjqK9mt1CZDWTDdLL/9IAuIS/TzJLKn2uXdkWoOMtOF+OPPPJqM+v6eqlFDK7qE870OJd3TJ6AT9Chb7VjIc4TXExNLLDGdXC6L7JybYAkNea4Qd6ofw59Q/+Uu3c1pmnzQOU5uJRFeVzWuGDkEqwyBpEjNm4e3OaRTbwcRXJq5VUnaXEvXsZtca11aiKstdPysvpD30TXYJ5vrISjBey46CaEcfthEBC8Zn2uovW8snyCetlzK9mXyg3CCfN3ZLtCzASppGH7wBvrlO3sjHS9c/xvCfUzAj7zfBqMllSVlOXm7uxZTOb2age+R5q4Fo/8QboTF+cFI5LK1Gy6hoYJ3jMYF0xqTDu0cFdDbwchVs7+vH8oi7fvJXwmi/vQU5+vxqgzukuvqJfejm/WLPTT3r/tvtc5hk/okPiA47hyx8ItflC0u2DfNUjjNNdWbC+rESDnYSODbj4kI2HxqesGw6xwJlhcEGp03uFY5T+afH3B0xBLLXreSzvo5dY0pact/yjDYgxN4e0rOWV+/x+/stid92LpxI8Jgs3Jdt4mHjcIiZzuHQQY6bwGkHdZzfDJmp/fTum1JT1mRKO19Bt2+huiqqO1oMZiJrE1FlWE2V3YOYWHdDkm5EG5t2UUdff2kWBDpT3R5pCyFvBwY22rxUXNoRlNUqkvWP5bE7OPJzku/tB9c0mGNnqRM9c90ffD7N9K0jbYw4CdkA45FCyr5tcRoxYD6l/gZslHxznCivHk6YV9ainvvnjEr1w4mEKw9D041aAUOiU41xIYQZ272drcY11h93S8FRAnmFbh675qSvueCF6Tq/bD3xVqnTkXieZVY3fDhPsCh3AOnHeSAZ7NdL3IDu+fXj7cEWSn7ZR0bNm/FBILewqG5iCrCK53sjt2vfgysz9/FUQ/EtzKd5CItZqlPLzlDVHo4/EyYsRCElO3WGLnx6k1S6FlTJUuO4lgYwU46ebkpepic26xRXX4aE5Zl6uzlZ+uL5ByPTfR2VwlcVkKumsc4PKgRpV54U2CBPPlF+fnkLFO5JQFvCx0SIS/lSwl3oLmKDyET91KVXwkIls50W1D5BNgmvDQR+cLOEZ2CsiQtbt/NwIlSgMuFQM/WwPTCAny3gR7JtodLO0Obwu2Aw+Xus2YlCAhdVwKEzaXRJYOPXjt6AGzlnlyOEk/aoeUxoSojmwslCUn5HL2lgagPWzyQ8GjvnMAmLa1Grv5XYMcJDTXPoMNWy/E0HrackJYHuMhbawp4XysI5lwa3GkOT1i8vJT+B3mitk4w+Th6m0359r7S5TOjeKeRpLZEsb0pwu9aXA5R+w1nd9wbXabB1FSM5DdkQtKQD9mb07X95oNajnQSm8bY/JnBoyitqZKmwr1EpUsIQ7OZ9pj3PsXP4GiUiKYp5FG3GsuzXohob5rO7bhkuIVK/rymBWkD47JftaYUIV2NH044vQ3Uyd38twQBNiUrvJNkSq0kc/5MJ9OrWx8IsI6wb31IYzSLiHQ1jjUpMMjiidU4F/yWqQaYM1Sk/BvxM8NatoePf5LLEhctxC+bWFkTrc43E4OFNW9iYfxZ4sIsT9cmPebYFpWCJrebzDDWvD/ZBEUPojDgIuPlNOOWgF8Xrm0FnlsNLB29srAPcTMEjEGqPjsY9rYNJ+gs+2QSYraU8aCT03aQtzNER1jMKHHV5KDirXqD4+fJl66dex6NAk6YQDGP2NuMtwuKVw5rqJxuxeDBXKp4je2IC+ylOYGgxZXX6L6cmuCNqSQnx9hIaXT1NjdTiY1WBZTSYD4u6q1BMkt1PjdhlnJL34AiCOtamPI96px9dug9PtU+KULwHW5KRGVEZZWWpqiu1Ex5dV1MEpRZCJftY+iR1gSisFBqoCOfmWWlxieQ6vvuXLXAl37oYgUQQ6JhIPtWGsdLCjFKBKRHP23j+LrJ8rBqc0j7Ap2i0hu09ABysq19hK8cSihZnS4zt5pDVd/OY3n1BuAZ35Hq0Dqq1zXBGOw1i7GyWGHRJaoJ4FgmZ6y5vN0KVmBGL53wFt+kxjT0fN6YgtbGxw6FmaZAm91nRFF2l1PZc70xwGA8ZVClOj8pA12uDGkWUaWUy/4mMSkK8fYL9taO7WtgWpTijmWQX/opiq9DXjy0FgYllsgQYHaS0Wim2ULYfuxyS/R/azh+/zCBNk3q9Ki5z/SQ9+IwoOD0Tj816zIuVZ3QycBalfQsTLFwd7NjBlzdupW912KAj92goc8iX3CJsf12LGCit5Qmtox8q7/6+NwpEYnSC2WFXvoTGJ52kFfO95BZEslXBuqd7KYverKrvq5WxgCs1YVmPTRwiFexY9evo+O5IeecvFxS3e+5JNekeimSzKRaXw3MZSnY/lS2H02t48+MdarVG32GT25Bj+3Oca9bOuCuXKdshESfKADBkyNUjo4obU9+r49AWwWsOarQLZzf+EeFFZfgAXlpcZJjGjaBzFyG/nG18e7G3sNGKVgt+Rvv4Aw/u0nqlQJvkZNNuDBZwp2m1YR/ISdvgzx94W3wWWQD/1PgAwAtiwGyTngJAJlv1fOAJXKHwQ1i1EtUWFoPB/7wWtXIWXEeFZbmfD1VRHwQsQVK4De0YCZT54Mpik14d6roe4q62HDd5uRAMY+apniY6GTP6VovRH4Yv5ZTckBqDFkfE7dogfFX3VdEVHViUQyc8QP/C1ai4+SayRiSnwtI8ghwd0qpKAos9GjCmkre34GRT+upSUFbKeIYgfCzjx7iiyAdW8/WIT6Pbm0etZZ9qZn1Vb+bx04XRpe2OfgUfi+A8Q+Md99sGZ/QlMcextBKpGvYRbd2iMU837+03ylCiRa1M1+4Km9JhLZJ5nVKcbf+E59+H9UF93GO5tdjRYjWfM4lPNF1x7KebMtND+xJxjhqtSg1wLUcbH93O0vCn5AVkMsRS2JwnzPQ8+ZEfosUvF35tMt0HC3QmLHtUbV/Je7pxq0DYO47WMDCwRdYIzqptsyVQEAj8XHXV02tJE6tFB+82H1futk4y6sZJJXO8GKBKjktD05nAeb7ThNNAE9/c59RyfpemAG3HCPbyK5AZ9Az1VMkj2yjOL/RUS7vilBLDPSnaFcErKlxeMHaWATaKYUWe8bM6WSnlJ9/yeP4453cGWUtC3ESbpIWYehgBbh6/93En+P9Na6SlNdLFeLUWp9zl9gSgzmUlMMn3pdOeE2eaTSF100V/bwluhZrPmxveuR3XfszwLwwX9GOeUd0h+HItxKx1+MVtH6Ngh8uX795YJsFPk98ecqziH7E2T6dhOORoA5Y/8F1zQrb48IoKebYNgOZLRJws1z2P1dOKU/1EpWyO9RJTwPPNoElfnAolw3Y6GPUtnDq2YTNW2wWzO1mer3G+xQgShrJRG5f1UwWDpMp3MYLcxm4aq/XbLSP76lkUg/Q0L7jhfMGnpkWbcBTAVxSAUx0IKM3RvP76cKIKmPlDCrE2UHVkF3DVTjzYTtcqQrG77iOL1XQpJG6k3MT3fr0RN4R/8+Rg3HI5W+d7MRCh3X1vL6fPE3Qse2IC8+QIT9VdsDyUmslseMoAexvpOgD16+qe+qYihIlv6M15XtYMTr2AQ0dNY2nHwnvGNyMpoIMLnr+WJd3IfEnYAD3AIUNgHzNPikujr6EGcz3HRuGArt9zDi5XPzwF4MzxnA+YffytteHM06Vg/+JctDGleQPjLqSfPKalaMhZpyhHmRLD029SjD3N62qxjcnvnxFbOOu9zHXxmsFJSRYo7IwbUSdKmjms7rAqSrlGN9ChK4/qsgXBsdFK0y355yn17FMuV2P82S4GBbk3cP4YyViXv1XjtNW43a0N7JQKUEbp4bz5MU6R2HxdTzEGseAvTRuw+c5AeG18gCWdqlTNtE/ekonXDbBkSlorvnza6Lz1ApYgFVV3GyAKS4ecX7EPF2ipLhQ7lXHJwm8RPYb6aT0FO8CYpsgiCw6hfjIwnBhft4EkL9EERvUKJnBau8WsxDkyZHsV/BboiTBBX1O9sz2HBmSuBjOLviSNFR7Y4WldPRlOG5nhbjJCFGvMzMGiE4Q7TVwqfJcEw3x8wrQEkMS9bahtnQ7VxbfjXPBHOoK1ykV/ya2tlqXKe0sG5my6LNuIhnuQTbfgWZcgHI3TE82eS8H4yCMrmaUGk7+XtO+XJvkNQtt77r1dH+E5f6mWhMR+G9IIp8BvkPZwqbmu3VaP4f83dB6JCWELCjg1QghWAA449+MTI1QD9mOufzDu9iDlEYK4tT0HV9T5ERuUt7YlNC7upqGFsPicniYjHVfG39UmQB179//mIa5Ys2NfiR4opR2j0iZUE1pp6lVbyvBNoHuDDCjnNV2XDnOKdPOqjy1OlAtZdqLreY4iL0uMSjMIr9SPzAqtdU+beJ7gfwMRTFoRjs7NK98bmhiMHSTReAv5Q4odDmtBHXV+iC+4dCnBGtHjeb3MoWHuqeyl7aKWYpbKP2O1vzBjVcPS0XNSFnJi/a/eRc5wm+GrcvKLCPGPZ3t/oEKJkOGbsBNXWAOKEjT5xxEcvcXOHddjm7l9N94NuFA72LJ7KtNMzNCcTso7NQaTcyK6dKHH0quyAacRV2jTrdZr6MjeeuFkgt5LVmPcdUgZihVD1UHPxqJli9YbXRq6J9CiFGmJZjHYym/JnBeQ/4VuL3fzVF10StHcJrPljTJ2YDiS1BS4PRK0DDRfNaZhx9zFyR5chf69fWYzdMatO3MnJMPqDAYS4lImdAW8Y6Bl4NeJPUqeaxPA6gHu3wXaGZvHmC3vmYLFACZZF3c0gZiziTviUKsUUv7x5mWkhUbLHyotd+4xZS5SaIZXmWk86Txw/h4fKl2nSrO1ehR/GFIzZpwaZHr3/cwXRx0lqDsne/o0HXFv6VFnvMxNeveQ3I9Teu0RvaKjz0IIXaqnwD4Q4qqzvjphkAPN2NaKeq57HQ25TYJTBT1QsGM0TjJiO3X5wqTLcYXsXgUwsHJmdwXPUzSCxZDnhgZINEff7F5rFsuxGYZkKQUKZaqGD77RhNhRlMAH98vN1iyBSeMz89ATpdRPFGYd6/EiJlDKIP/UFSylPokEjZLWvC2kDsT6KdgJKmEPJPNqSgZcg5kRMAMInUQyDHwUAwZfDc7C10PFx1VjJFuY7cRE1MFWsKCak0rJjy9FEjEttTTHrijK+LQNyi92WrX4g0JyH4zVumeGosiffUHtS8KQ7Qgj6mQHco0ky+8+hvMZZFo5ieyYgvrSJexW7/VG6IDgTPC2LU6c+ALc5h5YnCaVxzbohLZa+o8EmfCgW7Mcf53DuvQ4gq6KJcm5oBsQ1qs4KdfSAk73JGCnrOaJNVETWdmLSxEMnJiXGegIpJ+pvPy4gAQNCqcChenwGln8julRjlAHym36sAm0yCIxqvYmyiLLFbhhzfBiPaskhK8MsJbstxT/xTPOpx3HDDffKqJvOl2vY2YpiHCXQAxm56dfWoOnNcX6EDQC6JJQk021zxkmSaH/0geaiVnFSOV6QsTht6vd9m4wusJ6D3vXvb4j1hM/DrQzFey5vQQziwGztUqWWO6lMeDvr0NhOBaK7R2j1ko64+SZB1B+h9XV8L+at3SHjn20+/DMB4J/uAjJ4PbdhuwfJMZZeiumMMM/q8VKj/g1QW7v3QwtQ1t/ekZTbC1dXltqq8RTgULUFjFcl10+LJKdFmWvrXofdwJe3h49V7taY9RHIdHxvu77bff+ytHb0dwJy2MeF12xlPvS0Dcy7AMvD948fwZDfUhv+LAUWTj49c29nyRIGP3y3/MLKpZ4/AW9bHAflXrU/iXHxldZ6zmONsAgVxzjZ6ihF6504bsf5KYDC9ZeoGInT51uIcUIdtZtKUwo+MB6Our3GwPbQhu6MDq+b4QYzSG49HOhA8MUSRe4bEXIW6QJerLtTEDo0H8NdVayECu2hecxHqz18AESG3uvB7820C7wq66gg0jWjSft8jim4UukpL7NWIIMbey77tRhUeE24BBe2LMme8bn2P1FeDpABJHbvqmX6TdVuyL4gtZhhBPBizIwLdib6MZnzBemu5aaZ8DiYzCmTMHi3x28PJ62nXuJWLAXi9sjaAMRBPclLgao82QYUE5v4lAcKYueIJFvpF6OvX8bUo6XSaOm5G8awEXNvrMqoZxWjwXHN2t1Qy9qmEwAMeU2UDjtk2hfUM7oL9M+0cQF+E7JaLiLHXF4DCj2MBlaRKQGMfaSy7lWRNSXKO6aQxAEv75lvFe/V4ZLuQGDV8WQfibPHV3v5bF04K5Y91IN4sp0fvYYruyGQraAvrWwB+LGXACdkEyki+YnE4UqzpxrHZVjdMr0z/06o4KjxPuCMOzuprk6n+AfEDt5n6eRc1yCkYXIKaddrodLBzdQebsNrBfRvK2qazuF/AbJSpY4D6R5GYLxJ8vS0ZEjNIFtXA7Quq5zem+9mZspsCKrC46TaI3twT2LbT8232/rnqAYixbJrO4ue16FbCd5WtBgHF7HB2HD2w5LVobJlJTbtbcvGSlJuw4uQIQVG/sDAOlQw09/ZxbOpbetoXywCmeV4D9Da7HNQ5iN18FZiEAIBkyMJHtr21H9+lFEtIng8vlkv2eWJgzWuK3nJIM7ZkbjiNZnKYrVqhoKuDVu2hAnmUq8MBG9RfSEM1iyLvuce/LEqK2OGd2YKIEd3UFC0yZ0L8BDdsfhz9WhwVs9sI/fd1hhnJWSnBz9k5ZRWscGSfn4BhWzoFyIsuR8j0rv0i5V4TD7YZA3QvP9jLZLaRRzqMQsm/GwoVIfv7EQvKZAcsBsnrcid93HgT/k/xgeVlahXc26gYdmfqAq049gIb4ITMEXoK4XKd2nzZAxm13mzkHmAOEnjGNJPCuHF3tL1Rwmign3lWfM0X7e0zI/UsYVz+wW8Yo2+Dq2duhGU3W/F035wqfmvdzRQYMPU5LqHg7KMzHn43smVB8o1p8ozyu7duBsB1rRsOosuat8Q7HLeY0HRUxXUZ21PlmxEVDNQfn/TLrpbRf3XuZ9S/aKilISyXLnSgVbrlPXLfj8jjUy5cKf4RW935dt6EZImMs2HSSGYRvjoAgiRKmsPKOFYt4s/IuofRYRuleEgGB+ZmhDXJ6Y0UvxeNn5r0biP/dqUzCsQn6Ra0MYOpeasRi9exaCMZ4DiruG023YZsyybou9mWB8mOTMjTR8UgmTk6lbjhkAZgm+KkxlEZNDSzA5PSEnxLkT3WCA3fOUuZ/PbmT3weYZKwya2otwkLsP3dRU44krrP7DmGOdNocxPUnme68xj89ikYEGSvzAba78da/F1piFS85+3y0AtD9IVZt/W4rv954MB/hb3xg0iEA2OE9IctKzAl2In8u3Q0BWJXLJ/7HCeIP7mLry/E8LtRx6ZInt3h3G0SlKoeiARScj/l5cWk2qEdBk5JQr+Ocpr0HeQh7opbBM7eUVxdmX0py2gl2dOECzeVRI/LJ6QSHs1cvR+PJpeHbF1LJoedNgrZ/B0rv+F+RLageEChsuACQCGPT/R0plbj7Yxq5JWCK6HJxwCqtT5z8Iz+uQX9Gu/8BAd8AALj5p8t8Z5VD9MC5S4yvge6xDLWe8OLu9g7jA78Dge1H4/Skxh2QWXMP17PcEoR1jd5vnWmWSV2HGfQvjiorxPxeYk0L5BbZ8rJJcQI37lnwmSuEV0EWmbEcjC3On80gi+xramBe3s3R7zwBPToAxl24K4p2iDt7fq0eskfT9b0ZG6XnYx7DRKckbR+L7XMs4rFFWr5T66npaJDIsm9hzQnfbOWHTgtWqh83qo52N13PDop+WMH3xeng+ooVNKXlchYpM5HDC/Sk0vo7sjRE7qZThSWDkcQMj9dpyjVYAlA0vnq2gO40i/i2l8w1Z1tcSU7LEO7ZQKjXtcu9Jn3YGQvY2OY1nNbkUdrgtyIDxLzgRdTP68RrAXK4ZJHFm7kw0Jztt6OMzHTan6a/r/NwwSAnDyceFhoEjurWmjKtNWrrrlVvKAPWkT+s8OUUruWWzR/OVn8k74ncfRm6DxCzVhc28lbpCVZv5RMHyv7OSYP4xSXrXs+Nykw5lkq6LyYV30nUyzQuFHKFQOvsmB60EIg7NW0IIBQCu+bimKX0nBtj2LjmHBrghLBYb/XkUYJThP9FIYxumfp0KmvksIiXUXmAGyyv7Uao2elhxpopcq/scCvHkyuotsc48CgBHVJEm2hvFC+2WSQNyo79qilJv+oQZZ0nM/+QplJ0Ow6FywP4Vw94S5wrhpWntTF46/eWWUUmg/4PPjJuS8JOVGSqftgMTg/YJzeDY6IEBAMjDwrYaN4HfqFhY5VBFBPnPedCBU46Kl8lZFdp1LoTH4VjtDW8v0j+ScR3e83lUOVrhiFbFL6Ouv/CKyskEbvjBRcjaAOSVBPajdNj80Pi6JVfSxIV4PfekcjowqS2E8xXX4ahh7QARy1yv7zBMRGoNpbCPw1ou6QO5xxsF34pUKl75purrhdnU36pKlYfQ4kD3K7JKxofzLOyna05jauqJYboHyVtjzHi5LlvnJLYHFS7A9zcmnv1Nst8L1f8micZ9zkq0snpZ2irPTQbrqP3R3/Sn2IlrzrpEP22nhFuQdXiijTbIFC+HRnaknk5iNm0e4gAn1YnOI+EpkH8pW2yFhzOI3XuKf5a5NxVRUtwWkdMa1Z4VhePTT0sNDkwvb5BnhfbNL+mrsL9hcbYWbW4BIwncq3V1azizQm1SlWF+RzlOMnOndUJ8n3QeuZOVghZL6tJKW/HkXrOL94IqrsGzmGhCAKDH+c56obGuwniMgNi1iy+SJice2xy+Jub/iI6xpJwGp5QBCR/GZ1shsF4mW/cLmKo8od/kWNdgQZtgwNIx5hCXxjQJsvMF91zs23DrIutw5/Jwy8oEy2IK0JtR2j2HDVyX0MXCbiZ7SXsD0as+jhHecEpeQxaUFQmg9t+TDv5YLru+Lq+180pBynf3nZV3oBzcTp/Uwp0wwg9A5S0TIzG+ADuW8K0Z0NQtASkvy52I+8Abfd1ITgn1Vr01HGOOBEMK+EXWlEM3llA0UAPOM8pCLCSYMvi01cfDQiawn/Y+fHh3CLDQqOd1jYZF0DflXwSpO71Yz6wNBjTnmDhT+D8A8MWMIT3okLBH3SdKW5xK1BXuTb7BPGwQaUhzVGVJ1JEKWE6P05KoLJPjSmWgdtJAPvoqiTZnQ6Q1eA3B49Z6gdIYhmPNtf7+9Is75xvX2u68tcJWqKJQUCbcoi/Ihzvl1xtksTypEhvOpXHqX2qLIyB2y5jJ+3DDpWkeH+4Hw52ybZS8J+bgJjIJF4qXX9M+2GOLdKcZbzFRY1Hvf4MhF2KdZiKrEdXc6yY8fZusP9S0RETtAuO7Z+MFMQxrbqyH5+C9NzdcBGI30WpuvohkNn1iGx8KUZQwf1D67TMni2LySOBtwfMwpI3yNrud9XKGktKISw+xPwCQfTUsud75CYic/D0VDRTbT2yguFhl4clYl5/+TSHXtTuHBx4NoKHb9UOy3qK++Rlrs31dOi8SbraNExSmOuvvvOu2ntEYf4RUToLRAWmua4BI1GMEiO1HOmxm4XUoUvJT/n4bZefAlJp443PQbEgsFH2IzbECjjX7eQ271zJ4TLdL6UJ8Ux6pfx+TGY/80BLggxMTiYwRP1CEvtovn2BZJn4Kdd+F0Iy7j2k9CPNOPdz7k4JTzwsBYOLoMkaAZeo51hi69/HDxOHyWuOSQLsYVlJnarHjWp/1bN1U6twnL2hm5Qvek29A6NyjVpo31iXzYnQwiFJ84OXTpYPUWxc5JQuTij1qVpdH5sOmuru+R0DzvH/BGSNOZ6p1PL9i+SrH3dPDJxwpbntqVJZd9NO1gogCwZRBWvYJ2lfefJqLSKSteJ07ybHDbZodkYJDQJE6s3FxmsmJ1vuLn84yxRdGHY+0twkqY8ElFcQAkuvI6WJ0NmXl0Him2jQyEv1/63FL2FZKzwxsIvpCZ5yCycDK7OmDGAraMJZFC68LIxmDeuLixFlwNrOSx1N4DrTMsY3ujGQjz2IRwS9J/6SQHXj+t4pL0ljCGiAas8/+SG4L/qE1ZuwXS72B4kpynDdMgj6s8oSZ6I1H8gyW0cUNLTTam/afG1ZV1xCq6FLWdbfaVN3w1f+XDL5PEfqycgoiTH8indhxwiBkCbk9zMSM2+8mtiPaPHhTsaJReaHFGykL56J96kmBPwFa5mWLpJqtXXN/+BBkHQgdG9xATMqRoze0jxfYT1rkXw6vU1Q7kjcJvjaqR1xNKDg3uYlbprWKOZhAr7ZvO1CesvsHCjmPzsrs3wb52S6I6dq9ihX67B6K7D+j0ApbdOzgNQqmF+sZxTLnWwpjjUdk21IrGTU+e1IHINqSh6WiFvVLmokGTa74rkkG8rTX8qGQdBFxRpwJy89GxI033gXCTkqGqYmkYYsW61v5jHHiKGwnY6sKTKaPumn+dAH6IPYYTTourHxYYmHzUjybw6EOVOBYNw8Sawa17nJkmRzq6wUjIXBCdv3a83Y8R1RMmaBXUbmUwYUvdpeA4zwZYcvhEs6/03GuwECIfA4pH4B7mq+WbGmniX6BWy4ctGBDARmg1LHhDGHjsfnwtEMvK3MujJbPeYyBWL78PlwlFVA6kHRmId/8ZWWbEpH8hlEePEgl8TMoqqEvjTGYQdHeo9+OIB91ltAB2SvFlnKiEMZNeIVIBp69y6mmwBNgYvG/cUM8KGp4zlsh5JHwSSsFrsVZ4KCZXTLi/36huehPiE79ySzfhisMIwf3viULK/cF5U9MhOZQxiGKAXhxW3LuKrK6BbCmqGgCNPEQEEPJPu353JB/fVvBMiRP9hxxohktCOoFLvO3FQXjjn16h+yU12VdIJ2TjCu38pGWfxkcPPw278Pcifbo96eLV7QXy2NEN5kPdg792D5KOGLOiTWqPZYD2lm8Y0j/oKgzDkaH3M2Ymk4I0fzdzoVGzVDEPxhhdNOQhOg46FjlHvAnfowoCno+l6iSsslTPt/Ol/XC16DdmF0ltr80PDiTXeDNXN/TXa1V9vpozkS+ATPaoLMuO6ugsq0FiEkETlWXYtkTa3cTX30/hVflNZRL9TYjgoLg+pjgpQFRj7eUodK/XHJmNXDl+yZsPe2H7yVA9MFk2uSOQZxG8SdEKVDJS+3DO5DdUMVX3vJRxdqFU2DOkpuSaeLhW5UZ7po9Ro+ZdFJwtAZxBW+mpjTbyrb40GT8uxj+MMoA2IrJOoUziR4jeuxJCZOlAf96sGcOzPqA5+2AqaSZOzlCbe65nCckH4syF99WXv1h5rBqGFvX8m2RBkNGavXiuaQ/4s2UevPAdqcdPmQo6C/66i17Wox+nFavi/3Z7wlHV7+Gkutj7Letjy8wOkxMIwzgnZEl4YWRaDoD97gJ+buMZw9LEYFYMsVdMNaNEBVVZmcjm1o2es2xDsCLfX5ZC9/2Pfj2Zz2O5YYBTtcG+tWy9zMmN0LjLOkeFwupcmj5la4B2TM3dt0aXFGW8QQgDbXu76U72Q/9Xkm9ANCo9ikMnc4Z/jm1XvUY0EfO4S2jNmPOIDdDGQI4eWK87WDb46EAQvKkUtjwFid+JB9PSqPPmuMAo8ZTgLmmMVUNoUyZC3Ml+ljmgccKvvsNdLP1rb0pWrReM8MZ4RQLYgboqvqV1xCWvUR8LE8SpkipuWBFz9M495qh4AHCazSRGSKKG2cqcDgrTNiTcinM+/2kTcJRLT1RZXFhltNd3lEzhZjHErfZxs+Ty3e6z/6jqfytjmRq0hzF4PlzQp/NSa7+wkmbQHqkR2HUeGCI2pNQwwyMhaT+jfSoGbse8OKxxIS9wH6LVTaW92DR1xPuhq3HrLR0zXMHf1NTK0f6Uo5vR3eQAi1K6yd3GOo4N4E9PGXvPxr5E6XkhqjUUXcyrReHIGjiXRkcTTdG8ySsm9wmxexgzUU2f9ED6Xl1AKItv7QjJF4xaWNPQJGJmIohmXZ/K1aXY47U3KgYusbr7kwdFLIvzJdzjFDsioX45S26iEwTRYGO+MAV1AOUxnneIYZG5EomfvB775omy2nPZ6GbJQVHk8B7mQLThuSEpoFJ/unvalAY/7thLBjymC4Rf/C6ZKl2uu1UzXC2xusdVq6RfeBmbk/ArTceadAdtvd68cnGJ85UOILAWWd/jhpMpKpzbFUk87Wz9oeCz3zs94rY2kJ7uHQj8Aw+G9CVv6p7VRcfgQR2IlVTft/PdGGcKXUpc+IGtEDP3INoUypXpDgpFhmXokEwUvUvM4ssVMYbdpQgu02kmEysPRO89Iw77Rvu+z5r7dtIu3oF+QdOs51xN7dIcBCGkPN9/sGw34dczrvZ3Iem2f4Z0SL/EEq6MJD+FKdg5EIYPm3bHvD1uzPpqIeRNjIcvPISwkKGi32fcw4d44ucqYkI1ISTQog68ZFmxSbXCSSM7ZgTxXgUzQ0eSVtrBiEOoN3difMxJkbPojV+O5uP2hue9Slx0MddtmUkt37+uDyK5hmr5TAhgw9n/x/wLf6Ncw7I8jCfLdHxHFKRmBs+WLC7+jYTHp16nh6kohL71JP0aE0ZF5FDve/1W74dQchv7s72FWQnXuMmssKI2mjtdWMCEBSNImno9aOSHe1iZl6zkXABQAqoQ5SM7P7kl/2Ooe54oej0F/VYU/0wyIme3Mr0cqrux2PHREnEGQzpFwzkSs3ERxHVWTGMEJFU3cwC9Dib3dDjT3mvZo9GnWNJPxfWkmlvvi7dzGDs5zATvpzAmhBiNIXBg+0F+WP62cvc6DgliihNRtUp9oN7B6dR0sfSPsdpaL+YOXmdvepRtEUg/4bsWPOwtOYO7Fl/GEGqYIlF36WSkNbRj5EDy3yox/wjAQN9oqtUcNdsl1DzQYPWI7mqmMq/rnOI5nj2yOUuRIjiOjdLy02C2mj/6uj9gyqGzZMAwft+0FU6FC92QlCBoa6JRDc8lZCxwVcz9dS0CxpjHVPkJ++q98v7YtZyEqCpyHlICXozREyExgfImY6o0rwLCnKXWmRciR2amRivhVneu69Le7ngpKgNQBmuUjrTPK/UgWX4NOcjd556xyV3rtwI0meX+spo/vneZhRD7i/ZQBrdDk59YdFIJOJUEaJTQbxcMnn27DSzsSU1ghJNv1Tu7KenIZkpd0k4K02Yo8+p3qItYVpVZ+NrXoUliA2FXYHUGfY0DA9V/2LVE0DHDQJxo88wdM+fcz2+65sYa6dbeWd18doQCnv9hrVHkkkkP8U/J2FNZEJY27v+GDkKsYRUUivDMIOa9HZ1dnatncuqZoHEEwbhz++3agZbMk/ZU/e1UHTG37oP1hPWadj8WNmaBPw1QoLnOud977fZO6JMEwAVAuFnESnTppJMIqfAsB4Ex6NAZtliM96YPiVQK7S5oQRUnQSWjCFcbK/UwjuejUUPgb9D7QrmJZ4rxInZ5WP1cfLqZvAyt4d2eV+uNncFarQAR2abqnY6n7fJwDsn+JRHcF/YsiGhT8fun9spPrnR0pM5iZsQqUjTmXJ/lJvw9MG0nFDXtOdKYj8KMhFVWblqne9aynk4qvPkrG3FrmIasRN0iDjFuFm2oSEDuYk1seaB/6gXKmhvjL9AY5pXbsjwGbCA22s1vtzuhd7ThW2aj694FBHbfdRebA7IaX043wKaZ8NTRXiiRGF5lt0nVoUyTf8tyciCZ+xBFtSkRlfDxCrqMC9PDtufuhb2QcjcG6Nd+xOuv5a3FuQc/VI0phmsHcDboQpb1WUEzpVe7brDEFN0OV5Ks3aERh17QfQtPZeK5Gzdxl5Osxf0LPusnacLfYF3qiixmZhHnru6FIc9Xs8w/hBixQfzyipQoK/v9v+JK2QFiZqLXZQQ2UXNETMcbunNVLiTZd04kWkPklRlZ3aAbvSVkn81QZdRYM4RHxVRTZLCRbZtfOUAqTkH4EBfSykUn5DEBl/DEXJuo9eLFYNmWghZfbjPx7kev1/uFBlkN3+Bp6MMPgpDYPv0h31e9M9vaevIKPgdhD5Aetp2a/zscsF7axTxP2jLM+KMGj70Z9fAadvNeb/J/x9QwXk4/0WfPKq3c+bzd6md0C/yVkCCjWUl+8qA6zDmbK2j9VSLv/KXYuuik9Ml2k/S33/P7ITH//qe4Bb70d3zG6LKoS4WW9WYyGNvNCFseVVmnob4oLKKaK1aFdYWHypKbJUQ2qBddzhhY44ZvyvFbi212gMZtlurQmwTfx8TuFu6tPs4RRc4zCdEix5k7FYKZRorQhOasVY2r7zwaX2wzYdV9w6gtXHdeUdzGPq3Ig4uA0GUARafnJTkxZCBOESEefi7Ohfq4BXBBnSGL8MkAXjEwdYaiKI5cxWcWcJqr1Man11ubERhyngnpk50uReF6QRztddI5/L7bDTBj4JdligEW9H0kuMhWSAuHmqAsiT1O7sSNQrXnnOUOYs9t+Z/pOpYLAVTcyAjTbXQGWuMWrJm0B0+CcMNl79f35l+L7a00SGOkezs5EYrRxnaRpWlrjuUskCS+jrWhF/QeZjrIbBu/dqYAU9VkHqWyejVSesidjqz+uh+rZ+iOiOR3ryz7P5oZCJiyJ+kPyACK4GMlijBiAke/ZfHHPkz07LQU1Si+SvHOlww8nWMss7UDtDkCS/UHC0RY1JC5VkK86AKzrqdGgztYI49fRFRwp32NU4us0mjTGXhk52V5JnpYs0XMoitY5haztfezrzklcvn/hKTy85dxbrisn8u8DH5FsQDjHzFeDcjr9W1dEqfn0k32sxBxm9HMp/rolo4aBZIcuvaRwNAEtJvMZL3fHTftBEa3dgdG7h95/xEfw2yETp7OhubV3ZJcOrYscA4MSdaw22hFI9impRMbC+EdMipe1dRM7kSHdv3bGM3gUdYxR1U6yfOAIPFhmZ6ad4jS7YraaNuVKRZEDl7In5Ssui4YpMGgIEI9pNBiFob0+Mhr+7Wk/hlXKT9SUuLT8sa19cp0Hjy52ubvn6cY+K3PIrC7KePAsEkXeucxx/j1cYiUS2+g/27KGdLr052EOSXIoYsPacej8MWJNpbbQh+kdP049c49SD7rqB6lXFFKjqYJHAmSzodXZRwgGNEKNDJqxswJ33o+OqHqmHwdSrgcwBW4nIHw1WeY3bMGDhxWMvBHxmsfyJNew7SqsezyohRw1BCcN04srUHtkD7M4YJfn8m+V+3Hxx15MsT6YwX7l3doXZ80cWyHWDBmfvmsp3NUOtQJXqF3Fr8ZEv9V3PfGTPMoIkWMq/lB/Fb3WH94hf0cxEmoeXsaOhY7pBozbRvlDPX7xlHCtoNnWhIqDLwUUaDAnzyT1zGa171gVna0Hb0etrrHeKNHii5VjnQiYtoVL/fTvoljclCx0jn5TNcOn+1s/jocludTpB4EUbLwr3NtIY3/wtwsIrgKHn/yixdKQpzZbMD2oDjL3r1Y/ciw7LvP35YA/43QJGW8RRPjpsXH+ivMF75cFPhy9oYcHGtrnOEKyjtyQ4WXIqe9UiQJVwsUptKCsxZz9p5Fe1sRLtFz+gNpXZ7I8pPyXYBkKIPi5GY7xmaOrj5X2oM1xiAGw6SKlowNvx5wSRswUTcofbMTWkwCrCdkVRAbkMTElZ6ZuZPUniR+U8CJL8sv+LOEIHeNGcBuKKq8ziMm/Xs8Ix7LTWBBaLo8VlINyxV7l2xcEY15L2Myc72pC3L9uQq5sbIC2PyJHVJi3ftHCwsR5nCGYQN4pwfeJTYF/oGBzs+CxOAmuthvR1lw0THQacBYcfn2xrFvc27oHZwbLFQJKvMTr9D8/XbYR/GjIN732bIZ2yyRNEzNw1t94M9JQAnbmRXSFBRWijZOVgjSlTcVMk5X6lMWsstGdT0kdmslbSObtKYu8KpOhFiUcDlOGjsAx27g0Jg39Y0DsUW/4+2vjuXNVviXfytjXJKf8Zj2+59wndFqbbTsd7WF7Xj2EUULiTORsDJrEodLOULBCTiYsMDIrLhPHPYuqZKwgG1/FdkfPfDKJ73LwqqJtrjlamtseFsBAz5zbsoPj4BjaL6YAex8jrnV49/u+idAXYM8YJsmQ30e7J8Ka/zsU6GYD4VpZisKC4jYM9UkxFsUb4dKGY0iNElza6YH23Kbti/5dYR/5IoLzi11sSTuSnGGknF82nDOQ1f2Oj/9dcX5jB+z3TYFNJMsqBOEY7aLDT+88BHMGphO0EWCXv+qSurlIAm2KY+orsLwOyU/zUQgr1rV00W30G8KePaDTek0b+mrHop0TBjXLcZUG+YwWAUCQAI6o3+Iss1TxNgCYkQQTxFLlljyI6OmzQFkpcE3O7Lo1n1Oc0K7KNcpOhg9eDPApbtJV3VE8dKZTaXUosCPQ7gZixDRl2ESn5u2MMtmTZ61nR3u9DRQA5fTGlh3ANZT/BN7VVP+yQR/I8uDJEiMssoMIX645Epn665hgMQiBBka2FTgjfxJwhY/brtZiS6aJCsfyBqd576oR2sOGYwifbpFkAehzQqIEH5zgO6EtWimUxamDD78oA3ShxRRYA5fA7F/HXyXINYw/L3Syx4V2SQypnFFdipw5Up9f0npl9leQyaqkK4gTddwb/YQvy0Ktkvq2vNOb6CwMTIGoPuBwuRfZ/z32dSBasnNZfesGA3cL7CCYtWSLTW9uBRxspranSVLHxb0duGLRsQYUUk7heG/WkOSS1itqUF9ULcmN3akFrUdbJa075HNsRJVAo2UaSwx2mDHqumpNE2b2Hmb06AOXUaKMr6preWAZd2ZmiWA7LJ7Z7PXMq562ldxUSXgi0TzWXcyu9kDw5rSDrKEI0YCb/WcpDPu9XMHBszN606iwBgDO1HVFf0get+zmaMOT8Dtsq0bq3WrM3ngPrC1NZYzuQG2BrZuEWHxdtqbwd33FRy9PsBBet4DujBfNcXYqE0UDP0MjjHSHgvQ0fHstx9EIwOTCrVuKJ5cn5x2BgGoASqzCvmDosujzG92+0y2ddmK8OAdYo8QGjC78jSI8nXbZyIRSGZLy10jMClxaOsufVLR2rKWVM0tPszA7Dw7caMmBIX5Bt16Shja596ti2solKAdfiUlWYSBNqnEjHjKqRolNvl8JPl7llaOqQbbfJw1iobOP1fc+JVYDflJJ6puYyq1Wxz2rwoVPPglaFCzSQ6jcsZqjBCmRhP+cnXNcRL6sRCI87bfLkH/U7sQIvRgUCbq9hYb8O7kSclKmffLBa48FniZW8fesFG+rDG8x8KsJjt0rBkc9eCTIdNCkvCFJtQ0ZoQJkaSR6kXOVj1WFokcS9r6QqXcqjuDQ7RYIQes2KzmLaM1svywUz4urhqyaxm4KBPBjGd0vW7Y78yF+3MFoZfGSOGWdFaJj+0O2UIODVHv10FdIZL5szxsmVV47R53D1VhnkMaWg/BS1nXTytTchJbvYCMpUDLrlpejHJ+zlcdaMPj7sOhAkQBfpRE/qdkYTgO88Np7WwyJk/IKXNdAfiKAep4N9EhEz/dgxlRJusEzgb+a+njy+JUUmoOOC7LOGc8SYX+Hjdz7uDPOdP9h02wVxZkro3kcYUwvxp4CQnxQzP9tbJ/uiquGU6Quv/+nNFRo1ok4bF0LT0aDAXKo+71+xdfeQVOMzXTZciXCvGtKmk6LVekQ0X9nZNQXc83fn+xFBAm0zpLzS+18yjmyrN2L2vHtlyf3Tkov+5pI3fZodRTsX4kMjwjrhZDyOR849nePUcu1Zfk1t1pj3sKJYmphMGHGinT4Ltt78W+LED3ZpqIRuyfdJjRIqUwYdomp2vKc0nLwCpjQE4pQtmaHQUIlxeK6Gdft94zA/j87gPVj2EYcOOh9h0rE75D3SagAnluEPAltP9F+XDx7NZf7XfX//s+K/qqQvCvXmJ6fDH1R8Rtn5Ov4t9bDrYdzCgYtIRpRdfluYlnpcTY0qCHFk4caxfr+9k9pPSE1zSXRYAy0WzY0WC6vE1bU6uRRsx9418V+tlXmJruaEzhnTbr+MpFAFts7EvSSdvBYde7N7iu1gT0AC631Xy/rfOq7JFiWef53qhGFhpmiaartEGm5YiEUKxFijwBWwGbTOfmpXx3T46fQQz3NGOnw6e2Fd6I/wtbZ+V2fEpLYUy8EjbyX9Kr1XQXiM8DvxWmnfvUbri2RibTVvEL8UNLQq3Nkusm7Jy2ADkX00lSZdMmrhfjz3PLvHJPC/ChxuTab55p46vAtBwa6FKbKPKIkOLuJnmuDcPbcOgPUSjuoW5doioQgCN7eD9wcCDZJ6TW+jPK1Is3rywM1xD+dTfoGsGsc9h1fJzBjKRzJbUO/wxz41KwzPlB3Qpk373JKbdGf7MzznKLIOkuWELUlcUOU6bhvg4VImMCmlqEpUYVZMUFyuEVWj23XqEwwMLFVNQJ2+T3YCitMSXSmIwpmA3suJtSWs+al78C+J/zJ6US/ZEjNwRlWUSaMZxyyC/Rn1C9smr4vYSJAgxc0Dr5yyHzmA4zB25ooJdgOs5EnXxR9LHl9k2dq2YQV8ZTSVMcAXMG3NcYTuerJgr+xb375lHSFAp1UYgQwAxrMc9QVmAy/vajLJfSrrBFG1Jr8e3NpJcBzNASzZXW3cx6WLmQ116TSWJA3ekffI7r8QMDeH+rOXdrbthCfPtd67OEdOugl2Vmr1wbeyH22uqq5iVW0L+yxmKD3vnkGCW8Wid3JLX0EGavwGw/Hpk2KDLdW26P5x8PfB4uRDcSP/GpE4Szp0WFJpVLBEMv5Do4X2T7euG/H182qlyGYRla8WcsWFCL3KH1hx0BEU++5ainzXPtMhff+D4c1hxHuh/Ec4S32/iAOvHcp48nwQW0wYpbpfrhh589FGqYxF9JiRRzw957pNPIHUm6YVISD98Fr06trm3Kz3CM3rJ1f1ebwZ4XQosCSGoZEZttxq2+LZQ4FA8CBc62/jV8ashNeRD11pnJHXoLvi1d3xU0IUweVElzP8nkv6jPPh+Xi3NG9DfkG9zzj9Fh0W5Ju4E3oKsnK6rM+0+Sw0uIzmcm/Txg0FsXMvRrcQE3Npcs/DnaeqHlZ28Sb/qM3IXWUKaZzO1zCQ3ef5Y6VrwNyVkZV9GPh1LKL90w5j8LUyX5p9QVf5NayBrCk+B73yK3eHqzwfxPHmw4aKn5OAccKUq5NePvo6UHU/KqlohqZuWpOMT5Y4AjpaCc2Zk88HYz51NZbKAKQvfy2GEe/sOOUTX/KEZSpxkblLSGf+/ViBipRaDgdU4FiLqCxQrgLvehk/OYaKwSRs6TrTLmRs3XTPx5iw+8SyiMEh+2PARPotJ8poT43wnyxtdn68X5kZjCSpTeNBr7ckn1TmnhdujXs4Dl/MVqk54DUq7jflIquPK7X7dU2TNl3tahbzJuIfDF25qM7EgdQFiqNT2xa5JgOxWPE1xTJWzbUIAzXx5bGcX0TRl1JPvzV41pERydWIvPALoXrUDx3v8I42ryIRiz0AWPKuCiw6YZxkPEAJzh0mcK7TYOlRxpPhuUCVuL3LY6Nfe619y6HNfDdVHOUA8lvB/XIaJyU13MhWG6iQ100703IanRbYP0KQZuLEYakwiROMzQpz9c0icJpL+WgwOfOhLuU4QvZALWTHCvAharMy70DpG69eLvxl60yE183UOC/A4Sy215KA2k4IBaHTpIjXHe3R8PIHrUCukqlUL6tszOmQSb1Qg4ESJk/uQqtkQ+9GXFFVEU/n+foiPk4fmJtUgYv45om/dqhzzRsmb+f0In/5NadOCb6/B+9k2LCCjyFyzt1NZTJoszjdbLo+rQn+6sYJ236fM3ubabUDzdo7yg9qIm0TP52y2rpgB9xGS866DDvJcc9NG5Ry8IaaeFnnaZLIoKbbEgd1fZCgri33ORMns2FD0jjaB59242O3YRpsZiIYN8hSUqFBr9KlR/bbYqmeQWWCHjA7Is5wriUt7jn0ctvoj5J3t1osInk6+wwqQAWlOMlPd16ZGaM2K0rZhEGkVWnZ84VkpZJYtYZwBwnCEdLIeBpAI/awiLjNJ/9FHRts5Aj2uxH/MwZp/JQ3jirdRrO8Z1CX9HOGxAilal8lx8i2fA5SFllX53KPgptKVUkGk1Bv+slUSJFFR1J7AILa1w6heduCc6XfG17/xdMmZu7lgK1xbnydtnb9RXgCgDoqnrHuPAv6ouDOQF8Ts47YZhgk6ZVclTCbiNjPyZ9Dy5IVeBEwqDoavmAfHQ/X3ah4USW48z04HpTa7kyNLA3273CBej/cyjQdYJCUbaW58YH5XLirEDlksp0g80uF/sKNP+m4QY9m6/KiOenPIzTnOf/7GliVD5hul6z2+6hkt8LaDkFerGFAB5A7VDKevMBDpIs1RvaZcadSEBiZ1JLh/cicZlLXG4fWSf5v/HIPYJOka5l1WPAWaxCGXS1ogqqwBbAjcFyE6N9xgPodwvPIqu3n338cUr3JL/uUm3bUy+A9YikUwb8VThXIr9T5VKhMjDzCmmzJ9DqZcnpw4+LTQfn81RlcT3YwanwwabeMEvzQK44clTNdeEHS+Kq1X00uR5E1OetRuyS93I3K7vJOmwfRRCV8mTLKfnCWoTtDuS8y2MEsOfVKFIGyprxspv8z8h6L93+wiu4C1jbxbYCBghG3PWXKyyS+QJttIPK4XElWQYQvBpgo25y0fOe38JyxwryiNvbXFMRDT8dIOd3Sw6/FkAX1cvq+waivh8oTubD9uTIxv7B3TMf2Bfc59HDQvV+Qn86hNu+WMJ8FoK1zO4QdRT/9BI/yJFhzpstkZU5akRYwW9pJvo+bbJuYsWF6y5SBWYIftP+ASt6w6LHeclFbQ9rBjwn4cewGuQiuWB6CdF162UTedhmLiXeJLfxfqcTcujPCXo+xsiM+/JviiH79G10e2Oec9vkcGMJj7nwkvnbXP1xi+9qIjXpVqP7C09pV/cTWdq1kVtYJkad1dmuK2IJdc3D++C1WNs53ccCENMGKV7l/zG9IlDIfaC0xs4+3ryyA+nGlhQlmVlfLWE947a8ePDjOc00sBBOIjPe/v2KE8w2aPZPdnoGb5qBgKUunHiRDrcli9ugppv4bdqKaAe1v3iHMAKp+IV1lvwip3eFcZH361PIevQd0hnp7UYKHeUiQJD6UaDegcx8Uj8rEcIDPtDtVgOwCPyrA5Y7Lf5ecmxqZsNOHKKZm4SZgiKaHjrL80vBfVdMGdVMwvddSaiiW8L0/1Q0wsoZaOylk8rTolRYoAWAteAnLng+jVC8h0g97fjFwswEvOcW23XhU0egHBJeQPuccTCWknkJ2A7BHpDoGy/hBRuI/Fb2rboz9g5K5yLpGVsFIBh7aWf3EVF6uPGR9DEn5lXiPtCvOamrp/YcgeZEHQKGByzYq6H12rUpc+o/NjXg4gwQB4rB4uXPOAHJZe3D6Fkn8JEfRB5WvfutDCICohoVt+Xv3QpaiLT64wq4BXAjoyp5PBWgnyhHIF7sXbsiLaqhn4lybkIqFQO5oQrusB7joz3IrqAfEFh84vrXeJhuB512G5HnsBJakkFxAK+AyqDWFWcB+lhTRbMa6Vw6wjlz2ECZQrcZAdgs5riAHIKUw6EU3Z585iXaorCrKY1aP3xoxAz5Q4I6D7Ne5dnGiVuTB1Xwk3r4k5yaiDfOU002fy10GdiERGNQZ6EhE3AeEjgcyajjm55tKOyDcOUKqxuGmU63uuX1YJtpcqugP0WOtDJCoib39UH3vLKcUR4cARhs7N12gsnP6Fju9Z7Dj/OwIg/Sp/yBYye8y3EXpOx0Z6kT/WxqY3rgAri6QMPLNnPKxbDfuCafgNXMrGQ8LVUIyTGnKOasEP4wXcLog9ghfThNpVBiIhIfLf820VSpeEbpMHHM+a4tAVMD6ddJwYxGtyXzIw09Amoz/HnZzOtmjOl+mrwqJhFmJ6v5rkNz7ZrE6bbyjt0mkS1ULc5BPeB9wcrVX1MSHgkN3bxKO+BjPWlfVfP6QX1Ruiggv2XZGx00+7wroKG5ujIbcs/3AJ/dGDT979nhryyLtT9byXNIQFuOIn4r4i1785T6MhIfbvLPcTLnh6b1RBnfRjSLhpgfLl6b82J3BXUXj4vR/gv3zGbt26pNSNHRI8pWTs2ho8f2A/pXGaBZVH/sEgbGU0Z/V6DLwSSwlNpZ8OZIoJv8tllNDTDWW/UFIv/dWdqaCw4bf5PGrkBIHdYax8mKSKjrprRnmOmGd/+AgM+G6gLVVitMvtCM4z2UCCdYmPZVLtUfTn7WzuOTOvjMWP4j98VnGDPa8TElTbHDxYNyIY6GrUpgzp0mX7m8wBb8m0+fDVgQ1If0B5ogz4wJSxT7UCRS92aTkn0T+4bIttNvN5JJNxVOA5c4Zrb4q9Gv0StjUhbsC7iL1rRP/ynapR60zyfi53G800YqypA5CW5QmDuugn5Vx+0IXJ84LkR8BPnQ11JLVwpHWEQ9yaFGiq9TUa5CjHIqhT0j2SkmejJ/SoETrfZ4+7V1hoRv3rPDrx/0XQlDyAJ4f3WmHFYd7jLFCS1iqloBxSwGakS0e84lIlifrn0aKuWVOgP9sZFmwAqLiRqWXMHWRsYk06QKWg8kxs+WKQJzRAX/9Z48CbiRJcwbJd664talUadKV+MDbFxhcJZ8+DmBlmKqMpyoblfcg5f1iN/id80xGB/6OI8tnJ6AJfppkiPpgK6JhrdokFsLWLndH4cGVgKUAwEVbiyB2oj9Lga1RyoORQhJ4jbZmIVsqhwC8+zEW5IKfa/Vf+Y+hZQFh+vpPiLeDTvQPds4mnVqDeKji5oVDcJM8plscloZmhJAgYSOo4oT1AtjNDeP7weku4d0ZhRwJY2PVjtsgfA/XWCPIqsdUM6g00XYPtAEP05ATimM9aAdckFGe/Pecmx0zsQevUgopJ0oBwYvFjb3ahgZPJ3/k4o0t5LztNOs8tm6GrfRWHyQMw8M+8w1veGQyKuwJo3ZyF+TmPVQLIExpexNIO58FXSh74MTaVI18rBkxYC8S+/nDKpmp8TFm0y/GYsOFpeRWFQ4rxJKe4oZ6RycunAahwF+3Y7qvR+LUjLidMWU9p17eHQQm8lpn3fWnsGLEvJAAcuQQQFhAtsQbclTGgrcc3yI+2/GeVVRrNXX/o6rcASiuoCAFiWbwDtHY5hhU0qppG6Q6LVWCXHNZFWeTLTALze4ZDmrpNp6cDkeB8a3CW8vkrfZrvkU3bILkP8t8SK/Avbp6UdrSSp2kEmst9BNe7nyRPJ3IrjS6L6cwh5n73zbQjxv7duIOAlrit5q0ZM2rAHziqroV4MPFDJezO6RO319yTQ1T0Ovbk8uOu3DA/QfgjK0aByG5ynjZwCzyQ+CQ96uoGWRMM+32S9IbBVOqP5LSFezv9xSyKZUs/U+owxFJE1mDu/nQckt+s8yYs3cE7DobW4RoYOS43wwQpiYrtfZ9UPwwf+PrL3Ev0I/KolIxOjRfNm3+QcB4DsbtcjgGKWnW5ELOrlpB+TurPMS9gxqD4Q1Os0ZejgyzOvgmfTJibcSW+JfVXZV8FciHNimUrmuiuEr1XRsNFI+GO5Kg8G/UmrQxci+wzugQ2Jd4COuPblWcuXqiEliIO4rNYA/AUL5g/k43F9kAr1O4oECvXMfh9t2Z8FvxOrC1jFFN3M70f4dAXYOuB9RExappHk/W7swl8fTzA3BzGBsXSdTlVZ2yEy+fGCb60nOzmCtxmta7dsXHWym1pVWAK240GZ7zR0kuU7O/WLNbvt+dy64Ci3kzj+7FnSHDvOR5cZulKe5u344T9i4/NrrJFPqMPb1YXkIZWsHrZ2l9WRiMVFuBB4xZnQx74TzPm2R12p2Q8yrA9O7omcrcrXIiFcu7Itn8xVGaqa62q1NwGsLHwMm/35VFgD91kHqKRKZesK8ogxscq9f4NorfyqgNL8B/yTTgveT4WjKUXs3hezqoz6MdMEQQwNZr3rRJkPX0wDK8NA3t/NH/u6IzFyEMi+lSJJkmX4qJeTkBrLgjDib3WNDertBPQqeH1Vzpc00sdtwjginjf2Y+XNV+piLFOYnfrhaxfwICpI/ZGtAFyRy9rFqazTeA9kuW98wP+/2lckqj2ZsZ74H9RSvoUuJmLg2wn60yibIknJCdWbhpIhFEHYS3REXVKFza5LWk3xXviUQ+n4ySWnrGW/DDAGIEPbDwYT0EJhDR0AN8AJClDo7IsVhfUtddVFXK+Hqa0bIkhdwV6pC4EnwxMCIzO1PLBcRb+JDdNlGjxo62CFno8/tu3iq1gJR0A4ttVaWunfxNRYcrkiibUvPzfksAdrxLr9sWo0KICY/I0NjDmGHvfSfXxiylgdBcvmqetrQ21trYjU7Um7YlTK/oWTIZiubZpNXcCyAHPDDr/SymJgV/K4Zn6rSovgGs1jSBG6W1PGBJqgvaB+8Ere67A/WEz9Z9i/lTHoGwO9+fHyQSE435zGTajX8p5OBetD1WTNbe+9KeF9Btoujoqba1cRF/t7fbmk7frrDWVW+e/rPTDt8gfGLfcb9qCGPTcHhVtt27+fZsBehraQNlr7ZzQFRFk327dzjIcNHsVjxnCt/FQlyie249TDx+GiwVskesJDJhEAVfr9ikFQGGjD+LaVvgdVSJr66pbuHZTOWjxfoWK/NYfsVY05kFYmQWdF5TxU676eIHawdxtpWi3PndXLhOAcL4hxyAMi9cc1+vKgEE5e+Jd1H6AkwHkMdTAsgJ2SAKduZutoOEksksF2pIpBXtrZxG1FhP9NG5tGXIvyFwqapgxx1j1IBSKuY6nJcWYwxw7wmFW/KPtDsPBzNxrpSfr5j8tbfmyVIlow30hCIv+Vs/OQuJXYDEYj7yrkQa/ACXMjUEpBTZg0toMcg4vio+JJXC1GIRhnrc+uuFH0u0cIAIrxQRNoEmYU4Lb5RPGnRGfGD3xnlj1fT4AcZTqrrDhfYErsm+fwavsVVUY6IpvyeMhsWOoN+juvXM55HAm+FDYzzP+9uoufSKWaQKNlV91dMjsGR/7oodR3tLlERMEvrn9Ukxk/VjEEgpnlfwlnvKhnfU/FWw6mWKn/Ozc4QOm2y/HaJaSR75PS26WmxAa6mXeTz35IiNo/tZd1N9TjPThLy5Nurrv2aFwOzvxqxDa9tkd3ur2z/5a8REF4G5KQSKlzQ5Ks7XFf43Fvxz2z5I7R5LWE+lpkfJcY3KhuxgZ+p7Jaa/D2MnwzwhDeL6Nk1QQZOdODjeq9VEnLaFcHw+BzGtTWDhMqcHGKacGx3F+rqDH0XFiB04B9262i6c0k4hIyoz0XEBcsNCWZ6SyTT5SFhmIkF8A+Kdt97j0cbZ+klfxbkRiUz70c/oIuaqEqIYQA/qzUPgONVCxt9l/NIbwikMh6qhKN7gV1O+CR29TDj6cX5RslXwTD8kDpDxRC+v3/uKQzo6WLQ6w40cg3fnmsDvP9VXIVbtudr9K9ZSZOGrvnpsaJHDyFccabfHLPGiGzRvdA0bzWRaOJm6Dpt/U9cvAUqwFbKT5lwL2bF7jSp/bO7pVNAJbUF/5UXcBkQvU7NArao7GzzD2ntFcfX9gKW/t7aWMbMj4X9msaufTwNUmvKW5OV2oyJ2OkXavzYN/hqrfVV0qSXGS4OBzfjhEMZFpRlD0qLOA94D4VhZPKMWYXA3iXOJPA1BHph3G5QWu7BSF75iv+SCkVBvU0QWvm5HjadxY109BXLvVb6Q7HLES+piLw5AuTW8dB+srDtDsLL2LIymGZCT+Dlf3nSoVRQomYYXJGTmRtEnrg2slthFM4M9scTN8uAh3TJ/8BGXtAWMwGIhc6BrBVkYPhsZIB2dQnqm0Q7BxM8lAWiYOzxGjHjDtONGeJb0OozfZDNna1JzCZ0Kaw+Pxx04JSfr+jnP5PIoZHtGxv2/51k1MSqwwelcpROxbxOm4dvzruaUziVj0itx3H8lTwF8fPndMYkFUBJGZXLco8oqjv088hVcRoqYKKsXVcNdCKE0UqYTmnojmfebqeEaonRyVX0AS1INGzTmFeg2PQLOWg4BkcPLsBdjBtp9sOvzkcDxj8emx000yx5QXYVUMQh16a0G7dz35d5CONYr3AsgMH3lz9eQrDPe27eZwHQXdheXO6ilM/XdRFZJOAY3mMKc+rucKgdkJT5CFCRd39R+VVUddGXg9gNlrMPYJr/K1HmBAiMLUUlenrarKZpNnXF0lfa3yFbHwT/J2/uVXifYlJ80VrEmDZ+EMt3a+/lVSX2ov2mqhhOdsYJEdztezywfM/+77Qwn9sO8WA95tNbDRN3EI2NbttFMCfpb6JIWA/Km543MvUitxmPfdNz5WUtIcT0FMcdPpLUahZPHM7auXOnFEcGf8AX98/Ains1cd74aPAVICsajyxEyELOfqcL4k5DZGQwGV9bsDnPZVcN0oXA5cGwIjiQbbqxXjNkt9PR4o1x1G3GOC5BDHifha5JcjnHdPgvzS/gAdB+CYvdOU3jzJ0aCWeo4hJv77KSbVszxwjIYJFwdHZjREc14OuBKJoRMI93/m5kUGLTFjuEIrbP3+D+hyMM0GR2GI9E08fRHuuNHT37Va6CBgBd1ymxVgxhupx50GRTj6q1LXG0aYZn5wEApuiDFjCosheTRGkHW63nrZfv50gc0VbglffnDttPQKiR4sBjSlNo6y0cQvSCstAzg6dkJisCfvQxTFEppnLc/CnRBWSqyk3E/o2ZR0eqCbSHvjdOQvP5dbzut5wcSsTcri9nw1re2J+IBFZO/FK1WZOYLnDaaXWu6GZ1v9c6D98rI/bPPT8RXwMJdsjOh65zBhvtEQrqARHqD7j+W27HLZJO4EzWiZJUxOmDSrqhBf/urSYG7OdNCLMYlMPk5Or1e5rMCWBH0UufczhnAv55H+3JkSESEDLrhx4dRfB/n5rKoVwR90NDKBFWE9lolED/NFFp79EWgnMzz2ZXAkqFaNKnMdyeInOhX8RRRPPgFyGxWiHNPFQjdc3HBU/bHBIdKnPtv3ftFBChClaArOrmTbRo3NdUEjF8s1Z2Dj+MShR4eRuvGU81mCGw6GA4DIFuK6eOgv4LZqkRgKdSJK5Cv3gtU040TnJCoPTSyn7WHQFEtDLcFwB8sejnF63K7zQXzPjfFDSdR5m50H3f7Foypgk6F9ec107q1Ix1cbcLotsiyvYNBtm6O63UM+GxnOXK4WZ6JZJu0EPa9z84IPcwzwgPW1jNDzg9lJBQ4PojA3HQ8TMfEI5PKJAgmXjSA9s5AunfUU8rFtN3fAovSXecf8pxg0OTY5G4fTyPleTttVfTD+LlyfN2BN8GE5b/AUcsESSmuZ271fkT8CNxNv0QHvz1PGJtA+c1VxR1u+cQ+iClQYZlbxJa06HqIYkV8Dfs7Gn6V0Eajh48rDEJoPKCvJWsnUIthbu5eSRY31ZR4ShXj0uYnq6917aB3jtE+T3nrmJvIs4ggZzbvbcBN5SVK7b/BITdGNCi5B3qcYTcV3z22LDF0ZSBE7GER4R0KmemBu5ptBBWofhGTAVGJCz7gVMnFkQoHcMtIjAHIfzf4936XCOTPLWg4oQtjijk4TJ7dHfDCCWz1kdrLhNj3iyoeGEqfL39wFbWfh9QigsBIakxcAll0sFtWw977jCmUBHsq7gysRKfOGywKK8swrDvgEM54Pk2FEy1jdqSsJvEiDjN083+UrkWk7t0MGNOkPlYcG7cc2L0odykkOkeaP4Zn/inPB0ILOb9p5ZO5/rUXvGRjsE/bcAPxRZWQvguMd9hkCXyzUHRH/KQCOB/PFobbCIlH2V9W8yMyVvv5a6xoRvFoGwODqic6vqTEOICK3LzcPv+bOR8wGxUn0LVxeVf44uoEajUwCjJb/qxNmOJJD610iWjS/VbaWOxVwdxW26Vd5FE9Ibp77kRYKFq2O/WMA24qbI0gvywrx16rTgVEImfaNs3AuB31GKFaDFAedvuZpjGdre002lLPswmGkS6Q1XoDBethVq1hykC/ODb4v1/yNkzUMRs7D+P6Y4sdxuC0gafzmLeQ1fZJkOOciWE3ASwprzAeMYpZFt2SOENaCLkPLEE8IZ+G/HiU8quNpH7f+mWVb/FoPLK+QgNH7Q6bXs0jg3EYIOuFoTMaVkivr7BEHz0kRGHWn1BGukWg9fsfritvFScHRKxqCUtODo69kqYW7m3zVqPBGk48k+dWDPiH9l0IzydFph9qpnohBmQH31cpePDnLcdhQhmg2xCQlRf+nay8zEW19FoxOENj+HJt8Od972aljCMelDoXf5u9iEBoMO7q+U6NAwsjgVrqgGMyE6O7ywRixROyLyaWbn7sG9htOmliGnp/hZ2tWhlFqCJlrPe1tYbLeOIDf73rbOTR9Vo0CwpWILscnof3CQvYrss8GSgLuLui01Q94QMRNV08hVCnM7ZeT0ADMlf92LPzC5KrCKO6C8BrRL4OqB7sXURj4lJzYFpjDOrqSm0d+f73uiBDYHKQlkTKgnhV0pxMiKvyuygeg1JWR4iNdXyKKHIc0s7HwAUbACLMqPzQpx9U3dgwjk0WPF+1z6QJWRquD5cLKocv7zEeGCvGKKyPY5IlEAKfrisN3WGlQUouCUztpPvikPNW82NTi4Ny6/AvdtWRFpEOibVInEBHF4z0+Y4GZHjQR6SR1OQBglIOwQym07MZDXVOaXPMQeEj2C53cjg1jfDYkn41JIk0/jce4EYBVPiNywpZwt67K0oZ0IiER8ZIdGFeoraPd1RprBgYI0s6JscAGPrstRhwFKwNZtbu7SW0Jzdhl9iRmRG5dJKNfkC9j7OlFk5uyNOswQCt/AKSwGuijg3FrMOdqzXvZ5bFZ3TVklF7Rty/qhqNwJUum1dSbo0yucHBXj5kIzCVrF1yicj1GLjQaRbcueYF4hd2TkGeFdh0UslmCFTNzEIea2El8e+SEj327a09ULMTMCPQIsL2bWyYttzQUkDu4sMFldIuLFoFF3U2S2WWXxkjE6Pk+5kak9dsgaZES8ipe6vbcNZesO7x/5n7FRfI0uqAe7V2FIdD+zeooyXPKogmzYEBA3tVCSZ3xQX3FiPoga3nkTLiKnO8tpRMPTg3oZcXOShYINh9E14zqKWJcL4FtEPX2cTw5FvjEGrGjMRMlIBF0ByjQT3M+bcwvmjjLFhRtqRC8UXL9pWl9Sq+rBGblLYefSMh5l06/uTkBVdi178fvhgZ+cXYRhENMxDGNi/3c4cnKiIYu/Jaac0fNEP1UJdJ5aDKtqh2/JnMcK52P86p8QbxnCQ7lslX3eNWZDnc65rHo8ISRTZ4QoibZJM2j12U+0HI9BWZgomPs5eIIkl8oiChBKsYEtzpRoI3LvLR2h44Wh14B46m1Lpj7M7FJ3aQgZCfNanC0kQy7N1emKEtSahDuOwRmaf62D0oG6bHP1QdLUmV07dL5PdHGdyM7S8fXGrlkt+VtoUsMoJQhcsyFsPtW7UFH/fOHD4d3LP2LV7VMmInx0lIgY7UCaxKNZ8QthyUv06cI87qjpWj8xW0UfNhMPM3b0cD/i83x9UlWYYB2m0mZM2rtNBl6td4+IaSjSqveYDPMSnhjh3VeVKFNq3wZQLTrHVRuQvAk+mdPrlzk5wt/uTykOT2VrLvvVYCK9GLHiRr1ewBvP22nB/AsJ0AOPbDKg2wXn4TVuudWgQYjVuLjUhtH68bNwIZRx90AbL80dALLX9bMUPbwFessb0xPm7spzz8NmmXRSk/ieqFZN3VXsQSXx40lpCPzUm4KcYcJ7AnlHL6iv0z3mBXrtt7jnIWd/DQBCjiLGOMw+onhFb/+DKT2n3rjNgN1dlIQpvJMBT8J9opk/fIUweeaSMzG+z7RHU3Q6/CDOazt6avlaqJprcrzESv5mAtsC3sXnz9CpWs04YCbXMgIDaoBzn2TUZjIvaBuU1tpN6YrODLOcZQsgfFEQToYfLgB0JuIuQ8zbQldrCCnRad5C9cPn/ZjL9LnavO+mqHlYbxu+X4+RmtuWDuUKdsklcj0Bk5XcmnP6AoLv9NaZhDuz7kTTD9lNHqi0wKxpoT9S8OTMfPKhLoEqHXzaTjXazB9KiSSga8mJCtV6gnRKRDrTSsuvAU3tgv5NFbGfNYnZpp7oJyNMaHAYAw7SxkdIynFc9qf7+5jGe93TxonKWlLrtriesBQsnBHGVecV6e9K0RM+3zuCc3tOUQocxcXQVz68MpJYQtD7T+cw8aPChLOEEW/Raej0eXD1jtw7YI3090gL9rhlnJfNS90EcZhL0ZvDcFk9DnQS2D9msuoFkz2jiDKsV+L7RYgycV3XF4mxuR9XobxFLrcovlhpeLtfRc6ZuGxstM6z8+4m4BGu8Mhmd9aC8hOKov1RGDYnSAXS6O+AabReM06wFQvWcwLT8qwL2RcZkivZ68TIvD8DqRcZvQ89TwuXYgfyx9jBjTwNsCAvXJq0yteL1dAm6GOJuYageO/nYDRUb95jYtZC8u9tnDW8rbMFrYqeMiBd7ZwMNG4gkf98+kpeR/3om1MxhC6OJUniBSblXiaP2tkDrVk6uo/VasZLV110dqgTs6XBHW/sbd6KwSm/K0mduY6flce1MqnOkU20SqElQhr8CWZRQ+NZkLMDnUQ7Ajt2bAnin9pVPIshelHI6KYICRm7tcOXMETYLORBITibZs2dX+Y3uYjCqTj4JAWlzJCoVAornvt/wDA4icTI9WvkS7CGq4Nj1mEe3bpm4UNiseSxwA5M22Us4O2FKUEkS72ifQWjkJSGOhXm41LeAS6p4MdjmJbOY6E72H6JIHPHOhLeAXVsX+M/Tsa94x//KlT+R6lHiusxNucsjuBtxxsPDYV2Oid6R4TBaVYNQGUNkMUCrzadY1JIdTOm32IEFoZzamETNCaCs4P7ItEM33ElKwAm3ulhi9HLhtqf/+PbRvjo+AWATUANhME/mtnIKcPeMQ2Q2WU6UMwHKFlvFmckAdp+7s0Xkv5eo6xy7FVShJNYd+oJYdKQroDDCn+4lHgotoDafjUFuONpoBVW6bGxRX9a0r487XFXEdx4MHD9qy+w3nXvAxAHKUcUYbswIloLxsb1a5idbrVFSDeDvY+OJdMGgtjUJYT3ZRBgn1QtArhuCyIWmse/tKpkJIVTuGoTcUZMN/CF5R/+vSM8wWtmbBELPKDq7lNT9w8PLIrh6L+eb7/PHdpzA5bu1VkbwV3lAlI9Gw1MdD1nCWJgU1Ch47u/JJuWrGIxE2oFn4wHNOubLfz88tmGjo2XN7LmK1EyP0K02kqKuV16OGeyTd2ipkPK0hzgaioPFdbg9kM2OhtKCtMpskmJ4FddoIA+s+VBf9ur1LXKMLXjGG2ncXewYqcWOXBsUA031RhnO4mP+o6Azwf05mqPsP9TqrAcEl00Dzf8J1SPJ/tqveRhJkD60bCYjXlV9UVBAvGD5qCHNnDNt/WU2m0g7kvLrEq6nUnJGXzzSlDvzyRs+6y30DIZmZT/Y6eTue1XszvNUHWnFYxot83KJkeLt6HPIemL38ajhkRdPGt40B7SzIy68pbIWfpzA7mNjZ9pdZ34MeL53M9y2QSHZghHDKlyORWfSCZYbeNk0OcianO0fFzVNMSJ3rZXtZp5IMgOyMACTFKj1eOwyvYsM/Xd/eb7/l2tGqzwqbiwrkWrxw5MmN4vsNJn+n25fxCqNlEPohl8MpAl4o0uMrSNyZZKWgOWxBoWrrgUrmKVtuLF+7NxnSP02sMm7nWO2c4wFdyoZGqgXT6fGiYDvUyW9jM0C21rT5tLM0kZdOBM3R0qb59ju+MW1KGRoiiS4pLS6pgQ4qH+me21y2knmhfvfvyiplnYEikhTeOjQDO3qsZF3s2u9fFKgqk2/yStiJQAt28jbudA9QiJVXC2nq/ldDJ4heaG+DvYJY7zdbCqu0+goM0NwZsxNbsv44BjLpPaKkYsGW4JgOoC/zmu2SSxdzq3AsDzr0g5L8Dt4VMnf3Lweke1r+warXKXKMY4lIcleLBkuuItzQnEexFmy2C1dZ1mHVRW9NNg2DhFvDa6CrpBqUhxgkpc0IEyCvMi6a0Km30w83Nb3KQ1q8W/KKrT24NzwS6NtjZ04xJWlLiJqnnGiHLbMSbWvSZ8lys8CibIreRFGeeVaQM9G/LN19nk5iBjB78MTIjLpAhrpoz05kFuf5lW7OjN4e33opLc/3aPPxuIJsqZpErWGxqw7mcE2aist38mEu2A3+ei7nm5/sT1uY1lb/G0AQsV54BAG+FOo29yYVDdvz4RykMCY/fzj660FBtGUPaPt/iLfNSvdP1FXAGStknn99l58BGIxKbW7hSWudVDGhb80pxXW9I/JfySOV/dnn+11m0uvAH+ZSpZN7/OnrdGP3rrCUo3+sXL7aT8RTf6W6WMePvFA2ODUgqqVkBmDBqrlCoCWzY3u8eSkVXusIpIeyB/7pmz6sxNQ3iD5bLCUJNss79hq/tvkC8AFIaRUmL1JgxasXwZhdBWcDAKNuoe9lI9CKZs+kWSfwnkRf9yW+lSokhjo6lsTCbo6ntTtV5a8fK3424QkrpW6z+9gEsUHcJ/DDpY80FSpoIO+64UCcFbVidqufLbRLsgIChUPLTNz1i0dlOxJKPSYYFU6hRXeXJ19Jn7/EIg++Tb7pI4gD2/jp/8cOtkR3SQRl9C/pKH4hW+k8KVG/gPKv3/mFTOxFM6dRtWV7OBCvb9LtiOMveKiagQEDcFdiMfcEgp3QrZxK9ZBFQJ2+IlM9hHHjSRUCSm/Cl01r/WmH2mWLdyQOL7ArgoEY6Ciz1+kRngZhxVPcKtDHUWP9Cfxqy19azy7GdgmVmp5JwREZirCsD5yAw3rLE+zK6xFVlHCUg089g1f1tV2P3OBJAeU+/1DxB05gA5axrcCBhmhlBu9z3Y7gxhtX92uTXgUM62Xmxi9sfQQu2MNhmcPsshtCqYXrhG+mFXyrROxEJZhZHit5wu0MQPbGr42dldyztw3vFz7h3mHFHJzf5URc0qcy7ch0bUNkD9cwvjg3SwQp4GQ2698GpYYryIhAcm5DXChCY+za6WxJcNvFUjWtDYXgrhvdpEYGAfkczGBtC/Q1MhZ/fDD3l82E3OX5YbZtaBcZ6B9rCoXJD7NqPR0boPoBMPXlHzbUucQOwHO9wHOLlpHzQSzwRWNe4B+z59DtNygfnqSi54ltmTYUwf16Q0QXvcvCZry56NpMOBWx6sDi2UFnd23dF98Yy/v6KnyBJieMNBim1TXb2N6TOh8PhIEFU2jvIGDBsCw5kkeY0l38HpxJEgc7MPe8uuGA9Ibc624l2YXagGVNPCaRuLEprZI8TYRdUTWAnN0dxBGcCyrVTY6Ly1SS8JIUKuBpwJ56RYYm1Mb0APeY3+6KjlncZj9OgqoDfqEuihXAPYjxRxVyJBBEP2goTHr8oI5vF0HN1NmGNHSSr2nfcn4zkrQVDVMRlpZWO8zyf1CGNRMkztkRu9SKVbYlXFWfrYm6RB/GxT3QmTYOF814+2ag4H26W41Xx3GrCNc9MyR36Iblqmv6BAirnUewWlL26BuO5KCNaICNb0YO3O+f6aqht8cUBGaWURPA5tJxkUt/s7RIqefsoCGIpDr5TxyaepBxBVs/tDedsDGEOOyJlXQk78KyGzMQah8+R3kj3Rkp8C06u/4KiTfQxvB/iFNaOXvVerpptISIQMlkM9v11nikNLYpc12rkkYmWmK/zsMmjHoARUd3HFbWP6KJgrEjiDu03G0mPnTY0Qt/A2AsBw38mwjG4YsNm6uLQrP9aVTbdSrKdDPBiLjg8Xtgkx6IprRpcao26Wb3EDjNg556msqPd4mqseWa8CQegeRXIMX2a4Px5sII7kg9+9Wql1E21BsPfbKELS/McopzFwFx2H3XyayM/HjRgXaPS6dwykgPOxsQyNJP6Ufyi01Ykr3y3lyb1kBgrRjjYWPn2Q+t2a9+zCVg70CgzyHhgk+KB6u6rAeGXb4v+LsOw4khZ+mIrRZce6iwytuz2KhmwwpVTXa9mSiDcHtGJZstwurPnaB6D6mTJXxYRuorWkvnGy+Mhpe+ai5zRuUNtEYwWlJ0pIqaK74zC9rzoeMkuUFNAvj42tO5ar0HaFBtrCoD8/aKuBAe45SiTb6NM4z5H7wcQjBk0CvzlzWG2+ShFrtEdJY++qSxPIa+sgiklMqmfSo8Zp4H7f3GA4/NdwYB7Ysgs5JOANPJtCd+TrCpCTS1ve0cLfnskNIxhLa/SzEp/myuMhYYhQhN5qWlf4ywVHsmsQpQvlJ13p4JjvocMI9zUKbUK9Ur9k5+CiN4PTm0GjlTMNC1bN/wFivNXHt856JlU+6/CiCG9Z/WT+wgqfC/A8I15/y6drBAJZSzpHj1ROk//ymme/lMdo9EVI+NAfaAxh/x6GaloEPLiEsMPafhIM6YdEwvD+6DgY9YWn8sioH6DSNKs7CNbCvkHx1oy6WKvQ85yVMjC8uM+8ZSWyk5EXEGnrMA+z/aKZaPiihHXusUG0AKs21IOjgI0RtyPoHZ0KiwfNxeOKUPDxMZ+PErjnTm+HFBiX1zPwG8qc5RUQxlBtjW2Is26F4N/mJ1DDoaMJbfMXsHOGGzlcTgc0ghNpjp6w0jinATwQVU4l+0nGExfSXc3KCLFZ0e8Llg6qIrEFJ+4YvQkwNNTK94BiZpn1mDtqEacvR/5IkHfN7poRHWb6EyMxEkemAJx0l4TMAP7JGNJVrjmwxouB9YZUtrL2aF5ulp/jep8r9RLc8prCHs8Ug2bsoI5H2J2buHovTpLJnVO2W1cZZ1LGnnBiTCUlze6Zyahcj1urZQcd0uTnrkENJheRr16FPuYaJtAmEKyuRSrP8+flfeUeZvRmmDbQzRF3umjjyYVFbfNct1qKhQQoF4OxQB71bi46PIxadPvyF0MFRL7sF+mt661cdMNJlXWqaGhX+UXB7JjoALoWXt4IJU33pXhCptZvwreOMWvxgDGRQ3jvM21fqTIuW7ruPd2HCd4sMJvU1mvL5xzsByoXCof3FuKbaXofHsvYV4rFowDr0iczAkkOj/YjSu8L4wygZqHg419bBePLzTYhEfbV2ocLQNDfbgg8PFrRYsPe1YK3cLZGhP7+XQBYnIIoEmEia5GlOEMl2szgGRzMliwnyV2wuBV+5MuJr5l1zRK5FZeyUmdAGdJPpMGsqLhwcE2QOOgSCahSXU45W8LVsHLjQXkLa0pebgzp3h9qNjD42gsHzFlVN1QWLkvycSwsKpd+v7FjfbVySTpFShOoai9/Dp9FfmphIEAmeIdK2ofxvwyGY56VyaWZ+uAtX1GH86AkR6bPgBelHq+AbjvLx0KzwJ6FOexccmEtjA+cfOmouG5OkHdw+NmGkdIRpZahkqAxaux2a0ygFoexeFMB93G2Qj73Erpb5Gm3o65BU8CkgZhdl3gwpD7aMt9MG2B4veSkzvgyXrFzWYaLjlwGXI3ZfH/0A3PlZH16TsgEJFdHtgd5q4hylLGnCAVj9UGGPAcTjBVn5uQWOi5g2wOEEoslcJSDZtoeOIUhZzJ5ivIOpHGfJyPGbiBAPtgids4FqbYqnQbtOLbDggNtxtEv90CPBkZqTwG5Ps9PuVACsZoWDE21WKtW00SlgYdhuA9jFg/C0IO9bjjoroAbgBsnIJe+495gn8yUGUsyE/cirZAjiQm/f2TVvPXnKy4BtoRDDqbNKGlcdARDdedFM+xMYN0e3y93NEUiiOIfzdh8MAaXSPHEnrS1H5jMw+ugDhFS0mAwyuXR11G0Z9Zr8tR2dXFyyujvTgiCTrl5buoYVjHS7DUfYKux3Ei9UJPTjVVo2hZXFbKC9XlqsBFN2MloqlbVCKqgFPf5PyNQ19tNDkkoxazxs4Y8WQj4pWofdZxNIAGwY3xO3zVoJHenXX9VGZFi6ggEBZjawyUz6B7L/mUz0x2+pabt8QN/bxXHaGHHmiQfviynsWb2RmwNqA5fZFgBFDEadXuLrvQXauad5Z52UwKjW6acQ/qPzdtyelHwsl4EGW0AIVwSP21dNnEB3+iCyE5QCMjQYBzGS4mGQYpnzGwcWzHBnyueqagbPZvGjvyRlEokCDR9ydvcD6ay2j6u6gRTYqJmp+YzmCWpPfFp+VS0aft2qADC02UX/KiCTFygZqr1k1R/tMpvipp3xQOh+JUn1p6X1E2Wyav3epTMP6xzNpr5WCiTx1fZ0+U+dUOH5SL9rPh64Af/LZ7WPDhpSH0IavXJ1S0E9OoXJop9i5w5AHqQs8x5QD55pcOhDxbQuJcM7b5Nnwu/VN9qB22ehzvukDy9FwbwJiC4tlBcPmyMWq249nN6BzSpK7In9ulieqZKDoOl0SMkaMsq00CQ7mvoTvggtlClcZ+NSuW4L0zthBh2n4HdEfrqqvFnQnJTmEex8LhPrzneqV3ySrf+kcz5zO5OavoaZx3W1Xl76lBabxB89IAftBpFEmT2quEcsd1DUZO/9NJPIubPMy8c7B1sNEgq5smlzqfPrABImr5dumhWmrH9O+vpLcPRlazvffnuYob1Z84AcZVEWnbXhb+wcezwRmgGsW2xpyBMrr7J6JLE060uK+qgvbmjvAqgMZlWGqGzqM27SaldVc29Bhe+OHKEBwg9dqQBCya3b7tFRKVMQd9OPgdZ9LwdhLY3t6daDLPOibIBl5HGVY8U7xDmOOmswPmyZt8TIVRpGx+WwYxvnKAtHtoTgP+saQMh/tZNfIdHHAqJaNnKZpbc6pLheY298d6+eTIG7RgU0VNR61n3aO6jqb0EYlJTN78Tg4LSdHjQjZScp/DwK2MU3T3YPqDZjzLOhv+StX4zP5gCGZN8XymWO3LtPdy7HU1v2tTIexh65ltgETYar6lhGdTu5+ofeyJO+pgpGbQIG9jY2h8FuiiKVdqH/ji+50Q5X3STbTN8mARnZwglVoBjUc6y1ERnzBuwvni4xvLPuBOe5lYxOaz8EYEyBU1HskHNlSowBol3lXbu/pbVDgfB/zmdRTq+HZC6wTOBWRo2OnlQeN7J9yyyh/kAmUEAO2rRUtWW1PrFfFpelHmwVdGXv0QxzCvN9kLqPcXlkguJbDWQilHKX2cI+HpDH18jHnCCm60izutamZTgZk/e1rU+y5HS5ZmttCHbsRvngirTFORD7anxmdgCO8aMdxniU4G4wSC2C4NZtVi/h04l4iziohBheY0NLSw4R/lDPRXTEIMxEhziOU/P8GcXAOwjYSWkzAQiykh1xxwlwa8p6tqGx4Phy+eLIzSbI0SYS35yPJg/MhQvmQoADeTiVHTkO45+pKSsiJUqmrORnJMJW1lgvieOKppqrhw7TrWnf8bAsigmSxv5xN9gcJqnHuIPrzK4NnLH8o8diWDCxKKS5EZnLFVMtr78YOQ9WUnL9WGjYsVNaFQhYGzFmeAj/d5ta4vOvZZaIQgjneU+MHX9/YwVo5lddq1MQhXLZYUHWVI2Td5DAedGy4rFPkwGOREG0fN8kh/BsMNCdipRwVsFGcfGh70eoWUlkGW59XDc59ArZu6cJt8GLDHBkniH+tqr+uS2srLFVfVR3wUblJdzJkeN8yxlHE81SRdN78HzHs4Prw4cQChRxEzyQO/lga/gKu8UXIz+64NXn2SEMmP+bTX8/9O0S/TTpTGq4fmqOf6VmDu5R44LiEZuUX0DGri5r1uc1ZX7tdtWuKGZkNnhWEqRU7NDsYjbupVoYFzfcv7rDyG3Z7H6F9mw/4+l0+R2YIUsvWyARB7jlHWxhNjKABrLNZpZ545MP1gqu9QOCPH0aJwsAYRSQhGZavM/EuAD/58kCmnrmOx3FwAw/qZd5t/AyA+nKpXQ7+vRt7+QX417C2LLykQE62z/OeokHkDXG+K3XsPeh/Lr553+aqR36Q+7pTgBJgx16fSqBYNACa/2ufD00n8QeN/hH1bjCeFojVSuVZYfLgcuBgACaPbYvkyDjv5+bjvImqcI6IJ0M9OD3NayKhJkzJoxV5sx5k4nMEJlEgP6x23mdH9ZSwG4J20/ok3iUotpy3rIPdhkxUj5QHC1ZhiygzAyoMKdc9kNSmIYGnUr1E35vQudc5wM8B0TDnZaw6VmVDw/DjA7eYfA2FAS0IHR/OM26F5k5kooici8+ZZIfpSHjhS+kLHo+gbOY7VPYYj9E9YYnsqcXxEImYWQPY86CwmM35KuH7XSWQuNLYFBqkAOwcfBxZdjioHBm7teZjOI0c9KXPC3c6J91OmJpdJJZiQxNzZRe2/upFhQQ3FlHE7w25UlDXA9T45YQA9iBV5Vv1NSnGhEuv85Bnafu4YamtEdD7k7MHAhkeJuwo2rz/ad6R9oOKdas1MF1N6JcVYzJZcON4VtPEoXFkugZskNh4p+F4QE4Bh/I8gme6dZBJRNyLTTZp7Ihu/sSDOcUvdhNNGF3VKMIrz86Ld/mdd6Yq/Z91/W6jvk5ix7Ue0nDMHGrY5phdro+BP0tLHV6A2Z2RBq+8J+delkP5HxQq+QPntlUx3S1Nx4Ewpw0UlqxPoi+DiTUUi21cWDk+bSp6cnqVPJC+R63zs+UGgiYqjX4LJrb7ZW9rnWPrIsa6Rlmb8s2MzjN04adJZqpRtp2i2p6GyFHISDq292BFFQYF5KcrFiq6Ow3Jups5Mc3Kp7ArRo1JHk/lCxF7prhp7HyAFMLbn2wNQbHnt+NTLyQk9IMpfdD7Fd4OgiiMrjr0i+29lnh6WIkBVvHVNnWyPmzlIjHzPC52woISguceEKcalpvlJIH7oAylyQv81IdL88WQXl5YCrOBUK9lcmV7A0ysexNbzrxkplzhbBpyy6QTG8eXU88KzL4/WeOgvPhzd0i8M4hBL1sr7ADtWxtdDotPvD1pDjlkTizYDsmTd7BAOkRs8fIluFG02Jjk4Al0iAlYovI/GB7DUaWe+ShbW77RfxI0dNt3dqEm6gqmT5hwaQ4ihOPf05e8vCLRhqtPjklGX9NNJ4Y8NEfkpAJjF1vfnqMSNHtGKuC2N6XHmVBOYVEOblePUkiaI1oMNBS6PPsKfPs0x49Hwzjq/17g77tAQsv59INnL+1ZH5vyLJeTpc1zvE5TZchId2Va6Exa9bG0t5j6PkeK6r1TzNkx4MKXQTaNEvu0xxmGHMkImvbzf3aNRN/ENSKlKvcBW+Y0SXv/Ga6Gbk6+8FNZuSX5ORYJHu7YmIJ8E256jwY+RVDR7LSFqGFuiE4foRBmFie88XUuUfMm2H1Jk9dnojEDh686+3fmKd6qOkZ+m4qXUjDm93K2EA3dQ/UBm/fUGGrq4PkmIxFII5uzwoE/KHrcJNdGsWuSPuYMb4S4EkgSoK4rnpI/819+WNmLiYRnpEUriCtnfry6MqbxwKpRRuxtG/Bxc71oeaXtxvu+YR1+rkg1zFH0qjjqgcotxjau+5ackLjRxqBP2CtM7R88mvZhHhGqAFY2izCMy30vNyA57evQM6Crprp7AX51lP9OehLpfwu6/MN7vvr0rj5pp/uh+uiouCkbYPQ6kxpJHvRrGP8+8QJcqTQ3iRj6XvqSk57R4N544cDP6QC7lYclqa3p22Yy6Ut98xCkiocpioIndDaVK7pUwj+ZwmsmBxe5BJu540uaM6nUwycZkED1uqQ5zYhIF30lW4CQr9ShoFCQhXjsYE3ts4yms4G0DepNMAli6LACf+HbXQUIksHi+i1dT9ebPNo0aKv2TJU3wUtx2nWmlIpaIysPwvmNXZzT/oi0Ej1c6ok6dY2AjjkdzeIbTMckjo7RUmxEFh5SUVVCY8CzQtJj2FelZ0siaQ98cfi7VPO24KRl8wKDptaMyqtW7TLzba3+iXz5n4y9Pa5MwmByZ2DVXAyJbfx8rjREnkg9JfB3eYkCay6gRGsrXtc8wdtSwzvfITJBZt7SbJUW28B7ZBOyXSvtRtA9QM652L2oUxQws4mbFqfiZ+y0u634N2Ew+uXY8jjLtDFaHLEobBeKfSPPcD3mHRztjOJ0w0+WnkTZ5bPeqa02mYibGRD9cAhe70WzFy2MAnR+BI6f3/Whk89qCN07qHcdiOgJFfFVHt+yIBfqUaDyVlvGbuAsnxOtCd3wsvbvDNsJXeFRycR/DB5rKOxYqohOHIbQ9XvOfa6gGv5yb/R+YFtYQBPGOSHwsYkjfdcu47A5ykuGMqU375aGFNjT7yn1enCzbDnCkzbcqLgpkz0fl+3uVsEcuVXkbgoNtlUQ4gEMOxMm3zTwO2+FQvJZtfL50UIomBf7toLBLV5lMpRCf2zrJltlpImhUuFolTznw+zSj/rXp5XEL+ne30Qd1v7qy4BpKL944RXV3csPG4gHQ3KvhfJAlAqEmN7/5hvQXhLQ0O9H5NG8IYXEGzKj3ia4mfYgqE8nLTWg6zrZgpg5qeEbeezPpLKFvUeNl1CveyBwzio5rt2vE04zQOl9OsEz2M63TzE8rmhSzSVTM8EDtKSjjgDtrwwEKo2c/Moqj7NJSpvSgDAx9OSd54q3KmF8d4+bG61SYpnxe7mWRptrHLPSuQErsNJEafCQzeHTdCFwR5CdVDSUvs6YIfQm5YemFTREyAa1MvyGhIsT/MuLJhW0pcCsloyOvWJdK6Ue6UdMnB1ehvw65ihqmiIBnA3wQULHiHV0bzrqivg6Ye8zdBlXfYaghL9H6hHb2s6Pqy7RIUItWu3s1NvaTWgRqkN7l/0KoXH25DPyH9H5lEQYWDdBU85vJ2mU09F4bQqFdaf6xz2nVk+UPbj4pJMLwsRG8fbXh2HvyojBGDo7oMTfu1+WSX7Kdaj89iN1fDLZDu+TtC2kF9i2z9LFSH5lkltyrxhcPk+RuFZ7OOEoO1MVlrNctyW20TnfHmbVH7zGu0SBfvqXdZs3ub3K2ioHxjBVWUl6ta9EvAqvCeMo9oTKEthI9PB6vV94dL36+snxRh87NKvRMek7kWCbBPv3YdrzrdiF/AGOP60FGmVznjHgATBWuk/bOG91UE4oNcVIThidWvGL/5HlJGilqfI5YvEawAEQfuKDYVGpOdJ7otT57FZWdeKra4D1J0StaMLwzz4TKQzMf8m9tiKR7f9QoWrrRCpWAqUN3IrLey55wgCb6msMbIFegoXeslJ2j4ZKwO0mm9yAOO/MNkH4TNQWrUJ6ph0hqGRePA484EPhqkrBUgI+Y2Ikj52bEx3QG7tG6Gycua0sXh6TB9RQ+pabvXbnNncTkIc1wMxGDHzhWH16mqwsoBIG9J8XpdJQ6gMHUnYUeiPJl7Md2hIxpRvFDmHeUyT5A70Fx9doEByhGtliOpvy9CEVTrPoOE25u370IrgbY/a5OkLsWdW+CaA82zGb1clJbGhMKjgfOtk/r7dZv+hMEvNnKCJJIQplJI2VTz2DnihodXWNvGHc0+M3z4FaMzy4ZNb9+9cZXGQYJCvKtiQZXaZRz4xeyO6H4pnMJpY1KwJxpcah7lc7QyDxJSCDI32v1tlW7H3X+OR5RvUTnAOyrNWIWGr6BU1QfJHIouxDlCDAfMsuPgN2k/WE8BtRttnNoA/QWnyFpvEvdE5C5+BIzY4INpjH5rFFAnGyfJoxH0fgx+kIptdKwR0rk31K8T7l3DvOF49DTw0gjl69wryPJuWYD59qxRPCiLhzyo6p63y0Y4eBzvUn+7C7so7CWtD94we0bEn25D/Fp6dLW3VwWrL/nwai1ZK2E0nVnsBWVphLJ/dN4HAJsbTWzV2YVaiFijl5qe57ACDBF7wSR6XbXsHCaTwJMg2CCs0CDC97nRR6WRqqh29r6S1pIBtWLae9mD209fpk2iE2yUl3eOBtCAg8wYNT+gNQnLEI+/hKESGYBTgvocSmbFdM3w0DzU/7LeaFpTeGBv5+bOVebgIiCXUf+jVU/h6FGE5qm5UHhXfLu20sYqgdcRzvv3hbV/CpaKHfxbEf5cNfX73ML24GVg0RuS9Dxnkbu5fN7B2qHqiTzJbJ/eYqMMONvSzgvcbKpjh3TRuD9ihjfgfbEMrarSCJ45inYnNbSj8rgPRqecuewtYnEJ18Z6za4xIjGjBRyh/ZrHVhfutgWceG837limIMWrCXSDVSP7U9Ll429Un4DBJVMIcpz7sCPKQ6fX28Y2uaaOo7PkW5jcOdUD/BhGYE1B1sy1HsIXe6MUCvyeviMWi7R3F0nuwNtXEtQhSANUr7YKGc6MXdF9Lk3fTDeOluxS5f8UMffLJ13h1ThgR1EtqxJ6bZgrOKZR/FVIi0Irng4y3fohR1U/NoOLkol7TYwGZHma3agKviB8e0zjfgxpRHMwPQJBkEfMxyKO117iiZfssZC9CIOl1uksTtKD6Co+G/f07wG1ViipKQpuGTJDf2ERCLQi2o/Otd12yBog1opRDXiF5i51W97P8GDfAKQ1nbKPXyurxOmS3XP45Azt8n9hDjTY9ofzRbwhEwHv0+3fiuQG5rTVnmfKlq3bza39ge2Mz/YJ8ga/n9e/I6PzHfSzX1BPzDDAMY9p8kLPe/KRaNk54hPADyMSADRfl7pG/KfuehjlhQad9rpsLFJBE7MYyzOI+eyBjmPTgNmOJ8J5wKSImHmD7kGT4vai5Pe5LXK0MqMZcMX2b2/3Gr3LsBuJ8Zswk5foD6pJvXFJVJr0by7O95EjnLufk4kaOhxn1n8X/nihamKVsvvLLxcvFjMMZF11wdvG+dlI686Aj7W1/E7jFE07WJMc9mvZ8LIrrIOljQXTZ9EZTINFVnIcG0WIi7rWSCpHnCFVqDn2JSaEB5dFsIEi92mSPPpBYJtvq4vNgxjgOUmCQ/bF7IHczRE8qjhjP+hFekSaLN7I3AGZm4mKui5x58+WGvNvx9OkWFYvC4MId+rYSU9DARlPVUWqHURCeNJp8szNoAN63/qtvguKDkhoGWdbraIc/3B24dUia7MAJ0zXwhtVKUnbxsu6d3xsceVMjgF6Dx5+A4pOcGjoAExv3d3YJ+4EbgnUodIFDv5ENhyysxWWO+o8HDVAKXGABvBTckuxvYxDdzxU/CdbDMZGjzrHRBwcbZrDraPZffmOGGziqaD6Ir0qMLSe8sGo1VDNrq2V+Cbe4HkJZcBxPvhbG4yN8u2CQejVXQTwlItO3zyYt0sG7/0r9zpF94VFN4q8XMar6D1MbzH3QJecrOj5FZX6MSFJh7iTRrEfWzjZ9HHAy958zOFGwd0tjz7cvxVgjGboPNpGw+zibpwI7HTYkhjpJMGkbYwSUBkCYOPLCkdT5qxfJU9NkqlkO23zM5HpgfDgRjT/E/oNinqcqFEbiS6o/KtTwrAH1fC5RfmeKZizdb6ZIZB/2ttPfitrSSFH04Ym8eyKoFfNP/wSFFkVB+Ve/hrxATDej6rIU7LBkVSHav9kJiuEcMF7YvaPVcK+4u679OaY3k5dE93WNZnqz1VVbEn3/PvKUNQuxId/+kfWbv/Y8BwLO37LtfF0yQcV3KsX8+DerKD/6wZ7fk8O/aLD231XcMGf3s4s27SnSmk+1aKz6N7r1xGZfozER8EbyV4EcDhQEXJ4y/USoBilMeMzfU2hGExDDjIoiNDPxoOvtidkuzu1Rk9Kr0JO3NCpbpudEd5HYwekgadYRNNBSBKTnQZs5EJhjuUBnmD6wIxEo73b7iyJ6KCOsUWCEqIM7bzRflwfnopDTjQsHA8DRqSRtqVqRnHtNWReTyiUG8LDrBN671y0XNc86QNbuIdzkx26hT5QO7FL+edR4BQ4rDAcY+kPpF0yitCMD7SlxbVy5JBC8nzLJqwCLPXBQ6eQAj75NgRO4xbLW7Kwm3d3mvFv5wILjKbRFYQjJZDxnjcxi8tOHxUronoCn7fAA6AFUWj/1SGKX+AiXIlmK6WKnGUnUO8+KJx+lkyTKXf9RT/l12QXDNmJchqyGbguzj5/fD126asfQ9dPs9/xHdlxTNPyx4x7wQzt91A/gtOIMrcgNkh/4hLtFl6JE/2kIX5UJSh5iFmuSUlbdsY3sc2f4XKjWvaQGXn2lfQPXE5IEH5BOyyLHg9s9tBAv/GRtIyNfJwPeZo6G6J23iNKODmPX28CROdUS+GE53Y97FoYpCkdgRVMbjt8B7YFsMdMhiQkb2P16gbGu15PVG947N8EurH3JU6GvCPfS+sr+Ew5xyQz7erhQhswwirivauX4iqGi1ZlseB0ZJuaXQxeAcUycyioINW3s23/wijUdabQB6sPjpkDRGOEeXpJi2co1o686K/wWJDemqO0HYuAD3nl1G/MNdaQB8+YyTwLiP6GnQGBXEqEY7ixnWdP4+XB+iE4zmk2TOSkMJdU/FJYZIcbOFuSs48roDWQgwXrOTnD8r4hzOFsomfA5NqNRtiMImpT20fZIzfldkD3dESc3ccQNUmfAWzr44EdCs6te2PWsgUlDitas6vaJerNTqoFi8aHcB3PQkvZxOjo6zHYzuC2ZSEJ9VibOpB6d8ore71XLDIwjRZvSxl6CxE7HtjzlLODfmxINmpoiyg9uSh/+ZBsSHVrxhkhvIBqocNDsn8hHWnXcBljMngs03uUsUakpDnnRHPuvfpndJxbvfdU7zslYmKoEz0CZqZm6/LS50h7xFu3j8PWOfDyBHktuvKZgTpGS8Zr91mX/47twrT5okMKZ/fueMu//a1CuDnzgMhzXH0FifrNq3Qc3M8PZm/FzeJNU6i2l58MKKVIgslrMDwtsRA8GlQWk7CWhcK9jUTTH76kHi8K4YTSVUGfWS43WvSAl1DDnoyr+ybDRkEVNbv57UlRN1y/mrDNx21sXxACeW0YimVu5Ud0NpjW0ORWfTlulR84PE3aYsrKe7QOuZQHg7n62BIMpLBqrA7yMkrFBordnk7voZ8cOLxzfSoP84kPMKedVfBh2/e6r5bTcj9nQ5WxozLLpV7khHHEORnpBiMmv927/c8XClgLEIlIL4Y+62e1aGmw7zJ726Gwei/SV0FPDP+Re3Qzr9Q5lthC8YehGlRItuX0Rj81c+kjKOjPHprX6nlW+3GoGgZuCI1xTsHYnkvlWiOXxyCvwxHVw2mmGCYlXcp/nGXl9l8MUcMnULMUhDu80vI/c2JGsc155IzgWCXy7XMsv4ODweSUboZcJbJ41gEYS3jeHFDw921LIXF93WMsOxCkdwEpYxydFUQzsr+dNuDruXOOd8Inxmt+7t2/JAdCMXxt/bIZEsLo6E7++QK56joASPHWvck8TDskbeG4MKdFycOPTVQHpTPOmEABhDEaAMmD7IoZcc1Gik4gQtEDp/CnAMgMLCWZnyNB4w1hkfKpCfo0DOcNd2NpqnPwhLyaOO5JN+ndYIAXK5tg8asnjVn/oPFp7c0eauH/a4oVURinzyJ9ixyVXB2LGcJNTHgpw98JcBWtebz/Iw7l6hvNCtR5fPTUBT05i85+JXuZFZ3YRnJ8yNOHkFPdNK456GsHDU5bYRS/GHGNs0MiBmGv/0x04EedrUsTxmyegZBK5IW+5VyZt0WBbFsHVp48EUlXjws0QZW9iOSV7zyPtzhTVx5aoA0Qm+1I7k3AnG6gMVD9372XR+FArp3L3NGRPs22ej4IYWblC7BoV/ysJLzoBeNe9sqrsTZDhR2/1G5x3ZxxNBY7u67oz9Pgu70DwXPOureG15u4zK9WM9UX6pplywrV9FouiCw+AptiA98hQMB+tr2XGSilSkwjfXlsO7aefnxvJ41MVz2q7oeL5SPjW2zicSwpyEX2j92cZSeCdNnn5V0C79VcOpBYuY4AVVAtpyD4eRTVx74BlvcJ+X9noEKVqlCZSOiHhiio7P77C6hzn6YE4ms4RS/VH5g2afRJyUDuMt+9jx4G4d39/ZCoB7NvfjyxIzy0UHHh5jVpFZpl/2guSS14b2Ntm4tOZND6eLDzyh4xZ6rMizLHpx7ZRZEvsAoO6to91+l2rYL66XB77Jv+wkqvM8z6vEmt/bAv96SE7SBtZkU/wGNZMiTwMDoMOS/Px09xZ0b4dArJ6e6yLl/XQbOFwpD8wKh6joISRNHaJA5A71RXMXMBdOyaTlPwCOXv1+fkAqR+pDFE/woPIFAyG2l+UkXLiWRgCEbhh3Mk7P+ELxXOwCmAhsoUhTiLmlizn56Er+SVygO99VG6nAjxFUEbDHzp3okSz0b8gw0+yu9eH0G2tBHzhPsc2mCMPTCnAN4dMYYob9zWf5Ibpj6kDD1NawwPDe+sp2V8bjI2jhr7R98QcBSjuWuJ/4GovULJnbqO1ndKwirBdUKIDNLnnmYQVJJoqdUfUV6JmSZc1+6pQiqxcY5DZfadqHeqOzy1A1Wj/BvLft5pNVPRBk8meOMtJ0GFlE8ETbrjS2S7wf9SOnFrBHZAXfdn9rnxWzCe/HtXv3jJBuH8BbAchnU3V+PyrYXmLNj3r4NeDD+dbDpoxvoPGoYKI49EOsuiLiLksnuf0AOi5zfzADETOfJAwWDB5TnTVijBzYi+3xqhMhowtksRAa6/NjjV2l3rmT8xn2Xskvy9L1mkWqucr+6u3oFQVv4eKvirAauvCLQEEv2I6/abQeBBXfCH2YR+3ajtNhoiuLpii11O76+Qi+Sxt5lwOusGlPsf0HPJhmdSkod7kst9aGHY/1dSwzbqqFSRsGiUD+Z5jNLLyjBRDAataDvCndpfd8GkNAdLxzTjJT1+D0mBJ67ZLtinCbIXeI4VN3NqX3w4tOi5tBCseSLCDjTrRdW1LoQScNtnX4X6+cjteNZApfo3D0eg41vb5/VhoPr42qBRpoK8hqjqHRKU7XQGrIswdAZ2FIimuxB2tswsiaiDs6G2TaEydLyxw/BrH10m80bsRpe8SUcbOXQRlZI77HaL6YXlYB5pS8sITxlJ39wm1i31IAJcp3J4v5svepuK+NuRhdvqe7DRAAtvmKebzLZI7VQuIp+XKNHH+lPTnAFdQ7vZtrav1GN8USO1EOt786yY98hsqQjqdguem2vnkM5EDMjLdUsPRRUbtJ4lWAMFYGYHshh5FWhl4E/8lsZFrIQoTnvUidticHa+svR1kQ9Bt8uPCTBs2vnVsTzLmwykoS+P46a3HpUKKZNBU4k41uTXGEu2bKAmgfMw/kFgZq/4yAzM8kZeg00TJvpx22ZgaVKpi02SidjGzDIbnyajLzASe+d/iCT40tPDrrm1YCkVOdzMeDCdjKAJWGylxpt1PJrVV01acpWNgiBts/XnXH0MgtaAteyUtZAwaw1/tdMURFxcYUG2sOEtkgUH0dlunJE2AfpIxF9M3Rccqw0sX4cHoauhOcmyqPUoua1Kn3ROJuIoxxWkGsEbDHxNxvP3rNSCIfuPz1UN7yRQkxNoaZb5kjmNfNYbQ4kbJ5M2zuMbOboHnqahfUV398CHYeKe9ZB/V3DuusiwNxwHNLVeStEjnoQ/nGpbkGD1TYuwx9V0+ub8vs/HtA0c7NRAvqBir+wvp0t9N97W+pQRmJxFOxwSPbrHZ9zPK5HaON0APlhLzUhSzDTpCx/HOBMGgaqIi+Rh2JoozHH44BHXnTn29G4tY4rzRLjp7gRx417nowlRw8LlJ09zz6VJhL34XCnISjSvqcut7VREGUM349SnEfA/QYW5I3Nwn1olNT/97VIu8mZ+/5VB9o9A1ay4YC05QyG7Q0lj43AZvHEOIbccjeKzwNls4gp7vbIGfoqwm382XO/b9YzcP+dzDH/hvfvYT0Jpeq4rftgJLLjg4AwC8//MwcDxZd7dKjf1n52xwHhU1NpNpkGKVgR+LvmIGfxOGKbrvic0zH9BrmmIy8D7ywq6ipZbuOIqM1ky3CwgV5ztCwksEjavGaYF7T4YlrB6dXVtq97TM0/ZnDXYG7Ww7zCItYl3lU9ygDUoev3PHI/ipSA+PXg3+tmRyoa489E2Rjqel4a27pRQSy+Yx/StWxvZNSoxNSXwwsye7K2XjzfM3DiikJY/peyjIL4BgsxIwwOG4h9nEO2gajoDe3y8qnl8ilFQUP9NJlhZx6v2ogygN1x2i1zMrhWMz7KyYtX7LBcFudydpREeDaalAw1DTBAJQVGzuTBbiwNtoaaFIb5vfNhERrBAJWSO9P+l3XlVzUswqZqip7QawUOVrAEbzGB7S4lgpLvEuYMWgjbMGRS9DB0hGtYCrODXlUQhBabIFg7RKo+FBMPM9mdL7XYJnxsCN42O+AStUeBP98FIerwBeHkfK1pRpeFSiZWueJaKog7kvB7+PmsJ+ZdaxFrNeqw29R5/iWUyLY4XxSSKdTOUPAQgfumXck8uPoGmERATraOVIn/zWm6vcpdRjk/ZQETc/GMkfMhYdZHZcwkyrvADoa3XLqTpDwoIME+xmS/VEA1otPXY8WH+cSpaP4gA/ulIYbFcQijhRWSeoCqNhb/QK6MjfOr7OzAcShqppvgV/aS1XJz0nejpViau9qUwOvSRfFq9OV2iRmM0sAAQgAsDOCWqaBV9iwcHRPQOTNKOeD32VyY1Fpc/h4RW1fsxAiF+7iGgvALtVAyY8Cbn7jUW8TBnS6c6TuF4Qk2PwZlyb5P4AzoKQNv9hgYtveyaILc0hD5E3xUXywjFOvoJJuBOxYh2Os9CAjBeokRCTGd/ej5wvV177LR4MaA3Ds2SznbzFbLs04GKUVwdfIe2HhiAASfM/sZkSGHdG9eaY04m+cLknjHqU/g0JJRBQiUpykSL/wTz4AcFIzk2QoHmoGXwiRb82zcGS/DyNvk8hhPxHCBpl4jbgW8zhUZMM9LF9DU7hkp9FgIihxxfXm0YzUeQEPY5tg2T469OzOYJf6evIhim3fe+yJrQpl4ZeuOu+IUKlFFEsl8qzL/zkPdW81cRtEuMzQgPAnhZmCyi4ZY13mJwXqp4aRrV6DFfD6isyzbj78wrQ8Hl4ehmwzP/FjHvfhEwYoco6h3DjX3Lc0D7jmgg5X2hTZcN4Y6ioMVN4T5q74EohXmRRN1rwYwd2HbK+oXxyD3c2na2VMnB7pW4SRistwIR/sN+qTWrS1646SL7X33PoVsP9soluyBeMzy0h5iFU0O7mY+TqocE8gEybi+LqOqitPdXHk52MB+KXmT7r0GW6d1BQ9zvR0v0h7tC25Hb2ZtmHQwKnt/at7q2HLI6aKr1LcIV+y5Fxy+n8wjt6662B3D9XSO7ftzbF0Rg2vIdru55g/F18ape9RMuPiJyzjymH30qi+87I3EFn46vCP8XPwMGiVtBzHyyQlAO0buE8S3BxmkSMXHaW92YNRBsaZyf3CAPHKsYuvfxJ0dM/h4wO/dh/vtMSL+DuIKAf8Kkg3X9YPTLX3PzwvfzMTHPehL+oghSoZnG2OKli8b4GTxYpu2aMNSPBryVpjh+PUwn+YpUcWgaCCvzHK274FnYOWcDy0f5jpesPzyNraTWtUAbysISJLy9f/EizPWq8xoZwZf67nsqKMFG+bg45eKEF767IOQeoHfXBnoVf8yfT4XUXzxJePvu/M62uLHwcjIklkAU7u/8fvhK+J614MP2MEDUQpnXyKg1d1NaO7ahVHl7B0Bvt+bjMG0a+3fWwg/oBgMAcj5+alrF8/fsSKHTav2xJOrDxjvxR21qY83W1jS6BVYUZy2At59VRH/oq9A202yzOdNbCDSkzwPAGMtwbJxgiNY2S5U3l4xBpwULz61892An9lYpQ3hh/7lVxCarVAyOU9bTZZG20TDt34k5Ne3IzVKk1FxQShh6yt+a+Gh2QC6Tl5D8Hjpg4XadpYQnug5BTRXo++Bgo0fJPTll7yzsg10dFH5m9G6Q8TsVxyj2YQ/1jQOmwpDST48v2CbteK5QdWNJclAy08AtqAhtovJqC6w34sUMyPprZ7og6C4uMzHasktX5ng2eihgPk2DjRvjp+WAikB18VjbyC8UtJvp24uRxCXEFDIZEdALe2Va15chnyEzw0rGYaqJxePC2q7LGRoN5QJEiCCNF7lU2ArN/IUM6Gpxnx4JmPUoOTbYhte3UzBIW/Q/tDyps6CGe39BkUEEtMpe7oJMMHdVf2Gf003md3OFrhGePZVthzI0cjnMmofS8PrncD8FwjMhRhB4InbgH8hM1BBxz3DlikxkHY8SMNyRMWNVwFOHOUGDNCeyPP6Dm4YX0puDHErSczpH4A1J7/tZD634QpewyiGj3dMINuzLfsWulQQkno/Ce3Wi5szZsqr6GsRkNjFh5zWd+MGzLyL8K6vSN0NpYy/4JBZTjORFfT5HSetLH5HKLBPAnhpPC+XJOAxNlnadjnFNlSI8dWpWjPajvoURwQ4jAiVobiDe0Q3Va6rFgXgS0fxX4Dqo9u32lxCsZQ9Xns82Wm16KPE7FCSdFpBJIhZ2PAhWNEIvxqeJ0YUG/5R7c3dRSwWoUCjOog4Fp4JtQaBQBYe317SGP03wbnY87KHWSvaIXgZOYv9vXR9Sop4tdNDiFd3PCxulO9EUd22Wy33BY2mLFJwDQwfRoMaRBZX3+x3/NN/10CtuuLHky4e67ZLzW04VCc0M/9PAqCxm+q2Tbqj87LpcWntfSMsJs9WI/bK+51NTKaP+pN/g9avoLhOTW0xI50TlWh12Coqo7VUSYtofUyy8OmeAfILnOEeo4rdt7ZxDv6li0nqZ6Hf2IRxB9I8Kx6K6H2WE3I4GSR79gHq+MsOqU4LQune5m3N5b7RR969JARXoAtYkl4TwBqqfca0aHcJjpAc9Lnh1Gosk61uCaDXhQSo8DllK8V+GhtxJjKvvSAsa/jy69AO6mCG5r+Cc7kiE4hrtxSsmJJYtVYSLo3iNePUz6zd9N9PlCNHi7BpPak0Gl+giBZwJm0Rfx4gbxnN8SFR7pQiNr1t7NUPc2/th8A4x8sLJyfbhssWMSqDPuasJeXW2g8vThICY14zFha5A01pTLLKVzF12FCeunIq35KT8K/u/RN3ttMXxuhW175v58CprjP7BNtU31nphsZeJFIVLBKD1BG6Gd8ar9cn3GiukerfkODS7T/Az8Vn+FBSVNfTak9dY9zur6MoqZvM8kppZsO4FWdC9gYtg0YTs6dqHDRWeq/jWbfzd6QTX3ez/IqG0y1R5a6Zd8d+zZvlaH7W4KZxmtjJyFKp3i0LRTbtUJ+HnIqmshTHK5FMJulNpSOPiakY7mvsyYmDMxvFa5sQOr5SOq0qjOcv1Lz7ZODqf2ozDl39bzX0f3s8Faxwipvw0qmEL+jWATy+fDKFX4f9l7q/+2mwPhk9wrJ6v6A3iWvtAW1kOzpvbACg+NGVPiua43qWOjLw8a6fuqgb41r6rkRCLufdvPxDK/+06uIdnaOlp+0mwEEJn4mE/s0ylju5lrNcfst4FSNvVFPTyP38nA9x9oKGD4T8eN23QBccBxPJQTgSlXo5sL/7amYGij+61kFSYKoTJr3S4l6glXtKX0WupzbncHW/tvUwGtBFd2DgRqlegVjvYGQiiCkd7Rsl0BVQaK4HCB3WpUrt0UIY8nZyPm7/I47swh6weIo4tFv3h2Xh+/FzkER0+F4Ywouk7kJMtsMkadTtKfxlZz8XevWzMCEByhaiCwLbnrNJP61OOQOZfMiOWm0aPPuu+06kPYNjuPgsZ9TeTA3WIx0piyeUI8KYl0Qx7Pyj2cH7vI6OzrZeiFZFJTdSEa5OfuOnFLBT5gtgvkG0XX4gy0CeloVjYrhIRB1kCePagNIjeZcV730DvuRJd04mIIVjuu8VpwBL9215k7834MD9CEBVQAaZTluzPBSpg9rweLa9QijtM3eQ3FD7WPSiCAvOQinIylu+lEt+ODZxPTCA/8wZZJDCPPMO5A8lIQkQ819sZ0NtIWdASjT4wTfQYI3FjVw7mwsJDk8MWNQGeYu05n99jAcswrISlYFHJ+r+yCwQ5uCM4O6SlxcBQ9ioXC+h94FXK0xjD4Pedim+hSaUnOiGE1EE+1cbOPOxO+vfpeE+9DcEQpviKSGTlM55mJgrV10n5k/SQlBy56DvPk+DrxyFAqYxJtkwA8wFHBgK3k8xXCCVUPMTafXkF7nsquMgljBWIB2ipeYhD8DPu9fD3sLS6kzGTekL89e+kFayIyIceEjAANEGu3DA91xihMq6bSFNbyWS1rv8jVpzaWMFia4nc9ztDshCXdOiYfadZRDV6LtFwXyEkzHBFBFFJQY1mfRX342bHBz0XI5RPoTEEGueV3F/8PHdwc/rpfeX1dnuF1YgGoUBElPTQ/4paVaeb6nQtBuJKJDJb4KWaBZ5sPWk6AEpcKDiXlR4jQk16mZYTe7aGiI/8Dux+eCmGySDQkxZI9poWC17z3DC6Mom0a7ApfhyUiTw4h7CAVFhHIg5rou3EU0BDX083HtAL2UhHN4u/gTjETKelxL2E+WslFWnKjvkMQtSLiaQlp41K2IyWadqg/sCWdfV5JH3Bvx6wJztUJ/PeEZWBJyLDZJhlc6UqaYlgJPntSr2LFPE66nndhMyj4xQ/VwdX7o8bocFFWIQxg/h4VdhDNrmh8kWLvTZ0V2+xY7niP6FkhyIHJD8eIXTWngiD5y6mW3pX5/0q/zcX9iqkZOdt9YsliSc1LFOpzoaQMD8VPr7mClsxprj2AJT5s7U7pm0AEtm5bCsYahdm5IwtAoHnrCDxTid8aG93YN23gE053kNzWVi25CPStfMzuTI+eQ2DuCo/f8npH2+pShiCaC8uWV/0tJoQNL+NdRwvLyTss8jujSjY99Wxp1DCcTsaOLyX5Nn6ExGJjde1oCunN94DcBtsTEHPrh3b6jIzPV+J0jAFaXbMB3FcAU7s7be7Tjng+gSB5MmBN/5N+XXQG9zhDWVUVtOLjtScZuzCStco5b0wpzl6/8AWAgyDJIAEY8djNpRzT2rIYQwo63RY0wtswE0ddW+fRnB4V+d+nJ9Z4AUnju0bkqA4XhcSqKV9KrEqoJzxhrWQd4IFyOwKIvO89Etj+Q2dGThfMPc6Nw/4XbcDh0CLHnudrYpdFk6b/ZbI5S3eD3Qo6QrvLQQdZibn8Z4yMAxbh65hwHx0JANd193AVbhaZxDImytYNQAcXrUsFhAKETN9im6YkTRAPFcRiou+WRYtZMRtKMNhrG6yZGLjZ2c5P8DQnT+wdv1aTBAUKNNbgv8xaiB1nYDhe6QGUopYYxylsfO0dYwdMQsfDxajI1srqdkKW7qJk1vLpHoBXvIkiEA8h7taJjg2EAjrGCJOHjGNnxqoCSuKqTOtXD29/WZqvD/cZyysn6TDCexP+KDQWIwyuaZKoumeFlfCR4Es2gwA58QBtpCAGgpnG8OUNFDPeD3icOFAoY5b/tGywLy3LGZgng8nmtuEnqTXkF5LWFm4r5i2OtLlnKSvkifgDyVz0zajE3Hm0YDTe+wFdQTE4KK56678AUh7ovLU0IcYBntqqVG7j7hyBLCJnWhCTk638G+fMX4wczF3uXmZgV015ZPTJId1Q1LdYt2WvEoO0eS7xY9MnX3iSQVNzapMZImNQkOuG3E80LzIGe3Mxs29vSLhOlOArzE0ZM2WWc5Sejg0sghg+/uYeSKq1XQCzqzQS/wilS+wumnaCsgwpQZS1kp/1e8KmCWNnRl0jyrFKLKq6jhYKNHcHnPl7N28PBzXh8FDxh4xOoA0r+TaZlRBPnJQ3UleaDcxUzsKra3BhpqExtgOwTRr2o/AGorTZxKNdV39FAj8nBHeezbK1rmGn8riDm/cF1qm4SVJfNp12q0OLJuRD3BcsXmX49N4QqlVZApAoAlG6YHLZUDv25qQPejgz/nUl+QbJ4k4abFbkkobzZwmFidlXeC2zIF6S1RzG1CyxnAYMvTva/RNEM4AYhRK/vQSBUo4/0GCdHa693as8gmD2q25LxxFrItoPNMohRwxlykDf/kQwsdT45j/K7FFjzOMiRGsQORTpj7VAMcTxfxB+QCP8rabB8k1ksWqwkrrM47qLpANm27UDVwM715cJ/ZAeVys+lswzYZGbjA37l8HGYGRHIKIWPYTX9eu82ABNTwJUdQLM9PTHEohcnq2K0V/whMCioeseB7c37vyCjfZR1aq3djbU/Vi1IDs3kcA875HpgeiFR3hnSrKTsdXW0GnWtXHOEk+bA5gODK8OC+MtBo2G/84WBEvV6LbuPJgTDGm20UsfWvinBhE7XCdw5s0NLItJ3wWahFgtbLwS5oz0ZxKx7qbmydN4diDggoJaSNU6w41aMueJx76fmkJbWuN7vu4H9gxt9qo5qIBADGzXw88+I6aWJ0jebGcS+H+e8oJEeZXg5ec7KlUiK4lGHYa8JyS9hIefRA8+lZyy68wEUMOshqha9qCGwCctxfpP9ZlP7pe6ltENSDshBeb8fOwdvK3oWbTLm5rEtl2BNjFslL6UjQ7xYLD5iVBLA0kYEOz75eDHouN4bmy/c+i2bAwOn/yqZiQG0qGjqMhdeUxTmf009jxGyURyVZtP6oS5f80ob7dEFSHs/LMpkH9vdO1HgHpY/9VodETDYb8ylNW09KyWF310C2jscB3s12fV7likO6bCbV8VuQVfsW8dZQS+Rx7U/0qzpJfTgmqJh1Wh7EWloaYiIWe7cfn/XN7mqBmVgvh+Kqmk1gZhk8R/to/8CYgY5AqZVF+5b6dgdkyaPfroiKKQoKJ7Ehfp+OP8KzMLRO8a52Km1y4BgFNnpGsyD+CERT4ejpYclUKyD9wUZz1x8sExh6k0evJOxgw0e/dmRCcL75rLlLKuFNU+8X3jG8LyoGjWeQJpUPfRZ7xysCdjvEFQqfCili3iOv8/jLWftf1lTreua097hvZV3f5TkWLcf4doA9OmRjMz4B3Oi92UDlUkWgXFrz/aJsy8Gf0qjJhdlrOpxLKcyTuP/ETm6vpWZxqcqa2Q51eHi864Fcs8fHjjANwezxfvHN7+pgZPfFsIP2vki0Yz5ZuconPx7qfVTMyeif4nx3R47xwX8w9R8OXyvzdlASeLD2kB8BjBzX3zwV4p3Pxu42Gf2NjkAKZXg7M8+S/IPVvc3fhlOzxJre6miBc0A/tML5di/HFER38LykDt09xGtNhbBpyWi379VR/xuYSqEiD82cdj1DkOCjEcW0zKmWqbmGYjzC0tygSARQedyzdDTrSQ2KcP96U923McyNnsccPH7Ij2uEl7lZ4vGloWiXQ1q3nAshdc3VWiXcyWEclfvmXHybaQVXMn5b2Cc9NqGfEOn32Ijrcd6fi1IAe17jieb/oxh89jEyC1yBByw7O2Uof2ki30lD6Rjv7E3oA6KkvUESkMySeEc+YIUIB77kmyXySTs0VBWFoUrn9Nf6WIpZ6nXVml4Lia3enTD5H/voly+THrRHrNxKEPafJpv4t17hiDmfQk0M/IqQwknnbymTtZzgk2Nowzg0ZbkHLnZsyNYv4ichSt6ltDiCTJ3kW/JHd+JLf1q4EQ1n3kYv4FcG6GPfz6uU4772H+UeMCR31WxBpujLYNIkRjg08devvF6FZ+2B469C/8N8YZTc3IBqwWJmsMDTEaRIc3SBTtcnOFg9Ku5xBWd5vnDTRc8xWQkYihsFFMTRJB0PzcxlEgjffuzvsv4PSA+Vn2HkdS42ALp5/0oZDbIfIhErNdmDdjWVR67Eb29tEvEefg78uL4RdpATf6VThZv9jBlLbqLKTLnKHFpj0Y+kyIvn8B76rfBBFDrizYLafMViJ+GpCQsWBWT2lmewm7/HZLRhOM4gQI7uwjJMfmU4UnhN+1Lrr1VDMtTK/nBq8AfAFPJJiAmVL2cq5ETbwhrANKnIhzeJmOVD+ljFx1bNM903pvIxbjKNm/CM6GtgYmTa4OGk/cNJ0NLZoVaSsYtmTfBCCt3HkWpV3sY0r8AGbRxq2v9Y28EnHZV2qTUHmcZpr8iZFCT0RsR5oLNjbsLaCIzMGvARnqEfRt44kBBdkcq5LolCJ6ji7Ngr69FEbtXmU1Ss39RNE28uC49sWm9dQ1u8aXvoAnu2S1Q/ChW8hn6SCeiL7UZGfzBTJaxq2osFoT5HYv0Yx4rJgHVQlANFO6Zvh2fDMrYUejY/pbsjl3nml2J4ATppOoYBrcReW6nC63BLrgGMm4obXLt0x8uR2kg88owYCOEMnVSLccDYZ3znDN1qbR6vyn3wCHDljOo8gaLhjrYIgW9Uhc9KynBtRegscBjC+5A/yr63NKDfUl3gUiHh1PF6SZK7W/mpeM1bYqJYsNo4bFfM9ALPPe9eFv0z7pM08yQg/Qn+f6DTwqYurqTq+8wXPgeA6IkQxNAaXQ+0VRRi7QEkWat+trmDQTf1OXhACHUO831JijfCpigRDQqdq8Erwuizyz8YqyAMZoYIDrEhu4XVEF0xny6qpxhXA1h613rKRlQmqvFVT5/svBtTKkA4Ak1bXa6OnAfRxBcYtD2GVVmRX4HGjvM63mNWx7xMad+p05ONJnYf27o2ykueohT5QhN6qE4jHoafDHAa5BRXQS4YD/2fdpZTHieo1kAJZA6wxVv+KkKKbOWkPfRnzcnLl6W9nLEtx7Xl7MMZAiID/cVcBpc3Og1cKxlGujqnaoYej6DLiPVgKzszOgvhTOiZuLC7ztei3FV5yt5+O9SSOm0pYKE+TUZBilRywYESxLR+4uuBYCuFF6oE9Ssx3h6Nk+bDEbI9jVvt8UBJV1gmWTdf+Xsh7cTkd+4yDtensmY54bAgWpNFLWUFbKN3Guw/mpnD2fs++HW4K+j0uffkOFYWcq2w/+GI9eCU10tg2qdw8gPwvGiwksWjeyPBDkanAksTbIfv9GB/cG9xSHOL+Y4KGB49iUTsB3ukhlFp1hh+PibvLnlEQ8HF5kvzHBmLcaWTkYOzGG1nvNiTj0HYoy9yaCXdFJVk40zjhlBAzXgf1Hxx/ZUoCV9w9EDrHghh1qlRQFTD7Q6DMD4RsgQLvmTZXelARMxHVA15NlH4gfz89eHfI/MNxNusWKdgJVnTa9Z6YZRuNPRPJyYHevdY203miQhu6ZRj4Iq6CEuzpJ6D1kM5aREAMxvhjrJ4Sp9N6U3Ec71wcDS1mPISMpDnavIgwU790Gf1YRLhu6P3/OpdFcWEPAEhxl+MtbCGw/YE/QuBpB8CmqfEGBbEXG24HTmk4QrIZ7c4jaJMshT3F2neWRH6wlcuY11ZiIJaNNzWOnYuTF3u3iNJNpTk2cUruOuB/1K15T/08vIEORc0Y+OaYS2GiCDwJuFuD2+H3344f1TIokjc1dcvmwOOG1qAWyH15R3bdHpTM1zS6gXK5z25idJoK/3gI6lRLennclmF2m2i0zlE0Y5PfSU1R5pXFFKLRKaAvH8UD7jdCz9FGjjxGnoMtVc/EoLJGHhcesCfpilJ1Bsqe2+y0VtnGelQR95GgmvViorbLg1PDAxU7MqfXrktDkK/KO04hVMKwQzfLtkX7mkI2rdPagnBhqkStoOfRdEM6kmpvQdwvZMCuQSwhx89TiXOV7zjK54gjI/AFjRVu6wlqcBObSXPX9KQqXInj8vma1oN1rrWS5QQO5Ax3On/a+PjO3CXbMEleYcX2tnsRJFaP/N/1mdnOO4aSmwDkVPYczzI0LJYLLxSWaiIIxbAqxmBq2DC3ShzkUzD9ldi+MIxzz8VYUVVrZuh9AGycgXq4eKVw61mAZUvO55hekVq+LdYXCuq55cmXpLlU5K0v+6t7B701eveO67u5kMR2gMsLasSbMcMDdN4PqFpXDQssZrLCzPao/2ujSiNFnufQrCMNScZh6O1tDE++phFyg6fXoZueg7WHaf5OF8XI9lbfdshS/X61XH9cVJUu4q8n6znoNwW0veivuE3KMnIpMIuVNA/xrjn4gykwDD1W+uH8lGOWIL5Gayfogq24c10HDfAgWXz76XpxCeoNMJaX6Rnself9Jm64ZD/KoBr8d708d9dkz7HrkC9mheuGx4qgW3Jk9iscfQFhIEGg83d4EWqtaEZ9wSysO9m7a5MxIrqcv4lB2uOqMr4oZ8nSo66sD+AJExBhGTDb5rMap5hsQhQP5G1A3La16vZIwu2BhSDYVlaPC0ZN3akFG8OCmYZ0/7gzJMd0YDSBmFyeha/S3Z98Zqyq86eXp5tMqg5Qh0bd/OKiZFHk4pWPL66et6tpaH/nVxzx4R/9JKroAI7kNeDTaMRHmbO+eGShYL79zXe23o/eOlS4axKsm/lzxq5nsBQb5zdcK1xfQUgKeYE1co6FtMZRyVBNNkXiUgX3tsSTMcWtluGUyCPUk5qhzWAloXNhmc/+YSIwSJ0Hd6KNZKWHu73fRjfwmxPQSlgh55epFh0bHNoC+aEpyJuhI/qjY1z/8uPwitW3Z/sjM2xlmN9faI4l7JEws4yfxXo9Xo8KO3MDI/aXAs0TdAH0CS6VAMer25l7HlDn1lshu6oI52MT0balgJyM8XD/kPtaLkVRm2oN4bcQHC7e8N6T0kXXu/mWmbqFYm/VNkjKsToaNG2Oe980+X1X/IA6CIYGqH6HDtGbKt7Z0/4SPtplrdUPqIYUEaRlUsg413wyxdCCdJwX/TECXj4NIjpiethoEServag+WtHZgX4BPEu6Dst30DtT1keHnjieiN/LWzQP9ezS2swsmsACf26iiAnEoZfGKevpB6y7FS3yks+hsbpAP3C8W48eJLKJkimSzUzQQy+iOX51Kn+ObA/s1ynAuX88bn8IuUetdH6KuwUMqq3+1+9dmbkbqJ4ECYCJeEvHfvn984iJwZnmrw++b4jeXShqawMKREVIJAu2Xg7vWNBdINXX86SwgJk6kbUda8A/UUhLZU6ErGV28CGTudtSe19m763RvuwYZfkYveUz3PIZ3AaRVPyzgowf1bLVqZEtG0Rb1KfLdD92VCm/cHTplozVxWwsUWffiQjPiPNbqUhLv0sW+LI6HHPcujlxc1HzTQXBDuwTmgyCGcV9ZlkklJDga58l0hwTyEUwRJcxEdiAkoWIu8XLJrkK99sUTSAOQQakIWj41fIYOwikTOZ8m8ilrzaEkRxUAFE05Gf1ab5nsTVYsV18YwYgIFG7NckwM8+1yjko762DHRV1CLuF5Qc/NSEeeUrzE4z+rbwIObEhlm5rPp+STvJVbaIWkw3t5T6ohlbEH3r3b6r0zkr98pKGQ9+LXks4AyTSWZYZ+evSaaU4GpYFk26/siM8Dc8lSu6ssb/qS2FBxEoYmsI8lBPtzLvjl1GLdskg4/FsH+xlQJPO+3XX9ONad1VhVvdh4tmJBx2p3RL5CPfiQXAP5l4/JNAVHWkIwC9xgmvD59TL9WQBqJG/QxzDOqAC4UG44CpNNfsFyxNWVBeM+MVfQAm0xH/taL4Xfz2di1rcPb6mW8XrEoc0eRkOsimRZeMFfWI1fWcQkjOTfU7ydF0rofARZjXlLtu5g4OM8ojXhOywFRaGXt1OT9PdNUwdelf3b2YWSSJc50cK6Fo1KJeO3shVovGu48yvBkB+3e4XfFuCnxi1NdsG1CLuxdWaaaT9nAMKh9Aex6NyID0W3B344VD8ObJMFPdADRjY7zcCN5YE6CYwmNoyE/AQwzd1DPJcfMbF5a5bSFTcyyibxX7M7MuujkRRz5RO8TfLgHSszfxzT7hkDGEuDG7K3C7/k5HydtU1MAdH9th7ay5fnZCJptteUuHr/hJGk1ShF0LK92N074n1p+CJOH3VAeUWMvxBwME2hbIN734oY1ZQ1xwrbSppedajrv8FYc5o/invxvxPfjJ+q+KxGOVU8EgKogqD5LBAVmGt5zSlB9x9unsrTJnhVIE9wzCkX7NE9AgYtTOEtAYxoLuJ/rG7GJN9T99KOOTJVwYUunRaZpYBq3YAXDA+hv6/5X7IobpIQ6kELs2vMMEP172WnRGoD+5P6bCXUH5lYQKJpb9jJ60bGKzEPmqa8eIfCleirdXLUdZ0gI3raT7BDFYW3v9HBBOM4j/UeobtJIOlgxpBuTRSh6Br7rNwilbiwtAbqXhgCXFQxrtssTIcfRv507wj+4LsBPlae48Kd6fx3Xkem2qNhba2C5AXcpdoQSlbXTABuInDFKDzMRqNpBtOgYjyksObFNxvU2u2CWNHOjHkZyklcpmY1kbVIhFWBCELherL8O54xUt5SpOxthAGh2c+D/w9X9neuq+VH8NFafc1VHOq14W0BJyiDJHh1yo7dhRco1goDYXIOTNEA8auJYsFAzVwWUTQvGDya5dPfXQULNOgB5IB637FT5ohKEhgrnodtlSAv5PjQo7BwPq+DyNuZsnGndADYkR/Oym+T5QCfCfSKyFkJHVeVQfwJTRRomtEc5b/A1wH8dztodUnrF7sNOrojUieaHg+0I1ieylnFEeka+x3whWaHuB4b+V1yH6XGS1i7Z3jb0NiinABsdvMjAedxri8xNIYytpW3gb1XwheYPHxBP1Di8hb/c9q5h5gbQ/3i/qTdZ5UFH5z1a9YlzdmZ7zKunhksiwoVBGjyi2MLQwZnz2laIogLeXwwnxEabCIXqK8NsLJvmp4qT6tzLcAHh+StBIqWY9sGL5MaSg5LCbXfLr6d0vpfSMU6ihEgloKZlaZGoxYkXjH3IXoVWSP8XwlaAuZRMDR6oLsFMEGw269XPnc4VmI7KYXxjmxjrbryeecuk6Mh/5Y3IdW/vVw5jAo1KaU/Retmd3tEIEo9Gj2hdn/RAzrO0wH9BL6cPfxvKzxTewFicOxdp3i1vs80+TjrtREXQ1upk5YoFREgvPhxLrB4Dfagbn5DE3Y33EPzqoHnYmO9iD9ZS56ml8vWNC580fbMaQux72EkZ1RBLWhsA+cCfZY7VqzWrV1N0RVgy1/7OByrpCPiqP5vUkHG5ODRKSkU+iB+72ihhNwtnImap1VuZoPGII1WMBG8mk0ZCPtldusglKdzAoMVMDSwulnZdCXONG1HzE2UzvLOKN7ElZmwQAlCFbs6gPl4YHMGUMbuy0KcSxQUQYA5wqOzM33CaHX09aaWEvNWaPWEQ3eiL6xfVGG2uYOhELf+KgYZL3o5BQBYwLWdyFhsbH//5zO/MRUj5JNLbKjTzLlyYe/OWL6V64vxlaWOdjak8EXpldaCBN32X+728p/UztXzBiBaE0pBqllO4r+iBgWriQWhsj3p3elaEAo5xO6IZlPq+H0x82B68OqXqC/SIa2kPGNVCp4vCsVhY60ovmOttACrmDEsfPr9A1QAuVbJs+czEPejH0u4z1qcIdN6tELCmqevGdyAFDTY95wffH5FvomHg9Nfui73U0LN63/fqvKFT57YrizteqDsBtW1q4raE8xgqhbTUdPNTj3QE7hhmDcSmPzPM1aglIPBN+cH/ljsT9u1JM6nM+l9NF7jvT2KvGgrs6A2JtCIgbGCvel05jERjAEcw6ofgpu5FZhMjFnvZdebMR0cYfAg9+tnrv62qnZ3OJxZM0EOxuNAAns4z/Nc88Ne3BYCHr/mn23BDHabt1mv1aBjxX9Opmu9pZ+H5xzvpZIZPYJLdoMkgjkJZR0LjKfu7tcftn9WGsKC5Wxx8rKx22fsazIMIYROZjQH5BN7phRu0OTFnXKqaN+yK5i8mkenGxG039SHRNP3kYvl64eRV2viAQoAyT6bybdqN28uTTubICPHZNV1WkOeSLkn2rwJwyr1nyoq6BG8p7CbFoHBEg2vQvc7uzTDQfFo8RjJGfI06fH/GilHRKH+UK5Pdyffzooskv/5hFBqrqDF8X3yxoEKjdrW+oWfNJ0KgNQceRcQumcEwnhkF+t3oe/tcuaxwT+FASV9PkR6oAK0+evy6qyh4klgcIj67Ef4pevi5po+VVj7w3gBPM8dypOocI3L+TlIiXl3cBp5MluY+Mi2Nn5lZt9W2MPbiNLpG9tSf4AtYrDCcZDnkN2Z9CWKUnf/WUQdNIk9kkY4VlTL6YmVpEysabJQLqTwg7DNTwmeo34L2kLS2wlTE2jvTN2Wp8JcOzqCQt+ecc4fBHPhwCcYrZ2FE246v2Sii+3MIANNYDpfg7D8WDT1VZIT2nNoMEpeXV59hLffDoxoV3K2lvU/hrEXnKx9jV60DBCfgCQJ6G8zPt19WlFnrAuB7XOwTqZN1ebu4EFrOI8Gj7U1hzSiC0eZKi4O5LJ96gZwn2NYycfGvY4T9pJ+I1lA/T9rO/JMl8tfrkGONAZS5YBfFTI97jRfO/G1YdgVAj7Y4uinsQmZdknek9fBEx/B/3MM46DHx0O5PvCvJ4ozM/cYqE+JaT71AIRtCEtXgn6q1xFfLw9KnCPdgLZ68257UaUa8KJqwGmLSQBMZyNOlIpmPBs5IBQtM1d4rM67O5eVC4QVxkzADP3QxFPRlB77WXbD0S84P1xjkPiiWYgmpGgLBANp/x1QwLydllsNeIbyGBekhhgQbyKYyf+E+9EbPIQBahKD1i9PYzhQ294G3m0Zolw1HalIBPffTiOioHKPU8O0fxN8I5br2kHpj5JfWvzSfL81ca0GEriZZLwAxyxzh/TafhvJTTCBoyHQUW93n7avcwWgTTNBb+wTpae7SjXi7cEA643Kxk5fvgnh5dF7pVd0bgUQ5o73xN+UgiKQk8i62tD6dHlWPbt0WGSfobCj5Jmb6SzijJomV1HLrhDDc+tqDh5O1e0X4Lac/Y9w/6zq6CJ8gqeqXZlINza26a1W451VqwO8W4FVclmaebj3NZx9Cekj8OBtE1L2uiYwzp054rBMWnKi/5efHw+/Ct596gYBv54kAKCXOnvdWyJ1b4geQfh5gL3Ls/Qe0+9RZqgPBzGeDTOwkEm8B5An2XwHQZp/fhWsybVEYNGvKWvqGguH+6P/vbeoX+05iEGm0iC6G/PCQC0WoeU62c57c8AWmaqRr2MWjt2ZlSXw5DJqw5o5qVKoWRzKjpTOtj+KWl0kD3x/kA32vbaMQ5tAPcwa6R1yo9xKQe9awtSzvBudHCRJFGzShhYSdVOsmd3dVkNkvdLF6+UQ/WwcUFP8rJys5fOs2324vtqpgahCWiCgcl5/rkp8QlkeIXomyBHwWzMAe0Xp5AMRuuPr08LxcT7wcWQRF/8XMozcEUL54lPsyXf2TBq7k03/tlEyZOEe9Lw+irxel9OJj+GfMovxUgRcdRQrTwj/I/0Vtq0cT9jcsnzRbHB0x+IzQmfZRlZteX8t+T8oekjqHoATGbzANh9k+tqI79jSE1lHjmEr5TlZCpM77Xe7HZBHfrE8tJEqPL1y1ywaQopU9o0t3os16zRanFw/8fus21p6m9x+6X7I1RWtBg8zcyruGul1HFWkkvAhPl5qltI8zg1wrP22GtFQojxy9Vmh4XUq2bZ1iQIZMlN3KheWteoctfFDh3ks5HpwbhUm0UZ5sLFfwrAjHC7Mk9lmmjKesHuB9QewUl38WKE4LfKTrDqaRXxJjWKWQowzqEQiaoG2UY6+bzjoeVcZRWCv6B1fsD35zgfrZKHiQxYm/IzaOWvOCupJPeRZmat8PetAzYpt3EbCpTb0YQqLqLcdol9i7cPgAVjMqyreYE35bPIXnF0ONEEJ8U201nc95dFXdklEUxUWgTFoRc+z2qKpO692knMG+Pzsktv8HlqpCrY83ETZHW7ZwEn26waPu8OcAFtzf13U0so37aPA040y2iOf2Pieb2VtEGlPGA/ghI1EMdfP0Ti578zTDJn6sR9ihb+FnQJoqgJGaUGUuaa7iKbME+q3CrnYAEkCaQp0XwEf5eeCL9GyfLs/n22y09JpoVcrnKKMTlE8TV22UihEE5YmBdwtESpQDqMHeg+/EBmeUkDd73omxNzJo3xwNC74av+R6/d/JzVBHeieW7pastvjym9TVn6RTFp10d/Tos/3vAj8vVy/n+KzuUnCd8p5afdrv4iVlgbGdHzOuzfJMvrd7GmG6ZDlekATY4+BHx3V29Rtzl4aMYQn8HzCJu+C4sv4euhAf6tz751mD9i3df+Thg5g/ak6x/31LZvEs+pnc+/b3ubWX9Q0P9Fiqf3kD/0k2cVOVfIPZk944qn785wSfwQOyeZyLGMby73kuWxIh5TjRs8Mi3WMTPk0/Mq1zX5zDMCDfHSnNjI2DlEgnPekmJubuCK5RfLDvj1mIJRnoBeZM0JPl1R6uGiC+325B5grbHkzsL68licJQ295b+47N4gZCK0FBaJytZ4DldKx0XVzYbX5g7T9nNXivr27kIZ0IQ893o28n8tPwHTznfp8Gbd/2HK7IgcyKMWrRUlKJWckC307UEdRvVF/qwJF3lZxapqv7fvCjzpmarG//6xVma4kjwJIgMUVGfD9ScX2BWak41jMpKqovkFw6/KJ/K9UiHP+d3mIrSi9l03WWsdvvLy6nSDo/UlpneHiWFcIgbunV9mTwOha1Sn/1pTCZOowdf8+biR61xRTTjCIspo/ETAgtf7HoNgUjl33EZ7xfZD69m3C/SqOCDl9+HkrBWFHEKnkuFZ1R5dv75y0xyhrO8pk5gxREemRWJypQ5xZnVVEmvQvGmpV8nbNQ7DNaJNaY374XrFlx1bjqf48zChqU8BzNZpoi3SKTOOFLXxTkW2yA135Sw/ukM139JrscFV4jijyOg8+ueVB2dVVOF3YUmjL2+B1aGEXhgi6+L7K5kh5GYu5zLquFrMv5HUP7Xrl+R0PHc/RWJzteCT9YPdwvFBZCVmQolWDSRpOtCU23Puv6G0L9t7uepjUjxU8rJ2TVIAu/HM2aF6Ia09iZOiQwXpQtob8UfrztwhBiBC13eZ59MSpf5CM4lwOLMHHFtJBqJA5DJbHXA9zAuwXVKrg+Yn6cMWUz137y1ONMndiQuq3kO/rc9VENzfSk+TRB4vOPQ7MYiHrSHvz2lYZCP8b0uDS/0ANL4R/F/mAfiPy9b2RenN8Ygxqp+cDwMrbpCW6ES/BhoHqwMtP3ASf3/D/5DPs91XcVijUSHqay5Nou3ENpZAImToB+TryFR8tFJyJqlB7gMBdZb5CYg1w3p/r/A1nU4ybnpoxYBw6S8hjhXmsmQUhZz7x2OkQMe28x5StR9D4NthPmBYDU3gJlqSHoeyAjmuK5rFoF6BNnI1zmpwyk046hH0HgkXS9Z1TvwmkESlbf7cdD8HBg95a/KJS4ZoF38Zy96Z+XcnZzNgYrqptsM3XSK1d6vTU9Rc9GA9C6jmH4wyB0nnkrJRXkiNTl5y3WSgmZJKZXs9ELW6pJrJ0dXEGAoq5n4DUF+ZBVtTouc52Iom2+SD8bi80ff1JYAdKnIo6aJP7p93TlzdgSAKPASIKz+jQBg7AmxgEMNiGcS6U7wfPt4pmeXd+cvzWNXk6qv6sbJW/y0BgECdYocgNr8Imie45F2gX3QuQ1DVab3vcyrJRltewPQ1mxaR0myqdzyeaMV3Q0CEN+u8UNHlAxPawzib0fgD7edYVxjAmcm4qzD6/62tOoJE+Kk+aIdMxsDEmd6sVasyq/NRqA+wHUXKL7LE2atG2DPxq4ND/015P/X/qvhzUfnIL6TPjd+4c6zPzH/2mf/FNxepcFjrKplQrEOEnr+ZOut8NK76tmXXyKXlNsNGLsBxDLJGCojmEScHlAl5ZVqJ819d4k+iTAx6y1HP2/NdaUM6gxX4Mbjp9MTSbGpKoP8tcA0tSfzWPh8jgsLHL1H0uenUkX2ghJaa3ql558l2pXjfKN+66qY5zcqTam3oO9/RI2VrqD4fcPJvo1nkHv46aEo8QfLhG3kSJ/H1jaWl/oXNxJVvsTQTaf7/LJ02LODvA4rFCOas4EdU3Zgu5mP7iLOk7XVjdSkfrX8spGrbtuzVM6HfPqMUH8I7PRSuLJNnfW+RZl6cPFEw3mTbL14aCI5A3ZjGSEMYllgLz47T5dBjmagYAIbrLU/mR4Vsuom4N+lrLa581etUy8Ca6jFxtxCVY243B4YcnyQRCtRnaxOhaOjqDu/fQ7O1nUzl/Pp++Inxc2hOam5XFSP+iY3J92cL59GIPLWY62oy+TsbPez76gnCbiQdS7z/5AmZPBcT287FFfIsyH076xW2izSuFIYUDP8Wq9XTQe9aasrZFbkIEl6QyfSPSvJVDnJAYsN0D76v8msv8yGmUboqm5cVKDLnr3kt8RAmlbt9aRSGwV2+2j2Js+kYcBEtJDXyvQqE8gqbtjQ5vn0h3WfjLp2EP+DzV4X2KUVas2hAAB6rd1MI+X8+TG2f0D+07uL9hqJ9xIH4LodsUsgNuisIWjiB/LnDl0IRi2HJEa1H2poKukmkcm61UEQIbH3VazQOmyWPHHTj7if+CcKf5E5o4WEQpBlNzTnO1mTbqxmaE8JeuUIXCaaoLOETTLepA/CMgCXHclLxs2+AvelMquveGM6iMrqk2dcvTnI6y9rrOPN7FytoiDxMXCRmcs6A8wZAAYFVIoRbeCbZFz6pb23YDccqD6jDUOhIOBazXX/bA6zWuE09SKkVyPE7wqWXtekhJ3yk9bl9Pu4LoP6IC3ZMk7/YVdiIR5/LYJPSg38sbihdN8e/Nf3rp8U+NC/8MSTcvrri7CW2JM1niyVKWBXF3aDFX7/Z1R9/jy4rPugbRkcRr47KbfG6/D82eRWweGpmP47B+dEznEfVJcp/qaP60UzsZlZXYp87ktqZ6mt4y96yfjtSH7bOTpV7/9psmXnb9mJCUJAOqyXetyrudf6QMK+7tKwt/YS7vZJHfExBxf60gzmF3oq12v95OcQzth+ytfdYWO5+Z2zmYdhr7X5ZMy05e/DBRwB2ewg8+8u7vwCn6l8p7aK02+NjGANoeldRoeNB66Uz807zPxZXW/5J1fznyPovroqXJifYzYHSZ/3YvDDGHnJF35sddLpg/gZOoHbgom1vUeja09emO7dTO1/cJoxStzt5XQhVj1kU4vVfLaE87G/NCI211rk2cSGWCqnTXCW1GiVMMe9VK5S9VnJJBmPcolEXbviqRSuN+SKtmMdb0Sy62MnDJeEmy/GWkWRYSVkx4NGGjbSmtPIT3AZ4t2l7XpLrBA4Wyu+Ce8OcyXWFysmBJej0TObQO0W0TEsSN7WLnYSmwdQ+YkgOsIhYZe70WVPyTYPfN2STGCFx4Yy7a98X16WhXu89XGf4BmSDf33+ddrPolWlf63KuwluPaCzJ4sm1dNfpXv/3jb2YXXZRWcsXZKlMQKTPuql6kqqnW33MzMgHE+PlI4eFvrmnalMMEoM12amQjTeyvEv6oVY2bSymai3k5QLaxNeYk/ih35AGBWaiaauwcc5Vk10l+iv+/KotYy5Rg2gjNX6cZwpbC1CM7Elyy0/YtQXunhK4U+W4bJSSlKXLCd8ZXxUmzK+yu/ZkArvL+0NQYjQtyYUHPPGbF+JmzV2crMwxf28W9rufCNbcNE9MxijTxiWCaFnfvitfmj14+79xKT8fMhiYTvBRyEiWURTuuQ1VHsOeXoafED0wS5z8DYw8PyGdNAIiFuzzUkMadFtZ+Ez5gyU0nNMgN/mnH2Ongst2VfpBUu1M8hsUTzy6LkHXiqY/j7ea1GTPhUeN6F1VFV2EHyboEx11NKOxh75vMYFFDQ760zRpiiYgPwEyc8EwxeiAGH9a6OH1/MJ9UrmIkAVrq9pQ2HoCG9kZjkBdxqPwuSuZICaH8r+/+5Lf2plXKrhw629lcP+bV0hwR42iKACz8A+5TvtF/zdzl65MllTf+mlrfZSee+Y0BSIUCvIutL61T5/M8ame7/pk0yd+rFnrR6f7SMxTseQNr1nzrnRBPHfXL2oGmH7U8fFf7/nEx3ouFuSe6/r9/vsTj9PIT7O4hK+d3iUv/u7i0z3uO3OAEbDvS2SD9MV/1I8p72Xps2hbMDWwlHMMtOPG/cJytbyOfkoXK5PKqlXxbO8UQ+jQYvQcn1cDILuH9dmv9nuTSctQOrEUOADlm4S7ppIbh1QGpcAPe/8/S0szpFNio5pyaUqknV7HDgB37pm0ufg9KhYhwNjn2YrfT8dqYAINQEorEChjnD/b+jiH8g+sB7Kdp7o82G/sfzUL33gV1p8sS482k6NlY6BdAEWPJ74Zyl9uJRXBywuMcGXLkISrcVhnOk+ERvhXdPkntDUw3yOf3mpm1yOiTH7lRCfC0Aq1x6EcfEAl9FlHJvWDRHvTUEW+iEiLY4ZYfN7uNEBJcQk4Azo6Wbobgm+UUsth7BrrEsGTg8Z+0pe09futVYPuhXRG5G//Oq8waj+dlaHq3hU+KEUunSfVftZGJsP11tnycIPXZs4qR7UskTYc3Oh0pj+280OqlnCSuUXe2WdSMIqWsvnQf6IZeTvv05Gzs1qf50f3vJCuRvfcnzW1xM70ZzjVXtJ7TSe5Yul6p+2qBYdtamz7KzbKiA23mVT2+hmR56ZeomqcKfbttwp7tE+5BOGQjU3k3G0E/3fR/W6lDSjeo7NQYOtXM3BB+HPwbdLqnqvOJmb5OfydGUl67+ZkpHaV+3au3fl9d5+VugStHxPDo8vpA5zjSQDu/lMUxtfkUPNMcUJvjOaIVeaizvIC5GSiMjJ5dYw70jT2r2SgZ8UF3K8I9rkJpLEqv7Ovt3fzVYn28M3Wqors7KAYeZWbzNBDT2fJ++x6tKPAi7iF68yBGxlDa61bGQ8+NSqnFtjFTwht28w9dh+av5TM34f8ePICco7sTLhedRz8sXWiU2TLfhultqbAx4ZOWFt0cKf+a+/rvsWdl8bc9jryrLzyGzF2XJF6wGN2y0y6bISK+/q8WbsC+FI7IjpwrHZ2UN40R3eSZpbAnKvIgoZz47wEh0n3QUdPp3Dmn9haurTuZTevc4v2i/68rPWG7TGFv5Jw3lSQGJwFK8GLTUNdYhVrN5mMoLkjriRM2kLIEurWQB2wrrnajUM/yO5GjPFXTF3JMHxfLBeBf7vfpbbXS10luhj0Ok6tcTMeewFJUXI5k5gzFm4m2EsCzedELitmbyhcvTua+Bp46k4SKW3Uur5MaT8b6P7bfOUojjbNUBjWEjL2NewloRbLdN++Wd9cRzPq/2DjsgRhD25wVaq13/4di4/swjPURDQk11eiLAlqJdENgvk98r+j68NSmWrNlPEr2YfCOZP4KNpP6TqaRbrzXV0c0wksSCGz0scLlPgsPdBOz4LbydJtJATioB126OR2aVCuc6j3cQKbXNXXdYW4LuZLvr+hCD7UyLtyyCc5vV2irmIvwGdTJkqy/eSB5ZvI3LYFUANVvQTNtX0H4p8ZubeWc2WJmhSnr8UA78AC+uyXeGjJQKybr5Kn2N5mP6ZIvegvehdJxagSjrk8eH0Q9ev6cgrFn7X3daPk/lU0zjRkrHzNDJccdZeCzODVjKBTG3fEMHEN2XCfIO9uXmDo3Mb3DISuX/lLHKNPpYCPxtlG1kTpyeTMOMLfd4rtI3H6bTlOvhlPzmsiSiFlDmpXW/mNKntpWZlQabEK8rsxQ64bgRXQ1YQyyYwirvTBmlgmkhfiT3FRvoq+lMkVPF9sOBVS4HRgWrSZ4EzvLfFcEZLlCfBL1M5WV+xZoBB4BCzZ6ZXjM8sQZoSIOYs05B+B26iEcC77zZ9cunNMRaLkL1h2XbzIkyyZhf/POwRhy/2Gk8GtIhHogvdlyD4zK7gUZIEbNVPwlyrDAe4Fs79ccqeGJv395fEvWh7Zeq/svxH9uM9OFaGgeq+PSG8nJw2y+9wKRT0QkuRvG/Ma93sTwc5pmNI6MZeThnnDplomXXtFTbIVB6IDWDxlRs0Xz86EBX2TsIwR18gtFMWC1do4xOYV4fkREu8hzGRM9LLU/lJm9v6FQKIRTp2ih57vfDmQWJb9Iv+2hYYPqOjpg3IpJGIuKinoW+MWk8Flcef04kTSE4a5ywD/BBN2Os77xOcX1v+NJCw3rnagF8Z6pf1tNvZNXMmekjVUGp6J2Caki/8iKYC0Npz/sLrQUIGl0E8AE2vE7axt8qSGQhpYbDT+88/BZ9gPkZeOPwsfXbC9JVmoHEUYeqNxxoEFYPKV6MZRCsddIyV7PY9xJMHZrdgvVFKeU4u0r+LsYXzUN+s3YOkx8Pnun0KP70rD1VBo3VnbNR+Mm3Nrm8EDJyBwvmTlQ6jhGtrBN+Mt7oUUsTFcZ7y+0VsnQbqPE/yzEUz3ObtXmyYLurDukUzjRxu6PWZQgwnhsNYBJyU5zIoZaKCzE8xSSV2tNkfmyDZrcLYs/cbkNMthqCSVqiN8L7dBHjo+40mYKu3wB6UElZ+jE/EAPJ0cAGfDEbuYWaPLBvbQZltRFG+AcsDjfy4KfisLxwbHIBdDiiUnsBJE/T1fdLwFVD+K8vbW2M7cyTQBgNcpYay3r6PwTx5fQjv+aW3ZRddKSYUjVzap7zylurWdd6bXaeEgqxISGDPMG0rB8o5Jrt8fLsvxl5mUc+JUDiIE3SSAr1GvpRLkG+u1EHdaAOk5ubVnqu+nPzMC8g/iq2zkSkM10fnq8QaQ5REJ2lKbTy3M+NMZ+L1V+eTdluPEJKeo0grbK9L3dzeGKPYDZlx07lmNv0HXTu+YaN79aAW+AnY8tNv67bzTmiqWrVjYZ1TT0RX5Ni5+QU4wDDN9bSHK3bYfboEBoX/r2NUSmxvgkkaljMzYRRdCSJm5m54J4Wf5/ntzYjt82SDeUs0BHQEEr9I4xHeGI+UGaW+r+YJ9BXCRc8dIEFxmhIdl8xgRYfJPv/yG878jHzW4gpm9AvPqNGPc20AkKgNDjCKI+lrJE/WDKo5gxNTo30eeGPPHnKwUNg0Uv29Z4o7HUPa1uNN9ToDfSdQ3tjbDJd5Pnjj7hhs+8WOYGS0uT9+ScB5lNVnY839bFHjrEjCnKVRhPsBJU+PQThfrLQiLp2b7mCP3RbAT4qKVPiZ1a5r06mHE5siVmi2DGVw/Er9vLwP2TrvGIJSw/Gx8Urz8ajNWEa7w3epqgjgH2bYMl4wDEhzmb2CV5Fs1UE7dyWc/1LEmV/8TtLr7YzM+rmZxEGdeikDYjTBXjV3sIq9qGGBLbibkLBR0z5UMzs3m8lr6YlwwQFxIUnm5te0EyQAAgfp3MXKG5kM2OczhoQbj+znBe02xjV+9sNEZOKfBw2gv962WSf/h0y7Q61KnkAl+/xM4V0gUfGjv5+gniZJ/20T79FRSWCu8ME2j7DjnL2F5bq5Seth794Yr0KrnA6O7I6IM994wJnPZ9MWe2pgQ4Xw+EYcER3nfg6U7uHEobq0W+SsL+y2ZTrfhfsPjXKjay5kZHIJEyBmUsO89rHG0X3fLB3wj/E4acelSNRGjqs2LVFtEvp8H4aSquSxdC4HPkKv4LZqvSE4RcVKvls+SZiyUtvWCJVQsh+zk44kFkeWmLPLuXiWC/6ebD8zejTsgsO90kunvVNK4q77oadSq5N7qemPY5hCD0Nm7riato1rFD5942+HNDw2/3z1NivpuQUQDJiUVvoX7c0PWbq1DzQn1uu7tRYIf1Cc24hnpTLdtcKCK6IKn6kUij7gCwuDDazvXFT89TVT/c+pxNi2bS755VdEsfnTsx9of7BetDIKCVhzUNwtlFfYoKFRr0Q2E9rK2nZJ+4QQuQOZCkr3NB3FB313o5ud0LPChf0HkW3e7LD1gl7At4VXmAimWJYrEZnkZC11cOyfaUiFGf4B/G3GfdzTLJra6QZwZ5ID88CiiCrynEhqzXEceoOYdQMax1+twnVDZvcO873jeO11hCHMmjEhUJMaLUjbNze50A6MktEfVjoQ0rrmRfiqvnpHkt8q0N9TmJ/HXoCml6gvBMZ5VMTDnh0jAdafh8Dt2nBWTQpKnSWxcBfWHRSsUOYVlYKklZK6OKr1wd1Fsx7+1qEuhX4u6VwKbzHA2bROZ/AwWrQLkwSANuQ+DOny8ZF+DtEQG4YvWq1XY1Gr9qsV6cFkqKQjYTCERZGgS1hUNJGzv8EIDadP/vgEC3H5cSvLjVIj4ss83iapi9IDLnsky1OuyTOk8VGxC6UIAf5JpZkArLbuZkO5THeA1ICalAMtvBNq/AqNTUs2jW929Orwb+JqoUv47gSkfAdVVvahNKyC1TVdclqd1hAyDS3gSyRGhKOhqSnFOtHsmrMKFoaoOL92BhlN7Cs1rG+B27290wXhlD8CICE9lrELxXLO9iR8oqFe0zCj3FW3wsi9T3I34Rz+dcKwwjTzuAbw8AUu4Eslho0x8LSGcX6jaxIpSLaqJm2BzBGUwLwyDPaSTUO1mZD/dZZWqsd079/cKnlBjOoafl8V3KXH1DYoSVoMJ1bwoFJn6srmR/Mp6ZlAB4Yz59YQ5JPEiYv3s5L9wn06u/mkb5FFf4VtiL1UQm1Y+WqJAhuo8SdaYT33a4BR+CTkG+FR30AzrWHYXLq8UhAk52yHgmmlg0mLrWZAyTQDiTmxHKk0gmhbCKtxtOgJnfzgHE6zXMFu+KadWnSV5ZCcbadp7lgom2pLXXyDsgW8SBD4kXVeyAaPu+z5I4GOUWfTHvdygKmmXT/1VDyN0nioVslrsS0tGt2gAiZmC5U5pTxZSWVwJ0Y9dAUlwllICe0oPMxp/dcJPxxkqVjU6dgFTye/zgYv2s6KJdam1vxBK5trpWAiQ3VPNpCEb90ABu300yvyoe80/I+iQBNSnabtQpP4KkVXUpxPTCewYcqBQA1GNOYYr4w4Urfrclb457ACyEjuW4D1WrHHo0lZgkTavsejTB7RUBtGBnzeg4mR054vAc223pOq+ppj5e4B4CEfQWeSHb8rqo2p5uVSzhYIvAgVvCBe7+99SgpfWu00GXjOKZJOtb85Tfs/E3xFKQ2qqHqi4KQCmEU8+AteaXIJzMkN/ZXg8cJzypq1WAlx/5FsisDMsP7w2YFpsRDGcJaIQOUjy92pNntLscQXo7bRKEcLweSaalgHBeMy54lxe3OFSB/Wlbn7rIHyqX5cvK4ZFtaHK9Osi3F0XFJXVCaXxgDVUq4Llwn5UzPaJMD8WBcymgDGL+kqXL2wgpcnr1IBnFDqP3WNmERG3oqiFBJ+yiNszxhAYwbXLZq/hWMS/8oHRDJZQxS5dP45C5/F6CrzIVzQU4Pk/NGgu+Bk+Cuq/m8iotxSTtnGPk1qbMWdYnKMqlbLGVnUJTbiY0kByaWd7GXcJSQkHNefMntvoSVRvZ3RfkNQl00qgfs8p6fiRVUZBlBg/0mb/ne7UmMWACO0bzmxRfdnktY/lRT4eZeQpN0URexv6nF/pOHAJAWbdjPibl8AFs4l+snWTpvbdV2s64xfgDKsa3AKyRzGxksEMiLE5uNqFJQUYDi0/ffzvJbRaPYa1bWINcpRZLoUndxylunaez7rgjei4mRc+mXhTjJ2VXBr4oxkXqPs/8Unk+j3cCXCz+itatW4Es4TyP1hPFsuRO4ThjGGtQcg56j13I0x7wRHDf+Wd+gRqO+lNjq3S24kRk42meUqEpGrXLgnUzxktgJgRjxEgZD7fAlUqtubxzdOkopkXo8glI1R0O2LZpLfrFd7qxXkprpvy6Aci5tOCQ43YnhsHaYU5ERkhVFQUgBE8uDcpl3BaUO+zpkL11UNQd/MlpAz9YkzCtintbB29K9+/lwc6n1LNJzN2cyHkEBzT8OExgWOjnmG4r3XDwv1A9gIXdxDk0uYtz42gWhbY2iAHMIbqRMW6znzaVLqHgSuuupxToCjo7mSHNbdojt7MuUaf1fB4GE5rCEq5fHNYnFUrUUGQaxuJqE6ZrodMU1jNnK9FxNr0KxRhJqYhmazBq2EruGgbRdqFS5dk0eKk2Oy6KoALyNklK93arptAhXS5n7hmNY80pzptGeOQsUBLGlA0WwDRX3xcB63uXYdBtREvmP4tg/yCyzsYEjNqKs0OsJv/MClRUOPAV9ytMJv/EGzQ9ja3gjCipBdmaMiIcRACgKT3FkJ0g/28OIrjoFaK5XFj39iHcwyuoI4MhkXvhl1nnvDRM+m/HKG1iLDMYFPxs7nEVQlKAE4fMQHp8AvBV5HH2/x1fOyGboUV2Ndz5ouMq9kIzYI7LyP76TY74mRtmL+ALleuBtmjwelAr4YiNQm9CP0asJei0Bqew39WbReCYA/4jc7Qw5ToMJUmblGvCRQb9Q/gma5jUwhMtpwir87XUO+fz9LtvvG3rT9bVT63Lu9+/T0nVoM+lgL7QKRZCHJtwI9d0IAqmZ7WfZobBP6v/G/DHtIohQvj3C/oRuwq6kt/y8Wtdzjejylf9Shgs4xVIyD8iVtfKwWEBXoJHxOiC8xLmAx90D9cVGeumsHwBtlAUkB87WKxMudrOgys5c9r7ErF1sDm+1O05aKoCH31H6gAA/yRwVrVWh/1FmcgakwqYO2E7DBaiEpgHpj20H0gQnE7JZvJDFsuWb6K0IbZcC4QOF46evhGlqI95TKgyYUpTuVI/KmUSAxE9Q6nj2OLevnEqNKLtv//7tQe0qKTTgb3/BYI1k5X50+oV7x/ne8dABVkJShO5UD8tZl0Ri9/7JQGLm3Ad36dj88TUE/STVwMHtgrRXpB64fhP2w6NgRsEwbhxfua8OsTM7vZUGX1pyTfvvTUQauGDTpCQhqWAPnngFv4EX+lf8e8XAk1tyXgCFjx7Ki0ROeKRfDhB3jE+NjHmxadvgvRVD41A97XH1tFQuEwa8DoAL2I0O0fHbDgguKEXF93edoLDUu4xUyVshtyBoRMJHeYm3B+9R5d2QnaSXnaSVz+0kO9MlDBw8doWPvPP2yyo+b6WbsR8JQV7Crj+IuN3CJe38OJ97lfbtOSimZ2APs/cnkM7IgW0+KWe7eaiHP9A+8ZqJvd8vPdZbt4F87uTKlc15Hl04DNjkPlKV44KAkCSzGSwSALjSOM6o+ZSea4ioKOCWcPfEYO3+BK8WHKcwiVRthF86Dtt2ze5ODIv/pjYsIcygIpZlptb3EmZI4YFotgtVL3rVVwMMJhriTs171pwLLtfFu0uSA1OwiHnI70cFuoiD2F9l+VcIecDYacf2Zrtkl5G8JegZbIuMNiRbmi3A1zOwD12K9/OQxxhHYRQfM95W4LK73PPQvnfSxRHRDWFWXLFkVAO0Vw9uuXCrNbdSmF40fgvQBffi1mcOzGzHVc8cABw1gqfqpWcgZqcmYjzhp5WVMgHijNFMg76UAKxjpf0CgUNmMBfsOfMsoVad6NZ0g8pR/unnVpFASvrdoWpTU7XhmPnbgHTeSk/Uc52WuKLsR165NTBizelALqog2Aku8CJvC24h62HxPDuCyL5rNNud0Gk/NH5zKFrebpB8K7yJfNeNJ6fowIvf1BMeTu4BhQsutxvRcDNz+a7bGricJ38UfIz7Hvr55bZsnGDtj2jB9/QIIx2gohsLKEk5TDAdeKhdnvB6NfW/p9bLEy5200A8LVQewhMgkxELYPZRfH97vb27zT6t79L41+0p0VK+FNRLnsFV0fZizxK5YBwDKlSrMPfeFr5lVrGwVAAl+FDjITyxFnxHll+TVsYtElpTStInTxeA9SwWTSnpNnumXR/xLPpYrd2WaTG7MxPd2yQ8mzN4ujUeSyOCFtxaZU+360u8HH0831YoFUj9WDsRz0v0xuJCCVhi0GQhPDXTv9/r3e/PrAkLk9GDOfazqvqQPQfAszVdalCvK8PQV+e3F01Gu/rQ/2ZekxVzD81/aneN0TydV96zyJ+Vqq5YPlSV50Vve7PMc4hDs0TKQlYuZP9mYaIDjAQOxCRpPH2LpFRsdWribbhSAlqZ3wfZJkG+af1UzrwewsdfLl0o2AGrzN9KpEx3NhN6WE4QbcDSjYPwD4L8p4Q8/ldZfRTKz2p2YHaThHMX5zBshDA2Aegm+SmovDiLPftk/FbS+lz4D2VcWNeBldN7fWjAZN6+aMdwB6A0T71gtV1ITbtgs55fUJJQ7XTG2iq0So+8wvwZs8pe4nR5zgCfCcxtrr3PqEWjxUYh9gdWFBpl2/yUmqO0Szo496gV4Ffiedp0LBXiCHImHAnCbVSmdwWDNEmqGkl188k4sma/BNyTIc/1QebsCy2z2/YwuTcwJMLgjwnrIpa87yhdcgsyeHtZOmKBAoSaCPZEtacN4SGLCa61lDZjvV6FKy6PuMH1H0X60eX+VOE/fJ9A3/L/PmCNOtQNi10DdltCOPK90+129xiC9RZZQkjETuDL56I11OMIlRiHCbtGrPOaICD4YpVkMEyrzboW3+Twv2GznHAAY2b+tZjjINHLHl1aI1Ug/pLTmfVyfu3uNPm6Ga/nINzCXSmmzuiaNmxQouFiA1OP+jOzTsruz+4lZXtzptneCuCXTp1ysA/iQVu8VFvu5n8XrxHjKaMPAxsff+dR/0ewFsOHffCkGd+v8nyCv/O4DvHqMs1MlT/k8gCmmR6hOodzmULh3x3NvFAMme4hFlRGxZQlKWKczuid2Fx7SIre7NTVueIgLKi0XSlu78Adxe1ySXvZNKVk6jQ8rWSqAkxDPvPKYZdNEufJYgOCa2WJE6VBhgqE1E0nFjuVZ3kPYJwWe01Bqf8edUKYJdg0A/aoIP0rf0Qu1TrkFAu4XZmZD4cCtXLqNDyBO8rblfIpoAEfitKzq7FpGj/LQB7A3k7QPO6y7pWjTOp+bzdJ/lteuVVJX5Sb2G4kaOXFuJiydmKj5whycPXzorRVrMLlzAdgP9WBwee3xxATcDc40egUm6fYcJJQUsu5ZEX93dnMCw2QuVmGd13e62KwHIMtsOUJ6f4Cmp7RENV7NZRy0q+I/BBboKmu5+vUrzEHbL2SHtr5hfQ3x923JUfG3K5ta9I8uxVlt8dL/J0E0HMMVFuijapfvu6ITOCaKRIXZVEqh0Hs5fThnLdNZS+r8Amb83tV+S0p5dnbCA8E+5wsxxo87zPGDVzZGllpjyq5IznyIig3+r1W9nMTeSAMqzj7O4G/K+CSlTGER6qBISqmtKWIZQQItxnikvqkgq3A3L6UL00vkTNKcsuV7Hg5X54dl3PKM0pkIOYGTZg9IqX71KCEd7Pics3JEHxUtbwlTBbg7yTmEoIDwvxmpvs064jQqEGfCBCzgiNykyDQJ1mg3Tuyv6Y68eX0kpxyJSteLo6IpUBEHHJo62/ljLnCkRjWb5sMBvhF9bmOVja4cBE/oiYNJg2qQJSfG8sVR8TCWCEeAWLEkRtGxKEi4JMVGMJDAW4A5NW+Kljt/Kv5Qv6rXpuNv5Yj8KcGNqSkFPYMbEyJgsKomDJ3BA8VDYlDPBDipxOnsd0tD4/gwumYa0UZIArKHsIjj1SQQ9lDGGy34JSTIhEfGw/03dzKKCccUXKHkrlYdcjJ/E3xfwqIulkl/t1KxgiWWpUN0T2FeAR7BS6cSzjGpgAUZxAZagGX73eRv8/5irP+4HG5rTwwZbo0H7pcV1e6/JPT/YMifdPhVEyGYQqFzIZhBuZSVc/Y0TKcPYKzbK8m2+nnKf8BADodJgzyeepV6Y7gf60XGryDN5vP44tzZsli/jBfyhcXH7Yq745cHW7wKuE1QvhKMb2KOTX+YWkBkRfq+M7YFAQC029oTZsDAJAj4LKeqpLF8OjNOcA3f6P+HoufcZY4q9fSuxEAzUbx6AJ1AQWam0bFXY0X3yWONj139o0ZmXFK5TIoMGxHK7yLbKL3XvnzgZncGUQAmVNPnbMTrjJD5LCss/annwLqqJZ4TXlNa7zWptrKa21tomGqvk3vKwqhdNJgCblEp06TSKLErpxlABd6D6F6wAq9TGC3ASPSiMgwjzeibay9aKaCi1n6MjQcPTv5f1DV8cXFMNmSBJMcybC4gggttipnZPbntU8TILb4HyBArRQdOeRr356oEC7/s2j2jNBgagqctzKSxF6SoWy4RUk/3NLk2N5oaD9dWZScJ4LIKL5BC18oi9F0+Z9F11g4ss6pJB0yCe+yN7y4kk+USg0D4E0+giew24FOoV3oMvg0bzQJSjb09LH8jQZYlKjgR1inZo5h2tClEsizaYPZzGCVqlLsKBFKKIPa1KAV6pijWJzik0wbKoLyRrZYXgJLCo2oEfA41uAJl/U5xf1/R6OiVidg4hfIssjYcDf6hdQXapUjGWnLCMQXCl8f+bZJMLFWTlUGBDCM5n8n/6bXEoKyHbTbMQNqihSv1u39lHZoXMjMgjmM4mBEdnjhz/xnfA5RwUPEI8iXpCqSsvM6EwMmkQUwLbVZTmnWfDusahGg0ISb9CW3ysA8fyFcyBt2OS7ohtO5mu6UN8S/C9dbCX1SFV3ok7gidpFt9yMNv1ontsfxTfrQniTrfJT2MjVenwFJn1BZKphHrSUq40bcZhn76/XtReDTgt/FsHMhhxY601a19gr2663XKPFl7tabF56bkvRJMt5s0nYGggCRM6NAX49XCFCIOPJrIexgU6u8Bn9QsCDVCmwumcqo7A0mQ1qNd/XCndnrKINNaK67gdi/9GddASCUglKzDbqLcJEH2ptlyHPFMixOhcUyVxzpWAJP+5tV8NSSherIygLYMUDiMWmVDFYp0nM8WWxB+15xSRmcVm7mBpY8R5Dsli+xCWi1Xzook+1mGZmg1mxCL7TLxGpNsfmWmgJLGWCdLTxspCc4O0noGvYAtVt4IS6S/cE9v5V1B18O2TaemmH5RnrZawFsO/zWA5qOxfc2L3I1aqpE6j2AfFz9vzfmhZ5E5DPMwQ6ywCZQEyTDqUgQraOvMlt/7MZpDOITdTzmpR+EVnrDAQ85SK/NIkGdUrdHk7x/6ZXaPRpjuYBmP1Hw9FeeXnopgtsY2w7RhhiahEDe/2n9FrzDAGumte7Vaw80vqcF3ioxw3T4qj3LwAdM/Z1EuPJ3l0YYrspiEP/ElAB/z4sfHiCgY2aySDy6bUnbckJZN7Mvie7o22Macm6Ta0ujSbO3kWhG2o0U/+tLs+9dUHCfmeCkE5EAVTIwu7uDrbHRvenoPZPEfy1hgVUgWyPTVXSwvhqXxZiBWIyJMdzJZjKBalClVdiNKN/uPlBHw2Yi0TilOhIIlVucuv5V6x/FjbP06JusccNGHby97bpKouqo661IzEMUZjHdpnx0TgSttN6l+aDb7tL0b2ruRRn2eu7XUIpH01hnMlDWFnvDJDM6tQxyXmwqtLtrs95cTLhx+CuDe1GBeKK0QiMZ2fO3xdpJCxixgS7GkLth2lTXSDcWF59uugFaE7ox44yEzqege7YxqwvSOQLZGDP7d5aMci7g4Vc/w8Zig55jwBcMwSqDqEwn5kC+zDgad3H7XoZ0QsA/vVQn7lvDLei/fKOphY7+YS97nToxrcuDbzOsA6MO4luUkc0Ggov0Rh5jVfLwFrKcRRk1e/qAJu+f75+WwVZQGcOX070ee5ZxeLNijhY2tOnuo2aMLqXGfK2m5dwT1LTVHooYcPeoyyjAfU0ra2VKZN+92mEUj6aPAog1VTMao6qUfevvl397A0uQuuQKmcJRxLSylY6O+nv07grHZSCvNY7lOR1Znn03WxqXu6jRo57w/UNw1DEKxNXGsX2ffd8h/usXPafOoxcvOmV+fw+UzsgurzNlnb1kqH1d8jdISoLxgGuUpJu/+iRPH2IJZG7bVkquC9Up4M94XXkvj1fZq+Tw9ECbohRbisX7W0aPaKuW1tbuznzk6UE1vkGklsoSuHvbw8wUZicYyzUGVUh3derzIBElGkrKEFMKzyljSJeJgZqSfYv1UedYP8knnxD6snuYTm1JxIshBsRU45DKsjuQ1fYwczNzeCzMGZZcrQ8YJcbJ1FacMwyCkCoJsa085OprsEYg6nCZi+GLaDrCtKRRkLRZs0Linnp+Izz8hPWwoLberZeUbWqrEB5OZhr7rjGJNnff9zyjrYcBJ0U69SFRlOQ28wn/sCA2DDg0obvEhpTlat8uJkHoECd3ZSV/as1i9wqAtbOKrIQJ1/j0rxCQ35P1kbgi6j3Bdplt1sZReWZpDjkxkY85axM1Ryryywy637FWvZJwrEzU2hUAu98i31VLRCzDb265Xg2cG0t+sUwwlaf4JJ0aVvA2+V5olsjjPzduFQSYLgC38wahL1G2GCa1/sU6I0EqLoErAgUnqrtIx4mKokkJA7OXzx54JEmbombtjOOMyV0z6neA5h5uWz4KzX9E608/7K6sn5al86OWoEokGXQyW2pTabsa5hwGYAWy+jAdfdiTSfgUhiUwZ8XsVCyfKqEtdrdN67a8YjvduZgqX2yxiwMeiRUJB2gkdlDreaTzSNzoGsQhYoPWqn+KeHzP2yoy8W5ymycPIRuYs3SS1lHLO6gB2JVI1yhjtlybMJlrHiQfE0uwK+FmtSN5RTrJySS4up9apy5uCRpl58Pj5OOJHg6uEDl0k/NSXxBXLpn0m1iykr5wEH6dvCzIMJu2gh8ZEMXalEJNpnIW5XX9dyo5hcx9oSPbu5VX6Kw+nZptK0CKmkJ128orCu/ek3RR7J7yU0+/TB5JghtLSSJ04v4W23qWYrn5BUqvUBSYSXyyxR2dtC8v+MFFeBDJ6uChm2XymKhh3Gwye0Cnf080OUXzi4wMIHSVoZE5HXNKAx76Lchlalg6j4sk5Dt6OeIlSgcgvkKdAOW8T+NDELdwqY+UlPxgv7MPEW3+wD3qXilcDN1IuM8rsVOxrn1MLF0DnYd6zPnCfL9WlkwizZE5Gj8DoW6rmpmgMBhxrzZL9KALnlLSZYFo/pwr5KNDNMXMtvHHWvRq/LGYtmCbvhu7nyAvbUSWKv1TBNBgBgyDLNcGMaMDANnmVv6eEa1XyEeHQp92V3Wg19Z9mDzQOslDoLQFIHegm2x9oIpZR1tllI1f9QyNtthYhhXU8rVjR+SeNA8VO2PHlRtzH9HK1SDHf5tWPly6qQL3ZGr6W6x8/7HbeVqF66HPMviigdtv5HYyNWVgYMXs2aeTtApbRJRs4yqsMNrAl8lNttzlna9EyclkysqmKwyZkjL7xhxdG7fbn7Tb/23HmypHQ1qFrTdJzEJjGVIYO7rOfaBtAi/iTjA2WmESta/K/XMLD2sV7gS9zSDRA00yarW6cinW3Ym9FZiIafPh1eZQMKfy9EEaC3wumJbWgPyqb5EonHlIcOzy2NChWGV7PVGVtdtn5YgA6IbrL1cYCWvtG3ibRLiyXWZTz22beHN8Ej0tCmQAsl+tzkpUbIAXEjuzpLvhY1p5d5vO481ZduixcS/ZrfL5o7HvFZjXo17MQ78jYvdBaMabQowhw6+zzW80My7uZt+iGCTGCUgiAIjWVespr/D/joiGHXrj8m36nnJc6twq0QZev519mwSg60FwqEKAR4JRQz+qtMtczhzy3y/OBw4JHQs51qLTWPnwpEL5AwBuLD8epnLn5ZHdzlP78w5m6BrzhKDOB2JnWksKt5TPBbEkj242t2aYHig5Qz3e+cTLOnuHBobL9hKduXP+ltjceZVlq1flgeTlZ8Jj72gdSAm4VhTW15osnldM1Zw5OjO81gDH2ETe3YgnhOFyYA01pxVc7H6LfPN/Por7ZjPizK/wdx96tZK5m6i7zJtLpFxxEzkH3I/3k2/RXuy0F9w4Rubvr5L3kAWpui3Wl/LLWd9KTJw7de48gOLX/5JRP/Muw+OLxv2+i/zQ8aMHjh0D0+iFC4fnzk1L0ikcCzjW4Nu0gqG2JufOXbFo4UVQveTVWYp5c90P6+SWVTRNkBaQUuTN43IPmBU1LD9bmqKX2Rbkpu3kwSQMr3wVaIh9UpJ+jx4SZ8uhgpJbF2XMFSmQFZTu3NamUxJWpCcmN8Nl2zr+gi/voK7/cphyL6jH60jMR713m9pTOc1u0yqJyzMaQVptw05ykR9YfVqdZ7RxUkfb+mg9lPapikqu3h/5acCAILZEtq42psI/HEHK/swrjBn1HERyxOHUdY0GHalU7sigUe7J5Yip6052pyagmJVKi3iQw3yLI495uSe/TkCTxVN2W1Pd4cSUN4x0qXs9uk4A2M2Tdn1rQ5j0LuDXdFAkXTCaZ+ZT06k8zA8UR0TSvSAffOKlnuVJ+5zyUg54t2laNQlpxStRajIFoKxjZFE69TADi/HcxXa9TCeqSktLUKLMNBxNTFX//7ViMegtKH7Erldo2srSklJXgoIZ4r1HlF9/rXwEFPfZDTJdW1lSUupMlDHDqUUPL1a//r+6jZaSVFvi8h8tDj9isUFxOc6iU0zopjw1/wmZ70gtTn3aL/vBK8GWVPeG3LD73adl9z7a0n0emaW9yTO7rqK84uCZ3OUOHh4u7xx3SffIC2T37Y5/YAr2pHpW2fUKnWiYXDXZmagwDW/3xDy5smdU/efUddQt57zfJ2W4hZcxkqLVuQ2kztTHqmOK16jwPzxsMXQYVEye4k4VvZuibPdGlFUUdWEzHODIbvB02A0nPLpKne2hBrirpSHi4fkFJp7g7d/Pq19+fUmlsOU+Lcfom39Qe7Odtfx0VbdmvYuNq3bzrge5h3ED5sobtLmylvFBBYbyvMlNNI+1+qh2KU0Mi032rp7JtUQyM0SsKawWRdB9RHViX+6CrXcfXRBTUOhsh8v484/ryua36LX4/LKlOlwrYWQGLY40qCIkmwFFzj8hgOUFLXqQSgfMWeUpVE4ulUu9qHtgcQsnnVPhaYt1cN0b3iS+xe5uRi7Kt9gtFG2RlZdC5RQwSIbTKXrFKRUwOeLVpVFpRAMrEzqdSveFU2hla+VWwOsrBFOqrVaZYmKLnasp7BwEtvTUrNy8hma0GfeiMN2f+eB9kFWTY1DoojnknzCLvL+gcllQuSmxun8BjSsh0P/pD6/NeuKwnHo6ekKsmJArq9rbanJ6pGh1JRiZp1OoDJb9XTSY4VOu7NF8Bx6Q3V0qHh4Q4WGVOYfFYQDETStp59tzpglLJ5aCu4dFL6Aql6/f79otHN7pH/A7u3bMmdMg259yKJsrY7JYeRDtClCeHhYUPyRl3zdf32zrrutM7wdPT6CxogXbuG23Toyh0uTrLtdvYVBz9AH/NuacDxVw5TsO4Xmo+ONh9J0m/8SGzlLnH2gpmdxVDkBvagpvfYS9YFKcKwv9lsP1ZGCLPG6PC8gxlsfFdpzi8VBOe8z6cpaf31MVLXmr23adIApvBe0FH3V/jH/cMUoSkX0WV/fRC53Z5d1V85byYPiJ79ABqT2js05NJ1NTyYqDvbtJB6AEjMRMDL2WxqLTCIymOw2B78wOIxPCchZ/+buMvmIhq+UXfktbXY+zphcpPY4EQDmvIE60KazQwwTa3GLzWfubCnfoCgFwnUFHdomBOLL1Xr7/8M1iILeCwBNg8u09IfKXmAYlYwlVPp0PdwW6AL4j0BXu4vOXUAXTwaN8W43nU0V9zRPj4kknnK4DYSAzysU9r6rKNU+ci4cOuJwPhYD/Euox4G18j9sqmEagQT3Zz/a4WQIBqs+JBg1oH9/jxgXzCNRjxNKmcp7okaAs0jmAqacZ8EnPpXT3YqlgbkTaJa5VCVj5Q6aeZtCQtt21XJbN7c7CHHdThA9kL/raoGr6JmDf9HlfIdy8/xuKMnFPGLgRLOmojtKsUBdmLoQbCveyvy5feimYikid/7PnwG+qCTJPSwtj99blSfwoLgUAvx9trWFP+LeXvrct4QbT0BIEgOH8C4jsCNlnxwuI6qQzga/QntdNp2P29xmF9BkGHUd4QOd/H7dVIUQtgq1MzDQE5ZgTmng7t5RbEqhfGngMWx1qL0ZL0ZL0wWa+r6mmvmXnAh9no6JEbTiI4nCu+DsVhJcXV9Mi+PMgMCguyad0KN8V6UpektR/KgBU60ruivAybnOrimVqpHoxv4JvtZroKhB/IkNS61PJifoCeEXuSg6IaTmChvtPPOGXqHfx3xbB/mbqZ5w28M6PeodgwhKqymUwzjwoKYms5l+OmGufZMHcCSTmmaSohZ4YFwt94XRdDwEqshpPoapM8sRQLHTd5fwiCdQevcQ/KyJn4cJTTA0XE/5zGH2n2V/KlLQ6dw6T1k1xg77x97P8qFh8QnLOUbjgYboGxfhPT8ctGdZTqMbOXUJjnhxFzqkhffhNm+Nycsej3AEOkEmKZWWB5MsO25uhWFLg2Od5IuhTSQ8k5Z4aXnGxClZeHOFXwvaHh/IrO/OHHi4H6uWp5eNIp3l7rNbG9GKfLiVFdFWnihaL1rgRRduZAcuJCbqYRIJJTYC+lY4xzx+YYzuPoCOdHFh8+uxOyDu67PCqbcDWz/BIrjXouQDd4eBP0I+dwGi680fzk0qgKwjhmpfBvpZU86K6XNWq4lokAUPJ3bTWxjtNW7081DIlGyFdQ3Bt832zHyXzjpnrY8SWn3dDWA7x0PpbiOZ8zqZfWqR8xZPCZt8jIlvMo6PUmyBGGH0nKZfD78N6GWS9E97lGMaTfXJMPMpKVCCfzG2gG1irwlESGvSVxolxNUV3CfJ5zi4La3pKb1oGmdl5p14kaCuXg9ong2WdRKUxQaTZLA0gGI4RJZJjrWRIQy8a4hqlWyneWmIKLoTBGTlkHZE5IidjvX8eooSANBc3KJBgt01c0WcGMcHTsNBIn6cY2IjRHkhCiw8yhMhKo6G40sTWncIy5AsYk3NZFdvrsRCmSURSiBV3inuIn5M8HQlc39NO1RCcmHnf7MuEjmMR3M4kmaPrhqT/aorWr8AwTjz28RocLjGRvtlfQeaGiBKpVlPQQlhounKYxeQ6C3NJUc/hEZI3VK4B0ksbvkPsDjcWGujxjXnzckuLv1paoM9ymBehx1N7BTWXZuY7itcbPo08e47gQhCCswUnL9RvmvD6BCYlzcidZfJW1MW5CeZT/gWmDOpleFSL8NaVTl5C90y7NHNDbwUXfA8oDGz1tOb3qnPe/fr7qIiY+MlCDOYZUcfsF1j6J0GLPxU0nYD8ElFemp1P9C0oHB/jti/OzSfrCwt6dZ4pnuz+VOvC4yHtYP8kVjxFLqrKuqjiUenvLSaXFI+qo3nQNTYYqnsnw8ENmbCQsAkST6HFG3SseDIvlp4iVjwFG7ZqiYO7EwVZzvCvnvJ8YwEEcbVoR5cXsOIptt2NOlacKr2Ps+KveIfrJ4VvmO4WKdaGaV4c23SsePR2sGCQtaGWu2XFtdYu1KLweAxcTIu1rDhZ/ZxfwPpid74yH6dLXvHm6RgQfUhRH4pGH1KVh5oiob9pNpYNE661nX+a+5r77tl6ci535CflT0C/p4U1N00w7Ak3wZxdJ94pst/cdFfqs4JXzK1z+u0+5T2L/VcxX4UQsUU8bdHwMZAfClv0RIkF3yv4lvV9Avd0/IHK34CPa8WgGJzMVa7Gq8RwmLdrhlUGywvxoIL6t9xxciV31EJCrP5HC58Qv5Q4juMgMn/6ILalUSh0nyK8FyXb3xblJkbzZOnOuHiQCK7xanYHxP2q9SUs/RLIinnJlH5UPnMyaf7SwV3rGG0JJ+XRPBw5+xMkjRff0yLcgIqPtFHZkIdzT676ZjRb8fOy+jh2OC5YuL1YvI+z6re41ItSXBHOez5UmH8V/EeIU2UVLebHysAOkvlSg2ZPULhLtZ6TpP8Fslq8VKwfnc+cEqp1n6dXc1ujOAHRW2Tllij9elbkW2ojoa8p/jkb/poUnyeC/Xz3zfcJ2BOuf75aoxVHRPjRjV9oRrfoC8az2E6G2nQhaYtFvyc897I62Ijo+eHfBfsXXfIM/caXXGOxiQ4fVCeqtYxkgWbQEYAfb0CvIHgh/IJ8SrBnSbrPQGc22zGmJemSUT4B9TItdpI5govzYlygNE44HaxmiclmCnwWC7cnqKiGzTAX+vl1zk9xcYEMah97KkOFRJi/wZ9TXD/HT4FsBnsqQj6CXfhY01BrraR7SMZpBvpJsoKkmUaYY9LV0B/plE0xfjKAE4EQ1YzWaTyh8CGTczBSSFHdY9LrVcH+1fpbV5o2INQIYQNCDY/j5nW6uosIDWJZpsJ2rqQ6Skt+CmcKZVKFcCPkx42k4fD1LTL+v0s5VVgfq02pPW4zVZlWwFXdCtPKZR25E8MG/dbvYMdB9P9VqdNldWQ2LJvP/rRFSM+gC528qbJ0YYoptfU2U6Xp3qxUpbpCeJsRNbOOLDq2GdB2ns0aiZA0ibH6aO6C1MsqczZaey3ISwMRj0qr3RG+HME2nsqj8h/EVVKcFP3h10i3bR0jcRmGrM2cJW022ExByGQR00Bd4OZZijzSH+YCdRKdNZoQbqOTPrQEq+5eeufu/PSpbg1tMNIrMkcbCYZUm6b8E9d2E3ktaL2qxP+5kAh/KvrplqcJskaR/awjRsIlzL3+2MSa70f0N1GyDXktRjdhTuQYxhlMp9k0JdO8AfLjImRTxxKEnxamKOmQLnErXT0j0Z9eRsfx5J6AunRGDYqxfCOzuDshadu9SH88LNL99tOO4tRZlvwrs3w5bgyKnTtx+rHmzja6qSqYaA+lU4d0v0viDCIXsmm5GlOxVldhYnaoKyaOp/j0cUP2Fo5+n3vu/Vase7fikf/PfIsCEu81eSCtZIlm0hEFI1VjDplT8gvybsEcIPSEyVwo1FhanveIh2PgupDkGq4RhDjlk1RppSoDennB6xnv12gMIzbTVFyg8CnBXMDxwcsfKiSZxTzHXIwQm+JtUVUaG7HS+UmNJtDiA5NP7zZ90k9gAa6N0qvMPXD/HiOsdyBNCa1iVRipN6LGJ6/XtPb4zEWs7aWTSFqAU5AVoo2Q7zVCNGn7Te1eL04WVT3H5GSzvNJl5GGEGlBTvCPtnC97sOD63CyiZ9JFtpxj5hTvKiRaD1ZdL2SaJzisfbQTLUSAp2V71kSGJrJoqmYSpF+GhiK2cseLFqJhcNJNQC4249Zq2Ojm456OE+Ikv8yc4uJyL68r/9AgrwFM8BJe7TnjZdwv2IcK1UxuYHtlP4pKR37UzYnGOQqfFBD3HA3OqywYNNHjHrCXNbodGR/FPADw28ncrsrZX24joB/Az4+cJeHCGxuZyhTiLLKmJAFtguxZ+c0wNk75bZZOPmzULUicGtvM0gfEeIenSs+eriwwVXyReTVt06gB+2hbNVWv6xdm2TLcEOQ7nDin2NbpheQGNb4YTkzFuncpHEMkEE3LVVx+tNjM9Je3jYljRNWOhTw2hmKNAW6G4VSgvN0v+I8EhMBpw89b+UP+BwKhwBNQHtgcFTvFZ8UOufMq9Gi4M/xsuAOUTvJ6kiCdlgX5acA/tp4Ukp6QQ/Lz4JsGNsviJHHnNwXclsOTwjsFfVts6DzW+VQgtkU81ZkacneGj/U15W4Jn+prZuPOuNDFp7bEQ2VzDcM784R+akteiLsydB4Td8YcnaeWPPO09x0DOTd19J0CjrNtuF1CfKeod+4Kxbew3bj9Qt7O8Frn/lDelnrl7IcNVcww21Hx2U5CX1kREmkUE4XZPaWSbSGMq0aGRBrFRCY7UVmLKhVTMbGRhyUeq/Kb+MuV6Cx4WOKJVDETf7kSzonb0VjOwtEIS1BGEUvUsX0gYxAIFU5NsgRDFMmIMQAieJIxGlS1EA1SbBqCvqooHEM1xYy5lEuI5ql6G4K+aoQZcwFXDFVWpqrcyl1wK7fKrpNVbi5DZepAMT+zVWgJU0AC19GtOWiVjWVwG7WjikYSKwajxfCZnQo6HDcwf0wcKzEu4LehnKEsm7NiS2Orxac6xZhQijeyU+Q6jy0qOTqPDRoWlURWfwnBOfyr42JcMEpXCTHPGxUWi4KOdYmLQ0/OIOoHnaWdT8WVsXKKFx3T7IzYYhBYHSlZ9NQvh2Nu6y6KJ75ahJXcxULUkgdoJnUgyrFVi8WuY42qzGZKTDmbOzuOBmZjXBM9ydUnkm4ZG+WugXXtaLkuK5HaSLaYxlZr12M9BsUwJkNoreM2rXtxeS/23dECtFHdsVmHYPrdjieX1HBpjG4HVdxUT1dqktvR1W5dYRG9MR+wwYqWFVbBFwOEM94WrzDgp15fzEsPAqUHKyrGfC50ev8WAqXphRf/m/8ASboApLlxIQ7Oq4z5kXIZq6OyxpZRvWNbqZWxa9SHsY8UeoylDcey8QgewrNwAy7EQRBjmRDBkBxUFAWvXMeXczv9qQHJibVIyFpgIqMkmasnT1YVO8Jx1rhMRk4qlQVKzTfVKs4MmSNFlfFKlS9IeYbcaO/ialnwYooqq7ESKLrTCwjm7edKyu65J2HP3FuJeNVZxkFTuyL9Qiw5kpyiQIu9bBfbKUUEmEHMQDmW5HYyzE5lpS5oOTOYUVyXEUgI1oRvv1OKWY/hQo4Q5xBsb6CcJRnY9z00Pe3cJ0ZbxA/F2q6WFvFrGhmNUh9IlqfNyBSXesSWlNwvdmaLzSzyXfFbUaFfQtL+qiVb7kzY+MhLfXQMP+UdQ+3NJk3bnGYYSN95O5c9gNvubzgr9ChXMucb/TRMv+zRrs4hWl1/5xarTvfIowF372uivVnC36zPTxb7wUluNwiqmCwjgC7zhsw+dhJvl7fCVwHKpve1JOBvzKz01kxsI8gp84ckXcY+vkogUu3PrJlBtGlQTYUXpEx/wJLoL3L5xWvXhDcxta+vH8R14H9IFltmiR7guH3oAW50TjpwPIiZTaiS4FyAxqMP1k2a1qRrncQVF6YL6SLanlNmFxUV590ijrsfIDvmz6dCvW2uuFKAH/KLsJ77nWi708YzWDcr6YpDLuNJy4BaqSwi1/59S7DaeskNX0u1MX9B3zF40vfdd4nz2T4fYC4mNNmpSWT3h0UDNusS3MBpKJFcwR/g3SsgJUmmBwqClEdfUDT35owI0UxA2oD2Dgdo7SGLVEnryI7N13O8sMOiDdbIPO7EvAxG1xYIm3gNJpKr0AHkXgUJoTeJBf5a/tlah1zelWvhk/MVkyweVWDuMorT6vGI8LAZGzQvQbFpMQMX4NWQ5nNpJvhbg2clEDx1Qix8RtAGjvK80CbwXFjWRj7HvNwj8xh8oBvzyMqQcQ/BDjMN/UTVTDBmzHbZMW7O1wJTb5q0/Ke1uGOGvi7RsDi8QqCO9X3FnaDkOy5UPv1wjP5YUN0fqLxC0ZJBjUZGlTxDWTImO/SULH6GqkA0xQ4thY0htSEfHY/L2xsNKo+jdKcYZqYSpF0PrSTz9LK1P91CFJrxK23nKGc25jiYWKc3jjkvVD59My14TN9z/5LKX5ke07XBTP9ruk5ZNT1n6uj3xmeoSk1xysvAU8GJnGrpaiy/KEsfyJEJ1YEcDi5pA0QsiyDSGAKBsQMJBR9P/+g4JLh40SXwZRz7x/uq7KCPEJxLsnJKE0HxOWbbdkMq1RP15gR6cf0ntse2ravsFfwyuJgewOn7GqlWWzxbn9hks780IpkrmR5DupvxUsKGdM+rCa/rbCPaCwOtrpGX7LaXTGNmTq1pf0HlUngoff0yz759JsvqJ0M0BwglHd+bmgeo96+/U2nXaoUGP1fZRKp/9p5PTFlozd7jVGH1nVSrJl3W5J4YplIr9brtL3/5r5Ea3hQ2RGpyjcVY5/+LexoeMjzubpmrmYxW9borsUobfuGkdw4YTtYpolzbBpvTpVNCcZ6FZVkXC1k1D3/igGT71hBpxCEqnVwwuaQxXcvnM7ITQMmwryUefoKZ777eP8+ja+V+KSZL2q6784Wz1xLfdhyvX4U/O8SVD32GV9W7DZy/LXhbuYnhs7V+utIwf366kz+lBu2yWnehLWcPeRx6jn32cODDZ+Ej3GmD7kTlrLfR9O6AXF+YuTJdr2h2tt2l3Z2iZFgRStSvVlgyr6fBx12/JIyPmxXcVL4ThePFjsQHqGavaKYDrOa3rcbqrMU7/4WBL/F6kg9Oefqr7Arj8e4mnR/CD8JtutgJy+mqe0h4kbpCy089xZbpGIYq1pKDhrX5/cq04n7Q3atcsBEyl8l4UFHWAp0iTqstNqjbKYuLBONO/9uVBpfONTgkl2h9I5byAzo8scJFr0ESzGXFGbZ+wKeMwCPgE7/kICI4/j96Tu3Ci3m+q1fNeS8iNT9QuDKNX/h9qOcPq/bvt3hs27ooOXZnoHZ9yprgWyBcMoTta+/+d32+ivvrk2kdIitwx1v0B8m/uJdihtyWvfc4tVo6vtci7sEqlfzCmFaAOS2xPOsyA0p5q/prCmvK27SpibmxC2C07Puo7fsLU91T7ageAllZbk04BN0FQ3Mzb40E/71g/7T3g0VrwFX/jWZ0ngYGZhp8CK7ROmuxxyJ9I5vHT/NqlRafHDs5XVcYua8VOX8kn7EyQ6dqJk1J33L6bEnPYq0CX1WuZBxqU2XzJcJmN90Es/4k14Z0KkZnsGVj+7Rmnm2nDbkAzGuiXFQzdAgktvdHDwHU/LnNtVyrBrHPe1pgDLZ4nmdRjCNWzwOU6GtdeRDL/5IsGFukJ2WcOqn4k1UXWY5r4+TCQjlIwjEfoqAr9X31/TUdXdny/GBk7UaPkM4zhv7MwLu0PV/wbPSbzWaeb0FmoF66eOsI7ZjFk8edVlyHW4Vx0h4rUM9coD5ibAnTQjihedf0kZEFh81GgmXpDi3GVnA9/+W6sXV9fCAwsaHUROgXqL2usbzEY5TTV/AMYaPVJorLOSMvgUbzMiBy7cojuKOJ0hgcesiFIDSbqwmQx28V4iscm3/MlLO4w8LsNvgZCkOw2YqURDg8ZOSFozdQZJgTixki+UtL3nek96tW5x4n7P78hXmZ5v7SIsE/1zxB4g4G2s0TdTaF+/LSjpsINOSvJlebboZ+YhEQ0Uza4U9ePpvxNi2Hx2dqmqb/1w64heGpxdXtKJ1WizZX97QGqsVq4L7LPGZlMzj1j423ycdHXsDU45iiMgClPCg9mPQgPu42xXI9pvjj0vHgcfnBkGlRCalzMGez9PaWDsDd29/XP9DW1jY9mvUUwR0hhjVp9mo7ZlMr0oFJU3oIk1VetgUrFHKWq8za7Wqbt3h9ja4jmkbrRhkGOjBcH8Sg5CCvUGJ5g+m01VbVdwcwWRC1e8uJEvUTkvbG7yxtaVqubhdAG2qFFlqlbuGEeAqpTWDCSDtXQgxDeOvJ3B10ztDMF7Q+C515X5lrEQO/Bz3SNQtMcafYoB55mnk0SE3+cuXz2NL/fo3/Pj0HLpOP5165Uvp4ZDFdBLmgfORtuGqT64VzH6N//bPmgs8+J4uYO9s8W17gGOaYjs+i2DpOFky/TqdPfDV1qSXJHTtJEvTxj5P++ZAEsCAiBCjAC53+Zx0kGLXu4upgeqq0mcaqrDqjTBNlJmgV/SOvKlqoLCiaTXB0enlY+K1rkmIdlYjDzq+v4lbwn6t5M/z0xkL7ZTz+29s6/3IWbC6EIH6V3tvaygTt7IJW1hVsB83iTUz8zM3ieK146OE+L5jrPO+1Qx4ETYmx1w65FV7DC87nhXNd5t1TvwCR8yYj9MYhZ1Qyz4VhjjmOzDDYazOVzPeHIJG/6IYDlhuNJzrmJ4yKXaLFE3tCE5y0Xk7CaVFiL60Y5kXRT6LZZV4equGyollGDy8FOxrmW7ul3aERc2RzIsJ8GF64xWlLg2GHE7Tawj1hRZmbYRWTFs+8EwQzooQnCRzk6cGJa3lLSb1psTv7ZtJbnYcnh5Mg/NFTdtX/MJL/VgM/syCjydP0E7JEz/NE/DRgezd5lFgzQf48rAbYqgu85KK854alZnKRMw88LkueSaDc8tYTSfhZyTYJDA+Tv5CUXSM/JPFtkWySQM8ZSl5Y5V3Umb6eo+GitiiJQdWu4ovZsdBz8KJ+gJbyVSgMSfWnExJ8/bU/GFk/bqdD/DG50JEQ+4sFt8Cy3bdtCpMHk1xei1/D0lMvgIF5L5Ncm/8/AxsPiAdg+cXTWYEJp5PtnoufxxwQH/hnGd+Baedc582exkzahR+Of37Oaff7bkFrzEPOi9Q1zTGbxgNQIqKn/2FE/vtvIURgLDD7i8eZS54JBDrpS2b40MKeLFYNZTU0RgBN8TGTVJonGeE4un+FHDhaJVgeBiBJGBAayQhoO3VxJJ4ndn4rErrKDko5pzVntOVUBE+nAdEtniqdTsXTPNecVJts5gluKRo3U42GqDNiX9N4CNU5SLiYtdw9zlarTKERZyfapvObnBNDfMFuoihASUhcXJwWBVmZl6Ps1X7VXvkcn2Byc8I+YaUFdFT4mTMko0Z7su4eU+IDBDUW/5KRopEyWgSIo/7JAUxXKFb9W3sYG1fL/KXO/mR2AOlupDHUnYFt1S4N8Sb2mXu0YpkhARQcdqbV/7Xcbn4xDqjmedw1BE3308M8Rjeo3bA4tmo6FPc6X/RB8YJZV30lUveVCi4rmck2Lk0XBPR+0PAtuFCXwhjgg/lO8JjFOmuS3AV8oQ3uZIzPRAvlLWwtsXMkZgO1F95x+OFSZlEAfoqrfyf0iqQkCtkZgplvJNPYf0MeB3M92WKMy0N58Ln4KYuC7oAIWnnfViWVkbXolbHklgGnNZ68LrDayix9CGMTUgaUgqea0eypFvY2/uJ/XM73IZhCgLA5Tg4fWK5zEzZpwpSpdcH1VFTMdJebq5fNSLgiNC6WhUwSE2VxIXZjVl9gDLFY+rhprPyRenLZwZKNPg2Mc6dNtvusHAcv5p3zhjGRmXKbQDjl4SKlbussGylZmJl8CrAEhmMBmXPdG4CxVLPpnZCEG4A6z90PwmQ41GLjz0Huo5/wX+pcfHRROWNYmFVE0GM2rHKf9/hpQPDEBXR5WY4eHhCb3SgXw0UDrqYfHN/KSyWfB8aA+NkCfy8qQy0KXzDoz+KZXvOA2AHNkBWRTyUCeyQfuHzgAbmVMvaRnvYA3sG9vPwEDdcn0pw0MsbDCuF36hXejaRomlrK5/1MkwXBZROhh39WPbKv3TU4Tu5zNkfwg7JZ7YcuZX+qt1UdwHnPkqrbujaNZTMpW2lKNkPwBwexg1TPs5oEzwrHZL+aFosfNT8egvv1UZt8uew3c9CPk9P4c+/MtbaGcvpSCt0kLyINsrbCs46+c6QHbaI82UHY2H/uWUcw/KyPAeYqiU7V3X6gEP6+FveLxV1S7KUpW4xoFiFqnkwpjYWsOM7f8M+tHe4RFT6DP1qWGh6Wf9jtO0cX8w+A3k/vVx+KSf8K6YdQF8nh2aMRizw5USOvI3dYuPSaCgnSiE7SohGTktRgOPxrIbSq+tUZfQd5B0MEPkV2dI8b+sfWvmcobC9sEEg3DFpkHLdmJW/iefhK4ON8c0fkRHBkagoYE18RdmGkO7IIL4C7FsKdpaYf7g/e3ev/QDYV/GE1ceNoEEk3S3IVJedjFiomgJieeTMm1stIImgHSEk4oHNZa9THXyYy5Z7WeU9DA/hVTTxHetA9zgHxB9I/fO/ZpL9UeMG7+bBuUI9+9AoerDCaJFdfsTYQcS6kauAJHiu1cFR/79GTGXyd0WcQGEIbhPsWMxfCiOIDH1N7a7FLNZiDBsEG2zGDVi01kkmCiUVBuJHBR3UoqIJ2NCNqourVWvmKC8MJE8fVOttRuG/Hjwpttcjo+kZXPKH0dM4x5k8PFrPj7wQR5Va3oPm0bvnNlcg0R5PU5p7Tg82fBsYeBKQ7CM8JZq3Bo0tpUZFglK5LRrtE2bmUrxj/aieF7y6nf26Hsp2O9fi3TR//BQnViKcsfL1HsjTAnpBR9qVZ1nHVDtMMzu6qbRP41RxODTJKVyp6cDxWJonn+tJpvUO6HDF3F8J/s6JL4Hci11enzJCZR2R22wX7yYxDOQ8ZaVLHJKn09YQerrBcJwbcs+NJDI0sg6+0F0m2WuHGz1VMPNQuEBdOU9qpU3VxYpewWq1ZbKK5aYUlGVU/f54f9+e+d/oveo15ELUoWcHcwIeLMGIHLwPu5Z1u9w3lJbjQQSyq5BqNrUQaDriRAKwzuPWGWY8D2CTT0H6DtoH/Ok1111Hp/aB4iuCp396p80yCLE7S5Ch2m+qY1hhTjK3sEqgnGlr9b2+zwzT+tB+ZxqF+m/gOxxhM/S7469WgSr7KkTqCC0sMsgRabzwQnvYQLsmJNuJxSlSFvDvpR8S8XQg94J6ze9OmyPgxOBUx5Svcty3Vva/glnd0/2jiVDoHOUON5qn0Q8UmEkog6xasg0qKk048jVE0MjRgnES8qHxp1gE0auAU9zXmx5FfFuMv76JjUZRzSRkcNjWx54rWd/cjwFBQ8dzUKNdYFMySy4xobq8yuRg239jXSFEhNxxPCZCkW/B/4wHiHu85NC8e+vnkoAsD3H8Jzhfa7B97N28MBgr6xw+unhzDwuIP/LH9put7GPmMlpPZfUzhE8KtP/nkU/tGGxxhqI7PfS1Ueil2mTVZHPjU/GcrREgEFIe4TYYbFOHcs3Nidf/5W7rQA8Jr2443e/Y4Il8EqgAudK2J36JPqW6t8o2iY/TKOH98wM33GMZ/nTUGS83952j7la39d0gPBntW5LwIpIvz46R7sDGo78HwQrrihPBG0sGXOLMizFJIAji49HzbGdNjnVaKHULNdKk0jzkbIDXvNjktMpZprHwZmvyb9DIZIgWt5V+D2dx6DO9TG/xFe4or5FadK6K5QbwP3M509ql7hvL4YbQMGSFFfGfp1Gb1WbxgUBnc3MNisnpn34AkjjfpLPcL5j8TPwmmFoxclFiMkjcvnci17KjogD1n3V34U9hVfg4XvgkJaMb8IKB0EOgV8aTeQEMKIhBtBNBG0DTwL8HD8foLocRis5iE+Ar8I7NH7m6nXT2qgqs/nJUkmuJBElW9STGS0Y0ORmrSb++hKJq+YjV7aqOYUwmxN2C6zYSKDRqQIFukmnTBinuDo37kaYopJpYosyLPS6VZcTNl6u+zrQ6nCGw5635IbnNuJgO9OGspbPtuLR2C+esHcBqob908GY7+hGA+6TBlsnmMsUtIsZNZlrGTb5M2bOZax3/85r2LUIcYr9ibaYgfYWAwj5REk6e5em/G09JY3dNYWc0Zer0/WeNDs7OF1gbqU1yhJe+2WFppbv5WzgK0mfNLEf9/syAQovpc18q4WuWMAOUMz+xDZfUB9TF16/zX1zDNwxLJHpKABEdTmjNGGAmEcRI0fVti605ng7J4g7Jhjx8H3Q/FLzgSNFTNtttTpEBFQQr69aHUmS5OiYujDqO8mOGfIUTGMRLS2icuVYx4LcUy2OJX1AqNijGdTbO+eYS4KeSTawu/PTmyu+xzmgnFpaT3puwkBT4TDJ1mF7PgcgNkfz5/nG8r1BjuNqYtJyk+ZWxDdsE1bsv2D7ipCmm6gM0guWe6WsmMe8g2WUrbIZ54BMGdgrQYNkU7nVew5hzyHqHUrhQ4ofmSdL4lnK4t0tIC+e2IiONv2fgNN/ZBZ+ci8R3nxV7nghaozDLEwh0mGWsFuZ2V5bMoPtTEKI1SjGcAgONHgqk/J1GFLOxj/y9eErGzTs+eiT+ZopPQp0vFdjmQz3ezUgvPBygTIrAyPw2e5KM7EFXMFxpLRE1Chg3DYsoAtTF8hfM1OGF+21UkYDFTRCx7uOFc7yQgRsWsJMFhtu0VO4xSIlstwlt/oLTFsm7bAlJvnPKQ9yIhdSJZk1ltGNrM3KecVSZmYn6bweH0zaAMcMOx2ciAAQ0r7h/iBd+l6jRS9dxGBInC0bEP5eJRgpqOmGSsiiNjskIBQsPpMiQ6vJczTE5+UfpDFGcJW66RV8qMn06nmMITTx4qoFgxbBGMbOwX4z7B5+kGAdp46FVUShSUlo8HfRZq3Umj7iQpFozvJJOR90nQfSNNoZFsPp/1wYkvKUH5jrz1EC9PMedLWNkodlSQ6uAzlpgq4Wc5iLQKUjb+VahBzEnHxRO5zMLuVp44RUY203YPKEYGYOq5SO4LAgqqq5BovsFLqXSrhWATs4splyPDqgWe08wYqymtg7TkDLxM9OFXyHRFEm6Fma0eNDMSOJnITMJJ7CGSd1T/v7gJl8r8kL+N7b0Zikq+yD4kHYzx820+wqvJU9hlYlOZOXcpW4UeVHyDzFZpQ4OnfYkBIQI3kVjwqqg3mggXDYSD/zVzrr4z3/hhdX8r56B7ybXbc/Sf9UfhxCWjpyP0moacYOK0H6apBGYyIgdkDz1IIx4QN/Zf1WjEGAg1n9+bS+RgeO7HUuskF4yVqi5JHUCQMtpFnQjjNVsGb+s5cFay/Lv8v9IWCsPCUl/FV+5lEIDE4e0mJOMTHUbh5rTayp3vjFQ6OG6p6xl9aAT20kmfW/kYHWQqhRzezaOzz5vYwsSGwHv5VNqf46TJQgcrxypXbJD/suze4GwXLz0M5E86sv2ou5so05EM8VJTam/YrI129g/Gj42cc+Br9FRypCllGg3TtAPG4ORJsjqZd3IIHNC/8NILo6ijVFRhOsxk3oBk/vcx9nErwdwYvmbq0ZWGBNlUoCeFtvCldAKyEB+n9JK4NhbGkNSiIKvRMMOxeUC4FIjkFkUw0kQbyN0nxWMn7OSoW7WgGQBypj7JNMnc24fyhScKSkGHH0eHuyK65u4f7o4YiBTKB38OTmSA2AI/41SGNpXRGMMgoxi16W4x9PCDsicZlf1t3C727td/v3xiUn8053CsGhNO14RB/Hgu1hD+boHJL/9U0v9NTEbsX4SbTIG5aalxoGVIp8PfRuJN8a4IGe7nHrRxZv2Gn034YuiJHj4rT6LyYb/YB2Mv5R15ooKSeni+GLJFvkviV28E+AOxjJx0Wf/oYdukAX0vcxzus01EI9m4oJ7aB2PN2/VjQ1xZlzdNujxJcD5INJANC+ryk8mPS20MojIVf3ksM5NGBVABtpStI+UYxdC72MD/ayvJk/ojsx6+fjig5vqwx4j69Q5iQ/2BEtsPMT5+4l0+RKjX+2zrxc2PtZPgAmEvVxS/mVcyJpKCJmofSe35zzim+WO2U5uJhyIeaoXfRDo9h048WtNdBGOobaRtv761w1c+hvch+4A8+6VqM+KIgZ8smQ3uU2NreNgiw8BhuhIsGV4njyLsLWa/Bo92eEAtI237Yz4NHbLr069XPpwPj0naN2ruBgjb49kDWWkrgorC78P/rbQtbmfxrwNnOLu8lqRV5f3r1V9KsaNCYgP5nm1BvEZ/dhZWGghfn4hGt+ZC7IsPD+/yOvCTNpbDfD1mMcMjJTJTTUPHJ1nypMtRpy4X2A7oz52NSB+xx31r2d8r3x8+6vX2MBH3XgV9NzPDQg70l5QpiN8akdQs/dMYSSPTzOmr+8/AQoPlDVZT4AG9mYwP+Rx+52rYnVdqlUqmSlJFnF7xivFg56AhZCgHspNDTyg9Y8MV0yJv/uwKPyGdmhKUcko+4Q9Inh+ms/P0ycG5yZ6h4TJpdSBxqJpbtiwy/Gt2sKO7AyImds3xO34wfO/c6ADwB3Of1/iQUVOjCSc8MMYXl1ZfkQ5htcFwy3ZyuyIuyekz8ubD2dZTqWswProVanjZoWUkVDPkUNFMNqvSUz5JXeMYuoi6R4X48JrGdY4ei+T35H+lQ0P3GQ05XB8p1gzZw9elqfiEyEkrQv57ZcPSyTSGjjEVZqr3kntF225Q3oA3cmRYm+KjCtr72gStOjxm03AKfJArgbWQpaGjsePWcMCuq2RWy+OTiv4g7Of8DWRpTbJQnVzXvWCcVtVOvX1CeOV+ONvPG+SaZDH6l3wkfxSO6Z7ugay56dh0cj74e0bauQcvhPv6rTRixPiLD788I+JoVoRb0CLAHHHtWjJ2OrMC28xIw+DnGWXnfm9uStgvoq6ZhlBMgXGUrOklR4LcQZKZaWoOD+hlpHd/+pnLPbb9UdjLlvxmMiJS1ok04cGjBua3KOeP2BcAfOYrtmzPsRiN+sV7XflkZbWBV+AfFkiELQ0gtnPT6xFzI8TNoxPwr20ZxjsXNHe4WjUw8V5u6Ea7E4JmcicQNHeGP7Gf07QFHE2ZdcN43RhxVghUAXzswYnijyWraOMmBDoERiWykAi2mvsHP3emH7xcP6k/2nl1Wm1Ru65w5q9+l/mS8MWhG5G77bR0aiHxmGCNBuJQwFmYSqUAK2U+FXsg2dU8SbLIUqDn9zwQMt/XvSv6tzp2POa88urhfu5/Q6kZ+8LC2/pLOv+Cwd6W3L3DvpPc/UYGV/64uhc6gDqSidMwWN6dFC2KYXinspqSktriWZ4w5vpZhW8KuLrZHNk5NqivdAmmIVrctvqVe7YH0P+56+B7FOzYIj/+mwgzfhmkpkzn1k/z/9xd+OpzEmyKLAqkNtVSrh6LC+vIbjJNeBs5i02vcdjBUq5/2tf7CTBgSnMzpfm3dYdjsrKSsJQdnQHH5TsPWX9VDEEG4+NwxSLluixz/3ULNy5gD0SiJKztJwsY66fJCtG9ejhgfA7ITfSZv1CbAa0Kgdd8A3sBucByJjnTOJ8shXt8k3CzcbNnNVVtX0fthcstWxHTVkSIwP4Rp3+jgvW9k8hWhmpF+kUzcHh3BuaYn5pltipRPC9Vl5pSLl8jhxvtP/KCZgyaxrRfDs2Q6prUyAkrvffvftpTAMzwfVrIW+vejGwadq8amiiIYchM5a6hMMM28ZfxdQOdZP2qZaugf52edvtvR3LNXvKq3KkoWOwNl/kz77ngz/v+zcVh8ulwYOriSrlWkS7hllSRjtLZUDbhLhHh3uGwUv+rIfE+DrKplkw/Ok6vvYdDpubJZ6TB8lFkxITYQMJ9ndd/tdVUrQuAckkIqXpJvXhwV41YGRLtFyscCeV2ecn94aGNNv2uS3Fi4Pb1hKBDtIt/EH7x/QuZsCSNSg4zlZtGw8hipJ3uFfFGK5pYcD2KdDC79deX9xu0zlI9nZeZwkq6s0hr3dITdtYAt39n+EV7O0k/pwBspnxPmkppd+xRRJ+6D4642C2K+PoXMNGwZ/CmXqiuY/C2nhNnJPyVe60S0hO2G+L3FH187RUIa5u+dbZn5Un4DdVOPTjiURi2WL9j0GfZy8rNSebW+wJLT+9jXcwIatrIpgtYsNq0ndmBV9JPNGaH1kEOoFVoMzlgaOTQOWzUxDyryk1TiC9SfQLRPC5Qlfx36zV5cHDBF3PPW4mwjRZMm12ruFjVGy5NbIrPsjyVIs2KrF0i3tCsrIP7RYxBVw14b2GnqM2jJ3w2FOXIFrXNhvWK3DCVdK38Uiv/MVjoBHVqgLp1mCY86nDnXPW+dT4bTOJSfQEEPpN+3zBlMr7+hmtFyOlFqTMiTt78AZst+asM50/YvVMqPGo6KlCb0g1m3vx7IyW7CC9bq8EfD9TbWgtDInfDJbYpfDqJsktxnXEWG9ETxHkUDCMhYX+kpCYanPGAo7bJe8m9yeQleDkkTXH2ZHXSPpQ/G9imkWmWHLY/GcV+jcY6J0PZwe0+h1dbBNkTW9NkUQEvbmWZRMXAxgLWd/VZjJTfNxEteCUHatmcKn0j6xxhVoWkgzaRZrIZHyTNeCvRV6xio3lsuIoN53Ge+Gkv/7gv7A1keok5WW6uHEFV/JSD5EE3KRyuXZQ78xvuV3tk5Dxp+X53qd+x6UGjs9EWp+BRGLtXsBgTYxSXrPB1jPGbLrBYNsKzrgZWNZl9OE2QbZ7eBy9b4yd81ogXClV3lS42nlSQj3mLXJVuZp8muwyvyuPN7NTdIuFgWHlhW6hErzerljuHMmzp0nRzyjwetubZelAePslsOF9WzOzAYyykFp6Up4/5219bOOrQu22w/xiErX+4wF4d6SMdbN0/8WlPgFZ6KUEyoTbWcwlscyonBCnSkyUJ8xSKfNhgjnfPiOMnBS9pQMPJQ0t+2rRe5zu84TanU2CgdzYxFKqFA0K8f87xIcsqX9MXO2r6Q/QVsk3I/A2psDWZ37FenOu7Lv/2AXtp81kzQ5PIoGkB9fA0S9i2dOnqE817/X9kvfOwBl4si0xnIy9ZGPMpXKWOdSRqpRGRsrhAsoDwSIE15Mw03yij2CCTGEf/7fAczWU+wx027mBzbmu7Zgi+GtRUNDkL1iPPUmfhCU+zX9W06WvIw1t8xzeTnYHS8WuL82BBwhpCy2kH2WGqYdP5bFhjhMv0IiM5vQb2HwXOcu4e7GuepNbqaBqRFcFTceW7dBUc1OUebMjamJn2i5cgO5g+hA6TB/tBtaL+t5L3lnOdV76vUvjACIGGK6/Ym18DhkWSgF0rwxm2+3r3jf990RkqVQOHjdcw23WU+xhCc0nwEsFXnP3mmX4B/QGwYe6d6NHd5PEBIJ/bAYHdi0nE96I5nu8Nz0YRT/mw/IBOPXhdBxQbSfOYeQ/2paPUU2j1hp5XVY93t1UqiascKDTVEC7y0Qe33NLG79M5LqcaxRUQrbZUQ4692XT9n5PU57/oExQ1nIEa3I2ZYSa9xpovXVpC3ZzQyszBJnHVue9UOVMpWaOIuMmBfFMtM8x/BIIPlzQ+ZwWN7gK4dg1Al60fbN21kfbm0nXXOfG113oFxQ2vDEMcKMJemiEg62dZZi/ZWCR1smuk3bn6Ouu3kR0zprri2rc5RidbrqC4LpTdzGGbWULLHtXHEN4j5B6Ed4HpwAxmbZLgMohu6t9EPHeweoMH7ujAhpDEDf4hAkuIJt2FmVEmJkSD0Y5aJCIo8gEVCUaINvpeydUHNTzkG86VRRtz5f8OjTRlR+XmxUPfsnjk8raGxa1EnfTYwis5cTZoT3uvLltZvTmwtFNQxJkigvK9iGhcCJif9UgJGXBWDVhLK44qHzdQz5uLzhuoj5F7B4BRWOjRnf+Abc6aF3v1GfleQF4eAHUay+DcaY8nDlQvnqnHO4ACwpR6m2y6e/gB0RHfFiVpC8i5s8AGa9ygO2pgz/9cbFm4xeVXRCZAPJKpGRQeBPSQVrGBmPeDLbYNdINnGxzeRSwHwBF47CY4C63KHszv8eN6sKCHzJwBcph2gBkwuHHALnjAr1QVv0LVvxd3q9VZOgpx+0nuBvakQXoVIvHruNsfwo9xzO9CJGcDC9OY9o+hE+JoVqAupS7QhdAXaAqQ/o27sKEu0BOFsL59+1wMl3Y3gOSAohsMVcacKv8IA7wsiAMsKbFywE9RaBEGiJzdnnANqFmKXUcU6n0TGMmJyNF+bDw7Cf3WyANBEasDuTu49zlZ0ffLH2Hpf2HJfZ1S8hsPfIS6xHPQZ+I5izAtse5GI8fQziUUWVPJGkiAxGTlHsd2Kbo4CiKX40fQ+CN8E9sCINAFd1UrZTAwmWPt2NfmhEswXBQ59suBdRfgH8OddQu4UA/Ib0bwKUIWcmPsJxj1Hg0Qiv7qgTSNwnQXhMZ2cGkH2ba1Bnm4H8hH2sG3aymBRvj7+lQE0aa9PLxMKiF6qM/d0Zi1JQvTjqzwwhhyQcFZv7neW6lpeGo5pu0/2wIjyEmHq+cY1ehNvGWq/xdfiFmw6ti4jMhftfdcm3Ks31/oz1LOHuxzIS/2A9lIG3h3rR/MNdZtwPEOOVTcRC44LK1iVaM3+aap/p8kjlq96oGSOrG7nroibz2wripyr4Ea2A2ZRiZdsOZoqDBElurPp/7iiqFCU82f3QbP3+gWlWbJdimey7TwN8FvRmUINsEKNeJ87YNxDwF2kENrT6q6KOsk+B2l78CVYS9yu62TOzG7GsGlEK42VSOqyFslSxPUTuiqdV01nM3YpkTkcUdMEWRBwV6/LuU1a1L2FdoTc+knB2bOEWNx2hlw2hwsYMefRNg/zPL/4OCTWmRWq0MAJTKS1jHHHuzL1VTjbsxOITdPaPWaYGeQPN8PFCOd4N+VlI4q32Fpe2052uveM9VnUuLoRaur9LZRK1t+JM+6lIa2Txb2YF9YKfbFSaCP+EFm17Q8oTWalGA2/KFSV+mwQ+0FumpbPEsCkbvZbV6uyPZwWuvzF8hwAWYOiykdeShYNGz6IwvYDe3WWhS0NliMQL5yBvPBBxWvaYex1viy+GV6kgFMibspPvmxoeWX5oWYKZOaLSmJLt6DfUXCj7qb07VeaYW21C9Ngu3LZ3hXiW95+wpQjhQhuAu7lrVvNoKR7EFySByP3McxjXXaoD31k8aOR5dDjaqOWUo4sFI1e9Mw3wtI7UnT/u3OpQnzMnJsXID4wgFLxRsi7A1l2cZHKZnYYFCp6nXyEXas/XppFPlZe+mmR2mecMnU4PAzEmEXBrhhVlxos1RqTMKSDQ4xpCEEEyxxghzaUCOOMNdYOqPDpiqLxo5RX0ToLyqKiynJqHX/6vIrugqEXO6hhp+BSsFZv6luVfZz21LNiSCGK+AheCQHj0H9zZgIPgQbvURgNj6BsH9aFP6hg09Yh3d2CqD9ByVZjljwJLBBA7Pha9QPKnsexamRoffryPdT0vCj9BuEXlP6GuHXQ4l5gAsiYZKyf2bLJQ35fbiD3xbhpziSIABv4JCI/Ad50R/E2CN/Ytu0GneCjWq07tD5DVQFQdAXglAeJfeRhrbFGKjxomeAeG+ibV8KmqYnYydm8D1sQjlytsujynUAnUiW3VpA8hAJfadkfoF947YYkDmAw2iS36zcp90rRboN3OD0iAt8SanxpAFWJVRybOgxaYV6gRhalkMiEvOoo1t3OoqRmB+771YfU4CaY8pPMe6k2+9X5rUOqqJkkp9oyH3wDCVc9hbPCN+KkJUPHBE3ntVeqpa/+6VoLpdanvptMgvG18L8j0xVK1gytAKmt9OmTN5wYdQXg/Ge0coAbZqsbp3FzLwYl0M8P5jH/POdLrhDTZWiGJZAVWemoViFTZuCyPVX7U8sExLI2r76+MR/gKtv8/jm8axludAsBZvlmf+wCTryShYl4lE+hlS3gdqK7Ieth+P47VJDbjYF5I5Ns8tAB6Q8oN79VqsL1vbOpemsVa5qU6nPzDpkrQH6eoZSKWyaIhO2AAQ8AzC/Owc2J9sHm26CnVAh6wGf8eB7IB74JGgGAxRgpQ3cBz8oOFxoS75nVfY2rLqADUqVIwUBldKux6V5KBy0AdsAJs1n/19S3QSGBPPDf7RGH8b+4Bv6kkbKkTQy3R+UfTVZMU0dOAqHzqY2Z4PVZ+1Y30DWavRHa6rP5uEcNVYbkaMouCPMwJtHbsbmJVUtVchRJR1/yH7RcJilIW9b6F/8OWlk5qcoyBGmWelvY3jFWT55lCTlUqNQ2AYVOw5hD0OVLPlNQ9vI05GzzxyzvUDx+FZ6ARTg8ABvRXXLbFvkdsOtLfqA5lHVsjmIz4NbMNZWdWTwr3/pGn40DZ/oBwqbGMSepudjD6aQ4xD6IMbwXWTclwW6fahX6rDA+8y4AHwYdKCr6TWehcWVsIUjb4GqT35tnodcwn48Rf8IZSsA9bZ2Van5T+9H3brfwgEPLgTDAFi7AXkFfhhJ6Rj59lys8zOfNU2ivT9ZKBQsFu7di52W7VHx/Ea4kxl8Fl8koKm9m5W5zopvdj8x5se5U6X5bWrfDnDswG6wu+R9f+7cyyhpLwtfhn176TTFHew0a2Xkj688Yz0SsVXRnqVP6irNhPV6EtWejRqzEAjT9OqvTnBV6LTp+Ic2xOsOoKGzjcx7W3oSNRx7Bn9Y72ydczo0fAbP/MS47a7fbqe2nHKocT/p2HJ+NeiWFcWSeLAqHuQkXNHcD4Nilemz4aqBNrTlubHqbRGaaNPKa+b5Jx7JGZsVBsogrO2SU0R/bYK8aZ4ee0I91qlLLU5dPM5vJP8ZH+n3ovt05n7OskE31EdeoLAcLLqOX2wu/ODAtSZRGZ8qNF+YZKlDvx709Acbrt+9CnsPPf709ANF3ZFKc53KTbl54P1V4BLf3lMFB9H9t5Tl3UNFGPDTdTd9drO0k5peNb5MZaB+LoTOe0S2qd6luL2aliflQ3cMbir9/0diZ6C6uV9nyVg4S9EH4mli24uH4aRhL3NQCs2SxV+syuQGCpZAgcu+46z6WDgTGaHRP23I3fA5eMfno+lIMDsNsGzxJKrzWb2sEG7Jg641n78BYc0qdK/O/3Zcjp61MP+jOUOgae1rYO1a2hG7bUdTkh+A+bblxqTBI5M/BjOHxNgGnqG2IVLrE4yEWocZgyK6ASkD2WpbtepRuSX8/uP2kzlyCtH0tw/kP1ByWqVUIHzJNWkRa7EQh+JVLWyivgLgDfzkOHiFQInS+IvSey1XbqwkhKUpoBp8D4vmadTyQJDpi1ZguYxXVfBALbLk4NT9fytXaBz5TxOoyRiCkKUHZtdafzT2wNZ5sBcq74QDjufxjbCx3Y1AFhImcBTukhae28yQnjMVn2Xpo2yukv/70K+qgiTscByXwoIJmPLoY450LEyAonBYHWXfXbVg5AA2uhjhB+LIu7PYnckgaPG/YfjMDTvKDyWnhXZmOHK/R12GnC6EGqHtx9TBhKXdtwYyMtB7KPMaRxmu7FyJtGE33d22o5Hbexc8cgYrRrOxRjrdHXbnutRqxPl5R6rlUQqOWgozu5Vv2PANEj62wC/iy9tY9X4IRToCJdKahtmmqJ3hpcNSKQ9KfKhVcpxlsgUzyoucVeVTzv1Mw9yCkCfp78HqbtLlpEC3YPgvLs9XRrLeU0WOJAKPq6E1FvcvjRlVYR9C4Q5JPPgUcu3tqLSDpVJHF3Rnyu9m2Wy7AV1ETXLE3ogRYwAxxrZK8RD7N10+RJXAi0ywL4S1FiWOfW5Zo0blEuuvJv0K3fwDCjjU4VDEL1cZLAr8fEE57V8uQ1LjyurstIiYfBJU81dXcVOzobPVTTwcX4f8W2mnN87Gaxrpw5Q6AFZrb5Z85Ir1MNwKypZeOAoi0vG3dBhyEg6qSORBabsf9bfWs/yJNj/LX+xonoscA70F3PrakoF+XF9g/soaaw9Z46kR8Nd3LhyHtqoM3o+Kqtqnv/wEddiq4N+wpyOcKotDUe8Fz+ZLAxZAXo8CHHnvA9/H8aNS9tMjbSLB/fTHmCbBCbd0DZ4O3BWIykuJkRW/JD4XKU4ZZQu2L6xIL5LQkU5purCJDQ8qrjC6/refzfmGBiw2DiHHDVkU62DoKIqSCJrWIa/TxEMr1FBCqiNWQHphgoxkfre3l/eQt2WKJGQt14rqrYLxQHxoYrZwO3hWnxV56kETjPJtghb9U+kmQb18a3GPAHsxC/y3rCHtEmhyTla8quTV6Lo/jmArXoN0VNy9E2Gh7aCpLo6ZkZOVVcAdgJdxYFylDBRNMb2TCerCQWAcorFL++863r5thxW5R1q/MoiH0CG/Y92woOuCVeenfwBwg4djKGI+fkOov+OhlhUbHDJ4qmrvRIA/88GQsOWzwjm/23XMO2funYI2O6lZx9wkjaPQURTnPb9vxR0/iZ2Bd5DfktrRPlE4X+jWAaJZFO6+KCU7O8uYaBff1BVdLaHRHKzD7ThzHv8oTeyk3pw6b51NeJnD7ez1zp53BzKvomMxshD1jTEyN5tJMt91MTyr/zV+1jOvR+Dzo29d/KZntmA77fjEY6YThQuEnsJqtO3isdOmgOTBTC40Euq5qn6hPyE0MsBVJv0I+3rR44NlvI6yZwsRR9evhS/HSu6NrPvjE2gZ/gYzUwtHcUgt9m729kMcr/rdA1CyoswnzcQHn8KtS/YWNmVUzqBWA+59+NCSiucolzZ1mxX7Ar8+yLVJ/hBTSgU42dCwcuDZHwTlxPnLOriJw+foPrhI4yIL2MbSYNK5Q9JyLywYqIfuZPqAk0dLPDMyMGZMtulfIXAmPvOPSPLrF8zTMZYsM+sKH3KU375O/8E6C5eHeI3LlMJDM32v5hBB82832Idf3ODuf8Pr1Sxr0DpKY+criokg4/Kpqtcr2XaZSkvd1UJV3YRbw71GzroPeScwLY89hYX9+CUYcbZXN35C4oYe7j+skxZfJccWLCkXzUz8NX2E5y6rahRZN3Xq+n01b5q9lF/XWjbkjce/yqiFwkyQudH5/Ni5ozUYz8Vcrmv/Z6p3fTR4z6i3cp+Zo4UD1JW7cqQ320ZZ6KlTDmUcQmgJshLvps/+B9N6fVM+dE6nlwe9Cl9zInzy9u0lwa2Tieke38gGVmCr6MhHSbaK4EJUiubGoyrsv19cglVLHSg8H2fpb4OWGi4slqRU9iVh6McnMV3AZrTJu+vECMDk3pIduaFIf8uQo1+8Icjq443Dx+S6q1oOsIP+WH8uFpS3KOL6e27gWAtPQ9Dpp7+gk6hSdBgmobfyTmO5RMEv8Lcxc0Bmcw2gQ0LWM0Fspwjaro9g2wPU3zT4zyvtC7d+VqcxFLimyochTbcDhSc96CCm75IWpXe7YL8A9cLen5Qpc96cjrRT23bp3Lf99x7u7UfjcyxtBMjH+vJwul6jpX8dlpPLhCGKChboKLH75t0uICXPq5OT9CIxP9uGLS81YEeWuT96Pv455+I9huh+DKZgSG0fkiY2cIWvp/6K0yYkQytXlzDg4vpAjezhXkFOzUW7MOr27BJ4spcu9A0jRrzKO7R8jc6PtWnXP1L61rcmGcyb0mvEDvYcwd96KvAI59T0CJntHjL495GrHHBtv4uPthBUvrTL0h/3owDRdhlT/XQau0JFJwvIJpEeoVXZGMMDPEjXU69LlyAPz9XZ8y+m1eAOYbJOS2M7xIju1CujwiOcXTOSNNppZkHqbQ/wl17z+N+1lR64W6q/P5GIf029LqVXefAvFqlq0v/AOb6EvRdhmuZ1N5vBcffeZm9iJwmXD8/n8RDuJ6/kaVyJKD12RvObBFiEZKPgX9rHkfLaf32UEoG/wiXh8EWJasviD4cp9oT7n5NWnKqHaUs58ld7YMPLJj3RjN9toYTlw+Vk/HuGzTSg2qLpTceMtC+kvGVmR+09tLXK7d7N02B38d9SC6/FE9PPHkH+Vq4X4Jyao46wy2PnYlo64V6JHV1cKpTWSussGccd7AkbS8q8lXCR6Z4zNriLWG3rlxrQicJTMDOWq1UjV0J+OU7M2WtS10DbaoaSPh7cwKnj/43YbVgYxitE88hQc4g+h8k+zvcTciB1jkieUaXvpbNPTC9+GFLVmgeq8Gq2U9Amuh+lV06iCOl1ChtFdZerpulEbZzRHaus+GcnOmLYGJYGJNRCEXyCOYnJKSzAQzTE1aKZ9lP06pPUqLmiSDMWUWHSCyaLL+FONrVY+eJfHjUteqFJ6lFCGBQTXP0CCANo3BZv++dkbnu8Fi8Yn8qWDEyCbaikLwaIJGpWtnhJnGLVtEorN9QdsH1t4oRY63usFePFrH/ABwuQvy8JDEij28cFA0GI0axfryHudjdUXKfx7hXvOiwMfKSDwHZy8FmSI2bpr9OWuCxW8HX8ZvNnUiLfiNzA4+VUl2uG+PoCoFcc8h+Sh4HEDt5xSDzkENruaUSdF+avJi4IOm35ZnrkT0HUWbHhNnLRTH3pgw6F/J/dW5Nx0wkbUSbj/uxg1YppXG+1pb9UQQLwjOGAB5TuoEdUOLaKEQqulVESc2azTR0y2u3mz86c6rnh5E93MGWmMCsxLEVXCradmqAySpxwWkY04YVOEIF1ao544iNu12lRvJSg/MWeuEEX+otlvqmSP2eZ34f19hVKTaTLHowKYNaNB7cBkZMc/fu0TtUm1v7n16eFKxaxxfFQd2YB76XGXSZUyZmhYV8hrpDN84lXJBBr/oe70DwDWoE6cSfzHz0sMtvwCOfQTGesFs1MgfnDDX77HaR2WHqtRlBU00iKImiin/Ws7Qh4XW5G5W6Bdk8mjXYkol7TstJhlt6gtXp17XQEvcO5vpmiqN+rO9aGdhbknPAubq4BbuSdXGiY4VSWi+/DLYHmN0kNQ0Gjwb60j0PlU59XFbqtulgNCg91tGLWZIOlQySkP+wGt3f4E8mPTYzNKhv3AIWGKd5f6ErY1Y54ygTdpuhVHGZAbdvBvkRpxestCsR/i24O59RcvDI+cXYDLubNh+2U6u1B6nGkL9ara3X94TYzW4c5rM3jHqfwMBY7X6f4B+C6dYO24VWA8aboxw02CfwNcuQG617MU/bYN/fZl6Y+S2y63DACK6jeWiWcqkcVMEeneEV/4V1AR3w3mahWaqRxrZO8AxoFPqGrAb/csdRI7Sz4c7eKOfWakvjL7UuN3IcXwNXNHqZfXtMJC1s8cL8Zb0HaOl9kUdZlsuFp7ZOOySKnEOyMnyKNJp6TFhsIe4+mb10942OW68VSscYnmIG5jTWiDlGk/hPE/EL2dxULHRNdlZTbiFAKf88hvPT8Apnn4lgN+2NvOhVfwgexzFCPJ3zSNsV6BpODKs38uYlepvccgvUzIXlV86tAHUWXG/Hue95FyItnSQ/bTP0NynYQWbXHJa96gDqOTTo9H20R28nnkOYuVmsiFNw1B8bxeo0hatu3UzOqqGbpIjVer66ETG7o3dloyupH+TtM+Hg0Ovm4bK9zr+gVjxCA5yusPbR6sq7W/2+SDPpPlKLx3jXpkR5XL0QzNH5nT9xCe+vNuCMs30/oPfVeWKoZLVKWyY2kfGySGyC7tPxPky/H/WRuinmCAQ429fMzdJQp7YlHOEnznmkEr1+yXyYzT4cuUQVJIHo25v3ODG0l2cFgt9BevVYNUeUqvex/m/AcYaSYUXDPerN5laK7K/cY1WQjD8N8IhPM1WBvKU7gGRsXPNVAkXCdvrh7H02Oej+TiRRzqaz6Ofr54kS1zqpHI4w9jpLhf25Wmz55nUNY6OKBO81oC9LW/2Je1Yrfoup0TjYin6O4P+8kaYziOXmmROIGHZaPPEVaMzC+gUuIKSGq5h2GVn8lw5N1TjakThXHB41QcLGRcgqXKDB4xSSITTChR8iEVpZpm6KGppOkmMFxLyKRaHe11SsOSOlkYj7TLsIIp0Kpzgkh6hSCWxr1e3IexxBFYDt1iYRnA7/G/cZl32FfYzmUFO9VTx2hGf6eLuQelS7mXStfzqxxfBOi802OjNuBxJYca5Iccom7Y+zyPHO1tQTbT+sd70JOFIUOZhVzAfeMcXgR6rzEqJffJlwmGHY/UFLlLNm+BPxvE+pTFCWF8hoYF2cltvelrBRtOzVh/yhhwqle1Dwu8JtHj3NofTY9ACmVaGOfgKD4zQ2iv26OrMvU+zxqFxKlsmzhsNt9mCCwAEoqHEoNUFW0nhMrqDuVbMpO/Qp157zxJXAmcmr62++U66PY2J1Urr45k5hAVkyupM+AfWaOzYRtfA9cmj4VnWa/MbJECTe81ivRta7oDs4dnw09hBwzjpMlTEGt0pBlHnlcdFf4DIFSEB2URL+xD/i/8RVwM+zbUndS+jV3/GK8eeAdZsyPJmaj53Iddo6LOnKfQ1mC7d2MYIGqhoMZ79rBv6zU80QRhFHBpW1r+dFcOKjsyz6lgy3SKSF8F+4ScnRqJDPoXGpk5q7SWHbXtnewpZoZAu33n6dn4TbXTezfjws5kBuRu92gJRqi7lktCUBnkq1XsPtHTZ1HflKxHcqT2b8ZxifcmlILC2jRdvjgLjJPK+1wN1BL8YgmYYmVK2n2UJX8XNOf9QWfUX+nJ0glP/NXXuUHK9+jT6rW/+2eXht8+6xAgWvhfkTElzRIgFG/zxh8vWgzy4++FLxM+j9Ly69zkj8VXUJTdHnWyqbumcMkGk14n6boBfsexrs7mnJGYDedLBXQpuet0k+E6ujRK8sY70uyAq8zYT7G/lOpiaa4xplXkv50V0WJYFgksb1xq06dQtIGuPwPBiCfXCJD8VG3d5PM9OX1XmJ+SvJtTpme4b4kSa+5Xa9L+PXF2ncYeOdVPmdgZLzekduTQN2b6QrwF/ptiCknIpYr2KWTEh2twZBSG7xWRgcRAaTIeNk6KRpZ6BCVDb+y3Eavt0U0HymyCRkr/Cn7RjQ0LkANJp61PHmzxJfdTEgh9XwZkH3exJDic2uFeEn8O0SbAkKOvGB+mF70sB6e23ObvvxJyuT/zeelfv+Vdho33edEh3Y8gRvuNQQ7VkVvULxT+tc0SKY+qU6BCHhcz8T+OUJItCXRstw1hn+jEHJX5YL/FldHJ+e1ReAD4cNx9gTuLO1QCuuL+pWMtr9Ay5ZcNRy/hP4vQGHLHlOhq56800RigRPxEj5/0dVczl1XzTtK2JqAZWhc8Tmy1g7vSnjpn+4T/q0/bojYd+SjipcMGq/A0AyPwz7Yf94DiT0f9XVfwtIlt+t1LL4+U/s5PcV++Q5JE/P39e6Lit4NRcpDJfL310LhErBJviTGuP8ssX/csVulOWS0hXnDCAZ3D8TceJNnlyAc8vjjqCMzlcdJMuSlV6VIX6T7Wttx7+gIRBdB1INIV+oUMXtxFQGWXq4QP17dhoQ1Bpzp9fRAaO5lCpwgcEdIfdbEjj7bqgsMSOs4zi3B8lbpOp34O089XIDAmv1zLx21tHHf5jtpQikF92jak9Qf4ECWkCuwNOPnxo5L15FwvygFZ0mIflHIa/ePsfg9RXl2m2rYFhzGQnX9tARlj1MNRmFCrnEJR8k3lZV1tjdo/BLk3WDzC430yKcTDYJ3gc4LIFLe4N4AL3uWf0cCgDtQ+F2S59VSN5QXAjIoP9QbQLm7yKZtVQHuauHcxvMy6EL4XImCGHLchlUww2RboxjzGi0Kd7nfmX0DhmcKFbmFeQoNEujSVwp5X4tiETD7kBR3QWZ8EIBnbsEcS8903d9C58lq1aDEKRt0B9VaosmRL6XxQAF07L6A8lHhP0mX6uk2CGmf6AWNGawpgS50/VlO+UTUf7y6ew0xXu79JtU/oxNYpJvgOD/jKDwmtn8HPgIMncTrI5GRWeQzHIDYU6HoS5TiwwXepGMWEKR7ysRVYZX/3VT+pss9+tybFk9hABNuI/3Gbz4mXZ/7as/Qp61m4gbN5un/i78Bkb167T0H8hTGLVmAw9abAw9Pxowj6EH+atgJ4OQWFKvxIYk/S0aw8TYm+2z9/khsdMe7JgfShJJBJTf0kZysH6DkNzKpFL3dfCYdy3zRLtj3C50VECdxl+SVKHgZsYvzXUBf7Apxa6fnu+rYZ/uR8puQeeZM3j0l8eP+exLcyVTLZmt6Rc9ZfTdG82vGa9MKV452NvFlRcPX0EMAfRDfFANFyFLZDoGxRTCzJRF3P/Xj0eiUPn+t452i4NDUWF05eiQ/kYCfI8aTiDNh7p81Yemf7fVE0plY9AkK9qquRxlzpv2326IKd37Pcmrs1PfgEwDq5A3BoY3giD0CGAV786SudvROeGk+dW9YjF2GHDPY3FPB1niEJCwF6Ros0UUp3QoogXmeiEfbO7QT8sxA+NOyxNGHEHM0BD5HSg/1d7NfjmjsQesd9fjrQMBSDTQYHSgW5LL/8V/gx5dNS6l5ZXvQkQwZOgx3USwugHa2DaNxZfhKArp7pt7o/XSDfxfLYu/g2TqgF5BtHt/20OvwF1Lqs5+Z06LQgGVnPe99Cn8lZbPV2B95CF8AVTPSbQJ7mumH4pI8QWM62ZY4QDOH1Mr6soe3oo0oIXHL96HZnvcRDCw8ZMoHL23Sa+6Bb7vv8U/bl7H0OFN5kF3xb5lKfRaX/HeY2jOJC4y3pnc1M6WKFOXXZmL7kjuewqfAWd0k7X6999St3DtVA4amr/YXGaiKseLblPaR+iQrych/UtKRmw2zx4YiFWIkOlvfz2TflqB0wysoUGEEoyIO0xPZyWeaxjT2S5z2ONLcYvf/Q9wgqTCgJJPUJyI98C3L4f8mdkS2nTjeMWghKuGd5HjkV4W6iPOE1ur65p2v0CsAEu5DcZLAdvx1Ss3bJukIOlxeL2WRzJIMYUnrK/ehYzkeSTRnEGMeqniASZmA6Ym+1Q+bZ1YUV7ZrMYPcajB3ILByF/KSqQdJQXwRecs6zLV2fsuTbB881VQm01YMFGljHXPt7S4HWm+qxfdQ3EUfNxdF03aKI3KtmTIdEvjlno1pTsTlmYnDe45trfrwibrGDbgnUK0G7iIHDUuj0SBLch6ySiXgvFS/hL0WqxVMxZuSMoXM93KWMXJht6hzTS1jAiTAYKQ+cnMG2XFwxhymt7ijr5HTFi5a99jkuLpOvWy45XtUO2SR8wmBUY5KT9VD9M47M4LT+oGDgV2/XW/oet4WrDzkV51jBIOJVnBzIbcNPJlCcFC2A7cQFJp/CvlRrlGjgN5gu6WBLdtQx0UzoAT7eLOceylMqlv00/rE6ShpxuClITP1Mpe0Y0C7sf/s5ythwEA/rjr8N78dr0imTWudL4W1og+jhZiYaSGuFIbL27RQ29pVSaXaUpkUApN90SSfHCmjVBdJ7fS7KtwMXPCry7Gqlbgr/1N3QUSfRH8r6wJ9mt2KpYNPNCRaPn6dEIkFbv/WGv+ret4zLcbHbANOlgs3CSSxHpmNZeigtgN8CjOYVQlIpIiiH6IqE5gUbpRmoK0RtXax0SrumeoslBjUMGeRCXOYzJH86FKC2CWTeBi7LlXH8TQTgiOIWVMA29s4JjtfFqyX8WW7pzjkina5Qo5YzRgpIDDYYlfQBZEKwEVmQNTxm88PyRUbPMgOAadcxpU5uQYucOXcGcF6MDyitaBHrHMhG0qvxpKNCNTRLBJKDiz1mH2vI6rjx0jMRrZ1kyDfQBru9QpQt90bO6ZC/yf6H4WN8N8KzfJukNv96ZrVlmcg3Bo6KjXZfp1gf/cGh0FwdixSg6kriypy80pwnNyEO9mHDE70k8io0BOra+9R3ugRGrpmv9eziHX8ohJPSxI95C/rgDZN302IE0U7cYhKThoq1LIzHUA7BImJponl1zlr9euBZXOMtIatpTe2DcjJpVP+1xz0qXoWa2F9o+lorCanuERi+PG+w8znMWW/FAd13wcy2uJXBmGPHezJh9bFlWwEmycIgexKhBrWqxNthQZqbGBLe4E3SyxVq6y7KytY0Ju2bot0VqQ3urhcV1sgMH8HWhqIH6auU3jW75+NHw0dwSfO35zXS5HT/nsixGDq/2eI06OoDFC7dFodzFDNRRI8yYrVHnN3Mj66qnVDSTbYdnfvtjsPFGD0bOMB9cIFaOjt1h5eTcYiIrCARdgOXiu0toJb2IAkIvJ3K9I5Nw5QDoCgCXXpEuUdITBYxbMgs8hi3Ky4WMouY84dRoGcZNPbz1VPfKMEpMP3H1UqtI1d1GrLOZHFrqPEdegsv0U8P31F45CAUFxyUkrT2D7NnoXLLsyt1OnCeLzMkVscQtxGrF9ZthcMuX2cHJvsZWGAq08Lc/TXsH97CciMaTOnkaxQDHs7HE/UH0gQbpigKJmfGf7jdB1pXrMzTPrOUE+C/fWgjP6IKzfuir98BSfcZS087gyeSTU7VM0n++QjO13cH5lVv3Zmu96Zq6elpxc2TWvszEl5plo4mAuxTCOVun2a5xNkna4x71CC8dYl2YfBgTWd1cw8UXf9MESl3dFh1z3feqPgM7yPPb8wLBg8GjOd/0/LobAJLBma85d5sqfJ28cU9DYnzPpNQ8Wi1x2vhAARXA3KwYJYxpF32qnXnI4Vaxj0k23/b/kjKmfSL29FgTMPgwL013tbfK8gCUJOMZCGoNk1N7rfgvineggbrBMOjvXSVR/ogl0AB/ZlEwdgriYCEW0CEmFwVp7AX9e17Tp4YxArYcAo9CQYY0imGQDkK9G0WdDbPHXBu7yco/xMg1yzSkbjA9+LDmBJp7gRfSX7OlJL/2mn7P9rp/IcVK6T3on3k2diRXoG/YmWzzvFENmpLTwIZE7EymJLM3MUqVfluwyl+6tvTBYEcv9Ns6MXSOSpZY16+ff/17KUaufoGNwKBGMetIEW1DJ4ve9M28DTf7iz+Smv2q71jp5gFx9/cSXmzpHHlM23SOqh3w0RXqk9SboD6fsS8C1iLMjmpy1p8Fl5Vvo/l99XDupM6hsdn7y/CYLHkOJPk7nmgjD2b35Lmm4gztjSO60M9DWyu91RJXnSNpIixiHS4vvoQbMKWAVS7FVpJ9AQM5jBlKBdoUhRmrPA0J/SROwOOXGlQQUqIgUpiWx3injwDcfsm50DvUAC+7g4GqLH0cFBKMGmz2loHukMUGE5lC16K5r/uMrsBkeoOug2M1uBnmcjQCdNjdU9SyFdIpmnQGAdR2GUX1wDBEzYJFbj7Jcnn+f5yIiMeqjJwLIW08U6rOvV1os7KB9F68lOd0+La8QvWMv1XvQaku2vkGJwrPzURGuFYwJR7ffe+P+4Qy1OQNucbOtAhQ9HZZLcdSeiyG/DuDXWiLeo8rE970RACgfzRQzVs0qZkxRjwh8nZnX8yApfSZbUxwqGYscNKeV2wJpG3167F7iJ4tM8OdSVU7eO5OhY/6RHVUr6mRCgmtuxm/aan1ScAa+Hvf6SxT9UBLnIl2YcFAQLH8Wo0APi40m676AtwRhl+JLDN7thNTIZCpAWEiGnYYdwJsa5k3bCrZPE2AGm0SNoYeIXH1bD/vHyRJGMfnA57Ew0/a/EYCsbFDIXwY9JkuFPFa6u+Tpq4pok/70hye4Eco9i00gZ6aol3R/K4PY6jpNUn+G6IQPbIoGCG8nmT42JqE1sc4pdOylV+UCmELHIN+SS8ngC91ptV4IV6lp1tJ1BOqzTHLK0bYvij1WwkcGg8VjUO7cIpfyAU1R9accYxr9qu5J5f7e1cdxqUdnaaZ/XAAognTS1fFp2W9k1ghQtQrIKImQt3STYBHZXF0T86YFaBzM852afu34LAVVI25AGvcJ2odkhcmSWCDuFZq/IezolEZirJXhKWZr2h0/u7EfNpKPnWYwvrrQjKKEN3PYU117wtUWDcTZqqt4w0VsQQ9mhoRn8c+r5/4hGo/1iw4rRxKjF1VOzzX9aALHLe7kEmxcseUinM4b9b6RQ6pKd35iYCG7XQqMb8NjaMpIZcb4RjPlWp7pYaZKLarkkL0NQdJP/j1BMmXWKXJIFYovE0cVFOxtXiveoxLBa+Jot66dbtxdEFOjV6ZyyWX51bUlVaWcxQwhVvmUnGLFrgn9zC407WNpUklvavqClQejeMWRsQkvMpaWwVoeTxTZ5o2mWRlo2uTscyiCZiMaY86x9EWA/gkz4C1ybvs6j36YkoPwU4Rn3HBbpxGIpO3z2AXjDc+19snk9fCKQnkdCtIRzX+rnBQtOwJlsxQxenVvhCv8YKwLHwisYY7T4iNxDw7S8ajykTp2fctDf2VYJ4ifi746th+IWdbG2LzLUFYLQT2hpSsYoK3VB+U/Ixi0uMApTkBKKoO3OkEahUPii5yHjdDaC0DVI1Zv0hcB3keIUAXMMaW94vBAKGVB+MTh4vdDLqWf0/jlBMg0NxILUYKznzhRB/6EisnD5HbhzGFjozKTYTXyC5ola6cUWCnANpMjCcD9CSoBeDgXxCLaR9zHvKEZ0hnR31EJraA8XpLlL0zlfwXTGbCZYWMg6dASeEdU9gi+BHX8QnkyOGoIvUdQ40480Hyv3BSCCQufyp6BXvB+izYwxlvijgUbAXsw9BOl4K/KQq2DXegvsCqy/uNVJl/KeehgQeDVztBuAhdAIM3fWw5ZZZS5RssKnepMkoqoJ0+YnZjC6xgfYZA/BUyn3YZZY9rxXFO3wcfUqEHW9gpEN9P1xuQjJdUDbygtQ6WQYfIV2XM6eJu4JHBp8P/kysM0ehCenhUnUat7SxiNRYWK4h8zXYWDMXYbi349okoGPEBu3uIH//eSIxwry65GRy6hLLClr6gBH1Ae+RmJLN9YfueVvBf6oc0uQdSqKOHJ7SQPe98T3xmwhHXzygvvFm7dm1nEHTD3Gxe2JSveTuK//L+gRMJEuQbeGr9+yHtotkKyqXyBdZdd/P9kURUzISkidzd3sBz9E9eItnbskYiWx4sJUS/JF/qfo3WI/zlusmAZIsQ2yP+WJ7iP3U/YT7hpQHsjsNjrlx+BvcF9JMIu/BoQZHvocOeh5XYG6mmfBLnpulx/o9DrfXA1HM9db49OetDfRzVsyIji5DXGN/NZgc9WhwxwtnBZ/Y6LprJZNsD0YMUT9dh+yFvaRsO1DaUeAcF5ooii+z/DU0h7PIDLMNNNM8imWRlfw43na0B2jonN9d3/LnSL/TmcUObdPzEZjRjm4I7gmn0NGic07AcjVr3W7xqkJpfDkom54aiMNqMxWx1oiPCruDQbJmz5bussC2J/BIdcggk7lpy5N3+BVCZ8/Pd5fflwvT7jiyL2Lr3rU/6xeppz86PdnpmA+6GwwM/etCqDDek4pTEmOl576OPx7muM7tJODXxN5Oz8ISYJU9Whrf2lFr+c58OMXf23QngiktyIK7PWvBuVWya2Im0pZJCE6FcWR+Wn/LJfNHrVJhXTZLVHpA39ZPImdlm96MsZoRhoz2TsIt1CgQfNBbPkT1vCcm/pLjmM6k9nnuIKnQi2Wm4EWk8LD+DaMDajijhN+B0Om8Ka9V/CG5fq8y5R6TegW8JjzyfpOoGfB3iFQRYhfkOpPhNcCBOs1JcvH3crfkMWHeZyzPxFT/lfaCcFXL32qqY6czbIR/f/elbEIkh4kZKfaggHqS2qbtCc4mxo9qW1AZOcVyPpfB8Qx40dZmGuIJ8WYPxvpcau3E15HoQZPXJ9cvdsE9kl84HMX+FnxEX6CIiBcCT5JHDjdN9LH8iPO9Sk6+z58MX6uRvrlpyV5kDRmTGzzqtzpqg6q7cTQuiCpgtUqEbKEEvWG/ovddxtgQVEQWyqvXPprrMBr+R6HqlgYm/aqh3N0kyOyDq3KE0RXvHQ9LD0jIpglYmGWhFUlZW5QIb5GMuabO64ccNUV13M0jZajQ8I9qA7pfWSHps7BZ008kOW5PezOc0VxDfUo8v2rc+qIwe8CrYSAxZKWMuUHP6T9ibzknj802sN54Qx6AtSBsYVxG8OIACikC8/ng/pvtcodDuYnYYfTH/nDZUAObJ584ryZ/2uD3W5GpQ5uxf5bkIVjW/UPZVDqDsXtBvS/Ks8XtrwHEvgl1TkW5bEUUVlDef3y4MazgUAdnJoatdENCZR/FZ8IDDwbrpXfwvV7Eoq+Ofty6tbmp3sObF0IrgPy9NpejQEX26fWXbjHwCc3W6Kbmbvj6CevWO5e8UXtxUxA16UVenBINwi3UeC9viGcJ0Lxngj+mSkxgr+VvQNK5lcvWn0+wf9Oa7Wn8QfsUQOGUAhuI/UBErMiasYzy0Wu88bMR640exiWN/NpiQreQ5nN9VhzR5/4mb/+lvbas/KS3F8AObJ5Bvv5gLDLe1tc9V+NggPPX4UCEqV+Bj8gT9IItpTfhevX909jgeRpn78G20e9y++3T8T5XKnEr20XNsEsaBK2fN8dY3wh069cpjFsqtgv1bhEquCFcPqTfu4XqgAp8pToV4dP5oZf3tDiolu1GvJ1McuWPsf7FzEBXhxQf83dLPmwzSrVHTYjppFMMRS0gttXG48J955kR5Huqda717o5RSooqf57jka+07S6up2hpiqYdwy0yJv1ftMBT78vx/R7iU8dL/oYf37PPonHZCBxN7vZ8JcZhS9jhfp8xYz0dB3zUoxVmSp2iQsufQFpA3SaU5E94pO35iHf3bNxAvp3ExLof6GUeH4xvlUWqrKDXcmOhskaC0uVHqm3QaqSoqhO85p/RlJlqoW1+0D1dmIKiY3PvJyChwVk6lPDFxZlv9Gltvd7xCqa/GaamChKyDoS6krT9CeV1BvCaBYj4gKb5rTvONDGPWzUFKv8YihML6WBFsYQg6uLDhXDKSyzfxb9MSQhTk+worPCeo0Btrvwwgwb6ABEyniB7bMmjpTyh337XGWFi8YSfxUxjSszQ382l8TVhdbQtWM5KKYowO1elNuKA4t6iAyhG1vGH1rsIHtMkGVuuaSSCX0V2cCUBo4He4il3YRZsMUAhpaJbWo3QOf9kUjhoQNBKvCvZkQPu6lcONDkLjFenzCBrB7GKR3UjfjXIKO0/n97f0sh6BsXcoWgs1X0lBXjwtF+79+hSXngfw2/EWDqL/vLokRA4+F/27D6a6/r7uMgfJjKXJFezSoTY8llwV0RB7SxAdxcti3L3Tn3zkOoaNX2A0J5InXilLciZ3fnpvl9cU9e3udqcAxaqXj0wki998TdWh+9ZDnSzD5BrM044WW6UdNtg1+fgeYe9bSZ5XVEX4stfou8gRibjEx/67LIbX3SJ67nZYpkVeBqL1uH/Kj9HlDAl3oW3XUQbt1e3yu8cUDgkNQAhtqkVy6t4MquRAYrpDSufNSrKwWcHCR9LmlJ2l5zGDwVMlyyigPqZXTJfLqKMGRSj/+H1wrotisoUKn6fGg2+ZttAMrfg+xOCPalqQ4bwSFZ8Ae//F3qcLyzy5qwLl1BDSfGIgqwT19oeTf7Tez7a99kTPrzGxhJfLq0RLF5orb4D2qCtTX/0vM6pYgXpKZNaTgFrEfSXAQUO6eEd5U6eokxVRwYuE/kZ2nUSsqZuWKBrUG5GCkdT/eIyK8F2kltyDp3FJ79tw7c3nw9HLQvi+Ywznup4vupccmcP5xP12x9rm+NEg8b0qcTAq15DaxgpBfVIWyer04pYo+6inI9P8tftqsMnwlqgGT7pPBfRX54z4OJeaqJewMTtIsTE1waLv2DLLqCi+J1usUoFTPnkZhzA2ZcNW/zX5eDIJHbnpz+CnkiZUPk/749prVN/b1hUyDpXkWie6LwWFiT184VJ1OlRnbXR0VVEStjXeEuwzfCOBDGYHNmm+uJoQGsxghoqvIaGEFPAM6h/KdOXsjpd60oLoIbTWez8yFuZO9uULgCBEAK6wVNa95WPXFmodPwlo2Kj1ZrySsqkr3zG1efgFBTpaEl8YH/dBkoFP8eDSDxgQLInQkJkb7KwyzwsEI+BaDXNZc5y04yCbKZMxdMlv9jraerEcUMtvVqlWCQUiOORAcpaBG/zRux0+9JMfDy2lHRRqI/tvKDoopHt5hbijb9nzhjquwYNfYgHPL2BhM7N5h5xjwZPazCfl62adM8hgKPlgav3xMT/8RSUqi5/eHizA1a8u9bDAtKuOykXmzgF0CvdYIre67Y09mkNwCEpqpQV147X7irF8mB9s1nKPDoDiLEJf7dRrjcEWGLSvG6/FKW0aomWLz/bwLM5jC1jPGTIKuQauq5rticIKMkQqfS83sY8gEp3bpxkKb8KzrJSmpP9rokV4zGwe/aJ/wmXVe+lZTeVqqnIwzus3SGPc+aELzbcV9tU0deafeUb/jaajKl8S1gwF/4S7MZBMQbFUbYIwlC3TyrOs/DCk9pjCtNNOHXVJE7N+bsw/5XG8JmrwNoIRcW5aYGYxktU/fl3UZ1D03lwo0U11zDDKoH03NTI7CpUATnyjFmtzor/WMRcR8VxHxcs9KoGc4BQ4sk+lxjZBcWP73D3ZuyCZzvyD231/ffW+9+nbdgl0/vos6eMPJM+jJ6dHJ3Z5IdaN8aHWUdPXHI3+SJcK6tzMGOc4XZAn2qgZ00/v7oR3mwVOOtlb7qpT55XgNXtJGI5v8nK/+D7OVq/LOzJsH9uoO9ZrBV56uavssPjAL7Z4+VJ00cCr9baqLpGznqOX6l0gOeDYkIzi4gNf4+R5khPRBueZqZpURi1zDHa8SZkBdW0WvrumVcqx8JAOl3uaHidjVyd6eMda//WD1Mk/hpjHj2Q9HctTxNfd5WluL2ctSyjeka2ldUaOiRSPzevzp+w35ZFPHBV1Cdo25tmuRzD7gqWKpkA0XDdlG55o3vnpTH1+VXrgKedx1A0ip3znLKUkMXeJxlAjtvKyu9X0KSbOyjon1FMQJmb/Bo+mrHwduiK9Zl1DaXOJfIQZY8HLl5j0K3sQrcMWj78uIZLw1cj0hfcmc2c2sVmTpSp2y/4PRTOK+zmGU/ZUe3hU3wloARDR6Y0DpgG7/g0c8/KrNW2Sc6ZL5jmX4KVDpceomcIiHH3vq0iObpNULD7pbs7An25TPwMdhw7ZbsRZpU4VEJShcybg6U/P2zVjv1OGOlJxPrRWf7tmwnH18EHlfSrW4VqHQ+eBuF8ReXoviDxwXuxvJUmpq8521w4ssmZXEAQrqgzVLPLnwPFG9Ye9EwdGfRNtQQuRoN9PNM7LKO+UaG0zV1anR2y+itjuTGv1DRXet2jz7bLMYAdYGron268oSf7Zmvf9h6PjcKDfQVaS7+ED+feirI+sJQ5lGSl3nMOfMES9fGwHVqE8rnCt+8xV3t0aeUO373EryQK6JkU8X1VZmMgqx8e4bLHlbeC4lEpqX+lmu3Be1T+SZp+UaF6WGR2WnavdEMp2jVXbKDtyJ7jfroJgOj0ifjzOnXA4I/R0+jeIWasgX/nLLgM1c/v60AnRBBP3n69FPRJ3MuZf+xE8ZtTYkxlXD6Go9IEw/bZb5CATPg/1rcs5uHsXZ6XCYR2dmyE7VEoPkbyQW8jMPJR83upOfc+molfg5tKSnW0e+VH9QQ5twBjx14Bp8BE4eLHrGm6RAsYIn7wIfIOG4Wx9LxdH6V9ydsuGhclPWvxT5/YC6dBYN4JjDxEvAV2swzgIHnWh+XW/GqVW5FroE+/jMIaL9+nya6myY40Rd5CwNcBTD4e1zAdfdYsNWM5M5373GCr0byLS/NRtJarwKhtnF+8dJPvWu3Sv7kQ3zVH36kSBi9ojk9PHhQkB/B3dRFsd/s64gE9IeKcC+dsu5A+r443EPqi7N5KcuyPkuem5oY+NBtPLf1y/c35IBpSCVPRH0yRkZkY0b0c6g/Jlf18SJlfYJIoo8buWWx16r84mb0SM/bYVvRE+UBHX6J1G70yeaMhkbZGuAktb3UYll2LJQYn3M+qxu8neGT4VVEXu2jQMRKKs2Kq1pUPqvSSqxVunOkulm1XNmsxMvKpP56W/EysYI5M3d9aiFKwu6YgONf1M7J5VHwHrLK3tx54KkLLtIbdieuzJ7erP/BRbXkdAfXE/NJ1OTgPbEGdWfewN4VV1XhbbesEbrmQKmU/C0kQ/YB1Za1SeiLiO+Yo1IkadhejexlV8YWL/UGL1Hw9Zi8bTehjXy/XnCMiBMoL9nSw50magFPn9mJCWo+niFkGNUoje0t1R2ckbP8IBNrKwpzUw6dahILdy3odb+seuJe2Y02G2gt98kprc2D2W3DRWs19I9H3CE/SfCEjQTBsTsUicXpuaPP2xJ6Nl/Npbhq24VNrS33LGCFUgP8OU2PR27QI/pJFaUjnZSXnaYkP1maYko2RZQEiJ50qag1oXS4mKp51D9W41I1tp4N9D332AIL1WE+3mSE9b/P7TV87cktBZm38hCOFCxhI2kwmvaVYXdobfUZDbdjbsbuG/OtJF8F1UmttHBYYGB1sk56MOmA7fANCAPfCQHWZaEpODdDmALWTQFnl8dW0BJTzlgyEI7dGDpitYvoNIze5HG/FPI2n5XFWCKWiO4NbKA1BAPy5j0ED8hYbaODqGPpGpgk4TAwmYT5oQvk5EhljJwbZ/oPH0reecd496oDHepqxUF88WD2dsmOMy84ja7/K70lleI1fzclrputzP/upLbBUVCBkMj+aiMjJ5+R14A9Dv+7vbemFbN+p7YC2me10+cXYG2csmi0jiI/jrDR04nPWCu6nnDQ5JH+kqS8kkS8J9y0NCmvNJEjYpnJYDPdXCCrMmz3Nzp192LVMBdskec8ciX3ZWoJit7acAcugi1umKJUfDwbfPMMfXbVFdKjCVNgeuZmWAte5izlQWSUgczMF7May85LUuRdmmGrpUBqFIM4XL3MMD28zDiNBIh02m+SfAnv177D0ffWZUbmfzHbs0KpLw9IKDuJzvcFa/wI/i+0aJ7jA4GIeh9Ixp+i4Fgm1pRJZBBsJqa9SynoWAYbDl6qymOdBZrxyCAD5bZMXklmwXT1eKcVWIxsEQOBgf4EiqK1n44jV284lomAaH6NEAqrA1ydv0Yn0G3Ms9X4qzUCbQi9M3wEgNv8Wpmi5xyxKHOGIawOQUg9SAY5gNMDQbVB3Vnd0+4agwbhG+H8YLabB3jTGWcBOa8ME5jrc5PCUI67ioVe2rKej5jSRdxeJyHdo7VEciSA340DGp0mVqnT6RCEeAOK5Ju7BECgof+FYqJ1Lp2NbBuDUORVpa56fkipDpWGsmJGXx8XVhKqF3oM/aUFeMZ4FcUn5P94FPUcSsQzolhQ4WNkR7N2hh29J0/hVqKUlhxDQ/dLj664DRdniMe/wfUM/4P9fwF+Z7PKuj65wBhCm6oTltxqg+32OdYccwWcQ7nvglXbNrMmSf6q9xWLzjCJs+QK1libhUy4TAJSHc3P0RxZ6k6WjBxzJ/Ome+hjJPd3nU8ZNKZzTSwaz5nLjVWgBtC6cg5JbrGBtivVxGrBcrp6rWStGteNyytVZcIydzMaytgygMj7SlG8FJ2vZCLAiOVbGWaUYOTnFGI+0B5D/pqoUoJD5b0xyCDCokgNoxmJGDF8CyNpLa1u4IakGF5R7Sck5TGjV8WbsvxVzM4NvVKtEHerL6yitXJDxa1s63W2Slkdc8YsFzfIzhswKG9k6cVsv5JfEohsr8ccWNiuKgTSW64LSA64XlqiSw9rBJwaA9fPRjtuO9x6lxsqQxvDNri5Pi8zdyO5e3onkaQNmUksmyukOLnXNGl5q1SOq5aqrv0TvAvvp5nNoDFSZbre1Ip8Eg9Przr/hcOsbL63z6dAL36t75jH2EdauZ7llXEN9M+4xTgXbRM1kuq4HSkwWKeqApUNtMnCA191cyERebNNQFkwhOuVoJSDnApfbW455ods32z5m/ObOjjUZaDwf5bQfLNGDOCpGKsiVEUyS4+KuR6yqqu+f9NDwE+QdEXagBKQDGrBYJIR3f86Ll3E+5PRpKshLs1RloZyUu9NoS2x6AqnxIED7LjP1zrMAVnSGVMQELf3Lfl8nscAIBXowaMjlOmpSPFeZ5m3X3SejSyJXxUXIuvy7g4LDy3CJkHLE4K/5BJK9x0p92FDsPE+5S6p3DwBuq+4BmLaukJwJkx9/dqF5Lbgb9X/tnx4b8MpusZ2YULX+HNCfSnegzCb3zZJVniboDMn3rT/3GzkLB0vdFs8I9yXZe3EbKZrVpRLzMFmCZb0dbNt3lnMr9Sa077GOBC4pMFuDU7H38KPpmr55LeE9fHhyqOzVtyU6BLgeegktfUAX8dbj2cPCH8p3N4Le3LWy1eR30O1/WeU+8Hh99n577Rp3BZP4zC7pMZQuoi8KAwN19vv74rxb0UmWhYx9ZwtcdN8YPPnjyaWue3Lyv/6euSo9foD/eUSxcQbvfdWyZbefjhOJ0wWTVsnY5r2FP4U2laUUxV9rMgT6kFabqZCXZHvJTiTwOZHPxtl9tOynSX+cvojQhB6nkDjGLePUC7gA1tAZJb6IuUvJrpu6ab/NUfdZ7I6bYlIxjbR+7TY27sl1xuDeryNiTcAgUQU7ETWCe8cObhjD7qAJc5gzx/bxaIt7t5DDfZtWP9SSIbNdtgnAGFKAUZX3ZuIcFiI3kQj1fvVAxpadIjJbqJP99dnSVeogViDXaSVZKc0pKtJD8l/AwNfGtBZwaqG6mZw6uIQz4ZFpIfgX22MRf7sELITGvJIrtWxLOJpmAooDnWtiwDY11yzL7t76qflpiFooTWWkuvASrb4h/GSbHLlQ3wlb9q/FXYBSCtFtwXnWckT7kkGD8qzHkO9GNjxJ3toMtRadTkr0VNrhQ/kf6gK3Bmi0yD87mbQ9xabgWufw6kAXDZ/OUfx88pKPRVqrmMdJOKroslw3e0Q5SXhlWp/9fJC5wuSDS4w3/r3nHLppY1j1IWsMvUIE50NrcpSI8pbyuG7URoifQZvo3YE+tgtdRY0RJ3WXd2fsn5F7POLVfS27KvS+Kf6CBtsFdlz6uxH36f9NNRCcsA+f7gX//8TbyWWOKI+qtqD9miOogzfyYwc5sfR4CzfwuhO0YqjY6XYPSbzA+6skWz65QY12ZGw830M1+3bL861h+mqHPu6RQVISeey0hHHB6d4uYcUNC4vdADkcQQdt1MlKi3Wmg04kvfXF7fDhfN+fd3fcx9x3nsCI5w0mrXDhp5d4jlqHC1CluKDouVmhLpENXy5k+CCcK/M5CrPfpsESYX+NN3Ajcmkpr39NvAO3NY8BKsEzVCzprwUYGZgZDX+PEVL8nMeQdpEDz4kM+H54u7MR91gHJAegGRfKv0/WdxDkVmE74qgR8TzzQPSrSdvO9hveI1JqyhVfvXfI3duykBbcc9Bkb/ohBmmyQqNNSsvChw2Shr1KSa2y2a91RVej2QPNARm7ihvaBrtH88T8H8Ip6IlfXkx0/MaOyKLqTZXnhNkA9Ks6CuyWTDWj5EqKH0wOK3QpdLpd89lqWVRBSjm6tH7fY6Bpsedp0MMIlTaRzFme905PSeh+E31CxKNgNjly+aRP/+9YZRWUXGuUhPOg/aJ5UFZ/6Hh2w8zVmLULb7nu2KD2ehsNoaCSRgymRRI0Rqi62hyF1nU+rfPhZHO/0Ps6SXuHEzE0Mq856DECfmugGiiLOK7hl8h7ddm4wopLkJiAYUvyYjfEr6Q0OumKY8NO3xvC2vwCqAU5ilKPCONU5R+v904iq9vjZL6GgVzGY7LW6U4sXOh5qz2gPG5XTlXdsE214BQmVNkmMl8T4Pv5ntonKZKoxpm/wtVT1Q9JK8LFjcq/S8c56L6Hh+NSfJZOSSu+ZAB2MvmPNNYkAydYwn1LNJZjb0ZO0ovpNOXUjNUOZbhelyOq3EJRqFor+fsWSSRrSf4Iu9R4r2Du03OdrIAFtiuHVubvxDFFyOcrLxY16zVdss/bWHDb70dfgtCGU27fVvSdShYV3hWEG2sXqsQ/YENTtgyx11OfOjpeOegd1gNY/nESo9CpUDBlGlZdbC2qUCC9xQ+gReamhfIxK+J9x6ZXM0ZnHifWfj4pfLTpmv2+/7hP7jmq6PTwLH/V41viX5ZZqoSQpfByKg40i5NLjXYj4oLttp5+65IvKrw4f9y/azbper57xty77oTse09pdTTEFHKM7eJJA+BS6CR1twOhv4OE+3mu3nIWL1+NyDWEuqGTLh2hFlomZK4WC7aIpwq3ReAc+cGWpixFmYML4ZvYWGWlYUwBXub+2ZQ/myuLvempFLE2g/EffGrLLwCfO1v8SGFX4xTJ+vab8+db2D4YhyZH8HaBhm43UErZPJ8AhSXQwP8//+UDDNK7q3khIcQ8qmAHxTNrr5UUy0Vs1n35PUW4GzggEr235qNPS0cSz7DHTfzbhW/1j8embNGSqFkEz3HxucVW+p/MrYjstuRC+vDZlxznnuPGs4L5zvY9q8VlIpYsvcEOr1vHN7vAFx8NvATNLThADwLNgl0Vmn7UmWGZfkdRf+HrzB5UX8P3eH/dVAeBEC13VKJcRhS61HlIIAm+8H9uUiG+IYQcRwVO0QK86IwmgBpP4nG0FONrvorq1hITJHhQYgHl584mkuFQFVpbuKujmgv8C4kq6slexE3TeTtMBKj3U7sSqBcRqbto2TUgXOslciN45Y2Q6U6P26ZhXMPCTmAYy4Zqcy3fTt+0ZKZAoLeprl974AQ4I3bgXklBiDWRyKzYCDh/ldPQslMpvoroLwDfB7oaS+xJtcTQz920YO+nXgHplk0S6tZWsjkfmYq29gOXkMCEpVs7RAkDb67/IT/V35Sl3A6/ud42BaYBDIVmLwNPB7M00F3WOvZhvlaphKUzez8+aSgRJGc7xtDRA35yGwQIncRlwAIlpIp+SgZlY2RMem0wxQBUStxSxGUMKY4MYMMNlf1wGhXeR8Z66joQt6P7h8a7w4U7Xnkg7VrSAadz0j+veovyGPwCP9eG0SHTPhXTyb/CKNfuP0rqaCzXwAFgxAPwEA/4u9snEO6o+HZxFfTNkUCqa4R4kCF4JfYOjjqL68Fox3a1yPqX+qJo9E+vUgYbRRKhHsjLVpzV4NIV8G3GBazQsqRWbyfza3emp0Hr2H7UK8JWf2DI1znr35na1fWTcxy3IZud69OD7SZJACEQYiXEdkIYgEkDEMKHN010AM9RmgcgTRouhMX+Yjvy0d8gGfHtgr674in2HtOq6VUc2M4ZsEsBxW5+ok5T8RHcgS+GoGOrIsihiNES57ADnYe5E0HBzeK5/fjFnRdSI8XLSlMPx29XEoJXdAIvme6vPp47lu7eKv/Jisw5vsCufceegFArGg/OQLtYvZuwvdCQZ6qo+Fo+mAz7M0Sphssb08Xzna5/KNS1MeJ4IgBDFEc5fiwYmQjELPZNJOKxpVC64G+y4Rs1TXsFKQsmGUE0myTh88O1rO57I1+5hwRzOFyNg4aLjPOfAygVpeSkmYuygUAt8c4mNMuNhYOwYjkhCfmdqFmaOXV1BCDHuiXkxmtxpbz1oune8KfZ+Ma7gIR1qXKiPWsUl/zdPk/m956mf71GKn6ZlHW0zL0B05br3Z1TuhwPnj16KDku9v+scJeO6PxYEDM05YdW6wXTDUjOsovPC6qspRKw0BNc1DMCCEkC2mbuXuqxkUbF3Pvq9LGc6b0kW+XqIeo9zURd2y8Elr2brg6PFDNUyAdJhgZg14FphhG+YBcZaLX1cFrELi6u4FzVxwTZ3+DbQeadpKQQGKUajW1CEr9H6NY3c0vrxa/h6JD2YABSHsmJKyeRYS0mUWLUjbbZpu5oHhAKZF8gTc1EXodRMJQ8Bm8bO6wE8QwLO/XT+ANCU56Z1RQkyLkAWje5tAAFH75wKNIahNURuJiCTYCVTeOWiibEunnKUQeESLxkiOOIMJe4QCbUqeAsW/E8mRFYpWN/N278whb+Bs2pL7a0JT0i20HYAGJOIZ7+eE7kMQeShlNCduyOXeDC1m98cTBQ1M99ANdk6PbB206za84yw/e+j6/WMQoefPawP4z8xDfjNKUOS100b+E3JpPkYuj+PEINCxReoiV6jr3XHcneD0T7n6ZClRoLOj9PXo6sVdiJa78GuXHYFKy6XDAT6Sl0jYyifwYYcOAqUDVM0mWvmdA/pQden7Mz9LEnyJooFikm157Ygu6g/zRPFTzmLVi6i10Wmf9y5sqo4gB5Fk6oylvJJb5LDSqOJkTweExZi43FgOcW8I9hrrCUdowCorotIsOJ+b7rq5U+/ivUiG5ST3e67yJH/ffKN5M8IqwoohJypIZd30Y5/UyZ3TWV680+qazvXC34HDLW9t97pbETq/NG4nVfZCTk7VvfAiXx2hckHeIEq8KzxlWBxXiM7nTRVv884glqNNc/7Jw7dua7SLLWfaT+J+c1fitpGC3NxTB5AN9d3I04oNlG6411lgfBlEFOqZ4oei4b1ZpEN/EMkk43JJWy1E+AgYdy85SFH2/9SA3Slj3Qq0qcb0Lpv9QxWG4kDYg+WNtePGn8J/rLQs/Iug/Fff/WPBiHu373mvA0p66SnQwBFAAlR8haEgS5EAGR3vHuOvVkW6UynjrYolMdzk85a53yarJ0b71FqPQTS+6FcGejDye6pgbjEeC05ZWPE+UlMfbGXAvSK7OZ5jjihNVtbfvstKtKIX+mcauuRh7uA5WOYO+10wszflMD4oxnzMgXzvTH+LS/5F/9vWVTO6nrK7QLdhMWSxV/FtDKFy8skeH6pysxxPK/PDKJeyUn0Sf8d3zsOfuF0kB2wPfdNU6P3WY3jhy1EQRHarsFUJHuVdMYWzWq/oXQhGcTabxlHlFXvqS328qt3ZOFbcZhovaZv/P45fd7xLob/faXbTdDK9SuXQmMcGQb/Fb8xHAy01sd65CLd17s11ey2srihNrYtIVH/0JZrRI8VSh2x8pZGIyCzArNdKFb+d6NAzbc3VSanfCY5uu1zyqOlVV13HQkXZw5tX1jBtnrx2uO3oNTJ3RDGQOeSJzTneCp3SyXLfl6Gcn7OcQYDIWKUfrG+bBOLi34idDXXwBh82v+vqt29IRmUoqrmCG9dkUFkTeXzyerBuyyteoeNCrKVx8lr8UN3Y15vaW+tb+vjWqDiStKV70ynGsdjswm8hQQWUzOJ29ZOS1GyIDZeMi9xsmdE1UUJqcVeUDoTjldCMacA9d8/lm/I/G53DrrjiWV+K5OEyKxN/R0q8eOijEO2rn/mG+nDkyz/TTZq39gItqwnX/V731D/epr4lvrIxWICvcn2BZlvrrtswesfA35Zr+jvu80tYZGX0sF3xz/l2xaV9RNHyjb3r5IjD52KQEQtE0Lv2OakjN0ZNG8myRD/vUZRDIExDyoa17NUI/Ns307009yDCFpJqN/lbSGfC63PJYnmZw56+OPZ8Kurm0ImnhgTQH1K8LSBCk08DUOqPrn95O/D99XAW9VFbYV2DtzFIpnAIIo7iHsnTO+nz/ZQ45YWhXcmIERBoUDzf4WnEiDe+hzUHDfEb9tbgJTz7HOywH2cKvMifdb3AwpWMgMALUrJzkG3/wRSLR6kO5s50bhyF1pQJWVF+AFwANkWnNq0LLFv4qzX0RNyFd5BKbJ1/zXq8GlUtAwi05P6tSe2QT/4ld9AbczeFfKm3Yn57X9WbubUoYcs7ezmTuHcaB8mfZ/91W8Fm/7d0EhHMUHrd1LfjQR5yxZfIGVWvsZ7PjetPyXxQiDN1URv/G6G6HvLx3OrvThOqj7sl1LEzO+vF4d9L2g6l97kTyziPS+zK6dt/3pr3agpmPn12Swtzcnw2NG2WvcNHxFyNcCnTj6uU/eFtn7rPA7pWoub9iPb/tQNmbibCluavg47FPNrqZirLCZ0Wlk5S17uR+0Ujx+I6cNno7NRR+KU7U2rI5JOX9JmJT8lHsAqAU6P/91Kj4fRD2Df7gCXvXgr8cyVW7BgHYj9O//oTIqHvf7NHnxSgCrloYQXEWfbVEoBPQx6Ge1JRHM/ouC8qkfypmUNtgNf43LS56CPIx/G94euKf251ko/sdO3Q7btSpF14E7zB51da1MO1B81LBvDh/feak//F8Xng5u5qwZ3CgVlCzZFOdJSmyeaV6KGH/8nFHMSHezX67t6bkm+6otAu0egtZn6TUXEaU2v9W9GtfwFzwoTGxv2Xse0ebt71pSZQZBLe8Xo4EHgGBPE6Ul0tW3+M/bv3Vu4YCYm2Z9czu7B7rQmQmNODK507+fI916ABH8H4k3/SiojtTHZTc8LnXiVV0g3wqDZyV1xKJ0e8G7t//IuI9k9greP+UwWfDaws9LA4lKey/Nu5LXhMHIJMxmXKidTWudOPMgowtr+6Rewc0XcTrf/5oOy2U+/xYp1RBYbfrWkn2OfAMOuzY5eKInUNveg9NtZztfxbeWrHwSOGpxo1Il0pdvaIY2408ttNyumci+2QvHsZOOujUTIGGqZ8Rds175lBbwmljjzdtuaQqQYSKyHQ9slaZbzPSHKpGz3Xi+5NBM1Hd+LGwYvt58T3fvC88rTjq+2FO5Db14I2VJGksOdzkXcRKfDuRMg84NbXVU0z1m13OXbvpvJKt1z+Xy8XdvHBX2qS+TpkTvSirCrTMJsb2He/9RKxd1hvvvrEBVupxKQv9r22Svtv5XSNGrtWVqz6MTaOunMIxxmddiLwjc3aVRX7fctgiYLuoxa9Suf08MZlBU6+/fXt2bSuD3PLdKnVzxq2Su1m5SCfHs88wcldNgvgBVetVt+TM5F1bb/O9RjObmKP3bjX97R3PftLy0Fp/1l+e1pfz0ifa5zB+81w535zXdfbsw5bTbs5tEp59fy13XSVuZpx7+3N4ducwG/fy+oFrZvLOsDtZqWgBiG60FpG7q5ox/fxzhi4RnrVEln3S56dsLJLTk6Mci+SUYPH9mPxqhcax/mPv6xipMbgsJ+p/ri25CoSaR6pID3qREYwu+LG/mT7QRsWrB8GiseTnTu76QeFyxYr/5tBTe7ysF2nHkHnOEHJqsfKp+E6grG4yXF/F183tZqCayvufV/dkuxafarlrFFdgxQI9jJf8biNXSj93BlWZoD6m+DnlBIVhS1h9UXdzgWpqtYD/e7wPsPMba8HVod7fWfMKM8IeTrKHHYpz2rGD54D0zOlgoDS9Bubcp4+PH77s13TGBOqdD7sYoizA5IUiIsLj1W5vqwENjXtI7bR8aCieDldFs8yBcA8BVPIe6oZsgTRYXAjNtCrIXOZGta0Lv7qwFZX5OlPu6nZbQVxE3KCO3JFKjyswh5g7Az7v1uufLEqc4/6hsqU4qPvF7QiwkJ5F0hvF8BV4aEFbNYAMDTRhjgEcc2jnENIKCs4pd8RsMyv8sygG6ak3dzYD1LwGZ4SVvypg1mbhtM3lUaYQwTsFODOiNCuRl1TpscowQz+kljlwEl+Os5CXP826nhIet3pS8krYE8r9MQYakIe0xm2FV5O+V5aowjdiVkhL6gxxJrMmIIsobKAeiGVDLtzW/M2GRY3Leufd9Rl8mOoT//PG+jEwEc6YP5MhTjnmodg8o70kt546Fs26WvfEpgZCXC9EI6Bcz6oEAO4xpHYn06MV75K7+fw2+cHSQq27mkE1gdzX7kOzYWsfw4V0VomoW7zvrf5GvSP9OowsHiGkdSwaAcU6VgUQAklxekezhvxr4sai2mmzzgW2vtXYTfql2/aBnNjRHC9PuKXNLrFbjCC+pEqPVBlZDGtOGdWPwegUhoPygccrzB2SqzNDhpGDvI271bBYOmuTfQF7ZixQ/8VSjxv/lTBnG/dc1QPn5NOj7BdIkbc7cAj3ylb5JtRUSnbrZ4EZBrPejCjCBUQyCsnjqMWp1GkC3scyKT58Cx2NXMEFygJX1cEdPM8L//Pxbk9N7z7UvpkSQ4hrhGgAxGt0ywBgokgOZSOQlrnJTRwsS19yrdpHE/3RDS5a4iZXeTqE3tT3ooybNt4lGAo4u0kwXUUC7UKVY9wwjrbIs/7vJXFDz4eGojfXTaFnOdNh+f8JqSMOiU6C8oHnbJ6iNE3i6WFCWMRS1SrZm9WYQWz4qvg/z0+lDt9UaLLYURw4gV6bRHtatSR0HI2E3SAp/nDG2NaTnz1+gpAGMJwF6gFPDMESBTzI7ocox17VXPWKUKGoqCZn5kHjrHtTvG/zX5mmPL2qmjhRhSGmFjeJcs0OhII5xWdyd+B7KVER8dAQVFwxTJr03Se07W/ul3c5IshVqvLeaJhnGmcc1aGJx1IxBez73MFZ+aC2CijM8zTXFgfhgoU0Zf9Hozu13ADcHWET2IU4Rxs9MIdvNDZVtQgGly/SjCOxFnzHZDy2Jqf7k9rr2VlUylHoZcMDfkkiqeNiUTE7xlem09snzN6esq1hF/RS+mlEvsmwBkRpNU7dhpHK8CvI4ZihHHTutqN1VJZ8X+mOl5K572eg7nzIeOeAcIXFhLio2xy2GhQrZ12eOnweejCjpmHXPntaR0XJ429+Mu8moP/3xQIhxFHeFZBlFgyMEcIOGo2nQk0Jx7x7GbF/gdFOkBAxgrduZFsQDp2Kb6bjJ1mTmwImRr5g/IfUIzjNNdYAbhWQ8yu4cRx3u9cpVgAneZt3vDAFTn3lvYtVQoiXtdDuSC3mU0KtY9Y0i5yU7e7bDEt0cyrTczBUaAGLLAm3UbTMDGahF6XIpbwOgyCFp2XxHYqto7Bvl4EKfBTj/tfPLsqdNEEL59r1WyCQeoV32KqIqgVcqhTcR4kq/tgh/Ko14ZWEsBopvnOxAwe2t2i30Hsa2loZ/d0e6qUsAOmKnOvHH4bhgiU0VX5qKW6RU8q6yxT1osDypY4pdEFdY9VuSOOtvME8nOg3ueFQlQRqBG+vnytYJAsWSgr/Q5OYh1zlvtEwTzd+q1cZPYos3ud/wwyPB+dWaDB0kx0av0xhf503bFNDxjv1hcoiIfReeQY/BDSJ/F4Gwr6xyCd2t9ZilWp4txUQsGEbx4tX4A6OdW9eeFjGFwaRqsCtBct53+APtzd7yF+ehZVtIdmWfgnJ+eyXzJD2xQ2S8dZmgo7V9kIe0OsdSMtK9f3hDRQW6SdXiuJ7T22hNI49w0H3UePBo+EYt5yiakG8wjKL3JRNZvtUeZzxE3cwcvsP0DeJmN2b/47QlS86Pw6Oeiwg/M9wAdCBKtTAMLe9jWdfx046FXkHz+k/DQfLnsNdNXVS3zJEh9MJBVmaTTPOGIDjALRX7b6z0+hV6AcWxad2Pc1XovRP7vshQ0/2ZUJ+walFyr7zmYSQYsY1h6rDIyuS08GRrqyslFdpVOghcfZYSQ8ii0/6XFG4X1p+MA9tEfu1N+mkszmqtJEpdNEsXRG/lCv2I1giX69MtweD+BN95XDetbzyWNkJO/s9HxP9l4Kddv1qc5aUxym+aZ+P4SGHjp7T5kmnkaO0K2CnYbl7uWfAJBCSeKAVm/xd/sfYtivRzr4uH0KG9AogtmCLOCGvZ5uscSw2zv48KCvte8QC21VJHl6z5m2zgf85p0WYidh6XqNyL7FPMO1oJXnJEjwk4hkD6KJayeoQZuPRayN5g9B3E7HGEND4v1DmufauaSKniP4deez5DcBIvwbJ1RPzMU69OxUVs8Xq+4hWzfAz4v3KZQrDzpM1krGVTOBUq9lqZJlL4UJWC3axExTviNgpnSovKBSZ19AsqB62ZatF7HWyjp+8/8ZDFaP/3dt1lIwTKW/TsGmFq6I9CjlMKrcNiEYOdGsa1EYESw4IVqZHgmFo3rGRuY3qgbgoT1hQtG/zdrTPPf1mXV9p/S0zkreJfP9x62iqg+plXVGFTjRF7dZmqQXpv88PDVDCn6cV2hakcrSnug4lGDqwoxUedAk7JJhCDGqVp4335RY8FssjGEgnR+3r9jE4dmyHujA1jCKhM1WpqFT8ndRpbQpvc741VumSTnszhqgxBw4sFrn7okqYJwjxdUaHzXmvJOkvG9aPqj/VMuDINuxMolYcwSr7IuISFmhRT6onkau2xcyZlaASLNdCyNtJyJ1ZVogKseSxxbwJxlsL3Va4j7T2W1SUCiVhQZIvHVKy015SJ9MNLawAFRAWd1SlKsp96BfQxJ9Wp0Mlwm4qyLJQFmYVbPOm9nTY4/y1pGL3bpJUAd2UDpXIrWBVGmAY6pXm+Vj6BD9MrCIkH0X6IxyTb6epjRCY78qiONO5JL0cvswG0Ket6jPoE1YKlgys80tbfY4tFsQvWAt3aq+GJZSsJ+Q0+Ra2Dlwiay13sVn8EaE9bGc1Cy2zWRNn2ZqE5gCMJTUgBQWvJWOaFDJKDcCAdOFA00xIP/W7gFD6wZ5CzVhzqTzLLC72C6vrqt3lYKip5wY7s0xSzpGOMq0pUkkZWxLt1+aHvDWK1RhzSHhs3RbjmNr8XkTzoB+tSKmGss2ncusTwxs80lim6zVc6FchXfS9ZoYoNpICI+8n+KalCoYDVKj+gU5ZK7atZJZGXaw2bD9zxD+TlcZpHdRVVVkWRReONGAx3m20l2+uGBDjXDYXZVkH1r37J7ZVSeqm5XUSig8wBLiks5ZW7eLRk/PoieyecMpHbqoVRv5dz7ecaQUzifgxJ533hv5SocQS3bUIR1d4Fp9gJCjjfAYdwGKzMbMTfQv7M2s20+b+8QS3dkZaItdlM2273d+1/GV96iW5wLEcYR8n5E2oeLPV2kMTPRPpSlGJxExfuZTrEMM5bQLsKvJYkIcBC7l6qbWWuU9lOBGttfVhtXZf02W5EsrKv1/UtUCZhN/QLe8NoTKhvWXfLIStA5hCCcEEZaMekLKI9G6rsI9S5tbGrAf5YXdJ3NTnU5TmFGI3CaM3SvtKtLG2XUEJFbamGJM96r0TL6HXLR7g0J8VcpasXMJ53pPw57sTqNTEqxJIWbYO2bY5dgBjI9OrNscGC5NMQ6EhxwnLmz3HI48bZ/DF2YxSHorMYIuzKSV/MvIh+HIjpdL8sA/pAHACMaPMOigVKlfYgauB6VYxXg+XDM8VLoP7YSjpIr+Gg7L5WndwfpUWzagy3653gxCjVFU+nTcA3wA4mJVD7QuZYynddybwGPA2LXaDPf4hCfsLvwTO3uU8NP/pL7Zois5bftw4JW+t3tYdab+ht+Un4ErXPdzu3OgD8DfXZq4t3CRSZ9xqpqln5nSbkW3XhjvRw5+gj2LXARU5Ywk9nbhuxuXW4IXMaqSSRgZVwjcCZ/+z6TIvBknsbe5ApHXGBWqT3YrAgbdwhyaaYjmS4SNUFSqqFZErrKC6kL970j8Ib+rWIB+yG13sDfLsnRQO+mbpZoEqxTW0xJKgJc6CkZwINGtJqb1Bz2KJXDByH8+PFcNp00+HmfEfUSsNU58+nmqe7VEgsFQCxy2mQPQYONk8neDj4YRAghKGI5DPYG91GdJZb0O+hv31pcj4+nCj1scpSWAZR91yKP6W1Zy3KeB9mYYiqjIgpNZyCSB+AtumtS3T2Ncjr3QzVJlNf9ksxrGStnvHhTj5YRN+OqfaygpSyns/tNgQ/soM0a0UtOMu3juK1qMnArQwiAL5QqjnLnWWLqWaDvSqbVfNgDOmePGACMuwEGEhpIvw0XTeYn5MxoQKyyFz4vjCBTZlLFg1l1Hlx6gMlNQqqRZqr06QkH8hhtYiuT2RL6+DOkzihVBvOBIFcqqFzo/jR7t4TjAnLd/l/W52InmF7qiLHBpJgpOUTJGQCJFWaA7SHhxuz65yW5+TRLhfa9NaKPlufLNXC/Rl/96PHwzpSiILmcR2YKwoIepcSfQO7ZR0ZboCSZGQlEZpNrgYol6JScKGFru4sTtFuBSGKvyJ86cFbHPDqCxtWc3Q8+fdF/+3XHD77xTP/GSWfkFMGIquOIvBUDf6NT1IL+DGzTVSAHcpUQc/IoWz/HUKAXPfmt80nupPalv4p8I68e3YGy8nnaidrfTiBjDOvAIz4IGIRx1QngscSo0gyD9+qkEVS6PyyRvSMJo5E1bM6iJ5oJz8GksQBd8F+plufgVDfphvlJ53NCcvT0iof5/SSpJazk/tWoQqbwrUhQGmlRPJFTN70/ZLkV0KLyhCiJSkxKIBBDvKgqXfUrFzLPM1IA/Dy4uGyokMGVZUe1gK4Z6FK1eftTl6DGivKB3YZL3nD3ZYN9UCfaso9BC9BsyFsw3cK6EgaLTY8VfSsWpAfctNnbd8SGnZo3XoJmJI+sgU4Aq7ygt+jU8YUi6dOsWTcaC9n2sVwCteqLKon1mxkG3XzzcSVsUSTLTF5i0yqc8EUk06DBhRO0bZEB6p8RoY0Nq134NxCLgF9XR296STdkvl6QL/3lzQdx1Q8Vo0FBGVBrpazcWByFaSVBgaCbBlfjct1YdYRUXspgqVvC7poc76M1TMap0onprSRHpUmBXrLZoMCv2MwAHfVlPEEgWx/VqYMeI7OPmBprv0LMMuNkIYItSmlGWzgjeEhmSPQuUMOiYqdl/c5IbhPZC/4vPPw9BLa24hv4SN1WTWWyo3uMX419f61r/JTFuQYJYZZOBXbgkJb4L4LbS/r62drXKk1MROhkE18yttavkOoQMIP+k3bfJAQ2N56oxfkHFj5r9qq+dfX/uc1ftu72PheaBcSJ5y3hCRXTu54wbCw1vXlNnMJs0ckn9wQuyi9u/OvWlqhtyi/3XC9jPTJr+cXP063v8AWC4mz4x9+BYiuFGjPosam5eEOQFP3VygDq7U4Cp+t735fvnL8l6MOSf22bfAh9Y6hDVMKddUrT69TCF9tq8Ie4qtEEgSiskzuuP6DOeOlEz2mD1jYlKAxGBMjuVJmCQhqIy0gdeEBrFGKfkMPLGzvyeHdv2E3vzTERybHkj9jA+OHy/gX6JMk2fwvyjbaeLLZYR14SdOi+b02YOkVIVW203nHU48A4wbi5xY2Yv8UxrQN6huShHoBpz9+fWFoz+5XB27xWxszEqsvS08+v+jlOnZlQZEPxavwgx1xOgOEkkNrVC30dcc/s+hmmmPb0VpLXzpPX12GexyqwEerDu6LNBY0wXn8fjziP/0+ecK7gTcuEbTmRT4iC+N02Xl6BiKLwtDVJMZSkzfiC36MP4IlestWeEuNWZsxjZDHN9G1QYbMAgHLh0wnyeYFzVPep4kpVWCKdqJS9dDvsP1OgeQrWlbgBbkI7djM94Mh3NfE4VbPz7q/wPeXd7z4MnBggXnA587g8fCqOleRfd9VmI+Ux25ZqWPi5rULekjHshSShTuIxmT9dtyimRQ1Yv96lml1D7XIIdFTCjGLRf9cPGENBv1PcW/9Br8z/mYGa/Ahq2+mLsWGWwpdBfW2PRAO5MhhvI27FTF8OeoSmXZwHx+Zq8ASuX+8oXrZQcXkwWqvp4N78HfoQatCXQBeeJgl0SmhTQrMA8Ze2st7Emf4qiMK52PP0W36Lp0C0ylSZKUY3n9b2/54Omgw3kyhN1lW2urwqrGb1QUD4yjua23XQKIelANfbFJCyVvl58L24aCu1E2hy66T1EUra9Ifk2432tUD2IY7NhuNKABRQC9BQsVfkQ3jrQ0GFG/2JhlmW31GhoMxGA1RKxGa9LoMILHB6tqYYLQV2Tk5bHW1D6daExigr3GV9BdWM+6lzdB6rjoVvunwiCpwuYLMeleBb6VsTTKIgKNGDf/as/f2zhiOJw1EAj2QwDtyN4SQBPDVZvnRgw2CLavwoYgX4vtTBknmAjCYDCIgnxxnEzEXuRlO9A1mM22gmjjWQFaT6zSh0udN/RTA4nuvAIHfEvPCKcf4ISTWx4lx/EXqIp1IIdY6B1VJ4D6XhOrzRZCIYhhPQKoYdJ4RYVJM+VjPtFrW4gS7A6sEVmZVdTNuinrVk+WCeJbUEYXJUSQlE9hQehlNirCPoCllOUuGhugcGaFN3M+Dm9pMAHDDFi98m4YsyAXmoaakXmB5yuYos1YpbKdILB9T42eeg/LFTgUQ7x3skIHRACiRROX0OjEqBEDg6dKHhBl/ncpx6SXQoG69UKpaOJ0dsXUxyPBu+hxlKrqxw26j7ZVnHGCeRkC2aOlHY1e+/79YGGJFjPDWyDK8DmZmbG71Fom13XoB0p/5THNLGCosVrP6G02OAW22kwAPapw8pQTYHRaIXoNFUyrAHfVmgzatGnU01SKbqHipnqUSg8/7F0GQLRKCKUjOK60oadhmjLanpUMb6TyMLpb2k9HZFPzCA+B6dIkTTyMrfhplI4DL5oEEd1JFQ5v14fnNUDK/dgs95nk97JCY+4HJ9/Nn68GiFQNBmQExYkNvQBzSNx0PmaQOs9z3jvoo8G/jwkZPGgJP4MR224BaLhaAhXDOKaz4EsoXRebWehTSlQe5HHb0TCqdrvmwAaiXcjltqKheQ5A5Ks5ED8jthkrex5md6lNdhsNB951R5qoxJvwSmvRlzBZ2pbw5Yfo1HXWwWA+W8NbqKaqAcEPZEHYSNuMjb5AZLfrQu9oemPlRU/k+XY9x9a4fhOu744gfcI6+qbwRIvwZF+QPq1dCkRSfyYA1dgvWrFVSGPDgXfOIU6BOqDm92IGkmGZmfqUxP32EW420GdoBTqDxgnagFaQxEnBiI2i1+mOFCQ0CFnQeDIc8iIgWcXWSW1d+ad6f/BYDVKIUXpvLcr6W8ke/Mi2qWPrsuDE7z5UkllK3zyJfvr2vAZJPU3X3rw0wJOQpQuAy6y86Iq6Gyt5OG3pM1KadSNumhQhax4wbqeWf9L737152lqNzBLv5H95X/hxlGcIwlAb2JSCHLLqhOONrvS29dSl+tMjKt44XP9oe0Fsx+fDYL9l9VVYXbhixP5iKEYqgaktG4cfdt58l9pw7+azxE2R78k8v91mehXyoWXis+H5wdYhCFE5UhmsyGqF1u76vbTQmmpVBBQxZnDZFMj4r/hR2Yt/bV+vqxXa/ryte7+z2OLIY9lSn6EJYbgJWymDZIABHFBhKijYthRl5Ua8u7Hi5ckftcT1bf+3ukfKI9XMXUlo7njRhor7HUnju7jEzAVu6/YyQVBXII3shYpTZ7n0yyondTtTbVmm44HKOfL3L4m3p5cGq/5VKFvHJ6PJX+wysqNcnt1ZX204Ou2BbuJ/6J68mZeYqREWQrYVO9jEM8ePWNMyw+wvG5+9Eti3hkzpK7qMG39xHEp+JNHa9P7D2qIa4ZK6+zrXG6XuPEg4rgwcSCvZjC3dV25eHlfXCDPufv4QtSyjpODUG0nJS7+Yv+4fp5BsOrLNEzJDNBgYFA7G/l9/hySDKjfBWpbVNlbvyK4n0DPbs3WjQW+m6yRiib+X/XY2eLlGXZrFdk6cLbksZjbLRNqwdvovv8/LkILZx8LKXmrjYCuDiMvhexWeSexLc095oksRPKIebEj7sfvyjNiiQ7DTO/Oi95gg2XTOi3u+1xvcWz7MF4oKkq/+lzqLd83Zj1tlB3IScgvOnkIDQrkPVldInMW5PEBGlyry5AIsyOl0KiqIEkJTlgBTSVUcj+IKz4+zh3U4hYiS7xZk2LszEvI6+v/MgmI08+R02In6UMYbNRW0poIj/axiIvxcgr+kEDxvNek8wflh7/3OqU5LpvI+8yyASbLjPtHOlUUNHWrQML7YSBObrhA4GqrTheS8kCdIf5GNfMKmaFpEujE4GiEaZQbGIDd2df96Lez84CXiQOSYoYZ0n5tfKpzOX7xUk8N+6ScPsE+Pr/qb1jSK9mWxUl//RSU0XGQD09LilgI7hDmNjG8tM01UB079IGYXvsHtPEdXoKUVqAIzWJzDbxJVfORNBHc2RwWzLQJYKaWlP9CPyXh7GP/qsWRi6ZMq6eOpI9hbywdbQ+mf7DfmnqF/RGfNWJ+WO2Py/fOipZ3hz0XLwoIDoaB+sLE3YdJLi5VP3+fLpbWt3Ixy6DOlL1cVFhA9F4LbsnegLW+5zm0n1F9Yeus85+x5s6Tslh/zkaggUYhzQ97S0No6ESwPTf85RZhajps19P66OOhgChP3+sC+zbB1BT60583DDVvjX289mV6XAS5Pa/ql9uEU2FB+QLp1J6GgjrH31Nje4tHbd6RagEG6NhxBwriac5nJBN/dDj85TusZLyo6dq9XAVvLzcN1bfpoF1ZM+mn9YRMSd/EDdZoCDDVhTMqwdsasfBYH4HRMYguTUA3591t8KHMnqwul366GxggyI4xMSGvF4glttWWwYaF4vp7Al5JlB4ef6+i7UDODHRemYBvgcoU8pqndGmOa/8a+KRufxrDQRFIgrsoaP5KdyDCf1j/mq0bGELIhiCxoLCYWA9P7tojtG60pYp4eztrd5MyN5zynG8gyT318WiAR1AAzKDNMON520EesQHyBD60DPby9nd4kRnOwipfQy2G8oPCcUk6T4f0og1ekN2oECeLrBe3iIjdTGF8vbAcV5rl3TtlPD6E/VDHYWADGAdaVh4gbHn3XSEP81+s1R8mgpTx4atK5wlVxM0evbEupG/zv2qv1GyefK+z2qz52tQiulTD2IIEmcSkm9SedJN3AJKnbGboHe0Ie5AnKn//8kDb4c+T3fBpsxn8BsrskhBwfIgF5oFZxwimvaGPVbb5Hyy2ZeYMAHe07mJeWWqUStqBcMBc7X/83Oh7Sylip4cbGr7ZAIZyEcoKZjVJEoaz1+CBGecojW30RvPikFIeETV0ADVRaMCsHzkkRR+jzg4fCbVJjo2kx34Z3D1dVev1+57s08BzOMkBbF/baMqapuzWSDB6pwLSqzizNYqb6h7Y45LIB9XDiw+OtsVIKetbx0IlkUUlZjrdZczRW0dCCfbI8RWOfMk9SEQaX9c6g31WoyG512G0yZWT7KSUSWa3hpQRjfT+JSnJCO2/yKQS3Rmw9Qd9aLjqRICgtmT+mp8tC3jCAS+sqddBSURuUwQjnVfr3j7f6EhBJNP513kbibMBmbZ5kLvZ/6sB/KcHzgc0WiqPJiu4OFJLlyYrue3U0CgTuUKl3Gy2MR9ZZNXHRo8YgzX8Me6eriyJfTEdrH95GfguAu1eXmZVEnVUy1o4Ct/tKFpPE6am2+YvxL2L33gG458FqF9vNtu8AHsxpLzcbupqR+vMXdcFupYqPxh2smNT4w3H0Han52P2W1uOJ5v0yxt+PelOLhhezz2OqVm26Sm0Q6NRu2MFcegDFULLOA6foKoLGO/Sfr6If6IPWNEmbiVlyJemKAuBkukOIRsbv/WyNWwXUeZZ3RJQupZfCDYqqunR0LJV3IDOLOdLFuJ3fkI5d2IWSi9QwTZrjVEG6BHA8bdIIs6Z8BBJdeX6u1Jo1AgaeK11Y0t8Q/e+84JUI02twetYEewgZegMDDG539KTL+kAZyJZDbSt2+JLjyJHQSO8myZU5vc2yCzESbSPyjHsu4w1eIW7+5t3Jmbn061WSMx4Ao2CZJ9QM4JCuIMpcWiv7oJdqy9em6mP1Jr0uWKUW9/07N0KZ7D3z8BhRVp3uLcR3PrG33tlKBojILFiQx92zRz5GBtpP2jEv1YXvC4vYxQy0vFoqzAyeKEmPnHzhCv2E/GxUbi6sMSH0z+NAEisA/AXSLuzPXtZ45aWR46hfu80ZLzf54w2kbacOMNxHjK8ZAzZ4M6E6FtN1idOAF82a1G7WdNQh8Z6vP5VfUVDfnzO6Zzi+GsXuuQTnJPATOtaIcpVRw9oeW27L1tXb6aiWhS+ctoFzmbTANl8vCg9Uwd5lM6Ex7/kbwZSWh34rYyKJoAiuxyYLtDRgM+Yx/5jOndL3AekjFlgwUAXiRGsGEO1ULrTRp4l0oSiHWjOV2z+EfPfYUI/XY/182IzYE8V8sBXqCWNjLl2GBngHVYic9AUiUyTjRLkiQTZh6UKh/jIiFVGtwgJaHXt6Ok3X7Ri8Z2tCSxZYhLA8UtPqdk8hGpk25MXL0zs/2LbmsLtUm1nYgmyS3GgucZZW1E5MLgj1EOVGB6x6e7XUgTE+nRC3K1TcdpG2R0ogXxad83T6B2w4HRCPYVdy++aH9VEBD53Spa1tBnix5EkjLbtHIv4LtbVUifnPhYSOLY0XBk+i8SGfhmj81qCSKGtUUBXAgRRJ1c59X+1Xb0JgU3ZDAmqvq/vMsGQpZevHveGHW/V9qMhfI8qnc+VfPU35taPtoGa7XPcIzKqUx2zlcYMqqu61e8lSc5zn1RDB7uSP3Pc3ZThxaboNd4Raqbg01YagnvoynKdxm890EZ93wXsZh9kyXx83d3+oY/auoS9lRsgxXqCdmoIkt97qjKoYKyILoYgV+Qirj/ielGNHsbVB6uiXMKSmvkJvqoPJrc1h6E00lI11nt69vc7GukhSlYg3UktmTEL7XTktMfQV+HQjY/fC0w5ExERuGArNRLqpoHJibECBWMk8OYXJxXeqCKbxbwcCRyijggzChtd5u8WbMJTShqiJOnvS1MzpkNs72q/9jeFp7sBOUUMKNrcEyXuirM7MTLElArVM2pKuyagDN/tAYn8fGXAyXSFE41zPgiz60CcO/C4d08LQ0prqkoOGm2LEv9sfUy8W+8oL4kccVQXKkIFSXpz0ClaOlifxt8HJCi9wTHujlbnRE8dOh75Cy20VilfPoZec6xzCc+rZ3Yjiq+92htfPAEZcFhuiaslPm21UJNWMTO2GIbu/qPy6fWBDPiVvz2z1+WvTwkFluDoGG6gYi1Fmaqa7l3jiU9F5FzRULGWKj3iEONCvF2u/vl2AUFlZhyHnwuYVA+Sv8827mXrHf7Lot5WSi/7lurFxUmNMQd5UouHuZv3UD9NufVzyrn/Rfk8q7oS3K5/abLy24zQwruhlW4wYJTB9aQ+5TY36xkbKFe8vy5lF9DpcpE3/8CF2N486l9dZ9tqjPhmiYKQtxjOeyk/rEAjFjUI4P+1AdsyXhCcy2j6unJE11u/0ic0CPKUDUZPfv3CoZDUZG/Jff7Wsksm+l6BEF7OluYcdHKC+kyZwwoIobpSgCQmMwMcc8ppM/lbjHH7kWV2mpO8nC9ZWYjZx+i8repsvlRzOlr2MMIHqKRvI9qTW+sDAr9KZHK8NCUlhEYoxDU2DqpgbusNksNQYDWU66NBJttNfjwU+wjLLt4/fc2yT8SJVXj9cN/R7AS93RXv7wZFnOpVQoUrjvCALf2paEnf+8fmU4jYsVv+PhGclGhZ1GKbA3bQjTOaYx3S9B1uYrsl29MQ6MtxwYUhPGJ0vcScjSlj2zJQKT6sAC2w56kvQ9EyEmt+MyPxD8Qr4svOIJks4t5esIOMdi9TEX4Bm5nzVhbpsfYrhD7Tj6dep3bMVGCtZFQQcwTZDUbi3AWapoKowL4MGmgdR5+V9LJm/BG18Wyt4E0oV3NsMZRhch7brlnM2Y/uXkBbaa5vfs4pcuI5M6dKaCRlFflC5z8qUEWS+rTfj4NCdFuZjkn+niLTaEMt7f+oER/nt2DNreGt4ddZsvozc/GwWYKtumkFqNlYhjH11roqB3rKSl0Ip2kv/DDmgeSSH8buzdLmtNcD6J8Fc4vfxdBXaBn48y/tVXQASjchLkE1ZjF3ZCxY0449dpJsPoalf1A+p0nQpx1SZ1uZJZb9K0VmhEedhkVE+T8H7czPA+XzK2DGzVONGbgUp1nBNNd9fNwcN5vDg+/uO2PcdZPPMGg/rE6S5JpymUYNrMarlXh8eV3A1DUMgG73VwUVIv+B/Aidc4o66ZvAWak5pRjDCRQI142gm1zS4lZn7AmyYWaeGfviF9jpgm9QbAaCtD21HvTp4J3PBjrbCHKeAbizo7zJkk7B52lRf/htHtOEa/mcFFdFpL9KYs9wiQsDKqi/U2EnA/KP1t5XqEmNwSxGxlLgrEZ1c6OqrNAp8Vb4khmfksdhdzr+0MtckL2EvODaQIt5eSd9/ubLuvbCF7f8ov3Yiz4xZVPyn0lKkRAN7eaFg8bI6bZyrimdzvYzp/0iHXD6TQ0P/feTK6Y4jADl0O06InK+Rxaz9dMn/+uEg4tb9cLk7QpE2M31+TZsAOpjvFIjPYHbTzwQ5YA7j69XnquuAagKTq3ROx9nfzehN6q3vimxY8YT6p+M1gDexNUuNC6nPIvy0bSEpAa45xZb7vbQG9ZizuFCEmAdU0mz9EmpJVHaK9g7F9u5G4+ZzvrhoIK09t8MOvJ1S4WtvVfDD/S5+W1/Au+PoQLqdVqGeVVG/YGtDLeFSxbs3Vc2gk4Uml/lAxQUJdk2Iqtota/K2aozko0v4bbJ9RmPrqERBntmmoI4KTH08+gCv5mhVNgUZTsjwZCdFPFefjVM6ycfp3o16n96D7IXuUVy0m5Zj+12Fy2W3ez1T8qcvpocjT1PSPPkdIuyYEFWGJhJB/1HocMmR3BvWtg3bZR/jznd7vjc4qHqO98SIeIC750phVxRHNxJrOIorGCC58apVc333CQacLQHMpvM9MHUHcavT+D6qV7s5pguksTiAA1HqC8jel9k8PHpBHDphXIbAL7TGljWUFR1K5zg/IBlsFRi727iCdxltNS7Dyt0EH3qJtwx/Qss5xhTJw5OH/+h9r3nYAfjpLExDYygdjKKknbsO+rBmZA5Qoyz3Uc0b2oQFR/o+UJxP2kN9rD6JioLm/VE8vaXvnqnr/H2XATjXlYsyE2GaMbfLiGEYNon8DMrWpwgHsx8lVnC78jK48aEINN2AhGhLEJE5r/w/gmTHc4DIVBAQ+jf8UB8nRoco+wiCRQhej0tMaGGHgRiLuzkS/EA8+u/Yfi5tI0uGUZJTLfIzOEeRS7iY4cqDG8+P2k4AU8hhQuCjEYGhgfL/g7DciQRqlPP/cCWnqCGZESjkUcmtFA+tjQoRJbeKeFDUM+yFfycRi+KYVy4aVTP6pWGKA9qjcEWVQMlbitEBrbHLcidxJaOVXczYzNh7iSp22P1MTsYmGe0kOp5fhmzIpqRGWfiL4sF8TH8N3AyDvGmSbqhJkF3xCwFtgM4zbQzfEBgWZ2N1F2mJqrssHpUbfQ/tnYTibsCnaBVOWr4XWfNfGUBm84div17Ffzc0bRL/qJNrdSIpyC5fvhJuiggQXs0SwVXsHj38yOBCgA6lbOgX63jdzSEU5fYvapOBw2p427ogm9U+fSV2VvWpOt+eoDQdDSiZ1BTJfgj7e1i7KPPvX3XXuQXMNyG34iNyMTRxoBReIs7IZMgbdA5J2t49T6T29UhFspORg2Yub0Y256WH1ss837lPQbc7+A+8FuwaSq808exxMA5QoPTX9c6HZuVtxHynHicG/6YVM7f8Iq3ZAjudP8DmTCRt3sHzRyscxh0Omilb8kqUHZCxjKZiDbdiKlRtsz4y0fDktvcO/WrU5GIXfUVD73ZvYorIV5X4k32H/tPfPQM7d9m31XnoR4RVN6qCOT2xHqYn+lml/LB1F69vJUv/1wHSle5epJbnzpMM6wRmUPKJJIpC2jxbVPYnsRKp4iHNmz32huXT2kA2YUy5c678ovrnpmfZ3kURWPIf9tCl0RVkApeo/0TklNdbxG9RDNKdK6IRHW+uNBhtKfuj5pwuq6pnqXMS5102DDaSWN5eRnJQZjbur9NVfEkzLwlYQS3uX7L+K2O3F8wsizFC/0ta37uVcTsn2Ot2jTmdXslTFxb1Ts6vuwVTQhkNqMhVksdCQW7ZdTLJic7feR53TN4BcJ9LTOSH0Hhd7py/xjrQd59se5Txb67bJtnFy+gf25S/9KKypHu2Ub1iPOat2cp1y1GG3aS6/XcW2l7ruyuc+mXlLoyRacZ9dbfosdZXrp78GRdf6G+xIVvAgafi5kDjsbAPz22sRPo87MxJQWM1Hud2Bpr9rJ5Qk/MNmlkkJqEmtwmboj68AHdEDdjgts8U9UjYcUp8NYdkCdme8Q/aSD9gqIq/T7WLVSwiSRVgSDqwWwmVna9qiYl8ggzKPNijIIoJ693kCLyDYgIrGjB1Jo8F/glT/gDxsaaS+K43Hy0ikFPK2X4eorN/0a9ivTSPobWY0DLVkzmAYKeBUoYhhuEMnSoe/objn4KgERccDg2vW601j+DEzXgJhPxWWH6tj4d3lpFDDXvFI6l8MJMSfhg8Or9QIkPNV3+kLrk7Dtu3GS4E4OYWOjF+KsQDq+MDeE3/LocVp+V8su8spiu1FJZbFCgfiiiny5wNrh80JWfjMd5EM3W6uym+oL7SOZs1GwTcpvjfOdGv2DPPuapOSzZ1sBT6N2vnNHuFWk8ZRVlu9J++Lwd4Netid1NmRJQ+Ymk8KFqz1A9ZxrJQfCVSgeDj+MoPk7ys/NTvX+TA7Q1mUuuOD5znOr++kVzeq4ee9bSKOSsGds7revbSuDsL+h+w0MosyAJbb6QsW4oJ4GFVZhOyImlhJR2e9boCGG+gaZlivLI9C9vaRmJvMWgC5DGKE03hUhzF+LR43kmD9mtHc+CtVfI6Hru6pQmJ4k2DKAwSwODaWZXqu3M3+thxujqyix1g8Za33cRHo/EX8Zm8rnj1MFZdUAayPjw/5hQ6FbYQHcDwDrCgbpoq52ldU1iCa8VTYsKh3nxXekY8k0LUGazLRGAkY4HxR8+h0CUPr/XMSl8b0EWwNV5PTHEOqT6XiDVFediVScQJknsUKwD/qRkRzyDacXmYj7tlfS3rN5SewdxH5FMcHNc/0uKtXb9hHb7uDVlfdbvFQkoIrqMQWkzgL4sWz3aHgZfY9vfgpRMPn9WJ5oTXXX6RL9l1DxQtECeCbDChIDGSvwfLKNjr2CP1yyWO04OsrlppzxKptIiTC/cYzs+VSfiTcwO300M3AHMHcLFPhm0bCBwjUi+oz998bpX8uZ094K5Jw4mRNQip3ixhvf42bIHikH/xY52UYjsdilX8Q6FPIw78cSmYcy/i1LMxf7svUN3tgTyjBlAcYeJanLOrNmImwEsVOrklNudjFgffdm1VDTRnfx92W3TUVO6D/QrlhaIM90IaUYrL+FEwzTAytEevEApFUYrAQjGjXpX+u1yoScD5v91eAZSilU/+BjSlPLZqqg2+a+n6XP2BqPlo+3INwEFuYHv/KHTc4IcSmRyJS4RS9am9XUxBSOLyvzU4jolWSvTRxNKWAcic4YPhoIzSH6krn1cPlRkzFDnkJLI+uKNan/4WPqyFNvyER7oBSAssxJKWIj/i7cciRDX+2J1Ykvz8IgdzdV7mfoECfnffPEt1fsJlMFF2dRqoz/ESu2+aJ8Uwb7QIUhLHPVpJ/j9vBP7SkHfw6l+QggYC9//aSZn4OQwsgFsrfI6uUFvegu/j1A/RLex76vdG9flXs0iMFWfxJxoZLk609h4H5vI56Nu+2m+V/h/7fZgfky2sfh2cm/X7MLgmT1j9G9fwsRn1jT9bTX+EJYEA+HUMeIDGO9X8quPpBt6iBmZSssf4N/fah8OEbtYjEgVdKC40e4Q41Yg5stVClTQMfamEraZOG7vyB1jPpHd9/74PfzvTx0CTL9n+/iL6Ti/mEKq+8bv1EvyFAG/5A3HHFVB3c60jSC2uek/EF8x496aVoKFUWdpuKcWcgWBIYbWSdl6/4I97Dlk6hExOvwBtWMO69xp2dW02X3aL2qfNLL79AlzMCblWqPT2DKB22+2hgDsWGY0qGc9yvL5nrQpKLC9CS6i8PDy/5HtBSzF4JkMHfDZmb9T9Gp3rgDrmS88HGwq4G64xr0H74OnpSLUOzpLlP+KFRXcAY6kdKj8Vh75GtafCNoYcePuvHZ6Xyx1bXPXfcSPfgRtme8nkqud45qFuScaTlKQ9zPLEZg8S/fGtgD7a5Bwfq7YHc12bQofH/Og5qwutpS3QSUNcTF3CumnkzH9itSE3OjOZ2LW21gq0JZRobBFgTbKVBvpD/iHJbWFNU+eX33CVxdluyLCF8grOcxkTE9RszF42FFzcAp0URKXUw6dOI7dl/xtRJz4jhdi1q84GZBX6EwPOFNc2zTFC3fL6DhRYm4vWts+tgJP1HnwTFejZc/Z3V87rIENFciI024u6MbNzHCjF+isYv6YluaPMxPwkZ2njpfti0xO+lpx2ifk6gOKORmHi6jRKVVJ5zkU5ku3SufBBd9y0SLRNo1gdthl4H60lv5eaoKCGm67X28duusp+aksMLnDvtJoFzLjGKJy/M4fMLFI93MP4sLd1/KgPr/U+Zr8TNtHRudH2aPBA67CkxjgURYc8Y55avWpzTQS+vQr3E07bmzaWssuVemFUauYRXmCT3lWob9aDDSdLyIOUerWnK/87ncfrwpO5o1BBQZEwdjVhRMxMSJ+Sr/BxmNNViL+4GuiZ7K9DpCTEY0iWbE8CUTxQQCQpP+MQwAFFMRaf4RzUZMeslma+iBUKmYdhcFVVFKyeKNBEPmr2XcBBEkVHmVyoSDFlQ7v2qKw7RqiUI38IIXGJ9EL9AcJhRTQviqkzgiOomLNTA855MRVW2ZVN8vpGSb3ptM5PBlQfGoBfs5zcIlHWklyiqy4jml3+mbCsK6whqAwu12RuUUtPkly2mb8KOz4TlnaHNYSUoUf6PYQPk+i/fp4ZzfXib23bnz8fXGiVkNwxSauaPfkrx9APhQUXzSutAkmSJCSJnGkSveaVxdh5iCp03aPUJKqd1HyO1NAOcZES6pM12Bzg/ngOSy8lCjVDzBw0U7OPtC+mB23K02Jm0EaRxwiJq13DzF9pQ7//soiIemq6UFdMA55u9+gjfWDMdCy6g6qNjmmSMpEiM4uZRw9V9pJ6IyewW7PBg4bglBSCl/yEdZj9pQu8+WFNZLZBNX/Pr7KSdexPSA3G2eJQom5UbKd+LU7qjT1MnIq/4HfJpbbJ5cUzZCYeJavqADGV0BFpfnEq2rTkUMFHzBVNzM8pfs2nzENRfe4sMhzwE9cv8i9MOm0NvDLxEKJaWxlUW2uJM05ViWjhTkEeclbXYkNCTCz1WAM1kgRMSNU9Qq50g8AmAXp9p9MOuIy9gpnH2XDUwhvK6sQaH+4OpCvyK5yisrxyogqySHkF36KEHtDOgsMiqGbVBnU9EZ/jY2ti1lk12BNVFSldRzOD1gTGJHFXKeGqHMBHkLOwlTgiMuKsFkEZsAEWWieUJatYsVVDNBY1UXM+iC0XbL5EeVGGPQ8EWIWTFH/VF5CHIlteE7GGRKSxUgil4PE7OlYpuCEqeDjk037Un3LiVAPTpf+n5dC6koNxhs1FUKliMWc9hFCqXny4Wj6Bqdgiy6HcVn8/e2XLODgG/kyB36RER3u1JjsnaNllE0NWE3JSTMQWaDFbcGkQN0mRJfk+DyFTooJV+wSkrhTVmq+T9cylkCQYyzCxV0IkBmyw7tfLsVbO8mCP2FPEtoq9DS4obxCr/Lg7kJzx3RPlkSGvkmj8PFxTyjcpoBu0AlJrjox2tE/yqyey8yJsd/csplzpKJufo2JDjZ78PT4quaCWU1ZWQuQprltZI+R7hmQREA0YS4f1CmYFilFQBXTa+vu0R2FvX4Ra4DNgqh+BqBKCZLsfWks10NUp0BY8+BN+j4oTrRbbqEg5HMYGRft28UbBamzJZ3texa7YqX7bFUoAqMXgb0ABIM8Ow7klVSg6Gfd2S0tygVg6D+UPJ2Hnt9gyhpLDRVvEc57GJziWKRsfizkgDyJnbUNj+1GyTYVVHjd2p2BqFi4tbjVIT4xP7H91avKTeJBENj96PHLqPnCcGlZDvlgKpzqJp1h/r9rTuwunYx684HWQ86U0hmCf5vdxmvV7yUgb0WJt1W/wd73+wBtxHg3VTFhmAp6IH/v7SdAIjBEj1t4MLGM5Qihtw05pCrfVbVdHzfIkTvqgD8/I7bh5xx5JNEnqKEoI2VFWvBfc3nh4KSg6PZptUFnuqFQc21QlF5cfYuZ8nm1hdd15A92wHSBCcFvaGXQmcRv8AXEfi93wv9jmbka/s0WGDLL/Bivqi2MLCp4ncB+9fcAoj8y8FT+fvDw0XHyLuzC4j9mRlAK4wZ2NiCq48hTIXoBUxDRs7Zyt7WSklhknzF9IYfJbPnQXzCKkPXeSO6pLvqWrCianbr/GX1VcXB7vva/x8vEbTbwD3wm6zVYfyyfV+d60TSvoJHpP4/Noe6725f68Qqt8pL6iUNPunfUD+snG5WRxAe+FX+w0NWHwVwj6Kin8jHGDLXcgqdHZHolYbshlu7Ru78MW9+KOcJvViawihYlI802lInUn4wnArXgA7XEAYk6i9+vxeClLiqVAEpCKzH6zUNrLbAO4ZxakTXj9/NEsZMzY+HXjjNtHFlwJCiA97o3qcXe4KTZmMFWOi87a/q/5oMW9q6Eg3kDZVdkiPAzCi8lUFUW9se+dGiVZigPmoBRIAj0S6sO+Y1jao4THAmJnFI8pBiqxCdKVvf2/gJxOVlbQDJ3PlaiWMlDAZ1eFC335WFstMCRTeJBtQGZpDHUUmX+9Y0AzZ4vXvdNBE6QGg0aXHB1/OML9fN0gDpctAbRLByUhHAqTcI1v9P0/5mZkGqNP+C+i78gKaxXYsXHO0qOttttHVhJ40LImoBWNxCUZGk4S8UYdkRTgAg/xFBxwtMzIi0B+70LUcR5LiUW5OWqPvLCkminpJrX35Am9xJxIH864ELUAgIcmyfF8RVicr39JBChdunlCkifD8++5oH+8xLjygW7HZjTYU4Pis3jogVhqRyMXgb3tmCyW5ORK2lxJ9BaPrtMqv8TrsleF9Nk0YEn9sJJ2UObWiJoKL8Yo9UUU5qGqGAPCbJ5wIlNbK8iVNLJ8jKyrWyAgRNfmKHadsVG/6rgtaKlrpRTIdoyh+HSPyp4iGquOiwikQ1arA/dtzKGoeIcyaKgv8gKr5Ai9DwhC/uh6bK48ZswD8KHPFYd2Rw2DvPAAW97BkxgknTkOuQjI5QMGK1x30WhA/4jxvpgxs+QpZsYhuQ3szmr4NjCOhEuJ0qYkynhpnF6BPxXwq8oVPu40dzQRqzPXVs3eO61ahZyZV55q1NRpiMasiTXr6ygWkHicc1Eg844+s8106ZB6dKc0AeuI6LmcwKbvCJiqsa6LI2mU2MclCoW7UsqdrNr4pRC2+jvI4ShB8MLmS2vPK9qbZWHTZwItyxSzszZYdW1Yaxt/6dx7M5q0TerHgokLYjQlBcqmalmXE/z8iWdegVJSI1FhX1GslyHPpyRwS4KCi4XiB4IYLlKeV6gaEPGqCOxKXR4aqjgYJBn0vjB0XEv1ofdiApfkl3slKB/sUue/wZHsjxj48wavCX7Omp/7FeCTIS5ogE1IZGKekp/qGAYt97rNHR1FfSokWX5wRamBNUU7g0mfnKVVrhI6d09QcNnCTwFN8tAdhHNAvcW+Aq6I6APpOm1oLCrfZkXvoPnPUptnbvgv8D5gDKLMpmWIfUS9Q9eH+nTbUE4mLvgNx2+Cd9ByHhFKCIBURsN4OgrF0WnNUXX/Z22dKP6jauOSwBYyMQh85U3/VTw8ijPx/1/PNyOWOK4903rCdnQM41sq1vvBXdNGlU522dl1EYBmvCBGNjhAU9CGMIzcMWG+Yz7TgAiyQkJj0IowglwD/YTOuOUkvIfYgwbQmUKc8wamyCtxSCxxMgiJIBJJEFGiJIbPo6z1lBaqkRogEEaiOcV0dL/7iqPM9u0sO/wB2MHj+j17Vo0tiytjG5Aaq5EhJfV1+v5lVFguaEWkemcXX90lPTcxEjYIUBFg4GBuoXHHhM0MFTQ1zGP2ijdieRNWXDVd87Wwy5BxlrQdEwgOHqTrHvsh/DiYNFYXnRiLLdmkF/8t4Y8Uf6NxJ8S6mjpSl2G0IbE0JZLtnXpE6MWvf/RWtjNPURPziiJvZ2psmjBasfn78O8whoUv5R2mL8yzNou+6DKjifjo1UN93q5NoBQddUHYMJ2v6J3263XWPf0zp2+pSq0SicULvdiizvZcon0BVyHu8jNCG021K8SnN3KF3G48H5BB7WrGkcgud69j7OrFQpYxl9AAqhzabgAv2Xzn2G+W8dhDkbNqsMPSmW0vWJueuyHM95ZNEvd8HnXtneRs1oU2HDG4828EfXEwC6GMjXWBahakzNdnly269iNurc0fu/8FDmbLX9HJhl4TRaK6jCUVTvc6V1yaEFr0RCPKq/hq68jbQxFpxWGlne3W/tPtRhmJGYoGs6OsVHmuMOgUqGbiH24vNB+y6d4fhOPnNS5HKZEag3X+4xz5PM1G93V66ac5bAV7MFinjwpXjVc/2++w1ir3GMH6vhkZqgQUcNn8+1e6bRrpZXWCulAElRsd/8X+v6gMKXPU9FlbprwkBRcMsidyXJTqh6xafVSEFs5lixzyagiqC3je80avV3zOOACVcgTMcXfPRKplDa99f1U88Xm4zDMROXsiDGWpOEodhLpPPXgoF1+fGT9es7Uq+tJO9TkXTUi5dbP+ywXQUZMIy4plqCyIgsYClFpfvOnuLY2vHt+PWG0Fk0Z/iUFqlApUzENtheKicIqBcH351E/q1zKbXHMj3f9m+otzjiWvfwLQigmMZVmJkLgKfQ4TxOxEmM3Mx5ie7TBQDGGJXoIxoC1NF+sXV3q8IwxFxJZz0uqZKSEpQVPIFhX0OjXPxO6QWU6JefGJph6grJYDcKMkRzBbrRuNrKLuOTRgvO5uW5InGzlqzTuqObFojIpFdK3IE4/TWmgBceTrRQkp1FViu3luSWjRetZCN0n6z3/6c3D0f34pCA5hqHc7nF0bdQk3L+/zH1eTpN3J2vL5JDT3+42ksPxVWPD9baKMyJl6wN1dSDBk0A3tX3+lTH1afEZ43ChGOBk5nP3QikcX1U1w3vsw8EGAOQSC4L30i6josnfOwadcM1J5yrLeLnVHaDRyiBEoAjFKDAwLoyqEkQCAcODOu7SyqeEK7kn1wPhkNuvZLXebhxzJKM0eIPSHGMDyHzVhDIxQX46MVQ+v1WoKnbv6DvX92ueTm78U9eK+t9wLAdDvIUbbHBkpA4sv8ZFJnknVdb1UQpuzwXWAqd/PlN157E7++5x/KRvhZIgZa9Bjp8Rd8XukXDjewsJ/pvUvKnF5cUTsxh4649Nruie/UEky7BumYntTyds9h0NHQA3Q56IueP0wbDMxxtqPwg/VcKE57Wv8q1X0tvY1gTUK+oZSORYaOo0tekRvSIo4w7eKtfhY1nWjs2TWCwC++MzH3CsMJVW2LiKGJOjvADcnbGIgWFP59g/WJ+WjgYgo/uehHiDTJoSwG7rDO7lD91n9mL5sy+j/PEXTZqUb7ktDUjEHMR7s304BqwNF4FmXqOq94fN3zF230sJl+T+o/GY6dzs4Rq6ed0iR3CP8Lp7XF9IWn/fTRiH77sw2ec/DTdooy5m+nArDHLnjVp4ZtHhHIDUP++EXytsTRuZ/IuNQemyGWJb0DSHUXGb2KKu5QJWgTQjH4UIsLuIVxYdCYnlW3CRolvDyaoS7Ii2uhtfGt1tJu6nUn44/VBLo4FR9XkTNKKqule4c2qNCTpDrJKFRnNTKxPwu291yprqqirOGVUdEd2EbQ1CDIPT3lzDbq/KrX2HUm9slxx8NPTun+kGQMyuZWtnMbXSJ9Y7J8v+fp7dyexm65/X0F0MJaC++ovXQPnzarhhybou6QZb32fEpx87KErNQ9dIR6R0HBc9v8kin6zor9Lsdmd06RPrNXt2xysE9u1HbR3LffgHOhMbjdj6ITYoN+At1Mi6/l59L8cJH+nveBjFzNrG/BEzHfw64QDzMQ4d5tPJJFDohGj251+ZO5oat3Px0d78yX/jx2erU1iu3EvMZ7X2CLkdhPr0qv5CDwxPcKBpJjksyKDaH/m4RtnFmHSWzoqHljBj/83WNxI7shmGB7Jk9lreWwhZ+uzvSt5V4bcRmXNl3LBIBJ6EpQdB32g3KLa/cK1E7mPUSxt5uoWzkoYB5yu6t/NIc54BRDmIjBPq4Y5ABy0IeftIG+RtrBdKn8DCSBVWpfCjGKHKbxRZVOVEWzLx6Du+e8DKPvcOQ1aOD4rXPqxQcF6yirXa2o2wkkHSQI52tjVEOx7fqBvaZObIWEtaVzg6aFnTcI9piB/NQ6PGev0zdAnQeb+spRcmDTxiGwYwRJzR/RBuV1x9V6VN8Fy3ZUukN+dNz3Of2kxN+f4Fa+hnMJk3xDuw1Ml7+k3OKKGPUgbXLKGbNZyvMKX86W+ZOobVzpobcBy8FoLFxwphk5Ut6/9Gnwzz/xQ+asmC1u0ycc2hN6MmWX2rWmpVjyrumWoMH9xrmJuWamk3umgpl+dMedh4CqfcRTQnPyP7NsaH+hfMlVkbHTomcz1w5OiYUsqayYAfbFmmAC64w/lg/pJLbzsmPafTfCzyq5C8vT0+SnE0BQLvH2VCVmexRjdj7ecisqUlp+98m0madsDdfqEX05x24Xh96nBJ8mqCI8kwfUPbx9/8n1Bc9bbFwp1XlckPEUfEoK/vL9iCwBnA+ugSOo+m7YimXrqaRsyJyw+N89eW7Wp2lDw4prELa4gEIYrHykDfZgWHRTO+OdkPxzKKg0Ha9K/Mlxj1mVDILFzgRXBFVipWFTqESbAduv2Ik1vW/McD0Q/QP5pxSHT7P0P4LTa1s+J4ZrHLqUJ0Wqe7apBsQZNHtCsPAjG8bkgNFohSyyOFSW4DhSmIHmbuaW5zHgc/ahtWrQ6pVE1zU4vk6DH9WyY2pO8yU+TuiwDK/ec4GQTfsv8Pop9opjdFTLXtScufpzQNm4iXoR5sKLttgt71pmXzJ1bpduwAcKVCKS9OYkIrvoPZQQ2hnRvG00A8o/lBNmsNbXR7RZvOBG0h0fcTIIQ5jgiRChDGG+NjjDaO3K1sXkj6jj/jMe1/dLgdpdi1/4nVgRzAk1lnbCjkHKPWSfJJBTGxf9WfNEEAhIYwP4MAW9nkGZekp5tiVfUXSMvVSgo5ftQ3Yk1pIeYxupQqJHuolTui08g8TilP/s1ZPd/mgRaKFWsm100nt8w2DxLtRI1lf3N1jneBG/N57lEqFgVVXxyO3PeX1AgnmHnsJjeiUW0tzRkw01RLpRRG2+bsmpq3RWhPRKhrZS19kGmT3x06YIAmEG6S5j6ne0npUOUmSIhvhFb6GVvCnynki24mLcs3DFEvIcl3BoNPmjeW63DJAUEYURjRnV1v/NGm1dD5HR1rk2pxww3TiSn8uMdnpJgDlcdNGCiKtRdykXZR4ZYl55mNvuhqqeTMyKwhfkNwct4mBATaEHLwe6nlFlqEVzMcnl2ZlVa/ddqq/rOZ0Xk3DzfO3EogyKZKyDJv7w6KKkPGeqGnH35O6vYKFXKkEShSMzHWtsW1CiDBuP7ck28uvdoyN3oidtS1xTXXd/JM7tRf8Z3j5WkdyKSidB3lHBZ23J1S+WVjRqxG+i7Tw439hGUQqiJKoAP8UzRiQT1MIggkSEYiJmLMLlLgQYqpKAXUjOG4xQtHmSP3cfUfe7xhs8bUNMqDeEt24h2acFwkBJAuggMnqfu2Il8aqiSvt95cugqgxMSlociO3cGNafGBt6mgFBUuCk+6Xpg9LJymaaFdmVDz3oYi+zIaMRKTqwd1GC722Aaydu2DSqpDNzoGfZXNB8aO8sxoqkAns6MZ2VMy1NF6/+66A5eW9ubnllXNN9Z9FWiZ+5g7VtILFOsklvQWTpu0z44HHS0b4r4WNutFsnv98NLl2D1vprH96kCNt3h++YtXm05QwXxIUzD6KKWdtGmxhYHF51rJdc6g/Rb+e8+ajDg+oL6Z9HvWbGVv0VfEBn4kr6tndX/R5WKdf/meew20NZlPOL/q0lnmGsz7qTZxOst5FjSJZr5eUzQNgX/eFe5m/XueLauZang7ZfCj29L63Dx7nFrA4S/LMbd8C3ffJoQGm/v5n+jBc6PbnjU59PQexPoXMcERxR/C36n+WBB4q15E5YvYKNnMkDs1bhLtNkClfO/ePKJeZwxz1IiRq5PrP7FnQ1mSsXSPptYs9cLXHA8O3Tjc0H3Z9lgNm6jkmmZntN6/+ZBSWXRuKV3Lfb1jYt8h7PjShD1+Ow8p6Fr1TtF3THdnmfclxk7/Te9G4SQ5ummMmTF923U0obC2eWUSW7FpVf2ltGwTYXVplwujOqr8ZxfuDr4znreli3XOUjq8bxNNtHc7vuO/p24YABiZUUY3IlG7HsQfO8siJVou06p+O8D7sGa8OcoyPjVW2+n8r4z3n2SM661KAS9fimXrWyYd/RntMQ+NAr1xOmAn10IrX7464UdIoInrfC9nDaVSTHOSBPcWCOka+5PYplqMVulopJG+Hi8Qm/+k7DoaJm3rtH4i4TCL27ve3x5YQK0fr1wTU5n2jlsAUQqOGDpUYzNB8N8MwTsapA/bhMvkrKgjLOSGW1cV1UkC9CaYXbrqHAr8NXx3fGbRIXeXatVnceoehp+13eiQkW+ECEai/vwbTLKoht29DCr8OmuAy9ku93yDSMdm/HUNiM44qq5BBR8sdSKcDk3DyYjnawndpHXrDQ8ldOhH7REDmsLv+p2rg5JcGdpRs2gA0BZeQbryESpbiR0Y61qY4G9v86QSeIrDe87BqwitC/+ne5xuK+i3OUKq6GK5jmte4i8SwyB9m8l4LYejpzhBFqdbhH85cV5UzUwWeDkQq46OCmYGmZkbUIxaIOxlK8WGBXJzPSfW40lRmjsJtFMNqyzfWDCo+zMedYmp+tuy9nRkD/GCMkw9MjEjZvw0jt9K1ZLqdZOQZ8xxZcQJU/hlzOcUSwmaNkAAyLzQwBmjfRTRIY4A4JaOEKoY87PDpwAhN4QxCmKm+jnSRo1j9mBqG4Xfn+NQv31YzD7l58RW3Bqm596xAHyLYcCN3AIx+OXQuKEc+mWhAKT5ak93Pshgqt5Dl9Da9PE4HypgtNjYn4JOpF/a87JCWn+MyWaKj839aQQmWSnnuVmuYXbFaSh5HW90CceEEdYhrzVYwE129yxmevl2B2pED2hmbxnS09cMMIj0/T3c2BqN55eufMvXIHHKqInf7gCMOMWjVxF+LKrhmP58x2MrB9Fd5xrhRbCw8mB1chC2YVs17gUCqZ0N5We1JNM+hy2vIijGgDs58ANfSjeLYBsyFM1AxxVmE7X1uUVKRaaEoLOUuxXVyNE9srve7E+NFMPcgb7SsBUj401AG7h5Fxha3EVyW28JjEVr7phMZzKM19T7/aGAglzcEMoWpC3EAjCU+rH5NSX5r/DyJh+vbW+A6Vt9cK5aGKQY7UqDeQBwVcxJd2JwdxWeqMkEtZphOEKwDMDz4XlcQre4cTvX7SisnYbgvWBj5Ua9KwBVxFYmWY/guyl/unNZfkjAN+Io1Dzrg3EWmyXmTAibD0c/hY2AHWFrHlcBrddkOnqR4mpnz6izN4L6lCYlL7rEdDW8nhC6kbEytlXTGd1I6wXmyLzxVlsKpQiweRQmVoWCTZHa8XQhAVyd4zhDUF3uhN6OHoXY2he+d52wg+T2kMhVeh6fbpqPpwFnb6Tm2obvdvKoM4+PSx/BoMLdcUWf8RwNPghz8UHnpheYzx//LnT3YqvsB9gAynleYbAmNIuPFTyyHTP//LJvT83M5EBfMh3D6ye/tZK2/XkzDHrI9KevNtwYxDCcqxnmO1Y6TjQGDus8jSehGbokZmaVh/AWqlRqRUSI9ept3xXHh0ii1PrQJz7ZiMDDOZupzFUrRFOxvbOIOR91biCZj9rNvdFdcMB3CgWfeUTqNA0gFY5UhxOJobV2BfOKEprqCEmtSnExp84GftunCenobHo+Mk3HDbVgtdyGX5ri3coKiq1AC/+70f3VGYGmN+KSjFviRDX6ZLJqCR/eYpkvB54jXgE0GoWGKUWhcohfqgUaKpwOhwFBKBxvq+X7sF3rwbTRCcGBHHGUmIYqjgn6YzhcOB8P2prs4u9RmMpY4ZPSll5z3QSJMJXrPTHOMaIgklQes6FuYHpBD1viCAIeiQ9GYm/Pi/o2pRM6ZDoLw4QOG1Th/sQjnByfxZFgqAoO+x6SYLSVSUW37r8PShRZS1edC5d04r1OAJZUzxjnI5JzUKegW3edTQv8aZmM4OjEdE1g9j6tPoFZzRm2vhbYgjnpFqcxbxNuzssWypHOG1TOMUso8jWkDc3kkOR0NBSkwRHlTconsRLcrbXJideiJF6zSK0uoXz4lVPn30WNWxjes/Nl24yy4TCu0lqhG8vptIStfeZthfthFrz547tQTt55d902D3b69cUE58Ss5TEABuU/WEbwMYuijGxaKZCkPNWPsLKBJZdTOKayd3ZmIh75NYatPB6XW2EGtXeoXEFWKuBmGAk7GbJXcO60K/Dh3kF3xjePhPOrqHYIRc8voVLs2xKZOjZ+jKdZMeN9GV3u1jK0Fq2VYejpMB7lQN13pct8qv5WMJ8zzXHlVqvlPW3aLX2V+oCDBhi8CMVlWmWbCZs4wBiUy9CSbIuFLNkSl7vxkaTK7GAYGRTJidxFug0vEeYjSOH5mMPwcCtDv4Sqg0w+qZkVioq+p8X1Jnrtoay091LXbXT0B16SibL0aNjcNpqmM0Kiyw/B9DpRNT/PrDPpLLZj/qOtAhmTd6xP4D9r32s8NYcmGo/Fqxv+RYkqa4gr4VDvXpBLkr2pyt2NjCLoB4kfQmqVFp1U7USdY5UuQHFsHtmS48EDIav3q6hiDrE0vLvDcN4xwXkHKg6FGYrfkxNxaHX8gS4rEhzg0WyTEcmrXgJvxqDR7x4XsldxJGncQ6S75nc11xYEnHVb0W/NVYim4OZmKqfJifGWsTilV7U6KYpaXNQLxz1QAkxtQJWsZyDScPWPiam92qb97RaxmLvnOjz3kWlXaQDovlBSIkw1ioXhLKPE02IMT8YLe+wslBgQxXTE/w3for7bhdiZfuzBDlvIzFXBt1AVb0oX61DcHmlxxfl5yS55cuzs8SpaX1k7ELKISk5gQuM1FtNTUKHRjN+jF36Bq4MAOYMZmEMdxaBpldcE7IAWAwWacuxFXulLb2atiWS9MMeuXo/UdP9PDVK166mm1rciXCc75vIHmGfthvSid+ON2txuBc35RkA781mvCjbzLvjB3KQ+6XdPUdJDOh4tlJCJrbOyYAxcXn+qzNXz9ybNpWO7y+qLBHV94OIwNyBDG4TgSdr5Zx12lMl7nIXj6EM2STKkS2qYg++lkk+JJdmTRSFmpSfVJ//Dj4YX76BLTa1tsCrYknvOC+WmA7FQIhWmBFJMCV9Sn7BeAZqKmhZPDBTZsbhVPy6HPTY87x0H9Te9xgoOQmeSRJSp+9QI0P3UvP5ulF2oSNX0SFKmXhuDSrObvDpTq2uObhYNFzYJB8FYdZb9AcVeV+3zChRNF4vqRovKQVot3yFvrlTlGrwAI+1+x4NyY12J/cYW4ad5scQ+5a90yUI2s8SuUYKhc0oHaEFFS+G91bKxWgdtJeQAtv5G+p5yy8vLZm3kSg78Dut1i+Q2PLf12yvZi2oOg5rOGIM2SUVI9DaqyxvAYvihajw56y171aeSG7pjVlWZzmMaG2XdOKQSgGIyFYijGme4vAEuaRqC8JINTdk8KAdaNb8ncSeK0M0fcjMx8IDRKjQhmi7tRaNYf+dwf6jJPk+pQokiUzZK7PQA/PJAWc8S4IpJxwrCxLrFuvEePqCeIClwrdRNivAtZ90Uxg8USH/wQt9iFBmhQxAODiva2knwVvp51D1dLUR9/6COFe0CYiBKVSYBjtOF5g9CNrPs1mPq6V35quQJZiSyalcSPETC+mlk5hZlMS/7xj/8k0rPTpFR2OkvxGTKkvzIQBiaQbpPm0dO3hOLXo9mK2IWXV4ViugDpLveBriES2Uz8tQgiDr0qEJgTHX4xWsRjVu5m/lfXyv0OWI9maKG5GdtMfmwum7BlULmepCI7T878sEIBkwUQI9U6aBlBcbMPm3zPbOlzqMNJ066TLWAy9ppjgPTMXfYAthhUMzYfEkpst4GYj/iiONqqV+yfyEq57QXwwbVz5BhOHkMbK1faJ3reBr4nyrDk7qefah64HdCDj9AeX9Jj1JHcEVoAwV1VoTAxjN16Zf3mGIViPZqliC4dzvUUt690KvK4/d4ShOrGgOm+emIvEK9n09hfv+xgo20J9qa3XV7SLsNpB3/H7n+5QHdE26P56N9lvHw8FsahbuYQjpGNSqkKqvqxgf/DPPNAB3Eh38Mav8SBx23qjC8gnIoTeZi1Qnb6em6RZyH2D9f3cTyn2K4UaWgSxHBMAiVDOCJBiPgxynpIDamlNtbZefCCeRo2O/ZfPoO012YIY2ZLqibVaBFagDBW0tl5vdhf2IBc6vjJfuMqHDaevdwMHyilC0t2Cll47v+Kq/GKAzHL3BhKpgcEaDLqxdaBKHno8iGzBKS0Jj6O4UoHMlFqvxUv3ch2sdtCyboBjXwgMB2lsAuaL+0UTyDqmPNllqIVJ7ApwZcl6mUC2aboUCqYpAIp4MRMAlZiNoyqb4d225CtOnYCfp0kXhQIo9Kx8io2RI3MoV15c4VRDJabxh729rQBIlWNMTLcsZ29I1rRcvNM81SeQfbwSb2X+vnZOGZwF5rEjy1G0AZfdGC1V/q/8di8l3of5B6PCXGgCI4wkBnGMeSIi8rdf9h2g+aDx7XRTp1ELGnh9TubqHjyixlEEln8QBTtAlDlHhQvFmQ6+QlsL0xZctIlDivKxg57+dpwTOzKhJErVpD4ZvFZvcyaUJlVWGVVAX40SIRlXuSVp9RmYlEVIbFn+rXt4jf8fufjqLpNku3cxr60D8m/lLgQC5MHz8vApqfWYQMnzcVY4UM+0VLx+q0ldVQQe6LxBrcd4GGREdslSCI8O31OJXg1almweVZ3YIN5LMaYuf4QMm732hK7UqBWG4U6ycl17X/xjhYceifezeYwlW/MFER3AOW0nCfUUOGH+gK91o720NXhpfmZuGYWdFPViW8UPsZ8i6VU4VRRwVTFqLS1WryMakWha+tEzcgtwRL82dYF65JW2L9w64xir6CskLRmYjd2etHnYUBeyCuqgx1x0cfDZt69j/IXARjGLLoMnWLOPO01jVomEqDqX1Z41xgmaJmDgUxCAOK0P/3vIPhLKIwFq4qttqYc+65tw8pxsBUS+QGAopYBxGYRFTXUXOUk+ae+1avDzFu3cdzdhwntVabZiZx0NM2knWlR2shHGKWR/XL7gTKBUBz/oXku/iMeQKmADoVGFuPrfUAS4+Z3Dmx8rMMkU9lxzo8q1GNrAz/6RHoA0CaE/+u1/84VPHZGl65cCKEJbdh7MUujXKg6kMZHGElvHmLN0Jw395+RmQ0stH7mdnumpG4qU7v9G6ETaj87PXOfOZzZ3wi9fXyJWFnkA+UnZdh7UB3O6QLipKzD+rdJfpIJSZM3z1DMWJWz+1pkoPcL99ulsi52QRfvZsEQLdWOBv8cdPv1oXDG/mj81Ho428IOddpd6A8xwg2RfqVL/C+SwMsoACAyeKZSCpVjyPca6/Ux6hR1Jrb64c3Q+ppXNYGTAGI+o5AxZS8VyL9fo4xc1iF7eQFgOvL8oVdrb9Vj5tTNFnCAdjInnWRW/OxmL1kb8bsLX7qgkoGStIu56DDj9W5mJW9O8V9INkq+HrY9r7OCGfjd/T0dIJX7JRbIO6yBXsZbVShnWoNbMv1QjMzInN2WdbVq3w5ZPym8PfZWaAysz/8mgRNaZMeXxL22RYaiZVPsWW5kF4SG8UyYjCiAM2YtX61WSp3lMYhJVLI5vr8tt7QAOvLos9XoTbwjBNT8m3MgQ5fMbD/4545VBguB0yEexWCLLCSoQZdXlJjwShMI5DT5QUIAoe7hETsNA3bCsYv6N2PHCQ6FYD1J/LKHhNyZSzWlV2SZvzfER+cezIT3Arz7VBmRHCAv+VVQ1RXtkFE9hb1jH4R5wIdJuE2kLWOJTRig67yjvDf27J1ZfDs7zXC+FgM/lt82URh55aYrjY8LpTlg2knDy1sIar3SHRwUIXYBsKwl8mlj2pHwp+2J0PijLJFD9ipsQET3HKPmbimSyLqtGitGeeXObdMy4M/YE66G9q6b/P1GQYQB45tczDzhOS95F6g4+SGZehRc12tj5wZ4XfqQCcbwt0NDyyqw+G1t1l6Mj2I7VGKK42B+dnAr6b02sokX3xdmMRwGIEGj8aPpP98c/nkxzGG4Rla26bKYEKQm13sbIU+/Y+5XMhpY4WExGaAnJgpTBX5XzT2yGDy8jLKlKx32TqfMV3QEWSAYYDT1fTMzOHURFiLJr7ZoS48zNih81u/x/CE71O5UCoH2FfKiEwCcRl8cBwz0wXGXU2qIpZMXLVHLxS4f1+Fk6RClb+j5xqRGetTMKTnEfYsQkd6WqD37tUHQyrGFm3LtCOeiOKpgYWTKI9/EsNkvnHOWFNKTTvH/OFflnnhspBLe17MpaFlKOQNxpva01jGRuIaDJdVcwkmY/2xtTSlKHLjvurNktgs/zvhO3pj7TRlFmLGKgqTxhieFRbECgrBuLMyxvnHyiyBw/+AoXX2XTHOVe8yEqpWJjQG63ZF9DWmF1zC6NLowG8E1nu0z3Y2e8a4RcQ/jj8lE8UGQCB5YbTb/B0qGv5FQE6NLzo9p8KHmI43bqksXnYkci2oC8JQKEpAZ9xc7akqahYH0gztL1/sk47XP9x99tilq2fln6V1xFaNmBPXx7oCn8/r3Pbn5PR4o51yYYJ8rAleGRVUOXZnY0MW8oP5VUWlDcpn2JceLKm8mVM4EMYZ1PBANCqDoolzCfo4mXnb+wEdJxZy6Axrsd5bvpuWhbQNcSTnhABkvLstk64ntnrsKh6N2gORe8SrKwPwGw+hK2O2/85DvBqYzSC1x99VJ34pQ3nbfTXJ8w7NdUIC4qc2gyz+VmosACeRe1M/3yc6/YaGWV2cYZh5sT0FMI6wbZ21Tp9tl081t2MvGvddRitxsqrnrtJx648BT4o+IHpCEFtQ6tQh9weh/KFjjj6H5q/DCTBbKtlas26fusGCS544hQCJFnCZkLo9Jd5Qwi5LXC1bf0D+CJP/TPko7ecytBcLDgcwOtOA3PuFnBCNERD6KE5ph/DFjrLLVoI/tLe2wXN3fO0KtLpplCvEM8/+rB8CuWYIY/J0u7O5/1UAFW2XQ+wYpve/lPnRw1uTvGpHFD+uvjWaDOaQrApH0xUP8XomhN48Ukvm7AB9wsgW4VT2GP2G0Va4abM4IzMedDzioVyvney4hfw4sDFKvifyBhFDEqSV8y3KvCM83KDQN9iKrK2odxbplZP61WLLHUWjOi/T1ezCINCz6JpY2zndhpCLFt1Rf+M8iuxxOCb9W0yb4SThO+vnNQy+wC+Xj+Q9a5hwVRTB/iYwZjA5NQV7cijkqUc1HwBCJ5JWRqSgu7sD8EAnFUnAaAsgfBLFKwrV0TLXBPuiZaqZV1gf2564dBtuhglML/PQkzUwnz4FhuLNiJtbtw0tQcg61l78Qr9QAb4r4yISPVg0FAGMXqLD4s6tyws27b9Qyzfsuv9GNg6MUydpCOAQz5DBtcSBVTMiqS4cqr43pzdjcK39gNPfk9mhX1FvBsQRCIovf/3N1DiF0wZsG5/shi/2btKGjRULlsg5zzm/7mpPFosf8ytIxNuB4i3GnupWeu3gV8cfJPPXstIIfe987nX8k+2eew1nGw0DZ+3Bymf31E3J9UZgFlHHUn5lCm5UJln/iHV7fnjRp86DX6XgRbW68e4r1wz1z4g2L/pT+5oj9QFSYZi+L2B8mg3qycta9EPpdXLbuArLGmFYxevmTyxX1Oum/RkKavqyoSQ6huFAxZRzGFSpcDrMUsdMANBqNKMAfVBG9euGBzgx6b6tM84Q3yS03/S5he/wOEq4R+OyYMHriFW/7bpG8CxGp/1wdeRhlWvZOxr4cBq8t/CD9R9NfEYQH2PL2588rezGdSYj898wriQ6IDkcXeoQOcupafk3BXPleNkeJl9vCws+HSAf/0mcwcN/ddMmE27iyhXrcIZHKCb8Ni48LYLRX9MoPrTcaWeXKR6HElsaKOuAtFk6uzg/xzeZtStbrisjhAr/6GtRAM3I3bFCX34MPMKGtZcEVHfnRHFNuRUdXfnBFe76n1F7aXoQBK+0q+TbcaAIXbpOoa76BjCXGBYLgRXnxsocA4ZwICL7+oc6fdk89J/rpDrva879N/MvuOohEsnXgRmjda12WN5h21XoukmvBKriox9nAgUuKixUYdo4Mq7kLkGy48JmDIfSi2be/oKbfppjqsCdt/bZrwOxW3vrvPrbR+rnsqN0q+4RWw6TJ2Cu/226lHDMXBxhQs5wTl6KZdijdEVPLZuSTvVxM3rbdD+kOTHDe1PHm7EujyLG7bVnoTt6Uq9B8vQBA2NJKOLK2FmNdnh0RGJ71kLoybb+oQ1MWhepclGTx0rf7UJQlcM4QxqWJtq383e7/NlaE9eOSXG+eUFw7GPuSDb9Jr0/8X8p2SIQkFHbko9tZi1ZYZLcrs4YuW4PI7OykbPpqvK4hF7W23d30/Qkp248l2yWU8Jd2kkewvrywiq/++bNc4HyBoTtC5XlfOv40zK2fsAgfc9R1K+VWsNWd/ckc30YV5Zvt8V6vF5vwxi5sSiY3mEUG+c2N88SWNgfyUCf2nwmUiMCwSLqMAivoOfIPLfrPjVz/dX2UNUVHrEeQMksgbeSntPDTGnhb2oDIgjlsWKP9AlKlGXStm/sIEOxUyC37yiTcx6iYMf1Bk1lbq2ed3v2YYaxEu6njFEVpTB39h3vgodJGHk+npk3p5dpyotTQM+276iijY4IkDmgxrQ3qpTLwr3PmuQUX5b2+WIgNwWM9QXEtT849oQ1MqgZvC47WTGVF7f7UY8xKXldpSr4+OtT+re+1swu2zrikU6Zs7PhQwzbpM3gnmzpd5zbj0MoDCKXTxk95mh+W2kZMfy+fKNveIa+92BjV4VPS78ACmKnkCLz5Hk70M6du2J27W6WFhzVoNhK8HWFagQgQ4xlb4fPJ1qEflnsqpDIXcKYYsi7hpo2tqub91miV0Fe0jhevl2FsGm25EFU+Yp3ju+CuWSZPc1sIWYv7oUsEo+kJqDjTabbJfoxeN3HTpBz7huy88Y/thb6/LUz7R7n7SZVSZtIerLodCQGx35XO3Wp7edS2/e+Bm96cEwxqSGhpU6tK/8BZ0yf2cw9uwZVy89R+RWEbimAXTBoyajzHzJGuzx5/YoU/Xv1S/L9U5glCe8j1FIHIh5qtdkb3rLjj7OMF/QD7P/X/G8JveFLiq9TFNsDYs8KispckzOk/vJCWU8QkQ5D5N8hWFv4pJpkoAnjNFCnI5eSRZl/m3eWMV3yYEHBpuwY+rPoyLR89SJnUB38C8HEfdyFxFC7zGnV7v3XCvdD/J70Bs0yF+RzwO09SZiLMlbhj1a7wQ5+gBbMXnjcRCedNxndBWcoYtJ5XFa/yGbvpvnoZD2VMb/tgFkIzPFPTQ94WVGjybSEEe2+H/0tmNNMZLQ6eqJeMpnZR2k9cP9Ie9pGBZLh9xnENUw6NARIe/vpBVMPO2g8sQ4rppyihqKwnETN9JaL0F8Di7NdbLrrxekDI02SAlv3dogzi9FSGX31eyHKQKcq7E80bZ64DIbMLwnFzWoBABxJ3WKTDF+GQ9Jr5sHnd4y//dUivXfihvde4iCBSN8e+/zOv7nhiNmmZtEhwXpRP8xCj6/kxzmb0QlfvD3mDOT7q6y1TPWnub/yslvtXd3SHw74xDTtzCkrZCQnqedWclmJHfOoMeIbnDDhjjQcyvXmYV9mO0JkUX4+7H43Y7KvgxPESqO1I9L57w4arAnqHNX2g7WqjlXRFNRPdOaTo0zu5kG1/U/yuivj7nA9Dvij1EtChVGo+H0dvrzVpPXJrnoClxHT1odB40o0PHbSnfyWEDphWh1ZrszjbwwyTC9rio9yPFkpOPyFRQyirATkRHCWj8VHxKIiHqQy/YxnvChmS/IVxpV8y213dEHR77Ln+ZDV/3KUuXNeP5LNleT5rlut7brK8YmR4Y2ptuXY7lcTXr0v9xn2jBTNQ8OE+F/4UEC9IpylMb4jHhZrLq9jsBSg1zh9fRh1qltCmHWRdVH0HR7nrofqDS69GpeR3spbUnLj7SMLvj6eV5yKqXXdUqx9T/7n52Yw08QRr06sTVx5RRzxWA4f/Z1JFnmSgY1gvJZ/xzXA2OD86TVgVKS7nhqa7rrT+TJdMdPmaaX/cowl3xN7WJJMr0KF2JUDOHdc903rotN2Kmfmic7OqzPEUJcxz6wkObUyFmLXL0i/JBCD/lJx04mKoZ9IbxwPNRSZjOKfLTZmbIH1AxrV9ZhfchjUpgcKSf5h1opfaMKTf7kvaYSne9iGRVRtYFsQzTBIln4oWfd/5nfU6+bjyw19YJen+5HebiUsx1x+q1gsvKFVd7ln2mPYwanycJIL3R4eKl4BGCkv4BfelE7tnVELAh2no0Qf3kbfFXCfWyf64RNy6MBecMc4IHMDR7xr/cudPeJbmgFskvwJWhF44tnt0eXM1D8bulnQ+NUgWTt6CE6yLHhTzQWB3dxjKLqbGYdYPSf7X0ySXHxY8GqBpuzvYeV2cJnryiSJ7vH0K62DOthC9Bs5Cay0E0+UNDGDfYdXCX0nx7y9/5HDkbYiea6kRtP/sClFNBWc3C+Baprx89wfO+AHEgQ+cgD8sFuTRSexyrWZSBkKmLNt3646UmhGLORZnl2wNDayeFksKrL0rhFQ3Mwy4b66HjA72MCzoog7Y4/mz3tilAL6HV2wGnTHep8lNmptwfNbEtX9mEd6GNU2SLx/iBEVCYSO5KGIpRHGIP2pZnefngpBKKLcTLIEweXOUothNXRU/AxUVtnmXpDhz94hF+DBxP5H0fnV+9LCI5nLVm3+/brO36pm065KBVMZa7S3oct+eknLaYhyFEySJue8nh+obgQCQ+CyWcaBO/UyUkdOJIm2K+76MeQRt9Nyl8fRdYwr+qlS8E3l8U2/A/08eHCu0nnLQGRuj5ZzdGeHj/tWeOxFkyE3SKd/LLMCmFHhe+Q0bHV9FUSVNC65+ZGH/+OWzvwzr/d6Wt7/DzYNSxSPcv8xYlKlg6r+h8pybfUX+yBefC+qbmW219F/BOhIm/tOtx21jaqLfU++ZfjaceNuk/4vwiLViy5GLIAh9f/r3HQ+6OPcy402udONISlPj2IKnOWJNL+XwuXGXodtbc69gnFL1B59CTkcxbrbHPEEQeUfEjyeyHpD+f3G0pbK9k3NawyyFAJrKQQwPlrx4DFkore6i/HccU6y9u2hn1XnKcK8EGXzg50PgDYLI0+H/PLrBgfZ1eR88/jlQxbmjtrZzLQzvBjtI6WcPV6BoeaV9Ok76L5YsGoj6xh0KYU2NVQEidTRnpIwwrsl7n/YYMlMU+Kctf8HLMbJ3v61ASo1IsbX494hsyZ+MWYtE3FnwzyMZDnT8pepVds3A3HnWen/+fEzkXicnrQslC15Wz0ibKh428bAz6amsMGmbzGnDIbiSyBn7P3m9aZ9c95Pr1tuqpQezPle35SQ7UPLQ+HMPPvOa79RvMF9oCefONAbeE3eUf40s6Vsc82p2Jp3ljYSu+/T30kjAWwWlsxPtvkxj6HS9fc2k5JGiN1w0Xef1T1GDcjdGO8PhhGZob56Av2sHYH3vbx0dCD8CDzGHwA+9MiycpmsKam55uMGpAoPx/3HNkUQtOUs15x96NiNLpu4tAWw7DijcP9CjbS7ejOxFYBb30nvjAt7WTkZ5GmsxwLPf7IfOH5+9VrAoKdwlbylNLWeRgJoYOTJa7rFLrAAWo8j4bOHqp3hXuuql1m76yq92vHjTryFtzwYBKu7OZ4U0SUsdSjmdU62EzebWqxVCj/x3ojyGRQ3wu16LTnYw7U5aCMOkzOPaa7OFRz0Ul8SVbPj+ufUgnXJ5n8fypa4T1X8k+C3fr9x/A6gxAQEVgxJIXvDKIAclKvk+FTjeLT14E0oHZD3ngy8/26s4V2dv4hj24hHJjc1owCf7PpPZydQlhPavRNcjfb9dlMu+FTONxbiSFUyLrCqE45S4LPRQHLbp4ciaZvsfb4ZcgsE8uPnxn92tb4c8RQ+H/b67nMIf1xjnJ4777krBH0hZ/sPu5hmVsZe8CDEAAX1cix8YYInfAHxRENJ3E0zGXOCKafQTRs1XMs5ac35WpOzjjtEbMTbeoSnXn5GqSh/3vkr6rTv0bhdY+FzUJmQI5/0hISvOmRPf+EN3zDmgg5WwZJgiIRhi9ZeBpBXdzZVnbSrskfvuudWncOMzJBrj3SZGD+s1Ej3kkHitFs+aIYqoHFKoYhCD/5ysehVjaTJ92OufB25uEtOL11DNHaIsoWrgIUn0Q+ncm7Rz9Pzm0/JzLodyAYG0UnrmB+P0kxkWdIEPH4T8AjHfQJMAS+Y2UB+Wq6yw6ozrz8p5qrp7lXidQlmeyIPer7GbXUH3Dumsph/rvV9DJq/Vh7XgaE2O3BIRhE9ov5r0g2fz9lIl6kEqafxNu5751IXo/mZDRtknpv3z0I1dKf/o4uOiNiPWwsG1sP3lbko+7+x4ZvPV2hrm4Jc9XFJazIYk9uhuQ9TRMIo5fCe2+16UivFTTHHiXzOFuy74uJDJP0v/QK6yULsF7y/yYvqwjwMuZmGCA+Zzlq6kf24JrxPPVRFqg5GtwBv5ptJigaZPGhPz+Uco3qi/vhi1X13w+ZaMpEB+u6d+qFOY5e1dzG2fQpvPndXS6gtgJEBPRNLYRDL3VpXWl8JIlJ6NFDAE97wuS3Wk6jv/SL5XHdt0reknpKTzmfNkY/iPxVa0LV3piDswET/J+XxHhy12+1662oAtVmA52wqLKzOWyBT1FtUoK20qwWzGjKyR+r+Vm+8xKn3HNWVbmPK5GwZiG1U+zIE03rODhmag3ovKgm+ruB+TA/PfLYPMe9ObQp23WuAiAhNtGUDQkCaKUIQ60uEimIWCUIayqKK+ZItQLJsoDir9EGYHuYPaQR6gZY7PzoYCFER13joiXTr13OOPwyGO/V/vm5KYD9UlHO0MXn+yDblmwipxIumFyJocU/s4Vesme+nkQXe1MbRoq9eYV3pkgDo1lde84XV5gSXqPFDz72VunjH41cPZiXrOs8/jl2DRPdiqS9JVmDoC4ZgxS7KRLM4CNwqtG2u2YMlhpyk8oHN+NM09uSxGbaWnjwv/+ezxNPZY6ImSSKbiVszZG5aTLIkkzha6T3hOsdEuJ9+6/MENWoX6Ft7KZ77oPjrW8/OTzd3tIu91kf2dYiA4nxSWDjey56umao+JfzZ238wBExhicOJTZSJ/LbejGD9QZS60aek6Zm1OJ2fVfzmyy/O7LNExFlz73P9kmQMiwos14589fPbZNLMmb6WFKmd99Y127CXnd8sATJPO2gO+eS406qD758tSFLf7L01vYlaX2P0QTJz7ibz7ZSXwAMa2qOr39iO0KW8D7+tbv7P67V2x1kWE2VYKgRIONh3ETs826JXkfx63lnvAjq3BkVS5GnZBpM2W6FKXScv+iPURSRzsX2p2QFCg8lWZuntpXXsO79sNDtAs/T5q+GPkcT+wB2ifjPxz05qA7anNw/Hzq9+zfFQwi5eJnCtKqkg0yeExSjZy6O1c0rxVb5/1KXflKBOb/iFyFKxAucLvYDELpDzEFgAe81CqsHpeVsHnuaLsVWIRf2Oq6qA5v1PO8j5zwMW81KjO8Et0+GvfOd4lhdvd6qeWOw/rtg/NhD8zGT+vPUbtrABeUjpRjiR/hYQH26vjaMt2LT8u9C4MUyWYJwE/L+wjAawIl+e3PJK8nF/1zsFZW6B7KQBb6yN/u1MU4fW4I+lo/4TTJu12f+ah7HxF3RzsxAJcepN+c0pnarPC4TWwdAQdvx7x4FWiG23dT9Pf/tSFvnHX/+Pn5fSHmU20J0+vdnlyIM3w1wfymDPA4HsHD07IM+mink8ejBOjGNxbjUzyca4TCgKNfA/EMUmzxuMCdnbanjuhwjfP5E1zljbZtjzwrGduar92LHNBHP/lgOnp7teCz+nhr2PrK+XP7NcI4Y5nnbnS+Zr62kprOGX7zfMqquQ122fpf+t3pS8b+2DnpFxB86CAufep5AbVrnSSXtBpSnORCAx7RYMNgOJJSIpcQ1eCkuyDNO8HAZGB8ZwOLGVCwM5Aj/+tjQeH3IT4a5+V3jsEbAb0KLV4Y3tN/wS85Q+FLuAtvl4R2GhW+W/2It6b1CDOeG5J2yZ6eKz34FN0YOL62oivL+YsrnGQNWXYHHtcRCfku5zak84Nt3oPudT80HW5pLRj1IhAo+NnvbeuXwCv4BmzW5suMfvFSbbsXAcz/FRwZGy7QQT/v1dV8gdckAVabEmen+2dm8YxfSQiHCokf5yNnPw4QX2LbBODvWYlppSebO9AGi3zS8V/yijexTGh08+93c+9PvsONnKQG8P3mvlUCIyqaY+oiVfdKZhgK2vHKbbvTohb4gIlroQaAKfnh1r7Iep58QMX1RW1bw85Q3rjPo3kVQS5ZTW/8nXegHz/11EbufhiV++6uCWomdfrEhfWMcprcge3zECP5BDcpb532aPnfQjmsMmU2pvdMjuVk/mVI6fy4mJLc8TuT8dF1zs/DAskS4EoCR4Hl1gp5ED1fmcyoRBluIFDommeRq4yzjZx5/ja+coY28RX0WssMqF1ZTcP5AbvOuAeVdXLBXdzRVvg1KSKKN27KyOZSde1K641e+CA/neNfEFQFJpjFTW043iCx9pFxfzoot8uBrE7DoDXWGJKmpflHdTsnC68mVgxVnA0KaBnikLN8jeJyaB1nio62pnyxSNrobkzcyHmT7qLbq3Jindf0/klIeaUI2vmO/oxUa9WfAf+P2yeFZvT+nK8c9I9Yn7uWaP9dLLJhEvhz2hjumLmILRIBy8RRr7FwbwmZ/FYnqB667p1FnsFNbY1jXZhHd1/uk6g3XCjhYxfMwqw2WTWmDPsMRdt5kLBSIlBPhW8KKRAz+/u4d5iw9dKqockjC+cAS22XdIdc2aYQZWAd6+pM04p6Ffctj31N7lNebEeit6bu4LWO0wendjqUX8wdD2uSzjDTFHXSO/yJ6s/CHaeyeKrChk3MwBmfrkFC/0RDd1Qx37CsJp0b8wrAz4om5/4az3/dh+mdxcewR5MxGcPyL/+cV5p6foNLGsmEL7Lv9ic5+YzduxvHPhw0hiTgRQtQ2icLq+30v7KmE1kt0bi7T88Yt2ChQ+Zc5cqHL4nUE/ViOk3Y0optk6L7LDLstyTZ5KTvGx9uZ3F6oNTneNrBcafuvIKk006wiqwARaStz/uh5CIILY7T0HtKy5q2UpQFjJHTRLEzw6BxreQ+r9QMn+7OjPei57DN+H88a1BBN/lIEkW+zudbeMAGZ//yw3vOLH9x0tN1sf8JBUlvu8sYYePnt5xHxDheCXljUc97y//9cGuBalu8MrbSyvZDIVgy6JL1n//4lixITTsJuI/gH6RAFuNY1Ksn+yxTeh3r2tGXerh754L0nkZad3Ms28bdUkNJ4+KYlTsz3/zztwt6NiKd28KezHyWGvSDsjThbXs5gxh1FI0o2WQq8pvYRd9jN2t835OaENoOLqPVxVdu9ZUB3+0w2FDy14/8Xx++B07feLJCwAeH8whxBWoLwDc5fmyByK5my251II1d5QCV3JxOF5kaPqpmqx/tll6zEElzspcmdN8QPb/H4Fc3P5jMir/9yX5vPDi3MKEMJTfKQhVAx1+03nkY0k9+UqkhBxqhm/esRJ/FjdDAif+5p3aTnnQRaggLPvm8dT7To5WqKQDz3lbR3kiksTh8t2IKuluRK2Fc893m4aq9wr9FlQhKbnrnTo+2tKULbPI0WbMflfkX09GiM8ZVyxmfJy956uE028Fke+YmpuhMVnwqGjfgM8Pcr0jsLS08dYG4grQUd5lp17RrPxgdfUXYgHILXdVnJzUQF68Rd/YgIVtwNvAYVUpmCrFx/RTpmDPpJor6/hCYBmOWX4oInIruoKCCqI42k89yfBwsEScg2+UlXbprsV7LBWkg0jCjp4e1Eq8LdiejOJoM7bNQINJ4TNmApSJRFEZaiM+DdbEf78m/0HfRDTR5ISV+TECz8o1CLOSkfJ+vRRRY8Hch7V/l6B3WQrwh4c80FjsGKG8+hyCj9gIv6mtANCJislrKC/n+KDRxcZd+0lac7ymSK/IW31ySeKyLrSnK5HulYvvr5If49du9gAC7gpUUpGCDNW5oG1cdRLSVRSDCDNqdSeSm9ATfaYCf45rMqnYmOC+B2Vi0J4neSdVsekYQj7sK4yB7cheqRcLGcYvrOlXq624PKzAivhvV/li3mOJilVAFdaABfQzrlXNwCa9PWCay9Lml+qB8XiXwvrNwW48AaF5LNB4pEqt9tpfIecBRq5U6BVjcbRDd6df0PstegIs8cq3RubUl182XRzyln1wYJHm9wkw6+yLD1SAfz/HgiWcZ2lXtQcqpwNxUEdYCNbJakkdkd4lxDYmtyxFXfLk3a3PrCi0RVNOfJQqyud8BnJRZdk2YgqtoippLcGmsMWAXoeVUjmU02ruPGwg3TNN5ifmXgvk55kY8dSbd8Hzv5k/lEnpjtuae4Aqd/T1eCl7rNZchC22Qz0xzbSQN4clyFl0m+YQw6i+j+OjKpwDJ4dq/L2rSyTP+JTUvi+FbQllKL4YI7GPB6cTO09hNI7hKeONIdbUavUDIKXHmAxLsCN7hxO9ELYTHk+Voc4O62I1jIViOBaWLpVPBdeezTHg/Lc88vJjIJBos1eZWki4HbsiBmyIRPHXqJE/b7KTs3/+ANtBSdCNbsFiturfxJy7647f0res5P974UH4w4OxB+jwoQDDcseNjVwhHazPDgjOoAaEfXEDegZmYT5yeGjSAqqKkyQK4536T/JQ7cADlsSVEL+58ku9hBj/ymU6vbr9wdHZU7fTbRE7xrgcqmRiKJaZ8AuoQCaEKVlgygIqj1ueRFVoGrDDCI1aHdSZLHAcNpsEbykHt6xITrH34dYpi+alll95X97ImHZTj6Kq9kaxPtWmKUPVv6z5pPsqpQ6I2NjJVlC0tCY+ecegmKb0+0OzbWgteCAMsV8AAp/SCVCuvCqDZZmEoIbv6kRKEmKbuMUgsT1YHW0Qs3lea6cBxLquKU/823Zs2aVWtm6Ku+QL97tKuqk4f7+V/Q5RDWsKxXZRsFFoWRpWnWw0C831cCGG7gbTeoEKGhPWO2O3ZDfgb/hc8gHrKykm0qJxppIfgpNcA2pZojJRb1hHt+RHWDiH34q0N4C9hfm+4YujNRw1Okw3jGLEvg7fQ6mF5JAwB+kqnZizMAyPZuN4fZRY3CJCWGyUCApPD4zaVo5lr3Xs0XPx3T+ge9jZyFATxaIlCfRkbnzuUFx8k886Sr+0UN4hkEllHXa+NnicnkbQjQg/j7IKo6NyoiV6aat2VFR25PLAU/cADu/BvPtyfMiu1sqoYHFbMIYenDYZarWwLPBQrkVyC2qIvoBITkRGugqaXRjaOYKhJicM4M7kfYQoLsTim/k3ZCmhvikqMr/Dm6XmB0oiGXxGqUkKnjl6cXgv5t2d+/AzqDzaLGk1S0MPTVlhtAK8mEqzk2dtsxAMVc7cdZuuyLOCBLanTEQdzFBA3RfaSBMxpUzYFJlmwT3fMNKUDLvgAV/12gkdRFNlsVXaZhVFb5iuGyJttYniBSBmVjVp4hrQM8dowc3KnxFdthHU99RSfltNU52kH54hQjeP8i01qpImlalYzVCnjGoj0HBJbIi8fV+xQumUNlqEN4pkdafi76P1FT22RWJsZeAg5nwUvexnKcCWH0APRVPOKkOlvkofMuqMrZ1KBhs36UyT2Cd43Ju5vNt5szcDu1iaEErrJgwWjQmrF/MSEWFXN5knvWz7A4ZXEk2Jm/TC47Tp5YiW1Ieob1gdGFNhOvfwldYWdURcFq+X8WQbYjHPnHJcPXLf3EXedDVsJQmVagTsMLOIw1XiTvGKcAtLX2c72fPme6j+hK70hbj7cgusW3KFFRmT5ginUftElh4Rk0vgjznrTdfL2yTjh4xaSZ6fVFYm5HJ5u1gm3x8TK5K3CWUyGcBnFGOlqTfdjhZPR3tPmeXwHHmFTVdm7/9ZlFvEkKUiDI77idwyu1viLpwsapLZXRIX4CS7Y0BGcaK1eBcUxy1IeOG9d2f6Jer/aQYuz/T8/YkAdLkuX7CJoOsRsY+k80CdCZp8XbAa5nlLgFI76ZxN1AlJEMs8WI06YQIltFA7jlLQj2jYiZxCACJoi04CJa2EGD7gj1SY7jAAWwrbMNCSJBrgC/VkRixt4DuIgxclnwqreCUX34RNfJzEeaYRmoA/FZWGmuyz3aceyk9p5dvIOp5SdlK4I7wD0AeDFEvb3f56SgiFZEn0MYyQBbVdybnmdOFtgeGI+qIuNKtIIHEUFsmod2b81pIZwG1wn/dkQL8cHo3zdpDK0jCaiCRQOf4COZmFbLfJt1sdWerNpKstFIpbhFLpg1ERbBYokwKV2JsJQb6xiJHLank2YuPFyJfCGp6HeISZJEnybccV8YRBPIGn9Vdsj7zjTI9iDn6kltN9mRQkbg/FtS+DewXY60+rbFP5/z6NXTk0o0PXUAQz36HFkYHpXYZdnsWoe4NedV7s9PwwRpvQwArYzdZwkqrHApIESL8N/sp7x3dIPVyQ1i4QiZscZCVvCffgvehDdoc0wvlp7XyRsEmwW9kbjjvwDnBQdp/fxbSiaDXioFVBSMDZyaggDZLr1ZiKtapYVbJK1BL/bNUW4AxglK7IRv6p47QB41yjT4+6Hrj6qpHpduAdggbleY/i+dmIv+ynSd/8vhWTk9AX/U5c/Dw8PO+fS1Kjv/5aJzhcllXyI6VT0I1ybyG3d3nH7esffCgQVZL2D6FTvmJDdXo2C8zRUhmp7YhnCl1UShxYLoLavlRFluw100IzdkInMkETckHFMPQ7A9kNfEJQBVk7tCtfQahRVA5fK5j6t1T0CkRFszAVn6/953r/iYQP2W/nS39n5XecOsz+MJ/5+15Hz8nDrA9X0Inz4c6OzigoFGtRiBXJckmpZIq4VAyMxm6DXcZWfqKIzEGBGLXXhMgW95+P0q7oejW5ywEdUGctzYx1jdTMZ9kHabWS9LIQWe8WOPTom1BeGu3n99v7uf1Wq8c1dE9qEIsLkvfidMAAiWWtVYjlLR14UmHkhEVIJ0dyfzEqRFyd/+rj4TC4jOtEzvX4kmIj3Wh07mBlFynoSoPhCa8WhEsD5HI5WSE2KySKZIm4SNwpKZIAb3OrymZPKzexQY+rVppwhcPWimD4f3SVxM8ZldlUyCPBnyX/sULkMhcqvpcPDZf50UbCZ8heJR7kD9pYHt4gx89fhVyPtc3pjI7XMEPFalNRfJ6f/xXcM6OdvUhhSvv2LN+61xtwst0ICMdxirEayVhsaiIfNJVc9FE1qWTFsDzrZJ8Beo6/yFZ81SwJ65AXe6Eaq5nEQiUpDV+FEShkz5UtA4rl1CMIeyC5EyPTgMCd94hznVmAQJcWtIvzPW1CXVrYDvaFXRCW3vHD36YUsUmYqnO2tNrGygqcOz7WWqFs0elWYwAsYMZGNz6XFn2ZsoD/24+YQll3u5Y9ZDqhxZaT4FOe82hC1tEFS92Dm2PfPidHAwP8KlPElh1mEPNTBYFCPU+nS/+Bnz0Y+thq2PvZMVc3TezlBr//YjI5lVZamNVdfhy5meYlHl8Dez0/94nvpM6Sq0+nUgqUnHalOEOcmS7u4BsUekGv0ll894pokrkcr+mitFB3XTH5rsRbztKLPrZOULj0oqQgaxEW3ul83lR6UWpbTvougG/XQ6XKju08/sckP8cdYFBADmOnykbTtTl2sHCGVJn+9rfkrSOnlAt/NT1seHXP0h+dOkTxoALq11NvLF7G5ZWoin8svO8BWKpmw7q/B8/oFfLprb7z4Vuu21yXVycfszxfuMT5lJfk7sa+NEx3YLeRzwtpPKsSE3+4447rpYwEsASJ01JLv98XmNeNvL/+swr7X1WkWbGwju5lS2Hqcy+Iz75TKX+oinBs8YKlWR5mz4Udf46uKqa8dNyCuJgJnZxiO1Ao/dAbfTIHM7Fo6ZZPR8oP5tfNWzhCrPK80RbnV2IvwhJHplcsuV9k1u6bYCi8hxXuzIppUB6JEtCzLJLETq5fPDClee734fE65+LYppFGuh2MwJi0EbXfIt4NGD8RvCiw+AazpfNOay4FCP4GVOkztm5BxGoCn4xM8/qt4dW600dN15kO3MGob/PburN4nsVmUsgXoo19BenGBj9XTpquDmuivc1bfHl8ko/Uy8NCdxLEbawovPyyHvFSAynCPdOXFjgdRfvPnMbNiafoSlaNdUgn6dRut1XOl9CRHpvApIAy1raiwe3cKcXhreXL+we68zst8Q/xF3/ui5+l5SJvWWXodq+b64SyinJefqDahq0kO3Hoc8S7gAbVG9TBR3qeb9AAGNWHIvwwWrGHMaQjQpespD83A8+Hqo6ne/8sen2h3whUspyiIhpi9r81szuqPRXbrBbyfPjRZXyMNNvJ4g8iCOY5Ic/MasXaPDaWABzjr+TP+XcaOqvR2jQ6gZ45GxP4edE2dNRbiMd6qgpnYexuKO9UFGV0J5u7cBeQAknThyMR5WY6uoZUm0OCe3E4bUL9iDYV9gf6UX+oH/eDJ5Qo0kl378UuUWHDFkRvFeC5oSJRgaC94Rrr7gVG4SPZ900M322Yun4mHIoglcFbdYxPQFtrKtnZXKi28M0cU05rqMwmA1XrvGRMfsz8hyFdq8HP6owme7eSPfaOwmDpYid19pmr//Tcx4//R/3diQ0XjF52nQ5pK3iw9M3WYN4/xxJzAawWMwdsD5WO1VoXqkXKHrSLFKkKmlUy1UnlPExvE+C+oBY0HBnGInL14LGRdMWmtBylp3TChXGxc0pwTocKLihe0AJPCoDMEi6e6i1yDY25tm8eyxmNAwcXq3REroJpM9iDkUFaBG1X5cATj8DqSqzp3TF9RqHrfCSa8a3LKQIwWVSQZKkJj2H1jjsfcjC3b9nl9Qv/UIxxsyFc86bIkWWSv32bZv2NnZ++0bBGSLLcEDsC9oVQN9yH+4A/Yl4Dtyf2l16UzEtJwRcqTDXlnc7YrpOsq2d4LMDsY/SkOylIujgv76GK++CFmm3ej9t6Qhj2hpYQBRgHiOhAPrVygQr9GGoXFJT1oXBRFHsEla2gR8IjRoXCJqzg68Uko3KWsrnfIxcUsr5w722puZpHrHA01Q2jFvYytDlPOTkDZc9RglmqnmsVgaFoxbJwUkltDuRXjLO392H1BwUDhnENSOMFThXeCT1SsmbegBCWXghDA+c2DD4gUZBlbnCqYWYD5XzAiuKG23YccuW+2JUofhprICARiwyEuRiRqQc0DsiVEn1IYlDNp+mloPvs/aXNlMgjRy56HdPptv6cH09/LtRWJO+vD8vutU7MWfqCzfKsxTNBTmAvb06POgUGZhAkKatyki+phQmggAIo+lGQscGmqolBpFGBnukF9kJOxVF1viUmNomR2CL2zYnoywsSQR1AahXu5lcGgPSiAFrbDnZhYliZIPzxPU+Us1AF5tx1v80QvRt4J3evCWnTcMa4d1wYRDa8rmWOy56wiWNpB58zTbkOXFZXBiyFjilssSRDff5Y4lKNZpyXzIMlbh6VHIShDdHFgr5mZKE4iEs8SLkSOamSWVxEiCP5Ca4IHyKZ+wpLiksIcSw/yRXjQ3Ar6iM1QxZMfAefZ+k3whcvnfl7S6MH94XI4xlrIsXHiXg6Rm+zNbSKk9KMuHyCyY03oUVm+X3lRUQnN8EERelQdZfQnXIRQo13g9NBSnj+jUM/lsiccWxYwuO7cz/FU3hwMaWlj8K/WlzNqMjaIZYhW1Syx8YsFR6Ujxjkw+BqX2M5Wv7p2Jyv8iNT9AsszxAMsly70tXi0CxF6ck9uOfgkedWX+ZLAQdjJ1jynjOx4yK6qb6VKhxk1MpwIQZq+ayT4+IcF/Peco3pu739qnO/9ixkfo5w0XdZhEepKyPg8PVzlcfrX+y61NjHjT1aZLo1Ybx3gOHhOKin5smWizpx5NcEX4wyqeJAHBKQgrrD1jwN2i31xmwOtCq4gWa99B6qj8rAEXVhWHLyR4s5yKrkBpl1PeF89O/SBAupirn0Qt/cIYW5l3ZZhOBadJDfxfXSIep/em1a6rIVtL/4x3MBibMEvKWSr+p4s74U0PHC74Mf77HgWSAW2MfmwhmazgHsO+CMLzkFv12wU17Ikp/LR/4wIe4tlhnP5QBvXQT76hkjeDHE/1uqK87+VbdAkvJPe5zP3cLyLOFxJKQDmxFnS0r/iTGas/XRrhP7ulClICg2nlq7B/Qgak8AnUuDtcryzy+PvyLtt+PyLMDqouo2PFNOLyBkWwc89lRvQCMCsEQDRI2J9XRIDlQ5ry9dkeLrWWdhZOftCtjiFwmxP6djxn0MYOIdaJzZs2kbAudhOO0nth+DnTX1oYvjU8eD8WIuqj4NjzC1//W4L6RwXspoZCK4pXefbRfCFjEZmb7gY98LfsNOXbwFEQpaFoANUlfFjGUONNBwveD3EuWoB1NDIbdGBbxfW1xs7Fam+ODRiI0/B/nKTNMTWNGgTA9EhdFFgZ/ssVjzGInugwEgJK1gZ9yEdtvDakbiy5szFZc38wbz04y7KjyF4LQARNvb7mw5qqApspfa91hsv61hKfjyCFiKQiN4HdTxEQU2XgyKoURIGofkqFBC/ZSejypw8gwHxDRpiCfiLeYirjTEFalaiwp5iEAkLBHJ0amyAqFPHZgnviN6Bw+lFB8qPcX5ZRXMduyXOzeP2d4mLMsZ12uM+D2E7LU/3rSaJ52wWrIBa2S9geO+NPN/rZt//arWr04rJzLKJIRVUJX/ZGN7aJsONR89v+S3TX4h15O2fW7qu3UtF8Wga+XtJaGlQtZYs+xx43fqjNW/POvO4ytXW29WxMzKCbC2OvjyObBzp3WxZT2t79jSLWEgd44cRD7/nGfZxMytPbW3uEUtmg4dqVbczslfxO8HJbwSEwB1dA4aYmYwY4IYauppFSudsEFzIiwAWjjSY7miWcn33IsS8FQMT2G+nrfsF6lcC3RPXXRESkulVP44E2IqZKLUpZDAHvXfZy3l7kv50vxjXMItIq1IRdQkhdUYqLnD0FfSm6hyCvt5DWuvcpkR4K75fbKBezltjlJB0V132Hw4Z0gruYu3PVKHNZaP867QUsdwYn3SYD0pug7wuQzonkEEUbDa3Iwmotr56CM+nXbtpUOY3JEJW+bNI1zB0c+4spiJ+9CvhUj8p2Zixv9VfyY8FIl1h8NQ8nfVt5g/GrXhIMrb+N3f/hGppTLw8Zigzyri/PBLlAOnMpNgg+2WOc0XLyiY7umeahpLOP5/DGga+pi5N+1bYpEHd4Sht9n3MCiomLVdxH73y8enWsLbtfeVmYGXEw/ZeilNKL1TgtAPNfqkcOFlShW64Stbbc/UM5vtn7VP4tN9xjlGg9uUGPAQJqa1KFjHfBOoVckBYRaqaZJfa8YG/ukYp+XP+vBOXnZe5mzFyS44ysTwS96lr2bC1HCVdC0FBnWXbxIMNWc/EbrkU6y6oVn1bouKg5P5gd5W+deCvOyCZ1wX7u+GumgnG6lmObIyhDgXEKnK+AmOnSHl8PPVZ35fz2z47Zxaniv+oF990Z72QuMJAH20KwBm7r7CXgCKqfCpL5qRs1/eMXjXhfsHgeM10lvpRW+ppIs+TMog0dYScw3o+FltAdUg0LC6E+Mhf+j909s3/zRM/3tBIp5113Q65yQaoLCYOESmntLf1ZzKDYEzR7qc/vPyzXO59DEzv98xxhnxC9+oUqVURI988/JHHJiI/vZHZv2zWLdT++dY4lWdRl4N+lejyJpy7+min0+VK//unvf7HbeHXz22xAX3ZwH/ej2KN4ax4Xj+FQrPeQYoBDijzzUdicVufWH9416pCNxQZa4uXdN0uclOvgMIpn0pkQmyE6z985F0LfaoJIXyuzf24vCMXrpuws/TiRPglp7s5Eacj2OMSUfBEl2cE3lNc2Y0loDFKEBPZ010TIrRVmZlCiZGm2WexYyUElITfi8KTpTL11MM+YIhFOspgcklM6FX6OstjhXZewJvvzT2BQWlZUFowZSmXocLfvuxVGQshFxK/ug95hTWAElgwwa34gbROs4ALkGy8kmmmjo/eeh78jjdnqilrs9v1othU7TvYbHyTiIilGaZOz1s3zVLdN72cMv9N9Vrt6NbwWbvg12CRTivm5Bne+Y59a4ubhc4zIkj9jJGpkGjrKwu2P2M7sdDi+7Ux2JOJM1O3BJ7o8aRmxIuPqP7bCtPXtfBRvm3+EDAUnw31YzrF14gT04YvPPObXOj7j/nK4Oy+ePCxyz8CbtPmzYdao4TlGa+2qOybiJFqfp0mg03IvzD96eFg2M77mcbr/Kf/hnsZiWQ5JyorevY4Jky9sC5nRaV9UOHW6emxepnIkKiZPcjvdSGD6BIlj9Q5nmEFqCgQuImugML4lGtku6fLeeNCvp5aNHkGMrjSnUE+YMThvgshNqBLqy0tpxeW1c2b0Dlvn9yRqzsmc2tS2NyufwSQRJ5XJ4VRcVeJIds+YNyqJmKi/ISym3f8az6MWEZI9e67zBL02nm9YNztfu2/fY1dfANaX6HsMDeITCkBR0ixHaXZY/JneFYjN7dzDgaKXa5ovto+j6/iMH7Ao5GgI5CYmgQf4BKo6oyQ8O2NbqodoR6Us0+6f5dwKHczTBs4LD6yZVqr0aFp4rqA8QqMehE11APqq6bHI6+D8Nql6jRLqvqAdN2p3kKf2NW3rGAHGbWWTP3Q6q/pTPM1YNgnjVSQSogRVDiFaECUoQkoBOdQzywxrZkanW7J6lJXRHWpZAeXkYX7YmCAFpuGy3dyNVw2B7rl4Sv/eVIxtHHHXL+Kzl1Lo7O8G1W97Wz2Jripi7GY/nx7Dw6hqC8yqe05bNw1purAB0FR6sPNlZ3xhBfsxHyKg+px8R6NM6o0OzbdTaprDQKaqbZN7COclGXyBjhUyltHEe9se77xL6tQpuZgqqxDlXs4Fxj2VPKFYYMKrdx7y9dDbiFd+gbi1HNabyL9dvhqwbAl2kKkviQPNYUa2eRb564cC4eZVCuUoqWR8KxdvHWbXtRRVym0XCI0mKifyM5uLlb3XteiJ9vj2TzpxJOca6Dx6FWYU39Riae/O1w9n60/WYAt0eA/ychnnX9TBMAdnP+oOGbC6ChrUzct1mylXo4IcKTKTaVwjpLIyQm7hp9/uiyLQRdQpUFMkRVzgN8OkmL8mTt43KnR9mkUVQw9QG9SEjq6YIoTHUbT0zh/E4FSDnni1ZzfsxcYYVM07z2J4VrRHfs2/XvEhZ3rr6pOOZXKCGTtGYC32fEA/hsI4qpBsHRW+uZQX3s8DvvuoTyKxuFeJssy51/Aw3wRy06LkJMRPcwJOESq1dbkbWEucK1jph+2Ta+uHKdeqDwceiaJJ+P1kYcPdS74PbH2DNwAcyiK4U1927lsztYYRa/2lNX4Rybxxm/7mbGhnuwqkbYVp25oWnv5Hn5bpVe0MOquoUrYSuWDQze44os8r+4p8NpAmvLhBtUmnGayxkmpqUsbn8eB3CS+Zyx0rO8VJqPg4RKbGj/ExfJTgJ7EvD/9roZ4/Lcqq3ciIe7XbrNuXmIVTaKQa4P52HXKLL9jh8v9xsjY6LoxzanPfaH5rN/aqCfF0z4WvPmBKAVk1gQepzFSKFr8ghRivtzu5N6STYY63zzzt9AE5r0NEAzk0ZpaJpAiOG/6GJmyHxwKj+wOZyMLTv9HZ3MqDgiK79Y+Dwhx4sJgpSbYCzmFj7CCQGlyyCw4K1aqTmmtCiJ0qTcbL5QJqgketWHM2Erp8rDJkn+Gx1NfBIHmWwKnYHaphwEFPTlsyZOH0qLVPvi+11W+a5MZENG6CM9v+M5ePiog3vM6/mouO/NPW/N/PCivNak7zOsr2wZTSlnmnRH2eonzKt6pMH2iEjwRx3ia3YRXmiMUw/nxnAPstXLyikGMk1ds9Lthm97hq87zMvV09YExE+8OKe0+EW+yDO9Uf0NsHsY/bqqRvhT/pktifnv/7bzGKJdVzljS7IqA15kR3+lbzkZpNHezHGD8Xekv/nNlQVoRsFWP0fNA6+EV+8k/KUyTj2UG74Cr9d0rfKIFnzzUYGfvrM704394ZwCr59VlvomDF1cVFz8X7rgn85GxVeAfe2HNFxonXbdbmt61piAN1003MGs1xV5HNfDrldrJcp1c8DaOaiiEbyBS1mhCBY3gepl0nl3YgRSkLcc337AkOdfPgF3/Wn4HR9noqlKAZTsGECczXwF1acsMNmwcBZGUD8KZi6MDiW5UpYDIxh97j5+n6u+vtjvR16gXd6+asbPLnrS2jN9BGEvggUlboCJEGfvqP/lNtane5b7X6cS5a/7Hhl5oqHRnPFUKcOaE2DQwSEZavve81hcWmbC2D4DxzZSon43/N22zl/xXUEUC9mNCrb2uHdmoapnIAnrwjqog9U33DfgG78LSM+JUkn82/4TfGco93qON2CX2Facx3wXbln8RdNNn6KEkjTIpHQ8bUX/6rFX8HH4UOeJtkFtIAbZIZW7YG4giZPNUTE4QnAH87Ew3TwJ9QTad6h3j/+CAH9IY/CXkFvxE7k4em39XeRWnEe7ftuZOtzRh8lD+y6vI5SzKyip0vbIozf79+tq/6WPNH7+jf/90thloFROWB7VV1uMEYvJgi1GC/iDpCBH3ZaK1/re3pckp8IZZzPutpEifx45WihoBtvKM7g7Y/yZ4xJ0v/ypDcvIvRjRI2Xk4IYkCmPFUTW4EaadCJxUZEEnqDKZ65iNvxn3oigVLQUC9bLKOb2RtadZB0tYG3tIh3d+037ZoPYd52lB4S3PLUOf4Sx6dhsMXKZMMwxESx9TkL9JRknYWGHx8J+jcL7iPJkA0OjA09wCUWoomvUOYtFv+ezgGDLuItS2eSOq0reoFElqBA8MXeQ+5ovS+/HvfWfhOieevvB44Wn9w8vXUmdySd80H780e5fW148XnvZ2P77WnGBZKZI3E1l7Q3TNJSx9QE/Z8TeoP9IGhoWUtGQbKw62FRck+8pFqj6WBh4mwV7mRaThJPpZKX9eCk7hQ0t6gx2ruAFVtq+uP2TjPyC5FY8LRkAi5MIGtwrpr3aQp8S9maKSmEC+jpeAE/jYcqsovFikhQTEzCd4Ok+dZyS2dbQGsTG94aAUHQgx96wwGA/4mkn9otJL7EiJ3WIkdopvK3rVmZ1OGnub5i70fTpLxV3ylm2qGxLoHfoeHSmXoTwDNgBdnasgkUSVWBlkgiJtnUVXxlIGdKC7LC3wR8fCwje4py3uz7+iyqSGQV/Bf/YLNdRv8GCPIYVTcRgfxQmDAzsM3XjmdzcBYYupk81UayiBtFZgDa6I4dgEFhWHcViL1vAyRRB6JZs2jdMpmJqEe7RWkIYLHZJD03IWdmqiAWH+euYWFk1hY0FGA6WeVsdVc6tUf1GZwp1m8qMOUWU79slxecwowI1KnYv2g3ncRqCbLptJcz4le6jhZ5olus6ja+OlJmySO/EM3Cp3YAejDODwKurrtbfFLvV/ZuS86QtfsL5MfjVGgWSx/tCAF0ZaNB3BpAGRgzhESfoVW8t3PEHKLhvl+n/5G//Hq7WLnC2LWr8fkL+1lDYvvwoj/CSnCDMOTNa2X/HjzodfuugcjqTjamW69ldryZadP2kSA4LiWYyvrRX6yykVjqvC/e7KDVe0f6rhKl98/5t4/BeS/u8K4S7z10Sxilr5EyVhbDp0t6VxbYr8Gipc/CxIYovJcuun5kyZZEFHNH4ULphAc9bOaUz+bBN6EYb4tNDo1+45OudTkQStFkoBymhsqLNrv/tGFvRfCqZI8gEvZi2Y/2EowXKoOLaw24zoF1mpVRilX7LVQnVOouBdlmumUPpu6o04JJkWJxHkyUBRXeSTHcML6xXMVK0xXKPUuv2f6lvXM6Jj2SOxE1xWH8Ma5y8xCNATW6iDlVw2DAv5if4hUFbIL/JJVwW526ykXpEVW0GMfsZWCs3YDLupOKSYm0v+ZP/4u8WwADNfZCCyIkbkj++fhNZ6JrwnyNaLKs2DTJzZ6OG5FsS0LYvXU7/Zy+G/myfQ0tENQd6LQuYN5ysAo/rAXj4VfXPzIpmb4LpbA0plkkMAD6cbFXwDny9kHrPSRuwW2LEdJGhCDMUjMC5sm070EW7rnNLc1ckzlGfscvsndKKY6KA0xCyKIW4VUjkZp0hNTFQkUVZtSiDvK3rvturNj/g58oRDqKEWDiNAA7dRqlLbFIRdoYcGoZZmbrgAkHL+kOQFoN0a2MWlciOfVNdS3Ctbm2FUidMtzywmUCKvVnfpv3VfLqKeMa4VdtFNp0PWCoEgD/1wGqWJC6WTv/0hT1BhjR9lnpbM9My81T/c2x3cdvPlquDmBNNrUh5vPOuyKGbq3hScL/bzar8yfivj8Z/qj3BgqTP4nvvfIV+hE69K/hg39FG1NalrFzBo7qkI3/xa6acdgYRJHG8LKmj+tOTdIk/cfLdV/6/Ycqxmbgg9+sm3sBbhMomKDpCAHMhHmDitq/h3BTvXvaHeyQfmaxqEZ+BHKrjDp67LAM9gpCerKcRiTdnkn2lxm61Q+2MVqBcDB04bcIgyeoVbv9jicFyoMXE30WMGxrvONzFdaeCVxBaNCKhH7VrMHMdxl+ZCiqVuehLW1OZrzqUofy/QPS4pyNrCd7c3b/rhj1xSCZZIocw+ZQtEbw/tM0Mdf3LMk6bapkU1iLG1pkM89ofJncAqEieBiiAKKvB+9s2h/Zaw68+wVoxrhXBeuHNVxbfR0K9QuYZmioYy3sOBOu3AKInSf92aMxwdDQPT4gVrojaHQa9YMc4r+sstursDRh6a9/a3qakIXGWY1vBcmm1InGBw/nLfxAO2vWZEHGizUQSEpcJX109LF0VI7XcMokrlO+6w9c/JORGQ/z2R8kCG+cgW1wbN7aLSk1GEhxVPxVx5IVsyUoDyCnm0gjQQM0i+ZKWOIp9UBmUEkkJR/l/KrvVZwS6YZqrdpu/b01LgRKhFfrQEi9GHgRbvvrdvcMn/s7lZ/pcoVb0wRa+sWXGy4Y72XgCUHkKNzRX13TocThTkYa7N5P3zqKsJw126HrwpbkxMFTA2Jgmc2KmEyi4tMRzlQBHD7vjeQ4UWWdiWSL/cIZGDw1IdIOT7kHZNq0LaGAh91RynvOOqHpGN9YpUW70y1T39FW89+OMCERZBsDvUc16znPQ8K69ZGJagE5EElRjzITSpt1O1Y6K36JA9lTdKSr9qriVwybfFpsWp9FpxrG88ERDte32tcWW8L/aP5rdSn1TM5ag4J3ShQG6qqE/lMKlqiQhu08zV8GB6PqyyiT1dX0Q5vOk7aW9P7Wu84DiH0MfH7M3ujqXVAtKTrLRsubVP5LUhfYEBP5shIzJmLiDLSMIokFyQbEcxcSGsgHot1DIp/1EfO5PVaEJF05cpxI0aVP+EeeRHY9hoIu5yizPaQi3YuTTrrk7+3kJEd4LboT5Pwtaa/LIYNv+ZYMoP/JPvh1aw3lyOcpj+GH2/CF5iMtJMKoSoyVqMFNYm5MVe1If7rNA6ihPIgi3IhE1sAiVY4xCvi31DLQu8QnEyqKoLlGF1qK4em6qRTh/HcY2q25On2akM0QNLi1/ETF6o2N2jY5d1hhrchgOSbZP4o4QosJootMhSLNAirejGbgMqa6KtohiJRQmRiNRYLYo7Ga3iH1QYhJTZJALCWmsZVttqZ1a3DS0uZ+CVh66fx2XX823iQxakCF+87e17VIAnkKruL3fDVjxZ45q+Df8TsJJS6KhQZqMgibYjohEy3YRoxXgj8tIZSTAkzE5DeYmkI0iM+rKst5pz6EysYrHBm8VOFViQhUqztMgyylJAuRXvQMhIoIXlOiXc8EczstGjeW7L3r19fSjm7x00pnX+g+i7LNkyBVEKMqu9tSUrRxqEPq0Z5R8GehYcEsInRT1ws5cSj4WVo/ljmL8iUaiZxcAhfpMHbjJPxbNhjwEpowGF1u/Av0QaW81KCR4Z94bh02l7a3nmJqbChYmGur7v0mbCjMc1z4QCP7XGpN9wkmZyr/U4YQPLQ3e/x44Hax6OxVv6RHjbeIRkmwDMgdAwW/ScOmK5/K0NgrmdNuWA8lG8/lUI83MkyCJ3MvIRdyQE1qkn4onIBJoAp2e3LY/+WAlfWCf7cTb3mj/eJn1d677KMvNAIpWdmY821tVOrWa+AHg+DoUIA+/wwT7Xx7X02qqXC7iT/kk4CRoAcapot3ilF6rOemBfy5B2SFYqeOa30/OQsMgDN1pGkv5IP+4HUqXF5ZRhDJS1EzK4P4As73AN48+IW8uS5+EQHY/ES33rOY1SmzsDmPL9OBCX93xr4ICKTn01fMQfC6tk/glpq3yLLB7SJyLwQu9G9lJn+CJGEb2FDN70LBMEKA0BEpLynwkuPiIMlIaQuxVk3gnfFVHMRp11uUWjBX5Xo9Z5FLFDypMfX+44rl+3SDZUiHnYs7EelGXOm+GOP0VzoC1Dp9vlvi/B8fsPDMoavicn9Xg5HO2+KsaP53Df2xEugeO1HRLDqjduxq9y3XCyS8iy38rRPAmVuUOMNyF/SVLwMMglgmCRVsJIvEJpsuyNjEiraUsX3fMOzM+QIA9VCfIhv8oJZm8cDvS8l/270otLMXgsMobH9rdE/wDLyUH3rr2tY7eqOP94UP3q0IrSfAM/w4zI5UbYfR1zlXMzS23p/ewm5ez3afvrZTsI2pT9CsExFkj//kqsZjqVylkl5Y7bTxIcslpf6Z2Ni4QBLR38XIhOO+B4/7FGIXVFbQ9+bWQPay2Wo1zm5XOHfYN76NrKpb1Z/HtImTfNoQM1q+p1En7OwkZHo0Kuk6vky2CnMo1iA57jysoPr1R/zLChCWUAzANUfA/tP3j0mX6cUGVrYEJcJBpegHMuiASH2WgwBIe/LUNJGEPPbYrtv/7Qn/3njWcXmK+1PH75uJrA37/J87HdSuPFlox6HpWzMt45a4rLMuydre/Y3Uj1e8WxG4UQrM/bkHRi4o/45vVC/6a24Fg7LzuAxGUlDFF8MMKPIO/usxR1vyDyirwzbxlW0GhPCN1TfxNdn/HYZed9Krq5IMQLFrvKF/VSN3kGcxPquWzVMiMl8MtM2tskXYq7x0MkdkBHqs8bU41ZUjiX8BSNdT0r9jAAVWLQYvzT7vE3LBYoxRoluvYpT0lUiAIxXidKKroPE6LZj1XnA4ZCTPBLFjcPYfDBE2yaMbciwApU2MptTwsZ/JrkmbJg5yzOEBpayinIQ2TVj4ZIb7aPQwVWXWsini7Xq8pgyy6/3mhftRvhCnmXI1G5R9msrNf47Sp7Mu6JP6KXeXYvhAx2bbO2xYqnvix+mleUbkkrp5ePO/A6BAZ6Yg9M4D1rWUllVVl0hxo9ZT915gaFWW595iVFEqTvmavLnHdeYOeEoMJYiTjIN1cIweyJ+A/qA6mTPG71ai+iWCwOiJkKQiZp1s7uFmEZ4CsDRlRxKxmZU8po/Iyc0QQow4EbEWZ1Epced9ZCEzM8ZR9BwKhyizcwVGatPGM01+yaCjnb67d8/J/7bwmxeFhtFh9HSVkEk/1+qt5pGDAxxjgz4QeEt2P8dGC7V7adtqiA9RgouuJIM6utrJCprz5VjQ1qSDB+98Rju3/lyE48GLuAnl8AoG6E1a/C1Vu7qPW2Lno9n9G75n1DSCZnSoEt1RIRbEwPMQBN+HOpyHWZMRAJV6DmkpbomfGSJzZJ//OveA52OOP4S1TlbGqa2gea3DZkAxYpogG+mexnHOgK7M9O94p+4d0+s+hLdwjokOweEbTcup3NGBLtnpTw4Dm8nFj5SXqHreGbiVnQ5tG08hm7mRvXyvnk2bOQcmVDyNGQOKzKrLVxIEWRHTmfR/AQwk8+A1JN3oZY4r9dPwufKpl/uf372DdwuywKi1UHPOxYKpdj9wrE8SNl059Ah/wp9zWfP/TqihbjVXkydwcT0PhR2YLs/031G/Gy7essZXvTpOT6mVqE2dNDouPsaUZ2gOu1lyo04p6ldhUTBbVBXLmGRNuBKxtL1z5r+sWRjgLGwqX1gJfLS9fC3HqWsrDHmJXLF2DBTxyveTLvhfMWCLD/nutt76mBqLA9LphYELY0FEfN8/9mh9idKWcwP+hh57Fck4jDMP73bcCAxS1/jhzL2QEYQ8uoHLpbVrhvJu5MGxC7rufmWFIkrtt5AUWzpscjVw36kC2Xl1XpWxQrPUnV+zeLffflmpZlHQHDYLGI3liEYrKNQjuSSuXIOTpp/w6jL1wEPdzFz/WGbdvvWbx0CS0bainonTgFm/noqxQTi3ImWHjAot7dJrzmLfIHbBounm0hM4mMeoTKoUqRlDnqTzk+0M141LFAHMvDtKKt3AE2t5M4V7lQz6+tMSe8xsziYrlI3seSwf2RRCUkq0wF9L7T09gk3bwcq51knX6IABGSQRmWQIkmo66EBpWXq9Oj0A629BnkrJ5PuEP009KhXqtnIKVWU2n55/HwWNoIgv/jb5AExJmLsCwTDeo0Eqr2xlFcWm63IbIXepWO9mCZCZo0yuqNKLJ7VrK462fyb/6yg1lIq+Odtk/fMgVE6F1LSL4SKrWIwbi7eAlNroAKjQzSypFrN0f+HLHXNA3YGtIZUuwmup3WKusS44/kwy9EPy+/UU/4f5ojHcY5oO+LECsEheBOf2LubS/RErW0BCQjOlo/m18tiS/yoZnvHfNzh8whnz1fgl32Z4QsflvKaid9zno1OXoFvd5eYa+Phrh7KuGaa/U4TphNo7hgNaWMVwm0UcShTrbzMxVmAjmjt3l399c4bMrZ6Cb/tTuskbRCh0TWjgkdGPaVoo9jY27HSvXoWDkxIhbb8TbTga7ArD6+KiJ37Ine4KihXW3cMPMMBiRGkahQG3vCL0kYJmGhkSs7FOJcSezcLjT1olQE1qOIfJRvVqD5NioOx6H+XFNhZyEWO3TLWtlNOBqp8mF+spIosFA6rIOgss6P0hmHcdA5qqIjFi3W1hmhsYpoU5YutGW1dGpMG+3wFUZzVzUxnXPoCmb5a/dSX/x+cnaXtgqsQt450uosy/xEtuOxBWk9llwSIfte1x1TLXiGA/d7PXmB0/8zd4cyK+Z67k4TPKpf/333SM9oYM0nwVamTfVwxuHI0uY254t9baQCZ8gH9LwvP1+l79SUI/nIuoPn6go5vViF7tqyA6U4rKBKiYsO0AAL2ea6AWnukPD6Xdt3g3gJ6/B8/eOgXx6W9JlUfRmc/vqwPxN/rFetWVd5Or9b5SlBz7lr1u04l3/TICdg6/iMBJuM5nKR+CW3CiuQ6pCORfBxVsAakEG8fsvutyuaEqnyC2uh6m6xUD4vjSlZxKpsnJxdSRqcm+kcFu1O4Z42THziYOvoY4eszxItojYAgIaa1Q5gXIX1wb5Jb39K2XygedbXW9uYtfJqk2A/wclDlAOTfaskv8V+YKPGpuaQ3xyaGzVuTrOBxbkDpZ0MdhYeAg/J9fgd+s0/S5bXlu7u9fMkl3n0I9cNrb9PmZNXLNCt9lUs0CLtuN0utjZlhY30xN1LkxXmmwNF5VVuQ9k2puipylHTpIY5MpMlk9bhxYJkIXtDDnfNWvWco9pkkFd1g0GYvfbWLXkxbezJnZVVcFPj8bDE+4JFpW3JOq/QlwI2xLNhDRm39G9bV+0zjpM40gyD2BMj5DPbdURnRZgVeQ3EUevoJE4GSKBWaAicPiv140ZbFEe1uEfdh/vU3bi8Nd7uxL3KFE5FQGQiMKhYG3MSZ9pGkk0aqKntU8M0W0P0REgarG3EZ6vqxR0iXConjY4NhZ0Hk9Xmc3/ic2TRBXrjdqffpOnPpFJenq/MVsdmUw4JsiXDBzY6JkgYCCvDcvsjy5O56GUa137nLygKJGYLcL4yR4M0W6ND1tS3keQ9DqndiiSGHLou+ZzjmJcBHlAwoZyS8jekWIHVFOzQ1Nb+IOyVTwx7C8ZGC1HoL8KE0Vbmw6Lx5eMVZoMZgFQgZklN2CKAAxJWUiPFpIGpXGUPq+zOaNd/DezzkAbrPTB1HTbG8GM0fUDup8OoMr7tKUbXZVZ4wjhjHl/iKQBKpvKJuEzRcRRHBJVVile8gXkOZtNSWvEb5ARgk6ppctUUYV/xCFFfZpOgdiHgZbE/UxkBZsB5QePFxZ7H/+rH7ZGMLEJt4mIslbThjL0EK21THdBL5+QDE+C8o9tF+078PSCxW5RtFSdwwgpdpAttgJNNhgRVODqKojSFs3ITj+52S4bpIeLEnOMoTxdaj2YE0w+Ak2k8wqajC3ABISRteOLxhGMlwd6J0fkr3nfH/SEPS3NzH72gw7mbxZ0Py4pPxsmsOCEm4iiOhkk4NZj/645AK2JRT4XPkNdjq0YXh+jaQEv3C1pEsHqqldiHbYw9O4faRQJVaw++SrAY0AUHt6iTCVtzS4gLhxi2q9tHMk0+YBIdn06aekACIG6GQXQKpRBBmXiSnMJNcsHa89vjokQCJcSb+atzRYXY3m9q5sjwVpNG+KVV/Sce5T0Qw9y9EQBy6dxphaVhWkCJNgxxaomKAkiFSZyUqkdRp65XV+W+icino8TVPmlxQ0QA9Dl2XNTQ1TMRWl1ReoRLxCBg59IJAosVT7aLj9aFieKkBDv9dGobJcXS0EburMm/EBvezfiu6Pj33//CF7OM6fEiIThLG2/6HuJRl5DPXpmlzxVZ8eZpCy2/MQUeTW7++rwFiAZENEBGR3BESIFCo01S+OWcNN8X8+o+YZV/tk04d3eQeaZQhXWY8MnNKBQvK8K9t8hoDdzj8j1CI2p+HSe7Gu8BYD6VBaBTw8mUN0MEYvIr/JYKe6kaUafhARVh+tIvYXHBzZ/WMcaEwv/qWLHQGAr9q2XZanN/pU+Bgbqg1IjBmCg6JKekEUqKnAXoOL36LlTAkHgS7oGjaO4h3PurdQLNjr2tElW5JwyfCbrr1YHJ2yzcH++qeFpqrK2iIIGt/kW9sdqMNAOJWcW6mRQaOPLTISGT/zNdkp9DHtdzfqFyLZ0Rnh5IvqaEqH1EKsxETomfbuNPrY+qN2UMENqdHkEmSmr8ggiI50n7Lo2c/koqceMAGZoGM8OXPxqzVmNaHre5O4PVk6NI/eCZJCbzm8JNaVG6MS2/BVzhKFC605oJc66SC3TNHdeC4uEKlrXHBfmJikTljbY49vtpmqLo6TQQ+BYyxivi8PxLa2ew11RnwiarCWguNmJJyTL7aGwuTddcP725ZRz2a6v6ZEY0Rx6/YZdh6Jkq71/SphDqsC6tA2Phc75k18vbNP2vNKkAor7ogX27zF3COzMlm98XHNDCx8S1xSkK2qebJP7ZqK6P1gt7OPXHF5QpBzBpTMn6/AKxLUYoxc/JBaW5GfJo7C66+tuE2K8XopQZmTPz9CQErRGrJFDxec9VCtXbgdqkQ/JajVgitkr4k2sGflPf4ywBkz02vDcbtg3MhW8s9LdM7JM693ixvBN2JSuZ6uHWG2k0Fp8psIT3uo0zUM/mxwqKucdL5KR+ZaCL9FrS+8SbrvdJ9SMXWitpuvcX43qc6/adXDXd4Oieyq4YysrPBixvWzHSO/hBlGT6L4ITjAZW9eK6jWT0NRIeC99g2qdeoLZsUS1QmbeUioBS7U0ByiI1WSSUWrgBMaBKi+kSkBgTJAUuG7Ap0zCttI1TJEqxlIIuZRUzKyVkcnW66BhZpFFOos6vZ9plMxnhJOgQeiLWwmwzUeFnLN9U3XGbzjMNGzFjS90aIHSTqP6lrVWWKN4wxbnRrhQN/W1/r3ZjYR3vfyndv358SduJYBdkYMCxPPQQ4MBeew0qAPKOsVsNsHdvbg+OKmVMRMPNCf1q5krE6NkEwt7bFXzSeDsRpVgndpIgDhIoIVtV2BT2z91z3vduc2ngvh57OawW3bqlfX2I6Y0hq4B1JhNiqGmMinIfb0iLWvdYOC+knGvA7PvGeMtBK/xf4O/O/TnP+7tKiUZ8bSfW37+WPxPoC4b6BPyGrSNVpaanolI08aoNRNpI6JympJSICg15XEGSEuvIKoH401iE9Kiv9vflV489uutOmzxxu+pcuuuxa2+5J9V9vyOLyxnYlchB6NJdKM4qPIjnGFIaUwyb8ZpwfcUadb3Naq2J18XBg6ZqBB1B+KYIYw2+i5LsXIPdMLBovXozt2x0LrvelR35zH4jj+XaVaasNprTEkEIcg9MkoiHMeFVpMxPUSqW8SkmyVCxqdGP/CarZvMDb+W/+zJePJbzPp254NZZMrx9rHDXwNDyjNyPZkYwtlQ8U9IuEpEXN7gkFiNnts5AKy4jIVnR36mGR1Td3Iw1eeto+X6kTu6tMZa/RTHp3/vG5+VxD+3QWyK5jdDM1TklDilTVRzGCxrvndszMD+05Tk3rn4mMX7ifHOPRL1aot6VEiaTPHQd6XMjzFBPb2+oz5tE3439Cn6Fk3kQyiUFvZTSG9qi6r7liPWuMvkLWvD0i77QThhqQgS0vlBvsIMydkvE1EBNrI6DNaOlH7JXlI/Szg+qUVGalvBSlanE01LbRvGva/nii/x3nOh0nxWQsmxj8eWE9bTtzLpVTCmSsB2Acv1sPALacCHxQ+K5d9Qk2twLtbAxhwbloWeJYO3x0bo7p8hfVcNo6/6wqODO0rDH3vbsZrsNp1vYd5AQlkjNGVB+hX8RmgRAtqMDYYaACmE4rMJFx49+2cL4/dLxdyP8IryLKywH6hkpDyVMmFrkva8+t34lm2fEYUkLu4fVqhJLCTpY4vSGyhFrEQ15cIULoebnR2o1Y2ZCHUxPLS+Jk3tQdxd5E0qHAcyqHQW55QlKfCWib9ghNLa4iqpCdF9IX0sZNjKPRpUGXBQbnv/LI260iozLXVT0g0z5YZ5M6Maxcx1DmVHOPPht94P4k6ou0FUY1hb/ZYguKwrMA61y6my477JWaMTaqnuIubFFiE/oW83Ar6LyT/B1EX8pP0kBAuaYIOkBo+cauRF0n9PF2EUHTdr/FXveifZvsRnJM8WONb5XESZ8//LpFYR3RqTn79oZEnnlaG0wJs5i4MiROTMdYfZy0zAQyleQ58kDTbcbdvh2NDlrj540QnfR9D+tJDdK4mv3A2/U2MKQ3t4pahcKqWQ+Zj3eLW+SZbeA8E3DOtIFA5F1cFJfQR0pcO34PdX5CvYr70q5ftok2T4/fr3p+oDxZNWfZWFBk3WO5Nxw8C4KqxgDQLiDrNlYhV0ZY8E9zen+/PHz1HNTEb2BzWO0KgjoFT1LetsvNV83xMSVw5YLgbOcORT+I8lRRQAKN5Hl88fVzHP/pTuqUbzj8im9aB9Tph+U5lEZMYHzTQMN/Xtt4fEEYYezWufvsNYsl6uOOxjSY8JkR7HCs/775ojPtCKQ+j0zuKyNM7nLOniAcf6dSvvN9Pbx2eXVtFQGWvY7Q5A1BgKcIRk/1SQbcvA676Z12U0NBjmPROv+nFXQNzcdbxjLNluRkNC2l1kzLTovNFXCQ07g89ivLrZw/tF5Z4XPpk5jPq1VwqPHNFSktoHdm8bjOMJX+kZaNnoSRENrNi/sUz6+AdEeO4+bOd2NjkjJofor8NitigvSWMnV1n3TL+X1bGcHfJ31K+AxxB3BcWhe259nbFmPZ4TIzrYZaMYPLMyr2aIA1uql/WWFIB39LMpmYnKj9rSTmdWtd8dWTtusSozvvpRBzIRm0ExkBs98hXf708UGD/bqJf0Zc4CF0ojIgyl0B1ZB+8Bg5iBM2yjV5BSM93SX87OlkQI/5TzZfL0AuNSVGHjohaFhZjJIfepIQ1qcI3YJAShhTkY5Y1V6FFfuLmiDQzZCGy5fTg13qr616peTd3/Hxl3hAZbrT16sSqFkjvOrOhhoQfTKOxnSD87upUfGVCl37lH/PWCcyHr7x48aD42NLEtItghbKMuK652Rx05bPbM8MpAPwKkFtDKPi3mlb9UEs0FedumZ/cwgyLmueIIvPebqPutIQT0nFdrBWb00o7Dd0yPwuAVdxlbJTrSVr9rJtmjfFZ8zQIBIonl22T/HOp86Ir8gwXb32IZ3G+V8UYr9+lXhY4RDn/W777aawWwMm8FodNTLfPVsNXY4ppIqr+9xyQEsqYgOhWY8zHSjN+GQPv/RW3I/WnmzztTpEAvNcNrrYOZBzYX01bwgtz5TpkryWm95U2OT0/KzwQhoYNiNykiZBmu0ORnfzsvgFfl2ku+FrqB+gpHGlMv+04RoPiza5zsQOwDjNkgsj5rDhEgzsCcp1ODPHtTofc2becB+vSxS3+WB3HiR/EcH7BQBWEmrrvb99maTWqP8RymEHZ7Lwmj0hG0+6jO7/UQCZXWl+tu7BD3L5vCvL4QMCx0MQyWzWMO+YaGJVMzxxVwWgD4SicRtmOyCiGcbjgSftNPJ/sbSyhGh+HRJSLEq8UiRURE73DRzQOOH1+Ojyt9rPRcKJ9wTgiDE2dwNqQQ5a9wstCraG4aytKrW/6YNqruUnxr64uaBdPoJWZOxe1Ug7s3YMTYBjxTimqz0UfG7/VslyN49CS9hHdjrpigcXFiGhxsvlhrngidPjkpbnPXcY3v8xvKhSfHSlCXyoOFS1UvkJQD0RsXst1OhpsChLM1pQun2f6z2989HLfpiL9270ZyIOUvjoKZSLJ3wvUbrG2kThY5deTaEmJhPQphOZrHsHPGMCpW56wk+vC/Hvf+Cwo5GmveSTsUGJs3vI31T6CqJXR4Flc9BA7nY3LrreInVXf3JYAySuFURLUzBbyOji+hGojcAIj1S1u7ErCUxrKpS1jbh05zmvBEzUzJenrmCmaQjEME6rq1i/hhTyxxh0JjGPdWDBS7/PpQAPCsCxHQTQ2MIY2Z2cBVckTbCVdo6SoSNm+MZVLdsBYV1CA1xLCtzmrzYwe2nG0ktg0eARSKXD8WdqKzjD9befQcdRzVbKN/4gA3IzkqQY9BL6/jjiD4Aq7E88umXxLG0GNQ+MQTK/lJq+Myx6//ajw1p7Xk9QIhIJ7mz3DF1LsvEas/IeX7f5I2yx5vF/auZ0z1LcWCJL5fY5jphskRe2f2Sf6/q3Fd/a32u3gIeEjPEmhkGFaUykO0YJy22c3257f8zm1b3XQlBIglrnudqVAtJcmC8fPihyGgzSWHsd7zlzOT/8p2+Lt3OzZE4AihjmUIobcF2QxqrxjlP0vAXt5aU21TRsMxY0P+jWDkBJw1WWs4Li/4du5ma/jrlbApQTWd6QHULsavDOJyeTpdHrLiIz7xP8zyuMbBmOPzJgDIUVFuBKih2tpMiDm0Uf46qtfZ33NE7uojRq3X7yNHJ0T7OzEduLfxql/9fSlIwmbe81dWhcWCH95hONaIUFUoYz2r/G10QWDMhltvQZJr2T4NEhtFtAhAsVMKj5dZyItacwwTMRNa4sxTjuLH4SQjpK9HjHL3Ijfr7ONrcCl46TbcwMp5sBHG4iY1cvmqVycpJbOTwleF63g3HKM1BbSzPAi18utIwwvx5fntPvCs574t2fodqNX81V8n84nPL6r4/QuMLiwsDKVpj/51A7ZDXfVroMZ8l+GoxKJzl7PmwAE/GJ9nJhOcBIl2FIB4bcMgxnIN6x4zQ2FqFLcMZMNodTkk1SiSS3eHhbKqRlbDIU0UVG86pcPhgPAfiLKamdb1JnJSUUkDFKE5Arjqrk0SqmQN+pV8wndBEM0FmtsiabS2Dak0K05YzNXQYUGT0+WqslhA20xoxVo0Lx+GkXFcE5RoFo9CqkW83AT+HnPWTPkNs0k0JroThSLfQu1mzP79IOukyDu24/P/tZICOzG/Go7ksd2k9sVdhrTaCIxEYmYmHtLbiOdQQXLIMiALFKVPMOzLy0Ot3DNPm0zdk2tZW5jZPiUIpg4M4CmBBB3EbegCH686GaDpNUqakLUzugLVV4zFEGvqgTwd1JTndMeJY2kbqNytrTFYquWkRYVF1VoJNV2lAytFeo5iYm1GST9RMHIsleuhu2q2G6i7opVNUUtGmJ/WZ2eVtfq4f01kaebZaeEJodWdaG1AKfoVdqUWB5IbHtHWCsGJBuEiJ9eDdEfIvid5jj2uH2awj5D/X4b/57gf2cAyxoDGU/i7U/mS1ige2yy/Mx1mdhznbMWjcV4AkNmjL7lMdffpTEOk/SbpdbK09zXEy4yfJtyc+CREWMRL7oGPszCVVF/5dmoOclTE1YdPXh7KoPFbOi/FEZLs4rQWyQz8cNp+0fjJ2EWdcyrmzlGLN8wt3N6H74bUCHOtYK3rCrVNeCCRirWVeoxxW9JZ85/t8S3kQra+EYv+PUEsnOuKqBr6suhacbUuGns4JUd7omVT/fPX1O3sPZBHqe/PihcP8dFH7CkbECkm6wjQzV+psnRL2j0Ow0ZnvcYhQ3uDpPfntndf/tkpVvOUtOptMkyVTwjUx7rRkzSeurJ6ndlqnrJKY9ZBjfZBEL2lRHJUDnNyFkpWis6Ve8+TJaDeEs325pESrLBg66unFyPXC3CLbSbc8Tfs7fCUPzVK9lxylbABpbLtdwCNTc6Z02yKrWHIccfdz8fFwfi2WVjc6IslKcaJ9P7GD5viC8jRbJh57KWmYospsk3JXhq1sWiW9CmC+P/ZZiBQihvAuFFRVfdG6POFL/FAxlJfDuArGgKSPyaCRThp9zsqSjoS4xny3xH2ZTxO22i4xU1T2iiuRETg3bZyTY5DRzy+hj1B1KLIs+Tfy9o8IXK+qz1lBBBSDMatpbTt34s+mnT34aSE2IygL+QoUJqLzLMjVfhVC2uG45U7+rHwZvNZrrr0xrEJWbeJynUstTpjmPqnfsUDBwsoB75J4Nutljn/RAnhvO27lQ2BLDl/PEDuwQxnHd1Ct0oVdcguWpWipRl3Db80IL081atYdXNcJUS85Z6MUZe3JZAdYgEpKd1Ed5Wd+ytaTxY6zOG3LsgzFlEdxxS1cjOz1J0yIUdthtN2kg1Eblqu8vMXxcEqzbhLdju1Cmn7HNvBt2Cbo8jsFCc0CwXfzwfyEZn7nCi1Eds6nmQeYIU8fy7dUShZgpr4VO5LY6ztMDo8rojdQ0Ooh0Z/XoMLasUvfApyMXvjQlotbeiweXM6tsoQVUhuyZW5VEV818srcqFuqYFfF8VS7/Eiwe5r7EFcC/UW9crsauKmmPr/GoZ9H7Pe4LTdvCDkEi3u5E/85Elm9OcK2E4aLu5HPQbkww7FznxL6ANU4vMgr7nIcKqEM7APeiDH+uwY3s/B0Sg1KpWqkLjf8yN94XcmVk2tHtVJEGZLXfhYLvY3LszDOms6nyy/ZjZjwMCIKOed8ARnSbxSpPCIAizV/ujT80FI22qJCOVyUI1j2YT2+TDeRCU82mWRLixv4ZodZYHZiWANi1+dav8t0kpUjoASZ4T3NKPDo6u6EvAZNQPXGIA4GKqTih2tL9UzAD35ToIVwBpxBSDu4AVXePJXSOWzZnZ5XncEub/MYTvDN0/+qKnFUAesU8FgBV/EWwAVwAwPvhJ1F9tZb/VOi7MaB9vlOHJvM+npiAqyaA9iVuT7i2wNLttmJ/pDsWVhr6O7+otjwfU1o0JkRXyQDN50FAi00ZSa8rw1h4/E4iT/mdcaKr8vos7kTbcUaAZu8F4cREFl4FyUe/mD45il5AXeve5CCude6pxPwXgyakGkr77bs4+xITpUkcMIBHWM4KTEvDetpka6HM6YbzkVzwaSA0OKcxEB4t9xvSXpEKJ+jF4dfw78Bu3QagrjKWIpVpirhDSz4F2RR3VzmnsVskdgP1SvyZQY4VGXtyIxiOAZNEwg2bEZsdEPAztJL6as9cccYGLoSiQNexdTw2Qe03sw3x2adEip1SqTUu/A5Ll4/aa7CokwNLQNcXk77aKU6ZqleAcy73/pO0leqPaWst7bXT+rST/LHVL23fpJPmaSZKYxF6jQXKemoog4vsvQ9i6IAXG20IKoSJgHhINJFImWtHwduJkE9LadyJl1DG9mTDKljY3uVTA4iZGaRxGw7sYqpqKK1kthNvPkreeVPOtpasY7NH7JwL8f5/2d7LPghMN1syNNEnexEogvWIDmUw5tnRqeo8rpb+FvZhpg7qcsBlUihZ9a/8+x6vUvc5pGUv6Q8r2oBLj2nXkac5snKEKX7Kh7VLWhgA2vX+oQMjk3QYA2vQZTixS8l1c69+cuHLwt8Kt+WC3dE0yX6XAsv1qL9k7oI/m1IS557PAr8J2Kg1bWua+aK2w8Htc7uKjE/vu0Ud7lCwE/l2OQ+VKcJ7K5AkJCzZo1t7mzsRb2Jq9DuUs+ke1q7FFZczziYd9Fr7ctyg0u+7SmsAXrNowTItBZEHh2LQlVDGks3qKB7mHau9OHTKWNUF04fp5rAuLH7D2IPlj4gzn7EE7A+J4s+/Cklri2eask2nqtuB2L9AqJQFIsBTWMMxpq0wDsi8hbwmcQEWkhSw3wFhrWYyb+Uk07LGgDkdrhRZi2psFPB9Qxth7MLppugEG7zjfhofySEDJAbzfDByqgNZRtVJFWDGNUOcZy/aRlT5nKEqrS5eWip+fmPO7d9VjekNnP4yjV6utExfZmgVhVtpoBNTktdhApOcMNX8BXfRoyZXmxaXMSRaiUcUVU+er3XuncXcCzIjZ9o9xFzZmryBE6+QAgy5DC0q1YoQ70+Av2O05tckPvkgDj5Yg7ENTRAO6mT7mH3YT1tp3a6273bjOeeDWP+D4ny5DwGDula3Rx1tF7NV49LDHHGYzjJ2PnLw+6HvEZtCN4XgecWbOIsc80mZoN0QI+wfx0vokSYSKtXhmvKscrehdOOemzyQcCUHkGj70jciVivUsqN8XuilCc1babx+WWeWN6scFdSucpd6gZcvhNqPBy97ROwQ/gJx4Iw5YnlictP+iRUKPimBGCnkxDBtRBZP2L2w6aUFfbgHgu0jOOUMNtijuyFd1ck9Lo0Nd0k7ZICVSY4s4zHGDSWwQ/ZsFleZUzdix4yHTQ5KAuzEB/yyaBsqJ9HIMcoX3yBmO+MjnpjDyShAhlUdWC30ozNqhDv7zSNZnfymfFsXR92dSOfSod1Sg8o0uBZ1VmkKEZSowAlTRkkMxnQVzDZJEESEx8ljIVIDIQpM8LYD/2kRFqG1dIojLim/W2H+lbvZcQs1qJBL7UL/H3JgK2QWZa2iGrpcGai1cxChwGwkrt2ECrQYm0XiqVJUnGg6LkND9VXE3bCul96q5batgs8mVlC/T0dk8Vn0lb0yyVIVrQ8fX6o8VrJtT7rUs99fCRamhc97c+4IudoH44Ns2zibrr8ySOF26v/FOmuHtJhPFU9c3xfG83LGmVEO62lFsbCOOhI9rr+Tqi7dWmFuIYOI0Zaxcy0hpvG4kO8+A1UEFbO2Wsb/Ifk2sQhW3QfRfVN6eGMx7glAK5OTMmmSrwiQCo3wbq52XO6C5US7d5rRfzpFHihx/vJ8HvCuaWfz1y7WAwIZsLQu6h0g9cUnFpaj6fTG7A3LJ0oWpr6tTJIZgHD+SfBCzWAFFVmYlHnBYZm/enqQjvndMrdFaJlaxV6c5aQ/ao85SecuRR4Sq+LyE4GzlQsb7xRild4W0p6FdUKt1llBmd0d1oWcV2BvN2ttcOWivLrFrKm2WgGmnl0V76/z2Okbstr+gk4XSauTF3rmWLzBV4BKfLzdvMZRJlN//TNCUG/jkHSMnwxk0Ys6Yus1S14Mk/e0jmBtMJzZzSLtGGgqXMYrXgJvTJA9XbPsA/N5a5d2pfqOZEZc1tUfN0RiqQEjEvOaHsnUDEfKxoOkO5qSjloNu6i9v06DsVHOC2CwHAHVQMkjCllD+QrVdGULIVov0CX1jzHjy+2/gt84h49wyvnHUsxw/mGSDhCf5CTNEcmVpwLCZUy1K4vB3QTx0jnopbXSDIdAXL6Xcp89pAga8X0+Ru/cd4MkfmrDvy2u6YxSzeQcEMG8xnDpWTfd5ThGTeudhLpMeUnb2dOi+eHSRbdif25hQA6qGdcv2BtfxQyXdLTAGUWvLJ5mX+2PHsx2koe/y/pn4yH5NKKalTMLHmtks9loNu4Q25fT+roicse38YbaRKJItClywq88mYZ5BK+LKilxFV5wS9l5FZUWvdmcOk6Ycp82cdn6HWKz+OS+gYvxoNMLJqgdaeOyUTC/A+HryCxFEihZ4oKcy0v9c1pbdFam2C5IxfLTkUurezHPVTElccomaBjcXl2zKFJIhP5StP6QBmLU+AJF3oT4YtxOY/VKougM6cXR4EAQwTnwgd8kLBVTszZE8IMVAbn1gnQW+uu7Bodrv8CbeA41fnt7uMSwbkv16btAqrCLyVy01/R0Qfu2sbyptXdGw1LGhPIBxcaJ+RptiYnQHQuGjUcGam1Zf+VdoZ+/alrYt9nbS4Sy+jBO2vv8KaJzEZV28cyD7En4+uyKds+0u/Dh94iN2exrunLESrUgz62d0E2CwwRbozXTgVIM2K9zLCJuYHwWnz4zzlD2jrPZfubpmvvLfL+zHPb38EBpMIgI8GUVGYSnZHQxJbMSb8xJ3CTs0wHGkW46SBhKJgO3/2U20j3vEQpdWqN+Q1wbDCe7OO0FIULBh9Cs+O/c5zdxtAvYOd2yA2SfK8xr0wkGFRYoT3x2L2EWMkIj6WGhe0+z9hZJ2YpGBcxEQP/iYoM7f5unT82oJgCo2LKRVFo+DRd2z5p4yz9OEUSZe9U4raKfyvd4FZM9ldemvBrTOub+MQaUElpvrX1aAOf/nVBxA3fS4cakbGbLYN2eHQDAm7Xs9QvrSYllh1zQAN2Xts+xF6B4EWhmoIhvPmkd9U0/lx6TiIiRYBrJsH4pHQNMlnK7sqZYZw4pcRlAhdWBFQMveghtqIIUWVZe0IemsqfTUUV8PTRC6iQtSIrLCsKHI8B0J63l40GzKG5sTx5hsAYKzOX/m38aAdu1uUUF+Xxt6r0afqMojznr5HfmeTYnwaO6iaWseEVHkYW/OJOEWAnNUsog6pI8m6KfZfU8iXwauCoV+eIGG58y+tQcebIjx6Vb57QOE9tNXd1aM4UWLnuEY9csVaSsgqLNesLGzieDeKqPb+T5KoPhTmzocLSXTLGl3rDtJlO7jqs465qRvJGIr9bgl26TI/dp20epalXslF4g6lO+AYlykMdgmyoWuGAy3wjzIiXAtDFgm1xX9m/ES45toey1n8sGj2hXyL8E824Lyn4bNhxUzQepQfzB7VaVgsiJnzgoJlVOm4Io6YG28gF9p76PK6rzTMpb77qgwl5H+tk42/5UTPjVSicOwm6RDvG8PnsRppXP9G5Brt4v8xUFVifglH+a0UnjLYt9l21+Gc41RkAQH+g759CFwQfU8KitJ/J0W8etoYVSD70xVrUiMqwAk2qOqD+uFyJlFiD6lEp/Zd8BVhGn1ybWR6/5tD5tR+5XadPdzY8uvUwiV5GacJMBYEPl5c1kDiK/TumeBaJVrFs2jHd37X6z92FtVfJC07X4Fedudrjq6tE7IaxsbW1M+0CMWQYhifmjl09U9R94elO0NmzX94FUr7fa+JKRLptObXZWZIapBsZdojJgdYJNZkmwCSmnzXbVTa3JP+/oWdN7ZvMFyqdNxRuI0GuG1qkPf231fmPzwfY+AKJnCIpCEWhaiFPaahTEHisZKVCACdafeCmDqmIQqigpX+drSmrFyS01vdO8k+THGTbKAPY/vLia0eudvGpUalR0ns+asQ+LILGMnq0uzZnhuGWVWNR3Ufn73wOPnvoxZPrF88auhKhfFtObWyWtLbEH18bIMCyFuyIyYwhSImpd5jtitjVHCd78WwvYYO5u9JlQ+FWBPNd2EiNfKF832QAJ7fAXzbVKW1WTMNztzJLhG8CUageYmahths349Wl/AMpGuHmPTob0nMW1omgkJ7oQ6AJ/UaXjUqLJQ3b6XcpddE1S6V0DL+PiBstlRyNEXWUTrMn6vkibmM7jUuYdyZY+PE6qiSjbHpkzhecZsN+q+f7uWatn7sp7gC5BXZcex7RN8lv6Oxmr93+kzrWBKefjw8tTdSpeKr1iWQ3vBF6xvxg9HIx8zvv2N3uZv8Y7Bx73/BkqCNmABRVcB/zGNKPiBBrW50xHH2Jj+5smK85NcL/zUxnfl0woUGODdLRDVO4U7dtjmesXhUkPqu3acG9kIgHxkU+lByal9LCFwjreHh8HTTQjt/4+7WfmXvWNP/zbeqBHIthsxvp+VRz8hQYqbLnTxtynGYlVWfUAtpebKNZDWOaA8m+LxY5C/KCCD45nE1H1JULYat/ZEhkUL+uNqUEk0rEMV/y5vJR5e3mKmU7T5/msflFtnY+zoLPFnYaPhye3v3awfznMsz8Z16L63JWfDsgff+PUqww3hXCO3RYYM7x5Ju4wOWz1+0zI9vT4Z/Or3iTHJ64ym7lydbwePx0wwv6NXTDHgOWL8w+EKt2bjpxm2RyCqeNCthDNhqz+Pn86mzVwwqHIi8wyBcLFgskMyo/EnrIUfM7WwEXL/m6g3SEJ9Hv0BTX91YTjwufHr2t74InLVl43z5/zuHilX3d+lSt8Qcyf4vAIGNGYMOr8s2b76oxZOCdnKHOqzegOqRuzyM+0beeVZv7MsNtTUhVfEhZvE7NU69PJu3vUuLv8HfAu0Qc/HsanR4glQZZESbN5rkJP1oemki2Lup2xOcFE6fkYaNMmq1aRYydFxtZIHRbM0d1v9pcOWwTyTRFh70twtgaIRMscLcIYmsETHFUuCK8AjIKvlrlSPoKqW7UTR+SPkU0fWKQm7NJc7FHJp+3jp7uO53TMKL6eARt5a3/tF0VxM65uuV+9/Xuj4UmZXP4ONjPiRZUkMM4bOz4akJhuaiGA5QGezQSRgpqqFZZcWvI9kJFtOJhyknyZGgHvMmQBowB0flrK/Smlw2YhrXTaSoFVAhhFwfSDbYA13Ch1Mwa2gturjGazWdcompkKKtDP+zmtKe7Z6UiJ12/mDHe1xdAS/ZTeBOfFRihcyKQQt/UPDJLMNp1sLGGeMZZke66YhJPTLbH+cnWOC/53WgpyX7NkVAOGmFrcCf1EDgU2mHah0j95szyWdlTi2xV+9tpM1LuMn5qLLaqVxCFI3d8xC7uf65vVMWJU29WVHHV04DO/BODzEXfkzh6wq/WDLSvdf5Lhn5BucznbycH231dT7xIl5xxxbKhH/aDhzlJFUx33BoVlM26H5Giq48KnKA+uMt0GtGm7Kf4pIHfnMW3ndWsKSfo9kINXfl0mJiT+jdaUU9SNJ43KjtkrJje83f/SUmaxkl1oduIebHqTPbRCAxdgvQhQro72bZ/TWHTa8aeA9QjY0qOb/eWxDt5y/xWd724S7d3W//9c5diPkzipj/40H/eS15cM1Jm6ybnr8B2dPbyIqE4lr7ESjH6Up09OvY8caMYiR1il0PpSCmdSqQ0KXeaMQ6ioGlPXZT043WV1gMfVQS5PozNcBiWsRFF8RdkkbrkbQDLVXIhM4Li1n/MIWLuMgqIerJUHw1bIyeQreKzQ+0XHjdjd4w9dy1f6G0h7c2tQ+jxR+9oRXm/61sXw9n78mMFaYjXMnHw3UZWw4crbWHpN0sin/0aQLNBBIHVgQxeehizNcxdbE031hq+hvd3t9rvMbDBWA3kwjVkBRMNt/biuh77MB6q35VUC/hJ/wjA5+5HfnEKTaQNQ3s2JXFSjC/2ZlilWDlazOOyJREs4u1JXL5ujD/5fnSd5inv54xlyazFcUOdK5yxb7j0lXw0i4Xrotj7OIbvkbJ8e5igJJs989xGpYpVrTuTaNuGrdl6ip4mKehFfJHro4OwkrxOuvjX0J2HJ4+G0vzAMoDDMkVPpSnD0usQbjxAevosOXI91nF70zls52sAXoEawemtvd1C2PjZjBPHHwkRLlrebpc0HQObV35c6S+VOA55JQVa5cCFdPy6lxdHX8BqtqlBzF5BLHl9pgFPetiGjc2MfSFuPSx6dEgn5c9/0nkXevHo21N4GW931/jcDjfq+cHWsWNgUbmQzrPC6WNogbl7vSpOEuxByP3sHhg7ZeNHJsel5nH8onzzvJ+99dYvmGSDOpBnOE8oFk/dtrkyHJ8wQi0xPF58wve7wP6ng+riBmfWNGWeXE85DAyvI0ykgslKUmzMzJKrVeNT+J6vdKJrcJBSDa8ra//gmkZX5IsJRSCiL4vikVCrsq+f71l4d21C/DuLuij3xFRLfeCJnPjHTrWgBFCAwhfXFI1MyuwcZX5O0ZLvFTNBmWq0rO42zshorJL+4XJIoGQanmvTphnLmDH3xL6Pm7fh10eLZ67Mjd0weu/dxkSfW/ixG1iVNeKQakKcOJOqZDZ6WNtHQwkyv0CQGXYgeaz/6inUblIDd5AfJJ7Bkn3iqUFqUDpDQvFJuJKEbKqUEpQAjfKfZhL0DBSgrG1myDw8SVCT6QrEBf0BLFUYzG4hVPo5dk4YqMKSFqwk+0OiWUkLT8kiMWpOw3iobWCbQ/D0+BSsLGmCHAP3Zd1FNwVksAkqLmei4QxSlEN2IIKnZMCkCSkVNriR22Ar/eLP3bmKU9DLR/awKUvpaNDg+tR1TvD8pPTvfHwxzHqQh3WgMVTHuudPCI/6BLIkeagCDjYG+bu2KKdeF/mx3zrAxEWmGVQMxexeXjhM4UJo7z7q/3NaFc45HcRaOLdVatGOc82GOLrORLFJOCdtNC41jLL8qRbuOyjEO96YlnME56z6bqH6TzJbHNcye/e2+YRTEe6JP5AKaO4TAqzUgopzrcUSIknG3bgdSsIiw3iZrShWK+8Uco5lhxTG+GgPLYxJ14+512Y+Yw64CL6afIMatzdv1tSgs4Z9jj/374jWkNnOl/bQdyMPceR9n2vcE2gzY3MZM38/q9NUlAFtmFtQDT+H5e3SF/ZOlO8O74kj+7F7Ydw9vaT6ZG3ewuKqTcfJ1Q27WyYUE325u3A8n9nnjgizJvdRWQGjboot6IbKBKlZXz/tzgibczvRBeQAiTpkRDF0H/p6sMc9/Kvnh4Gpi32pO/qweXl3B59rNn3N5DK+c3LwkzzagyhvzYJNMH4iZHL2KN8VJi/32oKmBtCkwVrGphPNcPIcNUTN0Ab1AaPQSI1CAzGIjMQozJwwlc/hVsfedNRfZea0EPoO8bZini/JiJfLSbNhcUV7oV9a+ALg1nzKXATRTUG0GoeTVCSFU0BqnIEPViYdKNuqRbVNCFUPc9xv29Al4zT8Knde8/XuAnu+yecQ8jUhubAVULUECqM0xk88PluMQY1Kn5lhLkxXpP+2GUPeDZAnlfMnmMw8oFforXG7SlAp3y8lF+SyjDN66QnPfxIHVfRfyKwmsu5DY0LHHY67zNMpA+JaYuUv+lSxScwRc8RQuiVPZzDNx5MwXBZx/QmYX7vKxuOsaIPMUBea7RWs6NEIg6UihWbTBHUFD1fe81yp7uJsLBsGtcDdkxogZ7WDicK8IIG33/yzbExGoX4+SWQpUSRIRIlAC1MNTNL8SyJDkbdzovm1TYZwL4y80b3R1JCxyn7rtpo73GSSt9p3bk53/pzqpIn1QI9rg5mAYt6lETf8Y+lMYlbooV5tZ6KUo3umCFtTQVGOZzrO7fKl5MxN1/1553lH1i6l67Hve6WVYPRTT2e0Xa5Vjbe97BgfZ4WCCyxKvqY2gT6YRRqT3w/jcyniFwpwqhohU0ZMJmd6j+LDEFEt7JA7gVLeAayUIMhYGsu9m+sdjIfIzLmU0ko71669PNc+drVf9mzviVk1h2v8smPB6Fe4NLXk7UUi+ap+Qn4K9/Au4zZMSLHlvqvX3cN1WB6fpaCVijadzYh46i9dLlcZIwllIhFT1HZQJMA0YK8ISTp+doKxWrn171YrcVlZZlyWge0PU5SaqKP+KCVUi9MRf4QSqNn+CsYbgCxmvWKGUOl1YJ2JZRscuF9fiQ1hbMIYWzHgpqsRxKMDDtmHs1FPxAiN47jIOpwJY12lrZ4Wi3eHk3VDtIlUPiZuKE3nedswwRnDPGUYdnXxjH6eJl6vEWj2THIqlN3Hu3VlAp7pKM6sFxr037T6AwL8gfM/lbB0djkgg8XK+JoyYlVXHJEfLPD2m36WpDgl0/O5nLpS2Mqn43QhFmboKCMSloti+DScpooB6WoqpNr00hWDPMQ0NlVm7NmPXe4+0/goJww3IkIVbkgJIslPDpvX5zjXOOTszJo4K6+2pm1cTe2yZE5EXuyZ610uyTefVturhxYhlr4LexPk6/tcfrmn6XtMJeae0relXp4jMWMYfOIZv8qMeUheY9h5OFf87wEFLAiLghUIIRVUMcqYMif9h7qQcDT59sDb7/Z5bCpGaxMFwlCTMHAitSeYF5m9R7DEdYRN5rjFNChByZfkg2+tnLT8kRSOIoyL8jlFJnIrW858MNyQc0T25smVX4Bu38M3uiSqvECmJVop3rsfUtxp+zF75/mmoaEpb8S/Nrlqkq1cqvFJ9dKmQsYxU+IcGuAM5p+nO65enYC0e6tn8+9LAKXm+F+5oHHLKvlVHhKicBIFgURF7pGG/HuI0XiDG9giae2V1qiEUdJiLCaYV01724Lo96F4GuAYghnwU2vmbPoNkvoxT8K3OvVIf9PRv5HfucX+2WubfupWXj4BKccpZu+pgDDNam/vyW9/s50IzLFPqafrH3k0bfrqOfnJdoA8hcpTBvORx/vLuJad27j8fgg+3HIoYFxd8MvoevZa8WZCCCeHuJnkg/1Xe/Is+/knrnfS2K6AT2nodEIUUYQSnQMYI/LeZPPG2XVLdRmjpc+m70/0TveON3O3rm7ix4g84YjtMX0260AELItTqI8gP02O0QknNo3pHkUDABmpEEP5IA4nD38sHZAvIb6Bhv3rFXoVJwS9LUnvL3df7SW3fEobr6pUp/69s902eGLf3U9zOW/Yynp7glX2t2RmR3Ulr6QzdxlejNbsSPf6WRT8oabd4qBkOUVIqj/n6i3m+/FiK3nN/Bx7Cz+2kt8sPAuH8DmWMBEtqyUG1hBMe4NWxGjVyC/EsWbtE5a6UdRxp+9bR6LbULWz3JCdlvFWMNwZqsryR8o5UhpSs/LnVxOzmr1V+2TYPE6Xjlvheabh/Mhh7G5EzuYfmkStJ13IbBQnMxcrkt4vIsR5cdW8dr7dTpoOutykUirOCq9CLiMam7VzXxTt6fKHPIe+0rBRQwylLrmMvkiyjCFvVx9nvakdld3tbRq+Czqx8mQoYmxB89VjddRfn893gDmoqfa5BlrlDPipSa3UnBVeg5JmNDFr52CU6OaVD9KH/pAKocbm9PklMgZIyJSpZ9303VDLRBVvegfNTwK6gXukNykVf3RlcJJUj/fB5k/+03/xYF1nal71R/bbZt8yvrVvr5L2IcqMmWcyVZ6npd8s/GsUnOgRL9B1Aa11yTXK/ziU7dYsiQ1JzIrVWK25f93SDxnTTk56W6Vyhd0FDGLSrViUAAvWfN13Zi3gXRr6iu8FEXT6CcfSl6Kmit/eLFLUjSHpanUwarOkS/N0XrT0VNeINYJh1KK5+txUtKIBk3ODPLWq7jM58XWixCi1EytGiVgtjg1IobTExKjt9mEQUwVRm0M4JFLtEy1m5uw4x/IjZq0ecany1D9xiHMTI2ppqavrwm1LM06X/Gvc/5XABVcZlHu+OTJaqGcNpGCqEXbBLNDspVxk+9ssOroO/nl76EkTUEGsqKTKSqU8Hu5C0Xx6O1JBVUMOcnS7bkqcLauSl+YxcVKQ3wKjccEBVS4Tnxi1OFYQzZEyKTRjJ328o01k59vtdp6I3LybPCAuGJEdTKlGdaPy0I6onTt4f42/MVwHrMlx929Uo7C4BYnxXjPzJ+O8zYQIKkIoiqKotAB9DMOk/nUCYZG0Npe2H7U873nDSNrQWp3is/RR5Nbxp+6Hua8pOGrIT8xfr3l8LjJ+0cn7as7f35cxvjXR9da1zxYmhtLR2R2k8FNXrKRB08G1ousTYnfdsKE/2oylBE/NCGcdzqIpDciEArSKjrD0ducDDA50Zg9z5/k3PnkzuCc//ZIaRy3MybJaiqfB4cf0+5TfBoJVVC3gxF+xCzS7mXlUPZOT8/2JI/YjKU7JOZWUaBXwORgraohJ8IoR3spIL6EV2sXzqHImhyoohiaEC91b8fLTq45RAY2+3UwETJT+Yb8PKmzmegu/hkFVh6dLBbwqnyDY83IVLkYkW5i6I5Q4j0Iz/ZqVXLtkiqEWW21Y+dtCWONRW2S9YHfL7ox8WuhA8XurudFMdDGVse/5m0bvHtc2nPL7pbVXq6BGddA6D3wk0H7n1zC7ZbjT4A4/K7nisocelCut6xwyIj4fi10aJHq18WqHUHnXArgAgDPdIBkNw6+CV5lXccfi0ZuZ3lhxXgpdi3TAmbuV5a8neNL12cqKL8ld2qjiuv2sT7UJc1jp2RNSJEe26J5ML+p1rEX7CqQJs8pKzJr++lJSReud0bND1B5Yy2R3PrkUUT4ST5QeFxqiRq6FgjK36LMSou8mf2FFuU/Z8YvXUG1c+ZgDrjKoqratF86InUGeAY44xIkMe1bJj4jObpIs7sEh3sLKZ8EqVQSmTz5JIid4s2SaLEohF6y7OHfMd02aRhO+Zv4H963I+Fvcsb6IbU90ORS1BGItPD9kIdxv2tnOc0htsYpE3C4D0qHCc6gayJ4Dbah7pck2ll1DFWoaMGlSbtCHFmbirJJ7DwErc0ZMpd0vsX6TK+K+4XzFxXrvh/ttFa5rKyOkvwRPGFekl08Q6L82V1ndMszIGEz0T8UjZOhPGdKX1mnqBRek5XwQH2CBSLZIegt/TB+mAgQgqO7YC8EH9S9//5AKmOWTwrwCrT1YalcBADJ4Xg165/naHuSy84TluLVOEKV/2gnfxNMZ+ln/MuFDs5xweVJLnCBGXIVPhSIUudQCI7pua691NMqmG37zQk/e6mUU5Ul1vefjpZZ9VsOeECckfp5QjvgddQy+4rHeZ5G4Py5FE0qXz8whk69r//VoXmN4XvRH6KZJ43wl0wMvu3Yw8vjjku1IT+pb8sVvYwjdK7MFPnH1Mxct/3jYz6r/Fef04bjR3WZUqmFkssfPnQqfOIaeXVb329pAxuc5+y/sJF7iL0H4i4zvmadJQxp72KDeKy2WyaXJVzqQwvu42qSVgk1Iw+/UAZ0LQcB77f58i2wNhs7b4BjmMKcwerD0+WH06fsZ3k1PW+zuCuCapkGeptJusCAO2jiGtbefpSi77d3T8ryQHec1jfx0ulME4EJcL7ir05mddAxBWAOHBK7qNEbtL+qsYquwDBxx2G3FVkGZiCRkDWBIepGfcU4lYB8KSqBQQwHUzsN7HxUFgRJpIyv85NP5zkGq/15msCyO/fcKcPzhx88/PDGMD7DN8TDDOi7soyhcF80/K35owAz3mBj7FFs/WmskP3+5Uo9kt7x7yWvVYjtNwJjg3yznouM2D2Vz/L4w3H+fKw68AKaZ/E4Gf8F9g4/SyukRldB2qTds/vaWicQNkscfFmRQhT6aP/z98D1OpstDbCKL5lcij3As4Zr/+Uzvs0H8+YjY+l+gM8NiC86AZya8QjTJMifkfSQH329ZCRpPi+KTVcT8atEVR1Obpp/vCVJeP0s9LQaX2VA/3upYKSb4tWjg3N7vZtHH3Teo/XUMVu8a/hZT5DdFEScQ9+RtHfdsHow7/IiHHUuCLDYOc0KExZnLF0Kc9zMWdsBVLafba/8xnadw1JmHn2UUQJA983lbrbUeVNJKNJj5cevbADldFDORBvKhmRIlg2wSmkeEFMFJ20UousVeM2495EDgI8lDgNRW0yQGyl+XHzAASVt/QSs/Qxakfe6g/Y5YbBTA+0+0Z9J/+dDsqMc5op6SDwH053Rez/EmT/kA/6jzA1CopD+iZh4L20vySL8IhAIs/PYIVrk1W7iAf8Zi/MD22iz2epmiR7g1C+GPM/7G5/g4/lbiTdiJnuEQpKzrlahbYA0rPyQjw+fXQtMkMRiTq2qtbxvyZOGrsEQegiFJBOymJZB8nwxFVmCCLjE3ra3QydPzofUdycBhyCcnyKPOF7z2jlTTppBQlE9REBqqo59/yyN/PvERef6i2FhXZ6f9e8HVngiWfv+sqN/xR+rmylUs2/VDxW/WwUka1p8QeZIwV/zzf2lq/2U4IERrJmdfVGGyPdB4+/kzvuBz88efVpc2IgN9jlM0+6x8m4ehKZE+WpN7s/ZeYy+m+dTR918Bv7dA5j1nx/T5skJfT82iIELHYdfFx/xz2kKaiT1fkC/GYNCUHZdyMSIcTsiVgd2QOzJlIXIMphZoTq0LRHQBbIWxQNx1B4qQvv15IixnEq4m/Atbw/PE44+Mf+ucA0xfCDQE2SPuoWy5UObKCNKfF0Dk1uCPKpjPoP+zbpwcpOrfz4fQpxT8h7iwozJr8rGb/oavB+fzCH6/fCimLC/chqp9QGN1g9Gy5Ke5EfxNlHja4PjWW35oCBcPavAiwotrlsRk1wY8hjGIOJRFghXs4uSdesmsMA6L7bR4J9OLNsZdt3+Az/rHubhKD4n3rYHsPGXL2MzGGY7uqHaE+wXRWSvbdA57rkmoBgfDrLY6LlCLQb6/zQzOYJ6UNKRv0oCQOKrhQaCMC7E0A/uSKFnzIe+e/eTKPsHtfW/yQlXzYI9hh2oGjEF4gSHoUYWpPTsgnAIoX3WCHqJwYGXELya+ma3E9e6fXUHJaxrip0i/tyV6u0glaUcMQiMladLggtfOMxNrriRPXziNbmwW2hnXDJBR+5M1SzB7cyZlgW6U69XtFQVyxecyXSy536nHSoqDJG0HIucVrHKtAij/QBURXI5er6KoQJY9uWLYTB49EjlpyrI3FiDF+ASs6CPz5qQrwZjusiZJCh14jIRIsD56eATuwldLOpoka1Tfg6ofuWCxJiGiLK7wjxYvVQ9k+JZQ7S6O3hkCVx3Xhl0vMq9vSazecQtJwfFt6rBClH0gAaF47yb243glVDQIJ9W6F6icd+hV7f8nCV+kiq4l/dKb1/SXqfXVUTwal0ox9qcDGtxYxsLI/y+KmWNBysvYYRp+MC5ivsTjSt6CQZJgpxwyYKHCBQvQQGC1VbaTMCrcX1dBv1yZfJIuE9lPfeP4cSKDwJV10/SP4FMKOtJXQzSi2SFQnXYMiIFU7d3Chu31drqupD3JYLkk4ckEYbI/EyomsPG+sZ+f6VKTmBeMZ/YUd3ii+XNDj9WuyRlDFwbbnTZv5Jig5IIIGlVOdzlKO9QIOp65vXJWsd9PPjcqe5sY8o8vOxuz6R34lIddSHScJOwNLJ4ECLLCoMUsDpJ190CgfUYJ/8jHJfkUhkb52D29ZbfA/UNcWx2t6npHdKIP/BlFu8YZPcirfghwRb5ZwMJ4e6e210f7+S5tIHZSCb3FxJ5EzSDMEwqNvn9UJXyLPKgk6TM/zSykn6sE4JwTQpyMMxZezqj6+x7PSewNQNEkYSg/gnS7yFBz3WM3VgbiCeJaGxQH5DB8uiMNDFJoxc308hq0ZvY9VQQJj1fvxXivWiMUgdsHqYBETUDYYzIZacRKKvJYPkNOfQW7hapl1gJ24RDoJGP66tbrZWSuEYfcemqKYZ1xn+YRtG0sbmUEvvcYY1ZtREArdvsQUhp8LEVo+qW0oF/wIDlXvvZZueObkJmEB8uc34ZlGJ9sWyrCl3AcbZsoIgOSqICQFc+jmjPzsunScy5o3Dypa3xxYkW7CZEKIhwqit5lU+iAJtmn7Eqwy12uevCMAeI/7ol2D6ZAiaQaIk3Ikgg79EqfhUxDOinr1kDTwhD21k6Kh6bDg554I9exwnEpDHG4Hyxw9YEJTXs1lDjhj4rdPEktf0haWVRn+64FmOx3/H/pjJXzY0Y3uLn/W4pDoEy3pKRHsTXUhZ1DwcPgMvLgtUP/Va9Js8PhmDP82FhYcOVSC69qXlfeGhK9mgHzocG6WQu1Vk1C6Nqk7kDDwB8/R4DaHW920XcfjmfyNtY0FFPdjSJ48tLWGtcL0cec+/ZWf0ymOnZIpjte7E3mlDaFD2dgDjsvkbadbZPKhOpazlw8IUVJabbn2EFAfnsDJvq6dZmKQbmbA08BzWFBNamXKb1stQ5RNkScXY5aCKeTG6IFDQvNqIrohJbQvXuie7Gs8DRy1572L7ssJt6KJ3A9CDa8CWWFahJ6K0HzJmwpjplEHhA8e47INgXw8yTOZTdxIXiCfAOiziIL8QTEy3nVxuJ12cajD/X4rnWmh1W0LovzcaS7PP+k6eaPbcb3SQN+aBw6ZXo1umYg1T96zcKMhS38DPh5flYmVSaZSdiWJtIY5kHyrj0ig5uaKVzkRXFecrzhcjyy6pIFaYvYsox6VOgCqIBFremuwu+5QhfKBN+uW9lAO9NL28FkCD8IW9XO06IeoYs11WzZHobJgf+v1pkbnzNa17xzmsBPBmJ1J88bjAsPrcdgcuD/q+rRvUdR5ejeHhZMBmP1++4a8PmHGzBoBfYLAzDQzhLVwfqhH4Sh/yt1okAohmbLYBIF4RaMmlV1L9o0muLaq7LcfRJhoa9mr5IXiMRous0x56UCDeT33pnvTwAGorOxcRvXgQNsbq6l+Q7ll1LfqggchhXSw6jipjnMjs63fEbCJ4mn2Cv0vkAz7H4TbAiVN/kiWc2YUQ9yWBI1xOetIScEgqCB6u3111CtwQAwAF9pG7DgMvNo8xDhlGpB/LxkzAR9UCCNyQEB5UNoeHDYwvyH2nfF7QR44p4pd7BnJp8FjWdDz7B3TNkDbKwrRCIwjBgmOAlPOP0EszucGI5DyXwLb97nZoug9QyPDEs5zGH2vwbCdM7ZOHzh/xj+zVg+xMESDFq2Abq99KskLEcMIjKT37adws88f18fPmV7NhnkWImUwhMlotvtAr/mDxAgFxO3G2o91O3LwZPkOKrWY6i1g/kzV61tgN8jKTCfagcehIkayDB2U2+K8HpO2EUjgbCu58aDmvugUGq5QLBMyyskga+/w5MEbjHgwZakW5C99WoqSVLhD7+rYD5BN9XbVjWGqQKpJPpDD0iUmc/gaxJEjG6yjLU6dQ5jj+OkMwoeEFk9vmuqH6hWj0V6UUafmkVcow41E5Rn4BiUpjNqSaTF4JEQGChHDDFafDvX6IDuYYGjhHY2M+BZ4QGpiLyD/7S1NgHbzBA6Dwq5x0xu6NvNYOsSr7xR2GjGLLQa2EeWn3MZWJH9ohxr6cKMh25wnCrxV1WU+KQXauzeGkBUkUp8FVUlfulqjcNTA6ouNl7yb5jW9co906dt8B8vASK3VC41BaXI0oJcK5rzCdqQD1yMUyXfJps6OP6fxqePy0cXALYfPLIKUnkqJiy0hUJ2yM4oQoOfy10PmHNbNeumE/RErYJaU0irlJSwQkhe4+WIEjGNKsxtFAhz71llZa+Q0CK18jscrfAUScWUFiShlSS7e7pRSd6MFniOdFyg75MknKWRoNn2N0tksDQ+/ezxQFVkzl0tqi8w/G5qSxLHJAz4ztiS3byNywEwvoUcOzdy480GfnpaXv3HUQo2MMRV659SWN4W6F3lq5sQHvLU3Fa52wD01Z6Aq2zJJcaWXQNcwEEXDLVXVcoNa/l2Mmsqp6t4Vg7Qns5zv4moPy0xjU+g1K6nMAjjw2VZgy9FQpqsaMdolWDNwlP+6ERAdaYQHIUG2YaWTiwVpuZM4aeUTAVZJPmIi6cIU0DFjJLOt93Bl5NDMGId2dQkc8Q5kMcF3VlJ4B2ltRvGqbsWg+Eh5tOLfmWH2E9GfwPnQjYnNKO1eK1it1nAfGms1Vqp5NOuxcsstU0gcUY6NMUqhsnpgETZNcWnzVDnzZLmgsjw5wL+88nJ5/2Bc7faeF632V6HIHMAM54qTRTO5OxJ3KAiYU6na3YN+s4emewy5Tg+PqXvWFNZQJW1JFU/7OFLTNzgSnzOIt18gErH3HRfFeJN8ci7GztIYRLBPvSqsqAiuQMgUzpUIuwTSsADK2Of5XE32/V7FGmLnn1nXF4+LpWHR1Y3lhwGIeiLrHckxajKQiuVMi7f1uTiujLwtCStIaNBKe7OnaJEKpIr5JwWoPZLm6qW4E5K5SWLVPB2KzL31tnCJjTn1vlgyl/xUQWf8kQKsLvUQ8zxqU+kcpttQDCV7JRWwJBA4z7c8V8kWXsWmko1sqG7FFzati/Djml+zqLtFnUP7hZKG07WYrCH0j4aAQd0Qo7BJL0TsPzocieGI+v5JJgGedFntWaDAcbH4jm3rQOLmP9Mcbhd7gyXCGphwmd+yw8u94+q9dME+L1LsFv3k0fkcjkeuXwQjBX10x1Cc/hK1dHqcGZZVWjp0/ZB6RCWgdnlKTmSAD2dDIxR2E9LrlHQxak9eAOYxuKeVQwV4/o6HPQGmTaf7VXkH459+3Oh85RK3v88LQlB05RPCMrsrUCCsbQsZxovIpmVloOfli8D1q1KJ25HX0Mp01KBGw34HOX71/GDpbXE/6kz8phee8V7VR642paWqc8XV6l1v9VRaTAQnIJszqm/0GTlfXPCCy0KD2LHup099WjIzlM5smTRTtoQrkGgzdPdmU5Z8ByHkisIuWLLY1QecMBoJI7TEg1TEq75VG0ylRltyioh22r1iXxQUYOgOtNYV3CeLub7LKAe9BezWJjeu70ddnP8fylHLcb12ICDF35nkQhNy21paPmYVLsVubJnNmS+IkZpSsUnpHnMYgM9xvzAeKNNnaRSS9OLYfY1niEE0vmrD59d/ha1o0mDoytsSzRDAnyNKtkkpkdZblW9UCPzNS0ZORJwd900wDZ5Plw8rUsKNL7t0Vacu39rAU8dMtdT9OGSWnDrBrZxoA72o4a+ZlCbQFIF5PyR95ITRU6cR6Y5Pzo5oYuKxbkEKw7Cm7nTHUAW/Haql8h9NUvwkOn2NSGxhgTh7BbURB1XC5D57L/NfmiVonRhs5FV+OY4qIus7vXWY9B/Fv3vPTmgauOFf1uLy/kZzkbP+cuCsbhYSYX6CMCft834F5sEL5Ilq15T+WViOZXp/77uwm+fpfpAcO3p4FVcX8bfLx6dBejxJfe+fHC4gWlfxFc5HJzDCQKQI5C/1841cfZeHwgIEwAUtQnLZyrulRWmULTlRU0fgOu7kUsA/pEjdV/9VAHoS8zkqDY3cmVzlc80v5xYDhz4MAAb0oxKQzFwGoSAlxRHdreKMgpQQWgSagRx7sb7Zv964Jp2yFGS0H/Lh0yFT7TUeMfdxoMg2LVf7geiYbLHKvXLO4DDNfghACPpp6+gQahn+pfWgmQQdeHZGzZKy9Cyb+u6PAYCW5v+ya2/Ogga+SW4zePDPj9AiEwXI0MecYboGUoGiGoJhEFPUcpzx6s6Cwti2C//w4PWiScDOCCB8G5N/9DXFKaRryca+W6gFaodfqOtQ9NsF79NxskggvOItqlBe+vTut/km7VNcgNeIsyKnAag17Pp0dB59O/QzpuzHQUAqpno0wJGG/3F/wC0zGaSoo5ds2nq9IEllwtXmiv6skrLwalJMc+oFWqXVYs9QJaH7DUHvvdWiZ5SXIpEFMZhTwpOQUCn96Nv3Q92l4XJnyIXQbn1yVOPbto0ByiEOpT+UUXfuBHuOyjG0/9M9CUmFK5d2AD4xR/EdGsGQCuAIGdxcBS/wqpQbXGLpWavROz5KLECZNP6pmBHOzfFXa1rCU+bd+zlLhyIOuHQd9dw+abp59U7z0wAYhcc9v1EZUV5qJn000ESEE7Ivue2nH2bfRJy3G8DuuY9p4p7AyNhYJZWde9dIZc8+sHOeC/6iP3b0D+rbvLapye/D4C/tQqt9K1Jmck7Vw1NfzktWVwElMEbbhtZpnodVwZBZF5ESje9umFk9fc5ZmTnRLWe3An4NncJXaa9U8QFQERijjzpvb6t+a/OhpJP6IYty9mS82IlCAWf4Tus+Y8feFW87ZslTf6KfGPdcaBF5p3JUnJK2bc+RZB0vip4rgdwLhALKovgZ6ZTAVIwHinWzrs1cVZoGdBYq6BSshxw0PgVSdbE14uVbRnnRi5lC3uhCAK79H0ClQ3lT6aQlboazVP3sGo1VdEEHygly9t1XhE1Pq+tL+ZaKxebyVqAqEpezmxF8qj1iKQK5kfFjwNiIDlhUXgr3ZzJtFTV6Xp8GjhprAf8nr/eRt92OEp+FCMHfw4apQ6xs8yp8QN7LL7gh6LXPe3lL39mOh2+YVlgX1YlkImU9NevVTnXYKPY7jjy/dBrQ97jIIpOPpTf8P2QjI7a82G0dkH58PoUIPDLMuO1Fn1E26EHxw4LhRZtRAo63UI0LQuE192zkO64DwzSi0bTi0cKzbW99ZW9X2srQSI4FSBtE27LFevBZ2APBEh6okqomlQulKdVitMB7bcWjdusUcJmePr/87Kwj60GRm6a6ojWBwzP4Kqrb3S2hrvwpM14PQYxjv/UYtwJ0lMH6JcWWzUrvr0zWsq+eAEGgK4pzeUg1Hfh9cSK89HH8WqtZL0ABIp5tJC6p3rE29e7rAfBMy2PhXb855s3o0TFZGkG8Kv7tsH94VANouoipaNHpm8nK4HX3L0rz917omrP3HN3XAVPO8mrlFwl9ErqL8fN0smK0p41+wKmUvkrUIbyZ0XFnwmQZ9+Y9dMBgDSxoP+hAomlP1SeKIoqkmmIcCO32abISA4I92EJDM4q41JmcmD7xn3wE/fviB5UiGaiN6DgnOk+GOWjscIpOaO8X4Hh9mZPVwGpHHSX2aD8h/xliGD4vS+uS9Ba5oI+NibBWBjGMIo1tM1gKn1Kurubk8vcnLtMKq5qgVsTx61mF+qBWdeSeapvYWpknsvitlqdVqtB8u7MzeUzBHEKx9+F6bXAxV2fEIHFudhy2es6qar3yuIDEkZ1DAA9N2TGvwwfa/fyVX88QEBOFocCYjLHcVVCwV3aoTKglHN6LarP4fLsc7yVaDw5PGUSha+HEWvW8XAY8PRKE9J4Csym4QAecGChsHQ8gQH3RCVXCQZfiqWXZ9RUMI0d27fYnmDUweIreqt559ZhLjeHzWAnMQVcyuhOed0xbeOnyZt/vTe6x/kfvrghTfgYR4HunQ5vmEW6rhG4BNqUHMgm5WTN4pptwd6+uiQyywjSlems3NS0aD2bBBc5KZjFQbbh/sSMl8V8cQ1sLh0tzYjGV93x7uDMioLTzawxRmM8ncqb9rkJIp9ARFDVKDpdhN5QvZwO55jIGVea/mtroVYdv4ApFPRqFvfidwW8QJUZMnrUnmvGhWbgf4t3cyfcD7X1mYu1h/ftC/vogf7tzRHWFOuTuqDyLlejb8pk0wKoRAtUKknlMT9bTPuRuCTsCsV5z9UjyoxEH0sMNG8utw6Bi0jrEj6IQRUwDWa3QvhblVWR+M/jNEs7KWViNG/JAkJ1Vko4EpdP5kN9gG6YZ9DcUzq1yD9S6l2KCdLx8cLZ6CAWEx9ecAC11/cAyabinCJJ0812Xq+OVBznHtDiFozPZt444aDrfpx9I6IVuZ3ag4UalQWM44mS6i85Y7Ik2sIKSwFam6OOI5R8DUosPVowJh6sIeXT0YKe4sOegTWMLShOffOjrHSw5EZTreNV8Mt6pGA0y+nyOtPhPK8i76hD/sp/zPBhFrWdF8PIzl3uH+SIv5HvWM8fIDgGsw9H3PHalbsr7YLnThBKpWOHfnBpGBBbfV/TLFMMFa00lQ8QEAYyEBYaw8gfMTOAA1bzXILP4ArataRsVBRFv+zBCqq/mKmoS/rcSts7y+G4dWNUfhsu6RKnAIGnNaIskYVW296DYrekF3wurqwSJWZ96G+gr8C25kZ7o92EVjXwiLDTrZPtg5dKoGQDoQqg5WtQcfuSheEFO7ubxsWm5SpiA/wYosJ+YSl6z3EKVLg68FIU6+ji7z0OFYc3ZKogw1OwE4eogG6QrEYvabI7KaIKd7MJCCfSFSpCw3gfjugih6Mqpt2LaD5Bnp9AHu0l6DsA9Hqpg4YFbr1hmJBiFBw21LnBrWiY7PtZqCckQIz4wJbWzIShV8W2ttW1zY6ss07Huh3rWfJ733x0/WRFeAe6Sjt+WdRWDPSsZcXOxZ0mZ2+pEu3KywQG24F+OSWwnS4NDdjigLtNcfNCZgkbt2+tiX4wiZD/Ng0OsmnduRB0xlGOLVSAAv/YLSuDmYdJ7rTcREIato65l6R5yWnIYU64CSpjbLF22Zc/jsrpxRB82lOh07UyygTZ5+M7VGFA4QZ3jIhdwKUIQs1bsUXKfrtSPoAQ2TwCo0Lz5h58fdqfT+yle5sJFsVsHGWzm5vo9UoRLaOIlsEaEKxLMopKMnCoFZAr6a0y/r6KTGeAI8gGHb2LNAM8C5oj0/5s+iY3ILg435U2nM+sV36xeG7qPdAC6BpBzYNitnn/eAPcSDOAhNs46WjGjkabR09xYIcOdG7s5hrbFHV8622hSOKWYAnyuJLM+7GVlPeRdOh7qVh2ulyDZ2AR4RLXEe049sOlO99W54Rqv32CspahKFbkU4WjrLxkpNcg9i79itDK9Z1T31wTJhBsDo4sm0YZXUeshpm9iQNvKm9e2LSnZNcLa+ZZrIhcMEYyFKk5YifWDQ2F72pev/8CyEoxeSnuRHsMCwU+yseN4QehLZdJuQR+dO8LbCsi5A1kWL3pSOHM9LKT1fkkWYctFGLPh7MAJ54XzxNu7nEoJshObLsx1n6IhZSzvk5MZTmZNptiPm2+HeEAnIiTJhwTNrE1nRqyDdvURG3FVk57HDNtVqH0ngqoB5k6oXIw/S+l+0OTtRszteC0CJg3SHAmWYfrfxKxNFiKa3QxB1KMpSu2Lu403K8ZU++mNQuNGcF9bbtTnoTuYiVOrXZvtKCy8MRfXOePPX/ZtJ2+1pR/2tSx8K0p6lZPtGtKHGFEW63zfAJ+/3YnufKaA0ntbxa9j4Fz8VKAF0fYmJqs7oyGED3kK5mk9ZcmSavMQE8NUDVgwRYTMZnRmImuE1RYWKgWrzhGRhtopgoaTZxzCnMmmYlNv113usf1UH8If2aTlCaT0W43TJRMkDCRO5gPgw2e2f3jL12v7017LCDvbzK/sUIhC+a9968/deifR2474xJ+1chlrihizDl8/UJM1VdbUn7qZtSeOZUT50DIDTQkn/vs/psRPqjPSIwebKgy3xbi3PdIR26dd2KOjqbNPiY0mG+Umx7bOBi8v3qbKvMh3sp1eWkSwP7MiggUg+CGERQlB7ms9swXdS9KK0IgPlmC4iQQXkYsMUk1MxK7HOiYdPKA/uFeXN03iSaCJOF1t9oockNBKzPWjuWtU/5CFYoARNeC1jMYbXin4GQY9s1NzyGtgjlXXuRqCHq4wqN+Amr+vvH64q9IRjAFB/a+hq8BA41KZtjXn7hNeR+kmRmqLCwWuzeBlze0r0vShx73SP2WdOZ4aYVjfV+eaUi7aeicxyJJ/e27ka2ji5EKe+yr4FuUHF+Jrt8eU2DDeadCKwz7h3hQbheMKiwZvvtswxpg5qw0diHCHiG6NYhjEjeZJKYHhk6CjUbTJEiHheFR+AbFG1RIj3m2CPUNm6hRIDf7DvYRQ6mwtHVEWrwvdAQfFubepsRVoYURcG2mCqXPDJ4FnDq2uDkMtYpID4wChI0bchxT2qliqyZ6/1jeZPFHnd/26oCLzkr9DmE2o+MhLX0sOamEjt0q43wvSa0VquWHyHi3MQHJRUFfrD5eGc3HkJu1mt2tLISpG5nxJH8Xqczw7BPt8nMJcOquCYr145djlPtGggEQY45rCk+5p6ipOeZ7d74dY/gVS+bdOxYDMIP06iOF2H3mYusmQO3YMmE+yGukhiy/gUl5DB7YwomEYVG/++uhkLnkuBYdyP/EUIt+2jTVOcyskfLrCnj4tLFuZ7Kc7OL5jJ/TkitP5s7jnV4Vnparyn4+uuRfp9HpnF1Kr5Tk5Mdz4/E8O3C9bITKypIYbgwrids3FBVVSbM5ykMmsusFOXqGlNI+DXfb0+mtAuFHrR5MMiKcKk1lILUPdZdIccUozlFDmQ05x54OONwy7rfcM2eLIC+EkCJklyORUHzJm289IZQcpGg+vJYAAgpHPPU7fXF9XbzoTBw1eXzNO5TqdWO3cgVXX8pkP//MXtSpCj0sB1ae4z7f6LUZ27jTHcOlhXjhuUPWhzxL+bU8u25v4BvQDnsjyIUPcsn23u2ym81UF8vlwA4ny8kzDUb+MENcLDAJp5F0kpiKIBmtmsfdGqjDgzPaXV4rk7jqO+EvTkI2K6pMiAGvpN+RScNw9Wr1KfbdUVsQFuh7KMCXsaUczKDMb61RFgSyA7nSnxPK0eXTFSS5D2MKemajTecSuVp0eeGwJkRzP8Nz/RGFlvAN8nNwh0vazMPF8L+IBVRUzdRrjH3dYiPbHsCVHEnRIPmMNAsigN3/6jCqapxq7QZ5QjHXu7SQDb4eAdk3OXHdYkmRfhskrE2o70e4WodUYkyDcgOqigaZoRpYw6xaCw+CNLeBDjHXbJA04BeECT7/YMD0jERETD/XJgDJFlugwSnmmkZiWJljRPhaDjgm0FgBOjjPHEZnoMbNIeveuZp0BszAyJs59/+m9ytAWr6YVFB6+GzLoXuTzzv+aQWAb8nQyR1DMSAQPHP2Hkfb98+02oCuc13oLXY5vXBvBvADz7rjR1H50t2tRCClyCBSUJKVD0Nig8wYdOE9TowKWXkud2ZAPl93rYWfE6gCNfpZE1t14JQSfvd2qkCRPrL7rr4desp3ixHCTXNg59TYIuYhp4PZfd1suXcGyuSzaNm+FVVHKimiw7Uf4ISPauX5crIDy6sF7TLJBKWYVqJGhnes3ruU7GEdZpfRxIjAcl8k5yAWgNhS6Jtkn7+qv/yILaQK/XL4f6pf7+1drYYe4slylniouPaxwPvWFZ55wEUg2/vdmHuAxBrZtn4Ucpldeaf79LmvioKfmAwHF6gVdZdOm2vq6ZAM2aqKf4+fTIw9N9jjZkSoV+NvjTOHVT1/NGvlbTByIqc9v82kKqFMnW/v9PT5WDBtftFVJF5yzDHQA+XIpaSEN2UcQNVZfAmIS3wzLWCjFaCT7w2vR7F1zolEWwnasTI4gOzGKtGGPWA3nhbdfIJtY3rbQY8vXPBJJJF1diKvJr7rqj5BUUlvtJsWBFC3L4lFCO/w94c2Bzj4mvoD/52bWG3N6quMv1rBKl5WEixpRqm2KDPmVoFqPXOekZpS7glQWr6y06WwK5oTOWBuAA1jySX7UaPDFXzFEfy5B/eS/OEO2FA1hgYjNaPfMxwL3xn/jm6VKQQ5RYV4ELXJmq3+TqWoZRbdoH0DGVwb5NzBRYcR7w4OcD51AjrWzoR7KK42c2GLpl3NSRIcLUrSuZGKnOXJCGG5/rulH+p+iPTVb17X3jN06I1Gvv6/dTCop8hwBWiCrtU2FIgoNUNOPA3K+eyx6j9il3gIMTCW5Xgf9InX3Y/0izGtuZuGkOhrDsg56cr16mRFxmV0/GBBLIkkYG+fHJq5MslBIVlGgGnJaOe9H1cpDwKemp3vC/a7sICSvmFU9G4Bs34qUP4hezyjcjVJD31hWYK6SOzhQCsl3WEfktILjRTyMHe/Tsq8W2xHT1voT/P5VJCRboSNFhkLYY4lPwy7QYVO4tWCcbQBjiBT1AiMpOkzeBZhZXHBo3eyhzffkVS6Hn94Dc8Wrk7LQQ2mkVzd25rvQ2UszcC7Wd9kL9bgXXacNPG6dxdQ4VQeJf1Fm8THJTpJelGaJRDzehIHw/9hkCFuiwj48HqBQ0At7abygjRpbswbNFqEhxbQRS4HJoXbws2Dt09pbMgNsNBbIIinyVStne9yL82SAuJk5115rzbjNS9d/t110D5Ely/OL9/pOBCejdoANWPTKcvLPqcULrmCYR2DPSypNda2Sdf09kDmJzWu4IfJG8TbCO6Kr7kAkV0EbdIdR2HpjdYJUKFEip4ppZvUH1yu3fcNtCNXw0odu+I78X7/v1WEzg80hB4z3YZE0n9pv6eUjnZd2Rg1NROnESXzos3EEqk1CozRkCmEqCZ01gDNuPq+0fFkjd116D1bcW3VTARJj/L2qKvj38mg22lmS33Gfgjw8iTMR9mq0qVxY9krtuERm8mGGHtNNoKDRMDUDo5gbiICIn0kUg36hOpJ29UqwJXpnNnKVmILQSiYAsV04qgDU7DhZDv+A6wL6HQ35876PbJiZ2afc8dbsdMGRC/fsrgmTYdWtJRDV+RJKSKj9FXHHstw/hzpfi6SnwvjUPTmmJhCiDDKUWOqMpApBBBSpUEZZ0tSoFBxwa+IIcxbNYfw4Lz9aLttJQLrCvGKoWMalHVxeAjZ1KVAUX54NtqByHwjtK4KgmBVCh5F3KoACFSFkO/hzg6b6pkWqtLb7tvVj/dckKJLwggBW0HYu8Xn2hcpQZpCRJQaYXi2BchLdOAWFLXFcxoZERbPST/vCAYhIzZO4pxlJZ0fkyRV8S4GNiGyJNQPzJ5tTY1TwKS9H91TYRkdHzXiCpbat9/4J841XX7FRDv4dUnGVTkvL6Xqtkrp6q2gHZBSkshlwk76HQqf8d8XRajNvR5XOGyGVaGKFFEgklxGSHljnS3a9Rh3pK9XgHlHg+/3D+K5QXl5OZhq21/8ZzyPHo+IUoVTaEWF6r+Qe0N5zqe7gh29JByj2VKq3BWqGlVguqyyDpGaMBu1tYzIZKisgmgaNBKw+VvyG+jAQyKu6aHx+qL76egEJNWZ1rNHUPUxWQEFVKXsIt7fTyqcWeG9Fu6fU4dwmcvHVHexy4aFHsxjoi2OGgkF7QgZZsD/yq7xr8aIz8fJrrD2M9FLzty7u5J/dt+uS1dTkv8FGvB+1vM9JySUXvMIVKR3FTjpf2iS+6nSeZ63Yy7Qo8pmhtgG1AUt9hFgB7KKb7N2nyrGQJuIgs9qsQ10dbhJnBdz79cLPhaKqLfUsMFWf0ggWP8vrTp4WBUaDHQibT3ScOuEXp2bokO5chrxT2eO7bRyQ3eqSXZtZMHAH2eZyX+EshU5AXoeqXZc6dWtGv6jEh86IchtqTHzDLFocF65a7hwi5r8FC8XjvwsYvxrj0WFEVcYblk4TgFadgk8/defgDWle1vnQALXBp23ODQKwGmkTi9xAv0hz6zjAZaCEoAftdVCTRnItExQHawpPFj0BLd1dc2pzq8IK1mbqBqb/o3jMZDUZM4lihrQMPLyTPeGYSVLelfPHC4nY2Ut6/q/pzKwN4C5FBes4X3hSdxEkUAcQttrfFOD4Fy53fZJu1rFKkslWync7Cf51U9NiB1yMEFHBmQi/aunI6Ti5WTukR3j+tqJszbgnUH8aSkYtQTq1uLyINzNIPFvV41t2jyIJLRCjoF3TlTVr+JChQw3knL1D/1H3Qo+CDrIMNMII3PcG7kSCtfRDOLDIuJ+eq6PKW+b812thQXK9BprEaMPfKIiuFVQ/LVYt7bqNPpw73NLFC9AjQkodZKulKML7YIw1dKAM62XbdN26hzZ5dJiGCvf/hn2xBGWClt0pxFpLei8hCsLvmPuT/rnTWOPh09AC6U0yfJp41W6V26w3XWDJKuRCWFI8sDYLpa/9/vQDDcolTL+30RnZbmEaL6V4d4pDUu/JiG/RzMtgADh11LefolPw6qOTQoHcC2vdo3LH8znH4ViADoiUP6ZArSjY7OmcudFJ/rPn2Xwta8Pr2NDN6z4aR4EaSENBRD7KvKVKKqnKVivaeA+OlFjLO5vmqrBN5SooKoStFEYLUd5Yhksk3VhN6HyzonQ7Q80qpi8mZcnUp0SQojlqS4S6IagG7r77OafiihVn0twhr4nou9jmbUsRRe4xEQchagkCEFxuuQJg+vimwjSRNqbiTMCImIXakTvwjTolnZAuLazC0rmfXWzo2gr/8l2A+HSaUu7TcCxxRU6LagKmB41zeB/+AFdkUg84JGlQOGDvirQyXiJ/DMOaOxG4mGaa1BYC5uRWtgEphnMMRbXrZTxcQortYg7/3sQNK5H74RcUkHzEvZCBI+bAzJKU1BSsJDLsnyrkv6VzpK4L7j+Gg4kA1cJHzTLWvdlk5BiUICZD4gVK7gFpMJZivmavBy/Inr4eLg3MDOgQhMFj4Ekytv5AHPlhHT5K0a9eCdEBPgtjfwnzn9gY7onn/bP1O4nQ2X1wiO8zFJBXN1nd00uqArt01AfELPD++Zp04rYsjbAeVPpdSc2FxYNbssOl0Yd+W2W2v3IOLh3YGDLl4JJg57XBeKa8pyBfkiGTKuJUVTzqSomZUmCnrLIKu95+s/qrpnt1zF6hVk1bas8uwK1mhNXHUApMqs3Hhm/nrn63/jm2h/xKhVI9z6iUN9c7bYcJDWb6uRTzOjc1pkswPohkoqWRjqbPDKp9KTijteuwbTanTyNaqdb7RvbyDlPgh7S7WtTE9ZMH6wKm1d4Tm2C+4C8JFtyfadfzqIBDT7rqYMAdkhtzkYsKDVklzTqPpRkx4dGSinW6d9lPs3cIGP7jkxV6zD/36uMnoVvWXB9tCPnhkCUU5rr6VikWZ7jfXKv+D0zvzGCdZ9rLIZ9t3dO0UhzLIaW3KKlC36blal1TzR/RdsVOPGg5rvfq4A25ps2kXwayXby4NOO6WJ/Z6B7Y2hoN0oc4pmgoxyrHJw5hNRKwTmu9rR6ptXvRq3AU8HCY0fqca+3NCcZsDXsd5KvOl4KhbF4+5tG3Irz/m6ay6S/HBXdk8rXm2fHujc4BAbkgQopNHSi2d3nNYW2MnJ3ONMVBwbrK76imagWMou4hBGIyCIQEYGoMl0pXLkEdswiF3g5Mh9Kum+TQgwJkBp0oKsk2mrQGyTLmjRbb5CvZIm+2alR/RTsylQIG8boh+zZIUZq8S58oqLZm/hb0MbCrh8sgIVZqBXYjl0LjsaVXa5dMH7xez+j4XVVIdF8cPQ9nYoGU62Zb0WBbddZCEcB3B+sC5ZIxtRpinqN3pFV2iamqM/oQzvuciQV7SAKC4HqCfOB5ritWWpJSJuks+qIAPRGfsKNjmG5J6FNtVU/u9piItVFRKlhQuIwEK3WGB3hXh3RMISTnQJDrBRUGJuMZpQlb4fWveWgagZndoa9gdWlmrd/wvmo6d1Qtew7UK5Sb9idEzoWUM1vJCnvAPvihTuqf18OSiEPEtw93afuADfwDNgwDMtutTaDMK+sFhj1qOq3MNETzAiBTE0dnIK21Zf+w/hEs8TQXvImRpRheA4eVLYpQfeMHXwQmvsym2Fsm/Vv7x7Zqtcu/eTyQ9C0g7AT0PiCSUsc1qaGgg5iieYdZw/Z68X3K84B2VMc6fOJGQOK3tbR6z29zHMdLgdSi9xZbc1XuxbVL2k1ju3guHri6dQIIbay4AgoWp1ulMPXQ7NqB3BURcFRJLuczKhOBYOP6XuINMyGryNfg9TQlTBIh/bmkDA+WIBgXWRdYsnY2UIQHsfEDAWPy67EmNWrHW1qRBo1UgNNCIc0GeCdM0x6XR+O+oduB3/u8gcxDRuRxdI9pdC/1eFe0Gp3G6Nn4BA4nDJAkrkSaI/XLlM/mpofOYJs2up5GIwf8AUQDlegSmBazeiE2PNDDBVQBKbTrwI8FTnHRahJMw9GNT7iPH17OuSNuNjag4heMy22MQABYzmxuxT9mzJ7ZHz+79gW3Ju6k2pEUkYe6gooI1kI5/gbaFbWadpcdbmuv99R/Vr+yn/sofj05ZJQXGe2ICVEYPzGxpeSydvkKFVsdfmXW2iNWpnsrQbReNHxeZ7e23MaCKGOpZpB2eMKoVED+Vr/9dd2LIikZ7F2K6ujl0XSz9F9H8DazLo1VlzgDrlp478rpWdRqpeTtYq3JCAS7CmmNkGlkgPHkH9NLPJjpF/mB4BXPjwU94CDFz1dU37R7hAYjeB0XpgjwlYz6d63+NpLrLAjIne0c+kW5QPVfti+A7TAajJuzUvWXsQNCHAoUAEnkQv/TF8SxY2z9XGCJWoj/u0HEhG3IgnHkXOF9t+pE+v35UGcy9ROK1XJWsG/+GLMWEKsZcG2lyWO7flL8VidGGFEayPuCFRc+Kdu5Z6wPr2nhotAra+GaL01CmqRVuUzFCOeFJTosfGGphRweJVrDu4ie85QkVQ2YlNSyhkc3fJXt0vbu5BqQNpZsFgliwipm4KLHKWN3fFuhOf2QnQnsxUKi/JxCjMvD8nTuP140IQVGpYGVeg2wb+zinSw4SFpe2fZjJX8FV46MD5ZYiSYGvFXJCcz+5tDAQojFhwV98xR+dunvPMt2J/QRcJZQmhJdi9zH079D2n/wudZ5zRbxgmT/Cdx7ibeoQV6aj4axBahTkhsIAYPeMR0LCF0XSzZfOGQofI5w6ovighowap1MZOuhANcRJMCAoEAC8xpM82b8xagZ4QuHvRKVA3YKtrV1hUyQ1fM6awwhGUCGZbxZYZGeZEcCgKFMcQH+0j/PHBr1Vit1YEuDM8KpzPuPgC0lO420be5IVBYAOKVDPy+gKmtfyg81jhp3H4CmI6Vm97ZkIRyWL6+HbbfZzkHaP19UH4Mr17pKC6/uJN/eSLr5tV7WkF20hmvrK0BgNt09PBUxsKzrNZI+K+BRftbz919lTmUsOGQft1DbdtLlqEHw6anT5ydwZRzFjkIkQJdv2sC1tX/OhxauvG7xOknqJxpg9INI4bzsLoanjc141c7QVXNPnI1eHwEj5C81iHiVI+TcRXSjmw1t/7E1riRV4v6koD6o+a5sKmjHKZZEo2DMYvVgnwUhiUuAFhU+FzClYeVEZlR8KqTSmRGsE6vD+u1+v6ByRD7qbiiQAShAYbF6pgN7mwckBFYYoSH2iTkUcbJ8WbBZdlBe83O6bKnFZyaEy48/R6QzrdBl53E0JWkIJumqp/4M/OT5O9qOBqbXIFae2lBcBDptpHKKgiEoOATeO+zrg9BBKhKCfRNXMQEzJHBPOamuukH0cKMJLHW1ZbfJTD294xJ2lAY1Po2s9hVoZahZfm8mZlHVwHrEUL8NZa4rq8m1k6Xp/bs84MVbGlDiZ9grRnFdNDMWcxPllagHimmQDu14dQ1XDKkL95T3puUx+vraHRIMslkcdmud46dndiLX5EJj+LfHTZrzSnpR9vMN7nK8IxOgiunqKqwx+hB2VM0ZSJTgEJW8oqXhnelgnSuh8Jmf7vrJMrcp1F+QMy1PD7ep/J3uvPho91iolK1YFEUOGRKpAWmmifLYB29IFw/jPNfZ5XfzvejHYfnv73asxr5mj2sbyjHAHuwRx3BETWoU93yyonlLkY5amZsukv9fvOgunjv9vZfgVj3bGGEkDoo2Bf2mXxIDNMRopUvBdKKDw3pwjKlEMLKclAFsED1eFUKIKSMg/0NkMR3QWebMXUCoR4CT7i62yTiYI85NN5jCiH0dy/DMJEe9MIU3EeaTuI0VHYiXHMECqEqpDu3NYLle8tYgi+hqeznyxwoTDpusaRPKyzdn2Xr3td9UHhb8yAHOsWkpQpRhAEzFXACObaCnPrsKqJadroGzulYKRiR5SYMLYXW6WHg/yZj7NoGUmmIQtxkLVv/QuuREi7xHVseCaM6l3dRMalPh3WdpNu88qEZYx81qvXJcMeXoiNqJOykpCmuAsq3rmAzMlOmbqi/sMB0Mx0mB3qnRllUZ0JfrG+882dgY6/faqHzvgDlqeg5/xgq1ItN1pJ6EfIWkrcaVaDScAYIvoqhGn3Vgt2z2xOF0W9mBXSjCkYyaq6gqDpYHm7zGvbNlnPI8iQPvVuDCR1Oe56PVS9gGkVCi+A3alK79xISXunfKEKaoQ7GgAq4vb4TvZtwO+Z0EKLrveA1ZOAEcjI0vq5XohEDRef5rtmlV+fpcf5CRY3/b7n0Wdr3A7g18jHVwtrMWjubXZ7V/aT5pMthZw+Zdn8HPeZezyjYh2yrl+5aDr20eKacP5N2KXb9lNbHSJr2jdFPH3/rnj3k//nowNiJOnrzxX+bf52uX1eBl53r8yHS5j8i8t1LWb9xdHtUU/rpWjbISL2qouR+TvakT3T3SaC/W5l3Xwqdaa/MmUZ/guiS/C8PI0O2H+4av3wo6JHaPrlLBV+T8r9FCiUmeALIzYCaK6qMB46857cFxTbvazVSDr90ctGiyCmsjHGVfIMxC1VHxdiESBWKkzYhQi6CeBT3iJZbnltvM95IUaSKkZpTJdKhBYCmmIMMvls5QVNkOwabIaApdKsZ0npiCELQUA6tdflx0DfP3aWvdnwsId1OlZuptzZ/as9TNkHGUL22AV+P9UCnWxSs6RVpMooCLSHucKVlbVS2wU6NhjKsJGVwi9gldc+Spd8mU0dU9+wEFL5ylCIX569ITHc4qrPEk8+HvniiQyaKuosl7qcHtRP2h2HP1x+R0WaCEMVmyNO2TzNu3qO+9Ud1j4w+0nCPMTO3I62CyAI4oM3AUcTTdiL+BWrk+pLgqkyD5Cxc/Ey1n6JFg9SsLUZjeVHg+r+bkE3dVp/zovq4i2lNvgpJzloSCVUFOpbYJ6YzFL3Ko7QQxDCFxE6aff74UUfb91b7jhjnu0hu4maF65UkExXzLGcwThJ1AjNwURn+yyi4biDznDerLPbh0ccVrVNq1GTRoAeTp5dyRqZYnwSdO3L04/kn7z5XfQG4qGlijYbrrYbmorTrN/okBzOn/hv7ZKyTekqimH6jafwtMKGxu75CgJfJYwze6ykRJ1RAC6CwFGlvLaCrEN5JVsb/jQzdTw3V1+9effmSQJYHpm2GiofJfbEdIjHHv6oqULwQhOoUWfOK8oKKb4eEMg1R7821w9WHjAMe6zwqDxYBui1YQWkvetwXCrM9Y6gFAULISpFIIjgiycDjyEXSRcufxoEcOchDjEkN8RMPiOl4bdvi71o0WrtAfGV5J+nOAL/ynv98to6S3vWNs42RwdRu/4vyft8KPuX1V9MBXSBp+mVaog1DWJsGTmbn881NM0lq1rG/I6psKNfWTp1aTwatYOR+1nWrhHwYEU84XFGdx61YbSejHUgM6qfWOYXV7RB5JqJD4gLg5eEAFuDEAjdcdur86l/QxpKo45mQU1EfNHhFNhDeHB40ltWMq9ua5nTgkkHNnbIJT1Vu31zZe/32l9Mx8zqb4Gl10aFlbYiQNkFAIlqgQBch5ZSK2LBNB3RVWEf4VJD4wc9WOoFTRRrIMZEWG/3FZ0vFD8znuJrRanV7Xd+e7bt5tkpTpaycSD3gkSZA6oXeclBJ68c2LamCZGk3dHBKKre4kjLOeU+KELhfuQpWcYOVswN3G20dYnSgPNOGLXTJr/DBN7ucQ0t37ZG5JdmSlJc6xWgIt/oL3EQ+JoOuWMi7JV3r0PwKfUpjGQ20eB0RzV+4QEX9jcpLUoxqavq8SPyAPz9XIHMQe56zPB8hXKH7KbXFUljW2vaT6rC+PV287nnCKlhMKxwFGYaQKEvojB7Ws2BxsRNTiYhdj+wRrerrcuj12pirYqqQIA7+w+stgjVgJViHii8L+cl3o7vZge7qNqK3NDncDuv0+nTf5gfi9KsuSX6Xzl5hSDGTJUCm14EvqoVk6GMu7GsAwW9c2IsXonlEN4l7mqIyBZ9UoLu6iQmf7MDMfAwKNp9fnh27YkatjQt4fb7xyBtYXfN2U3R9u+0DJc8OjiVpl6Fif1AUWB4AQt3KjqBkr3lJZtVP/WN1U9pTV5yZvnsi+9VsPv8Tix8Vb6pU2u2PHk+K6CcnCV92GvVfeViJrNvUOSVbae2uSj/fZAI74PssOQaFoob/AZKP7ONjUBGEMCEGTOVMacKuRCXcyQd+OPFwec5zXU/FX03UlI80ZPheXIDqPp1OcR67R34M5h4fy6HT9qogXAf9VO9ppH9NrDKCcacY2YDUbN4yFksV2sEYuXOGJlmN2lz3UFbVMZGtN02UOOBmktwmScgq8BSsbut89ST+rP6HDLhJvphfMFGRDWU5b6nRpg0pCEFqPoxlxhkCZlJBtVZfafPb/8p+UH72nBVMzi+wixnQHJhDpI3G4qfSbHuB5ucwY/WSVQ6ME6a2nJY4Ymv6hw3WEyr+u7Rx5dtrNZ/7boZVKr52AdDlwfahjZg5U80SZ/OMzM8cPs1P0cHp1yODXhI1GRjhDdvAtrcW8iY8HsLshvkinooEbhWfv7VUarekZj/oF9DHdULdhrlojQ71haLzPpG/2hReRFuJjcFMYpdRBPf2GKd754b7X86kNhL9/+J67uKNN2PvtB7KNBLTp8l3xe/tQzYRrBWYhdEtB1ySDz+Z9pnvg7LftICpUwHut/a2Mq0M8EvvPNAcdRP5kpSElb4z2GFvAfZJ8O7BLSuw4eNVN+Zbv4PxCsrHmRcVsSw3OiDCfBVSxhoWI/sk5RKbLTXt9OD1upV4O4g5ZO4uKi5F3NuFP20YDUv7R6L/3B6lwTKp6OXz/OMiFsFhQBVrkVzm8vOEXvJ5lvz3p7KSwer1nsKvQxaHrnYGfl25wohHyTJdy7UFILjNTrnk9PS4YOYaV9Euy/4y5vzhYm1nlW9y7cRmbnV/va7kcsBGe719M1p1l9KdHRnXRQwwVihVVIhJdQFWSz3GT+yKYILZX++VUHV50K2Bmd29apnRVpPxvPNHyYO9QDZJ9+LhzahZ1vWf+NQx2GTrQp6mL9E621I3d+nznoyEYY1s/30rcSBb3OrNZEb/cKJ9uACT8ggq93f0zR9MJt7mkQMsJDgzDeywpmA1Z4SWpcmGGMjhtya1B7RZ2jSRPVi0tgmKSgc6Bp1aO2SUJrArgW2Zdmjt6Pc4++qV56dKYgCzAPVavlKGnp04kiix1YhbU908H+oHhK8arkJLQ6HbHMO3ojhzA1yFDDtfurxObCuY/cg4Jipzj354Zb1gOI209xBIIyXJndgo4Uw4Lpi9matE3DkQqU9NZ+NTT1SmoZ7/e5TvvFrz3GWhhMmXN4McmX/e1l7ZhOmzWWp8pNYaj036itxDvS2TgNMgM7V3VrSk+qairOEGGgobo3vJ04NL11l7zyp6m5PtER5GKMkEz+2Elh9NSG83tdnb6qNzu+VMeAcqTPslp2Zxt5wFPwRrI5dqdn5TVYA9r+AwFuUd4Jh0pbpb/eVcmxnmafCfBu2SxKD5zQl+lv2v6W7UH6i5DIgC9PT60e+zYfSiEJeXCWEHdpaMPtfaFvr5jp3FcNGXZAR136v0oiqg0ZZScdNN3pTiB5r5MrT+XCuJdyiVxWex4FUqz1gpuNqVw6kUhqq+ss3J9cmBBgPxm5CLeK0Ev4klPCWWg5zaMwH/X4ZmQW4rshoeOg4KWQxnKQoJ/7xpAYhK7aW5ZjqzO2f2mOeK0HO87X6iFu7L3oiYzxRXNmnS5JOfV5lYrZiphohJTcyYn7thMQ+/zQubfY1Mmual8UUHWPQX+U2MgFnKcJh8eV7p2sd2Sx866W6uhc1WX4/yP62SMpJI9oFOSeN8geqW4J60jSf8l2dpagI/atwwm2cImU+yWu9kCLxFk9e0Kq0xeov1MO5XkjWTOOTk6imOgVX/CX00Pt5npPXt8L5YBpv+Gs/3Tvew6U7InS/dvXXQnfMiuffcWPCPkymiWR58s3/DYlegUkKcRYTVkXoYOhabADTr/j5oEOMWOv1hvQeBsMWN+e8Eru8r5Cm02UXTutbppOVN6ILdjwezJ7TsYccpAd4qTb72wf73u9QUIeWKUNWFEsWn99S2DD1lH58HqzclTOVVJwlPiuhqkCcX5gSo0pBOvIF0K7XGprsO/9jTzjdo96xwp81Mk4z52kC9zH/8iq6z1VB4SBombVM3dXJ960BeUeKOKjDXZVJ6E/h1jnydIWFwXZjygs3ug/y8cppikfdLTn1znd6LXtuuIWcF89YknvGvgfuwc4d54YeRMreF4W5CLp9FfcLRaP/W0wmW3X7OBMu5qTwUUgzyjIPSux8b5aI1Sw7g6wOZZmSrtJbdJ646v4q9bVhWB0ViOw4UscfYyjhzRVMB9ip418qy57BP9RJt/Yl5ugBQ4o+YBwuaoR8Lyfuk/QTcZCG+Duws1oqyfz9C3hNZeOJdXmMPqOeDkaxHi5SeuuuL8TcADBhbpHl165TMVcCCqxUfQ4lmzZET64EdwcWYVstQnfEeaw8gSK1gercjkA23Q802LdA2ePX9aWlqqDQPUytpqiXSYe4Av8hxXzSmtZ/i9FHN3/xvUL14ru35Mlr08eoDhvVnM8nxCyqIV1PumkxfR698O/vRzG/K1NZ60Nt3OhF3B0GSR7LsrYq4Os5dF04aiDC/Zuaq2LdNN/Bf/OkrnJIsKqf7PK3GSXBTXE9k8917boDnr4l82Itd62U8arZKVy0EWOaPY9yTwlv8UZvSZeV78lJQWlOm53nyYlAkK6FLwXNbgzwvJsX/IwB6FsWqovP1hguJ5QcVfaZCU95684gsY2ePSDEvQ+MR2Bn7nqs7NfW5SzfNszQs/ugxR9eKvWSwLo9C6DLE/x6MKvJzT2cl+rpBK8LwwhXUNSjwkSEBjsy9CXjGp2SCbKBGHJzOjya3O77Fiakff4BTfbjI+LAAC9prHTdHakZC8fBLzhe/nDKLXc4nUpcD9bTwt4anA+F6pmTOPYkF5Aua0iUOc0VoTA5j2J/BuyIS80hmH99fkgLSukovQaGPu1o705JI2CwnAk3J9tCahnHDh9DQxg7Qr5xrJXi7ECv7BwnvVSpbx9rz7NyAHTsCZIit4JJt3NuvvnyI3ymhDPHgm8Gr1iV2lLn1S7Fo+xNErzh7C8kmhb0qfrUcVXOOUbHxBln+aTpacT7n0pxgCVrVLMwWZQnYa0/QQes8o02EbZOGiBUnx/3a0yJmK7HYkcGbk5ZH4+6VRcMDEYFYutwMhgNORcYxPsmg9aGWTSNDCiuCxaf7WYqZ0jfFtJoFcF0TOPv62I9h5um/jY0ghai2/j3GWsXTy1jQPjJu8G9zOOVsf26uw78AVtFhtyew2jGsfZ+lqYzHNNg5v2KpRaKry2wWzrhTMJv3O6pvI/WK0MeIuKcKx6lZ+jFQYPzYbdH5yFvRILmvqfWOdjR3cFrhXbHQ5WiwuwH9ALjIJTINdyiUSwwKUWSzjOJWnQs33buNWClggKibpIs10SGCHOas3fh2lKhqxII1j2WLwJ23uqyzNeRiITJk6TvKiZOX9ZM8zkorwbtfqy39T8p7lUlN+vTe/t0lA3tJ5gUXw78bNBfcb8f6LwmPL5ElO0lawkKApsLSzaoGzluYZ7iVfg0lQf+lx9y2w9EtlXHBHP1THuq5Hwh1l1VBDslPNfHaUOMNKwtit3vi1MbA4Y4bYbBdYYoO2zOgCujyUHTlwWPM5znh1MS6+5zXTM5U13JkIi4boaf0XOa/N+Gbde8v6RGtLuC46Rh8D5Y2YyFhYhsKZLOcNZvB+69ub6Zs4X8fH4ZaZg3d8V2FIvvvLKWlFMdifd8LPbTieZ4LFteB5JBDUoFzSlo0uvl0BTgD+7JYCmUTShlNNYUKxgKouvVscPYp7eiLk942TrNmz8l0LTwT8UfF8zeb2sUvyzoUihahd+S63NEEtjfBtEgDx4ygbAcXyyMFzkkBGX1GWQijY8gq+7uwe/dozbtzfGmrFl6qoHyeqMzxNMT9lfiO9WKRObnNTCaIEd9JHHmYCqklqam7ZuP9tDXWNG4TUm85Yxlv5rouctHLBJ+21XeECTasioNOHLIQ7oMloXNVApQPaAg9BcEtzBeSzockJ03puETgXSgqI2XCaLAT8XkrWOM6P0urj+zjUxAs+D6EisiciqNei5+GLLWJEwd5pp1/tiY9STsOkgIcOaGUkcfTBBfB0HBTufP/j3tPRZPzuW8bNglrcv48Jf7C7wW2VeO6FJvTEJoMT5HMbxd94UFt7T2/ItSNvg43vAr6IHbgQ7q2h3DHOqB9Udi/EyRzu0Gj03WKukrRVdEFpeB+VC6OfWvavqPxJ1ceaZFkFPHSooqQupxHK/omingD7nPWhFcYFYqT4IU94NpI3vV/WBbI5vcKEXivVXTFdvW3muJZ6L6Kh33OkXA8vJcDw3bR7ecx3YKS/8oXkEMmMrTmMV9qxQ3PhS3OWeCP2p6LXVw5oIla0vYtHOzdc/OzDsS5MeL+c2B+w7s2VMNzpHRpgF0bhjslnlbd8GzQYbI1bb79NX61P8f2ehfWwmFFf0fRN/7/AS7zb4qo3W1hbryx+Lyb2XUFlCN9dDX8MvFbbkyn8d6lQRnXE7+aDchlDh7X3hfoEnDDevwTy65U9tml1BEjTtOlh76MvS1ZkA/DTfsHoBnT57X8/ACtR2AA6+Vj0J7YiDqLLTNaldIIN0TndcasJEUNzIaiU55KdPDAz1KjNHtYecAQuDk2s2qzILcSvCHFELwV8q7zTCepOOvFZ9acPw43W6BXZm5EHQV9HqQ3BDwre69i1LpEjxhvLB/H5Q3r1kIDSRSIG1eJ2Bia8fFw6PPZxe3ujw+5zpkR91JxTuPRS+SyptPT7Vf/Xv06PT5gCxJHNPTsUxwQxrDPjW6/Z5tDiS5fFKPRQUem9yMZLNzvbel968wgy7nOVSa0s19QkfVMu6A+Ryp/Wv3Qqjn4pVaVR6qx3SWamSlk528vW5bfurLJOt6LIq0nnBL2BZNgtz35E9LEPAk61b/t2bh5nPLtrFJNahkgRE0FaGpGbtIAOexETaMrKHe7BA1VR9eE8NI5w+eM86Mtv1hXonxk5SwtOQhbsRkSLEuyKZIpoKheWI7E5SCZaMpqmPadyUXtV4fqZw9tmT94TpfptM3klaBeqo8Sz8pnKEyry68X8Hz0cyremg+b8yzYJ3GRoTw3z1gq0Gi33CCvuIf54A1bBU3yuL1xFH4I4KLUZ4HZWm3Nf+IQeMPG9VgW5FoLSUpbmFiVMB/5C2OJaH8ZlP3l0mZvMVsg3wiNPuZrQi5cV394D43/kxd6DhmBfzCiazlyRw0ycP1xI4CTOiCjW501aCPsNA7wOWb1Kk/+YZtwNTdgtpxjq0l8iDmyzlzT3Qzr/Ws+emprJpb0sMIT0Gz6wtbjn5jFrqNaR1p76al2m82MZju8KP5qiJqlpU1209IU2UCiBKhLLaU/nzvI3bWAQ3qupX5K7NaS3jXpqN6TTi7QyR6raUKqwagJ3wWHNfPy+HWpj0YGIcQnwEz/+mxSsS7kE0D/9lJce8Fpj5GfpLnNcnv/hGqhqFJiDhQiYge8aL8uC7P+LMqCSWCmR/BFLZVB8yHlwbs+EGWzB8PufkNEB8WVqDrRfjkJVBtNlofkAkG/Tb0UurjfbDjWHhmzkDr0i891jNCI0phOYGIGE92/4Ec4xr9Ul7qzkkuaqfBslJ1ZOeCX1B4NrZtkqgFx0mHJkAs7t/5I1oLn2WzhgTwUnEfp4fsO0k8IIWQaJqKW6Hb5r2v4U8LNK9IVGFnLANkZqDvEi3FxXzhc4H0SAT4qyGY4jEyuN8BFHJ1wQv7E701J7r1bl6Wd2vBnucoXJ8zx5yPLRpBrsiP7vYQQqJEKkrXih7v1o28aasCpNsKfaOh4dO0iIHixs4X8we2ykGUYsHzFXw+EFGDPmLclGAvLPaCccYFrBe6RQiEjAP8SYFOaMeeHCuYzBVbeMNv0lHHvjAWg82Jezu095RGr78Z5Zuk4fj2WX6of+stQ0IjoJSxoNOQMOUAxGb9NHjH0E1VgPzXt3IUxjeAVaORIVIWAV3tCeo1SyPa60YoXV6Ynt4Sgd/a3s7W7mwJX0KbUcuPeOIyDjBnTwnHnvE0R8JISU23u69b1pv7e/7sZbt6mYHfyQvfYasrE6sW6kCBhsDbsTzNKHSBWPgjGa727xc+T3JLXBSPg3aGr8EK31Wh3uDz84oOyT/JhlREdD3QbpadlkmaP3yDJ+gfqz0eVgf2IKILtGDmbq/I1i7WxesLiq25O6E9l093q2o03btmXM3by7cZoSuDYXAUFCoVh1tMK0R5qUX4sc5IEmTwGQssaAUmakbv0+pWCmG5fnD3FXrLmnUM4LJ7/iT3xctlw4uTR6+ZDq7SlIT7tmr7+EwZ+wK+ucyWGPtNPi+DH8qXm/P/N85neug8+7HjTA5lJG7e8rJHs+mAH5s5Zxt/IBhG1pzR/lfAD1ZTiLehk/zR5fJtgdqU1iNVBg1vw2Lhd2TM1pCB5qEdS2poccr7HPOCWh8hRBI9MOyXI21pZp78+x/8cJe8fEtHG9tQiUu6QXexp9oxpsNS4uaEjNJ5swIuGUoqXN8uiu1HFSQ7/qlCLZ1tBRhEmVRJUR6rD0QE2AjFceC9kzfeIQTEpVOmPMTy822PyUI/Rs3KIp+HXSjSmvWKN8aFfoRtv1riK+ha8VD8MaoE0qhQ+FjzvUIr5tOG4Ct7Oi0txE54+7aFoe1/pD059diwv5LJdXavAIRoAGxiHktDyJ20c8dQ079fBBjWoqk11o1D92rd89ZOf/3ie3jex9/q48zvyZe75q55P4JAPw6wBpK0W1Ddf2cK/7qob5+t9mxL1JY1iAfy+V8XuYs1aaMAWdN/WA+WM0+d7nWkE6dJgJKJDuIlwZ+/4u3oli4Qyo0DMwrr3uhxqkxLeLVegMnn6ulyixCxCm4u61Gv15yZWVsbolKQDkHrVDPL1j/L/PJ4d7hsSW3mdcSUPy8+Zab5FHyVWVwu+2lfwqke/ZtBVov1Eu/shg1wPfYs6uVsAt5kR+zjlvzZs2VZzw1rZaJcGesUMZgQvywXSNi+0IfK0TORV0kGygsRnTGE7YjlkkD0S9Ch96BCMUUYQx2MFqwOgRXy0yStGX9DzHeCQHTnZI0c8kockRzkiZG5CLlkCyQpX2MBGsR8lfCjah+KKZnDMbaXCQZkrGDEfcIpeBlrVm6zNOHeDd0EIssUc+vzlkfJ4vsytLGg1yon4frfRGxL7+z8P2ePlIo9tQaOxhc5PJ6SvyOYstCy/9rG94+ehdaHHKDff7vxwJT49XnBlvUBuWZxTLnYqJN/mE9rcA3uZivlmePKAWGk7NFrJaUOULV26MlnxcsrGjHIrLNjE6U3iLpAWtaZzRBpvRs3izrPDBE/XsdnwD1O/3w7yl1KjDPuE8lBA4OB8eTae1elMIZI2TfJgcsnKrDzym1ToNuSxid0WJCqV0+xSS83L/VidsuqnNfHulOHodWCXGKgf0STCacqRb/TMciDSC08ZFcgzlEAy2mEECY2iqy3lZySinSTPWIZ2lYzwCeLDp4sTLM2GMSSU3PspGJUnpcTGDbnpNFPRf1lXJGPvaZ7rD+KnqSJWSUuzg93ugQeg0W6PJO3J5cWtCMxAtMPaLe5OSQwQAT1jpl96O7uv0B8m7EEIAmcKDkB02bLmfF67XZKwxxSPK2OCZAmlFzrY+bgQxti5wVOEOpumJoYn2cnkpHgSpGatCEZboBfZNEqpmuZzNCeBZBkiul90heCdg/6+Y4ooKa9rw09RhhNmYwfNQmlIj5zYghRArlOSIpLAekXFredEL3f3vVQeDr3QkeL11OB44ZoGackiSACZgRwI232rz0nRKjRSDSRAwuKSnMsfmsx1CLzRS0F6ylFFqAVotEePDZlOU7RJPMQTy/8KJ+5hPeEgWb8RWwc6cI93rC8h7lIT0XL1pI9PGk6TB5ZJuTr9o0bMhiGxLnwLcvptJGXYONNsVMslRCTZ0U3wv59/v+O/0vrLfsYHBFxJGCSBm09lKtsssmvNctNWjvjr32WyLtwYTz3rBcNPu89e5EHJXRtNUo9aRF0C9mYUsLxFRUSaqwu0u3N2hqCOz/dBziq2X83aJ5xmKGwv3LPGMfJ/lSF8k/f/sAzQe9As7Jef2SRaut0qUCpiUYyNEXo2SzU5jDvHhaNjkJ+UjPsr5WFAyFtyKNYGvYyT5rlueIJ1MiYa54onUoozAzyFWm8ndhZk/cwMDCA1cYZQiz7bSk0lW/Rj4w5TONdKcHfyttwfpPz36SIddcmlu3VG7srxrwXOVI4cw8d7CmJfLxLbQ5NQdCZ3THiVAsF8LuqQhaqjEGXnF9lRg9Au+OxGAbOkEhD3Uw5pmQmjrl3EwfB34+ci7DPeBzNxR7yD7QArNO+NoaAbNv8zrlfPx4rWG1ZQBh/pEl3s0QdezvS2wP2h1uAAV3zB2/NlHaEpb843fcu9/vXAHVyR9tuBgePzawGZlAVYYDuy2Tf9KJdbjWKHO0jXx4fCHuTwuUyurEk1TRcoBVdWUAXyRjmbkfnaKFL2dJTo/tvU0v7lPpzl88iyUpRhwYDllqjG8SB8SMGEMQtYjH/fNxrZ3owmxh8vNCZKMULCjI/GPOSN3ehWmCBu2MdlLlaXuhHnx9yN2Rsd2zTXhnhY/1f09LOg6l+z66m/ZvoWF8dz9jQll/spCFGu9J6pUUZ6Ej3innlhZ0Z8wJNk4CvoTntyASNFp+lKXnT+eD6SAjQQXRVOvnM6C0hJcTDBGrGRy8649uZuiV7OxZ6TdsORh3RLo3jTLXSeM8u7+JkYkUlSeA4L0HbkEyZFsroUi55ktHxNOMP9iKZ3eeu5IYVhzajE9aAonYaKusRIpsG8S42tydBrmBo2nG3h1BzBhQym1POcU62wtvu9lnO1HlvmJl1y1j6u9UDZSWWOlRSFKRkFFQ20HOayI+GjdWaeWLwlXEaodToUKVyTTqZbgfUnj/HV+oLcwtFz7e40whbfTna1Io8FOcxgDpuUH06spNaPRl0YyyCVt2+BpVV+RXqPTPaIeybvwHaMOUabuoqcDl8pvpR9DKREDJtqNUurYa0p+caICrTtHJ9uiKsyD8X+vAuG5fWjLL0tepyksDZnkidLvBfbKITmP383B2tIbD/n2lA8LHtf9a+78jvF1v6zcpcHWoYeyY/FBGvH9utjDlpe7IdzSyfd6z9vwZoY25k+XZaSBm5ZUXnHnhCzUmNq8Ke5T9Eqpa7kJ3Zkjkn1Fl9KdlOV1kCwN5xsA4rrzwpPM2Mr8lEJKK3PRbcsY8vmTeMhoqMPl2Q3kLc0cP39XOTdqOMgQgohyKv/EqocDELhH3xRqhhYInacV9ondAr7cnRJqbhoAmxp1oE3GT681xy047Ju7FW9BG+C9JiVgJkaodEUvxARd7HSC/WCkq8fJ8IJEiGcCCkGrYzu1N1XE13z1rmJMyUJck0FWjBFl2K6mwUtAcH78qKOOnUakK+XfHckkZl38ThoVYF8dKVCzZE5slmp8sMmpKuVvIOibhzLpiTM5bfLW/4srgEDLCS8mZrGZxjAjayXtl0GCr7M4jzzlW7WHSmvfbImIFZVRog70b92V8WX7jfu23ajfsX+REXaoF8IdY47QWKMJkQhRbQKqhGNKWerl2pCgTV23pEpX/H1xWqJ/41JIp8ygWnKsITusKfUqnAP2UDCoLOrt2QRe1Uz43fr3aN1qYP3Bn30mcP7kIzkaoTAUncF0lXRFYVQ3etBYYasP7HiHxqYtuO5n+EMIxLsD9d1ny6u7s/K7azHwTvms8vLmPM0Y0DZROIUlqVRZ/FbiR0Sh0l63ndJFHM73WwPDcFaC+pF2LEMzaq/Da28GVYZW0k1U2anrHpCXcPsDJsgh7vfjrL3S5yl+dYaCcbidg9jR+nPk0W6AKd0QjHNMREkP64OUW5JhDINabCuGWeD2WIg+TmnXk6Ky7C7XnIgaMJA6ZYRzH1fsAzJBd85E1GETm1N0s3IReeg22ESnYEaLRexIx/dutcrom7ODXNiZUADxQdeIEkpM1GNXi4qQIEvdXUl4WEoZ2t3n2p0xZQsimqZv3xI7rIC+jcSBQ24hZRtaUNdgaXoCrGhuLOgXfQwa82KkB0j+KGz0u/4a7ibExq80d7qiIHnzIct77xzH3T6+2Xp12rSG2czlqsU5WTF543Mf4kmd/nuC4nleZF6Yypb/9EL1LyLCz6tmjtfLG7+4VKOMzmffFLaiwXjaAxkZDUCWvMFCT2CO6D3Cv3/tfCEe+1GpsmQgNKsERoFXmhb9q2EVEVb88qInhzrARYmb2lyN70uvZiB1ibmE0SKvvsiAmoIS2+NePNaxR3W/N7HsOSB3XsCjxfAdDFtGL/rFasNGTlaxuw0E16blvMi+VBIxSIL/XrxeJnw1eXIqf2OkkYxFGwiiCUs2ZOmR/bjpkmbiWxTG6xiNRIbwc3Q0tsjSTkxzo7aASuzqv7s+p4gR2cT6jw6FVOEqQU0Vfzs+13LMp/6yXpDEhRo2cVjtQmciLJ+VD6PzzwSFxsD98MwMQxhEczmEVz3xoN7+6tnmDx5a1W7Xmp2JBVvHi9Ush1Jhwi7w9fBmME9mrvlL/z+K25t54pS+ObHR/3bl+WAsZaIZYN5sS6y+bDGOi9MjM0lpuRTq6yrBRMA50OnuAjYoMqpgOYVYJ8KSuDg41ziJCqRAShMsUPO4HIVPOLt67BAoMnoXiaC5ap6d6d9Q3DEwc8vPW+ICD90hRKNNtby3HlnzDleH2LLKl1uujy+hAm/aMAl30rzt861RbxIHkmvV2bU3O8xw+2xZY8wma1LI54d1Fs/2XqdnP5XuaIgpsp/4fkywWAMAyS1IH2SZxtdHMCmXVuJdZHcqOOZDP2WP4bK8ma5Gw5n3KptvMFzfzQYxmeffTZD/YEHvA4dx82UF1WiZZtMNCvJYKd8BjXfsSvlGdvx+fO6P+LmF+oxfhAWMnAChgmNl0xR5ZDrtAJkEgt7EhcU4XCQPY1bFMtEejOc7rIF1g2U+X9tyaElIrhumXrwUQZIN5DYi151XOx6tr3UtAjzT8QN9/1Dkaw4NSvHSPzI816mHjcLDpSPwdQ6mppqL16IEPQWojbIi+iI0RIdb//Ac8QNtnPKZyK8j0Gr3jzQuv9NBWbFYJOc+qFdIo/UCuNFUhM0A7TjF+zO2e+yz8yXQvxvON+8E1NLcWryhUm+PfK/ED7v28J5Ih8Q7f94E54nZmSOMYWdYUXbTESTMWAqSmlblFNs26XU09Ciki6WEOLGqq9G16n5MmmTmoh4li36noay7jaeRXtzctjJdGcEW6zPXBUI8rqWkrzWR9qCQiaTAhP6KKCEpKWErFCwOYWOQsu5NqmXvLvkfM9agoKrtI12zm61Q+I4os/Cwbw9lDvyWIWYKh7/0Ujolx1riowFcRmOzuJca/ehw8dvKc3Ul6GeVToBaDtqjcJXjCN0fn0f0n5mRLQK86aQYoAFGPZs8DpSxIlDEQVNS233Tjks7e7hSGUSUeYZLHmP3NGfPgr4f4hBdUwotDnRcU0BKoaKsAjyJci32MBms5EWavG3OLi5LaiJb4G26+M3e/aYwdwtpXMlqw2JZtbUSwBbbufaLKSZsby05p4Zob7hH0JxZ0yZrzoQdgeMt/hOdDtMZh00y7eANNIJmnhvyyY7HSM0ShiM38qKeI+N2dDG245FWNf7O5uh4IZ/9ZOfqI3tJp2RcztMno9Jx2zLf8P1cSeQFiGL0Jw3M7MI4qQSHoysQVfFskjTpOy0P8wngSkPGms++776317ue9M7VuYOIJD9i3jmV3VZ5rn7SwZbpTf+8Qzw6ll55Z6EAE1Mf/Zw0aRq2H+P4K0t21Rkd7zQ7OdQ/Cxc9C0ZICSsbEtLJ4W50TXcx7+Lbxxjnt2iDm+D+kMHt0SNQpQiCkyytIpb03qmBqjMsVT0/pS40fP1YIaFbkTsOQzY5YazEN188CIr4YXGdVMxr3YtbkeNx+/rxisy8nJYbdo4PhJPAUNaEAH6HBSo3YdBLggJmjCD2Ud9oHIq2jgb9YMfbFEQYAdk00OO8OA4hwftNseNG/5/Q8DVDP7jD7QrQ57uvt/tJ/k9ASBDbeUMPdeYj9YJfs4PDqu5iSTv5tPmSw3dcN9LnsGlk+mVAkHdRckNoyE34kZ7dQVY8BSoMlBlPbsgDTxmOX1r3qmxHiauEulSQ6jO9FVnfyPss6ac/gaMA6Iydk4VLXtkRmvCtDheoDWQkjgA92UywwMtc+riadkr36gu6gIjBtSY//P+yiqqu4XkHFFURP8g5r9ClReg4PFgxDeD2bNL1/Ckwb/CXSRApnZk21a42W8nD/k3GF3URgcwEdhrrR3oLfXUlVkrFn+KhV3QL/ReaTHqDHfizgio//dg8QunbLi3r6iu7gNSyU5weV1S6HpdUVKca5sh1Fk0NTlWKwQahYCwPl1rCnyitk+EuBzyLu954bOdv2/A/gNVRDhTExaTodWJTqsfN2Kd1VmdX8wnjIBQ0K9H/Jz7AAVQbfHCRd767HIg9p9+kLVWtwaF7nXN1em4sku+zMW+YFaXcGh2zL6fb+TPKQefai7+v+3968R/Lmit+4xvCPUjL/ExlR/yXBOOynbYNfAESw7z/MZXQku8rMAWrzCRf3Hiz/gMXuoEY7bydkNOEwuOGxaEi28Tt4lT83mr2F0SmalbwgePEIaSGjatC0lDl3aD/PHzeg80yN76mMFgjnBfDAyFQzgUn/sZEQ96MTjUjQ5BezTwWKlhgGtZAefrvATSmTXZyOSsvWfZcZbk87tKFG8eGrUpVIJpdQdIylIIpFawUqHDZAGLCU0iiNQkW1sGJOGOoxi1PtErhvVcwii9+HdntRPJ9s6KE5HkhLgc+Qr+WsE+JmPx0WAXC9gAQsGYnI1mjcGLICubJu9z4WdqoZCA6N8rosLaco4YW1l+byUvHAsTiFwakER+RCcWZRRoaatqnaxmdkHbwxW4mvP3YUhlA0UNQEVuVYsn92lqWDrnfvlu/gScinwsuwPS80jrTbKk18XSl1TUIpLs9p5muh+H4+HeXCbZou5GEUkURaU5POK3+1pBvOTZ7wnn7EJfP14t/6+L7K/oA4+2Scw+APSOI6NX1CarWBn2wY0+VXgAXeT8VujI5+90b9fv8FkvPwFS1DqvMNTZwvybZjxTTPUc1BRT6MHPrmQwGl3tJ6hVetM0nipDjW4v8xaY4VfGNLy3wBtKGoEOHTOP9DD9AYdST4z7ypxTaTtq5fjRDqoXikv8II3p8IQ5jCsUHA/t5RCosUbxQlslOtJ4v80JlkGskyG1Grq8LDILX1NFyrImYkUM5uwewVPSw4bzXb/Le/53/u0Vvjl9DGMMwHwIr8Z4axBOekAHUOZgpA7owckOFGxozOs6Uk3/a4fre1/uvjT+s+TkDx5J3/N15JLb4ar4UYhcQIJJNpHFFrHYLP3Fnhzbv8RF1taXYUoNRXV7u5lunzpFUIhQn/HBEsZroy38EXHT24bjRVM8Dg2rybm1Eta+8nmsTKFNZ0Xy05h7SHP2LUi22wagaAsyNddfsq81oujA6hndWM9CinH5X/RfGewfZ8IW3ZKsCYei7vLgXiQ9/83PgaqcsJOVKcRm9kPTxUPPnbdruQUYDiAiJwqYBa4gx6ziMJt5vod/6IeliqjvA15UINiGNwg7UAs0RRnXy2DljBnZl7hKViqNPIBo4/JJPk6y3cuahguU/CA1WGDY6OgW1mSll5FatgeJixtT5rcoY+cVbW1iavexerHec4yn0TPVzJ5doBkhztGcgEKe5ouITnACQlpkcz0OEdOT9bhpugAN9eGSwiZKf0NXpOK1LgoGtAIMrLsxxXTsRaoVXTssMNvSdSJd2PsgIakPdm9oBnsPqBx+u6EkDA3Ti+ih78St07zm9g6sjOkltsTWqpO5OgF2q5lzX7fznscrcljpT9rVD1pq9QsjSo5a0CQt3a1m+5pFg77zE5uJXSf1T0/3v8SSZWzp1YhW36aO1qpYlSKr0ICT4yVe2UuSa9OgbeWC5dQN8z/IXbnVlL7cTiXRGmxeMo/2zIN+kke/gS1a3+/oZMls2wwMLTZj/GJSBEdwEfcufKOoj9APVW5GKk6qnfIpDcnkfFJOcz6JE96a4uRSYvef8VJeV/2Uu9xKpjFduomnvY7ra2x0v2ZYY72TBSg5ow0j0oFcQgUtONtZ+5mn1m5c91fjp+ByR6j5T4onGI1B+zmavsSxCSfA8VviRJaboV36qRMcoFS0ZK8unnnW74nlPB3ib95LQ+VAclzJWs4GrF5sXHbHxQzVvf8tKm9YmVRBkgYFctWe2ryf+Pa+oc3erUhv0Bce5307Ih2lIiiJpkgKJKb0GIiVe0sOdGdwQB+tHsQgSGDe4iS99TIxXD0hhpHl4SAxbEcCRwugyFNdcWZrGXAo1a0MV79TvnkEfCLQqf2MPxI2BpXVIX93flCvwyGyNQqgDqCjkeXaNRkn15/0S/yV5jduHfScGqDRxYAXGiw+KcSlXNrRBhhAIS3UaP4Gy1s9S3FchZS9vynsGcPaGseJF8uKkgVCcAQky2dg3ly4p5AXRU3b+xfGbdRjuGcNPWE7XwMOil0lnozIFGHI3OlihRCMY0nUOaFdAmt3bKKtsxueNKzVL44yLVhRCBaBrOJPanvKPhiaOlEGwr9eYzS9tt8iVrvdg9vUqXMLgrXZnFYyiBbujwDrHgBZSlrQorYNta3IT5XftL325+sswXEvu3bOTwvB+QOwN5DqBXtxL0jPC+EQC4RiP/E7/dTj1GgfpaqlhKiF+Q7kViTQ0ouMeZCJa9QitDpVOr1UcgqLjIQROcYxIzJyNECXhORgTFhhAG0RaDCbgAQIpeU5fYRlP67cJHhfs3b1Km0pEWNflxVAYzRymqE8Mffhk/waY+cOxP685O7Lu1q5fxXoYMlJTngzdERy5JXpul0FpqJanbSSwc+khRctaKtLdMA+UsyK1TQhwXm5mzcdvvBh2ttLBwORIEjLahAs7kZeSjHDwOsgsS9IK61y0eYiIZwLawLtwlC/QXYuePgU7XFlHT3jLTrZBcZYSFIYqOK4zmBYiDHRRkTuEGGjlS5TP0211g+i69ILi0JyD2MC0inwkwugBB5gJLR7IFYaAIkZXZai1mEKoxN+1WOQne/XIRWpq3wBUBGl15SjpYWZfhm1DmKIBqQMY+B53JNHKYbsXWvCHjqNyau+2qsDaQUQWGD9JZ/f28JjOfSxxWJVSNpWAAclSBhB7uOt9QXr2qj5otAr8dgCFhY6O3vS0VTZhR8J/2E908/i9xIelkEWvBcVMPAmOrZ3LbdhHDbd6L3x8r1rWceqN1HxtCfCuWGPY2lJVLoPtVP203TtHx/Jyy44Da+Zhw1ioYms4Xgy036quWniT23VQn6PdrLTNoWBDcbSTUbCEt4w/bC5WtNDK3paQUyrZ7NsnH5EwxC8tS7O7rlTSeZ4IELWndpjhazJif4wDyGLADF9w891dhmHoAFpCFtd218clhSBRiMQYTXQIAih/afmIQEAK7KUFdhOExIppQJFezPiSGrbdVgwrl2/0OMFs1zqpqjrqguwXwSX7e0a4UYmK5sozPh55bq5mhoEmf+myIcPqOwY6o6d+q5PmR8sSw9M2eBVvzPTOzaVPWZa6BCZKIy/PA8gbvlkHbSqWwkzjrA8DJISuvpAWVtyJGylH3cYma9nP/U+9WVkLTXtabEu+31vga9arOcoYtckewYUkbSliBzzu1tNWrAiOInfr2UWIsSEhFRi1w8MPgp7OKIF05jTABXEfi4EKnuABnwhdv6a+/++hEpglDfWGJHjXGAnfGnFs/PCYupLu5ai6HFS+GLTep+ALlz7dBI3vVwPeXX3iNSoXbuiB/0odSbLz1vHmP/9PtcbAuwnhBC7kyCrK5oP7/Bf+tb12RDWlnFh7mbitZFDZ8aRvwKT1uguvuwtThW73Vbt2qwmC9YgBeXq5Kl9jNv5BQL/b5acJnXajMORjojes1GbmTLupVfcW1GL1IeC3hqTdmLS7gJkhhNDKCrDcvTM7HZlgSl4Q3BtXD1zF06v+l0YBGVcXdmrFezLzIOhDUbQSxCP9Ezq0dIxdedfGkvve8GX/l2/Q88BHfSn8vZnBXQt0sF+QWwaBZUNM6jPtqYXGrV2uBBG6hV/HHgcpXggUooEICzbMiwwswBTwqGJ6TG1dPUtTbWMt2eS4747/EyOL4L7uS3Nn1l1iyeNMMZx7gbnYiJJ/fp7Y3iHjSHzIH1GCHpDdDETkQVPxwivr7g+/0AvMHyDLnhgJJdfngSig0Ipi8w7gxbYwqlOSkaSpoDCEX4HJV6QT1OUucefzDVS/wD9QhpZfSGOoqdeKkzgoop8iBPLsNBekhcxYxg6Oq02c8aRtO2AzlLH5ewOlwcbZ7MtC02fO335jI9o6iX5FIE3AhZl/mAmjzKqPTLwWPhLo6rmmqsSUy0YPqqaEDT3oJBU1Q3DNuUyVJP70XKjUVbhdw+8fhWAEX3YBCIBIVcex5pd9zbTi8tiyGd+G0ZwJgGZjm9EIRK23o+2ck7spI9Vu/hhCQl+HuVVULlgK6fWWqMszi5dHSJ/pCefHCikFLVdvaCxa9zzMekapOG8R+S7BoGeWy2KIMtDPMxXNFcD7/xZymN9EXXi6pkQQtydI/ZFcWb5IQ6sEeCArgCh7jKgbO8U+gc31w6t2Kc6KHrvYMqfH8vTNoyIghEt4V5XKubcSoaxw4KTbVE80K61o3lTn18D8mE5jAi9yKSpmQVBCahrfGOBY7KqFgc61OBfVMieA70Y7ud1IWWfGiV6k+2z/7+eCq1EYisO10PpVEiy2KtMDP9tt/+g3wK6rqKncADI1WYjTQMPN4gN/2yhR+HhWAFWHhETUdl96vU7qmpI7Sseg/A0pivmxPR5WTXQr3jZs0ZAzK0BdrpTYlA3kKMaZJ7t1AVhbOTzKVQBDp2OQXje3pqM7QIi30WKp9vTrIxipuRdqluvphJ2b4adMGy8yPjr1lR7koSrZsjeC3Of8Eted47Ucj/TSZ0QKbxc2DR81/vFUNSYRd6w4w8jzOUY6uLDN0Tifi2/OQqB+F1Nw1JTiMXPePG3LHd8rev/e8W/mln5134x6J5Q1Ja7PAe6N4OOpJAyq5hn4d3yb+8wn97zyaGm5ZX/2x9mTpWTJNjnWOY4t47kgOvjz7YLM/fzVXfqfOIhHKrgMF5LbNG89Woc7cvVRth7zSc8nAEJAiyO+6k/rtDo5QLtTm9h9FtvgT6s0AzJsBnI0A68lVLGHvpTZ4QtlNImm2bNwh5oeDbJ1gJtrXGz3ckYk62ZHv4thAviSS4HKacVPKpKNwZJUZqwFUzds0T96c7KYP9bTInesi1KOxlyQPwkKw/VKClsyi6AmT6JQ5gcAkTwnBwHIhfMcZZyqu1brVW02CzRssKtOjYRcLgghFK0MsR0EoERBPeOR9ui5JkiHHTnRMFIjgpy5UwvJN8wcW6Gsl2+fKygJmLnwg3Slmc4Tdi56JLalJ6C4l/63q7vdilYia+Okfq/y6ZaU/2Cyb9+KYxbDcuUVSMa3vP4us9Jj5h+nYx8VUbVdBWk8bAsFKbhkIcmzn2fxtlN0iXfUzTiJGf9D3V3bbMkUkFzCX+9x737fcAvdtdIqB9J6sSVwy4bm6e17fpnuInnf9Pb1d4WtGPzlIN31S+WjJR0gBrXpDE62mv2NHpggNMCK34DXxoVxJ/dYRfUrsiCsGIWXfc9SDnMhRqngMJ6qZelrI/6WBlkzgMRm7W88lYs9Ti/AIXdqpg5NaLjCJ7XYUPYSr1CVSPvdP8xEfO+CtcC1xxnbWOUUruPjIuFjIwXhhROsdApI9GddjvQKd20EAKWqopzkmafF27yENQtvjg+/Dt/DpwQ+OzGCtiaG7OOoUWtSUx/7Jrspzsr8P85tZA4UY9FgQ5sguW4DPvxEVQMS3EBtir0+31Xwo4RVsQ3JDLBTvDkVHR/rk0cneJH//gJFgqZ/hdCmskw1Nh/zNf59P/JtKjnU8dujHvx35kNlaNbVVOT3AxgD/awBvH0izoBazq+CYN0ytHkkplczyBHIFrnT3rJPf1lQUtiwGVTBSgMpdfEtNsOvUlcRSaN3fQSX7so5G0Xho708kzz+mfYnof0tyVls3mTm/jnXIzYX6J/TtWLiaQnfx007Ahj8XFjDhJrKOBg65+9bjLy+eNDxEzF8HD/6PzwTXSM3RJcOizqLIM/AkqGTTO4Pt3lZYDQmHmSVIwUUSG6O5n7+hrtK0q9O8q9SM0ByWNtEFNWZamPrdFAKhSpRGFPdqZWRobjPJPKMggJcRKhMugA1wPD5RDkczWxYihhn13YnqqUNjcLq7OkgXeU8DnKT3t45J71Gp6wSToYvtj9tABgm4UbxZpJu4lQngv4u5vNLRhatWKBEnMmJVNR1lhNbun1bHnxHZ4+oRtGuTR2hxIoUbYUikg5HqbZF4RbPASraubQ37xTY0b9K6qvygcgJqUS7a3RYFmReJ3/Yuo6J/3S0GftRcB05cpIf4XLcXBqwdDS/PXPJTfeT4y3n+40c6diay2O30Qe/HDf789V32Zy9VtNwT12K5nWuLELv4fg80IExZGM+wdVFJ+zGK8wJdLeRDQzrp0h+6b2oLZZr9+qEz3iiiKpzm1Etw/hDJiMlUJeBXzT51AlfFp7J7WtKgIKQxVGeCs0lKbZPjJu81QZ98xy0dN6WESO5CqfKrEvpmujFsbpSCSsy4SO57QQgyI/8OWWqiVeRNr1wPMvZsNbj//5v7KuiSXJzTAH00BKtA/dCkV+6vdmeg1Dte2JYgavibbbhMnRTOcW5uAGv5cRs+HVg/CeA53QpKv0Jz+VClCkrQguhhMQ0eEhMYA7Khd2iU0GKpb1pWksomwVE2g0GXU6z96MppJdSgFxT6tqmZRObhxNHOUQ6PQO4oimiQ7C2kBCSnTLLBJa1goffhaLRLUU/86r2I1C7TvOWo5Jww7rxibnMJpxai9jZyPCRG+HeSNQ/5wo1w8TfK1ClfpcKv6cXHareW5g3SD4wDmV9zOEby9AzLwO0kU1JhDzZhZYpWQrx8arKqFq+/1dqbtdDPf0WazTTK3aFKKE6Y0ufYeg1ESBQtCmltgUcalX06qWtCrCqmofcrhSkC1G297MCAi0BmEpKdKODqE7SIijnHH6u4wgfxqQ/ClCEl+9KZ84zUaQMDqI6tLomg2LyY1EHv8k8h/INQgL1GPNCuAiyKzI9ZuafsrUPji1HRZIQm0XBJpIaoYBPDlbJOSDEi9RSZB2RzfBSYoNMNZKfZhmjiWPkQS4Gm9l/KvdlmczT/Yw9o4aS8gKApYkgxAXaR6TqSZctJH6qXLaxvSzu2ESraYVZxv10WWJKsNYtbWUIIT/HItrFUwYI9KUHEFwgiRwcNqGp0hKIUqSJIVFkpeISSHACuwnSEWUFZ/NhUz7b6JhYPMHKf/Dvsr3GglbXS/cWRieGuQidODW7PUNnoAxOMDBwuSK2jIDby6zx9r3eOMmGjEarzRsdXtyqOTnosCj8tpB8jeaHXExV0pWW7XoGsWpm67sVfWaAVnL1l/MVSyq9bnaFw0Kyy0iTo5wSskvbHzEqYf3yx2D9Gjw4d3be2hnB5U27t/cw1tAPJdHFHjTZUpd+owhWt2nVMT1h/YiAjRQqJnqSkEmzH4A/Zlg8eiUalgz99zcHwcC2iv4RnxIzxOCvMBTrJhpScyJC5guJjygGcmO0dkdHRU/k9vq0OlxJvyk9cT6DaEJBwpcodpaqTQygdniHxCWldS49ocZIec4ZcKjjVtNOyAmIiAisoENqq3UExa2TGL6sZ9VV+qQ79+0EKsSkZKdDBeru3zURM+SebMvo06hpdXlMEfJh04rRKp5PobO8ArUb96JPhZeB6KD+TjAvZxlyKAb4k2j/jNGRcGKfVI3F23KWqhRjq3842agA+hOO5SCCq60EBOuV/PWCD2ljYrkktbS0n9EjwBznFBz9zwXExnVQgpRQolKVD5IbgEm3mdG+ejGd+wuz/ab0b9ZsZU9A3SImHsT9NUTXg1DZe8zdxL/XbvUHP7LyYYDTcB9w6dX/f+woo0iAy/7bkw4d/CJiG6395Qs9/tNkDBfbP6xOs+A61I0w8dI9fLaDnnEzURiHI8/pbBjlHb1BjLeSpqZMulnQkpwYpR0fEyBX0fL+kbv1d9ZLyAZZCJMC1MhPbR0el/6Vn0GZSkkM9F+WT94CYVNDLl9uUCrfTaL4gtLhebln+RadRVJrSvrsgl+NWBMuQreGsgpj9vT/AuAnBab8jl2RWGqFQ4rI+7If2JEEPXOuob5jYjdjZHeHuw3v69s7Wdk3Dw8eDvqoJj4FpPVU8JRyxAP40+8mg28DREuvxDGca+KmydPx8ud+HdifTcTac4g04AoqLBwkAsV7b30LpAsVFr9DrnEIcOt6ZlerVD0BHaLj/WZ8561qPVzMsRo0/Z/GJj0kGj9xiNCsvzimLdudWp6lPqXSKgc1QTHFENbnNyIYyiOwH5RaI5npTXWwwDSYj7ekULx25Rc9dSnZrJKI6ECi/Gd1tyWFYKmmxczByKWgA5gHxKjsTT4hrtMsIdpJJUmdwtqbHlmrmp8jjbv9DIZO/RZKofv7uFepBrqlsDMfn1HwjrY4NTOb0Fv70M52AesuwUkCIYsCNqpX6TGt6AU2HFDgdp0dSXdkmMuMOf95oAJ3An00wv0TdS2TIRlvlVwAAgoBl2WMrAkRnP90Y4bInSy9zb8P1uHc4/kDWwae6AV/y6s7xbS9pqehd0UvHZ22Jhym999tqLEyEiFPRIU/L8a1iypu/j39MwrzEuC97Zy8mfP6qmEHTZhPyBdRQza8qcqQZePtc3Kn5hwOrEk/d1XTPRkLgOhfooYJpRg3EQ8oGAuvo/NwduLtoPlpjXd6G5i3627yfaAfdzZ5oD5VdIfIMlJ0l1dOdH5MBmgS+ds8gim99AaXl9oZ4ZcS2ysYEUICKviATD2C7Cj1id7DwxSl+J1eW9lx4H4mHxRtVozUAM0h3Z7RNO6Vl+82TDefd0v4TjC0Cek9QSCgVhx39rNZyifqp3x1SvSla43l42f1so563BnJIXVv1dad6I0GK237F81AeEBJrMkucRpA+I6COYg2jrhnEXg6lS8qz3j4zrtywtHU8f3Om9O2LSCq7pk0vUlLD158MsG9vJszuRqGX1eYwyoDn+5F/Ozqh1Lv5rVcdXnaS+Yv2CkYULnZ/3Km5IkxwOcfRMM8AdQN7oEo/VSHEEu275sp5xsk6h7SDQG3/mBw2PQ/C7giraRfA6GqnFaPtlgiyo4fojRgklN8ysAT1vdXJ5CtDJ+8TeOaJGSXnGORrKk+ea7CJqLpngsBT/qubCH7nsBewvFVa7O3ozy6X7mmXPoRn0Vcr+N0M9IpzC6Wb9qVEH+fkpgZmIoXzCQqWEUzDvl6nBt+NF7xxF8Ibhqncwn3bzyWkmKsPkT+cIL0KfX3ZAS/DxgeBAovayo3m0B/If0UQY++S3rTdX92m/Kra9cYqKsh43uz5RxazT+fPH+p5zrY++ziO33rfS/MM4yd/JAoNgGRfmzeNT6AXnZKtwECs1PlMZ6loeND89WUcHqX0MQ/FOH6dNLFtcmVntVm3TvNlZuOJ/ZJBPLnJ4MfU1U0JO7zaMLlLC0M7YhY7Mg8p+I72UalQ996+e9WohHwqcR3AbLa0NZcHJzMNq40IoCbJAG0wG2JsZNQ1FZQwRBDQao0ob8o+M3qs6MgOXrc5wNDQlaxzuibKXEocClfvpLO3mtlva9MzOrLZu3mAz1Swl/j5DK+VeE5DOsOmR5vLtVaXQ2DD4nOYds0KJeDydNXQN36Rn8FdsVBYTamy6XRrOj+0/zqyicjJH+urBEXzGnWnnk/vv2SYrjmSnZn3ZeqHQwT3Be6rxUrPIs78KuiJu4Q2zI3AISEjw84HkitphMVJvz8X4crn9Eb55tlxi4uRZqtf34NClF3xyzW7XMoyfdE/uOv3IapM6HcLG5k+1MdUo6QZJiEOD3iMD7u0j/kEdKtFnXztRgvB+FrCgwjGJMox62btBPRKGUnDpBcQUqzk52I4yh1E2BWCWdC1M4jSyCMk6ZhGwnRH7moc9aBJcl/v2KRdBxGgpW62OC8yBh5r6QcB8jfBwbtefag32wgS4wjWG+5iALzV2/vvvXteFkZ61fn9sO2kw6wcNIr+1V9mpKeBIw4WGS54CxMyWB6VWG0UIPNQRZc46FBIAtZqyZ2v/77Ues1uAoR1advQYadjZUfDLOqj+jy9vrpGhfSAnFLPG9h7316UMzSN/sGXrzk9Jd0woRbQkC81Ef6gv14T5A4DRwgNuYj4G4+nMNB6KyB+rAa6myCEXmTJlfGxQ/zG4NIAnzHgw4HhdOFeB/XvWNgWnVLAP3w2dqpZMNyYgdjhfIThIXsvbQY+ZAXsItdXJGBweR38+XMtbi6DS3zhoSKq/x0jsS/8D/jLgYUXPKEZxT68ypDvLniQND2Z+CwXvdiIs/7nYkSJm2SYa2xL4RI5TwescwxcME45qWqDonuXp3AOlXSBfFFygHgxe7x7gCicjXm+wNaudPXxlvVZyx84kQMlC6WgX14kP5EJ8lNwMzFywE+VB5pUQZEoKOn7egGLR9uyPoPvkC9m8i2TNSbuvXnOwzbJ920iGBh2Vs56caOu4BPBCzDZqbDoSvSvSFaTaKowSEMwcn8eDsrUtbwtGQiLMfCn5kh7XKy2uUl16LcL+/CTz9tRHS/fmywoXc21rm3MUIVjHCxdQlYVfP9b0xV0FizytfToJ1grLgOIsH+3qf3Egz5zRvZLMTzJOQe7P/+W0xyRo6qWjEneJXdIuIvUNUDxPKAr9r/buYLl8X7AJJaS19jl0UDzDMmQ4DuBV4Tk/kD+IDvUsTZDvjgumtxEtb6Z0ghV9MHQk61VKnipaHAgL9C+FDXyK368o3GdhtR6FeZKqEX3Ie6kARa+zha96x9DOnNlY5J/0459AHIMBA7GGiXwZZpWp0mTOULXaE5lYuKy4mldlVpX0G6WbfsxRM/G18I4wxmxPgir/7sfvjEWymkse0IB/AERLBBMdJHAf1lsM4m4umsjFcpXO/nLCbmBwAaRy4u8zbFQmfvm9BHCVRjG8BWfXUxf+0rD2VJlINpYe2AIMQ6uUKXeF4bL2mIa/7a6aivYbEIYRDxH4PKVjHg0MLWhJdYp/fyJtXZA1kmsFccQmUAiYa0TTQEF5thPrhSPFiH08cm6SFWnyrhC+GBV6ggiRssv+eQ8Rt7+Q1P73KirKXFj9KGpPr6Bs45ycpK2Ep6MEei1rm6I9wyVSuRkfJSgPMjwa7Eip4auxgRKgYFo/7bQxeZCHadq2elakNQH3LoZ+4CFjV3mVD0UmERHqaWMgHPKIHPIIH/XYyPy4/BskoVk2EV2sZNjRYrr0cZ7IHy+yGX+nS2oJltloHHJvoTUerjFeRPe1auR0jq13ERbeE7aJ3IVuKmp8zORnkQ1MDu93CyjYnBc9XhCW+zksLF89/dhy+mzPK+ohIyi9kmQp/vVLoPi5VSnttHLdUlFUZJWVFfJFpdg9mbLiovrBSYexcOIkBFtwCJJXVfh0zup6x4m5o3C07Hr9bESXvDDhut98ddDDGKt6KkEFRAUB8N3E3/XN95x9h6D//vs4bLqDkZAEED5EbY7d/npCCgQdUj7csc0bUlsF1/w+ADgftHBuQqy4HvXWfHkn5vZfbgLKvE871wxL0TligXcu71MPbnhgUcHXgrBFJYSpSCtMBx5WDmyDnALPRI0u9vcLGyzfKVPt/GDE/XkrsXwZ/QLCfBBYheXWwLROLOPVYM7YsPk0qjxr3V5mN6rVdlhm7kgPqqhtSqLi+C25Vg/ilXWEQEp5sY4LQRhA+JwGAKAAQHd0rLcBiCCsYsIy3e9hEDBGFAJHJWU4b6A33CmRkn0WaNfhe2jtfe4rgu4LpG/Mdr0low+4CNvDqEvDnH70Re/JvVU90B3h/OOP0A4QEXPXh95qqB7Vh6uM/ZIsIKfRAerkR1AWPvixw/9y/Mbg+Bg+qX0rxvQ5W8h255HOyMvb5WsTMZ0EesuM3xOjIG6Moy8XJk96Umiff/yItBZ5MMA8bJ5JSfJAhNHeh74268u2UrZeg/PphJOqW/aw7oPFor80AnxRcwE3ewf3f1s2kbR8mWiYomtSzwK+2+7A+/He46/++ry4wDsm68e/s4hHoZi6moBu59ihhrOrPvQY5EAUghIAC46USDoJhXLlCvNyg069rfSwIg1gkIgNaNfRA3Iu9W5SQghvcbAfaDyNYFxJgb5BiZ0xUYqsG9AjVpOLoJLfSiaJSUra3UkX/qE/3tJesvlYEn3P2c5zxDb/TO7j2O4EBb5NvYzn/iCmYUSvqLTMB8jcL0gT7FM3cz28kCVBRbfwkYsKh1tPtKsrdlwx8cU3GGIysz4f8WXN93AIVJkkzTJJlmAI7JR82l1U9uPeRIQz/H/i3dUbwn7sMHL0rRpmENO/YjwPgMuvtutxGUQonwQHIgzAUbrhBUuDwBPUNQwyScH1QbqsHmFn4QrKWv46pcF06bVkdtN2TRwfl3UbbWbHEk9evClxNOkebeN8rgOO0CkPDsRA8cqTEtYV3aGTwaVNV5G8xhrp7WtgatiCodoUPLN+E3YS0syCrG/Eus8A7oU+45IL2k0PKY5625+eZNkkOETUGe6nGnoNuE249xjjaY/iSt66MpLlxGcUbG8AQEOV9YmC4nibcovk3STcg7QCru13QtUsFY53HPjS10EZdiFf/RhPWr/sEDGncyD3sO4iql/NgPqvhguVyaFV0Qt0UMyg2gfAGSCMccCwNYtbRf2UlFm1tjyZIl6QbOOzkMj4Id3qlYRUmgsbQyWiyl6oJStfL1OZq+KIQFDmRirx4WvAwXFGJ0gxefLvwz839B7uGz0voyAMbJArrDiS0cnt/3Cq1TeP77mKgwIG3nL8TLZsT3rWFV9gw9MjVsmbMSrFOm4xRDab3xV6IrA2VBNVVn5rl3w3OyEbVM3jY7WqjAqFAKpBXrEmPfDr8Vft6V0NnRhyI/G8Z6tJyJfkpjrPfzSgNyL97uHFQv743465sG63Bz2JmrvbjCaCwiCH9Rv75Iec5oeIzNh9c/z6KKbfBpD3ofvDfES7oai53ff9fQ9hy8SWgaPFgujg/C1nfHMI3oTOPnMv571PtkVj61Nt6yTGYhiHazDAz1mqA0r7ywdJ1gRvdE80xfFGlVspdVWmGx2DIgNyZqj7f0WpIbZsV9Rdz0TTeJXSR8Yl0JWttF4gijzhuQAGStc+caEjlt98uiesRXxQcvzTPKCQpiKUu4pNFzwcu6zO61Wc79wi8kBhWBrXCaZ/lSQ1XCUPv99aHNv84iK75Q4tpeyZW8r90emhad2Pi89EqHyebdWZtap23ev+CKUWFoRK0dOfIIfZ4R58z7fyysMvd4o5IvhF8tjTb6onLn3+Xw/O2vV+cXsLavvgrOafDCEvgSByIRCySeINHHQszQVzdG0+4+CMERZNL+aT19I632SSnDoo00TlEP1e2c7Qjsu+kqYoK4XU7KWXMlD+lLdSdT+wyMWMiqWOIUrtps1sZFXie/QThAJblIy4sME3/id76LPLUPUF0WXFPUE1ezGrKtC7YzWKpp+jYqef7m8cHXLkryPd3PKXOXyPEB+mmXoxhSiWTXJejmJqsAKlFyhPjm2hSpfa5N3Z5yjY3CHyzm8FhXhDRAxiZ3V1aW+CcofRM9aUR3z9dT+udZLdnyOSmiDC4qoxVC8L6o707ZlBQm9NxL9P+MQU5E96EPAl/53LEPeBkCkDSTlk1yJRS9eFuut6aO+bbR+Ze+lXDp+6DN3KSmwTzj3bnW1k/a58+L6U5gPd+58m+0aV/2NvOoT3jmsbvT999kP59DtMwceTlePrCR/PrbrAHVviv8mVnlu+nXzKacwSJ1xpgTpHdj/hiiZbyPA0M1uwvrSWZoI4yWRCcSxRAfC5TBMk11EE2qtKNxNmvUbDgGuJg6PRXcMXNGt9ChjP0Ui+Ilh1BQPp1AV4Ot6FU0vtptcAyx0a88XR5I1bOk8DICR22A3gfleIttFMoNRRpr/kSzCOaZbFjJYbldW9kjm3/H0iUbEiQtsJ+Rq0O0em8gbBqP2rQ/n1bpbW/IpDZtFfuh1m0KHIX30TdSvazUxBlwk0YDox1sEBP1CYZNIdkWB8e69X6k0YaDPvXAV3MSpWH9kOfUkvdvdOTeOcqXgLmLu4YeSpwfvzS0Pvzx6FrqHf8t02aEexKX0rhSmzQYruscFyOz5hEmK/I1YJu8fan5418ivl8bRJT9gNCLS1xkluy+7O8t9cE5izmwnJJzAuoX8mXRlA8vkkkkKaRy6tvh5bvZwJ0CpDNcS2m3SGJU86XxqlUDMVqq+7HCg6LoTC3k2phdt0sZWCX4l1BlXkg0xbSoL02/Ot6HLp16e/7liAhCNotiB7dMPgNaJacae/+vGWnEaMNu2cjDXjcjdyFy/jalXjMoXLTBfxigClSVeb126Qg/a8e0l5bfCCSauCXpLIPIeRp5abpQyBMq1SN7dIhSjVOZfF7rO7mtj+vLK/9raB+MJ1l7gU2frIPvu6Kh61B+NrLLflWAO6BIJ+TDXmzWqPsq/2YUgiaDJDhTIrNyHEYx8N+D+8r8D7pSGTKmHChq5/vZfQjMUgIxOXpKC5lCWXITPJ8w6WeSl55wgaVKzxOJSbJEpJU6Rc2hNRVbDLDObXoB1HQiH/TSj+iZTv3QW+WShGiVD6DDdsD45qMZJkFew4FyHCa2NvjelsRPb0czBho9D+SfI+AgNuNFFTIf+LS7oAarhKNqFCDE/ls+BuKjNJQfrAs0mTS3nKQ2I8EItMHv5I8bm+Y2s1wE2ALwGCH0i72e5be7EcNbPTBRI1LAU4Rs/gZq/hVbLDnx8v4LpD9w3s7pmlrmVwGHr2ZxsOSpEgTKqG8kkdwWXQjnaWy52j0DH+HR4CmF/wEUNXB4U+esYobjS83zB0Xrow0ieWrFMGGiheubzdREnVeT6ITTIhn4b2XWbsR6AxEmLNzSSL0wcyVz760azMjSr90/upZvzrSHLNCdsGAyf7a9Wq/KSs91+BFjmPiFS6Gx1074U7Hncxel+SL5Pid6/rkyId23GrVCbZaN+fmZNcfHNA+Z/Fi3WCbdCvvM1m52blb2PrOls155X2dDjEVp0f7WnVD7cWba/1y50nvGKAeYAbmv6sh43eIDETeo4YRffXqH0NJ6CejVBP9Qdpcsa7dcmzOWLA10kqwEgZdyWfHTbzVvDj8TFMD8Lowk13W10x6p5yztjk0jnrBPK3cl0StVuh0dzYC5X9ekOb77S1Lwfiqn874avSvpOvg0BfnpGNnnmFcBRI1Y1eeYVSJDCNi1EuuaHhm4Y5k363Db/tvtsO/3qqXfN98gH4xtCTIlCttGjEGEq6RMFkUI2qjnRwakthOSmAGOgB9ialsEvyENsE7J8NYCNBdf6MN0OcFdG6Qk8O/PmWRMoRit6itc0PNFZsW2kllwZPw+qaSqJuXbdksyK5Br9MIZ+BbB9P7XFiIP4FJxplbUWGdCjFN5miStofwztduH8mr2WmJeX8Q2PJ0CH5Gd+Dn8whEZhth1JSOhj6qEZwkmJMcrM9FiQSAc8BpDjkBhA6gMhcZm5LgzcuJai9Y0D43IbcX+z2supahuQaMLgIaenMg6O2bWveWyvaanWcvqAFoSlYUGxPG9XVt/Wcj8TVVQPt/Wx2N7iCltKPLPUK5k8W0+3KUE/xxIN4OJZfnme2+GZgvCmYwuIchzpS6cYzinnseaGY7xr/x0XsSQIpsR4K0QwXwMnUBne5qv0Qx+XLnMkZsU7A5ZiIRUa+e7brsUB1WF5Ru/jp53c4debcaH9qB2xcmtGQCw+jlnolTKJ45SKaHxLg2u1zh2PuF1IgHBTzQk4JuSKAMD9wxPMJJtiBSLQzqK3b3cTzcJNIiEkgeeFfwZSf7rcXlpB8G8nqvBhDSb17KfyKJdqi/sulB/IuJ7Mh8ICkly7SpbDJU7KYypb3ZjB2i9eZV+ayTwfUms2EWm2RDxAt9DqND+R6Lf6R9fZbJRak+Ce71+LqLG/xEL8T0Fh0Zu+pVT9ZHsSq+HaMONSYDjbQq7TNdLDiN2qO43nm+IiJs6sNuHPQrMgXAWohnyjPPp/jhYkXB+IaE2QJ0oRRgcF22nq3vuZSsOBYZTXrmXO38BGiQ3fJ9TLPzkx5AksW1u1looHqMmX/i8jbVNydRUfcRNWsvgdYifUpM1VRCRSoW+4PgxkgNJPoOa5XacXThtf/VvxuNBFt+BeKNAcZCt7eQIcP8jVDyw26/sfnPOaTGYCMObe+DsxllzbeN8b+Vtg+f3xQFqnFIwokQ08B8g4cT9dCRnpZP+fe+myk2L7nB99KdJ5178Kj9W1+UZFNt/W62Um39AgbY9UhkC/QodY69qQWBKqJmt1hG+B0S+ndOpiuqfxMb/XorczLy7fKrOi8OGzxN4RXxaQLUUlPdR4UuaTL1+/mF2b/pWumDpW5tikhUTh6DwOkgTwMNLqmGAh/4pH+BJnw/xt6EfMbksr0nXkOJO5iChl/pkOLtS6v3sBHkUwm8p9JGWFLO49c5pFa/Q2YNEDWhN8JIRibVTyw3oEItWKXJY3/Ffi2lPgkijPDoqz8Y1MIGPYQnzeJAL2pRPGDz5ZjmegXok93Y3UMfgDQf6sFZdDwI/bKOSaEDv7BDyNVJC6JaByr/Zn1k9pMO88T4iYgz4FCBrY0x7hCf2Z2fzOraMgwnAHxpXbWXzQM3117oBS8WYm6Ay24eZsI8dep67tBdIwb486+T/2mTwpTrj3SI5msy8dVQnMM5bysRc5BKmDBpiAJ9YQlcOGEqbHqbuPXflBCpC51FRITV3SdpxrWAfXmFbe0laeFY3KfOyG881tEtqUOF3ZGCMluMd+VCsozNovyz8ZUN0YTw7UkEau8RsXPdju8UtO0QjSlDrfTQhuvxnvTwCBAgRIUYYKJp0fevqm51dvaUaC0BAQRnBleuDkiPtrxupFqzgXstgxpud1qeZuQXxN+5uKuqx9t6O8MnCfUPXnNPycz0dUYWYqzQ0tYguj6TMbmNNyov3+jsSgu03fSsqPZspCYEAeJUIMG4IAkc4CSR8TohKORKXAISUphIKIONCQ0KLinQHZX5rqTm1MNij0CU0HnseUvArtFRDgsCgxD9Rpb3eHIXiaarT3IAYiwZvI9RCP6K1KUaZ4QkxC33uf7cJaqEiV/vNpiGQArhRYWR3doBK2543C+epNNvCYhTXfINKiQk2zH7+1ghPxxoCIEtDWWz9dW+KM+rybhVpKuUgAmp+DHauFqsPU+iyt51yZLcWu/uj8K30tYAd6Qm46mKaCmwK6JNrQw/JcjOqQxTqjvKx1WCY6hDs8smJDGJMdrf52LISbYJXDlaO6x+Ui08jlvLHf93whEx+wPZu34bjohTAxpUtZZdaWlOcW8ca67CzgGdzD3Aj7ZDTwuaGW/hKOV+JCi+jfMpzwKPygENJVQUlcUwKsCoZnf7PfqqOzvvl+wep/M/62K788yyOqNVel/FEJaiDsPM13kMu4jgeBk1G6Qgmds2feBIK5M+OgwTqwf2xVs+/v7WrcB6QB++zvF7fzqOuAnotszR2505VaWraj3tJhovOBMBXdM/y2PfMhz4RtqmNXyvqOpIpXO6vaVql2xPWbGMoNlr7k4heK46GpVIcGwECCqOi0qClIJCoK8/Oggt0JRI0aRIsqK8TfI1XHK7QCWJYQRPRprl7Cj9ez7wH8wwdoPTrZD6papUHnyjHW9nkWRry04g5vm9fEnuGc/yQNusDYFCXgBhTQ4cboSGD3xBF+mmjnPXcWWFq4Z1xB8OJdL2lQcZVsvs1479jPHlO8XAknIkWJIDTnGqiqHyDMkA87KfsMyMf/epnMXZJCEHaGnF6zbhJHZXndJUvnRoiwFgVEAS1W7lF/g2lzcpe2RkD+1saE+fnocLn9khS706xjgmM3i/C/Afv/5G6pPKkywtF5raLPYUD9QkIEAVJSjJEiCcbtRJEKuLjReT4piU2KuiZEuUxJ3LaE+FS8u/0DQ8CTZHyodF9SAtZOh/YtnkmQnlVMFvdpjSgFM8JTf4yZloIWvt9fPZERxMVv9XCVTuOdx/cViQ1Mzx0g9+ZQBKOUxILgcX0DKad0ilt3bA1A1x2O1ektEIuUeTG2NI2FV9naCpD7hS3hvxuOAwCM1K6EykSBcW47SbDdT4WV4Z7hgMt/y/mRbybtzRyn0rVAx1tw/6BigEfnaBFMs3KUkETA6gawiPjqmS5kv6ajDMkYYUwmwiaubBqSbH4TjPjKWRWr3Eie4i1YRwHX5k+oh/iUiB0T4A/dbs4f71JIixOTqF9DDP31sU3LhGaKhNvgpr3Iy49tDP2FjPeb4NRVTqVKHd6RGbVCRva7IP9e9uZdIcGg3WH7zWFkio2+c9z12XPA10G7beuf/hubqWsRZy2QxQDtiAK4zJghUHZTkPBKj5AuUpCUFc7HXRZHb0Xen7TqWBqAp1Z7zbsvdv4TD29GMNGcwSeuzyrwLquzPbCqt/Pg+KyL97afLWwjlqfhNydReD89taPvP6hkOHRHPnF8wRcKcg6Q9PwXGgr+2o6quFEtE1WffM0vFB159I72hNKSBvm9bV3gSk6JUqS4DRoTQ7FGOxhyyx31yYVvgLGkMDThS/Q//Ujll/OQWSLFuBgLRJAy4N1x2dcSCfpQJWv1wZrjprB5VZUpNLIetKTj9jtRK7pc4vulSuGhznjJDAHy7ecPZJILcVf/ZPmLWpeNmEZqzhxfr3FTK8qCFwwdC4Rrz/FZPu/wlIvORgjLaHBjBXy/iTh+tdAW2CfeyAw/bpVZawsfY1W/777iPog9x4q8AE/p+qf5IDLHitK9/jqZ2Vmx4rAH5LtH+6fD27YM1d9Q2nUOuQ9arwJLcereAEN4b8N0wh1LtEv+D5edLX1wDJ7Gfu/uBouvrjb8daF8EBgY73jnGI5Y2zQDZOErVBv74TO1o5XNUBOhrVB2tv4BVYSrvPLL0HXD/AMuA2S5d9IdA4tYHlAGk5FRpR1s7xkyljkjsxXsOrZqfuiN4371l9Hjx5yq3PhSU6GN+ZOkLGw/Rdf0cNQaKLcaPRbB1rJftitDUV7Yh3fo9s9d9mWQ0rbPRw978L+qiojq3TjwHguFOE5hBsxrs6SHPlxYjoIZPOF78qPyVIpbchza8T7+BuY8gNVk7I3BuX5EhJk0ws8TmQfxOZcmHvdBLOGdFjeIAk1fKRr6xbr4PHMl+sUBP4F7PXtHADp+pW48lpacCCNcmC6ZkfKfxHibI3aqIzW/I2+06dC1foq3BhNlsWOVDqga4lnSl0VPOM6q38VLv9P4Dbfj1KeM3z05iCJpOuxLzodaHL60RT+xfXhemLVvmyofDyV8ageT8fxUe5hbaT7JNW3TGYS0rRWoNLfR4S19N92SCa+G8b0MuJUCd6A0chK5kGSxRGi9vYHhflBqUiiVobGNRxPOgRmOBFr9ndwZp/tl2R0bxaMTcoSZjVc+fd8QeqmO5NjTCGzVqHvKUGptswFTQvFYATZHY0aOOEhN6YJFurHLl1MQccyoj8Els7Ly+aPOSS50GVcYpODZdD1RORkJk7pEwF6whYzhkPPCisNELjWP5DUXwZ3qonlw0nQPU6fhVD7di3uvcWu4RU5yC74sDb/V77DNwNe8CxiBgTYBtIluQoZw2y2SxWxAXr1fk90RpyrCQl+9/K4OGIJam5aIuKHsxYFSSBq44iRvCWBB473pdU8/792ytP7gP2sFTf3XzfScziqbwRA1JBjUDEDW5U13iOjeRyOIfZIAmVmVJQ3s6LAYCnzKC8WaTB4v6nHT7kHDTDWhYsEUL/fkDwQ15uHLPK+sfDDmz5TBurTxKvzeFxmK5SweEbyzBWneHT3oBqrIvKuO4D1xN/VL2X47R+ZG++SHJH3rTxABBTH1tca2pOlcic6sTzbLHltbrnmDlR+ivIKRuBaSrItuCo0akRzvmxUG2NQcyj97OcKeUNTcVcudBozZB9WQVrj9riJLnVksKYyXJ2m7zsJSvRK8zMoiDRt8EabRAMJfE3wg6al4S53I7AswLxA3opNTQ/eCMajtwMN4MPohGuv9OA2wA3ZFe+YBMa+0wpQGZyG/bLenCPl4isxaOyaLF/mYqP3goedOZJoc+Q8dLgJtVEbZOHiLyuDGBHh2Kxbxjl7vjZ9fW+M84XTh32sKYtUd1zjpsNS4m8d8Y13iD7ijyWH1XgCMmb8o3Pq8rZ5GdYeL6QWPQtMouVWNjFOz/ekBvl0kE20PCSl6M2yRn2IALGHf1g8VQa5HblqmyR2gRH76l2XdM6YYGSWfzHg3wkshDNfS1PtEkgdTLX0+Ji7dMSmE3GFy/k6EeOA29HGaK3aJhY7nfPP1dJkNPbt76y0zSAp4v21tLTEq5GUw1frMo34j4lUXep9/4J5FYPBA/n3rMDrvZq0NGa/TzL59YrepN1qz5qUAloHpOy/8nnxUIjndnLsNF/Psw35X3tFK/WdkSrE0s7J3Rs08ht/3g5METXPvrgVmXrMxuA7C5GpNrTKg902LHndVrLVJh3sYNNLmawaVYMUTc0mBu2mrtpzV1J43fK5kQjNnNMM95dVQRpQSPL0mbicKVyXFJZ0aPxvLZntFby2YT6aHxFOX49gmNNt71ffaoUdG9B3PEknyQyN+ub1TSkvz2VNvsC+Cir8LR7bHlJcsmzxm0FezScCc3gmXWBhn70T1hptsSX403eYf8n/w1v0QRdfogIQAA9Bub/N1GnaOQ9pXWNN30/fL28sruhFwEC8fBtBNfFL9VfGjyCmbxBp4yQdhJKt8/DeFq5HuYaNzv0tHB7NQF/YvGsEiseJvSLGQOMy41d1N44welYwXkiQ7vpN1XhnkzlKvrDQwNmKLbGv/VEOq3usu++KH32qC0J+2XVCf2M+1nm9DFgLRRbP/GrtLcq4J+DviBWiu4nx53e8lX8420jxkEGKWQ3WsHckSyTPC5X96omEKXhKmsa2d2HN09AK0ENIJ+K1+dcuLiP5N8zd6gykDMEaT66kcBMap0pQUu/3TDdPCIGsHwv1NRYgrY4ocfRuGl5o3mjZtmq2g5XEHc0sgL2RTDmZd5clwR1DiY90J9hlm5Y+r75RGR1eauZMv4wWnpYL3wU70X6YghDM/QkS+92L+HjQXl5kjx/Cjg5YpoCJKGozrONxxPaEMOyp1TGOk0N0VW4X5/IZcjUg6WZPFCO3GUHOxgu10g899RPTfyF5+qZO9rRgPFZhliH/QOBvSDew1BXW2TKMXhQ1zxqkl46+b7Lqf81F++WtR//HDQxzFrk+lngNniiWt997gfbMVPeAZuycWipLJvlZha4YxHlAktVrfaKv89FeXN8930D+XqtdRwuiXOQliakTwlLHXQf4ApyL8kyyYTJ8aUJhR7WRPQ1oeInZO+/FFtfCKtLYkbcOTffC1grX8sk5z4j1/BXWiJ8RDDhyLyGa/HyMm7XIq0OELKsPsKm76NblSkFUXGVucQuHFbUYdPipG/kDOLFoTUJTbrxEN+H4uKmfs91Y7fsqnZCqR+LKQdpuqlJZp8hbdN6Cz6fj2Bz1lz8xFCPcWuAgTD3Wa1rkOi812czSUGhFw6mVPdfWv5DCiYOWfEU10Y7WFNt/8YhDT2GvUv7cl1F+bm/4VqwXWkVYi1mwC14bPKughmaEhR94BMd7e1OJc9n6fdLY6TocUK4bF9LgfQDr+gVOvYjRv19rChtj9CIIwIRexYOrxU225v1FkeLDsCE2EZGlhCGBBRsFe8eARjzlz37cNZ/XgHJMv5OA0P+Fli28O/49SQ4Nth3M2nWN6ajBoejv3EuMFO+lWLmfuOp4a98ofMJecX2b+SQupqT+Io7L/9Y/xIfwSjtL96ZSKs4KpFVJHTCJY6Ioq9JT/OzjH5hkKLQEoe80LaaIAwI3oAQILvKE/bDpHZqplcKc68PzXbGii1NA5fUMDIXuHg/rEZq3jXaEtmq01lCJC7rgBB24CBuWu7ZV3SosskKRRwPNt39I1+SRh1PaWJfkfnY6qiW9xV5H08agJfnOHjiYSEszNSCvCVJ8BYYVxIJG23B2h1/Ev0v+ndxtcTym3P1q07EU51re9CHwDy2nJMtE2AdFBYdHkCaoufy2CoOQnfwpQtfo/ZdX8mky6yOC43L75wkzwy6AnGxrQFykGmLYkavGEm0ehAMNPkH9nh4s+IzYpbZ9KzMyxzwm/2YV1bnZUQjhC3Iq0ujh2Cmzg0ismbCar2hD6UlykGYmz4SCn84+VVfMTySQNtRHB6sP8W5QuMSBvLjoxVjcndVMLQhRwl9LlPqcO85gbH5bdEhup++6xYAqTyUeX3o81sxfPG+OnDz33TtGapSaffg8UaJBTlO/Q128D7ot24DaGdsVXzi8AlCmHRfWT9X2+KxjD+T/AoT8z8OJZhitm5hDdedxRo7aY8q8+Sg0B6TxcCBLI9tBzRE5Iri/OBiIoRuhQnWQF5ipIuEw2Eczim4suV4S/YFtMfjrudUYGc41U2RSbKmvwbdfUaB6BvEWI2GfSi6Bo2AFAnJQ170hhSMXQM4HXRdh0PVZhqNWyHPx2gMcRsLcJSSBuaP713gSBlx3ik13HFjnHzUCMFn1CyAJ+BslrNt3jEh3djmB6FhCXdesimsI+nm0TEIH2d/twttTcDmZR/mf+k8IVSdqaXuIwM4Zaf6cmuJJPqlKclJNe9g3FkHCAu3zIswvGVdUrzIORRRIinMp5qcvGySDG9nnG7fdLW9CUTEqQJqEqlYg763JeO2BBH6gfB2EkPawAi3DlaoXF146vMzaSL4A9Xtipcyke2riF1gqNjpwP9B8nPCJopAT/lScj36H3taNRWr6/6XCPQUHPQxdAqmsvK7y50XE0YFpj/31KRUtbVRj8zlnOmzm01W3pq8NuA4QCGor5r9Y8zTpr5Azo6tlVUNQD8zEnShe2AqQS+UnetVbvJP5Ofao0lZnRKfngV7hS11cXFum9/6SHiR95WAzXt3dFHom42UfBCjEJP8iXfkjMsrucBGC5yNcuUDfzg9uT6NxKZfeWN+g5teX8MG7RSlHRiBxAmyHgWrgheXi204w3gyGB+PcSaMtbu/O0V90l0upDWRZu9qEC9wWYDOYXPwDHYjSsQdOxX9r3HLpwJ5EcxonkBctJyc5zxLu5xXZ+7l1pncwbtvXMsw9bQPdduNRuoVIO1yWtZ7rRQ0UN+S5XxOiu2sGNgUHzsdvJL9SfWyADuvOu4k1IPHqnMcHUsod6pES4E7GEt8Za7zd/la6pWqyT/BxweqqnkPjStfsNT1OnGHWYy+kTwW7jB64kwHCxSnELqWWmyyqaL9jVd6keRWowdjjEDj4SMcANsMu+B86wq01CMBO4ntD4WdPxTAlv9zjUoX7mFZ+CnF1nVFoCz9O1uAueOnYd4w9bVxB3ZZFOKO5CNNNkotUbqQyYnOXi+6CAl3kmVKrOfn1soGDTrfOtBUp7B+Rgdm1wQNfd71RsCoILQCWzfVGvAMonRxvRa4Qz2bPmw8yJJbwxstYK32hny/iDisvEjHgZC+VDg9zF9EpCSCnKtxyNk+tUESjPRNm5xw85p1K5bg+vqIChvOH8lyqHHJdD0TVsTMPPNpQlpP5jRC+phcLPIpm+EktEhl5JH37fAKw0IcOcgyFrgCMTMosEyR4+K1FwgbhwskjeSF0M8QKaOrFcnaY0haxRziKsLnfxUqtQI/wBazD4rrk8grEFjFQIzDGLrXUPL+WkuHLAoEU/T1PsmzkrXFve7s+AR+N3ca12qI4yKGdO4SYbghlgsbTAAhQk+LD31mG0Y3AMDNEXBhWUPwmNfDepy78jYlhyu3IInlSeNgnXsjWOEHmZhTUYxeg7b4daSeZI7Z45tvjvtnZoKaRV5cM3RD1fdc9uxfkmaLWDkr50x6ERPKKMoXfCyx/kppSn1u0UQVLYaRG3U81mSetzz5SGkURTBcFeQ4emUDwfLXA5p611DlgWgNkgl/UopfIT2KJCtzz79X9CAfFc5oYSKbCMAIsfNfIPIJ7gqH6/Jvyv8MD6ImBE8/k1IIr8964rY6HHyDOfNh2oV7QxKv/iJ2FAJsGbBSrO6bfvCDR/Md1+KBTESxc/6BG+4/FXUpd48pa5Rl6xcRFLYNhYCrpp9ISNRii23IzZj9/kLkjP2Ah7SJ64qb+NWQoWYdd+/+sYI2YdoRQjiv7qQQ7sl8ruL1KcXzI6Y8KFad9ywDl8ks5LTv02mngMZey2Fhh+aGDJX6d3t/pEO4Mf7o0mR7X9AEK8uvHqc2jYyut/Pvq50BjyvxDkx/fTxy9EEAbM03w6ScxOQI+kIXTfWbOgXtuHmv4Hr1X/HkhWIYM6ZpWkAhQzPGGEjrNuIezQR3A+4QMWXCj8mKk/FzUg5T/4iALUQupIHhOzmIShd4HaIaWuDbSyJ3LG0w5Y2KMTZhMRz37KnfM0Fduz+dsT0i9Nfh1DfgBSDPCc6x3J96kAgCjx3HvRjMU+RPgoOUdMcN02p2+THrpzk/NIYvb4Pdavyj93KFdGbNBRGwaOPCCRuzUxesdPaI8LYMVwpDiGNQfVcUZTaSyTBKdbkxjVpqMjagCg7y0WqX7bsuxswUlKpB/e/mbwWgrgIfImhD20nBeYZzw/1AgNPynoLcpEuaF+OBDyL5si7Q+JK4/hnjwmKtu3KZ6I7ysNfCLdXVqDKn7dgb0TRyF//X5Q1/efaIckXAwdCJNu9MtQLPJOqriauEg3RW8+ckMetQPZvRKGzEosUzm0CpGMFD/JBgiOCwCF8NU7159NSeyM42ZTeCp7O4pzAlav6zN4ePfwJG0hTE7lUgcT0ZNy4xuykvklyDeWuvJFGdrI6Bui4ojp+3W/BqqFLC5RBN0uQrfGPX6lW+XNbrHg6V36vknaGGqwdXBneBqTAMjR8uhTxnqxiKUdeqI6Ss1hqmKMtkJTGvvXmBv+WoDopUwe5B/Mwb7cKogxu2/PJI89miVIH9IlWsvtb1aDIF5dcZajPL5aLv92PLrXZ3hmR/qcpYqiGYMBOK8vclqtvbfE71UtAq/Y4Dwq+rKKvBEy/K/ekCUqBSxQfpENT859/eX5/AywEtU9euxTkf4eUip7YNGPg6ZFumHe9tgQmaFv3HB2/279mNoXxFzAIN4mX4NYDyiUFhhF5r9j36LUHLuHTXiw5U5oytx1l+Lxv/9meMeBVgkRHcffrTXub90cNPKlSLc6286gbzmPjJQSbJPYLpo8gTiFt2n6KAD1wGJEUJJGeLSRo2fpuGU9bePGY9FEdQlhi/W2UZ50VymMVO6lRQwQEkht5mnpSzowNJ/nXa8MbBstFv3+PhDPiP0PhJHejcsElmT5EQfvGY8cAygCvkjiQXR4na1qI+cf6ZoD715pbRixJ19SI5RCcNVROEn8VTDPlXLML8hTWuujFnX1QYQYiT7Etk2lFTMtqKabvfnoiJ1i7tq8X0TJbqx97ygCAAX4eFWEHEOQlJqpqeFk0VshBmRGA1PaJ2MpjQVRNlDen+Voyl7+uGQwiwrRwHu3gGA1TJLt6ELYaRFlRG28sgh3nKkf5GTxvVMO6tmgUVzbBJM42VGklAtqV9/czMd5V+brvm+0zuRRC7fyJRurbiXMf2qWQczf5hJIgClBJGKV8ei8uclD8L2Cjti2Es0WxeewN5WzLv2fm4iReBuTIifUSg1+rNsSmYHVnZdxE0IiVahwxyJipE/687hiAm9CqmhjAUT7Oy5ofPMpXLqeQT9rn3bizv/yyDs/Ew0QkJYPT/Ee5N5j5JKufO13fA6PZFY6IdpC3DIBMOKqb60BdPsuLnbWMHhUwfTVcnC9Ze89Z8YYuDcS+5yIz5Te2sMxRe8g2KEnZHwdjJ4WG3odKCtMetLIl/e8jvYWY+9qfmM0VvIXrkH+H8MWI4MpcmGzeMR3SPt2f5GjHh/HTsddBrRHAAW0pNApxkFHIP34N6COTP4lkRoOuaqQRR9HXpvHACY+eUIWn1JpfNpemws1gD3lD/rix9wH8Kz2tzom6Y3LnYIWYgpQ5whw3TSpH5wrix4P4S75Y9wrSsJc4x/moFy5qcaRVlBqnXatgubLGU8zbh7ZNh4qkrIO3OwcAeR+4VqcQo89j7ptzU+QDpPNKnJtBGpDzp40dq9ZLZaqGY9wbXEtABibVuTQ5z2vadkbFu6nPRpiBACNPRugkjx4xEnlKJv9oh80+IVtwRTTZW50Lgh2NQY83THW9TpwjqHvUxZK9/6F1NiZx3yGBSCbWjT6WHsMzkCEQUAnGK/GjYvJzkKV/OjmgEZWWGw69SrBxqLrPNzcUiD5ALIRPIOV9ilLrwBkK0FqxAgLgo9v/6I56EduUVn2wef98KEu7RY8cmYBQwKNAew5hSYKdwqBIjaR9zmDmOce2rVYp34qjGzw5ImAgs7JOskUn+PIQfLPtWh9zwygq2iy59TJEjxyRlLoVpxXb+5NJDw0SlgeTqFI/ASSXgFrUi5mao615kyf3yKQvcwLu2qlbrL/6FnB6YllBKQYr+KveUflgYG6PHmu4BELIQ4h8uSxbqr1bHibu/Xs1cgKZFxOlhvUfI5Jinjdhr5kYXb2GWCEbEHOYsiQ7hFYBPS8MWCAbNM6RbHSFdfm4R6w9H9VpKZxYDzwfiiFes9gQUzI0p9xP0qVi99cyrgA0mZrjBqAatJ+MoR8bMTGYkqNG0MdX8VJ/iwhjtzBZtuHnp5NlE6xGf/ncDphfSOo8Z+ICm0X7nbU+2foh/Arw2brP/U5rFj9j1eFbpuCac92l3hhTQ0ul9tmHZ34eMYu4tGQwbuWalP6E0v9AqRDkJyX6qDwpnpQMUprvSR2ntCflefgbOPGP60A2gCV8+b8xi1hTP1w8SqCD2mCHSZbpSlOp+r63CQiVqZMMBVnZq+kjFedsS4HRxBW1Kv1bQlfG4aU740h555UdamOnvMa8rDoIdz+4X/8nszzMU6teys8dy5VgGI2uS5dsudyhfTctABeGVBRQjr+4N0P46PPXUY5KA/WOfstsF+ja+kwNA/0x9KIFJBZUkpvxQwMZC9YJr+UtEci5feKzWXE67dG5nwwreN5bW8DQwE5BZbsZujQU75jVN/vUirXNyTx9VjqkaVU7wB5r5R3rhmwGSx/6WIiuKEdYykzI3O21/11e5b2G3c4awHcgVEyaq460NY2SwrUH0Ev3vszrQU1oXIxhLYWqehFsOjosMCvdRtfwFXSRBzASHToYm0zZkK/8PDj2ds+buWkrQfGnL1lsTnqVVFqXgCdKwluj/PWNJ6z7wpPWpiIES/ewSD5dfUBA+pGnRPygKN5vUA6Ql/vfLKLmnyhrgRlDctMUkTs2Vv1F4WAmUzIFmTCBtP/RfLf4I500kafXWDG8X/ezTPXvTC+YftE2ajCzuXx8Q2hlD7diqaSIQMgOtnzM6dXRA0B4EUX+TXH0rNXDilmt6Y0qYDdLq74A6lJgeu6NwZLvY/bpZ+LIX3M6fxXtPBafSx+Rhlm/LwszEWB62KRHNFXt46uyeEKl2i5A/8J+9Pe5/XfNsPjBXR0VM+wLyQF/IGpaofy6hapjU1fqIKwp0jEE2ae49iljXIvnX8aK+Aoo6jvkL8TxPlHRY70G6lge6acXzwufNx6R7lYp7T+9ZT2obMel2JohGLDx+BXVNB6h55poEOuN2MUmcVJMmSza08VecxR1vyr1ny0oTBUBj3tIGJSFNxazkS3apGituCfpYp9IvXZOum+LZFOrUhWXq/wtRXZYaMW7ur9SEwd8atC49puCiAlBx+FI4GWGI9GFMTmGKj7X5B3Cs6dG4Wq7V72XkxE61RI7aZfuPStUuxVUAG2V9/P8jxqeJxa6LQSWz/16ati1ucK9Ik7A71jlWPco+perfRhLRd5s/evh0+B9a0FpaD+iyIS77X6EPZF+0jge8FUN631tLKSJRA+reHMNPvNcYzO11aK3Y8moMgrQJTVO4Xdn4rU6HQAL5asyNPvEWe2pg1aznS1HNz4PG83XMOxDmEn1CFGXMJv21baSpVum9B0XUm8j6eBUrWDIlzkBG/1GHHgBpSI4NfrKddmTzVsfu78d2MNmfDxcoRTX3r2L69XXY1Dt0sXI/uztIrdwHINMKD5RdliZT2e6i17Bqu0zsVrp6Mi2I7mLBNGtCmihS5wKsyPDSaNtYe+ptErU/+xUT3hquKP105q4lt3jPjG84fubIcH4vl6WF9ca9xAuQfrUBP0UmL3j9drD7HQNx5HWCM6CA4veBL4oEEXM1TpCFlB62t1DiZ89UwiMwcc+3RFue8dIBWYWIZCNAu8vr9II8uH+7/dqh94QYbkWx4ZuTR+ifLKBNaGbp0+mkKdFXho54pLx0g0p0b2IRNyDImZPE/MiW+CEOqB0JHi76G8IPur3PgyK7ER/uL+jKbD80/aYpG4CFkAytWXFSRjcS4gLM34hzMVa2WZ4px9jZhRUZhyO/tuX0tp1eUg80ec+Ya70k35EuxW9IkUX5FI9sAdolgLrUv/COncAHspa358gef74TAN/3sABtRi6RMZTUJ1gaSErL16gY3ms0rUvu5KO0HKtDWa4Zuema0j+9+6LLeFnNdSQ5B2czqNg4TuNIJ7kGvwb4m1JAHYKmPFFRKtdTlcRJZXI9u9EdfdCRAk3fUrFuft68sHfWdaAnJo7ZKjH0lDLjZRPDLphpzVVz5+zreZqzNJVSrMK3JT74z4cunBznHxq4eOeOViy/D4f50AYzSMrojXajJvDt3Wi5FRYDwxm3A8R3r21ZU5OIguwxhloXmeUiabl064MY+XOuUSgb2hwwPTXjr9HdoRMAHTWK9YDBwyi9BPxQvIc/9Oto35XlutuXgMQ45Xfy+vKbgYGX5mYhRmZWiZEc7vmu9fE/7ywWOc2/8XDo+ZlgP103dOneGXvxWMNc0CKRhxWLUz3jSfKa2nkvXrRW6Gir8Z+7H1AL5r4J6Q05vXRqoGyQT+9sHs4q1p6yc/vnc71DOkkiFYDNBIZMhibSDXjR45Q4Lw/8jeRmbFeTBLYEYm06/7RP+wov0kr5itPy7SKABYj0M/+d8f1LxvOJth2Uhe+EhD9bHhgeZSYRQu74Z8b7142sauZL24a/zhK1353MEflaA1DSEjDovmMbOT6fdTIvTjrgPnV1D662rJdRL/p/F9d8oeVav3mdz6P0s2fvpIo7L7dVd9e7NdBmtLrEDlbUT+Wf6/9JHyQhC6uL3rzTvjEgEAu5vK/ZVwru7PwW1PNkvHpzWCLay5DrD62lnmUcp+EtDgouCtLZSDIGhrgRZ+69xJKe/WWvTic7r82vO76zudGjHNrTSXE9ppkZahbRt/SlDT+pFImSujhQ9ku8Q/cBKexcBtg4jLNJ1F8rhsVYs6/sEPHlPanPJ85lJR1LryLiboU1weuToM15wRkjC095RK8MUzwRN1tHVgd6igJu7BJ26oZVhDXCJNYTEfDWCC/xdMXTJwk9k4B4yJv6SwwuLl8QrpLCELa6RzE9maUaLcpdzaJsE8EPSHAgLskRo7sxuh7GDCkwrwN0lTEYYFxoag657OrdWGZlQ64DVdspELr+6N7/sODsVqkP1EFT+jsYjdw1midM+UscUMuh77ujl7tEwBIMrfAKbaQ9kPr+B2HND1gZtb7P4n8cGYaPpRGAojQltAWY3AmSScBjCbadWY6C+gj4axjeMTpXHfXTfiCUHhOFTGtRCmMUqOxj5kJINBvZfKK5Lt3mt7V+M2xHGEczOIO5C/oBhlQmrz5oz7m+b9weXEmCYxUMClSjjCKgu9vCUBqH5HcvFclPqZLJtfFqr0LO/y8PO/aW8bSRNXGa/MIPbaF7y8agnwrTADKPtVqSJTUXS583uxARa7e3JSEfzIGhAAkkwGVMiVzqcImdKz6/WaxssVUxRtrYPcoLX1NcRWrw0L9+SvvQg4FzyHLnIodZhY8nrr7jVsfZeaGR1BA/PNvafaEV2cWKDePa0HZBRSJb4C0X1v9HJZUXW4si/BqJ1U7gZDpcN3OUbVobkoSGbDOIUk6Byda2WCDWoYn0hBq3NCJpwJAJTFaA4GzpJedqO2o+2jSyvlcBgnVL4RVqKc9lQPOMjOCOFb6LUSjkJVOTm8W476RtWEn0kifqq6ursNEOhqV+7Z/TQRofkX1v1X7AxuFJC8LIO5udSwLGbK99+ICULBZ5Zd5GmrOuYPhvMdoJ5hSBLeMBfzFGWBj9frqQKw7gX8K/1O99vg/ozYkgbg2DHHmjM9Ep9ZYH0LTI1wCoMOTW61HMkIaKBn0lJrsJUOHPoOlGiA7ONMrSADhpF6ApYGImGWQLswQsaLG1G5/s7v5qqUHHyIWJHybEdtTex01jkoMAdUa/wQ9QPJIqXvTaJQyfO20unLspOnypLi6L6++a9vJ7oaXiSLnw8miS7xeLXEBAI3Or+mnT69Mmx14XekdgI/HpbHSU15YU1lfrI7IIlVPG4nYxSwshJZEiC8V2U4aILc4juqSDe5hmO+0Y/S2tgPNxwUTePuXAu3Umh+yE/7SY6BI9WZG8L4ndD7v2OG/1iC24q4otNUJXPMg3GAOyIFjcAKz/qBqxL65ntS/iY6wzyzDMeDq07u7MoOn6W6QSxESjJ8kYGFGDKCgvgePxlApvHFmqOlDieATgvA8NRdlspTNj2J6x+PR4uUtcEHqbFz0WY+fWW1Gunhfk7LSa4+o5QYjTOi6Sv7KDgtxv+jR+CoqlZoDobLTrN492nlaigbQaItAjZ7bH5M5l9w73c0lnmfq6jeWtsKua6OizQuJDHgt+Z8va2pPQd2dgvt0Un92c3/TmQt//VGwOEcZ2OK+UPjcljDSB1sXTkD6EZ3ZzWCs8cYZWhU7eOtgn9EJJacucTM78Cxccz6D1PC4VUGQIQuVHTDt+URnt8v8XnmT/KooNSQmdHIde12oe/93KZQ1eJ/ofQy2r3UDh2wNB3fZj3RGV2Bx0lmeMZpzETR/J7J3LVQ+2kei0NMDFrN6PHxR9bN+glineDsc/ehp9iMCz3t0iOB96SHTP7miqO96kohjuofs9Yxa2Po+bBzrFz5Jz5h2BTdng9MY/0uQzVVFjBOesTS73o7FA73ls6l5O5f3iumT2uMUuD7rINnY7fjlhtOjyfsF6x9CXHfY8dCQYtZV2dEJHU2kIVC2HmVGo9ZxAPUoMcwCjqbyIWCpWyXiLV6ZPQ9P+boFlRbhTiJuOrCcQcHW3EKc9X6oGlTF3GJd8Bf0ydO6ZfGRtV25WUKXZouaedykN/wqc6HFu2ZQTfs/quVAOav++eZv2YHzXaKaj6fJQsm9m94UMwp7v62aLkrScsln7U9Zx6xmeRPb0/0b5+1NgO1lSMDmhkePE7DTdGkhAeH8f772B8ALaud8Iv7h9K8tBRDKHIc4WejCcEsoPjj7akeOFF8IbCmykmxAXXZe5FPStLUFnNzBiP1m6zzrohTWho14VBZ5eOkUHqUtUlFULNM91dIVMOEYsbLFcSbwchzPtpZ9mU2F6MlNJK0Q/nAheyyMN3rd7I1MRnD78M+zyrwfwMcUKxxi4okHnNZpkYrF9tJETM3KipM5eZCxVUPUEo4c/afDtbK7VV6ci/zn9ysMeBXWW4mYlvgBYuOcOV0EMj7+7Cp80ecn6V06HNmi6653FccBYdschiXkgQD1ZVx7ypFVtoT14MaRJSqZYDbS0aJBIoh+TdrZsTk14jVxBB2oWwcEwQXLjGw5Lv7yyzDPqhDiAvt4O5F1ljuD5jhWKar4jxpsKI3FXO9j3pGDl7td7AL6iVfFSTyIc6OEDU7etyC5d1EGz2bitAo75vQYvMJWmhxSm2ReOXozjYiHEmZtR4oHWLnEUk3yefWH8Lm/q74SLVphxdJHO6JfP9jgC2I8NP/Yj75JZC5iEGCKEmF8YUq5kEM3zLrPG583Qy4pHs/ogTgVc8VVc1bAwV1e0JjzZcG8CNRm8SsUeqPS19PcGMd8omeD6CPEYDvoBCoFIw33OozyvTQgFCjiUAjiVf+XahCwZIbKomtlW6Nn1yU7aWhL8P+x1Yl3ad6rPWey0jdiHA/Y9Xv4+Fy3HDxMS/t9IVF4kd3vmnXHcwKTRh9iOapD8FoUK0noM1LOGR4jVqdes5YlvG5dyjfHPFjIU4ijim3502+eGAG6xTEHM3mDDm3aU/deB28xalQhh8zQ9rnqk7atETcAEzkB3y2m0MBu2VvL5WYa1cxAy/YO9PTcnw1CUi76eND+wXmhQ0XTQ0ahY03T0JKoPSqJ2rrHae8TcwJrE0aLnJAuSbpvJPXaGn+XiwUdLKRyCCZJmwewxn4vEJT9niuI8oPAvQ3bWETg+eqnn5pE4ZhyxlsRdhfi63cCFoa71ujMThq39i+ctzex9dErxuyjarMI6icqvfzbJYaND63Uxi//zfS4lZ2oA/HxmB4Zz/VVVdQEpE7LRhmrHWbJRW1tLqcWvyur1gY7WtCIrizKyGMgqZtuUwI2Xgxd6E4VDql3jtfZBcIoZCHFAvVMwj0CxIRjqNAs0SfCSodj9oWMs9AbW6LsbV78ROPSE1d/8IV/QueZjYqw0TgFubX3BJ7Ocnw6I+Jyqbw7XD6sdCSQrT0gbn7EB0iKnkYO8jHoimH/j8tqGARK4bZJVQ6IiZlOQLihCl5+K9f91ews9kEc6zUgXt6P+Xy5/JTul43c8aBK8gNG/h+IX1FdRYtk4S9DAhaopGaq3nfFwXQuP/zwPh7pzn6AG2qljJ+mV3Na2PAV9GQ2xxMQpkCjv12PLUSG/bgeFu5Fs4YX12PSm1EvbUUAc4Lz1KFZW6mCieRl+5hRt5iZpepQj4eYPb+0qV7Uqs5MbEGcuA8tQbhC3m2R2lPTLURDBREHO3qF1BjLB0qvu0cPuS78x8QHD/DqVpQUlJqxSrGoxGbXPK+LgiD5W5D2s7RnFm1d/L3OH57AHY6a1HF1d+NtX//nuDwDN+aeLlUgbPlyBjq6ddbdlU5mNbTnh5fLt3CWE/etvQYal78/twq2XjYvJquZZkmM0Xmk06Y1meeUddwXwfyC2D+B63jDS5nUriU6Nc/k4EspwSeBXRb3Za4aIOqCFPXmSHkDP78xSYFHohQb+Sxthnrg8L1ViM2qbJ/YuvXVwQJnQqlk7PtsCFYLLjDSRTjIEYyVmxib7UQ0ebCdHMuZnd9nZQh0NqpjUv6aenGUehMoIiYSX9M++qWulqkUvgPTZgZpbwVEhMucxZghFe6pao12qL60Hvt216j+dJHWHZ8+hyTjZSCXphcaTyChA0zAq8I9VoMUFaIl0+eqn6BjAMjAm+v/135q4qnMgd0H+AsTdQq1KVFBVcVzx0eM8bAfhZ3V8X+Mj4AJjxNgQbZgr1O+T4OiRTWYkf11GbwJfi2sFd0ebfocdt4uiqlaa9vVCKnuX6o5ym5If7SfYOrasBn6QHjcb06JtDMNV+G36CYUArW8p+3NNl+o3tmYdPnLXjGqoy/qlRFWzinY8xRxZ04Ru7gMsgp62U5dCrhMcLkwhAqAkwCF+6f/eAT8hq6vjPVmNgHHyOTPOZ+pPNWjcESRZOF56wat8wGPajUAgF6nxiruNRFvSv2zoV8OqqTkd87zLqECsjESGLd5edKfkkQ3luQaXA2sBSiE+OBvtDzxUAcZw7mBEcJxsMS/LKkcDJ5WF4zVPw4+nVxUYgktIl7rqgfi5HtNVLoUqBz7iuBfzlzNsWYVZCSQRhKALdXdJWdg6KIwARdP3tw0Bib3snP+9Z6qibkWz7cdUttqBJ5P1KyftUUyFj5FsptgkRb24QfNZsGpFL2ny8aSN5ikdyiX1XzM1saUZZ2falLmuLJTQRS8/WD0GudkS+8J4tUYJHwcG3i5wn8mBvYNsV+2W3FjketN4B60EbzGGnyhJ0CYLkK0vQCSxt7KabbYSMVhUcQEdOxEXwzR+U3qDynJscNZR+oaedzpTl6sw17DOOWkoB0YYwJy5N+PTOwMatWPM7bWlsVIjw0lZIx0kpDBCA9pf28JxhsR2Gts3wPQtu71r9uVb0+K5JCFXTo35+8HD19ajxwwqCgCI28YsJNsOUnrB1ec42/6ytuQKvJj4pf8vA8w3MPCDJm7W1x/2/0/L5/2h7utzhbKvZWnN/iYicSu7SwRzRcqYvitSfNF3UoKWFU8xiMT2b5fSeWPkIsJx031YsHVFUZ6Qpo+UKfzBgGkhTLzaZ7bgNSFTrZDs4Fyt5Cf9TaYlPQIA9YTttVxyVZ5ZRBDDvpMSQnnrVCUm+9vFbKDwVWwn+QQSScAX4QbPhZ4guDtvxfT7D8q2zhmw5o1jmakHdpdvpJsUN4HT4PzvVxkYt7VBk1BdmfO7lG2NeBjKMms8184OLP2tDaDpEuSRlaaBPIYu1Q4LG9pjmsWFc/rU/gfocqzCg/ZmgdTxKQ5EBRFVh4yKFlhX/7tXArCXYjIKY/Dbp7Pmdnd50ySB5PfMFsg+3nqFtcVLy9Rh3EOmKvHY4l8gsd2/iaVWqXL2uKClkP1tPsrZMJVHyZsF8qT6N4ksmiPSAKua2/WYpG1RE7CWY2yz+0uFbAImjuHpKsbIPzv7H5mElENSs8Vshqo3BlxhDGfpWUZcUk7SlInGMOmKYlQpr/S2YEaZPrBtfg2qrU16k1++CH0ZjxiVS697lfxBAxy+N1Lx38NKJw9q+Lsjc+maldeF/UkQujf7wZL/Bj8+7Hhp2hkRdYDikvbYciHkXU2tCm9fWCN7QOWypiHqY8rUrzx/kfrC3WPkUb9PO4uAC8URfZXL5gm547dFuFG0IntI/MGcR+cNdLIf+iVWE4GIRSD696TptxxvcOKtN8rqrt+9y+oz0JebzKH6sCeqzxC7vFbsNfqYT0PNrAsKsGgFdT86KQqwFG5bOayE05JOot8TLQqU4MoivLB4de/fDRzciWyX3OW0YjLIt7pBKNgHdXluwbR0BXtEXUna0vWl3WlTiTTKsFrVjQycLrb1JbSKdqZZkcVQZr+2/uMVXYZWWs6IZaXloM3D7c0CgYsvSvHXhYck7APcJZjk4nMyYC/CIu5EH97vLW+iw8ySu8NtvKNJdlEBSSNjsB9Jr/VQEtBEhoiZmyK6CEWRiU0mFcl+jQ+yPmGNgsR5Q7xRL2BS6ytuyLKm5AcCXpPtLOuvu/qfSiARm3dvu7Xt3+Q27eUHUs0FNl+KfZfLu+QvKw6t9B7IvxLDCuysOYcx7suvSNQnyeVCGc7A4UkVIhMkAatNyF4nquFwRZyIRuuQe4D/n9WOaT1Wgp8Ms8V7pNCW5XkzoXfi1fIrY9LWbzkxYReAyqdDklDrnHiTZad2SaviH0sxI98D9Re4gyPnD4+FlOeyG5vMAM4yTBz4GAxYSzHnGl3j8LcKQXMr9pHiTfxZ3D6KqqJZMBFFXQ1BUgC+q15SUVQMYMBYqeeTJ+M+80z1oYQYxKAYwybu93WP/+z5WYCY1Ct4ewACSgIPYosSHvaweFMUorb31b6/L9lUgfUjgEEpbYlzg50Rbn/9167DBd84PuMp+TbRF+KfcQHCrbMUeW+Yq1paVpJknJX4gSfSn7gSWEdPfImIL30KizqegKvCNWY0ByDgiGEshakCFhy2nsXUQGBQYOnFQDT59poNJnCJIDptMIIkTgtYXFYCwDvlvBLDmOqBOSRXQ2vqKjFIcmwubQkmicNF708FHlp21wuDyqkjY+RLjnIwWuoNTft10HjDe/Gj124Nzg0M5BaQTORYIyBpMMRwCRxN0rxKCu8FWbXGrfceo9U2zBbcTri47VZr+sUkDwHKpGIbGZNweDz9KxX3V+EEBG1SkWhn1H3YbcbZVA9Aw1oJE+1oF36mf9vLyPiR8KJ0kCI0988CQyQ6CXh2CFrOMnbvmCtDr3h8akto6ezNFvQ28w9ucM2q3mj9fE30WlLcaFTnHDVK/lcbINKEiBVBsiK60e0Ep9sPW5HRLcxtWRUb0pqYzEVTFoczS8IA8iM0Ykq6kZ9gkTtlCtNwyxL5sl3qtFNAWGS6KIJbFbEx+O1uTWIIn/vL0IrZM5HANQ67qpwVcr6B4KookqAV2gZ5eE6IquoTYkZ5UZ/Z/DQEZ5IMY8H5/p4W8kudPLY8Nd765oXhoXEAiRpqzb8pzIF2Z+WweLKH0MJ3qG/vvHZJE3ByYkKvTGoOOMwOEokFozQTtY617vM6WQd891Hd+ZrXqnG19cUSh3ihzGYm59RTbNo1h/TKCGjUU0wGZCvatZZnHl19fnlRciQto17UE3O2GCD1LAXg/tgoLHiexsR23yZIzVLkxXFu6+8MxTBPMND8EPazuHEG6UmppLIwsoFDkdESxaiUx9v9jelnvzxfKnXlZZRcKWyxWwaKpSwpbLKbiA/gaV6wYrFnGDdXbrUquDfc1Zovc83ABOPvVKa80/z3u7uiCZ41U3U/3Z5aZB4kmIWVUgVbAlW6UV7oj2x8lcRvVVRLIz3KkqovFgh05SosYT2stOxeDMmCYTMzilEjM4YxbHR1keZq0m7jbnVXqb7+G8387mZV41FZhpgrmdFFnjZ7eqCoFMWKU3DPQSz8z48jDm55dHuUWrUBfNZm9nNG6Q9HT2q7nfBUkevqtqm50JgZaS1uPO7LFjmT8st3gbWcrYjMcV0E8vKm6cnBd99RLz6Y+t5zrz9ZsHj9vxYAx5L96nEvNvi7v4tOMLQY1sNIHh0RU++CklqqsuA/v1k7W66+tBoz6zGAxt35aAzSoCVOD0CbJTriSj2KO+Gd/f3Q8q/cfm0hE0IYUs6LUDR+ZuBrAQJNuOg7Qu2JOrS8GPEVDZ2LBeOrr0oPsFv7ma4MtvciegLEFQ6bL00Qff6cz3abEQP4L19yJPJj7SGCO82P4aO4smG6vbkidm4pzf2GJ4ydN2X+b7sK88Z2eSaU+lUWRzObWiQqqswwaUFLGMID95kOEG77k4icZxe3h05MbjyHzzH/RAVkPDSiIWPjbSsAIOowML/FGMGoyRgqhDAOcQ96EpAQqsiacRghPxpcpwaxGkcQBpZIIDneOWRbrDvkXYyTYBHbP9l6vV3HsHKCXbCYR4zgOBHS73JUN/FouyS3GsJv2nH8+ckDpLRJdwkyyizw+vzk79hVwstBL5G8BibhNB+a70dTZpE9XaCRzNfgagIKvjssQmoCVadKFU80UGNGKzZYQ8YP1UibP0WFJwTdrIZiQo7KbpMO5iKqIVrcmOjy1GuKpXn4ZH1aKBll8tqs8qX96Hmo7IQru1m0pBDhl3j8gvARRvTzgNUbbvjjbzU9BUmDZsMWATEcV8Dl8SLUUkUFznGYwgxg759qDQY998zyTnsV/ghDyINgw95kqxQ/smer04U9npmghAX5NIHptrcC/7x/IIrS/3dEtPdvEUBDu6ftftx5IXO6Df9G29G0p8shacKtWuZ1ne7et/9qEiZJmTaRWOsQJoFlv+j4DEdUs5RWYEfWaqkowCTSmpDIWHZrq1Wo+tv8JLGcm5GFLQZhFTwvkuHoTSMHXsbqKOe17Olz0uCLX/+/ti4FTNWhAeMs2bjtkvFz5iKFlVB+EGySovPd5GR49A/PzhPhQB66yi6Iii7sr5egQ8Jh6uQrubTq/vhlNrh4dW5YZrFZk34aD52XXW9yIFHGclvuU4+LtrPqjT/Ai4Bd18C7t2xXN8XCdxXYg7pcCdIvSUCmepmuG6DTvj0ihKvzmyfsRoKnGKQRD5X9ktGjORGWU2upF1FclgN7HvZCJA/bvT92SPtz7a17VazQWj1BGX/XdLD3iRii/ILjbDdaz5fEsywja1qeY4ir8q8E7jE1J2unmW5awEGlO6k+KCXjVChAqqanDigts5pAz8Sm/t58eabgBPUMvnq+UND7UZbl+M+aV3vIIVAMSgO44BMWY5+azTrDD3e3lUOT13x9tuCH4XHnR93XDbi9z+gbtnIK40QpK7jOJmsj+4harOU9gYsNDsgeALIWaqTw9chn/q69M0w+CEBPakLg+ecpguKA9Q/TstuiPWj6cA2OahqZdepVk+vGkQvMRvWbmOouH9KeuJKLF0e6XhygkTn0mJ+GAOb/gBpwsHp6hhZHp0KIcQSr2FCxilSoLol1c917KiHOJHyVJBPhhRgG/taV2KkOoPuunbPTb4cwgOLMHu9AbduIEne0ThSOK5x4vVwWw8AzvOKPYQGHYAjODD5aJfcUeKmKGT4JdofaEWg0Wir0ezH+bUeiYGcvXUjxKCzyeY8357ZpekghH3Mj7s8sdtfqyLXnj0GsvGvCk48PdIN3c+ByAOUtNBQxnaU1FadT+nRooVUVpcOzhqaWIr4Cij7hJfVxW3c8xzL7x7xwypNLwxsnAEAy4BiaCCMVqR43F65JcSGd5FQdBROKKvKVLgWFUZjTdLxvDcqnTKd4TkFXYXcSL+tDFXYzuOHMOm8im8ox3+g4pqz8qoanGdqlniqaw2qM41YJApuTtlH/m0Yn+Nu78zN/4Jm3uTANVhac0iXqlB1+z6odzSSuernqSHvQwO+JdpRs0I9+Z9Yo5NM3IuJ90Rzkyu42Hf9zLoUytetPvEckg7SMVHmhNx0tZDCZyKIskZU4B9ni9T6UXxPDEYSFfp0BR2EQB1kvowiei8Hxlt/LXosiM14nc2a/EojYwimo09w3CDM0AihA+aCwPQPMGXaxl7COXOof3n73dfpxaXZa2OK4LN8k1K6Dlr4Zl+nlHw2uJ7upf1hTe3bI580Gb3i9lX3HZ1XxXJ6B9pdcip9QADKpFiVuw0SVZAELWosmBBfBKVHOfMrRs/sHTJuD+iootkQeaYvLXx7fJQzTNyQ++OO1zAAaWnNrrWEwH6b+0j4XW6MssSxbRTb4RQFj46mRWs2atcUiXzkGQWTSXaAQOo+JH3IRrJ1oRFpvGXrL/xMzblQKeRFXyeT3R9v9MiEYXUMf+emsQIQGP17ckHZjYfbs4bkgmuTNRIPu5XAQrp9QgsaPawUaUWU1pEn1viiplMmoxa2IAZ3MN1wx4eMUoBIpTYNS9r0DfktkxX+aKX5bDiMN0KxEFs0Johf3aXpPdaKYP7Ffn+M/dvchhW/Di48FtJJzrGYhihmjZWAm8TfgcucL3Em/7+qwlK30gffqF+MBHOO4J0NxzAL2AbUaEWE6UsppVcWqnjs6xocXVRl8c664I4EreHMWUwrMcqGMxpE5jhZdSdyBINGAJZKQ5FmYf86up768hMY9mNPAZVx8V3R66YtR1OkBiRv1rVIap9fxoufcvhzuUpFneMFmLahr71aqXcbE6smw9OojZ8+pMfModSUUstJWHOW+sPG3oVwov4QiKAKYUeyFplmDYfBgam1GrXc0JbrNXNP6owr375gUMVMRwi3hEGFZJFB252HyB8SIUUgjxZ6Y91lSE9e0Pqt4wHK+w0EQOywYShbp+ldI4CraVFGiPYsu0HH22wArKX3fSkncwjYrdsmLLxhjzbJyKahiKuRWKqVIQAw0D6OdP7kldsyv/NJE3ET8DAPWXWZxPj6LnlSAHVTvd9CEr4MA8KyVAJSlkJI2jYOCFUDQJ41M8mQnRolJklsTkcsAsRfTNz2VmGaUD/GNYbZWVDhPliNFWwZ0Mo7FlJ6b0l8kACrs/00bDSka7czQERlhF638r3RXl9OGyWhX1HeJi2OihLkmdqBI+2lfCF+bIG2jvHoSSjSsegrDfpv5FIf6Vt4rXPY/nCDJdSCtLzx6T29/iFbeYrfHqunQTZWpe22v6TTZTiA6qLq1FxmjS0ysPcvEZExekM0dOHnUdMjKJ1i8PcfkdY1dcqKlTrnUpPA3dqVP2QUfUZD739kfWNUUzajclncx78irIQ92ZF0GM/rghwpirrc2sBBgACdPQpJWIbR/10JbUxbyoGdauTTw3PFOLxZPOLAajs6fK5dC+yqMDhSvNNHocOMLnSMK5HyGSDBu9iKt6k8W+G2NbXySWn8nrtULltlb6Cg1qC4VUgewf8+no9BDQI8CmcXEYAz7fJwEku9UvI1d/4c/y5ryKiRchca6iXES5zuPcyAIhBR71aF9pjDiJi5p+kVau5cLSrthiR+VLYQg4pxbfFfHJeKsmyOhnHI0d7wo050XO2sek67s5WmuL7BJF2slPVwn2qsZ6euPMznjvTZvmJceGuz2v9xwb94mYyA5xuNOcBGFV7rA4Lizc1N1Ozh916P4Lx5Cf4aHEHHTu18T14tT+oreOkGZb2w8BUmM4azhc6GdGJd7xZc5F7h+8vZVvBIgmjdYQIBxKZGhlNsBDQaD/crHeJXKsHp4ruT6Gcss5grFS+MfG+XFOQyjQgzTcWQNxuNjzsHOkpWI48AdGNonoAiYfhZyn/ho07vPK7HMu5T4b89Aiap5P6vIRZlfhtMTcZJTVZRAc0jmpBwOr5pP/yZpF38S/PN/pxcSivrqypF1vEKwtPeZpGDPmqtnbrfj9kUW8L86Fy2XXIdXgoR2TJgZylMSaHUS0NwkwtdSWS7ZmalDRxRlYKuHWG32wVcvGJ15L5aVpFvCWFn5dFzcdK6v3kWYKOW7ThvUXroMCoMIT1X6ng7RRBvwbs8C0w/ZNiCjbq/RXd+Fm3zSPQ7+FbECzLs7RHKsp0J8s8WWuymaA92Kz3EEPdIXwNidgdfFHuUX9cpXtObCPfNktYKuTJDoIfkp8fzzXn6+uilvSuc6wwzE2Fy0HXA6R+1D0M7ECFmsZ4FEzySQ16m6JI6taOkX7U/HwraCkt1VzZhpD11YXhwFQsdsp0/L+ySY89Y1xGBheX34CIdv7loJLj5aCIaXa2AshrIDKFlsW8EzblshdroAfV+O6XrQjviWAqZHaoNRuo3xZT7SCuc5yPfZmzm1A6ELuB//KNwKLmb+nwKrew1ibKyp/ajB3o0jOqUJfaccsNEr7GDhA7enCgCWje3sON/z+zPHeOzz/yKPufF2FnMb5zTNK4Wg3JlWpoFrQxBCFLxLc5uzcC5vSGkVfEGBTGiDOYWU14aqT8WtKXp6tk+vzdaHM40+ssWQa4drfSe2JRs5Z4t945b7JiYyYx6XGjgM82Fr0VOkNtIq2XCxQqBB1fw8vBQvp5BUiNkgixhkrDsZTIQgCUdbPcDCk2no0JxzBl03JadeukJrjIPcHcMIZ2vU+I6YcTzrHp67Tec8zwrUobQx0zf1KykYTdMmbENj4ei1K2Tu9kCZRyc8N0ed87VJ9zKzOCtsYbqNJGaIqU3az+Ofpeiy6xVKgHnub0mp44NpRA0qTNBSNS6XXuO21PwSm90jBFJPIEo/18uj3cbajFtwkwvNMi5wMUVLVKJAY5aam3MFTab2HZOnYFX4+5fb61/L+nwtC90WmCsI4zCIGWRqx5RbsbC6x3OaS6ChdHbzl3MsOntANfLEChK6Jfl4YWVssO9frFgdz1ioRG222uYkao2U0/3ziu6LREojot0L4PcxWTUzrmnSRS/S+e+eIvzVBlMgPav6XS/6a+1jmfaaqrEKnlVf3viKlHfVvTuB/l77jw/2ONuXIlIpAeYb7Wx9e0ae6L3bTbn/cocaSkYGG3d+ti/eerkIpFhnUj95ifK4+2P50V/J+K8yVzSpC0ETkJIe3TW2YhRZ5mFF0VaZxbC2m4r3GcmYaznFpRo7n8nFAcm4F9WIDuoQx+ssWW9iGhw4umCgw+xz5zakZpINDXHoKIV47Q5QNMWS5Mr4jLb13lmJ8A+vpp5Trg28W/BfBJjv1zsqIAWpmcfYzN0RhprWJipOhCkfdg+EXOaufKe/TZ9qb5qrJ9R1FuQgb1rsGJMAzfqGhSGsTd5Eppw5MlroSdhIRGcDFN5TiW5HCdWhmG9PhDFk6kh50PUTsC/PIOfuFKuw/5vxSTo2iLbuD8x+I5inI4SPLwQmIuMIyoZLbvw4Xnkqo+vKhiKG2kG7yQFZZyc6AeP489YEcqdoM0YUja+SkB/KMTxuU0EBo8ZdIz8VJ6uw8cYPT10XMN6krl8DotxVl201zJ/zu83u/Iw3zxXr2O68BwUSPtQBxuickHd349tQvKUBcvbmmZZbF5BL6gHRtBGdE25eMAe36SsmYbzhKudukq6CIwoxHnkPeFKYinsurT2W1hKvfpnNsiTOwfl2HYUiamaU0TH3A6ephOSe3Setjjw0F5mbS+hn1wtWcRkKiWEQp6BmPVUmYNifvvIKCJ2H+Q1EQwRdMKyrEM49frxQOXDNTS4eOnvHfKzNvrtruKQ+/Ogd9dEqYvD62vDgUtKqOwJM4DDU2oJ4CwpF8cFGC4AszmO0E2qCLOgGd7sRLkeKdhsWciGOcNuROaSgEhDQ20hb4I2RZIpNgXnWA+9kk0gTLRL2BFqPxUlMSiEISXGIfyXgpSAlhSEsZSAjMpIZofESO3LHTNQTkiuCHuR5V024YzMPRb8ymigQPPd8nsRSuNl+sewo0Vz3NDUX6KNiSryK3zK0nukhxU3bh1bUqUdOBIrhCP0b4Of5AxQHGqobBah6r2ujBWIIn5lbsxnvTwV5dBGVOtAMMU8n/TtEM7/C//sng/ne2/6ZnyyUIPgj2HiBx/+Fjxd51jkka2rh8TKDxoo4yPLUErcf4ouTPKTGDMLF/SS5gOgyMH45XGb6ctyjyGa238ERd1vjZSFCn2MhM3thOL64pPCm0JnNe1m/A84FU8au8WmZDQrXhKMzbkZpMQIjAvBk0EoSNCxV6MQuQSeAZZV93RvYozOePy53bv50/LmoLp0L/Mci5SFKxqR+ujIRptKZvMS6tk8ob1hFScimqSK6zJ35y7TO18SJTghm2hwIqNVodUyDo6jYKPclnHoXNgfvrh5IaFceT3QGxuN4Ky+vL3mTs8+VcGVdyO3zIMTB2D7FYVBcDWuC2b/jnwjjTLJX60dRgiejNue6HZpopBt2R/h7TDLibWfRmqjKaRl1rv3Docvb+B2bn85bQcXvWbvnGOWc/zX6iY4ZqXLk+0sXZyWt56FBDLnBoC/0mkFqBO7t97g5SGXfALIUrmhTAVGbc81eh1b23f3XrtlRxEqovErU1A1vapimJuMFV8C+Vt7jzZ1QNRHrGRWwNIL4TEYTCdzPHYae7wCZhtU9pB/6zUuyRSbAHLSLHbCuChX4ivO/v0fYDyzSWX06TfnfSFa3F2oi7zFnBmboGOCQSjpAJ9uq0cXA8/UOSo/VtIjV6+R1dxz7TBXFk2QrLuQJnBId9Vvc4X4vzdHaKxu/MnuIMRfLxw2CNmbEbzLBnAw4P6l7Ew4RyTgcLihOBJye1LxxBwSFzFfSmsSMaNo63CHGZOi4DrMaYhH7wl+ouhZJYoQNiOO45R0oXI9DbWmoPZd7MGlPak5l4UlZ9DKVsARl9HY16QlIQVCtdBDZeLkdR3KpQ08m0IG+71QDz1ejgItpP3x5vQSonjYJlN28sYaRMBMk5t3310S6ZD0tuXKu4UzDElUXiBhpNF6k0cBvto7xmt/XSfCVgnFIHKlf3Xww0Ph3nxHvZbfyG1TdbKgm2mzeCUr8mg3szqDI+EkXTz37C3O5B+3CHSN6OLPSkTFKsqHceibgJAu1ow/RRQkFI51PfAbsCaRJOqFrYN0pSzJknkBhXdcbXNwQMfnBptDlpq3bprpV/LNDsjRI9aSFzXjD8vDtPLvTX8yhdmYC5eNEuKcOncZSRLFqEyANEJudrSIbZLxTWnN9gJm/gEnLdfWkDmu/iTZC2QYI0GiwsoyAwo14jRRk+hgcqeBL1b1xho9qXLuxmBEwAltSz7IOg9RVWOSrMf35j0L2YkNP+ICV4WskPcmksSQKTdu+FmjCkTKF7CF0zUN9Y5f96IUqyMA5cDuxgyWIgi0xqKrfu6opGIcsitQ1eIoIRVBrDGHabtkkJ7EPyXWY2T1okn5UjyECTnKm+FFmkrgfm3p7W1Tm5zCzH/zaE31MPcV0o8sTJG2A0gpuvJY2ZyvGDBKmCTmGjDo3bH5ZTxVSN5X4+LSTbkmIzE2qncE3cjeKtxFiMtLPg0kZhx7Xydl8eifrv4GW5i4AmhuGtHvL9ZnXm9Ou5U3zwgQYdUMkoQQHKymBo6f+VvOYgYGJ45J+wug3lQd80gvV1ze02TSpp/saMN6SFtRzgZlALzDO57Wk2o8kjpgv6/UTH0H64xHd2GI/j1xfXJAj4YzVHgXbV/+zTwWJzX2qjWkey12v7nywt7vZeyPpUE2hz8q01Tc3jz2v3n7P7T8dUk4w8lVmsHwkNvg1bOm9Ncduq+J2z9FSzwBeEUb1CCvzQE1ZJap1RTBi86JX2xWSzGUYhl/jUPj8cXcbyrrw0r8zF0EI8iJnk1dVC52Loypq8/dwM8WD3dUcHsu7Kzhsiz8mETBnfSNkWFuWM9vtblLdhX1zed8YaGvFsEZH8rCKJ4dObs+GI3sH6Yty7l7PuQY8+kZxBjOfci5sKqreZS+/KcdyQlOXPrHDNqJAZYDLujRr159ufX6q9YXa0hSRKfHI4f8BV2pGTpqs/LsJnuXYTMLhyxLAdFuETnN+dkUN+evNsZrcrILoGArtOLUSl+FHkHKgFReyLkZx1wfq5H+vCBMYVs85+qj+cnyA5VSOp66uD0dFqc8cknp7cYmPDuwVCMDia6J3iQoQwXwTJvp3DZfIdqkjWClbwlKb92zYOVm3rRpZSwlZbdCHm4T6Al64DMCIT2wUM1plHOTokb9rxCUrqhApBe5CG6vhqUzoOG9Ex87QYAszYj+h273WSqPap7ILQpAyLERQDhZTeWIR9icfWBv1NGbKxGUPwJsA+lv0S9Catevme2+Q1W0ba/Lm/69xx7fTdMb0zOsmniYoFPtf1XIbIXWQkJJ7uGGD4ctljGiMcbHqJx326UbvkVp7zEFj+u+YwcwqqNhxuuiPhhLMs1qh9TLOIYIv8Iv5iFbNfzZNdpPZ8hE/5K8C/pa9yLiFnCEk3XVzJzD2/joQc8cfVlJSsr4p8wWBddL/UIozpvQWJJ96cFLdZemLrR9DSX4CJtEml5iUMw7J67zEP9xiuLr7t0QnUu71vyFtIlF9u6EYbxqnW3FbA0p5fSC0tx+qBeYHuy+RONZIhsa2iizFcRtbTpLuChSFsTBnN2iMRCHaSY1BcUk5RXNM87Qi6bmLbnEWhtbuHQI6FzKwjD2t2egRlN4agUqXGw8Tp8LAHf9/ArrjbZy+pU4jOPQFfOSSq4s8N/vDGOm5RFlpZi6mDtglJeSgnjc2BFmYvYAFWy+OOQj/GG7TeIvlv5lQdCN4Olp9cboszGNmZK+wKscxez4RU1dOSTrv9Qv8ln/3MlPydFi2b4eQeYR3p3J3C8gP0r1yu3F7Y634Rhtu8xPXCC99OHoAHGjgUFpcLM2YPwgWjt595sJCjOhtubmBbbd8ThBd6dm+0CRUmRv7+OodKSIANXEauh3GC7B/fXL0RyWidS+AFhcUda1yU8O7hUcpLrA2a/8XJv/BN25aBhKCAFezTdIOKUadJOk750GvPYESKV0I+zC1ha46I124OIpa7ZrL364PAeE9tphgbdgvT+KTKFnuKbISBjvv07XiR1GGzoM9AOM8AOV7/pW3LH8lZc4vTHzHqv8cGnWDKkoSmGDN2K1tw4+jTK0HPB+DtgpWQL7g7udjpnrnTGiUbwqvn0wFc3CgH/rnLWYMSUsmnPkwvzcKnCrtVIuZnhVsXY/rnqEIl0794+G/p52KAsdJgHwyyCdVqN9+XCEu2EXzDPknuuc2jLSuz3n5dk+5u+33hfYLPoCwXjt9kLTbg+jGGxkByhfynM1r9VC/xo/8biIkd2hiWD+wDcQMN12KZLSjgDiPzsE8sRd52Za8X/AXhaCwrsiL5S+agiYSaI/nUGw+itPWVjvHi7IKQlyK8sJieaf0iUgr1NPtAVJOwsY67VbrtYoqhdrNvuvxjz7kYtTGVn0ONZ9yBwUCJjSiVmbINAOWxzpWoxRJxN9AJjT8wFfvSNiKc7GtBNwfX4WoRJk4DBYmk58YEt2IZbaBzSxAj8yNDsFYWRxxLTmM0MU8pUqv8AvLxGbmpF9pVKLgIqMTSJGHevg0fYr155u0wATzazJP0zw22b+0FtKMaBIVDGgSY4EWg5h9D/tmMKMEMajE5hyEOY95JY1pWwlLYUaibAaJcvlgQ0WEzeCntDeNvwvJ7HCBbJadTc1KZvs/GZ9cfBQt6OuUqc4Hc27kWsFWSv2x+2cGiNimuc5dfrDdy4hkIxjJRFhktBpN4JTgSa2Jj5mO7vZ7TZgElFO+xWnpoZRFq1yOr+9rZDzT2tmJ5ewC4if8GRrSrfnpXvazw7jj7nF6JvQI+XR/8X8yIKDeUoNOEUW2aPxwyvwQNLD1zSrhAc821yOQiFE8qzIpsWFWCsl6DJN6dkRDcpQBrZ0Owt/IAuwN7MV+k50ECbBH+pfgDZtcfjPzTbiyANfmfPG52Mmo+uNYKlWK3gQKv5HZA8TgHtsaRqxihS9T+mdprdQn3zxoY3H1s9fcEuJqiHx/oqbjKtJ7QvmPTZVCwJQf2ONswhKnQoPLS9NE1rGVE6pplyMstesnJh69V8kWBhEblatD9FA5lIhnydw7W38MsysnlnvQf69WNOzvt/7S1s3sehFv5DfVAM7PpRo7Ssym1fS/Us8xXQdsEzZEix71+v5mvHPWWFIIKOrbzoYydTlRyzHO6yoLdPxsMwwLd5q4+rgGGsynKlaz+I9oweo4v2+VMGOZwFew2RlvMb8iLxP338iiH/3Pmf5wX9jrJ6C5QUsHFg/8DnqCEkvCHpIwe3I7ne2ovSTdkQ5qfOHZrFdHsCf22PgfGU9oXOYI1h6aLf5tu/yzE+5zwY1NwqQELZ8BlQ6FzSCR27IgoNgzfKPsiyfkGC77t6VjUbn9sJh+p/x/VWErzKaEmIXPfPKN70ZpKlyzby+CtplZVhv90GWPBsfxcDwwXMSmTGtXOCSwYzs0Er8wgM+igUBPvCIbtomGsI9faPKdQYr9kEw4Y2lKjpDpKZjPaAy2dibeCv4/eu+3kOnys75orflXcSuT704aS1eYFA4cihTQLUkjeZJMnkyz1ribODBBpuyV9lckWjXxE68eYKLosdOXFsEqP7dDsLRRKHDeY17qLeuQBZ53O7BcpzK6NXfoJe/bSZveJxlKZuigfbXyyPUdOLzHBTZuVICEslU0jwvyJ0VmfJVlRt3x2hpLQXBemytXUUCHPbA1I6HGoZMLI6Tjmks9KzfwzNPY+sVqUq/73pVbJNkmb+qJ6Q7PSeDTyzcQXuUJ78DgdCwcZeAC+l88UNMqoJY+MaS9kMm9jNBdeKnE/JPOj+gOPd+jkxe//+UxFRl851R7+HZQbxOHAH5sZZ8szf1HCWadoSu3wmTTdCoF4sbuOvSR1vw2bZj7BXwyQS3pbjT95/J/7p0C3ybF/YgwVkZNBoItt0jYv7901oBlBeAwa7vgM4Dns03a0RuKVuBtpuzkZVV4ClrjrxzUWiN1ocvyuNeri05K2zuSm0F9k9381t/3z47P6bBPjbFHHuN1WAPW73GXgDQklxXmPuiIyee4YL3vqKGx1C5AsnWBPjpF0rpowjtoNuf7ZP+8tLZLpLmwOhhnzLFH6VicelULo4VhWliVd9BYC+T1C9HoTxdZBlH6i8m/puiS52+UApfxpzMcHOazdP7iSuzowOkaVlkg79dpBSz3UGpZtLTbKEVN3RJslGG3n2EeXnC9c85ow1arqbDVGbVH35L2CGtC4rni6QP6jKdfVva4kyDzxpNcQMhrCS70MWVZmU1tUB/igNpjhkhl2g6+PiM5LZK5tmRpS5LvVLGqeYRe7pT7/vSbXN0WcVldf8+E45X5/gsgE31nVcSlFI8mg3U9Nd/z+b81dCnviABgmXAkUJ6BRG/JohfElJPnk7mVxNvWZfC6FavLSxGADb0VFXi3J6ndWTJe2U4YoHxgNpFHcDzhXMpDIQNqlmwQMxrYoBEcUfEHSjdgyeN+zPH1bNyMTzfm21ybT2torHU3/OPdaecPFnHruWOjfdcBhB/gZgXGf/mv5xEn6ZyLavjMSmLSRgMnJOXTSO7v9R5uuWKbprkeZTrGz6Jk7V1BJzIW8c4I0g71G2TZfKIaBD4HXmOpZfqf8nc0371ioHzwCJaf5Q3fBGz6kmAUEcBgJpZpdprFmLguyodgPQgAhVAkrwe9wgVTUL+xINQ2Qtpbhq8COYLIcn5P08DltkuyDuPLQ5gSYTPJe0vsemUjrs+poddKYUUFVMi8woxMBCYDEG71PSp/JhPZpu9mErcLQmNkloa4IdT5pqouqvYo2BN5BiJ+tbs3FAJdktg9VCr+T0Ab+bRc848jIArpvFV251mp4/mvHzjBQ0UCAxgqmH2QTtv38lnU6gdmAa+Fs3hDVrxIfXwwtfQQgNZq3YlRiSqFRYib1B26vF5dpo4ZClGDml5wf7zAs86LrF66RnQjVlPtUviAXFuGBTv0L+2zWJJv6+eS5mLB24NkD9QtkgMW4ZX/7MgDLUsMC1mg6G4rZBmoKEdCt+HG5c89qxNaX/VkrcZ51NXrHbFMkrn2/4NHvkMqTl410B/LP7m9fcSv+BYTWbPzrjcYgE3oaESpBrXTCI6P7HrOl+z5FTyH80tYfNQr4SMaNDk1aFOlP0Pxq8JlmsVJQ3plu2vdG/NZ8t87Gk0O0+YXn/W9eKdrP0nuAB9jkeRHIRHUlpJH13+5ZTiOxS5XvVKUoOlmLDz/5UruNzvjD7JdLirOzhX7uzpG6JXMwodf3s8RynZ9k+My5XZyZBwY7EB7x3VVyVlPe17mrCD8D7lyuD0lM23IINpMEAlQ1ER46GkKwL0YKLwPpHI83QE/zrXjoOrzYl/jz0jjkH95pe75c5yQLDttd8lMp5xul83ZNe83rzqQ+uJXwroIaOf93GqnXwq+ZHydbNmW6Y9DBvDA2ovf9CAv0WBKZp/EBeqUGmF4EHRZ9LekLIhaRO3nqlrRG8y5ZFwN7mmwNdNO6XJoQ6uoggOS02vatoiY2AcJCj6chE4LDfFEPtQ8xZxXi/crExQPX/MDwtwS4sFfcRGnxEg6QHEsm5tpgPlrhfQCrhlsZMIzqlPjj2lKOtJAoBh6vLOeEFaw1AxQrHTOIXxrVtlch86vQ8xac3di9ALvelzpD9hcNinfbW87atze8bDq28zDPjF717QFXqAd6OSR+6w+LSdFq2wfHf+sknL4KRAKWRML8nfmcjhLvvtS+P6gvk09tRZz/M8oLeTZpjpq0MSaHIZKW12RlPmJ46RAg8f+rGwCHK4Yse/wh1uR1R0eIOv/XtClcqptqS3ILo/57GtbedTzd+K/tbAikXHSF0PcfDZqjvuBv5nZR2kuyy+FguxsFgjFHQg43C1E45mORPE5133oRKgEWdlWw8b3Qv00It2kVwNqkySs0YrDRbs3zBMJM5g5Ndes8qqdSPYz2Xa8TKTpwA3h4SxxDD38wuMtx3Dfiw4ZSe5H5mVCScKz/9H9q/1tRprtMseXJQtBkZzF8+yRsYJIZ/FhwBf5DBqOjeaDRD4CPsS2eQdBlwQkawWdUPvQ46uQYUCX11/QnfQ5ZQ3y60yciTYEQmMpWESOYz6k2etQ+Q6Nv/OtBaeAtBYWSntouJnyiem5l6L0Dt1PqjCibKEFOhoO3b039E8Fuu4Fthze/Xi46Gjhsnb69+2xZ18UZZ9V8vohS1J2Yu1JTYlgCb3xDJ9rg859EbgLvTMF/lhW4JYxOYZPE/7zvgX4ciJ7hnmFR0QFlakrHAZnSSNdmk+zBguKmwp62qJuVOG49GI1so8mH2yD1rgP+PpIJAHSOOoEBAjvbbqED/vAuejJUz+RFV237l/YaSC986HYU4zNZ1tRwMHk3Fe6QibIUIXeBCaN1KGxaN5x0NUjqljCnDLBA0ilMN8BtIUuV3utI8MVJJ3xFMyPIGosDA9B4ViiY31WdP7DQ/0txsmvhMpAr9+tTlxT2oKMLAknrD3heeRv3VGE+CMvPxfb4TQx/u5shjkYmqx++/Gpj0idX3RG4O5KO4fz8JV8lHn78ajlxwBAb2LK60BbahY6abn/bpZJ5eH5/dvZQsWRdOWjfJGpr4GkxD5E4FymE5wUB/nHx8qCL4VO10Wbzb0QUunmpiVv22D3kwXzfk2i7/zK3aAvLQ3DoWGgBz8TMmhxfZdWF/FIU4stN2B6+djlb1KAKtRBk4Z70LbMDX8KFUzRoMvfek0tGyHJdSgM6D1EG0+9Yi/p7N4m+TH5H3INm9/TRAhrkTIL1BuMqkCBWNI8VpHPsCmfV7IDz87T0W8vNR5VOyuAeZGHjTAcCKGGvAZatBbRq3WZpfgZMj66HkSCRnvYc6ZEVgayRinyM2y/KHFsugn8t++qQN7Y3sekcEke4UE7FPlmfv+qxdJALRmNAAy4xSNj6kIoSQ/zF8op/r9kotvpit6pOWNIDyjpwDGsvH/+jiGgQDZGfbH6RJzXl+taXDWjd3lqxHd1t8Ivo8X/GssBS9/kE9xaoJT5NumqwIrZuZuvlQjV68WVrsL2kX91n9oEvAJofrbhnORuJpusHigayScRposG0N0stoGq9jWJf7Z+cl6Zhf4Obnpk0p6bMZfVxulPJw6lzrfkkU7LE10JwmVUVb6VYO/SkG2XRdLP0kzI6aJIY/IVZbeaeqNa020x1Qa22deBzY3lhDhBwd5Qv7Ef5Y3QjWy58kKwMZo88r9xQfQSW3+L4xMfyyrh6uwMbPagNe5Lgyu2g4JRUzWiCUBAa4X85jHCPzi3H3Newqgc9jNO1mv9ZaPqN4L6wStEvsWALrsluKr9BdlRQBt2/MvTX003K8qLVvpRL5DaRfrL4m+RT4XFFGq2fT6E1jrZgZ8Sy/CrsG6MyCm7DX+Noqs+mIOg0zENkgutPtfr9FeP57ppjuFxD/cZKPVoIAv2hYNOT/TeCg5MZkse/Lr6ETBf+4hRBrCV+gK42Iby9t8w2NddEjMgOa+wacHZllsSo43ivCYEHK9kzjHOQlKiQftZ8V4chfwePlLLVPXrs3jZx32oXQX2OzU+Hd7gGcAyOXSEmrsdE5/+HgPPibY4oiWE9CNkWNS0f6Sv8c+r4AGa7GD8llX6vlfuwI2ETUG9vETHSb8aYACaVVdPzhY7hR5gl9O51csQ4Tl0T6X3aqQpux5luZ4YtCfb2CvMQhswellBKMAvA2FRKKM4PHUkmveTg+yiL6xlfyGV/QVc1+CEuReKjuIi3SkIb2eYuPhejEgE+ARbQHoIopDo+nXSNmJ3gjPsB38DsSZBHmbM376uB0jSDmUt7HbXwZfI5LAzdCzM3OqqtBwG82sLSf4aoFQGNzpsA0GGl0ubo4LIGrFNFYEIH/LHoFclOHMffx3TIHNr95bGeBFpp3Ejlw5UzGsY8v+1gkU9L++F6Xbx+9GfgWMZym5IriNviQYXODQPEnDj0gSBmvjGxXlWXDkIjQQmE3mLbsV6zRHfKIDbfkZXjVflHuuZG754XzxLANHszXL1j9/YxFX/CigAkbfuEXDhS3+ZSW6pYRowRhn8PuU+TeCuynYm8nzfCTtKuQ7E9OprEaMDHMqiVBCs+PtdhY+y5dy4/SYwkMtwxKFP27HqaqKpKFXklfZptkW3LLffCm83nU07kbMXCMVMNPxHLrTlKMbjz9ccFMn9yVHMDcfXvWOwUPFZuu0ZrRPBYYtmsnGBuENzfQbTHVTWuUxoROc/fKWjOYP4ZUA2m6w0IOGTf4PpMiBzu/syaH/0CP4vNFaXOCskomKYjJQnvXbkTaH736cFMuxn8YQvQM5no1MkGnTOO78R9AgQOpeDmDSNhcjp+f+9uFM8LQDtHlpM6nSiL+ZyQwoGp3O3jMxtNJM9qUQlcp2CKKQglRKpTkIk0oXzqK93C+MfW0WCxszmeIlSlvFmiNvdMBNlt7PlVEQljBEuq0N2/B3JszQ7od4drssqSZH1nkr7ED4IjiUoM1vWaDD+R8qSKQVfWt2JCmeh2AnHXT7SlaCY5Ujm4z+XbCjXIu/5fFRSvZzs+ogLUvi7uy6swf79TTs/R/8DqpDdlIlIhTby46+tnN3HooYz1miMj5hE532w16x5agTSB7jYJxkHGBITvYfM2AmvI98qNB6ARsGTJWb6bYJJ3d7nGH4t7C7N5t/SsebeSOhpJP6U/I3Su5CsdrDmQ4in2WlsuEURm+LolQeysR/JbvDNQ1cw91qnYjptdLqRlWEGz1+v9mBFGR02w9QhKc/4d7mEhs1Cp1lTxJXzm/gtTX+kNMa0E851LWjF7nq+yYsDlcYqgwrlhKzM29XTdWF0R6GUYmm5yXZV5CIZ6tv2FoHlPZPnKq4+t98qz+WikyeaQFyiXp1y0tDlF9mWLLyw96nAloAMhhGZAfPH2hmlzYX6me9U31XzVJu1PhbUqJGyVtGe5HGv8eFL0sShciQkQFtyrgQw38tsZyS9WpL1ukJ1ySWaybiCq/kLDGQG4KUSAClRvkLfQMeFmYN+4gJcLqlHzv9CScxFl9liS2mDjK/658NdpxDoBhIk4qGjavpnHD92kD40kou/JQZYnRdD4SiFX/T0M4s+sDmTzQRsrSbesy5PiihWXB3RYiLUS7VSp1aqzfZMKI3bL2rcuiVBIFzy9CbDzx0/7OxfoF93Hy4fo2/a8+VhFNCXV9+zwzsEO3iB6/rlrz+PyhQTGJ2HB5JpGhHoTvA0bwRleuSOWpIj3pYX62ZmEU/KRMOP1kOzcZzDZeYTJmke7cxdxf5vpv2Mr1xcTTeAw+eIK6TWCR3FbK6OJpC2pHjwNmqIkOnOe3yFIUtDy5Rl0GSHvulCQspScKFpJWnMwMgar6gs2iVUh4tqH8Kzed7k4nX4eL7Jd3iHc3t/Aaxq7pkbqjcTFNtKNSIeQRSiIgziArct0SYYmwubFlC3ptIiJRLzCZNGElF7lDv/MaGAF9XV5ORNfxZBvlwFLXoTIG0mzu4Bo9c7VKo5eEf2r6v8ujvd9TKoMZDWhPX6gX6K0CpoOSxStWwYry17ls4dRYr1oDduUkUe30ypqyCaw8PgFWwQezbmIYvqHSNqyy3Y3HWkJSu184uFApEBXwkt22Gg1T1a4uz0jaIJA/kw779yWxRE0mP4bpkm7kVMepAueQBre3QRWnGAM7QzM0B/iTkCaKMGakTjwz5NGXDPaibNdnfG8cTM7wsNdCCosSMN0q1qe3b+RcjntrAAvVu0uPG/kv3MJLXbrdOdAgVLgajcdki8U9BM8XNyCwmZl7unadxOnfe2VsaSoWQX5Gor1U5trnXSC4Pi89ZI3Nv2coW2FlnFLPjvRyjtQ3ukHGLKJmJXonCTE02v9OqV+rYBYizqn7GFu6CJtmIzttla893bkpcZI78z7+gzbSdsATKRZlXDayQmF7iE9MBU8D/dZ3PtQfBr6O5FJvStbBG6u2HJBRRJqbGz4kmZXCvbBcNXBZuLoeSG4zlJ7zb4X1MCh6M1SFxmJVJZAbXeQ51o3TKlzKWUKRtbZHSZ3agko9ZW3guIBkmctZUvzPv341mm0Qzi6b3bvUN/0c2/T/ZCb/7HG2TrbgG2uGXtFuSscRgW1NgNuuhNcC/gP3aSNth0CJKMmq3smFwly3rWRzv4d4T3QZouCRltKMcrzWDrQ4aiEjGfFBFDmH2b+HCASWitUUaA/px7phDt7HBKZjsgqSsDibaxZBCHBZFvDslmahwQOdK3PngUq+hf/xdnYVHucCkWXqlWzjHVUd7PYikndDCnJTkzUXZKi+cvYM5Y4vEzC5o/CyeEiJFC1rJGsClFpJXkKBtVeuiB/FndRC+LuZAWiuH+3hG3gGY6VcqhjnxOEvSQAqMnTx3Q+K6c9NsUSa9r/Zwn61AfP0NenqncM0Tn2QHIEVUKFnBQx5Ay0F3URRpPhddwYaemogFbueFb1hPjdLlOc4XKI+PIsNqdtlFBVmAFy47e+905ZMaq+b0F/XoLv6mP/TGmK1ILOnuNmFqsDXUYilFbKuoN+nR5v/Pg7zjJsADneMkBqmCYrEp9OKdIt0EAlfVfvrx/cStLuXYQGzUSLNEosTJGzgEB8js0tcBYuCNs5DPgLEhPGzrIlIoDDs3b+ctBO7L952cXrBqUSftFwrPCP5/yxYs7AsRqf/9WrHbqURjSGBUONBcMfYeNsDIapLbU8aAWbujZPfkrVi1r9z3+lKG+weOBQnKuLWKRLkIaDJDMBxp/kOCxvHF5j0TQQMjKgxcTU0qPEjyWjmTD1MnkvkBUoLK1n/0MmSMDpaW/0AtLxoa/k3vgYZwcqj1XMiZYsS6pmU+2yZakHP3RR9n+E2T45DWJgQ98x536d08tOL2E+mP5PqOiG7cdiPr9gaY86hL9UdEpQTPi58J6KQBfiwKmcnpWs6PZbGnHk2TCfNb0aPZkfoEXFcyQ2gx3rOWfpQtLJQ+/Xdo1JkHZ0jbkH4tdL0xJH1MV8hJj46/Ru3/BmLEblElWbe1QDntqu+JZa0Cxm+sTWxCCDtskQWswnLS3B8XLa/wGhHVL64BZg6o1Au4EM0Egrr0T1HxN/6PKpBgKW4TslBqzi5+VtclA1HtqF9UsVA+F5I/oqUCComWIfuJEEGpIucAmZJNS/jltX8NNLdAKNPeImXJtPEmlgdI1nT4K4FT+WWEA45YxGJN0g2XJ4pd0utVEXT0i2ZVJJRQuqABfRix5Zn3HBTuPWOSLQs3KpTkXZTIy+lZCml5k5Ny1k5/hKyHvNHnV1GDeMGoO0+zKEPq4x/CRHvFda0y7pRHfDuSOvyq+tfIDol2/sSrzt9kEsuzjbSM7J8DBpD6STJdAm9PS4Vlp1wc3IFYHw4/4BeUKBeFINnIwYYikfVLoiOj0+DfmBUhv7PyM0GunUI+BfDSe5lTuW6CpoqdD9S4j2cRRP57xeSNPP+Vn6Nj1KWk6/nJzWgar2jZ4MSdVPP4eY0fljAx2HZRJiYF4kgzZ8Gma79oVJUOAJJmyKRCV3w45NmPkMYyyBJ7Quds6hd1Zs2U8a7IgOqmBaMHUpKw6QQQ38kc3bCM1+ij7GtyuWp4+LGOCegCGRYGlNZ8PfTFvHSsd+EsmPEIN0ZT3rv3kmaRjQMyg553mdapmyNR7n/x4D4xjmD/bTeRdMugKhCqNgwUqTYJJ2pk6hpcCnSVGSFwmo3xJRW40TGnvfYx6CPLEbZATqJim2bRRPewTE7PM17bpx030czpiFUTmxV5tEg4iOy0L5WSMMVJJO1K5Hn8p2iobBoIVRRUi11BddreJunY/FXLKmGsFvffcxt5KJdDC/WaAtTKgTN4b1ilsxsL5r4xsoJt0Df4HFo/lt+39GLaKBGzUbPiOrfuM7HHlimQgRrq0pgfMZ1SLZqhyRTve9gxn3CWO+O23lFtzBT8P/AEmW4YZ0K90gEMZglCABMIQVrrApfRD5im1gQGU1t2AfN3rIq4YtA3rjw9omiRDEw2P28RpR2Zovz6HFytT/bRWs/oLiCgB07IrdL/pTQOChed2MhtXu0Nqc7yVGVVJgRWt8vaww9Ghff7HqEb8H9+evB8BxsziND+4DhmHOo7/PNTSetyV6Fe+47npRrlp0c2Xj5XOLejqbvbTfv7rFlIYypmyohJ5BCJKNywHpjKyOrEKSNUU6LfoTXokEEgUv0hLtB7waKPg1s79eENOFwkalv1nzdKBqFYxtXXdHKqQlFGJ8Q0nRevqXz3eF2mb/WAkrvavE/+7Cl73Wqq2dnQSnIuiqsJGoxGJGT1v9MAihg8IE6XwHlB8DJTm1zI9lP1eEqwYF1YJsVglRr1oH+GNvIZRloBL2jCuNKu0tGVVlo6s2oLUFAy+Xd5jWd4v8dkbJ6nQL89nJHj+2vStSbOg1HFh0BeGjT6kuPCqz/y0YHpFlfjso733n8t7/yUpjtUsS9/gFQYa/u8oZFML1/jfjV8s99/MYBVCnFQiEsys5oOF9vNaB4fKtCzoz/8te9Lp16AdXR7Kjsu6kvvE3nnwNv7NFgOTFzFIrlHyK5O4rvDuXaWNvIHTf5q+KWeGSKGmbVhoslEZqFoXI0FlbOivIbb1imANknee0rKGqNoxSPCFDDXNwYhCVLuuItpeqHkzOcCMJgwU87rtKZpeVZ4e4+5ENf4PpOhZ2ucDtDXyMFUGSTVrh7gF2bZ9lfBts1chExTvLsZMfgtMQKrJ7kNhTop8udCyPF1jQxpkr/q90vck4cEFlvq/05aF7ci9U1F8xcOQXmLA8qUaqPtE5Lgx0FMlj1Sme0Y0u9dBq4ESSIvmNkFdGfGfNgINBox6QaUthw6EvLoJVz7ndvHCiirYVTcgTgMLPoHHC3ZFN8il6HCgoxYdfX2i0+g2+Ewc0KaU5Uyx4y3L0Z98A7Gcq6Nu5y8+jhZV7FdLz4od6WvHG2Sf0SHb1lYf7nJoDg6GorCifMc0JCQn6joVvQDjcQSYixxdR+W18aBAKxWVUC14vKJHMJIioOfNH4AdvRqX8AES2QH5Ojz3YmIOEvc6KMNNOsLBXHfnGYnatXisgL6pb9SUyM+GbSxWCctyHAq+LKSGTDvam03oCqRsVtU3GdwGWrk7MtfjjmSPoFf3v4KSZj+HIs6u2/uaRDuRjapQY9mK0M1TC24LfmTU16Ttpk1b0kN9UP94dLn8bsR9lF9SiCYng35gxo+Hw2cL4NIO5qaU2OLZ1dM1jcw3dgnEcuMLY1Bun8rfPIh7nVdsy4pOamd/ZdU9gDFpqGSOGMYcRbwYhTliJPsTGapxjGvN+BpkN5pIH2MnvBF8yvx6pebiZxdsUWJA3E9ANyTmUxFnBGQHtUrrVXW9jajY01jQISeo/8UHzrCyUmEIHXro9gKN3muK3Sf1ZQh2qxQ7cFitlATTfH8u2l5SS/TmzZR10eIJhV15wF7KfRfXP5butMF4pR0278mmMiDLAz/e6bf3l19AKcbm8RvfobiYZXLtxQXXLDLelzJtOzi/VeCvfXXr9Tsfr+vW1/gm93z9KWd5F+xPNMBfQn7FT5DY6HSHQeyMelFkbMwIq3NTQmTsE2MqQBKvyEQb2Bp0+DqFBFJXmPxF4a3VGsSxxdF90Q0LRP56FJoKPinQ5IuFaM/tNR+ocDrA4fTDelTjVEF1ukmWWAcZH3BHt6GgB7TJZwaQexxnb9DF0Rtm0uuXvvgxDnDEjFief4WDcnhjO163w8e/b2lcQf2GAAKrHBDzw7APfPXcu4f+P636bvecCyKrwSaPiBekDz2vuM5t7Vsp0EAqld+hzEPXDhEWd8dHHSYut2TLaWnWyhthcKZCLyeb84xkU58HeopMUZGm3+tqsqbJwBXAvLPSwyN3KtPiuGqePB7DvlKuny2qRBKycpwTTvvUkHBvXhtUarDIzrPLyJNGpRKUCE+AZqUZu/UW7Fg8ed7ybVrzSn8f1YKhUqW6IX+gg38kCZ8E6lnV3D6o9wUgEElDugjFfsQsR7XaGc7r/pZxryJCVEiveHdVbFkzv+9jGFL/fPtQ1A/KVLpxmFIpPrLnTCdDigYOu1VGSwmpGbnTRKkZKCn9r0vUOJD1yHdIWfevCa/yMDbEcZF/awDib6AmWHpL9CjJoUkX1gs0rNXFH7D7tDbwwudQFxTdzAcdtS8RbUvXiRR9qqHvlEuO7volDv4magzEArX6I2SQSyf6weo//H3W07Y5JUaljMy7/Sf6zvNG+b7Qc1Ktn6ScDLq/eITP85Kx21rFqJKvWcoD/hWGesnkzfGMYT91ayTtD/1/HkBNobr3laVr80hUkZ65nPkeB9uoayhKT03n1gYCJDdhbmn/M9sjBDV8l5V4LZN/dgl+4LuF/pfQqYo/ZDPMiCEjxDOKhaFlwgh7mQCl+73uIzs3+EfPhFwuPVjnTq1qT39yQ78yebXjXbHWX7hQq9ppc1rskvzkER/8wtTWVdHvccDIHNdZZk2ZZ2NDgW6ViNliGLMVsZhm6Wbs1ig2LLyjDqqGuWuXOfiJ5xzSePSb9xQkz4m2E+mj8Kz2FfuqDnAT6JEDHqzhdzDqCHuAh8rqAHPVof3bsQfPhtAqHwdawvTpkymZK4pRVwYuglFm6eEN/93TC4oxLY+hOuMxawwUyBWgVYjRmFDCS1AYvyBT1W5gMD7oPVNBpZX4XNobqxlCDITGVUIzJ45JHaOI2qNl9tw1YkHoapil/L4jS6L7LCDYFIJYYiUK2iLoJa//mKFB39Q5cD23nvv/mH46Yu3KVqs+1Eg/sZjeM2XTqTgGc5y8s8GFFDyp+D8CrBYyPWbJwUldla0G4CEBDFZb9+eTTxlH5CM45lJyl3eZ7y26kukj117canDOiOOHfEnppyhdvmOW2D+/rg+n97GWKHMh9/6Cv/ffgbygSWlOGtJKGelXMwsivKAsJgGbE2DbQfzmNBiBstZeZUuK/dbih6HCl5Mt6ftAL2Lh6StaDDt0zWefZ25KoDPG/52TqvFy29q015hE77bivnZgZWQDUMSSVosghejbig8ju8qCyRxo1gsdKcXLS2uUAkeK1UroYRLsBYMmgapC00wQVJqu+kO4NldKh2SBUur0Qg2KSag6FBwJCNSckcHvMSQO5zjMTkLSTNzal+FvgAekSV/jPjlsYu8noOfSEXWM+ZURF5X9NM+8nBfZtDElMXVKMOTOHgkdsKzyzLWmxZQSp7+6cG1cPIN1vq1gb1+8ux+glWsEaiuyW4I0aEKTndotDdM9vz8VVUHi2YFWFN6Uk4oK7trbkD/Ld1FqzFmE/CLpd4by7fvfPmZn2HJmj7x/LU63KRXieIiF11Ex6MTBEYdJHnBVjTBWnCyKZbIyGMfkiEY/mterUSS17exyX6CXoRqBiJaHfDN2l0CfUbH5wEoiaAfEz0LW2GQkcAMmtEbBY82rHTl/7TOHfeT/sqgVeczVl4F6TegXCLi9FCBidkImaKAZcbGshaVOMNTWyDwPScnZQ2POknWv2Q1muEg7kSSGMY/309dvUJZZ0FDuP1XB7qO4fGQfwdqxZNXO/WZCEPzoHxkaW5g8uO+MMwfYSTxHzCvedc/T3NUIRnFrqs+w173M8H2roPCrhvkdNJmkyJeGpKc7KDqh654kO2V+W2EMlkqcUxP9ZQFVWCYj4wKJe2vuxKgj8n4CbsFEMXfkvwp1yUQeDGNQC2Z76RVCvdA4hut5YhqyeJqwqwpH0qjkSZAPZn5YqqsvUcK/+5Hob1texVoKF8rm/TRDF5KKIAIV1C5qlOVcdPwupGNtHYlXYs3Dj+pQGAxNn594IPojtj9/+XL1mPmwemgMzXeFp+9MGHa3Qva8aVf2oO7/T5nrJlYE7zqRIpTiwWe8s5sdwRYj3kx3dSc6f8SBb6X+V2qsMR8Z+zIfVv9/fxzPdUQoFTX6606Rmh8JAwyHe/KQiy7tAk8LAzefJP0QJmq2U/v9JmDuJPkAolkR1mF6V4qm3Em8xQ+Vtlh47ozoFmfKCBNhKTmF49UpkoqZ6ZZtYKilFfsCKN51l9xOxiA4rAUvQ6GZDt9MYsYXlASvbsWuw4r0U4ArCWMEGOYu/8sbEOU20C52zMWVB9+PWxIEouItLvLY+3eoWk2MdS7KbHzAEK6M0zSdppI63PybFLPFZEzzB4HU5C1t5GyNn4tzw3I19ZqFeIoqUjGeffBpPU1QNFpKsrak+ScBPGdLIE2mH2cp3WK/Bapj5YGha3+wqgNMuixDXqP5CSjsY0wzRg0imo8c40PY/3A50jYsBEUWl9QFlmmNfy85lIY73jmw764nPLn/U6Yu6kHS9EiKhXtEBJdP8zB8gqjD2Q9xeLdatFlTfrf54CgwDEWRLrwPheanatvgKuJdPw+1YaqLBk3GhCEBavU1lR3N2THqO2ZRPe9eUYn7XLX/iBfGWxlihWBLbWfF0tAQakmhjw8YkI61MuzqUl1DbsW5G35qJZNyeIIQdLXdvjRvGGyK3SbfNSXJajtg4KtJySvNVKkFan2OQWMlLHnrpq1ovkXWWgs3wh5nFN0pebk+WtfyUnkzGA6liJ6vnrmG5Wlc00Wi/JlpxqkzKS1s7ZS/+C6mEzNC0LAoE5IJx5gJeyaq/uSrS79rSJ/5SuXve5tnBw/Z1/ncZi7wo37a5ZwhJd7VHgdLVDuzv27Z4tfgp3OG32oeHF+yy6859fs0SgGRGF8tR7PtpDD9DtEzxR+yihj2jbMhxkzqMXHy6cosBc1DoSmYMoeiqgqmNFOAKyeFTuj8Ej+vy0nqcnh/m+vKPl1oqf+UqVnsGG9WaM4Ro1wjTcAm9E81Uw7ITAKXN3dSfHWnNFSm1BjSG4IT2Mm9XkHzP7Gz6twaI1SQiLn9GM0GkCOmYmZpxu4clr26G1xf+nfOsL37/Rwbo3XmvjsGu81Dqw/zaS6ZWFD8yRZayXyvqc+XgQ6kB7OFi/b8LdG3n+smIL5YwlIzPUEzutz7KYKa8rFbwbmWiCqk1nUTbf+NfrYI2NCGXwtEmalSsOPUPDjArv20i2t0VhJf/xsnOHD6eqlqpacx9yh91N5fYfvOyH1coFRGtaxFz03Y5rVErFCYZHclzQuA+VP1kK6cp5Djo4Ky+EMMr6dzjNWjL2ZX/Qg56cOMg5PaAjA1PP+r40p7HRp4QOTiP8P8UHaNDWkwgXF2ukj2x98Qzdrbitq54aJfam7WyhXZpahrVp0Hjlw003AVwFxkH4cgm2kUtypdqGXvjXzvm0rQ7SL7KfBYYlRATTQ/OaALhAoJLNRmQaWwTCsbBWcHnVeGSEsIsqyQk4oK2I4DTOMgY+IcGMed/ZMli4DylfkqtNQf5l1t+BCKNpsN2xyGVQ/1rKcvKGujnvEKRKbRh0+u8+9G71toB9KUTtAkex/CrHqaOungER1TCVF2rRqUVAoeoZy8Xln4DSbSCyp1VVzKN3pphagP5KYtEGARipBZGYVl5LFAdwvyIuvKMCyc0gjUpEkzTRRQjRN6n3KhB14ME7vCzQJcAxVzirmQNNRXjMmA15isOQu60M9mLaxeXKuPrPbhZwuzBFltqIDJG5uIK8JIN5J00gJ6+9zLLTVxuBUG+ZsbrNrgvxkj+lmW9cWIrAuzuBvXIGGFDaVMimFMK2KTzobpyJtQtaCs1e+fOPax0VjFGnlKaEQclbQYgcrDoL20qTAuxWf3nr29TxW9hywy94CjihxL0Xue0tsx9ofszO9beuXIL99UKa0AlfAj7f0rVW8JKvc1PShG8zZoiFs8m0mX/os15JW5lH3RzpkVwB2ALkUi+LdTDz6b7e4F8D2lzI/U4m6lH2tvJlZhXJKW1Ex0Ciu4dlHlAqcS0jUIqk+OZN/JqzcfGL93TK3rSaL07pProd77+oA2hJIsZGmMxrAZZaLBcuIRm/nPytRPPeqLHrfnw8j6oZEawKG4iBEaoSlI6Re/If+lFBBRxG5AAziHvHr1ncusNYTW0395WTka5fEwGgZLu4ajblFI7ZzqcztN8el5Sh6vUBW8dGMDu4InhTNglEvt9xCGmg9NUjM6ACOk2O5kH5uqzuYN/Y80IT7byPlowlg6OPyceQD8y/aNq3NQKGncvxnO8mlRvdn4UXKY8edWRg+Q7pD1xwjjWbBWkV1WMOq3KptIyISXzb66xlhIcmLyIjD7zWi2gY1H3m8Eo3ShVQDaVqtR5CZHqZ5igmLtX8mW3K8xUVtuVfRcml7HNVqwfK4G1Dmdp/76ovCy9zXsGfb9qFxoe2jGPo/i1MX43MxyEYWDp4v2ajj9V1OMx7PUBtRnp/EOGhUmJ+lA5AxMkY7GYjztD7+yAzf21XSyZnuX7EMPB6spDYnPLz7j7rp55beAe6ByK491l0jZcVKetJXh74EWz4caxaeUfXrgAdAMfl3WVfOrlNFgWpIuSEvToBxphs4Qvn0rI4ZB2d/W1v3E3ny9nznLRlxL7OZRhrOvFh7aNwQI6u0KnyAkTKYAhdz4vesexfTHKybLLoSJuk7/741ddNw2f+7W95nF3j+PLABVeJ0FW/5ItuKvQVfpMGDzK5S5sR3tT5fm5rb/sVyo71MA1wF1Y+91LydYxh8x1DzURf4nSofd8U9Es+cPoFnAhKLokyrclrk8XKfLWsyvwJvLnkhJUxDn+zbqsLbVWK9tNxo08gbv3noiEwqBTEOXp9KFgjJ7GP7sBPPG+RXeocHlXiGrwZNaigSj//dndVzwPvW0ybnAMnw4WTHkHh9LdOHKslKmJnuNKIeWJapG2j5QBOV/bZ39JunnfaxB964UuuhBHfC4TUk6ZyIY06iGWZr1M3+aptFJOoGNINPycsVtjgBjEYrFFnwDcqackJe9DQuWNyMf9qucLHT3UcdqPmy4o9dnH6TNg0aAnGSYM2TC2NYf5upWGNUs5zLybJAl3iAQ3Y6Q/IwQ+GCZ8Fsi4/JH1vKnBBpKuIcRHjZ8FGq3hu2GH40MB0KYgiD0QDlrTgDYLIfXQo/NuBDjZFsEW2XLPzJOnUnPhK/kDZe3AeEMJXVZg+20scJEIk1nwiDYkymiey3kytPnCTHJBD0DNZhNdAtrNuPNDLb0YTwm95JyqX27rBtoHtcJlw+rW3JmSDVjwCuzTa2/jy+K24M06AhC0J6E7fuoXvbb1F6OO2rzyVsAL9LNkE5E9vMhsJyGiyGgP0Bp18lEu9QCu6dFTg40MEYJqIHrecVoRMGiJijn02AdYAk5JePL/VQcS7CJyZape/31u4nhPrYv2SfuA3Xw0SOQ6wKXMqVVgFNyQXa7LpKrJ1jrFcr8D0W8V6liDXXZifF6JXLouBvACNRZm1o2aVxabuBPyvxYuP31BYWO8Hjyl4CGQqlERyLQmZD/9JG52tWQZ92FFp4YOUAtnkh5pYPHusKckiI5LAtZtSjXEFiOLM25Hpq1U1AFvhCJ3qOzpZf0/3dStWDY3xCB/KYUyQ5pJ9ebV1RBbb3o0wVWAURFG4dWZ6uxO3bpZ4TFoAMtzTG9J+RUVWI1CtLfaqDp8TKONWKWzX1pgckaMckmkj8t78Fkr4yyhJLiwGuQWpH+j9d4+4pbMOiFxPZwjI2lYuIYGMWQCBfKXN8WyZk//k+O9a9w//hTHiOp0ajJYe8ermY+QaQkX+bxiO31ov26OIz74ygOBhgu65uIgcin5w2GzGKudpCbxjtiiZo/vpls9wK/oiiJkuRcE7298zfNaFpzoADCTi+hIoHSL/TxEOyiROKcdet5pj44OCKb2moifr78R451a+pc/VPwMRDDIu+HjPk2MSg0GVrjuJdzeKkXNDQ2dBIXdIh6wvkD71icrquwkWTiH8omgAlw9mmAC6DNnMn0mBJT8FWhnrMNjtFNWnilr19XzJDxDCP2Re0JtlOy3XmHmumGDm3vyhMPO7DQGfzhEPBer75D75MDeD6aJZVklI/uyldFlb8I5L0hYGKm+v/aSaETO7HWI6K9FQUY8A6S097JRUOWaqImhwBlfRNcCqP0HsR2CFRQzbRFtq/OMUK1zNAoCCq+jftOvOQgfbvcDn4p/FXDFVnhYwTWpDGpu8uL/0VU5X3MQ/VcSHEDsTotBqkAGrr6U49htHHhFIG2yLDonYt51ryyrFv34NKJC7fTgQMCTmx2bKbcqRYt+xkvBMEHPjEBu1G96CWxby9Q0tKnxmEvMjl8htb1CrawvQFXmBX7FvN77ktkHvBmus1YaQ/k923qbCw2/kUlkckgbeIlBq0tlYv3/Xic7BX92HBk9ubO7841JmSiCwz6t2gLgblugG/hszHPnS9Rdgj+YbcW6EWI41zc2ISug4IgBsWyYU4wkaIbIxMJjR50gTabbY3bvoAkNYGBf6MeDRotubi49Gzap+M/GNMbqxvk/HpSiH2XJNM8FVc9US7pGl2+uUNN9y+h+cOzhMXHFV8Kvyk0+xWfN96d4YFGwIg25CfO5QFGK/I5kD9LWfNy1zVp/NbEwrP0KFuEDWeea25C/KFeUQFx0uVD0RSlMIHYPFUKW2SWQLd6fYGZpLnaEVYYmPjf7KekNo2Fq24lXp7KzOLDkHtawYqmBnvuLczRYlwpnl+fD7qIQEuOk9dcJUWPUjBrmc+n1xOBJaxf8Tx7HfTmzxHVr8EaAuk393Fo6LXkr9OldH4f7aASKGiV1gSnuboTFeb7npEZ31SmMc+42r3Qjhv/uFNtIgr23+tOh4KxIKBQwuyOwkNz4Cgsi6U1GiJa9HeXlPicKDJf8Gl2cOqeHxxznwRNsSZ0AEbG4oSUsQhPeizNcH/DjaAFTytpndWFtb8rkIE8yurLlLAgTCcFXJeHXKIydR84DzgvCKUWDbAt4AEr8LQIOjImvmECoZwNnV0RC8BRKJ6XQLHLpO73yDzN5XmYZmeolrDP5KtZ45emzsTui8CLv1JqwdRyptUS9lXEVcidzjyhzbASO5yTU23wvEhTbfabxvXGpgbq6uUsb1kwZ/1uW+dkxs5VVlnMQwjWhF1polQG+VkTAmkTdCGzZiBYZQqfoikJzMIQqnnIVLax8MAUkbVPc5NDNAIZmkEORcTe0xDBAUTUoBbbLPYWdG2yNK6UDXZokcMUZmHBgQl/2uLGVkyuzEQeS9pHwhIawdp6u6S7RlD+o04bEjKejHVjRpXOQKqbr9u18rB9iXbuU629+fm1553eZs4uuAMZwIyR5Rn1/Or7SkANbq1ZVNR7Z/XaPcGh2cBl8VFfjGk0sSIAVWMsSIMWw+JVK7agrwSLtQsfz7799rF6fevWYt6qxxmnMoFfN2g+6BTFVmC+M64gP1VffTQKta/xXNvCeJxFtE4a45gJ6ij9XCDxaswnhr0prA/OOUz6/0a2WAVu+6yucJrFh6UDhFxHguFL4DChgOR1ilKGKBM6qua+OMRJLVV6Br7aRc68ZZF33GAlayll1pRMCpG2yybzC0nOYJLAd71MeBfbEZTOoqouSfVAbdnuxnJMS2Co0dgV0acvy70Cxusv3QWWUJJk5004gLVDH51g5TjOfg7UcwWuQMM0bEgs1wCVKpzK/VRlHYW8nd92BA+6yn4Q9hzMsnlMIwLON355aodK3wIE2cHvndUZw9eWvwja4Hj83dupt0vh3sZB6NH8/l//yEA/FHypz7kXi0OfbiT41nW3h4vvPtbc2lRss7Z5aPHc4p36R3SFBlUbE3L0Ph90wuR5K3Pd4wt/zJDx1rNqJtKK/MevtMRoqX/+z2jE1AY0eIfsibJ1RWRzjg1psWxpO2T0upaaa8N4LfIOqOMmrSdznzjCGXfm+YIWU8m4zwiRma0NgvsfRtkaXmif175xKuJzeruK6TcO7u4z72+fd4EcSwzW+zx3edfbGqfCU15Zb8zhyU4MIpoS4krkNhhUwqZdXzJQFHFaiFddopr8raY0/d2VsHbDSZSNhC3Eqy9RrX/tJLVxJMOvZsBPUYAXvAENNL9rvSPpgH7q5E82gwcIXt4DOrTu8nf20iXpFdobuAoudHniIXL/9tf9bxLy4N3Fge6+ZJJcNngzxXsW3QhdJd6G46Lcx4GkjAqC5oww5V1WsL5KHWDcv9mi4JK5+YU/Sg9kFKig6tK571uRA93oZw0kJzWiAAYSLDGA8c8+nfGZYK6TrXLMqliHKoVOQ3BYn+qUlB4NqfVlUOmVztqhtilaBecraEbK+RYdbcTmPyaeZqnT3wVYl7Qvhgwkq8PkD6w04fgpMhFdyoPpWrnvmQOafEK8E07Vw5g+GeUYshKU9CaY0jnQwVL2Qt4xmIB9/0EAu4+85Tf5by+P7hM5QX7emAPYNFjkUjTFtcJr2EguRENcen9jMfMqeJthxIjqs6OdniST9Ho+IEwrezBZwXHGhXNY1WeXagTMOt+71Db9i4MCH9R5kh8ojLv8oxxd+3gTBH7EmMgp09NQ6BfgBVE6t9xn859wivCTZIecH4Z55KO75gRcu1qPM8lyE4O5vEF5TMfweQsJoc5oSVHy1i+ZyP+3SIXJ/72xaEWULAqMun2fGjXgtn+MoMXs75PeuVFMZF5aIQpl4sUhsHaiDVW/gkvDsPOwy7qVcFPPleXHBJCf1LhB7GF/iWoF6iEEm0HdFt6h6TmjGi3wd6DnhrBBAIu2RJ5qA3vOBd6Mhz7wpa94Jmd4NP1WZ4ZIeTsPS56WiQgtrrAB91XHeHTgphw1e8J3bdWC8XRF1wJVuSfyagUICrPQIncibhKSUjM6BHnxgRufLxCnVaP6Iy+3vPeMJBb6qtB6TGoD+4QGcaaz4DY8NnhXHLVH8JJAsikwhMS2sNbvoGOZwO2ZfzjPBQeSdfF79fwKxG3qV25Kkw2klij+7NifOXSOuS0m+XvrOVQyAz7A9zmYASOhiQlDZSVUD+YO7moBs6btDS7C1EyGSuxvJ3z9jfeaTJ/dy3xgmQ6q7mPZISr6jGCatNRolg8rQmVSMKzflgUSKVhORBoh66rQe/EX9KaecfPZy5CSNMgD7qTYjEq3RnbCzOXeM+KrfIrOXn1kxPF3RejdZNWunZQscG7oIgm6J74PBaXwrKBW4GBabNVG5dowowm7vESkqsxaVxvmXhAssHHUtFnxkxkVT02LfkSylBsts5dezvU1UQZeynw6fJHZCK4EhLASherz4WX1MkNgYMarhNkwt+K1LZP/0QWO4SCNJ+TrfbKRV2oQhObJV9/gwF5KEgmrpMiXz7SbVidcgXFc449CNAIWYQHWPNy9bezPrjvm7zmvXufAFCwlkr3aH3vjhm3Ju7VUHrHHv37BSXJYt4yjmP/tn7256oAlO7Qi5CXdAOBK7sLLvTDCilDkwxB2OXhH3sEcW/EYnh+D9S8n3xa/++Entvd7m4H0UBApYzVQNyj6CCh8VE3yD2FyBgXqLfyQPCNfVlg2NdqnoCik9wcrGwlXTUsf7RemswPhluyDbFEk1+O8iWgX/aoq1Ovz1Ox61demUcgYLq+VeSfYcX6m/B0d6FlccBY+zxYZfYc6LpiLVY643PA6lAZw0EC5Ci/v/2wLh9hYEMNJH+Y7cUaJgoVkG8hKmCSM8Q5nhcMLl4no0bRZgjzOyYlPBsKVO0PMDTfW8yAhma8fxDVWsl4aZp3ABX0LDIIBeAISn4zo3SR+LKTn+JlMzjt5nHm5J8EmHPIqTOA8BsBqeFcc476Ztem/uyuxBpp+cFIDAfL/a5kPnVQJu9efINsdl4eSumpQU3q1uzvLppafG5EVoTmdAi1gmVTAPeHleFssgzRMSo96w3RSMOW6f6AffV/9r7+2PrtwBOzEsQjmMNKy3jQ/5TT2tVTffNQqVlwAHg/cIeqc8F+529CPuJ2XZYc98u51MMcRxUmBKk9AEwA0tbAkiCiNdrilbgWuvcmnvGln+d3Ky+90HxkDvtTpp8lUkoi7FF5J8HZ+NE6WQehyXlWbXmS2xcyKeajQkw37CYqwNbwPRg4dpuzmP455PnhJLnbJvGPBru+OZDlALC1uJyBMLdgrbTpFXafIvP+BCEHTg73Y5gBhS//adObymqDuSWzCZNKo5kFPz4dMNspNTgRsNa8k9lijKjqOLC+8UAwexKlYik3lVh2I1eWP+1Acc5aooatRwW0Al1Djg9EJTqO9TVfReHf0KcUMBn/0H7/OZC3SMV18NyPnHJpBBYYBqjtkZ4cflibZCO52kUrzmlxwmnRzlvwulPhUXiUUu2hjW9TaNB2TPAQ12RgpyRRmitOLoI64cyvm6+FW1HJO7CnO0DyokEPouyXs0st1mmif7XxHFJK5DfufQLCMJReoOTucCC36rx1AOhHQFKqysDQ7T+99arO3fbuOLr00PuwGomejQFanKxAX2m00Dcm20A9CFU+oEuQLNrBZ1c5FKvqbHezcRuTkm6Hl3MSJ4A5fmL0k75L7LgOikY/1IgCTdq7VQirVoIQCk1GNHYeFlYVKkxonvtewM0EGmiVW+sFLYdpmOAdVz9RsPIz/MVnw/BTrmltCKd8sUZ/XAXIS0P6IPxQKVFBb3JEnvS67F0FV7r5XxOOW7jac3U5Q6sE5mHEPyRA2xfCRsR3ZR3UHoiY5UaBr2aVbooFkmTijGeGHFF3yu6AAjY7N+np+Xjb2Fgt0H1qeci+25Ee4/xdSK4QcVpai5I60Hexhz21kRasipa4x93d1ovSKAbdCRM2mQeG/6M7xVd7ayUpDGCTOKIQFcMwM/bkt3q0SfnWPdJqLoMNUogdemQ8/JePZqmHbGlGR5CfNrEtLG5Os6ALu0UHKjXnm3iUqeAVUrticHjUKU3IoalIkIo6khSrz1RqBx6mHry/VNZkXkP08dvSdboB22Jlzri43tO0qU+gayIvil2HewPfDZJac0ZjkJajRgVIvA0ZsLmkEfXlXyyo7HSPQTxiUHyQi5srIVSu0nVsSZHPHUnwf4p56h17sjdvwP1Fh0kLzxX34yEsmfRLOABqLbA1Q524WLV8azJhwz9TLB6Dtyg0OywsfT6T/8WhpxhioV4jiOdgi+KjPtAjiPDdgAj8B9HOAIyVtxTQ1A6YorRJINTvDI5xT3aI6FuQZX8f7yuFvaci2XT/XGtK5wAHBIliFkDoRBkjTYkiMBkEzciuRVGkJTaMBkBrWAiVO7XTEJwYlDnYg5DzSupIs6Xax9AWzHyDim+MyT8eBcUsqhwmVkL0yYHNkxGu3NIGfOmzK9tJUrIdp9tDukpijaUXEazvqw34Yp+alKwrYizS55n8owdaTGBX4L1k/ks2eDOrx/842VvRjiW5qCKx4cL/RNFAC9GnF7OrVajnE3+FAodvuSKzvURy4uNGef27MB7/xXFLTaz9GoAivGIu1Quf4lM38SuT8WQdHxmDNTL6Q7OrOk/pnr8eIXl8edUqU43WHnQ5lkffMVD/pVfjvGMem71efqkB31ElnVxnXvSgnnbGuul2M/5YfLL3w4UIHKAKmyONYVl2MG4YsTHfOzbvfQLINP6373yaR9BjRn6MmPrTh0yRDVrc7zSd6gb8IPljtJ5k3BjO/MHgLuljGjnqIQ/4iKgaLsAgWKOHiAclU2KhPaIrgaZrmWtFNMI6x0CSXGgvTUmC+wT0lw6pa9ger5Dhh2i9HcQw6kdCz1IBEoOQAvAqp0ibxFm9u1OM+7OGtN6Iky0FOYELj5sviUhFlDhdggWPdoovJKiU8/Mkbi3yrNI027n7ixdhxRG/Cwbx1Yo/waJ1MZY/3aBj0yDY1eUWBV28KnnFcY7fcwvy/bnZlDnlzjfmcSfvrvNyEs0CLNF16+aSziKUMHyPJhrrs9Ten/YtJ1jl2hWBctYeNCVDJWiix20knY0UlOxcVG2wXp+JMzIVX68AQY5y6Ewk6BB1iM00Yi+QkAU5RcRBRxVUCFZxdJo6t2ct9YKqyWKgx/2dyEs0ryJh/tegq7XV3xVJEh0znV2vQ+qxjyrfrycBBTAnZ1+lgvOjtMI0nMy1E60sZ5WN0Ecl17c35K+FKMAiB+kY4BW2udseUd8oTZIKTvepRXq9B0Y06RxWJI9UipeZGMXEtHeRYnLd8rH5FDfQyFPdfVLNN4JtrCBET47mh54RqF7F3GQ7D4/t+3+n5X/O3l+5qfLNgkoS5EB2GgikEJ8wVE+M4QchZcsNODlE2AsaIAIKZQn4PMvdK3O27CZT6yEYCtOTShv01H5qrGPmOmWHIXofE+Yb/lxVUKFtf2z+waQRGICm8BYSm5Qp4TkQHlr85ROkNByWwmJvIdVp760Omb7n00K7jd9b0r3cpiU+m2w04x7MhlhtST67XrKgjFIuWb7kxCrdb0O6oP/u0tADhedbaA2XxJzsxyw2ZWjEq4b6mUEcJS5ExyZFyCw+sc5ZNLP5G6Q+LSSsLqnjZ1+LOk4TFJnmXsPTVf5Z5St1VOjnfy0al6+37J7dvdDh7rFTN9j44JuDUppixtPMrRUt/vBRvYIa4kDENR2CwMcgFjT5REMrPSLmU2JTk1o231Nzmmnsd/mMb/NVKcxKsPvLFDv799IdC2C/wTmXjiQBS1gGqm2wXb+t+5xCGvw2kha2kKDUhfaL8geOIABQa0J8B598/GMtNys1VwlaE2+4znuvhGnA4CapQuS6U6G/LItF62ec0D3b/ajd0gLlMVZmTQazMKTRJ/nn3UCnoFz5TFzbuPJfBkchI//HO7nUDScY5W6kw1zUndfn1jtaBF0FBTponGQGqHJWIohVQZJQjNe0X2c9D7EoGrNVqNGdam4amOgIuGE4u3d1julzYLJndbpqEyRtJucK122oBULMBA4vhlkTXpk3UoCjaHlGgyEW2Y9E/pomnngOdCFECEgIKPYYZhGxgA4BkHuXb+OdJqGk4jQY9xKKCesre+m4Hv1XSmlYAKWpYVMvXZDqR/h9pLR+/cmSf4su8N29DfC/1YhFOwGDUqJZHiNCIuYyuhXZZLQ2QldlhTPBRZrf3Qd5E/m/DJmO0wS/fZB9cPT5ixGfV9/AHSQCaCgbThnY5Vfq/EUSadnJAev43yubkBwfRMxePihdBN9DN+tb9ZbO1J3doy8A3Xyqh5p4nC0dXYKOoESAUpT0EoisWzmFOgjT0q2CosSbJ2SwPtY7Yzn+PLmawMiRrswVm927hknmgn+2FvWx/fuGVr1R9rhzhcbex8a0JLGVTl/rV9YOX5EU8jDYR9EaF1v4nu+gTfKrmhlP4V0iWXcOfJquQoOjZnyirqRkmv/0r6jP6Xbl7mz+Mhs3VMN7o1ezfHjMcTkT4V3xcr6yPTlhnsMRnedjxcjn7KRsPaRqxqGZEn/UTStpJO78YvgNqxMYTa7Z9e7RjIOl6AdY7F5QL4L/KEAa7GrYqu3fXaIdx7dYZV7QlWeCprlBe6NzATvzva8lrDVxyOVMIF7QmNo0WY/H3KHm17SBir39k32pPgJq2bNTn5gsfm2Iror5V9xnlz2Yk7Ov1rD4GyjkBJUlIOjW6Dmqc4SVODRWH5TC8o5jw1HP8EiUNYLfJauTQJq2/E+Nirv32sUcjvw47d0FWv4AXCHsdamjVsIazyPjiEyV9iLoZOseC8yqHnHAAwvWwlOp8kuDsGsplYw0WIoaapGOU5iWVr67R/Zpg3tMKEh33HlIkErI8ZXH2hpOMz2cmSwhtG3N4lMOtpOwZ0/8nM9uWQ6tchWrC0OUMbhjSE3P7ymgMnUOb4SJo92crW3xTmjAMT/LpEF6EpOj/lYGi9EQFWuYNhAKMlNVQmloLcyab1rUU5oFz8rE3V1u8Yvl0YPSWw472qZXOSaTG1Vh5ewC7OmCDQgW6+saY30R2Ig2gZ1BUt4eoXmOm5+uGOATmlNtreGKXFvKOBi11hjnJHllqCk3MINIerZ83DdOgHxXIlBy9UOXzg8R3uNWVsR7RYfYbpk8nEVGhUMckG6qnnYONgoeyGdVVHqZtLrkLCOFZXOvSIvosHXNXD5l+poS+Smd/70LsDF6NKfdqz2pNK+1XtOjLj0X63AZ0+csm6s3fUv33qKbY1UrgKjyEaBklCJAneUeUJpxFOn72AvhmUXXwP0DQs+E51P+sReiMv/fyB1M0dYl9I4qBY6ZwXLobEfu8UQi0O+M05cjM2+ThcUEV/tgd2vkPuwAUJQcagrvRQRiOs3P2Lu6A8U68JioY8aL0bdL3uSkTzvToJ9GHAUVQ0DY1GIrtLyDqiHTx0RgfemN10o0xkUGpANcZLdINOM5HNnBYVzZ2xYgVhw+Z06gYHa4zWNTX46QY34Oy7mzs3EWV30uZPHdo0Zol6YwLFLcigmYLJH1gJggYyiZESEMWtxvsDo0ownP1US/mQKZ94M6Ye0VHpzZzg8cT05B0iAE3A7IfBYmNrUEbyUEeUI1Ojr6ZA5gDlJpNompn78J1DOGWUdRk77aDxFFRe+MXncyF9FeowwQuyb1czAWsQ+Hq328XKFdVykOSuYysvA3ZJ9BALkqiLCU8P6cfk/AEv5fkfKXJnauuIAzcbqJmiST/plHnm17rUK+mW/I4oJBH0I2D1wl99JiMZKZ4SJaNKe0CVy6PjQus4Oriyvu+89pLxFbXrlPnxM2sKwnJpj2O8EWhh+CPJb+TusX+TvYUlduZX0RjB4XjgGuFZa1eEoo29PvwIAnaoChRCyfHyIVyKDUUUIzgbaQNY8saZZZxEzI84NOQFttg9K6J+2869jC895t2ddK83jHCohjfMx5Bw44CViVKYiSKY9gNMUDEAnVQMaPSyaapHMPCe3lpLvptXBWP/Wz9ul/fnbEdAyBNyJ1iEQ/6owI0cU3y2aI0vA3vuob6bDprboc2XvzJIOHTrUwjH3or7r34dPLKC+Obhqmnzj+85Uq5cyW6N1bU0WyYY+rN2od1+xTYy4dCkcW/yphUcaaOKnuC57VYblZD2eW2k0o8t48mjgLO9pi+uNlNG0YC9yZ0Ul7iRc+1S3vysZ3nyeKnuoDuJl1cc+MRsYGvbBt2gmMN07Bxr3/JgFPBLVStM1EkfXWl9JewfJrKUWKA39wMEXiJ17BP0qzj0mkKAVtz+OHdL5r7AMlnl0rCwOOLIhErm59tGdjegfMUonDGEtxlZDT2YBWILY0QBSd227qg9OeYJ+ELD2I0n0ZWZE2uDmQHAzW2/X9Snxo990U5h+r1DInZLY9Lf6MI0nEfOqhzQVcAJ4KlwnCcyWPL5X7mmgti/SUd4WDtjXEPM0UzD7znXL9RCP5DPmGwS9Yy9eePcohvQfZVl4yAsbrhWtxx8fwkoykhx2tgwxk+m2Z00w4+dLiqhA2xuyU4f58+9ZP+EPGaWmdSvlLKkk2Q0Iz+BUTKCjstNnaD3QkL+TEd2TdZTpP9LE3ttniukq5tB41gH5IvtA6jlXAlWpplfB9Lh850i6nZvmO5arybn5XQthzUwxk2o+sS3TPLju1UkP0RuaVIUab2AB1OdkFWx5sTZ0mBJOs3nQCJtshPtoxwxUsD4jB2hF9p++/Bwz2cH/ycB3tYk1gbNiQxmCzmeI5yLPccZwOUkxUDlHiIB2xfdl34bGkCXXeXMX7Rq29S1+2MXXqJAupf2HoKrY6fHKvL+l8RZCB4aGQWqh7hyVnpLOULRyxc72kXvUsIXK5NwuR032EdIqHLxZRZ0ADXVtaFMiL7g/IlXQj4QhBSSXwJKMV2H7djQ8zN7XJ4HlTMOyK+bZhK3uptWGNJvPOAJCz8a8F2c/lbdIbM7NvnKI39Oc/TBPTT4N0LQ7850ChV88+c08Rqsfwm40i8+YAg7BHEViKvwzkJO6sbCqFOK8FZMFQzCk919qkpSaAcNiAg25LMP7IYa0aKsdCJLoa2H8j9WeIZ2PeU5ZHWiOYp9NToO+wi17iBYkSrIjCocDlcgA+Vg59vUjzsoT2g+3/lq2sTpz6S6a/QTu0foiBMP5UdFxwLKQG35HYPTfbn/n1MD+kkH6uZBpkBGKXAvS8tpVsS19wcyEf85jIptO3nz2bKqZ7N2bO/GQYwxnF6iXvOgaShcWOsPVhrGoJ+5QtXxO6FkxYaV+SPtwHDe+5WObY9gC8FnQn18kg9mWihp9ceocElkBhEYcaO/YaC9qhcCjjH3IbztmQnFyOXGge6oftrS08KGFBwwhJCqHnhwz6X3NUZupY/SYKsSoFhWPmw42zH7c4utl/CkdEvaD3+NixBuQqsVkM0pKlsKgc96DoYhcyhPAZcbCtyeG77V9BGLL/umy6Nt1LNym9l+Fa9BD981IgKllpRtrWnFmoHnu3UacLlrxuUFgUhvc3Vaih210nCGQtfFlGvTnSTmh6UlVL3S6KpLkvu3iiGgSqtdCzZN2xSnuIiiV4toPwg9vntGdZ1vf3MP/zJfNhsG/j5qyTnFOJmEgcwFFUs3Ki6yJRM3uV9ITsNUDWTCUIDDzBc+ziV09NtiZauvWilPF7uFd6CGoylOYgqD4Ay3C4sk84YlGAVwACAACC4YGBDmApdB6nj0nou9mSxueff5040rIfpWFpbI4RRPZKEhVGU26Y0o1k2oUdOahEQnuPkaUpsPM2d5GK+Na5zAqL824eCFzQsvq6QWoqVyyClOY324MGW1cYWoBuQoOzp05dQKTPVuXiOBaUdswxPbzN+3ZLz/XjhphdFtz0AmQ+OrvoTl1W2AuSM6nuv/3VxZOWk22KdguJXIrsGuUKDL7U4/8IHwlsNINSWX1E77CfYBqXG/1Qmr+2RQsnNP6xenZeCJebCYa9sjKhUwMiBnaB/HmJWKyTtDTCe4egjXlqf8OTyUvrgLWdsAutIl4j2dIvm5EtJxeSqVY5P6nstJGER/frkFbqp+X+9E1rAOrup4HtIT7+zBiMlRPhU8PKUD0CApawXfv8u4h6YDJVOqu3JOwmG9NHD9AxHge/CYUS5odajuCZMhy6KKqVAKNJdtwLYBuRWhdq700DiDYcDdTYnX9zq/2ahXHqo3EDVlw1sZOfKqh/BQiLhX/CLaSM5G4QRlKNkzswUF0by62RVzSq1gt0NMPyb+uGtbLZjS5ES/8Sd3uz0kXaYV/1mAtYgubi3RCZ4kxiWKH8I3xw8Vk5v+j/6O0ZHcsLCPmz7tMbe/HL1R5DThcB74Ehkl7GRz8WyiEUP2xv1E6EA86UqEfUUyABClQtsvOZYUrL7qvaoYucju0r6L8SvdC5zJyjniHLPises4TiGyqTNib6BC4vCaQpC1Er8VAnOgNH2SKwYf5vaL58fvfMxZTof94Lh0Pq3h/zrNxcOrE/N68M7Znc1DOgOta5L3XlYyxHEL0ulzG/0WBpfgmVMf5je7/9cfnOwz0cJfjMMnz+Hvjmmsqj3FTv2BoqdElw8FZT0yDKRkvKbxchadTNfg4tRnbk5zEMR2Zhn9DrCuuQfQpmodQw+FND2k131EFl75KfB0xVqy26z/XNSSfZUI7X5IJI9ZnPNR9e7hQQ7sJ2UbGQjaqpxCO3D/necf9fyPiVSHsll9x+XgelcjCRoofeQlzZ5KHR9pPh+yedexeeGDPkXNo+yYTnC35GN4atrae7exfclfY54yd9v2Nh3rLthQ2B9obFGbIkxnGPufSvv79kjmAYgU9mNQlDUW9Tiw/Qsu/3XSTyeD/Ii35FgcnyQEzlUoOZaGhg8AzHJZJYBhbgTufVQa4M2nAUbrgYWs5jn8jHDKeQ7JTQvKHcI+Q4J9vfzCD7A8ixKTvGRlPWCl5taggvCfLhjIYe1LJ3C2PKAmHrj/mtqvRq0w0IX50GwnKO/ODGiljNuKpTAdQVVRp6i6JJ4EuOE2JVLht4baulJpCAFhg4q3MiSHgZm/H+pnI+AxndaV4nHKiLum66omznA6ynSpVRIysYg5gwO2OlRlpCpnIQkow7YaKEOCRJCVKSdERYnhHYySxFgsZkOv9oKGz3Kzpqq6Uxvx+nzVn7yr+IkH5DhIjjCRkiEy5OdFFlyipURMNgAa9W7EF3BFJsd9pmZClU0hVVEEEsDcaYzpOW//mJvHWafsrfrNdrn/xUgOu61dkYXTx5um/Gus6MUdm+xdpF6eJSZJiGW6pRSAwyqzAtXedKoofW1uZc2HPwLj+7IwWKgOdUpQ/pKA9IvLiNohwdum4hPWwTP2dPk1pwSrjq69LcMZrSVUz9LX9rtffynGoaNEEVEVomqeHrU1ZWXGjsHDUHX01+pNq6xaTVPpaOiNOh3OwSOB9EOgFSXvvoURJ2QF3DRIJdUBBq/PHdCBbHPQENyC5gAXFsK9QzO2dPBrncwFYWg5K43WJln7bGOxJUnDv1xeuxHgla9waS6Yd07DqwTyQD8szsjEi5odwvvSIvT4+vX89Utr4vbkhxPqKxeWbSDXR0sUNXhAl2d9VufN7MTZoxzI56G/QTGWUioncDINoG55AOKlMRnXAoPe5ke4uGEbGeIxTUKeOtiZqO2/TAWFAu1peK1dSG7WXVWvhst67cY3ERVxLWdPRjZ75ibj1p+cehFheP/PloUvbKLNTnFygIbpzO+BtEISeY4qJC2UYvBttLCfpkGFvzJ70o676Mtl6oBggQXRRL8omvu0wzaWF6HcJJTc2jE5taKOrI5ckTMkpVJm6BX0P7I82DsJMvYlRiVQdeVdZRw5bk+21ETE4ghA3aixqgt1sEymyY8JzkAALMF3JJG1znJEpbEMAoLUmErJTxIWsXGOEgElMHu/YPygI9SZljyY8k8sytTzVyBVgjD5AQP5KP7rKEP7lmlsln26cCnP2pznUNmKoBhqvc0Xcflh2B2KzwfEqJGaUSjxd6yrK6IemwUqwx+Y3cYzJOqJIRfIhOTnY2QyUa9oDUSfL+CpiDshnqk5XnNTlUBea21kz3bMvMaXbfa3qBwqRIvE4h5ERdp6vYEHIVkeW5zI6k2uZqQY+6Ta5Sjs7FdWy68UYTtXFOGFB3ZZMEhWt3rRfx65HDlP8UPiMhJ66WZDNMekdrWW8npHvQEr1PTcR/jwhDjeGlYGn+OGGUYzHoytDfqxxEX8GpLiwitkdiNYo/B+CyXLXk5rXP1vnS+7jxwYFIM4LVRg5hEIKE7iwSryIgwTP5BFwvbV/dLywO5LvQFjLYEtfoTvOZSbYvQFcHyRRzf1DhNF7jgmUs4dJt9zDSEB4ziaFWaxacqsG9fj/WVlVnkQw4foW3QtDa6Cweu0nhLv+Exj/8LF31LJd4AeV+t+Fpxe0LJcQ3BJjP3pCX+uE+QGK+GcKJt7xcx3SxazcZFAvz0etC9ndJ3ngkgvnW04igBKIMMOtIs17BmEJSz+49RuFzT3TwWSlcbYP4QrJzwN0B8IYQcbGS5nF/mko1a962xNWiNcBcbY6WeohljyWMEAa7a+bQLeX9oDhOjm7ENaowqUplQTJmdGPJRYi5aYxWTSLT99qTMfrHBjUydLjWs5TUTTA45dMXn+TZMhE4bl2dbR2Z6Se7cGh1FKrKzCdX2e9I9rL05SJpRA43qsw0vqDZ1p5c66dOxgB2EvkAr7V9ixPu5HWP8L48v/VTU1xsjMu5BQnoytmZE9f3A2T95pkQaynon91IC3yyKxWKWoG2yOg/1RGnUS71RcSNGNO1JoyHRypcfgQg7mqDvpi3CrhVFKVGwNhgZLvVzX2G+/HyOILbH9urenJPA7kv6vijDNMiBaGZ+91WyWOAY42qFUMwdGlqv0O3ZpE4p7snEDRXarA0+4nZsft1SF/n8KzXHXbm1UXsIHxm5cO3qVSzRnTrWgobUAfRuYZXAQcf339XXNNgvWm/3oryRqPxrPGx20caGQNLpq0vUye78PH+uqj2rRzCQpHnmH4A/XfRl6UIxKflezrb893bH0uSOOeXVoT1FGICYIUAKIhEJPwZihFLqIpA/IY8z3Ja4ipmR9YMo9OMfujWRMQ/n8TK0dQhatY07+J9CBTZdBMfHHI3OpiwcnxlUmETYRafZRN2MOK/8Tl6vOqVR9biSbc/s6y5/l5XOVEajqeh/eQb0GTX0Xpn7CEkuh4aRpONpJ7oaQr9sV7bNvVa9PMajLaflkzh9WN26HyfayHgXJ7+yrH+e4UhlRKVr9nWijV1xZBmxHBBFTRYEFVyBWZyF7fgFlA1LcAaW5a1bfJdAjm5W2NchMpF+teSo2rJZ0g7e1RvhP98GAkQEvi8qz/wDTDWs8oCCjESPrfqJPCyNlB2yWe7fLBrgrM6Tyi4u8smeL51d6NhqatynYvxll0zMky5xMK8/TiTlE8FKY2wTWR85iarHmgBiddMwbaHxLc+M9Ba8ml4kR3NIlOGT9HGt6E2UzpD9jKI3Mil/bK1wWkh+g20yjtHsaSZ4ZLRFszhIXplMX910zCEbzGShCOKOvTesO8QJOYZzi3i12XyHOOv+hMizHz0oDv7PQrJMVCSFmgefWg8aFvt6nLi0pHD36GbPpNPbfObvTL6nHSJ2lhEfu1TosFvle6Ni56DlhtV9GXLnxvakBycBFxif7MG1FHlbCoAFsuksyV6Hlh/PQgY3O/S+XggmGKxAhLA2eqFp1wEbeBthhPiqLmfQe58HI8zFqxmOJgae+B2v1J8xBA1xVgEmIaT5vcP4Nx4w1jJ/X248Hna3ovS8vfsx4wFgb30JCP6Z54arSdjkRSbCl75uTTwsboUipbQM5eD3hZWbIPGPxOIvF3SmHzJM3/bRjPuzxHJJ0Y7AxrCWRYFNAtKo4Ev+F2P91Rb68s7wolVrT6KXLK73sg7cSfaX66iQogxen7PpUeNSvElFr3IfOJD0IR9x4fSfXon6lYE8MWWfaxBja3sKHocDJicVrk2GwEelStzxOuIvYVDLR0/l1B+thM0b7L3iJodRh3bxzrBRg2yQkGJRGCvZlnYABDX1lr2sCmqABnTQWV/ZR3nDvlTi0JYBFIdYk4PiUmZwYlC4077sRvKx9tN1yDEIaARW68DV779hCMXFrTjPol2i52rdWgsia2WMkXHrIFZQfoeYMNlBi7bADggqXbDrZ/uJns1oebOIHVw4ZgHAlcfSo/cpa8PrZ0Xu569M8FmlNFGee6/IGegAxLvDgeTNchRum34vg77i+TC6bMsx0I2mUUNCe7UNUqk9jykukILciQ5Bp9yGcIrxSAlHIYqLvuoU+rwr1ysTWXIxVSABPrud8Y1hJeHgEw3aYJh5m79hqFUAmv8c9FYlmqA/ASSnNYOuO40wEpsBOTwss8I0bHlo4owFXPPRQYKU5D1czEm2+m/qzttmcZJ0oqnv/kXf23wnGL/qfrssCRPaIW4goY/BTm4NNXacIKHLvk/vvONONNPlkPwO13sjdbFomSPh+SWkMmK6WL/ExzBnoHjnlUKv3arfNit0JrUJ51wVtud75S8VYrcBUmpE00yyBpLLUhu2Adu8YwjfwNeN8uM+WqG0ALdzIcVsmHgPSPAQJf7pW2H6ltdTYN/CnGs0zElKCrp3qlCsw6o0BxxvHw1yuPUaI3p69O5+pIrq3gko8uoWFfNGIdV1XrEy+WVhDa0ykfjmkImAS1aoSQ/TXly1vgQFdUTLKEAKaS/BxJfOqlht7P1mcGBRBCXeCb4W8zOeMLJpnMadjJsurKUl+H+0Aj//3T/jbkXQgvRXOhOnQsqOBY9J9G0WuB9hGRkhSCFgQsYNTMPOSRLGN2ORIBFJBFIVepBPi3zdyCtxEsazyRecy7UsUbhLCkHjkyKiKCKCUqu+WCsSZSEOB07xpOCVo5uglAG8MdJLNYb9zNXPjD0D/zukP1J6VjIOCgFnKkVgjkYbDH4arWtyMtdp3652oPJ0Hw/P4ap+X8rEqlnL8HsWdKZuFCJvnbQjaWPa4FKM8cZCu+dqttZrpcIT7w7HUJu3KdzP5F09TFFcTRlrkQfXgHwlK7bDmhdV+fPCqlUbsOmNN2RcKUl8zTqcztB0i9qb8YI39yGQP8vV1cFSy8jDjHXGk61rQ//QL0PX6LiY0IrONjLnjYP3ToP5R59XsO2aOcqHJaTIJGUtYlEvmQfF1JyoD03qNEJQP7/3NZ8YbaK6J1a8yxywqqgDIwpqLADyVgbF/uJKxM56iYQlOAIN2CIZ1a7XIK+7wuXJEIs/6futdFoHFbFM/GqjIVBawRVnO/GLSltEMjgfyRCStEFUbhYAOzOIRga58sznkwp5eHWsekYYcWx/JQsM65ayZFNg98ytxWJbBbf/26Gh46zK/rhswdLRpvL4kF++GlKZr2arP1MF70p9dKapW/35JrKaCby/Iz6k/PP65L73f4tryF9V+9et54z7OF6vrONV9HuZJZvklGvw0F3lX+hCwjF7qqLlVQrPxsMWc7mLduSR0rM50b8w6K+2DuVeLNR2oFSEEg0n7Jdyg5VeJpBgaIwkJIh8+m99MMizKpaXeE0wq7qCNKtgqZvMDKtksRbar32TXnqV/8Bhtfq+ewOJWS0XBNyrkjvI0gQFFmzaq3J7O70exAgLUVH7Fufh2nRHWQf0dLJrfKyX236O/Da0uPF1zePRGkjPYQM+DAS8TGT6ag138pNa6d50CRT22e+depgdhETnpKUi8YCU+xix8gk13N6V1nfwx3HBFn+JDRm/lXoCqW3X2oUFa5r6jMrN/rBx/ZCGLhQwQbwkoiBGQ9Mk1RKUm1UkKM51ZjqZfXRYTvUEOYwOcT7Be8kEFPPSGMNyAkRRhT3q+CYl/TQXP3kN8FcbGNJsn7Qxc78UkY+TPuYV9g07TdUYdoLZhxmyDroNiAsB0QspC8UPTEguypxckln5rNcbMkdd5VcuppehgJaCvk7eORQUTMM2N3VXocqf6PIOOaTxX6m36fNE3kBCv2bzZOtrpno3epJQ9ALQD7HeSCrqBUxEmQp2YnKYAI6x9DoG8bluM/Pv6OAQG4kBjndwBLuRnX39H9dCGu9H0pnf/bn73488Ho6ruupUvSUzuAvkxMSKEqZisAvK8s+EWarW9i0719NYrGdKOI4gOpHYjwMYCGQfv9dTFVa16lTYbmFl4db6y8fnKjqLcG1EzbvmPeOUR80rEP7tny/82BIUPvisHFsHVP+/td5bJlwkv+3cdMEFB43Xwu6BdHs0+poa3ObNzo7aMvxbkJTE5yiFjWOt5LDS5/b9RyJ0lClosSCoU49IQY7SVkflhqm+i5o8zP+ipA8vNYb14AqgLG4pjWlg9hKLYAFQFC3/do9ClaXcWua517QH4VWoBmigE7kZi66BlgUVFgYYPkRWKxi9nGryLFe9M9j+aajCsJpgLZZjgeXZre7FsiBqXfKooacX+0XywEJhwOvtzlHkbG8dUSAFthPuB+FslmTZnE/vNNB3Dw1YhhvcJjd9fcDMxUauSZ1x1IUn/THUNZfQP7bE9zZhendATVpC2wbutkPdMB6vFVDsNhV3r8BT0qgILmElbRPiU85b9gg/dmhUDSmEDZmtAD+EGt7ToGnDiCg8amqz3TdmbkUfAkS1HObFmnmTS8Cl0Ic1CyYbri6DClMwDWKYonngg9zziFkuMlm3mdA7FHLxx2bJ9/iwvC83sM6+FeQqXXaj2EFkFVKeMHhIm2uCHlDA9KR8Y8IuCRTYyJxVBiVAELPfpZkjwelNzhGBr2ax4cTqIMQxaWQYEOAClJuPCDwfG4N+7EEvqeRlAoyAyrBEBnH3S/4uylTZymGUuF4UqBRupbb3PydNpcM7iU7I2v0GjfkDScYdGzEMTFV5jmcHbk31qV3w6XOncnT/9xTS9xLMPZnUmAdQ88kFhaMNZcAKFAcmuXqrPgzfkvU8xNSoq0KepxDaGWkvRjYbJjdofb+nGmj0N6fSq9JFzOyRjW4O06Jb9XcmXLr9qrplPunaZzSryoS5H+KGrcFvORjCKCM6AVHRwaOpS2Ko/EfuxqYKYntfiYU4adOWUm2faLo5jb++dh9nOrcdx1pcjN9op2QNsi9+KIof0S0C3kHRaKGT1/r/tC1iEtlDKLPBhtzYKJ+nADZEVC11JSwg8wZjnMKgaBSSCedmDMG0AbN8Rb16U3yf1678r3mNh7cB1iEZX+0HarR9SgyYzfOGyH/WQc+zJ6zpq0ZRvrFIXINKgWvkIrcEkZ0qP+zDvXnC8mYgvgTxdsfwIw93q4KETNsUTR2yz3EZFH/h4un1fmndyhb/0XK0ekMA6RbEi+JNlMCq3W5B0fbc4DOT7OXKb0oGjAsprftyRZAbKcHFU0jGoTCQ+2+wsotKNHomK+Erb8j+/0D6EyPBYssEV8lnY+rHrtx0+YNJ92El7GyocOcgbWwTMW+7k1vHuGsoZAlP3WHDTh+uQHpm92Hzb1+hHQsRbQ6C8w1FXAwWURGoARe2VN+8KbTOp4MEGyZhDvGm4XDSyuLa0wImI3uG0MiBsH7T3dfEvkzDPbBAvvbSQamyrnBUP7l7bDXIKOLsriEuqoScxliclUN2OuB2sNC6ZhC96aZkP5gYsoPLgCk2goULcGtfSrh2qQobQLJS+5tvj3CAyoWffKCSMAFPfnKz/p5qhSslcqs9/Qi1fO5yMRGEpuTAtMseGv0gbRhGqMz9BpY174/8PVxpeKhrYahjQ5vx6f4h/BRwVusXkwX03vgsbM1kK3XeGBJ8EiHVUR40quvdiftAIj4JwUb35iLA3ikyh87BXDKGvkBaCw4WWWW+JxwHpRANtZN28ezz0ca71P7zdTYpTvnBplf9xN3EuYbT3EnhVrNmsfD1mN3EJozk1fKk4Q6o/m/l/GuEW1iKDTNnd0uaTor+fmV19sCBdfwAvf8QPVAqhTbsoDPamUeZ0jTK3LFhl5yLHEH/MCbkP9wL1+tYJ0BELPoFLFhgqUtAI0CsVuoVWsj0ovtGOgfcpD7DAcdw61bZR2pAjYj1Fk75WCcR1OJRXnnueHjJbBqn7VTLiCTnJWFyFvAGbxYbDJJWIyUkLPEuphPHaAUssKIdqxbFqUUs8hLTgeMUTeFmOucD+IepmcfovuuTuWZBL0mxkFJUNz6XCI6O/k+DnAFlCAeSNE1HiBwue0kbk6PFOWaylTrDt4/7HPiCf93HM0qg4smQDJOl7sWTuCBym74mMl4ep9tYeYb2ov4tMmYtgRMNOrm/OWfQQLs8VlA6cpBFJ+WllgjpUIT8d382w7kYfVNLxEjUi2dnJb+yakxxn21JLFLlUDZzcQPqYxQhI190EscD5meT2YFc1gvUIHv5/DNdVIOUr63tEfwnCs8O498pxLz1wUu/LVI71mIUf1g0ttj1ovxgvswIA/zzrDAf95tdCdLrgJwRn3ExdBccPEgMMtKPPsxdQjRNCJeWsEXiVKjLj7GMxKSxcEAQph2Clg/0bEwnxRSP8xQSZpU9FIKGKTRGxcZdgmsJracceKqa+0sf4nEh3zP4QCbY9zzoZRCepQXaCW8C4gAEPP5uQw0JG9jX8eHAwr4ECN38B8N+UZEcfXd5O4GctT2iz2NnHbRtvA1dy7BWA8CVIF32eBjt1pjotbrmWF3DYy9aNUP8NrnAJosLXCq7XGCXwW73DfSqMrZyiToMYactI/D6MiIvN9k2WlN9ndV3iPSrOaT+Ww2+4fUrhnLw90jU7xzg4rD3Sav/b776oRD3FHnvQNGp0kIU77C73lxmC/lmjjEWU09dtsL+fvmDrPge47YROYejx2J6cr95jx0JcF9zG/Fapv/SavfQrpswMsNYHkyDbkZWG45vbm/6+MGn2ys+knBpnOWyV5CFQ5zqPW7GUfxmJW41e2inyUbEKPW7fujcPiwaOm0CJWlFRGmIhCBOIDIgp0dIYAziEZGKMQwDF2uC8ZYMMiABoWm5bdQZKXf8NbMxcsWpXLdhVNXnYi/Fi/VY+g2MPQ05cTIK1ncMZGzy3Li91hzDkWTzWW59lT9+kKO660+ukkVLruD+qiXTfUyoPZgK8yNr4iNLqjgRUes7yiyhLVUeFHg6GBeoYPY8y+hyND1hBNpgDJl4zWv83VLxWZm33WbzaAysFz0jRLD7tf/QHLdUTs6uFfQKrK9vk9BUV1AtqIl7a6uF8UtvycaOIkZVTt0oigQm1RyC2axTdZqGsqqKYCAe4CYIeqOk9CvnEmF5hq+JB0G68/x06j04wbk5C0NujBpLlglw8VoxISBthwJUT130x/8FNFAEEGQi1/9mcY0cf2qoi4ifaPdcvioJres+bN2fwoXW5oEVH9bAIsKOUwx9LHkcJ9BbddcRjfY9t2pseli22Q0jcWIcgFyktYat+uQn/PLv3INWBn3hIDMJn40HxaeZUtebpy1zNds9ybkFvuzJnx5LPHmyi/mqdvNXte23QBfAnBhNMhV2JRTqoLsmdCDQkDi44OtL4XH5OK2o1JALEP+O6aNePJFQXaKFC7TNCgGwC85fpOSNFDdiVp+t+ez2qzTokZpg6hGx0a/nAj3AbAHGHcywQ7DTeKYfmZYURKmkhZMkLnp/pQewKsxdGN5/L3LQ44lNIJjjDg3ijjQlVaYybC7D4RkhiZPNdXIIYWphQRNeL/IORFncWh6v/I7zyTUxrxCCDuo8J3Ot9m4VVDh51rWo7crYEDM2OjG3ZbInuBzoR7p5eGGxWbC5JrDjnozYiZ55YZU/L6qih9In3Ir0nb6eAGm85ECD5sZlWEDIqShwez7W0PF7iXc1up/bnkY4QMq0A/kHPbd83J9+NamcaV6SiBJxS++gXw5jlXo89ApeHt8LI1ZXwNthynB4ISex5PebMLUd3P3eG/SWtd1fbxY2Nbg7APhAsuaN0bpUXvsBcTwYCT1Xlhv5JAbh1EU8vOh5zlX5jLJ66cOnOF6CqItBrp6vNk1DiqwlsqW9025vaB/oWZynGbj4AP250oH1pyrPMx4zrFwsbhrdF9BKYL1ceVnK5TuD25MYaf34FBdPTWZdkthe4ww1kzclBHROQjIKuxDSxXxvkWbrhu2w7bGIoH6MB6Pyn8EBpeBWvI/9v09XR0n65zz+F7+5mcsUX0e8mXkBN2m76B+7whTXdV30aVzqoHHrPq3j9i0yhMbGADoCHWJz4wa37IfOo/PmNssdi94qCWVBufyJZLYHWYF+EQjtknCFK6UiKSzLcmjVbzzJF2tgrtHndjb4rsMFjv68//aDjPZBwa5vReHAw1b6dYGQgprN1lrVl/YLBu6zGJLr1zOOnualLsr/Nrc0drTlr1yxDqKhH9KM+FwOY5JnvJzWvnQzjkjcsbnfUQx/cQNjbxezbvzTnZoKaKEGAWxjw9bpASo3Z9foXIes73tqULplw/nBZGZKcS/0YdJ428Nrz9N0lsnodX/D9qJ3zbUpmaGbH8XU3g1Oyyarh3jY7UpTnhDI7dsLzAIuCB3YOnWRQm6rEDuyUpTZgovlhmacSS4v6i078VuL3eusmsf7PikzuY18EggSmPiREX6qnGYrvRlHefNeTFF2zjX2UhVihcvnFHGIy7SNUJJ7WMEBKI9wjmmtQMiLQPQ9VBq+BIrvZoeDHVQ4UOvr+Od04bkflsyflDVMbwDFbGGcdHWl1rLORu8P+hvn2Wi03fTci6PLaF3WcR6SV1dq/G8LvWW3e9if0hOHZCU0fW37Lq1EVCeOMOCyrS9BHMrMj6XBurzcGsdB6NNBBbQZptdLv6k/PDxPWtF8RKrT9lBX2/AjXEolocTDrZxAOGyLLVRawSMAlyAYCuagk08Gy5uiaY3JsmoLAccQal9cGF0eSMEWSViqgEVVRAGxSihoJenN9Dh+t4B0E1soNrzHY1q4NJ5KUAx22FjB9tpm0c/30lwgV31i2BlAZJFTRBXW3OBeJNCzVlXNc4eCf5j0UOULkFdU7cCS47zCglGKeEhLzzAX+Hgv8bYzdyOSS09Cw6gyb1/bRSVcbj43S9WWx1+gb1uces+y8QfUxNv3hsAjcFUIYAQJooPVmc7RTyydsTFp0jpf9MRMzV9DmzSKtYMQulUJpAqtjKqoLvDviUxA6Cyjrm5UCUKudOryK0RaWuYJr4aGmUkItHHWfENHzLGhSd9GKoeUsOc3qiLdtOAoww2ZLZi0te/7KymUvCvhTOnin9tOs8aPxRYcyADS24gYoenp24M1ngZAlDfO+NldaFiY9+GJ4P2XLKlv7vI/0GmtVPHt5CIQSdDd1vq819ei+vvKseTL2aR03ptn0AOY9I2TIjXGgAjCduY3IbMGDg2yhBu2rmOZe2fxiYMt7W2TDRBx3RDinKnFfPUnYJNF8Bza1/TBCXzDB3fXe3Pbd5aS5GrM3IskfxPUUz96BJYFdgGbaJ+i2WeklxQG6gpE0nTzELO0bvpBZ6F+GMqruQj0+8ZNl+1qeyjSudUovzpjB4orKZA8TjIxYsJRIHs5sOf+qmY02BPf47ivrTKMfkFBZdVPIyuX/PGeP1YB5q20hrk8TQPpx4jEqUXnCeP7BLVZn6vtq5N07ASAFYULcdMI2UC0LNIpgfHVBEUClNcmEal/LtOMlZuuzC43bI+uPqbZ+XVtdfxGd48O8uqpuWcfgRqQWitH8RzngjYBDrzARaPiW0yGbhWsCbcLpERERlgYwiIJhxJs+UdC7ZLB4vYAlaz9mWD2WtfJaYEeT/2ngVZs5tbenN9PWoxdYvXXaN+7lq9AhlYPy+I6UoScr5N6ViaRbrr0v0ZW7GNkII0TORAeZ/IguoTeR+fn5maynwYoXxzkIOj0VlBFxRwtZCg1ux0kcjQGypTQao5BSCFHmCsxpz3sLpTl1B4br55iLKJdx8jziElAnZiUQ1hzdD2jKTPqi1J5OkP1hkUlyO3BHrcf4y30UlonCZsC6NuNqMRnr1c/zLOrse72eZ7Uf3SAaC9oUw3LGkFkWE6CxwUk2MlCoYXoy1uj4p9/Wf44T20vr/OyetI7KfGuWtuLwd7oWIat7muU/iXIXeg+ZQs2FeRiqLIOjeMcBN+b5n/LcTlZDEljR+biR6d49D0/1pgvDbEh5PySlc1pa8fJDF/2n0qKTng5Gs0MSltxngNiEh0A3Ly0Byf08TB/AZzmyuuaiGZD0U3PPFdfK9CHGwte2MzCNtoy5/4/2YrWX3oWVAGBLvuQz90Ll3O8thlUMynmSs+h0cOhFwCNP6S0J+2kMjJLWYy7A8UYRC5xd5XhUoOelpppmS4KMnvSDeGd0BghkTjuXFwsIS0qWzImIC1BiWbUbs5C51ZtReXvtus7z34TRpPSutwCk2m4/G6kUFwJfnYSoXi4SY4DYwGm6K3v28EcF8P6CcordibVjL5wLAGysqaGYnEy082tX1EWvdPo3OxVZTa+5bhFK3Gwc0XKm7HtUN9k43K/yoEpwcmpTZQ2uRU8xCYfu0PSiH8FMKjeOl4/szX0Vg5gtAsW40gep8dAmfNBCL1VtlvvAG6qUOW5qgqTBygZnydk4uG9uJX29VDivVmttEFbcGgMr95tr9GR3sFegZUHN0MsERENcUzQCJ0qjUxlCkwK8ilXY4wQeCtPGJ2UOrkmv4wtZsgsQ7H2mJhtnmEpvjG8iQ6PjMR7UiWQ1p9JrO2G0vf69/c+u2JiR+YV+rtBJ8JUaFfFeJKcmXi2GIiU1+q5l+dPDy1XNhozmOKYcdI3Edj9kcZb5PzMt26xrymrzZk8thylj1jgiLeE8iXdINqgSScFhITy0KUddaYEJdGqNgsAJosdzdzZjRLSsyzSq5VP23W+xucWzhytB8DhRZG34o8QlLY1r5w5vrUQScAO/kH6p4HIrkHskgVFc2AtGQFTqKtphvsST+RAKGGDBPOA/3IdJqzIA08tOsnj/djzSb09wdItVUKIZeDGP3zdHb/QHU9ufHRdex2jWBs5jS140DNp3hTnqKbjv4Z1kf/be/l7WQ49EG4D9pPcBL9WwmDrAkXY60uiYjpnuXBm+GzGt2prezjUsTJza2ZRjFJwl25Zv840m+yC70AAt/2wsFIAmytUG8fFRXtZUX54DuwMs5OUsMhdpVjgLL33cqkAlZtB741ccC8EmYIZBXlZtbKtEQJv4QmjiyrbsuwroxfG+PYu1yisHvmD4raZNQf3KkanTNLzqO7BCPK/5/xRqinncrwZxsvqMRHrzbBebrV98/Ilv5Ui95GVHUm/aFuysHS/I3c1tfxlo6JUryciy7TKlySIWmuCT070r+0kkr8dQ+x9dcSM/h8is3N8yKhlXFYxzxzBcCK5hPTFPQ+lcXIMJsmhWxBkvYBhzC/9wsMkPYuOv4xTHDAbknSQ1ZDwphd8w8VtVm3Iubxf9rMlA4ZXy/DoflPSF8dWmz66YIHPvhQEsl/n8Q3/9Lyj1rzLq/0QPbX/DBCNFmggPbNDkLNt9W/Ub2/LIWf6kQ2tE1pWHvpRh9dVeSwVrApUYFV+W7QEwZoSUtSLo8pvGPH7i+KhF28nnyqzuC/39vjITZuD0w3DZJZIyyvXKZ5PtjbcrD5HXYB+iJKnD27B10J5Gqc9T3/jcx7Mu2hnya7tXD50ap2DCD7n6u+cetEvpPFfum7A1mRGt5qfejD/IsuSZbvwcsex9oGi8nPUcPnkHi7woZOxhnJmC6kG9W4uP0RZkpuIDXXl3C6OlGre3lUmO0jtYYlA1PocFduXZZFOoFvQOsjC25dmESf2aUYUxRqamj9E5CKeRk8TXs6Svcj55t9b2/88zOo9s+/Meelgt4Dbmj4JMfzgmv3i/eejandXMO3yhV4MZox8hD1NuW4Sp8rrAJP7Ir59ohm5IujGIM0Ntv4HXfaT9SW1RqfGYXsRSa82DOSkdYltNbfCHEqui0xeR4xI9vwYu+maKDeDkf2ysHYHbVtgL9681npxR41yz+7GriscC8q3lnnQQyNFYjsPZVqXQIe5CwZYOWoyc/bfhamaPhiJCsKZ6iaePtQ5yIbhlPPiggtZsc6NBQGfJ+26dZnxn3ORqr1UCqPVaLfQNrLW5oj4oitGWY3lry/u9M6UfL+BWgpnMz8vxA3f6e9yvO9booo4h0pNGIr4X/GmLn/6tc3ZHrAFCOjhxafiD9umvjM44K5oxf5Sc/iye3w/ySZKEQndl3Ch9x2r4ePyLzDjsy+65dBiYLWu659bHgkTNUU0JjKBB/8jEikIv9/VLjYSXfLStz8+YcxsHIhPoPRKlM2AEAoS4O8yEl/GEjBxsHHE327C8AgYMgXYNSAl0h/iGU+PWokDbuQO+dA0KA0pFOmFyhsyKOlHM6A6qVGwji7oKIdtmhdq56hhumdcwRQh8cAQ2vBCcuzX9ZiqZaBcd/MrNSXh9C52IjqYiFNUxzO80DGeQzComcUrWI7UMSF3RAZT44WI2EBwMPDzMTDmYk5aA8Q3tXkZLWTMt3dVLWdG+C+YNbckwF8wc7VePy8C4rKg6pzzXUJY5K9RACAf44VhCPNj7T3vo+9/IQvnqbO5vyKCy1IARom27WzAN2pUL6T5FfIpRnhiIWVH3qhzapRLfIXmcK4eNAw3QPycmvjD0mKkPe7aHvkXZKHe+ht8kY5nE/B3215DPGvD2m8iI1cEbyCqtSXgSIEtizFd+pWunR/P6lraAocAlD09pcLL4o7xx+3ovTDDhhHQtOXGJG6078a4BWuBiy7mW1/n3j8qiUn3Fu34F8QsTcWHoTCHc+5WLKYhVcVgeE1qmU+Gd/Xbydz0J7YvrcC0ib1di/nqK/sj3vABCmcKe/iOkewF+HBjWRj2jQ+ekJRA6Tx9iu8OyRg6z3APxnjoARo3v2CURMQSbvIqqJJro4YZ4Lcp45d5yfOemv1cIv/x+pcvOQx8wLLc28kxLwS72wERcNRy5NpuQq/sRu5eehzSXKkfpXQiAHyyHyOzEyd84RLbScqa1awxuSnS7rWGZ5/oWp4FAkDrJCh5FTQE2VlVYWdo+57a8Z+ey41wiSPxT59DP18CnRyNmOYTlxtfpeUWI6sRllNkjc1qLz/pb0grt/s4qxTwgZOCPKLTnKKWcSYuvKHHt8mUiVrO8TJ4yxEhZMpoMxQI5mxXJmHKDLYHWlErJdqlGd9tJl0AaKq0m4Nh6LoYtKY+em2i+0RTiLKgvqw5eVP+MMGxqqnGxqWK4qbLEt5cpTW7Eg5Z+TLpdZxt4davJ1DWv06NzUv+vP5TyZBEZ8U3aOB0q+4BXxSLAMevEM4Ge+X4sMHLvhPo2ov6kDylhNHBtGaglk3iZEYjsS5SMduu56RuMk0IRJBCNy2T0tsCgfhmC4E0GypyMZWFWjm9jYTDs+9nrZD0K2tgxgl/Qae1KrqjICNFAG1khCGnMcmjo6yeeAEXKol7HkxgjWhJIvjeFDHWkthsCpoxzIt1ZGrxwiqLpiyYJKTbm9H3ZNL4P2ES53edA9yc0EywcHV/ZAn4ZKcGcslFeEue3kH4SIGxRRJkR5Few9HVh1DXMw49JlPkqUJdr3/pzo3KLZUNh7OBS9tuLL1ZJh9derNie8PtrwHCV4ujG4B/pkpyDaYHlE2b1Sf0GLZ4oGnwc52Si9gPhMrNgf1gCVJm+HvXmZ185kT+kGKN2c6n0EE37JLB02bAh5hlDhyUV4z2inHbSTue/8dIiJ1waY7oUErEzhVS1iZToIWFA8xoDDDV/6Pbl8S76SqH037ri9AFPrDuzDg6ZC9E1HrA6j5AT1q1p6tLLjYYkw39hkCBvJwIFrly25GkZhq08+KFqSyLeyGl0KO+o9gupwoAHkyM1MLMHqqoT2NISA5UjWmBHZbxdbeW/aW8S+B3W2P2kXZj2tp061aPwrLzdXZXkrt5XnJb1U2AoFsXRMIBM5dJBThcva2nsMAIBSxcNqVzYO+/HmgZGpiw6Z9aoay4k+5t28PvVeyS0Stb0ULz2dpJnYhi04WNUdXvG2yWhLUYjBvJlpQqbk7zt3enIH3MQueBG0CmYb7j66v9T8ZpF/rHN/9PwXlme5VOgCVleMmLNxv5MtQWXyDN/IDPej/8sTWZ+3Xjewk2Yx3v4+VEufnJmCReeSaZaYrXECd7nIQ6X584KpPRheIsZOW8uyDQEVIf7LdoP9lvaZ+VliWCXuhF79Arxvu08EoYwIYeIvwBnSv6ma4iayqTbuMfiC9QoFhweqmhXVq7ivjsxGqzUb3R8gWxp8IGIDxEt1+tHjEZEBuSIZEE4+k9MvwuxTeUhl61fsbBKjEB76kflsCncXo1LLP5Qx8Va/9LE1r5hX0fS8z2RXevKVi/wE1ppIbk59OnVgTOu/lFygQCHv4OnE6HNuAs0EQAF7403u3nQ/Eba1BvUjK3xNYAEjndp5cSOqFfwhKUALEX+27Fes2mk7QjAw64aVKDl0+Z+m/95L/df6lcGewBey/rXGe5UwRl8v8t4iwVVrpX5p+30OQ/4R5q4Wri/YliF9SvGTmslbQ53el87mxUSd8NJxTZoIWvPZzcw0mOxSnaytdWR7vflmstd+ycI5nrNDaoxIDMAi9gHroaiSMhgu3MBBLn5VMkRzcmT89xmV9eVyr66vVjisqhgzkzXdkSnclkLHhOzphVPbgDrxDODLCrFrdjd285HBxgPfKhPWa65J2nlUltdWBxw/oq9eE3AniDFjRmQK+EeWkni45X9bGAYGFP0L44MJKLCTggAgYHM0/2WipTR9SF6vAgUsrGuw2ix77rSzx4l/zqKlADREsCClmHOdgEwMLPgzXdTKLyPYo4owx6+yw0qcGUClafxwmrfBJMpMqC3oGB2Ws6a5bv0QfIe1EA0Bk+iAgSnQBUcrSswzyQ0roq7icxeey6g6ejt/G+dy9MHw/t+n8MOxDLsbiM05iM0ayaeKoumDJXElshs7i5qpqHeWbyAiKQPUgEUgc8SERGHkLsh37sWaI/S8dSMHUQE3J9GuvlPs+MT3ZQsdznXT7qEKQoJ+PSFssMy7rGzmDH/rKDN/wvzflmLp+GAA2Cs+BnNOUfMWGxzuWYusuIDejGRg5+GNFcsR9HwNpUvH3ES78t4LhGfoiU2UZL4kl9GOAI4LdORPykMe6njH0yTjvErzEOSqAw23QiHC/oArz+CRmXjDt+QGf1QUxduPz+i6YvDScIulWiTPQMaU2ynU4tompjtXoXnUXwoVs845PlNcdcTYqaUa1iTdaAlj+hi9Ds2ecwKuWvLPHfWgmsLYvgpqQF1HgKfLLD9KJG4TPU+DlJPXkZHLPdlXpWlq408tfOu/vj6Wuk95ExO4JXOGefu2Yv4wDG6EAbNwlxNtyDYaAx/hprg/5724R+c/SoYxYwUJOzhjJd4anjqBYmNUcIJOvsJkHrQwpsgyh8vlagL7EKgmU5JFMJabLAEitaAM5EuGfFYElTb0pxpuJNn3EtVldcf2/UaBAM+KcqCjkMMysuiMRc0YYKPHZuQRVDIjdxsxUUiNps1npHd0dKQeipQfJr8nNXryQaaQE1zsK3c8erNMj4dr2D9X+5qJyu191NLyELUVDFkpb6iWeRfUVH+ie+GarVtc1yIgiDFrTSME1CWCCCSQSylZul6tuF4C+7mGCECSKqgqIta48a/Dn1Q+95sd9tyYTfbJP+MzwnmlT3D/itVfyN4w2CPlWwxIKKMFewqYTCEyUMYg0DrEjFAIZmQEP871R9u6M9xXqK5C7FgW9Zgca++UuisCUYwQryqN4lL/7FpEkNDtGY6yFSQzFg7kqlIYxqUcc9Y/BU/GiUU15M5/NCFWrrkX5CnennGJRlWEM5ZXSD8q3WhabXxLmLXAjDZ+DsuQMC9/lWNmGNhD6GjueU9K7US2+eSkSapzTc4mdxboE5adPJuNF0RFDVJfaaqOvdStbpBIPhBiGt8pyZOI5Nt9F+llNrbDGArCCReFkNByQc6BJqUsDDDLDgNh0TYK/wUkbat67efnLeTdi6XbQtFfAcpSYkUKLSU41gQ5NwrwqznkhjG4zXbpDWrD/2bMe6xNahq4Vkul3MYtwDHr44R1zqlMyRk4uRdaF7UFX/g7+kLMH3fw9R+dQKewMe14lXu8M85U1qieyOyyuFssGtDYvDp+cxJw5UB9/LMY7JlN7vAmzLJToe+5z6qgBC8ceaIBgoov0oB7icGmpncFWsT4CeEsSSLFgrSMLkDOmwcXpPpHzYFBn79dDm7mLgUVEo8n2nhIt9pCkU+E4Fl9FeAz+UHhBDczFuj+Tj9aKeQBkSuKlWujALV9MiMtsYwTBI+1HM8AyO8AhuF83fMB4u/phVIFmYnYT/OShRyc0H+jWjepr27v6xllRhhSs4vlPOrMZ4gzONaOUL+H47XUBhwt/WObsnZMHBKja6XMdJrEoVkJJUfuC12U2UnV5AcyT6YJE1/bfaWVGG9Jz2ebC7hVwVYyZeQVVtWrr7U/Xe0eCxUwvAZulAQFGEUQzHeCBVwEHZJEmPct2DjJLSkMCDpu+l6vlnuxSt9jgD+7i/izC/fdGNFS4j1k6AfZerLJCCudeWKTbooFd9co+HqaJ2iDuH+FIjZF54RLugbgpyh6mti2D9Js2h9G/6NhhhsT7kmblk81pleZ+Vnd+GqfU6tW/iyY90ORd5icv2K5ruGy6vImAsB2AVSiXVYlWoUlGK0T5vsEFQCsPuREcElXDVzzzc25nS7psCpaeACNByRSgsLbILzitRBrOUza/EKbpA3oMb9QLevGT+kDKM5b3d3VJttj2HxTCgxFHjNPFFiW/G8y1B0YC29dW53TDUzkgwUg1DQcr6D3KMypYwmhLNjyTRAcZ7OK+p8l1vIXzrb41Uje1OXcsCRSWK5TXN6fium9e7gS7exAysoKXaK0RfQ4RivRnNm1E+MJHCnxHPSSkZG2dJM5LnRyNpdSV3MbJx1xU26i8mOaWQvTO1n3E84NgIeaJj1vr/owV/AhoLcUA4WV70Fyr0zPlONhGn3dQfMxD7OCZCLBVnkPHKcEESxxA3TGyxtA9c5NppIMRFeKr+MAT2Y5m7WRC/vT7DIVChkxZotzPB7iQDIkTV2kjkzY0Vm+Ks9Kb/xcxuGWuE1jsVVXkyXLfP7E8TKeoTW1XatnoDhQjhfukHEJUDMiCAYCRDaEGj5SU9VaZZz8fZzoUoqAuKkUVPycmFlwFRFEXaA/kV4LkdHag+q6otTwwsNnhq0dboSmvVBfiQGsxlx4K/QwFXIvp4J0S6YRIla4s3Kn5Tq7t8wtasZd6VWwI8TrKU+1bhigo9CrfIIIct/EDcrYRmr7wkXHbWuNYABXlcqAhXHHjCIW1n/vEpCuhksdWSRqpOQQjYz/04LDrOvgZuKelnZTyHugcKbYXQnhUG/C/m05l/12A6R8+TMclJzAkOg2/EcveDzCzDkjGuhrDobgQ0Zf3gK4NRQgYIrGnuWrzDbQYsAQGQrcv/QbNo2uB57OThJzleBbfgCsFFMVQ50XZBtZyw1ZiwlyIrXjUpnsXNtmUli69aiPlziXCwBg8HtExUwIRZIQfds2JPvGYtx3QOT/xli7/TK9bCwEzVVkyAqgbtd+1ctztup2zam0R+BJEXbfqcEFNE0yalVECCW40+mwjc2g3arcT0qlHJA3wz3EaLYEBFags8XbHXhzY9UrLPtT0wLeOaoGr7GYufTJ1V0ufn//KbLkr7R2/Esdc+697tzfPyuEyX3KfrFI14ELRqW+jajY0PrgCiEWUXe8/GiatrPJNf+MbxEUbIwJQpfc3e6hk/PMI3F8xhLeDnc700LrtSbfnQJ3LG815yomc0zGvJ/751VQ/wOZMCwT+kEhMYruCkoWKk9hIlXuCX0AIWyCaXHwZo0NmMvZywYvVTf7kViYetu32BT7tTaUpybjXinP94e+igzvOC5fwzfaamahpWb///OeLhSBDYkqQg7Ha091GjNHuKP8WgqMxx4G/7NydrzLstXUpITnR2036kfdP4UEhltzZj4rR8JYcZvIasWBtsrLAR0n6lAv9jEN5D+gQDKEreBCaMzJjDnNcqZsQQbRS/3nBqV0cT4NPhvxhPqglGJ0YSbg5KtivLsLdY4gQVGanhEF/Tr3YGUj/mc9O/DRdpSfHumYI+Nc5aUrzAnaYBamqN4FU75rfBzoSDjuF20eDKjS00BvHnf9zV24gn6iN54O2qAKPm4dZh4fl6z9BRZmH4i8I+EONNgVPO/TDBInJkNh786fEMl1CqWFo0Xc1ESFO00OmOwgsE6gn5FIFSLNpy79698/gv/1u3N9mOPr/zCMClUFAgwZ7D1kCaYZezJkAi3Clo6t5qSBOp5IOvuCY5ZuZDMbyXjtTYGp+tCvqIUpLcScEZp9NQbsGsC+zPNbZLO6eundB3V2D81Zic8o8EnaUC62ctPPkQ8B+aB4bYU5ByN8JlMMKdhKQ9S/we+cqZksNcfdK2qwnTObi17rtZ5gA/8WlXSZmkcR3GjnZVQy3FUq6hx5dTzdXIpdon9DJNJSUT85U8Yx9DD3fgZj8ZS9Bdq2canenwQ9mXdK/e8OyidBEzgP+gkcu4POS5OMa5QuW7NGmE328Bq5nwKIsnMckFMcjFiWryB4h+r+gX/FdhPKQgQPz2tKEZTQ7jmFp0Amvyf7CVf0oxDRMRQz0dabwa7xOvHp/IidAchrClBJfAcEuYXJ1IdmqVmDFRSy5u9m4PIlrqtUcymDF8Tngndyvw9S1GWN1JmowV4WqIh1FGM14IlAFy4BcJ/VkwKST9bFV3fWipx6jDkPTeDfMuLjSZez7j5kLrY8CzLdiV9LbzbkNS7xSzp6zdUVQmDoPbLi0jYwnp5C94tOZfpczcm+r6KrfGir4+lp3hxJTB9qJyDVu3U+xp4ZFce2v8lt3wz/C4wZ0lCbLmaAFizSJgnK+wV4DLjqXQzEAZl+PtaCP0+KqtA62b0l6ZRui5EmQHsM527jTZfaXmD8PNobsYcx7vLsXQ7oK7/7mfJ//GodLEzuOE048j3+gg0GnrlI36AIqsc8ylHSTxrG+3CGaJugSZe+zGToqs8lEfvJqx6ZT3lQJr5sfRfD0wjolma58D+qpHbAd3OLKfkW8syFAj3ZNG1t8z0w8jBp3w+zC4NBBCCNR2YBXqSG0WNJdCXLmidl6wAlUAb+8SaE5RxsbYrBzkS/fjVuznTY5Tsn1NTvSocp1AOXMMfcJDlxzx0lPJNTfH9ApDnreWJWqRi0MhMETuYtd7/DtM2EOXLiZPADyD0giSjEyWhYJkawavdlACkzmKXFTQw/IcjEDKd7gMlpucYWr4GqjvsMJwIhHI4eRPUw3mmMuEMpAwGu7fzGWh1nFfFk5O88PWZwUqynoDdbrZXiR4YsQbh/tANq1U8XVNMhpr6yWffKSzzH/3Kb7ZnZdHHAcwW+xjIaBUB5Ffoo8QIQsdpCA0iSQgQRSovgmZ2jVkMNBhhaV3x7z7hOZ4keKWnSdJIJFY1DbkVi7X67Ov2zmOEa5Hb42E/EKB6dOCoDhkgekW7rnkUOEK7QCM9JcOcmuAQLsXDxcZVebqWjx9HA+WPuUxVVBPjYcFLE3r4IJOuuQdY0dlUA0IHPZk4jgDGRyVUVKWt8FkEpERnF4zOU4AJycZSecBPu0hnRYP7aHcIAcJ9ENRKIADIRVH97W3M+Zl+2LsHQSfFYlpUdfuzKKslId5qYz6gpltVLiPlkFssMUjgDuQqz7kzYSKRW5xbJZT7/xOs3uG6Exg2/x5NOEopsmXkn5fEqsgeljpg9+Qxh+uh73fVSxa8drh1f9LYmrBIAkG+9sYEXzkWNnV5e2XV4+8VbQB+HZ41Jphspm/u52sZtgV752QQZctG2wn/k+fT6AJnzKYY6Xw8/auZ0j3HqrU+HPqnumA5dzwgCNpsWfagLiiiexbG203HACYkfwAR0sLnKkL2X+jiUueN3Cds/aYdCCqzB3vVOqzPO4WDIUowGNXKC93CJUQ1MW7G1I0AtiBq4cQG/YzqgBD8ZFhj5AZxGYfVm8u8bvUA7iWGocD4lc+zvljkpvnThEYoPoH1lCWN2IkSOCwFxunGV1m63oL8FAlsd3J3pW60GQ6TxzJlSjHieAKlxexAxv2LG989KlsADHj8apOUwA3/brUfolsLV4bBIaM3t1d9bC6xBj7wdrQTWcAjFuPg7M4xHkF+E/Kz4LasQ1/rIuxZZ5YWqix7je+ftifnQCwqwFPrxI8wlSpXcceTIX5tVmApB2Ix5wle1VqrCYxQWVYVTJvjULUqEudkdcjTzFwDa/opYPME7KAt0weQJixXJXF1SYNVD211jOY3SFNpKgwg/IZq7rqxj3p4lZIzaE68rhZRBk4KqTzLu3yf48+2mZsYf7akiOBc51g5mWTa9yDuO1VRYJTGEslygR5GdrJ0IyIm4Y8/SFEiKtSgxWN9h0j9kCz0aki8g80vrHqrF2lwpRbnCJeWOW+2JQy5NwTs1wTcEj84FfMScTPuU4SiGKb15c6HGqy3JCWaZ69pcVF3MGz8/KaAwOKwsw/lvFa3+jYc3UPxxcxWcRkKY51iK0TOh7ImEZBI38zyXR0P9Mh9lE5fabKpIWmU2a6vnpB+SJpJVZdVSmHSEmDy6P3JVaYcE81za+aC/hOLlBdrhJAOQIlCC18jS/ZieOIiJCSZFNFP5cSNakFEgZyLpxp7DWjFRIdcNR7Ai4kYHyO0mIlCfD43tYouGF3dBu97WyeaN7Kdui5wHL7Cnp/RYeHu7h1kqxezv8rL2p/ReeTVRcbewtC6YcEoS+9vbwztZvhbu1c6UEL9Xziu/Pdozr3N72OHyp1NCvf6eHTVF3k1tp40Pzh9ovnajs4E/Z6ZhRf+8zlEMvv1bLUDOqwYSnuj/lGApy283shvJq43y7tqvcKYhTzZs/UjiyzeIr1n8tqq4GRUyCh6I0efUC+Gwt520uA9cbfEvXbH/swKXuB20hD7/vN2M/Z0LObU1Okd+X/7FZKg+Opyhdv70VUwiX7W0c8IHkLjNdvSk2WWp1/NTyJEk1Ey6LxaKVX8d6LmKAhL0xzh0w3k52pOSaLG3JJ8D4mt75wyCp3pX8SJUHzmEz/wn8XalbGutpxgNs4b3byjn05JWjk0PYtt4rSpKboD5hofRLnv2CCL/P0H07Qbnsry7jR3b+VenJEVZYjS69ISQE/H4n/SfNoDGg6KiOsy3CnevT2WYB6dSdwELdBmeGWiTmHj94POumYscWQ5w9crhUSaLfaymcUVLrDLHhMH5Tkh/RYbEm0hUg1Y3dVFnoMZVVFgwMJGszDX96S2h9YAoD11mBMW9E6sJHqecro9qiZDNPJm2D3c0rwEIovTIr7iUjYhwaJSrc/CXhyVjOm2ltI29TGn+jVhc/nKyg/p6e1hvcA6Zw750fnxZD26VSv2mtK986TVdeAwUxCDNjyOl+VhEV1cx6zg/2rPSqM1ZB8RuVOfW2mcNE4lYI7vJBl5PUMZwxuXFuCm4ikXi+BhL0osimGTqLQTR6sSOebVqu5XvRV2C8tclOMKCDYMTbfDlY08uWZ1jbMbifzcZTL71lpDBYR+QfO+hzOCDr0O1XZsBu/gEAFMAO3dU7fHygJ7lz78pFpqV99+rgQ+UenxJoOAI/0nlJiiVSMRoFbweD13xVfHO/4PWYKzq1p9mdGxnHO+V1P1zqzHAX0DGJOM1Q+A6QCMzjgbULrKsPoUvIOlxPqnAQqStSzmw1yyDI09FQMoAmQcb/W1wQuqyygsrsvf8pjWJTPfqF2Ar1ohLXfDBsMvrbg3sPwYRdg+3qk7TywIONJBP1oueI7nBJEiTVRdAtSEEbKzv2P1wGLhawBDEYuCiExwmKl5R1S2N/t377PTHkTf3nWJMmSfWlAV+3iflvu5wzL8m8+DTlpesOPew082C+R/8PIifq2Sbg/xW8BHC4VTb9VAxnXcVjodmTLvC1Cr9CTlFj26F9/lyIr9ljTpyMGqBj5eBh8f+fd5jT82vnEBY9BfkOb629Lq0oLnABI8ms3lx3Ye14Z26e1RHxdYpGPkXWqNvhvIfce4UinLXTUcazDDRhNMFqTSRB5BZVm4m5SuHE2qK/owEUrRY7kyhE15zQdHSFT0GMWhMYRzQVy/wnFIgWHDqvoCtpzd56dTXoMEl9CpZEVQLiGxxpHOckI/hw1+CoBIjyh//ZwTZDCsLq7KyDPsLXHHyxHp2qpIaVe3lXNdEkAb6UAhLCbOgMEW8TegLKtRSF3Oq7356FxZXtVRmyGh/uXOPrqVwGw3hiMaRHFgcfbhF/0D7x0xlmE/ct+SOA4zmn4QMegyQGLGQ8JE3OkveBNn/6qMcRCLQ+Uw9MOsGC+aICji9WqXBUvAF6wjo9FV+bO0k6rexD37JQ2XvHOVa5elgVdkNeDazbMYVG2SoFmF2KY6xT6V4lQzw2RrIHTBRFYutgG5a73hqxdDngPrNvgNlq8wj4850e7H8FZ+Tz03UCy4Cth0LsOf0+sThYyXnpndI3xqYg1LWG8BGyIw60hsQALqJ3Id48RZVnHLP68unql4pfuR7qcT749FXi11j6LQ00m2BVsMQ1BeOgr/7rhuLxjPaPdLfWs6QJqzkzDe2ZdjA6/0gcMABb0365dkwcHiK3qDUuBUMPKGiCu5+NT8kMS7ZDxT4zzWYavBNT77EAST/iasCvIQT18SYPr1/uYmR/DxUxPqukE2PPcRhL2NuLXA3a+lzcLDAYsMW2Xx+ugY0kO3wwlPxZWPQNxuxhixwsrM1+cA9S3x6YmgCfwLZ0+V8hmLvnycrnu0+NHOu8NfPpdwBQY/4fHhAt8qTIB/h+tTZ8FzcitqYme2USWWMiJu99nfyrDlxF918B1u/rAJNgXRuC9EJf890U49ErH7+DN9LD+JGbyjRwD1OuCMW1CU//uCuEhfuT1LS58rHLrpjhB40U3PIq9mY7I/Ff0xyNfdRVzT9v99a1EMFk2EGt6hEzEsvVmdCMSPHNa44RXYxg7CMlj6yo1Ec3lp8ra07jVNcWXOlnGvK7K8D3yqRooBQOKqgkXYsnITy5eb5DVB+U6/aKio+Azcdt3EbPYhBxO96UZ0eGZX1y0dzfqqSPPgze0o4koOQJrU4caXq4dauEuheMnSyV9vYn6nz51oto+Ah1Ax5r/5JbzqT8l3kFXXlfip34L8+prr0fAVVBwwfetb24ToMSkr81AFtnVCCnnRQ/TzPv3V/tUWmDWJZuuacLvwaDTYeGimDXQWdWgv3G0Gk1a/5N8/KGOG2PeJHxVr1ualGje+rUrRd85y7Lqw1d/aoN8uyKXcaM4F+U13YZvXGYk7U0/MZ0296Jy4nWL21S3Hlxn06qN9Ec2wbt85d/zFFtHCrJ3gAkvb0T/KKJ8vZ4v0Rog7HY81ZZpzIAczryeHU2+ibiraWBZfUi6ftG8WASilp2xOHzm6cJVMMPeD7XOPNaX4L3CwXg2s5egy38ClGdOM3t+3cdHGmwDKhSweqemfkVwj0usEAQN9XXH51bzTGURr6Gy1aQ42TMmfc+of+2nzOI0vlMiW7KVL0phohwoY1bIFyLyl4W+nnUypnO5yRZjE6ZaoPEkSh4P2ZoMchazCrpvq0bJQdGEboNc0chTHWqlh2jWiPsAjaLy6G7SSTBwuRBN3FpCGfr1o0L6e9kJeUqMkjLAjKXdQMGdZgVa4DtRyEK4c5DjozTKwhhmWZpl0TYiYxooDqGrrrIhYnO1yYbUzKV/t0LssgntefcRc2UMqKDfrCn4TtJeUm0tkI7+td/CdxRQKNfwQt7M3yzThv+/PuMRz9X8k4+n5XutyQ8vtFEET9jztKXHPVVZnWXRT43HhxR/f5yB0nfv5iwGMPUuGCdxDD7sGcLq6BKoTfMt+lpPPuAJQMAVIG+g0oLcIOa9wx7iHKP+ftaBV23NLkyssFqhapHPgxaw944WRCdL59owpZonXnQqVQbbdfmeeaolRkzASKMeOAhNmjq/7DNQNDGcOBBAwVrXfXNCr/H0xPND9APcufqLZcwjXgcWsTRVy1U3jOMvUL2hFcC+tfGDN2X3jJT4USc6Lcn21uxAwyiV5BtJUdyNDXEvoalpx9V9XmSpF+TXGKqXRF2yDzkg+3ssjVNbE+cwczOu78janzytBae2JA4H1nlh1YxuaS8j2G7YmzLvkg97g7XUtGPPV8726fBvy/Uxsq3Ac7HoF/5JTmoKvgWSVyo9FrgT/MQ6L4g7N70iZFDmtnmWx0LmsWFFKq2SXwC20/+Tm6V3lUlbFSEuxIQY2daI4rE58mG8CmB+Q1C8eczElsiJH5yBiWZCbMWhIosbkKUGaOGJmHHjkKdWHq9J94xrbtwMbQB2+k5Xx/GEKV/QLInweLk7scNPdU2M8pDDHFS9kthp6BR2gikzJMIWY8q8logVfV2RQrcnYbOBbSl8mZGT4nms42Q7mM/Wo5Z9BtByKxhbkYouoZQKe3acMqTvpLBv1uzuZyB6wi2+FeAeOG/pkkRSSkNtOelyzmxdZGRrkL0ac2mx666Nw1K1nmoYTV/ydGbsAbCAVo6KFazGXZ5nrwqw+1BpOlsBOuSUa6hZzXPu9yHR30y7pGhzUtQblPoyFaqubX+hj1ZbNFZ4Pvj04Xoyb3J2KLKRWod4AIu60b2YY6yO/H9d4A9pPzderJlBHpZtxS52V27rWZzuPHfTf698ZMzmsbm91mhCLk0UXQ3N2/fBJN62ixNP103xYAzrZKS86F4Ro42ft0zjadMstgfbxXfIV4mnE9Qa+Sgd9FBoU8PYvCwK6RzbF0VVeJV3CcZre8aUrt8cpP+USe/xGAGkUbuAKXa2JAJenUcWXnr5oB41Zsf9DbQaexn+7tNk9zxagNnzFqLpHnAFU/wb4EIYGpjqd878KgPbDE20mMFMhmbUEoz+XpRnaDZdAhhydq+SXw2HHUpSe8/I4M/oaHRJGKt/abgErQpiBQHzACGgpGB2K7U6RCrWs8rM1HFJ13prtAew17FoM5QdNgKq5MJYQWZyf943fOa1bDVjTHtnBTD6whwZQ1/CBnKwicEnbXo9il6kqEPLoK3+CGlwsO9/nf5Ujen5Xs5WyDe9v3WkR1/8ncTqWLkgn5inPynn8m9e8aHmdVeqyp+7gEu01/9zZ5IOxrGv0SE9SuMv/Fsng0Ug3I4STyJZOwmE+D/6ebQ8KqFsyoaOEuDEmsg98lsbhPMK1KnkpGNd7c1LNsQg83lwVlBKF+2or15bK/FSfkrzsfAzg+iWACQ//A5UA9SmOpjncneeIqqfaMi6Ilz48kLm/aHfI50WESXERxuVIUKMi0GIhqAABStaG6FxyDEJQiJEJaX0Fwyel07xYDXGrw5LzsU7ASVlljNMPzJNE04K8d7ITVK2MtJCYT1GZ+psp+i7opxkK1XsY64YKKMXkyeh10G6byFAY3IEI64s3h1Az9Z9eUHzryEoZxa4staAdWWlkCHab0Aif4nGYeTyEYqvdqOS+fe/N+kfb6EY3I4YcqSl1LybRY5fUAz/W1HBVH+t6MmPf4XpRevOV2Y+nHbPu37u2nGeddVZIAQkb5USvhcdkdAGxFaIWkc+EoYrGt93EAkCPPoKo/mp/IeAZ8Z9caYQOftI3kpWw5csmYfC7lzaC3M5c28UjJXH9jgqD9u3PawfOmlaU6dgD0qTVu6gHGOpuRErdWl5emLYKuEdSigYzyZgSOryo8t1JWxXoot0geMR0LLINvRNIXrS5pgFq0udwBVg0icR59uY3qvVJ00R7j1FINdH5niM5qjEZX9IdCelV7pSgvuayvKV7YMAk2xJmkAMimq5HqFvKU8NYQtC2upR9k8d1hlEn3u1j7H1UfBPDQeECcu+RAAP28rQqoAifvlM6B+BjNx+nuQic1wWI7jmm4PE2g+d9021C/uxrIMN2o0/fzMpGHgbeG8Q755z9RTtNrqNqOE/XbvMG3n18vdr9OGfPSIRQhe4OkUTas6U/IZmYq09iQNcjf8mcGt2Pbb9SGlfxvGEkXDvmTe5mdw9Pb13TDYYb9xxWyduCBPMhrY2aozhvuXhRmB4YsyEV/W4mR8BJslNmRCQtCfV6a1YuC0FKbkZXQ+dajMkbAWiACiOWNASX8V7MUSMaJRBfpZXVxKNOv7v6OmETLFHv8t/pSfxuSreLsjKfiGBp2nvJ1eOwETZIIWSKEbFPF6B+DnMiZOkmX3Cu/f2hFSNlb7ePs+TWZ5Yi10xgEWNaDwpaAOaVf9DKcgckym3l0u2vw1q0iSIJVDg09DJWvhDrJ0nfCXJ3kQE1IH+qGIUaUnCXRqGg3huweduPCnUX1i+Z3ca7JXWMJ8gmE8MCglonY8cvsHmJCt7csQQPcizgaxNV7PC1bNSfcnYvxpqRsGeSEFLak/4XVGIpj56qPbp8zdWTUz12g8x88k50E1NfSYuhity2gg06OIJNhe4Krqxq7O/jTDv//4ndiI1W6DGhrYIuIRHt9ajEnGUc+rQdR4PMshwXujdooHIj5NCF/08Pzs5PPUo+zrxnPrz/XKfHOSs9EFwwlob/8JK+hl19VXbXvd+DP/ABcaXWTxnF6AmPg4OojhkXCtGnsK3fmYnpAZtYS2eFE1Fl0jVwyh527mzvTlNSLPrjaCaMIw46qFFbFE8Sjj7vj3BpOTtFWUj/GLyPF9+ybun7ANjvkv6YsvhLGrlmpiYSG8BLtrFLm3iHZaQ1KM9SZCTWYMmojahBXkdyF9GHqn5qC4KtpLW5oR8XADtwE6siKoO9/7LK0BTAhNxjA9iTu8c46Cl86SyQImbVNNYgcDSIIvqpA6BFOSNOIBNgXma4BJcGR5gI7ggF6SpcxqLmZOAFOXLFghRvXa000OYMWCeRIdRPDJtkCBvcd2CP/sr86FwR/WcQv3JzbAKPrV9Zxb5+vh5F6OaMGdbfiHFjiYJLN9HorvYmUGpZ1NfwQopRsDLILxOG0eC8SAbTAD5i5+xTzTXmsF7ku/azgc9wDarw8ftLc/MI+oVlyL/OLcIcOxsPFyJOGShiihEGTqviEfV2M5caqAd7LydlE4syA8dPoENysY3LVLpDIBNEuoVNv1iBi8o+0kWWQIYEktYEt2Y3Nc9V04pWq0F2YvKYHFWQQQz2aVlk8Lrv876jzJiKrkvY7hwsaN5ARuy/xhV7DEz6UTpxPiW0+2K8b1iwuj2nnmkdf6/yX77959uICo7rIbUvIJggdjsNJP0rC1GrAm5SMPywNzAZmZFEfLv2nKyN1muJE6UT93Bvo+52IooPEdCThliZBmNB96ZYRv2p10W008y/r3i8UMp9ujtmeooIhcsulKut1EfCPFIXf6lklgbUkALVuAqt+ZPradoSAvrFqct+Wwn0gQ8b6TlpPijijYIV2WbVK/ZyD7lm406qqWlqvO1kkawCChYl7yhXubrYZKjJqupr0BolqNmq5nQAcolKjk0GEWCcFuUyQobalAv1QeEBXkzBWmpnNv+x4F4hu7oQJFvFzAOXtFzGmjmIGxEdWbt//9qvPZqP/9/fWrktFhMBlYVVGv8N8rUdWUFRgoF6QLMJ8BcmmMJrE6Sn+ELHyfJBbOS++7+2a1zuwXuuM5upN7JuM7ngJmgozoRmp3gNIcAo30QusQwhKMYzT4pugCifQyMmF32bvZm+1TAIlmlcQkNZal/y1DH3S4I8mUHa9fRF1uD0err6w+t0WPnR0cfoSw9bDQeJVFAixsa0s6ppBn3d1McszoY6AqUfWPOXm+N587kjCJMyicEHbUpXnGQnTChciQKa+abc1Meqo+QXsrsDd7K/KUaEkxQfoZzUXlLU7ChWZfcIuKMRvKSQmVLxlhuH1NMBvavdvdEhmh1Kqy7zNB0qArX29pxQG/DzhA7aAAmAiXjCZprr275IJPE11w2qOyEhhjE4rRo+vYCjr6lsoTNaLnETHw9FIQOlBZzNs4hieaRy9OALU4OvxBSWOQLgoqFeovHPVQrSM8lwXjya8p/JgU06Rsbdo8wkTLtWwqN5nFbkro8J/nHDXzbAZ0UVJtgEzIuSvv5g3I8Di9KGA7MtcBWZPGp8mTKZhopoCT2msImkO8LNVoHfFEbasg9KKHulQcIskujMZt/LgaYpSic29vpPiPjshfKc6nsYRFli7yRh9dJVQHLx2IQvgyFvGuAmhA1zJl0ohPXrVCVMyXTgr2fQ09c3UEhR1OMgRMrRZeK/hVp2xXPTtR8tUS+Auwrz+E9kK76XDGE3upmdVw9xHxlGZLQeoUpsLcmmXDq83xX4LuXKxzJngUATm4i4pAzlccefBHFY3sqA23thRpFDnKaU0tDmrQ/KuJh6RU3Ev3kJ0t0qdAjL6g1Mjmgwblreu/gXXE16qxKVUlKf98FfE0YsMjdpIQiTTLLXbpENsHlyvMS/D6GML1uJTxN5UiGZh57NCkyyabi3cX+539QFxgGWcRL1OlLZEHnEjNzjxnATejPGQ9AG8zDSWgzRrq++D9tOiKVvd5zR9k0JzA6KZZzSmp/k8/Tt9/8lNHUd5qGlqc1N/2uVBsG1zHY20yHmCUBrdhBLZMu8A28ipQ7+nxm9eUkmvJkLsEaC1gc1FGdcbuxtckYNt6lPHepCws+qWB7ffQn1juZFY9oidDsAY8Uhe1IJ/lJwnt8lPzgtyfhOAy3B0nlVglD7EFRheBSgWI22osRWmqXzUgfH5JD0xXVwmOxPnLDUm6ubYehJ4W3Lp1LWenR87QcSka8ZuzW1L7wemkK67EEKiCFpZN1baQt3sa2vY90k4lTS18qUQwER57RloUZL1ZQ8X/Sd1zNf9fFX60JxUINCVOGnpoXvZoNo0fmccI9EV1ZbvY14T6osgYhmMZ0CEJWN9kVFZBtvRpFviszvvz24W/KpUv5G11t63zlIeue4s30NckosZd3seq2AmhkUMMPwmIk35YqwsDQmoe4YsRb9ahr486W5RYBwt2Ray9iOTx+ygF0bP3JBrWK9kNsYuYLcWZhhCbik37n7xraxw4aLqb1ir0+UD0VkeoIsMBUlEwOZJbnH7hdt1o3sHph6s6qHmXTVYn3sOMYHgnr5MifHW//s/OOFG3DyrW7+rx7Uk9krfMKb1B4O3LOfc/8XM19IQfzuuvzfpqKxT72774qyHGya2xS11gSlmsS86HsjWUb12AB/pca9R8oQt+5NX6xB0o+XBlNpAi2nPo369dtKGPWBCTkVnQjdKiNhKi2gj6CZ2Cjh54dHJGweWEZqWEuP+8HP/PvaLdCBjnI2dvRMRivs5P9WZOx9QjOxgGluRhJjYZBa0QFrB0QDS2WGzYCLUk1OuGDskkBqQRnlkbblmrjkvi4bYZQq2kw2aYUXBnBKSyLiz+928Si5Dxry0fGcgxbckYdzd0fKWZVo9asVzdRWEtts2PMsjJn0jkT6RAnRzjqiiyU/Cqx7p96wAdElbu2wLbNNcSPIFfPDzNzrciw+u98304WSlyaclEx2wNbGKN9RJoFNUpAqpodpeoTK9Yzb4TC7Ksht/e9UCGCgl2JBqIkTy0ptaDmNuZjyF+SYR0LtQSUX9lZfrf18ju9d7lU5AgsxzMFKOVWmZpiKpuIlZSpjNNznM4hI2UwXgJ0dHYxMTyb0Dh3iMxMfJaDIpfyD7sIcYf48NDaU0/z/e9MmgK9eHDOAFLnaf91JKVZXTl5NPDP3gmhwLd9t2/9/74NRlAaYFH2hq5CxgQBphKzORhZri5AgQPqduHWQEOoh7O4gG1jBXMHa+q8EieYAlXTl35xxWolX9i/xbYqE3hckuh8pVyj0SDtFjpAPh/Ud/mV9kLosScS81+Vg1/0u5X9Vx+O9xl8WfL+w/JiLmLw9S06qByMhOm1NL+/SdnISMKXlz/p1HBQwdpXDt8uGB/ylN+1f3sRyyeXeiowqz9ezEEKL1dzQfI0tegELviEcUJ113EyvRatTR2FFbMKA3+Tsa80JqnOB00Vr4lhqKhOSCUNNCkM0J3AG1DMDSdpMgQhRQUGi1CISJpnkCQLJDGkVm2SdLfkX2TQPSEyZ95ZkHVTg52BG3AJXm3RHUC7+uUxZt8KJHSRievwMVeO07Typun5KL1Wwev37tTtEuCtGJ5riCHeiBeDEkCLSIhYOUrKbu42J9Cl+jPFMDAABT15Gr32SwnklPDnf4Y4ZFsrBeGiYCHIzwoNwY3zULvZOsMYSYkc5mR3Pz5D714eJt6Vzj7BZ5BbFbFvn4JMnx+d5E6KXJEk7eJWaPGtQesaK+BHqUTrS2m+zjmG3f67YFmyjJJ7PTXcSbn18nd+yYBSPF4kQO2V/nhc805iAAN0Fzrzhkgd58vcGyhMe4KJ1Qx0TMVOlUjW9BEQh5cfhVc0mGwa0bWxWM0KC/SXwA/LgxRGeRHlydkBPPOm4+214n5/b0vQ8aKGbORlXZ4u0XCMvKRLo+VIXa8+2r3qjtowZg3S3y8dQ2T9uy3/IJ3Ei40cW5FkSY0JxZqZjmFflcBEAnw3SYkg7CERvpa4BaWs3NpDI/zSVn6O8Bs0Q9BZOwAkiIMkRnZCIwltLxBTHwdcH/Moqf3U9RNNsycr+MHuqfIzgikbAqjRMN2Z8eU+P3j9SYQnylXyDZowpMH6DdagloMyyhdiIzUOKOo96BgUtkO7b0EhRklRVXEoBaGTt410N+RC8WsjNuSlWEhKidTi8NjjAjeFBLfrQaA96Z4qrS30LGqauGopLIlslUNmZzXC7KUOYTm4NRKqgjy//u9Fu6OoFcFvVDsJcJCEXCeVwspI9aC3KEYN4UWsbHjUDe60Anw/H/Qc9h+VV7xgET8kCcaHn5GMWTx63/npTAMXfLL0gkFkcN0144u814idchml0PgHYwMUulKx6GR9HqezxEm2KfrhcidOOiNBcwGr/zjwKdfjJCVRbTaAWJZBt4ch9vEzqnAeY2M34+zNsESQ2cl5Vs3hSdppIhpVbU9T+w/byWG3LQg2ZHWGBfDw1Loqauru3bDfGKCqXtquSCycsIHRLVS/MuTt4UWGmIXHrvBhNfSzwSR+LZg+d/T+XUbxwjk+KHS/bsjMVTcAOauiz9YmmtywvkIrfBWq/i+E0xtBV4oI/kuXFv5dFtvi2sisyLqgY59w7OPRbrC4vR7OAWNtQLZT3yZW1oyfh5srpT3oXDbkB6lECqcm3JNQXR+KESPUwCusriyDfi+DriB9fhZfe/5dNPXMt2ieJi6JNgvJhmyfowaC8ryiaw+S/he3tUrmKPhn3blQAxMSXPquHs1ZoZdtC8CzXNGZY2aypkj+ZhYNh2KkmircSiMoAmqZXuJ03RJVIlcngB4hpX1TznsM75fNbd9c9WtQvFa7I0XA9fxTI/ImuhVs91s6oepsO2sX2jzS+lmW8k3xJ6vic0EowNLvjmJF27LhIuVZVeiBwCNzZk7xNqiQu+mZUtE28ZTwjM3zxO4v5DtJ4m0k632lmxTKLM3e0V0P9ku8kfKwDEVQrp6V1eGXh3lfnsl/p0/oaB/tU6k9Usv0/sAL1gWvKqRD1w7bM8+vlv/d2MGsLYYvzYIs1p45IBPs4MzZHCnKhUEka1pz6L6g+KvIJzmnvDBSkMNrC6p/eGt205x9cSy973m2FQ+rGrWI5S3CGdDmNdFRQohkVxLCKomrQE1exX1ycbjeGN4T1uu4+AkX0u8dtbYicenX1Bme+FAKUzshaGeCmiCg8LDUDNGQ4abxw9PXQ4s6U+yrb04b9D05w21tOhdfMMAfQMP0BpDLqXHws/Yn8ET4+sLUnb8ZT47n/Xe8369JV/jvXHbMq9LCRwmSy92Pschy+IRVXek/IOir3zmDzle3XXn1dg/0vDH8xFuONSfCsAtscpKHbfKVUOkkCT1qbcHtkIcmd3t70yJfST34WH+KaduEbUm+rBMAL4l7uIThYnXei7netSSN0wm4G5HK9B0YB9fCYyCe2NlDkoXaQ+Iy6vGC12PCcqT2+BoHyllUYAAuJr4A5iQSANWW7z9rR2i5AuwTHsQsxdD+yJj0JkUERnzujDc4BzrhfBhu1cavYIevPNKF7s55EjcHLGPRk8/wWBQoOnGpybUyHvov2Ox5tGtohxXyhyT7JBNiKn7+Tlj9OulJ1A8hl38zmFqMzBRKo9mY0zR+B2CcwZfzFub3esnxAm37/8etPrpTWDOSlXPkB5d/24F4sW7oVVKnEF8U9pII6qqhB9U0dL+A826T/v2eO+r6D45HgZVUd8VHmiKwL8sgzxYtSt2aiciyC7daB5V+f9nyTOvLlgWMclDL+IiPTvv3MMFukfxpdPaDt4zkVWsTHJ5Pn6Sc9gk5v6RoH9vAG3R4Qe4CvQSR5VKYiQv0JJjdyLqD2ipMDUSVHfgsbArDLnFjj40RHCMMjlvBijm/j/OBhtHhB3eSGiVeTSbatOug7sxtuPgEysV7HNcfLYwtUAuV5qYzvutMvKT/1UxOozTnbM/FLteojs1CJ7z+9MBce4xsAOMQQpGajEIDDN1SHJPW88PgPfp1jSYGWGXuiNa72E+Px1R40YEENkIidAl6DubiWgTm0jguVEMkKrKKA4e1tj8UOGj/PUyS8a/Gzo8ujLjGdAZiu/hfJsnb3MxUvi2QFmrImV+JvXlv6P5Qh2th/LRj/wwp2BTah+TN7kJhIFOwmrP+lJQ0eiAgSZf3/t+CmfSPxI1uuytuPOoeiI7nZJTrsyzGBEQ4tSvz5Dgjy0eeddBkQkWzuXnPvOxyk7OlYEPlB+jiJXDP1f7Os9RxY9b2zbVULEDSCmSn0xV0sylSxLnnHU/cS6QB2sZug4m0lmMo8UHLtHEcP3fqegOU3o83RAOMqaD+O4fwVJcZ5+amiEd3AE1UZgKxQMr2ZDpILeOyFngXw0Q6QMmOk0Caw8HpPomz7Ork0OZG+IuedHsa9/HruDwtVAoS9jArkBcmy1LAQJsIuEm2CMwug8xKJ1wadOwUFX1G8WM5IVIeFRCXATCEIqgBiqREgmyJReQIr4jKamwXXuLVLNDFE8s/2gjI/tFWAPFiuub+q1al1nVKHaJRip/n95AsiJd+vZGl/UsrCnW1RBgcUz1Swp6+DYiQlD4ZLj+6uH/XayI9ofUr/RMi3BQ4DolO5GL13CjW01GiZ9EmLa50cfak/yJf+oLWbns/G9HVcZ+Qihj5vNyf9TBc1ZWu1GtIUAuR6lGGtRTBc54AuyI02BWKLzM3MDsBe1MCIV3tW6asURKziVL7Z4mNwVSMVawGlR9kHWff6/Mkn3QfTZAzFCmmptkrKo1mkoTRcXsEwbsgGkRh1s6tI3Z2Smk0bjtQQDED8Y30LJKbUxYQkDnqe3ddyJhXPeChgrHP+KhExB+rlVAUWPBJdphIT2ybpUijjmlV+qxBxDT9xDOuP8qdXa0a//vlGDajgarfZ5yeHLsDou6T13Fhj40x/OZ0lAhvXzgLkRYJcLmd6XBiyVtarONYx0NzIDojUeBatCkSXs2WQMJyTowoQvPb3AcMlq30yQUsup2rVl9JaPJnzrDqnsybQv/TuBJBjD+d+ud8B0CetIyVL7a/eZ565tjAOWOKVJXLDSR6KTnqw3KMbAqBrIOToyLa8F3HVufeT7wxOgMmmm5MqtNkLtIFMNco4AvbjWJ6unxWCa97brq5MHVjX93TnqXuOPcAuTAbOeol9WQ7FUCVBBmRmEyIRCWQYjg25DfBtaahTWsSfjtjNvHX7U61d9dtIXYoQGNoVfBRJsbx1xctj3xSZtYi3/ODMMAh7Is4QxVOHQGkoNu3/FBkNB3DLatkl9VT+7lxbsFDGH59PkQWsiir/dsE6beGTANJmyEBozCBOuGLIB9FwCALtbuRQYpUD0knyD+o580vNgbP4AUSxJmIqIgh3S8UUCRlJ5YO3L/Mf4Ch1AG72vAP/VbIf4Fcxf96zaLGvD0Z4WgEtQBMdDEe6L0EMdYI4G4vzVXDw66v7B/EllqXLp5vrMJN8Xiy1w/9maHSK5/7RIYfXxHCJZJ7bi3Gl/dDD27EdxKBIxk+7s5MZN+1NhtDq0cnxT51SfT9D3iR33iFI7AgsyBI0owjVO0ixWmKUpom6dZYgxofU1RT0RaS73TwWmsbtZLC9rZ16znIOMSewGllid75Lrt3+UtIY6copGCA75+LGw1u26DQw+9WtfZz5iIRptgN7jn0C615raooedv7Kd6DEo9pwbDUDcjz+AyTLfeCvDQJUQpWBzoV5gWqPNXI1jK5el+I1r30/ZgCLPlbYp2SF2DevfqqiAQUZvHqbAgrtN2eaeQdHjAWqezJyrf9gQ4aDFKKN0yoOy2gWQFYKPcraEO24dwffAjqUZyT6Fbd+Jqp1LgeJ0hcFR1seHtXkzz2rWNgNrcl3D26bryZEWu7BJc2izrLIo+nJUgrrTdXwrtXr66ud1lMY+DkcVMqduJjZ7SXtdA6pKnnhZXC9FaDPusQxNbWaEDPzJqihpqLpAhoJAhIrhgLRvoaZhPOVRvrcoSw2VnBsXONbpn0EE7PmFYuRKGl3odO2NY1eMzNoahLGytAfPzFzQrlxj5nY2uxOybYMcBmniO5AtfMZ2LwUpai6szvBvhc8iWbYYoKLABSFgcGfXmt+WiP2bIA8sfvD4zuF71feRIG+88UpQtA8KBDl29NmO0YwG32QMLOgxGfyBZI2HhxTlqLm3kcwP75T1r6BkqCMHq3jOMk4WmVQNkexYASLdFtaObJMHrakKGYB2UbFbBtsmGwLivSXe7dGjM/xXKqBUppkiT5EpS81FuBCu+dGXv3FWBric6xhpTI7UsJ3Z+XKcx14nF8gBM44Hhur/cK3qdbf2kTKfXzp4iIPU8DxZ/znS/aFl4D5IwKzzKLwTbiivlDcBU0hGdkOa0mEht6MiNLJWppUTUAxAtrS0XMK0in9vxRe+eruJRTdFUMBZyxkpdiouo0gi/q7aV+Q9vTF6khYUfQgq8hsYx0uqHqqFL1JHLynBWfs6VeM5Hkpp1HEMml9mMQBn0k/MtfW1E5rxZ0MFyUUwiSM0IG2iWKIEKLCZfAB0wjJThFGkEwFXL61F8+FORPSb/bskehAWG3hAieZW+xvUHhfOI0h0CbvR+HNE4Y8UEK6ApzsTkILW80g8uBKjyIQMFfM2uLleJQfEWDP71OPQpC6YRuOr98DCX97gfi0qwyox7BNkychUFd0klGaumATol+tEFPxkNEpLzjVa59tl2Kv4avXasAaM6EQ6yQAIljOhwB/zNTLBqNVR9IMkHChgY0ShKrwTNg02wrgIrVA/V1TWaZfhATzmIXFojJKxZQwjJcW2Ip73ZfIAnDUMUCugRu2ky+bzhOENytySr7cOKAexLW0iQYoWYzikID07sC0u4EvkujF1lvOZM/0J7VyrjI5kJuRT+JMx+/gDl5CZwUXT2lMINkYr46FIpq5dQ4rx/6ocKN+5gOdp+AIL3IjBwPyAsffVHU4Ld3qmIjBZSnM2k/3JRxbwzc6Rxu9ygeP+kQ8GuEgZ/h2vfJbtDhDcJ50JdrJa+s0sdtOtZOU0PyvBSKGsMR5ymaviS5CUUpJXd9zbTAB8FLACnLDSjJBUTm+IoCznyi5CyxqjND8852dhOMpeLtIm6DBCtrU1ZRgmq80I0bfzUHcDTAXGxuRGw9TJpLPoB0KQv45ml4KEIYxOClbG+Iy2tEYyMXMRuNa5phsF2oTZUvDkT10dQ5+DoagBCbH0smphquJM8DmK3qpkNoanoussbkt1SHOi2BXK2pp943IXl/3wWW5hXxqvT/L5Cu3ePhu1wILKSxXKAGSFCkFQbHNUzhAufo322fP74D6Tc9eSl0RP9bRNszc2/U0+oMbjzCa4iZTDXU6ptLw1GKZWESPQmzkBllSdXQcJImaeiE1wIUhKAn06kfTC2P/g8y3+KekXSArpYxSmsYxea6O5aNbivbv+hkjIT2Gzm7/pNzMWBBrr/ABUnLnuP0nKpNdOMx5oVYfELfg6bd0+oIE5ls7ETVqwUwh6FA9xwjeJ1XS0L3OYAI2g87LHcWh8cNa6bJF/uDGT/ce1i/CEIgBABBuG8oSpuF4Jie4nC9UR7cAkFZJA7pjRc3/11RokV7KqjYBKkyxqRe6eM0x/0uj/tGeKQWIyQ1eMUB0dseQkeh0960PYdaevAQZUne1ZdQdyl6LyWv3BCPUkHNUIygJd7+lQb4UOpPPRTdvuek9ZzYtdbHlFHu6uXTNTgdjKK9H0SvrPfYckquLTg1dWF/QdOj0ApC+XRu3+crz0nSbMzv76E3jxbe2c1fb+mYany5/APIb+LJOrUVl5GZZecm5MTKEJ6dX0SwusVEYzUxx6GBuP7suOgvyhUXXxM2/2wGWQp2XIRwfp/ipulxDNP85EGh6cwypAIa8+Hja5x7hWG71r3BPcvrta73DXkfslsk/IRWz5s8vCztI2Affq/holXXmOXRfyovivngNf1n532jQHNyFNNjarLucKzcPqUF7ZDHedINvUr6t1OMi1pl4AdA3d+uXajmxGegHzbgEnRBsb9vxmodtHo2D6vMBXEB3DDwCeudR9IvpmCPzl8Mv9z1dWqcx8OkVArCXSqjVpfvGpoqqgvcEW0ksE+vWtVei+kXPO4M34/DOmv4UTXP7ahX7qT/aPj09YTW7a4+8S2/VnLMtPgATXu/xaeNzY3Vq+ABk8GnSyA7rcLPsf32FkIHytXwcqjt7+C2w5DVsSh6caaFnl4mbUwbvR446FJSZlIRjeHyGAnPDUmdXJ5TQoilflzHwvJir9hGL4KhAid2Al/MpXdlD5WUF6eLqSnVeviPzJSBoujJg/d218+TWEbasjsXBk84za7ZTSj++c81fwEPw3xEsBBJw/3FSeaoR8Ga0WHy+C8KOZtRp6WWpwDOO9JcFibIl61CCT8G6NaEkjJgmDcnM730cGxMIYklgaI+ymzHcrW+Mi81WGoHXAw7n61MUyy5+1DJd2LJag76u7T2pvuLca2uYXeH0taaeXA4/PBLXaVg/iwCSI7zXA+Px9DyJW94Cdv3uz2gLdDqsqfBU1a8e2Kii+yd5ubb/XGP445iMONnwSs8VBL3YrBLYBC7Nv1Mx4rH/eZ7nzQEevun6b5xwZcXxKvzsMtrDQQ6jDOaQ/N3+I8Pvoqhos2/TsVQf7F/ueKiqtxSz03iRwicL9/HITqbTX7fOiTax0KOnxw5UpdRTB8uBvgmmihJXIgbEGv5aaJlUbogpjfrDM4Bpq+8GM/j82hieFMfYZ74f1WMc6+TN7Y8DWgp4xmKyCEtMRZu4wYszOP+6wAbiWaRcaaDfgkautFcqoIVfMdwHgUkQec5KM2rFPO5zBrEDRjpF+sxXtWjEPMUPNnM3YowOAoHojwtEUoyN8s5AKXDyhjmawVCWgQideu04gkw1MYOBhBhWbf6Ds4uGjFf3dwzMgnQEgQe5Q0t003cgkk6GcuSxSWBeBvRBfk5A39ILNtJZkoTFsRzxmyJxvbYnlBat39uwBrc2BtdgxVomcDG1KPIHW+n7XE3xDrpohaXhGErKQlm/tbhHFSweSK83HkdzOt+Mfc77hC7SdrxlGDa31fEMU1YGDJCOESTeP7i4dzOpKI4oMBTOIiDkMTJeV0P42iG2mLj2DUw/hMfkaTBi/6VY7r+kmd5ejftPPDBpK/+t4uLW8IIGQFIIQ0AOuhOgBIIIuZtezaEQeHgMCKS8A7s2ROeU0JShgFs/aNldlANVthwD37/CC/prTWBjA8Z4K/jeXYqmI+0EMqEaAhVMfvilA5yeuBUJEF9R2/D3XTmUGi8RIbpDM/geuDNWdp7VgdnnQ6hfRzMmYdQY/a2rZcdnzfdn/yhiGXm1XGIa8wdD6GboSPeuBJP39091IrJONirVsoif+75XejWyaimXp6kRYi0TACLYHpCVOV3PTGvWmQLcEsaL8MiUnEnUc9Y2QMPdCWQOMl+sP8eY/XSxeYe7yZVDW42QtzX33MxCkAdRjQvyeJsY6g02hTHcRGKERxRBktDjWmSw5ITWDcw7fIqMtLsVrVauC1kpMXNIzygGPLGWGOaIHK7FB6KhKbvNahydJFNTDKt5lDyIj53XfpIQK+Kbf11SxR3CNymYuq5cPva+Nzd8ek9YuddRt1Gbe5qYZpIFKU102sYIWN/Wp2X4YrZ7SCjw8e/wcOr4ikC9IB9MWun/Eonb7Fr5425l+/I/XpgH3T+jOO603r5bVOzajCiWqEafl2sE65Byc0G0I77UUiJXF3Iw1iIXJ5WgW7GgYukLS7KYmhOGKWC3LuSmBg3Dk78vx38+NA8f1wANZcHPB3YpYU+lwlyeZ8AuKMzVH12R6NoZTeOMWx4ChKsSAZnCr7fYpYUnS4TxNx4FzGxxGSMEeZUB2lIpnKA5mwWEaElE1VQSn1wESLUfzto0zNxdVbMenujAotfu2hyMy0B/vix3jL3+gevJPDGPPTU9PvCgZl1bl0Xrfsvq6iCAGIQxSgVyCwExPECC6A7i8UP09tdX/tUJ3o4L61KIv73/UqBVHspPLgQXdpcsjmz23cOiEo1Q+uU3MgOndwu5Nt5MNsltwn5Nl68zrmLvzKmq/cSEa1NLLAJ4lyXwi4W2AWww30tfxMGmLLJiVfAgu3d5Z2zxqDpR/VUq4e8Z1QJMHiN/mFPlpi4P/m5il2vQeqD44PiWD+QFTZaz6xbRhZYEKB5qX2eiyLTZ4MuvfsrxOF3H14ae1qCxG6PWym1ONGiYEVQsSokyIZcWDX/4sm+r4palTfYFoHPCoLgdbcKX3+Jf5lJ+73JJI237c+lSr/4XvevPrWt/VtIp+BLBkti2yqj+TJiOSVqOe+ATmo6BWIwEi0sgSrKPyxCfrLgkh3hWPPqUaN35BUeX4pf1nWzsCyyKei8Y9Xgqvvosi0Kb5aP9RUDo6io74aHQTRB9HDfpfyl/u439DW+f4QYgnGjG8XX1Z3Ad3nCHiHt6KOX0DeoBma7gLMnDmsFGLSnbLHtaGCIr8wYxmxqihS1yT2RXBdyLj5YZAOun7zs9IzWcfo8r/kfmrirBZx3a4gSU11gl9iG8Hk9pozrs3jR9aVLZay7v+uit0+rqmxy48ocAMroyFOdoYmbkWl5y6a7xZAb1y8veUfssDqwS86Z57ovoVWkIPdM0jN3EHi5VH42JfDggI+ROWvsmSZu7UnoHBiUid/BpLXkz2MCEdpSNjato0p9DBV1OJzsv728451rij6xWwlMohxbGkyv5FBz/DI3/b3KbxcRH7bzLnLBR0zaiOVUSLstV1G0Z1EWVvBRlALTKA1Wo7YyuayJtRXUrTaLLDgzss+4xiTSjkx7JLKlJyWl7HPQEPryYPRk9V7VqGh3Ltu3UmgkJrgJsNrniPJsHzhVLTYqW5sH8yW1cHwwaq7ocS/iXTrwXw1DTfL87j9w3oIV3+rS3VxIqY57hfDcf0NTbLilUmlahKfDe1rr0LXx5Zmv1r52bKNeNKbFqVTBolE4SCkqK4mJ8CwqRhMn8k4yCWsurfBCXUHFqhSXlNYgzz4bhQKEBXmQZEIYz+KhnpkOy8O9d0KWXUa/rqRgvyw/UGJRS955fH2vOJMr9YgeXaicXr8g4FlX/PfjQP7F6oSzchWa8Drnnzc/32uMD0DTCMtRGCizRPOmAQmsHAt+6HVrrCLo0hWvXSCJPOO1iu2vD6N/dS11KtaDbMnJ/fwgvhdSOV3UxUWCShgpqlJHGvR6YMr70nedSxcaJDw0CS9q9+EVL5K6KIfuo8TFCyPl0XJGbqQ8oVnOk708YsT/SFIQ80GAi3FXOJjCml1oajWDWcbNsJkgRIlJQFoFDVWqvbSdLq7ahcrfv6uVeuBODC2DdsidMI0WlN+PZAoV8bOTdGw13CNjAGMNzNG7ukCj5rjPWBAl8srdSUstrwVoWhHi4MopIsfrpJ6QcaSVS72n44L/0XJ6D5EBSj+TBcEpeiOdk+vNZJ8jYbaznw2g01FBFXSFLWQolF2hnPTt+geNHUx6mCxhe2Ow5iOO1kQhW8C40wzBruoJnaQJ6t70KvgMkRq9rCNImhnpUK38t8Fv5BaWTWLW6XbvYU04veJRNRnnEoI6DcsnWJ4jFXe/YVEZvNtw/oFsxYvu01+wuab3zvGXX2iN0s3z3P88wYJgTyeQYc4GEWPaqzbReF4Ldxo2pwi1EMfxvMqFvZimQ8PyA+Q0er68UCTmU+syJX8OLvvcxGD6cMluevXfriLTsfOIwFyvWTN9EBVRwyAOpm0mrrZxyV1gUabdGdpDh5vGtRaFZDOVSBtdCdP8H1VSV5zACNnjbrDXUYPorc6Bm0FWuHSqVK1fRSLBRCKCSEBXMilkWmh+0bOQE/H4BWtnFWdk054ePquuaPqCzPduV9drWtdFY00Dt2e3KuyrqIkMm7/zRsRE79SWyusHjQBI1payrD5NPHDu8+GbOdEwXKBxyuawiaBVqJPriBfiVmElkJtlEqYKNFul2c/T137o4HqIGDBOdPyeAx4D3MVMzmkCeF2VMDdda0+LIiH6uUvhNE4e6aUj8UgSkt9aUhW+iQIXcAHXZlL3klFHLgxGIOxrier7TBF4uvuaCPQfRwbts/a2GxVDNChwrSaTtAiCMOSJbJRsOHbbnoFsNqa6vyBI1cjQpfbb99WeGT+acjp1anzoaFn4SNr6wNjd6aabwgqOt/99x9O7ah/P+ZRw/X7lp7Jw/sLZBlVFUjzny8HTuDh+dgQYfFBF9KHG2TeZBipQ6gOxD3QU5eT744lwb+/XTprj0EtOj/otWjFNiSKAOrUTlTHC08YUhCd3lVtbUeREga7rZzKC8s6F72frLdwaFuVhP4qlCcHr5w94Ap+n2J8xaHtf1uz5/OCdoiNZMRn2hqzdlghwXeFYcN7LBHfSc9oSBQGclVAQQDKQkWV1Be1jFAjQbMywV+CCLRnJvaa9X9z34SJpurVnDpMM7CdlV/xLYbkZbrHRZIoWyIr5QgCbu8zmjlouIIVl5v5okB1JfYeGDfoiAopnBIDn8izetvpLAzuwWh/fc1ywd6vxuOoizTQJS754tVorfhobQ8zUgZH5bJLF4yzODyCL/7F95GQ2xboSrIs/gBCffT3vpNtFThqGicE7+ryIpJuHoVl0bxxK1TROFxUc7iPK3rSl1QFqrgjNwxQiO49Sifyya54sWdwVVuCxr+r/8VSPe1aub25p4MerSntcJZLrM/giYNuPbmPmNK8Xx0sebiVTZ/J9//5HOb+/qZCcwMdroOIMWJyb4OF08Q3nefEHb/z7S0A+mxXxHFeO5O7dVFMl9feqJ5GVdDiz/mT3mW9qSWczIx+Q8Mr2O2qJBKlzJae9kqGuIYaIpqJ7cqv19yuKB0HcsmPWSYV+kvDvWQZRwE/Tf59J+vS0wMhLySOZF7j2xwtfWLCmqKDeddpj7Zuy3QT0fZ7Q8WvWPElndoBwih7jgrk9O8AV6pSPDuCWfQAodZaJJJJCxQ0RdBQFb0hh7Dr2aoPCKLXBh3bh+g0hDAvwMSqSl9jPjdnTBKistw7iZpWAyd1FQS+dbcNnUA47Ap6+s8Jye9tmk/E7GdhfJHfvtZV7ADyd/z08h/skm/skypb0v2Hiy8SHrHCYBG4m/E8TO4tjaaTsUSR/0DuBVcMbLbnalBDavexiP0dHtOf6IH8N8HryL1wKLYuqIDX1X16Y7ACGf5CH/gkdHb4CjPzYFYoh8ExY87Gjfcz+m/acdW6rZX4Xg+YKuYhbhYag5KK1hkPg4E4Asj2hQnHicuBmol9HGfE6G1Vu7CmLUwS7Q5X3tjPeLkE8+A838xrYe7XKWWO4GDYNoA9hskTXh4yZv3wOYnqxTBM2hz2iJ2wOErLSiLBN5FYFkJ/z48Osfkgv/Qe6et/ULkO34Mo37irZjvSuYFwBdE2EtTBUZn3oHE+acvvTtFu10cLB3kNFpDyqQvFDJ4l+hsRohutB/4IJTMgxxOY3KqTTZKLFbu+uXgBULqBTxDQ4xPeyE6gv0QAAtXclK9e/C7K9krFNKpOsZj9ClaSn/jFR0yCDitiwkMGnzPtIFuiKoF/4WnuanSeF42SBVC14pjhHen24cBQcSWC2O9qc5JtHY68SO3z9sgRAlDCyCESYB1YiDYuOjdpr5S6tqz1FXve5YUnOArH2zlmjAjSeDIF33tG66eqvi0uIYmmS1tHbhqCKfSHyTNRzwnNTnzaVxDLoDMLk2G8y16VuzmCVgZfbalFld6jcb7bx6W7WrpKnZBep5skQArO3BCYT4ZcKf29tIHT0dZ4vSjr1G3+hm87tyPiHfdQNTHmxnqXlq+sK6m2h/b7jR6szRYLeLOA4Te0wXrqoDudybKX7hJmQj9xvjrXYieSJTcz/v0sHjH7cG3nNVsW/3e7OFx9empbhcFbsAraZ8VQPjlxb3NSQ98J45mSaOHdWNIBlnhaNb8pAof9hYQ1RLlsP3h4zSqh9oXyjiePQC6USHRbAkCjjtf75LuvhZwsfEqRI8P+Tnry5+jtHPKMIu5tRFg3gd1E5SoOozX8GdUjqPup7pqxwZ+phJ6SbVNx169IfK4XbqRETgJvKChZ1to5jhHjTfLdLoM/lTvK1P9QN380J0n54gm9xHOQuPtLrh8s60mj12SufMxC3mX82ot+YNz9rKwTf2My+SLdmmGkzbqEthNXhEcpIGQim9MiBKKqX1n21mm7pAbbal3V/ps3OTLg3MAnwMii3nVOuYG+gTMG5S4qqpwWXmiekHJPgCv5BPIZ2YK9utDeiX6J+3IE6xN0gt1q4e1EwUjavI82YyqFtE/H/q8L0/GOK2txbaEo3pASa+5vYsCHR6o4tFj46fFS75Z1JntF/XvC/mX3jlgViN28Mjcw8AarqzpVbKi0F0CCmWCqIwbQf/akYHsC2vhYirjQ0UlexMc+0L8RY0aIzr3h2cHZ7qdf8lbvAVaA1u0BV585Dkf8KauipQXXHAibEZB37h2K/jlV7aPW5yodR8VyN477uede28eP2vQKNVDClqmFBSi4iP1TeEPg20fKiWfRz5b/P65J0olBplYg/IH2HG1StnVof+S+HU9TXre5cQF1M1rFrHwh6sTsP/Spx7PcNbjgX31Y7c7+lJZPMrGi2DGKqH9fjGjW+tb4SwyaE5l0upwsgtbwaHQxAYAI1fzF2+NE6DkbAk2Nm5jIzc7YMb7BMwRPE+gDGZV+RDMQMQZX1z2Rp/b6T4oI2J5SjHaXE6TbhZNBXwltg2xfw1NGfWK+2BxZr2oOIxDjOleNgO2g/i7kpTOUMozTngnxZAFNy0wK8rlby0w7zFS/B8z1NPHw3w9hAwvOsK8DNk3g1WbcA68L/rQ5Uvo9HESyseiJcXXMWjizyAeOHzuN2ulovi6K5xO5PPSOwx1VJ86iUOp+1jVjnWoManoDNJYTBHWUxd4wgxJtQRR2221pf4Ig/zlkE7z5tfzMDgEx79FUUJp6Ae1bzWPsaEG8UpnBO+pnFrQCWSWlr0FjbZkLPo2cLvP0U/yu9G3/GEszdRYeH78SOr7iH+gArzvJnD5B+6e//cLeieZg6GAng0T6Ti7UbRyL/TsWDJS8U/j1MEt0YDVwuN5OP3t3RhfBtQy3XUxwps1lhMrx/zMo0bJGecz3TNcNX9JuepvdjpGcCEgA8o57leVOh58bHvUkPH6/zFtL+ISPw5FqZE5btM2pe4cToSlGnt04SNVCTysWEpd1sYvEOYmR7oyYUPmxEInjYLGlOqktzobPx+4ONRgfN9Zqxy6G/AOv2kB3pmQw/wYkRtRomZR8XbYVHFraAq/Bi/157wUEJ9rS0HdPmM9T8dL0UaVPWSzsrHWxVtGqEfOfvpcop7QTcddiBsb8R5+9BBise/VXlBDRjXJmlO7mOEITr0N1RXUpdALsFGx3Fj+UvkvXESoL51sQJYAUoGGfRa7BY3IBNdQjiEEpLx9HHsFqaAEZpBwTopV7UQEMf+BiwEISGvpTwkmIpIvM8ot9UHpJ4HFcY3vlzvN7NJSCa7pvJDqLjF49//W71rTWfx3sCpl6csN5j60NbYvn2iP+w3i+kPY873WHH3VAswKhWIZ+UJlheRffn0j5LnJVf4/yDW3Pw+F3NgEVNxT6KpSMhoLFpAbFvGGvE/UtGrfODeS7PfLg3xNI93Hmz2jQQpPuBuKgcoCFT5ayy/dhVxlcnHur7IrV6Mu0PW6epFUgAOAUrDhwoY93Z6bf5tx+wts5S7s5Y4kgIuyo9v6dqKNPbsncgpWgTeNYFdgjmcqsgHQe9l13UcU5/XM1MsacRxl/EUN1ic9bnPjA4B+ZO6zmxGs041L6ZQ99an/tSZjazuzatsgNYGNhTceAJ5G/Cx57/jpNlQhM0DzA2FdUkJMNh2Ip04TR5WqrjxKs0E3D7jTa0/Q3Y3wTk1DC7P5sFgkVGtGW1ir3dqSz0x193WWvWWPAK5w6utdI07t+kN+M7Oq49heGyDG084NccLppky5Y+7U37gvzaGZuVMDAfLN2ewDpGCnzEXo9wfEbhE3m0rdmUNqaLMkuvSUwJpIO5LoFipZIikTqEsBtGsBd5cRRFZSh9HpqJhB0oiBuhwFqgF8w3Ze+7G/67CL477f6l5v675M9VoGP7VWpjUYPWc9sZnU4prwx3/K9F5ElUO73LNXR9aE1BCAVZF3SRIIyNoxv48pjTR6sNE0WMAv84DmNPFLVJaLM6ZKBSFes3ZRq+HwinujfHFyHKIpJK3DtsoivFxmthK1ZVFY2wF/ltFLAhh8GsjR3XoeG2Oz12ZREvPSWsl/jC9ntrLMBC5WjWUZKXYYooMKtKy35ChLmyLMmSWRnUEDkBVStYcppUKjia9CwHcW/YCMY25k1EVZsIeW5FRiy1xZBQTdXKE9r/y+HhcNgQG9D7N4Go4Ku1Tm5EE3bl4u1xoyyRqJxpaZoOMOc/WqfHZjXq/V8tyZjYZULrbf3BosbPm/wfdV0OuASvnSoKtHPbRa/f9FYJq+2S7UOrZ/SNfBTwtpf0xwifxIwzef+wESJCv66lDtj2W2gstk1TTyxnSHF7JfzTZQyVC24EhYCI4T0CT5g38TAIyN8qj/qLxo3+7PFV1tuPvhcrflamo1kZtOKFG+OAQ5FJS7w3MYEuDBlLidQlqX0yzIqMX2wsAo2c0ztqFAgDNB/79G+OPle80uk8JSV3RY37JjnbyWwfozMsPcl8s8cCjrr+wIej4R+9+9NK6YCQQotVN+vfysX9FOuQi0f9vNo8NbgKNloQm6ZvJx6tkpqIfZHrA/wKeilnWUZDPQki37s2nydPbEaOK4Zu+vRZ+r89yUOduiDeJSRBu9ZiykVc0CNIZ9NBJgcKdHuzSNUN0sx+fpAmQNzKLqNnpQ8NPzX6SIQU50aQBpLnVv5vsX94YAkkNWJKsx2ift0MWhsGu+DCO1GQEIOyndwsgcsTyCjNPL5iEuz+8hZtcHHj77fmqAfWvzq9v9iCQXwoYipxj2Ux5tVRF0RXf2bk0NUnne+IgoaL1otNIkiT1YUnkInxz+x1FTMMyTDcLetGaFcUU3ULGe5F7iSDEDf2xdVHTUXdAESImeUfaInvQ6ZLvtdUHej+upm27qmPJTnfxauZo/phSaPBgpsZM6oikcselg6vbB2fh4VEy9lNeALORTVErSmEKgdC5VKri29upKcT/cIYbKA9TtLB5iluQ/G8tp1MjwKu4EQraCZDhLFre+Lfj53LZeqWv6TVwa35zIOc0UzNFhc0RLKRZAnHTqRgbK0Co0mXokNNn1d+fnG7Vb3ILn75SHJf80tgqR7X+kavFV0Z0SmCCC4CrxscMvIfmzsdpNcHsf6Y9UNCRqkrCVlPoCs4ewn1hUyIO701dlPKdwjtfdzt7/uPO3RcX39YO/IqaaR7dtPVK+azRJ71uSEorzpj+feZKBnXPe+zSODtwocnkaqqVDqVirXwNG/xvwp20NSsvrY3XOZ9G7ukQjX9vMobro0zRSaA2WLSCsH7GQlvBPeIPcuRNAAihwVned4ZBXb6OPVfO/GXy/NghwwpGKfcuXJYcmY2cuQiMfCd2aZaRkixBFm9uzEL7gs9gA3FQaAxbInkrsIyJWwccn2UIRI38BH34yG5XngUoh705FdzPkcMaliQBW0YBCC+oAlqcZTmt4PjZy+dTxsebvfittxWIYS0MXrFzyby84duAX6qCNfcIbwpxBB3sAb28+nAFZA67lrsvLc2xVqzHdwIFmz84WueI0CWNmbVQSaenwLoCzGQPGsTlwtoDTfbvqTi2BZJeV1xv7C6sT7H7qrOdi2pgeEk5gWozVZaUPbiGXzHAa9Fw0kRPzj1zOFDClv7A1u4fQsQiTnI0BVB6Y0YQ79nUf3YBUD1liW52R81wVdv9kodSJN9YtNbIEIyrn1Jlb99yU5QQe096vKw5NsBb62+nEi6PbtyxMoG1zgeLdszACIXNTcsS7aUQ7TI9kjFNaam9/yxqrJc/dEH2vnDZhq9Fcc3Az2eT1H5V/lx2yxmo23JpHaGt4tWGeZulJG9QvfdSjsLPACxIrdzn8VAAkTVisv0palrSrjBgEz3VtK42U01X86V7DhNHoe0UF4hgypzWgbBIzzbf6yt36/L7vVF1t718SIkN0v6X49TDE/4HkC5PpVhxb+yRe4sLrkR1tgEWijTPjN1RkOgmAoKV4sLgfbJMQcXVuccH3Xi1jwBgJ6wNZqgcghLnFiQ33My+OQc5G6YelOrkOc3f1UtzqNgOz2F+EmB/Rj1e/Z4gu9sGwfs5hdC/eujkvAPLcGL7cn7mhh+26b3MixX/d1/xifOA+CJ7ra8aaGmCp6yX48O+EvIgNsesSttRyZPyWSfKJzSY+Gcvv7NeSzyjpcF3uBwpE68DajO5ls78MxjiFiGO4vywd6YDva5qgHC5Tw+V8mRT0jCTAfUleg/UQWZV3jnxplp0iAvK0ac6CTrKjHglJMNZQdC6CA2D0RRpqOoOcuGKTzqc3CUpNYk8cm7HjxPfMlxadXPfGkU9rsJb0jWn0UcqCOhlLSjfZIUTVta1olBnshRxzar+4IWh9yAy7hSAWL3fqq9Ho/rW9YJjakK2nvlierkvUfAuDniZEH00H1s3Xd1llNhJzmTV+LSIcoMHSHPP1gXHh5/DTxUmTM+fMZJybabN6n+98rEoTtrn7/wH/290pkRRu+Y5qEhM0HxjkTKO0bNP1RaeWRRy2WkM9Jnx46yF8pCKn1H1wzYL37p4g6W7x8961Kn4ZBp3txdGuwH3FG2lrmSmHQH8O9ptp8fH1/bRdlEVLedFZWD7mRpHXnMdw2YgKggM+7DpuiKcGI2DSU0Ikq+myFO0NVOnRX7XxKOipGDSo9CO9TBUG5iQNdkTxbpMvJeT370WM2KCX32hQNx0kemvRhnyAujWCXTey4/igxNTF7+ZeGewweNx7j/MzHPyGw6tLQJkv4bDxgQP9cSnOOwtMlKeEoSCw9LHtozSVoB7YCfrjac99w+pqK9DMpsLt1SuPLmh9nSDukq5LC6HMSR7PLYadQFu7y7UBcAOJU3FcUk5s8get/QItv0U5tV51qiaW32iX9zunnbO+/10A4DByOP0sQFaHvhxJzxi6beJ/mnf0dutFjugUMefDSSbY3QVytbByVHYKdH2KOn1zvumdh8udDvNGEya3MfPfqh7+3r5qWVeyVJUe4j2EoQ+yqlbvGip5WJhGOiRD1ybMx7X9Ffu1D3OspIw++W7Isg6eXs3Vpl7GMxPEszTDmH2/T4a3143umfd7w1PfRVlhjPj48Myivykd/l/PnhR97uNSL6e1F3evCTivDDbPTgPAwAIRVFIe753w1sLWb6wVxr9njls4ylnt6Zo7Dn/xoWbB58lNlFAMSjTC26YhBzhSDkSkGqhKU0pF1hCLviRCCko9mbaiD9qjyFDGuHTO/rEN5Lj1eTfEl7t0u5yoFk1Ch6qbPT3hf25pl7T0HmMxk2IAOifD/Phb/AzDwddkTA0eez4JUdoRr55vcYnz58+cSedSvxb0b+N6qk1RitWVdWSUmD8zprCNQw4r8iSQ/nR9a2yt3z2d6PL9h5s/t38XjBXc41X5mos9cATq4Mcs565ViMqMk06L24NG0PvVb1HX4pcazARedV63T9KBUNmDeh823lKrX3N+5i1HVXH1PO08pt6aE/9HwOGLd0WpubXgBl9zx8w+KzM7Flc+ICY7rYQ8j40QrSO1ev8naKGlHJXXva5LxXaGbX1QehYQyfNvhiKNaptSkuW9oWO6y0Km5bxkZKge7XN4gSJjdym7zIW4xPcZq2w6tBgVhm/RdikVGHDhsHbse+mEi3Na7pa8B0N0sN4UBjUBoUiRlrM1Cu0hSelxAQNg/sgcuBE6B8w5J8/Xrl5OKP+kMKnBv/R0ZjJCT1yx6DxPyUblAKJP8VfcT8seWikORe53Xr/ZfxZqYZap/WvKbdsJpRT5lqeq86ulPV7YYCwDB6kRtZOkv5p7q3i5nX3ph7Ytf9i9W3KIMSrzo/wf1d6uAgdbQ5z6MQ7xZqrB84Ke9mBgKAZXNesGfJRKh7KunD+NjAVKkBecQvXHH574p52dp23jVbgUFYzcMs6vTrhMHpKEYLBTyJrIUwhtMpohFpEX3iWhaIYlRsYNXwiau8NvcbT9xcXdssjxJiQ6DhWMN6GOCN6miZK4YxZxETRz6NPYmsxL2esv/MgAZTziBhjbK0zJXFrBpDr7/t59e4ctLjvvTWFSoxrCZIJ2z8A3wU4ctGX5cqUjLXryG56wlS0BrU/NIxKfEuheTlWzar8ZfmbT9GfjrW8/UFqO4mUAqmxgH8BMqVKCqG+lp7NseRi6cu4KC3UPtO0Bc0yqz81qJzbh3ehiHf1wem7FvxUsPZ9g0BfkyRFTNV7+PgR5RjuZaeBzZO5KcG+HocEaVVX5dIL5Nw+1sBhy+FTL0O6O8No8uR4ABeq77THwjuG6SQuB/FfFnMdpNIHOV80fkW7fhl8uZk0eV1uLbfgYIrHI1ms53ZAOhUFsA2OYm0xuoxYUxrAnsWEnSk3rq3CW9H0SPJiNbJft4Ob/8fcLGs7SnIETRf0bOvoFvbhwmmopo3jCLpF1cXUmrATKNsF0vR5e+DK0AK+ehr7dtVc8bdCTXDV6g1J6QG/v5CfGsSHIbfxX13dmPZAPACbDkqSUjaY8tEVwGaKhgQRqjVuAl1KWrISr8kSYYAqd4pzgm2Nn1PpLRaZ3mIN1ddR9pNv3aiXRRrJ6jYzfqgwXqrE+hFdl4JYT28iWn4lzIh3W8bZjwb4KhHeCuD1iJ/SZAP7OgXmCRVTV0FaNxPbYLDaBgux8spkqlE7TAMpZ0wDGVdTLib29fgDiPZlt+WTWbMmY/LOv+Gro+2qkC9K1mNHn+ftArzawK+WtSYRVheGR1zJ93MzSN/GhNJyk5Ltnvaksc9Q5KEPWRiYrEsZGOhrQS0QWKrw5hRDpTa/KBRM/xe8oPKngcmvRoEVv+OG3xZm/T3Ae9UdPXL+ST5hpOAjqObBtV2yMQglglDOJPG81BoJgrRjLZj27ozeIL5yv24HCekjXcW2wOIsK79qq6hD3chMNiUBc5lRYnF+VikgaYu9TV+XtDBDytBKsvHdULzZFSx9jqxprFepTHqoIxL7KrMThr5PBIvp6dFews5MDOoQI1v6S6FsHijdFNk1ktDmEHlNW3oQRCLm63gR/uTeFFQAWOR+qV3elFss06pQEtGAWUZ6TQnE2fP2ymgIyNC1+eCVemKDOGUhYR2ea0Qipt9DgPlZ7wCHxEznHfOPJtR6gX9wyY0gxXDDuyqgWp2GV55xF4g0ctZO8VhGT8UobO093NofGYik4gogWObjDIzhA8+Wv3kz3thinjxHrAndH5V+av+ABITvdnsHLz7vwF0dwTnIxj8MyQj4Nc4wQaX4wzMoEH0T1iJKi/uRPVr5tPuzFDYBbQCPfsXp3kYw+4Uev/1ZLOTuUroc5b8p8gL41Nu6/DWDwTAmjJRMHsOc2oUd2K9mjknU81Am0v8Tj8ovtDHnDI9WNRVLjtZXlE3qm/6Qody/Yudi2ysqOcZjtD61/yMuBeOLZ/Hkp3V2DokX1umFYI5V2glpuUwgrHe7LSbY+Xsqhsqh+ICIqCVsu//m2fcupflNGFJbf/LyGu6UFMCumz4OBFTb8nPYCOsVF7K85dwURvGxrAkwIHnI1tpwxO/ENNbtzmKht7S/L5w6+F3L4t4j34eWLl606ekt6SjxsX99JSl1zHeToo0oYnMt6+OKT0mIYGc2KHpiMgw3IJCUVuGCKfk5UyRUFIqX/GKSBV+VPilQLda0DrwCJnUwwivFzuse64ryd+jo2/9rOa67468ikSQyaDGqpjeUtDweMCKi58+h19rpv/txq3ioIBImWPsttq7gGabPJpA3mwj4KEP3i3z7bgYea3pmdwnyS2Z4MDzAfLYLItkKECjqXfevNHej868p+U26+9RHaPE0JHlmz6oEC2ZeBboxUSo6wrA+GY87YWRLhsWAKzeFddPvnnzvK2Hp/U6sV4r9WijAOE69rZcbOTC362J2SBt7H/hfS8Su34Qe6QoCXumewL3FX9TJUaMPwJOqDGrjsUFuuunfTIPfKo/oP/vyn5kFkaCU7/suDp3fmk32JEhfdA1bK3z455XrHVB98Yar5hx3KUIkt9+EI6OXS8FfbzyjAbiAk3oYZcjTmF+ck5INLOokY0L36GZ3a7FDIhiORme/JaUPwM/WoQghMKPMNxFp6DKQcq/9Vu/eobWQseowLTk5vOZnSQu2TOXRgNPvq2PV9naNmO2HSov8/FUYW8lqeV+0fhnLzWppY7XHnzj1An6ABUmoX8ZhwV2kULLdxB6mhmuwEJaFAZ/iZNDUTrVxx48hr6dJv1zE2bhK1AGrNCe7umS2QaqsnC3uDjfJ23EXNsGC4Bt+6dmWHPsPK3DyNdIOzBDukrhS1ZpExDVRlMtN09GZAhE5Whw08MbM+OLzjV39Etzx/wmLzBSxhGOTEcCbqkWzv5ibCCFX14ObBs/89IHvC94akKV1CjDGpZPUTgti6tGYYStSC4WxRKGcEfTS/C/LnDkpkZGBbKcFeucCb5RGhYcIVmrHc4VVMDxRWPvRJGYgjQdsIL00gJZsNCN07d6lvSxFy/JgxYgm3XvpO6FhveKunKKXeyXRLQzKFgAaMUIayzfdPmbqwJ5MThWCNmt45m2k3kW8a0EUyp03z4Z/wU18qXRM5CrkOO9OmXsEYzupcoVJTlXP9npZF4s20ULR/DhYC8h0dFyltryjvfbFdQgcRuxorUGgxdnE7G3285YwRAw4ztC4P3ZcGkzc27KtfOv385f+XAqRurlLkqFUvsYf3Mup1eObVlZQ61tbHjedQ40MZK2vYj4XQ83p0xVWnlsSRk1cdeFlS7rQu+2XA8dtBx4Lv7aLPiUmlRrPSEkt0Q3WKB6MAr0gkdR/7XvhefvgJcHoOxzn8vjSWQrAceVg0KEQOc55+HMHax5mRrhLT9ryGUr1htjd0pLN+BtEcyddXhF5QXXhIGMIe0Zw0Gex4ZBJScwXl/+wTbxlqcftzFDe+ocWwF6jJMrt/Ps61mQPzr0H9Noc16KbhQpwGkCky/94GklITkOgqFw4fFb4j+zvRaqOjOfepGv+eKh/r6KpTd6LZXhQosuuXGNEs8mdLZ/KksCPg0DuNpCLgY/12xb0Ja5HJWU/r3HjZ/JPkJo63FIw4NZ28JKuwDbQfFlIRnkodysQ8eHUXldky5bTS93a9vUq6s9VMT1l4GAP6mrZI4QciaDx1BwdzbJfl/G1DCGtQJehMK0EKGIFZDuAVd0FfJ+QBN/ZgDcEzTHY/ZKseMDvHe54ugp8I4HjyXGTf57gL3oB3HQRQLFdyhDy/Pt1eO7E8JUDmM+qpPmrNoGvVI3UrZKC5aaMQM8zU9S0FUHR4JlbA8p6NLx5eLzN39PqjwO+XUQ+bNXehR+E505usf6VUcH0aeEd+88hCnjCcZP6PPRGB2fA4UgR+NIfwBqtda3lc0vyUgiU+QN4T5FT6mzb5EDPDmlR9G/lsW0SdTa8VIhkTwjbvSJMf2JwgXlwmBxnCiYYflgCGF49ArqPODXZGUtjMxVCXRGP5SQVI2XW9umvXIf84l87pmKlWYKYIt5rQGCKGKuhJehcN9EDJvVp1Q8TAzWeAiKmK+JrORgHPI15F0s0N4ZPpnCsKhmEOXGB+3O7Ce9Z8rCQv9SFlRfkC5zIJnSsvNSLaemIeNOOYbuS6bMPgpgKUeMTAPN9M8EpOC5s7S4KJ+iKMM4o9vW+Eq0P7Lt7atCyyC/gIUQrvjHk8l7DGTbUBAm1qK4VfDWHY0N7D7Pm5PtHN3zl05e07EzAivemm9kA61yDd5f1z699zqVOd7xBZ+TR/UXPy+FTf0JrFEiOi7LEx9kD9ejf9+YymUyDWYdHygYeFBoVB479fsMuIxItuSkoHyg9jYsWff1G28eaAMYiyczhr872c2ne8a+xDuYlMERPCSiCyryIr43naCPUt2zbKiv59HrhA8W0KY2gDIgGbp64GCXeUDN4yitUgtgrP0fS5kSHvBoRUevP0GNsbVjNyccUt1BPlkCVWwlpa1xKjAzWi3msc1WpIy5QN2oHruGcqEMW7Y4omZU3loxzVFFfMlSqHFwp9jdi4PZ2arkVcMerNOU6SsVn79KdUa4sd7nEaDF2QJmymOeD3Up3TyEm5SrTT+Uc95CuVyF/f2xS3nisJORlLrLVAFAi5qK0JyFrDnR5hvNbL4cbUf+ufjc3DI5R4CTFXq0EiVuV+xEKKfk+CgTkIj/RsIfZZRHz+wc+7jshjirj+Oq/ZIOXxDcCeaTfIO+Ke1VlqJUkLATcwoiij0eV3eVXMRVKvk0ftMlqPutnd50xWCjbsPNv0mnHTWuIFesA+eN196+/9UO/M5vn0P4t7e8rDkWv03jXtlyl0J7tT2852PhvhZ0CMbYG4lAyqxoCeabpJDJaupO8nn1Cm/lL8YeJYNBWfOAd8HQMZPxO2xfQ7I0DFdDDapnXDq31hkoY/+QiUbGD6ZvGbgT/27V7KgizIQWxSayYhx2wgwRYMexlERemTXSn480sTz5X78182BgXh1JU2wE20gsw1HZwYBT/nGMDzBovdd588zZKTMr+3SSJZnuPpF3J6g/gcoa1smuvrz9oo//36GfvYGJqK3Z5zvRPMvoSrprQlOINc+uqR1UvHvwC//laPDq3qWhJDdGend2MZCoiRHjPo/c0x22ahUR55LPBaWQWOkjLvdOZmMJNhbsSeDIzBhYn575h7B6X/pmUS9kFHK9kveEkgsWhLGhkPlcbOr7M5hoB4z1bgCuiKKwBxndyZ+0pcFmvP6Q5ZhhH1UmEgwfYgyfQloqDDi/mWM0/NCK9xTFTISjg19tjUcE/lbdb9b/if5BBfb+g/yZmOQiQUPqtTJnaD91yXqqMWHE6oFvDPePc45ZSI1MyCXnqwy3rJwiUA8VXocjidALTlBdZQnxoiA2TwuKa3nKN45ymfDH2SqmJiDhjcJuZPAmR12QVyW2n6h4+edXspBSaCEW0quO9nxkKLgagIcGIGgp3D7h/Zs/6UxuFpZmRfSpfxJFo+4X+0gdPz0od/2JdoIIoASoPSv45Wc/NsMjg+y4vTqiNoP+cCJs6SXwWEP8+EmoFosyHrwRCfatoU3z22OLC6ncN++22YmOTbgX1AdqGNJ1FsAHr+gmOZy1PHaEEFjHS4Wse+h0Mfbnw5nb6o59d/RSXP/eLP8oV+jODYks0bvchCaWQTEdUUEAL0HSI1bQPuHU9iaksbbSPETJoUCLNWKJzMPR009fKsuotSDj6DxiAK+98Lzp3kVXE//1CwEf4+MhQf0uW/rWe2O73XX671TL1hnJ5S81gGZxYyp4tT4CeeQfm7N2xNy8YfEBwf5V42JOpNPqXt3kmoxyP0NqCjSwStt53f95OOp4BTBCZl5TximXA06UjCdWiONeMYufQbR8hqyHcW0cNCruztT/ZXTBGLYPstGnTfByWNmr7K5+ZvGqutxM2Nv+wmg5kKHgoNWD4PSsxr6RiwFw4+6FkzOlDWPt1f3ILF3xiRrGeWdN0JEdWUJ3nGYDPkl2jiAC+oC46IF7kMXAbkbZn5jdXvud8Jf2IdIEkxJRmirJy3w063AyHFJsRT7pV+zrHiU8BcGgDZTJnGzQPNucVmkBk0euLOhvp3BtJJ2EQHhRcaZpU6k0dO26gdm7jvV9k8YyI1db5m5UEcdXlbnmuK79lD99s/d0xnjue+EsmShvRZs0eLvFafFM6iKa7nLW/uPE+Fc7p3tXAO76aFAvZ3O7xbcx3/AAhIyDNMfUdN9SkteXPEvdWOpANIcNsf5gVPiKcEZsU1l5yp7frr0Jyu8udZxdq++zsI78RJ8LWEHME2wZG9oo0M1SeCkUb0b2jDnTKtjihNBzZn2m3rSDT6QMZ60H9zEhSg6XItk1NhrLwLt26jPfqOkokfcpnF7jffmz7Y8SrhWnh6uvAm2rhCeNdWk1jp5Dk9+X9PNAOaaU5Ga61S37Coud9eVfN4KO3/hn6PmZMERxTtoKIRZoAdPLfP2FmzeW5qCWWUGvF3RqF4dR6bS/xmmNn4xBUwig2+QMy84xL8nRtqlGxySphzyffZTtLeFzmm/bNU3nLQCBkFEyRhsl0ViUjY5YpnChKAITsWSneFgkkl35aTU9airFXOu8XsvomQdFO8ix/CbasjM5JX+34mEp9JMGtdTbJzLMuf0v04RM8KBHDOOGnFYJFls2ctmiShT3YaviJFRCtJYMUl3NlPSATwH3bEPVJF7b4rIM4kP0JUrm7Yh1rJ72gOZoSR8kSKRZkXpdzcu7g88FKbqXDfr+HfIyew/0or/Vkp52MdLphqsAl+TLFhjZ7UM4bXDhVJgRntaH04WLAqQdHYblkTyjQuF0oMs8VaAZQMnbasDwHlEfzeiRDlAIdmRM/bUufFFTJEa1vJ8nA15M39AZak9ZYN+X++z17q08csn0DZroIpRyg3URJtkJ0OH2uXygmJJCugfm4NIEynMFNSBdQLx/8dSTCs5khxkSPuqrn0OfP/deEeY+yxkq9pSPxBXbD/0onyid+o0M0JFFINpoyB7CgbDW6Ddse3HCweV4VkZRyMGqc+9Zn4VObf08KKZyuoyuu04dfI0HhxFRhAsEOYu5TrajNkpfhjtlzU8MsZN+oWZ2zea9/tUay0fFtWRxX56c4McahPCUFf98Zl7cLxgiQCZIgmkZNcoSoKkIRZaEJLYge+uK5Zl1DvqvUQe00WBW/wHV4JqCKwWrmDvGXnyh4wdFDEOYJUg3QFY8l4Ay5dv93tHWngo035XMKvKrINFbp+WufWLAExRHTqgZkWKvqopNcNTcHL9lj9hknPQxlPpZxsbGqKtj0295NItCRAxQbqZmhx36ECfcVuVWE7tOdulJ/bL+gAocPV4ml2RffUCutAb10r0kvyBvJgGtLr/uf+PnqoFkXxrNvgTwokyxjlTHIGn8Q+5Gzq05rZ4lt+W2LwGJpZgSdyunJQ4OXuLZAsB2sZPowN43rutc6FwXrodB1Uu9Lmo7Q7CeQcevTvU3YXVG6Xzd/XhKZ7ykhrLrIo/TzYtUCR1xw/eJ4cmHElQWOyRSq8/K4JNUlnSNxGI/FGN/dhnje+EIw25ejlZqtMWyqo/wSFaVP8xDwP1lBXdZPUwktA9bxAShCFGPbJYjZqu5t9CDDZsLVoG8Y3nO/bIW8AgflZ5qeyJfw62ShSs4mDaWBzKD3cu1c76ZRsgd/UHgeBpz5S4CV4I4tzVZFlBhce9ExtwhRD6SS+wm1Gw+DJuhRNuWKAiuHQVQUwJdRUIKUEZUysMowoMenx3tfsdKhwhtPi96EaAtU/Ilqk8++dTcj4YhRVMYoiHIUGJIizpCTNMTjDLCJ2hCXCJRDjHqS+vC1DvSbw/ojsNi/BLKgWT365W4b2BEh/oqoeIf1+dYHarFs18Vf/RBvJiMUb1QzslyWJisfF2Mmts9UnVJUDgqBL/1jdkTNMNHazSF8zH7iI6fX+nUdk0S5EFsxPfdz4nwWapERZ29biIZMq3rh0ElRbp0nKvY6TByyKVYvdwKn1LcTMoJEiOzD/zmOMYFR8PgzWe8PsuSytt38CiEOonFTN5hZVoqe0AKhLf+f5bjlRof5QtPLZL0wNSKjkcdnvvZ4jqSX1U5ElFdNDlRnGATyYQ4AWhhE+9J41qXA84f1xLv66YGKb4g9ZIYNYXtvcZYPe234H9TqhSc+x3X8hm1QtAY1H7NoOLWTfY9pv1h2Z4Lz8bOKKURo0UXhT8nDe3+6rGi9JrEUhu60ljrj7urrnfArogcBbtCFUlsq3BI+HbTQOIx9HFFCuH8cgtXSCbXGc6R8r7siAibrUPkjKEIN63A5U3OjKEExRSkOtbZdQnFNeBk6bUyiYXxphfNPJK/vZF8sztyz+3UTC2yBV6vJcfPcU38exkYptzEONtAbPl7ygJm0lCLs3gfps1eTq8ydgx7kDiWsCAJvYUitmwN6yQWgTB1GIxJ7DAT00TZUdVM469REhvABStzmQB3tuIAWaf8q8kMdAOGSrSE6Rk/KkIxiMG8EKMzrmtSeOk48wE3b8gBbAIcghEOX6QXsDbOO05j26dvwHDBB2CgbTLABLyhEdANbHOl7rSZ8WxUH4hdjdwTTqeAJ9lgPhcWAU9GMqO+KGgHpx0ApmFh51mlDQHXko3g2MtlKRiuq7vSc4gFmrCklEkhcIZuKifw+bOIdfODTSeCgC3llI0PTrCJBArqsHpafXbMMQrFQHLl06Iw/35NFU6oMpcnH2eAv/JTTn/tAuA9zdNNyHZn79auaiZfJR//xlx/qG22HFf5SKZm37j9tAgo2dN4EJvsda9yRLc2WTFVk0rMYkmmsKzDMnRCUWgKqLOgJQQh0TOMKekUqLfxgsb+tLREEGQQMTyFOwbHHnRDjbFmnLnqiVpSTThdKvpv69QIe4086JXL6/yAmTOcXPYIkYxWheC1x6Uysi+UsWivEJxJrf7qsMuQPzVYa9kdG5Xh1/WbUJ487jOPxoNPY2Adu43kKovvc8ELk6roDFvw0zY9B/hoGWa92EpM02mYdWNjWRwdG9EKb2M4N3CruhMKecK4g1xYi3Rs5oVKlv54WHDVah2QQJ3OE+H32vGof06M527gBy6AgfYmKaYPmhL8y4+TakLMbuR1o1gP8okt6zK3ttmCm9alqWIoE01iiN0Ro64VShTLB2qNicNQJRujcbUFLgnGtTuhimrmOCMuKFJyBP1tb0huRklvmv32Bjh2NMF/1hNBkaneBurdrILxI1mQPOI4gtR2rSbw+VAroAzeIUSf76vfMHOFbuHFymXi9R2KjndE3u7YfmmAMcI8EurS2Zs84PFQj+6mblcktZdo/N0oOu24XQ6iViCsvX8n+5esMTxdoGlHHVlJ+OPi6x0MHg/PGUpZGAXcPe5b99HK2aY8eE7uESdnB8/lEw2LK2ZzGcxmK8vzO0ZGB8PlJyo2atgWfngOqEohlHJr0NAQCuAAvY7WTWglb3Qn9mwmR7sllL6xVz74YHM5cxrQZXFOsfNUzU603xOjDmRYZ65QTSzxJ0oLhBchXfXDKitq8vmuz3pxzm/M8hasfEWvm8VTMSJpeThPSo9zY3EoC7GygoLmpMJVohF6PqNZpjrpSkQCTdfn1jpv+RHe2bJZsXLqLUxSDaVKzGMy2dptkiSiJCjWdaYdsYHw6II5ucH1QX2g/9kQ0dq0JXh1NWOq1HqE0CWcS2QymzBNC10/6qDi5hXtz3eXZ+2JpXTyHw7g3KNbiXEinv0wRHF7Hwej9JfGX+5qoMqVFsiXWOw/0qf/iyTiWDX/vFAZRU00PYL7w4HMWKcMltgkSXJVOBeGcVUNtghqeVCx0xewLeYWlp07b/kco/acnvh8C1YQwgqpVEEgC+xSKdzum0TrMxAqS6G5wlVK2suKFbZy9u17okd8H9oyn/suilGjKraBUEfaDHS6X4eqYpqmK8xDQDzL7yMRXVNIC2Ib1bO7YLV/td+6O9lruUu2UhLPZcngv+eJKVqwTUzDzeuD5sbmDJJ+xBa9MsfsRSJ8lpwCrXyABCjgjr+v8tLbD6MbPWUrVC0z4nZQgqVuisRmzfwLp8LW9kvBi4ppcEdKFIfnpAVCayZRkV4TvpT1PIlPS+s4mLnNxvFiG6z2oF6EcVJyUMU5KLYXSHVZlpsJfx69IS/ViigZALpHco6Day9Ca7ka6O1R11R6tEoXLrBx+ZL6IUaIT0rdRrQGmou6DLd7DhkWMMRCBl1kUppq2tTMBb1KterXAhqqQP1SGxjulG4YV97yZCvMZzxRs9kTYSPxCIlEIzjyxjPZwyfO6FEHl3RHNwNGHqdTs2xWs9j8odzV2Ci5vXMeYjdnEpBBZC+UwyOObBxTq5ACi1kR+2DTwpBhhpuVsX/hS0RSRR9U3Vhp2WacuEYjD1w2VCF4i6xOiNJetAyFt9ZiwnCVpKb8eJZk65HzQUTt9FQA5HHeeaxAq1ihg2rmiIcFQQlVMyZTlB/jEFCxLILIAz9khu2QSH5dc+JvgLwtlnNuGR5YAf+QeLMfWb5dGMqhPkZh8YWLZxfrFEMPr0jq3JIDDebjJM6X4TwY0S8hj5hSPsy2JXU3g8/C8GaHYVHWbaAN+hcc31dL3GSoz0A0CgtQ2EQdV4rv0MyfBY3A7WeP0857YmxMIW20isRiIBYkI0MzgaVzm25bKrGcOA8fhISiXdTlBndiX3Id1tmdeHWO/jhNToJ5ffg7NdJZTPAsb6MD7mRQDaJ/JqEGPnLSgPvbdx08MJPURp23H8PsyrtbRJKXdiLTX11ETtsPd9dqZu3obcdlLUxPI5jN/4oPWdCiQhp/8m19BDTOrtHbh15ppKuKQBFp6kVjTrNMqxzSpest9xg5j+HZot/FcGoY7BdEEXcUsTV4bxQ6Jbh6K1uuZHm/OcTc+zIXGORldKG8zDYCb+fFXVuxEbGGvv6y6b+Vq9R/ra8J0N/s9RJ+ZoNo4w7ud6UCbftD7a7LwbVxuPnQ2MViIZRWyZpoFEcjoqPffLv94VvVFuIEk96L2iIwibA4Xfr9ZYYJ2l3LqUZHxlzeT9oebYIKYs7t/XNg5g4/6f9DybHVE340ysC5OUYZdsft74eBQAsvbtQG2EDcmyZ0SmDpnTu6IfAoDFGiJOqa69GtYtTnd+YS90eBWIJ52Eu8Yrnu1qEcxqWlyMwVSWJItVFrz0Nu5MNZhsIQyHHhYQbgIQDRkOy0eEiA8tY4KnRnErWkSE4RnKiu2yNOsAP3omF1t0zQfNr/KyOPUG8AnaSNM3GP7QlyE5o8ylegwmcXWISt77/gjcOZKeNPkLP0rSFmm2tSp1Ot2bovWkX/SCtj5kfBDb9EYHuaLfJ2xqC2V/QIL20gvi7OKpY+yMPN2nQm5ZMt/SmYAhUzCCFIei+XSVjVzkcp9WMwngWmtt2UJN9Erx2YPTxLvnsev2tw8V3E5TirAzoQgl7Usvnel2KNCVQ4ZH15CMaREkeORW6VwJ3UxEiVlF/ELN7V8Pgf8lU3xSMNDZtVgkGm8D8h599G9i1krkIXJ3q69WbJEaQ3kiTrSNvathts8/4WCV7h6JJ3zYoY4k+SKBeMIjEhEsOSPA3EAmAU1Qf9ZgdwlnO0tJzxSilof86jfimpDFHJ1/N3i81CGOe5sNtPnBqIomiQ55BAHe0xx6afl20eVq+DUWrdADmzMbjahKJgDG9Kp0EUX4gIgv1MaFsxvcqhYrUG47Bk/Au/zyx+AZB83CYaUkAJsfMddDgi0Sr8RpleQhOT0OBFAUaBFJS5lH4eChzKPR9u0VV5qlf9VPchy/EgHERdUJ2muEyQhpLnzB6GzTCav2jmz6hVEmEwfl4+L3ktFoV+phyr3xSEQdathoNhdG99Y1TiTKz/vTL3l4/07ZVpY/dfeCs/6mBoYLrcsSF+czMQpT/TwVbmzMyPIabxANFtTUTBuSCqrhhb3gc/1NXmQj2yXS86/ZXbpUt5ckvCsZEszLFef5kvA/lTss1YP+KfYadQ9FksdVy6wYH98dGjk7vGPJ+9zhrRtXwZFzW8nbZydyg3siFwtS1SCqtO2jOIxtZlbrnHpNvPO4hwVycoZiRdb1/iI4R2RvyHS/Vl0ZlT81PDnxiJMGWJGTxivyvvCKeWsEw+3zBrfYkPXwXTlUe+yu3JegZoBPvyA5ody3WCvqu1qHteqR4NN9hTJ+4GTesqJrdgpw4HXzQWNZRnbUTlMGnfd6uWhwgedi7FIR9/xggfJdK6Id8iVui7nhDJG44DbUzB0JdYOadF17CkFsYDqCEfp6dyWw7ONjwh22l28GCkflgkRjXl+FhGyn6U2B8YcML2HMLNyEIWEjgBZXIChFb/O+e/GhwaKihuixlWPLSZSf/g7KzKFS/67F6/Xw7y0Levcatv4IUB3SMX0Mwp2BLSFswPQ9l/kjs3TcS/tm0iH8uAPzXqHI/90dC6e82CdGI02PsAzWLXct1AMWSu3uqsP9VTKTNm5Ry3/ZQe8V/rboray28DclKAR/koz/Je8AILUaDg698KwVU68Xw14eKP6pqnA1u31Ftswpr/FhQDqm6SxZlmurG8ZwV2uGOaMc3MH6v73erw2tfZxwSGeOcctV88piFZh/AaoSUNEShEMeyTkJ/jN5AA2NLBF9fj8FNAoQKrPSE25FZpOgFtcC4MheTekDPr+v3V2EHUfjy+fv8NGwC9Xges91MAsFoM3uTdeA1z0+/MnqgudkmKh/Jf7sFm1P+7XqFBenzsSix1n9yNwqAIW26ZNvehF8d+Dsy9GOWikRd1cbpYwzHWGzg6+glood1HmvXn1n1ebXjc/LETtrZ4kpb5BLU6v2S4GDYgWRmsd2uFtbeGaFs/bWGhZ/Vzan4e5HwYAknytt+BZEchjEpmrFnhFEmWiFFyEiPFo/Xk/2gcI0ll8fMy8vjKsYRXyrX3OMW8Us4Dr1Qk0yxS0fYwobWSa88svUxilw6qy+9qEQ4KcO29itTfRYcobySi50+/nY52omJ0ZJJL4C7cuii3WKDLvXkUX+/YwNZnpxUVHp+BNFENLERpbhX4cEESZEFuas7APzBrPwHOVObbvCoPoeMWEKV6LPaDZQ6syO6VchPOv4IKWM0dnD9ZyE1cAfLyAjjELKHYIIbTR11OhXWK5BkRhM30hxS9KGHfPAnJYSehOSFqz6OWmeYkKO9kIqqTRZl0ozqopkGHhcExruq79TpqYnqJrZE1ymSujgf5jrT0uIJ8FK/IYaYPV532iNVoFsN8e4vpK5XIE+uR8ZzUfVqRV/t7kXH5ZNXThcpL3GcBSRsANUMVNAPe0kDbhMYS7ZZYFyLJ115dLb/ERS/Vmz7lh+GtJhDmm+ID1RP3jcAtkK/7W7sh2SIzTIaWHVVjaKyIu/vdkIMkL2LmYOjIFKZCq5Nu2yxy/GB9bKnild2TgUv2zwRGRlVLGR/xUElej8NuIDyT1XN/lSS557n2tcTxnM6HFh0UGGeLP5GaNb73YPITC5dwnHcJ6tIweMKzIoSX+ok0fnelsPuNibuWHIy80PX5zf1foXf0jrpMxgYABmVSxsmDImFiXWF3bG2f5APXS21Zmt4YH/TgJVJKdNAOnNhCO6K3yjqdaLCAyJCv29zM3ERx+ZoeZsjUBZYqY476xclryElF0/5UkniE8X61rtzL7vcpacKKh0zLfoAqWEyYyrs2O6DhXC2sZMrQHiqO4Xys0AX1wTycDaNs8rvvrdh850P+3WYYyiTBt3EfOLquR8ITYuRHd8HNu4asqA470m1IPnQwhHirbaA2H66zaBPEJcwRqX7WD2La82qb3S6ZSqAToXXr+svrIP+LX3yGgmyiY1OUw6iAg5hX2JcE7NJ3Wza9VZPGz9aLYoP0877xbl15Z9/gEnrzgy1zYEeAamyu516bFlw82QoirGHaARDN/9nY6E8plgZgmNT/QnVi7GMcoXA66JyCFVYl2itikrCYIxzlgJt0o/Hwg04JDqicT95xFf/5Y2cYu++BKmoQu/+Ol5+CkEgjmr5ILyeGZpLCGQx7NoSbToIxZmJqIMdAiD/3Yb2bcLLWmRSfgFdgvfED47ZCdTCYJ2T1cP9VzOBc3QJ8k6DcJv6rEACDtOX7gI5F+DLXOmNPnrkx7PPNUkp/g23umpM4r5lOIVe6ksTS9Fu/HTL41JZMOLiH58jUfmhuynzQ1niSObed+6Xnx+oXAfFMydAW2nRaaGjDSJJJecJXVhOk9E7PAW/jD4sBIUbPHexknluAQ5+W9bJLn1OU88HFd9BiCVlNZR+YKqYJlZRfLUbWkhs+uYUzYpt2hwUrIrP5Jo8jTDvLYcJiG4EPWax/6JvR2yw78jXnS63du5t3KYkvL/3L1onsOizQpshHMyl/KJt5H7/8mf1S0TA6uD/rHu2QYvppfU2Fz+p11CwkEN55qL5cRG1miwF6zeMKeCvxnhD4kXPsE4U2DIZB0Dh6RDSEqbRGgaKlyED2f2f8hGYjrhWC86Fg8gl8kUXpr74j6DuRkgBCxT322diuChs1NgpeuegzucyqDIsMfhy5x7J7LVka1xntH3mwaWn5o57G9/m3HXPTB1fh/nXLMBgDyB+9YRN9hg9OfTIH0nDPy4Ne/yb6HKOqpTBPbFYO+WtxeIQWUhwiMtFlItNYuio+x8z9UAYLpfIXR6eTx3BwcZTlmx92PeaN0V6aC1nyABSQzPSIp/zSf747Q56+otK9auILcvG7WpzB46BO0YxR+14CA9ehase2rMgMn8nszJjO8HkzHs+Kyoie9RNSv230N8b3O0dRHusk7yZgk4jURGH7ziO72rejAyF4fZ5N5zGUJY6+PDzN4Z+N6hl+Z5eqpAJ9x5ToyAQcO/feVI2uW4i7dBGlyfLiy6ud5/fJuNR/oskdnh7JxmzAeoh9yUz+bxDfcNPywHHeiyexuWyCkE3HxIiFfRhPi3OOMsaFDl/o/0ahwgwLl+P8fggcy233rKeurkD83Tumr4f5+CWnswQO/6Bd4vNgSUdSTUoVaz2p0trscx48H8Mq7QSCcfDi19+62bUKCTdHT/v87ONSrPcOpFjD+m904pLbR6Q3DuN2P6R5rZIrkQGv2z4z/fNkAW9RBxhfin3KQluCempgww6A5nJgkPeMTp4ZOl45MCx8bRtZAJwEJG+f49LtKnvL9PP/46QvBNG4vb6c/vlKvuKCTlMoBqhEj9jEYdvnh9HLT8CnPNTfoZpanNAQsGtd/AMAZCo2sCGAeidoggbrbRQRiyBq7CLV3+gj7YrR6ZsXe5UK8yduZzeCaDA32KKcltDdB6S4d4+Y494v5Xg50ZH8CXDPjVJYW4VPMfaT2VIgXaZVRaFZq6/lktfuJD92itlEoZ8SyhGOEOIXWVnR/kl4Rmzq/ZtPG6TTeDmlZQBf9f1vZ++pWpGXyjHCK6aXgVWuesr2HvuzOJMTojBea+gsMmeX8Z43hygk94yll76JwogzyMk2wZkhIN3+zOjeCvuFRzrum5l3O261pqhBdlHBe9MC1wBkWoco1YjGBSAknu3Qb0l6crAeXmeEfk5bqZnoEjEbMIVtCOD2exl4OWGhy58b8LeIYEcp3ejw840uCjianA+13lU1mpbhXEj6qV/Mlnxr6xqtZEytcS0bXXN2IryYYWyqeaXRcDEi1SN/MV5SOMLZuz5ESnCrADXLByjxO+4ZCC1h0skck6UFP+MJJujlWTqfJp2rUiaZzDA+q2dqfEOv7nHgagbrGPUCorHf1940bJxYS6UNMhSSZzczHOkAYcRXHItiEsjFbI8APOu7wgCgztlDfHoLWwuXJAxpxOSUcIgzJG8Lk5itRE7QNluExG0ZeXVVmfbQqDnd9TnqR3t/Hmg1FoGuRpbHw5PcmxZ5OFyET0RkN3Errh5ldeClxto2Q9C59v4W7IbYoeR5YFSQJvrcNoGjmRo5CH4v6kyOU9T0MoMnN6wNl+lTbZeoXXLghO5A/tqQA7E/KhN/TN7NXRO+b5Lj9Urp2AdC49hje36AaQyxmWGrGSmg+MJBTCBCuSeBmJDP/F2v0vYQdZ+lqNX63t6VxJ7Zb+6Mzu0+WzPirbITykm7lCXg4VEng5lFXMRVbF/wgMqL4g95P4cgFVslpNvvVQhuwWjS2o/4fbH/YSuai9Me7mEHWd0i6dYC/4y2ekM5Y7iTCxKSbQdkZmNzPBqlCV+RqrosjQcMNZ2w2isuQmMlKMUo0dvtyXu0hNpFS4hvQJCBlQYqHcsdgjWoYdQ6bGWyy/g0X1nuOcp4dKLmS3kxCO+CYziKoqICFTEI84aS9z6KljJPopwYvnzx0K6OihofvW4UOyT9R2LogvSiItC/0jUCw/zX7Ln8zirvmscpZ9uOhxT0KDlElGK3SlTiHlctWfT3IGFDh3C9zdfX9y1nuhqoMEblIH/UEQ6O/srvE3c4yJ91jFX0zX73+8dHKCUkf8G0pWj5FqpAg1GSSnwqlKAU6kT7YXgovzqHmrt4oFSfvC6X4NhAfwlKK5eORjSspiPmtapP6b8yKKNJmhrmhNOqBZbKHgx4N3YDAft7yzF+pRVE1+iZHvdBdFVRvsAxpQphIfaIhF78s/TFTX8od7RjTXMPwOzgaMJE+IQ38fHW6cWZQFRTasNOdhNewzdtDvT897BjRoM9SSbzE36rymmrSmp2lQcPJLoFBwgQjC/PRUGVtZ8JqcOo6P3tlOGIc7H+3b5ntKUgk9PBAa5TDyVP5paEAF+ctoFu2EBKKqhFUiRdUBUqiKSyxGfMOmtnnImCIqsuxuoHgAiRjDFICmOAIxJcCGG8cgXye9+RKI7qbGEpZg+z0r9KkCv+BISCvyzTX/9oAr31sQA68/Wa/S0Xcmm4PLO1z+BwhX8n6M4j9KLBG1GSzmdzjI+qZCGUEvbEoVzyS1Rp41DmNIkL0h4uhKwrQE/WKrCZNImJSjC1WL9YHdTeLgdtpEAKuAt5lPja5cbRjAhcBGR+20EiXQHtaX7PJxXiyvdNWaVLziGerI6kJWlASfDwKG/RpC7iEgzSxViWLCkx451QIbg+MfEtaamBqWd5jZ+Myzg9y2lczf6qImHmWRPWs6P3RDeDXX2a9hAJc4m+PAabj2Sy45nrPiAhckej9x7mmVYMSlIhCvrz/BDGCA6n45tYgOQdwgP3R8Q9ndtqSXMokT7N3WuL4Lm7kEoFJU4qgW8vL7swrxWEyY0pZzJCimR7tZCAgY2mAvpB2ZIMyDxyYYZ7ixLLj4klJWTzi6B08IijvGruxNbTPYWolEa+9uvTvZnf3avcGW8dV6SwXdJ6+doEk68Q10RclKbv50OfIfPJJIbPAb+HYwUeJS8aKeHoxB81tDU+ZO79dnYqwvDbLtTeWXwE/cmhlfV9pxzU5MONf/5cbvWsIMMq47DzVt5hKSa7I3/nHBqUMGQ5OuDjBmCAPtWaxVmhFW9FKUIap4PGRGFUp2I12DuTVFjcOSZ6DF9sZxKKB4NusY1JPL2LW53X0cuQd1AkHpflKX2mxoaZPoaeqRli3PdAtOPcei7tUzWt/eM4RMVodJbEilKlWUzZyMKiN2Zti4t87KbLPKo7BV7CDs58x2VB+UrUWysHCvwKyMuiGHBX5w59vhK7917I/HYddu8OGnlVxeystoPWnw/afbcku4Ve579Sy7jTB5OHBhv6dY1cxXVeiOCAn7l8rg6egIq2zYAc4jEU2BmHiDb7ExI4YNZgAATathZ7vHjNS7410sWFd8ktepFhnWXZv1c68/sgA7e3/A1lC7H2xtl2lq8aJG04dC6CUHUtoJglMGshPTk319te/UMC3WVLckWkDsW5692Wx3g0398uxNhjmeyZrbFNJz4acTl0v/o7n/0tDUB+kb3Qif8NiZOTGBNT3GunA36jGFon9+H1l8X50vUWM34BrfUMMaIxmNzMm+KsHQbktABiaShGq6AyOA6qw/SsxQJBBpkHKAhVqKqs2oncEhs4CQNIAlkhZrGTCV4I8OqsEM/yaICR1elXpnb/+EOTB965svQWGtr8yemIkaZ5VYJyfqGVT0DzZfEfNiS15pOW3ZcTxgZoTR8JWj8XlY1GUmdZu+yCrCD+up+78oZf/XEO1zHAPkmTxEQoba/Rq0GksCDqdQSSDgauSI8rGwe9LSy/D+gVZP1nwtuhHtL8osflLsDMyhMUpyYzFXyctqanvxHjALupwLvJMBTwwiDDcELkoSL7QLXIBVP6bi6uejHwVuvjyub1Nqb1SyF8nPQxTvyV7R+pw3J5TTaEJVJ1JMmpjM1RvqHId4UmAzOvOukVfVaLmTHIZUBlZDZbmqhtugjLfAtgKwBwPg6J8uHgUSceZb/Ss51FrIfn2QREJl4tffCN3ocatxOHTS0CppKNmV8VHBIqaRycrtXZxhK/RqKoaAEKva8pxVUDxV93lYxPCeerbz9EDQDMikJTYTAR3ONZXSGRnRSkJfutaf40iWfFTjYR5YX+VjT8np6P9z9BQkN4ETI5Uyzr1Fh5nifCROqzCTHnxm5JxYsYheTFXk5D61Bw95oAe1eTu7JOhqcyn4/53UABjcKvW9YQHyz1t/3SGEhLWrbDOsg9q2aSfKYJo4RTU5yPm4iNcbZJ8qE+Ro7/Ln5P4JMb8M5/MeF42299QotxKlMkO3hZme30lKsNfy8TsQM1pNMiaxERLDh+XzlykHxkLwSbYMrGAuH26sC5QDvUhUBmcYsk4tDP7I2Jb/aKimyBuNs6LvTihpbOwFX1w0A0IZSqX9Tx38KHel/fsnn+oz+VmtqB34DoHccMaz6bUgP5tVc588mVA+fH+Hw3rdJZKq3TrbrDDTa6tqK9PXr9xba1m1PgLKqexoMuZZJyhZK0i5MDyZj3jVakkpGJ7FPWvVZnyBn9DilkWkzlqYv4EfO3SVDDU/Hsn/rxIToPvSZal0z/f2rot/Qr/xuyog4Mv4gdS0Caa923Uo4zY1Mrdiv7ktvUorEwS9gIR7iwSLohJ8wTPsLkas90AoUAew6YwPbJ4hBx1p3QSx9g6SCutAccYmst6+1DyzXZQvHGXTO462+flHVZAJLlqLMBYwFnW7v6M0MkKFQyQ9aJSDNruFgXcVHXurixFQjThhZidriLi6eSxSFvyZyP41hYvAgdeyh1q7YoYd8IbjMjg47g8qASxJkgDQlUiJAIE6VKeaOICHLmKhxJqDYtAjDyLztVfCaiyHJZd2/QT6eqdTQ162JqZu5AKT7zjVLrJXxFwY63tFUufiLwXzQmvEkbEVrduH/+UsxS5LX5p3ZlY03y4kbs0JL80aX0bMJDX1Az1brCY3AQf4mmn3R+KV2wsfmKdJskOoWp9cbsc38NWDgvHbD59J2tnZGA3eLAxkU/iZp2Bkzf1w/5lHS6MjFKXgUHWMIH/oCugZFxR7p+wX/qOlv7ImseEItI2cI3ujr7+7ysD75oDyOkeQJchNLdUUUPtY0uUQKkuSlmbHTAAVZgZdk+G2tRlGFlXMTPcDYbJgZM/0qvsRyUBR2MC2kfvTfNc4in0zj99N8Y2zg7xbSkBbQQA+yPepyQdlBChHnQ4fVThKalh6xRQxkMGctEBnlneC/obk8IrD95I0PPuf1T+LyX1CZmLb3+hFdGnLw3v1Ri46nogY/s8gmcBoicQ0E4aK3DnleNsXLSH8YzCwrdTP85oTWjNf0vLUUQomzPJd4T4jhrzbqpDIjMxP+X7JG9f2cLM0l+E1wRmSYglYUWullEqmZJ7kJpdSlvEA0KC/iDCC7G72FDm3JsocLWaO3mrZoDlSVNXZ5eaB0Yn2b0OWTxgtHT65w7bbn/CRhfPoMweUtiNKuAlsQCInFEDkBKeFRFatqAqEAA2Y3CYQ+pTNpaUpkQOU1zrTV6CDj5ClqwZTKR6hpx8/LbEopBI0UosHNgtpeOcMFVWOLCX0x446MaULDHSNKRJ+fQYY5a1Z6lvr52Xfeyyaweperaee/hcDx8exlumBbhjrrlWwj1ya9sTdZvEoMleLfnFglrEtEZx9U4BKr/XvXQEl7sbY0Noda86uJfffOBVPMN6vc2QClRyVd8PM+PeRudjTscOCyTVJt8vSotQqSnXlzmz/UnCqT39cQsTzmxqIpn6+UONbH25MpjnXwZhQ2I0Plc5o/z4++FrbCFBU0o7eHNMIEo26rQ/uGp1YYP1m7XF6DebpuSiO1n7o89/DbX97+p2NnUznsa3Ksun5xV3ekH5ryB5eTUeFmjz9ZIztEejLUPvvjp4zYvwpYsFDogZEkHqDfDIOUMR1NLFi53AQ/9TRMpf9/k0Lzgt/jk3JmCP66YPvb0A5qKmS5ZfwclsOGAg2E58T4WHykaZycZWbbP2ggHpAwggAmuf2pSpYdFA7zjk8aqb0g+DiNCeYLPupfdXiAO1GVnpj7eY4uf++PwIJn5/vsnD5KGH2QieNZxVp9i0Vy04kkp5ecYS1PLw4yWziXLReWBHtg4qMUyMXlQ6JdflsW3UizBy3bxGUpGgbcB1/jFFEngMKMRDzEzbuTAnoPt4bmEAo+CbufPR7mSGgMIBbyfSZIDjLmnRm+Irv9Oqva0rwOiN8MkIcSuCkFCgxBiaQ6Kj+Bo6+av9QGOS/NII9tZ1PhFtQ4wc4+byMzQvqDA0UEPArvjFW2PrC8ensbSQJFNe2YDeqUU70e7N6uc1nML7Gr2UE+TqIJwl5arTQ5wBeQknKzOdiGGoOywQFKnbqpOvbbOHOtUQunHHR0vdON/U8p/9Ryz9o2x2XcQ99V3Wfx/8/UPHezJF0eab91+yirnvXrZ2XUIpT+088GnlsZOXeluN1+l7/xOsWJ0jxkehhobZZ+9mMzUifx/Ijh3ktu043Yy7sU0dHngPTfE4KOY+pQik0N1cxvkepmA2TVPLuYw5xOwoMkkcjGuuxQwD2mJGyTFRz4OmzPu7f9Wfw04zPIT7FqC63mr11SINUzSKZraHx8S2abBEZld2UbOu7mV88rYVlhpmO7+mEahdergguPc75zjr0ju37yuQ+tQ/f7NHegBy7K+3PzupKrk3RZUx2Au+VviP4cBSJfm3V0S4f+nDYvB5dzfaHT1KHUd7C7Qp9CF/d0JejYZ0M0sNM/yQJQWcOJg7Sb22iRU2P7RLOC8heWqxbAIX/gXp6v9U+brr2Y6R+YMd52ORy2nl9usgRvWG/TdSpkuoiivDl3tb71oQU6Af71zzPq8TNeDfgk3snLB+d4N7gmk03ztiF7IqjNfPiA2Pn8qJVi5ZMGeq607Z224IdSxJA1YnomOvavcGuTbUMrY3VS7Ys+q1UnTzVs3lcSzzqQjWRMBxByL7kjY9V6F1XkIJ0vxV9gQx2rcuLcUomcsS6wl1nUNnVbnOqg7q+Lg4xfaTG7mxP4bq7S2LpB3FxvdbKt2gSzJjIC0BlpaKHfKQlq6Z4JsanIh4TxaaCDqJg0RLmj8cll0cIdzWvoW43/rbDOe3qGNhhSrwlaUxnzzhpYHO6ky1fvsvv+MyGwUvME9OdVtObSrGvS9sWG3fCWHyHn+cz7N8k9dSzu7t8l3L5kPgiUVAqUyKIfQYbp4yTuhFOVV0haj5YjA4DEGZ6Pe1c7vX5XxRToDgDEuX+Xa/oGHSdp0Sui3B0MzP1oprx6Q2gNTg6Lfe4FB2WZaLJGjY75pxLOlb31aOwQMEJMfvo24ojCEw0qvYp56m+wOKagcMy2eyNVxmiOe81DiJ8DjVZQKpijCMIghr5LMnd8ztGdKUGhg1ZiOj3urf3eXZG1Zek9C025Y6UAX6Z1X4TgzjgTUs/b6dnicbEVvm2Vo+UiY56DavsD59MpzGFIzanvnjYKnebYEdaovmPsIfruxcmk22IHxonM3C+CSx/2nex9E3d9LaI/hFR7c9JyOUN5WmCjGEdgoB9GU/1vXFR2LObx4PLLclrxJXKfjF8YxU8vUTyDtLhnjemA0y+KU6E5lwqDHnI2qGIMuMwHPuJC61g0jBSxhVmRGuHDXza7f/nq4IKv9tWCLbKA0IIXl2HTzipjmqxDaiLF2ynv0+K8TA6v0v6lTKS5PT04iXnyQq8zFrYFcTMiyxN0lhn0GLS000jydE3LL3xpaD9UREong3KbJX3BWagp9gtLxntrjnnTCThD53469tqiTWw6szcftGG9jX6W35RrLu/lHr8mIXPeuK6tOCpiL146/Tqfz1Y7g5tWOsWOrNQhRZO5S15ui8DX2TwjGUcfTFiRoDQODzZJ5xfRGKWxtmi43qCh9xcXaB1dQzgCDs6dfUS/wA3H2O756Ul7a7c+eG/qU/lOl/bVcDn3/p/d/Ktb/s+roSSedXWLBS1Dd1YB16EN7DN54MVbJojwg5qNzc1FgzAMT18liqB52LzYXPldL+Ib1O9FA7FuqTj+THstBd4a+1V+H7KmM0znS5YAe6kBa7j5FPh+QVGzVNUYqV4nmUasxqmjtLeJP5ZYtg9ZmrFAm55j4A0fK6ZUDZsT3RjriZ6NxMz4Xfg60Qk0OF1zUkq7f2nS/xBiybE5CVlMeQgHjKIaWu1ceWqYQIiWEZASRhNY5Z7aJp5ddyt/Uo/Sa383Wu3qlbybpj5ZS/lg8OyQwD088kDhk53pqjOZar407S82djqYOEAx5KpRX2ILX11bzciCC7QHjLBwBAe3Xv7TMVihHkSaIgsCNf5n1Fyb4m67sg6/6rV/5HvYPfu7YDrhKuLL5B5RaaZJ2jj3RbMcFVmxmYdFsBSjtyJ7NVqhetuxU84ZlWezWjZQv/eyLe5UtP6AZ9A0gJ1l2G2CaShgY3wMzByvlc7t5C3auM4J0HFg5C1v5qKXzN/evX5F8jT+603UAZGQVAEERLGADG75ho2I2zffK1Vp4bPKlNf4g/aHhruRqSn0f1W/52P658ZulCUTuc6oO/stPgvKct7pEZj4bjOjevyHAoHNTcGsIWlShKKUMsbwaB2K6hEopEVltbM7KSvYnPcMP4pmgDjLH8qfVQoywhCT6x8s6fbL0oHDkMSXnLv8K1UzI4wW2c5et0ZQBGllYKXN6GtqGtccpYWzqGWE8Za7Ean7RY5VVtEZqsEZoVlOabRH6cpa5mSeBPNfPXOe94D3X11zjPeC5x7Zk0A3gPZztJoVj5ytbfkmx2FWi8Ksa8S9C81qrfhhtAFZB2JCE2rYSB7u6knPILvs9Cxa9SSxA9/J1JKcRUzNHqoHr/FzHzq1vFjoe1c8yVm3cpCgPOTcsvHARmt9Kqg6zxJGJag52DcCCaUETBhCvUNeZjKqE9gFnI3zLy1f+n4glRDpb4nDA53vkToAZjGG/9AtSkpxT5cE151uX00ZmWd7f+zdzj/+tMzfKnLM0iwd150xW4jrrkR7hn03xrIIMsQzq0yw8dsBvFP+IJ8dfjtzheY/6UJ7jcX6dmCMvIS28M2D4qzr/IDO+wZiy+v+HZ0DeUvj1r6HgY7KOICPXEg+5fMw6txFZ3nPrLIHAjACEDV9Ssoun1NrK63pwO58olc+qmV1yBVo1HBnspLUhIa8Co3l/8mgp6ZBKmlE0VpjsTWO2bz3p9ZTJoAzcHAf8B84tx38Tn3sv/O4KXAO8WgLEIzkoSJ52LY5aN7Tbsz98D8jVLXpz8V4Dl055OfBGGnvyCsLhqy+u1w5kDrVibOyD/ZQlR9KN2Sv46aw74+ihpQRh3EaLoTQOpZuO+SpOYFdnktXxM+97IFGjPFfg6ShQFNjTbxWRJ3wbP4nCvtJpyLhUfBV8Py9foJItSlYVuFlJVWhsiU39Sx3PwSk5lcgNKDMuFkWlH9HtNqBAlp0/LQAhHmZ7enE8H1Q56B85h/r1WaZC8zP/q/buuXHHZRjl/c/o+b8ARcPCsIQlAwn6ObqYjBfpHw3N1GKZvGWRlkezcp/T2nXceqqcI7kZic2kMrrJnkU/DMBEJhQbCcrXFSDRal/VndiK6xZGZUn9NrEXm+SsWtv3SpJGOoDRnIBC0iHOp4egzScDAi08pdxn5iS28j7l6bbQFoT1BXHCY4clPgYeMTKjN2JwrNjYHltES5cbIB1Yin7XlZKST52UdLYh1nOHj8xLfknqP8D87PKzUZV/V/+KmP/byPe5RPgzK1iGWEsnoy7+Xd/VuLeGdw6h53qiF/pkdqv6g5KhjQWBO+qq/YID864JfM1PfDsh7Oq7HuYXnyjIh8Z1Y0/3vwpsYIapyLdBT+5x42c4dGYTBynR2MUEVPMKQ0q7BhKhOzQUDbKjxr9mWLsGkyMMn/NLJ1f+FqmOrP2C5gBmwz3VxAJiXd2vApoljXwM8gvbXptPjmQASodQSmeABZTfBYiOAaaV90c//zngIted+cKU7LIeQecSvJBU7nx8qpTuCLDAp3OatXnvdLUpSUiErzFsxCOLSyaE8OBhxaG4hRxL0CVLLpdhGd5tEa4WWiQyIjvRJWZeYwYCeThPe4vsMqdy9R4/2utAsyb0c5mM3t+VTo/VjRrtoLAi4Puv5+ivUdysUM7PxzruOuH7zwcxzadBRDP+b6QEAtpW4c6oaI3qWDz3NmWo0QMJj1E9SqLk9vQ2sAaQ80wzYIbJJBcsfJGVaSvMd/jk+dVijtRgAnfLmLdHd2Dr8QG560ypx5M3SmrWwvZzEF4+Dn5hBBuu1J/1S6VR/4j/O7OUe3mc6OgXewez9ANnwKMLxPtj0UO8PUyyXYor825D8cLcxP1YtxAQiRo+FA/jGIn4oea8J/ZPIHHQDVRFUSsi5lt3O1x5UWNR6PIOkyT9Oi7+c8Txd2qq1hDStfb+Dolll/xd6h+O30iexIHx/CIKtPRMxunffZ9CEzxLPSV+Cf4nBbAtfRhv9erE+vCgr0s9CxuBUnTB0c8ScOsiQLQ1cJ9MnAwP4n0eZJ8UkeWeIjVXmI0cDtNMgQcb4oTgcyQsx0oDy9CiZ+lLivNAyWXFRx2OuFB4wrGYSfHWG7Jxpi7+Y20UEGNNGuQ8JFuT0Als+PVrCUHORaMxZ4Uuf/gCQ5GUhIqcSL8r8uAi49og+BDezXDbLsVV34ySZcdilojrFzHY/m8VmOYj5vCeODf0wqRHNeoC5V3iuYUC0D5EDXn7NsaKj/lx1ybBMJ0RfW6uwtujqT0WUsd5+z+fPAe8rm1H+/6jHCel3LmXKfWq0M8WcP8C3AsPhowGDZ0lKiyPMs6tW7glu9L/boL79/0C7k6cSHpJH8PynHoeW9IGgeNPEOMm85rgtihpBeKjLV40sMDHG0wilThiVYXSySDWRmCrm5qaJtq9BClrecGaAZ5DG0fHeMMQ02+l3Pow1BdQE2pWv3KKEWD9VYPWt3vPjZH/0M79j3Mi4BuXJWa/v382ri/7j2MsK7/ycyOf9w/1LxjB3wBLktBP/Tzg9pnzy3CTfx7+4QomXaxAvzUiM1nQzb0EaIGr4OVh5Unkp7Gf1wWcQ96DivBqj3rr8kLVJA/n7+3Le1uwlo4eHdMnj8RM4CwEhbTCWbDBHD5TYvZr2TjcMIx+TdNanBWZJo/c0xQ/L7QIc3Bt50xlBvH/3WbAe8gaZypiCwcv6YSdYnVgOEsRQSkr5xhx9uMEyVss3CyMGcIO1fuXXe0RTuZTHuvBYRru2xQ37xwjyFeIUToGVJb4RWby2jf6PbYzEupbgM5ZK3h5CqFbu56z7g8KaJTKIK3N0G5odOCtyODUtunqjaHTOEIf0CdwUufXgsBtN2JrPl0bTWPSnEtQvUb3swVMvRgOCBO+IbCNOVr2hxKOY5J7NcWFHLeNj4Y9Hr76TkwofcyjMPU1XfDgx0GDYktT2iD3D7NC3w/xsxyMVczXHEgKOwC2zKTDm8ti7dpt+/HXrDpifrfreJGtRIrfHF6Cvxa6aZndxTtFooyjNR/H/HHkFf1UZgIiYNS3XK/wtKgornN2vuypiIuy+kMx9Pg2amn1DeWlFYrgXuIN9+W0GlVOi4pBHqe9VtoMILyP2E4dTRNMzueUhe5gCxi7l/bz5er+07RPCijR0ghuYH3V4JbHYQVZUcy/3P8mO8YA38gcrl5bYVI+zR87eSrlvQl/hL0LV3H+vDX/PHNy73WvLqO4r5SlKzrAP6e5L1sbW/+W9bok5Q1slqKebkST3hYcSNzi3O+R9if+AsthCO1rt6GuO16Jdp7JF2Oxk3FSPhSfiDc2EE28ZpKny51/RzlcXaGqEA4pSwMKoC42gKzL8meu29FPkvysUC7IxdrvPOD3+2sp/GkA0Yj/mygDgkCupFK9LCigZpAm0nULIU6yQuNWG0s5ape3JD1j6tLz/E+MDEN+mG/q69P7gxyZg2HqqzxIHmiHdimWOqBjzq2u7WGdYiYZuwGLZNApwUZ0GklxKKXN9WlceBBpQ1ZLmUDr9XVIVT+pUMbymDDpQFKxkSDYruboYSSORABpsRbG4pDiSkyIllAVxQ2qQEG16a0MRBUMOFoFeXjPEz338F6v1qjCavLsI27QVTA2TCK/em+IOVRyY6O0+lXLm6aaDmnOrnfpLd4ZDU3/yDe/0quygfI86jvMdc1Riz7VmpzDDxKOpZcWkdo6Hz2h0sJeTMaGFWne1D8WIogtjL/qN/GYyPjGG2YNhwXH80Jt9JhozeG9m53qtwo96zjvelkxy/20uDcCQScbcCjyw5TnpDzPeO8agL7yIizq4j5PMIfdpxiK1s8F9nq+tZKynJFJEjTJHkb55CyRO403VisHbWIyuV0IZxWMkysVvAeo7KyDxTKwkPKUqdv8r9kwrQUglgW5t2/SnJe4XuUoR6MIO0Rwk/GmOwWYRcDj4Ro4xhjF0TBhDKlXlMsMjKh083HMKAf4xfOVsTaJk+30QShnx0s4V6X0nD9If77+alGGfjm9JTtjXFc5EjCnPV3xfsuHXFP63ieULzm1IdYVe3YXjZrBD5Z7uZiWl5olSoK5Vn3HROLf44ROJAvLiiSqKuJGJKFtB7yKPh20DGBbyZwD/caNOEnWnGz9YQWmdJVaOaOmFGs/R79Fseqretg3eqnnt7uszgAn22voRzn6caQyWfB1rGR7WIZiMVP8Sh6Kau4KM2sAul4+LTO2rGQiWvt/B9vO2RojBTV3r6zm2XOMcMfW2D0pivvPQQcA1iLdMFEwnEHform8slaoFI+d87+U1wvOXfeWElVCxaps2GaJ4ViGlRXT9v8lfCQIJewCIr7MXJOAAil3/QwMCynLKXQlTZadtGizZ2axLNus+kp+cRuf3smn1HLpDbySN/MLKXq8ZvJjXjDeqrJFvAVZSM1Za729dpCUsWDQ3Ctwqp+ZJaeW8TeeztbdqEo2Kpk6eAb/VSOx5BkQDv2ue+GDPEYrttoi+HNUY7Nhm9GD/VtXAKz2N2jW4s+l/jzCEoy1fi3TjzMLOkcWB0yB21/6b9Dk/PXzCqe4y1bads4+vmVRu2dCCC+Wmi+HCCjvM8n5zPBNNlEYmJuXwEvCfkOVpZyDSPrYw42QGVTmsdA/578bfXWX7wjL8vc+4M9O/RkySzIQbiUl3+DTohxe0EHtAIt3liJWH6VckCqH2toozxyvMwvMG8tDauO1FoE1CSLt5tDKQNIiof+x1ylX1X301+zW1JJokPC3pfSR43lWQ8kiDjtxzU77lGDh7PAXubQBYTEdGTjTg+VwtEmHdcEo/hCVBlVYZZLMi8i9W7V/CJArt8q66DSRLMFwM/af8sBHX0xctKaupN+J2DUy6X0nYk2VRszLM4ZaRF+XAiGqxjqkxmpR5oQUuIPHOF6HnV2sh486oLsDRbJWsJ2SBhnAJudmKWzBewUeEt8KC6tYgB3pPTLLwoWkFcfUnpkWCsuqdmi4LF3f+WXTZESqKPS9Np89iTM8SJFCZd3EVH/orVUpDZrYzWZkfBnBWFDuMeou4v480/p9bVn0AxvKuj/TDI0C8Zb3DaX37RT0msFQPcF1ANicHlWPAu/efmw/d0PFBpMJktUFkif9gr0FLrSvhop5/71AUTFGf/gLsnOhpqQF22WpUJwpWVVfjvoa7zDVAPgwpKBaVRvdABcn1M0PZ75JqYXqWcxsBGe8cDi76TtZuOfnQdwRLwdicMsCJShVhU6pFV9YrxmsjFQuE89G1EqOElztgkL0sWRUV4Wf3+LWSw1OhvVly2FQGgT5/ajcZ9Ys2gXS75zGr5IPqCWtR+6xjLVnzzx52fOpgVs7qbiNGm3bO0tCwmXlNlsG/MguBvxjPeHk1ADS/0W/t6cmJA6AxoLGjeiNvPi3NFVilC6/ytjLBXE99HRTKVFlsEzlxaJAnpWnrs5RmH4NE58mE1w5lhb2jTpMcS2KqJqnHcDncdb2uXpzDStVkY2cLIxfB5Uu32bPOWDnAZjeclHw3YSPRaIcprZX9wGlm6db6CjDEiuzPGTqLynhms81n+iXt6CKP418hUMyTKaMtP1ZFgp8evpJMqTSz5kSu8BOBKQOjn/re5JJsEJruVWCFNKc2GpoRjaDuYvo6R4vWAV8u9frJFa7hLpwwQCldJUUGUW+eapVoolDKovBZUsAFzMB+vTGqf2P6ty6e64ZwYZJpYRNBqSi268mUkxTB1W5kwHFhOH07QVCYvyNW8FcF27LoMKndiqAGW7XcBt+CeXbOONLfJjqxf1uiZJHY1FKRdlDChprM6i9JPHmqcBpZc84nYmjZ4522CfoGfHKCYRZLkdymQqpbHAFRfw/oOMCu1errvZvkQ7LjLUoJISgXjJ6jDe3uSdg5ajy3T+AriuOBWEmVVEGaqDjNE6rG2FeF6k0VXNiNEbrqZ5S4akt8p3A07bEbIlFk6g30Cvs5UY7kLF2NvN/qDVEmNlI2OaPtyTmTpeeHsYVEW3Yff3HVZM5LPTXTya3AJeuzVD8U8rV/6SvM5P/Snqll+e3gYRSCUVtmSqUVc/yH2TBPQ74o9F7rqSntNQgR1n4yEXjCOT0APG1bmAU24ytJ8dH6FlzPfnahd/WKOz/WphRHc3FLt/Fu8wTvxzPNPUMIHxJce0Sv9/JG3eC2GPZDNMOP/1QjllHD7ynJYb7X13OUA6959Malnnr4CTIH1opRpz8c4n/1Zq5i2NXVIJKcub/6bXGuBYA259vtlX9a9I52nP6pBm6QWDpW6y4OLJR3GNVaTOcSwZWlXzwe8g3MZENjjO/cUqM9o50t50g5p6l7Obs9J2Vjw+9/tCxmH2FCvw/N9qz4aOb65p7KXsh/dUBGnpAPuaLm0gxydudjE0xMPmWSOIl+dIZSG4+fuMiqeEu5bsVvZ+ZCudl4JrC6utnKtSXaROxtq0OEavzUYca9HykFie8a23ea4kMCTuiel8CYl9AdI0+iGA32mkgN6urIbwZcVijw1yFpJl1D5Cmrx9HHfTcBNW5Jyn7xVBj3TvOUP4knzkz+Jnwj3or9DOVoW9hYFcpqW24VKNoCiv8bQ6T9a9v67ULoaCwowIKHknNYVI3RJe741GY6Zb6qopkPnDcWTnh6GqpT+Ky3v2I9l7YHaUfOPzvSCmu63J6FYRoArKrgyeyLCKSLDXk2pHOGsk84NQTSQWwn8aFXgsLC555VDUpwKcd1ROq6c7jrpd1Jqk4/ckTDulMimokvaKyfYWWfjG1Cv+GaQgJHIS8EA1JGZroYBZFnGLtk8yQrU/S+HJ65J+TEgO0iEtnXiZOeZt8pE26oW1C/lUl/dNFVMuv3GTefQNPQ9J8irENxI7DmtEp3T/5JnOXm5y6tdkWlZGNyu9D+fRM8p9/1vQ5n07VdaM7A2XedB9dVuJ5zfyu9ZIVc7FGYTFJbmgnUfz88bqVdY3lVWbgIS/5LqvtE00yxNOurqjKmr51OSRoDPpoA3ehdzUkGsf7t3nFIc+p04rexzq4031hY6ts336aGC27TZFtOp5rBQi/ZCS7TdXSAr6TNLtvaufdOd5bYz8j8O4a/WPcK5U+538umoHL53RED5qmb8tn2byP7eOzl/sYWsVINP6AdfTDQBrSOAEXgYtHv03Mas+aQXM8uHFRMxseA1nbbVEUtQwhNJL3VrgCPS8OlEKVY8nRgWzHsET7tOAp9xdbIdIwp5A+F1IelMPoCpMZuQxFgpDvIiG+nnj5zfgqqhIMxMe3XK2eJmHB9U69gGonDrvQescq4RIfYjg/tzF0MKzuC41XZ6KUJIADCHcrvhPXTy5sefzAlsvqlLhsfVDbmQGFTriEIEyi4PSe0Jjw7bymWLSKm8lv8nb1Ws/Z6ENMW7ej3ALoeSPOWH4sNug5VXDPLfFh9iZHzRJlnZlynBH7WYiQOduMTFyMW4JELewhHqaN6i6avJeNIWzNPPFvXwR00zs1sXm+K5FKpJg45zawGbI2ZoPU4vhyvOdC8UJSfRJXBgq8tL4H1+MdzjHYzZnTc8tfhKwxYSjkdUtfqFdqvaXZkXBod5k4slpy/pH/aVgiWdNwUSs9zpjFM/PV8mb7rEslfdV9Hhg3QI2Sofcw0TT3Qk2UC8XyNDqa2AyD2dxqwWcUtyq5WinY5+aPvjrU/Tdyfy9KId6E14SIMiL6hFB6nLn9vHIUqT/DmUw/3PFjhPKsb/M1N8a/kzX/toCfm7pTDLN8xMjlGL2XiWUFP8Zv9dEzoCpExwwMJ5TKJYh2vlDzycloHrI+PlTMrYOsnEAhDmTq/mJ4/cGeWsv30Y7heO16ABWF+t0aCiAHIfSdKKAdNU1lKnZv/iNGhE8nnECt73F+2wQcu0w4xEnQMlw6SZKR6Vn2yoVGj+SwnV8aEgUW0sloSYhYh9xBJpXBmdBx/+ZptUv08BrQXMnWyRG3vuorZnZDKeV1Siiwm8SA3ib2h8/2yD1JzDLo6cgqsD0lisuQ2W62OWpmkvV0Ed4VhkzIZdsS25UStVRHkINK8XlYSttJDB13UE0oXS9IXlf8ET4McfKuS51KAKVZGd4Ecytyq0Pv8Qv4XCtUAz7JJ2qSdr7XI1iugZ8Q0qd6LjRajRMgvz/cWI9XAw/2CKEH7/QQ+5cKxf64vM1+W6ygZC+Evq6/XtZx9p0P5RwlxmQ3b5t8HzNSsZJ/VGV9gPvtUhDuhowXzHhVmcvjv0wvkNRdmRBT5tj1rF/zS+fG8BdX6L67uL9Os1+VfBvW7pzpwyeCzfYLxF8Vla3NkHzIjrw84YvjPJIfNLcQ5KQa3hwVgu3CP6FFznEoTuCThZhoIjiiwd+lZWuSzoGT8aSFLtBqCx5MxRw3mEwvapxpUyKWrZU3e+Gi+Nl3qn1eIJRP9C2rXxIDT1zZqGrV9PrHHOq1c1gGPTZ7zlR5R/rc7DF3TjsOEy68jJ6BVaZnVm54OINqjTHNdyu+1m4Az32/qiykE/EAHMANNuikjfdYkC1/pUBnf9u7F8DVVgOOFxmxETWQC3QpVRmghXOzGxlASDJwYJODkyIQRfutw7xgs8191KIxXUl6JmHyE+7hy6fwqp4wuIK1NqaTVxvXya/F5KOHa9j1Q2FSama0cxmNch4j9+XsuyzCvz/4JD+V+/1n2ynr40I+Ilmt+xGGPtYjVvM05MSqqlvNuLX4ftu8G112M4cYp6bmko2m89f5sPvvBFRHiLEerwFe5AXVW7WUANsw0q7Mpn9gWfosW/9VmCV1g8i5hfl0EdHVkYDToJkBhKiACxoJM2JDUWgfbLtBB9fSRP0loL4Ref/6IDgKO0q54UoNXbncGY8G9wuX+leLlnI/n5t1MCZBKOz9PVwLP/XBkE1BpZ08qB5Eyavh4nuDOdcaXA50u+BYpDauLj1saMnOOvrmqhWces0enoF5FuoUOilhe0Og4tbr5l1HEXD130v+0DDkT5v88ziVBi6WpYE8Ut5r4GFFGuL4fSMh81EQeHc3ee6ZHsO8JLdVNPfmcYcKdcGAtC9SlWniKlX7OUtLpomn5G9OiuRpuuk6XpcJfjnSGVOBufqqwKkETdQoQGzoqcqYO3wvAK3JKrWaR7Lk5weD+92n9R7BsbNK9jRxD0dl9UXnfr74NDsv12re0tcCpgTE5GDM/lBjHV4FXNglVLdjsFVyEu6FcVj0gzvbvRn8AGf5yEuog5F1EPq+I7TDzFl8nNQ/Z3dpauonl/GRzWTP7Qj9kdyMX1lOenBaFQF1JcneJXAQ2XVtYXxEilx0AZ5gJqguMi40QFAzKxpSMPUowc4+hGIpCffDOMJ4uimBC0hOCI+mR6G506+SyTEg7RUDpVNnD/FGd9iLSXUB1lg8Eg9wHIgN7M8cxPp3Tl1WA0ohExVIUN3w6bXG33V7ZUUDTzj2kouDzNb8SLuxPNg3lWKZubBuQy+yYWtfPm7HgL2hLq2Sn0opF+ztQkWe+4VUjOD7YYSYztf+y+UvUjEh9knqpUSNV2hInxBuShO9fTA8KDDZcfFjL5F6z+x7Gn/YtV4A9OakboYvD6wyOCWh/oSe17rcwIh/Zqv5Dh/z9VuzK5a97O7c4T/If9YJyYeAp6kHUqqhESAmud7pAEhnqEdo+HdXDW20skOc06CeBUERAPAD8ZBdGizTzotjtap/u/35aCR+gSqoOjjMQX4wSS0GyDzjwqXjQD3mLdsUQ1sS348R4EgUXhD0tRW5wKOD8+Nqsb+cqba4GMsPYmThsUAwuCt578iYA1K1T6W0nshZO3IwB7pa65dCJwG7K7uh203Tb+aP9rJyi5Wa2sKkaiklztU6fC3Bdd5RkS87PeW+eVMwGS0Us9B/sJ1pzSZ4v4b4qSzo5wJmk7WLx9hoamvQbb6U7mxLnCKcuN/Of2XFRsyw6aPkVcTWhluZ7nLXplHX6JmzjCdawnvUGrwVpoiEHwEs1/IF0ubcsno/TCAlZ5GO142PzVmq9ouY1RAa4bPHHAcD77Qe6fMjzWVN2yMmPJrqqoPZ3u0GTtTalwk3Jkwmac1dwKUzRyHDCEZjcjRlUVXY9Rm+zLpRDfcYW+H/E678jmu1/70P3eqOOFnsoHC5ew1/uQueNeI3tw41PgTOQ9EUCAKnXKO18ObBeFH+eH4gy31lO0dhWZRvddhaM438YmGvHRZfJ8kKtt/zMxT8FYqDG4J89meOUXnQ2MTpdWoKxYDRbP0f7ZZO/AfEqdu/37OgidCGWm8y+aeTHryDIcviGjvs/4c6cITNy8touTxv6n3S1DQmHdghYANYhc+4c0eudNkQuMks5Nu1elKboDdR2+CyVonGNW4lPwO4SyJoMUIx4BpTqmMUOfu2qm1UyYgnQbwEtANvs71D37FPGXU7fdLSX3O9bewdpnEP0Dy1U7a6MfQn6tLvLk19cyXbYj5rOdfjRpp7o1kvuUrr/XfUPLIKgMnoda1ZnBpStoW7DIWBZLrdhlwBzLdAQ0mx9wliieK6tjQ6pEU+ihwdkNzT1THrNqNG3SUp8/9HzbuV6OPqEJ395qdvoo3v/2VnxBebYOrPCNE8UQp8rmMXYbm1pPZNP32iJAYDt5zpp1w6LDRhLM8WgrvVE4Ro2fFWzf7O7LzkVFsYA7Zv9MFXYJ/jRsxFJNtWmkzm2ihWNfWZWdMjqhmf7T7s1XfuWgmStW6HeMKS5qCkTbN/3o4/Tkw2KAEUpABEBy5HbmD7P1HkKPPOinYiyc/l7uQutSl4IzcFQ428sVzuu/S7I/3TExNrK7F4n3OgAq9k1P7eGkp4tUDaZIXt2bj3JgguJ13i4P2VOpkEzI+AfDoPIrLqysCuALjMqxipEeAnxMtGmCcBpTgjTZGXuIq1pbCvfCDL/fujg9lLW7YTYxwek2Cf40D2i6Rs+lo0ihhLMmiJQ1qkwDczwsFOAgRyvY9Cow3hSiO09SIbsARCwl8Xz5iRWTRggxzvlxjN93cFvvr8KwvDdS8+vp5tMeWEUwT9kXgdwwxZ44KtKpszE84zGa5q4gvUtQ5TQQRGiGjDdKuluN1LEo4ocGead8wHuQVwikhDGrDZLTuujfSnzblE7vcttnslJvJXONYKVjjR+JLmn7bZcHW+QTcTNSPvASHdCTWAUEAB8m7g5ukaxquodgEXjwu40ht3dgDIj6jv/rw3CR0PasLES8jdBipcpp6nWD+uQImK6P40/j5t9/eqqEeo5sl6seFwGBs7wWAnIJFxPqsskjSHgjUKtCzXCdd550Jg71yLWAF355yEVouWfRXazkBd/m7lZMDR7nhjyvOBCeAZ0VkCe/CFPU3+klDm5tyk2JmsQ5L8wwoslHbaKZCz+gk9+fvxL7rac8agkS2/Fa1Xuydjffd2oLYZaoiMxEqH6RV83X/dPtA0+921kxk7Y1aiTLkElZ/zQZa9Ro3YWACUmgJDBGwUrM+ili9Od2K9zz9t5rBSAALGGR4B3hc9JocqlcgX3Qx9vsfIv2hVLQgVkf9/P+pZ50QglE2G9mNKKF/Is/kibEjnuezFRlzUtYxf/z1n3UhSPLec6r4fO1hqj73mlaDI4zxSb8LN7o9UzmwESlt+EZ38t76ogqDPZUf6Qmf9XFYfqV9r2AuQEC4f+DrpKZr4o9s/NMPeONb1oZpt0ifQWRAqLobsjh60qS+1pQA8ugBf0qwVuKd9VlJ1oPcaj2JJn5Rwi1Qs4B8D1pmEDSRJqwqHLB/POkudB86PbJw5sb8Elc0J15afqlSdRdnCUqjsDAculE1udEOzZ4J/fRR/zZMXyBKf7u4FTTa9IDZDKDnK34r4gn8PM2GOFtX/uUJs5Pdgy8GGpARJsM5TNOuEfJrCkL98iLbgbMGksqJAj2K3c7cRkhGVjl8M1Jc09zF3Wa7Ti+qDq/YzTFUmvEmozZP8Pd3LlUN8dIJVbiK7QleyrsKAmUTIQj65Jkq3YR3k9k4Pn/EF5cE12S5RI6LMV66ChXUKWvI828AlKrCREi2pcAjqR/2MY41n3e70wx3HfPs9F6TLpuvNXV0yWORsZPPpg+odYUTDmFgHMSkH3tlJGIc9yxU9NBU8KBDDVTE50x18GroY1dp5dN1cZqMDdM6NVcIPW64umLwHbxMOHVqe6R38c/Hg2c68mhCtexlJHCZh6pikdJ86fwLuzdzZpgF/dOyzYALANbPmFTLfwb8NRfJ7OAGf7QW+R3Y4xXKP3XBL7QHi+7gOepplnw47xaOopt9ccjb91Eqx0X+7bPlj8WEZ8sbtOtExftO+2tcY1V9JCr057GHdNxtMUkL2UVNq9hnHKR6HaqvMFc/GXFrJO+Fn54dhmMDEFbLmQWnT+n/LCqTmfxW7tQyAto0YeV28jGncc7sB/d266JdpWeCKaGrOIGAATr0c9bqW4i+YUiDeyU2iCrta0nvYKmtXuvmL85r3KI/i/09TuwERnSbVkyhnHcGfM/XWPMqDmTOMYfQFgXOueR4Op+aSgw0QuMkX+5q5q0/jT+TLGWceFXh6muvqREPrOT/Cjl7K6AYgAsRBXJHNP8RezXYGxUPb/zUA4XYyQU3S9NHUMRzD1ijrCe++HyEo2Ul2gAYhKhtaC4IXp0PnpYv6LnwT43Z2DmVBC5sBeCzWLPq6kqXzjj4l5T3uTb+38pfBgntvgVmEZzFeGz5K5Y7/DHNvpP5GBUESlSkRnE7YDABpFlGa9KkMwDMpnMkDyLQ0idwtdYnA2C9aI8Lzuh9tQLW7HbabAT96Of+K9x8LPSjMrz7YIrQrcPHUZilKZG+kE5o7stMEuHJC2RhDkiQTSXFyyH7GfpudO6toYUm5V5DDmSi3RgxdJjGTZmPlkrxWAHRY/dhEDuiZ2aYeeNOz2ILfPKQWdAJbTXsOuv5+re0pQJ3W/pd/no8IRvZF1bZm8aovyK4WaMzUaH7cilz0BWQazO3Jvb+E1NcN+NcwGmGx/4p6tJk+sAkv55WEjnqa4w98vclZ+wafEWeiUV0oBKFMmh7Apowf/KEYGgV4yCtQz9e31mcXU2qhw1D9RiyPVA6tlsBAdo0fTYTAfjjQO5qrIz14f7HtELaaZISTW84YcwFGk7xLjJoH+XRNcrMBQ2iJDF3aThK4m2eUECxbJdW6yIGm3HleRMn1h04cqyeqQDJp5JjxKLDWa3/iQZKlNn3dXNawvljtxg5D/ZU8+qKwkWAl4u/NbyToiBU0DZ3gljzMG8wt6Elo3r/Vo41ecoKmbUV2NgzzoasRox5LXMqyyOZraIGEM4CmBaA8RNMjaaOlEi3PXWs5uoah0pEuvpQ5kDHJWCIN0w8b/WS7tkJ/EGSZSAgPu7ZxRW1o4IpnjK6FuRtw07mbccTUe9SCUWiu8Z9fWP9sKTg1gdh8O6iEQqe58uszmOFyBR4lpteBwYCn6T7rrv8h/qLn3BTt05ZjFZt4ws1I1GJo4iY6Vgtrf8RCghmAMQzxIq/qyJKiwguAtEYBQ7SwT6JutykbpHRPk6vAnyTgeOU6OgiosJ1sKZbT49iJtshdxIUPWUD0aNWJzkyoHolXoA40bP7Hw1nc5ZQGju0HzJLZqaOvURBGdEE4gjQbwrA/1pLHB1E8H7a47L6Y3QcWFs03jxQneE478owF31kpUn5+aY/lzzvmF2afgt/Na+4BjfjHFz18yC/Ew2OJuAjBAP0EcoDVLoAcBTIg+GfL4PTfQyUWdgSw0xowwSAmYVmTRZfvaXx3SfzZJFB2v5H/Ae1ChHeTpNsT7Ww6IvYKRvoZTW85h5iw90rrVZKjxSYTCtuRrEpUcw04mRvFzpR/YPQNVrML3rqqZmqxyzwbDbFrJa5WCQ55WifiqKoXeV5bqDUKJjlEB4cc5BNDfLHsBGN6gdb4b1utJf+MtPymjeaSeeoaiJbXuSOGWjj30OYCJn/fs5tJdltu98EnoPShKwZ9wt7ZF4Py7nvvcvsix4pH/G8jnFiyk2Zuy3LdOhJvHKEMa8Og4yaj7ovEayMufuV1QZzq4VBo+2o1400ytaZwibHfYZ/lsxDKFEUpFZPhyQ4WejdTqkuef9w7i1ZU1ej4WwP10Cugqb7cMM5NuA8oYbS7qvZBvO7j9DknpY7s+uBRhvmVVxlQYCFqUwWbEWUbgF3F0og8PU+9AuSVGkSsNwABIw47kd4I7DAQ5wk4t4+DDV8JtitmIOwbELnHPUjP9Bss+sG2MdinfySyKLaSVETTbDpqscXOoDXA1gh5r0BmiDqb6QSe7fbfzrBqyPXiDOEuKaRwmdJAvC68JAbDvIGV8OJMHpJXI6muoY8l40nqDZBcX8EluD6nWc70yy3ywfIgfqZfaXGhoHsnoBK2Nn1k88H3Rwhebm/GzTUnWD+3tYYDUQ+LSHLoCZgl8YK42gq9UBj0kH8rruJOywb1BRVaKWRorRq6teOSceB0+3Eo1DrJdWE6I1s2DAiX0SjCH1v5bxIT4w2FMDQkFPV75whHFrai9/rH5CIGHowX3rwTePoAQti/eLr08SGYHYPeMyr/3BsxgP7Hr46+aVAX9ILBp1ppjPlouUKivc9ZXK+DATVO4xW2kjzvV6nyajOKNNs4LzNnNtialTon5LIfvWfYucLXv+qWMhfENTJ6TSUguuTLpHwCEny0602T8/emg01B8rRJuGMPWhfn47essMsvx0qsCL/aKOtXKNySYvhsqFrtIE7JPE8EK/yYMzt34B/Vtega/qdn/5atgc17YKfTPDp6xTio++YElXn7oHDGLq1f9ltNyKPzDYF81YMki/0lFZafGlNXGd8Op9Aqj8Cbbld/U7lVvrK9kWw8+hN4dlp+lmEl8/WCAzDRxDJf4iIonloZy7irJ+1nK5z94IXrLmKs4Z7Q3yI6WypVNiVWHdAHliHtj8dceSDhXb8MgCm13L3iEl70GMnUtkTExcEjMDocOB6aYJqojo3P84HjkhAKmZHVi/ySCNIUpoBLu33sr4Rfg4c02ewD0vC6zOED7t9od3w1c43Y46VoKb4OammotLclOtju9Hp8C8kJzR1m/Z74Gqzeq2ugAZ7yK8Cd59SfKLd5HLOp8KdvmZClV0CXbIvesda6QK+0vErxJb6L4PHaCETlOS9kYJqH0FiMmJ8COJ7cx8Gs0NEl3gFXhjl3UPp1aAIKZ+Q9JIwo19XhVYjojiZhNerlLeT68CSURVvnCfiz7W1DG+ouGCEjvlG8ugQP75B4tRtL3Pj4dQC7vGaDvjyKpa1N7wxi6WuA1uSQXy+BslDfZJZ8G4LffXSXIl+jUTSDtLUHN7YUKqDP66d+49DW8brBtRSQG9fWUzvjsXkRf0z5iZ/3g58lbHuxnY4NgqUDnJqIjo8tLHztOr4A+udn7boFMJcDCfZqgawIRTkGMTm92ESwZSjLecgrFagoLPK0uv6Ewwr+19O2edeRJD5CZcf8lCef9G/EXRSxb5+F9jK4IezmRPIwon42V7EEFlXoUA1HF/MIEdvtTQW+IN4FjQS53DPQIfYRiqPY2IM97vkqvnUGnUh5iattv49hkzMZf+8RLuG0OjFBqfL1C3maAEYi74VQAVTxx6eohPoAqb359mYhqlrKw4z5pv9QnFrZRv0iRZ/w43VC7J92Ivq92vUgp6sxis0ATrhy5ISiQw3KL6UumPzNBZXLls6IngwAWq1VnExe5dowAUhv/NNFUDvPS5OtvvC+2eZes1SpXHOdV90YFtajRVDcyzIYl6aXY/X1YekuKD4hDv3A9pxt9QrSonl0YZCp2VU9nAqNlwlIkUa9ojGhGDVC/bbnGlvjGX6JcHP2IQMJTCFy16FG5ybD8dy95b5I6JnBRkBXCzVCtuD49oM02Q/pcxgzjMPidTx7h0z12Dr/5VtmZuRtu+YL4PQllxm2RTNtvTbPzbry65fqagq7n0o5n3L3r6jZuPhndQ8RQ3VikDYIZHt8StDroR1xab0IeL38xXemrk5n6Lu38gjobDDLNNWYb16e9pjN3aK9X30uRcteLmMqXyW0aZ5b5Gru28C67wxbXJVI63YLtZoXRfyzvbCRFoik6dm+dtNcHjA/WOUxjDZS6buCGfqf7EDsH7/XF4xrdLQXA3bHAZ7dL4MbnZ0dvINlTq7An9tyq4airxTj3GMKBIzNRzGfEI5xWdqettMSxmTP0SjzlzvdTF4Q4N5vPSB5kqw9WGCbiwQmjAg6ZGmYKqpvbUa6eHPS0U3QCEUt3BvyduDOT1mu5v7ROBlNqTdIMi+dEqytfrZOBq3w+tNQnqyVz23lhMLdwz0KYKGvwPWkagwj+NKjc2sxIh0vv2HS5jUfES7+IdHvKfta1c0WZrhHZW99GuCi5wYHA1dPEg59pqoufalg+ridFm5IzgTA2xf6OiWkVdu0tvwTRTNAZ+9c1ejeH1C5cSTn+RVJP7AdpkguthEDlLI6fNO+nL017g2jjWHDiZ6v99lSJOh41J7mt7Xy/IYXwMy6AV/SO8NnragFXvclogbOLDmoZz06bs4TjJcsv7kn6g8BdtDNzhkInXLIaSMDUwxkZX4Q12kc30HH0oUj73nSuVy5Tr9fY8Ni42j4KJtQ3rYkGLysoiy+oGL7OVdfYHQNi6gcvi5suY04gC27nNd9U7s5zW3RQJaTQXjIyxln5ZN1kZz/BA45+9KTvj9snEF6Iuw8ltkQ+JCdHo9yFY6WH+xC5hZRJD9jsY58c/jIfmrqeUjsttNROwMwEAA7GvRVckGzopqdllahXLQjz4TrCXXcfVnOJ3/SRYuKQNn/htJHdHDphziRZ+xjsv9ToCeM6Sa9sebEMk82k3WV16fJoTscK0RvOZ9vmqKbK47cpD8YcV90t3b5B0BBtqzKURsEVV3fyDrIhszlHEtmA8aH28S0OCBHs+1uyN3ovlfAOMikzfQfedSYYM0DQkAiejxE1+O6pL4HZO6Pha+lf+DA25KtNGc6Sz/U1KXS+wnA/cxyw0HmB+PM6kLmr+tOB1LBm6n3lC7bm8CmpWrXs/GBTHall9zqKllEI6n/SvCOrBDDhFwSMt7hjY4x1jucsUs63Pc9C7YJMs8ZWm+GlpVeBzx0uHdQ2iWHdn7pxGuggpLEpRkycOvn/TzySuJuuMbILlpwx50Gv/pnOc8YErE9eV0F2MC4CtoLev+Jmd3kdDmslavmqbPh6XfCr7lvrvijMGWhzDGkMJeOSG9/2PGM8TO7DBXRFwTEFdQhS1ZpUdvB5QsudESKLQxAg4g7dhNcJD2DzkiA5B50lnU9uLeuvMhNQj9rrEJnP5lVlZ6PCsCMw4o2DxFu1RGJl0D2Mc3q71/8J21MLf8nOQQ2dE0l1jfZvKITwwTqHnBng/wg2tEbUxf5y6fkeDkrNfPWYYewUdoO0KUvbiwr4zGuiDwF2a86MnNL2uHTqdwyR730T3TY7RJQ/bX3S3KSeXTTd2S+Xp5fxELYyLxSH38JwajH23zYe6guuajurp739cqs+z/cQ/W0bzHFVIix+4vu6IQrj6xa8OG/LaA1Nh0z5J1bjnx2o8yvqhuz7idXDSgXEHX86K0cJKsaxv7rGFHCTZhXUkCZoScRnkgZ4DGjcvdutZfaOc5loBEEQqubQd3/oRg3+FcEFxwBuc8iewss97aIjGThHtmxvxgysIDX7t1JApsLvMoRIl12Ev2EfhR7K5lskyUbMt0c1xyQ5jpOZmfFr5IYVc9tURuhbPAAoRzJfVpHtS/9a3ld51WvVSV3Nk1eJO1Y/cGeI65mX7ztofu9t2L3q1pAACR9q4qIvOiGrS0g7KIfOCPsdvt3V8u8T6WahpdO3ZJ5s/lQ76Hgb6F0kyfNBX+4C2gfoVf8vFvjXTn5ULcB/uFoKHXW0aVdCL+bPJv+TEycLHD2gKc0vFBTG5PnvdX8TzVpCz/AJXup1DPrq2F7BKBuYq+gVv8Vmb6nN8Ve4tMTc6StH3OjI9+3u5Og9/cTmT8ifs2nIOFox55tXKuW8v/WJOdt/UlQeP/XCX0JB1Mm396T6I9tyDnIiYUT8c6+OLO1Q2uIP3J8DHJUKDG8WsYwFocY/AmSER7F2bCRH2Vp2+sgY4YIAz4Ac9p1/at/fsuNnIyCO7wunR3g+SZSsDF1jwNqmwIe34lPM1cglGh9iS/Vn3WbbNZoDX+Hxc8Wf/0EEaH8RJ02Z9/MfgOf6JWQCCN5ey9tmwbJEO+eEK3Xdt2Sne38TnJBA1Fn70TIB3EWXvMybKJ0EA1KJ9GknTiIE4XMHqyW0iP6OlAgjoouo9knOXcfwl9i9R/5zOMVr2WgLneiOSXKtyFE0sbG+UIDqeaus8pEvlvvhN4lydCpdqeAsvEguHp+M3yEvHnajqP6UpZyETZ1dVkCQSz1W5QkbrIKfPu75hfn8sjP3W5s6i7RkiqXnUdWHZ2agpe0bi1VFiuprRMd7a78/y29Mm6t6tgUWjMYx8SkICPaxjQoFst0AFcd7t967cFCL3+8ug5aUQMMk38YTkDNOZkFomgw/LZi98N6YdOZ8izB14cPH21IF5eQUy7Ln53AxWE/lhssxPhiT2h7aKquCL3KAx/E667p+/2qMfoY2U9+AsYPzhucRhxrJMNUJaiWP+jCGPZSr/lOm6bi6o24XK3frVoA4NXvwK6G3VoPHmUxLSj9i7nlSa1+cPsirwVgcj+YTTFhEGguk6PtiocY7rwwQMBqZbQEJe+xMPrAsOmWPxtw4whRMWAudoOXnqqzFuAm2/IDCIqjuFUB8SYniU8M+URf5wg0n0zDkKF/PZNH1UQkNbOElyL6g9yvS8k49wZGVtjGMdI9OrX5nyRzJaJFHGUDdmzEKk33djot8Y740HJSTYeyjvXu2lSTyOd3rg0P+/s5fXjiKfrppJMtWsni5Jxusp78zwJbcx1OFNuIMVI1ht2Bse+b6ShnDH/lUTzsoVWq79LSvKfy5MEJEuAfBhXHhYMzq2UdHBas493e5xF6mqnkKbdnzuCeBeaXRSWAPwDAzTUnCfYii7sNf46UM73k7LG5uhx4ayA+J+nmMXuDAh5E+LNm7lecmkKXEOIb2Zl8Fgv6pcRLtulsV11IYj31wH4ddNjbL+q/s0jkKlldgIl0MkKcXqRU7gYiMT/5HKxUJWsDukWk7bxtwj5Vtyzij66cZq4KigBJJ10d63vwRNKStKrnXPE1u0Jps3fKjx9fl7GEuF+4vb4lUiwkRVIBYV1IwsI4zsVhbsE3JBTsOAG7neP5VFiQ+WGgOIzZvSjmpI8hruBezKeMp86v+40nKk9OigkpLEXbTv9VY6ObD46lJ/LLs7z2SqrkbeRXwlIgtZeFPYix104MV0clgeR6lHZtCdvfliMkJkle36bP4fFtiDuH+wxtYLWsHVftUinz2ySEOOb1qD1tHh71tQljsFWm2AMyz+OmhxS/mk6nTcauCe8M7tFQtxiGKKjspxXCq0DF6x6HUWdwJ14P2oFm7IqDF2x7jhCPiPfwPUTprdHL42+v55J2Nm5yutA2ab+b9R2mO7WGFNsHZBFxaSp1vyDpUZR530zG1qshClXjnf5f2aY42CiEIWzOYtaL3jSmzX7yfEbtJ3trx5sqUZfMzdnwr766xWcWe2qY14FsK1qHScbQcKL6l5YHGWLs4KcyT2l9fQLTfzMpHoU6cXQOtKF4IeTrLFt+tGX7S9LuDp1zwoeGExObpIoE0kpSqfJuUHaAehzIarei73ovfFSG3l9cWPFk07muOLxc8/jlE5HNXkk5dgZ0OnzeVgBxgJ0zMprz4hzTs0Hj7v41pdhOMwpF2tKdrM8Bvx4VkLVW4uoVOFWWWq9cD0TvIXdRxiI2DEtYLhI2s7ONdAVfgzb67p+tPumlCq4ZeQtlFgIdo3v39C9OzUXkG/IrAmdEK5u4rK1ci3ZWTgUBHkzy7CJY7VbCFkuQs5o8/aR4gXo4V5VlHx2zKVFJHSGKIvWJuot4CQp3R4gwpYWRhd0c5dxhPk7jrAQlN7pzkKMDy0Y+6jNGaZT3l3iRv0ssMZKXba7pe1O2b+1zcjRafkqXedYtuHqQf1aZ+UCBOMZ2qeAxCFhSJRQaHypcIH6WglO5oBo9BCONFrpkD+zTZQSspOpiM1zbr+N3FctO5k+d0S2vfF2DUv3dlvVFQaj9viOq96Mzgr+3z3y3JdlWhal7fikxXGfoAi5r7ocJeevM7bnyGIzJnLqw2EgpfnuS39MpgJ0xhAyKtAjJVFKHxhXHSC6IIQqcraz+ufOLMBqhfl4kV+dEfvBDrM2A7DiRw2CNAlFNySmYXYSbl6M/++gxrZ1BBR+mB26Xk3qQYZXEHDyZrhK+R0ev2lbV9UAe+RTRcO0gr5xAro+EtIfWpAfxRy1gLanuAspQaKOo068Td4IpSDXZfExYLiV82VIvLtcgJTT2e966nDp6mN8Q/Wurnww6HS0ve+j6pggxrrQVrT2YMK4BeYrlniLgPJquLXC+rJC2B5ODEJQTeAjb5EBtfhMfGU1oKuiHNGIYvEo7vLaJd+03numNAOJWQ1uBec101PjK8C0Cz2N+P0ucvaEPrm6WEGI/SqhH0MewRh0BRvfmEA7fVAJUbly9kxEttYQXQWnj/dS65qxiMhx5wdNH0Cymg2FflH5mwoPApqIhfbTtB0rPcg/YcN+6ds7Br2VKK/KZ+9C7UFsmHiv2vjkH/gIdsGEWC+1/sBm5KX8Cd+WMOtuIxiPzAHwfO6+Xe8cFB3jKXr0o6H0b/52rm5gqKiifN13ZgNP9VMh8qCGHDjXGjXrLRmICnhLExO4uCbVXc1tBF0BJmqaVJriB9fn1bCiKb1hSH72Iiwa9GDtgIGdKBjP5ariFL9w8cEv8Ri3Z7YobBpSuQhrCljuHCMZORFOcayfJ34K3BvSdnAdfuiJayb7rQgisXWGtXPRTF5ZWr/LWfFXVfnmZadx3dnSbvj2PvA+CDxnEX4qCP9vFz2RfEIc1rnkWTXRu4depjdCN6FbSgKc67JCSZ/1d57ycFI8iY6yGzaQB4pm04kclpRs0Uz/BeOZgIVVUn5Ix1IyT6xoAlSTUh9j0fZAryIMkhFYPesU0piUVwvuqG6RC6WNLD5HA4gWL6ZOT/TjSituMtFTJPqm4l32O203mCK5+xYcQwRQrpYd3Vagf3NtGl8l+/mDS+euEsxhNHn34Oo7+2qOa0scj1+Pk9ynNVVexEbPxXq2szFYDRFke5JF829r5t79wJdP0BN3F6/ccOGrT3x/lI1Q9Q1uMOH56nQ9ifEL7D2yN+ueNlBQlT9vQP/aCF4ZSpl0Dop4lUqCQcZqx1liI3OE+0c1bTCUfiLndZWJej1D8Ib+OKVNnuodyd8FrbDhjUBbFI6xUyUUNTaZflcGQZuy2yDHUmFPELieoNET1Bd/F2iWZqufktk9QwQP0U9wjBb/PV1r6FjE1iQHtNocnSxw14aC76QS7mWVGzJ63ibiiAsgmPIKawRLsNKaXpngim3kYdv+ZOTO7IpiaR/+bOdJNThRQ0NzrqbVU1ls2conOuF/iU74G74IXhYmbTwqPhIga7WAvQhFTJ8mrsEiyaQr1Icct7UjiLZ6ocIta4kiIqjheBp1PZEKsF0AaaEu2t+UjUjIBSj+Z/tHPISkn9UgVrGEdy6XZAFUBS+xQXJsj5gSjVgUhtmJCfRFQnW99s2rYr24Yf1VtQD3LLU2+2sF94+bbvZ9N6rPXWBS6ZGnklymbCwvcMC3wcf1im2V6BS6YEGSBxizeJLUwDwXNnUv8V54gWv+U6a+7Ypf1P9uP7vdR/Wiaf4dm7U37ON+2djKM5yA3dHmMkFTEdbkV6ZAEdVSjkY5O20hYy7Xyn9dsbe43L2EU39NT/zn4DRDI6bRGJbwEemxTQ8dmzb0uvj5u2G8IF7DV4MARXD2rHDkcRNOclF0pMdBo1fnMAYW4jP2bi3qelfiBuBCfawaBnbLO6njUf+BY+8tm0O/tY1xj2xDYO6Wc9aDm6szUy6Gt8L3J3eeUYWbwGzttKkYQqZxARHTfaola0TsHEyfx3J61Y4qFktjJi4CIxH5gEovSgvQoT6tRONPb6ZfRp/TxBqKVzjq8mvVCKU4gFMWMOZXSTgs5LTNkC82z+sHZB+nWUHDcUcDPaKamm5/PtbwQiNbIC7hgJLRBV/kYbiisBycjoE+1eXUAuvGfl86fHYCpUzsh+f5RwdtpNw7QlYQU3v71kjQvtriKDxm5vK82OHWwSIeqSkbabybPA+rCzwD6+E1F3VW6wzH4pUKoMVTzXRpqLwTxumYKAxibcBsd0Wm5SXUHTalj/7nL5u5WIHgXelrVRJbVHhOR3AqK5GJoM0bn/Koty5+0vuwWCz76dZ/tyNmBbRe5fs7LTBwo/FjGaupJw6QON7mkjNB8+iRK5gpC0J2AYzDUbdt2aNWksa0Y0TLvkiBaRf2BGWGJmSWP+Qq2ucqO5f7HKvvlwDcXbINQ69DCO8T55qE5FxffcUuOdY/NfWAFLWxiStHtBcAZJnmfSWj4Rqz92gmBcUjZRcLJkve+d5iq/TkD1gLVmaCEnj+1xQ1ioBgItAU6HJf6kn/AZEPqyv+cCZQLb6lPpvjnWPEsOmIJ26memgsq27kF7iG45KsZByRH+6weWNiknFAnuhRQ4l89Vyh7LzqoLMl0EanI456bsSRz+rOvVV47ATOmJEIzuD4kg8wjbzOi0XbUKgDlKRWK9Fp4KMbbr/ORrYlWKj+1xyYd3fz7vLMaE4T0ZMwaxWgpg4n9eD/HWUUimZ9buSaGUKYUTl/W+6NjUzANe3zZzhAwaLCx9q75ngnXOKX0/L7BUz12AV1KzYmYz9mmx+dU8WH/usVhZvlc3xkljj0AKoGpT+cNs8fpDohw9ZR0hQNJtymLWVu8Xtrite95/oKh745M38n8YJ01ItrE/jIZ10r/IvO0kClMibQHUVymRpFkYGqjT8FzjTmVIzrHq0+l5iJ9LA/nQ2ssQPYa8cj0mAR651h5Mu0Z0x+Eyx48ACvctFGWOaxcoTEsH5X79yjQTwvEJR/cbfwO6CHQ0GVDpgelyDdrNj+4hnNF1wNEqRL/O0kytT1imCob8/kgpaqyL5Q1+7/179ZgCDDRZU6XryxoOWP7PxpqUPsYSp11I4/Ar8lE9bqMdTUtwpMa6hE1jwaDxhiJxfQakO6SLbkx1/7DEe31aGb78kxGLw8YusUgJAu8J+X+wweJcPnxP/MXmDaEmbRfInqaDzO8DMtyfOxtPeGYR/24HQl4H/jM0jVSkc/MzF6z28t7X3Tk+Yihkd9gQlMQgpJrlNATWNBo4vsM/+CguWtOuHZAlozs8VakCZ+7P04L6JKwBsH/EJ+tMVeaLpFG6LW1ssknK7PixNQAlWKuYgSm5FLUhHCUjSZhArad++32W81lmmO1B62T3he3TRIcYzzusnZXfu8of5dMEYT2QwSMZehRPRHapjkM0A8zV/0qvlkMz2uC0h3cLw7uvMty+WW6M1ok2xonX/uOWXfhz50CbA0k6Bo84iHCq8CetAayymjyFns0Y2dgjVRArTKVJVNrgU/Cl4wDSrlEHDcfrK79/lG1OWZvDy8kWnGWhHAIYcZ5cppQ2ibiAPGb+4yyHQeESwIa7TeOdm22aNkPSghQo5rNTxeg0marKLAzweikTjVIt0KDqpGDdkQm8kM/SjInhUnIDd0olzTxFlOwfayIR7FDn7gVPsqmi+/S4H2Lyqmcxd+UTXUo2r+vBbk5XPDENOFjRQb4vJooBhUZIuf6CJsSLFBt7TwwBHRzhWITEjwW1SNVlAsaV6AxwRgJgqEaWJQq+BiNgTIowREW2sFAq6TffKKy0ZX2Cfmx6cltp5pt+c/nwp6tuGLqiVF353hOO2h4MZ1NEFebFbwzxTt54DWeiJI6akh1jSkP50GLKTjsnAl+iMuSv1/3PefxGpvYGQhO/Ct90cq8a0dgq3n61N6MQqrMjtqV25FeJZC2CecwVAtyViwL407J2+vV0DsnKbO8kHOnBA+0IlJRHHqFlIusAtF/PyWU8i4TmDTErBSFHUgvZRA1CSQXo1kztZt50hkz4cKUTCE1c2lMI4yMiTaZmoxZ6fFNkUFzmhiJNbXBrvsFklBBqj1NcQvCiRyIg9rQqEvEyoChc3uLe9KZ+MLPYc32xNVjoR4mUdEguGik+S0D/BgGTY792R8uk203FdUTRtoUIaZpGuPL3B7tiWZOOGpc8cmcUoa9M4CyJ5U8Jc4r/HAMtg551kTeNHd33R4cGhDnmWrqw/sIlUrEMLxwIcL476iedZI57IHcY5If+ojh1dnLsN2QPM+6v8z/hk8fWGTTwfGUrtoks2Lp1u+VrpMjLwdOOdZh+cS5WyQzxg7RnTYqQWujDn0frW0kGgUJ0kohIbmaYdsEr02wkeeDeYaXJceimOi3ua1BMijyBx5ql0lEA6JckbuFGw0ESidDza0BMej7pRrD0aQtO82FD9w+ogG7FnTF73XJqVkKlgvDg+MyHxqlGurdXw0ZVzJh6odmjGShj3mVMlKAJIK4umRcNt5GL/1OBfq7Ysxl5TC5Q9GmT/JxPgEjpJFcYPHnWpHy65ebSqpuF1HhY/n9WFF7xSL+lG/R6sjmjL23lcPxf6EQBfOvKxDL5GKzJah4c3uaa7IEr11MBH7FyEfJjnad6/ZEc5Mdyt5Lv7T7tfIhl1GvPmOaPR3/MGW93SC0+lyUIXNDVZRvC7+ivfefkAJQVF/CWNbzUmnAnSEMNT2F0/vKMr0xXAzzYcPJBtPYx0j+iv8lK+Y06ZF/Yzler8xqTBVTfIojzBmj0LXsYp0VHi1EZO1L+2aKVqepFkv/3meiRQ0p/1xdr2pNWvMhuCiyiWd8EYqNrLFIvI6IDReSIwORKyzVNXj5UhvETzpLXjT7ZZRDZvQ2m2wixrFmAIM21zLOmilveZTGcedmWxMRLcy95KZ1VWWwGyoiaOn1lJnpj4ZaQ6Asa0ed2plNQvHKRj4xWBSqmOAtpcYF6o5Vhg6ZIfKLLZifdT261+oClAdaPUyVB++sD/Yreu0AGy21SOarQDmApm+KdHAtkOTciYWg2lfS5m4thC4wsleZ/R/xHggmFGsUouUEPAGtZQ8MW5W6tQum7ponZmq/8i1kV70qeqIB7/Q4fesFoEfpHS2T6ejVX/8WSd9x7XIBescX5knKQy0v69DfiN/L0hcimpcBI06xqMREuzhcFpMWu5SR5xZonqBTXQutgFR/67egKQ0wl0HekBcBLWfH4zEykS9OSv432paZ8qrj3gAwAHRX4nZY/+k+eBE5cWNoVCiFoq/NIEkzQcaEcAzSHjQSD83mwQHdy1kFMSOiuF/6YT0izHLDuf3iN/2P8GCTNOUUX8s+m1lR/etQoSkoOE/x1ZCancEGdfuEfTGbPT+0vxUrHpfIs/fz3luFti8hEDWd89f1pA7fBTfPeQKlGpte6+eizQHUpVcz6ZFAk/NHSD2puCFUwldeknXmtiYrIHF5/i3Hlt2zyQeUAOq2DTLwJtYI7EIG8O7ITTOye1SWLWWuF2i/8PiHprIHskW/moNufSUP6iijPvAZrwgPKBSTlAVSHamDiSjx/hRy7URP6Gfajd9a/l12OADqli2DSDoVXNeMgcxm+pCxjmcbcbC8FiZjqR/PwllAV8oRQePBrRNn6+XG1zUJMmnA/92a4+3xBlPOaJ8XHqsAP6EXI6LMpBn2LlGqwbRcgjy27OSXW0ul40Ua5/qVskgI0j4bzQX3qtzDtJi8Bb2rH2DQO5fDocl4VcnT+N9qEyUgIgS6DhOpA/J+HlyXJFXd/qpZUW2k7vTSyzrhVwlg1tzHofst5/vA+Jivol3NqGEN6n51veHKkLxHRn6WGyuEOCaDPCmlQn7bXj6d/ZdYXwKHy3LO7QWU2ubiGp6LdcXZZNqVBAU6b9gEwf3ILHqpV/q1hLdAaSafKx+h8gGHtr2ue2ghmOvDDXi+J7QB0b7/XxVs7U8fIeU5xy2aiVzKuWSfSf8qNFt6/Upv7QT+6t4JEhSSctDAO1rmxygZ7g7C4HgCWc7ZbZwN3IRbSnxVaTA6OxDr3A+u7OdajN7cTFfQxjuzWTRk88Qd81uASGPbQzhV6MPe9giOCvamp9DUvzlg9lBa0K9ixsnGb+HCXdrcXVRwxVIaKujaX8GnlplsBWsN9JRPmOuJo7v1b93pFCnGa5FVDfmSLmDoTFlrgZog7AgpDwkkAk1gmpTCTeEJvK6STmon2Tk/jCUFU4p/wNt/++mM0G+m2bFVIKj/O/CvuU9WgbUATzDqCSY4TQwN5U4Y0CBbK/SJu4DDxKV06bCkMxSLVHQa224t+r33aBRKXDtIDgZTUGcTBA3uBZ5we6TuS/xuXJQmvY0Is7m9XKdxtsBxyfgTOwSbr8Sff1KTovt1a8ndrk3QTPfYCa9K0MQqpTDDYhsYPwlDfG0wDfaeSYKdPhRMxJFGlILpWSNi10f0uo+yYIcPEJFVi9/q5Hrss8aCjEnzXsdrP1Xf2cSJf+A8Iqpbgv0jNnopZIA5OfZVZ3A/NZtp1SaiCbXW4iMMWuJGqjzUs6Tmn5Gpmzow+3bWOcGeCMLDfv3B50qBmkYhpjdDbQsHQxPacvZrOniSyJfSE3nSqzJyVXn/df1pOdvBCzz1+R7kL9bpKV4tI1/gj2XK+S4fn/RWs5SYGnzB/qwRnuYzQxuxX2vEfkyeUYCMdhK1sx73bpR5frVdAnpcb33wO+DY8eWHph483Nhvo93AB4OAjs92ZymfG214Js1RMUAi2vVJlJWpOuG2vzwzy3ttpj4ueyx5a3Mf8vP1RkGogkLZ1ALt5I61lUj56ul8dOoGs+hocNCTrNXo7JoUOO7xYd+orwGVVWoUPtaPK/Dp/bRWxeyJoMdNlsy7F/dLh9J813ORiw3Ti5BnQl8Lck2MBaTY0ECGlU6UQ/Kbl6nubyIrFC9ieS+uIX82YqIkijKUcIGY00lChnrxqHG6OXt0gV1+TsUoXanbhTgmFtxHXsF4OoWokaS9X8TShpYM9fqYaG0dWSnyc1jKhbPrJ8y5hNVgeuMw8F06TwAL88DrAL0Q0WNZchi7PdLwuHYw6aOkyDKke1XYwVh+I8LzjOmo4FCu1fp7ZWeZ3p6H5prLVPV0yLeh+Vr6thH/uQQio34XSSbM/VwYOXRvNmyKBHL5anCi+nFPgxUQqeklvkR6VPghNS/UTWhyKJeLtT+bc/4dk2urmedpjWoaT4WJkEvkxTAv8d1x6BfkinPiLNPza1k8ftjo+2/18JZ4+SVR1xvP/pN6kkVD3Z8/Z7yhme8R1NpiDC1Mu5FZcU633NqCYbqBjHAExwcXxM99+CbQTC+YvVMnYy6YawIiH8uUIdw/2mLUfwJGrTf3X8UrDvi2ySwcc0UyPFj/bA0srlTygPJyDSogHNUFxDNrbNT2Fwxp1Pi/tokGEoGSkuO05vvyX3KR6xMnhbiy/IimWPtl2dCXoh13DLJUhy9+7HgLYScT8mkdJL1Y0A27gBvZpLXefbxkxVvhoT1ahzk7x/Qmer12c+ZJ6OEm3V75ig/CI4A1RNflAOuyzQ2I2sXI2IaR9n3gaNvjuJsaok+unPHM6vgQQ3LllQt7Mu4erHqY/M0S/NpK0wNRGXQ46JeaDuTsMFWQ+/rLG0esz1c28D6edujx2be7/y5P2FBBfns0Si+98mPe/rxlHFVpfFWQMC6wP4z7UGLix7ntu23BzcKJp/eUPJr5tkje0lrvDU7NC7NkaM2gz/fR1u/ypsjY9BxvY+OXl79paRd6iTCUdqFw/UJsIdi/j4hkFx5KER2WbueRdf/3lAF/6rHq3PjZ53H14VqllvSUzmFRPWZa/zUuZK1iCuRF7p8p/v2Ttgl8urkrJ/EZ3vsYLaQoY1ZwVxvYTMwkf7nYAU0Ns4woiECVQcssKfA1vd/7jhuDfcYvul4JqwnLWoIMkgZadfpPdW0DNjD5g/3QrjdqMGTGuV+A46+Ix/1RpkUgLxbU8Z1FhaH/awGclov/a+awAq8diPRxyXCHmC6dpeXFeU5CYfJTv6uLp+h6t0ZFTpWZvkCOtxVWnAkvSVnOdK96rEFq8dhsfd4nK6sttZhikJfDqN7PfZTIrqDPPmu2FkfpiuRHloUI4Ajlh6g/3J/PjMgtFVn0LygQDs3n4pCstsJ6lVVncqcaTN1m2IEwzaCZoYikM1NCodROjTHc73q8AlQ8eQIL65+ihhMmy71+I3uzpmwwHhmxtLF+wB4yNkEswwXgLw+fSKjB8e+2OdrZwKoHSmi1l8Mpgp4HybsHjPG6wr2lArJPdh0N2uj8b/LvFOHGfHXQkd608Or91atAO/tDMfrHEkLTxdbiE544NEJoGqphl5TSC1G8rlMUAHUTbBNGdOqud70jnFTH+nPHhYt1gN8GFJA0wDCq9FTABhOZ3YCuhAT3VyIWS7sn+AKWuTE4EpShM8GCsHZ4NSE3teWII2ynz5J4f1DoeBX/gboNyvHVX8g65nHkit3xgnnoLGXv5KMpT5KP0tZk0arWxvqjewjfVLQnWqFp+OkDvtMe4luTrjkQUbe5PDPCEaRK6DmJ+1Sjy0+nGL7qEvhW31ww7fqifeKnpwcdPfTYJYIPHx6aQCrppxjetQvusD2X9PKFZwqGdWQoVs0kmfp3R1vDqugk7mAND9Y9lYitt1Hdc6P1IXVmyH3bsFFzKmMY+4eOmtMGXIk1g4tfuFpyf/JvAv95Z5NXbMAnLfc6XcF9vVOY+ZUcdi/lr4Oq0uWgyNFsKZFb6Gg00jh61AaCUrox2I5JGQQoNiMHdYC3xlZLs2Z1RLtWQkPKCw4aARPMk83PFnAbMffWX+hRXJtvmFpvdWtYPyq9a2JDigJk/y0VoElPMOEQqA1t0sAxgXl0uMay1Q3TwlN1faT8Y/47TgjKhh413QWEPJRZfeiTrRjeOX06Nr02LGxKF5QGfTfmyqZduRsV4QVQ9SjoxlFeh3fzOANnSZmnLPi7m1k2W4lsMq9spSTMBnvzGAEDtyjw26dfImWaPzxVftZ7Ys0byHhybbU0RtrB1xpMOJajSTiJxrKct6TIraC2WSvNa5Z7jCtY3RJyx1ifWo7mtjrLNWNm/FHy+0+mZd0EZZIioPGYWUfgJ2x116NeqU3Bk4VLHqY7eZezO3CEuAoJH4nFxWdyDCvcaaEbMBNmcW36hZ5gcMK5xNeltRkSuhydUm6lL7KfQ1BbVzVa/oNtkEcjZDKpxG5n5X7MRdE3NuFR3qbBXBEBmZ11HxR8F/AcPmqRPqaGRCXmnTmgl5dT5nkEK7teB807sd5snp+OHGhjMgLJAJen6G/JI9zNtNZy+s8KC/TU9lhwCwNMI3fKLdhUnVylcTE3LQm/Dt1Wr9L5ddUv86Hxy6Kq5nzSWTGi15wEtoulkFqDySZYkNFOD7NB7o4n+q/IplL+6gRPCdB5CO1y17io4LBBPwlnPWbowBqvg8fwhF7JR4EqmwpZdwcQZJmKYXc9jYfDe4TEMpbR6RFFlrtpDoZHb3AR5eDMfzsgtderbtQXjnlXHUAHFkfD2XRgnwLM10vTINtRSST3ukG1IwbnIJNDevDlWNSwAqEt1UKHpT4aKcXppARXh/gVLHKlhQ5Tu6PA/eEwmbDRoDycXv6tiGJ/QBcUL3LrbF7wUHYZOw1qVVrfJCD/aycENuvCdl/Umt7sgiWI4OJ7j/DBLGH9XnOrpu/amZxM1mnEOxhhB50JCM68wsDxWGBpCNyiGoGTZuYRODcmfyZmF2fQQzBd3HTfTgIhQx9GzMwCbU7FkTnZloHiun1QKjVWkqgw8PB4VOi3H6mJB2c1/jyxLF3JcL7uoPI0TBX7+mPZ60UFg/GTJF3NeiBaIBQWcl3wwXiadtyyR8AYh1zmZll69NYOkBnCktstPXzyKpogP8UQnEhFL/cJyZf4kxQC7vbHb89st+4BBrEMCUh+QssTaRfZqwToxKK/Lh/kJYmTCwGLb4uMG+AacyEpsqj5VWlKj2MTD21QNlV3n9GSRQqZ1qf7W8kv3WnY3qDKcXSaAmxopGOviXns2AXxe594Yts3bo9Lb/+Jl+771QXzobDd3w1KOrGSY10eiS7AaqXW6HYBrx8Xn15j2SnmCSKL2LjvfhBk/4543Pis+EPY6GaUunaIHArkvZCWRH50vvXlAY7eF5ZKJOWkP7fOruRNzZeKI3OWZhUQzcM4cUc3dfXUVS2ZeV8N8Dvjg2p1xtSk8JZHYPUva2olJMIRKn+pOyu1lvJcMNgt+LBgmNLzoiE+kmQOTNbyrt8i8Zbqc1padORqWbVAnaSgaSQRAE6lNTF9aCPvbl3ftMH7Z2DJCqH3SxtwQHO9/26ZEbQEYRDGuHqYBVvnxgUla8BrJbF8bDfbBjV4Pbbrd+xfQCnFALOFMnM/iEfmi8G6zOS8S8p2md3rIFgeGCToPZNyk9bPY/JDvMsuhmDIrUPdHUdbod0dgAG3cPbPHpAThURIZQU5SGsuI1lwGTFRXgkYwnknSTPVinG2Bf/FQQSYppVw1LjWhJVVaiJ6ps/FPEMF6YFwXUYFx29CbQaZ7ocEUxTPT7ZnrPYMnvvxBc+95MgIvC70cRo6Or365ZfU9//donD1n/37+re1h50AshDBoeI1F0PmXGraUUZI7oiLfvEtoVpQ2fHg+Kcn+et3UYOuhA1NQa310AAbuLGIjIAr8xDpGfQI4mf5rer1D4cQelslJHtBVv2sSfL6yIoZoQdAs7/2yXzgVLMV6b1WT4JaAE/NgJLYfBSRaB3XEwQZLWz8NjUW6GLiwTdASEEcYFKBn0UOwdChBp6h41bpSZ60MtgP6engvAflEYGoTUIW87EY91Wz6Xx3vACKF+/yURxHz7bdX/JYR5ra3S4CUUu0knk2+opFoJ+hS4yf9SegPYf6xDy2juOFPHE4SeEsvoMw04bOPkdnph2REacGXQwUnpgwqpqSVJR1t2ys88YqZptGtFbcCsKFQZgbyuVyQUZCgQ8lP/Ij30IjTJE4jPvxEt6FBuBXOLegXbz7oFfu7KFVpKluM2JvYlbRSMH9T1kzDSPIB1vRcQN7HhRsmlHMu6P8tL1MM154AHF/GtCYznLBSS8vpJMqVvMoP3RvdG+magNi8JhSEAWt/k3putSZDDLXZMlbVf7Jp4vOk6jamLlu09B/1hI0zh/1Y5FzZZpEvReCFpnb9XoApPx52wDXreUO1vuOL45tPhLyNCAUTp0BHqGajgNh9oJkKabPZgQCRDREBsRiQHDCDwAWBUCLYfB8G5TbzeGiADPZSHkyjc44mYUuv5FvpS9mcrypk455/v9Ine/xmknpAumx/bA1xLe0Qk3VZFOuo23Mn1dYG/eN43tgiKuagKw3S37O5PDgjy2BLAJVpPRUfZWB8EYwNs5fL0uJqQjR5gVfPEXhhw8BjUVmii3cylwVq4JJMYRCYLEMXovD5S3WPUNZ1OGdbSgqRqnkh8UI6nbgA6BBVaRCoNf0Eh8qCU4Ez5xWYa6XQJfnTlOQtu0YM/pGVE81gZsukF3QSu+ADtnt/14guyyKTUjbbJ22Wip8GOOHPiPewyHkC8kvtScUOKF7VoHPvE9WfAomT0lj/SarBslOmxxb5CrEafpV7ITtNGBclsQmyuu6v0jhXGLhXM/4CGWt2+cw7hg3x/n+rsMXl0HIzz2O7D2yowPj9QiZ2E1GCyK50NurHPJI8W9N7/1uKRl922Lsd4bQnm9Kqj2puTUfjlnhYoozdPLcGRxu9Bv/kMwsi5MGHVXz+7ACIriEeR1oPpW+4BN6c12nJK6mB5cXeqb6KKbDgnueKN8W0huD8ZF7ouBGNjMNfgRud7/7j4E7Ph0/PWAk9LJP/5ED3CGw0wU9H2iVXOaqoZ1hsJQjt3KMooFtNfACm2g2q1+QpaMdvJ1u0suD0xTR4Dl8iJPSk8fAMfbBTLDAN8k+yOBqCZV9Qam+jfaGVUUqsw0yGQL4Cy3dVLuei4esYE62+gq4HymzMQ0agxIix6wXXyxtNhaeqWpI/jjXQJhgdr3rL0I699IlPAlJEYOYqMAJlC7mgC7EwaLBbcuv2CSas6gB4Y5iDnRNS1NbSPDhwoQnW7GHEyPf2ayuuAzEl3l4yX9NHDQIq/nQmP/kvccsA/5nDJafJp268Ik7eKBKx5DeWey+3CKaQ0rq3TVDpupZpRZ/XbzMdLGqfImPKL8NyHzVYcpn5o/pzg84rFJfUtrdryrVWnh0QMJVVolFSY0awKnxGcGLIXlztw8ViBVCOQ7BUFKfwj4/VHLaec6HPT3OZ9m1+1UrQ6FjoYeDUuYbMWUOxupCBhwlJjIFsHgMb6mZ0fYbAUoYxGDW4CmVPJDPrDzz5oaOqix9Ez9nv9R1ONauk2eAAUQi9OLAE7dAudZzJzonL4du2h00Q90VCFLmf1m0CdB+WjzBgqSYWz3lvpPQ3MW5R25YeQemdJgqUg+9WML2HzpRHt7HTv8AdBSC7vqv/Ryif6kOV15aub1L/fgThLScqD0wT2X98SG2kxj/+dkBQehN3Yazuf+8gW44G7/UwkSUZWoi+h+9QISa9yEh+yJzDSeeca3xl6aBGrQ48r6JYfPibxMdPbOTEOD/PgICm7hy1/y3o2ulm5y0kxnkYNuyE32D3wcUTpLeAexTkepkXm+swQUi5efRX7x/ynvPwraT75Pvbdj7sQVBjd9H4cE55peX/MiKrh/WWp4ej63bOG1zx+DGoD7Q0CUPKjEcq6Gk95NHIzAPjtp+cvCONdqxsTK7b066NfJjwaDV0u8rrO4gCgIMXFqMSEgKomBovjP8K8ng/WNn9a4nVNdn2WaXkX3/LTBvi8nMxnWvQLJ+/2Ixm2rLujdm7bb43CYf/4yWPSGfJERo6A08Fi5UPt/eNPRmgb0/PquO0hO4tDWC3BHtIDra36mQuITW0zuWn2stA3pMOS9ujVbbUGDhGgO9c+705raewjC9McNPIi47DQUwkCyc924w3lq0PdO6IFboOLlE/9JERSAbb0m2gNLO73dknlZ0CMjH/5ljAq+/qBVYE7gyEV9I1kfQFrGQenWwCKptJsKtJdL08/RxqctU9N96j36uYa9b9F5bIdoH0NZGNs2A/Hox1NEG3KdCnBmhJLuMtqjx4xiWeX53cLEUL1QHKLLcXJ4wxmFTyc4xpfe03LepyDSalLuknLLLjen004BbEcVWEig6XcQ0e1he6Q3LKhEtRK0e+rgYyrk98zwwToTp2pwv8PzaJ3OT9B4RKQipIOCnvUsUDGvlCAc4K5WeRyG0AnM7v/GAjZUMMwhvN4CzZ5GBg3NxjqBxMA+FuntVgoWw6vNJZeebhUr1y7ZTHX+RhpGLHzv7Tg63lXLsK0JodO4M0QvQVAm3WRumJtv6oqWX+19FLkBtt8FO+1l6tK+O5ftX4umKO8c3HB4eTbLQLV44sm4m7sh45DswS5pXhmBykqdVIjDXcuyYs0sC9PJyBKQWv4rm6Z8Kr5X/neE7KdFRwrwGPamssILOhFaYfEiAgT8kKyUN9UKxJPRwBA8koSWhkLyKU3oMh9DPA0a9CUVfsbUpfuhhBt5O+bhGjzbJ51iRQJexKyXT3nQERh5UUSx2YNz6tdA3v/7YodFWqQtgrZDYy+jj4tfe02veYpChLxd/0X9Rptr8tO1lT3P6bmBj7UuEeESVEE3qLj2a8D5EW3CJILJRf0xs9lUJnyMZ2WBzCSSuwzqYw6XdtkegRsnEXDhok1Nh6RXSPXNzMPVs8QFboLqAaM+HXBNWXFpV6igclz7xHy3Dn6lKy0WrP9MMN5sToj8+EqmJWu7x+zBf7/oTXrSEVscoWEwuMV05evvSVVidz9Yh1ZnIk0ZHQCKfZIAotQQqhX9GTETQbC6PeKxFdWVVZ1XRyVj8upHC+vIxDCrSYsPdhcfMJxRWjWwGHE6JQSVIDPzIPBeCg1EOqAwTs9IED6PPaU1Mblc9ZBu0sfkwZ2wNL5u4YVHx7Rc3uiDzAyuvKKirvXnGP+I/hqVRWU5I6zOJOQjjrncA8wiPipCNOrjPYOCogIFYK+LH/HeEwXWkSxUR1TqxPO4Gvax+N1pePDeQ+fyp3eVS6nPT+DtfBHWQwUb7iibgpXTigVp/sO7KLPDJ2gpam77nrA6X6rgu3G/CayQP87idc01o933w9SWK01+/c6UThe3IAUukGZrFHlCDmQn8CXFrbFIPSlwEIiKv9tMuLgxhkdKeSG+wlh8TSMGQL3be8M6BwQAc3WfZDtz3nglMcf+QKFOhcy13riKoSUhmwhsxAFT3XnH6Nk2wGtjSX9uTCqiJwXsj1c/tSsG1vqjgRARGtkhgQYmjeJiEc66Sx3rnFKi2PNJHGc3GhHvjgN5XWqxK61QEihnsuICXiWef0RKmV0fEOaqfIXnjrxNP+LxrYh56oJ+DWh/zTq9AQRUolx3bA9SW728T0QMJnZ9ikoXUFsMHnSNryV2ffIArNphSyaGMf/zBIsL5u5E4Rp0l/zqh/r5rzbK9f4WRntkN/qiCxWeu3gT7h6nEFdKZaVlcOY0WubefUqeovTk+jVwGX7yTv1KkMhchAtzzl8OM22wb8Ro8JrAX2JB0cRZYLrx//8LESpKXJbxwV4c5zsPiGeljfYkBKoE1o0etXNq+viBgGoPlQz0y1Acwm7nrvgRrbv1BWo5rQUJSwI3cOZTzIm+A0ZteSAIKeDkKcs7RvDYABI6dvnFsdIyurTtiO8ScwDV4hU1+o/zRXTR+K2FgXnOSa8v27spVmHe6dylg1No87Aaebr2h1CpZVr8nAksIu8rHYSdq1NXAVXNX5uzo7KSww+P1kfLUg8r5HBeTZ8zNfYbkr0hm2gDFjGdEr08KlEn/RXDPS06389/uI4UTKziKt3LYTMjxlvQGIagqmr71IimKej5QvqRkV8JNvYI3PhIzJMNDRUpIcBiGcRKdBuNxZA2bBhBEZeEOK3jGMHVKJKql2Gpx+CIx9GLTC73YS7x9KcQ1jDaBErKBDDWEQkFCoiiqWciSYihmEupSb/fhC3ShXSI1+WqBuTkNXf3fXrpxlXf3kmVvyIumuzL7w7El6IyN7Rri2uoA8Ign6SrTpxOjyX9mjocg+dsjuw88CUnb53ROqrxjr3HSTR/3MrkpEwfE+NPq1m9SgQXSeon8qeFbo/Y5YlyshRvNzFFgfWfDBjUr/BEU0f8pEkaZlPyjOX9sNEsgRu+ccc7BCy//Rf7t3IwfQ2Z5ilHfbOinrV4Vb1K/bVk/frtedGOcB08oDD7UMrgBigEsHEi+O8/KcL13bLi9terXuthPITKcb368+6unquImw8ctuOX4VzcP0facp5pHuzp0sTOqx7pGdHRqDBdzMFgriFiswIxc/McB4VRcGth7W6YsiDAlBgFpDnI0rrZySXRq6j5U/kY7zbnjxTBaKi3JwzCOan9a1uVW0Nmfu1EQYPgcTNAbLrcDwBb9BPDil9KCPvZrBf69AtI8HNZrN4X0YrX83B0BI46tiLQHjj/K14GruIMG899WbQBFnYWQTS5lVgzY3Calfh5K1acRk/Ey+qe2DJ9sahpstn1rOhugO+j/tFoV6YpqxCvQdlQvrHzmMPnHxulyxibnNiHv13fE96SBYKCxoLN0mXGIT2ucSoDT6cTeZb/QWOfg9jIlnpiJt5qswi5tWVhD81HQkbv4yxeRssCex0Appbe/FMIwCCgEA1IVVtm6t4wT+4Dfp42pFRjhgACFoIyil6O68wHrUHD+9YPm7wzW/89auX47D8TfVzD1C9XJCjR6nh+9NW7wMP6fS+gjHr7guyEOMxr4Pvxd7XmP5PrttsK+3azOejmJjdJuW0D78l9bX+q51C3/zWlu8Ydlrn1Oy/Pd3Jyb1GoP7yVBZ3suZJxqn0i9Y0nqXFFDx9bz1D8dVPUtuSQ9+95YJalO3tVixyCPleEIih+YH76A3kUjMkK7vuuqIpfTLJ0O/XWST3QlgirbEiWYRVHlr/G617Cjat3N6C7MjYLDiRGL4G2ANfOS6mboqqRwgKPlIjaukCJypE7qEZlE6lz8axXrv0t073eR7i0yeMkEvZbOdri75pkGwU0sSCCRH8wuUc9tM9S/NXNZBJg4MrGnVUkrGLaOhAzFGUVHACcbUoskYNn15NvbjTQO9rVMoUMs80QeXJYbOVX1Y/5XPSUoZ03ee3D5kXugNTHvVQpELc0m6O1Ojv+p8yfn3A9EJ13jmAFYeg4TN0tnHgbYC95M+ZsLqMYeCesfkaGfw8JVaLybOECiguc4F4FARLFX4+RD01NfkMae0Tq+XFDWDUsCqGJxC3eS84iP9JQ7yXr4t0ZeTQ68A/BW3VLdBF15EvALC1196ZUD4z3BVqgEk8A5CRsNqIs+ZX2frt+i6ZGDdsnf/GJ1s2t0ypBB/waiOfEkh0KvP/C73XydRm+iZ7OfKwdFSmlt2zOrbUZZLmFFkA47yrTKShwCtcmDNkNRJ1wodkWNIQNhnw5+6UgVklawBpBvuQlMlWjCp90BjD7d3uRpOEGOnEV2vu9FShStIqgLCivjqWwuXeWgtj2Ao9rkvfReGlPmr+qFrnVJpiC9DixIwjrFyMtIYhvkLopx9CkHO0/vdNLdYq19LZZAAP6L4ZbkfelTWKcRmaiXw9dx1nxsIV8UKeIbtKsZNeXpWWqVXlRW5/lAOQS0AMHM2/vv9p1RfrwJl9laOLC+16YjAsK5YYMXRWL++ZBY0xd79+lKhw399rSTYGvyTKTJyMAIjZl4lhqI1EUDvCuNNlSYkZwq9oZwc2AaHJcBdFZUvwlBfuYFNg8f0/fKGDSM4A/gMjWxHWedtpwAWGf7+ddDylH9FC3+DMs8r2I8d4csNlTIKxaeHtlYu6g7xSwb1FyxytVI6D/31BAqhoKzzTST2+1x/63IMmp1OTZvsWo0E93tfxw2eU2JbgBU9zMbEjMGlkDM8/IVDDYj/Cai9IOoSjIpgPDhSgIIn8SKeYtRWeVmOW7FUCwAA42FDxraJ5VB7vWES1Q58qVhmpHzYdbrEzpovlH+SgvFECJogZm+YOdI7uE4w2PbQcDqOuQjDdl8b1oLe6CwqUYa0yB0NhqWWKx3hq3ZH+oy8f4olpiqKAwbx/qpW7qp76hAOQK8GQvRUyQc79zNgmAt95WeksD1GDYh8lOX+4/neFTNnpgvEPtpE2TeOgn6QqL/M+zrmGzv5PAyyqiNsgpB+Pm7qlfw3jclRamPF4phmhcUu+esFggq8JmS0rpiKxiGonqFc0afVnzKcLDQUb0YnsifiePo4QStRx9Ag9CoU0tfiM9MlrFaJSvQSeKh7AE5RX1lRZKuO7lvkIuw0aUW5yGBUGh02cUOgWmVq+eoCaWxp3eVYLrMAqnl48a1TRgnfhY90fufFBsU7+erEheYdaIuGml4073ZntoJuYxvsqIcN+Omc+L7i/ceXc4qJ13OM6emsdaP9LzGZj+5INYGutMW8VFwusNkRriEFts4GCMMjERnZruYeNqCzHPyqfaZWT6ZfHbFvHh/qeiwUA7+QeAczTtAFn8ow1Dza8ZdP6+vmZCP9XwbsNlDozVq8D75jJTBvN/H/WeNc2diNp5fBbd7trkCyPrZMRjNnNr1bs73al4bZ3gdXOCNd3GUSPit3OrLsMACHwXPhEzptaw4Yrce9ipjZHIByBBPlFUIXCHxQ2JVTaHN73NllUabMzlpChCTJM6XTnAgDM6qROru6bpynwpoHFX2+UXmsV30qek9fqikoQUmt7BFIMnirC95WZUyJFDgrrTfD4qCyr7DSy7XlZVOAMDkgXRBi3RMQ9DNA35CRlfh/C9LCAvIe404l6m/fZH5dZiMHSrpAY/yALfdbqTs7AwaKzkHDbFF/mR9pTr6q8G5lbC7luyOFRPuKI4dXRF0pDHFRFnScjGuBFCzgGAFHOHk0X52c5N+YWX/GcNPbr98pSq5/X3Bq4S0hbO+ucaNXnXZJdrS5I7JnGed/3788tVlyTcfVo8mTHsrXLJx6KFLBTsDFDlSr5Rr+VGBPOii7D7XlUOs51XoZ5g0q89s3l6xBdh85/KDws+aTeoL3YS+GzazLxVAuyB2x0k84pkVmFbaK2yHg75xNDyLRU+UpiAJTr2qsJ2qvQxLR9H7r98/pnoVmY/fnwqZ9z4wDITCxtbw2vZyQVbkzFRQSpcg+w8qvZ1GPm1N+9WdP16nGEgz88xmuSK29Wn8IjpOyN9pneCIh1k1U1uMuISS+tS4kuzSkKRJcnl4W1OLAHySlKQLyQrvkT7A8jX6Y9Vcp2ncUlUFidc92Tci98mxqNVfFN3nDxPi0eKprih3fyNgrkK6w0aSPgb6n0XKh32VNbSS546n4RXMrzXcY4ocK1HlB0RhVABo9Z8tUxdBEL7rat4oVypnUGlAaS10OVhi0HKKoS6ZdFETrq4es3Z9IR578gCvMZ3nG/y0oRDpfyFoWwlpGqmifmiHuFmNE/CNA/LsWrL0Ss2lW5sgsejHkuRTITMAGaDlIREiSZFf9JyBsrMyYuV+imq5aTO5O5i14uat1iuxDzPgAAqL5hOEBj5Wl2ZOeCye7ygktzeNdZJg4+1cI+UutoAeG5idccrscDZzWuEWt9aRb7TxAwOWBnLHlxlBkArvxIk5kSjHalXGUjdFMVeEZFTs78ZVp8/vs2hOJL18RSlNTBzQXJrOkXYr5WAfMn0QLCMNOStv+jPNoosKvr2D7LhqQx/NuWQ++7xQTiv25y8TAv2rfl97eMyqILohinv4X+Gu2cNWCSsVPIKh53jO2uEBTAqfJbuCJH8j8uUz03WVlWmcqOrHbZ2F17o3ZEqTS4conduy+VX3jOW5SZUZC0wI+Ep6OAW0LyBTsQc8GdYa11NsJ7VrNIc5qandjFyJjrE6nIaWRxjBC9TcUeZyPdU+/EJzAvEcjiIIT1JbFdLfdVjKiItZqj8Qcr9ifJwQLLFUf9sj+1vG3wgLYq4G/NtGHySYerDn+VOKbHoO+qeV1iMTp+FocQCLuJndhyRc+ThU6rZJ031KwNrqrlR3TgGFwthK5uFr7YtSxd219At4OpxcW0MbO3T68O5/uWMUqpxUgGuQ+33eVRkxgTYQIeKq/lQLesj1CUcizLrAFGNmKcCNgoNJDlaq+sqjc5miRY2feg0AJeqjohV3UBU3GV5eTZcDQXdyOvcMf9Yl0qzlR1u9/xop29YLltg+Z71xu8YtQuNYFMnF5R/93fwlqeAPizvkkvs29gn/w07kCbYLR5R68d//PUupQHUBdOp+PMoLUx0USq6Dni6cwsgsJkcycezjxY6rIY1fMy7K1L0L7g5XXFNjVmM7b0Spu/xpvc5GDaqLaISTJ1RvFoiHGZkLUoCApa4o/ub/sRGHM2lrj+2oEZq9aKKMXPX4VP4/1/jj5W8PfT1vF9+Dq9V8+TbLmEZXvRa5bbxZvwULPmP6F5Km1rd2uMUvKg3bKqwDzsZGaNxyYKfL3eCaq8mXth32UuTswvklvoyGuHtn34lLmqjYniHg89Pj6wm7Qeiele4JXuYF2fhtoVr5yQqbMBcjehH0IavdOhKhUhSgdFjHCeEvoBVHd28kX1H1zcuWifw61qR5PqQAtXVIwqy6fB5No3/Xgf4/prg9WO8Sug4L1ETCDYsyiDee55+r8RaWT9qgPA9HxIXUgp0qVqEBRHTHstJixkK/w9E241k8ZM3Hbe4gHFBm+cPruZb1nWQXBtTRbMYoqbLq6qcx4Sb4FDsgzMcLajVKg55zAzgO17GNUH8RtpE5JDqa69IvQ5+GF1poqurVgC5ug6Zq18j8QVIFKVkR1bLmXbhJmUbmPeh+VL0tLr/NULWZF6NdZe6MfEfwfp+J0Tjfxm9omL7tIe82WHFfQpRPnBWmyGquZutjEZhtwhhGbi3aHZciblUdjS2e5iX2dKmy8KZTxpyAFzSS9HJcJeByXrzroIZVhlIF+oPRrLsf1w7/TqzlcloHis+PPRIsRcDXS7YkiTrdK2Hh06ipDOFWe8qnkKaQJRhR93m7SJTx9iGZeh8QeFMm+kHG+0gIbNSpPD0hfaTxBqtGsHUkiVdStF9+ZcGhmKkPIhYHJOIcwEEHPmOk0uVYjWrzO+cE7E0UFfEa9Q++BihygTNfxi/EOnVk+aMIPUAxklp1RQu20GTBYgaz2EO7g3COdLhCTRRTUUKcRt8XrEXFJgpuJsx/17UoEasZ1e/dTPSceSGxt0+qSfPLHsoAmGWiPeWrosMJVdsFHyTYv+Ojy1FhbQF9/wc4kksyAfNYdZy8eoCP8evRCMb46V0vY5k4Dzxto8+szg9INoDSodg52mEI21wLCUgBXKgmZlPxFOJ5KKjQIgMuMGfL3ReCnnQPeI19oEzt0YUf/GnZOVcxl7qSMzpTJ8qZ+1SyuO8hsHI0kTa2SAaBEUvDZLeJeog0CqAA6QtJYUEj5J+XIeOAXkMrlH392WNxiufCZkVgEGk6ITCAQQ96MR2Pko4Fv9ZRuD/Yzmae0MHsNJZJur52yQJkoW/CpsTK41HqQyuL+bORWe4sGgyy4Gpkss3zCCYkmdQhFd5aaJNPJa1ypIOE0AAobAQ/xfPKJkRMuZrYP6iuEefTfNin2Cxm3Wzi7ybYVNCRA4AOi+PGfCEV5u2WcigxRw7uwYcjl4LH1GXGkBLk+cRY3Em6Faaxx77bKKJSHx8Sb26sSqf5mB2XSvSDj4BhxjY+6XSZ3FT8uebwbgekap28JJAolpqk6PUma5j6rekF3zyJbIl1YHJJwV4OABBqIq25j2OcIbtdrO3foo3NHluyATOeKD86fcv0p9TODistHNtUlHDsceHHm49BCFKNtQ4ql5j4ttv+OKE5GTuvKawZX6ECTRnpBm3DolAvb327jGlxoTFEdPOy0jFyzjAHOxZt05zFQzI+anMGAZgW4lEYyjiqHkJy8shzNsmUylpnHTB0GNCMX545SrypdtKjkRNKmKqIQt/Nr86Nie+ygotrfP+QLkEil+mpCbnruyiBfGkRxtaBklcy7d/Xw9uIfFLapThbIilIdgU9iVfHGPoeADmj8eQJUqWqanBD4SZ8iOnj17BdWh2x0J4Eq8k0whpj5NmM9yMcl5J6rqPLWHf+NU54efF0NhL8j2KU8py3HUEO8LhsWLAW3yC8SKF8zR56gvrN++ECZTPe7KwqIA/sb3KYIwXMrkESxhT4tSiZa45ooqscujAy2nxiToTFHUEWaXQVQNvzymsRV3hh0GzkmdVsDLyiAqdXgNn/QeJp5iTJI3ZttUw1Xgm8/iPe2fivWJixkKKkZ0wgxpi+lBrbRKRJKKYvRVhGTGqCPmg+HGMnHchPStCbJcHWwKpsiVTl4DBicSIRM44jNHOcX0diECr4fSadccMG9aDsJZrcEuwZ5Kp3f9Xk6nDvBRVIrZzGQ1yep0JdW/jcLciU5yjdWc217NrGfZmSqRi1x6RIvK8Gh5EdFZYJIzASvOPe3oFMiW1PtxBWl5+ZrfnIlqWLh3/TWF9Y4MSEwmbwS6HAyGGc+AQTnx9eY/pn7TqjAHGLpszSNd30sZMuKz33CJSndDRWlobmxQ4qjS1mEZVc+3qv/zQzBL2MwipZWYOHephjN9PXq43RWYZcivgIOJgRRHQxc0nkwSs27Bmsmykp14974Eshg29eflKwbJO179bkIj5qW8AytudrBHZMa0YPiFmXgineKSxoGE1sZAFS9vpnPiKdDJ2Rn5VqC3qIL2Cl/eoyY0bQiF7Esg24EWQXpvMylYM0yNbXVdwI98XCTAmPcStu0fo7LMzRabvGQ0QrWaaLP1WpY5UHlWQC1TyuU1+XYusZuKc9ZDuNX6V0SofKUVT1E79W5JXROKxhvkZNaoaWLs2GuFGKbapsfJgBDuaNDWbv76fpX6aBZ0LlsqXckHWTy5BawN34o6vEKfLCtvls/Xqa+UCmyDrbceWjPsa6HUzXaNiZoGmWsjmSc4ZpjCnRY+PIDnVjRxqNPUOMk1WOvtFWvZt1rXoQOCjuSNds7gGdzvg1Fk8BBK8MfYjnrUaF3WToQkrcXdU2II2QRVQ2f9i966gHhfcvGI8hQRuhy4cz+yqaVUFMMfc/14wQbU2z2zrZ2cgJaJ17t2CIx8YL8Hup+WSXEt8OouAYRMoHDRLVFjLIVG7Ww/VBhp9vA801p6GCmae9ei8NPaJ+LCfKCCNesnjxt0MgUDKBsebeOqpZLDZyJpwdSCPsh4/5ZreFRHK6yr5XJarvI01vdYqny4+nEkc4CLLBIlqMRGm1HcGOVGWb63q3GESbffOR9Zk3z63CLcKfL9eeHOSojbLaPMP8Nk6W5RE0J81ZzQk3M3K/IG5z4Jb45ugglTPIQmwGMiIrZk9dxyCVOJOJPiYIQkp0BOKSdLhmZqN1UhuQBAatM5g6C8IlNqmoZURdnExLBS2nCzp697mf/TNIL8mgxYr0VSmi2hEm+ls4JEJQvO0sqVKdidI90NBtvCKvTM+KHOW66V1I+4nbR5qSVJbL5K+XIZveT2blQBwGacg5mtQP/KZwchajD9K2KTmDHKt9xUp1w6y4Y9/Zq9B0vTOlkA9ZLw98G22TzU+rPVVDiReALS0K+vY1ZqIEMEJWYt3ULWMDCtTfYSFyq2EDrUCs7f2tJ4Z6yLfp+8h/HxMs0nAfM8gyZR7xlHhgwBU4DkNwPLV72mgQb8Dd0RQjIr3wyZ7s4RP1erSJzGuJ47E5jYVp0hC5ZYoU7OBc2fNy5neDwElsz1yzxRyiwLOJAb+cT2YmTj65E4MVKol5froyRCINKPf5vN20R+YvCX6SCqU7DWebkqWwEEvp4ygVMp/0rgKw7iZ/8NHc/p1xcEhhRWDOgvz0GoUbun1ee0eINgeHoYXPnfT8q8vIhgfpfhdCG7FHF842E3VjfNlSWZs6e6dpHsrIPCjcmn1c5xke6H3VOhjpNgN2fgJ2zE4Dp9prBHseCApAdJ/Cbjh6NmhEHi0cd28CXoAan27tZyC3n0xDhxYMPX4M4hNYH9wNvVBH2hbUFBEyMHKsUBetWJ7DgDZpPsziRjJshH7UyhSMteIJYycoimhZfWHa/wPbzr+Ovq0qdzTOZB73+lkOHYQ+KJAPONE7Ks5YMfBQ9IT3oPIvS07jPvyEfBvqgrCXIjU/kvNvxY8LfleZtiLtDJn3IKcJvyC/v1s4du19y6RWyrZm7TU2NytvjzE4M4OpD7RB2cFux2+KBn8zWmcD1uWttus8r9s1dNTj0b2DqUdyfniXNlf2HjK3Li8A7A40Ezcl0BAPX6VN/vjpWPOyac9vVxh15nUWkzRAV6tZG94rHPRZf45B8mEGahRPjSlocBghSvNUoIZABSKAsCa0FC79UAWeBcMC5E2Sm3MolIz1d1HYL7PzQQye0Ydd97gDxl4NwRlwfNix4HT3SE9b3tBYwtLk0Jmxgmy+KT+TuIWuKDuKf1zJssfXzyhZyXLyLfFwKvwnygTftBbtl76I8EVqGABGG5OzeXwIJVR/GxeMZ7curWhCvkpWpS8sgsjl/DBF47f8rrHG0sT6sRgjTUSUEsCqicry8/ygnWS+nLxgRejLn+LY1zIgF2gOdYoJNa2id0ENEfMKAgI11mm28GVyNghdbNUMC+weFTDfzEBdQHVF9IR2LPYr4Ip7R0h8Ivfhfyg4DH9YAWn4H9QhHMgkpLRFhCklKDAJmpnjaKa58PSsHdQbnfWFWA2Qa7RU0jgTp9JwFwL+29R2OTGjDN8Rafc8EkmgRg7tlIPCNCW4l10Vs2Io9WvBWUAx0EmksCOYno7dW5wYQE+RLFOg54IIJk1yTDziZQJJxo+nhWEVRIpHVVOLMybMsBV/zipA0Sq+dIWHrsbACtNgVXMlLPobsmb2SxGL4PpNWMFfcTgD3LVO1AjSaiWMeA/c9qs//jQna2Y456rHiVHdntyTtMIiwjmLGOdvgbisHB/pTJr4KDnJOkevtA7CCjl5HOIcLRJKUjfLOAAlER6gXhsQkwAA8uSk4lYYamb7glnKFyjCPtp1GxzqsSS/uqynCwvQszyAEsPHfdhHeq/HfNv4QZJriRJF7oql2+sv1He6GdT4DDqGwR5+R7tU1trUZPZIcbvWC5P7SbIm3SJVXt6EfzGi4+efOJd9xBrVTjfGvxCEtIl4mF9tIP8G4lnxBIdCKu1lWD06Ir6Iby32mmoPY/U2z8fQsh0DCkE0pqMoZrQvBnC6sZflG013EvWyqhBDcSG4NKtcA1xAT2/eJFAvSTd4kHaWc1cX9EWsBOw871b3FHOLsJrE0XTlYuuiFohEE4kIIhavoc3RjttDRyr+VzO6UWrPuagAgk/VQ+zLKnXUzMO1C4LR1zBqI9NkEWzc+reSCrB/0vD22ij/P0DYTJHOYvbb3hHjAHuo+J32cYxjd1VeggfMZky1Ho4COpPYjEN60nJhiP4X26wPVf1LHp7y65alUvI6lGVk8USh7+95xA1j44swBaCSPViYrqQ2rK+YvYfup0Dl8rFjeyL1udHeIBan45XTxsmWGWfdz7epGD7ZEYSP8Zcap9jhckIuyJy8TM++APT6jeSP4nhe2suCpGwCnW0OA9jVLDRL/t4rZAYQBCwIGtb4PM4LiehJblNrDuf41QJBzJ7LIGhAfOH/uKNiCN1vhj00bzum35oIrXUx3jtBo8RnAvko+pas7Qp0OwYRByNVcY7dJ4Ua+rasSlGqPhSYm/QhQCLWgHcZwT9r8Y5ZYE2YeH3WwApf7c0tFGk9NMEoCUc4+r/XSp+9H+rZhZRWHOKDOOKFCcuwAELnz59jNa80Vmv8iP1w+nxZ9zdMLDpOGXniD7ZPch95mJsQN5MDepdL0+87NrCRddloL8qxGiklR477JY8VfrZMhqQJnUg5WuvX4rxuzyanQ18br9PEuMinHOdPKvl3B3s824MBuQ2Zjj/dzOjzEvzErFmSYQzfPci7Xk+HIm4eh7x+5iiSnxnFuJi1pUJk8s9Sh3rw04lRO7Tma6lBHVolKrYijUJxZkzywYFY/vvVbj4y9MvOX/Qdr3NgOUU99yhuXnrLdwYfbv8GUSej7cSRBHlVFi4i96ooUttNV4r1v2Dkz41/q55TRslzevzG6li5WTkifyl+5gkQdL7cARz1WI2lB1rihYrf9Wlnw7WrUqjDiljv5l7sDnHmWTGBMsljMH/i0CWy72ZkYAd71W3Ogaf9qkGdmztx1tne5gPEq+WLRg5/k+Ud/8klGp5Jny+fiXQ2CKuxPtJoIKGYJKOdDV1nQ9ftHacveYf0MYeh0RTJYDXCVCW1UFsJ4pNPTu6+EY3Daxonhg6aA0ydgwjl12GTSMpoSnrSrZP8SfWofNt88f07YoPE/oCBszBfVI6iOvZjDIMVW6PMMUqz5n4pAA40uunE7BvDuJX5mg8jjBH0eGBEjjMtdB1izSD+WEnUgqvKqrXpHKjeY8QzvV//wGrj/q1DakgSePqNn0uuFs4iSJy1Hqv8R4RJauwot9fTImOOIc2q+56AMs1OrP0/5fG2gwlh/ajfERLGayf50ypcuKYwP+LPJNQxfQyFHI225iaTu6B9bpwX8xO5DQw1PU/NusvJ/k72wImcJOfo6V/mEHqmzAZtKVDUNpLnsU9t2XI6dUi2UwQwj/SSOpS8TBdOv0lg+YfzbXEFaNRA3QBWsd4h+kUDtY9kA6dX56cuHV7EkqeZlrFucI8132Ov115PQF4TfekgJ151oNzXbe5/SjVylQD2ds8toBVcr2eSJAOX7qUb43yfKnyYy1PsBLluVsTs2v46nDvlV+Yw0umx5c1VYYki81aEMuusu6rGELhuYJyrtrSiefDyygdeXSHS2JFSK7hlhkGCb2eoaQFG2Vz7CKp4W78UtB3IRAVxFnjATdYGDOq8pqN3NxcjwjgL7gyWI8IvnFSNUZVZNdZhZBg/c6GbUXi7FSIkqaVQXF2o7NSBu42Bq3roOk4qqCtmdkC1aNm1beX8yoE6PReF38Xjt7Y0Q7YYxOl7qWtrmd0rNq2AnN33ydYt4Uwryb1fI7zh96aRPcswFC8971IFjNy2u1f3TIIe1UlA0s0cQ9IzDzoJ2+UVVe9/P0bp/A4EXhLd3UyRe76N33TM4OGTktsjC+eS647xr306+N12Y63wpMT8qu8tZeJlpTe2X7ZhQT/173G3mK5vWNojoKW3Q4BduUbpCzYKv/PxTz52BRolkOO03Im8KcPARraNjGOlazcoO2rg9DCe5M87nWk91527mLtW555C9KPjHEGF+aB2ttzmq/TEu0BcFj4Xdlkn+9mpvdbfgOZ9utXY/3wozbForwFWLZBjucCGbUZorMdmgRRLBRocOQcaHQUpldg2jTxwrUh1J79o+fd1zSpOp8/bzlJXWczbHLzMu1W43A7q/G6E6TqABb3726vi809ZM1xmy4b/3ItLDMyCfIAQxxKxHT8PvcUSVGRDkY47VSLecx6I/tzK8CD1wUco76+E+LrHdOvcBLyUYBrDCH8hyHxJFax80CFTex1Et9rwIDuBpWwDnEeebMkHBQSklFhpYFzVYp8aIRQ2SjWL103z1TNeBFQHyr1YBmPaFu74tiytBhonGKi3tx7RjoDQH9njfQQa8mvXQYAwAGgoja5fVz2fQwlzP14lRW6MPvfpVHH/rePqcrihQKOquPFfgPlENkZ6K0Er88AN5CeTLV2gLA253npX9zwb/a3d2who2kcHP5V1xWi+bAJiBvTxgJ3lr04j1E3eEO7tlASVK3doweimLCP1K6pfBeIiv4DkMF0zjAnEXzofX9LpwWbjwls7XWEXrkcVPnPznJWO0z+0vrp+FArS/0Gpl4VbfAqD9SgkqW1+5cpmDG4Pzv2gkTaQ+x95aiz4d8t7M2jA975UDl4OODPru2mfFk7XiWsW4ojx5u169YG4sF+qEagQhrDb7zB03sw7o6LVtOBtzrJW8L2YLuAO/mT+J5I5XOBALJkU+2mc1vVE4z6aVRKuKZgfutd+W6mNn+8fnvGypmEXP57Kiyzn+mdQlz66undhkuHxqY4bMluo9bT1ogyerKcNKhRn2N5EaM7bEULirKPnjlFnurF5x+aBkXA9SQRCZBVU5hsSIf2Vz5EPQzMyG+eraDxWANpJExe2BV4Oqoh65zzl7pcdbfICAgd3Q0No/ByGvo2H5zqj7DKEJBobm0dQXfcSFkMredvbUhiDHhCX1xEWtOzpHwtWgJ88GEKYKz7KBCYLmK3vZ31gwowy4mcDiRA9PRSKMTExwRt71zmm+hGJbmxi093heproRiaaRoWeho7TUlQQkfXIVDlkhMI03EN83unXt+/ruKNok6XMRRf/RF8S1LmbjLIYqxYHoDbqwxl4GqTgln8089CPPnHniN97gIUEqnM99cB/dq9NJzVT9lDptQt3msomfjeXUc4Y5/AyUximzYgJuSEUDWnxjVeHdRH3R9ndUu65urmIV3pr93Bby4W11ZuDgSIkB//9YGR4Nmz7ZiAm9xvIzQt7/dnt0G5RaxnibXhAosTErOkdCRF+fVzWr9BWWnNJ7tKlm0QBimwlkZRNIEcHXYjBA9BH0Ce9rMRMqBNXL+bhoLaX3jF1B/SCoHavlSMcirHdoO6x9o6Jawa6KtMxHev+El1XpfR7E9PzFqGpq9rr1x3dIdKmgwDmL5uFrhEuahWIQWb9RbNII587YpOHZXMiECmtiKv3WNTlwKzU/iu7nT5NHNbVB1fcVewLETnWh1ZgdXPs1yDFLNDSi84kGjNFvmQDeCpFYQPaAsJT0zOA02u8gzcJ18mbqcm31ly4w3GOIKm9bg6A4rV2XQkQpwO5YBEVGVcLYcSEpMg+83WV2yUdgH+nifiBa98gBL1LNcrtlKAWuzuXeHAeCJOd6en7zZEnCRLfAJsxzl1z7+7PY68l8AvHdgn1iqyjv5yzt3ylXhQtWCudekEnmQPRNNp808Je6p4iyrzXNoyeNMLSHQivT0zwGtH82yxC4plhgmywNfXcSXx1kJt+WPGfSxu6oWbfaWOMLeaE17QfVYPNynKULEpH/bqMD+5H5nm94sbXtsvRVu0uhvu4yDjWjvy3jutWH/S2f6WYAGJtlU5h1L5KLsf2gahuNUNfEb/LKPukwXNcZYvR/xtJSA/OVbPLy0M4VMVhvM6lZYJljIYRweAyg7fZQzxKuM64SerMo1eZVKIqGsltSO113HtAa9TJtnqh4LWzMduWQMnTpZKERC8qjaC2J1QjcdUOnlyRNLnSNaXRta98DPYq3JVCzSNW7LCJ4E6TEP5+Vn6tFp8vj3vo7tRSY+60AuvDlX0NwVih9ZGqomX126RwY4sN+cr5fXDl/x/iE19wSqFo8d2fwJyDaQX/IJWudHXMPD7LvcEB6XQzYmUgno0takWrcWce8+2b+wfHhFTh8geBX41aKghBaQx47ERKvi/SfoXz2t4Znj6HfgFIEXqfU4AnNWw44h0UOmgG/fXFO3QTYtpwuQR048lsD5Hx5pMl8pZjV2k8DBmScdWfwJUZyBDf1QifJ7wsWzZVrWf5g7Qkt974+7DO+XV9J91tS6mWfIeQLyG/vqhJwYamH6UkGF6ICOINbSyEjjUw9Yo2fIWp/OJ/UxPVSLtpM6sIa5siLdF+AdED77iy19ZI+8SzLbHkf6gPy93dMiC2R5MDKdWYATp8dkyjSm/4gmRW9uUu+2qp8qM7GKfLz+/vTQcPQn48Jnvknxje7Rvo6o952boJjfgBtpQlGp2a43vMMXk5K4p+NiE7Ek1ZSoW+Ft7ShT3VcPTs9PQ7KsErUtfHmz1BuL3ZEqJb/SqxOVjW7MkDFN57cGc7+AexX28Y530ZTv9OKq0rm2luzrbeQtNfFG/iqJszOzj2RC+FFysuQVWjKjAHGkiyG+rIdv8Y7GI2NYYCnTvBqblkXUtJdTHx3YCx3do+8SpN36pbO+3sP7QMBItaI5zuRyJp86zoxp4MHDB6C6iTd3r5Z6ab8qsCQBsTtolE9GonJQ4EL6eiTrkbGzZ+P6MVo17jvWKnQgNMlAbfCTHRSYwhEkHkQ13WPmlIXc/VYKP/+2jnL/hj5tDBKQ8K68QKTbM/4UzcpcjcloLZssC8R/HT9DhOOam0ZjnC7EV4w8v4oZRSk/Cpehzy0fmDgFOh5fESXI9na1oUKp7QLBU/ffrsDpwk/bSl6UfVWbv/OvBhtr0+YlCCClWK+UOB3WCx/1L3swx1vPEeNN5ovJ4KpEWuOMRqOMr5OWX1ohJebNI/2VASDoU4Ubuq2N5tP5KE/HZQ6DOKUwOZ7TqKh2sQe2L5HRwIWkZ9G1rdzHP/UgXQMy4SKU3nhZMYYXSrO9RH4B66rBpWR0TQwuh9cRTSh2hVUGu/PeExHl8ApPsVhBb13VGa9faaqkGDOX/d4xa67thNabohTI8wJk5l0lPkTUI3B47926yZjLVxdMH9+TF/vHnS6SyJzqKT7lfXJ99V5mwxDLcmIWdkKn4tCCcxprI/UO90fLx9l/ngZ5GSqovVGDVhSBnX6NX3U2AhI/qRv8lF0oYRd+EP7DEROA4y6Zur59Qe1BZux7rDVJHRUeCggQ1pkUEmaFOLMm0pH2FWQVKvvIRXvwbKiCqCrFRhwpjyk+leczPBaWSXG5Rgk/IoMuqTcXeGAtD9yFf3Owp3nxZcEj+f31H8PmTJ0cMUlWbKxqQyN9Om+rQHcDoB0/wrEH3M3UTZBhK4dN/0a08+sACpNcAgzoSBMYSWQOPsDaK64qAevshHJeEkyj/z0K6IptIg14gvYjRzoel2lNhKauU5tZ0C9SvxwhIhmJgynDwFZHNuIFFOcwY0Olyok9MMYNbUHrMfK3eKwGUmHHqnI25s8sGRbQ0z1nUC9zhcppErbuC0Z7j3n1tR+8p31sK5p3eb7qnGMdLbetuACS9CjZ+504Df8u1tKuSRXF+J2OcAnKoe4EJabYurN8IT4RbtstQoyNhTOMCPF+ATA2x8xZocyLPxYn6vtu3rtocIytx/4ir3jga0uRySEen/vPZc5FE3LGBs7RYbqk+87fm/gHu1Ed3BF/l+MN+FpjymNIjUZg9hzRl6cChJeycmPG9exLaEeOKKMfByGXcTvqkTCQnsEuIQIihxSANMr4rzitDIWS2t3mdOqxj8KGYEvsFA7j9dyINTc3hSFBZr47DWgsoJ5nWAxku72QTq4jVc09O4LY/KGo5Ru11QB05nL+b1I8FSsETj/ZOX5wx8GGM/1v3In0UehLHwOBRX70A1fyJAmDknfbGJ98WKU0S8v2iPDD1ebYmgKiBhQ902bngERWAOnQRJ0EIWDMSJFsjJF2PJZLYWUPncp7KQovH8dZcUFj/3olVePZWtRrprfAwkjBFezfBsHcrz6e2ldmccFCBdEAO8mstpQXCva0MkM/XyfID0cZ0pFVfH16c4ObpZcXN6vf/axvvrFefpQMRop3EU0QhG4oYjqJjoQY91Lh7cT+eTsRC0oqVjv1NvcJsL+XGM/+v6Q0UVkWMwxk/Xr4MSJgvhq5SuOZrX5osUPqQuOZ0aQvnnlIKvUcWvuA2hw2v7JbBs2FkZhrH9VqIutPGPPiUsqSLu7iqyI04/5G2hJBMbAjhMDAOxFuJj9L8c0MgZWKZD46Ihu/hfOHKRuBF1q8dObXvbUamduGVRsf295KWAi8diHUljoMCLrygXXOAlfLpGDahiEAbTb5+UHpKlXPym9hRlOlZzvbhEqUm2FJDzUW19jvFoG92CDjyudy+npXxrSL9jlPw1q2rPSL3jgpQxqwLAt1sPCDKQAQKzjHgQBd3YHUZhGBwyY/wSPxrKueTSlI2Sh0lcmB7UPM4RLT8s+9O1Ikfl06nYVXKd2JGbPiZbWwbRgbf2817++GJc5en4O23+hs9+4IMb+GDRRBDmwkU/ionJjlg2aGNXLbLC/p2eBzMDG8aUk/3syZekPQFv4Ge+E5B0H8y38QCA+nFTIh4G4oCABGGif7AnSq0SdQyYBD0rBISFCqW4QXvO8pju+GUF8R3Mg2u0u98sEe4L9578hkuV730UjPqsTAd6ttsmpGYc6t0Jv33tZPr9BCLWpFce5kFc52oEv7zZopNrn7Q0iKxwtZBrTQ9Ha75AM+c5tcv0gNvxmAPpm7L55IFvL32bbzTFfMwLKJ6Ge7Q8IAQbglUb5UV/t89IPpdlsl/9DIIHKDwoMhJuaQSwdBZlHN3maKQ4vplLncYKG+GbLnSsly4QW1LQ9xYEb8WdT8vMIIu+mXVJyQT4YgiE0SftWNecg3nAwwg2DF6sbfZgtnN12fFeopBuDVhc8V68kPQ2+yCLE9gQkeIL9jJAf70Lq+zgzIJdxzbJY4nvk0zjyDYY4H6nSYFvX0iq7buyOkyfv5xcq1TaZuH3rzwOE1yV1oATEgWsuIxLatnTTBDeHYEyFhtw0N1INEbJorYOEX3zIu8hSjSzwA2u/ctX1zU9JyHsCY/TRdV7xSAkG8hIkZQP+WQT5c/6vUiLxm7+2B/BZYTnqgURmQrudyBD1q3DySXca3RJcu6bezB04cbJiYjGLZUBetby5baahVm7ok9y+zOQ2J1WsAh6R7SzsOpYpd5GJ1Gaf0/FCu7XzyRGcXpJYiEhZZb0fujFOP8mTjEwunfBReHKUk7IjxLS7+SJh3iytP5MzUD7ZJP3ekqRATysx6PNWNBtapTeuyZOn0PQWaKO9AiOhFBIxJXSm1XAzxkXI3WEZnBnztabrJOf7J/8rocg+p0+llztmy8eIAGVvqtp7UU+Aw69e2wEudMXn4lrUfw2oHlK71rFM0W2z9ZZbNGcEpryuye5RJvERGyX0etfTDL0c3LP0czBcA/OBOLE5icXX2oqC6cda3u5aAvgumM/n2dQ/1YzqgkXF+UT/Q1HMAvvVuMnH+5kagTEvk8c4CDaZ2NeC36h9ALYKjyToqV5Abkc8drlsYkX5/hui2kkXWSpsXeNzcd69uRDh/AV7+9XqXXtmQJE4xB9FqsiEZ4+/a59KsloYbdZ6DeQ3YZaPzTfsLHbTYpLpl8JbdzX8hR701K3pU7jVC622sVi0AfH3rUxZhLNfgUrmzRQ3VsUU1xv8d6zQhQU6b+UdmaWZMElu/DvNlbx4prcNepbM84bmyeDRJISjcpRmUNlKZOgc0m1S0A9udM2XfhSXP9kuq0Lo0o0ASAcBbpiU4i+uT3d81p87g/ooeMoht88CS0kycG4SxvMKK6lvrKQvPPDEu89sYN/mYIIknQokHSGguGgemwse7JA2sqpD/+q3dL/+k9v2JTT0t8flW1Tpl7r297vhyQP76n4wOodzMqaJMmxfvi404cJfRwJAwLAP6d5GCAALhyFazxrp9K5LZjgOG6BBVLLXuRVLWxlSVbHuupGbjngGjkUgsu/OhT4cGARccuvCrsR7cKNbshvghyq0iYncCaycZRqSbb3hIv5dv5HwoNRAdoPfua/zj0MWRsnRSntLmAsn17wK4+4SysV+xUycTDBp9buLBpMXqkD4rY64acDT4VHJNSVeMphy+qXZe6cvXnDsWtB7MRsZM1GXuftvaOsvojqosyOfvJpxmGurcrWMb7ztv3kRqXSPChMDOFQc0tQQlm8qJ0FuwTNmwH/5SnNfhzHbryjNlUZoXJlpHw6YEGXeylBFU+Z1CeIjMXeySIRc4QQyn84ge5aQPOB73kyEsIKsm43AiUhI3OoOeAtm+Z+fFvDW17NDfRiGk5k8Mzfx4xPC4OEAKdKngV9LVM+hwfU0Aoo9sGqw1m1ATz+a+ylEO1TjBoU5+F2ilGWesMMW8MEGMZ8DCnrl5ViTwQEvZHa3EyVZkqMn3kCtF9KwJXO+VzsA0xZGu6qGsv8XDouv016Obp7LNRaQ5FLKFGByvH+LuPe1KxngQAS7rdaPmowcLkHpG6K4ZYI+4BZJUrBFDqGZXv29vum12qKv6OffDMes909trbWU4mnk2w/5n9r8Nas+SC2xJF7aI53N3XsQRamI0pPPn/qV90tNdxnc9Xql72ix82Ge72ufKY/nXLUJEArdMt2kYKBBspJum8+OahZt3qkwAqPLNJtn8XywTRXTtF92FCuy4tfusecgNCHqUYazJ5VAscNGj0344OLhtVaPWdYCPWAvnckemDiOpFSabzWKz41xScOmBlJSCGvYcBanhRJEfpwkEVcF/YgK8mRaDfTDu0kwjGDpLAXYspZm7J88yudhpWzojibYlGuXAHzdlv7ViXJBZH3oBTMw5kc2HIID2L1Yv47X/kp+GxHLfgbjLJcMb+1WB0eg2pd0smxQAs1xMTqkhBgQzkUWXFutbTs6tL2IRLNdFjnF0y0Y2PJzTna5il2oD9bs3OZumK589lC4PFaBlcCtkY9K7557q2DuNLj62P7nKKwF4r2Uqw7X9gz5CcJ9Vy3NljOMjDJPSrD9DQtpRBtUDHZNR+iN34Ti++IpTtz3AfVI/FwrADOCqfhBWySJCVD+CJTJUmQBJsH99ZS2ZJgbpRY2k7b82y+bce8kWe9IjFzA8pNDQ4ilUu/+OyeqoBCF13SAa0a1XKQiyVgO6qL5RDEOYvZrJYauqRgrj5wEUN2dU1M17vyPduGDYXvtRyjGfSm6WgGnD0xhPqnSI1dhZzmag4i8uiQgb4uKIXmtB8wwUepWL1AmZVv0VZXVYfeXfAxcqdDphVCx8VzEo8jVU/vM2BgGXS5e+jvxjHx6Cq0TeJfXtDXin8/aBSZheDRiT5OjRB0xrGUh6Ieb5R+s4vdf4HIp9Fjhy3ARPEV/26p/MZPNC/vHNF6bXggghYXKF0QRPbeL/xn5ZgA9KusqoPeOsTdQ5KR1xUOtTUDvwPTKwHGaSPn4LHq1JrCZFYMWRmYh9RN9i6hg7sJRrJtUnDmJo6oh8rd/V5sKxHJBGltZAcuVNuDBemX5zgt+6iHx3jcI31sdLQ6yJYffg5mNkayW8ixbKWqnxud1kQn4fquCMpPwz/4tURlosgMlqIKCm8VDqS1ah9bcvgMxLws/0PAeHahspeTSwEJcTl5pf9ycFX9fp6GSPexbGl1Gmj3M6/k0N7Jjam4skij+wwLh7bFVMmyav28aVNgEhMpHEQWpnpftToxLOv983ey5eqlMD4SxpvpI5PeLoMhgCM8abbXz085/97V6s056sYTLguclwZeZZWSrkQvMnmc65K3B25DnEpuk1/Ab9fc5ivL9BshPWO5aexqzKKgROe1+8HclievPjbMuJt0OUH/Etm3VAyFVogaPRMLsny60Mta4yMz57LEW3O0X73PnxtZ/ZRqAExc2Sd6KgJ/qyUyQ09mD/Tf/+TEvRyZ8mU4H0ZGdGhbhPuHQqN2Q45uE5Dv+GtD5roGr5RxyqdIoj0J7hk1Rox1MbqTIt/tc1BLEzTak7fymjQjCIaa6LvLj9U9VbWj8dmD7eXOyVjbdZ4bPixpPW5JXbL2Az2tcXEbkE84NYaG9aJghMjrBbbQjXrjQdkf3n3Nd6q4zvV9Z70COJXdprAA6Vv4ZUesN41bjZUrU8LCJ3R+ub9qta03cdGUajG79X35A0bYsU5eBhZ5TYXgVmE/2lPtrYqP3I9lvOj7hwmuk+UrerkPKmwILsIiggdPI1fjPInLzRtqH8tK1Z/OGp8XIjmBLm8NQdgsQs0tAHHSu3AFes7XhIl+A58bCsv0gXLqvWUipkJfESWFPW0MGgoS3Y0vUJMdKjXtN/wl6bidXJKe85tyT9ucCGyz8wLKKoVG8Q2P3kJXvmbD+ciTAZqjznrl6CnR3ozsUEgy974vzFulhvyiQvfCJ/SBQ4ErIwRBzgqHSs1pfg15tpq0+RI8wQoMHKWVtwaoylHlvdxVop5k8ri7DdWgdR/v1/Sw7NvS5tIEUSJxAwqffjNkxzA4oVNYtcVJANibHx4Gpf4k48sSsiuzFmSvygdSeAsoIDHtFoa0WHqL2Be76XJznbWZAlQkwTy25PkINZtI4WqYLa1CVq5MEkPK/XRpFBaWFF2TGe8CJS42DAGZsHMlGfWzmfty5Q/p4oIXvuYsDROd2O1BxAMVs7mlDfxEWqP80zq/KAEbWDJ6LU4w/wgIWS8cOdfrH0CvnDgLSa1kUg1sHLJSYKUxrODsQ8n7ESq1SbTJvBSyljk2U0j+UGyHaMAb8FAi/rgjUmndkqcZXgveqAa6h+aJfZmmunv3rjYEuJOXzVHcuBvfa+PbDa9mw//EBLt48RteeiOCAXg3juMETdskuhwqbcm1FjGQhQiql4fRjV+5ewUc8cCbPHGJdrVCb9t+faqVY2inYMwhKT06JMEc9sg4/eGFUHY/GkXikvycB2HXVAanqMgGK3SLtZCe9SZKOlKWI0ZwGdD0jVbp4TC1FBLJ8Ty2QxlL1zGPkzBXsY+NIGU3wzKF1Ma52Q3VWtgGM/p9bvsAPyk1dvPF+9b3/KhWwJz23Sa9gGi33+QHOUSlR3Fi2mrW9ZgduxAwEDrmDT450Lt81x9lUriz+0N01JY8j2/zjyneW5tgDHrca8WmpUld6aAZ1xMl28MpiqSgu7gLRHzaUcr7y2ndYeeyIrrSzzgVA+hv133XuehVxV0zj1dmYzBrcaDQX1gO2+yHYQ5LBOOMz6Gloc/B1zLY4vrok12pEiIy3Xr6WoMlRVx0VolLpGgQSWEfkiKEruQxLGldHTmWJ25lkq2MMOQU22qFNkZc49rKX9a6LqqNJ7VzKTsHprsR0ZvcV/FXY2lqNSxSW/vo6X7/qfMTVjOdAwGqA9wbvRwut2V09b9z04unMUvFFR1ThrsTglAHqQvrFpdeXry6tiTu6OPmFLMvr0L73PM/WrbqBvPYBWrtza/UwRx3nJJYQLTbTtLkdu1eSEsZbpq6mnkDRqI68VH/EGmsCfRAZeGh4JjIfwRojMl9zb4WZgsWBZIASiuAQ9Eq/Z3kGXS51iWcN2uVnGOqLD54GRbA3yEXMsyxn/qrHunT6dkHjprC/o5nbM59N2ApwjlbFTKK1z6GA1vwVFEVNv4obvImkobbjrb6oN8zC6J0+4csBdLzZM2aOccU/zWtcf9WU/9ZiPMI6i0coiljnfnZT+HWKPHOwKfO9cDDMZNvJrO6P00lYsWdCP8clHwdlnqc5avCTN+f93w0xCdQttDGg4gq1/5vK3L+369yVwIX5QIxQNKwe9BUHP4RLsycXdrusqloEZZ30Z3yJLDCe4na2NT4bePR78uGD04VzJgsr7O0tICuiQf3TQik9f+zanFRjFIX+UMSo/kRE/dNYnUnlO/F3uSHp3l5azYAYO9inVHVwTC/jxbm4z/ODcppxDzKDqs6eI0k5q7cN81dhszeratckQ3EIM/kMjUnarn5qm0WU0uilpfPI7t31YjexyAdgQbWsy9Gw/wIvcrFwFy9BQlm7gdUMIb+7+csCCoiLhZY2WTNrhX2cyZnGTCrB2vKllK2WRNvTM9c7rZgat3EHWJYwy82HrznAN6n0neaPuDDHjykG3gLZ8A/b/0M6kuVJYzPUGA6tp8NPJzZtr8HykzpiL26Uc6Ef09vwOthPdGMdVWsi6++Y32l1vbw4uq0YtAuPfRpHYkKy0qV2C8bPge3an8biCfOXsSWvVGNTW65rsb9LMTrr9pS8G5iGVxGttIb3TW4+utDpaG2T8GuAd72O33Jwzj1EQ2Qvr2FWv3ZN/mRoiMK43MkDkAU0T7qsgNA/QHHX64P2MKu/BV286iNbyOUtThiV7AiysRv1/DGeEpDCRhtAfEzYAdP4ZopeCaNu3Pl25CZB/WNSMaI7k6fFQjSFcTrhvmBAuCXtMRYXiJSgXxKkgnXZgzDWBmphs510XYuxeDSZDkfVdKXVgr++0XJzS95AGJAZfNXJtvy3yNXqWLT8Mt7OU1zrh4aA2dOaAe6KhGio4JdOLngf0aHqK5UZYHlvVV+MUoFUnL3GmVucDcASctgq8LgG6X8+mpNJwqje7l1YN9yoHMJv2Fxci87tEd+A/jBPNr0s3jkh3rcn7npnJ5WX+jTeIuWuA6dY3w5eHcsJ3O2+kmdyJjHJYMkkJKQbHlBPMELqkKR8lvtDn3i2LzGljB0Qna1tOP12Qkv4Qu2J2RYLCCMIA2RPDl549NiUVFdwN1o4fhRHmo9oeDdQnB2+4SK2xMlk3tThImQeW2kfKnanNplsVQfzQ1XvEfrvE30f240PElgE6g535e9/A3vCQ5D8/Q419izIV4nOJUUyDajkD7I7YY1lMvasKzI6J3GNuLJ2WYV46699wO2iK35eB8H4E6pL43zwNMPa0ZXotHsoYX7xgyNOggZN1UEEATXOyeyHl53e8yQqaPYskE19/kZVCB3i+LEf/+OFaXXvwONcQUkTstQKOOvWdtrQn9//Qx3K2Gl3LHQBbb24oBjZJpHRhvfqPFNQPRWDIeaokv/kQbdWi8AqdNgnsSqnh6gJaFRBlAyhLnUlKlMcMja2DK47LsKWFjAOUmJC/Jpngq4yjdz6C8ZF3/VQzM/dD3WYDh0MVoIecQATgB1eRCDlJUz3QPJupKyucGbXqRJbZOnhYxu7Ych345+hWi10OnfWMzyK78SCA4IKj1kmW9aQE0BziL0zfYDuB3dcc8giXRqb3vI+P9mrJ/NpFp4GqCMYMJVjuuJd6Ef0NwaSRy3AJ9HJfE15cZnbePaKGb/c7aW6/iBUA7sjT75+qGkf2ku0JicrUUDMSdtWhtXNu0aOuGCA0WkfmveGgzsPMoxJ/50JdVsEaf5fAcuO2eGt2BMMDD6ND4kPgtdF7RAGr0/fzoXqKLfgidvUmu6K20k935S3bhmWof4mSgu/a2HJrKZTYdROYdVUroxJAv7ohsXuU3KGV4+5/5urvbkBx448T/e6LPaBjaUbW6TmlGuHAl+dGS03a487AqBpg+q5rD14MvVeFtPAb3ZtUyZ/jq7RpvMlnN9cP2eDa1E9JEhkttySbmBqR8PyKrQrmq57mfDol5FA0O7wZ8qVUbo42yatcsxsfg/rsRSy/nI/G3UqOe5MixE7Q6H4eRFIAC71UOflGMZ9ExXsKJq9PZcOEYDOFYNPaOn+hL+tpr0gCE5cMICOdrmOzPQ/k2Bx2GMx+FUYyYrmyvSYj5Hc7l2ejnjCNtpIR/esJMll6OFFGWsJU3MtNPLmJieau2PSRtlN64S8zrLuRz2kc+j2rHO47HKgYfAfdD/cVYSVfUczekd2BUnSjk2tI0qdOS1xKPR7L4r4HkPZWdU+r1q6ju2uE71e9rC/SJr4cYU9YLHdZYZZ8X6erszwe+DUrfWHM8t7HvWHl2jPf905UTerdB6zgDICyjuNJnyd1WcNevPoczP/wBZoBLpQTdAp9NWpq2WUaRp2t2BboSCEltyN8F6vGA+xzYH1jEm+9BasC/8K5AiaqNx6jcPdPRN1pw4x7aJCY4laCJHZWkVqnntRRtvP3CtO6gzn1JpjmKpEX4+FdIiFVVQZSqnXdTlHU2nqdywmXzDCJO+nub5cRg09d0itcr6w/0Q7FCwq3AtR6U8YF5bV5iNWt+ogUcJz7D2y6dJXLl8N6GZ/uCUF1sWZD6B7lQ5JaPNN8tkvVmYRdcACaigRpxHoHpRuMljoW8xmkbDz/7PhtW+BvgRkaSCRcRoLGRRK+zf6lBQM5SgCQSE0h2ABHdN+35oNKkyo7Qdtyp3eeBL0/HD67nbEtf5ilZ/Lg37FeWtl5RILui8H+A/HBbja4Kxd5a2c1tLdP6Qbn5b+0XmeoxrsPbDZ6RjX5Y4hYQu4BhvDsd2lXHablLNV/koFvaNTukOSvanQWU/EbiUcxEX54MxxOdksyfl0woVD8qjdJUp6DJd4NI/ujX0x72821IkG8amgiTsM0DddOzedySMHeXrOZtxXJL62ZB6wHaOuYcQsxqAkh7oQ1aDEKLnuCIpujRFmsC6lx4++H9/Wh/xQq8YwzI4M2drpjRJQ3VMjwyaph8iB3nl1BvUyQc+3Q9XQ53u/putOjhRNhzRZiC42NImaStok7YBb+hm/PJvA14t66DDFRqmNC0KAfwaEND9JERCkCRJETSkMAoqceDFIExM9SQIRzoRA/b7A/1jgoT4JR2Rw1+c5vD65vUN28qAa1L35sBG1RMnoGPSbxvhyOgzBoZFsjGHza6LKugnBY2zXo2SGEi9PJ0OWEJbo9nwKDuKxh4tDxLvsG4kRgovuwEuM14/PiGtoxC8UBj8y5Yv+ySvJkaiK1N7j2+uvLuAEjbUkect09nuQEro3nQyrX492DKL7sW5Rpcl9UYilxRDxdy5AnYnBPv11lChufvZd3Tv7jYIzuWkrCwngzFgVGsQm4F8HVW1S5jLOhuT02CynK35d41s8VqNbBYP/XYU5KJCP+zJV/JwFFq/YPl8Gz2fIS8NQGcxVjEBCakb38xIkzQpIX63TMw6pjOl6rpF0adEW7Lz+zY6S97Mg8N3h31ESnEmj/55O4+ZHIyicWGAuOAbuaKmlGboeg9kOUheM+8abH/3HUiN6+u8ARfyORp6SmcZ+DpDHbKwWMIHtgDa4Pu/KZDaV4aUx5uRq3qCGWDyT9LfHchow4hIrQaIN9e2KDiPkUwCDwXaK1K7LSH11Ae2QYnsJm6vj0xCmbdKkVUUz0MGZ4plHQorTGhdyDVDAeZBMXkq4DSYRNJf8h/fbBhXVfl0EwHiFbO5KNB1Ns+JhIcbp9v64NcZHdAH++Sawxhm7+SIqgkNt6d6YIG49vFT4+0J+07gDi+X89DZuLuNF+RAKztydo0AGVYJnVCASljpDvhQuC8ucpoA6WEtD+fB2PPk5PVwZbTTyTETkVP62H993FtkysiDnvoxCR6z1yX/rZT9k9ynnb0F9AFGTKuZM/JZMaH4heny3MjbsTyphm5nQZ4W/0FtgZ2eXCBlppucoOPpOm7LRBKQyRHhvKDcWegRYSY2TjacYUNrFUnvvknY2v/69egvqkueWu5uEMwqGBbuIkhJ3IMihi33w0FUA+F0mIQRXUnSTOp4bTo/tE+MCCZwz1FDoSkQk0K62R3L3MQn8/x6FHqBf1XTjToeHsLysIzRWJgJSMlJUTXVXniHbVfXms/JL3L5kf56y/3vLNobqpSZh2HMOZd9SLmdnbW2uqcfSTJPmxOb6pLvmNdl/xo/d6cNxIiwHEIQIj6ampXI+FymXyYh05UpuEN0kHgNQyeRFAFWm9V8AOGNwhsz2NV8xDHEj3i6Q75gvQAtcVzQQ6sKAdQEoK8yGR7oFk+sxdN+X0v8L+jbm1lSSC8sPx8fRkQY8/OB/oa1XnbnnLiktS8/0PEnKTwRm+ehFPWnoiEHmZgMTbdY967RbOjpz4sLrHjRHsceQXm8W4At+/0v3/2IAB1qqt/rsUOkhIJBYS74MwrF/hgTyX0sNC8GuDTUgNdrN0EncBeB0bW9f6K6fQAmfVCvu1bSjWj2Y1+NWfLNBRD/3uSqxSKaAad2VfFPdZb6/Qb5rawcEzXkKtgR29x+aCtMOaj8Df325h82QHuriVhRbv88oaAZ0wqbKTSLmgQXKyy5VCrqu5odPRw2DCylPYaLFUlTiY4/EJaJNw9aR9VzjJutVgIL0uh+CTJpYV4H94tshaNfHbY0NJmk+5N+7zOTCp4CUXWzbQ0e8hKRk69k0mdu8soHwT390GOksv247o6fm3Aypx6gpGtQI/zc7EqQ3c/GW0H6vbvlTA2H7iOdPA4TY42qM1L+aTq70H0nvum9vQiI/FB2C7DFYmTpSsLCJjKVgsWuEMboYEkczCFmMFnvrrncDkZv2VPzdEUvkGAa9kGPUYD6dlPqVTfNQ98JANUWJHyCm9pS4GHDE751q/CQI4/PoRzHMMhz2df0sc8MMaO1WyLh8iPw83/Rx03u3vTZzZOipxVYDUX/lxfKPx1F2ao2LILYi+xN/xsy+P10o9O9IIxIvhqGnaRkoMDyUtjYn1B9TjvkXEdn81snaPk1rN2DurM+A+IJIOw+3/RrYBVPFRLCcHV/jq/ZXRq26KdyUrzrQblk6yuBpB82kpA5A3CMkTYd4HeG1SfRr2u0JwuOG0Y+BaM+fYdw9wbRlYUXdmzu5Vx3qsO/VxDKb2UR6biM6ACUkodVqDktfGQ0L46rYZ3pkEcOi9QoMP4OenX40ovkv2fykI/gW0KYPuAV3gg5ZfHdSa9efI9G03nwoxEI/kdkNwbZVkOjjjL42nGImv7J+AP44GBPKf2nyg0W3CWM5+pxfJeCFfiRCL9KM+PUk3Q/fmw5MG7tHGsLxbs+mu+o/WkvPV3alN559s4DoB2lWvGW/y/XQMdx1O9WrB79VvO3oYASUmXyea4hviwPYAy3VGG4CMJr6URL/tUybJoBI3zlNhJaK/YVEI3NYNenhjVXpdUcTPz3p7K9V6lk2YyZGbEiU2jL02Ps9Twr90MRPsswsvCBmL7vAs9YaKg/4/Nwu54lsn/1DsQzLPnb5njAyuXhVecakMViTnlBp9jcc+zcs7zc+fxUiSQPVqVTH9ReVJ14+rIbNX/9T7W/HvVQdSb0iIjvYHr7ebhpAIidZbZs8r9LEj/G3sll9aK7Zf93DfGfXHmqedHqofV/YuACSPt+Zfv52l1Q8LiZeQOxClOiWnJXCRpeMb2crFuNBrM7BC7PlsDRu+qrfOH9cFxdByRfdzAX1OHlPOz6O3bfI9hQ3cAhhUS9bJvefY9FE7xANolx75kejQXmk6m+S+QwNI8jZxuio+H3PH1eNfd0GLuwMk8fVlxQhJAOilRV3/M/L/zztrHGzrdLuuNB6aSzuqBz5in85wQQZNkBPoba/zaTbph/81XJaicEsrhQwIJYxKIJTUNFGcIV09HmhZwNqWaxRPza/nvOZvjhknaL6y+4y//wpTC5UiBhK2BusJUMN1olgfp3H7b39wyRXxeg1FCzYNJPM0vipBpvImnMXmwSO4SG2HE0jtEc/mpxEzwC5N43TSHxJCr4WrC3CkeKkcfu0Bd/1SkxryOHoln7lefaZhwwtnkqGF/+vNQxYTY9MvqqAjX7NF8IefdndTpmF18PNFyrwzfFwz6acWvUng9n0paVPJc+GvuF7iqG88hMylFGtMXZ2Y/vYR0//Mm70eOXT8dp1xCzdX31El4CTUBbm4Y6515TVTJHYlw4+qgJiBN5uqXtPjhc04GL51dHQx8pI88saAOSXxv2O517CRxDxF4Xe7g1KgfAQgNlDOsCHpBEy3bzkgWDjsgalRkg124VwKJFVowmthIwComtQUPJur/F1gpsxGMxR2CM7Lri6hV/WWKkqHFYs3yy6+5HomkMz3r5sGC6y2jTMmk1PbViJByJiqbJl0xCPz8/iYlytAJxydoEanBen9/oxeuRtM5dk5Ny3JZGL+PcTp4msBLkAjthmWn5qRvL4nPeMVP4pUmFey02Bm90a1OtAkGGyNrhJXMlhtXDxxnnHIo9k99iZ/ylmlXOO7qs1By2VSkcF1ZuVwHpk+ESJNrBXgoZPyIzKLHSaUndX8ykSra8CKSfcf7Yts9ShRk80id92+iUt2KfSfk2IvQmZTDhzNSfNd4H//sKSEaj+UnEwkJL1+3YCtFydjlayPvkVDXwpeXqhJi2RnfQnO9KsarH8xvHvvLEW9o7DneQSx9dnj31qYYhvDrXqhDtyTF5z+9jlN0jGNVmOwBpkku3GPpAvsxnNxxabHnZfPjR9SVG60eTHuum7nqc4NKexmWWLGY9ZXw9clhtpBoMbQ2/N5egWtTEuJi97rfy7Pe1JxrUSZ0DctaVAQ5N2L0UJ8yzz31GGw9ofjyM2vEeCOitH0sMFTy77mDXzNXg6tjmdw+xFNGYDstRIUU37ep4/Oqr70eri+cCL69SgIt7d9gomvcBCt8AhYOcu5C6TnHX/YEkGM24BOY2+cWbP7LAv07oq/fjLb4e0EiOh5FhpQVlj2HXVtvHAioTq9ZdRijaicc/ahQeFc5xj5dTFe1vV+dqGvgqcturBtjqWyDZZh3EEi3Yq3Nduaf+7RS8dizx/3fIqMhc4bHQgK5GgNF0phhZ8p9L9sTQJwU0147y3bFI/q22t8R68QNy9D3a41s6UghXtkEqBBsv0DCcyTNHqO8Gy8Tg4Gv7f9xiK1WEvBMvFTK8IAJRZ1McSh84m++5QyJuO0WKyhgew4eL0lj8n86ki+FCklgkZ2bv6hKbSdDpbiapRWj5pwHbCBcPh3TVZxyfVyhZM/c3W+KnIZ8eCs5PZe0mxVRKP59JnfQdtcMVsoT9VBVdKBjC2O+fy+Qe8M997xgy1rRMYP2pSXLRWyCb4lap8Z7TSU9CYd69iUJOua0okcL5dYlzHOyi6PCuXxb2xjZuMgaIvF84pss/Ho9reQGwIhLSAgoquq3pX3t53KxfbXJR3qiz9tc1UnxsJqQgZW7GbhvhbcRGc5QEI33rZi/sH5+9YnAqRry/ySs2hrPlmp0kjuJaL9oPw5VOoGYk757hJcU5kBJgFzE8U7asbft/Rw8sFWzNz7rkktZNmohDEshKhmE/k8bjKKQnagtlZ7KAQkE/xrBH3FcFBNW2vT2Timt9EZDlejALS3vINjviRrYcrYydcOGLZX6hu7FDeP/cGKs192/Nv2RKvh5pv7gV7Rv3g8pCrx8PwAbUrh7yZ774GBPfQfHVLUaaRXffcE3c94DeqhYyOQEJrQSlBEt0oKBRdcnu7QRQAMjT+2yTZAcCA7Qu6nJAMvR8mPBLqsa2gGkeBsxxZhSZCg7QwNdkQ31xPb3u+K2z7Y0so59vLpJVXlEsgkovCmetCy+fnB3ei//nT4pBIS+IdV1MBY+Nu8IQNfxRYQKeKAE0lKrBjGRzC8ZPMv1DGstfFHeuy/uvBmnF8tYvlEvejq5LUF4tmqg22DpAELiX+dGPOH5/NC0FTxhV/sxWULirVRC5D/56G9s17WeP4PRQBlHbGCAsxs2vq5g8UGjd4dy6IWBOLOXlJvh3p9t3tN6kDiS0f5SYujBJghEixkW12vkqWFvL/tGJPrYK+tTVoVkZr5aLkgU/XLVPWIlVtxSlJYhofEtEz/lyVPEtysAAQisG78PmxuY/vX1NZ4Coizq4lm0HrC8VwOXP6lw8OSgCJsFvfacKmmIzOMP2oXdguc9bHdi2/oDYj7NlTwDrdApi4BCTxv3oPViB04o2huDGYY72oX/CaroYZPtc3YRCrWTSGbELYz9woQgJnZfIRf1pGaNacyRHHILM4pfXhVOeYsIveythRkkHHvBe8PIaaLwPfO1ICEIlXlIsRpRdgvdFrjRIPAEiVhHfgC+8L2wCkhnUiLCp1sAk7p5/aBuyYfMxKu+LSIlOx0IOcHTa4TpU06nDns8efnMLLe/pbZvXjD6VOHnCibOtiTUZxhqrIzWFesSvNxIW6UkiY8/wa/zUQzLFL5u0/HPOy4ilh1VkOrlmOe7hl7vONcH6mNMUlcYbPuh/Wv7vX3wbQ7T2D3Sjb6FsjRCULzv78ykgBHrZBFhyuGfQVaO1ZPGRf51Pyij2g6H9ktbzp+DbsXbglfY6bpGQ9yPiLt0hBX+2X0ZzBVqC1EIB810Rff50/wfDccPrxOg7d9k0NrN9GH3GBWILGaMZhgv+lSJqjQVlh7UB0Tkz8TSZPe96mmbmc1cXBa8eWGm9btJ29BasdjXOCjb36LStBT5fClIaMLeMW4GdXJ/cITQvZ95VfTIiyuEqGKugfTf3ImfSsNnQ+hhvbGi6z+0iae0PsXd5PfQEjgdJ/HGI+1rk9E2IEIj5ZUIv+C+IaNuTZ0HH2ZkGoLsrwU9m/uY/hXcKmYu2fbhoL606Fhmave+T/VUzDU/vuGDivAs6uHymSUr5n5Hhf5B+pRBLODGoCERftouu0yHIvNURpmvFTqUgEKjDTjk1H/RrYevuy18EwWL51mDZpORy+K9lDe7bVbtwl4/XBFCZbAhhDvXBROfuoGSiy9gAuV7UAMc94ECurrtqQM3hJGUMfNuZGxlgb6QlsBIEotfymaE4sbnv2NQjUoxKK2oaO/dMt7oKhToFZ5ZpWAkhaU7kn0awE4l/ygsvcXfjG4Kw+NRVLwZ0SKC2Zscmyt1qbNkcOSMYl51LTlpNvZqPxjGicyzkfnfg0ddxG5dMDzbKdYLd+rlwDVdXMz2Hce6ZSsNZwbfxpR+A7AnrtB7e+uIIeHkWg/ml0w/7UK07T737yX2TjPu/9acL6JVNmNEyH030giNNBotr5ESgNyetoga23fJc3QPlJJe0lLAUwlAL9sobIn85KwDdy4ESoDQYuwRioY7EZAWVVzJ9nbihsxYuTMaoxR4GGSH6+52BS7BjzJ20uHbmGYDP+O+JIKSIawlLsxJtrPj5XqYBx9LIrpv4UV8304lBY84FJF3azt+F45+svorUKnud9V72wrryCwVZL+O3ionweKsE7RVYUyw2ZluVNtOKb0Cx0kLkQKFBrFk0eZs9MXxP0nIVCYoqqHTP76Q3c3qoZTV9bfqJ+m5B8CPuJ3d25FtR45oeNPp2eDzPzUGVrVINfsZMXEvmaol731yesJcxIi1mL1AWyIRimj5+qJQjCM6gbiXVzzbncZqD+j1+XKTTTYYPxwkyvTuSF1l/POJ9sTEU9nz2bFEPEEb8yJRMz8dCnc+bu9aOnUqmV9K0wH6+dr/ZokXdf8rospunm27fe5Q7ENOEasFzMNUB2oiSaHm30d8Xkucm0eikuuQ7RbULdsuh4Y6mzd2+XoS3dEVTuiCFNZMLaGdnCmmHjnkVAETETowWJzgF+FLjblDpjzDUlvAGHk7JuWJk7kl53WsOg/1dgjqRJItZj//z12/RtlnQj4W+LoS+mE2+3LISPViU77ouS0In8+1FGK275vi7Z0wFpBbQoAe56/2TgIjkneR9XlRDYu/6r+HJURYmtn5bIl5hk97MuVQnefZ10VOTl3zIwJqawM87eERvGM/cOlex5szpdd0FBZr5W8jfgKyQpYxZ5bWjt8/dMeGhFnHT+VJx3QXZBaOQzhNlUTXNbvXmF2/RCNS0yWtaUZxP35TXLNDo8V5FP6pUljYm3yjjXUdHK3ez5+uDPdCqktxSRaRAkaa2nbMOzR8NWLUYN3GsJ5cBXwEU1MQt5sIbHFGH8YNVEQwQWL80nndvXQm57JFyJiktaK0+3EFu7gVKkabPNMObT+KTrM7lZPwupbL0sRh17KnS/3V4rve1U5Te+KzVL3fblfftDpQaKuSxCrnHTe5vVIEflI8Rp3xhXMiY6sILmDCOvF8qsyPsW8Nm+e7oRybckc1V0npLdGD6HfHHk4GxQlJEI1wJo+KhGwoDFz1tuG1oGqo51w1t+pv8fkaDVcveLwTkmJUQhWbsllk6bM37fubPqEXx+XUXjynqO0KcktinlzmSql0lZWpgfL7CqMWOIMdUE4DipYmbT7ecfqe0jxnDYnCRsQy4vqkQH6qtOhEPQ1uOEZnUYjfGyoDmlRtDjPmysNBqp8WexrM/vFgL7XW3E288ECCmgyVQMZTEVgkMGK2eTDtJm2OYSb5hcrSZMMNeyluaR6ZmwkcZ3V03dwJnBzpInGDWfApLSBempUTl6cWaV5HeLnKHfbkawY14bV8nDvRgP8GsM8EFUV840Nd1QmFezjxvR/XOqG9eIVRsGH52qv7u1tv434uXqK+2/efHmTgAjRUY7MnpZB/81546jr1gD9oD9olbgtuZtaAbM36+Jy0Daz1j7XDKnSA8/ILpiZY/QlBxHc+vAeoCCp2cQNQZg+NZF1/C/34gPmZbAoptucASNcQFOfrFDHheMwAY+YPU/hhWAmeM5+3KQLd+NRs3+Ql3d81mC+7f3ciVH0btkZTHFSdvvniyXzP6gJNh+P27ytP3GzUaeC+pbiSpuaRrGCC4bDbF1MIekRs+wKaJql/UMjDzLXLsO+R0LiG2zK46l8zmTFjLGmhyBaWgb1Tipyhm8fW3u9RXP7alzMpiFM8tdXv54tsumEk4VT0mIUmcJ+Nyzl2ZEM17DIM7EAs1M7s36eH5bNGjAstvKLh+udSE5BUXrJUcOZ4zKwA8B0oBa0finXAGBnpoZGmCOtZ1a9OXZyWZPe0ae5+3R1i4ybGJgQSwOMSVJnwARWtNZMx9I4xRXN+bAntvMA/CwtHL9zcwc7e0dumcWl7aK892AFBSLq88oV8M+1jFUNc0V4WyfmFG08drcojX2cdvegsqvQ9zGfmowSvQ/8ZkAfmbnsItHUePCFtXzHeWlbSDHco9IzE+cjtfekF+4cE7xj3Q3DAiCIbVivDaEjHrNnJA8VfTdNNfBrjljw9rtiELgLu7DxcG0d6vqqWGmVHo2sTHzEtjYJV8PGMatWourNuUU8Ha1ZbXKH5RmETwuKkZxUTit1LnuXNOnr1OwnWfCsaW971vkplBbpC3wtS5+KIycBjwtxluumtHZT5/Z5Zn75DQNNse6ZgK57aBoIBagEE/CpGmpSGiDwUdRDiXEstS9y2pjHxcVxYJohN2JOvU24nTyziV1rrpZZB/tKPA/7jJ95nba3JKLZvSc7UwlvfrOInbmQqOkSQpDmvpCr6BqHFXUXxujvbPmWAY09PCdKyyTk0ky+WZp0/6/2V84O6s838d0ikLkTnVha9mIlIplDUgVeyugT3IFhuuRPJGw4/S/CR61wOyWHfRDcIJmj4uxNB81k2ux/TbP986IX2LMMfHNaeK2KNnASxki2nzY6B5r/XUg2Nt1P5/7dZVX/kv2fXYvJTkI24b2xaSbr/wp79TWrEbFMqJZWMNKZJKpMSpYfsZ/612FE5hv0NfUT4T0DJcG7KIdVbTbkyswwINSIQghDOQiDp3wrqw3W20NwnxXkO37yr10ceZAcu+yUaCvx3d7/7A4N9Q/mcVVd2d2yw/dXK5IoQOuUhETMC0wls9TWCIrRcQZ1Q8B0oapV68f19abGAzczcSiu71JIgqc4nUuCG1HW3wONcsEBefEz8SDQyiW3gD7iG5pdCAqsxITJG1pwb/QrC6rXuKl6hBv0qsobowkBHN9AaF/F52Ff837cbjvbkMWuY/io4vwHc3SmbLeGG36dG1lIHJlKq12Z2MIcUNQzrRPlrmPaOPWv4Ir6jTuJdmXOVeEqiWa3JJ+kDMoLqz7YoroOsD4NgNRyOxbI0DS7Fz+LNJFljy4b6RqMYWsn8v3x/fWLK1GCQ2g8yV9FJu8s9GFyEc9j70pJn5jMndTgTUQ2zVbSP+cFtj/kY65JClKNShNdPMsKOu9alOw0BCs9QeVgPBhr3WUx/2lFG2MPzAdW8/mKTpFQZXXs3qAn/DPB/GHJaKNhv1VIm0V4bqAOtG7fO0x+LtZ0zVJyhaFHpwVpOjFTYsNfH35pboTmoxap7nZew5M232nAdYA3UG38Jiqm1dIVW6eCJtiBORsNJoa7E99Q+EdtrNXzGg/3W5Sk13dZdevdm/m2mriYknV/PZdxikdwya8tRN+mlDGH+ZufbM6eUUceHpRF0YqNTkfxpnv6m9zmaggfc4VnqqmIrub0uGa/70fgbjYhYc6oek6m48J/Z9enqfvF6h5BNrflW1Bd02NRt6CqITm4dKly0XGza83exGcJ0rNK5bASp6jvQHyZinUAOSWZKwuLrtGIY6Ia/nwnVcyPwR3u87g+mrm/3JvhyuP7BnguXmDbAxP8xp5LbkQWLb/zBGjzz1IC68NtRfdEZ48sDtCm0D13ZW3VjRgCizAFxgzrP5BPeAy6uE4Y/f2jOv6NN+0wE1Wlv0Vzk/sO2V1qOq8bk7UdMMDAMAdeNR097qIbxdFr8gw6M5J2UoR3hzKpldF6oT/lcr0AGYtX0Wjb9A63VtWBx25svsELoI44k9X6BIlWhJSSowTTNP8/JE0Ps8dsq9WRCZs1UrvDgWlIP9OqUvYNtTWfxU/FrmdFqL3IW6udulf8Xei33qQ/thQAAB+zhMulVOCY/oicuIqc1oIYoRpHoXf4+BuBUfVFHK39pdGyRArwBmOfdNGku+5IVfvsTDdS6wFNkBiGKKBJJ3T8Od7zLQT40jt8nk2JLBtRAdIfgXtf2Fo1/wIVU2fWWYZmrdu2ocx7qh79syzb1qA00Ba5qWtc/k9VbIYfHnHOLRv+P0y0a8Yt0TlX1d3yolmUIkm5/RLPkx35AG4FT1RKMy0NDHQMsm5zkOekU2NPY4lUFkmdXPeFTwFuMHCVLaJFSrK46eGqCDGI3Szp7Yv4dtzC4B+WUf73jiBo3ALX3T3gD7qsOPyH6v482NO/oU0JOFrBVZhih5AIa11FqxoYTu5W/ZOePbIRjqzASqidPtH57zlLyYs0LUk+yiyqj0tL8sSd4XJ05cAt28p5lCDgYG/uSEDtgbgV5oPndi2VtIR6IZ46zqxwLoDGhVkjRptsGVkNtG29T5cY70Q36+1HDbnJlCABVyvT3yQWZEHhrW4p/QhtVJ7oo5Ixh9TqDLNYtV5OtEJHWW0Tu1hRFfJfpn9qO9zfEGhdg/xvfR7a9uTLf2sjPON45Z7Nbwd8YyVCHaHjLgZC9jwmhXhrVdzED2dv0XFYcV4z/eZnOE5ecg/5waSlp8d6T+Wb0ojAnNAf9YPppb/7UsNzO0PLIepHvhwF0GnJDMniDYwUA3PNPL3XkmI6Mxd51vJBwhjgUJYni/vHPBjJOWgFNb6QfbkwCfFRuCG5ei4e5ywgxVcgLLrnmUdygw0QeN6WmaXsE3kLskES02SA/60UmeVtoftSRuBDiWnKDpMt4L86jxXnP5VZPoQaH7BoPy4cvQVtNk7h1GfXZ0KVm9jCc3WsPSiQkZlQlfP8xUnVXh12eI6/t0CSe5L67vAEjoDuLK/eBv4bRflQ8bwc6vA64x/xwz3Ni/yhduJ8bZ7sUqW0XGYnKopAGOwtGqcrwr33wG8MLO96/3SS9x/WvTnJUXaOspC6KXG+sD3GNOR3rOtRjWgHdOMMBxCjDX3Nn0GGa874niMoaKxzdfW7UsQk0LU15JdYJvwZarRvOZit+HYbcwYT/olcE8qOohIBS5LoJiyhEO3hm1NdUYVzsMrrvdf771oM097k1uZOS2MaxZUFBGUfvF/OIV7hp2CUpCBjJiJ76ecUoro5DYufFYWbCokyxGzQgIkkWvBTJrEfpH9KiPWkT+Sz+8OX5N+mVo789dBua9Ju3XQqSYcAP44kmHdhlLfnqQljdbH1I2OdCbvgCf0dPCdHNBP6bMAXBEz16yr0whpLIiH1+Gt6cvrvgpv0BwvcrqTBZTJprEbBr4e5CwIELGPhl77Lq4iURZbnmeMQc7es/7URAOWFaExB1xOyGTGGhZR5jEBqQcL0tZb6z15ybqi/wLlM+ZuKXT70tES+u8F9MEazvGTSIIxlx3IfsDE9Q4XeSlbjoGn+ZFlJaMpD5cz4JSpQS92G9FgX4cGpr1m+4NaH85h1EL11+SAzLCIOOErH1lpkzNfy7/J1TEI4l2GvP5A3aI44o13U9iBN9ePoZcbov4WefdNOuY+xSFUCh84K/FbI4ZiDsILP8+Npxesxzh3814HhZ2IWqkArV5wVVihL1L7LnYIZF+nkLj5UfYBJC1Vrp0qLzbmrfN9+urqVkVZtZbsGfPN8FBaoLGLygf+QRWVKJGQO1ANscu3HKwTtsfnN9dzz2gjvXsGZrMMNxFjTRb4n2YDi6cw1YpKqsZbY8D6qj6oFMdzgt+e+tGinGiq6cylw6NNz7kb0XFwfRz3jGy47/TD/wu8EMj0CIgnWPdTcdl2A4hGi8O2Ci+bxxfAM5dr5qJmVc94ztM3g4rsXy3sz1b89p/9EOqPekcJGuQs3rl4B9Byo77XvOFol6gtYQ6Ea3zk43yiM38T6KOK1+9kqSzvEd8/PuH4evaVQEF+LFRfdUaarXzYfW9zcUy7s2ECXkz88VQJ1aILZSEdEjim8vgyBLVaE1cSLCJeCSe9dyWHjJee9SrTqyxpYvTT3Yg58Jpk63+0RxzMCgyL+51CzyG6ArJxiyUFM4LBH8AoUOLFWDKbHnWr74ms8F4R8wRtS5eXUwXvw4jq3n0qkBgJWYGnThStHRl8qEbTM9PrQz4V9toKir5ncoLJfkcLLsskSpNrcJdNbXRylpMG+SFz+/vhj7yACXEUuJzU2MtIy3Z6Yj0gRTDxSfLawSrkTpHKFp4alMu23zX7a3GL1j1KJPwoQnTiwUDsBPkJVUNfaWFng56lmltrmTjYG3vUjW8GGqWLR7GSnWgbzImjqXtLNB2P+tT/FacqdgOjpFC+s0XIlTiF9umpXeO+WIqbJtz+yj1F+dXq03hIepBphZP7Hwfngzr8XM4vyD8QEJYkX1tNTHyDQmEN4HtMnHDdZpWglPseNIy/MzuziazLluDzxZcJHetETmycFpu1vZPEzrbHIPyz5gFxTGlZ4GLIpoIKEEl46wJsXtyU5OzIntDvfvqNx+lFtu7NWR6hnkwUfWVSMgniBpLWMXS9UoDibHN+ttLY5EpYEsazZLYtWHy0wBmIpZfm857daFd5Zc9srKn6fgI6utmuyKNzmIrVYoOx8ArWLa+zIkLZMuYnMvsVjRPUv7an5C919faPEGjZoV7ZWQ48JN45I7h3OIpILvx5Rpq6Z0Rya4fI6I5aZVI5Yz7M2yhUf8gtpubYv3Hv0Nvt8G+Cus8WABdfGdVhg9CnMRb2z65uJWy8H9nW361Ei366zdx25kpO1t8sy/dtpD+IjXeUTaSWZtUd2QN7CVhUaVTGZcG/WzsS8aiIWY4fg5E72XtLJof/vQM8FVFZY+Z3ytgSYLN0jv34rOqJxJFsKMuLTjJ1LBhJAOSILi8/SqWfkY+haEMF/ys+cIPg5PV2N3+gsMdnsv/bhhEdmwwTYCKm60eLpt955GNuzg8eg96z+gCqHHb5dxRPLV1O//DX5Bfy7WQE7ky4R2O/ybB5ImZY9qRRydWMz7Nt7AB1ef1L/cgM8/GwY4mgj5AuSx/1khewIaX/9HAuhofJ0tbvZF6HLmCo3btxcFM7BbIEWjGaZRKpe67NbjT53RdNhsixPj4VEixCYx8GZGKHl7UqUk7xP/ZypcuNN2OupuOSDmrUGVQXeNWMw6n0RtE7QATqVSKdMND9DOkkn9Uk156LrGFZcg6FEeD7xKdedHLP28ivTjord8uAMi4s7U6HSOwFUjDJJ9WyfOkvBNOEXpLw5mrUz0JJNqAQAyIXv2OmJI05Gm/Ytk1wrcX++OVu/bLIHaYIPNENtwDWEoqMON2OA+G4lTqwLRxMH6vgYqgxtlj7Y25ciPaZOET79mArUdZZgqCkuAruRFL4fQuPBRrZ0QkS+qvQccPlgw5F/pyZVyQntEElISMhU6O8TBaaf7Ode2Peffkj8xJwgXHqMlPiieUGylTjISJj7yZuMOtTzqBfkpJi47ygk1n7Z8sa9F+lQ83lQAewOgfnK3rzrVegAUP6Q3vY93YGhQFJbl4qlbjdp7E/9aQLCFS2wpXRhLrjjVH1TFSdgtt66FT7kIer6q8ynBLxJ/oRl6pM8wl1IzzOIETTJQmmCw9FlLXY7ELMeaNQG7Z6ex5fH98G1pFNtGvjim6FTf00f5zbb+R2ldMjg+ji46DPCUzz6zrgvXRBuQUKJpBoftbGXeY5sj4y8DwFmiP5egMag85IU3AJR4lGuxY2dgHi7ImTwO8g4Ea196RZsZ66JwzCtzX5RkUTEu4DpxUgGCTD05BTVDNVEkVmakZXW5wIcLKlzLmOF9cflFXSZcHXIixiqUiLRaKXBHFE31bbTk9Z9XLOPY1QW03b/S/NmyS2wo6Y8GddqLUfLryRWQogNF+9VWbBMkRnM8FP3BIbqLPSHnMZlwlUP5VT+/PodNOCGiSJLMPaHZDWQi0yS1TPNuTfPdmx0GMeeODpzjob3M3cJy18ee2bW7l9DOt5VaxO5jYax22YzOQHTVevxifUZPQegnC9ujjhquii/5c09qSKAOuwQy52eNaascXSX+ppCu2IBPROzHssGwI5fS8KCrEXeWqIMhIEhGlQVIGFHwNqozs45OKA2Ev8tuJ0OnmIYM5j2SiGZwBczAHKXtlfvtHQzv8E3Lve7ucQeKPWExtdrLTfgpVOboS41UnLA9GSVwpx1db6swJw45TRyuM4CTzWwitXs3NChenWMZ+aQMJrLQ++Jqb8o+bhcVzvr4jHZkvTmz4NhVLS2mRlJV6Sy4UBrBBN60cxMAioAIsjtIr+024VKR4vDCsxFaxGJ+cnhJAUaS7w6cYEcLFCRtaZP76HoGwB7gAh29ES3dOrArtzUbIdYuqKBoZxuJlx3ExfsC+4KqUjlphEq7bk7p4+Z8sirFLHhqyVrcGfklIeZ12uNi3320F2FGgmX1xsaEcxxRFC3wPAaC6uiyouy4rVtOCnVrZpnByj3dS2DPvIu22Qym1nMVLe3LTgfm3KU+nLPv5dGcCS978Darq9mskZ/aK1v/XLP8en/VHLRMTcotYqJmU7Sl/1zS1k3B112CWPe2wwf2IwfTJED/T81hsbalYPQjth7G9q6YvsHdtLWCOpm35lrEtltlhkkTbn8Xkhxkuv50l9+ps/tVpLGahtD0c4VtZtA0ETs3hSawpnhaSGv12erVvF/++BWpvtKie5+M513oUtSkYL0TPj3hCLf6yYtw1q/5jf9QFeczeiKB/YbZ0Cp9GlaJmASmNeVlvSGM3hQ9uHXx+xRdsXxNCDcNi0BGsUozJdyj7bx/tjIfkZxziP/69XC65GSFJOYz/jxivO5B25aX/Osedl//QeBw/e6LqP351prf8ar35KKK0kC8IdUI6VHIgUZ8/uQqzfn2Ot9BncmaBMznEZRke+0ML0kkMF36f9jjjOsWF1aAoPfTuoZXJo3O05txFW+66EAnJrKWu1inSaG26u2whl1bdPsK+4BSeUTEVEHRw5jXC/y9ith54y7yIG2OOIXf5w/AjTs/3tZfz/hYlsOc+2R8zJsKbustqQTYlObLtT7d5vuf7KtG8X7xHrZeFpZkFuhvigm9A4pMmCktuOu6F2Uee/fjRkq2taU9NtecyyHul7c/ouZZ9Xc6nGOn+qLwozYZoSxAcNyjBwoHdvJCSWhfZID8KKAi5/3pSam/7cuKd0ME7aPts2gF9PxnnzlLIvlikamAGTazkZy4eLYfFYrXwix7L3DuGbogu9lO02OhKW4ut4m23V24k/jqfTYUGIP8iMQaLClbeKE6DN+CJkvQGYqfvYygX28mHdKXAmbonyTB8Z/nLrnbNmR3jISN7csYzsWX26fgyjpfFktOiiNJVQ4DK86KGIdQcfLvGwmx8bEzQ+36w21Kd7pSjwA1m9F6cCXV6JQMnz3aLNGf2OGDtnT9p97wm6/Qh7uYgGHpGI+QQWRsuDbbCrc5JpL4g3OYD+JPPetHfnbJhlD0dNYPToP7JvJTFDNDa5Y4SQE/6/ltWYjONuPNEPfeNvIKWB+0T4c+/S2Imw7bMKEk4AEySjE1LhRtOmvoviqog9PfNXfv3uHGPJIaoTBG4Ip7JBN3Seo0zkpsVUkozJNMarnFTEmPKal+sheS7HHB4Wzu21h8asufhjHLJSHQiwMwc4lumhbpHwhC2wArvMg0wFlEixOgY97c8A2K0DMGRBVjs91N/UKHRs1igvjDc1/6tKckP5Lg4rp0RYVyJ7KfgVGfbgyotzBxNxGAjrFXOB3Jh3yDXGaRnYQGhZBnC50BxQB0fbQd02NmWvc4m1mqtWt4ztk3OjvreUrL7fZedmDA2mZrSrNYUOxlq9xebqj1R/6d0lU+yv5lqYLmi+GmE6DFn7L0G3T/lAvZKJU6aDvh0/p0CmErjHsFe+NV5qMt83H1foHpB9e4NrfhvQtxJKsiR0mr6Wmgs7iTcmFlJfgg05RnUKe6WtMza1y3JDKS1M78cyTUUoIpjk1Ae2vNBPc1+9Y3DizjOM1+Nu0mVn9EZfKGL9RDPNeT9Eo5jWRJ8CQURIzngE94MF58kxrgahxEdtkk0LyVbLZUF7bs+mEjzfqOzFFYk0tRR/Mqqt+4JVM+P6D5FpnWZP4UBhXm26mNXKwd+QQGFV9cplx+sUBahXUmVheHChmoC0KJb8SnQ6LIrw9oKwpHhGwOW4mnDHTDQya7xF4UQFBU7s/6g6oUN8frireJJABIVJhSnQJjAS3BGf/3PiggN/lQQ7wA6TqC2P4/Y4EtksousIcX5dgG/ouni48mlXGqmVoUDwUu9FlhaEDYhvSYun/JonrSgNzZXUW8kEDLmIgCR5ie/TIo/xwFj8vzADTHMvcf+4pB7tSrHKZp1XN5H4KjCbTv3AbZcZzjL9pFruO1/fzJfAfNX2nHjt31NevyxPaKmPY2zvt2YRTNAiPZMIKo0aBOwIAZpyLEAzqEc9aKhIhsUNRpeiniNVd+duR+zFd9Lb8Q7GLUjShOv2NYa10RSvOzP7yz+/j6LMim6ef8NOaWopkVN9K2tgSwp6iG+rK1ViRHunK+MKyn1k8D/td2Xj4NdXassMKp5sE7SkD6tioCGSRgHpq14DMd84EtiwfguElstYQhBjuc+8/r3KS2yNzt/s4O4p3hoXcx3Z9Rq/+srx7qPpjAWAvjw9JOCJAlyDT45dp+00Ppv49yCiJRi+L/jMKRbzmz1xVBi9j8wRrbH50x7lbhAloe8rLmkebjmtx9IrlSMjAkrmeJpEVbrlzBAIEbic1o/PTfOfeD83s10xRqzEQBSJKVzV6yPnsgo4AH5dkiFnmxZ4/ImnpmNR+0utzjUqWfU5zdg8VNBCaKPWraZGR7C9JW4jY/QkVJY9aueMqp+xk6DntRvt2m7kj43R3XPgqUbsYiy5XpbRP1s0WpBvjjmhpfxdz++HBpYt6L99+HfTmgllzTWvwg9dshJ7Z9m5Zv4gq9uShxTYLJQ+IyY0TZzzzvU1UbrBrrHn6Lc3pTQPb4SU22yrE08COjnJRcLMeYEb4ftfr4Kuzm7/vce0+47e1Z3iVhV0EjOelnCzqMmafyK/CsfOxUDFT05seGXZSfswjc6eb1C4x5TunUx+6Wh7JHjAVAHnea0TUKUsc9yMMriGcw5MsBusw53YdYAGgcoAeIn1FKX1TRS3UWz9nKnqpicfgVctceibEXplb6n47NqnruQ5maJj3lWWnhRw0W3XfbjHYFA07zg7YT1kEBDMhaJkKMiSwY3cJEi22byZlSkYnVvqVZ1w9/hjY4x7k6HDdxIBVF++Trh8TvUIYVKmunFR5j4ZEIEYlgG48E4DHZVQoE82dOLe3mzRQhDRLyLu6rMn1rRKe4AU2HYOKHMA+S077kMbkcC3cCV2WRrIynbIyY7CqiYLdnNvwBRIesqPQdJu4W6PT7Y4CXzto3T2N0kenKZVHFJsP8rllhffpfXQXOM4jMs1lcto/oTDg4O++H9kJMsbIarBf7kVIq5MMFGZNvmsfIfI6ubZtc4NRHHFKQFrgsHdlXL0QeWLffxvVCX5h21FaJXl/EXVer8ptFKAD3wCiOjM3bGZ/X7HBg6rXVBqcMgMQxuPC4AAYuReAuUsjHlFfiRQUScbnPVxS3k7W5WLp0X8U1op04MeIyJaJG7+bzzOVcATK0XrKQKyW4mykAfIo/Jlpuk2kQRCMZCXVD6x3JiQk4lIveKcPK20eF8BjPz91WZOttWpvns8kmibY0mWi9KiJrDY4tjCOFLIvDUpv2MB7HDOMwa7D7mDV66V0apykR/2Qjl/HlzxsjAUClytENtkWuXJgYJmvQ4doqsKfsGDND6UORn2D+OoKNiJAjF2uepxaus+9v3+w50qeeWoPELIB0b6I/+DLCg/e36X0g6yZifojc+VvQxNcl/evF3fBKHufNF3XX67wxvDipMyE8u/HvozGuWc79RfRqwmeEMo2Nj6KNGnw4UMAvUgj2q5xnaNQG1WLhKojGci+jmueMX3ioXwjVtS2B2iZCSAIpMVmEC/phWtJg2TPq9+eEL7+Cv8QjJHKhmesZc7YTp6bKiZNlgYblszYF52k0PERR0NszV3lRALmn+rTAiR1vJOHT/ouppL9y++IV78GDMeB95dauK9yg+A/eGCc8Zz+lf8xQwETMaSdtiZtBoXkH15Pk2sUecXvDCyHLCe//prFlSBqboOClAq+bKJ4zjotWs/TqngGNj5VnLRuuRR3YwcrUYCWTdXPKf/g3T45Confj5RXMg/R4kzfGRWmcU1SM8Dw0Ioi6+D/pE315P4u7TlrDljDnd+xLWSnrNsYUopYqUxpti8GdNlGehhSgMkIDRuOwclnmNdm0mbuNCXsDirj9RjMyVLBdKypN0leYcyglXesfIfPzWmg4I/Ta4QxGeupx0l+jJhuUf/S5A9v8n5EfdO1UoIZ9y+t8dzTGfW+5WuyN0iNMsx3Xj6xkna0Ngh5OndjQGcE41zkt1JMYZldmknIs96SXKI20AvH8fsx2AJV3lRFIljHqeWm0ntKpR/fh5ZOoD1W97h9u+svkwL7wCuIQIj/IhEmI1shCKWX9Pe3DeW88mmm7sPrt8qEaWHNuVI566LmfMYwnA8WQWDgQIda/5yOFtcmppJf0AiYuZJ7kQYE49iKYMbTe0L8Xu5cbDSNxv4AhSF6nNN7lNQezgePJE1JQ38fHqmUV8CKqrtBFnlU+oWxHs/f3w485velN1nFc0V61YuW6qGfLg8cSof6JA6NoK1FvnM1l1Kxr0/nHKpOJcQlAq+IwhHWAA59hg2ute+/O6NuBjE5vGw5rXc+U2mNRYx4Lzj1u8fCO/RRTuNGSW++Mc67BOgCtKC6qiuBQQ38nHu/iFv2dLPbO1XnRvyffj91OP96+BBJaSafNOnwihHXYY6ob10S8vQx1OGM55njrsGj84tLK5zzWZ84fZYBGLgdhNhYBEJI1q4aWOcDYqOSJ/Ua/Oz+Tasqtb+xwynI7DjoCZEsP5kgm9773+tM/1ID2vSVDcTtpxbiB/34CRmBk6gOWqp/nRDSG87ceVqx2Z5YePtuzOuJx3bhrZLsf1wQz1SxG1PDsKqdmLetGb+LAQ48ru8tM7NDD4iGQ/wro7YeXS2mfRscZ4F3etV0fiLOU86SRsqUAgqpEDkqQZtgMUerfy9BqRltcCKMw3Kv/NuXL3R8pCq3Qrgq3+nQCZcyEoTkAic57bsU80AVJYOn/mI2tfw1OamTH9ZjOPhXGcUeRaHLow4Np/U96SD2MDlKvpP1TGXVO2O9tKZo0jUhQ/Yb7PbEBntJhkXnoNHr/ke79svTqv0/SLfUGN6+Nj60eXLUy8+uN61THKKf2r1go52BQXAp7tSiLpKmjHNfARGoAj1QGV6bgt1dMYAT8EuTOnL5GoK+JGCrVZ3fOFJ2xPWFaRK7DWPJ9TESQhg8rlYg0EzBCYD1JTPnQuzuUUXVo+VSz2tLKS679Co30ZfAZngtFsFEepWgFG/1OieIZi47VNUrSBew2sR3uT/gBJRK46Ce2AllBpuYTaUQhjucx/NpRERUm2tQ2SvFecXTvYNp74/ofKSashyRq9k80cNQaOf7tN+iaf/B7SOa6Z4GFIDHWK8W82APAZBX3Jmu2Ro7FJRo0vKBd8lflGvdd1EqfT4WYcwzX91qnczZ2K+HT05W8mlexQgV7zCkyx3vLMM3g5MTAa4lCYnHVnNq4BuzoGE9rAxk3V1qQsUzF9T86Lu2/wW1oQvr0Kb0356xODEk0vY9xf3sHzPdotyLsGNn2bBQyGVYWS0HdaDtWxwHnLuVWFfjFz3xX/CKxhGeIJKM/LoXJb9W4Owi7ohW4XW1Nbx+fR85tKjRcZYO1+fvvOcUhcErc1o3YQhhjMeOsHFN80xQzvNtW780/ZIAC/r1Pe1Eu6NGor2g/T30rj366hOJfNdd7Rn2BqCh7J146MX7E5HEy50nn75rB7QgjVBF2zwd1FvOPcSR7pQtGP6enehYdIMADfcunnbCsYxYARgDY2Rns0QHlgr3pxBRNMjTm7OwPQdBZh+RlUMRpnbqpAaP6YhS41n5oq6lVpU6kLdepAG6c7ROLz0nEUsdsKtXaJ4L5DIBGsgQ6PJfBr5qwOpDPUg5MpoRmFlsWrNiF91b+9T+8T+8GGklNhTq5E+s7W5MhxuGT9Bxp6bena+OP1t+/8Ie0sBgS7oG52AYaaZzLYpQ64FeQ47fHoTNIftxamb8TfEmHPMZwz/DWSAlcdmGkvL5M9VmP1NTD+ALaHlnhwIV2sPTLwKuk37MrLOApowWP0lXrs7fP+wJ9VzguKn6+4IZz2yOvrtAQ/6IY4vwZ8XpasRCsNIv1KMZvi3UcwiWGFUOv3vlBXONYbYeIGmaWSka1ZiAKYduJ+wz93Y3i/Z3vl15zis9dAW7BStjoI4ZSQCC1rNysKcZJMU0WEDWwsAhELaVkCTcwKVupsO+R0yEkF9SzUIYJBSNGM3Pg6pI2sN+uJtq4wb6aAp02vl7+J5h51X6EQ0m9FPUyM8sm+haxRi/GfqrmfDyFfE2p8g7cakPM/Ah8V1SBIrI9Ksb1B2c5E9c4Yc79PWAorA5jePPzSHPQ4Z5TvNbFUHlMKNPlSuci9SqNUN3lEbrWsBTSquEOJMA4/JNkeIUG3RjQ3dv+wG5Nhwshsxo2LQ3ioIjXyFoa+bULni6+RMe6a7Qg6TwZnAm8L7aPGlORNpfvvsY5uYOEz+pU5CJmjFwUVpwyvluaDGeACAPXg5ZlBrR6i+4mZciFfRVvn7uqKJO7ajf229eYQ4fvyjEZ76nIvHA/gdTFHJVYDAqZ12VO3aY/9WapcWGFvMtwRPEAednVGQnajO2KEZjeF5oXW9dCaGPHlPGy6ikhgDqqNAsJbbUWc4P2V7s3ZJXopFJ3L/X9HbrZ1MPR54vUH4telJgCA5rhf+Xw6BZZIaOIUwAzimMfsx7lI0+bq3nN+XqwpK67Zo0CF4o6scLgsa4MKYyajA5DAFEBb1uWuF9JHa/o5JEX4B98KT9+1OTSz25/D95vDrV8rN1O6L0fGsnYdobnuUjk6jl0n1/BtxnGvWjIyXpe8N5v1zlqRGc964WDK4VEvMjHhTqPsdYxZYJmGE0azDb9XXNyGoa7vbY5j/Lni5jlaZTHM67Pu+pgRyc2kuKIniiPOrpP8mezqE2w08xOtgPtaE8fSJk/BEmxLpWgNsH38tzeGvKMK99LltTfiAeTUdbbfMF7uSJiCQ+VJzNw5ckzKc79TI1QSlKTNrKAecn2IV/WHHk4cMjMFQiaVyCkxQIaMYg+yDrCQAEI8k1wz73/2bOXHVf2ZnKJuZrrUQTqfLNMtTKE/zupUQXx1Xrgq181VWlmZL0nIzni+LBBHhKTOopwCyuF1RRMZdreQ9F3HX7Q23lPkyBFhkpAJnEjkXYzjh+0+ccD1jzQkU8vQDGme4NNgI0nl5tDsC/RHGNQ1tro97zzbbABhi5BJN0+QTpgLJYankTBR3SRnmVrW8GN2vrqeHU5H4jkciwEBwIr8hGerdZK+KX/qe002W5J/EZCBHF4ZPF8dzsP9wl2UQfyV5bFBIKEoOJ8dnvm8j1I/x068SOFV6ToBOglNsVa86NwemXy+3YDNsTxbY/GXN/pFfdnF1qySzW3inyAFuOcvjxkOOKPammReFEMdMUhSOgD/v8+R2+GoyRKcsWqQwW1QJAjaD+jswFix+TtWljbXV+s28tDC3M+BXoTcWtMl6eliBYloDWkBP/I3GECBAK8PfZAGKMdghoTX6v6TH6TOdJVwSrIE6Gp7ntnU7pBOl8H8aGlspm2WNJwYCOcUW9rrLKduGTjJ6vHC/vQHcvG1MDwM2MaU9BfWOo5bmit8H2J1n/uP3v6HrdOCcuLzIO3Z0HUvB/RQ361Xc/YuwiO05Lq9u5F7FZ9+ZPOK4guyXnVZcW2mJ1aTR6qRZr53w7MShmixkzH7S70YSht/F3Lx6LEIy+zeWZ8V8iRgAsDmHepkFWl+uO9wmVubZmtq6z0WLfiXCi2PpR6p4crVjqGuxxlFPmTqhYKjDkuNwABVcMIvIJMzZaCsandmCO4G/sz0zjuirofWUkqbIjetBeUwnnJj3j2CHZiMaFoLFLsno8zlGG5B5WOjCz/Z+voMSjFAsQ2sOhKV4EGxHdb4hMoDIWV1uXvlwKVGUyy/yuFs4UISlX4nwwRma7tKRL8lcS4LLPcadUPrQ5UgNWnFdpQGvdn4yk03Ly/S+A/qIrrdGMnOQVnzjnX5gOv/Pgn/xVbw7n8cRVLJ9DvVHPdqcEJLPWCfQkfFdPoOKkJ0FEYZwJSOVu16GG3h9Qb6NYBynYMcDO1eW+OTS6c8bfOtRYPmRXpa0/51h6jWRYdX/8poq6Tfj2YGmQSJeD+qgj6CgWumHF1+QlH6pTsQGVOksBhAAdHTr+eir++pKzeA9eNfcdW9giE9FSBTKRn3J1gJ7T8KRxo9jajHNj9HcMlRsvYu/VQravzwN6hrUwXx0GO+rtV/PN14/guMoqc6C15KZ4d6viq2LPKsSq96zsLdxtKSfnQCfeGCXZiAnjtJ0enwBhwA/WDjIDSykZtNDc7eZZkJtLQJophGvKzMX30i1I36Ns0pcK03vUQmAsdrPXzXfN1Sg3Cq2uXMeiqO7Jl9N8f3+W/ms5Tnon/qyuNumdDd0zF4WoV1JEZR//ObYJccZh0+90GuU9gdoQ+xef99unV4jVE7NPiovc6XdVTpVT1ChKHb1WLyj+nUCGnK/S8UkebxIYLvD2PbhZfsDt5U1F6G5yxhE/ZaKCLD0H4jdui+Xzk3xCLye5TpnFTDmhd5PTqSlafGBY4auhrZ0D4UishRtN8aPzT/R56FVEA+j2c456ruwZvDIJojUK6iv13JA629nInkqumXWNti9KBK4v5qHy+MvwgPdszkAEJzlQoCy7jup1+neKGrgELaV8CpoInzBZyDyE8xHihQSPR5NDpthjeP42tIE7V5RrmEJL8EpYCGEpeQupsAezLhkw87J6IaWFz+T8v87eM90R0P/v4jYi9GMlQrZzPnH4Ef/CuNQ6qrRpcoRm0HPjVk96N4WodtKPX02SZLkVN4D/TQ/kt/9GGX101JfyyGrH9nJwp8thM0f5uexr+oNb6Gl763KXnJgmRIFgSkddBhBexHcbhy3jTZ3ORyMrhbZMTqLg2MrJxEp7z/rrMrikp/UHoPvISyhRxSdOhEpuB3wnpa32NzW7ljFMBzdAZKjuMhnTw1OINy0nztZWq+JIXtV0gSpbfNvLxLRUSWpVTkoD8soG9eo71qHXaOwnuvvUrlI08RkkQhde2Rt9BXcKTCwzbKNqWlnsWy6iuYj6jq+SYeaNplz0zguA/58jfztFNEHqx46qAURBarBjqPxMphnjKh8u1Twl5lyxWqVsQmn/ZoL9TjytM29Xd/lDGhQKOZ2rvr7n2QnqUCgmJCy9ptwp8gnjV6IqFDY6EXj81rogfWcw82NHh74lfQ+RzSNn3B/6fj/RN9Nx75DOpkQfRnil6TPqfYWmIi3B/M4Dmi6P701ex3toAnMHZkEjOAwX4zLLEhlWQTcmUXrnAOnaNSbNr01VYpYPghdTgjpb/J1RkgAYLJKHOCVqaWPXDasDdmiPMGRmJzCVXNz7xbHtC8PJtixutgomDtnoH3RbyphGI4OJUiQMurk2s8rWpMOim1WzhdsxqaFhYoHMsUT2ZqATuLd/jONXdMu/Q4lacD/UEJ/77xRBf5cAdCEHpDl3doG7Gqumd+DBRQLFlhkPm1zx3lOvvJMevTkjyn6JBgWgrDYaGqiJr5N+ewUS6brcDVPxflHH/fXR6hK2983vVePm3VcMfJDF0A5GhVsDSuniLkdJ3UMzKJdNHK942s2MukgTBKzIXQKJMD4YX0OB3MDUZW1otynUNs6IEyVNKx7FbaZm20rp/Jnw27uqfGo3RSZRQsNLYuuHy9yvj/VFVRry2Q7S4IJyQyf9RH+zfaJ4ZGNF0+fwfpOImnO09wEKCtcbzRgDHgRAxC3/xxe0TQAbNzk7G4o6mkIvhUOEm92kOFiwHYLaV6WLNDN84Z3ttQ3NeCrDI9OyOt3r4SP1FFGaFyxHtomvToHkuSKRagTH8ZFdlWh6s/mNh8nQJ6zE77q+Kh6s7JJwM1Nn7nDtQBF2HD2BeXCONUwZ5tV5Pt5FAcmHDokZfWD2SfDQdfa/nOoRlABA8SY+7pr+x1BFfEieT0R3CzcnB2wehv/cUVsvCRFjr0neIA/w4CzvNWzMpItC/ETK03MHlstmJmdcX4d10V0nYFodsOv16H5eL6Xe6kberYC9arXIGNXbduSKDCwyvZDaqIFt66LzF9Bt/4cqbXJIGDNtT3U2w2FJHS/ZX2qvvzsHdqqb7xKFtPnH9R/mCYT08lQs/gxX/M90573kq3J3h0HkfeQuVks8Oht7sqxUajY4djHPGB+LKNgJinYgDUeAGEmUEGMpUBxi9fbbxCw1eksCJOiPKJX9OZqcW38kamGI6HAkoduwdT67f+f0K1aEOAJ29X1bG3Z1LTblvYjWa/4DSXnXkLFQuwAG1EIjbG7VBCfQYy0ZyHTNtLG5Kv/Z4ZY3vIbrCqkEF65ffQvd3VstLGcelP5N9y59d+L+53gVJ/PrT3o3Y5Yx220FO4H/yShzmQJnsxnEVpghQFOAWUICQhSBCf7TB4h9LecWaU3MbQkA98ZJ4QHunhhRsubrIz9o2i6Zvtmvhmsk9NJhacEHh737/GhTgCtW+PwJ1ecpV9DHgywAVBWj3PqrVf8pnEJI2tlKyY1nQShb0cd/P+AtyR77JpUxpJMYW5m7f+6ZTdWxSshqonArzKDQov7ZD6fFIq9j4vZS4oG+doelFCNK2jJxKorT2P0ibCNoD33QegRzDtxhk7396TSKQ9LJgQAUC8RBRAqHTRdO/5elISDEmUAGGXEiYW9yihda60GcZ2WImVuImZYoJxRegWwtxlEyzYzZxbNl+0MpM3e3YPFNsVJ60KUkm0Vs8XUFD0YR8E9BjHtv3j1CuqOZT/qd7li/dY/dss6JHpUhrXyrIb/7jE85EqwB97UnsFOjEyMAB3Ae8CO196uSV8tDEJQS7ZK2EKHgrNb8K43kzDr5kYX1M5ibbt79zWyswZxZjGf/xe03co0qQofKEqW+z03rw2x1Wjm2kTY1NbRlfe+wPvzeTCdVNbwG9jVd+6Ddd5aW1fX31E6ddw/1417k7JnAgvwgDw13ZU54X7Z3/X/MmpMBxfJYQ5i53Uhm0ZBuy1kJvlqj66465EANQ+8ptrh7P/T+AflJ5H3GHZH61fOcbu0VH2oA5AhdfiZSv4CfVNyVvmpV8raB1HzPlcNeOqsoQVHnA7nWY21OLQnKJcnDyqNbMCR6vgjeXXYcKDs9pPRods0n6++zMUoGXgVgrwSM+a8aVxqRo12NL8Kqt94FOv1j2LpDQP786wh58AKoBysHOmbf6zSkQYwpsQsT91R9cbZmjHThJE8R/iVxpjHffhBc4VIa0ExXNPB9nyCMzfndS4AAmxKQIIUoMHUaDkx/1oCHXM9Q1JfcTjI3Mde0CabjUlAvbhIYLQqs1dRVOC13iDKp8AjzhZ1LtxODBUu6duGDEWxMz8KeAuj+cYz6QLi62fmSt/jIKBfp/DwJkgUwBEBDWHU5u31qfBQrcahtfG0cIrqb5stakruC1i2jrzPDyhVszvi/H43ddLjQE8nAPGZ96bm+k7x3+ayazJOQWuT+q2i8O+jvElmk+fsj3myPaFGwK4telK+bn3Chcz93L0QHvuuYHM+kciYIvTxrSVzVD71wnwAYLRFew85WAQEr39poF+fTBl3xnDT7piNlt44n3+q6eJU765dMA5srbJbeOR8C+PXjwDZ8HIzIwpOPsRhM69fFEUJcwC2Ls7963A+d35L79ORmNgz5rm96VsQt33lL8TCPQAU+KIMTwsWxnHhYagQlVUoCIYeGnztqaqZbheeEAoFR8sat5ZiDKgoWCAccBtulONRV0hEbI01YjC/QN3zwzI82JlDUSF0Mm9LZw+G5kuY3gNWxklM7SX2tOuv46v8oIh9Ap0wyWhb8pgqIs7GUniFU9PrfC08jFq745cUIe+/Wxvz5cH9ksdKtJKcKLqQnOOCOMOHMNzN7Ce2SqMl7wygdBBN26J9kWHeAnCEDYAIdnwU4wuZxTYN9vRtVJkiLJUFZLM0DRNG5PJI3JU5vJg+bLZBQQt1QY9OEQ22x7fyriG0aXuwnKSDzG+Ik3SwRKdvtxcOjgr27iyXmnfknUgomCgtoA958AWQmy6jAC/8ClkUiU1tF6X46enZ9yE75uz0VZ1/6WAtczuvBQCl8yxePHVWDKZpcT2SLgd/3LXDs2iTNVnm/JgIxEWEN93TnikxtRa/AHkfJHa4obRmZDTXrHn3rKI/nd/fEFYwZ5t4lvqGmSwEhJSfTwq2QunQJ4kaWiU2x2PBLn45nv+J6KKfgsSfcMZtXJz75vv9z+mHxtTxJYE384LLe49In+j0hWEoAvLaRAhXHnCSPjzzsQCqrmpWa6xtt08zYIrD1xeHyvQeZecue+UW+yMAXtOKKlvt+wpL9nBeDVSrRwjVWsq8sYOHLr5Jsg3xnLY6Zft/CmjAYw6YdDzRdcOM+N6oBllwaULxn+8o55l9gbAaF7MePKhVnDD2H/OIpW9VVy16MgNz94+b/+box+rkIPtTF6T+N/DbxgAwk4QcRe4unCwp/7vczzvnZN/O8vJ1aYXSaVV3LMi6107c/GKixo/TvkQcgsgDqrqMCgJ9fR0ZeJRLjGvGWNw6tuuw38zS8EWefi0+blRdHHzWcRgxexLlVVr5t9eLz3TP9h8uEGtO1PfuRCcrW4tyDHVxYOkDUgq8VP2g2baHzPM5vJXcUBlbyWVpq0T7jSJOO82zdENqV6xfN41x8Ic9iHmOMS9OcTDTF3MoxDzvUZKz0RuaH6n3qk6qDpjrcWKwBdXGPG8x0Ac/BB3HuJctGlqvjbYxRzYmS+npYM5puRdI2reCcG0evNLDJ3n+/nADS4A1kYh6vbtILREhpqup7rTWzLkpB+00v4nG5hfWxZxcRnv/Q5fe8q8eDH/Y6qzVXG1tRZt98404nlXgGqceUPY3ROwIoBn0q0YL2IPEyLgbxMNUkKJ66MIHU+DsdI/W+bm31nxT4/54NcNzBsLg4bUbrH7fDZXT30GLVKa9YpkfaTOEA3jBCX32eSH5l2CYB/gdZpf7zzZePb+luS4VwGYIBnhK457Bt8yGzMJSSdzijK2Akb0TCjPXRV1FQFJHpwKfLbn677CeDkYLK+fWjzYpUIsedwqHIqOCEaXBFweftexE1i7d0R4o6DDcmFlxV7zg6HD2PyUCDlBkhFjhJWztnMUvXnMHlYcnMrE7rYLfPVb8+cLMVWrHxoJbNv42IIaOeslgdbmvXYtvvPaozEMo8zHxn56QpitusMLeAO8OUt5FDpbRjdSdN9JQvtk+oWW9boLflndYJZNkEufsVQi/TaLWRvtNKbLQG2x/FQEWb9VogO30X5k4bZGI+u0mPwTI/lalh/8aY2O3h61TIcaUwgkobDXh+JeV6kyuxxR4mQlIRliobiUKbC8fOtvDN8SMpqN7XHoxN6BvRnk+j0gAY3m/s2fPTDb9514xDSTduNvzkZHOVXJmplxRbfMQ1nzWdwkM7sQUnQUKDQbTFEC1cchiltIt5SHW4qGQKX4znQE+kX8poWyQ2B3WxLbGNSRCSLgrQSiTofrAmWLHm2qtTsblfuY5B6fqL/rJi8bWkao5dG+NMb5mBI0XP/CW78Vzp7MrOercjHQYwiugAQPjHIeBKPnPwFNmMAm1JLY9G4715+BawliFsdcI+XX2nX35v18+mzmZiwcEmcVd5bjxjwP3OuQLm3zdJCxhJoGOQ94AChXgM7ToKs0+3ilIVfORYXIkywkgBH71JxgDQ/KGMGOI/QhEhXkTg5hJVcSt5VZXnE9KFdJbA71e4bwR21JpDQK+ReZg4/NYnpGt3ECxKRn0YThyie7ph0H0dLeccv2/r8Ed/vFBnsjdIGNP6O/GKdcDaBkHJK2WeBBpGjT6luhH/49VuWyoWOw28v5LQMVsOx+SEtjyH7chMWUdhbBQZDB6kfzlBwFUu50Uw0hMsR0Ti32pQdJA5ViwCgZO2I8XgzwEn/mCuquak7Iy9zokw+gZmAWxGuEi/oUymvLTNMIwvEz63qnp5lUkVWLX7D5Q1OC5BGouOT00Gt1e+Wmhcn9o4cca7id3ZANhQBkmqGLaeGWLX7qr62lv1G4M/EsTTbwGNz7FsHLPCqvjKClNfo39iIh1VFVBH07bYim31yV/Xe9PUT5ppxpk9+mmtNbCh9zy0G6Yh6Ql01omqRg4YMluf4gAwnJLlWAAo05bGCLgRX6A6ijSDhAZhKTxGSweeN+5fENUBZ5CXqSIuu05BfotF3wA54orwwzoT32b+JqYrq3tJiLnnfkauvVMCHp2gPvzRVSMilKHfVfRy/VzJopJ256vF2KOWV7YMb2U6xSAPMlE/u4TfgUAXlT1CAti/8f9jYpywF6xjkzMnoc1du2y26LTD/lmPek1kNZTHrUTl0KwGvGmRC9/z3c6aOA9pc+lwAeMy3ENZjT2/o7l27p7rjc2ldhWbZqFAnZ5YZwVsWoOFWv5FzcFE2Oah9/3G6mlBcbzDk42cE5iBHnwwZMIpfR2X2wLhnmLHM/m8OhRSGnzVm7qvQoT33jyP6g2KGWjX12Eu2ixEvWewa89+0Hxo+mxYipoZytLpzdjnyIIE7SSVXOBnURI263K+rV5uygnLTUUaeufDOy+/atIzX6MYueIHXvsghowVTgRj3wogH4yrGeGN4ipgrdRr1wc9ncR9iN0jTydlGQC+g1rEdLJgbO8UB+OLDDQqKXMf8gBxts1stA4GVJ86/8GF/xBS3WgHm8OiXB3IiyB9HIgz3E9igZaSIV6ZbVhevp/NKPKPLaLy9sO3klMZbUg9zX8bKTN3ZQPd6nz8oJ4TCw3NOqMWxm+4LiqRIya+G2Fwz5rFESujuGzpFovIf3/fOmtlfPQTd29rko/+sVBY7eg993w+GNXMVkbrYQrIkp9HhNn/RNku95VREI3xwpqZIrlWHsqx69ZDJv8sTDl++FEuEVZpMSr0z7EHYHlEJBUkrEXbKMN2cjU9OKrPlO5bXyFaChuj4xG84JJL2xt8XcXZl/2OhthuyF87ODf0ls6agz4gerBknrlUMhkpwPZ9kRjRVffh/mKysCfLUJts8SU+dwg4C5y+ytPt2EVx02kq2SKsZVamN9MYUmsx/8SeWVJHGPRyjL/wWKNR4KqdsqSNUg8lySqgw4ASfgtqhRntNg90wj80ndSgNR8QNLUtGGQ1YRUUYluYmi0kK0g9MBnQIOyYDtjgW2LajAS/3t/OLUNo3BGCWlkJCUGnS3U/QKyq1NwgVd1sArHeAqoKhlongbNVbIPd+bWZDmLV62+Uns5qyWnzbFe/w+tNKUHTsJnh/EGU7I3L3zIm36eZM39WZ8rPraN4VOGN895cD62hIc+bi946UDJ67f7HqnPUv2+47ZVNcgWL4fBJVXjqD7cV4eslTDpHVzZ3pUv6plBLYuOqwIWZU8rWjeflc1usz99ubh1peRzMdlw+RlENhqiPxbRH5qt9gKZCGZcHRskViJJdyvlJ0ZVMJ0LTaYjwpJD2ND5v115ti/wk3tuuwAM2jkKSHhJb4ALobq+kcr1IkoXKqDUKKl9WyOMzbSRjOQimoEejfrt0wofn00N95w1X3b8ydfQ9iCPb8+r2girnBXOgv/oPidL/c+P1j72dRLuAdt3lajbzoAiM/ByHwOdMQrv+H92miRvQG3ZMLUOduG/zYzkEpA33EaaMEpG4dn7nVFz/doBnybf1ldQin24lnhG09NOUMguyH1IFP7/cDiUAkppZBk3MIllEOVcD4qcGd7+TEbZujVakImp7i3w/+1wIa2xB/c/domvdo3PR4KdSEbi7ROJ2E7eP4o4kZ3Kf66W2fOheKoPpvE4k9/7uLuujvUJfaVB8vma9ClKOcm9+jvFLgw3ERQ18Rng9RSxUMdtpz1gF90b6IAEz1z8Kr7N5lSlHzMJ6KYJgVyYhWpQcpUOI0v8tVDJ7aJO3XIvhXPapHSrsIYQgm5aMJUyv2rSRtyTu5IVmZk40EPvp0IPj7Xhm59BWylJhDRhIjX0ZaQJRxAyVVm51oanVma9JknbJicmUQP5fHBHUfemkdxQIJjlraz/BGhSjinTCZ4j866K6LJrhm6ofealo3xLlVdAsfuaA+QwuUkeU2wNffn9tny5sd8d+hN/7P17mkCBU50EhZXspofJCQ9cL8muOO1lkfkK+LbZlqw0YD88auiDW3kdwjVqibSU4ykDEcqpb79v2OGWOqlZZLvWr+xkC7FaJ6exPaAyC/OiQSv0ZoIC14Njfr+knUP43kgqqHExfPsTD+jq9nPhp9y+bbA+MrhR51z6SnhvfF/OsL1Z/BOT6l/ahyGGUP2BweybJ+GvRhnyouiRF342/nRZOgWoggNNhqqS8fjYkntIJ40TyT2BMmqUpxP/DV5YMv/RdXtOpMdf4MK/D8A/To07DnLtMqNM159ZQOFWzrUayB+mor2DyO3oiMMUuRR0PaRSWiPB+z4EaEdDcEN0+YbSw6s9/auMOFTPXoCHw0/j/lnXUHjt0EhPWGU6ilAV6CoajNK9sSwEmBFbhl03fJanvVUIBrwR0IrJCWP/90aSWQO62uqp3t1b4zmFrdtD20E+/yycXP6vo8KK+Lj+x3jdsq28Zz9AlCHC5pYKBct7R/vJfyetiIZsAcAZYMxIKuGQLcNRvQJKMR80XsOm3EWk3jB1yfGMrVbtwY8uqYlJPujjS1ZsF0QDO/8xXXiP7cEfM5Xg86lGWFWz0g0U2Ib6VAiP2akcFEL5+wsWH8aWIaOqE5aE7B4nteRpxx4GJ4IDY7QP77rxiY8XLtCER201p92bvKSL7/OfC2FcQfk5Mwi2R7Nkvn5ndn5rgtrK25ZRb8AGzoxfYwexBLuIitm4H1G97nHG0DnhBPEY7GylHqkyTsCA9w2eYEfENzvKpkl1CIGy+0d/e4f6Nja5n/tmqKYJLulREFTodhEzkKqXRp56NCj2vJncIfQ1c4F/tyhnBnLQP3joAac2sY2O1HhDs9ymbF2iGXK85EguQijTspyF1FwCnegLFOuezpYcfXXWpzvaxk/jkywyHuKjf/2wU05dhVxhPPbLKBr47oone0j7/QpSSQykvyJ5zdh93oelYjLBlQ5c23eeG4VqJ/ipm31nxan6+ZaMENJ+rPZ+045zdUqWnb7lgmpgZZUZUQYMEJ6YdFcI7T0pKPWJelQuPruc/vh12dCSpRfxlQUpxlRaJkDG57MvLD3AZ859k+Pfk4fBREY+IViclGVtJVthNWg5LNWmoBmE//OCZH7/toA8sfu5ZyZ1ZYEqDzB6BQ+LnG/hMRrwgMBVFv6ShocS6VqDtaJqG5qvkA3PoPkiu4DRVx6W3NAqCU+YvlZQcvdqiz0vIUnNAB4225kPoYsut73wg1T7vUCYUHZdAKrM60ex0gykfVIDIGov+FJB9xoWxxyt2awl0X8rhCXWbp1anvSo3qWDipU9naDSiUfQzrYN2kninH/dMlI34osIz15ljA3Xdo+k4bA9iQ1dk5P7KGgIVTVJN4YPBh4ufXaeUX5v1cctC/9C/vr/Eibg3BuLrur2g588NtyYWnr2CanTZIXv4PH/KDBFVKjJ9ynrML8hoivFrVkkdwWYhBLhItHojWPfHdhIn9mHK1ZRayL2C0ZQuFqIKuQMaS/0JZeGoJHlrA+ThC0psrH5oC9VCReJxWMy/HGKSslL3Cc/q2IV4rSCv/B3E3w3ZOB9Y2bQNGogRZdSUy6IuispX49wFeD+3X/6zRiK/iAK0qYQm61vMBl0dsMCsM5g2Aft1ZJfgLbp70XskQG0kmwn3yJQQHhNXaLdKkUZIwgEpCqVm7jorUV9IuTRkAvLu0c+0XPbR6P0b1GMQOWpeXB6GgetYRx3pFHV6IU51XX7R3xwyBtiEAAVaGuN6hVr25thQzLNXOllULt5lBVEvr4f38kRDvp0PzpnugrhCwmK2pEgyLua1B7Tf2aJuFwFxoTFXNtdOsnnBIgVNIzmhURV0TRZWTGsLP+uTTjofKG5HIKW11mQ+dIkTBgeCjqaktmG843JlleTxR/8iqySrIpfWCj2+Idk8tF9Dw1Es5Z5+i/pOViinjqDNAjLaWnEk19IXHjR5R68IwEKfg7cWyT8l8R0H2LPaXHRJC1zW5hNXJTfeA9IsfumueFnPc4Io1Ub10aJyijVndsKg5nxiLbvyI9zr4/aRWqEJpPoGsOVvL3zOVnJtal0vn6667mSAFIrd/gV+ypYbbaMA/zOtAxTDJWjXDbuCQPLJ/yNbQqqEoF3YVcK388ng4qRnsc4HC8k38WiEgeMlnDELZGaMSaxnQJShnMWEM0ZA1ByBonFFIBWa1xiFsTNGEtYrHEShPiNqBo0R6eITlA4wQ7F+cUXb+sEZjGv5/JHWgP2BWRlBjyn3S+56IBb1mud3DEIlGAu5UV2HNIvYPqRrF5OxZDoiKxT0FoYrzlc+pSekq6sSc0VcgfKLulkfXQeOYbMCvCnlrzfNPsU0An0KZUotQcg9lP/c0CP8HzkWg1TDYXeu8tRSGlK67BiGVaJziyyUvy5R71dTe9KVIxnWsHQy5sEt6JvIcIvwllEsQ+UrequfC56QqwVf87eJKU/IOi+K72Fuw1N7xdKSn3aWmf5pse0bQxvm7uRTMRvfk8DTP9qg+t+MI9TXQcxb3lXjQWLWtdBVeB/prIxgGK3n3ReuLuY+fG/tm7xHnZz3Dz1dieeAaw3jdH3OE3N3ZVYevETxnK29RL7l/e6/wOrKlRAcHt4re/j4a/GH+H/G+YdG6ezniupCFzsHaVH7TLzfXw3EWCsMTEJxdlvpTkzogq2vXPk5qnbe5VJS3haoNv5uNR+dEEq5z7CR/+tOHNEzMBVqhk4Fd/K6S+e3mGgf+k6DKFk28d45+iaEGo4LGxqVrP9idZqEpacGoIMahyXbAZLgYlJT6hLFmd+z/LxTOrvVGg14pmsaLXhU2VLzIcQ+fCKO1D/Zg6ynLfNrgTOKbqRQOLTy8q1KTCmFnKnYd8c0WHGhcKkDpMdhWwLSdGKFotUVgSoi0St9Q9t8bzWduN+uYtqYcaj12a0f9bjbzVc5KZH+3RgWPkKYHg5T3p2ttQuMBOp0U8kkyUYHSobSYFv+Ijw8e9gmmuBv81Ju1M3AItavE78D/BFibvZC3i944JNucQV0W6EKjhv/112R1HdmsBWsyXqMB3ulp0Z9pRJa0OWPjTRSciWZZRYSPMI/pSHvxScsZBq5RjtH99od+ikvykHi/++iatf9JsWjJCra3VJxK3zcjzcjfwEKJjYBM+zW2JfnFQFTOY9lfJGPlR+P/TkKJD7jShxHIrW56GtJBM1U8A+du/a4XQYgneH7oE+neQ9EFW3/8nhBQlNhhi5wkxTJXYzStwH6/m6/FkWD9T0h95h/l7UfPlnz2GwvLWd9+9AHpXGxE76s4WcPrUyd7Fp47NTG0VMqnu1jNPirkk+Teacki+Xm0KlYG1wchT/qrQ5vdp+RpRM7op/lQDsZ4qXkUufWLcXdTSU+G1/v8S2VWKccxyMHeow+uSxAAuL2jmxmj2UzTxpsqVkKHMJDciKOMKwlJR7SiwYnyz+mpuc1XueHBukfv6VfgZpX/+pVocvrzn1c1pYduvjsz9ZBluB401UK6acZEm/wFLeyjjOrhbrfmJnYtd9fdTXlllY5zB+GZc5zO9kZCVg2MTzOdRugPjAfJ8f+rwojm33EpF8S6ApPxggOBdapptAdNyGDDHGVFEKkgDI37GrPEI5I2wulzL+/QkE8OHhsoiQLESEfsDygyuHtlMKPhf/Dxa7hMQkAbgS5Xmqhi+Cvl+WY5M5u57MPH01JQc8GL7IhQY8Q6Y6+N4QYeV3VsbKYzZ2twTXn0kmNaCaQGwmPsqZVBgAD4K9umD/J3Kv1dITFlYbGyvLVSYvQkC7DH5YNCM5vB04IWzptw7yA60cxBATO3BLf4/GYuJYMOuc7OZkTpsKhrp7LS3oWxsnfDivV/hImfuL/HF5VtE6z77xItSLx0rAbamJKF5Tkb4cv3dvHVFxxuN7rKn9mi/LsV0ll1mL5zscGPM81zutKPDWRqqci8TIetaHCAzYwoZdMAgbkwVGrAO/moajpvPpboZu2bvj9ern7YqvYc93kdEaRSzvQbCy14lBJtAeihKJfUtI7/gPupmJwvOipimUcyTu8I24mk8c4OoOIwdIhyUxLw/fXB9WQqG2XhTjzsbEsOlVFzFOX+K5vn3eNVe6v+/q7e8FHsLC77Wccn+Lp0Hjyi8H30BLKYTgmClVu57NXKnryJYg1AoSfspSkMRDd2ItKQOMKE/WpMpRZN3sLcpzVeC7Bpu2eUj07sKZ/PPOx6rvNeSlq5GD0EKeVXO9qIsnNe6J7mU//RgAUpHKWoGP4qog5R4VjxNIZrdCX4DZICM8mraT4kXlDM0YnKpKLXU+sAC3KQTjrHbw3jdd7dJ1mzZhdMdc5M+uwwujragNjFW1S9qYSkf+ioQ8p6Bl6cSfT9q0pTdVZamu6rVG09syPa8ZJfQHtNL7t90Aj8eWKGgRfJ9hozoQRF7Lj9tGcNjlils9XRI7nRcLWnhOR97QP4TpHfplzYoDfM3k5uHl3iXpaHa4PNbxQvFNuF7N16Ie7PYy0rOX0du8kZZrMgZLOiBy4bGE33S9nJ/htFO7Ql4l1Qvux8KAAp2wI6NJTG5gb1gXLY/K95GCP2ReR6TfEvMQv6rfBnc489LVfjPDsrctgnz8flZymGY1jdHr0qXlmj/OB/DbAd58nYwwpieiyoPPuC4RPZlRFWLKQjIXh6VLNSa58LMwrfUAkfCpJrG05IKJmtP0eEOFaFPqsy7LcY/t05i9t16/Pq1QjFhQcnwoZq2VdjExz3emhESWp976ay9scwcEaW6NTLbqJevWMkkoKU4ZuvTrtnjk2X0twaLBx4+yz3zidjzL2xXKl+f5AprpaF6yaZofipEvtrDZ0WuwEEUrkD9dSebKRL1PHEgYTXCXYgGKnLDvzMd8xw1Ozwwhba3gOljv5xIvQPN1Wg/phSOxAffz21q8iQRCCoAooz7G0UvcS4Y4Hu6Igjg/WJ7LlXIHjnnZ7xEIZOUZra+fXF5MwCaBlRz74RKYdWU4orSFQVFxdH9lOdV2NKFkbUjimxlclhzgRgvM5M7wU6Sb/WnlNcvVD1AzluxD/PzNrANuJLd2alKnHdhHht+F7S/kXoLj0zwNmx8XHFAv7nssuzoU7U/2MVLY8dKFlbShZXJQOrOnd3X5BXlNWdjee/WCVwPOQi99+iELvIIhsKo1btDPJwpPXsw2vrxQQzjlz6nJ26mGrLHaPYJ5TTDM43T31yqzZINDb81Fzbzc8CWs3P8lGlIJxaL1Cuh5vvXi979kYozaFY/YVzrl/T7EoAp5zdO9M7Ks6VZoiybCPNAzELW1YpugE6zlRikmLxqVRMtxnFWuctZaHN3oEAJvDoYJqWNxzf+EfAxn77NzEYIvAtBT+MB55lbCfGscIZRwXUh6sc+qXDgA9oRWbiP1ACL50rRjQv1B8k2PHT6DedC0mFNYUopf0VJ8JgdsR//Gct21+3pwwrRy1HJIQ1XeQhkzhBstZIxCsViMlRcKLBCIwp5zEsjZs3brkteb7fRKB/ERo0UiMWtZsFf/eaV8SEUI/0rFp6YUTBGEQ1F86t4p2s5mNSHnmVDhORsCCS4H5bT5cm7JviAxOqMqjWtDRAs0aTHYXRgFHl7Qso7WHqqzoYWnwWkGHWT+ACHeKU88h4jGO2X8sspsOmpwJbJE1l2uvQHxBj3XZbEvUHDuOzsYQ0F6TXZk3DfRXv1ca9eaJxB3fKBxuTV/nc2BKIrQmrXapvDF6YctzRH7td404p0Y0Qg/lVL3ZnIJ5z+PTuqihps2QhwxkvFhLHFKfNS06xfYX508F4xdZwbJEiPKlzb5OL+mEB5JsNquM83Pou/Zu7UAEZsc3gASY1+8DMHxufACian5bMFpEL08D86jldqOsEXP5wkL2sZG92tNjf7PklU344mK0cgSiEFJphTbCpJCZjEFHkjHKrw67n965NdHN7ObJrWy2pj6wfXY4JTrkpwIOCcqI/0FY0RHAv0zHIIAoOgCf3indEjVaIEJBKYmERg4yNqI22dBp6aEjVxskLa+DM7WAS8kqNXQ+36Dlw5FCAMWxLF5astvaUkJK3+UUy3sqDRXrOrV9TVQ/CjkvFAscIDODMUYhJqnrhqEDfnXX8iJUL9ec+yu2y5ZhGzKVTROgvWSDOoNMxMFuhGkxN/GAm9LrgG8uZOqteGNEmpB5scJSxpcRzE5NngZ/obutyLOCLyPPNyxlJUfN9Elz7ds+wQxVxFPH0jfl7OvXLYjE/s3J8/Ox5HpfGoSLUeowCkSK3QBhNe9gRbJf/00y4TU5iqd/tLaBSoM8GvXxh5mv9r7uoy07rOMzXZfYib5xeTmFaPfj5TvkHvA0FMQhL8JbDDEmDBFT7H15fY/AE5pDeiXuPsriQUhnPzli6y+ZjQpukmHpdS3DR3KKUoOX55FP2tT4qOh2JcZKICSpl4grZzjr10lWOUiF5RLW9pBqqrH93jCzCUrmx8r6X5Zyjm/aoMDC7o/Izim5qNwNp0b22c9aP0CiEy/+mFOmg0mq7/bBAM+hX8ekkH+mtmjMPWCtaAeCPd1V3gEdh7XFjPjJvFhGfFV9F7IvWpoyfLffSpbZS6Vyz9nkjCI/ijsHn/p2bkVf7teO7iexYcJxCdg2wtxlJ2W9GxCdo6JavLtpz1/uLa2Yr4cTkE+UURnCdZx8SFL3O5lK15wHI5gf8hs+DGrpamHhqPldG5EoPHUHYx+KEu8uo8ZHzj/kOllatBvJQaZaQdbXsCByeB2K+iWREqL5EA1GfW7il1E5DuK9FcVmXFik298wvXXp51xRqp2+Kn/hiv0cRcAKqmWIiGLNy5+1aiQAtljykmXrX/9L1NhbvzGqGBzmmQyEGzT+qyXIsLswcwuZwEwycBA6FGBtnqwgksSuM0vP0eX7CXbCpf4X2a7mnbhW7Wv//9BqNQmBoBr4Mx8eIztLwbKqCKyd2jTx9gs6OVjmvEHysmuS4t/2sEdx8zdVxojdox51Kk6/op1/Oj7XawWCB4pLjU5980nt6qefvFA31NcuuL86HUygvijVEcwEak2wN6KFhS7jMALcszGZuwS2zrFcuNGc6G/ATEsFnqnbNv7yCAI3uERLyF6WwLXTKbTOt1tUdImMmhMSlgNaMiWyEQ0aWxabSsuOUHJfAcoHxRL+LyoX0EdMi1RSiIMJqcX5EcX1ceu9V2BA5YSDWDbSiSnzqSyuPIObdSkvca7ybNN7lGZNmCrCQL4kkkRBc9NlxcKo1cxw8q9a6DP7WopeVKlTR3SUWaWlXllm+7Di1+86SXc6iw+ydDFibJ23GAD2iAvnzg6kUiMyACdXASqA+f+btNJ1W7GiAXpMEx5FUea/qPXzNexFt2+N3+uhyPGyGrXYKxxqfq3wAZA9phejnajBxyoBPLhNQvs7L4Px4acfpZrRwPUX7EzSqDJILlxY+zNJlH2z7ew82670MWPPcL7Ue6E+rO8Hi1tXGvuukz6kJaYWxQOjgrZEz4GCr+aHvwUJVwoaMqO+Pxe6AHwJvE6ttqfC3/mH7onhYPeK8E0pL/jqeZrUjyGslvU/lEX+dPqWdf4wVg8sogF3SD8Hv5L3dHZIlasHgZMMLUNmZv1ByZ/zkT1fBTE0DmCJQ2634LBNsrWEy3/WP0vwBWq4wA/olppo0CP86ji4EhHfd+oHlbvsZAGgZhRKflfLr6PBP2AvKU+ph+XKtwOhzJ4zzFEG+7v6UZuHwPnBSWc0WROznZAXbejWS2kpaTZA0MFbzkJnXJJzmcP5yZ3nxur/k5QdnFhH04MBi5c9zMjTHDSpdbYe1zrfRlMghxr4J6hrgt0IsjVO2edwkhI8WWbwj6DUuS54iilcNIEMKxfAo8WMl7iuALtn4hNPSzVLhOcpthNE7WtQdWuyX3OZ81nZurzHVUQd0FNq42nMWSzzJ6YVEZCkxEYdFREhf8wyIsCus24w3exWK0IzlKyFR5jJElk4Xg8AY4p6DWqHEaAERdOoIOd/105OJm/us+Gy22WbkOcx2jglmmnU0UkppOZVwsNP7MnIMWNeE+kkPuM17mA0sJZLVQBzork75pWX293HgsvNAG2WtQZvPlCFrho6CEXfThz5zxIBVNOyFfF2a3Ib8XRTpQUGpdU3vFIVxmUVMW1TJRAksIS8lE9QeziKIcr/mcYmBNOBvTFyIfP/WvlNy6NBaxm2UXoARqggKw90qO/JXH/iLp+EiX2FZDyKMXVs8O8ads5zci1DR6hcp/4CFd9X9+dz/l5bp5jq8sEP6/n4683GWA9p566cPc05wD5cpF3K8T83X7SrplLg7aqNZdtFXSa19m6GmrjMIgkZ34bCTPDtU2La0AVq/9VaM0gJoQQuzT8x1JyS4RHSymwKZ+HEjDvlEpDUMXusGboPlCB9hVprwfzoPf2i6cjm/N1Vypc0/aAiYmkRHHZkzXsTCuDc0l8uJ8PE/ysTybf3o9ebZnDX/1d5mTBKOH8TSh/lR+71QNjDPfjYjdwIBdLlRWDHlXHFoUJ5yUsW4CZqUg24/NaPpAMkbd224F0/x4FR4AEiOTYJpFKkYhqtjeftWO8qQ2s9Al5SjmSx0KoH7oiKmt1WoZe95+p6xnt4GnkmzJjFiCPOsf3eQu9py/fnX0n0b8WwPb0+iT2Xd+zsDs1jRmjbtFX79UKbtpOHajIUo67NVje1sFTuye/JVREpZiwITeolVPEuaTWqaCnr+F1HFmmEcsQ9PGiWvdqa8GmKm5NVMKOOV0BVvRzowqp8l4M83LIdnMDx948PQM4x+tCavo4SJwGvCbu/HM4wwXD8KsIQ5y4X4vjxp626rs2WRQCgxImV9ZB/XieHf8MDsgQrJJLTi37JpthTYlSU2xTROKjwKTbGrBkxM8wlxabfJcwwMIVSxqngJdxCNNjFUrhHWdRXbI7S9l64fOt4EhlV6KPxMyTK9bC5+mBqZXHzWt5VfLKPMzDj+B7Ky+sFphaEFBTlgxE7XYZhH3WadLY66bM/dvEToph65DKlxtDFpH6glZPdqImj/i9XY904UpNK/7oXV92wxooZ8slynoqNs2o9FSn+iFwpY1qddkVnij85DV14ZvRg4wjtCnJwVbZl8a1U61epfQGfFIfSVNp/1tHOF7zI1Gl33BdbFEDZoKgruKfZh05actUYCmF/WEl6AnjPQUNoWkyEQ2kdC5Ax/12hvW6EGIjTc0fI3y49t18pgulIaOQjJYXK0ggkV/d2iyoJMLP/qK/6Te8A5zSl2IPVpJKsK2jWfeXUz8VhllG6c/4uTcNH8hO2AEVXI00ZBO69cZiY3QJex0DD4gTZQ5bpW26/79w8nNUheqh/KnQRxg8nixfowUbaGoDkEDWjji/7WfqNeAoYkJE28mzAmhCueNCbaD+jQfAnQ76glS4UIv54UwF7aAxck5wcbZUOREcFM3SCHgoSyX73BaV7QoePKrCm7McO86r/i3026rBM97pdKPy6YH9yoeGoF4KZAg940Xymjwg76rr6sMroHftaqsS1Vy69zPYxIysqonp75DdugZ0TIlkIwSRlbG9RDOrhDkDS0YTrlWRbvgXjqUxMhhcylKBRrgY7+wS/KgQGnRuf9xPnvjueHcdCVsBEob6Vr3PtgLDABLMPiXZ9VoMPJQzyjmV39Rzj8Hkmw4e1AsUH9bIriOfNiDMUnR9sxMINfuRYf7KUAHBGSxTZOQfdfxcZbmOHZNGuZNrcgXUrtZKyF1ZCK3K9mCvBIrTL17tPqqYOjYvZF01LhzYHcS4R1sPhKqJZl/CxaG5VhE0PtntlRQyofpyxJ2QmNepDOpr82P3Rcw4ZTres2BY1/DU9kI+k+bdaxJiRwiru8OLfaV2syKVODF7jnCfIyeBIhyK1jQ3VQQMWF+9eUMD7B9t7VcGswBXHbptwOY14RbEyh6Vs0cIoWzwhkawGSukzPeVWvwTB3cRlKbG0/sunOZcwgrQLJBFEOTyn9N+xB/ofQc8lTGwNZDMKUvv0edpOedFV6SbFKXacaWSNlPkQwF6N7dFhQ+2jBpwfAa5DoyBZhmAUv26nnhNxlHI2RYXj+nIcHrjnNT5X9F2330ykEvu89Y0YOrh2jKcVomeorvLmHQL7SkaHOtOUlNST6P0NVobdriUlsvFLY0J4IG3y+tAMPKX+tiG4fcXFPf6/NL37iJPwidqrdzw9leKpotu6GoD9SJRA2LkaLZF/1o2smPyqctSHO81/dN90qZPB+WoVs+5JHQN4xrpCk8KqWWrzuB1EFR4z9hDmj8/yD9C7AA8/v5BlJnBci/t6dHX14RGIB0tSIxe9NMJrX1tUoxX7SuVaPwxOW83OXdxeeQJ+5FrVNgsjDktB0VQGdFO84dhGVhR2WCe0imL06KPq45U4PU4tadnp6rk4rCOdXNrPesfx7LPT91UmgLHZ9yjq75JHFeXDf15vfh6CQ/ULbmrZoJ8b8altVf3V6PuQwOZqSwJbOwTGLrkCzUGEDUFKABo9usKQHbRKBfdebzDq8niyQC1lh9pKhSJUm2CnfojEaPz+QjUkbTJtdW/UWinRBdUaSvdg5sPDydWsGlpygYdYZe+D10/kcZDWXQLS/e98/CzD9RS/tIwhc07YFsquHUVdn9OXwUQJ46fVcPv9j+kqKlRtYDnrZjpFSyOGiu7/DNwg+5rD2teo0FmHf+3cl693wzoiMH+8020fI1phSfqn+Qy7WGsT/aU+LRsUWcP7lHImuUwAeHrPo+w1QzbRfJz/MtAhRvHQq8y+1MhRQssuvOKm6xMw+sTFQZIpu/RAd/d+Xc5H/n2Bpc++XbnH9aibu6TZm96KAe0xBYUH3N3hIly+8/AW/aAxCS9jpFatLeQvvP35r7UZTFxSOf6+zhv/kbPXXRa50fZ4LcvuqH7PkTvAYqY1J5SWsw1cpo1Dz9CDGuzEM+IN0OdhOaAkY0KvXbWDhRhNwmpO6cHdsRgTKVKByRMYlQLlkG5KfGtRSzNitzhz3Zer6jLOyDx27DgI9s6epx1dypG4yzoVlpgi6tSsAo1tTIh5RZCxheVS3n1NHtnc6gHO2DA6WptayF3CrhIpH5RSLlmeCCUM3KPRsVC3j8BiajPpK6bABxrCKKshm9cxQAA8gdMG1c0KhfeNqb40lGS3+GycxVVYss7fOetLstVSbSE4oDs+6f6UnvrZxiETkvSUwo8yhvp/bJUpPA65EgDfppTXmFGiguHUWHCAbqRdqQqI9xSrCF7C4FFDehqZO/JeiSYvq4kvubXZO4A8yO86+e3WHKaSHVRC7NIvq/fXopzhcvM5MbKgLm76hb5qae2lGQb89aohWQQ6ohTZsDXgm92yy2Vqlf6uf/sXvmNsWb2KzG2tHJmbWYlvOjmYzgSJg2DOawL+5obWMmyNEi76LU4T50/DPdGBndhpYo9hOa4//OzatdmO5iLokLmZK/vEggs/OeOQR1afilTati/hcWtYW0ndA/1tuiMrd+ojPuzWxwk6nmGFxJork0ZxU57EIHD+8etyxEuOJ0JK318sYMV9+S7eq6Y26S+5evL7rXn/HC2DgEhtgyeywuLffBYapCSpnSFtiB/awx/D6cF8LNHCZh/tt2zCY5X8dPvEcwu6W8DNL6o2PFYrbWse/Z1O9Szr0dCts39zEgQCj0qBW2ZYviQxVToeVju2Nr1KaPFvvooMAocyFFGWR5+SPfMji1DuooHvGErRJkKiP7xQlbbJsjUMtdPsPWYH7bIl831ghbRjTDMQ77VYbzkHfj4yi2E47yy9lyslhU0AVCGVudcE4LR0lyXqKbGhNDga7fjkiJJ4Lxf2z4QZqoFuU5Y/0RQu0QA/Pvf7JLIOo5ok+09+t7p04a/86OkwXJ0e5PHNcXyNQPuVNT3U5oQBN7HA8RCf0zQGiteIw82xZcv+ABgp8gsAIuaWhWO1v4H0ui+cW9/E+kGaC7NNFX/6uAIefLV0rqiZr7+WVycenxFh6wqurTYYbn6o6Q0Ygqf3zVzackq7IecgC3gYEObPxY4ttMa/dIOeI6z5BwFJAl8SUXQrrBhQf0TshL68jjgiZG7Ku49zNLN5rpV0oHS+rifcEWqE22Tj9azLs5QNu9SZGIszANu8AVpVGWoLbJjWA7hcOmlTLCV3C3m8bi14h/SKW7D5mzv7oryV37TAm5+P0fzQGM42Fed9xPU5hbsoJPllczFT+0dI+54s4FLW0XcBy0owPCQDqcCQ8TTATpYGOvFPatsfYZ3Dd46GVAt0yiaGHYLiPT4IzXG4p1V1XAcxgnUcVW0aynWOYwd5KmFNrIVhJ2xk4WVvthIqS36O0d4YlqE55MYg6BFZjYdjmZlWx9W7AjYMgfbP70emQnPimeqtG8DVnKyIIIWY80Bx2Mjvfv45VEiWzC/klW78OLrMOIoetdNnxhb6UodqRHut91CrUU/KkxDJ8nxTustnEoenzqxZF97aaNc4/yTDDfhPxNLxa437i/od1ZsB0GGTuXoRDhf/izrZbREwZTWT8XHTYCtZk5Gss9nPXeejc4SIphtpolXAV3qq3TOPgXfoOpywBSn3+bQPBU31QzDLNu6GY9yKMntmQ9X9q3aw40Y++lh1YPICOS/7r/PMEfRi7MQ7iVwzm3IGglZLkFREMzaCGWeoqgz3Hp7ThVSvgD/nPmoC+H29pm+Cbo1pVJH8apNie2bg+U1R6t92O/lr9BoSX1yH1dofF1T+7Mzix3/C7GzPlqu1G9aDX6yCFIX4sKY5WEdlYBT1KM5n0fLCOT9zWle1a7WFlZkNaGix9KZawUxPdR8WUdtmNJGQnTsIZ1WZEXOznwksM0FsM8ItT8TMjhW3f90yy5Qp+9KOd8UuMpkbwbQZ19xSEXGxW+/GQF5umj+eKN6bxrvAOj16yldvSFrPcE1PrGyGS6CqWt98y9RkmrfF55IPzMxSWwIWvQEaRi8FeJEGgRniZ36LyqGkpYjD/3HsLffjHyzrQ35sp7b7K4aCVfBWTry5MJJW6+TQF3t5fMS3Tbh+7/oh+gFVCrAMKocBGDTVg28yHIal85E/sk7uCRxf2Up6+AynO8LhkDeT/nt7g5txShh2Cj5OE8FmXjxG/l5bXG5BZz95avWFjsGnXOdTXDhW1enrsTA7s20Yj98S/BPzFhzG2XIE+LLWQad63J9S2uAusWtvXeW/UlNGO2jaH3111snWMmWoOixEhQliDZpsRoDrkuu6eLGcQOFzYm2oRGM9jFO5qJ23voHrVlNvakevQsaB37r6yi5f1FybTtactHSx0AGtshJ2ckqFEYytAvVZWZYF8RIf/Z7HVfRzYi55Nkw7tDV/9QINybDbjHLcTXdc1L8Vp/5v6haVw2ElLZ2CcWU4XzQPoAFodo2144Zfcf8Wh/d/e56YoFsTMv1j0/Nn4r3ljy7Sonjf8YM8dCIalwzmNQcQ78QiyJHWHR6xtL3OqHAhB0rv5IQ7xLcioLDWEgI2Fj6KQm+0UjXJku+CXIvldQ/io/953C7OuWzIc75/X+Xfsrug86SwTbNx6F9pcy/35sdW3Xz/OrF6driAnUh4ePCOteGO9C4QARb0N+wAOIK5VclaLAfrb7PxRvx8gavyyeaWXram6WyvRsv0x5GS3IXf3oflhvBKvg3s0QQePfI7FQfh8bEtP30p37y/yq7A08C/cRuLBB9ES1cKMZwEWpQiqoVGWiYDyQ2x7Ea7s00XrJubvOSkoW6z7Z10G2JFxv2Jx4KOlmqlQRstgBWlHeeu1nLAkRCoL3DVsa/S/NPhaU5YPjdH7w68PaLfQoFKCcnzK0NE2bv0FqAfL4sojHe3g2YUtPL4tk3AQiXx1eeFjTeNQYWH1001hJHoEd+ZWwY52eiJsv2gP7ai6bH+/hvluqsmGDSq3B1RmlYsZozFjGB1GU2ETjn7h7REl6hqNTJDvtLnTNALfvhn99/fD0uS/m1/Y+exuye+q6PYB/tNyHWmIqU0cl8w5Fit57IhSF41u2EDQbyX3RJJHzqYee8zM9U7g/qjIlSDKxmGi3zERDn9/Pyv4RFIZ41n0+WCdWyxMqrVzsqkbEjlCQBGkva7fSZKdZdPYm62YT3U7zj51M3FHpCBq9XpRMhwwW1ZpQvFV7SZuuHRnILzIF1uCO+uLAId7GQKRzbyVR+b+Vpqs4MFmYwhKimpofWahJgVkJvk/yx4R9JIVCE6z492b7f3E+bwk9aYlbPN0R1wQae0WDWauwnkXc0Ygxl46qd6q88Q4DZRFtNW7kgmktuMzaDeGKP4brP0C5/uLCBJ9yDt9Hw3F9Bl/MNHMmMo2At3jchXLhYOaReRdfOmgNv0LyxYQ9BGarH7wZQngcYqJi41Jp7s/dVMiT/Kz5zXm2358X+fcLPrNl1cpOpV9qV31wJouWGETxppzxZj6zBJvWUzGrtZ7LRI9kXZbvy0Mg8zOFUcPilm1bs0+VqtTHv2cPbfaBRpsEjqEFPf8esNiIJphhx7wn69fgbawEAPiU8qupfYxmA/Te+GZI44R8u9Paayby0Ez6wfm4T7HYBX6YzwFmGIJ8sURdmXMEkCKU/csn8E4f6ul9ONgtaLZfOWkbr7quKitv9u44Bq2lo9LPTXqCfD5vBvuhE52eq8QBiGCLJmfc81rC1HbukIW/Ch2y42rI4jRhapfpO50h1lEKo+PAookaR0s94miXRwSRJ6hkFyGaBK6wglXSYPrVqvn+O59Fc5qdwhLVB4yV/QinvZ/nX5wTwl39OPv7Kk7f2MldviCC4D5CkKITBbkudSpKkaiyzR5T985i8Xz2BBuIOHNC/MWlZnw0eW97lUZQP0IFs8TkKw3S9zqee9ygI1RA/Tz8tYwl0m9sv89QeOeOAOHW8nmYLwVUAYVFAG8OQmjRIZXkgIirHK0pEipiEGfyv+QdwOEzCiWbcUDeuJVE1EYuyaVsTRLbsWCVaW+Z2fmdTkV/W68TUMuReRRC38/Bi4iAzh0B0jNNvn4NvrtXmmV008TBP3MhwBAvsUEt/apG+nfSD8UlyHwsmcg8nQOZSCcNTLRMkqdXOLcIhMGPvLJRgVoI2dhyFJFkHddzBBldVMnDWoztZ5IgMPZV0GPHbf1+5pJPo8ZzbQzV7UxSS6fPki2HKIiYCa9a0pLuGDjYx5Gv3NAS4eg/+JMrvGxf92azDlf8PZYmBPHatWO2fr1mlztRWhR5Xz0uDNppRcFCVgWF0YIQ/NHIquxrNtM4rTGKSXb3V5tkS227ofWHlcW2Iyzi7kNnvhqgv1FjkfaQK6Kw1+f/DOVEjxRg2M2ynBs0PgvvJOSK/EkCAMU6cC7enQirmFRbDHpD/59R5Gag1WnqSqoGrQmR9kKpwNcymq2UjQGb5rOB78/5sYXh3md0bxrt8ga/LNm0yzRgK4zCVA/IoOAPs7uSqIe67GJusjdN2if44hFTWuQH14CE6RWkGl+3OnksvRzFDlrBfC6zlvkIcF8icRZT24wCKyGrt+E3xFqXWamyiwIv8IfKUiXsFWLTqafX1nRWroRF+4S/X0bvddmNeb9jFMuZ351DCleFgCIocUGjbbIx5qXOgF3zDlv9Zmv6dndD2Y0V97/KzxIMFsZPfOLT4lhPoyV9jvcnG+XxaqhkW3+a9xnCOw4SPOoFEOIqR5phs070Ls7LGyZmftYE1T+/sTbr2uUjB2LlC+MS5IFS+j5y46X8H1oQt4vBjuBiMW0fbuI4AWZnNJwGnCB6m8eg//NyX7vfOwJvSIbUIQAhLgSgUYjSYFuMH7ZkO5KUydzYSRKOJ8Os+FpYyHoyrCMQvrGbXw6HM65QjZU2jPo+OVS0ISeE+2Bpyve5aveMrcawzduFvAbzxuAdw+YDYDgjqMEG2v5hXd0OWVuBqF9bXnws33b1qw2OqjvBSGMZWxMB+/PdUjql607MnwZ1zlmQ5gOutwlyQWtLg9kArc52H+ZZlt9V9en4L/znN422E96tQEox/IHwgXk2luvPx3HtU5W/1sX/FybHxWMpA+uqMoPh02bCTtiPZ9S3a/9GuXJ2xIBym3nobO4KSyWhrFcTkX/baBjIvJ2u1/TEFeZzjPMuU5nn1S1p+tIhgLzauNrqCnwQ1Bjtqh3nvspgl7lfacxCXsU6MpLLvSjhMJA4y1Img+1QsHDAGWsYycFx7F2i41CGFzZ1MO2fuVppyxuLQnatUfnVZB9vULjqb2N5bsMYWuWv5E7g5JsUV3T1kFwFFcovFs/+YAxIj6fBCuJBHlKnAjGfqADFFbQpyOPZHFvV60E2Gw08av/ijFjeVzu5Fsmpp3qTwMnFd+IHTzXj5kkePSeALoBb+W/nyuqGuHFEXaUhYurUQcL6fvR/ctTLjCl87M+CSbn8CbgSKKQACgTYSYZ3RvyIh4CJvXCBGFzpXg8USr0VpCMWXI/tlFgXE1Y3aoio96HSIK+mnDRYG3OtHXtlfHeZbWBQnEkoLnJXeZBik6ATJZDh7vMTApH4GCueFDrQDCHkJWgOhF5g5/3ok1GkCxSaFY9zKJSSKbS3l68ZzoVheEpeAWZDUOWG24BPobvFWzROB1OU2kJzfa0m/yA5HYFEDCNrfWoWXzZA/Mj3p8UgHHO7aeNnEBeWcDc9Hs9nAFvDwUKEjrPXLWpPu2HHxXUYPwsv/k/aPHMv5yjAO1Srssyoi8WXTYDbPDlFOKzjfbfuDSb1H0f+zKTXBrUybfoWGTF1l8Gzosh3KBMcPpjY+kswT6eRrPAtcIH0vicOD1A0+4xqHKnfFJB3NLzd+KcBcOVYqIDn9DM4bk7tAvARFtgStvVf9QzWqtabR4bu9C6U2/cXdUUXSq1vvl9kSkEJJ2f61v21HH22m/lhy3QkteN4iCO4H7n5eJnKnHOReOrc/QqP05CF+YqKabJpCru8DFR3KYOWGI61oFTyk8vbch4cK/2rrdUhFty3YYdkRFlZoAJ7clZwvje6TWQCMGfhvjKSgzgYWeD+DJEyxf/8sYZyrI0s7c/vji4K8L2krKWZ77Wzt7TFV+kVXIIRhM3f+omIyq7Xn7e95Y56oa8RiduGCKeeX8fT+PJG20WYZv6SyKLQWynCO9o7SgmU4pNjx8OWQFWB6f0z3e+9bHeoD9+STT3+xTzw3J6X34mzcS+Go4fpzuKSqm1sZHRc/M8PlYsfX0q8Tkm7sLxa/+dxi/ZHO4N9WxwvWhDDZ/H0d+kaCcD1xz+/bAhP1D4vO4vbvJ8ZiK/dDsREVUx9jupkLcouWf+Saervz/mPMR84YdyVwyvNm0aZAnhevspFSOnJ4zOMBiAXwyhMZUY1Oicy1yfBxs86CRT+oXlTFz34W+xDOcRI4T32Rurbny0tcnjrJS6RLpQ9jcKxpwYFvRG8IrjtM2fDRZEirghMAkxbi4LFm9hFCS2D1FcZYjM/y7WO5jvLor47iq+4KEswWZ8IUwi5o+Si5hHF+Iddhv8cG5Whvq051F3kuSwb5zy20/Oruz4xvjFKfE0R33Fa+7IcpMS0auIadaAUNlxWbNEJVw+cP9fT16yfmOGnEDcdXk9AGMiXZja9Ga0M0+0Hvm6BPHPfE/PdIxUohUL+EGuZ+ayy6ERMKYpLP35XAPfN/3/+Q7Fo2pLAHHryT5HNbcUsQTzVUWTbpdENlS5Gzws6cmzQuvXYSya35axcZzVM202g7tl1/xX2etTMA4J7pEx55XFJDlfHiGx2GDoZeQ6JN4TEuJHQI+emjcQBOZPod6AmMMhw+zs2OPEwJvzY+hs5urCRypicHIn1nIJkOSmQRzYWW9P0Z247gMdx+SLLVarBeYo82b5Btetr5FjywWH3jvoded92h/qZw2r7ftMquVHNOyWwhxpVWI/8bTD5TrPAzpwM1DkqHanbFVAMMwYNYtYHHzY+GglhotdlQpnWZmw2z1HMqxEdDVrRwApUCp9B8umjdG0o+TSktc8Ui47pqG4dcPsIzdV8ovycVVD4teUD63BL6zU7NTfW541FlwE5jQuUoTGoLI+/bKX1MEkuf308oM3rUHaNc80EGzM4Fi9HH5x/ER+A5+8wM+QcCSAkQtFl0il3Q8PP9lUPYisvzLl47dJMHpf9yqrAXFv7oTmlJS1pt8qr5Ncr0yvtxlG9crWVIkF7p6bURLXv7EN8WtupShE8spsPNUMN9/GlkD3XfWi3u4dfJBW5AuZMpHJ5v2Dy+ifxLncr1p3amP324jOAdcqaSVLFqlvG7Yjv9nTGyxGL4tgCIi7tprpMqgfYeFeQPIUE1pmJ7LxnugSX7HFXXxgN9h16HpSHSm0xZh8KPDO+KFCeIu223b71BwOYoCObU4oBzdEw8w7MMgjewBNmx4L0H0NzPYfeg2GfFqeaFSDGhVyBK/XwnGAQ+2Ms7KWXO1ZSBGLFz29UU7FmcZgqPhMcbxIlcQ7h+BwdFtURoJzNE5EXFIe+5ihQdRaQrXM4kMaR2dpgtRciAKqnz1pYlsRMW1MnHiXHlqjEKI6jU06Dech5MxR0pJOAk8CwoFSkPhBjcuP4p/blYc9wAdxLVZZCMDUrBr4ASvTwidCJzDPOkrK1s8rmczwVv2uoGe2zotvL59Ymf6QsArmHVJX5zJtVsjetLq6KoiU7BNGHfLI6xyDwIm+YhAMo0CzSC/TTHJRVsySrU+VGwqCO9V4+YIDeoEil6c1QD21OQbnYwXuiAhzpoct8QcClST/cz9z910EK4vGDKHcNh+sd8WK8RUyIqzLipfgzDsoElcepMKAX/5apwytlKN6VHPzOCbkko+shei4xAAN8paryX6sx12nP94TYrf1iCtOxu3x8falV8fbnSbhp17ugAZX+cXFRO3TdeT0sOgSdcCTOWAJbB2zHqEYtz9noT+Jg0fkRbR/MldH/dzZnigfGhyQ3uTp9j/OtBbe9g+b/d1fRNzw/G46LUdHtonKuFd8RkjBUjnlIRIFYNgQQAqafQS91sY/RTYwN+txGPKzBD3oWJNpQXpeA8+jh3GUHWBETL90aQKpmlzJDGeBBJcC8OKZCDIa/9JljxVtwERZRO7RMaPdp5qcSpUcTr5hecAOd8EZbXIf6da/aAl1Wx06BTFPdrKNTaOVu5KlRYM+dwOwsx/LypEha5NqwPSYtIgSLyIiv1Uab0iLNSYK6l8E8FcOdcniNqltgd6fsXivCL2BDYSyuLuc1LMQtOnTrzIGscRApLK7p4DVtgFVu+OOyrTaTCKQVt7rdO15rTV7yu/ue3x10mTfHUy8NisEkpE8tokSmUep2P/iunGTRvlKFrQT6UFodbmd5k/+kN0896Dxbui75U3WczveK6lOLF+ne8g0ymQsQChRduCmAURhg+odnpPJUbD2PVLImb7i/88HF72hlfZlxCReKSRJILEgiFgkiGGMJtW23VNW0YcAP0G9LnxKwvmxePtxiX3H3KQghIGWJvL2sPP4WOO1podujecydWk7M26tJDINzalORkzrS+/5Tnb9jkMTaJJ2NRhdQkpl+RjSqEP016d/2nsC0+sEzyWDrfUkEW11eQCdaVA8gIG5pufTMAmSo0Xu9wxeOqnA6+0OGMVT6STE383Zi9K8vercYr6GNFlM43pMJF7ujKHwm6xexl2/esxNTmmJ97uNsGG5s43UmpDpCBepAgS49UAjZ3GXJpk83heGmmX7gEzWoiSpUiQ92E2Axr7mB/IOrELuBfjxFWtZvqx0qb5F4YWp30ebk/tAu8WsYzxQypYJqWRzMcqIqiOkssmhJnx+8c8HuCMoP9iIKv5OmEY3WCrtTsPPh9YQKuNzBelBsJdQDMPfhLXRbbBmsTzMv+yPOZA5PdpUlvQ1H/Vj9iZmy6T0MqOse7GkmzW7s1v04fmRnLELyuLkOBhi5RL5Hy4BECKt9eiwqNBUnmCRggosC1TTJCLOmMUcRchtWzaHNTX1i1EfnhBQlVFK6A77/RLmAppvhPuQzQret/4K7n0oCQr+cd22I3dk52Z8ubAEJSTqFRAtbcvAyIclHq/MPwD0NW8FLRkHkjJtWeSSBUqshSvFhBaHMO8WJT/wTbjLbwQ4J4lDO81lXxTDDeVq+vC8YzdlFp+WSgtFpHGlOXxFne71qt97EjtJAgG+HsBbFMVyVrYsTE4bJJhQ1kJFH3vt3UkVOKU5NyR92nheNQ/ft3ymHn9uI7xzohOjFEDzYNlE2gtqAXMjK+hMA+JV/+NFQXs0gQNBsMhF+7eDoAT9hynTOJ8cX/I7Jd/2EKTvDI76DXaAlZ3g6tj9GKkOfKxVWUA7EFSy6Ge2Rgzmrq2tKxDCB/kYHGkqow6hWxhw3BksWdu4L2WAYcJkgDMHlQ0KMgkdhsnyD1sGNfv4Hx5a/BcX7dBp4uKDtHA40B9pL8RDcZgFDrXJR7Pf6eco0OKPj1rCHubAoC5Ze9/nS5Z5ZSH+Du+majZtsYFlfq3ehG1je1BZTJAaPzPZ0Uq1HY3a1zKxdjskOsZOUOC9+RLHA0dz3+4/pzo5AeK1Opfel3163R26y3rDWrnOPATqb08mskaxBPngES0M1aVZUFisoEyiqNiHgFb+06L3gFNLnJSK/eILxfaugCKUHPWtWzTT3VRo9z3/ExwBtVS3Ti3RSm/N8kWGoQt5wKt5+frvuoUWgfwlKbRZ+JojcgseVSJ74lPiJCmnkJFfssxHYhrHOhESFXuBGtgiz1BzvS9rxOwt7RqR5lpB7d2Mqh6R+B1KpwwDWqUpNhD9j3v0b0OFz34b3L+uhx2Z/a8ilMiiSAFiV5drTMp1k0spWQffMTREJV5Eb3yMccSSDZoPptb9eistsjTu+/MRdAHWNmbvh7gOQnKNiAHhlCAkHZZuimwnYsSuKtVVbIcER1mBnTx08yeNVd/FwTrOtp2YOVisYSuKAVoI80J2gxuFhpqa3MmSuR0yCkVq4pe6FCjyVbj98+CrbPR84NuoGXLea2hpFpSthHptmH1f+vZgud0lN+pomk6pxKcdsYB7uBkMdwCTpKeu47WP4Kr2ieeeMH8R2qJ6PHZ5CIOU3vgrJdfy9Fc+iZu43Tn0lay7+2RbWwh512uR8TPgSZ68CJkvFqPgZYmjAUedKWT6OV82ogYcjl7qYJr/Wf/ww95F26e3p9mAZiNotrqUmHnsczUSKd9K4Fmq7lY8cLy66685LUAOOc2+msQsXjkOyAjp5gILT4Q0c1s+YDqFT+y68hfAAZkjEoWdXGaHvSoGhtsrCz4adEmxDw4q3yN3vlCShe3Y5oeEohrfdN/G9M+HD1/NYRJE1xXXwpPqIKBX9a63yw2AoJLuwXrImfcZxwkmOUYpU3ltu/tby8iZRNHBSJYmEAaMenUcST1T8cXdNaqMCxjn2rBnlTu+d0M2eV5T5iZcdl/ygFY6S2rel9shmJNcXxG0qG/8yzs259hIAsDFLI4JSGryUr0G4DJaYQt4ZTb092NjWLd4Gw5XKPfuLetc3g9q2ZPV3jHA5nMadHY7H10NjsbtXTixmR6kGp5pBTLtFwjo7iydTpkg4VeqW4Uyn+QhIAwyBYzzSJPvBOhcZOi+mhSh28VfZCqKtUQkii7lPjom/6pBTnO4TABcgOafHm2tIuBVLhlLvb4VwRUDzZOKkQs3VLka0cGDai7kbj8c5+0cM3999QdRyrXHucbV9uA9vKSKP6JuJluoHw4p/66j085QcHdG6z3EXBlRCWr2cjkYQ03+mY1HabYfNNviB0WvNjgy22BCMc5iPzaAJRFRcA1DwORmmRrcbHcpyx2HmsT14h4NyuCE2+VWgyWSu8TO4D15LmcUjUJKBMtRkF9DPy7/9BpKVduVNtFjS4pKaQoCW6zzU2ZMgS2X87iXfUWHlMKj6sIzuUNpBnCiV29VTm6My6jgRpXG3o5qw8NBp8YMGkTeGN5iMQMlGOOV4+lTDc0gQoW9wSPzUFiebYg9I+FwyzxRvcAGfw0kZgwzG/D6XExoDnJgNT3OCy9qV9szb4NjUT/rWwffPYcqzeSJnEQ72W17bBgcQwAYSUL3cszSzI8H7oN7S4YXOynu7TxlODD4Ifv34yhK/nB5B0+yJSqrBFEQdCPOE0CqO6ENp1/rv67vWDDbfN6unNzUI9vPoaqG0OA3QwcN9M19yV/oFU/nmfOmdy89XnaS8u6/ifvf3Dx8PLLlHohn9xpq6D72hOgukzShqC64dI54QJwY108hxGse3hgXjfZXoElnGHP4PWCtLGfkPSTCOK4GDxXKacPhPEl6hyGq5yzIlrWiWxLA4LwMKnDkD4mkCPfZPpFXSVTyV6WUS5Jskx5off7tQTQ4jSd3VAQbTihnxOYNDLp4Se0F0bYNfEOkEYQeuYX3TO6NsLR/RtzN0fOXeN2SrQ0KsEOWbPiz2cy1Miq6Dl7vmrcmPmxU9H3EmuSOIPyaYghUAf82D6OcrCTlT4aJP/vjpBCoeGWyVDSwzfXrCmrKQOtzRVBp+puxdIjTSrm1CrbjvNVvTq1w26+8hAZHW53YoRLQ3S3tpawgWU7ePVOetebO1SQkbD/y2Vk7O1dLQR9XC40TEYdP17geAxBFPqXOuRIWJMIDf4fxN6exmzVe8SI+AeawW7Wbn4rTt9KbBOPhxAK7XWNJ1DXHhB8gpW+y3WLOaDEVBQ5u39/0IO+dKerXV44RmkHkxhA0oTe9pZXu1QTXSSihh20q2Alepy81RmsB8ZEkE6oeQRCKFcQLcFVYD+MuRf/9tVP9C+1c0a72AeSwm7WZrn3kHt8g2eDe8xgRRbsRNJHGF9MJv0IdpgVkmFjYooNVW7vmhY3wUQZBmZAY3c8cqCvssLroCFZqSKaqWzXVCKYRFDIATz3h3FEVatMGd+me7dsSDCAKNNRq3jaMR/zMoTqKLvo9uhLdjI+il8jJ5TEsdUOb0TngwaxJ5H8St/1heYWSA9RdZimOc5Gv9mM3NJUVe9u8vKK5SmPP7WEjFj+H3rIck5IOYl+KXNXZtlUyAoP/NS8dyLhTpMRy9beQDBXax3Vzge4TV2rANGxlzS+eLZneyO1eN/8+SG6PMKqhCiWXhb/fwfKky/jReejo+RpFzlyORj3h7DGOSh1sbqQ5Qwet6r+5+w19kJIJCP50u6CQr7zWKEzhBCMl/5LpylQmfcI3VLsQAE0pvffuahpY61D9C8S0UHobPTTibuSXUvbHHjxwhNevhua4JdPfOPLkxqE+babbnNJxowaddARcWrvYJv0olPKr3IyfyPM+jXrRS5cGV5ALYaMawUae20HGf6mpVB9Ux8USH5y3nrnfIt26WTn9+afpcXAjbofSdHOvJKjZ3txM7rHjROcQCuGgL33jnf1H3W5AFWbRbzyT/o7bayTd+toSOaeDF4PmE9Viw+9oJFC7aNhfYyXBCfqME/raE/hdovAYhDajfGQ94xK+J6kHl/7QS15dMmbNp50jEQN7ZLZlp/3r0XuAj34tvtWshbFpJVdX4HQf+oK78MxZR9qV84RmkeGZBBVj/KVp+0dbZrPm+TmgHojfbphglF+cGTyPab/Ei1901vsUgKFOt+ZDEETaRc4FLWfMJvu/ze8NnMzReZgsoRbFRBwXTcr3xGLM2xY3aRvrSGi/mejTsVIAYU7PjesPjI78yCVwJAhR4UqIORxNhp1fQGMk5SGOIWv0bPnOG2yjrVUxl8kVZK+swSLT5i9k679UvAl5NXDMKgl/bGpYHOm2ZM3LI4ZU6oU59r+z2JkzDu5Bn4F9yglDKOiXRb9MVw726h7pbSjBCA81oSdMYSB8t2jpm97JZyMrPBeZ2XeRsf2vuwBJ55S7EkNauPDOMBztBmJKSZNQIkVGG0B+CmpoVgTNsugV1aBa+O+A3chMXSJI62cwEeC9ekq6wzyT5SYlg/kU5RE8wnnZ2fJDmb7Aa7yJX3dKxAfkt+0v1I6IOi9F6lVLplnDDBtuASyp5HpilEFhmD1DgK5vfLZN6fDOArIk5XekXuN/DU7riqidtm9PNc08TGfWY9jhuSsaWjtGefx7CURY9JXABKha3c72l3kyUaAEpSUkBJShJqY1TvVaYin/5Ap9PeRP5uAeAULv601h6ZGC1J8FwAnCUhSZxavJMwvjap0c6yaEVf8ZyqDydAMIrSA/rzbIeDribD9fgX5xSb7LNSMadjFhucvgvah2nYdAE4yd9w/R2ieAYyqUSMDwr+6JdURAYO2Z2zLRZ0GJNjV/xcK49t1ERJNLPlvYDUl67rGaYNs4VavfJpzx1y4zSWp81qzGgnqiX3INtDowDuyRt88BGdMHUYYXgShQblzyFQ5ghLY0SsJIR9RGl8OhQ+f9cY6wW7Ly4ZkEdz4IP2qqYLzZ4YtwjO4+cOw6ITDTtPW3SyrXxPjQePXBh4fNWy9WtkCd/ezT//DfTw6mQMDOw0wwzjll+XfVfrzGQJ8zxc2XG1J/o3ecy4OigZ4fBB329nmmYnk9BC5wHa8HHzCawjBbGavqvtl3ZF6mjPVXUv746RlwQZ90ZvhbuL1S6nGYLjYZltX25z7C6iA/cPS/N3HaGcZQPKm5Y1Efna0ehquSZYtC87c6xlxr4zWjr49QYCc/Vn6VO8ah/Hi4koOcHZGhYGJeIFEZEv0D3lBFztilfapw1kKNxGSdxiNO8nHTZZ1yMuKpO6C6XTp5Chu50ZDEYocFE5xAbgfKjCpDoxIZevUO33DPULWO2G/9Tq5vOzyEkjJH+CuzvWWfJuaDkMCBbZ0ZyyMKLjuq6ZVFJiZcz/R4ousInSikxAhn5u6Qcr/xxwKkfpfdho5D4ddJRKYJTyuvEvJ6MyisFeTKva5g97Zxw4rqm4Hs5mkdspXFZ9S+bL55d/mDxSXQvrK/98Ov0cgjIogAFWQC4U0UtNLbSbvutX6mwUcRWltmfCnvz/fjviCIdn0uN+SMVjKG2+gasevygxlvv8DCrKcDBG9x1A8wddAVKLopghCRrPUivhG/790EZsI6WS9x31AhBz0d491SIvtgiXMG6lkdOSXAK3Qj34u4HdrQNzIMZ9NEX7e8WkJSAR8dEyDBGBokZ/U4oMIHl7VQC3nW7uzphFmidnVAGcvPceGifetE/PTVajnIPoCfyD1dFwpw+jI2tvy0KVCG3kSlqjip53d1iPTZqmgAFkUqCCXMc2JcxEPjHnaDwWVKsM9cCEpWkdH4bmysCEylnfca3xGxtTM+of+xXXGfLNLvjpXgJtPn5dnmUnCRoUfwQRbDWO6tjdiWTeKBEfEpy74lFopY3oprNMg8Vk0bKmogEEuYKvc0GSn4uAIxhcoO8lLsAM6+IP2Y+qMBYp4MGWvhLPhb6+ZJ0yWehJBmTB4iPQnI0yOO1BWfXeszFCUP2iciol59zTxWCnWeKuu3ePoiu1M8oMqHqRWxm2bkxXjX+zlf7KR01fqBHg37/DMLnK8F9VdFOo1FvS0+FYucC7mEKJUJNcpRiBlYEx/4T+CKPXos4d+f3s8v/Sm1MszK0k0uNPXW/lRZIkG7JDVbRXv9F4SvxLDK4xy40O+0iEVnKfHKE+iJh+2mT9RdpGZcmE5hoSOPcezDg+lUlZYRYJvb2SfGr6E0TYnd5eOw5tBICpxWoBqB+DF9YIkOo7e40Q7iVg4FOhTb+7bqz2P3vO0cU5/T17PLoHnV72+nJ6x9M02zbk8V4KvntVR5umrg3tOfWLcYV055hMrcotLeWhJ8SklMrEgRhyffCb1VV5yBu+WGBhHBAEq4ojDhFYjxXs8sjunfstvVz5mv+XU/DdCBUh64tHPHPEigw2gahPzgw3D+eRDsnE914pbv602r5dCbP87RN7oQZVMlzLP8T7SgeGxZLEmWaZbY7fV2cCuW1Tfamtt2lBPJU4YRLb0eZ31hQnHZCstY7F0wWShV9Y4u2RhdWnUmY2I0FI7+/tfgLZBHInXwdFwlbcErFh0mpqZwtgRbfFf1tYXRhxtaowqarUesj09PaMgotUUG9DQJgiwl0TfIz12/FyuO43kPl/ukdIeh2DxHOMN6LFJJOJMPXgpX0t7F0z20czV91L+5JM2/LVSkb3Rh9ikRnPCcwtgabwddzlZNF4OSyqC5XSe3DdRMCNm5uY6g83amkm9eEdugxFHxZD17UIzs9KumUkHwxyObf0ujZZp5RmsVOI60SlfsUyiY3b7oWOysov53nhyiK3yAtA0CYqIDNobmgmC3va1Ls7WW+Ou2PhMDVz99TKz9roE7cDyoncUp0uMEdcONi15WNE7fUcTnva20UFV9tIdsDnvim12qkGgEq6ipEvTQA0SXgqeQTnpNfN7fZ1Rqumw7pJYwfpmh7RggHOodsbG5gsdhGAHhe4qNaqTbnWNolLElpK+MU7u2q0rwIH1T8yW3fsYoEu2onRUZGbAvRs/s8P1Ez3hFANIiRYNQtYliLwrbuTlYcQCPCUEbJq6NUGscblP7TX3zmLoMCqfnL8+Sp9wCA2hc5fxBUybIN9IEoro8uKLRzQyqsDejKpjpEZSZHtPs/OmhoHm4elqTfTIn/O619QtvVEcaCwLPulhFo3pa5VqUksgsDuJiHVF1OFNhIJl0o2GXGpnz6iJTbRdl331tkSSyiHXp3jqJzYy8u7u9bFWLK7+tqbn78HPA20C3ew6P+pQWfucbaM40FW4n0G/IDEraC8OUUmeW5fx9QLCgSMmK9UImzpVZ/RqKdVE4T3EFRvr3StkxT0QTIK1E8uhnAuJFImbeitUsm5V7zaJ45FS80r2UC6tQpkBrDkhfFaYy3ICaOxXU5BMkoFbWc4n4sZ5d+qXi3aYMz+7sRaZdZmwjI6dglhtPNwINi7yQkI6E9BOWR7dFR3HFXAnOgHr59FVNZVgPNWHBJXJjF6F/NbDEqircZZR8Vs5qVDiOZAJKpKY30BaqvC+9jf/5MobT8n8hP/JzQXz3ZpatwEbXkpGEYtLzH/pW1Wx+N7ORIQ7lKj/g9tdd1axcMNK0m2TQROglayiPeUmW3rqRymA+yZR58NX2KDGmrjXWm77o/5eAHmvQbbqfc2msOZEuILcZaP/jDLByAQECdIyQQjcfJIEBVFrNysuOpPyOUMeBSpn4SS1opJVsXT5MF1DeAuPHoG8P1eLO749PY57zz9tDXKOkjeIpjcylrIEUAEwlCJsQwZgykGOplFJO0aQqX6099OLZBQeVtbSnmWnMau5zMJAEMxjRIVGdSCxsa3J+vhW0IzPuTqnDBo/nvNZ8s4cgqFdI7789oahZ/PfmMZ2A1tjRKW4EHd2RPXVy/ALuvBV58fiTBKZzZ8Dhxhj/50ejNb28AYxQpwywsB9svf9o/37TxH8fxH9+1RguBBUY+J0cBf4oVPvTZw7gF1y4jbczdLH1rwlISpTFt0Vd7YaueBlI/e7/LzNg3npq6tITGpdGZnsL/zwJn64JOWlW8M7EXFWBNWDJdnZiewLGpsE1LE5peirWbNej1OtYQPEzZWp2m7RJ1iS9JcF5vCpMIpEO8ufcl7uipD5sePDQleJKf+rupxTSet+0nVbDdD4KS0JU3fEL2UzLl0WW4kaeBqX4s2Fj74DXy030yxUeepOc2CYPT/B/lTQ3A9M3e6OfkjKhkdA21mYbRPgHtTBVfKrr0N37g/v6L9QxCpU6ZMRfEza2w785zNbe4Shiers5I5vAMlSRAJtVcR7fb6hFVXUJnqObKQLrprWHh5elzrHmrIxNb7yhPHQJVElZenAft+s//7i3b7qvvax94ahJcI6t8ujqYaf+M8nNw6a0eRBIUYl8itfopd0+zl3njEHf9ftHR961Sm6yn3mzJcPxwCivtMBNU7Pxepzhp7nqlClf7OPACbftzB6GOlt79NNIKVM1L8G4aFxblBHQUDAon+2OhEboDAZsLcmhk3nOj5ed+HH4ZI0mPpmjpg4PyIhjuyCRMxneVIdcvEMz062IEPDcINnZFLDpyDmLPi6Gly6iU1mOgMZBh2xZnI4FEnUVo9oHP7G63VLWA39iaLmplTB+vVlW2WzkBUy+RMreDOQg85YwZ84OfucHN+6FQj9UlnkaUfqWXR/Zg4YuGeZXSkkYY4j8uwQIEJfffFIzm/YJYH5DM19z5+V8pGl9aLTHhExAMzMIj8I5tMnfqnPkGLmRLv5/qpnqRnZqkIWwXu5AiSznx/DrUvMOiHzpHd34BDheo4jyizqhSlUc+qq3QQH3FO15FJGyn1mHhL2hhf4pk1Rx5RfauaAQsXDdjNfP0WPE3x/kyB/b9OgYFpt/sZq5MSVPua03ac1XWyHLFi0UnGWu44BqPvEJ/V//eKF3/ERCLuPGb4u4EdiY1/1W81B76mvLhCKXI415pbd65gi9liQehbPjxgSxWzoA49hNSPbZ2339Lk6J9/pHOC9ScNbjhkH/b5bRBx0rfp+agxj2cvbN2qr6pEPKp9DCsYZMt+b5I9B41XLr8oOgZrKz5Nvw8iaYiR7gIiUuH7HsQkxchOoXmKpwTrZ+NWNgmA292i8W+v7km78Lta8Q9XUJrPP2fcmNaU6iekXZ+GX5/w7dPfIb52zdrPL74NO+amlBUk1BACf4rqGtHIxC2WbdXzUPr9EXcq+d3Nq3x/eN1I8dVCgP+wP8YHZLyQDQdrETMdnOXrJl7j3ExoSWxLjFoKvvZEcz3AMV01TqJbzQ3NhfFCJsWXVP7EITsz33y/ujg6I9KyaaBYwczrKXKMrRwr4yvuzBaid/wbKDx0dD9jAse4up5q2vp3BppJcxq9w4tuLX9qVyv5eba9Ywg6fGFN44HTnjq2ut6uKNoKKY2lBICxkB1qrrZgumn/rXOlZ4mtXjdUjV0JmgDT9FjcE35VO8WYk7yC6JsocaM81Cp2FJAR0r10MNFUjL7t9eG709KrNg7bLhN0juLFdK4lBhLqdyK1QLkVuUVWl7XYXXsoopiK4LN3T5NxhYvO1L2ciJtv3H5E2hMJETBKjDBCEbRAnsRV+TPVfGsHwxhXgXcks8FIyFX42NHDLj/EnQwCQUIddj3yxFrpAMld7ll5zJ65q/Vypme0fyGkP73/TN6E9lzXhejUm569jy9VsMPr9OAqwjVXvQq7tS1nWmXwu8ObXSV/ZAbKSSt0dz2pYwMAIk72MaM8q1aXFdNie+fKUKbsXvtoTsK7ub5xZmFiJRCgHaXM5AnAXQPcbt0ZJE9foWMCezjWhgduNERHl62vXUPKbaWeO4f83dWqBm+hcKj8hmaAsPvOr3lcGV8MIY5acjpoom2WNCVM9t9XtrFQ1qITxFa4i5bwE5pTOSR9h+r7A5Y8hWgCQFswhiIaMWMKTbMilYjMyp6igl+U5RcO+oXafoN+T5JN4u8+bbRmM8BsK8suyeJG5VITcRUzUov9rMaTAHtpfRCGLIEapw/QHJbwSlhlPGVqV/qzIRxV9gTe15INC2ctey3BAJaqlKlMELsiKUeOZQRXOf20sG8vIlzu54qYo65pSPuMGp2NDWasGJVX1cj9BnCyg5uBKrf/DnovQU6xm/P2NWZrxsVATphUlwlZyuzBjA5kwJjDUESjARxEEC9HkbwRWgkBLbqua9tx3ntXpz63jY5n/ztuOLJXcozOWq1yy1AlXbbl7vA2R70Z9snXKKNqb3aH8xDy/hNGxdOflEGwAXoIfwHNU+GyJr6FjjfV20bhC1848VLvMd0hKRpNmr8vpmv9PKqZQOIh4RQIz0ALZ7xQ4FBhXo/Ijzo6WwqZlAAIixt1VVo2TVjc1qvkDgATXmKMxqoacPItoLVcPXyJuuE1yf22U/mXy1O08TLTh4XGlFMUWzJXgvQa14glsB40n0MfQGNKlP98eWgH2F2AdB7f2ZrPhji97+FI7H/TuWZOo6b7ayZGTfT7pcH6knVFWkZEXbUfVk69ZgfOivObAn0F0UDesMGObIE0IQkgTl5mSgtHFLtps7t1bWj/Kuxw1a2lVqRTxaTRrRQi2C/Em1WjNoqpYt6XJskU2nDxT3rjAIzSU3I8anRSq1G67gq8e/I8ASHcMETTa8hNK5kip/VhAm1rFAR2AHCyVjhP0LwEQokInN5dC8WQlfq/gFvAzA1iQsc70y+k2GFhkQyuhbSgxiSCeJgyE1OOGTFDAo0BFHZ9pH60Nqq0u447VN7c16oSd1cP4ceZuPXzTg5p6akOaaRryViTjUYaYjS63mcMb4BomMGnlJ8g85f6EmAR35xvWv8m5kbmL7ZmKT6Sio+LMXzaSntcEPzs4s9cDnC2bhzt768clgGhFJIj4cJmnSDaZyFzlhoWVB1dZ7brrEPNwSEIHC5cgD55SDjeb6RUx9aHvmdshh1PuwKfu/eAQwiVnUmGq54iRNvDdFqlfMaJ4fj/3AtVeD1278vhRDwQQITUCqVpGOOpZGjM45MDpjwBGBgdYBO1hEt06TI9DxWqiUWKscSyLKmE4aAipY4umSDm6HgR7Vf2A5DRHnlXFrRfToRSZnsg0VBiqbxNkFog7gfHV5jjgtOk3vsSYWgtq4B9f2r5pX+RkyYiCsbliJZSCozHXIQpf4Ekm+GpJ/j4RwQw6NQ6OkwRRyUoCTayhLUnOkY2mBTZQXhfJNfbDBCGRLhtwQaRlzDqCPSIAEmk94LUp7XZmCWLWzTk0xIUGaPYPVLU8uUJXll9eP3/knh0DBmKsjYEALZVrZDFMFAYAgLgRbHhlhoyBDDGiHX1ykACa5Ii1a0pmiKC1FTz2IIsoY4Ng6mbczCNAuzcBa05I+oVnhPBlFMkBWX/yHK+e/R4Wt3SgQOiz/Y0Ht5NSRafSdxtry1jxXk+hkxXRU6PPOnnzPsgryTAqfyC7vJ1XJ2+mve7Ln1nPoSui68qLe1INyxNWtD8HgfrK+Aiss4/FHX3hqXjwu7adzCcs1VU+pnXxSpXbS9w2I/UVMPSC2jpaKYKNE6fNuXvwiZuOtqv0g4mShKDQ4riHMqn4mvlY2xh3sxScoFE8rCws6Q39Wglnx/eZhF0LN2w5Ng5fyalqJCl7HnzGqFD4Pk+wvXbh5bv/W8J7AfpPWMgClhAANowAKGZBVNAg1nWi8BrjrX3YahoifiejZmJOwLmC/wiGkZ25CVHZM1MSs71z7R4p/fXe3c2nDYPnPSEX/gsLuN+ICPuoK3niFTdxFk3JziwpjwzDWfaBo5JYXdQUyjUU3ROseGOEPWF7s99hWd/O0nSugj41edlluA85/FaCFDOkWxmSyfs49xNdA4KwWeWtcXu4ZuP4brma8XqueWmLd7Bq5uLrQ7c7InZufs/YKwwNHh0dgV+WyJ3ABvM/HKzzOtg/yu2M9PQMMI10UBTBsbfOUEe2UGpsb8kF7EXZkenV1hd//lXG/q2YGX7KRwNuL39NynOQ24lhB6J0vNI7r9i13Yb0Sjc5Qrubjs4HndaETQmziO0ZXOL5HfstAyLGzyuH6fltzEQlYl92C5TVURlKvABJmKEfI4CqyA7vmtJFeRmQoAt2xZ03mb0pWoLvfAyd497HLmi+Q/ljGf9jxN8LES+xLS8HPj3T8DD+TxbrJ8TgXRty2LqG/BXm8n9/482IzPHnF396Q3sVFW7+0z4mk+aPv/uqztd53rCVwvGzW/pzbeu2CUkbyom+KQ+2ycNhkWQstNtciQcXrwf0kNNPI78cU3y4X858mnGwo3VrcMgJKjeSE9WHcnKrwxO5r0idpye2HYSR8dbjBbZzO71hcAwP0cxM/9mTD846aw8n7jw8eG0mV9mfTw3kjco0LWHgOaxHKfO7SYFjZ5Kuimm30QRdG1u3w/rGixyD9U0fa/fP/t6xGXJYi7WW4qQDVJS44O7Mte8X/BTU764tlhdYG5sR7l8grAYW1rp/CF1xn8IYIEsuJVzL7RaIU6l3IeQzirLleCR78n05hE8mrVcbfN8kQjPQx1kaq2nOgNxjoTc1qzvjvciuZQBckrQ/AZCKA7bBDAk/CYfoPRb6uMSOnJb6iEZbnGIBYEHzMxog5+a6Lt6ubnAuc2VqPT/DwXMboaumuh/T4H1XY68eZPzED8TDqAJB2D29nVcS2FxHe/Tm8fyf/a2MtPD/9A+rFWzwG6Na7/Zq5JmS7Yxd0L0MMlabCe6FAIdSHv0B50lklTx90OTbp78a6+Jmq95jHn45va4trMFeEl/spo6wH74OoghXSnwRw1dYwtWEfHPDVUtaT285shse4rec11gQbDDBuqKj+3bQlgGjvfQPdgMpiADVPnTKblNUFkEIGoH0LH5OplEL+NCEVvKnjaLDC3y1kdpfCYPddhCtVobfDpvqf8M78aL9quW8pp16hZwL9ux96JR6ErKn8vgmYFtqSWvKP11dXw57Wp4OAV4k5b7Dif9FxN5gvBnthzjWTCFPno9IvpR0FOXnoHEZ96NKTiH6779+3HNs0rpMJfjizlWvOI+0UDJw1qiiaCQNRaXH56l0IZrBFengpXiXVrNNAE4V3JB+f0kqxeHbFnXZXyHnOlH0ybxXIZFEgOH8gj+dtKFCMVql9Im05nDB2AEgP1xjCJWVECnxm9WXus+OXO/te4IQxaf5piLC4AkI3g3RcqBfce7ccDIBtdlAS0nDNfzAn6UJjSR0kRSXPRa2R7cZrEIWx1aT1JOvw0E7RXuphgboWIq2dCNCteOSCD5gDktQY4aH4UO5AbKCrbbq6tqayy4Z2sdRhHXPLCiWauvJBbLbTHE7H/XeLwt01R1+gkAE+I+Wg0G5mRp7xJonHqXzax2KvUsJqM58sEZrZcyhD8vAyXE02vRFDnqSsLTyKWh2lrLwvWEhO5OCxqto5Nfwip485XXDpYnbrm+oD3ZozDM7KhekO90Y3PDSji0moWjW+OvTlK8ZYMH1PKFwkt/wVc6uAYRxJhbSJ51K1ZMF7a59i0R/Yv4vVH4tdmhEPYX+zN+eAla34GNlm9UdueJTiCIlqJr8N+cXVd1NgJTt3VCczvO9Mg+wjs1DKmLh2PPvaXKxVMbYu0W04b1tuZuPqdhexnSrrLJDESDESKQ4jBFPGssCJvxIOeEJ7iXWFDgXWH7Y++JsLpLsYzghDQwiGnlAi1D8X1wFGr/2zfyLAObD1N2mOXgnoHvxdatWbxiPHS+McBywFkWuSBsiSDbAKTYoW9iKvwh5RiqVie1bQQ3NNiDeZcc5ydI+A7Gg8m+1iSAduE4X7E2kRW2Tm+FkSHcB069knqlemID0nTAJlwtq0lCz0+oH7BJiUiavZRX8tBQd2R496NJ4OAOUodbbM4nzMtI9794o4/aBw9bLL4o9J/kUsAHVMJURCoYL3B4eZjUTmNXh08HuNhDlfvqci7sEyHCFnt8iYPJ9zq4YYJ64jnhN+rZdmaNdzv7Rf+slMlYLHC2KxhKS3+CY1IjhzWyxsWWmjyve4HAGQ9AVT7GBM1SRZe06MCbFTSIdtnc4Tf0EbqewghiBByyNRLcyQexUpFSvLN5gZjPw+sckZ7WTG61h4ntXNDngMvDvhJYHAQonemRT0WVDJHmtKzeKiOH97zXEcTMmJHOmKxjk99COkX5Pt8uklUUOV21sIiaU2CDmZlBkMw5BOtchnC0clRjvhOzHQo/P23YEc+/5kc7luW7vqsj1q6OmWOjbvqpZ9t1Jh/+huof8B9JkfxmaV6ZKl2HiMgWj4fruwdDTc5pM6oLHy0hngjPp2ouMQFeKjymxN1HTpHx1710rlm8Mz7x1jmE2/K3eVZH/qZFZk1BVctgcfVUW0ML/EUrJXkKzeag+ZUT43cWpnlfl70qEBqapCpHcp4YO3XEwZV0zVaEhzLs9m08okVrPqKLA5baaL4FJdRMpuQ3CEkWA1lq6GwaLSoQUGO2RVL9mZ6qt2fvTd9+yWXoOC2d5EMmY6/uwXlkjHiT4uyFChB3I9t8kGVbdFNPBKXeE1LClb9fjYAxM9HzqapYAzoRbeYD1Knhoftvf0Mqemofv6PYB+eg0EjCCaWtxHdK4k/LQZ+P6PiO9//dPL8sYB/9zwKIaWrk4BmH6SvAcwYspN2467cSHP5btER9F5+U7zRN1YZXXDKOQaA+yOjllr2hYtRiBpiADNPpI4Ip3gQthVJyvPLJXcA6iKsDFTHd6HBtyRvbApXBQ5JoKlobz6DqBDtqI/8ax0pBlxGBqi2QX02X+bwngJF1zhYhvJxF+QhtQwZu1ug0RPLaWIETkWOcP4eUptpI+pU1OBVPrXpaOtKPOCvt9Jib0cR3fhyiGA8n8jWHia1b6sOCSn06nTSAWxP7W/iKQfFVt2jJHY9ZWbeth/ZgL4g+WOOzRSCtnrzjTZ0KOeNH7arr/gHPgIkY2Y5Glo9sB0K3nZW2TyglCLhNOlwkiNnfqus6mwEa202GLFonR+n16TXXEhWpqZCFpsPkfWhWLgx9fJMZV7iMGi/eK3000fy5ZmwFl0pjsknivJlEg8lmZ1HUT+FCd4lfe5XnRFn664A1UAP7WpHvTcsrpFc+H2/q2pi5l+0ytse/jPX2Kc/ru6fv14bFy8TYcqQVNYJ+5d2r6nMMWBkCUiYwn38KwDkQvs4EFbrVuNhWRL3OVkxMvGQi+AjdObQzUCrwBFI7Xu6Ovl86l/nOxqWWe15cGApMdPrRnyHNLR+9bMxUAM9tHsYTt6ztFIN8JtTiVjYOZsHw1oRpfkRK9KXeSneqE35vGAK3Cj4YLXyG4/+71JqMMutc+A4nN7G/tbaKwzhxN9E/AVaPfqRLZfGK86kQX7ysu/BNKyiHTtRKmdagAVqI+IKOYbHUaQWwpBm33xgWgOM2cUKv/lTPfPnyr2F3Ju/1cMW3sKlfflwLjGO6GZe+Bi29I8uqEUBU+ow6tx6dNoW1B10TTxHbk20bgz7SrDvwqVKTWGFhyG3WfJjX1iL3qeKeMEroLFfzNZZDXWoT0LJew/URn/4fHatZo0RpvRAuOTyWinQ1AElLV6mNWQ+6ztc41JpaiTvfHXDOtGgTwg8du+6NInPVcMxVui8XojupWJHdtPUiaMAOqkJnzZNFwqR1+kiVA4jt1n3c5GupRiXuD5cekW1x1jLTTEMZtpzZ8TroXzDsfny4T9nToX6xlofdT+3Gap+mbUXd/UVmIaE/chRCZ1CmWqkcPluWnOSYiasSH//Ov5tiLOQV7kcEEsccL/rSDQR9AdRsLJAc/Up2OMsRu+Mo9A9oBJIxQ2wfcvRCT9gGBClsgQS9XNB5w+i9zl9P//8LtMR69w5CNgv6oM0b93PB7C7+6J1UCMnokh47ZAByFgKUADhiBSeD0UjuMeDh6MYFwvT8Mu7bS95zZc/pvY6+hzoGEnDz8CRKXOe0IHQmcOV6+SR7X6pTpkv5ChZBS9QOzNQXHqsTjmGmeFnyjiDrLpehCbMGy0gKIvf+fwrvDcjm478b/i7FHjYhLSljYbwP5lOsVyMjGNSHglavOLoB3sveUkNYlfyZ0MT6RLLoOfr5cpjFOSK3E4dFM36BPrgH/EiUCApbA2cXg5rmcq3W2yGroSgrzcx1SQmStusbbdaCxv/qaKEjJtqmWLC3GxdmJNdvkhqDTY2KkbAW7fyPrxlTpP9L6T7YoHXQ9uvpU6yLqjkkrZ4WtoL3rlfySsl9fu+zicC3hthFU4ZWSAN8J0WaQeUSMoch7NrpldCRcTk/Kd7kpizK9UdHYiuLiqZ7bS1pvnBJ4mLgXDTODbv2WQjD46yP+/9q41AN75kAou0vlfxIPAWdczB5CfJa/iizkWz1TTb3bwLl04vdHZoQKKmpJAZOHxyai3OQyLdIiA2sMyG30qHMx5znMvQcAa+0hTSx+CJymaGEAxiZGyVMcFAgm2rgG2bLC4mNTbd1DtafxugcVkRgfhfASMkLy3HkYVT3u+YsPXQyrdYG61EIWYjDe8Nom0RyVin3buFNwyxsjXzPezGdOMq4uUxQQdDKTrDDLpX9DqHKpMWEvvnFXFeWP9Zu/8B2DMmD+UnGXcZjWGTjs6OYlHnCQN+NBflo9tfHA0iKjwKYgEr/D+zUV8rSOe5n4KPwgoSzWLiA1QwEFfeR5MByxy+hAEx3asqxuc84yOyNKTUFGHWmqSSRBRljuOZPiA/PQKxo5R4FsY5rYFDTluAdDVGF2B0IsNf2K5G1nYV5gaYGfEA91ksVHRrMPvNu64wCdd6Ya/Oba7jvy84o9xCZrOJ7QXrQlA+YIzvMRd5vacJU7qBMj68SdTlLy2AyY5UFSaioQqSDeMeTorX/tmKdx2TkDtQPmJAi5OQSVI/jS4Zj9aqHNLaFGJx8DGYL8+kKsBIyXO95i3/8k7zLmlXKClAevUujcFmq+uQ2eYi9SWeswkwQKaQ5WQmYOYx+o1ad3BkyNKxUfekFyY0i3Bs5a4nWFhXjEh9hNTJ7GDnGqwCKATEnUW9BqfAvAM04rN+pcHpSZfiOKXU2Aghrz6i0ysh7ZTra0svyLiV9dF9XIS6bZtwl7KJrAuKClggtJIeRlDyHXm58r3dDosPmqwkNVJCCaEq7IVZMl9k6HyXnXYdxA4j9gA1L6jvL79kqm9WaB7uam0DSqpAyC8ExWuXjUM8ebtnl90Wre5dhTra0virlwx+/L/4JlptoxWBlHSvghifc4uPCNNU48ThCBWn8kKHQ4t1O3KqsUb8SZPwXIl7O+Sd4MRQHI++hv1hU+d2mnZfwN3W2svNK2QS3UQoCtFm4q7pfjx7br0pzONdyeOA9XcPYIVC6TjUfsqOfqAB54eC5JPL1dbEi71hh5zsAmtHWjG4kcU7otfL1oSukV0DaOleXR57OjA+rE1Rpsiu+oQLcyyho1SqKOp+jbmwQqzc7XVqGnMEe721hqixe/uCeZdOGUVyTUiV0TmJSXsRf41C7fF2rUfnAWCL8QndlF0jlyagj9cyLj/9l5q5Y44S/10IQPYOU15j/TDc7jnW9YUVA4QX+Jz7dbX5qZvvJ8QAh6O3YzsH/AZn+IVHX52w/OdvU+O6BWksl6jVqmwk4PBP4VIvx3Z7iUBppH7PL61Rif6wYi/0svLX58YjRyj+53tJKEgSP0DUsDS6mP70XSd1Vp1q+yqxInj+7e1xq/7Y5u9b/hTr1WoieP5Yo39zEEGS0yMgO1gBT7NxKqv1kMpmJeDgUXECVKmehNw3dBYoXLZZH8ud3ZyZCoY+wB0kV4ZFDf47/o8BpSJQkcKUi7mKWHTmMLKzYovmjDzcW/t5TjfCQ27UxkyRvdGLUiQunPs1PfDTHlEj+9oMzZBBO0vwLzufDMu06xi3LRczkze6fGp/Nje8CaNjakfMwn2zz0X6uZf8xKDZuX74tcIEj8rUyWCw7wagKjjKph7antavqCHifQoOmptqbyO2PBo1oPukUSLLjkW6xU7Mt3brrK6peA69UPhHjfFX1c4rurXQr1HwwgVA2g4liW50Nn57wLJOi/6QDaaxHt+4C2T4MEEwAfgfeeUkGIZC6/AagGEXvC94rpnm6ksi/9wz+1zn9W+rlodfqv0VyfDjnCKMapjkI/IEL9J/s1ltfcshIdCQOrfOB+UdRv8eUOWkjSqphYnht8wtbR/hbVj9dwfWLmUXf/37bIzd88sAcvHx8ZGO3OudstOzogAu3SsjhufYeLndcsTtgoBjPiHW8JHhcuYVyF+TTHUojBWT0uq9Q8k2DzbdITQWpHF/GzEKdk4kMfyEYA83c2GyOn0tWQBeTdyAG9T2iOj7zD3XZu2fcutfPmox8KrcFbHYpJGMx8fZ8crr8Dp4eUGD3wepJNlj1yz60Ci5gYc/U9X2dmlgafv+2ms4M8qmgSUh49jS+6rw4p9rJae/B+Z3puGk2ntWHfxMUyx9XLZTuotnfj/6nDTIPIFlzrX53RNXz/6J2PVOCJU0vrxl29NvMO7dOuFjWn4vV2kxN+S136SubgzcKHQqep9sBRDcwra1OO6sRB2PizSWUJjeQ0a4K8yV5BN+t8IiNFxjYL/wc/cwTuLHmZiF94ARuQZeLaN7c2bQvrpxzjv7735e4HW6pxZ7Xm6f8h03sfvqcndel3sa6Vv2cZt/0TwqFkUfw/hY00BUlXWvyDPdeAdzm6c9b5X3CpjiW05d0UDAnRg7Z4yy2UBwcSW1zZ1K6O9QGJY9P2jRaUve8sch8zv7WjTbFI7Lw+JzcwD+SrYmsCKKfgVw58WXGIa9e+PQSk+hs9426nVJpOvYGvSyZVnYsnSsb5Afu7vfvih3VEWlqVcI1dpztuxOMkSx9dWTJlUhfCblIV9ipRzZr9ES/KNS7F0dI3TZMExXwy4VYZ2FvXRm6KtLGMLfFjJ19BITt5+VAi7qNsOt6iUnAPxYKjRwLihhVCVM3zKhGh3jYpYc5io1Y7fcrvxyGy/U0HyE2sBQ18ZEobVVqx9ievJ/U9PoVlsdukucm0KE6lZWpTywX+TGqeDq3alWV4sho87dzBXI/gkiWXlN6uPwvyMwlSHzfOdRvrI7aXVptoxgZwcOad5l6HmZzUp5S+JhqEFrC61VMERtkgQsArGpGKCv2pmP7rE5x2GBzkfUBw/0z1d8PqHFKQp/3wYpLG/h0YqYmTbdyKtOTZWRKcWiph31K0W7ACJhx2dGDTR0KhgD3ShNrQ/PceCUHBscU5HJV72mHezrIupEkgAGvAJ+9JErcBZg0yMgR6yEpx3io+wMxwmCt5OzAWUNXTlHaPkhI+4hkp+X6LxJTOz+LdG/P1AVEdzbQsvpri1B5lfYg/Zfsznnlj/kwi5ukDiQn0T7wWJcyNMN/JaJqD5EXAuqBCVqcZFetlsqxdxQi7OdJKVvWkPCJ+g0FX/d+wNeYlbb3jsUXfTZZfL7AWaFSom7HW7yIRDDIXdBxnynGDyv0BlDHnR6IDU15K91Emkgg+RLZNNmst/N56crXuJmgxZA3GbsJvYZL2rERj/vHx4eRmfsbXU4EU+wCQBIGQwJhjtSY+iLiy1K8eZ47c8eQUcts5WdfX70mteRrHb4fcqLmHsgxUUmMtZ6/a87FyJHTUIDOUVLPgROEGKwuAMfjX7wVyzVnXr1TgElP0sa4h+J/KTt0T5k8xE3hrHAotjv18Z68OZBeNyCDdRQ++tD3iUtlgjm1KxtMSQ4Ng6TEglqZsJuzrRFuZnvBS4DKVeJTnO+LcHNE996D6ymDC0vCZ7IRIbB6H0ENv8sVA+pM56n10QG7TxfXdI7c5n+3MeGeG9wRWAUIS8kqbzQKvEq0F7lLnJ1Qjr4NVl+hynJt/5MY4Pg8xa13KfDt1+XAuWB9Hm2NVBlUaiithCx7rKgLMOWw8WZ3pjHrEabakKqBiwAw/ypxLuKSa+nLKrPliPitWxx59HhK7WkioZCf2MkRvpdGF8IKWjV2yuXfJ+IhiPPvN1sZs/UYCL645nrUPCTHw7dZWB9UPqdJcAdGPX56DNa6Y0UaQc6Ch5cjWsKLnSl3YQRYYvAnISkBSzJh+VitGRjMDyqbF05ltZNmC5WaZWj1apkw0YdepeKV028ORGVpFLoy21Q427DkHvRmWlY29R5M549z8qQy/24OZaTxUdeoQ2TzsMroOcQTOMQDOEojL6LmPkwToZ0zsCMmiBMwELerBrxalqKEWc+SQ0/HwFi0r04MTxnlxBjZmnamCb9oodJ2PskSKmLzJ5+2+XhKTFQ5w31lquC3PDPmRnNwdgTd8GZu/GkZgBx1Hdp7TR0kfW8JWD7D0UxGxBksVlYblaUNwOOYgLXwTFeo7i7imShQGi+zlh1UhVvxa+22+qSqvjbFeoHUnoxl1rh+mvyWLBH2nTV/KHBCvPcmxk7W6izJsnAKRcE9DDEca5/WAPeOQhZBwtkMut9p7Sj85NcyB4hRXb6NcUieTn1migfTY2i6FqsqBKYG5j/iBmUEWv4EuhRmFFSjOxZ/VkadAFMHenjeAMR9prX/V2yftmG5XivUdH2Fw767IlzMB7hf0SgbKhHjlHm3NstnXzxILK6d9sxbElEFFwLVx8TZoq/3Xf5X92RIsctBILczrvV6YfI64DMK1dRhKZXrMHt8xW2tV03g9Q7W1PXTiH8chAFIySS3S57Ed+9Aaij2eHIQLw5v0wK2xiyDbdN1CBlkwNKUXywhPdBVzDwz4Ar15kcZrjmCeKQxsTM4LR2IIIGeRsQyHQsQW10yg1mPwdiiUG5v6xKK3uK5Qndq0LfOMSn+nRwM5KEZrAThqDVOAsAc9eh0CyKq9mfi9dTN/pPxHuuks+kn6Hq3iSXQN9toWj0bjoxUa+AsnyaOwvhYZMpjaLbxdGb1ZAbBel1G+yFTUFxgRZfibpWvlil4MdUfVXlYjHWVJlXrmO9/Jvr1GacjMCIY6M8U70thEo/jl1MHZStShsdXLdZGbg9qC9wG2hlZspAdlmqqTQVqj8b1vJCxcT8datLrzyI97kNs0xV+u6hohyTdyXIeF1dGIdDFFvLjNcFPRmmIKxUkqEWyfrS1zfEOrlBjDNc68t1p4zWQJIdF3kxx1V/2Hx3tb5w3g+0CsP3fRU1rcDlPkNofG+6Qfugsb1fDoZeJC+Neyo+mlsCCnAgGHlX8pwHYnm5tYi9gYLFsAt2hbq4LvBqV8wh9lppzj5Sh2OPhH8FP0aQelZUguj7PlF2rVOvkCmv5zVjSjLZ+WiNyS9wdUAjZfIhLD72lOxxQKHgya+RxDjKtQqRDjNK0llZiiHD/QQDnlMIjCZUntZbE/Qk7BQ2JNJD1RInydhkliZpW1DwbuqQbNvAsZ/3WfI4QQfvscT4PnzDEfsTMv/TJoF1EFfm5SzlL40ngxkJdhINA2DzKHj+vP6sWnyT4+JPKh+KL8ixuAgeDcxfRG49lbEbA4cdBG7cA9XsNYspkcVzqSdg9Z0XSH/YOc+mQDwiyAIiP2vlv6uJ8BpqQTelpmXGzHSJXhmGRWGbNtrtorR8A61ZnlZ1g4POVrZf9SLQfFiaaGvn3D4i3jo/5VXfY7KXEIfhnWbZ24rpRSfK9rw4vCGEZfLQnd9xd/7ytsda11j0Ahtz4vWObcqOvNAQR52XnETNQ2E38RBNacPaqkiXYEmiEKdfdPQmZNO9cwgfFZAwSRcVhaze3JhcU/GbWlkW3rPXRl9uaxt7IfMqZZWbME9dQeZ+HbBnVGkKFHvXAzsPmHJDd/PNfO0kkW/f/tjidWdTGRjqOZfugp/xQQiy1pmPLQzYuXNhxgl+AwrrUUgRbWBsoppkkobeltMAweAbtqg1k81x197E1PXYtAVrPD2FT/MoRMEtoyKvdsjAADn28CZtIH9YgqkspyG2mmPS1eaCK0C2VIxFR0lPXI4wfbP8kyPsFMM9zp+iCHDV+seEaBvzPp/YV0P8FmwPdmo2SwwVo34ojs++aR5tTSmikulGhy+w3L3E88VXIayCQpsTcssYmHhhtfMB/MFid8R31s1hpKqLMxQltoRL/hZXacY1/rcS/BGGzRwRih9W26fNbX8h7CedD2S0qEJHrzCo39Ig2magPi+PIxg1eFTyaV/1t+cHlyHCX9nZemwAPiJhItQsYwFtcP7k3drqCIyQHMyRSJXIZAkPsSn9l5nInp80XSvDvC79P3ZBW6l4tQtX0xZpQG7HtlOS4TL4DOCAl++6xG2HoAwCJeeKFtnihNJipkkEZQyoUgX2Kp4mAAA0oLNAax9cgCyFEj9IegN3ovrYJ9oAHX1/4ONTlFZg6AuH3Qq087+Q9ADfmw1lGEU8fJ/ii6rXkqzEXmpfUV+ahXI2MTgTdI4YIqQj04Zz3INwa5yQR31kfExDhJdjofY0Lr+aKhWFtfJIr6v8iOyt8uPwbIshVKh4Dt9aD+8pd7i+9DpMzj6NHRUBlExwMnwzBoibeHDaGiZhPEaS05YBLgxbeReW/RePmpM7z+rrOTlCkjqXQRFxwD38DtJYbsBFu61Rk6HbFPhFxYrTftwKIh69bAG+/XfClnZge7+MFH4uJELz0nSl0MvHZW8dHOeOtS+Ed0CP4OKuvK1U/aqWbfrkLBuwbtiQJ0mRLwVZM42nu8iXsqQ6ftKAuC4Yyxkz1blNcZCehApaiqorWORF5S/Ml8dNktUx5H31dfzz71D54WXEwaHZObb1dujWF4Hym0qhoxgJGElfzxjdgaMJ2zqAwfPJAUrj3WnDl+7io2OzzmXXu5S9H5P5C8oHylKQXehLwYpN317X9fmuvXtE1XSHcON9QLKZiZ4BLaXmkIlg9k2KZII9GJPhHN8OFM5GqxCT+syg9HfTAwCXXxqv4sq5ctahCthm9Tk9wFpVLqs768ZpcY8YrDDZTYSK5TeZXXR2E66i+YBIX5S2JuJl8qH0Xfw1+3hkHtNVKX06jzsBrEiX/A6yvfyVgwjifkLngUxUYCLKgKeTsAHwryiy1NHk50oHvdJdgfRfR/vGzREEQZ6zIRLgGVfTq69wxkfxnN6dlzTmpb0EerJfuqVMYwIhde9dzwDek1ies72AjnywTnb//0MzEldCr2bZFm5y24ZjX+Y+w0myLFCY1OLuNvIcPej08MMwqmaP8ypCXjYR0kJ5LU8iQXCBghQRib4UoXLWl4SxWGMSRr+MzhXjzaQAC6gTOldq96m6okTxb9lXHO+NwQbIaLA0bsF4foUiKGnQ/dfMChoa1U70BmsfA3RSoViwB42K1OzfhN99yQULiXNCcxFOF4UjW4Yr0R2XQRJIICnLJ8qiJYsy4ndmaCsbCoVCMKRjLs6/LyXOQgJ8/+g09tehKBDTzwQC5T5RYXMbzG4sV+eiUSgTwxLHXUr0peBmJutMSPbia3FyyfUpG+LhiNxupsiDJeE3YcrADO+BsTxJLyrzo7KVYESS8bAPdTSBbR2q4a7D88IKjGHsJvBOWOLCY5MSvHgZWZsCD6+UrM1z3+qDnpAPLoWnylZQYIagg91SQjwlJEzKw6hU2GGZjg/66H91sKbemObK+x483zj49tg77egvob1H2Y23ARt77WZE2c3uqw6XREzUZjTdy79ZhDQHwS8Ikg+vxyCwFErnbs15eSKmca6ppD9SwLH7WtRycTD5rm6KQydkxFVCTvzHaspdPePo1izq9QzAFtxZlAvlowtMPiClZG3d39Y4imZl8Hfb8GY6CUlWlRthEqvXcWjx6Oi+1XhUQ2T51ZdULmLnudUHirX1JPchj8XFc/Go8fN8Ouftka1bZEyplHz37pEJKC48bLPda5kck633g6JwfEc7raQ13/xHPi3ahlAy5HHsQkjNCSkfS6FOpzx/xlcrGaduvjcV6y0qE8AIsYJi8DeGEXbpvwOptX8z8eK03inK9k2l42wM7TSznuGZfLzPw6FDLWS1nvYYTyftS0fYLkumVv2PyLHFEY5qJoqPoGP3iY3iqJnyhDK72xPMTjY++ngjc9VGumgt1TOVinBBmAXcyfAcm7vK/8AdX73FJYUW4sK5DYVMlivuchG9dpmCkzgQNQRlTpleHoXVV3x+EWpB90RjvK2eab6WqbYUKgKpmWu22gwQaFAT5Jsz1uQ7x/4hcYL/o/3Y7w/yx8SrSBB7kznvWJ97hIh1ySdm4qNTNWGn/fYpbxPPPrV5Y3Et4Hu7/54zy/7daB0CmMmhQSmbuc/MZ0pnX3MNRPtPl1zNfTsKVVqfQ9SD74kbFINA+CE0Uq4026iqqSueFkqr6HUlOT64zdnLyUZBPg7xviQWxUuu6bOEJ4KZ79rwa57oXUWXhxU9uOGGxd+L1JVQKScdO86K43iUREsbwH/Ng4/ws5fhL3c6NdHuce0Ky61tA3xvTwgH0Ddf0X/F2Y0jNZzCGMcxlQi/d4reWqK/oksr+rSH36zDly0gfxvk5bY7ocj5UzasVuz2Mv0dPciKp339Zh+WGNSv9X8znkxoPMihy3tjlY7FzWfDAJ22ofyZnpKZTwOHAi46pr92r55rhhskFVrewj0PlbbWXxsgVaVjz2At5p8OSe66WCsA4opLRoD4L9Aj5VfJv8h5ZdvnlPBMoTsCctkczhVEPr5ce135ywRrpBJdYHJXlE3GuS7PkX///hkwJoNgA/TEoKqvrg6MnXSOWWns+91bXLfjvRNHGlnNjYN6Twr6DBtWYY5Jo+tyGt3OZeXTXbsH1Qnrdnz3IEhhIjvYEZsTBPySndDYo3xSjHD3Y4YVRXFYzwyMfvKEfblycQgAa7EoCFUQ/QJ7mU/G5IrI+78fakiJIGHER2MCEsbQqOE/dzaz/xvBiO2Rxke/BLM9zJR5XKmTKvMCb085qisJVT7KKvo2DMDGFRp02sCWUEH901XFhKIytxtN1CTxS58dRM5wUE3IpANoHv3VoPk5hXoooHq0YixgPcWcenHmInkaxmgrOPFXjTm0fc0AOOB6r2t63+3yJNUeVcqZkSOOLXGrNdis+o6TEU8sR3yhtmf0Wclvkd1+bNd8NKSlM2QvasZSqsRKJKfJNvAkOeMbFMU4C/eB4z9Bk2KPMoc+FiIX4tHoIxWQZmWuQoJ0MkLrbSxxPT1WWW0/3X2FQbcBVotu9NIf+e7jcl3xT/32lWJtUulxzSHJQtLUK2xbSTTr7RHGTL3eeTXxgbdcyHOLc2qACFMw0jqCs5oWnMBVoWM10j7HKL5RWeWgF9OLPH2yb36DS1/X7cYGe8RL6qoEH46L1xUCCJJx+gy9hRDEfLKEJRNvNkPWnYqQmSG0YhWhImI3ZcjeVCtrp6qFHfoETxWZX6x/uLFL+M6xc5oH4Le+HhSoDL1+MJB8va6DfT18twKopH9r0J3vY3lfB2a3bVJAcXtdMp8clt5iWfPjKexbmzJK+6Ok/5s069/TTGc7WZjs4a7I9/KjkT12k8/POzFRhBLTY7q3Fk6SsO/347seDqrlnvSu+nKzQJfNFS3u/jLGwuiKuMrjXrBo3MQgP4SYeRR4F37NlEcywumrj3y5UfVQNTlxovB92XKHbGWG8AK73Ww3eh2WsVmYZXFVXyObAf5sd6IRdYQN727Xn6cxN5hA39LR44JVRB+BAYMoNj5rgXicNWTPc3m5yBVqoB3CK/fQ1ezXzMFAX5B/TmBZjbc2sJp+JC8uL0BTJFpCSUQxkpIOcfnLGT8asmXzBN47VS9mNHBDakQyRNkrx7TKYA/RKgStQeV3GNTc+sm+IkPOPGlvlGSF0LbmztxNyiXYCgvMgqjt9h8rgn56A2NIjhsMID9tbmljR2MODrsrVOBKVtU1Eebx0lix8nxxiqVUkUhjK6kY2t/dXDLgMCgKYDrogxkoXr1VkbZQSRpkblFyL7+cUBkvZ3j5lexTJKVsKl788hI16E8dFA2xkA99DbsiT30FoJGBYmRZjdsOLXX/WFBHRf54EzDfAfpM5GaTB/cWEWOUFTMfV1xplQDA3eG+LKSiWlf6/7FnpGTkmPOOt0VPO0BsRBvdUqPhn7HUv8jmMbjPJIXfHnEm8oUcgOwYERLCSlQo7Tpw2zMFJ2R3NG3BbeBymz1qgWD3saM9rlTtXsfLXku65QYgLqUvhmSUGzRvt9yrTERTx14vTNwSAKUm8o9eyo2UMusMbYCxEYGTgnobiOAfRA57811JPkqkWETLD50XpX7wNhnzygGVRr5vNtru49YO+a2tTKNwYj5OWsOSUfNVUPoX/tVkCfussSGuSy8sKoIRHQY9OoIYOM9qVWqMrrnrlDhCK5eJrj50crCV8uyJbzkskMJot0YEB+t++Z7SH/OcLStv4QVPiEG2jXEJ7i8w7CBaS3QDAVOYbmCiaG/9ye+t0k8dOS1gZCT5FKRtDqLEOO0H6o/lqwxksuko0+zBnpvojxvm9tIF/H83pTbRuKmX4lysEptX/laV8s/RjEDtN0+U/RH6KUFzQcKbYWaWQneNhHi3o+0FZlbzrR4sTmJbQV0KXwxJKDUIn21JuxuPJnfcX2i8zQfMMxmIwAkU9sR3ZTnMRFJb9bDXf2YAOjNQwhAXcFJiuHONcQovprurKf6xB9C4dcNfPLCcEq6hdZ8ZXwMyeyL+tEnc0JPCesek0B7QNwf1PODjOnSrtCpTTnJf8V1fr8ZGWUrjf+L9iEE2DiMCV6F80bTNpzTiSUh8bVO0vA1gSpKESOhD7itttQ0jHqjzwoX5+VxtcNAFOXkzf2fkFGrzY6RuHi/HIXM2evhKxxVCv7wfnFqgpKbkxNaN8uGIR9V2iKoz+2hZ9YYi2PE6nZEERXVzLrMj+HIuLpTXkHx6lpoyZ6LHV8uolK0bxUYeyNB6ibO9FDcR6/X3wmxvmwXK86YBVdzeLmAU8P4Y45aN/Uy5uBTE/ris8Au8qdEjJ1VAIyJFWHKv/zvr/zifj16tOm2VWzCac90r/hdnCgKmTXTcHuypZaI7FJpVBiwwarVuwl3qGrIyLMkS+ES+ilDncexvpc2LzlfjIdMNbU4frAEykismLLM41ZJz0HmXMU7lLmjK5SVBJdBG3ncUnBXluHAQkIpp9CktOg/xq7xqZKnK0qk63WVZftrrkrs3iH1AQuwZHX+MOLOYTRsMAIA9FJJoQ9JySAUFblOHk9ggYC0fGVo+4m0iLz2PRg87WdPjp+xczU1r2G0zWrbW9QObGkVAYNA3DbERpae4W6m9K6Q8N6KmxYF4HZ72Y1VAip5esACgxlxwEf98wJyqrePrzxTtqu4Qs+pPJaP6GvsBp2wobSFYMtuKF9Xnq4/rYkRkEaWT+FiwTajtFATpPqfDBny321ljey0/92ppASwplvUHOLv6XtXno5n+9Vhl+Xmj3Fwp2UuJsQBml5rVEtPVgMMU06x94rMclv5iCDtTWV4IlAFrq1uOgqSy/+jA5Qa6aVFgnFDKLfYkCGp/vP1RjL1k+M4kAHVZ+mLIghbdbzvHoqZORmOLvlvIjhFh7xQ9AqkPEdMNdyBZ9N4XpShc0oBTBDEfIDSWOpzBiXHGIKDz1VBBYzqxRYMuQXnTEkYTo0r+qoLeFFY8DI3by4xoxauwuOQE5ww9RlPbUpby4Ki87EfKy1Ye/xXgjbrecE+BlMYXoPn8CxunFt22qEwVZWKrznOpkOY/qQv96L76wp+uz1l4mW/hI2PcYsDeKB21nYL1aWF5usfRFd3Q/lJd+5cfajXTi1yg6wZWIBQ3jO2/d/rL86rn3qFB7Bf/shNWuWCR2cYFjkAcUsx0exkxFXmknKZRgW4D0q0kk3V+lIhGWKsaUxRI7g3S/fxzEuSKzn/+Wke/nHRpkG0LmbFiES1/jRghvJy6cr9fPEAkB/AIfh71s4k4w5287VrvC3cfIviPUUH7b2VaVHxugO0F1K8DO5u7AqX/j+3PuQiWSR6yPdOO9xyDbANUhsRLEgO5Ku2eUhnnKTKcXbRxSmY/yDxF1Wz5+8lHllwxq7t1qHlw5bjQP+CHnsf+wj7cHLG5EQwALvYfm34LzcmZZKmg5nA+z8prnzZ3Zl1bEiS+RzC5k+SH/KpyhQJlYJHQ5aSrN+YGVDC/ZnD1z1P9rF2jlqd+FSu1pU7MVTEo09vH8pnunGV8MZ5A2gUbykUOyRaoiXoyGq1hkj15Xjvl05QQcBUeLMgUXPXwHeupD8D+GoggSwMNgYdCX6mh9HdaxqsGlQANSHlTXIsfOb1Nn/W2psiWViY2307YaLHRrU2+CgjVuhqdU+ZW+N4LSgsQfXTWqoJN/FMvrfK9EoG830EqVSlSZDbywBaQNTdHGWo+gaGmgnLOiagfIGGESLukipeKgUUunUtwE7CgqUOGTuqMsOp5GBXWqLbQP2Qbt4Smi2bAwkNkFw6zj5E2rem+rj/T6tjK5N4wStmYLYvZXh3GmWCqmNoUkMQgp96qlaGadTCHEY3TpCNWYlpSBQ8USUFfSRXCGai+JrVeZYg2fax762GrYeZPPf1yrpe+9tLlVSSSU3/k/3VWQHZVGayE62XFrDBa0teE9ndTS2jnHVl0CsWJop/xyIkeATPsTW/ry3/0uXgXr/8dO+wU0cEa0F86yiV/J0QjcTZVqTmXdPKw6bVVI0EAnrAXMNM8lV3o6t/krn8gn9c/GIL+LEb1YUb0NYcR8V6qeXApjC+yuVfbWN1ArSPNJ97Kva/Luu9Ti47bmF1f6FSfUVbRL3IM0CIUR1ry2aBDDLQ/FqIf8BKMHWM9k85q6CJ26k7E0NRi4m315/cVWh66UVYLQZcpAg0i9xfj4fxWWLz8+tfb3qXg2aD5tAn13/lkQVXQcL0QrUC/BmdV5+phNR3uq5H3w0cZ9QXlNEOZoWczn6eC36UPqPtu7/vSmYa7F/wCVxHQDom9OFsW7QSUXB2UvAoQ7/FoZkYw9vG/Mx2g3aG9IyQlChSJWXDp2RpE9zGkV/cPU4Pj1J9b5he3DMwcUzwiFtB1VX4q67OyfP4L1uDlmdyt/r0q8CAC9CC8V38X3QXtwGqvRul50xWkKIWGpFwcJt5mCarX7cTL5B04cWGMpvS3AmlDYItAY87moV0doHuSoW+AsO3MmTIGGK95M+TreU09phk0bZ3hIGCvu2FTGP93PcPqvyJdyxnssQpjrFj76oqklQC7rH40bAQj/dsWUviUicSaNSf3fKcKMIfyM8Tds2nEmpDl4fwFT0C4755Fx75ymzZBydsBm++BVvjksSV1SXRoGqdX7dQZqu+83l37x43I+wH6JXS1wp71scuieF8eCzXQnBA2vZM/pr4QyasntrHO1ZX1IPPaHj7JJyxhRiNmR/dkkGQFNUniBQN3FRmCQ+xSvFRIUtWok42yim4SJWzMl/bizuNCAMn2+YffNXW4vzcC8PCRHaaOYXe1tcjUQSBDM3rwFDTPbYLV+Kf7OTW+pXe0ViVPmwfngUGAysvDxiyZMA5uu5dI7lcuc0GfW7YWty8vvLhfXXnTBNXrKl0At1V9VF6vRb9FhrX+KdgGe+jg9jmZBwFN5Bm3olysOFXWHlCOjH7+L5paO8M8Giv//xNC+M+a/e2QpKdzq0mLZZc8DZN//vKjnv3eIMB/X/9NtKf0Gm0txBMijIBl+AbTusIglFHiKwRfQJANbzTnYId5E+qyacJr/eI8eWOMDuZDY+CcPPDNh41O4fSPVCr92bx6DXsi2+ldWapWvcKMbyddQXSO7yWgDwC7LH4QBgD9teWjbfFwxbLNC/4jhZgI2SONpdn69Ouf+Ej1qK1xVeGFoLriwtvZ4J3R+WdecCz2IHpCw4PYmAlPMahVpgqMfkB1h4JflpTueuNpHsmAUwkl7Z6EbQoHQYRvr2YN6ct1XRX7MRukXGDUZHXTNdndPBIvpZsie9241ex+NSh+ZXoVxOBdc5OquViJKkF8QoowDnh8Mpr8bDsUvpO6qqf6Ug4QZJu0JXNa6nta80hEHE0sSfknBKx5wFU2dhGZL1KMoT8xSEeuwyCf3vsoTmq4SW5TVnOXi1GakxcVW5fzQgW5at+Stu36KUCNUMXMYrd0AoBkRQaOydqsuL8jeKdwJLLAbYlk2gLBBpsg3wRNdFGDgC/xfSSi0+n1lrdV0DPgk5X6S2H0sV9i/jWPFozE5kuDomu0hWjzovZ6mZWl4hhPRzCSSuMpFJmKYSyt7TyKnwUG7FBggktMUc2k9uzbtooeSt6ZqT8+vXnBV+Fw+1+k7l0/kyLlf31TOCkEFeZcGqb1FTda8dFJdXQAe55yLBqJpkp7YS/QQqBkvs76ary+JGnaZ+tS+0N+6f1qkyggdJ7oPJ9JPpC8yxtWBxe8PeRzlQ7Sp4wl15w/zFQ16a7dgO+hZY13bZ02DBWoRBY/3UZ/bm+7VMZ9ok51I3fC87uzG6gP30/D3Dd6idZJH3RTlbEHEtSNbjUAAQ/zNE8HsLRODwYyynUfLiGZ5XVh41/VuXjhsxCgxzQF2MBqooZZ8kXHVR7WeTvy9nZM1DlHYBXOE6gXYBMEchfdy+Vl4Yu44s3bBYk+mhQoU3tvJJDcoTkOw2mQsY71wkJ2HQiPasIZJBEd4Iger+JwBSHS7BxANWIEIilMucEtOkmh2+Fau8uWYWFkSdvQtox0GpOLL4pkmpA9LQ6GbY5QDffg5TKJyhdAnN0ZHW3zio1hbDlGw90ooq4lwJTcfRxAC+esPQXNP9s9VCAZ8VZz1Fa5zi8/7bSQv9+CFrCm345NITQvWfHpnTkB5Y/K3nFeO0rNJNnzyiZKxURWuHDIH2t0LrRVYACROzl4XLIkk/tXHjxYSxYBeoyqP8bGlhj/5iaEN6N3IGtfgcuLoLD8rDp4WZDWAwQGaRIYWGeb9gpYQ/KkQF3u37eH2cwiaOlJYE+bJbDT/8E+n3ubfLJyZW22gSu/Ya0USeYqgaatMm19B2rgvTeXe/zCV/N/7t7yc6545ROhbf/drSo3EiKhBuXGPlt1yZc8HuMTAEJ+0t8k9i1hVBj+SCB/TJ9JFf93ephQqXv4cFM1ADO3GRVGZtRDddv3zCxsCCJnsWKJi/nRBnU4QE6/w3vzarr2MuTOCq0CNh5xkRqT3ZzED+8RSev3r7xp5JNzK5kpF291Ksbgwvw+QprvyVF+e+lAox/9Fj/Jl+qhqEC6ZIF4qpAMuXgtekhYCVdiJJM9sM8hI+AgVLkO5J+fijJ+FH4vT2m4gpHzjK4eXWKd/fZiF1ABqXvsfjg/Ju/mnVgqkeLs/rSP6Y+6rTjKYkEV+/A3elHW86zwft0maw06xc7nJo6r9sFGszVE4GmYBNwN0QUDjKO0tIRmTuei1HZuoXEYmzMBTvTls3JLQoOXiAflm1mR29dfZq9c/NoIPc1pFk/VzSXULTuHfiBa+yM4lAnlMT+exWyP5LzhksK2x43OFwnmrgCWx5ZBkXF8eJHjZLAbw6VIwQ/44n1fGUYVjAi/O5uWvzsoPxSw8msnFVgLrW+cNsNY0HDG4aPrnY9ix//1/p+SPhPHav+yR1FRbOqe9dIIdRSiAhPsYNdc4FKYkhoA3qYqNFvQn2MWVPUxpz3efFG86Q+aUKYVbmq1s7iDnJ/S1pVjqksEyWZaCBsOIMW8wmxu7zAsWqJj+TFORxu3/pKR+o7np9w6TiXTk9/NXz6nkdVW/aPzPOCzIcVGIQ/5yt+0J2WqNDb+5Em12kQ/VgiIVY/6aHfzFv+owa2cZaG1zFqQmHBHwnPZL1SZ/yirv5rJD74O5QhuJWy1TNzcrRDC8pGjzW6CDAiNxpBLny/l3Mi8rv/jUAN30YUIaa44q61Wd+2kJKKPXnnabP2RNyF9UeizS9eYTa7bhiYR/fSW0zvuVfS+De2Lwm91fABs4qk8gh9GC2m/ar3TK6SEDLwnjcy4AtMCpEf5JOBMyVFraYhRIbXRjqkfieAgZvxgB9ALvJTFdlvE5a2Ic8CxWHaYXcIqrxAuESrcV1Mgh6Q/UOe+JKQMy1d4sEEVfMvW1Zz6dy9f45JpaRxmbkKm2fSJiIlpODEpftgvxoCVPCVIL2ja076axvDEoHh4EFPci9yM8caVBpk+TEelN5ueVaMPG/EJ8YF31NOyJyWB14g3mT5Xo78zopaUmXf2UbLGXtHxNCQoF5r9/J9eUw9L+6a1QZOJPHKQEzvxVcjEX4YS0e+8deUNmnjWjw3p7zXNhc9iXY2P3yH/74Gez3QWf7WxOBBLStY0Iv5Y+MZRV/TunVlKubSIUXC5UiJs17J3fzeUgak6aPQK2UwdtPPAPT0sgRKV/u8tsfT8ZhvCPBDYJ6xzVm94MLT1opAhPz50884wTwzcw/tgUESx+sqS9vM5s2Hr4der9Sn81SmzXHTWbMg2n5pKuK8kzA6fcre8oK8s1I9oBb8Vevu/7hoX0h2iuDYYEIgPsyvdwl7bxPwN3BRKXPZxKVURHlypOD3PsV1lhYy+nz8kXqo6qONpZNzPF7yetNcU4nGbj7DKMFFAxPyt/7HcSrtiZR/Kf6m+EvQB0/q14MAT/Ni2O62vYBKOTmpHXtcPVgPnLxBJesNen6kLmF79v5g8Sz7YU33DLX62Bo9j4KjqiA3y5ngu2jARWqwNaDOa8QH3ntnhQVuxrsOISZzB/B40398Ke0l7hR+iMsh5+i6pPqv8LECwtg0VX1jKh9VVATeMY5+jQ3YIqFpiaw3/0+cnnTNXc9vcP72Xl8ycRQlnJZ/cckSvN2U1av68ncm6DFumlU6VsC5OwyuuM0CojrHaqWFB0rZF5fNNVg85FRouKheJxhuKEMlLgA5P1p0FbLEU7EjnX1fzpBK989lDLUEqEJ104gKKhkt9M7swq68Il5T5+LWEmWDyFQcP83CGP22MZ8fw9y4UM+8yVZ8G/CR1KRyXDYUM+vtL2uDvvOr38qn3Yhmz/lG5927sY2Bdjt2vrpwbSnUh7ZLr93jCYeGGxlkT9Zhfzv47PebDLBwjq0jYsXP1psudp6p4zmRX8YCx+ccqP372TqGRudSgH/oQMxjMZicJWX/tZcAVhTF8Nu7JJbMhKLfilgJ7kaPVJg7iVcjX5ltqz2K4ILUIhyUmYyWyOvRixSFlYmcr1o9FEiMvcpiZQHElV2G45FJPcO3YhS3WxD1Y9/Y9An7Dcd51LeglZF9Vs0/Ipxg6KL/99xBr2+nj9v/npk2C76sCOZn+ov/25QZzbptM0F6HPMVy6UDS3xqhSzPY23UDQ6PoMyfngUBI86IBJqqiprEgH5EsBCgcr71AvAmhuUdVi+F6ji2qY/k1zxCpYUvpUJHRDbLVNBJxqDVD3LWFshXSTwoPCaQrAuY/zNt6qfE+5DXDBpaLNoZS94d4q3o5Gr54e/F8kfsY2SfTzAC6KSYq0JAV7a9PZs7YK4usYU6komIiTLkYWoQwDQs5PB9ZfUXJqnY9g9XNABK5fytin73m3Jte60rJYKNAHA5qkG2zDLVj7mY1VgnoMS4Q0dIHx3yoPDFgc40iN8FGUFWX+kXoJuz1IOG722zskC2mMd1MjdH01pRjJEZNccyLxnuIp+/ZfTsU6jPynVLQin4zbSrbKpXxMHP9nhJnNITNsu0D1URUHWl+WmqOFH3OawQMb5qdvMh8Y64/3N9Fctb/oQaLapZmM5iJ07iagr6n7PfaajxHwYpeBUsXgWG8yuJ6fD7S0l0GfHeUZmjLpgTiOiU/+Udr70nBXLPMqAJuIHlyheNcjHGff0WAGhCysrL8erM+KSf+p8D4svQ7Rlwr//A7Aro4FHelWbTkZ7vkLDEswXgd30lOStL9wHuJ0Z1bqiTdHmEUxwk5zOB/a4i7gWpJMBIRRVMSmqotX6NudOd9Xh8pR1p6FN+yWBszOmth1QDXaPq5FWcHSpftPCyxcgUuwmH/yJIUd1+W15GemWpDdXDEZHf7yJkekw8EgYH+4xUjFgXtcOnEDbcN2qVYwQyGek6GOWGFr6ALBxvJwH2Bz6xn9BBFqFWSPADv5Zc0qZeIFVWQD2pazvSAUyZPPP/xLTgfAtq2YIiQxGTa4Ke46cgmPqYjaef8yWn6KL1IaP32jyZVwJCzI7sUFXy7dJWZy7j1U2rAceB+TNGXHPr5Fqzx/mfWo/gOs4NHZVUT7ACIRrWBuhuIhc4Ttxn/IjkFO62v3T5f7Aw6Q5ywnxVSaVXWarjTcHpswEgZczG1SE1eTELIb1ppAM9CTX/h7WYfBaD8VyfXkcdjwN60JDSvUIBAZtkk8+6kncGovXImpivn6nF8fZIw8xnEO03lqCoz144neopUwhSQp8OPftWG0UMrf5zRfR/Ux4SuUQ/9nL6jp43uv5RDvD/2P1/zDtADWIDLxTLHfZDLdcI2MXzRLk3T8uYB2BhPQAo2lT2TZtFCVh2+z6irbr69xwPsZnDY9KAM+2aDvr+Kb373I/HEYFqksGLwZR3qoGdJH7SsnU/p/EstoaPuinsGYJ0Wblt7kdi9GJpZyhbco79jF3zr/i/fq34CzwAqFR1hqa2WjXwOxkpwCGNisxnKxPUQWXI1Y+C3JRWF/A83DYjrIUWbBzIDMJpUA3ZvuJo9VpHwJrJy90ZSGvYEko3DT6jCi2H2W2AOG1tX6lbjZEkOkOtRNJj9kb9rbcPohPu5NReCFk3p+55zJquWxQmgoIHT60nGiJKc9ErDRS6FOIBEg60VvrZgT/QspcDlDgow/tlEN0kXl+5pmg79SgFQo8a2CfNibwg8GWH+dveZ3HET36ndkjRfd3SPvAta+/YWXTSdHl8Gu5FyOYrxaLLPQHK5XPYdi2olJME2nAQ3DmSQrZDSTBrgm5aSV+jMcuHy555NygdcNlJxwaMEoHo1VqQhGjIGsvPaRlNhOtFf0vjbberUqtzNuiWJkFFfu/l+HJoMwB63sXrRz7+nXR0RApcNA2pcm86WSFY7H+aJi2AoUwD5TAIpofOj9gzhWgRDefdI08afKkOX1yxTB/iW9eJ6b/aG+8Ufk6YAfdJEyRwpSAXisB9ZAplCy4+pmNYP7Sl/luAWUpViwQO78Heccbaaz45Yefq7VvENBMMKieprb8NEqYDpbxkWezrrcGTNvVbl1b6oUIqlbx1L8+2NpGEvl62NAdNImxQAmQsP8ijBYad2yUM9PvCFaVjyRV5cz01IpB/YWPtt5AFB8zZZ35Mz9jD1V7muOXKxfV659470OxtC+QtE1dcszU1XwOIB4f+sfj4I3P0v8TG7KBH9fjAjK6KirAvOj/qQJLVLXzuT2L94T/2xU4btBe4yCIkrkAfEK1xh0c0h1tRKPML9l+ddOJuDIgUn56zM/2FoaEIdBf9RMXL2s0huCP6KJL6DLeuEtHmpTOiFNoeeYOS+ycT+4PYkKm1uueiVqAZxrkALNJ5Axsn6C1k2cp0daDGN08g9M6L6WfWVPwQOv1oo/Y2kya89CZn8XuK4fen6OfdZZrf3Ubv3WLy77pDZwShd0cbRFlpVmW8kks+pyrR3F6PmnwNdwNVZsxMeRq4QuwYiG9RRBLlcIzhr9uFcjBGbMMF+mAgmUAKs0XzNxGx3ttt07CbuxdqRaGrDY/yFXOGKuxwa4rCv8XVNL2M0ypqZOQfpPf4HW8C+KsTgbL3DMvqhmi1nS02Hgzq4NssWwBXG98ITjzcn4Phao4FBM7WBQM7IHCPHsvIydJyP4IOFWvz6xSx3yXFFwEJvF+xC+acWI2ktH4O8tKmwBhiyUIpkoXGmGfJ/Mu3+b7g/n4OcD30FKKCvrnPFoucDMnRtNkBfU7C2ZdsdKhswyleWAtCYvQjNfvCb/In6CRJm8nuEIDCrr0QOnDz2yMwHGnHIxPL0j13IoNVfAbqoZA3pfZQplHwD50CzzrPlpd78bxYwFNhXjRphI0o4aGH5yDgLCWuic59ebaJzlY6+V/7V3tohmy9M/oQnCt7O6pp6zK674CFqYKjsc6P9jtFKhbAW3ENR0e/8Tn2nJB/QsH6DAR4EnG6SFyZQutheC6grTzMWZS/4coXnQyNNyvKmGo83mz5x2A4MG966OVeZIU4jK+n4wN0xKbQtR/5DK6i90vnlUNesGYzceXnG6DX96lfTNNeo6MxzYOMPP0dZKe0Hhw3MFayHofsmtsv9vG2BuYxHITiYA7sEwC37XTEKvdnhPLzbRyhfuRyCQVi7I3upxEzA7dUeIKPGaEuQRFgzKdK12fEAo6D0k8ofPw6nQR07v+3d2IIeXZ5JtscrL81005rKO/5P0+2qWlBK4y/aPz1C62r7GTqUemlqkjzZRwSmZk8WthZ3GzGIBNc0zPmhbFk0lKALgvoAoVzocc7YzBmc6raF6uhO0SSnkDLfOdI68NyLTZbxKwZt5DPAf5WfO10NWYqvOf+683dvRPy5AfevqDVTUzWpaQCTNMoNrapSuCptvxMJFn8oKScsi6EMDQabk9jhJDYQXQe2iGn8DUpWhHC7m7lBgJe345C8U/X3VBsAknk7wkLL4QFfO1I8aRY2asuptaoYMQbd6ySAecFbE8L/admQNuz40Wwhhy8jJXu1BGMhcP753uyDTVccyZqoFv+/BYyyHxC8x21AdWTSq5EVdHYtubFHbRQk/1g9UOmiTVO+L8PdQYZZXpOJ9qA5T+2h7hsS4x07iv9rovC5iYLVd4ECYqN4bt61E6sv8It851+8PtTTa+Ff2wGb1JeOls50FDdjvxq7SPTC+KGevgtydbndKrlmZ3ZbdgbvlB3bx48+GuIPlRy/CvNresD3vMWNzV+aFvs/GWP74XIJb9Ki32DrJlHR1yeCmXqN8jT/U2+FNzsgkIKlNYJQt3ySLSbO0CX5/nl0OrtSFHyxXcedsea7eU1DU61kR175AvSJcV1BBLtAIHoJpGX9Ar7iybSdA7V7czmxYS4aihriT4kl7FCvc9p7qjAR9lJ08MAP2u401XhVawYQckV8WvgGirJwDM4V2XZZ74smdOdOlT07ixmLbwn4H4n3SDQqMn4VQ93y30NZJly99zeguUlTRGo2/OM1dfLiGXex8IalKkTp7K+Y11mw5bleJUazU/rWqEj9oW6oUQZH/tn3U5MXAYyx/MFXda39Saq3H8PP/6IlnqSFao4qjH650GXALVuWA4M18L0Wzivt9CiFk6L+QD/b3WoK+wuIE7V9JEWxA3/UauIMNMymK3CiRkxpHhDYWJO2NuivlKFX//LxySQE+9jpMTbY1+GP6hM97svDwq0N5p7FanDKWGLJHytRQN8OX18DZF/YnRBySn6sRmxTvj1cu2ki6ZsXwC5dRzfLQ7gWWY6HuHtg4AUIOM/nSyqAvbzf2jtSNGV9IUrAFNBs37K0UsVe7G6gOTd1j0G3e+7FSSF5dxGvdemTNPclWe/2mhQT/Mnsf9FzAJbN05jb2w0DzL/qRQsCtM110cbOcN3124qpNfUB2ecfeFPgx3hFjMb0gFFAh10FVUAhskX7bA+yrhY428/uhF0Oba87tVf9bO58vRjuWnB/IbEdA3MUohaK46YP9zm4BsiY8PWT9Y/ZN4jWp+/fOTABxA12gvQG/TMBtCkkurisqG7v+tkCDlNsDLpOdtmvIGprL2sMMbZM89BFHfT3igxcF/G6D4vpD7nAGmY0iNGjt6blA1r6ijw7wAgideIv6sU3z7HYFfFmz1z9kpjl6Kvqnint6ADDUnf65Ed+t+QXC9fMyleomVWkOQ7VTJuJoNMajEymMnNQrYKO/nxg8vHyZrvxVDVwMfUlRS4KFMbB/AZMWSPEguRc5aChTPi4HL1EC/+c1rauA+BRBxGaHdRRnfZRY2uTGkp8X3/i0LbG93YbYl5BZVCaZVmfdfJbB3HdIODG9QS8KUzDQoY7tu9rUeEYwiGEDz+/SJ65+dSo2ojcHVFY4u9YTpYMDf7nQcvGslvok6nDW/aCHWI9NTmOC31A0YftNuTDI32qz7/lEqU7Sonql1vGbXJmeBMNhbW8J5W7ABUFHbl+NLnrxLy5WqT6uK3p6eGgL0z9tEiKVrq7nr0EqE6DWTrkXEjDtqrGAiT+w+RLd7l8q723pC7qkHaxt8H/7HTasksJVOOmy7gbLSeo7PZ6aaT5qSYtcoVK9u1TI+InFaCvwHYlvvbYpPu0PTsZGlEMPaJ5KrgjPoopVHmckVvBRIRHCZxPDAuzKKrdgjeAaQwOt9Hd6fgYX0KBhk9r/378Ej7Ht4urVM9ZIXj6FdMGv7wUThEV841PBvVGSw7CcvA8KfoW8jjCmvK+bHLa/WK+oJ/xFfAbewoEjd0FvEbSEeBNqXeLyvLQ8JYlwRvUyt+d6Gu9MmsajkblnKPfQuFtUqkgmB1mkiAGQfK6AfLjrsh39RnmwCr4jxa5NKaUS7MfXZaQEg3SwidRX8Qy25Q0JZeNHm1VHlhVQY1dzOq+10Q91BYmIdtGLgR6+hm/x087jMWui1ZDoFDeUjVOLy44YsX3F3qw5agga2N4JwwbOvzrAcst0/PoJTzklnjbBa7nd5U4ELxTLxRv0UjBodBX8mncrTUveFHocsPlyi5glYyuK9Uzp6cH4vVVDa0BU3sNv51TqyFvXrC4+r/UmHzpuFcm8eB3vT/7Zfj5o31Sj5c+ez/+NofpjxsONDK/NxqlVsEPn5umUxLYs3Je1RdNVjkmyrjvZBcZLljue3chOW73zb7GXjLDZ+cOtfb6AQmS6vaOQPNbuic18hpUvAh4G/bNu0rO4QM/Xrx0bEsVBkW7I+qLkhucGcz1FyO0UdRL01vCR0kEd+kxLkXPd04VsO8cJI/eERt9IOa4t+DLcf9cxwzXvR4jj81PH3bpMwrALx1mZVNViLUzQidtD3jPpIWWfLyo0GPn+GjSDFsB8SJF1vwP8ayfxCj2h+OE2LB7K7PWvM02SL6vij0lTCe3lYSvN+WqRe//RJiLSWhqYt6BFqpU0hCQ3vTSfrm/TpKjH7dV/uqqoGEoCX/QhoB4TVSFdBx73KyaiaCTMA65bzhW9ZSb81FkC+EqXvfc4/NDQYZjOWVcYXm3qXOQ19cz0RsyiELUmGNfBhhdlZak8yivUY13tOlJ7p+r5qbMiNBXMRd//lBy6BlO1snIOLtKVUIlJSWRb2oeOPafueqI26jc79a/sAY0Lrw/dubzj0RkTUwR+m2Oxk9EpVhcqCFJz1IISiWQqCkB830CFUSq7+B+vZJA+zEipdXdCFhjfN2br9enSFysgpkxSFKHtPEuzb8qaH5W5wtylzTQCjC9CsLOR0LYx+0jdH+29vF/+zSR/1uDoc/ajbdJgD4lvnmqBjHEnP5jzM2V4FXngipzaPNYP9VSRQZCB5b3vPXf2ylyMPh/XkAffolYfhY3Pu6TWSBp5oTCrqCxYeUOwf91kkp8Y+fLDcpBQVxRgCYP0Ta0SSh5/oTK8bzIxAIW5NBSTMmhQatbmLeNV+kiIEUiCYeddLKUXy/XW8iBPjFpTPia7IpwNJkbq6WPlYmWK0Q+22rKBJKvVFnO1vcHARhpDZ/rF9qMUzgtu0XKAra4DtN0iN3P+J18bKVA+UyKKIAmysxVryRRVRm9nVDGSHUeOnCrHbb7/J2WPP+WG0o/ve16knI1KQXe/n4tftFr/jkimV34cQat/ioHG5+TnvgNBdXw4ZtCXJ0S/MooPp8envrOBqbmJwIlx1bpUCjbEVKrici8lFY+OjgoCaaD4uDYErgEjI8jgs+fMEvbwlgL/E2QRhKmqW8pB3CyfB+HOhz6z02P/70egXIxBtage6WlbDigrLHfrNekuZFoOzOwsrs/gaUaa0SuPJjAaeJNt0AhOAVeIFISEzLoabaUVm8gwqWDfk81YaH9t+GKdD/KpolSuoSl3KIpJoJwI6piZvHunUhN2amH5bs9xiG8jUHzf7WP3JeBIVE799pFjHRTqdBfzKaCDybBr1cuiCb4wMWQbWHIdTpepCZr51uJ9vVmYfGcQWPFCmlJdxF2xxCtATtodLPz5S9+HvBuuRqdFua5IrubAZMFCOwLNF5V/1KC+3JJyzMdQM9qR/jV4TTSFq4onwnUwA7IecDyUuoN9ucJg3+HeQhHh4XL2SJey1gVV1DPwGpg/tfi3pnPdYjEEgZtGHoo+q7/enAUBHWVjI4Hk0h4XJYlZdglSmSYvm5P23zrPbrCfEEzV7JwiUUSLMTxemHdAK/utPneXhs7XvLhpAHPyBhrZpOMaOe85t7SbOs5GSp6RsUwyOa3YveOTNrbpMDn5bCwI1VM3y8BSiRyEkxTZsbBmnwPl0VRdvXzPWk949DCmwcJaTzpigUr4UrgdOkkO140DUXAoq9d1mV4G1uUNvrhJz/MsQFRdmg9Xg8EBSbfOQ+7z/6M01Q0ZGfSWvND6p23HnX0KNm9mEZNEE94XlMWrVLeJ1Nmid4rTv42b17Aqk2Y64ALkcL9eZ3lHDkKzg7xipoJI/EkGVi0LHQO07IZMFUd/lnWbUZnKVtmKnlse0rGfkwIj6kE8QPPjDZtmu52uDjvVmn6LXOjYs3/+ApaLgsUo9TaoSg2eRBymwpQCPuIji0vWhAJslxnu4bbayX5jw3FsVY/J1YuCS/9Oij0Of7vD6Nue/7aDmBZRjfS5UvuZzOhrp7awh/r8MHLfCIetM6vWtuqnOOgVSdMUDq5DejRSIe1/ag7SkQSJPGXKvdwVP8newW2bianLyAbDU7+TfyfoAP90/+TOeJ9NANzOzzDWjZNRBQ3BYZMaSIIDIfL5LCiEoUtnYalsxBNylDTcFrukq+B84gWxIBpKK10KbH9CBbTWUio2fykcXdAnHU1cr70hthllvdRbLt8zG0b07qoYaKsGJ1iDSguNaGrYZTSQhb4chRYH2trU5NO/pTfGBwgOypPkBFnMVpc4Kqu/5k0Oq+Ecv9LWahU1WyAGguzhCGQO69O4b03zr/meXvBsCCYgFBvMx5DVl/2VFTaeg2Ut6YwldQNMjoN7hxCGZi1FlFrWmreEM7f4F/0lUKnqcWDbzA1fJsAKvo0rTmdRG/uzYR5RTKzQgahTTkoeaUyXkmK+PHmfyE48U6/yzdXFaEr9HyFWPbsV6ksDf/zlc126uVsTnQTt1SAQoyL5SEvyeg2QF7GUQbHMsiPAD1mBOCDduIj+jgSQRvxEpQ6iSvavL4axhRm/aAP9vstw76ldXDoaBNZ8YMO43i8GQNwRV8LGJT0njGcjqpSNCulSEpIz2PCV82coXkpSZJCDmWrobIl6E2jJkorOHZsOBQB9VC7FOLbbdRZ5wx5kzGjq3iYyGaHRo93FabOTJLRMTTEVhSu/p0q6+GWBP3BMRtZbgxdJM7tRX6DFPuuQlSt4jGXCH81CpSuVNXPiNvznywro9X7M8TBjfwDJBFnro1YIJRE6GkmUCbldJmW6wdX1z8IacX09F4a28gPXRklF/7D9ltJ16A1nzH77u9o1UNP5r61X/3IgoBXQXIExahS9G+UiG0UI7I2bgFLRdbsJolIkpdkqweebJ6bmNwUvf5uHmr56IBljv5QGMX20bGWdfMKFf2MpL0rR8gRm6znjEIJ5aTUSMry2Z6nkut5oJ1JD2KgE3RucZhe2GiZk8QyPDtsDocEj+9OD6d8h6TpEZpQ9tlQN55/v4wwPQ1akflV+TbTcOZ4NJf4eRuIkzV5UmHlmFQUeOtFoer7DErZW+gXA/E3hrCHz3NkF7HBBZBdYy6mHnuZKHbycYLAGRdgx0st4dDJekbtiCy3yiiMipH/UB/Y95sYweIwhOtvtvS/+40no3/diHtP0SEfJhgVgB62hWf+uQ2b/5qjt/aO/1tb/7hLDCbc9psXnyYNjYF5NL6kFrSRWCCqA0WCSF7rk4HW8hMisJ25lxF0ra81itOHvAJchyIO3HQOLt4cjqXO3atwJxOcEAVIp+uqpBIpjUjy7myBm9uy8xP4VaOnf4bpLt7evdbPygReItIY/TrB5RMbcUR3WX3oOm+KdtTqzbyPT38DR3Ehkl1NCKstMrt01G2Wtd7pnHZQv4kvJ8M2STOMbbcABakC/tMOPeaJlu4LDjqLTIGKKReg/FIxChQEq3IGsKwdOeITcu41err33tPUY1hFgiZ9rQ0pRrObwZ+2pPzHZpYus6wN+GnyTPfTX7wpmITSmPxm5u7r26bHEpsUnc969GWKGaevdggBAgCoLGYNYmgBELGqgrp5mp0DUjukV1Av15pTDd277a/4jfDGAMkILuUsanHqYh3TAsukZqpNxLXGDOuAl0gUE1wCTQA5/qZvjW9venqMbe+U1VN/CNyxf2zd8SxDsf9r5gUkhraYZLWcTUZ2XnNGNzEiN3W7ZJBdbnAbwPnA50OCjG8uBVAzIuwsKzg7afuiAao2Ry6hf7AGc4xoj1Ca/WmE9HsMf2ymGitlgjonlAjXzUTWRfdVBCtOPXfxeY42O8lnFnCmhH1YwGuDD+4d2wL2o9Tm3NFZsm3AFOnk7opTgzij0AD2uD5JtvBB8SydiffRRuwL4uDbDF5nHi9K9CI/4KTlIYUkTuISOQ5CcQpxv9SMLqJeuvOX+WY+HnuLddtiFfO3Cb1JWyS/7SfwVsnEg5IIkKCC16D2YfwTICtsQmX48i4qNWJGKNlFO7RCydOpZnmKHuJBVX5PoCNPHR+lZQkLOHaGCIB4k2G2r5pv/Je1IW09H6CWGVenj9C1mkUTRVKZ/oVZ12Tjr13RFb5LEgSJun9SPqoe5OEsT4p2R3yFwE0yE1MzuRhEWqynzFBBAmq0a5JL2Pla3yKXg3+h3/b2qZm/TegJbJUe3D+ivkWtJITQQRjxR5gI+JRinJYY5cK6kVlUbLCa0w7uj0+/FpIQV1AiPZAVlImspbcF2rLmwLSWvHupSKLcpP/rkoFOYvbsuDvSSYVGlmdShs1gSKgdCozmcmJICDF6IyJXBNhgoovUpHFbZSt2YytvQVJVe5E9NBkHgyxHHDjMCGl1WQG/HR0Gs8qZ2LOF0GFpT8pJSLCIxZtbiMIqEVwW8J612IOTsfGYMSWM8NI5DRovryM6m/nqFPd2LcsAwxeCrcj4AJZDMKGGlGBYYGVn0T15mDpB7ofRlllgx07mSX5eVzLoxcLeGilfX0nFP/3o4M1T/aBgzussI47jIIVys96CSRcc4a1TQRts0UKT9loBD321UcU847whRP7c6W+CzFavb42Eflf52E1xW6LBiDtpnetcUnxMxdBcUpWVKNgYDrrX2sOy//O6/qrrpJ8d13wmAcaiGv1wourCzcVZI87FsfSVD9IsDrOpGCOxZmzeedsZnqgUfaZzVF2BmHpSVovfhDwnmOQ1bX7LdSsf3oGG+IaVTx1UdYNwUdmi3JP9wHm3XFyIOFkJSicGy1eBhwJl4Ut6O8JXcyzYR/YotkgyZGrQ3PXVufDVJ362TPL6zR5kAFaCcEki9msbygcNP1BSEKzONFiNweRBedq1w+Cf83IkZsmreW1Huc27GE7kK45w7G3Ofq0vGvgtVGjc6RcYuVXAEkYxG/FYSPEDjyQWThAf3OoIHiCERcdkCuPJusA3a9SfNkiWcqTPXHr1Ni+Icf8+U2tI8MvHmeduN+b0WSMUzjnmeSholkb7tKUNvfaG+Y9N0DZVKH29Cr0swBbVSEQ1xzX2bJz7r79ikNb0s1edfvv1+IzbdskYzOVHJ6220ZtDYjCaXACb3h4ROKUNwuCI2stp6hDgJIbJPdyA1vI6QmXB/teQsEEIPPqVuEloRGZr9wAFdu0IluGj82b4cKhC4ijBV9R25risrpsdCmDZopYnaZF+RJA1g1wQ7crQ0Y4VjLG47mThdv3Ehv6ClxgivKHOyjzLC3eX7/va0j5AhXAIRxo5AL3j9eJGOxFP9HI4wNi4ZiImkKImuwNuYTVkbXX4ebTG89hLf+NfacravsmoPkfcAgkQ87j42rZX2Xf2JGeqgUkE+5ZzJ+dpRvt/8RkNrqKQV8nqKOYHCop7eMI8cXc8NhkQpCsH/xnGPdm/lu3p2XhGSXfURfLEkmGKT8nI9GtjVyjoawWtEZt/CGkG7u+8OFbcumcGYjUgfpqjVV+sTgcpfwqlsubZRdSrEtWkpg81U5iowQDjHF+U7rWhP0SKhAteUWdB0ErNi/gvi+VxlDnhfCKg1oX972lGUrWSJXy/b62N9ydSrgva9vhSAZjvzoZwBRniB/ApVCG0v0307I2e+2o43Vn728CFNx/9HjRhskm7RVEuaOJqAUuT22E+lm/yH1Bf13X24zlBEAmMFTDal3m6WHbLefEDimDHvAo073H73MIknRflTJPtBw3r0oLT6nSxLhWokhRJQSfcC+yQJmlSKQ9jZt/o0TK2rv2ibbvlijX0U5RQEnopRMcLbdDUfvLlBj+Wl1UGLGkn7c7EGgiuBOgkNy37fALHFQYwpM/x45sb11sMqZOFT6xXghy1ktEbrMwRdz1EJyBkoYcwWVN/R56j/CUxDOdAmhh9EXYZafF4sQ7mPwfvPUpaB35CcnSdAcV37dilzINjkXwT6kMTttfH0QYe/WYDoRsYNIJiyAkhUiYlXMaoDvX11o66MnYfmREOZGmfwVAvyy4motswu5E34W1MEhNRH/NNDCCOIoMsSzQ4Q8HqkDaGrIJQ3m6Hl0P91qUAFmKuw7bBmznPJOaudjQw6pfCmFWUXP2lUfgZHt8ClSShEc0rdyQtsBAdvheyTf2aJD5VFn+p+trL/nxsBIyFjSqQVRCqBd582o3bDFXGCMnR55vrRqb2U9YsRPncvQoM+5kXiOlV3pkBbF2SzyosdoBKrOYCqDSlFP1laRzijDJgpWnEo1NBJ97U0DjgGrg662y0kqxDM7U6UVnIHu2OmA5Ric9OIGW2gkdSYYODEnjrJkWN3f5qoWxxUpl9kQrzJxwKupcyw5uAGbRWC6nekMMPu/ywGAGLbiYQ6UiA5VmSBICyHSwVKY/bk6MqEh1rJYUue9/otsbdAlklj6C4qkS2v/uOO/QppEg2Ip+ZJ8y1bouoHZMopuagE5NvEtWXhsXGBUXGCXldKIgNT5OVSQLUflRE3EyahLfPd5/yDvtfpN6UnFvA0YEkDXpmi4uIJurhPeU7FRZ31ANWvWYCfjofVXgMDeH1At5BkPnE+kufTEn3FwcjUFOD1NgPBcP0xaG7mECIb9lh+dV1u5i8lWDARxlY4aKu1v+VjoTWdkGjjjHd+vs1EetGuClFP3ZLOWZHne2Kn3XjKj8tCCvaaVfx5k68H6PbVrEGwqEKQhGWsnEMLfODKItUwfyo/+Rl4zUoNooQ48DtjV04xR9SWUhq20KHgdFgVBmntf8ygKkudohrjSnEmyaSzvgpbtcOtPbjjFOP0Z3PhHqOu32UQVnDykedmmMKXepzd59PqNy1AT6DhFcbAlovYmYpAEgmlYFipugAME9ABmuCzsPPtOqhvwgavn6h6rh81sDjlSL2+A2BeGpojnHbD5ipfpjQDtl52S8lordIBiWYWeA3YhJF0CbajrJcxgXZKGPP3MYteCaTaztjN0F95eINlIjiyTxHiFk3dON+swinRK/f5FjFSlN9fGqw7+gHjmRZyynhIcb/bqv0R9qAejwILxzxNEhuOrdBo/zAsIjLzScniqThRztR3tPxD+OGLhgg3+Hjjhp4EispROE8ZAKKOOXLrsfvlt78oj7b6HgzFCXzysElfrOfJ/xxLd/jRs3MnpdPZ+dlqTpSJ+xzSKep+m94r2lsIlQBQ0XQrYaefrbI8s5z4M4Z2PveW+DN+yRlt/Qn5CQJtULC14oKgXhrz+SbacL+zgeTzvsyCudJktMXywhIq4Ynr9vP5vIXVn3vk5YaabDWqkI9qB58CZzoZoR4ubueiebUswVmPOi5dR2+DQuQXNGD2RSonweh1fvTj6OUribbz+uKXOD9FCHTegRUwxobgFAdPGbf75hoix6DW00wwOorNBMdIk49K2/ZYf3ccFEIzsTd2Zaa42u2QkEf3+yA1xkUmDkJowyXTxcNR/aapqNJy+uXHSltQoSfstd6LM+RkDd5lxX63+sfZNyPa9bWQJ77y6cteXnJffOzhb0CIUa4bItMY8n96uGeprd3D85/qP3DomM2rgE7VXLPsFroQU0pGZKwJjZZY1bJnPOfzd+vg7Kj/PBssGzWSJgFwhGNA65EeKLxwKO8jJquN1SIOeGcdMz1HgdG+8nEyUtnN46vNT9Fr8/3mQCwjxf6YVdQLXRWMU8AUsgK8Ed0LHfXYpfowV87DXDlR/caz6+UpHF/yOVzcDjv4oQI4tw3pmGsM2djWs+U7nnO4MSYiAy5swMytqa+p9s26LJYlya3vGfKXjpNQ3xblvVtUn6s84HbstIBeqaO6EDXwWJeVhD21FYyjwMhKFjD8goOYifrhwgsJJNStwLSNzt2PSc4kHXFy5vVqYIzgOK6jwreoQ/ep7/2rvvUwVz8Hp5VL5uHCK3UdsIu087HiwNTDct321m/LqosSe8uLt21WOvWWVhMEmsFOtWP85MFYPVk/nkAshUbWARojWEIizE41+6ns3s9j/tLbaCAlCleKuPJ10j44mUyvoz2JFUmhgoz1ThBB0RxVgXADauYjf4EB20pHhgeBwMtbL+/VSgin7uwnSlbzym1BM8VPw3dAloAh9eph3VdgNnLIbzDQ3nxkGX++4t8+kyXDUE/VseNtr4/eDP0+jXFoo1DPuOCHpk072LoLEvMkgUXQ8epD6XbTZeDjE1hkEIHsg3c+lJ0WDHy1FkuFtuNiGG+a8eRNu7YuX8+Y9QsXnaCdh9lc/m4rtaD13W/MW0chSRX/1f1bfl4bnGAODlpcHFe4LIBy0zw8gjvJV7eNSJRPNoTPmQCe68ZHVt6w5aiZLrJhCBb9IVsGvcTouR4EDdNaKJ8vP6h908boIEk8d5e5Y4LCbtl/ZGSUbM+7MecTdON5NeeHLJC68bHQr4sr1JYqRorGORAu5yIUh/4mvu/mxkiGqD8DR+nMygShartEI2IxqH2Fed/+JjuGEnmFMVtoAI81IOmmKlXAwnL/upeWYx3cQZffkqTP0fGlWkLFg8HlOpcbjpFA7Xp+wcA8cKymGhOgweOZTT3MTzNsS0uhrstBeF4CaoEe0suk1KBL8KL0ELLn0LaFxxsat5dumwjb8F1bDpMqvFxpmrRAZ1h3fY0F2pfjcDZaHKDlsItPR/LAvJSQA6J2Dfh3YHC86RxsE3UeLstQdK2Vno1CLfFScpWWNcc0hP19cFvPwaqdyyHlOirp3DuqqcpD40n8B7W0tvZ5qas+mSQekUYls4T2RDGJHBmLQGSbD2mM48z4tIV31Lv/fP3ndWo2k1JttGPLffRyY4XLlD6vROAkT+nQlikFVuWFmxt1Mcirgt6cKVolxlOgCiTL4iFkXRlcknes1tP1Yuy8HuXnao25Yp8ESyd2k+NLDM6+0sNCz122GFqgJK/Dx2FsRYLZM0SytI/rCWUoP5jSe/62l/yHnG69m7/2kijHAyFKLYb4NHqXS3YfMtXXNxVrpvDk+6q1QFZt4xzWNRaWDZN0atESw/mIL13h31EleQ45TOX3V59P2XS0oYCW4RfsvBli3+hUxgtDYeufApSXurNQIaXBtsfXAcSRA0ZBS2V4RbQUTVRraqxq+11JAURHAESsmQHD/ZtKnz3WUVNwldKx204jlSZRxo4XYxaEIIoL4kgSgtSkQV2gQJ6fxY16XYvg5euAMdgqGA6p3ZP55zgg8oCMhPFC6kCKaSlxa81iFLvlTOV5iG5pBLmDVZttaEcRiYg5KCHyFnT2HIpmTXQwD4JaBvaf+hHfvrZv0cfBq2zGG80oGem8/Yc4xqQGvnQUKZkBaeWgX4rDVhLTL47oGWCTVQGVoQgCjaLjg2vo+fPQ9WLaA/qh/24B6QlvRiQdcqZN4KLPAjvxHpLHN1K/y4gnavO0MwZ/l0b19zvDBWq0grTfLW2oBvoqrMx/1H/I/rVY34g5QTDO31a0kf2tDJOK9F13VBuC0KZoC877z97gbx2dGmW4vb+4vtyVgN6PwXgbnp8z4WW/p5eadWdOJvvdmcopKud/r5Cs2Gob/F79OMV/KV7pcN3MHNjloaGI41oHeT5HzJ4ClheJmnBVs5jK1B9UYeq6sFhKmoR371XECd1zXfi/Ly1WcBQqC2IdVYOFI0nvAYaJdS+BSphsEQwEZ9vM877Qnfka76IepicGcPe3vrHkL9sXnbUBuPng2DVxHIc7SuhGAlmR/OG9W1NxIkrSCY3ckStX3CEYfT6sPLyepCa1WMquHywAyYefrr9y9j+jdVNdEyPeK6u8IPsHhgED0JJsxmEwZcBW1j8JFlhR+LlP+dehtUZmzDcCEG1AmEIsWF2ZiIJSQBl8vsxP+ysjLfmtZzck8zPxTcXLHyj1nF7BRHAwpJ0ZVsPnlqyakJLFp/cGBrhsXzJ0TbXmrqsjFi16dfG//jBmIuQKMoKihRvYjrU57bipV2BE+VZCkQKRxYnKoh6xqFNDQ7anvhPanf+V2WiU1yRHnRUWEMttBBaqIPDdLcCHsF0pBD56S0Nbk2EK5E4VNDDb+C+N/Dxp+HXS1o9xXdMOx9xsWt96qmwh1GpFIRDKqNmru2NrinimuBZERHEkrccVl+v2fw8j57h1xFQ7Qw9quK5HPHKMz97/TU4xzrTzTOyZedpXHIg3oeAwT74mUv3AZUH/xUkOcQKanyCKAWLPc7N89IdCT0P7XWB1gg/M0uUQYVAGTnBLUYvafJPLL9RaUp+F8/vVjGIfgIajwZ48ybbf2zorlM4947zNwpUphytw7/ytO+sDCig1v4CsX8Gn1IsKwV+CS0325cfPqTca9NxM17CrCdst6inNjci9x9OcZcLxEaq91OjrJvIqVu8orAMUg8LYMOVMA2uQ5RlAExYUbASZBNdQ8QAIxNcwqyS41o9wUAEymyAXRlVc4GbqIb6dDP/a+kXf4UITVqofo7jZfIgocTZpuY7UxFRCuZMDIeRh5fLIGg6m7mXDXHRY13y5g6fn5OnetwC6hHx0QI8TfJiL1h4KaOEagXVUdApRMAy2vpt4II+dymh9xycXo9KxiJ+Fvuln61ZTz1DTcz1ztRsVVTyW7iDWwbrN4kHDkUeb1rQgiuGNoZbxTbDF5Xby3fJKZLAjONik1201d7yI5uEFIC3M9C3+mJmm4Z7aV916aXPsUUvcKnaitnHB0AkqZ5dn9IZXG02v1NYHKltrv+ifRav1kd8HOGAQIQnfIigngBi77i1HbOrE67BxKGO5ben/W8Tr6xa74y8Iwj2V/mF8Eog5T3EY6EpmhWgcPcfXtUYbbvgYnw/Q5hbDmY+2XqG3UPLnrY4dW9Qo0RbR29wl9bG5h8NYENYpebhf879sFZH1eSHnT+l/BAhTUaUWnSfpIHCCvxS82LJfCm36bTXn9oGmV3p4gcZES1u1a2i6FUCtdViblyDZXkxtquX2SlNyuQSAjmwyQEx03i32qXMh4j295146pWJ7QLssKfXHG92sKJng/FBvglJ8+BGTiIsNhoEI9vgWciN9qbwkkPrTiGKUw6MKpPN7vsyu8ZGBL2o7CTMQSzl107XIqnR8IDr5L/wvaXUID6mm5Qn2jLzBeMjwomiyTxK7fnRqBAToX1YHlh7qRRy7PRfhrU7K4DPzl4k8HvchLxlvExT/00yARMBvLGz9ze487zngK68GGqjUzpzz1Vk1H43bQzKsn7jjR2mBBDdBJFW5XPmIvubhyrxuH4TWNyAg2PMJ8FPEv4baJGLhj//TC4r+96aIdpKCn8ly2s+5rnO5SDj9oIVCMABNBnmlAXLfF0qxTkWQQJkfFC5cVZ9dnZ1JN2MBHUndKrLENtF9pCjxXpSUDwo26AdZ3yiZCJyMpvlxszz5OWPMG09p8DybAbFqybiVnyKH+pXRdXwUVn7S20zw7+6i2qfTHCdCe/92RgBlUpXdZd4wTcPwbdcAfgSmQlFmrhJ65KsC5vXBEH2tt7a0Lix4tadG0y67av1QIqY0kAJsyyhaj0CQ8H89ckDvCdXh6rez37BineJfL//rpnvxbg5pXitF/PIdcbTUwjAL4DBbQdqL/ZRsfSvS7HLkQ829nC6UrqD3pH/UuUeOP3bm1ClzXH3FleGT34ZWP1qGwkHZMxQMVBhoxQGV/bE0XA8JhlN97L4dqhy7g+UilAJ9mZEFokDty236vo2/k6bp3W4Vl00LbEnMEONvjjaDAsiGR+4T31n1m9z/Zst5Wxo6zw0QEvwr4CGk7546YGtCucHwPl2vW0nO6SiHkDI8gFsrGkSeq/Caa1wFS1M4pYpxilSdK+211NrD5IJs4BNvNgXZ7MeJuk33x3QNtO9Uny07/7eGiAr2gQTu1iGyLv1rl8Kv/FMWYLPGDaUj/rv5s3hTD6bD5Okm2EzPj3jNdowaEg1Klq9mOJbTLqFTu7w37IqIofswZSZAA5rm+vdXjAHwC7OB2IsZW2/XznsW9YJDdtyZ9X+R36sEVeMFgnWmS1vnb434KXKOivgdrWhBkHTBc8pNiQc6ujG7b8Yif8XVE9AwRbcH8KScCvT+mNX3JxV+TkLV930vgPwLwTI7ZwpfRf4g5bpClFf2F9aZvYVA48OqTXDdQPI1R6ksxZWj0vvta3eThmSR/+vFdRwA/il/lqV88iJApvSz6Thsh39BZEqJVgtgB9DQyIzn9yIsfRe5wf+oGJku0OA+MiB1cZjxnGStGG2MYSRLv/M6Vu+4FP6SFCmLdA0q/CSfJINyRatdjP23FPebWKEiES4EGqwC1ZVwlCzJz3aWUD3XPoLJ/OjYsvljepkkkAYYSMRxsSZoyp0mf+4eSl6ro5rx9R650Z2XHB1c0G5jT3/0kx0NRfTAFbAEtZ14SzVlhMPFqIujonsmRVijc//8mMQYShQ0MnzBJ1OHcchNN1Z7TQ9RS2O3ecR4z8dBCoP2MdDXq/05PCDXFRUGNUpWh42km/i5oke7Ofi5FL63SNal6WxpCibmUlEpjkwSEPHpUFIkojR5qYUf6v2n6hTFQIn+l5p9J15RTUTQrfzP4yU1NQjB6s0RHPJaTG7cTTekL3OkpwxOARVoKU0oqETGzQXOFR1UE/d8qLQ5WrHDSj/2MW/RO0zObCb4IVCxflahcsS+73WguQEkUd5H/EJ7lktyyKWSc0hFmVWzVIX25jB8qaCHdsGQsIcuyowIFLJKKaEwAXhHiS7Iu3TLIe02UC52d/RlTSP3ZJkuWAXYt1U7fz0MTt/QQXycjmq8TxKjNb/jAHP8gJrIYa9vIcXYynR+U1BtZ4+vCtZ37hC1zgFintAJXCfHtCGqQEI1qpELu8AzKhHcfLeBp8yYqpkJeig/xk5t+Ut3zM0Ziejecynrof6q5jlbdG5HyAZYNbDonwjiRLQg4uAbFAGXHmtKaoMia153JQ5iPC+vCAgWiGVQk6VS6HKv+SkMlPGEqbzggqiA8KYw6n06PlANCbGkML24yfHrW0WcYstb0w1jYpzzmhXkyPa7ZUrolP3+vaDBxaJEk2pEmcQ83npWutKz++z2Jhqi+1JnwYdSPH0GRLmE5tQUCdawe73s9gbA+K5jPYQOHjqdoVLDz9RxBOGPmDIyCNKLWxBFI8uSUWTKaI8IMOj2GREJojD/DiOg5+RN9xSefoJfiIBAZTLiXAwRHAasWENgcu4vAxRXOGfNDhoz6foiaZ1dFHJiTXe46WtWJZH/6xzGA/U2ZhneRD1X+NqV8GLQzkRbhWT9JEsZ9kfrIm7D8tKU9llnomdiYrLkpofZDljKJevo20wNb3IuloU4SOwtXFcRorUZauyuLdGCJW5S0cYZl4wSYYJsUdJXOR7OLBHjBtdv/dRjJa+WwIquEJhgZ4P+Dq0/KAqwKzjN+dhX1YNVtACCESuwzSn76l19P3qRvhCdejbf4oOX6jRZsFpy4hrENsx8RXL//A7v9isV43Xh3Y19HVfTMawfPxoJfl/E7eEj5u76AURry3p1QqFZReCJsAu+VJUo+LScWOUKTflpVPZr7FcLxTUNb48DfdIzKXR9nnz+IvpsF0tysufupb/moClK/Y4r1Ohib7O1wGXPVE/yL9ohkpCIUr8er61oj86Fv1R4pT2j87B2mmKpMROeB1wSq0kR9tQUoKPB1LF55VaF/wHlWScd05wcOcvNYLddq3XKEoogGJxTGJ3Hw7Di70JSFjY4pSFcoan30DoWZ3qiCoIesqHIjdxUz+4fjvw+kYVtacYqfGQi6TCAtvBuIY2hVW8uW5Y4ZMMqlR+RoN8jV4RiL7JDp/iIV4WHbPToNcNuRCKmq/VRCTdrN/NugmJoWLupBMkQYIWqouFsS6MMiU3VBV48w2KqgAy4EBIT5KLgU/PJnOHWXEs+GR5K+2iqdf2GGG7XcH360GZZJKwTmhdJz/g1BhExfMGX7Fo8QMd0KazqhCvWQMFei7U5qj6oRDrRG5V1c1L/6XC/d9rcAK2zhklTi+jOtSU+QBMspExTlrcbGxMLjCbcWjuNhb8mEbBQP+oB9M+DRh4gOq1gucNNJ8nnDfuKUt42Pa3VVQxtXkfcpMZ/0jSttiYjCu9zsDfrENYhwd0avTzkCDp+eOMK6u/BIHlxFGYBp75PRvfQfDog97Rj1c/ce14iCI0PufZmN0kw6GTFeNCBMGugItBiQsTdWP10N9YVpjhAOIFboX01a7PEdRJWO2BSZhUyvn+phiKqTBVGIWVSn6gKQVT0Muj+lUoJa4ifM0e1WfeSw55ZigOWSIA0VrJTLdzZ/dnIW7yQx+4M0T/o93PShsxfBvEiOj9Mzn7G1DDqVlkRm/nuyuJyi4SVdpPYTf0pq3CHoO5QgCjSBgt9TUBir6AgZgnYxP3LHvExVqTInFEtG8jNlyYWKHwSQrc3zqCHkFuCJyBKHW7+iwQ8eDxWJzE42g2HIQ73TBWw2YlD5vcawZgv2ccOTib77x13BLOsjhaJSbMxpyl2HaqHDaaezMVYE5kTYYFqginsVSgdeHC2K8YGUVvL3+9smrijrnO6qH91PLBvL2KYIyGthdmwGM60v3GKZ3nQQxiSERKc+oREHH3bvBlCjh3yXLbnxVI1xzuCAX9V4cQKnPDbhmnIy4ceHDTDe8aFpMIEloST0Z8UCLWMkzv+0UWKtbUkrvXdZtmsOMhPeN9gZooFtI/Asm2V1nIR1RHfFkllQ5vFPXjnG2fMhgFDxE5wvkkIiVx0iCGD4f7364GeXoF1Nsh5x310Dv0diFPgiO7Io2xlMC00bFyqAX4mlk+r/zBlxX5yv6ZfX+ox4RyoM3jyJlgsIAI/O3gXPOrJf9HwAcpf+mGl96yrem+rabvo23VmQKJDRd9IhQpqtgh8PE47+v7lUa1Dr/G0E7b+1GoSXi7o9KCWfFmuq/8D5OQfVxJiL9wEX93NjyVtgx38vCgzzi5bbxMHLzJmUwUBPO6IQOmFSsmEt54QQNK9jhJOYrkQjpSVEjS9jz1Fiat3dMms9pVxxH5AEfjZYw0vQyxaEr55TdcUzRXitd4njnJYgm62aKXRIC7cMH6M06DjdahIVUedUqiEkaIqVJcFeNT7w0MC95HWoHPZKeI0kq1hNvp0OVhcG3McYqhLkluwggsD8tv/ua4JqeRn+aePfgEMjkyG0IwzjJ1Oqg4HIvPwWX4WOFCY7trhpGgxT58/u1lnYCbjtIb4sffSF4+R7F3WX0Muu/CktzdWZHzU5GjoZU/ld5f6WTSNtYFgez5HNjcoP/vOt6zdIXx6SLqosfDPcjGP/BfkBKcSuLfmC2PdcpBFechz9TZXmhnUiyLq8RYtFGs9lcObRdce/pZYJy58/tJ+J5Xi1j8e2sOEDzrvq66Er7oe2x7ZNYj0eHP+WDdSOIPKAeLhkK7pihKjc4y0019dOD9/yLYb2tIOy8o/3eaODlvQpO8oqpIYbtKuBiNjs3fyz2KwV6sdbeAwGtdfAOphUsnKG/xu7eqVR4kQlzzN9PYYWKX1vKh9y9q+hAsiETsvdih+iiq0vV2fTFQBCcYq3plWrXpgbLfq32wu0DtMLSqkVHhuPpYxfJcDHilGdSO/LDNgLwLpJErUjCaidJoX9a+AXNGfXbNLRIwvNrP8hk2cIfG5/dvR2W/VzKtENTNjvtVuZK7MHjZLgf9rJn9Mw8IKUrvsQg3ILvsUJRfu+YdbZEe8VaAcHmhQWvg9qy58sLSB9ghqEAAXYybL4dXQNF82NKO25MyINVO2ulP5AkzvpgwBy6rHEkFDskmjLpKSZyhz+b/KEEXkMDzpc07Gs/B5D/Kb5C+ltAXndDlu8vUcbc2SVwlsnLRTbiKEsq4m+ajS5rYRkhk6LIBsebd2lCGzwCyg4wokjbLUaiNN7h88Kwcerr2cu8jHc4RvbqVXU27zsSors3+NJRuJ8rsjDLe49Y1tPexq3w6T1wXWfubT413iGC9/Nv/NFAO+DRb/WwA6kyuWkw0/STvi18Gvfve3ehZlgcvXogIVBF58NXJ7VPRpl/HFJR3YRbegwqXgf1fvEqZJw7+9hneM0732ehv3e5CcAn8lPVf/opOGvtuceS85KHFMOMmfLEtZWFSk5KFCWXAWgA1H4m7ZgUT5q2bil22qCH//Dfff/15Nqp7bApt7VSJmLnKLTDtxDTkN0UDD+YwGmIkz3InCq19uWyejKFXnkY2uUFQ7fzUBSy1Ek0uQAMcvhh8932r1tScvDUjeUmC1aaiJjMwFavYnm+O9TkLbQu5z4dg2F18LcKJUI8cp1qH4gNspf8KkEANMGtV9UyUdzny6LMDpYS/yoPhlgoHtdhaKKz5NG75yMp4bHxbs00k9D6FSlIiMaid0LFdVfM72ujDGwpKGSJqpz0ysQ60WQR4mEacogKDt/dJrJmzXrYWC2cHSl2lsgJL3ET0GaLlaX2c2ioNihmXYt9gA4ysdfFtb1m4k0r27LJmEJBh7TlbW7/2Vh4V0tQvmZ86gFviArS6jGQeyDYL9Wil7kahfzQQn7NFRz/uDxBXF5IMUcFIW+FXH9NFvp1iGaac+6Ece1LNfoiTmcIGDFKGZ66op0b1xAXfPg+fyz4wbrr7xckX+oxWLPMERjB9uiERe1cZYKq5WHi7qGUufQsNRO6Zfr74F0Up/oDyqcf0Rinf+to4sWn861pRP5EYR7k4ZiJ5MTLMzgKeLVZIAE3BvmjwIMicJ584Q78JYr5SzisLIUoROsTIPjILuul+I8zlCMZjjgTsgEJD88XRyumh02s7qksC3LjG78Y0PvS/rf6n4nxhmXvsdW4dJaCMeDWwgrJWNgXEi/PQWPVfJtcrVEklM3ntvG8dr01VcPg6+YqIo1I9JJeTM8ZyB80ZG6aN8rnLZnF+fG3Me7fyxWUILXVYBg+7w8wqywsF8Hh/+fMTqOHFpIGJauoWkHvEWfvGxy964a5qFPRD+8N7LsWDRBXbuH90ZyN949K+OP/S4PRiaXyo8h43bgLRpytTS8o88S5u4ojH8TlM8UMr4gbrepFvbZhBTw/8GabxPcJ5sMLpxk2/qlXdzSGbediy9SVU856SQNlclWOtE7+U1oW666QGp52KSQP5bRqd4Fny9N+PvXwlCE4U6Ir+JiNJ2rlwVIQwDscYwEbdBE28nudZtDfo94gQQRrSoAhboQTVcU+Zl0bW94rLG1p9bsVNX9c9JVFCxWujtd6uE9oP9pjnAVW3MGQ0y9/w4ju52vvVHpsKgoHg3tFFY1E+xVUdlr/GHpz2kpbYKZOqZpqK7uJUf8JWDhF0GoSBVoHERzXBR51JjjAwtLOuI35f95fK8mI74sHvUYaiTjbkLRAdRZpbvklO0uVr2xp4d7hMHQXVNoRuVDBmhctdUM7PGOjop0/Jaej1Evi51qQhdzgedAYQ7y5all1X09AGxZoSHPRhpP92MfNoKyO05rbnutJvHRtFEcjMd3v6C4cr32jKnjx1uBib5P/JpincFKBVEyEVF6jLC6SKlL82797hSXYZg1pbzsjCPzfJDxA+25YVxB2TA2EiRAoBjv+REtnrSIaAjYNKLA39yYfE9gc1bEbigC/WOWiIRRw0G1FCx7uEtToEtFvFgKNv6fH8nXMR5MWI3twWxciSSIFckDEf1hCjSAwyEYMyG3ZoVJXozr+RHtIX4PypqUySfJ6yi3W7IEzVZzKzpE1Qfp5ODdKJ4rFvC5DMrCLAKEm0iUyIYdIJgaEkaVz6gq00gbN36CqL0v6HzMbfxp6Iq+AS25rrH2Bhd9Fye6NEdZdrnbtiEZz9ddnX0kBBbre5Ce0KSrJrglPBjXRL62pZPT/TLp7y+E5NZyxwojIubAub+Vew2fgtRNTJORxtBB91IsdWaLsGIj046VZBcUx4rnIwdMfI/QLioRkRN0xmA7e5j+tUbXg4yglavdKb4SnZloSFCClPxBGMI/fHGgQvML/AAc0hheELyn/2ozCuTA1CSYVva2gNAFjhXzJ/bo007i06GvovrfEoB09U9dOykVj3dyz/+gDoHowowfHxX32elO0JCUflOFLQ+0b2Obad6QoZDm+3xhJ+ewt/Cj3KPCc38oOfRc8cKQWZgnS3Bq9SGRe4hEcpLkAo5eYIIBg5ysaMkleUuCYDSoZfjAc8zNtXtMRuGXoy1S27We+aDvZoiK3I90f+3foeICbdtVHq1BWYxr5UCOQsX+7Uu7/Q6I+TjJri+DjBJIiCEMM4FGCVsMkBdy8rRNbtHHZUFerjQNCVzWU/hWr8yET/H4EaUdpTUUovnczZmkF/7n94piIR4JxSDLpXlxH6zmqP+KzaLEO7Gla81ZkTSbWm2upMxqKNDHe7l/nlAyKu93ck4GNSg84VYJKB9Fa8oneFVXoYDAX2EqOqoyhbmo1ImX0JDcRKsH9JfLXyhhz7s4dakspiAaiSSyTxCh7BnlAEi0QI4aSACC7DvKEo1tKW7apM4eUEefow2XnwN23e0+6rJ32hbcrlnDsJuaqH9gcit3O9oTLL7GhcWv4wcKf+pXvPW+RV6JWaB2yNWIZkTSJbKFq6Sh6C8bTevVJrjUIoKlFREZEoi5t98+sWqqqImhAwfINjuKu+sWbMivj05ITaSkAfYBlzXgxb/8pg87BM6yGLb183jWpkPWa4IO4btESsag57xKag1kTCaHfPHcVjL/HgiUWiwEQIjSH4m4hLjPfPS/q8jD3WUz0qrRnrSwk3EyBfvZCrKmMtHWcVv3Hk/eK3PtqZNG8/WG3/QI4rUPZfGKNgAm2CMtG5QfvmumfctjHWxsqwDJzLd0n0pQzXDxHOF7sxJqaxhS6UA9keC52Pp01MuJtU5SucRzI3Md4edtu3cvkqOh01Pn2NziBoJYeeUEnS/s1N+sFUsOeK4ORmbOH+49j9lrIl2ZrrVemF5bcbPfU6qsjES/E49Kwum3DKmzQdvNdAQIk2Xennj5gonA8om3in7W7kgODYjAHZsYtSsMyYe6dRZhchR57Zy63b0IJZFOnmNi8UBfFO1gLmIOiHSPznEkv0JYIsHfx02M8CjjmdII/lcmbI7IPHhe5cEFqZzVhEdRbFY8yihT3nHa7qL9NdGkG6j2FrApCZpeIYponWoQ4AROb4cxy4mADnmk/qc7J1lRCQkIIpWu5zcfS5Si6RZF38SR1KJHmXXDu+LQmsuxLpMX+3vXqRu0U4GRPbYU9BaIjLSQC4rgSsPRuRevfbEwu+pi0HyKF01oLNoOOe+ed9OQ5uqfFiqD8ZO4m8h1oK3eFKbJ3CE6WF6AqCi/tIxwEb7+SYAR+N4V0mrYJkuz1wFiqkCFheJBbrzXOKpXmi3OsUAwik1gABNRADOShNihPLhZH1Ykiwj/EXuC34wYRoXOYxhUDwR+6AhLgPbgrYHepKM+SeUXAf01rmzQEOOaiXUVO7sZUifehdwwlyHrOnalj30Daju5jSNj8vmxlMkzBuBpiHeVNhIeckVl49XlY10GcFCZuslgrki6+Mb1niLbWth95LfPPuutLsXUpHvxnO8D0yeiw3gT9v+rzkFiYuLd38BbTNyH6z5Kw/TkKsKtRvGAIQEza3KarbOleC+z3K0UW+dGKLVxzrYltRiSFi5eD3vmQUtnWlwhIq4EJvPYriJhm3krpAtd8YxVoT3N17sSgL6aHbhLBHQmc2YR7y6IVLZxDhoEQFM1gLqGV5onNaU4HI77+PbojAbCLXXxe4YV/FsZ0nCEFfYCCIRrJpmL54RAFs6GncmnSntnf4iPvmlto2VqL7J5CPhgdRfCdnjrxaQrcivWxV4X2KLdigP1ffL26kJmXjVZIxlQ0YIRkfmdeSwiGmItff2OiUTyJWGdBzTOTthJ9SAEctRS6piwceRUUqT8MBSfVgpYjM8wOv4kfHhzGiSj2ssws6hfL3xrtoD7WZ/UPsXktAj2buozqtre9URH8QqLijkMa18E9Q/VAdOlVBeYEr6DDganlF20pz9jPqFt4hrGVh7cuP0ugtlUzD6pLK6Kk87jQulErz45vAJiTjh9qJUNg6LRdcCtyVEYin1oRs5XTFW5Nv0Ro4lRrhp5Or6jxtq4AW1JG2mPotYDst4IvSfkUF0V4QH3jZ5IvUTehbljorJ3wUvtG7vX4E3mDH1u8njq8QduxI5IZ3J1DjBF3FUqleknWWydLPzrJ96TtnToPSqHj61KGCpZuYW0WHlKRRLRl9oTzICP01H+opXcw1bzRRFzAHcHu0vjwiZcaBMbFbXmSmqcbk549RG0rmgCcBwaEOIciiBEp4ided8g81kpIu+X79WnAVz2BIBz1D3LQEXpP953F0WKP9k4UPvmJlmsQ9oqB0Dm+oGLm9mNRmUOYd0+/qCeTfRatPrEEiDQ0fdcbHz2TwL7CimwpQ9zWLnjNVUxt78jV4P3fyk5ytW4uZvvre3YW+yE04l1ZjrFN1yosbdx0GEmKKQhTL9fI9PXo692ZrEd4GDn+ke6n2LsKvJwKkn5oISmbki/THk7jdt9eV1gv4IQuO7IOmlUERFxEuhHE4D1/h23L6hy+qUHGO4HFAzOdOCMQQDSs9HBAxHv/V38iUaKRcrCayMGesUEqzvSGh9gUbNe+l9iAD5DeYOAScftj+q0q+JU0h+OLLqhSupUG7+mm9G3CDrjZjL1IL0u7iUChZKi6OieyYtQGm+UP14zZs93u4hL1Zzst5yXOv0DzO4pW3BmRAfb6QCVU9z2+ShItR/JWoaUOB3Pt2m3je6LpJsZqOkvi4GJtZZ6BU5q0JUo1Wy9ACgD+FI2zE14w5Ums82enbxTxysAJjy0kicEvIE94b696qfeMDROBYEGUctt03IRhEpYgu6CUkxEcRRTIJWIRhTNQWjdFIM5v9gxsOSMoDnEp9fS5KMxEoQRFvQWo+oON+Rm3G1YTdaM9An9j91DpMQmsRuJTup4M1eZC4HaA6KezHU4ibchQhGg3QbK6jCP2FFtxS8JN0H102z20A8iCTAUo2DrQRZsr1y2ic62SU+6QHtBBQocsRllrp+1GX7sXIOiQ+HQ6soXJqrHW2ncyyKpjDUXuiv7bExu+5Y48/Zb9pvvXQsnl4DGwkOOBrGqtZzxVYvqtSNB+uiwvrs8u8La/P58y0GXmBpZ/2WwZ2ig+NelHQEY25HH/sDDoXzDPyvk3EHQjtnh0ypM2s5iGG3T3okN3SU+0jNalZM77586nPJO6n56rdEclGj46mfaTCyUIzhlLxZ+6a//dubFTm1wb+NTvd+mIfz7y6Oe8W+aM/HfDsc1sNjTJiTWmqDtj0UwquBF0PDmnVAuGGF2+1DPLY566/u5wlsizjpUNL6QPF82cngISiWeq2sqzea4RqSsdAzcbQnI0fzlPPb8jfX98bwq5sryvhva9Be85WGVI+4M/V6izRTiTeTQYidfcgryamXLUu9KQT50IC24IL+HpAylMwADLDkpY7uG0UhsFkisU4Ecs/l59FFIRosA9yvQITHoH1e9jhaQvHy2w65jmAm+kkYaJdPbe6sYMTO5OVFPTk7nE2y/8E38X2GQIID2YsoVx4YW3NmOLxf7jZI6DE+SVGQQcOvJVVwA/9vBhohjwDwPnr/VAEgNBFeqSygBS4bVdXvDfR3Z2pwhycJaHf8DYiEhK8HYyaeximfpeGFCf9Au1VcuvKo2NaCmAZnAvM9ELHPBU552YmbCy/HOXOc/AmaFEKYFeKdq7uz0Uo+AQIYBg4PweiU96dN9XKoLDvLb8XX7sAa2kM/BX9k8mwMIPh6cxruQH7ag6z/l+gR17JrlLvCroUHWU1S3t/tAErsoRIoKukRTnp8hX0pPcIxQbPm2sS5RrXgHyr5GY09i0icP91tw/5efrgeYtf7vEGVQ5qDReqnRwcfibx7vSM5WZDIvAD2vSWgHCUDS3xNKRFh3R34/Jyo7VsSJ6x9vx7DIJf9w6CeFkyTRNGLLXMXhwN6mosGJtF1Xxji21fbzrtox4tIrVXdwZFCr/q6fIkiNt3zwtBsnXz0TmgW8sjUxpPpvWg+k6qW8Z4Ou26AwYKNwbqxR5FKirxEfB8smRWb8Nhf1vNmvz7Mhgfx+WUTdfUWxgmUdIFiCKhlHw8z9VJUlhpYqN9z0eZbERhgHIcSPrSQjnMwlFiOsUe6V13308zLQ0HQKeRSJo6mxaILN3hWuHrz8mId/RFOvgaEoJau5wt0ISHqEeEbBdK41VpKCTGBWX6WIENh8WC1ad2wKpMemjGjyCBWXXIw1fwILPnK8R/xM/W6VNkEHPQ+J/KlBcRgaCJFSITVKartul87AoDjpgy+QLLmHDnJByo8m/f53cFVuaGcn+/cqbaFedxAiExx/c77bM+0N/xHZ7ElANnUary1+EMouzFM8hWnRujuX3UX/HYjwpfEu7NDvs1k+iN3ffbhvARIpNaIZ90AZI0WZm89cI58KJYTXNBl56tO4wtV5GSRz4xO21fU/o3ZkI5nsigvU5zE2oJQ9gI1sRsnV/1tx6IcuEnYi8lHJW3xByhrKZoLybr9nkFmjli5Yt9wv6HbYE8LT9gzn/iUGpwiWRulQjDHzu7vLmZuZ+ieKWJOei3EFWaiANuHQ8s+AVNogHGSf+QxtGAywlbp669vD4786ljyytf06dfjragED/u+sC89Qrk4A/lWJeWNhqNUZA5UFvb0UTcUn2itRj41WNWNo0VqKL8KWGrCsy0lTu+O/6y97PExnj3GBO1+vaxf0Z0ba6TVwL4B6cKNmoA2H+or35Rh13krSiIFpc//64eAqrxrJiMQRmd93KmjP3MyNB7koedU8g/+DZuF7nPxsKDCg7GfHkPZ4qXR329TdJLmHyLswr/g+/+Y+s1y6Eo5YypTLUa6OkczqUDKNNOKj4z0EIXddmrMB/vQppH8laPFbXaWUZrd+LsI5Ht0ifV10LcPhHfz4J4mS/21Hs+3i0gweQFuudy4i5ulZZgt8Z4WHdi1Mg5XfBpzsJaaBlZr2ZIJB0loBezKFvUUaYXL51jNXBy3wejPF5qkMoQyowsOxt/i6+DPldvMRdPfKrlWGIdP6XQA3eCQCDrTz+s2nN6Yhp5L5IUNfwjBp1YQ0ZhUm8msZFwDv/fm/x1YBZ4ygODa5k7JfIHShbhIuZvpMyv/aOOLONLT5ePZyQFHoINqy5WOLZm3rKeJkKnOe8GMdBu3tMCGJAbKe3GTj+89ano8QGpF4R+3G2oJJQXA134ptZPuvYPS4FOoKf1xcOS1/pQW/NDZw7iazsqRPVBJV9KOZ6ujnhx+gbw7M2JzYOshgtNXDnMk2lx9ALBkEPn0oajJtOHgC6wC2huZUr2jlLvLwz6zHScqNb+/MI6nS0/hkvw79Fzt4FIZBfd5Dfs11z3iVhk+qJJsvmH8x6oIuirfbk7jkDCw+xDXnDwkegr929dJG2qeNi7t6N2/OsW+u8XjMwgMBWlErdoS9ugTX18brq+7qDcfWZwnX9Bzq35qGPoHe19AJwfEb2UxHigvCZxROu4bupe8QmWkf5qhJc4XInc6foSQcRgjLQdt7Ne1GZpXWkJZxC9DCtF3uP+RswFkVd3BsqcLnDJTnBqKlP0k53LKxJwoCXfDJNOduj0ogNwuDjwOiFcy+96fzAmfPlKffisCsZLy0Lr/AZoOW2tfebT10HK1MR0KslCjmmUJYjbycBftLDHW1bIk4KDB74ev69SbNHT8+dcBQAg6LeIF9fimtdZU9v2bl3tj14xU8xXlQoVF1H1eXl7LDPRYHM1m3V5fTrcsjglfRoTuqjzvKd9V9mrb/mOO7OOqkq5fD6Vuzlxw3yiw6+b4DGOzSSMvhhJ8FJDjnHjZ8wAHvMWqySRyAkeyMTThq5zSkHcHKwc4tZzh8fF6JA7IQwlpkz7jFUdjQl+1xXg9nDjWvcmuc1ySmYzk7OApJ4/FbF7g7HGeGUPp8rrlt7nPdMWlUKZOYgR837veZuwp8LvnowMRClRLx5/YJkNLLWJIY1/vDsJ/66CdIxZVvELH9xI23sWkDEwT75+kgSJ8FwuDN3KSVQkQeRtz9lI+sqSULvs/1mu2v4HClB4zQFJ63j5mKWfGf99FbElefIWKHC3Qw3KSciskR4ZO9kbRmSkh/dMI1tz4v/r36XB6G/OTbnvH6+hc6taktU/TjEB/zEpfrYrdzgne+Tz/nTnVZ0Ng4XXm7gL9A8GevzS6LvUEsd9V8yayyDX7Kbu/DXK4q+iq2IjtdRnNr+Bs6a6t0zq5fECNwFQ4cVtFMc4+GEd0kLsrnzY/3Aeqs/rhxCdsu/jQ1STssDZ20XftuOb+Pwt6G+BK9UKMyn6gOTp9XSJ497PD/4/JXlkloBob9FlbS1WjBzAZBsJhoMYNOHOR2MUwtnorQ9+4pCX33KuwdS4fgIceKAIGmM7K4ZnoleTLqpKW8VZ2ZjsXWAnq3c04+5hsDzWikmWFF0svb15alY1sEuLlMeICRzmPfggbTPz6KCt3WlScxN2bx4GI5uRTONSB1wSJpa8y8FNU7XICv7AhgoUTBNaQwqF2FboTPlXYBeoM4vjoQY5OHVmvFgQ6VcKgJs4fcCmgaqjMAp2hmvyiYXPzOZNRhlCSBqlfZcjkITZWC4NJsfhlecbQ5DGBMPdxYXrkHThvIzIqWYKublYIcjLCHUptJyTrt8VZ00Ph2MnxKscWNOjYciPN+Ar27I757QqjedX1xzrCnoN1rLSjkzwxhY4ApLDt7nTzRB5/FrNlY5SkF/yMbUOmcJ0ck5BGsIB7eKiOEBCSbEniy8QiARVG9HTUJ0vwYZgxvkS7vhZQhDDhsECLkYdi+SZs9uycBgVQcst9Pur1vihJuhY37eTxY8Cq4axwMQIkKk3L2AB+Q1VBiMzPUbm2FeiSQt+9sRwwhCWEfHNa0ilRz6HXBeCGS5Fbtu3i4kDOLlJiWh9UxCo++2k8l7t+NfRFuR5J76ofvpuH6mhAqC/MpiWOo5aYAtqEplfRuHrMu8w+GMLF7rkfkgsULG3HKUZMUwdPS1gxGaM+4/R5w6W/KzsEaw/AhINJBEC7isj2etmQqVk06mU3RDTlWNH8/i22oOMzVSuEoxWijNevzLICKygeKAahxqEC7w/dW4jwSCVtHbmQ9xPw1ZE+c1+klQ8BhU3GI8e83wBu/KnG28GRDAsmYc8lMG0fBOpjMOXeE9DkErPJGfgYblil7rDhWX2Zvwfe5VQG5Sc66D8Ilvo+T5uOVbGdVpjejsTTynMYYrLFQdxYOrc1SretWsB3xKTDOXibJ8DGQ8ErFavEAud56VvUAxnIoQbUA6hUC9IYjXVpl8Ch7S1czdQL4KukPl6qwVVpJuaMBGB1hqZ8lifiRK5+NUHP+kbVh373BMTpMF+J9Hf+lsQYJy3Y3WVHBYSFDsiRIHUEe7SIgOYzgF3nTBYXIKEElRdJofRpcuVyPU3uZu2hc0zJ7a7ZgLmeScMhYiPd3CmYrsDo1PAJ2l1Pm3iRIj5gNjH+WwKbwYIqnzvsTMGb/AJHyg+nu8KohHIyZyMdPK0fAPZAIkELPJGftvMc064s2+v1YyfLN/KLpc/NZ762U1RrDmW+1rcnUQK32zBlrfe+O/Z4VdtDe69atjdDTG58f2lQ2nVVfRvvx86SIaFY97xMNJu65bcvAHg4SbUcmfhlI3tHHn4kzVFVRUbb+7ejs1SVxpsfPJ7j058rQrzTefthoThU/OkuVhx7I/uI/w6+EPfWFRimFeP6gvocCAcGPAS8Iap+Yw5naayYjdQRmkQsRVRUWM7ZnEn6MAFQLbnubh4emwNypEUCOsS8lUnunZaEGxdgC6Yw+cAlDI2NC8t0FZq8wX056pfCNiB8O/BYDoofiZI+kXvZAKqUK/pWUZ8Vx0L5+8ccVqDUXK08IeBSVTeyAIYR2mKKaQy0TCNMZhGGrmh8STozF8UWr8kIAvCZytZ8AzKwZyHeIqwWGe1eOVpwz23Pmh8wSmdMiJDYgs9sthyivUxZy5I6RNWEjMqe4Zq2VIeH/replUkbe+soW82wnRhiNhbcNs0bT/R1WTmrW756l53mvbmhE9pCKPzw8eskq6W8T3VTzXTZy93ZJSGSWj4BHCiHRVPhVBMBgADxl6FVbruLuPEbkD5lDGFEiJYkxHOFVH4ckx3JmAdumq6t1jzlWnSfGXCgh9DAfCiV8IbmdvxFPMp9kQ526Y1RUWW3jmkJiy7reh29sZN2MQ3jjyon69/hJExd3o90R/etN1tnP6auNIatf6EbaPBa/REuA9MfFJdh098utX4bPxBvLnbs4QfzKSFiDkTg4VumikwSHBoeu98Iom3Wvls56oFvzGFTgIllNxQYzke1JnlMe3nfD8rWqO4YW7K+jJiDqb4IHgEyYhehMHx5qKeTigakH9Cdsh656ciCzJx45m2u3CsDJn7HzsgPNgr6FPgn8Ghnn4SmoP+6mH8BfInkjMohMNF34tZ/jp8mfJHZ4FrupnUrVlh7GEv3aHFhICIUdiKRvFn+qY78AQIo95O6+uz8kEKMl6nCw3xYNI/T2Z/o8xOCbVMZKlm0bI44YdC0cTTEr0z0e3vgbLtOIb6icQN7nAI92J8Uwny4U4stlO7q4oYK5a8APwOxNXMk6Ox54oHohdp40D7mUszhn677u7b7lyJp/1xoG/1ZhpyAWa+Nh45+gCQAmRWwHaqEV2CvhpqfnJyF3NKUvTtU1x7v+Yy3A+mlEJ/lVL+x47YsQ/sdG4x1i8TKvyp45Qsg7W2+Ofdj4QrkSr47AzeC2crmo509TfC4Me4u95x2jP86oDrDo66aTgZnLLiG1+gzKXEA0/lTNyhaajsTAQHm5MPqApbPXug7S7unhzB2Tya+wq43K0RoqCAUpH68r6WJhnkv0I5NOe5cjmU37yMDWwVUbcigXcUQ1sLSc2qLDoHo7/XVy0w1g6x87cv2WUwa4OkLyBI5M7mYrBMu6lAYTb/1dnjLegMEW1dTHd69+MjVvyG8PCGtFrhFb80j5VbOUrqDYhPOg43vBAGM0zQCr6P9UN76StUThjptcgHC5rVu6JoK6Og+whYCya5yQU3ld2B2/XUWOR/ye18eR+KsNEr8vq500jASOWGD7fkFEtC9+NvugyXkQmFfrfet8tiiTgFnmM1fvD7sgBFSlQkLr2Om4NJuoDLzUn1hJzbEgk3nEYkyFViBmM7DKht0OHlujmwEW/QapNavKBLjYq8winCYrrw4Q3DPhOY+nWoYqkktJkBvcM25CVQoR/Sqk0esdwr+fdoksPU1PtZe3tGd+pe8g45ABUGI32s2VtWURz/1yeGTHNf5fUjpMwXTbMdE6qgEWmmDv37AnpGHuDh2+VJT4vvFpOLn6BtzsmDM/64U3ZV+pjLoq1RTfhO8PpE2YcFaAo4ZDbmwHS9UyI+/C29acGnyZDFjr0Bi8Xtu4WqLgB+0PizqeguLU8PvCcBksahJ9X42K2mCc+5rpQGV1C18JzxoH3fbNXbXd9hM54ca+yE9Y4e2qSoMkvPjTflYyUcKV9Sx4JRjGZCGGoKo0tQbGHVNGO9uWabByrWEHMPXjaCS+Fb1pkA1wcZDwL+j2NtgZ15ZtOIZxO60v/2s2DH0mKw7Jl8makPLbVjuT96UnhxM/9CfNC3H0WiT1WTgmur1t8xLLEtCa78vp9UWRY+6dz/wCNoSaDOOeYls7qZOwnJ6CLa9T8xnz+HHRrpc4zmTCD1onKa5ujGMU/OpMX5Wrm358Fm3QTcmJEQhBSmzOF2a0nex+dl41G0lHytp5uq2MNJmXuVUinkkBxEEDdwMNJhi7f1vCF7e6C9VFQhM+jgRs19hQoXfHuH5x0OI1Vio2vlLo2rK7oIR2qTcdcPJOuRz1Env6EXzTk1OA0GgM1LvPyo5uOha9+1xNRGIdeVPTLm8EWeOS2Sw1Hnn0viKzVVZyzNkRuBPMXAwIJOA8Gq/MbuiZz+r28Fzv3/uQAZ6NX3Udx0eD8BHHLhlBcy5XvdjNSHMRpj3jyzsKuQGCd8ji8aTvCAEzMUoCkNaVPwQiFxKSu40F4Qey0MecIe4gl5EESuGTTQgSRB72Ebsn3MPmqth5WDXBSjecibwquTx4P0czrSnYHiCY3PxcZDs2nfQzoNM1y+ZFH23wPnYjzGBJYnNFNWNj7wXLkvZU1PtC1tn8TMQ5ff5MabgDK9YFbjVP7EjS8NJ1xMK6Bk0bq7GzWIzcFlGW4fQiJ2ZcLogDUj45Z/84XHFaDiEePFsJG+GCtrwEUuCZkqYSrNz9QTgrcyFg+x+807AM/OOPkCtNBUCRL76Xe+ZeGJFHeH3zfPLyX8TiGcWlahzmJo6ZakyItsEhAqyUGTXj/2r8hraYOpakKhghj61orBj8NFJpwjvVoW7gK6wL7UPOMp1Wg00mTVfg8xxYXxL9IXzvDtNexZNqlIxENOeYnO0dyGDTEf4/PqMxGAhVyk1DvspXNyA+8tkWUa/4hcrg0hYsdihofI0u+YJpiI+qU44o9QVm9EaK1dgBnSPST0QZp22uvEIIN25qnE3a3T4FO53Zt3YGsv7Mn+osamwUToCFNpuRxGistW2kASnJidVeSHexppnbvS8Wjn+TYX59zci83XrpUM7gdn9PjVYR1ob7CWB3vwLtyFOrhgnZ3IrY4mU3N441oB63dR7JUWejdmj13hN+w/zwr7YNYjgQvR3M16imvkZTthiS+OFBDuw4V+xCsPfK0TJwiKRiBOJOa4OEzpSwIu74mFdiOmdb/iVtawfYAB+dpQqieNubMTgWf7STM1uT3JO5xsow+zzmWYsAC8iuLhlL1IT4BQe7Tc5fDFHH64KD2qbBTyVLP1OoqAv0cO7krckr//zOzi8COgPsRpRnftaW039cC7RPSLU2f7N/qH/hpNGv/Z0H8QXvplP3qpYtCPn6R/pFMUKnO4ybZ76jPKVXBu/caIAzwqqim3746ZKC+XwpOT8n0Ji8wodU5Ot1WJP90/eyOg8KpsHOZI0Rkne5l6Z363nY5w61lonZtOD90U7Ue/ORycAHrPCBYO45h6jSmhwgolFSYUczgnRvFmnCfmNmt9T/UERUACEN3nfuBtYy3NXlGezY464JmzDo3ZwWYP/eT8tCIsM87HB0EnOhdzgdYaJCG5cmyq81E0SBYvyYe4wp1XTr4V/Gmwp5TIDEkUhiKugJC4djBeLFKUolbsIS7sog/SmAsHOY/vsj0JlMaqXT4TNoOACZ+pZlgboeLjIGJmPtEMpEgRwZdzo1c8Ary3xH8VZDbGhMpATwXAatscvNlZD8GUD3z5DOJBJWUXmdMXR2d0Kf5iqFcUNwu1ifNe9Js/exF2r84VAOlsmqYRKKlweS5CI9Sga3ANTbv2ucIf0EWkVpYEII1aGqchnQSVJL8cyWVaWeLWPcTb0NTyc+eHo97Qyz/MRSNdcOpFtXID9cbu59iZs0qG/YfN8j9AsfM95F61ZaWULqhovksAbguscWoK0a2pZTwO0x3J8Tuo215RwF8r/89NAEk6cTkuAhHOIMugkotvi9SCMqSE0Smb/Y4m2s7jdRXx3D+brsp2mjBI3gHHsU4i2MCzjAxHNnlEwHRhYNuaxtu+8uC9eOb2I0UJevufMyutwpgVPRIwsTDUNlk9coLettNj1zVvju2XplKTvQRd0XxFGXMSpMWqhAsgG/bD0u9Z5hziKfHhKexm4hgxCqv5DT+isbs58wP32gMmoJ0gYpZgWpjQJZKr1FkBEHR7PZvdrFiHmxNDzk1aJIEEdCGE6AJZk7hB5lYemmrn9stDlVVcGYUOLKOfo+df/zsV6En+L6uAF/xleaMXgay0KwookgzRjSMVOdzN9nwQAhDw7ArAfy6QnzReXPMaM8lbiWl7X7nGTWfBUqQILgDgtESybAInHAJZxqgcseUWMZBRDLVbmZIgqGxayMcBe7HX2WhxuUBmfT2MtmNfGhN4EJSn15SZZhx6nZOSoGknQG1Je6jORY3WK6hUxEHCDj8cRxvKwjMbrZX53Z9AOEZEegHb0tv4QKAnM9uivx8/s2f2fnBtnQl9SFPPZF9nQqM8gzzxLdVls5jr5ovKT+SQPvzpTIuDF1BSy4VEsDLDs5MNfdVz4DI+XD5BCrHEdhIeVlg3ScyO5TpF212NNBghkTnr/hiafSqFEo0bHy1FGKbDjOWL36S/K3EZ9ywG47R3idbLyJAubpT6/rZP6revCkRsQrtxnRmwLV2nGQFLw/tU4dTlfenuBq8CXS8Nqv1vzRVuo+M3ZGHJsxe1KZRvxWwt5gfTz5E9V/SGN+HpgYJ/+7muzo4qWWUPti1Xxqt+kq2cBZN7MHctS7DxKlYLbyCPo8AtvkIUnObMaSfG5jYSRtaMO73Qjxju9Ov/r9xnOK/fOSxbRuOgI5p6ob2CjWw1iVRoOUJwDn7mjeeynZGIfbqtqRFEnl5xMf1nB6jQxrtbXMfefALiLwfge6AiOQa/BA2ZkLIbfH90HlBu3XNaHcUqE/MC/+o8gGyr2CsBSzeYsZKsMCitfwupw6SLwnYLpru0npzPM4jnIXH2XQ1xaZTiNgmNnaYWHOKKajWMzLlUDokW0m4qSHJUF/0C1FIukqSqOLfSW2EXmnpYEcvYbWPtnUKW5ViwG594VFKdHfdx3yXPsNWr216D4xf4mdF5dMsshOFtRrVPFNkzKM85bKU4eKyIAPLalg8k1GqyZbqILMOoi+hXH3AfMVshmENKo4VnbIgdcV8JbqJ7RD2UX+lIfWpXNojeZiwrG5nmcpSDkfCgdGkAiwl8Dr0KJ+cjp3+AuRDh3U9xT0JboSIz51CoqREjd4qXuzBOLgqvIHWhr1plVyopZ6z4dlKRfVdiKDoQ2YljNjL3nY8Q7x/9vBiwlFQ4QpKpkl77+lLyeXTLAhd7D43+thd4+neCvXxfcwdw3HQ/lFEM6HaStXJriLJOZW3c2saR0kQSVci96fXz8rRVe5R+EWRQPx3W7yjjHWXUbiHa+RummLGVD3mfVe4kYVizcN4AfPYEWaEAdUK3gXmrbmBHVlAqKRz8d0brAjPJEJLzyiEVuTAsqW2GNxAM6EIJdtrPplsjR1e/DHK4XQSWizCn9b8myafY0MKxhVb85EbUV8nOTaGqS+xY17JTXdVx3lgOzpgrLkGKvBpd4+6Ox5QLEv3aNKpNtxmj6iuJ2Ix+hVWhLTRd/lLcCwzpyGb4ihDPKrd5CAZn/r0qvOXPCfNRX3qRe2IQ4NFnA8xX9acMTq5sZ5vRX8xlYL+X78p7xjZCTozm8w4oiJl8Ln4r0vCInEy3JlLr+URnXnJPHq9dltyYx/tivDUW0QMsyN/Z+bcPSZnQim9g6aCobw3am5pzDSSnnbb7fxsyznwYETAkjB0OZj4T/SVpmDtTc9eH9mzuC0diGWNDyMiz6o7zZGIFnxjlC1cIiFUCLnHd7POchcxGisGCHW3jJndyhTX5klqO8PEnniUeSLvOagYdrS+7Jz+1vcRcRjw5G6qX1QOzx6m4wSspCwxsjXOlWU+ogqDFPb7OHK51KjJjNy78UIYZaQMrSd7vYkbu/MeXMA0ONuOQh396REH2aGKwqyMhG3OjL59Ff2zMcxvbvnDW5d6ODV29V3sv2TzHv2y1S8kpxO/5kKe7YwFkJG+rJWXI3xDqseYdX1GM88T+B9lGEbt2fkheAG/MNpjxVeBJ13U5/q06+8GnTVHNVWTkWzqadK/uDW5MSka3dggYrVekwGbbkYH4wrqI3gAFzA+afj2Cw9LEdhFUtIitAXbXrV4sj5pwJmg6nr9pCe/PspZ8ehNs8t+Gaz58Y96S/aycKyYvHmKMOCBlXfbf/csvRiUq4lnkVKryyvpqLJho4HhrK4h2Pw7R7VSUFn1254wKy2ZhJdW97dAfVYz3QCGZxPwo5Xh7XZfbrCgyG2b/NBaTPlrL297GeL8B/q9B9Pkfgl7gKOmLub0FmfklYe9L/7RTZLK4SMyhUh7yUglKARooQ1nSpua9t8U0s8nWPvgBqAq3fdkhtt4yUbjiZiEDFR+ToAD67dAwdb9wa2BoC4frXOl51prHl83Gm+VcLGcCgWanUOUJ53I/dUbmco+1T3VFmCMUPeuvQEUr/OmS5XY6t6OPWZco6aco9QXlDA8xpiWHYv/NUQtaEv7yCHFy6bbKr59ZWzLnhAdsmFgoOAsX/eUjIpjJk0fWjsg4j1FRfbqtZr7abynfdAoAub5wemZZYpnSYRW96ZG9AaKLUyvdP9kS1CZujh5HOgF24qnf6ik73uvSPt6j+JgpgE/2M9H31qN8P/b8D46N9p/4OXxSPU+oDKivcPzs/l4l99swbbyPvuryaDkw/BX0fQ/LuulXKmsx257XJYcW/N4ieZnok5Wi2Z7fcAKWLagmzn1i/XPLfMamZoHeI7sTxjigHs93csNoEmqGfUgXqBl3BbqXNxS6meZMVMEjMGWVgXaotErRorcjDeIM1rJZWxD628pzHEeyFnV3Tmw7M3VBPYmb2OyDdnnXtehUeTJ4OSf1l/S2WWZ9prP0ve+u2q4ggLcwjIizLmSti/xdJ8k01AXOSFZ00S8Z3uNk5HW6X0zTdD/Z9FTkWwFPaKH3F6Z+Mt6QnLNDkTSZj+PXDMojNpTwlw4GwWYbluf253HaZYkNuRx+aWE+tvmWLAf1Q4y6wlzB3S+RfEbKn1gQc9F2i7yT6/OPpXpLWWZZD/IW+X7UXCFboFxYZF1AX7V9luaak8/UZYsHxlZTM04NqjegY9AzNrK0StWHEixt4A3TsMuilte3Q4BWoFOl2jwKt9legG/cKa0qYV9emmVdq5h5Gxndq9tm/kVDlV69ktoD0PM36imG3zGsZCvhLtHvY61vyAmjUHr58o2I3wkutes4dQFRZeg/9d+p6zZFe14VpP7J5Zd1P0dQ1H/P1KIjTzSmLS+z/vlqbBhPyH43/cnNM0zy2Wk22YxDtTDAo1vQymsXip9aWonkF0EjVkUtWVuK7PPbw0HvwC/46UiF4kQGGmNRfoc+5KMZb+OsMsz0vM3aGOj1exmSsT0AoRw2pIHHE5WoKIu1FE9QooIs/Kreg+C5zBvzPL70vRY9iNePiEQvTfruUAhuJSbmqN5AP8NGGA7Aa/iuK7fpssT7j3FU2oI3yYPd4EExsp3hNhAQ+YeG+IS9Ak0Mpw+Qk6gY7I1JWFrHZBkMmlWFCLTSjxLdyRXqFbOVn5Z81/2hmC0zZbpT0y08CdRepzZCsMXPnlTQwlRi7bgdoUlaZnC4PaHgCUI95onkple0dc8bc9m7i02bR7IpHMj1fcxguG9dR3nJhSF7JiANsDaDewGWDbx/KDUWXmvOzookKwwRy0viA9qQk5+2RjUnyKid2v22Qb61LtOpv4PsvBT+yx1ITPLDZ1xKyUd8tPwRzCeSM0C8jpIBAmro9kV+h43GdJm+cu/jOeJX3m1x6asZ7Q2/6SWOjBIJHleU5/JU8D9QixC0OjyrTuGFXh9/mB1VqROM4vi8TDSYJFFdtjCszt/BjBQuerIbGxTPusjZQAATbNglEfSDrs8lOzDJz0vxg/W9m7py9c/OtBnj8BCr0oeFZ6wky447/WiGpg66AMNdidEzKdiFU501TkORlV8VGg9ZzH29odOn52H1jzA3RdIQugsH3MS9aZOkzQSol9ABXxVRTrof621kPRkL0u2xoQqgIEvq2E5/QujMcy/yflVVCA7KwBmlac3fFsI69GjnMHe94OAT2/ic9UJSP5+OrxkUl0gpzO92esFmbFXl1vPYP7UNEOu2ByS4I+BMLC/LLbIZCderAQegMFRiXxc7DQ1TY4kmSpjG8LdOhk9yOshhrj0IvMgbnvGoLcRhvGF+jCD1sTh/Q5i+78BWsSOPWcGNcDY2xz0AcQNfD7QYeDLRa/aRn10l/6TFqNwq1jQgy9ILFMPoOoMxlol0+bfGwGv4vy5bTG3x3Dq39WiCPUfnIgSLXn3Nma/gTCn5eRWTWBYCdkqr9df9/Zqa2R55YmseJylLTOfybgZUzqE4+d4Lv9MyJWNw3UWM52ABzrp/h899yUX6n/G77e6O52kFXmVmnCPUVWhUkdtSRRTcSrD6BXtv9TGrpO8bW2k9X4ucJsyKqjV0yXeFbBd3Ew2GtelAyJ8iZwGt30u6p4kCSAXnDXdnRDY0en8Zt+3DRTvSVLHFV0KSK9laVuxH8YDls9ku6/JLQZ10dmQUzt2K4K2ndJ3hpXmhyuH4YauktXyulRNW2zfzGk4ERAzlG3iDw8c3cFHMQG8ke6HB0FPrG2tl/qB/o7wy9W9IB2MDYb2ksbXoqLQUu1WiwdkZC4CpOiRwUNsMbb/1NOc8IIAzk5f3UIFOJiwYcI5kfzeHoFPiD3PB35Z/+CEZCnOwcZCXV6TiKaG5iA4OrUoew/bFsns1ZW3/VNH9c6eYJ2mrymqiKLyZ34CBbB6D8jnpxi7eFaGuSSWKyFj+rYbwuWq0qbiDB24nydWMsZT4V2O+ntqxcY0TLn+nYrlCICBxj7vRxAeZZnJHYf/U0Lv3KeC3X/1A/uTMNbw7deyhpDhqR+AXu3gY4v9B+rVnLfX/bNvaQX6/KljoudaBnwkMMnDEC3U710YGZIjL7E356lOEQOuAjRHEFloHbeyWElt5GGqhAmod9iHLSFsxroaq9s/DOeOwMCt/7cdbUAJ7csGfb7tz5ibw0WcrqWn75gQaXc6C/vRy4IvupTfBOzD1D/aSbGNXnRi6XphPD7lXYlptszYACDvI2iuaXqSPxEz2zttLhG/wHBiQbage8HfYoA1ntzP9hAZSHTK8+LjO6pptf/LPVcUXJ5zO2e3/ALy34rrvqrZcPxwyVRCsfjXahquvb0L24DhJ2bHqk+gC7lyI7P8bvC31ph3egDFM+X3LE8u/XDk6j+xXJkfperK+QWiJv8GB3Sht3U333NtJLOU5sHjJcEidVVCQFtrDmYvE2Pj+dOY3yNS82kwzbAo2NAXeayLskbS3vrylrJ8mE6kKs4AQH+ZWfALTd9Xyyi2O1fTqC8OgoB4FZF/soHSHLMcBTMqPYGKoimaWb/tCDGi1wepYQ9PTzt28+bc172vmu9K4P8OxcKblHi6WRRlkf9RPU94LSTLLd3OgUwwkICmf1/eHVYIpZaVHKhgPLqWMmyQ2xVSai5w9lFzmFDuSYvD1co2EqziE17rDQwXBGx7h1a6Uu0a9+c33VPTpRczd8vRB0OmJGDrNd1/K1FzQZ8SUV/oNvPG90FxbMQUwv9rpse77qBXeiwPzlxQl/BvItpzYaB+8CTixCQWefraMauF74R6Pti1v7N2VBGwoWCGVxvIvTU9WJVHubrfjbit8sJlT9ZC0XgDrYPeUtMYuEgsFMlbCvnfuXxITjjYFijDY2ZuwQVxoFlWuU4LZTkZmhjB4LtQ9mSPmD6n02uB1yxQIaT5TbhQ1iHE+z9LADG2YVilZNbqz1Jq84dmMTqrvw9O86J0ec3f0ifYPfgnXI1bYjpU70BHMuVnqyrMztMUxJV52JmiaqTOPnJB7kI8upjlnkXgH2rGRkxIClmJCL8+YbIEpe/1N2sTyAqAcux/T78MIPFnuXVc4y0XurJV+POg1B8xPbMUaR8PgJhA0am8cZROF7G31sZUXZDPBQqhkkaeK2ORc9Q0T5XGdb7KLPQJUeEbBPYa7G3e8MOBYI6pP2Wp/OGMKwPjcLvbWwaOhBfOFZyjkw2D2nSVTo5kXeeI/fyttxXbWUfP7fdfw0zVR5g46ifUA5KkDWF8cSoRIntwKQnAoGcLpzgaBMMSH3II7KASQ8dmCasAnciq+vBAGc0/iDLomKjzXWjnfyBALWmVhgYO2W6tlceORXv9tdUDWDcisHB7/quQc1arA+MlDLspNszbZemae1bbudivk/JZWcYb7mo2kkZWD90vOq1pt3F/7Zi/zvKYG5BfwxM1ryKXjZbxgEymbjquNQ/RSxHjODsjNS1rlBi6NUnPcKUDn+JF8uqA0xr/MPWAdcGOaCvNEBs59AB2rOhpKil3Ntv3UNRa9x11nKJepJ3H+q6LS9gB29nYJgKRLpOOVMMd3wBepfL4UFvi2c6kRZGG5Td5cKeBSRM6ET/zqw9hk7uM0ca63F1hW/eiMrrYUuNWnu7mnuLzTjPeJaRec/3C5XVp4yq5eYzfWZP/sP5fIaVsH0y+SMdvLyxztgnb+YclLrNTKKX6QxgVJYqWLweYgm8urtZfxl2lUc03/sWmF/oDuyDWCi7QuJgfyKACGxC8IiOAo4lPIgW7wvBS1QKGw7hWbKU/g/30q8wSIWpDCkTZzweuCOePImLO9wc4Mcz0lLLpPUJDZ2FiHN8/c5+bNR+JAl9D7JubQIpOi4+vDZgwDY3JM2SckCRCvLMW2iWzA2szkXjO4Rnml1zHfb2jneoVPICkgw9A+rsRk78ZUwYuHeaSNdFOkEBSwPPPGeLWcbbARzH/4IIffXeyWr2x7Hv//dfMt0GCQWOxiTcVd94OwnC1/rtsrohuRc83I1+hrelWBfLTPQ7LkxsxonkmN5ArbdunSiTPZz8FPhOa3zak1LbltrykCyUKrSN+n5litaW83me6Gz+lJ1bTQy6+cPCdRu1tgA77hHXiF0FuU8gUqKntnbaep0Sx4FQENQO2gWqNqKMRak2S/UoKRIONpZBWs5dfPT39u/TR6Wln3hRfbkIgaqIuMWyPTwcJpvsLybujcweS60Xhqp6klhNMgKfV8clcbppiOl4YdzMtcGQHwXXqG9a2QG+IOiM9URMgp8yvnjp/NfuG3qKFvtQTU+9ujYoraFj8WziouBVmlubiUWixlab9TymuZ+XOUp0Abnox3ktVbkvH8ZhmUGdgJzLJYPeWDvpQWBi4C0S1C3m4SWPWjkHmotKWTzaFej9zsWRWO2dHSymR5zTe1WKskUF6+FLLiMRA3M/2UQeVIsrPY2UKQx30ISdgGnVZHoPjq0OR6OdbXdJQk/blb5Bvq0LjaHmD5wrKCGgw1qoyvUtqmh4rrpjmdXSSiAc0Y6dUg1Dl3bo2eWZb3iVHnTzvTuks7jTX0MNRQ0YBiBwzzWuNtg91Q+Njyid5JHy267KjrTbdT3dq2R88eLpkB3nv9rhKEhh1NHLQr6OsmnmdjSG3Wxt1h3pyYmadjba8UGyVpXWmLBZcicBeiydlolBYBbkFRB8LivkGkyYZzJLF6XxgZgGnQm8Arfi1tY7UObsldMK1Dhs3z/pC+qgFulEjuzV0weKxNfyiyiEzhE8+TAIND+KeCEqL0pSkmr7vA9LuJAcmR6qBytRZoR0mPPjvLfO1yiBbocpKDm6uqNXx06hudJEnNZAUX8f5h8xNDQySEiC4FXWIxtYQhiNpC3Uhspkjd2XNxSqCMijsjIlMUiU4Q9ND/A6x12xPZhsSaXnUmYxRqPpbuCaAD8RU1MjJP8cV905Bp2g0RkiJtBes297ajIqraS40L5vtcoZdbjATXSWRThZgW2hs5jH+B+Gs+Uz4LnY7RlM83vvMDNpn/8/pMmvcpNBYsjQsgObA4s0c2/lCQlqXmcnHLkrJzA+dXP+5i7S5STkckGtbeCRk7jjJGVFVyzTytHfyMaT4FXeukl1pGWxreMemMP2xTDBYPqXysYOf4RhDfZy9bkAO9iuMN/dDJ7QKaMttiXHCOu6C+/0qZ6NSPAbmJpaAlWnE5SOj5x1+QYeLUwpK+d1ZBJFnNOurAZwGvGiX8O+/f6UY/ZX6yuK9NbXs79uXmXGB97xOW1c310wZw9aiUBtQbuLtvgXHLU5VYNm5JKL7WSEm/eiseii6Rb3+IAqoCe2tLQe7MK1qHigcWey+/zNWemTWE/0nghZxfo5xIpduiq/NgLxf8WL/vMinw21dPbLYlisBjSGzVbnigGKgpXTPQCx0xP/T3kUiaKGOKWw1rZYCHaq6VwzC8fXqtq2QE7ptaKaPyvXm0afSj/jap/kU0kYyilOrWY4tTf95ZeSZgHvIel8t3k8xX/57vYoThTwWay+6XAp4ZSSC9HIFexb6pFjVp2vIudSTJ9zOHYAUwZWJmJICG3LEXbjROl8SjaMS4V4ufXdUfKbx3709Q/DHNOC93k2wYje91JTJEmdzzs6soYF7LPwXVWVWg4auMl/5xhwQSr56f5yC5e22dTzTKEvLRxMe7oH5/npXiHIbkwPsSmXfpMdrs0/t8Nj4LA3Zz/gwW/6Pu1b5ycq6tjdPXknioeK0lj3DCT3Ql6NuwtAuz2LvVocsiGXonjzDM9jyH2fH8SMrEnBcqNn0iwRVvPIvyijD1DOT59WCTDG6gmfsPkT/J08TlN9DBhzGXLDnnFF+iY0xVpFNRF4VRGZFVEV2dBkkHxFOhqrp3b0dwZ18M5aMcRObLhC7o4R2IUeC2AEW+w9ycCi13ZBSMel3d2Uhx00NlGxW5BMtkdw+U9CEDF5jffRTo/4+XUPU4vD50/fbMJf8Mr/5/uqV6t/c3QAII3XRpGpRveuFQ0dLDWlqlYwz+gHyfJnBrthtv/3UqJyOOkrk9mINBirgjkVJ43mYOiW/KntiHLfqBRNOEiVoSC2WZyFmLamezf5nu8sDtqoNLR6gheXoMKF10E6vubTLpfuqaxv80aAe0HTPHe35Ve5PrzGWe4xiWOcZ3jE7d7N05n4E+jeTgw3yjYXg7pu4R7VCB7w1koYb5IlzVOOKqnHlEgotPIqIQwiB0eKF5+hve+aSlbiiY44fcnNzCh07E0KuX4mkyf5spiZYi7WEbtA/ZaoRD/NJukLv9Kcq4d4ua7TPY6wKBFJFtz9j1VHLJLeUlXzxTa9boE7PrP0QCunvcbe1rvZJ+VWEwF/emrQfLZjWkjn+k+BUUrbzxYBQaazZ3uPr7iJVbOgcijFqpsTVxkCgEENL2fBUUBxUyMSDE8KksiL+vDO7sSNJ0HLkTaPybVD167PU7gYL9y1scx1s5U1RpasynWpIX+E1SjbiUiEPVLZcJWm1teqLX12tpuvx/3tMX6pE5+SUMIrwTEbhdC9ubw99RF1ITput+Kb/zkSJRs31Z7efIv58MIt+caASxLeYW+QKBqa5tAQtj5TjCKDOypCmAWk7YHnGoeHRWS/GURVlGRe0Rf43zCLjqNwmdm/d5rX97sfCgZIVm3jOs2xNEKaPXV65JgFQjAEvF7v/8Iiagd2PT0l07I/BpIgi+5z2sfMGNSgeUvRQDpt9ENbXpoSuXiaaRAhDpxrtDL+Rp1xf92Wr7jwTxGy39R5dSuC1uZ3j/V2rGjCAF0tzHhmA48Kcrsjk6zR2StKjw+UATw5RkgvQZe8pWCyb7vj+sqav0FAT9QdY1xk5oQfUlB6hCBXwWGvm8DdrOZ0xoyFRvMgFO54zwYu9SHhUmFoupjn98QYpHXbVQB4MqCMpFDeXfJzp/rNlzULMlLkJy5G/wyTF8sf0lkeCudflR0+a+tF0z5TnwVNHGo0Ygp02CMCNhpnztOO+cPD5JiFkWnARjNmxBGUJFnMLxr+ICrCeM0NMXZN+mhuiXn53THV5bHGJtj7ejLZ6M70W05H/FTNArvb6Dj+daR0URs29ELSTRNU/h6J1pZv8b3IuBbl4L2vaS9mUVwHqJWmDUosrfwmhJMgmXufuIRqhZe8lbIIlkElDauKUqUcWxRA/14VKruRFMcQuwyLG8HbzxAuN4lQWjgPekirkR+kniUemITm8hlhB2jrx1EX4Gy0xBa00jselC0N0d4dMMBtyD8xd0g0Ed9yMaq7RM4mvW/2u+TxdSkk5z+lTof4JOU1+rPhhwuQdgZbskc6ct384RGScctCL40TTDorxkhhXVwaf4s6lxIjM4ll9yHXoxsqumVjqSKr+IHkWuZg6M0BsLpGyH0JBwEuBldLbYq6hkFzFe0+J9/KJL+0A+LDXPWTjL0MJFH4yUl1hwGpRJnM0Rn3uYkGI8XgG61ieeR6fmRmnu+S6l7iWvLZbZfgOsY82Yr1tDSSqWts2o14Rb0ea1Wmx50n5zhQC7o+S/wl1hlcplHUc/Akp9fa/vC5VgtvtIvtQ+0k5OyCVW1D1226AX3bS70IMpvCdVvKH594EiYqNDYEgeykihYZx1Pf8vTaEeRv4OK7Zy/wR9xTs0w6hXtX+DciUofCsnIiFJCOJFTFAnIrS9rNR2qt8WweynP+Q6vwWlIuCjh2y3ErfmpT6MV43W9CppV6b+7n5NALZwBVGHSUW78LOPgQ27hbOS+2fy2pf+ntloBfMFEsTi6IZ1GjbxBCHo9YHPE4eDiOfhQcBrWrxDPh69F1cjUyt63z9cHxwAcnVBpK1jFa/0/sMnuMyXV7ey+ZfEBNCDtSF2B5ROVjtlKtO8nYed9smY5tc3xGWg4N8n4ASopgh5ZcYRCO+UvMUEGA5tMxwu1XYws1lVaHltjGSdmMpAqmxT1ivaFLGiGUKL16CSsaWLQws6n20za9lW8sRMQQKJr5LS63emXhaDez9I2Zwb7qgoEfEe5SRVZ6y+Ca8/NeyUF0Hi7eqtXxmqh0iF/+H3ldlqh2IfNiLqJ7pr0ULDBST1BlehMeiymvI23xD3e1PiTDckOAD6vHIOtfPgy65MAs+kJNQszDT3GEKoww6ZQVawnbGY5u3/QYQeTjs4XKjI/bk/axtjaVolQ+fe7UuW89ziHwaAPVEBSeZJocNeJQg1KkqLupoM4rS9SdpIUZlQ2wkPxI6EftRaM7mZ+U3tstvLl1vbGL3SNOpTreJllVSU21Y5fx01Ma7qas0Sfht1MvCGtu3Pl+MFEORGCNgmRjuwzq/q6f8+R7Vyd3lNuPmBy2MtNw+V8EI4xM+AWg/1KVDw2WidRJhlK9sTjxkUFn04r47kpXa3+geWf/N0QVGuTeg2l7SJEOyUgwLKK0CjbFTItLJ8Z6/YCbQocJlcqBsbbJzxbZkbkKa6kPGRvq/nOPhvxtwWPcrBB22uTKfs2l8rLn6E+JMtbDEoYVpekidx5vGDeZka1Z2/q2Vs8mw6LwtqA78Mvk+5dn1qXeloG6utkj4dLV6h+Ih3A1vvD0cA1DxpyZS8EWOQtS4CIwDQHSgsg0OIy39UJ68JiDSi7ipNmeYm+NC7LtyQ2vz7924WJKGkdBZcuSK+cyoriCcIc6pnWcNqyQQu2+h8tIV4Qyc4fw/cV+OS40ipZiGp9g7dlTBRMaoCFc0Y017ruXvwbYMNCkiNanR3FVVrxOuCWHvkj7ZSHJp0klPvlj+6FHrseT6u+oQNqSBKZ2s7bF2em0hki9LFwxuU3rqMnORcxWpYGfZOjEd8GxHizDXZ5ZrACgJng7rCq0FlwNQKdEEscHcRTLi1bZQ2OiMHnRiomhNg/mGPPiyQ1//BHXhvuvYHKF4QltBqPBIgWD4Y6kPFcNWiAv/TBbR64w0X+2Zri3v36vtRwEK3vvN2XqDc8f/173ykP0stmVngSIGCQp5Jqy6NN971+E5XN2nRFZ6wj0qY8qQR7b0nq75HeCVBrziP1viGVYOd1erB7mrNIOBQ+pej1N1A9iPfizb8xoDs3855oOThaCTVSEPvVg6QAtzpx2LIUcjsCNyLia0Q3euiTHXouA6L/+4iI7s2J4EWf+pVgAJZtgAhwWy/LbYjzK3YJ2vKm8w1/d77Igi6PL4/ttRGdfGw/7f8KpyHz91MsglOE3jwSOyGlj/x8M7rk4Tc6hHfA1GM9NURdNGQ8be5JsUjjl79skQJFwakRDTFzOIDn4V+s5QnYYMBbP33MILY0VY0JkHAu1KdBRlruvekL+jyT7FDo8VH+IKQ4S3rZzDjbsKmzPBHsHACHpjaFVJiuMkim3eZLdAga1QN5/PcHUL1Q/87jaoyXf3uQtP4gvjr95op56zF66Sf+6p6cQwSNIhBNQ5xD/P0TAfijQhvbX5fvr77Ufv12MUlEUK9nz4ar5NGEbkvpRW1Bu7dbBGBZTJ2TGCMOXfHrLUCnHyw3NX1l44H8v+4xRy7ocfJFr8kFlcHLZt55X7DQ4VReBrsKM/gfyP+hhJQx0ZvDjiH7v5yh+3rHfPiFdK4gxiQne2aP1lbCuv4gUno2G7jaha/pWHkOoVMbsRGuQMHI0R6ACfVdY9Kwwg+aOmJtjL2iBsgx3dh19mDBZkkJ5S9v2/uyZAGamWtkDIWSUJ1TCFuL0f2vZWH0uan4pkrJyjHY01X5Ip/+rqKqiTMM7JVYtC+2gexox5svoLTmycHNve9dXtm97CbSfWchX+dhFCu/EoY3HD1blfUWqZ0PNUuefP7jHwPqQNe5XyPrVLyOYTvdjlo+41kiUR/hXSJ1HBFXXewJHmZFUuYFXeEh/j8r/KTyxNyGNfWOGWt9obKUNEH9b1c/MwZErlG+/VT9iS2uS77/GfIghMFWnjgLtR/23wErnF6wOOMwV5kdHrB6wwSI333kPM6BhXSDFrko0BDEFpQFgGKSUT8T6jQOKNkjNHeN34dLw+0Ue5HdYfwgY5GaLJ7aUtLlG+PG8OS/ZBkz43K34WixmXvxLhv1K+P9gw2xSmCHQ4+uwM86Am0TeEvUdWrxp3xIWhX5jP889SpS8Im8Luo5FPjTj3v4r3M72OFwDRmt+0uaRBU38wOrMIC5ctqDi4sZE3/yOipKaCmb+h9MvXm+ZOFFXJlvhGBJqoL0eRMkCLuhOIrAqRjRwZQC3rGZXbGjqWecTCXdsSdIWi44DalmioWJ6kHWFKGjC27eVfYKhW/6x++Wnrqvn9O24P1WmzzxKJPIJg8le3qF2YzSJJ2QSv/L1HCrLfNI1dPfUfsdrgT1AJzaQJ8Pz67Ctc0o+q7j/vkCqTl4rw64d+X4Jbt22l7WbfkmhIgbdJMyRw5zDna8U0oVt+wqC5TxtSlPbVufAdKMjaQt8a3HGP3rMK3vHdC85zu117hgiJ7PV91aqWd+T2/yh/V+TKe90Gx6O2asjGw7xuCOJ0suKg3gk/0Md+yWmmjFCqIBVawFHZvvEx+aGnBL+TWkU7cc8UOW4HbrnWJE+nlL5OtHeX7PcbIddBUPUmy1EBKq/3fzr3Ahnq5DCAPs2GOs5C9DvruIpcW4/NObv9FR3zy+ybnH+6KoZK9Cu7mw8EwcFy+PHmkdMcCNeXDthh54wFjeKHVIloPbZzSTxJX7jKlIwl37GNxZWvP7tUnlDr1H9U/Klw+FR7z7Ar+xUu0o9ZjQLwHwbGW0Le63rGa5uwqw+r+E4CsNY+ZT57WjiQ6i3PN7UNjTH2mlVlTCY/887DARac2zu2OAnHvvfTEFdm+gP3j+cPHAR3hqKoFaxc4ssFJqE7zbpFwl5jDszkoHFUeRMtwK95ip/b9Dc6GYNXna22IOpYt1te+EDPeznAkeUfHhCnMeG5Uy3yZflOTM1vUiqQI6evfHoCmD5/Yrw8kWMJVOA4+sQnRkk6SNyNnbcV9GjuTnMrOkT04fsmriYxConczXAtjrMG2XWHiroP+tJJRA5rohNFwmWOHfdjUeXCYlQ/cufAmtKMP7Ln6r2wXnefyljbsp3tbnLfQi/9MBQObmtI0JtiQDWtxwsA86vfBaAtednbFHeTbN/PH0brBqXBcPFTvxwAPeNL6oSZsTEFkayROKt/o68zpAUtQQ3Bw8xRE0yV/818JXnf0NQd3P7vvqhm9a1cQj8G7mbsTKQ3kTQMCHdY6RLU9Sz4YDpgNao7HKP+TsGWbrUONB7ip02a2cdbBbegTiBYIJO24eAUMyu0eUXOepkzNuq34rVbNvdHtWw1CfGQmMd+3euk/ue9vWHCaCc4F4SDtRjfeX+H381VNEemFFRFYM7ytBsO9cgXKfHa4eOLU03z4whj/FK6uxUFtzSqrwTyip1/VA+a1jcOnwi1ImvHhPUi0r5gUsyjAWlhUQFd+dpfsJnp6/n7eIIgZoppYbDMO6xeoL5oyiVthN494EQb93A9kp3ERvfocvlEcYlW+TSDi+mzR+pmwpOP4x0CXZstQYelJ3LH2gGLzQ86cxxZD0I9Ffs1hZt2sIsLNyVA87d4XHhnvQN3ywPDfxMmWRU/T931CvD9vinJVusY6rlBGbgV/scaQj8HnEgUhHbR3owh2rRd/AfGsNGDB2zLOTVC583+c0pMTg+LqUj230pagpQu+8Np12RYYitJ1MVEJroTRmr36U13ItGbMcJDkihgd4W7HjhMxm0NXxuKhNfvnh9JUAYvQwpcblMxVwpKrHd0B08x1t548GUxrjctAXRP0WnvBniKLxR1qIjqnnIJnjSk11PCub0u0HZU6B5wPbe4uHE4TpS7wFgkPHFwbin4n7WyTffvej18iGr1iNpPc/qrYyGpWFTUDbkEVxzbmCkFH9W0orgi9jAb33B04qNEtba1cT80P3x1rdTbPs9f+919GYdX5EYaC/d+RCkl3CjEs0iImaRJbkU9JSD0oih00i0WyE0Ok8j6wMEWCJnIVD7or3l7BhZ0XP/klfjRatCNptS46OqNOxMSHQy9hFA6bauMWO7hgEmLhx+FAXRWHYAvIXpyuet8wILLXU5Xyq+l/HRpZxWRsGeJaY/p77FiwH1bB6i4DkWxNFE2TdZWalQo507KQ9bRhf5IodOKQVbb1EH4yuAXQV9uFaUQdTiM6mGUCo8iL5GXohRiZYp5vbCZ5FO7G+PeZOW/9GBB/LtNfSBQi8wI2/NIguTPzQ7nJCYHx0iOqzcHr6qXF+0nDDrJqVq8FuPrKnLCKF/whnHzer/Udy3yRSWv72D/gMffk7mLImy/dXd/hxS2fsfjN2I0fJ4kSuZ76zaEN66+DlOne9sOOJVs3Nq9mDjN8USG6aNNyatj2N/zzdJjEbk1zpS0pA0fQCcOPAyx994E8mV+bArV0yoq1wNS7ZFO3S+7K4e8Z99L4ClgEnvHc8aNbmPIQRqxorTPebKmpTEKTj2ndYg7al4O9gdg+tF4a+Jc9/cBuXIFdHdlxe7K3qhUjFABRQk99pUtDwdPcEwPPVABJrgyZaVUi6ypFsDSe5BjNRSy6uvHdKNncSBqFQCjp+n1qI1EcXqbLgBni1IDSVTklxLhZmrKkCE7cA669If311S8P8d/YCV7Xfd9B97i34OvhIPrHA/DupnVYnD2O7oJJdi/ooVAcw5hSxLYko9CFhXnMOxyp74jE/F650jUwVXpgxBcgS65ye0Gi3eJ/5tOtIrOjKjchO3s83Naba7zT/QK4Y4U9rJk+8Fb25EgVliU5gtfpv1l68hs86d4IyWIBlhHVFDLBD36z6To/YWW8Fwp2JY/KJdxU1GirvQyFZWExJeCGKhSHNf9xH7Ot6+0NiPD/fr4ttJl9ZF1fN6IZXeBOKTiKJSkPeCLfu9qOb5jqH13jZRC+qMMl3BRWuFVDTly6+Y6vtsPhVxvdQHLMRkgILdgrtXf6Zp57ptVcjVP72tffO3qHYuxmRcwkdWYdmoNkq2W6Xe6F8vbZYauET9Q8liXjSOwXbexkLTuc4GAEZF5d0yHzfFkA2tFKVVPOtzTRQez+V+BRH1z8CbiJ06ed38dCqO4VY5d+zk6UNFfq5aAvV4N/yMGXqWxd6eUfYysRUla01xwDP4u7OfVXLkiO5ImM/+mtf3Dj4G2sLj2HGhcFV2JPxut4yJRNtsKjFUM6qOwqCX6IujkfoFwSN30sv+uTXZLSqNkdEu5Oz6pmAXezUQhUl4LiP3hKaYANXNOtmmvFMgaVW16mPFjVo7i9x9uGHzoFsvUeDpdd5MwVeJnmXF6Wuizr2fEIb3F00lsE8XFbAWFqRT5Zow2oay7vMzeBsl2H4pNaVM61kqz1JmX622L+K1RoEao53/rkS3uAm6Z6MlvE0SqoEpMiLrPfaGtgwg4p4R0OktghEmsqvhty7vsIUA2XOwN/NHXo/O0GhhH69KZA+dAVeRWobs5ti9CIG9xxGreFIj/djSGUfrCnbNw9O8Mn8MSEPbnfqyDAIBfMX1w17XEaFLheLtCyougf51Ro+l9HkoOSaiaLl2+Rhy3wfmleuDp8kfAU8ngi4PJDR78xsqaUyq6pWpYSREHbm3U5kKMU2icHZNXZaVHFODKSgnteJCmJ13F0vi9XR+J+ObmXJhLbl6/aupL4ti0aDoSa9X9vU4x8ecS/TO96kLGtcN0mv7N35h86N5hEUivrc8piRIYsXUcj98/RiVvLlj5xbqu6PcRyfknvtOinNdYlV+wglrw1HPLQCI1pgx9wRaWfD5hw9mauJf1D8fhyGl65sfMEQEpw9LZkV7IFrj5507zozeLsJw3Iqc+rYZn7reYgy2FUjLPNgOZaAWIIilWRig4XnYUqR80QBp3WkqxUZukjkttI/oaPSIbZ1xstJh5mgaKNN9bJdRul2ii+SiIl0yST3V/pAJCnWy1PcdFjcV61eVali7SbsKgEKmqt/9ToMzx09fmz4V/cL8QTkObG2Pfj6VUgi1RZ/02ifcJd4dN9grLGnC869V+0bSpH/9/ffYC6Hvm1RSxKQcrTiU8iBdmOSmLTdgnha62s1V+f7f8UpRwYFpkjvXWYlDvOLvI0e8TUWEbUTITmHOTMHUg8PEUGM2IHCvpgdHC2wgm2oaWesEvWEOk2XOEYOgPWTWK/s4u7pFR7jYl8+VSFr9599NVUMq78hTZhLyacKyX8H8/msC8JE4Z2Bd3feGDuteNZOwnqJ3JGnwFZDyCZYVCByTYgGCK03ddwLg3W0TPRuLAYtYwuvTBik1Jk97TKKY3C4uYmRd+SHxzMst0GJjGNh7BZDC12RfyftYhgRMnjlShWayR9ilugevK/3GaRb0pffir5em6wTNgywASN7L3jtwLrXrmVxl+4s/ZyYiBX2NTeleU18a1DbyDw0Gf2CZL2BBv7P5wQm8vG63/3OL6oRO1c6cTXqZXm5fPxvkYSE3VIbCAdzYlDx82UscdroMZJbf2vrimFl6rM+mXPtu7sMnk+vMO8f8y17sJk0o//1bj7dj16yfejwxhoBiRuNRKwDRPO5uvOe/NtuUoJyi7OdzDHBAeVZMH0UpaYjzMPyRh/3CW/lvue9yT01Wp3kXirxcvBcO/OwC7s9Hcpu1+Rv9S6AF+u7pyZAvUh9lZskdIev5MKzKXpg+pyxCs1XSJtk5OCyfrDFVkXUkjZPmrbRumJpSMQxUeBCeZ+tj8JSs7sTQo7FzQqX2Un479XFETpaJOdZ0xwW64TatZuwd6260mtR9RaGgwae3BPlBTYbpJCuA2UR0Nj1XwcLcMGbxrSkZhVXCB6+ub2dx/5G0nN3lcCav0xctTItjS0kGwAm7ZrhTq8EeoWjoq4+5SrBjlPG9vdYat7RhHBXa+9a8q+UN8fw5tPNpnP3peocW4Yd+pqxwGHkr7/8OMA+ketpSy/iO750z/oHzyC1/LUw43vG29GavmDCxB1Nk0NJ2tE/2t6SbjQDj+jyHuj+nOWdxSzzsezlKy2Jfj6LrEhZc5Lo5npt1tGPUeMQmOHmnZ3RkqxZ2y4v9dMf3rKjtKAjeyVE7aW5NMjLAt9FWgPleT7Eri2ZDT74B3KThcdRI9y9Y4ZNLLDykk5fYgD5ZRu7awh/jvsl8rBkIhfOwj9p8WUv6bsG1k0nrOEsbzUmSIVDn8KolwKvhgyoxmXnNzGNodf+ib1chNbniaJBHs5KBF1tilbrM7OwOte1728gy1NhTUiSszMxPcg4/M3D0K3T5+P1kfEhHK+5qtDY9En/+GWt6vmlcY55CKnjaQkzUR1OlxcCINcYSGM2IIDhPKrdQWAxweF3zV6vREiAuvNShpoTIvLtTjjFKoYm5DLRnjzkDcqhKBVu85hlcNeoNWaViiGTWOfXXtnzvgOW/7R0kw91CYjp4IcCmUqVTU/qKspLDaB/LsJROQ+D1TSIQuCeUIaH8f11Jc9twBdfxlgoyoiZk4RrYJqZdaUCxyjuCPpwf2iwLZsswk2PFBeE3RO73ys8ORHhgIv6rQFQWLKXlxtMLegQCbigIh4mBVdqTeYm/50J7XH2gkCo4UgPWoiZEI1PtA9erjmV9jJN0LV34Wn4rX+1zxGtvmudQnnMa+E70IpWtNlQE+a1LT6I5FFRO165m7R2k4pW1f0UK+vAXJRGh1D/vQbTWeGebqKeMvu+NGu7z7W+0bSTvdgyWPfC4RBLgONahy4oTlYTCaic3xO5bzlY/s+rNb7uC8tJ+otCZqIiRokNne0NTAA51n4G45uTwK9UGcd2nJEEXGbvMcvryShLk45pZqaN8/in4C5vaS1Ngq6VJR41eL23oPrtd2mBQYsVRP0T9cHIckLXjkAAZOngz8B2DiXRmkYVrasYjqKOqIG2rigbDy4aTkYjG6LJ3kUjHV8jW/LzXLKpwQftJgYOMy0MeJRupiFStWidx7yvqpvCH/28kB1vJTvkhaUWomEZYqBDsdcyv2zetNmtOy+n/OFU3KLfc2cQZcC1LjxGiOog/O6IVaeKeom5pjgyOzeszdnA7Jc6tchqxJUlYgOFsCC0QZvdBeKJOyidwpXbv0UEobFjwa5UKjShFKMeuvf/YRNX0JjpISfDAf50tVF70rNmsb7FVcZ7xz2S+LOZEdUTBQnxCb7leJpw3uEQkuVJOjlvfOvQHJLZKMFGRZlq0pzn/j9Z4HrzCExsgncQtWwlv2X4xU/ez0/XVZhdIm3SKLvn3NsWeDKOwb9VZbWEtlA0EF5s8pt7AqhkDLUNSNp1DZp6xA66AJbZRMbiQfkQlv0xvKoqP5y4yWbMqSv3l/nB/sxaSzuVBGh9qCnUmM5FCZo+KsmDd4rVfZfFMN61V65leoU5tcIN2PZjlF9UZzEjFXCJbLnK7lnvG4aQXpa2mylUSzN4XbGm0UzTIt6CF1aKdH6SIVY70HQowdHTW68H4U7O3FIta/O0Q5YOwPZTMjSSPnHgvfcRJw0s34s4TpJPxaE+GD7a485g9pKPtEh5oXmJz0m88y0KxJoLGtgXqG4NQnWIpDb4CEOGwtRexCngx7201lkS0k1+oeUocSA944PDy3dTkYkCe/eHLm0HIZW+CA8YaWLfWEt/Zzq/NZCvbSTxztxi8Fcx367XnzSEyA+Y8dXJjvtIXiss1J5pr6M9KxqANeRbBeKKKv5yxcSljD1q1BctC55BBABzTA5mn4O1ma8TniLijTd+kFrolC59LlXcP2l2/NPgGQNC5aS2OEhthNjB7bYAgyFGszP3A4rI6q1yr9r6xBSlpixFuilU2Be36ZwIPXbN6RN3xZgInYu71I4o9Fi/RmF7GISPmAyIm2Di6Dd3dmB6lyJN4aXe3oPfLzmUHdBx66Ea6k+pF5UHjIIdlSY3rP7RuVybyJqjmkL73c/0VYgRsg/uaPilFu779HgjiYjLWUxg/ZHNhMsND8ago4syzAk8mC4Cok3/p3Lcifmwb8XBZ9Ug3SL2fBu5IQkgj3ayxKOcrQSuRX7c6Pp/Wfa4y4MTuizczF+VpEDBAsbvo1ZL3iZ48QBHkXSoBE8JkUmBmkCN7q7iSGP+eZSdA9SrCJDGkzHHgsRhN6RncMwsB4uw3JP9P+DHZQ2fIWi7a1v5RVIGCNMljYSTTOiHKy0rlvzGqK5aS3G34bpfXvWsi9kriE0L1rcIyy3mPQjmG4y05uiCdQ2um/OzErqhwfmxBbbiLYIR3z8CMi1hYdI2u4KpjSRXGYtHg3mtceFGsDa3zV3OT64v84yXPz1tA5e7qsMX5T7SI5JpjbQiz9Utguqi12ElUwE3nr1XtvxT37kND3tMCksiAdIiFKFoTT0FtEy8poaqL4cUFgXGLo/BPEPH8otrh3YnDuaH595fFu59Vz63GwUr/Tpht3BbtwNmkFk376Ji+1tPuT6B31KIZ4AhFncK602XXtVIUsT8sYEvcNDmCC5Sn5OVrxzRL6LWNaauCwkludFR04/Xhz9BCpHmKzPn9ucjDxImJTDOMbIjzvj+H/sPN4lgxBnJtyRfx/cKYgk/GZrsjMehoLrNp/v83HhfL9rL2zLyn/dHdHyGTAL64eXXhx3H1sCEpbE86Fvl/33ii1S/9OUI1H5/17fS1ksLwJYDY2oYLE/y+gejj/Bo9ZoFaEOJwywlyVHZXO+OGJx3a2NR9qa8S713lVcP4YIHl6MG3kZ9CDyzGHO1Yxuh7Iy8ehXKmzPtXZ5sjdIl8LbCzLP6k8vtqMfdswdfQfyxNQUD9gmbl/AHiZ+oSp2tkaP9f3Xd2Sl3AO/0oXk24Pm2SIssh3ZJfoP38zKgITbdo4RJvXpsMQYa4ZuQXkqyoY3z2Mt5hsH02ggLh6/713kVu91rpdmfkgDktyG978czQktzIGu5Rb3LmK01HKZ9K+GPRzoG2tE7qXFMBT0kj2uhaUphv/VcwSMjVNHDl3dA8KCchHhxTFZHi5wxx1FHXUzjvG3lwntr9cnGnf6N8QIdZHPD3D3OfasRfoWKT2COmVhVxw8zk8zCTkByMoWq5HmVyT4FR6O86r+n3AFqfgeZXc1gPFxECFJizOcWhfTnTN6jHNJ6AzSCP7xeY4GgyyN6TALz2L+hUNuqzd4J8zKmrBMriZSs1DiGRWpM3QpIYun30D/9AWwYhD7nV09JfPpAx24P94OkkR5P3S/AtZwTzkiLqY2o4O+Ye6Ebn10t0cb5daqfIoFUZaDEikGduLEaO7uDZKNm0NnNdUkWu5eorRnHk7kKZi95pWler6nIHmlk9Hb4XZQZrInzxUgTaoN472Lac/FXxEanrTsU8xVI6dTwfC5b5eba0KrQR/mJ0f7Imm7kgg1V+QWO1swNSKGSbeBnBEToPV6J/qZ9prni/szhKSUNLP+abjLu36VBcvEhm9b11s5ASbRg9kjVivMueUnJx+8fvhnyydupRHKHeseRqTFQYflRHjP+9L2AgIgB7quo4K9bDUjB/uHHSjSOvZc6rVqj5Bda634H8/6F/WsimHp6x/7aWYGXqxWXI48t9TVzY+r/FUeRE8HmRE9MbPEVrd/wP3qQXS5SDUzERiCaPX1x62nIm40L4bL8j818s2NwnQRFwBIzOGos6ZbrkY6ZwzKwsFEpKIXMWpIapNDYqIFfPN3iL41CnXHukl3qlvSDXCZEBhYPfDg7hSlTn0R7liuchl4KPzoSKjsM8rSu4Q+kjYUJTsEHEvNiIzSnWjnWORqJdqMkxjqsZZDvy0lKjmHTGJb00rK7Y3CBZVm319ZNzleoYbtm8t6klX0rkCjpz2u13++8ncC731W3reBpLCNFEkd0Do2627ePH0Unh06oZ/vu8Ivd1ZuqRL2IhzPrPKcgJtBeEIJI7OD3eiUUZdAA6PTaJsswWfuiXh9pnLTO+oPIZix9nJh3Cwmogv4pXWyIN+i49gt1uAp22nM28RODchXQM/rxzr+mPg9Jh7kumK/bscE0rhQxMtQlLS+faahwtEpp6hgjjjzZ9pjkotHZ7bh7WxORbbIU8e39Oh49iWW8oiIR2F1ElzSKn7UsiMzFh3aKKJnxn1i5PFMbvwxnag95W/O3t8ti4R8vs5P6MJcJexxTeCCpYUNgjS5zL9Loxogppzm6UKxsG6lUzgQPgodg3u115KPY9idB3ZyRWt9ewOjWJ9PceBjWVJ+3cSwtDSdyRClp4dFGPg0FHWjsMRuOgGWJIlqu9MKqj9EmlE9bPVD+d8dzHyMuEteBQmH7ISHOOTvR/3BftgP4qIMETMHVo0CHPBp4FVuReJN1BGatlLqIVBEPmNagagxXw9K7GqLhyTGVF5KggrV3WIB8P399MZKs2KurNxn0D2ptfbuPqim5moXE7kv7Rgpl9FCUHJM2/he1t6wNsl3d7zYK8faYAXBndjcfPfm02bCDyiRiWwuMa/3tLPt1YYKTODCBpKN5P1xiEc3P5EelLBgg5wL4p2xwyOBZ6xB8ydnvXAl3bdSHQgJ24ymFgN5of5L24RoQ0MyTwrsRbsJd9PNy9ZVa7o2Ed0vFZVPCW6V2K2NpLuPQjtAlRwLaStXyT/0QfF3tNVZG6HGadaGCU6EVCBRomWizRarzATQpwf4Bxbo8YzA6ly30kfCAqpyVFKKDkJQRjmV0m4wYGK7mM6Qa7GX6i+pXnV1h5fC/1MHjZf0Y5K3B10P7bbgQurGzReOLby/OuV2flskN1rNZeaNmvovTPzTRKyavfTWX8dOn5hHqnJN0kTBOKWPTcLW6WvXrMFwkwnv6QeM3ryarz1F8SW5i+LxGi/6uB/tlQUF3u0N24dbuLomgp7nFRMtcAjnGdvbRfH3JPkJh47bPqWK00A3so29zKh6moxLTZQZ6LM9MhhfOysmdoJm0czTcqWF6OhFb+m92ZrOTgVsIo805lrQYRjjK2sEd88m+Xkh/MJZQRtyxk/l/x003YY42poajiWGpD1jqjXA1VI+WwTCEL18/Icnf31E6JUMrWI/X3vQc33pO+G3fGNIbZWPq06V0KZdUy+osyKYU8oDGtmrdgtsD0KxDj5DpurO0QToQVElkgZQcmimaZYeeM6JAT/vU4MnD/JJbNaBIGgXbvz0dw37P7HYu25wOHWlJWM5vw7dguKCxKiGt3a6KnkwCJXzUOrxX7mheC7ykUM5SJasiCWaE3ELi9wlnq/zn47ie4nu5x/xl6fdId/le1sLWKogH4m/qzCuz3XvyS5VlHVoNWduDNgO9a38Kiq5Y+ONXWN0N6r5ykiZafGEXtmkGMy2K/oRjALOuw2hKAnyyY3MR5FGvPZrD5lxr6f5Y8oSEjF1W7cEPLqqISapqqU9hZsV860h9iguX5Em01vgzD8PwfrB4jQbS0+zW/Wc5yLKL6qDFhKIpN/dAoUqVhceDpN2olOVQ0QAcImDlAC/7omOgJqkejFvOfKP5W1XCbJWMo1aanG3NZEgWj0l5j/4e97iXltunRJsVALKAd0uyClgyftwGklGkhjRCsQknPjQ2IGC4qZRZ/P6j9zHJsPWnNfOzMYsUctOMbs0OZvO21rLY8kpSWVOqO3XiLp/9gJ9hcLwFrwKhWc7790TplmTCsTGrOhu5Ds5Pj5ohP8YCTdFO58DVaMtxDn5WSeigK4DSXHpTQCkrTCDuXtKIn9fBPRlrIxW9uFIgqBtyLovdSJ1iR32fJ45nHaSDTYgmdvsD2LQ5VwpiPv0WLNyqC2ZFv5AH/IJyJC4rAlVFLH2oKRE2Q9bbZYNSPjDYfeXmziCSbQVReGW6n2haFRcwqCd1JnnY3IXlTCwL0cBPS5TYn9zW310ftsn2TPvutmZ5lk2AXMz+hkFY2aVcHDKj3cKAqY3Vfr5h8c/toZ7PXU3G+SNslkDc1S8/J/W3u+klY213Qs+AhFSH5gyJWWPhUAynfAfUSW5zbJNUZg/LX5CLrN0y/mgIsmUW8Co1vArZ92WH3Pv7s9rT7aLSRYn8Z/8JjX83YzwXmvkhbPAbbC3T/V6HHNiBPZdcRd/WMAeOt81NETwSgfCtpb4zSYMc2F8g/UeMstd5kvuzi85vuFP/uMHK/IUH+HxFHdNVNQi3SPJSPd7JB0CoJKMkDlPVB69vA/BX/qI3ms9sq981WAwV3g8DkciERyJzyHQDe6h98Bq473iQ++7ox8Ztfk/0pRx6b4F2oy0h36mtPnxl1dGYXgW4iYPM2w8KNObH5T6CSTYp2xkPgUUn2kkQCfHyLWKab1ObyfJ03IeTBZRlBUcx1JZrCgxCZjVilbV8Wv1HFHgqFlEQm1KQZCQQDLxP21KqQiHk0cfj10+pLjV7zeEQww/dPb1h9a6a0U0HpIStbS0/3VjayysKRN80C4rvaRKdpqpWb9o5ecqEWug4fYZzvPqdvLuBtSC81uzHcJqOYb0IF+9+EBiXejhloKXemB8YGHLEw1rg6Ga99+refnM7wXP0oPlZYmkmYsFfmnjb4OraqOeKcQuq0bPc1WEl/k1bAEtHqKy2XB+T20VfR2Ol7j9HEjyuR7Oc5BRcyQ2IidCc6MAlIRMauB5Xl1oWSybtEwqXg+GjUkCKW8L/yRfOJsd/5/9IQUagGR021j0Inds87QZucZqg3YzmqPzHvh9cUmmvBLduqJdXsBM1cy6klcrYb33lAtWNutlZ2f81v0KSFYb5M3FPBfdmyxjqJQ9kKLeFIBeGiR/JGoFTB7lDtdqK3TMoqxBQm6iqL7gMB4Oy01gN4bnmbbLGYGy1NZe5d3eZL0onSWlcv95sMuW4e9Nq1oTLnFTlILpc3iPo+Uu9ai/DUnHQvGhIEAuc0/xmrLLVoWaWUUo5oAZFa+Ujs/OllmIEvLguphwogd3RnEQSFUb2CPuM1YRll9H0VEqtlD07f9Hb14wXe03LYQaSacm66J+ZAKZf2AQ062hwJ3Eb2oqaXHUwbuTEr7/0un4mynRaCRkZY+u4nQbzPlzEJWRr4iq7SOfGu8gYLNTe+Xoevqx8Zj/fGGT3VhvEwU/OBOdhk4DN9YEXXX8djapXC2ZwtIkONFKQetjNhG6OSzocsELq4JarLaKXiTfNzqOpAnbG7gDTjAS8DxbvN39QmNxstfiVbavrfah/y0blTCE5madYYL27qgNyTdYMcD5dzZLl8TBuk+uWiwD5WbJmZc4D5CZ/JPmOzkBsHffq0spg/zQqt1e7xsLtJSmTfbANwK3mdcvgNvO1wfsOF3S/2JU5exLHtuzgYQ0lJfk4L10DdTyRShCiqZoGzoBk6CZJiC8f+MyGzQB93OjjIM66I5QFJMNgQkZs6fJWkbXE6uqGmoSMdVNU5GPZRejfJWhpkZJGmwYhOVAV1/5jdV2pddzTTo/8xFLeeLRaMhmm4APuzZ81iKx15TTghdUT710+mx8QwMGY34qnVorNeKci3ifw6T7kp4k7QTYuIOAYerAQalrU4s9hhf9D0SlTE/uRZtDhcHlu9M5y7uDphdxgcPkpm4PerIdTQ4KkwsBx1Ts/UEQrONhn39f4x+pugEGXugNH4XhFzqFn5LOkyaI5bfuQ/5SpH3O2z37GSDDYyE3mOP+esC8bb0k0YZaaCPrgbex8aSB5poZ3qn9+Kk2RnIAPqv4yatfmtEcNz2K4c++SPm7G6hFlrWjqMgK1i8sqNhnNXH8VmvdI5nMmrEL0uXCiLw8vcPdLoAn1kgX6eInc5dp97+110dJKt6gEFOtw9NtVWP9l3kSTGKOVz3admpRdLvOUaXAsTaRQf2sFF5LB7npptdn/rC4wF6vvqnmOEj5uwVbxkyM+9iqBdrCnQo1coZ0b0DsIF7PL9U+D9h58wdQV9bkJc1fQ1N1RBx8S/6bazvbH7VJH2s4fScOo0yNJTwJUmdMqY+V8b5kaE4+0UIIQvNYd/TPSlO3wvBQB74FJbidhEXpy6v5r+0Q21ov+GhhJWFCeaRcdflj+cEyjD6SP3mpbOtjAmH4dNL5VkRuJcF0m84capbVm7eW+vJDTRqEH8elOe3Na9gDzYQSSbFfbZG/xyT6ZADh/N+lb5hW+263Fu36/EcMa6tyQADb2ZUdxnBXg1Sp3m+BaY14KM2caZt/LvYIj8MHV3uKHve+xZ2m/nIduvsZSEipYMYiZnGAw+yFXuSfRKpKaMXLLRgMNxqi+frBWhA0pIa2kc0Rn7i0ZseElxMhCTN0CYp+hr2Q7LRVPPLOb1l7oflcJQpNFsoIawFit4zc7N3DwZ5dlZTWZCWg/iSKwro9jSSstN3E8YLXDBfxuNp1m82ufHLCpKA50AGjaDg+ERPXCY+z8Yw5lqA7qoxzIqNlyDoUR90KSbspMFPw6vX9e7SKdZAmIInHzdxekQVXZqtj/Yw+97K287BMxnDZPyvPi+sfThE/GCNesxO+PyDSrqPov9F4i0cUhNgCn4Gwkw9uRPAi7v3M3B6p86dTzlzcpAlkB/CuJhH7Fhbj2f7tIuNa1TYb7GjlyoQK/ZppT5PngVquE9HtOJdd85SYttzBOPeM2nR2dyW1cQRgIOKp/TnnAj2St2/Hz8wATLKDvVvUB1EyPMdhgHYbVCVYlzdw8se2ueTY+PeXWkHilEmZT9bYF90jbWej70LKsP8VE+4PrHxofr4Y4/Df5FJq7ukZmcxi3fN8Im3mE5mLykTclFNfz1YTroWXod+Hsh+lOXLMbBcwkDw/h/BefOG7xTvcYX2n804S1Fbt+2qZ448ZBK8i0gwOcw0rLQ3AiWqMWbmLUd8HgvYr2Z+OlndLfnmADKmMBElySau6+UNI3uI+ZYG3KBU7SlnSrAb22xNuD18bd9/0mP2FI2+PPTtt7lVzMlf0h4K4rCSCRp6EqBQ0Boz7AIo3vwVxigNa6mxsbsJ1xW82bt2XDm7/es/WBMvjhndxj9XGKEb9tWxhUGIJrW31ZFxHhysLG469pvphxKf7T6ol/vnelsOsHEqkKTXVyPSRJHkn6N3mh3dBU5vN2arwK+L8P07SJjfCuQfUOHFkvn1tcWxjbcJzNNyGmGqcXL1e1QUu1QsLSKU6FpwDdhiczSEsstbpIAMsIdQLfYxZpZRqCYOxXPOcrVTupEfBAGbrLJtwDzdjCyv1gR0EWzwLAfpLqIDFwIK9A6myBDjWwLDr/EpdzYYhyJeUQQo4sKTwjP66wOLkr+T1lFGRVDWOxqNsNJtxa/72GVdh7i3K9+mgiZEs+cOLk7WqOxMPES0TGUADoOrvejQ638eKaM79RXPLx6ej5rWaJ3C+nP3N7w7IyJhABhkuA+3oKIxDdjwY1bWckThiev37aemmMrlG3rdICv8saZ7/Kgb93UN81ar6cXEOSPEOBb0nx2k540wkmI9rClUt4p9q2nVs2CUJI6v58qZZaQ/OxUcgwrs4F4vQ4DkbriMB43gTjx5pMkMzCN7rfzLXWX6ZAVs0dsjYOtERGKtpgJyteMFGO57rUNqWV/GWsbuy3NXHWxj/5BAfiOM3EObrI+BAVMT2XXoi/qs8bt8H+xEprRc58z33/YJ9dGVzYpdTHuTituop31VxzkRHMStyXHL0wamkY+8DwscGjliHkGUz7xmE3ShS/OBLQV2hCXI95tX3etnCAf1wY52DfQ4xA5J+Dw9Y/QeooPadnHPmCSIM0QPsw+CDWu5ZfioyV0KZcRMBmDKQMbWi4h8NiKCxkT85ztvxE+L2eyS/k4StEvvhwREEPoZwKcgH+Y3iOuN+pklSQlnDAMN2LKgvSSsrco/iixVME7/391p34WQ9a+UGJr2wc58XJrsJqjaYNqRBNwZ5B2yEcI6YcLc2bEsse269fugHPPj5H6JJe08Lp331/JC5MFp8/ODVx2cTKDr10g2xvTKG7/1m+/KguGI0FyqF6eCzevuKyp8UAGCsM5pdjrfHDyWwaibKD2EKJyMdNSFKcwe2BWib2ppJ0iqBXBbTiME2MSiuLTZygm95HEXlc3WcIjSWYyYHRzVnlI0IyzPLKbv9F3CSIfVsEOx0IwMo9KYo3Uzr9FGXQ7nZlq2Gg07VMmoHoSoJk3X+MfmUvT2qKFYqZeSc2Be+t/6TLuPex5/fcrIZ1U/Gfa2Jdf/MvzWcTyFK2/Jtwgq9PJ3960RFde7dfpj120mp6utSG/SmKifgzoWfzLq1VKAYdvrI/BFimrCXomMsgX3LOv/l3EkC/Psu36BlfgTDYfUGOBwOoaizYTkamR5bCc1aFzoEY/Rq9tSHHcwqiJciIYjlKhCZXWS4aQznFFK2tyQDrSWPOcZHBQXMZqP4Idfxbt/b98XADzSR9D5Tz78c26/R4pqm68WN9BVDpykegocB7EdBqU28DLkHZe3qjO4c6NIOjAAZktefFH++HfmlIsU+GFSm0LhgkmCt8VZWyeE48TAxZXY6xDkccGIRtedykRnIy15iVZvOqiP9WTBbztZ35/7cz/kwmEcS5wmsdj6KjxKFrKSBJge9Bmc5dBZWlq52lj/ytoJcBdV1DPXCA6vjNRsX1OqQVlZPaPsHczMPpRfqeFTRQGus/NDaSTJGm/+RM/ODU4sqqb21UBo6g9bCtcx6+XERozW5lM9M+tYt1+ysFCiW0ccejrb7HKNb2wXv3+zHvPcU/uv3J4Ia6xIkfTO5Utn8wvwpjZuLqS/hE7/YxU/7ToXSbrSC0KMV0DCxSsGlIVRRnF8k8gh1V7Cs8Y3O0NhJfSqoi89sZFUYwI5OLpAuc+B3fc3H/4zK3G0pPR0qvDEQdSEbFGnnbtcFimeEXLV6R9H72PzmSTgNylJP2k2/oHz0wXNgtFJn9SwbYBeHRNFqAdr46shrZX0FWhMKwOPOK/Mql0IDr/oibDs3pvsWtm1PSy70htpvkBreH2k0Yxv/AoBZJ7wIjEFb9argjTlT3JhwhMsChdABVcTDii9DdFpHfwGTcwxmpct1jr00jEp1XNZFPAgNwOrEjAbND7TpZGhLmO4AKF9cvNOcaxIdaC9dkW+gOe7ZNvpVr2KSqBpaVac6NjqrCyNSQxGOLMNELdYVSPKXYTnLGtai7+6pgFVxsmZR47ifb9tc004F1cjDDdvm/j/ggOkfJlzWmOEOu+iv33ifA3J5G1EplhKNRpeQLhfh01mD7JJC4GD8x3/Z5e5o4XetRm7ze9oA21n/Og65oKtrI6gAPYO/pCmU4rXrZVMRE1bCLWf7ZbtdvtzN9doDVoL25FJ74V53qNNTcDAAO/YKqMxk5Kv7IlWWOnwcobPKLS5iPfn2z3Kb7ZtFUUZo1IuS0Yrsyxtwxh4BvA9OTu/PfBsEaqZGLpkPrg6+4lb+oalriMHxGw9mE3McfEw3/n4F4xqOj+acpdFmtfS/Nzpj/FUIm9JlIHYAhXHYhoT9YhToxp6KCS9fas/J8HW5X3Gn/K5h1G2uvytKCq1s1OJnJYldTm/awwzjBL+QQCnlxuUub/UmXhpIOcluBXBKM2yVf/w5Oxwley24T6Xpl15h1e8jS+HJivhy7o1HvrxzrmA83wDH1O26ZqX806hKJH7JWvrqfmNAPG/yAM29gmnaRkCQDuhSxNFpmK7wAeFNxO5+/Wh/lK/sKHau/Vw6ZtGB2jSHwdhjSufSDEjx9/3SvD3raCuX4H2gpTdiJjHvnrK9lDiml3uH7/UOr9wBxcy+YLpxiTaRqxNFaVGx9IKO9zzRT8lOV6r3jToiU2s6fECSxtdbOP5Mt4brZPUhKfAAa+R0V67e7el+l1ms0zFyCFSm8BCWrCeP0fFCFXiaTBCpLWQceJKME5GWWvFUnNBBNWyAMYgjeePCvr4699Dxw5KHPdfs/r1gFmAKPv/xjrQi6OIOPnaSEneERHpES8+I7VgAExEQdZP8O/dlj6sSpJ/e2pyiZNQEA2t6IXmSIHE6y8FURov2yF6DT5FXrC/6YXF/OEpXadATOakXnfgWx0CzSXPh1ZjmvV2PNo2OBTqbWxsd1YJVSVkDcUovZJjrKx+0c0q+ODqM7i8LfeRgEbt2/Syz5FUewJJ2eO+fFPlO53xYWOSz0eTQVel8ZlY1kOs2pcRzo5vOwUu6uMAI0ZBBMltAYlZHnEl7oN/TtA+CmwGxz69vO8lDn48F3CaUMEgVCevKcysNI/NJ/2YRTt/EpO2BiQ50lIkNB5ZKfbZwjk+n8DdIOjCWORxsW1ZBLmtINscYNRtAeKXQPlA3AK3RBpT7cv5FGo8M8NErqDD9Tny+09cb9Lgb6noaPcn7CaXfLoEs/CaNfvfI+So1QwUS39qJFqf9PgU7OYaYda4tomjkmEkKP4CrE5fblx2X04M/hmN193X+8wu/LyRqU49/NZRuXZj4xnSGNRg9Z+FAKuDgg9ue982xXNIiB2+DxhV3Sm9dq6Bp8e657mlFNJnc9C/qTOtf5ij1+s43Uff1+nU5z+853eZ/w4e63rAKDSBOkC/DQ070O8ZNOHpe2ZJCWtsjwP+123ZD08FnrRLYqdGI63iwAzq+u67nURS4BmD63R7BpJRE253XI2Y29UuyJzaGXd8cJP07MU3x3kbEvPMgQ4HVZoiGTJWmClw/OgbjWPtwggZRsbTCJTTQPoc/YPmzYpjmbG97Ft+5l+EGZSr7ZVQKlUU6FWyI+vRw49jTXMj2CnbX+Rfuyc6oOtAAv1h/0Lv821R9Bun5LuSxg3v7m8p2keFtUDM6hXuVKwy1QRsfQa9lTb4G+FQGanx7d1oYG6XzlIg6NcczJBRmIXoQm6Lb8cbVJYiCwSAMArxWBwMTJD1znbU25dYKofkV4+FtUDBInUDCUTCIY4Zy3QJQQWNsDO0lJJC8R44iHRJbrSo042sJ5q3ZZDNcPNQ5ra3GC/ZJvMjrRJF8sJAEkHp289FwqngT+ECLL5xpPM0O3PS1oLD3f2SVvvf/T8T7iJEvxP65ryOvIWF9u15P4lqCdK+BWZsQOOc3wHNIZFehUHEwLFcGmqDsqcldy5qaz1Zu8l2TQau/V9ub+r2mndZnRL04hj7veZk6rPORuwrBTUuUWL9ThhPaEcDPS+sJSDN7L/b5VJrQnDYYuhz0sxCbF94EHMuOJkuYhFcTa+fP0X0UN87lf+b+pbvxTLLanHynLlvpTc2I+1aSkhJK5wlfxbcy4MG9jjz4M4jKoVpyibbcWNlSlHYJ1CqXzVUWvoXbK3OTa3LJUd3VdNesoAgKUoCo0iiubElXtp1Dff3A7/gA7Btr2Wn6PKTMh7vPG01YxB0qQojdzyL/5ccb8Z1DZnT2WzWtBxbKK4BN7odHQKzcftQ3Dlcv4WGdo0/RB0oDMFPJXVpkmqjVgSjvJ35KE3FR2NGclzvTsw1ec/csfGZs2VcOBf93RkEJ5+MQNq5vyJXVJ0fDG7UDwo33q7zR5vTXTKU0VfHYKTcru4u59yW3qPGJeVWIHKb025u1uN8mNAVukfb9rtXy+lcgoUAxe2PPPIuZDsrirsYqssOlL0T1J3413ccITt067aysg9Jp/lZL8ZAn0u3vht1ZvU6FAiRggYa60cTkg9yRJX7gLuBTXSwBFSHXym+oDZ1S7k4OZdSfYASX0qT1pUH+KWEtTW1Te3WYrIEZFBPknicFCs2dLCmFrMOedYkgupyr3KjxpNKR/jHhy51C7U8BEqVu9wLcavSS1ibBT6EBgh3NijLmJ41ZmYDSzYzYmytVPe+Qfo8v8Pi3GwSKt6ZFYykTTs9FUxgFr5UqJZBUBRQf8fVPCiBYzaEDMKzCEpQmKH/wEcxzGjLbFJLbkhgz1UTUE4VRfySX333ciH//quIhoU+1KWmP5790dPjwjKtync8vyQfDSKjwduAVxW93ET3fW0jSuaiUBMmy4K4RiAAL4Yn+45Af6U3tM+vCFb1PGCgynSjDRT7ac6YnyWzUk1OXqM6xq7tO2jJyOd7sCBOdSAT/vLgpJ0QxcQk+K/gFKsR7qKGfsjR8o8KP+k7WosScA/XEFpJVorAV6ZUcyakD8Hix97Y0sHK3kpb9eKbtPNp2cH9yFq3roqtfPf5682hfjK8L3u5BSj2Pobs8paIBMjenJBPh8xk0T5fVZcHVn6/py/Sc9WHdgXWE/K7xa7FIqxg5t65NhY5TM+RP71X4A/nlPvgzxi7gtlUUqf7SRvA8LmTtmwSK7ug/ZfSnLKkRA0s6kZsK0qkH0OPqHBCbRbLfWAiWdx1lyXgbGUZUq0g7WW78cNl54UZmBomeZPgTOCVpFu4GXsOJ8GGN5IXmG7IjoaGbeCVyoPlVtMN3RX4s9D5B2O+GxW+KwUnczhp/MuqM9zJ9hmcZdu+DhggWM022D4a6PCJY9PqQJ+i5re7XLONV0Hl8OC4VjdxyvXOzuk5k6LV6unfP5VozBGtyFsvVOswiueuc5w03XZCELj///M2312RMGDGBd/5w4oItt76TUToW09sJoTAL0ZtsSL+hczemrttbi20dKWJNU2jWe4UBQzroo7s89TgRTTBRrjmmlx8ar7XXH3GM3KE7E7XytHNwLjbgHFC3OCvCbKl8k7v2UiU3dcaQAP0nRO56P79exutZ7ofwapVlOFcggg5lLIYOJoqieqTVUIBpAiduBBlT7OLa2nr2QE4IrQlqHeVBRwjO65cQrjjrZhEbILaKVZrDjQ9UKAv6S6z/6Dno5UozzKoHeAyWaRVn2Bli8jKMv2ZzBZT5OB6t46c6e2REbF+rDzN7kpIvYG/lC6FYRW/0sz7vy7LXu5FfWybFBsJdj5sBIVGCENIYkSgQ6+4iLrbFTEbQlcAazH+SNJNwNgye7nfYjcYVch5Vlso1VDxdAoOX2IfYfgOpX6rCQYdnAIeNjTSJNRcgfEo7IBfaFh0ELt6ppO39M8VNW6x2xscawc1/08zEgha7agzYLn5HDp/jeRuvvdCu3K21z1LhYIcozB3GRdBOM86vxQJl9ckNELqIi6jJhh1rH4e0/q7caXqYfL++ItNTSxyzXM3QdnE8QuuXr9Hz0bmVLNuijpcEKZ7nlUNka8WT3x9EcaQHUlNiwXEQGyu8PuXBvyrRPGycaZNEWu0pANUvfYw2+QGHvw2Nlub7b++4zvRkXG8sXAiyGYuXSjao6DAlhdz7VSgW674PJd7ZhaaXzQWR+nUzHh53w3B6LUUW7B3Wsm4SGnq3d+umfnkNS5tNp7oy4fzuQxA334WrthUifyBN0wG05+yD4TswvDfQlzqHWYYuOzKpMZnx0shzqRe+XKS+Wf/rGWWM9lc/xfI/yDghnD93+UXcdsmgH2582Vbajvyt4p3Ue4CJEZFiOIoElZkHtBEXoeV+cYApXgh7LRxLQuOIeJfz1N2lh9oK3GeERpeo9cAzLFbBYEYfjYlcdHLTroPOiY/SG6zBImFdKS9j3jaKnsfRNQ6SYC3xL+zP05wZSdWRANmDOb8Ztk8eEWPdl6Fd3CkGFdE2RZdkwp2IUpf1lxvKvXWACriKVWFodGFLz0MzPcqWKFNVIKf/oex44Bt7W3kbz4Q5IYFrMucGr26zFixp3Cn1YvvnzcTVlWUm/yYv/ZksVsSxOX6Ejc/lOPoqeUYO62sX9j+D3kJqigOylt8hDs7y9bkZ+2wHa4xt9gFO2B0v5BpcV2VHrqEpbcgTVG7TdksZwKVwSoniqFIkFwCnogaHFYQN80vAJYLY2PLlbZmtkjAxuPvrHD9PHINcF3UZ4HomqIt+7IpClz5ZdtiNM05UeqQAg4bnuO4i3q1UUnF9bd9KKocTKP19C0kw1zZbbBoNjoCoaP43pk3xVxMyQd3PLr3jiletTuhPu4K+8XyDjX2w0+qLKZVvybmS5HP1FXJ3vldzN1vxBbJWQAeYXxBYwQBD85O+2cxvEJ71UnkpOVzV3ZAyu7E8cPzu6YlG0C6kXtA9vqxtRfPV6bOfvj1Q89uPd4TCSk0HfRDaoYAQQm3K4BivCIp95/PRB0WCJqOReFvvwtVacdbpc7GM0jYgnCvc9/RAaf4cvYQTWWmUmxfex3iuWsEB7O+SZuNKt4gHPgAiIEWBaukrAbvXqTRvDfDP7ohK2J5u2HX0qloYavOEPOtqoJ61rJfrN7yKo8puaFP9Zyh8brBu4Fz1nRBZ60OgjTWaxRgJYZ+ciLQPjDn+ZFuD1/B8RjRdLrJe1neN7F3f1TMeMz1pR4uNn1grWe2BXdQIxBOJpVwGvfOX6uYfa7rCY/njjrUgTUKk0QAbiLjZ+KXruHT7fP12ywddXqi3ATFMY7hITgfBON4boAO8A/sEvRBEd0kcg9Gt2jeV7hig+dfHhj1b0Z11hmaXfs1esZiw3SzaV4O99idEsl20+axRa0d6dFHmydLp3AtqoF9UZg2TcBuJk81eaB1KSGozEVdDARfS7k26ErWDUs39ezaxZsPEDNS9m9orBs+Gi/qUUPCh2ljOVQsrDPesNGbRjqAUUnSHDiX6YcHIq+Cb/k2nTf1ALiX/sWsjrbw1+5qMoPnGy8kkNg2wMgABNQ47EdVYk0PQtli/wDOQXCNKclyf0s4dSUO9vv1r0Aewrcqc+EnhvXWunueeJiBhg8SB1ZeLwR5k4hRyAaR5U97Nu7qjkppV8cSxcwpLJxdXX7G/03s2ky+tg6F/eHWuumqyN48tWpQRxSvM4+rE7NrRLicdTZ5EebpbXcvoNKLRZlfq7MTbQpEVHXdqJ7XdUNWdlIbJ7htD/6lzEje2xVPx//INuJm98xmZt8gT5DesEX1wqBsbfHTr1EcSmTo+5XFL9Mmt4N9ghUnN6DN8eb4wkT084DjTVC60mKNffhvkdEjGvEzgPC8U7aMG7sBzk+TbQQQuLROcAGRResHFsMvfj/pNw2hlBC8sta+quqvaenXhRJl4VbUNt11FETbBWvCNslPPMXrP2uzG+SWLidaXd80bWva1P/478sx53I1CEdXdi/uKQIQoSrsI0kUUYgCedWoYP8cYkv8yMCfTh4TbEDy+M5vxrfWqSy492ReVzENAWJD2ERhtzk/CNUe8XsmEoCyAJSV1prwQxopVTK3ESKVjO9bPtjx17t7R3AcFp3g+2L6FBglecND8i9shKfkYwZRXKYCvuylGDvyjFknrvpS83x+XI/jWGdYR2bxP3OaWxBr3amq5QISLoCAlMMmsDvRnkeIT/BmS85bFA4NmTQRFZYzlgdBoVRy4rQB7d/LyIPbXn/gf/b//vHzfzEL9uDUG/2ijD3UVpBoSSroRXpL+Ri90pKb/qLZlAvlGPpdlNcUrz8RJ06S/wCaWUTukWAMOJJ0mR5FBS54ZhjVMaXCLezBdkavaYIUP8WssKElEiBu3P5nLO+KXRH16pOjdHRBamhfKC9oJfvFw234rD3p2lBLo8Q9OBfIGISbxaHiw/L42KGURgLPdzTTT1EwPuMVwqmQabIaE7+UwDO7vDp/toFvWPv+7Tb9/fb+meIeBKVKROncvpL37EAG+A6M6/KEPKJOD0zX8CYGzqY0oBvockOrCzEMLosWvXMDMsKkPrTUATeTPLMuCsT0VOl0/nZ/84P5wXVUm8+hLz5+SYSFRqyXEcTPSel8nTGFYJT5Cty9OyWJcoNTHU0IhyDjhekVOG0hcwBEd8kO7UKgpCgRr4ouA4ptdJYD7e9JH7e7P+UFkXa3nbKrqiWcbh3asb8cOZC4p1BPRP3YTniKk5zSNkOD4U9SyMSA8v4wpX/QvS0fpSekgEBdYxkJxV3P//1h7ZUYEdD7Stsz0RZIKeTfu0MH185AumSu9YfPjgiuLnyFSpkRwWbmdtiuj+DSTpmhBcYpBFRSMbY6/XyYQOM7ERpBky4H4j028Vv6OkWD4mA6B+YdikyBTYV1pg/khTy6IjO2YUClQC90IGfRw8tRfJS+sF3hyOzCc0bZp9qE/bMb9Jk2hSkHdfpXBpdcZ0C/t/Ddxb/X+r74nf7rOB4cGWI0B0Bi365dH2kl6Iu05t5b967kwAw1AB2QqO6Q21OQajDTaIVR2BN/GxJWY5bSNOVsRYSV+JhTL+nMz2xNwlJLVuUa8hXbkR7eiRu3NrS5pruQlpfcdBx0oDdAjrsjTir2QLDtkq3ebiN+Mwj7wlyEIKC6SUQp5KKD+P2WY8lRPGLzhwZL8VXEq5G1N0MH1QcAky0UXGH0YXik+iggHiopLoOjKh3crR93CjiWvjVlu1DxYpQBTedtnE2QaJzJJokuyLWSH0ukyFK6ZA3kn/yzvKjensL9S03phyd2AAZdJmT9NxKS4wV5YoONAZIzBUyCNOFHFdgZH165MfKX181m2zgd9SLxsD5ZK+yggqLoLG3AH3bDhozB2HWlt4QwtzXluxq5MRpIuVF1SdjdMYBblIb3sPRAn/uBx33BE6rGQDNEKTWJy7mnV6vh41FCEqAyeaTVDX+RA4Twp1Fbv5jrQL3y39+2+lboKt/a08uZ5JU0rN8f7/5zlyUaKT/WTtT6klGNZf4RjDoGAeISyNI6B34WO4Gn7ik1rMv5H/KzSV9TgSRprQI/1IXVsMYzcsPInT2eVPA8Mn77mVgztmKOXC2u5+Lm0niv2TptJ6MA4uiQ1LAMTW3H1cRDWQCvc7/BDXn2/wXPH0FVnAy1fPXAggofx9cOYd2cVwn7MhwvSehSG3c2/fpkq+1lGf2ty58pDj93vUxs7QWlcVuiE0OZhofqGh/Iuy4b+bNHIvp96YTakzwajDPuMfIuH4WDHOqXQPOMycYiLiMAvsmKERDiW88NjEGOJ9JbirsK+RNi6MbRH3gFoEm4vjWOQl32Qc91dM7IdRZnhrfODP8/l/aue+JvqIMZOstB5blYI47AdgLgzz4MY6+VnRceVNVHHJJX9tXBMc/n7t7z28nniMFucSw/jFwYUl+lyxNXXB38TKNjFdsXUBQUTjFlzUiWbap4RFfFq65MuW8T/TeKxpzSWFjVTpROibBgI2TVuV4VFQgcpUr5AA9uH1LHh+Q1P+lsaRHoKSHoSv1OAvma3KwWg9RxeRPhRjdVCAhu4ONy5vT7BiITTxSjYFzJXt8Lplw3BEeD001+F/IK0gaD05Vk2f1HnRdPYxnP+7dhPJJFasbP8fF7JWS1w1aJ6gYcqjddCkMssuq7dlxHvYuu4y//r3SztswO/vkG7/6MjExmsn1CjNcDzyd9w8ib709p5BwTuIZFxIh8ElargXaKBPuoLQECnOviWaKEayM/kEYf7eeCwECu3QWNhI6nQfngrEPjBr2b7jEP9k4w9GIImOvbx06KZzm30q0tjXkauIPUNGvMpvwGFfsK538WGFB5CCAIsjvipP6zQ6AWGT7lSwbFvTQXaoMAlcaEwhHEVcognTU1qfTesh8nXJA02yVpFLNJhqp1/dqbmGRvQTZeRKtNNbwOJz5Ara61TbWGK2yx72OH9mw5zKN9qP3enW2PSmoLRCinGKYLdG6fWF5XbSfQPjWaIBmGVJuNtsmK/EvXLfuqX/D290Rm9pljHi7dePYhkmNca9CNvQXsejaaPrMhkOWSxxR/d3nyIWb43lwqUJA7WZ6LHh7aQgmI/CEzXb4xva2Nf3qQQvf/P8+epb3upZYAxMII3y4ZPlVD9hMpjJ4JcfOkEOet5PIH5Qk+8ZV+whePqN1kdczfk8rmbcBhVRpttqFn9sRG2VoxJ2jYrFpUP3iuDHNurChNTEXg7tE25oHXwWekumIfclOz4WbFvw/D/8te0vYh0Ic6Qr8LDFuHNM+c9Ug5M9wteCt/5LHRb6clenbRLw8/C/5j82K3iyCr49ydnPJFCbtCHmrC7P581RbT71lZLltAKV/ISERIWI/KJYBKT9QZy11h7JtLgDPu+nEek/Kta3/TwxMaR2dsF5HP20ccf/bXEur7wPc7AWGzVEOom2/Se69yC5WmajgJhp84VIkrv2QT9zmgX7F+erwu2abdH+4A8JHES1aJMDvJgz8aCd/zxdpi6QlG/YU82Yhuqm4NACtAHtBjE9k6bRCwN25Z+8LMsG+ZYTvuB1ETlk+QotFrPfHFVqXTbhiO7p+jYWr0kyEwCriAvwAFtfz1hZdaXE2EbP0V6X38Xj7zT+0Ju6jR8l+dE30YsNicIKEkrOkzCmOK0h7VuHsQFOwusp7wUd4dhzt7KvJScZeMBpxIO2JXXmRy82AxVv3V8/Aqv/snv9csdPf7VAxih3SCFVGuHbT9CyOqweRQzu0C965IY1VLpaXor+waLzthqVlwbB9MGcj/tt0f7IcXRP7v9abxdL6piUJVUogMUShERYchkzYDEhs8jVjZaoT6Ubg0PUq1ZFv28Qb8n57m6DBQlDzLcSf4Xbe6xEEKlwg6ysGONvrL5H4hhmDjLNuN5QcSzjzWg4PWCtxM9TNBc7n4coCYnaF7J0d7dLZBvQLqf+n1Gbs8HXtesnp5gTi4MNr9knsIDM+m+uqs5w/7NpdH1z8b8p/MGAi4BDh66WXNf44TNHnqk6UiAcm8nyFPJU0+HaHc0CqT2ysrQwfPhXmXMAtCLLolRKkR2E2R2m80rno++6nuUpXvCpTUF/1VB1cuMZ/JtmRlOSzbXh26BiXzOFPVAk1OOq2yAMa+Z26o7h/DdHM7lNep+dZCW938PPsiafiVYYtdbzlvne1RcGcZGmlAcW0kQT8zmYlBYHps9qa9tEs6mZ0tzBnzvj0/+URL80M7B+Ca+acDQhiP2+k84dIBZQyxhb/DI2anG3q6l8Eddp9iIdGmFkcc4f5fKqJ9Lnp5rTMrtP2VhJiTEX9R6baZf8LnzfD+By83RRzU8j3PpvJ2K94qn36mNvuDil9rC+N1UMz0+TNPOdf++t7lB/e+I6eBXT/8AEQI/CwCWqnYfdTlYooYqSDlaoT3A9QqmMdH3htbkF7pUGZq0Gy8EaiqdMul2vx/frDGPvHgakdNG9byhYpkKZLS0U4wyMnWksOzVL3Y95TfVLgnIn6ocV9j/7H/Bk7ar3SWr5QArGwM+J2CBVcjQqaTLRE4eY+JQpJDvAo1MQD5LEm9ayV2c0q7hMZa1xo21yT2wY5NGskOrhKhf8SMmRVV6WTlzIG4jFSZNcs4UzTpL9AAXNrTn9JTW8wTge2EAuo/tdDEd9gug2MEabX+ejZcJoKl399Q9AL2FZb6A9BPVlvrKXtWjFq15hj7nrnmSZFyZTgnc+aE2xggu2OPzuBipfB2ftuAyf/A4vSjkiM9vJX7qqRjTDmXwQz/6sIR1Eyb+7XP9OwAj6aYhMRBIPbhCzfeJwc+cYXZniIvYFXWhQaQIC2X4rd5r0cxl2mEvD2plT42XDvy1zc6Kva9XJVFHTzGixRAcdBjCSVRJP/tuwHmTqLCewzgnxqFrsNZSXJ70CMf8UP5E0nG2+qcLw43r2LJfLEoHggjey7822Mpzu+7XCmoDR8fJ7j2Nf42EZEi6mmksJiEz20w1kQIZq7ctUcu6VNWHCQ4ffRE4rrnQ9TZ97/B1YgH6jz0FSQwwnIpRWye6ECEjTNOSrR4h+BCsIerQnPcqSx/Q3RSXMmZ/IuDgTI8k1rUDDdOboF6zCj4AXvB9sBDBDgctl/EmnJO5W9jojqKkRsXIC+l0jPRdjTGpCBj39hzU/zuXZz5ewR+avycirt7HBbVLQKPmHrRF8NxDwfsqSp3rYVUpEeHvfgxZSa6w06TgzSGxgkfM4+VASXWi0yBZC7U+3gBKUFpgATTStVvXHSWmO/PPnddKZGLIUsmzNnxXwWl+FdWkM++WQrYvkoWls/w2jluvicr31qxFrlCBxuxmUAIB8S3Z/jTsekAk3Vf5cVXO38BUVgtqZ+veoZ5ruKnK/JOolqWys/r/VxKvz9mVI+6KK0JHyku5yvZKdGUCeKXYyZVlgsmH4GZo4jXQBFe2FpReEoAVIb8N0CfEnsKtIk9+z50dnK2n7EDnzuECFSwPYZ6VxC671UktfsD5JGW+413FRbkoiDa3sLtnjny2cyvrS+FSVvJNTYS0hQhMkW7SHe9mu0FiUDOFWeIPd8OI2boEamLHKpQbrBMrsjoFjKRYC1sPeH6rX9xYsqN9WjwYMgbC1W7GAEc4da2bjyMxKuRZ4EUTKUdYLwuszJ7uPLdPKG2QpjTIm/MptX69qMOPMC48KcClnAUW8c1omDroERppkHcf8KUjEMlH2AhKMwpMm6FRgm42wV9QHxGOc5wsU93OR2j24+7nPIL0m2Enz2bXBX0j7aBC+jN18E0ubi6zb1C4xzSPYhLzenTY4NslZeQs2sq0Xqopa3iy257Ip7dflu4LRqv98Vtpn+piOmkWLJwmDpGZFoObCIWZFxOdBJmXbnBZaMkt0zv0/9dXZYaDgkzrln05O1m7bUBq/tbDQqDCmI2XDCZu6w/mjnoVV6O+Q++m0yjC0GVxO38DdKuMcx3hWrXAkO2Kmg1krEMlckDopx5MnL8I2n2OB0S/PKiWi6ryPMiUD0vpVgZB7J1sgQ1wDW3DKDyGEYLEoT8m2A1kGSTc2MW5uTFr2WAENZf/vCB442nfCvFavydnQie9k1szvrVSTTg7hcvTRhQjB4VABE5njDSY9RxKkiu9Ow9uIYnB20ECObjB4jZfuNOhv7MQdF5aaOLh1rxX3kYf55/6IBcxqTUZR13QIvDXIPyLTrrsw7ZrZbXatUhamzobwIKVEOIpk7uLtpumoJvDGtTSjKiKDtHxIXnqVioD7cFwhI4oxRPBUl/s17hUj7rvd22HuDH2XLQnPzaPdMexsqHLo4+LS/JwgZOp/K+jnelNMjBy7ftlznuiVMS7Vkunrrf9uhzPO8PYg+rL4/cjzvIS1glSXy0rt9ETfrRnjpy+FAssEUlKaZKUrUBm6sZVxbo4Kl7rcm3wHAXWiJ0HSpeqY4NbZDRBGt/5QvVzj++Dwm3bVcH1ZOzjd5WasPKW+5WLC0gss4/ifB397xH+IUdkI05iVo0Ip5mKjiJ6QbC8THKztiF8hgI04qLyZM5dfXDnEUHcr295BdBpez+Pg6mtjF/x5CKVRJGW3Hmkp0akUlr1JCAFWzqPrZAedyJeJmxBtEQLXzBoumk0d+zuzJtPrOSPy6PL3t5D81+Qbw/avUUrEkapzducIjzmSzUX1ceORKxMKZv09S+9+v4kJVsYgzQ6b+la+qK7rJRcRgDkWGYlvTneWFqoBfFsDm6DQdkI0Yc7tZ1yizyY93jQ1tF+OH5qPF/FAwWW0yBphkCOBNpwW6gNtYFd9QOMuUsEH4EzU39Io4lMde6Qizg3opgyavKW5mz39Joldh7x1Czlm57q4Nm3zmIQceogBMpimesm1lnMcRzlExutEdmM5E8CHnVx6jyzcEkQFg6xIP+rcZePNoDFKd5sz9ydWlvGZwNVE4KQx0VcES+sRAcX6dTRhYRu4vYe08xByz42gt4VPkA9IPI4xN1d+EaGX2SLridTeC2Iq7AK0TFvER0YQiKJSNrPaniuey34YgoFG9OxKB4rpzzrGEUqLGR8yLeDBBZBGfESL2fCYqTgPMSDCLIqHfJ5A2WgodTSjo2CHb+G8oQyXFJZDhIlVZ6qhZ8urGapsc5puk0ieptcZJPFRS6oyX7HNnobYnDfCh1T//Gx1cNaDiJQ7MvtLJXh+Io7vpJGe54eWXE8bDp2jAmo/EFyyNpPCuQwGfk5XOpq/EEfXTctB7BrRYxw03IJ6PmmV7mwbxSdYzX7BrUC38gv3Aqkog2ma4Ubep31tf4ggyPL5MRJpiTGDKMAbysCNDNwJdU67F1hjdHI4PobGF6L6fFexBjqBIZ1B8NTeTQDIbGN7JcFPPdkZvf7i/kUCx8AGWqBfriZOQTvAPFiSzK4QtDkIcu86yghvO7ppY8mjuHWlOCVqD/2R0/Iincz4XqFsC8ECJlm81B7vB7qcQK0AYJRhG+hxDbJ26Vhe7s1XC8TWJCnC9nPUrd/AmExYQEVTWKKPjIPikRrf70tqasRwsseOVVUG8J03FAjTvuhBJefBZkkNXTBl5FkNpgFR3UK0eyBiWRCpxYDmE0mLbabkG9K5lpJRNDKoRFMTxS58+3QnnfT2CBd1udSMGI9lYaFelGlGxl39+rS1djJ5D62+HzP/6io1D9df5DFl/HnC01vOWPRpAcaLMSLcS66FlO2QDjhYSSKCSG3fLhKOHSJm6+0uQW3Mugjkr1Ez+4KGyDZA/UQR2EJXZS9f7Lqk8ygz06nILBK4g/VGf/x9Ba+IP/mEDNbBbY5Snn34waR61DHake4DmtChZRq0ErGWpMtmnwHc93fCdv1BgnJm+LSqSf61rVc1etjz871PUCOCtFSwawjNTzj+64nlkfJv+/eKAXbfW4XoFr2051Ww6GIWNTSQPP7YR2q8wsTU/7YcygoRrQkgoMW2i09iwr5LJafgCxSC/fQpWzaz01J3QFuGiVkRCGFCOqbYGKKIwzEysxuLJRFLMoYt9M+FNQi3wAKYxcDZBd2yXiLjOuSqV4VihAny9htoIMYSw7ETbcpVx/RRrDcR29wFh8FMe7xzMJMbS2NFCJcBGFD/FLslkFu+G8ZJrNFnIjc9GlO+z+eDChwE7cO7lv6P/5WIAPCD37aSB/gj6xqRNQlEC609kn6Un3iPlBR2HZciPHBMdiI6nCUxEhXS73fLFxWP5FxUkM/7b3KhPvc6xkvTv5m1hzpW8HN6XSjztsqcCGJ1xe0Wp2PGvIsLe3cNh9Pjk2uIxfDSsGsh5dmJLgnMk/9+tLyfD1NeJu6LTP/HnJA3zM9rcHPBYEzV+fsOoUdUVgT8CMEHdpeWDXLNL6DjKVaAtL71PE/JjnovS7HTt7MB9V29VHWtGplrWFhravGppXZwuItEbvoXevZSyXqYgjb7RZFVCBs5MhsuyYYUoINVBT2cle8fzOFWvVJJSOMtw+lUS154FXld0VQeCHxqPcN3kQrPaQekFbtzyi62UjFE4OuAdv9QUU3MhnDW0LgCYB1g7PNr0V4P0Rqt9nSeVctvnksCWE0ouodfEy2+TL3OXyA9rvynexjH7fZwX2MN8mZYXSkPJaJbCCRajaSYkgDreaC0aftYXgDg6IUaJgZIB9mVlBFnIYr151PD6N813bbCswx3PninxX71fLXMdYRWUBlN8SvsnuwmzsjzeoZM4yovCL9oSTI1GBMYoVl9cBPTvfsO04PKuIFdWOcy9aigma8QRSc4bD4tELe00nrC7xaAe/eHAsJIeimTVcvrku4qoqKV1estQ4YYk0Aq/tc0HVQBWO1Dz909NLmfWmfLEQPzJ2YmJzQBFBgsu8gql7Pg/lsHRdtPxvaFB2pjxCGQtJ8JLA+4uPkaTnTTdxRiDYmXplWMDwFk5p5fwKsmUoqueDpVcGqb/s+3uszgHmWCeYIihugbkkogx4YXfaHUsOzLokfuOBFIv5fC3FqewknDvknEZD/ot8A3bYG6y00dYJfwEX1HPLr0xuE/QVn9RMmP8IBJ4DgLbsIKli3HbjwwN/zIFwyhI+La9Ww8fdPXMPpC+kCn3dW2UepmA0m5Llr90pA7J4YXyyRk8ZR7MMYDnfs55dgVwS7MOHBu92D2/l8ux1gx+0y6bl0nagzOxSqO8fPPLDAD9wFDDsA7voSKGowCd4DUwejapFw+Nu+0ZaqvL2tIQ8pjIX/2zGKGQxcvk/LSHYhcNL6NNotjMH/Ul7Y1zkNHYEFx1Wd7i1ywdnt1g/kTShRq4FFtHaFkZLVqV5w0egQX/s/cXawUZgBFV6GcpOgmX3vYQi8s7wigrhhpVjulFR/kLN334b1Pu1Go8/P/WFzeQAIAeEEEUA6izgADEIcBlnomUUWIZTuNKuJNIG0TghWFfCnjzG/uZcGGZb/lBuZEDODuKOcpY4EGbWECeLlIY2z0s4gEoqRIdZ+5uZLTysdORXiRUdrbO231Hc98AV7707onTalnbIlZOXGz8ntUJ88dBkU18upC3aJ6gKoaLvLrnUGGed+tCDiQi3QgcHWGLobJobNF7K2mhI67pUkc6BbkIgkyRzZBUMisNwoe2FsN6dUeEEqlcJu2R1e9ZtmwavnhAXf7cxU65xwCRc4mv33AxJH3s8Ex63brUrQ+YhhUVRhSKI8N1r1g53m0qKuwEZH4xGFldZ6j93ZDek3i/uXpjftD+RMgh/dXZkeRDsFiKauD/TRxqI4fj3SRpHrC6luZViCRn9UeKw91ADOnDIYshykNRFZFFNQB9gwkcdYR4d9k2x0qrvXrs3L+eIaOhU0XAHe4F+fhoh/v33u9p6wGwFagH0hTuM5ch0ImHb9vn914yiYdalZTTkSloW65apj42LUoAc2JmF90Pavi0Wztv4w/qvs7mhLMOiFDdpTOqEisxAYmII+N38ZnJ4yAq23hXc+ipq91tfRFtPntpLF180IfkaJMP7HFH0OHzXxnKkt9IoNH3+PpLJuziBvKe3lmddY31YgvvpgUQkBYVGfVUhIa2StGDclH/F1MKv5rFxyI8rSjTbilQws5Lr4lYK2TurVdxy1ntDJnv+RdO/ZW9yl8rVbRCr4zS6aKi/d7n/cJalM72eGuKI55A2+Z1xrmIUcp2Y/lwh540Ei+0aBXHHqppS6KHrFMo36TaafgwlTNNk6Y6s9ugkfKcNdv3j24fzLI1u2luqKpGJd8uUCi93VfowKsq3xVOp/kAvPteThE35d/hiOXU1LNV8axZ9hk6Kfj9COv57iQl12Gg8VeplzQiTglGes4EbguVcOqgeJcibhGLw7K77DqyiqCThx3EY1lVMqzrplRHAG5VR/YSv5DJ/g/bj6qPNDEpWa3InfgDSDTJScNGEyp8LZNFGGJ/fPP2I9MYOfFRsT+OgZJa20Np2R9uGiZvK7aOluR+ekeU3Smoz95S14ijcqvy5hH6JDe5qXOcf8b6qlr4OYv3u7xkWDPwJ5S/OZh5QY9m6bhX1djFL7M619cRn33mKi7RKM1b9bpjoVOv6gDhoQOhss2s/CrkAIoHk+fxZ9EcF7FvN2kRL/3q2gJAqEEXtwJNo/RoOMSpI4eVsMx97h1BEAEhDcIL/GqdDkimDRGxWRdKu5yv1VP34IeWQGXjl9ozaSW9j4G4zXkmmmam2WNw118Rh3v0H9RmXyOK2seKDgOqdvPA7eJ7o731xH5AsE/YNShKjNy6S4+2vUzMquEnrgDpHCWkhWxvgnVXCtPToQY2SbE0OMLXjVii7OSNbOtkPyhaATmYNYKDn51Fn4lfSiEl5A2UqTGGAu0MAhD72Ap1TIdPDb3vshG4opq0m8oMmQNk1gb1s5nKNtuRHYkAHdTyXKZ/KZ/wikLDrmBBB3GkF6V1yRDzxcoJ0W1vMhEFLW7ZJWEbbQEtNQrmk88yQHAtxqIW6PQgLxloyaaI1t57Po1s5+YX36CL1wGXSjz5+02rby1G8Qk9OHCNwL/YkEPAlSEr6PX6vm/zHaufTkzrRnPjWCywOPrnUSN0JnPBNonIyqNqjgApSeGj1MHLFHlApsolmAGb1/VnWya5x64kaEO82MGwPnY+oXDp7mcO2d4c2e97JA1xg51HtPCCoXi4jVTGuxD4ilGS2c3tukOqdy9HFGIwRPzn+jM9hyHGiyczDHo6a/NAoMccb0Epy2000ArbF9amba6DEg0kH3LdSBcGPy9oVMHySNy8eaUGPF7YT2dqtJ58yD63AyVNspu38Gp3mFEADH0NOBea3iFsyZm/o+p4nsWryqJpx6WWzRjWqgsEgiy9GNbvWC51tPl6xvhxe80BuY16dz52/RG7HIGpCUy6TZ8Ax6ruOJf4EF9xOui+k6vuRTxkAC2Fpgxu+XgLEOF2sJCzk/cPCgVyyaAFhs5b6onhuhMfATqz4KcE4hnNcg7Fn+Ogo0df5dJjtHXNdQC6k1CCZZN5uF8i6n22HblvKDWPfR5Gk2DIYdvfXrbCK77aYdfbbZV3mjwtX2ANOrB+hf/s6ik28XvTJdydmbf6AH9zLpw6dfIZr6CTXakUMAUfeOTibaN/jfmMs65VoilSz+WPIbksAJc3AkIIh0GiGUGJjFFhLoVjVpIOSgagFgxErc651GTlb63Gb+AkkuKZPksTGMWT/KDCGnVqbbfFi8YgQ5gkAESYYBxJPqawR5Ao68WIFBOztnf9FD6O0LZJiMyyTwUYGI2y+1xE8aVYo+FvNrO7ttW8jta8W2LuC6dfl79wkg6fkGkaws8ZNbqEsOFa4+xy3sRuQZIqx8OnKnQBITpBQ4C2KB5aJGP35Q4avV0Ob3EG2uNjrA0QArBAxugSyAlAzNM/OZZWuxB9lye04Zk6Hht7gzv4aAdEwMdPVrw44AVDyaZjaBPCPZAIPXbd1Z2q7rCSVSooGmvlsrfrAQHkbM2sIPxgJW+zpgMzjKtFIKMFi5GTMZmrjjDIZBGhzwppGa2DQmSyRrGj791pKRsHD0Aqar1H+AdTnuXgPXuKxhNgRHzDXzuWvXuGL2JfecvQ01kbZlRVFDdcNW4bRboex9RYGtJ/wyk31Mn6h6dXTNspJMR51/dsLg+QvGVOIXn+JiyscvCc5SK0k5o5TM6O3nFq8uHXCB7K0HTXJI8kyBLH63VEnfSrxxyAJ2MfVpOB/TqS6UiBKqT956RpHwTNK2a8RzYQ7ECkIsCDSigyTEQKy5XLi61MJcP4QQ/27TlrSIig2Ly/eyEVDZkjSpWDR620FqzXteItxrlEtLBHWeLmEdF/cKDSL1hqm6nchPAImOT3m8Jcarvt+4tUdyb33thGSKHMqXj3y8LUqx2yILnxWzr3khWPILR8+rClP0Z1PXq6wV+moknyqHoV4W4Mimva99BxJo60/lGrUkr290gNbkZD3eXQPCO9wSndowCrANrQh1HVCiiIb917oSqeF+vGEX2vTQd38F/FY6z/fXsjuhd99+8r6JkP/XS4OOfcTjFKEcB1HLtzzRYNasAh+n6Vn9PFkc5qbSKWHJBsVeTCeJXFZJPHHrrMtznBIajv29FA7sqGbaXFG+rVFZ3cvHDe7W2DIKkUTf1VPew+99F9vanLhOL/Kwh++Z4mqVW+i7aZxNSpFWweJ040c646NYv0or2woBgZfTNSY0tDKxUrQ+F8e4YQtLfN+oucLDrzVaw88XNtth5k7uR7i/hKywBqfOQmbUzoyNUXQrjDczmsajuixF/PCWNC/ggb3/kcl0LSn5NP9tRQdH3iXsl9X9zv6NFuFRisqDWS14mwrF1X8UmvFY5OmpExNvkAKG7u6/TZLEOjWLHMjecJs3YanZOU5XtkOw6R5v4qjNsjT38hXXO9ctOZcfB597aB9PIiPH98EToagye+sCSllT2yQlLh8hk/tuF3r5dtyWKdWRhqgQggGWMCFzCPyGZxphbReGeDSvvFMgYi8zECEyzWzhDMn7El+vokb2KPjflP6gYTBpXpKya/J+ytJDulvcAY1RMVCC0vNoaoA73OjxmifHXCX1frGMT7SrWeGomAxM5KZqapKs39EawVuomy6qWSeqs0nr9xLuWhF1hwy6TXs2WKRoooKSPY2RbGyJFWa7OGvSUdRPK0V22n4YJkbI639O5mRI6zPhtKMwVezFr6H8oyXGreyzhflovrDkSf3JuGkeLqkfk7hrFGXga73iTbzqywX6i/Y5jPLGniYYlkUhmy3PSiIsQ2x8auMXm4gyN7R/w0DZOC6lGkCLV0GVLwNbTQGrVROXmgn8cNeXDGt8FRYdJjdsorvR1/PGQu3kRlHg+v+zhS8O8b+GbCX9ajK/UX37BU77GDs51oQ7Rvr/0vvr4/MKPqVeIH2a5hpVOyBUCwRDrY79wJs682H6vYyfzTx+3kC5+T8nDxBqMjtrht2lRk+CuZPs/lA5uvMexHByHFD68XGZ+nGVFQNA7B7W4KA880lxfBjeISzBmeiptazj5z2B3e/k/ZZhRU32KPiaCoNmHT5K/bg0/XNq+o74naqIW6ob8j6ZPbj5O0c/Ddev1uXT9U04fQDXw6/totuxxc/h4xRxF7OSj9dCJnFJqIgO+VuPlr0lEy9ewEiJghUn01pdwdg4Xh03MbQnCCdDFfEnQXLi3lxaNw0LfC5EToFIr/57GHuH81Hg+L6FfIhUvYCH/Z9lfzNPKghNp7uEdV5093CFtj+ZCc0B4DPTq6qKgVaEAx0JKW0QXglLJMNEaWKOmaynKVtu+aSg85vrc5ulQNITJmEmQsXKDALGY4o4R3symOfd8DXTjv1CO7vnKhCjmeaRzA33RIEjtuAFMNaOBhms3601GTWtD8KunZ05+SMqrs6uyHBTUTdsYXLEo2Mn3MaVe65V9pty6UlcIRnsy+AMEgU4WrbX82nfmGU3rN52yerL8ef68zZph09/RT7XiOVxn5RGPfKacfwX6UU5xnKyFoRnyQiozvCYxSNYgsV+m4qIeZH4v8789I/k2Ybiew0oohqIvlJ47P6hAFDx8sHUSQCv0yYDgvEc5gQRE+XZgHP7s2RpGw9vZ8Vwcb9AB9qO9l8RCwVcmHxm2HaUQ9dKMN6DPYKOFdJioiLwpcDIDM07SRqU8+1P/C9HdAQHCWUFAPPxEB4Ks2LwI0CCW8uo71RcGxvfbTjard9rec2fIRmhKF3P5u8k7gUTcqRXdNdawjO7vypvMPKjnmMqlBhRILk2+r/WgzaOKQvy87PElCnAPyZuJhD6bSrI/znb+pcRO8pwQcc4JVkHw4HSfJuvXmPfIB8LRHdI+URIpELi5JaizLHSDN/rygi9zv7CNt33eDv08ufTmFkr8oAfryz4CLEjNO5gogvcMkeIRm1X2q/nzPXiCSRHGO6d+zB2TXTJTsMljdsYzpH5oWuC6DFvUmR5N5pvKyHLm5bq954hskWQz/OAV0hAtJq7qiwmJnxaPMHdEYG8buz1h3ChlCbT+7BvmFbx+eOsXMMFhWWn+NjEFx7x05qWlAtbPd7s+oJDt2Fkx4Uomfko648DTpQaLoHj40AkdeFJQkmWhjx9ufJ0+ZzKSv+NMsG10nfFCT4+HdjIzYfNIzxITu/aeiPtPdG0tt7Gt5Nfi2rF2mZblsk6CtiEbhA1431RJ96P8pACLlZS6lCvcAThai9sg9ahdwaxd2iJjCer23emfKiTo9lTB8njnXL3yY0hBGULuED7mGN0PLajJ8zX8odX3veYXGvxnnp0G7bUFRulVIeIU/x9pVD3JNV43ySBCqeIOgvSwGj8oHJNGgSCW97rG1rbEzrYS8XijcSumn+wucygcM5v2I3+XtwmgJF1Nuggc3KhPCYXySNyvnwU3Vr+bkh+YQo7PxurFCwzWXrIskfoNlhnF63UAb0OHPbWlJWXQW+MmvMW7Tnf0afa8/tnNyWan/zvr+sM1W8AH7E8qrV+CkJILhnLhPzvUavJaCVuvfQTO92OhHlGt3xz1cfJdomDMxWPd5Xxg44eRq2rU1DrJmU4uJGXll+9IRPxodNLv21eW2/IzZ6+mIOQXSJ9aUw9/UyTCU+W85ctE/Ywnk9iksf4OIXeW8eF+9OKaC/Hx9Qm7qDwR4H6oSVON1W3PJPp3yOom9SK0qKKgBiI2xhxmlvkKNMcDETSt3m+9k/fgOeyZorJeRo6iM7qYUdiqv2V7iV5Bh7Ooxpo1+xyoo7/VfnEXaWhGvkn5fURgGhUK9LWlFV6xzT3newy0eNmUwcfGF6enDl3urgp8AxRIFmtDTDDe8iOnUoB1/W7IRW1z19da9PLbRFxvavvMTlq+WNqYVrI9YbjQW5DUvU8Hna3xvzB05dBD0c7mA5JbGGSR+nUnpC4L2q1oEWxLzQ7+ksSliIeY4lNXJQxV65mr3xwp9/q8YfRFfS8i5bkt5A+vRNJZFytidWibc3WfvGuncVQuDKvFVtjAloxV/egVn4MLIsoY4zi3E0JNhlJWRFgmdbHh/cuilKa/rsGhyNWcVw3PUnQAG5baYOLH/6qhbBRKH5EmYYJfjId78bdgn+ymUk0Cq0HzyEVSlw3GtFzaUiLcr7385BCAbwSRksXKS5GEtvcPBctkbIjoTiTVSE1Sbsj1bw02Uwtw9od6N0ZRRUTzIUYpU6l5E4iuaY5PDMM03XHPy3Z6zNal/3etITuC0CCZhwHKYfcHb8bEKwTzGB5V07qE0tewvKFAzwOqwRI1hZCIT5fVlKhXZoi0QJEjjxDGIXFNAXVO9CdUmpTxeVOyIMc5cQ5bf1HoyIOQIzLmwWE9ganb3u3dUmnT9PZtT3OfGPjGN2As1KDOi2S/ZIHpY9HjGLLsFx1R9RYVPO3Do/l2f2CA5NfHtF/2ElFsBOAynAUIcu3gHmB8bOZGau97jW8M1THIMMOTlPIfN/kq35hW7BMxbNZEI9trxE6U6vzb99e0FjnNLKfOfuefGqthLdwpcK9Y6kg9+kNhT421+qSL+wKl1tsBB6EIG8JlnCGRCdeih6oG42MQT0i+ylo6zbLO43rm5qFYKOtfKMN5B6y775hY8suMtuHMk6ETZEHkpn9ONXKFlfMKNsgXtyzt4AXSl8PbPEKMvQuMdKFIVTJ0i1MiIJXJUTcQF/JKKzQWWoZZmhnnh8zprLOHJCfvSwocLfKW6v6B/TYKpDFcZVzJhIBmqmlGTochsKXrfLh4jyqMmzePAQz2CiKy6tgEFSOmvc0aQ65dIX3RotEc8c1VUNykK+dy8hXmYcfr7ntEcHOuPFXUo2u1T3aMxOTE05dzo7eOuKd9pGrVDusZgHtLnR/yw8A2LRw+KvyllWKrnczkxdJUbS1vp9SdqXpUtRf6Qw9k4K9E+j2Te3qPr7a7uf1jg3s9YyixYOoLX0UJX6zjWeor5sJRYGP3Pi78WRh6nc/u4OGHFoehWdhEq4sD0hTS/TYqKIjfNQM/9RMZPKtnmZ+f7dcEi6o+iuPSs2hQglGe5SoU4FDezzMSEYTzfZ230LDX63h3TjuSUQypT4MUcofmKfM0gX67TGZqZEALm+BQWjXfnPZWCD/cVn9iZ34lkarohm3S1HYu372hvMev+XNnWmbI0Vd2YUrTm6H9FjSNeuILSZzAwarYO7EoK6hcLmbTJR+9BuS+XS7CWdT6qvjv8DVyv3P1/hs/VAqqUglHjQNyomntU8f+9ig+swqnFn5v7KJrJvtBReGQIxNqSKj6doA5/3jfiYu/LBw/PAmqGeoeE8tEMwr00AooDBeDssEJi21KRBsRSgwN8ZLvVPwRUBOAMk673+Ts5viMPrfwsWXIB+Q9Z8fua8FOKWBMYvpyRBaOUmSJY3EBsiy+fY4LjhEZghlCMuSwSEqU6onsxRb0CwIK9LSUJ1PQ5pTAd6K3kfII02FF48bU/iVJnN72kq6xEVRK3oFhuxQ2KWAVrvL8T8HAtAwhGlRFmkHmKi6cMiSQbeDkapknuooYylUI1jx/G7Ht3Qto2Y3zXHfH1lt2PYjwkBjjSVejHyB+L9Z+Ry6+v29QfgxrJjB8E5pZiHZve9GZjRVFugRofNq6VL5rPQ5o/EbFJ51fsT3Gck90rM2yF0WI/qmBfeKJYy50RkMQebFMQy9jgZmo8sp9gCL7BQb/AKViMl0iihA68CxXnq8UGK6oohRCwNdCSG5MIYTwXIvbaYBLWXXfLW+PfvLFD+UO+H1G8CkSSShNq9AnK3ky2haLrIFJSlFKYw8UGX+wlo8wQHxM3c3RbcYTjpJrHKpTmxy7rNcFUVaShir3DUOIH1PXAh0+cBT+X+bBSPO8165M/7HojL/l0ud+6xWgU70CixgNqFaqtWC8wNJe7Fjo+qAaiLVc9QTHYFvONK4dElyu1TGqSVF43GJZL4qvaXTi1Vszl6ZTuww8JLzBAb5Ebt0/5sLs79jWJjlIYx1hrD8kc1OgPMFN60A1OzPsX6XcHEJrV5mcPw57UWNG0HyoEHVcDVF/18ygyf00DoUStzhSHW0X5CWOq3Ph4pPkFxQmGB/0yQ4Lyo4K3jHuZ0UmCyV3L9FB58JyAXTE2Ot07I7sPgUtD2gN9uBNW9jnA6JFSuMppAlr8WWm9j0SMi/Ns7yge8vSpZGoZwsiwOtvaxbyxylh6GS82qV9Q2UlFImSJit7mdDqIrG0FmiVCWjpDQVKuYvmcpRENQxGlBfsfKLHwSkvM9NeWuuQEsRKElJcESLfhi3mORY3h3uItqyD9dvhUyRZA2bMVyjuPrSPrCT0nE8m9RuaVtCfgUoZXlnEuXUCvD5r/q/VM2f1o363PkA3N6t9wav8ts7uMHFTMcz1vdWfVI7frPdnHybf/RmZyVSj8WzRTBMdaT5XNHPE9RBvpzlIPNAG8Qx13E7xverGTmo7hUn6nsJFNeNMkzllXC38jb8OIY1N5dq29MgaZif7SY9xyiYP3VvXPZtd3gK5WVTJO1TxmKI24Nw9X8inMsEOQ7JiBoOiZ5OOFNwPRTgYEFm3BnGy3ai2Upu9LEUW5bN1UNqIx5CG+ZxMFurX7rrQCZlX6D6x8bjd12f3ZkN+dvFc8/DVzsSbrA4KAZgCAYYzshbtwa4WBJUW3kPtzogcA+38zs8yZqqmNpAiteDadzyj78OUiaSB8UrzmV8uq4qApkoTEREETgII44lqoiyPgVy6EJI7HsQj4lfoqhrSVINYqeyFxGqghbYU/aSawhwLyUXxiUg2FzHgufp+soyx/0lk7zFZNFvN/YwS0NTxT2+PNx2rItLUO3j8QX2QttuNgauPbnE0B51to4wvDMiHyyNMWzPmDi6dgH8YXGnuYaQwx/zyIJyCoetTsAvuvCMFFS/L7f4B2//4+pO40EZgEnKC0NNuawBZ7a7QdLOuVFGroUrQEEChSZgSDqobjw6cLtGdYya0wbrndqabLSYE2cI+FyOjPaX+dbrFDowOA9lIRfIejLYnqwgibqGMHefC9uwmzW3ar5kW6br7EfGNehdGSpWFQoGwJWOf96weuOS5HXiVY8UUkZrXn/it8Fg/I+N1SQFEH1afjnrpjwXEu9vc5ZIt6d6i+73/ltT1LjklX8GUkSU/DSqzc9IKRD/Ws9MukW8n7h0Jl4eE81it3SKxTo3pbA4nDfAXQtKe+dQXtwR6N2UIH7koOMqtXO89D/sqOdscZ6rWsMmEnofLmzI+i64QNaZyRsV1DGh6TQ+5lAygAOEyjLUDHhYPz5zME0mvD0X/UJK+3oKhFxmTlPkRbxEOYCEcHQK4yqojIMZkMKUJTYZAmXA/JMxNHVXVWJN7TeDjaGYmgfuFb6PL5RxdjBGrtAkx6D5O/+v73bXK38/63MO5sbSKvzi0ynMWdUeEBBViJDqRV6stvxDWNq1uznJRiyjjofb8KAbuaMoGkABrC3QQs8yNv/VVkygjuNlPg/tXabF+hLas06Lb1fBOs5lwACKO63gJql3YU6FGhn1EKKwT8TimVw9h6SpddBMpqNEBPJFUszrJNtLltqDgOulU4FnOuizOD8e/p+MtA4HeH+d/uj7lDqontLfWkdE1HNqgoiM5CnUy42VLZdB61+Yi/2/ygIeYAjzy93u3lJNavzDmU40oZLtYdQHcQIcs1iTq6b47iIONXiX/YbhgzwaPT4yGuRGmRlogKM1E8/pBiL113zv9hwP9PQobi+wCEn5oL5aTUaSAv6Dc4YO/0tYhWgm0oT/60EFj1tf4G+x7wR7Jv/TuHKHU5kZiS3Om1s8SaHdXhq4cIKU2r1MPXXrLJYhbO2YNrcw93/PC8vI06drOuBtc/JDxe1lhtT+mbkARtQpMcYHpu9E4hI/hLItlcwso9ZPRWsDcjvthTSUFLwXm1+YUQhzPQ8tmF+VfOcwlrhJjalXKlypbOdh1MbU2NX/8iSATcyQYBWkQQzY8dqNX90Dh4qSAdghtBygpPfZtbvy39XRxZ63jprmaJpBgnZAUST5ZFMMXWoLPpbbGxkVhNfbvakx3mLA//PMiPNWA9HmLFeu/GBL+XzpvaO41kcM0/Zcn2n699rbF655ARECjQaiNHfqNA+kj11YILGkctgx6I4BBu6M5uZ5apmmlq7AfR6e5QdQWO/ZKE4gmRncWp1fxXIU+vXAk0IehJEPkVnDcS8cSr4NaD51Wk+UhkZhTf1Q9q6duyBBty8wwwErl0sFOeSNdBWZCkywsV6DgVd29eB8RP/SHuXcAX5j6znqPOdsBr1xlMi3rrVU9yD6TU91pu7m8I4fyLuPW29zVGTc5W7/ZQnAd1BBjwXqPdCsfZF9zdcpznTT+1OOzokJfFLXS1u0Jh7raY87D1Jq2qz4HElKPKoepJNZWcqMckZYpZkN8RVRyPIAGcbIEhs9/gMLF7WLG/j08F15DaANmUypAa5ozPwf8CUsPyVM450Ed7/9pxQTbg3GgvxoI5YZ2OIYmGcyaOEXciGsRalaxepFkRiGFt0O86s4fZEuw8GEgJ3vuuLHNemjrL0fBueduzJ2kil9vnjmx/gDb+1J9JdGbtjjWBcsrCDVyhLqQTqJEUDgPkeMCbYxIbY63O/aj0AIJwtM+Ow7/gOnXnqTbjZ4EDgAiPQLu9+D8ynhlYsurqWVf0XEvVBWXVocd3EuIlrRazTgsC8Cw1PyB0qGRmnZwJYkmgV9JnoDpl68qDIp99EEb4Op+d9NeyopnLojPMWJJgYBII0KaaAxnV99KpbSOdAeMebVBFqohca6Y+1vVrEkr5XtufuiWIbz033jyqHEW3wDLOT9C2kl7KbmlpKfrl49sxhSA18aAFW475SGKe4ons9LiDtBNIJIgFCFDCvGZtOB1RLthZIpF/+wIfvnGW1R+A7aEeA2KE6k39liCU+YKrr6RzwXAFkumqO+WS3s3jyVM5s+bjXktfc4bjiawDTCkxUrHZX3TEYSA1suyuQpri4ws0Clnw222l0lYz1Vk3dHdcSWOLi1UQ4MVxYEcf9desTMyiB6I8dF/Pdh/LMzO2ivn9zDOLfR80C5SDGvm+2e2GTelo/yXOASPtgGCb7FCKfCedKcV9QSLkoi6fOw+O+vtvbWIUN+vzcEtDB3XRjuBwHeNiM3vu1/as7fQWmznn/InL7Mq3cCHGpFVrMFL3kRgr5Nn42evEMQ/qNoY+V6wx5p7ZfxnV6tMh9vQctf9MJ0wUhGSKspXkBQeS6EupklO+DimqwPzQxmCdB+vEicaOY2sTnIQYM+Mmwo+ey2/eIPd1iMfU9hjHH38bPUuY/ybITRkmZ+S4u3RyCek5EYE5ilYNcsRTXAG2OEh4KrrUrHub2hHLCjzlK3kdwV1ycYRnNJPlImpHm0TCT7UnfAr+V2Tkh4r0XZ1d4slEQhytSGaOOTaWt++9PwyD9Hdd9e5UuNMpFerVR7KUW50VzR4iLyvFwhWr7cG8iKQf5imGNnGBW2oxCY81XdGIa3jpG5nGPt6P/7MqDZxs9w+4oqmbHfmpqEKP4iLkxZKhL2NGUg+KRVZzx6y2eU5M5Ax+xnx6jWqm4eoO423Z42OWzNEiMkUelhyOKOOBTreZyviNgapAyOBF4fptMQzaRlehaUnfNghN3Q7fS/2pA3aABqr4d2P3nJ/pByBuJpAuzANpPKY8dCHMapmvuMzr7k1CBYtvpgDxrViC3BA2aL2FWMMVBolaMwEq+qE/8Y4dlghc5eYMturviq1tnCQdZpoRa2rsw9ayf8xvX1XZZHhk/Ede0MQv1GWjtVdgZKga8AfACAgngWEXQ+3M44o5gBpyiUMtTZNTmZ5nfhdsNfMKdJ3FvVISHsIL2TDGDaoZzhsC6A1dGNAooyVKA8kSXPwSppJWOE5nPSDFtt482HGC6Qq6MvOLpAA1ac4lp2xB1EH3hdKrkisJltvqs3Rrk9nREa9sHvpxMHmrlUgFfADo6nw9jY/cjYNco/n7InCI7KkkpBuG+x1YHdEURBFpgNfxWs04LfkDbzMlx92oO7RvMZDT+rKH+c+O+0mknhVb5ei6GBl2t0dDRp4GppThHj4bnFcQ5JraAVh17por8aPoLUyqMo83nOfo6EPaxRF8PTZP0gnldJGQYVgSOgYVigPAMxGnzeN0Zjmd4YjI6kVb0Ad1+rMGONKwVc2SwfG2YpWFFl+l8bg/UOBza4HfL0Vtkj/wyWCyRShcoxugIaN4xS2MaDlbfFj+dnu+HJSCjBd3K1LLIBaBiY4jUIIXygl+OeOLKgj5XJEu+QslQpBP39K/8SdsmFkj7HigeTsigVeJvnNWBiOrs5/UdFh7mrCbz/65eL3v18u9pEFAU43XaK8prAHtrxfmD0lAhLdDBo5lPgWY2s6H2YNLSmpgc/zQu6zTxmgkoR3IRLyXeMTpHPd1eyDzB58r94GNAlrYlw9Jt/3vLAvrSj/WrPRuUSNxJ2tO/KB5ayuL6U7RM9Fp5+q+kS/JCvR0UbU/wV5G1NX6NA8hw+4Cd56IPJ2VSk5kyNp54AB51K8wc3/ERjZgffeWfFlQAHF4mMUU4Rqzw84bShVqOD/sw2TPMPEu7sMiI5WCSGLO50iZPlu1Htj7Ol8/TVRCivKcPunXrMhwCalr6xI0mHLzop8EQHFi3Oley5xFUZVmUgRwJjChNJrsO6RTcekPsYxtV4sZms8WvLU294NR30UhGB7l5eS05dCcNaHHelMTTDGMe8EYarvZxE4Pr+50ElfblGsNr9VFpymsN9iuft1d7LTMs0aZPxHy37Ixjr3cdkvBPFtBH5Kpsmf6v3tjUkHA1jaS5BjukY52NUdXRKa8HLJCv93xPa2PgSqPlq6XCRuosz0mAznwbPMmRJ78HgxHDT0OYb+hD5LgqReKGYUZNiG7wJfqX0wlgKvzhqf12qaFrcPRvHYA+0hw3xMH4XPxDqjpnlZ2Snj8TfDqyBxy4s3ZW6Qqztg936Zm1aR7pUOL9rm4xVjPE+ajH6eWx4MJtBCB6n1Xj4KszwxhGUaqvpjbNAV1KYjyU/CHgNmH2oahBCm/fCGR87Ke3kXsNfTvFwPs2zAIowB6gYPSPNfyAU6rbTuFD/YwhI3TYais0e8lazodaIj/+UbZsoYd1dtzJ6xfM1JsvC4j0dPzrDzLV4gcEfl3iXrCRqMg+5voWEaU5m18wAnMPpW9yuoAimYmxQtg/7SULcJEkmSr04Stt8vGKPhO8stCdvM3hyZn39CmAAxph59GXebmftpS/S/3WjAG/gzzaLzVeWin8R/Uc0927+6s267teWs/rCMul3mi7sS50xZDerLy0hOB6722fArTsa0ag/pyaoeFYAR9eMF/YICjqGw1KMFmpD+6tP1HU43raFIm0D99BlGSIqOK2oNT4eliPGZiVe9a5ssXb2l7q2RZVcrHWzNGGs6Rzs0CdHhvDjgCw6P+RSqsE33rWkgkX/bJLsuuIrq5KlmXCUa7LjQaqzUGZmhjcFfbEFihHcwWgAvSx/Xmm1AuUuaE4jaLrBUzMkq8pjM6NiPFHtYvBGwnoMRnIHYwb8OqcjcC7HDqkkq4EmohB1wWldSha6jhOmQJhLIHEFBfrkcSBYtUBnOXuQ0vnFCgWa5afuCCm6/0+UGdnBlFEFp6SwbB3peLRmaFL6JNe0cm2XVxP7Eado/fxwK8vCxKOSeUM+3A7GCmUKvvfHfAubzmc2RBbOrVtX6fHb/HsoFpovQhuSNtyflVFQRwrOa+sOtRXLOCSQiPaUVskhUmrK54tJC3ROyXKNZY1FbTkWIWZICsFJJjbzjUT1PCF5/JsVH6YIJeWPmA2VEL6wmVGrZqZ/EX4tdXJSSrznmm6Shwg01d0ujNnZlJzskrjW0ukCYdzxUWU+BhS2ocDvWXtMDWlGV1RE7VCooHVFuYwgRMLlJj/REZRAuymSYDQzpNKeamBUszhbC6LMVELz1osqo1SWCI7i2ULzTaxnhNipAJqjHHXKjBAzGVawDihGOZXxMYPxOOHHhJ19X8PGYzRO57dOwpZgxrIzMfoahmjdeGuCd/LbWoVu5+jHTrOM5DXNmfvD0qpgDz3uDGbZkTRdX2yU7ywiPLXXZP1nRju8Jdq8z2ntkboGu4ZWe/KqsDqBWFN8GEkupBeHYsDpMPFtKsADqam/rGJk4xKP8YREJS4dw7vjKqdgaba6Ih0M3YCbdzXy2VSWpmjIRDO03BewYWQEUgvwT5f2JW5Dtna98BzD4C7dCZH3yIFlFChhMs5pgwwl677S5NIPxRVG2NmoD8X3m1cmKTFDvwBzKUx1m1J0AlN83l8YjxZ7a+QVZFuojUARgw3jZJrKFUmBCydpjGNRW8nm8j5wkeNL5FCYli/RZ34VuuT5xczb2zPsOtGfwoPooNvqdIIgRI1QbST8+pLpHxKsWnFLWeYfitG0I9HmV/2fpxieNgdmcWWq8YDZRR9XdS28uP8QVh5tdfUIa0mvsJGKaJvTArqp/+Jjp/gokUslLdbWgNelcQ2LXMRpMfDow+Toj90fJWrzCE9/Y1iW4SAHeYMrT0de9OGFcYAHsMxl4v6zHKf6sHjiCzlVjKedKupBazXkcgJPllo21pm0d+3/CsNvyAw7zQLbLzL9vrOxQeXHVW8Dp9NebKG7+xp8ySB/sW3YPkFMalX8ncb7tcoXip55pEHJXJTITbcVet2hq3q8tKk3IQOG8TeYhrPOAHblCOzqw7zEZ5yI+/cw5ymniVPyvK9rOhdKt9jMyV4V+BstbDLtZmLbcmtfp5KfwXrQOxD/dNQpt5tObH62xbd5HPN0rOi0RLc06/XWulrl20XPPBeS3q+rG/kNfHl/yOc6eAf2HH8fIfo8BJBwPPUG5PCEfIPtlFPXkPOKWZW6BuD6a9nPhlRAiN3Wo4rDd2HVIKZOX4dd/zggoezV6ddkrmu+Z0S03Xh9rX7gElJUwArBsWjozxoS87wPRu5rT1n4QAUyJymu4OzHCbDOinpj41eKLjNiQIMMWvVXBbaHpiDpcS59mLJyhR6MDvypnH9tUlo0mTPByE2d6OR1mjvu6ZUmCDq3RG704FLDc9lXFODXJzX0TsbMdfTgtNdeWa+CMPOpnOWaOr6Y2zxGYJ58O7NgAVxo8oK5ihNyJFTxissgFehcMgfiAz3BigfZ7BdvDI7NqatV2pVxnbGw1ic19s75+ZvT8NsahZ22Zgl+7OW2+3mjPKwZuLxtn3/8npCBhceNb4Wrlv323mfScPoVZ9EjbdVSF/FDbQ41zr7C+RL75qlSnSkH3utZF7z5oK+MpHZv7QMMSs6rTlXdyKk3C2gmpNw1F1a18BF4f3tch9pDxxAFlkIGIZZJKyf5aED73dhtIIP3BSxi5S1kfZvmk+1ip1NhoJ8rdeaibfeFVbeVsOe+sIBgBdnfW02GPGV00wJ6wMpHHAlIjoAEQjYAYyi9Hk0RYMmP7jTu6FVsWTPTTW/YmKxiaon7laF3QtZa5Mm5AQh99sSMI58KhqJCQqhogHQHAP9oLUQ70Hr9ku8Q6dwThz9PcmCc2z0wEIXnb5bslNRhOU4aKUMo/wAgUoxPyOQwByTBCZcTBardDVDidrFuaXHVHhrWgIMACAeLXZpm4ooxWy/07TTRr2dVgB3p3zrqj2BuEwAbgK9sqPb5iwLFSwW4/lc326yod+z6uLrN/LS6zTVY70Z+c5HXxs6IOKepUlyCeTaJX9EW59Mz+d4WMh7VdhVIy2O+EcrJiNc379rQq9ZKrWuUF4KzdyUs5AJHCUpqxrNy0lZ382k3IIyQTAOuUJHkRKjH+qyA5nrtsel/i/0T8XS6+KqVosLCmv9yABTXBl0ChD0BFSGn/rV+yuSF+QhPss7MlqKUpS69UZVGXaAZMVCJ0MzES4H/mmP/9F2SxNu82IY9VYQdvfKP2tmhLOyjO1/j//HFI6/6yC+ePkZr3Ct5k0hYpgn9pfwOCEMUuunFddNniB30bcZJp+phK2Z6UYdl8RCjH0hOm6hBVRPvO3wxx16SLY3HG9eYrZhMUJ2UXnjw/ztw9q5BrkP7Cw6iDaIVQAKGwvn7323blv5v7rTRkjg2/X+9YuM9oLmN/SjsWQzIK3Dr20oI2C/IuNl7lJePN1DE6mnm08p9c4478AIUfSb12T8K5PgHRKek8Pmszw/cHiPNQ7y12EWAgX9ctv0mUgZp9/WxlY99ccxXfD/SvB6W7wUY5H2EXC6m/lnYtkze+btQ7Odm0uvmfjZ6r1P8Nu7T/SJA1IrE7FhTLVncsOe5rntm0u/uOnl8ejDHT/iV+T8G4A4w8OczvnzylRA087P2vrEj7sy5hTtUvW6VrwdmpAlKF8wfi0OmSpHhGvNovd+tfJsIZMtKpf//7BmeVph/6z3DqgjIN5n00/NnjJ2xFPb+Jrh3njU7YCGH2TXpV+z3FztrJ4AbwKAbs56dkKMHlxnfaOkmNWl+6e/RBfU3EyuxOqRH9rchZpV5oEj3ekfitNjLPuXiS1mTmL9sXpKHw37sMuDIM1lfnuixSa71k8uv55pa4DtqX0PqW6Q9gM5XQSHejH3Tlbv7H8XjnX2efxQeFcW8AYV/vPz4T4Z4ZuPrsTcb01afH7i9QWouk/aCCyaO/NPy478ZkqQJ32quJTffZNYUrjKH9ktAxgzIrSsr552+SAzbvQsvd2EH/CsLN9WT88rnZfZeGgwD8rDUSJvulrA98ueqlIPZ2eiusyy7XC3/2OIY5gs48rWpX957cSir8zctz+bGB+Cva3/EGn8sOw74lQHSNKYbZYp2lN95oLS+pSUsuaOE5zLIfY7+GGWd9JsHrDpRF97fxiCa7NjJduzzBByuZimqqV7NrNiWBYbDfUZ5LXouGIrBkw44AiRhLwkGcL5dpZ6cp+7vHSQtxhE/ikWuwjAiw4AjLk9mWwF7BCMFVlNLUDnhsj5AsX+QlsHYjtYyqCnvQDPmcURUft3JvOOHyFeX6zEL7lcU7PmD2EvO3v8uoOB9Z2sqmriM37LJbDihTFXoWuV+dadL9TXqOH0g8iPAvOcrCkFIZnIGMrY4jculujsMpS6ygYe9af5xkgujlBwifDF5bTLKlZh882IDfKaBHbAHXAJkPxD8eUyWSZr4n7Y87GiO/+zN3Yz0V0iXgIuAog8lf3mqxwLmzt/HlhYag5lzC3+leVxBTAXeJgq/oNeXTkE2MFdMHalrb8o+umtyE+kuly4GwYh06csTzxEprZGnuDAVvfJAcGgPrKBHy5oCWnIt0taiiays1bumJRyqHgmmXNpayxhIGO5lF9s/+3qaJ3bgfj++P2VSpOXy/xl/AS4gyTzu12UbBj0Ti7s1u0Ev0KaUoKg9bDF7qbdZ4Ce4Gz5qJZNszvPeVMqF5J1WFBamddwjy1wlX61XX3DenSL91fqfSJB1XJDTTiZ9iVF/DiHoExP6xsjVfEh25QsX5BNK5jrkL3T8dDmWsuAMeGcQYw4ERsBSM7PAZ88r/ZSKacyG4nhjc6XtPV3LLbK74vkvLMFNfgpUmRPR4oFHXWnFRyfV0D7sfsqhqAlNlC6EC4GRPA45clNJUN0++7XEmCJJfSTZek/ndE1jRsxx8f9Hgacm1MEcZFgj0ikKp+RxQ6iAsFWrDW68LAg3r/E58TudeX4XseMY6uvFzt1PwvGU7jVj8d8HxinvpoMXr6ifjtmOFpmZSR4Xmk2enqs+4fxkNPKbPCCUMWZcy0TtD1RRfMcK+1DPtAUzYxqB0GSCzjZkXzj7nyNQAKlu3QjUTex+dRxvwpgfVV1OzxarW5PR6i9sLvVxZFkx40EPCafhg0ghBTEYZdH2AznN1xP8d7hGK7ygFe19xhNpjHBAMEjQS2J6HtxTJFq0TwlJHodU3U2OcH/rQKa4/zwh/qVyTOsjwBNQcNWxvl/eGvDkppeuFXVRdJjh+QN/qPre9j0FYLsNfSAYm/VbF99f8mk+hVvkEe42LPM1LcBGpQAFpUAuKmu4RV3T5yWrX+1ThD/uVpij5HbydpLaX7SnWCp93VrnCUcD4S0rZ23q7STPM/AM6Hrhz3fsuvnombnqE25ypigOOm7uWYm9684x3weynQp+EJZBrk/4suVhVTI46oEv1C9EPmBywM0AvoNQsRaSs/ARDJZD/41QDAa4i6XMhp5M6b+WvYnACaDtTObnBRm54YuNpLgJFRtWcGmdb3jWP98KckKIyZUY9g5+JH/uCL1SWs9HRCBNl3hvpOhb9e+2PFmfOGwh1WtsN4v56+UqwIkoi1kDPDuiYXcuFevwwOwP/7cnomUpFQbCNKL/mU+eT049qOtzq9mrZOi1KOSQgL5Rd6/ZFoJDb2F2u8G3oVGfPqUV7CebJ62ANe3EPjANx2FI/AcoJNBh4r0x4oMIuGop3I+9Bh5T/C+/V/d/AA1Le9/HbkVWARoxHb32U5j+TaaRB+FmlAUhQVR1suVqMAoXGdmmrshbWebDWk8JlDCz7h8/RJsme2DRLg9U3GanjZc/vlYoc2YS7ry/h530pEct0QdmuIP0AUL33pgvwKl+q1BSM9QnsVag4aTYm5T47egQyaK9fmI2f3brQ2rFrdWf0/VFAlAmYEy4gfeeNaf9hP7aNRHOJEupi/Zy0ahcdFef0axROolih105NX9mNyRa2tftN3apC/vBfBtm9+Q6h0LN9nr8VfBCh6qpw6SUpOOhmvVhq8mEOxrMEPOt4vVvB59biZ156emKWHRBSfQiX2LR383ZqA1j+8ozeA/U8rCp9Sj8Uodz6G665PO1sJq3d30pcj9/kR5VH+XHDVuIbHuMb3R03AAUr1q27+c9cw7jiRzmQFfWWTwg5w8pvw1tNWx/3c1D39n11t/UkFLvXg/99p9ZNqli3h9ZQMccbf3wQ7babCnbbnXbmjSFu6bmNCa+QUi7jeQk5ReIzdDqrwaFQhFq2L/x2TaF9d+7H9P3ZbbO+MGALEGsA9EKHjygpLJKSSfHk72LFpsQI8rr7O9HOBc6AwlSXebUZhxjPgMxv3W7hlH4WfPBCEYQNn7j6UqFMHfZvBkhL1ZmJBnFi10Y7B996rjIzFlaAsxIkQyC9NL2E17zu8Jts89NSRNrfg4k8yE3h3utCesfB2+8Dz4MFIjKeojlj6zd8ZArth65N/ykxLa9lJoo3shcH17CstbYPYVhmfhRben2UNTy4Aki/Sp1JsaaAIZ3YVrWp0U+p93mpyQO/dBJmPbTJSO/LcJbE4GVXo/1RJt6Tsf4xRZ9+k82J/9XUGGiIxLGSUllRj1XVMVk9Kr0FDPTM1m4CDxu1n1mLXaqnVZbr5mo6E+YFgfE0q21gao7bTW5OqUupavrCHcmxARBy1fBCiaJkoiNDJyPC13ehGswW31uA3ktp0gkETnBVbAOb1YU3ABnnkqizbuUTtGseUh5kI9uSrV4jkb3cC3+lcBMx0rVxU5gL5G/48ixpgihGdmGA5dWmMRkJIxbcV0kReAhnQytXvBaO7SKVhO9DzqVfdNgxlgydFhF+yP7vsIYj34k60Nxl+iX1N/gaaz2+6CR0dKL4fufDueSAt8Pu3vbHl+Fp21tgDg6FqzXBmjRaZ8iSkYcwxHvfAdUiBEOgtqkzy3OEIPbw49oPJ7zOHcxdHP3u9+Bb7AfWWyxzuKBdBfs7+uAPgYNdEm62gTtFn6/OtSPGUdnj9wzQemwqhkG07n9npxs8fr5g9XwneeBISwmRSkEzp+e3nR6bIDiXyQPhf9JBgLVNXUpds86RJ+cnDMkP+v8A9VJgkwolYswh2uTfZr0aS8JkllIdBkz5A3viS2h3OSK3GOV7XTPftLYxnh/3zW8OgaMY3KkM8TEeTURzeS7742u/1+98RhJ++8a9qAZ2BhrxEtQWCxMQA+HQHz6vN5DGebbT6oo1kFFyBgqhPhQ49FwqBtrr2AzRy+r7qpoMcvb1dIkFv4M17zY4rfxgIHFG7rhWSdVzuK3x5abLc3XLfIdqP66gXuu/eeOEDNxJjv3FDm1vq1pY/uneyPJ9evAX0ZfF+Ux7R0Xc/DZqKmn48cSW/r6FZEfUSSN7UhH8qTNf9uoJ059ka1azKzT6nJ/lIlrOOPpd84gz3syhsK8dy/6NjhQziHvhBiUPefFcUOqSnx+eGhKDesoIKv2XZ3LJoqJQCmHlwrEXACFb6j+/PgUI+J+VTUm2RbD5Kb3Qdm26/bgOI5DpnVi5M6nxv4qjRfcmXPcY3XfkOOfDSzxM0N9xuno7zTrnsDVwX605eom1A/cANleH/nsvh1kOkI/3zd9q9Hys55z+N71pdOpN7ke0Auk+i51Jwq9qgLeOsgR4gMzK/pSe/Y8yldFZhKXWxHYMeB8C9g5DOH1LxfvSG0NZcfghQfw63TPqYFIh7xsffXK9wuSjMP/W94EHIG1TdlfKrmLNwi/PjCSWnHZ5++PFtH/3VKXaBed53mm0Zenci6y+O+vDT/fJ4eErquKisCR9IRHxNYcse8g3+j8I7zVR8Bo3Eag2kOlwL66FMLZkGuG4e3Fa0J/CV0DAgFXhqpmVutPh8gobidS/3VxeuAFPejrSzOzX7Gxz//nCGwfC+alSh3yHVtGkfuv7SCPdYAtVXR06OguGbBS0kZk++qkULdbFBpP5Kbk+tZLkW6vKEK4elZWq38URn1RJgpGLk47OCljjLCIAkoL8dpVZ6uwYV7w0tEGDbZLAoQsvTyviIUwsLOl/M4JWV9oR4HcTD6QzzyclupN12p5X95n9JELgKz3ZX1+qstKeqN6DEwtY7q6emiRb37vAMhpOQSYQEQRRU2FVCGFzdhtRZ5cii2FJKiaOPuiYdqXv1igecaZovB9tc8O0XG6lKr3jjyqueX2xZZXQ8qZ8MEPVMMz8UqNBOyKAxzO1Vr5gheFjqgHK2uBNY0uL12pLWFyn2ZwWJ+k+clLp4Vt1vUGTWoTT1+8KyMal4keyf99p+Vb2c1m4b9qF+yM+Ioc/ji+kZDG6o33A+RGnNvz1wl25ADPZisftOt+9st9E3KP/vAF/HJNk92cdhbtI/28u834MqYvRhGEMbGZPYOH8FjfUsuLK7mpCsBhZ5h1sac23y6XsmGdbXM1ucCtSKlXpSsMpjNd1UzGZnAjmMvVuOAcaHMqhqVrrWgAY/yskrDGrixPtBrAKqR0myyX6rlez6fjgjT6KBRgaUgLTMge3IOT8qiEcC8TAyFVxsf8JcrnYZ+JRPdg1ILRHiM+lImKARiA8s9PzRCmSPemXVItfZbTs3AjlV95I9qFkf67TTOKjXlgk91dScS7+t7Lp2rg0nYE9BomtyhNWp4Gy/LBQ3CWzluRFb/rdmEag20T2zif8pPAfYdMEz45Xid4haqjfZJBkq/UQ+Fmb6FU58f5ECWXRKB0v5xmnPVozPlzopwGOYkm+AbuvopZrvWf9RPPcZR0cqnVB8tOnM5uiOyf+k/NXDA5wMItDtnC05y8Ql0/8aco1+ycULKTVxvL1qmQ2mGspxGMtvkwsBQLHWpgGcz78rAPLZ1PeEsJ/0Lf9OSMiBqLv8PB83OSPFc4MTDDCm9leNJEJWBZZc0s/epBNvfXi5xX90ij65Bx9U1AXkdzGLmu0oq1tnKl4soqbmWLbidimxmw1jaKuCIuDLYN8EKc1BkADhwkl/cTcUkQBsVxqH92qn73xZXxSA9kHyyHIOcLP2+qN1Q90dgMvjwgqvpoQMUPG35zeRGGWubURdWA0/4ZjsKRNwaT4QTQLNvnIQ7Vy2O/YBImQVMaU+Z0NBCUwoEyRs1wQQuYH9xCkDkZLZwF+nywBADBgXkbnZaBEjlXPmvFjRjuncKIf3pCwzzvbshffmUfreL+OeC6Y6d4nJzRwqnio5T2e4dIIQEJP/oPr2X0kWyu3myBpY89SN0WiBZokRNjdXZIfuaPojG7a5NCitFIURhy/MKX26dSWwlPzg1+DtGvS/dJ0qSLrRsc+O2hUGYd72jy9xl8oBgnCtDyO8UdV1Rh4wUTzkc2ow9OvTwadjnzGzt7AOGgWDXsGxSjhzQVt1bnv5e1T/bY5DIx7K/nn/pZpAbtBw9fp/LVIq/3+fJGP5zx4rXCqnIh1/qfhl63fq8EXgLUzf7KaFaVKwKB+XJd6UUr+c13C1aezmzGvbCOfOBuR3F98RD++W+9+921j1SD64oj+VLOnpbs1ptxRx5vmdG/+R33CntZf59lYwecQJhNJgIyIJbsLrNXTnGWBuDA9RyH3PkWweMzV+SReUfa62Eb8rk6huEAuFiKBsEVgKrUv1svrJAm2XDOMLBZ+m0Z/zT5dVjwJ8qQ0wv8oNhJB0qt1tIWQnIR1GR9xJiQJoo5a+AByHr/yC9vFDjA0vn5vfEnLSHMupLp12NnexFQyM+Xbb/xpYps2lstj0ltd46jXXePahkC9KWbfFFg8/ntzXB12MS1o0B2WOC2psdYHFrvOXspOwi2McbQqLT1fa93/J2eX8YNhRb17at1I30oprViDmnE4XflgAdA+5XUz2/tSYrizyZejFYKfFYVbx2CS96re4GiyAdG3byuQI5Hb7Z0tZNtviQED0Dvy74ngfeKd2Tg9WvhtOaLg5yCoOklWJfxNiw+3iNPfZleKn1A8I8leF3Vs+4T4WVEvTwpCtYNtf38TA/aJ35fWHrfqvfFFD1wHfne/iMFoCkFeYG6JqhXLQwGXaXsojj5K8OHnuVoQT4Ux3GUCzHKvdqHwaeS/ob118unE0A33WDJcJSs3jV8bi3+BQ7VUH9O1FF6WYqTekdCd0KbadkcsrbVonBgGHJds0udOyQULakW/tXGO76MqxJJ04CVDrMpSA074BpFThj05ARBTggkPb8GTU3fsXxQ4AsN/xOj66aVYUq8/DgmxjfllB2X1IM/iINzr0tdvHwoT6ZKkSf38BlH/eUDU6+ZOpQux5u9bsC63nC7YEf5OEyb6RHt/cIUsO2uoC5M0vF6Yup00OR8kOSK3AICI5flhvrnXyTx0NEDW9xL5pvSq9Hpr1Ctw9MmRH83xdagajDzSmNIvIWmHrP1clEl5KanHHuaqcQ6FUjo4fKcV4KF+/iFHqnmZseOSeUS2iGW/rUNm5X8UV4aXLaGg3cbWcd4esPISmPiY8d+h8loqkUk3zX3RKviL7SnQ4fuoilZugP376lEKhMpsg9ZWdlPXd8XtVp58X+H+USLk25wtjgqh7iTnOTfh3JoUBKRyqPdnEUlTZ1Z1xPpkuAtJLDA9vr88f3B7wwnPvJrLrUqWb+T/cX57GtEIQPPkzdv01dW5BFFy6SQw+ib3/WY75zD9TeBYNwEJ8UunsbO0E2Y5+6hgAOQUh5t5lLJ9uyWpMGL8AjGvoF0n4SxAIvhqtD71qTuIzCBYXaHybKrxIS/Elz0tHfUEEWDtzSbySDJMwHZGcwZs7hsPPWmGPsJVgJW24cnCh+E/4MEc4O/uaYP5Aa3IiDCibONDQr8Fa2CAGkTRNiHDZU2/L+C9FVkBW1smO/Jcs1xVkTKXI8k5981bo2hJ1ap4adTpi7kgYMyA5Iek6EgUoiQROTbBckNa26gdkn57aJobH+LV+5GfVW+ZXXKW58lC/5LL7+c19g0B5HK0UgMRTMjW51zI5rjzW7OIawmFr2xuUb/WdvdOP81CTRCk3Z8UpeBscfos9Pii9jBa0WyEoq6jmGVwW5lAylNjeLiyXxttaS1iai8k6AFyxAermByc8u6q6C/njbESLJWDeKOTKo4FKGqG2TOL7uiNtbhUepEGNAMkLdZiAw7aWkiZ7lvLXHZMUq7uFYSXA28N6wBpYon533Kk7n38IxiWFy+jwWBTh8xCTc5Zjl0/u6je2cbrWlmPSEeofcsCV88VgU9V+V/xIaYFTHO6QoVOMqGcAgVTlNkMw9ufPxS8l/3tJHlX3ftq8nlRM3uEpseoIHGR0JWPmB6Km+ViD31pFVRH2Xw6rX7xIUW/B8LASQXg334uac8s9UTQ47cM0Dmx3o9SzB4UZcwr/bXD1KoLx8WUlmF00LMySPSvoNdDQvcaGbWuKadplTrTBEnTV9/TFgmNqsdUHsGsw/0HnFbgTu/rA89AFRFjblQ4gjXQR1AmsvSSz5KKUsrT9nQkZF3gt6knCU74LAkd7g8jSJ3sqjrweY5Ve1/BngV1GZnUjVbKh+0yfeIqOSaFh/tc0TuQr9P5TzlWXwS3QaSIG+Rptm8cYvGU4XLmtr4I0qxo5eTSO91EqmR5r0tLSPXHSHrYL7yslJ+ac7ueMAdYOhVGZ8uSclKH9QT02YXGvzrmbGc27n1MA3Asy6I0gQknDqN2qOsh4PGg8/x+Iv8dQx3SvUXVQ3/r6WEjF2jEWfsoMFjuBrQM6M5Ry9Eay+Xbw//qn+kM+jSt25U2G75Ua5EYEIxKY1IKnsMRzqZm2uvJgVXDzL/rfjcX6jLV8au1BdysMQ1JkjWWSjDGd4qLxf1YfS/NiQBtATC36qvBXAAEmQXrIfAoIX9TsPlWdXyPZEjPo0mNhUNYpA9mq+3y1FwDyoJCsrBGxiWqOqMkbNO+3Dh/RgbL/rv2LA28yDsTWD1kbtTl1xARiYGIxZPeeF5DgQcU/P30JTitw6paEN8q7Don+sPTmwHw9UXntBfZro3Om5Fraza+wlISAo09ni2DWsRcvgf7830pDxiTxo1NktE/Jn/1jtT/4mU9QBdQISayZqaxIYPkQuaJkgKVHVILcVFLTPXD5zIK7VGoZ9cBHnW253iW0iKq1ROeV6Oq3erqLYvIDMJJqYm6u7s1VxJdgKQTWxgQZifMxdeo1WMqlDRn6uv6ZIFqrb82ytW+9an9qfQa894wirVuOASEF2Ljx9tyjqJYOr6VjGqqCmkv9tzx/IKquYxV4f03KsK6qiOBp9LMsjffF3gRjaBXKyrX913NDKyinvhlPLLV5klCKoMoZP8cjrID+IzqEJoXdYnJugvs4L3gO1aiew4sbx+aDCSDPddEvvRsZtci809LzxvWvO+cDBHMX3aB/9YVzYXXI++O8Pcfg6i7z/muozu0Zj/HV/57gN5vnT3TvUHIZpJ62TSRxkmHHkItLztes6BBL/xPm+X3drAYVrXi8BR+aoRmuZNkb+7Sw2dnIfXO6bf2TB+2dsxuA7oSmqhkOkDn2DABVAn1HFeMQ1JRKz4+SEJVdNU/RMiBf+9WCE82+DVU11iC1OGbtd9AyhqEaPRIaeOuukcaquQJ8FWiaAmy7IEgRs9K0sDaBXa7qXeDuiiCgLzhF6fXMFdA1jTc9zxssGUs/cIQ4aXf/hd+tWoyyidO4/cwpf9TebWMzWjEBZqUTf9XDhu1+FTfYRYv5w8gCBiZjFVAiQg/+ECmdvDf6nh57/qlceSRwPKzVyQ5WnvAiL63zq5DbluSiRnRPbaFQuuBX7mib+LNCmWmPrZj45AcPN/n6muGboh+uYgVmFsUci7rUj+11G7swXqWch+cw4nOg08iOpPb+1lOZLJP46xodPdA0FkeuX93a1gRylW2aj3BecRehZI+LDlILzRWoZkTDN5UI/k+TZMXC0QXZA2GvyaUSB1yjhSh4wl3VVWSc45Wrt1l/uIFoOG1VLiFojQ+G4pJqYsGtgOP9wsLxY9Ko+EnvsONmL38ABtL1olanP1x7luI8vr5kFCGwU3uIve8Xixn4kqpyC+Lm5HleJbW94S1rzayHhEamxuBVaNoruu+OKaoI4OMUhO/ZXDNdEKQ4P6s5QzSoRA7o0RSSQ/OZEy/CqNAyaW1kCzfv8pQm+doDVIPwTKeQgWl/2gA7mMA8aWcyEq00nUj9Bg3lOnuLghGrodv9R2EzeF4+2TGKu5X4huIwsZ178zX92WxMWoiB5fKmDtItCcuICDGMatOFPdLmr8j5EjhkxG5Ear47zUjMt94YXJupXFH1mdkW+P/6H+/A3itTG8oYBIapplkclxgyaxLNrONqmvzngKetD/f86olpH/Ou+6+5DVdF6LAobUfpLxi6LYdYCh418HCAIPvOWnvivb3R4ql95pHbnmeeuepeAgRJ1/3I/jnpelPV1zxyDT1bwIkjO+HEo4d8btZJJOEgXyIXeBUMSd1w9RMoFcLxuEzYufsbtjvgTKjwgkLOo/+6Z1qG6/FRbQZCGd+MvgGgqOEQkfOfh+6JojmTd95tkM+hGXU4wz/1MzoS/wyhUg1Y5AWWmONtap3ZXgguucF3sBM6uTdW2n2pre4RTcNzIVsz52HW/z7m4TX0BJo/EvYZMfg0tH9sgsoZtFA4dFrdB8TCUXxS/kt2C1zL4ksR1N94xA6w0a9SNjVUbepyafN4PSkMqw+Avfnj28wR6Nn0nP6nPwteHq5hByNFxKIubXpy04cyiLqRHLIijPuEmDRTXn9aibs4Ju2I68LseiYN8V2vk5pfz/fKy0teKjM/QWnNT0UtRH+zv1lVmTfNiT11vLaY1+nCaN1Xqg/YX2oqE/0mRkv/vmJHPgD/lp71zbMPFINQe/SWBonCWqr/mb1e6NxZvx1HG+h8tvI2Dto75Za+f7ZxbbKguv/4/n0q/pt+i3wYX8m46QTFbn3tgZy+jK056JfhN9DeMWOsU9swhmaHJrVtMm2RNe8hZWHTlePB54GWhQRexl+nCcPv8H2rSn4+jkGY0R/LQUhyuBPtL8tVYLYs/ZOnl06RCSIzBxD0hW+tDI99J+6cszlXwfzzM/Wyzx2OLHwOI+tzAJBjjK0Y6cDi9CKxDqguCNC59nN9kSP14Yev480MtOmEq9P2Fop+P3oCRqir/wPZH8sgMnpe5JMJuclMtyPoHy4Q1sLOhyj9d5xqOEcMkR6w/xDHABwv1JKggigqK0ygtMYwM9gB00OtFsXU4z5rkFKGQMHNi5lEnJaW9yJhEq3T+Q+KN+dP9tOmLzSMLSU4/j8vWhCdOqPRXBVaA8LWtQ/kIiLJXRw5TenXjMyfDKERzBFiPRmF5RsAak05Kax2cYuebzkbBXhjeOKnoedg9senS/d0lHHoF5UGix9d7+p1aPhPrnVx/VM20h/3JEDU6ndVzVXQKQZAjU7luQ8EsDjsiqGv9+EE1gxtLjFCxJe1HQIBq2vpuNXMbRdy7sWKYrNc+h72oJF8o3w9e9zW3LD0ESMazH2TrBPPBNNEOR6oVrxzTYog81eAnkaKwQYDmhmX3rAjwxFpw/WTpZn0fYNgtTiew85rzCxcCzJQsMSm3hPDKTqLoFY9zOFlan/wiLk2FsVfaFQrdkykjJJgK8VDXLq+Up2Ndo2PgWOfSsfTvDtw/WcmVtN/4jONiwfPOe3k5JSWrmMOLnnSdIRHE90k7f+XxTLfKjLhtfLtnZo4+7GeCnSdIzFut2IyRfMzmBfwdMQeDemmEragfBx7uXh6R9OLXz+btNKhoB+d3KKCfyIq8bud1+RLZ8u4WRuWtCz5qt8ECZUnU8e1jS907UDuwEw7C6HLj3QBmgtbm8rUgMVFBloq1ud8PUMirTppyUEjF2/ryJ57tkGpMcbShPHe/mKUTKh/6CGygiRTRlfbf74DMjl78uEqqnO8Xfi6Zb4oCn3ike/P0OM+2nlq3tlP1tmpvt6Xf4PTc7TWi35Y9vEo10aozWI2jEmwkm7dDR2/iLSH4brBz6jNOv0axD0eOCzFfnwBnBhv+3dHeiW/T+0ZUfg/md9PIGQNVLDAM4MZ1ldYEF2QvCZMKmYeqrK+ym4zQaw8jaFu4eyU8qsBfX3s/9xFFT7uqkZNn4mHOAPDeZ8tbaLSm8TvvpKs+ryth8hLKYOSBPbsZH1GYuhVU2SeMcSIzUQKTcqPveKNCn7SYFe+9YR9lr1XgvYOSJGRwboQ3z4EtvLHdSPXLq93VL36f5IcY9C9RU4rsreH+jbRFRbQmRghRplXiPqVeL/I1gfSCc0mBM+1x1Vi6BnIOYt5yk1R0V37ZHjOO0ov6B8GJm08eP1KOQd8ED1eS0DWxY4nCq5tKohGWnikR54OKMB6XD3sQH1cWOZjCN1nwXjqFw5gxK2wUWtM5OsPWjUIAIMwEZyjE1ExIowOUfyA/L0SThRJWN6EuhxON4uInfH0ACkgHG1fiSSzi32EY60okXfcyLIDptOnF1Du2FRhkreJcdzk5Z96g/TDPDUoQBYIBRyrrApf2Zkq59bFyCBy8p69UsrmNuVo0j6GHVtQTVNUDmAAntOWje6ZvqFxpRlNT42TOswGGWB8B1HAjUw0Vx0ptns5ZCYrmdzd1/JCV6JK767ObahYY/Al4maL5hljQFrnz2yv0547M+ldvaky/EqT052PmQ3T1jaJZkiLIUPxXNe2XAFpprvejeVYPuYBi3gOzvyTetZfpSHA7QsnPFK/oVMW7R6t7/rkEYhCvtl0l6aeOX9OED7JILuRfTzk5I/a3+iqTQY8XnQiqHc3IrEWP/tmrbb2r0+Rw3Q/xs/0LS4gGuv5S6yEWs+GJsIcrMyc5OGA/4JAdFAiG+e9iuhlClTzG7wgsUYBpEtASoMjhQr665idQANsKzoBGdWXJmSZ/Zyna5r+v74wjN97QPu+D0d9msssYVnos0XPuG4wvco18CI02yuTtWLxwX7i588Zhbz9vhNPdoJ5TOceBmAPWU7TObxD1aJhVzsoWg68lfXP80YavQGbIvj2oMxCLCKRvcxHkQ0LDx/KP/op2+e3Wk+EXmtL7s1ZiBVAymSl9IJFFtwkMl8QCiaOW6y4gNVEO8gWx4SYmETFZShD5OAWbB4mkMclxOSjMh7mYNXAGo8IFPoEAxcbeLIzs5QgAo30ilOklIL8hEjcrcfQQR3YvvfRpxhFO/e8OgS2eib30YmcH7Bv/TVzRQDBETRO6YplmgqpLkogw5iufzAiJHiUgwcRNKbCSEsGjTy4Gqu1tjetezsciNmVK0TjKFsQ7w9J6Qb+xhAPTgE/HXY6mCdnZjkihIOl5cZsNcLQMHKcWRCm2NCffH/Xwg/w7PvimfTvtKjw76/P//uyRS9fXYiDc+umttQVgjqwdtEnm63+53ltMG7rVw7Mar5y1kHFlWpbJUxQdEErjc44LjAsZjEhtFHLaXIHyROTlW8+X9QcNn7o05q0x3tR5LTbSNKZvzhnUmAGeAOb/OHrjOY1/32W+jN1Yf/faPUt2Es24aiQByOAMOw3KxjGADVvaH8/cpfBtWljoVRBEu+U3BLAmWEJ2nhwh7K17lJoH2lXLvYYLzBMvxj6tI/U+khdNejjyLp8ucN9nkUUbyDU/HkmnkzQJlw9UX0my8hTStYW1ITBGliN11OUctCd2Oo87LHJ5S61VlLwRl530WkvpOJYuqrY54neIUGsNO+QgLk6013/5BL1zT79VWztoWt/NAZvOOc8volqbiWODcq29T0X4saYws55c5uChaWvBxKbL3tUedYcrmB7+jw9hND3qxT2wA3cC8Bw0MJ2WTbKX7txvNmBh1t/zC9BWyNXTKtV5e6Xs56rH5VT3rf5K43rNb+m9QD3lFUWRZmaUFUZhGzJrQnu6DpU0YKEByhKiQCVKCkggQjJD1BFuoPqeZx3uDflfg5EHYqDYtuq8m/RsdwQVcHOl0meyYNSiDhlwTtskvLCmfF4XWffLzmTvlLGGHmpUU6ckwxT4be1mRlJdqEPZj7gjHayYKJ24Ami22Yh7OKTuPghMuBPFq6P4g4Sgp9WbPC796YGE1tV2FuZHNm5sGcdAgA01b6oLDmXFxkREYrBol78twYaJYjEwlRdSdpAm6y4wi1uLGza76Wii3kaixD/n2PQXDm1fb2ZaJaS2tN5heycWNIcQ6iqEcyjWU7iVL51pUPNtLp0iuF8sU6rC7oZZULPUW4NDa5LjEWzQH5/njklcmN9lFUlouBPeAYHLGTWfgttvm4YobL3zcqVzfAO8JrEedV8qG6l4/NlKJd8nlEAOEi7k8TlRQTW4eNbxOhhDGWN2ukfU4yAPZwpH3t65XODy864i+FU+LSZTzhAo+sGiwdcOIbZFsPLRzeMWPp+f6UlNMcUFEs7wwyt/AtlT4C8sLtYQULM7s8wOso2YmBPTpzCtFbdk1rbHN/KaoxuzmjoiD1SWWThMH0fHRWRh9tG2kijIVfGgluQIvEd7gWO4sUF0cH4NZksIdNWi5CUjCuj5unBTyVNNX5zATKnNae5p/gN/2KM0ZfI8YNNcIeq4oy91q4UqhJvqKvfoppmZUdrCHGBkF2bK/ExdyFgIb2b/L/VGiGa4k7d5r3YsXBz83mQh+OXuEnn0U8Duwu6dKazbvOx/3kdGsix2og34w+GlgrfG3vC0bXdkfqTbMU4ZzG6SODaUXZ73llh2qznx/Xzx79IyxYseFM5NUpvD9N69KWq8/3TPe71XXE6u3/ev0hwVXgKiaTeDdM8vlSEZL+w3MjWXO0OUA/oif88fvYgLBbhVMN0KcQJ+6qbwh8A45/8pc+Yl4J7DirdjPdmyfeL9K26DsZmn3WdZSLHoo+b+fR8bZstAqt2QkJY6xQ+BbCMo4wvrtSYQ4iWRgZe2M0Vxvi41Ib4ZNtAnWvsXsGXR5Yz7ylJPeeScXSFugoZOMSzk2M7HQYLhYxh4BmeGNrMN5lcL2tT7Ijnnw+Y2SbKtZAUsurfiqzxqJCQLWg3Vk5gEjsFd4RwKmKgo1NiM3D4Td3rUoJ2Es+fu9CVDGNQVo8lO/kOR2HF1OTqwlTILvsqMPyBX96dqxduROhyH5u/BFm+jxhg8aWii37EPX6s9FlgIl0DImJK2SsbYurbJGasn5tph9m2dc+7u23+k//YFk74/R2sSDp5GLL99R7XhW6o+a67wx21t5xfbwVsqsJ91JVLSWpQJr89Di5GTU4EXhLCy/X7obrNFk5wNyIZA7qjaYObMsgP84opfhYB62omgSzTGvevSjcebhFV42TH0t2PGQ7rjf6EDDRHhNylBa4+SPK5lNo6z/qSMpOfcjJa1iVLSG1dAp3Ln/stnpc8DXciELBYViwdkMIOb0rcN5aaX+B5hVSBjfoCkikgOcQAV/zm9IbkcGPkVDy77lr4dZYDLw3bZTLQsa5729NMFmeblGC5llTkYz3QvrVzyx10vSVWt2dqklSJdBZLd1dXy00DTRbiHWht5nqcCq1jG7KcPYNz7JuEEWRQkhRTrAXhdILy6erCvKljFT5KX5mVjTs9YzkJo562nvdw80n5n0o1BGRy5aVSUtIVf2zPxo/1TzruPWEHLl1gSyYPKNoh1PMO8qMbOG1qa+kIn/STFoDYWzMvZwyaDXO4CbjPDrXwsqQH4tACSDZfDtp4zChLojNO6wxkMUmFppUlGabIhtE4yRunfNYEhaYj19SIXb4qLoIgtwQDLbHZye71ZkrMFIUxNyccmw3bUeFYjmhV/LuiBHsqZTZa9E5lEXj+nZ/PV6s62mvZ/heZ7yVbDJsbpxosGhikmgRYHniSUxPW3G1I7h5vpsIESktB2YntPe4FNDE/DfoPyh9Rs1js/w+N9KmaXBI6jZwG2deXE63gN/gFrmB7+sm9BwpoSHQiZmgHeksVuKGOraZc8UADcrfgwNT1hhu9FZXzDApxaHTUVFzDaJi9pe3BsikuvwmNa9vQ9+GDMRRZ5hnU4RZcgyV68W2X7YiRe+zjijxeBlQkNfXgCYFnrqFF8ZUztxyPCvq8IokVmJBw2Oi3fBb2DmIs6g9XxMBDH3s/PCv347B8NS5fb5CbEoP/D5M3ANys1MaPWmcLT0sLic0zoDWEqiDMaIMQGEzHkDM0qyUZgrWjoxxEOKQ5+/AjPQct6EhhDNASgIWTQBNSD69qTBP9JyyTssqEb5lhVgkY70f1Y/rv7bzkGRJVSs1EuKVrBmz/mFKs7TdBiuyHSt1R/SqWJH1gITgAL86C/GMT5MMilULNp3HV03qqdHDiiwXbIMsooZ8gP26z4+oHYhPp2ryYw8bTelksRkJhvHs6N9lFzqfH2mWvXIq4ZhQ4zFnVZFKtS9L5NX0of77Mi3Do9JDKd2DEcHW74djWMEanTZD6eSaCYGJN9GiNulDk//lxE/SK9pyXK1qQQOeySwbXI4I7QB2OYSBFWUXFQLW41/1EW8eFfYUe1HcTxroGHsESn2krhjqnX6j6K7tA/1WZB7HRqT6m88OpwKjLHgsIYQijMKFEplOllPG3qTJaXw+XztbYpfYLRcj5psLBq4P8gCRSEDDybHICbn8EIULkfr8rv4hNGCFqm2HT7hfqhBV+WGTP3AUZBHGiAvh/NeRExD4l6dMvAmUqJ6d6YRpnAEeHzuC64XD1MBOICailx7oD6Oj3DAZReGo3zacOSHzHiRjy6tf3IGiN+J5Qk7IHShMOnDfTpkX4fHiP6Cw0N5gK4Qb+hDiwu+MphpUPLkfw4wkNn2l2rYoMHaaPeCslCrBX1ze6vEM12/7TKBPWZLfkVrtvJP8X5QbgdjUD60/inB4ZKe4GfXr3x/7wrrxdfIla+7ib+Ryk1lDClF45HvQmGUQRkNso2jHDKs27PCB3RQHJOBDRDdpzj1+r0wdpvfrNp8hYcpeCy5C/CgBBmpi7oWV/7VPvlIGDr/On1seqMfDBlo/OgcqBNo4U0VX9DUi5wbwtZV2elBq/Zh76OeS3eUADVmKmChCLIHL2ThdVB0oYsg+5/wIMUoQggHQgUgQDXqnCl15A+ilGwYDVcyn1ZmuWg71QbYnMn1Khq5rKLpiZC39P68c9UNmXNv5ixb9Ex4tukZFNA+uExhCDvRmYKUVTrhlAWrpAQirmbF13tGiV1JBlNeJYl/Rt4ZHzCEd6dc8l0LWtJoBKg5dAStsBM0tuIAF7CAxcE5QOIkNHNm0KgGZv9+RsLXOc2NrR6OfK8lN2y4fgotfvGEauC80yGKd7280BCgBAcmRWmhr0GXVWumIWJ6TpSuxUYwFg0TdHOvF1Hs8sTc7jkjW1tEjSYoIgoGDN3zBFef9u5pRviQkzXYz6Gw+XrDzZXQIo/xXw+SZ28TWW8dmFsDeEr6uGaUroAhfwgCOXswZP3Wi5owDpn2ze6Cffp3b1LcLxjCNCmMNuwulFA55NiddFlDwSjGKInyoSPLg9ZoPOgx+3D54fMznZ8UCKfR+ncFX9JVawhzgJlZa5iD5gCakRxc1yHTkxLkJo39QibVmLN+mVbq/A4HfebeBxtekQpoGQQqcZYfLV00ztVB5Z0jrbpfWX5mTXKxmfArfhlpQ21ywjKF2olp794nUaCZqS5419xlWnPD8Nvnas6T/9qGbP96Jd+lf7XF2a6Adzo5K92f2hKXJ+QNX8FZfrvcYNMG3SdTN6Y+9FlTMleKxXYsdj838je6f0/rk4esV5Y/MdSuaefelMqGgjYShRoGhGGUwb2oV44sa9Eobjnn8koXgN+I2x1dcLHlcBqlFYQ4jTqwY82elXSAFrkluA5FE6Eghq0fJjQdd0IC568WCD2JoJh7Rk4AJfoFytFMqAr3VmBTo9kkYvz/Oq74M2vjTeOrYX/lps+8T3yuT/0uMcNKTFPrNkhlz8Ji+Mgd0OfcXWu7lqYHZmVg2sNfnCmEeGqnRr08BW+djJTBmn+uxfULlxte2t7zPxkYrdoRWRBrb+EddkXj064AgjgwbVNrr5x/yZxO9bvkzIv8BlckY7+3jz3wfRlPMhfNZPqy0KJR8/PobxW0b0TBfcF9dnCixuVrwU/y1TK35faZfvd6BlGnFgozsc3tqZ3bnB6+3wyvwYu3KL6JH+Mjt30u+s90+4Uu1cnVRc7jJ4MLck9fOYCPL9o37IvFk9Vw+pk2tUeesyNViMBQJdIajY06ckXDsc97VTPLbpsMf5XDDiXVNSHj4a9SnBJzSxhXXqypx6gExiOz0iKPbv0g/OsX0eK7U8OjwuziYYeLadSDxEDKZJhW9M+SI0LyIFutwa+2D0+QCdjHWQasnErAZAMccwR9iJwDTJr9TXjxLjHhjmQtNiHvTg7+5yWKhoklom1EXYGIR/GYKPEC2vXOPunRITlRRG78H1K/+LflCELFqlZAYWxmTOnZDzAFJljQqvNsGIoQJzXsG64LB73XuRLwA1sIT9WjbShg58x/nhSBz18C+EpiFAMLqL6kA38seHxuV9p/X6c+H0Dmoo3H3X2UORmkzc0YA/4QYDbw4lx2PPVJhPHj6jBvBmEPUzgT6sboFLf5sVD544qVLMOKuOI3+TS12PNtjTMfYyQpo5yE4A7oBflu1jeLNyCt8hywcqfu7Vv0at+UQN73NQ+GL0Q0tRGkn2kNRnOSDbZhHr0an8U/siufQ90PN+OB+8sTxgAS2U1lObtJL1qjpNDkTmteZlnNPLGWZgjWf91tVkEl7O0HoycotE6wWb7PtLEUuOlp74OOvu8mnQP6169FZyIYFc2+Wiyd8aj4wNZrvdw+DwhY133dQdvYo0N+AWRxkQLvFGg9mc8vUGmAM5R6JO3DospbEjpuonlmRzzNdtGxxAH1W+kvbXVZvMyKykiV3Q3tFuBgV2rN0dhK8jUw8xmjd4TmPd4bRXnyv6UNDvmvHdYcPPtN6hObJYt4i6lfuV28Q+dx0udq5xfigNyktDBsy2UJV33z/i2EJX/vq+MdooIsasIoIU8ajrYocUr+eCnPizHWMA8u8qZ91XZZNR1Hyu9GuZM8oRGLoZxKZQvY0bP+kH6biLChhLIeArMaxhG+EyEeKW+PryUMMbgKitj6G3cAcUaZHXZ38hieE5wyE30xr5ram2ORIL3ix8fBaljf6UOxHEt+mf+Tsx33gu+ZxNqYRQzzTvA+JcNKx6OkKCuxRWiPRv2hh0Z5gutv+zd5EcsaovuzSKGuKJNGR3iX3Kl/WsBxz2gCavKc5RBnybmwUaEKUg3QO+F0aeU8JJYkf4tUf5Eorwm1ZH/ZPlde1s3/ImgWAAk25HeaHMrbiMTNqzDF+o8FXC++E0stA3GIWxfIVgcaCPxF9ld2PGGrRs1Td50w9W2kTzYcfu8+Zby8YgaEfMCm37wvU6JV+7MPipGjZhL+F9fisSS+5xeryZOzKeuinaMXdsXXn2/ZYW13eIaeZILu6Ual5eXi0Pyel5tSwU0gz24RgNEiJo0dBS+854paA6d2v50PwYEgZq/sjdwDU9dKLYmfySyJQ1+Mv8seoD/1MytEjSaWf+42I872SKtm9WTRM+pwuw0T8/Fo9IkKyLaTuqqtRECbEtFU6phUftZxh20sT3zX/l8X0LRp7iYBq3rso76bzy+9IhLvss8mD7d4pmmZLU/RyVFxcjQMWbOdf3vT4jNiwx8yU1UxAv9hvg5PWPoW5z8lP9M+bfnKkHiqOk8VVQo0J/4v/ph4GyiAZMwugOKnspUUYXQ3H+4Dgn3TnRJHhZDBjHP4D9gEC8/dbRG6yX5U8ZjiVCwuid9LMSXdXuRByC50TdNjSPrcw53A2cMd3oyzjtvF4OOwv6WBLqmdL6CdTM7sjHW1WUtTrcB2hTXoTQzomxzJoqNIhIjNDHB8QwyS59CVEFQ2iTpxwI5ctQX+CyuX9u2turiW2xL1Q5nU+iuAYwuMDbVINd50+yD0rEiAVZRF01z4KZK0zK0jcTz5ZcbpNlXOOSdsJZeE2mFwC+B5uokmW6z9HBjotj8RLjz4s9cydrtwpqrcsQ2QZ8xC15XMtwzHS7ZcSwhoNoxBoejeT0KnPClcrlXF1a4W+V9agsSxxG4/8OOJm0WiiWdATkS6Ic73cB75jTJ0DZJsFF/jJ8iV45xcS5ydi/zHZ++7cRvu2uI7hlPAdSD90bn0uwBRaifLyYgB1KX8bZwjI3xR4Mx6A9pQU0AtXxXyS8iqfFJvwxvO3SNog4yAei0KVNIfanyHEH6v+aMu2bopKHegIwn+K/N6sw4fNN1olG7AiJ9ESbytv5V7Ya8AFBWZGMPY2DNOpygJC904jcc2km+2la+bD83UlYYmf1g7U9TtVvj3OyB/xviTVwFz7Zeil6jmN+H4nN9bXfa4Bv9mLTa8tHEkJytyz3xxgQa9ln9qpKzEuvD5T6AvgXOGxxOWwjZ141mrfb6Fti5p15SQsWrlDZWk+ylVtlQa2nA4V4wVaZGU4ICdxXXYjaSZupm8NlO4HUXwaUhX4LCN1xWrOWinLCz5RyL8CpOGvfR3zzxRQmlzHaMKhfk0MVKKU8fI4kzcHafz243TgscQF7MuiXBQyHcR5xmioTvkJm7gD98ju99b6/5Jk7e4+wm810jBfv1//rn3YqHPz28b6PAd+n4juQmM9gboi98tB6hSxUTvI+9zrGtpGhNGezVMe/d2KTVp2AcEZCpZ7igquZjZCkkm0svFmPKuR+3VgfMqeKvmw04gX/vqKB6EJBVU2QUuk9bBnyBZa2gwB4ZhtAL10LmoQ8e6Z5Pp5klPRZhFSJZqNjxv7IiaMUU5X5lrhxNbjpde+ODeSZliw5HzpB16P03vkTdRCFoiGONzmDNG28Qyo4dXedKO4/4032NvWRNfwzgKOy5mYk7z9wn6vt4ji1lb7L+kh2t5/Qf6HJ1QRE7qd5XBFLi8cMnGbf6izDHmqpmnuyZykQ8p87Eu2xSh3RRXUNGQeM+tyJoZftyOwnrRXw9PANFZTfOhNekZRd74AjOZgzQoZPAkChMqq9m9qG4uE9M1VfEizTOpC2hqFo7FPhPSqgt0n+YfPv20WcQtxxKuHMr46DsGwBMJQuQ5Xyp+qtgO6enEKWkCiatfDDcZRMlfjiijVucSfVUMQmMS7eWBzOabzFSXVAYcodpP8HSKZXaLCvQy5VQuAW9UYzdIy7cUsSkmuqkW0rBDuJzRqB5qluc2SpVMaKscSSHiKdA3ILNypqkudTKQgqgbith+RCd4NrvdYYOYqKlTXfogb/qxaOV7Sk3pTf5BWVeEPjSbt1dMF9YqXszWdN8GEnIc/MwDsUOqJ0m0wySZsGQ4GJ5aWqaUG7lYKwWOZHHIr2eh6/PiPGvB1gxXwAh38qdGmcK4CEcLU0dWPjfsq9yOZW6pANQsCzJI0AQ0w2vYaGTGvdHa2Lfe7IV9/X3y5uVni15uxzZIsNLntc9R/66CPLnZs35QnAIDTby2JKBaKJKWuC+M+xRN29NNvX2mr7alc1vEe/1GEBOkXf3ZkiJCTO/mwQBBejFqQxQZRTZJxC6F9AjeUOpS1gv6CBwkGHCI25fSzczG0TbDRVrYOlnYyQnOQFwS4BU0gmPXqizixU5SP9HSiwlbdL464aWdOaAJW4iT5rEHeaoplOIOllf1kpe8wktOPNT9+pMSTJtrDTDOsuBZfyqrs0fhoShuKHVvCm9kcd8ptTjwwBDfqqSH5iH6iGmxYOlvYBeXeE3f+WuBnS+5uJPEUMAQO1n7+8h3cDVkBnhYK6kv2OtMbUPBwQz0qpC1jDziO3hVg0eUg+ZN1mGTGqHctmrIY/2ULRFbYukq7y3O5pXsQHt5fBZQl3qF5eW9bYyn/CRxD+qO8jpl6iGj6Z+TTDhgYL8uYWETLTAUGuNQOE3cy1QSTE9q4Eu4limB2i8UAZ/O7t7gZeWu78RdO7D05jG0LLZR75wmYdfb2syt9WjonvCWKmPiuuYASjSzcBCliZ6MZT2pNuBFvrsg9UzcCw6OiaGtcUcrfcR4rFUgRquyR/6prz5B75Vz/lx+9U/6YGsz5+Kb1ka/K3ruuvOpJZbUzXmmwFhHRhxlJeKlMjFbzL76g5i2gfgvraHYxZNLR642kKUxoBABtRTsi+yt3kgabwvTcDtuF090RYfcofVboLNKIyjuj8P4oHZ91+ghU7zxJP8NUpnL+GK9cTMaBlprcQdD631F4t+Gy+v/LcRZfT73NPbFk2El7cpXJtmybYYYa+xYgiN83Bt8XDK1MHN/zGnEuVze4TqdjL12uKmEY8sra4WD/Zpd/JX6efwdEbG0afVAfQ2xpqsraMK2VT9eyb5RooAHlbKHVeQQUhopHhdmJG2YacdBeUVPSGFm8iWYflm4ieN9OV3HEi7/XaQffqfRiswIasGm8zlIXW7lTgeZIrCgSXvVVoHzSDQ0uY95lJFjV5bBM6ZmOHpHBKEcAQVqfpjub5rF0PpewVq8DTN5PMmkppQhXhdtFtqQGl1MYjIN5f7c0jLjkkNhykQMWoPgtfA/e2145nU89s8Sv5yD6JwRdW5Lu6CwftgglbQdjeCJt4zsTSeFtxLBfoFbQBFMm9OYqwlgjEUxLugJLOK8TCbPfpUOaAkNa51jhSIQw5HsTTTtTJHuTK63uOijD56O8OGYXU8jT3hltf6Zpv5T2n1f9lo03mxl/PpRifxXX+09RUd771zf+euOOwbRvb0LHspA5F0By+AtlqmqYZ48OxWxk6DD4xh7jazwXgGnHAfJxbviqBnD/RgJbyd/0VDP+2HNOhPmaiJ+wL5KyfW6CD83p6lEOnKQb/6F+iJM+DoK+s3zQoJftYK1YJe3qFfe1FrqU5nb2FWo4Dnhr472NBw8yxyd+3pqSOXsgs+M5pYWrQ4LPMLqwkkSqQulptnpi8IZDKjLKnKXpIZDHUkL+AbgSMMFvlahDGMAcxEb5iStWKybToAtrPVJ3oKLoqZG0Arx5OnRPjyx0UI54QeBy2liD8/xJxfb01/1Wvu/pUNzxvnRVyK3n5LSZNqdlxrSrsydXJ7NCmNue0fZfIBitKXuzYn8m5QAiudxbCcrgS4ec9KStVRfLG23Xm3ni+03M3NgxO7VGxuh1rJhmzJk/YrQit+PMgXeI7XgW/mxitjAxr3YW/25s4JTqbQw+JnXSbIQyPDRwHqkjsxEDxzOMtSWw5cFb0mMivLPv2Vwm0K8vDRM/qHn4uSZ2BTAPYzX1v/bGTe+ymOZ+/Fw01yr9AyVKW4KEWLykGxrobareh+4u17I1Bd67uvRjuK/vgCRe6jqutiydpWO9kOPt4/lQk4DghDyZzO96tQI5vM+k/to/X/QntFb+zt+tFqY45ps73/ybxXbWuocQQnmL5nTte+E6z+MPOQuJJ9YJ3G3NkhftNkiwma9EI+vL+thALEzqcxprNa5WfDEtDEHDaWEkQsgAF+AhCUXdZUb/8BHP6fwpuyNlPeGuy2SlzSqVSY5yYf8AzP1tUunlUw0q3N4TITH/yKekdglcL1Ok+yV2bl+UN/fH+VcFeE6uPRsNrdoqZfPFXcUoS1ZOagdgPiGiF8SQaz+fBvf//MCf76uK4RSydU0gqvQ/yP3khBv8vFqxI8BQzhjatUnimB316KRe5AuFbSMWF4DnCZ7DqrwcACuFVSWBCoU70xyOvj7T62+rZS86NgCNZRuycPRTThpfIAQX71PV/IpkcKooD+29KEYh88MMDr4AlTEZlFWa+5r/9oYxIPvwaHaVtTK9oBoPFTNO4Dd1f40yz7Cm/YswzimLCDIoDKjovvJGUN3ywh98W4kuW72X/p7wayBZPw3dKXS3u2u41kdemX7TxnuC7ziI9Cia5N8XbHR2pWxvo2Pue1BqOJJeIHdy32KECiKaNKzkUspUatvtexP0cezY/yoWzZxHxL79X/Rh1jdBYC8B4olFtiui6fFj0kDH6ixPq1a4hD2Aqu+vBt2F3DdgUeR5BFn0FhqAO1/M30MYGLX3LSXse1Dz7+Dmbn5FmF8nOYAHfoJ/LfHSl7sQJKU0C/0eNRldYF0Z1pTWX/leL8geEXVd+edJQHEOypqnqM/PzFk+EHwcsvtIpHaq0DilfJkwxEaCRfYLpb5N/vKGVTyPrNX+SdfrUPdstW5cBTNyFpaFenlhWSq+fbYeNSCE8LJeTxsfmw2/mfzyOzsPw1vjez72HsBEws+9brPluLjluQCVQ+DdNaAHPfHTWhL4DKkbQzoh8pMqH7WecuclKpRM3R3E6UUZW0dHyZ5v39ONoaSc6FWtMBSgrAW1Sg66KJ/O+xHGtEEc3vTOlUtpNjLCP1hAh2MRv/3W4/jaBIXKzbJo9uhMdEGbZN6L+kl5HW9pE+fW7An5IvrONdgjQ55mK90WHYn26BXiv/Nq33rkdUjvH3xJ84UHc+qzW5H2iMw9xf4kGVN7s7LZ0U9asetKrFdH9wftt2dgHk3YyGGHVIPQW9+uTv3gGW5U0AlDGHKy+HseIlbtCTMnfWuxtPQjK+GJQ1c+lNiuwsOfFy4FXkj2QVb6ozCWaf1mPCrxs6i1MhCZl75sj0WsIB3z+NPECDuRgeEIToepfwjnA7jFWUOlG+OSnMe6qneuPLi39MSyPK2g1bO+ZDGqNARIhuSsnW2GXFhM+NUnSndnnp93bAAvWNT4J5bIGLFkurk6PcGv7U2hX+OVe+9jHrx5912EqYGnLG4Ck3tXj5uExoNn9m1llinqImTeGauV7eKUR26GnScqRULKebnfv78jgkbLnysEZt79/gubN7jCOhhmU5kCKUPkz0BAXnu8SnECuDthJA1ogmavtS5GSewq+bxqt0/xFS2dOVu3ogoyhNguT8MYcvLJo+dPATBv6e3a6U9J7vL7lFJms41dVMS/Oj4P3VCu0Av5PQqy6intenCkej2WtR/zfjaqyshpFrX7w02YTovv4mGhCiN8sDHJJBqOCCNVn3n8pdAiYl3i30EdBNh70qCZA/ejFOD7sEer050P/hDJOS1Eg8tggERMZS0rPH+bUwbSL2nZSrdMmtsgD9lTrtgvuL2/fXUnBFXKvC9kRC+EqA3PgcV+3spEastI9dv0+QfiBIvVst0gjXdV8C0w7huMzOwKV/98wRffX1eKtUXWInyDxTHJ6dINO7ggI0fRKWUkrVSPPMode9QNxTyBmjAB841QjfR5PnN+y+ruD29N2g8femwL4yYgChkImt6zuh7+UV+PVHBBV2x3ha3+vkHAESWW3col5doGBDi266+Js3YkP/1LG5nWIdqQdBfBa50QePo0kSZUTRehFYkCkxuqlZcYvL2LZlnyEKV08smCAqkkNBvsj6wZUESTC4UJ5/Jz87KO2Z+TozCKdB11orKPxJwBTWMCWsgo+PTzOMpz364pWtbH3L10zujUedwcYgTo66XpdqL0RXn9v6EwuvNOEN9xIKVSEM0ojEKWzUbqBiWqiNANReor34TVD5U5/q/ow2ctQnM1ufmMCdmWMClTb/pu6Uc6Hh7blIp73AGg9EGjS5d4U+tN7ZpKZsl7nFZMDZvI01FG/KmJHILt3trSXTI3yD1StvKzrNVdQG30o1dShdAKblQAyaYJPBfBRIIP7Y++Qi8fpwg8HqU8zTfNMcmmgyYh1+Sx0c4mvGBgCXuvukAl07fkvu2mdbdiGrHpTXUMMDIRCDd8NXAi76zqfBZm1b70qLEF0IwkjFQP1Djf9G/VNvM47KnINWZgGfDsM4ATPusVvq4cE/fqQk0xbyy6UMCe6Pho0PYQ8fAvr2DwcHZc9ZQioYewtMiMO1oGfkpf5kHcvOqOI4LjsEUxtfINXQUXdQMMK/qWMsjGKeKOzsXZUWXnbd2C1n+yVIjzamU1Ilf3Gznkn97vpJb6jB1xujTOdcv3vnZRPHDJsBU0/z0QkOchKffRUGltgGSvjvAi1jDitf9XgBPaSayS3kVIlqZeEdg2mQSJ8OwgDEMtTWFQdl6YnCPB/ql4+5X1YnvTl5rWoG2mRpImUT8HL+PgCAou29+4Bcr6W4q9Wkv5QS6EqpUgyAAXx/x8xKV2l47wIdfn3o4jIPEvITO5LIQZoEFtvtknsReeeCD++0YkC0IaByEl5z41iV6wfjFh3dZ05Matm3Cz/l45c1tNFuneXyeRO6umkhWz+fJjaYwO9GTUWz88lZ/7o/qwaUFIn6V1nrlz/2VCRD7LanrUJ14cGjOx9Csx/TmzD0GvcELVx4uYLsaFvfn0gZq9xJL21OU8Xiwl/7r7vOAjhTPaVXYyYtNuungGV4R99Ba5BXyIAUtLEc52rQxCt2m2QFdcp7KKX56tsmkoi0Y5CqpmjraqfZBrntUKPHaelgMG0Ihqebg58GJGvgqLJNGUIT1AsYvoHJBkOXoglTq21V+fPB7UE37WauggVNPiIBib0lsi9UL1Tt+Ref2VJ+0bMtw+ea66I3zJLtZfaMJDou47V6IHyRLPTBw7X33EdAOCMCJOG5GE60SwGsYDU7sckiwYzokHO4JyjNZTmhAxzq3yyg+Z1tesD/bh31gIJqUSnzct+GXGtbuJt11pmFrPjF7nPPentUWUlvisn+rMx9ALE3n08KDBnX2pYnBqpzcBS6+8rQ00GeKMcA3TE4E8mpnnvImMVnKBlhgvf90i/vTouPWPIMnq5Jqxj5Fc87yt3kEhEpJBTT7HfNXb+omDcTTELXvKO9uK3VD63Pvs2dxJuueh4spP2slpivR5UV8+D6sIlcpqj7XLZGidrxzXZFh1kP3Yhd4Q8IBwxznreO6nOvlNA63pHNfug8oaRhQkkcSC+yEAqr/SO8cltQ7rpSEPBWA0gTuieD5pKon8kzmITUXODe4+Sb5vnzwXjSMVM/BNOxdPXju9j1TF0Kvz7e2NZLDKMjdXBDjEp+j9S7+Hm+uogF92+aKsBgsf1JbGKdrNuItXs/TdvFjT292Xjmj4dJKGf090yLYGCGFJymrUIVlgeVcEGy1+Soeo6ljif1c2KBynzeC91OvDArdHA88K6HylPxTVUSMUOiQxsJkzmekATNNSdxT/nDHowIu69+QK2BibApTab0cRdr8+ftSYBmTHFxYHEBn8n28L82r/PxmhmhvKtdjf5I5VEXT5SwZ6Y5vAT9Y7GZk8GzjsNYP18Oqb6McI2z+PIcddzZDnlDpxY24rNaY7zNuMQJcaWmGtZO3MSm5x4pmXGI6NwiRsnWnf4foblu8el/U0GQkq+Vfxczhqw+LyAzCwmAM5jbcT7kODxDSdg7HP0op1sh+1f0yafZQkKg02jsAqRKC85DLrLdQsqSdpkoGC5IXzVb7f0JFVGQBzK4M4YvlqIzEFGfNr8dkjQFEGHAAEhEWWM9U24OwIeYaBV/HAAqxkP4MVQkFYar6k3zk2E+9qTHv/T0hGco2eWnzOw3LZBLXCpCT4YMUgioyiGGDol2n2HK3aKzJUqydRDrerJEs1CLf36c7W5QmFRsWJ/ZxxPtEfZ9aWb7vjjCPub3T471bnqDK1PSpMMaEnQ4seaOUVNtJ25MxJseMzgSuGCze9OrGMZv4B0eVHnuFddMQtzFjWv2bubgYOU/1X3Ca5YFRabJtlSHD8ZozXO+57TzjXKZ1RtIUoYvjBpNI3/3QWdmNMI7cuc5+gCR/zjtBrMWkm2t2zoTWFPDBx8AzJSLHo9JVU9Y+y/uAl0lvSWQi8Xg8KIvUQn2FUw8yBNdiynIIJ2yMtrQQmzdcBYdKeSy+IAgCN2gdkuJWhTUQvN8MAyhrC1lmUPFMHyDOZWB/0Y3P8xO5oJRYcjCD8E51GTmyabcS0j8s+SuS/6k2kHGLv2qq2sqRPT4xDjJWD2SUfD4gax3ILHupQPuWijc/9dH5F91qNzeRNTek9VfprB9/+0VueTzE/JmK11379M6TbqMXS8nmcbkpVRLYdmivhVVseoy4NNauHOvNVvou5UWNpXDz+7UYWwt4mJGF6ueiwRkmnnDFku2s7mao1oE6lrGU80OV6nZsUOruJLD995EEevkX6HMMl0TJmmDIbj9RkIIRQuBLMp5bdxTDvix/RqAulPaGq98e0HPQAbvtsB2vX2QIhAO2bKe/Sz3XkTTkB67GxP8vCPz3pK5X7Irzyxv8AvSXcHzuNYAqCJUuFDAviGPNZLPfI7324CONoq1i9yPyxcrUQ2YYmeSNZOV9rSKTDUYUof4hIkgZ0sDoIsoTmTh5losb1ikJS5li2zjPm+W/13EC3vFyIyOqKSxUJCSpGuqDErX+CooylRtJiO2jRBe5beKPOQJ5Ohi1vbiO8ukCsvcog6PkEKt/rza8ysWa8yarKp/YMgTMoH84ETL7WSDSYIpNghhW0ua3c/a/ni1qYdCbysifi0sx3ngz1MebPknymeNy5K+WJV66nuP5dvDgcouZRDFJVEc6TCPaOC6YQqIABftvl9ZGlbiDxG3HqeKvCH1szE1fN3Q7Sn9pxBGvbGJX1a9BTwj85cvRtffteuqM7iIs6o2kewbKfTzrt+0GE0x89hnv4iwkMUOBEJNZvVuOpmSShSlGWMgRAocKTMNJC4ezYhwLszjv0igW5nE5VUdpAFlM1DZcQPiaS2whqqW4ruvylJYASPV5atHOkQDKowhXZk0+qCLNgPoEQsnjC8+k/Pw2+MZdHdrXl4NvXNKIi4ZVitTAkU4oZb62Ht2GyTi8wF1hJ0Trw2NY/HzUpgXu4dEsDog27XNAq5WaSsjGrz/DJk0C+qLiUnuXW9dfgxYlEhjlPbMnaT+f8dOKvmYp/AL0a7wSWsq7uX9hX/fF0+dp7EVzMPWFhb7YqyMOgs3JBQW3G+Lq2EJX0A/LVjl3S4d3HYH5ctTiOpKj3Y0+ubtdorVwTsK8+Lvtucogu2HdS/dPY7ppPjvqqBZTJQv991ak5gYnpzeRWLPRSCAg+7/xQRD5Ccv2KGI1rxsqevQP0gp6bblJTFkFwLA27SMdUQJtgYRR/W0OvfGtVWjKHxojK3JR1kxCLmhIXTwQbY7lJ6fHqWAC8JfPu+JZ+PziKWBk8argaoDKEatOsAxITgdZwKsSgf8F9+g9+ml3Yd6RNTLzsC9eOMF+GddVgk3DDbYKkaxijSog1aZWpzOnUnX7Spmb97ntFpz9Hyvh15NeQnI5OQbKiAaUQ4B8c/QLzgxooD4ty3rq6arRe5qWjyjVr1rYXurmaT50gu1s3jENfhi4EhK5LGABgayE0FtElpkkzhqEOQQTSLXoJQ7rHIVQCUMFIqjCzc55bcLp6bcX95YqHiwhHpng5Zo0QVZFUS1eQVehfINPn9Jc6OJlCJUn0t7ybt1qBJFP6HKlVv4cQ7IF83AR4vw5/COF9pAd1nihzeFU9emH9Q9LYmGkl7rTy+akue75jt5iodmX8M5VdAzxNePBO3e8HjBF8x5KvzBGAr6HzwKeVPMBmj7hWsiBDVbL/lMGVOaQ83bd3/MO3HsawgdE5dPqkxVF4sDXgFRpVI0TCiwAx2b7OyfNUsDg10sLHeIvUY7J0rG5eGfiRCIv9vsprYcE9i6imYi2DCL2geuJhleOzrVgByYA2rmwmeVzGZjHYtaA20RYAR6ryQSeq+W3/+8Od7csnoP4G8n+hC7tWtG9RQIRJgA3jHqg/3sROzhVqbgWXezASJ88/vD1qEcJB+VeHHmrMR3YHxWAYrwBgf9p3Vem044j+8PkfKxk9Ue0osZMN2Pu55Q5HL+9G5caZ06krW8VddzyxEnBhc7Ht02gim8c9ftPRjOOBQPlOBD1EeP93gPgR/TimhGOzlXNJKZBSzPWwXDCCyVAmDhdTgu+fcyzDS1VpFcFlAiVrgAT1epB8TwPUCkAuT4iLMpY7nzmKO9/k53uR7pAT9FHDWR4/FyNhEVTmSaxxENwyxor7j/+xIT8qZ5Fk07s5YscVqkxFh6VYKqqFx5AXwQfhuCbB8YZY8WmYM3ELIF4o1X/8MDskrsnzajnLXBJbpEAmxYX0EaK9AENr0ObRBJj8kWRxzw9evA2GH5I38vYS5XzAkUGwgcR3R7YxTcoEIQtzvgKnDPAXp+1QnZizlc6IVgM4mAhSIL9f5yW/lK5INldzQCAWg+VlGQsNz99QO4Dvxk3r+hyoFJyU9RfYHqIgKm4zgT/DvvuUqtFNFyh6hg3oki63gp1KwylC5LjVmKUQ/inFMq1D7E5qjVVjap59Bo3OVeSll9MoTpKaOV14UC6/WuUuMxDV3OsuNkBE2fY93lYc/nz9JaZiWbPqE0dpn73tt6xtURfkZFY265w32JM+ynbX/lfE1j9yYlqb9XqpbvkaJZsEDys9qLoGOnSlZHCJcOqLeepm0RYRIA7pAmXiZupZNyZ200V7lu1kK2xmUxn4zbxPJWGC9pupfbWJ5X84sOoRB3MDsnKFRfiAAiNnXRpvv6jjNemidsa7ns2F/OenMavHTvSTw9kt+y5/67wPGzbjrDXpdMvQW40wf3QrwS4FXX8eIoveurm62t97IWTI25YLQREiMEUoZCEuPGarykhDPmPH8TPt/r0m3pBhk6w23CuC9yGsoW4k6SWPFiXYnZ5zd4/qQR/tRfzMMEm2rolKOmtbgU9RXrhJi+hTXE94E9rYbXpwI0MUin/1KxJs1KY3LPSHYoaoyPBjR30EOzskrOMX4AWSVs88t3CaXg7jXLAb4WX7bgQuHQCybzIoL3zU2MDp2Z42yuRGe8lsL2gh2cuNxFksUidKwpMoTMo0aO9/Ip0+btNpvk+kPI0eh7Gfse6TcTkouROJC7E8/1NNZtkJYU55hfKFUepobWuTGNTpL5+1q4tvWEoQtTgxCexNvrP3xz12p99rCuWyuZqP/37OEpi/fngSM/cZ7uChzUfvlECUFGtiKgBHFAjGGansyDsNrGZJVkLW24fBrUlVJBRdf8gHC9NngXm4Zg5aY8v5zWFhGT0/mBP9ouJ28Osgw9Rzx8rj3r5Z6Or/iECWhiEaDi2fUO2iuO7KJ6S/SWygd8PEJZ5mU1c0/FsJCVnPjKh4fCUKlU147+PbuxuWcDWOfPFWfDeLPSc7TzoCLxGrJSsfHM0z/3FYa8xo7W7yZOsU4vh+ypOE2pig0vABRzoLUL9UJqYGih2jBjrlgjFrqQIlx03xfjcD5UFCSt2SodWgB6k60TIJn3++z/uQhS6cu9eDYtLvb6Ic0rFOrW7R6VuzkfvXL0fPH9nKlfygbndFZNexQFZlrE8wIeVUKJimFkEbYGJROgOm7KfQg7/zNWU+7HwZzcYMZ+AEgq3dGOASSBbksIlXYKGtga/5fTKKxz6pGl6w2WxeSJWUF6OJFzGKOtATFNO7UPVqYDxFhflSj7CW6ZM8Gpz8hjevhwma5fSJp8M3EnghndiaExouTh8vHoP6stNZlqS5REYx9MYCrz/psXLM5wqT8KypzCa2H+le/us9SQrh+5cM8QyNC92tenNnAGlFIIHh+O/KctsQPtcStwNPlMW8BkePiOdwMEIwafeK+YMMjH921d2KGvyzw9ZOyGTGHroZ9tOCwUDuD8I9ReEzye9YrUcNwTSjvSKzv0gmBBAd86N9hOfM515VuacfuL0Xu08kCvy4bX1xiYEJavNHvlpNXEev6aO3HWwR2P+28XCsxJn/xMNfAsOgw2tWOiOtDp77HdmsQ3ZM9YwSl16Ar4mby6Qd1KpRz4bdQRbANDpMHp3wixPetxwHnZQ6s7ZfPI80mv52Qybb/B0Pjs3Otn+di1ueAkgwhbdvQs4f37epeHpuEzxMqvdeix+D4eOoYBkWc8hkRepnRaA21FuQrOEHWkxqGWq8h4W7GSWxPAzbPrsJ7mLNOOX+xNs24Dow+JQw6//7DriyAgphmMkFsoLAdwENZxYwc99LXsRGYPzq3e0wn0Es3iFuntRuXFU+ijYqSz5K7eWsy9hCECO3cZsDyn349ootkWkXH9HANDHgHL+y21l4hNuFnLKI50e4SfNhyBGLcajXmuqax+BCMoRNx4mAXOOoGAmwdv9p3c8K3VzMXiP0D5UCqJ0GwLd74am51p3E6/YHEcc/cWnI8I9uHCTH93Rk+krOWcG64wkfdoWmq60D1F34cxiLY3TXsGbwZmakha6kiV2pty1Bti+8KGavQt4pimemIMW5OtXYpSqNy32twy8kr8gie2yOQNvDVnIOSe2du72wPv2AGd6os0kaWEr5V/Ms3U32WBOjLo3J1sTFFfIQ4qi2fRuyqFIojpgEw4SAv0RoGhfEd/N2wOv91vAPSdzDfcFUvFZIHiYvrxDJvXLpNjJD6QKd4fYQ1bAy28dmU8JAWPwIr55+KP8k8CbmgYVQz9CDiNS7pWZBlY3XX9vH1vIIPJEWJZtjecpiZiKBiOZ9D4CUUTMbxkPE4Q5R1A4k+Xt/qew49be85nnRM6hVi6Nmg+EoCQYS2DXCcaKdJnsOrz13OCuysnIPy4yS+/fxdlYhzVe/35AeTxyUryhIWBC+gZHzQlaojN1vpJ4+gVr1NpQx1dGSIkSmSk4BIojYPMV6agOHC8MotRXW71anHOYn+cwRRH3jDrMOxbIb0ZyIRUJRi0HUUJUK8F2Lwt2kkMh3q5/why3uc4XXpVYp42NJiinwDltgEr61t2hv8v99W/ZAw7buuqoc2oMi8SCVQ9UwZWh6k1JOHTbZ6MqFEQ5xabdey2sIFCNfrC/Trbra1GmhL9WoIYJmCB5tB1aSBzGcdThqVKibtXdkeCIlKiqqpQAcGYvP07Mv1zT3BW0dE2mr95JF3lDnq9/wfGFwB52AFH1xl9yvIGMEg7R/7viTk7TcfSZJs8rlM2r+96IVlrS4j7H1lOnkg96gMMPmTG798Qz4/qbh6/VSiHomN7U55yQpcCTvzEGxrjA1ch1sN8OS6Z7vVdqDsJJMrDQYEsWKCY0MUXViZiVOnldBuTVTlvKr/ILpkW5xGMmiGFGFuTEBjDpV0xYYEIrJcgzslahQL1wiZuaOZneZe8kCKrvewoUsVhBI3FqRjcDwgrCaCHfkMlgEXcAKxdCkCwjcRDFmFoL9ruhdh01VMXZ9cwDmWE0H74qME9r1D/ySaFsr6e5DovWeU8Opn4iUp01J1k6oKfa+ynnmNz/AhlHBCkI6wMdwroAbicbaRLdU/4IjUwxqDZX/cdl+sGOOZsXDQ+NfSI555Hjs1A1Z2JH7v1QAvQ5jNndd7b/tdtdjrhJz/nDov2WX4io8Q2BEunud+uxIzQAoo6E5bJ36lC8QOA/Iea6XyT9OZ1mVc1CtcvCeUpZ30/czpIQEkdx3xZwrEI7s+zv/lpSrDrpZM+JNE+u95CRr4tx/n/y9NLv4F0PneNbKJXFZOkrSk1aXzbIvutnfnJNDOuNz7/THy2nUSbMv+5qkBnZ1B6J/21n+OraLN7zVvvCNK+2hI0bl5xxjQ3VZJMXsUN08w5gf/AEZl5OewodEsdkZWHV3xT8VZTfzPFWjPqKa9nMqL7ALvxLyxEb8+ZdZK3TmrRulSG1zgmTOLLgn1Pb5+qo8EL2cedhct1UuhJuxVaBZlil3GFqIrSjcMLPlw9M7DNcGBEDdPjjptpBDXyYcamkKy7NyL4u4CTRgzxEhCJWkdLfuh5CgSI8VISDNwrRGys5FzISbGkoFB/jpI0pNpSrLshAb/z27mX3gu5ut+SbuPwnei6wwJyQZFUf62REJ0ukWYL/sXeHThOi3mfH/hc2MOfPhENzvwC6fDTi9yUcwghV5zKpt/PYO1GE0XPa9zT7aBfu3s92edYZ5vFnhEgE8wuyINK6XrcWtyw9wLXDkYBIgxohxXKREBnKqudyuFfeMB8BuUjfBtxkf/y6pNVagUipRajreBDS/To6kZ7DSlyBA2a/+xfMSf5frPkPFTHisPkYakFruy8WEMd2dHHxWwr+KGWf2d/SpzHjs0Insk+Xb+a/3rLPyoAfZpKQgTt1Kws58y9tClcDnSRUJSFCNExBcw+B9KC2FnVENq9r2GxAnO8e5QyDLp6alaAUgTL8tF+EPWty9zeUhGkgcCV42TU0QtWqbqBsmJ8w6ZPLDABthS6XeELlXYpaxZldqadlC+4WhOSULZJfzN7eFyGnGnn5eBzxZPz/UPoY9nbjhi7qUU0ME7tB+c5Px8abQEo9hTBLp6+nW3WUjpN4GhnuHx98oy7/qrmdRlrPEdCYzSDnn+QM8UuWdmQfym5U0jzcNfAglMt2qr/7otnFGS0GbYrGqOKMjY36/cOgQgiEM/IF5z4CE4TTYdxJul2fuITaH+bc8Mx5mXbxcv0aTB7OYH7JjEUOsMSDsXa0tmuNdHRCGqtmDrHGb/OGsvgJQe5kiqzw9Um+KeeLB6MRtCDBWpSumUu5dcqRWpdNwPQYx7iGsc2QqQEGzHTTJfvkgJSiAlAuiOzfRmv0FB5IjqyxvZe4/uC7Ox6MRRFM1zkVgVp6asXmCBZQ2sFtZlmNbMfwNGtWoCclUIKNKvSwYC5kXD0HUsR/sDEl5kTVwms9ET+bqo1yLwgVZhVG+vQ4mUx/MnAFsX8XMTyLlhxbcJerZoQLzQnqD49F6pt2XnTLVCavKQLtEzQ3g57Q8FwgrEIKpiiElI7C7iJmK3utN+ZORErAyL+Rn61AIzTIg8wPpDGxud73guezSWEoY3HTtIbLy+9lfnV6eVlAem2KHr138LNtqqeLveY9/vOvVQBofhi9O3aWjM4Z2A6WdPxLIZxHWFccD6vy9Z/KX+g/2fTWLjRpATBVMywGPx8Mg0UWxBuaJruk04Uw4tDVuk/+WC1E7xQz/qd2j+XB9QPBi2G3Cd/UrrAwvgixqIiSkrj9moxipDJ0CDuSVu7QenpFmEpvIm/DzTbiGZS9ZPmV1BLzJl67LllU9KcWEenbDxBPwGznABsIamuFg90EKvaMl9vWlbwmcjhaeJ0MKbvbvCBTraGK1yCYwWSNBqqdMFnN4Iw7Q21AWECZz0JyoegydubTq736Ic6VvZmuZ4JS2qgzt2CQLZGAkwfyQTVTx/BWnljRkbhI9qRCKJYK6SQf1YPDdxhCZ4Gu+t6FcuEC22LVYoxNMtZcLeabr9itRfyTKF90XhUgdLV/zKjXcqXWnr7pi6LrNSrEDX/zem6ljJypdnP6mmFDKRboOi+fokkajUjE9Sj4WhcK5XKAoJiRAVHG5Q+7dg2BWkNWCu4VzveX189NxWB0SToZvseGrCw+/WMKt3/wq1B+8fy+yqw5Y3IdJvCT0xfCpH7Nu8y3RxYMGDlJKCkum0x8hCmkhKnTlSJZTciq3J0Dm2u+oKgBzOG4KvyC0bzHcO+J0cQ5MhhxIKDFoaiVxJb7DBu+dDDPDY2ofz+XmrE6he/C95uITMt9RPYMjVCNK4rSmeDQzYw+y7boPFSH5XI9draJWxUfT+IWthJBHEzE8HqUkhjKUPOHc7KLTyxJYUoH6lQYsTmwgmqKW8FrwpTXfMgQkGzeNcOfKCu+MTsEjO9l2SoKVHsabhpPn2v38wGbPDDw6a/QPRMWmsQLvcTL0/YwXAH4S9MGFeIzHc77R9JOAXJRuYphTtWqoXL8bEsMZlkJStGsjjE6hJZIFKNp2nYaHUTMAKuIQ3XRIZ/a3Tq4qHLnJtXwkQq7/Ec+oByutSblr/Z3SRWdDQyazCdVFRZBuK3BU5W44oCElDtB82nfu699IgC8Lq1iToIi06cguQNjPB/0vnyKpfqQsU/QtZG+fbiB5UjhYV6VsEdNo0h3eE6ITysyygTzRgzr7zzYJsY0fCasfYhpQ9aiWw3CN2QgSg9AdDOTZpMSq+k4UZ6DEpvp/HUisJ3vwJIEbZJlDsuDFEnLTUOAnu415qGnw+MsIPV32sL9TYlcNrBQEv08NfeBQkzztkWL3S1il7wVcXt3VrY6TOEyzdkhfTDDgPo3cXHxCAI28pHQwx5hnMKQ4M0XRYZxC0ONWMjQp/Zlo06KD89HX6CQHoKxP6eueOuhlfKQAvtBaKNGSANpBlp4Hip+++03y5Ozp9mjM7Y2uNpxa+7zPwBvrBRkCqpwnKWARfZadG1lxbw1uVFDI3UIpFTZdWyvAppn0jS0osgDFD06Mey8+aM14SFnHff6g5WbvYi4msWXe0YZXK2qJfrqflFqV4vKBeCZiY4f+6/M2pP7kON6y6iq25rn40BbiWT27wVT2A/LE+sm7ifQLtQ6rkKwAQQ/hXWx/7/BnIY2p/+tAhIwPNBBeOfCy8vs66uYeOJmF5HfyX6oZWykzmAymT/1Zkg9QXZlqjgoXl/OW5C6nsipXg9aKW1yDWh6X6gnhZiO1bI6P2rFs6W7E8/TMK0ffxZ+OTJ6HhC6Hf2HUswtMrFRZvIQSevq3yjDO+QL55t70y1KI5kCwaInv9d0Ux3/vBMzAXnw8g+sOZH8hQiQ0z3afHjaPz5KTfyaiWOuJ7ETvqJjacgwB7HgzZLLCK/JeHihR+VV6UdLPHxub4nMB+KeoSY9kIrJ3ppnIxrAT2WZyyC7rlh2egBBj1TCWTZOZKLfgzFM0AJRAv0+jGWglcMtmLYdKtOiLrGrlY+hqwPHoRaelwHcSLVXHz3QGG8XW4znxkyMO4lYGOmZjqDGJh6Q/VIfFXpf355mEuNMo+9j5cT85T8/9M8e927Qhyz1nj5/AQBPdNcHywrD+tBHWSuMVijHsHNgKxzJJplY8irV4U9ny6srUGjN1Rrig/Sptc4adtvcff0h+YmNNSOhwdJOjF/zZd//9qH06efWZlt/xa4T/geh/cogl0wkKUHsL3/Su4NR6UDrXn73vRffk0Hr5X4Havij0pljnyL8YPv6uJPP9KMXo/AVHxllgdjWu6qdP51T0l12LO6DvR8lbi/Np1fYWP27umXXuiehyfjE+HvQup+AWPRQ6XAXNoX7Cn9J7stz7ObA7kMQzK0ZZVNs04H8+rnX0Mp2jlGmd9rWUtshU2OYLnm94Mid5wnAVj3iephlkei4FnqpIZyzAdPCkemLYR91jfKVidC26r14nG6tq8TKPze+7dEIeuh1RkFyIvPSf7S/pbprery86w6oyNSllrds9jWF4+uZ9T7WH0QO1jZWW4v47Qzm6KzpK2V/a4D7xHTpmd8VSutVbfRC8GpdCa5YHaJ0BRyQ7UUWfZ6HDbM96COJMrefkSgexI6rzSV1ITnTwhjWUngChWsRQroRqzTOMd9ONB8vrds+r0/p0lj49zp+0li/WPD3vPGIq4VVLZNRuakD7FoQaiyM9mG9WcD97T+VsK7TBqhdSj4w1zmA8DcOv6Rn68PmB+8D/bcNE+5ufBUDs+Uj3D6/QBiBiW975l7JLH4818abkGsWTz8fJfw9oTlxFZijRP9Xgh4Xj8xpmhgARysSN3c7ehP+ppnDaY89oC7d/ld2uIeweYVXIdAxcsDfffrH5TPi2DJUIJRBlt5q3kdSwHeiTjoe69UMJ/DxwY6Eu+A05uvc9TvnLtIX/zN94g4mgBly5eOepwcUD3VaSLMIUhjCLaLeNgGlO4AtEYhJ6PrwtcFlyzTJjz0fFyVAKbKEmXHUc/H2okthjSeJJ3AVAFIEc2vyS2RjZHm5Lw7grzdLqJzKleuyyGVFMplSlwn+dPvcW4+A/NxJkBOrgmfZeMbG2dP6hMAhxspVcqsZSMvICiosOy57jBpMZsx+2F0UEobhn6uGnSKms5RehDOWOS4DCFVL3ZbzF80nlzHx65vmngL7ld6E+IglDjxlmadHHyLl0tSMaJ4X+Z4Z4TzATOrSWBKJxZGbL8mhzS2ZkMNbqCWh89PPVk9IRPx9438ZhQsTyZEbs1MtGN0OaoJ9YSZeAFNYFG7VAJcR5EzlJ54XtNiqZs7eNytcCut75uTs5cYW3tIv51B9eXKM66KE/EkZbze1OE2ZpZNsPLeq2xquQzs7AlwjEVjYWQXlf27YfIMXNxzYJnhZDB0TCeVCvHp879ptK8Zob1rlBb1aInCC07l1yHoqkShJGU1+lRlyD7WWyYsEekOPSynbfL+LkAl3+er9ZPMCAj9Se/yHdGFbHtykI41WESMUxhBu7RrsDmQoPZBfjtjZr2bs9FI/VDlc2uPIHPjcpTCNLPaJVQ9tPcQc1W74bli0J1THeTl3j5LJ01LL3lyHCYUPkc3QmdL7M7OvS7NAWNVjB0U58fW8MohzHBhI4cgY39GryiozfRL8+HZYKkI/1WsjtoCw27VHxnH8Xs5DtGplxJSODfOHJgNRZBO8wLbvf++vCbAttBHs5sJ8yCBeOjbm1oWX0Ji7dSxwPH6L11brqcw6D23pgSfwJog5ZH3rkOIYgXJTIex9NfNBvSYcgnfIPShBIRL+bC35qwOT2c+h01b8+Ncq8WfUh9qwHFhrWHo7eBbTbk/c25jyRD74YxwHg+Z6lO9a9Pk9oJTi2b86q1odWrDi0ONAm9AfoIH42wjNC2XcI5Hr5cqzrJzAte3teAsopzuu/HN6os8OeJ3oyK0KajulwFsSIpdIL1r6/Wvl4Nk+Sx0t4dkgoyP3aw3XHIB8BkTbhNiMXX3a2HT6o5NLtQ5LfbALCt1ETajp/cIgycPdZUB1UYcu7ndspZfvJB5r/PnG8zHIqC+DYnZ60HYR4iq/WICw4UnsZkB40AhFrrGX5C0ZC8PEHqOiSY1w5R0f1o5orVRu2tcctmTnGu/FjqTObnJ3C5HMMU9QXwgyFvDppOiTT9gfEXZlq85iwUEvnLkK6NxiKb3RaMkPMzaJZ8yeYfvFmh1tAsZo+KHh5/G+AH+zUUKIEkrz8A8o9P0CoqF6HEn5tF53AwIQmtqgBGXJ+9ti1ofhq7zB3Hm8GXMPzMI9tu242xlQWvPgqshRWL0h1PSnEsWGZyP8W5aV76iDhPVC/zI07l+Ol3un8aZwIVaxNnXXX49GSogNr0dVhkzjb9Lsiz43HtLlhoh+o2LOKxuBqxnLJbkA//sytBO1Tqg4X5+QnBO62H5FYMl85zFosnFpczvXPpELuDNkpvIXl2MPl54Kbvda+ITyM0i+aCoRCsZFxXw+L+exS3rF3on4XSM+hvbNIEeuHiObc41kU5Mnepli1ttcxviVnwyTEe1Ks+hr3NMabWLr+gaoTRq64i7S5hFr1Bxf4Vd9hduhb2GbiHcKsnZtbdJ0g3DrQlg10hBErMyaKxihpejyi383xSIp7Kp7PNS6LTUiQGrzcFny32sTN9SRAtEVTAUtb1Q+hJl3h5vc88eql2VQpmLaZ60Yob0ZVAfqq+MG0r2k5lPldwFkKr0n2zYjz3QH/+9Q7SLIbKLRWKIikarhEG28QnxfIN2g/W2N8cuWOyppuYVsisnjYz4i2gr6B5CBJ50vzKBny9nqaLJeQNQ9K4deJgu3IlOQBvsXGIwX/SgG/uwTo6NGaK8/QprCxt9Kjlt0Wbk9S8yOV7VLtsueP1pgMofyohY81hBQCQ7awUkpw7vyd/sxcU+pyJg1OXg/iT6snKSo1h92LDa/uOCilRBWH/SiIe7F+nzaEvwv0VluQKkaqnDk2t6hNYuNskjS5fkHqXQtm7wC7h14wjIv0VJpUem/bR7TfblNWX2PoF8P7STkLwgHKOgC813cUm9nPs2YlAIN32Xw6gtydGfI2rj0SvXvk9sOxAjOLG+B/X/Nw4XvFXd9QYtrMEE8ecWip5feiil3Aa9CsRYn5j09+E7Ac9H5rlVtd6B7W/Q+czyUXjQXCyMsamW3w+80iPjithKb4TPBgEHGRrfCYictrVyIL147qGvV2OOT1IbIrkkb08RPxX46yd2+OOlb1ZZP1X0hJ08ZY/Vau4/gbvMFzNqBPAtaDmNmJkUtEi+N1gQH4wxBkNLSCYn2UIOo/Vx7g4ARedvEXGlLtgFUuJRWF3E80ZOjs/Jd8W70QFJUPznB/vitLcbMWjX3hJkg4Rqa/ekeZLGApWsN9cigwCNlrsthyLTnXOkUj6Qn2Lt4ZfEjMe8sw+AuQxmqFj/6bbaTiGJ7qVPcMR/uGAlnA2Zbgry2Eeq6ztozaWb+HlHa/OVUHoherI99/L2v5Lr1BANXwrRoqy2464gtz3gLyGzfOrEd+Vvlbc3aH12B82gQdPlUVfGa5fvTvf8O6ulXfmKd46gXvrbyXZcR/6nW927s4Qa7wbKd4J3q6smzL/Tww1v2a5vso+7nZ9LDQz9t/kVYZRV6RqCzdxLI6txa2W5qS7VxirVzq/88dxYvn8LU7gDKYVZxFXp+tExxx3HO+69Sg3a/u5VZv2d0N3ufpRL+oNF9vYINB/Kpi9u79NnQUhcRDR+E4svdsjTZesRRQOJAhvQstglcGTdblDsfpAq/KHt6Uwc1a9nWI6eO44H8hEDBOY1gNPHA+9I+U0J6isZTQTqjlgjNR27FwT0pkuOst3pt+iUNLiZP2zpNEa6dZuia1rIyU0wNi17LV7e0NlT23V5yyvVoKepApUsr+0hvuWdwCONraKonmCTCPrQhp853BCTc4UnA7ibM0lKieh+zn0D6MhCxsKrCdCYhy28JtUvTB1mBDLmf7bJsUWDxzVxrMDxeY4c3jYbMPx93+DqpQdDwE7uQrvcmUsZvfwSjXvHBf+n6jzQDIju9dQpqk4VxWJlCKRdxgt7zYo0GxHX1gPEUK9XLvEN1a0QtUNQb4txhP/jdsa63+hNNv54spsncDsDZy8hgv96vE3EiMP1F328QIyW3705lK6sO0f3Lhd+eVsseHZTW2gSFh7OYTbbhW5FwmnToVhZgW1132A8BOOvvFSKczhnDmK/5Kc1ts/niUirJnZNc0mylnuc2wI+atSIZ2v+ysMqO+VYhXAGPU5/vTZWtJVtgqKsd3QBjzDZScGD5jhT56lC+sK/nzRkOf30a0lIXvhUlKK2QknzVzzsGjgK1DkhWHEopmwN7v8EuRo2/z9XV7jR6CkPJGx29fK+hD9nuLmJ5AEUptFKAwULP1XBXz2IY1wYLghqZrJL4Tg4T9GRP5WnhYrWwjn8OgvHABg6wy5Kpf+boc30DsRuZFMNDnpxeMXvgqpfStew/ERS1n3TarzfFwmL+P1m9NfH86mz1yQaF6dVC9k80YWN7aUKMtmbHAxn322Zf2Q1ESDDd6Ypahh8X7JEyj0mqau1o+eaj1POngiJfT6JM7JlGA7GFBiLlS9GF4ENXI5Ixi6KOornD25qCvHUxSoHHSjiXbUdG/yV6PotrnKYv5DNU8Z1jCdREVBbt/Y3E/GUsceFw9FQea0XyNflt8bRywPOsTvAPFTkW1smgbpkHe6QJnPAyIp04JHVi3tyMlacqgZTuNrDq1xeT37mf/yjcIsd3GDYlT2VGg8SfIkT55VdFd8AUVRNJe2SOmXlRoGT7rvISWOdrozkUK+MVt35UQ2+NHCV56JzccaxYP3MFpPfyPcPXf5sQ+Vqg1f/kVmPeYSvb432Ut0bNgVM6cTFWZItAed2IrkDeu0PoThTo3kVWEOOs6c7LjFdjFD+YhRv7LGB6SUWziDWLcnes9ZpOEjCQY/pgSLFobVCE5wW4YVJrHB8Xkn9PxnumqX/dwKR8GJDXE2KuHjKoSXpPPbggb5J9UkCrurU6KJc45oROo7qb7djrc3hN+0FKbxtiqYS3efGuep7ed0NErtLJu1KEG037idyjFu3aju59OxZq3QOjtHF0B0zQNpLM3b5bjjpzPUjFuWdoEQ246H/afpMGN71nnTr8xo5u47xs1Sny+Hc5FBPqmDTea3syfmpwJQFIfeVs5bvNGgVXATEHiHiMVKX9Fn5FeNSjdh1u41DB1wV3tVHgLVcUesfbauS1J7n2B2cSdJwXs3ioGQvt+zznrWoioJ1u1aXStcsilW4MaxMrtc9I8LVUUDTr/s6NJ0IAe5/qibY1MKAcd90z4yfJ3nGtCxaw7/U+5nY1kvfQAunfkaJPLJatRFfTELmnCTjlXTHmuS4xySpYaydozyKK0+mUjh9WXap+1awB44YiwdoxxUhdpsvbNUc2QLMLGVDYagsOb2s04se64AmfnGE8GBlEg0MVtJs3147dxU+XH5Wvgp8H/R/hYpsXPvT8213z2x+V3LaaQ3URzzlDOX9gw/eHRZO/utj7fDrNOig4lkz8VHCL3nKr0v99c+1rG3pTiu4Hv/hbW9sucr1yZGlDfjp9IHW4N4WgstyJLo+PHUzSbfsy2MS8ao6d83NkwQmtFrRBzVqB1LN0w5bS3/iK2FaX8WpdeZMtSj/Lu7jwBgtdxoebo1rXwQaMJTTbCghTBw4qXHgPChXLFabHWv9U7PUg/SsaOPYuyqH4Viv5FzEx9sU69e5n2e6aDQfR34PkT5o2kamuncr9+CRKUTdxO7Ew+PB/p97tLSdWm3wMiAv+4vR+XoX9ugUrIBj+yH8o9Hqu5tQXFB0aYzWXnbdayO6LolNEnN508h3Ly9qmXfe8SJ82RREoGhnEVWyeLmzh0zOsMSlRW6eZmUnyUwKqaKU9JpHKSTE2aUfWk8gE+kele7/S2X5bKrH2RhXX0iPoZ3H0rw7si60007+tzzsSw8uYv7mfw7cKYNvp3T4Estg8wEjc4bxFpGPG3Szh+tosqjfgouyqxwzrJv+Apvpo8JfLiNsTIiC9y5yLXG4wTkmkGXtWqPbPO+Y/W+6/LeyShDa7IcXY3mqnPNyCy9JOfTecLYp/MHTiOaB2Q20qz21epLdQaEz/e0VYzhzy4A6LQEiTuQsz/S8Svffds1SixQVCF5GohDfYb8dLHu727JXsJvGib78IZu8o6yYKneCsrf1pcPqWBlF6HPxc+qMiVFtY4mIMyH3FiUXtYyw3ixnPpSweEreh/PWnzDxZux4fiNazn3250PFMMrCVKvMWRGWgreceaxOOL2RdEYKk15B8ncChUuU5uix9KHm1cgtCi9J+Zq/JdT3xhSteGKKXO2ECsmrjbBU1s82UOjqmm05v+Cno39VjN9yfleaip9XWNnHi/vYsYyWujYE+r2ui3YCEnVLoLVv8Zb6WcboqH1bn4GC5bQzr7U7kR0CrE5LNLfE8zyb77m59MvJbdMZ08+liDmPmY/Lt2Uh5Jf1/N9ZO3w4q63XDol9pt5ziuVfAsi+rNxkAsSXZ9orBbRHLFSZhhX1AYEouWg+LMyTjTpKkK0/yYYrCWnhFRFaIcjFYqMxghDKWDWJcTC9UpUKQ2rV9K7Q8wwQGXz2icEUxSSZTS0R5dCoqe0k/n2buAEhSjUREvQII9IV6rKc1H2X33N+saxdKgpwbX1NBfil8Ie23nVHPMfK1ksswRrGjTP4YiJYL3C2e6B8uj+Bnrb5bqEhBt1oXTH9nWEnsVJMKR6+DrYoRBfbS1RlK01LdsvIF02kuUD5TceyXuySo2k+Mu57Ylsi4tssA6kN/ml07aVBc9RTJP8qNFrIwsRFstLjSwAmIL/AjoDwFOupmuDm/m3eDm3OvqrpMbhYbdbCwfPNHd3muwhp5dZm9GbsS36GUX6lTZPsZ3QLHxpoiU3+6cQLE7lRzrS+MokcJfaLtoYodeeN25SOuy8NpX33l4UDkNGN/gmHwYFjo9CecDELIgwcsOqebCRrR2JDhj2VtU3UCkobQNoHvHGmAQXM10lQVBkYf0Cw2wB/w2qBRkOtQ2rQdjIIYqfeUU4N0zyOY8uMlLt5Il8hodoUKboTaUVAjLq/8gR+r9Wg3lOV48ku0pLHaLBb8aZNgjivwpQjVHazwaOOVPv6E3jIRhA9M7xGSoAXnZucC2liB8weEKLD/qrlEuPfFWS0Dig8nm8S5NeiqRg+yzi7N4Kp5KtjpmpOnBdvWThhrHSBvZbpHLg6zaQElJpjEXRiNCol5uZkXQEVOVGCRGZwOTdQGoazAhp4AEpNzsFsEl1TUPMka5PQUboMOFx5TaUU/BP9Ux/4+wAnaz8Fp4Rta/EO4u3cBqD5IHWRF83WVTuGxOhtNZVS07w9YT9FLZ+H1q+zZxHSqeeNirCj0nBV7mWtIEO8VeTrCIt1BAYtssJuQr3qvfnb7qGI7sOtya4l5R7FCnuzrbO9Cmxvyq4vM6AuuOK9DmH69mXiv9IYCMlIIJU9gaMf5vVw4yqFfePDtFWUVgDE0sSjV9J9OBovjp+OfJO4GPcPe6ma4DEZbrEcEobO8k+f7lyoGT4ttRabqYPzfDzd38ytfUBqcMREJe6SIn0gNg7i+ZqifO9zrkJTow0yYGuqxC2NthxUBIT0ck+MhLYjSrIVQ2+TINb9h2lc3zZSNnPs88khLQOdiyvPKKRzv4nn0nytT/quw7A2HfMHwGz+STxb9B1Pmx5Rid4zNlIxTsVkHDBnE4OLkduDD6UQ3AgA3Z3XPYMKhdZ4oOUaXwx7NVCkm9zX64Wv3pE7utLF2zBbMKeJGUESNPKMowbpR1ZURHNnuhy2DSscRz24t/CrZ43N7t0X1ZKW8blCz52DVhXej5jzpV3f4QFdbbHlTysOII48Xay/HhwK7W154H71ly9jbnIos+ApvQ1g92ArU1UlyFWugg54E6SIt1oql1QlKJzaLLx7yivaK9y6TnCBc7tHYWWIPAiT+sJzKrHSen3gcAGbK2Yj0FvUQIN4FdQlhJym6yK/HWR+HLL7m6I6MHM90xXowBZUpQ32/eryU8z6vD21syYQp0DZ8BnWZMd2zxzJIjHmyNcZELjjFb2QI4IxoAolF+SaF4T6llG6rKmRMkmIQjSo5FUhBu/FYbzEcRVihS3hGKQpaVxr7/dGYOVE2aIL7UMjKKdRYWw9UkSyJPudwnf/XRs8TGlOdQEZoxevmPfgM1mxs3opcZ0afNgDk5+K1eGNc+d/Pm1idyEbBdCuUZjXhUKnPcEf0mLXiLYOe45dq479nP8A7EAs0AQQU2yyCCPUTP9WKWut91NFXzP40/s2YmVeM9iKd+gd/wnSBNL5ogy3nNxPcrNyNA8a2AY0jjGTPMeqyAhLKCU/qFnpE2Dcr5EGGcVUM4Gxh07n85AO0QcYVn/aHZYqvPbuE2hLEErs5OQB1YIApqvSpwBGHiXBfAEF8fZLd1N2ICgZEpqX3t80uma9S+bf5UgTL7BAVRiM5yPtjvwf7GjrSpryRUI6o0yFoeaYCOS0YtpGAexIfLhL3A8XA8joT14VdLn1I6JQSwtKoy0M8vJek1kRT9IeThKssr3/T8l7agi3266BtwhMUt+qD1WbUvKobTYk9OrNPTAx7pVhrm+fLUHlSAm3bJaByUAEjWz2kokx5DxYyCcoQScugNMYkhYpMlBrZZWJJhXYVLPYqHVKhQ4WI1ifjLInAB8rUIWxbHUadayob2jxi7D1VPPLvSj8cl+103litqiu3UligNMLmJ1P2739Iqll3JSQQ4zpgmAMKGtEopTlndaIn++8TegoGiXMYVy8RQEuE6Nf7BhV9oH7AxJuIQYyL47gO96qkbvf94cY4wmJk6qrNQYV3kp4a/btQ2Y0i/CdHKd18ScuMkjo0BX3BdrsHskcn+YA7gOfiJahoaa+LmGz37kCkeQKYzSTKgxkgqUeNDWEHCVBMjfZEpuyoFrTP+zOHkGlacv9ewWUuoGo1OxquKsoaMAqi+goJyu6NSg8nLUCz+ZSePxY94TYukWAC5lVoHVZ8FFIlBZ76uRXn5od7L4SYp9x31B+VE7Der8yuQMrD7Ymxe5TfbhTo0rYcbMpUNC4ajX9TAchNzLr9QPvD4ilRyld/f/E0P+LTVffe1qVi5bytjk0thhyAivEKfbr46+ciSldeT76Lc9sBED/dx9BUBHAeUupClE4GQOsSFJJuZc9dfwr9+F5ostcdIH7BX9JBCXzF0reuVtnOrVNHxvrtmXj72uogVBcIXlRR8LlucSvcjiVaeRlAIKns9BLp99e2AOAjPsZNBCfdwYQzBzAeE9wkLmo2CfSa9r3+HBG8qff5irOQZQuXr/6AzHgliUbt2wv6VIJm3WbC2pdHiZ8J4k8xRj9sNsk5tH2oxrGwixXyG/r42wfGcSvrVh60l/AN79zphPYoihUcQxCLv7SRfYa9rx2/G70PSx2oMF0ty/Pxwe5w5njR94mgjghWfkPbWxKTSyykzwbP27gafy1/WPnhSNm+dyC+T5sCQTcLo3LjQnnirg7VocdMuEroaEbqwp75lx2z54zR/YaJSk2xr48R+to8Cy9tgvRX7Rzl8pDn/rfSaS2zv3Ao23MxqRC3h1lioZ8Tw08gWS7JIflxpDpqdMMY3g2rsnRBwfFsFZIosiUGHGjRb0OmbCxk+93aS906NKFuZcawJprdiZ7U2+W5ZN6haJ6n9aKkfnXfFFA+6xTSDR/sazyNXhh84tZJtf9y7LTmZZb9eeMOJ0HDlFZO4LFqqmWf+xPtN8XOAb7ZtB7j05Us1nJu4TXmEWKjvnoJv7AYNffysEQbIlHA8qAm2/YIXzt8XuzH9qyIBwX+/k80C4Md6iLP5bGas2n4F4Hnbqu6xcwpBeEk4U5txCd38DBJY0+9Nvqs2HHp43sBa4IfTKdt+e6cpZh/7A/+ytiQctghxpzvCDPX7VcLVwup7E8dsu9xv8zwtfl3CvmGYo9XlTVQiWpgY0iVCre1eOI0vbnvDudnEHag5KVt7JCRJER674rSZP0K77g2dyuPozC83f/MTBunCxT6mL/FBY2QEhu/t5WXO5gpVYxPBAzBGjJLImS9bxx9ygHQUnyTiGVKstAjm3D4YgUrGFYHYESiXAwHotbFjEHqgHuBXTLYn7Sa+KhJwhICJOopIJ195a3c2C/FwSEcdQLV4zPphWlqmmkHr5K6bqi+699zw/+X+nyO5fvOAyCno9A2C1MNw/R+5OBDyLZ3x1HnZd4YLBvKpa9Qtu34G/R9pORblFy6K/UP0JTiGemRGTyPX7gB8nfCHkEfnRE1kqUqgBL7dVgVrXJ6nPrszuVi/B5asNxbjpefZCTPE/lwIx+ydXDDA/Jad/Vpi7dDL91I1xaHXbwKJHY6EW0IU0xmQgBr16E8qROGp61XFtuGlU+iuo8Dfv/1tt1M5SPkeSJISzokHaB82twQLClV1OyZNVACffySXn9vK9/oHGzB5JNSvZL2Cx/Dp5Sl/iY3nnCpKTKngFnjBXrGuUe+p0A2xh2IZ7ET8iSRiJwFSRoZQXBr2P9Obq6AUDpDKORCRdH0eBC8+Fw9Zdk5l3WO+548/+RdboKuguW2BxgjekrmswJ5nAcdRBkeXFe03LTUSnOh7kH2hL3xgcqzwslCONxoaTSDFor4IyzjR/xvOB1TZq418iyEHWoBB+JQ8lwXI05O00I9HmchZ4EIBATY4ljDrKnlNHMPowtUvMOIZEM9OA6k4bmYobaL8fVp5Ce+GZ+OAEonEB9sb3gYWtgf+n5HsfA3d7MVp5mHrbtySSDl2Yf3fzPbu+qcfP+vxpTxHGu5yHHES/1CHxr24PCf7ws7Xl4qM2KleuWegabX/aRVbTvmeDc8krbbR/M0HsumvNCajBR5AkIIZPHNTpQyhGbsYwa5UJ+g4L9Wtd1G1p5T8/5YpVuCbmkH3QvathD/fhVRZqCbJ+PIe/am1a7S2VXicSEPMDS+uWvHPUGGMFRvF3/xB88vqx7z0vtPxnkL7dpnepSL6lPZvCmHLq3HQPxbn6/klMJ4YpLKzs7t5yUarMg8YU2ax3YF3XIcrCadx+44Q6/97sc8cDC/6pZhqWuZc5xTnaU3jm+290fY7v/nhyMi5QPFb9W9K0boIeHuD2Y4Up5fhXlsS2X8DgMtc+xYqeQkPjaODP5HCcnMyrvN3n6YB888pLpZP4x1dbbFb18LkMU0+19aN5zRbI39rE/siMCeLQ0XfmuaCkfyBmy72z2dmyTPuODNfHkOnQT319pQPBEvCmzp214CiYN2ETBr5YHg51VstgHW3AdzZkW6nlXSlracrca39LmTXl44s9/Lr1DLwntNq/P1okfjL47ct57Pbvwgu3wVPNPK+LQFdVNTCtLht9QH2LREbxR7GAXtNWL1mM3ODSqSji80DeEO6mINoU6D+ZQytZRoidHKiDIs5J+EsQ833f1PRoTw97baFmgPlGmWpFju7J/uSsPrwX3ndh0Wr/51y4nmhL60gbzT1mDcbu4UEs9y13gYuDpPXjD/vWQgGDpa8Pg/YMYDkyXy/IE72aV5spmb5qXktoG/TmKXNWHRMfbEew5rWwAa0MAIywD2bwfEt2I0mB+YAO//NbDYHHPjgn5Jdbr4OxVz3QNPbM5Apvy3m9pXwMJfJB8tOan3X7CZ9M4W036qD1zHlxBFZ9s/kGYIa5WiW1SGyZk/G9AHC41yhkLrkLKHj8SpBHOYsqaWf6hV/jsSm++lvWY6eUbQUGhoPGl+UbGi1qvzqb+qFLXmu/zOBv/pYkiIz2+c4jvmtVOOsH14DXH/r/n4pH5dmxOQG7oLr1jaboRVBSigH0nM1oNPnFxi9NYCVdCFR126yJm3o5C3NlZSFD99/OAs8nXViXX9ZsXfUPSwdhLIv+jm3KkdH8m9X1O2genbyFtOZ9G5EXIa0EXP1ygG1cmpKM9ajBpT2NngrfNwqes+LZyfeLATV9LX1Ii63JwNINljyoGs6sRQILpwY2qLOdtVcGKIScShtDpCxio/HF7X9IxBZVCcHw2zGGYeN6zUqjPUWb+2e+uX7IKUjUP9l+ZJaxnqMj9NkIrrUsMAaBLIoIqxgGusJfj6At1QumsS+qd8SG9d4Cq4oQrwKup0UGXVIlRFocgueR4UnYIUful3p5hq2h1pOpodbG4ADqOS7l4waQYzvfMkmeP27cDZ7TS1wIW76ByBVFe5t3dIVhwkxe2HDc6g886UC7bTLaCXem65GfWDTgGeo9hMsVvCZKXoT4ID8OTYWa0BdsfWMERp24w5ST4LVooEx/CC8LHBfWHH3Am3I/a/vAU+DmjDlmAOdVAF6q4a5GN48MU7REQNjwveJ97gmFvh42NV9E198OP1lf0TKvailRUKS2HCuu07/V2R9UeP5C4ZKU3LUmcX8kQ4NgLAdyuiuBQAQhj0DHoaXTa8hhPIa2ujTLvZhv39yYPkBPnSpJ6rpzQuKIYC5wuJY1dcya+Udg1PAGWjsBgwl6stcastCKrJo+8lPvxQcBpcR1/wDvswryOrW/1TmLXjIjo3Cy0mm7niqes3jrIDl+6DpKAW5dpzTSRS1F+0uwJItDr//Qc7V2wHLj4VWvAM96JwlyKg5vYV1XN9t6K2w2+Z8KFr7vkF390WORfu/kz6Zg4w6PqqEuX2PCwcedRWbvaLsApc6xpTZYfVrc6X896KMR8wv12Do5tIwXYiC9Qw8I9urj3MsaTICJpIKKF6BiAgQnoztHBe8Er36OC9JdshAgRuRPPhBOVYtCQOZDlhDWegRwiuwUvCrUUPerRpoIj/Qwfh20XuOv7yCpEpT2fhmd+8fXjsQ9/nZ/pOtlZrUvlLkBj7b+1PBhR11Rch1nUELAryosUMl1xQGssIG9CAnMn5Vrll1BtPd3CJcH04CaXbdZkg9NdRKMu8MOTSJkL17V3U7CZK5fywCQ+57TflbNd5rW8lLp0ZtqSdq3/ixnC1tgaRgww0iilIYDd7g8E5naONG2n+0g/KWCYnI/V2M79edEamZJk46X02u1bxhpalq6qM1nu1GpaPsTw/V4c8QZAznuMoYuS+yL/uX0lanApTYt6VFmRqpLPZcjB3o13U4dj7sRuPvZl+ieGLNWmUytyF6xyN2KdvpunkmqcQ7JyIudfS1flEW2bOlyixxEFnS7DmXlvSPWXz0Tvf9R1v3qu9m+efP+3bo3ITPdYHw3eS/upkV7NP5sqe7AbxTjsvP5OqjJ9MP2gtc11rIsJ4QzqiJzzTYQFd6o1yahsXEqtTcE9BrnmZvG3nrKvGFXkt7OL+innbpAqoTaOhhVyicnR/h98PThbwqzJpwZn7Hal7GWwY5q4rNkzopcvvW2tSOO/DqbTvaiWhyb4TciTa1Q9JAcFiDGT1ncDFa6U4iPVUshUxEAzK/jiM33c8zhE8LwsNB6WeFCgcn9iNH2LPtbtOgr6ZzfzBL8WKQNZgofc8UxVbMxOtDQZVgr6GQ12rYjPlwWVMT8QTnjTVPpzjS48f6dol9SKA4yIqIRiHCHap8c6+qYiZoAoSkwAFPZU8/Dbo+hV5FGqBLfr9QYopuTWbIsY6ZpEvtcYunvzJvngKOsuw32Y30YSTZfFDBTc0ENOoUMfuW/2evOjkZEgDeRDFVLK7TW0jz6rdceRFEGnoItuD/P03KkSd817oujNRm3Fk2Xv9O2fN6VK6r+N7YlqI4qdbaEaF0LWsC3WPLoPB/3P1rXOqXGtl5V7bOcvqUMkqz1XKeC2ePZDSz2ry48Vp+nOTGruL5IIodq4VDnpKxHEKEUI4pzom+fW1zkvZVkrlaA/FKEk3hkWdhJ6znUi2Wa63DVDmL6duvAp/NWFI0dz0UeZI8eZDGP0DZvInl6dXbuuMKJZMoReg3iARohpb1eiu5/TTofp1CUYS4z/mAcheAbZxJ++AFjOAr9V1jkhDihEAebkTT3tWLBDbMeO/MBVfcQOLmpoPA89VH/0H+KLtOOF5sZzG0aD3JDHV/2sppP4OQPJsovmOWm2iDa7yp8VlOr6rMfyrmRU51CNUYw4cXiuIWHZr6FtbVHzOfagsxnHK5fVbLY/HzkFKjw9AtTWQ3+XXmM9Pf7MqwzkC2Y+/CamopH6LkD2gzIHicq8X3gKN4V5t4nrP/E7Vwt5LVTLxIO3qhbEcmncoz/nBZBTo0TS6P64QiPvuJGi3DQnJaYRef2SneQ5j+iet1GE48C3nW43nGmHv+GpVzK8NL4eeU7ENsXePLWiix6RgWudfsIQmT7QizEmWID9xI08jxIeGcLC05W5gD1ZGngAGZFp7EP7hsFGgGA0tP1QaLSCwyOgChLo0Lq147blTcGZXrsxPs/FihUlcVor6p3CBqfqQL43TXuRVDZTavzcBooEtINHVBckhrGmoVrI4W3Pj+DTCsFRsAPIYc14UJgNplDnHk9C+Jn0jBvMNSVykm54rNmST+EgXPVeGEG9UrJkpVfPcB/kKgjp2+kSNQdD0mS4NcSiwNqLFPHymMmQc5rP2c8VaC1Go4oFikqJvhW0Qe3/WPJjKlgzAIqTcs+J58mnqKLFGM2JGR1VX+Wo7jGSCL7xzVVq5bWV6FspaVk4z8CbtNRgH71UXCB87Oa+cz19+voZajjUnvzKZWtZ0b74F1zb5s2fuK1hAPvoDBmfSxjVSXD1Y/PA5vfN1x4uHWoQt/g/+/d6gati654UrcVF/rMkisO/6NrYsELtxYgKt3+gX/UcT5tgd0wyQk4dJF4py2jE0Vq8rzL7cYx1nnUaXv+uGhzCqTXSF5yZ3HUCUgHa8auqZKAHh+eOkyzt2EXQn8S41OyM55RwOVITGaS6UkAIdbN4Pz6vJa/SDGZLJjtKxzPE6YaErZqQcM+Sl7WnCqhnXZ2+wUImtu0+W8PPukZWOIdDRlFkns+6mrxxAJt91EzO7c4Spe5BMN2ib/Gx496KMmAbcVHe5bLu//V1n11QHLrT2xhz6xuHHUYU27GUCZ0O9GAZUU0u3VFY3hBVTdqRdzKwFdi+lwz63F0a1y9N4lbMGyWN+c6Cju3YsU5T0qkS7IXfV3dTyvYO5JRdh6Rf0TzVTfBke5P6YtHJ/FUOdBdTFzY/ap9sOPJvZ6NoG1AE9bXCsSr82fzdN75hXiUZP7C5QLHD5d8cTu3ydOESWf6T35c3babncRL3o0C7+Bg4am5ugxKPiTo2U8WnIKYmyes4Liem3RdXfpBjmcnuvtOTQrQa/TIqBzBlH6hvkDj13++/2tYkXyD50uHEqulRrj13CU4UK2Uaju9LBqg5+gGG/U+OLCDlbkCyr/vxPAMm0kG6oQGKHIWJF5qT2s0KY4+dRKPaBhTyBF6Uj7FlwIFuAN93+XiUTBwIoEBrB4o8W+HNP2ez4YE8UuvTDRSlykHr9lnfhoe5LPv/vHEMeasSDfI2vbcSWop5nH30V7gr8xNW19j6KibPT7QXbyibVRBp9TgrrstDioKuAc9ms3HPLxzAyjWq/svDFqmxb2bERXimgZGuMQ6rCEC+6VaTxpYfKd3K90Pg9zkSHndVPltTRVy8YYRWX7tzAgWzXW5jg5pr2uUrL4sTq9U0sYb+bKLk5TPg0h51MycJn4+DsTmZkIhPoqhd5NROZMRwLoqDmQz7Vj2L7kMqL40H1knWuuJODX4KcKXxuMq5NpD8fmEtY8ciWeynIvfPyTxdXCCgzDeXe9OeZwSkazZc3XIaHfccIztOLW0rAEpksmWFQn45WhU8iLSx8Tf6Va0MZx4ZWOIMq5mRUsj3l/iHBQ9aTGkIv/Ju1V6QMXOKGJcvU6sQ1n3fWLhiWPZA2oGkTZff9xk+CS3YVYPIaQLpKgR2ckHWBS6mwmxPDagpK8HboeEm90FOHPAALqEZomNYnqKx8jhfXAMnSHQa4fTv3dpyNI9vd/q1oVOza1zRE0rnDJztaLGvVFGkbvZrGd7MQBNLp9H55FJZyDTocYlzt5br8d6xBsJrZFcVc4Li36w7fIgGuHDqPpjmsxyjeOv7M2V8BPX8asv06FYZ56NFVjl9mghslrQCvPpR9uAeWAY/S4hAOefMYZiCV7I/JuE9fEeq1CI5gODON6TUNOjRGzRH6mKzyjVPZQhsR3U7xCIYtlQxkJKMUOQaMaYVnVVJbd2NPhTGFHaJmOsQ81UwM3WhdWxzyOIetdqJ961njq0qlszK/caD0TALoORVtHBBAhEPYTld9jTau5RGSAai/3v/h4y1Ehgf6VJbidBVPlWYfeyH3UMQ9sd4y/BlgGFTgAKZJjYhCJHE5KucSVrBEfWG6hUcgwry9tTNueh4SXXoKb79P0KAl8fPsy2oFo9ImcdNc+WCNhkgRL3iUTDbo/nX0wn5SH4ntkuPAoJqXJJdhgg3A2uLj0NEQLYXBzomEGMl3fCE5fVPC4PhZ13tgpyIfKXTkoxqV1YtGoSr/OzryUfBr9S9TSb+XbnMwWRMwJWbyc6eZNZWp0Jhvdz0Uqxf2jVgMwzD4yFQB9koteCicvL+A2XQfBIKKD/ncJjILuBBEQbcHeZQgwtPnUVZvMR3y2Pn1JKR0v2kkn29YP2VqGuMbUQ3AeW2So4aVSDFk0WKQ19eVdpUfj6lu7jpF/XYQ+XTJIv496iUG3zxmSf5oQUfxeKi/VshhsoxNPe/CnxEH7q2VKXmTFo2CfouF+4uV/YXAxnhB+BJLrzFO6w8CdCMBc6F+DusluGlod9DnFnPohwZoXB+J8y08j0i8epavhXVHVFxnY30kakprSGum3cTN3NRx/IFqdElf/0iiPeyYN+HGfDxlPRcWNh7HtVPEbeYRqegYxiQ5bJKixqg4H/BvzG84+S/P12xcSWsSksWvwpRSYcWZEimSFmlSh6dxqeHqt0VaILMKf4SHElQ9BDf61rekNKYvaHm9w1BCCy+2L3jbmBV11qsDGsqvj0hEgOwWkKDJeK+GWjhsl912Q9ZnrI7ENaKliJeY5zxP3xwT8zJw28Vja0Xobzqt/MkpQaHHkPVU8bDTewbdc0TaTzgoQAmiro99NUtkOXu/zcuHgOKWkKRJoldDrRx6mrv6xgH/57XdNU3QUoJX2DCbJlCBR3YEADzEyWQCLg44S6PcB/qt6mPHMkWYRAIQIIGM3wk9/FwmZo8jQWnjKLf2uf9pPgIxPUOudIm7HNhYMpvpVPQxJwxlQyiU0ZqCdx1n2Rlc89nHuoNvAGG0RKNPqXdKDU4Jz/PALdrjyUuJPbgG8etLpkXrRp+aRw1rnuJE1z0l5BXH4kI/iii+DG17ZpI4vul7rn/5VGkmLfB11+JfytUU/ovBsZDLAT9D/oa1bejcmFW3UrV89m3BwTega1JHJDJ5hjuL4xOT9hP9U4PObbxZq/ze3LfBtbj8vTf/WK0vQRB7JKOHQmr+wvi8Vt9ok0cuoHEjzuLWaCDzGyHmumEE95q8rD7O/YxD7ibY4MHyxULHbTUHHaooA+9lddqC+RQJsrluCU4Gmxqw533XBbx9V3iC63O7QlhclP1MUAq8FBn9vf7A+6Fv3l3QBPpDJeQf0lJ/rglS339lJQf/6MrLWi1qNocjoKZGwrF/949mOPZEAdNNMkxTwMww53BLnVg4+RADFytLv8nd9qwctp//6fTzti7O+eWGSm1P3EsRJrXFBymfvM1qG3maYVorTXxsOFVpX+/c5H028GMYsXkLcLgfYjWOJDI8kh4XiFruSPZzen6A3K8TpMBGaKs/jMtq7oYr15KZ2E0l1pdHxBId1PZqZ+OFhMRpj1vuoSOJN3rINnseRLRElnxKXiaqTm/MXOATmiF2mwmrB8Qu3BiKu3NE8gepYZ/ocvsnOh1L7hNAVsGvML++bkucZnFdsXBd0VTBOhC/hcfr45wWovi5crHkhdXrVaUjeu08DZ8uYeCXHvY8KAt9k+YmNm1JUu9emChaVzpVvA5coBGRi9oTkKER8AFxO7/QaXA5d/qVMcK9Uq0Ptrdi8ipSmZ4KvFzBMyNshswMQEOasKOndPOmoHBdO1wbXYvXAjfq4d+tP+SD8QFRiTLlU0RbTUYn0VKYQBBbGZT2PMkarAE3XNU7g9Kc9/6GThS6WzFWG6VhthjRD2jGmXpETitPQGawEh5kSyQpvyAmtQQEcQI92LSmgatovBW13LGuVuGl7f38gcF7uhNSAmYtYlFjWpEUjBlrmDOHOWcKPerLW3dMR5CJyf/OsQ6wo5gzTSyOYFBGHvs7IWNCDp3xiVmDOPclF0Im8+aWkxkQugA9IGr3+woWzScQI6LJbvB5d/q1MfK6ZNo8dgU5YHFyb8TONo26KhyZBMeVhLRmq3Fsotdh+b/s9xTP8aCIZBeMVSVIIpLAiZYp0CIVoJBgiSIUpTgBz/SGmq3WWxBOMbzLptnNWRGuS20K61JEzyVBjTJgvQUu/eUUadq6/k9C7kaEqVN9K2KGKvAhWJ7nMdXbdmssNkIuM6s6JtZh0hpSGnQF/r4NzfKdhWcB79MB++rwGKakU+SQdPUHVrxSrsRKx+MWfyAYkrGTywUPoTs4OVAgM78i6n6S4sF5cJxW3ChFXZ6ProVaVmmU+GGyOFDbdSafppLAnaTQ8qCQuI4aCQWZ0ZsWdGQ2Go93k/3nRV/kiX5bD2v+BFB5czZgUmC+Xs/F6tLhZWxknYGL16dg5tllnuOpi0nz6uR/SPk80uAlhdUhTQkgkvxTCkoKqlnHI2LwhIdm3qBeWtYYZvVIKc4PGPkEbBWBnoltn5+8OX3VsTJDuqwbucGBgvSiDK1+lGn1tcLWTu0fPOOHviMSLW3EnwYljWmNbDQXe8Hsvi8nflvEtxzyW5H7pMuBCJn8lG1QvyNLBAK1QmfqKkZk+IKBjxatLCO9oUGqdrR9r5JOQgt0uDsCN+EyVXV8OH1tkP94wVJ+u1kqDEoYmupr6o3yfN+fmWLP16d0hRhawt+4rEDQAXyfSbYJqdFGpiBD19IgF+LLhPsDqjJh7qD+aFi8CZZQN4NUCqkJOh/mnX6Bb0nPPNTevyGNoHu95K3XP57+duG3Swsiq3hTvNHuPQUy5v6KPNHs8HN9WopwAK8RR/DwmlUecsX4wJ/RQcLHj7YqjRIJCiqR4oKqU5riBAyqvj9vyJ3+n2X1tpGlL/TfV1PCDPb61P/J7/jmelhBE/GbUkLFRauH1CkFKOosfGFqp5m/LylNuTa7vtXUEqk1Vad+JD/vm4U80ECJO2JDlwlf9EmheIGQ0/iimIOcVET1laHCR3q0zAJEmg4Sy3IUWHYAe2tBgVX6g1bapmPbIGg+kFMehdndK0keKKucaiZgjFOPHje6ff/bvPItUqLmn/a1W3LEaVLfBj6DmJo/J863f7np4JuLPz6SOvtYyZmqP9eugOyswe9vzfLyf/bo8tJWxe1Py81Zrf26hT7Y936HzR5LftPlnS3hhk3uF3Y+pYVkknB+p+SlyUX+stlv9betAv4ISHPaH31cmCjUOxsTbwZeop88CN24/YlcHZfVaDTb0mMOMfhWyPTmm+PPnJYE4BGNJ9pMLIsBUyTYgpgK2yIRmw4NOthkxU1ON4p0Ig0LORf7QBznudlwAYY5wfvN2MHSbeqI7vQiz3AzrYZ0v1n87+2KUXkQgCxChDCE0Q3zSI2RNRPCBjxNUvH4ANOnyQGW1XPRh4v9zxqWAo2sAmEAQcdSs13m5rzgHrEAL3itaI1ClLbFoDfOA+8BHl7wpsjx68I+euKE9Dgf56Pe0XjMyZCMUy7hGbUCr8MIRi+Y4G9eVmLLzFyx7ppvCOQ2DfUuLxwpj8+6KNcl0GkbKE5TdmwaYKzhDMeqtV99AlJvOhIIBUdlu7W6m9SA7LXAF1iGRud0h0t7PLXwKsVBLhvCiUL+C7TZjK7hkZs2yBunfVdxtik1ZttoeZRHKyN8pM+nrDjc36DypGpVAJ53YpF0FBfQq7lpRq6PHG/VgqVXBYPrijnWNb5+5KiMR8qFf5ygfDOklBwSopFvTlj7CPtAFBqLotwOpq7HOFxfK/MEPONmSfL3YoYwNl1cRE6iFPmsRrlB9/0xCgw0m8gApIk1kTHsPDaGNM3V6c/1+EQETwG61f3A0yNzRnoHeZlm1ElH9qqPW+H9xxfUIic36HFAgrt92+MkGwopDvoodfklic5tKXZjVv9aoCCr8SfiYUqOSQzaCqzD5dVLy2TAr0uSL7sK0SfHQJsaQTZBslyJECYlTWYlky9VpQ2MAHERFrzhubm6TsQd9TgjZLZoWj7zY+aP2yjMWEknoUxFH+5T0kaR5pJ8X0Bp7QAeUeSAOOSHnkBpB4U+Xjd67p05bln+at1UglmIDaq5uJ9cYtn3RRc22GGKOwj/+GNOvNZxnpfNRVA2RhCTWWnIxJXWoOJRR+JEAv/8vNlQ/+9syp68lW/F9bSBc8q2O1jPTfeQY86LoF5B/UAmK7Uclpzq/n6LtvLP7lpENe2zy+WMvy3xCi81bDzOnGux6gHhYptkdTgjit68RT2Ij7PjJsKXJDgiKanTgSesoDfguDGogxhzftYIvY6mfubt/9H4gP17woUd7QeCi4FRKLI4Td3YXdywQ+zqqG8N0Xne5g30p6VfTvjXjC6OsffdkLtn8PyRvU++V/0/7zmdgFATBwclGZSREKYRlJUMoXXGvdfokmfbqtZrikyoRZKCy+BJXNUD2nfQN/2q4F0Twj16JzwMWlKdfI6axjtj8md1gZ2mqYSctM9Wa/LyJ3P84AK/bOXZ4PPBc+x3ikpylUChoeDDpn+pJozbm81KaIoWboK6KU/+ZSCbMgbmOUQ3R5RK0KOdDZUNvNpdKuETxt58beHbtiXySJ3XEtthj7F2MIqqSUTpV+4dDz1Fk4h+CxkgB7Wyxf/9UAAKYMcWRtyfFUZtxF/dV2PnQXd1+HzrtG+96hrhBLISZMtVUJCjERsd3ClKLy9Ny5jKcUTfQuBxT0u8VrwSzudseel/U28sh9KTz4aXdua5fTzueiGqK6LRZfr2X0/8y9V0D38B96Pvl04Bw13mY2RuOVovUqpuE6MT1OBUmS/5NeWK9aqqv6z8f1AI/P+xhT7oyE+2B5Y/AQt5VvN4lEdFowkJhM74Blatmj35H/gTrxQo5jqVf1Lrnq2dQ6TPdpeu1LxsGL+wnVNg+ccWMnEZUklVU0f0ckeLVSXwdB5GLJpc9WW7W6YWrKLd3QiUAKEIONvAqT+lyy1x4SJXHFSPwQG6HXFksmD8oYXFdy2uUBHWedwv4BiqHhS7bd67oOv9Awm2HwmLylUaQmmJYNrUxYoVJ+KM5wPywV4KkTp58b89TK/ZB5QqZ2LegniTrrGVCYzvu+SK/J4XGG5FvMxH3RpjTM+qcITXyKopQqxvb6MM9gIek7PZmpi1/io6m330i+v59ZfcDWH6/ydzs48gYUyKhxE5/wFV68yzYlEDsd8L+mWJ2+gGbPld76+VIZBXLeqknuvoisT9m1/XMriSKlNH9ISjxX+xExVuPDly05dggdA+bvKyvmv+R2pm87Hxz5X/ok150aeWQkHBvnxZfu70trc5xXSvEVz9bcFcPnNH/DPVs/7F7Zsa/GxG65vsYmDNCGcdJXk+X0tBWC7l+ZwIdeb4ZuKOuLG7oSGMAmbaNRZvu43vJcOOS8lZbsZxlDyuj1i9/fnZ/ZmFPb8METnIqtdt5GlJRPOfAb6iiPNPoPfwHcWNy1VMPzk+y74Zz+5vqGjvL/TwjXk3vgochF5MisozCqhV7hX40LuwQpAP46LpcESU281KpJfRotsyPl5fO2E7hf4dh+l4m7/HMqh0k2a+izm0Hyg8dEJAE6QhZOv9+T8zd8kdhwJVW/hwJi13p6v7vFGjk3xEzPYniadpVsey/xIrGJlAdsSyJGpdPXCc5gW1TE2ovBd2rqRrmDPdhcLlPAV/jU79lNm4n4YC29JmGRbuJuiKdJlAbFk0bP43pucoTVomvmNq4iMbkh4Hz/2TeeGx81ywKPDREIEVEbsInX0JZf3iF4dcLST6RCctj1Ymf9Kc/FlprdqzT/9q5ecDtzsmGSbPmSu+SGRZBRAaQuZFAd/p/ZHwcnFuf2xekt2HcCI6z4XhfqNKxdRxT+RwyeuctVBdbLgxb7UcWH7RQ+A+EfLkotOgHoV6FKhnvwtzv55HuN7vcX6/IeO1mdlh7AS7WuFwOXTGojC9CLfWH/EOq87tpEpwSWukOg6bL2OVpd2Ze9lMr1yFGXFyBrnbc5DYgIUZP0KjTkQ/bOSMzKantdvijiVvL9DfPkVwz0E3zw6no/DT3nSvLSvwWsuiz/9I/nTp+cS/MbU99qGGJCO4XbVYSHtMLBrU61GnAJEIcX00FDydEhBviJgklc5Y7YSsloStD+Z5pSZ8LnRCWF2SXW88Csnd3GkOqhPw/xF9Cj+LDd/ZqwlMWhoOt/BAC2/p0hiwQfQVMVC2c/h6W8aJxDfPrKXX266xmsDvnP9YYrDckneYE1bp6SEHygNb7RWxLIsy5a9xG/TXsa8QUmIldHzSfICzDmsokGx9ODep7bNIKhKbrAmrSYHZdRpikyWfZukbJGLTCq2SC9GQgWRDhnPFZpi3kk1Y+v8sITfnBF+7lPqXS302LdzmWxL9kvptM/7lni0H1gTpRgKu/es5r4s6Dz/mknN/VRVWTLt+V1NdIOV5taVvFSmLpWPlBlrQAuDPRcrj6XiKpAy0Qa6liVJSSmIqdVJngNDSDoZx9+n8nZFlIEXSFz1QLsDrYoXTvgw1hDQCiuhtBM3PGbl5PM9URy0e5ZhBu7h0a8M605KPQgHcjQVHwbawAvH7xegDx1RbYljJkdReCFKz45AW+v6nPZ22ZWCc8CrasAG7xmt5zLuiGPUWsdcmk9mu3gjRnSh9yzwi/sLuF3x8X+9KV0kYw93iSozE6lT0oQxtJKowk9MAjasCI3w5UvTvaGKHZiNL2xTWOATT+ulIaKq2KtBF0jKHlDB8W6mw2ymfw1JGdFI7KRjhXbhNPaKUaaMxgsWe/h/iPpTfkFzcYF+cs2PRPjyqxQqFbLTs/u1QyEZ4B6X9wviWJrMnc5aK6QeSl/81FZFkZ/84+inOxqaCq3g7Vhz/PezTpzBedv7s6T2k0/T33uj9+q3qz+6flmkCV8RhRUCYhh0oySRRH/oXrEMxJob821B35Jds4NXRVkzqIuTpro1UXXQnXRdjbiw5c0gOwVlW5rCOqCTW0bKTCeNSoDyDGS96S1jSUhhcKb2F368bddY/GxeMtmGa8ppNp33pTcduNFv0VgoKQhgsmKuZCGviqbm52ujxarBm+4AgRXIreFE6BVK6gTxPu0lQ70Q3H7uEOrWahXW13PkSRmS4/ZbqmZpHSllfX6+ji/RWWlTKHVxh7nt65VNMWquG5Mfn1Z6VxQAUrpvWyr44pLyQoggXWG57kRMJfJv+ed8EunerpY7WHLX2/EKtsAaX4X81AiHTHk55GUD12Lf3c2QnNWTyLnfXQ9WVJTt6cKUgyf7zH+vGvj0d2NB4EDy7qKFN6ils/rrMrGNZVacI/juPk63+DwBls6Yxa5PqDUg2SgymsLX/E9x84qvKjUNgT32OltSM+18xU/RWywvw3jpzIlQR3pbCzXEzoVy35Ek+iYJd1+tki2fg2R74FKtzbe4Nfn0b/maq4O0Fkm2vA5qwDYrn3bv/J76TMv89JnHSj7TMlj/UQeGnAmZNYtJXxvtQqC/Bb/7I+Is5aEf6ApSFt1nk9MIqpPbV1MjTE22I2kmDYedKQadH4516LUd1gmUEzIbjYoN4cnPnNfOMFyTJycGX3bAnxyxafeyGD2Pd0hqidY+grHO+CwSHHjyr9nW/fOcv2Ir8o4HNy6yb6n31DxkudIZ7mft6MngffeH8rD3/ACiFQGaPyxbqN5Tk5bzxB7Ve/uxTOW+yhKgH0XgNk3wgdVIIVUsT+wfprjhAkZKe2BwQModk6yOSHB5HVnsc4o48XoQiHGnC/ar+KrTUEybdebgAhrojum2BpsZzrfsRI8dsWNjmEoRMLY+0rUcuiFq0Gg8K5YySWNtYT+xhMnXY74LAyUDVQvA07w7HvpwulIY3nB/tfEHW1lJ9RfBidyMkdRPyOMemeTasi6wPB3EdXSRMd8b2SmY435V4r4d5X+NaYT+p58Qky+/Sz2d0VuqoqvqrbfKRAHJ7951d/EeUCOmJ0KAD80FE1yKfPgHFYhALg7dH3YUeBc4jW/sdIt9Pni0P77Vwn3ptOmKr6pMjM7fnbOBdU5+EHQUsUtg02Uci2hOiXRwtg5kd6f2IoSmzrUsyz3Up6TXCiugLmZDAhNiE96FwMfLod97SbzPi0aT2rHFEpZdRYUoMY0ojXo3sWiOxUo6rfaO6JzDMnLUZWUgs7raxKUY9/VwzkKl7ogYMwB7UoyKs2SwYh4qfusO1dEnC3LCuKqsBGGmDfeVWp0HufqAnUCm7YdW0OjXzq+u2E8zb2cQM1/sPv4e+Ruw5+MwY4RkvgmhipggaSLWmuNUh+jpwYtWAUxnCmxnUu+90m9pfrr7Li7zcIPFPMCCdL3ZapuVyyzJ5V5tkh7SK6jXObA+Umy8sX7zA7lAn6RHWJmh1u9YRE98L37fGyKx/3IJZrKzw9FMBCAghGJouhEl2WF4EZgtYJNXmRZ/sB58u+eBCpu+JIVKExGoV+n62ZEUzw2RzEckkaY/mfDGt/jXV3Ho/HFaoUa2QxGTHMZrwhmgB32VcJlYYl5cOmcgoafHqh2CHp+brB7opbggbUVDZ4Lu6DfXhNU4wtJhmgJsOLqtPZpnOEjjExbRK5LrE7NYDgCYZE0t+K9VPK3JHdcunPBtd0oi/e2D1Eux4zp33w8w2awKTRtMPTS1vlAJvP1cmh6IOufbszX2yQ+sHDq/lTwlXkk5EPOyA9BKkXb3ysG36uJ5tX8/nOd/Evq7a+Wjng6G0gZyP9/Fztgz7ZgAh0a0DJBfs48JIK/uPMhz2M5UT1bf28ZnMhjIrUOeG3MW8qTIFFRaFphqH3w++x7j3wZJfuG7flbwuseHSfHTJnB358pSQ69zjYdTqXcBAm+vzufVUkzRwJ7SLhOxYhrhPaqxVybNGtq9H5saFeXNEMz2McA7bZcMsTHLqZLW3V6f8Ohx8ek9KQE0G6BmXNC+WGNrYXcPfgcEfgPDD2/K+rJnQrBvuK6yvjLzjhDKL3BS7v5cD/RSydbGoIY27TBhF19nf2vBszOJDw9XY2VNADIj0JWLmti8GuUqbX6guBtU9GlofE3Byu3PHrzzTQS33Cd2e+kYpoZo3tupdRVf1uY/nugHwoYsF5pEbw+SH6JImWuTAulnkvMGfnVIpnAWrUnBiQrWUmkLzSB5KsyLAjuvz8dkFg84/7kqq9PyXse8nOd6Pupjq8pL/EYcFY2TvcAyL3AG5LcjDGLlFZATsCCW0LWYiNV3yy+LiT24hFXh1OewyMOo6MQsEZ8JEmvvioETODbEXBrhPPXZNubjwo/zum83AurE3A5Bebj8zg/tM2ED3Lj8oF3X79TPhdzRnRT2MTKXeU1GPamN9/D9ZPLnZ55uFacOHhR3AUjuu9I1ei64MOhHQhSQ9pYYZczFkburmkXfxjHd17SR6oWejYJLCBRtttZ3pgWHz4i89CaMFSnDd6slHjJzD58/Ko2MOyJ9HET840abIaygM5wxlQlAI231EoB2yuzraycRnbMgvhK0lN9cWtWSrmSeFNevZ3CRjq1fWERQRpCNZIquJ5HIWbMCkcoUGHRdtsHBXC6OE8VyiIRW3jlR5RkcW5fScU9g+6mNb/QU5aGtlFbuRpcCLzZWwojtEHmPfxK8X/im3E0yrSKb2hvR6sYxhpuVJZOxfdVvfhukW1FV4UBUSmJ9935EQfmsve86UU5AGi4wIQZ1KXnrMSPKXHHw7wRxYuMXZ9nRwxmtyGwjb2mdvb4JO8NVZM32NnFq2lqkzvg/JN7nXbNrt690oY9sLm+nHwghuSc3k6Ot2o+69Ch37of5ZJPczlG5wNq4IQssoE0CdAGDn7Bn53hrlnAXpQVXhecjw5LK5K6N09M9zgn7UgQlPTVybMbN8BCGKnszY52geOjZvT5SKC5/dTcrNsl8wvznft+r9EcMhkt+HtOaj4pYRtzQ3YFVACR+ltb086ZtrLBbLBZovNNu+Z0FWxlKQbKsQi/hfodt3Pb5OO39u3Pza3jcPL6x9c+2FLYB/NOlDLZGW1ko5SekiXeJhFE7ftgjYXiDHonmVmm1XPedHiVO4P9gSJ2QXyUjLPhtmwGqDL6i4R27P3rrwhSwKcCrIWVezwUmFAb059CDlFLKrPUfzuu1pelcwT/Bt1SeRFOX2dq8d8D40rbYCZj6cSoiPJS3iNToBpT4TFSLt04+dTWvI7VppSCxHXXuKTyb6IgOyMT7R4XoI4NPxhMNcEZFuYsa+XOhzj60/9anaKYmiAxWFX9bJcoxjKHxPxpBZnpRIcowSbCLtbF0owwvnbKtgNJzwVZvfsNkL+yyuziBbnURLAjNIzBPHtbe+Nkx92BZ4uWjSpNfiHzepb5Mm3fIqgW8/5jrBhVCKptAeYF1kZAxoUA/K0jiE47Q4xEUM6Yz/8f68sIvlBZ82eN5AMhwq4UoP0MFiZ7WA3bx8qrB3qhh6l/Wk4d3HkU7opNKgUiYNNbjwKd3xmJwYmZoEK0ExSEFUFwziqIhiTawTc3FsZ1IWQAiqGBAbW7/uyofEkh9tt75x5cQvSnc/MpqeDsGtXJu1LdmNaQZt0UsMDELffmnR+4nU94sBzDmGvpg98DvrjhUuoSpVmGZzqCp9FJOHj5y445NG56a53sdrE/F9lAFZGsmTLUhOkBtJIL/hVIF1svXq9oN+3p9y4ZUdYPYGcpQfXPuVWP+45V+/eGc/rCsa+2Yht/ucHhrBNdDiPFltHfu9MdC4NVNarCVfTSodZVm6M/FaS2mibXPpxwlVptn1z9er/DqqncbtO8MnRIrrL6XDMaX+MH1LLQX8Wy+rduObq68ycnAibjO8N4PcKbjc/X322rHaz77p5H1OP/Syj2TAKdvamo3zO1PlZp/j4GDOgdqXs5TxiU1zNTYFv3nvz1fQWqUO21yRQqhYH4hom6pRKGxRQLNTMRBLs2fyaftDyt/XXbDcqqWpPidbmf2z1+nzNNhMKzlh+pAnXPWImhHfdWS/UKTMhDSUVitp2EBvMvb3ix9ktI8YX+McG09GVMw/Uc7qal9XpNR7x3Wk3sI8TLKqUnsSDn3VaFDFqMvMpG9cnXZ33WdrRCJjre+h+b83mGYEjtg11eUIftO4qU8KdAEnZzAW4Bj3gc9Hco+/XkInrMaWhAcv1S5IrvOeghfnEF9XJ914xESo5B0wEuTJVkIQCY4S1Xhn1/yPWxSzrI9oxcfTbh7mUq+QxJMZIHk+owKtPhA8B5xdtlxniYokQogIBBOR3GUD5S0aGN0ra0LMTgxWaIKUORYkzVHkoLwk0VhqmpMVwI5SN0hyMIezuSwXhnCRypBXKzCEweEkRKCQ1zwHqDklmJkTN9NzLD4pHOC4ZOP9w8ndmOFIwBk3yJlSCT3KGd1bR6kKGNUEE3b6i7m8H1OmgUJ8rWzsUTJ34SF12VqBcaeBaA94mXEyzAWd1gDL3yf5nVX8+Ouu8rgHMHlzzniNp3dMEpR398O41/nle2qjfV/u/y57nOzDOhGmAzf3HXGIcVFgtBFCvz4waO9zo+7s5tZGGajhlzTnVDorsqQut8AUkhIpmg1wYv2JYQYWkahITM7zskTBEesa7SXZbwdiybsLQedx1fW5BMcGXJhJRS9iHuMHXAouzrMDHM9serzgZ7ipijOr1q1P+UAvXbJevp66GybfrlbC5GYlijkK6Y0VhEoZHBDxXW2rUSzFB8CNeuC/fBa7DCIzh8QRPRuiIOyUDI4QqcQhPYoSLwnuOfrQ9Kv5qPdJKorYIVEjAsmPP7y1BQi5D/Gle06bBF802fppcRJ3jOqjuGPyUj6i41fIz7cMCkHv/3l/W100OagDJqmoYr/9U83YqWs3Zu47XkwX9T4o2e/5IyLiETQNr+xzpGNjkIGRTEt7MFkxrwlNioRHkEwx3qKUK6295y7QNOxiA4jbk0BEPd3asQEmM/wFnD9qw3grm/svaRY+Fr18PBT1O0DiWxfxn2GlJimypwsZ3NVwHR+ZkB5ImES27aOd9Ea5KsRjWJSUcetLH+AFtim9IchWp3ajz1zzVtgpu4AnAv89GeyP4hH6+N+ZYcAFbH2Wh5DFUqngtcTKXxZef69f+e2X6I1Czjr+/a2LiWBcvyvhjmo/Vc9zRPqDw2idhLL7G2OfGxnrBAaU6ySNvZK59LIT+nw7cnP1q1bQtIHgK91VaKkRxt05EqDlhuq3OXStx9r2PdsrF67mZZlQle3qzv3I9sxFqwGAbp9/ytdGpo8xhe3h0tjctj/V0cUo/R99yukxgqVnQbZSqzZXqcBnyNIm4+rQzu7qcu++RNynI8H57SA3aJ6AsezQHYt3SvC1Qf6T9CgJax8nDhgwLy40hPhkXchE0VnzCsHrpXJL3K5OhryTWIGtT9GLPCeiZKmN//zqY0p207+vNDzRzovVjesXfwPg+8WoYd9t9jMQz29ia9Lfkd/G+F/mlODAXvHdjLKU5ubbuK8yxDnUoeg4d6j0EiujUWJMNTVH1yq2YJJIBWtWxg9l/3CCXS6JPb1ETuGFb5QJx+Iy3qm23QhY+Rkoa1/AbX9YRgskP7pGuRVTJVpcsyL+YsYzSL5YFiXDBil9XTgiB9dNTJ0R4MnYGt4ywqfkq/+PXsJHTNjzkXDLaa16IxMXuptkzSRCexmMQdiq5Icg9guHCF7RGQ3beFcqp2gJSzzw86gvnAw3vvnsa/cvgH00wOpGt5d5w12QyMI5H4cTr+eyts6QKcNW0VsFywDUAiSb36DVgkhABfO9cReZ38hVl6NYjPUAsi4pGuN9vqjTkTin00zSQxRfUHpJxDSsMxDw5wNS5z8mKmEAaiuk2HJArxVXi5W44sTHzmdU7eXSWCl2JEENreHWBnb9YF+0flV+HS04RMdEP9RIXmIXJiXwUd0zeX7dYs2y/QiCTqF2JomTTA/qURLSctQ19JX8RaDsRUsVP+AkFwpu8KILEY8wAAtZha/od6Q/wqXgeHSMchn4k1q1/5tqZSH+XPylSLYwy3cJo3QL/VzsK0pKqwsWDFHINoT1okFSASy7mwZwdnE2Euy6p2NDadzDZlL6Sa+KEZESdG40QFeINAMzorcGZR56Q5UzJYxhOY/5LMtmMSsnyvnnLUjrBwBqIySeX2AcNeIwWeMcoq2WKi9jYyDGm9BXMTWCkXixnSEGc3FeAZeDjM0O5B+OEcexdTg39CXensGD+frRWzqfIcKiKAfFcgNLeGQvQfW9u6e/keXde3TSphJtY6rrJurF5nooGjCxm7ptDo275KBjRRjMPVxvmIwEwsGXlkq53dug4Fpzp/a/ttJ/4Qz86DtweuXLKhte1WJcEP8Xp2VVqnZw2yLPBTAQsCnUXuXm1zwibuyXN2dG3RlVhmttYl22x+aij+pYnCMqou6BEUkFWv1vhTpgzKhKQQIRRGerSRqid5M4b57l0Gsoq7Qt7ZuxkZJrrnYYHQsRAgaKCiEwNDYEKLJikfOSNOwUdeNdF0cJ60f8spHDKe26QD2p/MmWFQU1woqegasdwmAQ6Ij90W6TxavWn6nX9l9MMnRfkRzw1TuJQ73hBPxf2sNz3w4iAdvD8sZAGoOs98eHr0hJzTJgjWBEpOIQbX1x7iun09Z0DKnmsz0LvxG7ZG4bGTEKmNU5wu8lYC7UR01LFm0iWAXODgP2QUUebqhLQskClp4w+ZcB2+pq2mNz73VTmPsDP69lQ3PYJwlsVI8hB9XFtz6MtR5oc2ZByCpGo+MnKjIU/JK09TXKf22ipQAaDfOiUlRkflntx4F4Hzgp3SY/PuLzmXqj+BVXfqtTrpqEuzcru4cYliRevfZZGwyjqu1s0ID1jhHer2w3rUHq/gS6AFn7LdieTOHjV/f7+0QwF7P04pje8KTudWtZJW57wm13jw4o1HZLNlg85IodCgxz4Ulny8bGw7N7BT3o3ZmpH+grTzlDDbe9QZzIfO6cr37pAFt7JfgUABviLff+umIZi8e7eLtDiH7xE/YiT39Dy2ZCZoS5vLF/Pa4NXL922GmjPVxVBwfhXd39SS1nAqUroC6fgQtgWD5O+g1UlIK+6VyFDN+gZUZ/jOBpulLBTztu3SAtlSCmdv/eXXodFIgzbjiI/x60ITe1KOFbhJZj4ge60ZmBJs8ex673Rz+/eb5X3/UB3fR+8pThy/sLj4F1Nco/sGJtbmfM5u7wO8EfW/ByozrpuX/IuxZrUXlgSxOK3gQ1nyGZWWhCXGpetRZgUspHXJ9AX1nLj4NtVyqyuWQM2qwV1RrQIWSvldyAIVJHHuvi3smhtuRrL3hnwQaH+MalcPHfe9mLXsGz5SSQnSf0rVtyetqDp0Uw7ZWBjJwKTF25EnpnqjGurccRhookYDvzi9cuq7rhy5fIvrSCJCYQ8SE6lLEp8LlZTRwaG42kH2GIEsLm+VGoTl7SkVfsVd7FKePtOZm+a/v46j9l0ro8egF9yrRwoeSeclXkCEz+OdYz5sZ9ySn1G+GYoimHcp6bybrgoTltO3eJyoFe3QAe7zNSKhWsODSPO4DW3txUd8k1gf/iHL+r+b8+zoB5u8V725uh05roFLLcv0orlN9Wg9qJMlhvE2KS+SkrK0uzWyKtqssfEOKg0RaGsCODd3lSmc1WqyNhVa3jlUq+IyGpEuGkWQgxDWkaXxWABSi40Z2FLIRXeUBivYptjQg2ob8QLiCsEEXCRA/REkpWZvVsgIV2QlQo9hinvAacaS5Ak6AKkMhlZmYBBZ7xrtao0HUTt27DFtQ+ljfoW4N1v5zJrD4UKFdIWSMiked1TNxL2/9qXZ4Hpn28obeZ0p899jk7CKsV828qzhoTOvJXVPd4815jRfvsr3dPRve/DrfmAVIZU9j84JcVjO5cwCEnRHRf4s9ioi+GQLnkBW8a07n5JY0AqA2QcMUm9VZI4qtgLh6+5ryMrLxcGMNga4repw5Zd0cBapi8pp7JgjGde2FR7bvxPKbolz46OAGOVAJr33ozHOX7TWvIXOv+phNeMYFFLf9rmiifE0P9PPMnfRcffW9t3bAv/QOX5tsHK18cMct9Ym++c0rD06sjeu3JWm3X61y/nIUaNArkVcScmIIDyCymkKomNLk4mjRHZ5sskhUtdQlYazCVuVWmEvjWd+Cs+T0ZhqhqKQ6i/xT2ZrVbhpfw14CeHCfiioak4dylboZPP3DzICLK1969eX/AO5YroW+1fm7CKjUn77zj5OcbNwGXRypbhEVsKkueO2MeRqyFD1MKaFgI4Pb+QQdHnOLcJKK/M35c3wke8xLi/c8bATlshTEGsWIaz0MhxShEZbu3iW+oLAnpOZf1MWokgoaeO7AzQyEjj/kr2IvfrVDt6Eq2E56qyMQmSdVsvV6mQN0HQowLOewAIF1ww1bV8ZThY5GRN2ZoRg76uywNXTiJkSlYOiJE1wvIJa+AvOX+JbEFxS+8B8HT/M8GlD79VrtUQjEhXJyzL7VZ1KxvaXugSHi3f/TZruQ/5M3/HcZaArmei53hGxuiz1MDbp0N/HTWydxTnwN5q2WKvcpGZvzbTaZupoHLHRPCQlLEG7AATTYHFZdi+UwaMkT5ItZJcyeiEi7PUhSfJi/TaIm7ZAFqsLowrCdo4hfDpP0E9QXDMAn3SxQjVcT4Qj5JAlZlJ2JecAVwK6ILBuDmrja4nemXmWW9aZb3QpnUvMiWrcH/86UJK2bc8xNeAYRWM3C510zNUtuCr49WXe4wgrpUnwlNkUIDGWr94KBEaKu0RvD7rX4yi8FhRidjS+WEP+3pHKNWJOAbCd3X+BIXNqlfkjTeWlscsOehvuRGD3Aa+GG9JYGpTgbUmKmdKsNox1fEl00sltukFuyNelnvgrAilAl2aje2eQ7pMuaIL0QIKhHJqVWjDFzBEhREoaOwMTC/kBbNKyObYFBk/zOFjNe/0HBLviGiJF5LpflE3iovDtQEz7gzNSKwKQooWptWXvah0Db/6coCYBCgUbaxyG4vssnniTxUyxTqErka/zUZIqZXn6L3dOmK0FxXuNmXevavTs3OLqPcjxW/erYDoGWlHWkuxFM+aaIOMc/YKnG1rzUM40I5VLqz9S4EbkbmzFBrWvjs/3MK7ipTvzgyMaoCYNlEJF0+12sB0YAWVvfEDSt/JVNdjOIwtmMSfmP8aJj3XowJ7IrWqXnB2gW9X3Rak5Hsw4b0QZ6gp3uCOiObYRmyokwwsTaJi2Wzbct8CsNZX7/XGtEm3nPonYykVyGdHcx4W2hF0r0wQElQp9SrJB5p4nhSqigtFeit04IjgnHhFJ3k10DVGtccGHl4c3mNrtmUeysT0sfRTHAVA71scASaTMk/FAQMaFpo44y7Q3iGwgX/SRGM0m2VaNlLtmYPI2I2CvgKvHk3dTMgOLLIdRsyGiybSJJJG17F5Ul5xhyMyoQfzzD94jZtRSvWTbW4XdB9JW9Zt1ZcKmgAL9vRQipYrJAo7ntyz/Bg7xTj0hsKR9xbnPDjtkcxKt8Ut8emZTbbUkm+jcsxmdEsmMsZIddUhz5hEAtE1yHjMFRTuSsWBDNG2dbwXh3ca1CDx7uSwJop8QEHksoQzNHL7Kjiqj/L+wYav1bnvCzYCfrNgSRy3XFbsmDJHuabrSnjE1BjH7l1AcqSAuenBW3Px4OJU8RO6muIjLiJ/eGl2+ia7R79F6aZjnpLnlCE0iGr0kKquNAsLs2a0CkreA+/QoKme/tud+Lq1BNibm3gC5ZiMdAqJXP1OxRiyfGb8Mb0TJLgeo7ikrnq4wvaUwA3z8Yd7Ynro0cExHKWtchPMx6PYWclAy0Wr51Z8LSTnbMk52NlEYB/+w423akrGFUulYFglWDR4njbwP9k7W4a9saQzpNglVoa1koXH2J4ePc6RH4iNwWMbrX98IPFYxvk0HaPCRDS/eY/DinQICMFqvGUV1BRNr305jaktoFt7dQIFpoKEF3+z8Pv9paoOPjLPKLUjzV3CxtpYRqxAuuW/xTEFXhofhrzxOyWg26qHfFPLOYmU/1tn7jO3RqoaQ9PiE1garyz+OHTVTIQiyxMsTEylmx96mgQm0g36DoxkCmYW+ajGyf6p8VCWBfgiPkEty7dledYWlT+a2jadoBV17Xn5xB55j2QH2er+dHdyWY4Wf3vY8BtmwIkqrj7UEnICT/fRF/R/bSfunT49uoSCalZe/N6pUdn7Zos211++29kOK/DrhdpFv099/4+yOXNWSSdBosNpnLeq/3fhcm4svWmNwWR5QFKyhGnGc1RskU+sb7E6ZWM2q5adAXmASGggqFV1PfCCTlVB1DXu7qz4ihhAGxB5d8CrmSG24RdGori+wXxapH6uBsVYPEwURuVEaiLYCP+g7hVJNt4bdwoc2GZluJOAzQb0oXdq7OPsWLas3OO8bKh9Nl1zyFeEkyzPmq3TmbkDFd6mB08OojpDWZm56ztlyQe4hCu9lnE4CT3CZ/Ly0rJaTAU3yC493j7KUMm9rIidcQHZEYoYmYRQWRGMJpMoBk0eeskyDK/n1CVuxj+7n4Xg8yBZBJAYBbC4KGHw49+h4yRA0ud3KwXF3x9wjht5VbdFqc41wua5GzLrugoQF+v3hQ5ZJAPVhpg8AN9Bmo0xD2QOTNkbLfLV8HdYj9fSg1+k9Lz98VQzxuR4RP/MnNh6i5MKvrOpdsBlG+ZcUwUFH7n3A1IaXEZocAKawislCKyC0HaVEsmmFJyyoCEJMLq3Zr5zq6C9G6daV+lieAIhaTmD7QYMOPLQzc9kvy2b4u+IiO5cWzTk57h622wkzYXVJ5CDm6cjAw34BnKsLVei/ISibtKvSgt/skdosKVTtbO1viugDZFD58QZmXKJM3JrE2R+rZrMd6bWZ9ZoOM90aLkd+ay4aZnJT/EEt7hp1hDZTxpuSq7mgjS7/D/961kc6KtQEx8SR49xCFJ6ban5Io/HhlABHRl7sycknV8SKZNCTmmEM3b9+IIuJav9KwvUxliwz+L+HqxN4V9eAKy123tOst40v/8/enxmnRsvBgOMJfyalqXx4gItL4tmR54zKFjCCBlcA4p5pjn/tv9Fnu4Qx5lhs1fEmNiwbDVydQjZyqlfBK2FaYhsI6Zfh3Bmy9DVQ5mqhZu6dGlo7EcZmbMxq39tF/NwUDU5jB2FrCEJc7DeBpESwXmtH2ei9JpW1O15dGRoly3FLrHJr3kXtpVkGkivywKQCwBFmt+6tcVGj01F62vN9/8KzfEEyS4IBZBvCAuTTZTcLos513pY1muZbAWa5VCBCWudMCLLzOk4hUOiGvH7Tt+zTDKV3vSWigBAR7QvgptNqygi6fmLgok/s/vIz58toPWjnDuTBbhcLWldFNF3zeunNBQShZjGli8cpaDIEhgHzfpFmp9oHnGbLTUG2SDXjcbTxD4zKH3xx59rvDp1aJmK7/ffenv7DdTxSXM+mhieS4GRckknkgYVhAQ0ljiNMqiKmwMEh6Ole8VgRxJ4iSTpyW386Y+nFNS4hxaUppix1NUuogUmQRJkzzx9I3VrtRDSNMEWGNJSpJAaN5uw+Em85m09fmuJbOt22cCtwtFLz47hiMtkC/eNrjiENFiB6BE0yX3jQ/DQ2Cu9HLbd+0g1MYiIgXr6s0Np6hyi3OljdO9KqsmbPX96lryn6Iql/+7YO2rDNMApnUhOKoP4VCIYlB6MjIvGvb+9xZhPaipmzuCLn+jWDV407gBRJ3inGglkYameV/lJO06cSdmfupzGZC3muJzytg8jm3tZ0LqcCjdxWcfUuEuEvFFwUB0RYv8GrK4X9lcugLR0AOU3l3INcwp0eMkEyYxYmJY0ngNF9RvrjD4p+OhIeA8WoFXBPGqHYA8SZ/dWl3Rrgbj+7U39wZKwrE/v6S3Ye8X22ubG6WAdrf95ZE3+HFRfPuu26hxlN5XvsK9ifep1jnJa1qgvexwfOp7AuHrwNQGzPK/hB09b0liGGpco4Tx564X0ibFGtZox8CD88UIb3rchX35uMrD3Xd/TsT4PwMuhP0nSoFoIcybQ/ogN7ToY+1Al5rHKfFudPdR5iXieYVWjVpL2pH7DV46XwmrHOMddvr9UuJ5zkkhsqZDKiJ6zfB49unTj934Az8PdVO4Qg2NJ/yn0ETtP2fmiruY+LSgo4Fm+ed2Z/w3gfUtwcr0MbqsQM+iLSKGnT7D9+9pB09SmX1aTIwknuUeL0lH9g0bXYngX6hiZLJ9VgEJN5ucRZfwSbSQsmE9Z3Rw7RBGhkRMPRPYHCU/COFO5HawIFB1pPJiXPFFNR54SInTD2lwRmO1NUFPSuKhIMPp3GQMEnphdQTgGyPZkv1yEzDZw+jq45+S1nNrLpUkSbHqdkVgnN8xIb9MCCSZyCIR5/x6McYrQg2MCzsnFLcvJg8NayafbcpJE26li7YcGSgq3BESUV9mlBOK2i8bUnHvgvdw+S899sbCinWV6oE3P3U3CYbjECcwRMB4JMqqABXy2nUOJKTYNPVMzo1kLwqd9G/1zBlZWHGGaDTpOtBjXahI4C49zHipI/VQP4fnFHDccgqqW9+VHYoatsnJyHfC+ZuqpD8XcawAfQCrq1FwldeWf/zNssfEFlfiJ5OrByYeugQUVXNAT9N3FJgbl3s2z+nctBAJ6VUPdxloWlraeFmODkZwuDm3w3aEzjn2mIXs52sL0v+uZOpcl5e4ii501UiIc/tg9w9o4JrOe1XedvWqExqPT74elX40gaKmQy/H0xY8qji/H9s74zeGDWM4RzXDm/jG00A1mWKfjhOWacWo+pJtCqKjKct9F4v5+r5PDo++ce8dp2A8pBAl25sOmlJ0Ran7zg+2WOg8UWHp/GolMH95qzqqaker9rRv5HoXxhJLeNcVCyle1pGcbwaliYBLaumtfz0K7iMMtGkQWDbpjx3eRCkcXmWCMCjOYFxjEP4LVMDfxIRQE/B/+LKby5migAsgqxQmISKBQggBcu3j02pHpyPWnPVbZWJrxdjKZ50S8VjpDLLqUhqE0bs/FLItd8i/evhDGjIztzO+Ds2EmQRd3rAZW7B+NDUYNayVw+gbzwvN8oVDk7jjIK966imLpIpl2BPpNREaRdzY67WwVRmjXfWDBZ3XYo34CTqWwR5eFn5YV96IcX1seEm+ccwA1eN9ycJWJsinx37/Seo6aDdfchySvpcWh5Inf/LvXB3CBpz8NPGjYWuTm+AFlsE1FBrk2h6cx7i1fF2D7DLM67pPqJhs5W2efCroHOX8EpUmRFnXz7uKGz3dKXX097NnPDvojZ/lzuaS9wljPrrOWXA1ZJs+7q1QH64CUuyX/H8s0+cu7tCCC4A6vJ5L3lKXdys7333NhJmH6i/HwZ/Z8ET/hYrPTo6a/21JJO45XtObPdm9dezGd4ng15ffHsZRHpydCz197YP53+jS+yMc7r3axB8XUDY+MHMDniaL+TorpyEYgJN45i+c1x29AqQBXQhife29ZyIIgrio6oEwSIEGgSyMk+s7HLVqZJkXKt6bO8YHgo+4ONskVJe4GzxICVOv7kzhVndAJk/EUWohYJ3hEUB6+9ViOSD/mC6VxnKEbDmgkBaZ6dMPQMDMlK86LDonQDKUvzfadaXZPWO7vU3lHxm6Y0yHJ157oY93mrWczRtFIf6V1RxUUU4OdYrEdQSPlo+B9X005I7x6wngso+7l1yPaRQh0Usf3vBg4zoG2kEA7ATpHxTjdtSr2thfSS1INxcTlU+PcRpdmzfZ3jZJ3Wws8QHFiS2TLTXbm8YUjfFN8l2OJA+sTTj15U/YeT3iEv1FeRtgy0nZLUBMfSmq0nkhyP7XSRiahLA1Qq4ZkGnWzw4Jk8B9ZHvXEnSpPLgZFhsgk7OnBvfUvVRCnPVtGpsEluZMo+JV+6yWlkyjVP4R69DkIGE3ewLNbtV/DFRPoMmtxEeTA4TV7PZvev+kp7r9JiFBvwMmT1yfo4/qd8th6B+CngH1wTNLyDWgH0mCPF4vgmUkVXHf9NldBZZO/bBNXp8h7UcO30I5XnZXHL6G3X+Xr3puIqX/rpyu+PC+bZRwKnfp0AMzY3mXz6VCb6Hd7YuSMYaSSphs1SCSo1EaDctsqN2WbDLKHPw3OjbHA/+q/oSArKPUBluzGEhyf4RkiLBOim4VwMzIYcNyjpQ73S2/krR3kcmNzIh4zeT2VAjICNMd3xAFMSlloA4zqF6YOFy0PLaJgzOaOyDiNRpaafJZ7nLP2e302ncXPpc2nS2euyXUJL4NWP7xmHi11MNw1LH5aIKfi90vjIS2puN4jPkGfsG1Zls5JddpEPqLQvHlmaMXD7ju1XaiWzLvbJ4NGAuGu6P7yxRfwo43o+I4A00zS8VAhJ7Hzk59GW3J4n3v+nKb4/D9dKqq18msKZqxxXGQwMCybcuVtihUV3rKKIDgpoEi8KS2+OnJbxthywCEsyV1syapcTirvS7HGIxpgWtlVt4Yl8LG6dAvOKxJnk2wAVVVZtEso2dMiqMkbH7Lon0IK2ihOX5Wpz8EuIsZRLMZyBt0MMo6WwpWfZ4FNwMuJivZVxvey2soKRR0S5jAAOxUyp8oWk4JNBhu7viqVX+4RwAwYRl40dusqg0ChHHTbrzEdH5c5RzgnxLeCK2aANw/OLRaPcE93x6FUWYxSL9F4+l0r+rTJ0gbUzvbLG0t77wifD1n9eQ92tspKV/JZ4gH9Qh0J3KQiysQ7hSWdpmkDq5ScKRB0HSINcJ0KM+R8wGDiMWWd0s7o0ttePbK5/0uZwnz6CMIcJNShosgP6phDUFaXpaPhvzehV4rMV2gwrFo6PukFTLyi0SxLAZpbQ3Vy0ZFKpF8VRdw5QH7OGEgG1168dESgEf4iH2mq0Jl8I2nka865j8GooGPH5Fy23Xe4h2TJzmnpulsb+RRnTKzD5FBP+cRS89BcChATz+IIITai8obnBzB5bn/df0O3wSFqQJkiVam8Tmu5Z8n5LMf9T41fTYzFaVro8MEfMecUq2ZLpSgh28a3G2par2Eul84XK01LXx/bnzRJP1VyTL0bIfY+UOdJRFo4KNHHQ/IeqCwxpf7mDHhnQIULClISWVqkqV2CZ0E9ntDY6QtAtNSiIBHLD7LTNM+Hjz8dHVwIaS+BvW+eJbkOTUYozp1g9xRZ6IbJcd/CWpFeBODVpz73e78nOFzNCTSBRwI5OdkJmeM6O5Re/NnwHftoLFVHQMOx89gu0tpWI3z6alq3Nd/9WmpyooJWPT4u4On4EOUPrYHDe9aXB++wO/Lb3K6K9ln8xsual++9cJhSxyPNbfg14IZDmBStpW1ctieGKJ+0FvOZOSRlujCQfK8Mx9/c2WOsm3ExH99Z+4wWOvPtaLSeJOCF6WO5CppSaP9wo6wapWPr49Ge5HdEFSITL8asXmC6HIkeeOWcmmAUG6DDmgrfDfASltWEoggnTSytZQQFEDQBGJ3+BxxIPEWVmGm+hn2uJJMAa998JCg5kLNgf8Okh93vlMWp9ATFOHAuWNBS+EhbNYyB+sqMD4IiflUypECSoDCzMIevmt7MoxggY6VQdjCRQ5zBnBaPNQTQw0SM0rxsZJ2u1C3ePtKNJh+W68fY6ktkVkempZLD4H8b67pxqDcDOeo2dLWXrTFETZa1i+838vy7f+Ixt3UsDtm6y3pm/FlmDrGxpzfdI44sOsTVqeg+mnm8Nlc9NJNeHUljW/4xQ3OHzUpG+8BwyxP348uwXoi69bdl75feb7H/L5l6hAwUCrTkhPCMJuMXwqJa1nBpXbmBKQtfRW8UCSEQ+EQCUXn4sADEO88gb+9fihRN3N6Uw/myzuvZWJOi232vOAgYSDvGunDiHI2Fr5nAEmm6JGXMzlL12gp7s7wDMVcKmhghYea7e2TsFEIUD9V/eiHhN/QHggZpFL25ko+p3SmP1Al4d1sl5cL3zlveK+5quUS6nvxSIf21BDGSBjONJ0JhodW21YFXGB2dHU+qffyWFNgWd7RKxDp9ePasA4aAipJDTCgb3EfFsi6HpPbdUkcJa1hDNvSeAwF26p+1uRW01Ur8d+P4z071Fl48GWO0CiO/ORCNkpIPHftISxPPEHMNFL8TO1HrAhDa+vdo4rrZmlMhn9X05qOgYOqJ1eSUwlDLSmahhtedmQqCs0ftvzZa8KrhSnMvoyLSY3j1cUYeFpfXJQ1eLL9fAtevK9wx7tFM/dNz8XrRBdoCgO9nHAxDHUnpXW+MY0f+kfsmw9QYeWyBYE9CfDY1AlYuuBcmHMD9eIl5STnd3VmdB+dZ9N0w0Vln5y68vHKpWDqwBQYuxKrsduwImSteQfaoxuf/y9WxdgN+/LG825Vdp/QD8jNIgJoUTFSHFcA7R9p/GvH4E5Nnp5kQ82e+sufRwD4y9Q4nqhFIsErZlFQ/IkKAij3zRQfBCQGC+O4XWXvSQXj2slEwf/XRUEZ5/iLvd4QzoKmkWPrp39Y1pQTOlgso9BsKs3vVaFFscng6paSngyfGIp796wdfQ7yOQ2NTmb5bHjdeoXYD7rtXurB8+5BHc61X80u3RnvtwakP1f+q6aXti5tce2zgatZxRAo4NTYpOfksLLVclhPXfTLC5gab58TO7lV/DnsHGoxl3dtDQxmeyOw4gvjC9vgvdXvBz+fFbvQ3kPvv+ocAI3oZAW+X8eGRS/7rvaPJjfUws5DVe0ner5kgPnpPPBqNlyNv+Xvle9dXjfdBKdCAFOjNFByQ5lQOpy1UoDo5ptH/y6Z3DUU757wFfnNddu64ft6Ylbri0Z54GJx6NSgz6RDx6drnFbIkiN7+8TQF0LA+5cu79Dw93xEGshCClJfdvAPiZxUiwIQuEE1xDnmxeWG/U8hMgtIMhVOZhQnBMkxqq+o4nLjlp2FY7FJXjWcpHKfj/JqkmR4FjEODL5/uOsH9YZvPd3cN7858mfov39+gupK5/NFlBWXq5j3nn46BVAbpbnWJE3aOeFHy/951tEI20OXjp6CuM3zhsfC1w8jJu0opNcW6z+Txo3IGJR3cI4Kejn7VflKdcSP0gorSft5Pb14r7biH0KWIn82C72TMJ/Qdcss5ky9BMhY+odLK6BQS77RnPcgDI0/rHmxhkZDbuXT/MOglEJjiAw+TyySGgVuJKwX1c6PTXtx3SesLpovuyw2e7abxMzsZL7NScFqKD/VEvxy+K6o9+PSDpnfPWJ/rr7oDgHKIxW/+eh73aNDTqeBVhn/RXNNWxQafEDj0gGaKlDlE9DYj+lQhqWr6lVQZQ+q9luTNsHT3/+whAOXyS2dvrqPig5d0ZCAWPPwr44rI0bCoW2PZp3WUaCNLME3tZzcQCc6SzemkJgAK7tCiMcLVR2lZEXbmzVPqs6UaEu+SQIks/T9xgAHOKsDzh8unjwa9jzw4uNCJRY6Xb/u9lsKVjGlDBeEgYPT/3t+LxQv/aly9scrKZTQlujrw9h4RJXYB/Xe7g1YRWh316JmS7Hvh+SEys5ycDqobLxAVDo282oNfKTtet2y73+e6x+STCgZt+w6/FsbcAcMzJhMQ8LclHr66PWpaBF/+S+Z32tZ+vGRHzwvgBozPMlpJ0oOt/pkLxta57x+vRkdUa8or/l9YqPuMTUHnozSoYJonORRWQ9aDOtR3zUuu9vL+k9GFnF8e5k+94n+cIix55IW0AG94UAfNP1MzyyYxK1RJguzj2mJRKKw3rHh61nfLrTWW2YjwQDfiM97lsJ/l4r4Xi1xfb/FbwUQCdBsa8ZutQU75oGuHU0/3KE1T/T177p9EhWkyrAq8OQxEUeXNTZvLySPZC2f3bLhE5/tvuj6+BcbW/dEkO634L153e4v1vM/l0ilmEjuD+XATwcXnUCwp3GtkfZdXRg1loaOmtz1rcyQyPTrLQN1ICr+4+Drg5dunyA/SL0Uj925Cgm7Vaohxozce8hcFePklcul9iwQKrlKRCXGFdQp3CG3VKG75oB++rByIV11PAP2RNR68lC0gQ3af9NGDIZK1wY9D5WJlNTCUYFBVodFTHsKocVSxGKcxXPWEiMMObBQRfG5kHLznSIN+K3ICbvUXirP32vhLWSMc0Fm5oD96FhqMw2lRRVM1hrVMXGrimQC/zPdE22VzE+2peZdw4MbSX9faxVDLuWtdp9lQETSUkYrwrYw3qD3qJtZpEzzlC1L7Le+tjDBIb/7qToP+CrqZnNKRSSaWz0/zrleBu3KY/VRcUAe0RQyIYhB0YFnLBd9Ze4T21+qWFz7y8affA5HncKUAAaUDJ5AoUqQMMNGXl2hybQZj2S7mfouaKBTKOWqw4Cvpe1YfHKZ4yinupOqS2rBBLO0rgsrAFPtva2k0MYW1L/x7vy9O3xQlncNarDFjQszX7GPgTH1u+V3QvwIv/tbTaKptXBIVCBydwHQg25qWWuZdgh+Wtniultxtt9sx0pjv7K5Lh24gIifdtO+ycLx5jKV6cgyalGydN2itQLDI4aJUCcdXDINnNUVPigfiGGMmLEIzQU8vyUpzstPjyGx5N5PKh1Pltj8w79kYLF/VXibVynTXurVIwdqZPFcM2gka2lviqM5jXjYlXxgbk/LA/HWiwGszUv7Zk4NIOwbRlUj2oQOj1/kkJk3hoTsA2mU//qeuAfK9eS1luQ7Iah735e1rnIRpDleGjsDEGnp1vOqv5O/BaxAntFiQhhXcFqMsQRN1OSF7M3oOI1z0aW+4oS+tS5IPqeydWLFDwZFaIshMkUFDYiyGkFh1FDjNLyM9qlTC558vmn1vKOplNPweDldZMqutqcRJEn3A16gKOmnzkk2B6xBDTou25Opc15fh746fX64zjV5/4CvoG9btiHBIE6on6Da4akUscqDwojY76UC+ncr3xoxWo29CQFv/coKyQdMFk7IcWfHxVcd5PmlrPoif2jHSEeMbuhcie96JvGaa6HHbEsMBIWJdBNeh7GiHtPuTNPjP6YWtpDB7Un67CFFxxyiT9zFdOEef/qrC2Ty8mFIX9nGwZUiAX9W4fEyOdT301ZY47sQIeC7RrYFJBklZ+6KSkHSPyshfU2BA4ufzBcnC0K78iie6VVe42CYYOp0rEfYyaSuBbIg3z/8j2uc7kzdP12LXwsNFUduykfuyGXqhW5S/a/tu40wtVeze8K6nUWKszbGjDdFmgNbAxj0Y+rs9n/YL2g70DbjYi5SNgeVrLAwTEnbG/TK/aaCTU2NP+01T54IgYd6vOB1UzcEqdA7+QAUXZyIdgWDgpiOTUeS4cazi553KHGpn1ZYKN429S+BX0sFT/H1so+mJneP0r1ZPfXI3r9XBel5s/SyFO8KmVzvH16Fn6NrxeRCkmpMPkHO6ASufnucB6mNMKR8cEvueQPyZ5Y/bJRaQvQLu2bftXeFANMyh6oAghVRcD3U6vUzbWKggxg69pWxneXuyxu5Bhqt6DMOvfwhCj1/20Q+hW1pzEDb8itQgOl2wJEHdkR0IEqpW8vC+UaUViJLOXeLMDyUI8iIhtiPFvbZaBHIz5oScA6JClVjmW18aW4QzK4UEIyXOGEisLOd9O8dXds9c0Y4fJ9s13ek/5IGRjA7V619TiP+jD8i9vpKybGvAHC5WXFHuQ/l+NitV9VF1Fz7cG7HVAoxvvLWuGKPGHQwO2uuMNkivXpeM+eHZa9bubxjvaax+UwNvuubFdRn1QtCDu7LRwl7Q4v4T/xnQ99cwOy8JDKc2tyRDfn3W7NIOgiaX5t6wyhXCYWLd7TCW4y5jKSBpNRQ+nPfzqJTKtC25pD5iSXzMnbvnkeRMAv9ox98NE66oNCZnu1Y0k9AL5xrjAOtJN9oe6pSLe73rliy1rR846SBxITNya1VkElbi2S9xHKkARjuERuYx3Qf5Xtz4cm1FGn9vIJ19CVkJ7NBemmM+IbSIKMWtd8t7BZ/OhSPv6NxqXxBHYXIBRSVOPCNk0QDnQWB3p2313Lc5YubOiAxqhawJMqYg6oZzKHLItzjp9S4vOiY+6HMVLhcUiru2+EvxeUYKRSZV8lXpgAYccoFz6Xg9SiRSqUchhzbispWKK9jGn1GEUQ2WnGZkbf1/tj9hpi52wAasJC7oXylCHYSq314lQqSvyKUL4lyzRp3b70VWXOX/T0yuasJC7/1Hs54oQo9BMPBX4G3gcDrzLKU9LEPD+MfLKyU1ui2nRzQw94juL1hCjcNkzBJ9RTJ3jxGnrxzE6nKbSdwHgMtzyo93iQneG7MxYy7mE2DwSek3wJDgaoOBuiEWpsiikurTeXBE4TEiRdEzs+saYJ76TqfAHTEcaayzNAxe1dWbbhpg1wlUuaLNLDSCyvX1ugKwopFWtjgq6GgFqVFUHZNIDSMhHZRuqiu0E7tFeRWZx/MyW1zPVnixdhNWaCcYlOnPZj5ccfg/l4a67Z+766ssSHtiFd7lny61ScjfQO4islK/fRqavm+0jeaUmsmytCUlx55JRNhnjrL3A2aOjomk08K+BeabOVsT7KO8dI+nx1IZFfhcZSGrupvW7DjC6FgCC/9W9SQClFrrPoLWJpAAbpnuk8sxidUSAtckIDgld69REJNdJTfS9aE7PLPcq5l4JqFUPpkbeijFg53VmT5ddnnnC8DreijhvUHI8nkmuWjVcioDmXijid//8HdcSqzVy1f6mEpy/W7fFiQrsjlK4USVwTHVlGKrd4d3IWdTKXI0rdJe9wkMHlMQhP3ISsOxWMS1BI3h0wdtq1lnGptm/X05O+ZZbpU8nbi6lrylujQK58g9tYZnamzcO7efEsH0+KziCx+NlUee/N90FF/0C5oMQGICjmFCXQlESyMtMpEkrBIAktrRpSNgNIyltKHsT7yRHbuQGDSrDrvKROWpFNPv3kGsyXzcn/oan0miGyX/S4G3rQmLPjlPC1hjY7+8fHZ3mzp0MK1FRpfHmcB5QVEHYjTpoxRu9ZcwZyNrXRY2kdHpAyBulAQJtZ4GEJ1oTAMNNm+r+7f23BlasswdVVzMnuZ0t+b/eYoWv8D76xRToEKtDs/eCBYS0XOnIuZFEwVFMN9REwBXxAb9PyDtDgbwKKQqskop8Gnca0xwV71G9eoUNIYHcgD/pvXIhKs4Olfqa/qj4PJ9ff2E9fKI61qbWsNWHcfVzy29AxXw4TAJ2WP33/+A0j3F3lihDDVRcpMDiRvy2EZX2Zpomcoiz98JEl6N1J4OBxID9VSsWjzt3b9Jo1CmRFenigcbCglki91t0HJVaD6tvNUKKTXLBWubyX+1meV0oBxw7+tvWpA/S5vFWJ7sz78CUNr/ep5vtRtYz5QVZ81WaHZwddJ8AT/PMFeK+1edRpeA3L7p///rQrMke4N+V9mU5PlBZwdjeJPUEXUBrzO34I5lWEUtuKHGJhlYIjPdoyjhFIP4NEhPhRPwLZY9ORRnQLsTm0ZTuZbgaTEQw8ykrQXeT12gIRAqzPdfqqdbX0SjGs9Kz3lBVpwoqr/CpYlHcfdBTr6WA7cSu2rfjcJ/q0/Ctvz73OZFUBScZXoqwujsFt0hCVeNWDIw/z6+jo87yD+Hj2aCus7ahXrQVEdQhNI1MnVkgThJWnzTugMTwo1kb0zKRou29joh9qws5f4AdjdH5mhkwrGcWiFG+dEI/R9JT7vUR7H2r/W6MclBwm/gbCrQdwKZwmrrEBqnR/5vZh3IkrrOu/8cfk2wD1APOPfFqUtkW0O4enKTFBfM7X8rjT7gvQKcXpX2grCQ3fTRblBXPbtoNqKFVgbGkADZCVaqYXjtpX/hYKb57oQbTkPtwZORbPBWTgb4EYOuH2tM5CcyBmecmOuqUwiHnFZ5vOWF/1zxAQ/qU77S4G4r08Fs5aAPzJiiFzmIfOEsKKswfbYM0Hm8Qp37ufJFzKOAcx9OjZsdaanwtxx2QXFE/H1QyGWIMoCuVVN0b71xVZbYbdE9vjyBUaGsZUgHaekuRwJ4LVZFc8i5gu1lk15qnOrAw5GhDcZW2/awoe5eU95HKiP7zJ4aDALW6teP6jguFOabqhlA3TtNaxUkL2hk/lnyF/zmfJw1NjAYbTsGMnldfn3Fcnk6gLc00XJ38qdrho0pFtfOKDIKOisyPnnQ/AUQdFD1vRNsXMjOhWMxh/uC/u1A+zjgmhxwhSBxoSP+BImUkA4KSVlDlhOco9jOUdxVVZyE3vN5Wvnsk7bTWk9Fs6wfNw145iULnyT4q/5AvIQWJucTTaCihIhaT7UHHaNkpRQzwqUROGqFhIbwC8MErTSZkx7dmLQ+gQtUmvxtzg7SOs01GjwY1yD2sNH3WsNLGUyQCE7dUfTfdw7Xq1f+eG+se1RuB54XZd+1nhC1Z76XyVw+n8E9cf4PwHlShcWqE3hlF10R8d91OjGV3XIamqxUssHmqomCFATtJII/JStJlalHQHUAd1sDH0Ja1k7SDi+8AKh9jk1bFyH0tRRHLXxVCRBBK9IWJ2wjeKEGpFff4A4+pH1Df7x696NMNK2zAGYAx1sCn7FVrNVAyTPFu9TNYN9lZu+i2W1FZE12eKl+9khK3pvJo0DsGpET+bm93QMwE9DXT/blVOpMoF5q2k/hdNVqDl28UnNms/p5dTYUSc4z6L/o4HMG7jOs/2P3L6rE+jpx1boySuaYAvVfuahuHuPTnSLgV/Er3TIhTlLPnMdOBm6UexM3KC0G+iZkSFshZKLfGyZwDLOUTfRQy+C2YekO+p5IKyBrim1U4m0HprYIPycrWc7Dxzeu1lu4MT5q4FSF9sgnAkY7X6T5qTMR8ztQDnXutt38o2blhmqu4q4uz6b3rmxmIMcs8vo7BnjqvPNX3ZuWOhZQs635oSCgtFpFpuSu8wxbxGPRtSLzuF9dYw+bClgSpS1CWWHyGemmAfp/taJxAQwbk0dHMFxwzasYwR56TgY2qig9noIuQus6JT7N/SlNknuB1CWmE8Qmy4NwYBAXDb7fENMHUSeVRGmxq1f8VRvEg0cxTaJvAfxp6k9K4JZf+mV46EwfUpzq57LfNRrbY8CxopQYFQDNYolnPQAaD/vOQItfiJVefnA4IVfiv6j74+lekYLrYud/IGJE4IN0PBLIFGYzn/myJsVINqrdlt43cjJgkh4y4IyTw0CajIEhJUhDeUuckuhtClmpWSxVrG3RMwWry+MwNKNRM7KwdgtEazt5nBVbwr3F20Y8F4WEaGnNWv5h30vhU/++WHK5y6dGOxon1qHkqCm3dcsbyCO3KEem5xUIX1b87Zm4yJXAJN4FwyDSZRGTUM4b4CQB+8GO5IAEr0OZdugsTJUZome+RiywCSFunng7vQa8Nwvbrnvc5pk/AOGir1wRY8ZIkd0hSbAuhRY4WaxqUjHYbEPC7djjo3brZKZUWr0a3YPlstBr2LGw9oPYomAUFvOpk31NAevCLMpUz3FQdBHHovwWQLpBo0dodHyGf1nA9fnJDE47+yeUALo7Gw2UYIiae/Ik/M3lGhD/RM4pH3XjMjBmnNcBlL7P5Z7Q27pO+Z+cjBbmCbsqrE3yd/M/wdYB/EJ1T5QcVmCXUNhec4bD6dGsp2IaXhZORLIr3XYEqaJmmx4fQs2uN36yb4jqkfGC+9jRZXLuv4cZjMNJL7YVECsgQAOo5gFWEaArmGPyR6t2cxlkdg8TwmI9dDxTw1s2GA6wYnWWs3at4nqQoBKGLlaKhBfF90NVm6UYn1hMg4cghpAe1Ll4OLKVoBJp8RoPcPj6kvTl8c1gJilbxY9k6mwoFasR3qMsAZpgssMOfQK8sMpAFk6wLVDOwKoFTqYEHz0/6ux4G/mfo4Pr+x4+L96ZlrtUwt1QAzZ+iEiLXbmD2ZI7MGtAvMsX/3b2KOXIX2DUweE52S+jRpS2Ema1ALtqFOzTnJp9CzWUkzXqSRMQ6pq2kp6hg1MdolIFWLTSHdSYpEkorSRvFoBdqWCwqAvKApyl+5Zi8oFb0JIkPzlhG9IQyENpztSbZ0mVNdJ2CJTlbsGNFpKy+VXSfPqxsOEuAoeI5xizgbxT500Xqfs806qlNMspAE2U7HEAE8RiRLhph++xr/YDaDvWcUDkRZQVBELI5bYYSvJhsb64pRw/CamXeRP82kXo8veJl48eYIUT6ks1mTpZdQY9Hz0T5SD1lpZRx363CANZJ2eaD2Xzv0hIj3R8xHjBKdfE7Hs9LUeZ2Y/kgMJJhB0oSlFkvw4kYDFHYJN1H6a5ksOU2d7ehuxCiNjH2Ee3VB9BFXedhOBJHLfcICfDDqf+5l9e7POy211EYzNsxlr6/IC2SXzIXPKV7bsW1MlkjOkNfd/8jSk3CVBj5HmcfGP7DRM6xL+Z177E8lBbfay1o5O7SgOPmtTYa4oyRcTBJONras019ylr2BeYyT5SFQlK8lUdYM5yoDsR09LcMeKLd52C6kLmqGZicPbbDVjgqZF67Jb5/JjvF9+cKduYpZmqbc+5EApv8O4mFvMvSCbg+fBr213P7i4iJtimTmfmn6i/M+NeJs7z+5I0h+JR0BpA6wxVDO/fk6+mp7z6+/37q11h7YFjD1WfPZNr8Z3WbKMeedlQPfmI5Vsr5hK+IovG6AEGlGK+iCdcZI0Yj8vWvUnasELe9zYJVmP7+gB/hZrBwpYoCXb8xOJsqwBQ1/0Hnr3WSwtjq1auzOwNpnwJOUcaL1l/K38lL0/RVplQp5CPq2Gb5YM1dqi9/aeUDMz7m5gVvZkZBZfbzR8tEH19sOkupMUn9Xr9lJavBiGja47L7C7/gj45y0QLrb0Hwq53nLxkcVX/0SPSCcXRy79dzDbJaWdWY0OR14N3QNsHmUogb6Otui1bR6kN1lRW0ZoPFdAm7RMcoGRvMmFT/vOD6BKjvOrqRVV0NJpp++sTeygHqeO4536U5DhSYjrykRiXjvGD5g2G8eojvx8WLjhT3QeXmrvFW2sA3505vKPL/LEaPakY20rhimtdyH2LTE0IIf8U7vpo7JQbDJSnwtSzr9pT7nUkm4dx/QXyFIyh7qaArUzZTY7BUVctedGZRXWSTOcd9TlxjVzQJMY1UKejPFX7UMGm1cslznh6Fizak1e2BhXse5MWNF1HqZK8RZer9U0Wgx8tz6VxDato1w1K93NuL3tFqHkeBhnJb3dp4EcUalDbLEF+bWj6ImEWnt4ZEDHgBcYeSNymuMDp6BXLm4VxHp1Qlf9xGYMT/BZsFs8ILlVPJUtsmFW+6D/mf4FATxO2NTWBZelOzSgs4CeVapU0gdhVGRj2Jd3TTkZGrLMrcJSww9vaTrGVz9hjG7idj4kfH7Nve+3w8NXubqdHuqlprq74Ca1g6Z9v2ggMcl31rV1hpkhSEv763ZQ5FjrnsJVSqmw0tT8RMa4gc+BlVooNq5543GtFVPbzWlc7hJIOCa9F+XGz16PxC/VwTIul2dw9qf/oeoRc2kXNHkPbMEi/0njxiUaQyMFEAmVd+iwBrKNxGU8qer7sDtHr1Ks3vAmkTYQI1Xz4Ww4xctNQZKt7scQ1NcS28Tmszlr6q5CfP1uwNAF1wancwnlE9aLbpLOMBYcqKpPHhkllix+k/06AOQU674UsL+jQK6mn8MzUq9LdpFg56CQcjqFpSHNE5DgNdiO0nl6rqk/1DR4K/S9kBRkWCS9YZvCFtpYam31P9c/CahTuDtM1EzfqeHAzjyqJuEmNXG36o7wSbDaE0ABU3jX6Uq0X9PoaMiXFMggd6wx4Ti828rtseI5HL8SR5d442b53biDrsl2GzaME2bkeNwS3yPFWyudc5wrliTVl+9oK/HK37Z+zHUGepiiH5yKz+ewvMYWDDXFblVMLKggYKzG2BbYzBKnZPJa/iMq4UkcX7b9iq6znuJevmDhjLi2+LcPMu2FEc7xBteUh/6b91lg0ddFpRwNvk+IJf4KDwHtUOzGs0LybxY+Jm0QxJY65LYG/Qt/Eqsi4xaukzz/UL995ilxfzzkRiqwO3tKtwgP1pRLN1vFI4hELmFtgT7hfRymrKBpFu7MpzsLszE1PmKEix0XvZh+mqjDO41YrM3Sj/8OTQQWC9bWaT6uob+oOJb08f7E+4+AsyWCSopB7jZa+Q1QZZgR0zp/7EasgAq9g8ySBmpSlQXnzc6w8oybpYc/8qgly62BbDlv0t2Du183AAme8/Y+6DmjIRUJfRXtdS6/Rhb5fRW9fmhOvQxzI/zS6Owh8PvGkmPrjukK8c6gTizDaVJ6S8bBYKe5y5amWc7ApWXea1YOVbgCT6MCOs7SHfFaD6TIc4iCc0ZsrYcdCNub04eUj81lcSZfQsKsVH3ROE8gzfp1ITzUv3itVuLPYBRvMBS0WdlEEp9K5/nE4uLskCqT3VsczinkuXUOZ1lyrDnAwRpDIfmAdGI9HwcZ2PbBTYEXHd0upc2lEZyo5CHL4d5dmku5Sw1LOUv1S9lLuyDR4lWsgu2BzI3ZS0Gg1ZOL8byqOdeoL+lerPgKla4HszXmEcIAg+0wMGZMG3C94rL0NOZjxrhPyYqTVlxtCLbY6yJ4sys3hKvIRhssRIwe2FNmYzoryMU8VQ1cB/G9aJEwVQ0M6ghmULiZJRoiDdxAwSNULspW42md+AErV/M+pbqxZcMgaP7SkSGi3/ZAlwVQdSG8SCPVQumeHig7Z5SxSCNfok+DSNrwJAXewt7JT79JRZ/rSO7D8cefGD45WyQHRZmSqNTpFiqvrq5pbYq8NSpWqGvYAIvIBlGwSf+4qXrgEuj8yPrxzKwYDEXfpuu8MV921G6Wq7yQYfffCoDYsBT72vSxa4OUuPsb9vxzQXLT/dHZ5v+8i/WDaPITiJRpGirRg5FyBmu3y88PeTaEVq3x4yu36mH9YjC6lqXkBbJBeC2eGQQSTuKKci2mDcJgBasud2lcf+w10SWRRl+6b/Q0zdpYNRjIVLz01qjQNEF0pYPVslEBughGjVBhjjlPgdWipEf2j1gFz2kNtitf82l7VjrDSWwME7ICcfPQCgD0c6Y+dqhUjrbeT6r7+F6dnPx0ZRDjyw56PEMxGyQDHIe5jR9oRezORD3UnSzbzfbxkKnftqTjGddaKGEfQXzKjtl6lee006L1pGzTb5GW64TT/lEE4+juEQnFIvUkmIgFyQWwumFyBPo+DO9bqkY7Yy6uuGhl0jwVNPIVUKg2Hb0V88tYeIsiQhvU9JV5KyeDOKNzNS9/Zd+Ez5UpfMkkpOIqFr3LRCUx16J6RpXAT9FuuN7d49gosEJCYSeUbd2xggWrmUO5JXpmanpQjTlJCv+QY/wM5Fr2bcZsz1yCOFulfcWWL01KWWlcSqSA7eej+zRDLQq04xvShJeEQ3+c5pejvf8kwS+DXA+2Q3hqaD2WDsigI5KYWBy5UQQ3QfE67wCFrxxYIQuwRuzydFmjugK33U+f8PCrp/IZ70UHMb5uSfD8XKvw5BCv0tRmdaFXx1ypMBnMzu3cq4I+RuZph4FawTTQ5Leb0MQFygqoDWSQ7GOiJxxrpKJzqYwtN62kXt6+IzNhlz/zxh8arn1iE5g78fruSP0ielAxceokRbMIwCS1QOai+iih6DhFsahbbYjLtxiM2Lc5aZKkQvEv7OA+Tb54mhiQ8qFEUyDpwwX5JFdGg195k07zy3wVd1h95Gf5JXJ1B+6JoN6UFylVx0PKK7iWE6VNNmiRGJirKu9/aVO9jmxn7GI/nAs7xDbGJrYoWAVrmo7ESuEJUM+b8a90gyJdE/O35V+EHU+NK3jcRJiq/QXJl8hXaU+HQrffdpqZSfoeCfdcvocnynOOyenvZCzPdQRq+k++uUgeXwP80Z3JCy19YTFafm+kqbTVWGy/PHdlczHx8O6Vxd4HH55vjTBlKr+Ovhh3obZwPjSkRyuXylNXW9CFNIv+iDrcAQ09i6iRV7goTXOzHxdu7bSQQCQi1WKRsLZSUOMXJpYoJdSLZ0XdsiImw0bzJcMVaOQwwdb2Rm0o9WBDd+4kTbQ5kEMDZiaFHK2fSkINpAmz5rliX02QtkNMmgYpkTaHOw78XJhpk2cYLhVw5ws4lOY9WxO0sEhMZILSIIAv9M3Kip8QxSnvhB91St9S+hxoCyWBi+/e/j7I++ybGcn6hVRDYVSDnDQJUsM04bWUj+FgfkXwvb5pSkIkdSiwwgmdtCJKQDnngP7vX7uH4/87vPMi4prLujbrGOum2vEzj1Xd6KmfbwB6N729EEo4+P3ls+hDwYnLmuzeN2TqZ+30SX3aIBt4ENSeve4gJXnpOEBalR5GzSIDSagdACCpD8jNNtcxUGdRwemwSOWAG6Heq0lSCzTG3lQe7YvzwpKODXpcAfbv6kP60mJi3M0QmP2HbyqJxRv0YdIL1Ma+VGElh8m0yu9Z1vDYnUId4b6cSjOYl+/5EoXGY2fhPpndwhwVeDHPsJoCYN7RZdb2lVj3e84rY/1YzpoK1HB9odSS8HV5rFefsgeWp4Bh0ZLQ+R7W3S1WK5wbp2ZYI+W4ftOI0OFjUqvC5tWy3sbMS+slBVaQuzXHMiEgFgctNP7nEWmjZvWrPIKQxx24M55sxfkjqg7bQ2LJU9T4Fr+SuT88Q5nD3IoXyccLgeHaBZio82GfmzBBE58a3jJ6m7J+Gvfo7MDCtC1p1Li5PWT4PP7L2/BHA9SMxgrYsLlJvHYj+1vH1lSfwD8tDQy/pS46KzGikvn5ICXD8s41y8JJ4sE7iZ0c4bvYm2rKMC14qrzMEMN0IRJUxrNborIDytYytSFSiRKmwvk6aKjWARWQ3ngSFpmTOFmGlSMobnaDaTUjvP34eMoauK9cAYZtHiA7+xjMa65H36HG5rxPj+Zj08B0eFrSuANidQnzcqXvjdGz7LFy3HB4WuiGTex1YfNrmTcw9KUSHmQbxkky3mrRg9mLTSbvYw8uXU5VHqr/Yl4Yk/XCwGPRhrGg/DBSBmjv7i0O4ssl6ow1MpN5fJVue+HIDizjIFwDzt17HHrbwnhHVt6aMZqlmquBIGwzr9YbqmzvhtMK4yTt/DHR9BnC0Oe/65FiBjGVwtoPiJWbIZfXbxw/BFwtv4Yx517SKkj8tVn+jv52Van4E4slbgu3f7bYktVvz0+eDkzrM9aHP9gHiFtvp+nkf5VUUow+R02w2njOkpHBSORZFXqIOGZKlT3uUbev/A4/S3r8u7G54jcmV5Z83K9cESp73pdV/Crwa4nVd+6rmFAlyqenR+n5FenMwsnGou2FNcsNYxnGiMTa4uCuT+Ai1+53fKcquOYAA7cxIV6OZ33lfscP1/GmIYAZ7u8QkROtZVDzXdWsoT9IROUdxMfNT/UxclrUhZYiaxlBdA+GYW9bCIe86GlGoUEd4XF8wu+5/B+yOZ81ychSzW6LM8yBp1dbxDQhLd3JwNMb0gQ4damwpu/xsGpEahFZyIIQAa+bt8Ct7b9iDndmO8J2IbN9/oiy9Ck6KqD+ZepmUYlIzI/Dd5nUshH/3N3ETvHcEanP9/MdBTF19lr21mpeIf+BYuKxm2qKpaRMpel3VvmL8PHnveG3vG9XTSuDSc0JYTH0ASy0qqqDlHkxgD8VnG3aUictupedkCHD7y5N6tKhR7VE/VMbQhbh7uJEeDyDH83+qrnoejz+oRUKphHF642tQFmLjSmcKn16T+KLlHPhc5BfwatNKvss7j06WbCFpyRlNp1UAD1+mHKbA/fzSfP4YIUIXUWRZCe0QW/Q0e7udJWUL+jk03v4sJ5La+JCd9NQDRm5f6cOO2Zn48SXELo/mthiWW2x4frcHrXHXkIjXlfrVfEFyRy+yaup+KtmLnrF8N1tzsWdanjy8+FBF8u6rcf/9OXfc2ZQ3WPvrCkilm+sf7bs8ok5Peb8YnfrX75zf2g47L1q174dSaq+OebD74xEmgSsq8NR8EhJI0KTcI/C24fze0llKPOiRqYbXKo1j42XsqoWYldpsVYdwp+jWrUO61SynRdZVmAdzytLL6djfHouCTbGKGlJOClJnhOESRrFlLQE3L0yB7F3QWV3jgQqWgISnaRVIdM9nAXFIvsX+JQlzSloT3pZb9xOykhucmnp2hJ/ewPbuF8C04Zw5WLUfjB5zeGdMZbt7YnV9DFnsHUGey1q4H//ulqQ3U2vrOv/VlHMvWwdr6tL5ck2pQ6YMkleH6F0Brcq54LX3R0vv8EqVm9eZh599ZZziZME6msmtsjh+tXlNgKOK/TjK/7EAYApytr16tLGMCd+5dxBhfqGJ8lU50HJNOkLNIvNPLrXrgafI/XS2CrJqsLxfIh0Nrjfpp2g5LUgwwFIz6i1reBx08976h+meg1YN6+RE24TxhZ5FZdIkfBWkuLemXIOI7Umz5FQMrn5rfn511cRr1ucRQ9nVjEV8bKT0ZmREyJnglwuRrT3rmxlXLOQNam1w47rpbbQq/SJfJieG4Nz+fpaKRLbKNvZF4tdD94ehoMxA5QZsKGJPoWkn5VEkmf3DlnhPaErNIC1ySBpiBbyzoIB8SrE/Iu+hzjMlgcFkUqNMjpbfCPzf3TfO7tKegqNzfYx1zGisPyzOCIo68Yqbvs1qxTDgjhoIIYQDsXmRK7ZiirAnjquZ63HPNOEjM0nY7B3/5F2z0MbpXbhIyEcZa8tFBOunUApf28uhJIScOVO3Ya4uQzhfClJPl/+WMRv6DeQ82H7obki6VlQQsd55XMPUEt4LzNcrZZBeSZ3RTXS5n6/6t6YhnzlRhmgaf9KOV3crb7E0MX9DfQKrcpRh0W5z1dtNpsf9uBbR/kC8a6wGLEIJNQbWcr2YG1sCqXEQ2jIAueJexz/GwXgea0/2THP2zHtnnNSbXsrF4Ze6vr2nSjnuv/iJX26M1LngQMjKENxq+PWQWpIN36tpSDx30eJfjMgqnTyhHH2yaGJdZ/ei5p79icE0aAuWITxh4rMu+xZUhvY2vlk+zi2LoFizTKdM8Au6nFhPffqtqUVElJFIPFjfyERV1moN3WpWoHggipHoHcPvwiZJ3wPJAm0Vym6tAFRaMSifFbWjaEbkY1KOn9jhn3nY6gZpw8gQ9JfLM4wqBpu8GtyNplkWhnwfpTPfCfexk38s4o2vom//Dfxz4HsfI37S3qft9w18aur1LRS4bJV0b8g5lNZw4abdIi9ka4NbUIpmjTu9gZvvmb2xZl3NIFDH8Vp1TLTyZvMX2C5p3A1CNvGLiUcDTjY53Aqv8cxK8S+XgBMeVkr8JKSfD4UWpMRXiYpG74PfdV8El5b3RATM8akUWkA66innGhcBmLwGonRiq2+Dl9TxW3wWJHmCZmHVw36WvPqt1K+9g5AhwSe3TWud1zaataISKJah5CQ/3d+Qlf887qQMjp9gGetIdGr84oAJUqGOKRBbp0PENUTUG3VXAvto8XKWUaTBblWFrwGLymrZRwkuOt+lAVTMvRcoQCKpJVjs8R6p0uhJk8451aEkMOYN6KDPH5arTBK+b9HHpxrFl5B5S27rHMhAFyvahKDj5FgMu7Ru/XMdlsTadwaJKj5/2B883/w2JpTDjbxjc4G3zVGQ6d/hwHMrkXoWGu+5D4CrUvpY1BtxBJMltT+KzrVhjqAhRm1oSSjK7cwEhPRi39uV8UIYHc5t7Y9gnVvxKbcu+4J1DeaIESNyMLSKKxWJWtV2iCEHcgtTaDb4JbawNPyDkgfJOTNISIsM1E001+js8TVm4gohn0ZunLLEY2naVlpeeDdkC+545zwpHjw+wJ0WrnMJUJvIRawce4ziy+Lc9DDqf1jjJEteEoY4ffOtkADayXG7a55pndcbA+TN0f5bAWrDRUIYyepXI46VkSuuKGEMA7BsASuOFk7wjXtmMrkEBLRzitxkwisw0Z1GGu8me2Quoswx+cyEu0/O2M866J579XHxqKEmrN955/ov4vkbxIVLCIe+ZG5EbNpTmOiwGMtZGTqJqGf+IVpKa1A5T0WJZs96pMYE5UgCco0jy1CP8EC2W/j4TWIq8Wf70IcelCB/nfHlz8fLDZWJrhh/2Ej1kqE2wKUhkbsEmXZ4VkS09pD6QHn6nNZEHqYFVvRrFuxc3yJpILCmdVMPTahHKWbCLYFeR+OefaXX7WCyV0JiVXoQ1QUUbY8q/HqE5+lvXV6vwB8HWHoPvKra9qfnT95OD9qIfWzcmYD0J2VFRNFuPcV6SxacxGd4RyrigqaP7DyVH41lXmaFOUJBw5hNbE+ae4nJTxR0iaJK+ViXTQ0r9JDzuxJ5f4QjqB8637NWlBf3CjJQJkkhu+gGme1WhDeEqQhhxp+leVKQYHYoWzH4R+hd97cZNhns8FIl5xYwaC0IEJcNDiDbf7w9M90vvnxaunQRVsJb22bTH31DFe0Pn5Sby6mxwjUXjTC7XUjx7sWS9BNz95EpHM155TCW7bTbGhuBjUKb5HWC94kjRn58IY5j8YaJH6pHjxpBgfbvsJ+3KC3nLATHoyTCrhIxNmcXQxu3B1Lz8J8ttKs3kISM06n8lpVv6PHe1SDJ+S5pMoM/iC5lL6ue4Jigf3pFIm5Z0Dx3XrU4PBibymrcAO3wzoJ+jFDJVJJluWjzzfMcgEzBy1zA2dHiPa0DYph97P+PtojLx2w4uuTI3fasiFjBlFo3prbjQ/xlmZgCS7UvDDmHKuo4PvurLHqiYkeHfE6prbMjFUtEPXsHd0HkKZqjuN1OTY4cVcBPet7w4yQukhy6m5NtUIom5jTuJHDm2C5PpKpRTHw9lIuyteW4IRDAHrT5VjzlpPOkbbYLTv8eDNuKkSRF25VRwHheXMRkZuwSfGbnG2ix2ipFdcYRVTBeXMuKWqfVyzEtDSeOoCaU4EU4llbwIaognkZMzLTUWZRNN5cGYvm1nmrZqMMFhSlw98tjAcEnVTfP5r4qWTQClFSKILl5X+2ax1mwQXC5zXl21pNC4iCv8iZniiCaAwl7dA+AdTWboNs4kCB8CoF88lFEkZeWx8JqFXE4yfHgLMWRlufuZaTHqE4jkowMrYR+fqkYNH6g6v8Y0j2YfV2wUa0UbwNaY75iT3nRX4g6Ybkk2WthJ+MpmZG1epVqURKK8lLZZSf4b5icCWUmDLN5DCKolCKYq1xi4hh8ILOAkxrr1bNN0FyHGNTd9jZENGGuJQMaePN0Q4HVuCxl7w99OBuV3J7G+O9LzsH5dCYTcl6/5kDNnOT9N1nTn25WVRfWcv8tLibuA/9nzgTZEEpqqam+H62GlOPg8l1CDmsp3t2lgxHT62g454zLGKNGhyQMjQs27kANQnKqYGvr9vwmarkS+Y/in0D/dooWt+zQGHFufG/t+uPiOjdNW4i9M0jmiSdyKPG+xmuedzWGBpmIbeE9Tx/k/VFYjO37Py9zhPAvKwtIUoN1qheaRa6+lGSGaKZ48pJijLWVz74xyoqprpr8lot9XtdYgvWV5sb3mTmrUqLDStxKInKoQIXupG9nDY4HnI7sYPryQhBOjsq9KuErdib28MOvv5mjFXxDxtumJg4TG6omAHk/YF6dUfMxT0RD3CsKX/2SS+4PDFW0Jj49zSikYb5HDsVzuinLYX4PuhT7/OfKJ+gJhHseNgL40nbPk/Q2W0UHLID6XkRdPSSys0roBXDjxAx5iwlL+C4RRjZLXOLAyjrWUG+8krGjSyaswp4tu2I8SvMaafUde7RQOpSXSfsgafC6UeH/qmB6lcSDBkOAbtj8n6yQm/e3D/gOnHMsIswvd/ZotvIERxj3/wmXoqz14TK1WP0LyaCUetkZgH75i2sa27KBmR6WV9Q4i1/FiMH0Wk/tGYscG6d+4rvZWuckrmbTdh2JKyhZH2yMeiEy0KI3cK5f+pBwkG6cv2eU5a2UqTiAy3QEoMW2O/BGwde7TvTfLUfzAiPuJ/zw2TugvIFV9S+itgVs5yUmQJwzjIM5XqCVDjtZ63iKIp6iKe0dSX/coEqTIqDqJd+MJJybPXly8SI8taDMHekGt1GtSPZ12htzJ3msZlb0N8bE4xQbmv4cfQT+6bKfUswqqaxT2+fgREsqd7vK9Gs2scotAvqywTZPSqrEmR8QS3tbvzYQCywtIl9CR/rS+2qItpAhEVTdaIAd2/pqKZjFlpI+sgwckqMyCgxIZMTLMs/1+MI/g+spYlaPzcWOQ92Do/Vws0YWdBAFpjrEUF2rGBD+F9z036xrGvPFcHPG3I/17Q8FYCjAWSsBRlqxhh/RpoK9W+9Vx6LxcurMqdj0wOnE9PdBn15B975rYKF/vDJ2hbA3GUpOplR/VuLUqaKjcIqL5qJmlThDH/oxovJvviCBLGKabahO4bcEhMrY7IGPygP6L4+5w/QvSGIoSEUxfkRfeWcPT5utD6Df3TfjDDTlw/d8S/u0Bp7Kwi3H92WQIIcw186B7dCVy3YgWcdyZ3XeQOwTx3BSyoQS10z1Blld1uXW756n4myLDuGlcEfXnEbFMk6kFgSk7V/Cj/4oW3GH4R1uMfV+chE3Ioc4hj8kq0RCxbtXTldaxCH89eQSl18o2gWIP6clUM3epBJQiShkBRVzLj34lnUq9tsHx5UaIKVeiWntQmXfnuC9DISF655A93+IQEYO3cb7jabwWiMmMFsDPmQKWRSKGWG5hEUZ9xA0RQvpeUzJmlPPjYCkyxjBdQLZVSrFY5qmP3SSZqHxpHQuUv6JWa0sNtMSuQJM5nQHsYh1Dtxr8Ys/Bd8YQEPTPsaO7dFdhkRS/gwoVCWjnxsvMkjHSSiFJ0wQtKA23EHWyMyt2ZFPPGXKYjZ6TJ4mt7SXHvtcOtvu23OKanprNj6MHxqByVAG2LD6NQO4TJ5E4Y0llVyq9JGEyt3asey7ZtNvJI6WcfpCuaeNjTxH21Rl58ALpbNSpvlU9nZpv3E7IJeZFtzo8aYdRGv71Wx397V2wODluwcru3qhqghJ7GFizr+WdHlXe0alaLfF6QcMzr/RBU9nZ20nxkUvEm+P8AcuAlg7SxzcC5DWvxrZ3TrvD9a5AtD6hP+3WY9H7bcYsX241KTIoyRTuQxEE5TQlHuYxLGPPsGwZdVp+fLpgq+2Ml63Qaim+fL8SOvKXdOZV0G3I98L1kwN7kohgY3kYWW3OLceAUpDBkcxmBab57NiUoHtlrBz2D05qN3RGBzWN5j255eenxLgJbkLxJhY3JCMQHGNCFuD+52P3bnHFHORmKzGjZ+SZctwr55Kqrl89u0xp5Hu9RP8R5AanFQX9Ucxe9Y8AVE8ziEq/wv1VWmVo08xiRGaHoS+2N+7E/dVInae6I55HDZZqmjVYPfYGcGJmgSRWmbd/g3YGqAZ2YOtjTcOmtFQFiNdXqo34BUHSPvZFqK4w2ifDTexenCW1yBbVZBQ72Ti2jav7L9SjmMTm2jJXhnfBiV2kZJUFf1xuBT/wRHws9xSIiAB63GqGNfACru9Ov/fUQm5jrW9WTsvpAaU0XOdv7xqkxLTErDSdqrkvdafYMadxwfwKhJjkYQPUOmS+hc4N8h+rvtlA4U/XaI23iB/mSrzB7w08PfN0wVe+t03MTVs3npZfbaNTfl7bUou1oJWgx+vR/A2/oKpNUire7VFsXfP8lRjMMtMK1k/PzuWp2GDiZ0JIV3wkLbX1nmMymBDQatjYWvNQll2VAn1HlKVQqwo40at+lL9/s08bdXLqSpe5OVKEkCICEhPYu0XqX6Lk0Fc5Rx1CWTImcsMjOpVS0JQ3T/zaVcoYFuT1HTrZt2tGXjCsebXN1T1x5lMoLJaIbyO9r0I5kmO1yXfH9PbC6pojEv1e8+taca9XzzZ9RkgTTFGXvKXn/52hszRtZwSUaNiaJVFOccDoyqETLncGjtvzm3tzklANj5Gzby7zMNT59/Mfn1h1rFZSyq75O0rjAWCLFGZQHtaLF7dFTcAv7qgEYuaYEb+tINzLMNRvwwnKMCVm0d8hoCVGNEEQINgxitCcGTQ3DxzNPY/I1Mg1fOWOKVDdKyTG4mvmIKuMTU06pYjZSD56J72BJ8wJO5ygOmFfJvJfyrFpbCbNJxosf3mYQoe2YjmlDTWZZZMasSVcq2j00ekr8uxzeO4woxI9Y1IcIQQ7zmQSIVuHKA2pi0mBxMRailWUxMMx9QCITtxQwoyomRSk7kFOL4CzRKsCO70P2waTz/TzTjpkfB4wD8pBX1WjfTlzvcNjDjtmImBDUsIDAYi6FCVSu0Uzt1NF7VoBpuP5Ew4F5kopqTjzskQ70wSZM8HdUJupdIcpP5QZAAIA/rer0+qdXkUrSUXFGuocConlLb8y9DuuIB1KcBW53CgbARByopiwY1Ak37Wk0fNJr7r4bSs9R3b6nfeNi1R+Scgn7hPStKM/9otXjQShJDhzmL6KxoqzYmNpuKmtocNznMTe64BZv0I85uUgZa6Qd4DxQEgcNVjdBY6yZ9znrX6gwyJrrz6VgsxsR+TpFZWTl7M8PZ0sfJBdxzthKkNCETZyk4d/uDE7T+ZzR887VIE6xSYqUdmep+qbtnlI2c5LHLvzStQN814KMjWJjEAi3J9v8XApsi0WK6mpVsEm8Ox53f0UhIwdCv3c0IfTeh3IQWrs1YW0yZ/RXKY+IR5LQ8OLSE+DEJdLGs3+Tf2bDaH+DTNvw+DrcqXeEjF7LEuukV6j2/KJ60//xDdpf7Jy+rV6q3twOcGeg4cxk8BIgJxOqEOUOQ+1uEMXqWrV5qL7YX2kFOO1IHG8+NHTC2+m5zzjUl7L081n0EgKbiWx3gfE4zFa9/FwjT3vV4ACN3uvI6hlED3pll4epvH4hfkr38zZ1c7sg3xROWu5Qnn/rH3zspbyjKtZVU8Ez8aWbxlUfxijtO+rncM0vfC4LtZFkGhH5/KIllF8TY0Zd/m6IqG45PLlRum7IPtBszZlKN8g8wQ28hq43qTQBU6kqxSoM0mk/OOPzDFaSGkBi1cosTxvzq1VQld7WjA6IBaXWwBEkWYBDBeAGSRiojLZGKCLBZvw8VpU+1oU2XffXxAtuYfk3GiNN2VWEp7YoOpVCRX0mGnluZSZUlcU7CvCyA7pk6Sqw0K1YTA3xvlQem4YJJIFgT95d+HNeG1se3zcr3e3CCSwLO0543St0Vf0bbvyCTBA9GF0GJ8qnoeiXzfUS/+8Q61IpN0IS9eAx14zdREerBHdfHA52JMWRZBgLkuAoTKGMHooUYTLPH2SLJKzrKx5Z0oqLfi7mZtcWL81YDZbtpAlrdNpM0E2h6ja1RE0QXeNg62L2MVORLNLz/1q2Yb5rMOjllubjIoeYzZo9rZHleva5iHsXOn9fsxXiSqZjNukSZA8wpDKDheA9FWLC5WC9oeTYrbw1zV4g21cvJA4bhYRxJznjxVSFCbMQhFxsCe29GFGw7tx43Ql/pp+jmdyXXy573j/jb32is28kwqPPzfXnfNMGpMkelQ71mc7jP3tX2+cyleJs0pnyf9vvmBcNdy0tMWVlPvxcmC0EZcSfLe9sS0vQ+28A33UwzE9N6I443SaRjzJu/pZ1/zPlT0ZfP4EMH4kDnNexPW9I02CTKIAWIw+wliuTpi/Kj9NNnGSwjKTFnkWW7Jhgw2/iwe+bGiT/iAXFVW4pVaqxWjTX+oMvxU/ycsomOaeerV6NUGQp7r3UQvuuf+0lU9Z5ax9E/OzwbgdtPP8Hvyo7xJgAcTV1HPB3CqqwiHcUVffDxMdpf9Jufq1aNg0X3RDZ25DYQjvXEGZMZWY5WfameGFSGKcpOB5BlPRYeMF3nTJzoZ2sgEjihAZqJOA0tzQbV/E4rIq1sS4P+UCoYa0PMQnsRI9c0tGNXLddAJ0iCNlBDgYBOjaLVkzidHE7DVXf4/Pek7TOcys9BQ4ZXR2j8VwHoYSabQjYMcSK9XxhmXJHWtm0qsqjbxxBz2tXlGDcLwLzqvfz+J/rO0F55L0jpPZpmm6i2qEZj4X0Y3jaySANPoPYjcZnfzwIRpbe/guFBa3hJZ7rWi+drOXRiNEolTjpgE0H+fiSK8CWEjEMsI9Ru61Yc4W703pawTauTdXxx3VVP6AeA0LoDihUIGlJlXUok+2R05Ogst1/WZ34o6DYUcSvj+ekTFlxYsTAC+Hy7J54UASG0wpLmhtIEqk9b8tttkf1l2vDubdJlh42Yk0XgTaHxcnUJsHSPB7q+Bu93ggrrydiwppgokiipKUet/jwZ4bAP2moCV0ToKTraZhr/QTA+iqo0dUv2r/nFsV2md5wTzomfaO8zAILLDa2HGDMijkcM9Z8O69bh2qQ+6HNhV2jXhxLRTTrClYciF3EtvPVMkPwgd02+sfnQiLivExbKBvBRQvb5ASLMtPHsAMOXMbcJ4PjVdYgmZ9Me2Tr3/f2NRgUvI6wrcC6RQIm0tPVjyc0+5RzGUZgUolPXKC1f7E3yIaXGmaHPQgeLKIV3//SRbUd0E8lZysPhvMFp9vfn+befS2dO+/AS7k1rJjeff69tW4u15vv50h6XzMIUB0VGtmeUvSnRV4zFbuzWGBtxgZHiVmO5u7FRwdIB5cMkLmB80AfhCt75hMJAtOvmXX6FvLwWAWuY2HyzKA9GoM5lmcEZjA4yg6B222A2GfNYT6SNzgm06IZ/IB3JiHpdVsHxrNd0Oy0rWRNsiJdPwsWid/1vOTS+rpqQx55v3WTf+0Ny3KOv8gz5su0bqnIZxoEbVYNfkl0EFm3p/CyFsYsJ9hRywvnKpdy2/i0zzh8NlhadUCngnryorSfGWssDCEl54iq3sm/c+Ojc6BKmf1BXUA2RkP4PN692VV7/dWfQA2nXH2q7B3KbDFgAptkoAoWWiVjQsE8200iAJIOQ9Fhx6JhPlERjIl1aVAuXsaFQwBk9c694jl/8gzphe1mbZhG2c3z+HaaPrd3AcRUU/X9oQbT6bqsTh30SJRLm7a+DrPhpVIYk3B1rnu19eR/Uz1xqFriwS4yTz4WVAg/2iIZSAy9CIlx9lnkgQhXNT2wW8MU1vKwKlvAFKLod+Xlz2awXHcs6KdwE6zxgrvd6ImH0GhljjvvGvcd5Q370rDNLGLsxV8tm8c2+U4Wzh+9ixAU3cU9KsPgkxfFItPByG3s8MC4aD67Oyz3MjWsKTjTRftnz/eJinrK8LfSXKUUCKIpnEw5ZEBwUacbQTPXpZY+GdqI+QHfbByuGkve7hrgv17I0R89lRelltkRopVZB6pctJajMwiDn1b7HcA9jNnNZBHYY4w5TSSEARcQu0mM99JIPhfUiMzZD9e7De62A73El81bxCv+EKyxlBsnaoBg9Lh2J89oFsMg1IhrxjQhFZCHHaZCZAHwZCiJrHAXxLGtsyRxzLaY/IWCJgiIRNHuhI6Cn1/2G8vaygg1C7Jk/qqz4kmpqFv8NRh3h91NRL2foRIK0EitTEmy9i3mfqY8ox0OKJbx3fJdwmHUGEyhhAm4sIY5iZ7ATrC0tT/lDIHqIsWe4o83CBRe3J9vdvvm7f2/2/Z5BlCGPwCSynY8jB1U5miwzmY9h/Q5EN7yQXjDOJH0hf/j6kQt3x9sqtyYwttmvmzqag8fdxbfq0l8HZDHzvgUGSocNaQw6pDPYUMmsP8VnJjmGnbiXPXBqqsYMBHECSGt1fTOm2RzJj2pnLdOArViBFD3wU0Z1ODl5Zn3xrsF4cex8IWwkmLjDl08Y4QZu8O4t4/UGx+76Lg/0ff0exTV5s1AyxrktupmtvY6yJymTqdDd5Rf3hJcCNajX0D4ua5l8CtKueBQRuU1GZDqsM9vwTUhnVrM2s+3Bz/737k458Q7P+GJ7Fex1gUc6J7CXtio4cjMFwUwljKBt7oUcN4rny+PTjb1GuSOuZTQtJAecnX9PPfZX+qQdsycda0BD41M2ZkpbJnt5n410mKg31/Y+Khg7CfmaSih8zL+/1PP0wD3zTZZEiTlXPTH3mTuoays1EjCgiWP+fpg8aYx07xteLHyLhQ6S/bTDW28a4ASPgQ7ub7EX7QIf23BcKbNh4NsnfpONh8j2tsO1mN+xFWNGSPiGQ4iBMKyN3Wjg2W7JetMrsfL1C67ep4xfNpZU35oE19rZCKWClWClFycziJmP8+NEMIPEXpq308vwAlhtLSFKLdTmql6tyx/wwt2fBV6Y2BH5TUeMLauDEzdlG9lEnGMuz4cph7oemhgRrNcBiMF4G6QXhEz8FP2GbXDS9xkpE8Wf+mtdoQ21rTCieLWkfVx5qevySdTZzZ88pEj7wHtIUbF402Ht0LHxnwrp2xaG7P9Bc7i2x19CqTeXBv7z3joGksM9YbWduewD97vis8RRA24+QE4N3hn40vcljPb6iCf5R2xw0QCjfIU1ppD6VZCHWp01x3xtjbCDCY5GZw4yF7QTwml/m7G/XGI6Koa0ln2/xvHHY4YTeJ1bQ+pGQEBXNhPapLhTNZsaOjxtd0ZjEGvhgDzvJnILNqEwg2DY14h3A8610IoYrQhq2Altd2W/HemxI4QrK3ZNioA7uNItmp7wiphP+e+B0se3yYZKSKu0ciC6Rl3zGZjVPkJk8nEUept0nDam93DbuN2wTw/TM//5vee0fReO7ursuZfuSaWv3e+RA0QOKtkv9/5DSiWrr8CFh+xVLB2zKeyv//ZQKQRe7Xt3iYrV20juPaEKFKNKzN/67LOQa08k9JCTHKkf05r+Ybj3pjMqSyg+fqBG4z+j1oDcp+NapHL4Kiagh3CsYNu/RmmLpYcZuFE5k30DoqJ0mUOQ7+5wtGyw2L2dNoIR7XTAXp/RA92uMWMTW3iQR3kggC3pzAZ+l78TIK1LXN7oQop8BQpyNSFfbn7FAxxxRf6cIOsckSvnALC1qg76apLj72PJq3JSM7Wl0v96qjaofe+XzhyqPfOerORv8t8DdLcu5fD8cRLlJaSpTKSkTxKmYeJegHnWqafBzcyf4uHZ2cCTl93uU53mmzSjsHvLJE90y+Jd0HbErMODCXGSQ56DHI1AhLaqVsJTEkDZbvsvXLgVHmbsQPGQmXRrUMuMEu3K85RqqT04O0q9dXTyKhU1nC6jN3Mwg7h2TEswPbmJ6YIPtBWN32UJH0GymyscG8zrmLpcHV23KoiHi+mACffDvUBcOpXaYEmDsgZaopQ50qX3gbBTcPUc42zmU8Rd9kCXHSgmvHCGshlr9mMKutwraNlcAmsc39L8Joh5dn7SsnnIH/q2fGgIn31fmfvg3O2KazQbfMPkvnY6PAG+5c+Cz3JhgD9Cs0drV5VstqltOfZjvz8Dp1Fdz0ifDgbc+zb5ZJcsw6QOqTY0oE3+Cr1y84kqmBq1pVI7ySVRYN3pStf/a3gdulF0agUjXfekd/J8wNR6BtxB9KpH9ABRfcxpf4NvdcNuUbvutjsps9JjtImXEGuEdTi2FGbSnszQlMrhZZxh9qB+8TZevSiXBlDWZFlGh78w1Ky6Hq4InG8jZTQWaeF4Jy1dt3saT8plkHULtISx6bwASlSj/R6QXhLeYKNO/+kCiwCtS60d+u21wHakkN2wO+Okri1/Uyym+LI2hc+qUiVtwb2IkeUqpIhR1s+k23V5k2FDo78vmflV+q0h1JwrPI7217v4+i4q3yWXxUizLFgCsUMptstOo13WdNE7PNonb4vehsnOu+tVz7Samr1XW7tp8bovr98ry+eMvZ0fWZllykDLeo3hkvQZhWZs0N6AWv2CsF2m7veJaDu4Edtp5aPQ0nGXmIi+tDIzhApYiw7hbYArRi9z5AX3nx2eVLJg0RhJE2SlUKWdMEF5dQvoAGMQ7+WQbhuSCH7rv8ki6R/z4HH7LUgplFE5yt3NsPcLewmMXHWoIPiZz97HnTKpg7xr/z7gAZdtoYagK6ubMY+gnKQm18qr39bRZKfpbG5l6RzEpmZ6qBNg9WMbhqjSt5wfp8nn65NFeUp8/9J/yimud3aJBfucrPLIZEbUDTZSC90b+u2lOQzKSpYRwT2PZxJG1XNmDNyKg3x+D98zmbrtQbBnQqKrnEt30Dsk3fmKgH+IKyUanL+S1/XaQnKy5keqa45PJklCATpmNbvKGrVnM/h2MvVyslyp3FM+cHZ8HWYSyvZim6agy5oB3QRy6Xez4ZZ60/Vw+utH8r6nTxVbc1/3pV2x5Xa67Tpz3l6x0oPulXdTBdcWAltSW9mF6ALoO7Lx8B9kE3YjLn7FpiZyYwzOMS7xqkm8nR2wwob7HwGqLT3hA7akitOsHgjG/0Znzh6Q5MCMq4ZlZT07ZhSPR5cdfBgg/ph+yi3F3ky3Z21ccpBWiD0p+GdZpLkHWZyHhCahs4soy+/E5QsJPUKOsFn1RgGv61ie5u+DF2a1+tk5rU3gGuVapPCD6g+bKU55fkPZ8uQ4DwYzN83YILVO80TzjZS6gzuLIOc3oAj90GE5UbPRD267KcXPLmSQ79DYi+7PcdRJwckFqvXM/iH81dkuhzz2q+E+qJgzOFUT5tlVCof9boMbwNqHyGzFifR6+OkqsDBMce9yh1DgPZvtX349/FgVZauuBOCvXKgnChNO7Zp09jNUfn7qY1++znv2Ovtvt2/iVPP2W26uV00n0ypzzQCoKpYNqQ46k1R00KQ5KJDFTbZfXUbbwSxclyVjd0jsYc4mocwH6P3kdsyq74hlOi2TQBI0Y4zbnIE1mo6ReGEJ5jYJRjbDl1SVw+lsujJFaOlWPoptrntrycp+NSfYwagMOW/BXpRfsm5ziTyulDE4NS2u4hPixHcdeSTJ0gPJGWhczSn/n2TGyxbLHprl4XBNGc5eFD4jySmSd/+1mmOmR/3UqHb/n7OmY8+EtnuBnzqlxdX4v1uOf1Wt7fZtwIjcC7WE0qwx8BdkmZ1fwiVvg9ezBOWfOEZ532EslTf/PQywsp4Ejybc4Cbz1EG7LfytMYcDHW53VhQvzxEe3aeIhxWixIPDq2Pv5jniV8932MsLd7Ex2IlfaOf4QZeA5GuROsehZqSLnVTNurcofcBBO3nz++flPc8qJWKNT2Q83qXKgayoml1pSNO6yiEhqyo3UQRJkkOj9nPMklZsxxvM0k17azvjvv9uF1C66l+1Kvpq6sQx+ulrhSbJrVF2QW18cRbz0oeMaOBig5tO/3R+XdrSsooaB9r1TUx3l5yOdsy4EdY3B014ak40uKEvGXEssOSKulLnDW1gEBkfm/691SxU0wjGOeMObdUwe80hiiriMLTbOl/jXYx23ctuPaXENL9GirbOLGumsfVB+nis8yGloTM9u2S3uzNftWZ2qeO9DRpH8Fys0bIYbTQv5jaqhm+zRAyC7iELnT8/NfLKqrKCiDEUM4gxC1I/CzsnH3FUraGAYAGZaCIk6cOSa11yClEI601ICVFSOGVx0R3HgWwX3RjHrTK0IMaQG8yH6EPpg+geDfccwz3OnaQI0KzZ8ilP/HJ3mkTsEw+6LoBgSD89aM1uyObVfKzFp8tyie8GNlvzq/3xY5E9bmmLBcKXhIGv7htrRDN74JU/gVi1y+y+RUVLV6XwDgpJ/BwWN/ZEqWDUw1z+wrAsOL4aezw+7MntBrQX90n/ErH2ktj27rmnw8F3oOkEpgyVfFfdNObbzLw0UfFHTMFkNNiffnQEyH3S862m1lxmJJwmc6zwdR7HFU6tufSBTPGYuBrCDfyrmADGytg7xYbHkzPIa1MudQMLS5vuVY38GMJISUiiLDpTSCTZHdaKvc2cR0axOmvxtejcRzcSfZtLsOCScIJmLkFjbDVDu+xyWNL04wsF9nFlQ1NxyE6x2HnuGz4F7Itz5f++dIAAdr3xONIyrKKYQziMCHyDRhpWYcXO6oMJh4z60TpbPwaRdReebjdj3KYQFk5PiSkAett0cHwKVXFVZoPoBhqTaBX3SHvuJ8Q3pKxa/mrM7UGCOI575qT9lUS96Bn5o2/QA/XNrH4ren4OPXDmwypNN+4uHAxJJzAEwBe+xdIRIOPesifz2/iHHBwj8pnrcUK8cAa0MuaNC2KNq9OS6Nk6JfS+rPyyj7AFTNphukIara+hDvSDeZnjQywXo6tOz6v/3i1vi8Lt7XBvLbkmOT3c2vcguknqWDygcrP0lb6XtLZtmrZgoFpmK11JbQxcJiyTt+AtJ8kaL0KhLdu35BBr6Bkrv7tUtJ9NccgTHDHrSHGzRu4bghrnjOjxXzvq9hDvL4HbM3NGFHmC8+ro9NJd+E4PDxcdOsBlozY0hN6AVTATtcDCqn6iAe21ChHCQwIitMJuLY6nnYPcoIqx0ZbNC99c2FU6tNwV3/v+xLJtCC5sMOfBvOA4SJWbXorIWmJTOdOn5Zr9BWzJ1vh+4Tv6R6QZhQ74eahxibcHJ17EYZt79iGoLp/2rcqV3InEL4KRSHmeiGwdRTWiFyedutNQdawfJiF70szcPuOJ4t93rHdbH9CGJRnu2rZuBLxOGq3btW2hwFXt4DX0tqtHCUI8KIRgKEESPugTfNB7zTQwYUOZ3Z+La4IXBgZ6/lGvM+K6SgeQqBunN90iFouoiNvhCyCI9Ktm/XA3nZY2LVikLAImHXou4EuopiulPRnk1//eWkO2bF3uFs/MoUS7LbeH3JRooiBS9SUeXJyHdJKbaZ6HUXoOcuysNosifjT80+7UxMJ2yU3S3BryptM2zmZ1YIS8NO58hKhzQoF8vaN5uSncuICfPTMtifLKma/dORdND/ORi4UCMSyLMmXfG4snrQNuAXC7hmRV8alpy+mkn3VZkT+vsM1NwGy+yxRzRrEP3jqRopsps7so4DJrzvwsrBQftsHhWxXp+wD6xtp1t0dnVgCoGwap4FGwEpwwr7DwflbognKdy/6bp97SURvDDJ0YEqhT0Y3cgokuBCpBewqL6VPDFTy7n8LpoFtMJKD9NpifSyvcp8TIRLKnFYWFHkUTZ4LYRUYUR+s4FqA1xD/voNwD0Wmb8Dbb58FwSeA7MsImSPtJSaZVSfO2a+6VgY5+SXGceQWCbUDMvnTqrurjpQUW/nK9VPln+dMQIFuyZbaeAX0Dum8ZKv4pzXpRW+qHfvctciUMeGau6L1gvjRSvM12ufXo48krk/OplbOEY3d2rvtNXrN2jdt/wLG/znladQPGta54reQnvr7Ey9krD4GuFTquc7FGG9Dp49erK8+afYkv6QS9RcVXg2dsF84lPwbNuQTMD7CNX3g55EcDfTd4IKqcsIfDXLeWWTLEx5yXZKCpve6dRErXNTq+4caNwltsa8qJtU6hbd6rOOaLekZ2gcAGcVeYH8NRLS5v0zYmrnMcr6ev2T9d2Gp+KrtxqxV8a7SNsTklnHRtCatu85JqohWs4eI6x3AX4vwWlriMbkDV1zlSwZOPyC1954Xl/kVII4peDjpX/TIwAsp2I8VjUsWvgcKqjwkXU1xMZz3YU0RFTi8mGMojDhEcHzMbgMoDGpB3fUVLZuIwEi3g6w2+e7/SfTUJTy+T0uRwLoACTQN/mcQuK6Lcw8jUysPSUPazIQXjg1LzLLTY5lO4xcnIeOAxaPqu+YLl9CjnX1npCekqB2/msWeDix3OajfYUghTXwmUO0Uic8kQzI3yKdqe48Dr5D8agVVnfxCSEZ8Ayp4ZVp+BmMcndQfFVjPzQQox2qZOaUhpqQgT1a0mUP51FA3/yxvcH1jup6vvHItjPrNrZ0LbY4dy8+YNa6JxdJdZOcA3WdGgJFZ/Vx3Nwnvw0mGPDsdl1hzOZNXOV2HJLS6FLAka6NoFtEL3Zrtl0MqpIOd4muEeF05SBKKpKP2V8pUDAIx1m0lSxvIWfooaAXmcgMclq8nb37/spOqbFn55S4UADJceQ90r+8L9FYC05JXISkPuFMP/boTosHBMVkyKorqqqo20KTFSi4NscDJFVQhjAccwtd5TtHmNl4f4i/hGWyDzf4I672gjpU5jlKUWxHAqC3YgYio0Z/kYACCLLnP+vCt62/eH8+vHQ/9AjiUvbLajFPcHSwn/yr3ocSklg34j4hzR0L75Ljf6RBbjxZlliPKXJ+0pCQdqhsLc9RS0OXUnPjQeDq1RPTBJtXzuM81N1u9L+WpemNZpKefrK6gHw28+S2G+t6oUmzq/1G5o5BVRvVXvs2exRYlp1KIj7xWrj/+IQ1yrLjreAKY96Z7VjAKySxjIv8NxLjyN3KU6VaS8mhtPerPsrWiK1LAtjrayBA1FIPb74FJCnXrWnEV3ngznfPSpaLbaVihA9gHhSEA+/36NIQJn9QmnYzm63L4cW471jN4uLm++nUmroyRdCPXMOc7g5RnO8gIfrybX3UHl5Fn+YGhcPQb7qSCGLK10qPh9qLFMQzC67KQ5o0xRm72PzfUUiwJn0h3DMUHJ0W8tXSJmDkbb0CP2NjaZLHBJFLOu2FSsyqF0yRxah/hWdlwRckSe63tE7OBf299PL9HJs6KjpW12DD+TKT1HJDOkeFuAoYbUzE+c39deD84rufzNkVfUNU04NuiB2YJBnbfGESEejBXLOtUwPSBz5NJc+XG8jNwtHUnoVlmGLrNiojqxz9jckmz1PxTZXKKFoPo7NV4LCqGX9ATCKI6O27yUKbi+7b5PUXnYS+8mR6Wes+E7FiFqHX2YtSdqsd/7k9A9RtsOmHq1x+DEWJdZauOO23E7jMFwodQj0kzOTfmoH5yFBc6StTJPU/T6Fc1BwHK1Dxw4H6voMPhIA3K7ebhP+MXefBbkc8z/DvwdWHuyartzmjDQtV3Zzu+fWnZArMT4aPjkDPzIYrmNbhuDJvITbR3t3vMlJkT8GrwMss8AJh0WFiBdDLKkWQBlvZpyj5xySKV06wwQ/jkSZQmFc9DyJFMub43K4sqTdLm4Lnyh+10Rf6vMN7PLrxBwK8fQhFM6JqNyJ0zqY2TCTFBegIVhOZpwqzbLoluftbfvqiwIKYqoeJefiRVDWhlcURGurN8H2Zx6MJxqKr/1vHUkuYD4dsuOX8WFDWBg4482iy7OH59UdbxpOlEJ7+RvaJBtSQrhdHTgRYMHF8OXoU9dH76cDqHOzGf3Sg7g4WK+ZKrZsshxAdqYK1QdR+z/wlWLlFiDIZXThLvBVeagAeQi+AOUuYqJH8dVf2v18Ht/hUTBqa+CMU2wW6qOYBuUstGqjQPCPN8/VTpPSftnxKu1G6KVp78GSRlcTRXofE8cEeARDx8Q3hluPyH3YI6X+FpBbKg4XGTaa2CuW+cIIzW2/rvB/hFlwmG0SsybbTKkUkVckamuAseYhj7m4IZ09mtW5+AkOed8KduRC3Oejfkb+cmVj5b7WxfYul1LBNG4xO0D/kjjz7hHoyRXopHAHTclPKWmTsXEopwiw4ezMjzNlGXnMbDUMgb/6KcxHrF9630Jf9IKLvve1H2Xx5QI5xiBde8/684pvIyvDOqsYuS5jfvfy3pPruyW9easOh9in7MI69X1AuMWWx4QgjJtZhfIA9gp3LDhmwE7Ruz1VnLu/Ue62Y5GYxGHXU3NnUMfys9mhnrmSXlAaCphN9ZA5CfB5gGc3Yc7mTebMNHRJCDEVbuEuL3I64BvNRV3+KMVT6u8Vo0Xa9ehaZy8D2GIEZ6mAucDahrDq5XZQgVV0hWQ7VmYfy7soCV1vPCt+WpkoM/CbAkpMgojKGIScwyKPiqRFdlnbpPnBaodJqccyYklB130hcEPUg8rhNemInolgRMYN7uwwhjvNjhfePtTGwALHKn9js5sNU7a1KGVeMYxeQhFfVWC9I1Ud8AQb5NAWFNXXRnJwxq4HwqH+foAFi6CSw+m/jkl6U/NcaO+6+18QAJDgzLOYm3YIo7CqIWtHo5/6HsWZ5ElXOYa02IuMkaLnhYShp2+gtMdQZc0+CjFQ41tRMr1lvdXOGYcycKn3bKBHlzmCbU7BSFCTfchiOC5fzHfCkmPVmutpgIiwCrDSsP227BFfuJPoZQrL3imFy+ThnGlOgIVShInS0JpEKr4KHiTPY5hDMYYYcTO03Tch32/rceJIw6Otl7A8ATA4e6jm1wauMzMF0izBB/ixb5zZSowwRGSzd1cbMq425XTuvC2QNRdEosy0xgOBx2+EnXZejTrDBne0PF7eaSq3BYNfPAYX2kVAK05R1iu1UxYdWWSsJWfteNiAe/2Edq8kzRzddhT0+rPR2nOdcfM7lHhLLiaDh3QSDhjOoD3uVj8Em3Ek/TUJtfaEd1EB+2cxHluXepn9Uj/ZolPOJ1GDX553qTme05eKnTqZjPdJhV2XgTyszVtscCUtRVfiGbqoQSOIsc3K5zZimBomr9y07te8NPESOkKYqKUXWVzGSp6TCK/Gpl5lWZbsdcLIjAJI4wACr1cuIGDUzlZmJfzYRhOaa/YKr/2fZe2ribRkboBgmynm1CY8WKO7za+WJ77yqRd7CPc98qJ+KLBJar9qjqy7kxyAU+/OVge96WzhdlUGb8pMp0rzKLKRAmpXNkx+TJCvEtEhhak+B6hsQBJYIBFZbkUFXGVVf2uonVRSk4K5qsbdDNbQv8evHf3JQdsdj0xT5iJshIR2/JjRwbKUOovDh8il5o/1lLV/mKL9jzJCvJtdVHP/eimY+kvegbqdacyv4e8CdGsB7oswc2FjDLeeUyl7yMyz5Ki3nSfK/i3CiWjvHZFDmC8uAQQiE/4iAI1Q14NDk6gb1OEl+IfJlofhYYA8OqCowZS4hZuwszFWA5CRF38jiM4U+Ex2WwYusNyq1IIpM+cVrOXvS1fo1gB83aNzAZK2mcn0czZ522lLpOm7bud0JO5d/LT1x858LNqyoMpQnY7C/ehZCEjFs5IZ79g1fxk++rfJJLPYd+Z+UFA21HK2dxHt8HwSVKu243cir5Btd5vqYlIaSlidh+bHNCQAZWkmt6SalJ9Tdmy8vQWZNkdBffQ0lKP1h1jKipCh1dz/lTfvF8QFjqlsmCIadztZpEEEpogDbeOho4Juv0xckfgngVVlunSxatl7GslI72qo9+8QnzfaVX2CBDPKqeXyZRd8+YaPBfZBsCd58F0aD0LNDIY/mFzORyrdVaEBoGeFqZVWL9Bc7NaIMxyYhLaOp2OejM8fCTSmam5ZsdKwgaqs5gCfQt6FBLWVjuIFxrNpv5vTw0SVIicY+Hr91Y40yxeP5URkJCM5UEChLKft/6pYnnfL/RX9UIQft/+6EQYKDWDcwK31TeNGX3VcJKc6FEITlYN2FZXeRehRlUYVXsE8unbP4UusYa/WXEmlBp+b3KxfPXt0qBVEjF8Nitms9Trk2/rgYFehLDchvum9nzy9sbDjC5ZIsPGFR5qjlvCSrp4tcMOG2tMF7U1IKbJLHbGpfPgDw7NgWtl6mBzU584SBVZyrIxR7DDoRo7MquDVge0SludrbJWV6u8ddW26mcx65zxH84POXMEiLE+l5/OSM6vCFw2iCEm4p08HkdxoHXkgiaqiolMEsa10yD8FMIlZ+Pmbw6oWMX7658PA6OpAHIohAxZHDR48hTkzqnaXAaJyDyGXnc5HSY+4cMIIXXyjHPLITpTmZXVTFpAM/5Z2c3zA1dI+9d7ZYunbaafTPhV6EwuGnensbwdULkNjCvZW6jSrv1DFc9uh9nyoTukFQSdgETglS30pcT2r97Bdeb/6T9OcwixGPe/hHSfZxAVaHzZS5rXDd4OWzR8lcoa15RfzaPWYS8isO4CWMn5m1dlyDm2xDnYl6PqnwKOzY/HDQbq6Yoc0fy1Ta5/MCuOKrOEIb5syyIZhqlZk7ifVJ8IHRjlDL31gHcWmicsBa9MyBr2KwCArT1wpGW17DB8/BTob3S8eJLzZWJpyNJt/AqCT0DCf/MOLu2/b1U9KHryCFImPUYEvkOjDbd04/yYr/Ej+zLOqJWGx9e0gFOJDwcYxnxAl8HaAhQqy0e/N25egOto+f2Ghp4T1kZMK1rFDiOYaxTsPa4oLDpLDorBTn36FY7cM6vpF3l/xtIlcx5OG4uJQIzz0HkO4j3e0NV4laN2XfI5sVR0Rjf5mX8arhlv2WaoXpnbMDXegph2oLw47HZ0UdzFjr4WvywKE+qsbdP9E0RMscLBlfWhttvr1EHrdK+dJU40R83dmD43XfNmH81jRf40dHq+7/nfEtavvJWJYzve82a99zRXffEK+L6IuRUIYtHbHw+t86HW6paHYIHV/+IWXcFZu5YBbxbtlsjB1eJ9qj82X/mC63EXos1KWj3gUcxhxOWLgwSg2O4jfXFHzECrv3ehYmvFrWsf+DYD6CMDhoOoCV6HzjeAeaM48nJbRsg94HTxzPYydktnYa4kom2YeAUsKEgRAuhMKBOkLQbS2xWugKw2AqZNPs4X8LEGZNYBeK4zm7eKyZDW+wvqjasxpn6FjY6OowRdN9uq0N6NWHOT3B+DMd+fBcIoo54/6fxBH4nk7lz90MYXy3xt84LNjR0GWXIaLM+pgMvkU4mGhrr/d67vjR0QNaZ78ZTkwqb7Bv4Dau+2ntjLWS+kj43BB6jLHSZVzcBp3lzeVdyDYW7u3ofgdKWS1nrsD0GXFnsETQggNDgxheoSPJMT1VE0TmsRoUkDsvedkbwHv3WTP1EMXrYHGNW+RYiALVXUOrcClv96Xt7PNSHXf8aovlDAWNGKLQ/+sfQxrdmIuLa+g8MrWotowulNhdhEkE6/+Izoa0u7SebzDhgk3s0I6jb2+870i2bFX1Jdyi2cAtycuB4HgtW84dZkxsPI4v64bN9kytFTazJtUyVX7FkefV+/iCbOXFuKvxNXc7bBJHO7LXKyn+smt+nl4/c7fepVvPpDeub93CUGoO2wgDfXGDb9UBRzjm6ll2QexItsjG0GAq0xyIhXRnJIHh7SYE8Bfp7fsy222+8/lcgYcTAM+jbSSXywGOO0eTxzJYHzvTy1FOXCHQOKXAXbY1eW8GKyslKNx+owDpcH41DsRnsQp+YHiuv/F6AfHs2taBbgqaix+J1oHqFdPuXx1Rwx3BuIIumQ4FJFce5EeebPl+gDcgP0F7bMxwomE+DEcjd0vosnawapQ8Mtnr9PJLnMA+ODzMFjmRDWPv1a/UtT8uGMkYrTsQr7i25z2lYaNZWHbeLb64MONu7qEsPhsiFUuT3/ufIcsx62GXLnvZ/2y2RirN0I6qnv8xmUAY/Dm3Os+LaAyOnNOTemoyhxUAWHz5i39ux7FGjvr/TJkJ06kzDarDgq/iOsxuxkIaIU0wE8+mxvZ+5yH71O3Z9xuSK7zeTJAMh+NB4z4B6oV737whTO6GhEWXMInBvQAiHuCqnsmFxqsykEju3iNLWBTLWh61uZG4eLyRmLcpkbfzykUhkEn74Rk95b11JNKG8xTGEkkCgPPJFVmOUC3/YR9PwR7YFRlwACfTgPLNLVRupfgCzyebtso2IGsLC38PQjrVnCN2oh9VETkViGBz9iksU1RAWrrJGpeScGMbyyRJxW3lDbaJVCE2yAWqUVuCIAR0Ok+llj/zriRGS3lQuNThe7i4qHCAti3Pap5whfcxW2mcJUTnbX7PyzFWH7WzMIxw14dLVnXPKfix4tNxkRcmz9p3XqN/w10M1K6b3dCrEXPyPIwwglCo1yjFL1TA2m/3GA65wfYX+/Gvmx+DmiYzjEzXI1/s+DdYkZT3y23qGEBA4KieAa/wVL7tp/NDiNGMhIWoGrjJYOa5KOdCKyT65ElDFmaYW6FgDzopn/ZNH58V6b3P1ZJVRWs5iihLPiKRLYDXB8avd3jgIbHGfMPVsSHP4nd79ezXtZoJzbPeZaAHAcWMYAcxod3LLe7ptLMpVz2sujsEK48gmJsva0c/hdjM35+oiI5vQ52KezWd0V9au01yrMzlC7M4TXeCD7rw0ceBlJbtnPBP4H/uBVkX407eorKWvtC8V+CJ/1nOWqE0ZNX8AftTvM+wYQUB++JlcoS5obkgukHemRQIrsaoDa52vS0cW3LXD877SycL7fsArS/dYaR7/vTUBH9t/IPRPb6h+geDc6iNY/Evuh/eOIumFQCP774y/bI4FFTqmuuIyzovKUix6QoCXdIhKxFbXSMSCcJRVWmbAMk0yBIGIhjDASUHu32BFKhijVsIFgNfMu0U6d0Av4pXZNf/Ss/qxiPdZa5CRz6LTtX19bLo4EF3xx4ulcI60oJH9YaMYOxxYFO7OVn1nNgXK3lEZo+BX1akLiJQ9+dl58UYmfF/Es552EzQDLzN/foXOEnpWS3pDq8lqQfIeQEivwDG/etA7nSc330KqUi5UC/RZnOEwXUEHrFPa+Zu7Fw0NsxhFYk5ElIPtRcTcLkk+HfTqpWRV4XztODD8t+U705/yUrytxK8dz3Bz4AymU+KsUBmzFXXV8fWfo6sBwThd0G85bRYnbt2hbZVxfOwb25HDKMfBrgS6flrmUq6SjdIdzS4n7dt+g7qpoANJiSxKrJMcRUJoYlo2pA/aLXRFjWAftCglHMg1WCiZN0lTpFWh3sNHRA/09DSeIyllkx5fuJHvc7DurIYCX6dLZQqLOFFC3nSlaLjmPLmXajJt4903fgH/uDz+44AgTXUOasdJ45rQG8xTFzXPrcYrcv7vmxYhRQxMKR7L0o4iXWIeb9xn0pe/vofAnNXu4m4eFXPUfXUTNLm3uzmIAro9Rdqv4UkcDV5b13KNaCk3Nf7nnsAu/Vr5EUJYNYNb3j00j/s4/FV4OGLpUvpq0e1XbevDJoKDlfxDiYbogD98H2PuVTH5+Xm1pcY39/S8bv1icX+2oHcBW7tBKwVbfI85uAGe97cKEHRgI5hecyTZH0pjXljsdPWZyOjP+siPzJ18M4LzM42QmvQs/TJq82O//X+u5hDuWd+a30Wm1x/J1sSBSwE2dyetGgQOIP4CtfmdmqH+ibAJnuP5iXZVf5r9YNkg5HeXeICUcWCMqJZfvq5f5/HOCKNokGivuIXQPtB8nf59oNbRY5jU3DzwTpcj+5mJ/J9jZfT3qGIlwJs0v0ETvmP0LF43I7QZqfR9n99pijnHsuUc1VtQ5s2fHgPmT94ydVQFApEcd0xLas+jae0uFQ5iXEIi53VixwJSPDCZnqx6xnABc4r8Wv6sB8hTw/+3gFzWr2BGTyC7lKJx/DhGtiq5QZ9IZU1lXVp1NO1xRlXGuarriKueKORZEFb16tq9At5HuMHyd6/EvDV+rHILSOoXZcAjlzAtUvhOj0ULFYifZoXouvV+tPRdzy/n6MEcu9AnWK0TLX82kiwlnt8bOHCglN97cJBDe/2XRvgTxyvkYQfibkXOL39DWiib81gVVHey1dbW0mYqxKtkfmdFbhididbEKffL48MtoNpWpQ8fLmjHRhF/s+W2jAr328RUPXnd1zfYEum+iwnKZTwFCj5Sd8CONIPW54fNraluasu+ueY1/5ci6fl7SCvFrJaDJp9WWmZ5DU9rckHbdsm7pu9CtrxnvZCngnSYmauux4on+OL8dPMq3WKhzbxRlGdBZzqjiNk1/7gUAnLqBE+ermGbGEXHdXaubl7im9DhHnW3jcUoSE2t9rq6kW+nmjOsBw3fhttZvopeL+j857pTYOeELZyYiq1CHAon96997bD0XHmaSe6ZBveUzoD5799O+Ny5L/tpLd1+65ynxX7DnjzfmnFt2T+/JlR0uv+bfV8wHwte4rA29KoO2Fl43BS2NUurXjoV8wArALvCACFBZ0lYzxWWtl0HGShZ6J8Exsd9WRrqL+CBd4ELnh7yDfnueaO61o8EfIP55lvTJC//4BG6V7Y89oLQAG/YBVVPbzUtmukzC6wcWKbwA3m7PLwp9niS0frX8qF+HXlAW+n0yHBR9yKfIJE3H00liZ4n1WEEDXixeJRErcU3TBjpP2xedrQ2tPFSeMbeSuHZ1UWgQNFtNVLAEkm+Jq0UwD7hqe5LrWveelYTP1Yf24e2T05LrJiFuFPERNgWddWfR6jdQG2SDkaalrITMRwvMq9PNvv0Hrmk8hfjKkI6c06+405gidVfcx48ajviE6qlRepL0Zyi5Vj9XKw33mWYc5TK/vh79YJDr6SHV3pDJiDtp7OeL8jZlkkyC7zP8jdwREZ/Bts1Kqb4WK/norC2TmCx1T6b3f5AZ+eyN3th84Xen756uKtnbny53XIetzkNGTalyvvO76jsSPMYJIEj2Ja7r+TIwGFH/dlspl0cZcuYttEsqyAa+vCSTVL0L/VR/Ge1eWWmC0x4PQHoGaXVFaxUzrTpEXdLCMx4lH3VYzl1eFENcjBml+BNsgCND8a6up2z2b6WUN6oyXuPxGLcMwzT8S7dmIN6r4g6eJrLrSS+rzunVYH8XiaeIZEqN+A0S3TtfRgew/qbEWC+WQeauk/vmFicIZcxFhCPluYSo+YMVRbuO/IhX4Z2abMRc1jokG3SEHJzkMEUTj1/jdXhEQyw5OckThjMUrLcoZliJ+vG+DmD8tJ/7KS8GMVHf09gRtR1BLWQIfSOMv0u405ux78ToBnt1+zarG0DRNphKdbB8T4isk1fW1PRc+OhxWa+boA3G16OntUznp0eu8UBTuSJI5U1fkLn0s7/BRPhRgb8KfNYILqJ1jawpAsQ7uEaKEtzAA5i1Dw1ShMRCPJBO6Zz9+qFRt1Fck/1hahnaDBBq5wwv9HaDiYSPbXNLJfqi3sMsVL3fHLd3z9PzwbSJ4aWrCK1RWbBFSVKSso8vV18Kgr6HZGaq5lWkCvsqvnAeW13wqM/Y34oBpEb+HU1yVg3Fq1dT9gZA9x1vZlIuKDGqyX/fLyZ9/WjGw3bAvSBQCsHMUYsgn65w8s8T4k+x6ANqpQiIpmBYgKBduf7A1o2DTmDPLbq6dODkIXr7LYV/O59e/zYP/1yZa/sLyqUITE3z2rC9s/gwIZzhSymCjaagLoXrkzggd1jqg00BihzbP2WfSyUP53AXWTnje1+7RS+JFmjJmPkSG9mOHVMwbENtwdceVO8A+QX2QiaXkEukjs+YT+IU9nelL2qs+5sQC8LKHpmQ0SUWyS2jg2a3GGANrOCxNiNbIi3ct6NnyAN2LDkARGLsaRLchqgFLg0qyHfpW/NdbpPlrN5Dj0Qd/mAcoUxkgpdmyiaPWNFsoPFoqW0oDOYO/zO0yx2yF28EAtk+0SB1Z2bf4RTectgVMw8G2bRsF92KaktAQno2Jmf66IAsPzvzxHKpwSZzIiJF/B4dnIySFScAR0nRp3MWXEWh+fbSscCgZN7wIxFP0o6D+m1x+T595ZIik2H9eK+6S4L3iyaGEzw7r65xugBhDUJ9sAW4qiFAbkFyASHcgjYFWgJTgbYAKqU0y45OSNy9MNqZbOiax0SmwqEiWPNdDJTPryi0EpEBslm4pjYoKcQkfpVSPF8JJAv0qBqda8awTG4yQl5QSZR+ATHXyKUcqH8c8EgJqlbIb0fELAVuV6uoJxkKrvxgihGP34fHcoG25PEJLGQWpnYy9EymTMhUw/tZy7cXfbxhXsWsrPgvJoCfdp+9GyIf+GBKxVk4oHxbs2mrci8ZkYogNRILtohIIs6040dKpjRh75aHM7675MW/OWPfcm/67WGQc66kLj1UWpcRKiHwEhUzqJIViNG7dceDxDg3dNtwQzzRZ5wIFsP/7gpNbXXEhPA1iu/qD//Opzyeyj+mLIF3V1fC6o7DZCTLCAydWF0Y+daYwCawkvmf/NEMPGyGu3Bj5yhD/O/DPw9/AH6nlWZTZn694Gok3q0Kat6TcyF3pl/21Z8ekEkIUWO1woqtCqKw170PdyhVXEjIF6LObvdjGKUJPGFrxbLyutNm5XjapETgWsEdjCJUxAi+W7e7IxJ1nxK5/dcFJYfan8NaH7aztrR+ETQd2O7TQEICBIgVWwVl+DY0E2jm8osCgtSVy1ndHWGcbGqVqIEOvRdQSRgQkwx6wuAJYUJubw1wEr1sLFDG5YXrsXYSxvXDFYzISrT8uf0xhLYtLPc09HG5l+B0kYhS19p9rT5UWLf/t4DBo858HmthnUacCl3egg800g1l2F/Jjcbe8Ki+guYjRGNvN3bCWz6qsc7bi+voTatFv3MX1VtfKXRgq38CWzu6XUsjiU87/S3m3BW7+KEcxmUUrb5q/pmkpNiwyaMOu/IuLNo6B6F+C8PMiI6QRjxlSi6CXKX5seC4hIO0vuXGcGKpPJ7AyoAcOtOzaomdvyF8IGN/tOFd+7+sDTMm2xugFCCBhcglWn1wll89ikUGsuxnm/esMNL9SL/Mvn2V8mACJnAcxkkvsnUsvziw+Xn5lUsPD96mT5RTJQ1vJxfyoahKJt2rjPTfxf4d7y/u2y429WOxe2OyMYTH15OGS6QUo9YVF8orXNSzia+2DOxsmjL3OCnMZf0Dw6KTP1TjZD8FaMMv3a85teVckpmZuCrYpjE9IY7i0JuHxWqNaAo5EfONkmXgNcfAUVgGeqZUKJ4ansS9MWHABIY3ZCH2IWoEccf4DQSEHblN/3okdzUsj//zr6tpNoyLiIvbEhK8dGN4FC9OemEiS34uQRO3opscYXzYShxRxrfJb1nRPtZ8MGYGjdEDxSVJvOGBu0GxAp59B2SMq88qUUozpT45P8SDnuYBn6HBP9/ewpIWsqjsq87313w54B1LhsnIcZn/+56uhAV5RNuGc1SNnQr2YMb0ttxx6ZGF464Tlp6knoexEXEzKvQKqsHSEEXPJr7M4/7WrnIxeGYhDW7nH6S46dRmnDC/sNrgmpDFrNtJOOtrp0fcTgvHzdBGt7cH9kJMDbTE43KaLi+V8hNXQdMln90HND7km8Y6L4XPcas9pcAzBrnZ0mLMj33QiGbLHd7xLkUO+1UNgRpA3SkdO5veWjmkw8KYdZ4bIB2+7WLE4GArooZlJUZmfRQCVUUITkETm58WFzRDhsSoWxbaEYh70Gu/SZOcLYpHcY6YnDEKwTmdQN/JFRxL3kLvF4/ULA9qaNFAqpPAaIIZI7E588mT956Jwbh8fkuXkB6JpQjiKdfQWyoWo5pet06qj3mfwXoiERidsVa9ZVfjyHsQpbF8TDiSJntqaDDLeqdJXn691Nfn4lxxTuHQDWYSaiEZHNTtGBACTNAgyu5noHNUo+FWoyk7h5g6dx3tmQ6DRjoQE+ZhJi0uTwjKSCzk1aMgYoVpXyCvPWIR/2AJhR5SsNuJjnQTlHsx9lO/h3i8frIW1nr5yvQ3T68VNzuTlUrV8n5XjKRd4z7iM5sTBZS4ift2uBVGC1OLvzfKbVhAtPLEzx05l7AWAveQHPYj/pAaWxB288pFAkFbrYdp9+KD7/tCTuONEGTXPGtpKRYUtSZ3Wu3xApakSEqsknOBXUygrN1KqE4yoU/vlmzgvSH62Ydh/Bu9bpnXdb3L897U94rsIVtAW48EnoYGb08S9Gd+DbvuxpdQ19d95Q3W/Di+l3u+sD9ipzVhSqTrd4h/4WfxWdZpPuT3Z8yHhCuZcgWhrIDRaxrXZ1Pq1XxdofXa5JYO5tS03UxE1bAGS/QDEOoI4iBkdHl7pklYAsbD4AX+B5UG4ytFmqr3G61doTZa6oIdZRYAO0PVm2Z/3EzEaMAi5wGNMiiu8JWJwaFb49Jk0uZmTtKgL17shurp/Nh25bHipTy+IxCti7oBb9laUasKuO3xj07UowOQ3Mabq1bbeMPnfWqRfc75U57RsOkojBiYsiYSUxgU+9B3u+JGZNBafmsn2esjpT3/OoUv1QYrlV+YEhjkYj6D7qhO+jdWKFeNc1mN4+IEbZ4iuKLkVEBRcTbE1HIYQ8YSZlbgB6gsC0GLlkybJApIHvocyVD5/L3YsPFCO0NuiYIxhUxXIU3mQSfOuFJRrFBQYkGQpQVHlOxmDI7MnkLfaU0ERh4z0ovzgeyMDpwAMtZYbWmitl6RLAuoOBPg6bGOkZaI0Oqh7JoC8PThlVF+YvuJjnl/dygRuBbJd9l8cZtP7HXCv+xBOqtEQO4ujREC36hW0jQYsH2yzZ/NajRudboZmU/YppOoDXvRHMSEnXq/DUFfBoTsfPAcIWXdynvL2ArGvcC4RXPTzCsBRMb5nR2Uxiuwbt16wNcTrSsoYARNJjJGq63hrfT0jrhA7fSCsw1DhAnS721ZS9Pai/m0nySscGrlXVyTcHcWKV/KMIJDMsxBRsGIRBj7nO74K16QbL0xKxeR6wJsYG8cOd8KQthgBGJ6qEB1gQrY/lm7URfyeD3QA/pYvu+W4Kb29emNuwOV9Lt/Jcdf37tgbjZ+v2uOweYuX5Wz3DBDW5ft2RtoduhEC8emngmJArC2HP3Rx/33s/rQaueZwLqvKXHtUfDZrHz+G7ZHm9OXMNQ83ZNRuGIwe+lQo98b+xuveUW8xBjvejTPmcDC2ip9GHHOBHK2Ywr/VS2lz4hxd5Xg95L14W8i9hZsN2AVTYyG/y34aUshIT+/c6qYwXL6icwJJbOfDH6ntGlUnScRLpzy8qF8MqyplWC3WYhNQ9ZClb92I0rGVJEToJzRCcypAxFWrwnpaY85xLW7u6ua+64s8G/3ZeTzy62FVZWzPeF7MpkdHWIQxwESNYT1iYVjRBpaiJ2laxw2QCLmMkPgrJ3GB01skOJX1+SUkDIFUnFPiwsQKjeQ8jb54LPrXjxhMAEPH4jn7GllGLiPPZk+a90ZuMOs6D0krGgxiUQAVlDmXn+TseLiANaW28aMU41ikzZlRX1++zk4V//+SAfG11TyEONzm46FArG/k2mO/FM8YlxY9v0AiUt2tY2U+fw5aMbONOszgQgJYYuRSANDhKzmEN2b2q1yA7UUyrf7GwMyfz0CETdxNw58Ozi4JAaT2UOWxxV9oncWmQ97jkv1eDSrnFgKeE8uajvlnP1+/gtNfXkfuwDd2oLzGxpsl/Dq5hkj0qPzwkQ8qgSOrQyFiBgTFjNEL+1H9LBT/7w4348OL9Dqfq2xTNXE27epgdEdebdNyIfiUfif97v9r5gB45o1o8oVOG8xWfe5suKHBAlxxbR9vdPsSHIIieaDCmr+dPJrXsoRY9YIONarWRTmzTuoF1lPuc0y8lJUxbvm977j2vgUyAwKn9dNCTeE/5jPQwgCkWOJUaGyVpYSi174R+WXoS5T2zmrVnI11iOlwTKJbekOgdD3eQ+w83WfCPmqz5jG2rbQH4u5PJn2K1OyUoIM5c1/TB7ptd7gbG44L8xNFbzPYafjXCu7Jg/Uclwzpqa15G2jlV9o1IXX5sl4fk5PqwvPAuuHH8YIqeJHun01Du8/D8VbDf8J4wTVoSO68Xv6rw4t22x4nmWLkd99vK1fbyhIbB2ghNuM1GcCOV9yxgHo8v5IkYPZU+N0H+ACc+BmSRTFm+2Ydd37zuRU8ZXdvljb9fmZeKrE/UFUepBgiSK87H3uTY0xc22M3KpVyO9G6ZqXia8U+TW2AOYTFr3Gv8BJ9uwvW2bx/X9p7LM++TPV0IRWg0bI+8e8f3moOLLaZfWkosPIOKaz7zWdN+NnqS22jXwMLfudlBP1J8dltjHObc/8Q6t/LfnDUkac6Xg8owEUWTWoMj7bjD0uQevVJh7XWne+4m4zrO6OUCk/nUtK8ds4ZvK7mHsd9Z5PhvZ2xvfH2SiB+1VR43ej2rzb4e35Ftv3mVDYinRNA1vQlMzKSz+5YuNtwabM/374voLJMEkr/ujK4OGzDzyxv0Ap1y9TfOY+avZEmcHWvgP53mCxAivP+sDeXZnI2lh6M27OQWTeWSOp75n66G1v1MGqWu202CkIJQa8aCfWDwRQvEPnag7CzDIZiIETqIB7XYR4vxUOrcAFEHNCvvH7yqH4xkSXnYtKDqOTGCUtbs+iP17I9ZN2xnDlvcw5rHkjJpHx+6pDeBl+JvtO+hQgClBYJE/1sYV5GO4Gn/M+SFuZZJPSe+27hLCmNkVES16kmbiDX0+TidE0ZP65NVav/U8K9t3Y1p+1w96jvIdnC6AEDoVO2/K7RUHqf5ENGSYDYGNgyOBNEY9OYPO+CYVFrp/iETkwLT0Yxogwn1FTkkGLMZyWapSg2323IPSIVbSytknulmOJOszA+pjSTRt/APD+Y/lQZFG8y5pvj53EM8++o/NpRNZ03/47OidzRKg+E+XklBzhEk3BhcNIqsbDd4MT7m75Umr1bUS1EO4QhCx6hd+JWT5sajkL73roy2tV7Sc1l9+jdKc6PHj/+/afvvdPREfVI6bJL2tKmZ/ped9yytxlJaElHrhLmvnD8B5jdCdJj6G1MFaeg/gsk+vMi+4pinQnUQrKOqXXFgYf2sdzD36XLXSW893QRi8PZCS2eP8mEnduujFJMnLJg4d9+CeF0I9F2/wGysPL+SMr7p1EW6+Yq/GP37ideVIgt89wi517/SYokM2SzCpPheM/DnJeeM3lsbinIs+hcJGV7y4nWdRnWziCVjzNpWZCj1E5uh0gMm4QwQ/+JUMxA7+YPXg5cXLff2Xvcw2oOa8esu5x5bcrxeJ/fkwmv+rBf6/C3nfFUsWpp59g39zoEyY4fVWIi9x6jltFXaOTqcpRTNfSHnk66MbYJ+U2330jDrB9tTufTHlXJuT3jDHRa4lt2arrnrEOTMNoBG3eq/TxuD7nBW8OYTN0LhgTJ8eITMxKPiZvSXWpMXFY1/oJWppxpq+BR3cwaop5pUF+QKgYn4SrREc5JTzlUUDqhO/p3/cfbiHe457dpvpIqkvtKCclTuc5vQwxtSNXcdziCCYIscR5fOMKjLCvVcR0jTY8YGRMpzxdhMp9by7KXj2rxyHnX5VPn2wDF4JDYQR+fQihVhH0SuPv4E1u9JgQBv8GY9r7kikkbkc+XwQj3STiRAGfrzb/VLax9Xg4VTN8njIAiob0zWz2bIJcb/j1Z5xR6+AIQP67z5xxjg77JCDx6P3BHTH0QvcrB7tAR60ImCMYEajQx3jWzd3mdJiwplPa4E3Dfvt/5P1SSjQjV68OjWJxrxkzIKl69WloydLs6gOgmre3R7O86hQn9RQfcS2f7ypniYrLKxBYL/IzXMc6nl21w46JpnXYAlN8o73j7SPbH6S7OahMuRfTHvk3G/XcrjJU2kqiaA4Z2CZ9T6XcKUXygkTUAknsFdzMHcGIO42+f3153sVTQbqvV50+WMGjjFueX/pFEAg6T+ii7KMLNWux5dEFhCY5eCq374HFr+pNcXsPSszJEE81U/diAimPPaCh9NN9Fngz1EHp1l1i6p2R2IC+rEej+nU/tlH35CoVzxrWnWat1Qc+m48c5BcwYimCb7N7+q4JOG9RmhQbC0Yy1pP1iKfsuIq8qRiX7Our2ZI+2kv4U9Of/yGV7xP7HGwq5q5i/q4t2Psm/dMduDsBFQrlYEZ1AmIe1sLLYJ5sQ4DfzrT5i/dy1XMjLV98kCsngusUQNbrP/bClV3lEZVEac09h4zxq/tVO87E36hzefpD6zmo3Bd1/3Dmgeyol7cN/8F+K9G1IYO7YZChuC3zXBTYr1mpXhmxROcnhH/RqO1yLTD4hW8Mkx/SAEaSPQPw1QOnCmoN7UFvIxMQW4XmIvbi/vXhwEBio74nUY3s8rZHpvD/0PLLq0UeGaHHDYoUyJxtQerftcz2l8BLsMN71oR/jSxNX1zOuQhPh9nzMmKMLD1ktULPeSE69y0KMABr1O2Hoa7a6SPmar4LnVYvuGoKcl6vmIx+usjn5rUnSzZGC1p3gFsGqpntcvMIzcJdIUfbeZX3hxCdZhzPofGZhC+j8kdvl2v9b5UpvOXa/AsP4vlJtEXnuVYt4UXAd2/vXT4FoktQRLEOZX9xqL7nLnS7XlFEho8E3xFmup+kq2Gi8dGrz3nYfVC9JA0zCAn5Q1FP5vOrZMUjJnpCfoD9wbRLpRM+zHPnTTqfgjFtkptW2myn5YrTqjYLgsb9T3WmZL2px1rnzJTkPwV3nfPOya8rId/QvdLyUNf+eaD3tOT1twt/u+YCy3s+U1eX8bH8NLXNupmPoa7BLDt+EvKlanJ7lXwpL73wnXSvU8/SmP87XzP/KC/L8EVe/LrfH5+Z5LDeJ/I+6T/GPRuFYWBGsDJy8vxibXt5IdeiJUmRWIgaan/5qzu8XSd4wadyw13vaopW3BEYKDcGYbes48jiDpGqTgfXr7erxp5jn+1VoPljulrrq3cdWFL9JVs+QELYneY6XnOuxfSlnRmja3nHojZ8/8S17vPBV1ATw861W+hL9vqTZYzbt4r3PA3+ujMO4PrtB/C17l5XVSM2RjvRqfrAB0rva9SaS6lv9Xe8a4btLROECTUGMWcGMgVWyEPeGYWomgL73ENgGGgYPxDvf/Y00PZanYcD+bvHwcbwj5uZJ8+nBJ2S6jNnqqMaz6iCSmSXxfG5yarW3oDSfSbpr3w9Uua758qpM/VLRjrKJb0vTvR6ODKQHwcpLpHhE5adc0SWvMB97RatWbcD8yXGqRODaR+py9XbRjtXdlBPFtHvjL3En/Rhna807XwGug7VD7T+7VnUorOL+cUl82y2ByU5L9FxhQu1DuZLcOT8GXEpLIhs5GBkE4ohl8tcqGn1SK/ej2rocZHnSObhP7vxxeFpvcZjFpIcX0dLJ/HoMwwNMXNHk/0N/2yoaRG3jL1n1hk39xbuweaPFW1r/jmdvwCRX8/AvAlIRJM/nYv5q9t61sQuhygeT0gobA6mJLjrA4M4v35Z7IbsD5515lGP5dDmnwHZAbICp9P2IMOA2QUwD0z9omk2gdnOA283E/Y0O2xdWXuaBR6dGZYgdXNQxk5hEj6mhyeJXAWJ/NjEZjB3WIJgf0YB2ZZqUSzt7wp2umr6UHziFKRqzZeBr9k6lcrScwjeS+ch3tozs30KrqGAJtQhfFTXHZA7zcA7tCrfo0IVlzwCMVA/VxNxZBNYqK9hrkr4abVNtcLabtgBGvHyVe6+QmF6irQlIufcr9O0JA/wUJxS12FX4O0mZsbuaYubFwTTiq3GiUqedH+gVOZd6m0M5jzmK+GO0+GKTV8n/1O4HjfaBBXzDGNuyx0IrE1uOvfX3ahQVvzdTGop8Wy69RsY0EW96/+9FRtluSiuOYoKF/9++XFY6pmFu0YBRUzVM1R7zOiJkWHgVppk2p3ZKTFyp1xFqWM+nDv7LT4gxcCUc8rU7iIFXe0yCeGOdBI5JTRw0ddPOOFXeVqXUePac+5vtxe+y4X9RPuNn32VVPW04Ms2VS99AUdeD0vJ8SLEZBJ5VD023ujJMNacP/Thlarkp23Yqv2GNP1DXsq+pGFtOWQM/2qjc/pvZXpminiafXx3hsTjOhevTk1+PyCmrqrerD2htTJ5MsjY9vpIHUkHFU+Ypq0Oy4GPmHxkssGdQfAEUMb+OCJRAx8OR/EH7nSuRz8Gb9QLMX/tEUCbNoU47slkOR37e3ngIbTKrZ7pEpx4ogYlTD0Wyh6lifJyrY1hg3WofmqMGxG68z3ymwLw0lbGfWbyg4qI11zDUXRnu+S9qZbpN0HKpPS2D0rYk/lkZdB7vZvaNANPi0YesNF8vRC4tyh7IPCy++iBPAmwJuZ+EVzzLQeouaVpxa0m6Kxtg+fad/VQ2/+UI/e78rIJfHY0scnuh5prlOmb/cmC1TX/HgMFcRMBM+UhL0RhJ9ILmfP8A9A2o4UxAn+H/cQU7HEQOfPkGNouFrrvg+g0ybCl7MKLREqXv08ExwFmWUXeumHJUt9srummxdMt1TGC4Z0ZyJXbQPHWy9XUWYvgU7Ki4GYj45qKYFe668Mf/QBmmpSy6tUp5esZqY9VGvd4/L74al7O63n8jayneDqxcdj6mc9Y28+qiV8k5uWJgZQk+a6pAHcJfn8Lxb14HFx1aHXOeR/RjtghGhIR6x3Mgee9N4jVd92aU6ebOWwKCsP0jas0Li0J8jsYdHTs8pZlzO3OXxwL/hFhAmyGaOQ63feS6GfNfpQsOfZLi/4oM9PTjtrMMNY2Y0/Kp7rdUwqX2+izIyocrNSVzzG6aZVdf7wMG2HQ1Bebq8/8bc/00CoQhPW9s9omlxnOXRMXb2wxjAI2XamPmXqvvdnoXv7hL+lvv2JFNWOXm7+jczYMclmSrst2kuQgWxqp60STq7LcujSMZ9xrktTova/uLddcb1s45j1CORgHKCJZDa1eQqscsVqtvUGSaCQiWaXVqStZaT9O2FsWXtzAmFJqjEMzKbs+9zuvCccV9WhcIwdPvc1cl0J172krtxe6tpHrXsU7tsaiXnTOMPmzlvPTpv3R1aPt8RBoRUEZdTN4abG4aebysFGH9j/DXZ1pHPOj8p+1W09sACat7iSFuDTVHz728yOfimV5et41pYDJPX3wAaJdUIga1FyzJK23n0r//2xWDNgtGtViBhVKLA1Alcbc1G2pmzn8WQkcR0QRrEJIK+Q6y5oiVhfkJO01iJJJUfsDY5TesjHSoBLbJ8/hnYBf8ypITDRljwpSuZ6yJE4qleskxnB9/23NmvRUvm5qXlPKY9cmcIjdRHsLz2N3UyydzgW9ULPj46JUSsaE3JlxAU2pEdocrCbMnhTZVydZmlS4lMUtZyaUnJvF+wMnypge40qx1ij3tGJL3ADZf8jKvbqNwRNtG0VWIH/Z1tWdinnxXLM3cWk+xb2xe7SCZ+wFbkkuilo/q7b4kwGj08vD/vyXWz8BUUN83U8D01DgcXFVrGdc3qZhyOW//2tPesjpziKh00NF+3KTWTFoHVLKf9x71wXRbSzVHPQavOAgJQnNS2XAF+scU2/P7Aol5CEf+KK/FvGGaWXNI5s7FlxCCWniwtVEDdYHkMhAhkWXOxgFiZd2fUjz/uVmZavYl/CxPqBOWLMlgEgS9iGTxr3ObvwRJ8Xwr/2Kt4UPUcikD5x4l7Ki7EvGYpPp3GFHi2Zvm/5RWj5xwUeHndqfysaR5ISDkexzFZDT8iUL3GsdQVl9YYgRmtCGlWSQitHfKZUz8D024NSKKw1cxprT1MBl7nrAwXqK1zn251JE4bakYimuDqroWpjUG6Gv5EfLGmCnekSnm2LW+isdgfxLJPrO/ZsuMUBDkKRJkv0k09QxpPmncYhqOoJWhvkYjYlfSnlDdNjChxrN1izs0RmPRfgb6AlkDJB67MOdlJy+g353JWbfpucdl+1MQuY109Wb7aJZdQ3SHzrORqtPVA9KkjQjK2WXJhCyqUbNclBm0mDTM4Pk3JJStb8dYgKIzcOKn7d/r/+xxnMYS6MYDf4KC1Yx/rU7Nz8eONPUoxfVgYzEloY7JptS/4aU/uz7InggXJ55aszLSIOrX2s5ZKt5YNRgK8kyNsphSUSXCHggZM4BHzukgAkxD+IWgCJlWlkSxNgWFubMAXefqq8waAbQ5SowVMlcSW4lZhWihQC829U6Lbiu565Tuc8IkY7+DXrEJbrsaTHtm08lnDHz3rQgDNzvLc+TtEPf//w1Cw5+PGw0ZHvEnasOoQ546yfmY2hpGKTpXXw/iYD6TRe/935tCsjezbapvyhiIe305a1uA2pA7FfQLwk+B3UEJCoFrZMuHhUD617I60KDjZKKn6MUKe7iuEoqep+a/9L2tYahmu44/thdoSTh9FsZP4EHml32l0CP7+CeBmrBNUT/ZU691WTK76U4gWvpTvda8ATKv8U1qpv7L+UL2K7vtRgQ71KsxNNuMWxoqC+JdQsILu1G51Qv95bmcH/nvX+szfYiZ/WVn28cxS9k8bquAq0YnCKAKSGz9M4I8XMN70OWXKYa9ZMIj0dmOSxGP/NsNmj6IASm2AAMsKHckpf37u6fBv0UxYU2UdchOa+8RAm8rWUuWuc5l3jweudMKXpqvGDFBcX8ZDApNjqNpHxk1MWnrxs60snkRNwK/OrC8b12FWuTH5Xek7j+zRbSElNz4+3OL6+/9KQKYTNlqlEjlusynIkfBhax6lfMaWbuKVUM3Hhxt9/9dTrGiZhGVdvZCi+tHGkLhcuaFyyJzIKQ32H9F8IOZmpEY2v1tRBpD7KOSVzHJb1xHfcWq3KSYz2fq+dD3aOUqmyOOE8ex64ZcN/PxVISSvJbHNVdNa4wu92tIzEa7/X8wPfGSGGKkwQ2ZjECCIaXJioJmoNcgAYKUHDV8BnCJEIxygxYuZ7knJZRPwc8psMd7rDxLvpTZYh0TQ1TVNB5hGICt6LRaIepfTlVt7Qg4UneeMcbI0WMZo5DsmEWKZhvb53CqVVlIMtxlhYw8LUulHVopOycnSmuHROtjSz3+8UlcdoSc+eVJj/JYJcgLDZYP2kCoaz9WQpmq3voMDLrpnFR6sM5B7AmZcX7VYhiqkiKqAVekEfa3OD2ecBj5nxstxdFx/2uvIlBAEdN8qttcsVwYOBdGhhQdFHS9zp4EAvzJH2fF8BTGojU1DCZc1npICH3AzhmjON4WFoCxs383AW3JgRbbhmGGd7qn6ImomD+vGne/IYVSryWdGx6QxCGWI8aC8o1dqtB3l83d8XUr4eU72VAUy5JWrer4QrU4Njuym5jENvkNm36Y2TlqyJv9Nop20pQ0lvL2ttbAC2QhIFlPQ+x1OPyehQnsrS84dldr7Gje6doU4XXpr0Cj/7/Ru3NqZWFdsZvevXOXF4LzyaSuW4iLbsnFxbUDKRJqJDeUXEb7cMF75T9yV7ypNBtD6DdmB4pPHMWDpjzE5KjrcE64hHLl22NTe3tvKMuGlGH916gYlogzrKco0bJEd9GhM2XdJkFbkKsGmbmx0/jFlYgr8y6N2Y7DmusfGFF+ffRVzLMx8IPqYY1BJYL7c5LYMIXGYVWwV/VfPQrwGZCzYbjJjjr1us/rkQP1KF/nJnNZotjbdkJWRJeTNYSJlE5XULULPK/qM16GV4GMyIQWcyKPuQTGOLKMoOZDFsfkzFxL5abRcm41y+kbm8PDC2Y+RKdk9k7zOvxOAcLVMfPbPzOkLAHcLUFLVnKEnPiyQvng9mjrx2qXI73fpy5woB0MHe8UhmjxdX5IBRJUUjNM9G/rsLzxqHW3sbj9Fn2TIBVUaa09T5uifudoOT3ZOUJXkTLLlMZ2H1YrR4kDKz09qu+Xtpz3jfZvHt31oQCalqiYUYToT6Xkg5ILeFMesH9Gt+yPu2q4DZVyCNX7gTtFh75muv9Xp/KqwcBxzlyLokXkHrRHSqpvtpYdizAM/eG21XDbO1Pm2bO7qcuD6cmz9cjPYwFrAtEaMci1kUiokOFH8E0QWa/H1CSxEmILnABzn8hI0XaOEztJCPFtExqPrhDEC/MAQeQ+LI9j9+ZJvwyn3uqXrtL+wZjjk4EXgkk7VEnr9uSFEoBSSW/mkqvJrHaneJUFyUjFDgM8R4WphXYDLyNNCEOAxXXbqo/SaR9VzfPdiDxWpNf6IjHrXZ/vFWA7Hg+GtW0GFRKV5YlJU/3X2VLtX0BK+PPLRSpfdLPg151A3oQE2o+8WLY0fqnuuF/HTfzXaz313j/SnjAQwX/XjRISE8Edlat0RvW/t90kiOg2s4dO8CVwFajaHpsx0G5+SINUn/Pji492in2IZZ/pKnGvyXW7u855k+InGyDB7c4VT201Pe4nPyENyBx2wgwdMoTT1fdJNmB8ElEug891RkimiyWXSqK9IcZHMMtDgcYDtBD/+bZw4DHtxd347F6JVDTRCcLfUw51k7Q0QRUgdyvF4DVIV8erQpfoxGz9VWZ3XOPPV00NVbY84usBH+e7LyvoJ7jfHeMYfzAmG0wtXArtiM5q9UF0vro2mkK+pamntFWfNuko9ZMMogDkN/7G0bN8tdC3j8XJc46fZlZ+80sAxxDM+uk1bcX7z7KMp8L38ZtHzDnOa33xd1ZpLkrQspzy75b80dkeK6pXKsFdTDjCTadXNPfkmxbUi0M915meuC6oosipmexdxTQx4N7GFYnDVDF6CvQlpDrSPEqmR2FfF9Bfg93mDNkiUYmvYJE4cA3Q4S5ddJMV8/C6WLqo47iHyzpHPIp2XrRCcL6oc9jPKp/VvdmHnXtdD4Qb6NR2o+rYHfk1FVldQeqg7YomjegDBNPuJZJAju1k7dfzgI+W9OtvSYlglMFlx+l+2wzgjv4eKvcr6degdBZqqbHkhAeJOh5PoK71uHUPZZ30tsYWbTlCxcBJCCn73QRcKd+blpPR0qBROrTNY8Q6hnxBZf4ymMTh3an3P/9Rh/ICFGDj/CuF1/lUBDsLPq+cwsYrf6Dk/aiDJuafa2u1C1XukqCIVwhQDRrf+rsfxEiMcE4jD5pMNMiW7e2GR8QsnKpOR7K1LmXygq2zlSb0lna6kt5iUQpwSUeYNW/26fI07+z8Dx2DegihZZjDfb0PnD0C8urTao1B1B1HRm3XXjzwj7Gk14CDQt1pmWttp/7ALXo8by0OnvqlX/9Ym/ZKesTVpidP0huT5i7wMDD6sRRjoZ2nW5fa5Ij83HyZDNcjVSyf8VQRXNH+u20ZT2Mo2V1J3pJaUlTWPqsTGOAvaPgJmeJgSkuP6UhzOJ6NcC58no9IEQNrVg6uDr3/d+8+Yk2vvEbT/jJfp7VGjtL6EJrJ78ySnXLe6DP72N8gCrAi5SfaB/1CVTwN+JrOwbhrBZ0GJG2NC+Zy50nE1d+0g+3/CoMR8ysujIVy5JCPLFPSGwDjO0BfXGNh96O0VoC8Vt5rVFyt25mynvZQ41pAIhT2BBmSN4WIzuYOltiGzRzD1TgKWfOz1+rXvXr/l7B89CYu3MPzkVCbtazjyCYSPZzMGh63T/B8fpliX/rGGOKjnRsZ48I3j8psbsb7CfyAFzcNyvkssVQV6D+TOx0sh72NLlJW7tUqMDPeAiZHcHnqW928r1BD+40YE/IRAD1xvJQWV4LxS9FLJy6rAj+YUzoa0oY7rNqVgW/XNZK69Ylj7SZMCt2nX8qn4VnPn1ZoK/BwQm7NgCYR2amJng/feJGyVVU7fc0H5v7OLbRnZhjabnOJST6Ir2yNTzdiE9lgVAHNUoHB5ijKQLOLbY6JhSMOkIBiBThDM3ssMMbrtAnnqnafAsKs9Sk8GiTNbTUSOTjMm+OQMFPubWjB0S+NeIET6hAsI9Isb+amqkbNgYZSLL+93m7tVIsKNbwv63U1EOTeH6/Gps3meefZvzy6ng2Ytwl0SFQldCJnr+Bpxvlx75cozyCP1MfEgqr7o2UY3xASg5eAE+Kir6cdp2k+nF4O5xupzfdmHKmrd3L+7vHXOHFBc0yQVtuX/HPYglOoUQPJdQkZqeYtf7DXTho9vSLzk2nWHjP24P7v/fZMAnANhU3vHkVY/YKcW0YTK+kBExtaJIOSOs/HpEoZ8bwpSdn1TsD2b2/h5pxa/alQdtfZ0DWnPMIYoeVJxGAkbwD74jNXRpr5S59wQFjq+mpwUyOgdjNBNYOcnERihpoOcjhFNhwBoApZvlM1MeWwHmfk0ddA4I6rBgNAanYT7v9rFjQDQuUS662NCssHVY8dfLG8+I+Qozs6h0L52RyjBSQk0ZJhjjwP1iOs4h6HtTWviQr2lH4iYcRuMM4H8KrJShYLmZMqZh4rmbuLLgyErgpzjUDJXJIO52Bt8zaIjHJXtpjFQXmW2UB9JzBhWu+HSa0tCfsXCrsggPf8RGPFZ1ZUV/r9Tp0M6T0gS96EU83/ysjiHRBIelzLLyYy65+BzB4ZTaA2SOueCN3T/6Yx851Odn9/PDGw6k9ajzgRRk0EfkIF5FS64Kj194pBMBHXYpzJ0op9h0DoG7QcGf9aSkWoOWVikz2QDv0bO4C31jMvK7+opFKsa+GuPzEwDf/EnaFc99QSHt7mVdIg10h8/yVUm9qZfgrcmVGB4DM7Y0yrweQpwy9r/XBPqhNyZGU9YPfKQ6Y6AoLyFQOQYgRBow0uQohMCml+xADTI5yqK1XkgMQS9QEaNfJj8QeJ5TQ19d65fWQer90Ped8n/6Iw9bEc3H2iB26Uib/h2h3b83bwe+Q/mMVzVzeodtqrp+ASHmTS9tbbJriw51HPojaQ3N/sXmvZ5sJ+fD0jexHAJuHxYaf+jWFRk/DDNE/ly+s/ZUWaYRROkwMEVwC1ojg1OJvHsEqpJmsxkb4mksd8RvkOoLr9tVtW3dhKWPVgLYqm3PkJVfp3xnbLv+OF6DJXlvb6CtaxpLd2VWlNJR4mp2Q4BW9cwDOgtxfyk64nPJY5ObUIvTZGXYON40uoemL8K9AKtSyPZt9yordLT0vLzGhb0r1cEz3xOOW/z16Nip1o/Ikuv5u1uUJbATx0tg3UVeT9Bdm78besHY9Nve/pf9jWmwIi6ySoqkyCswIU9rxzgWNuFxNkw4v8MPA/15VrfwqFdphWqZmiwBzpx9b3y7wx1iCltEt3FsY6ShfW3Hj7lpXEuEoW9uSdl+3duZGIb7f1WOxPphaponiexXfogJRfOjDme/G0qDoiEdzMHVaI/O9sGURn1bgntgGXmBvWQW6Z5vQ99WyTG+5+4RFUwhWVU50JQzhyEIFrAJeRLa7oBDRElGIKmRmwXsIW0ktNVEafYdL+eXDGslfbSwfr/AjlGt26wYMwmE148FEtxcE+zqJwZeoJwqzgD/oCHIcNXHIWOilytSY0O1F11ch7ZziZ53HsX0xWQO036jJj49glS0NM0uOvvklSKkD9iCPV93L8H9BRs+JMNVmAHkxXgEruolb8TOK1G+HweZIT7X78BlnShQgexH7zPaTbNpTA5j8Nb8IjPtD8MOTYCm0FLd+eWkkWNXUHTBmVy1U/ImV+bO0+66mS4paMLxVt7SgkMuGa2HCqZEN2DVlo+clsQplknPT9jc4z/Ze2CHE3PHjMIXjrSnXS6f0mtOKXc8yYytEEi10Cx90zAExSTKuidh5EoZgrR7hKEm23IjQs4L5FTlmf1l2J39xsLMUe3BtqlnP6IT+p8Vja8pzjhVFeZx3KlS8f1n0qM9mt5BaDNxM5b1xfzdhjeKox4wv9PgUXP3mgO5P+J4DjLwCG8Bk5qjIys37o3Aqclmaoc0q018LQn2g2cSCDMk4ljr8NZGhUlAAcvDNqynlxFbFWbF283EJwXOh8vS8X9/4de5UA72XlzyzeLuTxWC7fNL2ENuaCbINhlPmkblGP/M0MkyrbxSqvtebdzb17R8DDnLtu4ojVEmTbG3dG82Jwq27MhWTN9o3OCvCs6PcoxetFtsy1OohV7Vz25qiNzTZxW4hin3LCi/Di3+EpfQCTy9oamaXaIrhp2ZwC17CIZax+hopotQg30d8kknOH85SvM0gNKrv6I80lZrSJ/Le6YzHCvLKzKUsCicG8sYK+mIMR1zk1/PDG3x44eq815qmYb8fsstqQ3T8fvj2wZPMK3k5WDsfwG4RlfOaTTD0HRD8fMFZ9FtvivJjkmmIUA9LaPD0C41+v8jo2wFj6pt9jymhtHu1XG/aiDGwjAjydjHs1wMM7206mJ5pIdnxBXNeP6FB9TiWdXOxrJouinE7JcX3/BwmaIVmQOBl34E2eVPvUUVoMVXazcZQCqfwXqjCek6HOkVzMkK7Hk6cLtvS++Q/iZxc3LNd5SIYRziRNnQNKvuXXD5eqbzYsY34FaF58SqXh32LjeRCPPpGKxGw/alFQVrexdmNhl0dw34S4qagceMXj3kQcOemwjBz6e3/GqOLcS9su2GSO95ffnsMJzkzRxF7EgREuza0nxYQl/7CKjV7vwFPQwNQVnB849owrock8KzoxcE+aF2hur57id3dWUWeIBgSjk+KIzIS5lhut3HkuoI6yljdV/D7VVZXebdNfnRiph8eEWnjMEMEOy/Hj4dT5KTsS/yEEgDjm+Zzlk5xvPm7x9qNYt/duKKRhJuSbUKrOELpze/tzN9gfo9M7os7z8Oen7aUca8yNvdFQF0lJLHb2BSdxVqXgAPYeC8u2W2CpYH6J3uud6nssOm9GcONQ9a429z6mzlF5K/Dnr7ZDRg8g8ZEUvIAeuvqYcYfzXv1OcDI9/exci/0uiWBKDz507odBXL6+mi5tQiLfEm1cKkBOlnYOZtEeLIWAWnYAwHqTtFpSJMy3IKSSBY0HoHIzFxvYaSHiKMP4VYyf05FRAVbTvtLNE37InLGX2Jodl1kAAwgTesHjDLJ1X3Sh11/FonpT7Fi/kdkW60Gu3LI4LLqgmU9M1yOd3yuNk1Ccwe2Z/TRrPlqtH6bfvAwKz/KuBgZtcnZd29S5drhR/9J5rcshddbgEpdi/4Zw5YCQi0NTgaFAvFG2nBbxEtSdRDp98sAfa4C851T4DXndNQg3EGNsJGpXb+NR3yE7scWXXrvyqt2PqQpLen9m3IcQfywjQ+UAx3FIx5RiBKGMPgwo4DYzhBpHFSF7Y7aqSamf7FAbrBtdbWc7hyLeD8Q+9KQfaLiBcH1XilpsA4JUcM3Ztz1CGFJrHRiclPPi3N0xwiPRyQCpU8lFJV2QSQ4vS51rkckqFlN1iiTKo7tlgmesIglyxYWYQyxJrTKRjeRk8FP3NSpWw5zFbGulJ2w/lIrd6UchIFs26o4f4AiFpoi2fBE7kbM5pg92JNHPy3+Fhu5eYRMeTZLdJfFTt7H/OlK94jKxwvIZh0m8pAoVUXZ6/dtX8kwR7/mjOIHe9gFv8fdKemjffPiXeFrLvPDdyRLzyRjvM6vRWGKo+cHzjHjCgwqUMFs8mmxxWDxtGr/xGlzhnuwrfNLrJ+S14MW7FMYvW5RYtpC+mwbcc+JnzTCFwOJrzlp/e6WKDtbEREUgpxBWlF3S9I0DffIsAgCul0YkbH6SdcsvT1vY/SQNDgUnNp9RMeAbz5Kknx1cMGCyUi6s22w3+pPSsGQ06m8GCAj43c+Vyse5A/NXJtPOfs3kXh6xW3oAUwMVE05MFSUhKTVdMDmuYI41iVSUJg2e2ouo9C850OOSu8V9eUfz9ZeEHmvHUevDMHaeWwQu2By/OHD+90QN3m0/KdphPsHPlyQ9qFok2RGdy2aC8dRZYbd146/gvK/XTnM/5seqm3rFN0R3ibEZ28QLgNsPBvTlAclaSmUktIk+OYyeeKCQnZjmd+oqx+7cq9W0F+8feuZ0EX/0zNDdW8/ehrlKWxsugflaNCoefDcrvnQ2vwLbqmr3vJoowJ5qcBnRCosyX6nqalH5fzEZ+bFVOuLwOwH2MdqeQTMGh1h1o38L2kjwkslNstS7GNVfbDW8CVDLmZy5K+ErVH4JkV3Gw0HagU5CuNiyuKCaiWXwMk+kXd9hdpCcyKfxdZLpUMuCbzejDOYGgVIzJUyix6EahUFRVEIhpuMZJUOv7km4vufc5x7/95TAjFoQhOFkRStQuR7mp+fVlQyvdKW4/tSY2h7sm67rQJ80CuZcRq7OjzgQS7g7NhunWf06+dHbLDv/TOuM5J4PGulOtY6FeULftD/BKD1poXc+hHglk8r3gGqZ3SW12J79/Wjl6XR1UDpnJDcVvhy0iWpvm/uRy2r+lGJRW86gutGvEzdBzJQ0kuCOlXSC3BdAMGNS+8mROFFt5l9urbF5YwXZ+HXDC6K7G6u6JtdiFbit2k5xJyifObqaS4ZK/mmee5usSUld8Xs6BGaUHg/XQkAdNApCywVEFvPjfbnRlSazev9IJUNqxSbVEEr+HmZc59j/Xcli0XezSp9mR83rb+49kLtoDd/VFHWhFk264NLrrY6+Zmy4nNNFmq6CdqX6+3LBGHE3ey0/bNKyTnaQxBNY56aGmKgj8UXn8J/c2vkR/G9b56Cb3cpmdP123b1COzFk+KPdgNHGB70PIabTqDGBx1xXFaSTvQMzvws+JKExU8CX05fPMyrpwSAtahY1RXcgfi6hrXQ3BaY4+ZgRiuIymHUWKw7LEEEQA64G6vpQWlWHe9NVHJjsvXX8JMDnS6MwsXpjLoWIHewZY+74U8OK5e8hF7TGL4g0727SodQYvJCoviRn4Q1nTC8DjLSVBlu4219CfItl5gC9juvmR++sK5YKRFE0IRJN3Cenis64Y+wcxgh8NgkQCjcYleRRXzBI6UJYFVPb5jDbQlcQ89AK9xWG/kz/F56R7a+eGRIqMklSYmEwHX/+WwBfWWy9QffFW8n2bAQUaRCVEvbFXPT6gDMn7ZCjmMYji2TRptgMgxRaWOypn5FTbII9f++V9R9OPts+Lo9fPfNb26h7ItPf+fX1i/9dzQ4s2IONDIYnpVZ1i3DG/oZjjK3MrDECkwooks+y95vFb+GgmSgmY0bycn6Lihtlg/v6wluSkre0Iib/l5PCmLcrBrjoKfQPKHCoZEvIwP8vCA3TyobaTQzWcb4ioGIQJMrCEEchy2Qh1VQiVLOfZHTHloNwq3tHxq+cJoYSh5t2+dUf9MvaNS+7Wxu7hhzZIM6BzANNJlSZ9OpvI5mmYXCgfZAy8QYbXyRg4q8ZU6jhdO9YifANBiWNA1alTOQGl1zPH2Q13+C5asts/RHbNf2azibDhtb6i51GhlBYCJEx8khKppEbcXRqJAKct5Lii+xMiYvX+P/4Sm16bIpXX6W/Hn3xb7tItQjKnwVrlPnT5WP1q4DsY/RzLLJdCHGz67azfl/zyyOArilW3jAIxOHWtTjlXoicRlOBLxKviNNdDo185DltQOzo8ZsQ4F8duyC5I0SvT5eouHErmVMuGz5R/p1CsX6je7l5l8aSXF5WZF1UCkdxcGJ4iALqRf6vr0jmp+t5LI/+1XN4UXRLun0ZXHCJQNsJgHHj/JUvvJyvtElh9EVyZK8qvH9hd9s4063Orxw97/H1qdmVv/y+OUzlSuL30bkYn3m6teR5TTCIdK/WAQAThlVaWyFXfNbB42IRHtKBLhWQpFlwh3RmLz3Mg1fexB0zjuiCFWgmrPlfqYMSrsjwHSbKLfXBRiqgbO5Suwhe9eIROF90M71C76/FNIbUo7+eisWLk9puO4QPDyUmCQklTEPCXjAQyc7ePhyC+rMFoHajBY3NypO6cFRrMwcPqARUsxMxdmARMyUNCKJ57Aaq4u6jAj7gRxj2KjNWnOngneHhDHCiLsE6kCoq9qRnkYakgnv0VonfJlOm1Hvj+U2nitrBO41ZD7HztXrIuqTHdVL8NhDIs4qjicKPTKU4i/yCyWPZb0n1s7cN8sYtxHnBhRziIKJQkSOU2yI21JDMCNnWIEeeJsnH1B9d7pjcANL9tmWPtqCCfGdhe1tfaVPq8/al4CryGgqIKnXfd9/HDlQ/86mDB5FggTigawt+0dSzXrCHPslT8NtGvAIvCSqGNBuxxlu4FtdUxvEHAvHRJhR/oSefyWhs8W061eLSdQR3B0UDBQjjpGhnyJKUbYchg4GVUwZxTDsumBOVHnNLTPyA76BPO1me+5fyxuZFJz1gcXbuQtJtF0+m2RRm858b1zhqLdx+2A3TmAuSQJPRbZ8Lm97povfeKGoTa+Gx+NRNpUkeBmNjKfV9RHL9+VB+VUlqz+Vk4Old16i06bLeyZpe9hvXF57i0qKrV+WDDoN6n2mTGV++uSL6ZmynuhzKPiH89paXFJj/Xfd05DbBfvs+fYTdXydABRs1PX4wDVwQ1ibJ9V7T0th7Paqt56ZSu+2bVeHD7YhfY5EBfO7bIQl7HYbTG2P8FHdN+T8Zx2+MpfPPcy4b0P/6dbW4Yb7r42ZUjJP/KfVQ0PyFZdx3qX7bvuqNGo2lqmb5+fjOyB0vq2yf7adnGu0zmJhMmjtkq35I8kySrU5On4S3chx1hfTkdCvZ5RpDl59C99CVLus7IaHLvJnYneAHQ1xCP/ddNj9aesG/hSHn8nzyqHg9DLkrKQQGGv9BIzDNsjXgoeJ/4QnwQaBCfYlYsf//6GB92dP8a8R2pL5lYU4ewZckjyMMZX9OtDbRWYVXLzD8f995B+G461rYU6/D+MPH8eXMKzWYiv7RyiwR+iaQY4wf17ZU8OnfYOK6mx8uWecYkm8PYFN0wpdc+DN/RVBYl4UJPqyN0+ET0NaEDcygf/mmfAshr2KjRh6UI9hBDeJZzmcK6ugT4FQP0fcTuqXuCmONPb/9zd5JU8KjqLt4+NovfZ7sFF+LC3AraSqWzKOq7sa/My79M4/cQZi6N6Sl1b0w6tOWRJfMVnTOuBfetEk/etGz9gqdW0T3ZDJ6bzEHro/y+uWCH9BGjxpD2owGbWnP/SYsW3vmXf4xJra3/zeNbarvdS7iMSrmF3Rmt2L99hYpq+iGirEM6v4CbpIvGnA6na53eKS0dZpkwMLK/uXBbK6pSFIIU3SBeYURae3ftdgOpq36ToGvheeL1Dd3tOGwLJv2+gRGndmaJ5l2SIpOqM0wVTpVZPIDqmxN43G3hGI21gYZIb3/CkijqwDlhIZoiP5ZRF+/TCOvl7zOYJHIL9F2l12sCAEor5BSYTboA6HIzNJuEEoxsNRcyzfKokz2KaTzMUSB78nv4/simBNrZT9efxPQNwQYjt8dqu13qbKuKdGgXHhDxLH/a5OIfZlhnIKi/qT2LlsI1I4HhvTeBj2GsF+MRJnpUSowHzm9NMRnYi4Hfic/ibmraLTN7clrP901kTKX7eDcbwP2xfX4HxN2JRldq1eq62hHBVIxTD7loK7z9ZL6M2WYXHWrbAVBeejVdgJLhhEAhgyM2rKTiiQ8OJcQb5JJJNfIlELiO5Q8YdkkUQBrf5CWAua9NTlY7Kg5pln0OYhXwK17EH8kbw53leEVCRA9vEHF2NPqEoPsev4+uTJGVLnKQtfCkBN1UkwtjWSC0DYkurh69KURectY/xw/j8jUNmFPt9Ml9Z+m9CU2CqzeNyVXW9pknXEZqZBDSYErjFXbzPsrY1KF7kTxQJN/4SKMgMKkzAk4SRkgXqcBniDMo2/V0SSIGYvVDdVoPyhXyYXCsM2dojCU3//vW95VDeKzD6BfqeJOCiAhxhOJwswVswxaWwMfEigRTubDBGR1RcRWt+IkqGjpulPAQ1v8S5SV2cqn+id0dfIfPyS0d1DNq8Pui2npCyNUu8nvSxUMjrInTmLavRk0CdnhDhUwYuwARRDpiNEtjH1DtnKOVw+B4SOVDBA2YJdQ2KzM1kbo+XarmlhXhXjtJGGGSILWLoywpFJCAKpi3ho3nWSw2rNAjnj4R0MLxsz8yy6Pq73crbcywCGi3LAAESgFrWykRD4l6jxGVklQKnQX95nZDtM6Gvcj3vz+9yMbswhud9OfzR5WO1fJnMjp6Yz0HjbtrBshkNqGk+j0Xzo849xFQ/nf0Li66IeY7sQD3Qvq0S1/jzNT67SQIsxbRYISYHZBVZU9MNF97ftMTsUZVYibSxFUwt1LtJDqAPKkDrgz/lQMgaIbD9GYiEMGbULytYOoaGwI0Qrd/qjUCG3Cg1oLQf3/8kEmmEpIxtM1ndhMvX7mBf82MwK9vQNRiKS0/NBh9eDrFGUWYpUsTANz88ukxbiim4hpPZnBSMoGsNzFu0/pmEIO2AOVdeEauZ/xV6P/PGWxfuZrNtEgkCO+uIWtSZeefgYo8n0bL2MAucM8QAvNkroKpFv0Y00lpllYLT7VMfW8b5C5KUCyw1tgojLS1RajDvV3dc+ZdnwkNJsdelqYZs7wPCCq7fuuImW4R4Q2nfrT+Vjy8C3LfUTETWIwDQM2a0h1ARwR8FvVVrQxV+pLsJINT2vmuq3Pf1oXZ/OYfzGj0z/0jLuN4zjJQfmy93HgjtBwg5QhNSHW0D+Rxw00Eg0D24c/JhGYQokwZNYSpp4BISdplC5p4NY8Tgal7kgilHbtxyItEtdfbHlrO2nbUCkmyJ7qgCDTzhWTQcrpNDYKT/zynyYBBqH8SPXzbM591/i5zjHc+//WNNhDJGjcH1jOAYUtBxlVtPPZ+ved5C4V3qBkGsDUfA5ZGfmQjWhgbZwhQ7SiUgd/SCww3nRWKJ5aOM3NuZAUqVjYmFRgoJh1cKQocAmsCI1EsYo3+ixFLcPN8FAFdvqjwghUr0Ppp0O5lyLoO2o/061BdC1fEaDU0oddtM65SYRX0Q8ZYnOUhacXe9ZWRLA7xU/oo/6KqTCxP1ZvZYtNhqdT58cQCl7xa4ocN0kYSNIK+UwpMxsbPNxbxcpcLZNu6fvmmIKAZ3c+kcZWiQiHbFynMZpR0OmCAs8kFc5sYi9hA7TbbSxFTpo8xkj2Vq+Vt+W3uH3OcD0DCQTJOmIycWU2RhGYRGKGtIUUspqiMM44W2YcQVM3Lt13KV8xSEB8ducSxMu5FfgNtymdTOEwTY8aCOZsjacCcvzF3zzDCDEDDXqKeUFqHTRPgp55u1hhXpqBASbyKNFCqH6Qv/bLJ7ADJLTilqF6KxP6v/sU3T/YhJE9sz63T7DKyL6IyB44WcHVaDIiAtdio3skwjhwxM4cj7vw1IoDOGghP3FlpTVZfPdr/wGXpYYbOD3VtVyB+DA04UMlm83nikGPqsLe7OSv1K4Y7Bycd4e0MZgehIlxTZkW3uPqk3ZU9aFWegE4hRZophnv1nwBgbs1i5a1FhQl/mHFa20ztn2jl9wDJenVXBHtUyXx8ZcdZPQ9QxFyLFrwAPA7+KRKoDZfhjNMtUOgZ+sD7zIx6f4PykhxRwFHboywuONH9CstZYknGeoJYQIxTG6hgubO6q7U/1pHPJBDvqdDo7LH122M+2VJVCWkdR0kcpnmDzLIB4sJF1jaMRSAPIHf23JV+8Pnb7c6OTmaZLTVXdJGMynK278v/CWQlx7NfSVvjdhPj8eLFqMVvy1sbUJoOfehSunkR2GkZc+kA49xFP68SpZCndAZLme+1Xc5Ij2ybKAY1nJPNFDD87Te7UA6M1oNTOvrRTgWBR0J/btw0O2RVx5GX1CzYWeDFm1XKnqJxmyNG7rX19Mm7v5yFCLPa7Zc/0+de7Jc3Dm9JEu97EngeP4sY+Uk3uSDhZGnOD3fu5TEsmwPAuR1F6s8Ed6u4zJt4ygT2GNpS5D04u6SrMxS/WY1kVZrdfMexsFTKEHt8aZYQ3DgdiEZKJgQjyRLtYC27t3Qdl/YcA8dB+kvznaanE+QoNvXN0weUIZzZlfJbxw7tIFHv7iYPr1y+aycgBSOsxlcKvxoDjS3HN187rKeYPe6DL1OrB8N8QvU49i/7KzjICMeX6Cqx/e4+b2sFm5sWNGmQZ5riAyqpb6MIa+8CJcoh+bbEwF3CJlthya0tPyQp2U6Z7AafkIXnSmUeD2O6K8g5W1rfEMd47nw6x41CtPAOtLjZDoTTmKWMPXlpO0PJtjDQlieLaXS5IFhK7xLF/9ORkBtnVZObnzYQ/7HF+tCDOHKe2IxlDu60ddqD6LG+ZECukXLYhS4x1Mxg8qHcClebvaZqcOevgS8Qwhhwfv+6IYzG1y+sMcuSF5Fbk6ah61GpvvKLLD92S5Z6cwsz76xW6p4o600cc2vm0I0k1sEtvKXLYvQv3yqleh7lPtWcBq0k6hMe75Hl0g6bM4SrQvWv1QKACDSZB1UlP8oxMN5s253o+/zBX8snlzqG3xVmOIunCzRZnfg+zXNv//87meg4GumlSPsqKNkZhfbEGTLXjtXTdyKt101xhxgGPGd52vFQXQ42k6D28OQ1akcAhGK5g+kb8x5e//MQVSckbkaIzVb3ssZiqvKasfwLijKIGDKCjOoIwJHVxticIroG4cpcQhFMIJYHzDR8NRgqW5MjkGLFzyYhlKnV16Uz2hEe0P8QEsSZM0e4bThSj3/GtEfqj2UnXww5PjQb9o9a2fzzHnwok3Vkndvn4SyDpY+1NKAhi4+WXeYiCxxTcrilKvxEaod8hf/NW1l/g9O2nuPyf9dpns7Pmss+qe68XU6ptByTs7FIBXzKaxRcFiSJfea7gjgROhPwR7Tcv2fv1JQ0M5Q3r8pH9Vd8W81g1d9q+NUpqp46LDrjrlzcFfgHAIoSykvQLrAhX4EKg3FYq7YHdFCHmnGHvyUdprpqbXPKa1adlvgxPzCHVxuoj4iA672ByLrdOVSa0BbYS0VyB7Uuup4fB6eph70sA0id/JwrqEBE2tqsJJ0kGw5BYng5kcAmYzW9rETIi6cfc0S6luaePJokQP9AFwzfwQon8inFR19bF+Q1JSWpVvPuLHWF4r7W1RreyShqLygwQknEmacbPuNEk7I1RYD2zulfEJoWL/5SnsBSSMTkR/yXRBpL0CqPr0e0SIByHbMwI6KdMK9tWTipzbxkKrdPWR05j1wPH+dteDwKeoOAQd5IgzLEQZGxLhECMCXzR58n5JzBBaYBrmPyGobB18lZA/GkVzy1yXgvVWaJboAxGAiGqU3gG0azxsMnVYHhhhkVLrUGuH5oeaz64vYHdv8j0pZz6xf/fLRvP1Q8jZh1s3l5dvKe8adfN+xqnbh6tZ6V48vNx9nM9f416QqJrn8bVzXVqyPKq6WSX1aRpxZZRpxmc72plii5WEGsyBqvNVfYairZ4cWIlOMLIyUJiiJ6F6VbnFg07lcPGy7FbcuosGtrtDnyUyWnHrCLNE3VwQYFG8r41UTajAIuO+X9UFsigGAewg6CyahPUCOKu85krmaCiHdmxg3aDGvCmI/Wht7Ee3mdkwwVEBOCGZjTyzruY1PTw9xBHftOHZueez5/Asg9Zd2Hj44l4D/RhfBFoqvkQnU6BL6El4aqJSh2p27lBOXLyHWoSNTvf9Xxy7420TEJ7MeiVRW7h0ELMDqnSGfwklHP1VrM7B/CMDx/xa7Y2wpwhYtx82TTcRSHQGscbcZD6vkfQSgl3G9PDchLApJNA6Dod0R5HEtOLWATi8supY6yCo32YbbI+vf6/81rE8fzUPtFr+tRel1ApOj7XptShbg7543biaB3dSEwCRfrYGDuX+7s9tVq01+2CJfui3glbLOwvwx4qH/I8mlJzEH+s2vv7Ic+d6LzB96KpONW2r8xkpdzpjrM3Pa6SB2u+hZjx+X6eEPZuwDJRL+OI8RNpHyJ3ODVRtNFOYeWPqHFPrYOGk15VG0N9BSflrTX5RcW04MpqyTTmJH4RBoRvdhROcle20oSXfzFPyN1ptzaUCV6lCoA0iJhA5AQgAA6tkV6NBh0bCClWyOOtoi9hJKz8g4tvRp7OyxIpKmzwJRp3+3wz1+AnyrZxS2ndjqwwDxW7VGeAHhFq6rd/kPqa9m4kcx2lfDw3XcX+zCk/+RjiNeVZdXRLmOazyMJ5uY55/AcyNkRUEwj4X3KxKilyBJOVaN08XW3BguQtTwvtOZznP57ZitV1SnoNya++fxYFCEOQNEPsawCVn+VKlLefK9CKHlMLHYrm+/3Pewpq8nc/IGv3T1sgxnPYT17AY+zfE/aNfCaaBZ3tyuco262MLt5S7sSWidjrL9zB3PYY226UuW0xMsJzRMI5VfA9HXj0/v94i4zX/XjFp3PxZI+RRatF/TpGDNcq8SlnGv6OXf0r4Swxfqw/yz1No1tPPIRTWYKKL7U5bwVVuLdzGX339FAQcY3hHVVzjbZ38TSJSojoqb1BwN6uURh+JzGl8rPukFXlEj971UHVuBgE6hSMoUaB5m1s2qfqUHB4mooMWeic6i6ZkAEeBonuUD+fjI7W0S5MZ3MFmRkcS2ZvEIXyj6n5l0mCJz5vq4oFfjcvv+qmS9GUmHN1791Sb+e/X06Rdv/0+5tXL3hPxgJdvCAc/W+3zQi2zIZi8HWDxaIqDkvv7uxzM63rNOwx/3xvpXfKd91kfv14wo8xJvHwDEfwjSXwHuZBgk+766V52Q+CY8VfJmOMnpnb9Rul4CPXEPv1VwhL8af2ebTCiMaBEC9t9184S43o3TTC8ZRsDctu7o0Dr9YZE45zCEDghjqGYmHnPpoyVqN912hQaXoaBMumQg07ZgV0Ms7iTYeAKOtc89EiZZAitPnDGFV4xd2vpl/D+WlNSUwcnurHX4+yon03gokrZBDo21AbBpdaKmdePPoDVqHoLdiPL9Dj95FjdbqTqRz97GT7oy/y5lffjW2q4X9R2lMOS9XvzG4yJiB0ssSJo92vjH62ZWcBfekAKjxvcLj8NnXtr23uyANJd2AVuj44q14VUPm5UvqHQ0cu+i+gbsQdHzQ8fkxfkNVNTBVhKYeCmOWNXOE511UZtuFidQRn1CPoQVuJSi2glwSphumlJbtnDGqq3z/LBjC8BCbVES53YnVtYjUHMlwX19EaAv41b7bn0SLXO/0xrymm5RnB1sjvvrW5YebX00fd/9wH6cJqMi0ERiLlI0dbJTlPCZdcLHMXMmTCEE0+vTRl7pnTJlVXuFGYBAERwd4Su3uRodJI1BYKDiQT/w5kB4TYLWC4M0DahfvDGbKQbnhzFTiZlkGdSTSTS1U3hdUVx9jWofpb6vNhRx1790PpC7PrlijfXtfAFrXCIntQsL1k67MwfR3X5DJwOrfkg4mbkIDsCAoSknYwBa5Ez5BJQ9pWQXv7HvVP0z4Of/93HgUIQgmRPyEf7m88gQ+QHghjmIrrxA6YtDVRVt/xR79nU+f1RvTE1nxwwXNnnrU0cLCovUvFtutPywCHA86gycX1dSIrWle8fz7olaDeHFfJXIOqHgUXLSr5Wk+SWDCfuKuDGT7uW8RRgssDK3zU8EOUh4nezM1Ucrac0P4A+DGwkKmyjw5igm+CE0EHiwiCWX4HY6nUHU23OAyHTOfarFP+mru7CpDhosO1Mm76+R5rnhXQMuozfWbFMtJAzkgZ6UgDQi8MDmUJE1RBMl1f/BS2DUAy7dTBEV8zRbDS8Q1kdcuCgQxNGT0B/arYYiuh+6tdjNFZiS1Ea1S1q6WEqDN7L9WanDwGxmARXlrmP7JjNY13RtfaXYUsHtbf93KFx08s1+8wWaAzl4Qi0hlLIBkoiqdpFX349HNhe2rgFRW4XuIhLo8YPd+zbjZIh1a2A4vahZDaVrHsymxWbGACW0wHSRn8LxHCCejqmF2DqY4GpdjDzAbqtgaK06ej8hS6mRTvx/VOmUMk39u07REkqf125/mc6hqY/ThHjlku3O99sjz2Ueb4GdpnUD13A8xPg4YLfzhivfGXGSfe4ecGH033uTAsItgaDJfwqXGW0tg7xYq8Qvhv98MkRVR0+p0EfHkul3pvK1va0L22J3xI8CeiLKNM6ac13RaeBHlw2QBJ8D30EZPFdJJVH30mz204Hm91ZlS/KK1KOLNUnSFROxgFxnqWyxnDk8C2K2UqCRKaU4TKHWbvD3xuT5V8sQM64CSyhJPKrzfsvfHmyxh7hewQQsJ2VjFP2bZNGKZDHhVfEVh3RDxeYqrqLLk9n5enyT7nchV0GIkmMd3Xq3zPwwGZvPopnN57a6a4dZqoabaUv4AMgILTD+Hc2nNfQvL0Us3Z3djqHk71K8AAPH8Ilo7MM/gWGMnX3qXzHMeckLP76thLD7Wn+hb1U9mLeC71yunwn7JKT4yLnh6c9o2k5ikUt1KZrvaLZPjdjhahF8EAP3wiLMyPYiQDV24XgDv4ipJx6k8LV1blHhleblrRuR98s4S9JEulsLdIphAADbkDp7G6/HQIAcNBaRMdyMIVZVHxIjiHlUF1x7PsW6VM56Ypi4o1tIfid3YurjuhuogE/XR+r3qaKuRpZuy0kib6253nXNsDzpcRpx6oollpPertKBfKqXmQDAHSjSlUZKKlasbRwkt/rohLe3Kv5RmpXUVkmDxwCH4CsvMmH9NbaR13+XBorMxghPceSjz0hwYuWcbmIRDO4DKfgir1kKWIfLFKBzM+J2WkPyJWjt7dPGtzwVYPs3gbG/YggJLq4cqsePkrWsmw4GTLh0vX4vMNH583ASB1YTwp+Fzdy139TDEp+eDNlMggGC3PAcHliDiY4lqsDhVccUoSdbLWv/T8U3eepBfnnGsPJRD+vdvSxd0O+2tGrKYMh85dfRkwEgwlVOlDHGMfFZHz+U7Uy+zXj6BXekYmgv+VIIj5X765xNKcv2eT+z8rzwqs4xvkbDJ6a/NwvbdGzrHfj3id02gIFCFFPMBu4SNdfLCyb8dNMLlOhhC0cy1XB7LMZ9cPnbDaQdY+/H/R/ZK+DhWffw5CQTDmm4dO/QzH6rrsSwba77ozcBSN3AE/QxDphvLXj440ulDjUtPChtjxKS+DdKxEXsA6WNRI1bCgqxWqvBipp8TIwzY3buLhmiIVvyK+OH1nuy77ptk01GGOpQ9CRpAnbSkfiWMeZRoBSoSpvStjLeb5lEKaon5CTl1NKou7pEpZf0kE3SVUPkRLuY9y3N0JfDoz0gdkkfC9q5LZjzoS78aIxPNBMEl8Oa75YwlM5Njw3azinZXx4ThYGOVg+ShtPBUqpI6094JnTq8CPi1WzdzIsBDe2K/40mT/+c85ARtja8EpNVy9mqmcWkXDbF9XULx3xE2F3H4lmP8/d/SCY2EtZxB996jgKH/x9aM8IW/kuRw+Lz4qgPZ5YwcXIxl95NxbS9w3Dthu7q2dtWJM88sLh68Wv5UNmv6b8Yi5k1scgdQsYQAMMgHNS26AcIzDAwIb6iBGbUAT12HuSsExl+9Ifh0ee6pA4GydxaTx+Te9EEEtrw4AjVv+lob4gj444LBtX+0xTvBZdqWHctNSLRzg6uDBZ+izZKfRjzOu4mAlv3Uhme9RS4tqGt5L49NfGcfIn8xztJi0100zsKtMRxfWHGMzz/I60rXct137R2fvRVNhmINhZy15Vj6yXZ14Twr1jxiQOMtBxbeG/pBqirzqC6pAOur/R6GPqz4ZtCB16ILVOO98MQ2k0yN+dBhQv2sLSL7pPY7g/a7Bw9oGlSLzKS0fHaaPGwiHp6ZxYZ0YDohwE8oLS/I5puGl+bB0CmIqWs14/+A0NppHMCC5uqCBpYYSPYI/bEENGe4cKGGsJnq9INhsJdeKnY71dmuRUouUbj6lM/VSjbyZm2SMy6s7EIn9mLF2GzjP2f7sm4SgydV+Tj26qzeknZJgrfyAb4+gy6JscoHH77Kkxl/7r64qKLzu1TJua53JcJ5EWaX5s62RwFMHx/gApKH80u4Z5DrBz2PeyROcT9S+YVwGVQYQaCtaS8NFhge0FVez/FRj0eV98+VTALTZci7PvMsias39EqOZF5dioDl93jSJF3wtyS3CUX5T6b++IUbwTKN++gFalMBihMZuKxBeBii7Bls59dj3dt1z79HrA6MmgQf5Sns3b1WYDqfs7PLtbTR3qYvo+IypeHkw0GSMwvXmt0YKxvPNT58oGI7K1ZwcBo9P9HBItkfpyRceOSB0yJpYniD76w1M3v+lerjZ1KC+MjviPZcoWzddO7Wt4kdpycuOgBRTLCqcpelcxk0322qc+DPnTgo69zv+zo6SvakYmdmczWed/A/guzXecMC0wJg42vFFpAbHMzVsVJe5+FYjGi/36hKE5DrFKCufan7pYR+bRFX5tgkfeH1bTX2EwzDbTf7MNVISV7dPBKZcC1pQUxKtbmCMkyaXmuShT71LTRvrJ7kcvd8es+I+WGOFPQegNXSBib99eGI2hJGWkfgZ30R52nCv3bbz2y8IG0Sro93QE9rUzFU57LSakE9Y14b096yys224/X+dJlf/6tm7t14z/k0ikI0tNlmVNtQSB18AhI2GsBzLyUxRaEvc05Vve9Jj96N2+yb3sBsJjBtUBk8CYjsnGyvGvaClGOV+3QU9HjRIszALypGYSSu4LAge3ZMKGU67jLB+sFyr+1fv6LRFFlnSXtoTko4kxfdi0mHE6RmIoJTuyjHB6yvPTKwlrLlrRkY3DSkR/VDKcBnexXQwuYL/7lEMr54zWDiXR1+K8raKTixHcuud8PLtkqal4yzceSxrV7673TIfNu4V6T3dZEGbF92FDmMIpSGULxXfaxfvos4S68ussQeltb4Vm40Fo+Ceaud+NFdwUc6itDkefMpGtVd/G8vTbmlGLYydkzSSuwCDdVeDhHQdwvJxuovC4Hs0zu/gzqVh3iQwWAKlj8kAb1YNU4iT2zG+E4No73CcVc+1SoYOzngjo/a+5xOQiplqGE+JvR3YcfM+RMJXT3D1im+IRSkruVhbuEKW4l7JS5F5zXGu9xzjBkHOBP5T9DT10VC70i0grk+V5j/votD99WkhH+BJDJVjaJj/Y/+T7tGQzFyK/1yJ4Vb7JruCbnH/4haHi1sF7nt5RbOZDLILm5fUsXw1ctossiT3Sp+NWFKRdSm3ZOJ/fOGC08lB/qwkRVFVEwdSUhYejWo+lnsTgpzC//3Yz9sfxW1Wi423FN8r+ih6T2LYoommlbnFgZi/EuwRp561hapcfwlmTh5xSPR7j/vWNWTzxSWocLlO3X/B+U4mLvC1GI6kswwzvpzOrHempflJehtnkszFzrdRfrM1rnjdkX1tUnXprUZ+rSG7ElA4Apy2WGhtIwAmyR5BE2J0hcWlv/f4q1svDXRlUYXM+f/RnabcVRgsOqyp5rYAd1PMj+jiD9ONxWCAbxG6VsyaV2sMcg7C+Esdek0xzOBpa882WFA4UaCHYDnikCelyKg9iZ436ZFpgqbOhLUy92/Revix5V8AkGfT5WgamH+yYfmJwhYjgqvcz4cIPOd8AlAwFQ325ATm1mcuM+4YF0xQfRDaYbRoG1g3Lbwp+ZjmBoHtiOC58NSL5R4syDHF70A2oM/xK5j3RIv0iv0ZBzzG+sNbXqFCtsFHgu743mub0uCdFjxrRp0wD808/Vn0cStbefH9fdjLehPNYMNVkJN1niGlzXAps13lMWhBSBJOae/6RNy8lDPpJL1QM1a2aUy/NGOyiAKikzCZ324K2pInpT+HSc+MuS+2SE+ZSLUM+w8hJJ39toDZ/M6EqT5AGFaIggNoZirA7Jr82HHuWMSR0PT9e8Jhbfcgn+tKJNJP+SRyuRqqgY5LCifgslw72ft49tLyiByTvpXpvSpwkrI/4sHeRhnlC5oiiE92V45vrlDBzxOFf8Q2YkU/M6mkOKheXgcjlwxNb1MLDNqbnbz3bcmIhXaCQHo01oh/tw/2VAj4wdYV713PZzqLD8fsqqV+wMfKsdmM56/E5d8iu7xZ6lI6ZbOEP8ihwGfsU+uTMISeIBCGYIAlWyC6bZ5FZk0rVi76olCuxpSHL1F9CKWyMg/6k8OuBEVz6z3aH30FqAwma+RNLdQM1kghDOOGv8U299F+z3yFPu+cqZ8K5Oe1E8pV1ZPUvb4T/w+HBZE8L3ujXm/7Skg2KjofDwlZMJINhhWCsgqogo7wRh5inOpMwJPmMuANwANrP4K865l8ynEiu5WuEnUKoACRLiMD4alRgO+R6GhKB+BuO5sxQwnqc9JGWOjasBXwKHo2eLnPEDWIe6kmQBBfILZsfr1EtUYY+UWMW3GDHtWin+NIhU5yL/q7PwIEJUvqP9offgYCWv5Sg39xo1MyZRXgWfzu4uSeiXwdJJQFMWGvFc+vXXvMD3N/+S7ELWTKv0I9zjYjHW7zA/8rKmHRGxYanHTiVI/G3lFxAy1ROXSlo/Xttryk47vAWmrF8FGprxwhPRcE2LgYgoSA5yyg9BTJ0qtMOPe6eA5dkPlVPGlGEU6rt2W86wtPufStbao/n7O/+pxzcn4/z0OJ0HUuJKRAZGMxRCH8kt5yjWOuHChdiWVfrAVB9lG1SS/EAv77VI4k2z0BoDs7V1AY6tiyUPrvvRgh3FhzbfFyD4Y11Yc+4dGXH4eCqQ32Uil4ALMkMKERxVAziVThLjLOT6NDkRYpmzX3W9DghjsfwXIF7dDrOR1AJ7WAH9IvdudKAxc8owgKsEQTxuIshOfVU2jWeeFe1FpznfP3n1fpOdvO1XvMyM5j6VnW/dNXwcA8yN/axPSXaEDX1czjDF5YZHMuCWykV55T3xF04TU8tOBO80AqmdH/12mxZnelA7Tb7vO7I7ZY3pNYJ+NWrd2j1DISzjHU1fXe3IoGwpfyJ/eU8yw3oIecgxtyG14GZ0QXHu60v+TMpL3fe0mItK9CynTvn5d7rCX4w9ffhI6ptPcLdydz463aUqt+RmuSxhy4oVVqVAbcKVZzFvgex8vTX4TmjmnV0XlGEfEBXijzYAwoq+2sviq8/YRjkK1kB6EOqIhZkCDscy8MZgrsqycBXwsaCmyRvxCyxwwAoXFXf7PG2ZQOufQ7Xp6ITE1gThBCqGaThZCTYw/oIiIAE6WtItg8DeJsNP8gGecoPMSpFKwvTsP0b9pMf/lnACbrlcI21CkV4P4K16fgGa0LTSdbsALzhp37bUdeNR38t4QgtWBjMVtIAryF4m5HvZ/085QNsQLDA4kM0ZN9nO/nhwAjF//dYeFpOT0O8iT4oNhnywkSS2iYRf2Si0vVtd/bR+cAGNwyDF0LpkxZ7tLKZ2luT+gpCxGUCED3EI8qEAtzEPQd/vC21wAVx3rx+lQbBlT1FkYiijMYYFc09aT71tjxwoNqvPAZ5m0T9BFQIt7LWXltBPUK3VsRFZSagkKEZCxl+E6KdYfagxNJUj8jzhd/qW98zBiTqv4sbA8IqeNZOMLAQIq4SgKgS9Y0iB0/21abGYVek6bljBKyl5ZbfcoUookfEkX6JEOo6rnwcZ2d5s86GpjMYGMFeIjGnzTvDlRRAQHiYpFpmUoft8iE/A3A1RitQ3+4NKbrZM7FU4HCYjVg20wIXHvDwieslipEwJ0sAzrZ9+VgTC+QwbbYFcVCMtk0sF0cUryoLDonOyTqSHTpJBiR3d9bvFxp9NB1H20Dg0Gy23DsQxtIHEUfmcDeaQ5esDi1soL5UlscCxbMuyPZPalxbey6q2UmPVfH/f0Lt4uEsr6pQXrIm27LPbD3ne3TaW9chkbLOsrd8lF8DlaKseZG3LPQyVdWDB5UiHxnh3rxHOG3ao/vv34jDASMD490JyimRhmyPvbRhS9Tw4ga07ii9OX849xyBdoXe38OM8T9XDpc3hf82v0LiuqKedjXtFk8KYZOj9GA65HlQ1Zuuf1tLBTwfDJmc94p7KnIEAOyREtvB7kCHFaxMBBFklNlT78pgUy57osDJF7MloypIBYWMY2BII3eR0OZKnZ7ku/pfJGQqMDCQPGibws9k928mN7QU52aNgLVwa2bimbDTj9PjRjWMe/fsCcH+yF5hYt++5e3L+5Z+xs58SZESfZDY4OgGwPmRiHHELGx/mTqOp64ZuLH5LljmFAeGCU7dXUIOFhJzUsJkNsW1OrjwQUgMLgwfRsOBYQYZX1oT/7jI5VJoutFW+R0e8EdQNbQgYgSNBEfgyKgvdTrCprzz8y935y4H1vU8P8q2cJ70l6tr7MsU7+nEf1tPgTXXG6LjPT2jcQj/3S3wr+UcdofiHMaaZaVqBVHn4tHohRK0/lF/b9vf5HWr6YJLvQoOfXXcD25rMM4C3Ztt8DDk34I3yME6MSAysTCgMcFcMyI/sMAokNmH4whC0HzNyBXX5TbF63Jk36uKvC31hacquPhfVxlvmudimYgFLR04l6eQodUKk+9+SNxLMwq/gi6yhMxDHn6DyfsPv5Pr1bW3ux6O8s7f+JTD4mad1GzM8X/HEjAF0KMekeskO6lXE/dUOb+eefRy5ism00vEdMhfvTMeSx2AOCYs7RWSVKs/85RcZ2FgkqGO/jH5pJWJIYC5dhA/XC502hfFT5yNrihfRL8HapjM5CWqNHUst4VXvg/XBXV63rez76LewUeNR88IyihViQT44/uO/IBWTEPaVjvyTTjQAcw8gNeKTxoAYK4lpKyYKj/ui+K7L7/MSZPcMozpkzdSxUQxA8Mt4ySnaMIBd7vWgwcwfVoj8qjbXVgPLMqMmzY9xjuJMkO10ntnpd17nJXd48BlvIx+8Vt9JyOUj2zcG2TXYVewCoxIVsmezPpEf5zyWM4A6Xt72acWT9U949QC4y9PETAPQgi/jazAxVnxEWDgwyaVmCyjoeW8lIw/jnqQ/jvlbBGopXBs2a2u7zafVlK9kWw9tv9v8zFjnXqW9uTjb9YiOJwUC73PYPg0nXz0dtGTumXAlfiQLT6U3k3eYSvKpSPgEPf7aAyuZCZA60IzUZAMRN58D3PRCp5hngJez+hDrshyryKy4jcRfwJRJhB42yO6r/gy1XFTuaIWJj14OBDWx/p/Q4V2pTMtmfLaWIDwOUM2xZhg6kQd0pPgCTbEEAn9Bv30mgoRq/6Z5MqiWNTpRft0YRj2cRkBjRGYrltEbz/2Lv9S4VPr2aUXGSoMEn3UBmBqEaRY89xD9jIyaTygfBUjFRTUxfrChtjAb8nQVdLzt11cvrKkfkiBxYekS04H2GEht2hqMe3Hc1WHQ/CnB473qziYAbDX27Lrk7csHfxXwd+oi1i45LSgLiSJUmc5arCZg3LeIa5qSmXx+9YIYrAf0EYdSEAah8LGzKs1TG9c4zh0XkTzCNwrPs27HlCm2kOzLHdm0ap2htnD/EkJb+fPKu/3DzoMvK7sJvIaHy4T7pIgnj+mou9tAGNlLKc7IHQm938slgMuICrO8Bnsn+1iS4hHhl0ImbOqsTB2WI+b4oxrho9JjAH4Ldncem/kiJaMPfCR9Y3JA2SlU5tlSzaIbVdGchUY3C7V+O5n0VmqmNf3Th12dUP044LHrSsSeZZ1ncc6/tsupBPDdpyviBkzq/IL8RZ7pnfmH0q3mC6vf7qxchm24v3azXWnIio5LnnhY1kf/UdsXA/3eR961INEhWsAvwoqvO8r+JXcmdDjPQ4EEpNY8nKapu+yXETbOOnZnpcawfdO/m1wuZv/zoUKZos1hGFj9Yd3HjyTiNx3LsMLBR1izSt729h3jFzza9YjTEpkA91Rk0eRl+2428Pg8/kY4jIH7tjizv39xg899SOitTOfR6aMJM858lPWbJzqHtKiMiq5AqMaBQd4j0yitTM8t8dISUYAcv0xP5eDEzCEC8QCV8ix5fu0S/doObI1JVDPYqX1xRuRW0PfhBt+ZFsKHlCTbZcpORNzQt71KMyYvCCEZdDa3gAdwd8XOr+8RmlfGKN6Uzb7jAVR9+lbOe0P8KD58d9CEhjfxOS/ckL3YZr6Z7ljl8WLc79+WFt+gPtsh8tDWmqtwF4Lt8CEOfk3mf/HzoN3TyqDP9FuWl/askQqX37u8xeuJ8yIyI1ff+xE6ZwVnpqo36yr+b04XvGBZRUdkTBtn4Y22Ma0fJNkqWwZf2Y2I7ihZJ5gAJgrIMgrB/gd94Px8XVR/c2w4walMMrn9k5fOCEsJG2nuoxIgUM3evB/uPZdIfRH2q8d7NPT+YWVk7047TL+tvokWDPnCQ8e9vmFUPnz9MO+l8rCy/mF7feu4K27Ll+i9q9FUJmDRyhH0mTbssj5szXjCsI6CSQDX5Wf7dU1X7JhfpUSht66Dqkibuq0XRp0ThBqu+8uKTkzyg0SiLfUWMYKrW6F1dOI7gjZRGcS6zbaNqVxQE7lpZcsl8tslnAP8e/fJXCqlyavlXCM+r8DFaIOntMthyS8lu1YkUcLtr71XaE2oi3WRkqRsFYK5NdALoFeq/R7kPbH+qMascc/Pg5gHSgbG+UZfhGNfWcXuvXkMO9QE4WuHH9Utwmx85CXiPHKdn3hJ/W702iVMfbaMwHCiRs686orZVbGM3yzjep4rSANcGoYDALOnK3v7FdTJ1KXri4mgj0vBhHo9qvQ7bdhQVsrEQyXob47pPzjBHNQI2iiSHZvMJiLRNiPkaNrxL+NaksQXCMTrhFZkfwzCZIGiZx/hEsIJoHT8IkDpccVv5+/JCZ18BjEFOFwoWFlyRIr0e0P87pqmkNhUeMw58fIl/hmveAEVuI51EDuWnXF3JuTvY2LEBhYdB+Nyk7eI38J/GPBjNq5nEXduEX8HH+KhEDTSB2keAhupSBDzbIlVmIWz3kzWJendmwS/Ko6srSOsxpHrxXphdKT5zu0i6RH8YtaVlVLEmDLZ6atrfFRXsko07YN2sLc4QnMQ7Jy4ZWu3qTtISn0OvOCAJWDRRqJMYELmGsIxhDn2hGZyz+ikEMuLOLCiKPVF3Ssy3+PilO4gipS6D9v1mW1Mx8R+3ADdmBS9K2jWNwC4xeLBP/2AOIeSnYCZ8qGy1uPa23V1vVGHiP8IY7RAZ5ZlTUfzf91PNQefDTj6rW5nq8mGCJhGwbuDh8//4ZQ/TqZ831i2W4jAC20g9g/ZacWwmg//yGMY5HBpiiYyNSGBEJENSQQBDDz8FivgyzPp5tYSAou2fDGu2FyM+eo7jdgmyF+E9PjtIfMURVwzuRBwxEqlLuYy3BRF3ZSZzma8esuZd2PecvReRueM0Z0HjYiniIHCAFcKskTHjBNojW0Xg+mRQdP2JfTJL8nKHR5TMq/Bh2lXa42rM2PmDV8xkqKyFKqJBGSYYCBnEecZHkFV8IknMVZlkKfiqCINEEj9ZtFVdwvEkkUg0C5YjNqBrI7kfnZJ9YledOJrK8lN5CFk9J3bZDdjJyvFpIh6/T4Qm+qj3JLTagvdBHyIraRb9jlMICBNqkmwjBNktNu2jsSxAtsQkgKF0bG1A2+YtU3FVx1bn2S1iT0cLxFMvqWFqwt2HIO9ePV0caou7rnNmxsBXqMQeKQq9Lmh2KXfzGaoqFQ8Y8+fPVXAJNmUh4drppah3BXWoPA9748EJw9E6XPRhja0+/4eGyF4fqqyo6jqHBAnQ2ha467LU7etuDcLmUPNbgdRgsCyYyCtLXlQOGh+jChInVs3WUCa9x/X4qWZa61llhVwUOz9nyfUkwedd9DeSIaTkc2tE9JE/cHN6tmq5s9ZkE+E8sOLj3+fBkTf5ZLZF+MO9QLrNxpZz6GSYzXRnG4o9CNnHBsmGh9Su/8lgztLrwsXUJV0JJvVMJ0Q91Jry9csu/Ygjpg+m9pBDU/MLMmfpxCp2RlIf/Ni6vlymWvah7IBRPa47sSi272GtJcX4Z//HnEN/3JxLHdhoCvqZ1KvHw4EeQpV/j4tcf9l0Qxl3hacmzaRvnPIeWq3J/TSippuEW28MITHJdA5nAIHxmw16C7+Gp42wTe5siLfyT4bQlMWqlONAUu5kpgwnf3aXcWD9CIPHT+MyAgeaT2EvsNopebN0aa0N4+8VIejHuSGOAhhtNJNbnqkq+/K1QJIlJAaBzlyCC+hHQBFoiQucoxzCdIE07skuCR8t54fMpzJprpAy94Ud7AfIzUisQYJgdys0TQs6wDdnh0sB2ghCWEtuN1+YHWNSVZjMLiL9dzE2iepIKXA+xoOBIEvxsXu/Hjh6mq3zup+aiE0FyWN5qZIIUQFgOogtROoSwqNJWzP7QVnC7HnY22NAdQLk9vG2FxXxwLCn10I/pCdfs3RwjCc13yf4SMR4IbC/gnjosiisjx8UyBK1Wh6jYtu8I4CmRiwtoElCsyuedFB7gNA5vgXMCdUZVANBXLdLTqpX7uWj7OhzZYqDQGYQRnUbqw55a/ptphmPAdPKegYpBZIA70qVw1LUB2Ll6W9vMQW0tGqO/VXQpuC033qni1H5ZmFhrbMCKgAkL8ITZjkgRvZwIvI4Hp/X1SE0hZt4G4HmlzDYGWTAMk/8n/l+bdNpjWk9WtIhqgpfUDzKvU4fZ17Eq40DofHL5roFm7UWGAWfFmLfkKqBDpy6TBLB2EYNqN7nQcD2KbU3N5eOkzNQDoifNhQT/6g47RcgmxxVQXsGwM6OJkRxlluwDU2UiaQrlIVtGj+QKbKHZ68vMJVV4ghWIFRDzAfk8pQkxjtexzHZzSKUQP5GEbjCuaxMDTR0/e995e7YeH9DJTTP8uOUC9vWMRijIXzwFoQ0oE0kGUznW/u95Dn23sS79aRKt7RT7xOtdeNYXPlOBq47NSnMIjp/y71XeuO7IZyZUm8PcM3SWpVoeKfHOko/V1J+3QOeBDoVIjtF1cpnJrpiaPmObIVH80feMG471YJ96ItJOsrAlnk4RlxyP3asn6GLvj5Q3sb8GNH5MJcaWdsDM40RZtdAPRF99NGrozpVZFlrWqyxWqwW4mCnVBRCFGrYWwJGn3vnJhQujYQFlv2X0vfu9WML8rmzFBZb09MwLxUza47oACuxdqMYWxtpWM3ehPNcYS14QekqM/M07ettGtmLiYdTmNB453wE/N5z7eP7T47Qv3zS9vJ5a3ewGl8lCoubA7ow5XjWS7IZSpanHO0lGqetP1zKKUqNubRo7pnTpQeG9s+U5ieS/MT/eKhgEtZ/wj4Uq9u2faNbbZ8c3yuqCJQHqzjXEVjPGCEYaalDi73DvImCiAeLagSZS1V7ayzdWVbTWxehlB5guJ2lsP1e5HMs9HdTIrFe4jZs5CXpX9g0yTbYCMEh58ZozTuKlNSUg5yMLCZb74sZDJFNwsjr5J6a4u7Gvf3nNPfQUMNyWe0Vwcq1t6FjSfbyB3VmjJ/+p8DjrKaPpb+4YOyiVOLDJSzZGNfkxAMdWC9s9d7aVf9k/+DAATr8CVdzixz5CiKqLUoywWXMlfNpEtxgmG+JOzSjTnXSyM2Zrvn+O6dYNBbd7Zfg/e5yeHL4+3fwBEYPU8Gz88gOdW2MiIpJyPDkuzSWZgcsA5GVAEKvhiAygIyzN5Ic0ELnLLbOc7GYu1IQqk4Z4Zp58MHDZXFWrc4kx77ucLfYF8dli9Awji2sI6gymjfi4QeQvVwZv1yu/8Sb7QoxE2QpMQHCR+TArP2XstIGENcovNA3sQT+/kWjGAh+QusTTvgXw9VIbqz2ax4e/XE5fMCL3w+us9xQmX9mpk8vJFn5ticz7z4YR1514lLFk8ONKNBfN0Zg5eYvxemXZhvnswfNTCtYrwyI7OkGzdovu4vC00517C15F5vfZQIDWoU0/Za+r5k/UzNWprohbhrm8WyQ83rA3ttEVyOgskVVA7nSyIIZ+VYDvbPpaGhqCGz7ISD2WS94yiHb/u5P+lIMNQ95PgYTuLnAi4sEID5sj8oEX4lHmdtxEvBo1tw7fjXddVnylhHLn4zOlHkyN/NDMZ4hRmTF+IplsA93pAnuQjyC2c3boBo+fjFf/1jJZ+UWZV3KiF1bybQA27/B/PD+BIfSeku03u7afGIz53f9soed/AlVpTkP7dWX172OHoE8tl7VCiQTCvV0AkeqBFTLY9kqTL8hUCjslZ/1ZuvT8h/OV668JHtlPV84Gjaoqt1UJAZyJlTwHxbiEUkyYwqaBmA5IWsDx35jlDZve7kasCdvWCzZ43AJ1sg8KVxty9GHZh4owmUknKfZXicFmCKFxCFkxDsI8726at3k40Dru5u/Nx/cUGFgGKQT6qReZ/MsB7mtK1YCwDa8ECHYhbkECKjQxoBoBPsf5/NgFyP7f08kFGfc+JPyMc6+cEPuYUZfmLuL8bQPDUTo6NS7HEc2z8fFHJmlYfzm/G80NxlC9iPDbWfrMtM5elLzFBaWBW01L7LGitY0Y4zzUjmAd2JLC6uB5qlSZB86OXmG+LdwvohUz1c2fDWbkX49lQ6MfVxtyZe72JDMj2eLuLhYZI3kcwzxdIkAqllzmqDzWZEnp3Dq1m9/xI9Af/kQAizkFRq/gFlboMcraTSvknaP23SkvxBr7hbwFQ2nVp3Lkb70WtnUXw7eAzoao3Zp0fsSC+4lHw9lDNDn7QHkn8AH0CkHnxigWCTMKJdnncjNvjpi1AbT7Jsfq8PYkR/adJZgpodZquMc3rxl3VMLs9QQoRIlnB0iNkbQmyG5bivNSPfRt3DV77Ig4jXaAeRF9fab9nJHT1/e2Z9S7Aie/lYHSrnBOAgsS1rKg088sxAp9AKblK3P8phC8h25O1iXfr7s7Pa/vttL4VPZXCHtqGN9mwtwYyh9nJ1Gnm0pq+FNPRIQsnMpQR1/fZ+t7FQPWQFmOs3jJG3b0oOqJV1SqDDvd/K2empXnzJ2JJcYy6caB40NnP6ECrhcby2h6YVIKxUf1QsGBij62beskt3BctRb9tRK2/6RNKnHP3vd69sqrHG2v0X1ym//IOJeoT1IZJxRSYi7tbwUFpNfMOguORvVwO9dqs/d9PzO3c4xs+qKxaj9dESXh59XCqjoSfyDSWyKhe+vorTgKiIfSVppzsS3DkivCtlS/loU19pCWqBuTKTYhoWdNNIsl6+G3sODA9c11cMIzN79y8MCAMPeonKq7oTSu9NlZwzlg4a5M68tr5cmtdcRtgpg0RYhrTLEZjrAjJ5Oz16dkTHteqe/m7xOycFeOj+F8mLYzvNj6/mvSMaOSIseZnMUL3S/w4XD30ABnxOR6Nmat+O1ixUMixNlL17yRk1QNKyFSwoGU56ZIiocAId1jLbpZiOQoKhZ4agnWV+lK/E5qjzjjStkFSEHoJlUcckV7p03J3s0HryhKd+mUmfVXViNLPloRzKqUyXpBFyV0TTBF0L6KuF+qh7RNugfOgzdc5kdd2YwVY+VpLH49acEf0jO1DpYdh0coCTXnOJucHTbdUgn5U0DK7i7XG0rh9/sTjSRNA/tR3t6PmKLCyae9skw1rBPqexdALSSbcy0VpTdWvpSE3QlZF+Gb4VyDMhDZwKGyKfzDtRPEueHDpp3HFPDRSIyAFAO0fX4R9SuX3WFr/eDPpV8BOsPhoTC1fqpUY7QmjahxPSkz2hEk17QjthaphktHrHqu1xXJyqKxDnAoWfAyP998dTF5j9TaBSbHQdshTBBACVtpTHBRxXVYmAmoMCVHI0rw88D0mWISQ4xflv1wdkc9Yce29og/kwN1DBmJE9gKRjSe/dhiXjVIh1sLQFKjFL7tplPGThszbnqvGB5ICJHETe5wiq/6H4io/iZH/27bk0gIP3v1d01GG22KRtdW6PjBSNy2kB+THLIUoFKFozl4g/Bmhef8VJ0139cJN3qJi40UDaHNyzX1dTEJvUqjiQY+d2k0SNWS3gS2z8iHGj0Yqw++D7CSGvE9DisJyVu/cKWmLDwvkLNJkVkiLur1MlczyQhY9CUP9/mRz7dfk5lvqsz/G3y8ol989Qvf5z9Uyu1IIFAozCrFfIcOqp8/Us2vpA18Mf+kiDlgu90mNQqfPWZdfEt7yKH8d8YF6ytmLH474UaWp23aqgcGT0ogJdTiYG6W0c1Sc58CJeyo6vR+mGUdnBB3y8mCHMdIfh4KRIAk+Y8i1v1SV8kEJZI17A8T8Ci3yLcrcFEpiVNCMcoVhwbcCk+qn+K2yl2mHJ5hbuEZLC20rojuh1Z2i7W8TtL+adtvpS+Kj88Mt44AxzKhsU3kbbXiT1ToIZW/dnXvb4C2VvoJpJ8RXGN5Dls9Uum3tRXU1f4PfFxHKIV1vV0PYtkxR2x95DRNHremDvZ6ErBLY34xoA/fx4G6JLBGnLhU4UK3i/RUEwSgYwzFofVJwOe8nxJXQy3nRwlmoi47POyek4ymHiBQ4D+lwx1zJQdgQEIaBBinNNBj9t7HkfvEyF/l5rbH87dlmNgP0uZKkAhl3QW7H+JuKeea7dtb3IXv3aS6u4t90dtMTv26j01PW54WsvJo8u9pUNSn8Bf6cRxGWlytbsx+5TfjVMK4qlQ62IJYLxWEjFaEA4DihZ1TLIK2LhetVO4q+o4eBl78vvgrhJ6IclPtrUUUfJ6nxVYGaQiQb7sVx4JjOKwv/KpD6daMoaOVjOsulV6xxpnwJPR5++8nuFAm5zaR1UV97KlXvrt5CyDzNJjW2uZURSipN3ZxwnxLMjDXPrVGozrUXXzj96OK9kHQYCZubbtu4x5t2kBStNRnWzFI1O6klO2i8wwJRMYZyJX2DGmZTtxte1r0cs4g0/CsFuYAfgZQvdKNud0w1aRDN/bQAP05xlzI5l5Ei77VS48WN4ksEeLGTNGO8Gm7Zwn6H303vyEQz16xSJKnQ/ZOSVwp5JS90xOwIVNzQHX1lO89fEdU69Ugq/6aZY4WG0YLqPDakawFxAmeugFRnFD1xW09xyU72ye8MPhEw71gx3zdZtRSjcHxSemT6rEBOon21KqAs5ZrybR3ap2Q1l7nQxAWcLhTDQDGH/FinvEC9NkQVJvW82611knjrf2rdvuQex5aXLoXOiNWqHf/u/Yc8wlt7nEPOdIRXxXEWzFF/uUfgmBA9QqWXmv4YTiuPfpzudWz4+18+NYC3sajwQehXBS5WnOrDs0vL0EAiCO/wOEc403svPdeWX2Wku0VnTa3LdZ29Rj6H0WWjxzpNp8s8JJMOJ1IoBFUMaHebMEVb1h+TfVlWqHU730Zs7uK/qZXUa3EBFlFR2Le1zNDy1BTzDnQFMVqBoFEPl4wPqUNnyh1bTS8EdAD1IUZNTQzlMwpNnO9yi6NIv3d1Y57yf9Teff/K1QlNjZnxDEfPSrVjDisV954lrwC7MUZDqPWMntG6bV8s5vl8PJ29uGgi+3Z3VJgJW8JGnJHvGOQCoGl9/zWrMViRkSyft6q1r7h8ERQAGEg6hIMw2Kh+e7wNKwsS9gV3FeITVAjHqHS3E3xkAKcxw45ZVRoUsqokPbco8mFilPaQXnWVUT0abgDkZACJJRAb4+n/ihtPIOINs1YmYOkq/YUBcSs/EZi76HcztvRof6i0PCEnQRgUZSqKrkuk9/pPfM8s+gwbUYlMonegC++DjnLv2CyDsj+TKhcNH+FCtrKPeR3ImkoaQ9TRfV13kORSJMzDoBXu6Z4Rm6OJHcOIL6gNgkUWvOEy10bbWX6GwU9hjOhXmBGkKG550MDCH8boJ87f+DML+yjvZQeZ7RPPIj+wf8n7FYdK3Ga1pn0PdUcAOEpohECeazRHuS/ShN7tc/0eXT/ZKp+27YfXt5rr6Ts8pcaptD7QSvevmPwecIaPt+Ymu8NWzKL5/yXgrK/uwp7+kCt5rpdAX8KJ7S2xIxIs9+6NCJqY5g2/b3+ldlKioZDrC1waw1uXFJB+vYG4iNHOnQPkZeQgwUmifdhHCElurXdJuqPnz9wkf7h3hWT0+R5cabMPOrPxlXWsFCohz986cWsxLWvv7d0zIYFtuC1BEi1Uv+KuXgEfwEANOXJz+Lpc4Tjq2y2K2d3ZMiQi6rmMiPw1DpKJKvC6dDiL08gaIB1+qqiUHvuL5vpP0lefDbfMy2ML+nwh2bsLyNJWFg4L/9e7AIhUb9BsJWBmqgJVpxtNsr+n5UYTQWTQcmhCVDdz9IbLzPkzraKshyqvfYCbHrsTfhUZPLpaBnd/B/tgOV3Q+g85dCkBg0HeANCRea1or/Ae/SFSmREIq4mwVIed7ZH0ZCnDbJBI7zVHycg+2JBIEprHWBS1yAGVIbz4L4kQ3oIqKSIN7sEFb/f7PpkaNBlJDxRGEImJdRZQMIL39E8EM8gWnIG3Fg30WXedEqPgeDN/b8pGlzjSeYq/4jE4LOTBILkgfToxGKHERMEGMaE0UMlP6PZctk13byEyhbJ+T3UwhUJdkIWRjbZM3ybRvNjEmTfVk8/xtDVeO532IACJyLIb43/h2wFx9lFB8z7S9cVWuATdhOEbSU5FIfqgEhVumAeEaPmemoab3j5R1T+fdufiadUpuMq8VHa0TSkWAscwf9Ktu9ONQoANej+OMvvMCbUzkXM7ZujO4u08Ff0I8w5n6nvVkD9FpZsoe4I/MKnBvzokykbQWuVHO2COUzt616JCndr/fJ07E6qyiESV9qgpuJMGW2JvB41SCeTVGoEalzU5tlT6Z3JLq8Yf/Cy2qunKd7Dqz35/u8CjuIW16kOqRxzQeuOE9CTOXuhaybEvYFMaJ1rrhu9pJPDopzwSnpDhHRiLPjb9dx8W1rM3ll546bYuvnP6dOe//qXWBuIwV9B1thXQwufrQaaREyqNJNBM4bP4aY58CPP2gfOY3MSqIz61LA4mp6DcKnyEL57Wu3MdPZcOVbMpEMB+5G8karBRrbA7LZ5MmiNYCuJWTLn4yMC+jzCe6HIns5Xrf0RySiQ6nxeYdIlZg2aO76sZuOjZE1X9E979n4WPeb8szVWI7ZvyvoVbqfs2GeN5N6j6l5bo32ZWEmvc2THzq0TMtgdpP/rVoIZWJuNzKpBNTAmp9OVcQFLNF+7+O3xZMyx0XPrRKgc5fWOJe332lEOHkJykFEkEBSuShNuwJKnO1javWaZ5rYX5U1N9aavu1/ppuPiOcxdIzSnFAvrLEWgik4bUp8QDYqjTnjMyvzT98BShVcgmn42/dRyeFqGflgcRBKewIPWnNxvz0j2f/InSdHeBBGl29T3Oi82PokIRD0DfkwIaR2MKWMnCBGEJ1TvqM0SBuMWKdhbwwmgu/t36JWpfG+6wg7L5siWeKl04TaS+y7AlYaA/w0A+OS1LPH1kZtdxjXA1xRkrJJ1RYtMzGoh4njUgMMSJHwRcX5ySFgQo2B/hd8QWhOr6dXYcQaFMSHrlH+EiglQUMOAeSjqqTaBjw90evOhGD4Jo2yROfwz6ZXEiE18khbNF7mS4CH4pwGBVKhn9ar9dxmMyEISlcQ8DApr3rp3u3NzmJnI6+T4Ste1TCK4k7LDyrg3bepfEqaQtkkfYonmUbcR1cfE2XqOQL+4jgFPHVqV9AfOYFfPCA0QOv3CvP5e8oU4Ypa6ag15MZ/Jow/tHnCAdbgYBakM62owe6QAuMfB55yAL4lqP/cztHlHT/yScwnjBYxhORmhj795dEPM2z5XSMUJ5PWg+5W0z/Nfacr9RhKkCndmZBdrVPE9K4T0JhfFUd+bW5cIOQqkjtkzk7NORdW/xh1SOBuT5EISI+QuHEYddDtthxQJGJueb9l0ynp4jKwxcK2EYQzEXIDJAYLnDwdTZMpS3GGlCfdjkbkRDjDJT9SVj0xEXZRSN+mtQ/uDm6a/8/GdFcB5CFNwm/cwIl+z21PuveshI5YV3O4QZqB+qr+MyTbkE+Sox2420u0YNqwofuPeDuMrsdyyHC8qH96Rtd/jt5mBU1Q/jLtpYfUlxdUGJt3O6UNdmAnrwlWqpQl/6coCxErDKw/uAkpTkYWmfpYvXiZbB3/Nt8Ca0yUdaDeaCwdCyNaF5xDPt+qxoUNcRd/T73XG3V82H5vWaEjk+2QJnKRlRvz5iCvX6NxOHPb133TpB9bfYT08N65C4ZEQkSBHzTeh0blj+sows5tmSqqu6NrsFMTRlIHlCcecd7O/vHKBOq+wsBgoFSBbjh1mjBNMvrUqJYuVkKClv9vNSqKLbMzCvNYjJpqWUTmBshPGIjfx6BjsMRuAKURD2kUwGXhSQ7Sz7C3UJ4y2Qt88A9dH9E8m+Rnc5vmnTETFFHM1u/eltQvtBNbiF81RFeg42l/fo9A4IxnIh86CCfIDUKNjouMJcggl+9ukngif24h2FJaxBLNAYGO2MnjNcefEGefNxiNxcmk6IPvjH3ex+YOijd2Dp+JHm5srmTpDr9xmEiis9eAscd8EdcrJzDI6oCc/6DdSp6xLmjcHefHHszRk41Wt8iNGKkun5DM1ODc8z08Y6GfmVua8mAN9VI9jtC39sba1XJ35PZyqUqIfhJibA5yqwPGXmJCFRS3/tPHvtqV9MobYtVyeKVwHE4vf03OfJSfWWg3w45ZzNxzwcRByNTJ8+8ZrmWa7/a7mKwF/c2aT50lh/SI7x0OClfiIV+H2sLwhBNwKIRaj+88s3W0qL9a9WiGTxvB3aF3Tlh+S2e49eS9SC6WOf4+DvTiHXsBrMQtVrHTJZe98vFpzfeicXiehtTgG4veA1C75TZAPzjVLUAySvUh+Kz91QDmsar7ny5C03NEf2GKNn/oepiFYhgu0MN4mkWJ2P+JU9fgx9eykIHWX3vjPcOCi4CYutfeUr6E2i7OFcr/YimuexToQPieF5g2msK3bMKOcJWJIneeiX8FhXY5plpO6384Qm7uVfywFB7vMPHsd1dzzk3Z30rFFsFYyA3FPKY2P0/XcAhRiDLJ9+yZ/0aORTzyRnLdxra3xNpmzxiVlfGML+HD2IjX4/EmRkaDZRsERorolI4pyQ72M490s6S/4QejdjF1O7kdAHcxOIxjfpbTXtG0ZgviTefPeYRakJKhiXf9gyDPKhCSc//CswWnW1LgZ5tR4mt3JEX0Zs+HUXODxUOBDGMrYpGyzRyKO6QRmLAioPzs06E/ESuHbTRhJk0k6icRGrSmyxGKxyFlukSR8cguoaGkTm/v6eiH25yvrVoxMZyCzYjn6tykKZFGF+YmJwU+yPjzJiIPQxprIJaSdQkem4X7QjewAoIUSedm2Ze/TKSxI3m0t3Pcycwapa9eQ2kafcg+foW8lsTHqH+gjJQW0kX4fK7gqSG38GTzWmV4Lk9s1FKHhbiYcfR6w6gRk10ELudRj4CaxTaFVQzWdOeG6E9tsE+FEEkusWVazzLyu4WVV5xwRhCUESFIwpKQ0b7jO5ZoT6LflyymT3S6a4a2AbMsSqXUjxyen5v5zg5YInb/f5jzA1WcgZKjr2OivReLMeMetEe70Hu7CdznnvXTx2aj8gmgU/dc3nD7+Rfeo4lqImbxBbkITKBhrMyywuVt1ErCzcIB/lebb6QJyXPXhcbH8ibN7QaN6SNkYqxjlcL1pyTCqrpiFNY8eJcxTMVBIVVr0pxaaULL3WgtKnKXhKnJGBMtgI8kVjQVx6gcFUHt/BPLUAgnC/VblnCuFhTKc0rgJo2BJShM3o8/QatoLv6+UeOr8d/1WV83Jmin6yHKpEz0i4FdF1DLpJrRFBJ1FBBLOIMLPBQm6Ta7wwhZuuReSyiF/lb5WL1e3KZhfKleS9rpjz3HpFwvWLY4Pk3y0S+x8dTSBXqgyxYI6bduqcm9zGL9kvlPzigCe4T09mKsbuYyudxa4GNbBmDrOE2qoiUeCsUhfAML3wCcspog3nZRcsHLQul8h/Jfrdh+0QUZ91BnUEGzKTL8W8jj6BiysTAjmDpmFBzVx9vDztWqKHxVEx9IH4rYpX7oln5sbMXLedEcYCWGh41PDyIvTvclMeiGIfiB5VbhFhn6mHCkcbYrVjuM17HfyfwX3FDZBHypt0lizSFoHjvEOxcc0/r3pnZu7MhWm4FaAXFfyW2E9gkKBjhp/yxMfRZrEs/F/Rv571kl6O5rtqxJS34C1+zyHz7UtufxbV44n/8BCm88DZ39GIpCwkW0YLFM0DI5zfZeyVQp6+70U/ZeGnlJQr/3LqLJDWgRuH2U9ZYz8w50zaYFuH7buiUYYySXIKBuxz6dhYbEzRpMSrShWtybnwtuRqtJOLyjgtZxjakP/I1arXt7w3zdZKxfmKeVqquBJ1hY+n+Apv4U3pc7/BUBen8KZui+NJSwc1n6AIOe8TVRS4qT7eIf+EV9Y1yzNxeelv5TdHtLt3MDxnoF1XbxRm06ciDZgpOih3yLGiXOxbPVJvUQc1ITmgowE5jRjEjMwOFHcPt/kfznncLLTqeNezngk1I5EdlV64O7Zef17TeSQx0xpQsYm4dER7BDUDOu33tWL6ldbRurwLxbwqyy0yWiLXWWae8bZTIMxb93zFSn8cyb+gGYEioTtQItZURDIHhw8bU8iXqdypQgcGF4o1HQq3gj5H/6eR010n++2R1DGKaUIKz9/GPIXyduSuZ3R8aZtQXVaW0bxV8Au1/zFFWrjBeoudukRLhCUqVXUTzAAbKG0DEpKE5H3vqzEIids1Kr1TlALp66IBLVUgDL1wJ5MP2buxC22S8SOSKS6klKugv71xuBHFUQDaV//Bd3SxZInh+9n0dW/eRaNYIGZOxA/2ZhE+yi/w0wdX8jHGefnetM+LBj7lpoFu0nKfaKcPc590IkGQVHvdTm+f3m5V2NP632i3f25K55C5SCTGjfYLZnAFdwVOwFB3AhKxGO1Uil1xn9s3VA8L0QRDwiIXcec1WJLPSJEtXYjuthtWIvVVOSS+/AW3xRFbbnclSNfsQO/GPL+X+mpOE004OS8p8H1eInsf51B9myj06br5Ia/TajracURn7VsWQLnQJg3fd11JBHJFgm7Ezr4ipS4qD2R2Z8npn7s4+a9xXZrT8xQ1Qyc+DX47Xew1bJWU5SvAn+iwukY5R26sojQ8ObymJg9E1udBMglX4pfAOwkloXK0Z6eFJkuEjCtI8w6Xs4IY3TJmQ2lgEaZSAhCG/UERzbhaniKFRX4SSTB9MSnZmv/UsK4mlUnsBPQBFhep4WfAr3mRWViAq27vdTSwbTnjzqG3poHHwX2R5cRjz56OheUH/KsSP7Cu7XJuxJe0WzpuINIEwSrCtN4V8d8iK+V9O/BbkT8fcZsg5LbGMTkvwnaLIFJBZz5Lt461a8alqXrAadRs9JCvsoQaYVttqTfqg8HhPmGY6/Vcy7BqCF6ss8kp6NopXVHEdxdAF1KFnmNbsYeBlliYX2FIN5HE2Y4PM1KbAM5hfNAX8CGIRPF2GapXIeh2DBAwu03I2wlM/tGvILLrV04QwacWsP9OZz1x9/hSTb1a2t1VGOVnayAec++fCAQmkILIFR+qcORO8asHKaZGDa18qNMXRPFhyi0aRJlkmhNLww3ZaHWSh2mbWc4gFife+0l024Cbb1uYVuOkGxYcYQRKpUUBNFKSAtSDh3PNSLy8Am1pH2sARaggihZhFH9RjIkcVEj+ggrIBg5XyMdp/3d3uig07Ugz1AjR6OASeieOByA7u10YQg9UB3yGKxg224TioJ4KzBM/tYnMku/7nWNIQjTdTBkjeMOT618A2dRIuV+oAdb5pk9GesnG74gan1uL3j4QTn31yEy7LonbxBUqhn4QddL7RD2BK2OFromtcLXFrx9dyRvoJ2tcR8f30/rpa7fqlm0rJ5FngQGmytTCxaaLaXHEV4dv727qdfUrMSXh9FjwuwJDcaVT2UN6RIVfqEaGKR5fpG5JSheb6/AgndqcW/oFPfVo6k5/a07xgGCJa1TkfGFtLbrEp/beK/pJdvY0CjbB4pqI5HnK3t9iqAcgeEqkZFVW7rrNSEmx2DOOv4KkprwmurDLcL9Z8gqKirNVjldzuw9nJX7nlDrDh3d3BGvteDZ4E6UtwplQfM/wldfqBXiq18ICi0dZnC+xc/AogzOkCaMT+DU+TayioDyKlubS6mza2fu6OjHtjvRa6hekU+MCFFz0tBTFzx9+cYDkj6VrLFsk593TZwliF/LlMrQscO0k9sKt1aff4/Qcb4Be+vPSe8441tPy3AXQt6lP4XMJo+TBbcZ+P+fdL/RrgsD77Fn2uf50r22o5om+lrKs0j429IKsOq5TpR7TncajYmVr94fGQx9npsWi2dldezb37SXUeOOzr6E/08PAGvOVoeR3LQJP1UM8zQ8JpGAq097KL0UtIVc3G7MtA56g99e9v8CbVOSSCS0UZCPcrwc//tHbol5HlmNOJC0oLk7Y9UZT5qNNdsZ0UFeA240SSPebw7NDSvbswYtSE/EdCjnrr2ZZPpSAiuYHn5RXviVGkEf7OJx6jQoYArTIVD+NHv3R1aCb+sz2BShTIkB+eIfNoB1sgIqgbJ/pB6JPPoQ2mUWHhMJLc9CP7yqXi0mGxxkXO+pA+Aex0B0c8whlEFK3SZi7ZdN3Q3Pd6mcL392hzWfB+H1txu0LnqkbC75W6lAA85RKJ3rQJKYuOM/kIz7dIMaAEHYjLrW6cJBQDCp4uw2aEDyKg0RNREL3E3wKllD64KUL1iJW21YJh9MqrZpl4/DacMWtJeQScck5aHvaWlrpS5vQinaIi8nBrjKFwlwfs54dGqjZk6PeUuZP5LGQF6g2lOlOwZuespbW+NKOayUHrGNYMO6PMDfU+zdmqA17crTnRPlTeSzmRQrOa2hUOFheMMOT5xh1zKHkYejOYigEFI9qreMKzzQ4bVeU97hANmqzLixYm+BOSeWlueF8vPuPL01LAPAy7Cd4kIGo0AIds05quY0ZkdWcP8znHku21HMJMUMyso0zi106NF09wRikzV310zGhFCUWc+nIq4PmZJcAtjWPYsZnHOWgexVU58T8rJ6AqIcRoD+udfJbjKAqal2wuuBsLQ/7IPe5E8NtPuAupttWd1Xl/KfDeNScagC59QGsGWZPGmgpjwBz/cDkZIrMETVDnVnMmHs3Y+QvHCoxIXRRbqB+9IAuxRXHQCPpnszWTIyH9YbEZrdagQRdG/vhuFdLuur6JMWq3XUPiw0YJ677HK0FUDdOX5J3sxpYtZ8oJBzl3aYfJ8Av3TeC7mfDgMmdq57lHAH3mwgEOd9IVap8x5NPr4VCBwC5xI6eAFG/gXGAbQmBoRXWoSU87NylAgbj+85HP7iRuXlJq8iMJYKew8UvdYqLWu9EsnMHhxxtzSRIsbJDPN88XsCCdfFeOgzIk+1TcJR//rGUesDer2Xe8uOCqL6dm2UhSMSZJPZ1OpTYPqzLNkfdJyx3Drk3SYN6WMLpP/fYwZ6ZEnHv80DYShIPt0pENeO1XzHzdGP2HnZlooudbQDC0wGuY3nuf9xR3eRQyHyQ+b12gHPDNnDr49fgsvkpCj+y3Eh8lqlizt00A+GddG3qysFt1SL4ktFsYPkLGmaLOb63eY/c/NWZb4BTww7tJdJNio80WvBtZqnl2mMjFskuBWf3tPkQwQlciI+Rz3BdPAfAWbdhnfyNiTMS0zPxxgJgVVtruUTf/UGq/W8ebfMXh8xj29j2LeprgL4lT7cEn+izBu4bokAra5rA3UuCs9ltxEG0iWU18cOu6tNA/YmwmeFx3yTA7jFqXFSL1YNbGF2lYupyX93sUpH/RdPf+cl3HcBO9BkJ3wY8cMoZn4ji//HqvPB0pijUA+4ej13IC47x97djfJJ+PcXO+OSNIlzR9qF60+fffbP+9R7zJGB3rU5AmIZQRgB9x7YNFdbas/bVI+5XpouPRSM4hjqSNOY6ILRAtAx2Jho8LNevKL9oVp5hNZ7rBvlqhHpFTZzw5PPLYRewb94pKUfFN/eTPvnIB1wA5rPSBO7gs1MtTLxF1WTje9slGHRXe7ioFz+JStTNW1A2Vtat9riWG22UvLKpIYOm8mvwplCucQioW5IjM+jPKPl743xzKdNRu3U9wkTM15M4ZwmMB4ukR2ugkkQReA2Jim/FBk4/wxzNXkJcMm27Rl4eMyCZjWjP4HrsZrcoA/XBUMMR0lQrCb69uCTusbiaA7fRE//Vqhn65wnpdq2Jbd3vx8plOkzfd1e/BNW+VDT2ZnY07e7zkP66i58u0NGm2qYp2WcdB0HYIyj0HGeX38Tt6jj+qUr97X9OuPqKLvn3whUCXR4PaWkhx+MxdpQbqM5kcy0/k41NF82CumDRcdgP4A/uwLzyugm437e1y03ROWWJovrzdxNY0PQAOSE/nmSfUeXy9tL2G1QpxFFKLtLm5viTLlOcHvm/UZrHPY0Txh6ogNLpIjiB5Qt5DUBl4676Wlvr1LT55n575QUszXz18V85c5maWE8w/UBiVHoartxSl0ux+qzDtYVFXnvUi4BN+wnE9sCqTBq8+jPs4tjEYPwZoXAsM05YbpcbhvBc4jD5zcmtmXuAz1en2yOv7CnL8HD3wr2DavjuFpjczOHQI4JG/nhW/91ZR39Rv5eRIA7Nu6CdCTegI1XezohWiTTSyUKV4BU6M5n52cZ3hUOKESS1hbzBZ/jrZfLAcm5mfrnPQRB9b6SQbrX107iv1+B9wE547kwVDqzfbGPdgfxlBdVhKFdKFUr8d/KXXHzaxTWiYD3Z14fBE1mWTFmTfNF8KKA0a9F/kr9PXgIiUv+YsX9X5+f26KWPZzONoOkNjeJpgGx3N4pG4IgMmRfggCxI81O6Q0uvHn9lR7KecXvtQ5BdyKRjUJKFvcV8Lt///lrNB3sdI7d77hdg6zP3Nk5+A3IqBGGpmh1sPf5KFqjs3CDfT1E92Zq5Gz86y45hTSj9ndjLRFqc/04/84rnLPVPCqQlxb2X7wGavly7CrSXDp7l0WPDU8WVRS9oq1+vGVV2z81GG6obQEydvUXp4QEfUvynfNoUAC16owVxHJcR5t4kH5dfXb0axxGl91Jbs+g5nfsxQ8YUJRHt9mrGpb3m2AioxoKT4uLrvc1XSkZ/YJqvC31nokuJC42UubHOQteweQeB5AHSD+F0cQ36AvlNkXY7du7+MehI0GM05d3iin+bBjBMs29ykyeRBkWNvY7gcfuYLb1MJD2Bwt+4uIccpfxjk6izzwV60klUP9jDNg73JJLkeKpg4MVgyX1pwtszUa+Tbl3snQdQ7W3QJ5TCVFY/hhQYs7NKA6bXDYovxOF7B6XzZCuWN/vuAYt7opg/Ig62uoHNI1/WJCkmA6TQIBxCQ1JCWINGpJjwmgzuOa7lmgXgTz+rwyIj0ybdo65u5tQtf/yIWN8tbKqOPnjNj0ynFn9Il/oJR4PkkurkP897ZtLxOCbppBLymulfBL/0lzvaWFhgLWG378ppOOVmDjystpVv0RJwXqqMt14Mey1tx9hXe/km7P4RmX3Ix417sR7nFHbz143irYeYY4+BtG8qnbbiFVoZ/gK1Tsfm2dzJqulfALuONfDHROY7rjJp/otqzzlnjm453wSiCnRD4Nf9lHfHdfOW0b51x8EXioDkTxHHxmdpbDvAvItF/tHIesjfALMMM33Yl0fw07gDZVGW6ac+Y2gvZHUdc4PUlY/d7SjPhFAI5cFeA3jQ1/eYvNXpGfHTNgDVeLZDxKceyC4ssF/rf/PYrP8uLfCxHopo4vCUZ20a/L2V5BSRoy+3fTB+zaLbejf8cTXwsRXa5R9wh+P1AzyOrabxNe4Dkb73QEvmnhKr5V+8EZMDX6SFlbCTNHCBR/VhqGNuIZr8CqLYV8MydTscc7GuokftmRjLUnuvKdGLPyWZu13bEjdXthMkrEUs3gCrnrAhbZ/4+4NopOnrGWF7LlpaMeEQW61GLyuLqnazoo29eClPIVHeZnX9CVmm7t5p6feloHyR+CmaeV+5LwDVQFsfn1YSSngfdsSFlYliZz3H8lzH2Yv1EqqQDiwqTv8PxXkguxGcb67IAiZbhPcnYFp2xQn8R9PU2692n3EdMfeTQBatJ9QzZF3KLyE7IAx12Ig7lMFNv2onzRy1+WArm5skbBaGCkVNa4Fvr8jYHSmfOUq9N1Fa5XLtv9Q/29/oWvcZ1U9ETcj1qPjn5Ji8e1r1iqeYuraO7ZDW7x/Aoyaw0OgrgSJruEMJ8lCeAEXKB+JwQABhrgEROOBqlAqDSqd0KjFMUhjUOe1kps6s0Bhoy6OVAu6Nf8S135lpSL76VS+TUFYDqZ5s0cwEq9XzEWcXUu7r40HIo0G33t2q9OqvTY9WuVtVXgP27n4i6w4Ubsp2PoYm79+GXCXPLssOqHMEybnKjtBw2YjIHHruwkm++pLXedSSC38M4AdoFodZbs3gE5hbZFVcTVaCJfL9cXKfo8jlELN9ikbxZBQsJKCi+1CzzUcDh6Oxlt7ZRwKbEoBh/GVLbTHS4rwDfp3SzohOcmdkJ6UTVLQiLdzL9ehOX5pY920btcHRkdUCuUa9YTXehNW/CqzauiG0CPtB4KC2cLvfeYw8LN/nonTGlU/Sbn+PJjVNK72HcNfVTHWu68bslq4NczpkWHjVvryxzsmRI2s//hQ3Z6/p2xrAoY5YMwb7Ws174rMUWXC3XSEWvVR0KX1lZP1JT7892Xip/S4D+8wUk3ZVzTfoQOCzjb01CZMHSOXgXv3wLVYz57guVl4MdluhA1YbQzfKfY3ObYKKt8jPB7B7b8NSLJuTwMi2X5sRe8lRYlm9G2VVs14uAiA3m6eOMXdPHovWP377liemzqdBqdJx+Y1W06iSccblAJA9KCBM6/CYNjqIqcsZaky5fDTYu8x3Hdivl8LCo1Lsny+vZYzNBPz2s8aX5O/2o50XTTUX4wX5QiSvfW9M9wex+0mj/6dKTcctldq6GpasaMA3fKK9F8GjEF8eMMXjXqXS1a9LtQusHStm3oH8ms9UjcO2UnfSYvzTVvBx0e2Nq71VcHm7hDaG4Z8WWRAcrtG2W2qRtFFcOYBm7bq604NixvKjm5sPUzQDfvGPoRFjfnzbFEr6hJs535bfqrH/Tt9ciMXal44yi9qSyxa26t0qwGiS5BRIjFuONwTRNRZIAsriv+/SZ+ixiBb6kqvZuPP2IzURA6jSuAF32FaSDZjRAoyre2SEdRqHlKY7d+OigijhZM4kJktrKodJPp1gosNM2L32rs7YEz8vPaWE9e5oTv17wyst1D5ekvsJwUPlMRo+4on/ki3Kkxd3QsUwvduGtb8uvJ/bUV98KlQw0QEF+R4lkrrjpm4BSO/BlIgML4luZQe374Ft0uApPFtrJ/ZL2Fv+TgB0JzSPtUDWn3erdj0nHLzbmfpPUv/FocczvuzA4UPvamxc6GnXS7OO//TbMO3c5lgUEkD+7R4ZDiHKgziVIxnA3ZcdWPsaEJ8kpAuOxWDjOO524Ymbj58EAOXNUxXVf6w/YIo/zjjgvRnl0n6k+8T4CpCUmC2v7B/1GwkNJMGTAeI+cLUZKfGhbw+hTqeoWSbkFJm4Bo/oR0YDR3QjYMlKjHlgXo0H7firAlmsR1jPdo3HE/FNbV5lcSzTix9h4Ahz73dM60fAvO0cLCiuR6MpRnEdHivOfw9ulS9HS3jOo82yjwDA09TM3dvDpkPJpIkob9BQ9dHtItyzfWS07EHIr1yRNbJuT1V5kUe+RXHULugeu8ajiRQorIPcVX0ddzx4Z4QNjukIUUV1KT2KpDuubiTO7h9lZZ71X6UDL7s7nogOnL1pQWx0XfOEf976LpTxfMI+q2p7zS1fcU2i7ud/JcPnwSlpbRKPwY+grGoAZ4K9J8/YZfKSjtUvxeIM7lclwfB8c0cmPRz5i1mWzfuxDVelFJSZUR+ueAP73fZvkDz1TgMOd03nvJrFRm31IjMaKUr1XYr78T+/8zqumF9OSPEy/fthj4JpmbYEiGPBu0eG/bKscGNRQheeTGoz157hxFTv22zRvSeox4BpDgpPYjiBgZYYHuWk76EkMVh7lPJU/L+AG1LfkS21ZIu7r/IyweXGtuMgmC+w1cMHMe3aLM1I/RhN/N2VRODs+iRrQnrhGDIPj/NEL3e86CvPA+733vC2FtYfITud/JjoO4Hmj2uG3xT9+OjbkmCGZf6JlXdPHHTn0v/T5zu1n/G7L8XE3odGO9jjfEWs8OeCoEHcMzdqLDJM3zTzhars3s3ix4KYaqD/dwFZNVuGrsvWLO/W0XSgRGT+xJbiZBy3bW+O1URRu6YL3O/YWLMXDNkNA7Jl/DHy3NtOti3Is+XBq+5qpQqpoRsGzm6gtFJSPSnkTJz2iq6xuL46nXXPw00b4WnEVQ4s2R4zw4xJOhLjT0RasS8jxns3cloyoOWINZVnm0a6Mw3cJtiZkaTetLIQHITpliF0EdZY4gByMSOjU0xwwcJVuEcrJOFIYJ59ctmYODtvhDdrBZkLJ0mlmYaA/0jesNg6SkFzTR9WYlvyQLiFpU1em/tOmLst8AnNP11IEi7JnJVzUeGOxY+PdpZf3GY/9tzO8Krv3Cxv1qWdgVGK03aTjfNg4mpN8I0SX2PNcxesxWc1a/p6RxP+WLBW8BxD5jx9FrDj1mgSbe4rjo7V2Grg06MNS1fM7dLti/eo8roapv6izU5P5LUcwU5HwN1PSKvV2vuKC0upEvAG/UK0EezeCCDkhxU4ujI5XrbAM+7ZkZpjTsd5o53s7WvAYYsctj5ljcOEsE2DLvT6i49qpdMEYp20WYliNMZizdgN8gfszb5+7p/jN2di0nyCShg9Fwq5p3uv/LY4y2J8vGNx+tmZxiHa5cCqpxFDoUh7ZKkQOyIkn3OhjXgpd+pVhY1krst0F7yuoMnUVLb7fcZTO49t9PTETaBfpCeuahVrazQ/iT3IX56G4A9BRw5wjfVZVDvvRxnXXPBbadDqJeVkuM8deVnc/PBKvt7Eyq/p41R6DTU/BM5RHJmb6IM9feuhXYXs1w3XT1ZXu7TKg2hFRTNzguQ+lXAtA41k7MIbALT9HpYgbzoXU/YAaU6K29Utklu04q6jlGZuyDe01a7fViLgFrnH2sNnqmhHVdCHNjBeZW1MKv3o1argkWEteev4krxpJZ5dYK8NLJYni9M8etDbm3y9uP3y+m8p1iWkeCTUGO68PXT/rmo6NLo5qCsSd2wNvjBhbcW22yV5wmkZzz9rDZQ1hOVMe9A+K3IDP2BEEjrULwVMhrUPD8FDsSOAUdM4aMtNxgips1h64UcOf/C12h7a9rKsomHZf2yBq7VGpV/fzq71F0fJAXw1vI/NYEtmwvbXr0c7GTRLM/VOLp05BgIujW+0XsurnpECL0ziPj2I/rDhY//g6kS2c1uXJdzLM2fRTVvhwAy2LveJMfUFtApgfT9VRJiHUFrsE4lCcSbb0SQgkNV+lGGN9rQ24FhZ7UHIXSUJqn2zAueodyvyexoz6WViz88/VZP8Njndo7bIRNJP954eQCVjbTWzTZlLZz/m7VOvvvsk0mpG+kD2+V9vbi9N7JNYyrm/bIb/jQLLFoIZqU5MnkKDgo/+5//rvILXpmxHdSYiN1GgwThsGAbCHpJ9AorGy/bp4eocJ/4lp8rUWxxt7fnTV2Mi0Gx9SNwpu5TthJxfrVc1YMqSmGZBm3sa0NrpPNRT0wigD5ImJQbZO+aijc4BS1n/rYdo2iyu8tUZhvGGBoVXiliMtuEjyOlrIOw+kmgAJaXTaKgA/1yQBmzmikz9IOrmm37dIXV4OV/CCyYXfYF9RxKX4Pp7Mhznf1uB5J0gb1p4+tiGws+H8vXveiSZnXx+gG3gT/rCJIdrPMTPKtKlwxKThlFGR5fA81a2qcI8EQeNyx7O8sujQV3DxcePigDK6+8uQRncm+6yeV94K1/xtptZPJMH105Vi1qT2QUdFczfvkhWLNValB1rFwxZ5ljNB9VKU6YG4UBUk9lgDYL1pmokYzep7EOdG8LX3gt3likcjixZb69HMoZI5WE0Z33smosaGFkKMkZn/cuSfycOC0Ov+1UB9IahEPAFnNv+PtY5+r/ff6S4mQqh103xaH73qESwY93NhksRM5YC98NxnkEPllWVBEci+dDqRAdaHo39hF15ARc73jY6X2GvaIPc3dhi+dok/ReelH+aIzhXUT7H8cHauyBxcQZTtdlY9OvAqPRJJz//x45+PmLxqAV6h3OY6yaRjOc91UzeWVgI+4+4+rV4sBdNSTQY89na8oIbsXyqPWay/xtZTWmFLuSXIlnPX/bhrB63ZhAswhtLJOafAwGDxslFkgR1Cotdjx0R128WH3n71w18ZQcXbehSE50E0A4w89Yz2BnrDZkbWBPYlbGVZGXmIfYQQDt6X2FPmQo9v2bWFXkyWojKw6UeZ6ztbP7tCyLfRHs9D7t0lo1ZiPv/DBwq6iQwFnPTdYsMgMZ7M7kKbVQzWqdtr96eNlDeWG7CedHFKzMctOPx2OhI/L8upc+zgPiPKSlwfzTH7cUgc1eKvFaLUqdhjJlcXYl9filkuxVg727zjN0q6h/ZKlBzS59odCrhNOYTqw/Xg9p20SiDFunCrBZLNQL/XlFoNl05a7RmX7KsOt9z7M6KIAxM5RBPhCO3aKM+ORnPEvHZOm25Mj1CkC0TITsggzyCs/qC7OIhTzl0BMy9jlq70gCBK2qwmpXxBcwJIFwXTXUwTAayKOt8dTmwdeKZhjGVYLtREpoflEHffCwcnHSsD0Wetiku7ML8fxTSaHz6jcDSc8fvNxV9atXLObK7u7CtAajtFW9tJNCWnmjPT0wXc8PPWmfj96IcTw+mrKoKx/x+CzqDIr1rn43G7ZIqyKjzGtbO48jbBmZTtpMB7RMdtDyxe49ZeLW7ySMJKeUoQzALUbaBtx3Jz1R8u1A45EPXwuhQNcC5r84+BkBaYgsSglSp/WjrDW41yu47sz6rEzHFTGJartyMXEbSKSCUhE6Kw2yvM/CP8/bIsqQ5c7/+H1SSF07mC8byN+Ekn7uPy4K07vfBToycimRG9/VQx0JXTjFso6tRF3LF6UlipN/m4KuSgd4VHNKD7rFZDwfdPWCtJRAsEs0tzeKtC7VaNChTYcE5O5OEnuekvKep8XwCY1H9fw/UBlJiR6/ThRFXnuabsbv4Rk3V+w/qRNEVg9j9l+MztM0ucq4lDlcAGTXGekxOLNFFoaGEy5n93NbH/ze4o05iimR01jWYOe69L4klr01O9036EmmjWQollUyR0GW/JGYMey9LcFGb0eFe3vXF18YDU1Ur2ExILzxBog4rJ3l0SJTnwJLIog+IXvHgHLSggQjbGxBWH2x6Cxflb5HXmYMk5H120MCU2TQE8XljkRaN1tGvpgxGBaPxpa/Z/u441GvKYuJicrJlmPA5nl+laztF+Lw2q6+YaXdeJWoTN5O9uzBdcuSU+YXCs/Js3JYivCwwrKj22eh5esk1w7izKfuF/Xrj39quBVvnFYSYuO7w0L/JyyDvSKiZJfKYbwmhA9jcksBC29EWHHHwQCZz5dOZVNT0BoBYYREyuRm5pVqwXkR6/lY1EWDBbO8n8wnjMMpCODAJ5hwB9EmsMMidVc478tHGC3bMFJAKlbvdLM1LZwvRxdOrq8BCF2cRf2hir+azuHoRnTmZzIj+ieFiy4iDQztydLdvsKDK8jjqWO2J1lk3sBRFWQPH2SVSS/8ME9ew7MYHYugD1/YagkvluncvJjL69jshThGyKHX81a71tZC0lQi0tWguW28domT9h5jpHMAErkEjLiK4AMosMbi/tAqvuAv5t/y6Qp5o0H9Ur3QxYipAnGwqlC4x12ems7dELKETJyHPiHB/CNtjjGXwxdH22AvIM1j/9W7uFCnsRJhigB2LM8dj9MfPN9t4/DkMG8X/gKOvs1/R14x+kjf/uevQQsC8nhIDkHW5Ogs/UVVO1N+1T7qlKMrljTG/pucZG861tJDKCZJLLMKCT2984e5PtBJM8TV7m08+ClcztkN9IPa7IkShKzCa0uZxRd/cH8nt59sw+C8INI7rSaVaxB7D0LVgyb3ZBcZK+1CfgTah4dyQ7gu4QVnoABqRhsF+pyQ2P2qFg6sLMd4Fw6QLdukJxyzsJUHvnx28hHeiMmjtADF5xy0dEHo+yNHh4KHYhcLKPtznRIF1eExpu+nYTAVg3nnSdpi4m2mnNzIHUOEunIIb+aSin9AJmw3zUhpm2mXWMxMz9V3gt4evfdrxpH34QwHKl7trL5/FLTfMGaVoKD2sEHtvDG0ZOxkUbE1/9FWJ/gMSVx39tAb3S+KnzXFgwYcRRAf+wYkMDd5HdtKdLK0teoxPoauDnX+McrrQ64Gp1qkbQGErFteMcQMp65b7eeTeUHnvcON+uPkCqH26Dae3RFeEIJ2Jwq+X3muH+RstjW0F3MZaCNXWhnV247YWHqbPSzwRPndH6BQXheA05DWh3l3OxA/Hn4ddqNU9kTup3RL78ducFnA9aDgnXny4+3LqyPd2Jc7YaP/M+2jHyRComw/Bfcg0b6fnm6f5DR5MXRGjRpoE0nKJewueoW4UjRakuek+l/J+KP9nvm07PzmjwFHp/wCL/xQr8b5B+SptQHmBY1UlqGzjqmgpnx0totCT0+ms+kSVc/vsWuI71a8dt4mB4yHtJ0MLeHef7XVOtd2SlG71NQYc/Ii841SqHecoSoDgqJ+BRSMY6YijS1BUuV+PSS2jbAVrQ8irTbnZjih3Lvfvv/3CwLdMazkpn+iL3GvIvUq4NH1qUL8wTx5azeGOYKHtXA7Q25ZEC52vqUmMDcQ7+qh8rjrYJlw5xzvNDXLo2uuZws2jPBpDn8N6lEIpJha2s0wvcbDzfKx8ppd18ARlacMuqXaG7zTsUnR9IUWGHk1ypkyxoY9R6IZFgHPdxEMxAQk9QjWjzOd1tTV6us+rvs7Jw1Q1woWBmaXR6KY0fUq+z+e3qJv+mM0ZaEY/3/oG/TJlziZjvf9M32r3K77UGuylpC+D1BCenYdK1XH1RmZVFnYt/a6I3e3jDIyIqgJGHbkEQZejLmG9z8SPRfvnhLWyygHubTEtxDXonBN5Ghpiq29D9yCIEnF+AIjsCA/CFDsCR0JEcrWaOrnC+xF/3E+LHFvRTZ9tNXPzDB5W1guJskPjX/iZ9HAvn/2CfTo9svv0RlPpiotU3ihOaBDDMshJ59+16V8z3/t5nuQnwqd+oKcZtFQEyK4t+Sv7jebYC09/ohlbstTWv7PXfWEhMnLHjxkvSphZgYz80Yyc0DHij5dPJobJc+80/EHvei76xRItoHCJVpg2lPU9gAeoRlGrlypG+vPkN3wMA3WoHbB1decTh2I98KVbNvlJe/lzPnmGmMbuW7sXdx0868mzYMwUu9vSmM7n/vLQvliqw+vf/O8DO03y0APeyAyt/AJkvsvaWnfhzEm+PrlfWLatrSxXM2NizbenLHsBx6tWO6X3ga7k8vn7ubMd6dmA94M842z+O1EVFWRJr/7/ghfvxK0M5v44DSd+w2/Ux4/GbiVYyStKewJIUcMLfwMfLOBu14Ns2qpV/PavpG25WVsNeDerIpxVBceqSqwk+J3yr/TOgu1sNzhX1wDmzKiBH8HaGTnvsZPRheans7Hq/2xO8EWSf/gnyofTNPd5q24AvsZbiTty1qTr65DqnHsltH5pkKQJq7ww9cF9R1/UKDeSB95pp/qvcgfkus29T0u0J2Bvxk5dJkkVRsh3IP0k2gWFxqwSlOJpTL3Ke/27qg3aI6rjKyM076x6WnI9LwSDdHVitcKCynTuXW+dQeh2kIc7oh5Wu//1E5PcyGw8zWCl0KnZurRXAtlptaIUJqUqRJmxHQxY4yOdcDmMSrRPM7/xWR3eDfPrY3TgpFd3DwbaMBASkEsm/r3QkgdWwfRI5BXHolFzcdjsYM6iCw80EIMTdKd55BLPkjxAZaKu8iRzJMxUXjskqb7sd+NLHRXKetXxDd/ule8tiSJBJqq6ozSNx98UaWS0fZePfcWSODqc/r38jVdZ+2XV3uGTw48FMoPgL4s4AzVDteEIaQ2bPrG7YLfFCvVulgg8+ewGsWRY7kb5rYnSh5yqF6bsngPazjynKpEBopWrHAOfTr+hiPOLhptBZkgZ40MDM0GyBdsOo+XKaZ4TMqAsa0ih5v7E6IfhDGR6AnAHqusJYBILPX08ECDPFXIPnMNvwxyvq9acprysUB8qCO5e4hH21VS088I9jMX0jdnz33iEdUslefhdhKbxgGEtgN4ekxFWx9J5n9bitWiWufe+7c8M0UDW/vQlqySt+jEGQcyBVXa57FDKjMkr0nWXF+4dd9Ax7Z3QSGyfSb3pc8YlMdf4HukfmteRprWj05kY62tH1hLL0i8H1Bc+t3MRbHnDeJYrsWbn8aZ+HOjDVT8k+ytza/2PRBsrzG4hhgtWsEpY5rLUA1Dh+UiJr6MY1+YqvY36SeoF0QpEjD3shyEo1ymBrwsX3kI8MNWH8qvdoVaa7leIqKWAlO9WUd3mjTSte2gj3xGh7HyBbefBa2t2PvYL0+nW2XzO4K17nv8PvG97CNGGVdLBFfY26d6b8lQOY03i251jRryzhRdzN6pWRtUZYtqUiRAuQ+kfv0ZFMZkhPpPa9bABO/OsTQqsWoqBKv0a3RqA7rkCz4/70jLxfnAPls9O4/5dOYG7+kqxeXYq9+/afpYXr4x6M5dbHkFZymF8EVUrMwDaMZBLcAtoQFBSk8uZicblhGUDmqCLarIZjV43bWniWNkdcZAfUg8VpeXBf8DS6kLf8Rpz53EwGWLhmKwDddgJX2512RjyxPLgXH8tVgWqunO8bQEPVa1USdGXO0aPjFVh7HAMTEiqzA1UUQVM6tXppXD5QAelA6z1ENIXlAIg6s7BwRrUYB0f3OgVvodbgKR6VXCjO11VGZNzYIqxj3fu/OZ3vrsvRHlhuA+xhc5p7hJqMKTtEdiG3FW3x8g7pl+rsK1YPehqFA4EQR/E/2u05YK9IOpUdMaBVecBk58aAkBdl1LE8gZIbFrUErh/Qmv0X2OT+neumMTeHk268Fms2lf0WRZWb4XFI7vzv1qgDRg77TYBTzbCtGoQfQCrVa3qeQO/R4v+cgL4z5efD5iskVl76uwvN+QW2O4Y9FwbqIYSEsu9kDlwKT0zlsDgB2+5D8bYKhQ49LnGSwKjmBBXVyUTlB8MNP5jBPd/wT3KjtcqqvUFhvXJgGt8cy2i/TTDSaq7CaVk9Nz2KJpjiVwXCOhvWlFJh0OUfEpjViZ1pXoMPR3G0SNbkiJLZIK1XN9Zr6CtEDGW8CaGP8mZv+XXFYKe2ndVhbm31Rg7RG2wTX3MTjWsmmm4JvGqfb5K31dEdpT5L+gXAKIpj08Y51Afws4IZHWIHwgRtfrTstfXj6jr507Qkyo/D5CGB6qzM7enb4vyvJm5/8fo1Xt3rJkBUHHX6F9+ahuBJ5Vr4T6DnIDr72HprHslpO0l5aVBNFb3KAZmU8z0bCT41u5UGex7RqadDdDNw3LYq7wlbaNUOyZoT2FutMALoWSPHFrn1IY5hzu+6M47MaELBfRM9xDK1gtLXfGJXlXT4XSf6Xj6HH9afNZHoyaxA0Xs3+QCe+vuaF9hRQPHjbdyjMYTg7S8fxFO8w1Tlrb8+M0khtZKLXGBJsDkzkBbsDvW8VvMjYyHOD2tWfafIypLCEcGk78tLDLTWn6MpuK1BngQYa/686wZc8XuznjGtP2jXOhDP1Id6lVV36bkJMXniMHQT0Vz9I4Ws4ldLQ1uYcri5E3xoUrqPnmwj9/LE+mqpQh1IfKUl53vZvo+4C9C5ROrtI+QuH+j90J+eOuWcLu01Whon6OgL6Z5nyjXBJDRpowM00KjEDcu1vVmxlIkt7v2DwH7vj2uqRTRRNRRGscYaMwd+NiXeD2ayVyPei2VOfxWONvDuxIQHUZKGGAO71CLLtJWhSh/KtL4LZrcLoqSDzTkHgth+eLmd6twQa1fnDcVu/ydLueAKlYkweQdYQmB18YskXmyQd3gfiZ25V4DZMFWYmEb9PVX4M0ZYwVEHT3C1zBJmUVnk/ewvp3xtHE9zLV6eMPsYfdyJahiTFDfs9yvdJhWVUg9U2XLz9lRU1pB2sUwKXOUkf3O+XW59/xx15IRF0c8TZi2QyS3jVhyatrWHtu4yn5Rrz5+iA/9VrCm/q5JeDJa45AvoCUY7P64bJR3X/hRxx+AWVs/HuKnULtnCLUZU5dyUpJQ3Lm93R9m0ZCnmDle/CG8vxr2x/aB7XnA0I+1dtQTxSWrlDkUq4cxLNCClVnboB/bImc38BGeyU469ufyE/RK96zL3LDQKq+kymdig1r+M1bEhFeSNcipgDJDDUL1snSFhg55eWVPDcSMosBqW281MOmUB2bFpiflX9kC4f5E680+0b6OMuZfNNMqHOCGVWbRvjd+LrKdOXNR4QXbJNTZJYgs4K8CS3XmsZbSHq34hRiOWnfNXClPoT6Vg4qx+x1D+JDOwvYIX3K8MVxeZCWttNH2n9Y9DFDfeVnpBHuES97j2/H/E4mk2HxcpauDHZR6sVfwqq0L/v+JheAPVQlg8O0l4FTHyYASAc8vykDpu5k7K0+zri+eatgvRO+UAuwbfc+bg7wv+xd0SetkgpjjugFFhDmfjt0hS8byQXGenuTsFJiFj8T8szSz2ySNLQ/IcYAYjitDMKTww5vZOEUYhvXSzrGPLQl6+DbYHZTG4gOWOPCtwCbHDeg6pD6TldVYg++meL+JRFtlXjo8StKL4iUCfHVfvHjyfs/Qo2wfwDYyidvWqGu+FOG3jTxW12lsuid05aPSIC/Cfr3+wv4lcao3qXZn7xNqYpchqh5RYyGMY70jTByPZU39wzXx2R1qqa5rkzIT1cZo22uqQyuQqAmTQmyVXlI4C8q9u0YU7NNkQCiJmjWVhKQRjBnIpOR5tX7r335a2PTtbzsLzhupyVq0FHSSsmNW7/zgyLsX0LXzRsPVPKBI9GZplzqaRcYPsASfxGSERQbrTEc2OgaiBAGj0riMy9KsId5d7ye0YV29lDJvJjbjm22FuiIlwIoJQ0pXQ6HveWUS0DuCwjrNiH9Iirxz0iBH5Uqla4vbFafj+P92zAcPUnP9L/O3TS3X0MUU5nkU0pM9XOmrR31k9wgGd/o+KMB5y0YL6AHovgkxSXDeNOmin0eHLVP5P4RueOSnECdtaN5eIkaUYA3dXGG53gGSRYWey1mWFlRFDLwuPvKi0GbjnC+AX09a2IR5K2LEsmCtbKrIHBSHJzyqMBEtExxAe6uywQnyydImk2RSh4FqlcYcIKXumkjlhsvNDkFEonHuYzdty0Aje/o6K056PZ3Obo7j5kCQfl/xmFto57fONcGcxbbca71AsC4bkVdS8lrtePGK3g7ZDgCqe4hN7c9SXKFBtrGTTOUG6HMzQsWQKdSyyg7rJk0UcizF6L8k+ahqlqPiyZZGYV3tr9PlS4GwOoCHYhKSin8aE0XGps3iqDyakhWPBngMeCTLrRWh7x4drd5S3du85/RQY81QkW79UNMhJmDcDFR3lBaE2eBILsV59ZUsvBymuMfySpsS3gIelauJ3XBtuArO0kceh55QuOW71m7JJlsR7Yj42XcUYTk45F618hoWtD7xR86QLLxNOB14DhlDby25iGgnlFN8sllU98Bj5Ts7b1L+uLgyuXNDGnWiQBl5ypHr8TLKpr2mk66UUOddCgmt0Z/9JQ7sWwEsNKUgZSlBNPWXA3+snVGgJPipiBhfmLNEi1v8TDwOizVRDSYf4SkNny2t8SrdndnnKtzez+eGACL79d8bQzlgjSu0fpGv3vJCvMuni9S7r+9m8sn5j+2nvkhSvVenWoND8ZfdlArHE6ve/Xb7decxK2Lxl0QErdCntz2lpp6a3G/VoX1Y6L6PVj5lg1PfWDw/JdN51jiw6+O9qtpjCXsYKvZQgzRjpbSRjyLytmkfNdjXaWNHbmFu6mFFoxyuf2+Qz0ZQPMjV8/+HFvxgMMDPZ1x2cnI3fqPCZS2jfehEcy5+8V/g+mf1mDIIlMGAF3vbkBdf5xsj9rbyeibgYKuzG9g0Q6ox3puEOfbtdkriNKCM+Y8aH66dZfSeNxTeJmGDdJ7FQbN90E7Pc4e/PtloxW2cwJTvrIOiE/iPX9YsN28vYOnoeIDq9l3uMXqF372g5Zw0vmMRxe+nH2gvY5tIvNKtx4bf0T43JWLWFhde4UiSYgJ5qwMdYDqAK82SCkGhWYjrUI1Fv9YUainG8ZBGOaa8AuTR+hvROk9JArvV8xCjjKbWecmYdUwvd6Q0h7a0W6lyjMslpKITu7thNz9Fd1f53Nk50bKaPzTCp7fc97robu5qP7Wc1A6gt0wCZrWDnd3dlEWrXR+N0+vh7aYyLJhzEAMeSI2AKolZUuSh87ADvQQL4QCsMYchLHjoLGXZ6FVo9kdP5+51CX6X2ZUzu81kq1WwgbNg5vXYY0bVk1C1TlKtFif2fLHPdNbO66nk2ETe0JfsTPrZyy4+P3I5MqGZ4Rw+cejGcQ3nJgIlzrFcKthV/bbyd/FRrAspNj93URveVel46Eo/w2dTAOGQc1wjesAlSB/vSejizzutoTtHv92f6SlLlNn0CYPX46BFG9GG1ipyj4pjOl/+wowvTvPUxw8+6IrWZ27aHUAQdCXKFyRujja7iDdv2lUqxwvAiVYZqjLI8uPKhx9l2X2U+rx8mUa0+9l8s9TxhPuOKR+CjzkJOCFiOTe4ERVk6r7ol7HBH0sXxL9PecjzZdra/ZGacWmfzcmZUINLI829WO9Cx0BbJZ/8UIrh4RUp7TQ7Mfm51lfi3eYP+wPhe+HQ8hubsqTNyeXMwoIgd3NfBD7fl6hb1TonIXN3QIggt0SRYy3xzFmxVS2+TqQpnF+okfyTOBf9pfMUDR0PkYgV4eZfy0WBWnFi9B0z8ZsByb2i0980Ay4mUQVv0d6UROmUiuuXJR6uZuBh3Yg878992f/iBo3SO4YrmtG0SxT3KFPNZ2NlBU/z18dxlyaQFweeDG7MpkbdsQmtxlUXMI1NrCsnsTIVlbdF7uOgVEqbeUdYiL1sn6g2jDu8buXr8y4bqtV/SlW4jF+2Q1x66+IQVwlVJSIZH12T+o0dCndCXkk8SULadSIJvWQrRfJ2SOlTy6rqg7XH5BQ+33CR1K2JbR79mc2BVI6xaQP8a+dbskE3V+Nlz59VZ1CLBFHyymPI3b/kOv5Rxwz69AulIDnToTQtHwOz4cBabED6sxXtPEbwfU+4pIlRvx9d8p9XB9dO5pn1zb+rZOuwmBlnrtsER89/nElkfDZKtOYKgF+38qnLBJPe/Ok+ZMqD3mjrswqP/42LnbXv9v6orUCyaVx0ll+s+TM4KWfaBRxdD3OQzR/MkrTfeMA6FmoGSDjGWPqtpjLdBVrf9Jv63i1uZEb86PdMJ6g8C3bUDv3BPuRvv1cU7RNWUbg92LhkN09YC5w/J6m10cqGPaFfVkM518Zq1TT+Im9C/EwOl3l1bqEwdZnuzJIrctdWoPV6BRbhS6DQYrlwkZ9+Z6a1oMYK3gHWvlF1qMOSXjYNsvTyGD87MjDobPL4sNPb/HGRsAUvXH7kMwnT+7092tBzsNAafKJcNnxZoTO1KAp+Ae1tm3ZqpCHKLgDbtIuaRVDsiwzMWhF3nRAGZiz+buv7sO153ulxSPVOAZS3KAe/lxkGxxcqVgPE0E1sOeVNZqgQbRd5aJpuZ5/AatpNU6IQbb/VCU22Fmifj1oAEduKGfbp2MCZcpjVjbjxbx8b8nqlZvZJgtXLBNCGB/QD4PfWWTbzFYdNnD1spDTGp/9kMy2XWRmH92rMKrv/bwCmv9BmEvIcQHaFisai989vC5J/IdU+T0Ubut81mVaTigPCuo1FBF+hNmnjdHLylI5/jBMp8Y2NPVzL08vFhG6N+QN+GP6/KxMRwgja2oGVyDrRRYFM4WE4bCasdXAE5yBD1Igmu66WiiIyK0flYFSMdkprRfS2pygEW/38LPjy5O1Dyevig9t/v5bPYvK+KWpZ8ZU74J1/f7Yn5Eyduf5S8ceCYNJA3usEhwd2jHeeMUvfCwKL8JJpELGwpkAEng+zzAD8EFQzuVcWHgS1H0ZAxcBRz8RXGAeszsYfzDh/fH+jsg5bCDcW35HdaXBI8Bo78NwiAEvvhXcxPoMoIm+GNrkH+VoRsw8F5W7klsdR3I2Qxnsa4DN9PDCWU6BZ7Qa74HfjjFOTvOEHMOjg7YT/D/OYRlGCtTrmeY/+JBn7S2osBrPEbA1xC7WPhS3Hvs3nayQKsY8d3DkMZQUpsjbjb2hq4evTt27bPzRUbXcAIDH7c+JfU4PwTI2x41PcsBht9D7i7EGjFLY9je65qhm2qw/rrgLe40sFr2nAuUDVN+aIN9rIcrYIJ8wMUuazyKQvOcwgNCyhI6xiNZxaMgNrNmtD3/zNVvhdHjDyIR3rEQvp7E7zTrnpEOs0gsdgUoGUbDtGhya6kfGbv3e/Lb1xqt0sXbtYo4YVPo3iVBztPHsSJd7qHAm7gNglykUIB6dmh0XV50Go/v9WytUtMF+fLghvhfIz5AnycEWCFCIVAc8TGvNe+QsrkXHtIfnSNnurR3c1f1u1A+NPWrZGGTkIpp1wo3JeND9AS3OQCo8A3CYxG1t/nq2fc4Hp/5KmafjAQkbjpu4UCcQ+3jqpMRQXJk1Z/fBUCJM5iZTrPnnMuMC0719Z7q3z/y/H6z2pmtyHWmT+OS/rOrBnFGh4/Uf6z/zJJvSZ5atl04J7htA3hP3YIvMBCbRCEIKQnIFEFz0EI0P9TxJkmpIQ73V1Jw6KT14pUdmZtbjSZnzoYOA9i1d9KZ+SyoSdr/5igT0LCrvrR8OmHbefE39mv2Z5vc1S5SI+2cKROMH98rlhOGug8GjGfP6vtSqrXgTmP8T/PAAzbVQCStZTC457wgbeB/oJ1Q/DsKO+UWbUy7MJ7EZq7kh1Occc3ecSD4S90VKTOwjB5o1/zcw+NSTDvG2VeCIKSUlPrSj95pXv5WtbGcG03oyQAtKOr+A7BX22lG/bl++Onj2MfZT2vMZ9+9C3Fzak4LJYYXBMHZfBrUejLkZ0A/DyGrt3pL/CMa7KAS0WQ+6yoyXbez21MG12KbTCEIzqZBxYh0yQs9QRGEeydWsnDTHOCEwsh71SO1BtKJ/pd7xq0fY/RtKeQQg9DkSK4lLYDUQ+g1XO2WWrCb6U0jGUNCD9NKSYe3eXQ9rZiRVRwN0KmslF7ra81NFCU6QRNjcEnc9fjpbDJtQE32aGbuE2fNmx+sXJciyZcb9jUNNd/Nu1WcZCoM0AF+v2KI22yaupo/O8YdPzGRZm/nc4w5bV5xJocBlnZXCdaGVoHb1yg2ZiM2SXf+7bsNSmPg51xTNT/Gvf4jcPyox2SEyuPyoD3dsyM6U5N3RF/vsKxepJ/PY3OqgkaoLG8HrNjpjUZ9AhXiB1+e96dK4JGYlbLtfsCWau9ndgmRL8/N5mR+s4+PG7FCEkBWNz3rtwmHh4MxA7O5hKIoXZtMB3WDhYcq3rnIoNOvv8Cf3nTVMfQh2UjY3tJq15ZtARlCfJqCBChoR2GuNXTYsoeXA3mSCuyB+Ofj4Z27Dkcx0i1dlEmsZZY7pQzDnTKd7lVrpB1BqJm6mUW1dDzKCanmMw6aEFdkkIETsLoaEj5TAYI4q9yF9rXSqUWw1HWxmA3D9fvvUieO0rdH2KGQqj3681ucZLCNe/muv12ivBIG3Lcs+qG5JQExcd65wANA/Z8z89sUK9xocbc/Bvfv53SC1z4dTUunWANkjNnVdAXJR/O5ThMu136Z/O/ef5KgkjVeUSeQRpV7pQ2yxUdbtKnl4LjAcyaSRayLqFDguPKN4Ryk9bkYeI5vsLOZwf9urXzh978kvvkoYUFAIhJTlp9B6YgJBwK7kp4hwwralLhClpAAYkQGQB3UvIY3dsVN1L4bHbCdAuC6tbYkcKqb8T2n7HhNfBLzeR2e58cOnSli1mHvw/8pnubGzG5qTGD49F6HN204TJxhj/CpbT+Gdb2fdYFENX/3g25IevYeeBejhE3XcXmHup1brMP62HH0D11uAcnoswEZ0jc6Sv772NUOuXvKHGwqdkiMdTJdmNV1enzk+feqmJgLrQslXWy7AbeIfdDmtuG7OHpT5yalgiqp4rwFZ9u64dGPUMmqctRLuh9v4NsuqVP973RKqdGwZ7GKzun20hNayHsnL08vNLLhFT/NmFN02jmPNwr0CTGT3qW1yntWbWo5YLH3xDPdT+vbcoC1d+fzrczpyB2Rbq61r2GekmTwOdfb+hjWV/zp6NlZKvvxiAgzs+yB0qrnl5+xddiYlPo3GHU7LcZO1rB58KavPQh0NddG9YOEj+o6lcYoMKdXNY7Jyea/u1EdxKMNCreiloLuIyXj0tfee7DP4UEM9LJyhKOz796utilM44VqYuhe/z9r+7zGMNbYz5Z6TjA0ndtEJHwDDy60OFVDzU007aIYXsrU3X3GT0ymZkVff9f8Z1Xm9tE0tzJIwAnUDxKqq3G84rQ9mML8OkgoAPa0j1EkPZ2zPAnAQ0iDlFr2Yj0wVr0Cojl8oI9/6LRzb/oX981jYbGtTyaNCwrunhcOt67JQpZMo2YRDo1HSbm5Vyt4FWBm4yWy7w5452cEvdtevTZvWdeRf66LoeKZ49vkp7g8TTKC7LulXNUkZb1nPSHS403a44pa7QYzyfAfog1tALY0Z9rmKzkVcnOXyzmae4SeZXLYSSir3H9ePN+GdDLc1qHgxTnfYvPfqOVoJqK77X1DFgg0bfMbi68UkYhtjXZ/oAEmsV9wWST75QZnMqPfSBW1Skt8GVHGDUdrH+8w84DL4rffYD90iBSFNHkjpYMhthrkDkAdckvWdEM9TlvaC0LEF63pKoVURvCLTs4H8+0nsHwvVSef41nVch6nn5Axfp7MXplXrBzmDDNc70mU5bfH6uok+/MFTQJtwXbZSDSO+LCu7UE/humtRW2Wy90XtgsiqO4ro+Xf0qm/8D2gvLOB/eT1RLTo0dj0/C+JUI9qWDaoaeej+Rd4Gl/faThYkP1ZuEk+fJyOlxtNv3Y7U8cqF3j6ZBPLGDGoepxyi5zrpP0vOit0sCyffa7xbvpb+RheO3HwhzHoa0IC/ACG3bZqfeP/sl5Ld4Dvn9FOUVceS0pRWuNRMzBNkXqm5e2bKcvqA26SfgemB8hp1NRN/CXtTVQKSYftjPFPQgOOXDHb1aFHiKfHy9vU4czcdLq1CTKDXP0L0zQjfxJJjotVE14KO0Wchd4Bl6rpHYahTm5B9OgLQDy9e6epSH+gG9LxqVCqOhi5dws4UtC5j4UPB43jgZRqS/D3ro5wFtwjz8ytvt6P3K305ZfKiwaqfONql3zdfejUCvjnAI+wUjARFU69JaaPhBg6UfxNUDbahyrxL2VqqVP22bD03x8feuC1C6OTp2OyWwmtOsX5FIhnoFXFhlfXoWxDe/v9hVbz0tSqwk2/tY1qgxwr/Ejg87elSB3zSTKqCF/qLrf7MUxCNUuIz0KeJvcipbM/Ra7h0DUu4vrsqLLxLHFqF0J6cyHhZ4sjxzDipxMk2UAu3WfPLUfjNIuPx3fZEJW/MlILxjL67jaId241bzX/YN7UJu07j/KT1FRI0bdlTIaBmEUjwSRpOwsmXcHSrxMNCOIxjLGdE35SQRgTav8Vu9Gmr27YlYW2zMtJs59HVxXXwTKaq1ZMuU3ekb2F5a3lx7DQAdRRCBi8MUS6sigyOXc4y1RLZ95ceRHhWNjcSYPZRWtz2wC71dPKPPzigP/FG8diHrIazY76HqMSH2IQE015jMnVbfFOXHHpLq4tXF4uxvH6DPkacewmKk29hIDNt93m5Qtw+zttWI8Qz7zoiVmHF51F7QbQo6WRS1+/UO77mNtrcrdPeb/nfC56UHDzjNpMo1hIjYPxpQ5Lft3AXA9l5qzsJ0LxpqLK5nsfFEuHomC5VyWTSyKSG1OlO3faRgvEtTbBOCFMmTvI/1ZXLOIZ6DGFtGLWiEhXIYDNFgOIiD68U0G6l1P+9IXXAqBI9surzCoj9YsjOTQYkbPNFZlbc3WmfcycSqlQ1QYjbmTzMREgHGff2Y5axhDRxnFevpAa9vA9bT8cbbnjJrlHSdQDa89bMcp2Yi1Z4yC73qYYy86Vg1rCp4wDFD90VdzMV2I37xVYx+f0hyZej1oQPec3FE3OfG2kr5n3ZQ/ZfFObFqu5UAiD2fC94i7VUM1TboJG7UXJM1lbgk9A6n/2XA+qMe9sWCdOZTdYjexiFqbGdQj2G6043s+aaWfgPJEqvYq6XKw6HymH0bsTwcUxHT+aLUrVAyNNkC3gTBmxYrwGJr8E+teeaCSS2e3bjqehUc0i+ghaBKwNmhFJ+cxjC1k+S4p3jqcWK36xTd33yA3RjQ7ebmsqtq6zbLvqWqmNYmU1BLvBOwjb1u2H//R6o9Wu/0lGM54556rxp6T5DLrHQiIveJoFEVU8WAb4MO3jtdrX5PSn+xNlndfIe77tQJ0qzo5ee3erCbO2qLZ2reWVjFjL45Tef3L1W6wLI9rJU3HocUzlFctZyHbQleA//mLUEm94L9QySD4O1QSugyvsOCMKRHSNUgD1t9PIuRLx20QXh2ojgFbnq0g6+yECtFEnlx6ZJtTwydUzAB10Trtj9kWb6i8Vbd+tvS3buyRM/8vHRiSOglGVEDMfSNvu3Jt9xqO/dgXEPyFuDpFehycWbXHqEwKdRwwuwYitJwcjfnJhu/pEJzfvSqPuGskDml/eoWQnPlSMliXrTJ6Q3JkoJK7wo4VApNPed2Ec2ItrwgoJg7lwm4nyN3NMGBiulV9sqQulZXo6Jiu4wtuBK1ypeNRcVQzEsct9qw+cQSqx6SMfZ3wKgArK3Aj/w+eBbri/20NzCGtY6jDU+wC7XdAfEN04BziUfjDQ7ZeEHk3cWIAlu8HyFOau5jrz7yAiG8FPIuconReutjZLS63FvnieTgYubiX9az6/ZiMD+nseVyLrR8S2Mth9+mAgsMIufAuq+OkTGkd+aS2dh2GxxAFjKtKALKo8uNGO0uegs9zpaDZx2/H87ShfZzavqofR/OAyXsfGj2QmgiaA25airoJL+M5lrqFrb4eROxmeknuM2jIOCmMGtryu/r40lEB5edYMosyN/JJzzQUe8XPrYnVGU7b7lLjalyKdq5LdHjTpft9DT+UkwxQnV85t5zu4dmhLDrVJs5m9o7y0g6u1pdTEu0ZLBG/7E3MW57E1BVsAUqTmYW+wNQl4Ahq3TCTQNtI+9D+EjyGRLpkrNVw9qiE2LiVPA/U9mqbSpvoG83c1uPhpJ4XGIT4Y/PKmQu9/E7FEJa+2TGKW29S4DuXPzT3V1TS1Mvqj+f7rZna4/C4YVOZ8xESdgC/Plehtj7nCL18acNIdo910Q9UpeNYux6a61vb/8UryQZ8YOHeM9PYCZVUq5GZ9EmR+eLgJo3/t0okNixAUD772IfXhSdiMjLRAtw9RTBGquoV7MzDvdYRNKw2SuQBAV2ZqT9BQ7kpLXIhyjkQE5wOqi04uFDB0k19FIj0sFt92crMF3Z8u6hb9Qz/rgVKZkHqZ2xhNy4DTB4Ks468VAOEtci3wATpipIu/OVb6dOEqRLW+lMfCv0R0iO649a+o59F/4Wh54/q+bSrbJXfOFSlguH7JQX6F6soCAeznApTEX9MsjT1CjSveL6kaY1D1VM6FVZm3Z9io/DDqTn/UdUxI2yhWCspIZSGoIQd8N4kea7XDpRCDmf/qijKivgMfsNQ9eQz4zQNvVf0k7W/gwDJq4hW95EwPrNUXgA6TfbibEZDq55R6pU3i5ZCKJYwI+BtJsSEetN+lifh3riJr2J0cVd/3PxTZb6+rP/T5uT9tnwrweDwH/AOHnfTWjNgYY6qQWlkiK4C3bAaZOCwlboxksGmGf4fKz15t+HDQFPNWFvPgJ+be3eP5aAOyD27yU687WxSGy76n+dDIk/ZUDCQfQlKS64z/AQavM/hb/ZxnENkY80ZE02IP4hEQysKs1ZuPGVtDC5uTyJKqKnlJe6JbNRV2Hs7WS+DFx45HepMfQE+w8y58rfKfaAR3MAQXHQYf9LmVxZBnSedZ4CSRsFkFneND2ECH7IAT2waYZ5+LAUqHTjkSFiSoe2Ygx6Xyi7627SUnHvH98tyNBk330rcKwQeC9fsPL5SmHLmpX/UuYzix8+P2K6aqgkpFOEMhr0sb42ro895D0GW8mFPoCw2LAgWIIEhQa6XfgD9lvh4QAxjnRbbhhEbfL1CZv8ZUtbH/zNwZfc0S2eDSMiDs5Gh5qd1eaDCP2SBJotWyIes3lf/An7mnuTekyXqFbNZaZOwkXPNdtqzYwKgdu3eDCjJlsWDmTqtwvUeAtFDhyGacxVrC6W95bcR6Sa7+Lj+gwy/L789+5xdsHu7kq7pAGfQK2vdEWaGUA20kUbSFN1vZjhlquQelLrRqO45NO+p6zU6BzSdJ7Y8sqUrnCsRCsN5XvPnSgX6Hk/+7P32bfQzNZLXa6l8bGN5rNuyevJ5hXIohwJ9aK82oknjCNWZw6UWK0FnVrkXcFJ3jIKsZXEUidoit2I7fTcVLsp31E8aTJxikq6a0aoe7O8oA1R+2MiR+KN4jw0T2jYoiYB+xYAzH/GtUuYi9hsNnBiqzHD+ZnTWyL1oaSDiNcoLL41K8dBViyu6mYktGey4IF5Hhx6N9TMEne8VMHF6zHKmICL6gGDbk5Q66LvvfYI1tDqQlFEafjAXuO0+p0OoVVBaAHSe/1wafASX38mfAL5qRtLx51iYSbO01MbEKPj57OMjQcYf6g6hITsmyujMXfp5ZpEgmVf+JJ8Tx1vOANcmbQCFaMCjODv0RgYwiGADGI/wQIbl7g/MkM8WIFo5KYI2BqIc2nWB9PyZQ/JFiUbQuzDGUzD0C3Wk2NJQ3LVD7hDJ42lhNtFXSvg+3wpJ6kGu31T/ULajfiGoF/+smUGdg25sqA4cY7W9y7JPiRucKFE9eE0XXG+Ff4OWmoj80TROmoCxq8ZG6G7Zg9hfQNRwedtzixX46d7dMueiuCC+TY4iTAHl19omtbNtIjI+yCmTGv6T39WuzeoO+Vot3XTMM7BHIZ09dRTHLXNaApOCZpjO6hmDNyWwAYzq+HZjBWc8wn05ZnUNmuTHXzJORte5mBcpl/gaHKhQYjS91xmZxKX0MKnxLSnKPUK18vnMX5Geys8t0MDn0X/JXNH3DzuoqB+GUNYmL1MxLcsa6W5xvpRcgmidqUqzpo5vyfG4PQif9jh45sfkyxKHqwx8h4WFUfBQLtmGYZ2LtbFxQizWQHFN/357yuitWv/bGDxWxfTTXdLoCs2yF7gH3O1/Kru9vEJ6Eb6Ac15SbnFUzO+TXgpxkC3ojyqxCCmaH0ZgBbpeDHvuE+RfLT/cmixVpGSmxy6wrGNz8dvhFczrgyK/oyfabbIQIP3semywKHVv33U7DQR7BFJpc9txN/hiQWTrWba7g52Ux29PHl8ADvUvvhkjVeBF/aAS8fmCIvboaT+qHFgZOTG4DBMaNWO4YZQWBFAAQ2629Hsyk4xPdFeGBfH8urZqy6LnT/tDb+lLjkzUfbe3c/455Ku0uJKLNf++bZOrWND+r+96Qv8grkvloLUWVjR1JVVgb3uE6GZJCbYzuE2X/PLjwlL6TRS81T8eOOcX2qoarfr7DFN9D6MexxU/FsOStwI4eeuzg8ZZv5fZc1X2M2jRVZr77GVvMDg3Pn9PrxubHqNxCQ++c6AP3bs1YrMEPylcsVg0prlv2NhumvPXbw794nOvKZ97RzlN4iXV2+9IvoClva40pSXF/Ou2PrqJmaSNvHFnsFH4Q9Xcrkqlz9/EBOvv9/x8VYn/g1xLtGFmNCvJ/e3paa5X/qepfk/xxnlil2njAzgMVKWxdW0yR5vTnXE589kb4qbSTWNSAfs31clbFPBDhtg9shxMZL85v3LEVGPyp9bXnUpgbDQ2/qtOH5Rjv2SP9s7EDmujakehtiFfX3HPQ4bWWtGHFdv1ZHf71/ITgRkHYpm0cZ+OSnisyzjPr/e46wXBuwUWrzD2X9M6dCFD32z/yoMAJ3fy9ABXwdDzP75C8UXWoYJe68S8qLKQ3IYsd1Fhyv2nZizwP9AAqCrBfsOSeR6RIGiT0dZd2ShwJ1JZ0bYsczH16Jh172Vd+fhzmAYfEsRvZepbAgO96rHS96FPWtO5sOEEBljC0lOVazpprc1ymoe/DccUou6sQs6+lnKXcf8YG5hrGIMixoy/+ahDb4ET3glRx0lFJCzc5vyJksnr3bDOkbU97K0C8Xk0dxwjuTleNFrJfiKMFsbX5PLu5t72l8OduN+ScQgZoiLbNDW5XmVyYjG5aIfy9c4zu+zBuuTiMkPGtSfXEmn8C34bivPjQoO71jMoexdaMzVjpl98yWkdazrrzsLzGRy/dQ35jNjcDB1vgvqvESiVfHv32NYM19oJuDzfA0NR2uN/GbiJvT/AL7y5Z4jTPRxVEL+JBSX9k58ABC2Lmwspcp/ytPmbN/E5nvRFi/DKnABDjiLQ0FDPxUdUXx1o2S2gu9ILjxVvNLcv9ha08sQntswpJfsFcmce1u8FLdQeb16dPGFFZXOpuoy31KV9TbZctekRxTVgebq8aM71XBrrnO5aJF/uTDIwsR59G66stOyEl8YcaXDEnaBfAiElbDm9CDuekONjhKuxcgJb2Dsjg9jsWzYz+s4Ndj/QIMcuOdgS/CtH9H656pvNEGpgXsD9cHV1rFj/2AdPOmqtCHdsJUqB4WnTgpRsPQ+hjQLmw/xgmmz+ZOAxp78CW0Wnf0zFKnO25+H+vwe4gtbaK0SEoAihjm0J9ODKXxtE6uOP3zeNLawddF4U5A7nbO1cknKNKuUpl9ksYer2X+1Dhw2T22qW4zmcCN7T2NiX3pl45QTC5Y0Yvs2AQQPQWhsDjZNbgmd8P5HWy4peynElJctUaVReha4KUeZ2RqN7WbMZD3uyP5Tpxl6s0vDf1pYomMiy65JUe06zt7H+a7/9x+7AjSbIKXTzU5SUjc+BOV7KF9X9cbNf60FffyHT8Lf/+S7KNrXfumTHwHxSphpsZ5Y6u8H05VDbebOLKy6jn3og2euuba6qyxUDYf40WMaYp8o5QaqH5G4535gH/emgIqq6hk88t1zQ7sAnEsjONzJELgCrICLqRnsbn7ib42YcOm+DAmWzz9fJ3QjcCqH7XKX993OrP5O2UEL3aUvAk1xvSFzka5VEAl/jYWaEu0wKgBW5L7rTmrUcO/CNH5gE3jfUHhozQ0ObQYI6oWnIblGfHbYC1b2mFpxBhGdbauwfo9vbaozz3ajqgMqeXbMfwvTUJUjQjfC6g1HBT4ApAQ1b3EINdsknD7p0iU2FDrgQOV+iXHDf6fCK6vcx5f9s5AI1kfd9U6djPzibH2PNRt59zvWL90Ge1CmudAj7zWJPseUzPSfSjeL7Halu/PSLYSVLZAexqAb67QYKnFqksYEcy6Zsak+OFA9rpCm6Ftft3v9CWwPtI50jTrsLUg8UYiYedossjK3+0zWgszDDPt+/1VWlFKlja6bjONNnwHCQVgtOW77GpDkAwduuhU7s43ZJrnnhn+4Gq2OovoNG35v1iKriuK2ZLhR0IkN2fYs5+s9MQeQyIJfy0m/m/CyLCO4tSzb9FUJhqwPb8/idHblbSCCm8Shn0rol2VVc/Pdjjvb9+YaSZK6H7WsKFePb8y9XeNam0BXrskb9Ozap/DLUuYJbiK+uWGEQqEt2xXLkSjbwKueb66RFEXsWbw9LrbYTctuXn1bs0R+8e33m8cvm1I5S7Yw9v+EoaroofWJCHZkE0DwOETGsgtYM5NfjivuCJVXJEta6qYogVkwNAzcKKZvPYRrHbPVfdec5J0T8c6+ULKRtBEkcRuwFKPteXY8WH/BYOgpcSGNt8xV04otak0lbaCJ8bWCw/HaBeqgMsZjNNETbhaxOd8CXWjvkvgXsOuBEoMHq09Kfa8+cMS4tlbYHiw3E8+w8ndZ6mXhHxSPqh3RR97tOPq6jZbWlCdrT90Y7EYdIGBzjdkiPftzeuchHdosEmOii/TgoWKmr5jSJ2OmiAfk/1sq1wyGi9ANogS7zxpwNHVLgxWIkpjv5SUmZWZJ2LwYmsXYkJRHb129KYqaNuNJeRoPuNgZ5HiGeWNRAutD2WR3Y7/pRLqsSTyaMCWeNKbOeIZcy5MpRI82vQo97XTzm1vEmRxp6B0Veo70CnZivdDrg8nq+hmBjMxp5xdRN+f0k0ieRFgB2K0UDkRJmuHaybkglMts7gaIeIk36jjFDAJaff/sTydHjiu3gEffRucdWmN8mmzvRMFZh4Rv8UdbHlOXxAUxyceAXy7pIX3aqDU2FHWRxA/b19LdwdSIAh+ZN75pbp1jyD8DBU8eVEpmhGsKTT10a3cHc9i9XjjsgXLP1eI6ndbu5oXh6fuYtuKvbpjfv2ck1XuLPWzinrrWFqQ+dwGdx+S0x/pi3n5tcgLc+9t/8CrrRF/PHN5b3wpYgDv349fFErrMa5GaQrqgNbnSLy8ja5D7NG0aaS+X+xTSfeyCoNFC7KbjgjDpEOo2W2dgcNctzL31T9Q29m/4wp8QSxJ8BkQhsVKAw+ob+qIDS0X5eW/Ha4RnZ5hOchNFH/gyiPwFrCFyl2iUDFAJQcgFB2+b1lhhbSxonxObrSrORWbf2Hz+z9cIDfQHVFA5ykVLGFJ/uv1ziGaMhUz6kXF7OtI+DXShrgX8caSZEI3CaS2Zty42C2eQft5tHBIW5VuU+L5It4D5wZX9PUvZuVmQUY8E0e4F95iyNJTg7/Ee98MyLIHy9Cgd7RSlfcUlawQF2asabNPtEeZF8kcmuIQTrpn4QJR9wvO1766O4XBoV8gTvXas0I5bXp4PHfryLsXA4FpvDexC5ursB0L7bwnDg8j3g+ZgNBL/AlR4EKPbRrTlCCiuxB4+pyLTkdQYv/NPZzAmddb4t75CMTj9Orlj94NhnnpOyxfTqqcyuB2P9ZCmRemgTc31yIg5qmcY6ajtDdaMLxzPWRbEmmy7yNuWv4hyfo7rP190UqjQUnfWaHqYcrFw1hRbH1d9b/ndCdNPRKgKSHuFn5IyTyDJ0dnT4A1nzeZa8LpovatBa8n2xbJwJU+0JveBGr/mgaS5C3e+jXnid8jTF430nSr85tCzf5zb+3uDDn0iQ2eFM9Z7kpCilu2BNd1PoOSp/8rA3rfpFj3smgNr4f3PBsDb3n30HvcklaPY+Id5R+xcQkM6kdsCPiGEonySQtAh5KqW2UdGHhMupc05BYvPfTz2uReKPZOHi4n3flm/o7UkEKqj7391AG1W6TzbyeVv1mhc6l7kt1JPqVlnxtY8dNWhINE1d78fHBi9+TYmtK9f/ZEwtZr9ODXtuxgsp/aggtKv4CzuFs+CEatEHWbzVCT4vZ+NSe18cj4XI90258JHmBmLvcXFsPoILg1CJ5RHUBOc5ToGhyFPFVWMW6tb6SpggzYRNFiLzkY//UMdZybNPJ/tE5aBV8hkEas4W4s/xtOCv8/zshx52fAr/rz7z21KVFVju+2wENeBJ6tYnvjv5ILfxzUeZda+/Mh8d/T7p9CRCRN04mO9a1gU4O5re9OT0MYLmSAN8WauRwCqNM+7ClIoxaLFxjV6JKtEObFLgr9owYgqRFSmTMsvZcMqDvXUy+2zj+XfQnqhVKUZ4jkLmrH28bmESm1uresRGB6D6FIQ7msbT4va5qWlbQg6OJQGUSW3++nuWIpgQvR1ItCBEYVrQTMzckqIVQXZlUJNp2AMesUToDV1Q3kokhbsRw50I+MlH0Lx0mrWLw8e/gIynMFxAWMxq5UtwBZWjJzonQTN1ganQfHiHHoMZoid++6trC68DAeyijX45ziTyH4yyOigyiH5tgvy7lzV5EqfvKZp79OVHdeojtOkaAvam60e+XFx7Pmn0xpeN1edPaf8st7yUf2gQbVzVFSalsc558vX3oMIO7l2rx/U/tEnzlUrNM7x3A3qAv7y1vabv4WMrEtIo6L/GVH1h16nu5ly/q0Huy+6iArku7fJGkrI7XTycWHV0iPi7eyYPYpSTBQ2qcxk0R1cefCGyyPYywGU08ej7BTvL3QK9MSZqpJu6NHh3QwGSkcDSkyiwxDGFJsrDfbKr+QdIuFUdScd5kw6//Om8465+45Z+br7mhZ+E4Hn5qPLg3p9LnYCb2meT2QqMU99InfqBwzuBHCZH+AQ9OLC7j4QPuHe1KxktJk1VGk9Rdjt0nM/h5c6eSgLATFOXRTpD85hF/b+p/qpApIcx+SRg6zPRg9GLAHAPes2FwXGHu2z1+S4mjU8715IbJ13R+6X7yKyMWUjpVTKdH9dnwMFPVT5AuEJwF3yKauNiA+GaMiIsUe8OcVzjMDIkxBZ7ofiUGKLHgOy5k/e9NRw65pozULWNDAfnhVTUBUNQSgahiNBeGunN4q20xjdHMIP9CipnmNOO+mTKfi7vRl8POttY6qOTZPxPb/inro+25vXw75Iz2vaJ5/gUGS7+fqnVpmDHugyTzFVhjQ/Bcid6jOByuD8IzZszzYaeVaDdvPsajO8fgnm0rfAB6zcY0yUDk+UgBSP3XyAdEOS99jFHMrDQgj4WRfhc2RoO9huywUv1hKd8sqWssQyOXmPP+vSu+Mo+kNBnKtH5v2FxbD8WFlhela/zeQCj/sfQycjm2lrQpf9atfzj3qdED8WzdTnuPeF+9edfxmHfyxOOXfNmPpGIBweWyA31ETQetd8prBCG9vc4PFjuwT62DpjC1Zrk2b9qnpAV3Rt/LvT1SjVZ3urq7QvyyeHBhbI/fnMcui/JDhM8fdeEV0vIUcy/Lhkee1lmHlVcm2mxuUS9O/zLr6fiwPKj/5AuGRH227F7YGTyPpHc84Bv9xptMycrdv8eXxY+5JLxJXklnBaIGw5sQW72L8c+lYya/ulR90cHHy80m79FXH6kyTN2/u4bMxzU8zcF7Zgcubuj0TbcyugCxGYxV3Xa14dC3TYAmXOIDDKODwCEbyRiYHnCrU+oqgW2eg6z7m4bC2e1PDTeH4eEHD3fFzowNjJIhxJaK6VzmIcSxipc0QFR+HNZrPzs6jCN95GVfMqzHUdsWCnfL8bmbkhxwlVu1fBBqL0Qle37YRyIbJuCeBVFGmnA3jP23Xqj+mH/AwBmChbyEm/It8i0KgtcTuREVYN5AXY8Dhoi3lgsPYyTL8o38LgaJZwvf4VviET8rLefHt+9Y+fCrcKTPpXe1SxuaHQ7ihhnadtZL2FvspUQRJzn8nt9crB1rQa9i4z5ugKTeG7yGFS+i8UTHtzDVfP5dVpoK4W8nyvkhToiqH8nhYe7TS+FmU5NrbOloxZqXqCdn7Bu7fUKC0MbBB1XyKcyL9A8WuiqsUCY9fGo928rtC4OiAycUsOQtfdfXtyL95vshTsI93OHzMY+5awxtor4jwybl15CHo8Y0sy1JKE6+lZ9Za4ieA+6rd0BP1Qa21v4UMpwLcuh9V+5qb1/OWSatUQTdz8XUQVFMy1XxIx88H+CiapLGUGukrwtvUu6+jA1PcV7qvsmr2PNql4466WXH96Idcc3aLe4XdTDhoPEqlfa4/XjemAYeGa/DTXzlsHO22BfZsYEh+SwJD9zvpRWuYK9AGsMlvKSqncMp/qx9pbP4dO4shLVXXmIVEMEw/CDc0cbQv5xuBbS2sv62G5z+rw8Nn/pxjz5qwJRbd2JJ1ijyZZkseDC/3NJEv6WxKAFWdQ8tW/FXqiyeEFaS4tq6cdpf5Cmnva3Kvsj9zJLVZpE1rpIJFna9EBuO69hPAcJh0l5F63i9bsnEWOwQ6O68ocrklzZ09lYCzou7jhs5ji+FNhPxbXN+8fK7PfhGuiqNzSQrmVuO0gZtxG9a2QVpveGyW7k0nF2GEf9FCwNuSwJQe7tBZuvfULAaco+KZJvxqpmkl7E4OFLGUQKkN5bDYZ5dprUKNaxBpjGkkFPRhQUgc+RnIC7tzSkNLaKbQ3CRvs+d2mZP59JFzz+LfaT+ecj5bbVwgHPWQ5vd/LIAdm8KHHzUqzpeebc+ZXxYZCwQNtj6/sj7Dw36Or9vRIyigA1XmzjfUR8xDvWb59Tj4HxtygoQfVh5fRTy76GNbs4+R941DVeZWYfKcE2fzJ4bf+Y1t8+5oZowS97kUVRpJH13cckpSOzgAD98HELbcknnmH1KVjLS6f9R4Mn8wGzS/sA3ZdiXS4NT03GkTG/30+dqiJpNpzPIb/+S21TG1UaJ1nkV48DvjRy6j3fP9nY/Cg92z96gaE6oUv3my0rUxQPfzJk1wA1n0jjTlRJPsJ1U53pBaPZxe0mLGQNS6Hl7ifuIGzfnFwvM2qktX69sY11SbOytGbDMWK8qebzObZ6AtuUHGvK4duvWvkTjuT4Ht/Tgira61q1KpLHOKRxQfMkvAA1I2zrl6VYiPHVmiR0GJhEt7dL7QVoZYbeFDUIzTRgNCrkPvlYGKwk6fMFIJ3keWBzE1egaGkQB+P6511EzkrOImtNeVU0rI8h/g73QnD6vtf9CQ+IZrPbt0pzdTyWr2Bec0l2mx14DtcfI7DtWJCjFfD6+vchuVSbs+cQkvJP1F1mjaT6rW6gfdrJMr2Kfjohe7TH+AXXfyuNmZQfypd+RYd6janvCfPdSqhVVTIJs/9rSuT75rP5tnyGQLhxcHjjlMs++hVF2caad9UbpwDunHPGNoBqW6yfLqRQ0MMd9t1Dqznicc3jc/WmKFv79zkM/8j4WJgK7E25/1oVcptEpPuEy4OUMKB20UmLsYmvxjUIqoSplif7/YwtdZWcZ+Y4w45PajuYzmK1eGBbHM/VOViEDvghWthJGehlCbl0nDY4UX7JixIU880OIc3+MHboPfwpBHWCKqcowSNsKgrAtNa5+SJ2hsStGcKtO+4wxmSQRkygN9nKkgapUk7EDyS5LJcAhIiy3i+Voys4KS4r5G/Jfry1dqqILTr8nci+rl4cYoiTzHT2nQiXAQjVQbEmXBY7pV5yCkyJyiKJ08mm8cm8gXbJVWGUyffIb5OxVp6bKO3/7rHc2Nwqe5wHya1zi4ygvyXTde3YmBRKz5Gc4UvbZRiK0K6FzqZ5ADkdCE3a8YZ9feMbp7WOHB/xrb9GSVEt71wSv9RBxonAvV1rfmWHFIDLtVQVUgffk7EfjSHkHAt3KMvUjKnt3rQYR2dN+vlq4eWC46hb/VJ+qXahPFPEOq9LCKJdW4yb+Kvq1f/eIntI5h+2FvdjR4NCMzJt84RjGvnW08ycIv/vqSExqtgRFpAT8AMqRu5ZefrZ1vXtvr8RKhFjv718sLfPPynVlDhlCmoBBfs3V3LQk+sT538q9NPhXvH9UMC2/1/f469XCw6lbg8/lubNqnt9LI9bW8LEmK/Y1NhLdMX4aNPnIIpL4bNCIM2OxEsTpEUiQRaHyazO69doUA0BH/o2P+XJlKdLg4/OBcr50ahLULiqH9QShzqgKTCNuudF6K4l/dsR9T2n9Ix/9nl53XPjML9dQi8fwIs571nMcx2Ee5R8/QOlukkTMOlgGKZVMUjB/bEVD53AzCmDWeErAUZ4D+pEdABs60RTQ1xtbBHrkosWEuU4Ka5gp9r74FnFMHwjLhZf+Kb3WxXiDxoh/JQidQ3Nr48lOJAHsj2DKWypPc8ZPx/FvPJPsTa05eJkY8gz4B86VcQckEXe6PQCf1sCHaMI/K9pDzyJPBZcnZPmdk5I2+blJgz9Oja80wH98JYigKKQBRQbpJzlZ9LuOK/NS0l7p5adwRmHSr3G0di3cz7q0g+X0txdpNs7Nt6q78xvfzy4G7A7N6O184xotyURbExgWnomrstcM4mQfRNp7V7tHdqt/aRMrVwOlZTEovZ2m2+X6Yz1fFXpCfiXWL/ri7nXdVi9ZeXL9FPBEogpyCojf71tpFjz+tIzvuWlkzFD9v/2/3kh36P0Nof6D7rAOJGp3hPxj/eDd2UnRlge1SfXS1tyNfPKUkjB5wOrOSw32w5z8FUe6lmVl906lfHV2X9TouSRVE/5mcbm2XQzkzop4EpGrzxe5rCBK+LHiG5fHI/BuhmD4k+8eb3OYO7YzrPOQpRuDwRdVi9PrgbGbqfhZSpPnQmsocDm7vpdSGoEBAsajr16sMoDrWbXK8MWuWkLZuo5rmsATXknHNlocqMU6ERCqu3EVzIOIBrvswm/Hy83eHRFlTTb4oXLQ/rv3LS/XnjPkcPsm8RRcJQgLr3/KRSRr5uELKWdIfDD2DgSDebaJQYbXN35zwsN2PD4Hqt8OrMFejhF/OJ0l45tBjEfrXuzyyxfe54R1pjK9/kl2s0769/0RQAtvzuNfmgVaGwMe3fslVKyVkdPnpiMTSvMCxCVh9PWhnGsrUhS+arz1huvxRZj5U7GBVbHwfix68nWl+/fBfaEH+An1J5sRnFdi0R4l926SABV1AlDKaojFt+CxHtaDx4+3vsQnI2JP/qzRs4EH47NeU5f5Lt13AWGBs9TpKS5xsuhHhTgKT2vSLGV8n73CNBtKudW0owiZrtUi/NgXfjFK1TXuYZllxyx79WbMnosV6pesmHeGQMumzS3XF9uJYbDSpwKEHDk60+JQRhXXKSYcYDvHjGgFFkOXAQ81WUyz32wd0oZ1gElWs6oR7uv7uRulUO9n66UeAoRcjecq7hVyimpBeR54Fw1ROiTYCrCGM9FiQb02e/f/YJ7+OcO2p08HEHnv6YHRp8wgHVT0wl/V7+n/CgS+UTrKDw1LS4qt/Fj386M5FHzrtv/ZtG8gaYs6KSmD0P+l/v38Fp40vuuM/AM7SmyF4RPudxpyhC0ednf3Bg6o8FDNjv11vv9riUdtnm8cv6y5AyP5O37oEX7c6eqvH9yFRsnnb26kT6+PbNzDPhtJ8HIemL34FMYToXn+PyCElAgk0GGFJmimxuIVlk8HupamH7w1TtPC7pcenG5+vqaTaLqeqfTo6BsVJpkbfV1h6b087jQ5Tqge4889SVlfJ4ZWVLcoLwfJErDwr22bbQaU+LYkECfvgHrWx6PghJTXtoVW8mp0MHlITUB4OkojedV7s17NrHFL54Cpp/FQp7TvOBWi6zYeXT7m3f39pKkq7Me/OHuULjm67hjAWEl9zfG2QnxAqu+AyvMobin7gCO6O8LMrRKX8Xl2E2QGZvhZh/rGfayNWM8CTDr8Kq+x8Cx5jJFv3N4sE9nmybZsPH1oDctZLMGx1nv2RAFgbCYRzuFnyRyWeXjNOlMNzEhrA1uscpW5Ecpt73Qs/MpUA+2LGe4N0dCMPwS46+eTkaYnQzldXhwFhIQbpdmBBTdKs0DnFXiR7KRCSnoQoJqnK80xyBg04U+NSGvZkoUeTKXo1xw/THLIpmiqLhCMydGw1xAFi8Hdzvj2FX1+LqPJTXl9e3o4RoCbtxPKghW+1uTARRg/t3+fBeWITch8pY03GhsZv/tg5/0wrQixr8GQDODKjwPRevWW7e4hrn4DyE9m7r/UA3DrnTXYBs3KZTkY9A4inwWchqXVPbhfzr45CLTAGUDLxA9RVggS2oOif/Jrxjeh4nfJzjSPkgor5Dkq8hpQETSolhFJaBJjm0ioQbi62f3tDro2JYNuSIIRup0xYgaMCOzwX1pkLTZNAPN0xAB0c21wTTsnIlIiAxj9aQcEux8dOGtMqUK6qpRk3VpMCtjYgAi6rfp/JJVd9FWwOn72QE72LXT/d9QpS6/wffEdls9vQhlLWHwCHPfGplbD65ElEcwr4NOez1+LGfeJFXfQmMopP/6IUKbwe7w7iHn72TpL9J7HWnE5rvErN7exxakd/YzrngINxb7Mbs25OPBIqMJxQQVJMZYhxFUZTBG1EiiqyVxAawLzZNFzfFSN3S8cwzzjSlgUrdsW6Nct/8rf6YC9fJD0JhGjmpfOdfyn6VL7t3sRs/98XEUKuqsDX4ZK7ciMhLoR+lcWR1GBHTiJwHgCUkkdb1ykBZIYbE5qkIZMWQT57nM00dTEfVoWHVwLUuyQr8fq76da+Y5NJXlFEpSSe79y4urp0iJxdBpIQlSnFONsO2vTy61dhDbxqB4evPSLxlpJzK1cdU+zJjGeSKc25DHcyhfEx7iq6um4Jtb6Ln1h3/JKG9+PZjyvmT5JXjJHO5+PzJtOFjyIiV+4htOhwXKaqjnFu3+o1mI0+ShaiBdGuSU3Sk9d6x5LOkwCKyWTyl5StH1TyDuKBA1PUSIy/AMu9TSRfEqUh2uT45uzN8pw3m2t/VhIVZXEEu/Afs2eD+IHyNpPG6329r0SIns8T5VPwvs8XX3V+MVBHmAP2wlb5pc4qnn2XtCt25JTZGeLDm858PUyGOzdltPGuEgLWu3rSt/RglmSWKEhDvjQ+yoJ0wuTJ+RlS6ZjKL+IwvzEROEXCEgv1VKi8wh/Jd54x2rTXrWgbMcC+UDbRM1uTz3CqHYwG3wQ3UY76Gai7xxj7071HiPQZ8bqrvZf2NkZl/H9OJprapNhUpr+I6aGti5ZMyK+chq+r70/XSbNuz33UFsz7+pZHOzl63/4gQZ4om81s9TGlONate/f96sxbr4ej4T9JUOT8aVarLmFMuieV/Tmx3rbqAt1aqHecyPac8HGtS40G8JSf/9wqf7btPJyG+A2kjrmektlrh+nBWQF4/Y6rVzeLAdX3jw1L6MiN38KUciiB0IvOQo6RMcfvdoicjx9R2kCog70mnzVKKQULmccxsfFaKMAMUn+AnQV9wXOo4tsMN+mNFzM3iPJp1XBQzg7OiUT+SfIiyXGmwYg56zqFtYDZV4bJv27amg0ppjI1JsjdvXZSfN+MY1XB4cpmoUC/O5voKdUiyxZz9kVqOz4OKj44StCaFyH33lV7Rwn4+a7ODMge5O7Ef7ZdcV/tod6rOrIe70pr+WZwx6WJq3kQUPQmI3pWqxul6E2+1t1WiZdMxAT6PdOjQHz62809+n7BXZqPjq2BZZ6RPu1pfcjwxRU4QvhBbzk6ZUkqRQppCuG5Aimhl6dfOTq71OArPI/aSRnIsDAktfaPdS/wD+15C+vToOYYzLp8kKdRvfHsrlf1ydwbyr+sEoPNbq1rgZ6Cn68qnjYoujznkxRPtYbWFtOfdmX/08/717eaiysHxCfSi9ye7yNu1jxdyB+4sT0p74CbUAzysTPLvCv95aAVlzfj1/uJ32Esue/MMr0yPXaiqYOSnRo+1EGH8sqfchtsPXKCq3U4y1IbaQArZeyVftlxBciqB+iKxRLDZwc0mWfk68a6wrjGJjd/HeJW97X5F8WvziRnd8I9nH2Rv2ACn7rX+48n8/EX/RbOANLfesreYE9yqRNt08X4bMGpy4iVE7kpRpGKOfbFfc6yDyvSmu5o47U0RlD44zivDksKsHLzhUH1GV7XPsmsrN9ZBQab3v1Sa9mDYo41AYL8T6odpxftUwCWV+trY+sJsTQSaEAbxG4PZdRIlmETIXR3UaBI6YRfeZvcsRErh+5aMtknyfkqSaV1y+9q198qAn3NEiA4tgJro5GGYPzOXad+D8xxx9VXxpZ8vuKd6C2EhjSnTsHz+CPqC62vJJnTY+cr9350V+extSvfX1igzSEGfNk6LUbCebJmvqFjfhJJ279CdsFVkONu9W9i6wQvTGIucJ+zULFUmnD4+rk3hu88ZC3lGSof3kmNlX0ZAaTBRSlGGYevAeuiYNqjrUoic5+PbowmsdSi6bSu60DVuTjpY1XVKqyruKc+lF6kCCA56zBfWb00xMfzAor/10iUXvRyqyCEZy2E5gWbXP8gPPW+pycGnaEJw3UuYv74nNgWbvO+eSD7R8LKMUS0znDs2z0g6iEwh/8b8AOCs67CQHPk8O5+q1xjS/Wl6+pWmHRZ7YoWwTOtvxZOzSG9VTRtl/uA8+jLk6K29fMi4BF1ixwPtHmu9ZvHCWCtMQAxT8EGbk/yQR558FMq/enO13tNTI5/crmStHjurBy769IZjiOE3wbIl4T4uoDo3bKJpzmTXjtj8R1NcnXxWcgnpE60Yjm11YMRuSCay4W5qLhfFCXmYI9AWA4kEkWASkMaiIAghFOIsDDPAv2aOiYjncMmhd1v4A+TeHnniORwIoN1aHRHHYJ6VMVsOF6UP3VdXj4u5MCn3wAIlDFGsSWzsADiNHgjvcRRGkl2WxEkZDV/UxT8os/sjFeMbFIcDY3R2R26l9tXZQoHKwrhYEfYisg5nNFFNsSYSEWKCkXr0ZGwu8oZHygW/vTWCHWZLvIyPpTJKkjgZnevRrVMJy8pi1egO5Jbv0WLs72JrRXur/gWllrg3mwVU7AOVPpn6FqRxyfpJfAR/Qo4Spz2paRfR5s9rZ7iuMn53HumzgL5VMBTvb/Nugdd34VPK+LoUShmfi5RjnH7dpdSHS9kQIGbufuEmRFpuaRXETzBZwU5C4W3hNAkjeEl9hyShTnSZqwan+yKJRcWF/KmMadTXknW1o/mcJmgIszuB2R/qxTHgTI3WARcNew21fb03uN8NLnsFVVGsa5o7U4D2cVH5L1QxOP3Ir079/4G1iv1Y8yhD8Lp04yq9gMgRIpH3JbzMN01VdXbLiJP9iMoKy5Yx6KTMWs3Pnf85Y6kfOy8FAPxcMi9ipnlcGnlTzpN8xOyT4WnPIxp/3HsFTnaXFx495XKzkRTneX2fP6HVexFoTTbcdyHAjf/rtiHB0aP2r40v1H/d4/UIVMGBoCzS2oLTn/+9t8DSyOcPbv7MPaa2uwI8Xvl2wRr9bQWk4c2bYia2IMABsVY2W03JbEFzyt4dRyTxgIcCLs+QPJicZNecSydf+8qBfulralAipr/kOLWjRBPvGgw0zJI7nlpqq7nys/BScrgb6ubOIkrpbUkeXDsP1JHyHuXrMS2AYBFugRmV8vgHe++NEZwfuGVn1S9AuPikYLdwr7hosS226KRyd7ZKHfULPHDDr35Iqr4IOhtvOLt8oytwInXG+PXR3auUyNmLPqvv8XH/fzVt/dBa+eVs8B9zfNx6rZGHR/+ZL6L9RdqncesTPLc/5P9zcvCnYjMnzjiQt70HK2k5NbmjdgBD+XxPaOgVyUE3O5+Biu3cKYZ7jD9JYWCbs1SYflHylaOE/7bG/DKCcRoWfVp/8SdJkCOyCqTXSgptUZTjvhNpu3RQ+tYZSNE+6lsbIBqPTnDsa7+wnLK228/IHN4pbfi4Y41y7HtnrX+EiuXbjIPAdmOP0u9Ny4JVxZjNVczfbcoxBAMp71rlPsEptgAdTlBkO9qfCvVWkaprtxT39E5d9GyrJrdNmvjt+t9HAqQ9aXwPDCDV31tyWSRdllMDpkYtoWlIM/jrJe9F+QaJaMvyO/9ObUzTM+oxfmaemlAflMLYshTfqL6TONL6Q7iLJ78pDO0h57xgsReby+6XjTPPFuO295h4S/Mq/gjnvyHFwn+mboTR4iVV4jotkt4WqnBUz9HTM/10QsjMcPNGTmybHrru0jryxhvjU6HikbEV2+/PPrD33LqdqPK+M2CN28jtcwq3ip9Cp8jjAR/QNAvbAnNN8L5JwcGvJJdSS4zcg0CaOlpA6L0jCxvz3oOj7yGYCzPYjSeauyS0wUsQUH0sBzIRv6N4SUlIzr2Y6xdX28EsNH/J4A7kHvpsP5T1ANoHt2Pbzl547CMhykPMntp6XAHjl1Ne4Po8cGu6dudUHjXI88N4rZuxOWwTTPwLAx7t9DHNDZ3+zkEOR1W5bDWX4lxc33nSXnMM93nxZ4foO0pG77cnrnW859TcB+xbBQjyIAPNZeYIudJ6/V4QoqyzD7vGUcysGNIjbDHszUNLl4d/eNs6mlRMbHUt9PGDD0N1Jw0ceVCwkm+3cA9WnlaVayUIDyBuz+AsqjO8OulBdZ1QBTWHcq7hyPEKODQto46QTU8Kab8KHkO6VTHRqw7Kt9Db5C87G9xunaj5g/JX5snjIU3QYtaCbcl8YdTuj6EcZYUPsjDYk/fY/zey31LuWQdYTfqOnv/z/A2g+9mbo78sGM8fN1EO/r1OTfy5+SWQPDg99jFhUpkGTkW6QehwNcoxSmXnP9L3Q3rzCEOifxJ/UjMXS7k+Ac7/zD/LAEa43YwCUf0ebai/EtcuKy6c6XJOOGbFFfxRK76HyzvpQn516y8fqPt3AvwTD06F+7mwA4sdi+xDzKmoytVoLXrArC++3zuM9XbEWFTe9EJ974LHwLaj19eW+IeYHbsrBkNzmIISQqZBfR/v1oeyv03+KgzHPnc9gb19hi36wtGLJWvMzPV476vKr8KgVpDXykSBjLDUlQ06g38d4SlOh4UzTJfJTdHBGFq8PEQsIzNj0Brk4hWX43TtzXkcue0KnVWJzfaIb6J2TefbYNigmEz0na1oOkpBoabt8d4efzqrhvIyyWofKhW3LAuITV8ER/LX40NbPzY399n2LuhMD+T9APgys0qJ9BRhCzl/+Im8U8+1OM5TiJU4ipe4IyjkFlchkfw2oYE+E3Bmb2345IizJU3Cmgsw6+nv3keV0N8YQhi8Ppo4XbM7D/a7BAj8AJ0PC1gQWzFKG/bOLCzEK/bcJaW2Q7z84u/dY/wBz/utfSJbDv169HhIw7D52AlGU5MdpKqbo7ir+yLj5Ad5KTo+hH8vJnmQrdfvv06Eb28oGbJOMPNyKPM+9RIdppSQ462dcT9d/q70trZUIeVBaQnFhoqJKmLeDB5nKeMxE3xC+B5tqa4HZT4vdS28FGizXO5i/yiW47farMAUwm/5cHk2f84Fydmi8MWdYu4yTnvrwQgKfL28NNjZY0bvRC6OfOcAe+1QB3P73lT5kHaqjN4Zp5d+TajPLSMM73bSBByZZZmFv/u7YGCRMJK4a6Cov8cJaDkPK7A37UU6mjvjixRS8yVS2gtEiDJzpJEgnSNriFM4Wae8DceyKpzUvDtyS8Lgb0jJb/UY/NQ8Yj6ilHk2XstB8+5SbOboh7W+rpIZsIQmxUxdrtNc6RFu9gPvgtTyuGhUpaw9FcNgYe3nB/S0Kar+MmKzCNsL94xcm/3GbXv6/FfZs1CqNpgLcfbsA5KXLudq7P9uPZJ5c4e89s0T8juubGi7jdmBwop8deFwB5HcKzvThzn/gQ/JMpp8LDMvuxr4OH4H30mH/Put4E1aZVZztMz1iwbhJQySeXfUqNRo6JXUNMeDkLSwWwBcOiwRYG5RxuANcrVDhkjSUStGem+EusG5e3xBaJkzsBLbTvC0zUZaOtZv91xXXv61OIp94+zKl6U+p1BA1lvyYJ55HKTqTS9GmOHjzvagM316v2gNozluo10tfEe/TZmR19CDfLGe21b4pQMpMl+/6ROeD/6Dy3nbImnBCH9Xu8e35uZy4gzR66/3N3/weWZQvngJ4VtLzl/8+lyD2g/pgogHSqOwBdj3NgThmw4FEB6MHt+ZtsAWtiFmHvoXy/xVXHd691TiGxNktW8Ij2x4SNCWCsSV5HQ/1VqlP9CG8hdWPVdG+5zjcTw9scv/Z6zxpyLHUeYs0OKBpfVmvwnxFz3QaW6O4je+DzdQ+XYdpZt8b/jFxwVhIPJ6w8CkBBkU1u55/kiIS/Kfp6shC77iOz19tUT2WiPadI836R0ZUaa3j/oux06/hw/Iwoqe0454LnafVF+45Wa7TZTzeM+qLDUV70/trq1e4BPwLMVRQbPclhbcmehhkq13ngxAgThtH35js8AvCKLdrt9QaRRNJmynmsF7NDFGnSs57e9Tg0saqNrsfXS/O5/M4A4niK1lszVGaZSGkQRz5JUw0Qi1zvDp14Y8pFZclC9pQSYGpU6cG49TtsN1Zl3INrAOrQNtHYJbvaV4x5TmH6ZpY+ISDLmX0dswNNcCW86iGiFdnLHdzRX18333at7pWEeCYvtgtD1gmw9+dkTPDs6OY1pkiYksjeMdaYF6SPXbEe9mqeaYFounL64w/He5H2nA8KN0ytlgSX26UeQb9UsXK+B4YCJV3Z2vuCG659xdsgUPXS+yKIh+zi6LRk/5DB/1yl3ocpVgW+3xp5UlgzHadGO/rFTwlC46cRCaAseLytynyY0aE3kW5eVkocz9KnnG3KVFcISpkkV8h2tiMXJWbVIqQlD1KctuqpMU+GqdMTMd48lhN8lLgGlOqTd97t3sXDd3eqWePPf+cCds1wHSBo6ctY1w4aBY6llRyBedJJis/mqnQE57Z4pkh5ak3xr21yoNQt1rnam7cHvhAW1U4+zmy8rJqjEREJxWYGkeVkOCLjblWmgFIh4Ha2Dj8p83IVfJQy8qdyvxgKk7w7vG6ETluQzOvsNzLjaN3KU7NaS62hvDVfLZXGWK1ogt0fctXRiNRODDt3mymTL9hG0G034Sgi9nN0VicjPQAIAEp8Ne7h1P7oROBymuZXuYtaGfZFGzrK9HWJN+iotKTqlwCQpzYbZSh8CwedxaGR1s+fjXFQm6kduI1UAT7LVGpE74o/NbkNGV1COyl0XTZGSq8YRW0dVEkPuBHnHavvfldPsI1r83oi/8eAXoQgVXyumkZhtnwZqAiJ8xg4NEZseufmOejd9vOuwcMnH4USKrYx2zzeASw88+a7pzorlPVR4HYu/Mv0wJ4+CDPLQYTzwPJ+Nemxg6HfK7eZ9icgMqMJDhk5P/KbPC6OzZjYj70GbHXZqz2KWgnIZtrByBi4LempjE1SecloGiDhmwOdeMm6nm0R0IKvGng39jVFrjvthMkY+t7PmmLsSs6OMoc9yk5fbYePOkl2DdJ0Sy0BND6+Z0jMpgxpAT9ELk/kgB8qrAtgOm7561NjtOMEtj2nF7rMgQDNuIJxDyrtmVVb5lM0ospMAVsXI+yy72XB2MFF9jJgWkUbF9Rh9tQIxmdZxAkz23ePkFjx2Wj8aasxBOGwP9W1u7SIhMWBUSvfzbu3hIT1ch3ZDHqJZF6OGX5yo5UceL2c/E9RnGgu65aeKKWvuDdK+Ee+9N0NlpA4CoIxy6T49pz4Vq2A7VYSR8A6qmJZ5oSnlSVTPnOWD5a9TF/4slzZ+mcCGMFeSPmw8EXvK5eL8cbh8Hdu0Heg3LQ5oWMDQeYUhlc6eS8fyMN7ESOSM1FSd9ir5oWkUTl/hPUSkeq/X+a7RM16njJriToCIcQTs71V8LcsNIDWb9/6jgLttTaT58z+HRth1muYHXBpu+a/svIlYJa3AgDTvrOgluJlqTpDwS5mdHVGR4GRHc5pYOCquZvnsNpt5aRg3F24+AXxswhAmC89GrIwnucqfnA6/D/DlnsDKBkDnoJhMgyEo5KSTYFusCGNGHjswHA2wivJ8BGRQqC/1ZOmpzgKoVcIuuEzjrrCjUzkrPf4l0BXtYrfLY5FbCXDxsOxE8/6q+vfU0EDMktrqaKJb4PMAbQxUtxKQz1kQ0XFgvwHRlfCcajrjnv7zbGrcVGAajEqQ7YuThFjHIkMhOxF3KwU4vkUVWpW8GSpA9Y6jR+KBKsqnXN9jQxWMMSvDm4vJptGbk7hngftESvg4gV8mOZAe5TK0ZyCing/MZId1FVWrfC7Rr7a/k+siyqq2/znXL9AQ/Mlc/66pMYQPQ6dKqzsHN1GnnS8/qP855bCjY1J1c+fBSf+si+wW3XYayJd5gzFbxZLSkuC4JzZ0y1SIdgTubkIByi3z8nMzwMXvOmUKGRIVMUIXtRsNUcETKBlQCSW7Onx2SchKtXcNIKX79eYYIbIAsENd4LoF01TZBC7YDzx99Fqb/FrNnL//7JvuRBoIazCZDtkg1EPY+UsXT3ZF8d0xLRfJKMWd4TQKpYW6V1XCTw9Lhh1Q4yCXfavnNgZOIeb94mdUb0uj8KiacrDE46cxu0znemUmHPLtGbJT5huY35g5Axgqyufc8b6TOawpA7rxutcsVrb9PzpYXq3THGejGSB/hUyb38qkt+T+E6uMftCczXYJCUERPITBv4ZCgewQHHaGXm3L77dDQM1a9j/dFUVx58bHnfpDuwk0S0HbtXyYoqOucXBK60ICU7d6twwz51kXC347NINyPnzk/DN6E/3kFHBUvF+gdUedTwmKN2EzNJpBKl1Z1BF2/QOHtEtHOaozPahylZMH4lqy69NYhk+/0MkUVFR/2pHSPTjnadxt3qCzCGnhchp4z8+PfWBaVwgi07S1yfiGSnmPjiRwTTwrO+BxfY00R50Bniwlp59bkPsSlG2vIfxIdgZmzuF0a14RGcc//bC+gmi+dOaSc/dr9J1TUV2sqInIcnyzzdKtCd7/keeN37jlemIFsbwA3MX+t5rGWRvIiXmCoC/YYC9Pe+7M+jE+ksLGVzNhNOewvRPzZ31Oa5Ix922YigoLAx691ltnvxZ2hgdCTuX5OX7HFosST79JqCPov6ePflqGs6BLwFwcAmgv3XMn678io4RPZIwUfipcRP/5e5sTDzYPSF+2DTc8dJDXZNSantyzs1K/5l80vM07O+hXeASwHk2lAzoAAA2wLFJAgqSaoTy06EcBlx3vxAA0c2yy+zIHrjS9LO79+Vu3MEIJ/aJVfEXDeFU8i6UCyEGuH22gcdubT6cJsopSeSjyS3H2IjcESGN5CnbgHzbdsV/gfOsbbb0De+FLGrkfrBc2n55t1jN79AHeyXKki6E4BYV5RMkk2sW0+SgpGxNk16XIiGPpa1VywMaeH32SWPkCsx/G3I1QZmIEERmFUj6FYgARKC0BTM2OSQ8JJ/t4COtTlEFoGE2QTmrJ7wX3rT4FRawGs3zVcnH1uadvKapu5ykBd/M++DIhqTCl7lyZfdH9GwU2S+YRtIOu12fC/TbSbwyyLZGfaZfoiyqMtQ614eP08SfqAozagR3FxzLokipJ4EQGqT1MoxW/EZjkSkANnTMtDqDAhpCMlY4LCyU2BtVnmp0+YLMOvCxUtlhgKFLW/Gpo2PW3itHKFXqp+Gk9z5mRr1EVvbGk80dT487H/7LZsIHpI7MCAXbLfoTd/q1cROP+9td4NkNVhZ42LMLd50f83evmpfJ+PvwpTvqTvTJ1vxvmRta7o7dxOam0/PMEVy9dENGHcp/qkzwTY64e+EaIN4arqQb6yfMyBOx2HDdTgjklNvl+3bcs+ydz6jQI8FgUBXUUudDK6uyVUlIICMGrC8rq3IaXj4ZwnmX++iNptpKO8vUJd8QYAdS/2Bn3oL0AfdGO3snPFp7liUdXh1ymfBxhJZ/ZtldX3WdGCsuhPriH91BQ2npkN3gJZ4XGHj5EfX5S5qMMijwiqcqLD96ZnIgKqjLDVO+nMKKGgE8LB/GYqCPJHi+KDJ6U9tlmj31Jx6e95MVM0eZc3euWUpO7owqVuV3QUH/Ok2E51yZfdwiuvm+Dwpy6y/YTZDSWSIZvmpaCoDfu85ISN9oEbeamh4JDC1jqi0CWlR5NICy2mNu+tUSE4RmCerN2QzEbFRmy0nXTbmJo9wwKE7Xy+oUNXp9BRlNbCOrO0ZomvbZfJWQE2Un2NJOtCu+Q32g50XfK2RM65Vwj2vNxV58yOLpyzjGq3llqpna9Lv47k2aDqq7vw1N5S6IJ086mEok9rt499vXe+M7RhjOf/yO6zT8gnuQJvZs9y7QLHl8owptKQpdETuNgnNVgEyTKm7pXOZ0v6CuCjqiactGfWoAJwdkf/f5bTd8K6ZE+STQhmQByMwGtMOngrIHHm1AM8PU/LZfLgAQhqVTWmGgRt4OqVDvXCLLml5DcUXZXEFgCZziRxuq+b8XnUL8lj900j7K1PObDld+I8uOQaHqSLr37EYk2WtGuIUerFszhrEjOHczCGFKTEp/jOsBAqcViyobR9OkRUgGJpVaiJ863Kc0o5MuEdRNDvEGtDjzs6+HSG0kftt2ILn5HI8AV+lY5rSS5gLDvsGV9UyrjBVJLNQgm3WDOWe7EK/85x9RF8YRU293Wll8Dr1XdAX/HzqGk1AKczMa7cJdyZS6xyT+OdzyJ1fZrESBVvTmrAKWN/2n//bPNUqeYLp9iD82OdsIE5u0feS8Z67vU4CVet/L+KNpV/RqayezqiLG/CNtqv6Hv8YXaqdn1e4fldkUKqfbLJpDiY/yqq4WpT/SsqEPb40z9Fg0lritBGHaQ1piUiy0uYmXxpLaWWxbUyJ6Rdf5ERR/9fWG2z6YZDuyPiiPb9mYsyzq8eWMu9wY3uFib/swOggwOgEUtBihItO/Wk0o2bz4wAYVE+RSK6PQESn7zCp9+7O64F8IfyYdvGlMlDsyTOSP7+MMgf8LN4A1sH5be3JUeR2pu+krWCph7d5G8ShO8OFV3Esbv89/Tx9bEFthxT39vq74/3cpMvHczgZ/bWqXY87p+cB8UeL/cG9DnsUzng/G+NSkRRwz3tQX/beiZ5xFxzCV3+A/686vLy2PpvGW3Y0QgNt2Slvy4W8upREqg6mloSzMtIcibq3XSMzOOA/1vnQIhnkEV/lnu9PhVVd1AJ8S7kcc389MSfb/B9bJ4gXIdILfYvXJT3b7mzWxI1C8DShCyvul8BLzElLKrTclMpo+/dxS+d2usmizwIhBZMDnuWjeegOqD5xG5T24LhUw9Aelt1SQ3lXDgk8yYCTHqplxd5k0G0E/KTIhKTWlJz1THf+qFboVJzAnvbgUh76FzII1qUlCiSha60oOomMUuwdC9wllVVlL8wT2nlffJ5TlrRCFpgtUkvUNWJp1q0nFZBfCdfXqwj2j+7zgX5xchq2DcWWkUrsFa6rjM27ioTGWAaO8WrI9A2ESmgGn2Rvqi9REePiny4iGrTn6+g+0Oo2yLkvf/XKnuuWkyeaCKbA+notbxtmLDTH7kJ24lIhlDHgmR6VE1El5Vwv6No+BoDQDFVyAgWtDPuClXm53ho7TyqTjwfMwbnUvYRHVrxFRqGxZ6ObilIHR/2eeO6JP7jw83a9lq5fxLsDpH/LFw92H6SaW1n13zgOx1MgGp07Wy3lVpOvWminp45vpx7klIim7dB4NDk97tPeTGxyg3l6g535S5D4TUH7DHZD/5sAZm9eUn1XqUhZZOAXzk4uFhBtb3XNLdpVcEY+gANmuNaQrsTuJcSj9rKbLMnMGq2BKATy9XbRpLjTQ/7SG8H14eDpj+KORaUw4Bq/lDHuw0xxjPYHFbUF6S2wY2waosVrmkMj2YmSauy8C0zAMaurzWy7WPDBY6fgnATgPDeI3nFPqCf1FZeYbCrnNhKtkP+6aVrCHMA5ZBOJXbZ5Lg5wj3cDp/Jnsn+EG3ZKg1StyAuSFc4FEaPrkHr04u9xUYzG0LxPSwSpGIs/2FxNlXQwdX9PEvlkKsE9mdxO0+mslWqHlEPFuppxjpzk574BWUq3CkWuyAM8ylUHzmjyCe5gfoogNzWunNjynk9qa8aIK8vGRm2G31+2RzL6NrGn9cRdp5jQRMdPWzxzNajqCWU176V3B9kih7Miv2yRZnnCH385qlUdE0ordGwd5MJxitDYiYRyYb6UUyJ3VOzA+n6DFj0Jlvw3ZUN6zB3FjpUaitXHrQFNqhcGhgwcUiiEvDdAtKI9c6MFoye61j8Jsdj26gyXoFBC46RxXXWzTTvO3V+Sj3wkfSk+6Vs6gdnTzsLJafg1bfAhy8oivlj8KzgKp3k9z3Tu6vA3du9+XT4RhmsgEmc5ANmasb4ILJtegSwrfLrfo81v7imeSX+efO9Qc+FZ9kujfc9E5nJMPceCkeKVnpe3mXtq0uKqNk13S/2nK8J67mnTlF6UZKILrANNqM7qtMyiY2Y8+5sU5qxZfTHFQvBec/zgbLZK48LyK9Oa5AVYVWeeSQO+8pIm0iUG+CZuzAc9syhliXm0MuQ1I9jzdFVeIs5DANuwR3bYYY1feDV48wP+uwTIwox9gipvOc4sqiHe1ZsitY49pepLXEuG0qMqH0+2XpAvgUaPKcWMZ++09FzJuzdiZR3fc8Fnh6GtFrAnGlBdJrJ33vpakBxjM/soqmuhDdNvGRqVIa9aezFtzEJv4UB+MfVLw7+t4J360jj8CNj1CKkKdEEjBWWsise/RCWKY4Vn57cLk37/Gf3zL2+PrPvK3Kd+92cpmkGapopHCKb1L8yzf2WorXde0e3Jz1h067r8EnRSklLrKc0Chi0BAUkWV/5ln11IwEvTk4+nrNDRl98Y3j5O2m7VlFMZVBKjP+VuvyGOZKFr56a11TcLNj5hWbapnws/6MmwYcSYEdMQo9TJKN6MLSOgvRs8xA8iVR5ZX2+QU1HuQhezBoJ7FG3PvN7gfYjynf/d7/Pt9E0i3nMoLm3UPvIo+l2Kf33Se4Z5HEAJzoHORDECzt6X4fgyxvMhnD8LVf0z68XqUbjA+uXl/GPHPD2LvYsCfPjtYtlt3hGbdl9rpvwtHUHiN6F3XjABnFevb3HGni5Gnp1+DaTH7naFo/T3GrX/JuULn6burqzdNV3TPFgVCCtb3itnbEvJws42z8gRxZ0V8C4Sm8C/hbk9g1IfazihPLMyIMWBzz7sFUK+21tXrubiq4Y6/x/G1Q2PmqjoL99cSVSpYBN+41CClWMPTH9OR/3BySTOVj87IuwEfuc6OtNBegrSO65v3AxP5ORoZwzqKDGA8cwi7J8Se8HDl6fbw6RJ7+pHOt64XaRiRvliUz8xjde69NYhzuKIhgztuWem141O3fx8DAOQI9d4rl57ZnqSV2GsziBqfFN1gxXcQJXkyesD/iP6pw2OqPLdJYmsAp8qwWWP2N5xH+OxTmxboTl8UN9EJl8wtAe3J/XkS1Ixk1T8vzInqp1V9PvWo2u92LLOg6UmH17/5uSTNpTO9x4sYApIW714WnK9x1h6x/nP1H9Px5uy9KfcW/sGjGChb6ZAHk0N2AW3YYbeANu+4BD+cKZccz8z+VLhU85Vhs3DmXfxRIKKbLyCDmFtkAHgVScitN0ZyucXS65T3JLTHcEFBIxcw7MePWrRwVzo5ZzZYDnOsTEnkmFYr6SmfnS+5sghn3bt9kfx7pXwm/BoFs/W/bxit3vaR2flE7oLocUoKxjuLwK5W4yHfTucHUk/4kylNKs603N1b5U5Jrf5mb5vthvCuS+42MbgFV5oZcAWGUtTt8Qu1mVyHlzOGTd1UaECYHIoxBlYlEQArW3wUhoHwxbOqlDwsadtIlBxrBpHnm7vZfhm2ZLPMZJMPuIC5C/6jHTVhBZXcKogGntGVSsm8n95t3r34Bvi129k9InvX9TaR5tewfXbz8qjzH7axtx5VqxwJqABG6FnSgTF/k3O939auiJv9zSryzxDhHOlntdvlYHN3LgVtrx67/nyYDAXddkOpSy1GPD2wmFqtCtyjECdsdcdC05vj6l+XgfWfZvuwkZk8A7cj4QF/sXsYwqCoqUTVGosXF/9qsexsWZB5G5ShCjkM/etonmUSokmufY02Y7JmZrUVyOblPiUVNwKQO2fTTfdllgyFSSxmKG+rGEtqSIGSzTkfrrbh1/2K48/RkB623R4rT0BkH0tYYIIckvPiTxBj0xe0hX4aUgfalwwqQvdlGX7FgMaPE1b83eEdVgFLiM3iHhANUPnVdiKBYWvlkzJoc6FP5QTOBfiXpAQ5hcHRZnqZtDPsHxGM+c5Ebk1SRORoRIGIfVNAl01kIwHi27OkVjj1vxPEj2I/ncHZub8LZ5C7OaUJSRcJ5DaQWorKlVCDedDswNw0PHiuzdrCX5lXdZFx/0iQtntMgCzjzuFJO8TdsacGbb1y+oRBo1IS70IGp76Da4bSFrtM21iZD1zRuZfjTglYHoPdnp35Dxv1QdzaFVmQkTH/RnxHbJLXWx6H+GnHqPqX9FDZU+vxl9t2OY5VnhGLx8V8NoRDnGUOcq8zYdL+OazmrOaHHkLMrYmrAwM10vuaE29knK8pdKH3/9IWhOSsm5TkVlRrqsPD43+IOgdhT3N1beTgfKs5dJfHjaj7eWcHbu7auvvwm82Hf3cf33Gdsvu8tBlD3FEheZg2Gg81Hu5LxcvCcNRvJRMpHzSgyjILdciAvog/PPEBVgUFagiz4haSRA93zBzLyMVNS1WAiRRmcQB8X6a5g2mZ/VsPgqk3NtutqAgXsZk4STZYhfMGqizu73GKLZl8VfcFhdIU1+tJjt4VJ0l5iKBSIEUVAIo/DoWADi12b3DwoyxS2KAiJncdYbU9M3nNzymlbT9GyfquExrFvxLH9Y+x2UqdZ+KLhNPgnjaHXO5n6Wq2npWPBcwxfETZuez3QVzy4Vl3ygu+43BGo6oWv5q9XCCI5I4yHOjUkZdASk9BSKrfSwXg6h0B5lHTJvTy54R/X2szZLQc3zJ4llZR0r/qflEdPRcxorw01bQ74QsBflkA1EumRuS/5sCS+VXfwhURafJsdvIhosCzdoe4brt4RiObfLBqmtLgmh8hmrutXwdCdnhvKEg4PoAx66Ji5Il+YeJOJHtGmFoQ6ZdZzOFEDowp+DiVavTftPBJ6Vxr4npHjRQYkW/mu6N5t+bwdf+nH098rgseA6aK0TGTgz4URte1TqctAiDRk8C8AcQ2V2o0/Vwn4z7Ijyy3GLSMOHFA2C+pCEDFFuq/dKhrqlQy07KAiYVtKtlEy9YdZ/gMXV9fT5odsmKU0DBGUermhmO2ZtzWg/GYwgZ90nVJ5WeYDaAhTAaAw5PKsi1ZNSMko573gYY3H3nVj86wfdBpRkP9/p+NhG/wGeXlfe54+u536PQjCv1NBweEEXkPxlXZHrISTTgckuSegftHQU1a9GrTeoqaj6NngWye8x0PcKMz3ZSH3BBp7h1d1MNPPp1vy5jLgzqjgTK6cwKUtEAkrBFIqm6ALcT2eieIFn9x9nANLfmpjZr3YGSg/pQI4kUCIEjpD8aXk3AWh7BsVIBnnXQ4+xMKhbcIA58LORuwAJl/ItVt4rrw7m+hXNuetH4F6jHvxwhN4w8alGwJy/MOiJWDVEsLO5EKuW1bizU4ZqXCNrsKu5CBOqPXvGF4fm/AF/SSk+YlG3lDhaX3h6PPivHGL5w+srthoyPUrZtdN+ubotcQaQjlInOCuaM11szzvzmRLKNqUz3xr7JvCIeL7voiV0WGFO6LbL+AGS5PgPwr8jVkFcDemSIu6e6YkassicrjQUxkCzU8ZQ7KwNWCK2yFhOwqSFrbkcNVhwVKPYmjrVRhgFopOZYfUUA3LU0QaFXW/Om3n9NacBel3N31le0eyBRI7ZPth+zIeH1SdPuFkAyJ00NQ4WYMHEinFtK+Fi4g0Lfez+rVzCbApvJLe0bxRNXvxuEuCHX/aO0LVguV15oEbu7UWBbBAoDX3bJ1jZfBKY+8+ojSHL+Jr0oZh6D3TwifBElDVByG2vFta/Dqc1SJMwMXfAhKJ1FEcYRVChR/nIj/nFb3SWaSVsyVt43Ym5TbXK/bWl8oAqk0fUl80lVapC7qstkbepNrmnzLXUnBzOdD9dYXPbdr0NSHUr8NfmNQ3Uq+d/++wYS7sBpz96csm2gJ0YravfmX3JzJ6+C2ms1unC+U4vkhSv7gvywhQON9bFiChOPAF8JjJMtdEX7x6pdyMR9UJsTXBpnLjXMVELSyBkJkEiOJGHK5zKNS4xadNTmrlc4MRE3umngHrSW9bqYEAKYyKLbeozN6Oz0AG0u+GIc5ry7rbwHFuOT7jzdCjjrMb/xnJY4S28+aFpI/0PdISR3djywFwcIl+N0q0UPox0wj6Uo6t9r71ntgfpe/QU9axINHM2W3PS1XmKa+cnXz96PD3+Djhvx1+VXyF3uVYetv/D747Kz+J56+mVQWR/kJeAD9GEvqj/e07cl4c9aMJzJI9sXwDLFTIag4Oxr/E6zQ8f8USGlcEfv/UZTzglrZTgP2llIB0885j6P/swOmH+nB4NuSeRfFgjELuF24ksXKlEiOdADXGIQ1Qxqfp4m674rFUr3bvzGrnyaDV/H/Sn5o/f09kYKUkbcxjyBdcJAlKqWYyTvdcRLFLOGEbrfnRhYqtEzw5/ELcZJPieulWaTemaW++pc7JSBlhP1z6JIFNqyds6s8Mi+qlLv9GumRwxg2fHkLbXk7Ub5lllrhqMBAT29EIfmMM50ozPg6kkjdOgptVvI9Nz4Z+ClKDTD74JOvBIGqozAmRqVAOjS4tZmeDekrLj5VfYofJC1bg4uj0fboqUjpKoGSOxUJq09ZVnAtihXkgy0IqXOcWDyAwj0MH9Oi+cxKRV3+FZwl+i2s+EjdxJuAlrwxAYxvoGre4vlYfTJgrfubYCIKYHkcRu++0NiFNUP4VjfIcclqBLtghqsHBSAI1bdoDhN69R7FdPQErB/fOGHoNySRdibVzR+Hf5Yg6q8jzZBkCd3Rmar1OMWtHXGU6vb0ru3qJeCKPUNUdjaPu3CW8JsBs7QqWH5y2mexwu7FXPtbMO47iUeYINCcHpPFpmoEArWSRD+iJBeV7ujIc7KwjhXH6Dikm7KjiP/3WEvGnhZOm67MVfFxd9FkylvVR/2Y5QunzhQssfeCKX2w1F3fKtY1ZqwcTVm9ds1xpi3VydiGmaKZ2vjLIqlw119lBBjMv7jmWBSvJsfFkv+ervkoPIjpMxi82lW9Ezq/LWYVKz1nG5chif+La0+kvct48qERmbp8X58nB/CLKL7jnoF7Vqfd/ypn+WCOYYKC6r+Tu4kMCELKbaxNKA7JP25HutBvtBJYLaRiFK4G7haMAUgFN57oivCgzPy6rXhNxihqVt5ifb+EYlHko/EIZ449ZVGI6LAi+7m8ZWiVCMM/9PD2SX6+bx68Ct6alj1oUAbPAOtFeT/d6TmtNvdbdSiylsvnC32VCwv7K2ey5jSl4NOjsvoscp5K/VT5GipdWeNyIslUUdW6jHxKaUqoZOtooZ3A0Piiq0z4wp3hxmu4h3RKLFlr9hpKgwLBvf/xT+wS+7ANrFYPjpzZuF5GBGxhxQ0LiXTPrniEUM/fHJSku4jXv/rWz+sBuYNpdRlS7zRXAk8E+RMMYk538dHPqghywAZd8Z5zk+sK020YfQob2G/LTFa8anNOl/vLS+8otcpDrODRMY9Q98/Ar88snfl6rZl8x2oOZu0iypCqMweVHYdn93LMT47q13a2B/txtBTjCEQc04IWTTK5vFliHSpw7HBl82PLmUr1PAcFusxpM9aTZVubKJ79Ovkq90k0LpM6qPXs0CQxCpm8N+jUbU/7OKd5NfF957pazJNUWCTAevidLf6Ew0b5kjnq0tJ4MI3DUYZsdLU0InkhLZ+rYWrKNI0ZUK4rroE+OI8vnpzVlLiRfnrjiHvVdC8TEIeMFX92OsU0TkQuM6zMo04K7583iiblrbQfqKcQ0LsVemYcIXbC5vR+Zu8ANA9TJlGWW5DG74L1c1xzB/vrmOXMkSMyg2UYM2vG/iqbEe8KBhh0xCrQYdzwcN7zQ/POWzjmnWlLPPNcgWm/b9S/zGPIBwq5kQj6HIr3xFE6R3/1a6NqG5r516h2MHQr1f2YzPD2Jtg5hfV5GQKcOTENYOUL9Mf/CRZMkfv+7FLdlEFn6FPsCJjm/pYbBPIjpe6MMR9ef7xJl9M3BqOja+CjBx/nfxBadklGhFEYRRHD3qnCGQQslehFsOCBAr2CHBW1SukZBxz0OlaKV/LzPfNZnt20zMM+09VlByDzJWpA8iqSVmNrk+JbQk5rcaqUaqigIKlkDC7ZB9p/vQL8rSNTumQAFFUMfpIGPlUndmMsgTGNCt1TbiJmnCtVCLWVkIEhBzYeGsAIIb2tadzumQJZgW9eJoTiiFupEufYyHe0MxLYiWwJFezKnEgw+AsOoZ/OK3o/FP2TNo1b6FQS4K3z8AZdAc3KiQebz9BglEuou6PcRv2HLsE24XmXJkw2n51MDXVZMeW6cyYXI//D3lc0tmEbkvpc1VBTqQlLU2m52jM3YPFqrCvMqCzR+Vbt14AKBtBlyAFrZiCo89iqN0/09LQ0saQv4B+siTSwrdzgFhDSv2QmYNAWlIk/z4bCiTlNtiytuZUlfjC40sgWkTaABQ73PiTQ8zhfZRJ5uGgPbDEJ5e6vRngb6zEC5ak5mukjVfWVdpgoRQV4BHY9KXgrwkBmQKM6u//uI144BL/7Cxvd8JzTsneHHxE0lkKE8+vtkIzNyZMSjpXjX6nDE5MBFqjvxGUtvyMV3t3LGH6vAC3Pw6rSr7ZJQyhV53lCuiArMcV5HrU69w5f7ZfBlEE81NcyyujyzVBTyVjU5SujdI1W1D0DZ/dQ67fKCSX09OUlOYS74nfaviJ3z/tn/xIH3pap6h7aSRO1jNsf75u3tWIqGtLL/6z7zy69FYCSBU4IBpWoMf7+iAWvsLkVe8j6Av7hwPMzA9bploAgmL5l/1SfVlvj8wmQDQYGytqwbwuW7WkMF4OGyt5W5rK8F5ZzyJpJ38sp3qwzdTo/s4C43GDYgs5Vw5ojEZRE7ucf9Z37KzOAq52suRcDGK0JEi1Z2VmDF7HzTWJxgmFf0NKKMRXdUjpmpOmkUBCtEK1EJkCwm401H7enEMWZgHC8+I/Fp9mEag+VmT+25M88HWP5u6krzZSfQYh5pWBY39/owqxtwVYfayy4Arq/50b06YxLLQWooBB/aSJHlcgASK7Jmcm3WMrazqeXqGdGs0Zj2avQeB74G3Gi7uOWTRnyQfkJ7UW2cfTn1/xSR7OC7ulHV8TnTREj7Q57bQ2UsTeksTqprs601+5XdCeBUVrSdXLEkUKCv04VuUqATIRu9aBEipAy7bYJF+Wm/14AOmfKLe0ux4mqrJ9VOD23ifBZ8pl93buzAqcip5cjLc3NoOxp864cG/YJ/SXWthedGUtFu23D1XvtyDp/9UcWr5HYicCdGmBTkxg1gul3Eq+VhEIN/e7ujfKG0lqdRrXvlvr+41TNNHm1NByry/eOiriA0bjn9tGw6vSkXybpAvX3gsjCLqbYMaDSYiQQ9XAXydLCUWAz3TrPLucFh16ZuL1lXpyjUjTFIMCaJwXEiJIUnNzn4lGVobpJk/jw8TUgRH5AzOpEgqjuOygY2VVeLsEeqK0Moz+boEZMfBRXHngN4/P8X3Jy+hSFTcZGWqjRFW87Xh+aKJrIq3n/M+PZPPE/iyH4KlAMAPRZdN74+ce/F8k87NAM+M8v/E1I8NoyyO0eg5T7pUbw2vAqPfG/vjG4C06XACDWx8jwIkJESX/tKKImgQuZv5F/+kyaAQumUB3CrjpEYvdq5NcVSxVS+8OuhOgH21dF8s0R4zXfZEYjFQdPFlEXZIu6E7dcTD/qAEUIUpQGJhkk8QIoEnaUhbIatrKN0wtw8NRP1OAdbN0aloNtjmrAiLDc/tngrtpT4P2zSUHDvwqv34fzU09r3vb+W1WXQ5yfgH7p9mZejP3GHY3duo4TiX6xN/5Bv/dobZeH7hsPu/LngpBIOAE/467YdaXHmrEohcTxxOPyW1+TkuAtzAuHj3mc9YjEVguut784A55Kr64OAD1OhKfVa19LjgfvcPgeNM4sTj9qF5S7y8Or5fX3PMPM52QTijWEYv2CwdUjH/fo1HlvArhGrF+TM3ri2/Ag8WA9Ulov1h0kqZrjyxT0Sfiknvcx4QDLgPODGm5pRmrHEjP7pj0Kz4i1PHCk5SoNw0zMXEMeSJjVkTGFyKT/Fl/rF75MbcJPSx82f/AWSTrXNCMavCA6DEVA3I5m/PHB4dHDzQ/aZheZ1G9yYfl3zXEGiEYMXPKQFLVAqfa5hwsBGbT57U/FMPtUnuiV+yMbnDKJG2qLTInCK8Qu4j5ygtSWJsYAX1FGbaWzF1JaWvtEcZ3I7bTnq/Fw4gXTkkki6GRuyEo6gEN/o+NLzhkOzSu/A5BCcaedR0NOoodTlnuRE9DcvZy8PqZE+3ryjGFSRusPGCkkkrZYONIL9gCGOpQrvhlcqPbFGQ5HtX5KoU1FBRbVub6gohnavrYJ2+jb+eEAd4+J2R+t7MZtxNJ9rj8Q1ne7STtcGNr4uMehV+A2P6GhnChKzDYax+GTXRe1cCxFl2tq9URiOk/tgZSB8rnWTjHj/xeFK3wkZR145nPD1/B5Bu0VAc3HRY/6fR7RcxUZsdUWH4Ny3Nc79WwiODUMcd8ixhJspnMqko36B4lFsXg6BdM2vwpZwIkqjYKgqIepQoFjBg4majsfG7ERD7eQsKssfnU/dyXm2vhGxsx90o5HC8c7GJ+ukh3pl+unkx619sKcBVUMnnEvs/LWKb77V6hsPFv6GiaPPffljAneXOoX+ZD5ERPSsct934BJgMdUCXLMj03axiZt6YOst/6xh6/39jMRmi2dzJsxQCUuNNf1gckPW4qUi/fzxMn3NzsO9Nt7z/NJTT4C77I+ouWNk+PeIC2VF2tCNd/Rlo5VoIRVCNQRV2BkVIPcyDr3e+9dY4VITdKAEKxZrQc3S3R+2z0VSMWUBZEXf9ZW66nkgNZFcotkjbfs8C5RLx0IHgay1C1ZBVJcRCQ7vHjdwRN3SDHr8Vu5DTnGWpJ29RbLBEdpx0d563P9wckW9LytV4imxtGT/JNtmFd7Z3sHSODSD5ZdS/bgL4+4Ertl0u5eftB1nSx2PmB59oTvw0nIobxMgl3W8b+GFqRjdbX3gzr1XJ3e0Hae3WqneP5+pGlD8svDHjesxHIafs760Pc+wnbEdEOxILZiClI81TjY+NuLa5ZnwGpzK1kKXUBKcGPuWh0N52lZctonIhGkAQ7rFTF6zJu1VyyN0e4m17EAn44iQ5gQs5c6w42EVaz/t686u/Hs8NmUP110dS0ci8+d4Mphhj9l7empMNjiDzdj0ZNBieHOE2FKQKbvtn48ZAoQ7bRyVCyse25wveMmr+MSPwKy2XLIWTq8J/LGtZbjEmjTRwONTobw+MtC5ev/1Xum9cR0GZ7h0ySL2beBjMBs5Ld8RHc9Iv2VsG4U5S7sE+3xhuntY9MTdfco7fnHoHSEeoNZravDw02OlCemoe0dOn5oyeL5yz+umw03DT7THmrAMu9J9XayKdj826BhX+OHrA1LUWk5fNsL/Kw5sLmj9vYFpiqG13c6ZZdE36YLZ3spD6y7gr/7y5CRzbGd71B0hczeGxbqlNnHC5ZER+y+ko6pJGWYEJUZL/Za35WCskZwH3S/KrnXktGD6IJzSvjNwpu08/X/wUTo/abBCChMO6REHu2yxFrocqakdYQpKXV6cCa/5Ctpwyd2sJz7/2jRvDUPqySg8npjNme1GNDaFbfzC92f/J6dpyfmpfLehGDzV1awPHWqPG4rtVZrB2J30WhJ3kTG63nNqy+KFPdl9xFf7+8kOJkxMG8SxpITydlYTdSYci4JoAPTK6KJI9xtutfipZ/jMd6CbClE3IT6lzdXhF/s4T3yjYMPWvIjDl7yMVJ7HAdjYCEfvWWNFXR2N0lCu1Q3NzNUdus8w6QaXXPBWDPv5c0xBylSPznqKGl4L0w2O4lc0CkJlqa3onhke4bx35+EeGOvDtupfLgYR+z+ay3ZZNhFPLPVFnpwuVNb1MBln7EzJ+tdemzzvDLuBUagpOiHUn7+S0OWc00UZwDd35ivHZ1tOMnJSUCubHj9n0p+kZvqKDNLr8Uqev6CRxf4OKZutoP/2pO/rMzTKtVpp5XhZk1Bu2P73yf8Env8Yu1/+eSlfwXXK4yJ9bMlAgp1xDWE/V5sXuE0YrHcpcY5dIx5fibAN9xsQlcyzFgfieCuB+VTX/1wy71jfbNazMdQotpa5WHVmFdfg65B2ff1hM4xhE8m2GDGBk4mVHG+xC2Z3iIdnEGOOGuvl1C7nVWChQjUPkXyDrVtR9Tz5nDX5UUYefA4rJ6rTJLpBLrvPcKrkTG7B4+/oToVhoDQkPxDM3hqUMrBvTQZ+1dqRnRCGBA74F1pTKUGKUjzmzAeQtzKoM+YMF3oeQuebPs7adjoKHrKAAUA/DZkYM6ysTT0TZ9ScxUB4394ZYzbuHrmUbxwB+7Lo5guBRbjCDPd1UVxGCVj6wsuZ6XvaDAZfDldGNUXjq9EaFD9Ohdb1l1ovd17nq8meChvZLyumqSTM/hdQfSzd5KGJkWlcC5Cvub38LRjc5+dNxRxejlPZvI+15Zuo1ieRmmV5FrxSMgcIULErli713qHgTt2pNvjBqJPECiPAcFtC6HzinVfjeYuEGkth2pt6UA+LydbxzdDh6UBSXGzJ4wMaTdViFFjNPsCBusDV/Xz8JYQfKwTZUXMe0/KakS4rtYwmVdz8+TrApEitB15Y1/2Uo4w/vO7Xck5+9IS7y/RDp3ef9wjfwoU8LaByzDiqFR4Nsr8um+W6ejdL9GcdVOJYaB/oR/EfNxMiHWmMC42yjWryNvh30g6D/AA2smDzn8YdWqdlBYt5Ei9MYkKvTWqlJbrG7arjKs9HmOXN1+0aGnBY9h/GdAHrHrCQBDWvgzap1h+JstGEP/aemKsHPneH29Tx4VdOKvVc+cHhO/cApPQ3sOn5bvCv5//I0gqgj0dmTKVfBiKjl0FLhtbYdWMdlpDjR1zRUGmQJUH+DhajdnO/afo8FNw9oxmH7bA3Zd6ZP3Q0fI+3e0YrKZAnU7Z/0r9nqCtiff32YQ3/PW1NsRpN4JIrJcH1lqDXz3+kV0X9d6fgOgaJxyVYh3s3hoA2mPGxwPr+LnySpKzErAZRG4EB1H5/VnirZ8MSUqZIyVKhPePXIOMS2Y+VP8T+nKFtdbcoWjh9OynGF/hHdRampCLtxuW+cDKqCYk4Lm/xVbZnc1C3WjA75cb1QeDe+OaqVVLHilNLhGHrHgkiPtxcqfoYc2KGXQsmdf5FneX75ntt6la7fUJ4QcD3b0NonBny/9d1t5/rBPTTzqLsb0H/v+6j3/xWswF9qt055npTvAvLQpMsJ0+FSeB2YTcGMZTDfqhFf9/AgPVgIKaneGnKahJKB7Tt7JmgiMHPYv5FnlQkYlvf/NKQA0oL5zpE2MdLbTeN9glE7GxPodql8BPbzPFHg/ek61aLUHWQUSlpun+7pJwmB1Eh6415T7MPvpj5I8wYJQb98V6vUOE9mkNUynw3aP8sHUU80F8eAu65/EBOlv9gkliL6vwLEBfkjEk9pdM3HpZyrHUnxZ8tw8Fl/n+8sY/BGXiPrs6VgPlT3Nic734n7dAg3wq8udAwslPWRhBdosdRRmDP9k5ypgm40uaoEgxqTOzpVetftAXyfdWI9cl7CR3npZ20OGCh0+Lx4nDu5aTxSf5M8hTD2DribpOtpGOAHaNDYiJQgZaJx2MBA+187Wqq79Daa4aOlDkVBLi7z/y5fKRRQnfnxAS+rX8QVfnr5mC2n1xcwqnmulzZng0YNz58p+XvBb0nePkAgGTQ9n/PWLvyW4dMvLCX6PrMABx5BKJ6CMLhCIL70cM0JBjCncBrAGBRubBEW3C7aDWf6sG2+vEW0YNOtZIytATJgwMBbFPuni7xNmN45yWXrJJ/cPTpi8LQpTjFrJIVJIT44TiGhPr9AI1oG9eHSqLh1K8dkA1ZLtbbLdwL8KirIpH133Ef0YdHmSC5ayeP1QhuorArWBoj52eS0MhewHkrqg79rk4CJ2kpyR2jWspqNOIb+0tffAzcOVq3g84Vg/SEAbohmQ6rrBDLbTMdGcaT6RIbPP32pHDu1IpJrouh6JMeWD/vGrKpHDvwHU1gpMGea29Lj0zyQJXFc7Z/JlzItQETyLbv4c6foS0s08TtyLhJ2b3l85qG4LQ6lmTZojCmhtayEgQFxTFomnMuYBF9I2VNWQVyZHmEdtFJWBoBafjgQLLcfOLhinkphJ8o04mLXaUxGhyD3fVxTqmAlZKWv2IeMYIXQaWl3Nf/2MSPq+iHfKufscBemWpW8EqWwHFnMcUpC6oCeEnAnSxpsZqTiaDgXSMeZhCgRQTW7e8WTAg5K2BkJPwD9+bYAicgDMDZRuFiTNt+XbzRyykoG9pzeO8GD4ldHcf2QyC/yZfnajwdnn3/vi09AsPGETv4LAWBFJxMJO20n9f9vhKyhFlTdrTq/pSxXp+9m3bPc4j8WkNsEqi6NhfQegYodNr6PQOXnLOAY/lYAKg6r1Iuhyvdt4Cief1jr8ktKBGVGsVM0FC5tJUi6SheaHlVU+7iTCeZP/UtXOQGSEWzSN2lcD5dRkI94jGWILYKor3Bi/DBfrMOGc9MpSF0eXAd8uxmEKcxzcDn+duZWLVMhw42Kak85Gf7+d7TRkQjAa+il4ENLLnmUNBiN8F3z+b5RRp+KVOWKGZ+C9SSHxzmXuMuxy73D2XjLDvjHUlQwUtRfueu3Ul4fB8epnYjLF4dwDAZC46MJjQbZFwwVEClvOLhxVWLxw5E5/UlOhDOFZQ0IJ+4Q1fvgmdFK3FgePyhGsamE+uxgJUP93iX8Dg5zvn48oi13APtsLruvYsEq/bUqsyvU7gqRNVWQ+R0Tx78MJa/q5wI/Ar9tFLl6GMrKgO4BbnR0lKVnJM9Tp1ldlJvwMDz6gAi2ZsMiPr1zMc1rSkDG9yuaSo79kApJ5Nc3fsvClGdbrTZnVrvnhGeTM/5RXONBsQHcBEnS/pglqhZTFGu4kTFCxVCk+klTx6YgH3wvplftQw1Mcw2Z7PqJsHUoPKmw4f4Q2vah1CRrYXBnb7qZkxCNDGpVWbcN318wG9Q0QnU7We9Q3+7sUDbEdZSze6fsS3I1x9VwrEA9fL995Ub78gPXDfXuSE6f5ZP6sULvLiKMq1iVUXu6qgTD0yH0TKc4e9nNj25/B7esbkbO+DvrGvgwLHsASdu2xnYUpjyoLzILGxuDa76gfQpe3xK/kLnrjoXCnhibkFIuCEVD6J7n87s72pozm2/yFDR6COFFNK+m3TAFQZzFAZIlq7kaPz08ahuWzvw6q6qA/ZskAQJcUP2QHGailRAL6xTScOjXNeS/C4Uzju3CnVUn2yBvHNuZhrJMFCLmBMdZZPZv2ho2TmswGOVU5prb26MqfZ018Yn6ES7TGKrLcpv6KzbvGRJPPBv96vAab1zftmz8kfxx3qHJ+zxjvJyTTFDs9aSUdu3NefPzqdZqSszjDyhnQOOLTa0gKWUOx0pZV1RE8ZDvejCAtVQ+Jul4KRdsch8iQ8snraUXc47lW7OjC6jRkbzELVsXsNfsp6OfFdmxmaQK/x/Sz9pPomh3pQaZzsn6v4lqV5ZsbFZdT3zblaj4YeZQZHTwzfW2gRg+jR4FFqNtPANpWwpqM70wNqaFkWVE8FMmVVxNVvDKRkzHdRvJRm6s1Nnojxs1Dyjp7cfKdLaWvvWG1+Uy910IX+6NCAT9e+enOEJMxPH/+xzO2PeudDwp46yIsQOS0gUteyUkWCjaMWKQpn38V/GxyclcSmtyo8ERXd9ZnCPa/2+h1f47boo5K3FxAN6SVv1sC27Z4y5jAx+nQokR8CTwcap3EHSWZkl/24fGXnpn/+XwPrDlTvFOcPJ0bUEr4pOOCTkKOON17N2qmcN/6+VOI5zNx0t8Pvht8ke9nLeGOkKXeau5BoV2NoeS05+XKh3+98Z+fc3P6tfnI5ZvZbiAaGN/WPf1O+GF3O8UJ2hlppOloFPQRZ2qGg/X1XCXQnVi7Tv3yh6p7apJ6BUD9F/zFnO+yCPddv2hMTK8ipFIONvuct826ZZdBh+6H+vCi16UmU+CSX2VM4Ng00oLyDxzvZA6sfjfPHwbkI9StUaZS9WFq0UmX2uPviQzhhi7n4KeLE6iOpf9fYully8WP0uvotkamqfTAyoXW+PiyYKGODrYSit0aRBe8sY6YrKK22f0xt2U1iDV3rB0MHdFIByZ9X49uFka+OT79lyNAiqcsBjQBnqmXaOTTDUPy4NKYrydu2pdoTeFPXggKiPeFPGQLY2LFNIgDtpjf2xtIDsi3j/XhqOHaCikPjBo35HrTzLAlje4+MfVS/A7ufCAjjQ2fvIrZXNNfJAfWW2W3sbBatdWWlrxiUP7PDYoOwvZlXJubeV5IOdYVNEmi1PJ3DClxQhcQtcUPf8KsaFg9a2myiVZPvtM1hW1xxQgyb9dZSVb3TvG5QEZh7CHFtvgRGded4RZH7xVt98vOPLYbPoMXO1VX8fcbMkY0izwb1aQK7NnxQLTdQFGPXPF6s6UM3EH+bLwZEM82HeNlbz4PqbeV/ZDK+HuQxOG02IxLgqRsoKlQRE0EY5yqmsfF4cmeD/TdG6y5YzxRvZ+Zd/2MxN4B/U0PpHsZIz58kGe7gEXNDYcw1Jn9dXy08CVrhogIyMQ8WItBcIyBYEpHotEyekZJnPG/c5FCImXw5L64ZbEWC8yFT3z6pOIdEDep0ESIWSPKSHcZwQ5TlcJEYtRGOViOrBQlcOWJPWFi0RC/vUb5Z6cE5CVQNroyAaYVMEjhD1bqrHGSybTrj22kZTqkunoHBKyTc7U7sux9njSNTioa/kpSFmhNQNZ9x4cEiFcgbm377C8/aXnpeVPoXHk2NPqoT5F5u1zS1zSiCXY1ejMoMBesbeV2rWklFpgz2cZrzvIeI7YvXVYFD5fPEvP4SqMfF9k685OBGYh1dKLD6uQXY8fO5tOvdmKOrr7lenkfRzl6Sy/kUOV7PbtB9tDT2q1JIhrcXW20ENgONvwwmhFrioyntpSWaXOFfoxhDP1D2cT8K4x2oPZ0mVm9bJ08pbBM5vKAUcPk5oHPYPcaHekscf3sq9BJ+z+c1i2tIuZPFcH0/nwLT+Hc2mSTuCEaiBDjuPWjVfyXWihPcK8TV54/0nOmD+L3Q36L6Lx47ouJXYikpIMqueP1fVpap5vH10N2HzP8ftl9pkUEEDoSHDy0GYD83xVcEIWC7N3o/QEq6cSnJ4uF/xhrIJOkPbi46gQtZoag3h1lStWBCfXKDejiTv2pI6Rw7w2YhsAaEQCz1kOONTEpzJCnckqKkIzuzWyYp3FeAOgKvg2+QMNXwhJRKLKvUzDpmtLIzsN3F2xsrWzyzZvuYLaWCJOGYC36n+vxC5roNo/+3Z1DQuEUkay5/UV1HYU9iV2gngfruKVUlxyJdXI371Cfw2N05bvdpPQ9ZYW5PqJZnI4acfmA/lMotpNf0u4/nLsxWR3hGY7HlUq8MDEf7PZ+11rpHlvN7asOf71M58IXozF+8IGbBkqa+szdyDRo6Q2/ldOdCskefCrx7soIjrcys9HCMgzUqCrjX2V81TyyQPXy0kvLuco+V8J21l/b0pL0dD4FBlRnfsJCvhf6lB5zI6sRk/qo8MY3GT2v8964zCY9O8dmAFs7e/1J2B1NMmc4OTsDIqEJUHEf+bD6fBCLhohZE+B6GX6tRbONwXZ41X3i3lp7u2ns2Wj4v7v9ag9XEVa+TaQtmq+dg7VhTtFJ+7e+O0Geub71zuvxS/7/QQF2wQjXKp+6vSETv4aNtbz/83nKcdAdp8ZC5Kcxk3Cu0eGWjHezXN/LQnmTvgC8PlJ0Tq+hlJSnL7x5pXJ7AAHE1KRnGLCHCL4pRVWqLNK5M+SNj52uRUuQN6xmtY/7Kh+vcrFomfrdB4eXARsq/ru2OHf+GwyYYsdY+mJlWviAotSfc62XcDYmZGUy3LSmWDZlQnw+palXbeKHpVTebhHaQ5pxlO46xz84+d2PdELCDe+WR5KABsvxD0ANHGbKogIdag3RsWLgcfE4G5R7AE9LsydAm74zNGKDXur2rtN7rH/HiGOy0oaFVP7Ujp9JhxPxFCsmMLrUEIxhEKJGLXoLxQIiBpae4H1kmrwfMiTJNgvLJLrEqrQpFMfusppfo51+lzasBu/mBd1P6APVQ+ycUPV0lETn6K8jf72GhPNfS4XnzaxtvkpqaeYQ6oTY4rL+NcU7Z/teYU6ygpjBXecqkYnwd8I4pQ+QJZQb1Lu2VbMOY6NXEuMhaP0jqK/0KKGQ/XG4g9C1tVWjpR/ELPuxRnG6g9S1tub6dX6AtLtxZoFcnQyEtQBDgPxCDTjiKBto7YVUJESERiLkvlRM5FZVszN5PY0fT72RHswj2J4DHTyD5Jb2cQ1fx0bM1SFHxbVyJtmsQvr+jt+BuYT4P3AelLbI71CbDBKTqCqrXbjW937AqllhZblc4fWD1Ycnp87JS2+8J9fI1f698NVilfKkkh2eTHru+YHBbW6RzPOheMY7C8pdCZ+lJk78ErIbfc7BTdyYVy6vAB9aPnrzLsUCJWtnrjOw0cnLvfBXgFkJrIYxzB8Y9wKXRgY0g4/+eChfWOGpuSd1fmPHXkyP/UaeXphTtyig+/KXR3OfdddK6Y2FuDaXz9YW3xgtny3zDViSFDqgkacQZngEgURJ/Yvh1arQF+nIxFxr7mOQGzu9rnEB22XDh5bI5fHgc2/Aj5j3/ijA0z16W3buAQS6qqv8i2HfN8dCBvWfE/8ivDd4qwLfpvEKxMvHCbFr1YQ9DVT6EArPNTG7WyiFlFsjcMW9EpNuNlk1DlsgqNJgDkvvH9bXPrnojs2zimwbcP3ETnVrD6JirAnafY4t4dAgFtxBpuyW1XSVwb46D4cQ8I65K3NBt14RD9pqWtkdEwRaeEb3x7xwQtLn1Dirdgsa39WwwhGBWv9SH/Rhdc8SH+SPNKt0wwLX3ogDJu300dKlTn3/PXy26SaS4kQhrIII4p0pJMOU5TK1N6BY9/hOnsJpcipXdkbxu3vSBcIsOzbfgP84IJKInGU27D6GcOHVm72YC6kgHJMVhWo7OaS4Kc8kxwaYn9/+ZA14frnMq35UU4helYcP1/59xYZTuUpUTJGpwCVSUsB6RKJUrlXrJQphTMq3EbzM7d0M99RwQoEg0I0xEyRMNexmwWh6K7hmpLEzTHBRChAsfrUfZQhJ+dZYDUiSLVV/6GGIm+7OJbpQm5dqPB7Vy5XAXFAdn2NnNtI+iPv/+CI2ToeSNUdhYNoIn4kNX8JdF6Y5sj7a858oJUGtCIqOFtbaXyl3vGf9rLQGvO9PzzR01p2ls8xiqwpWwZuG8zUiELqks845uc+wFnXOaXnVF4u2MYFBRCa6JRvRyedenDDK7EPYs76k8gJ79b3fR1Hxx8Z57vA8drMgvn0CMUviHsJTJ/Ke1Z8aBUTBkDWcIrXBhy60oCK3vjPBJYiwgZBfjKv34r6OCGLwN6byntfUZogr6ydb6yWhzzYd0bH+inwPf5RyZpa2y7LBRg77vmIjdt4wn+pw4tf8EvnHbp2LrR1/3BJv6jy9UM+PyLA+XNPD+fnsrr+w8pjldtb40TWV8NrLMwP315MfUgwtC/B0I3yMbtf9z1VIbdYrnJNnsKAgHXxadwDu6LTYf6H1hdfHYr+PgXVPvyD9clxTn219OSWcIxnm3rxPlcWkEeB2zkzSIZxOImStvz7DW2TcKi/P6MrKTrOPtlKJJqAkyPtgRcSsX0qaXpyT88cSYF/XjZWKraglqzP080ehi9EsWn0HItJ9hVTQKfJqq6lIXHXJwlA85sD4DP1mqaw7Vz3B2QecnZv1zsAXa7sCG74cZuLzo4QH6dzlqbsJkGWVWn8xiMU4zrqUO2ZsBoSsHkQ5l3wC5rAw8jQKCsmWhRFtQzaABO0UJ+LIuKC9nV5/9BWX5hCj0CPgelmbvChCUq8zIsLAn3IZ2JKWn/QwxD+KvTpRg23yKsRugsVvRr7CtXT8rg6mN1kAB+C7FUrMPILeSt7G4t1dbOBnE4FYZkMeBWQnmEX05zJisrkrHdPfJv8ZIFFY//qD7Eeu+O7U8fSXh0bM1hLmoz95cuUsMb8m1B06xLUXk4HARZHF01Lgdkbl0+6TkWBscco7C1k0ihRezVSdfDqaQ7RycE7Ugies8GTj+74d9Smsq75JI+exZ6R8WFTJ8l8u2dFY6m+1BT22Co96aUup40VLVNa1C65fFd9KDNfO4bKuSwGsyeF8lCjxkFhde7aJxcEpzKn5L7eOLAIQ+LbI7vHPwpycaZhXYrdFybNOLijOvbYCKhIFi186dr73EA2HrD+fyfctbJ5PwB2P+KuXijMLY1jV0+apExAiXQCJjZykPDQLSbZqfbvTbnKUwdV4uKgaVzwU/RnVf7RTOEtZOJPcuRek71tSdjKE1H44veOT8vu/5b+wJPOeTLY0ZVwurh4cYQp8OXMO6YHd5Bfp9zaAaUnpdazbVd9Q7ikaJ+kpk0Hw1AHrInTdATOxEB2khPDw1CMAxrSDmaXwSrkPggYVSrcLwe+swEH8w7nUdngEElhZmvlXU1c6QbS/mMDgtE83gW5r4qtkqjsmRUYjOIauulRawv0wNj1JAEtMA5GRrSFnewLKLe5Eyl+PIpJb66AJl+5SG6VQmKE3eUWqPCKF0hWtf6ez0OJiWu/ON3Nwu3f5Xeg1YQMUvi/e5v9D7ago6vdCkVxDeQS2VAlZh5h/ypgVXLty4LDNyL6a5uPPC7/7QXgVvM6Zn4LWr9SmqYOq4Mt4K5CATTMSJ1S4PME8QgFthdbVknpqvn26QI4tJB5Gn9y/ri95yxvT3o09qmfhXpRqY+U24CtVgupaw9KSdVTEqmS9Hg8vaPP2NnSM9qiCs9OQ8BE1bKa21YAALEKA0x0eCtag5mYI8ETxGdF9SqI20mS5ElDy8TtiW06OpVvIi0dNomdyttJ67oc7jLxwkUO4dhZ7jS9382uPZRNPmsEH3oKxzMCpmzQGbnjRBCve+/bYKT7zflWy/650B9lOfk9gkddBbPGSlTA/hQtgUvNgwC94jS/I65VSN9N8dJ9PYZE64ILSwyPY5HAOxZM60mt1r42VySvO4cZdFdxiUAV1LeeGxa9EUXyfa/a379gpv1QAlK4n19THd6AAdJF2LaPBGRVmANWIawMZRmFqIitS59oWh7WhReu4jl5RbmOb9Xdh/g8nfs1NDJuhYrPWRtS8dKSeD3Roiqub3o6fgkLoZUTjh3+4A61EQ3fJfPxcQ/9VwF8MfG4XeC6hXN5yD/FOFkKkCsj2sIOpsKbs5v7HcTmDL83uJufquH5MmrabWteqX6RzSIFyeExziVQQQj6iOKfnU4k4bZM9Gss34G40X9nZfg3pc+bbvsa/Er2t6eFM4nbO8cRtJ9nDBbVnknYfCKiP+/gY8vLKyaApeeY+htOehgqwzBEMASvDv5lOLpEfvQawhb8uiX1u5D9m36uQcrPrVJbHhSEZ4A9k9T2bU6WGI9AA/DALRDU8+RgVv/9ikawFPHv0Ubo8wH/u62atNhdbk+NV9CLc6pMsNrjgZwtaKGikGd0SQvVSA0xgYkE1SO6CbeARSFQYtUhl0sDSP5S7nO6l4dP61fW9j5oac35dN+TEJ9ssX8w7Affvwq2Gz+vbJQC+hlPsU2yUzx2KtjPAp4K1J+/6yOjguDOuzyj09KB/FimaWWnUEeLfssFDpS30qTA404j+U1eyFV9Lnu4DIwZQtKRoneIQf+QMN5ExLeGv5ez1CnmbXtLKgnRoOqT4z3POf5ZTuHZ9fNS3KYpJt931nxhfjDu9dfQjJgPe8akm+EHH9sCpr4zXINJJATJjABMzeRhYAVes801gymuJEpZYaXcwAxHkEzctO0WJCpzO3Xw2WTTvadvzZf5zC06FLF9EYMZ/94rO4/xZBWcX/h13vf0eK9fjSwfSgTZiE7f75SIHEUDK9BFKCKy5y+k6/K58erQrFcWC65sgTP+Ifc8eDD+rC95wAn9DhmkljOrRnsWPXF0HWl02rmdd82dmmsEDyXuE3cHH6WAwgp9mxp+Tob1nnWhiGPJ5l/vgxNWeB/39in/f5ne8gJHB9Qnzoobf7xuLXPN99vkpZ2geRQOg83cTSdbLIZnZm6G/Ob107kfg0dPv2QqW5puxSxegJpvtlG2sUfu+HKT9QxYoReWPUxGc5Hcc3P9PNBZx5obaO1pukK3Hl2v6U0f9XoOiXGCEYlLjOUs08SokDsdRNd3nzcefSMfe4CtfJXiZw/4/8uPhUAjn0EEhyPhPR0qz02J56iF2x8PBm6AapLHkiOq6S/kj9SXifDaY7ZxJund4m7R06HuOjRDBBDnJ2+7CSQnncF112MNpz5Zq0zOejwsgX7M5BZi7dGA+4tuQnQ6nuDxdhsk3rmYfso/qdkpJmnYtrrTI/h3HNrhVeePbh7lOdP/j8ignCa2aexXuuzZYcVb9+ldjuxwJeMhY1OgSSewuxPAWX+kl7sTeUbvcq9GcgOT8BcwuUKEtPZOuaD7zrMLrQvhTv5j14vekuSv/1o7PM7vqXXJGXxXnKeUvJ/qrftgNBeC5IWN9sdwiLYfxggawOBU0AFqPWgwKrBWVNZmlrP9/6Aj5FKxcZa3XWMQxacTZQn1MkbjC5mX6bJC+VoRZEkMYh6O58jBlkrQFsweLmyXrqEO6VHOzJE8gmeUmU8S/tSbZlSU2u9JT474V5YXc6F/2IOqOWC2MPjlhLWtGfpAey4+AeC93rnp/4mz5Uv48IluK0+DuDTH5kgTEt7f8ZvVoEZ8UvpCtm2ICEKQhvluNvaC6yMOagzMneIS/FI8iT2JiEviEDd+p4c6+o8uEx91RhTC6IvwNIGNfa1QRwVVNXM2L2Gr03XjOQxPl+Al+1x8JsEKu2iMMaH6hfn43pnCYXpUXTj6myibWh187Z3/gnF2kf9NrPibtRLevRDpUf/t25cHeeE1a2Hvh0z77ori2cqAmzj+FCuB/v/aqET1e29Tr3594nH2SKrSMm7amUxuEbvCqZyFE8PaC54tjBiXP7kLWxFtY2hG334NuvCd4kxKXeApv/i6YKiExH/0LZj0ZaBiHAHpKvBFGMf7lHkQGX873b97rzMQOjP6DCr70yimaWT5pnnpeueYQTN3gCLUxNCm8CsB9PLpOc+bBVu2+RkhQ3ckTggY+Kj1CJZo1OotzT2LhN6AixS/1d9Co1GW+ToUt+KYh5rSuZXrU82BYrsYbVghY5RVNr75J0so3lzJMJdrB6LSNii3Seh4uXG7sIm9Ia1B5a+qBBxCC7w/cGpTMJdbN19r1vJfnO9vuTNok3V8K2jZ/AHMa/n9Rm9NWPDlf03+0bPHGXyApKPOu0g2nmuUYJQmGEMxfxzW0l/k0U9JKvJPBWUdiAdqn7yNtGXYKtWjGHwpsA0uY29dAWYKXdLk4u7qYtYpPdYvbVVEEV3WxM7+EUsm6ztY5apWZ/mr0wLkx/vgj4jRXrjzz+Fk0saE/B9g2pM1J4CtK2OWd0JKQbEviRaiBqZfT7oMHz+UCSGRnzhkVwwTk92DEPM+L3KQG7OZ/ymL+DQvi9x43vti0A83wA1gMdiqQ19jkMv2U4/lUynzO8vXB4+beFyqvMTK3/LVsb5M70Nf4H7bfsLjcqAd9VOB+CQxoVqHKrRGp2LY81dAv2M/3hbeJUFeS56IBBBLuff2e0p3itMpSYuykHdmtxk5Umbsv/B5rYi3YrwToq6UW2q/fhhpSK1agmtAFVI+XTvXUWSBf6lW2AxzGskyta7teZP5A5xecA1bitz8L/st6V2RVznoCWztKE/DP9Xx51GMNUA2cGKoZtLqG7h4Gu32Y353cW5TENpz3x71X42/rOaNDDAcaWJzSsSQE9HxYfY0/qqgeRYTLrlEhKsrvRMP1xYGbQtzYk24FnjntaTmMVVMALzzlLBcIYT89xZ/ZoU7Hyn3DbxVESXNYi0LQ84FfiU0qGc96kBDWIAlp4NfDEDvoQM/dh7dZBEOSRh41mvcG6wytNgzidHpVNZl5k06oz9ep31jvWikCsCdRpme3LpwJMM2Fgi0/FH/DUc7flGW7c1YRVx9r56kvEud7DTh1abgeJTGVnGZk3ngFKX3hghZh9y8TVXv2vUIiDCF96s9cpToCzbmKWPLMXtoB2bklHJZ/VnziK0Tj9py+djqN6YS4T1Z8vw2CZiBeKdoTTBA7FbliNb2DYAnR/FVDdWJRODJvrexJiz3BJ2glfCT0NRTgVUMF/MCYO5AjgA8D0xzAuOYSG4cHckgD1G+huFFmh/sFTlWulVJWmzM+aDYOWvDjJfAk1lDLM8/yqyvEXirghycaCcPCNehPhVqZMFHoLc7TPeHp2zKXaqHuxBbfgDOejSoDfIa1UfSCdK6f4dkkXia+BQqomyzeeFmMfVVRZS76IQihY7lWMpR2KRIIGVoRUVAWFVXv8NQdBitAkbnqPZhCKnmEA/wUyZwDOMjjnL1O7vodDs61v6kZXxWMiNPfyh43jE6tIUrMfGxo0Id1Q9SydOKALaXyHmL/RmnhwYIjI2vL8YRPLTm+G5jN/bU5l0bIKK0nT7gcY2WmLsVmeWpZJ3XAkztf85vmm76+Fm3ndaGkFJMVDxk0MNadydqHUvJBoCe5z/EuYlU6oMi5MxgWNY8xeSwAS8oxs4spVrynurPoz8Iv7oGSFciOW1j3p3e6kJ/WE9p2X+x8U2NQqVFxF7WdKZCWxkX3qWTHNg04aaBdNwhFh7HNVddSJI7U2fj5xdwFHjkW9UM+r3vNS/q+Kjmug1go6u8ETzIggMEwzuE2t1FXGzDj8DMpRHWRy/WrzLRv5RC6u78+d1qckV0IMf/t/c7JUOhzRZpqe4D3YMju29mkzVUYaNob2PQex4xVSCChKUeepRmj0U2EAgmm/NYq//CvQGALZlMn/Y4KdNtz5Qb9N9HYdjPB/TraM6dn8AVnBcFuBalNrAp0snVWiIvR4r7c+i1F4B+8uo7hc8q+4NP9Dx9hfr479ZFC4osQ+oNGOhn/DSbBTsk/OOYUHRegRxwdNlpTx+n9qQqnHWnReF22CwPQc0hjlymkHo5fWKqOnGDJrTJkHz3m1JjBr6vUDBD2Gk+C1cJBVfi/Blbozhbhy126s8hlKfK0Xx15pYLRGAEoJuJNpJS1ZU3aEJXkSHuO3ls2Az4D9+BIC96GG4XhZec3wKdW9rtsQ+voRalqh2tTjOmddqsD0PNsEAesnvRE6wYL/xEhrm/q2NwoYUvkkSpktpgxvNWrOvlrTYrnE4qLgyQC7Y8+8AK7gS7ugGy3GfeXwtDLzhvhapMrKz5XO63m9vtF07BJf8GRVa6mYphoVPbJyyhF2Kshs+PHwpc4AIMbzFBwph5t0Hs2kVpInWrH/ua+bbb4ux+h/+EPBmQF//yOPC/IEVt3ydAnD+qcu/2BefNmisuaWfWAQxgiQxkWFX27L7jK0th+ECXDLVKfCIkes/hYS2f+soSM+TmMOceorlfdMOqbLOeiM50w3hJNwnkYIAS/THbZPD9Hs7YSZ98IxMvn4XydeahHtkOyXuZgOaglPM9w0dQ4prXmUdSpnSVCmdYsqRb6C5dN2+Aq3DyycAsCdovYJ36Dp2r1IJwbC+MQWl/1o/Yw6QGP+K2RYGfNICg/fXFNV62QLy0+NTck/vQjTetUUCC679HOjNbDfDC5pPzLKtoxN+EqdaELYs/gvqIQDVcVaGl7aViCZdaFkfwgfhvaI8JtwVoac+M9CUQFtZkTbj0AzdK0+XDks+DrvWnGbpsT/q7r4bki3Q9hsU4CBOLHV+x90PiACbm/P0MhtJOxbU+2y3aI7ltRmHu5hutQANfI7smeFaO2c1b+cbGAOgFL7+9triPzRo5Hjk9sUbje8LLvqrixOf9oV8L9cdUhyqdnOAMScwWaQYjGNzSE7J/GFi/qraEWB0Z4AFU15Fe+JNNgqmEfKD/rOf83kV+9kBZwojU6/pNs4pTz1o3AfGntBqH4ffjA/ePDa5Z4ahjwbzQ/LuEdns4q8gYJlAL8t1Uddag3zYUFsk5kuIeqFvj9+bE2ztgI1dgBVog+e8/4oPF7DVqe47RPvtcH8tw+RhjuOMJY1C37lq8e4XFfF7iSESrtddfwI0cE7C5epkmLLIBo6yjiJbPNVmGHuOIa59WAzC3xo+F1RUG0+XlOiX4YrCmVpRxjdGek2Dr+BpSQC0nvb/VV13F/EMdJfyNp3xWW4dB+6zOsG1I7OhM0lL5gi4VSEe11aj5hxzqN5rvf7qSxRx/vsxIetTBe5zRq5k1a5gAp7si5mnO0/gwaawzIv7PSLOQ6Jjab9lbKw32fixie6wBETiYTimWBk31fPn/e7YlUxrEtuBTVulHCdKCxNizSaZF0q3wZ4sJ/ABOl1l3ct5FVLTG6+g1kBS6DX1YML4iYKZ/y0pBkiEj15f9gfHKFjXTSqbJVmRFuUjs0dajGIHFx0Z9IBgqbnm6aPo9Gi//xhj57ELAYU0dnSRcYfLfd2YC61LoTWJ95NcoVdMIhX7kBOuuVi/4PfDniBGMnZFq7U+r+EdfOex7A2C3rqS74LNztf6VF77i6sYvBUcEWTMl/BPdpaCJUwLDBwhU0mn4CWwUqUdy9XjgCvMYkuXhX6ZasYaSzMJLQhVN9dWe5GziQD92hTFVGOECCjEdEn1yaFmPx7WiyX+4tGaw9ElCNSnyOFBjQVgv4q5paFgWYXd/er43hbvgBQcpnLXm/ZnnxPZitvsamBRVmJmSHZ30EbHZUZsaym1IUozKltYeJQgLAvM95DDYI5Fl+TWGxdjocumTqvquoP2//TaYjfegIUO35U9AshGDzpG87fXDP9INXq5Y3Tz7V8FSTOG3QlKyN5rdJP6H3wLgeKLKk2HrSoU1pcXNdE+5bGxhEsUnNoTeVCbuJkiSIi+mRGJBToG5U9ZkQ8tbTv1VyYoZO4bsWsyw63RRKoC6lX4QVlZoa961t/623IVXeSMthvzqKv+LPzsVYSUQHPWxaqh5mTfYxRCpxRGfMczs30noNjgWYKvZWwXLJHwuMna5UagvjI4iW58Hhbv8mN3WT0PLZcACeXdgfBq9WWyI/k2Y7m00FQYljabVAc9YIHEbiJix//eC+ZOLoC0oKbtydFaUy/25sae+WQ/CP/7LaMmsBx5o+cx/fGpDUeOG3i357dTR1xqmB9TurV1P0jsE6x6W6n0P3hM9NslE0SRtVJslMpwJQcHsQZxCEAJENYaKgeJ6S8kU0LHz/Ncjk7kJvzUFLUSaTuFXC4HgIuIUBrYikhY84GmUMDzMjsNP2Vo2CZqofYi9e8Z3RIvs3mNgd1NUv+SNSbWWvobKep1kD53g2N3qo36ZWeziOi0k5f1xxc/qI1wv9LaXZIWiDoLSCqVhsFGicZfq0lGpNh3I5VRUtzKIEiMkG0Dxla48lGo3c+fnK29yUzsuBksGxwdqz+ogXnRs0ZfRTPRzG2wIlLrtafOXqtDTC7pr6LOUgl8r/fmdBNZcKMwIvNCL+cNcOES8F6MwsntRvccRPqa3hskKJblD7XIsT/drf6idMENdfx+MFd7Ha72J199c81o1ACAxvelF7tiqV61Db8RCkK9u7r5xH5fYBTZiPNfHMb9tK+h1iaTPaYbNlYHBNHkhdR5wH/tQNYz22+zafy71LtT8WM3Vl+9Hmz2IHFkjT9jk2ZhyUR0V1qW24H9CiW0kWUxYBuMp9ZtROR+VD8utHU3kRoliVE7oT4V7nqQDn1G0qXfVaTebadzhX32N79xJz/m1Mso+8MkJTKQwlcWsrGS7rq8CqBMhFppixZjwvbrAP7/UHSQ5XFdxvWUy22XrAyjju9xSokyJeI/dn9TncZFdESoB2UiEQapicxaUokR1QXoxRnV0tCIN67KTeCxj/C3uvzylhaIm8+vycAt5gOuaS+g6FyNCXFKB7Grn9xeVjqBb6NguuLRzdUuxnlsbTpaIjNj3ZsHLxPSp66+cuM4tnf3mOoluBMIs17XwCeOQr/TDmr3zuZnUecDjx7+C2dpRZtg3g2Xv6DMBQkN7nWLGc5Q66Dw+NMpasYlaXXc5fiOWJ/ghzYylYtHtLohWp1q4WtNxfbZz/H8KdIsaa8vZh5BJMtk7kD55gc2nJq8VrF7m8grec2mcvFejfKyH/m4/HpW9uOLd/fXzsK2Uoh/3ZuzCZEvWX1hFpN6vZayiFCSDf54wIRBUHznlM64lC8Zdd+4m/6+YPlxfhX00UpQuJE66wcTp9dTaRuea86eBY+EJj6d0D1/e1cj69srix1+KK9PKJi6LDoYf9nzWtn5GzLSM8UvenHWMPSNbrlq6ZFR8YnnjhHRNfE0sqI8yXDo9PZDgla0iY5ib14RvUdIDvPSThEIsi6q/Uf0VudgQJbTrqNoEXnIbOBvTC1EomcEcg5ilGTX9406Nfoz1Ho99jX4RsGgJN8uaLSWiQ2xmAOWvB8rilcw2IfhgEP8bb/Skf6Bdt5X5o3b7A3j5C9TBQZrcBe00jNAGtk6RP6uy5hHYWvNp1Fn75F4wLBMpgMNgLROWjTovik2qhnil4FccFd3diHsT4PM2T9z4MGVDDDGfBn6vXkBeQyy2fnu5BBqNYQzbMniX4QlHsOhtMUmWBio9BbaYVbYSpZy0KQnNDb2TCN1qYiTe2UL+AFWXzxNW/PLQGFxhdPUTqPfzi1uqx/ahCpxlUW3FuYXom7RLu39L6kVHbi8NJ484GILA5mBxzPPDsvzpg7sDu32FVeOyC4J8DS2lXHeUvCnPUgry8nNk8up8kF8YjLtOrInTECGGdssa9RoNIMETbRzrNz+Vslw6/Oz/N0Qbwmq3Of+ecCR2FcN4Cr67qDIv38dLA9Ya8rDp1j/nN6imuU5ytUjv2yr2rpHSBqOf7rOfZFcCK6WdsFM2hJTqsGJXbbvlxOq70QwPW/vlKTnq9JXJdHs97fwssVIgIbGOWnmL2mjbFeQbYtFOZDSwm1Aq1n/c27Hhx/qHpABsQjkxH9Cz99WlxO+FPOwlxV1SvJ+5W69lNFDhCrsRegeef41O2NBQtl1OGb8lg3uE+50HU2EI28jR+mUAW4is0mSjxZQgUH+1b70XZUCv7+HGUHclSgnNknRYcgQR80vlsk8gE6SMCZHbNLKD5kp98BvCH4x5OIJQwHXpHQKlm11sgTa3oJKFgVcykpYJKSO7OU+auYb2v/uhkfBWq/OfIKmUFc41GVgGGCIWAwruY7gBAW1A0sIHkD9OQo7ZkQCaN5UcTe2yzkFZzuBfdphEpYe1H3wvvOvb0562rNe/ilxV/EEHFvsCt1i3zUu0vGsI1D9y/RNyb+0Pfoc0vxoonuXlG5jSNFQhmXEa9gaxjD3JBalNMUxiSZnzqjXwQQHxuYk7MQIlxKcSFf2KtsvaRbMkAS4TdgjSWF+ICcfIQg35D+2fSNxkKV3+h2zzk4ZK54ux/IEXwAE3D4OLEXwJ7AArQMJ+aAWcKtVJy2RqaZVMG1GlSoWKzAiwQCWOvnq1CZNk+O8WNSn14qbpB7Y3AdmQIj3HU973Uc2oV2M1mhyfMkudJ8LoEwwPDhz8vAjL/wAeftBylS0rUqryN1yTlON69MSLzK8F9vaH4lf9tmJq/K+X+TGP1RkORJ0JKmX9Km9sonuVPL8rl6jRGEiyB1rIQb9nrheOUJyJA9FiRIvMrLlgdpvkeAveqn7vkH2YFeI18y5TOr9bRN+vBM+4LWEaGdQJJoZnkZ4McNLdwB6CSeuSZqQ22BVyxa4dYyaULJNlbUkhcOhSz+gTx5xv4Ku/ruM8h00XfhwuP98CTx9lEzPtDUkH2cxyyToiCJkCe9Ia15h3vZsXTd907DVT/7/NtU54oulhlzlsXPnQLN0pC/CSiUYFxpziL5k0MBhOH27PHdagAElHcyVNOMhC0DrzklXW9VnpRT9i0GNUtuJ60l9PZ8VgLOSOkritpZorcHD4QYICdT0zqzYgdxgcXthx2XAkD1OKPgh2SB5evLYvSo9+2FRPkaadxMm0PcNl4E75b8eHf1WU/Tn67EItemTZFG4cvATqhfgWrpWSDYUO+Krk2/cHcv8VbdEU/mvipmigqQt1MtBlkxZOweQZIlxzI2COmuJADghByBm8voTwtb0mH8UUjqtRzdMpzaveHzvQ6BtHBB/OtJuvcI0K8UcBVelZmn4/9QwoSssJmqElDflEBoqCNYS4T2U/S6xhpklpSIdoKAtZqjWv2rkld1sCNVrygpmIBruXrcJzIPLfUgJwVE/WQYKuSjdRzKJg5mF0oC3hjTnDkRgTHqLFsqUW+ZmUPm9Pq4/med7gyYgnZVL5HKlUQrwMRZ+rn11sI6dtC9dMegIk0DQSxg/SxrGCq+VpwB0TRvFZuK4Eyg7l//3Q3Pn9RZi/PXGGaFmWBlnYLNTMjFlWXUMWPk//wCSJQ6hoZc4K2K5+FCLJg3vb+pgwLJs0ibsrQQNPaqXQucb3WnEd6KDuTY/NMBh9ph9b3pJP3W2L0UEKBSi00bY8Eg6LRYulNJUjpZMqAOMovB51TKR9iwFpKxUhHsayaplc2LDUwNqbWxJ80WB4lJe2Zuxx0hkZ0LPzTMr9NVTbulwqNdwlWASMBD+i1AIKHupRqGKhu/eIuU3Gb33RD6ttyLbvmVbrnGVUdImbCBwtrUvcFJ7Wfy00E2LSvDQOcZymFHZ9qkAOgQkVSOPYJqsoCZKo+yp9IPHhxR1L/UZElmj8t5jmMgpgaCpRAZdFFkF4ZnTMbk8wxa79Tcm0z6qijPe3mUnlBZNq7rU7vkMkmssNr8qNhYqjSC/ZFBJW6QWz4BcerHiukYyisvfbdskDWB6iAVmSI5Ik9RTSBagICVMUEvRZT2RssUnyUk2DRji0u09vq5JSL3YTmeMZiTKssIL6l4xyaweC7NfXCglpJFj5v62Q+R2Mrmx93hK8pcDBFkeIg52z6kIN9DSSq2BDna3Eyyf8Qc8IbHQYbt16o4D1LXnLGVrIeOI4+rlYSPi7AySXDzU9FV2r2mblVuuf1+yCqbHXGqA7J2xNFWOQEZmOWMoKhXmnaM7HqYLLLPb+/wS/eovQtz/nyYrWCodWMoFMCJAQv8F5RiF8zX7dknA1iAn+jUw/rGXnIpeK/HW/rzzVmJF57GkFL7DqDEonJzzrO4yGvSChVUm1Ddr6naDFHZukMJa6GF+lBIoyQzoBSZRASw1NLfUL6msQXk9/jjzm5v+CcNjsYNqHgp4umYfTaGN6k7yPH0/CNBoG7UPU4aCG+qRXIX5Ekuaayl7zJWzf4cQlKMk9z/0+G9hd+lXXgHRKky57Z2MQx92kFLuHpq7RwekuB28CLOfAPZ+Vcv/cndioU+ToeG/v71etp3xZTT/VJoyuv4lRutWn1VIvUiqBOVGGYFvBX0h6EUkiO8oUjdLvF+c6+qLr/jiRoVm98ZPOYqyqg3H5QGImrkk3zIFrqGwskKPAXCmuDQx7XNg16G2k6lINkTjaD+YF+0116Lgj5fYkfM9ZuzT+UFp/sJ+zQJyuGGzgDfX97lQQXEotlRDzH2Paps8Zk/jsb+JpPEHlxdCR+s+oFV+nvPhZZlCj7ht70xTELBToc41dvW/J27Cp6weTq7r3slQwCk+D3LslyCuw0mpND1V+fVZEFVB8lSnwwfGGtQRijG3mTiHNLOoHPUMg0jWpRB7+34b0xphaFw8bpgpgrkBOB2YnHdfuVa6x5xPRbV2sg9OFAqs97cXEi7Q2laVFwsLV74emTLyerbIee0w+f0BQ21965lKrKia1yUxf0X67eX7MGBqimwMlMbzgpqdBsbwQ3gCMK82hU+r6/wajo4yYZHPgoG6S+t//b6v6pzEU5nx68Amjk6sHhdIQPrtIs3ZWs0ry6/OCnicyVKHGZBgLsRXhGI4V6cY1552TDu1BO/dEAPc6NMrSMsq2Y2eAVjM9p72CfujIemxXf600ZG4Ai/1ZoOHj9c0S6pn4zsIHElhYNhsXKjX917a75a8YGKHSCzLLgIzEwvnGatuwr0Von47NEOoAJJfErByFWPNG0kLB8y0aocxRXv+luf25AAy3vvECG57nelBYwyUWlQw8vJAV40dBbuHJKxyLSisP7/qzWx30n24RJ9rhwSv0HsyTb3mQ5ApcOZ+liDmQkTqY8/5+HtbZ4ouO2UBiP0zgbKw/H0Um5duXUOEH+dj6zJ6n3RUDQw7AFdHKmx+CEI4kqUeGKCwnqyMpGAqGhou9TdcQl5+jCYT+n9+fG8lg9ry8N6pBNecmzYcdnbHFyeGqfB9zO+/5kPUJMxpfxU0WubQsbtOK/3b2nEzOlUA/6Tn7TQ+t5GZMCET5OQdSqLUhEVzLM184a9FzrdKoX023qoooJ2Fr+aAutbDYS7fv7YbJRRdFxZJSzHlpEHizJ9/tBau+euXUJpEGafFnTYbshnXUTdxlSoM4KBXIYWCRDGyg4l1KQEk4H5ae3mv8suPuGKduva6e71KoPbJPT5w96Fne41NMGvtPyRKfRsSEMLs/qObr1VZP+35wbtwAjl/CXp07w+PUIYutQRnRdIbnCnyIiYZYyO/4+QY6HGG0LL8R6kkkut79TbS5mnyShTfXR6r+6JU8O6nqZUfjWJ8PFzsW0aSLlQ0tEcBo1IFHoR9VeS7UHW8pFYvEOhyJhaFyPcKMq6S1JqCp3Amvyxye818D/Rd+o4egON9HVKYFhFHwEE+ABtzELcjE2TP1pdQNrOX4KRlhM0vSkGvPktJ4LRQ8FL0voToHUZIA7y41/JIuMxxRppL5mrDHzGVKbCLiyrFpvvRMR4RZX8Ngp+WL60OF8Hnc4mLA3BA9hhjqSxEPGfPC4XkN5A3MMem0Xwbcv8EElLGbBlXTorRPz27Eprm3ZelSH9OZahet6cLLcI/TOBnB70Okkwy96R8YlKqJrrdi7s0Bj6cHTFre9YwywmNQL1qHV+tdaA4FGx408eqXItGHfZzzKUpc4k5ShFaVncgYcV+ZJ4rJgOQ5LQ4bOcZSiFOR/IJXlGWQVBTOtUdh1MfZQpHm3s4fJ1TWWEc2CjaCrexCajbdqlKpaIDpmUL+xQnjZc6vpW8QgZLyZjcjvnj1wyAgmmjvTi+bsV4zG6ZudiiHOcSbd8h4txJMhVPWl8attWYD3f97Xzjb3H9ZviJgtoahh3iwh/WATnEX75t0LEPTcBpNMD2PpTaFU03GXjqqkIM1DJZqLizlPZXw2at8x6+QS+jn3cbyL0tzwQ2Giq+/c7b9VSvHbx1F5xIiKkd6ndKnq8LGpo3CzdajHoGsEZlDOZSYKquoD/QtgdTQoipDWNbd4sx2jqiNd6u95G4j3uHhYfN5f+uCYBISF+33tW/johtUSqc8D3H9Bk2l7cdwU7T6YyfLzfOvolwfRmssz4aR1ZAd2u8R+lQZZZOYTrRgeJKUxOsoCNQgYcDL5kkeHSpkI5zFMlZ2BdaGPjs9QuMOCOM0xYRoVMakyWdZJrjYG50ynQhsckfVLQPmFQ5EUZpwaGQTU+dIrDCJAY/SwLZzAjEAaF7ZCovEnBeBVX9+BEp+t/Sbboyvhv/9VX70aVMUoe6tYVnJAxLPWE9Lv9YNJQjmCqGXNg+JAiCe9zbLxMo40m0SoZg8Fo+ereYLPhpXQWsAgFR0yKRpdbUJYP23z+cO9rUGZyal6J53JIN1GvGHhKA7ucdeLT8i9/pStvv3C6ExjiWcTSOSJh0SC20t+sus7U6vwyobZQiCX6l6P/4vF+1+11IdoIh02eW2mSlror8jIKBj+TvKtMRJVqd5mHFYlRyS5gUhBa/jcDH4L1pLCi8WUNrAcMkjbIv1qJSrWaZsOloeW9NJ7lUHMU47emRQiJtf2gQp/QB0KrT9o5ijpYgkZcGdROUoV1o8HWipvlkwxRZ8wSPc1jAdiS4dN2dXg+6W2eDO6YOulbOuqcMjBmRmqUDfWZ+vDuxdcaZWDzgZooade4FnwbXthb50ftvVtP6FQWfTR4vPmJrbxC/3tO1ci84KlD0xhydp3QsakulJKYDhxd5O+h28ohIbA6D5iqf40cj1O5dOm51x9iOgh7knzq2bwVed27DvNHR1lczPI1GSY2LfS3BPvr/F+gSnUQbf3mYZjSph206EZ+y9XJzykj7nzXdMVCDOqDk/azzh9Vl38FS/Ea/VgJGh6rPZ9XYHnNEfc73l1gvNKxdbhX6sH19Q21lyyAiAfzTuQ93+ZEFYeALgonSCi1A4Ob7k+Q9uLXvYi9tEzOyynp8pSOF+r0qIR1A2xBDP4ZK+4G0Ezxmion44trvSS0xXANeSfrLV90B6X/6f84fTXQWreik/GhIG0pdjtaHTPfPfscBmWKiXlQRlq7pdXtMSK1mU0PRNESEZGI9QxRJxKbCsv0HFG3XYF8HcshhvioKvHDP4yvU4Y/nFiPQXpFMAhbUtjuQBT4G2y3wIbkznY6Y+b30O6Y38U6nO7bJzxgXu6/oT8I23eOMCKNA/BJcxXmheEhlZ0/szd4oSuIODA6WvNefmiDepF8FxrsDB2Wju4CH07d+oG7XfP0C7Z5rvsMpVGyllRkiEL9KjTIiTvowqv3P5gioDyFl7zWS5v0248Fc6O1Quer0qXHw9lbHll4fob5oTZtihxYjROisNICURgO0zVej11vAxDt062CIfFhg8POUDlKfvmXGItXiYPrXH8MVAxBiHdq2uhe9k1Z6ITwPSjUmPq6K32LPjz0B7qf0Jm/XoEgY7FhhPROeOf6qQ0zxUY85OWjFxFokvqwytc5RJmxOg9YQ796HOXk5zegWFnszkohF+m7XOjzzWSG0tL1Hy+MlHhhyIOiNVz5bSqYG1/NqsgtAhGJs2MvEMXYS1njYDQOlQz777T4zGb2jQe3ETYdmiYnz0yHsXq37zht/65hSmQK/0XxN7AcosMectt1Zp+Kdpep8FtHiEP89NDN5WPS2NkdIERKhMZKosUyABhDAJK6BQeZkcyf/EDQKltRGDfJFA6WxuLrmgrzbtpItMTanqEpdLp58+eEL9Zc0ec/+JyJr/9RI8c8bUD6vPef14wO3CTdD3iyfRDs6ONpTGqw2to+ZOsBiOOW8dvyZ26xjQcr3GgAzdokcZbyH9y/oYJRs6oHVc2UsAKzBuYt8J2HOeHhwICvv42Ts5lehlsKhIpUWCDRz9NRwsXdOvxJ/rtCYZxzT3VmdFe+7jtdTzDEo8DNYCjsHSank5rx/2C33S8zRlSWIfC3bapibJJu3VA7xDUz3AR/o8KRjQqNbuveixjRXkPQ9cwrF5TqaFORsMfpFv85ieygxa5wEc0TlIRFNtrXc59fHY0zounGTVxFlvh8eU3p2h83zpllofMoshJhNsNhMKVVzw8cCXuuKEc3jNXwppDRbN9E8rNS7LBMF69hsfnKd3MXbWZq22EeH1u4JdpJ4csvfsNp40K48nZnjZ9XcT7Kw/r6R0urrzarLyQ9thQP7wiwFevyRT7wkycceIpcI0fCmVFaHiMPz0Ar0ttJEwUScqgF5X+llPAu2RTSh7KRSe4V/qdNQ3jdKW/5BXTjGsFxmPEcsOMOx/ffyBE145TarHVZzm5MIZ3S9y9Vj18WAq+GueAd0dL1nU34q5KHtginMGQJN3vA+Kt4sdh0nhrGsDCZFRFvqpM++jMxh48+fWYu9KcS6wrhVEXRcPwcZL06+eO78WxhJ1P7lXF3+DROQDEzPSrRu+hZbsNOsQlg68MWuz9r0Y9yWuLQaxN7WousEXP/rQjB7Fy0pfLOT2POXsio2vpo9jiwCrpncQViuiE4aCc5ct5pJhz5w/7R+OqTNC9d73A563+QkfeyTRn0MGYMbRMI0aOiSW/nfu5y0d5NN/fuk3PIjTAcSPCiB4iVf3MoWVEvYpCw3EUD12v9c2J08QW73GY4uTBp7jjbMuN3H/3hFF7ZvWpXffuTxgYMx1HLBcO1qL1dahXIGHBUEE8ps0THGcgdh3DwNSXkywN7UKD/hA0pmjRWeZjfmcTITGZ6EiGm0Dtf8Xp32e3PwkeeDmxf4Sx1HNGcGjkKmx7Vli7pok0LLSMhkRkmYXU/d0oNU6HPNjIkgriggOTVX3M7C9th7sU6f8r48M9kwlCAs8IitqRONYzoM6K+mX2RcmrIGcb/ZTpxAKFv7UtrvlFdrzwMzzV7wmN8/yLkSroObZvGf+yL/yCQpMIMdX+hMJkmDvjMT8v+nKhM/dqbowNfWNZuOXOjL3D2vh4w6VikzaHELwn+eKoVZuQx/Now+nGPr2V7wAAWOAlsGab+gDszjMSVbsoVO+GlkPFdkhVEigjYk/xUa0S627G0l/WCosWl3cV8Wnj1+Yob5l7sUa/7SpkcuIeE5ERrQGYx01if9GIBP+1epUS1Q66B2kQnhARE5WvA11KpMdvIG5iZ1NMtS97zVHJkt36Ek79cxvAfxCgWiD5C2xP7hMKU70LdZ/Qf3A212Hy1eUQnn35DmgfjseKAaCpb/ciA3LSPPozM5L/oEs+UeTXW4XlcE4UdMF2wuY6R5M7kB6A7JHMcARiBu7KYsI9c8h+lkkZWkoNEB9wi1becuaodbxXcy99PcoVZkoqO/B6cJAlvijYIRopT81MzYCBis5lYGwsNIfFlV+mNmw2Gb90e2w7ogqJf/49uyEeAJMcvZlpki2VSc7GGNr7knpwO4fuJ9NVG3KtlHtoWrGUaNzF6Y6Q2norJsejwiHhLaHczzjgu/YJjXw6e50ApCX4tfpEWupiwxCHvUmBxJhnUzQ5w6m9vXVKNqGfyUyD8m9+jIgNt/Pouc+qKbAOOqeVwyjlCHl1aMU3UZukRlw4KnDFX/kZHBcpInAuzXbkha21PHz7Dc1L3Rfhvb7Kx0phIm7pAjkhcEF88gTzBkTwVGwsCt3TB+VGaqWK0ThNTgO5bz0sJannrjw2uWEShS9LvOpph4UJbh4LO/lKS8TWVBJGSeWzCrxxYvEJ4iPqPleYWlqnPR4+JG4OgnOw/2r7hIy9To9SrClxzoTE+VlCIozOEMoid8s5QAUgZWmbhsQIwAA7xWyX3JfqJbtCODNWvlAdltbHao4a09WM7je61d/93YuWUmKPu+B+STLNmVrFXfMLitOYjwI6NtiLYmSRuJCfNuweSIl4UgDEcBcNrNTBoXL/2zEd1dG7/zEMS4RhIgM+So+O4v1syXQGrLzQ6fTcR4zyfRBG4msmWOgi9/Qm2xtiXN7/EHLJ1JQOv0cBsGUq/oOfPdjc/Ll6JRIPLsCnYEy4FW04IKxHo51X1i+DWSBI51XHBakH37MwvDyCgRNapSzjQ7kryroE7V8mqPkn84PaXDj6XNkbDIN2I9CW5icatbxQo+VrUvlaHdYXT8MQK2Qynnawnse7+e7fz5ozBOuHjMx035mAJ6aQcicXPKAX+oU6kR8ATUqJcyqIRHMzvXOlPj+jBzzUm9+rTMU6BfWtETVZFXB/h3OK8leFXeyy4xrSJCZyRczwKBhWM6DeasvaMygOp2neqaY1v6EG+XRcsy7IVvW0pjX1deqvEDhnw86MLWYu8Nfd4EMJEgER0iGZNzNp9oSLT18cDJkFhaR8QSJwHOIhmRlSSLn+/pW6R6E/NKotnglXuDIRREQj4VIyO8/2tGIEMkujL0MEzxWNtdPnGxy7Yg3eAkRGNFJTbBLEKQ5Qd1LGtaqTxCEBVQpZeH6mWL7WZ6jLNHTy4CCh4lu502Qmw3rJQDSz8nhW5B8cF6DQ6zDCwiUCT7AsMrseme17pSSbtLyb0xof3cSmgF53dhr0L1EXEqW0iVDS50dxkkt7/aUjnpKNsVyJjQ7uNxrR0t7WyPlSmK1YsJm6xWYucRc7X22f3iDApvuDmCQlXjjnDjw+l3WIefaoeK0izKXwgNO64U0T6AdQWqLl4bP50vgxqMCJ+OYX5gIOUobiF1MWoo7Qz0hnLSRRX1t0MQFSZCvwNkwlA+TMJdCxuo5hlGDwwX3NuvFNr+plpxwvCYC8QzV77gs3iSomhQnqFXNwSRH8KPf1SvPddN+HcWFewbBJWTpylQp1LhHiBFcHRRGEmpdSJa7Lx8g9MGlYxa+1XTkDCPIi3bQcTf7mcM6T2+f6EWa/bbnFwJGiTL9/kSGPd9915BjAeeVwSgqomEtC7MMXdf5ggQDEXUkYF4ORDwyBaTTHdzuz4Xk2Zz4ACOKdEE4oEo5NPaiXWTxqu6/1cl5dZ3wXYgsGm3BQvcx6hJmUfMjTWdDb1R/mA2b4t1zu6RwlapPc5kfJ7RwHHrf8c8UYBSaQGhWxlWsRmAEBwCjwlCMDzwrz8Wx2SJMzzbMy87ZwpIFl4LQ19tPMrWb/YnvrXtW44Uipichx6u5SiJUH7aHCCBHrEo9m1YYrGo5KlUx3KnPM/gvx8SKFiGjsQEKy9UYyr5znPwyh7W8X9AU+ZdeaP43jJPM6V1RA36DAn8kicPaowGX4O1ww6NPomLhWGKHd+Du2LuM3uBISthWUXjxzTr1o3MEyLTOX2MjyvLmFM1BghU0Gz+KN8knUdEVudbtYyegqTeBgaw5+cVOw/TU81JqSjja/Ed7cZwuPpfJWNe5JHH0nyNKFv5xlSXa/O9Tbxckft7wqQTbnXjmG0j9xTGW/W5YRUP+TYpkg70Ym2XtJd96NA/k5qg4geCuFrRYyHmGPO8QJQYAAtpMQkt6lwUk53FJqA6The9qroJ0idTOH5doqgt4FSVb+KUm4SeUU7M2cySWW/E1f15Fo8pTGa7X2fv9i5y+1mioSkQBP5fWmdWb47YfJEzoWZ2GDmrUj5Ui7GNey9omUDnesatmhzGOun60+vq7gFy666XnpqqUzurmX09yb09hGsonJlGmGJAadMNKfF52uqhQgmo3IOiu3jPnb2zb4xvBfcbvtoU9DGC6+eKQXUpRMQBhrRjiGmitybVTZc0J9idIlLdMkjwoVh2cZKda+4qcKoJP4sVZWF0os9cq7WUoz2X0Vv1KNM2eH5MprTfq4GlfseBoGYfKAMYwqvF0lKG9H1nODG6eneTPLfVREyQuSh9yWFiVEfcy6g/bIieCpnWs8B8S5yCqSefG8okt+vysUdS4LRtnbfqB/r6T8SBR757xaPm3IdgGLltHG9VP4LoX3xrvzPu9Dhaoc8udEAfluvBwIsxD5BZ+LSGcKrAZwJcY/ejnFfzsI/n2gI4T62u7MxAmm9ikSvnF/OzGcDSmVuq3xmXh9uTKlQvc07hAk34tpNueETUsfiSpKTC31EKSqVILlO9BfjCZvTuSwNzzvQbLdI8evHoIZdDHph07stFmkNN+aRRoAD6JZgOL75MxKEAfXHybHJyDa3KPCnnr9OwK5oJsYG1tW9zWxO1jQyWE9R8M1CWn4XElT0hKEAQFKWkhnW7e/Jd5oR4BYw16GFIWq22ZLOf7py95jVXzIGX4qqqa+trIcHc6K2jTYcvgOx93nuBi1Kk3D60aGaV++1ipqOlYVKO3phyWo833k6o6shtPzJU9KWpqxNhWWX3r+JZanzXf2xWx36CQi9f6h7uoxYGiqHKwzBE5qBmXf9YuIz2j4+bkeOnLRo79fxS5pQLfn6kuqur4t3m8zDTkQGwTYHgKkzJI+qFr7E0Qz2w9mfBA73/0nJEYZK1Ny/4btlHp4V7aA18pdNxClTc1ad42HUVOqyQC0R14TbpJXNT4HL5o4TK1vl+FZ3UCyAS7HggPwlTJ2jFR2RUIEuYNYhni10roP8ivBJmiyrdl37+5IWytXYr1r0DVf4WSamk3xraTL4bPrpbEwqvMA57nGeu3q7CMDhJWNFQucVAFD3nGFdEN642ggteGlliZy9/8FgeLKzCng5kc2zUAc/DoZImpS7wtMEyngH2JAGUkApcJ6krsfe1rnHUzsBb7rAWQmCU1ITrBZNGRw4HDYSsAVHCnIO90dNFsBhA6rUi6u17qXUPHw6v7W1q0dqoz7Uen1qt9Oom+BNUznH3RwJpP5TnimjOY9ELC7aLmNDDJzGvEx2bjp/swGTUSGLzhLs3qlOxqIEMY6UhvmPv/U/hFYRS55y7d/AQp665Q/38u3tu4/7vsXd/SVmRl0Vyf6HF8YAZkP8u1oWNP/scmzG6PJlIkp2bMho+NPhiD2bcnQSjPtw+lCA/qCTD+yNQIQp5kSexrB/iFCBv1+mk6MrinbkESApx/BB23M3LKzdCErdHCKkeWVaYzFHSYrbNHStkHUFwBCxtWADclU3dqGT8wffBgWduXZlb9gc/J3H/gINdjVOHvl2rabvXq+50NvPc/L2TN9MpDV9adaJvqTo2fCXgfTgunb42NdkLQc9BSciAhLWO77MQSujOuOYcfcG3+GiN25Hzzmy82Dy28sdouf14hKgyNlAw6W17Fk7pCWhmivMVADSXL3NN3zHgml6wd5vkHDgXB01Fvo1taMyyMaBn7zY891ZwsjzBZMkMcmkeKFzDXIgMRM7djHW0CVsTIDb25+ChVMfeaV/AYW+9J4oKLP7acNQgfCOV8W38fv10s6ZGhpJveo7yIbcegCmTdw/oxVMoLgL+0ZhnaITW6on5jQG4P1+etKao8J3fDC8/UMHZR9TZ3fZH0uxIgbJ6qqwa63JFwE3ccxkFEeSeRdlLIy0IgJA8EZKVuI73wHurL2j6kOLB8UgytZ7fSz6zNWULbRb95A0dd7Lk4lbwM5YkK3VzIAsbp4EVkHQ+87qxhJ9V5J6evyYVofwRKfB49QS7kZaTJiN1o7Rlw99wHV0htSuSV8dFyzUPA6TKUpZaZLYn8kbBThBjCxfe2s21DVDNzKNeU0PnCOIII43EEgojqnoFJsBsj7LZ99A/zi2f4YPD0j7RmImAhsvC5ot3KaqS6ibjeIbK6HGKLksyOfYHNapE/Pq7WMUYMPgPY2+IbJN5J8Hunxl1oh40dbFnHnRKxuA73dXsaEU14rkcKtvOMtq8hP6oh0iZqmsHe5t/k422W7OWoEiFlhXmopZ+a/FT6yr9gvPqzrAyzlkQJZ0QGtwo9JuYhl/ZF+n6/kw/fTBjPG9R1HA2FXOvVoreaj9nWSdnfpznOSo+b+XG/e1/DRG0oLIQZctzhB53Fe7+tvZ3gzFbWzknFOo763/lrOi/fQuC8gGWNDywr6cs6kfDUnOOgxUBGoleVvTGmz7v82NPc0dU+5sLrHZX+hOihPpuuJ9VdRxpJ41VNzRXWjeXdy7eqS1LdbEub257NhfY/MKXM7+Yh3q9J3nC4s/csw3bzlbVbOVI1AMDlHLflvyQ4HMdFEpEgxzUPwbGiRaNHjXv9yRjwOWeBbhyEGKoh0wcN+yQ4LyeQAO3PM99YQbFgm8mJ7U0yN7d7aTxWVOE5mx+QjNFvicH7iT7+TNgyzKVDq9AZ5CyvF3NkhnMLcWAZCU1naUD1FPN8/7HASFG2PMJm+1Tem+UpmbEZVygwxAFbIxxhp6yJRTumsuAqlHVk5CfRhY+nvpP6oXmDLXD9VK+T5+oWvHPCaaz2E1/XapPWB6W3shCNEhsaWmCZ+ZNoxEzVIvw7EkGg4M8C/tmSpBEh6UFB5A7RktYxXDnrGOothWNdXJ+hhRCAEKFCms7szcJ7pb5h2M2B37CuJ7sl+3rjr1nVPNTaZGNv7KcQbEn3Zk+398ec6xsaIkQLjYss9fWweNMxluIEdnDM81KSgZtuKFQqXypw1xe+ROgchcEk72hGBZwY5jXg9s7xSmMC/MkNuJYpBKodCizgWW0Eti7pmTHRp4ImWGfBifBvfb0wwRBjrHbOqBJw/pBNNaR8jAExNBw0JCLpiOiV612wpDXUk8ikKbmrMOO47g5ruYKqLez3v6Dn8G6GZxLl6bo5JAiTsL8TQA7/x8c7pKzuFnnGro8VbAKtoRmlAudb+BwKJdjhn5JHmr+SnjAaL9gNGR0ZEFAH/e2N2+MOB7FFFrXBP57NMKQSCGITJfbILlPLrOhBnL9a0an4tqRzNH5PHbbgLHnUodKxgGPGFVgTtwJvwuDKIALZWfzKrK5IEdYWhdIpETSWYM5IoaxpYYKH2PB21z5qRq3lbP0u/geXsaZ88SNTwWXI+X7AP5KPb3eKTExGI1SRC2QaDUl9Q9ZM3dbuRFU0hE6DfHKZzKQxKf/vKHZFbNHOS1nHhYuwBg4ujG4yi7N+VRA+v8fl8+mnFL52povIZRECLjHFr8/bC2+Yhu/ikvxmoyshFrnVREalpYSMzpDujOJ2ir9C+AdKIt9H93stuhbJ9Tne8l6FvGAtlctl/dkE4I/c+dJDIQcaVoSCCQrB4gow+nSSfNngmGlzfjJgstigpCtsHn8iUVjqnPRK6dfFb4CwBsPkbkYoyAO3+Ra43p4v0hTs4WKwCn+/Rfhx89HPiJt/pR1WRmQ+Zk7HJ3J+b5uKaAXdtiwPbY57arBEZbfjVaBFW8pZ0XgOn9MYb4wKJ8+LFadVlhxGwqnCEBuGahM0H7Z3Jc/2cpNOcYpcCjBod23nrhkdjo3jOLNEJVos6B5jsPC4CydBc4oDtEkvywqfC7kGVfycTP6vz8D04LUvWYvPqhUDf2tj+95VhGJL/ujIx+Bt5lqazKn80KVf4Kfn682roCICl0HXD5jvDObVJ8FvV09Trd+9qnTo2M1rqsoKn8dSA5Lf2WFVe+jzqIjpbUPwGy1KZ3dOOKRk8zLFivW/O4rmXMTopbG6NaPxIvQJEnZGdzvn6J0HNRpbktRkvV0OVBMZD3k3FlnZOUeM5S3z3Tt9BhUHklekPqGd4N3EirlkWCt4HkfTPsE9egU5XfEgFfnrVSSoEjbRpli4G/GWFCCIFS6FtN9Q6rJWH3e4FdgwKvNNqKuzMOEjiFPJfYPRGqkTnCpoUiLZvuxyZjWlgGopZyAvnBkWoS948AR+yf63Noi77Oy9ZYKUz3f8vC5bDvih1rTZsVXJVRaNymOOUMeJT5VlspiXlqbCTPNXFdKgtcJ+pXhiZqykuyg319T6wcvtx1b31bizhZ1fngoJjk9cfzns+c9069yjoNOABWSU0fdpKbPLXqaXffQ9rHOubHC6urn2RHGZp7MxkBxv8D2NXEBtbI3XLjNt8MEMReqYbJ3ojQFzRfUr3NzXqPSLiztEGQ6Xj1Yfroc066kxlvuC8TWg4jsaAE1P9jtvKNocCp6tClvxF9nDZwzg825Q0G2A6lo8qoP2bhWWmndD8f48CJd/cVOEuXhVCtF4h/IisyKRS1gfqfPY/6w7cjqTE0F/UJogMkC2Qt97y/i3efNzgUjn3qumJatGBLeFEjn4ocOhbWm/jkF8SD1sMry2XglncwR/PCO9687H+f22otB7iuaPZaoC1/459sZIZFfmQMKAShAkFFB0S4hbZ97egMs+VP/7ADxdGyxuT3unnwzy+/pihh7fZh4y1xtVi2Ab5CoO6khWf5e3KGgVVwVU8hsnC0OlBOpmMwtpbDy8j8/CXQrsOrda4gla8r9iBoHaKinAqCUy7v0/pytHLtLve6HPgy6jqG1lUGV57eJ9AK7MsX62KJbheJ8AAy5KsB4xi86uIkZx8MaW9xk7jByxP4+omVxKEgXT4PJ7wetTQFEz/9CemBL4RiwKfeyshabftnjf8hMQL9sCVcmfdWBzIexmAC1JnjG1XIr1t0N6CIM+cZ0VRcFexJOEWcKG8Hw9HRtBWhY2QQNZNeU8A4tydOqUn3e3hUl7fuPQ80vsHjfC5gj8ZkHu8pgObApy54tNLlY4PcWX72SpKpvYlEDyj75B06oXJUjCqVhTNIWyjBWP/fh9E2WbNyNAmTvVeU2Wr3EdoQvsIsJuvYOjwcEJd7qBLgc3jAZoJplm1IxCtAX6tHcLwyV0Tc0nGB2xsLpAh1uMhD6nbY5YwkAs4sNHHQ8f4fJ4PyOsaww6zjAnWIkM7F2pPnnG5Ew0lcrJz2z0aSNal4I0a0LWskfIbsZkR1LNvbzssqyHlxdOXLpVWjGY/fDWB+juCxErGjIejnyjKSrtZ3TbPCtQZUIJVhOb4F0eAOlkGiBk9Sg6LQp0twnBNv8umlgGaZuNzUafkxZFTjYI/yUW9bs3E75zVfyEZAT/+xriBUAF1NAgPtspzvfl+YxVycc37OlhYfMRNSlHL8GcMhGobTDZVUEaqYOTDet0Ym/0bmqNsWCxmkyph1andCxIMIkQQoId3m4vrc7oIAgYIkDgvG9Mbi4JvvXU+T+BYw6OYjAJMjMEor4jd43rQ4wE/wRIiNuFXajwOn3fmcWObjnlBjzrY9+PvsmGFLOL+DfmCOG/WfBqfbqt5ziABxTLFt9ezkefvQ6LTB4sph5ZHJA7vK80APX/cL3j+lJjAAPSpC7BTCEP3bcf4mYtGfyQlz1eNDQz5YNWPnyjQ2KcD9lu9/ljGpbezPjvJrs7Gd+qbdxwQ0HJ6/gNs2NmrcyoD8nq1DTJsST+39YNSDrE4me2lYr+3m/IJPJEmhrxGez7Tam0YlLd7VpO5t2zefl2aa71jf8w+8r/zUp6X4oryL0WZ5EHyVm8GE4FsR24rjCm3/T8HlO+jNl8bbW0zQBZZ7/G7TvLMPYHDa/YgYe2O0DJ1n2GAWd+Nb2zTmPbI5ieivDfhXhfV5cm+a5SvL6l3wMh4/yQU1Bh4gNhyLtiIUnWybudD6b+/I8G+32Pjx9gzt/iMJyfiDZvecy/LCeK+uESoR1bbB1sROL4GqtHARgg9K9A+5HSlVChvLb+4RltVDDtBDYZos07wQYxYKEwGpBAr5cJ6eEaQTYK1FQjHclCtLUwccZXNjXGRwZiivkLXvL50xV1d/JckRQOr1AsfkH8P8lF2dE80fgDeO8j7+llcicgZlxI+qi8M4G3fluVieeGSWHVqcm9nVLoz7oN6SNAu5gcvV+WfkN8SdB9uLKh7KJAkAOMT8E4ayIq+e5wicJbh0dDlGAEBiQk6w9zacPiSQK68fzYUdUezHgmJrJBTBjOs7JdYd510o9zFKsuZay+awdTsZRpW3IpjBxbu8Chbz/3sEcnuTIq73X2sLOmp3aUAHhCLcCSUPyyitS+PK7IklcUvfdMCVYBa+l3b1he+vjbEwZjjOcpKpZG7mML6Ivg0We7v14YynP1D2mG0ueqrQKET899oIowvD9GWIkNa4O3QOq46ILgjbZlozFVRr8gU4w76Lp79HQtccW2ddU/Dx5QBKruNeBHhc+TFRjHU919VAXSIAQOiMM6Of2VCM2a6k3pqIt+0iuvrX6gsSkQxs4faT929UVGj6vLkR74rSfaKSv9UENlAKxCtkolvHcIJSZdyBwgT7w8BC/Mq30m228OID5CyCoCprWdu/Poby3FTfkKpA6vLWNGwxvw5FhfwpR88ZZI3xVH8fdezXikE7ZSN3pzblOjZYMz6uPzCnw+uWZpssARRRxEjdC0RjsFUDbVcjOwTSRMmIsm9ObOa+1dNWbVdjHd4pyA2MyeUSmQ26pJ3M4efsyas+IDXHORPypYuMVu/i0z1zt2w/J7opLYzHl3Ud7/C4BPDO3a3yazmMYCJYUNPPKx147r+IPrWJ7IOgYu/3joKWdq1T1PMd/YpK3tZf4zZUnwY2b5Ov5QNSgLeBJJttpQIYnBzYdvGiSAqb3nd7FdLwoKbal2Z8/6o9Qd/l2oC5SgYnRdBUwN9awpnsNTqYNM6bHwK2IUmUUwJBfM/jzty7EQJLWYfsK+Z1WkJzHdpVCzwBmAT/+jat9vv1mnflqWX72ss7smxWXo3xT0tA/BPEG6BlO1QGpgFEqlRAz05hguiVa3KX3O61H8mj+cWfUiqyvzHl9u+i5D7xDXh5u4ca5oAql03ZTeE+aZ2U8T6kazqJuu1n1KTkriM972YesHjt0Jv03xj+9a0X7Ewt16y1RcVi//eCHv3OW24dXlhnDOZ/O7kjo86fprKuqUTWARkCT2FuwdWbYdaggx3y/4VgVZUzlLA5T3NmjCJnL9n/Axc5h/ilQw0LZIsUgAtJtEbUBd/WdZ7ty7LYWhcctmMNMrCRKLhnYQONPWAlQWrQmbOhJtKLX0PmP1b1nbN6/WX/FV2wlYXsk8vXw8jbpwprtktXkB+MRU3DmM0BRM0PXNnKE0nZkL98zeSprdXts/DMY5bSRemo6Kp4q2MLQWxy46hrucyHzA+155fjGYuvdCFkqU5T7/F2gFrAoVfTcvJXSttOmsgq31q51wMmxU++tNfPo64wU2AZIRfJDHbpISljAOW+K43VD+RafkpD+CaMorr6I/wcKfU96Vvn3QhkiRGdLgUiISTGRWiHYYf7x53UXS5JJaNVk8Uf9tWwnIm2VaStrDFmgn4Umi07ibw/VHhniZNt3tTaZkK22Sn9BOCxCVf7desv/TVRGj1P3wz/540cLKd/ecnC768IRkVVj81aEsfF1JT0dsChETfK8h6PU8QXKrgCuuCQsRlnAhF0DRixb1J6/Dw/rWXN9+gUURGCErcXYTjsKaLvu0vxl/NW0xlRQvzzX2cp76LrC8PPpLTwlQY7wtCiMfk39Ygl57OPDybL4dNSfxOamGNb21owQRhM/9jzAm4mEFeF5arayttE9kAFzUe0kini7jnY78btM/HcazsRulK/c5BbgKWhgP+EsCKzO1sDFc/0PKswfHE5a9k0ylMPjFGaHPRXNSGNIa8ZlF5NKnvQkrwHdMytXA9u1Hoc05TylHQ5no3j/mTWQdzxD+19VGFr25E29Y36/Zlwz46QoMiWZpWUOigTSIXv9Vhtn1tbN4KbKdVfAaS3E7h7i5gDuQNbw7/uszm4erc/ARHJnS5ehl24BBzwhV8BRLbbUPc7PTimwhMfg41D2r3pjrAgYR3QqtdvbnW/NI3wGgc+8Q2eE9g9W4mqQ/S4WRgsbjZh9yl0RF0O6ideBXr1lk99hjXtJILU994tiZYO+qEJ61yuRev5WKlLLYOwAA7QAxN6DU9MFepHCTQ10fVUgKXVRJB7R6M+O6WjBBtsO6YA45Aes8nmwPfNF5yRPNLI+nqwcknL3B/UBPnyAHPcpvmgCnBibRx/IpiI26BynFbuWkoG+jxDqRV+6H9jVGXD3Xc5i2XLJiItpXG99vYGRmBX2Vrewl3AzSBpfmSeXq/YJq0DWseQMk4Ad/giS8kcTPa1mAaxRcxTItH7ilwn6TbK53drLp5AdhvZCC4u6jXEIqqaCKARoI03CapsVw6qdzENBVRFUWw1Ep2CPhC2MSqYBczrB2MthcNRuYilQcfZfG5+BDLyXxDcfuBlnYHuZHxJzhNI6BssIn6i0hHZN85mxWW7rXVwgfYYXv6oLZSFVvJWUfEEJ/dHrh18kk1zXrlaZry0kfQA5E0OAIJveRmEiLtcB8LgCUWCgGHALHML2LYtqNO2xXXCwz2aWtu++KXarrxqt0zp2Ryf+7UyGe19xtCWOFw5LRZqneFQdtw1UuLsq+SXc97arUvOOO4MsU4UHd21We7GCGty6nxI+YpKk8vxLPHSMwZmt0cTfSS3DruCHh5HpuTakLKv7TPW/jTDEx6pdCYU8upXrDLHwTs+odoC+T1XnlA/8FoZBK0ocrodMwk14kPHZeAVsSw9LBk8MHGEaMJnEOtiPVsLKfOhRg+/7+pcNoFYZTLH/HnvXegBSngiiwP68LJTbcYmh/sDb7b8njB+aIyWRORnvKbPEbvY+RwSc1EwXlbLOSppaHSJQrO8IGFGXzspZXpcmUrUzbiN4/8vOXLgZpWjhOZ9ryZvr6UBRh1tohozRGK/X+5azbvhiHWOvuTsaUJtjH94ZabJVOQYV4NBzmIFnTfDL2CCijQRdjucczpRKw7kWpwaeu8AzcbRHEOF1MU8vqVOFiyI2yUalDPytlknT9ARhSNbmJs9xVuWeHANfzuJGMNVds+c+Zp23kFRDZnzl2PhTFGEj8i4xdbtkyZHTcllntrSAp5HoGNsJ4wxSNzrsUdo5WIg4I9fbJMplGHKn5oAjkN27snJaBmvat/yP5foqnxSZjEmzqgr4Td5K8YaegIN82miJj+6tqLucAQL/tRqbsZHgU9Z579ruJbUdPgNB8Pf0JBa1jbOKZ81lS+WvaSr/cAiUoZJ9MjX9GGtPipXuTCmPqT3TlRcreXLTRNRS+2sgRH+vHwKZ0JoexwMmOIhTVk12dwkveq4zMyOt+GuOsca/FSFFM4EKLtk5Ie5C/Jx/9Due3ynNUm1DQDX2h5+aUiLo0vNQsWfj2QpAepEKyuVgcKu3Mlf7BMLCc75rsSFyZzhPUndFp5xVLLzPfnFVNVrvsvJ/9ZN87GtHel4IpWKKLrhJu4kMoWxnLhZU8pCU6nkZQX3/S2u298L2tn36rxvcQrwUeFNPt7LCcjPSWConbyFJJmLft3Fk2lKvuZZBsSbhQLOe9VRy5G51POEyk2+kRIDXMW4twr6CGSeJ+cLt6Wdm+aoxWSLXGf9zGaZe6U5clPRE8mlsF8a6dAicBci6/kwiGqL9ldjyQsscjXGt8NPaz35efO3snZsm0NSVQ3J0gtwfQDYfrvf9T404+JmcfcpYldo7F/2Jcs1KQH9OQQUJcjujOBvjTp3S6rn722M13S0MkhePeY/rh8edqizMpsZGUqrpXSnlAaIZyDn89naiF5N2sM0Xq/ww17Ijz7Xqbmzrs+cfs/O9OjnpA7sh5dWJj+URTql43nH33ZJaxH+gRtdyUl9JTUDz1Kqv31OS4mYfdBsUyi7NzfhocX0jTm+nTdL4T2xihqxCcwCk4oZNvyDrDUI661rFRzHx/31QeqSo8AJuFp/E2NmYv1ybXhgb96l9QSakJM1wzP/96urZ/AK6Di8kMu6Uo5QjvJxDBENlIek+N7lOcrTKO4LjcCcNOwmNQvf0Q9nAZb35KlTMHTISJYp9+HNH/IdpU/bF+d2FEEGhz8pgXZeLX8g7rRGLaRCyiKrVtO3KvmSJ6/W1nvIlDFzHOOnw/2v0EYc7jxu7Na7VpZw4T6bgz2h3hvefXqimJaxaZztirC+3TFUrRXu79qyHnblhyQAA2rklcVFOZ2j74yH0fOEnDRtdGNotereQrSCXOc+oKxzA6A3qy2mujR1lCiwNPZeReCzW0JJozB//uGEdlmdTPJIdMYNpK70ximLpSPx/fb8aDXQTigIfnBGSK5WdjYLPgFrwwp4NWeompxwyPW9ByPGPYECrzzjhmCaGrGe4oitNq3AzGkdtgeqsiVJOuw9QKa8cu6vUSb+R0Aha6/eUKxT14CQI6fedTADClTZlMHa4CYM75hhQ44PxqTP24wn6bmZVwaGJOfwGLi+txQb1x1HcTR4Vf5jmorLausX5UyWHPnN0T5DCrC8X+VVkAC2QazRw+yiUkluXRmAcPMjxJfOnsg48T89asL5csHOuIaP0K8B8M8zRhQW6eV0aKr4vPmzmUx44OOSo+N4a34QIxOFkTQwi2TM6ca9R+KtyF8d+IQBSity6ghhVN4jn864F55xoXyzuLmfjT3zI6kib9Xxmlc0k+6D11QkZY4hR8t5WnM4ki4UhKJdQbm4V2zhhHqvrD8+bHBOIE6IRZqXfTlOfYUC/182TYA7ef77fLyyG80WW3cHSCFqpxTTJlXFruHs8PyXf+QEVZ5HYWO8l4y6gt/1+8g1lxcYVB2ZLCUn7p/MISCfTYni6VHmekx3g1VG4tcBb+FFUurbdFuqmaQFFttiW719drnvBOaQEt/fxOpUhqLPTLq6AqQ/J2dcU6nXpYrejbIzY6UhmV5vLc1bes4WNnglodClgqQBbb8pzhaHh6pJyPXQlSSC5nmhVUIM9mdOxSkGsBCuJsUfGjsArLCMNXyMk1sZZJdnOd2JSBbA/x8Ca5ACh55XUDzzhxB17VFGnGd7V7pz0LPCpJU4ab0Dy3gBk5pXvezfJr/qVn8m5X4e5tMVWlaZ9MpHudqoou4vIq2ZbtPM1aVm8kbELc90bTwx5TxHf/5ylbQLxHVR2n3XKRQpQ3EZnIXjl4SNUdqePjsw9vHhkwgrXnD8gOgDJJ1W7zBWqTOokwiTRYX1p3pMofpnPYD+4jGp7w41jq7M4oqgZM3UVr9zN8Pyt7oLEpcUfjm3vFmS0fh2Hr8vO5ih+9u6hdUsIHry+k6STYUALp5hroLnApGif6iuI3yRHXGx2Mz7Z5WFCYyMf7A6qP67lt/dczsnWR+q6QCb92AA2I72/4JNZckCdmRX8fGfxstiA3FO3ZWjB6KmVCAsDyRSI2fbKoNqJKB7TzN+yBh4uBHJcEIshE+Nhpz8NzkiB40cdl3S1wcG0mmPuwHGZXXkuA21z5GT0H4GBVJZHeLFvMYD0IBdoSUlolbJ8ExBmNRuaaiRiNfolNL0ZPZu2WnmELYo0WDw0wOuUrgxBoj0k8bWKjPLDV024514dAjSz5Wg4y7+TGHq7aP3A5PQLBCFxIkgKU7QVqHKz+FNfcBUFkEWQ5n2i8ijdys8ew5wo3zw3BzKZTENRYN7iFrmxi9w+5Knk2m1iMhl/7ddi/t1Qzi6BbAoUu5GliiMvpz7oeK+KglBsJxmmplv1SSHAJDrh15cF0oCCk4UAMMhtdf3Ic1VkCizSgYlJIi1IORBFFItZEI+zTMcmkE6b1jJtgIzWHDULO1m9OMZeik182O3c8PGtQPwbDRbmFRHJjN6v0KMrAY43FHXZw+EFo54YxPoecUJhuMUP0+e0KF/608a6YQ81O0Ig58FuISj/Td8cawwHjxTOxf+uYuixsXs/ZWl+/HBz7sfkwEJczQvpBJFWM+ZvtZS/x11UoEdeoZ2WAe8HSVO4uSGGsYZOE4vY4Pp+5dD+PP26Az25WDfnW0YYDJ6FMTpANGPZyTABCUU5T52rdZumV9Y0y2Cv4BoweWlh/eThiEiU4H6gd3BZ5TRWgdZM9n7kmEEgQl/MPeXQcGOD/LfwGQa8dv534BwC8y8UaW395ZRWMaeRzu8VPdhHSRaK7394z9YWbS+5eUdAhnuGKq/RS6W3wckoFAfJ8ORF+asyjzgOt+a9fLUjjDIAgL0IR7Id59B4UAYqJgwZJH1UuRa5XXkw4KYtgWaCBYogO6SQAwOxZ0esFu7EOgruciVwG6oHkLTz5ZEPxZkdPzRa1rjP+8lLGoKeGP/NeqU0be3vEujwkN30PPGVTvamV1zHnBhqxQFeQu5GpxG+IF+wRP9UHkBdey/GwgoDDvzptD2f0zV6LQyR79UVgCOYNitON2+wyqqvmp1nO8oMzrBGoCKoEEmbk9n5yVJ0Mj0+fc3HhKqVV3mIdQOHk8BUNinhg3c4x8BJYKhpP9PeZl/sWFR+sL0o53+1qMaUEOB9/KWAbhab87aVik6zbEwsWOKFKozgHOcN+Cp5BYA4CvAV+af/+mfV0yjT8UD+xgUoXtsBp49rvBFgjgHB9OiaGPcJDGICr+zpzm+zYnnFHRpNNDIwl1LiErwLU4xEhaMTU9wrmygWGXWtcVzxDa9sytuqonc1ssbmZJlBAfKcS0RglBcleWCXxcaiwnzKfMIO+8L1WBo9XKqnGf2mdOH5LZP+V1/IFvarxfQBcuQUvElLbHg+KC32LsGREuMhGFq56I17stbwUYPERrIxRNT/vE+e7z5RUV8q7ogSRmpwKd5up1Ovz7ZlfQ13QgpcrFBK68m+IA/LWn460fv1rQSe23BW0FNflAG7l+xyjyRFznIZUV6J20pSfQy1L7ZDUwn+e+z6+QfkbiZCfeNmb4dtx4pafMs0QjB4+4999vxKlxsnrGRc8EQgZDWskX+dgpIAfeEjEI64jHZwKcYwKsMziIrkjTCyhhtAZV4hxf7PDKn2LTitNcN7axJGyZ6hj3B0ALD9iyKeq1HPmON2zD85V0pNcn7f5YQaYzBCBBVs/RB0oMx1pyI9qhpiDT2BJ42vTSG93RJb8aOlt6EiHiVyh66KOLcRCCo4DMc1lc2NGko4PZN370X3shLgNuz8DcLKj8BLQAzdc4PL4mGA6xmiguYhcAEmmpeOM3yMOk1wvf1H2wYvcAtm8Ue9Bnm7/pPplxRbbX+po7faQM1lPiknn21whlyqyz9ln0F1nYTxMd8l9ofi4BFKUSHAnoymclRRsGdWfRG+MPMoM8Nx51hiLbL2yIaYKwlwTjLX6p4rLjXKg1Vne6qeVexG6rG36yJ5+98yOhkHZr1bYfzY7vuPxprES0d92jzGqiAZhx7HJ8WSBshlexsUS169hQQ0zrOAO9ySXeupQ1eZOecqFERrlBBAeiZZzYTYEIS/S0iDClVyE9njEToJjYh8lg9iECGN1Z/xRzrkpeJXARqkf5bjAXQotJUO0AoofepMgROVkmCZcQgfBMTPntnmMhEAObtGymSAEbqEspJ+hZaddSkeuOLfFLm5jrwIbf6XYbnSDx0m/8L58jzuO4ze+DV3UV2qZ7/qUVxKuxZwAcA728V4//LpobqX9OZ3nr74YSh28GOfVBL3BOdiU2j5gayESzyRpfsG1LzIkbEiyK932n54kp4K0V32Q8WEs6MfVaT4sxfog1/EEt4gSsHQcC/7gwck/lGNNyAx6qddgDR/1BXVq2LTlY39+A2rU0GLZa3exl+rSr53sN6TtEi2zhwWVG1L+P7Q6SJTy+Vrtve/OVv3pcdMxhezfzeHXYgbVcjGc7SXgOBlDJ9lzbSZ8uCbNbutKc9q6tcMRRcs2KDTk0UrTy/C965E4yb74Vo1zui+mjbrbNqeueHkg86zYjDgvyzOYymJN/4kWk/yFkcLFe0XvL0KOfwc4Xr3d05/Z5JP+KNXaSKfve8zd1twu3zyHPUTq4pZ+hFuH+VAr8qtrSmW4ZSmtYWi+wWWqtLHtiMyZVSeEtxLC6qvZWHZ0L2q5hb2hkPfmQsT4R0GV7PSeBwk1zpgzAU7CC23yM7O9kQU+drLLx0l2e4sRWO52jGXBMoVJaUjyDzThhlE41jSWglJIQuWySzenX4uFcMlFU80I4TgZI8xQnz2hDGFNgJ3uOgIc4ilgFA1tHk8buwgtivAVWvJQvCWBnMCYn4GkS2HlGfPeLb+NHsFTwEGSKyq9OGH8cz44hZjWocd9/B0eot0xFWTdayILF329bzBntZH8ienK6TvqSNnKqTPAu6EiVs2qHxZTdqidLC/Gv0nYLMdsYnbFvibBocl4d3hC1B2kAY4F/903mUZxyf/1Od2Rzn5hQHn0G/1/VkFbZAL38IperhvxULxpcUwr8CgZj0J5C74RJF/+31/LnavTvasVXTnpFra87uZgnWfphmJ6YV8s+GgGZrkaAPslSYCsgCpXDAQOd2sUFrsCf26ROdzLbbPj4iO6a/26FwJ4pcGn0A+xufnd6e0cnt+esxxu3e7H7mvuWqBtUYTpro+Vhgg65aKiWgQikQCsR3WRZKHzkZNnXg+aX5axjn9KEeabmplh1SxY8yW9pAt/sUsaKAFwoQDqtn4OuRpDry+kCBsaG7Wcd0yZErzrRldeD0zpnrbJ711nil41vswL4xhV8CxYB9G6R2NP/s/iwcyQ54MZtDQWY7D4hLtihSPuoT7yf243FlT6Zk46e++sEB7Qxr/N5W3s3Ag0k+lUYjtg7bRJ12MX3E0FQzrSVlhgD9WOsbPh62j4GxAIElXvHPrMmf8o9eHBG04sJtRKV4QdnJ3ru/Jh2r7HHP5SbIVLqaURHp/dh7G05VBQeIJNxPtyMVrNJcGqKmq2wFL2Pd5QhFw4fcDJg2KYZ8V7KFL2aYT8O0xy/f56MfS5zmu3YKGTZnctEy7kRpDDVOxAwXXXmUZ46CEo+Sy7jseGQsUOxlsTmn5lcYCTRtNXD/9zIyAiOXwYeBU+Kjq8P9Aq3FvQA3sGhoNmb5ZfvHgzc4t8IqdN4BiXY+G0OEgJ3K/bx8tVwA9LYMA90LmEC4RrpQfCQtUHe9lz0tqbJdADtNEM8wjDICA4K4g6zMtXUDdMZZgyf5RhZ+ZYRnpR3BhRSez9sY9nlGyFtaJ1vON6barPUtavKz/RM2EUYuWVn62Q1DV9XM5hvMe7L3g3cY2fuSY9k1l3zLg3S48cBd+9uE/nFO26aXhaxxTNenDwQIQUHpaQQQTKW3CA3Zqhidvp7lURS/KMmhYREAhdnaBz5lLKxr3QsmFiW4AeIx4ngQnkS4v4WkTrnG7NGKVwxgT690IdRiVUL9t3I77NBsqlZlvbPYjZAYpU7U8NeaoArHGzY11uTqxbuwYFI8SK0Lg9Qxu/eUOJP1oW/PGvFwr59jvUG9nIpKwBVGaYL+VbzDddahtQvdWwE1NJSX5KnWAJAg62AvIqHSNOR0/Za0lmk25lvFqEG1/ll1mtqMNRy9kscuTgEbyBwwowqOJKBTtDZfhQbpRhZFeoAqokTPJabrglvkFeRYabfapOE9R9rOiq59XQJIaZhKQ+N/DNH3mhhqyR7aMZhXWRUjvtvQ2vz7MDdjHRwI3dYC0ameDB/jLnI9fPgihYiggzC94LBu5AfLi/YJ+wKcokTvHTgjuLmmIqq3cUFsWlDPxbLVUi5r7Y0wIL+OcjU94MVGLJTWkzwpW24cEQ1jfmYScxzRJx48Cmezh5QSywQ69k+WkOIdG6o34HeGZtUPM5C9roe01ItrzgOokhesafm02y2BVq6GAnoFsux7/gAFxltZ6891LY8Oe/xqtzE3cTIoeKFW1XTd6dwrJFA2k/g009VLPWsidM9DKzM254Di8vEaZ9K8s3sCDY5Lo69PhluOa1Gf6fseX0SvWDY7kr0BZH69UlZ7pdZMM31FoEaJgCnrdmS28/AZnyan7UelDCI7U4NlhV6MYE7kqAJS04ZZXBHjWo52GIlNAVuZ8KF8M/iXh8ked4BFNDFrJErmy1f3g42khPvbR909KPgk6oeZ4+tSBOstkQlX6Lpfvm3TpD2P5N+6YyD1dLheU3bT6yPG2kce5NccdmKoMW9W1+ibWYjdP+0sotNlvX2GK3+udNsL/r17ge09jap5RqdM4+E/tsXIfKcZ59M8MnQYEIWSEatWfozML7+to42oTrlGO2A9bIqBwUUe5ejaTBSh5LCbpLtMO9xg6Guoj2inSDa0qyq6X0stg8199P59TEw3ez/eNiRTiYOh3afP5Ht3ZYRax1aMfx1MNes+PCcrBcuwauB8Rdox4/jZlOVORmQwftrTs3cOg2rTfWO/rXugye9rnmd2rzPmf9vtU+qY82cOD0detAbNtAufzySIO9f52rHGtidKzYBpW9ZfTuvYTChYOvvnP4Atar2iW8YlBGocBDIBm8WuaqqCsyjrS5YeZsapDDoZPVoANMQ6jlrEzuvC9QgY0uhSpLeKr+5/sLMpoQ70lE6hRAc9Mu8M87BGtmPhkQD5h/gak20Yya95s77ITyJL0/luPUQ1ZyYrkMPiGxFl+Vj2aSsNDIB8JzwBq1qk/uhcwzeDFXzaf6l4Ri2ipvZuajeDCISR2gQEr1Qk4b7IqSx5Ix7OW9cjKxLIXsLVQQ5Y+2RVQVzEMCWpye+zTmwK1FGvZtFPMMioyoHdkts5wcVTTBnSWbFxxgPPfbZrJo9gXw6EI28iyIQtlCMZH+en9Eg0MmWVe/n5U9atQWTprnJf6UYFoYbkoskluyYje0KpT+04BE7t7NQhSaEIeK56iNTXWTjD8hyKq/EXldryVD7qj7LYqB8owfrbJVmmC7B6l1ZT578Gl58dsLTaIEYbAl58HGBxfwTjGct2yGxC48c4EYppuaSLeRdeezxLlSREyiNkIqBXCASzJbrnxabjqNMHD+X91sRRHnh5UFSYjZdBq/us/luVb5Dzcj0F6UZcC/H+KJ3Jg6kEAiNsGqrTYxvoNUcAXlB2n/iYemnUrdhD+kG/o6DESRqm+OfecsooT0r159FsCwoW/9GrBHeHz3yAc5rW68OuQvw63QKGqc5ntT0KEUr4ztYEc6oGUxqPkCT3kXXsyzxsry4OP9C2gnV+qcPkNiV1a63xIs1WQg3EbWkzc+mgT0r8gRD4YhgvB9sk4tIyBErBtQgLEyrR5oOjDYHqalMEhApkyH/HqnRz3aYRC7RHuCXJDvl0IJ7bxeSZYFvLMLmzEzl3nouXzx/5BTUyOmFr606wxni8zsEJElKbhtmleCiKm7C4GyYQkjGwzWdREi8sfXH7c+NW2xsnvdhD+nZoONJtGDLqNRlwuTxZ0inx5E6FXZxbRmr9oAg235XsRFpzS/6cL3zD5T3cqquprHWgqrFGtQK1SW0hL+n6XmmNTwv8ABupwg87TssHWwb2sNt07yXpS93qaMedL2ryiIl3QKrhHC75T8IbsIB+hrtbzLRIcsaX7TofsE5YFq2W4PqICurPhMH+KD7modVDnDLvXB03qP+vxnGthZ+ti11+IJw/Hcsn93abJv2ncSJy8IyxrdlaBKcF3piuSCxsy+oCnjWjMTzoG4BgqZmaSOppbwx3HBbu/i4CTd4KBqdWLb9ksR2eoJTxQi62riEo/QlDF0M6X4ULytJnPM3fyhpUiLt53QPUmEJ3YmohFxES49YwTgTZhxudZdFfF0BFDTydszs9YY5Cmb5yXRLSvNeHl/HDOMyCvZfPSdidHtWNetRVlvSVktSIN6gu7FRj2IKBVIpuVtq1aFtvJGcPojF7fBwNRqgc90Tns8I8BdNesojf/2PI87QjoF6JxXAa73GhxReWNCwauFSM+Oz5EqecktXBghyOf9QdN5jyy3sFwJPtyxD091jh7sA6m4xfkR8WpgoAqXZxJZ/jgh2OJS19UwaNJSvqut9QbnVs6o5U/vmTEjmehltp6ppQBEdW6JDLeXlNMU3CaAIKXuZ59Cgzae6HzoO67TiKtUXQG7ky9A2jcFeNEtvShZ+E2Dx/SfafmoRAwOPkEzrkr/ENAHxcGfZmqcXLt+FbdRmco66K4ABJI0mYSkS148/g6PeaCAn/PjkU7eN0ZkSb7BhpAEcWvt7ZbU1s5+dvt0tWRtGHdh9Yh3JfoYHlbLFKQW/KBKNU6RBtXAFVAwPPla+X4nw3PLwq3McegUonI7WB9LKQt6XKBlKPvMsEZu7BWE9Fa8havRT/0pSCX1Z+Yi31/RmHaiUDscn0Bzf3s6Stf9rn36DuaXwnN+u6naaaXkibkT0zzhljr34onjRJjQYxDL03wc4noS2h85NGwq9x4BspisWWmoGe7T/LblCYajj5QRDT4S/4YnzsFJiMMSiRBSBRUNwL+jz0gxKL4ubbbW5YL4TnkkN0Vpciuk0NU0fJwspvW2/1YdvhLlbTRi6rgEn3VYK2miruGZ9u9kko9vVKwmGw6XIPgixhCgZZ1Bs3BooEcjrIpMlymoRHJLhSABOx/IBK+de6q5YMiorIC1neU3EIA2zJdvvCznnyCjYhd0iUNUVUaxCwW9tMyd4N6vgzd0dnNWOdgpnEpBKhaJ4TWpq+OtI5SY8d0lQp4UVpoYHWSgoZml98Uk8rFe5S0wonZnYo+z2M/Wfen8XZZmPwvVYMZqjZ2lZkFq1sYKrw/L3i1Vz9QPpcmj/+gQMYQ9ZdSWsob+oBxiLS6oOh9nQ7xJYdjbI3//+UP6sjkPLVNpkb44yRZuOtFUeitZTeSYzYvrLL5HbgOkG8pdmNsHTrDteSADgjrGx/R2aOFDOgkS2lNZKe6ojE6IAhHiKK5mcCZEQkVcVL1zBj8LMaCZhMMPplhlhu0MZ1M77DoszlDC0HlhtPTGCIvXugfxtTiYdXVLUBxpnEiSg7/+sM9D13t3lc2ybbNXmAJuPk0kaYJeKkPWFaM+SHMoJitqssGW/zh8voyGz2a9yXSukKizhQcn0t1O3WjWRp6yMklkm6LOk1dHQneJn3hXnzvAM2nfp083IEQTRwiIrCFNhrLihUWUnDcuTw1y0KuIO7RCTVioEsix/XBXXPZhFWjiHcf3lsKqf1c2HnZyUriLUoBnMMa5moJqR0KRH3QYSareTZTmWQNXvk9SNP5GzrtCvtXQWMUTthYGFbvR4WIylh7LRQFSg8wjA0bke0qWCsaA3FQQVhvztTZ5Nh7zgHeBTjRdM/8NoLpWWeJjygYtujJzQb7dLAPGADH4zsAPnhjSu0RBxp5TKXBDFSSVBh9wzx3Ebh0O7w7veisw57llthWksgqjJmbMS9ior+mbTWhm4C7V7kcxEIS3tIpRVj1ZXt3/HwB7lrx0r5IFpD4TpEP/yi88gFH8oipG11JkA0q2/n5LvZETVYb2DX6FhOiyQK80MutpmnbReFpl7tg1+Y2n1w9UXl+icaBoKGNtqenzw5FLPfxEQ9LWgrD9liKXemFDx/QQV7Q2JUxu4x72FrxZhRdF5NSt1S9FbbGW97VvO9cUdvY2RuWy16aWU+I57eN9mT5oL3Q8KgBFo6Hh+r+oiWeoX+hbxSI+VnX4+84dOI+b+Uy93ONIebg2JiUcVbezywld221ecQSqHGk6EFM17SjnT5Kqn7AEQ7glgDZjo6OKLyMCHRICClF0AQd3JkF3WIuUxAFfAq8JWcoc4wvLjQ0Vl95yiybxGrBxjGXKLQW++pgoNrZp1pEO1dqT98AUpmhZBYCRiRHWse7rMypm0nyn/CdQLm+9NLopBjZMLT/SDpK8Q6LSKnii0Jf77SsX8q+zbas9PxNJLD3nbCyx+hZ33N021w6eGbOmKWme1a9ncVRaJxAQLOcXseiDOJArlhNAp5KUiCQkGoJNRU3wTqsVb5mSyPqTQXNN7IDLFSB/IOx0sTOLPkeAZEePBAN+97G1bVIWveBB8NC5NI4HJrWTblatWGvAXdZeVU1ScO5MKDx0IDyVVtDluy2QOGG8FuUsVLS8N6Q0LAQIyYhHW2Ck+2cPhYOE+MCrw4SaRqL6xslJUA197HjCDofJsXSEYoGovWRE55a6/8Fh8xwId6WldHK2E/qJ42WMHfHht7DXJDZ8ddCPKe5NnjTZWWhN0dOSK5gVokG6Anp4ZMX+AqIFU08QTFkrn4oTHhg/xkxzxYAhwbOkxnPHYdGa16VhOdlGaCzEu0MSU0WAe1P5Ndrto4rBF3/qoZupffSmrZwprHmfSi4PCuPZINaiQFENsaGKj009jAQVHt6vknZG2S6Q9q1ln2Dk9Wn2C91vuiHeAE7cjSCmBCm30Q478ka1HuwBeqU0VPz621HGEd4fXMvu/l8ecsuzoTiFcbf1tIZbK4lVsiP/ete7/nXPsRHT2mDLZBcFSU4U2eRBhxgC/W0w90lvbROesHGboceWcxg+wrBW3w53uMrt1cr/3xgF9c7qg32ZzXpJeD6q6wqizErSn0SVLqCrt1aOoS9gTVeM4Q5+B9lBb9vOHqdu2c2The0HmTUAELJ8hReI6MTsaOgh0Bmc9n8u0kLDw3mpLU8FyWvrHmU+5e9r+9IkB+0DITUEgiOSSnNAH4o2mctKUY4LmYgVaa2uHjvT8Pv0KmIwd39lI3woYHTMrzkjAeabMxWu1cmT4s5HL3ky7qxjeh2cx8dm1lYqYhIhuEbYlleotLXJKVOtlEdcQQ5hZUMH58zd9DpJVyb6XWOcMa8tYNOBZjussGRfTYFU8hKU9mS8UjF4VTCaKwxwzYv0dykHtjF3g5iDvZQiW1QjtC0jJZ2GhWqrizX7/pvFF0hHbrrNKiWlWHlZ6y6do2BSbzH3r2fdUyoikRlarEjPQ7VL4Pv8iXcoEZiRfEwuxfhwPyIEkwm7Cq8W8uMwXi6Ke6j4QIIfdiHd5QXl4F0wxICGdY/yzuI4eAdbmNR4JESOh04QzdhV9iTmnBSYIMPjqxs3UVhve8TqjdHoV77FIfWI3yTk1P1nW9yoNtZvo2Cip3beJqAEWH6WQ3/JBMa9LqR9PMVVbj01zHieHBt8+0Bt0q1wV7hh8IMBhx/sA2eg1zPv1vfDUWYErmrkAFVpUasGfhU2i68+JFZ2I2uD49c335ihQYzZX2q0hcrGhwfoI4X72PYAj6/njEpc/lRum2+5TAgGkjabgl3N4tkKftAuvXk+pRRzrSmoq7hZ4oi+UsWwBumP7d5fLL8lYPR7Xq4UG8/HCQ301EtWo2GA6b35p+qxRaA3J0eDwbqyB8iQLYuKguyiSBzzpU634Ls/n87xeLsIguXXX461Pa2rfPE9R1qzfB53xzxGx/PodewKCIVMReA5A5D5OnZ9YmtxyeWQZfZpVyiue+47OT3g4EAC06DU+nhL24hR14h/2/AHqZgkLs+nQgpSQpRGhSwkYq9tjVIkcdH2cNu6qAmyQozGhBSyL6vjmrkpa4w6UrybrZ1oR+0r2WLULbtUZF71ZGYR8MTwqBxZ+USkYG1OcfBFQ9B3vOgeZQH0AvXD34bX4eMMzpe9bAN7v2nlgrg7yzehCUamfwipiTsPaWbBIU+3J77Xvy2Rgik3OlVbYQvphe+CUqO53/C1AdDXAVrpGtTbO4FBKPUTf4j9270tmPfyEwy+w/bxRXVuxJV02F9jaKOOOS4zojBubW+ORio0Hu6AHfs/4pCEHu99TKG3zCGg6WxyLLodr5ol9BohFie2/MKapRUY3TaMVa72FAObHCERAQTDfvnzB7iGpD8IDUHxJTkqWgq0vAb5BX6kgI+5qqFHFPu1a/r0tbfv0uXmPlEnLkLMXC405PYAdA4TertnlRDapm++uOfTNLTjkXVqeGmTMfbOptN+9aYXVkTCnA0Kv8GvXR7hOxPsgGJugcQ7V3fveh/bfK6nXyMomD6kZC9xWzz1P+cD2v1r9DAqM2GRJRm+kyIVLcjavJu4feclIB0TW3YnFyPD75dRqQ9GyhHIY827lHjgRQFxG+k4OuHyh30g1a7l6Hvfc/u9sfhIVtfAdoVfjj64B9Znh2GuPCergs9pPuP9jRFDptlH192/PvX8iQCILMq2lONtiTamzHmfT3XmmgNeeqtpBNXH40fVLM+VAHxwkgI9bWvoH1v+wHoS76K6doKCWePxEDkSuIhoxQIYa/GtVojjrDXdSgdm+Kx3F1GxwQBdzVZKAtfUy2kxLFFD6a8/NsiO/IIOgISQa7aluk68a+lRioY3WWvE5JzAneitoAQK7mMW9rr1Sm530Y3PlPlyUXrPeZmxPbTFF2wW6rgcS3bYnwSHBL+Ey9iKwXx2xikdgfGHBVZ32CPJvy663fw+ruV0gGs5a3nl3Jm/9x9ncjmj5hXqfgYg6VvJVK1mvnMY2trdz84GzbFRwEHIygdwADc5vfgfjIGgCnMlnN74kg2d9dL+3SkH143QcLYDPBuazjaYT4DZYBpr4aZPtfayFeYydTsij4nQHTy0OS7aNjhXn4PAy/k7tu2bad8rVLmpbKzJJ1U7vvzhg/oHMceWvknjYfD+XbeXUSbgamphI/wHzBIhfJhgBpC2rBIsOdnzY6mGeeeHk8aGk32Z2bOWQtzZ/MyoJSyfLzS7fEcj4O1DClf0I9wFjPdRoJcNGoOArebAdKI+tjhNw/b3S9g4lQUh7sXh1e3+aFaqYmmTabCaRJQAEt9xvzSJXE/lsWF6Vz+CrY8HupamA+FPMnsTps/Y1LqmBMFTHBenzOTRZsw+K/fKEbE+0/Q8AY2WMYqk5iEVzI1MUB5uIKXjLKsNNbVt1bXMIX/0z3d0yDvixm0BM55YlW9yjEX7FVrVz8iz7QguOEp86Lpl77wKS/wuqbxtQ5zdY2dBe41fYW+H/dXx5oAlRh9OWk/uVu2l9m5kDZGab1bJ0cA5xEpMX3DU95mQ8KgYmauJrNsgb4aqpApXyUjmwzjMt+LCsuGXOjMt5/euWCgNTInXsc4Lk8HqpANuTndQxpigjsNytuTr1TR7cDW0BuSrbtgXIvutQ2Qtdk49omqy7YiwjBKOzRFvqJuyb2ym/giUomdE9guJauIivNWe20NMroux1TbNUZJ8XI48IC8d5QGWsp45GKuiKfPiscEaeQecEZC+p6lHNyqNJUSlsUF2+ulWiWg5pWPfSfaRkhjbq+NCziegbEWhAKH6H20WnYYUPLkn1fJLr+OLEQ0E0m/u9rAtsZoD8sBulunoE/7hy5kQ9h/zTwBGjurVMG6S2EcT5wFinxNk742h2UIkwo6vGIpsd+zJ/txUtjqfkzbcAmh6LIK4rf9JSPdrWFtGytsKdGTLjnFIHflQTTFj/TC6m09xf60QPo9xK64PAmxvIwygGIrBIOow0AASOHWHMb994qvmEHRNgYW9UA4SQpAE/aw/QAJCFN9lOhHYtjzEOiXOv2Zs1JK1UL1k5qW6AICYd6kCxA8PCxwvGyKypSyXjXgmy95ZS79AK8QJ24DqUb3xtcLFSsOqlk8H3or5E9tadedKElcv6Kye06mObqCRwAIHUT2n35Hp36mx08Kkr6NT927f03rp9nK09EU1cxkLrIAW8xulYG0UuX2Gav2uTjhw295enk9FAas/sSPdHrHzxOYlMQ6zIvno5x5yEVQWDCPZBDQGBqqKYaAb6GKvxYlAHCPwZsTJSaW5sZdNzh048Kvzp1IpyEfmzdy/Gn+9nezAYPSGyhsRL5S8P8XsD/uHXoe0MD1roGxC+wR1kSxrL8y77tZ293X0J1Wds+FY7arqI0FF9+mqXumyKVj5wSikov/BaGLfg20w/2QfbcOMmuZoytpGgfAkPgr3/Q7xW4v02RHE6ocA0HMF016c8HRxD4tPIU+qfl7fzBoUzoUvwxMI2V5CnRvOKGK5yOpau7r1n7TvMgmL3WKZd6d4j0TcPFX6TTbrQV5ojv3JpwWSdU9YLt4K8EQrOzywR/Ak5u1WEVgshrIH8pJr+rtpt4RsBpuXMDtttm2VMG5uxwdRFQwmcGqy7IMtCnAIqHr785RgUE22kwvHIV3eW8kQ2gaL3VImIG1+uPBPMs0mXeV1OhsOWRdaVgpzcFJvXFeVOc/pyt04D6SzVyAYl7paqucEjJhN6xJTU7QTn4WUaVTwzZSjE0AezYKa4e8I2tcqCcWOMu9yRriNw5Bj45OZAhdkqYPK04oEJjEc46WFTqlCysNaEidBG0aDCgpLMnjUwURRiPVktCAYhO5umf5nnDPLmr+bSz7cmtd8wBMa+XBmnhsV4HVuR1OgYw3iDnG40TetjhmJUwBQihnDKU+4OFalisNQqoDN2s9PFNAvbA1fY3d0cQiKt8IyrCBSnMgnPCmKutpl8aMUjtfOQszj00DRcAB77dte1pO7FPJJGtIkmUIrNhj2cktpFPB4EfLSDGYyc4zHIU41CRMFPLaC/L2iJClzix8gK8+oFUbbd7oTuPBCqJcd6FV3nWcY1voGPuXio7hDfsKtZapapZbekqOQiB7fPGyfXYy20hfbTGMBWW8cXw1857qOqTPC8ibmt79fcJ7Eu0DXTlCAgralMtZ3lKvgZqynjUvF32UYrjPH2562W5N5rnA2YzbX2hPpZNx+T2+7cqr1kmYTGRnPPxtLss+4cfgWkxHOkHI+xzLSMiQRPMgjuSc/8qMZqepz2qSW71ZCJFQJCSEqzaFSlWVALcB4VgeYsQsUIrVu0HduhcsvBeTPDHplUC1Tpk/nC6l+gJE5XeWLanCOneFYWGyo0ebFitP/VSdZKJV+kq+v+Idc+SwuLLuGKZltM/MZu5nvBLuginuiaP373FSzkDp9//5LMEnMU1pQIFlqlqGBZsb8Kbj21SnESTzK+Wq23ARDUb2bm1jzJ5aX3oyQGGdTX7Pz382Po3/NTvw6P7JRQ3YoOyIlFvYf8ETkBBH/LU5hmI3LaBQ+3EhnEimMKld3MVP7S2H1E8sI8xBrDl0y8ov0U0KAkcDj9obPzv5Jqybjxb0R+Xry1diIZ9fzdRK3i/FcVhCbZvUhvogPWsuAUb6eIjQI5bV+qzfqDchE78Jy5Pwblp9f8NxldM6HSDKliuUMTDy29wP28TUaCCerjROYSTM1eA7tyJF3hWbKVNWDBqBEEvs5kgdYzkz/OVHxUmb0i0H8JUFbeyPhXwmI2ykfz+gHJYZRUuSvY2lEnzKvSwbyJRPjCl/6eo4jWQuynJUXXIVR9o9In1HPL3BJHBGRAFxBUmyxEtWzHtVeqD1bbgkn3ZXs6ivkWVvn9yYVt4BXBPBlny+8KrVjn7D2Wpgh/EPDlyYRzx1te4ZSeIQ+vesW527cLCtBgTbnNgyzIa/SC/qVkSXFkfuMTkdKf1DdoOjBwKTolZ2q7CE7klpvMWpc9R8Su37QdDMDPWhLuKgDKuA57YwcD/nNfkBN4UgsCFCwWSid0hoaf36GkNvKcH99vWqOAldcNqmfjY54GSpTrMAiYq/XoO2Z8UG78FI7rhCpODrpTDXaH+nOU+XlxXPywN8oUF0hgrFSAl0E4kth7J8/bqzfU7DAVIEceD+7+jyp3em0vQhiSVebprxICiz32QMVxX/BE7Ct2CkPUrMHOoI+Ls3dR6ZMeasdOTfguChdx9XOuodnnvsTyeLp63tlKj5sw2Vis3XtsqpBXzB8xd/FBrLAJhu3cbunFeLOcbP9sBE96mKFERnVd04YI8WpjMrVNGBmTWzuMOl7HB0ZKpQDIf/rPDIrDaCC5Mv2fF8jyIUI00dPNIuiQHLJVFTKcF2VFZY3aNn9cZe5HKiatW3hB8zCpVfJKqx2xQgErWK4neFP/o3etHBDYOi49cOFrMuKzaZLyi9vWNyxlm8Qy1wYoSlKAyKQC2gDM+jPuJ3SxeF+CsTb+1hsma9//MWLQM/nmvL3IppA3zMPeSKEh5VYlGtSUxgmeJ1Hwde0gxZmSWE132fTPoeakfhEp7bmJEtLXNrV5fH+qExLiEufZz0ULh9g9mBAwTVZaeFLiZVG2I1E0YP0Z97hZ5AKQYHCuJwKMyG1jktiVL/MuVOcS/wgzkMZSxWDLkl8pAnnMXXLJm7DBRrQSWoL4Oa4hTimj3Obd/gOB24EAorOocuqVYCzOAE6s/6D9cxs5zud5/c1mFmggo7holTq8ASjYTyMB0Uv9HqC7wR94D4F/q7WQ4/op0aYNTcbH4IuKfR6kXJ6oJhwHyuWEX6DBP4PxOxSKCpr+K/inYWZ8GaBUwN7owZ0NDS4l8QXxasE66NN6ken8/m1p0et9numl8he3oABSjXf1FyOk86Eujv3+vZmXCf2cin/m9pd5pHso3UdTWMO5BunWY4Lm+Tz+ZEm/MYoTzDBzW0HP7+y+cp8/MxIcvkKPSdSkGnjKy9QNnFnSqVXF+ufVebZqUNd0ufgm+qgM1lm8E3WA/u9CH+pdtTGn3Ig0e1LFiCtC12l4pn7diFVhSuQHUGY+uVTjzPekyWHNvbpx1FWh2pzGAF3KXvsaTvdNhWa/MUaajoOqqSSeoBcimXmqLri+5NiFSuiRg2LLfiRSTjQRctaYXe4V9B7PvA8pamcCNONzio8s4WURu3+EV9g0zBF2mJMURM8VgM/62joP0nSln7WuKCHnPcQ9drPGP3ahWv98tlEaP8DS8r8YpDLy9CoCO0Z4TR3xMjoNcoJIUXUCBMjsEIiKe4mxa8HXLGF9vD2FS+xWYKcIvqhn/X9Z7Z9aGjKBH947fbNVw444GuqK/RxDPbcP+Fsu+woMbVyybX7jcCVDgzj4y4kTAxO1MACYUu7GyHMreCsu0SHTOnSSrrid8NNEyFurarbFZTzqIeyWXIDVchSecJUxZ9w0JpXq/rpJO7dO9MEJiNHhkCx1O0Sbp4f1C8a2axp3pxqdz663zozNRVFDkcFgBiZgvzz69VfX7eQHv4jzI2PZYgeeczG1rTzmX61P5by27uRqSZzDG19iuZw8JLc7x7aA3NVpvX2ct5KaYYxV6AIxwuvYrzs9xIyMdMEttEJXISgUS33Pl+ERrXsu3s72D5sPOJ7NydTIcLaDP/RXzT+SjMLr+Vn00TdU5L9km6OJ4F50yyIuceMB5AXejkGylKARmfs1zCgVQyvZe4uKHSJ7LyTxc/uuDVUSRUuxlZjF2a7dhZq6k6F+SlfuLkcbMsekTioMgScVLSTs4LEKdRnRbWhMPnxxvxqSDaEafYwJJlQD46BCv8KG60lZA0G55gUdkEIBrItmEUfWWHATB8njx0ATddGcSjN3LZvMjzTbfX8JbBI1U/pz3uMYJCRZBIr5b4WoEKUJzEmp8N0BK6DXKrw3gGukoB1bH+zgMB+HW+Xhcv89Nw61YqIPx7+2TlrY+MUOBgBJg+E9QvWTCuYznGzOB8tG01MQZGQdWhoE5p4SdnMlRQ7Xdr8sP6JzDhy8MD6o/cpotX/Abjllpj3dvJO+rd1tTtPURfZtZPFdwxDa0sGL0VbMPIczMFQvHU4H1pPZw9n4y2TedBG7mlqeY+0C9izYsrbTplXR/GffeQ8nzf2vevwg8aZXxq5OKRvUvmThKypinoLgeqFHMrBPMqP1CFMXKLT93BegYrR5ITGq9oQhuxWntioTbiZQh9374bGffh6IlqkTsI/a10XBhJ/Wey+Cp/FYfWIOBf7e/AoKly1Bm+parlnI6rfXkMqxhHNAOlRUwyERQHUhwCVdcZRC3xFODSpJFSiJpCYD3zcJ31MlKtq7G+m9Yrb2afAzh0ldUeTp/upz2/sE/lG3MH+zXKQoT0gb1niP68t5VMh5wO95nUea2vEfwcPaGJMfYr6TM2vFt9pV9eX18Dj3rEbJKrdw9LSXxTpEZHCFbFQSC0zu600g9AJHTP0HcztrkM19rrbvfdZ4oV+21LOS4sZcodYeBzTvTcfS54GChSswvISb0gkRut4iYaXpiERAitNyT1Ff2NPZCfmImM57vRUaJdoma7EDLnO4RZEtlpnj4QJpV2zi9zSvMvqWw/BMVFu1Q7HqykmznZF7h9rzH9JKA9K55VpKFRFM5IhkKh7htSvZQJMCYpxYrqQMHK2WEBBJe/xiIEpjYplKw8tgEZa7btng5R6aN7rXp1i2xZdtaNZuekWXltN08CruI89vfEoF+Uu7mLIb8uEyxy/oeTQDnrxfzvpbI/PIJDRrfvyamTNVisJXuGHdCNUB25uN+7A5iswWg+BPzDQ2h9/u+K6uo2j9FT/t1IFF50WaVKVm2AydlJGtmx8kNs4TI80sqxtdDRl7w5Ek9djb3vWslx25urfHGV03jolADQW4zGSEU3FE9rKnqqQ/u5EZrn5BvF+MGBhoRbz7Su0yQCPcFHRfJLQwMcb0KwJn9lHpFBuUyprimAThUYJTrlKrXwv+hIRe8ZGbVNcT4ntTS2cBgiGvPoV/U1prh1GsyRpvEiNexZhwBM/DEAi4cvmZqt/RGiQHmyHi0JlOl7YmuQaRwfDoN5Zoz7Bhlk6PktJ1YfEdz+AC1ANgfGl5O8uu/Qg4vdoNVat42KRP3Z1koauYQKQB3y9Lzb1q1TQ1kfGn0B/H6PEuoFQGOri5d+YxKnsqqL5FrVlbdDt7Q392X7HSc4szh2uPhAb/Qqf78754y6NaL2OlmJJcnJTjqLCLLhjrxG6vgdPqsZakH87mTUjq6bHfgLExwWuDh2hzidZS6qexd1hI3wdCqjE2Jg1Uahzgfy4Gp8KFVoRUzQltNHiuswm+qwOlGo1PDVpnAVVhRRNiWWUNqknIbRu7NXb6RmMVeveZFFAgglIrEqnnWng/C6xb4uOKI39uYrhxQAeVli4nszNWZhpQroQjixtJV4kBIO1NjAZusJtBMHdl50vg4XdHoQuYaJOqQ8TplrWP7G4EbkhYO1mRHYEcvVdHF+J6UrZvxmDvWWFj15yRUCiP7kxcYkUio8GTwG3MOsQb2oyDW3ZvuikoOIfQupR6SRK79ArnvZA1ugPEn87iFBeMPD7yoqAVALJr7Mb4ZZ7fSKIHhfETw53Xxj5xcl4c9vQnBx2EhFH0kY5inTYC6GJWt4UruITNGm2wiVRDpX2mzhmQdKlmWJYgnqh9EaMF0r8haBkV3VdXMQWDbqBUZ5hHyqX+xI8iFyA0mJcAiq2WxsBhCEr7EbmVf9VK7ZVofD8lhN2zYGwC2mHpMeDyPbPhRFcZzLsrBp1Cy2ka8uOc8ggP4i8DzU9RTTdfZ96IcpOY9EYRWX/RhA/h/FF214BoB+DZNQO23ES9hsBITpqAVJ6JVzy5NTjZvPgq++tGKT06uOMt9vKoc2ztLZHpvRAFX0zedLTw/S5U0keHRiMQzgrSZlToA3ggLY0VTcbULYzWf3imfV1c/apAYreB1ny58ZytfWblfz1CtI6WSpi3UaEkZ2fzhXdZkpKWgnxmJ6n3fyRZjyJsfftynGilVB8MmrM+SV/p4UNkJYZM9Tz7o41x88RBQlhDgCBC6sSCQGk3PLPnNlWSTHWkKgyT8MaGyHBV2ZIdLGDtzgsQQ1I+O/Sf+4kbHtzPO37Vv5UwmVgrvkNTlb7kqG23vdmsuQvJYOT2b6agBj7CEd2EQGvD6/UAqSHNhInMbMhLWvKl0yqNUcqJFoep51qG6pHYCTiHM/liKnqGmaeWkmVuFTBdFhgiUxm5z26na/WXNZ/A+SrYlNelSo87FPEYkISg3vIQoDzn0I5FHHhxMpcDO4q2gFW6LnBk3OdjXQBVzrVjBG3s85hp7b8v8pz2oaBVpBkAaD5w444OYkxO3Sz7CTDTg+yJSJRoTveP1HicOaKoA3QmSsBc937Pu1tH/fsQ2VEZ2pHj32U6CrnpEvcuO/C4oiKdx8pZnJr2uP+PDhHSH3L8rodwkOYLnVoQyEkIl6nGQGuNbC2Ofk0dEL0jsXEAmtxwGd//2f4uhQ8lgxyyIVmQyZDk0kqGWu8/LnmzWqVKy++hbeaYsf/+IMxVRFubEom0tBdM2I30cPXFKXKPDVKJCKlDQbNV92uRTOcO1ZN/7kNaVIZOICMKcJ78yyJxnH6a9x/0C5pYLtMKni8y6cKZ3sSHfscQl+fQ+HrOemCeqJnyd+c5Y/R/Xxz5FdTguyaqwpOk6zmq5OhNULT3C/j12n1XS0e3SsVxs7r6L1ar7T6v9zcGGfO5JKupP+rZ3AG8+29WjcUNzBdquXoO3wdU/C6rp4CErHyoSNcwNZwu/uKy3h/u8dOT/+f10CGvfKSxlRIItptW8WSXkzbs/NEBMSTqc4+E+VzzPXi63RryZYzk+T3SppConOxSBZiU+sANYT0WL52iWTlS+M85iNtZZjr0jvCoi4DVaPhFu15dnJAnkbtxq+3pL36Hdbc95+K/modv/jqcHOAZHO7dJSriGlhDAfsumAMRRtDksZ6bWGP7nE/8rjixJ36+YmVdxt8O5a89YJ0N8aGaVFcQD+bqHI/aOl/fQpx/VR76/Nlqvam2UkP4F7/quVa2LxerZ6uMuBtTM80H9i2b/Gc1iQHrl0PC7JvgN+apPKAnC+PvzTMI0JJyuvHiOnXEniHoQhuFnDNzp/mfn8791ray3dHaQKCw2551ECoB5eh65btgdtdJskm/WtJCj7mG1s9zoo+YGzTCzCT489hLx/vVpcEi2X8ezpsl1p/Nj07z98RHJuNnc36KI1WujzxCCmWBkt+I2C4yqJn5GJGxhDpCIBrAfLFyQnJhNof0DoM8TH33NgvB081XF3qo1ZEpz/5bnc4MliQWADMVuZ3bskbDET3+lW+3lUrPE5uia4Hg+gQYi1sVosDEMjQTB+ivfbgmmOhrkGU3FLErbhrlcjJeMJO3eZyDWsrl7wA1CpGaxP9hk2gG/pNYhvj6RUaZRybuLaEhM0W0aWLj2xlx8zyvXZmChl8fj/SexkAH/sQ8yxyv5xqxNQMH8Dw0CIdfhG/9R89zWhVPiYEbI6G6oVewQ3dQomlvGieR3BBl+BPJvS3k/7XfMmU+okJ1HWEgERxgIPmNATTdMI6OPm72qqSZkBoowsn2EsYmY2wOdZ5en5TlTf/I0nIXBh9Z4H7KasZdzi920n72I6cWO+aU0GZT7Tzwfv/OT2SY9/P3TndwWcPuePMIZzMkgVIOW7qQi3cpS2nBxI7jZJg2SW4Av0qZgWBddRP5AMGp2iOsQzrjNlekaNHYLUgoBiK5sfw2J2lpIdQZBG1j8xEB+2DKpdI01afeNrNwGDNFQO+L+eXR3eDwe+67gw4WzTAVLGaIPHL164ezKvVf/lnciAxmiZcwZA6aUBQIh7Ei5C6mCSfnJerViGSeXFD+MGBzdmXQ7Lm6YYR2MhLICBoM6PRNGI5JNeJm18oTOCWkpEiohZCUf2BjRMJgqN/KIrv4b3+3wcKbNNCy0XHKYJM0XLj91xXSxnDzzpGofcKOrzvdILIV7ERrGfiLJtWeHGbu67FLoxnyfV7W2XMK6jI6ELsVRT9KIXgQhZSzozXJb4vO38nTo6+N5hdIs33t2LlK9ZejndowWnHqiFjBJlNPd1D7C43upWvUlIj6T3R7ds/ems8V2Vh+LBi++rHG5JE2my5lo3iCdKvgvGtten/DXX1ee53nBFu+Wdy5C8gEuKR5eDC6wnKtdevpjH1faEm6GcWuxVarvlRPHBAS7XNfloweHUifcmxyheRlrz/y8btTBMGJ7lItXnSLM+/cvcWGN23qs/uXcVA7SWG8ZL7Jakx7N+0Cu9TmipLdlQKTfi+i1iJ1CMg3wLKchi2/uFRH8+ti0rbP2iqauMQnS/Q2D2C8YK7NDefbv+Jo3GnewIYSGiHpJsm1ia+L9u7IYHmep6u8q36OAAQDrtFkMaJxCsrrs2yKiNbdrQKk5mvtg9Xs7m4kYCDpLh90eDj7hU6l8gfKxPLckdUkXxdG3vilYEb414Ns/mIkhTf1gOXHVP+ZYo8FlnWSGh3bRi8oLUvor67xar66BF1Xx0JfkLT3/f9wwo3CBj20YHcPzZZXLbM6VZd5B6tYj45MUGLwXIz9od+AFE+3YixNMEKOtx53dZ2LYabt4j7Z5z2qaDTvbc0YP/tmIQnLzgd8Xi0Nr68Pv9j7zmCDshpPiynZY1XRa2llf8duVvMVZEVdbh3iHa8HHP3VMmvs4znL7ueqKT4EYA02xlUTsmLv2odOvq1YvrEAyuqYBEf0e2Bm4pGePwXL5Md7BO1fLYXrFZdNPFBIfFJnwIGlprBf9q0aeHuE4dJVtxuZlE4N45n3GBH/g9+U8tifsvRxLhpBQtkZBCokD5NhoCmiHaDGwBS/9W7dECSwE39aTSmQk3d9fgRH2X5UzMNo5sAQFpByWDnfP8W47tlK/jb6v6FGQR22lZ91rGPEOVx++yuBwZ4BtKvmPUO0by8HZf4ioRBeFc2hDGSbNXIekbbGl9uEIJzGoG+K0Jo2vp6QpNO7ev8KeV73xThYcPMNQr5B5o66tyPohEBP5bSPvEHGrn9zYzXlkBSYq8pitdjyD6mJ+E2dD52IbyPYb+A1XEaQBhoq0+ZZdZftcpBfW56ZR2Hx2c0pdWezWfcraZaP7ydJb1ov2511r3Wa7qe5tWjM0gp00L4Uv9E+3jNhZMogdUlO0S0rdT/+Hi//WoUH9XT30CLq57g99/JkN5iLV02sZdvvxi7ylw8zYQsmyLbLRY1HRNPcAk87GJox16FKKKGqYcfrpIbyG2Rdtb7r83BziOJDiw93uU8+oBQlubJ0HQ5+yUzmWVoph/0mzT4mTzwqGp9wH6T5uRnYn69FTAL3daLuPLSH8xdw4G8Xyrt/CxL2Fiw8k9qRGrEaPPVQ6x0Y/+6suQDJOIejd/rPiJsvvpNzKe3cSvQB0ctq83pMVvSAJTYDf3ZpEzlY/zzTNn/dxWSVkbGqns/CwcjLB1wzU2qyr3Sv4oJV/5Fe5zJPsWEsxJ59w/VWu2Y2Ac7dpO58sqGmXVF9YOpZlMFU5ecfZsKYZLpdH503tjqo9MnAmHKvwD1QvZ1Zpxj5cZnUWv/3Uz63hdGLsucgg+NvXHepJ4+1BQ1zXPF4x8pophSjIFzi4eMGQI9CXG5NK5xemOnofVgmiqYph0ZBuL5LGr9UiKbjGSmDORPM6+LkgjGzzNMirtTrlT5eIK2dyWUvdtIFjwBZEpIYZ3ay3ZPgy8BMcpFWkzTdImW5ESCpldLjA8dV/nzhdznz5WGJLLFxO1UvkSRTlb7/UJrnNZ08izmUEW8OAQ64ZP6S9mR6XOGtWLwuSKd3qmaizHMUq0N/xiSt+PUtL45J9SrlU23YmOilYEfABwNrkJVbphTCyNRaAbN4WSd9sPf87M1OMF1drsrIj/Zj5gsokesEK8MPIaH9Zz1eFmvIdp9imUPA8YhOt8oMz0J02eOdcuUnn/QKqsQ9I2y/NKZGvXv+YXV9ujsg0HV3k8saJ7aGHzSmLy+ZBxjBFX/e52aK2QezZwTuxTnDPBWIrkb8Q1iBD+5neS15gqIpQPmuaHDpVf6Z7Bhyr/4aNG9EUdZVm7a/GK1TJOyVLp8C93ZVjs9MyGpcNDVLCs7ZeKPj3P2gH3FGd8u2LGGtTFqCg8id969Z4SsUYdKuqGp28KCFVDha0xMbtWzz2h+/fl/fMCWXKNwXwg2w4zJ3A1q5p1tmK5aJF08iSmZzftuO+Q32znR2/ZpCgYhx24wR+eNAmMEl7BQ+viHf/uRpxP1IxcBQkrqtYFnXcLoqEskgq0FzT9BvbVcD462R+4CUZORKvKbLf9o//yO9RilUcUTTkNMzP0VxjD2x1+uPVLW+yW1QBQjjz+oTFo/6mpxiBAg8Uzfjsn3sJQzWnV3s1ua8bK5Kqpmq3h4kNMfmAoNo19H7MsW2Xql2oq5MTTNm/RTJ552ene3MgqYU9VVxKjeFCcC+rCGn3ZxrnhkxFuXrLlMboQWPYKaot0Tc5AQiACMGIGTJAS1HJKTMKHIIYiSqF99b0qZVkiNq+nd7oKLSTEK1cPm5qYf1IwlXlHveJLhb7xqS6nah8MHWCiSlPFQvyA75t35gMwgoXCAyRAJSc/SdSdsoXqIk4ECJPPXLKflM7AzhL9HJFV/YSP+HmdshEQ2gMORDL+Xfg3q+e5Yk73UJqwACL2AxEjPfb2UwFjzHhlbGkdxZTn3AUhn9LZwZufidsJidL3kmbjSEsTfWlms/yJ/WUjE0yTWYs9KAUQK/7fYfnDsAXciZb5WpUPO93ckHYIyV7DXuuwOsZPuzJauiG3KtF493u0bTcCmvzegHoo2L+OnbbyijkJXnJ1UPMzW1XLGz6Ap7lR/QGkvuPJLeNoMhNA3A4cTZ5y7NArKtgSOL31rOSt6KZzHeXpSYu1QDMmHKSesD2dDBXun/m6eeCPexU5pkxRoG767MWVc4LsHs30WUyYCURRXggxNr6TNJJ0FQ0i2GH/gTD3wS/OOePRt32722plqEd6G2fXYnza3IQa2Unh705PtuV/hn8TF+4S3hyz+4kUlTeFCJD6fhxEOx5h932E1MYJnbYHmScUfZOgXudMYqVOwD27MZ98RPgHm03mv3hVHlrlkGJF5KENDPCMdQIVwoY9HWNzJHOcczp3x7oJj1rA0Rtic8ClEY81ydszSmqvg01MS66uwoIKg84Mq8ruvi1yYAI6VayRl3ay+G4iGmCjjhntAKB5IRZVaJKyE657bjY5XaqfjtAlsZjJwX2W12Npfg7diyDHna/b5SxX3EqMDGEy9w+igSuO/cA51tm1hVZej7+RthlwW+zEaBMO0Tu0DaPlchvMAN1l4gFpHeRzir0OOR1xGmQKPjgcS6xJS2pV7cYLuWLBT9p3WQMhfgSsMGXXnzGHU/QG51cND7yoBe2/yKOMrwOSAk99s8BaykI4p6dfS1hvOG3PvnLHxbkyn9JvCeLy5/3/4d/bfpuYy97w4y7n+OGtnX/rCHBz5Db/2EcaWvnP+SFg8OGveRi+zhP67fegHxyEOTGRHOx4gZO0zcWs3Mt6Yx24VOGA8qzkr3kfvgxSXBlXxYeV0QJAeAVSDb2YPTU2/1uF3g6T+D7d1V5QqflsqCE2AscRKVN8lGun1L9z3F2xL7hfCfv4Ltlj89kKWtsfBJc9KSAR3O9HdLj6zdKPVz/fDxl7ER0G3x7N2iLztC8uLZ3uV2pY37ve94cYYrJ8UZsUCLqstj8m2uiSclldmIduPmuCOZb6rZeqEnZ4xQadrjN+58Odeh8vkFF5RybX+Tvmpk57o8bJyCzGdj9G4Tul0mJUgHp8n6fP45i9RS/UJtEUIKXytITylF2tjepE2ohdqqZ+OtnsdSyJ+/nrtE/g0Dauvsp+XHfPJCTkRVVtgGNMbaNLvQ5NusBM2YVH0xmrKJZcAXAru1YZnlGLXuFICkdZ/fC16IPFm8kAZ5m07QPMD2SSczzinfn1AGGfO6fnDcOG0PZOgP4zb0ziMKiJzHs3hKI5pn8ySRFtdhHpfFzCufnxiyXXVKI2f5X/MYv2Z/Vp8VySI1Zs9y+gMjC4cajL0Z7oqrlc7R7m18ThNDaKKX7zU4MxG3H+Xt7+60naJ0WXXOdGhNh/1ZSDY83DnM68UlAo+1HaLz2Qx4L3nQcZWJ8Th7hgeQKcIJknMtx3FbZvr+JvQdTUilYc3/u2jEhbhUee3AGu/BHeiOtc/v3m2V5sKlk2cPzmO1pu4WJu+6CL0zFk04E2hkLAmRCtJbH7I2thS0xYq6PX2yH6q41sfepO9jy8ireO0NDG4Sw/pfQzUlhpMy3ezrbt+n6FSIh+maaOx/RgCqrnFq6siVifX4NkfdIwgMad9p607lZWwaABoZRjGa22vLPFoGR+Rl405SjEMUujSChha189rwz+gat6GbHzENjtML+ZnuemPu958oOqN3ovR1z9XUvutsZWqk7uCVUhaB4QOhehrFTMwaSyt3oqjnTY7692+Guui64urSnokydEDEYce3Yq+MbvFSUogku04N1LAxaQGJizs6cAigdxba44YrtjxO55xflBva8clpasH9tuzkXLI59jWSC96u5inEF/ojPuIbcDiMOyL1pw+VkMssKrbhr5eWtJxp4/Rn3U8vJudXvnw0ARqR2K3a5/q7HiH7TA5v9YL0eUOTlhCnaBQ7MeXLBSvH25TSn9zILvMV37j2nFDbrVQhWq+ylZ56S8zjyMS2Im32XWrMMG+nOxL/NdkhFmLqXF8p5FQx5N4VzTYQgifjH0UkJOMR/Pf6Gsbp5+sPedbKWJN9MYG110jj7BXvMBy/oHJFSdhK9yJjEcW7tSDPV4AsQ9KYGDx/G8FAXlZ0bgYnBBHMMARiFBd6qQDCvbINx98bvRAx0gcWAClPOTRRF6Ps6uou+iKoIynCdvkqyGoMCGOKAzDygTjdn2C9JMyIiqLMe2FBVCugiqSsBvkzirhstaN08oQXyFFDvFhsv4f5v+ex2TWV5VNmW4B5g16Phz/LXSEAE7b+LGzmbSgJAdaaJ2ryuny+iwgSUCSn52t2v2+Q3Yo2+aK8gSN5k4V50h8jk0p4bQqOXSp8KebEbqBMwPQO0MAE3VMqrDCXR8utfC/Ge1ozpUuU25tQP4laQ4fSeaKnANM4japEEvM8061+u3LbsuujqXaE5h4BCUWHCcRiFhVqRphWXJW5AsEjNPbOzJZwps6jtYFi9Gw8XT+reHzRKMmRReHFz97Zd/rS5lza2sj29np6QOsQ0MnNBkf9ZiNl3e0jHsiljhEPNWGSkfbawh0wbK9Rl85yh4YnlZKGucEaKACMlLc/Le35bW7+t3KFQu6OYEfI47S6u2hj7/gHIseHRfmDx/KWd7VBFxiC50FgK1f21VKT2+5pXTb9tbR6aW+tswgB/IXe/JYRQYcI1ZRFvqYBVyfG3Zj3PgSEZsEUl6NK/rcORyXogKOalq5zb98wASHN8lZJfPIvrSAX0Lgx4y72Z4+uc6iJtR5VgrgdTy9T8MpnKdCscAjR/nFwPbUbT4LTwz2y8YScQwxDPGSDAOnnFYmRj5gVgnhAdwgm39Z5o+IgfGpM8xO6Z0GwugmzIp23oZzfAKHeRhHWIQk5HhU+0XaITQQnwUrxwNJcOhr49JcGDILd4pjaxd5rpOejPcFsbd7f9+CzMLPfXGpjg2y43gvvJlZnPVEhfn9JqY/pLn8q9xSI/LU2xFR9wm7j5quluUjobcWPyZiI1r8+zgtACqF7LKCuwxK77BB4Z1ukHvzjucP7b5aqrUaCVkF1GoibJYK6AxoleKNa7eUIYVMkkNBiHw4T0/yfFq+W+k3c87kTKCEKOAYUTNRGqPqz1QmzAFhkAkkg9GvlnfxNAwf76L0h7LYMd3GiVuzG1jLg/qdVzhj3skvuVvjDGEmWtUzs+sHJRM4ijHg2bSH/MA6lVIeVink6Sq5PEO+Zxvt1tMeN7vXHnASgikb+hyzC77V/NaUNBjFF4qlXOHguxKLS18UOlm640OK/kAYjeYfluZI0TCfWxuALldsjgGAFmZyeMRo0P0Soas9xwsAN8SgpZ2K6D06obRFw/YiR6PWtlNtCbGEX4Iv4ZZgS1rlfqWMystw1vbk+6dQyOOjrVP4GUwx0kwXQ82u4uLs1uZCFzehibhJTdiNa1ZxD2XXiAJxwRvNqz88Jaba1Yj8czO5t/AcpJa0CUCjMkqV0z4WRcs25ibR4kk9BhFgkVnulsYCl2y6ErEqRvfdvlFp07Jx3bL0yeUWoDkuY2/3Ncr6aJ+10zuHomcK3Uk0ka4ZcX2ZW2I4AF9nXRS9XzA/HrKNF7+pi73luOnxlBWxynVHUgI71MPYwDlbQTDUsTcEbfgVLjrgAjpdYVmfPGUD1Sv1zZsV7Y/osNV53LEnDH+9tJe2MQU3tuiErBaIYNtkl7Iu2clnPi/OEbdl9O7pjBGVW99ubD2RQO3p9HxUxstsFEj50EsVI8qy09uopO4cJ9YG68x2/qR5qlZwhMvayv0//veaw2o2WkX6CJ551rAvZFXzxQuG3elCIBMULAvSoDXGMv/hJgzXaeJYAFtQ6VZK3jRtkg5JIBtz+Gv/cdp07iSetqhdM3ed8aEXOu1GTCBXwDjOH6JIJ3slkNLN7H4CX3hTefbdUHdn9Zpl3SNjP0/oltfxLGFSSUbcIOQk8PGojPIfDghrGCwns0PycNkJRePC+JZMQGJiWBEQHYWoHQlWuw8BaWcy7nH4V1W8L1u5nGTSPOsGwdy7/hksS/WdlobzuAgLKC2TjQ6uo9GT91rMToKv3ZnhxxxW6avnZanOY4WADg+e4dsesFGguGzJsbusGG5BbACeVxbh0OIE3FnlYdwEI7tkf3wzm57WVw7YKfvBVM0o+gI2alJAkO+AZnnORqsjYWLJVy5DmmMWrPv9bneUjnm6Nxab9oaI9gqJcSivdLPauocfUtO6hwCHgV6oDbZhpi8LxxMoUbc7PfnrURQ8P5KMnfuSRF+VyLRSFtqltv/Nrby0zlIgXke1xNz5kWva40BiBlIa1jwoUzsx/dvmdPznVnclsZRgNA6M717u6KY2Br8UNqlKQcobTVNK/9JuWzWak0JNdVDAXoPzX5caqbGlyznYMxiL86EG/1LcEZCFe3HK0fAWBpmHqCN5buk/P997bAyo3F5wrms3WsuVa5bnSM++NCg8eiZnpLwBeH4qG3sXO3G+UmIcVxZWqW3iHx7Q1ZZLcqR3gcxfHW4J4vnv75kOzBNvtfhFTdoiDHDJJJu+f0H1mxNCgPquYiqNx4L40iasQWQabFsopcdOKgcI7sGAmrJZw8dFirH/2rIFH6BoxTue/zw1yE+bBq6LGUE1ndjaFUXdXnef/tRktADWPeATAPJFHRMudPN81u3kAT697zxO7Zz6d22430rzSv1WxRn1IxlbmDJ/YP9RwihgvQPQQy8vOLx4NuUEv6x9SPUr4m0toCKURiUmxSBmn9BJQ9fD3SEqWJFs8bdAA40SlRBTJ2zLU8qx6ocxh0MMdrLpuHL31bncs5lKSakljXG4vdBcj268Ngqllq7QGuKXjds1HElznwIz7HVvy4t/9Nn8Mt6eN+ywg6Vrr1L6p45wy99JUku0/ioF5+JOG1z/6ipyEHhemov9i+NxsUjKsBkf2kXJK0B3jCh7SXfr7rfrmX3CiXWdDe9QRyX61I2SnfFdAJXVUXGBT8TfkdBOSlcJfrdGlnyii5OowhpyjvGZ8lpXgDzfGUmE9vmJliqhdDB3+hL2nle3wjr3ZwF1QfqqIlLnhisv0UkoKvGQ3a+hqR0FdIinhS/HZGi/t7Pf57nIWYXV32anzJP9Y51A5uQkNLWp5xtTgdtv8W8dEx8Qd/C/3hN1axawyvYmCDrO5FSsUznOETVBoPfoNt8o6te1XIK2qfbkD0NHQpsa+7M0RCIYAWyLswehD0NudrDSnWZHzM30jc8KDC4fEyNhrSeFuCaizJNykld9TBt7KvpyOOx4FOyRdFnvWfHex7HmjIg4otsYNOE8iU9JiA2MXwZqYlhG3pjNZ/Uig4mEuyxoEl4tyBKVrAIxdCO/tcfOYSvynldW2cBhhZ6EqxMmk46efEFYVy0uz6K8OsnNp3DbUYhZLNnTyPUT4uaA+8uALoYXZ9iUSwWryinxJUUyuBcF22al2nnGQ51ZhYiUSoB2V2OwQHYfRaKeaA+Zc1yVqHh98JHpm2PGzT545ZWVkO1br2+MYE5ZfScAf32gDOpwezJnj79l8ckIwsdUZz1JqvUNy/ZbMox8Fwxj4+dBA6XHENfM28HOmzkzs1Ola5yiDWxHOD4FOJG3Dh4X3pNAjeKd8xbk/6dpYKN2IC1xuvhApe1RHDCiUeXUwxbNmOE6Z22nXDyg1PnCDpWVR1wq0SbGT9uVESfPA8MUErGEJkHyjgS4DxqQS6fifCmyNGaw8xnM8flDQnfVxd1R+3ymgPLoBIQyr1UmuP2G6KJaLK2ltXx5vaiMzB5vXmiTylCSYRVp3wb7Bu4zzm+CTWsmLPScG2CBrgUrzFwH47c+KK1TPThJdlKQD1xG7Czs5SE4xZxOoJMAmfLGu9aEPiXvUDJNWQ8815bTGHQtx+8Nxj2EBSYXdUGIqliDK/vJhwFnDcRp0sQqMp97qiGkQSCesC4Xw6137DuaNZW/csbitv+d48s3+xru6AZytvHWJ96eCJk+nHOt5NM0v7ly65Pjo/MDDg3/w3l1RCgtZT1LlzAS+KuHfHGfufWocbU3QVNBSG8vcpkONc4mKj6E7ZHt3TkZm09IfCYn32nXcGu1tecIaz3xwL13y87HB42XUvOa2MUkhBUmoFoDTqTlL/cvAXFqlgOwT+WGUWVcm5LhOgRtUhFdOroUEz1SOeAyofnpkzG+TNJGRfJ23m4KorRXK1RNl201m/T7/lTupXOdso41lfR+uJYloxn1Q7uhgtWgpGHxeEYi8mQ9kOlCJKd080WJWO/P5Y0APW0vQ6sb3JYgmPnEb5trq4yIR0kyHd3Ew8xuDnS7/iLSoBQiFk8d3X7pWxuAmraTodUFLksAzCbtheaUCj3OEKATKUt58DNiqr9/vVQMYYt76qNKf0De/ytRrI9OKm8NWnpNS2vevIvuIW6+Jx+WLbyXidyGIcNoWiNDqwqqxQ1g/VU9JbXJSu8FZCqyZu+vn90UUe76G0+DMghY1PyXuj3f2oC7Izw+m3FXsgtP61qYMUnLMRQdJdzn+Zfa/y9s/ieL/qDy1RWJ8EJd3gMD6UQ4gDfR35oU/EuMI/0OD+qgWwETdGk0XUrp6AyUn/nL99BxxnC858X3WmBG9DDwFTuddq0d2Ry+37gooSoCNa/Wm6jDi1+NT9wlH5IkN5THfTJO69LQEmTYxhjmWZ3ALC+sGN2lzj1FqcdQist838JlD643ieOBS7JJX8IF3+4CN1lQqIlGOU+17XVh3IbwckROJMlyHT0U2tBVZ8mnHRulag+rO24iaOMusFEOGMSQYXI2KsgQ06At+kYyig9cq30URjsbLVlvbJDXvlJKlpuROvHQEbcAGFA0ovAp8edLa5saSv7j4OezT0mgHUGHyvbvWzpDV27EHgLyJDZPPFmdiOZG+ViTDr0vbZ0gv9iCsFcc9iT2X/T/u2zjLvwW/t2TOW3RyqaI70Bp5iLU5kIQGsYZFwzmPOTxHVMAFlsd4eVWJecuua6xdZ26B/k6iigCxkGVJ6NCKvB83FQJpKB3/J1s8KY1Ln7Qo9jJpAE3iafjZYOWwi7xFn7KjNkuoHpSyI3BIaaqxW66ueBFtFjY2Jv9UcvG40f8uiE2DbIadlv7c2KtQ9dq2vZBA6d94dMw4tNEc90PI8E4RZNJ7ZxwOGrJryiVZYJ/H1tIrLamUtHJUBHWa7s/O2WzmuXdW06QC+616T+DnsnTpaeEvPPel5duAG0AK0fF38LAxh9vrJLs0UBPLWa2peRaTB+ucy8XfW2uBW/MDvZ1fDrmryfj2urrL8sVY34C3up7Z0fyMrDbP+RAiJULttoGWzD4uXvc1bytHBd2Ar7O+pMJioTRxXUFFT66qsMUnuU7CbZcFNhJGrfsmPl/QnReng9atNvkbXeSaUYv3PzpxJ1Ri/33Q6kftfDZG1j//DOg99funreOoe+pw8VSN499vsqDKsj20RQNdChWsNrQJoKo2MGqCCD4nzqsHbzSm5wN6oBkyA6gytPu4pQ7q+f8SqI7NR69x3BFpZfkmUDR//dRy98e5v7hF4+CNEi0XCwD1QUuU53ED77n3J8bFkjizxWc0oIRc51Im8le1IljFoUSCB6BguvVAfbosE8UHfXJokQlJdi3S5Gh72AFGgi1dvjF34IeSzw9yRUKpydPlunpb8cNQR7wJH/EgbLPNXi5ZobZL37ePeS6BcV0tDgdM+igW9nlwwhOA+2kdGq3c3S0D9pST1IOX1ODu1HTbxsnzNWll8EgIk0c46p/frBSSS3McMUwVRILMnbhsMSM7faE3Aitk53IbO63Yjt+0It23VDIe4y/MpQN0LSyU3zd5TbL9QPOlMlJlo3VTx3+M5TkU0WqV212e2dbALoRLfYkNh2iNA/ChDqIgsoIqnl2hNc56gXOiMJMKUgpSFlDdCOstcY3Fmf5tCTcEGxUXT0LUNvmB9sbufMVdGPyvePGH81Zfu3OOcrL4Zrgpv5wrpE1z92WGTf+fFXR/XsV/qBKJFViGVN94FPCEP48Y8A0phC7mGdNaBcNCivi5s3rFuCdGoGMFd1Ew2p/V6paGIKQ0jaoZt/kaUwSmczexp8e5m4bYgne/jEdqfUZTvsueLrlxXC8GibDt18M+vJ9Fsp4V1rjfg/aG90/Xj4JZijyXxHDF+1ohdfUGa+8OuWoeGY+ZsLjDmYoxK77hTmEj12bTkrsfXJN+IU7uA6YyfVaq/QqdqH1yXuHqiQZV8VeTwntH2B4mvY+hCpjmylrMXVpXsL/RutiKMUbQVmfzBNZpoWnvO1hwtfNvPMUu1IvzF/qF4InT/J1X3Ye0k8Jge1deafrQSo0B7Ct0ilgGetQrrnQCBFpbXrDwtTJMtZc9cC64C7HooI/1BeJknOIxRDTEN+UijAnUwiXnYXZk0CNnCalx8KqSUaOIPlu0yJedMKIKwenwxBXaHIZYi94saIraIEz/aEf74OkhXeUTi9dutUQUxHPBJUoREKhZwTkBFU+snbo3TktlDFx0y9bMbzkL6GqTgmb8k8yumN6cFm/Oi6e+hXGXVjCr9jfMDS7coiUyfdJ4cOE/lc1j7nd/iNd2W9s/KeEhLcLv4V9RdVFXeeFxxz3wTgU0OJ9THzuwM212SMTzqVxkKkvAHGaAgFY7s3QLmfJB0VPxaJisOqYqBqm9ap2MTJir0KsRH2yD11nC1B46YV7dx428nTPKnGEBWyURDM5chq0Zuo+xHrCPymciJpyJaatWMq9GalEpKy58wHOY1zp4ZI7s/sbF3zeqx6W84ekStQ6/4ut+a1asOi9qG7zi8DQSclv1Bv+wJUteh2ODQJi+bV23+P7Vi+34t27wuWh6WtOoO/O3VSb58nF4EHPST2nwx2J7suNcdDazHBfFmedDjK6r9B7mEMivNPa9wn0PUwVJ3QQiPTfDlPgpAmX/EtZMDw+sKAkVcsoc0RlaBzgSNe0oG984KQ8ONowCl3hhL7fjt6dMaYe6YRvOcCbGHAF6JiN9KsMMRtQL0nMswMknxdkmQrM03/MflgNknbUhEjqVHnd4tC0jw+aohLVDbh1WDc/Lre3lcYtU95XytxEopFS8XRCmHLvuVLGduw028MjwgEKeYHaJMmdHCNs7fBjvxEWBAugH/pRlG+/v2SvbBbkE0tA2jWvtCJDCdyrjhGpg9uYL+hlwphELMw/1y7G/9E+THRoHe3AZa91WlYkH9lwgH8Ec0/nX+AwBjjalAyFU/58dkPC61uGXM8YpyJKEsHcP6whrlN6+IaC4gxiBngLFw1Op4j35RDtk0IQ4f17FoxRMYM3UwYY66Mo1XYVROT3t4dgRHK+CnFOI5kub2VawRjQlhfijcefKPGjpx6Ygm+4Xw5Z9L6ZANjM9ffPRLOOeXcmaPPd2/KH3U3rSmr8WrR2VKZ4pJb4qIQUEe3h62JgYiM4IjwtIOdRqc132OzYlAqi+R/eUPRHJYjSp2aKNrOTNY+yydDsWzh/zAPPeADZOoNAob5JKVKfvjlvu1q1oOQCRHvR5WoGyUD6mVPoS9fdys4XiERBwBgIgUKDQdAQzTpr6Mx96XxMqEYnNUmEjD/O+HBvGKmg93fhpX4WA3GArco3gHWTeZv9uqoiphqBhxX6MeFlP75j3i99CBFnCBBAUW/rFKv47C7dPJZ8YWMeVn5QTip0XErxhOweUA+wHZ4rWPeV7XwIX5LvrtsUrTVjPMvHOYLbmcC76Vdr77mkpC88MPqdiEfz+B0NgZy95bz8PH6tTe/Q+PkHSJSp2MtmQbCzFOX+UjLk/ytmuzmZCsice4TGHVl6KjQ79JshCwCcsHYQOXrdOoMDPhQygVgpbujfjmMI9/xkoJCaLKxbcGVP6cGZhF2/aGL3O1M+Vg2oxNmq2hnTVIGc+LFOdLB4gGytCZRdMOoRRoUx1uA43j903OCUHXa2KIa27Y63plxsf9w7xkkKgFLz9x7s12bJl8reBYeLcNO6r6rDTQV/hxcUWoFQoOW5b+Xt1rJbEJn8bkoTa/LwGUhxFMK3X7Q7p7IvBZRGEbjtAE4xSRs9WHvbhvLOn7Oy/iMhUb4h7aXRWZL4gxPLKEz2pWXq3WESigh6ZZ6TcyEEElZLqEsggiYTyeAIF9bWRdP+xG7V0F1/vtIjGHPWzaRrgaZ5UbZSxhjuKx8SEMQIoWGBgb6vjqmmajov8IydfG31WBm4yFfRNhrLfusYPNziEXP2ls0JfTcdMWf1tzygxpiauHJL/5S2/r1PDtgv622JZ45zy88sX9a6q29pa1v27dydmfGBvuUd9nhMrvh5I9c8Jt7Wsu+F/kZhcH/O0wewtYk7T2zoPQzY49SnTZFrk0wGNzzGoxFuCIOmxUfYWFrPNjp6ZOB2g8W4nPbyv9Zo/dTggKZANBfwhUIO3lSW/8TtuVZD+Nvth2iCR+nA+CQuUhZFRXdCEfDWH79bykoLV+SdCXcA0dqrcRMXCnEqiEUJfiz/8uFiSZdPzn6Vz1IRItLSt217I5HUJHnftomPiAYi5EmZQ0LUpSrKQuDrQjKGwtlGw5//4r7DKqotrAb6Zkqs/27mjbtdd67/+O0svSR083NMER5E2hqgxMQModCEpki7tvubmPKKPJx9NVZpdPvd5IHGtDLz0HKWbQMUpf2xia+o2QFaSE2XiEQQo//UnMisehCIWvGISeIP+ImR0CtdIDKCMXqt29S//SPTH9R9LE4ucQacxPHE7cxEqhCmRPU23Yh1pu1uwcnSULvQ9lGLZLJ2MzsdIIWYf+0mHviwU5FvLNgfiLIXYz0ljoCDJK5M/ZA05oAXijTYSzxSZek8EQI6rWu0tQpRo6rYNzHtBnSPyxchuuhI9e7Lq94OWcRhqKw3SPdmm9LXjPpo32UWp7GdApli+wzMyHmDoLlUndSeeYwBuIX+d5fSvdMMKFvcqPGx15zFvRxouCdYE7sJFCt036LJhz4Pevwxqg4K70Q0a5dRmXgIXs77KkpyN/7VIplKi35pYRmTJysikdPU6hsQZUS6ysPdKuUWdfWiV4TsusV1KQzkM9Tne7scFtWO29G/GvoORMEwY1i+7zsoP7D200KdcTzk+0IQ8hXwIhTuC0LQZyb1Mc6dF6f74zTZggoM19IqxY2U7mFeTIva8E1YmSHyaDiFZU61X3yVOy92EDifv80kkUmhFOwz6Iats7ELG0gFPiZO14svFRJ1G3EnqO/DcmB1nQZp1yjnZ8vBiRsFjbavKRDTiGC2M7d0par8PEfvPz745pbwwRRbfNXP698XKTINumoZV8mWx6XQV0rbJGQkJCvHN0rkzwTDORvyoFKBxfYQX35GlFgpAQmiFPnKvORlIGLl8MLoR3JXUMNQABdb1ckfBWOc4JrGHXroiN5en6oMXijqDFQDxfrTZJBBJ37qnuQna0G5sNknYrYEuk2PbH2mmUbistuajvwVAdoG1Gjhaq55wg8rWb5EaZFdwcXGmQWKDSsyt4c3Fzmbhv4CTXvQGVrPHCVaVUuWhLfUctHw953Wg2nHUhqGvlkcOBGu+eWCremu53fmhWEfwqRTmgq0hyFsz0LWEYNY5BFWviBTf1xxrW8hz+kmil77NPLeYLuPiMXELIMyjOHEwwLPsXL1n8oDej8mJqp44/d9DdaVtHp8IF+qAiNPVgtVDPijwM4TKn3lLFcMKmEpb/Gy2Wp2YRLdxNWCL1g9+K/cOkbzFMWMI6AZZkM5NInjW8ycK9+Wt2jFm5U3P9Z0hxyP3W7449QlwOZCFwONoTOf8UDo0srpTw+/TLoRS5kf497TFpA9COVDpzg8NDrCLKxl8K5AcXqJxS7QMlandVmlmq9lJKdE4EJoOhZSoNFK+e24sb1BMFsYXScFUlAiGf5MJFQKotcGDlM7Li/oer+WIhH5wdip4rgcyl6RMOOaphRROc379R7oD7QiLrMEkoI+HD8vn6YgLuP0F+a6ioAzbAfvBKjpPvf5qqNAJOfAelxckTwu/XRuXe+w/6tmJlVnMJ6OtPgj3atN7jhUgiJG8h9wIYurimHmbVbP/y5PvnmZfSw2XoXkCtgtd69bUQEl5mLkx4glP5rk7OX5aXfZFdBwoQu8EvpdaGs5lF4l26nL8DX9NVvs3JPQ/PoGycjHXqebB35crYLsChMkjIFxEgiHSEHD9DUP8LUVuQjLSDQp/aZAf3pkBG5honc9rKuNkPocuYmIpv0d6BGAgMu1gpD1JOjWUiyR+hjJLBXLBGq/NktTOAkJi3UJzYisDVEFH919tv7s8jP1XBnYu8KOFL9ocr+iW1QMZGizKU95Z7uJYWvScW8aqSwm2/8KCqF6BRETZ0VXMdOGij798j/4zy1ermHxmPLefATgqbnsh8BnDGY59BSjUOF86MpDLKd2N5ZcqAuhKZg0q17RWahqtPUgajrxGUO5yb1GQZ1Mezyt73iLDBEj/DzU2pIsKbtYeu+EWcQwS6bg6Ua7wFkz0U3n8lG6hB+xOsyp5UbfgBuTbAF3AYs0cL5ZxLpQf6j+iWd/2/89J74XBG+edkSdD0b8SysldXIN7JzXP+2xZ6muuqReuMrc7/KPFoARNpaClKaeymeVfyV9wS+91UDiMWyN5/pyE5UwC1xIzXjDVTD3nnhH+tO5tuspI34g9jEuhH+cDWu4tzHL2b/5DM5wzBD4nwZy59UctJXTM/XFh1ky6dPF+7HfA2dnrUS14QAWY1tJIFFJhVw1bV0z8sTgd00WMw1cfHVEwqhzMo++Mj7rndy8J9KkWZ7XhCczEvxAq4tXBi1vwNkh6q12xWJzt0aGVAzSOpC+8uOAckhCkqBU8xkP91JIE0P8/duPeBJ/f0CaOVOprPuNkCFeNX+VEVVxrViXSKZopJwRDvZA/TQES62S5XWQYoyk7Rm15J7mJXdnyy6bWNTtXfgsYLHRsR0Tg7eLkInRcUnOnS3iSajHHj5MuMC+uo+y5VH/vAZw3n1AM0h5wCMl/spIJOPNP/sDqYJc821j0xShwHxuPoDJTjhKIhDBSn3EEYKQRGUUooZWH3dGWt12Kmv3Wls9EieVdXrxjo6dL/JYQpyohEo+ruslojb9J+Qgy5hR2fNq2Z/p/2eYoOCcD4HyifeC9M9OW2hn4LAtZ2XMTR9COJPvxnBKXTK6XxUISJ/FEdC/rLejrdjzsIbRF1n33OQSfscU3D4RjboN0AQo243dCx8Zqf5jNg+iX3afMFl00gnJXRLMK84pRgqAgdJtaNeYVepnZBqaRvn+q8H7012Jv663K7S86vEtQlSPrH4E/Qr24nz5H37wk2jUrw9wqehqdwX2I4xawE7KW5auUixdV9e/0RNnuBvUpWUJTCI4QvASxMYy92J3btctIpW77GJYEIVTDusoCqljjEdmeeiLgERI9/mwlkckQT+BnzcpXkK+vHSjRt/kCDx/M6kbK4LW2fZOA8WHOSAiKZt3EmJsMbXF5r6hGkN7W6oGS6JfDFBsX+lIUXNcXfndoG1VExQNi9tuZJRK+ITKqI3v63x9xOHXy7SC8beruVO9lt74IEVO8wMY8AWsozK+wrKhR140OxT3e2e2cVS++65PBbgnwHaW9mTLqkfj/XTFy9LXd00CGWG5wV8JxTw4vSHMrw4yIxTK1izkQph2ImaveKYu8PnEeXLRkH/keBaA8E7D5Jxvgzsvy75WRmoPk0V40CRcSpWmFu5aMuZPZiIJgyhK9qFQrxwDQt7bQWj3IyS/wwLaAHdeAfGjxBr4+ZieNZwJ+G5suBQAsbvbNN2eiBAtkqtyw37zN6rLI1av7/7xFU9JllLLuFYGQfvSICVazia6e9HlaeyOjJjMgIDppq1RMnEYN3kulh4uWi6lRhg1mVg/uOrzG9Vpq79+JCwxaer5+Vc99tT5Ie/hF/S4NcPeOz7DwUgB3vKe+sYfexSpxq8NL7/IEj64Fhdf5D7O4GG1zox5AnBeEj9lQ7IM0e7dp6njPaxmkVbM8Zn0roWvDIT0F7uc7f4djy1mX949oIXIYDkc45TV3g/Moi0/KRXe3ILg015WLfUOXyTOxNQ3DoJ/p19YJ4P3ogvvmP+P8W+5S0tMJs1lOzErRbER5EBXCk/7uYZ0mPLikbrYIbcgJFIIJczCUMpYTq7OQy6MXxuEVJyJFoJANkDVpKUJQsIojBMIbHNhmjaBEBCfUIgS7XfihdJx4N7OEhlsVqUNsvQR4Lr/Ye1cyqujTGM4sd0T/PbjQfPz/DOikKu36oRaOLAALgBqmKbn4zrWubkLtcdPxXhcyrWl8tPyZ/doPXSBecA7BeV0MnJ4cNW3P7T43/R4nScx9wS6MABvGynoqUKeYfNpOYhjs3AORV6UTmOsOyCeO+7yQxmIPHPfo9YIqbMtuJ7WAYskuCcb2wBnt1QPWtFdNj6PSagIYBQJ0AHZaTRGCRMdGSfHJfgVUKImpwZ++F7PwVs+FxY8PitAGFcM7Y4q1Pq+tf+DwkAJFA6ISPQSrzF06Yt6hUIZpPQARkECSQqmloXjYerh+e00e9L9UvfNEm2EVCL25uO53G9tVCTce5erJuA9QAjsSzHpFRU7mBGz3mWVBRR0C0pQDt5VM8oN0MiJBGPQMHmAgNPhRVy2jLF53Kl6F9xCUmcIoRZ7fj65pz02P6QCXo5cameavDrw4yXsxz/NtJduXpeCiC+4QMejeQvJHmjgWqkDBo9S37HIw5UVIgacYDc3sNOo3+xUHiKCFCcqC+BPX+yE6v6RSdxT98YlGq+fGWbU/XewZ11hHRLg3nUqwWcDOy4cn9c4Fwo+V++dyQCYRC9VOjo7IWo3vDW9Jp+l+7rQ0oupq4QzAe7fdBW4acttrf6XNkk/VrIJHFJJZ9gZzWFzc1Z5cDGy0M2k9B7o7AghXOV9ceHIX5802wtMmaT7uSTfq1WAQ/HsV+HpkSbiNwe+XnYe4P9Rs08hyo71wYtDBLQZ3SnezG3VA/qITQdq+rMjbuIkM49OvDdZ2qP6S9nJ7YnfrPSjn/dTS3UKZfXVNyRFY0JaX+g1ZUX4UuMV8BGUH2SW5izDLIqNSom8qdY8NXFwsqlH7fYCspFXh6XMHhV4PadEv1jmf04qtji7Mfhgfr0rT+e9Zvin574Q4rzpsFpeZT712OoPJ496Z9S1XnubcI5EGW+Mk+QZF5ONGFYl841fUFxOzrFXJgzpOiwsn71Tff/7PorQQBMG0VP53/ZosYGt25cPVtRD0gGoZnccwcmgSvcjmI6ER9Jp9oihheaZlQ6e84YshmrSHPmruLYGqur6MxGnM1T6IpIk4ikts27FDS7t5Vo5MVrcKdxX89Fcjg+9EpKoEiWEniCpmmgtA/APdg9G1EjNTkNYyTNpKjyrUCI9QHr3JnbsY9kwPiaaOTfv38twuAVSz0gH45Iu6soNuNpm0qPK/DSN3NceUirC/eCn/bHEYU/g6w9XxWGE87o27E3el7yAHEZxikLpr0pegbfneUKjutLK9Peix59z15PWi8bI9KlgNL3GHra/0dBdxZ0ssVaiOoYKvRiDqvOuJdv8bffs4abbiyklRsjGEZZBD89E4CYXlj0CDCQcaVSf4jbUP5cWiDkrFSzUbhzfHZJXePzpC4xXCBom31pGdZ+iWXBrMDT1mkjmg7pF12NuWU+Drolr3rXqvgftPmc5rkxLXBRiVTKR/JGSxCdjaFcLS0ZDGT9pPx3UftMfy3f8NV19ERlhFopMdAFIndhvFF/5n5iTm2vxGudRyrhX7gSYxwCzkhU+6RMCFMcufEgdXHs5KfvaZ44xqw5KnYvP1MzSbBzbfSLXCxOE5bWBOY06BBXleOQ9zejy4XAbU01EW7mOG73yYUiKDY+lJRL0UXiMN+pJFC2QZnEZVxCm+DBLAXuc0kPJE4F5QHkt1T/yjw4e8yF01J2FOGM+32cNcO7bJ6LVPzK6T+yyN6Fcvntl7Ll/SwQ+h4Zb8JptDd3H6R9BBkcduFJVwTQZwEIccL4vD5EowDJ5TOImmgVxgb+GK7DSIUIIyR6EApkbkKf8/8KprHoDyJ3zkGrQRcDVBQQf4gqvasSUCVjE0TpE7uD3qWWBMsyv0zDQks/N/oPZfCF2szf7iG1g5CG7wR8aw3ShEBQbpEO5Z4nZXd/S4azbnNqXkCfbYNS/7Q2Z/rXTdbD/qHO2fLl3FIU+MBtKXS6Mbo+/7b/leH+cOmKDXxun8GvMSGmGWkd7THnbMkY5LAXWliaHooWcqfdnKcIbBDv3Nr5CncjQle9a/bjlGnNePgSX81QjSgwY9ynMVcQyQp9J+DuliOXFFW3pK3LzSTW5N8iBw8w1QfA+cqlmw0F8O8uuf7xuVdsWDopN/OA729bEMYjWPAn8iA4O1lAdSYfWmV7GDxJKkbHbjWU1Ho2SYf5JONh5r/9c7kIPH8lFYX/8qxoLI8+n6GUcxQ+JQLoi84sOImiJ5u9C1HeDfFuSemwLPahU9o+Pik7EG2tI8IKcjzN/2jCF7OiWhYEXurnL4V+RPRAXfFdFOeS/ZV53S0wopDd5qk+R4YGqFpdTBzKs99EYdPbNAGnMjad/bOEn31+5PtUt9IY+wMvuwJqigmD+NInqWVp2TDjJhV1e7Wb9ONHnZwF/u7+EuPM4Kry44rmOn/dJXz24+FUeeKCbumz+irwGcd5v2NV9p3vsTg1xYtcmZ+5iWr1TAkQrpkRSyrQRZNke6FZcS0lr3/gVREmhUSJ7m3tvZkMou3yTO+KRA7bfoge/MWjuwMr7LhTjhx/hOs9on+ppAy7YR+kwfy3gOyc8V7kABFs2b8D8akH0mMkU3GazKQgb7sOmJHFNMQeltcKWFn875nHofGav63h8kWrFbCgcZ8aVn4xlYOlxS73bLBHdiCUtiA92bH0OqQD5Hj0CDyLVrn1/no7QFydTSdVE5gTvvSBwUb6oys+lD++1F5naHPscW630fzd3vtgBwwgrT1lKnlvpJCs/byV2p/uce2vEy8/W0NW5iPZT8lUZgQyFGBLHkcA19VQauqjrj4etlWNjkwmWfaZGJ+hmY1KTxlPnu6f0qCdKTIevfpmgqErPgbZWFaSLZiWzJmXrmge0MM+jsHMlfCayO2XksLc+R7HKlWEVdRmnPyemj+GO/moXlJSsqi96cjQe61BflhphMCbEhtpb/EdK2zo5b034KI+7SRH4WkAzVS2/7/R2fVZFiHP1OaCuozaucjhsAEt4TOALvd6PJW+wCnAR9Zqy/iuxkGnBhWDkW6M45pVdRtx1trR2O2XWgFWkRj5Sek6Go1Pf1i7I8DLJXv2oKc/5CxZEHK5Rx1elEHFAt1rL60oHk8gRdbWqu//60BltiNm0yWYUSYsxIVhBIXVCYHPzu5KxOe3xd/JxOR3atLkTTZ4QUNwiErEGNdRBEUemO+aOR6aWxzC2Y29nNvYUm58taSrxpYji5yk4apoxhodphL4wiB48M9R8nlb7+vi1bSq8ek2FrPOwQ5CkL1cnrbGDA0AV6QcnecbZ2fdLP6lU8o+Gv1dREblky3plXrohALl3eKBkdXY0+seboUyzsAIzPA1/J602P5gsR7lWScl+oMDn4F1Tw/M/BU6fsrp9+8a+bzCzLYbRXnLW5YCJOIZNP2yYJ2lBR3l2yG7goKrFKhT73NYXRU4Oo5SgNGtntd0q1E7zPs5HW5zR84f/zaBxhgmMtcpndsZdHaK/ZBGwcGrGHJcCzBGk3cKSt1eGz6qvnL+dfaC4AACREmZDN51ZEHL0REikvFR6QZAsXi2n3CnRIw7E4Vop9RA+BWfTRzFIdHq1/Gk1tkOMmBG+uR0D0BcUDoCxkAksHE6ktpltAinkQto5nESpT9GL6DW0ShyGG4+ockmI7A62tswARgle9STATlKHtCVFQf9DE6cUCJAokFgwiUn0+RYySIK8PgGF40SwKrT4g984MkjaqT6igfokT498+kr4346sBjiS8C4C7EYT+ScmwZxvJ0MkFCGR9zFXTng2pJBJnDgV8pFplkS9V+sUeyu8YXrEB9eixJEozA/A5NEw8uAr/AvRrVHLEHkfbFzKV+iKOsD5TfmYou0+pSj/ewtt9/kFwlpngHSweWWvqkxTIy6Ph4vrtS+beh4WO1iPeWCqsvMwAE1GCLBsIQvrCyxEBEeiOBqWIsEFVhia5CgYFIGLOLRArQjPmV6xusjK4IIw5iz3lD2VVXX50/XadDlEy7kchfXTw2MnkRDEQcG9QEd5UcYKxti+ffEFetJfYwjmczLEEQ2XEOpaX5c4JjfnkGsI+tHbi4mXlJ51fqzUIYQvdK58O8cZp6ZRWjA3/X56OSh9eD1sz76t0VHbpnt19Bf/L0FYXh242GwD4ns5zsV5+ofAzAcU63ZYy0HPt4uCs1fmwI7+5Uc0BVyB9XbkEURmIE8ooo2TpdEo45xW0hvtEKWHhvyxZyLRme8/tkTkhgd74gaeRKq4hjXDS8Ere6ikCFTJyZ6eVFKnOT7CX2Oue5vq6hnBUT7TVejoiJdEJkBVCDpmhPa/4M5Wfgo4Qh+2qmyimW7XFK4y4w6pX5GMbkjZIuQSJJENbxRAFQkbnSkJdXdGapUaDRhOcMzL9/B0crMSmrc6IxA2hGW62dTJV8gk8wE7x77beqCVbg7VVQ4RucmUg63qQn6Y1Bo5m9dWlSHyri5t+zsSvmNnZoGyKLTXrt3BCqNClkZAUa2lgEbf+7L6k1fQlhX9Lb2G+DNvXnKrr0kEBG+L77FfcSRHzuAdkRjVCNQIdu9lF0LxaeVCUFbMmC7LRslADxd0486vRUY0KZINVplI4qG2fEfGGqIDwEwnZgSH5GINuDaxQ3qPLYkS2YlJJO2VYjd2dxrhHiTtVJk6DDkG3hzMqv45zV7A/Bv7kRUYcx29Lp0chBmU4ctm5Xp23a1tjTnZC0ZCU3Gdj/UxOon43sjiWZpXOe0aiCG1mC2KGvFDb8I6EEdS96dxMyOUnO+JO5nMCClnyAQDyeatst2/HvqPrEdWRCPiWAzHYj3xjzkb0Khp0PQOuAtYCDPpBK4euMtnNTnQlLVeWygW2uB0az5flZ5eOdhyndj4lGTe05WQmc8AZK0nF+c5XaVj/WFOQuc9gqeO6kykP8hOH4g/sGk/649BNRGINWhrGjM83Iyx9ilv12NsNwQc7RTUP+VN4yIPedbXlUBq1+0KUswU0V5NVtiHJjbg/8eMkiIszqBLS+Ub3c9rVkn6EMXwgfAm0qkbyidBBVRT/AB81YtfpRoN0C+BP4ZH8C2xf/dEvMHZheuEV39U6Vx/lhxr9VGBlIvskSIlUgpgg1+/l0F7Jbxbqwh1GRVcILCiwvVboZNz2H+4M8rOOJoizreiy+fHc/MAUyqBpZ83VrTHGSaWLdUdqmA/odcw/3Jyfm80UJmNdrG16AtmL/5KsY7SnskTLrsmTwvX0D0X5Srd6U47t95K+lYWccmjRCguvBZvV0r0L6adTb+l/OEm8V1W2c5kJ5V3Mv4YRSMeCH5hUppf71QPGJo1w39wPWi9TictUBqlxU0SfnJ5AcZuabXuL+vv+zACX3mbOdsq6h23VYhhEgvTc/9TfYuuqm5AD4vDoXZYX0FcD8wIPrurYrW0nIzqq1ZYXUrHtEZDhvYWXdJV69qo6S0fK4uyGpPFKeTU/xzslXW37a2fFPRh3mT7opx2ySzZOKqXytRlgCnG55/N3Xa/kPpwSPS/HtZ5sVcfsMixTwuQ/B6e083AziJAKidNnqEMCaF4SBlqC74on+mjAatt1BNbeYLBFeAgJG9a8E+TOtIzTR/ltdm3VrZNGiCBD7OxP853AgJBBgB4L/ntSRFhtSxOxqkZC3lQWmmRXIi8PsRljPkbMRJATYjRB/bAwmTNYP4aixZ6lMihSMfJ1McQlRDfwJqgXSuWdkF0VjjppiopQj/3moZlIacpCsVykRRrT4yD7ZQ4j9N7Vo8jT0gob21YgkmdkREhRgkw5YGDjM3MY4K2dldJSpXdK2eQTYifURM6QaAC6065DdSy2hmQfx1xe3EsNZlZo6ry5Nki7TOqeMpmoM3spn3D/9pkwN+nFgBf0ikvbyqN9QtH+THbR/aLgBuT8HgBVcG4CPISApyjoaLOjv3tv8OzooO8Sc/PxtTxmrjeWipfM6JNGzLUIK3dA91A7+9C8PPcBxgy9gHh3rLaQZXVRmPJ1tWqgXM7k+ku4Qb3JGVONwtaD15fHVVQptHnEfZNxC48nzivEgEXbxyHe3YHYmgWmuso777BuMEbEVpyolt6PcIdEGCPQebzpn1+3/QqV6X3P2qzn7rPy6T+NdwUlbZWOVCCKP++ZN4sF+V0Mrjo8JTJr3Io3pemas97bCX7WzX1/pxm9daqN/2cl8bxBFpCdsu9OWJFOykXui2acDn/DAS0zWjH7r2q+7N3urEj69xXQWH0web3Bp+rDchrTLMqkD8YQPlzGW6fhCf0AcDaLwO5SdaSIKyFuSS50yTDYASAf3sp1bLQNxZYwzKMtZa4MwYxN1ZKII31loQztkTHojITYDQgoUtzmqSIKK1JEJKCKVLB58JUkuJvWX9zrRQurK7NSGw/uZ49cXqWLvrKT9YBa72N+VD6qp3Y+gFWAFxnPh5WFNLMljW6H7CfQttSTX3zeEDD9E8gNzLcyI3lvQjNr5ehZqyZNJYYHeIrtJ2SbyUucwfGJ3IeDuMCyBJKGfPk/XxvR9HaIhe1ezUvy1G4dus/um5D62az1ifsPabW+PFyOhl9pGLNMExSsfs619S8qMhFCh7kSSM/mh6CJygBr8szVOLYyIh8Y9YYwXl8nJ9kLz9oJJkb35Uhv1M0dGW7/BRDS9eQktcWKqUA92rVzU8C/5qegYW6uUnjK34njgN2hlBgjQwhkoAYIZjICOK+Ui/HxwQLCGIgPIiQhfU7HolmtMAWvhXNGIsyV6IGLqRbs4UtnltoxWQzrBEtgiOAX2hDxRokIFOAQtmRpoBE8Xno50Ee0b1AR/aP4qgf+QX3gqk6TdC/wZIEJfo4GJdjjtHV66jyKVDkYOUn0tYrdzMOmORbrly5xIcH82zkSaL/CIwIipEU3POfiBHM0tSUplczILCMLcsWaSvmcbVNAQlN2UZ+htp0RorVsfUJAsVDyXYTRlTUtCtYK+cL0YRas11AAdzlvIuE8QDTqlA7hg2/i7AHAbAWHFYFf/4esR568XwhLwnXXyHAiGLUGXxJOvDd0UvVg23zW9t6rhUFaDNCaR/sr1akgoFoodD1Um18ZtX2TGtpvkvyktN6x4aKAjE8bubObuf31xkf+2NN+LDr38RngMnLkpAFqqCMo1venc53UUG0MdqWF7UVQuVDg02CafzoGJpMiDQ1zXMvTixd1RXTCykmAZXGX8FoanOwG6yyDOXvImr++BL7vxMdVX9vsxujT7SsuTiXvVIlLZb77uFT2ZRpGsg1O0yDTiyvRc0oyYdqkz9RenHdk2lj6RMV0ATbUk6sAbaPv2FTP4cPKRyIluc/EAYg27YK3EeWdBbMzAsXPaQSvRVo4M2fnLrrcylHv57opeznZO0vTsfeLKV2v6zrezqA7eolkMYyaDECtWVYJ3Qykq2GDtxy5C1ej1x7IAb8dqMH084jtivkzIIbQ3GSJ61aMd4UkzFBUad6tQKnSZGQCYteTNiT6wx0Ot9EWTodMjudt1NWRAKoBFyAgg0PIer+bMkZt/oK7JWmC0+nRWVChR0viyPIq7KGXPNQEFA9yKMGG7F1N3RSPG7kVn2UT2k2F/KiLNLB1mKiXbVzBFzBtRGe1ghRVlZm5UXoSS6LLi9KKGKmDAAhCcjUuKOh4APig8ZiaDRsDXlY9bfGeC4BF4YPWKt7ynIVRcC+xVjUumY43RhxDtpqDoUYxFwjkXPyHH7wTcfUL+Nk2DNVVxujzgQkFIIZEG3I09sVlyftwf80LInw5PSMClhOfBniI9NjECWLPi0MbbtH3IN5o6JTySR2K6TuFADbRR1h6Cj5TW0kylrq1gdTdh9yfnSFKb7pMydqz5HfSKkvb2Vx3KrjopyVLKP7DVwaaBskmYn7+40crp/msSZGn6TUWShbuF77ur4vqcazZi9XM6Yv/LziIcfLD4jYU1uZta9s9upzb69jfKurT3vSBtjCo0rzFaNhLsPu1bTe0lVRl/RO3Sl9CpCNm1wRJeBeAxEyp1cwUCeneKrHigIVxowMblu+BmEALrYveIjU8A5a9cSNIIHzvr25tWvpGHd8c/c6Y74nCZ+BiBzOCa1EDEFKC/cx5jPAUEA1Gg9A4MfeWvGU+I8IDjTxuE+MgOfjHu5hmEQ/b6fCdiN4TTx0sYebCET8TKChhxLxlUzE3N19izecRBD9CrlRO1Gbc49K8GGGZ1nHQLCAwwZNRG8ClV/8LubJbA502CrjeEeGJV40i4y+rbaWJR+pAGCYS/WiUMGDoctuystBMVOzbZXu/qvGMP6ucVOBUhf5bB8G1AAKe3cVo5cEdmMq6jyN9op65jENfnY93da9Rz0dKByIkwmDsAt20RQ7G07CqPebk3JE8Zxu1b6JxBV7+xXB0b9vTYY6YAfa9z6V8nTZ4VbXpMIvNyNZ557hdzWE/egbheG9tv6w1LnDQfTHWwDAsC3VhzZqkHbZeZIcFCM1ypr9jho1GF8T6g9I3JH39qHBNS+vtX8wOYexUw71tGNOCVa1JRtjIGEXYjo5J13lMQ0bkPKU+ztBQOMPN6EJdXt2bSZo2d4nAKTfIJqTC4jqYZ8ayevgmCgn9+vjMkTpYc2UBcSVu/vkATplhwDt1LEIJT3QffeOmZpHT560TzSJEn5jTdg4Ro6AXuqrhWMw+CanvsH7h03tbgsVCNVYqwQ5AKtxtYtLUFboEeVwkWWInsNFRDbopVxcgg/AsSaDxDE5EXgWTSyEwT0jAh5M9nN+SxzjIRZKY9oSiXx3Gxoqy0EpSq+qWWjl2f5lUZu86+J/degjWkqVbNcOZ+q9wkKkAu4ekWiLDA2WjfH/EH1pGS0RUQwHrOg4fARUX0aZdYl8S5m6PhWK2DCWaJFXNqNA8ikN7o78uAIBzd2JUo8Lhq6sRYrBIuh6epNbeOCd5/fjiVc2u7neZaX9+35hXt5tXLOuezjF9IB4+xxTC0OiY9kPc7ehNOGjI5vyQS/YnpDlum/neKXszHZwfkCaUTZ25Vb6BdSzc9Hl+17Xei6RYWlFtd2uLSiQHBROkmg6coyLkMocggMaMadEFKoQ6bR+GEdFauILdzWTnP0HaDCrpmgqg5kwDasx6Lj7dYOhxrMcqKZ1n4Yz2Bu21pNMBZepMKXGaVwH4CANqhFovXeyQZEXuxRwJI/Icu31x/vJVkn3dbyCc1MRQ+RxE/IrzCIJwmUKGpzFyuLG46rVy8XIq2c7eVfnpDtf7ZSRwxLA/LHeazeRa+4D/jgqQIITWBpcVmRunS5ATj3byjsyvl8c0JOirZ7n4RM7PilK5TdvBGyzKagi3afHtHXfv87jBC+Kef3LorL3tsX1Ci0KHVLk07kZ2o1iiX9r9v5ffNw8rsxO/5a0PZgbikW2MK0dekcLDMaDfHBfaWVqu4A3lfgBLimP01tpitbKD8UIx3X1fGQ2yEwQ4KglrNs0VSCA/mCpMR8D2cDSQ7Hx07Z8IyGw1PNsMDi2O0xRrqgCfSE+7272YvlytxIExkyl6nwEFFGkYhcJS4BpSfFEopysAlkeP1dk5eMjHBi1Kg3moXtEC2hFQ/EXfUclFcoSzLbUI6gcQaQp7N0qmdYAv+02j6JAxQCbajz+fms4B/M+jzsdSOHlNdrqo4NSo0rzv2lBMEWgjhYZ6IUF4B2cw+SixSUJzS5zOxMpgPWJFLlMUh+rpXpOewqRSCt/bjutcnH/m/jyim3DWY9Hix9+yEu/g1fLY6q5k57HxKZxIFdLlTWJw5ecCXL461sKqZmdcgNNz4Cwv0yeMl5SS36GsDQtXIHkhcltRnWr5Aif5qKuDGY0qmlOGr9aNs1Qpp8MONtmuqO/n72TFzxpvvZjR2piBcl6+utrXPDL2wKfGGQ2ZjGbaY5tCpcG9u70IOlWtzz3u/h9DZAYJTEYNiFWZONZK9hU+t0+kCKmyCbxpsmfIpGD9dCCK9roJZQzXGJI/YfX5fcam26w7wb/PsShsHEoohn8UPrV1ZWUKLHQ3e2Wz+9v2oD3GmKX00G26LTsk0r0kXMOP7fYcL406pKVBUcqSxSE2u4PfE3Gvo3EbnCsgcWZYigzNm3YerP7iP7f87PLzJA5yU1Pe+aA8reovMkSR5HgapEmfMmJ0KD8mnWwAqTKJbfoAp6bmDitrZCOtKtqXtALeFf7fBFakFtgQ3BuJiyiEMpRV/8dhh/335ck63Pb7LX7dkh8E5wXRjIzlUDzZ5CQUEZYOdG1jaF8kfm6xVgLWYnwTbYOokiCfIDEEqh64NA9zTCx4++Qf5fQnmypEj+IEXMV0vlv+dEuA77oyKSx8Y0H7Ucggs2cTex5Zl5aHP4/GViq9H6k2mGlKWg2UJsul2xdUIWyNUimWA3NfSlQNBJbGch8XLSkzXbfZ9uDvJW406B0YDufgGyxEpo4EyCNMfpo7CejCRRgTXaQO3kohauElf93w7glXd5frXHc2EDhX7VGv6QKREAzrxiG4WcMFv9o5zD3irF59CU7gX2XC9ctkVJ1HXQksTCBksnWDF2ykK4HRsLK5zXrgkYwTicOAzAEVWh13G0nnswq6UWMECLKJ+qnPcj7bUT0fD4btHX+9tIQCc0zNnafFtJcNCILmqZI3QzmCcYYK/mGcpXBafmMRrCf+JXKm/w/EMzQ4CEUq3agjF9Ji98XNrCAv9wmjm9UrPQCiquFxrcd3x6Wd17lanVr3Kg1Yo8eRTwRr01UUthadE6E0gnnBJlQRciYD0mTG6ClxQvecBnsQzZhDvgsYbQq3JeTodaGLSGKcOw5zbMEnxlczWqhGkVtEqnZK6B6QDJJkJdpOkgqUJPXwFCdnCrTULO85BIVlJAiHcqyFChQkx7Je3kMu27cg7WNgtPEK8k2gpeH5YUwudvxKB4B6T4rKtueK0+FWKEwu/y/lZDXLYoCP1cB/7p6nCFpy0TylWw0ajiIvKkM96xbpimDZgGJGf2e3vn/ySNLZsfaK7F8qO9nRwP0tn+sDQRJdIoxm/Tl7F29w8COImzOV2Kwi2YQ34TRfjojSCfCjlcIGlrEH6OVV9gE2WErUnGpQBVnXGXx/UoPhbfLkocE/21NRZjRPHR8uMyfhO94pjvOR/S2fz712dqiLxn9y/k0GW4iB90rPJjG+AqTAbKo6gOmJwKRSqKtBK2HPnnjchhI7zPZwJBMSVDgcPW1K4bPRW5tEsxM70ky9uK1iMnJVWPmXCoJSr7P/Y9Gy0n/7pGjwiBGUXwoVWyDppVj16H40R/YfrrPxx0xnvT7GHgWtOGUgyX86Ms2qGz8rYD1u3ToizfHvsYuv788Fj2sGoG2/EkYH2EmYm0BNTNYS3SBCm2n9oSDsR6l+GgMolfpiV4HOqMRjCmiUPcJcd831gODUTmqalChbKkITb/eDvWqCuiyzxY25ajROzxhH1mmaRn/sDnBUqNFuKgVmfCTIOdywc8ty7mE0KrjLo+tw2IsRBIFUa4DHNwIKkOalr8OnHfcU6USuQtckiAENUSTAbWEm/hpgAr16I0ciIl1uZ3eT1fLu4K8zmFSW0se/X/cFuRUWPykPAlyI699mcPusiNeE8Fh59ImR3KDlVy/IFojAsqqf9s9dqkI9LDUAwKn6G9ndREuI0rbLA4J1DaDncH0BcT3RAyNV2niskayix0WowXFDMlqEaPAQiwiMzELQZhJZgS+BbB1lHDMxRK5ERto2bPxxFO/F/uLPAUHaIOOk5vONiZhz2cG4X1WJRp/p41Ga0u4IBhlV4NYPwfgz1WYBG2TcvxLyK/5lXk4urfLZnSmV3R73F7o5qPECUQDpSZn/mOY6HGaVCjNr4TsyrpTS/8ZItSQ7VEkIeWCUVgjzxMgpHEzVaIKzAm0E0cgqpFoAhKNpLtKOpYsQvfiSf8rj1nyutcf4WZ9Ys2R+j0ecfNq5zn0ej0Su5oTdq2/6qGbVY5Syw/2pC+peAUlMEbVab6zTTjoKVC/+QZPG5UvOxV1tAeT6TdVJ1rvljnQXV2r9uuUuo5+dZ3ar1fqUSP6hnFiB0s7NZ1DOovbomx1uhFx1MyA389TIV2by9oYPIRsrGzw6AKIr6jliWqI1g1uXCLOgOS0gNF9s1c+RS3rpvwbAlW8PFI5ZxvFGklMunnVCDiysMcpetAb4A2884HCb7EZBdkdpU18khwpKB9Q0TOambymPwOvRTFyTV2dX3QMVV8LyvuAD1K9VlrEGAPxOhS788Osz1Gz7KBl9D19nBLKOqNpQh/B9ie1IH+KD4zxSJ96Lv4k0v5Deb14iihHJXEJ3NJqQ903BJM5bqpCFBGISFNg1SNWG67frVH4vbp7Rj/SsE6GDSkpF/U1/DvT5cZ6szHqxYuvcQ8HRPdQY9ChS8ADyEpnQQSx+VCzYcKqBL6soUxWahOjLakC31NHHB6gT3TpQyeve0JzIpFOSMs0ErTZEc/8C825IROLOYjLeOGsfTtXtXOUwLFsXMkbbYbIy1SsnlkYMrPMKOFuop5tToC0m20ZL75udHKuSRP+TbgKw9jghONOFNc+5b/TqxL9Bs5L96lAiUGHdSmisORl7+tVVMJSAw+ajgqWepsNxY0/7CPXvwFDLDmSHZ1Y3Q71ZzHHaNHClHARM4U1q7gLakqu9ZkbGVF7Qnv6p5TBCvGvWzT4/8BUuqAR37ymvEybbE/yIT+yYRgfRx0mwynPfbuFM13UrCnTQ9GDBqRn9KAU42UAcW0S8/N0e9ZEe1H2YMXKWruN1tualrPm3f9TRXNMXrMDr3D2sff25bwACTP2YihIglxkTKOeFSUlq6sXOkwaE3quQQeYThbXpZTxSVq+cmEwbBYajAUN+eoj8bRsfb3/3nlducuD86+GHiKH5oH5gIiAmd21YOkgt0BlWEdygey2xhWpsjZPAajZsmvxj5ExW+lVghKtSF4NCXWm+UjO6j4DUjPboZpq3c2/c4f3U5jLnwjy3+Bnxo5+gg6DqiQoc2jD/8ytMnz9/4jd2DCI5YckQvUTcbPhUPIwmDNm6y5Tp1g60la1rMpD9C8TStbu57+itqfqrEgNKMpnu/WiWFTLupf+Gi0Yfzk3zPQMZ1hJzk6e4v9ALH2JjthO3Kpa/RjGe2UBOfdpoKA0pKph/TzyBuJvU/hQshFVHe7wrf5wovSJTOFla0pP7r4YhQQlpSDlo3ziOCURQ3GwFm3p1bEJ08TLYMa5v269v9NIr3GasWS4cdghNouREmpTBH0HAyglHZ9oY+kIw0kaSYFmm1d3dZUxj3SoIync/TOwO8Lrw4MpPpSHoOFaSuu2FrRA2hCbYnzeWR6BFhQeSdcwscXto5wrEep9bOFgTvn5A3oD/JGne90ESD36JjdXXC9uPGrtfP/oHeiAfdwhi4AQiefiIZaGtAIiOZE7wSkvA1awENdQakoteMEG3sZPFzLszMUyQz3IyKu6tqwzIU7m4Q8/EjL76oOS4tMAD9jkBRgeFa19fErl8z49cAPgMaYJoQnrSBETli3Ln3fsx6SrbdcQvncbuMee1+/eWsOSCaEwieUUf5Q2CshpadYCQsarIiq9BlaGSGV7GFAfBh0MeOqIPkx0BJUCksgdVP71VZX6cpPd3d1srUdLsdke0b0RzPZN0b+khGt+ewmKuA3JcIuXdDvxBrj6KGgq1S7vVyA7riUxnhydXT8CqYOS/CxcA81C+IwyhwZOQghOTMDFqkMqT6qufkfOKA4py02CY+VAJRgAC0ZR40eYE1qvt1lQclgAeY4NvKza4wV6oLsxUjKnAls3iYhu5HFXZWQzeGT6JWbh0oPLqXosVa6EW4/Pu69HgI43WT7rMKbuT5MWBt+iwNA1N8JN69XVn/ZbP6Tm4cr+VvzeuD6Kefgy3eXpi5rYnzgQOBE+7uXSbLJmD/b5M5k7ecoP9oWnP+v9LYLfDdWPYps5VPwpOHnehlx4+P/DmAWfgBT7Q7hrpzob6pTOglgTt4RX+y5o+fUFMZbBziXF12xC9PtDnApRB8YX4nVSoVOqENAbwKg6s/PyBSQBWSD6cZqmOZxM2p4GaJZbx8HAZOvFfo0Vaj68wDx0O8AzXoWdWseENNrZG2vvZF/KpZsud4FlYpVUc/ZJmjnOrycRiJSTNlFX3+lxGNIoFbdY/3/vjKWRWtjiFbzd7VMFCos+A8Z85rUXlwtFF1tpeEUPThcwfGY4Pw0aaQyg67JPOtANgIKcCMz69u+tQtFbQq9fdU/drOXamvfdm5YXv8sjX/i/sMAQazWLb1W7yKX0q+3Dxy/CrjK2jdk2h/K8BT2MpUtF8JnbrhtHKmPaWFlwrv+kOLwS5j96qsaY4ToMngqkp1MMuYe/NLFoVyMHV9/NQr7bLm8whlxbvfZIA/bKJJv2H/NPRxJ+3137C5kxthokRHSzapkHx1kiR3j1zCQ+Z8VbXLHeV1AUQLpaSl9/VsG8g39BFuZkmoAUCrCBYJgeDbrA/WvXY523I6DPBoNP28Pwc7LlZY09N4w0cBjx6rOc/GsenKruYYRpdaXltOfqil0K74PVnUurwTsOs5y2g2beHohLLuIqMuy1bkWFKCUVJZM6aKY/4ITwQ2iY1kAjlRxNcwv2Cc8kUKzoBAmyNWaiBJK1TvvcKUX8bsAXlV6CFVXqicGcWuVS+3U7Iao2oOvIiIQUe+feXWNyBSDL6ZET/HPK3KIN83wZkhF60EEYIaRJmi/WuEAhBmLbHXF0x8LYPyHodY3V3x0juuQ+i8hf8lpe6ae5b+37AN9ATTfxqFKAgreGboHJGvl5u09SPJybHO3Kgq4AKhjVaLsccv6GbuL30GLVhQl0vfXGpLcKc6ZNiPS1DJu6hReGwYve9wYdrzifL4tgjN31MMup+3q65b/So30AbYFcW42/EbvkacxUpuD/jfP76d214Hb9FegB9Uf15J4Qn/wxJml3Zmie6aABKSF2QQ9dSNPOYklU5VaUbzI9Kp9nzv1qcnjtA/Wfx8IlG5AZgNtx7YZnMunznnVyX/bB0bqZUunqruUfCEcwoliMKZMgzxbofZyPni2cPYap5gincihRaYf2hkPrhFNkFJqVQDRpvQIuWXnd5ZtLkhJGtcpxJVy20Jb3szx/wK3G8LOsBqhN9IgV/101Yl+Yu510/J+CirafdjzW9+zzFYakxkAbpvZC2GOKGqOAENAQs0qVVLvveTK4+02LLDz+PyH1u5ZGHnODty+mZtQ2/fdp2lNZaqt9twWHH4zZup+ApSRkEmq46vw4lLTePZchx+Ubnj+joP1EJwOPxnAWcGv1tBb4Ikc5D/akaKq0+JVB11QxlpogkpSNCgOQJqIJ10K9qOajYnQy1o1J8wQ4pO1gOvwdsAPgZGOfy2uG6O7tZaVOzxk1WxV3PIzDMOJRPL57r3HgnVHnG6Zrz/amZqokgoYqYhXM4wv3ktv+dO40vL+0ttc/kOlZPwgjvj8mbzUN/Zfan/z22d40Pl86COG9AlM/RZK3POCDQpQANH/y/Ck4V6xGvSNQsOdDXe3gC4LQFfWAp5+ElNXWMupDJ5PHgGA/Rkaf2dLlsU2jgeiKlcJx4mB/Oi8FyBwFBzjv5IHXSnzL18shl09zPHkYt4eHPUmzzsq3KQykhxyGLL3OYyZZMoDC0FyDKrISkZuMrHdaDg+BJxdEZy+Yc774e4uXM0mVa3xWYrq9DixFnUwn3UYXikWgXzE/4XcX4vECR3jfG+LXsuJcYAJwxnwZuntn78Kk+eAK9bOn5eEVxE+rMsh4jw7GzsRKqdtHfaLz46As9WvvyHyYEQbRWDycxca8LtCdTy9WwrbURrpOkl6SbmCYfaBTlO132Xe3lCd5EKUu7GJVvJCRsK45HanAf8JcCwkKuJRuz8aZ0O4EH1iUk5B0A+4inD22rO37jw2kl/xTpZcbZAxKzGhpe00jlVGE5H9fDlB+Ty3blHXbUGvJAclr50n8Rwxo47xsAROv8M7RDAbUtovcWEK4Kgqzu2gIu2qCYQ/yaQnfUAfZhz1PZtJqw510LZdlAHOKspDlutG1MJK1Pv5L/nAz2Y+eFfmKquxTWbhyGcPHhR50CEZJLOgFLYp8yp5JjcveyDUvlkD3BufZw4FeoJP6scAGx3Wd3UDW/UOh42Wx38sX2/Wyg4e3hClAMvKnLO+TSK6Wmpkal1ttOypmfKFE8/DWfJ59bO8Ab57M8EyDK5v9LvciVHTxBbDV28q0Ah4gEwvwoc4Ad3HEryfCVbrO1FhV8Pa870tf6ApcTZ5gxVMNudNXFYC1xy5AdfXDkDiq4mX/LRe8QDKZaTVEaSlx9SHxtgoxLHJ9KGhHobgfsQ7wLp6sgIPY6eA3xhtmASmrAFkokzI3AFtz2dm7ulOJhxZIJdZty2uV+mX/8M6rW+WKmZdlQQdr6uvTC37bPcKZ9M/qhSy2pRqlxOcngpMZ6HwTp6la/c3FLcJ+9JbtJ5Je/a2AY0ggGuJ8A8sQULJaDV1wLMNnoSDLZL+ttGuX96ThNhqm60NwGiWmicJ4cq9Bi9gcy1R9yTOMR7qOyMPykNuolIdRW+Us+4S6AI/FA7qQrFJ/d6RRfumPzrqxDUeQ62HB2fQIxc3WjU7pqp5+kYJPjKvBQQHjcMMujb4bknDWWMAIxPLUhJgxhqTA5VbhjlbwEFPr4GyUbIcLfqTKfo+dfNOuYY1mifaHDYK468R+Cm5PHEvjJNtzKPcC2F3mLMJzYJEc5/G/vM8i/8yTLY/zmw1gdmEij9V07Nh83CvOEoOGKRI1crVuMZykzISXTxpppGdlpUPlb8sSg43zs7aoey5jFF1lMOALMAEPLQ3U8KIE2p9rHXFUGvSPPtER/fSHqe9a4TdyZHbi9zT9Cx8tjxxUf9Oa8s+Cut/y6148oe1Y1nIcvagExA+eAYMQYmoi54Mwf625Pox3MCkbWmgExv4B6eyC9jRP2SZercNklPq7wp54qQ1mty5ORf/Rpk1FyCIkVyJkVi9NnP6xHZoiUfWV9jA6Ox4nG4lutMerDRCte1HOoxI6Ab9LIHiad3yicPJ6Bf8VsK+vIZCu0IAjTJV87YvUIvaFUfeNciQD8AYUzd63DuBKI1xcxVnCHBllBAfLd0rZZsdow2N6OdCUXIiJSpZSKqZQ56mhgNZGBwLcBAUjODUPy1azrQNotUrmCWpOw9eAoT8qtizuvzsdbleJfZW4QO7bRbIZTkmc1yQnFnlkpGxAdILoekL6GN8k7YomKdf0cmy02EnKFBRpJYrfltG5lRKp5peeEAZ3g3qAWT00QlUsXxPrd2EgXhftoiBSYed7z3tzL43Jx3u/dd8GooP83osN0wVsEpassZ3YirzGfmAdgubsvz1DvczSGBEqFkj7ts3P1NmDHvq54TJQptdcpHcwX6jlVYAzDlc+F/N40IEiiNj9BJlHLCwIwjRmz7XEKF0shBE9KRaqWuKU8HReDUxLaFEQLoYQNLWQMuPVSRc4NJn0r4FrEidAdU2B4X4h0DqaYPUs1ntYDKM9Yoha/LWif7ksRKOntTZm6CYyMZTJmCAHkZgPJEnHOgszjcBaGZJpkJXZYixEc4oRt0OQ6mq0JIYtjacXFZPTOFQYJ7T1Q/3HSq67visvpJYL4olTnpWYFpwbTT7EVvPcSWLtqZhgiv/qmD0rPWuvCZX8L6NNBxdvnhGFAvBiF5N2wzbQLOn5EylIYZtv0Ae1Mp/n/vCwADIp6YaZv+8VuGvhINrWRPiwvAb7Obvtr41zoAEdJkREVpiqO3OgeOr+KmhEGeuU18VuhUlU3cmOCqfCtBLxminOwlpvmKORAxtSlSgFVmFqLQyp2TPEiuG3K8Wsgpb/HkYO4HKjpF/RWgH7gRj6EiW7BlqKWo2wvz5icWWaZ7IIKheNUYODqDMMjpZnQKdpw22kH0qGOnRi7IN8NzymIJQcc+V1QengRMnebc18aCDePA3SOOEwvR6vUTHJdUCX47w/DmRnvOQU5IVegS56pcXflqQZKOIiUKj1nPjp4lHGaeCSUwYoQbuQD7nnMC9QyPt1guGW6THoSn/Y3adXLO4EdIaajGinvtg49TGgYfxtmRuljqsDmJ2KZB199ARwOlG+YMBW8fG+BAqNu2Db99raL7I+JcpPDTyWXYck8xnLgQA/FgGDGRAmQ3xlPsvgML8V0Je0LoBwzIa8lIH5xdYuUveUPGGBiSL6GLZ0+PSf6EMLvCO1b9UeOX71qbmIMsbLqdPTHKENCgH7KgaMnSorLutZ5VQfhiteAqePUBvbA30aKU/9p5uR4Pf2wxARnrVj+zfQBlCGHXqwB+skvSBOzw8aG8IfZDXu7O6FL43K2jneXpZdRJiZQttujiOiTEaMfRBGxWarclDgocM6ca9fTz9lQq2zLtZf2uaMuQjhGb6fy3bliPAT57y5zI7KGbYtRAv3ngri5V4r6FEWJGiNDmU3FFFnOli5l9+KC7rxFWr/l3CKxXESMavzjmCASldXvXfplXsyV+Y0jKQuwsIXnLnPs2CF2qb9hvSHCJynbg4Ti/YNvXwkdmm9zNIhV+6sPj0R/HrsePMbwCulBiuIfvFv00Tn9R8xwzB/HS+q8KrckRaKfuRUtHSnzju7OeZE+Oj7YbAKGPsYl8L8J+4me/tqMX0RNYETQolMj90L9qRfs8H6piwmuwSY8j278DkuzjZpvp4cxPVjwrZa23zyBjMZhU3CJXz1Y6EelqaX7qPfVrBj7F5BDu2WBnLCJvam5C++Fo0UII3TMshxHIfqkruZKxKtO+TBJjQxqKptENx5fwLvBBmcCgdXJF80+4eejKWV1sOu1oUtvF8Px35Mmf5reUt4uBmZ5wpPjLgtp1jMdIJYv8JiV93IbhwwRMo4fKyonefXtM+b74Cg3SHp9b5DHiMWK88wbAJbCXXiID1i7Lb5qW+WS+YzfJ8LYV8Su8R6JEtPSxovyVHBEGl9uDnecLBrkmt1Srhibo3XDJFtAkaa+wA14YWVhvuRA6trIvOs/fu6ADB0sS843nrC9SIgCGosHGRDhdYuehtI4peW++1yiV0A/vBW/vzwlYOD2kWhmlJ2PUfUKmCh7ApEIphUheuFjHpyns/s06wtygL15C+0H/5r0XGBeLeze2z/51odnO48W+bhvaBP799X5OZ2gnmjKMvZyZM+evT5cPbKCy0ANsZ/WEig9zxHrJtHF14osqyGjdwQjJoVbshC04YY8mhWHwyy2KouSjpdhlNiDKe7yOVyu8Cl2UmXy8jNhecOpboqS+c1NaUpV734TnNqlFiwmF/r7BRANE241LS6Pq9P2xqxMmLQ45tpb7GgTMIO1lAQf1Rqrqe0k18m5Em+UK6fFYX9nOCiMkLGURHT8b/HnEZjTUZf/iUUXpA2oKwXejtzWLuJgAawl3gZYdQN5/5WslFPJAUO/uTrzW9tT5kXHc8+6OTLsXL4PMJm9aSm1h2NsVA4NEk7L/o8rFa4adFI8gr7okkaP6+QnDBv/F44Urq2GQjEx70iu7TQCxLIXH2DHlldvZYV7XsmyR5ebZ/QetS19JStGKsA6tHD+XWSyrfJn87aVX/SsVjhxpycP8ps/mZDkAhwny1nLhxlvZEhq/riNLt2CmKQXRPnlxQ/nkjOPgpvPGH1xsBwd1NLJSGwy6mn7P151KwNfUMzKhKFpsfYhBiKLPfW70VHa/aUYeFiy9VB2/DhKsNHoy/EnQ4u0sHq22OkpfWW9Y3j5p5Tx7/yv58LW750Wrwou1LPqkfi0vwkZlWiMozEbNU0j3rxhtc1jUnp6iMXJBT1/d+1YZeVifwl71dlD0ojvEzgX9bmOXuG+xBK7NTsP4eOftX0dAf6YgmCHAsHRGYtM9jl2m2GKkpsQLCaO6VjEcFb0y6wmpboVLBbBIcuuNm7vrQjRFoDh7nRDMsoPaQRSlTyS7CDYRuJDbs5rfGM3Brrzeitwa0qlbuDfXPBafYzZyx2x1Xo9w/pconGxNm+QgTXBSqVNqrCbUOs6ZzVU6wufdabm1IFv3Co+SmxnOfik11QObhwjs2fLWeU6tCXD0tr2Hjz/2jq5uRxFI/TqoY7r9iiMpWf/bqnYGV5J7ZT414QsYQkgoDaIWnCOV2EEzGSLUiZT7tFo+Kkhr1NiEZC3LCrbd9IAHYCE5idL1EZAXIv8p9pZ4gJmMUwhpyfpFCO0EqUoxwiyop0yCd1hMH0GVvOd8zGZktXclsxq3Mc5gQlEz6lwMaJ80sVTmEb7vEZpn22RXTawg1jo3JfF/1K2danLpkyZJkHR6h3IAwbKaTY8tAw1/gu2fDNdM8QaTQXs1IbBic6HQ4hjky83RiwsBWA1s4LvK4niStwSWCdGRoMzOAMIFZIBdS+tjcvQGz2VJv34IiZWutlKKUasyg/iqNxWILMd1QPWZl5srjix4/Ti9qyL2xec3Yl5OA7lzZyB2M6NgOw57i3vjRzFsXlPmXvhG4/Sk67z64zMq2yqpoNW/DwfXTUQ4/lBowlhEfzvUFsw4QvQO2MvO3JVUsXc7200tFbvoUjfLb+m5KJ7GJycwVIw4qcJZG4uZgL1BU4rLqi8xQcVumInUQBZXz0EOBm1BSyc55PjLFWxYs947EoB7/ZG+RrbsGRcDqDNu10FyahWcmGtzVMxHv6jgTaA7aCfAStSeIr+gKQxkcDGgMYqTV2Iv6PCW5fUZYJTrjai3zaw7N6BMp4z4R7K50s2uKkZdgby74vFG4nTVWZ33TekxoprNLPaGW0Qr9dM4eN58+Z5lw4VCzHxkOmK1X05GlD/eKepfwemjP9/Z+eQAok1ocSY0x8AcHRsRvcqCfFeyQqvXK4K8aS4eu3Z4IS6jWsvJ3QNsSj51NU+auc8gT6i46RnnK2XzwjnJQI2Rh80vpALPvvSKcMzbEYfIKrRGWRJLoFxBE9GCGRWR+6nNtoMqFMtX60A7AjTPojD8aZHuXQh2XcTBi7Zf9WaqYAs73CMIcKvTibYrBPK3CKs9I26UvI89ScV+hMYcv6RqT1k8cDFBe0OtsvNi99y7JUuv+Wp/2IQIwxiIupZlefOkiHcGXBfcaMKt3SvDy1RaOZaI7giHAz3vznvnvXG0qeP510v3MZJNRIyxq/n6yS7vSWpld4YJ+WIztJpOXy7lSFTd5xRIlZvWCIWPj4mRRbcCltKPmgQio1o1VVzjCU+zn9xfPdzOPcqLNHa8aa1ePD3BTKYJGGEXRWp7bPeH2j/XbB9oPofFnmRZcuHxsDxvUVCbv5ueDBtowiKNH44YtO/S7TI+8B655gnflEFdrouH9MonUJL5U8tz9n1F5BqGatQ4Rne/groie8Ml3aPh/KPBQ0Brn8dy2rrEk/NchmObCPaOlgsVGODxv4fOy89puC7Ph/C/cH4eBCj8PbD6QBHajKUAR5dpaCPXfWW25ecE8WjDVriihwXhq44pXQbetf7CkrQdZoyffXRF2g/Qvdd39bR6hoqyLS+t3B3tvXwFuZ+Oqb9dh24AEYu8jxCFJESyOlzqVH3laN17sKYIXuH0a6xRM5UHf7sT+P8wEccJs4uenphKRhswnXderDOBcVCBv0Ok3hyliu65gtHk1GgTovix7pzGIkXX9j8Titaefq49TH6t9W2ZLIeRu2mFP7XXpYcRoq4jdRtMANYkgTCGzOeX8vjVXFBYMSAESGGGB5HkfyQFFb28cZ2E9TB0gV7bRfn4O3DVzXmo4SK6Q/H1T2rrQJZo36WHBaZYtjlChUinfNowgRhQkZ4gE4ZZzJueL93oyEJlGRqngRXTm1QkEF9xdf0Gdfj+nW6kyDkTSIhMrz+dXvD4ka849MDOeGM/h7/uSg3HcHV0zyBvqj2oE451d69fNgrtgkQz1uIX93va2eonqZh85rIsD1AIM9ds3DtyBr6tAW5ErfG2T8lZPjeKEMbbkYBW1h8EKJ7v/HV1kHdyzsm0AVPc3jP5bvkKCD0HE13dsckKa9dSHp8CutRMXIpFBnBqYlegBBqZFfoaJE0RJlEYmKuN/xJfql4fM8PIevCXibz0+u5Qme6hSea1FM0FUm/Y+LosG1C9ancKBk1Mm81CFuN53jsguHQtqYza7mL235Po3Kwd5ZrJ3Blch9XmiqYlCflF5p2K+vFaIvbcf29WK/bdk9wylDL0/A6XTXqEmMT/xeOfi4xMdzMBhxf5jrNytYgkqKHhYL19s5qrs94CjQrl4NEvR+qF/vnk9OQZ13rTsLfbDPMh+tC3YJTHb66M/Qc0dMKOfrS9c+vabaN9PCskXf12rZHFPypsrGMv+6PibZgWr36C31v8PmZU/rJjvjjEYH2JoAOU484Zz6YkidUXO+rH9TRf8XHizI61EQV8QFM+774XDbEQ/1WhgkA1PWtVlnvvSN/sSyAldBOr0Unc+79ujGUTXI6I2fPfRhKhH3/XvyiTq2QMeiaVF6yaw5SzetOix1QAf5cShV9Qra7JBbuKGH1BRswpsCNPBLvNnJrDUG0eIF1gIjfZWzj7f4L72hxjfgdISKZrClN0I0tvsIfo8ifNM8UZnXHZV7Pa7HR05dWxFxhkpfkCBm0hWTodCiemyWJ6q6BBib8pgdpk7KWd3hK0Wesmm7ysqijrWfHGMfiS4szOi4eYI8fMS9sNDYMXrM/r9ug3bFTntnyNrz1tHHSUsJudIZc4Gvpcl107zS4iJnECDar9H0tMlu0o21Zn3Sfy+sOsCPnC+ukHzYp8kr4imN7jRGt+Y0bN7ObE1dDyaBEajr8hfB2LyBP8DDeJR5tlO31kx23r65R8VJ6yStEr44pY/brIi7b3hHtdglhQaY7Ux7ganHAfTRkTV1qWNTmNt+iPiZdY7g0jNUf7gUsR2D3kWQ6dAUDEPgzvdT3Lc/HyvDt4wDP4wGw8Wj8bLTjX0Dv1x9ePfW+9oL7R0MN0THDOOfvIN9hWiuMX5PwjBUg0g65HWydKsrbVfHVIsJkHLz2tmW8Y2eH+3St9zKOCtIzzGMkLWFKgtfWTtwxC0edrSQbZYFEfO3s4MtALnwRtCW4pVuRe0SpPexTW0xVYhqZlEbKyOjYMvZWoHzEZWplW+HUju6mEffShkV2L9cpovD1BdWWzIpx3CxRc5AzafEf77dJPXT9pT8Tpa+HU7Vx87iGU7rpgiK+XLY3vrM8MFqWJC/4X7H952XDBbhQP3j/hMCJaidsgumVXXdrUjCJZ9x9Z59/5Sn3WTFacf7C8Xdqg/mM3hwvIUoDynY5DixilafRwA9WOE9uuLy6oEza5ETuYjE98bIEWD04uBRnfk9s8QjulG2YbDhZwGI0d3o7rmBKhR+CxUjYjIQLjFg7oQEDTCz8YypvBPfNpPV5uJFmZI+x/7aq33uQLegeTdZ4WRohjI/65B8vADoTHfzh1kNoEvIiB10BgwnXkHqrdbRpOvWIEzRY2V30p+QwOM4A3owFE26nXlEqJfD7vARfElBHG2pultDU9A2GOt4Uf+kpUv/vfiYGTZc3FYyD0C5IZXJhTvXREod2ycnhWWBS+dGxXUhrdyl+3VCTyOSLTvSFNDiK1uz1TvwfRu4LpmLIB/8xrazi5+30/7K2O8V/b24z+bFZ5nyWhb71T3dj/akkkdnaQpuX6sir5LP5v6dRLeRwd9bxrjtV7tQYTzSlWIYm6YmWeLXxjeAUiQvSUWpUoLYNUtRJr4tfIV3AA7Pc6J2gEoMRNqDLTj9fEdamlGXGqgYhbJKghcdL60RSHXWbzLPZQB0RK9j7ihE3XGMN0R+O+RqaM0Pcl96tEwYd4cJqFeO2GhaVxwA93bP/LYo4nVyUq1Hbbz263+VTK0ALhS1uBfe5WRdyH7FQcYMqts+HF96hIVujqtWQtXjynpUj6eaMGnVUBBgYzTNNOvi6bl//904RKVkWf863Gf9Wh12ZgEAmzZ4MlucxZUgBE2V9BifviWbFbnUA6UrGNpkCCgxYibkop7TOUg4H/lKnXRvdSTmtFZ9YUzUSATRhGMURbMk1yiJyUmZl7S5dOnslinPLqr7kT0eopmtak/dLeUNKQm2AwX2z2AekoyDnMLzqQVqlPV8fuMUDk5fP9vlYUoZZKvXGYR1ANhdvdgFrnwBHziaz/ZYTJjc4HuwFr7qN2GoheliBVDIm0OHGLfMnb/SRb7HSa/lx9CWoYwx3LoxZvXcuFgz3ylVBDusJAjSDaNe+xNCopGUNVDxNS1Jf0tL9h4vnYK52YI11r2qgjezyJB78VpSq376IBftpvyAT9cB1rqZeMmWTwFeaNNEWccCJGzeqoh/I8DLyhUCdhLBF+QOx4vwN1Aiiy69XZg467pYsEtus4TSYrpzOZwkgFvqWyoJJw/8PZhqxKhH0IhQU/IiNSnhm2BljbwN8yZPoqKnygkpj37z7nCHy81YpDaxBH/7kRbqnc7KSUVriwXleowrpTqSBu/jJPgyDa9YlhQZUp3bI3WZvUFk9fBJ8h6QEDZBu7Gmt2pOhUm6p4vfVlYryX1/TCzhOdHz9QGUn4qMi+Im4gVHL/jcUOLAYtD+Y//oDuL1k+sXVPhX4M0GIkNSTWT955t27fy57/+VWNx1mfYjvomNHxGjK9h5TuQioPtDUMzhuJQL8UlWBb8vFHLH7SPfOXdTMH4SN4i3Kh8UtPPulwDH8pH3Bj8+lI5fHvr/SUnkBlf8llQSLcAA/SOEeCooUyQ2/ApcfHO2USPXmkEQetomvPjzZ6iTCaWUzyuyKKssYMu/FopSLZukmOpXM6Y7mavW90IH6jugPeIO0aQHRQ83N9/Yl5e/A8RPmP11/3IsZjhfraKFfF9Q4dlLouI10tZEOIj+4/v9jo2nBiDj53mSB+O/r0yJ4RNu8/bD6zblQpYMcDN3CEPuJCYrBxbvCTBGURcxswQxaE/iYRRsD9YUNh0flfE5yO4WYNzTY1H6pWcvdNgpxYWkXB5s3JcfJOeQtQFJsFG/btLugSdUl8xhGAsGrXdwvMyOu/WJI0IMGtSkFpiChXYcX+s0C39efKbaDEa6tCSeu2Ti36H/8JUWimzmDXKbhTjQdR7Su3iHQdI/e4RK2MJDBYs0rYbc8A0a754oalwAK7/iNiw41M/Idamu3V6/2Jhr2ppqCycCByYSZyf23Scy4FQ/ndkxP2HN8JGDg3zKB/CgMMgogVW2Eq3WfSlG2Yk6i1e2wmsnmIa86dQwHRG+PtS6027zEecZDJOgt7OARROrhiFzjYg3ecaikLWKkXE7mYeItjKYVgwP7WGc5nzVyljSdbv0WsJFZJS1ZOKaJLdrVpw9iK9Kb1mqRAI/DharAxwOH67Gaod94jh/aIffC93Gyp7vb/YYtXYSzezDF+2nxKhBFnmDg9ZlEGnZaM3oCJ72ataR9lhDds0P/C8ZL6SdZSJgiRNkyFkv4tpUvjaBzwqf9BmMb6Uk7Z2+2xAlW50dPMGa/bD3s+CxaF7+BEhk5KLshdcSHk5i43FSMDpk+B/xxEWo4aVP+T3WjYLfN6kL3FMXfdTvOAAfc58BL3MEq/SqvFi4q6+5dZcCirpjLLGE9re+V+0ajysxF0z3xZhTSfaoBvEC5+ggAcd78e/MDjpqC/SYun0SKSx9kXioaBc2MyflKLD/CCRF8O5VwRNKk/LdbRjo6KtHTT3FMLxnRNAD5SAXlC8HDdrU0/fKfGosmLFvHjEAKZMUuegaz3846V39xt2uhrl6y+0havM9/XcqqSMOmPKYDegeAX3q03dmoJt61Ejp3tS1uPrnbRw3/Dd66MpCCm/fBkmcTXTiWGPMxOX8tUFpcig3wS9yrjZQZCLg/gi4sCo+sd7kNrkf4s6vvCXs++FYJ/ls/BpLdfAC4KRPSBDfyet8xnhax1+YXXolcAQrugODQFpI+0KZ8AZXO7TDOCN2o+a9825XHgpDf3cCDRfAToEYmMkD8spN9mhmqK8J0x2sYDwJlVr8gIvnbnwIPucltNnRnoQkRk6SVymYCdERqDfEMGZN4i1uKH2LHsdhVrF3ABpFIPJMMDZqS/JwAsrmFEjutNX1uaTuYkc7otlY0Gr2mrxAg82HJhs8GeWClSuYu5yLNnoOZCy043mXjylUcPx1t6H6gmMJI+JO185bxUM+6k2M45+CgL2krWMVrBYzOEhE8SgKd1pnln5mq2wqx0SGsdmo3ZUhpmG9lElhDEtJdGykxhDJFrTQMGYScVrsFLheo2FSClc67+hJaiIH5ScmCcZvADF0u652dV2c+Vddwt01g2Kh68aETuG0LNT8lzvkF+ebZycYu6/fgjPwiLuYWWIYa2u/FnLJNeNF0NBlSlxDQA+PWTXqubr23GyvSUfXjNQuu2Zkn98a3n4ezyDkqdBiDM/7QG//8Mio7gebxYdmhZ2LPPlZa2jey0xsGg0+TjL2pAQmWnfoySliLA0vSsAc2dITn1GM6AYORw6d2+cckoZy3uqHkKCldCyHpltV47OE9wc0cYImQ5MbFF6rF62w88KwC5nEIATFK8ehXWuMF5cLGAlEnE6su7SfJapkQW4LgAfMW4QHp64T7yDYYG4dDO43bRYeIDyTLgY7YvZFJzV+xEbNjS5TOOTscEE3iZWlwJ6HkOnGYxkjLxvQ4JTjox96jQSOWBms/6a1b/HHcjt/iPfUikJzStj4vkrmBJVf5tIwpJucbHZ01vzrWhyMZgUstaFYeZ6yCYpxCgmQKnMZ195YHrSZqMm2hlEW7StMSk6FWJuOLmX34N7rTEkEvECjf5ds1d4JLDvk9LPwvPEy4L7+1wPJ+FIQgqyQzvikUuwGdxjDPQj9txQ7whCN8Rr4+hDXEGLoruRpqSVAnF6xHqiJm6soJ8AHqSxARylqGYzokuBJNowsX7988khlfW6cZ0vs6KCOM5lJFIFkdBRb4Ri0GJ35hfCArgmK090Ki1h7G2UGvX5cXL25XmQGS/kgj5jAlBzpMFalXEbz6+97XXCKfa3xiLD7xIOBE47kZ+kBjJoEkbZDjmByZsuxH6RyMwHN9oPii4sUqSI90u68xry8lu1ni1qaViqk2btUpc2hYyvj9XW00cB8v2BFHqWge/XlqYPWmWUA6o46k68dPiaPjGkBhSnSboj/Q8s4J0ZiDerW9IVtdk8NzB1cFyFIbQXpmyFt+E44MLs0+t8eXK+3gc3RpReAVVYgsVvpF79gMF63EEA5ZX4QNoKR/0316KamVjj/4qO560yLIgjZYQzzwIt1tw/dTg1H82fW5rJY0wTMQJuunpKxAdgZMDtA1vz2OOXOCEp8k9IGXHxncnCQ5qOzTVbRUh1hx5iMM6PcxfakQgwObWes5lTNyljyOxb+XaRLLqsc7hX3i3G7psa9xagsj8pUZmJx91hzSjpXzbkvT1SIWu/4Ic+v1arqXy0vfJdLeRidB71clq/382uOze/WYx4bGPfOP0OQS8rDsJALeMqHXHfcjsRfeVF1PmYGMj9iDnLG6JqC+0fVkhFYsYybtMg81UQZOr4BZgIGPOP3Iq9qtn9hp9keZxi11CtwiTLZ9ldQMptMeWBtzRDggyi4wwbczZqej/cJmEdHcm7xalZcZDT2tHfH5p7zr62deVHDipsNwD1sSP3RClTQJ1kN451Tz2Ujg69Nmn0ke2pCwHPZRmxDydSsbFp34LhzXB2gnKJ6TZnPqDm/ivQRH6h9lxowOeRra7H1fSuxRC4qGRX5hD9I7tgRATeW4f7Z8MookvDZD6f1+O+M5lfFX3U/q8EfttWulTBeerBPxB+GQQSds9WbtEpByIn0JKue1zztgBzeT0aY5LpoFBRiNGZGc3om3/CYrbDebDkp2IGCwEjWqpLjEasQpIe5p3qNQyDHvqvurmitLJSG4fv2jguYm6dYUAipk2Hj+US05s1Vx9jMDwpMnRP1h9URWAbClLILbjwk9fEwtpXQjdpy6uM1lFemLbLKhbnWO4S1/81v2zDHLhcqcqSn5xTILWA8elAiBKYINCwrgC1ipTfRRskoe63MapYC54vSC2FwxV77QkRNp0HxhkP5nXwq52RaUyJeXInfV9Q6qkNO6kwIqZqolGtD1Sgbg5XioxJ4krzR3Q3Ek4wgTEbSlLCMQJldTZsubiL6FkOQGRZmtwaICCaowSFdLtZ+OYFeFjTrLpUqrWQCjwfht1MN7kVeVn4nuZlSpJnKdXA+b2kQIE2m4ciIiS4M1A4EMddiiXkVtEbACr1+6GSSSGw4zGoBZpDNJ4ftN99vIv0OoyOPrM8dejoZz2tKgyy70LOEti3pwmcgSQwgKBvGC+93Qu67TjNfrYE/NarN0zKFeWY1TUSs/2rDUZsfMmJsmVmCptlIQioI8izuVbOdu0JA/2ofSuJPFaHiI0EjX61OEV8Q1w3SWH6YMWXcMANDQeBUuhMoPAA5GYYNm4Ef+qUwVy/9pc2aHXX1vY525cLYDwGw44wkSIVlafIyVUvEEZgNMHQiL90GqU1VplmfXgz0g2Q59FzHr73USnOkFn6grwIRaKsKpc2dMF+cFwrywVRgzM0P1l1hZu9OH14NmfWZnzO97Gbzma0wlW0zFs5jyMTMRp7wOMH436TFfY0TBtkLR+B2XzsXsu+d4P2WcVZS/Rwourk8ySr906vxia6VsGMZQZBgFakmu1NyX82jygJbq/1Qz8cFLQBETq6PhTNTUd/ptcdvM2O11x6PfR0+Jz+A+zbGLo/fGvrlLwuZu/bzOopR3pCA62w0bIExCvMIUlB5BqLt8cJD0NBjtXXzfv617gos7Y4dNMVGWksmp9lQXl3AtbbAEZd5M2ZuQ+xnQiE3umG2fHXhRdIbj3NgwM4zv+UX2gHyxV/1WjDzPGT626uhkW24sziz7Pdne22zfjz5kyhslOi3dhouHfHjKRAGQYRBW5a+dNr46cLUj0Ihb4Ad7vey+vc1sWaJWQypklCNQdwenbp3w9O9hOitua0fBfiop436lxRNQxIEv+Rv9cv+lxh16bvmhGoWw8mlOSreLhEcJ5iz6ijtRC4gBJbmza5HCpugsiAmT/KX34UTKC1qcHxNSDGQjEa6Et4L7bL142CdZqMuTsxLNycMFRWAAtP1rbQeTiZ4qfxZtsqG8mzQrFALM2x4LjFNZUQNeZRDGQPYp3B4tXf1u7JwVSfPamxZnMkv/pIMSaY4Sd4gRGIdF/FqbyG9M+0T7SlYhJjLQ/RGPuwpj29DnBEGtoVNhFqcotqkNudjTWLTHxgHq/+T8ioFi83ByICOlsesXlAdDPXqUWnazVH3NFEx5AjOHp/sziBacYc4ilt+fVOlp4huzCMBZTJ/j2RsqkbLCuJb0xt+rTFTeZ4G8+qEDn+FBd2ARBtjfmhmtkvY2YiIFNQLLB6MT/yDb4uIJEQBiFYSC2FCyJ9j2pOXkDGVGdnYkEqCSwPhZaH4wlNBAkywcZ1jI8U0Rwe8s2i+R9qM0lfk/RKB8e6eQkEJrTi7sQM+OtE/zzCcXOA7gVsDMC0dkCK+A/tD9RTklOnW+EkoFOSTFIDapdPaGn4H9wOUWgQls4UoIrE6qScJMlrZxG0ajOlhEoAeJKQgDjJpIEyQK2DFoWae4e2V9qvKrtZop6y7WgEJobZye6G9HeySXaTb8g5EXHYFFvTY1k6WhkrIfj+Ti91J6xeqdB7/c+Fst9mPPzpX4GPvKW+XQ5wIIs+BuWAapUkVnwdhGIeVQtW/PKczg4PZgoJrY3SylqrP4ejrxl66lO1LihjTmXQHih/gNO42Y9CMA8jMmx5kaO3xwkO5A7XO8DT2RYvgwyb2ykv2J/bsRYpRAOujDMbyGsjt0C5aPHvFsVcksYncpk65rL2WGZq4dIl09QeSGUJbhdUheukU8ah+cuSpbPnPjHRTdFSYD5yB8VTmIl7UxDhG8AUQxAAAX13+D8WphmQmamZocEcbHaRP71VkAOvuIe4p+dsdyL4zFzn9+sNwjb60+FoEEyrtIE8Z6CmlECaQuiPFl0b69lkdz91URlMeLzLAFvZyr8mOxY5JMqbEN1gLBpfrGs1pYo35dseCqWr7sPWMxs+1b4nMXw5s2fnYkdg7ocQbm3qIC2EoP9QMQeur3zWnzFT9lbxIuzE/pqZHb/v6RaKFtNWCezMZV1axBzpocwxhE6Ez7gz9fkpr+q2C4Oqsaw7twOP0RqUBh06yS1oJupZZrJSFxuYkxxRTSn5l36RP0rRqpVBA5vrw2FK4vGJWTAeZ1jsRs0H/sW+y3eKdXFoF825T9oJTsNBcFaVfjhoZ6u8ypVYavFikrj8BfMbdVzwGiIutUTNRJmbZcAxXxlkjVtaFZePt2s7vLYitMRSKA07wrSzaIjgKItF2z86q8YoS3gj26L780cV+6oUZuG1RQmsWcIkVJPPm5slMewwVCzKFeW0A8RW7EV6fP6Y7kZFHi+UvBCdfVYq2IrRXwtVWw4NdWTHk7Zs7eZqub5elRhfBZ9rKWO3D9bHFvt3rrRoA9lpVLUKtO1fcH8u1VYzE9XFKC2vj7A611uop0DDsljdH7gh68oeCK+3VyqXCHVEBgESUFQP2sQTBmlhmXqsQJll5WUTeimvXJb7x3HHZ7or/Kl1YlZzJZU6u1kdyaYbopyQ5qBKYGLnnTwOsjA2Eksm2RwkvCio0s7XYN07I72/ztxNd3/8o1NyXGBnAPomjgmeQBQknhEc2PAaz3xlcVonkVtEcWfDpcEGHd8X85v+SEhvD1oO6BDD8Zjd+/a0Jlf5b3eo8oAwHAQtYeSOdQpcC81jyn/tmdg59qKfGTKTccupWJ1Knc7tc7DnUivMgYVZRoDjzXo2TcHaG3VplAi24BNJmO3RcP+iRBxCLOKSn/vzwrdTSi+QGMxPdeGVRxMJQjWE07mi9bzfyV61XeDe29Fa8ZynP6iVwrr/X5wysDaF5A40KjAfww8M8CECkpp/JjmQgD4ZbD1G5a1N9oK821qcrN8AFnKuyCrODKak0Fnw5Cu8ut60X5OsTKJTMUWmqc7hgOOTM1pGAWTm+wgaQxKK9JkJKDgzr8D9cGfEh7NroVvDoy2suJQmdcwG91yGFQORYJLZSaqRP4kl0y41afdGE3SaehCfurPyLe2gtB2/TQ31MqAU1nG+1tbcT3TZ0Fnq9bnaZdGE9MZnSOvVuaI9qm8B6bfNge/8WCecep3zjC/IphxvN1283fgd9Oei0sBghgPEFQhkEqL0oyx1jlpcXl61K1FhaFOdbxUrUeekAEu2mPdCag/OO3RQ/2orqCJeS/EwALQppLH7HsHIjpiVV1vC7vaiBiYr1dkixDXNbjOqlOsDhgJcZcT24XryI75iNVe7oNoUWlmuAWNZgYEFCePSqnSVXzfQoCLELeV05uQkbk2844vHsoMbFN0wRBJ6XbgMlSnSYJSDKG366F93a5HvYeLVdgwLzWi1aJQTpWimJp4Ep+/cf+I6ZC5fXytfpw9TpzOpjejuyNjeGzRBWQ/xeeUT59Exq7+JqqjNRSDnjnEdERjY3Ba2tiUBYjY2L0vnW9lHhchYPPFYBHNhRzfNLruK4H9g7Hi4gWBULIBDJITB4gjHcMQ0LT7iGu1antbZyFaRVvQqaaR4h9fmMbndqJy8nYLOEftzpMubv7esvETvEXyR3JddPWF5Zjx3IvFjYaYMlwMTrgvNL9mYt82iLaGjnbZbfnrC5/3c2wn/Zj5OnnYnjujL3uWfTQ8Yoz5fO4GYBwH0r64bkMzpAQ6qYhS5VkhXeBa6lDi4CiDmOaZV+nJyueol3UoOJ5r0cXeICYiAt42uOD0gEQM6lu6M1BwLSN1AwB/PJHQX7i7sv/ODKI+Vy+ZF2mOEfEoFL2DcfPet6KzuJhPucq0O2GqU5X3RRzf0iGHe37UnEfQSWKDRPU6m1MZA3rEy9O14zLJKateB2QgmqvEO3UtXGpEmZsC0+gFK7M+FgfNVPWoHTqyEH+e5s3fdmxBtmQMHJg007tyH47e1yKX7nhggyASx4NyJJpJs5fEvyUJnDI/M5wFwthmy43QvdqTqqp7w40Y4s92p57Ec6muuhZELqoaRCHOhkYkuz1SyPC4nYalooF6SrmeYTecQvvIVwqQilMVxQxGIAYv8uNMz28c76NjrGG4tTTWgMd9CE2Fp8odbcT0WzboZlJmSjK+3Z9BQJ+jv62QBULClAotV09OtLx7+ipyZPKk/oE8I12su8CKaAao5np5mLkOPBLOMqZlXz2aDmXXD0sT8phxPcCOU6s3adzCqw6s11z15jAevoafUXT/DoQr1Q9n4s1q2DzSVfS7DVZQc5HUBjyKMSgl183v/5bdHC2Ezxd3iqCfyy18fIvFbbroY69YqV608tMb0OUwwnD4QklBsAx9Ixwff2R08izV9YIfwBQcAWbTuyNpckGylVmUv+lQCw0B/Rqt4HId7OgQeVIuN5KeGtOi2POQY9kwqlLRWZA+75XkaTytIQ7uw8p8izF7JY7t8WDEH1sv+hFR1J4AGlwHxfTLq9GxKsMeBMXjjzRsQDHmE/w+A2FuvOOiYQMTf6GDlgEOF5o81tRVYmNr22lWNuLlvUdvozfmzrqFhk8V0AsNAdUSnuhyAvK8ADcmFgpZrlcW5IF4CDVBQho18O1cwL0VlrZu96vNh1IJmsUDte258kQIFtlKD1xdNHo1Xp7RKvl3rHUxvOLVupqoIbh0ktF6WyfHxGuYfPpKryoaihw0fEx7Uk4okBi3gvuiEvEqGMwdKU1EOQt0nAByzCyoI/ec2X2DCF1S0jH6XCHapx5G0wT+Se6aeNME5sy9JURjfIPJECPwKNjHYjgz1FKBtzoIf3tXbuEA+md4YK5gXLgvcFyLcSQgAbyHztC+QWTA2qYXv+hoHxm5pHjaEXg2xd33bd0WP3v/zdElMNKIRheMz0RruI1aA2GgM0gzM+sOmcqozK/0ChDM6k09RhclNxa41tzlD7vwaKziSNW0tKiT45pcNuAMuEZQayptJkOMjXPAmZXn2m0dWEjj9SkojfWbzm2d79j0JlWuIxhj37AezeMACw0AlRKOpDAE1L9AGp0FdWnB7nhlQBf5CKwmT05XmSuSE6a8ks3YAXuw4m8ktUneCFVm5KRGXL5DhuZCbVMYzgSTgWkPCjgt3vWbkyVOWRTsCJMA4brqiZ2J/w6/Ou7au7K+rkYDRhUgaLLIezBZmQLeYcPnH5zVp0/OMGkgHx1OULfGmxveBgQobwTTXCTLptburkiI3E+R9uQyzw0TfLuCvV9tTlZyT0z1PM93dnBKFNzIOvQQ0pv/caf2HsL0PRQ4kPPMkaf8M+7CqYFyUytQKOTGyKkk7XrTs+Sq/ZBm6xnHB3C/ZPtcNyuuU0a0OuQvB7sGeS/ZQSF6RTJKUHOrveaBObeg0As85AJwB+G2JMx8R2B6YPMQJW6ehqpBPkoEqShdFd1nzUQDDClPqTIDStkepHk6DpHUiBs+eFtQi8qMDnTa9IGSEmnNe2x/Tymy0zHm3TbBEtGWqWgVjh2D9PTYdmNz3TKshHBDELW/Es3ols8TAOx2RK0dliCCo3ldmVwLabyi71wMeg9wxl7TpI7Rm9te7+kX9iTFQjAyPngTRI28mYp+WhwYwJ5U0ksaFDNkagvrGI96ZaXrPuy3Ym+E73arUzTkKnJmg7iVWiD8mit3IeYG8v0oY9ZapxoVI5wI3KW02SK2h6nPifiXGSB4YC5HNkZXS2gKYlvjvL4S7101xUD2NUCe38pcbUDQ0oaxJ9jZai+9HVlRUXLV9gm3nh+YfjudsjHhThVx4EBhKSWOCbHq2DPTFpBC9DRo+FLT2LNyOzblJLQ7/KEMbyIU6fvZFulszZhPK8Er7kobhp5KmsgADYOjXN20v0eT0l3qYsakyTM6pFeDMMNMNmSpMUI7Hgwz4vp/wZ/eAhD0r90yrY9g+lPGKm/a5XADfPTyG4uKEV1+Enx4Tw9A07WsAg+B+YgaNeP1VPYP4WgQaGibBV85aH3Yvv22YbMZ1XEQelFvsIJtQKr0WKzuj6B+45Rfyq9HJHwzvb0ikzJA+YLoz59bBb8Dl3V6mEGvEr4lpaCEFT7WUTKhdntvV/OPrds7EfrUY2jeLaBy5+ExXzlu2XbRYYMoNLvxTbMQOb1QM8JBrW+pkRenoqsxi2Dnwq4FzpJTHcEnSyMzlzbDrRczhHkoIA0kPeHInCNzgShUuQIMCM9BVD7ah1xEp7JXuzcT8+zv15LlQ/JQNvOGrJqSR863WBZYhqoSxPZdLIw46kbUbEKhqg/0s+iR+TgGRGK65qzQ0k4eb/XuyerDn/0wTxbzr/6hWfB9qKEjSKo6Ta/EK+k2d0dDajztsb95kco6gNIU8vSeESU+I35O2osK/XADcgBeE6hMIy+6SDFHNmk5MmrQBFYjG64FA/exsBEqUeCQrv0wr3DVedEnrmwScn3awSshH2VWfP++PWFj1+8UA9m26Yy5NdV7xXrZuR9s1O7cqJaFLV88ihuHZiChZTESZPrSA6xlchNf21r6myLrubhTU4JyFMd/5SV9cZjXTuHJlWYtUAEYeo+bnUeA4IfnprPttMNa7tbn5r+BGT6DnorFgYubj8E+dhgQirCirTL/nKopYiiqz8R6TJtCqrRPazSB2ZueshFDuvjDFTprazI+Zs32a5HJRURD5NR3qOF3RhNAoNEI8hU3PNXf8DArKMVrK4bksr2r7ApmkLugV3ogSRnZZUaOY9rqdJ4YKwgaS4rhGXOcvPGgKyGY24/uJcr2S8xaGeeKrxRUDd3Jji1/SiZE2i9r/q+fyqwK3PmEta7CIR9WxZwyIlIKbwoaLiSz6W33br2NYcniRjUAF8QztMDZ5YV0pNb0bvlK7rrmm7WXNvWNs2kUbuX5DRHWv7qL7YYdOxKXJTGhD+WMrTAQHfddiNayjUQs1kxYScBD1hKY4TlOWFTC5QZgot9RapZVrWxbfW7nSs0tzhjQ3fBbDDx0vAnu3LREdqR1kh9kD5LFCh+uXmyfRU1+lwiB9buWalqRdYD80eE5meFxl+Bi0pXJc44w8B5mSYUecqXTn0Qw/DFAu97PfRNPbbj4QXxQ+kOzmqA5mHX3UoRvJVIGqdUf3CaX6EUYkqZqjb+SMWQJADbZKaNUIDEnOjyzHN6u6cRYqy8krqUGwfMQ7HJCzFhBmuICnoLYtrFMkipVZSIFq1sjwg+KCPbCSTJjWi7c8Ht62DIiro7JWzNBNWNE4lTxAEPmJhoaolgXeZ0oDqlubmUaV6NVcqzCisGshQEmQDn6TUN6V6Ggb3/HgfyoyVnGrYpAOZ9rtJKdLrCxxtfcGqdftIOikS0Q5SditwlRs0e3hiO36rERWcBjl9Zh5dKl4H+yxMlAhpTyr9F1TBdcsYrFO4tCwH97H+x9azhZADobxl3vLgk37KF3C+EjcRU/ltRBs2zSDqQOU/bbSDbLMWfxZ8cfTl3+t64yyQHoYa5v5vYHWTF5n/Lzm5DtjPS/GJZUkmy4OWpZ0ZcBsj3ZPxNpQY7l0coK/hnFJ5JNqJeJ0cbFAGFcHMoBAE5ZJXcZaHRcl1RUS5aVm5BLEXsnp0mFLyV7E9AHml7jzrjQV+2HCvvqV0oeaAK9cuqy9vIBdq19sdd66W+7c+cS8pD1b+Jx7hsQHsS9riVsuoFQ8chPAqMsy+5odbmZ6u0K/TdBjrVGlMVoDkCIzIaVT9zbHieUvrwMv3eKWi1U3xvvs1ICGHlvRHgmAXYteVhyrgpzHPUxECASy0QWSK8hBAYxJ9QCx0OzzYY98QFtqsO0gJJqNPF6lyIwyjoo5vcIgdByV+llLlTl0HW+4Rzgi2tla7qTZ5RKvn8kLNbmUM0lUrWoAK9MAjmi+1lozowZYrT027nJLLmvqF/7S+rK9lNre91gBuVEaEVUPRbuSWsWw04n520tvFFl8HBI+97ekwx7q0vLukdvRm8VaU7A3jsMdH9TLN8kF9mz4i53KYKET71RLiKDagAk+/PRhSKm3TTviKQDm0G7USLdQjiKVBvcQNPnygO31KAZN+MVd8TfzMCbPyiZ/FJdOHZwUUtAmIMkvW4lK5G4WVk4sRnZ4mW/gUXb3+4pr1cTloTJigLsWIt3kNcC57BBUrCit55hGVtDKVF19C8crE0H64HzkYKhgGi1LmBKqWyDHCwSfTVuLN2FpcCcMyn+O3+oWM/a340fq30pBNpxWiHKEbpKKM2K7TiysSFOJkwKlrD10g3gYR/BJsyGFSkBBmKshQdoNMdfKNX1cW3H/649XfuyR72fwxmyEWUfHnmW5BYdX1z0drYKSAqMoGPQtMpsAq53f1yTfkYKhim1UrzE9NzyfAid8vCBlWJPC11kN+YpFBcSgODcOFESEKhBHEiTI4YsQo7SY6XTVZ9/Vyq44Y+xajVXkdu9GfIIc/ZziSXBSSZaiVQqI6JGpor5bDNbx83vDswYIfUxGElrtmL7wpjnkZ51PheWbbOi3TQFPXvRVKAFzLrnLzYcGedQ1iCMLxG7p9HP41QKAWwQYSbN6apSKhHkQA+D++FZgqQGmzLchs49peK4btUS5+SgNhjdyN8je1DNf/98Nfm3d29zLoQ/jeWo2SYksf5Xx3st1SlyDJV3P5+HuzGZ5ZbjNszmenrwnHLti9pjVgKMnnsZXbQ0+7/6XI/tuY7YilV3dXP0D/3kdmh8X3TXbajr/eX0pvK8v/C9QZDX6p2O81o41F2OstW3OKu3g19ypqippTGntVZjwGpXSEiU6vMFyHmAFCt+rdHIAiydEJe84bjI43oIcSuZHOKDSCmj3JYUqdp2AoOJRKpaqJCJk+PlGIB/9PM/QPPJ30ax4D8oYCKCr9WwqMkvglkBeYBvLFGqpRItOoCcEPf+QppvtD/5jfD7z+PEUwLhCqO1tArRQfzTfceE5Au8W13mfcmFdNIQ/mbfk75b0X14a7bqwYyB4mbfoZ2Z/oZhiMU6HSTK/Lf/961lohnHVqRv4SnuIFjKu0GoClt2FO7/rFul4E7cXWYN8bp9tddz55Tb4p/sBm2NZzjRlJEsIX8JENvF6o/7LeXSxALWxilqoZ4VgBHmw/wtjz4h4cQXxCvzWvsmUBaABE9pAhca5iUliFLVGHOuCQImhtRU7W4oJ+vFF8Wb73isgoVZrWXyR1No+5eDjBcvoRVz0VnXHdRkkp3aBzQhbPWPnvJyX44633Ha4d8+x7fv9MKHbsi7nJTKhyGKmofkk4D/IOEf8HKehmmnHjk+XmwqtyDw1Oh2hNu6l8/jgMl29R4QKRqNmQhudrtkdUPNtF8znuJkeRjJ3HTQEK8wITij14KVvRR3xlUub0dDdlSKgI6TlRxtk0aRke9/3sHhNc8uDOTPO+WCcX8oAM8AbQ55/H/XiQpcLhPu5ZEUxdUD7e9zhteIFn2VfW0llA77U0dhOXbOR3ZNysHLLImJWzNngDJqUO4LdMiDMrSXHPpC4DfsML0fM1/wHp0Noc4k4b47d4b0KtJw7zSUiKIuQ3fhOg4l203enFhgmsc32I9puJhzBvJx4DEwzJG9d97/6aMPVGcwjfivJ/d43nKMhS+Lhj2RezAprv3PQipjV5+ZZ8gZ1GNn26Z6SrI/46oRw1Q15Jgps487yaHA/+nCzdXj1+FqeMVv41IqaMH6BM6QBjuiAv+H7M9N0toRPew3ZE4HcZVcQhJ1zc5H5OIscuw0dWiA5INyD8rL7BEiuxEtxzalbl5YbiVguPeTmBQr6Ex6Qf3SiglAQI7QORpeNa/Sf628hyDSeNls+VfSeuNGCm834NbirQC+NlJFVn9wArDMCAD/kokZaFWLlcisihOqlbMolUuMjXCtZ3vAGjuwgpiF0l28HHop+i09talQQuyGahDWKI9sjk7Dz1AQq8TqBiVZmNdWSZKERFBsZRnIhBjCU7CmxKFbmquzBNt9yi1L8oZvcZDXwub/a9c8C4pSfMtWGvHdO/aSXAj84vPQCr2MLt+2uFJvFCIJD0SMAykGER2ABzWKJ2L7/onEfehsnfedESRExulrlC+H42Q8N5eQKjLUrWaJeaasWoHAP6VEc2ZhWJs+lzRk0m31hitr9xjhEUGJW6T/h7TbJhRmCFp1AVcH/aMZZPIXGAx9zbB7vHDsVkBtwpfqYdpriTPH/QW+P9Dy/Q1OS1LGLkfl8s3f+g7Y14xjgHTZ77SyWrShsDMiUVTmLTBew323BbyI9TFTYy5BIA99UyjNxnxMQ+Siala0bRuIhh93AnraB1aF0QIxXkR2tFvDZbOrnO8PANXrknPvcIkrw2DJxKFaDWZ6d2dItg5JEjW++k0+vtqJN7f21DPVm0okCA0QsHO7evwWPn5FVYT8LgHzJ6Xa4eQpHP/T+Y/pTcHLhXsvFms31WEF1bAIr7oKiDY1mWOtFsBU2j89yKtTFhH3U/Vm+PG0ri7MwUuKnsijdNbecdnCAcM3/srY2XocLRu3s/+aDOaf56sc33QDF2oswkrfTlQtg4jv/zZSTzMo77i1MwFKgnRwe1x8eiuTPG8h7UfeNYfr1nYGcHbNIC8uwyd8v8bxpi7tewdJTZTVqbs2L7TQZnzvOYQ0NFDEgghBjOMEGMWSeTFIlGyIZRc7DakrZWO+00MmUwk3fsmEnhmNgr2EJakjes0wm4qilb6GJUkF8YAaZiotyuMDBkA2WnZLMPyl2DEoX3VplrH98l2fQqOPTrmXhKaUrDmiPJzvGpP5SUjYMxDpPjZP/Ksj9biDpCEgabtVnDjdhJDbgSdxM2JFpSpgGwPhbSUM8rMBVuzdvhRuGpuIMRBLA+OWyFvYWHUmNrfEH9+bt16jWpzp43oCegsfgC3qHSanGUPvJ477tC+qRdNuDj/MrPByi6mRMZ7Q0Qm5Ws8nMBbfC8B1LXdAN/879U0DdGqXNZaHWQ3OzGtiQ1lhjgY7ypi/GolhX6lHYtLogF/95YkBPa3xOlF/JEWSFo4FRWHKY0VWveUjJzxhShRNaU90d+0/y46O5ypaWf9ulppwxSyiENaisBCf8z99A5p7rag5T950M7doUhlWwuEBYdVctJ1IC/qj3p/MWPPiivMXy8/YoXDKZX7/jx+UMm6fM9Q8Zr/d9FDgAaHZXISWjAW+UTHz+y6oNy/wv9vsPWAH3p1K23rv/KrPo8uV3h8853L8ilo0zRcRe4qq2fDncMe+O278G7R7o68KR/AzfuePQhr+Ntb3OF/TuHelAcgUmD1A055MkUUleHb5t7pFx/ty/1XKZKtbCRM+PYkpj0ojeGMbNbWat20F+xMDu1Vys+ratu9Yat157R4mQyqqXfqTKf/TUw/Y/yCws9H3stBIrFEv+7xkdyI/gE/87xsUa2F7ymKyOmCsWCXzEpzfWQlxxfkTpr97n+l7eWrmYo1eGuggKyirkEB88Z7DhhRxbJNW0gFpgaPkWhCKZaeC770uYerTel79z9+lOdPjAoWOxHfEkqPf2oFmub9R/BiJq6l3+mGUC24AJXi+Fn151RgbdE6aFHMH0P5yx16x793NWBjk/mccZW4D6hxCUtTXXICffrFDAL95Bjip4v7XMWo9jR7mquohm7wCONuYXcExHNG+KIJQMxCQ/TY4F62lTheK74gC0+sr3DUPjSJGgSJlHRU1PPLehtUEBvolLPwiSpqfTcaErLcZBO5W6Xbpzw47878oCODxlH0gWmk2Htc//MYFS59TssI73K8c5pcXpOklQZT0JXwrC+KwSTm8l0ECa6XFjJnDunRqfG0IINZ6WaaNBtTeH6eDiOiTPppCLNa5P8X6yprg53H79XuiFWKJeQ1r4Ohy8pKrzUEaCo10kgYScKbAqi/di8yYWNmPTImRIOx1T3zOs522C4Mviqh/TPXbPbJua/KaZYjCg1R457Z/mKak4IJwm0x0v+pUP1kk+D8OKv6C5ZhcU7cthD0ygvhlaw+oNqRIP1e4k9GH/V3IxTcOiDWvKdH+6li8X7sIugtTYuvvaW7XvX+bVay1Sh9xjgl6E0qAqM5igT7GBv/B2O7Xtr8DFTx0jPAy+qtfWjj3ra3k0+d1NzrTr/DWZNmQY6BR6KYBRUUFv4qqZeNO/aZMdLb3/Znwxb/8+Un2xfiOcqsQ9pYpADZrpLnbv7p2itRjMGSvuoG1PWnkNjKnexatVPLNkHaeeGbbuKL0A7IntD6sK/uKGzm2fBHRUtyJ81fNwg7fjO3cy/97QX42Dta/fo/HM3g2dBuTPS8S/MRQ9tNBT/siA1akpggNh13Xcs389iOr++GNKhZSrPszgmCqxXm0Us2jJrJbo/t20IZdcNylcu6RGXnUfH5y/wAgoxMd5PnNdeF9JGlP08tMGkmMN9XrLNLvfkNVELjmmJATA2rQT3IZMawIAWWpT/GsbYqpwmcVzZXYcbRVIqbELd53OReCUHJsopoek8Ifc6ehzCwtp0N/6RoAeDG2azsy/UMxNrhD64UMcQ93TTnGQd10GToeFtAq6tcc2wDWC+yR/f6QA/PSVMuDbsrLxMNfDdDNHTEQ4/hqbcOppfiY0LbyWm5XMK20IkfETmPZOg7Z5nIMBVm/vrnCq33l2HtDclDx+HB0u8FH+IUjnWlkk5T1PMNDYoBGJCiS4TTaq6NIDQAK1d6xPHMVbcAHYkCx3DEM37Y1+yVEb5DBZ/tlDjCX9pSLyneoGq6TIpponESRrnIBd8VJiVociNYaJ5jWVAcbfH48H6gNZeRkTnLZdTgRoaE44S5X/V+ylYGNctR8ulnTjZ2XDhbK8w4RoEmqC0J9pCU26wa41zP37vf4+iVhw/vbSyf8ibGgUtKUswJaVIg0nPrE1FOl+liY/+J3ZOUv5kc3VXigwKh9mxetaNWD2ljW9C7Xd/moqv1jTuEsHjkVQ+jA+WI38wwpNxVRrRL0XAfuO3lmQkQVGVuzgPVZGcCKHnRwKofdMlJ36B0gusvXFZNgtaj3Y7TkRVOgKMXto9I/4iSn+7e7K20pciY24IGTzBmYRETmUS2pfO26bdiDota9Aql5odrd12FS2UVmk4nwjXvJ4bkhZMANYaqoNBI78ZTaMcGjEKQSbHBKo+uxktvF4YUxqjEOSs5GgYCvCmPkhEM7O3CKssHC9dztP8R8io2zfRrXl20wznEud1wXyCooGZ19yfSqs5DpQD2iSr0TVkbPp3LNayiJdRq3/J/m/KSV+f8MGmDkyYdG3yCU7XscfFB9WfF5Ht8FF6eJAHAMKEOl7epd7dfI179V+WfzHWsIQ/8mqXXZQiy+r9BOxuIUoXGT+8CPB+wJnjz0JMGbzErmPnsUAnRq6NRLmYMbs7ZsjaF5ahdaBXpX4vPiI8i1p+u/CRvN3iZURvxr+PnVLR/tvHhP/3nAk2B+bEx00kQado7JNS2H8Js9dRH6qjP3exol+h4Jc7/Pm/BVORnTSjWmp3Kswv37uW/ASWYt04yqADluGLPg5MAlq3pA8GfbN26yPlJeyZ0sd7wRfFR77G0TGhgAgjBaIrQbXTJN0Bl9HseOlnleCGlrYz0VNwdtUCxplq0i6Nwe/5zn8spGWaokC3aICAVkgspH1OH+h1iMN47yTzmkIfmPsXck0JG/FR9oCjd89OHwqb0IicVNxygf4RsqKu3N1VPfyTPm2fWJ8U7GCiAS2tveAnqnD0SLMB7IyiOdjmnY7aNkXoVBXBDh2gXiydLOafEKg2y2g2tIR/kFC/sO2kXenQnDMZLpX9n5cIw3Rxmrq/5JQ4S8TFvD+cmyYvgxZgSnz9OJs4uwSsPja1txiN5GLFEifz2Q0qsJec7sJ78vZ07WULUfx0YuERJ6mP8W+/MNUXq+rV1Ct2Gl3ax0tFSfFfJfTbVI9y2jl6XaxXWJeagOI5+HJVfT2sXBAv3aHrC6azh4llqvq6DnChx3SD+It53GRTGlH8nEIF1CmqcNYxmqM/yBlLOA8WEcIueD6MfSEBOlaN3Q6o/fXSk/ei07lyIcbKZrhgBrhWiGiN5YkuJXONhDf7xpLQ2Doq307mMcJWhBWRUtCEasPxiSTltDDMTh2dvqgUUrmQ9c1LMNGIjTEyaoHSfWPwgpOmVZia2CzNa3rsnQJu2bk78qtd5Ibeizl3bMpcjyWbMkSKCOOM7jXW5/E/OtAiOsBR3KO9O6NquY0GOkVeZ0+cE4vsJb6p7vW3yy6SnYsB5pP8nE4n9t9lCHnMc/mcSxQDk8OhzrLQX8rdnW0VKf3EL4RyUlHrcgWu1nLuDhBQiAi+Lv6YHLlHPs3l707f0ze2JWGifcch2tcgBs3LBDaIvECcgl7WIhYtfsxv/R0SRXtYtpqo6YRhzLQSD6pTqM+LycQ4ODIwAa40IaF38t1928c5nscvOScYz830rST18kFYrm924rVd/N4d9zDgIop0nYKvSykrz+2P3vTwB9RkoZa2dbpfhkcJwlqgmAz6mV3XQ8ZFudNHJv+eBeQmsUCHxbx4/eLRxHk/fcfauqcJywZCYEzpll9XgWs3t18Z/wMGRbXtsKvlMkswDan2IC0KS6XIlygtMxlaG5Iga+yLNP+n/tVkluS7Zia3T4+SQPtORfFRa81QD1g1iKKVeiW6tBhmyec391NlfZ+INTbM7PaK/08KJbR7ubbmhqpArB7pZRG88nMhuyugbMQo/pUv26S5Zq6MKs6cwz29GGNrGmaFBl18cWBUJPKInJhZJJAsdUsD7H97ayB+/10nwlcWXyGCRjX2No2fj4pb9C987dGLClC1iORPfF5Mbuzt4qwRfy58JMpnQlrNRyeGNvEHQ0BILLTcztcpNnMTHgruD1GOMgU5aTU9U9Kq3dyb9GpyKTZNz0+0Ca+CwkLqjwEQqjSvID26KOkK8X3Rkr/khZQpnkK++UJ8sPzC07NGM2sv+AmU4eWH+ypb9Heedseq7IqSyIUCR25KFUBqu8ZxuS8/W8jy2VyWZQlFrkfYd2SUT4MneCzwi9Wqw5i1gBJPHTBC987jzI2VbM9MGjpetvjswxPiYkIAYg3kS1bxkvl0RsbOmlzU7LzVS4bWNJeW3IZqVqlPkXWgTnICs3cN4UtJFP/tLsioaTUqnZWuI1vmxDldr6S+chZO1lQg0AzRnNvtdgMxl0kY7Fl6hA2yB//NiN2p+guVG9rMFZtPQIHcWaoi5NOKMLV1PgqrqubKAScPTCAX4TX3x2fVB7g8rnigdOpXKvAACjwjr1ylcs6CEjE6u8rkDOXHupswPZsjNuJQpSUMavKnPDyACnfxBnr1y2gkyxA5SmOm6gsik5vkm3cYnYQgtW9mZcsDNTN1RVK5jbzj8e1xJy63DpBqmcR8HqUMSQ/8/OHSpTdUsuGAwR18hOtLw8CzLsbCQeZHLuPV5ePu0/4o69ZUPMW3LbZmdWHKExliPrCNwdl4SAWm1QRNqG+IhtQotO85TWvSZc6mCPnpobIfifQbYkANs1b6/5iKR3utJn7X6ckkio+em7Id4aI0oc0GNgd7R7WQiJhtkRF92Z9U7m3r9A9VMYcz+VycCDKe5HQE/Iq17nmrPZBPbCylYrG18w2c7NSKMgq0BEkxnRR9CdqyWD/szjNBIV1br3VFnT8vulDeAngAJ+Gvh+TZpwX653amqBF689tCLaN+3w4OfCtaDCwi1jxqPvpQVFe04zqvEowD5AcgYIw7kA5D5IgZ/eCPHfPhTE5VJfrxqTdC4SjqqrsEyRybyeVijnRyhab/wJCitCRg5XDS/EzUM/fRR0IpH5K18/Jr6m/GgnSJPvi/2rHzBXO4YTllfEYGf0DFZP2vg4ZXNbU6Nr4Qn3xVmalZTmA00nvWfMqDYTDwfdfXEKHMmx6H6Io3/eEDGXe61TtuhDwWjip4IHahkeDsUhV0LVsAMe53ZiJSjMgo5xyWbA5ZcMIZV6l5cvS4ODK9nK8tIyKSkNRI5MjukSqeXb2CBGatGMy+6qI4t+SO3CDSesX5S8vUoLV0bzKYCfn+PBWWoHLcqu7/NN0cSss7rlBD4cFv/7Rbj1EnMC3t6DTVVCLBI2PxGZ98dxvH3fNkBBXa0C+UKFrbY0eDePhMHpF8E8aq6dY8gnlTIWUI/D4JUHgXSEtk+exM9jeAc5ZNPApafw+cfrkuUvLSt0d8Vh+pakDV9I3P5FeNKKZnLDmvIiPmJeZhcOn0yNouRbggFmvOKkxiRBQhS1B0Em0Ck4KKs22ay/K13jqcbslDY2NskFGYBkpasowUTNOLZxLnK94JQlv7oemFZhUigzsGsmYKy72M0sCa5/dTGhCpw2GMwbKOBKMap+GiB043UmU4RdE5aTFBaK6155C08aeK9YX+ZA+34c2Pg4VD5r+Sdn8d7348/OafZrfQpvdeL2FUeaISk1q9BV70WpN4AFusfvRbA9AsE5oDsiC31JxDTZlgJSy3PUlcv1PuF4scV0Lc6GZW47uFJx4wlPmKGm2Lte9tkuMiGhd9dE9nAZvIpcm+YJNjEjQJV2MSbJVmYerS4zE3fPtef5FZ9a0EmMcNt7fYQsTLa3ASwiMRii3OoQGC+y+hvs5TFoKVX2vdHAI4F7RqswKauTYWRS31caQkA/LxNOTK1ZDDdFKuE6T3yAdJDEPRH/JeDv5FuQATzoWFu4tpc48DRowpZEIGMuZgr8JRg3JtAhG4T8Z5E6YqglvkrxlIgko7Jy4Ol+r94I2ezJUlM1L3V1dn65iCeI+u/2A13BfGjDQy6JHsLCaxsDRGNzxKezBJ2pbOof8/KgLhjKEYLXEsPPVwojO4/k/Hc2R9xxfULFHAdyIYTt5RE3ebeuYLQCNcOumSvgDzIXU1dLTgYYztqmAS8kEf9kIvbkX6xi37t94Z68uX7t0DzxLi4neVhusXuLNJdjaoUEKJf/T4pCL5crPv7cm5n7ENXMmMbz9FAqVK8NSHevB1bs1IuFgv8zZTlj/YHQzUKkgqTAabWELMvI/G9Htiyqav6VzxTjupakme+MD6CadQ3NQ9q60YXK2TyzlrcM6oM7wic479edWJ0QCaQSC5rOABGaVfus/lDnjh77lH/hrh6Vi3psJe+V6R56KuxRXf7Zt4KALVirmXX7zCESFcJKt1YGOAidPtf41SF6SuLslfIGh1g4hkIhsJDI6GQPU6z/qyNoHWhnpEddJg0BgggZj8AnghYsRwIUMCt5PR8pjFf9RdEfYc9n2ys3VtDFhlBJMuGRM4v7q6/hClQ/d/Zo2kvKHBKE/ZkM95WFMJU9UEe/yFhIR9lHNF4zpempZ+Lec3Vf7PhwFHwAkxSgoYgVwLlP1leuvZVg6bBe1Ww5kbpTUcnjstZWiV3tjJtdUpS3ZDeY3O3OJ1zPlaP2/ytbLJNPsBwRPvSZs1GqcabrofXDScVf8ngPBXx1pzpW0uaqzQk0gbI7SfYflPU0k7Jx8t2sk8Mu1d4llvN5p1jWgOuM4Sk014813nIzfxYp8++7Rtarmm3SP0bQduNru0uKKBOUqSeemKBYDKhBcd1kRjd9inArWwubAmqHSQG5+ITNWKJHkTIzFJLE01sBOIYZDLIW2+OV7qjiPlc4YSohAjlUOcZE+9tEtCP7CaXucVL5HW3X1iDsQT+ipUY+irgJ5lzxTx/tzD5z8fqDeNrwrXJTf6u1GhryVfYuRW9ejiY4eSpBZ5CsDXjxFaYqdrd6X+0Ur7hyVPilMSlQmuYIZhDTaIQeNkC6yhPuLDASRWQhC+NGsCVIPNr0o7zZTz2Zi+DKqt+rvxw2vSmMQBwJpGE3QZ9gHtUwgvLXOAz0TG84KtUIR0T8PrKeI+Fdvwe8UGe7+ceQsjPe7mzTPeotg3d+YcTA85NkRCbBxxZyhiquRorn+X3r4DhTScGLxZY9tqpiE1sY33L6VG15U0POJO1yFv5d0GXEWbb9YjNDOKcLc9eQrkTIBiEBNeGcucJOW4mRkFSGjwoLOMCWw4DgdgRXmEVDJlKnvAMyDnQclVg5NpI4xQcdXZ2r8xjPPSDYxM6+u3qy66+MgaVMqDgBcVSUxbVxZA49Mz2wcworB2e7uK7LEAUL29GDVUHKdoxmbHfgKDutQSwR9fNpZE2nj/T9z1wAYj6mA/tMzxzW/5o/yiYf/v1HDcsvqH28+Fel7Rxn/cPY8W7PKPfdb8Ra5iWeqlE0vU3f3rWr7vqyoWuNHFSPQ4xBGwAJfFjOMI4m7theUMoeVXTGHSA+cYOlL09nWtokP2859X0xcTXoqmvOj//ureWAlnLqKQw7IblH7o9/uRf2UyTNCZmRt+lLCmSZ1Z6O2FOZx6csBDnboTDCiDjtd4fMBxGzOflrVPvgtZFkOsipKEhYXVy3FdK62QtCvZ/1Vn8xud+q+2R3e+0Pf82mxRKI1o5uYPaW6SE0pZ3xqCKvqagbiJzom/WEJd9qybGz3wNvol1jourqGGCmomALF/PLee6TvlC22H3qv8L7cM+xsa6M/4kJjsDRPn1hx/HyJeX7/7rfScg4qMaEGmBfSJTCCLvVKeuC3+LMc/yPxe9kCgP2qSJ8Sq4IiCLYlC105B4JoM5SfnMMg4SbUNxbIEw1UidAWxK0z/icZ2hfSrRBvk/DCltQjbX62OfMq1xfm8OJ5PBQMLJJAkKhkylaWdVqcTxC7o/djg1MHt7iKqFnQUQiIV75AYxbDe6A4gTkKZR0stq7ed5AIz9dN7ldwOnOrln38uL1/gYxakSbXO0zC//O3A4nelZbF/XNdqOBeBFQJK73ERSvI4T3sYPVcf41uGTBXMfWLyVsJkr/y6PSDaiPdi5fS8BxisHIXsU7DHVOhNjrbaRojgLLSCZcbVRv+W5/Sv5s2yp6XMv47waXFUgvx6bSvM1Zu8cxr59ZGt0o+44OuFxLxXGos1SnQQxz58nUd0CIOuIAPpUTR67RQsfSg56Asx42LjIRb+LmP2Zl5MFIHuCyARSIFOE7g83I3nKqlAO43cdhjKCuZK93KfK9sZ2F6sU7O6xfIk/fX6yJxa6BnFS3qv9+L+bJ106nHPApCd5OZSLmzdPODhTXwlreaV1+154dvuWF6YeexE6lr8p8wuRE2CSj1RZr7wM8gbFBI51Oh0ny7WPTs+7zfeqacEFqrl02jCh8K8xEuh45GuBFSAFOXaJpcUm51aZOIkSVIKk7CUgzOgzc6uodPH9x2fseSWc4PR7r3RyhhJSwgeRp+WpF73wMKoopXhdcg6Nvli6rfB3VmVhV1QJOvLu9Z+ttEWG2oCRh+jbPgcWo8yQ12BcNJ865cSFu9uGBPvpLWn7hwwrLTMl6Sjqh4BdIoj5sipT/Z323XcFsgf1hgFLHgECJ3BMKbzYEPoXx3Tv/mFWAqohz1hTuxsyDBjrpSl976/B909tDAlTWCZw1xnqeJlT+XN4Uyck4lz5Y1NslWvUFI+8ZnvLf3MfQiYRlRwcwx2rB36nWaGEUeHjT0MAI/uWbqEjU87NnFAWYsISfz6or6d2mqxr6bQBC+svmgG0mRfLsmyDGor1JvtPYwhHjQ1pm3kI8SHnIgAG/PNNUucMEwof4UGmAC9/Xjd1C27onvzxL426J2x2iIHUXMQpk+NVs9itYHpmKaIOgGVUMvQtnPOZTO3WH9E1n6dbC+UDnxHv7Vqd9/KuwThQlYOUIF/o+DM7adSKFpfeHCUXAlR5vP/Pb950wGPcucf3su93P7i7Zd/8tFx93We00/5dt9sBb8ANsLZ/FIPylcxzOrGU35zL9OrGh+tgjd3bBxRAEC4rzd1+ZWWg87RBSsCq2RQMS6qDsKulGXcih3CyhM28CWTNbPgmrCPC3nKtPNOq25k11laWTLa8Lkvk/NNslHLRiV60p49tOky/kfrKFZF1shJa1B73vBhMXLcm850amQ+fXQ/zL8RFSeMZtsbJsHtGDOOZOt0Gg4cWdwdyIMYHGxUtQfo6olSiYMNdVE6nmsDtxhMX3UyWDn9OevNSe3TQdQCPI90SCW79zkxC/Ns+B9oS+BMZpl5gY1gKdNN5/GHT0Qn4tbZy0ICMXpUKqmWpyl0w5pPpQs2vWGLmbfy77JAviQymEIL5BRopCpRy5RGcESqkHNAmBTAAZQ1RtCC6aKuOLsCkrwaspnVy9xumWWbYR3pZh3E3N7x+1E9/If539JT+AD3wCzQ5kfQnhWgA4+gfbNBW66idcITRdmjxYB6eKXDi8WTqmtexZhUVGs9JIIDxZj7MDPjcpp9A4Fyty+Er7jcED077r+//p6WV9wmdL87RzLhwv6rrkvEhdPxnSi7fwV1+6a3+x25ubsqETt3XlqTBXwiMLmT9QsNo4l9XKSxO51xwyvwSWoGIN82XnyvAwzs3i3Yu479pEEruE/JFbNTZ7SGx653zGJf/J7Ryf8slf7C9HIIev0m2YQteZxT3hVdsYXh+srXN2icM+AaunqmL5yLAn1kpFhbP/L21Ob/I6zL/gZw3NRZ8kcTZoQccmyZcK2NU6J2qt1AQmJqRc/M81KV4tfcxRrmWH/4ZJphc+fHqrckXi7JFZPcEi9x1o3JbpkbwRmMyfSwrAa/w7pkGO/zKpw0zI2K/j0oRKl/NHcvQuqsLrgLriOA8gJIH0O/zOxpO9KpfrMLBjgxipBKWZJl80GQFkugP8dmcvsymVGe1NNO289Yq2/obOvhl79S87LrO3mH3jqwR449CVBkdGWDxitK330oyXpemTMmFisdA1Tjy0Jz9PzcIjQgCJC26uFCgSc6t8koKzDbD0SeY16VVktCOtZbNv49sLEhAhK38B+KPytiA79kp/ySbjqcOeI2C5Qduxd3rbCoMIWYi+bgxCvciQ9oc2FSQ5+D8vhvNd1lSPWBrc9/cmd0iXGjZuVNRRRIHRLGS54e00i0heEqXsKye7JPWtRkYslrD0gcuQUaihX1KPf502kerzzB4IeIFtYTprNlrc+JnETeQ8q6rou34Dvh7BrQh5nDteXsovO9Fm24b62YFtDf7IEXdaEaKQWppOKHLlS9IJ8w5GQGMhJSJUV4lI/QCFeEzpNLMYuaTr58Wq8pe2Xj/aUZZjj/uuEYFrEXoG7oERSIl0AEuERFQMQLBFyj+rfOD3Qf/NQGnKyA0v3xDT7rI27gbxEC0CezOKW9f0esPsc89NLupJ++LDMCBhEOih8ZvUxqyWIlAo9w+TTy5DrQpdrUg2M503cYHW6IrehM2bXyyXzSPODL6XDNoUD/Ya0Luvp8h4XTqKA6baavAa2tERCjXRxCEg+bw1q6rNX2i18ryLJLLHPTdp3AEp4+QT7rVCWvPCtRFHdCg73Txj9/8LDv/BKmK6qE1Zz/yE08uSqljzdZ28t6ZcwAj/IWa3ixGbmBQt4lozvKrvQ2rENSczVuiXGqTRac8KMCjW7NkzCjW5M8Wg6fUIyWL3kCk4hce1ROklwxH9Yo1exOjDlvXIMtmyx0s0B4ntq5LGD78hWdbkUfe/XpH2/n/qBEq1d8e/77pNpW9/CUWIypfNGBAE3+UFABxLneESDtFktvx587C1Vt921Auh2kJTCM7ojtlOqIJ2U4JsqhAboB1nHT6PrSCcCgBUkwlIEzIbcX+6VdUaynGN9gTzgWowk4gUazTKexOu0YaTY2k7Xd7QJI6fvZvXnGSPMvppFZq8VHfYaBe92rqoGh8A2rGheeUJWfH5n+6x2tIeSP+x5qRB1cMJmBRV+EuyQ3ScoXXe4Mu++vaumD5qKXQmiEqoIqmtZtAE+E+zh0Uqxq/sxy5svkTdrzrXpMm4CMh6VKiIZcbhrf3j8Rrj0SGjyu80q9vt3Z/M6CnGVKCU9F/IFxTNzgXLwg57aMaUDXMMCuSSlJiBGogZtOjZBVfJg/W0//UL516VkMXmSVBE0c0KygQK8NTkB6dNG3pHL0zxDD0XO7eL0A3Dzw3SMUdgAD15b61W9Edm5Up4+FTzidB8NMX2spzMOe1miUcTMfz2tm7pzUuHk5YVld0rKSsaZmaqTHa5aCKW++uy+HFQTZ+yLg1r+qd69MJ87nHPmEycVen8KrN70f5EhhlzLIMhQEWCj0RYPhMtJJQ0mjyeJhzJdHPXKGOMTUJHQwUZDOdSR/g6Uzic19BqWXt6ZGMjvD54MSwADgArMpqi42oEzBbl3dt76kzz7dXzH7ADah0UHUtLSgdmWaZSrE4i8nw+Gya+5753AkIS2MeF+bILRV45C6pdb0VjvMQ6j+atU4m4UW8PVtg+cCxTNxLdZY8U5G2ElruU6mZwtFF6eOV0ULpPyDipCaMkdDoGW8+v0+cuo3F3oYvFW6fwtMXT8iEuMMIaxpVRLoKaZIy5SJsuGBMppOT3LqI7Pdl76AiyX5Bg8ER9MCeWI0VkMGQPkXqcF+dtylZsJQSReEYQVG8DIVrFz4oOw/JQS/Bg7wdSkPG2Bdn0z+mNDCU21BdVDRVnPt3VWXsFlI9/0saALl9glVEt+Rcc9ZSoDu8UNgbtPh364fnDzO/M2dYMK2pVfU2jaG/CIdKTWIO6T1EKImygly2TdwNuRzYMvc54q6ZkJRx6GCUaEyP1aOGxUt2NKV+/Spze8WtfRXPf7LZD6TsuxC2sPZS8HS4PwiaazgO03nbemtrkdOJIULYGENCswvDLVD0AkQo0Sqthpt2PC0q1+tW8Og4K0mhr+QfIPNL+OPoeSGtxUp/XHzd8q0Gd5QxcIoWorkhA66Cd8nuKnIIEEgF4a4UKUqarM8EKGI1fotYvk1EtlxGjsW9DKCsjOvJ5gfPn/t3sBtytnUvku91nHtqF/+tj0NRAhCLAYxXlB1AQslWGLDEGYa0kgBxZM8XIqKbHPNyMqlwH6I9phhRiF/iY6voDhARmaRtvy7eEvI77QUy7fWdveJG46vOfNTbw94GO2EeN0Z7hAIR0fEuPN3oK7bSBF4IIHY2yr/fL4WuQZMqePpoHV03Sf1SpF49gTmut4INHyhVQdQyMumzQdiU0KR+Qe6MMCZZ6UmXEAmfEB7V/WssVrV/7iKLDcAAhxuzNvw6R2Yhq/8rhw+8u/IndLs8o/Xa57v52XHZN4phlbRjAW/vhUs1e4+BKu73cE4vzhgqD0luFZN2Td1tQtjBjhjZMtoSAv9AfUNVqZGEYo6DlqTDpCMqEiNoSWMSRsemYFIbAhEmHAooBQkOUU7RDD3xiqZvw68N8FxeCX9t3DqM/YI/fxMCDViKHDVjFbF+8SwhcSTelPiTPKnkAdN2R7Zj64PbHwyv7529TAQnoxy2xnT5glzuWmVuQl/maTe7X5DJsYJm7XT1+a9jb/WKZ+zs4rPo1cwfLNkOG/gPTxsQ2X+kKIRt8sEx/DpESWqbUUOecYCXBk7oTbWfsbAXIZdGHd/ggUTDKTPa4mOkz3spSo9aQL2nMjxLyZJ+LDBG5Rf/KYjQJ8jLCeLRuTvGDS34e7a9QVWeWQQDaTrw89v8FydpVrcTZXRLmmxiyZLGXOd2LPIFS/YZjaJhR7GSGVoQoZwCiphBaGuVWI6N2rVJf1/Ek4pb881iDc/mJ7Lf3Za/a9p2w5Ldhyc5DlpvS5OYBmVxTZyCZMp5iiBAOkCYRL2uUlyu0AbCTj7YlX6pSAphuGbQMsZuNhu+3iMv1oMmnbdN1imQ2fc5nMQBeOfjsPzX5ph6CZifR4XNx218ulRtauTuTsUFjFUoCJ6AJE7kz39pV75Ak8G/6//+/vWd684bdxvsgM3uLrIG0RIzgSkgol29u5pioS3HHSeJQG5hKQIUhD1ATFnqWyoZeexSl6+O84S+VMT8HgSwxJkMKq3JqIMdIGJOMRdw7HlQs2Oo2h7QOwqcVEEWQbYwIS1hnKhpj6hFZMaSTLojWzCRNermS/poN48J4t7hK7Rbt8pFE62+kQZpYZ+OvpGI5d0oeuX3tO60KpWGHVCjXqoKZ45Zbc8SDT+vvKdiIdEtMc628n9tDZv1y456QDB+ESSgbHnqXR8y11/TbnJ6p+ww4B6BwZn1JTtWbvwdmx9YOgVklcQAY81+uIk7vORzLbsOTqqaUnPHByDVTsatzqX2pWoKUVsZ3RNet/THvumnnacztl4Qnc2qaGc6qSAusNg2XG0TiuoYZ2a+towvIH/KS5Y578o9l6Jr2vqSJ9f+rQQOuhQOGeWKiI/+T4Mqj2QzsO8OfWMcQUwrgNsJeexpOgUk0t1YTzfgz2IoDhz2vhcGCXHeMMAa1BqqBYggTIqK1nEum2IKPzcPfwpwkxElMWI8stUW5UYuLtKonhAH7Ko/kRA/gox7CxxSyRi1uiK2VTGBMwBVqrriKjoV5iMOhUZwqQPeyEub9EHTSZhLdSYMSUClK2p7Zf2DBWecfRxoJUt3Pjjm3qbj66PTMtyp2nDC7QokAVVR5WoWw5j6L6XCqSEfM7oJfIFGbB21r+DkesIqhRuy6MiRYoiLSqVIY3DBA0YW/QWvEMb4J0jItouOF1kpEAdjaPdolRtZHlUKR1uVKHJU4Hk+yum8P0EmK4cx9p8HUyU307SRszxQvyoJw+IrJlqvqumRj0V1+HNLXc5AhA56AfXXhqjq0ghdxV9xcBXvDpmbYdaqNxdGdcXvD1zoHtr5QP4/QTDuAyx51Cw2k6GW8NyEl0EkqRY2wCPrYGHUrW3Xy8VPVO6Y5Qp9NBUxkh1cxKlzcnjpEqvmECbYVK2+wMMBgBTCH/hOHwjrIBF/AMwQGIaSSKqI0FC7eGZUB2wo6rJFAMifgdfdxvpY2/vuPxDQU/pPA4o9aWq4gsHD627juueNjISTMCJYR9tsBOAZXfJ/LjnWBnuXMR6ffyplPWTkbNfzATkS8iVSZJP0Id+8u48ZtG6hlcSWV/GAxJBT44B+jVIMnohlyOUgyvEE/g5oBRRAYKqdNtFBrwFUimXnIrpc6pfQ3P+/9EWg4Z3OFgaUKmd0L82fNGmvyncnotea3MBgkHlJIezBH2FPDWgWCfHCLTQTKPdv7Jhx4LU4It4yVD1AItuLiuZd7xKnvPe3ZrqMfZx2y9JNOiRZsUlOU3sDqi0NeE2as8CU/R5NOO4/BEXJPI015Ud3h9F79yvKcCyz7t1UWSvdAuSVm9PwbqmJalVgn+eRTnzPfZCteQ34h0akELi0xQu+a8h2AZmxHfm+wq3SCGXpqpIIajm3wMud78U9S87eZ0laF2a6RBpHCETqt01v0y1h3sb1zHmtG7G31DArju4GhHL5TOrBZ4oNsvplGr+B5P3wkwg0ji/sIh0AHCyskkYZKZKkVmbb+CX2pa9hmdRxI0DVX/1X3LopjghxdyhiYFQ9sUxE1e52KA25vM8n/bIHLIFgjX9LQbFSRihnUtkDGt5PwcYK+WcoIT4YKig3HDRf5SQREwfvJKCVSZI98GxAHvQdlDjgzvHX79/80VW9gvzmfst//+y642G/lHBIXTtgDy0aRz/qXLw2t+wzt/8UwLZX7Lj0PCYiA5bPuSzDt/Lbnl7qqbBPEpgKzlvT4yyJXDJoN3akFbBHVFPjljU/B1oxwXmJeLdp6PNx6GMSrabXHdydcgB7Jb5CghXMeKwBwEw0PxKz0+aJz6Tcrt8jnmVU3qeSuWQ5pWfWRPjnbAOBY8AXF6arEQ+Z1D+kxjAuYfoBmg+1T9zVS2jQa6gppaZc7maRMAy8Fd5Fgoc93tAk5Fx9VZ8usivZFnJeg3AIrZcAtWQQCVAovgQjMOBqp9Y5flIHdCKDDM2t07x1QyTxh6qtkcd3+02qZ3c/UzfND9zFPyCfQBLMXDX+IaEwtVmcObqJx2gr2ZCpr4OEhhVmpU3yHzdsLpSujQPxjsd/4zY8Kd/E3lF9PalBn71x5NWHtu74J+6GB0daM3McBZ3jadd++AqR9FOAzvmWkiIGDG3XXyKfGdDYMIqRKr3popUoMpYjUo45wv2pMw/6rX8Kok3RSQm4Yo1SsIyhI+VnoU25Ea9tsph4xpWzx5YiPIGBVxtrYKxTlIUg+y47Ehwtr9suIPYG8NR3LHaBnfweiSOZhSNxvMx9bNbt3J+HClkSp9BNLJnu+HSYHv4sehYc2CASasyG67rWevqS9NbnqJ1V7ntLjWeD9DNI49CLS99iiZ6MworK+qLCm/a05N8FuZ+278P1ZSh1EHupg8kzwMyrzHxKHF9O0lzgwh3a0gLwIBt8OeBeWfx/XBbZcb26Cpr/IrzLUnLehTKQJlS6U6T2ixmzyxtbTvXRNRFGiIqD7af9PYs8yehdK9j7bXizRCFVbQO+C7Bz3OnSBawdZCjd1/98Tx/pFizK4mHwy5MzodRHo0oaQKr/J0oFdH6ubvEIEiYyZ3TkN5kmOiFnM5r92REdS6JzjOYEOdhHjX6u99XUDbiSnCDfwMdooZlD+VS+IVAKUgFCUkbolfkSvqS71c4ZndkynkhUbZAIaKqj4eUZo+htDvnhm6qcYLTBwQCCIZKQsZkQu4LCTzl65ajgtXnwrJyg31LxwxL2mVep8JLhMBzkI6nGMZG7w/gM672YUplPMSR5h7cMjjcVLiVVDI72wKMAoQJ6hjI6HMANLAh91lAsAGe0DfaduYkTDPJxkqT/0YVx5rc54HCrGJCcRNbKWeYAtwmRJ5f6s23QegOK1/KV03z2OVLlJ+Qjn3GE2hm5ix970J0ctMsdIHZ9NkzrbJbiV0JCS9Nx9NJcSAG+UAeUOdfbL8qYb0/ddHFlJ2ufhbZEfd1I8dXk47ekn7bfvGws4eQCuiLXGx6PgacOrNKhxYPJcNmD+FerhSFyTtv6bfzjBKGfdPm7hwMCQZpYnWjmUMuhNobpiIi1kKNM2TadcITP4rCR5trlRyo9Ef3eAFCFd7nWN49gqlPTb7I2lq8/KOPWUIb+cvyCGbwKrV1KXMJdIGtXD6FlUgnynELcaTGxb5VsL5zlbj3YjlGnavC/H8ZVtZfvHa9QykG5K45qZQGErdQz+GGyYMHkcQb66yHeepGDvKEHmjeeetycVFAIU0VRHqbVMjU5BS3Z+6jP6c9D5Bbl7DUTJplLOsaNpeDHNktadCN3DDo8Jleu67jcs9IFH7iVjQ+AvAMqTifq36zZDvnn2OZjFkzsAZ6tukvzHCELESHhXwhgxYIAzX0BEkCKS/9JSW6Ukci76KAQVvEmBQviXdj5lxuvKejBfaSlfkQpUyL3qcog7D4a2OfEhavYgzDCATGPg6loXhdRjG3NOg97EZiXco4yPoQ/uLKJiUxQKHyc2bBMyhcc4rVNTAp3+OsPty/6p6RTfrhZXA6gSneR8Jc91IxtoyV95fc88In7Zpf6z0G/HkfGvGdGkwza4MFwqEOCX4OrRwaTxMWQ8WypzWWPLdsZsxM9zBVmQ4zlRfkJYyYzn2sxtxoZIVNBH57qxDIKZcwqR9UMMGuoCBdu73IFZpsafMtMh1uWKFjO6h0yO8jN1G9z3L+rs+ZgXCsJRGtn+8a7KvmOUaN+NbzlvCtRFqb64uLnu6OWvZoFDCVucYa/W6mOx86E294q3M5cT635zznXHdq4/xz7NCRwfwUpAzBwrbiwTE22fO1hMwtRZ+eIT/+DtYcSR2cV6E1/tcTXCcx/t7NmWEb9lPNnq5KbezqHG9o69QYzYcwWMuJWCzCpMP16UqEC5eqh1uY4/OUANCZzoKqi3gG4jfs7blps8oLe6fpqumE6Ey4cPzLRm3KvqyhkDwGCKo+5FN7YfsNHdTg8yOvGqAYOWkcwRTkw1GnQZoahRgmUALktP93bRuKKcc+W7J/OQTLQH137FJ7SxX7/WCRjcXOAFjSxgniA9KHXSx8CIw4YRjWpEbllrCrXWMYE/6emGuJ0JEtlL6MEPhPBnw1LoL8uist8t1bB8s/P1Ku9wQOsUyN3vbcc3x0r2p8sBN3mG/mVsmkqQyRq6aClImWYc3lO9maHJKKwLooq6E5cHMza/enTG7yaoxF6rSJtPrHnQEjfoc7jp5e7LIfpH67j509BGVBWVbkyfHw0keF0CSXmLCculwrs7HkE1g8yULe29BQNVmW6sr5cR5n7rKNx4j5d42lv+jn+CZfFWm5oteOHQhae3kuGwTvnINClJKPUsniDWSFTQX++8cWv8VjBTWCDIVxrkG6dMNqHZfIiVUEwBjAwZ7IuWljvryfKizC1EAU5Kl2rHryACJAwfbL9TXvJWFg7Q+LkkMMLvPjJcauL39l88TqR/gwV+iRYg1O+5aplf+6wPv2z716TuZlvhfbLht/0GnnDxKd99UjNedKsn82TMm8QIpHrH6jtSBCG28v/lG3Od+Gxk0CvRCzAeUuiNsXdGTUuGH+E492LDcy82gBxj+3Y0hBkzbMe4JNBsB8Et9HQcDOjl6pNgmRW/u2+hSWpcIc6aGNZw9IQMmWsFwTq7/oaVtCD7mKefZ0Cid8LKx8EuNHNA4nsrGKpBcox4cX0IOTFet4qhEmRlgt0hr3BvMOW3fzR6nB9XRL4uf+xm4AzLLa7FqvKOmNgobyO0b1pa53ID2bcimmBjjKwaaEpdFl3cMA80RwwLU7wwXH+g+7iRNVmwi1YnqzRDpfiOoK8GQ8UsvBk0c/QO9sTV1Jqo58MkdjgBQZoPolcpou9FP0miK/5xECuGSCMvWKJa4fsooshV3BZ6rHMJFS0LAxROnrzKqZs5tUDItCSe9s6Ljrb4Z2GzkYE0Ek+gkBpDGFYIN0HyIimgIojOIozuNzoTCN0tK53xDOHS0X8gMrjjaFxZd0nJEblq8ZddEYTZhXQsa687BWWJvM9ItndaqVLRcL9OVHh+wMFS/dQdzhGPand4IOhOIZmaFtkp65SP6mQfcsl70aD1lAZ+Y1Y0nNIDpW1pISLiwLkbucNVPJWOuSsDoFSeMJGtJ9DqsfWeIL2ve31LgQted74md40/9I90BkTXUs7CNQ1RVy6ijBSNREIxOltZfntf6HgretO5L/VOH8flaARkuey91PWRLMpFC/DGgd/3okhWgi/cnmsTUGd/VxCGdCjdjO4MbuSFH84dX8nG90ATChc+vA6QanSpaW/y2pYX1+nn6BLyrDs/MptI+Ltr6v3RnCHyQNjz6LxlI981bqjGuZbpnOzwdeGNGBTsW/2jjv3cidM70aGMNUQ6ofg2UAgpVS4UVAsRzjewy5cIVJZndyO7zPtM+LhWcJh8o/fj9fhb+Y57mV7F8FPdlDGROonvTTxlHhjLY+49mA9phqMg2Up6aDc0Dq1ExQG80hDrG7YqyxtyizqPPs2vin4+SiSbVtFbCAOtLuQbRsi4dJnzc+g5zPBiH2Gm/8NTpSHldhg6yQ3fmHk5kcNzkzWhrozxRjYR8Q0NXSb5D14ltDnmmEeBGEoJvudhPhEoPMFKx5L9fA9rQ/OcFnfaDUGUq49TbRRzgKref7HhpPEzNJheTHvVWNhfN5P0+STpaK70eq2J40jDJevnRVjxxedxE/IrS8IgaABw7QBgcErzAMcBpHuStmnMzXM52VVOmDXLdAhUuAfhdbm7Rw3OzfXNK1mhDRbkrR9r7bPVjcJGWhlrPhi/lYc/rvIJVFAhQH3KOfQaFsuFdXzaD0+l4caRHIaogAzs+LAEb5Oddk81DtujGWZhRfChB/3fW/V/O+Gs5L0etbpUfiRvO8RAdy0AFKKVeSS0gCyMzqTbEkOP9XhOn0/G5746Tla2zX3rGbLhuxPRmwMxcP9CRj+Jp2s46kP6V443WHfT/PmVLwbz537Yv5nz8691kuFP4UM5B3HMObhkhmy9Q5xHYDvFNHOmaORPE8mGLj9TFBRCLUfk4YV9do8UjNKyn0areZQdJdUEDmkR4elPyriwjH7A42JELqTwLDsNr3vz7KxbtWiVROfxHwTajfdaCIkozCCUkw/APCwkgvS77g0dwiCG4xxesUT4MQ4czuR0QvXW/BYiwoguAtonGxNafJ3em2+quwtpA/4rtGyzko6te5Iu17sz1IrHVrso6ueZvF8cJoo7RtOc9+H49Dojo2eL2N0QE2Vuu/8Ems8m4lk04GOTKfsxJ9ocI5FgcjloMUV9GQphdjcGSk3dAGeNAlL/1R/j6rWB0/gR4/xwIumcKWPzyPP11mg9PIfA8RRkmh1aDXakPbHN2zJbNGX+6dczWSo3ef/6w8JstrSghrVnONu7htdDjfydTqTvnr1a6knLl+d5ccC/Vx7scJPYs7gOt6IceFCs10cwVXwQWKXED0J6GE9TFPRcQ/CB31aBcGNoF6TBe4ond8JGVzxK1pvdwmDXZGUxFGVVhFndwm2gNTqYOsOOFuO9F5RtxFc8hIsir48xYPXoi2B17I6FFuxqRSJPNoBleYJkudZ8VPyXwo+Fa79OOUGv8oCn15lQtbucMrisJSuu5ZD6bl6SyPmrQv9XusYK6kqmrntVo4oaP5LZ9BkB3D8nmCOxnqf1o8o+a1KWn+vcjPVtxUn2wpXM6yuKHC5jkX/7xBX+7QAXG49eK8E0mgVIPLDvDyHy+v1S06z7JaTMt9LNVN+ZW2ezW3MyKy/XfelOK7WYncdmIcVHVA3FfKdE3aTMe7BJcP7cEhoGohy1Wp0tOBH32Ivbgt88rMKH+NZyUQ4D2E0wnUoWvnNQtzCoJe2xZutWYHzr82pgkM0lFdd/Wm7VPINb7U5DpOYlGqwCVdSgW4zW4gBXoBjRllTkZUKf3hMLeLPNQ/dzbsriTbY+BTV+7FgZtTiyKpHdkj/pV8PL3Ntj5/twUxtmxdLHj/4Re0neLm1FgA83rZstQYMuNpGjm7flNFKFiIexRZLNTQ30C42M3h07CCTV/DcupD7SJONMBIdZQFne+YThUp+XKtyiP1h9hWiOs/wsiJ4Vjw5n1OF3URN5fq1oTgM+szEmI+9WB/Ps1EMCmv8fjgrI04a9nFQAJoLMzCLMaaju+SE7RNzdn9qkulzLgYfycEMMoYuQKX6cF+Dp41DZFqeHCAbEpnB9o+1hDMeCrrJMGG2hclMSh3vpXvQV/yxh90oSnup2wcdoV3pJm5N0hMKiqpOxJFLrA9rPYSwGEkNkI0lF8vk27+q9BAjqx9swiTu4Nhx01svdXaPNAHRZYFVoH/RGu7fJLZCIPIDYyhQxHUcfzTVo01AjsQ3zBYoyC8rfG8apJJRWjIFYT2ITfMn/5gsxAOSJXIlg98+Y8P8n7LLzSUQA05gxFjzV14aSvpE7tUCrKJgdcn6bP3GFywofLCVgqy6f2vZrcyUSd8Rfob/6znTTekjzPYBlcOnx7WBC89DkvZ9CTsuMma5L5clesxlZgDCFvtMLXjwU11gsEKCW+5wJV/djXv28gZhgLoQX0A+4yWg5jtZ6Wa6tGdsSPG5Xi5zOLU0lnLn3rYgYpek+ssi8Qk28MgLDT3d08Jq1WiJZObSdAJiR04URTmBjYg9CpbEF3x4CS7muGThConrsvdPFfigc2McD5UUI5oBShtkIBb2XJEral+u6LCRinuEeXVlEAfKBTTkexuW3Q2Y7pb6zjTD+nzneHeskZoTbrHGjehHgDCgLRCH980KjeZGqTC+fpNXp32l/deTcqgTKO5ISpfMoBd3O1BKF5/Ar8ZmebiQOgAf8Ccqzv5uu0HjyGzPwMlIs5zkChZKw1pfwWy2ZYH9lzJJLupt39xv7tg2a/sOPjbDLzDYv2lJBMNmXnaoSF+9utKOVfE6z4thw+0k2T1tGgGadA3scJWh1UiOXVZNjRPtfVE/gHrxV8eZ5ylpTWKq4HNa3dpOavExJFV0dc7NStCfNaVhWwb25ZFNzDCboDDMLQ02NMerTWeF4oLduwlwW1edbTF6SoauARGS+DZ6pEWOAYPHjZqPIuhnmF6OJBqbfTAu9qeiLtXxYV3L1WDaoAmItFuOAM9PTSQcVJ3hfbeet4JOao6eiK+Scvub6r2VRH/El+Fns3YfXGPS7a60zNFOiqKyWmXyry8VeBGDH56oDJ9Ti6VWEK1/3/Ot/Z2/Aj1/5u6ATH02ME0jRLSxwRp3NfwDqeiEaU47PgNCsRIRatBUxLvlAvlcblURoyQZHI9d0UxVDBH5y5N0ns4QPU433iavFdLfUIhBbf7J+3wT64Z8mcuyQc+F3GVoBTp+bwtXC9Au8SsNTmGwEOYcMOkywZCBGnXZVy5c4LuKAKVl369TzeDGwrr/trYmgNrZlFfr9roWe8tm0K9Oa1SlceLg5O2PApGwqioyVnxcKhukJYsPtqqdfH/HxtveLF2o9L0INkHWg+qpwHW0lXvfTNjQhioFEjWgfbMK1jaaXkPhuI8o/PzzRRrlC29d3OT9uKNxR4gBOSVIO3942hzF9C22mnYeRQ20KvleM5xDcy1Uk7TEUNuuzRhTK8rpKad05KCmxDSTQ0BziLfS0C6uWLTy7mQGf8FPwMUUd8sNImfCe4+R/+ky/OB4GvzL92VBUDg942jCz6we/7CaclZQihoFywPwjSZILctv3YlUl+DbcOm0NTTBodhcCB3ZGykqX6L9KNOBv/Ppm38DU041nuR911CWXCd3x0rZ05YbeqQOgrYaSGSsITFrJ7USbRl77JQFO/xo5Ka/KHPEcVEHWFkH3OegJ0K4P5m8KMAkBY0pcjX+jL19jzUIVC/CGp+my1cW6gJP34R0AJqhls7xS6ktEwMMhDkAnGygQuqD+5OM7J5qOn/ULEg4IHDwDZPU6g/YhiXJdRq3pmVvMnG+2BPADAEv0DwnXyt8ttuxl3dFqJU5Y9hYqMiEzT1yfbo2VGScBZomWk5BfkC30tCwDTRqjNJMvZBoyuKHYTEkTwtR+FcZSA8qb3zHz6mSUdcy4QzoXA6gC82KPU7FyTujt3C8x7OPuGM2cA3absOoYkjk7+/0ehihJoiFYuXTBS9yJ1Tz0cCOtGgY1tiP6PfeH3u0WYuZRAkazNXoarORu96IgE7qFw5nRKIa5eh0/t2UGOJ+6zF08MMLDjgDSe7D9bngdXkvY3EGqeZZUduMTNVKGTuidHSGYN/SZh3+zcDZb/J2OOX2fk8OwdmumU2Ps/Gidd5dsO500G3VN3Hw3Z7TGD3xUR2TgVu3jwyALmh/mxDyucWcG5vD7r7At0+7vZXXtpDJM6Q+kYLJl5VHXITXlrsPr4V5emKYpJWraGoP8DSv8lvxGkwTxvUagwkIFAs64Ee3PIIMr/5Ob/NbjqV9aWo9J6FNrJ3dJDZzL2l84aLT0TJU1KKaU18eoL8G/76+iAflMz80WVdbxBhESiSbSJVzLRupH/uKr/ttQuIA/eV9F8LMsgLGujYzJU3ykWz1d/oI+ueb+fOl2erdFAjcYhTDdJmgfObqCoYWGGAK+iIoZ6E2X2Bx/a3e/nscZsn5Klfg6h7w5eD5YY1YONCoV3nQ1rU4tzSkBlQB+KCMQlYmlwxZD28fInlzAGxP6WRx0thEZf4Wwv9GxX1BzdU1hUjtSiPQDY+R3IsTcxVIPD8Cb74exi+36LC97/71eFtFzts3cw17gm48IU0CsJ/NofmgKhEKV3SdGB18fuB9kAKMGPCTg1rbKl887bJu91eGVi45qG6gnluxHGcwxAvKXhWzmu+33eFAbMTri4jTvH3AoJFwQcnIH07+ZRULztOQ69uYyEKOr4ErBkaAWYeLYLNRLyObsJGC/h7H7UsthGLgphAd06dBb1gbFDKOP2sy2mj+gnZaooKJ9ty/Z2krPyjJ6PQE2OBQUr3dDKzSknkv7cBIghAoEOAjln3X7d/aFpz1WHh1Wu5NzDhKTKkd7BDK8wYDg2FnBkHOB4NtCzNmguZsxt8hFD1CCMqoeFBqpu1RVZ4HNqyaX+ouRlUI1z2qBadSdkCjV8mHbU5pcA8D5fkVjEmRgXCaR6jL3pJzHife07wh7XNi1dvPYpoQxrkW+phNbPWXhR9E31p4FvRapP0WbGGveOr1g83aqhg044XIOz4GFAPURxlK+QcYGdjOAZJNHJ1wZjJLANsK0U6VVKayyZSfOJKWRn7jC3/ClLcEbuGesf1G5lRVfojCNwZIShbhGL9f0qGA9qkUanwUuecoQm7enYKYxznboqwyUgqU7ln/j3GGWKdlBbosFaOy24cz64vyFGjboyjJyavnmmug0L69z6hF2aVNSf0/zILqemrQ9M1C5GjfwwLOzIKjzX6GMZcyX0G+Q07npbe4V1c8kSy8VaGYXFuDQiukMpmZwm/93JltSGjSoFzCvJz8gYcOJTVRlvkszaOZhP2+zuEHqORcY6ki6OX3A9wPmw+ZFwT8uDAGgMjeElhAz0rHBCyGIPcNKvrf0a1UFJEe5wi518SYtZI0eogRZKJmRaeqnpnF/JoDNDpA3kUfshXmTP74wbCDo7pwRGgGZxPfCoYb645Cwk6t/QPee2kPcpGs5xY9rlCX8K3pZWCZY59KAa+5VshwRA1CsWzMwleQrePdut6e9RLkRdSfuk16WXh7qyR85ZHkUqrOsdNJ7SOD368CVdoTjUy3qk0B7ou+6q+vDIJTXnO1P0oNe3wkoNVhik2pjv0ukSMxqyZko6NqgqkvnEpcsBjSQPlbxjBeToVQrovX2r+lUYd/P57oT34tsb6sORsCby/aDxpBPiWbsSGc1mclaXswi8bnJjgYhAuJ3CCKyLlrdZEM147fizzfF3gt6E3/UgW1+6q+ZmByOV6rtJdeUH96sCV+OnjGEcGFrZf2L5wcCCUcyZnws2FxBMObwmuXvksM6fND09LjnCrm+P48Q8bQLmO5HoflWB450zRnT8+P7J6dvFJX/KyqX/z/k6pBH4SV28ed/skPqCs1hrT3r4dof6X7NYOInmx97JAzbDGy3rBaGVDYldSoy4427bMEwmMjl17Nz75NWfh546Zv62rpu5WUgK3ZUxhPwc11+S51EWeau6oWEzSSFN9D8M9gK/99ueK5K4mFISt/qeWiC675d8rmJEAjNf7t07cdMszqiUQdNRAYTGIET7kU0PocmBQvR/qNMFLM7weqCv888dsCjsEwst8UCijEIUM7EMxENU5ACE+mSnAYZSQbkXCagaeq+XU+0+mjwnsC40d/P6ynOEBha1WcLJuvc8sDFCep7egQqUysMReQbeEexmhzPSOJok07xBrFxyFfdQQCRMoIUgk8MrivCUKdW35qzm5yslAV2ofbhrsFwP+a88PmR2XRW6WR+VLn52xLA1YMc7T1vUdP4DO7qZWF6eXHfqysthbvjeg+GnTDhBzcbr3hIAf+i+VaPZpqmE1uHNt1f0LSowX7H4wDRKdFppP8EpijUlF4rmNvPJfIF9rFdo92eyRkx3NqUVZ80urYkPFvts1SMxl+xyKfmRJAGNojvj5z+mkLjIgJLjqI19JN1noh+tQV38xl/5uNTNHQLyKt/RepEOWPFOV24Fg4NIKnjmdwOVnQc61EVaz8VfdcvN+mBHiqw6bska4LOeM+DHCrnsqen+Y4OO2jum+taeuaqaarjPzBpmpqmy3qfoB8omnzeAYbjNnfr/RYsRKJf0t/b3BzB19ojheEHA2HQUyK7M03ppjalJrh0IrX2bR1gydvSBi56cZOi0AFSCRF2dNdavInNyZuUB+LuBma7qeCnVXUG0pwMfYEF8xr9oHfSXOoHORMDpyGK7TF3gkKRjsbE6ocwJPYkKiKkv143/hICpD9L+mOHTB3SDxusibj1LoQuHQ7t4xbv2v/+Chnyn3PxMvz6t12vS9r08nZc5UL0JV/aMhbl/qBKt9t3V2WsDU+1uCj25qIlAqvdo8DvhcuA8dD+S6MEyBEyhImQULqM1jCmVYCPsFvyWYlPg2VlrXySblJx8qb9KMcxpyiuxjqMrXrLpXMdFfLJ/523FxFYjNz+DTgAZu2y146G9ZYTXtpW0hqBsSebsiyFUo1YBrL2FMTt7Z9U56w5CbuKT1F1f/iAuhq2zGjCA5hDEIcqeJcq5h0yId7PrnSxl++tv2H7Ai7vc6L+4lpVKUc3g6yFyWhd6FAKEqyyBFMafF3XwbHxVdg1zYVSlyj384V8cHkafU044h7aYx+JATZr/z0JBD9H/qaE2xM3IuJEwHrt3sCV8jotRxoek/Yaj5N5685s/DNwO+OZB1KUec7rkfHVPK3prbpOEOci6dYcjF01UAbA7is5mP/+7Oxgva6EIbfu/lPFIA3XNZzo9LISvBkU0aRUPhvm6DVPAcV77rVdsC3K6tnpVsKb8puy6OlTfIVmF0GoS6XFl1P0j4hqmvTp4rDTdMT9GfnGSEa+GLb3Tw59Oq5rWE3mBvAgFVJh4meNC+/Vsa5pmfI5uuE0nswzSaC6i3klhwdYO78RnSdev47tpPgoyk/P/XC+OQf1mzPHDHmMoh2cUIn0x8pkbssc6wxzleSfGRN/oS04odGn7I2nc4knTzcPwL6cwEclfxb0cwx8/iYz0Ls+gJ7+3CkabYVlO4YOvBMUO9Zn/coLwc1zfcrNI1OSyXHBi2fa3IRiJ9fsy9YJVcoKCqUukHEZUzE8CiOObLt1R2zRz9kNvwfEWSybQkbb3UFsjDbf48zDYotBdwE458Ku5DBlIhc6ZXS2uzcbZECxsAbYQBhJ4AwFOmy9hN2/x24l+d8qXopa3+kgIVox2H4rxtQQrzIMcYyCzyIq6xbw0rCwL8xNtjkalN6dlkfpUv5p+J+atKcYhceX3YcaD/aRB7qdinnfMy+qFQe6vPLbuvj4lExZS2xqxwAPeEE70V+qT6lFg6Zjj9Y0lZjfk1RWWqdR+mMEYUcctNIkh5SeNOUME2W6DaBpOukUCX1eAMy7DK8FGFYW3u3k0PT7yZL+JknrdXQQEVS1C+gi8VhpWfl4ODKFHUajxZMji5iQNiYAvsMSwgxqnwSkln5kyhXVgB7Amg24LFiZiaxGsd3bjwMHEgKsx/9XMCvXt4vtmq9L0H8LmShe0/YxUWOupj2ehzr9u7eSRicCzqzrW6pSUaL8NUo+sNjfqzmmJ//C9YXhnvCfJe3fWqtvpMRWhhZ2VYbawK8bqYwwGsrnLwksbUhfZHgmq8MFbiH8t3ym4suMr36MTBL4YavOXZ/Ke0Q8u/7N38bhQQdkGNAsnSLWs7u5rF0KSnNNgb8PJ09QVvNCOCfdT2icK872bRNTk3o0HC2yhpVprz8PI5P6tmypbOFmobh2B8gT3B7SMhqqppToT+hlYdSz8zYuZ/OBANa6mbVypwqPptHaSfbJjlY/rba6JgxiIT81L808kXV6CEP+mDf/Z4pyT5BVbyVYyWFfvfYuMStZ2MzP9OpthobKqRRbtRGWaFxa/PYff5RtxLqWUHpR+bOH5ammxMbTAwphlcZpzeIsxlZFURyf6GWDDpDWXodqdHIswiRBfE33Acb4TmjKquQ9xwcKQe9AajhDcEI/r+qr47vU5g9RG+TunyZdVdOziH91MK5yoGn1qNoeUMMS3dxy7kHZaMqIqJ6cYi4dUQrstYDkDo29K6RLJuUYx84j+OCNs39gpZn4u+JoLdiDxjBSr8kncqnKtIy1LwfLLBtgDb1Ob42IbJ0ciU1RMpM6xYyZNr09POeSS4HVjBYaC8rajWapyqCBZfvRppUI3ct7lpxd8+irarrZ1thfCgl3aYVTI4XtF9PYZpBn6mBkwIbywU/U772n5qOXr/hECOD0V+vELN5yov2HUbzYozCK14fuFAd9X6xiyKlLdTKe3AzVQd5SMmbbXYn/35Iykmek8H5Z93NQkGpE6lXMe+tLGmtovpgwNjuX50z+knHHMxP71xYP7fb2T5UBjjRnALxv/oi/7qb7NOLtY4800l/+nXLI7izwvGknrCMQ96hkCvmlEOZpCpazVz/aRvLbh0pZruHDF7TBdng+Hdk3Y7udrFuVNne1e8rWMZHAIqT6gO7YxhvDOBqqCV/YSjk2nuDV3MlD2A8BRDVT3nZj+1V9odtr6MVBWkCg6isQrtSParwKQwS4RK2+bfpPzQFX7kYjte9mbMDtOrC8rhxBtI0Si/gF9AeZ1VUYixihK6ZN5r+W05qr3txttn3OMVqIc4NH+P9kHVTQaFiObmDxLcg0RqtL8+kXsJZxWmRIBfI/zVzkRIij38s6NH/Ir5aiyuVcCgZ2LgkL9C60zIBMnBOIohcRnHgszSLOIfKE86ozL9Lea3H8a6JT4rfee7eSixJms0MGWDkDyBbcy/bdK4n/nq7rujyu/M/OSztTnh6Vu1nKUCsdaKi7IMPI7tN1OiZspCNlzSBMClA5CqvYbD1UVg85xZN7TH8nd9g//nmhy7gYWZ1uyriGCxPnuZb8r9owRcNk3QFuQFUrJTxs8HQocyPwTWAS13v8h40ojWTq0f3s5su5J9tOBmX0fOfdmdu/FXEfFaLGsm1cQXRHZQi9mbupJyrgc4d4hzS81kiuMySf3NKtNwlXQgeQveq455/v4rSJ71ivopYvl1efFooEdbgDmafenMHRifjecZCXL01uARHmoboBeU/eL0eCXmoQvpyvlA0AOvWGjNhHSmVUxQWV2Az3KITQ7RWJ+bl7/Aq1Ja7cSVrkpZ9YG6yJuNpajelqq228Dlq3lu7r8USeblEDfPX2SSnW/o93I566BzQLGD1eISbTnFRqeE5/t0LrHRJRFk+GYMVwFs5WMCHoBuWMWFthrUoA+ixFS5oMwZOoIX+oT1YY4m/q/7I2+0tWT3uT0X2mfG/03ZBSKsxwrZ60cdh7mMWF2jgRFvadZ7Nc5UasZe+bchnpnR+RB9hgX0qVUMmwkyXESn2XSQ5lBwzULZfC/kQTjYNFqJcktwPdX6KYqcsudgVXZBRWVRV8ejRi9o9PT1VvsMdM26MpYaYn59bWzuTSUHZbKQcVh4Fmq4QSJxiYRkSEa2RJO/qGvvMvaD0Gj7uw0TlAulqtwdL4hcBCvLUFCcVNfje3ny/YQjwPeem+4k9DxxX/15fCN2J5xe7AQ6vMLbrHhn1Vpq9ZD5UkoyfdwhyrGI586loQuV0zMU5aaciYlClrPjfJTnEEn/LMvh3Eeos5iXzxBh7ptmoZPBhA+DQU0XmMoGafWyUOVWV+1fxhvnzqWQ6xDnaNG2Hd3Aw7x8LuzUaLQMiLv0pQOqXdeq2hiu/SIioW3J6Cr3LJp96AGcB0Z3R6H6UImWinUKt0RQ0L1KHWEFILCYOsHQhpJ9XEZaqfxCcH2XdDzA1npOLg2wFnMo7TYKmHKlsJhvMXnegckOIcj4pZPZQZoD/LtBLGxYC0PYysMhaLZCEELhFz1hgiR4aM+K0VN4qhq+jh4C5TUJdGep5dCWJVkII4EX0eYhv5eM/H/r/+mBJCy8aTpk3inEMHUSbTmxwTbSHbt0/zmNKyOSAtg5ccGv5WqE0a/ML2zFJltTc1vi/MVZH1WzKlJ4Si5z284eU4eI6nfO+F8xi2u1JyWy6zu+e2q+4ZkJgpupoTNkTdoEB7tBIJ9LuCBU38WT7kFT3C7f7y/V8iiQsv9hgXDLY7qyrzYJz791iSmey1FNZJOGdS1ixuWkpbakus18MyJ+t37t3OoAOz1XKXJTr+wNOpSjwR2u3ahb4cJpN5GFfNusabrIDEtsos12CkcFuRyPEBTTLslluTAJ81l8hLbxkTmtkWVvlET5vE4hfBS1vJCTm3w8g4kOYMbkANhogqcxtfgBxoti4QEBVnBHzun5Bpr2esErT+DLcna/FZD/elfNXtkcj7r9Ch/5YbPpd7vbvEtmyUHU/Vo7eTNfy7IeLZeUX6f37nTxqJLzJCnZK/8Gp6KkQZewImNxZ39cGDVcEdKFgMgLG30+SO31Qa83tivYJa34vUXyYa8Y6/nWPqEsCS8lvWDESYxxuPfcQ5VsaoLZiTW7BxKwyPZniVcqf6zQrwu+a3AJMvR3yJhz2t/FBg8yragcaDCiDJPjC8BzWbOcjivjj7We8zW0O7U5/5R+0+ZjrtPu4sHR8GHGo/KA/GOdgv2c+37uycUuS6uMxE/bglJxyjSetJLeo3Wyt/k/3J6fp2k912bOwkL60zalQfm5eTMJmoq1xY2BB6sq0QogfGj97v40M5YboMQvCKbNmVC3ummGJBIMGSuiz4gFvyCkyILAygqfR29OfuAXEwVcxIUdvoD6/IqT6mDRYmGTlYlkuZTn9OBWwoeJN3yM9GJ3pZ72iilSuPkn+xJ7bwaxFnFDX6jdoVjQ6P/LAVnB3vXQiALYnm4n7c+f72+L4tx4uL9lr0EUi+ySgACG81xx5719JIg9fkgvdTi4eITh20C8kgKyXLhGXjrKz/V0punlKLuXuxaMDGJENozKIkK+aAqRoHPudlfczmc2FLz2V89jOPfYNq7t4oZ9iol9NlPpvzKe/FvVa5P/GhDU65ig+Mk1nJHzXqiApAdIhqzIKdVyI9XoSQvvVkxrcKAts0d2SC4ZuuQQg89xEe6NFjLeAOPB1RA8FYkf8jNXimSJrM3tGhvTbIoKbb6oyMYxPZMbMOljGPUQlmAVvJCc0qibbHQaSzVXSsCteAjYcFc0kL0804Jd9VbPfbGl3mgasYVDDXQZBvrkI39vSJbp04Hx5OWAtk329K1nD51q8kXa32hdlHg8jh4/+1RDNDAynP2C2RzFgVtxIHymmYnBFzfozLOQUOvL+63IBFkvJcUdznMdE8slin3qaEeJy77Xt7TZhny9SYv+QvVhsUNIVhqTirCX03F26YyiSuHFYTc4ZBhletR9JGI67PbGA+xojp/EBU05mCf65eZcXhwzhAvjOWkKAjHHP/AtZ13PP3c88GIpCWV1P9H4oPyxvjjmDf6BQwvF+QBoJ+1+6s+nksyULrKQps7xEwtCErZOZlUW+XX6SeiamY542rxBvSc8NRSVSn/pZHB5evzUgrFTq/KJixzP2Be8K6LwN79UWPtjKoB1+E4yVBHanicDYgE97YmTOtde/G1daxfFY74mmXTmI2dCCPyXE41g2VFfwlbFG1GyqPsit8vZ1Gk1O3BLAIx2umD1g+fNSS2qUCn8b9RMNHDNQf1yzepnFL2vMp4UihYj6e+/nBVI3R0WRtLLn7yIxS0wfLcPS95oJt9zjVGQhQ4ogDl3FHlXZH7hxtxz8ezsjmDQI8eGBhbGEUc5501Mr4eEWPp2ffiTpzjVy49TRUAsaAs8cO7sXoN99X1/Z32CCqNXmOgZqCMdY3hQCWZx9djdqueS8LEPWW9w5oeR2C+61Honth8QcafTin9HK/DXXhsK65PSCzrP5kgln5ki9Emk75OrAr/xpxUtGJu10lI0vvPXbYg6aODOZTsgyh0ZOZynEuTCBdb/aMSzoPG02M+CBNOTd/MLdUGkm2neRppeFG+wWVh/etkmC2bdnB1nsqEt83yuFXSMfnMkUY3baNTBHql+s6T+Nb4Mxmlf0yUbkcfN73fpbVapRSNu3LhfplcZ+fa2kMTXKnV95p9Evt6fNT+jFxWveJJYd2Xh3EXmcT/zhpmMXT54WeaIcv4J91XmjQN7d8r9xUtWct/NLc8L+B0FkM0nTHPnIZmTWuDZfZPMCXO6FBcPSmme+C5azEV6EtTLhUKCfZioGQFvM2/jLT8Vrq9b/fuOX95gcAD95BXNqCaR4mP/WSnNfAvHHn0bpuX3iywcnSBbInlEPaYYd69H8W5BPHOf5CXmKZIlQ+OrxcSHfJRPHeOiDUJs/zTtP+BjJEOGLhbK4csUzKY2cUCtyr//ruAtl2XOsLyJhnI0Z7TRtimtC3di8op21OKdSqCykUIUuRRmlWJ7BCcAd1VStpjhuJlKna3BNNQkl7Wuc1VxDqLd9sLOS9CseZBliAEopaWcDUtUwJ4CS42niGf2Pf/X9mKJVsPEGmXpozR11DXHwyR3fJoj0vxdYXY7JMvb6HRuV4I1SofgkGwG1egr4/c0vjDZ4fuuk7ac9eZ94hKcWVzO1m9Dz6zoAQVBZUb3N0izU1LPDzVD9vLsMRP/uN5+xDf/d9aTIXOax72Zc8ff+0/+Pmdbg8w3g2DSjBFKQxVa8YI3vBOGS3/vTEpTQq3ec0d1cCOgfGwFdeVJMragTob+yCsNa1AfuVw1OEXyKvME6UNhlf6n7L3y/78j0uMgnUz9Y2o60C2a/7a3QBqcfFqA2LujGJL418ZHqh0h8NUoa/6L3mXtIi2axKyNlwSwz95J0pQkDDN1oxPqM4tCpdDfcKCTtm1mnXHZum3KmMXZaJZkwRAi2ozPc1HXU2pPTa7Tt2HMvlNY6bt7xvelokIMT9ODJ7bVXYt/NfBW6ipMgjMLTUanDQ0gNfZ/6/VxhZQgTTPpEqnlMtZOU18uQtUb5lMD74h0WOYaSt6QAV2YODowQuzKhsOgChWaysAzipZLOdpH3if2kltvrW+dWv35cZaKvpHMH2MZhodqZBrKaB7yJEVStB0ugzFYT+LE39f+7jVoxG12p1xODM9itZJYbpMWd64J3oTvmguzRTrxYcbptKGSsOiwGrVzMAirp7TH1zOnDYjDHgiq4kHY8dwyuLrAmKCJTIIkkLZ1iatfc1qLwhWtATbhTHduHmFQyuQEsCvaLtHQw5fXiTBcURvwJpSprH1Uw1XGJ2i7C9Hr5RNxxNfmq3ecQuK8dJIHQSBBJlA6gFPzBt7lXlPul8PXc/97ZhM1d1e6+9KIJ6s+8OcfLoANMMXlwi1R/omtHds4OHeke6W+X9Fv+oFetfaMa5qcmcKXXJ0N6smkW/0L3cLom/rAp9sJ7TkzqQ2dUW6ZECk58I3pk1Z0EPtAyGPbodhowTWsBbjxw8Lg1Lh+N++TOWwx5t47cLAa6s812NbVh0ogojfjBF/m6boJg3IxHFOCOKhkyBkgXLGwpaDicb6ITex6X9V16eCa01UgXCud7TnQsvpA3K2hAd94/i4F0T5FwQX/KUYQgPbaW2bupTOk+s3LxxsIw/tGQxxLirR5UYu/jlC3kz6TpZ+SIAktpH7gtneTd/dzqI/L4Mr2DPqngDUWFmCAl4M4II2iLr9RK31iuv+THu37fu34XNYrpJ18ht/Rl14wsxmEACw0G78eUo9xNzioXre9/FZ0LFjJk/EzBWe1bI3ctgCdvsmMcHc3fuNYH+yKH7Iavzcz7LJmGJBvzeH/t8Y1vi4Kbg6DfoEGxyRN35Q8imNwX9XJ0wddZsD2Qsl7WTOZX806S9oHdJlgNml+mm4tuKnW4DE1g+wwAOfzgCToHIfBctsvJnYKekbzcrRMabKrZUr/oMLaeg4kZ7s1iOyUYB+O5FuNEY6V4wJE16EO47in/76LDJ8nbJYxEJqAt9VLhcSlBD5jOQHxDj/eloLnqypWpI3Ez+wSspnfn+Ug2Kc5SRsBhf8bxqNR39n+tW+F7GY2n9WQ9tmXj1W98U+pSKrbwirYMfemc6KHe7BvX0PVacbO4JxYtonTpmRIYCOmE0NCmB+c+FfVxQT9vemlX+QNziP9+t4IiQzP2i3rbxGLRkmUNfOsxB5lhHTA934tjrIFgJkYOs3oSw0yA2U0dEYy0rYqAFFXHUcgyThneSisC87nrO7C9q80wK04fNgMwOly4uqfm8T3n2Ndd3aFgP7zgGOZz4hVz1fJUCg2TQFp2kJCAWj9ALmTqzRtqq/leaJpCtknX+yShjymJbilu2cggvVo1IsS6wCYbyz9acv99x6N3t9U/f3JN/xrLkZvnNuGDPenex7eZs5YIVR2hKlrCA9amkY0wBSEaYjix3VS7Rkl0nmlf54tkGDRp2co4TqcGn6F1L5jcO86LL9PQwM5HRuv57KWvwTSw6ix15+GjGmPWzcKVAVkynqUXYu19yZKYUhhtyFVlMOwUgTXTGr9zpB+N6iUklLEjDBQ2JTI0vtQQEsunv3gCelaP9N8/ntnYNj3depNPQwu5kA0LEb8RjwuqSif+v1A0aNlhhnHUBe2fFCSAYkqB9xqagjyXlQTpHND3X9uEX8cCUX+irohhGVQMJLbg8oaW4xlYEaeWAEWFKC34Urr7ddqDVMRrYzeQyn4nSIIId5Vq/vd4Q5ye0A040NNuEpoedoP92FyX4vjSZchA+ZhObQRPU/zKAVgC3V2suDvML8fhSjIOYFH+Egca/4diNVod9pN+v75PiVj+6XzjDhemhX1pwXkk9UmFv3vdmGVNZGiTkL1kvScD4E/5B+1qHoJlopwEEe5I2cL5N5HzdQ7gF14fZyHArReNSvT/38jSHPg/PnBORVyNfd+e8XiERfaH59rx7pVpLNu3/+uUP0Z5WWcQbG0WxH/tBfLYVjSQT89M0Gwqtaq0px3s9pChTQgVYghsxZHWVynVqpijbT//IiiEiE0tPI3kgJlXlFHOwOQ3tChbSQdwkVtBM6hg1yFyq33Lt/W5VFSoA/KIZ3nSHGg3YGybtZ93cIRQLY6rsBUIB7ICN6ezDL3LvLnKSNHrwAwZGBilNj4RLMRc7F6412YvwNIpfBHy9x8WUj9MLil6vOSYPkK0RFHmN4bIoEhzSIW/saisAwS6eNzdKWhNwqSuwLAzda+L/ECR+4YwItODHrfwfLv/hsmEopGh0hgUlitVkTNL0SsYC87TF6QPC5TGSQ0/FeMyuoOtV9w5psPZ8gqiZIPQ7nSoL/HQrh6Gh1KItBjVTxQoxgS2eUQh1P7DUyd1TkdtfRJ2QcVN/XkBglBUDCwIQYcSvVZARhtz72yMo6QUvqpRC76vYIXZQpeLAKMiOtwvKLcYEOqz04p/iT629/jek2LaLc2oTWMGS8b0oAzfruKt019VRLMpfuJWAMdlvjp4oq2i+nTAuA/yXfHKA9GOp4uGSCEXrLGbN2hi6ifQjO4FuU2P+9OtR0Kp1PDYl1uG+RfZend2RljwNoG05SZBEV4SwToXRyloTX7+xMbnJ9COjO1FSbUiPRcDJbeMJCt0FDecO8PhP6KyUdDi102jfik/HBU3Tuu+l/x1h8tHM7MkpgcEGo03O44AvGEY46HgsbUFHvsBw3KmB+azJ44CWxLMhiskPyC/t9CDCae1kf/Cv7vbu0Z+RE9M28xab6iu6i24OzcZsuyIYNkX5bMt7fEW/kIVTFue18o4h6XiWSkpMPWDts2Y8nQ4u25M7uBBHa2xih9l7uODWyf63Fs+yWXjySCDgR0wGAIuA0T60w9T5/PZmd4g0egjKjPZhfZ62FvNkUpw1xvuaU6tSe3+WlDTSO2uBGNaS75CAv3hWGXP7tSohB2HxetkR2ZcOIhr8M21kSjB8ZclUcyi1FzssCh1r8Mienpg0VChj4+ymR5ZXDM1UmoI8IJAWGhkbM63qzI3lj1GN/KfX3Foee9i+YW4rkJS4/fLCiPJHvwcU11TJe3etPzuSLTTkVgQ7lb7UPl/hXtK/A6mhNH3xl7ODUW101pkR9jnMV6qNC0uqmYDRCn8Fk5TxjOJMxYPn/XhcSKk4cXkKUYcS67q5ImW9bVsAS4NZjiSANGTjPAgE39wsIH3Db5OrBxvx/Q69pHg0ndz2j1MSnHgOW83RCUc6yg2wrfnLLOJgyxcE8jXwT9dVu/4qE2AziVLtfz2mAOoJekXwT/+wrLH55t2AkFBq/+5u7axgUcVBm8k3OR8pr4Ipd56B5W83hlfFH/QSim3G/d9GVZ8sf0CQfmkFcPSH2izYVuyeBgAs1vdXEXYK+Vc7e1SFHFKnDBwBhVvjqtQqeCl97XUf2NLa8ok4cyVopTBv6mOL6g4K0/3OBrxuusWm3/+P8d4mG9KcTT2msy/MZNoZ4GPAfE6dBB9L7j/0F3+C8IDUM0Zu5BjHZf32LNauBRNhOpIfXRGFkcNZPZ5UwolQlbljIVUFmNl0FpNX0P1KQw6Q8/42Qj1WRgNItsHjWRmeXFwi65jF1DLcuZ7hWsYspq2xNRCOtB9qBgJ9wJDyBgx0+gAfLb8WnBZRpyZu8bOvrSRzLI6kexoaydJm0UMyU+gUYBFSmQ3tHYjsjXk8nlVChxF3unUHD7Bp76udoB23XwWrDX9YFb38x1j4SJf+5Jx5Ablt2u7Ho7r70j2X3WhygSyG+ndkSdEq+yClfK+fsN4XY5B5THx7JHB2ANoQOkpr9SMk8iaK+UjEg4X59lhUOST2r6VsZWeDxB9r/9TgAgW/u0tu8nB9iQ5ajv0f7fZVRjcCUh2Gi28DWLP4UYgfovBE7WIKZjexn8n84I2Xt8oY/iK+7OySP7R+ELtqoBvDSYoV7vUcrR5KETN0zkn4OMk/j8LpxiCZRGptNA9CYdVbaxfkzM1bcrlPx8QMnXBXuc87eltTuyIwMGen7dF3ss1sfykYXgm+y6vwQvYwDHDBTwKrZpAidmCozVBjnXe3cYsyOrQ9UBvEtSnJf4vSmQLKkeYtGI79xUY4lnHYkpQuObvaSi/nMZ2WHlVNGZq1efmdCsErEqeRzd3R5Jfzb13x+7qm7uHCMY6JeHiFWwgm7h9kzKfqrm3nxZZEviJrB8anE5xLgGdTKCZ6BckbQThx3uNDtc/Zedp5pg6u4jZ9N38Tt7jvudBPjrA4zCyTT+kUphd5HT+NQncZLH7Lef6C479MsbqXx8KNtTJKPjFtdU7a8Y+n3uZx7anvH7XlqelK9DkPvewgzWFunUUIelW8qyW7lEUSiC82vVhMGy8CwAebA7m1Ge1gitN4zkFif+Vy5GpoT3VjQ6zt19OnMDbGpCsPYn1UKyZN1TwOWY+vNLR2empC9GN55XD/ituXUXnD+h+q71H+XVIKdNKGwtEh1rT5NQJFTCAj6PMH3Yegxag0tpZ4vmdKiLfq/lT5D9o68PbF+/BwQlTJGbufeLf7ZLAXET4Slz4OAm5m3kEv2yNVu/9jnfr6BtjYQbA/itcUv5viiulP7L5z76fSqNr2ENi8WzVCke4f4nvTi1yK+fx/v76W0w6cLtz42316xkZ8D/VLDqX0zPiUoNaXr0Jujo1aYo28JNHZFJAtkHtmC7lP6u4yxff+uFiEy0sY74g9nd7cg+uapUQ4Ii6v0LYdb9/aK/mx3t7zfIa8Hwe6IokLcpH6vOM09vu5lBQJcemZHBGdKRgbUirx3vt6Ehz14Z2Naj3zNakvw3LEqetZoFwB2i80XnLyggFjLk/vsodc38VLK331O2S8crXGg33u8uo9wP70HtyLxJFwQL2O9RYTF7NKBMB8aTmB8/XTtIpbsxFj/8+I96hGGI0Zalx6ggWmYg4yvkoR38jPSyT7kor5GV8dI6ooJX0LmrzUSI58oQdjhFnNe5sqVRMnrXOdzdxgnW7neJmI+tfv1TmW6d9udNI22ijTiEAwfXM1gF8gCFqzKW4Phb1Zp+TsPC5lyTUkbDZHZURYVXENX/sGBJDHE1zOArVNuy/gDQoI2yEg7/wIOpwcFsvE9QLX1QkSZEgtYLuj14b9Ru9U6ST9LnUlbkUy7oS/VIr2J8vJQrYSzSAlSXQTikUoZmN20vONCWTnBYK8T3MtcYpmWdUlvTqmQZU/y7CFMI+lsY11CwdTa5Ww0r3tsatRojeIAfd+Ut9+b54+J8O9ymo9/7e5ovzWHJK8IPg+VVv0/FC8Ll3PALOYTn+i3NjMueHxnlleTO9n2BVF+wE87m3urZPix23G+PcSusqn9dwK0ejKxMPvibBipLUGy6LhWCJQhrGQGD/iO5ghYwg3Cl9fD1WxOtxlub9A+PEeuMjYEmxP79ev4ruyvsAVM1DdKDSB56/W2gEvSCUAEIxylR4mMh4/rY0Syr6qHoRwlw+vYR34Cd/LDiNlj+Hqg5Fu2C8Mt7dl1JpVAQkzAecrwKvsEAoW2JTXBcwy+ynP9b3D12c2/a0b0T6p6zoOdkiSEHupVpsKb2wv0gX5MO61I7zAz19jlnpvzBySnKWy1HbGt+7BI61b07+KRQao7aB8s9KXYbWzTo1IcVxPlobHoW8qqqkxEUGQjp+VAe+rwVWPH7YSrNy08IuPj/RRTxo4TytGosuaQdqt6TCDl/eTyxwaFk+F0bhSFe2lT93wUeBLotGWIcxVGHT/978ZAO7PjHbjsCUW+BeizgFLY+vUWsOLZg+NhjNWfc7qizXAag7+dNZIlrBbvd8+F2zUX7itvOh68Nnc1kq2LOBy6NYQLaigZ4P9J++sDPxDpL3/98zPEWYltRSjllTcWTugsO4fue0OJ+8MDuuenkm1TiI0mxguFNc9CFFzzowdEkr0JmjkpQZ4JbmTjuJjqvawzOulu98Bxt1vm5JwyFxeDOBmsn5P3f67YzSaFeCvC2YIrkbIz0i5lko6bMT3VRf49xceKF+mgCxhfY/vdqq09TdntnM/utOLOx0yv7P5YJnuBPArHEnSAxKks92vlXOwwTV+zf0nv7sH699KT/Gw88FHoKfiLPy8zHEwcEFNaeJJ3lBYtfdOQy/k1fH6NTCLbdG4B8/Syn/TeV+dk6sPU/Lq/N/SD5qnoG4rZxcKzBRxsyPsaQ87EGhNs/I1l7iS2vQJkpbeDaJ9MN2GauQJUpb8aylPCUZ264ulG+KX6pZIc7dS42u4ity9axNm5z1MNL+HsXwxgVqo2Jv10ej+64wPe83RBIOuQKCS4gAelY90bxXdDo9f7obihc+jbkj0vTDrTp0o+h/4GrZxhj2QNHu8hY9zeTpeWA/RtFq9+rBYuvF5ibpuWmw0k/i5S0ZM/5tV6yu6fTEanZes+HviFs3RLNHNBa+v6a2637ObeLYSffE1Phz+7DfQnKrjjUIJshh7Ezli1FPr0wuDPQvo/HOMtJ5PrcD9qNZEPhLhfem1V5+XXiSFZ5GWWCwIueE1xEqyOxh3qO+WMQ65iHYUKtXVnVVchnPGv3p7IgubJD4t4rVQfWvjCJ3T9CB19+hmow2Xc0YNi71W8q4HJzH3nIbg6x7OpT1jpr+MaRhcvVN/O+2xo1YWo9hDVbgNbLKbbydt3h9dlrD87jDUzjx/akIlfCRj5iazOzpnBeKAadRlJpcd3bYeulnvSGecaJUHnYk81VJmmd2BKZzVcmaJ3UofcVEkK4TUAErQPU0mF9qHHP+w3l9Oz9Qi27s0PbEsl0/h+OSuIQDocNTPpmiTZZasMPpK1k7858RZz4tncMsFzlUGKeh2dDbSbCMpLttu9uyW62gt1Lbq/5dsqGOUlIbzDbf3a4rTYGyTlPvnj4heBS1ncNIo6Svff6T4hvQdNlBpzSCScM2o6F7/lCUy5BH83xOTtmsPf6okpk6yRS69ybHTpwDfeTX6ENW3/Fh7AALCzO0aXohSWMfiPN90RLJ68eRC877OJhsBl5iyGcegww99l2c9EGpZ73w+KdKW5Iy2ENX5AIJr2kJTgknwK12qLo5HS8PFbe4PkrTtzxDoeOQtKLoi5/eJAxjcXdHDjXhObGgTo6KDk4ZiylN2oodduPIQApjxFBscfp4iduQWF7GHP+BgkzwVM4bCec3ErlNLR0Jn+nrZMyE/OvJPb87kLtF58ck9X/oo2FPwmEeecVElCKlUMWv4LVSzNfOmMbRpz7LTEfXdo8n+S7dZqP7ZaVUiu3wTTpZP+wT7hz9KllcTj7bnbHbALY7OnYIHphQTE29uOWb+w7bvQLc9sReQeax9Q1Q7rv90X9jTTaWUxjC+Rsj41p/hbxpf6TSynJ+139O1MrrJvTGI0wbgqVBoujF9exr3CweiznU7bUdsI/ns7pKl3VwyCHTv4chFXmYBq82ZTtKKPlGmOHn6SvYrdS31UxQ6XF13DS+nvFsYjvdf1R7DCVY8xryYn5WjV7IX1JYYiFeoJlT/6Ywx8jxH3UHvL+fiRBPjKrZY3iet9OuloybOUVtd+abNt2f6/OekC2cYOIeJHBBLiDAEJIok7lted3VtGOMgXG3aI/+GyR17qNWStiDmOdMKeYbAoGcFMgQJiQw9Fnpt8TdaEabtYTLPcPX9jZvt2Y6f39lPzLvWVz32AT384nNhsbDUftFm8tb1BAH0/HrqCEoRZEtpHu/9BgrpDbAgxWYRiudkxf1/LvhpEYyNu/Kwf48T7Sf8no5ZUrX2yUN0n4MkdTkZAE8cFuSCTETh7g/H/pDR4DuBT/ARdTeJMXz1RlukqBFmcJOVw/LOm7No+67vRZso8h1vE5KZSc7BWHPOVeJnTTlWva4MHKQsRhIvdeCUKNua2iz3FUTGYs1rj9D5sf1YvW64bX6w/TM4T+5TLOQrhrxjqRBJZH9RcwNKGb2Wv0TZ+FnZzMNHyrdPFQY/qrgOs3vlwrWBcwV4hEZcgDfA70T8vzQ0XMwSJMNmQjvqSYvMc7FbvSBDTDEilRZfdGqdZpDEtz4EvIUVJetHB/5rIK12U9++kvhMBP0rthytuA+TEFxmv6OQLiJyOKPWhNjracSSFpmb4tNleT22GGpxrFyfMb7/wT+0BACrg4VJ6UoLAYNTO6il+uzv447fv01RfTpZdhHkV03odeCpE6tHbaI0u/iRkE0XxBzwuSMBNC/Peve4TNffCusjyMSu9OIWScg2n3htUJxBdvezgll5uCP7gdJ8RP4oYXbvmVppiYbAiEMYZPP9aGbRx6BZzpzXKWfa2OcuAfT8hT1NLRskZ9BlNENteGPC8GVp8yIYNfhil7GXLDgKcQ0fsJnTs1MJvdZJtZGjxjXJbLRcfwKsnqeIButMB5+ts8jw4/6+i4fm2vWjWeq0XVs/D7m4zJ1Yh9pdJvqrEYc1e52tU8hEUKcJxR7N9ZWl3hampC1LrCsVjAOB3/DQeud5GtZx2XJcV/rkPJvC1qqL8kvMmIAMOdDGCoVo4L3OV16YmEKwpROxaKIEW0RNzld0kjBMfH3kRieCFJkc5zcTPyIidxMx4vN0aTL7/3v34o0vQ7tYdciuNyk7pxUSfMIPkKAyigFEq5BXfUtPiFXpuNQLw2wiwMhOdSaRXxv58Q986Nqgu4sDALOjkM2khQCFLe1e/uEKsxNpCUF02L96n40Bi/GJu3GrHJ37Qjr/zC4UAXDEc3FTDoHpX0l8qLG2D5shMEf0zu5sAZ++d0DkGLWFcvQTK3//w451WbotHV85c6C9DZ6kw6sASpnG98knY7lRZnEANcD77X1Gzgc+YH5KMWJ8iy8Wz0I5hlgyHPReiqTYaBYhRBq/0gDUwkodfTBipVXpiMQ306wsBdDAYPQd11dJBbXgnlvxIB25fO+1t4yPMrD87NZy5d3RbNQxrHElpvfcnGCkLDqIq063xvC57Yamtg8Aoljah4Q9XKGIr5oI8ufdyAIsqC1G0PdqEXxMNT4u2mc57/diW+LwEApa1xEv67zAf5+jhThPNmjf28lRx9eDxkLvtwerH7/p3JLTdpE+xIP7jDEWv1srYTxlL8cTbEgbb8njJdE74Xcm4kpSEEL05T3vr+kOGbSXSNIUxG1fKzdzsLXbdNzzF4Oh7n03nXSRx1MfoLkV0tV2HKuTezFTVIJT477dpZRdszyQGjkdGod2JGBGZ+vw8vBSmZh4MooWcouVG3j/OXuBXfn5Tz/hJvV6T+6ntBqZ9e9i42sv7NHF1zbuOvh2YtH/f938MMxTdZ2+0V9FnAWM9dsOdcCdjBTQJuwbMHx8j743J0F7s/6Gcc3Cy8d6jG9K5WOYwtWLGRpFJc8EJXZQZ5GpTWuiJL4rKCLBjRIEbHAPRnHIVxmcEw/L+KZunETe7Rt7Ku53Q++PJHceoLYruCgLnK1dBS3oJUtjeXnN/CgZsmz9ffHn+XPRM5Ewo4XzlksV8YhufpErqPg9XkRTKiuzcCjq1Gprl4jKQMeSh10438Do5OXM7ACcp7BL0eclFk/wZ0xd37J+xyVNYyRc0ZcZugy/9+Lq+sCQaVe+WHJL+oaJGcbzRnMWyIjaOJwKNRXaZfSqF6bU8bpNnA48npRmvoZURInoY2F5YNP3ZOE4j7xbsqaUph1nu8Mi7uYwmZNggIwUCfACM2yxvFiyUs/G5okT4vR27sGC2WeuVWSRwX97NZEXJGt2BhmgCj9pz3R1I53fmUrAJOveA7mQYDWAayRGGqqKMt81A/7QY+nC4MsUF5aOjIDgn1iF/oJgxhoo7FeKWX1rtQ9GnCFz+z4LPTnqDllnuyEF0DDd4kTI4A6IIK2406x7k85O8tyo7RTDrASsZuio/7GqWY3iVjGV9C9F80xSJS3RPVKb3sOJfACsLB/oslKAhctDc1MuW4vY1XjDczxahadfEH/0RMMcanpJ6l0VGDGT4CEb/uQgkf9Mw6GnCn8MhTdOerD1z0aoaPh5vkdCTecYHs9lZRhWTsgz4kRxCPvQEZsOCRGnxbMwC55IXElkzEeTRZ8vJjMnYWmq+Z5ChWAdsMEWCOUCFm4zZMP7Mwl6HjVdpzSRh8z9H1EF48i+j4zgr+GuAuxoFvWCm8wY3HFOnOAvRiJQh1JcvY/KmSoQ/6Gmufyhnq8Wv3lJv0H9GjIu3wEZgQaboqGhUTX+uYPm3zW3iukPWHV7H7y186O0zzhoENLG6auerX9y2kZqdtt8RxzD9HuzVtxK8lhqlEcIgVBi9fZ9vv2KqPS41x0rLduOJ8RAiP4a7v84pGmj2hnX0/WO+0TKxpHAu8i1WYFf74WfnGqacDF+IHfmP8RBsh0XvMow/AlNANtbYnCHXmJOzPaIjQchkLuJmu0lqshsJKS8qoUy4pI697fGwLqcYuA2BguLHbCFSDWNRBYtJoGSMw8bFQxNDAMOaqYlA1qPWpQJhzY8jWwUD3K+Sn1/v5DcJEAfVfVOZxSskRYsM7pQmFWmSvgj4imX7CfoxIH0I1m4Y4FO483mWetRDB4c7l3fOlUC5B3m94kouxXnCK08ydkw/1YNNQXFj1cNdEBIWrpp8n3cU24Qp5M3R3IVnyIacmkOrr5SyorxRHfRomrLRAaeoWrBu3rD5oi/ABZql6i2V0UnL2rjixHUCwsySDYpRxyXSArq4jJjK/EVhLvDqtuB970B93I/5QA+9LQZIjFdlFef4ZuU93VN9L4UjP5TTqF3MhshQbrEFJI5cbYYwaFUnINUjhFWeeVOaY0yF4F03FV0NTjTNRo7YZcmn8/dwZLMwHuMQ1NlY+0AVgonigwEgXwx4tRD4FKtdY92864x3szebekbVF7obkjhTy0vi3aQ9V/wZjXtkzDG1TYYAFnS40XrLFvy49MstNK75j7ZUvDMubaVMTs4yv6POGb44eZtCanMP9C6mQi1KMZz9XzZZK5rrUPMch1u6Aed6bZwc/OWQPxROXtd+NW97JNn70JnOIWpa94zD32rTMylu4D+osZgekkJcuBJT5VLhCxgcE2SSJ+6GbCnuQ6k7d/2kW9Yct8R2xjnOXYWTqY9xrKyKvZvUfOm1UsTSXe8eurf65Tse7SR/gMeCDOKacQxuq8jlNr4WJXM3y+oqykuAddBVSqvreRR/lHOVWo+oRsToOLpu8/aNjRDJc9FkwJjbXZOC/0/JqO8/sQQguARHWZSQPPaK4Fo/skq1m506Zs5uGdEzMbg+X40D6WB4YX7Qk0pDm7Iw3yh+haD4yiANojRHTnSVZjw9HT4unelTPxWa1gshw5LppGhhLVSaEWRV+JVCRMrGZfRLyY7Qk+Iu8pduXqgTJ5IYnUWJkic2JJeSrHwHIPfNHionhTlp48ei6wCe+Q3J9SRhFp3k4GAsWgzW1RXfNYJkljaNKZj7H6zlKFDeF4MNo5CaB222G6XKzFbQfJyC5TjNYJ2OR23KCRKTv4OmQsErTuHKQ31cMbVO5PFajyJ1MnqD8kDWogOEwR1exnfohGGTL500fTDp8WvlERECewHytmlr1RYi4Y7HviNGgAXhvuk3W2CsrZ1JuW0oC3+/SFgcMU2DwZfnFuGukzuEwLK9qfEHVGbiZ57ctaUZ5raCXWuVhTGByElQ/Q2SU2zY8BcWOS4NcNFzW0Nh1bCsLN9hMr7mlq0TRqR2Fcu1xaklKSBadkCjA7BDEcmbsleMrM91hmBTk30HWcOXOKUovmcFecF4RjNs6eKwRc9mCX3o4vKhryumQ2h0w4YP+L/53A7p9kfRXUGnKOdGJxu6xkovjztiQ0iWF6QgFTRXcHqSEp1Bnr6iERBknqeCFjauXn0yueFNi5uL2r0jr42xuYq3IlN3TlyVdBWdySEh0fo/ExdgrHEzKGzSs/9dPVnBY+uknOEcn6kpQ2mSINJyjHzyONZGtbjIqjMgrcMXd5hCRRQhAVJM4xyrZCSamh8SaYySFU3K5AjFo5nabZAARFuEGXGI5pinaS8hQOswYY1Ml4XpYiOGYyTxfCNVDRDVRF6EeY3D6Ycn92u9Egk9ArBIx6oYQxuEIjkxAw4xZN4lC0DHlI/SA0uTHEc9rF8BG7zoGndOe9XAR/ADQGv0XfQWZS3E621ZBeseLOOgqUXfs3EULAZUYdR0pn8SI7SNe6GnqrkoKrlRu6JhLqRcBEKFiCl5x8kAKTmLWTSGEQxESGcQKRt0gism/qDYQZsCUYMuN3ZRYnb/QwbOkpbFlnNo6KNXMN+mHO+HmII6HsxSACBQtyPRlMS7YBF/dJxL5ojgaQAHBX/cLgskmHbLo6i8uH0s5Csm4HCQZjQogQWbQLOl5AR5Z+Zuaxw22+qdmPrLLmH0uoETBTiUzAV6AIdal7qzQfdF8oks5RsJVMdePWOxMXINxm2ntxAJUOcjzE+JDQsJYXjxhOb5JYz/kpsktpCVXnSPOWeP+fJk85VT7ZotQ1m+GQvQprMomHv/rQynCaIxuIySG66tJ7c1oUInDPRv+qJevhnpP4V3Nbc/FJmWQgl1NZkI8D5NY1wmlyg6kCzk4Mp+HZDUaT0afoUrciatxfiPztnDyY6SKISMA16VROlBGm6B+8wzUxVzLuKRXXYi2epCuPlEnLgdx0IYWIn+9dNlcNgKz2/yosEtbRsErCo+UmE9jJNaJ8eiHGu3XiHciv3ieI5afTKzi9SuFFOe+GoNfEZGUh1jF+KJkyd7N+a57Vj5keGpf/7/4vKDfj7FbjCo+IuWrt4n58p0OS6kNM2XOxNnXkIP9cPfwJ3ydiy57ce8Vrsyi+QbVNF/KeAIhO99Wp89X56RxBm+Kek/bEsb9f5O6ctH48Wj/1gMNcF+lb7yfW/T9ZvTMD9kHOsLmfnpdZvCHedN77lh4KSNfpc2JPz0AC8iAR3dlUxW6pjxqQunkcghlquriPdoCihcWixLTCgisJWpQaJMlXauPZs/slXZoQfzIjureMHHY6BW8ca/CC3K8xAScEJEYeUM3a7k7bZyiU5FenEkn001vz8gLqGGPuG+qbGqaCE1tk7E6b5SBM5D+kWU34TT5KAA7nBwLrfMRo0vdXnH1hfPxLtXJkHK16nCVF9sT13DJJtxJWKXHtJIg07ANRc/dLT5azv5epC12wcrUPu04k0fh+V5OZhGxyQoQ/DZfnuT1oVj3/eZS6leA5drs/LD8Q9dDFeR9KUUXCDm8aP+wAo6h+PdNXX7ZU5GavhO/Bm9ezlrng+JCmT0WoxzC5B3sFEiJdrVQGN9C29UZruPrZTMtIr3TItS5zeeWnwSt4YD4ibHjLcDIHEz7YS8v776JRDMznaLbGSOTb5KhkMd/LEdFd8vxgt7Xt5VNttkBQCKpaEEUoMBgTDBTECKB+Lr2Mod8orvmFrDJGNQO0dlP46nPx/hQi+iFaIm+zEJe1r3ku1c89Mlf9SvogcrtjJZAStJqM6HHebdkXcD9C88jWTfwoGqAKQKCIGhYQwIKQAJVrD5lSJONeg/M61yczCixWf8w4LCcqotffYzRSwdjzlcBzYciOBfzJFCIO9TDA5HlpTEIHkWgF3mLkIFFdZEPDeBC0sJ8SEqjmnDYGicsBmUdOTShPTzQmCdflTCePKLsQxqoxrGGu2Miot4sIzRK7Cd3GDouInEKSdUS1wgacvLurTlS0M9NlXds4HA9HOE5OQYn7almlZJEpcVYc3N6DWpyAM10O2dOJo0bLKcSFvKuKI5KMWFJi62XsV0OTFk7IRe4mYVZQ3JcFt53+BLlx6yVSGoAX4oZ5z2wyaDyjxffYjVnIpT/rztvoE4+JRfv9hJqK1Lfimiu5N0vwqykFihymEBW28m6V230Q4VgK4zvfuKyOqPZV1a4BPa9cG6uylIEsPgf7fOr7Vyv2C1GG/8WMDheodhghjWSusjP5byciXGVI/sbxSZS3KV8xd9XBMD2JjOgMR8xutRtFWdfKB/rgi5BitXQ4ZottiWu4ewVtrUw8rPkSgMRKdmJvnwECcQYCywowRIuib5UaRFmMIPbMGkdl3ItA6yepmV/huI6LVhbgJDYEpBA5STkd/6MC3AFwxPC/d0mqeDJ9MGL9xjuHOG++YQHewWgVNFqt2Nln2nh57xziy8iclGDhCzkZ1HuyzORQns8H0lGdhkw7v+crT510Wm+UdFBKQxYoj+VZUI+FuXQy5Ks83R7QsyQwz29KaK8Q3ycn70tUMovUotQKN+7MAz4XhywtK2Yv1C7bGKv5mUJNHvTToR4yKKz0iiy3Ydqs7wRYpJE46U+FhQthdEmtO1ldGvfjwKQKcnEHhMsrSs4kd6qIwMbSZwM4ZBLmWJyZzVSwTkAicAGgB/dAGu1BUUFq7SWI4e7GEEaSjyB30lvz+WXggIWoISbzuuIh4hPsuFAfXAFH2W6F4tC7/Ja567xD2bti9PEBO5Y9NZrij19VhpzDNEFxGoefWjhjPAZTCnryxued0WljC9fiy2OzuJmtc8Kn8WSMXQBeNYTlbF0Ic3XxJI1k4GvpSdXeOWz9jy7wFWx0b3PtGkp898bL0aNbs058cidnWrWjSLhC0jiXlwbox95zLRpPKp5fbOn3aRoeuKDy8+fGb03YTQIm7svkthyvcjiXrZ10VbRWcdzBj+F6AqCC4FBCaUnSl9NrJYF+Et+UokYQ0qd1ROZVeDW16u3buUPHDsm9rFyHj5wDk/AgJ5DNsJchQFPCHLMVGPOilILnGkrkPhy1epOecPmsPRnldQV79I9jhSEKsjRQMRcQGk3D6STnR6SWFIusENGYwzjXzFTc9M9BYwnU5tzlsJT4QEuW+dZ+BkRz7g/JMLHsvmlUL8SSGEkIYRkxM4YUn9sl37baMFTdTWWhz4UB4PvpswaKQNGOVWyKTbJcYi2QvkMTYuZ1O4f6KvgRW1pIRhSsZod+v+XDl5xCZV4PVAhFcrg4SecmBV2kLZgqhZe/G/eSwd68sJNoqllDZc6VexcKsthDVsr65VPnMSjB4scSRMAmZMpzfjMU71IujSkQ707tuBrN7fXyBpxBrHBNi3M/YBKjYueCzy4kSHLHlMArxN1tF7WmyQeq5hO520hlvw8csWR2ZEkBBVN2lbICg+6sO+NGL9NA930WCVX9BGOdUcPrK7nzjaytVxxznbbQ5spE9mbwJPCMW5IZskLEtkGcItT7KzmEJTY7ZtcY4b3fPYFYubDcHREsXT94cjmjIwk8SSiyClmiTaYDSKwCyTLdY1O4I9cOshdcABjWv6nKxbyrfd/TaBSVZBjuqhABSmzckJn0pcLcnAvr2pTLzHjhnJyuEbnBjkdsjirECW/fhYeNPGxcBfnBSElUpI6kvl4PISI4KpN7GdgHMVm9Bjv4lCeTOF2D4iV+rXHJfy54zSUQYapeMYMIPG43xXxQpzPzUEJUhbG4o9UjHBEmXn32W0z7A6YksJTGUK2ZsRIowy8SLYpNMphHtsCpSFF2WDCNWVvhpecFrUlhmBIwlK2dbO4PkIVUZHWAmVYpky1/nkZMs41VPr1SEjt9iO/Fp6VWhIqGCVuPrl9RU9w2v5VBnZK5YNoKkypiEXTgxPNiQO5DhROEUsJseYY9pjCNESECdefsXkyKURezvDY7K6IheBqTjJT7VNT+NJ+vjJoAmGPlIY0rEWGvvpqxeFI4kBTpi9N0m54wA8YO2vrvjKFpc4kdLMWP0jemcOOPGj1n9PZXXLHjX5rySsyhHJBoy5JntAE9DNNVak8K1ScgDUfTltyF4k+e9bp8VIehkesZZrQsYfdkjRiv86nJkEv9JrE9FAykpYy51Mcq5kZBsMwM8OLMz9uNP6tLR6gg3ZW6ByIJ1G4CFI6A2xqO8C/48euLBYpUcbrpNA/7IXOigQT744pMM9jQhxhVJALU0ESLOAJ3JLPDrmESCEkI8gos2wlBc+LccNjWIxzHMT1gqVIxF2eFhYBBpiqAAxoWDOHbnwpYJaEgQxsIEIilJIkhEz4WawkKYW7hipbOvAqC/WkMXPcLYz8tPgbB26aMwVWc5jgC4Z0eCxT+9L0iCGSbEvJq1b/BDlsQAwp8J1wGfZGcMRnYtObrzGncLxiVmCzrtAEqriNxSxQoUWB7nBy0glj7NrieJU5QsD5qjJk1ume4Ctu7/blAMcJ9T2ZvDq3Q1rkgdZRsBeaf8NHmUijDPe4dQPPVaulqVBAdhJtq6jQAx4BhQAEBC94zcnQ7ZDcxXdaoBqJvBgHnsrNGsnohAvUC2pSuHqsC7lYH/KxKfQFTGWrLqgUNF6fBm++YcCWfAE5Vj2ASTU29W50jlGIZ9BnMG2rcJqSd72B0VPK0HK1Oew5L+ujlBUTjubOzsvak3XooTEDerHNJ70xDcRDQj7PAbq1vZhi5TyCDNhYf5cWFnAl/otn4myD8CO2NuQX9U2bcXg6sSJFBC5u0KeC4edbiAnFu/dHK/iPzbYVb1uknOhZT8O50EYe0Kp48g+dZVQAJKETplO5gAcWbmk8R/T65U21QrgecQemZNhHQoqBIieKTcZ4CbcQKZcHjY7gOhm3qr5gUIigfu1+tFg2Bm92VsZJO2VFLKuaUxonoTdEn6H5BavlIQ+usSE897Ld084trx9KLPsIQBMO3B1euxbW3zLkj3qbcKpXArcjATjyokchSgIFJllsxnTJZaRYTIr/DVJFPt66MZOyV3rugL7nUH8jpqbQ5DgYSTjyRBmCUdIu3CVx4Yw9K2/GOQy6EFrALdKIAwNPCW+hESlMrivJYpsj8kswXIFYA1OSPqxAZLzGqRJviowyVuTDdiWTSpRKqYUEwbRaPe9DH5+AQ8jmFBsl5UpoUKfWiqnDQ8bUw2Qx1+Px0EC7ZWt0zYcdnjt5zaftBDRl0Gf4bicX2sy9xbTCSJkuS0eWI3pGZ+EbhcFJqcBRDLQ8gFQmJAxpZ/dn/psCUzSycDcwUZkxWoqaoiQuVrXbqHfxDsIlY+3mOzZBjtOTIumK6EGzTGhoXqVA2KmyElU5MXKsDmjfZWnQ6/VULjggI0je+ZuskTmcWpqBI74oGRA4AZS400hONDdcS02jInDdM0JUydTSUmxNCOdMCjte4cYZa87qOyEtuGR4Hf+BhNedJnOh+3tdo8s89M+/XASlK21pBU3M8FlfSHPBYcky8l7UYriPUl1pG9drkD7pPzI7p0Sa55C5twfD6mXmdbzl82Uk7uPQgGBMnlnxyHTWwLpUviz2VGH+fDFfogEPw/NtyMpxIx9HVk39ceAXGP6BaWxe5t81HyqaCCmu8W/5Ar6/lWuLCyfyY1r4iCRZ4xwXQfTfYz0n0AgAPGyOxA8y8xjusvxAoIKvC8Dl1sBEsWTTN3nfEEP8QOwpDOxav2XCAtrhxgRNaeNT+M5a5UJqLUACai6/s96gHzUafYE834NDEPCVImiy+GInx8zRMloSm6r50RS+q6+sKZyrzzRh92VcDJ4EYGIKEnWZkHMjmTQirUuNxauyD7ZW2b2CPfuzQz+Q41duqy8GpDKW2BRD0ipKM11aLEESQ1lrH4euV1qOTzRINv6VVQs4EdvnpbSYQcHzyes+bXPz+h37XsW2at6YpGVV5+W3HAcAfFSgWh5TKix+POb54vrMtC4x171uozb7eWv2gZYxUKp6CLA3JmITWVfsBdc1zPynXfHzgJpYQW38bNfmQGORQKT+xL9ta9okYNeFxw1eoh7l2t6+mN5ohyGb9MzhhvUDRgDFp8LMHSS4GrGnntym9Cx2YhN2Pyb4uHIEcDfx5uYPdw9kbV+z+3nS9eUbJOiSfIoAAohaisX94WI5EDIPgzXBGFS0I58c6FKTjbXNqPvedJ/FZ03VhFM3RvQmkT1texBzdDBWTk1BKnFYaOPULGRJ2DD9pyvOTnffypJbjLFn0j5494uVP3720zZDIgfPyFZW0uoWAJLrD/l5CaR+/Jny+SLFKzPB9sxGLQCTslm0WyPWtkm74tXf8vvkvCaXz3Udiop3meFlIO9Gt9pirP94cvUNDSPBoKouebnxb1juOH055bMDMQ0HCZxvKEeQ+vw+EgzFJo0PzU0y6PM2bpwXcIsfZMmnXk+RWk7MyJtuQmbaVxJoXcD5XVbioSnfgwsgmhqgz56jhEMp42peWSBo3zFcf/eg7c09qFRuaqiuT4WLSh/yV05G7di4IflBR1YIAOBjlMzhB7/mguVIpvmW11UhEKJsoUAXDDEEpqU3ecddt2kGIcNbcPS7RGHY1COpN9PB58L9iHDe7/fjei8RIecvMm9kl/FZXdP2ftFzFPn/VMkP/cVWWKt4w9xzf8R3XXsyOTf8EuvyHQiVY4iQVsasXvTma2P4iPlq7Ul7xSe3quQm21Gw1RTjCcatwq3/rcaMFzwBMBQTj5XuTf1Y2zrbMvP7rDc8S9GC0ktQ5o8RsEJo+pb7XJGj5vxnUBatF+P/uV+HE9NeOVlHgvGHqCpGV74rZtc60cmAlbFHob73vp2cB1Zx567pt/clVfcsbM1+hFWeHLKnYIJJ9vO/AMRqFAwNYKCjZJn5JUvF845Ds3icjd5ZniBYun/KUHJBSePR29d+YaNfHkssHXH+M1BK0zcfVxOCUDBBE2IV6qMQO7rC5x+3DQb4x/N8hrc5x3V4blSt8l5xf4hWnu/2mJOcLeeTP1YAo0sdsHA0CdZk2X+1gIXV/qWCsE/891ft2UZf+uUCCTDnEF2LPOhRQPG4YC3Se0wLy54/PJ9ZjOixHC536H1hcrMITXcUIwiumIsEMaM2+d2IuwHTDDdfcVyXGHrZr+F+N+79gi/PxAdjUHkQHH6DVDtjfznP7I4dJVyzViy08qz83F3EMHvReDPzvnfdJvFVUONJhW/0rjqppSMss/mXCM8Hvor19oErcioW+v3M2ca/WBgGGhl2Mbb7pzVnW0uhiHe2CX9MrQZ8WsqVKa4Fz0U2+7rd5Mhfv3mL5RtBGGZ/pTNcNasaW6S650WUk9LvPLLZINguWZIp//GSLCIhCD0lKilOug7iRSzqg/n0w4O07M6MaHYfQdLBHj8n+uI9qAmPW9N//kD5WyZtL5oc3lhtwzEbJU7jdaVkIyM/9V4jfqvIrUctOdFJ/Mbk+S+ciTLe1litFxWLKCUjPbQkI8DR+N10WomZz90x5rglV95evdOuof70dVd7WAnpdOs/Bp/aUN8cdiFoC6BDn8rkIxfdd8Xt2neS2Zx1UmHEEXH+9y5VsMa7qjGymvk1fBJD30WmlDDxnTFcGcdx4W0Dvu9EyPeC4g1mfW9jdPWC4H+rL3a7hmGrHiYdA4/GIt9ulcPjlONX56yRnxFfsdIu2eu9R+y28d37YtKm7Jx30F8dCp7b6IhvFoCFmIY+VfJO9N8z8BX/1db28MnyILJP9Js9+VbHvLcyRXDI/78OXQEcSQ798zGfYRv5Wllcazj+cx8cikwa9g8udSjz3iaZyz8pD6/h6dAxLlpVM3wMFhLUCqmHuN1gr6okLRzLPXzLqXCn2r6ci/6gcapZijlIceGPbkzgqmclj188+1OHYcm5WAqb9trXla4T0jLwwfBib1s/Tke05iCQYUAWBM3uIzZx+8x5+VxXmlEiSLGwuQa6JAKTZwlntEciLEtlQV69M4YybbE9dFbqcbxVJFDfIOZdS+VnvLUAXfe6F/k5PZ+3ElOpGYQhFtg70CY3Bq4JQIVEAYCl4+/8dT9ubBc+/nk0yg80cSyEbgKdwUyHqT3BdDr5OL3kTa32+pG70n7cW8Ky95/Yp0cSj9wqMDS3194fYn2VxqBESTQGhdTQTbDWndJazV8cLo2Zbrz2rlFN75UTXZ2+nmBcV//N2zFZUz97w4rDpDMBxyrXI+aJdd/IKP/y25dTlXCdTJ8jH+S93yCIlWJGiHTmh6/mqJTThuVJ3j1WoHoC4aEPbK4hHbxg5xZgZmmBxTw+d+Bvi9rO3mJTZ5KC/V9iVqkraVu8qOKDZeJzdcK9RFtg/45yUhBCHVrqhaLjgkmAJ61AAUQtRmWrTPV4Qdw1uXEXqV0a2TSe8iK/25CspgVWjmlyTmMEmsdac5IlzS6W3pxpIywWTzIe8ObgbCwzJ55AWUr4EaPaEh4x+nkkuNMAsVCYYgQN+kkyMBnV/Zq4GxctdvezCX9uLc+pSmlrtqzrFy9fLnvlZODltJGOY+DUnlXAiGRWFAVbTMlikk/2LZB/vcbfzYtSnLoaGKPtfOeQe2cdp7ubIDgLBLGIEtMa7/niD5Hj1zWnmEKSpZWFCZ+aSkNCs4x5mjiw0EGubB8i4nY6sDQgvzjJ6WSHy1H/7WLyGTLsPwmVB+V+/A/nnEXeA1oCM0xaazXZ3CTC4+E+FMGG0DxlpTNa/AX+LGuyR8RDRWv4/kXf6l4cbuqzF+cP+60DbvGvrx/ZhWLTYd36uca8BRbyYiHmw2D9/Ss99DqQgQW7Cot2RDeOfHMbzhq3lahcq9eDLCzYl1m0I7vq3DeLlkrWtJydhjSi0x28rfb3zT/IA+ZLs3/pmGMHXGhQoxuweZ16P+FE36qEHRaPyX9zTWDKlM+SIcLBVPJfOOnwu0xXHzxT+Oyj43HlH7Heg9/YGGjWQYmTIRRti+7AiSMhc3skKTI1gCalU710HZ9Uep7G/beHBP/g+7/2bhWEo1pwBkJjEBiwzYfSWRj4CbDY03mUSQLlkEeRpV1JciaX01KlPkxdaNUrSZN0Gqeb1rMjt4+QvPEV9c8QdorjzAwNf65mjBvjMzXLMGo3UM42qzzLrSGzsG/D2qsB0VyC84Py7V/AORCoDPf47U9BD8ptIadION4N06ziNrVhBG4rCdl26EaLvnIzMs5UGZrNa6a7b99xvcpHvpNf6QI8QQlLi23AoIpZs19H7sY9mJ260Nr3t0SGX0qnP4/fwOXunT9NYt0+WcCdI6ggTCCRFIDPppcSRrbUJEdRt48oX885mjihxhV6hdO63UYENeGrstk3cgDzrE1vAO6fgus5Mww/CI/9//YIttD6G27+QtzOXYo1I9Eao9MAdkGN8d5ByzzdChewaNySTQCp5po8dGIabYMpohWMtdCleAtTMrvH+Omj7CRUHL9yCNwZX6vQuktobleTA/20CbK6BjhX11SQeACfMdWYMUfRlStFuhBdnsV0PIaB0lJBIbyLadKvXes24rbwVCly1LPn073KJtBnO2+zgZqlHOpsWPcsZzQmxQmqiU0q5qDQpFyFHSQxM2AJOI5t7ympDBqs0GyvoST2K0OKMOSjUV0vAEjx8ArvuoAru6HhyCOYWSaU2kil5+XiY71p0oTEslxO6a1BhcsZT+9fSs+uio51p0kksS1xDoKOSFcYff7U+RD1fPrpVq0Aafu8ip09y6MhUGvtDADMxAmm1et2odNLZ6bPdM1NzR0xqKs/SAnv4NiwVoWb1ERpdL6rXH5Zk5AgaCUXMvCJBJb0Cq60013QEh98QcQQSwQUZ17pPShHqW/GQcmBdF0WbbUSN8KjKsPVdMSFp4fNSe0SFLkRJC9DgfTNhGsPB4SvCtk9MaDLiHpkoPKjawXWc4GJkGIDg374RYPfMb6Z2uoZ9XB4nFeJQ8bPF+1kKpFT+QWuyhbD2iwDTKZDxW+jkPF2x2tlllu1GjSMT8ZLOdeaa3IremT/CKo2F9+OcwUP7d2qbK5k5duaeNlkhZevSA+g7NNSXWF9PJMb0SUKQjwdZu9P0aanJkwO0ZYb0frJ9XzCnIhP0A2RlynjQBOAAYikgZaSirk/PPr1tTZ91XE+exoiP/aD5TvoRY2Z7kGj3JndXUQ0ev04RO7E9ZTry4/o++nM2yY1aEz5MqI4P6YQ8GUMrkudFWTvgn6GIsZ+BH9xAf2cGzG+ZC/T85/FwJpT7FSPZL/fM61c5uR2zjFERUKKhmiU/g9rIzc5P5koUtrUhUZlDjthJed0uT+V4F4Lov2qGMb2WYkJ0p7PP68vL7wgI0iUUJalN4PrQZkwqSg/6rPS3z6ChJxTrXx9amdcY3vD0KWqzzS/75rmL36TfuKGOxZQ5eZbnp2+Dcex+CuNr1Xe75oCLTW0fA7ZfEtOdxGE7QFh52DExX4WJWynFUpazrg9ULxaVVyCFbRAU8NSgYvH+ceznsP1RjxxYS7lBAxNCZ5wa5lzauPRSmckMefjUbmnOjHLO1Uw+gPeSUTLlklFoAlYYCUuRNQzMDicYn3YSwV88Bx0l6VU7PtKIZuiPxFpakabHXpz7GwY3pfxniMMHZn9QCPuzsSHxM8ABbCp7K8/LzUd0+EXUNU+QG89T1FyjmzWBY6/7cqQfiKI2v2iZ6SoPY/qZP1LeDES7eU2jJbZy7+ODCi7a5gThr62QG0ahUxqTG4KdCZ9uQvc/mSOJiDJWl4iiegKuyYYRND9Lg6VDfY/Gw+us78auCFKoHc+w7rHEp15zAFlrrXjubw1AQxtCOR/jrtaFUJiqnVnMuawjdPxjklBHv/+GFF2B3S7IPX3mfw4oX9hgTTozZ/jADwly6n25u6D/6kuL3DX/h5Aibf5OJvs4/AY7087hlzP8caXIz5L2Dba5gk2vbeKR0I8rQ4R2UxcUMEwMavqluI1+vYyq1Uu7p/Z152xhE+r71/MVcHXibCtPRWSMEdKfW/uIgpMvzBefscZKrPV8i4oPAx7VkUjNRXyHQkTrgyHBeuSizi3J0BmfWL8tWNh4/3agG/PMZCq2tZwFNofGSDLdaBg6eMlv2eMHZ+vxkxPP2op+d56OpdT4GFNwTmyWR1R2XpUo88bTOS6yMBzkqSBXQL8r14YYJC8QMdm2Sxnsfk1gSmolwPxElksOxWq7hH9JtS8QWlEq5ZDA0Z/Hk62cFBSAKhtH/JhsCIylpdIBml+JQ6HYzgWeYUMud1NeqOyr7iKf/2yspd3etr7MDYuopc8pTue6c9aV58v27emcfBGoZGjI2DKTFJWZllWJjLHcjJHOaW4FQqpZ7NgioC5qj/l7jHu8I7PWVL/ICYvN/DmHWroiBp5YpTQL4Y3eFPs+vcJK8Bk3/1XnGKXObYqYSwKgf+V7w52iEFL+W/zdw4hqP9S/cxz66i86Ko6DHN5+bPz9fvCnB+R3nNTggNb9WCqkXr5jUzSowd3pv22NTJfeHAp0pzzpRAnFod7sIfm0hOAUtIIuTPiJYKnQArWlGadU7hewMH/hhxQIjo9LRKau5rfRrU4VLafwkEiToqKMRwT6jRtwEP9mvo51Rw69HKhbPu8AwtSsW75rPYrQyZe+bmKPskAO/jwheNoRc1eI2jtOqTVxa53IPfo0gt1UeequHf8wVCb4ZsvzbAaNS7oFol7R6my61sWj8Xp3pZhoZfEfwW1ygMytKpf/W7hjxyiSblAs3J1302gmD1fJKvAH9XCl4gokcy1J7l5/cygfjVpE3r6MzOtKUT9un4XAKzXQGvzr08Ln1+jhqXVoFyNC3pb5r4ybJ34jtVxRcCQhmH2N8RPg1plASnq7nd7r+8GDuGkTABWru6BBIpZ+6aH6kON4KWs8y2zJbnOgKiUsuPvxs1tcFK9kPzqDtu6OSPNwTJgzWk0WdHYFMtlq28aphGMA4F+atQaMp/FYEVl/J9VnYvbvMNB5w2XNsw3wPD7FtUr1LkAGkVUUtH0WXZckG9yQKzS1Ye0OV+8ISqJi5hy9Rm17Bg1zC172+KG6jDSKLGBKm/DjBBz7D0Wnx8ChlQ12p/hXM5slQQkRHrpJ/UhVXzWQolg+8ySl7WKn1DDqe+yH67y8H+HRfPuvJYUV+4RU4tYSBdJJRIsa/98t4Ha2PvQgSl98Wx3cPlurZzXiZu7NjO4kyOPjXS4jYNbiPv/V9ekonH38TtfeQk8dfGbzY3JeKYriN4aDG9TNZA14VjKY9KDF2sCd8lVN7tzLvu4gRkiwb987wEaz8wXQaZ2iG0GQjZJ8kcam5dYiqevJk7CM4kpv5q4ATvHVhdEnSYN1tQxsTkrN17NWeDo/HsjUWT5GCZ4A08TF3LwwPq+o2s/4V6L5+bxsTsAB/s2soyBspRALuwlp+h+zjI/EomFFV+erKKdrWm/6vAsAztKLIMYhuSdP4oSgWiA0YBj5+X8cW7b8sTcB+wQdRF8D1hRYvX7UXdjr9wdxEqG33KcmuH9wkn42rMVEK1R3XOndp9d3ziawuixu2HNDdx1Unjf2UugSXYsyf0MC6gmUnEUc+S/R1n9ot0YCcyNNhjNumaYycBjxLN5drcdFhrgbutGfRGHteQFZfVep8/h3IrjdU1EmxTnxPEGI8fGYEZtMqKJKNbwyifGQiLKhETpL+GQZehQTWMSaRmi4glVXh2Mq71GW/lSPvfS+QJoctU1Dx379pHy2vI82zVMY1et3MtmxuhQlbDExvvIy1Icbeh7kPZXq0jNYu+AeUnjV7VQYkoBCCT/oINtYK+rVMz/Bzc9+CX73DUPYOyDCiK/UHJzm5SfZLCsyxl+7r5pYW9wnmS0lQundo8IcBew4tOlhp8Xhb7JNfacEFioW/Ew/57QyTJBWax05TenOTWRqLoOwp1KUTMOUwR1nO5A1LrQSGHJ6XWTE6vXJp8ZlN3uOqPclkSfahOGq3ax9TEAEaEcQhACLyRmCvpRf31ecF5j5FO23XM7Y/LDFMH8igbleH7qlpkTwHuV5D3rrjMcYtv6Dk8L/5HzP09bDTjxOOItEIsv7Hsj3/Q9/9RTAqd1/AUSJl32KtsEvph357ekuSrig38ivunTMVZSs+7BAFB4BDUtYpbEFr5in7fF0Cb3GAAmRtyAztBzi0Nf4rT73Xqpk8j+JOCyBsdyiE6wUk7CUgCypDZn4EFWgoWSTaagbnBVgkVdUcTeGa0njxsiG7LI+wyZ3jeJnC8cf7Mn32BHcbOwNPlJdFSLxvTssPx2LcUZruItUaLjsb5sjAiquhfsoLqC727FOEnKzP6sAhxK1KAs3YkhNYAF5NijlZLYMsh6akGh6gmtZK4KYt4zP5d2bIH3cuPqCZtDljtv7JfRssZGRI1CMK086MxNlP1E0RsHUopjA5D+ozXBrGvw4r/n3NuW1Hh33nVEp3P6+S3zigJ9ty8RSbjnOyqxlHgknb78hfq+GrH2/0C14kvwnWRiiY/rpOdQLG6BMAqkrsVNhFZ3nauNDuwLomf6bIcpMhHbhAHKGdafm1VBxJmRJ7bQynFAuRKMS6g75WbIut44Id2XdBFPdILvFf4BJnCXge2pGJfQ3T6GwK/rOW6fk0AIJKCXUkwdEg3WN9aUXagS3jDwwT0HRcC9ququSVvoWlpCfA4UmunXRqy4bnztLou6yWkBDPFRTJ2+i4ZvN8nMu/rUhcZ9ob7qQWl8c23Ird61YJ7ebTkSvOW7MMPJY5ufRui+6Wu1s/qbd1lmub5JDXnBNu+JIOtDPnlG3EUZXEn8ebQGPxDUsQDbnE5lq8TDitOpxLEPi4+FFVdseyoYQtENE8Ox/WRyx66ja9RGuJsKODmlK8XlgavEiW+UJdGonrKlJYs8W8va7/tc6ukfEWATq8KPbDjkfdBcJVN6etwpyvd+MPykZ/xe/uKb3YGKtKRRqi+HsSu4KGj5dEBVy6aKGxneHNO+BuAJRz+HRjkskZ7MxLG1uUNX2lvyrfw/6SamKwevI7NEb7gG+bAWs1SOa54qILUPAIH0K3vQO/VYILPG5egDz0PPWrZGPxt1vq+4HkWn9MeenbNNxz7Vu6sy/MlUvPoPvpoeaTxT+4ERPzkN72W11fzlbhuFZtE47UCx5V6k+VIOYCDSuEOEDlZAziqMMYeDFUlblHGKyMEJlIlghwAcjIiM6Z1JW4MbC8AK7c6XYl3WAp3Gs7plQnhYmDU0cWOe0u2wlFfeOdSR6QOZ24E1QI4bAeQinANANwTQRTiIRCNf8bSo38Eb+zQAcuY3XgaVCRCX04fzYT/u5EHG+Dj6Ey3Ap2BuoMUYKVLCzauMFTsqdW0035fxtcxEpxLHRbuDWkd+1R3ekzBsnFvf8mbkceXg8xk5rLuG0buzyxTqoz/93wzEtSKCgOT7qANwQWrFLsEqejn31gRyJdAWVpevLGaOfcvqU+n3toRNpUokLvDG3W9s2/eePnCbkb7p/b1HOZPPI4c4sVmAlVGImtZMd6GK1plnzaJuSpdU3NN5DUs7zm1AcT8X+tX6Q08txE6P2hDVSgv4lP1xvfIyarjINyJknpDkFKoO5tAqoLGJOQ11MffoaPDrvx8ptC7dfMYjGCw+O1jDOn78vfD7jW/mroD3SiyLGIPknZzLvGg0ynig4QaQ+7uq6cVp9rfH5/pXQJnkV1kpZMlCQBbkth4JTwgognLekvgx61LkeI7d5pg54Xb43psdxRBNs5Xv4qH2e2TEZSQzovQ+fsCFGMjkSSangJSBWsD6Qic9iO9/bvJk9CVoZuuLyzt025obXpqSimfiYMcv4B0hySmQaXWNBvhVKtH6Uqqvq7I03va1hHV7qr85sPJvae0r4oZbKucWZJtX9gGTgcCoTgKOlhf20thEvHt/v6T69V6qn4U0+aZZ1+XT/dtWK+iXcBuXe6C+7Lm1VelVMjYRg0QkHR424wkwHoyA1G5AyLpKK+M81r2LkPAbcXeBMrf6iMvmq09kmMydQZA2Yl8N8X77PIdG+ULjnBfaj1jONRoJfDoxAsChGDFgYtdpvB6fWbbOuuSY62vpHHPKdd2IPpdlfLnjCftVajsF0Iu9mOAm62dL8svTsv9eMFBVgrmMiHhZwjl8F09aeb1w81kVlXbhz5IOB8yYJ3jd/46ghWdYuX2Wu1v2yI/mAs6LD+Xm3ErbxW5aObqqe51w8fhgZGsi//BMns3QmC5bWYwV3FY7GFFT9nOPJeXeWpmGW9IfnZcZf0s6IFNd5Lg66/gpaPzsoasvTMCDGpqq5JVLUB5ZbX2D1f9Yhi2K33lnjWqOErfJ50vUsseyrSXjFNqi/YIVI0MJjtycraBtPKrI6SERhdJHZgGDlt8VV+0u/cwvXkA4K+81EhaENesYUkYAE0btGwV95a8FgDNb90ZoMU2SNRhm/pDhU11ghc3+5SxWYItu0DCtyWU71Oj6whHZrCvvGvvW/gO+m+qtEXdRiD22y6TGzoT8aF6LyB2Bcs9UmZDzGFXuli4A7mBQdNgrbtxxB4R3G1y1FxqHS5t9s69kYMOzZOw0+9Wx+aCYeX6DvTr/ruuh+WsYhYzt9H/sTUzxf/5cKKPrdLWCeeGfF50fI+HsK+xAFO/gGLqF+kXG4voXJDVH7itatyKpBj5x6s/k/zs8bwfysIyEupKQnJH5cM6pb+CU2FhuseI5Dl1ORIcXYq+s3YNhGJnUY3Peu0f73dTjL4UWUnru2817P4ogvp6NT2FjIbjQddAfJx2TBDZHiA6Zp4+N1sIKN4Rozj5xno5yHSjvHr+Yylxy9O27FLVvSEd/y9p+6BqKd3UEY7pSIWJpFmX8Cse8zL4giH+WX1rf4fzvB3UpCv4493mn1PnbUtC6UIkzN1PKNlI/ZaEhGl4c+sADw3xCT0TTzsR7qBod1V20cv/dWVmY+rPZlZlP6f9xViX4u/3RrIbi8QU1ZumXPaOAllwY7YCmcDWCPvAIwxzJeYNgvTlDPfqe+KU0zJ8ZERv9/aX5v1sMjoJ1bzW6MgpxfeMfkuK+epQBSRy4t7Am9Y1mFFLDDrkF9etfvxxPIrzp0HEo3sCYtXtlZXWekLJKlvxWwX2MAM8sPhX6Ik3KjkuL05P0J4fqc0fAOhmjlZdh6ksev2him1eHqYm8mdES+9uDhcOp73yWvrdSS1Ahom/8xcrz9xVsfP/gqeRVDm/YM5gckjIG6Rq28nlmlI8b2o8WDxTvFrfcG+tithwL4/0VzPDxVOdvtBkZfCahkM1bm+4MvDeDsVgY1PbrgxhS0AhxPsrKWmARqvaOyWNoDJFnDaO4dMiONQEk1hRG88C7wKWR1ZDeMPmt/JqG9a2WsnPV9fAu5XeDZQJUUFzh5m7ouIqQo+Pyde6d1tLYikeQwwiNMQOcztckZuwGZvnX011Y37bp5O8F+aeeCVLL47ZbhWMEBx+lzLo84g0QVpye2if02+6/5c+egh8MuKrw+hwGZUNggbosIng1BLdRtqeZ1mLa33Ou960v4H63TvbAqWc7XbfYj4xyhF0DHR0qlic99zjKrzr0u+4Fk+JaSXfdgIwt13L7K1kDVav0ik1n/PO8PacZG+oC+ppB3ZtNdS8fKs8Sn90R/DH4Z8dfr9dp01creW8HFfjtTpsW3Y+eww9qq7ar4lyZNxasBI7eUvGpF4xR/fCp2B3kNSop/P2+mHMCOqNrOqXQGKBhrRALLlyLAWtO1biuiGRFOuXfluiKC0z06/pyp7BH72Wv3Xeg90tJaopBw1T+iQCqh3exRJu1fXGoY/X8Q6l3QseeuVWgNLjbjP3c4eBPKYddbowUfIqCXFXrFhSCer4qjItmc4+AJTrKToAEDoeqcWAoh55+a1KcFExteLjNftKvNlf59xhsNVJxVyaBZ9/UNfZqjlH25+SOvVpgc2o7LlotM96aFK+/o5Nv3SBSkz0+HTU4nFWOQYXod1vHdoFhXVbNtQcbwjDbudy8L8wXhkn/e1W4p+x75z1+Qjk9p/06H8KNvObC5SASIbqKVJEhPwql7N6YoCl5YCIp9WBg+uqY2ztO7EqOsOR/adpEG3P8ndj7eknj2+I1N2q//gAqzOCid5N7fWtHx3XSoecdYC6bEWmt+wWefTA+vV6IAw4WJQXTDASd+oWojXVD9+jQ+QJLZED1I506Ghv/+/LMrspA4/VZ0eCe7mymydJKH0osS63Y9yg1L+5mooyu9bHLJrZcMdzMA42mWiE9Gy/gAlLJoWX1hr2SzkLsbbGfIcaFylm5tdNQEXkQekYN+zYN189LvIl/3LCsN0RBgipNMAP+phNzbysnopDk9rb5U3GYhnBAlMSQJEgdhQK2GBIFEfGjvEIqaVzTKkRRqKK5qMvdR9fZ9WRY4VeLSMt56STKHVOFd37zR/49LSeV6BDwKAhJyrx/p3vu2jZnaa4iSBe56x7ZMXx0L+1MiJU/vcj9/nQKTEIfYCQUTQOs6Xk08Xjg6ssSx+45XaPrvxXfGY2gAZ98jcFF1E3E+Pc1P6HP3LrJgDeEdTNp2xrS0+oKtQOgCmDaAHbyJmzi3citgGszKVSyiVQOIy9fiSt5B3cSEUCwGCEjH5o2LaaLBQlJpgZRKgBe5RjqKrftULa40BT7CFP9iNeC/dj+qFURa9ni+/MAky8XJ1s08krKFR9s4QfZwY7XzW7eoHNlDuKnf6orlz//t5s/aM7FjrQJmmbcABeY681NR3W9QePk/KBrjd/PiK6zNUaM3lOxmWG887hdI6oKF2wM1nTdPrB3VgQ77R+6vbDPIm21xjn56skRb8LomkvOt2X2fEN9Wcj7B+Rw2BDUqz707SksdTt6wLYjHe3ZPDNicKEeO0wI+1gn8B5incQQZ0a1sBY1hZ2JGtZZBdUbAOuGjurOx1O/6slWR8GQF88ufPAGFEuzPdZeLfomnt/0jf8UCSN1G7MmSUyWB3wCtI9PEXtpQljQc0PbEFJzIje7Ut1TZ/UfnogsB57MaPH88cHoeu8P9pDcL6Ymw0JQ/+1Z5bivHmdDfHWlsxZUScL3PhlCUiChLpo2p8Md3it3/xQOLk/ZU2uYgknZJMh7MNLc8t2nAU9X6PPODaywDyydLig/Yvb81eLuQlf2rOrXdZAt/wFZSpZkWcj2PFXoRCbijDaIgUjYcH+62EGPbpTSPWfZeM3AxmIEi3hZOiuAIsF42XkE8nOODSSA2q7jtxuxOCzQCWVaZv+1n2jsG2Ku2CWIEu4QDXlTdD82esM07E4gzsLpG/A/jWA9kGZOXHSpWMBfmf+IoUiiGKj2sx8UqVcdYS0bmyWPXOoa40SEcsoS1KVksIRleQgsdRNx/OuVRk91hswPPzPSIP/fFqCOi/AoH4Uon4fKg/dympDOP789OlPU3fJEO/SLrNnNKCeFV48NY8ETeHalwITYm7h0pETyKc7xsCmFrhRRYTgrlwSnQl6PGaYV4hUQx58sxxBZphADnCXYDd0ZOdeizR6X4sn0NODYMcsH/Y7vxKyBH4yH+YgzWPRvOBNQazGmYq6X0ieZu4WnmWnyXV87gCISsbg01M2801fXnfCtm3PzdJPOD6dpPa/+hTyByILSmfP4+UH+2QkBdR0cmPUlcTaBOlAo3TEotQLYhTSmAjUT3kdeWLAkjsKDSSlmyJeo7jCRvl0WMkAJsgQgoAgiSMKSz8NHazJ8zMzyqo7ySXMPcjTUj5s5PlyT4pmANErxvOKvEeaU54UUOSH5e4qnMocJSmKzIUaJT2Gb2n4MU5T6QyIo1AbT6MA3uIlA7MeUShQb+8VySSZjnonsjB7Qb6fi2T3l08oRX8T+D4CP528T0h2LGV0zc9ckVwFFRut0JKI2cU/wmRgMcsE3Dd3ePrdONP3qlQnWInegW9EADAPtZXvWP7PFn9/KrRL9lbBVYzn0xcSe2lorEJ1crknKO8epQ7kXi83Gi8ypO/Gzu47aptIOnu6t+scJ+vAzn7OTwzrg15cH64fnHhO2/WbfriqjGav6jtIurmKVNofoGk6rdbNo7rD8BKYzDlxSgUXozJCMv+zMBJdLS5BwLgvCcZXjr55XciY+vsurx9JsJQitq6Y5D0b68SpjFvwMTu2bzvITNs8eZy9la5IqOXM+I9Ha/lBjFTzVz3Njn+r49/fqdMlfuJD+ep45YNsCE8KgsciM3WbFFtewjv/K94DNKkko00y/gVk9CL6RbFWiEUtQBI0gD1pjcnNBrb+Q9UbYYblGdRifezis/Vne+BDzqMpPn0aZYr6YokPrafynX5in8/vH35VbX3+bC3oAKs2wjKUgZp42cxGE7KeJ47UUsz0J/1y1zyZ+huOWLYN/eUWAacOik6DXJXJtuTo9Iz0+mFY6mB76H544E38F57el0y8T3MD1lSbCbr1CLqPUx0PUOjSXKYUjQwBhNB0HWb0fEAYylGlWEKKsL3drDUenFcbrUXCIK/NuhtAdM7+NPYvKGZVjPTqcTsuWTOfZIfKUo+/JVi022OVLlv9s2/hWBPB9QceVR3uBSzBvHZsxxzMvPW9ciLqF8THfgsGwDoWX1Ee9lP5wKbQfMTCYGOui5X067RZtzsWCHlutrbC8OJnkKnKMjb+dLwDsjNi0//ttQZxTht0vKbeJKZXPCje1RmKI3yoU9akNUcnh4JIM09slVG3Lx4XHD14JGRoavjzykq3G3gAgUSdQsrsi3LoD2dtyNoAcxRwDuMzLOBHOO2oJXNmsxqQOR3uu3Fl+XMfi6lw8mVs0+1mLBTdbsn5gcQkRB3iAqDy5dkWb5VnfhoRLjLQp/7lN/+Y3J2X7DtTJue2sBbVcmQR4AEtCwuijAhY+g1hAOQPYFXQF0EX4pheY8tz9P8fWnReR5eHEV88rl7z3KNZBcifWzF5HTVv9Xnz8GVdURSjkSpFyQXfj9Aic8lhvcJPXbY/kl3V42IxvLyrK164BBtTOqs3kax4xmv1X5KY3UlZfwid93kaj+3v6Oib8QKQDc0HNQMMdwUX3tHPmdaAVDGkDVZT1Sxx5WfiVQL6+jPgpffc0/7akEAZA3AYrjleUjwpqPbBhqqe9MPQ/OAu/oAQunAzQ+s3Gl6lePksu2NCaH8R616tdUcm2XyUOCdJ+h1R4HHe3fPity9BBD3piHr3giYWUnjpF4lkGZssmmF+bRtGDigX30XYFie8bLe+a6wprviKuLqhEytLLWwhWGzwETQUv9JvynwJefU7tYyYHBCNOyvZk12y5NnS+mQxRFmCtroyiKTtG7IFe5NatCw8r4V3Pd/H9HN0CCCFJd+3hKO0GGJASmw2hxv2asohD3cnjBJruHOKwgA9F8OlQiQLZAAxQwF59PIlHrubej8k+qdVVX801B1SzoxrBnOf/abRiC6hfqeLEcW6gJNjk6tPH1UvzJUU6eMbOg60ihtVSWQJFVj1AK08CxpR1eBjssb4A0agElyvL3LC016Y5OsF1bQ8JM/bHeoaSLaeBfLXxFx8KIXP4pyniriAKfaN6JRtM0THYMJROXj+40WDeeiFFyFZxBHXf9Kr+XGc1DPv/7L9do4EA5Q9x+EXmGkYWvBL6zInef8kK3Eih2gjPQXEovOHfqe1zWRSNDr/SIKZHaTha52V9ZTCbUAg/yOdIhQolCdHyc+kz20HwrcPzmrZBF2UbFvwhh065UyZ4DrM6ODC9rbHxkegTAhFSpRfn0i+7jlCLIUVU7hWKxJAqqlQ9SmcNw4r1Pgkhpr4YVCjsQWd1v8ygG0kSy3BdmwEfQjvYb9yR6wbCUsBiUCZ6Pwzcj/z5Y36AqTQTz36/pnUOBxRBhxMIXkHyI8/g0GcCQwDwZOj9TMDgNn3Ro7MLYjDscaF6bFX+pAHp2GOQzSseHXlnQC+mhjLHbOwck//1YwnVR0RBhuiUgEpo0+BuLI3SOT92RIgB0GJ9r1IZwDQOuOvo8SXTkXA0/xjLGrN+2njt1juHK4wX+gTt9g+A/awwoYxriEheMkLl6Mcx9ERX5KPjGuP99ePifJM3fsUTipta+8nGmGG8HVS0ffmHyINi0a4/LQ43E5a93L8k49DDQlAMhrlV2AKCs62fxcKmbRZhUfhnpYp0kG7CxjL17ALGmF/Q+enI6ZCh77gCNB0brJqODyLGqfIvOkSEyfPl6+V06ExgtKkjvCPllQIZwe+nuy8Twu6/pz9zoghPhPNMAm2uiqMnZ7bs9r3XeOLtRsqZLzyfeTeli4dIvu3++t7CU8+VKSIYa3CJKImlxVBD/5MoKlZ3Yozm9OiSYxSVoWBRYcFkt+uG2tEF0o8MY2qfIXK/tGeWKD4SFgApwdjFAAxIQbgYbej/BMU5qsdwRjxZseQdQi8+JJJK0A5rSZyZ6YHPepTPmEG7Ytsy46Fc7RexvAHTp5xRYM/h1CGOJ1KyHJpdvKsdLLTVu/s0goUiiSrwR2cF+TYdn7aZ88gcJZeWwhayhNAfKKnqnbnT8TcU5Fz4v2tFcAHlgQUU4+u8pU2lLcuCI7FNjaMfmc/k4w0SleH7EWVYesUhPar7++eJyA7SrrbbTEVyEAvgeJIRXL+6KFIR3vRovbe5/sAvzPtv/d4F1FO6CmYPQ1gJLpOxK+sS3HKsTbMJd8lq8EqnOER2uSUIZgDfgwXRUPSY2xRmkP24x5Rkc/8lxUt/Fn547k89+bNJ2/aHo6w5IOuZjFVvAsSJEzRUOQs0nM1oHfiXW1l9wVS2lBLyrE/2hTSSAkM6qbDgZDlEZ+m3plSwflbuvNkF/jhMEHTSX1QQ4pQ2yAS7uQEGuz+MK6p1Y/H//m+aa5RuMc3ruuO2HFH2UIMh3YiNi+Y+tRjn0mBOV0axyduQYCk/kc8Hn7NvhL8YmyoQfRdkapTkUvDid0a/2xl8b4z8/UaC+9dWRa2p9O9Sx2/qIV+K/b9qX6Xw47V59SSAUrAmGPrv6Vw4mKCFm83dWEn+Y7joU/JgrCezedDTQYIObJ8g9LzyjPMGF7l+ItK9kU0EGXf2rWKL2GCPQM6oSx8crfzcWDajFZVSUx8RtG2z2DK0CpcKGkBvicS4WeAIru+rlpNydcdz2ZWmVLQ5Q04ksPTOTXD+FW+lbOf9Pyeovd2r8K9TecDf/4n69dGTGHDAj5z6BUsMCrvrXPZ38NcbchWe/3OEslDA97wBqfjWRvHGaJ7X5ft35vrszdUbGqroIvwVbrVkl1Bj3dXiLX+ZTmtTVu8ieHugzGESsvVytpfIpXMBb43qKda9S+wzJ2La471zBEXB76uUl25ovaTjxI+RhGZPBWwecD0z+l14n/86HRy6CJRL0VC70oeiIzjrRZGV5kRqf+ysaw1C2HEAIASbdt1EsGG+ffAQw/ete7P4vwjnTsaqpa1vXh943I/iHvuFat112irpj/Cx1OD9PMtu2c3FwHoVkeXnMrlEHhfj12iffpvuImU+3j9HHFBBzXn2SRY8+oOU2EwocHbI7ViHd/YDMet1cfgScH1GHm5EKrf3FCrIjbj9y2njv9WrkrGrMtE8WL9NZAW5XDQA21gN9Qnj3iX1mROf8rEB2RKyhTRrG6DGp7dG1B4l9232gxY2NOT+WkdB+givQ1ntOATabQpBLMEYOyZoIzWr8hUG0kfDFbeXoad8CWpQtfT2w2DnkAs54KPflkH6L826JHfxt+dwaZMMrHO51OBx9uFKJCC4gtWIJoscECoEuxD8Oft1rDcFO4w309FpsdMB7RPITGpX6ejf1H30UA4hCnkjZ+SN1MjLJKI0lVt5QXrFBTWUO9Z7PMfFtoTLQ7xmSBtqncu/z676xzHOpKuhR3n8N3lOcKfdkuP/sZEhC3eFDF2fJPQ902OMx3MCiwzU8xl7j6fxP4jJom79Z+eaG//F4R/lDKHHmAHUS2L40KK4owW8q1WUgUBgcM5gysV3vJ3xNxrPFKT1xW8Y8dFzt089xODzkcCKse0HuRcOXDJ/mxsQ2BibTRJV5DssofQ7L3PRTqPkqcqZ/pf5Y0vjxWQTWSYR5ZSJuq868/L3/wTCTaE8z7beSrj2aKHfEZPwadKW551Dd0/owtJaX8FH59WwUDWjexfGNuxD0i7Il/m4C4g2TuhbU3Rop9wAD76vILFSSZRIpUCT5qmX1dd0INLSQ1wYdEqF/vshZxdVwWMRjf8KrZzNbuMTXmFw86oYc5MO2nuh3DM90n8N9dDxus4OKaUPdxnA1+1RavniiAHpkrDcJfeDtU+69Yy5C6p4unce/LzfAx5PCNRXD21E/hLE63iXv3eSqg7jHtPAlC//wb66AXGyc9jzmjl2l1MBT8ocPPL40fE5sZ13FlIUeeS9Nvz4CUtMLQURe+dxB5i1xyf23/Z1MfJfnOM1/nSXnM+82Vg3UD20UeEf+qujpMXJlx+1ATyPrQSJbnCB6+TI9517qe40jZhpWMITvvFIoCPte293a0G19dCmrym7/eoZas5Zr4bOeoI0wmQD8wfVDWycTEGyCYlDWakNoFcEk7PKn/SMlg1oZMpwwEWb8yMrE5kMoCZRSVVESlTAJYUFk51KSCcQVJ8cwJ60F9zVKj5q+h8t3ZJ/bRiiiP092xIU2mSDMDGKnJ7ggxeFdrLNvw7g3XiXax8ZVHKhTzCA1zhn7W2L8B2LddNxkzjM3F/bAy4kcWPmRAlt3mVQpmwqLEUkXXH76jFYY4liNI7xGMYsXjJmlsxolRNzXliU7QROzjVXRt71NIxEJ7AY1G3esj0kd2C0gqcdG5c+Mhg/TdKCvJiP6fL7K6K+0RFTi9c5d9XVfWTI+4vHgTzBH2nj49OUfV2atkB7ACpf4VsLUyVJSe8g+gXhMkl3o8QeWTCO9OA7H/W8vM1mYMqnYfd4mdfdzpqNLB/4THzd2B5CKlPksS/VHBuT1Rmi9kk1unkj/WySSqBISjrzG1uCCcY0DCTKbd0CyNJmMK9APTTJJrAk1QikM7oSFIMQbG/BBw5wp+NYeP7E9ysuvu995AjaNX13cEPGggsCiZaf+cnHNrWGtoUUn3sCnITlkTygQuFQYYpdW7/LHvpGx0FTL/MQSWe2vV9JZyj+9Th4QZsquXR3t/8AUExjvh/gpIxuRMQugjaigI3lbWaubGN7b8sm0Uf5pSvr7NN2AKmcTHyhv2HRkm17Z/q7lIcW/lv4tkV8/mu6jIIa5ZfteGvF9laaCuHzdSIel6tFHA44AdLnRuHy2BoHevAt3c09jSxmIdhsc/1f+zPgP5MJv2Pq0S7CWLNrHbUo2v/DhnjJoKwCFrRBqIINJiIiuVDGlJYZMQrCWcaEjvqEcTChVOvRskSn9MSNWjMizn2xfD9E3DPcO2Fm/XtDkqdlprP+p83A6nrEcam4OTLjRn1Y2KUpjR9pUzK7/d6AGMQDWIbZjtVIfRhZToEOCEJpXGLsy9yLck4RaArbK6IxOLLqmrTI2MvMbFN/5bKGSvymqNJySZ77xyVg5DPuJlRcs9gf1O3yG+XRdoY7U7rSCie/T7l+jH6EhOM5eBXqqNd5FtEQKXAfhVuITROmKBpqgk5PQdcmZ7Jp8hI5OoqSb/oPmiloztK5Uj5kjigb8FsBNfZhBGQS5e6zu5Rco4GERPbZ6n1pbgSoOOoIQmE+lvtAFx0CbZwNzJwZjZwRFKqA0QMG8rOoZqdTWoqHzLpeIzdgeGcPj+jFUQvkfOctxvquAxWU7HEB2BWAnDgYod4E4mM6QOeYi9y5P7p6AfTGwuUJiJJAU769ey51U6n6pgg/TTRqZFGF2cGyuSyf5foMoHTJM1sT3Il0ohOc0psYL4iU1Q95LfigD0aRZkjHpx3o0HX2Iz9wtGVb7kOj4TDJF9S/9ZRRb4e+IVKQvrj5aX1u7M76iLf84E/9ZdzO9owp4ueDCcvOXVnz8GyjCQlk96Vg36wDonezzunGMLWGj+5KdWh4zizcxQS+0DboNVUy+7bLjrqs2zMHP+5deZrog536QXZit5KTZPL97gwIN9a2oe10v7QsbU1hObsJn7WGG1N6ysjILDb6USwbN5sHr6ISFyMBiTCG4xDnA8uLn1pGyZjmgNFibEvA+j2jPdEU7ybg7M7+dVomwCUM7nUxVBACroLykMf6ZIPDWRNaohEaUuvYTXNjyiYGwwcnPcjr7EgOvvF8OMHFAoo4IAKYTbY4S354Pk0vzIg0cpkp3E7kBFM1+u+K1rdEF9JUH3z9/nJfTyo1FyxCkWAzb4X5qcP0NVUieShrZOJuXFn1yhSEMiPBx3QDx7lzrfi91cwUcE3Ljm0+hErRSoODfmSfRfEPsnIlH0DWT9B9hk3YMH5vvWPpsI4n9GC8hcmoG1o7s44v3QN16kgQ0XZRNAabObiPy+Du7D0W1GOJHQ7o0DrQC1AqIiO8CmXOK3vmxFvlGlu5TnnlJVD3p2x2jAhjXe6y4O+10wrfgygfGuQSwID/lLTw7eAm0/Nm8SaUsGB5wSROQba9XvXqBM2EhO657LaeN4N7SXYisV/IvCLcQXEfzl398J8/+fQ4I4eppw/w0W/FPagiFWYzO+N/gI697PqVg+rcKxNRaUfNHihhbK0PFwdax/KCSY5gSqqZvbuvw8+XhbfMK4dXJZtE9p4MNk1fJW0MW9PnbaZ3HUZeT/IYUXdyT5m9P+sLA5AxeBslzch04XXcjdxFDDKj++CQXAXM43xCSOTjOGplMST65ZJ1ijrSAT+JNQx8giYSPdNARiZRuwR/3qKks4j4yJ7ly8hCbI1jWOiiN+wD/hONaxGGhQ1ATSLjC4Mz+VLWVs5E1JiM8kQwK5pinzvk0Q96UpYUQMKx42zu8V/tSabVZ23+yQ8Q2C4ZtjkEOCAwe7u1Ue9hRmG4q5dGYXNgkTo5NFowqvZ54KhgrryjuajrcAG7fpsBfd+6s2lQBvAkOF15Acs4Ln7Lwbp8aujRWYo6BlQcIqiHTvzFCwOjFRDyBTbjsmlK1k80bWF6xe94+QX595pRxi0nAO4GQAfNldkX11UIKBHkNTSaytZWZiZXlruyPpe97t+aGlFE2jx6iCHCWvX+LQIJ/W23gjifuejSyU3EqIquSQuqnzSI+6mL/meL/W87r/gxLw3k8cM57fI0SidSzq1vtQh/dq0m/Hz15YTs6TNt2bHnHbJtmSs3hjOybNujC+Ppi7bH6M+tCCtecbv93vyiebaq3pyShlm73BP13RlF5aaykuIofGRerOG1Ve7mFb2VYQss8x+A75ltcDIytWDLMupX/H/2tqipr5OHkabGkzmekoy3EtS8FyqPLyLPyCvtzaTin3CEBrcSazlGP7462Q4Ri5DiEWY3KvS6ufTZpnk2v+jPa163pvyyqBo1zx2K/rqSG+s95pfjAinGRZpOntvJ4Ua7a6jkm7ESCNO6tc6QNxkJM0TJ5j6ojNWEfsU4d5p21vhUdyxjljVBK+ES0As90B/yc34Qj1i8TMA55csINq7oX4oK33C3dHDM5kNB76yPO9bW4+8ohx/DNMKWk/IqxWpspRV1sccHKWWkwiq4k5tJjT7GBwXPEAupA8EdJUTlmasy4+IYrAxZikvw8rJpe4yXKt7O+FGH2sjE6gP1wlrvaQBFzDhOohC1qqBaw1ByVtQwthUSuyVcdq8hpBuviIWtAghWZV8E4qWGfwW4wSJBX0Pa3ow8PLSzK+Oj0MQOw3BQBGlKUL87mANyrktu/y5rhd1peV6CBrcB9AIkGCpW7QbX2zokxVinWNZ3eva2p1bRga/4zr/XbZ2u4ni2mnQsxkUukqW+a7OkvsGcaBCgdEaVmaIemjvAUhqEB3kfhLJJRjQwBsU5E/8kSoVCl1LcEz9k/4pXkU9wmyYf5cujiw1gVXPqVyfrIZ9IRmvpB+NeIOG1aUxE/CzK/cV6kKESUGW8eh8wMJIquFmuC7ptHF8dDHGlI16upPdSKkOqsJvmWzMww+dUlYt20/Fi36pOqaNLGuRjOJZH4f/Vzlf9EEKRd0secxKiHVP9NKIOabLXx8QO44U/+uFGL/ICDKAmEQEJQRTU59vCv5L0ycOb2quw4VUy28M35tckCIesuk8r8Jba9eDJ1d7/9kV5BzlF7CtXGJwgEst9hFByDZJYQZWDhk01sQX63qls5kEc5wIeOUPB/1NjYQ91F6ARdfp2oTDTuWqajwbV4KCzEFCX4xBO8oUmDMckk0onGIVIIJEIgE6toe9VJCxIJ1jQ4+twFG9WEbJo097vzIzr9yKGAB8g+ptYe8Stj50Bpz8b06PMfwrVo2KI8pSiaVAa7X/ZLNaSkiW5rR2tPgI68Y/4jWvs+CGcm+W6cRTj5/W+v8e6Il+J/HWcqV2CWP0ErLSQRreNtOBuLl4IdeUzuOv5Ww7KaLdpsTmly095k2JAnJYhk7zPaJQBipOSIpEgQxn6CGlUdMRXGs+JHX0jGEcz8sby81Hx4VU7uVGaTzwiL0EN8EofdEGsdINbXvoLOaur0lk3B1ZDda0m/oQ2MjjY6/MaFCCAzrftkT3huApfMc4Zl/35UTGsKefrSUL1rtaBEoqYuOhlagW4fq8pIb9QSleAy0GTCeTx9S3xYhZGFkBrv4DydEnYPG0KmWc7MDBzYvcfNiC1Tv5ntz9J+P8l5MS4yLvoEkfIu1EW3tymmXZVzEqT+Csc0jrisltU6VQ/wpShdoaf/VmlccoBh3LNWuuRD1SFm4yXaK+smz8xl28QyxyY4ccYpgVNMOK3Ylb6u+vXpKnkPp4q2L4oie51Dwxpph35t0NZVf5BRBBIoPICZ3JQxYYKVWQ1FmSYaZyGVBIWodZcdaMkLOCCV/CWcAmmkRqvqXfVksdErhZrKmgHaFAfzjECd3O6vsCTle00sh31hb4TIf2EWe3cqgwqVFKhooUcJAowOnv+LqedmkQyet/ml69FuDyOwzjOQC3UDUS8PgNlQuVZDVZDFk/uccYT96SWiNlWlLheWDnVfegqoe6WcxfG9SYbBbF8x0l1cCXxTZn7ZP7fSrMCaBjRFRYUW68QFjdRBJl+oQ5jcBTco8OIrMQTuTE6utSTBht2LlK/96OifWSwAvnZI1N3nTz90r6QfN3uh8XgR2c2WZdcUY+T2ZLUrSM75u7/xP2983Ev8VYaABHt+OC7feRmFo0ZHErSvwnv1FgFY1jBxPxWR1Wh1EqtViRYTNRURst5Neei+tb3HJxPoUmzpI6/6si/52AMAOQCE7fBur3g8ilo/RDNZxzDImvU6z3MYtrLsVFr8HS0hRGwUWYV0Ph9+tg+1pNyKJ5MXzt4S8JYwEl4RUDrl681+6vLwA2WMcwszbKL2eONbUJoPRGooad+XIndxFKY4tsScvVYxnEejL3k/JSD/M4V5bf7xd+TsFJ/WjxPn7UWWpQ7Y0DcUUtJ4h+j9I+knVWhs/Wu/9BGZ9en/KSyK46NL7vrAuAx+ChokjvMZciHp2/8DvEC7luAxPc3Ko+TIWLY5YRYQs320h0H6Y64DTzaFelIVwQeX5AUaV0aGuB2CaPO4uS899AxaWx7VmX11Ma6tOBbjq2AR3IgC5MrYn+4iIuRAM7UmMQPMpp8RUJ7egiJYHqoZMHO1pAYYwyx47npnb0GsLBoz6LuasFcwwzIowXYYZQBOkeVghd5qZw0XIamOYIRESpx6oESu2xcQpJr+/EiWeHECGOakWi4Aw4/ugZMA2p372SHuVI/G9AvL0Zi5csaO15W02kk/kBO+dn4kHggjmrvJuU1IHWAqc49btiGdPHcAUlGoGFhxHsuSfQd4hmr3hRsHck4oBEKVQugIRgraPJ39kqLsDgXzVGC8SXOLBHs3SEei5LL7vQQY/Y/F04iG6ytvXXjW8zNTdzlerW0SIKCmINxoVWDrgxbhRVbuZXUBo/yYMmJfCklHmmUwmCW8c/Ipm3gtH83tuz0Z7EtrTfGjsmIUdHJoevcQCreDxRHKDLMchazjDUU12EezOcHWFBKjpc8E7Pis+GNng61Gj9MecoLb6S+KW4Hw99y2TfpJXOxbU1nFY/CPiyou5BbTf2kYyle4QEn8IxDaB72leZgrLm7ysw9VzIUREkndNjGDlZEmzn3Np3N0UNqahitUcaMAd0cy9o3ISACI4n4DnPsYDlUQRl16dSuGq4x6W3+2Fntybst9Tsj7oG9/BIMdSHiNdhcYIraYxMXBdzE69K4yZbopB8pFr7klPV0pNffC2AkFt+hxw79A2LjTpT3BJ0lY45Ja/PGzmpO2B3OOpS7BXSgtrtShn84LbhGyF5ka7BXoSp7LW93Ho56TfdzA7A99UCyxiLLHFa9mGI/Z9x3VHJ6R/5ije1gO2J7/oEwjVOROdDaLM9b9tVfnNmZvBjy7IK2IzASie9QY4fehJi4AwU9piNfOacmps1Fn1UXt9uSuKa3DRR0aZpR15hTH3Ibz8GS+njtH5qLXe7jH/P8smpZjoTVz4c8+jRGoxwhICyxEr7kQAd7GzlGfCCtZ7pB2D0XPonXjwqJKsZz48cPZUp9wsz3adaMh09iZfd6TuIgkiBGTnxJ2ACAjTZ4JhKuh2U3PtVl2K2X7/fW/zaPvoqBL7tVgyGECpkQD6Rc2oqmBom0UMZlkiEZ0YKjtlLwYbwatQ7Ajgeb99qKT58yP3Qzf8RXTOdGgfuR7bEK1ddC/HH+a4w8qNrcWZw8r2RJextkG9INsDuXt6qdBz41HD0ik89SYUEXO+5SVu/3e/s4ZbcecXUYOYB+3WgIxCQbxNS1+cwdza35dkrzSxA7yl1B8W2V64th/ZC/ksh9rFUlOYPan80FR0S48WSOie/qdw00e/XRfYiuTyvwhdpbQd0LvNE5UDPOKWPfucLgCzKxvEKIS/ZBCiuoAISw1BZekLxw+WLV4XwgwlXOVLOBMB9Xh3Yy1lXBxeKKhtScYWcIEIuZCEmcwbSdavi5WeCaVTn8HGHuvn8SjuNIsxwXSHiMJ9ZZ9mikVQVLzvjdMDwYgWPLkpJAMdSigJKsOkireepVDcNQ+oSNYRuetpg9NBsGDLWIXszLcSQmS7iUFJHVyqa/+KbeT1qGHSQypTpIp0t5UkcJUJCg5HhvRq1vaSCe2XhiQvaYlf4U1elCVmA7mGStp6PsjI51iqZasLxGUyEwQOWvvNAs9P6Bp+HyaykTvxJRP3JZaFsSn4lURC897d83t8BhqTDhtTc9BzQnqKMRoUbu7f3W6SvC3WjSBKgSAhDdgI+Ir+UnJhOJASdy0AV7fVSTCBsqM/I3YJoK3HNA97SzUbB1uN2vt0JmfApmAOGefPl0tZfhQpVNJ84weN82P8B8j13DII0mtISDcOVbij8M8x/aCtmdGCG/Dhs+Tv2x4zkJm2yYajzv0bv50mUkk6daULxC7RAYXOUaMjQGlTNJAX21iHSABImObgkGOG0Sn4kERC7JWKbWaB2TRjFIMPgAS1UpQe5mjG+1mGItvUUp579XjkmJWu2/W4UlN433pHxzwR2M900gG/jE1NyZ31/xv+qZr9Hf3tMqtPRXzfuo+n1TNnX/r7oQX9T5cPBv5vNZQBlR6soit8Vg4JU5860xlHK65sz1R9L63LFK5OVZauHxSE5BmPJ1vnDNJWqmupnuVDzy44sBHtUv1rdYtoYtZbToNSYxszh+o5zdYixwtjJ3bx7LxJE5zhtQbufOeUkW6EhIgRKmUfCDrSUYkQKU+0f3SP9XGZjD0YikShFVVJvblUIpoogKtR/nh3hYgFam2qeYEI8fKowarEYhSKuIbqXGP1eKODJqYrLPpnquU+JGT+XqKw4oLyXgeMDuK1JU1YLmFeqDuMFXnuSFpqB2PaVhQxuI4wBkO/rYGHCWJDpTnGTzl/zYT5UqV/MUZHqcPAHQnPeaCEZxv2qTyvBgbsANRfNSssVU5qEuL2lJRCQhURTvZPgkJIkS1RoWrMuO0VsSKH/CawI5TcJMaYCFoRBOwI3Flp4vD+HuTFIXGmCYUHK7VgrOpqH14jKi8ZAiCjyX86j4FrUlTh+6Zj9vqz1kIrgfPieeGs2q5TaMV11mc4/35Lo3lvx/6f+mf1XReW3Xr3R4A7eYTWAiWgON4dL+ygB2XZU2r4ynImgYQl0bGLzLUSeiDmW28wzL+EBOsgJQMXfFH1sQs47LZep4RpzUQsvWEQy98q5RF2BKARSQG8yK4AkaHtVX1ds4BzUK6XjCG2S0yrlOqXRSLJUjHtlD7WbECHVYQ8TSktXUlV4tJLGA3VVCEsFE3EsXaQv5zFozmU7B6te/1ryNC4Smw0ZHy/BkdwqfHCCYg5AQFIcVRCjdPKjoyv37Yb8AMRXywzo+E1FzZjDqbQbjrVGiX6yK8j/oj7eVgptoo07Ey6qE6UIPLRSMDtAotT87cnvhFDgvT5F7RHkmvqGNtDrFYCnTyGStQwj2PS7wW+0G587JPfpXGAJRC4cowIM+BmW+DBvKr/MnspprECr03kgtCdPtfS7ftXseJZam9FXUCPshtXiXAfM7n3PM15c8lv9zhIPAq9hSIDEUKVFGCiIcwAh7oZfDBMMx7o1s5lTKs2urt+VoM6Ld7EP1agE4iiUGmj285fWK+K8jBlaN9c5ec7R6eUuJB+HtMwCM/BjjAArEcCxQe6LBLNwFacwgjHJjsQ7WRLMGfJKFfoiXxAXHydbTaCufOEJEUX50EmmCrHqGGAGkPEG0eA45nTmQsj6knzXQRFOeYxv/at2Qd+ZsEwOR58k4hEAl+vBUAYZBoI1I+sFjoWa7rPDNYBcvKvPqZC1gOWziU6drdJF+C9gNZUqFOszyA2FSAEZhniLk+TsGFed4f8ee0d+enWMTp6Ykj9VwyftKKBX8Y8e96uZK2erbx1hWPTSbH2N/fmDCOfQ7A9MHzKKnweZD/FwAwXyo8AvApTnGXUrksBUGWWOc2uUJ/zPtE0LyJO6Q3AWX7PXUYp7nUuLflTT9TRBVSbZxuMUDpvayl0YtoJvB8KiMspqs3TAQ783B/cUpJknW8Sz+jl7wKgYUpihPjGQV3TNPn+XidU0HVYgBUyHQV1Udi8aY6NEcS6ho1rA7bAqQGEbXxNFqGCdbFyX5R9gcW2ogXENNgjnUuhQQbOubhky5omPP/kSrIKXya3m6ZT2xZLKlnTcVwwgaZ16lxHvhmEhi8ZqHHlob1babrH5T+HrArN6wiJmQsexfIkVxILovIo0wW0S1d/8ua0ILDVleyqAGWabKmSzAJ92+NCvaRTmUNh3bodvMv+P+NVcR1uS9Y2Y9By0UzI+nvr1xRXTnkqHokryOZwRcKYRjtW6SlgeBj1YMZdXld6wP1Nqz7lhN+a3L4/uMo24E+bndUJmuhpHrZZTAWEO+/QzzOHeSKwQDzbeU/9UiIbXaFU0RF4/j/3BNy0GekNdVO7MUmBe6WuI5ICLK+vf6hqq3Wij7deCl2d8FwDuK6oyaPdJkIcHA8CRaLfMLP3BSM4gPzbAH3iJnvx+3gxp4+VWRac839o0x/ud91pZ3Aha/B0s99M1SfJpaa61okktPEWF59992LaAeS+WA1zDU8Cv5ySFmJnEJF6YjDUtq35QeffttVsW31AijsK8iz2SUdDQdbzTtecfZbrb8uk/csV7AfUsduXN+xBDN+IJHbwRYaSt4N56ILXfS308q/E3P1fO+XkrX0stcvoeD7NQKDGFtZ7/k0gLULuwEcgNDIvaTZbs6zc9rcU/f5aPhYOlki4l16KbxSk7XA461po+aKYfcfRhY2O5as+fyu2nrt6DIdywmWRR5vwV6fi68200D7fcc4jXHrKSasfV1akKbvgf/pNSc+k+YjsRnKWPj3qmCzrafVZ9Qk9aBiV7KDwjGacvDmAPTBjBFShbhXqrRBb/WqkWeTosD9FkfKb0PAN0+Q0+nm2vmCfiSQC/HhNfF/U17ycm38LJarLlPImDHFpGoXgTWZy5FvtsTT5u/GtnVavJ0ut/u76IXUW/1ljm3fx/8EKB3PydxW403VkVo0xD25gsk/fdYxtykpgnOEyqlse1ysAGB7fgQ09C/QYsMkk9ykmiZm5dLfrs04vHMfamH9JcIdEOxnJ+34SMFkdt2lkjc1SGDbQeFMBZpLn0RVc5cn3szh5d89/151awzfVve+PeAxS0aMdJo2wdAuBGRR+CAeNBG+DSkFYYIkg54ycTOGZbOFGaTZQwBW4QxHIQIkzI1HbfmObTFO8CFcPFuhiwIVGSZm3N8jeF+mnnax4QWlEf25lWVqBtJTKxOgH1yacCwYsSCxp2HR502Z/9GN7JYIvPYUWMz66YpPR27mRvfd8Kc2jeiH4uetUq2vu6gsFZ51qKz5hrZqv2Gh6or4x0OY7QJ6xIA3XdUIGar8CAj4MgR0tbYH29tYi1u33yt8PHQBa2FvQJr5pOFQSG3IejdqelUxKbkLOr2YhA5b9ET0OG+gUb2GRa9KN6hyICRap3Rzbg8k7Ucjj/7AE/2vHnMagDZexs9ob5QQ3nQ1JFnzmRJ1rScUJn0l6ZNAmB7PkC7SverPxIgcisWem+Qblc9oEa68USHlLELrW6aijDvVUkrMrmAqxzjm6PBfp0UogJy3rVeRiFy+THC+1Fmm3woLjvco5sJXMFvwVQcfzscCbgmhbYMOhhJGTyyPbUGIP00TSZyC0706ff1mxpGtHYmna1xdkcWjiws/CIxHjqZtwE6joXKDaOk65Iscy2JTF+DGUQAzuvJ0Wy17OA18iIcxjteVYqJ9G2Evn7qBuQajHj+q20yZfJvt5+Th8QCowvrtcMHHt4lDRTJLr4RngdUbiUB2iOshld4cb2o54AvEg3YL/yGHQUdEPjFKv3jF6y3JR+5LBFhB7bvoDmRVyf8YbWBUpFKlCa5SrZTj4BBtgp5H3L/r5nOtFkGO8kLBeKLbnUJIvXwYwF+SJL+v+a/whfQ72vn0va1obZ6/jYpPAKVeO5Qbsini6j6z5PFzSQbxWaglnms4MzsuiwR67902+df9kd3UoNK7i6Il+QQuoXSEGlAry8gE5gJpP3c5TdaljBGli7yb4J2mB1xXPhCH2nmi39qsdbZYIVfOpGW5ATGEfLk6FvVATHrZTqJz+rCkQU18dUlwdNe634zFm0A/vJqkPp5K9OKys6b9bUOQjwhIMzT2sMV6/hrvLwG9ktU6eGcZPQ82UhC5V5sNj1G7KHS/zdalk+5le436C2KWnPoQxHVFFpFcEdN5b2FM+95iX6oDVXVeRgzTsgUCAJ7sBW+sHokOz6JPEXwNyNENopma1wNf2G9MV+RT2WLXMr4bsLz7+EukldUnUDw1R5kGD874Zz/7dTckjSffjnk0bsD4SfU/HUbg+Lads9S5rz8qM/+2kQd34Q/0MPi6JuatAwkXWCq9Vl0KCn28L6qAZxPMNwq9zmfB2SHCpFdsoua8aOdxdyD66iRWVEoO01nsWKGRJfpTIFJD5TL2tXRZrPNHV1ZZ9/BzM3G/5BUaBwIIh4C/I/iPsExnfXSNkUyX1EoxtL9gXu4zbPiUdN5qWjvPE0+k5owqZsXDr+T4b+cBElJLPzyKtfsopjU4qW5K43zLXHEA+aEfbz60Om+iX2ZtocjpqFtyyNocS9YP6lMXwqmzqu9dnWsaQyXouxiGk4+8nNCTE42y8c0ySdEu129jOqeXiwZkmPei3rPgppWWEDuG9OJt/bevNYdQdy2KDFSoPQl8iM1NYZxWMQ3Do8gsFc71S2Up6ftytCWx3Pwvx+lkHrocVgIJn7hFTFam734cRLPxR/nIIpI++B4E4vdRrl0mh1mUzEFDq5ZnoYpmb8duUdWHyVzDQ9/G5Qb9m9Ix6b9q3RhQBsOdjyqxzyIK2V6N4Php8IYR0K1+7nNGNihRAliCqVwsIPnZBjsdsHMWCpVFh9PtApoZ0OgcYD9XnRHpup5eeHk6iXy/AyHhALkafkmD0aM76bbXWVZZpDlZZ4k0vnG5t13B5S6EsHN799CbrYkBHmunmdkyRxEyPhhxNDYkD309FvOVfnXPp1/tN5toHl5unMyKKaR+ANW84gqDP8/7YSfRQlTXIOM/Ic2lBnt/pd1YA6H4rNn3nKgBAwP9WD2YyPMwL7hfVjbCV1G0+sOEjRIQ5tWNFMCOw/oHmqznWk3OaarXjcOzL8UQ003B2vrP19MudK4Gl2JPd5EXsqEJzrY7x/kGVudF6GnW+DP2myk55EmI5dFrJg1zuIGUz62oMW/xYKz7FwBhnC+JlpXmfbUVJRPs2OlQ+IIR3xO2yPnRSIYCoWwb1HHZcKLZm6KdItKIucp3CHLosFePVPCdugmgMhkoQOuATE/34UlbeI4HbITo+U83lXKNlLCIGb/xWmr46ZlqM03OrL75/hXzY0mHb9aWO0C7J4Qk+guQOorY2S3I/pKltGZ8TCKEn3wL+QqTk/aUpdqXiCMlqziZoSTb9541OkKlFc/gywD1OsfI8vMy/5PUs4rXN+ZtG7WsM2eY98fkk28uw9L2wxyd32aGj8pLXbW3Mzo+e6iaXI5xnCSJ40Ijxg1rm3kqUAjj0eNFMJdQRgVDHBBFqzAWgma1KVu8LBuniRtM9PwzRGPaHxm+ck6hE1NpyfQGvsYeYbFaKPpRMg+Ta98NvsCgPecjXi1Ixd9treTyjlKX0ko3DusoX7F8fYLe9uGS5fODcRd7p5x7T6j5bmD5X1o8fd3W4ZT0YmfkuKTJeLOuGNMue3vYgCneM2rw4Ao0G6Z2BiB794CIhFnEMawAYw0pN05enEd59eUIG/pItnAPisFFgYyYX8HqcCdAdFVjJd6lwaW9nYk+R2Z1FStvV3Ujr2zycfz8BuC8nYbZAErciPyxmLFA1YP81isuTXMBUP1bzE3tFnv7ODiYjVS376zmoZZh7S2VQ76KeKvUS2fthnYVz2qcVS2ktOsw6rc1r8q97OhTjbMzFv2OhnNZy+QdPszOt0Fhw6+e2mpt48jNp28UkjOphGpyhqQOp72TGCLFR/3iHV/IDPvbW4sR9DdzObvKhtimwSC1nbE2BcqdSn78Fq7BWN5ZW2olMrG2KwZSe6Cyh8SiW5fsdxdJduXCi4GDaZa/5r3flu8/Tl5LXg2bSV5e9hD7kapcz5vNjYC7y7oz3vPokxTRoyxUhRA26cZpdbTVBJf+IH9r+FfZOIsRPwmSL864M2VMdvMAfu9YMRhlY7ASAnsajj9+NrYrCFN2hGNdZIorDwVFDlA6O2rTN5WUG/fLvKCjxdmM0k13b4RET2U+sybyO7FFeSwO1ADL2JFk5Tfpeja+3aIXe/HbZ4hCW9rm/3+XYTweW8xHdYbugoE+15zWjOXRZeD7oesKzNjgVWZVyg9oXA7lBaNDVLhwffomzV/iDqvv0iWXILdO2Hk6vOUn+2ixAxJwsAzVZwK8SdMcunBa4ltmPWFx8mvyjUuvv6HkMQDz5ofUc93tUtkngzTPD5eWvsFeiWONkHv28ej/OC3KqUZOht69GsPl+QAthQz3BvQOVwUHtX5zjgOHPdKR3Nk3nS8obB2N94e8UeI/nZUcDTtdq4LsTIF2m8OlmrRhZyVWrkDO6zkAmbJ4fM5h8xjZpMJzwbB9m6KrhBC3uT0o9jLzpt1qm58FSP0PPzOvkn49E+/Md4JklBg3wWSWw6xUiMrbX1g6EX7fXIYI7z8hbhveYSEO5HhrpRapIf8EzT0LRMTXy6nTeEPaLdxlnjD9zJOFBScQqaSPdaVzvlSf8LIVtpznvVen/9UraGj8GTwE2/nMd/MwmnAb3eGstcfSRrpeB/MDj+ymxM61Fq4XxMynnC9oIBWA6hIz5dWb2+kkoZoyso0ztpZV0gvqlzjtM7Ciip3WgsdWHqAjRXXhV2440ofEH1HsWKegy+MPuXwQNGvnriOeussTO+YqfCCmgcW8gryGjmhAkyrKjQCR8YAnnGNxVFhFZyiKaONpdy6c/4pY3afSL5+JoV2PCH9gwOZ4CW6I/0vhJANRjFN4yrTGDk4aSTXyAqNRMaZwVijI/P0BXL0FAYpqmNf8gqvDU3AiPGoDcOquMd5lY4DcoTLh11Cl/DwqAdvcPsNMDhBSBYSetNdEJoHfipKfzj6/2Q8/pVCpufTwW8foxV93ahv+uEop8ReQGv/bK4YyhdAX5eqXoDSVGUGZqN26IgxTwOvAErAQB3r4D2OJNSeCrqgx2mnAo7pCUxM0D11n+lRdBToZc+rBpV511vIfSci4qkh31e8/HeglxYNZ2xTjx9zhkMXWsHU4RinwB7g471zuQUw8DyllRT7cg++icqQCswHmZSEBuUhl8TRzLZKqe0OKXEl7jC3/LPRFu3m2w+KjyopLEIE++hxWFPANitFqVSZJcJFOkwe/r9pyBxO2tJl2HuNJXveKB/a3NKodVVF7uCXivXxTtBV+UXKHePtuqMPd6+k1dwI3O740wg24qLK3Ic7HRCissydwTbV2YG9+iRLpBbBwTcvqX0aTBGE7VLS8jJ01MvSybevUtsQ9IMFz+Ff5Z+BwFo9YaXPH9eEotIOoQIeVvGzN4rwH/OCJkLhm1l647X146/o9SkZyr4/KTVQ7fHGexiyoHGx/P5ejntoYUq5midyI7a1XhthCgCzWZfKePBCjY7kKXL/2nxcszOOa+kGm1TZX/hsTLnqXgVFnW6Tm/OmVa7BmHjQ6SR45AyVjnRqdNpztvxG7In8JQ15A7DXqCYAg6FMU5PDeK0C9jVU/zOBKiE0pwknRkQy8XEfCSykGjYIPbgtTOEz3WkcelI5qujNV4tvRdVIVUdL1hANWWWaUrR47a1hGm49V53fuioK1d2+L5QYKbHXUWvMFIm+d0hPs3iDmbFW6y2MaulwiwQ04BM66jj+sx8W7Ss33lQ+Tzwz+OdLEXGLWFeSi4dLHgpCJz/b7zAvZDRwTg+mq50e3lglGp9FD20ARSF56Fwp23AbWHba9ZTUFihbQDTo1r9tlhfrsuEjhHf+/gru1NGcbM1XnQV8L52UPPopX2CNfxvR9q1iKuk5acD6JYWLcZc5hHSGqr1KLOggYgxQsT63ZiOYxwrnEYc2W65Zx3oap0n0POIcuZqxAQgNzjzOSyV8g5lIblBKpFOdj7T0ws6bgl76CPnwVAPfkP1cYnl7XJF0v6FNvAbwrOcyB0FjtjdVzqc9gprnqcYd+nk+BxWe1sJWgtQw4X7wO985faPYvlw95tW83jUKd+2b++EEqmmDNRtWQAY24gGQwAIZhRx9jrXNx4/j/K1Zw6Rywdr9+/ZYsgkBhH6F+u4jlvegfBHasEEoXlAc45mXORjoktcpsbyJcBWwg33yZNy2TV9erC0rAYw5PYsBDzxrkLuB+6YDO3L6fqhzL08AU8saaMez0gJkredx10qMgPqCEfKGncv7nsLHZeAZAvytXne8EDn1Nq4eCAaXjvV/GiX1lAu/vTvb3ilq+O9MEOKQhPFQsRQzag7/860ZdiY1PRVmt1OwVSfWtDhD3QWGdxRRaN7EYOe1aYAk1Qo4qL1E+r9a1incZ4NqQlqt6ki48AwsT58wbYHEQ5hGXKvesc2PyevAJm9ozB2QmxBwsQfcscfDL8rk2TPTIm1rTcL9pYVsUf0DM+H5sVntfQ51hMTjaxj14yhEeQk7TqVPM976PsnROaT97D+S2VFprzvDjKnp2l243v8PLjSXNrs42q9xvpyXYjEtVbmbFM5Yf0NxoLSlnNnuGbEteeY+2/CNHP2K6D6T1Yg3eHQHWlWF0stheaetXUWdMleNgB2x4InmH60nRFrNaTact6gTmqTVu6GIWFFNe/vZnazZc+NPJ4ffJHz52aEQmAeM0EsVLvCx8NvN93tWsM4VH4BhSslsG/6BIR1OeWHGCpFA7OdvfDUUG+feUMY/GWxCdHqc8gOP7lCrulD6oZC339qTVbc6Swz7gIEldv1umy1ttf0lxj1pzq73theiEo5Iqh7t66e+0xeXI3S3LnV6TvhNm3UxsqoXtiOVPVC0Go3Xoj96Ua/vdhqZBYTz0qae2gQsOls3AZmNzDuRz/Hmn1scyPFpdEsclq/WvDMG6cpq8P3Xgrj3xH+99EMZ6Hwiaikg5tpwZ5Nedu0bGrZ9abkOU4U5PggeuwGwy+P2N21rTNEUxt8omEgaB2UBWSUOmNh0x7HeuPeiDJzPLDlGvUSf18KkO0RdRg93n3c8H5bOGNKfDHGJy1w+OC7AwA1U4q0nPrebJx6vz/0KMmDDS7zFAch1CtEGmwyx7IlTjjnhEYyYb6Yn3SrZUH2pC+xPQs220dtMY2ZVRySo9IPHfRh/fNv7XfnrFzVVi8/NxP5wmCtUqgjmB/c52B3rgJmVlG47plYfofQ2Wg9+gxmWvZ0agf9cKUjLjduqfaVRnOomJ2iiB8v8bmJRd0/I0jhNPKN10jG2MWIQm9R2rcAgswBLCW4jRlT0vPdXYUSK1d4zZc+E55rsQlawu6pFtOdSqiNlMZjweOPgzgpQiemwWnNvISZImCn1sSE0zWQ4+xdf+CgrQ3kL3d60SkSOP2gjBucrxWaHRgy1k/nROraJ33OOzLXLpOMWMSAWQeGhQ/nDaxfmwlF60qi5BhMPf+/SUHYYKHWP8Xshvc9hi4vB3O3/l+eSrzk92y2bkE6DKahNStaE+UER8np8yKf5kM8bQAvGBpS/EnZRVuyJa5qm9hnEXkobB5NYsAQsEEQmFWATJCY5whKsooWtoiVY2jd36Xvty+9XnSffBrtSPc1584K/MBhme2bCr2HeSyOjttO4uE7XhJy7gRNwPxNIVvGfNnIX+P0KryC1lIEkCfF9+BYScSSjrnuq0qfxCe5bc8ynJSxLYvF4rzzTbE66bx0UfVqlyWZGVzmQOaqbmcVlGdgACDKHbXdIKpYzUt8PO3Uotetq3rGktJphLdwtfHmzetggdr/41dUxNY1/LR4e5nQdti8HBiEjD54Qf2abpkED+7wsypmAK//hxvYFRa6HMSrtxhMTMttluBv6oZ+jlBsHYKAyMQ1BgeIcrEq0sG/QKKogh6If0EoVB9ZDrrN4/UHdmbNs23i2ixUZjfyUwnpy+9FwQksC1WOSPdbpPEnCbK6PBcmK+Ejq0F6E9pnCyJt0Ra69LImu1RE73y4gpZIBaQDTuDZNDrif+Wrle8DCfV6eVBpPTkWbYfOcCjhJZycRylb3YjgwV5/Tdat9mW5AvdhnIrgflJAIc4lDhqWywAcdaQlPZXmf7I1jdl5DhFiUY4Bpl8MvoxD1QU8C6FKRFl4D7G8AIh0hRDUOSXAwJin3J2FL4n6Rhf7HR1xiX4CqWAnFKK3k45P67TLYQLmuB01101hq1prGjDxxXUF7K0x9c53BKRvdaHxGJVNlqzoUZyd5PHf6w2Kgvo7AaeXpvftX5ULtmYHXdBS2ZJ8Ua2A3RIymmGxrwntIRPwdn4cZJjaO4ouQlI20mnd8lQCE5ltmdYyUdGjRGozW2ZL5Jhi3+VvWk0ZdhH1ualuELfL8xI6INtw9X3xK8pzJfPRAwy3li8OfW7Yf0TE+PWHV6cSCwHALdUX1tUd/V0cnP/dc6dtVYBzBVFiEeUL0bzybYoY9pJAO+XrkdBtu6bf8HHNeAI5iJCFlj3Z38lqthh6VTheU50DapfkjTrOaz4m5O3K3P44IRIaZZuZkpE0dlbFB1iSbTmrxY3jxuSntsrONbXzeACxFbuIheg/L4VT/FWoF/vYH7nER6Tjq2UD4Mpt9dPulWtBiFeGgGjKgaeVzsbEHcJiw95fF0FcGDbfcQ6VzvCW+knt6soSDy+2QMt5xJwHi3sYklJA3SKwBFIyCs24vXCjQFrZEsKnWB+wZTZnj2lChbdArXRQSv+KkCEZuIwxqUNrfg30QGvGWvvfAUkNJaC3e40kmjYkBVbpz0WHMcl4MUpVoreZQXDWvac+w+8HR6DPYsSu3Bm2ZxpXbFgeUi8Oqrz2mL1WNf4jwrPxXukh/H+6+NyhaYhSk2QwN45iRjNkcamWqJkQggcQGx5BYC+qGZTHFgm1MSJivM5xyK3HCmNOFj6gZMOZwGXPa1qY8w6QDvB23YLrhF8PrxNL8Pazne1HL61rEskn7rfKNQ95L7KLTlsAlZA8L4YsnCQe6C4O8OzeOcwLElqcWMolYQ6ZyrotwWEOiUtvm1GeBDbXYF7vGhdsjuFtskLjnWKAL7ukCYRQ3wQ82beQdOqkoK2ad23SfQxmqnbBjuylZ7C7q6s5SWcI3hDEDuxwx9BbBgroNt3qShUuv5HP4e1cBVxSWWPHhSfyBlvzqnqbTtERp++YisAj7ZCzHuwqko3EsOVkhhqHMBe0fH0jVEw5p63tmxEqws2tAsezfRFKzs3hi+y8ZTSUZkixmrDksBdK6OCvb83N6mqYRJXYw9G7YeMVit9YFOUSTiJTqhGXeTenLgQ3lrq9Qb33hckuZOn+FIx94UwjPFHMaidy8oNhFtaFDx7mS6Ge7RT+Ua0/RSu1UGbo5mnj8flwGb1sUxW7fYILnvYCv+VlLFfORLau7hvFca7x1BlPz0ShQFMV+xkLuJr5q+wwzIeGs92U92J8Gk12k86zeSWTeq/oriRtXkxYLaSfk1awepMF0hq1+cq1x2m4IdXajcH7NInv1U7ZkKh1A0zNqaCvWdmyGC3Njvz97Bwjef2Mc1RmHLgUH8gYM78HgfXAkustUOpTz8bjhSKdqR2mP5fFrZUA+wysiMsM+5O3RiEP0bAKPJ2fzcVrbC3MMod7TTlA31cxSd0xjOKo5OMs8LZ2hPkeEc0QhzzLxcBdvoD4vpyftfpiNM7N4JqsF+o0OMtglioF+g8P7zzLdUYWOIhc0MTEQdhjA+bMkZyBXgntSKO3BM0oOJcvYA7epbF5ZE3TEwWJOjTRbKblGoQKMhzeoc4+J/vKZq51e6pfLkHPvJV/V1Cburum4KnMdAqor3go/+P3Un/97CcwEDTXsuUqMOSy13sr3Z9E6IewCCIcb6X0NgsHWfCC56zibx3Scu5EAmagyyKluyCOqAsq98eK3dKUD1fxL5pzztMEXoZuHmSU/qmPAJMI+KUglQvsIylC6T00aynUFsaqsDBETcmwuQAM5i1q5KLuLGHN+6s+5eqZ/Xwe6bDRi3P2BXhtZpQn4nMm1156tC+husE92YH1AyvaDun9M8y5e32xWzZj/G2Xn0ujay5m3qnEzzrryeetKm5vrRneOjmCcAZ2lgpRNUETpp3619G3ZQgfexTxOM/dn72NGKT66mnvtww5VgU1zt3QVzrDqFyiBPbQp4x38tgw5992HJnnDed+b9YqCm/dmmKhlZK8fdrinzPQXb14eJTJ+lm6uPjEbFxCQPA2uQ2S0r5ZK4zIYSrUtLlX6CqMhqn2hRdz30be1boFSjHJqta0L1FZJixe0Jemet2DY9L5r6Ccmvv63dt1T5qUczLOli54G9317hbBhU2KDNSRlCxvD7nCdktT9IGkgyZhdlBrn3qgbaMatWcFb1Jo7l4gXyUJbdkRCeuHU5VY/9Q/TkBPeqRsyMFfvGr/VPCC+CTw14SmiCcZjyJHOx1NKplAMSJyRhCzkSI7Gc3G7tV59MQ7j8VNaimK5cW/qt7d/4KsnK1VbCJOYNPJ3gYT9JyZoZYgOEPmA8GzhRYx7nOdeGeEqt4yFiOfJUa4FTCshuM7ZpFT7OYGKJ+XklS9hUN9kgeFHuW/IqbHEm2nYj0xm+TG3BANjEL4Z6WHX6O/ky/0laBlGnUAef/tF6KSC+klzoCQqIKSSBJLSNB+Jv0I9Wfzsdl3QlOvq/R9MUu1GSmivbn20gXlSoQJVRUJlgrsnDSKttDJUnY9IcQGWz45d4VrL00nxFlry2lt0AcZmM7qcpEcOn+avSSG2lA0LOZPlsHcU+cFIzwRVfcMJGrI6O0Xk7JKAnE1P45vZzCnwmFf1ET2X1DwJmSUgGN3vaPlLemmVLGXBa3mOpYP4o1hCw8Vhc+o4Qx12LuUyYGN6KL25IMjta3nnKslOP5hw7vM/RzOQCtVPb3fImbIBQZtK1kBDKZwlsBPxuiVerVxJ9bcjWgrBPovFn0UO8E2CrzOGBXV5eU7erkguZ6ZGMFvPjBNJk41yd0PTfshWPaMrnTFG+6bN0Jkfpdu+SA3JKX/UBKA7GO5Tm6S+UR1MJcPTtLYaeiaORKLufJocJ0c7jYDgajuXkroWHjNzSrMg3aDK0Wv/sMVp/AHHGaejg1/JHRkItYgj7Qr0zLZes1TA5czhwc8h+18RVrnlPDNmG2Vc/To/O5Bw+OGAR2QPJOx+cGQQcj1czN3eUene5omnO25DL/0I4VPgpcXtMgJvARdYBP20OWQXD0bpjO6B7ibeOO7df/ke0eng/H917CP2W11oHe6xMRtszf6s29HtbfADQkuhYwvP885f8Pny7ZFk8Cj9j2b69/QJnhedv9jm2tFvent9F2L02v487k/u4D6NwDQ4vs6HDv5sjKIbZCHq3HnF5jL//rFO+qDC7JuK45nELBdNSnjxP9jLxIzkElxqFKeWPgifDWbN7HevRMVUcTQtb0tYGYJ0Frx937NVgtzmw4OqsNKQ9IlcM2YKUsdq3g7J6yiPUYn0nlnuS/aNdUhIHzsY6AuTpoHax8cwW/2GcBfzjDKmWbGbuAZgtrKbjkCjKU7jSgFudrjwnEPsSs/BRivFAiXmVtxoBMil3o7FR1rbjVhvgPhDA2ip88NdqSk9RjDFyyFTXrx8JTBWddk8ukPpDhx5+Eh0JQf/PLj0ZJndwfmtLWFb98EDyMFgrG9biGg9iFyb9PnWpEsZKB+tekchdqF3NEWhgjUS8/cNWzm/haH1beNwNCaZJoAkJrzmS9xZH+/Rg7rQh3LXKEt4W16lFA/zKyM5mDEX3URXbz3sQvU753fJibcHrJVDCngQCRNbUdLQmQCVYi9kyU/5iK/7nWhb3Y+EHS6ZIakfKv+y1iGE7UvrME4/Au+BI3FdFmYhn7hELHq4noSPFUrshEwhoRLim15BpGCYriSpaalyhDU5ErefQziIDdBgrOGA3AZ9Tq6GwZsx2JGKzO0tV7+7V9+TU+d9QR+RF1AxSINKiu7DRiWQavra+cg5CjfOeV7t/R+zgvUFaMCXpidjsy+AiuusrIcju2hMfh03/qeYXaaeT+Vofve7jeZSz7/bXJhz9dHsXLoByn5Sl46x9SB6HsMeY4NeQiWiT3G51smW82VaXhieJtQuSC6OhMShFH4EbmB4hJ7shYby9LN+8XoPPYHoVHU3GkZUpYBaNartHfxDxrn48pAlX873QQeQbJ3FjBjVi5yrWTntA9LRBon/CdYc2dU27bH2YhY2Sm83Di5yQbnxhpMv5oSIGJ4zGMQMihf5Q4BLlCUU4G1nmJECBqbLg6yt+Tu1K6pTGWAzZAywuFAN3hD87WqQ85QFJDvTv4AcrayYrdi4JIm7viOZFQ8ojfZ5e4VxgLLg5UHBz3pW5Oo1lziZy36Vclx3oprlPyiViKsdOLEmEa+ABbcHeyR3L2bUlUVLqGYRfs7dSNtUHBWrbij1vTMP/kAm8at2p17iUuaXSS9nqTkQMA1EDbLjvHMfF+h9DMjqHXxvFedNAUY8Ul0t+6TzhC1xa/Q781HYLSgJVuMraiLoFpnvAX+w/ZeKhrtMkhZz9R1KlP59NBAbFuidN69Re+DdstFWgsHdVRLcqUXJd83GYUwh1sWQL9fnNprgh+m47UKat7Ki4saLm/rYjgN+vqemltGA+M2866T3LY8Kk9JdU9FbvNDvdyrcUIF6t91zzOp3NG+rfPNPuqC98IpYsZGAClH10PUzc2kJXO2Fp3x/HHcR3KRpunJ9pO71yJBRjGhTNoT1Ex0c86hhKbIpzrDDrBbA4zGodlNdfuXjyefds5ka5Pc4e6feXwLUBJFHeB/xcZ4eNS36cisGZwq33NVNqMfzOlQMle0XpgHa7RAKB+GrvDMUHnf0cdnIcBPdQ2NvAtBz8J7HSrwZB9lEXzZGVhwdr/Y8USc35PcZHzxT+3tk8mmMUlJPVwu9SEtxgZ33YKfFZL/LwraNwn0916aiisf6yY/maZMXINDDEzejlExVg9d9YJx16IxD/vm4Rfg/KgLqf/+RwwrdzV4TgcEFqskVuwseotUbTe2mbdgwChn6Iu12eu+Chx0HNzhu+2/cyhxCrsDpnLwQg/TGULsq8qEO1x11Y/dladBw4896mXNyrEjSXBcItsrF8lhJm/j53T5teb7X+cb5a8/Gx2/gaAIqcQTGnWABa2lotJAPacAsv4N/d96AG4b5mYNRjXVVE3hrwx6surs7iXHZ3ov6dlvxBexWUladFpjRk6bJacGivu1dLZS2Jht/A0lGV9dPA/2CJY4laM3FIHjh9c2bjgwa40xpMalqIIEEIXDOzXlMK//7lfWfvE73RsdxNYXe3adKRLEuszdEfQAQ/oONXb4AiJq0Ij9LCDnjcHXQKOhJ8yFCtQOhZJ1Uw9pcfQ7LBD8iYzmiEhWEMQx/w33LnPK2HjXLc6WCSDBv7UGIHt6t7rfSZpS2nxmg3mjSA+SafLQfdzJonxIdwBkGd5UPoaEHMpH4UELQOyLm2cZDzPxdxvTNBEwpBjZVn8D71qBbiAQ9gmcvxg6syG1oaUGxLPEyXkIfuILMLXypZDB9wdKDbtsnWYV8wLikAdPUi1iFgxqvdt9215lCUypv0j2ocGIn0LPhYoTQNhD/DnuYnFXpCrNb3bUkQmO9bgzwCkAkWT69SCv9KNGbSmhJkuzILUq9N+AJp8wgUn+Xuk/CbjkjPkcxZFN+dJLWS+uj0WXcYYSfJOOQ0FPhIl3s/Go4NPzi4s3RIYE/32YhMyomaXu+p8Wi3qXjWGNhVw5OQSZXBLmAsdmCbxoXDbbkEdhDR2V6mWhNe8Fy0K1ETl6eiPLbWJ+3nJIHsrWXxVnHD6wSBopuW8TY2ZVIIQUT5/Set1QsejXdHZzUyH6B3nwiCGvxeak/syuw5J2I0mg+Kuwicu6BZBnLuqNcU3qh1MsncVKEkznUj9s00bHP3Ny6DJcV989lmznRDjrcIGyQGWWTcxyaCTlx9IfHdJr6vpmwupcHy+R8yRWXXG5uoD4PP3Hf9bzRGWEJdT1L+ORV4O3yuep6IjjFBEh3afxjm5aIeN/sM+9Z0JsnQJlAQ35GJ6NGOAdGAJJQ2pBmedzINqYgGUrk53ifLLtUR+F8exRGchKT2OxLD+JA0Bkk2O0DZh5Dnon9R7zziJP8+PPiNdNllsB8J3mb5JPuf2GgCXP0Bfv7m8uHi+FpiNe1TH9HJJdosXrTdW8evf3A872BaXkP9AJbrm6No4k6cx6T0KzwXrcMU1fMs7OVi3oyG+IgjD4mXVaCDKNRenlJAyF9bxHhPrOaf7nd7E9uIni+OZKgo67zBe8t76NdE0u4V0Gj2uZ6Wza7by351SlILva0JMio/qjDB7vdQrs/aveBpfqvSnN2m2KIuwodFiUFmZ6M2MY5470I98lApQdl1ShcMKnFUlupgYQAEPaUS1nfnRMzKqT664KbUYFX/OlncQJTqdUOeYCOcy3B+elLwWFhhIBbyEIrFbi2GXM2Nv9r/HD8KU/smYiIT8WWWcd+RamwYUt0tLwN4wVMFxrsegENIgQNbDjypHzgC0WdBTeoTnERUmcEqOIDG7wc4/loJ+H00NKm34zEajBJfSBxzFyixrxzS7JjvOB5Sd+yVHTwNUyItDowZZYPUKI4nlm8vc2twYVD2Lf7a38boSTq3XJovKnWfIpL/ms5SU7sBw95bC0fzE91Q1JVgLO1Lsblc0EXUEv+1UN9m2vpb0cuH0es+iaWcE8Tvuy9NQ1shaxBmhRp4A/gdAiHqNm0sIUKpmsdhD6wTm/70bi4H7nBk7XcQBf94vkqo3ALB13Kub/N6hDiCmiGikuPs8NLFsybNQ/CmsCvAPX2HAGEo536hUA6Q91POsBPKQf0tUNFSH6Qwz7zu4c2AnN+1e5gIdXKVAfbJ+Xunv4rPEknsUNv12HYAR1doQGFKBaxXCNiVzprDn7h+MNnoHuB0ufIXFSOa3Bhi06yy8E9eYvKHpccpqOQmzS/iy84OCIPXe7bCLM9My4u/Bn2jmnpAwoGgWY+KYOBGDjswaBYpODqVkL3w0hUEST1HhrVUWkWSjvjOIUiff8UiGHmmv5ccUwWqLDfTdygdCsga+IelsE1zhClIhU3h4vnITmJkAj2kcTCahJfwNTmDYfoYvvaA58IucdToJAfKrEKBruqq4LEd9aApqM8bsTw3bXIOzfvS47FK80En1nsyImxVEKHsLoWZBW0Fo6DDGR4ML0fUPHetqp3VkkaOv3FPB7J6tlTIaMzsGI4+zGHt/tRxAC0AWbc+Mb1TrfXGLQguBA05ucHdhRLzXfaOjWVKtp6VaXw/PfMBW+HhRKVfWnQtmIm1BftUxQ3nThOAFAdk9955z6PL11m+msnFaNEpGzrOfDYiOq6/pPxPYi5DTDfMvHc94re4ro82f9JnGv6OaVAY7pL3HTGhtc5UebWASBu4u4SjkNj9nxMtjhq/B2Rn+wW17x2W/++A8zKWI4Hp4nIYBXHJRwPKpt5168lbE98b1L1j1mE1erUuu2slvy1D40pVGTtmNfwVlkc4jhLcUV6hLFwCcTvJAc6Klqu+VFejVo3Yl1blIdD//Q4rPq/HkrxfW0QatxIKO2aMDF62WuSTQep5V8FlSMiY3dgY8NvlonMfXc+H/Mv7ZjSQU74tafLilocMsyhkTkqzFyjQClO8FClRzboaytnXS0S04YPALQ+ICIgHTTKtLr3cskycMTYAsOh6pTD/+Nwu0xjdCoORhjZ2tiC0uC2eoaAvAyz8H89QHgrWPzmz7vcRpxFtbwvUM5uLo7vLf+5c0TqZnntYfA4D6bxU5p+XDmFo9sYuWnzlS9+Mhs/kXX7fDQ571+fHjnEY9WAtez74DWzxsc0/09u1H+jCFd0R9G2wEq19NiwbSnVjhk9kAoB/+9Pjyg5lcenDTAOyCQFEBwYbMM7SWFe2ksguiWxf6UBrngLcpiHetlFo81JGzw2tUfMahiq6qHDEOpsxMsaZJOJzGAGaKbOj4/mNYrDil6Sj35ABnrDNhb7RVzMARw0pbAYOySM7+Ob8AAm8V/NtCwtcyijgjoCHUR0J5hgEHqYzFp52ViGkZ5gad0vBSkmGO2ExForP8owVgWVrJsxUo1YpSvXVu2j1XUJr7Nzqt6u2p4UYe8UGTl7H5eOWK58ZImPxM3QasvemvxDHzYbYllsv52OS6zOUvbPq2K6i1CAgCQDE5OyEqeQgX4DDbNmmGRzQMGIaSoNC4KIxIxIisQqumMeqp5B21Ae5nEbOM923ulz2epJuF7WQ1xIotSV4c6OH+ijNg9V/5kyQzm/I952mDKncmtRVrNSR6djydZzBGsA/DEPAGZLionbc9DrL30pa/z+dI/x5DOOhZ/FRNZDyj9m/CfMS32PCgM+040w+h0t8t7Lx+4rNQ9V8EFI+FHpqrkeGsK9rXheA6Gi9UZ0KJ2uaogyq38dyQaTU2ph3aSckMHFuqjMlWLOhVq7ZIEXVT6hSMjxxt1CRh0Ev60kumTEDcxML84YMKZ7fQw/pD7pxzSzwUu8DOis6A7Q9CXG1opc19jeufBXVP3L631RRZ48BtEbfomVICWw0ajQnXRHbYUYFekYVUwB5gZ2XifGsNBYwIcCzlg3c4SiU7n7CBbpu1/tCwUbbgY29BuS4sfGl9jqTDEE50dPb0wm1y6ezWwTU7FpsA9Wk7bq7ncpHcwmnxHdLY98YRRskdwNkAAOKM3kpcWNHz/iOqs4yc7/tDnY9uMD9XN7GrqV3R/KCaPOt/qfkC35tcdylPfH04F97EmN29ktuIpj8JwMLqxW83ShIWobz2NK2jlojfgl+h4iUBMtK9zlBeUY46W4fyp4BZyyIVGjrZzdNTG3sTgo/PTMJ5KBR4Q+n7Got2w3TJ6VUPSQRzGEoqDFvcO4828hc/axu9V/Dqijz+wsT9vMPbx4uFyguV8ZlrhZtW6DoFT7cJ9Z1maXv+3g6hIPu5wHjes4mRLX45XzJGE3ds/pW1t6MweiyzFYz9LQNrB01fjXNnMnjS8YXay9qzF+lkvBFa7ENighE1BM5kEp2buw6BAzr2T8OCg4adrxnoH7vN8s8S+LMcvDQKc6heQZE5/+q1dInnHpuHFaUVD4P1Ek9EaoEKZZWL5z1rChhebcF3QOSnihQ6JiYJRJKx/PafaIbu+nRjp+H2FxrTPQ+cL2F45SHyOs90m4YreEDSImEvlMypUW2DhEisucjK4gxLfvbPqqZOaj4JpRwRjXG/pqoRN5soEiIsyAyoHpnGw2mjMx5vNw/kmVvmsWO4E1CzuikYq8AjTKG+x5r/XklEpQRD02Wg917+xb4sS1tyURE4hUEkDV55HfWlXxOJaQRMz6dlgjQjEl/HsKxPD/oWT8hlsPWYXCNW1Xd/6baVbi1M9DkhgrW90d/TwZ0MUY6qyV2Tk+/qLbuADc2+SgJ+AMu0UEHyIynGf2LVWPGLpdn1i9M22CJaVO5oGA2ptjWPdM465/UnnLgla6baPnje7mHyEzTMlYImcAS6VjUvJ58Zp0b2rZ1jmDBxO9V7omZ+Qj9YZEpW9Bjr0uvkKAVyobKUAp/7YRxYpJEdcI3IAUPW1zWX7j5F3YncOUlT4U42CI0XRTepVdHWfYAhF4doYVOzF06/bAmOMiTLcdUCePN84VPhBhY3lrCixfC4cupMUPv+uLyUmc2cVIGBbj+OcfqrECIPziNrUiTM4JsH5mxeobl4UvuIkyaTlRPYwbB3S4aap6mQ8oEJt+Av2a+2b7fyb0RIUOb3HeRn+WOWQatwpVuVWYykPETLlbiSu8uFhHDmVYpji05Dq59ohZGGfRTQXhZ/G6Ve69Y/mcPpR3kEUttUO3HQebHR5DymEhdllg9HKRvna+VRdSluZHbBFcU/c3dyZ4elDWcpaclbHwxloxl6V89RNXHt7yHXrSXG7kWCA9sUqPqj+3uOc5iZi4+ZTqOVFLTyGRzEXJy268+dmLmLRfb0lRV87Is+MJd1VqxaOxd21rLwXFsZonk1aiW4AzGJtN9PWzBIP1udjDS+PaiviRRQmrqHFOMtLN8Nq84qReytG8ZUxPlw2OvQnZas/4TBwzYOb9RQXQ0UNGfYOwovNTz2q4R5QJNQYOcjUvbD2vldmQzrEU4h/2vBGLKmMR0Cm5nk8N6VapGQXKJf73CE8R+ZH90NExVG/k3eiZntMHfwX9UFcy3lmRF6Jrk+vePgHNNNTOOpgoz/dp6UkxjMNCmsiviDsnVFnESzcE94UuW1ryOxOgEH1zXaM2tC3dz3C3fa+MyLaGcEhMYLqoP7ffPGlrWeGPlkkPJ8RlcKuwZoT3Q3lnAKSHQuAgtAyFQW5eHJ5u3RUVGHiPNIM/OSbndhjMPWVZDtjURjxAONwOliwWjrcNmZEz/CfBXb5nchdWQlQXcSX7oYCobuKuee6NLmjDPF9B5+4ST/RUZDu6Pv3NDZJMnumDiamhUCVXw3xquKhr0nNxvfd58LwRXobpRKrZqRrPlZrekXPfIOO947iFznejmI/15Whuvhgb96k4z8pP6dd7McDh5M4xjbpPNb7oq3A6Ci2iUngoosFZ34t8Rb9CXn+XsV5n48lhxc5uPlRjRkfjOGuHRFTntePFuBxnov8AP5LIkdxe18fwGWIPTJaB3r+QN1JVcER8Zkkef6ariJ0AfeolM9iPu+0Zi/j2pHPgWr4BMsk0BSxR7bDqGdP34LcjtntWCvbT34MroGC540XnvRqOC3xz3qPEwf3jjVD0dGj//FnxrsdEKrdkyFjUPDLxB0FMkJCTk2yb6JDtl6Lt5nHDFa72oT4F4k3eP9Sl1OMGBxkhjWuxMOqw/z4cY1z/2SGSHe0O1e6QOLtZ6bfgIEVpRqgCuR2EUAf6welcocie2/h+61Jmd2S1opHBGtgqTvwPQQGEnPMUS9/k3ItzMNKEovwvfOEg3hEEZSZQ/z1dXV1pbtOIYxEJolvcV1LuMNIx0IcL6RJt+9J3/AZB4/iVAwLxzYs5oMr9V+V+Zd/awN4gZPVJ/2F6RnZ4Ymk71Bcivjw9zFh9Jw3O3IWyUbE73Dw7PkLbMGqkQjyrxDxXi/NuNo+YSRt7bFl5M7nlaNCH0stvaRJqdbraldgeBeYIRSaS81ycjsbLnz36uSOYLfttF6TpE7gANu9a/7E2CWE+rXa/gT6VbaI+3s3yp3VxzqOKrcGly9fa4O+jdJitYK3cWgm3H+ins6V52d5zCpvn1ARhKzNav6XRUWwVlcLDEZDt2ajfwG+IDTDC4tqEuoLxipLthPwlyajhvIGUBGBQgoP9tpNUYXCy09naLyIwM+pISqdjkZg8nOfie5I+lq+wTC6XkTwtifxocxqRipHlUgQ0NC1HR53tQdwqTeDmtnY6dgYOEZt/8N/9kGlZ7dktwDggIak01RYYUCbT/t2a2c05I/xwR076LJJWCv35GWwHCpIf3zdMmNYyYm6WGQq3f7mZC8b7kUHv6TutgRTErcE5W1/QeHjglkndScHwE5i7paHgHMd5NnH5u7icWisLBAbgbj3y9JcugE4XWV4tog8+DsbWebTc5TR1cO8FH4cgmhUZRyjTBVWOSnXJenurGkzuELX4pPAb/xtMniFCCirDMtux7K3Pj/nw2Kl6JudlS+kFZPVq6ZlKMn90iFz8Ji7ptt3rFkCPMxXtrimC5B4BDDBFK5GLgQdjya4xKjShWt78fjAWuWwO6WVQd3bCDa1oowO9T8Wsovy8Kx8Gv/BcuYy2dGO/iFtaFAcMMNqcOwJwmuLwJoaSbCqVQZVpK3KbOQnqScwuBeo25LUHE8BcLuOYUAeFWIWxQnqmB/5hnTynGZlH8dgVYxAEWaxQI6G6Aw4PrPrhAxDJI0oo0J7iKeggRQcJXVVAzpbtqwrj+iX/nAiNt+2tfGU2NOsmYcwbiZgGUFCyE25R9I/YsNJx79/qiRj10E2kRRWD7mnW3DdzJhZ13qLcEiqUG6Tc1YhcAnAjVhVmBPZcmFmUYlaRBws1WpPDNew60iUK2/4JPV6SXnJwm7jVu+phaBgPERvx1qt4CegeKgHCeTPgJf0IxyVs9m+JVC/6TBgN1Fkfuuk8hGl+0chpPkIV/F9EpC9CGJi7vgrLLtibWwfte4kuqovotN5i3BbHyNaO4F0jPVb+yrxAXKYj7Ra2NxCbIXwWfVvvsfCG/yuSdbFa99lPiznIyMkA4mA8SAlZNyxIW/iUrft3qMuGa/4006abITJGJuKDmFNSuvMZTB3Vz4mLa6FvReuI1YZBhvo538SrTe6e7BF8g3U0bDFRlgNO9jJtbN5+ulNL4c9Jl+XvlpwVDZUCaQIghYwWd0cWH05nNjBTY+tq/phGJfX/zhiEccJC/Fyuq4/ZhbpQL1rPeLzt+sCBFWTzfG14PUsxsOup/bCx681k185rL95C9V21cY9F+JYzc3YIoDmEBXlYVF8MOdIhy4tfWNIG/zcOeHkXE0P3EeFGUBEK+C0pFDQxGXbUC6m2RfxW2Cp00Odoj+Oek2xcF1k3TWOfE5rgmwSjltwhMrr2qp2PqV/o4fOzpiR7JnIfemKVMaOEaAVgqaWLPk/indsUQF/lYkmPp3hJ3gEpFLfiaQkUBgj2McVYkHVzPx0aEmbpw5Sj50VfF8lAVqgZdU08sUa21c2/Crnc5BS5Ez/Jr6DLYOUGEilvz43sG7C3t0M3oBvABrwlaJOaMmZ6xjIRTzhTOVhMe2Gee4dCFircjU3iu9Wk9cJTdRx+H5n+acp6yEmJXNZ3pzSF2Y8AhZ6w1jI2SFDD4sRethscoHuZbjgCbzTqwgjIdYIKMfAQM+Hl9U0ULN4WClzsOm7+DLLIyh+uQAss2Jf//ucfuM7fzhoyMKIPfKmHMDe7rX/cDFVArSATOQQhc0AEcvFh8e7vFLmFKORELoObwAoNlbFtJEo5szRvY9zPi4qm/mBiHcF6Oy8SaSiBrJsXR52RK+H0ue7Xj/Bdkk69meCu11+Q+yL1UW2FyWcDbwhC0X4RTPxR9uLzu6ebLOxRVwpZpaADwa+Mwq5XAwB7J59OSLqfKYaJOIfhEqAu6srdgZa+ksDOlEpdVSUEwvOyRfe9H/q8XHcLYj5/EEXNUWr7iJchm0FHWFPfG29ZIVyAFoA+/XvQ423uGRdvck/P1hRmpjFdeso0wOo/V+vXoDmRTrcjNrzs1EL20B/BiPO+zB9FkcBGOwjNnj8tCdafe6sqOC6CdeEyergX6LulwAZg9JB0tY7wvdhBeJA4ol4qZI5FK6L18++NBTRUsuCY7+6CgMI65oXicl31DfzzDR22E0dzfpzDWVrDKZ8Oagb5TgWUDnumfFn6MHaaOo0f1e+FHhdc0VUza4ti9bbt65iX6pkHSaF9Jn50Lx1y2+/q9f1fqyv7fuz1eezklLORMoVvCeBzUNohK6T/Yd1blx+F4faevt1ydKpk4vUHtod3qJgTC3SGiVWT0Uy5VXA1H+ki3mKdL5W0l+4Z5LCpADl1FDd+MLIX7YJdqk79LcZtiX02hznsvitXo9Cad6uWqat2q7b7HJeH3n1Mo93eYcy7WQe3yanxnfJppk9ZZSOAcrpgi8yGbXNSV6585pmw+60Yt3dRoaiur9Rt9rTp1SDWzUYea8bNmSVMqXD99icFNuG6WH9fwJda/V69pORoOhqLb765n9tHaaVnXIz65wzgVkJYq1mLlQ7ilqWUhh35YcAD229h78OYRpXnUj/vFU0qCcn/rYqd6JEEL9Co1r/yHym6bwJtiarVUVAkmSpLRcmor6nohpwwlRrmmDyfj/IyV6+5idWVLO8sZhvIAz3ePY5Y5lL6SuQJt6HhMm0dYz6Rga7ooPOEn0BpRXn0ZJWurgHn1Pk4hPIobCJIvAfYSJNIXcG+VRMwILEKKJC9MgjEZ+rZA2laWRjUBcEnwixVU1qGe4ALy+uH9MJVXGnsDbP2ETJilqzqLnz3Xz+RGUn9HFn+Nb6wu2cUOg8FxvIBf0w5idK7rO5HcRiVbk8I8BUi1/coMPh5MrD9LlM8/MR5noGUgj4XvEG90U284UrkROQkgAsJK62QnM0Y3GczBSvzdGO/KZjRDCgYctHhMo4Lu5DbfCMPrXIvOKyb39901+XsySyqdR0uYR8mCFdxMb9iNem0sSLrA+OSgylDFMHLCuxUWgtd0rLXLnsMm9n38d0EAhES8aLqa2mwcoJewCXGsWEO7fDlW70eHhO3WAWSrr5RiLwqdDqgv9QW2AtowFDNAdtCPHjfaR5jiqy0EJu9lUwsHGbtxp5yPFKcWdLes39XfnlTns8qRULy9ZlZVO7TiNZWeHqiuSICE0xpgEiXE1St6KCpS1u7vqPh0jn+S6OQLht+/6eyGfFIK4zk5uMsYcONSjLC+iNcpLyWaFl/iAshC07H9pEIjbioS7E3OyV/g8st/2f/r52yb4Kr7FBMsVPqzIT5foQbUAXBaoiUzeqMudv7+D/cSl898DcP1zk9/ncquAz3asRab0P/vYXt6sDchpnCOso9LEJ+/7oNwAP7m+zmSAGrsy5KAn8jSuZaIjXRCyyeMQSU+qF6PZk5l+ggUb7iFBuCQ2AxXSnwGYWb2F6tvx5GwBmdmCqiN8n2TY1qok51fluYdVkBa/PFoeJ/y+4E/lIj9z//OgDToezNwzw7hKjJZzrGArTB5f0MG2BbjuhxDFbJjFKqx89NIXdT/+YQNtm1gZTy9f1zpkFVr7TX3TGBGdvoc4DknJswDG8zYm6nJoK1BYFvaNjzL/18fw75Nc8nOmnBOajc/XRjgXPZ5GJ6YWs4eHf02oVqkHEVLQGjwT3c49Tx0A71CX47qtgZvjPTQ34DZ75iiJ4QVJr+pmLg3bM06s52Y5FN2rgVESJ28LUyCTJ6EDwHeOzkCjhZ3EMS+LX0aXTSYgcH7wNHsgl/pUF1ZcvhgMqYzJ1nvwj1WEsJQNh90Ql/Xt+2RZn3jR7PLgmjqJ9btvhfnnJjbckpS36LWv4ojTYgVxhJmM8OV+KuJiHoAESXXOl52eaJDYhtIIznYhw0oiunKe7XtA+eMR96PiknAz7DZAxk8i9I0wAoEUsCmyEZHM6EW6wxzUUEmopv4CDKubrxu+x4m9tMBHEQh38mJSXKznHpFsN73YoBJq6JuI0nTktcjw56eBwLC0AwIgruvvNmvHPc8Jrj/EchiS94gPX38xUS5swCVTad9da4wojE7xaJCALWykbV2x43mz0rU4r4smkoYr0qVb0GNfJsPkIjXrE8/f4oCEKDLne6/nGvUsPxdkuWiybhIEEr6wePCILXeHa2ooK+H8g3oy7LohsSL8WfZMvBJlGDx1Cy2I6NwPvfUmsCcmY8Inwxu77ICFdXUeB10sUsP+HHzFXW2tOLodGC4ZnPHsx34bh/G7+4tX0InEHYMKEfmjb9cwnwsSt8IOYiLvzdoe7kOW1wcNWFNfNVBIwHCqWmcCHbRZJCd5b+OYzHGekmB7VYR1dylYpy4G9hCGrccI7qWX3HwCjNm8JRDR81HL86K/qkn8hUyLbADijqRIKQAkpCI1obbcsQZ92rFVG245mmereXSKDqoIiRDQ7gni5tPtqPIzZivul3n7nvBssgjUOX5dYhyIjqUxwEO7Gk99fZrx8Wp7bOdaPMIWoGC2op6TSJDm/4ZVnlF5j/a3XKsfVFlxYBSkyPCKrLR+2oli3zT4ZEkU95kXWqoH/sfJzDvv3e9dtv/PfSSoX1cZUtpuGad+nQLXj+WeLcl2VgHBHysW/d6SWc7tYQhPpF4wjGHSkODlqDMOQR7IcnrcgKys2vicVvtyDm/5cnEPkN4wssDDMiamLg7lXDeGi4i6YtA9XACsjseaOL53tkoR3dUXviQFeARDR72NjZm/dv4Zwa0IdZfVGOyLPyu/qys9taYKHFFGPoOc2HN/8ajn6mutVIf/5YF2SyHdkTjhFTtoAsJOxfVpdTq8J+mOM0cLzYnUhU7hoMNSEuRxeLbGN5nF/hlHIN2g3BszmIcuu7Qv+QseePuSJXUj5yGY/mG5d16dqBEr+b4nMTcx69IUk7yxZ/yyibAUOpyeFtOr0c702tFE6RqCif5AAkFiThApGFy5eZQ77A8HKhtsRPuBoL/GHXM1n5gzrzfFP1YZzO8RU8HDevCjwIdk5VgSq9oJmlnHst/imjGj5zyiryBW7b58Zx07p0n087PtF1PL7AdLnXHEltpUjdl0s0amZttYm4ELuEd+WyyJorDeM5+BU/HYaUBniSgajnVwodXYiqIFgTafvhawkUCkUfqLYWfdhuLzP8iLLaZPOgVRNAuWbFe4hngVW/7p9h9G9+GP7cci3uLT8MwR/oTKtmV8xfti37310taas0IrA5uMjBPHGf7vIQWtM+ODzgjUmPkzCX6MvHEii+A9veyz22OMPrUXXyLSKcclghnuVzFQ/1ogCtLmq9GA+FzMNClgOPyq9sfll/qOnaVIGuxAD7wP5i4utOU4LIs7M5bWqNEed6yN6fOICzdmViW0Xi+8sSQiJp40Nrd7Rdhqt/0x2B/YmxhV9NGwLyA/qE6lYGkZEKXF8UeKKrGjM3QcnZ5MxzPE0sy/P6pmbLcqtbuMB6ABcOY15JvMmDgIjEVomUOCe0DkdjeWfREqz/lzkgL68HwU2GMu7qYRFHMLqvfFCl9XJqTjDqW0JdLlXuVm5JebtkanLKm760ge9cd0uKWhHeCNJZY3r9LgeBIE9e9bwk0U6eprh/TbY2jH1t5RMyP8bVMJ6ccFukkx9LUs44qTK3ohSSdMZIDn3X7ycmSDkveOe0NuiWNJrRFTvRWr+TZnRNTdiU9rKmpAG7WJRGofMGiyLHAKkDhWVF7O8BpI0IJGquJZfal2TVzFVD/56eXdJAnd8ifxbpxDUTJ8ANIymYGtUQ1OqOhxDatOBLkfMLvBgU95tlqu7zpzj8SlxABQRQ8qEQxIU5zUuimzBMfc7aAEHcnpuKtVeW8yOS5yg3g9vlTec8UPGnlM3DG17CAIOuPuzNTm0FpAtG/eLVPTrpm/tHNSeV+0GfeNtaj+CwOGTcS9ut5U9hGNfaTHiUZSvBWisL3XAmSshNHV221n/Zg/EaPAc7ZIEgFATSIM996aSdRsi/oTEcX6CoHWvttvrEDfUS1KQIqPJzFvfeLhhJTRbY9ZhBTQ44dBEERJzE+dCMhRmBSJRGIxDhrRn9Z36kakYv4bkW4Xe86ZNvCfwDn6eqlpr+WfBIJPSTEIT+DeFtd5pbG0SOYMwMgLlfzbwYv605w37YUfT/rddLJc/BqRVVBFGRIXoQk4sinCGYL3qEDjj7nZn/iRIquqk7TdMl2rh+B1+FKv4bImBNkRULnZBnxz0OSishyBQjBkVQQOEIp0lkI2RqtFMiFQodUyE1RmGHxCAk25J8EjnVGiLamislk1Z1LVRMKAr+drH99QLGARJOVxxlYyB5YvjwZ0FkZk1qIicqNJX6dmVmoopxuZuLb89ak9F06DiY1WNrICU3cTdiL7cWteuD3KWPtmJ2cX9/bj3xXNal8NTzlo2Y+3jJ+SW97YguFyFbFksjMrcjqfhyoSXmkPP6kVH+RM/OAo80I6nDvXOBwWqubUj9RXMigAojgSioTCg0r1zh9po3gSgJG8blWlf4lsfq4rhSchaMMQklUjNvtQl8H7Ofi/UIfLKD6wrVXjt95GVUiChH5ELrvhYoWWhtktYu4i/h0azpoTXiD31a5ZvxwniJkZBBow4ie1xQgxCb03ho8XrtrB8+tO41CMXPhtRZaIKhj6WO4wQOdnUpheQx5SnqBlq9pzP6XOyOfznhJhveMP3yL6uImWtoVrHzaD2xRFTh+Yb+BW7oqbt5Of6fkY45/saU2TE8dQ+vIXugpTzgKmsdmQoXRwK7AhiE8Ws4xc036DT+sf+RgV0u1oIt7oO9/Nv688vwG8rwkcUph4AoLAVdPUoYjZYWsROpepX/9Q9nF/eTyqBbfK/vekHzxYoasghKkwhOPFQ351n7DC3rmNYQC3efwRWFxxKSp5zgC+Kj32uXK/bCZtWTUkpKZbyGTWvr7FSapuiPNtNdznJ3y/cHKOPckcllOwd/U9dmTJ/c0utu9SKTnJGcXlEotHK5So7LeansA1/yzuCc4O0edZirgBJ9brtWqPosBBiNMQ7gCUcd3bTG0agK0hOUJsw3i6q63RD3xT9A9x39uGQqfWgEGDoBvIy/x2/ZxaB4q14RRJcM0R0S1y3dOf+oX44laj91/uv3OyHehjAWiT+zmhpSicufXqs6zS4dSyWuv3bHUvLruqbeFOK6E+9Z0+ZBcgWBtUqWSwi6eFdbv4QvnC2S8AiUiYEAIQiBMWOsXADPnH+mAbue17tWt8lbaIShKcJgLY7l4idkHO3U549lAlQPmHTwkMxldLARKHjMpwxoHp/n9KA9XLv9gtdxqeruz+frp0w9H96TNHzza3wRH/hO/HEh7UFwr57YkRe+kEv3qGyEpeypno7rBR5NHykmNXg2I+dIjFcDnBFocUKP7S+to1cpJxiQ5G+wAUmPnA9R3xN3PCWDYUmViANOI5rbvQDhfgwLlAL3TEpQ9Z9ro/Iju0az4zX0hxml46HcHoXvCazaHqUJO0/T7qJToT2QXC4iAWfOghzPMh3NRf7RibExS7k8jkk3OHQyscRd9QD2LfWn6sKJFZqmRfSTdEUxVrwS5+MoEk091QHKd4hRIBzo22YDp0croHacvkbku/WF6/Xs+h7VzXijoWRL+rhJEsYwWgOnZfhMsBsOHI6/zcwY0K54XXXbYTcsN71juwE2xAyCzTbgpEZhDcZOm4I00jQt54sHIMC3tNcuXcTlzL91oqwpFGnb+WR/6C7/8lTzsx7j4l3HsuX+HRWyVZNbNaIjZsHB5bumvTNH55AYr0UPXdJTshfrorrwzuCzOreh+Gwus91z1wijVtaym1+mqd7Nb6/r6Br6s5lOu6NgzOesNm7YLldP+yVLRq6eCt6shc1HmlZoj+kcCp6LuGSQZSIrco+87H+bMVl+JEHwuVsELsvP7EcCngsuYkNUtgWMCU7wnKzr5z8/DIXJyE2AI6zhCK2CK7hqfYl2P87tYaNqIVa+eDdZz3ZsYPdXlpUsUpwrl8iP0aUfjiDHXk28I899WipDgJBeRj0uCiSQvNTrTAmbo6Ug0BUbseRrRLOzm/PC93uozb5ldXMhamLADOqidUYds+DYXScdVOw7ABa0T+TTKbH+0KB2kNk1wx9W8MqHz13zoykbEDUatt0Aj94GkwCh6GTonkLsmtf/13csbdsTjvaq7ZuOGJwq5oo+23hxxg2l/y5C7xI9mTDgh7NN/Ixy4sUIGAA9vSJVq2T4sE8M6h+mPc67bnBQo2dyAVe9IELNmBwZ2DQwO+y5wMLBEeBNXdqsX11Hvs7TTiU/EYcjmE/kpd9eOt9EB789ntuEDXTD1HOqENUUTdq273rkI/vz9Qw/kQkXRpEY5l1HtsDaUv++gUDGuiKu6iKlkUhud7Bge51i44neXBa066ZhUdwC41aBJpGga3YRFgaQ+o0jOCGL1GyDsWxcf7YQXk5I7o8f4BGeVAEkCh4LqXOpbZiUF/AlCsdNvqJSD3jkQGnChaMVogAG11m6ibuykv53elaLWkreqsWnTOT6qYlqOEIL4FBmn5i/kXhCGFT/g3XOL1q/aAxASR4cHiywFrUmIT1cRiPAWsJKZBuiBTvS3cJlxUhEW6/pTLJ+VXYuwxExOKCgXcNa9PjgwmkffYcm2I/zZ3oIM2+CWTR5EylitRmvptFCX2gs2f7Dm6Ex0k+cozq61GWnAQmcEZaY2zhb+zHic9DySX+nIefdtgwjBGhluPi8Ozrz5r6JI5GWARQvLblG0kDYOo0yrj3bsSMtm4tRu+V/2jbXBdUEzDeHSTGxkV3xRCeAfe3skd9eDZxQBpEwPZODZ0OFt7jG9ndhQaXFU4MCMlU7mft09ws9q30Dxrdjp3I/qM528CkhZQeKAr+yqwO29e7Bf/g1rjBmYhQhGfdzLnVSt3PgCPP2CTy5cCHMClmmEGrERiED+VEQx3EghZcoG6D0lGscX1Fkg649jdFEo9P5rk2pCqWWvKNkyysRYHTTHPTXY0wA4T3tnS9wrbGhFSb5C8Iek8v+7RgR7nZArXnfFx+exksMdrWlNYEASv8pji4sZn9GwXzNAkbWLzhGvo+WreGQ6lN2lMiQ+nvdhIS3QqCnJriHSpXqc+R/cpDbv9mTdPZcZevLWtbRoZWuHhcLwdVh7Pu7SFRaOGfNFgMp4Fq2A2YuPMdhUEz468q9j2Ls5NV7067dfJjuCLTAwVm5jhZ2fKc8esa5MEbrftLdNf4B/rdFf9pwtGBmWoIYkbTRBTAdgOl0mqYz6M0vviDR9HUFP/DLNkz0sINvhRSxiGgld4E3FvtaExn4oqAzZZgn3cqO4IhILvRecNxWvuj7IZw52yi86S+/xMk+7Gen3qzhTbrRAojBBYP26OMGyXNnajRpfSbxUJWP7J8Cry4rN8A6MtBX4MjEuhGZAyAtlgoaSrlAKjLbffs4x8njIfutfXxQcPawgcN0S7LEpjftVa6k3RleSHiddfBo9Q51SSO1dLJ8Iv5Cpd9t0ZrDIS2Al1MK7mFHK4Log8AYOs2wm6ySw9ImKyz+6z2RB6jH65u8XiCod5WG/l/PJSe+8Z34d6HxXuYnk2wHmeWUcdMzvvkPS7Dep6jpFe3qrrMgCjE04tft2O/6Rl9axCy/r85/EmK84eYBZPkpoY/O31/uB7HnT4GDDpHyqFtYAJmoacFFrYmmT5swshKmUvRSFDo2isgn+98v1E6Kk/MTD9J6lAHyn9/vyA8IT3jSOx5D7T/w6bdS7lPf7u+6X/hmKzPqG+ct5ZkrHr8Gg/GyXXSB3zSKbTcabL7lvwnL94KKTu5Q83nzhs2puefNZoGJvCXM0+Ud/HEcm8lF+CxypUyt3DgEi/LyBZwjhBoD/kgpbktzFi54jFV1KrVAsqFXIh4KJNi+9Wz5PhOTsDAJ3DZ8Ws75pgsvi98URhfes7zdFEgDtO5BoV/LU+fpAH4OC85pIyp8KR2AkTQpSojq7pWcltpbqRN4QBZEIgoiFkUZ+iHYe6614QdMQiLBUshcBrIW84VjdwDRoERm4qXFAawarU7kdBB1AJJDItagBDKWWc1WfeyoQ73Ao/FfSKsyGivjJwU4/jGiQytdwiiKZSamOp3CIEJ6fNnnQmxgLkNBiYxFSLyNR0miQDTadGGgOhVR0xi2a62+HAKRZJtP0VHBNDu9INzCgE/nenNWDifU+TapuebXPo8GmEXY0zhbr3O/WVGJsVnZpfc2Dw0TbMnn5zcAXMIHa8w+j0rpTbW8gSQ+WPdwnUbbbM6uIjvZmHWmOVEkQeO/+DJOK8awQD12eI8FotSZEXDFKzk9CgZYvOpX/4GkGYzjJBCtj4AumiSnzL7yPLo+Rll7QYvotesJscqFXf0thCkb4t2/UQPzVui3ix2za9PB71CVcsQdnkXwrL1fpTSKcZ8WP5NRH8ySYS7RFjS9sMGOFovuo0XYIzPk604ASIRESlCKoxozcGyajiXLn+m/hwX5bFcLsxk1i/XW+2nKhLOXBTssXbNk4Vwd0pmodcjrWRv6gl/9o6+Z1v9sSPUPe865eFaay2U2Ao0xx23KRPzKs1/G9n4fnfHurPF4uZz0yjj7pmZu/MdPEvp30mastf7G3tB1OVSN59eOyPc2a68cELoNccckM2tlSWxUKQ9uRoQ2qrljkvpnhi42v3P1yajRpRmUoWdj0rf+YIwOH5jgG8pdGhg/DEMoffHg0x2d5fzMnl6weYIvJoBK7EuboDPCmdWg9+HK9mMWZfHbzCfMS/foWEU7lbsiEIldP0sEdiL41tCWYBjq9psg7eLkLdxtmKmelqZXBkIm5WosMqOC3+Ph8g2DxXamKZQJXXvmcAUzo1r6WsXPLPDZ344sEgFtMHxHsGuoDAOr/ZGEerunxMiR+grDgo+SnoB22FmKr82u8AcsiUK0YeDvIcK4Iln+YsKV+UNRDGXC/G0AANj29+YDKnFowqZ6Ui6LfOmkg47ZODQ4NRr22zh8wmD5lMHxH8IxLfB464vKykVKtek/dmywAuDDFBJlSZEkYblB5pLcbqMCgIU8xtwswaZDpk0o5EdlzaLZWlNxBMLF+CtsECtDB5xvmksaIrL52se5acYf2t//LjC94V/W2x96uLdMcKLhjqoTXLsBxRf9b3ZrZPpiKNNXpHznhXrr1TWM/lJkIGgQlvmFNwyUHjHnGcMxG7aTavHz8IPi2OYdBq9kuRKvoTWQuNP8J6cZCdtplnJ4H9hf2ZDLgJQSBnOcY4yGz78btO6zQbiKVGRQNBVPyCoUqYvyW3HEhOkVZoUAv5UgK0Hhvje+q8Y9dq+gvKne0s6S/0gyuKj+7t0Mm5aCJiR/qFEPI8aw6A98Sl3of93n0iiHxRlDsTx7A2CpYnMKVN0vs5Wq49A6ejmP/d/YeG/RN8/m18iKHN/O2U36Ffihm6vXH3EaQ1Us/fb48Std9O9NnUo7pdDaYIqoq46mVtOZ2ZVBgSB7sTcuxP0UeCa2UlnghsZ2nDgScrZF8fjdHmgqx01ZcRf8ws9hV8isD+U/KgBKyjcWq9zk2Nl34Vw5mHRVsWWFJb0hn5zJus62O58TPWOqOOZIt/UIL8zva4+eWLXrtzUdBCmIJbwhJOyuBBuOn7JiXXhqEksfQNL6WtC5ZPKCB8gJrRxdb4d2JvdBte+apXRZ0+5Lvbz/3ylPW34IJCOHZ0CTbtBr4Y1HENVLdSS1ft5z/3pbuFhfJcQLM6bKTnlEa+fx76rGjX5KmfR1YmKw4m2dhoIRx2gRdLQhC9mqy3I51i7fDhmnTR9ySKQyeaXXjnVxIjRuVYRihM4SjsZY0/mRX9BVr8d6xB9vaQQdmKble9/+7NTWzg0fxfP62nbZNe8x8ZZh2joSiXwUa1xr6E+S4oZtxHS8bHcvJ+lkQ7u7OJyekPRScyYdR4rgxpM469TLd54t5Rk4FkXrWlhOlZeDEkcSRnjf3p/DNaCB3wYO/zYrEfFyAsFqc7fP9RW2OPalRFKrxNJL8c/qVALpe5dI3Dk1CuQituWYJ9r2xhcThodNcviXOfyOB5iL/M7RaSPgeRmHJC7iRjAca9jm3PHzN8zLDXdvSfVR6XFH/EoJy5N1uYlZdIY6WUFLRQP12PkmtT+LJmyHRxw0vou0cxkk2pdzlIBCqzZyzFCFiqMCjxcgJ+GwDFOMxmUcawLGC5iLY/lvylZR1hY3AGLRmak0mL9XH8PENwM97Fwwe/fQuZiT18g7mRvaBg/4MLeWqehTnX1dLzLo4KXzKQiMjcLCuFX1ghVT99GXesXpKZWI/8ubecw8f+TKaI9RRXkZ1pobcSgHaZPGP25kYCbsV3emlna9yFrdBKTMstVGGOHYKqcDGMIsP5c4QKpCHSMSFEA+iPwoiFZbuYxkhFzV9ebBrHpnzFC8hvJNhTlGtrAc+wtPVfVBrPSeGAzapCNQdWSSBx+gJkQIiRxWQBmUMbCRQzmURqxrh1rHpWQyVJeYF9oG4HBhkQ//TwIuBIm7sFPw/lwfaDiWcdxr5pOykds93U6+dTOqsmLPOWSZMlZ6mzqzF2S0RhWmUccTDb/0DrZEbx8oc5+fUXZR741U3bmoEltW51RaenlU5sU1N5vecco7FNVcqLee0bcgoyzDApSz18yNTN1MUd/nCOesZK9ivFfDp4JZ4zqaeTTzOIrVvmB9793NGQndfs7PlkJa5svx6jf73OUxE443rlbIoGmLWdvfu/UGYA3WptRUGCknyKgkQQqkz8SKGHYU5AU1QqqZf4Sr3UJk0Z34o4h1rw8dtl5ph3kwvny3URvtiY149mzyZI5xhyntJYa+OBJeiW7Ht6s2oyM0fZ9rNws64a6mgfbD3bhqH5tS/8h6Av/BuNPP5rlmAGY0howf+pyjZk+cDrBRe528R3WNpdg4jbidrEOfunRv9JdKVhFvF5wuVWAxY7X0SqBUz6nrbho4Y5WJG4NmEMP42YnOTGLV/9lT/wCAxcGQhmdqNkQUPPsXnsCtAYX77SxuChw+L9BarEQjOu0n/qy9GEwnRJeOiBlecGbSxQVvm7VmEYlDn9/WnG1397Z+y4C12Mj82dzHjXGqXsjezqfy2XUoxWw92YVw/+K2xLhP3+bt3S+aJlLsv1uvq7WtMb005Zv/SOWFB9NO8/pLmDe3HvZvDcD83PbwLjYInFG8+pMCrAymRZ9RE6cHxcgrqEgFS3jxVAwsan/NfFugFx7E+Lq0ufoRZealg7SjprpTe+MHv/vhAK2NhmYdAUEpmOIkWAQyEdrsVjG2jYRtr5pG2RMlwZKAGSXJoYzI2EC7VXzbaeRs6V0rKwAkGyDG3pBWoercJIKJMjEAc70aIYXD8iSN0yYyszhLEoj1mAirdLf74TPjaeD5x9/iUULnvz98xx53OIhwY2kPcTIJpaxmCGovC3sfNcPwJLkX+/FqP3/LI86vLJyfUtcsM+FaJkE/NIUDffWBFEz50rhVTJraKXll4rpr6c0CwIh3oFERrogXjxWa9RO740l1Lm2iZaEax/ZwOeZYU1kdDLPyUS+foPUEkvbFGs20JUFIB5+f89XbOEo8Cq0SgcQFAiKrMpYlKCluEDFj8/rzVDADvG5hpUaoooVKoRRVZOVHkVKKSrK05uLzgbCaPDl6lDZQhbRRsFetb0PiPZvZchv1PeaysQ9lrkhB0JIuTVL/7P6YolrQQKPLU0AcADBX7GMjUNtfhzQd043LvSXkRAoWs01PWGokjwyyG+uc//PnPC1BMncK0v6ahTgAgWBxx4oSYntK40Rh6AFKuePbz4V1YgkokU2gxO13lniukEWu7dUnub0AsOjHQ2vaCq2d0uyoVXjXipJqPIiFwvVFvco0Akf8AIHKrrwIDqALMrCKXcI/CzsQThDDU515VCZXEXaW4SiArZBd/0iOxMQ2H+KMRKEZQynk+TEIq9x6fbJqah47UXGImwZKglISAjGbAjZgA5WWmPhKvYNGt/Nk65Lg2kVhorD/7DxSySRAO2kBF2N0vNCYhBKMPnLW88eRSZ+KWXdWBm4L4rBXBxFWgZc9XYpeU4HZRU/1/WukEHurk/8d+AdZU8q0ZK8icA3HAAkBmq6fLjiJmIQwv+rylUEmT7CBZUnLUU7wmkJ1FtLgJDIQBVrqHzkb4jEiEGIZM8Az87JaxxWiuVloMQv2oVD0h0uHbFm/eaT2mA0CGLWHWz/2u9FPjZ24zMHy2juf5Wm0JHFHEM6Fu3EUiGMwnzYtETGsni4O0Fbq0zokLjxoCNietesQkKCUrbalCk51gGLauC3REdgLXCPszxeW29Fb5O9PBZi+xaMcY0Jitgt25XIZRkll8x6fjADs5iY+u+ZoKiRdoJiN396Z0enw7GJYd8fUTuKry85ydz38E/KfCAWROpEYc8sFNkWiJIqjNIqz/LBDk702YY+dKONvXX7VvjC4fIbAX8Dz5ta3o9biCqegLBPDZvWVYRYrqMDnbS+krfAKZm3ljlyFLR74tbPsYt0+vcUTG9sG8QWvi+UOLOOrsKtcLGd5u/cVr/p9crgbGxaboqlFvnpjPaE2isgBQ1XO0GAGVkxSavICAgVuNwszodqFB1WEQsdKKC4KZFhv5+dXXteyP+v9RK50jykqSXM/oeCoUvANEaJeKI5NvmkRbUtpotbWgVYeYZtdvH6NHTuJ4/FQsQzHhJMqgjcQluapEfcTsarYU6FabBM1kbroxXyEYNyp8hQswRwuyHQPVGFygoE6bH3A6w2vFixNuJ/d+jR5k1fleM2jhh9jjkuP3izYTPePLslsae+9zTTowoypFSXFDSAO47hxCOSH9WAblJ7L1xXDZUsayDQ+mpU4ydMFsphM2zUZdqetKquyPgQvb4ZobDHsHJCY4pyJuBLL/sGPz3YAmlmkcxV3Ft2KjuiFcCmvppysW2X2BczHV/73C71POJm351jOyJXfCtj+bE8STmZd/umZGEb9BDR0yqXGNMup2QXR3PYPo3ySSmukNAVBXsdXqoRtxvBR06s6rXDRNcBqP2Ue/8v338mEoEzkBo+WacMLZqf3cY1tScYeasgBxzZlxplQV7ebez9lQPVGrm0o5Nl/b27teFTTlu4+6jDErcq0O61wMgwMGTO7YchJoC++SPlu+Zo4Z3PpW3DqGM5+o56HCUGHlMEfBuYEFysHChRKShiVdfbJh8agCXH7QIsEZLmgjnFJfQa0OfVN/KXuC485iPwWMh2RN88lPnLC0fTkCyXkJ/YVdkySjLQazwUuq4bzJkn5HyiENLN6mOeZpfhtQjc9F5xrPdCmz38LkJxDyfyM8FbuO+Q7qoOWi4B+zHmcjSJVqR0lE5zYM7xME7KEu4RlHlC1pf6xtGUH60ZaMsJOnzy06cCbhbHRE6w5ElCTTETFDNtVQWupiHsbRqpq/OHx7yRePGPu6aFNa7zSFe9gyeBfb8p+tjx8WOa7lKOMt47e17L8VlfWl+CUaj8XAS301U8yoD4Z8HFraIp88zNNDEDSWV4WouYaHgeIrjaWxdn5LG4ehHjI9mlnePPuLYnlQLPLU3Lurn79WJBZKhZU0EMU9mIzsofl5EMYPBaddq/0kE+JT8Z79Yl4ZSGVLTU959PmwtFuCUzyBPkRKbEYvKCXi6kNXuTS6yBmGoDXMUBk6wJgS6ACStQ3CIhcTQOaDgHJTIOI0ffh1OCUOEx+RfZksVuE9LhRK3V+XVZJRDtSh8hwTQKAhDACEQ/wkU821KRXe4P0CerCHyTxWnOvt/cPdxGPPSL1/L6NZoKpXmbYAejj8SfYKErhs+vbrbZBXy1olz4nmnp/vr5djQjNpDAx7OGEzXMyiik2rFzPAlMAw7UXXollTKQW/UsISq5tphMP173Hj+Fwty5AoR26Fbioe6B1+eocH3rsSBADbG6ijtEwhHpWsnJXzMelbYhAxI2s4XDgrzgb9fBKNMu5fAMpq4ODvze7gogLFehcziPAclW2aMTL2Zm/KWRXFGyARo2dQrTA78EhkEHUyYg9EDy4coiVqWvm6CCk8Hy97uVeoF/Q7AS7rdzesOy67VUsUhYmY4v9U/szZ4xS2A5U1BX5sD5eeTO6OrCSoF+78iN9wx9z6OByLe7MlkjdMjs/r5ltWDhxOiAoQWPgeHATp4vsCj1ivgDox+K/fVX3plam/eXT8nh+ulnbLVsTUk8z9oeuT/qk7ivla2itShdbfSYnhqBcBwAPzBTGA0STWgMYBHSgjlHEE21AS8T35NE1H/Ig16G4M7Uk9MLGWl0Hlt34Jq1ZUyagUcrYz4dHNguzg+8X9Wdpk3oXWl0SKPBiQh0iPu6OZ5MSoze4V/Kiky/iFY9Vlmf2fhQ3eIMXd9uhFkdvqmqxZdMBaPB+aCK4BBxh4ZQV/k7/Kc8mfyxVX7uBsjHm2Gz0vR17WNADHDy+JL5JkIMGU/NjZG83tzPy3crqsQWOPYLW+CqCoOKnTztHsxaVx8eTXfsXnEqMaa9Kealbk6NvKDcv4HlJvcXADFZDwPcnDReQsZyfUSxOtq7BrxwqZk7nMBqcd/xFzAMTAYffNxVLwguNJGNW2yyWb5LOI9+K2bDL76TvxiR4GooQpRptRFFSazyjtXsCbo+zy1P3lSpelUF/S57L3UnpEr5QXyEtMuDlySbszuq9qZ94FT1/gfiRU+I7OB4PNcppFNd0xOjhzUR7kURFeSODR2SE5vq5Hwmz37V9zJhkAlxOfg6X6agTfdj2K1/mvIS1J5XaOZ2zDUUiAVKaNPgTR2ZX4VwYzjjfiAexC39aRLjviawIRYbR54pkHnmN5cxz9sJkngs+IOV5cxpHzhh49CYDSv/pawCxSlKc1OGKLMmSkoNpBjFYFNXpdVzCnT9TmxrZDiGUAvpcnkkiOVRCJUtG4RIb+UJGk4t1POpKFc9/lYLnG9UJBB53ABf56YpOvxw9mti+qY99vW66YTqHeiS6/V8SVNIKVjJGHUJvCh/8e+9j0dXkCuPcSWq72mfdqzYrFFMCD6Mm7Atn9d9yTYbv2vHFhbw6XgIt+d1DiZ0Or1EFQVAvkAjUEHBwLi0CF0LqbmOiWJsNhWkwk+mONEduT5soSOPabFkety2+mnNzaR+OYEI61/9wT5vSqsw+5tp0N1U5jKbnw8SSXVskrJG/snHxafnnpnFlnOcLXCX6wssITHcdHQFdDJ/z4Yu5e6ONUbyLQ9E0Nu9xttEebhJdlykLbPYQs7HrURx2WIXD5EvkDr1DQbtE5iOsasCmnwyZo4h8xW7RPVl7TLHB7CRyuS+Xu4z+efTiFxQRSC1yrnlzSzwlO6Vh1cF7ebQpQRXKShRqbznYHzDsEwvbNxGkiYQKjP0nGuHRg/hT9YGV9pxnkwxwlhSIDiwUUnaAJ9qNsV2JtwSl7TeZz1+MDI6/9VnXNGRg8AW9Zqv9duHu9meMl5yy75/TDeGcvVzdXxNUnPnBIeSjLYq9bBkrGewYazHQ/L0SoyMHh9/ibOpl6Wh9xn9LH+Oy+rfYtdtElrc6w2kZZrrXr+5WXRn7vYZZt2KBTtD29KX6D6PIaX6IC5t4cbo79l7R1+eiXlU/l1379bybPXk7ubsRKQWNzD0olGc8jGGdF6/gsEG0ThU6Vf4Vkn8RgJyWhoZlw8z8/j8aqRZ9ojdlNNIIyG32M9JVV4RVrYW7WG2qPbjD57GUuMp/Rgi7ze19lXlJ63LkhfNiozZjtiKthdeTQ73PfKjCedL3pnMIsi/FXqZsfZcjcZLF0g0+tHcuMArIjP6I/0XIW63laLMomW6KGcTXgvgacVnm38POP5o0EnBReVIVUgC6wTLQmes5gsIlbjcKmnhh/qgPC3weYM96jkvqhxtcQceVap2dSC0YBW1pPt+7ExP4kJIeKJipjd4OEUX2agyHvWWe4zjUlHvbO1z7aJOrkULAfyB5jGaMhvtRGHaHTpML9S0qHf5Bqb0GnXd6ZW0ZU3Tb2tBFp/TjGqQfkGWt+sALeNmEtJ5LNvszJzpjPhGJt4TXCe6eQM1c9oTntxJHEl4pTapFigGwJ8YsJCMkkvQt5tmam2wwmWPeTT5bnEJOqnv4ulRYv+WCUDJJ6EgfYCcAX5SHCNaB2/LJH9cgazrP5uN7bsnCbnp3QMG88ilU1jlZ35XCTgtXUL52SuTcjeZn+zuy/P0XIOZx8SSKxk6uuzJqvlvRmwvbqBtHpqu3euyrFxesgz44Wc99fJslsyjNbSfNuuC6hgHXO4fjeJ1Puuq3gC0Iu8WHoR1wnxIyjnIDKK0NrApuddspjHbGUtwYOJrsrfNH8oZPWWHudrAd8YHweJNn4DAKF6T1KGjmyenamPu4mkywnZMxcO3hVn1ZGEZn9praw7+kF9YDjAppammG6TCgj3Yu5KAI3RTe7XQKxk64Bjm4Dt/vsay/UqtEK+yqCtjM34i9yP1uJXxpsDhkk8T66zNwyXHf3BaDT+xwxj141/bhpsUGSmGaCAWSvxfdPWkq+mauefAn9HsI+ZIZtY1Zbwulo8UeGavV2+7YYbkqxB93XcZJu3tHmKrglxoTWe5IkuZF+kUEljDxseRFXnZr4dpVRmoKloxIF5IisnpiG8q11wnlWNq12sp0fKe/RGpfY3l4wbyHRlZQj8sO6YuxB4+13y6SE/lRgHrpFaksirkACWvHI6HtcQTnoZUOU783sBNNXxJqkqEaz0+x8qOqSn13Nmihwrew/yyby315oqUxG+m6cONFXK8UYkfR9rqXVQpziNZdGs+mYqRl8ErRWzZKroX3CTwRnYLjcFcYqR4VSRGyA3yT015cldHA54bJWS5hdR29dwm4pu5PxY27Kjh+eF8EE3HXJbaxH6POovX//uEWxrGZe4v+pN0fteh3xyifegGkkbAgnhRLU0+9EpXlQFQSYh6jh1CsnbLnzWOkJ6xqf3LwCJq+pNQjw1qC0wKjlkpjdz7sAfYGCf3e91xoM+4VbyPEKm5mzrm+ps/Sib8AKhnK7JX5mFUvuLh+9YJoixJXKGcwqiN5fBf3z9sPBN8X3pqFxP59i0ONlUBrQMWq241Tu3lOmcEdMSQYICEaYgAT0zvQDDeMkAzOCGEcFmVBrspE/g8YgrUDcIn820vIgmu4BTeKF8Z5j9DlALAtz2Enhv3jL5wmpAgrpsq92CemBw4y8XoLzREzOXArEuSGLC+vVRjFTZ6eqoFHz9+o3VpKtvJ6vsf5b/QT76vkN0yXjEQPY2bPrKzPzjxaXtj5d3+jjrSZAPb17s7/vplSmDk+ApLo7oTu1ie2KoGhDGMWkhoBEKhqlIfA3Wmp8Pz5uKcz5aXwx68FXKX3994jRCeu+GIhsCtxHA/s454Vy7dD9+LPRLZDxXGjx40R7Qsvw/Xl9iEinB+xlL81T1UQqXHpVm8uW709i2atymWqr0SF3/RgabbkgDv85vuEwVv3JsvayrCWpPeW9H/uECg19LvAgjyYzNwdzj76M8u9Zs0eq6Lnd/nIZPPXt4Pq63Z+QJauMr8WOCyj4fekfRhBixSRBVz7HKGZSyMLMVgrVNr5QPG9/uj1ExwDl7iVIcpq1HXoBByCieNrO/nnJunSwZOGVwB21l5l5bfKuY7CL3IkJmCbFA+B9WE8/w8iKrffgIRM5eHgzP0pQX4+fPdj6SV9+a1S9af0N81LdkJF77dMhYNL+ErdCjogAqIj/1r+5KfyyPNnG6svy8Rm/M32ZlLDNEi+D5s10NgdtemtnJrgppQzzepU5jIBWkbEgiYkftlKHpmP34sCO17uX2XaRTNOe66i0F12c2pcvp1IpQLhCdZRamPv+ZVEIObftT+WqbXR5juJ56bTVqI4n2pVgZPtEgzjRvt6LtTUNNX2uCR4CsuMge1IOB3qldH9n8V40sOjmrbQ2rsh38GdCbkZH2GRE7dtPzdcpL6uD8N6+IEPwvndQqbji8osgS8h5gm7ZAIyugwLD0IMOyVumeK8wfhTjiWZV4bSQ58V3N1sm0jed46hKfjU8S9Yp8RTZtWv+wft8w9/w409bVIJrgI846Jbd8va+V9vl91aGQvWX/nIF/5Ktm3+GvEjfaLlNEMPuAQMG1FpnLy1PwweMhKXhS6z+YkVV5oQfeZ8Zsfx/rbiwqln0R96n95N392S/ME3rja4wlqR2VERc8M38NtzQMA1hAvG2U11TS0goyPW4VL9vWbM7Ff8PtEOg8dLEWfgrwVuCT9v6uRrVsaaBFcMc+4g9R5zTM84tCGyKnbWMNkIWd7IKnGTyc94Vvvimrc6Ki46FDe7HhkuKsl3BiZlXuRt6FljFBlg2Cb2Oh5gToLMFcGH9CkEhFUKJx6gMeyUkGUy81rd99lXpu2amWS6nrhlpARzbVn7TMli09OHzSaep5Xpo5nxVziknoo0nLZzUpXwjVGaZFW0JEost3hynlzN37bpSBoby2yfY27NEIq7i4s36GkC4RlFNZnVfopnX6205aTUd8y2pnfOcn3W6vQ/q0uGBZYS61xeE1S43RXN7UVzNx4SudXuFHFB7dKJ3ZQbMJoUSkmJYwC2I3jMYN43NnwOvcNXnzua2t4SMuKct6h7/cn9pgfAlQVgKnafKyIXWVAhV/06QNE1N9KwDGf26mBZXKZ0XxRgui6YttBdntoZz+JUAYUqmKJt1bUEGnBPHjcufSys2YJg4+pOAfnhesypNR6dEDEXWuu4aPm3UfMhxtAYPHLOEG3hWbDpxRLyWOEW3MVC4N47riYeNw+JFMfDUniUsk5imOMpwXFVbT313fBp+ZOcxJ0ACqcSJMDvibar50XIdQ0nlnS0GWTdwcy69YZrTuLxNvnD2bQyJFTe+0yy56ueS5H9KshPq/L3CzjWqmRttkJjjrtq6UwBSPhyEmFAqcw//9DjB4jJWHTCLrpV9Dz2B9n4AeFr8jP3iUg0DWl7c7trZCFIKtzsoJnOTodXkWePvkD8D2BfKHmXU5n6rx3i9C7uIOz9/eZk96Vm7l7+TddTqTpZT+E+s3yjV5/AbZq+Np1cZ+RkTl6bIvlxbhVA3IkSeKt3Jj9We3Wxe2OzX5k9SmDBTKHgD63ibaVbKe9bOv7vo0rFyKtv4wTYa8g2ou4ku2Kg+r8w9rH8IFKVOSkO5Ayrfpg5t4G6zL63gw1x0JJ32YAzJ3O68ca4exOq92q++F1XGM3x2FMkI9QX4ZpjmLdmv8RerF31xoXiV771wsN3nKEQ/sPvupG5xVAJ+RWdVw5UrTfpSmEZ5dSFdL26SbfQlTpMuXSRTUsFpmywxZBuj6CIiMUYim3k12PFrgsQjan9m7CfUhXvZ9swm2qZo7Kbs921VBbHuMoDaV5t4YMSSEU+UYYrZv4qRa6weRa3z/AhHmSiL2fTSFwayAkP/+oRCothIiUJBB6dYVrZo4zVDmWvVRc3kTaNPjdjerNKEwttXA2id7SRV/7yR3QsT0Bp7fxV0McCl9C2dEvtty7SwF7xRq+nG9QeipaXsBnF+15Z2SLx1rKydwv02Ijd+tCaIp2lse2XoarGGhNU86/cOgzUc+gLJhm9AXOubZBHPm6j7jl4wwljO1gQdLzqlH50viLmuPV4XtCxPG3lzcbKneIHcEHb4etfM+hJIUCddszjrajJg32DfD5J/KPBlfsoq77pCoGqzYoR6bNGza2oUTu+wAL27iUSLHTt2MZXgo5tBvAfO0t2pJCSqzXzbC5mi3RLyAki4CCNuXiEDBKk5phRVkbH/i/17KW4uRu5jAXWPcK3T3PTPaY6p748xzHXFzq3YFDt3sosRJLtW3J+E40VGbaHZYtIVvS02vmmCYi5sJcbLZkf2WhfRWXvtdu7Xq1JpXYCLIv3iEM+0dfRRvzhywuNtmRT38A9BOOsq3qzJMCRqGFdGtw7x5D50WQbWCzAxzVLc0Me34ixwGICqaogp4fNZ4qTAWwjgCMQXE/dC9OYXYLdbbrt99fQ4THLNL7p/MXNQHk7CnJNx6b+OTmzyca7/yu5EglpNnMGFvKIDgWWL4lzUxDfvcSlz8PsCGH3Vwhm2Otv+ZIiBphv6rdzZH0jZW9z970X+zXZHTO/t2Da1tp/j2KVADbcPkaYQOxbrDAX3kosRJs7ihHGoVBpHYyutG9OdOo5hljMo7eaZrdY6ULb9zuqCvnj2ZQxnp5E2W4ZxdDaOpJVzGdPS/kzCP8jEP/lnzkYqPr/yhBfsLFT/uCSyVDye9Pidpyo9JNfrCsYHVM+SLJ96ObCOfRAJvjpFDy6H3i+b4ERw9wgFGfMuvq/FSnYuLGCSG8e3f0+ypc3jL8Uqsq7zzWBhEAVaz2xOI44zz+JmIcOv6XJEwvWhn7rIFjh6PdHP6tm4jw/aa5iAlViVM0ph74n6H1rJKhQadCYweeSdcuFYbbSMMR9f9NIAZVvk/oIrdRijdQosERewOOzyUCkjNJT/QiJt5Huuf4MtmgiJ3SgaNro7MJctHoGuLQ9X5XEpOBxmnMl/iaFa/xFKwUio0S/ENT8UQVgRXBYlvBGEPW6QiaiwYC46UqgCzueQCbiRHBQHlLhtJzuU2ls6L6RuLFeKBvOkTuCVmf+CDnThkHYydYUCrMqSPZeBtStEfw4ifKF3WxCAaYwrXOdL5l3VAcKcsmRdgt6smMOCwdWDvJmuUmgWeXe5LEOQ6+p3CF1NG4AFQzpWkLZsNrXTu7vUr//DaPVs1U9rJumktqs+m5ZAY1Tsery3lViKtsr/GWdtrSAQXyKhmIUhzEoOMMdVxuhY6SuUmsYpeY6zDp7CYQ7zBDbbyfuddaKNfPD1TI+rFbUSiBni2qs4QuNhe4oAWHQ30MP3W6tPs3wyqte1SqHqTxNx6KU+udcPuL1uXxqeYl55uaChP5j0VZIzDs1obGG4JsHFgivi6x8VsuxmDJbNb7LbqWxvzxyF/U4A12wJ3ulc6z6o5wgKypkIMSa29V4U5ImLS8UcK9PSOJhpseKvgneQdYD4mv2NwymV9iMa/V1ifeONYnulbqasiNSuWWPvZyt3n/lxv3am8THJ9pFX5GmNxXGpUrLAU26ozAuVxoP694jr2N132n0s+lTVJkNKlv7Kq2bRwugGL5m5nTirtk96Zp5T6Sn4Dm5OcHXTvq5/rZak34zCcbz/SwW8GrwuLBJSNqx0QrqMdi2fnjgffVOAr6vHPHbdxxZYtSEgdhvgN5uBdBnye3v6ZPJhXgRTS6VKlh2KVHCMhtlhaH8m2LC/T9Xc+5NEUH879o5dEvTS/b0qhenUYpc5V9STl3jxtc4lZadFmHe1EV5ZMukbooWw38wBC6NAznR53smZULuEpoQukBF6Fme6FvzlpKRMziurCAkHGm52Z99PiswW7197CHdggIOihztpiRTOjqh29TVz5WQIEGb6LBoB1Jyn0baONPV4P4tvzAv48VXVgBhxP2g/VK++t7QwxCPPvi+RJhnVAtkR6HLI6XR+1QPX/8R88/i1WaPYxMWQFCiESLr0lqv1u4czbq2Mfe1mRM9p6l9gmc+b6u0r6GZBlcxb74zvkoGmkocUe+mpLwnlaiXT2K5E+IEf5mhCeeFCc092eScjG/Bl6k9f9jc/p6mwjVpRUWeGBT7HpQbpzIZpDAX1ZRJz49oB3oIh4RSVKqoBWll3J111+Hw1fznreU196eeeebO+GYpenbHI8at1RcYWMGD/7k7id2hWx8u4IifsW+QqyZnmS35yZB25bD5Jc0M6x3NxtBTsWtZ0U5938TWNYbdQayzALd//HhgkzRdgGj60vyRg2FFD05UrS92eEgdVC9K+aeXIsWTWp/Jg6ZbybRySXguBYGlHX1549+x+DrzrQf7TJBPbnxoO8LTPCL5I706ZgW3Wqq5Y9HdL5qNsZ0G6/zh+69SmYxxOOWN4ecu7uP6XcbDzmsWNhf1ZB8p3uomQiq5UDghHqNEIkTDgM4Z1zkKxyARxWSXa72SSbmoGyEFsAKaQgY2jHBD97MQxke6MGYoOVSFZAhUuUcmgSQsbCUyuPLVj+p+l0WEP7aKmGPNWxsCh7UolrCoI88ADB/giF9pElCCI6c+jS4Tfh0qaQeHVt8i3mnzyIu00QO4b/3Bq1cqeTqFv3A1c3kMhl3m9BFfCId8aZIukVKO5Hzu6MAfcwCasScQiQClMN9y/uEJM8Rq7eIGw4T4QNJP4vYpK/xrWLY7SjJ+k85c1rzCoKyrZfSz1x7eD6e8V7yldi9zi0d/+i2tHWszDs+hXhLa2p3ESAuVmVm1pjiTyTitnEDJAaT4Zvb2T/Z0dyQN1fzI72D/0IjB64HWXxpuTeqV9sYfDl7wsvEiIajPefmxcgWlzI8ehlgXgIPGugB5OzmPl+46vu9/oYfss80hMoIsi0ohgiEacB/JMk7UMs2M8prHkvEj8I+4/v3OTL9sOko9nZs+x+bVFnBz7rraGM5EgeZq0OHZtNwqUKiUPUXEFE6JIRQS47gmlevZlYZf1HXawVcO9z76VT9q35REWTGMwmLcvfnPT3jNZAqVNFNYtLAlBmFQjODigjCc8npxM38vrUXn/Ez03wjf6t7Id4ooJVrQEiP5AxscZQ7Kj/YBhx5SmUTq7ghvP59rFPu/LG6LA1jzJ35UcGXgAwI0WiQITCzo+25EafCIKgo7mr8ybl6gjZWYBPugr8n67S1ZTRJE4JY3Q1rnZFdlyN8xL/zOUvz24+cLaoZJ6X+GrVif6/6VPpI/9eBVnIs7lT/fIe6ulr3aJFX5xw/XF0ae/rnvXT4AnyFLQY5Sf7V4Q7vp0P237qlipEXvcuH7Ynhp4JA8MuS5l/P/xq8rYfpIOxHOwjljTLCFs7FFvfqImhLoUFR2tSRwbh/GPVg8SMxalohFGm0SPCBE5f3vgBL/9zIoIM2+lPcnro2VcMB9Sjk1pY/RpILydT0osUuy2yskNli6mN6z1FIxfYCQm9P76SVI46AEF/AXZuGMyiL/l+kL8e8wjAGmi/zCwiXLKh5UH+vCi1+UKU6C5qyPLGK3ScSZ5oHllpRvw+lZ/DyApLNTrK4RLdvZV9C+Lrosfve9/Wr89//3Dqmoz0G8HHoOyjjpe/4IurVZCPc98Yty/Yi0lk5iGJMkM246YiXotfaU34lRxwkeV9dpCntQFGy8W/JpVh05hzBoeWULlnWlzBskP2YUR1XY8XRdt/tHIH6ThCccIT2o0SnOxTgnXZeytxlfFwLxatH2Z43wSjqRYcwv3b9dXdXcyKOzXduF/1oCPxZOEBqdwszirZhVFSp2926z4TBVoVoxK8k6nrInmvYsaozJFrrQY4YxfCOx/2v6bA1y9TdwC1bCwL7X2r1QQ83ARi1OTuMTnF4JUztBKcJzj4bMRafOYezIkmee7lgTzL00xrKzDrjYpufiXOWQCyBAGzQx69Bhdhy5CXSQeqQHUzPdqbz0CF0s9qYdfHqEKZaLguffb9Sf2sH9I+2BFkCeJAKE/GYWgcvuBRkIj06K9z6pytrliOAXysNGzM/5Hrfn5NDHd2Pth+XkzQUf51GrW8D+vGFywYJ4RSqsVXYQV+NRr3y8S+pZ+jEEp4EVJgEdU5NDA9DCFZ4a1+msvYH4osRFNiQlNUsEmnkbjO0OHHGpVR2ecbQMH/5nn1yVgvbTA9X/yKKIUHudz9j1pr5AuywS+KHlPyEQ/VauKfXjgFZ27ZyF+2Vq5eJAjQlAM0tO+Pg4NKcaL35iV+yu2eExP/pyH1zAfTD66NIdSTyB3kZwbyGsYt356RN1ZTtk3J0dwUQm6A41HdxE/5zRL6eDlq+WFUiqKLgyKssLxFCM7NMlRV7W2MU4iqPEfxVpHldNX7NOO9tQWv72lEHyAWu3aVu8x6JLl6/LqNDYVRsGaY+f/N0/jbgVgynDstxBGIXJfqc/9/PQXGkURXHK5HPt+2DMHSb3Ii9x+dtr+klnLIXTp6bjDcvB5jhdmnPVk0Ha60fjqrcS12BlfBisadQyJOHm+i1EpXnUggUOAuwQSPzj5W9OraqTVbTf2XyNUQRVcrNUwEIWWW66OUF0XehEIRShUJ/LHzvDl6xTN6cJyx+eEqw+r63YPiocn7wE88YpqXPv2yv3aKllBXEBqhiQ4bOQEwUcvaub8HQr/NLv+0ZukWymhRHWOQ2aNOOJp2EaXRbqnfq11kGSMCWCZg8xpQk9sfGaMmiEUnswCSQR498sCTG8gyFjArkDuGLV2Dl2rhilwoIt6QfO4p6NxzoJLlwfoMQt9vRfSHFW3Oh0Z1J2ETj6RZj3HBl3NASwe9CkV0D7pZ936BEwSAVkQLg6JP3N/b0u1PjWYT1vzhguY1AlPToUfGnjH3wK7eROXWBtOXZ3Ibt+bSihp6hLzwMQJTNLDnSkE8t/nkG52EqZyESh/4rSpDedxWfUykRZKr+xRbBwqyV32lTTGKNH3pwYNdVPSWfQTKnJUeN8rAUNbi2MGZPyzKr+5/PEGxnx09rTqoFZShlN9vX3tQmaqNALKRELyzwdsKdNTSjlWO/MiU6HDcp47cxnUvZoB0kjGFm1Ok9HSQMYmOF4XfPmrMh0G3q7LJrp3PEcQb2zbT1eiBW0fVss9pWeNq7wnKyJxZ3VnQZIZ29211q7jgR27c6rGbns/HEATMnKUoAgCpLc507b+4j3CnXIQuH/itPkjzXiM4Gp7WWp/PoWoawjztKtk3yfu1SPjpTTiJobQxk0Ijp6l+PuiAA3wNczxcRkTIBWtla5yNrqt69xHR13Ijoj/8Hi0LWMDBynapAVTFqiAOuRRs2ZImI5vbwUICdwVbAz02hCshb4zJs6GH4qw857xpjZB4wkGr2E/FU40HdBjn5bLU8ugVQ266uBqQ0E0v6/aH/be1k2xjDbUDJiV3FSP5/wSz/rgDtoHAvIAHW1S3uL7tQ6UcWtw2ruztFvRsUa4dE0+0Dr28U+6q29CXVnnS83pJX2TC8LoYV2AwHg1IFDI6VXHJKJ5wEFkUiN9328UC3ywkKJFfJxeARVxaSFWLGgpSb5hlOtBoICK7kE1YS/rMePEGRs3V4YKcVR5tVrhZJfWI6/GUbdWXYIKhSf0WZRMiUDViuBoUlJQmHwGwnt+YgKEv4cp+sEr8+0qqGA4ziu5/EuZNFjFIP4SXEd6ijvu5IVfgrUQAOas4+zDUqB5IzZ8cXQyN+RUWPNAtAzWAzXTAj7OKhz9BztqKlOrk+MihORZzHhjiwwC9vXdC/sLsbvWD9t4tdkYfa0Hm2TKVNs+YtcZhGxyQwQaJs3T/L+ltDGGaFiSh3BBAi+FsRwNoQLUuv4yWUgcF/+pCn4krdz99+izaWuj+Du0gFtQvmcnfuvOz8YwmxMSN1wW3h8dsQMkM3b7HRJlVaGKW1xyi8sjdJA2k4TOyC2LYJpE340JZ2O92gwNdKWZVP5z5cWkJ3fvjk85ATkIKMuD1M+qphTqa0eQPDOjixI+2NKc2uye4orL/OkTW6GySQpkySWXDrmYf4/8lyqJ2b+OLI6U93+s6I+8M9i/Vnv9idllZ5/bneybIoJmrTKRFfbOfn8WrYjaS4If2fs1h+DNuRQdlTRVlAWTNM3Arvyk7r5mF/6SQec2bW2eDQZ64qtJgEZwK52SaH7Ob4DNbp1WMndPvKtgMSf3eD2sva0CHa2F7v2SFRdMNW8BkQQjFL2IZ8kIXORqpatxbXtBpckJarJZTKbClIgys8Sk/LgAMMmn7BGIftvWeVnrclkF7cabviUbkkMG9F0Pr0XevhHfYG/aJTuAp+cDPJMmSO5D7dw13JqLKQOhS2xX2uEi3GF/YdfiuHu9Ye7ESRphpW+vQ7alL50y3yh0wVwB6lEu6KKMjBD9QKUjMs4K4l5Z+16BJi4J+D7tZDoUuDmVSmUr2BgyfoRzfdnFXxjljZmZbVPBZf8iqGwSMNxVjNYhINFY07nPmA5v8NN9C5EHiJNDHEDEOHjOueDKSu5kpwiB7fYYggO+Nphu8EzYhjuV/xMGZ4V0OWg0ekZ6bviUbU1ZVffkaBt6UcS+xKOuBHurigjtjAMaBtxbAFPjKSBF5zy9t8JHVn4NoQV7D6Ojh2t7uOicFmnE4kPPc8GMM8hBg+/VLfDDtKOEmvS5uHC35Ky4GUmzb8Sk8O0/31n0ejjyY6gBeCib4HumfoMU8qi0zJ+u5bUnzfrnsWUxKLIhjFDzZrI8mVpkHI0FzA8C8WOVT8PZqQDdgjndjSHKE3sDzKYf9YZ43sjAeGmeE8ru7CLKKYbHOPesRMvJogF348KxWxVSfWoEbqP8iFyZ5/gs813M/Hv9Ji1pQOw5pNoQM6EoOyEotb/PYyuNhNd5c71gkywTHrOUvOG2wv/alsAlsqlfsLVWETxrAw7VfowxBSMMo0uS09LPm6KdUwpguska4ytZAFbSTkRtirCLtFRwm6km6gd0gMDAi6+y/0VZi33BQEZkT7SCjfQSOJVpVJgmSNrSARuoVHEjwIoS6lLQQLHYJRp1vl++vgmLyHh6dy1bMkrgq1M6fyxn4MBZ7Q2DsI4lzmkij+LW8W5osploDAx87X6gMjfmyFK1FOP3+jBEZ4Du4qyVTKW2BS8xSNN7ts0LPgQbo0ttQuC5ebft9KcDsUyWE6Ga3fIgPYLJfT+TsF7Im7ifkOCFIovK/CgAiC4rSE93TuR7NF8zsfS1Dq0DMaHy+cdH4udrS6hfyo/uQJLe4S5mLtULItjdrziYSwjnWdCTb3VEoJ+npnEdcNq/VcBxMziGzqY5XfRZLxWRfjekoiNa5/mKV66oZ0kaIwxA6bne6ZvySeY4+199Fwi2G0loNfMns6x3rT0aCgu7GppYvhYHcnQMYtY+jLN8aZ0bHOY9Wi1vI4j5/UmhmMj36MGMrRIyy+XPLW8Z2t6FtOGHw3D9d/fYAYAUQ/An79sEArgVR0VcrzW+azDb85/6dJqDtvGjhrc4p9HrDjHmN1OM4eJyiFmGK9cRDQSI7I7cEghhAXqykT0qw7XFeQb4p5zcEKGtxDQPopZMwvw4aMCDIPp8TbgKsX1BNEb3uKqB9WGjiNGFJd6S4wf1z5MJRnFcXmZMWnAOb+j/4r/GIseTcqe8Z+ThD0GjGt5Oi4/t1pICJiD889KKcCgyv55OqMmF/RkwWQ+TubkINFpI/z5aQLyMQalAddXFBPs3sEz7LeCTLwzKr2IpKf6EF79A1ygbVKIDxiD88+ScpNFrzsCyOY21BOHiXyMzM5BCgGHd4HFTlJG0gIaLSvousCcpIeIJoWj+LI3mqO7Y6iNRwBhjYXxC7BhHPbV4OGqsjFnQuGiBEQT1G5fyuQRBtO58TEfpKKQYigRetbA0woBIMFV7d1tAonhlSiOpM/LDWmxZKotwmNjnfsntbXtBxSzvnUVXe23oxxE50+IBA7xNTwbJ3ZL5gAGi6h/AIfYG80jzrk3psvuWKWueHvmBZvaqxL/qlw+y1oUHxnhrr1AXfdy9hOulfBXNELXO3u+exkgf4eq57H/zCR/c63MYRyGntNRg297zcamW35+lby75mbf2c0IxZhZ+MRynDsBMZEyyCSbp2soks/7hy4J2WIGWVw733sXAZIKbEgjKk3raiVnpMPbsRxFYAqnUJg3yO7+h35LjmsfK/16Wskh3VdwbRal/ruC/vWgK8KjM605mWxpVn/sniZLHdlb4M36Hn95TzyQg1inctqM2bHYwa9oo5eRGpHgoyk+sx6fTp21tQNCO64R77XWUqPiD1Emp3Vb72niTnQpBo4ocAEPQ5irailnZMNXiyGMwzi0ArOwyI0x5XmbWtYngfApIg4jMHL2mIFVrZPCVelGQwZXHE03Pr7HQEEZwRurheJm1FK/jEilrA4hMk5QoJm+F88IAyEro61QkfaiWDu115SVgL7ckqe2IqXI3CnqRnwZWIYvJ5fjB2n9/rxKZsuVpVNjdvywe2QdtxFG2k6r3lh20x0A0BQZsCZkwhoS68Qca2KPZA4HXJe6kPiNMcOa3PvSdCeDUl56002hLhf6/jqQ6ew29tFRrhA9W6Z7KZt6Njzm8nXhGsV7oZUCuXyaj8Ha+Vv2Qi+7I+6XdXcY+tXebmFw5/O+MLTtXBWqjzbz6mucn/r5xcIpgmNfqFJdP5tXiy2dpPC+eckz5acbk1rOmje+poqLxCBPsv7DFaz/wsCq316UKiuWA2MwMvaPFR23M/KwPcjtLOFuzaCLswg1DVfrhWYaAfpVMzAjBCEclCtlNo4dS8zFAEdVBijikO15/5KqS2ut024Q03bchqn9EPqoHPn3mAXYyHAzpTE0jhkla+3Mo95Wguf7eZpSSoEdGH8fC6cO0tCDoD9hN+ylWUGINRGu42SaCkMxeqOFHkhBLTA0MvhNPA+n/j0Wjv3lhvD19jEQXnanFkkKgvpm5R//aB81wQ9BIpiZ1SDeaHTLq0QVboPvUTWuElWGtn0i3oOMT3TQTPN83914om+Lu7Bnhm8b98XpacqAdzvJP+cVu+PoGzAh0cPLvmatXC+w4kgTn/T4+s309Nl9I5RJ9Jm3QZI972iWCBlFysfoIAt3+Xi/o08h42mXB4RmhqxLDZs4l44aDLJrP+XZvpqfgICtI/G3VEqMrXPizhTKHlse4cxN9UJw7vD4MyoVxtY1DreUix2Lcr1e/REDbpuJRg+CM6QWjB6bv/mLYuo9xY5cMSPAYna9ao3+A/fgCnA0LUP4eoxEJtHf+r0+GQur/z5n5Lt6wIW7rpJrTY5zfc1j6rMyDUoHKYVIqGQSsxQnK3mTS7I2a/KPB6D7cZ3tlG0iSkVOQTA3i9/MEG3Sgmx+y1q8QvmbHcx1KhVgndOVWiC4/DAzb3L2WptpsKsVTjErLkuIeTf26MjbAVs090/0uimZ7duU0aG+r8j7ps3saQg4tiDSFaDbNvjfdlpOFVw1XHQgfQsZ2dLnHj3XJpHQTHAF4+b4nwwTsqNTdn0ziAzyxAQqGHMSMfy77cgxHfdOSpiWWDU/xcbt9g9+NRbwNo9/gSrdgHJ1uHfcjTf1Rb2Z6bpGjttZjgr3QhRU1C52KBUtWeR323TItyTF67VXqepNMWWeU5s8X+72zYLhkfxYISD782NpSevLRJujS8VIWVYOEBQHmg7BEMrAjZwZBWAAhRfU5VMmCJSvHuKwEFXHydagA5WyuYCqIL6VuUh0SOXY5HwJl94HhNdRmvV+dxCJyP4Nb80cOWs2mzwcBWGNOpbh7af80YnvbusbTYRn5f9PurvV6Q0GKQtQx+oNSy1HtNvHqAdWjfsGEVa09OpwV2Q3JgLlPg2MxatlazBruzrmxw90W/ZX6oZzitWwCThxDkcfAXus36x0fetkk0eD7RmPzYPA02dSbfLfmtKMBoKLRgP8+RMSU5rK+biB1xy/2LHUe1qfV2Q1D/iNT/aV8MuwSggMI6sNCVeib/eIEx/w7TA3WDalRPPQO2KRTaxzlCb1Dm3eeh8RvG/CG9+eDkSShvndOpQsYW/WblbIvgTJFQL5AzcdxjZPEtYZveWrl39Ui7UHq/g50eE0WiNGyS+HziecbdY8bjZcvD+rIZRJUB+w6HGPk29OpcuoqsI6Mu7BLl4XHBqdYI6vEIxeIn06wbFvystueg4zVcP4736/OB6rOe1sGJDHk7Lz5xlz8xBVW+JBwfwfyJ8hnVAeStvdftyRLQYhyW/RKBU8b1j2f1hUQoO0VZs27rwN3SnAZcEP/aICFcmLtMG2iwQeoUTOZbr3fgEPN5lQiX4tqdAriy/ntPULoxosjAnASBV7HO0ZOV7VTGhS2qCYv078Z9VylNf1zQs3T/+FO/GTaqUHVpYaAxWy39Q8NqkJlka0cufuP81PFtB4Bu7Y856YFeNVDsrbjSXgokEbQ/UTGa5hdcSY1xY7rWahNDpB+XMSGqDnn1AdPN0ud/mrCzwZCMhpf7VKtLckR+cCWYIkzIb3674RY1C83CkZQiE12qF00OlgyZUOMH/LmKBmnu8iUoyQ997GXxnwlgGug4IETrgbLnxcLwfKkKYMe9PQeG8foelcAkU/LkfXHkj1ZpY3WiMkMINhqD4WnAangXHQykmud4nE+V9x1Fw0+ds7JVwPqyKPKyzX4SENMEdqU+/wBKVMCUo4KlFNSIhvPZ5+ceMceKfFtZ4oJa39+fh3bWx12sWlt0DsRxX+Clqui43L3fSaV30QQb62vclTd4KqWBE4WyWR1yglEmXEi512vjk62sBJoiPBtIuNpiPL2oOqeegCMRcgC002iNGAbrKDxZBI4ISMb765awSMIJRSdITNvaGq1XFWieHfnn2luuBx1SiXTbDoPgKV3V5BncBoODAGAQ8nacEeEGS9f21NA0Q4KlIMMIDTPI1D4aQjl4DKUjUmNTraRp3ps5UsuuiiyWAxzs9YyrDVkvTzM1bDmOLUfzkFD82fVaR9K7XQ/cJzwQs3ud//18lheITXOGD7dcFkliUkJzEjGOz4Do2jX/Gp0opJ7PK6SMQe78qs3vFxpE+BCF3fYYyDO17Rn9PRNZAoFv9itiPz6YIcjVxvI4odKvVgmMcuNly7Mo8Q8sQ1ictH82nNZaFcL93y4S5Z4D5+U0h18OflZynfsGdfOX4IkPrM0Oo1yz69O27OpS0PfLhL5m5zTqrko/msZkY58F+Go6f1YKIzNydsBdEUOs+y4ebRCmBNdbdPdSxRaXy0dW1zAfPCC5uzSSczWzaVCPKnP4tb5Tz2YkBRxQeQ7S/0SrAahHrm2AEHJ3AEYh3B5Q7CH291dnvi4XElzYoQ5r4tpRa2cKXfbdoq2w93JLxvte/qDfDYOqk5985EHz+QLjpq72SDTQQsxA9x3BCULP5Xb0uo/sTgJ0Kl8+D4LVIpv//TJqy5HFv3LdJuLlwkd3mLMJevCHf9u7Z1VvVMMK55bZ41Dbg3UFzDf23FdcOXxRoxK18RWtJj4cUQ3y3DNsZfmCgUh97dL+ahvK4E8zCOzjh3swGutXnQXfVhDOYplXQGrEtjB3mQiFykOtdpTJ6E0VTlKhW4QBSu0DgKa97WBiGfbUPbkkTwTiaiDDa2nTFIBoZIbnyzKmTC2ovZKj0DGBwM8Tl8xGXniEZgHTOCcBObBgSfnaCXJaGa9H3ktpj1NugkjEUDhCIkwqbgNEQEaZBdOKnlkMMm95JDU6E/o+S3Vr7h0K0fO6yUqYLRBU54HqSvUEXas8OzeQuOGolM0hjHwuEf7EQvNgL7EDNIg0zHQO4hQbivpnb7WYufOQ94m17hGCYqDgsnqmF0UNrvaJ4q3J4YHs7TkY/iqsxotA52BWHvajv0nprbsshycuRtRxjAtIZsW0/81n8KgCI7bb+Ni3RgLcNSV8zhJboSE20iiEvpXYibzt2MUaan8MF/TZaqJLgKuNC17w11eKhX70QPlxT9z235YcEP4FkMFgxPQSSATW2DPrAsR7qhfZthjceRjZ3m1zizS6zaZzhlT8V2kdiPv9cJzgP0mcpgmzPcl1fQ2GbqG+PKUgfrRJyqsxJajCAJmhGIdOJ7OPMOsxRw6hbmKHWGKbM24s4SUzwYitB9nWh4FXNpgZ0UUJ+BiYWQrPlM5nGUyl24nn3HKulTIOlQOPETfwWVQWpzDPBhmnMXyYyjkLt8/KZ3OzXpWnH2+Hqb+amxtSRexLAe+mPmIqrn7cdlq/QLPIZdP3Uhtn4k6370B6KSvSdj1NIYIr/ERtnrQ9vtutA2uz6EbgAqYOGpqpTp98IvX/PqinB49DIMWDnm02l1MAFfMW/b/V9oLwhHGEZIBOfJGYBrgcW6aoo6HHUx5A+nq4ra5Qhz+Znpt3UsbXCheRy4DrBHINFx4wNSx9WsP0vdb1vNBeJaiKljXZyLlZL27Or21ANJp8KGQ80ITiDqHN1epFnosp6I2qibAVOo/HQBQjCB89RSIG/MtfYKN1IDl2BPza207mYKdnuN17RBRL2RrXrz8Uk9U8QYPMr/4rQeFX8y4HClk3ezZ1zNc1ephxvTcNuWEpGIIJ1O7/JGsjqJtOKcH5XXjiJrSio4d1nKUW4dB28Qk2bRhzc5uGLiu5A8Dbv4ThrMBrkfH1vC1XwW/jlFRV7/8v7mN0FfIt6mxAA9C2xoRgL7jhkhXajywgSRad+DOA75mhte3jT587LwpHi7knMnNPaRZ4/1ANPK9twfPSGRehN+KRA7pDD8KwaVWfqsN6YPK3pOhybTWthYS/0sRh244fO/jlP2Q00vMbGsK964j1+frVf8Qg5BYqABVItOOQqFAUb2ItLYBa13hFf8yc2nUdvy5uxKrSGejKMjZRPGaUPgDDjW56i+jqlghSc8/9rKLqd8C55c2t23HUBiXpTmup20RmfmYV45CdtmE8WFEXvkA1NzGhqi18uNC0tl9ONIaFOmTwZkQ+XVrBIhOavVGNiHt/g3l/ZyO4IRx1HUN136ihJY7BsjnpnHl7tFOXYmNkIrkWP08hGTDO29NCL+OTVNraEC8geIVKKyAbIR0oMsxLzAerY7tvv8FbHbsS6Cc7B926DWaZbSFQw7nhHrFwYJOBcyB3l3e4Ris/8ZSWYmay+9fm3n9qz4vOUQ2lcTNxZ+gRiCMBl4XH4ugwNOVWAXYqu0QylxVbtmIZAndKfVJubb80IeSSVDWH2kk/iABfqtnsDR9ez7aB1ewijx0pW+EjwwP5cowLb1pm0DhqtrWotqhycq7thO1oIUWqMpTFlYVfazsXmCaRLnq07SYwgWPLUn5bN03Gk05iTMsolJR6MvY4DwWFPhFHbjTvebkwJS9CO4edcSR3xIDBZF6y7GGmOipIZlIiIY6ueYtC6tetmGPpmy5ZKvmmN/jm6nnnr9AnONKVFlojy4nQGVeKcXtzOgXt6BOs7GIcHCmKAvhIyL3mcs3G3myE4OrMOi4riZ8e2MsuHg8rrWc8wMUh6Z8iuiM95YbjPMQY4PikXEK5lkMVRIHuIR7ycqX4hBWDfMRQj7zwXqrhwuG5klAetu/rBrecWmR/5s92P5BZEgsRKSukiQXyLcSe1HCELwQplv84zDRsLMjFZyrJJkK4Q9LuMhcvWkYs4iZS08rdq6WaTbi9W904DiTaGVJncpVdkF+KdQ+QwYUHZjrcv0ybp3yNR9Ax6blGY8Hmm/98X7ZOGPFkN6ko4KmcVWAobRkicaIISDvEomNub/fL3iHe36oxczJvUczRt6HnyLjp1B9wlWB0KW8ZpD356j+f3JQPfDKYZHDBF2YEw1zuhciryokEvEBLdqqhlrNk/a70cKypIfwtTjvi/0eGtiGOI2u0A1dd1303fKuUdJoThljENARMJgqqeKV/TLAXP5ksOzffAnYHPpc4wL/ngZZkIcBHadnUDMomLrJ+PYS0H5JVxdZ3jrMxB2iOQly5c+0jLUgYqNl009MFmMU8B4GAOUT0+p8LQa6NKKSYdnOqBXGQHj0TJEdsP5rflVKri4pYGEXAF8+ruJjhfigT7B/IJEWcc8BweB5NSX44TND1bo5SfPDuJtsLwHWuUdyOh8oyLr9lOSo+uFnz+OrnWXNNxLwlS+ckqPloUwFOrV0rBiMvc7yYTzOumWE66qJcbTvAty78HuCizZuTInxQHXQvWchrW5Wb1AFLCpErxWYeRldZdJqCN/QLk6wK1EKCPiZySLVMJLWKopOMAPKKU3v27gC0hdyzWpNmclOLEWZNg7Ch5p7ktru3tWVPLrbVnosiY0soh0vKHlUemB/IY7cK2eNBrkDmYHNofD/QENqd0rzYWMOiEjTYjss9kntqxs8qXbVk9u+1eTywjpkSJGfi+wSAObNIJEARJwR8kpkIiMz1j9zHoaErHkudah7I3QaARmBX2so5KGmKahlR1CQoMYLpNshSAwr2HCRTj7V+mwHy+jxNrMBSZ88jowy0A7HkNyH/HJKlkDcWOiofEizfxf5NO2Rneaq+AehAYE81j7AkxPPJtMph28f5f+t9tx4jkju5+0/naFj75tDTjuIyuOxkRFVGtRcV5En/SUTbEwBthwsaIN1l5aBgnmst+W3h5TuyVTElUM0NVYI2pEE55uC30Sw8MoYRN15pYezuM04VKvhNDtjEaoMjWmDGVRlmXm1uDGcSU8B4fRHq3kaWpSCzc/rpg1D+mM2/sGWfgyjt/bnKyoU/BdZzzfoAigYBRtZvJktJBBGQqSt6UMq9cdxzk9DR5uTMQuhWsljrA1ooXO6cJPnJEizMqs1GPbxEwV6Bmd8ikKth4t0bxDFo3jHX+ygAr9Qjz4BkRhjW40IlWTYrCZLqL/XCvKFLG5URFYx/UMybTtivUuiwlDLltVFBHLYRPMWu4CXRVREaVMy+vNAX15XuQtpgFFOFstD30OGVngdqK6HS0tk6IxB1zPyUPmu/lKgfBYOuk8eOXpB2TXVUXxOmMSiGTTfARVB3n6OGnLdeGGq0Fm3FehMyawY9nO/jlwnT22Hzl8cxx1aMo+T7WP8xDD3lQcJAjQr3lrXut+alYN9c++ra49ADRg7P1VMcdC0e2BhUKyabi0ngWhwV+E2+c9OKiE//LKMQcZST16l4C08+lG6w83kFVv0WlA/2sE3RyelL1p0P5IcOHGPUlVgPJ7XCJ35r6H0aCfnA9tyaNnt35y5rxXcK9iATmMIJe9BP6yz09DqkQNmlzhwu/3BxsvbubmcuCSZ2F95gxlumt4XQIqjLzr68Mg9TYt6DzrMhkd+KUfyXcR3RTFJkEYhbUcuZ+aGyYD38VoMvtyd5KJ/Gpp9jd3jWcQtiWFPjYAvCMOxu8jFGJNlEUKOMVG7proMEg+C+ydFwQBGeBrCYhrIAGhwT/yC7h2vn0ow+WokRaqpGmog6Ka9jjcO3zR9yjweTzmAbUGSjD/5+E5QkUlCLthYqm1GhyZpplNM+HUYEQoHhi7Y6LQBhrKaB9IK8Y4qSVDHl0MxdQYjKkpviNkDCfMMpan6ZOTFY3PCNPQWbRigtN2X4c7Em7jhWaQhHc9PAKztsIMwxiDEh1cp4OkRVe+gg1eEBu9Daogq5UwOmXIJRkCQckYAKxOeQYfhkOHp3QzQb7FazyJ/zMcDXgObx10yLZ7wmqB8YNb/P3gLMMc/fmxD2BG/1GWUnVgokLyqug39z3zdHT65ynL976oow4T5W8pdoMIRnPkM+fWoya5so1ju7uIid+Nd65T1mSMR3AD7eBpJfN3k8H52oX1Uhgfx2EIZVhKdDT3SLsIx9A8MbDjoIAEKIgCdXP6y7URzwXNBrMTJPBB6mnie6OQ9i3Sl7OvK/AWVS55JcEgiaPlu6ZPXJvr4Vrf/5kWe5LgF6Q/G0wBc4nVhyTCKTSozEDNUg9bdY1sfQ3o8sncWGURzJgsRMQqpJ/7ZiTLsFJOm81yPwN2kD6lfNW5OGYs5jYhNCvBVlXqPm9hpTNdXKEwFG8zwbK7ojfC0y0Hdndmen3K/amYkhz8HWYgbXwCH6H6CnR99N8YsT/HUBKoY1sRooSX20FSDI8MYJclV4fcuaOLYFS0kWBmDHqAZ8MGb1+6mmFuGD2kHYnI3cDte4NPjzpQelSbAbYH56KiKUi137VIIkt2h2LX6jUsxgauljWbg4fnoTJHFLq55aTWBTCiXXJMxOoBnoLGbNB+CI4QmkCV+XK4eeqCC6oq/LxyxcLitqtTqgoPIPaVqxlG8gIY1Q5suVt0vuZdN5P47GIB5lsu2SjBK+3sINvZpwup1AN02Hq1qqhD/Y6inKPkhqKcBxYF2BjfBkfmEx942HsTtwBHGjaxG0lTUOdSNCe7qa1WrGPczP9st2iiTYQWddfy9DdEFfdfS3Np3XkaxAw3A2tB5Wa5jYQleLrruOK+GT5XWzcgkVGjmOlhVhtRON9QbSAr9gfZq3s9RmjynyrhV8X213UZrn/R3zYjFNLMcQnTKUNNXO1iIMnVQ894J7DhrB8085Po6F5e0Au2LnADKECHZhCibm01DjtZUUxyOMtPVLHj/hwm9ZyQnc52dHEmpSqJwxarlLktqrMYZyuPOohyDoFF4cLMTWIsbRypGiHegqNs1MN5mLlRzGVt1A0TWoSFISOOYWaIiYkhc+gW6U56dZ9GB3VVl0sF/hz2AE9qr+jdWVvQXXjwGWo2h+hMHU8XkAW7Q44rtwUphOqnZ60u2+XXyzq9Okxv+6ixh9Tb1W9DbFugbjuC7T6N7a8MfRMr+yPN3oDbEqBa3qmefsrgv67mqQ8EAXImFlQw4gBtp2Lk0//LyZ9Vy+WXAwFheqczseqQXL1JLNpELHqw6Q4UdNzj5LoSHsbjrXAK6lZjX9iCyLlYqqNTBnABHHOdd2n6MEmvXuEjjZuk0kH6R4PEqGOdOfPaISBaRzpIDFsSeA/3WPyIQOHVSNOfY0FINYd0GFFikeM6bLT4o7s7pEsFh0XIYw9VNkmjOenzhK2JtOFb2yGoWmLXVG8x4UlUWoTjR8vU3QOPE6pAleW0rXRqxgXVAl9sefTC7oqlOqfABwjUcTXScP9PWmW/m2N5OZV3W0KKXtLFjjHhmuCL1AjLgUG6SEcxnTlZ/VNNuUGZVuvQb43vhGOZEXjUexu3C443bGO3ksagosaeClJHrUxXfT9PzqZlVEKoUW+tUGdP2J+/kRbShicpwpuTl+UlcNST4JtsHv789SyfUL9d8y/CbA+CNeUX7LdFl6rdRgzNGgbrRIaZ5imhiDYdZyow/dmt//yNJsHmR/Dvly0GYAJfb0pouPaZmj0TKGQbLtUxEJUIo/Azh83hHdLDoqXqzB1GFFia8CgKLFEknTs6Dx9tHnhNn8OhuuJtT9dQcHMB9YpO5emntgLyllb2uTiwwaQTHYNPn4cvqxXytrEYevESbDw3I0IcRjI5YFcf8lDdq9k91MNm5nL7D9mZthBl+IB3HE6gKmSrZq3LfFwbK5I7EqCOw0J8onmWpliLRY5gjqXJojsw3eLFW5Fq0WGtxcp42w2WCD6OzRY3piyuA4HtiFk4ZhhLjiId7E3h6lx3XtGExDEV8/AeXp0CSdWTbmrYUKu0c1i9Qrgbmy1kgwsl7rNRmxxPoiWCnkkdhaNxs+Qy00RW+J9mwML61iszqgpvuoGsCnH/m8kkNqYhnSS7z40EPLNUx9jPZ0VS84h/Dvz5Lx0H+aV6NYVv/gJeVbVKDFz6MApG3+emLODiA89Q8hDXGdunUwhbk24jtY5WLuJPmlBnvBLhykDDSsqvsTayN9FyTrdoVMSCskDqhI0NrDSZNKJPUfuIYzbrTq3syRrp7uH6T/G7uCcAAhq2+dkCO3ESO9zghpMLnMaDqPYCL0ys3YSjWGME2xc4gGPY5Af/AhuwZg9OY91+LYBT/aWmEQg5T2lWPcB8aqz8wQFCavn7VUnEj72HTRmQCcRAbJBZhGlIO2MQu5DcdF7p4amTwmoLApQIRCzuIp8R6LoFpL/Cpq4rDAnkKldrq0CV0803KVNXL2qxg/1q5QZelOeBv9kYahjCJhvYAAvy/q1MQbEcum0XDrwcsx0tLvgQbJWAnyJnP1qIGr3HbjtdrN23xgOZ/JifMJ2pfqg8DGBnqI7JLqa6eaCszddnO65Va9ZcLmvXBymJtKqCF9y308XCq2DLY3N0CSxBQCZ5CA4TpkCVcSFcsP7xwtwktJw89Yjw6l7wNKhr7rb9Sib24bExeDEvIcwkHjsqQJdpYzjHf7yDHWDZfVzZleawMbqu4Ps6Qs6xNiVgc3ih3DBB4hM+W/Tzp7fAZtIWzLLWivSR28mI5bxGwoh7ktDOX8vwaP3jNCTwRNWB2sP2EPcrb4pvQPRrjXy2/h65NXVDrfDQvVi6AD+pO6L+VJdh5jtlzlRgF5vZb9/2RdlHrYcG/6nZ/wBGXEx2mmzS6KFr2U5i6nEAdVwjDCzpBi4SBsX61r1iSsCb8dgzEZ3gZAapDVLUzI/tny8/DovNeHPS0eAo2eUjdYsBzlf5LWJM3KIbIx5EEAXbBM3BTdJdPzR9clEQ8S5U41z5i+rk/aIcQLHxheqvicr2YH72QECL/NB0Cd/PfmZjuedkLfL5jxsnSI1d/XbEVlbVbUe43aez/VXA3sbKv2T4G3A9Q9B8FTB+qjuC2PJoUMGoXXMqilSGSuTyqzClrzwoU28I20A2jWDzHbKeZ1xKrirAo3CshZwGjSJ6xFNm9AJ1DDq+pvlfFe0LinZnUyYl0kLNnpRKCicm5QGeFThyGGt6pbBLq55PJKGX/BIw2f0MkMmWeuMwUbf5KKSAwE10YWuvmA4q2fbc0JkS8V1g8nDkt2K7jV9aoVFxHP/m0l8fks0ZREleAtmgmVqJnQzsUmp2RZq7NRyHifyuJhop8JW7eWE9calKKWhAa/pdT67kanZ2iQd4vLipBRt6Reyggm0P9rcnZBfK0Wl6MEzxX2lnh4tG7wA9ubmmnafRMAo3QYSqn+WQnt+5GA0Ua0tQ4i122qyJpYLuGhObpOngDJfLjobxYqabiRUgc3e4CcYqwgU1tIErsajKY/SsDhhiPIOVaB6XqSM06E8M9deeyI1NjY82s9F6MLpU5wGI/lMlPKBBV4JruKGtOH8tw9HWHmRhEhItBnoGdCcRMxf2oq2TnYVWTR+EqgxRHXQcELAgexGDKmUyYn1K1egk7hzKpTyY+WGKu8ylhakR9zftcHAjwjnz+0gO6XA+GAjR6RRSpBhrPW4eRVafiA7KWR/pca4scBfufwVzOQzkK54uytkmInbljEmN3Orh2f/4my6fXop5WUhtL13Vknq7hhUAVlTVcxb0y21/ocjrWNm9Dm53gdbbY5TPPLUV/GyHTHUlEJAzYajCETtoW1WUTX/wZf27mic7FAQI0z3dv2hEGLSFLCwuIwKn4HhTtkl0ROIYJ+dCQAdTxgQwkh7nVxR+kKTfIMkDlzIhlgzUx+/EEvFAkhS6q8EIkZ5bQR+JIV0c7+E+XRCD21DzKzyicOhJqvheBzNEGw6QXhPy9Gncj536OC7qxOafw2EJLydJuXfoTRDJHQF9RlTo1HgSDTo5BseR+x3NVvAGwoU674ITJFV6t9aM0dS+k+h3YKM+GJrH+qyQdpSWe/R3o0zPZYrYlNPMl4qFW8dUKrI7pUaBXXkqjlm11amkAn3Yz7P5npDLlV+Bbrsb3fPgI8QiQSO4jvejf6gF7vzdmMUnMHH2CVzNe9AjmPqEZr4aq8evxgV+Ox191pwSscH9Qv05xBoHkRWQGgdEk3jUfztd7L4bqEX3OTaO9KkrmKZtwFaqKvq+W9bcq8A6BoIFkE0AckH85hGy4TOYpZ3Audg6Skaz2QXuCCzAkT4yV3Jevx0WM0/KoHnAZ6+xa1gJcEVV/UoAK/0q219qS6g88fXB+0CWedAQh4ncEYAdPYzvYXkKQFbkGJQji3AUEbR6IKc5BuQtxXWIT5Ct36zskEGr0ENleJkXwYHctTqXluN7Z028BwvDgly66FvwSaSlgM0KJSiLsGm8vs/E74WThGqixPKirWlqxgw1Fa60cva+baKrJWmFFxBp5SbPNzKxKTZ/Ca7FggRZKw5SryBAgRaxi1nmEzZK4EVqjOXCGqZIT9nLzJyhef/JNxh7qr+zeiccGwApPeq9DXbB8boGe1K/4kLUpgLUHpdwBEeyIkk5bZZ6vzfGJzgZfv56HZ/BzXhytqBykHraPQFMmAdeKA/3ew3etQGjFZ0nfH409YQaDCZE3LXPBhUzPJG2aaO5iaCjGLQEcNAT5+uaBVQDX5OUBbVsGnpHi8ChItSlCQE3c81Tfnxt/WvxnG4EWkItb1JQrOGg5UfK6HFfjka4AjoppTJX4NiaoxDduoMEUYmwCDAgUX0ZF+XAV49n2ctwNxYl2LqsgPdLoVVQQ1HPNhhW4pWgoGj6ivo9TW03BudQudvAv6mtSKYTWQHDWoSRWEUYKnHUDtozwev6QyqcVU+HaIAMaRD7nJnbrui8swXijS9mM3es+lPRuyKpB3h6tQ7FDimQcxFJk91mb4ZY6uGmwNiq93DTHMFDeHqkMdl2MfPMj0hyxffsjRBOjWvGPInV57hHOZrdBeTO2O1ylhYve6utGaPxVex5ZOzEGTyT7+mVqb5uAdvuP7APcfMcwUMQUqAL9zRsRcb3vr4F1Mt4e8XRWNMD38Pxmwoixx45sgsX6EyTNZiwSwX8Hgm0CxyCCssw2x6hS2VaLfKqtpR+v0j8hqO9tGJLME4nMlMPPSreKBPyr8phlZBKvdZutw5Neqbt6pTLXO/xJKzSj7Dn5bWL7IIEi94haCIor6AQIarn0POKi1CfhLWnJCi+X5mdFaImYW+cb7ihFVH1fLaY7dZXgcLDNKPAW+M1gjAQ9QgIAxZysNilajVgIuZBT4JvoDN8LQ1roWAxo4MmLEkJdJQ/n62YMlfPzxAV4zy9Jti0EBXGlagJa5CSwtimSK3z6rYBulKqpnQP4RKwqcgPVXHt6FzL39CyS6ESXUQOXVuysmI7QcXutn0ZJoqLMRgFhJMbBe89bziEF+2QRAqyvKA8Shu6uAsiv96FrqItpp4XwlAxROutaC1aU16wuZ63HS1ufANYS35yFR4Pmyt+TL+dFrQNc4mX/G/I4nRBUiTEGJ5oL955engCJpZdSol7xLXAIbkaEua9aIjQVblXEuSe3oCHpCpInPGwIQKrWh6NYwMUdNCDchUkynvCDL7gm8aP9UV/rfpoL7MWv0R2tf0Ch5glnkic0MELFjXUH2BXzrZk9ARBTjCZPxUpXuQDaeFmQum8em5fA8zLul9uPHWgGqRlwyQJWepG93SDjGzZLuPVf212BwX5/P4m7r1h4Or1w41z219sPPlgQl+vkrAH6SCyPxx1rqjXBmoEk+TozLYV2VYQq9hEBkgMcdVM4DIhNpXL0qQN1kgGX6ht6L8jJSMrjCDhegxy5vxAvhNX43bwoFYyZ/3VoOwWC6iRjA19qEd1AMJ8QFdJF7bCuLTr+43UpBlEJQO0qYBrwh1Yx/kbBg0ge3c9bMN29EILrmyxijzEQm7CF1ebrXAZbh52z2J0YZOuD+gcynM68HFWjgwQiHAJug7whHAceDkjPAQiTIt2JNFqm8yeEMgHEnhm94IGwRaCoQN4D89GAQHBpauHOc/zWxlXpHSYPciFu7Hdl1PU3it/ktW6QEY2tsNw7n8fbgAF2Q27S4wn0eE33zppBgNXr58IucYnGp/dcH8RLaax1QveB6AOo1iKWkpV59LKAQuwFFdQFTGJTAMYOpVwlfBi6SPFOrnq/0riY16e1JJGVFFGMA7Vz4c/x44aUBMK5RIBShSidksnkDsaYRUpSWEDjAiNWL0hrW6iXM4z9aWifTWq6WuH22TystLW+cU6hVVncd8KBzh4ltWF9UQrWJ8IyiWuElq/FAbDHPJujYiB1pH7s8lNpUw18z7oArt9iUG0EV7dA1c7bY1/1yfzuLGUOmseJrUjsG74JqSPcIul4V6WnMUu+nVnGXXl/gC2Aobh1bCa8GvbxViJfw9LXkvzOBKvBh7zeqHXdkHzY/OJrgXVQrr/rTm7uhqgqf9c+0WT/zBSnWO8T/KlZPf8c/Z1NF334gPHGM00l3yW0bSwG1rOMN4n+WLiM/aOay2ksz/Y+nhzM+SzF1soIOBinz0Meb4982dPc8ZLDx01t0E0Lcxj9d2Mxfmik0M9PQ/aQD56EYHL14JLITrw1pfSQwyo678PDJFciE3ldw8b5PQ7UfvtgkKFYz+BF561L6HhuhfdI94aWl97kAyZOB7bvHSw8Vem7djyIzgu5bfucfJt51KINv4hbaNzLaQbT0SR3RmoHA+hgg5LUEfpTux14RltCYRTL7iHXTVQn7xDmn4HNrJBoyxWf00LBIGpmJXiHhSyNe07saWCLpHwA9GohlD0S18HqNii9+mepQdEdidfEpuYgrv0YZwxUfd4B/9WRGNuAZrvaNUCHyEHsQ58D3j80A9mk8JO3AE1Sl5/KSmceNYhNfP8w7gJQinhJzMkVVWXQvvaGMMrvhza3TYDgmTfvGlCi3V/TMp41lxI++qeILy8uvYULTY3WiUf5Appf/5LECz9xSHj5BVnzbto/yGwf+ARrwbItpzi7HSsg0zuJNi/9IaumeZSn2act62j6cQ7wHv8A/damm56d8tDLU00l95G9q08o22k2eQnk46oH8Yz9n3iMfqioZKmcq+UjkdLaSy7g7CWbtNV0mTq4INhVwWtSdxCPKauOOtQqX9xeixQQeO12whrda+6EpLx/bevodGgpmY/OQ+WLUmB4ibhBuIy1AD6NjqRqOL39V10IPeHmIzv23FoV+5dECX4xHtFdnyhecWttuM11dsQWf4r51OjTH5RfM5qPNNvAim1ca4b1K20Bg9nVIP8yt1k7/DvjM003/Kl9DU3Bq3L/wDs73vX+yLQ+UPPQ8l3oR3TYN/oh4YH0+b/fHEmQqfJnDV/JZ4gJmAhCQVxw/V3+f/fB44NX9jX+HaPoJ9sTyv2j8BSuZeFbNWpEn6tWpvbYxj3X4ffLQUpNI6F5qDcfJrBTe21AUPgDplN2Lzmb7NRNoEbnFjvb3xL8bvU5Qfj9kz1mNoBCVbwmAEKFH2WI/qAznE0IkoYhHKv0PHmS/F0wyqUBtpN/RM1vNWgQBdGXGgU1nSGh2EoHeGqOWobu1Sig/oMkQNJkf66ee62GUEX0xg8hAFngL3QECJ6EAGRETL7OLNKnczBMbVqQB3uCpNzmEeegzgilJjrS3s2VpVG3j5H3WjoTBNBsb27tSG4TXRSfPVWL0IIddcvdoEFcIC/srfomcb9TKf2lN8HIAjmv5ez1dVSV95jqQStFyPl0x+N1D9Wy+U/KA+DAktAjRiEW17YN61GQIAy0K4t1GDradIdBCSqnnOzCEDccPxA+V+qEMC4O/Cw7Y9Vdb6NoJAhgHA6cPAf1h5cITbqD4ZLjs9kqxZ4osvZ+1eX39onE3jByQnvxmXqt0V3wfGwxoDiOBpHUewhITW03m7/OWKZ1+YIHMkoTs5B4ClPhEPCc7meDo9Rw30KBXWDvH4sW87VRJkF+630VnEW38ysZnVkf7JLf40TX0M9dYZQoS8hMFxn+NqG0e3WYn2uNCnUX9PPBAiZhg1n6jr6sBDROYIb/wBt9+SH7RIdcVqqIU/V5cZuxt0HXn1ZVfOm8yKZ2DAru7VDNf2UKUMPSHUxqPx3vJPR8umPppysZjpQfjEwxrXgg85DcCRT1DOFtgWFNi80q/Ae3tKSdflCsSJ9sdS3Wt4CCoXcODmlgcm1VeZv1GQbfBxjLRArqS3byzgKfItjhWejJ1H8wpUXSc3kgizqozxtuDXdh2HooCiCbl3bYuVW/sK2CtN9ah2m95+ijPIUR/lMACgJJpf8O1p7wBhevZhhJUwangL7gINuS1ae84NYpCuNDZozx6IgiuvOlCZAAjed6Y6ACK5TBVoCcL0qsOCcbONsK1tBWamsm8O2E0C7strQTpEESUOSJqOgr7kV7pB8RxY3ssaSY3BTIBoDMSOSa3CT8D8jr2rkszoKKat1rsJNjXVVUPWVmQu6sID3NwQhqHU7souw8wharLvUh9tRvSz5xUzc8zZc0EUeHbGi6HAbYXrdMEhrkUVoi31pheInZ7jy0qx6fTs/9xHHd+ODPsJ0UG6YCv86djj1RQeXc8YfUFw5aj9OACfH/WF2aCeEps8+jQwtpsdsOYHjBYrVya1UqkYnW6dSjm5RvakqZ0jVVlHPAAROeG9JcPO2sJtJm9BTTyVEBmwH7Vp36EpxcRaXrX2MAMW939EEb5jnHHitntu8VSKn5otiK7Bonr5aT1QEpgKcc3n2Pw3zpn7Jx48ncYfORKfhBjf3oJhObfLQEVyHjTCwuBu4tKce63sgLFWERgyqVLcsGZUqtw1j9YcZnMMUS2xfurd+1EdA4aIBjcEt4iMvyr5aHdTRa1TgQP9sbTnNpVJBX/Obo5fex1P5f9joJuYuUNjSrJruRr72rVLVfX6AyP373/dmBq0HI2XTwzrsk2qZ9CWKqjqowBLQI4p0MI5FuClyObqiSUh21UlDc3gWINkfFVWtIbUSMSmW7AwmrFwB0zXYsMRtIllOojEJu4TAX5i9DCabrWGTjdCTE9Y1wZH24VELCo+SxIgBFKkI/juP0fdbwkubFRGeR0u/rmX3vdtgVMEDW2q3LeOLsCEnoicQq9hfxXQ6XHqcmVd+azl4WsDfuG0FFUMS8OuzWJUTgtwujLRoXCw2en8FHCZdYH9gGxzpM4iHPTdRum6TpsmvcyFqS98lcTGHTcMtKg+ucNN7nJrcre41dABef0Pbcv6ag6nLZe4l2CO1L1gyR1etW53vTvC4G6KW+6/VcmH6lSnNTSH4L5usDB1IiPD65zymeF2aRogmuqM8vZWz3zvDLX1PAIPWYYbtm9fFclliUQETuLqSPJj6CW8/7sNjap+sAbsHujSLIIDV84TFOIeu7azVpN4ceCpQ6VW5rapzzCEuefaYewj4n4tFBY8kYSaoN7oRb5sDGwEOV7tbbhEdeXHV2jngvtCspu9kT8AfhB4ntBkXH7iE5SCKhvbpIrIA7eevTGsZyPovz1Y6DM8eW7I7AaLpxasuUmdXz6IC9VvTbPUrrH+h6etoOccD7vAxOROpnB7H/n1a+Ua9EjhyOpsFtL4cKZ3+wRP/OX5c9v+Ya5/OQBqWuJVoroMAFih84Ab2AEqjVozgQJH2dDn/HvW0Svl5LPzOSUEoCssHIUl6O4Qe9KDVqs4qHeWWRk4PRNjRYr0UN2CrPnhjWgttArpQzNdfC8ayPoixg3VdWPkMjILbGll9NCZhKtLncBpr9T66CbqXS3ifYO5uFOprsKfW3tDtgdvm2SVtnEJMepAn/ALLmowsOupM8oA84efpYY+/+YIj8Rd1kqke3kM8EtiByzM2tNW1Cid3wMKgwHpcm/FZMgiyzSQOweHi7F2YluGR59qKHYMQqw9EFkFgHI4FytclrUcAM+uEgvFXA0d4QKwrYQQAjONAOlUJKoXMgZFMwHi6fXvxHham4D/5pN5w78MUTAkxLeMw1ph+E27d4RYWBrGvtodqmPOwqV9YuBJm2gbvwSexMAHy4yn0QH8HqZnYUThKAiGh5ZVw08yMHmpYSzl73+rmK7vGvJrUBB0fQcZK3IakBCssCMN+OfvcieI7hJrIY8alI+SDO7074Vg3QaxHjdu0K8THE9vUi6Q/rB1GWWrWFhazVbfbf+KNmxRyd5mrpyMqrKvxe9cyxmo+2DxNz19P8FX1A4YBsQ+8jYUIJ6uuPdQZ12lstzKMRoM83zutLGtDhuJiqvSJVTOdYk2WhIRGBGzW81Bdq+GrG0bVbDLTyA4M9FCehsBmb0QI1z7pZc94CjUNRxhSL2vPUi9F69lOxku9ZF05AM4PCRaz9UyS6egQ+9JQb0GCg5Llc8WfSbRZlLtbS9rIwgEmcC6qVXGdhUOD0vA20vW3qVSjQjZiBatwN8IEFYUWI4UPXLpjJ/vuCX6pyqNBnue8prGr8sm7rizrpwRW5V+lnNE/tpvgNtsX6rPsYvPQXQeCOdkOBAlaURDY/TKB+84oeFRJR8yg/bZY6dRbSvuwSim5NxCQJ0ftORFiS0XggApp0dCw6Cl6PI0+SesK1BaNwohm+ENnEhK9S9L/xMfvLGlFYo1YtFPG4n6ID35jNql0+mUA2nBIK8wQ2LDA3s+t4/AefpVMDS0pnb4Qu/VNl3jYli7ZdhlDDxkXNsGWubdx8xyOlDlfTMrSvOwCnCimxgAbTfbiWizwEB6InSVhn7qoRQUhkhG9sImqlApBRgptGymxSs524tr29yFA+QoCHoIysWNwjFBdVAx0g31QsSu6nPPw6uYrl2QiCta9uzVJBfY9EqFdaBGUEkoOBBYMzsMemxicDGtkF+ejGrFxCYjvU2Zla4er+CxKd/z0l4HE21oas8Y4n7uhpWv5zBz3Ypy7K2VYvExXo1ubM75bqGIwLsLr5oltM1yRpmm9+cAX5RgNA1nfzKwaUEVfVKBnyXX/Y9KjDMpme+cVWQ5bqCTo9PcWahtej4L5ALtBqFkI/lKCVqnqqO5+iYcY3IP4piwO3UjhEGISARQYImAIrBftfN0kp6HMKPRqBN6NFz/jrhx0j64VyqUInNQOlrRPRUmnPxjIf6ySyj6mlpmn0+NmT7DEkEgQO4iyqA2jRAmYNDwF9i6HUGW2qcHpVnU3+MqOYndxGB1ERr0ZzUULhR3muiNj1N6GFKYaap6bEkXfg73bKTkJUfgebrehrWiDSKs3oaloy61uefiLD7H2cpU+TsdebGnQmlgSU0bVl/3Ruin8SAqBhHf7qNUP9w5DqW6C4GqrRio02JTdM0TBhebVvFrV0UGqfbfFIBOpHeou4VvOlHVKOXmrujiInBRUF4BqDbfqjIGXDkRBbSFnpKZ2ilTEYFjtoNYJWK2hhP3fDamrmyG02iKXigw2VWufn+2xmDnJ/9IEsPEOeCsKasEgornh2cj+llq58Nv3lbI1VblHbA9w9gXP3Hy3F0Sdxvrz+Ai62kQ3LfyLKVnhm8auAVDnGJP54jEQc8V81SG4Yw8EqHEgNKwTS95I3Zqvzavy1gECfFNY/Q9YbGm+B1hxiDOW6Lr6C9HS7+cBXxnScKTB65dUwp3YaAObxkbSUF/3MPKXMpcSwfVq1cEEcry/bwYbHntQkoKDmF8EWxoX4MhEU/oatMXV2EG2kjV2nw3a9FAIBrCzxAVdescCPdKK+z1maA4cnzwPeTKFg1RDL8yN1/TOuIXrfP5JkiZ9PTDbvRWqvClob2ZppMK3PKnHRDCNM0O1ON0gVmHlW54iacrVQ2fbm2lUHJopGJQkCpoOMa1YmRPQQanBrlXhSF9ngujikvepq5DL3QGB3EpRk1boVVSD3qtLQL6V3Ucq9UhXjTKkSet0Rkql66rrwCpIKW+oIqDe1VOH5meJQiOt0xuUNqlqrRiStB0nIFaThKl5xYnoEZDHfu4CDMiHe9SZG4R8kb+HPVcYEhyGrPqEpeq2vxGXZiqREBQow6qMCzPP34pLMhbMSGwonYtB2xzdjosje5r4BTjSmiEokX93axX0kA+6jQMgGATBCWt0eKvCxHH6EYyYy94wQOuBPg3mdQDvYXYK/lzmBhn0Sj1O0pgtCVPNBEtZ24U8EFH2QQUouy1FS6ZL6FRBvwXzE/wgQXiPjLU/8MPGhI24ezhpsawgPyis1asScvx9txMFNwr2cqDa85arSKjnTTTaspXK9xB2YSVE5u8X0CO9xwTRLrhguMAd5wqZXolDRjE0nxAhnldpotFc5Ue/nivw8O0ispkLOM8uqBIlBqAi1Aqc8sxaNLeoo8i4fbOgTGOuroCeHd4jZe0Co1SEVrksYqdwPDaBlBRY3BxOcaGfh57iQF9OnOrwkcgAlWOowqoGL0605E2dYRFaQCQZL/wIq4MFT0IyD+oWBTJrrsND3mYLlBVuE+/nDqr1qGc9p+Rv2sruCaPNa+3uKCdAKPSzXCvHiL6lka1kNbv28/ur8lR+wNNj+Dn6zW63MQ/NXZplt6l6qq3QwJO1fbdFEw9Mo2byVtW+KgRUI6hlPfuhakNl5z0p1LnWTI3+zQ0A6VFTB/ux++OVnNUJlG81dEalzmArPTD1sN8lsXI3xoG9S3HFN7CTi3IF9qbb4xbO8qac/kf7lSLzltWhnvU6dvQ9jfSecNqyVrtsU7QnPBoIBUdGfqi7U0eJSu32NXna3GZ+PFpT1ddMtzgFVbcG5QfcgwO/r5HfkofmflsqutozGsf7OHqBqFxBT7b/Wi1fHpGzJaIOX0F4JqcKqlTtHuvQmhflWNE6pmalyQIsNK5a3V4JlWNpeFSelnO4k/kSQRC0B9fWecHLLMJTT0/Lq8Z5eYFqN3Uzlo5P6ORZx/solk+P2xmBRiu1qpxAoIp+NiN9SRMSqg9ZHCc3zRSN7s2iYxt0ZPmTsX2BU5MgaMqCfbKj3FMP669R28TjvD22oepUcY07S+2d+iYR54FYInRqSK5+bxsiE0ejHU7n/thDgVNtVOB4NcJWQsE64MkYPLH3bDctgaZ0DbQtAbX1AYM39j706n0xaO1BZFJtlMS+VW8a1Adj2Dp4CLMvyePRe6Lf8VVtbJMrRlvbCIQx1Jqmz8dWWQfGKL3BCakxso3cQKWXec/9YXNfF9DcLprqJBDpgblaEtdF77f0DwA96ILUALEnd7TSMzTZWNnfQStczh7aO4F0tYJkD6eKXfFGo2s0Qxtjq4On5pYoNthcYnWDyALwjYPI73Luj40V0I4cQ7QTYdI4foQjBsokwJ+LOapP9SK/0jus83oI1oCaCfA1tzC5PQcq3cIEyWrYA3rRs0xC5m9jrzSbBphQDbTlhfk+jPcwNwX/zic59sqQQ1jk/M4E9ThNf4kJ22naxMe2ECx5HS5gfl7jEtgnUZMCXpRm4jFizGU7UHyt7hi0FosfgQmkpzKKo8bKAy1sb5rzI03qGkBrxYUJs+4gZcq7HQvamSiBfe/73iGwUwQiA7CG6JXYg5aBAaBXeaC+v1jCLaTKAVLIvU8B64HFzb7tvsnS1wk0p4fWtedTVI6HP0PqgcjtE/JN9qasvwvoHi/Ud9XaKYqHKRY7wfn+AOSKmmzMleiDpr48pVV6aUPupeYRqXjCvIUo2ffYJWPf1SrYFnKB/bge8V7C+0nbpMxDNZ6H5EQR5ouwSIda5vkob0EI8wwnFdrPEtqF+iIn4ehc/HUNNakoCuhRX9RDhAv/J6O9rm4yWXhWED2qj6MOFV0Fye5zL3irUFr1aT51qWm8A/IOKlATHw7viBsHFzfs+rs7V1GsWDIWCi71NKYryGM3pm2xIZC1tTG/2L3mbyp7eScJSLEEDlD8oN2h4sJUtC7mRmmD8wfbGgZfUHHHl7SFlMSG+otU9vfWQqNpbTeqiE1rfqHVFTpnYI8V2ypFJF9pck5ZM9baxinzwpsGRxpCL6okiraKJSMhJ8EKxvs9nVHwbk/Du9z2zucjUmkb4cYaXGp+ta1vtNUmPoaKIAg+DT2M77S/o2197Eari3P2hQoHxCjxoqIaqOmHVZuKC2uNy67Uss7YPsMKVh6zkTr3jyRZydmjzvII7KIJZT19oNJLvTonkLME+B7wmEggF/HRnJRtrTepo68pARVdYTQ0kp4QH1Qs0COFg/LNRUTbLIoJwhvat7TlOLeotjiq4yBHs7fo6PQWBlspC7TIX3tISyTm9KAfwsVbAZPJwemOppStn65tXmFM1qqY+Cps1OMujdoRAvNUdpp9WJ1MM6nmD9ScH4V6NVbG20d1yDlKwiPakdW0iOq+V6U6wkpUyNYfdvYgf/IwTeWmsR/W1qch1QB7ijYszQlZFx+oucZAeiCx+bSt9PhFC9RUuKPLiVvWtizVxrzAJXR7mimpSWuRBKK+CDTUVvJSOYWEkBLqeeNyTLI8H64NXmnsLhtNi86vVOToyIsUilFZ1RuyfJpwOPQssN+5Lc8O4m09YtzMbKeL8c3a+dB0tHME5b1r1dFWbaQsFltz8TTUBLyrWEOYh1ZJ044ZNlc1YOgUHAAfV42EshlrcXWDIcLD62LR+deSPDXGi2CffalB7nCdzBxWBPSFu8DyC2X0uKdQlYZo5icntQVzLcFVl2rYJBYNttESutUV5dF+tWZvnrL2wMg2lDVBa6FWMxfcUTIih5kUF6PfRFAdtUokuPs6WjCgUCRw2CK5IqdXdYZuvoVHHaSbHQALW40Zm0SYFR2xjxBeuzZRpBwbYaAOCIQAezArBD8rs+xlk3Bb2WQp1yDXfXa2cjOiH5bDeBqaIsJh0eMgyrOL58+guYhprZqmp5OFbx+qvjKlUCDL9dqs2WE+ObVkd0o5xHK6nELqQeMwSxwONgwzxDlP2vyRj17EyjiHEbjdjrZt75RP6RUS0ZMVKtkjwRQ5c5xVsSMG0Ho2UjL13Qw9XiGVvFkHkEdHrVh6SKbeJEabiEWIHlDNJzaxC+yRfnKd2zWGU2my1BwNQYicOz7DG+uCWpx/4xOSZP9Umd/GKEuFogJ9vj9EwgLimC5ttFgckMr3GUykf7bBROjHseYsjCgdHcSRCpgW7TBNxc2aXtJrRJ3eiAvY0DCPjUCzgF0k59sPmXItOgek0maAvt24dF48hUJdEos5LGvgKw1o22Jm7GwqZlZJMZXqFbgBm/XV7Gqo+4bmyQRBrF5vwn3I1gelY8N27B2lLF1QEFC3JdJOt9LUUylM6IUrVKobEg0UiCEedV8YWiG25zXyqrH6LjYJFCOaoeb6vVr4Bt+10sRTK98Wh4dBHX0Pckx9QmHGiMbOSiqBVOpqran6v5BR0cwtLJXaouFbaW0FKrOF7ork2AR8hII+oNQsrQJIHxYHETuw25dDkhTiyNwYi7jSZG4SemGuMm/mEdmahOSkqtBCkDQUIq48uT2pWUXnwq1eNu00bDfmJghhBwHIwfr1v3FUjay0TTgF3Znk6Pok28g9gC9W6vT6vMDujzELYhSxy/i7/30hkHj+6l6ftkCtOHRt9LZ1Lbc2jfqBHAZ2LpLUZozfhNsxL8GvKAjCfqnwmdqvCwkZ3rgIkyac4Ya88/p+uWKUnrJWIZ+2SPOG7D/N6DW/fC1TS3mnaycc6yQBE+6bVQUd2awe/T5tH3YlF7P2agkj3q/PjuhzqiyxCE1UY0FtjU9dlyrIR5uu6fz1JF8hoKk9GM6FcBOtpatThjCfvSGGfC1uhY6BbPQa34GwiKn8tonhOkSqRigxOMRn7Vzk7A0xyvojGqS+Pb09LE9LAkNDQrbyl8rRKaNQmR5l0F5qaxilI8ZpMysHO1kXMedVFMMchmLVKgSmUTP6lYrEz6tCmf1N+QHiRgZ2QgARRmF+EHyLYNsNk6cdkucCS1DsFnwYiRACmn2orbdpLGhHR/BpYj6yNPL500so2yTyJKc/YfP9qJ6DGxzQvq6oOP6xqu7LFRrFnjboVFIWYhuQNGG/TPjQEiOKo70B+RpJbWeiJFP/9tT8qGJLng1kkbtHDVjM2L6YVXKYhWvmL1JftBd6n0JPusA6mj9H5ad8FhXwzGjnK7spZQzG+BR/hFu84O2TLVqFQrAj57eYlcPPs6MmRQ/sVg41RYRZpAVSlxOdpnyHhXXQVNKstnZbKbBtC0lWSJnn3sNMk1kxxFfVvU0K73outzVKI3SUMDRbxD6svptbqBfIklOQ4oCl7K/kOUiJYjKKfWpXcNQmehK2GsxctRPjhobRxSYwJ2SBleY84rKsXOiinJ1cHePueZ6yF4uuSFmtom+egYQUGFzrirh6qhxTcS5Ju35AqZyuI+9RVE0Dmrf8CnSKv0M50FbeJQyHtEMopZxRGXlz5MWNBVW+AsJxBmsMYxUH0Q9uEbZ63HxATYKP2dlyq70A5G9KLd+Gs6c8RGoPbPZ8UimLivPVoEasOji47rKI55s3k1CWkKbWEA+hOv16aGiCpiClGQGXkYLIYSZFqpZexqxVI7wNA0pFDiZWclRUy+D0n2FeAekeJcKDT6xY/SDGraELfNclkE0TX4GVtrtbfvyDj/Kv4/7yNVTXUalRwWaVpRJN2xX9Ow7+ruoz9K1al5Lbu67o4WnjcUVUZxr9SxJ1JkBiIIPYzYmqdeqNaCwaXZHH6plGvCqsqvHgREvzk+aER61QoxHgkCtyECVEXO1tXKpRLk5LBFoJlbK1HbRHSQcptRY/00pVy/fhF4Tagu9+VCRKqFX7AMwuKHEXTBSWFwhFj0ivnkOlhfxeW8ljCciOJ4kn4wjQmekFbYKaBqAyx/Ca4iYD1JdVUaMgFDViePUI1Td3kTqZRHPq5uXNBBPOxXt4PAO++IanVzGl5loYtxEaCXQ+YkSsI85oVdT3dVgGS+1vpFnrcz3w1/rqwdJX1wMLlazeO/ccvjTb8ZbakwOFUYhWIp1Jbm5kW5gv5HyypkSWS3s9sB3RNqu8oHpgIWkPtgZkgOoCl8UScINCWZDIBxexeCJ2Yj7atbmx0iVrjnVVm13IqmvaHELKYWibecQFd47vXE75Qw2ieaqBqh3y0Xqq3ds0FDJA6mEqh5wIBSfGJnopL10PrQdqdZVpJ3JSLenwUhqogXBycL0oaNscvYhAwMAFbO6IJK40ybNtgnb01xyb8iT5tklaPmAz1VP0O5ZRxqBbbcNbNmClqxwXoXmgwluRtp8f6XWMtBskDxJbkrYQShWbmkPwHsxqVmBqc72cIMcFJ1y1ahVKRxwyB4KcFuxwxaoVKB3kZTwC9og4ipvE6+OEfhKnw6i/Y8TJdM7YMl6Nm0c3M2M+po99Hi/Dm0Zv+sCe42a6CSILHrhh1QaULnTL3Ai46IixosV4Dw8lAaEfNzvhqtWrUDbikDtgnzbb4YrVK1oN8nIewfoEuxEGEiDhSlDCni6xwsmThTjaz4/xsJdKEHafTGBq0S2UPV+ih8Mn+zA5/ZierS1hYfvJGEec1AyH+BwNWeDSnUvR1svbedhPQwY4uHOQacKGOPbtkBHO2zmPaTHZTez3IQo7dnaMT4I0xCLIcboYxyfGkd9lE9gI8pjGsHeiF18AARDkNv07mAA+CPhLGwQmhn+GCihhq0rMcPRkFo62m5u1CHu5BJxqA0haVO/JJKaBvEXHXivRovNklBIjw/jeDhjhvO3z0NJqtpphvw8A6NjWMTtBHGD4P8B2sMAAj56C9m3tStyoS9egV0f7BC/xkjaAJ3fsS5qEzRPNeF7YsL2KbeOs92EO4piCSYw3YzsX00bcpbkkNwf+cbFOdDRc1diL2IiL7OpI8iy1Ytn3zN7T0XF946DwCt66TUc9LdmmVjSmQod4Mt9RgwEZgH0xfip8s00V2rTylNPyUaQ2yasitEgb0CZ5ZOyQ0CLt46Efa9VgbXIA8fM9BM/LfR8taMwIArYJboM2thoIPdHaUjenViF+SZAQNDdqCGbKmxgrPoVqRjzMKVOBq2v7kDDXQ/T8LU6D1SmB6eYwG+N6mRDwfmS6mBzuQB4TniWPrJ9iFI0RGqwxaEJcMkYwiDEwVoaMGTMReByamaWMizkgAjE1jFGngfXC0YrHy9rZ+HnpNi4asmoitM+A+8COd0pC9e4ZZ1wlrm0c4OB8N+ZuT5F5JGLTmOwm2AAP3oqsIBA6sePT6CHkY5xw/k9y8LNjfLtUPJVpDEKQ4HbRnka4h2hQBjonAU+/FmnFCNyGbDMQHJhWRmEGZoLX0QqR0t5mBAuCekphQcpWWK4QCFWFRFW1tjgIQf28efX0EwiSbLfkiESyMHQBm0I0hCEVXGrFwJld8mqPnZpcNNO1lD7XCbYBebW5yVGoOcHuKk2fM4F0CBZaLPLBnVj+d8v3fqBkapZWjBMdE1jR56Q5RxM8c7fo+zIKo+TIioqExY4iZoEcRt1M7hFHKB3UPZ4FFYbDHcNYkTPRTKNBejnZsg07EaVMsq2jDVcwcmbUsY9D6W1BpSikOLQ7IzQS1qGuBJc2RhHrTbydePF0p2ZkPevI2NtoQh+SscONDSDj0yEW1cfF6AZuP07GINMiorvlKoeQsG51VBxpdCFWMJKNHVVYQgZgDWac+avAFtTzWxBVp2VkvekAdjZq0cmS2Q4ndgKZLEoWY8lFM0jcwB2An8W3ODHmHascAvK/PCMJD4BxuwypsdbZdp5oZdRYMgT4op1gf0aXpEK4f9A4CSHtJNxDfdrFYF+AdUM4q3B0EPq9Vvx6Hajpz4gAv3J1SSNmhcZMoGBUsAEaGC8MursP3j9zMoePwLcsFYZTDiDm9CR91q95oMiwERWgpseoCvjYF4NsgU7L+AZCf9CIqGJCBx8L8cyzQACj5YH1c8Bg3CZRaFxKZ6U8vzVVMmrYDSymqi4AuX8V7FHxNjOmBfarZ4tDgipYd/YAZJuF7G6ML5BoQbRZRHcLPqfMehy3BKEs+28EhD0AyTREy9JI9fkDsbU+gpGKjeeTQHSEusCzN3wS/TCjs6nHdUSlKsIFHQuwos1MM4+GkEBa0R7rEa2KiF0dXZijk+tGfUxxiA1tBdZkRxZVEHs6ejAPJ31HPeQxkyNrKjw6OlpwGStnR51UIhl6U9wHhD1icuIRoyW1oNHHaqskV3aEuRYyALeDVQ6WwjBk9hqjZHIscQNux/wEweUF9j2AyJrxUUfFoUY7YlkdWdfhwxIyAPtgOvUpaczD0DKLIGx/qvZGNToYMtPhwE4gs0rBYMygrKcgwQ+TivCwhM0U2HPEktbjbiQmWF1eyA9LYabARxH81UdtO+KTfMwLwiMyNktoowjjRiujRlIuxBcMBMOftJQJ5l/+KfoIMb3gHVbEFHulyJNFhP6qxUBBd3pfSGDMDiIoc1gQWjBYOR7CMySBPaSFf4yMO60E9Cct+FdMwN+4UuMrpOIcPorYW9NBacG+RiK0uvOnv2hYqjkhh3cZxrwXQNCclOPXDGco2Mr+Hq7FPA+vvWjQukYu9NpA9w1U+Ndjrod/+lSSgn2NlPUEYKFwP2tIEo3dK6niW1bQPBi5wkxh59ggjPdQcGv1Ezdg3CjTmilil1R73jo36dxrasXXO4KRhiqJZ23uEknVyVEHaEknIdnoLeqm1uKdQnnCnV7WCl9W+JJ+hj6SiC+rROBFOCwcVoklP1YttTP0dmKuzqxlaYoASRr84bj02y2LyLH1OW4pDUnqeJW+84eTAzjM5PRLkUhSz+PUO2RJoo7T1eToUjLCLT6TVG6ju/94dP0LExH+0NGtd+p9WuTXf1dmI7zWY9vuNHQbMEPDr0yHB64Nh8fLUs87R+pNEwkJK/nJhyWLGMuJrs4TpuKvc8KGLpqX7kkLtMhvXFb2/RaE93VpPvqAvlrL8fPzyzuR8P4O+ZUTqzhMV3N3+UeVAbWqfmttMCvhmurbk15Ghb5n3j/+4osT1xtNjimhIzBBE6lWLZk/q9W/KhrYeW3zkRdgTua9cuzIhjVDD9XpzMJ22gd9MI3W6F8jyysWb/Wq2A4TQR+joPdG7dKLVDzHS71R/jqP9W1G5qhQAY9RoOysWbqamoe456emf0NDDQ3QnRMg9jGmz3Qnlr5mygCJXGx90SP5FHOxISemexGceR1Zehefjyz+iem4xxF85yeg1Z4OI0QjiliTE4LBExDct3X/ks+t5fjxX3RhN0hdpVuJnZNEH2f4zJV9S3xSw3Gdd00Wq6UKQzqLnRXcMzF+/Wk5nuvsVeGw0Sco9PTR2VmXkILD7XdazSaMnhGHFnFemH3P/C1bXYDQLeOhrvMZyFf5r0k95RmQJ/yC4otuFvqIKmVQ91wz5Av87ij8Z3Dofszo/BKkZxzoSGjsQ+oKYjh5pHyPH19cdU/+k426ytgTTfW+fGhx8KHJ91z3qPPPCwrO3I4udcYFWhrB9Gt+6X0+DZzfVFBqIFDealpqjSlArvWvq3ENn2r+3pJrpYxDq742aSLhJ48cvlUd1nI8651WVSR84vLeW3xCw3EdZ64KZLhw7FYotNLyRauKw+ypk4vDJ7Oe/+dXBoST+QCva4M2gkWrjperX7zv3yaZPgVrU67yTITbuYF0ZZ/WhJkd6dm7S+UrWkdLKjFr1Z9a3RFO5V7d0nanHfKBbInaX/r9ZyluH/TFf9YwSFpadmY2ZueN0BT+omGg3bHgWDpkohC8jaV/gt3/zwzbYU1AW17Q3iCOzF4zt2yd0RLEQk3ny09+oFIjdu8F2eju103CcitmC90whT867LjpGwt5zmIzl94nXgvr7mn9C5PGudyVpY9kU99qFdV4MV/sC5MHki3b+VoryejBvL7PTOHzw+8yfWMtyxkcwdL7BI3bL78zJSObwJK135ZD++nSQkMQCwX7Zsb/PxHwdJND6xfQK/t8lZjV1lD67eHtGa2jJVbMFvhTQy85MHf0Y6tQ4sE83p7Sj6V1P7Xmqn3QX0NnpyHSxuU/NGRGSrnK0J9L3T9tft80V6bl+H5t6TcS3V4tLx2WMRjrt89uMHG9063CrhTHhV5raEZi5GtMs22OOI5j31DiGpmx/+SOtCk5tvtsWTEO/TYjRBI3tXe49DmX4Fj+8+Uug7nv6VYQyjksOl4qL6qcWc2dilWuDpb/2uEcZlsy62hkRv+TC84pObb9zOw/Rqu35iBHqqqxeG7/I5wmTY19G2YfWVCgPqidXao2L9CllWKKgf/PpR/TqTNWYcNHkjuztvnytEKNXFvghd98mnRoz1cJIjL8vy5IZjGrgbK9hI8kd3w96cpprYLD3Xf3vvFZ0JlTX6VISF3qi8syL187lpr+SAsdYsKTV5perVbKEavMOfFtj/jCnq/i+ch2/X0RHfOe4JeeQLAsA419+x8bIrJvbfvxVl6jxwyORy7uJ0RXXx5zl3CVrl0Xndbpmqsbx5Zf3LU3yKGjbZ+dbGMrKG5+vOHx7ycFp4914IHn2HhCu7pWun3Yzsa43gA0OqiPDR/ZJ1dNtVaUsTi27c6p/f9Ln/xqkwvlqOvCpd7lu+aO6aExf9d85PDRts/2tLKlLGJ+vOHhjwf7TtTSCoBrGzrBka3fiU1syCgIdTG6I4Gs4iU4CBFbDULWJ2KNfxXW37d9wiHQ+01+7AcWeq/Jj/00mr7lP4BA9zP5sV9msWZJuyzdA+GXqBkDGnhqzqrL6i7FjW+av/JjMs1xXXdbQ/R04evWcpOW41dNz2oi/mfN5fASGYdFxs2uC89+dIoL+XYZ9L2vtcJCKYeG3mkoQ2KVa83lf1JMiOZsuuq/ivOqP2PvOFNWAc5QLf3Wfh9gwDeU/tFa9QNkilAO/P/Nv0148lXGVxttSsiXMV/zdT/b7v03rmWiQwj8vz4biLD3Qi6MiydTjBs78ROb+wlrHQ+R0OIemxoT/5of0Dvt2m2+SoaS/pfqy+ciji9AnIqoGnfXRwOBnoVreF6nC1Dq68rWNyVYNNgBILBX1uoiQfa174ZCtSxAyBc3lh2http5nCwumHPqFJAAz4IXeM8AGmah/1zZ9zPmTh9jqgtS5mCl3jDLgIWckuT1KaqS5PMmyTfDtTbrWgjXWm1rQTLXSgcDTErYLsk2ZRrfAmELz7VAthUkcSyacFgTiUBVheoAN4XjBhBaznEDlk8J0iTX6+3lEOcBB6Fy+B2f/x0sfuHzfS7cTHeO2iI09Y7aioCWL/5QkT/E0oey/BHuptMM5Ka5sQk9QIuFX7FYX8aSprN6TZxDZ9i8j+Y6W/ChByO3kGihZiEKty4CsVyLzWlkhFmIDveb7bs3WuXhP4HxWCBQDSce9HfZ/8vIvwL2n2j+F+OfFxyGcDgYHGHhcKDE8aGJ/B5yfG0in1FgWmAfx+0PBPdzaH+gyvEywZ4G7d/CIed/RiwepoodHzR8Cjr+H4ckMvWwRyQpYrdFJBy1dolLWXapyG9mxAxAznJgiLDDLkGIbcXSNDOci8UFJjQHkBMdCsfLDrvMc0nWKryQxOlYnEGQeYCcC4IcTaz0DZ7/hvNZFgmdA7Be0gdST5Vh2s6kCtbNiOSD4QKmWfIzEE0oyjMIPjMGk4itFtBqQipgmiA/x/PPy8rzPP+OVMXaSWIo2KgeYmCap5xm2dOK+igjjh4jzBqLQ5hmnckBVWJgPy/cFQjezXMP+uvs10h+M+T4hOSjqLoouJVltwap8jcbvWjEj0OO/3frPfCZ+dqEP7eKdqiCoDrsDBOy1uOZFM3AwmKKFpBTsVMnuGoUExnhfI7nGfUpkkjvZ/nayIqcOi5AjeI6JpR+KXUatCkS7qL3KTdJFSuPwqMCTO/DFaPOJQw1RgFMs+VnIPQxgHCgACJoK3yvMJ6jP80yEptXdmtlFqSU95M1swo62baPTa71zB++W23NimNYQGYIYMHXZeTCe9LL809yAJnRQacgY9FfbX3hlmlp14zg4MFgC3KwxN64wbm0YxMHkMpVVKtr/jvmTF+dVrbJbOUagaAEqpVEn5bDB6cHlTmVEl3QpZOmmOVR6w+7yz+CqQerkkD1ghp6+fe9Hhcmy7yWihAgI6ugEzr+0MV0+PSXzwczo4EFZJgAluObsvMHZ9GXZz/sTX464EjTVv2S5+sXf8/geBc4Dsiwk3DWd/ZwSTPztReBSjrn7MyHRjbdcjXC+Ke4zPoapLnp0oo1Eyv3lEK0ihjKGHf1ipObZ29Zfqzx/1JHikzjoCOcpUuGCz+VXF47zwJklqRsU05Rzn7lotWthiPchz0RwBLm1OVObzW/XbXZ5kGNe1VWXm7/yi2tpQ1XOSipwVG1yPcfXm3bs26JekVVgNSQsNbx6qx56xPhWVNegzITqEZafpl/++XRcntaPSB1gxSpJ2arRs+PnF33vISHNKh41eUVaye3j18Npb87NVolHrh7xeiePVtWM3U/xWhWXNy8Y/XyPa6XbmRI4ejlzWt6d6wvhdLfiEew4tIjjDeXQpi89oe+h3aB998y5Y0rNB8d7hEkNVKk/la2e/+M5dL6F9jtNEmZ7L/KB1/47MerXg97oiastt+ZCB+c1Uz+gh8NWg0XypatD4c/r91Yd3NDKD96mbDhvoHSiVkqBfPKrGXTQ7uvXH1AuJr9UClvbvuOK9DwSz1Ni1BtorEE9idVS6cyIzU2cCcUmtOS8jTbnS8+z8gomFAgaXoMhN7qV1+2bP9oGjAKbdQhLBJFifI036mHs4lOIVIkTYdQQdT26l//Nv3ScW+FDRyCIlUto1Rk3f/882K/EgFJIxAQupeVLCsPC0yr/UL7gYejKBpQHtJ79FNrs1KIgPC1CI96R+kHfsstn79QB3rYDJi99qeN5uz+I0sNJhsJCF+HCJ7qV+84Bm5r/YUuGWwCijhy85RAe+zAlU62iKHTF4j1ROndQHj550QmAxnINP56o3HRxvtMPi6rVYQeEwR2NcdP4reKOQIxtQkp8q0xMoYicVpEcp+UgoDFvzdFrmjWWMF+JW/8y9Wy4YPPZyMy8iaSIFa8LIY0rv9GFpLqDiwUxcHVPWuPfUQAxAGpvPfVPwEV0q5TOup2KFzwxWxo5Oa/YbsBYgEtP6fE99jwdddJQ9FBQVLEw0GGo2Kh+z8Q9z7t0laJwAuuAEMSumfi277yWqs8T2wBREpCzLC9LJPuF3T12alFH6P08KHy75JGjphe8etR0fAi+9hVnvyRHk0rVCIP+TitrI648+V/1cas/byNssJA2s6ehiMg4VmlftojsHTAILYG47CSQEh5Wu+24608VwyApLGfUGDRXvy1fYPtymWpwEoeokWif59Cl8851fB7GmikChaYA199p3HTb1Y0KiqsGNwVPDs5uWXnrCCPDpTdr2qMuPTr0C9Zwb8aZMsmDp36f4iAkhAcEeWWyYubytN7G5Z7o0ZwMxTKfa+/WqJtabpyjJGjQFAICUnmv1883ew80vD2IBW9mRbKzRMlrjj3D8hvyFVDKESPiRLDF6dWW0ZPnCIEw0bqZiwUuM6VBMqWysvrncvUGAo+YP8NvovLAT3cglSRL0OF/SqN8SOTc+TOnl3/SVBDVeofLf97+7SsvH/KLwdwryjbi2//27b/EDVI8M7yPyojTppenhalIyufemKSPsiYpgwHiKeKXixuwOqcY02f2TEkjxyEryz9NOyhS/t11KBiX+js1N4jjz6P6xZRdwKI556UmB5QXDk8Z0MP0ULbP0v5Qzd/eqpLzB7AsLL0Lahd07rMKn6EOFWlmcsOCkzLlRJiGAAxoMD018WV5viRU4iXQaUUuM+V9KmZr2m5oUIQPDyefrbnsab4ow0Hp/XoBgo1RRtNfuJk6384FCMtAZCLuxpWnWzABUm3SB4ccfvb2UyxCPtDsH6753hd+ETDGysK4XoEpidKmsKWI62fROTPWh3XLhj1gaS44RvT99N35R+dnhbXAoKakBBG7aBW5LGoy9G3OmkuH0oJk6csEgrpqHNy4tB9E9D8/MvnpwdFyaNT1Xm/NP1buIq6POLJTV55OsSDDh/wiurfNwmNnR9SJgapGMjJzKHtZuBVP32dVJ8oKT+ObSQ3AnGg3QrcitDxa8zgM4Ouiczy0HaCTagT2szQa5wu4ZeeGik/KmuEREwgIQz7QFiQ6Sxvff6NfyxhA4IUIGInwHCyWGh69trgtW+nB2cldc0qTa2W+1NCQjYddoKoOLq1/Pq5D99/vvHTRDAFCFa9KnxV9NjBbSDqPVW++sJbX6zEbKboBeQIexwn8GIVPoLCcTruKXza4q+uHBWk1C7gJ+pkcxHwVYNqnaWO8AA1AAENUk020BakQRhJjccA1Ud9ihR46uY3J2+yNiS7sTXHu/FdrKsE7ATyGQYDVCu1KjKBOEpumFWqZ7e0WoM123EKS6iWz1jENVWFujdXTlIVHfWANp9RNf3Z1vV5lUHT1g633Zk4jBP5VVDBqAFt/V60ZPodJf1j2k96TxAVPDYbaH0iUjr9QU/+1zRb+r/1wBp5T2S5EZb0YZVM+qxSF1oTt8AOUuKspkzff/HbUu1mJiDVJthFF1rQhP4DE+HCT9UvLz7IRUl1NAteUAnisqz8J/PSWd6lSo4FctQ0Ic1Xqguvfzbb/5s2DkqyCNQGbTbgYT818Tx053C5KbkWkLxIlmePAQ1UyEb/ePP401tfOHzsaF4PJ5LkG2btNoOAtKM8+YFtjy4p76gCBjJ37x0Af+47Z9Zrp8cP1ziC4MZ8bYdi1uE1/HvaT/7IW7AaQaQfLONupNrihnfDevnXquVqvWSo3X1yqiWpgM63ownmDyae1y9hro066rFRTKktgxGNHU8c+Vv3TbMj4896Q5AZQDz1Qtl04wzv0uRT3uCdIH6gDGjNnsnjXx88N921aj0bJXkE4kK3FQZU5o/jHto+UL6XVQ9JHhSHdqX0rXtrxeqnDzy566PNdRKuH3UnjUumCp/demhXdmwAQJApgXf1cytWXa5+/dQrd23cnP09Nc/rRVOxvY8FWx/E/hmxcc+gnK2WjQsWwYhoIyke6x/0wrB24VL31duOaWQO6Nq1rpNmOa2UjIZ8MKKdJMUjwzPdzcFZPOE5d89xncIBHVP7tmelNEvcL2gHv2gjqdFcG/oUqqT1Ue0QUi0iFZozzZ+qNdKuav6BW0KiR+LTGgiqFva5r74x+CZEjql/1IQpHZXycRqAEfFGkj3WP+1DcFi3NPsiO1Wz+qRJ7ijuypSSnJFMPPqgXav4g15BoQsHVjk3KWGfVIDWwaEFHwJNRRduUrJ9MuFaOJiZIlt94EPkMkMzUWctNm5SvJFFZ2TbKeR5Qacbc5N5UQMwT6Z7cP9SC7QMbOTnskEbkfAm2IiCb5KqmEKYGDy7FYUvsA5HtmLbZzPbK1qeRsdUtEEmIwfS8cwC6wJ+3JyC9s9XlhXNaKIsUTmaZHKqECZajrGQxbgVR4expu8WKdgGIhN2sUEV+GRSfi4dSZ/SoAK4ia7sFfVVdX1OO107Vn4gyIQNJMF/qVWrdLhkljwIDdxLmlyrsH1yvkweJ0lqRReYFNQjkRHJNJbZuv0+4erTeDuy9TGck4L229gxBX+SpGT06vVKR6GMc0GkZc8adfkdQ5WOjyMtWDtBh+X8CEkVddpOREolZ0Gsbot+JzbpQ+wINHwPxuQWgf4ulOo562eg/TY6JuNPzJvBvY3z4zDGSFzrZaqP2cl3BKLOegT0Fw6pe3wA+rE/iJ+FWrvW5s8N52/ChbwRM/yVWMk7McPfjIt4E2b4G3EFb0fCrboQsym8ScH2yeRr4WD/c2CuYJ0xqmw3fylGCbNH31awFtROAKLJX6xA+sJugibkLFGFo0mqCHV3174A1ofUtEFBD6TjL4pm9ErDx05OAbQijZrEZA6QtMRxo84/kDHv4hTIkjSs6FY43BJtIo3UT5LMki5hlwgxmszk3ACxR8G2hUhqnJy1OeJOLRpzae2W7zKGFRpB1vSpdNK1cLBjA1HnLDbwNTIc0/IoKPfdl4w4m61FjTA+9g99dlYfUtIyOUW2XPbGRQojPhey8M7RfWvq8jOQliuY21U4CSi4CYJBL3jT5e1Sp6JZ2U0oeiwMGlaRdlV9ZauiuITQEJVe9Lpku3i5hka6e8wm2+6QKXoIwAWgCgohk9aNvKHWNSBAZ0KVSQgZa6LN4W7QHKJSiBkXnrun3cNEOoMl1Bq7nxlXgStoBWu6pEUqNFiV7d2G4dBlWKWwy/62iicvEKAeWJVWtLqKpVWH2mOdEjyJ9gSwhHTXwsb5wPBL4+RQaz+sdTTx7jzEfAVsMW+BLZXbYXHDZiptNQtFW5jtuDiHF2C34BbuAhbDm7L6FdJ6hsjsvmmPqQd6rCthHcxkTLJJSLL9sHY+mdVjCsYytuq4EGmR1jOHoDlqrUELWosJomtIrR5Nml4waYYgNYcgQDpY6iRo0NSk7nnABTS8RYsYdS6pBNLTEvlsE5kkQROQwF6YG8tSAyTUSMPnk0iqLlrl5wXVKyClWUvnB2jEwZKzGcCk6AW1jyA1YtW58iEFUoy0SOSrcD3SQTI+IFuEOQtvRQeVmq4N0t8PDdixYTk4x2GfTO0mCh1uxEaUtOWkLZhd2AD7ZYajbvv8/q2Q3Aj75YY2gq7iOO7CzImcfAnkjDnAdoXzPhzDJfBJDPTvhF4KdijoAyFdskOY1RzNyWNOjpdO5nxKxfGgtm8XtV3hcI2sDqDsDiRLfsYbhjmLBmC3QtNalWXu4bUp28hbo3nUwcqvkkfBXXLYRoZ1uAYFMun46okKzG7N+WTqttGMdY+jDxg2WoN87K3Q8+CYXN0hio10FQ94cu0yPIaHB/EQVt6CyfBqSK7wG6j26ehr0B/tBz/Ozb8ME5EEJHC8ZhVOWzowChxuQA/qK+ZjTw62idUEmTDgNLpRzSpRMYPWizX8J0JP6gjpjRaLVEknUQ1t7GIMXmPXRtQ90IDDGD5B2uxNmD6OesWOLtLgWVHPInNsEK1748kiRwv5GkRji9Bv1Lq+FwP7avlWZ+KW63oTeqM90POgJYIb3GM4o6O7QxKt96GeJKCIQ81PZPguU6Cz87DDbuJGd0UrKnmdWCPb2zx2QoYZRV8EvUOovIf5ZH0DGD6ODEmewa713di9F/ZmUcurK/uG0X5tBx70YwvQu5ftFfMtpEaH5JB2grtAvS+LXuVLQXxXld8VhfekephKUXuDdVBMM8Dr2DLiHvUNRr2hKm+wzBuXISGjZmnCJINu9YBXsY01T30LoreSvIXgW2NI2AytxYRNyHoqraEYmmNBO1HlTMlsHstcLtfq5pZwOevFfeKd6IFYoZ78WbKvnHLuFZSzyuVy7RZuJZffjTeyzBwP72bE6j7qWwO/E/IdNt7T2NE4R9wDPzJEwR7WnvnUd5SMVH4k9AMC3oC5sN0CV8L8GeJulr0d/e0su3s2hfF76j3Gig/9+uC5UIHeM1LkLwXhS3CCBqeYf8Yfwisj17myBkEFXGaeVtXLzNO3ISqjMJFiV24UlcBSp0TWA8+FijgTIlbxjiAXnN3UtNlRXAbf4gfcK1yrh/PMg9X2yxHwL9vPR9XVgpuExyO0anWzORwg7JoVrayKAB9wBER7AnSmFRAs8RAsRPQuXk7AdVLNtuZvJl/hFKuygDluOZCDd8B9IdPL+P282nNj2yFYX3G1hbTibuSodMvL2Atqny7uB1F32cY/yLfOc2AWGhJxDFn//6WpJj1VEm80whVgp8Q2yFV79dAjlu5Kg+s7knyLOCBJEI68XqckSnhAq+SCHbdL8HM/HY3ls44CounpuMwc0M3eQV++y7gndPnjV0lgydDVT1iMpcOZSAV/RJyJjC/+ReowKJMlPEenzQA7umx/I2AeAxZccDs3BrZhoXy3nf7vfTWcj/3rpZtW3WFwdto6H1e10jqnBrdxagiX+FNqO6+xrl8rg+K1Og7jeR68kZ14/9bMdqmyOWrIOniuwSKFBTBCDTt37LECmPZFR+gl5sG0EfMCkHbsd/+nwqbkIiZnTMrPjvQiUzcwVBfJo6NudM/5lDyibB+sOSNc7f2/0SPX4ZpILh1zosfOp+YSJasTHbuaT2jno6xCI/RB0In2/lVeloZ4zmgw4K6SppQi6onvqZsOOub4RxSTI9n0x/bo0fOp2eaifSazlO5mNNXWolwzeMVHjWgKiFfPQyd/bNp80CXPVPp4EuyEKBN5URy1ejRgNGIcu0SoPfYLxVimDsvyQZnl1fD6GXq7d/pS51LgbsXzy3i+hdfO1NpFy/AycI1fef6lgnLKphn7r1p3lPAohN4rRO1toWQ5+OrqswlG4dXv7qm6C1CQET7lysH/iAre0XD1pRbWFu7jZ9Xt4kT3S/2X7JRNg3+eq/6EMjMAUX/afgQHDti/INj7oA2eHxplcbFzxaYd+7ntt972/qUSHlTHVCygTPyVMtmO7/SJ7w5GGt7s58HWkVTeOmJKLtGaS8BMFxomF5jD7A50sAk87UQH0OGcg4LFM3gaDJXFeY4BNCfG2ZroOnmHhk5MhPoKV8z1WbkdXPwGZQLBCUWegGjiVtxiQjxCkIit4srDF6M+Ge6A8Xr1IElaw8opeqruDYROxVBCIIjqIKk6eCLIp5jWpV7Ff/utaAeKT1EP0XRHWHmEYoe2iX7T6RhhGFWUDVF4HwgFoA6YdH4hb3Vy38k8j/M5vxpPvgY+32vIbQeom2wx2yexO9h4rXoPiasj6kGCtD5E6BQUIww9WasM/kuFePFyfixLMJ8fEo+0py4rwMkTiO2NDtMDOm3YbEFIc3IxU7EMHh6SVwPprN6ZXo93/ppIHhNrF6945nh5vjp9L55fxAbYGzJqw3ns2vyNL6fnGbF6GOw9urieOr+iEdPhB+0nkV1BugVxdX7KMddUajZK6Va1NSiXAB01F6nUNxwtt6XnGUv2wEzWkg87IZ8BY3TzNN7lQ3pVHseoeVbFLk/TO/V1g9ZB8IOzRj4+N3l7t5UsJWLxcsjWZfEYG7PVWp1l3D17Don1tmrmVKy724Ka2+3sCf+klvWq2qw8d+Cxo81ko9Cpc66bYnv7IWQuAGH/XfbPCVpjZiuHOI5XMIkKCrLGzo8yna/D7iqGqgw7/hb5f5xvNq6r56bUExYkoBOZEVVYjbPY9Wh66kJuIS7CQlOp+/9mhtkE+hSA6bgnF8YVLptrs6LlKG+2sAfCLaJYtdkzjfyO0keirNHVuqGnNvJ27g9lbsBs2CaOqkFcT9ICLC2mSHEr9YZhvSvk5xVqk/RvvgbX8bd0bKyanMQLS4hwOQzKRm0St5zLa8WDFFN2vIGiJZOpNw3LAyEfWIx7rSi5tItd/H18vpjGV+fylkRrtj7OnbjOZrNtGK6A+ZPxWhKvwtJagqwaot6wOFR0Vz/M+7GfDvEYjBaBfi+fjVOYdF5NXGZKjO5QsVetSHJawrHPCBJaa0K2QB2Oj+YDFmLPsqwYERTP5B0FDqu5rSS1xokbjkj0/KE8X8jzfGXiRiUS7IlCkZcIVPj7rcupZQK6UZyjmeSa1KlXUyRxlV6dWTBHV7j+4cTTqOvbyi2kr3beiKXWxCWV30qY71E5dSZnXz6tru9J+i3iQCShcal+OiVIprc+V9W7hU6LLZAIQR3kYLoY6pE5eSYCqPVsO0Lhd/DxmeMtsHxzhwmzzuYQwgxZHLgbvof/lI9mcfo1USFPSs8xHkGF5QCBfo2oJ8x4/y7Rz4kKQ4xWoWPrt6zkd/L6QhN8roKtUDZK+KyEjROBqjA0q/dQbLcPU+TQFkKvof+Y0KAwsa8fgHmE5zOV0s/VvjvzWpAHgjjfLdwhYIjLXx897FQ4H2Atn4lrHdurOxab89m4IspiVVoOEPhAu3MEOrCb0KrOJjGGZspQo7nQSN3wntEbV63W5aA2Riau3+a8lTvcCj0Q3U6sMI9U/kUgMa8apfCz/tORElqvy80rMYnAGaf6PX5x9QVXah7AQ0yGnqy1dCablM7dklcccF424eHvj+ScDGOz6G5NkSIq5bfoZhxFZoJsXcL5TAz/kfNp+aYBEECNsrGmFuaRIN01VMBa/utYeltagbH8YaC8H8BcOkxnm1Hzpl0vRdNwExgrdYqiOEEll7G/TPsIg62JDlMO3qLEjduUx269zkx/CeFvr5Yn3l1p4mLvbXzFv8qNK78L4r9uM5rO1PH+LIKJbzQawDcWo3K0KdSoni6T7fhbZH13MNzweT8PVo8m8BZsNc/Uvx0mwWq4mseripy5Zu4WN7HMHBdvYsScPuodg+qHHmJjZHVF/ZtCyIc0uiRlWnkB+BrKRsPyy2FeBV5D4JWmZrRqCfW6xXKHq5ZU3l33kN4h6GvqEr+kv6z+ibgh5AusaryWJKtiFxE4f4h6s9KKS1sr7222IkPqavSNeI1XfRBzdD27gs2voAi0cr01ZrxxFPV65Vkr3hHmCL21mzX50VVG4Yusw4L1KGGO0fDFYJdhB7+N1zMNCXlRiiMKPDyrr7KgmBsUQbA2KoJf5GIJcdteoDj2ZV/lcQHW+lKp1R+4/IzqsZLZejSRbXidvK8DzMUQoUBuisocikIEX9mXpQHQPA+2utz0czrFWrhcc61Vj8DsrHRfF3U26AWb1COFFVz8Tp/PdQJ24CGn2rBu0rKMHV5khgJOCL+ih41SmTsve0x5QvCWK1imXQZ0VbfqnvuaHrrEs6h3TiBAWTLP65Ts3K5Lc5sm9e/1M1R7SB/c/FLS9HW5DumHOquwVKGLyCQFa1f2z0ukJv9XqCHx2TplOzwMC+hOrebDhew2gtm5p5Nr8Xbr+p/Ezw0Ga5S96hahwlbq+Ujc+vUCpEbhu/zBGyBAZMUhKe+eluk7tnM4Bo7AT/RFfOXefDTd6+uu6GFPoOXOl1DQ7b8SxSC02zAHvzj3Kffg1tpWNBcUYseuIl5/rAQGrGMFA4Sn1xDbY15vgpnWKhc5A5w+7wIwBzqLwygcDMNwKQGYYFXwT5lGND6Zwt3FkMDJjqamcoGcGFxwi6y35Qms9iK2IxmzzPPG3+PD5yx8hHmQiK64cxUuSdKOQOlnNzWts9YNcZm9X//fuS54c+F86WvQy9sajvPILNeJs9XZnu+pFz9qmCIGpiWAmAk349CxcZ4+mt93Sj9WpHzbCln9EqQ/UPwZrfZav90SPSbM07twyx+t0v78PHSuMMB+//UDn3cjTKGD6smUqTJtBRG2yIXagTFYyYfjodbToVxCZRtcDs5SOfWC+qAxm7MnEWO2odsx4nnufc/sNO2ft98eFuZmSiSvp8Z4/5Rd/Jv7feNMXuiDn0h9Xp62mf01Ex50pgkrQGuYFYDOgPe0A4ZvQw6VA7tVJ3vdxqAxn7KX+666kCSnhz15x0jyPxF7WerNiNxXyLbvKrFBL3bP6rHS1+zafeKX+L8MLNbdM3drzR2ho4d7x2skjJRRQjV5S9Ew6M9IBK4h7lvnZ4xNkb/rnbfmZqtf1uckgr/gnLqb7zujS3h0xRfp6aetiD8+mOUO/pj4/igzaya368yoHA9pnTIT64kvAg+y103ifr2g3mLrem82ltP/qb8aoU+GZMYlIlKfIFUffgiQ+kK1oN4P8QojD8n5vr0Sklu3sYDDttgOqkoEa8U7azzmGOkJhUGhmLxAgG6b9XDbUVmhIms0rn5g2LPCLeuSYbEeqj60qpJq7ZucRMtSvrSsGO0+9NhxgnqSfx7AXMQ7d9HvdHP0oRHnisOsftQ67N6NzlpKYYIR7+R9s/cFgl5tvvkeJd95Wf1NFX8zswFp0QxMN8DncoHD4wv0OSXYQTeBIAtEC2c53OMiEezVKzDGllPiuRKtfgfYfXqJt+5xPLqsW9i6FjGPNI0V2Y546FmiOgXXpSObaCQ72nLXcB8m8Gmlm4u5zQ02a7Y51cyT82+kxS2Hj4nMzT7MtO+LgTjAFVRRZpL5ulfqr0GPNUGjo+YYV7vDmG8qr0eB0Z+SM0dzxN6C2Nx2JPlIQCHJRhuB+ITzNPInOsJ3fdWl/buKx88734XOlFNeWflcpWQt1mUy9NPPHsfHx7LviJEjv8Yy27uimFoZYNEYXV8RPdgVuZYB7w9voLvyFae63cmp/SV1AfqLLOx1G4j4oVmOKtSViPJJwNh96gF7bO9WIGOpXDShD+/O7jpDuUX7xuPsSyf40SfXMikSi76fw3tyFotv3IVdcezCaBoElZUk5Cc2b7wXiFXD2VXOCI+laYprMkI6n/GiD4iFQrELeYbtEJ6A3Eo40+q/VB9xMZn8edy26s49cYLRsBgwGRmvHZOKGSbUSxl/Z3fgDXIbjYKfUVDZZkBo2aI/3vLFy+D4KkuERUmG4BpG1AcGpAQqaAUo/CWAA66CoBphQ+wA1tIiF+IQdEqiZFWWzLlS6FFYH/0qo9r1zMr2CHRgR3cPZ1IUFXgVPdlwiR7NIwZJABvo5UxG8swz/ZyQC8hcYTV2Wm1Kz9IxRxG4VdwyJeni5rFgsXNwp/XWPKIVrhOPc9P8Xr5FOCYv7ej1YZS3xuFgKBE9mLNGPhXFct7Ozd4fneKXRArDnnr8s8UqD88w9ObP0KWgPF5TSK1pHJ6rxkTB0NgQ5ae7+0iY/qXUh30tA7gX8I2sKdq+dxpkrKeSlbM9IU4WrYR9wzbVDxi/y5qBS8n6f2EfQ+jLlEjFh7NLxvQk1LVvkNeXKRf3gZWQr7bvsInwtaD439iY2oUxqtB65bL/Cya3j2nIWI8wT5LJZIoyQBILjo1eP8pqud1n7E+RsQuHZQRUHAxzcj1hbg41M7H44Dd7VhXp5w6m3PBBfZJtvswjBL3hw1YaSWdqAWl1Y5MI8xteOa+2uZfq6cLHFvXHSvYvSlVrEfvadgJ+bC455TyvtH2we3PX/Mt3hRsvR+5w0Mi/O+s+zc5wXPNGFnPmaOxjyX08+jCdbPQwmxd/vYE1IUIvo7LQjbuOzQda5pn6OTZBNerUzZvphm7FcSskl1XnTeLncZwIN7e1hgsXxNkD4zy6U6mblJKdtGBo9gabSVWrndPqDbaSwr/VgornKZ4lKjd0CHOfvZUiuMqMx9WoCmFqHemAD4X2vjcwz8I3CEmYULxXrUKxWaLcxUVNv1lEb3DxpZjwJTxnYdYH+6bYJ3PiBV+41S902/k2X9jmFwfdJPR8GhckIpBGoAMLCxhxpmDaAHDyHdCyZlAeTfON2fF12TSsEK7dKa/UPrP4f4QBwZk6hn0+F+msrmUWoMaH3fPU3s2h8mZdtcYIf/4/mfC0Qx4A1nL1Z5xlVdQeY86uLOmjxe8jy8krhhqjH7qdHT1lPuIF9uOMV8jQiJZo/NkJigu2MDAn7vTEIHaPq2XqVbsKPsKfgN9G/KJ67H8Ni3g5B2NgrfGFUYr2BYke/6xkm/ehBcIembTY874vKzyOtbHXfLDNMXnim6/nrcIy6PCdpFEjUzsH2hJ+q5NZvIwvTy9pZiErxLLJ+5KThlDjiDSH9dhSQmrQ1qHp+FuNWuBmfxrqfJamL07O8hhpZdL4J1X+LeQolJ4R1d7Cs/ej5Q5YnTN2fDoX/OTcifaP3Iw9apP9ePO/HThuOwbw3evTy4b9zGHeArf6wiUfaLyvpL5REXz+3ANbd5FuMT8/Or2yoELjknzdsUqRq0ju/s+fF4MYcTDeWAw7jxgjIdoihSpBllAkBHsMStVCcNHMgiBE1s8UwNZxcUw7vAmuX3qJ2FDxjuuenf45YlALwzFYkOyBjptFh/ekWEOWqsM2xSlqfDfDz2enTGH+cZJe5UyAaLDAYrnTVnB5oCgH+kBpEmM4IeU02GCMGbSN7wjE+U7sVNkkwam44xjTYlI/Qla1MJ2D5YnuaNYsOHyxSpQJRZ2uP+dk6FeFbfJT1WA35Fm5hdYkf7ra7oWnGMgGG6xSOh0Fn8e5EuQErjsUTlcin3RGYQXWgXv2ke3mY5VvOeguUF4z1bFIqmqFgoYdbWkZfQzHe7LOdWq/SZZ914f+NElXnH+jhFK0GPDwr1rUirG9ufK/JAY2oKb9eUa49JcuKD5yYRG8cjh2qGC6eSJe/E89m9Hhhd7RskoBkyG8m96PdWzC+4mDRFk0ScrWWNyOamscq6eHyHbQqeukVx9cMXklNnZ59EZ/vyvzgujdLnnU7OWUaw27UOMQYcbaZnxzXLUtZWw5d14Jvzu9Vd9NmkI5H16Z+Pql0tB6rGu6wtYJbPOYTKgZgcT5Itj5OtIw/7V1zJWe61yKySxZ+cUYYXwZkDvY1zJRTNMywQmKLEv/cAnsCvXjfuswWhnHK/b6Y4Q/WvmKDlIDd+GlVHi3a59pq8faBrdNZ5jwt2X0mbZ5rG1423QmSJxUXH6Z9Hn0rxo/QunjKWTqk1f/VwC8kmDJmJ1R2actporFUIsYmYT1w5ckwGyi/WLz8J20ur8GnBS8ydvrKOg6Ac+aDZuMyiX3+TkOoHpaX1dxXSCdM2XgPkaY3e0rvpV9aYB94ob/l9/nWNDvqa8gGWPdfHN/H3d4U9zzODMhX5iEbX0VQqSpmVaLYvZhHXqEMJo84+/x31TCCp8KdhkiE0PArfztj3NVTp7MSrNcOT7UglkxXjHway1VGjs9pygh+9JYBawua+ikFmhp/o/To78kLljiE6GuHNVUGNz6MeN8LmvvyeDJihPva0nbsMwxs2VnI9y75BMV477Jj/7tUgxB/a8YwI9m++Clsy2M/BHtiEWXkK8AejM9PDQpxM/nUuiXkbxHME1z961uu0bz9MFaOtjsWT1zJovz8/TzjPtHWeuYfaWR2/WGuV6rNj43x06losswH36MluhHvPFaUuRxxm/+kzBLxFCoj8M96rl0Td+/C72kfvMidcddtDVH+969PHzr36MUg8V4DqgaCUIDuSh3xADxQ370fwwAqqHFMg0Or0HC0K0dPaFmQtsbeMz5N1iNytkyhyn3cH6gzfDAJ9mqpQq1mtqyS/K0rrtOScBgEAZ+LeQbtTTD2lvTzdp8L5QwXLW8lHvyYmrsDLkcAYDR7ly2tBqNnd9Cvz7EctZncn9rjlnRKVVc/fgdq2T/r22IZ3Jv8/XL+lX2V56ifmc6/WGslK7YRHRkAjFSjC9sdMwejRS2lkLGsm/I7t8J3dyaPVvy6X1OAA9ap5rrEvaQmXEqBZODijho2O2H98C+y3eIB/vnfRGmC5SeBne/q/lXef2pb4awa/Z6mx+flygaEmaYHCtudtXla+vO+CpQv1E35KdScms9feZDYA4ec7MaENAUS9lKqLER3Eay53tufLCpMutKm1mogVQw1i0MlcRTODUShODfwwSHl7JmBOlUciAiogrMbm+dRnxLtbLo9eCHQOk1NCiQ1ckhIQTLWfaWa8Hh9D9klG798jeNjwngu5u983xkXVPGoS373ua5MqjbIFknUG4+e9M4smSsaQWghpUk1NUGx1cmxvi2OO+GCGFR7lTmY+qQMbodz+Occ8bFmh/b7ZRh8WF9PlKG8DFmXCFr0wVnEVOX7OqUnMX7z/8ucbhg5d/iDydhuWq4cMm0H+awgwLr+HXtsV2gOpGW5nauvorxiewzb68WOI1Aa7RprLsn8fNdAVqAecF45URqpxeae3Rqwf0qD3t4hzFoWYUh1GgQmZGPCstiYQBCl33rBbjjUq9WKRYz8ID3CZjgxd5MdAB+zLY7ScnzjPuxddfe12R6yyvE4kFFZVg8+F2bVUgxwvR2ZBS8iJZ5gu+Ng+JbLluMP0mrBlLTsuloNlQw35IUxYmOHNnLOF0rvHgYa6pgik3E5Wmf0GWHdK/MjfIe0MV8NYi+4FFvj5k6rxlVEwVidn8gmi8vY27UCzrd8AsjfC2biwPXBdSLTbp+GOI5B0A74BhqRLmDLiPVRR7gE30QP8UNvLKXxC7mmVBNR/XACtkkAgImAAEIXGAjfubNmGRAthUInYwKXA4AAUShnzmuLKw+IjPNkHZDQX5SBy7Dn9D7ZjsEbs1ZIgta3QR1AMyz2jufhmnnRVczlQvi7zzvLB6Bun4w7JLegylG8MnUXvfyYBfcHAHVst78HVPBdQu9+eef0RrgOcgXxV4COpQtsq6K/2RaP7+GW1oDa6HE9zQ6N0PdlvWIb48Z6vfIj2Ve5cE5dPWe+4aABS9O6OwMI8u91dg2IQbVnxAXV1I18TQShpqnBGaRpDEBzvLM0/Mj2JpbDRbClGyAeAvhG4LHZWD4NZfHFctcwEduGHQyYDUOeYnX9auGqhZFGLjpb5fOBgmQJqt2WkcldHOkwmeBNsyGg0UW2ggaQtibMquCI7zM3FZK6NQ+f1+e+E3s/n317jUlk+eYL83jgS2/bixq+7O25Fe4X+WAHz8w664vmXzb+rv6paayFP7o0KpNtHDB5WQALrDE8LfnPlhZYWlb1ouKJYHKu1RBe4iGmt+fq39iiQQSUdtbWOjbKJx3vFBBkXe5NNd3jeM6MthNKAECLoEIERpJ/IeR0OnUEq8t8nv+9uon5Y/RNMMtdSgHFwKtWTDOt1VuuYDIqtqDZ9FHIg/Ypy+M1dczR13y9JJx9TRIPf6hz67UoUrcJufP71yHr2Eavim3/HKJSaP3ROnZndF062A1mTK/+aZ2fRZzWli3nbNarrrKdKZw+7OeCq6Psf/VYMABWr7cU78io14/+cTkqsEl4TF311/GXT7v27WKvKtukc9Crgc8DRxzr319P3RtLceNtExo67gS1R91hGXLowblcU/4ecgu36/wZgA8kKcPzQpabrL4V4MUmelh1fZ+8OD21taFiPfide/kAo8EhLKO0B0uaXIsL67Bp0IFKlxmgdn85NbnxgkoO23cCVyWtjXIqCqTunq14Zb2dquJ/5HmxH09Vcvrh/QpJQAkDGFGmWUFURJ1gStGYsS/yELXOlnE+SlPnxVCzg887O4bnJpfXU18O7U1vSpgWrz+lrT3ES9L/X+p/EkXlw6z8WAvKo/YFoRSAGjHRqCqi5O7SAhD2scEBcq6GKX1P8JsqdAhw4V+pVMqdMro26LwTw+PIZrK8jsjQyIzsz0X//lzaWryVEr0f58ALuWs/skJppt8S303yuKuRuMHpJLkz0MiUX1lLQ364Zgvj01C+k0LrnG/dVSOF8A/BXgXkDKci+05lHrvRoxftMvwsLLI1MXY96lMeNU0YIQ9g6k+Tey3+bio3V2dqweF2wvgBz9fYAs8ALBQgLTQ6a7Ycsvw8/2Zs3voH3lM3OE/rskiF/r+qj+9KhYawQkMgfGOLtUlRhD3xInW8840e5SKJophFBZFLIoRHEy3TJGNyCySPbxKOL6JBcFKYjnDGDk/VnPlZWYP0ckpmMiIA3pYjsQ8CEXG19brmTtWtwwUOWr6UY8bU0wzerGNwvff3Gw41dnrr8cL542RiRJkLN+MPMpHS6TkQ4EDAtK8oP9jwyHzJjWJcsvKI5OKMT0m0g4eK4gLWIDUOmsoIMF6gByv8F9UZjxc/80P3hjk5a5OZB4h8JLvKR0kbYlZ3GHHXEDwSqB9piXUEdWP8tafJ5sABoDsxn9l3PeMeY7/w+sWfzh0T3IvKsl7WDB4zIrZComcVft38ur4oOZWQMHuNDlacnibOLlC4qPShWSy2wuBb5BRQLHiDZyu4wt2og9rrIzQN2fkazlckHtgyEIdBhA7Q8prat/n3AP/Ws4gOw1tVq/QpvSfylQoaKoneYvJzTWwPPAjga6d8rxOdc8TlfSf0vR/bzscVazxGpHB88bFeWNBuUB5VWtMN928apLIOV7o3FXpyJlrbkv6drpMnL6T5/CJLi5KMMk8kE0j1OWkqvInJZu+2Vdf+pOcTZ2+9rGqYvuv0d6k/Z81ktPxxwXgE1DvN75uhE0fn1tdGlKat3Bc4YTLd/EKUXvnZtEA5A8sw/qTHcltYgfbhThpmlswaCZP4iAX783BCLtzGhflWCzvYdKqknxPX/u+/s/K9c+yfkH+8N/LfmLoQQWcCI5hnCeudKzl52LOwiwmmMfL3c3/EEdOsu8DPesyvReZvKjqZ1Wxvqhe2zBlBRcBhRhAKD4YuvbaIeJzmDmaobD6g1tdsnAhwoCkO5CJnvtpokrJQ3KBd52U7NGuT8FUo22HoBAdnuuOxKbqaEmlQYENHeLh2I6WMasIod6ExRFHociN4s+ZZGIvFtie9iFqZZEvmrpZEArIUA/nnl7Fc8x4OyQFHnj3xBifoOhMcjOG6N45caicr4qdvIQNRP9sgz6PJUNFrJS0aFQzrffcUnTBlCocTn3kMRzAaqxpbPz9rIPdKGo685PdOe9f3HJCPa9RbrQcktjDdweD1Xf//f5jRjTFXybB1zbkG52l+K2z5+eDfOjSsORIZhzJ+tfhfEUpY7QvPDq6IOrS3vjTof1vNTBlf6aaNpVCK1M5yuKcbjqBEV0HRzi2sijXRiIFeuSAPXagzwmJDHSGjaDk/lt9lqj9EPlIdLLNvhW5Xr5E9WFck5XVJDyS4b3nohjeSPDkd6/qdg9WltQJkUmSjP+CpU7ayUkLiXej3ZOzXoxet2GGFD/Wdfej6I9F4Ov2gpoJSXJ/Xpgi2jDNjC5jlI3TLMjbnWeOVnR6+/Nd8YppXIUHlrEq3/DEyQbKmKV3nfzu+tl9UyRezeHCei7I1Yc6wf+d6Aqto1veI4T0jb3QbsYcSyq4GS4DdlmUmScZcDtV0R1ArrT/oEX9lraCxUr898LYrHPvRm80wC/7IPSM7G8H1OKLM5yrII9jSg8KGzCpuUO2XE4Mto0kyXInGaUVQ+1ioNzECX1mFgZQbrH8d3Bph9rTsMtXIxqOYv4QQvo6J/vRC7+1lJbDPBcF1YprFkuWMqvE9H7cj5XLECXS8YMWDxHHfqEQoe9FN2dExi/ZeD6jGBRZvPjvUJbvGeplxwsUxWVS8PXdHl4JYswoiahcoF1Pff3+Ma7tTfB7Qkh/pH8CJ/lrO0aH2mIbPaP+W7QfMZ9LB9Wya2ZLljLboawXD2OsfUoG7c6vIog0DOvRuYy2cdiCvOX6Nl95m20oz+uvGOZSpzmOfrElL/1jNJHo21btxkh+8sryr7fbN5abf4P9kw/h0v9gCGRfaNXCUALiz4zXHNgkCGMN6/8aXH/KDvXXqX/yATYdPd3DVtPqxovLWIlA29xsFc0hKb1r8TWplFxZmhf/46UffBhEDowH3xQ7ll8anI/dvDSjuYVQm5pmrrZAxJtnJn4jxtKqPsR64ZWH9Wse1zkvnp6cveD/Tlm7vPbvbHnvktM0zTT+c6YxDWFFJEWsXKAFpQerufq4ykKy1fKdavQcZTXqK7+Vf2VERSWCWB8KWU+GZnyd+CATqa2vNtO3A4RqWw1VMDYJoQhHJRoxaIgGMQTjWIwJElBDtnL/SxqZZWRgwYxp96lmDEFuw2KIpf2pIBvbuxImQ+z/vRowJF5zIWC0iMuU1qLJm5Zq776ZZb4rGhWwZJQqJzhd8bs1WPxL2Z8nvG/b/1se8vJionOQ2+B24ijD8jhFUtAOl8EYVEei2N8/+u4boLbBhmmqyWNZlmo4O5D9jS8+nd7ax9YzTt0qtGlNUlpfkbSgoKd/zI+rEmpdboFWdk7HO9sTC1gjaN/cz6YULNxnOrWMpMbSNzGjgYRIHDX8EM1L5b96RbR5DHQ06y6nN4nOvc3a/+EYh4L671qs5UaSo12NQxYD5SNUYJN+oXi6FExACIdwGIchDev5sK+i+nJUFZSCF2tY00CbmAEFj9TG2F1nZiCcQwxxQjIbgfmlRjYowpV7mTIXFA1UxLWkHB/Eh6KDj1x7plftr81s/tmyx3zzXe+wZ7j0kU0J/2YrlGk28nftTHC/l+CWqrPSflBcaSfKodouJVAOQajp/O8Wa/rF65ar0OV5uR3DvX+5lSJ3vwa3/VzrEdkx1shTH2uqnxdlajvuF946Py2ZTchsIScBQoB4OcIFIBB5kpZjJPTosh/Sa6RqcihCS/OGFyZRmcEbBFCyb96OOvbQNeQxnxBb1l2wZ7uL6Gl8iv0BdzcJ+xf1cB4k5Thtah5tixE2tZYep5Ih0tclBeIhCCWI+edKYuZzYWi9OuqYSXT8QGvbzvh+o/NH9xXmuYCOURIAAhrRvFs++dkIM7iI64r8IjV6osbpC5dwzuDC1aww0fQzNwPhxzEiRSmP8g5/rlcvMLFYYVBRTdGxs3aRbK2+GBZWta6qmyP9bad71kVNI829D3e5J5rkVaAjP68dcpxOWXmPZ1CeMUqpxuWU7sbofFqvMwmbGNdhbD7zu4jOlbUJCHGWhZpdIB2RNbCBJN3TyjAIZlWWdISJhe66m+nmqZcBrMaSxrr3l/079WCRMpOs/mXuFdEJdb9CvtFwKMgevjYYrL5Ws72CJaWBzi+ucUcMNHh/lzx4VMk2q+fdcpxw9VtA4TRAJHTFRYX8zy4UOwqbx7SEbwwnG8l0/QLmD2NCW59qT5SG3rA9g4DjaXxWKEJRzBTsNxG6XMcmRYoj+2bKHiX/PhJzv3ilVlnnq7JjQXYZ3e9K8TwoMowPlwjy/kvO+WCpPm7qAFfYXlyCJ90j5UVWSwkRWVx3k6GYY99I0gxTo5Y9sf1NozbbUnIGlGs9Cy9aBhpImQlXUkqck6iYvHI4uHTnVlvXN26+c4qmjSb34xhyv2nbfPQfqC8o6PtK8BuumWdzhY99zqwP3747Xda3R9n6UFxygQ+ROU8SlBdYIQIRLQMZlVXH6gJlmo6qCgeaibrRomlkIsBsk/AQJEJ2ledVv98+KbBVyPDkviZOymZFC5hZd/7vpHVt0kw5U/YTv74y3V5gFIYOVCHEriHIUg5Dhdb+r9a5V9c3Zfz2hWMgL0+vNaprJBXw6cM7RfjfB3rmD03is8xHz2R/uaak+yzzYJ/9TPnB9eZw75ZGYfIuJD+lok4XyENDdZx1eg2IonJpnMltqCmmasNF368MmNTm49SJNV9ac2mIGOUTUimObJ3qIhXjAhU8B3PXHI2GhQMX65wPqAhAlECaR40MH0jVMb2uyPVyDaThAugpCAb7trTKH5g0uPtGEOr2G65+rOzpb35hDp3d3PlCrkj5wy5J8y4/ZY9gKdKFPFLaKYaxX/mBIFBdAe0kCUn76RJnEWZOlC8ffqH/ijjfw3MYMGJCRcJuO1W43O9MPz/jgb7P6/sWesv0RhFSqwj7Ph94f5VK860s7OtNzKEYy+dKXAxmssbK6pZgFN10KVj9VfMNWdPWO/ffUZRLmRTnpEus33uF2eZr2zWe0ZgFn416nkhDlnMEc1x/cBEdfueV7E8sJJgxH40ia91QxTnMHP1QHdt49xMRnoMxfkqWpGyO5HCCJJgiPROEMAoN4MTibfp+aPekYtZU0eoH6P/Z4a+VSSUqaiICjoQbaCAgbNQJ4csbz5CM2Qe8Nk8PAzMemt2mByZ2nyAPXWU4IpWK6ayhVp0gTFwtWM8XVtpcb4kGXcs152cY0Qi9tYKJ8tjxRfEHIUYHW2MiLhc+ud3Rt1G8c9YpUWmeL5Q0wS6nQfvpkjsQUULeOJVj3M6qOMxPbRKrRMs0Cr892uLFGzCFZUD10PmTDYN4C+eBELB7FQxiZB6o0OYgD912XOmDPjkOBNri9g0Y/Ubzi5Y5M8DFKvEmXjT/MXgqDy2f0RC3mIKnwko7npvNZFpZ5e0RmjtHLs66/oBdDErz1/u60mvSYXD3i+ncbnGoCvMH1Zjodozqo3bdmBHIEiz8xnFGzaCJT+zcrvWstSIhv+zAvGEuoCNlf1/XW5eQv7+DMH7M9VRnlCGFf2Mx2T8YuOwEMI6pdRfUfQoVXjIdfs4LPQtKdhYWu+nmMakkwN7dA7cbWfjeF/RgreJVpmVN0ouyMBkJyhXGKknLQRIUQFBt5z+/I/WiiZ/01yKmP6eY5gKJuDafH8nnYa5y0nbJ/wuXYtv2qwTOjNy7K4VFSBD/gbIwAQmlDNK8GiUsKHnIJ2kyAxklC8NzRJ3IqcTvHh7/Ra0WNLMAvaU01MueR6epHg6jYyr0LOFEi7HdEEUIrLFBSTCk42rrP3n5yGKeNoYEMCOq25t6zT3Alr84PiWaraVuUIeCh7WX1RdMl84Xr8uwpb9NHqdJqiB5VIniSZ7lf2i0Dy5+TTbDd7GGMCRVhAqvTBkQ0RwxS6w9s/IgeZ9641hB//VWEGBAA3g0JmgBDnyguUAHcAAD7T9gV5uXHTMCmNRXP+gH54diXMEIeCOL1P4JMH6A4C9cBPAeMIh7WvPg4RngIDuhsCRFLQMQoi6xJBHGLhNfERJMv9d+sJtBo9ujMRedj7j/n+qMNQ/wODC+XcdB/JSAHyRauO0QFCHLdAALSQgdSOX6EJaQuEcAqT0qFeQviQ+QtsK0c1zzGEO85iMJSlUiEpW4JCUlaclIXipflP97GpSRLeb4WbD+PXaHRiE48RJENCUZ8of/MH8l6+BdH68rwVK6cqD9YvVcsJ+iQyBE9SPwt0FrfRAvfyoUFriEZkpdak/L65hlwBUHAlB0BzwaKHu4nOsEINCt0b/yrkl2sP9/FID0+RBB1bf6Vf8akIGfwolBisH4nb73pHtL8EgTj0c4oxfHK/hf6D9CwiIneiYmXoWkFLVh45c1ITl6clCK1RGIKQczqahWwuZWX8AhniRyIFok/JCvD1wGqm7yxs8ZQjQhkw2hnn1lay1TrZ2Cr2WIMERcHzgNjOY88RZEoiTJUiRRVSftjKjrdwPXBzYHtjzZcgxYrmWSRz9SgaBCRQaiWImQsFIiJkGlYsqUq2CpValWo1KthixJqKkKlapOrz5RrUagQrU/dFewjxTSq7UorAWStKQsJnjiZxSg1FREDRqrWjqS16trUNQiEzlDQ13QWGdaEDZQ+Pqcm6HI8UAJU2I2zhwspJaqdF/VuhObaYRQq4cS+YlRCWkt7BQZVV6F5L4i6hzsoWF/rFeT7lvnk7lTWmTpuHqtupM23Ze7Fk9AYN2oEOEmNNamEKHaj5hUXBuVEKlNUfv0lUAmjizIKfHaoCAStZ8kHUHZogKrkFb3k64NGrAJbcvSfrS1nAV14in2Z01zblSXC0UP9DWXpECruqHQUYhiJuNKtR+zacw1C8WSWIE114at3x2p1xEauHEUXJNIDa2h9enInvbDvAQS7tN+MgaJ95O/ivL3CyuooqaT2EkDWl9AuBQXMh7sk/BKydoR104USlKvW6Fq7VYNrSUnzz00Qy2Ohg944DRgHmcZcsV+uxJq1xAcaduKta2J7FNFBnGK65LSk1pY2scOycjuu3nldSwDMYpA29fErFmg6ktnqrGPctSoqUvZMaCKJDBbKhqsqr3YFFgaCEqQ3guhDkHv4QSjqtXNJ3fH9H4GYdRKYlOS48pLELJI/tuQ3lClKlOZCPXAJmhE3aMBmiG0hHYndEBgVbd69LUCPZCwYg0dNfpDfBUlLOOIILyAaSRJkGhhK9VMuQpeWiNLVuUaqtkkcDuuIUtSp7JSFSzDXVmu4UYI/F6btgtPpEMb4m609gsLadFYV6JFUiGzyEHBVVZFjTDHYHNUR68YyNH6fqq5DjEeswJQxYGhOznUX6JbP3TQnRRHkpAqOWWyda7X6d7MPRfEEqyk1mwiCfvKVhEVDDyAXAc3P6mwSyAmrvtSwDKkquWBX+dR52MfyUE4ak5pOYfTGFxKyMo5kX2/Kq+K2/47raKd3IDFCVzEEL7At1s/fnUM40ghZ3TLTUyMaxBWwg0kS5Ni0jDDYrmfEie+blDwUzzxkDrIHpVRq0StnX19YjVoUrWqLUfX14mm3s6iGece3XEu1k1PVd9LfD/Qaj/cbUfEuKAS7weljMBsx5RfH+ETSm5PVFXr/eZmYIvasVcerLrW9ZXM0EJOW9lDgVuAAKKQwMjkSKZ8VZhLs/hrpYIN7Bbh4O4T5APjQpoYz1XJAlKY6e9zCyVZL6dKZk0yfB20QmfRQ0F7ROyQKjIPsVCt0Y6hL43DTzqkiAGy5ym6qC4V07HkJKHtKcNDddADGgcty+lZ+hAGg1EINUbqkE9EhdtGqmp7NqjrWA5dJzsEQnSTwOx3oVo1mA3iKzoKgdQD1QdqftGu2cLfob2Dna4ee13VHcOo49B+CiEbTshPpJCFoqbElFEVqkqaHgg9WaJBcyDLtiVExy+gN9ANohdnv5wC1aoFhRxqRO28Pm0bYixKdCnRtMDHmIaTZCRVZMmY1cucWNyy8baO5Tir0agnNnWxXaEeSNwEnI67GEWZtmM1xJrZZDEgw1FeGHJqd/TMHbvPIqQ1LRALSQnRO6NNkRsUS6N0W1nSvlBoWvDbEoTt6CbKa00BFz6idoxDSlpkHuXQFUdtNFCyDFBDR/kU0zaNZOWJqTLd2/moigUqWQ1YXzkLqznDzcGWiMKFTYRUsythBvJz++VRt1osvH05jSoL9UT20KCEI3MyOBONeIEskwsiRz/ElblN475ZwQnoeOEKCY4K0gZhxbFUhOhCiZ0I8XIkuJKkOjFNYrhxBZpV4ni9QV4saImMciwJKGeEcsqJJ1D1U0slXRs0FM2uaFm0QYc5AadXPmeL4NyyW0ILHuGg56a//1oyqIurIYbjSy3aVsxktKbMcijfL64clazmYj2vGl3Pltlp9qJBEdfhIjS0Q9WFH8OwDggOoZYPymE0T1SyqC/5NsQyqiplk9oFBIL6TYhYi4iKkRsSklLSMid7JzvYDxQUnahmlyI6mFW5QZ0JHkGiQsJGAxFT0R9ko5VLWIJK7+sQGo8W4VIcIK/AKBVK6uIEpWwPFrCitOsnXzfwGY2uLnFwWnbY6Wp4ub55nDRRRVARJJdwgveEsyZYLAlU3QismhQY8HjCy3WVpCDe/tNSFZ3SVCuGS9ulz83eYmBHv9NAyAeJC35IIfHGENfxKlEWKuFWR6kl27nx/G9pq26DbYos2XJkncAZ0VX0IF8BIRQ6GlfMJETIeKCUxBIVU1ZzF+ISqlSrEfWSl1AnmqpQqUq1GgFBteyUgPqKhE/wRERU0Azkxg/iiiqrqnrfuGkhR88MEFRUUt4f0saYbMQ/CCwG2iHHw+f6N2DkUIyHI2WiVBlzg0WVKFP8dr9KxToHG1ToFkK6SJjEMMV+F1mZOEU+SpGSZq84QA/XuD856kxjaKGFHA+Q31+DuPm1kwewBG0SBCEWrLERCNUmseUYhwiRdVPUPq3EVFZnkEtFvoQFEkHRLynkFH/dVxxSq3bXjQ02QFPTAm2pznmy+TVdwJnSnG4+LeTBx3pgXEoNuIp0CEasmIlWWjPm2C9ys3TU6lTflRq1y6Nr/CrkjTlYXEeSzBCtIUefiuHgCbxkFJKyOIq+Mg8xjUuYmWWmalU1/crejoCAsAiRnxgielOULPLO1ZabokZKqapqGsuWw+V6bfiUQdGJlFVU1dQ1BEXCIid6RqbMISEiLMnjg6hQtf4jc7d8JifPEKdoGFJSVlFVWw5bg3MiOwhCTEBSyupcsF8Tq70xQ4mmZL6BIx5KjT5X1TLokk1llZxma7a8AzEaSkZyMO8Wb4H2Rb8kynH6FRWxqr+vWVc0ii9umlIt27CTRUCuPF9P9uEgXP8U3A9rUeQYSvyLiULCThFkTUs6LuZsVLkKljlQxaUqVKPRaz7SL02MyQpOS7AwWCpWFmu4cQjE71JBt6id+2RCwiL1d6YI1hEVIdcUsDSsQC0nc0ar6FB9DYpKVH5mcIBGIYEChYzgGAJMDKXKBJSz0CzBin/72eZQzwiqFTJmkaD5R2QnZLryKihRVdXRDzW8ZguqIyfFmavhQrREh/C/V+ttyNvgvs/cxskdgEFtCPV2wuAYFakoMRCXSlSyUkGv/spU1hyJt0ASq1TkhL+EkuJwq5BmDdJlnMwzLfVmk+I6O9AkjCGvv3o3HdOUf43Zj2r+4up6AXnVj2VXQdxpdVLoCIqZINKhsoHPP68rRb5KLVjClfX92o36fquu9KkGriNJZsQW33f0qMGAfTSCcvxFjWRiipN8P7vw9yuV2PzqFQau4akgUZaKSZSp7LNplYdYDcqZVKCGDK1HN0pPDKpGJlFWOd13VlVz1xoGIwgZQ0RUTJwCCySp/NIysnLyCooCpcgpD1XRI65Q8wNQ1+BUOtVdA3FC0nWjzMKsgsZdTlFgNLFv5NBiailS1hQwtElt/ZyWs1cIuaecAQlFP8cldY3iUHkKuIvY3JIoExV/ValZul66DN1IMx8tgY2VwxniytSArp9eHH1xAEGGFiOqsZM2iQbGpJRkGinIDGXKWSRg2Y6rcNYeGyFuKYQTaKpiv2xUFWvjrenUQJBtuDq/VqsP9BBbVW6LFiaZSVpaTD35nvh2pkgmSeWm9sNwaku3cnuU0MX1BR1Fdj/VoqxB0KMW6+fq3wSGAoQ5Urw/oq7jfEzimBIzYV7ORctxGFCkLvncmapYh7PpjW8BwsRq9Vwh4pkm0BGVqtNBTA8iz0hh+BCuv0hCeWsC6UXcg8M4x+ycknHWxXR4mMEFd2ttDjn6NelLOvgArsLN0k5uQCRBCqjLb+2eYL8JGhMBURhbMvGBCSI5M6guPqdJw8y4WHKjwV9qgeLiKBHl5qqizapS6590GhZNBy2hDTn6Byav5Nb2PS3B2RbWuVwdq4W8ff/8ewkGBlfEMFWNaswE++kGKWNOLLT+prJWrAuyiWQr7oqrF4fB6+L/Q1xzJTS00+iw729mB4fuExDr2qe9dXTX+ZVr8q4TJcosHqqsDUnZmB2mACGEAyL8gK9aRJSsNLlBIZajUpqpet/cDLJy2pc+hIEZN6gm52kqcc8H7ML3rlTVdJv6eZwJRSs0hojWMgUXOGAxPUA+LUQXPUSSKvtZbyRTLZ3Q17gfEjtCwKSYd4zFoaqmXfb7Tn7a/5jZcfxXQMxBArOo6NBz3dxq4Jfry2g3gkMOo1LvbK26ae0K2e87eQUfyoi7N/QRzaSlDcOAm4YfolDOI1hUloRyuJVxAamhrR71IRsEswfTWKNhv7IVpBMkYNeQR79brL1sWCRNIGA4eg+Lb0qRYo7inMBIhJmuzxfPNPFExTxiZlWQ38++meIWrpJVvQKqt8/hbqNCQi7V6MmJ6wJujXO6QhUqWYW48FSrEfBc7jD7zZ8asA13N8R+l4h2ldjhOUzEW3GiZP0wB8U4pYRKo2Vk4fTqp99QB9Y+jsQUhFz7hxlo2wiPIiaEoGkHtBvuQIrXKVKsW0QyTRqiuzgDc+2C+PROVEZF8zh+DG8cUkO4DrYZiXogHGQdiLIzzMhcKMIlqwq9gv04B3DcGX2Z02idbeDFQbt7+27n6d1eWf/kBu8W+QInS3A7K2R4msbiiHhEpWL7+AGTmCmS1GPoUqLS7uMqI1ab5CT4NILFUUpc5bvi+HlVqb9llahdIuqgITR7tv/tM0mrnGw6CTTRsZpy04jZN9hz659u8ZzO7jYai268ZPTFS2Zw8F6hhowMxsQkMVOljMfO6xwsDJU6FtVGr+tj3ZU22eyGW7iD+v2h31wfi3qTmaGz3SBHn3sxFAwQmsBYRcy0DZQE2t4ZLJH79YakSm3q2pVAoAJ2g+oidu+TC26KfXY7ilMQpUhp37tWp7txbNVl6ax9f/9woBJXYlqCsspyo6qysTswItPAEbEm6ZzUYQZzSCxnUlJ3fV9RSzUne6K77HD31hlDO4wgCFNx5jtCpVY0L/EQ9yFtuj8sTXXs0E9rEp5pG1WOMk0duD0Ad5IkfKhAtj9JKV1wfd09yDSycYPcKvasQyMcUjz2iWwccDAtuE58kAXRUy1qSMYaSZlDSVKl3XVsQTTy2YSseOoDE7lp2XTYoLhcewP427wmYMCCDJtzJAKOQ5i4vTUo6IDws+tWgqmI6KmkTQRbFbIrc1DeqRhiGeIqbr9umU0VMlpS75Pw60RNo+hosrMUVqTCtXIzTjAkqBdqSy06LHEpt7/3+3ZlIWIiqZ10mWQqeKq/V0EpUoS7EfrPqO+Ypi5bS06FIHz2xHWGgawjKeGF60u41ZnrwHGufVZg+x3gLUxSxLgrJkNKkaU9xhtClLOYybKcbhHVMdV9YiOEm+vWqGgBcZyIqA7qdAsdxMT9IJJg5JesSroe9vtFaOA4qklP19M591uGy0RFtkoOt7juO/mZsQ7e5t+dRjvsXQMDOkCj/B87BUBZOm7NDHi9DjSuiNFwYuWISyE+3UiTSI/UEOm0+0xuseT2hHwPKGwPxVVJqnJVloIMmapQ81OPo6FpcrVoW3aa3p+vOyadpqk8K6h5db3w4A0F/p1bhH69OpDLThzAq0iFNWKcRYlSXcvslFWQ223dwnyg+FxsGxflpIpUuxG2Xbkj9/DAWovMyMptL8y3xAoC7lra6NZ1JMVokcWJKQ9R7cq8hSquA+qGqqkbCCAoxGtmBk4iopoh6w15FgpIWk2UphmnHZKjb3rJrcCYg+nEmRVLiCpbLQuxS4ykFYRO+LxKSHVllVNAUooIVcvI0kVWz6AYqUJNztgvcazERuzggOY+BPwVRcqcAxawCpsG42EFngnZrYqL5Q+r8dxhprVDcnU5PdXgaHw/VaZc5SnAovV9iXJ2KqCqTtoZUQcNqSYto9p0uILqVo8+1YCQahhR2thJt0LCkQx1Q9rUBKZKt4uVLPWCczkt3xEkmDILqiUqK23tBmoXaKhOVCPkegp2GSpZpeL2SNZxtSHIrdfpTaxVmXYLUVt2wt4gAnEQn98QsyI2SJg0LljqV+pN4hYkWd7UdQm/BFZd6VxpGzIHmaIVOz5Ptnzy4gp6LaO7SkZmIo4VlczDlTF4OV4/IK0BcoxCM6QvQkTXjPyhmCh0r4WFdDL9apBWB904aZMjleBFp4OP0Nt46AJv7HfSy079mdRDtaWB0DCx0DDiFTKuwUtQdaGJXyiZSlYcNBOaW7Iw80A/ZWkrosKQrCUrmwBmeAyOhGLanqAKaReir7TXapQsHEoklMpRX+VE2Sx0NlSxhMtleQ5iWmt2I7mLg4MhAi1CD708ge9DN0Vr8Gztc9PVi94hhIjQuz5Wh9Ys8pUfmYPo3xUDQGQTxKCWKVAcDFI1GCEdDujr0O8xdCIrmWHMcK0HRLxQen3sabG3hsdFUqSiFP0l5laQsb3RgTgi7rEw8k3HUcINOeg9PujKSiC4K57DibKbNJ5wqyglK0UcWthPjUNaeFJ66Ha4n0ZIRWYoZoJZDu4Ts4VQdg45F9JV3n7+GSZslAWbxcLELNIsVizxo5Qb6hTsSzJLeR/uVpkUWI5aUStZxazWqpECavmSEFJTXSgkypLDiPqG9LTQBarPpQxVwEhoVhoZWW1GJ+H79IA4BmgzwsUk9kMUB14ObnHUuif4eLrpYwdTCW1IoaUTbaWM/R5+Y15ytosOVKUWV+NmidkNoYAg0eKIhQSiZFX4wBA5S+gwynEqba1oKu7as9HNg42CBn0zT98+KfYnbKfDX5P9nTuIIQFjb/jt7auEnK+bO0ejdPgCnkCVLfGnc66+IL44BFbw0g5TvymBugpbQmwEOTZXPaqQarIcfAjkUoWkVWJp3rHbMrQLpSsnr2N5Zwl9yLApNQp04H6KVPaxUGG12JajZ3WHO+2PejXd9TAa2O0QL2iqQVBW0W779e5gu4cFDyfs/lJEbtqLBvt6nzlqBzxrXCfK2LIeo6uRbRT/cXdeGEIiNjOx+lDLm0t35XBcue74UQj5mhMlzQ+vlPbPljLuy3PxJ7mtQDnVfNSIuqbh97cjZfKIIcuX5pZNxwPY3B+dq7kvlic/Ln1gGvK81cBwpiFK2F2UkbEg6d9waJoZEHfINB8JBX04lvFmMItjrlBYnSQ/yhKDZqer5v1zPfG51OhIaTtuVa9DelXYKTiU5iZx4FF0/bMQlYvnKk413zSXGyUQKh1kuwP8Z8vs+lr7QJ2amYEfjpzgrTei+2yDzNliANlVUse12jlIvIR0X0mnqBKEftCmulmEi6MJotGmoF0f3CeA3fl9Q2hhoJwulvgqtqB0yZk07I8DzJpuJFJNTCWEySzpnMFyasioOuMqvG9pJU6gRzH1Iusu7weLeVFaiVe70rVmE0KYg+1OEm05cQkSf9AuTh5EN+1dONgxbueKfKE2tCt6kPgIJZSRUrpn6B/piZtWr6dy8P93Y91WyElxBl+dT0aJdFC0ZaZKmT0ok9v+aJs74fFYxxNa1uM6j6NU3jUugKBbqSFPsMY6j0853hAlvVBRY+PCl67IeCRTBZWOFiPWHJuHBZFYJcraisPqA2sD655UGsVlyrItcjTRlLMFnc69a83DnfLbSgt59qFlBOlWChVFnEpTjAQprlMa2RQfhHO/iiin/DlcQbUbqHUDdEh7XPSrcFBcg8SGq6UjekTIBRhZdIonsRMkzGCBqtSs1N46OfqVcGAZitGQcPy+eiKm0E9mrN/1LXmIhCWkpGX0nawcf7fo4xgMRSVmzRK5bI8km3KHBqXDYARjkIgomSF+EmeSVNOqlpGVC/9FncgrKAak3UlJeXkeie2vQ89yEVetxAb1K1rX6hQ57UFQp34fLKEJyl4J7aGCGpRa6VE1cVnZ9FZpk8UilkprqbS0VtM4uKtFK3SgVwjuS45M/Mab2x/MN30DhTgeFjRpm/ab6CwGWYL2+VQrjMHyZCXu+yo1qToNtslhJdv6RziTAfNfpekSQVD16NMpEHqBkGvIaGmMwQSBJmM4FRFSIuskLlrBrFveLUg5inLJJfGO+T4qqutK1uX09T/iok7GvGuJaA65PbCpL8H+cE3RJVOPJMbp/ndGVJvBeh3RpN7gaxoSAHQ0bv0LdWiC2FnqidyBr8luGwri7+I7FmnQD+x1JvMikiVV+FlvmiaEdqF0tfOzLK8/MvgZhYmVNZzGk2AOBgepX8o/OuLjqV/CkBlxxMkJ017WtzCD8yC9gXc2+Oa0LshlMlVxtwfXCW7gu8BmnBB88ZpqSyTEFokhqv9H15m5zUExFyVRCTXYKw+4v+LUthx15LTaOp/MmZeGdDdZhXSp6E+Nq9KmvYbUHnAQFEMsOK5J/RP9aX+8JUQsoK8GjhmbVnES4yRbIzUv6VoqQ7YFcdo/+FUg+Jv+ner61wbFVCfp3iZlN5RPt16zpaUq1OKo54Ph+H+zy798jV+9sl0QmbQWaht2EJNjc3ztnsKzcc15TXa7ogW9UfpzxbJzYMnxSjl8/b5/Vhyj5hgzkw7fUvr6P0HIRps5W9K+ijx8zc0ihKViNY11CTbCtn117Bfn37l1uQfUg+qauwtyj+LeEnwk36cLxSctPnWQyxeUuFNx8fN0gwQExkixfmCqGHI83XVBkY/noFjIVdeRZVVStpns46QGNXIhAeFBBjo2e28V8Mxun2OSTSdtoTJyRdEarvF/M4+9/Ou5DlXJ20JCddoimXamDqcpTqvphH4jGMAIpnlrYU7MJ2t04f26NDcV/Tq4geOQCKNuI1y/Fkzc+YlR0X120SqnaIEyMVWbfDY7b9fSMDhmW4Tu9qVPzMCMRGhHKfKrt7PnQqhVVsUG9tzsmmcjlz8H9SEh6DOmmc3zZxJqEYpq5i+apQjr/vDfLGq73E7z4mOs5mXQN6+eq2oaHbZ510nz/jCmD6TIFKfV5sSp7/MUIimCUtqTfEdihc/qxtR2VbdqLvDweipsOtg3rkx+IUGYD2+t+4awV01HDAy6tYR37P18DMIDrsywtCIkuVeKOH1S0VLO6Uy9OEhzLR6eyg1kiGz6fH0qUHqDZtaJrOJYVylNd4TY6hh26mcxmhZdh2d2y9Erm0iPEb7sTa1Yl3YT5FcTgRbUCtsi7ODeUVCnMWPgzm8d7JPl/JnKc5tx5RKQvUmSX5Tu5rdWxazz0hYP171fqP7N4GckJlWzB9of6yUD0CaCP119rngPW779SaX7aJzxEJOZTGU/OyeRpy9Ustoe1ktj4yAcV0u0//t4500M/ZdUsTtGsnziFDfAQpRi1U59vELqjY6++2F7NDI0OMVxLkejuOybDRWb6m1wOr3XSj2c0jGaflfLAgjupChDIFwvxxOJJCZKwrQ/cZAQkKc/zIHdU+OgvfRMHHPs2brMafEUIinWTkmFnH6/qkjVzdQSUKcwOn3WrRtsWrDU4u/0TbJN4cz1PyQmU79nVfrV+5Su0MxzyNWCnj75Jy0VaPUWkhpGZEx7BynGgn7QSiKdpscpuwO50fmiHLVwSa5GVddGcbRpd6tjP67BaxLEyNoF2T9wGAC+8WKscCzOuVq3cRGf3RNH8iUiL14mKlmgR5lzqKhSwba4U7+DMKAIjYoCr6iEFJWZI8R1cNOUcVb4QV8hw19BG0RH9FJDjTWV3LGnrYUVtdVeR13JUcWVVGrG5BXvgjZUWVXV1VRL56+eQTEygf5Dul0TzB4Ls47Xxg4OTYc9KhANEpATpNi+llrZUPiSUdGrM5idOIq5Xsx7XlBajKVRLL+ycfSv+lkxuCw48SGsA4lL0LukXp3uu5QtKlLVqlWdRkaaRGsaba4OQIIsXHoe/YkMKgoyHGIkNa4JUSpi1LQSUqsyZqrmLEDsAuoOLhbhTnApiBOpUxZwyapYww0ECIWtRvfNOlMfDvVGLCwiamaJmZOEGCQlftUK0mHSbdmynLyCI8nXpKxBo9AgghQHh1CkWMkpPVGmXMVr3/wuydVAtZo36FTYrTLSwiKmUKeuMnJISFKJNdRbQgNHaFpQZxrURVaOHlq11b1yBCpYoQrXcUUqWjHhIkiClCINMhArro7+zON5WRhQ9E7SXSwrKVYhjbohQ6asBbKlnpwzJxan0ExzEXJPizO9IPr6bUn6TgFX0xgO/RBdSbESCgbTcWVyHVPkz2yDWxwLN0sVVRY1G1EbXYqz3UPDfY2TIEZWzl4rvAE534KBjbgTTuFz8aMijSFWopCz5c+hIl8r1P87LG945u+RnJKAIJESFiEN0rKF3rYkeXt+rbleWjLljYy6xRInLsEfwR3dklSWNI2WpfPbg6STGjhTMWKiYQpi5ijr4lwHau7Q0GoRjty6RFMuQtxIFpudkrOIQVtEK/In4Dbpt1ZiJ6PEl93/vpVBn/7cGdrzvrB/m5ePNSlW7+7hQhN0NMSjNnmseGLQKJ/+8rSJhXlm6Z/PUTG8cPA/sR/3ItAsIkgcOe0LKqpsABtNi9DraoSZwzC7ph7mSPP6mhc6rEcWxOJHWFIbuKyjn3ytfwkO/PpwcMtGz8APqiDRUqQ+BfmLkBmURUI99r+rIk2/lL5Ahj5iM1+596rCegR7s25p6WgCN11HeDP4DxwMCD2G+8D7hUSUIWaihIRP6R11IklEXyMlMWRV1nw1d6FdUq1Qo+sbSqNRGVrNYWh1g9AOTfUdFpEswWoJrIUNCIIMS2uH2gXsmlZPNEocApK98+eXUN9PemZ4op9MyGdSFKySyqBmmhppVbge/J7olwxby5iWX9ZMbmbFIZ/GRYgGO+YA++Hdxw/6GUWWuPPbFZN8TI+UmTCvyAIs89WKtWaTqv6cEGwtoyrC/KwiYVKw899ZiduX3XrgQz+I645JUnnUYN8JB8XRwakE5+phRlhete2brbKbKc91lFuI96HGBbi8Z3DLLYhwJMcworUP0bTGQn7AryKCb61o0hJFOguZjGQ3gpw2TxbGQ3xlG6KUgLJYAdUsSznpNMZpuqtVbTpSJ5xanDXEOeieFBcGPU0/MZeKAXMVifCkpv8QEC10tRjHOZF7qrdyzrCfW38u8NxR9lAl++3V2PyxCTI0auuT6tRrHw8TY/3KNkQyI9XakdaofnnS0GAFI0hgdCx3pZhpIAl+bHL2W3OfrldWUIXtiNRFA9QrfEM0v5Ds8+Fdn1UUrtaNSN2VkSuKtJQzrYj6eG3c5agRdk93CG1Gukj6zhk040QmYXaz9AanfVSaoWK/Nc1ueRBgKOPKxKlILFPRumS6cop8lKBqlNqgIVrQLU6eYWLE4wCJnViZpSCrVlP3YN3GSW9dA0r8UuhBoyLmfCxNsJZD041+O7Dunw8HZ3mUAs8FaTxK5X9W6N+X5jZE69mNa0/4tLMMpEiyaoyUJRfO/KuQeOGzr4pCDooS0st8Uarvh5x6MZQsVWskXUaYKX8SVpa2HAG58uRHkPIehkphRKluUKzECMJK7wT/BbJYFyaFmDLlp+KEVLIKYg01ajf/8u3qd8QeUuDBRS9+ZbDLrbhSFipVsVZqBMobHvp4xzOCbPWSwx2p12v0GiFhEkNUrHIKgqTJ57mlpGWqlZOvgdFiImbhoDVKE6BAV9QQESa/HPtxaSUL+Bel1FlvdCnzgvzdqlC8N8ooy15WftSRl+ZFaFJleIIg29xEQlzO5K7x0Z5oheg4/dlmqt55+ZjMd4C5H+KNnV7KOClpXyGRDX/n7g7zsh/VoIwjOOUrcw/vVDBWp0vBZSavFV2gKxgbYbs/rxNBunzhU36YEBCRPXw3iCu8QTt5AoZ+rf0F6kZClmCNX3MrEfLkq0iIUGHCRQQ55Q/FFJGGGLGVI69Pwh0WIUksZYQyzJuf15WoBlHjqlfjZJ5pUbXp4DS5O+pUM1F1TjdVXdDz07fqkgHqiiFqVOOaMDWUKa9sLViCFbOm2rCNZAf2aTmAa1VJDK2/OnphsCoQQdKMMEOJYjDHsXCtVdnAzhUCCEHExtgnu0pKlVVeBWUJKkVN1dDSu6Nr77Ue/RCDMIbXxKxqYaXaaq+jriBUMUmkKcwyitfPq6BEVVXTTKTFyZ3Rcw01VqiJGSxBrCraitrrqLOCgAiS4exQiZof44bg8XGdUZQyolylqqppEDajs4dCjTVJDy74YQ9N9w2IFx9C9xtKIiWSLKWq0qTLkHmyTkj2m0PaWkCWXZZX7KnHEHjzneJrBpCNQDf9GAx91eQUFcRFD30nPKNEtiEYRp4ioRcYCxMHn28JCTPV/HF1EwRN3gswzWHssrSdPwpnrLzS+g0X5PKBq4FrzxVUsinB1orhLCZQp5HGnKQK2sw+mkskI6ZWY+AQRKsbceqeNv3WkXSOF/je4+Yf+ND0XyYhLRifiF5tokTNIC4hKWU9MUyPVuxgP3B44EhIo7/14v6Pq/080OCRjAajDtihfI2278SZMSaFTkipMuUqVETZihv8GSvW2g0ILYVujUBJDxQ2oUVIFTtUVngTgzUEmfKTA4shSQm+bXR5BbkkDpHio1JWmmO8ajJYKYQxHVAZimNCvWxZBK4ZdMoXk+8H40716twOXKhTdsXiSrDaIu5IJLYb8WcQ3NEXrVQEQR6yr570yoHpryfN+nO3xtGXMn/1po/73b36ddS+Hv0y0l8UoEAGjf/QcgUb2inBfRlJwBCK0LGgXq5vRsMZapEkWS4Jb2HOiEt7KPyKjHyI2Lg1S0Ren4HXtMc1KjKis8Y4lhnnkC3ikVEJCV5LYuWOY0DkPtjaTxwoafkSSviuE0tzq8nTsqZE6i+BiUVynXeaVnpALla1DGxKVUZkToHhh6xXUmCRPYMiArpEtl0fWXP0grmIvLE3Z4UwHwtcABUiDQ0Ic2ctcjFQwu2gfKrotdQ6vf0ZJ0gLzrI4l/8VhcQMKyc3wQKa8EYVrKziKoVqYzINmNpV1FxU4AQeAOJPfltqFwzgvCSxZdSIgeoMBepbaPB9rknS00i1qjuy4JZdDWokdCYogmaw9IufqVosgoXLOq9QQkdT7qNurvfstxlsEbbWDmUk0y3Qu2jroL7NGlqgdmMUxq0LBrTaETkCPMFP0HtnQ5v/U6oCzNqFbmNupwmEiZ7DUFlv3w/HhUXvzmRtVt+5f8v4aSfhWiTJmAOJl0gOHoyHSMNo1p20g+i4uTGybErST41qjONZWNioHHYnEkzQBSc3SG3wlh5ySFNo+/aHDobTWN8/p6FO788csEw426Ex4NyWB3LtnPNL4ILiosUlcLnH/HWMtIlUmaBeuRTnn5vF1Rq51vuy7qATaiuUG8zNdXMrDtu8fC+fVqi6SqioUKYdF483Qr8XwY5jkEeSNyF+11f8vgp3u/UfMhraE1T7PFirDmPsPfSJmP3XkZsHOuZJAmeIMGrwXwiqYp7W6LNanOXxn3uBz0UX/B/O1nK+zMe1Rnl1eAHrULhWPl45Wvc11MYbS1CiE8dtkj9gOznJR+uO97taH/CoHorjXo/um+I+V8FrFDKUYb8+CfwPJch94lQVhLPYM59eLiU6FUir0pRIDyXuMN+hYRCJxkSqO2PcPzy7SjynPIS6vojEy877orKcOOgwuSVOJd76+SotX1u8VnpjDIksoB1xeqmNQKeSL1VI4ddbwUjZnJOWr2xC3XWBVHFB+ItS91Caq+PWA9LeJyI1lc5jcn53t0K+7+Wfj7+v260iP2yW6cfFYJgEYyrg/HHboOUxN9rm8l1/Yb4dizQJ2hNh4LkS52eMoSyPYv9ItbwT49bLYE1UNJuQozdgx1qRHO2XTw0l6VI5+dngFwWutJ0q2wF3uYbq1JVHk7evTDtL9FltyL+TCmjPBCBft+aHBIC+RudO6IVgIoMwgUkVovANECXHKtInirZMsWRUUxRnS1iCfWozpBrnLGK5WjJyU7oIZcL5eU+ipqns++p2lVscmVcreTWHwtSvoKKiUgtS5rd59V3QopKLgTBUvUKoVtzq0wyYKA1qVuePazpeXKB955EharmpvXvUueCcLELdFiLjgTEt3/ZQIwYQ9Ryh3zPptUWDmWH4ezW6PeS4v7kv3PlpvCaudBUtEwObsCwxILFNxnVXTDsWg60ZaWaFeWJeWDz051VxW1BYHtLUE2xXqw2VtcZos7cBTLUVQG1cZtkJFvYdfRyC0qGWstoxqDQdg+jUJznDpcpU1xrtdhlVRPfDXtZBxFFzaS6AwnumbIceDxt4vutjzW2vKqpn2xC909KnHC+n0bc6/Sz6z3QAx+N68Y2zUM0zsN4ISg2uMIYgQn8QhIW3SNC/puGqY1/i0/0ZIzIyEorSGKLdl/kFY+aK2KlxwnjtBGVwFibuqsaYdItwZVUiEhTJtfRMcf3VFKaCaScVc03T4zr9vSoC2oREEscD0vOTnSREYy+yJxLmS3dkTGkCMtu5fvv/emelZiF7tEfqWgC9AXJ9wZwmmHuFR15qPgGLAGw8owQLHnlQONQzq1vCalMRiu9Vv8ezG1jSOUvPreESZdfIWwjLt0cAjbFCUbCXrvS7Cqhe/qXWsBZiEbQiWFeE9YpIYcOS0ZjqIvP29KoEUbmJXivxmmBTEJu1yBdiS1dsvYxss9geZwyxox10Pp/29O5hry50v5PqWHuO7h0rVy96u/btMKWJ6mnV74Fe4nNQSyKPZlMHRVAPRd6HvbueSVXNHOnWMuxRcExRNsdJ7q6gxjlRoybd5sVUj0pXI4GtcXr5nFkOxO7KnhQVPdah2SsYtbOs4Fy96uD8crRwX6yyDbjU49/evlMUupWkMJYd9a8Hbyu+WP6MpNqj3rFztR2vCdcv4KKxsY7MFsLQYfnYPMEuurdFbB3q9kfqLmbbxt87zJ0g7NaSUQl/2k/RF5TOGWPv97p/q/J+sA/XgQ551ATdBPYryWziY/IJhez7Af4dpdWu4jRBX19lWS6j0PxX0efARdOTdvPh//U69DK1KwG4tKTrQY1O9RPv5+NlmYkavm4iWw6wXNaiSin9C1291Wa3e2078bOGPobzH9JDCXrtjwU3yAU93+sw8e0BRh2Tf3XwPjgn57l+uRJXP8GX+fGSLWk1fzrTkAGEnmUt+lsCqc1Ry7NWIBXatFHrvbohexgraCbwR5UO0hLaFp1a+GnE539fg+dld4heRvvePbjI2woBwxM/tF2QrQmF/qZExPoFyHutiShwyh86hYiomDNEnu6pLqBSlXLXiCb5rqf2joI0ZGeoiFEqzwVEV2pRlWuwUQTQ4gneMVtyB/VCwiL71G8G8rgqKKWqqquRPbm7SHsoOEJJWSGGLBc4wlQAChQqYqyYUE1P2ZlyFSw1K6hWQwi1QgqETYJEo0v5zcCpni8cbIr7K/1LLGgbg2A+QQaBsGnbQ2SDZ/6WL6g1IA3i+wZ4zyUCWPFls/Up2Q60D5KD7OLLt735VpqOBp2kOCfxLHF0Qbg2EgpKTgurrFK0cYdwAgXsVAdGh0Tp5qd19a9Um7uTeA66d0JQJGV19ZBneDWmkEZi1IEfklogbzKXW3TlpA/DN8dFrU3gkk34dSYIoj8pwFbVxcPAcqb324tBG5m1ftH8Gmd5B2l2SV4Kst3Zlh+Cwzu/LYIQ9OCnFGobhNyahaxElmkMy25lcbinCEUuQ45SClS0bBgzE7HSmY4YF071E6Skn/FgQnOaWQhgnftfJ9JybxCWgbUQuaFV28lgyg4j8RPtlSJ1hnFiYlrZLkLdIKbVS6PqZM/N9HKECDN2o9rQGcX+og52cGNaO5xJX7Ju7UT2gg7eReCXoDMblY+djBZHPWJv8YB2CG7fOeGMHCwoPLkf0u7NgaDvLXci8xLTfa0cAt+D+R0iEWpLv3M9YsHEAkzwdCFKYjIgii5bMUoOqZF+0IPF8WyVKhFwSTLbLetZb+XEil6yMh/BmlXnjSvFVa9q2FAP61ap6QCrgtoPJRsN0Vt4XUJG3Wj1WT+6Tnh9UkaCgdPYEB6NnX8aFUW0UiKb7gj6g82phFYLW7XawqbX9XkDlQChV2tIk97aFQb92TDO9aKjt85rl5UXVl3uRrVyYfGiclH3MjzKTj3MLXiqgPevfG1iZzK9NHsPhr8U+8qxXziw1qWiW1lDHs4nJo7UIowCOSoYmzYXopbZVUU2HDdi4piqblmM+LsSNKpJJXoqUje0MjoJvLcjwMQI/IZPlo+/b9U5HR4zY6G9jq4fc1+HboljNlsu5+aleDLO16UpWZ0WxD6cYbhtnBKsayxmfzBYbo9UDCtNcgu3zBbZKP7zBe/tUxEQLud4oT5eLltMdIhYdjHX4Q6ywi/p7NlX7e6E/4DJ7aqLg4R5WoWUlU5pyU6rXz2UstHbyrXGdV7AfeFDuDc2UUmwUx0JNDevb25R2U443v29pkb5nBynRO6AuyfCP0b4fHA5GW0f2Ah6x+FSvr6OHMeuPQeCC/cG7rt5IDrk0cVh4DawLRzCBbuKTeOx+CRZ8W4ogAW9+rfJv1acrsyzLZTkwlGXqEyvjcAnq+nn/k28pfh3qKxr6qpSkM3h7J4XFvSgjs8L3Py750GXKEH0OeFFHHkK6j8vWVfVKgAfaEC37c/tVNfR2rnlEUbY/Zstgc7MXIJ0u0182WnYnH7GXTKKXuVckkpqTAynx+VS87LDIdtpOIvv4/Bww2floN0oeXeDj+GUk2A+Rs6K8flhOOpZwlXiLp7R7YklsS/4z8sEngkHeioiE7OsSOKvpHAscWHPhj2f9oIRfkcMe3nlW0i8ethrusFvNnpfK7vJWjhnnkXig6bVLbHJqVA0Xm7nUi3V6rdEyj0vYd2oZJ86bdAcL60qaP+k0XUsrrHUXi4t8a5jfo4v98/oPcKHunqE1CD/2rjdUO7LyPM7z7NUH2cx/Wfup2RHsoyc1hfEOT93bteZnRgZum+lkbt+Z2BgRIb9Lw+3BfHD00yMPZZu3A47Aohr7Xy4caQ/w2E/aZKQOD7p11BhOKbfCQpjxxgm/GzLyoEGAN/5eGwft4RMUpkry4n1LoRsRQo77dYcmbLZp89zjRbejLNiD5pB/ryEil7i+OX+F8vduKaRe6t4MwqeE0y6K7wXxvcN229Mfuar5iiwtIg5NMGepQntz1yZsXSsyTebR1CFZWcR/3l+e3zRROnrOCecNOzFFN0IdGxWmpjEHe5pIOwyS1Oi25A8Nqkq0T9NOmhXJnuXt+Mh+yPdbOsOub48rMTyoEJGf31gRaZSEY4uiEQiiqU4lbeB35jfs8fw3AkVVKwuJJrdT7Ye//wRX2wPF3KH6nX0dquJmGrzWp3qkDT27W5HaOa4xFkebgl/KPdS2VuWmaYlbQWGzrEGrYof6rIuh15PAxmpX4IGhgz3jXaYxjpMLiJ9S5ToS5OlcJsG7Zr1pmcuN80FFnE94ZJ+KjEsVwqrpkU4zgxNgNFo6RV3bclH63K0oQBmZrWt41yz9XsZsr23n3u/R8TH8d0cCtJxXE7h/CczJ/CR9vmEXOj66EE3ofv1zU+vB+PFhYFGBnTzWN8Zb9OfHh707Coy0rzoraL+MFIvuWvdMvkS4fMwX+N2NujXOf05ArowDy2Jxb7I2Wi7ZRFUPYUwgruF7INDFcKGRjQa0XgJSV1g+JMtIkrM9E1kR80dk8lCETks6tPjQkYlR2Nf7Obcj1lfxL7OrcaI6yJdBPGy0Ijyx5YQGeDjqHrsTOxBKPYkDQu1v5v0JNktecmUk33ZipHS89e0SqVdFaa1SY0jremAqJ4ktTPyUZGXBZHHQiYQsb2RBbC+MLx+dL5FIuuxJpeEyD40aL1dVPdcOZHbk1lp5MkK5I8mngXsQnc/L58Flgt53+IMs6ih6sridUdJt9Lwfe9NCfhxNlMuiyvWn4/U5SHf942K42T/TLVfubes6hOdS0f1sdXcS1i77mppxDR5yU7hrJsZ9T1ZbTrdmqgOy7UlJBt4v5GBur1mFecCPhbP59ZA/5hdt8caBuVjU+5oTmtxq7gt1XI/LuE9u/0ph8T5BCamW0UoXB3sbKKELOOZQezKEt0rRc9xzF4Qb8jfNacnIhDwsEFNp/mP2EEiQTs9eVxi5fY/TU8HP67XT1ZFyN6oidYZaQay1e37oAiH9LGa9JblqJnimOdSKW8f47vXB6uDzWKXGB3bIOhW48j9D4NMVP1ID5A6KiO3LLAvq1MRNdH0QNZuZvk5/aP7BwzR+xFydHzrUBUrRDpucgsochH36vRveKmD/pm8JEXLpnuQZnQChn9vqrlKaELk4d+7cDDk1KnPyh3l3dzvXaEGVh+tkBNI/2hVttoEG5YNl+ai8KtWUIyUTa2MOfIUQrYiJcMyQ6k4WxXRX+OsQToXLBkwqwx4ZrbW3aatBJ0gAboannuF/HOwxQlG+JwrOSItOIaSO5ITUiKsVESElMS+Zlu3070HzhGk+3drFLu0+lmyqiWOC5p1J2zk1J6Q+h7CHViAyEKrLNVa0TWpIVCCaG/C3nYz3YsQX8XCejMJTvSMjMXF9Cptl6AkvSpURiAtY0t24fIO0IFvkfSPKimd8h08gKMOHqDzcw0FCiNKfqviZW+dMrNx/V25C7gcUsXaU2MItUby5xPet+hZwiJB05yqU43IGOqCvRsPnKa6FVGMh+zl4+JCrZb1R5n46awjRD/aobmnq5S/8qg9FddpnImGuECj7Nmd7HtwFW3aY1yy++b6ovrZ368ABTpgoKAarBCFOgwMt74fwUhPUYpe8B7D14Givx/LOAfj5Z4wcRsCGL87aM6UqKQlgZI/WU5BTa1hSttPTyUIMwaLF5nJ1cpSwH7aOLNJ0O/nIHfeLjqkvP18MoyUqQJmei6kBSwSFatEpYKrTOWu8KvSVYjq5e8ZnJsWqUa1QkTd2K6TX7leBfKy5kXDzC1wo+g6qhMIAtX2XX0BpElCrkxlFAKdzddIqFE6VzQmyPFOZ1hN0ZzwxiiRpJEsJFtyu5Xd9owXHONsnydGVBkdPbiNqtNdUHdUXrT4JBm3afckECXr/IHN5q9q91L05cHO/nlNTqSai4LtqM4DLBZ1LJYJSY2nwTs3h3JgmHoYKqeRpV6McqsznUzwESGlJRQ8g7KlxFiC/pfxWzgnQmyTXX5ELe1tktyoOTWNwOVzui4DiDPhMTvDAthWmnOp6J2AjtU5r6SrBS4m8xK8zAqKX4+N2v+8vDKkGa8K18a5vunYmPa7Br9LporY7PxqEVrH1lxrRqZRqeqAUizbEqvA/eC2JqRn+q1WIWOsh8fIQK5r4o5iaZvaXcD6tOrin35rD/vo54HF/53wwB+XyfHsKKE17cfhwh1xUuEoaJzHHfZz6MR12n8f+HRcfEYKCRPwYYWeD9EkUe28n+mr6J/ONSYkLyKhnKyjSBH9x9+f0ZHnJdSmLeGJ7Krj1cSweKeNVv+nhwFvHLytC3cTLwmle42BUzcub20UcZ7tNOXflEQ2jw3iMTuOOyRwR8drZ1OO3p8UQbFj0rIX+O7Pd8K09/4LEfopk8gPyPZksXITidjLBEpjlNDOu9dxjHXaDEJewdlJRP0g1b0/a5TT7dDK7+TVyofI2xGHcV2DHHquunjxyE/2+VYOJT+o8vn6tQm91FONxUr2V7Dg3l87+EaB7CfJzE7OXvbrrykYb5cwzPyhCPet6TfKp2WnIrXDNCVMCtM2UW5Gp+uRfsnxbsEjc1e5/QyBIF56k50O73XLLDJEYR5k4Ac/ZNE6fe4mYkgD4+9LhdYZsqRo6i812wFjm12kkxFg+AvrKT/WTqZ+k7kIFS2KtUMWshyJ9cR2p8EuLZtdab1zuPGpYEYlcnr8nP305YyWWeiyQeRKTLfrANzoDX+tdNgloucKntF58+wIvnkus/gpEAdBq0t0KiKCTkJ3xSH8mvTq3dyxi/IhdTc/R/PFaeYQErQMkes1u6jbQLHDoLhQQkvS+ywpSodIRv2UVZRbJuUnUqEgvp6B2RUllGYJdUg5vmX/flL5Gcw8umpuR6HWQd+wuluM0LB619TlR2d5QAsTtsXaBB1jwmWQdKUn/ZOB3N5NOgMOpB2GeYJkVNQeJcr/vGzswWSu3k0nYkQ9Du9NebbMwnwSoz8s5teB2Bz+yWGZ24XNScm2orB+X+NsSdoIm+xA2FIGHtso2dHekGU4zO0SspQjnILm9qB1Ted8p/ufSScehgsyny66fOrNIRVc/dndBKS7IacATSBBeKTkhmcHnCB44fpR9UbF+/qsexNcGK3mIxvQPoj7sXtn94VfV7k3E1iC/qULV+8B6sy5faggc7u1p0RgkiCBUFAEXwdrJ60W0fI8/gGv9dZE4Rokesw0KKythyDhXYQ+EPa884ysI6yfdVXIvzS+aZTeQabPJ4H/AHyOABF+DLTFETE++G32SFoqEMok8SLyKVG9Wq+K0VkoCcYECZ+xOQI4g6FfccXn+ipkLZLVj/FZIIMLJh89IUFWYIOFiYbIZMkklOQBcodA1Vo/vszLlIOpqVRkSKFL/kYoTSBy5ma6RflUghgEZrQpOmUiizpQ+4tKb/EOZlcxN+RBqGZOHHNzR95YP/SezzRNZbHDrn8XHQETm5mwpmkRx4JO5BQ+/etwmVH4DkYBDrI6aBnbvDws7+JYpKJ4BUvA0ipIjOxneCroc68zBnWXRnjp8E3mKZajQRISBLK1sMzhH1WUCvCJf6PcNbzvh/WyvIgq7DOqGFT+wLlHrzq8m8XqWlAjnQGKtYsgojjsudfBlVDz4Dm0z8Wog5+fBorgONZRoA+ZvQcjwLLX0yOIrkIrCLmEq4GNg0CN9WiCNxX05cFPT6HtXpWmyWxpK2eAszerRT67rY7R2z7AhDbF9hLAoLc8NzsMdkp0ZagkiNkN9Rh7OjJSr8EFpSeQ+7ZHde4no8GBEA4aHFJl+JLMNCIgzS8vRzXHmOMtxMR1T24JyuTF/vio1zu/fH9W3er11n2CUZ/8E0CdfUpglyhNx8x7m2ng4mq5rD0rmOO5MnDMJzYLyHxiCrwAox94cYCli5lsrWViO+Gv/nmFNEW08ippjSCL6+DGpVvez27ftJPYOmS73vfWeBRU2whtLxnjd0OWkA41M2PnmJVPn2tXrDHgLi/L5+2TqmGkP+Gz/RRB7OEVRC3ZFUNOA0GbS49NYfsTlPb29xeqyjjoq73FjCuZh4plJIiPMtalAGd49DHpxH9B672iNwhbIU8X7TMIzH97GOfHMNYPXqyc//ukS2F5lVbXuzc1dnYQOq4bt+htvARCHI2dqJ9/top3bfI+iA+5f3MRlr9rT7eOdsfZ1Yg45NCNbpRdPB3XliI8AU9PzoivSEAMC0IitbYuHXEelto2mEloRfzwp92JGMTUnWSX4qApZZXlceHCSbMtE7TPWJx5gfjDnzVYOsPdn1fki3tSHHZ/mR2v1tRh80ne4cTXbgNZlKRqtLy5gMlvSvQ8RcrAA4j/h0620EsnJ8XEctHbdBGuGXybJSibU23/cOpvhfu5gyYXH9JaovM74fsDKFvdP6TCPNLpl/bJsM3B+HvueV7GDgAYHUg4/SPLh0zbT7d+k7mX8fyQnS/ygMtHW1A3v6IFJgsH66GSnOHhbA3u+XNusk+kT2JziEG1x2MPF0P7cX5+SkDO9vl5ofwSFB3DuY6d+zmIx7nJk4W8pcEnnbtngp8aWtBwgUMEdNhcEF15QCEdwodc/xG8MzIHRW61pdvdplPoFbRXZi0douliyw6QwyBHjRTnIvG/R5R0R226FI81pYMoc4L4S4mfhaaso1aFXKfFo7A87yr0r6PauEoI/PqCuHn41yfwZ4Vid6XOQ7mhwMRG2Ke9jj/OAL81veSu30tb5/adCciaHSpo54Ue+mm6ai063lXb/gFD6erSWBxExbG8W8p/ZATMGK4Jr3LTrlbSMrC6KmjZELWThc5x0fNH87civHJbyvgbMt/eVsDDOMBlONVw3QMUfwq/fejKdL0swlK/fzYY/a5H43zqIkeCCkzDgjQ6DzIWSCZxnDRA9Fs2eFSxOpKnQ5g+Yo9Q2t3MTXMHLW537S+En+hGtg0c0WE5UXrnw2rJN+z16NON15r+fD+gtZ822+wZIvAobBtJu/0koSxFwr5jtNrBfiq+1cWgR49waAtidLjjuhF0YjhT5+WF6nAhuoQjWHVjnkbXLYnzQ5p6npqYKgISbHiqwzKxwj6Jw+0QWWpJLBPEIBGS4M7D/WGU1i2xaZNhe7cPHXQZB221rVRNAzCwz92DFrp7HJLQ9iwC7AfeTvfS9C539dJ96Ft7nS5+ncdKK+xTKlKcYW0QVJ3+VyatIhmw895lBCZLqNsPOgOf7gEOvrYUKpCnwZBwhhoM2ziGJ0MEdd6SmO0euSBHEaODegzOj/AEsOmIlTWEc3dfKeyIftg4zlI8gdciE+ZaEjBx3sAOLUtPcvI6zhxb77kax8bs7ynqeqVJ06lU05ZNUfoJcpeDGcLMIGYxO0swWxO6IOTwlLfM3JO6e2Lb0LjLyhd5D5Nc0O0GYP4+a3QX5m/yQi/vp7MUTNNnwRDfbEoUPvKTvt6YWB1Fxxp0SVn8OtTWHCXdS1sAHN00LJYV0SDLt00VAK4wMxUqX2gPIR8b0/QqTbzxUn3oNUeXQiL0bzmFYFma8M6IjVh3Pblen5EnUnODYuO6OZIDKLkw5Q+6pzOhBWbHIwmaPtCje/MLpQD1TLGd0dK89aZdQlp+QeltbD97fuxQODx+gio3wzEdu7eBz7sViJSM5yfVTJC6+gWxg64Hlt7F7ozsgbGsXgK1+5T6BVr6J1UBORB3RcoHgLZt+NCXuL3W4NhxfcoSwx3PNgIjkT29TcvRU8bYI8+f9QXstnKOL5oTSzNLb5avsrC9JypjHQVvHg4X3Fd4n8x+HejMU6fM4aaXfiw/PU8AMGYceav7TD4BMfu1Fa+3trk4l7vMd1/oKhYvYwmXxr08USQEF+cnkWAAe8I9MzTx49cr8pGEm6+8fkmdiNUe6bMLqDWtx0bLnJveM6vE+LFv9oBbK+f2NpD6KiLj/S9+d98Zj12kuFtpslek5676D8de+n456CI4Skt3ZeChKnwDr2XLIh4ZIDcEN/XK7Jn57PGIdUxQJzy5kvX30+3F06E4O/Z/d19If2id+qpry52uc4Ma0oX/877US6a4PE7sNx6uNnckk0P5Vn0mDavyLMqGhOu7bPF6+jIU2B7lWvjttdui/Nam38ZdJlkBheV9Wj0sgsfcbeB0O6JSG7hDy3vQ9IGXr4oFuBmY53iiz9LyzBz4XhA0XdjoPgh7Zp0aJRXAOZ5aIiLxLWKFNVXtZWaQXLNvV+nVv0v6qvpiPPs2nt++K4eqFb/LP5JRjhd6CbnIpoM9QHqxc2O8oiz9O1R/I2PLotc+lniT3hVk8wChAql+5dOrIMm5UvhtdlEGVYr4pxUG9TcLuamg+XHQbuuA5gbloOO7Ub5ftz+w6QfCksEjY10BOE5mbn4UM4UE8+Fg2bjEs2DtYnuJZEnw2YCZ9AyMDLZBCWv7++zHQo5G+amEOZuriOVS0Nmon/kljlya3N1ar4nvG5tH7VueQvDOwcfkX04IPEz/q0Ruo2/HTiGG4MNsDCH2Z7wupjMpLBY5AG4+jpNqCSF6nNxzh1gOcWNFEgQegCXXV0y+ie6zisVjSE27nT6lc5Nl4yjjtiwEgpx0vfkIYmmP8kcXaYcNv2IOhfj6ozi9nBAuseuWokBUEiqvD99y9BTB/H4iUMH6VpSdkCwvDtW1tNX0bthOZjld5O0fuSGlLrQ0BArNY0NfdfgRNLMDFfAcWu1Qe9HQeb3Wk2856sa968l1CQIV/T4MssCQWiMNOYzZ97MxjNZzTuNOaOK2KZ0hm6KZn+aAhfT2AvyZbN/yJqRVibCew6adAPZh68ku7NeFhsMi3UaG6Ag67aSdj7cS0mVpdGW6abpfH0v28Pi/J5Xd9fR8OiH8gOnllzd9wuW7iP0KVn8HXN9n721pDKyRQW+YE33iNThCjm12mQwtzbAEDN8IRlRBk3RJfDRgZFpGpWL02WBzJGOU0aw1Yk+WsRcBcWkvbYfx+ZgQxA4HwVCiwEiyLm03RnuaPlm8+HJHt9PmBEJyxcwhwsbKGCnpVEJzMQdTSzAtFdKDevql7xDeNggZv4RRH5nvcWx+ic0xsnJkMftLlOb3C+ocrVxD4V1hHjEfFeYCqxT+OIpeUDGhcImbJFp5b6XkYhPw1WAZ3srpG6HFCimVaf+jKk8QoI5xcuSoUnXUtPBb56jdR+RGHfpG52d95InnDkQyG5bARgdRpYVWE6qQp0A0j8WmN1Goyi1A69Jy+/zWRp5SNY/t+YSJjrZx697kItHJ17+lcvPXLnUv4h6lKmCprzcG0F2nBNYnTSTGAKk+Opq8nljw4b4ZImUnII3fhQ3OoVaStgGthEv80R4KEVN9pqQcJe3ey9dqxfHqZgGgqorOyRti4CLGi1C2VK3d13HnrxsQ+hqQw7E5bfazBHrk2igVdQz9ScdLJ+AWablu6zd34vZ35+Uf4Z6bpSr2W9FGczk+LtJBOtg/rMVHpDUeGzhB4ir+BnX54BAiTrtwleYZ139a1jkufpR4H/+z6FKn6gwAxw/puOzv/oNKeDhrnubs3zhT9J7jrlrPqYt30vzFIq6I2c+50qmdFX5sBT0TcmxVxv2hgz62Rm1W2Ly7Uo7eQMCM+wPx7VGvc1NOXFhzj3ZH3xzm8UV4XhItKclWKNTpngNp0m1AZlipnhZ2bp4uR8CuhJftZ+zDQZwgQ3JEip1ASDhw6n8vhlIRQdGIJ34ZZpHKlKtQppKZWxVrrcYtFr+Hhrrr+rJ+NjGlZkWq9cblGvJrISDIlt0p9RUJC5BEgqJ3nzQqE5dQbwkpaQKEyRZVIGsXHj7lBxkmMo4qMWfkIBo1Yw8yCLLXkJGFmN7qz7hRJEsvZ3kPRJo6Vhb5jG8SFoolasXaYIMTPHOLQNfBs4wpyApSi52qjJyqoDSqqpq9rgNH9gTNxtg3ablY1crJn9Y74aa5I4wKpDjI4JUft099FgU0xQn0DuMKjYUYhQ42iHrA6aivl1ts+WHt7gDI3ze7tQlo/H4YXz2RpMJxMV1uaTFCySpyID+NwlwQeYhTU1xEMIvPIkmQgzJ6i+YFDioiVSg1ou6mUS/PVTQZFrp+H9MmOmnxmKPbU+LKpLc5MOWsAc0MQvPqcuGuHn3iMo7B+uqjseqxdQiM8FifqSJKcRdRIJbEPzKxliZ4m1HSLu6IdEbKWWg+xAT8KgWahCvE+CEellska4sNAOkfolqhgT7wD3L7TVOw74mkvEGdUO6qwh4aYp1tr90wwaWhbwX9NLDYCKKEaEO2agq/vCyyOUdtYasqbX3pxEzNx3YIow4GdsgEALz8y3snu9zsDmKPtXzAF+ci5WcYC8veK+1T5+wk9iliDowpF4f9qT4JB3KwGzWvVPX1uWIDlCE/tpfmoGZBHIeYw0wsKdsjugajq5e5LOVoQfYNEbISjpE6FMy2fnA8iyYQ/OcEffN/H3RUJttei3Klvbyjku65Faj6hTgtnMlYZ1kINq5bc/Ir6L43MoiohZWKuRbHpSKJylHm+32BuQguRZamfl+28AuPrRael1e83dXzM84yh0vo4V1+dbDVEVsdyvjXcsMTP4EsfpGgXRaQgTySb2gKkdSNVKC+sNxwq8IkLMLrDdoO5egvu37kjZqBGd0VmKTmreL2+4S6h6iyDbGD40TYiXZ/Ug8YDD0j7Q13DDoDSRedumfaftHL/RXtsKxEdb/tlcdTcEuCKCJ7ksy1CirHSPpa4nndv0+weTSHVOezzOUp2fcpGRZm6cnOS010RA+HIPnq32vv7eXM1GcOJpIbJQ8Jsd9hkfnLBHW2ilWiDCjr6EkN4m9yUFP8Iagj/vdIxlw3TZPDOoRlXOJNYc/k1CJgd7QIHcR7m/dBbxz+KfwIktDP6L0negrqoiJQrTWEkBiGRzTQyBTzMf4wDlOycR3MECLFcmLg3t5nrkgf0PFtTUGOE+03GSu/etkmNePBC87fKoYSG4cpv990GPWDBaGclttfsZqL9TgnaWvDQ0JilbabxTs61t7kuk2sLofCDl93tx9m09PIwfEQLal+HJ9psnxNY7+nlQ3VYT5mIlfBtaPDuvRKTVs3XEWeNzfFI35vaW7vDHemcXf0UwIfQBx8NyW0x0OXvf6K64vG4UvU9W2JfaS4irrHo6Dj5zHFWHQaj3k49XQ8hCcIJ5eZ6RRPnwjPIM4ep7OpfC6tLvIjDltTnef+ECcVEAbzMlSOwh2P7ycnq5SZ5Xzw/cIlq8LfW8hUq4nHJax6HKGwDQrUxW/7UTHJEGjGBIXOfQzP2+jKwP30bfCM2uVb2ueO5kTRAPO5gj1O96wK91I3p86r+wTy/ntn7HTQ/ELjgZkebHT/oUXz4QRBHwJS/BKmfiRk/1E/t6gwPW3rJZkEo1we6/jvIKF+nDky9nelqo6ACi5VqPM+tBuEQwKPdPMC6Qnth0Z1TGz8k6p4WD0RE0WK+rRBfGtrhU75JrqX9/s2mWl6uF5C9l6i/wolJ4Wf9tNU7j1IwlbdLmkmcVfCJWxxka/Kvj283gaFMqnUkr3pZDJoHgAtB5fN0RY6cXzqNHmr9dXc/tp1pElP02SaEc3iOfQXugW50PSEPrDMPuyTPQXF7yvHRgwtRsT4IRFJF3/1kKJXl4XUrOZRHMu3LZO98Kf+WkY11//ph55i7bEBn1fRdri5r9H11LewPxwd16gUhnat9NN2R+/BfbBoHXRizwr1FwMRS5NGFc3tM1lxQ+4v2Jc2+VEI8jUxL8oD1uJF+3SNhqIdD1ovox9fUAJF2NeKAvdEJpKmEiP3LPgst0iquahAHSITB/Rky+27TuqX9MprjXPYzgDi8Wa6iCkVcw4WsE5ctpAmy/IFn/uEtsjow237SMO7wUikiP27pKFL+Di+Pgb2TLLUTqp0Pbk/fmeyZrNeMt4yc5/vjwVRKt1IJdRFZGD/ivf1sSexZme/V+XHLhdNyy9C6IheaqiRYNXEHMl3UItr4v22JexBGupH97NnwT4+lZoI+Y74vP0sQ6psBxPctFX/HfS+11r87dHPBN10ncUHZPZzWFDnvRAX93n0iyHPqkta3pp4Ue3XATkiPzOEI7fw61PePIpcpI7yOOVyVkiPCbX3WkbqOBsbwpxutmK1qm3H2wd7WG/RPp+5ErrEGxLTE/pzcSYLA03IDplReMSHfVJlyiVV0GGP75Tu5GlKr8tM+z+SVOovRNon/q92MPTqCdanhdaMuUQx+7Lb71azeoHHet5ovsGtNwcF8QKp5R4ROQGnXItaRtX7ukY3+QhyEJJb7D78F+GHfZfgEvdxr4V8rZzxhiBTvRKkKljv+W5QeJQU6tHrk70lqIfRQFbX2ln089bAOMQkzDM1eGyNsw49Xu8HK9BaHrWvTAS/q6F/dFoL8hmprg9SFvH5eOg+PnpretV1VVeq+jQQGxph1D/GyXZN6rr8mBazf4nUgDBfuGchhsU1cRwZrqL4mR/LarVv7a42BEqxzUi3UNj1j/2dbmrYQcmRwah81YnOoIuE6/y4Jd53P8jCNjJDjzxFdE7QJlZ+eExch+hZxV7T7E3yoW9X9Bu1/4ABHgNlPyhHDa7vGVKFjERAOwpdiGFK4QpmBJfIoRnHkXkjEPUi7lsUuIUzmhHz5tu3T+wzjJuL8RvKBCvA+Ulk0qsWCSOQMn7cT87HFE0aiQ+PT+pn0W+1O+1xcN9oU/ipq/30h2tA2icjS4MlY2T+y/UFM1uOrOPIMo1CYHYIOdQDivPLDvRfj4ic+ckV5F03uT5Tvs4Jy8KCcRayihTM4uosAUv9gH/R+PhTdk243COlERXjU3kshNVtgn2zhdYqS2n+WF9Uz0/Ng91aqyfJHIE4/tT1iZr7RnU2P3QucwVTux3XBxk5s8yYeVxauY3u77VBdOXsicEzDCqSSjDm5uHgqTr4cZkq3tJK+MlE5nGf6KHk7qfXD7kSdT/P+2+n7Ab2UWGAoG721nWdH9qGhIhrJJlImp2sIPluW4xSJuNZN/y+WjnPtqhFRjfu26XRLdTHgX6u/clG7x8xvh8GjEWYZu7ncxKl9ZUv3LbH8eQ9ZOuKnT1GYzX7p//obw7BKdmAPGRfbOe+JKoE1FJNtXbj9Nl1o4KuR4yccuWmy4WPHuRGTAtlflbRCrU86vsCrAO2neH++aJPd65wREaX98c9uI3YpyuB9+jIHe99McJLamQZYpXSjvHuLQk+xNtfz+YgvJFCHuL9qWDw4Rn+uWM6h7mheh/t3ed5AxcuZtzr98Pi84olwiv4/eHPEvrQLxIPuQbdMnogegy5obiyD3wq7VsYrxZFByUJOQdFKrW6Qn8MRsZnnc1Nh7X8YNHeP7+c7cH50s0I53gAVwWfrOkSPdTn01d+QVAJjvHZTRhyDcvT+xBxfQrj0kw6DHSMT5tLGOnowulskhyiZ7ZNVMZnuHfz7WzuPi9L+lAMlXJZ+fFQHd3uk46rD3UWNlLb3eEdPYZuDiNwXJwTeKq5MqpVrg2wvr7efMPixlr50r5yU/l12N9q/3078nqQei12jjT7Q9wNKge6NBQPgofAw7XwCOJox1cugsekHO+GFMeJ8FErx8PJIjxl7J9eHM7sW2++NI1nZf/c1RXnO77Rz8kOVGHAEc4h6lON9Zh4/eWQ1JTZE9cSx9xjIbVUtTTBM6yoZ2cTsJmLUHbba6g3n0wVKAe8T2oMmtW/z3/cPHYJyG4L8yCKIcoSVt3Wq0P3oU/L4bJwDOc0GvNKMvvLMm1Vdfq7/P66S97APdzjatM3Y22in3/f34iAfgWWOAdtzGCpIQz1M0wtv/MXBzxGuBnJEXV8RS+IMeJY7bhl7ufUEvE91l2ZRAobiQmjBgdFYr+SjGh41dbC56f2K0dKu1Kz/OnkyzSJ9H5BgpiB/UyrZinb0DjlOHfT6zHz4HxDsP2CiVGYV5GLtUvEpSrgbbuE18eXXIVRRnNHkcsRFYO4rt5/XyWCK7Wq3spJeK7qqBnw8oPccIvMfI1amtINIxwSdA2ibpzoRFipn0wIIH8K0wQKoCF351fGGwF5wd2YVgJCGU4kouBf3LqyuV+PLk+Mm4GW6nm1uk1Ug3ZqF6bKBC5yBwSPhg48aUliuTNI5e6qWFkWxe53lQfZmgo9cf3ClrM6ovfq3VKFfTK36+QM+I8sb/QZs8GUEt2/vh+Mr5AnB8qFVgtDkQsmWYkapIPBb2+cdZhe5y03AoxWZ/iypSJh3X0/a7SwXb/57LZZdVjv3UAegSxYU4Imu4FRXFxjvY91jnFplcEarJL1/NxAv/nTVvD9OuOVY2JekyIkp6oENK9pzuSL2WRz1u2M57TmsTBtsHxrNaka21sLz/CopMya5miXw4Wo6N1FIwuJl6Bl/zo63aFhWkKNTFm3h1zRTodW6xrX91Mb3NzyXce52vmHs9+pLrbe87WibQyN5vXby6Qd74r+YK8HvyAOH07A27j3l7+k4kEV7xsVLw5nW1T6oAY1eF7iqG+Si+D2agneThyr7TeaekUn+Pum9LxWl6l/rJtLp/4z0Nnrfssdc3kt83yfPdm5wllzFXF+oi78H76ciYMEK+Kqw+Uyz9HbnuO63EDCBd1ZrzRuNcT/O8ObRrXrhtG47UHT0wLvamfDN7iw55zHfV4Peoy6pjydtCKtelHNzc9SlHPiaBm456FPvHW/vvdm4AmNiT8rB0igTbgDgcr5NFbHJOq+dyzlorWr/RyTeLYbAUnLE5lveH9RhXTOZ/A09HxpDvBtaPOFMVxmzpdZdl/dah3ZruRPTfj1TH3nmw4jKCdZkCciSd4cN6sHxaCzlsj2cEySSZPab4mU4/jL6QGuIVKdhyg8nOTvdTgm9XJZOk1tunavvWxfj2epTxqNNRmTNied33Es53wfq12t1qEPagA9JU0sIIM2IwBoYo30RyUm1FGv3BTMc/vYWrBcbkycE24tTVlgfXxsk23QJvvt0hw481Gs5HZqtjSWA+Anos9Ecb5/3vOroS/mihTYDRBY3OBZx3IAw33TfbC6tbM/wxuvGx+pxBLyFX87J+XZD/zXHCEwTGZMwbE8JN9DaLXDZB+es6AbKCxV5CR6oiGKJcAjupD02CPQanQ8pviOPWMJf5Hs+dWWUMpxkg6vPyg5ylxRIZuICbm5SUrI9/xkEZ4DDm+qMRUGXR3i7Ik3uqPlJ2b0THERdru7GkIw51dY0SvLA8+7MOxhCDZtaaf54e3+rnpXyd9KN1p6JQ8z/dr5Lcs1QSi3+W3jBp71+f2wpaIhqRppSU3q0Ji4+hVgTdE1fywutDKRk3x7qL1oA0JCp03dW3NOvYH1DRlETRemtDQMotEOwPjyvqd5bYJi2kXToJkf5h0+quhXjH/OfSHSM8mKVvnFDwsMSxjzZw6ELZk/g0JrRnkU8oyqFPyRBpj6Gs8+rRJYYyfx46qY07qcDmkzRCk5q25fJ75vus3UuDUBPOo+bZcMO9WSye04B74X9ld58XUAhx8n0KfjtQinG2mdBufiUxc4XC47vWBHrsBvQ9Kn2yLCvYvJdR9/RrbJDCzkPdlJsc8J4upblUNoDmkm+S7BY0+2r3z+TVBYZ5eiZ8u0E+odr7zovUz6DEF/Uzw/MW9WcumG3ozpN7ObkPzE6Z+WAQdJh0g6Szj1GXikJpmLaDeDDo9hK2SwfgtRlosaqrBYHRG63K2ZSR3eggQj4mED5/ymGBnCqGQcKehov2IQ+xbd1+ubvscFbT1GfEh2IQ1FwkesSLCNE3wR2FwaiTJP0wQiZ1JiJTsFTO3QHTkEJrkVaRNxB0onpLROdagMCTJzIleSMUuULahylKs854cIpoIoHIvQuDAjxyTYRtFH31Evt1Sk4iu3kkEXPjrFAlFyMUsvmCf3Y8OZclqYKLsOVuQsNzxOZq6A4KpkFVgtqHl0Wg3BVSuE67RGXa+ENBxqcCMCNbp9rnOBmoEEQkfTpC8iFLheq47ZPPcWuCXHArWqDe3+i4mZdvNkKBK3rEmC0dRmR1BrzHqJzI5hp7r+dY7m2P90FvO238XgbhvYFrIsOtqSedWinqVgYPOQcm+krEpTn31gv2jAgxQe3fFSeQgYjkv8iqaXFnNPAka+qXfM3veZmGODt/E6JHSqC67uLl1OE5rElL5QsV5ULZlgOncmMgxynzNVOOvWOebezfvqLQHmxzt2jJ7uT/ZFW9YCFku3jYkmDq9JGC9pLmP31xPmu/z69K4lr3haxVpQP0Azte5fwIZqApTeeQ0iUTfrVt3W71jtXahD7sRxt+nTnzsVe/mHGe/DB4jDLEw6iuPLwsQTWd47aZdPX9S8X4BImSNBjUsSitetVvvHPH0Pj1T3EHXis40IoQRhneHfaP9VkCBqJ1ATivQAtkfznXZTQXEIZEW+Me7yYx1vxXmenap+OyAu2vyPi3nZ+2gL1epk/zOMBjsGq3zUF3jn6L1UQbeusR59m1fbW5MA4gjMx+v2AcO3q3f9/hkjZFyHbgb7gwBeTidvlLXOKmlZSKzwAxbZ5g0aS5fuUK5oU6Le8jEStdTmndEKeTvzw+CV+9bvRgdVraXjoc3Hwbhx2o1b3GAdKlFdDWaoI04tJfyybdZbnkm9rNu8cHML/+F+e9+BW/j23eje5/tB2ps1F51ywCvR0ECc7+LJ9cXLk46MrQGOyxv/C/szIhChH8RPp220GfiMfhMHgaT4VB4E6etztnqBMGYF6Xh2eT9nPu7VuH2T7rhffNwvs5wV5m6vMtJCQnku5cSz7OVVP88VXq9pe033mw65Mq1SIrQKaRuurwFvhH3V7jfSPcTPWjBHh/O8yaxCfslrBZ5GvRt6nY1E9nuMuu0k6/Y5zptRrPz9FjygT0A4mKlp0KryfgtKr3vOphSqbsq1k5o5udoymPLGD6DgNNGQdiA6vvNz0833wg+RfEHs1oW+508cnDMLIBiyMFVmcGfJ9YUZBwbw6ePPvFwSyBRH5txxdZh/nIeejELA4kghJOtcRXokw0MDU4sm2fsBCqeYRalVkS0ytMbNfl3Obc/vHLSV46eJ9BI6h9OaaavonjECp54wON8cm3qNwtmr+CLoMNEh1fc722SEYbenH+HjTHcboJLZZ9SRvn2+9S2V3VYSvMPm160tX/KyJVckm4Ud55PcOcpuzyG68MwqqcRLPgn+GV5up0hDIM/4N17yjzJV0EK12BIQ/gFX8xbxa96iPZBIiC08As/HjtKnhehFvh7d7Vs+vSkHQ6LhckycjjfxGqduI2Frwuu7UoQh8oA3aW+asgalRXSQuAcv9DsmDxvEW5Xt/RyXHN+A5/aTeeCLNYg0CKom+ZgkL5DARTDsF9YR7w57drm8JSUV+pNlPUlQumVqFof7ByhtGbefJCPa1KutJZYhymYEkvotZxCYmPYtAMB9P8xOecu2JIkw6OBcF7VTQfQV1YSokFC4CKVJ1qHQ7q8TR2/OW4qK60OKfGPm20KlZFGE8trLMDsuuCuHyrTWkOsYDdUgjRbV2DyoX/MLJRK0EJp2S+gS+E2xcAfwHdlXpQJVXp42OhSVCLXXuS3Hqbq0LkGT5RXRTInfrZt940BRv9WT/aBxHYRmP/UW5x/HLjVrrUPjFKmCyw67Ekyk9i5hli4p29GQQhQ8kLD0i64Sx8NJroObg2Rz8WKZDFBc6xl/gf+3kDqnQN2d4fKOMc3ito7NBqdpD51gE9PZ3hSen7BU9C4Q53Hrf7XYrfMwWKzEMxiu9t0uAozQ8e3Z8zxCqlM8+yEEHh0eEvwUpsvpUF4c2fYsYpSS1g6lu9By7kTY5rKxsgnJVCI20zx32xxUaAfiMgj9oCq+MRl3idUOWFC/fxpkkwA0FwnqXA7BQqRVkGr6Cd9Q7bbu0OqMJCuQLGUla6nIRkDYdpL46XxxZ8huGcieDm3ScV7i3eTeXFzZWVRHyMrtIrtO9fYJaJ+HBR3weIoW5KSi1hmwc19J3Q+67IkV3CW68UzaPj8sSFmKgRTG7ZpLLRSqdHcuZ5/Smg635vE4TGRNTLVKy497K3eAEl+fc6NbXOfdbUDjqo6x8Jbi2srDI4VAEqQ7fXj+9pbPvk7kbgi8pq2b4lWU2SYvdDNJyY2J3u3EYM8UC7p2lZnAvt2Wh56JKsJTdXneDnv1fndGLamVflcF/R8qDNoN/30GuH9Iti3fAerOHXeibYjolln8LdI7UrgcOC5mBm0brxKwBQgOsW3JYebM0s1TaHz6CLkLxh3ao9LD2x3EsLiCmJkbCF9OF1UKhZ7Yd4YRDkcyow6S0U1A9dQu7pie1IUmVsS+57tePogLmdqfqiosuIZnFS0Syw/pPE4iBg0fIQv9EJ2OZwUZvxImCMHXIhJbyKjEpK7sgjBp0qr6BGm5SUS2V+rRNwGTm46UJd+xmDHcfx2Cq7qNl9TtsxO/qZ1pC4r0A328K7df+4qEWQjZdLoN2UmQcXEeKWwlt4Uy8yCZlQ/ZxBzUbygjx+jDJDFz9wcj6I1UM2/emk9Y5G5BQ+MuzOzNouIsFpR89+5iPVIZ35ZsOGNF52nK0taUJDjLdoPN7UT5TB1UFVhhYDp73pWuGrgarhHV1Fohoi43g6jPG6kZNrJ2E+UVCJ4RQTlsEcd25bxhx91WV3QSCfL3sZ43RalEzRt1o+j97KUgUgIIBviyPwkZs4gpxPRL8JS3QTje0SDIQclWsIaNEpDVT3agdzBAUZqJlVVU1dQ15Ui1sCgQ8RtZ8efYk2u+W0ZRMXEJ/jlT0moodN8dWJGmnKycPEM+xokLBExKWUVVX6DpjMupa8QcXdtuNfkwCIwQIX8A7IxXI0q6L1Vd2E3e2OMgxkFO/zVCXR40zM+1Hgc7t7siXB48g1KMNK3xOwQ3h3drAfEWcBJPSJJkKVYhzTqkyJApS5LsGAz118mz0ECDcGZzMygpA8D9mHsO7yJ7afV++REkDwUVSnIE+YoVOIFgoHSvAI6b3W8k0rx7jglEzaBM+Rsk+YQDpQJlEy1waXtxS0Oqou72n3CDBWpjON0roJKd3yNLY06a4w1GTNP+0yvwKsJtdycl+Z0M3FxjrhM29CX/Dpvfr+KT/yJ8q8WN75bthy323wXb3693HHbGYXccDszuj4iD43AwS+BD7MOGjsTRlcqxXj5J8TjqCZ3UKZ4Gz0TyLPGcruc5UYBqwJAUKeYVVBOl52yjmrNQLEmVrmdNtSE02FJFxCABaWTtxMirSFR5UncWtb/2HISj5oQ60xha9m2j1dFbXJkbcVfkAoCgJoQKc2wREaIgpipOgkhSpSpNJhVZJkeVr4JFSNJ5knkeqkJ1aVWjLjQgU/dUq9p0UCecOuqszumCC6YH+sxlEAP2inSPQkU6j7Eo0aVKeQ+YoeYq9stNVKVLWSs2VFt1+71fg+7hOoiEhqqlq0ivFBYioCIJjlrMIwwmkug8ZR8xrsI6RJ3IRuyoMECYvSJiqUR0n2WsnAJVVlV1NbI+h+XkdU4NikrMuhZWqOkwduaw6gpBFZOgUrKWK6dos8qqqOOqqZZOV88QySgEMDEzVPQHq2IDe1wdnBA5aGpFksXsZhFWsBlg9e0onn2SZ1Kaak06gwa0Fh1Vz6AY42oijqPKUwBFUPJT1lRQ1apRV9WgGUTLUW06QqCrS0/R5xpUyJBrhPjijGPSj8gjppqShFda2X42kXk+FogyjxVr+aG5jqtdfqSir0V0Y2z+8OUhHPy5xUJAzavEaILA32Fh3KAQmpWOQnj+AiBEsuuHaJ6YEBuP+GJN0M8uDkjQ7x7JO7X8ogdWgUVFMpS2IBM0KKQVGp0wSaFIyxqWA+Qt+zPYRBEsv6/uvQynxddxXiXdU9wdih07ylkJofyn+xt/E4nzuyoqQzQO05eumugYy++e36NSCFXHwy4pSmpUR2jkjJR4IPpM1qE5ebIFEsFURUFZhRFdBzel2Ak5lXN2otQ5LaiFSlUEYA02fkG2DiFhkTeq9K8+dedVFjyLE0JkfH2Qd/u3ZfVj/5gkQ83iBLprvQWd+jMM1OOXHR6t87QpzSbZZd6XwRW0Q3Lhe5Y6mSDH3Us2t72r4EBvv2HGb0aLTz6+4beK/BFgtK+7Rgdk5xPoIFIwQ+DQiQpS2EIMz+cIrpGOGlW0fBnDimVcWsUjIWho1qRdLbCDoVglMmnakjiSc7t0Cm2/ZMqLImV2F7gISlXqqfln0pjGGE9adkulG9KaGBaAjEdP+GDySHmhZHRSVci0BsiviKx5YqDsBYS6wSWj1h/22Cqd6ajk/EPTd27cfvmCtu94jTRlzuvxyB1P3mFLKdjBhACscbBQPvkBm2ADFiRDodEBXAt1tIpcDJZkN3vQD7pXcilUHPB5y63kDNhWyzJH0ep1ZlXSEITlcbRnV0DZrISqBHHGgsrmgw3lpqPoGzTe/FE9DyliTVqPGaUkoYJwDShGq84HHrXrMolIizoeVNXhMpLzJDgOMPzDMUdvLesRyGMO93tWKZ7Z3cKlk4Y40p01Lr6kczPVgNrSEnkEcbdD5YBQJyxFQ0OOXTrkglQXVDbvl9bCRCkT+amcSnC6igSUKmbDQPTGRVMneNqFS3Nve+WEIizOLRStid+Y3ZBlm5NWhbw10s1lLra143YJTEtkqk+qxOigRIgxQCcnHUbXhQH6BKzWIVjmRbceHnDIR0Xm00PLMtVL2HXmeXEfoj89lAXrUK3h4xrgYGkP7cMyVwy/slle6VatGEncHaE5vj6OXh8cIw1rPCaO85PlY7K1/ky1g2nOzK0Zzl5/mDMyAzhfYtlchjuw0FzP7CoWmyKsQ2HwD7OcsYRVEEspTVhO1qfCnnN2U95+kVUYjcsfonmYNNrvybBNrCTuotyDsMhBAgxdioJW3zCkyGBtIzIqcd2yKi2nQNX2qaghwd3AaSEyMUUOGwl6dBinnUg/Crpuk3RjM59Gb4Hbc/F3vdxph7ZHzZDsdFAMFURY/fAOqrt02xT+0bF3OKOOt98F+8z9NoHIfZnKdLB72IOUVM8I08ijtJwNHQseJ5lB6tLfOM20qDP/0/qHc5nsih8uXslAgv+/VtN8Limu5rpE18eshM9xM5/bED2L677PKzjx5XPHe13qLub6RRnIGxoP7Xn86tnx4szThQI3X7zyJPNp4F/srSNfzL3ZKHgXO2q8BONgHqdLkhAIuZ1oK+G1CVlc96e4SyUiExNI6I3XjURgUh3P5i8s+BwiEd77i6BrLeqLlwn8BS/PQL+iwH/sg3Pd2im9jSnq7WM1I/Cpd0jteu03ALFavn524XYPcO/ZRfycgmz03LU4yHVvGS2H3+EiVC5fChMTbRXetvk4w/nZMhIlqDgPPlGTOAdoJJlXeGRrAnC0p2xxfd3JYdrO+Te36AK/kVVc8nvid8VSP95Vyf1QeHIWMd8zPxyL6IPh9fM2Tcb+EbAP/GiByciuLjwwY7DVgIJrgpufLM3Bnvt+nZasuxdKs+ACeG7za43jgn+8uhVesK0zg/0HFDHNFgeFBKPP5Rwg8XZSTWgXDo6gXsgVP9VITimfOzsRvljd8VLRdaE/TQLkYmz7s7CLGK+NBqvUxlafGntY3V/kKNzj5ennyZYY3xE009kAwpW8lxLg3drDtr6gVtiOorNXWrJq0uXmXA7y5SM/kd6S4AIL4DrIIk6hHQ7hxi1zzcoBkQVxR86ZFClO4WmkXChLFhdd87ZkC9YlSRC//hqv6HjFHugx8xaipiC8PgfdGqJcdYg/Uz33NVzCJN1J6N3611S3xPh2jB1NupLEVfqhdTA1kdW1UFKjnOd5nkPSJOYozVeKpH5Il5vzAywDieqYpA6OWZRlyFGWUOFDfuV9VjZHhZuWX/1UrF4MOwZdLaE0TP8wkRXsxWKFcdQ3s30IsmZkq+2Tfi7NShnE3Iw5e/KBvvF7EapcFVSF1AK/e52iupw07uaVpQmJmpH1B7VqwSJNIVi5kCQ7D8pcNKila2hDfDhNaKPjmF9F1OlwcXP4nAhlQocol78GMJGn5iBrdD/vHCcC4i+R9VfvbqK+gyNNyED4MFQdMRaNRMbSpUmHMgXZc1x/zUbD/NCMe3Z6Xxh6mO9PCYosLH88HE4sOJf0ZSU8WCfuwrDz4TIPDGQjMgL5ZBu2Z/IuzOeNdkPFfrwOhzf47LXXUfcyYtEpI5036Kvy9ozaXpfxfrPtG8Ez4Yo+LUIoLdTZwnDrolFvEI8kmxuyuKfICLQ8pMvQhWh+s6jb13i+K/mv4/RYR+h+THf3puk5KrLqRZPm3rzJsm0fhO/Vu+nlax5tA/mLmAH5AJSsYiE4h3BpmYZuKyd9PRY3RwTmG0TBVTEnTsEOQQnt2U0zrDTDIxXByIaW30IjSH54/UJIFsIYKDbIckYxbvmOBxKMf2h3Li/8AjOxuASVJEEmOxSjFCacFA/nYqpV0uab3r5SAdEzTQPpuZMYlRGZmU8ioxOX8rWhz8p0FiFbX9/lchO8Vu/tNyrmM0uZgkbOJLGnB7EgF41E5dtsvz2fKuedNO5KwnUuOY/4Psj5AAzzENICMEcF/wUEH96KyEVIRsx1k6MJ+lUU+cILYMKdNPOpQIWR0+DHp0m9N5Umc6SKnAMWW4Q24RIoX/IqJdxgwTrk8RW9+TtAgqJs9lvUXE4ay296h+fNHXLEOqazYBGwWo2jqf1Z2OgEq1jKEwFLJ2pdRAjn66LcCetXhStJVR2O8yt2bx9PbC1cmdVP4MydxpFwwI3uIRkFcT6zRhGeBbU6cVH5Ageie+CqMCVdrXJgGt2d/fTRcXQ8aUpgC91oU6luUWJRPXNZ40YORUPfmMbVuEig0hHMeYRkfogGlRPoOV+Olhy/r/E/aN/a6mXzWqOFcmrtBhs5zZET15OsSC4QTfRzjCHUoWMutbItJPJTQGpXAvNvC+UTI+6A2qMz03S0dzv2omuwZLtKaLzdo75t4P8DDsfj8K8rI66PBvKKJyNfvMZTy0vWE/cwsDTfXkRfsqT73a0V51ta4MudSQXkbw5cByv3d8CPDvkdcJ1VzjdWMhhyMBWG0s7mgRgmW53FpPAsr96OQTeII34wvJrM4qV+jBr94K8SdL1lIIavrwdX9P0sEiK5O/gBY7qDkYrx1V/mW8fQBQslWHCi8wVQiHufSj3l2+V+vfhjkneqVnAcD1aif40f1TmVmNOrLY0PVsTz8syQZ0XDmHOPQv+BOGv6L/SLi/MTsc3dCRQvE3BhyVzcdC5pLyv94sqaEC3jXU1/zUGGa+TFIT+kPrmba/5Yv6Tu6O/PRQkqN03VtGVjoolouADGnJiHFtRTJBthO8zKoU0O36jeok+NUmsdodepJLd/gyOngB3MScMxmA66yuTz3uiC/YzdHJOmrm998B/RF+4tzfvlzvab4gHrUMM60iCOvxHkOVfS4nJv5t8gNOrFmiYYh16swKmjCZW7y0vymSX02z9fYEdWPp43wQvy/87rXVw2MzcuhTWuLubyPKIprruf+X1DvHw5oUHdxt2aQ/fxMKeB4BHtGwdNRDoZ37j9G+8ujp6WtXS+PXhyd38q965BRaMlQz6c68ZIGhfdNL/x2eN4EMDXLCyjYwjR+v0QC7lpfKr3F7F3y27hf7qcBCFTkfn9VAVRK6e4ENBFiuidz9olzjFnJGkwSPqLqeVr8qZ/SaM1D0IjSKd0I56Nr+1xCM5jbTFlCqhiSPkgh5Lqb1Rx0k4IetBq0ABNRQu09cm5IxCguvRQfQWCNWQExoqJQSTCTosEuVo3T1RMGWEkc7+Kezl+jXtRxo+yGlWtRrJaDkWdIGkKxTIVK2JtsEEFgmrVqRcSFhH1yyKFxJaBuMTiUQ5RZaSeSSO0Fh1Xr6AlRnxN26943R+yxyGfRsIBGBRnqGqkWBcgcYyHNKs7frnsluot49VbcebCIjvLiaxm1toNdK4h1BqBeIhESEfVLQYZkesqLFWoHEcOPHIIx8Gf89spnAfxLDTHKmzPcHlKeM6VwvWiZwwmz3MObqoBF1qudvf9DADH5Ut3pfyTktwJyk2PVOG55GhwKa2wUx+/DXs5wnueFxw+89sX8pO/XE8BZwq8opVQtMMCndesGuRgLKkwgPEdkmWGrmqJjLD8DneE58gHjiJHK8fAsaI4xSvhBD5zIilJyUphqsE0UrogylCmUmpWzRY0cj72GWwO5SpPCcwnJQi2X2CxEC6CilWiEpUSnkNlSsYI9e9yvV/hZ6XDVSyoq6Fk1aiWyYoIYp3f9bSQkGogNFKNSuCMOUtegS/4A3K9gI+TUG9VUtRjlZkURZT1QpRcf8/HHKyQXtHXixSbnx2iAnpAcDkKYT7qkWQUJdN6g1wk/MCoJFXcSZ9lZD/1NXwW/+sRBjej1MR88+sNFT2iqmZJeoM9FceQ6NA+XreJiPIhiOk+c1y3KsVqEnqGsgqU6mFFWLP+z4e2R0a2Onk9zGAwwsBOnvKrbglU/Kuwwg36mz2cYyL3B60Sc+muK8oQO5Lu22OE07MOgsGwSA1wLcgz5uYt1rrlJYygIhMTDHLGEdrX6UeJeJwJA0TkSgRSKUFVELFp+gICbSDLVGehRllLWm6d1hvqHTRYNBo0KZqZFqnWsLULM/P1W9Tj7xy9Kv1aCm47oBsI2/70G/WFdy1GGBE5bzEP8ZlitNQYxmZxHPH8ahlfhM5kcukuxRBKBuXEdqPqZoLURCZNZDKcUkW+9RbTLKS3mcM9zLgS6GdmjlcPs4TemfSx/H6Dms3azDptRt1xmqj7I3fgS5TQLQEbMBvOdCNDcbwy0bmbVfOZIPuJkSzYNk1mgEGIQ9b3HE3kSR5jYlKQaY3MNHN2kcNlXFSv3sB6nI0QAu2m5+aPRkG6LfG8IvzGxulI0hB2PQYbyvCoyilyUC6Ciq3j1Mf3+vGxTXO4LBxDPI1q5jdAI7F0dWGOaunKyWPt2WpwS6tdGvxKgEB/VSokmHOL4zgjKGgPr00TpnnF3wl5PZHNuSYTiyIdGUwv3h9EtpfkqPIUxikqSmdS8r6y/VQNafVX1L0w5smkfev6tk10lrkQJ8LpqjTjPJIuaSGd3rj9pqvA5WbVgCtWqG8zshDnyIcv1yTSdsqMeUQHJe8BAotpKjVHtf8rsx5iw2zzsdPsLQ4T72vZrgSSmKP7sx1/lt2A3mMI2oebmZigEuPyzcLUuYWYw10GtVIrsil2EAbKERpEOnDf7MdBetBMapEFkQuFQVm8qk9Mo2lBh+oZ3IoLmISZWA5Vle0Y1TlSEYQi9/GiuX44SUZRPbPPLnXwdbUUDkpFNdGabbywr952g26IPo4hMaOuUJOynmFJwNo/Nj+7cATVftYH5An5ckGSw1lHeZ2bYmW21sDSHoXx7XHQSc/Qp+kHZViB3qOqqAWF3vbeUnzCIWv/PvKI/UFy725SdWJnVDkF09DVDGvs42fyQdJ8O29fDaoVSzwPa4juygj6QQwr45LGN/7s3ujC+E2NPKsw9RsaVYvMHCxJrGBzT6BD0F3cv/5OvTO+vUGx4ALIGrHz8DTTZKjCMU0RwPmXgqRp7SUzsRFXO424E3d4lB081P8YWORFWWtaxtGGYuk/CpqAucxFpof4dvmLdM9ZnALWfwfnJtI1B0nQQgjh2SuNhsjsxWFRD2Lr6OZfeIhPMGNLYDGKZEfCFiClmlbzN3FMDYUKNkv8FyedpCtSRpZRSvRGwQZoy1oh1KCSkuREr1IL+QURncZEZ3lYgamoqBTHSSqd3QOEmoByqt5E5uClporSya7Qr3u9ePYvjgamTKJnqH6DYye1o7a6SINCC0IF+gfVEDXDaQ808bv7tUUNIGmJjtoWu93QkTH/6pI6cQDXXlKXpCd669P1wLLBp+FWyddGisZpy1CXgiEwsby9jJwzA2yqpUozg6BtpnkVWhwSLBNPaUsGC4f9tLJoXZA2zRGSu1y8zxVtC9rp09Wdkr0dBnK0k8jZLp4c5WDXJagohOYApTe3PW+r4Z53XLiJmoFjkEcOvoYh3FJpBWw8ZLK7FZSeKF6pBu0NwQLe1FDknEwRPh2I4+CLBk/8TTDh8D0eOUxSkh/81Zhi89Vkt3JC2JtEZz8sX/yPu4cQH38uSUZAfgLDe/iprj5m5LPsgjKwOIKoaQn/AMp8PYOPTjfqYJxCTuTtUImwhKf2IYXLzxFkxECRiCo3lFE3iTmswEK+RZNbvSIZ8zBz7AOjPMUtkRHfV6Hsgc6VVX5ImHcYixQBSxbvEsJ0Exhpi2Hx7lnbVOI9yb8BynEJSk62xLww6KXP+0SFfABxmxK5q2t3pOSPQoElpTLtMALaujbqWmahTA9CxrZ1z7fbnjSc/MCZQ8oyeiCMspmTY4lTx9I0cptolEdjFe+fsA6ZLwHrXiCtCha4UEVME614p59gZuaBiqMkqVRljNxalDsaMkkDDz3A+bDZWneq/0Y3KtUrHu6DPCueH2u1TZGukPSswhebq5euwKnyjmUUVV1rnEJUJxIRBtTs1VxAUK28FcO6Jlifgw0SjR4+GRzDdKem9rk3lxIDndQcyR0yQ9hyFN6gCOgoqqO1zydH+tvfS+531HZXju0zFSRY6RgNZaIEYcthp1G6uvit0Y1EYUHZk9G9EtgOMetDX76ugU2z34qBYQlEebeLwXcgDRlZlyQD295nS0vk1bD8NOJk0iiRBykljWk80N0raU1oUmi8WkS34KCInU8VdgX4ujm/wQKYqg6l1zeV1heTxxq0oX7LFcx3tw7fnxl94MehhTklnE6GmfBujYpj9qbq0JmdEKFBEOceBmzbKs4rjWmBfj3gomhJaH1SDJeDvEJLPqwa+ZSOsYQi+WGNOzqV1voi2ojNhKHt7G0HjC4rh6/2Y2k4wIvtX2iHfNFzdy7soWnIDl8Yh6R9wXhg6dBHEFZIHQvNk8Xxc2s61RcM6rRxy5NGfG2j7Wj6M/tJ6SIdXYOdBN0G3GP0w1jgnBtcFEmERvJwLYkIBSiW39bE75E8uRV4lQo/pGunddtlf2w3KrS0/XMQv0i/R/kX2mrkxUpweQ9I0NaVvHGdsfuOPaH3ZYFOXP4aEFeON1V8DgY8fSoAt4329ulqefckwPsbhuf90IOQb3+Vjy38O/FhY3658zndhiocy1QH/of8EvBoAf8b/l60DdHdUjkavm0yAkEGQqNFRBHQJMNcDWs6HIF4BpLwktwCab7WTE/r4dENhkJp4XFcl4x1wZ7b/JN7IFtfgJokLDh7gCZ5iaAYd+4MlB6EqALZmzdVgnpO/2sJmvUgHQvQrrVrWO18QnqqZ0Ya8TO9V2DT7ikWdNZjvlCL+//rtSKDHuif8BdSshnixAi/yCH5HmPw9txOMLBzWwNi/F1yXaMGTgym0eBnYNZP80BI+mThX0XfJZglmVi9KWJDMqV31abZoZjgaBIw1wicbaHvJKGcXNPAnVFhSv6FmncQfKewFR9B4Lqc26gFRVgKLZrC14pWBFOAAzREqEujcvLDz++F0INoCOeWCbHeN2k9ceJCFi1Q3IrlLnXSUoK1phhKdispYSHdWo5JSj7JnHhAArBuFS0eErQ8Tco2ZLlGJU90L/dtzw8UEg/pNjtyJcVI7r1KvaH0kN4HdpsG5XUf4tGZfw/j0dTH7t7LxUgpkPQj123IUYuqV2M49ef0plCtaV0Ia/WMCt5HB1Hj5gTEy6AJrRyt8/1Epgftj1YsXTd0pHvM+t6AzL/7E6Ubei3of9/Tl7nVNcbFPi41DYMEbbaf2VxPn3JV1xgNe0Cjif7BNPZocqQ03Q3kSG/7bxKahQskLMz9vf2kaOEIywxgWnVC6+Zks0QGJO+XYTuCXRfEUgkK+XhIT/EIsFOzu6Wwbz0Mw/1sDwXj8CFmjeBwqCXp3wVQ0BCi7T1Bx0BnWBJ0VAuuO7DoBvjcTCHnkLEQn6WiE5O4CkaDHsE5318TEi8jbzNJN17ou5lSVRkWVtOy8njP4PZ2CQQUfKysfCtSMJciyy7ty1z24doFIm2EHwJP0IXCfeu5bv9Y8+XsyRVuIR08C9JgNBo/wC/BHd+LstAPM9g6iYdj0Z+q/O9Up3hfmu4JiklbQJR+ewHXDCYSf6+cUK2EheDxAuHVGytV9oDxNw1Zvur7tp1woG6dwLZ62SOc8KPd6E/pOHvu23fB3co1p7fh+q0XuX1pN5p68KoIb+5PlRys04Tn5gizshyMiFhxeQ6dqFpL+FwE1+44w+GbOMYb9B2uz2Y9+FWJuEVas4u+TY3jYuKjkePt+ztuQ9tz3N8ddG1XUGOyK4juuxZE/xrjMpfAT34ESB/VAXt0SehgdScn5zuUgN6MuxkI7nXLoEgwcJccilwGg1MBxr0VdpDOqgBx2PWW1XOG7AYXJtKvID9cKKiMZ/OHoY7qXZTy10BhdpW3cOW3tSICkeQZkfn+5Ch9Qp5E9FxmablnROmCDDGKFVIoRFsZ4iI+aUpoJQD9DuQhn/2iWEjJv1xbkdSlXJCTcUXisuKR4siQ+paWtINKd4ZE5pARU7GoSAt/G1eWMcQkiuz8XX/kfIvHCLkr1Tzkf+F3hgK/CllEtVglKo2y7E5drvS8FupFvHx93ca1wpX5tOAqRPVr7lOsMVgL1gnrNRvcbKTaxGbLLaQhtX5puw0t1310vHobdydH18GTx3t23tXZHc4eYa+fWLz36dfr2evXWeZrIFDFSsvDYHmk2k9tUjhyXp+F4s5n3q8DqhVtPPe2kHcZTRZOGgIB8wkJB5n3m2oR0WAX5uXRjdwccz3xyYcThd87whJSSxA0+u43RSOyckLyIgqKSsosGuRjnan/gqraqcf2NuF8Gj4IGjiY7kmii/dVPQh094aR2no75EJap47QEVy44wEUHccZTvwZcdTxIlKn6owvSZ7xNftHcTbC+fgjl8trfdNXffcPnH7+zBjjVY44/dJv/dGFLn0FX6uF4kcuOrSG4XfHqBreG++liu+5Y6CG9Vqj/DMf/5L4O5vNT//cITf/jYunc3M/8J8eHcwq4ZYdtF324+DWARL80gG37MCE9Y5Ek0pwHxsPzbzTLPJMIcgiJLBGhFMN6SSSHJLZ+oD13XpIJqMp0AxZhNGKcJ9N7aCtHXnQcCUapwfTIfRMKy8ZF2VsvZwdJmQNOYXJFWa5u0gS+0EWRpBlKCOxWLkP6Zcv0+X3DghG8WAR8WRxsoQ0yT8a0W8oJGfvSCF1qYw0trwb36RYPo8JJvywBmCw7A9LAN5fhgIhqxvxfEvgSzZuoMCD5VaxPEJhmOpDtWY1VsRgpcHKX/C/kFeHsvHYrrB+qtYRBSvPlApUh5oklG+stv7QxzUB1WcSm+W/0jBYM5dyaUHhtdXw+dfBqgZr59fNQ+cXxh8rafNlGN34YGCyrvUk9P8IlCYbIAyvgzVosNHKSy9lIv2fTbH52yBiDU+TbAaQ6vN+XJgPz/retw+LyPar9gc3dbbMEuBkkKzCOicQbMY/wuLEO0OQsBV3MJgJO3larv/ZgDf3QMk0trCPHCj1IwRscXKQI51KhHOiokBwkXz/C9ecQHDDMKtLeNI23GvpNA9BEVnjYMv5iSVZyqPA1sTyhBc+T6P3uOC7PqWntyL7wn4M//C7Nrbv/Boc8D4+h4JgMDnQUpCDBSHoMy5ZhCaHPcLf03aw78DNwZYfHMEbGQEFOVIrykgoOmLGvDUQf646UKxijYLifor3hiaNKRNQEv924/Pbg4X3/F0nJwUp2SkGjL9TcpHGqeqD4P7td46OoZfeuHX/4prSsvpDMhJ9+mGCZH075Jr7a9r2+3ktaFO/v827MuDxEIyvJzYFAnrXXw0bNJ3TyzGDkGk0N4qn98Qg3xXMatqYDpWNnKAnwTQ/gaRc5NEQ8n8Snj4BXf8+iUM+DZO1CuLBlS+JmwWdBPlftBQ2/xMXPomAphVocNEHF1sbnBAkmTAdXPJHtamrPzlUajNH8RCsIvkAdS5JRbeGwElN/frc6+CyF33+rOw2EdLz9nk/AcCqCSS6OhEerRzlPITDuif0gINZz8uLzi/7zcRaWAEqMSulVrE6B2qCRs+VPWep/Ru9RKyrWBqfkKR7AQ7DQ3Xfmwa63BDv3dpL55PrmPU9i4ZDJPQ/8DG2N2Cxe6E6uTHITQ/cHBItk1uFbRthH+V2K9gnAIkdrbGzBTTy4K4BNsl1AX31BnT3ZmwdK37t0Se+qZ0NxF6p2Ohbu1I/BzwOhi9fR4zmta7zRuYK9hbhsGLHzn893n4drMEjwxK8so3H6CGPrapvPduD09LDSy7yxOPDUsx7D2Ji8GS/czOk/INfpcCxY62BnD8Q8HU+viG8lSdL3P2uEe8WDOQ83P4uuWtgCb5H+fAE6Ad/VOvP02s8NfpuP4+wL7/zhISwtzinEwR4QW+cNGbQ0WAuztbFzsSciysmvTGLpPQula4nmCQ81Pt2RXWeVqXD8IPrPgO5/R5GMHsjbvIC7MJxdowa1417VFFcu2JT9QrionDJjzqMAF+5FDT+RN1xKC5XYXa/mdgz6jjwqdtLWCm5fXkiJbSjC3OPuLI0FsXxzMAqdfTLgQsy646+vQ+X7vjLyYsu1wTXPCZs4Z/XW/j87qPxWNr2asE23v1pjtj44M2N2JYDX+p0c4zYSrV9mPyGS6yK7cE7g3f7itdh2WvbnHTS0dw/zzrgYXUOZURQkfT2O0efxmzJ0MBP8C9tn4/Dy0mTHLrj8AXnn4L+fEgRcB2sGHx64L3P7fZGnC2pmLURKqPjX4EvuAwMZAsiIAe/rpvY5nTG8/0xTukbv7cTc1OHAh2LHs/Jzj92gD/z4Rd3XND4nWr750ZuDa3MPyVgfQpdGmXBFE/v5z+rbY5yMfjynV8l6Bq4ExkEbHwT1HXEtYhbNOmSY/Ad8UQe0natt4exR+KiPSU/7r3BDx8r3mfGton8q/FPPbWwLiHg/1ri+BgPegZvd4t4pUfEf4oEbSntai7FVb4b3DvftfLCQnnGFgn9PRIpEGNEkg93yNuSS2oPmA6RfUgjhI9I+hQf9fjYEWTLNk9ZYIgcFN/QsOzwiJTjfrzIiFRzSvWCekYaBO1fvw7+uI9mfmDEJxmf/vRMpTO9DgYv/tnYIBiz2TKTIWaxmBVmkzs7vi5RdOHgSGAIzuwpxGVuBE/KgTfet+TX7+AbE236qeDPlScE/v3VROVT1YIwP1NIJCwRiUpYIhDzjyieN0hINPLEkxrJKGFJS1Ih/cL2SnoFubVkFlRAyCZjIIUPYHFsvxbFPgvp0a6cyihfFUKxgyykdFbeAJU46rSXlELV6lBDU0eYXCP76pHUgDShpT9oAD9LmyhpbYBXZdQB0PqTKyAnsHVR9LpmdkMfSUtSpIHjV0N+GnWo413jbgempGuR7kIwke7agsJ0QccqRo16ov9d0jDNmCCrYFs0xzeL+++bij1YPFwXtY7SciLBIqt967lsYwlSbCdBFOwu8hI5NGIlldI+SLpvDmTbH5CPOUO2f1iA20jD4Tii06DGjM5yCde8JYRb/jWCO43bz3+JUPbQhln6GZ4ZvewFeQOuVoKPv39TEnylf7JhP5Y/A9y/BnIgiPungBBsDfl+9TMkiKHCMGa4mxFEhK6RjEpVkYyOjJjjT1MTjGWjSHH0V4yPC3SGd0wQJgYxCUz2MwU1lWlGTa8ZkdnU9Lp/VDMbahYx/NtlXqpl5lRhrrvm/ZSPBWChsAgqVgn9I2tpLXM56Tn8O2xyETO+YLwsPf9JkgUVox+fBm+b5kpilVI1/ROoxl4hUdtDW0XW5WO9sEHXxtrEZtQWtiZjG9geVDtqJ7vWV39G90PtF7whetYTr1ScpQa0cdVVz6AJ6yACJP0hKEaLDCY3RWp+L3i9nrdLss6kHjvbxNoDAfIF8kIr0ErEBglIpTJyQPAldsqgqqjjaBA2746jA/1Z/bQNET68WfRGEUexrj8B1ITcZp6uZJnIKqX14g/FThwgPUpALCSHqktImyMbr5xCVUm17tBL8VGc2Npz5soXA/sXTt2jODqhZwZEPA4L7UyFSOMlX2nF4+Ef4+WLrxxlHUfNlw//Y4tcWo7x6i1HzJXpzgYXvX7X/AP6Uz/41rplWP+Of47bn/Zp99/sl9uy8N9472IEbl9p+dEWFrR57ypcBexGZPsrvkUVBHxsIrr9nGV0oXWIGCSOoB9dnPFNBZ/tzz1O7/L2J2v+DI/RJfZdsdOqGppuRxfe2//wqBNK7pAPuiSL3uaifkiGfbIhmjTNipZ8tBLdCbbVji6D0WVf3dpAR5A9AW3GFfBeR7Z/p880O0f3dTtgX4Z5jr5rtrfrv899y5igRwD8nc4vbPv/1GUF28N++42E+68d4wxyRHDrsg3pXaEewyQ2BkurrhNOV+6Cfyq9Vc67FPVK0axIcIVeQbiSaHv8gVG7OKgfTvXYhxPlq1iElII9Xnlrt7QQ3P2vJla5r5ZPPU4zGvbz8dL56cFQPOJ4TZ/DmefdHybGmAzcgWBoP0CE19pvmlGIbovY6+GO+ZiE15SZ1LwWLP2qdFyt2WhCYouKiBVJ+0FXql2wHt9T+tMGUbAupsxHJdSj7FGHOv46sTjPrGZ7atzapz08uqFPZ4OrcNN1J1/AfwfVVi6gl3pNwJ/PLcfzEjlqoiBW5B03rqxjSYRUklTLosHcpiuRDX/jNF751+ubohAZYg8vrLxKlIXKKFTVT0eVo5aRulGM8WouFXPzO1v5zvY2SgecTMS0eoYXOKtFc7obzUWy6tHPwqWDQaQErkYZki5l5K8xE2FKzPBTzoJZola1jib9k/ttD9jNy36UA7iWCjLV0mWnr84Aggo8ftzsEcAEXt2zGitHGm/y+UmMWaK0xw3O/FWt6I8bDaHS5ZuypX3vDV0XLagmGKqQKKRikoKkBpna572x4JD98XRQjVODRtEKXRb6dSO03MNMJKOOtIKZa2EVtiu59jpIgVa7j+cV2Z5Ft7MarL8YJheKipRBoXr4bmhXn2wP9xKNn1bRlaDfKwbNKISrxalIyZ/vHyzTWEej9dMucewc4+N0WtA27n7SO86w5dvHbkFXbB7vU/YZGmV8eawZr3UxVofaG9Nq80nkIs+DVgP0Gm8HrUcbPij7wAeviiGC0B+sNSfRAfBN7HhiiKRUUCnAkx2T/IGnP5XueCZLsHlH4V3d+WZRMxHa5mZXLajzUy80FA/j+tQS9cdB2as3CvPhQcVaO94aBJsMTKvHQfU3kP2dEHKjwc/zD+MnATnFhGMcNLyyaYb7I+L4wnmRjJyLUQrR3eakXY1lnCdHOmth/lB13Z2fZrZplAiy9LpBCUI5POh+CgOfMC4cMbpG9sG+o9zoqyHW09yIIECqwfd7vEY/J2PLtWPfOVHcTxgJSBEsn76h9eBzFCK5r3aGemI1toArvmYJ/xjDpfg7nTAOMQlzOQ7guL7Y95LVCBgc9m74qNLHaAmMBUn1H0ZmJ+scUWx93UpcjiUrcT36tdkiM3yCMO1+m4/II14TyUpIHdH18Mxxs6Hgr7c2UMwbcm0o1Mqhp7mrsFefVnUfE2zVOaX17IUZ4zJehmxW2iA6pl/oY/0ZdOsot0Vwzw6uQJZ2osZntS8I7oAh7MNXDsdSEaIdElPbp3BbaROeNk1inwonnRbM+HpjkB0C99BK+jh5j0JrFIMocZWtbFV9x0P9ca0rU2uHukVjV1VWM6yVae+PHEyWkOOUs4kx58uHfPbRTba7uK/00bPoZ+QyRw240gwVo7oYJ9NkPxkwjWNmKV/AQlimZXVSqDvJ01W7zYvc47HdJXaJ3WN/uFG5LljJDGyJfFyH7lLTDzFQBaKQpjGen8pMmrIOZlULK1FT7bfrlT3jp4cu4VARCXEWEiKlysiNn0SVof5B3aahV6IZp0W4fDydXiFsxHtY6Dlu05g6YSYWYXWzPcbpdfYSHCAVyk6sSBC0Vxu7yTxykdCulIoKVdMclyzdZadHhDbGfvfwnUcIYsrH/LBkKe4aEm2M/Rp0Q4w2zvbH6cnPjzDqR2AcP9PmMedgYdQLnpvVbFcCeHRoNfXGNHPNfVOYNb5Nc/+9Nc3z7sKJtGmx4JiW2nioqz4ty8/9idvXnvRpkEOc+ODW0bOwTYO4232SElNmKhOpqtBWUJ9LBs2BLNp+OrUQINxefTMBPe+3Tz9fpo0AHTn+soaMhhD3tU+JJgonToX0jhsT6RN1k5VThnyQ4e0swr+W29Pkj4fPb+ur1b1OsFVhk4/tEIYHM6Zu5d3Ri46nadynCcd0TCtjogGvbNUJu2I7r7rS5+k2onBif5B8OZu0hNly9IXKKXCW29ZSFadevh6CaW1M9mX+3Z2ny1c9gzCCCcg58lRw8DimIgYoB90qfIv0vvsQzvje676NMpZI1k6Y7jCzrpiHs8jN0s8KrBWb6oRrVUvkEY+SnA3SibXbZ4dBPlQFpaKaRl2u9u8DrhM1chp4JplYfj/ZW0a6OPrsXBW3jdueWratIj+ACLZcoZ9gjJETQrQEMQl8TsRQkJfN42dq21zSG0GGyFYkl4B8OxYQYrpNSrktQwrVFqiNh967d4KGZ3NAq17ayegIJ81xuimacR5J95rjguA9o7bJd+cR4XKIQQhXGRUy6rDGTDaRKZiFOPerYGmxAmuDjWKbmx3Y5+BgcS0kNqiWDtUzgAAiSEGIW5vXT+3zNcrEFI48j66pRVeyeKzh0MfW1V8bu1QQILwIRBtBzJVUSpaWvH8UqkqqtVL7aYTWolPV18BYnGmzmI+FhVmrsDE7POCZjJonDA0Rj5O0JrqArEZyorAoa6HKTn3l0GwtLcL1brks9MIwjfEsEcadBsyLYCFWibamYicNTMcIHYY+QbmKJD9zMhZmtdgUWP7lLIDMMc6qn/UQDYXtxyctOqqegRgrGkhJ/1ZWHPiC/SyEQ5y3naVNbGd5Hf2sBEGt5W9nDZCibtHgMH9/tm4e7Zlw1trPYJSuomfYZ3+qQwUB8+lLDh0RrckY+5kQURFjZloiSJ6pmShTrkKlKtVq1CoXfqKpCpW/VtRPNTdagG9yEwZFm9X73FnqiZQxRLykRcnc5qBQklLSMrLWfik5eYW32Bk3laSUPZDGmOVh2fJ1E5Z5kzdYxGcrlnXYXL9rcuV2zzVGd5vdlcE6INPEIGwmeeH8e1Ng8g/Vl8kWdu6xUvzlG9/a/vNSzWSFpaIc5AinKhklH5CfXjiTM/7NhX4ClpZcMbRgJku5LSJ3QR8e77p87c1YCExpl6DxYskhOmz69M4Km74y+uHZ4cOT6s/vWdz9VLi9RN6GE5lD4KOeyLcBJXt4WvqIcsl+2j/U2y17yKTJtyXoK+H3sUy0ub21DRj/R5TlbXHyRwCti1AggnIs7gEEmTwQrFLoIMToUX7bHvCvCGqL5r+FVUuhxZs6X0KLShNnVAbC0FP47u2Evo/8Ng5VGSmiqzUIEZZdGR0MElvrbFYwImfXBkB0qpOAN1NfYlBKo8R+NEqaeUgJ/paipIPKAVTA8iYeVHgxhlZonjUoFSWic49VM5cuWKbtnhOeBKVS7cZsw1D3ya2MhVGacZbiDYfQyxfEsLG0toobsxEYV6gTE9Rchm6KkpBcvS3X0pAp7V+4273lHuGqadWJDQzowYrWrYpTgu4k2I4iUi9JHGmX6PU/sA1tV5SggiNdNaqZ2e6f8YSkfx2m/yFcI/k1fBbSvehEZ5wUWPfqkPt61sPmqpApSa0Gg1k6MJ26p2G9ze6la5FlZB8jc12Rk92pcgPuSRryRua9x3ka+WrxN+RMNVEI8vNPRkHFDxpY4bZVgkThpTg2nKPocAXcJB0SLRZvJ0pmZiqNsuElk8dZRi7Xu88PKdMLflx0lGYqi5fdKwyi4gHdO7DmfqBGjn9N9VWVqmJ1QdbMjNpVoq5vV3fEvkE7rG8aNweZNyo1RGhDgyY6TTz8sMzNgmdO+pCY0GlqZBnchP3mrWLLEqK1wRh/QBdtfrUJ4nawY037nfOWrg5DcdF9zND7B3uOyL33fm0QG4Q+d1+VLPXHwFzc4MFpGsJwm+/2oWUsPC3h0dIIehpFGXvSNm0+LzJoPtO44I+y99lvbnWtPU2U42R4vDqMJldO8+fS4cSI15c2zW/At3cTzTrRO5cB7/U31/Ks+NDTx/7x7zROEaf3h8hkupINZ7YWpwlS23t4mmY5d0UBeoIjzc8xcICFi/yjB24FeTYOt5a7jc/HFKE3ymJPS+X8yf1Y/kMJlrTZCHBlOV+1t191uKXV7NPNEdeebPVjORate6PKd3We6KZ/YlNxE8xRsTUxHQyFtx3awe7MQcDm5OpKyWwIq9171v5+kA4itDcbJ4W+VCMQf7AP/0x/kwzrf36KOerCzoZYdBjYboeSkW5NOJIx/xo6rqdjt6kRw932nJ9PR8TPHbKEUbb8d/NTqa3J3LHitEv+j2j80ktaCc2vkF89rfbx/4+FaWm5N+PON3zvNGZefJ2Tg+BsfKTzzvtnWFh94/crX2X6EaHdOZx//nx6IIj46+GkzqWgfi9B/FM8Lt45y/5Zbx6Xv2DvR7rqcNsBc0lcZ8LphrdxvLs+4r7fqLoFjAdih5R8zTaRD73hBbarbnkL2J2hf7v/H6laxrPaX0RQy/gytrUpB5QIHAoQ+lMCfE0kAoiN69dE3yyTiLAiVRkfpeLjVUVfZjKGKr43SO43hWjYlNYbVbJdJPUoaYqYFtrBk/vNfE6CT1FWRn72IVX2f9Nc6ITW/YCBGmQ+Fww4nIV0UunB4G+s+cjcM2NpMnVOZg6Wj1a7uU2LVTZk2zisBfUgffak5mWQPdIckDM5OydXveA2/hbB/OSxlpeUuy73th5tNPkqij/KEje1Q4E4CloUUiGckfRNxDOLMrGnQ/mgKkZxRYllwipH4wc8TVFNOu3/yJI9S00M6ZllgCM1ltI/41X0cktUAghCWT/k0PECLM9Ih2OkfLK3YHIZkkLAu0bWWBWhhOEOZ1Z2xNDqD5WZVUG1VcXVR1Y3tsiiMQJmZjWi5tFRq0Zph87wea/aZgJIf9u+Cam60vMNqN/CI+tnBM1skECGMlKojVkQmiiaJoYZGC9al/maoFRh/tF9LbEF0aIKLXMHeIWt+GH978sy5zrQRiqk2A5Km9kOf7AnBzjq/mdUhdPUSITz7N1hF7H3ULg28X4wKPuP2U1aP7l/0j9Dve0fGD2yx0eG0fYHQcNnMLLnKxvCSzkzfN9Hwxfjz84HZcdtyfb9RsN/9ukT5V0CRg68Wn+HGKQj+Jiy+RQi28z9UP85bOP98BwR8ZERf0p42RyJ+D1upo28ZAy+I0c1E0PNBGEorQEE42Y6v6kdQkbk9DQkmhLdehhaguVoOSau9934rfUA8qB/Le/AG6p+mBA5Ov2U/hJ3czPeATQ6PI40PiJh5MRDoJzYt4JwPzK+JK2jmZMLxcwpgtSZ7/qHMZNUK43prb3Rcwmykd5NY5vKiKj58AAyX4x301fRWRJRfdFfd0lqXPS9TK6DmcA6U5GYmDaA63De121K/FYC3dZ5IUvrP/URxY7MmcTMxexuf52zbsUtP84TPPgAafkvNBQwKsS5HYJdfxPht32obUhprfVvqS+GLag+8lrO703zXGi5oPaZCxFFj5xa4/pj8qdJzChmFcM9WRONaKBdVwOdRQyq+6bVbnEsqQJxWt73uZmDif+JureuNao0Sg9Bnzr4SLhNbtUqc/klEi8S4ho+jcz8PF4c5pfbP3LFIsP8OZzOVzW9EFypStXY/naUMhTFTYu7Tbu63NfELa5/IrYHNbWnFYha5UNkTTVyfbdCSg1ozJGWzE1ggwPNuiOnhZYVpgY6IctSu9tElW7vTVl/EuM9d7gplTY6/wF2db/r6KL7MgrtjnU1FfS8qQmZjpE6OhoZj8y/i/wQKprrFpwPRjJ45oM2/Fsn7oG61eBeBHZ+M3u7PdvQcp906FTsfxjEQH+qTtOgh4oUjdWPthYmlEKxGL6mx/CQeQSjWdYmYInmu7ij9+bydBoPLTYwL48dP1Rvinh/70bdH1s3xqkhWubTA2LWBOISDDr/eCx1siUr2MbL0tL7jE/aaY4CR3SO3xIox5Mz9SpeH/bSG/St2f38YfLHkqJ2zX55c7sIfDsNtRi2+VASztXzu37gfbfdUKrlF0aA3Pc2eLm1jaftURQ+5mh5qsfzzpdbz5TK6QsuEs1EXN+2HoU4G7k/dxE0v7vQck+/quNVj3P6j0WaiA3x0gN/8rB8lvpfxKZoRatcq/6fVP6KINvEIbk+WrJUdwfAv9v224M51r4bzfUrnxvnh5ej7yHqWq90sLm+kbc+e9j2tw8RMu9sG7d+qP6NsTc6nPcifcbrFu9Vtk6x/5SXpjSHSB21CNnjwL/9YjJ/7+7u0lY296fvzb8tk9tZuDkqGw8Kh7c/Dg9/o/bQE31IF7X5AzXahFdvO6MjHA+1Lrir1qsiO8Zy0l3PBSEyFT7Lt+3f8oMl4rbxOGkzYtpTPs1xjV9C4tv0eUpfY2mM+zk5MxM8y8JzwTfd2k85WrAM6vk768cC/1wc8nZjdg+0nKx/E//ITxeW33fehoirzNfC+WZIt3GX+e6ne3rQ3/z3ykChcVt5/6j4P3Y87x+5Ft13AnojZLi6iUIQEYg/wHbsJFO2Ikhzf7T8fCcF+gV0fa42EbwFyUySO0gpqU2mzkGaIX1t9vQTgwZFP3ferqn+m/NRpL4s2toOCNKG29oH00f7IGyQx3E+9e3Tl+A2kdBzqBQ5FiVGIXxoFmFGRqTZ3NtEf6XbP/R2NvcmslFnQ8qjmPR+0NEsJ6qSE/WqommHCLC5TfvneWp7a/lUC0GSWn6vCi9ABJIJQDNlOzMG8Yzyy/v3LdVDLpsuyP85XN8VVi7Fu5KcSNHKsAqkKtVQa3dxKwcdq3cuj9AYt+8v2X7fljns+6VpLYe0rSNXmguA7kB1nrqkG1pzXgP0dEvhkrs+Dfxh2HtekpGMZWItCtOMDGH22AxppZYOKcOGzUBQ5K/miBaKliDYopVRrcOm/9K7DQFtddhlD6B9kBwWgaPqbVeP4eTv2ciQs21hF5Er3SKru6B2Q/UQLDzHHTfvuQivnDrs/cxvbxgeFD7DwPNuIV/5LC8vzU+Ch/8khpvWt4Bn3C+qjxx84a+W91gZJnAztleQTVBHHqohPR8y+RwAByrBKR+Hwc9If7YkFvDpfoqDtIJ34P8Qop/N1eHZxHh7CRQBTyDZ8f/gFHth+Hfcj8FKrvQztD1ENc6amVpi+xzxZiBUjz1swXSjbrIsJ+BNSMqcd1OJCP7+oT4+BoR1I4cbIF/fIXFVaQnhb2ZEzai6TAXYkyiB8O9+PhX2rUGJCVKER9L8GlJEIDpFLwh/5N9Bhf5jxvhGKdubtH93oSkcEKlGd5p7gBDbPypo0dtylu8w3W3usBmLyPk9xY/oP8yn/9jPJLJIPZYCPF9BrmCSUX71JlSX1G5AigmJEYPLhGTstgm1QHGKBxrJPQ/Eb85xrP5vFROCkOhoWs0/zSlH0tiTD5Gpf6PfnykZ8hGcnxxMOVRCBR5xXdQqGpCN6CvRRkOUJzgX+ADXJ8proNuP5EH7A/Y4VPeRf9tTBdnFUgMQVeYqfuzI525WIwvwck+TJ9OvluVDP9hmPBB/AFqnGgsZD/X1ICOz03ZxJk9cfgP4/ZMbwMfXgdIRfQCjIc8Jwqw4Y8TZo9+JWT6Hu91G0fuyff4VbrYiV3yETWx7paBAzEeRFbgrrXS550BvJW3PjWwomuVhBZ53/s5CnSf7+dc0FumvCfPurE/5cpVFwZY/+G2jtxuDen4856QRFFZJqCjwJw1utIwGnepf0JjqFlLRogUJ/wdNd7L8pxaK2yYuL2s9Ol79oSLjE9kY2sJ8/0MUdws+sK9j2wq7NeJo6jS+M+E/0LRBqbtFITlGk8Nm11yU2x5PGrugEu0TQ7ldRXRCkUpY+mgARRn0qmsQoSz3TFIgoqti0KyhJM/YnzGgngI8bcL2ec+Ny1J3LY7inXu5EeDzE4zrQ6/T44F+w59tDW0vuWkvVH8s7aH88cKRMCcEL+4gvKTWYDH2imPYWyYvypG5SqkcTe4hHTfdeAWNlOMejh7rT5Q9bCKpY9DO8FgtHyK6f/K4yYUgxlXn0Q4TvWRcddWWJ5/J7HvV8kXE6iquEdWqDvV73r1Vh9HQvK2VvZzg13lzb4ymuU2f1U+Hd3uTdgvq9oWUvsRiNkeqRa2EX7voGW0ei45Vidk2kwwtIAhdUhhqR/QLxr533KHXq/FQMu6w9gXZjN27sVVR7/YG6TZNPdGbgeC3JZ7Sr7atfeF37H3dOYRv/8zSDQRc6tLf/d/EMTDF+JCiOVjjf4XV3RZz+NrlcQiGODN+lOQYeB3tksRRRqaUlOht+2j76Sw4NiQ5jWNi2kcn+jn3LRKT/vw10KuIHq1EttrLs028XozED8W/7282RRaC778N57uMNBwq7/O5Hh8WzDHbrY/LV8rtim3604LpuHzGyv6TtO5BeBHY8jepJm1mwNinD6XR3naccsANuc/szu7ee3gHCJSaW1PRG3a5FRRD+Ko4p8Pmc6P787v0vjC4Chatzg+5vb1x+5CHaBx33FTGCJYWlKOtP41X2/Dv0ikjvfhXH8yLEGlhuUruK1o1fLW1XOf7a/dgoWI993H3ijdoKaItbjfKnaXFbnc9O6/RbI3rGhvow3wm40ib3gK2q+TA5+8bkjEJtBO7I+/l3/3xxxgSvSL2pu0PtO8D0RYPrwMchfe348SJzi2M/HHM7TSl/jf1mTw5TeyU7scT+XSl6e8CnKoh6f143rLOvDbQP52/XfgyseGbP4TGt/grmxLgu9K9f6kF/K7m037dHvL4o3gkBWXgugm2dONb4Z0fYpRDEO7jDt9v3B1Y83HKgVx+Evofr3ps/zVSkmccWTNHj10FXhm7eVGQcomhpZuQlvxuEa4Wc4xYTapcigOToz+s44TULR0M5unfqsvgQkuU8AY8jidT3xWuHKzytf5QnvaHPrSDfc3BD5f7XzX4H2ohq1LR1WCT5t/qjHDwtnMc8OX+n8dV2BpZ6lvvj/aDp9qTmLy8mk8rRpwGhdUOPO4NiYNroLHiokX8oD8/5f++CRJSycuPy0c278JLweNxiNc75qYbLKhmndAa1QU99eH9MQJwoB8E85I/O9SpW/DW8qZNEgQJaJwUw7/9xHKQsC4SEYndRAUxLTd+0RP86j+vCCS6Ixp83iF3FbGN4gxPo1g/SA3mRkbQUYO85panorhtQbgs3rsC8K59PDIeHov/vuPxaGHsT1QOLofwfVqSSSHPTl64uyiWZ4nNIEX14pitjnGgkYK5PE32+Xch/n37dVr/2Nh2UA7yV55U5XBseXwhPJB1HNSTTShomnoredAEbY/qik9Qn8az/4Z6mA6iNwOCMSXAdBCTmY1gafMd2vbtXff5AsTUOFjHCzCTJ5mNgn2sSnlwiNNcIm6xBUdKBvPAvG7zkfjFLwEJWLC63EMok52FtUTeRJWf0OumpzF+E1c2w5aw5G5Rd4gOLZjCy5LKUgjplpCcPa9l4gLQwMXfUjJNJHJIxrLrFmcAkpophTdxfvgOuXHIN3yvh4YscTMtuEOhHYpq2r58AkDJanQjGYitDKv4v6vasJmedMSYb2d3S1YjqVsDoZbd79BMoLMW+8mzU8xeB6tqalN3AxJMBP07JUHTMpgcW1Fn0DTGob1Q80LSDh2rN1uREv8ZmGpDO3TBaPVDTwpXptfWBPTRYU/RgGCI5QcD52HEIADL/6BRhn8JkgxNOA6jv2QLeVEexmEyBpnpftECm3KYpYl5gH5S+ko0MWjOsEC/f2VaooJh5egCA1vDIFQbQiBb2wH2/rE1ZndKB8CRG6jlyx0pp3AeE+twLDnIVJfqQFepbnCnVPeGEjw+iXvpTTckajS1qmDVGJ5oh5c1Du+BTHmABIdTucHYFfIJ3zGxpsDBzLjM9eE3FQne/Eklh4BOJrU+ee7SVskj0EGI4GnBYEgTDBWEYT5VwfAgRGBdX9RPPUZEANypmgZRIiRCGmSrjEKOJER126EuRwhe2nhFEbkORjO2ZflkYaXlkBBbPSdmoiz87mpgcRozxgXhf4n175Xete+ks1o+x0PoXxPc/DKTUyTOiZgiKbWvzdaqFQQZfR+1mLxupqiSOvBDOjeFOA2RPu89QEZpa524iRAaWTwj6VsmKQOUFZj+SXIr2zlwLitP+VHQXjQd9hmeoxTOowguHijKJY94ao6c+UkSl2rlRFl+k0V5P55DL6Shl6pQZVRlYxMvUktF9XST4ap5VH4N5jhqx/3rOOpaTuQ86t1AaLwu86hmk6hZLWjN0s2vjNHWHEuyPNrdweyMe+tyDhPoHuTRo162XtioOwwr78X/fryFivXzKi4a0zNE/bxxRQqrPlTf8I2xnVwCTNXqx0DLC5JaWXcZNYiXHebhp7oy1DREumsM8hqrjsPXmUY0ilbqUehSeMyKxhZN3nvux+PldiWwMQvHz7kn4EkQ3Xu+Wi1f11jedB8QxBtmeowEByAYqHcv7rAxQOTpPM2XM00tY5gZ4qYoouPWQZJWkJKWqbY6eQUarlFJmQU/VTZVex11hSFikGhTiPlPiFMYVVIRNdGgWjqmRw01VqhJWYV/olY1cXUNcsX9QYvKXJauqyrsiGrRCpz/acDrAd6ol1aE7/BwYoleL1tQ0OtVZY1k5Ocg9BNRxSS6UjIhRxXVuD5PzTMcql0du/mMgYDkIRB1t8GUJhDMn1mdyYHBYjz5R38DAgxKbehqoelGVbC2hzI39dF6mt51LRiJx59vfcmmWlQwekLELRTMD2OB9X0h7WUU5gQRsP4t1FYYOP3crooa6jhNdbA9Fh1eHaOw/yi8t1QnobA9507HoisT2P1dxFUP6fajEPQAzbiVUu0GWxc2abm2NPDK09CWSGJmqhxwxyicDzBp7mZULur7yV0CjeiUw4KKx7yR8gmGpDoy5xMemG7xDlpaTEH+F63m39wJQLFSYDf+qymt8DmevOgo/Ou8EiiCrQhJ4z6MItz2zMik7WXdFGmIogKxRtMSQHxD1x1g0ExJhOTITSlwYE7QLUV1I/XucSezSBGkP+hsFJleADODde65JFkwJe6oMk06Zl6QeGpXMHcN7gEmVKPlgn27CqLh4iwHFUGaGxr4u99PBSPp0KlCYw6lRSQtObMNlabOc9dNbS/1AyHH2urglzd57mUZtx3g6lxFvkGdXBb5XxU4yLB8KZrNC6UhNrPBUno8lD8s+mxsTXA7hCqKh3PZ21I8WYkBkGpIP9zyrxT72WhNJI1PbH8s6V21tB1+LIKXCqstdFhYd+nqRX2h0HjibUUTXTKWYM0i2CfGdlhfiRlaejbznahHbGJFA1rR5p6+X2kqtw4RGLS8W2PXqYmP9OcZfuuZdcU6xnehDTvRAt3Pf/hoRYa2nQm93kZ1GH+7lK1ifcCAW4u/nPbsjHwK9H3UWoINITa65vOQNhtC8NErVlkpxySxUmx91RAfkMVIrLIO6ZG5UocW5o7Lawrj/gtJbBORzsP0n+s+iv4sZiAoQZ0r5n1/Pw0rLfxLa08L0H+DCOVJ5r+Pzwew/L3eegG3EN5djCeWVeiPWXEU6z52z3yD8eB/J3hD2Ly+fQsxZBvkH9KPFiM3Tdsc4XcsQwG78OEO1xplHw6PDYQb6Lh7dAqhs8hFrnCzxvatz0Ql9t0bEtQeFLAWwt3Hk3N2eZoN4dXl2Hh4/9P4eQt/0XUAeKoeH1epPuHb2k/jx+2sO/yO51wO/1RAB3AE/sLGSk+jQARJpwzl4FGGDH4WwhbS/IbkBI7QUcIy9UVoQhfCjcsS8StiQKRqqEjvdBMqyqEgMoejSTFLpGIR8zHKxBkApWaQvEplJJRQjMsR8cd4rokWJURifh1EUk5BkTwavvep5T+kEANTFdJogMUo6S1K499vaJhqpFv5It0Y8+7HIcIvxOMxBf1J4u7JVQrsyU+1l4y7zeUYJeOx/cGq3mlTlKzMyJoFA2Z3gvRPZEZJbcJB0rO+p+PqR86/h0crud4sefPKLvJXxYJwRpLDtApL0Vx6CMV1HaeQuZiYkXFulghKjRaVMNjmkJLaf4qqXSv4UYbe0yqV4zmt0Au9LBUNmZp42gx7s6VJxKpEVWQOBqimQTWJ3Khp4rLUsq5pZaE+KKmDqW5x7TaoXhobKsKPsPkp02ZcuxX0vLiliqZDDVKNNmSiE8V1V+66TPfSXEV9SncL70dEcsZgD6vVhWCb+rd2VsKIO8DCo4B6HGl9k17tuU6ZqqjC7rzS5IZ0Rw97ml0V1b3fczY42RWhVukd6fWPaXFriFj/rzOAG2mlj/rv4rpJCvT/2cMoA2sJUrt5Cg5KGeoSkJvD4EiOr6Pb17+3MjY+LC4lCcdr0coCTEzsb1GFSemZIQut/XUuXn1Eq9VuKK+TrCIncc9vSuit3kVO7ivl/cCL3Df5IUgQf4SmYnqUnGz4MBPXPSZVmf1jwMgyh/lvK5tlgbD4bWLXwapGX/HPamgzhqc9TK5oQ4akkI2lVj4hQcXLmt5uroBcfrihawWjZPV5PxV48aR+PIWlYU4nt6KsfkO89ZeCWeGq3us2lluzVbohk2RZLuJPyJkNndeI69AGNq/ANTegVrNaOQa9+maNVsqyFdvNJmI8lg5t3Fo73bzC4PYuYcfqEi93TC9ov4vqkf7E3Y5Ru1h+ShvLzNgt5kSrtRf7oxyM3eK/KYfAbIyyxVnvBMhhgTeZ/E9JS0nuG+xb0AV935/Cd0Sc/2whAX3/voHkzv37kSd+jqUuV1GLPrqWhs9yG/rf7vSnUh+Q5TZArDApZs1C369skcFPF/HPF7lRuyirX7RUU2111TME1cikKi1HHhR0FS2lPcsbUUGouqzlzvoGG+r7Ji2qdnUMrO+71at+DQjh0P/9qMY1qYi4E6f4Pqm0MmYWc8UCtaxVrWtTaZbqpE5ZwGXa71e1ro2B8X1Y29qp/z4ypu8T0cL6hcu+OIwqrbjqL+bmye67afRSQ4011VwHj9jHgMga1DCi40tcpCZMoewt5/hShNeyVqrPzYYKa1uRsMm0fZqvdma8zzWFVFlV1e79+0PGOnICZ9AIF11tdfTgatSt7mQKUAUNpf0+7LH6PkLUXzHhZ2Jjk/g+VWkz2Gctcd/nLah90ZD0fZkKSU3tCuqyb1A1ZVW7OpzgPN3AWT7OFV3Uhbyzv7GXYODgSvbDuBrVmImqKTOquYvTcQlWXOvasEXtas+Bvc79fTJjy9939FxDhYqVIs53TryfJlapOcrxezWq1sbOlR5UWFHFQeaFJvs+q7wKyg6pQL2caqp9c3vePxt+lRoi5iUhG2O9LuWcC0Wd989CLUp3/6qfO23+6d6g89jiiEIS+OU5n/5rQtiMHo90/0xki2ySWu8XIjPOfNN/EELm8MJZnUjbIGzeP20Her8DdmPk+9oiKCYwi3yUrp5ojjWH/lJbSJ0jUl5zt9NgPcnS1fN+IpMczEEo3T51H7Y2YVxqk5fF9e7jElrJRsELxlWs6wOJX97NNa5yXhV29c4Mecfqt4FXctiPq8uxsb1S8EqOmHp6TcGY++Einv9wVEEipSDKFhWWin/kvrxqVacBmkZYH2qetmWWV3f5cIu20NHx1H4FaekSPKyWfXUOzihgky/Auy6hcBFEeN93vh8bTnBH6r9A1v5Hwl/S2xBJFlGwbZjXDMw1C2JJrKjWbKS2Zfh0WHLeay7nfvYyZRCA/m2Tvch6wGjCl4KfK1Y5y3u7Cmejn4oUSsensq4qVMVPaor68TxUe2gcn5oTQ2tlaRedwxNozLskim4ftE9tXy+S+mID7BvqMDruXZSN65LJwsW0n2ZiEGjOtKhCSxDMtrL2reOWb93CG/4gxXJb9U/LJ5AIiQvb/rLMB7vD6Ke92nc4JDnSqdG7s5xsDZ3R1aIb010BKv02z9WjwPo85a+e4XV4eqfN3i3guZLah+CrnsgjlZb9CP70L2BBARGYr8sIyjNYcIT4x0tmBUM1wqQ1w5E5uT3Cf6bWOCNee3MDEdQpMLJENsdCParGMUpBWVqK0N9K8foLzqwWkexoREyPbO4S27MTgArKM07xgFOe6J8TKm7+/vuxWyaSkpwc8t2UvgImIlVa8xn9TNNMVzWDmdl/ymIMKdt+UDhz/CW3pV7qtGcwT5gfhwL/OEY/NMixaRSmas6d8ixyMRCu+nYFlghLq6CM/klDrp7K+XyULwQvMc8KQ5U/VXE1sWZBUfvqTbuOor5LmplqYGM4myqyWdCiM5AetX513MfZFreF1PbaoU53MSuNn7qVHpadvzx7K/atjxnYoX71Y0D3tyhxMI5DKoazGNd6jjQHJ6uXeP8fRu2PbS3HpU7UyZ9e8Wuonm+Yb9Wv7zDfr4RmRv1QP3KKH9M/SWB+nkEznkUozXMOmveCcLF6LI1XU076b5/Ir5tYTk6IlXau8pjb1/9e4aGItpLy4T3X6CXJioNxLrfdj9q5Rv9yrhNfbLRzU0P9ezys+f6pB19ZW2WFN4uPH/G16e3Pkzp5lY6V9hCVeW6zPRnt1vvxC6veKfD/oxva/1HSjP8I7PDhNz6mQTp2dtV2A2MP7dyPbN1l3INY5FaRvX4e0PUTwEP1tnobrCoOLdiBpQkfqe1tFDccvsf9Ob2L4w4kYoJ88sexYyTYR3+tTq6vEoZJ7OfnofA5PESm/dN5+vmDU7bRDpRLBgD/f+5AlYyQbwugn9nc7mmmXf9q7Th5JsDXhhrQ/evtXnpT4xN46Mar//tWQB7n2frWx6MW5dZ6aPKtx3n+3i6f1zTfw7tauBtj/Ifnt9z/Do/wSK5rlfi+SsykZ+APhZ/WNCDe/5UPvxttS48aUXWCLLSiKJzoPFx2VYJGKW1NKH94OvpqnH8yKmPFfXlehNLhyhrZ1JF/ljzB5SmvVK6Gn2tqzfFndzpbDl2nyka392HZTcrXC3ukZzhwY9FPUMPxEnpCNs2bU6YMR+KfPG/7eZcP9xs01HVLESUOubihxjYG+YI8oto+PydOhjI6/GNQvJ0PX7fy4o24f0vpPI/a+W7G02LYuzbyX0iKuKsoZH70C3cU/w6MBV4c/w+3wnlnxbtydgPStoqv2x63qub58DeuZoggfrh+Y9OoRNs+vyaIRyPQorrXkGlm29OksZ1+arZaiFVpTnl0xUbMUyVpKXndqf7rZDfO6pW0SDw6BN1a2idMvu3p69/iJ6da+efHvP0SAc0k9uyykpk9scj9I4FwphD9WL74eefkTZuKUHkm/7lSbzyQpIN+jUAZa/EHzY8DyXMFL/BYrtXnb6NulbbI7M+W7CfMpx3yWYIgbV1HSKt04bPSExiMwYOHq9QSBr3sXmB9OiZjETBJT3GKzAZZKFhbz9d+o9ojap5jgw4rW45+AK8Pvt0HskeSI3e0ZsriygrBqXsqXjm5rOjK7eG3lz0rt08EPBhe6rDynqte+VIF//EE1hawqqB+QAiZsi1cS4jk10PgxnzSqWfRQZ9eMkQ7xEwLsUYd6NS92sA1FMY40x/Iq19fuv0oLNeDzCoRJwOSr/41ZFDfISQus6UC6Y3eRlfJ5a85IRbZU+ZxYZPXY4e09Fw/r2Ui3wHYvphz24eQHay0zHXod9Gr3JOhiZoQs44pvzhkbltWYSqIFQ97H9h0iHax2C2VlhnKWen3VY6RqnVRra9UV9BwjNJ0iRpF82NVwrZtoTWqdqOpUzikhcfKQR8WjBJ57NXXXfouaZE6fk8qASl8K2Py8BrUGz116Rh4pM642+5hBvYrbDCme2kpEbghu4cGr7dLTLz03/u3L+1VNEGp71X3UTRae9XqAfVWEvr0tR+WrY3uyDDRBn4a3iKbtXVb2xbN+XsArLhrUHU1E+dnzenQKCiWnqJYOwzouBrf0TZxl7WOIEccDQtuqMM/bldnb6aVf/JtFrS/d/oELZn7HIBWzTf3r1X0+6MMoXhcLQ4+LA8ruE/9GNK0Svar9Rg26j2tHJA+dfv1/ND2JqFaCO2a9iv4ZFT2dnDsOz5q2UntO28PvHOP6kLfcs+tOwnXuB5N71ysqq6duKbYDddVZfoQ7oc2bqt6hc7Fay4eA2H9+6yh6yC/HuTJJ8a7W5bPv9rBlm8e+qO/falzCOdP8r16X5BPPXiD609rZ/oAvg/d2TQ47Af4u1vppc6wJUfA3N6ORmA/fyyCQU9uEdxAuwnq3ejpdRBDzlIsddd2neFMRg0dNayXrmdULp+3wDW4oEcN/waIdd5eI/YtzJqG7ORhmrzxTDMX6a7F4ll2Ikoz0hFRvSAfo+mzG0TeghHda0xpqcfJISKXeYk1iJXlp60eptMzcCkZjMoYcTz/GJ9R42dFCxPu9P3EkOVn0toHTDou1OqJJdbX5A09nSdQClPvDUj7K5/XbC2H/axPHjjdY4Y/Mvth+MQlEh4tp2T1ZsMKzKd3qvcq/NowYOvNz+zOVa4V5lzryH3yzNEWeV6XNDmYPxdB4ywIR3XaJ8k86H8vgxdKR6Uwa5FwLF4aqd21hOZXi0qJW4LLamf5RvO5ny8svgQrNCsFVWmnd9tnDt/u23P0dkioNnpgcP92+2dIpvAbkqeL8QND7cMs7Rf70X8S/58cZ/su9U9t5ramFdYl4NN7JEdXC4A8tfhT+9Ju/RE95gu9fjlu1IZeG4u7CWHwmm3RahYOLbX3/PjC4lJGxmtSqNwDO/ZkdbTwjJ7IpJ/dWwhZDMSuFuikYXO9IxA8auvgWY+2f3HMX9L9IrbcHYc+CrN9aymnSsco0c1Dn4967byY6jMuARkZH2S9+6LrsHYvZ/jgj7cobx2C+cSz9pTeXozb4dyCPtUV0l2SbCj71op+R5txj4PTwcCBFji4nRxKttDS9K/DO58a+bSrtm7i68qWbOStJS6hZn/sBuN42pjodfKRbZ/1eRCvuJXJyKyv8YYba9abvwbx9jiz3Kfx7rFmLJgutZLF+w8dmmCbF4bX3KgfkrbxcVPW1pbvGQOmzVpq75kjHNMTxz476wxR9DUOZ69Azlma90pQsi3Zrx4Xnqi1yKUO8amdT78xw4jWr96Y/3fPyyF/f9GdH5ItP8Zp3/uxGGv+PkUFaR0bT2LrNR2bh2S1VyMLf5NOf+eu4db9voCf6nbPDEcEueeaPnYb3Lm2CFfeLchX9627g2yXi+dzYa/bua8Q9kP6UhruUNk9eOnee/Prb/lx5vfg5WyvGD693F1ehSuCuCy8OM+EBO2e9KDVz5vVGXFdhuOxRr58Xb7vwvaiabtl48s60Feejcb5j0fRpvBt2nCHq6AH3WN2jN9bxg/9D27Pl5/vdLff1c3yr1S7v3eYm7vVPzIDBr5gXi6NGOCKL+v1b5fQ2n6ivF9e1hveCu807vEPuUM+LN9/K/LxIkTPf72nRSr9j/ghJ3+58Oa48OdFMAjCubQQ/E6zZYv7U99+ksHX0G/X2i6iL4+Pi7hxgrSP32ctXrJ9BuNlbrrdc2Wcq/Pcg0iCdPvPsr2ozZgmqAgefZt5i9L6sLv1j+vxj93lz9T7tDTsYgBRXqQ757z9fjrgpkO1psd7YknVhCQ1IKfOWQQy4yM4yvabyoMyxxO/OPw+aaKvjHHFfBxNjTFowCKX7+Hd8RLDJB1qQTU9HYK8mam4DlIVqSxUscCGp6jaznt/uyiQlBAk7XzAk/oztsKPPSbfVr349JU1x5lr++/6kTKdSJakacm7pkL5zn/zK9hfs5XAL1n/nkeqpAryDmJdgZO72i33BxxQvddhu6i9Vll4IOkQ+Vf8NS+DdeLTRdNSXIKOonOJFlT//p1dbFb/r0Q1quGRKxro4tBvbArrup/o5fDin8vxSQ/wFK1wpr3kcT9DkDwt1+2i46fC/cS9XastAkA1mq3DSpP9EhncOO9Xk83RV6ncoJe2gAqOi6Fn14nl8WNoG/r91VuyXgAGZRdnztakV0gbyulWlWeOxaGL8XzB2MVaiV2mkA7Bq8Lux1LzohJ95KNklEwAZnoSv7nt80iZh8jrp13+N828/tcbtn8N2sUSOTRwQGq7yLmJ41paQ0lZ5Xao/v3vt+JlsmsIY+HjgE8XJ2HH5PTCGdrwZBWfUl9/Shus0GinJ9QZF9tHI7eIrTjA6FB7BsBecNiv/eIIR1ebSdvk9KNeLmlF80HV3fJOQmNiryDAid/971m5D1w50vLlxVW4O1yEwG/0n1zzFcEz/NmLN2y/I8Yyur2c+0jvhrbcBfF08fZoOhPBxgz+F5MV2wa+KisXZOv43QOrv3n7FcMOfRTtoJ9UC7fNIn8k69JSQKHc6L4vjlW5ESRdUvstWOVcu2lxBVUfofcYBjt+hRG4Gk0KUSMT9Bb/+lO1hQCeze0S4Cgp/RJeWlnoOkRLBFQvFdolOq1N9qNtnz2A5HOIWVl7KN4CDOUflpaX73aH1arWggXW+AG97igi9srHW4vDHoy2fzv27b+22/f1kU0STfJn7wP1ub9xSY1LepTJwahxybxf/2L30B8XtFylVq4NNRVUWNvlCdA9iBQxSHTQ/P5PRpVTWJSoqupqqqXLTY8Ia1yNTMKs61DHOhmAGtSQUTnHFMlrb8yUalZzFo5a1oo12BiGcd9vKzLWZ7JZpGCHyn7lQCFvkhz/S8Wh51sVrp7DKEfElO+Ks6KRulRLZ9GDq4MbvAM8gOIrCFqEUOE6FrKPtmxMfR8nISTjSIF0JBmQBTlUvgpVpISQ13VLoepRm1b1atAkWgZtqU5MVnAKzlDndPHTonpvPvnPI1yiBj+tluediF6zccTH74liKjWreS1qWata16a2tat9Heq6khjacnRED4XvQ0WT/n4kRzrh++KM75daqVJb7ZUEVGiEMz5XUmlllVNYVVZFjTDj3TYZOcd7DXwx89TsgU48KpwGEL1kwfZL746f2b+9JABBNkHOqNOWgr5ixj1PDPbfRYJVt+Yjg2kOSZRaMMTjf7dYv0W9N38D039tc/i+yTGALkMlZqv0l1rTTYpRX4RQ/GbtLfd9fdrSW6KywcrsUy/FQbXW3xem79+GMDit/8ytkGaaIyFkIDfSFf1nXjHFiqnDvlrXZNN6z9WbgY3W+s9CUClrrEyjkA9Kug5uKPPd8RiLsnzn475u5xxbhCW1LjOW+8+v3ebGtNg/ROKQ5h8kkSBWGty10K8bg5yRXFlE5B84N7Z/+h+QaqEHQ/T6gYfHyGyhktrP6gqb4UpHAT9zLcJRsB1Vuaj3p7l9rsUt38GEWvrwENncxcfzT5ZT3XVZMX2S8rEg1ObgRo7S2PkokiHgpio13YGaW0SO6t7q9rvJHQuN+LIkS+iI7eP3eCW8R53j7yyl5W/jBDA4C176a//bjoZZ6mc94LLbM7cDR4m3f7bM6/Xvevb3MQR/5Ek0gGHglkT2tkXVpY1TbKSAF73+TJ3t7w2wH9SyPj+SxT8t6vMpzCquzm6bAbDu4lSiBPaG05oP4EPgyGqxIvf8OYZPpP7V6ZVGlxr4cfz8m4cWfM66iP8zYtYal/lz5WvSRb2Ji/zbCW9foz3uVn8P/myGiPtZ5BkPM8dzm/9pwGPG8TvO+B13/KdhhqE7q+RDomP1/6EZnELO1JK/6P7fNDP68TxhCL1tsGYf8/FAw/EwMaM8wMxz09GQIDLzniBnwWYB9V8L0ECzuakO4JGjaOiPJ9gtDkbxWWfDyBFci392aMZkAvz4x+Yn5eVSCAPt6sQ7+l826i8ogtk74JCW6ghkrVHHgsIxs25DOBOdKouTNboNEV+V00BvpH2j8r9FlMdWMwXKlDOyjjfdpplNbG+gQ8aecxHsqNFJZeancrAzlLP8zFV8lnH1lOd01AQ32kJqqWoZ1xJrZpNPQNCtoa72QuqApW/213eCbZqoGPkQxfosSYoaNKXDTr8HcvZDCrVjFKYQZnBI4BHsJhIFPAZwqBwNFPO8rph08p5mvFLNmAsLzRKsUGs2DkJ6tL+M7TogGiVmEk0azi7EjHQpuRVilSqp1iGt/jxs4xzDNWmmUVwMWqFLTD+TK7gVqTt3j+TrCL8e4Vz9a0AEJgTJVcEOUVR2M9RjWAjDNSPUWyRpBCMqISqi89gVMePjOvZl2SlH1MOYyc1CLNKR7scx4x12IyUYQAK/JZIlbiQlJCvlLXXmGhNpH47YO1n++NMQmQWSlP6AfGVUQoZXC0ozIGMT+tKbvr4ZslotrvlHiGpxAwMy2/G5/tfGma7jkTUhW5QJaPi7egM5Pg/Iad2NN5z8op50QoNcebJ+I+EMFfOizcqL5k7ej2Z5OfHdiFGCHv2IWkeHCh4q6E9a9+58UjnfiLwBOT9q4a+ocrdDrf/9r7phQAH3RFVRkS5kFRmCLL6OR8mI8LVpl35WamFAQmYoMwJ+Hbph+X7V1gXKw7uRnxYV3ZPNFRndtyeGAhjej3jJ9xHTrU3Du+kBlQOq8l2tnKOMHzsxoLrVvv5/gpqr/G/XUmXpHHrvwvZ5ituQEaOoaz9VX2TO0JBAM6jPl9uPQM7slS29NdASrN6PgJZtJWwEUVagu39rqFpNav5DC2jVPRgWeWurtOfMmRjt/fN0acAky1SvjsjrWirInVCXMmpv5LVBwNG/NOLYvQ70qHG76bVfPmEj7+MEke2KUi/7oH7laoCDR6d+DyGGm5G38lqikegdSXrdyeifdqAW/VQ/R7mOadwT0xbyJAmNqfAJ00Ajeizycyax+jlb8PrdoxonzBMX6DHvh90ukrebWJyjro6lGbJqV7CW9csTdKWWYBgB/T6wVrxai2S0ZZCwSbgpxMQtcJey6VAZNpEWtUHo/naqerO38mkVO8g7QFHAJNSbGDnD2SgY5Yn5qXIN7damToyen8Z94me3yhq34R9bkZO4yjVnXPe3gQM3Mhqf8TaYcAvcGaviPftBnx//D0IcrBju2YJR/BmdZnvmqoa4uQfizWcu8EQ3zS8D8T+aZ/7N+DcCtDxjDyScz3XgaaqP5nWH/ybzkrbI6UNLBFFHYoCkoVErHQ7X7rEJS0XhC4716V4DpEbz9DnmmjMynq3i53x+8V/Jyr04f/v88vrj8HKgV/vAVx/DQvETvB4a+GatEmSrBPkHUmBLFW8bUuZuDQ03pDISqU0TqXXQ+gcQr8p0vPuuuf6m034fiQ/raweEY7O20g3pBx+3morbXGSYKEYDstQJfDSGo30g0/6s2UdnlMhMFousUtnI7ibHVsWn1vBHCte+4rOsxC/+5fvYgV6vCyK3gMdikeq9/ae+gzRujTQvgu9y5xv8HQU2iIL5KKRCuKEIt81wQ5ea9SdRFGuC4mKJ9bGfLAlLsaRFZJlRyz6AnJE7X8rHQeHqfXptGvh1wP/Rc7xk+++yd64qGYrqAZdX7Op/mcvVuBkJV1KKx9H4vGZTfJC4bnCrH14wx4qByoftsGqdJubmGHzqeCeVa9PS5csgftuf+H7NffOoMgQS6T5U/UqpnVBdKaiOUS2oqLf+wcgDIjQSNfUjWD8crX+LlJbZyT+kfizaK1PHElf9fBbYSkAX866J1LtC+pSMDIXEicyjyPB4l6SKtWYjgmqjGrsz59O/LSFhEeVCovdOnZHFie8LbQkpIpZeoF4Dx7SaNNuQFqFqVclVL8RVYvtIFNQf9Jl85EZfg36gv1KAnGugg7DAwVCIQ0VhDociHIaIzOHqHqU2y9FY4Bgolk5acYr/KdacgAUCKzGSxvooH7OR3DZM8se/p5p5gYYpnEdNpToNTOeADIsdFjtC3Jy4cP1oNb4+CidmTUT26EDovEEROb8YPtJil4d0S/vvOMRQRrJ+qPCZ6zccdyMa6TxiflCBDSs1sGBqbdJ8FLaQ4u8uuCDc6SNeywYU5RhYvOCBJWr9IsPEDKDUGlo4h0BlAO6YRwVyAanM5cIKIyoHVnVtUN3V3qPmf0ecNpokTqyNvETE8hUF5kTJGFDWK5oEkZEx3nmCWDXSx+Z+UP/jy7hftyDW12Ik2JAKjdJqdQxEteu3FY5Q00Jluebb+SOmWpvDaLgQ/9ZEjlGr9aToVt57s1yHoqVh68yuduvyKKktUM3O+dP2uXyc7UrDQP0slIaYQR5l1cHOEpHXKotta0lJjWQ37Q5KwcQuw92Inu4nKyoH2CYSexVcukes6BXUUl9kfAS0bM2xH3UAg699Vr8yYqhDq4qCWbVif9iIkXYirD1xlGMJoqCNFKN9fIcYT5zgpPKURHfTUtRTC4TG9M9PGDizhmhWKMx9xH/tLRzz8j6+HYMb5aJ71N7v/Q4LpQItoPvPxfugqaP7v0mPvEheEix/7/AFrcdVT4eLvzbor0CeuIz41ayJ7kdc0bPdFfxY7G2/3hWGcNhEGMO6f2x/4D8C6u6F8iiEVKsfHf2x2ratVX6pJfiT5XKvqK9FL6PIDGvypBoe6SM+O96vv60a+tK27aU0i4o8/uapiHL+RQ3qKUi2bsh/+Ksc106vZOLazijcy1aZ/9O9YSVY/lCjfS79YPqeE+/YS2x6bVyWxEVtaTt+zx8pSzvePWr16U/sjHiyaubfRsuX38EnCw//ZsFUy/XuKgVN3FPqqjvc53oQAwnHPEzrI/DY75OB/urUZ7uNtXtYW91+jPXSm27RQTLEOAX6x3PD/0gX+u/LIncbPsEVHTfOFq+hm91bzniEu8iMIP3jvYMPwGPaQThPhDucdCpGgzTxjN0n7lbqNtHOB+qPhG90eh12/EHQiNBq9BRPRqQdsniqcBKRiAPUD9VUSIb1G0Q6yt+HJc0yn0LKw5sFPc949jd6bmJ50eP50w/y5f38N8t2/4f/Qi+ZWpvj1dgVtQGp5xCYcfe1Nc17pTcAPT42IosbRP6NKFaaAWaVt61T1ofawDGI8qmiPiYqgDpylMstBleZ9IpIkypoVwYdWhII6u6HgXec9H4/2c0Pj6gAqQYV3GwOjxi7otKDAU+J9cklNLUmT7VW9605yIgCIK61x7Q4f2xol2lNDRuoB68gMH+158Ifarn0xmSRYD22XTrYJhFe4VE3VV+CYP8jcejJfZSfpHB2TKw99taV18/xJW0PX8FcceBOtliXXhE89E1bb5/MvtZhIdrcIN5j4jvbrEgcfeNM2ImfQiBJEEKqV9DNDeF5UROK7EB9a9G5JKazffElUIIgKUPJdpKqCyNWunYK5rC0Y18mMmSPU0knkrM8qFCxfO0RKaw/1FL6FAKvj/s3PxUNdKGTEmKuhe/lfiTlzaot/Mb4/iQzSKWT6lFDLdnT4UDvnYuU1g6YXS3qI82neVo0Js4b0iQh84ebWmJt8Hi3oTNvj9grU7rQy9GN0VUa+n1Q88NAVm1DLKMypkoymsyFG8o4aFMdZqNYSzKH+RPO3PMiLAZZ5CVAFnaNkzl+WhMfCZZY8LB+WO/Q+e6ErHat/r3EXlhu+E0aWYdQ6XHezi/6sJnbEyJwGiaQ3ixsR/9pNDZ/+2ThELVtIbuwahOFv5XLaBW+brU4Gtnzt6Pz+o+8+Qhr7ZzgXV2PGCu3HHBAC154WBTWD8wfSuQ6uOWmY0VIS74r7QQ7P6rIGlaOpmT/Fu17t7V2GgT2R9e6VSf0iqVLcyH1iPWRK7feWvfa3qDrwdBW0a1KcZ+nhA4VEaBE7vBo+wYa0XkiN+6eshnh9U8a/MpT2drI298KQ9U7vSD7AL6YQwDgh0fIMG5xpJTw70MQEIA2mrifoKwBHH0IzMFAv0AOgoId0iFCMSN8EL6dwkYj/BCxIdMhjK32OziSWQlGSY1GTF2DQnpExUXsokZqyca3hAyK+4FqvBIINpA47woniZJrilPh5IHSnE6CvCd7VzhDRWZuGJXpLCi7QCcwvdZwMynHOYRc3e+q1q95wPmsbMLAAtRCFOXoSO1gMbMkqJYKrjKVqyLKPoZx2axaySqwWkdN/1+rCGuHiADrZrIeQKo+y7+3IxvRu7QWHdErBq4gFPHFIEUx3yUmVKlZRc+zoqqa+0RRgAqFNK34VwJSTSbkhgUkqUCtaYJ+tVnk9v3AgRSrZHI4YxEWxYra3A0NYZCwiKiYGDkoYOmXoiYbyIbL4y7yCo4ckM9rKzlDJep4Xvvfn1fF/UvT0ceXMf85CZ5QUj8E4QKRMgtY1fLfe1zMnH4ziAO+LcbZ4blao5+Z/YhI9YW+vAEe2OYJGCW5nbFNE6OSSoPL1ru/8gweoAoUQTVCk7Unq5Y6WGrZloD8Z+qzX9GS2kBB/rF8IOBAdqqDGuVpo+f+o9/4LscVrV/+gn30zPbORYydP3/pt+ijuUO90z6jHrqXDnPrV7553ludJ4ZydKxuB62Mx5bQ8HXmf7N/GuDA14Wb1Tqjvq3vyuuvajb6zaNf9dh0p/jCK1q/TWbvP2n1YvmXRUJJ33bitxzLM/l9rMTWgjw4MZ/kSJanmqc4o9/e9xemXeKWr1jbV/iR9CL6k+r9nqk8qytqg8J49u4WAvmIj/M2j32m1bo6EjtoNa80I9Jta/mRJcjMuLMYG8T6oP6o0QvDVKaehqz3Cl93MkQfh6yQtd4WMjCYba092CcDUoX0uITncCzALkfFwZ/aEFQisRKcuoccg5837upPem1qARWSAfFljtCBuMS9Z7KS9TXmunLyTDNvMgT272GD6ZlS+mFk9FY7+KQNi9y1sCP4R/V0bc00HgVOFoLtL/ov30L1bi10m7O1IfSh6rDVGGXDyG8r315SLvKgd683P5+NAWVrmxTuBCKP/AuvDpZqiGI4jfd+CRCjjPEQTzuXIIRESyIqWZIfV7tcTMYcC2l78LM0ttZmyUKW8XZl2xlY9ydZrrN8vVBQnZgPPpCZFAkgpvvxlS99KxW3gUoI5WbR+Rp9lFTLBFxwWi6ofOuIzF2+J6vsq15/oabnEtnVpA6xGcphLlA9NzReMa/Xk1k8aeJHeEvKGbuVSUytEGuLdAig5c/+d0fRiGvJjfWuoZFsF6V67avFEPo/Es+WIAw6IHcsDI/pUw4apaXxvALYxC070kbCdLwnYAtaFi3MvpSxnp/dvnn7RTEI5jIqy94NFvzVYlh+k4P9kS2H5fusdQZkqZO0mhbW0yuCYtXvNo5PP0r8LjyALTmv47BX2+GOA4IDTIewBA7bJGHSzqQdhX32GuHQ2XET5WTNFrQuZ7mQen3hmhe16lbdl8/xsX/JohZo36M39AS9guCdJdlHvhKj39HZXxQQmp/+na0nB5K56pILg8IVrBBpvoXqOAQewFsYGZGkvlY0tBu+0cOoH8b6iunDFBGRPbDspKOA6A06xOHxGdq0Yhyr9uP2SvFMyGgwBVdLXUGHpFSwp87zhu/0C2DI2OpEC8pb25yxv6Vulbu6SDoe37UZyUvtc2LHfko/kIpHasH6Z0js9yc5DenH1fHIIUhw9R0ykhkrZ6YRWQ3n96qFnnV8pBnZmNkPxZKQDOVCPuawAJHLuI5VOQ/IN/qXxjEKxoJTcKFSEYr905kT/SJZMpOl0wQ/l207TKP2y82Ig7kRVPmj/AdsJFfASQ2unNWkRNUCH+ttCuD/ixHnTTfow5P1eHrTfuiijwibv4i2/vej5eNA9XyxheNfCuk6iuqXudCmmzeTJ+Zrh9on1W3a9hbyhd/DF2bvoXq7IVXD2o8CKJ85GLEK6jCwdA6LKirm10ewPhmRzQn+aPhUxO2NnYGFDeGl8ZFERv/7DlQk1D4aEnET2Oy2+G0qBjWo5Q+d7MvVVZBTTYLlj5tR00O5xrIQrZa+V+zcuhu01FBmeCz3v5V6L+2nDkMBT9zW3tVPFNfBjd1+R4NL9QSTs90WRCt8usecW7a6OEnsm0bjrQKmtct3ZcgO7mj0dcnJneqKhp4CHwtY3pzDqhThf8aDjRsH4DLWI2FmY7C6xCF2d37v+WaarbqxM3dlpz1N7H18N86UxNE9Wyi74QC+2zMpocjX+W0bknvVp/4YWP+vtPMqom/w4F+rTv/5xcj/35eJ5/Udx/vRzU0eORZ3wrNBotRoGRu38w7/LY/TYmAibhT/B0+OxfLgqaeqy4SbcprGjGrTtQyHN+DhJRuNRvvH6earwbNLiff2o/D+nOa8eAFeRCylZljS4lfcaLtfenM/CKfR9e1XjVdmevpxpwNirryq0YQNXh28Nhszruve0F8211QDsrL8ja1/JtKDt3OsX8j94N9NbyHY2Zm/RV8Kuzw/zrT7p9vWXbsH7z3xvrzNx9bh9GhNPmAcqqw6fVRLPrnqOB588tEO0hYndv31otxPsa2PZ+A/5nn1v17843p9zvG/V12plp9+CYMlz8Uy8Wrj4vU3vr5F4saxfKl5tXgruKOlieR7PxAeg/4yrOZ70RCch+DmWP97yGiC185w35ZteJInXfCFBLoSxtMmRPmGED8Z7kNDvfMDiMaX/RCSphIX8SSkUytSbA159pDnE2/T4sWHvFztloCvhK8NvQGZPzVDkB/6V1s4hYJ23ka+7KHbmhIa7dRrb0GiDPVedSpQSa/pUokaNP4UWtNRvBsf3EN83bOHvH+P4GuOrUN8QHNq+/8uf2/sXafKVhEM0gzHcQ1h7AJIhY/uIUyDjz/idsUzMkeCBUOT9j3ST1YBm2MtR3b6iYM/Gd/nxOc9GfLlXZ7H4/jDNpQ+C+4P4fGfBe/rL/6h7YJg8UmvC1/i5L/WW7Q6RGkIZGz4bnuORbDfEFrc3NXrfeGCFGGKJqbYXBTvHyUWasl8fk+SepNOioxlhXLr/lke21o7bHYbChMmKL6myEpxVynxpaOlMuo3f7e+q3IpqqH2D/d8u+oGaWcuOyNq5KYm/APUCrJ2C9DZwyfR7aK3PuqP2gAwnDYpGTYK+Wq8eSkmNB1/MyPFXBbnn1uRZdQ4oGV2Wi2Z1so2ANB/SKBzMtrNFWGbdTDt6qL9DQMH6x/GFYbjoTilTU9O54JwkXm1o3BdS//qpkS4H2vabTAIEDu1qRnADQ0PdSme9AK8Mdq9Jj69n+JLpHso0q8J+vsZoBgoDNIMXloJ6e0WGAqF3cPd2z0maJtENDELZEZFMmqc0eeEQ1kYU8tPsdS4iB+S8Dq3xARrJGJqZiiJOAaT435NAWJyamKkhS93ynRsvJ8+IGSiM2Q/cyOYpZVtKCkSOY4huXkivOeFbxvH/MSGcSkYQtfcVFw2cipUEWXvYS5mlcjcpSAcLDveKD/uzO8mVpyZqFyvXVb5Uf2C7vUtW9BbjdMtRO0KIYTDukjU5+tuiY1UbCihxl9xQEJFbSfdNomOq01oVh0VmC2kVrWZjjQY7TmdByalw51yxzxvnnic1BVd85Zr6dbdceoJbBKO2qN9tN0pvdGX0h8DicruSqV/7oUO3tqrI67GIZbIMT0mESx/uJnrEEMZfWM4ZcSjrDGNo+t55Enam0z8z/Q4ZbKgBjzF0dXMl/EUAg9C0+zaYc+QyNg1KoqY6JFKgVwSX5sG7NGa9Rw0rwFR7783yCpV7g8A+7ypyBL5KxPkgtsTlyzLfKnKqQEvsiawpNoNhW+Odv188YwF4Iiby6Jfu2Nf0jnWtPPSMYFXmDbJBHzr4XBUtnq76ddP+XtMaZVzWbAmvWClsp4o6A1iWogGlK1NjxX5yrZlb3fNz3oN2RqyPVsoCcGBaf+mQFLQ2mqFpKQVScvIhp7XV2BnwH2qudC4fj6PN5C9UvArFDHd+gHjW0q3fuTcPeYS6Qo19Z/G1LleUFGkrKIaG/LxFG/iaOPts3z7DIz/nVnQLKuCdo/ZjNnm7FxA72fAT5ETtIEDIjnQIDeBqmgpblfOPWeFpIaWX06GnrNhU2Rxhm1Duh1tMJArzz4pMPQULv+Wigu+xtsPCxxzshqCV57HyxDw8em5ctPGxDToTviEIh5f/t3/6UcGnV8QKyajko3rBxbknLNIK+YSKK13U5eq93pwBRuJNstP1WHtfhoB4u7F8KsQGI39lN+9j8QWQZjMkiUEX/NSFrJCOJkPiW/bnLNIzwSzKEHMP2LDmMWTvCyh3yXcV/lZEhvmLOVwJSy9t3iw5muZIIOcZSX3Jk9iUUjO78M2pRBf25vWa4cq+pE5/gsVSCtOhPSbYI9yJ8saNGOqhFKyWijnrKRv+l5VpEpJS7pSs3RxWYd6nzVY0tLUD0qrNy3nxYza+YSEzvORv4rkWkm60Atf8N/4NKQkfRnQUIpR0kkY52xi03GZyEzmtsjHp55/siyqJa1Y1rIxcOPkKwtbFJT6m61yh11+bZVgmb/1kP27g/sKOdpJwjnXa+GSs+sf3MjF7kqg8MiGWJ7ysjfkI1/50V8jAImSDoSCFKTge4g6USjD8Gs47AhSJA33h5FAFP8L9KGdRZfoxuwYIXFFjSGbUmzEXa4WGW9INBK6d6ACfuqM+5woSlKyEpSi1P00ZnrkHyA4A0657JJyJkXWCBEfD0k6Q5Qebe+Kkvg0nXjCTnPO9gf0NRs5h5yLyMvYVrMiP5c0hEkU/P6/jtuAhR6LKIpz+zZKslF1aZaAjyV+bgGCq4zliIp8OEXZj3Pldsu6Kui9mq6aNai1FcE6VpnquUMVqYZA9pCo3Fi7KoFCN8ZsNNyU796ME1W5BbW1tt2rtvYE7R8k0maM5+dOptNSBzvH3QF1obuu3hkbpadTKFRFrKiXfVr9GlAHB/EHLRpSFYfjNBKj7zd4DDE+t4CeCdcTFibeCbDIQNgsaSgmPwpDY1uhJljLderniXo3XM6t6tYkp+/otxlynvWcjvm/lri/VsSYF6b2x/Knhzgc89KYl6f2F/+iWMl5NdYmbTXHInDebxgk648b/acL+mbLjJZ1iL8xz28fQkLyXb3FddFXJW0D2xC7WSMp1Ss0S8dAUnIvlZqW7tGn3qWwdmRydnF1q/yVeL8IVfpqUXMvupu1W3aH71+qBz3e7Wk+qLlx8b8twi3iljYidyVWo0WP0c2JFTuOgd3use/A0KEjxz3Z60jHznRCOl074+zI+5fqRfXybq981ONorv31kegaP+hy0DQToaL65qM1QlYJn5j4BxoNAAB4CyGAtQpOwcQsi67RaNxFowubuOqZmZc5c84555wzcx7zmJmDsV8gO29BGz+FhHYW84jIS72Pf5zomMu+ZhefENLp2mM5OXvw6Kk76MFeD/VI4iRJe7aeeSXpxfSye8W1G8OzvfaKjI2NTYxNjU1NTU1NTU1NjY1N1y4sJ1XuydjU2NTYdBW5ZJWWq7zVT5g9WX/ISfpzYG1tbW1tbW1p+aGnM56TVWb0RZbWltaW1utsY2PjxcbWxtbW1tbW1tbWxsZ2cc/1vDs7G1sbW5jp3G97WbNl76yBGAwUOOOOVNBgwU2Y7BTTZsyaM2+hi3td0mVRTnU6tn5ow3o3upts2baTyZ7eMtvzp7h9EXvxs7yC9/OfOquEV/R6iZ30lDPnLly6ct2bvd7qnbOfDH29dqRh2113z8FgDO14C+/0FOkvxS/nleSUXjuvR9P8lt/u7/C7fs/v+wN/6I/6x3v9E/1T52eT3r9Yu2HbXXfPwWAM7edvp7bg+0eH1zZcYV7ZqPnrk7GhMfDwO37X7/l9fvBkaGhsYmhiCDz8tb/BtyNXhubqzp5vMzNzMwszCwsLCwsLCwszsw8xFXkqCxtjfBHEGMNP4qkRHZNrY+Ni4/p1yfXxCf2mys2JSbktOcW138F3+i7f7Xt8r+/r93/5+wP6g+v6UJpVHklP7nbOxzqjgx/VH9Mf15845smNbsGbPIV2FvOIyKhOOjom1q776aEcDU7OLq697fWuD+ecdBA6rp04n6VTe1P57tssfD/L1Ev9lvUt5h/277J79BfihVkUn9CXdJYmHqkiBBAAAADsodGDWTAcKxoGpwtP4y4axxvXPrLwncXQsmR5KxV1a7o+25C/xuwW291hYNeefQeGPdzrkR47kwnqeO0pk5N2WM/0/G4v9PKYan/vdtQ/+d8Gyzv75dEVz+f7RV6aGT+QiW/wjWPi3b7Zb/GW92hvjLGHRld7nlqZTHRXdeQC3EXjSM/le66+01q9Xf6emwRXeHS7ZgM/ZDi0n/+xBRAAAABub/RLoLwpDGbpWKkd3EX7+akHd3lqHKEYdOE7k9D+aPxYHg8L71+pPBUR6bf3d0x/Z/ldfrff4/f6fX5//8Be/6D+IeeHJ6p/dO0f44+fn+jo/kn9U3f7p/XPHP/67Ce/fJfNnW1nMb/EZ3af8x/fz3+u6Pw13q776aEcnZw9eNQspPoHZnsO3hT4miWyomFwulgadwcWz5GeU8+554HLPf+mTvN6/n3+sMcvKbNeTjq2Iedd57+eO/cdymhydnF16/wWulDl+t2i7nyBTbdjdxzcv1QP1ePdnnzQcyP8vuTRufS67M6XdyVWo+WKXNnNjpWrcrWB3e6x78DQoSPHPdnrSMfOdHJNp2tnnB15/1K9qF7e7ZWPeqTZZx+dadwmN1V47f9mOP1laMcD0HgwMjIyMjIyApq3wCOejITTHTCAQBUggy48fSWmpqbuTM1MzczMzMzMzMxMTc3MTc1NTU3NTFcaERkV3S/hS3NZ+j0cPebKTJl9Tb92+nXl632Db/RNvtmgB3s91CNnPDF9WnvORS+7V1y7MUy7lwclTtrttW1t7Wztbe3t7e3t7e3tbW3tvdp6tbW3tbe1Xzfv3r37EdxfLP2Urx0TX+8bfOMYYxA8YR9j1gc/Mo9aez8S+5yOGddjAI7E66P9EsIYa5xxzjnnnDPG+TP+jDNo4Br58/w3iJChOhCDgUKH6UgFDRvOhMlOMW3GrDnzFrq41yVddioTvn9h7Rrr3ehusmXbTiZbeHTESJH7IvbiR4naX66sokV37KSnnDl34dKV697s9VbvnP3E6Ou17+Y9fW/3J/hJP+Wn88w2Hx0r9uocgwTIpKeGzGoOcLOzne9il7saNfbQaGKXa8UATrm9n9xPjaeJcH48x3tFQZT2DdFqCXCzs53vYpe7GjX20GgiVWDFAE65TeIn/RSeHsGzCtnD59uhQ0cOHTt07NixY8eOHTt26NCxE4dOHDp2iHgKztjpLV/8KvtsuA7EYKArz/DyotGQ5qKKyEEAAABIcgZWAGY56TgFDEBx5DLNlQDXXLefLT+fIs0NgAAAAJDkCqwACOAUMADFoNbWnTt37t15cOfBgwcPHjx48ODOnQd37ty58+DOgzsOZ37/UfJIciUUhLUhzQ2AAAAAkOQKrAAI4BQwAHywpNKc1YSg51sVAMA0MR0zMRtzMR8LSgEAAAAAMHNa5xrKsLWhOWVX9+hM7H3TJHEhP+N7fK/v8/14IPKVCJgmbGxsYCIimqC5lq/BYDAYDSaDyWQymUwmk8FgMhgMBpPBZCCdisd5p44uh/dgv7gf485HXzIOGsctqQjAIAAAAGQ6Gqx8WQQYGJwuh9O4i8aRHZHtS2WV+PawfZM/rSp1U/rn0YAHS7/uD4nh0b5NQWHT7mTttMzMLSytut7rRrcON/eytPu1B4x/Lit7qqdjz3dr8TrXtL/6a43f5fGeLqMYhxzU+8w6PCJrWkadQr2kX2dtY2tn75B4wl7/z5v25MyTzWtZ3y/nYf0zt570Xn3c7VM/cmfH/Nx3G9HI/XFw7Qilgg/a0atfUyvhE+IlJKZBvAIQPsIeGl0Fp1ZMuIFG4y4aXTFa9czMy5w555xzbum5d35gzmMeM3O22rejfG/5vv2zaM76K6/BroBPok/i96szCUp6Za8JtarjTJg0MGVo9PPnzma5HJ5vavZQ92/kb4Et39woP2CtdV3PBhttOszXjsaBJaGQ6G61U+qphIrgMVIQP42fxc/jF9FL7KHR1U5txQBO0QAwdcDvtAJzgqObeQDGg2EYhgEMo9DBTt8CXz/LUP+LJ/RjjDFjA41PxhphmqYH0zIty7Isy7JM0/JoejQt0zIX3UxX3M2GXNg74kXvXJbu5Zo+qUx3IWWtvF5+1mtuDAzdunPf0Ze/Y52sK70mr5c7Ohv/svPugqVV12K2vcVt/5TQY5ySM1zjezbzXycgwRW+vkWOe8KpM+cuXLrq9V5vdOhsJ6jjtROmvevOmFtYRm19S7+Hp4z9+viG3JjpnB99eBliegEQAAAA7KHRZGhrxQBO0QBAro7Lte0FyE29GhL0BiAAAADYQ6PJtb1bMYBTNABAkJfokTtn3/Ptrbuem3fFs5611lprredZ5znPYlN43uG8MUaw4BdxL9/sR8RHLkdF4kXjtNsxG/m4UY8GECbik+LN+OT4lOBU7KHRNOJMWxGgkWfG4C4aR1QVNtzF3zehi7EUOUrUrlX0GDFtdXu6U5546pnndr3o3l739aUzmKx6uPaI4zPppD3T87u90Mtjql3f0uz2KV0XYyly+gxd6+hZZ7etbk93yhNPPfPcrhfd2+u+vnQGkz09XHvE8Zl09vZMz+/2Qi+PZ3Xt1alP6BDjSRI795lEetbL9Bqrm7sRwNCo471OdOpkE97F2iWrU3dMt7q7270ejon71tuZfv758vPt2//cdklqvXGexYbbeEIbPsgznvWc5p98w23WJ3bdptmfMMYD2nhYR+4Uwdm/Qu9QD48jGPnyBp7v6MvB9LhvMDHrgQ9wMExWZhpj9sbkyQc8fBX6xcsbeuLR6xAPXodWIM0h5/uPcOE9voh9/grcwtzSHHI4zenOMJGZYzyZm1tamVuZW5tbmi/6U4Oy8vHZbb8tVhVvvO4ApySTe91EzjO7urrGeoeMjE1MzcxP8SdPG74FN3RzPa3ZtcX+bzB3+gE7H+6ke9UD1YN66HiF/z6a8/z3oP4ny/sjr/VgP3R9/yav+q/Z88rbi8YkUfDnd0IBAADcNn4JlGAl42U0NPkAnAIGoOjbdL9P+RQg5cuQ8g0gAAAA/AnLB1gBEMApYAC4XZsbgCLj1cxKAQAAAFClvMikFAAAAADVzseXQTMzL3PmnHPOOWfmPOYxM2fVcjvABe/OdecmMEAd2v30ABAAAADsodGDWZ6saMApmio2xqZmXlZXttNLYHbtlHfKK+Fjgsfogvhp/Cx+Hr+IXmIPja5SvgkvE71DowGg+hNinw3tjP+hEwGxCgEIkwamDIk6m74UXCvR10r0tYC+FtC0UsHhbKKf6G61K5upRIXoMQIAAIA9NLo6VK0YwCkaALiqbXFd/VuY1rLLYqSg4D6mooSEIjEiv5O+zZ9fYPN5VQIAANhDowezMFYEcIoBAL7l37zYkWPE7DlxbvJiXfb7722ncZzLfT3Jb5HjnnDqzLkLl656vdcbHTrbyVkdr50w7V13xtzCMmqvO9mPjhOwuhktQPPOvqEFZwggAAAA2EOjaeAUWv1kbjQ4RQMA19uDWtSUUyxAvz3ke/7fMUhoxgnB9fbiu+EFWpVCAACwh0bTlBO2Tq/NxNixkWOgadx9ZClpljt5vk1MTE3MFvKcc8rMzMzMzMzMxMTMmYkzEzMTsIGjY+e3PHYXUvY6btKmSt33Jl2atJy8Xn7Wp7ziVa953Rve7Ftf/r6t76zr7jF8dBDQl19+frA1llGtOXfgLhpHCK7o/j7KOJN+b3Uda9FzlnS3KnYyydrr/nQoC6PJ0srcg70e6pEznuT6cu0rXp+bTr7v9P3dftCPx5x24dEpprSWD6kAqXTVkFrVAW622Lhpy60GYw+NJqVuWDFAat0Ed9E4ImZaSSSZ+fygDjGGsl4O7lxJ2TmHOPcyvZbVzd1EwNCo471OdOpkk6O6WLtkderO0d3q7m73ejge8fn+/vdX0Os4jj/HOMYYY4wxjmM8lzyLK09ejnGWdb++Gvs5ZQjMO/pEks9Hf9L/NfcyrHgNn9u6gY3HxJ83RqPRaDQaDQajR4NHgx8GI2A8fqNtJbPZbDFbzVar1Wq1Wq1ms9VmtpldzNAheHLXF43df1KuBEi5NqTcAAgAAAB1b6EtpTAIAE4BA1B0a5fp1el0LVTt9eaPKzOZ9q61pQKAAAAAYA+NvjFvV8lKv8o+q48uo6620zW4i8aR76v+0lrf5sfVEibaQVuWenXacVuXRgACAACAPTR6MEsTKxoGp0stjbtoHOnGu5x/VC4tBKbXHj20ZhroaKytra2tra2hIe0hRaxPbVbqhGtodBVokLZ9exDSCi3DMNxuWAyLxWKxWCwWw7C4w3CHYRgWYwcqoiZbZHP/0NadNNA9+rJ+5jmN6P6q5V2K76UeW8GWVqUQAADsodGDWT6saMApmipmCphpvYVs88PvtQWmdn9mKvFPxP41AgAAgD00ukr9Jn5M8BGNBoCZ8ZCaOQ7zp+9HstS8QJi20hljjDHGcYyH4+EYxzjkoZXruv651rXWWmutdV3r6Xq61oWBgRj/cTQMSXvRaIxfxia99nXcGBi6dYc+ZYxtTCqMbWxj17fX6/UnwvE6juM4juN4vY7XG+F1vI7XqV+fz+efz/W5ruu6ruv6fC6vr/sTCyelXJ/rQ3Ptqjwej/8ey2NZlmVZluXxWBGeCI/loTqnPsYYv4xtbNu2bdu2jbGNMcY2trHv902vjOuhrbojmwAx2jTEKhtAuHZ253Z+F0YRe2g00cqxcvLB/8RqV+MuBkfixQ+0ECDYZIgsBXCzxcZNW241GHtoNIFmKwaI7ADcReNIwkSJeyFAlr0yZF0bgJstNm7acqvB2EOjSdxbKwbIunfgLhpH4mUf6IMAwT4a0hyynDo/71/iV7/53R/+xBdbZQ+NJtA3VgwQ2bfgLhpHcpW7aH0vQIx+MMSqRwDh2tmd2/ldGEXsodFE6ycrBohV8zAG3EXjyA4ObkzPDzu8VXKzbq52qCezd3Q7W3tbe3t7e3t7e3tb2+qPcOuPTr715hxsDbb2thXGbQPH7YP2RzSP7L8CdzSZTWaz2Ww2m80mk9nJ5GSymMymNyWf/FLj/fDi/33i3DPWJSz8B2Zm0EuiAQEAAMAeGj2YVVjRwHJ2bjTuonHk2r5c8z8Aevv/m2L+96COuVK3v3r7MSZFQwwCAAMAeAtvFDEpGhMTE0ARAxHMX2vstJQuQMqAIWEQQAAAALCHRmMQAJwCBoAPluyNcu29bwsAAAAAAADM95QCAAAAACb+kwaKjxAzL3PmnHPOOWfmPOYxM2c7UMXb3rtcHIfmUfcS4LvXui+OERv1zdlyAQYBAADgyuFOvzGNtuNyAMNy5auJAZyiAXjTe96WX/vovcSbRINqV3oqcSKcIwAAANhDo4tdWzGAUzQATA2Lc7oRPjhKnP532Tw6NS3jMMYYYwzI3jZNL+PZ4dlhHCDl3rLm4S5xOp0eTpfT5XK5XC6Xy+l0uZ1up8uJCnAc93PbeK6v30k/xALk3R9DvvUDEK69vjf25t4a29hDo8mzSZkVAzhFAwCNd/G74pJ3VdexiY2L76ESA0nOLr1yc/fw/mCMd3evHz3OO2l91rfvm2K85lZU/QNmDQyN3j3Hw/JN1AZ/wz36Ij/+Xj+IL4J59FpikfQJAQQAAAB7aDRjFpkVDThFA1WAuH3kaM/uf3JSBWbX3mlmKqEDSPwG4l/j38LfAXtodLEzrBjAKRoABs/3wZCwJKqrlJ2ydo4BJoHYxT4OcYwS9tDoKgGsGMApOhoBDJ3buXf+Q/Do2+2XQAlX8BQarqJTzOTP2b59ge2eViUAAMB4C335yuMaYf3iG7MkfDURGJwuiMFdNI58w1+dph5XyKaxvwMSmCIbs7JXHZU6YN1xOpXZYmNrZ9/DXo96cjaT3Nu1D7g7+86wj/Tx3T7Rp8fM9vyWxV4+ZdVP4tOcZZ1Nrzoq2+ysO06nMltsbO3se9jrUU/OZg4u4NHpW9EwOF0DGnfROMIvd06YuybqcZwkzb2S9bxS5H4pXfV6elOGbo2MTUx7t9eZzp1iIrtau+b+HDpjn/T5bjf6cjzs831/vy63sbOzs7fzurhn9YfGD/PDffC5Pg/nTz2+/PXCepZXb3be7LzbebVb9vuub799Rn3IC9jDyxGJvK7+7e+vyjHPd3RDK7i/e0z8Gc2QIUOAhpnGmA9tX9eCQUMGDRo26LFBQNPKTh31N9qOoZKhEn2t9mF6KhkOBokvIb6OcdENYA+NrvYRVgxMHSPBXTSO9L7453y3z/8e1HHjpn05btpX4hoEAACAutdc5yBu3LhBKeKmfSUoxTGqv9t99O3GPOfhPz+iYAB6pq7v9RUDAADAHnrQGIRpn9a9P4xTDQDTY9t5Y/+lqDeXx7i63SohHW9IJwAIAAAAyTiwAiCAU8AA8HltstFSalr7RKaSMQMGDQAAAAAAAAAYgMG1ScYxiD4izMucOeecc86ZOY95zMxZdXxoqZ3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Emoji", "Noto Color Emoji", "Twitter Color Emoji", "OpenMoji", "EmojiOne Color") +force_autohinter = true + +[sub_resource type="FontFile" id="FontFile_oowaf"] +fallbacks = Array[Font]([SubResource("FontFile_m60m1"), SubResource("FontFile_cti3n"), SubResource("FontFile_7pcud"), SubResource("FontFile_8npy6"), SubResource("FontFile_vgqfe"), SubResource("FontFile_ryy6m"), SubResource("FontFile_nftyr"), SubResource("FontFile_a3ivw"), SubResource("FontFile_hftju"), SubResource("FontFile_x6oay"), SubResource("FontFile_2xrbr"), SubResource("FontFile_g47oi"), SubResource("FontFile_eoofr"), SubResource("SystemFont_7t075")]) +data = 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Vector2(0, -10) +cache/1/15/0/glyphs/317/size = Vector2(9, 14) +cache/1/15/0/glyphs/317/uv_rect = Rect2(244, 1, 9, 14) +cache/1/15/0/glyphs/317/texture_idx = 0 +cache/1/15/0/glyphs/290/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/290/offset = Vector2(0, -10) +cache/1/15/0/glyphs/290/size = Vector2(9, 11) +cache/1/15/0/glyphs/290/uv_rect = Rect2(21, 17, 9, 11) +cache/1/15/0/glyphs/290/texture_idx = 0 +cache/1/15/0/glyphs/324/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/324/offset = Vector2(0, -10) +cache/1/15/0/glyphs/324/size = Vector2(9, 11) +cache/1/15/0/glyphs/324/uv_rect = Rect2(32, 17, 9, 11) +cache/1/15/0/glyphs/324/texture_idx = 0 +cache/1/15/0/glyphs/252/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/252/offset = Vector2(0, -13) +cache/1/15/0/glyphs/252/size = Vector2(9, 14) +cache/1/15/0/glyphs/252/uv_rect = Rect2(43, 17, 9, 14) +cache/1/15/0/glyphs/252/texture_idx = 0 +cache/1/15/0/glyphs/255/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/255/offset = Vector2(0, -14) +cache/1/15/0/glyphs/255/size = Vector2(10, 15) +cache/1/15/0/glyphs/255/uv_rect = Rect2(54, 17, 10, 15) +cache/1/15/0/glyphs/255/texture_idx = 0 +cache/1/15/0/glyphs/337/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/337/offset = Vector2(0, -10) +cache/1/15/0/glyphs/337/size = Vector2(9, 11) +cache/1/15/0/glyphs/337/uv_rect = Rect2(66, 17, 9, 11) +cache/1/15/0/glyphs/337/texture_idx = 0 +cache/1/15/0/glyphs/275/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/275/offset = Vector2(-1, -13) +cache/1/15/0/glyphs/275/size = Vector2(11, 14) +cache/1/15/0/glyphs/275/uv_rect = Rect2(77, 17, 11, 14) +cache/1/15/0/glyphs/275/texture_idx = 0 +cache/1/15/0/glyphs/362/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/362/offset = Vector2(-1, -10) +cache/1/15/0/glyphs/362/size = Vector2(11, 11) +cache/1/15/0/glyphs/362/uv_rect = Rect2(90, 17, 11, 11) +cache/1/15/0/glyphs/362/texture_idx = 0 +cache/1/15/0/glyphs/214/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/214/offset = Vector2(0, -13) +cache/1/15/0/glyphs/214/size = Vector2(9, 14) +cache/1/15/0/glyphs/214/uv_rect = Rect2(103, 17, 9, 14) +cache/1/15/0/glyphs/214/texture_idx = 0 +cache/1/15/0/glyphs/269/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/269/offset = Vector2(0, -14) +cache/1/15/0/glyphs/269/size = Vector2(8, 18) +cache/1/15/0/glyphs/269/uv_rect = Rect2(114, 17, 8, 18) +cache/1/15/0/glyphs/269/texture_idx = 0 +cache/1/15/0/glyphs/809/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/809/offset = Vector2(2, -4) +cache/1/15/0/glyphs/809/size = Vector2(5, 5) +cache/1/15/0/glyphs/809/uv_rect = Rect2(124, 17, 5, 5) +cache/1/15/0/glyphs/809/texture_idx = 0 +cache/1/15/0/glyphs/244/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/244/offset = Vector2(-1, -13) +cache/1/15/0/glyphs/244/size = Vector2(10, 14) +cache/1/15/0/glyphs/244/uv_rect = Rect2(131, 17, 10, 14) +cache/1/15/0/glyphs/244/texture_idx = 0 +cache/1/15/0/glyphs/319/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/319/offset = Vector2(0, -10) +cache/1/15/0/glyphs/319/size = Vector2(9, 14) +cache/1/15/0/glyphs/319/uv_rect = Rect2(143, 17, 9, 14) +cache/1/15/0/glyphs/319/texture_idx = 0 +cache/1/15/0/glyphs/245/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/245/offset = Vector2(0, -10) +cache/1/15/0/glyphs/245/size = Vector2(9, 14) +cache/1/15/0/glyphs/245/uv_rect = Rect2(154, 17, 9, 14) +cache/1/15/0/glyphs/245/texture_idx = 0 +cache/1/15/0/glyphs/282/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/282/offset = Vector2(-1, -10) +cache/1/15/0/glyphs/282/size = Vector2(11, 11) +cache/1/15/0/glyphs/282/uv_rect = Rect2(165, 17, 11, 11) +cache/1/15/0/glyphs/282/texture_idx = 0 +cache/1/15/0/glyphs/361/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/361/offset = Vector2(-1, -10) +cache/1/15/0/glyphs/361/size = Vector2(11, 11) +cache/1/15/0/glyphs/361/uv_rect = Rect2(178, 17, 11, 11) +cache/1/15/0/glyphs/361/texture_idx = 0 +cache/1/15/0/glyphs/89/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/89/offset = Vector2(0, -13) +cache/1/15/0/glyphs/89/size = Vector2(9, 14) +cache/1/15/0/glyphs/89/uv_rect = Rect2(191, 17, 9, 14) +cache/1/15/0/glyphs/89/texture_idx = 0 +cache/1/15/0/glyphs/122/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/122/offset = Vector2(0, -13) +cache/1/15/0/glyphs/122/size = Vector2(10, 14) +cache/1/15/0/glyphs/122/uv_rect = Rect2(202, 17, 10, 14) +cache/1/15/0/glyphs/122/texture_idx = 0 + +[sub_resource type="FontVariation" id="FontVariation_2iyu5"] +base_font = SubResource("FontFile_oowaf") +opentype_features = { +1667329140: 0 +} +spacing_top = -1 +spacing_bottom = -1 + +[sub_resource type="FontVariation" id="FontVariation_wml18"] +base_font = SubResource("FontFile_oowaf") +variation_embolden = 0.8 +opentype_features = { +1667329140: 0 +} +spacing_top = -1 +spacing_bottom = -1 + +[sub_resource type="FontVariation" id="FontVariation_1lm0m"] +base_font = SubResource("FontFile_oowaf") +variation_embolden = 0.8 +variation_transform = Transform2D(1, 0.2, 0, 1, 0, 0) +opentype_features = { +1667329140: 0 +} +spacing_top = -1 +spacing_bottom = -1 + +[sub_resource type="FontVariation" id="FontVariation_qryon"] +base_font = SubResource("FontFile_oowaf") +variation_transform = Transform2D(1, 0.2, 0, 1, 0, 0) +opentype_features = { +1667329140: 0 +} +spacing_top = -1 +spacing_bottom = -1 + +[sub_resource type="FontVariation" id="FontVariation_qc5vd"] +base_font = SubResource("FontFile_oowaf") +variation_embolden = -0.25 +variation_transform = Transform2D(1, 0.1, 0, 1, 0, 0) +opentype_features = { +1667329140: 0 +} +spacing_top = -1 +spacing_bottom = -1 + +[node name="Control" type="Control"] +use_parent_material = true +clip_contents = true +custom_minimum_size = Vector2(0, 200) +layout_mode = 3 +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +script = ExtResource("1") + +[node name="VBoxContainer" type="VBoxContainer" parent="."] +use_parent_material = true +clip_contents = true +layout_mode = 1 +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="Header" type="PanelContainer" parent="VBoxContainer"] +auto_translate_mode = 2 +custom_minimum_size = Vector2(0, 32) +layout_mode = 2 +localize_numeral_system = false +mouse_filter = 2 + +[node name="header_title" type="RichTextLabel" parent="VBoxContainer/Header"] +auto_translate_mode = 2 +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +localize_numeral_system = false +mouse_filter = 2 +bbcode_enabled = true +text = "[center][color=#9887c4]gd[/color][color=#7a57d6]Unit[/color][color=#9887c4]4[/color] [color=#9887c4]6.0.0[/color][/center]" +scroll_active = false +autowrap_mode = 0 +shortcut_keys_enabled = false + +[node name="Console" type="ScrollContainer" parent="VBoxContainer"] +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="TextEdit" type="RichTextLabel" parent="VBoxContainer/Console"] +use_parent_material = true +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +focus_mode = 2 +theme_override_fonts/normal_font = SubResource("FontVariation_2iyu5") +theme_override_fonts/bold_font = SubResource("FontVariation_wml18") +theme_override_fonts/bold_italics_font = SubResource("FontVariation_1lm0m") +theme_override_fonts/italics_font = SubResource("FontVariation_qryon") +theme_override_fonts/mono_font = SubResource("FontVariation_qc5vd") +theme_override_font_sizes/normal_font_size = 13 +theme_override_font_sizes/bold_font_size = 13 +theme_override_font_sizes/bold_italics_font_size = 13 +theme_override_font_sizes/italics_font_size = 13 +theme_override_font_sizes/mono_font_size = 13 +bbcode_enabled = true +scroll_following = true +context_menu_enabled = true +selection_enabled = true diff --git a/addons/gdUnit4/src/ui/GdUnitFonts.gd b/addons/gdUnit4/src/ui/GdUnitFonts.gd new file mode 100644 index 0000000..0cb0f5d --- /dev/null +++ b/addons/gdUnit4/src/ui/GdUnitFonts.gd @@ -0,0 +1,36 @@ +@tool +class_name GdUnitFonts +extends RefCounted + + +static func init_fonts(item: CanvasItem) -> float: + # set default size + item.set("theme_override_font_sizes/font_size", 16) + + if Engine.is_editor_hint(): + var base_control := EditorInterface.get_base_control() + # source modules/mono/editor/GodotTools/GodotTools/Build/BuildOutputView.cs + # https://github.com/godotengine/godot/blob/9ee1873ae1e09c217ac24a5800007f63cb895615/editor/editor_log.cpp#L65 + var output_source_mono := base_control.get_theme_font("output_source_mono", "EditorFonts") + var output_source_bold_italic := base_control.get_theme_font("output_source_bold_italic", "EditorFonts") + var output_source_italic := base_control.get_theme_font("output_source_italic", "EditorFonts") + var output_source_bold := base_control.get_theme_font("output_source_bold", "EditorFonts") + var output_source := base_control.get_theme_font("output_source", "EditorFonts") + var settings := EditorInterface.get_editor_settings() + var scale_factor := EditorInterface.get_editor_scale() + var font_size: float = settings.get_setting("interface/editor/main_font_size") + + font_size *= scale_factor + item.set("theme_override_fonts/normal_font", output_source) + item.set("theme_override_fonts/bold_font", output_source_bold) + item.set("theme_override_fonts/italics_font", output_source_italic) + item.set("theme_override_fonts/bold_italics_font", output_source_bold_italic) + item.set("theme_override_fonts/mono_font", output_source_mono) + item.set("theme_override_font_sizes/font_size", font_size) + item.set("theme_override_font_sizes/normal_font_size", font_size) + item.set("theme_override_font_sizes/bold_font_size", font_size) + item.set("theme_override_font_sizes/italics_font_size", font_size) + item.set("theme_override_font_sizes/bold_italics_font_size", font_size) + item.set("theme_override_font_sizes/mono_font_size", font_size) + return font_size + return 16.0 diff --git a/addons/gdUnit4/src/ui/GdUnitFonts.gd.uid b/addons/gdUnit4/src/ui/GdUnitFonts.gd.uid new file mode 100644 index 0000000..b56eedf --- /dev/null +++ b/addons/gdUnit4/src/ui/GdUnitFonts.gd.uid @@ -0,0 +1 @@ +uid://cfycyafbg4gxn diff --git a/addons/gdUnit4/src/ui/GdUnitInspector.gd b/addons/gdUnit4/src/ui/GdUnitInspector.gd new file mode 100644 index 0000000..a6d53f9 --- /dev/null +++ b/addons/gdUnit4/src/ui/GdUnitInspector.gd @@ -0,0 +1,31 @@ +@tool +class_name GdUnitInspecor +extends Panel + + +var _command_handler := GdUnitCommandHandler.instance() + + +func _ready() -> void: + @warning_ignore("return_value_discarded") + GdUnitCommandHandler.instance().gdunit_runner_start.connect(func() -> void: + var control :Control = get_parent_control() + # if the tab is floating we dont need to set as current + if control is TabContainer: + var tab_container :TabContainer = control + for tab_index in tab_container.get_tab_count(): + if tab_container.get_tab_title(tab_index) == "GdUnit": + tab_container.set_current_tab(tab_index) + ) + + # propagete the test_counters_changed signal to the progress bar + @warning_ignore("unsafe_property_access", "unsafe_method_access") + %MainPanel.test_counters_changed.connect(%ProgressBar._on_test_counter_changed) + +func _process(_delta: float) -> void: + _command_handler._do_process() + + +@warning_ignore("redundant_await") +func _on_status_bar_request_discover_tests() -> void: + await _command_handler.cmd_discover_tests() diff --git a/addons/gdUnit4/src/ui/GdUnitInspector.gd.uid b/addons/gdUnit4/src/ui/GdUnitInspector.gd.uid new file mode 100644 index 0000000..06b513e --- /dev/null +++ b/addons/gdUnit4/src/ui/GdUnitInspector.gd.uid @@ -0,0 +1 @@ +uid://bink1t8nta6s4 diff --git a/addons/gdUnit4/src/ui/GdUnitInspector.tscn b/addons/gdUnit4/src/ui/GdUnitInspector.tscn new file mode 100644 index 0000000..b85dfd3 --- /dev/null +++ b/addons/gdUnit4/src/ui/GdUnitInspector.tscn @@ -0,0 +1,71 @@ +[gd_scene load_steps=8 format=3 uid="uid://mpo5o6d4uybu"] + +[ext_resource type="PackedScene" uid="uid://dx7xy4dgi3wwb" path="res://addons/gdUnit4/src/ui/parts/InspectorToolBar.tscn" id="1"] +[ext_resource type="PackedScene" uid="uid://dva3tonxsxrlk" path="res://addons/gdUnit4/src/ui/parts/InspectorProgressBar.tscn" id="2"] +[ext_resource type="PackedScene" uid="uid://c22l4odk7qesc" path="res://addons/gdUnit4/src/ui/parts/InspectorStatusBar.tscn" id="3"] +[ext_resource type="PackedScene" uid="uid://djp8ait0bxpsc" path="res://addons/gdUnit4/src/ui/parts/InspectorMonitor.tscn" id="4"] +[ext_resource type="Script" uid="uid://bink1t8nta6s4" path="res://addons/gdUnit4/src/ui/GdUnitInspector.gd" id="5"] +[ext_resource type="PackedScene" uid="uid://bqfpidewtpeg0" path="res://addons/gdUnit4/src/ui/parts/InspectorTreePanel.tscn" id="7"] +[ext_resource type="PackedScene" uid="uid://cn5mp3tmi2gb1" path="res://addons/gdUnit4/src/network/GdUnitServer.tscn" id="7_721no"] + +[node name="GdUnit" type="Panel"] +use_parent_material = true +clip_contents = true +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +size_flags_horizontal = 11 +size_flags_vertical = 3 +focus_mode = 2 +script = ExtResource("5") + +[node name="VBoxContainer" type="VBoxContainer" parent="."] +use_parent_material = true +clip_contents = true +layout_mode = 0 +anchor_right = 1.0 +anchor_bottom = 1.0 +size_flags_vertical = 11 +theme_override_constants/separation = 0 + +[node name="Header" type="VBoxContainer" parent="VBoxContainer"] +use_parent_material = true +clip_contents = true +layout_mode = 2 +size_flags_horizontal = 9 +size_flags_vertical = 0 + +[node name="ToolBar" parent="VBoxContainer/Header" instance=ExtResource("1")] +layout_mode = 2 +size_flags_vertical = 1 + +[node name="ProgressBar" parent="VBoxContainer/Header" instance=ExtResource("2")] +unique_name_in_owner = true +layout_mode = 2 +size_flags_horizontal = 5 +max_value = 0.0 + +[node name="StatusBar" parent="VBoxContainer/Header" instance=ExtResource("3")] +layout_mode = 2 +size_flags_horizontal = 11 + +[node name="MainPanel" parent="VBoxContainer" instance=ExtResource("7")] +unique_name_in_owner = true +layout_mode = 2 + +[node name="Monitor" parent="VBoxContainer" instance=ExtResource("4")] +layout_mode = 2 + +[node name="event_server" parent="." instance=ExtResource("7_721no")] + +[connection signal="request_discover_tests" from="VBoxContainer/Header/StatusBar" to="." method="_on_status_bar_request_discover_tests"] +[connection signal="select_error_next" from="VBoxContainer/Header/StatusBar" to="VBoxContainer/MainPanel" method="_on_select_next_item_by_state" binds= [7]] +[connection signal="select_error_prevous" from="VBoxContainer/Header/StatusBar" to="VBoxContainer/MainPanel" method="_on_select_previous_item_by_state" binds= [7]] +[connection signal="select_failure_next" from="VBoxContainer/Header/StatusBar" to="VBoxContainer/MainPanel" method="_on_select_next_item_by_state" binds= [6]] +[connection signal="select_failure_prevous" from="VBoxContainer/Header/StatusBar" to="VBoxContainer/MainPanel" method="_on_select_previous_item_by_state" binds= [6]] +[connection signal="select_flaky_next" from="VBoxContainer/Header/StatusBar" to="VBoxContainer/MainPanel" method="_on_select_next_item_by_state" binds= [5]] +[connection signal="select_flaky_prevous" from="VBoxContainer/Header/StatusBar" to="VBoxContainer/MainPanel" method="_on_select_previous_item_by_state" binds= [5]] +[connection signal="select_skipped_next" from="VBoxContainer/Header/StatusBar" to="VBoxContainer/MainPanel" method="_on_select_next_item_by_state" binds= [2]] +[connection signal="select_skipped_prevous" from="VBoxContainer/Header/StatusBar" to="VBoxContainer/MainPanel" method="_on_select_previous_item_by_state" binds= [2]] +[connection signal="tree_view_mode_changed" from="VBoxContainer/Header/StatusBar" to="VBoxContainer/MainPanel" method="_on_status_bar_tree_view_mode_changed"] +[connection signal="jump_to_orphan_nodes" from="VBoxContainer/Monitor" to="VBoxContainer/MainPanel" method="select_first_orphan"] diff --git a/addons/gdUnit4/src/ui/GdUnitInspectorTreeConstants.gd b/addons/gdUnit4/src/ui/GdUnitInspectorTreeConstants.gd new file mode 100644 index 0000000..8dd0265 --- /dev/null +++ b/addons/gdUnit4/src/ui/GdUnitInspectorTreeConstants.gd @@ -0,0 +1,31 @@ +class_name GdUnitInspectorTreeConstants +extends RefCounted + + +# the inspector panel presantation +enum TREE_VIEW_MODE { + TREE, + FLAT +} + + +# The inspector sort modes +enum SORT_MODE { + UNSORTED, + NAME_ASCENDING, + NAME_DESCENDING, + EXECUTION_TIME +} + + +enum STATE { + INITIAL, + RUNNING, + SKIPPED, + SUCCESS, + WARNING, + FLAKY, + FAILED, + ERROR, + ABORDED, +} diff --git a/addons/gdUnit4/src/ui/GdUnitInspectorTreeConstants.gd.uid b/addons/gdUnit4/src/ui/GdUnitInspectorTreeConstants.gd.uid new file mode 100644 index 0000000..0770ec7 --- /dev/null +++ b/addons/gdUnit4/src/ui/GdUnitInspectorTreeConstants.gd.uid @@ -0,0 +1 @@ +uid://dh4bey50y6oto diff --git a/addons/gdUnit4/src/ui/GdUnitUiTools.gd b/addons/gdUnit4/src/ui/GdUnitUiTools.gd new file mode 100644 index 0000000..0bcdb1d --- /dev/null +++ b/addons/gdUnit4/src/ui/GdUnitUiTools.gd @@ -0,0 +1,151 @@ +class_name GdUnitUiTools +extends RefCounted + + +static var _spinner: AnimatedTexture + + +enum ImageFlipMode { + HORIZONTAl, + VERITCAL +} + + +## Returns the icon by name, if it exists. +static func get_icon(icon_name: String, color: = Color.BLACK) -> Texture2D: + if not Engine.is_editor_hint(): + return null + var icon := EditorInterface.get_base_control().get_theme_icon(icon_name, "EditorIcons") + if icon == null: + return null + if color != Color.BLACK: + icon = _modulate_texture(icon, color) + return icon + + +## Returns the icon flipped +static func get_flipped_icon(icon_name: String, mode: = ImageFlipMode.HORIZONTAl) -> Texture2D: + if not Engine.is_editor_hint(): + return null + var icon := EditorInterface.get_base_control().get_theme_icon(icon_name, "EditorIcons") + if icon == null: + return null + return ImageTexture.create_from_image(_flip_image(icon, mode)) + + +static func get_spinner() -> AnimatedTexture: + if _spinner != null: + return _spinner + _spinner = AnimatedTexture.new() + _spinner.frames = 8 + _spinner.speed_scale = 2.5 + for frame in _spinner.frames: + _spinner.set_frame_texture(frame, get_icon("Progress%d" % (frame+1))) + _spinner.set_frame_duration(frame, 0.2) + return _spinner + + +static func get_color_animated_icon(icon_name :String, from :Color, to :Color) -> AnimatedTexture: + if not Engine.is_editor_hint(): + return null + var texture := AnimatedTexture.new() + texture.frames = 8 + texture.speed_scale = 2.5 + var color := from + for frame in texture.frames: + color = lerp(color, to, .2) + texture.set_frame_texture(frame, get_icon(icon_name, color)) + texture.set_frame_duration(frame, 0.2) + return texture + + +static func get_run_overall_icon() -> Texture2D: + if not Engine.is_editor_hint(): + return null + var icon := EditorInterface.get_base_control().get_theme_icon("Play", "EditorIcons") + var image := _merge_images(icon.get_image(), Vector2i(-2, 0), icon.get_image(), Vector2i(3, 0)) + return ImageTexture.create_from_image(image) + + +static func get_GDScript_icon(status: String, color: Color) -> Texture2D: + if not Engine.is_editor_hint(): + return null + var icon_a := EditorInterface.get_base_control().get_theme_icon("GDScript", "EditorIcons") + var icon_b := EditorInterface.get_base_control().get_theme_icon(status, "EditorIcons") + var overlay_image := _modulate_image(icon_b.get_image(), color) + var image := _merge_images_scaled(icon_a.get_image(), Vector2i(0, 0), overlay_image, Vector2i(5, 5)) + return ImageTexture.create_from_image(image) + + +static func get_CSharpScript_icon(status: String, color: Color) -> Texture2D: + if not Engine.is_editor_hint(): + return null + var icon_a := EditorInterface.get_base_control().get_theme_icon("CSharpScript", "EditorIcons") + var icon_b := EditorInterface.get_base_control().get_theme_icon(status, "EditorIcons") + var overlay_image := _modulate_image(icon_b.get_image(), color) + var image := _merge_images_scaled(icon_a.get_image(), Vector2i(0, 0), overlay_image, Vector2i(5, 5)) + return ImageTexture.create_from_image(image) + + +static func _modulate_texture(texture: Texture2D, color: Color) -> Texture2D: + var image := _modulate_image(texture.get_image(), color) + return ImageTexture.create_from_image(image) + + +static func _modulate_image(image: Image, color: Color) -> Image: + var data: PackedByteArray = image.data["data"] + for pixel in range(0, data.size(), 4): + var pixel_a := _to_color(data, pixel) + if pixel_a.a8 != 0: + pixel_a = pixel_a.lerp(color, .9) + data[pixel + 0] = pixel_a.r8 + data[pixel + 1] = pixel_a.g8 + data[pixel + 2] = pixel_a.b8 + data[pixel + 3] = pixel_a.a8 + var output_image := Image.new() + output_image.set_data(image.get_width(), image.get_height(), image.has_mipmaps(), image.get_format(), data) + return output_image + + +static func _merge_images(image1: Image, offset1: Vector2i, image2: Image, offset2: Vector2i) -> Image: + ## we need to fix the image to have the same size to avoid merge conflicts + if image1.get_height() < image2.get_height(): + image1.resize(image2.get_width(), image2.get_height()) + # Create a new Image for the merged result + var merged_image := Image.create(image1.get_width(), image1.get_height(), false, Image.FORMAT_RGBA8) + merged_image.blit_rect_mask(image1, image2, Rect2(Vector2.ZERO, image1.get_size()), offset1) + merged_image.blit_rect_mask(image1, image2, Rect2(Vector2.ZERO, image2.get_size()), offset2) + return merged_image + + +@warning_ignore("narrowing_conversion") +static func _merge_images_scaled(image1: Image, offset1: Vector2i, image2: Image, offset2: Vector2i) -> Image: + ## we need to fix the image to have the same size to avoid merge conflicts + if image1.get_height() < image2.get_height(): + image1.resize(image2.get_width(), image2.get_height()) + # Create a new Image for the merged result + var merged_image := Image.create(image1.get_width(), image1.get_height(), false, image1.get_format()) + merged_image.blend_rect(image1, Rect2(Vector2.ZERO, image1.get_size()), offset1) + @warning_ignore("narrowing_conversion") + image2.resize(image2.get_width()/1.3, image2.get_height()/1.3) + merged_image.blend_rect(image2, Rect2(Vector2.ZERO, image2.get_size()), offset2) + return merged_image + + +static func _flip_image(texture: Texture2D, mode: ImageFlipMode) -> Image: + var flipped_image := Image.new() + flipped_image.copy_from(texture.get_image()) + if mode == ImageFlipMode.VERITCAL: + flipped_image.flip_x() + else: + flipped_image.flip_y() + return flipped_image + + +static func _to_color(data: PackedByteArray, position: int) -> Color: + var pixel_a := Color() + pixel_a.r8 = data[position + 0] + pixel_a.g8 = data[position + 1] + pixel_a.b8 = data[position + 2] + pixel_a.a8 = data[position + 3] + return pixel_a diff --git a/addons/gdUnit4/src/ui/GdUnitUiTools.gd.uid b/addons/gdUnit4/src/ui/GdUnitUiTools.gd.uid new file mode 100644 index 0000000..1dbebd4 --- /dev/null +++ b/addons/gdUnit4/src/ui/GdUnitUiTools.gd.uid @@ -0,0 +1 @@ +uid://tpvtst0rpmon diff --git a/addons/gdUnit4/src/ui/ScriptEditorControls.gd b/addons/gdUnit4/src/ui/ScriptEditorControls.gd new file mode 100644 index 0000000..5e07fe1 --- /dev/null +++ b/addons/gdUnit4/src/ui/ScriptEditorControls.gd @@ -0,0 +1,100 @@ +# A tool to provide extended script editor functionallity +class_name ScriptEditorControls +extends RefCounted + +# https://github.com/godotengine/godot/blob/master/editor/plugins/script_editor_plugin.h +# the Editor menu popup items +enum { + FILE_NEW, + FILE_NEW_TEXTFILE, + FILE_OPEN, + FILE_REOPEN_CLOSED, + FILE_OPEN_RECENT, + FILE_SAVE, + FILE_SAVE_AS, + FILE_SAVE_ALL, + FILE_THEME, + FILE_RUN, + FILE_CLOSE, + CLOSE_DOCS, + CLOSE_ALL, + CLOSE_OTHER_TABS, + TOGGLE_SCRIPTS_PANEL, + SHOW_IN_FILE_SYSTEM, + FILE_COPY_PATH, + FILE_TOOL_RELOAD_SOFT, + SEARCH_IN_FILES, + REPLACE_IN_FILES, + SEARCH_HELP, + SEARCH_WEBSITE, + HELP_SEARCH_FIND, + HELP_SEARCH_FIND_NEXT, + HELP_SEARCH_FIND_PREVIOUS, + WINDOW_MOVE_UP, + WINDOW_MOVE_DOWN, + WINDOW_NEXT, + WINDOW_PREV, + WINDOW_SORT, + WINDOW_SELECT_BASE = 100 +} + + +# Saves the given script and closes if requested by +# The script is saved when is opened in the editor. +# The script is closed when is set to true. +static func save_an_open_script(script_path: String, close:=false) -> bool: + #prints("save_an_open_script", script_path, close) + if !Engine.is_editor_hint(): + return false + var editor := EditorInterface.get_script_editor() + var editor_popup := _menu_popup() + # search for the script in all opened editor scrips + for open_script in editor.get_open_scripts(): + if open_script.resource_path == script_path: + # select the script in the editor + EditorInterface.edit_script(open_script, 0); + # save and close + editor_popup.id_pressed.emit(FILE_SAVE) + if close: + editor_popup.id_pressed.emit(FILE_CLOSE) + return true + return false + + +# Saves all opened script +static func save_all_open_script() -> void: + if Engine.is_editor_hint(): + _menu_popup().id_pressed.emit(FILE_SAVE_ALL) + + +static func close_open_editor_scripts() -> void: + if Engine.is_editor_hint(): + _menu_popup().id_pressed.emit(CLOSE_ALL) + + +# Edits the given script. +# The script is openend in the current editor and selected in the file system dock. +# The line and column on which to open the script can also be specified. +# The script will be open with the user-configured editor for the script's language which may be an external editor. +static func edit_script(script_path: String, line_number := -1) -> void: + var file_system := EditorInterface.get_resource_filesystem() + file_system.update_file(script_path) + var file_system_dock := EditorInterface.get_file_system_dock() + file_system_dock.navigate_to_path(script_path) + EditorInterface.select_file(script_path) + var script: GDScript = load(script_path) + EditorInterface.edit_script(script, line_number) + + +static func _menu_popup() -> PopupMenu: + @warning_ignore("unsafe_method_access") + return EditorInterface.get_script_editor().get_child(0).get_child(0).get_child(0).get_popup() + + +static func _print_menu(popup: PopupMenu) -> void: + for itemIndex in popup.item_count: + prints("get_item_id", popup.get_item_id(itemIndex)) + prints("get_item_accelerator", popup.get_item_accelerator(itemIndex)) + prints("get_item_shortcut", popup.get_item_shortcut(itemIndex)) + prints("get_item_text", popup.get_item_text(itemIndex)) + prints() diff --git a/addons/gdUnit4/src/ui/ScriptEditorControls.gd.uid b/addons/gdUnit4/src/ui/ScriptEditorControls.gd.uid new file mode 100644 index 0000000..d454297 --- /dev/null +++ b/addons/gdUnit4/src/ui/ScriptEditorControls.gd.uid @@ -0,0 +1 @@ +uid://ba6eremy7rmmn diff --git a/addons/gdUnit4/src/ui/menu/EditorFileSystemContextMenuHandler.gd b/addons/gdUnit4/src/ui/menu/EditorFileSystemContextMenuHandler.gd new file mode 100644 index 0000000..044b9ef --- /dev/null +++ b/addons/gdUnit4/src/ui/menu/EditorFileSystemContextMenuHandler.gd @@ -0,0 +1,79 @@ +@tool +extends Control + +var _context_menus := Dictionary() +var _command_handler := GdUnitCommandHandler.instance() + + +func _init() -> void: + set_name("EditorFileSystemContextMenuHandler") + + var is_test_suite := func is_visible(script: Script, is_ts: bool) -> bool: + if script == null: + return false + return GdUnitTestSuiteScanner.is_test_suite(script) == is_ts + var context_menus :Array[GdUnitContextMenuItem] = [ + GdUnitContextMenuItem.new(GdUnitContextMenuItem.MENU_ID.TEST_RUN, "Run Testsuites", "Play", is_test_suite.bind(true), _command_handler.command(GdUnitCommandHandler.CMD_RUN_TESTSUITE)), + GdUnitContextMenuItem.new(GdUnitContextMenuItem.MENU_ID.TEST_DEBUG, "Debug Testsuites", "PlayStart", is_test_suite.bind(true), _command_handler.command(GdUnitCommandHandler.CMD_RUN_TESTSUITE_DEBUG)), + ] + for menu in context_menus: + _context_menus[menu.id] = menu + var popup := _menu_popup() + var file_tree := _file_tree() + @warning_ignore("return_value_discarded") + popup.about_to_popup.connect(on_context_menu_show.bind(popup, file_tree)) + @warning_ignore("return_value_discarded") + popup.id_pressed.connect(on_context_menu_pressed.bind(file_tree)) + + +func on_context_menu_show(context_menu: PopupMenu, file_tree: Tree) -> void: + context_menu.add_separator() + var current_index := context_menu.get_item_count() + + for menu_id: int in _context_menus.keys(): + var menu_item: GdUnitContextMenuItem = _context_menus[menu_id] + + context_menu.add_item(menu_item.name, menu_id) + #context_menu.set_item_icon_modulate(current_index, Color.MEDIUM_PURPLE) + context_menu.set_item_disabled(current_index, !menu_item.is_enabled(null)) + context_menu.set_item_icon(current_index, GdUnitUiTools.get_icon(menu_item.icon)) + current_index += 1 + + +func on_context_menu_pressed(id: int, file_tree: Tree) -> void: + if !_context_menus.has(id): + return + var menu_item: GdUnitContextMenuItem = _context_menus[id] + var test_suites := collect_testsuites(menu_item, file_tree) + + menu_item.execute([test_suites]) + + +func collect_testsuites(_menu_item: GdUnitContextMenuItem, file_tree: Tree) -> Array[Script]: + var file_system := EditorInterface.get_resource_filesystem() + var selected_item := file_tree.get_selected() + var selected_test_suites: Array[Script] = [] + var suite_scaner := GdUnitTestSuiteScanner.new() + + while selected_item: + var resource_path: String = selected_item.get_metadata(0) + var file_type := file_system.get_file_type(resource_path) + var is_dir := DirAccess.dir_exists_absolute(resource_path) + if is_dir: + selected_test_suites.append_array(suite_scaner.scan_directory(resource_path)) + elif is_dir or file_type == "GDScript" or file_type == "CSharpScript": + # find a performant way to check if the selected item a testsuite + var resource: Script = ResourceLoader.load(resource_path, "Script", ResourceLoader.CACHE_MODE_REUSE) + if _menu_item.is_visible(resource): + @warning_ignore("return_value_discarded") + selected_test_suites.append(resource) + selected_item = file_tree.get_next_selected(selected_item) + return selected_test_suites + + +func _file_tree() -> Tree: + return GdObjects.find_nodes_by_class(EditorInterface.get_file_system_dock(), "Tree", true)[-1] + + +func _menu_popup() -> PopupMenu: + return GdObjects.find_nodes_by_class(EditorInterface.get_file_system_dock(), "PopupMenu")[-1] diff --git a/addons/gdUnit4/src/ui/menu/EditorFileSystemContextMenuHandler.gd.uid b/addons/gdUnit4/src/ui/menu/EditorFileSystemContextMenuHandler.gd.uid new file mode 100644 index 0000000..7d5352b --- /dev/null +++ b/addons/gdUnit4/src/ui/menu/EditorFileSystemContextMenuHandler.gd.uid @@ -0,0 +1 @@ +uid://cjx48nslj16hw diff --git a/addons/gdUnit4/src/ui/menu/EditorFileSystemContextMenuHandlerV44.gdx b/addons/gdUnit4/src/ui/menu/EditorFileSystemContextMenuHandlerV44.gdx new file mode 100644 index 0000000..108450e --- /dev/null +++ b/addons/gdUnit4/src/ui/menu/EditorFileSystemContextMenuHandlerV44.gdx @@ -0,0 +1,47 @@ +@tool +extends EditorContextMenuPlugin + +var _context_menus := Dictionary() +var _command_handler := GdUnitCommandHandler.instance() + + +func _init() -> void: + var is_test_suite := func is_visible(script: Script, is_ts: bool) -> bool: + if script == null: + return false + return GdUnitTestSuiteScanner.is_test_suite(script) == is_ts + _context_menus[GdUnitContextMenuItem.MENU_ID.TEST_RUN] = GdUnitContextMenuItem.new(GdUnitContextMenuItem.MENU_ID.TEST_RUN, "Run Testsuites", "Play", is_test_suite.bind(true), _command_handler.command(GdUnitCommandHandler.CMD_RUN_TESTSUITE)) + _context_menus[GdUnitContextMenuItem.MENU_ID.TEST_DEBUG] = GdUnitContextMenuItem.new(GdUnitContextMenuItem.MENU_ID.TEST_DEBUG, "Debug Testsuites", "PlayStart", is_test_suite.bind(true), _command_handler.command(GdUnitCommandHandler.CMD_RUN_TESTSUITE_DEBUG)) + + # setup shortcuts + for menu_item: GdUnitContextMenuItem in _context_menus.values(): + var cb := func call(files: Array) -> void: + menu_item.execute([files]) + add_menu_shortcut(menu_item.shortcut(), cb) + + +func _popup_menu(paths: PackedStringArray) -> void: + var test_suites: Array[Script] = [] + var suite_scaner := GdUnitTestSuiteScanner.new() + + for resource_path in paths: + # directories and test-suites are valid to enable the menu + if DirAccess.dir_exists_absolute(resource_path): + test_suites.append_array(suite_scaner.scan_directory(resource_path)) + continue + + var file_type := resource_path.get_extension() + if file_type == "gd" or file_type == "cs": + var script: Script = ResourceLoader.load(resource_path, "Script", ResourceLoader.CACHE_MODE_REUSE) + if GdUnitTestSuiteScanner.is_test_suite(script): + test_suites.append(script) + + # no direcory or test-suites selected? + if test_suites.is_empty(): + return + + for menu_item: GdUnitContextMenuItem in _context_menus.values(): + @warning_ignore("unused_parameter") + var cb := func call(files: Array) -> void: + menu_item.execute([test_suites]) + add_context_menu_item(menu_item.name, cb, GdUnitUiTools.get_icon(menu_item.icon)) diff --git a/addons/gdUnit4/src/ui/menu/GdUnitContextMenuItem.gd b/addons/gdUnit4/src/ui/menu/GdUnitContextMenuItem.gd new file mode 100644 index 0000000..2f89c61 --- /dev/null +++ b/addons/gdUnit4/src/ui/menu/GdUnitContextMenuItem.gd @@ -0,0 +1,69 @@ +class_name GdUnitContextMenuItem + +enum MENU_ID { + UNDEFINED = 0, + TEST_RUN = 1000, + TEST_DEBUG = 1001, + TEST_RERUN = 1002, + CREATE_TEST = 1010, +} + +var id: MENU_ID = MENU_ID.UNDEFINED: + set(value): + id = value + get: + return id + +var name: StringName: + set(value): + name = value + get: + return name + +var command: GdUnitCommand: + set(value): + command = value + get: + return command + +var visible: Callable: + set(value): + visible = value + get: + return visible + +var icon: String: + set(value): + icon = value + get: + return icon + + +func _init(p_id: MENU_ID, p_name: StringName, p_icon :String, p_is_visible: Callable, p_command: GdUnitCommand) -> void: + assert(p_id != null, "(%s) missing parameter 'MENU_ID'" % p_name) + assert(p_is_visible != null, "(%s) missing parameter 'GdUnitCommand'" % p_name) + assert(p_command != null, "(%s) missing parameter 'GdUnitCommand'" % p_name) + self.id = p_id + self.name = p_name + self.icon = p_icon + self.command = p_command + self.visible = p_is_visible + + +func shortcut() -> Shortcut: + return GdUnitCommandHandler.instance().get_shortcut(command.shortcut) + + +func is_enabled(script: Script) -> bool: + return command.is_enabled.call(script) + + +func is_visible(script: Script) -> bool: + return visible.call(script) + + +func execute(arguments:=[]) -> void: + if arguments.is_empty(): + command.runnable.call() + else: + command.runnable.callv(arguments) diff --git a/addons/gdUnit4/src/ui/menu/GdUnitContextMenuItem.gd.uid b/addons/gdUnit4/src/ui/menu/GdUnitContextMenuItem.gd.uid new file mode 100644 index 0000000..41a4997 --- /dev/null +++ b/addons/gdUnit4/src/ui/menu/GdUnitContextMenuItem.gd.uid @@ -0,0 +1 @@ +uid://dfrqtgjmf3uky diff --git a/addons/gdUnit4/src/ui/menu/ScriptEditorContextMenuHandler.gd b/addons/gdUnit4/src/ui/menu/ScriptEditorContextMenuHandler.gd new file mode 100644 index 0000000..550c6d6 --- /dev/null +++ b/addons/gdUnit4/src/ui/menu/ScriptEditorContextMenuHandler.gd @@ -0,0 +1,81 @@ +@tool +extends Control + +var _context_menus := Dictionary() +var _editor: ScriptEditor +var _command_handler := GdUnitCommandHandler.instance() + + +func _init() -> void: + set_name("ScriptEditorContextMenuHandler") + + var is_test_suite := func is_visible(script: Script, is_ts: bool) -> bool: + return GdUnitTestSuiteScanner.is_test_suite(script) == is_ts + var context_menus :Array[GdUnitContextMenuItem] = [ + GdUnitContextMenuItem.new(GdUnitContextMenuItem.MENU_ID.TEST_RUN, "Run Tests", "Play", is_test_suite.bind(true), _command_handler.command(GdUnitCommandHandler.CMD_RUN_TESTCASE)), + GdUnitContextMenuItem.new(GdUnitContextMenuItem.MENU_ID.TEST_DEBUG, "Debug Tests", "PlayStart", is_test_suite.bind(true), _command_handler.command(GdUnitCommandHandler.CMD_RUN_TESTCASE_DEBUG)), + GdUnitContextMenuItem.new(GdUnitContextMenuItem.MENU_ID.CREATE_TEST, "Create Test", "New", is_test_suite.bind(false), _command_handler.command(GdUnitCommandHandler.CMD_CREATE_TESTCASE)) + ] + for menu in context_menus: + _context_menus[menu.id] = menu + _editor = EditorInterface.get_script_editor() + @warning_ignore("return_value_discarded") + _editor.editor_script_changed.connect(on_script_changed) + on_script_changed(active_script()) + + +func _input(event: InputEvent) -> void: + if event is InputEventKey and event.is_pressed(): + for action: GdUnitContextMenuItem in _context_menus.values(): + if action.shortcut().matches_event(event) and action.is_visible(active_script()): + #if not has_editor_focus(): + # return + action.execute() + accept_event() + return + + +func has_editor_focus() -> bool: + return (Engine.get_main_loop() as SceneTree).root.gui_get_focus_owner() == active_base_editor() + + +func on_script_changed(script: Script) -> void: + if script is Script: + var popups: Array[Node] = GdObjects.find_nodes_by_class(active_editor(), "PopupMenu", true) + for popup: PopupMenu in popups: + if not popup.about_to_popup.is_connected(on_context_menu_show): + popup.about_to_popup.connect(on_context_menu_show.bind(script, popup)) + if not popup.id_pressed.is_connected(on_context_menu_pressed): + popup.id_pressed.connect(on_context_menu_pressed) + + +func on_context_menu_show(script: Script, context_menu: PopupMenu) -> void: + #prints("on_context_menu_show", _context_menus.keys(), context_menu, self) + context_menu.add_separator() + var current_index := context_menu.get_item_count() + for menu_id: int in _context_menus.keys(): + var menu_item: GdUnitContextMenuItem = _context_menus[menu_id] + if menu_item.is_visible(script): + context_menu.add_item(menu_item.name, menu_id) + context_menu.set_item_disabled(current_index, !menu_item.is_enabled(script)) + context_menu.set_item_shortcut(current_index, menu_item.shortcut(), true) + current_index += 1 + + +func on_context_menu_pressed(id: int) -> void: + if !_context_menus.has(id): + return + var menu_item: GdUnitContextMenuItem = _context_menus[id] + menu_item.execute() + + +func active_editor() -> ScriptEditorBase: + return _editor.get_current_editor() + + +func active_base_editor() -> TextEdit: + return active_editor().get_base_editor() + + +func active_script() -> Script: + return _editor.get_current_script() diff --git a/addons/gdUnit4/src/ui/menu/ScriptEditorContextMenuHandler.gd.uid b/addons/gdUnit4/src/ui/menu/ScriptEditorContextMenuHandler.gd.uid new file mode 100644 index 0000000..daafc12 --- /dev/null +++ b/addons/gdUnit4/src/ui/menu/ScriptEditorContextMenuHandler.gd.uid @@ -0,0 +1 @@ +uid://cvko17ymlv6s3 diff --git a/addons/gdUnit4/src/ui/menu/ScriptEditorContextMenuHandlerV44.gdx b/addons/gdUnit4/src/ui/menu/ScriptEditorContextMenuHandlerV44.gdx new file mode 100644 index 0000000..a879e37 --- /dev/null +++ b/addons/gdUnit4/src/ui/menu/ScriptEditorContextMenuHandlerV44.gdx @@ -0,0 +1,33 @@ +@tool +extends EditorContextMenuPlugin + +var _context_menus := Dictionary() +var _editor: ScriptEditor +var _command_handler := GdUnitCommandHandler.instance() + + +func _init() -> void: + var is_test_suite := func is_visible(script: Script, is_ts: bool) -> bool: + return GdUnitTestSuiteScanner.is_test_suite(script) == is_ts + var context_menus :Array[GdUnitContextMenuItem] = [ + GdUnitContextMenuItem.new(GdUnitContextMenuItem.MENU_ID.TEST_RUN, "Run Tests", "Play", is_test_suite.bind(true), _command_handler.command(GdUnitCommandHandler.CMD_RUN_TESTCASE)), + GdUnitContextMenuItem.new(GdUnitContextMenuItem.MENU_ID.TEST_DEBUG, "Debug Tests", "PlayStart", is_test_suite.bind(true), _command_handler.command(GdUnitCommandHandler.CMD_RUN_TESTCASE_DEBUG)), + GdUnitContextMenuItem.new(GdUnitContextMenuItem.MENU_ID.CREATE_TEST, "Create Test", "New", is_test_suite.bind(false), _command_handler.command(GdUnitCommandHandler.CMD_CREATE_TESTCASE)) + ] + for menu in context_menus: + _context_menus[menu.id] = menu + _editor = EditorInterface.get_script_editor() + @warning_ignore("return_value_discarded") + + +func _popup_menu(paths: PackedStringArray) -> void: + var script_path := paths[0] + var script: Script = ResourceLoader.load(script_path, "Script", ResourceLoader.CACHE_MODE_REUSE) + + for menu_id: int in _context_menus.keys(): + var menu_item: GdUnitContextMenuItem = _context_menus[menu_id] + if menu_item.is_visible(script): + add_context_menu_item(menu_item.name, + func call(files: Array) -> void: + menu_item.execute([script_path]), + GdUnitUiTools.get_icon(menu_item.icon)) diff --git a/addons/gdUnit4/src/ui/parts/InspectorMonitor.gd b/addons/gdUnit4/src/ui/parts/InspectorMonitor.gd new file mode 100644 index 0000000..c36b3ec --- /dev/null +++ b/addons/gdUnit4/src/ui/parts/InspectorMonitor.gd @@ -0,0 +1,54 @@ +@tool +extends PanelContainer + +signal jump_to_orphan_nodes() + +@onready var ICON_GREEN := GdUnitUiTools.get_icon("Unlinked", Color.WEB_GREEN) +@onready var ICON_RED := GdUnitUiTools.get_color_animated_icon("Unlinked", Color.YELLOW, Color.ORANGE_RED) + +@onready var _button_time: Button = %btn_time +@onready var _time: Label = %time_value +@onready var _orphans: Label = %orphan_value +@onready var _orphan_button: Button = %btn_orphan + +var total_elapsed_time := 0 +var total_orphans := 0 + + +func _ready() -> void: + @warning_ignore("return_value_discarded") + GdUnitSignals.instance().gdunit_event.connect(_on_gdunit_event) + _time.text = "" + _orphans.text = "0" + _button_time.icon = GdUnitUiTools.get_icon("Time") + _orphan_button.icon = ICON_GREEN + + +func status_changed(elapsed_time: int, orphan_nodes: int) -> void: + total_elapsed_time += elapsed_time + total_orphans += orphan_nodes + _time.text = LocalTime.elapsed(total_elapsed_time) + _orphans.text = str(total_orphans) + if total_orphans > 0: + _orphan_button.icon = ICON_RED + + +func _on_gdunit_event(event: GdUnitEvent) -> void: + match event.type(): + GdUnitEvent.INIT: + _orphan_button.icon = ICON_GREEN + total_elapsed_time = 0 + total_orphans = 0 + status_changed(0, 0) + GdUnitEvent.TESTCASE_BEFORE: + pass + GdUnitEvent.TESTCASE_AFTER: + status_changed(0, event.orphan_nodes()) + GdUnitEvent.TESTSUITE_BEFORE: + pass + GdUnitEvent.TESTSUITE_AFTER: + status_changed(event.elapsed_time(), event.orphan_nodes()) + + +func _on_ToolButton_pressed() -> void: + jump_to_orphan_nodes.emit() diff --git a/addons/gdUnit4/src/ui/parts/InspectorMonitor.gd.uid b/addons/gdUnit4/src/ui/parts/InspectorMonitor.gd.uid new file mode 100644 index 0000000..28ca2ec --- /dev/null +++ b/addons/gdUnit4/src/ui/parts/InspectorMonitor.gd.uid @@ -0,0 +1 @@ +uid://d2cam2e8875qp diff --git a/addons/gdUnit4/src/ui/parts/InspectorMonitor.tscn b/addons/gdUnit4/src/ui/parts/InspectorMonitor.tscn new file mode 100644 index 0000000..893bfd2 --- /dev/null +++ b/addons/gdUnit4/src/ui/parts/InspectorMonitor.tscn @@ -0,0 +1,91 @@ +[gd_scene load_steps=5 format=3 uid="uid://djp8ait0bxpsc"] + +[ext_resource type="Script" uid="uid://d2cam2e8875qp" path="res://addons/gdUnit4/src/ui/parts/InspectorMonitor.gd" id="3"] + +[sub_resource type="DPITexture" id="DPITexture_sx31i"] +_source = " 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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), +"format": "RGBA8", +"height": 16, +"mipmaps": false, +"width": 16 +} + +[sub_resource type="ImageTexture" id="ImageTexture_eewkt"] +image = SubResource("Image_gkq5u") + +[node name="Monitor" type="PanelContainer"] +clip_contents = true +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +offset_right = -793.0 +offset_bottom = -564.0 +size_flags_horizontal = 9 +size_flags_vertical = 9 +script = ExtResource("3") + +[node name="HBoxContainer" type="HBoxContainer" parent="."] +layout_mode = 2 +size_flags_vertical = 4 + +[node name="timer" type="HBoxContainer" parent="HBoxContainer"] +layout_mode = 2 + +[node name="btn_time" type="Button" parent="HBoxContainer/timer"] +unique_name_in_owner = true +auto_translate_mode = 2 +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 4 +localize_numeral_system = false +tooltip_text = "Shows the total elapsed time of test execution." +mouse_force_pass_scroll_events = false +button_mask = 0 +shortcut_feedback = false +shortcut_in_tooltip = false +text = "Time" +icon = SubResource("DPITexture_sx31i") +flat = true + +[node name="time_value" type="Label" parent="HBoxContainer/timer"] +unique_name_in_owner = true +auto_translate_mode = 2 +use_parent_material = true +layout_mode = 2 +size_flags_horizontal = 3 +localize_numeral_system = false +max_lines_visible = 1 + +[node name="orphan" type="HBoxContainer" parent="HBoxContainer/timer"] +layout_mode = 2 + +[node name="btn_orphan" type="Button" parent="HBoxContainer/timer/orphan"] +unique_name_in_owner = true +auto_translate_mode = 2 +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 4 +localize_numeral_system = false +tooltip_text = "Shows the total orphan nodes detected." +text = "Orphans" +icon = SubResource("ImageTexture_eewkt") + +[node name="orphan_value" type="Label" parent="HBoxContainer/timer/orphan"] +unique_name_in_owner = true +auto_translate_mode = 2 +use_parent_material = true +layout_mode = 2 +size_flags_horizontal = 3 +localize_numeral_system = false +text = "0" +max_lines_visible = 1 diff --git a/addons/gdUnit4/src/ui/parts/InspectorProgressBar.gd b/addons/gdUnit4/src/ui/parts/InspectorProgressBar.gd new file mode 100644 index 0000000..d368ed3 --- /dev/null +++ b/addons/gdUnit4/src/ui/parts/InspectorProgressBar.gd @@ -0,0 +1,49 @@ +@tool +extends ProgressBar + + +@onready var status: Label = $Label +@onready var style: StyleBoxFlat = get("theme_override_styles/fill") + +var _state: GdUnitInspectorTreeConstants.STATE + +func _ready() -> void: + style.bg_color = Color.DARK_GREEN + value = 0 + max_value = 0 + update_text() + + +func update_text() -> void: + status.text = "%d:%d" % [value, max_value] + + +func _on_test_counter_changed(index: int, total: int, state: GdUnitInspectorTreeConstants.STATE) -> void: + value = index + max_value = total + update_text() + + # inital state + if index == 0: + style.bg_color = Color.DARK_GREEN + + # do only update the state is higher prio than current state + if state <= _state: + return + _state = state + + if is_flaky(state): + style.bg_color = Color.WEB_GREEN + if is_failed(state): + style.bg_color = Color.DARK_RED + + +func is_failed(state: GdUnitInspectorTreeConstants.STATE) -> bool: + return state in [ + GdUnitInspectorTreeConstants.STATE.FAILED, + GdUnitInspectorTreeConstants.STATE.ERROR, + GdUnitInspectorTreeConstants.STATE.ABORDED] + + +func is_flaky(state: GdUnitInspectorTreeConstants.STATE) -> bool: + return state == GdUnitInspectorTreeConstants.STATE.FLAKY diff --git a/addons/gdUnit4/src/ui/parts/InspectorProgressBar.gd.uid b/addons/gdUnit4/src/ui/parts/InspectorProgressBar.gd.uid new file mode 100644 index 0000000..8edb593 --- /dev/null +++ b/addons/gdUnit4/src/ui/parts/InspectorProgressBar.gd.uid @@ -0,0 +1 @@ +uid://c5vgnlpt82584 diff --git a/addons/gdUnit4/src/ui/parts/InspectorProgressBar.tscn b/addons/gdUnit4/src/ui/parts/InspectorProgressBar.tscn new file mode 100644 index 0000000..fe0978a --- /dev/null +++ b/addons/gdUnit4/src/ui/parts/InspectorProgressBar.tscn @@ -0,0 +1,35 @@ +[gd_scene load_steps=3 format=3 uid="uid://dva3tonxsxrlk"] + +[ext_resource type="Script" uid="uid://c5vgnlpt82584" path="res://addons/gdUnit4/src/ui/parts/InspectorProgressBar.gd" id="1"] + +[sub_resource type="StyleBoxFlat" id="StyleBoxFlat_ayfir"] +bg_color = Color(0, 0.39215687, 0, 1) + +[node name="ProgressBar" type="ProgressBar"] +custom_minimum_size = Vector2(0, 20) +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 +size_flags_vertical = 9 +theme_override_styles/fill = SubResource("StyleBoxFlat_ayfir") +max_value = 0.0 +rounded = true +allow_greater = true +show_percentage = false +script = ExtResource("1") + +[node name="Label" type="Label" parent="."] +use_parent_material = true +layout_mode = 1 +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 +size_flags_vertical = 3 +text = "0:0" +horizontal_alignment = 1 +vertical_alignment = 1 +max_lines_visible = 1 diff --git a/addons/gdUnit4/src/ui/parts/InspectorStatusBar.gd b/addons/gdUnit4/src/ui/parts/InspectorStatusBar.gd new file mode 100644 index 0000000..dfed520 --- /dev/null +++ b/addons/gdUnit4/src/ui/parts/InspectorStatusBar.gd @@ -0,0 +1,216 @@ +@tool +extends PanelContainer + +signal select_failure_next() +signal select_failure_prevous() +signal select_error_next() +signal select_error_prevous() +signal select_flaky_next() +signal select_flaky_prevous() +signal select_skipped_next() +signal select_skipped_prevous() +signal request_discover_tests() + +@warning_ignore("unused_signal") +signal tree_view_mode_changed(flat :bool) + +@onready var _errors: Label = %error_value +@onready var _failures: Label = %failure_value +@onready var _flaky_value: Label = %flaky_value +@onready var _skipped_value: Label = %skipped_value +#@onready var _button_failure_up: Button = %btn_failure_up +#@onready var _button_failure_down: Button = %btn_failure_down +@onready var _button_sync: Button = %btn_tree_sync +@onready var _button_view_mode: MenuButton = %btn_tree_mode +@onready var _button_sort_mode: MenuButton = %btn_tree_sort + +@onready var _icon_errors: TextureRect = %icon_errors +@onready var _icon_failures: TextureRect = %icon_failures +@onready var _icon_flaky: TextureRect = %icon_flaky +@onready var _icon_skipped: TextureRect = %icon_skipped + +var total_failed := 0 +var total_errors := 0 +var total_flaky := 0 +var total_skipped := 0 + + +var icon_mappings := { + # tree sort modes + 0x100 + GdUnitInspectorTreeConstants.SORT_MODE.UNSORTED : GdUnitUiTools.get_icon("TripleBar"), + 0x100 + GdUnitInspectorTreeConstants.SORT_MODE.NAME_ASCENDING : GdUnitUiTools.get_icon("Sort"), + 0x100 + GdUnitInspectorTreeConstants.SORT_MODE.NAME_DESCENDING : GdUnitUiTools.get_flipped_icon("Sort"), + 0x100 + GdUnitInspectorTreeConstants.SORT_MODE.EXECUTION_TIME : GdUnitUiTools.get_icon("History"), + # tree view modes + 0x200 + GdUnitInspectorTreeConstants.TREE_VIEW_MODE.TREE : GdUnitUiTools.get_icon("Tree", Color.GHOST_WHITE), + 0x200 + GdUnitInspectorTreeConstants.TREE_VIEW_MODE.FLAT : GdUnitUiTools.get_icon("AnimationTrackGroup", Color.GHOST_WHITE) +} + + +@warning_ignore("return_value_discarded") +func _ready() -> void: + _failures.text = "0" + _errors.text = "0" + _flaky_value.text = "0" + _skipped_value.text = "0" + _icon_failures.texture = GdUnitUiTools.get_icon("StatusError", Color.SKY_BLUE) + _icon_errors.texture = GdUnitUiTools.get_icon("StatusError", Color.DARK_RED) + _icon_flaky.texture = GdUnitUiTools.get_icon("CheckBox", Color.GREEN_YELLOW) + _icon_skipped.texture = GdUnitUiTools.get_icon("CheckBox", Color.WEB_GRAY) + + #_button_failure_up.icon = GdUnitUiTools.get_icon("ArrowUp") + #_button_failure_down.icon = GdUnitUiTools.get_icon("ArrowDown") + _button_sync.icon = GdUnitUiTools.get_icon("Loop") + _set_sort_mode_menu_options() + _set_view_mode_menu_options() + GdUnitSignals.instance().gdunit_event.connect(_on_gdunit_event) + GdUnitSignals.instance().gdunit_settings_changed.connect(_on_settings_changed) + var command_handler := GdUnitCommandHandler.instance() + command_handler.gdunit_runner_start.connect(_on_gdunit_runner_start) + command_handler.gdunit_runner_stop.connect(_on_gdunit_runner_stop) + + + +func _set_sort_mode_menu_options() -> void: + _button_sort_mode.icon = GdUnitUiTools.get_icon("Sort") + # construct context sort menu according to the available modes + var context_menu :PopupMenu = _button_sort_mode.get_popup() + context_menu.clear() + + if not context_menu.index_pressed.is_connected(_on_sort_mode_changed): + @warning_ignore("return_value_discarded") + context_menu.index_pressed.connect(_on_sort_mode_changed) + + var configured_sort_mode := GdUnitSettings.get_inspector_tree_sort_mode() + for sort_mode: String in GdUnitInspectorTreeConstants.SORT_MODE.keys(): + var enum_value :int = GdUnitInspectorTreeConstants.SORT_MODE.get(sort_mode) + var icon :Texture2D = icon_mappings[0x100 + enum_value] + context_menu.add_icon_check_item(icon, normalise(sort_mode), enum_value) + context_menu.set_item_checked(enum_value, configured_sort_mode == enum_value) + + +func _set_view_mode_menu_options() -> void: + _button_view_mode.icon = GdUnitUiTools.get_icon("Tree", Color.GHOST_WHITE) + # construct context tree view menu according to the available modes + var context_menu :PopupMenu = _button_view_mode.get_popup() + context_menu.clear() + + if not context_menu.index_pressed.is_connected(_on_tree_view_mode_changed): + @warning_ignore("return_value_discarded") + context_menu.index_pressed.connect(_on_tree_view_mode_changed) + + var configured_tree_view_mode := GdUnitSettings.get_inspector_tree_view_mode() + for tree_view_mode: String in GdUnitInspectorTreeConstants.TREE_VIEW_MODE.keys(): + var enum_value :int = GdUnitInspectorTreeConstants.TREE_VIEW_MODE.get(tree_view_mode) + var icon :Texture2D = icon_mappings[0x200 + enum_value] + context_menu.add_icon_check_item(icon, normalise(tree_view_mode), enum_value) + context_menu.set_item_checked(enum_value, configured_tree_view_mode == enum_value) + + +func normalise(value: String) -> String: + var parts := value.to_lower().split("_") + parts[0] = parts[0].capitalize() + return " ".join(parts) + + +func status_changed(errors: int, failed: int, flaky: int, skipped: int) -> void: + total_failed += failed + total_errors += errors + total_flaky += flaky + total_skipped += skipped + _failures.text = str(total_failed) + _errors.text = str(total_errors) + _flaky_value.text = str(total_flaky) + _skipped_value.text = str(total_skipped) + + +func disable_buttons(value :bool) -> void: + _button_sync.set_disabled(value) + _button_sort_mode.set_disabled(value) + _button_view_mode.set_disabled(value) + + +func _on_gdunit_event(event: GdUnitEvent) -> void: + match event.type(): + GdUnitEvent.DISCOVER_START: + disable_buttons(true) + + GdUnitEvent.DISCOVER_END: + disable_buttons(false) + + GdUnitEvent.INIT: + total_errors = 0 + total_failed = 0 + total_flaky = 0 + total_skipped = 0 + status_changed(total_errors, total_failed, total_flaky, total_skipped) + + GdUnitEvent.TESTCASE_AFTER: + status_changed(event.error_count(), event.failed_count(), event.is_flaky(), event.is_skipped()) + + GdUnitEvent.TESTSUITE_AFTER: + status_changed(event.error_count(), event.failed_count(), event.is_flaky(), 0) + + +func _on_btn_error_up_pressed() -> void: + select_error_prevous.emit() + + +func _on_btn_error_down_pressed() -> void: + select_error_next.emit() + + +func _on_failure_up_pressed() -> void: + select_failure_prevous.emit() + + +func _on_failure_down_pressed() -> void: + select_failure_next.emit() + + +func _on_btn_flaky_up_pressed() -> void: + select_flaky_prevous.emit() + + +func _on_btn_flaky_down_pressed() -> void: + select_flaky_next.emit() + + +func _on_btn_skipped_up_pressed() -> void: + select_skipped_prevous.emit() + + +func _on_btn_skipped_down_pressed() -> void: + select_skipped_next.emit() + + +func _on_tree_sync_pressed() -> void: + request_discover_tests.emit() + + +func _on_sort_mode_changed(index: int) -> void: + var selected_sort_mode :GdUnitInspectorTreeConstants.SORT_MODE = GdUnitInspectorTreeConstants.SORT_MODE.values()[index] + GdUnitSettings.set_inspector_tree_sort_mode(selected_sort_mode) + + +func _on_tree_view_mode_changed(index: int) ->void: + var selected_tree_mode :GdUnitInspectorTreeConstants.TREE_VIEW_MODE = GdUnitInspectorTreeConstants.TREE_VIEW_MODE.values()[index] + GdUnitSettings.set_inspector_tree_view_mode(selected_tree_mode) + + +################################################################################ +# external signal receiver +################################################################################ +func _on_gdunit_runner_start() -> void: + disable_buttons(true) + + +func _on_gdunit_runner_stop(_client_id: int) -> void: + disable_buttons(false) + + +func _on_settings_changed(property :GdUnitProperty) -> void: + if property.name() == GdUnitSettings.INSPECTOR_TREE_SORT_MODE: + _set_sort_mode_menu_options() + if property.name() == GdUnitSettings.INSPECTOR_TREE_VIEW_MODE: + _set_view_mode_menu_options() diff --git a/addons/gdUnit4/src/ui/parts/InspectorStatusBar.gd.uid b/addons/gdUnit4/src/ui/parts/InspectorStatusBar.gd.uid new file mode 100644 index 0000000..daeb088 --- /dev/null +++ b/addons/gdUnit4/src/ui/parts/InspectorStatusBar.gd.uid @@ -0,0 +1 @@ +uid://m5jpa3i2drid diff --git a/addons/gdUnit4/src/ui/parts/InspectorStatusBar.tscn b/addons/gdUnit4/src/ui/parts/InspectorStatusBar.tscn new file mode 100644 index 0000000..9b3f26c --- /dev/null +++ b/addons/gdUnit4/src/ui/parts/InspectorStatusBar.tscn @@ -0,0 +1,465 @@ +[gd_scene load_steps=26 format=3 uid="uid://c22l4odk7qesc"] + +[ext_resource type="Script" uid="uid://m5jpa3i2drid" path="res://addons/gdUnit4/src/ui/parts/InspectorStatusBar.gd" id="3"] 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129, 139, 130, 255, 129, 139, 130, 255, 129, 139, 130, 255, 129, 139, 130, 255, 129, 139, 130, 255, 129, 139, 130, 255, 129, 139, 130, 252, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 130, 139, 130, 237, 129, 139, 130, 252, 129, 139, 130, 255, 129, 139, 130, 255, 129, 139, 130, 255, 129, 139, 130, 255, 129, 139, 130, 255, 129, 139, 130, 255, 129, 139, 130, 255, 129, 139, 130, 255, 129, 139, 130, 255, 129, 139, 130, 252, 129, 139, 130, 237, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), +"format": "RGBA8", +"height": 16, +"mipmaps": false, +"width": 16 +} + +[sub_resource type="ImageTexture" id="ImageTexture_qagbu"] +image = SubResource("Image_8d0da") + +[node name="StatusBar" type="PanelContainer"] +clip_contents = true +anchors_preset = 10 +anchor_right = 1.0 +offset_right = -807.0 +offset_bottom = 31.0 +grow_horizontal = 2 +size_flags_horizontal = 3 +size_flags_vertical = 0 +script = ExtResource("3") + +[node name="VBoxContainer" type="VBoxContainer" parent="."] +layout_mode = 2 +size_flags_vertical = 0 + +[node name="tree_tools" type="HBoxContainer" parent="VBoxContainer"] +layout_mode = 2 +size_flags_vertical = 0 + +[node name="Label" type="Label" parent="VBoxContainer/tree_tools"] +layout_mode = 2 +size_flags_horizontal = 0 +text = "Statistics" + +[node name="tree_buttons" type="HBoxContainer" parent="VBoxContainer/tree_tools"] +layout_mode = 2 +size_flags_horizontal = 10 +size_flags_vertical = 4 +alignment = 2 + +[node name="VSeparator" type="VSeparator" parent="VBoxContainer/tree_tools/tree_buttons"] +layout_mode = 2 + +[node name="btn_tree_sync" type="Button" parent="VBoxContainer/tree_tools/tree_buttons"] +unique_name_in_owner = true +layout_mode = 2 +tooltip_text = "Run discover tests." +icon = SubResource("DPITexture_mb3ih") + +[node name="btn_tree_sort" type="MenuButton" parent="VBoxContainer/tree_tools/tree_buttons"] +unique_name_in_owner = true +layout_mode = 2 +tooltip_text = "Sets tree sorting mode." +icon = SubResource("DPITexture_wo03e") +flat = false +item_count = 4 +popup/item_0/text = "Unsorted" +popup/item_0/icon = SubResource("DPITexture_ixycx") +popup/item_0/checkable = 1 +popup/item_0/checked = true +popup/item_0/id = 0 +popup/item_1/text = "Name ascending" +popup/item_1/icon = SubResource("DPITexture_wo03e") +popup/item_1/checkable = 1 +popup/item_1/id = 1 +popup/item_2/text = "Name descending" +popup/item_2/icon = SubResource("ImageTexture_eis20") +popup/item_2/checkable = 1 +popup/item_2/id = 2 +popup/item_3/text = "Execution time" +popup/item_3/icon = SubResource("DPITexture_t2qd7") +popup/item_3/checkable = 1 +popup/item_3/id = 3 + +[node name="btn_tree_mode" type="MenuButton" parent="VBoxContainer/tree_tools/tree_buttons"] +unique_name_in_owner = true +layout_mode = 2 +tooltip_text = "Sets tree presentation mode." +icon = SubResource("ImageTexture_1mh1t") +flat = false +item_count = 2 +popup/item_0/text = "Tree" +popup/item_0/icon = SubResource("ImageTexture_bq8kn") +popup/item_0/checkable = 1 +popup/item_0/id = 0 +popup/item_1/text = "Flat" +popup/item_1/icon = SubResource("ImageTexture_8lbfl") +popup/item_1/checkable = 1 +popup/item_1/checked = true +popup/item_1/id = 1 + +[node name="HSeparator" type="HSeparator" parent="VBoxContainer"] +layout_mode = 2 +theme_override_constants/separation = 0 + +[node name="status_bar" type="HFlowContainer" parent="VBoxContainer"] +layout_direction = 2 +layout_mode = 2 +size_flags_vertical = 2 + +[node name="error" type="VBoxContainer" parent="VBoxContainer/status_bar"] +custom_minimum_size = Vector2(0, 48) +layout_mode = 2 +size_flags_vertical = 0 +theme_override_constants/separation = -2 + +[node name="icon" type="HBoxContainer" parent="VBoxContainer/status_bar/error"] +layout_mode = 2 +size_flags_horizontal = 3 + +[node name="icon_errors" type="TextureRect" parent="VBoxContainer/status_bar/error/icon"] +unique_name_in_owner = true +layout_mode = 2 +size_flags_horizontal = 10 +size_flags_vertical = 4 +tooltip_text = "Error Tests" +texture = SubResource("ImageTexture_ivm1h") +stretch_mode = 3 + +[node name="btn_up" type="Button" parent="VBoxContainer/status_bar/error/icon"] +layout_mode = 2 +size_flags_horizontal = 10 +size_flags_vertical = 4 +tooltip_text = "Jump to the previous error test" +icon = SubResource("ImageTexture_1oriu") + +[node name="counter" type="HBoxContainer" parent="VBoxContainer/status_bar/error"] +auto_translate_mode = 2 +layout_mode = 2 +localize_numeral_system = false + +[node name="error_value" type="Label" parent="VBoxContainer/status_bar/error/counter"] +unique_name_in_owner = true +use_parent_material = true +custom_minimum_size = Vector2(32, 0) +layout_mode = 2 +size_flags_horizontal = 10 +text = "0" +horizontal_alignment = 2 +justification_flags = 0 +visible_characters = 3 +visible_ratio = 3.0 + +[node name="btn_down" type="Button" parent="VBoxContainer/status_bar/error/counter"] +layout_mode = 2 +size_flags_horizontal = 4 +size_flags_vertical = 4 +tooltip_text = "Jump to the next error test" +icon = SubResource("ImageTexture_ikyhk") + +[node name="VSeparator" type="VSeparator" parent="VBoxContainer/status_bar"] +layout_mode = 2 + +[node name="failure" type="VBoxContainer" parent="VBoxContainer/status_bar"] +custom_minimum_size = Vector2(0, 48) +layout_mode = 2 +theme_override_constants/separation = -2 + +[node name="icon" type="HBoxContainer" parent="VBoxContainer/status_bar/failure"] +layout_mode = 2 +size_flags_horizontal = 3 + +[node name="icon_failures" type="TextureRect" parent="VBoxContainer/status_bar/failure/icon"] +unique_name_in_owner = true +layout_mode = 2 +size_flags_horizontal = 10 +size_flags_vertical = 4 +tooltip_text = "Failed Tests" +texture = SubResource("ImageTexture_suo5c") +stretch_mode = 3 + +[node name="btn_up" type="Button" parent="VBoxContainer/status_bar/failure/icon"] +layout_mode = 2 +size_flags_horizontal = 10 +size_flags_vertical = 4 +tooltip_text = "Jump to the previous failed test" +icon = SubResource("ImageTexture_1oriu") + +[node name="counter" type="HBoxContainer" parent="VBoxContainer/status_bar/failure"] +auto_translate_mode = 2 +layout_mode = 2 +localize_numeral_system = false + +[node name="failure_value" type="Label" parent="VBoxContainer/status_bar/failure/counter"] +unique_name_in_owner = true +use_parent_material = true +custom_minimum_size = Vector2(32, 0) +layout_mode = 2 +size_flags_horizontal = 10 +text = "0" +horizontal_alignment = 2 +justification_flags = 0 +visible_characters = 3 +visible_ratio = 3.0 + +[node name="btn_down" type="Button" parent="VBoxContainer/status_bar/failure/counter"] +layout_mode = 2 +size_flags_horizontal = 4 +size_flags_vertical = 4 +tooltip_text = "Jump to the next failed test" +icon = SubResource("ImageTexture_ikyhk") + +[node name="VSeparator2" type="VSeparator" parent="VBoxContainer/status_bar"] +layout_mode = 2 + +[node name="flaky" type="VBoxContainer" parent="VBoxContainer/status_bar"] +custom_minimum_size = Vector2(0, 48) +layout_mode = 2 +theme_override_constants/separation = -2 + +[node name="icon" type="HBoxContainer" parent="VBoxContainer/status_bar/flaky"] +layout_mode = 2 +size_flags_horizontal = 3 + +[node name="icon_flaky" type="TextureRect" parent="VBoxContainer/status_bar/flaky/icon"] +unique_name_in_owner = true +layout_mode = 2 +size_flags_horizontal = 10 +size_flags_vertical = 4 +tooltip_text = "Flaky Tests" +texture = SubResource("ImageTexture_d5kq4") +stretch_mode = 3 + +[node name="btn_up" type="Button" parent="VBoxContainer/status_bar/flaky/icon"] +layout_mode = 2 +size_flags_horizontal = 10 +size_flags_vertical = 4 +tooltip_text = "Jump to the previous flaky test" +icon = SubResource("ImageTexture_1oriu") + +[node name="counter" type="HBoxContainer" parent="VBoxContainer/status_bar/flaky"] +auto_translate_mode = 2 +layout_mode = 2 +localize_numeral_system = false + +[node name="flaky_value" type="Label" parent="VBoxContainer/status_bar/flaky/counter"] +unique_name_in_owner = true +use_parent_material = true +custom_minimum_size = Vector2(32, 0) +layout_mode = 2 +size_flags_horizontal = 10 +text = "0" +horizontal_alignment = 2 +justification_flags = 0 +visible_characters = 3 +visible_ratio = 3.0 + +[node name="btn_down" type="Button" parent="VBoxContainer/status_bar/flaky/counter"] +layout_mode = 2 +size_flags_horizontal = 4 +size_flags_vertical = 4 +tooltip_text = "Jump to the next flaky test" +icon = SubResource("ImageTexture_ikyhk") + +[node name="VSeparator3" type="VSeparator" parent="VBoxContainer/status_bar"] +layout_mode = 2 + +[node name="skipped" type="VBoxContainer" parent="VBoxContainer/status_bar"] +custom_minimum_size = Vector2(0, 48) +layout_mode = 2 +theme_override_constants/separation = -2 + +[node name="icon" type="HBoxContainer" parent="VBoxContainer/status_bar/skipped"] +layout_mode = 2 +size_flags_horizontal = 3 + +[node name="icon_skipped" type="TextureRect" parent="VBoxContainer/status_bar/skipped/icon"] +unique_name_in_owner = true +layout_mode = 2 +size_flags_horizontal = 10 +size_flags_vertical = 4 +tooltip_text = "Skipped Tests" +texture = SubResource("ImageTexture_qagbu") +stretch_mode = 3 + +[node name="btn_up" type="Button" parent="VBoxContainer/status_bar/skipped/icon"] +layout_mode = 2 +size_flags_horizontal = 10 +size_flags_vertical = 4 +tooltip_text = "Jump to the previous skipped test" +icon = SubResource("ImageTexture_1oriu") + +[node name="counter" type="HBoxContainer" parent="VBoxContainer/status_bar/skipped"] +auto_translate_mode = 2 +layout_mode = 2 +localize_numeral_system = false + +[node name="skipped_value" type="Label" parent="VBoxContainer/status_bar/skipped/counter"] +unique_name_in_owner = true +use_parent_material = true +custom_minimum_size = Vector2(32, 0) +layout_mode = 2 +size_flags_horizontal = 10 +text = "0" +horizontal_alignment = 2 +justification_flags = 0 +visible_characters = 3 +visible_ratio = 3.0 + +[node name="btn_down" type="Button" parent="VBoxContainer/status_bar/skipped/counter"] +layout_mode = 2 +size_flags_horizontal = 4 +size_flags_vertical = 4 +tooltip_text = "Jump to the next skipped test" +icon = SubResource("ImageTexture_ikyhk") + +[connection signal="pressed" from="VBoxContainer/tree_tools/tree_buttons/btn_tree_sync" to="." method="_on_tree_sync_pressed"] +[connection signal="pressed" from="VBoxContainer/status_bar/error/icon/btn_up" to="." method="_on_btn_error_up_pressed"] +[connection signal="pressed" from="VBoxContainer/status_bar/error/counter/btn_down" to="." method="_on_btn_error_down_pressed"] +[connection signal="pressed" from="VBoxContainer/status_bar/failure/icon/btn_up" to="." method="_on_failure_up_pressed"] +[connection signal="pressed" from="VBoxContainer/status_bar/failure/counter/btn_down" to="." method="_on_failure_down_pressed"] +[connection signal="pressed" from="VBoxContainer/status_bar/flaky/icon/btn_up" to="." method="_on_btn_flaky_up_pressed"] +[connection signal="pressed" from="VBoxContainer/status_bar/flaky/counter/btn_down" to="." method="_on_btn_flaky_down_pressed"] +[connection signal="pressed" from="VBoxContainer/status_bar/skipped/icon/btn_up" to="." method="_on_btn_skipped_up_pressed"] +[connection signal="pressed" from="VBoxContainer/status_bar/skipped/counter/btn_down" to="." method="_on_btn_skipped_down_pressed"] diff --git a/addons/gdUnit4/src/ui/parts/InspectorToolBar.gd b/addons/gdUnit4/src/ui/parts/InspectorToolBar.gd new file mode 100644 index 0000000..e4d99e4 --- /dev/null +++ b/addons/gdUnit4/src/ui/parts/InspectorToolBar.gd @@ -0,0 +1,129 @@ +@tool +extends PanelContainer + +signal run_overall_pressed(debug: bool) +signal run_pressed(debug: bool) +signal stop_pressed() + +const InspectorTreeMainPanel := preload("res://addons/gdUnit4/src/ui/parts/InspectorTreeMainPanel.gd") + +@onready var _version_label: Control = %version +@onready var _button_wiki: Button = %help +@onready var _tool_button: Button = %tool +@onready var _button_run_overall: Button = %run_overall +@onready var _button_run: Button = %run +@onready var _button_run_debug: Button = %debug +@onready var _button_stop: Button = %stop + + +const SETTINGS_SHORTCUT_MAPPING := { + GdUnitSettings.SHORTCUT_INSPECTOR_RERUN_TEST: GdUnitShortcut.ShortCut.RERUN_TESTS, + GdUnitSettings.SHORTCUT_INSPECTOR_RERUN_TEST_DEBUG: GdUnitShortcut.ShortCut.RERUN_TESTS_DEBUG, + GdUnitSettings.SHORTCUT_INSPECTOR_RUN_TEST_OVERALL: GdUnitShortcut.ShortCut.RUN_TESTS_OVERALL, + GdUnitSettings.SHORTCUT_INSPECTOR_RUN_TEST_STOP: GdUnitShortcut.ShortCut.STOP_TEST_RUN, +} + + +func _ready() -> void: + var inspector :InspectorTreeMainPanel = get_parent().get_parent().find_child("MainPanel", false, false) + if inspector == null: + push_error("Internal error, can't connect to the test inspector!") + else: + inspector.tree_item_selected.connect(_on_inspector_selected) + run_pressed.connect(inspector._on_run_pressed) + + GdUnit4Version.init_version_label(_version_label) + var command_handler := GdUnitCommandHandler.instance() + run_overall_pressed.connect(command_handler._on_run_overall_pressed) + stop_pressed.connect(command_handler._on_stop_pressed) + command_handler.gdunit_runner_start.connect(_on_gdunit_runner_start) + command_handler.gdunit_runner_stop.connect(_on_gdunit_runner_stop) + GdUnitSignals.instance().gdunit_settings_changed.connect(_on_gdunit_settings_changed) + init_buttons() + init_shortcuts(command_handler) + + +func init_buttons() -> void: + _button_run_overall.icon = GdUnitUiTools.get_run_overall_icon() + _button_run_overall.visible = GdUnitSettings.is_inspector_toolbar_button_show() + _button_run.icon = GdUnitUiTools.get_icon("Play") + _button_run_debug.icon = GdUnitUiTools.get_icon("PlayStart") + _button_stop.icon = GdUnitUiTools.get_icon("Stop") + _tool_button.icon = GdUnitUiTools.get_icon("Tools") + _button_wiki.icon = GdUnitUiTools.get_icon("HelpSearch") + # Set run buttons initial disabled + _button_run.disabled = true + _button_run_debug.disabled = true + + +func init_shortcuts(command_handler: GdUnitCommandHandler) -> void: + _button_run.shortcut = command_handler.get_shortcut(GdUnitShortcut.ShortCut.RERUN_TESTS) + _button_run_overall.shortcut = command_handler.get_shortcut(GdUnitShortcut.ShortCut.RUN_TESTS_OVERALL) + _button_run_debug.shortcut = command_handler.get_shortcut(GdUnitShortcut.ShortCut.RERUN_TESTS_DEBUG) + _button_stop.shortcut = command_handler.get_shortcut(GdUnitShortcut.ShortCut.STOP_TEST_RUN) + # register for shortcut changes + @warning_ignore("return_value_discarded") + GdUnitSignals.instance().gdunit_settings_changed.connect(_on_settings_changed.bind(command_handler)) + + +func _on_inspector_selected(item: TreeItem) -> void: + var button_disabled := item == null + _button_run.disabled = button_disabled + _button_run_debug.disabled = button_disabled + + +func _on_runoverall_pressed(debug:=false) -> void: + run_overall_pressed.emit(debug) + + +func _on_run_pressed(debug := false) -> void: + run_pressed.emit(debug) + + +func _on_stop_pressed() -> void: + stop_pressed.emit() + + +func _on_gdunit_runner_start() -> void: + _button_run_overall.disabled = true + _button_run.disabled = true + _button_run_debug.disabled = true + _button_stop.disabled = false + + +func _on_gdunit_runner_stop(_client_id: int) -> void: + _button_run_overall.disabled = false + _button_stop.disabled = true + + +func _on_gdunit_settings_changed(_property: GdUnitProperty) -> void: + _button_run_overall.visible = GdUnitSettings.is_inspector_toolbar_button_show() + + +func _on_wiki_pressed() -> void: + @warning_ignore("return_value_discarded") + OS.shell_open("https://mikeschulze.github.io/gdUnit4/") + + +func _on_btn_tool_pressed() -> void: + var settings_dlg: Window = EditorInterface.get_base_control().find_child("GdUnitSettingsDialog", false, false) + if settings_dlg == null: + settings_dlg = preload("res://addons/gdUnit4/src/ui/settings/GdUnitSettingsDialog.tscn").instantiate() + EditorInterface.get_base_control().add_child(settings_dlg, true) + settings_dlg.popup_centered_ratio(.60) + + +func _on_settings_changed(property: GdUnitProperty, command_handler: GdUnitCommandHandler) -> void: + # needs to wait a frame to be command handler notified first for settings changes + await get_tree().process_frame + if SETTINGS_SHORTCUT_MAPPING.has(property.name()): + var shortcut: GdUnitShortcut.ShortCut = SETTINGS_SHORTCUT_MAPPING.get(property.name(), GdUnitShortcut.ShortCut.NONE) + match shortcut: + GdUnitShortcut.ShortCut.RERUN_TESTS: + _button_run.shortcut = command_handler.get_shortcut(shortcut) + GdUnitShortcut.ShortCut.RUN_TESTS_OVERALL: + _button_run_overall.shortcut = command_handler.get_shortcut(shortcut) + GdUnitShortcut.ShortCut.RERUN_TESTS_DEBUG: + _button_run_debug.shortcut = command_handler.get_shortcut(shortcut) + GdUnitShortcut.ShortCut.STOP_TEST_RUN: + _button_stop.shortcut = command_handler.get_shortcut(shortcut) diff --git a/addons/gdUnit4/src/ui/parts/InspectorToolBar.gd.uid b/addons/gdUnit4/src/ui/parts/InspectorToolBar.gd.uid new file mode 100644 index 0000000..eeab830 --- /dev/null +++ b/addons/gdUnit4/src/ui/parts/InspectorToolBar.gd.uid @@ -0,0 +1 @@ +uid://ukcummwrkfnc diff --git a/addons/gdUnit4/src/ui/parts/InspectorToolBar.tscn b/addons/gdUnit4/src/ui/parts/InspectorToolBar.tscn new file mode 100644 index 0000000..1aa1eaa --- /dev/null +++ b/addons/gdUnit4/src/ui/parts/InspectorToolBar.tscn @@ -0,0 +1,199 @@ +[gd_scene load_steps=17 format=3 uid="uid://dx7xy4dgi3wwb"] + +[ext_resource type="Script" uid="uid://ukcummwrkfnc" path="res://addons/gdUnit4/src/ui/parts/InspectorToolBar.gd" id="3"] + +[sub_resource type="DPITexture" id="DPITexture_c7rhl"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[sub_resource type="DPITexture" id="DPITexture_3erui"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[sub_resource type="InputEventKey" id="InputEventKey_p22nw"] +ctrl_pressed = true +pressed = true +keycode = 4194338 +physical_keycode = 4194338 + +[sub_resource type="Shortcut" id="Shortcut_3lcek"] +events = [SubResource("InputEventKey_p22nw")] + +[sub_resource type="Image" id="Image_ndw0i"] +data = { +"data": PackedByteArray(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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182, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 252, 225, 225, 225, 134, 255, 255, 255, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 212, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 212, 226, 226, 226, 52, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 252, 225, 225, 225, 134, 255, 255, 255, 6, 224, 224, 224, 255, 224, 224, 224, 255, 224, 224, 224, 252, 225, 225, 225, 134, 255, 255, 255, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 225, 225, 225, 191, 224, 224, 224, 206, 226, 226, 226, 52, 0, 0, 0, 0, 0, 0, 0, 0, 225, 225, 225, 191, 224, 224, 224, 206, 226, 226, 226, 52, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), +"format": "RGBA8", +"height": 16, +"mipmaps": false, +"width": 16 +} + +[sub_resource type="ImageTexture" id="ImageTexture_eoihf"] +image = SubResource("Image_ndw0i") + +[sub_resource type="InputEventKey" id="InputEventKey_6gwbs"] +ctrl_pressed = true +pressed = true +keycode = 4194336 +physical_keycode = 4194336 + +[sub_resource type="Shortcut" id="Shortcut_2i8uq"] +events = [SubResource("InputEventKey_6gwbs")] + +[sub_resource type="DPITexture" id="DPITexture_87jj1"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[sub_resource type="InputEventKey" id="InputEventKey_fewwl"] +ctrl_pressed = true +pressed = true +keycode = 4194337 +physical_keycode = 4194337 + +[sub_resource type="Shortcut" id="Shortcut_f3lkx"] +events = [SubResource("InputEventKey_fewwl")] + +[sub_resource type="DPITexture" id="DPITexture_7oobd"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[sub_resource type="InputEventKey" id="InputEventKey_lvbnb"] +ctrl_pressed = true +pressed = true +keycode = 4194339 +physical_keycode = 4194339 + +[sub_resource type="Shortcut" id="Shortcut_6idxu"] +events = [SubResource("InputEventKey_lvbnb")] + +[sub_resource type="DPITexture" id="DPITexture_qf2s1"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[node name="ToolBar" type="PanelContainer"] +anchors_preset = 10 +anchor_right = 1.0 +offset_right = -894.0 +offset_bottom = 24.0 +grow_horizontal = 2 +size_flags_horizontal = 3 +size_flags_vertical = 4 +script = ExtResource("3") + +[node name="HBoxContainer" type="HBoxContainer" parent="."] +layout_mode = 2 + +[node name="tools" type="HBoxContainer" parent="HBoxContainer"] +layout_mode = 2 +size_flags_horizontal = 0 +size_flags_vertical = 4 + +[node name="help" type="Button" parent="HBoxContainer/tools"] +unique_name_in_owner = true +layout_mode = 2 +icon = SubResource("DPITexture_c7rhl") + +[node name="tool" type="Button" parent="HBoxContainer/tools"] +unique_name_in_owner = true +layout_mode = 2 +tooltip_text = "GdUnit Settings" +icon = SubResource("DPITexture_3erui") + +[node name="controls" type="HBoxContainer" parent="HBoxContainer"] +layout_mode = 2 +size_flags_horizontal = 6 +size_flags_vertical = 4 +alignment = 1 + +[node name="VSeparator3" type="VSeparator" parent="HBoxContainer/controls"] +layout_mode = 2 + +[node name="run_overall" type="Button" parent="HBoxContainer/controls"] +unique_name_in_owner = true +visible = false +use_parent_material = true +layout_mode = 2 +tooltip_text = "Run overall tests" +shortcut = SubResource("Shortcut_3lcek") +icon = SubResource("ImageTexture_eoihf") + +[node name="run" type="Button" parent="HBoxContainer/controls"] +unique_name_in_owner = true +use_parent_material = true +layout_mode = 2 +tooltip_text = "Rerun unit tests" +disabled = true +shortcut = SubResource("Shortcut_2i8uq") +icon = SubResource("DPITexture_87jj1") + +[node name="debug" type="Button" parent="HBoxContainer/controls"] +unique_name_in_owner = true +use_parent_material = true +layout_mode = 2 +tooltip_text = "Rerun unit tests (Debug)" +disabled = true +shortcut = SubResource("Shortcut_f3lkx") +icon = SubResource("DPITexture_7oobd") + +[node name="stop" type="Button" parent="HBoxContainer/controls"] +unique_name_in_owner = true +use_parent_material = true +layout_mode = 2 +tooltip_text = "Stops runing unit tests" +disabled = true +shortcut = SubResource("Shortcut_6idxu") +icon = SubResource("DPITexture_qf2s1") + +[node name="VSeparator4" type="VSeparator" parent="HBoxContainer/controls"] +layout_mode = 2 + +[node name="CenterContainer" type="HBoxContainer" parent="HBoxContainer"] +use_parent_material = true +layout_mode = 2 +size_flags_horizontal = 10 +size_flags_vertical = 4 +alignment = 2 + +[node name="version" type="Label" parent="HBoxContainer/CenterContainer"] +unique_name_in_owner = true +auto_translate_mode = 2 +use_parent_material = true +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 13 +localize_numeral_system = false +text = "gdUnit4 6.0.0" +horizontal_alignment = 1 +justification_flags = 160 + +[connection signal="pressed" from="HBoxContainer/tools/help" to="." method="_on_wiki_pressed"] +[connection signal="pressed" from="HBoxContainer/tools/tool" to="." method="_on_btn_tool_pressed"] +[connection signal="pressed" from="HBoxContainer/controls/run_overall" to="." method="_on_runoverall_pressed"] +[connection signal="pressed" from="HBoxContainer/controls/run" to="." method="_on_run_pressed"] +[connection signal="pressed" from="HBoxContainer/controls/debug" to="." method="_on_run_pressed" binds= [true]] +[connection signal="pressed" from="HBoxContainer/controls/stop" to="." method="_on_stop_pressed"] diff --git a/addons/gdUnit4/src/ui/parts/InspectorTreeMainPanel.gd b/addons/gdUnit4/src/ui/parts/InspectorTreeMainPanel.gd new file mode 100644 index 0000000..536fe87 --- /dev/null +++ b/addons/gdUnit4/src/ui/parts/InspectorTreeMainPanel.gd @@ -0,0 +1,1245 @@ +@tool +extends VSplitContainer + +## Will be emitted when the test index counter is changed +signal test_counters_changed(index: int, total: int, state: GdUnitInspectorTreeConstants.STATE) +signal tree_item_selected(item: TreeItem) + + +const CONTEXT_MENU_RUN_ID = 0 +const CONTEXT_MENU_DEBUG_ID = 1 +const CONTEXT_MENU_COLLAPSE_ALL = 3 +const CONTEXT_MENU_EXPAND_ALL = 4 + + +@onready var _tree: Tree = $Panel/Tree +@onready var _report_list: Node = $report/ScrollContainer/list +@onready var _report_template: RichTextLabel = $report/report_template +@onready var _context_menu: PopupMenu = $contextMenu +@onready var _discover_hint: Control = %discover_hint +@onready var _spinner: Button = %spinner + +# loading tree icons +@onready var ICON_SPINNER := GdUnitUiTools.get_spinner() +@onready var ICON_FOLDER := GdUnitUiTools.get_icon("Folder") +# gdscript icons +@onready var ICON_GDSCRIPT_TEST_DEFAULT := GdUnitUiTools.get_icon("GDScript", Color.LIGHT_GRAY) +@onready var ICON_GDSCRIPT_TEST_SUCCESS := GdUnitUiTools.get_GDScript_icon("StatusSuccess", Color.DARK_GREEN) +@onready var ICON_GDSCRIPT_TEST_FLAKY := GdUnitUiTools.get_GDScript_icon("CheckBox", Color.GREEN_YELLOW) +@onready var ICON_GDSCRIPT_TEST_FAILED := GdUnitUiTools.get_GDScript_icon("StatusError", Color.SKY_BLUE) +@onready var ICON_GDSCRIPT_TEST_ERROR := GdUnitUiTools.get_GDScript_icon("StatusError", Color.DARK_RED) +@onready var ICON_GDSCRIPT_TEST_SUCCESS_ORPHAN := GdUnitUiTools.get_GDScript_icon("Unlinked", Color.DARK_GREEN) +@onready var ICON_GDSCRIPT_TEST_FAILED_ORPHAN := GdUnitUiTools.get_GDScript_icon("Unlinked", Color.SKY_BLUE) +@onready var ICON_GDSCRIPT_TEST_ERRORS_ORPHAN := GdUnitUiTools.get_GDScript_icon("Unlinked", Color.DARK_RED) +# csharp script icons +@onready var ICON_CSSCRIPT_TEST_DEFAULT := GdUnitUiTools.get_icon("CSharpScript", Color.LIGHT_GRAY) +@onready var ICON_CSSCRIPT_TEST_SUCCESS := GdUnitUiTools.get_CSharpScript_icon("StatusSuccess", Color.DARK_GREEN) +@onready var ICON_CSSCRIPT_TEST_FAILED := GdUnitUiTools.get_CSharpScript_icon("StatusError", Color.SKY_BLUE) +@onready var ICON_CSSCRIPT_TEST_ERROR := GdUnitUiTools.get_CSharpScript_icon("StatusError", Color.DARK_RED) +@onready var ICON_CSSCRIPT_TEST_SUCCESS_ORPHAN := GdUnitUiTools.get_CSharpScript_icon("Unlinked", Color.DARK_GREEN) +@onready var ICON_CSSCRIPT_TEST_FAILED_ORPHAN := GdUnitUiTools.get_CSharpScript_icon("Unlinked", Color.SKY_BLUE) +@onready var ICON_CSSCRIPT_TEST_ERRORS_ORPHAN := GdUnitUiTools.get_CSharpScript_icon("Unlinked", Color.DARK_RED) + + +enum GdUnitType { + FOLDER, + TEST_SUITE, + TEST_CASE, + TEST_GROUP +} + +const META_GDUNIT_PROGRESS_COUNT_MAX := "gdUnit_progress_count_max" +const META_GDUNIT_PROGRESS_INDEX := "gdUnit_progress_index" +const META_TEST_CASE := "gdunit_test_case" +const META_GDUNIT_NAME := "gdUnit_name" +const META_GDUNIT_STATE := "gdUnit_state" +const META_GDUNIT_TYPE := "gdUnit_type" +const META_GDUNIT_SUCCESS_TESTS := "gdUnit_suite_success_tests" +const META_GDUNIT_REPORT := "gdUnit_report" +const META_GDUNIT_ORPHAN := "gdUnit_orphan" +const META_GDUNIT_EXECUTION_TIME := "gdUnit_execution_time" +const META_GDUNIT_ORIGINAL_INDEX = "gdunit_original_index" +const STATE = GdUnitInspectorTreeConstants.STATE + + +var _tree_root: TreeItem +var _current_selected_item: TreeItem = null +var _current_tree_view_mode := GdUnitSettings.get_inspector_tree_view_mode() +var _run_test_recovery := true + + +## Used for debugging purposes only +func print_tree_item_ids(parent: TreeItem) -> TreeItem: + for child in parent.get_children(): + if child.has_meta(META_TEST_CASE): + var test_case: GdUnitTestCase = child.get_meta(META_TEST_CASE) + prints(test_case.guid, test_case.test_name) + + if child.get_child_count() > 0: + print_tree_item_ids(child) + + return null + + +func _find_tree_item(parent: TreeItem, item_name: String) -> TreeItem: + for child in parent.get_children(): + if child.get_meta(META_GDUNIT_NAME) == item_name: + return child + return null + + +func _find_tree_item_by_id(parent: TreeItem, id: GdUnitGUID) -> TreeItem: + for child in parent.get_children(): + if is_test_id(child, id): + return child + if child.get_child_count() > 0: + var item := _find_tree_item_by_id(child, id) + if item != null: + return item + + return null + + +func _find_tree_item_by_test_suite(parent: TreeItem, suite_path: String, suite_name: String) -> TreeItem: + for child in parent.get_children(): + if child.get_meta(META_GDUNIT_TYPE) == GdUnitType.TEST_SUITE: + var test_case: GdUnitTestCase = child.get_meta(META_TEST_CASE) + if test_case.suite_resource_path == suite_path and test_case.suite_name == suite_name: + return child + if child.get_child_count() > 0: + var item := _find_tree_item_by_test_suite(child, suite_path, suite_name) + if item != null: + return item + return null + + +func _find_first_item_by_state(parent: TreeItem, item_state: STATE, reverse := false) -> TreeItem: + var itmes := parent.get_children() + if reverse: + itmes.reverse() + for item in itmes: + if is_test_case(item) and (is_item_state(item, item_state)): + return item + var failure_item := _find_first_item_by_state(item, item_state, reverse) + if failure_item != null: + return failure_item + return null + + +func _find_last_item_by_state(parent: TreeItem, item_state: STATE) -> TreeItem: + return _find_first_item_by_state(parent, item_state, true) + + +func _find_item_by_state(current: TreeItem, item_state: STATE, prev := false) -> TreeItem: + var next := current.get_prev_in_tree() if prev else current.get_next_in_tree() + if next == null or next == _tree_root: + return null + if is_test_case(next) and is_item_state(next, item_state): + return next + return _find_item_by_state(next, item_state, prev) + + +func is_item_state(item: TreeItem, item_state: STATE) -> bool: + return item.has_meta(META_GDUNIT_STATE) and item.get_meta(META_GDUNIT_STATE) == item_state + + +func is_state_running(item: TreeItem) -> bool: + return is_item_state(item, STATE.RUNNING) + + +func is_state_success(item: TreeItem) -> bool: + return is_item_state(item, STATE.SUCCESS) + + +func is_state_warning(item: TreeItem) -> bool: + return is_item_state(item, STATE.WARNING) + + +func is_state_failed(item: TreeItem) -> bool: + return is_item_state(item, STATE.FAILED) + + +func is_state_error(item: TreeItem) -> bool: + return is_item_state(item, STATE.ERROR) or is_item_state(item, STATE.ABORDED) + + +func is_item_state_orphan(item: TreeItem) -> bool: + return item.has_meta(META_GDUNIT_ORPHAN) + + +func is_test_suite(item: TreeItem) -> bool: + return item.has_meta(META_GDUNIT_TYPE) and item.get_meta(META_GDUNIT_TYPE) == GdUnitType.TEST_SUITE + + +func is_test_case(item: TreeItem) -> bool: + return item.has_meta(META_GDUNIT_TYPE) and item.get_meta(META_GDUNIT_TYPE) == GdUnitType.TEST_CASE + + +func is_folder(item: TreeItem) -> bool: + return item.has_meta(META_GDUNIT_TYPE) and item.get_meta(META_GDUNIT_TYPE) == GdUnitType.FOLDER + + +func is_test_id(item: TreeItem, id: GdUnitGUID) -> bool: + if not item.has_meta(META_TEST_CASE): + return false + + var test_case: GdUnitTestCase = item.get_meta(META_TEST_CASE) + return test_case.guid.equals(id) + + +func disable_test_recovery() -> void: + _run_test_recovery = false + + +@warning_ignore("return_value_discarded") +func _ready() -> void: + _context_menu.set_item_icon(CONTEXT_MENU_RUN_ID, GdUnitUiTools.get_icon("Play")) + _context_menu.set_item_icon(CONTEXT_MENU_DEBUG_ID, GdUnitUiTools.get_icon("PlayStart")) + _context_menu.set_item_icon(CONTEXT_MENU_EXPAND_ALL, GdUnitUiTools.get_icon("ExpandTree")) + _context_menu.set_item_icon(CONTEXT_MENU_COLLAPSE_ALL, GdUnitUiTools.get_icon("CollapseTree")) + # do colorize the icons + #for index in _context_menu.item_count: + # _context_menu.set_item_icon_modulate(index, Color.MEDIUM_PURPLE) + + _spinner.icon = GdUnitUiTools.get_spinner() + init_tree() + GdUnitSignals.instance().gdunit_settings_changed.connect(_on_settings_changed) + GdUnitSignals.instance().gdunit_event.connect(_on_gdunit_event) + GdUnitSignals.instance().gdunit_test_discover_added.connect(on_test_case_discover_added) + GdUnitSignals.instance().gdunit_test_discover_deleted.connect(on_test_case_discover_deleted) + GdUnitSignals.instance().gdunit_test_discover_modified.connect(on_test_case_discover_modified) + var command_handler := GdUnitCommandHandler.instance() + command_handler.gdunit_runner_stop.connect(_on_gdunit_runner_stop) + if _run_test_recovery: + GdUnitTestDiscoverer.restore_last_session() + + +# we need current to manually redraw bacause of the animation bug +# https://github.com/godotengine/godot/issues/69330 +func _process(_delta: float) -> void: + if is_visible_in_tree(): + queue_redraw() + + +func init_tree() -> void: + cleanup_tree() + _tree.deselect_all() + _tree.set_hide_root(true) + _tree.ensure_cursor_is_visible() + _tree.set_allow_reselect(true) + _tree.set_allow_rmb_select(true) + _tree.set_columns(2) + _tree.set_column_clip_content(0, true) + _tree.set_column_expand_ratio(0, 1) + _tree.set_column_custom_minimum_width(0, 240) + _tree.set_column_expand_ratio(1, 0) + _tree.set_column_custom_minimum_width(1, 100) + _tree_root = _tree.create_item() + _tree_root.set_text(0, "tree_root") + _tree_root.set_meta(META_GDUNIT_NAME, "tree_root") + _tree_root.set_meta(META_GDUNIT_PROGRESS_COUNT_MAX, 0) + _tree_root.set_meta(META_GDUNIT_PROGRESS_INDEX, 0) + _tree_root.set_meta(META_GDUNIT_STATE, STATE.INITIAL) + _tree_root.set_meta(META_GDUNIT_SUCCESS_TESTS, 0) + # fix tree icon scaling + var scale_factor := EditorInterface.get_editor_scale() if Engine.is_editor_hint() else 1.0 + _tree.set("theme_override_constants/icon_max_width", 16 * scale_factor) + + +func cleanup_tree() -> void: + clear_reports() + if not _tree_root: + return + _free_recursive() + _tree.clear() + _current_selected_item = null + + +func _free_recursive(items:=_tree_root.get_children()) -> void: + for item in items: + _free_recursive(item.get_children()) + item.call_deferred("free") + + +func sort_tree_items(parent: TreeItem) -> void: + _sort_tree_items(parent, GdUnitSettings.get_inspector_tree_sort_mode()) + _tree.queue_redraw() + + +static func _sort_tree_items(parent: TreeItem, sort_mode: GdUnitInspectorTreeConstants.SORT_MODE) -> void: + parent.visible = false + var items := parent.get_children() + # first remove all childs before sorting + for item in items: + parent.remove_child(item) + + # do sort by selected sort mode + match sort_mode: + GdUnitInspectorTreeConstants.SORT_MODE.UNSORTED: + items.sort_custom(sort_items_by_original_index) + + GdUnitInspectorTreeConstants.SORT_MODE.NAME_ASCENDING: + items.sort_custom(sort_items_by_name.bind(true)) + + GdUnitInspectorTreeConstants.SORT_MODE.NAME_DESCENDING: + items.sort_custom(sort_items_by_name.bind(false)) + + GdUnitInspectorTreeConstants.SORT_MODE.EXECUTION_TIME: + items.sort_custom(sort_items_by_execution_time) + + # readding sorted childs + for item in items: + parent.add_child(item) + if item.get_child_count() > 0: + _sort_tree_items(item, sort_mode) + parent.visible = true + + +static func sort_items_by_name(a: TreeItem, b: TreeItem, ascending: bool) -> bool: + var type_a: GdUnitType = a.get_meta(META_GDUNIT_TYPE) + var type_b: GdUnitType = b.get_meta(META_GDUNIT_TYPE) + + # Sort folders to the top + if type_a == GdUnitType.FOLDER and type_b != GdUnitType.FOLDER: + return true + if type_b == GdUnitType.FOLDER and type_a != GdUnitType.FOLDER: + return false + + # sort by name + var name_a: String = a.get_meta(META_GDUNIT_NAME) + var name_b: String = b.get_meta(META_GDUNIT_NAME) + var comparison := name_a.naturalnocasecmp_to(name_b) + + return comparison < 0 if ascending else comparison > 0 + + +static func sort_items_by_execution_time(a: TreeItem, b: TreeItem) -> bool: + var type_a: GdUnitType = a.get_meta(META_GDUNIT_TYPE) + var type_b: GdUnitType = b.get_meta(META_GDUNIT_TYPE) + + # Sort folders to the top + if type_a == GdUnitType.FOLDER and type_b != GdUnitType.FOLDER: + return true + if type_b == GdUnitType.FOLDER and type_a != GdUnitType.FOLDER: + return false + + var execution_time_a :int = a.get_meta(META_GDUNIT_EXECUTION_TIME) + var execution_time_b :int = b.get_meta(META_GDUNIT_EXECUTION_TIME) + # if has same execution time sort by name + if execution_time_a == execution_time_b: + var name_a :String = a.get_meta(META_GDUNIT_NAME) + var name_b :String = b.get_meta(META_GDUNIT_NAME) + return name_a.naturalnocasecmp_to(name_b) > 0 + return execution_time_a > execution_time_b + + +static func sort_items_by_original_index(a: TreeItem, b: TreeItem) -> bool: + var type_a: GdUnitType = a.get_meta(META_GDUNIT_TYPE) + var type_b: GdUnitType = b.get_meta(META_GDUNIT_TYPE) + + # Sort folders to the top + if type_a == GdUnitType.FOLDER and type_b != GdUnitType.FOLDER: + return true + if type_b == GdUnitType.FOLDER and type_a != GdUnitType.FOLDER: + return false + + var index_a :int = a.get_meta(META_GDUNIT_ORIGINAL_INDEX) + var index_b :int = b.get_meta(META_GDUNIT_ORIGINAL_INDEX) + + # Sorting by index + return index_a < index_b + + +func restructure_tree(parent: TreeItem, tree_mode: GdUnitInspectorTreeConstants.TREE_VIEW_MODE) -> void: + _current_tree_view_mode = tree_mode + + match tree_mode: + GdUnitInspectorTreeConstants.TREE_VIEW_MODE.FLAT: + restructure_tree_to_flat(parent) + GdUnitInspectorTreeConstants.TREE_VIEW_MODE.TREE: + restructure_tree_to_tree(parent) + recalculate_counters(_tree_root) + # finally apply actual sort mode + sort_tree_items(_tree_root) + + +# Restructure into flat mode +func restructure_tree_to_flat(parent: TreeItem) -> void: + var folders := flatmap_folders(parent) + # Store current folder paths and their test suites + for folder_path: String in folders: + var test_suites: Array[TreeItem] = folders[folder_path] + if test_suites.is_empty(): + continue + + # Create flat folder and move test suites into it + var folder := _tree.create_item(parent) + folder.set_meta(META_GDUNIT_NAME, folder_path) + update_item_total_counter(folder) + set_state_initial(folder, GdUnitType.FOLDER) + + # Move test suites under the flat folder + for test_suite in test_suites: + var old_parent := test_suite.get_parent() + old_parent.remove_child(test_suite) + folder.add_child(test_suite) + + # Cleanup old folder structure + cleanup_empty_folders(parent) + + +# Restructure into hierarchical tree mode +func restructure_tree_to_tree(parent: TreeItem) -> void: + var items_to_process := parent.get_children().duplicate() + + for item: TreeItem in items_to_process: + if is_folder(item): + var folder_path: String = item.get_meta(META_GDUNIT_NAME) + var parts := folder_path.split("/") + + if parts.size() > 1: + var current_parent := parent + # Build folder hierarchy + for part in parts: + var next := _find_tree_item(current_parent, part) + if not next: + next = _tree.create_item(current_parent) + next.set_meta(META_GDUNIT_NAME, part) + set_state_initial(next, GdUnitType.FOLDER) + current_parent = next + + # Move test suites to deepest folder + var test_suites := item.get_children() + for test_suite in test_suites: + item.remove_child(test_suite) + current_parent.add_child(test_suite) + + # Remove the flat folder + item.get_parent().remove_child(item) + item.free() + + +func flatmap_folders(parent: TreeItem) -> Dictionary: + var folder_map := {} + + for item in parent.get_children(): + if is_folder(item): + var current_path: String = item.get_meta(META_GDUNIT_NAME) + # Get parent folder paths + var parent_path := get_parent_folder_path(item) + if parent_path: + current_path = parent_path + "/" + current_path + + # Collect direct children of this folder + var children: Array[TreeItem] = [] + for child in item.get_children(): + if is_test_suite(child): + children.append(child) + + # Add children to existing path or create new entry + if not children.is_empty(): + if folder_map.has(current_path): + @warning_ignore("unsafe_method_access") + folder_map[current_path].append_array(children) + else: + folder_map[current_path] = children + + # Recursively process subfolders + var sub_folders := flatmap_folders(item) + for path: String in sub_folders.keys(): + if folder_map.has(path): + @warning_ignore("unsafe_method_access") + folder_map[path].append_array(sub_folders[path]) + else: + folder_map[path] = sub_folders[path] + return folder_map + + +func get_parent_folder_path(item: TreeItem) -> String: + var path := "" + var parent := item.get_parent() + + while parent != _tree_root: + if is_folder(parent): + path = parent.get_meta(META_GDUNIT_NAME) + ("/" + path if path else "") + parent = parent.get_parent() + + return path + + +func cleanup_empty_folders(parent: TreeItem) -> void: + var folders: Array[TreeItem] = [] + # First collect all folders to avoid modification during iteration + for item in parent.get_children(): + if is_folder(item): + folders.append(item) + + # Process collected folders + for folder in folders: + cleanup_empty_folders(folder) + # Remove folder if it has no children after cleanup + if folder.get_child_count() == 0: + parent.remove_child(folder) + folder.free() + + +func reset_tree_state(parent: TreeItem) -> void: + if parent == _tree_root: + _tree_root.set_meta(META_GDUNIT_PROGRESS_INDEX, 0) + _tree_root.set_meta(META_GDUNIT_STATE, STATE.INITIAL) + test_counters_changed.emit(0, 0, STATE.INITIAL) + + for item in parent.get_children(): + set_state_initial(item, get_item_type(item)) + reset_tree_state(item) + + +func select_item(item: TreeItem) -> TreeItem: + if item != null: + # enshure the parent is collapsed + do_collapse_parent(item) + item.select(0) + _tree.ensure_cursor_is_visible() + _tree.scroll_to_item(item, true) + return item + + +func do_collapse_parent(item: TreeItem) -> void: + if item != null: + item.collapsed = false + do_collapse_parent(item.get_parent()) + + +func do_collapse_all(collapse: bool, parent := _tree_root) -> void: + for item in parent.get_children(): + item.collapsed = collapse + if not collapse: + do_collapse_all(collapse, item) + + +func set_state_initial(item: TreeItem, type: GdUnitType) -> void: + item.set_text(0, str(item.get_meta(META_GDUNIT_NAME))) + item.set_custom_color(0, Color.LIGHT_GRAY) + item.set_tooltip_text(0, "") + item.set_text_overrun_behavior(0, TextServer.OVERRUN_TRIM_CHAR) + item.set_expand_right(0, true) + + item.set_custom_color(1, Color.LIGHT_GRAY) + item.set_text(1, "") + item.set_expand_right(1, true) + item.set_tooltip_text(1, "") + + item.set_meta(META_GDUNIT_STATE, STATE.INITIAL) + item.set_meta(META_GDUNIT_TYPE, type) + item.set_meta(META_GDUNIT_SUCCESS_TESTS, 0) + item.set_meta(META_GDUNIT_EXECUTION_TIME, 0) + if item.has_meta(META_GDUNIT_PROGRESS_COUNT_MAX) and item.get_meta(META_GDUNIT_PROGRESS_COUNT_MAX) > 0: + item.set_text(0, "(0/%d) %s" % [item.get_meta(META_GDUNIT_PROGRESS_COUNT_MAX), item.get_meta(META_GDUNIT_NAME)]) + item.remove_meta(META_GDUNIT_REPORT) + item.remove_meta(META_GDUNIT_ORPHAN) + + set_item_icon_by_state(item) + + +func set_state_running(item: TreeItem, is_running: bool) -> void: + if is_state_running(item): + return + if is_item_state(item, STATE.INITIAL): + item.set_custom_color(0, Color.DARK_GREEN) + item.set_custom_color(1, Color.DARK_GREEN) + item.set_meta(META_GDUNIT_STATE, STATE.RUNNING) + item.collapsed = false + + if is_running: + item.set_icon(0, ICON_SPINNER) + else: + set_item_icon_by_state(item) + for child in item.get_children(): + set_item_icon_by_state(child) + + var parent := item.get_parent() + if parent != _tree_root: + set_state_running(parent, is_running) + + +func set_state_succeded(item: TreeItem) -> void: + # Do not overwrite higher states + if is_state_error(item) or is_state_failed(item): + return + if item == _tree_root: + return + item.set_custom_color(0, Color.GREEN) + item.set_custom_color(1, Color.GREEN) + item.set_meta(META_GDUNIT_STATE, STATE.SUCCESS) + item.collapsed = GdUnitSettings.is_inspector_node_collapse() + set_item_icon_by_state(item) + + +func set_state_flaky(item: TreeItem, event: GdUnitEvent) -> void: + # Do not overwrite higher states + if is_state_error(item): + return + var retry_count := event.statistic(GdUnitEvent.RETRY_COUNT) + item.set_meta(META_GDUNIT_STATE, STATE.FLAKY) + if retry_count > 1: + var item_text: String = item.get_meta(META_GDUNIT_NAME) + if item.has_meta(META_GDUNIT_PROGRESS_COUNT_MAX): + var success_count: int = item.get_meta(META_GDUNIT_SUCCESS_TESTS) + item_text = "(%d/%d) %s" % [success_count, item.get_meta(META_GDUNIT_PROGRESS_COUNT_MAX), item.get_meta(META_GDUNIT_NAME)] + item.set_text(0, "%s (%s retries)" % [item_text, retry_count]) + item.set_custom_color(0, Color.GREEN_YELLOW) + item.set_custom_color(1, Color.GREEN_YELLOW) + item.collapsed = false + set_item_icon_by_state(item) + + +func set_state_skipped(item: TreeItem) -> void: + item.set_meta(META_GDUNIT_STATE, STATE.SKIPPED) + item.set_text(1, "(skipped)") + item.set_text_alignment(1, HORIZONTAL_ALIGNMENT_RIGHT) + item.set_custom_color(0, Color.DARK_GRAY) + item.set_custom_color(1, Color.DARK_GRAY) + item.collapsed = false + set_item_icon_by_state(item) + + +func set_state_warnings(item: TreeItem) -> void: + # Do not overwrite higher states + if is_state_error(item) or is_state_failed(item): + return + item.set_meta(META_GDUNIT_STATE, STATE.WARNING) + item.set_custom_color(0, Color.YELLOW) + item.set_custom_color(1, Color.YELLOW) + item.collapsed = false + set_item_icon_by_state(item) + + +func set_state_failed(item: TreeItem, event: GdUnitEvent) -> void: + # Do not overwrite higher states + if is_state_error(item): + return + var retry_count := event.statistic(GdUnitEvent.RETRY_COUNT) + if retry_count > 1: + var item_text: String = item.get_meta(META_GDUNIT_NAME) + if item.has_meta(META_GDUNIT_PROGRESS_COUNT_MAX): + var success_count: int = item.get_meta(META_GDUNIT_SUCCESS_TESTS) + item_text = "(%d/%d) %s" % [success_count, item.get_meta(META_GDUNIT_PROGRESS_COUNT_MAX), item.get_meta(META_GDUNIT_NAME)] + item.set_text(0, "%s (%s retries)" % [item_text, retry_count]) + item.set_meta(META_GDUNIT_STATE, STATE.FAILED) + item.set_custom_color(0, Color.LIGHT_BLUE) + item.set_custom_color(1, Color.LIGHT_BLUE) + item.collapsed = false + set_item_icon_by_state(item) + + +func set_state_error(item: TreeItem) -> void: + item.set_meta(META_GDUNIT_STATE, STATE.ERROR) + item.set_custom_color(0, Color.ORANGE_RED) + item.set_custom_color(1, Color.ORANGE_RED) + set_item_icon_by_state(item) + item.collapsed = false + + +func set_state_aborted(item: TreeItem) -> void: + item.set_meta(META_GDUNIT_STATE, STATE.ABORDED) + item.set_custom_color(0, Color.ORANGE_RED) + item.set_custom_color(1, Color.ORANGE_RED) + item.clear_custom_bg_color(0) + item.set_text(1, "(aborted)") + item.set_text_alignment(1, HORIZONTAL_ALIGNMENT_RIGHT) + set_item_icon_by_state(item) + item.collapsed = false + + +func set_state_orphan(item: TreeItem, event: GdUnitEvent) -> void: + var orphan_count := event.statistic(GdUnitEvent.ORPHAN_NODES) + if orphan_count == 0: + return + if item.has_meta(META_GDUNIT_ORPHAN): + orphan_count += item.get_meta(META_GDUNIT_ORPHAN) + item.set_meta(META_GDUNIT_ORPHAN, orphan_count) + if item.get_meta(META_GDUNIT_STATE) != STATE.FAILED: + item.set_custom_color(0, Color.YELLOW) + item.set_custom_color(1, Color.YELLOW) + item.set_tooltip_text(0, "Total <%d> orphan nodes detected." % orphan_count) + set_item_icon_by_state(item) + + +func update_state(item: TreeItem, event: GdUnitEvent, add_reports := true) -> void: + # we do not show the root + if item == null: + return + + if event.is_skipped(): + set_state_skipped(item) + elif event.is_success() and event.is_flaky(): + set_state_flaky(item, event) + elif event.is_success(): + set_state_succeded(item) + elif event.is_error(): + set_state_error(item) + elif event.is_failed(): + set_state_failed(item, event) + elif event.is_warning(): + set_state_warnings(item) + if add_reports: + for report in event.reports(): + add_report(item, report) + set_state_orphan(item, event) + + var parent := item.get_parent() + if parent == null: + return + + var item_state: int = item.get_meta(META_GDUNIT_STATE) + var parent_state: int = parent.get_meta(META_GDUNIT_STATE) + if item_state <= parent_state: + return + update_state(item.get_parent(), event, false) + + +func add_report(item: TreeItem, report: GdUnitReport) -> void: + var reports: Array[GdUnitReport] = [] + if item.has_meta(META_GDUNIT_REPORT): + reports = get_item_reports(item) + reports.append(report) + item.set_meta(META_GDUNIT_REPORT, reports) + + +func abort_running(items:=_tree_root.get_children()) -> void: + for item in items: + if is_state_running(item): + set_state_aborted(item) + abort_running(item.get_children()) + + +func _on_select_next_item_by_state(item_state: int) -> TreeItem: + var current_selected := _tree.get_selected() + # If nothing is selected, the first error is selected or the next one in the vicinity of the current selection is found + current_selected = _find_first_item_by_state(_tree_root, item_state) if current_selected == null else _find_item_by_state(current_selected, item_state) + # If no next failure found, then we try to select first + if current_selected == null: + current_selected = _find_first_item_by_state(_tree_root, item_state) + return select_item(current_selected) + + +func _on_select_previous_item_by_state(item_state: int) -> TreeItem: + var current_selected := _tree.get_selected() + # If nothing is selected, the first error is selected or the next one in the vicinity of the current selection is found + current_selected = _find_last_item_by_state(_tree_root, item_state) if current_selected == null else _find_item_by_state(current_selected, item_state, true) + # If no next failure found, then we try to select first last + if current_selected == null: + current_selected = _find_last_item_by_state(_tree_root, item_state) + return select_item(current_selected) + + +func select_first_orphan() -> void: + for parent in _tree_root.get_children(): + if not is_state_success(parent): + for item in parent.get_children(): + if is_item_state_orphan(item): + parent.set_collapsed(false) + @warning_ignore("return_value_discarded") + select_item(item) + return + + +func clear_reports() -> void: + for child in _report_list.get_children(): + _report_list.remove_child(child) + child.queue_free() + + +func show_failed_report(selected_item: TreeItem) -> void: + clear_reports() + if selected_item == null or not selected_item.has_meta(META_GDUNIT_REPORT): + return + # add new reports + for report in get_item_reports(selected_item): + var reportNode: RichTextLabel = _report_template.duplicate() + _report_list.add_child(reportNode) + reportNode.append_text(report.to_string()) + reportNode.visible = true + + +func update_test_suite(event: GdUnitEvent) -> void: + var item := _find_tree_item_by_test_suite(_tree_root, event.resource_path(), event.suite_name()) + if not item: + push_error("[InspectorTreeMainPanel#update_test_suite] Internal Error: Can't find test suite item '{_suite_name}' for {_resource_path} ".format(event)) + return + if event.type() == GdUnitEvent.TESTSUITE_AFTER: + update_item_elapsed_time_counter(item, event.elapsed_time()) + update_state(item, event) + set_state_running(item, false) + + +func update_test_case(event: GdUnitEvent) -> void: + var item := _find_tree_item_by_id(_tree_root, event.guid()) + if not item: + #push_error("Internal Error: Can't find test id %s" % [event.guid()]) + return + if event.type() == GdUnitEvent.TESTCASE_BEFORE: + set_state_running(item, true) + # force scrolling to current test case + _tree.scroll_to_item(item, true) + return + + if event.type() == GdUnitEvent.TESTCASE_AFTER: + update_item_elapsed_time_counter(item, event.elapsed_time()) + if event.is_success() or event.is_warning(): + update_item_processed_counter(item) + update_state(item, event) + update_progress_counters(item) + + +func create_item(parent: TreeItem, test: GdUnitTestCase, item_name: String, type: GdUnitType) -> TreeItem: + var item := _tree.create_item(parent) + item.collapsed = true + item.set_meta(META_GDUNIT_ORIGINAL_INDEX, item.get_index()) + item.set_text(0, item_name) + match type: + GdUnitType.TEST_CASE: + item.set_meta(META_TEST_CASE, test) + GdUnitType.TEST_GROUP: + # We need to create a copy of the test record meta with a new uniqe guid + item.set_meta(META_TEST_CASE, GdUnitTestCase.from(test.suite_resource_path, test.source_file, test.line_number, test.test_name)) + GdUnitType.TEST_SUITE: + # We need to create a copy of the test record meta with a new uniqe guid + item.set_meta(META_TEST_CASE, GdUnitTestCase.from(test.suite_resource_path, test.source_file, test.line_number, test.suite_name)) + + item.set_meta(META_GDUNIT_NAME, item_name) + set_state_initial(item, type) + update_item_total_counter(item) + return item + + +func set_item_icon_by_state(item :TreeItem) -> void: + if item == _tree_root: + return + var state :STATE = item.get_meta(META_GDUNIT_STATE) + var is_orphan := is_item_state_orphan(item) + var resource_path := get_item_source_file(item) + item.set_icon(0, get_icon_by_file_type(resource_path, state, is_orphan)) + if item.get_meta(META_GDUNIT_TYPE) == GdUnitType.FOLDER: + item.set_icon_modulate(0, Color.SKY_BLUE) + + +func update_item_total_counter(item: TreeItem) -> void: + if item == null: + return + + var child_count := get_total_child_count(item) + if child_count > 0: + item.set_meta(META_GDUNIT_PROGRESS_COUNT_MAX, child_count) + item.set_text(0, "(0/%d) %s" % [child_count, item.get_meta(META_GDUNIT_NAME)]) + + update_item_total_counter(item.get_parent()) + + +func get_total_child_count(item: TreeItem) -> int: + var total_count := 0 + for child in item.get_children(): + total_count += child.get_meta(META_GDUNIT_PROGRESS_COUNT_MAX) if child.has_meta(META_GDUNIT_PROGRESS_COUNT_MAX) else 1 + return total_count + + +func update_item_processed_counter(item: TreeItem, add_count := 1) -> void: + if item == _tree_root: + return + + var success_count: int = item.get_meta(META_GDUNIT_SUCCESS_TESTS) + add_count + item.set_meta(META_GDUNIT_SUCCESS_TESTS, success_count) + if item.has_meta(META_GDUNIT_PROGRESS_COUNT_MAX): + item.set_text(0, "(%d/%d) %s" % [success_count, item.get_meta(META_GDUNIT_PROGRESS_COUNT_MAX), item.get_meta(META_GDUNIT_NAME)]) + + update_item_processed_counter(item.get_parent(), add_count) + + +func update_progress_counters(item: TreeItem) -> void: + var index: int = _tree_root.get_meta(META_GDUNIT_PROGRESS_INDEX) + 1 + var total_test: int = _tree_root.get_meta(META_GDUNIT_PROGRESS_COUNT_MAX) + var state: STATE = item.get_meta(META_GDUNIT_STATE) + test_counters_changed.emit(index, total_test, state) + _tree_root.set_meta(META_GDUNIT_PROGRESS_INDEX, index) + + +func recalculate_counters(parent: TreeItem) -> void: + # Reset the counter first + if parent.has_meta(META_GDUNIT_PROGRESS_COUNT_MAX): + parent.set_meta(META_GDUNIT_PROGRESS_COUNT_MAX, 0) + if parent.has_meta(META_GDUNIT_PROGRESS_INDEX): + parent.set_meta(META_GDUNIT_PROGRESS_INDEX, 0) + if parent.has_meta(META_GDUNIT_SUCCESS_TESTS): + parent.set_meta(META_GDUNIT_SUCCESS_TESTS, 0) + + # Calculate new count based on children + var total_count := 0 + var success_count := 0 + var progress_index := 0 + + for child in parent.get_children(): + if child.get_child_count() > 0: + # Recursively update child counters first + recalculate_counters(child) + # Add child's counters to parent + if child.has_meta(META_GDUNIT_PROGRESS_COUNT_MAX): + total_count += child.get_meta(META_GDUNIT_PROGRESS_COUNT_MAX) + if child.has_meta(META_GDUNIT_SUCCESS_TESTS): + success_count += child.get_meta(META_GDUNIT_SUCCESS_TESTS) + if child.has_meta(META_GDUNIT_PROGRESS_INDEX): + progress_index += child.get_meta(META_GDUNIT_PROGRESS_INDEX) + elif is_test_case(child): + # Count individual test cases + total_count += 1 + # Count completed tests + if is_state_success(child) or is_state_warning(child) or is_state_failed(child) or is_state_error(child): + progress_index += 1 + if is_state_success(child) or is_state_warning(child): + success_count += 1 + + # Update the counters + if total_count > 0: + parent.set_meta(META_GDUNIT_PROGRESS_COUNT_MAX, total_count) + parent.set_meta(META_GDUNIT_PROGRESS_INDEX, progress_index) + parent.set_meta(META_GDUNIT_SUCCESS_TESTS, success_count) + + # Update the display text + parent.set_text(0, "(%d/%d) %s" % [success_count, total_count, parent.get_meta(META_GDUNIT_NAME)]) + + +func update_item_elapsed_time_counter(item: TreeItem, time: int) -> void: + item.set_text(1, "%s" % LocalTime.elapsed(time)) + item.set_text_alignment(1, HORIZONTAL_ALIGNMENT_RIGHT) + item.set_meta(META_GDUNIT_EXECUTION_TIME, time) + + var parent := item.get_parent() + if parent == _tree_root: + return + var elapsed_time :int = parent.get_meta(META_GDUNIT_EXECUTION_TIME) + time + var type :GdUnitType = item.get_meta(META_GDUNIT_TYPE) + match type: + GdUnitType.TEST_CASE: + return + GdUnitType.TEST_SUITE: + update_item_elapsed_time_counter(parent, elapsed_time) + #GdUnitType.FOLDER: + # update_item_elapsed_time_counter(parent, elapsed_time) + + +func get_icon_by_file_type(path: String, state: STATE, orphans: bool) -> Texture2D: + if path.get_extension() == "gd": + match state: + STATE.INITIAL: + return ICON_GDSCRIPT_TEST_DEFAULT + STATE.SUCCESS: + return ICON_GDSCRIPT_TEST_SUCCESS_ORPHAN if orphans else ICON_GDSCRIPT_TEST_SUCCESS + STATE.ERROR: + return ICON_GDSCRIPT_TEST_ERRORS_ORPHAN if orphans else ICON_GDSCRIPT_TEST_ERROR + STATE.FAILED: + return ICON_GDSCRIPT_TEST_FAILED_ORPHAN if orphans else ICON_GDSCRIPT_TEST_FAILED + STATE.WARNING: + return ICON_GDSCRIPT_TEST_SUCCESS_ORPHAN if orphans else ICON_GDSCRIPT_TEST_DEFAULT + STATE.FLAKY: + return ICON_GDSCRIPT_TEST_SUCCESS_ORPHAN if orphans else ICON_GDSCRIPT_TEST_FLAKY + _: + return ICON_GDSCRIPT_TEST_DEFAULT + if path.get_extension() == "cs": + match state: + STATE.INITIAL: + return ICON_CSSCRIPT_TEST_DEFAULT + STATE.SUCCESS: + return ICON_CSSCRIPT_TEST_SUCCESS_ORPHAN if orphans else ICON_CSSCRIPT_TEST_SUCCESS + STATE.ERROR: + return ICON_CSSCRIPT_TEST_ERRORS_ORPHAN if orphans else ICON_CSSCRIPT_TEST_ERROR + STATE.FAILED: + return ICON_CSSCRIPT_TEST_FAILED_ORPHAN if orphans else ICON_CSSCRIPT_TEST_FAILED + STATE.WARNING: + return ICON_CSSCRIPT_TEST_SUCCESS_ORPHAN if orphans else ICON_CSSCRIPT_TEST_DEFAULT + _: + return ICON_CSSCRIPT_TEST_DEFAULT + match state: + STATE.INITIAL: + return ICON_FOLDER + STATE.ERROR: + return ICON_FOLDER + STATE.FAILED: + return ICON_FOLDER + _: + return ICON_FOLDER + + +func on_test_case_discover_added(test_case: GdUnitTestCase) -> void: + var test_root_folder := GdUnitSettings.test_root_folder().replace("res://", "") + var fully_qualified_name := test_case.fully_qualified_name.trim_suffix(test_case.display_name) + var parts := fully_qualified_name.split(".", false) + parts.append(test_case.display_name) + # Skip tree structure until test root folder + var index := parts.find(test_root_folder) + if index != -1: + parts = parts.slice(index+1) + + match _current_tree_view_mode: + GdUnitInspectorTreeConstants.TREE_VIEW_MODE.FLAT: + create_items_tree_mode_flat(test_case, parts) + GdUnitInspectorTreeConstants.TREE_VIEW_MODE.TREE: + create_items_tree_mode_tree(test_case, parts) + + +func create_items_tree_mode_tree(test_case: GdUnitTestCase, parts: PackedStringArray) -> void: + var parent := _tree_root + var is_suite_assigned := false + var suite_name := test_case.suite_name.split(".")[-1] + for item_name in parts: + var next := _find_tree_item(parent, item_name) + if next != null: + parent = next + continue + + if not is_suite_assigned and suite_name == item_name: + next = create_item(parent, test_case, item_name, GdUnitType.TEST_SUITE) + is_suite_assigned = true + elif item_name == test_case.display_name: + next = create_item(parent, test_case, item_name, GdUnitType.TEST_CASE) + # On grouped tests (parameterized tests) + elif item_name == test_case.test_name: + next = create_item(parent, test_case, item_name, GdUnitType.TEST_GROUP) + else: + next = create_item(parent, test_case, item_name, GdUnitType.FOLDER) + parent = next + + +func create_items_tree_mode_flat(test_case: GdUnitTestCase, parts: PackedStringArray) -> void: + # All parts except the last two (suite name and test name/display name) + var slice_index := -2 if parts[-1] == test_case.test_name else -3 + var path_parts := parts.slice(0, slice_index) + var folder_path := "/".join(path_parts) + + # Find or create flat folder + var folder_item: TreeItem + if folder_path.is_empty(): + folder_item = _tree_root + else: + folder_item = _find_tree_item(_tree_root, folder_path) + if folder_item == null: + folder_item = create_item(_tree_root, test_case, folder_path, GdUnitType.FOLDER) + + # Find suite under the flat folder (second to last part) + var suite_item := _find_tree_item(folder_item, test_case.suite_name) + if suite_item == null: + suite_item = create_item(folder_item, test_case, test_case.suite_name, GdUnitType.TEST_SUITE) + + # Add test case or group under the suite + if test_case.test_name != test_case.display_name: + # It's a parameterized test group + var group_item := _find_tree_item(suite_item, test_case.test_name) + if group_item == null: + group_item = create_item(suite_item, test_case, test_case.test_name, GdUnitType.TEST_GROUP) + create_item(group_item, test_case, test_case.display_name, GdUnitType.TEST_CASE) + else: + create_item(suite_item, test_case, test_case.display_name, GdUnitType.TEST_CASE) + + +func on_test_case_discover_deleted(test_case: GdUnitTestCase) -> void: + var item := _find_tree_item_by_id(_tree_root, test_case.guid) + if item != null: + var parent := item.get_parent() + parent.remove_child(item) + + # update the cached counters + var item_success_count: int = item.get_meta(META_GDUNIT_SUCCESS_TESTS) + var item_total_test_count: int = item.get_meta(META_GDUNIT_PROGRESS_COUNT_MAX, 0) + var total_test_count: int = parent.get_meta(META_GDUNIT_PROGRESS_COUNT_MAX, 0) + parent.set_meta(META_GDUNIT_PROGRESS_COUNT_MAX, total_test_count-item_total_test_count) + + # propagate counter update to all parents + update_item_total_counter(parent) + update_item_processed_counter(parent, -item_success_count) + + +func on_test_case_discover_modified(test_case: GdUnitTestCase) -> void: + var item := _find_tree_item_by_id(_tree_root, test_case.guid) + if item != null: + item.set_meta(META_TEST_CASE, test_case) + item.set_text(0, test_case.display_name) + item.set_meta(META_GDUNIT_NAME, test_case.display_name) + + +func get_item_reports(item: TreeItem) -> Array[GdUnitReport]: + return item.get_meta(META_GDUNIT_REPORT) + + +func get_item_test_line_number(item: TreeItem) -> int: + if item == null or not item.has_meta(META_TEST_CASE): + return -1 + + var test_case: GdUnitTestCase = item.get_meta(META_TEST_CASE) + return test_case.line_number + + +func get_item_source_file(item: TreeItem) -> String: + if item == null or not item.has_meta(META_TEST_CASE): + return "" + + var test_case: GdUnitTestCase = item.get_meta(META_TEST_CASE) + return test_case.source_file + + +func get_item_type(item: TreeItem) -> GdUnitType: + if item == null or not item.has_meta(META_GDUNIT_TYPE): + return GdUnitType.FOLDER + return item.get_meta(META_GDUNIT_TYPE) + + +func _dump_tree_as_json(dump_name: String) -> void: + var dict := _to_json(_tree_root) + var file := FileAccess.open("res://%s.json" % dump_name, FileAccess.WRITE) + file.store_string(JSON.stringify(dict, "\t")) + + +func _to_json(parent :TreeItem) -> Dictionary: + var item_as_dict := GdObjects.obj2dict(parent) + item_as_dict["TreeItem"]["childrens"] = parent.get_children().map(func(item: TreeItem) -> Dictionary: + return _to_json(item)) + return item_as_dict + + +func extract_resource_path(event: GdUnitEvent) -> String: + return ProjectSettings.localize_path(event.resource_path()) + + +func collect_test_cases(item: TreeItem, tests: Array[GdUnitTestCase] = []) -> Array[GdUnitTestCase]: + for next in item.get_children(): + collect_test_cases(next, tests) + + if is_test_case(item): + var test: GdUnitTestCase = item.get_meta(META_TEST_CASE) + if not tests.has(test): + tests.append(test) + + return tests + + +################################################################################ +# Tree signal receiver +################################################################################ +func _on_tree_item_mouse_selected(mouse_position: Vector2, mouse_button_index: int) -> void: + if mouse_button_index == MOUSE_BUTTON_RIGHT: + _context_menu.position = get_screen_position() + mouse_position + _context_menu.popup() + + +func _on_run_pressed(run_debug: bool) -> void: + _context_menu.hide() + var item: = _tree.get_selected() + if item == null: + print_rich("[color=GOLDENROD]Abort Testrun, no test suite selected![/color]") + return + + var test_to_execute := collect_test_cases(item) + GdUnitCommandHandler.instance().cmd_run_tests(test_to_execute, run_debug) + + +func _on_Tree_item_selected() -> void: + # only show report checked manual item selection + # we need to check the run mode here otherwise it will be called every selection + if not _context_menu.is_item_disabled(CONTEXT_MENU_RUN_ID): + var selected_item: TreeItem = _tree.get_selected() + show_failed_report(selected_item) + _current_selected_item = _tree.get_selected() + tree_item_selected.emit(_current_selected_item) + + +# Opens the test suite +func _on_Tree_item_activated() -> void: + var selected_item := _tree.get_selected() + var line_number := get_item_test_line_number(selected_item) + if line_number != -1: + var script_path := ProjectSettings.localize_path(get_item_source_file(selected_item)) + var resource: Script = load(script_path) + + if selected_item.has_meta(META_GDUNIT_REPORT): + var reports := get_item_reports(selected_item) + var report_line_number := reports[0].line_number() + # if number -1 we use original stored line number of the test case + # in non debug mode the line number is not available + if report_line_number != -1: + line_number = report_line_number + + EditorInterface.get_file_system_dock().navigate_to_path(script_path) + EditorInterface.edit_script(resource, line_number) + elif selected_item.get_meta(META_GDUNIT_TYPE) == GdUnitType.FOLDER: + # Toggle collapse if dir + selected_item.collapsed = not selected_item.collapsed + + +################################################################################ +# external signal receiver +################################################################################ +func _on_gdunit_runner_start() -> void: + _context_menu.set_item_disabled(CONTEXT_MENU_RUN_ID, true) + _context_menu.set_item_disabled(CONTEXT_MENU_DEBUG_ID, true) + reset_tree_state(_tree_root) + clear_reports() + + +func _on_gdunit_runner_stop(_id: int) -> void: + _context_menu.set_item_disabled(CONTEXT_MENU_RUN_ID, false) + _context_menu.set_item_disabled(CONTEXT_MENU_DEBUG_ID, false) + abort_running() + sort_tree_items(_tree_root) + # wait until the tree redraw + await get_tree().process_frame + var failure_item := _find_first_item_by_state(_tree_root, STATE.FAILED) + select_item( failure_item if failure_item else _current_selected_item) + + +func _on_gdunit_event(event: GdUnitEvent) -> void: + match event.type(): + GdUnitEvent.DISCOVER_START: + _tree_root.visible = false + _discover_hint.visible = true + init_tree() + + GdUnitEvent.DISCOVER_END: + sort_tree_items(_tree_root) + select_item(_tree_root.get_first_child()) + _discover_hint.visible = false + _tree_root.visible = true + #_dump_tree_as_json("tree_example_discovered") + + GdUnitEvent.INIT: + _on_gdunit_runner_start() + + GdUnitEvent.TESTCASE_BEFORE: + update_test_case(event) + + GdUnitEvent.TESTCASE_AFTER: + update_test_case(event) + + GdUnitEvent.TESTSUITE_BEFORE: + update_test_suite(event) + + GdUnitEvent.TESTSUITE_AFTER: + update_test_suite(event) + + +func _on_context_m_index_pressed(index: int) -> void: + match index: + CONTEXT_MENU_DEBUG_ID: + _on_run_pressed(true) + CONTEXT_MENU_RUN_ID: + _on_run_pressed(false) + CONTEXT_MENU_EXPAND_ALL: + do_collapse_all(false) + CONTEXT_MENU_COLLAPSE_ALL: + do_collapse_all(true) + + +func _on_settings_changed(property :GdUnitProperty) -> void: + match property.name(): + GdUnitSettings.INSPECTOR_TREE_SORT_MODE: + sort_tree_items(_tree_root) + #_dump_tree_as_json("tree_sorted_by_%s" % GdUnitInspectorTreeConstants.SORT_MODE.keys()[property.value()]) + + GdUnitSettings.INSPECTOR_TREE_VIEW_MODE: + restructure_tree(_tree_root, GdUnitSettings.get_inspector_tree_view_mode()) diff --git a/addons/gdUnit4/src/ui/parts/InspectorTreeMainPanel.gd.uid b/addons/gdUnit4/src/ui/parts/InspectorTreeMainPanel.gd.uid new file mode 100644 index 0000000..c6528ec --- /dev/null +++ b/addons/gdUnit4/src/ui/parts/InspectorTreeMainPanel.gd.uid @@ -0,0 +1 @@ +uid://b8t6fs8lm7gqm diff --git a/addons/gdUnit4/src/ui/parts/InspectorTreePanel.tscn b/addons/gdUnit4/src/ui/parts/InspectorTreePanel.tscn new file mode 100644 index 0000000..ca8b042 --- /dev/null +++ b/addons/gdUnit4/src/ui/parts/InspectorTreePanel.tscn @@ -0,0 +1,237 @@ +[gd_scene load_steps=15 format=3 uid="uid://bqfpidewtpeg0"] + +[ext_resource type="Script" uid="uid://b8t6fs8lm7gqm" path="res://addons/gdUnit4/src/ui/parts/InspectorTreeMainPanel.gd" id="1"] + +[sub_resource type="DPITexture" id="DPITexture_466oo"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[sub_resource type="DPITexture" id="DPITexture_o6s0p"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[sub_resource type="DPITexture" id="DPITexture_miuuy"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[sub_resource type="DPITexture" id="DPITexture_ern2r"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[sub_resource type="DPITexture" id="DPITexture_qdci2"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[sub_resource type="DPITexture" id="DPITexture_hed0i"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[sub_resource type="DPITexture" id="DPITexture_8v04w"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[sub_resource type="DPITexture" id="DPITexture_arwmg"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[sub_resource type="AnimatedTexture" id="AnimatedTexture_rqglq"] +frames = 8 +speed_scale = 2.5 +frame_0/texture = SubResource("DPITexture_466oo") +frame_0/duration = 0.2 +frame_1/texture = SubResource("DPITexture_o6s0p") +frame_1/duration = 0.2 +frame_2/texture = SubResource("DPITexture_miuuy") +frame_2/duration = 0.2 +frame_3/texture = SubResource("DPITexture_ern2r") +frame_3/duration = 0.2 +frame_4/texture = SubResource("DPITexture_qdci2") +frame_4/duration = 0.2 +frame_5/texture = SubResource("DPITexture_hed0i") +frame_5/duration = 0.2 +frame_6/texture = SubResource("DPITexture_8v04w") +frame_6/duration = 0.2 +frame_7/texture = SubResource("DPITexture_arwmg") +frame_7/duration = 0.2 + +[sub_resource type="DPITexture" id="DPITexture_87jj1"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[sub_resource type="DPITexture" id="DPITexture_7oobd"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[sub_resource type="DPITexture" id="DPITexture_ltb1l"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[sub_resource type="DPITexture" id="DPITexture_2lq8w"] +_source = " +" +color_map = { +Color(1, 0.37254903, 0.37254903, 1): Color(1, 0.47, 0.42, 1), +Color(0.37254903, 1, 0.5921569, 1): Color(0.45, 0.95, 0.5, 1), +Color(1, 0.8666667, 0.39607844, 1): Color(1, 0.87, 0.4, 1) +} + +[node name="MainPanel" type="VSplitContainer"] +use_parent_material = true +clip_contents = true +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +offset_right = -924.0 +grow_horizontal = 2 +grow_vertical = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +split_offset = 200 +script = ExtResource("1") + +[node name="Panel" type="PanelContainer" parent="."] +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="Tree" type="Tree" parent="Panel"] +use_parent_material = true +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +theme_override_constants/icon_max_width = 16 +columns = 2 +allow_reselect = true +allow_rmb_select = true +hide_root = true +select_mode = 1 + +[node name="discover_hint" type="HBoxContainer" parent="Panel"] +unique_name_in_owner = true +visible = false +use_parent_material = true +layout_mode = 2 +alignment = 1 + +[node name="spinner" type="Button" parent="Panel/discover_hint"] +unique_name_in_owner = true +clip_contents = true +custom_minimum_size = Vector2(64, 64) +layout_mode = 2 +size_flags_stretch_ratio = 1.94 +disabled = true +button_mask = 0 +text = "Discover Tests" +icon = SubResource("AnimatedTexture_rqglq") +flat = true +alignment = 2 + +[node name="report" type="PanelContainer" parent="."] +clip_contents = true +layout_mode = 2 +size_flags_horizontal = 11 +size_flags_vertical = 11 + +[node name="report_template" type="RichTextLabel" parent="report"] +auto_translate_mode = 2 +use_parent_material = true +clip_contents = false +layout_mode = 2 +size_flags_horizontal = 3 +localize_numeral_system = false +focus_mode = 2 +bbcode_enabled = true +fit_content = true +selection_enabled = true + +[node name="ScrollContainer" type="ScrollContainer" parent="report"] +use_parent_material = true +custom_minimum_size = Vector2(0, 80) +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 11 + +[node name="list" type="VBoxContainer" parent="report/ScrollContainer"] +clip_contents = true +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="contextMenu" type="PopupMenu" parent="."] +auto_translate_mode = 2 +size = Vector2i(133, 120) +item_count = 5 +item_0/text = "Run" +item_0/icon = SubResource("DPITexture_87jj1") +item_0/id = 0 +item_1/text = "Debug" +item_1/icon = SubResource("DPITexture_7oobd") +item_1/id = 1 +item_2/id = 2 +item_2/separator = true +item_3/text = "Collapse All" +item_3/icon = SubResource("DPITexture_ltb1l") +item_3/id = 3 +item_4/text = "Expand All" +item_4/icon = SubResource("DPITexture_2lq8w") +item_4/id = 4 + +[connection signal="item_activated" from="Panel/Tree" to="." method="_on_Tree_item_activated"] +[connection signal="item_mouse_selected" from="Panel/Tree" to="." method="_on_tree_item_mouse_selected"] +[connection signal="item_selected" from="Panel/Tree" to="." method="_on_Tree_item_selected"] +[connection signal="index_pressed" from="contextMenu" to="." method="_on_context_m_index_pressed"] diff --git a/addons/gdUnit4/src/ui/settings/GdUnitInputCapture.gd b/addons/gdUnit4/src/ui/settings/GdUnitInputCapture.gd new file mode 100644 index 0000000..b5cc837 --- /dev/null +++ b/addons/gdUnit4/src/ui/settings/GdUnitInputCapture.gd @@ -0,0 +1,56 @@ +@tool +class_name GdUnitInputCapture +extends Control + +signal input_completed(input_event: InputEventKey) + + +var _tween: Tween +var _input_event: InputEventKey + + +func _ready() -> void: + reset() + self_modulate = Color.WHITE + _tween = create_tween() + @warning_ignore("return_value_discarded") + _tween.set_loops() + @warning_ignore("return_value_discarded") + _tween.tween_property(%Label, "self_modulate", Color(1, 1, 1, .8), 1.0).from_current().set_trans(Tween.TRANS_BACK).set_ease(Tween.EASE_IN_OUT) + + +func reset() -> void: + _input_event = InputEventKey.new() + + +func _input(event: InputEvent) -> void: + if not is_visible_in_tree(): + return + if event is InputEventKey and event.is_pressed() and not event.is_echo(): + var _event := event as InputEventKey + match _event.keycode: + KEY_CTRL: + _input_event.ctrl_pressed = true + KEY_SHIFT: + _input_event.shift_pressed = true + KEY_ALT: + _input_event.alt_pressed = true + KEY_META: + _input_event.meta_pressed = true + _: + _input_event.keycode = _event.keycode + _apply_input_modifiers(_event) + accept_event() + + if event is InputEventKey and not event.is_pressed(): + input_completed.emit(_input_event) + hide() + + +func _apply_input_modifiers(event: InputEvent) -> void: + if event is InputEventWithModifiers: + var _event := event as InputEventWithModifiers + _input_event.meta_pressed = _event.meta_pressed or _input_event.meta_pressed + _input_event.alt_pressed = _event.alt_pressed or _input_event.alt_pressed + _input_event.shift_pressed = _event.shift_pressed or _input_event.shift_pressed + _input_event.ctrl_pressed = _event.ctrl_pressed or _input_event.ctrl_pressed diff --git a/addons/gdUnit4/src/ui/settings/GdUnitInputCapture.gd.uid b/addons/gdUnit4/src/ui/settings/GdUnitInputCapture.gd.uid new file mode 100644 index 0000000..5f404fa --- /dev/null +++ b/addons/gdUnit4/src/ui/settings/GdUnitInputCapture.gd.uid @@ -0,0 +1 @@ +uid://co3e73fsrm8c2 diff --git a/addons/gdUnit4/src/ui/settings/GdUnitInputCapture.tscn b/addons/gdUnit4/src/ui/settings/GdUnitInputCapture.tscn new file mode 100644 index 0000000..b7894ef --- /dev/null +++ b/addons/gdUnit4/src/ui/settings/GdUnitInputCapture.tscn @@ -0,0 +1,36 @@ +[gd_scene load_steps=2 format=3 uid="uid://pmnkxrhglak5"] + +[ext_resource type="Script" uid="uid://co3e73fsrm8c2" path="res://addons/gdUnit4/src/ui/settings/GdUnitInputCapture.gd" id="1_gki1u"] + +[node name="GdUnitInputMapper" type="Control"] +modulate = Color(0.929099, 0.929099, 0.929099, 0.936189) +top_level = true +layout_mode = 3 +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +script = ExtResource("1_gki1u") + +[node name="Label" type="Label" parent="."] +unique_name_in_owner = true +self_modulate = Color(0.599403, 0.599403, 0.599403, 0.573423) +top_level = true +layout_mode = 1 +anchors_preset = 8 +anchor_left = 0.5 +anchor_top = 0.5 +anchor_right = 0.5 +anchor_bottom = 0.5 +offset_left = -60.5 +offset_top = -19.5 +offset_right = 60.5 +offset_bottom = 19.5 +grow_horizontal = 2 +grow_vertical = 2 +theme_override_colors/font_color = Color(1, 1, 1, 1) +theme_override_font_sizes/font_size = 26 +text = "Press keys for shortcut" diff --git a/addons/gdUnit4/src/ui/settings/GdUnitSettingsDialog.gd b/addons/gdUnit4/src/ui/settings/GdUnitSettingsDialog.gd new file mode 100644 index 0000000..14a8bd5 --- /dev/null +++ b/addons/gdUnit4/src/ui/settings/GdUnitSettingsDialog.gd @@ -0,0 +1,327 @@ +@tool +extends Window + +const EAXAMPLE_URL := "https://github.com/MikeSchulze/gdUnit4-examples/archive/refs/heads/master.zip" +const GdUnitTools := preload ("res://addons/gdUnit4/src/core/GdUnitTools.gd") +const GdUnitUpdateClient = preload ("res://addons/gdUnit4/src/update/GdUnitUpdateClient.gd") + +@onready var _update_client: GdUnitUpdateClient = $GdUnitUpdateClient +@onready var _version_label: RichTextLabel = %version +@onready var _btn_install: Button = %btn_install_examples +@onready var _progress_bar: ProgressBar = %ProgressBar +@onready var _progress_text: Label = %progress_lbl +@onready var _properties_template: Control = $property_template +@onready var _properties_common: Control = % "common-content" +@onready var _properties_ui: Control = % "ui-content" +@onready var _properties_shortcuts: Control = % "shortcut-content" +@onready var _properties_report: Control = % "report-content" +@onready var _input_capture: GdUnitInputCapture = %GdUnitInputCapture +@onready var _property_error: Window = % "propertyError" +@onready var _tab_container: TabContainer = %Properties +@onready var _update_tab: Control = %Update + +var _font_size: float + + +func _ready() -> void: + set_name("GdUnitSettingsDialog") + # initialize for testing + if not Engine.is_editor_hint(): + GdUnitSettings.setup() + GdUnit4Version.init_version_label(_version_label) + _font_size = GdUnitFonts.init_fonts(_version_label) + setup_properties(_properties_common, GdUnitSettings.COMMON_SETTINGS) + setup_properties(_properties_ui, GdUnitSettings.UI_SETTINGS) + setup_properties(_properties_report, GdUnitSettings.REPORT_SETTINGS) + setup_properties(_properties_shortcuts, GdUnitSettings.SHORTCUT_SETTINGS) + check_for_update() + + +func _sort_by_key(left: GdUnitProperty, right: GdUnitProperty) -> bool: + return left.name() < right.name() + + +func setup_properties(properties_parent: Control, property_category: String) -> void: + # Do remove first potential previous added properties (could be happened when the dlg is opened at twice) + for child in properties_parent.get_children(): + properties_parent.remove_child(child) + + var category_properties := GdUnitSettings.list_settings(property_category) + # sort by key + category_properties.sort_custom(_sort_by_key) + var theme_ := Theme.new() + theme_.set_constant("h_separation", "GridContainer", 12) + var last_category := "!" + var min_size_overall := 0.0 + var labels := [] + var inputs := [] + var info_labels := [] + var grid: GridContainer = null + for p in category_properties: + var min_size_ := 0.0 + var property: GdUnitProperty = p + var current_category := property.category() + if not grid or current_category != last_category: + grid = GridContainer.new() + grid.columns = 4 + grid.theme = theme_ + + var sub_category: Control = _properties_template.get_child(3).duplicate() + var category_label: Label = sub_category.get_child(0) + category_label.text = current_category.capitalize() + sub_category.custom_minimum_size.y = _font_size + 16 + properties_parent.add_child(sub_category) + properties_parent.add_child(grid) + last_category = current_category + # property name + var label: Label = _properties_template.get_child(0).duplicate() + label.text = _to_human_readable(property.name()) + labels.append(label) + grid.add_child(label) + + # property reset btn + var reset_btn: Button = _properties_template.get_child(1).duplicate() + reset_btn.icon = _get_btn_icon("Reload") + reset_btn.disabled = property.value() == property.default() + grid.add_child(reset_btn) + + # property type specific input element + var input: Node = _create_input_element(property, reset_btn) + inputs.append(input) + grid.add_child(input) + @warning_ignore("return_value_discarded") + reset_btn.pressed.connect(_on_btn_property_reset_pressed.bind(property, input, reset_btn)) + # property help text + var info: Label = _properties_template.get_child(2).duplicate() + info.text = property.help() + info_labels.append(info) + grid.add_child(info) + if min_size_overall < min_size_: + min_size_overall = min_size_ + + for controls: Array in [labels, inputs, info_labels]: + var _size: float = controls.map(func(c: Control) -> float: return c.size.x).max() + min_size_overall += _size + for control: Control in controls: + control.custom_minimum_size.x = _size + properties_parent.custom_minimum_size.x = min_size_overall + + +func _create_input_element(property: GdUnitProperty, reset_btn: Button) -> Node: + if property.is_selectable_value(): + var options := OptionButton.new() + options.alignment = HORIZONTAL_ALIGNMENT_CENTER + for value in property.value_set(): + options.add_item(value) + options.item_selected.connect(_on_option_selected.bind(property, reset_btn)) + options.select(property.int_value()) + return options + if property.type() == TYPE_BOOL: + var check_btn := CheckButton.new() + check_btn.toggled.connect(_on_property_text_changed.bind(property, reset_btn)) + check_btn.button_pressed = property.value() + return check_btn + if property.type() in [TYPE_INT, TYPE_STRING]: + var input := LineEdit.new() + input.text_changed.connect(_on_property_text_changed.bind(property, reset_btn)) + input.set_context_menu_enabled(false) + input.set_horizontal_alignment(HORIZONTAL_ALIGNMENT_CENTER) + input.set_expand_to_text_length_enabled(true) + input.text = str(property.value()) + return input + if property.type() == TYPE_PACKED_INT32_ARRAY: + var key_input_button := Button.new() + var value:PackedInt32Array = property.value() + key_input_button.text = to_shortcut(value) + key_input_button.pressed.connect(_on_shortcut_change.bind(key_input_button, property, reset_btn)) + return key_input_button + return Control.new() + + +func to_shortcut(keys: PackedInt32Array) -> String: + var input_event := InputEventKey.new() + for key in keys: + match key: + KEY_CTRL: input_event.ctrl_pressed = true + KEY_SHIFT: input_event.shift_pressed = true + KEY_ALT: input_event.alt_pressed = true + KEY_META: input_event.meta_pressed = true + _: + input_event.keycode = key as Key + return input_event.as_text() + + +func to_keys(input_event: InputEventKey) -> PackedInt32Array: + var keys := PackedInt32Array() + if input_event.ctrl_pressed: + keys.append(KEY_CTRL) + if input_event.shift_pressed: + keys.append(KEY_SHIFT) + if input_event.alt_pressed: + keys.append(KEY_ALT) + if input_event.meta_pressed: + keys.append(KEY_META) + keys.append(input_event.keycode) + return keys + + +func _to_human_readable(value: String) -> String: + return value.split("/")[-1].capitalize() + + +func _get_btn_icon(p_name: String) -> Texture2D: + if not Engine.is_editor_hint(): + var placeholder := PlaceholderTexture2D.new() + placeholder.size = Vector2(8, 8) + return placeholder + return GdUnitUiTools.get_icon(p_name) + + +func _install_examples() -> void: + _init_progress(5) + update_progress("Downloading examples") + await get_tree().process_frame + var tmp_path := GdUnitFileAccess.create_temp_dir("download") + var zip_file := tmp_path + "/examples.zip" + var response: GdUnitUpdateClient.HttpResponse = await _update_client.request_zip_package(EAXAMPLE_URL, zip_file) + if response.status() != 200: + push_warning("Examples cannot be retrieved from GitHub! \n Error code: %d : %s" % [response.status(), response.response()]) + update_progress("Install examples failed! Try it later again.") + await get_tree().create_timer(3).timeout + stop_progress() + return + # extract zip to tmp + update_progress("Install examples into project") + var result := GdUnitFileAccess.extract_zip(zip_file, "res://gdUnit4-examples/") + if result.is_error(): + update_progress("Install examples failed! %s" % result.error_message()) + await get_tree().create_timer(3).timeout + stop_progress() + return + update_progress("Refresh project") + await rescan() + await reimport("res://gdUnit4-examples/") + + update_progress("Examples successfully installed") + await get_tree().create_timer(3).timeout + stop_progress() + + +func rescan() -> void: + await get_tree().process_frame + var fs := EditorInterface.get_resource_filesystem() + fs.scan_sources() + while fs.is_scanning(): + await get_tree().create_timer(1).timeout + + +func reimport(path: String) -> void: + await get_tree().process_frame + var files := DirAccess.get_files_at(path) + EditorInterface.get_resource_filesystem().reimport_files(files) + for directory in DirAccess.get_directories_at(path): + reimport(directory) + + +func check_for_update() -> void: + if not GdUnitSettings.is_update_notification_enabled(): + return + var response :GdUnitUpdateClient.HttpResponse = await _update_client.request_latest_version() + if response.status() != 200: + printerr("Latest version information cannot be retrieved from GitHub!") + printerr("Error: %s" % response.response()) + return + var latest_version := _update_client.extract_latest_version(response) + if latest_version.is_greater(GdUnit4Version.current()): + var tab_index := _tab_container.get_tab_idx_from_control(_update_tab) + _tab_container.set_tab_button_icon(tab_index, GdUnitUiTools.get_icon("Notification", Color.YELLOW)) + _tab_container.set_tab_tooltip(tab_index, "An new update is available.") + + +func _on_btn_report_bug_pressed() -> void: + @warning_ignore("return_value_discarded") + OS.shell_open("https://github.com/MikeSchulze/gdUnit4/issues/new?assignees=MikeSchulze&labels=bug&projects=projects%2F5&template=bug_report.yml&title=GD-XXX%3A+Describe+the+issue+briefly") + + +func _on_btn_request_feature_pressed() -> void: + @warning_ignore("return_value_discarded") + OS.shell_open("https://github.com/MikeSchulze/gdUnit4/issues/new?assignees=MikeSchulze&labels=enhancement&projects=&template=feature_request.md&title=") + + +func _on_btn_install_examples_pressed() -> void: + _btn_install.disabled = true + await _install_examples() + _btn_install.disabled = false + + +func _on_btn_close_pressed() -> void: + hide() + + +func _on_btn_property_reset_pressed(property: GdUnitProperty, input: Node, reset_btn: Button) -> void: + if input is CheckButton: + var is_default_pressed: bool = property.default() + (input as CheckButton).button_pressed = is_default_pressed + elif input is LineEdit: + (input as LineEdit).text = str(property.default()) + # we have to update manually for text input fields because of no change event is emited + _on_property_text_changed(property.default(), property, reset_btn) + elif input is OptionButton: + (input as OptionButton).select(0) + _on_option_selected(0, property, reset_btn) + elif input is Button: + var value: PackedInt32Array = property.default() + (input as Button).text = to_shortcut(value) + _on_property_text_changed(value, property, reset_btn) + + +func _on_property_text_changed(new_value: Variant, property: GdUnitProperty, reset_btn: Button) -> void: + property.set_value(new_value) + reset_btn.disabled = property.value() == property.default() + var error: Variant = GdUnitSettings.update_property(property) + if error: + var label: Label = _property_error.get_child(0) as Label + label.set_text(str(error)) + var control := gui_get_focus_owner() + _property_error.show() + if control != null: + _property_error.position = control.global_position + Vector2(self.position) + Vector2(40, 40) + + +func _on_option_selected(index: int, property: GdUnitProperty, reset_btn: Button) -> void: + property.set_value(index) + reset_btn.disabled = property.value() == property.default() + GdUnitSettings.update_property(property) + + +func _on_shortcut_change(input_button: Button, property: GdUnitProperty, reset_btn: Button) -> void: + _input_capture.set_custom_minimum_size(_properties_shortcuts.get_size()) + _input_capture.visible = true + _input_capture.show() + _properties_shortcuts.visible = false + set_process_input(false) + _input_capture.reset() + var input_event: InputEventKey = await _input_capture.input_completed + input_button.text = input_event.as_text() + _on_property_text_changed(to_keys(input_event), property, reset_btn) + _properties_shortcuts.visible = true + set_process_input(true) + + +func _init_progress(max_value: int) -> void: + _progress_bar.visible = true + _progress_bar.max_value = max_value + _progress_bar.value = 0 + + +func _progress() -> void: + _progress_bar.value += 1 + + +func stop_progress() -> void: + _progress_bar.visible = false + + +func update_progress(message: String) -> void: + _progress_text.text = message + _progress_bar.value += 1 diff --git a/addons/gdUnit4/src/ui/settings/GdUnitSettingsDialog.gd.uid b/addons/gdUnit4/src/ui/settings/GdUnitSettingsDialog.gd.uid new file mode 100644 index 0000000..06748b0 --- /dev/null +++ b/addons/gdUnit4/src/ui/settings/GdUnitSettingsDialog.gd.uid @@ -0,0 +1 @@ +uid://vkgpi588vew3 diff --git a/addons/gdUnit4/src/ui/settings/GdUnitSettingsDialog.tscn b/addons/gdUnit4/src/ui/settings/GdUnitSettingsDialog.tscn new file mode 100644 index 0000000..610f098 --- /dev/null +++ b/addons/gdUnit4/src/ui/settings/GdUnitSettingsDialog.tscn @@ -0,0 +1,1569 @@ +[gd_scene load_steps=31 format=4 uid="uid://iq3dggaj4g0b"] + +[ext_resource type="Script" uid="uid://vkgpi588vew3" path="res://addons/gdUnit4/src/ui/settings/GdUnitSettingsDialog.gd" id="2"] +[ext_resource type="Texture2D" uid="uid://d2ukt7dja0uud" 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") 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6kQpkMqTvpYYOy/CJyShpDFrLyGwXm0OOO9dA+mvCTWGPxL2V9lVe0UKo3GkcNa+8LP4dEWWe0wUsKkmXIk2WhoP/w9g86JPBkl+5vC4VHG9P7d58+fHXegRL3An17yoBStKwiRiuPoNxaJd+De7L8QgZrQ5CJsTQqmWw4T6eI40cylofxAiwwIUESmixEdtgG3PHnqAeNEgKno70wwDMNDS2rDbqB5Hofsx+BAPoAKJuIC/p+kF8Sj8tILz4TmpoTRSciGDFM0z1ITQN2TKDqL9jDixyRRwnR4KXwBUJ3JrnOwheU4gs1r8U4n1ycUsEnnApHj0JlA9P4ejkPwAKaIAATaCFbwfcMcsDBI2gudSOBL0bgZtjyOn5Qvud31GzVm3Nd0goesmqRlTUIBS7qaDQtwwGDHw4V/xw2GPolKsMQq8VXPVJdSM375HBIueCoXW1NZn+Jo05Lr2jwimG0CdiIIAYJA4vd5MCqGrS7MFvrVQrpSYNxucguPfYhnoFtboWwbT8nE0RwfylP52cGNjhCiXhkkIC5CvaMruVT6AyKL33u+tQvBaLV6iIQomlbUmth3Ft4NYoQCFTZvACTr8Lu/AUqQk1Y3Ky1xjW4tMboa3WarHcRpjyFZnoeiyZxX/SC5o7EcCVLbsCDcL6oIRAhdUQREEFoSP8AwFNFI6gsJwI/hUyQQ0hvv7HUudTBMNPEi6FOgRnmIBgDpMQdGERcpGa2zvJYOuOj7BSF7rY36A4gdPxthCnQuB6TNg4iZ8QcT50+ieSAXMePHn24tWnL2/eiSZJIY4ct5aNpw+TDmcK/RDihf9wbtEHhVhobe/GMwpBW9gKgV8wASM/YBDWH13slwentf5ltEUwPKuBJuiH1zzdKD6nW0ZDRwvousARPK0+wO+PetwmrNBYXyJoqAmmZDft8K6911sHQ699FzqWa/CRf+8iaND3Scj6p56NVFusqye70L09h1lWvfJbrx8e4k58OmpD3qt9AlUH+znSQyHrr3rcvO3taqrt/cqqR8j3rqfcWI0ttdrRJ1uyf2uuEwJTIkddKgjhScfU086wzaedaTu2f86555l3gV1faJHF9nqpZc6w3GY2t8X9PUjQCdZxjneuE530FKcOQijD5RExXpI4gKfJkGWaInNUqQsghC2QaYccuUdAgWKlkqrUqFGr3vXH0KhJi9YgrP86FShSolS5ClWq7VWrToPr3byEw5rc5o6ltbpfu06P6F7Gk8tuWo8X9Ooz4JTXQ8ITEt6QGAsBAqaoUfRFhgAB4wQGdEfE8fOEAEG2BgU40h+EOB5DnLxz543AgFURGCAx5Zy50CP2ygoFkzY3l1+4sQvw5WqqvAEBrfHTV2PRe29iX1gmfOe48RcI8cSJhYS1Qu/2KAIAOiOBNroh5kMP/hbOsMr9pwhHRC4SUReN5+55vB19G6kLmGVZGX7h7+m/zRJrgk1tWiGxFOrHlkYGjcqqQ/LIryC2ruu+niutnMqqJwEisWZmLktRktmba9OEncO5K515On15MyP5ErsuZDxTmc1S1gq2tGEXozglLHlpylCjZcWuHeWokzVW1+t+Pa80hMObTioHNwQ4QYidOKROGqQjQ+VUoXGa0A7Xhh4NV5yOS+EvPp0vpiIYdyGc4M4jjz31jD3hS3c+++oXp7NvZ3XofOMWxoWXOxBFla6MMcebX/9UhStWyfpexVpsDESDnlZ2C1rW6tb3MHZvbkvb+3h7+2rf7Th2RzvRX3umq4PSGcPBnq7hj3So0Y1xdowDe2zjnkszNeGJTXK+Y09mClMx8CxhW2AZjCO8hW9SWAMTd/HsS7qymcfHW3eee4C43UC3ntI4VviD43h7Y0+QWSUczNdIljyFsJBXnsrUffS3sabhEvr1Ge6A3HUlP1zuOiURxyx0t9xet81Ya55Mo075q0W2ofthVuy3s7t+zgI7TjFmON92H0H22TY3i3e7yxzzLBpfrSWdMmY/l3TVv7fVCX+urF1+63T1yptlop/Wr2221Uw70H3IHnJ1bTvRmXUSYA4jt/mI2Vh73yHfdNiPVjazl/l2RVMOYu2zYn7tlDMnazH7qLS/22gzxhnnXfKoLRB264Y3rez69a/duPVy8lvYb+fDK+wDM2t/V8Ywzmf5rrsdNWnKL7H3jV768jtW9IJriPvDc9sbZbGXgwvH3jpcvVxY5bvtLca53dn9lRQ1+3if8H3Ebg+NwTnfL3uh/XZGZrsWub9DxxMwtDJIHBEmC3o6JyRUEG1w5D8uzXWX5olL86nfiuVUpAxpYwgKaWMGLLgwV1qOoACqm48WFijcIsxyFBdIZWljGb4whYVUVshKt5okrLGQNbK+3EAJpGFjiHITNZDK5muPoqMTcwgoGDgEJBRmLFDRMbFxAQIiEjIQa7bsOXLmyp0nb763/zMOUkukHCmoBIUUbIIFF0k6KJECqNCgRboeJky4kQukCQ9+wk+YCQtpIkSECAmSKLVNpPdWAAXKRIk0qmKjjmogTTRwoce3U/Jxf1OPlyea+SSJZIJYhwxTL383QnXQHvu85R2Hdu3XOumUc6657s7RMPf14akeexIM34/8DJE3BBGnCZ/XTq0OowoyZKRt5SCmgtAmOEbbKPbGcyYw9QE5UISCcMQc4YQjnAoUyBGuFIRbBIpVEF5SSHhzKylE3qpYJqBDakdIvZyQJvNmHP/Av1SYZnrpYPzcmKgTQ76VTfdV0f9axBecle0umG3i51qqcbSVUsvkqik5d83BJwqyIrS0O7Ile4N4SadQqOHurKd6jLqZJMvKVnxvgEYS9+qMNOfzgpbhk6nhx5dlMGmRpp7MPjsNQWyvT3qR2k3Mk0nJ5NqUgYKY/IW8DBTmJCJxqZSEVEmN1JpxY+jN323opQz5J5nyX7LELtmijeSsFyC5kiZ5I+ntwsMp2k05cx+FCSpVyXhqfKs0SKyj6INyV/5iOQvwbyO/ujXUgKiW6Um9uphEtwnurAwLNlxfrp5WGQJqc5pDlIVo0cxheebNElu+6RXYY+QqU3WXpfrKRk2VndpU9mpzKRyDpFnJ1y0aNWrUqFGjRo3eVURERERVVVXVOeecY29O3nvvfX5lxhhjjMkha6211lrFpZRSSinTNE3TNE3LsizLsizbtm3btm0XFCZMmDBhwoQJs8giiyyyyCKLLBIuXLhw4cKFC7fYYosttthiim/LmvjuupZjefWfdPWaf2BC4uVNnIzppnymULDOkuOcc7zzTnTVKa451WNneuIs71zq91eZt0FSWU4WpNNwjDfB9UnOJzk+xzc8Fo+XYunlZowVBN1bJ3nvfJ8nhL7wZ84oQ4lZUTolMyPdeNw0cJL8+SLnA0Fh+rikmvGJ3xJ/pjOuaDvGLjyE/Iwvaol5MCSHlZRg298mOewqBwrdVwh3M3iy5/W+8Kad3HKa20GSGGiCIYnJheSdmLQwVYKDZySHCh27rRipxBviQhW/ZMmaJyqVfYFyLJgcD7ZHspU0aBW/r6qaGhQOnLioWLgfwp568z1U3Zoewk20vxP7xyrpOS5Hg+lEfLkbAvfC4A7v90EeON3DYLhrGAKPjPjUWJ4FywvCc74ivJbXael6ma7wO0/iPoep+X2/Ofww9WlJGMxkSKbJdJkhM2WWzJY5MleGZUTmyQJZKItksYzKUlkmy2WFrJTVsk7WywbZKJtks2yR+bJEVskaWeuv7B1SmmDrgBUI9obP4kyG2N0aMqBlqwtgPv8o7MVfbpA5Mz0jMyM9PWPm6wAQaLmE/zuSvmK4AFtvEu/+gLvfsb9BU+7rZqOFTAcYrRBodhkkLKeoc9xaAtlO/dQGapnFHid9lj9OP47yBJ+mU1AIP5bjOL7TcBrPjNevSnHiCxFBRBFxRDrxpGMZ2q0jYk0DdiinZVDF9DLwpF46rUqO7Ti9K5oxH1NKrCBiEf6hVFou4BnIAj67YbvVRtLqvueK/tXzE/9I2SKbsykbWX9ln6kUxfyI3IjEkXykGukSWf3Pqi9i33dXXpIGABjjJJifB9ZD0jqOtPpmVdtO/rern6xzXW+aJApapRIYomRNm8tk5YwZzYKfvjVIZVOJlJP0ySJTKhOkJGKaNxhtoZ0QgSphZVJMKzrICurtyxqsEiIE8qHJkhERYxEmEmgwLq9UHRRUoQqhd+dyNVzKOc2Cebn5IDJWND7SUTshOwhJb9QJUphp/SSMRV3EcwuqDeaentBYECRwJXdfqoGuAxNDKGkIaGxpUIoct2eUjBcOSHe1yva5BEgGcfJPUKUuR3ka9auu37UAwU5i0C7bNlRqzSLU1ZhpZHbLlGd0j1NEdZAjUxhFPSNSX1PThKxS6cCQCIsZzpOMqJlHBfJapYZmpNUpID8nPdVnItMHs9CRg1L6ZDWCAiPoYHgIwYaxVkot807/leUBArQCkjPtEfRFktNQ5caGS1DX67oaJihpKCGGHUqFR/KbHbIDDKEOY8Qo+rUOMjkiyaXS5PJ1pE1rcklTc0BrRjq1Zp7r0jSaXQXjrcKR3hxXJ+v1kffhLz/PXcehyGzxx3tGf+gxDzxB8AYw+kai7zAheJqS4F7xDbQLcRyJwD1hhPdsFXKXO+SAcCCLbvhgdHsgV7iDEfZK+0DYzUjEDcKc4QJzUURckgjZtBFxjcKIq2DYpqdWmTYTdf+B4bArN7O4hwwUCvvLxK3SvO0lRTdludiVCienc1xiaiITmenymokBf/N9KCiVqpyy1ipSYBQUoi61yNmMJAZSvU8BwKcxAaUCmYhVsQGVobKSlDJP4HSsMipbHQhkVUNiP+pCjFfbPgYeF654RAoAgUKxC3ljEcqH3ya4L5Ty3bZ3CVhedk2luna4/tWNNlmMlDddZgD0+C6iomv+K0gVqIlpPJn6mvoHo/z+8dYYbJbOiQFAipSXetxYsfLC4f97W5RXGQq97MlJ6k+N/38Btf/rHLdfb0EhLCdgKPSUl3koDz4CEE21ayLLeEXL1/913gnzDXuOpa5cRbcMCd1tCj9wombMMk+W7wWZwKRbYB3aJX+viUNnAkTNupq4jRvH8fFHt48+kO0gtifXI9CI25aupSu7X5dKgOkX0d843iWwDIoVTwS10R/XguJ1cQIi3NhJkrhIA4o2URdZk10uJCgfNjQ1+V9QQV8ZAxTWrViSuf7qza6M+Yr+fSlP1y2kbrkbZx/786qb4ysf/33TTRdDWhDWakaLgwd+TvZKfEMNwKFcqv03ttHks6QaV0KqoNHQn76e/AtVybJ/rXDra6rvbXfBfdh7S03/zSi2foDEDiscODvL3Tkn03Hl+qDG7AIc3PJgJQdJ9u13hzcMzq2pj9vaZhyur6knj0LU1nuWYSjfStMuKemu1BEwQFvOMCqHeyWp+AGXezerED9BJaxxIiZd9as4b6Vpui/4/96zx2RH+PE/qihi8/eNKyHNCP+Eb5IxbN7a6zgHKxyZC5sNaxtWk7sjNn3nA0CrUXVtJ3i+dXHjF4Ig5wJehdS4JZS45WnHBr82f8f/PicAZEBCjooxgGbNPV+MngJKLaUgqkxJU0zrQoeNzBWmhfHs2kWiUoBWt6FUz3CtQFoaF+0sqgx/48JCRiiwgWbA8Tv8zS2rNHBMnC+GXbC8MUVi2/RZFT4iXfnWcjGo0RR0mXL+aMywAnVZ5lTD/gQIrtgQQYjfX5r+/Bti3jdneIkUZ1cLDMaQH99USI8B5ICLfdECOK+C+yWOri80P3WVtX04xwfWFnXByUyUs6+v2ITbW1xhsBMs3EgPUel0j5AWlPIvtgv9DxvBCL1mtiSrM/EpgupJfzgrxsp0sheZzUkBCHLQwoB5CzaXEJw7YGW9mAUWA13DUr1BUptoBKHDJ/7fwGXEQIeVe/ST9nsus8OJ3MKjRCNj9jfQgT8fXY2QwdfAPiP5Wv/uLURyv4J+0oBGMmWSs5TunIKopuU0OVtB+buDyl5lfJMpzpuUbLTfWIxHMhQjNQGb4vmtY7bdENqWGU/JBx4fVMGbqiICfXtAGaiFrGtZ9LyyuPgMAhzKq7I98SdtXQwRbijpGX8MDFioSEbDi/JG7QSl9367iqH8rt61spRx6SmQQqy7fT6nz0V3oBighhtLjpcxCrmwGIFpyI1fGHoc1ChJMREREP+Py7fGJUfEVRZx/C553tIQ2tfaFgTA+m4om2u/wOkJ7cskbm87mN+PLNjEtaTz8cHU8QaFldOgaJq/Yy0Vl2UoB8L9fklUHLauRk+HgmmrkgVL0IgJOX2UHT63bWSc4Q3EFtiXWYa5u6kmXvYoNq8t7vgMFPPYzzLzLrwInr2b7XYm77sbC85neGFJd6w4MchNPtzOPM3AuWyvt39i7NjBoUcp1BfAv4SyzcDV3zt33A2nAV0vTe4RqvY/QQslqHLoVd4/RLyowPm4eMwd40o25n3BYymltCj1C6joKy9R/BYe9cHnStNsxNeSRXOhPW25wgEd0fYShbC1H4eS6fbOQ98r4u7FkM6nKirv+dvaFe7gYJ8NuLHjrJKZ60LxSSXnwLzv9f9Qd4XjP1jKIxw+cJI9gE/HCq6NqlJvhvTXTU8SpmGhnJ7Mfxs90Vlem1NVaRWlyKGCAxAuOGGmuuJbikYHQw4PibFEdhRkxGtS/F/Po3wpB6Krw4s00tG+QwON79xu6FknWb9WBYZOB6P00y6KbWzD504Dyg3dG2y6RijiV0Vq61e4HG2TyfGagZGUaS2j0L2QmFGV1bxTys/Iy5yqmTSeNV0/i5P7Kk68WC9jpwiuHbjJnRZUt8ZN86ZQbnT8bpSYKrl4mFB2kX5pIeF+NJ3+Ef93pb2l4u8gmosLBwjZt8awnOApe1wynKZriWUq6Rf3HUE+lZX5Pw5OaCuA9RP5DU5P7P9e1QebYiwi2KLnW+k3vog/I++iOqm4NYVtBwHI024stlVy4g80caB7gkjN2QMDuHl4w2g3qjzdI3/yryMjPjKZAWFJUT04f4RfnuJqJdbh4ebdvfWcqIDdasbmQmvOADKorfSMVFsSt5XYi1r9ekOEI8KiNbh4yyme8Qws5tmswl2nh0hvLHu/RaLfHch6xa0lXtglMjtBHiSHoc8/ywoW4n9tZ7bmOr1xZvKMEy3rMznl61lsBmrNdmlhg4Q/oF1MLiS28a+xicJ/vn3QnKK8+Pxa1V06/RRzIyDIqjAFd+23+6AcmcWdW6diT4GtpebjipquGfaf/UTmyGcImICToPnozxGirKt4Pg3S9VEavVX2sX0ntLroGLcnyBS8t5Nf69vBjstprvK7HP03NsNZ6pzGdkKS13aTJLmUodnUZN3OJM37Xqdv7jbPGzsfBLxJa3owiOgfLdVnM07DuvgYXPyvEraWrm/oqKF9tmUzAPcHdXKqAh1o4n6ZoxjP3Y4zGqLJkOEfyfGCSLwifszgpv8Hmo6b69Ohqae9nQBvOKVg+9BiRUbxUHYPz0L2BDU0HCqWDwuSIUpN3bBtNfFJGliB2YezHBamC0/q4zfIoAVdLZ41s2uvm+xvcLATyFM1gzMfRWnQxBpLmNVIU5GojOzNYgQhutrMDzcWhDDVWCa8EWAN9Xo0w7UBJqF3u8dkG72e5TYtCXGQvMXvGGS8QPKP5VGfa7RO4O+Ga0pxw5W5rGQAeG0UXDPRz0OG54q7xThx+PxExV35dLoG1uNlWNUFXcjzUj99HpqbBJc0ANAndGpmdXzIu4oo8C3XWBO8H1/2nAGTYd4LojqB9n266Lpi7FywfQ23vena8EgqOmJQyYzrnabJJ1Xf7sPNhPN3L5L7Chhfa3Wl6R0mxU1ECR5u+4McaGTvbx5uNqggq/TGYMwrurik3BJgrKFvkGCpn4buwVLnlO898IHo4gaR9hMr0fsnnAB/X5I1uX794ALDC+VFl/Aa7zv1ZyK97W35AcUGg8yyw9ZPZ3lblnhuSSHNiQ/KEPlInDVcNXUY8Rr7dJBSW1Ikr2BFuko+Ic18KA80tNnc7QMoAEGKykxguv7pdlHcsSNXZjk8NsXxt2Wj+yqftRUxLW3z0vYb0wbjvO4/83Rq3cbuqQuZi7Dol4udM1qd4MY5BRyGZ3lKpseAJkTYknrs1s2bHSbrDaxWliQoTR9WgIpUynL5R/cRGByEvOFbr2QWcwhkKX+Ubpzjum9NW2pyYpMl2AdrvYs78/yEg34vxM0IKcCdnp3hCWXXP7GGKg3wSnHe1DRXd/yqEgzoDW8hffkdiKE9YKnTreT2cug/B10CSoIUvhT1rObOD3N4b7B54hI7kfAvk3e/qnJ12a+Z7RlQRNVlnaHs5RPq42JdJTNs1mSBN5sc3lUl1zV6G2D/cutewnpTBV7+RP9yGZP4txt8XX/ijatAE1N42pD1KBMUV+8E2578tjL7rh4L3kzp39ngrsb/l9NyLwiYJKmKwgQL6fmKCRfa7/VTN5ZM0VEAsJgXcg/95prF4sEjXzPTRJCT9QlJaP7Iaz9O8k1mVysMTkJTTv5jRh5vMESMlGruKYhtUG4GR8HuFjyOqFcIyWS4YVv7ruieGDdXDHjWlJmBNCq0oV57urNAZJx5SgeLRNexIwLNNrsTLbyPozPbzpVSmt7eOyWpL0nvGjNaa1G7wkz9+edwf3PckfuszE4LL66UrPQzJa8FYx9Osr1MH34NIH6kWj14YyreNYo87y4F6Pmt1LFxPyYepI3YcZ+eDprpkepNh0dkiMiwYP3F/Zo2cbHACIDn5dvXz9q7LrL1pbzLrmwQvoraXN0nnuHRwYupozC8YWo4+qRK3m5Gpp8ZXWXTJYVL1S7KY2zraDvsnef6cLNB6/aY8IY6MQiRLSAlwFlL1L0uedqZRrs/Ug43fTYcv0UnFxgVdk6tNvksK/vif5LOyWQUrlg9GemJFSCnQNu2ZSrTe3A8w0nkgjm5RVflz2vmcuh8U04KshY7pFmICxm/2f/zwsDo+CPQm9RP+7Iyx4tcjLr+qKB4gmWOjag6nY/rR+lzdagL0x/qR1Q48fkpfQaVNAkuYVuA7Bz26uqRf8jigjk1ySH/WakralKEQi64mLi45KQlxpHT4HFCjLI9VwXawL3eH7CzOhCDnT/Qr31TacNJql4RkdeRNjW6XwQO5JL3R2lagv0xi8quoWYrOvqRVrcnIuAWF+x2so9QbgWdTb2LecXY38LFqcleUiD61MF+W6HogivNdPVifHJZVg7HsUvzCRRCxs0kTsDg5jejldgwgkK0wCGypsKU9Ieb02WKqNZkV1UaU05aJYP4ky/NbpNCmY6dFXgfN7gMnZ52LHzYw5OQ5BQww/mF/cHpOj1DsuxsyCJWtcbxY4wj18nKSYHcrVEP823D0dV9b1qy6AyfIY5NT0/ay/hqVcJfET2lEDchnUxZERLCeemzA30c6V6qesTG4o3ePtXggMJn8BqMnwfNMBcmL43GA4ttCPCsEogbqeRDPMvDLJTO5rIkN0nUyTZtawxN04av7kHVN7P3ENsuyZjAcP3fo7AvhyS8A+L3YQlZbqybkbZZlcTfBFM4CaoAQvrC5bSvJxyC7y+NaL6JuacdWuKKw0iucvwHmVbPbe33tD9AwiQQT1MZNu84rizWPsEQtQBjbL0d+zz4q2TJyEBVSKFF58dhcguCnEqgIrfmqoRsKW3kYa6xqo3XwjPc30vMptNFzcHl5NiM818rtZBiXkBve8RTkFuIv8LgJCYHIY4Z8K258YzjPMT1Wz1W8NQwLP4SiLkPt+HEuuiPo319EscPTGZnAwxN01zjYarEN7G3xA4vjbCHjaY0zdUXhRv+hLU5hhCMw81hY4t1LL1BRKYqztgqVU7ibMHVkhsb0wDGMPaW2nwXSmauac0jhmTpT2E4efESZT/3SMddtN8EO7LRdhBZHN26NVF4m4b+HJmuoncQWg6bJWITjC6ppM/2ieB1/QcSnMBLmOi1mnTdNi5vXYz0NJoISm9CPhSrW4zudKii8meXXf9FWW9GI0bGDoi0iohHjwyOJmCZxqTyL3kweZ7l0F5cvMk4gpUoK1IM1vzNQAfzoVfB9Ay9Pt+Up3q7Wdrlnedrk5sMo78dVYpxufFydWmZalHF0BuQgFXRO20z56ywGx5Au8SpijdmdAKd7U1eAVnL+LFxExXY/SbYCfKER9k6ghDoFEeehZhuZ25BoKSZYVBxZwBAqAccl3D1KWvEPWgVvfoivHKD4r/RV3IOkWfeuD1O42YrD4DcbqU/WmoMrsY4637gc042Tigg6PFZT2DMiNZoHOfGLd7/lKANrMgahicvptUV9Yf4+B4l1GlEv72GME5qb0T80nV3gNMEeCLUKHNi6VBr7bOPQicgYyPKtIsk00Gv7XS2A8/zcpcTykjVDb+Vh4p4Iy9IszS7AnwhxaLyddbuWofWrojT73flOnckEqa8DWkICG61cQsfP2gtIU9zMg12iqzZfoG1Xx+LuokyziNtGjtB06g8oyF8Clr/29v9f8x/boE7if7d77hbkf7/p/y9zH/vSGLT5KBkiv3YNLNIyAr82xYWqg5Jh3mC0SuAYUH8lA8g9QFe6Spf6k+8k5oefGgVSsiYNvzLzkoU+n5vwlq1bNG+DPR+MbfqFfygpQQQLIgQc/ATuVfkxeupVb2ILXjTTUtocJgDeM3tOFbXt5mR2bVKeZAxerVm4Z+4ggDJfx7AdTg7brXpqvGQtkRg14QIZF8g78bjBmM4JHtn7Ff6WLn7eS+cwn9rIzxT2anWBwjrIknTYHvnYvIujd/spaD4/Siv5NpASiqXCE/bqiNf1oe3sR9u9rZjDJvH9y1gfx/2wqP87RNfUjy4O71B9T2rIo8NTrCUM8SNuWruIgabz7B1hS+nyAWEXNjezq3U1pJgDFv/zLQIojbcjGcxtIKgwGOQLxfq/URUePUt/PM1NQS/qmBMRPgoQuXRtPHdM+G+Bx1G3ltkwe8WTaX7R2YdBSPAtkzLX4sVLDO6q0+wGx6S0KP+YU/InnmOrfkPgsYpgi5Vy2hM0oYsabJZczouRu3P3vT0Q4bPyj8N6dey77RZqmo5QpnXBLxgdSRO/ISNwa47/NCwf4jY2s0R/W55ZeG9y2Bs8zjqj5BBn7Kw0XbsHU+8QjFql5hV2VrvWQo80D6eNoZ6sajuok321CpTHdQBsRbsTiufy9VQcb/C0HddCGeH9bGoIRLThSPaaFZLh806bmMW52kLZVnwssx0nw95ppsbb7aIZSkZgL4t1QaCVlsgoNMFAjabP+jQEmqZrFoCvovJ6ALKzsOVfiduCljIQuRQr/9bx3oszSlhWQo5ukKoOhBoLz+NLDtTXn6rDPkB8KUkWlpDSmEoxldFO1NRlSgU5avEguc67Wu+4LVO+xwgvikgp04PQUrNjPV6h9OmwGYSiJlYTAaRkGGrFNUB8O/O+8x7a0UQFnIjQXeopjbCIPLXehBmnkcwSBp7VMnqHpWk0UCYB3RB9+drntsLuIlm1Z+uNkVi/PIQtLymUtFTK9EZIyp2jaK2qSdK+U/qyJJqOsixlK6ZjLVaSTGUE+kaCf2hgv+YTbHQaPb7Z3EcBh0MMEF3yiTqtrp1cy1i+Bgs1KmWpYxeU9tE/D6Hl9tlD9pnL3fNtcWhWltLiLZQV2qD6TE0bzXWrgtgqr7z6SUetQ6MNefjmTvoBpUzarevbFb+OWO82DlpZTuhshbdubpp/vaNa6WR4icY62lbISfYoOI06m3imgIuaWrvhHpTUEYPcxsW9szKOTSz3hCiVPGpxNisxDe/ij9px0i+pE/fy+0HkdFqC+AkXMe7VhSgKnRxjsqJSYpikv5XWybjmk2c1Sd+ewwvWnf9/RvsDY4tUnvR6ESQMnLY84XU607Au2nvlgT4IkLMpJCSLr3KLDSBR6KnDeXGMGmlwJfUTtcUYaUmJt7EYFJsEEftqW6qsYG9syzIj4jPi4EpObw5FJIXSBDpE9h9hDrxUp8FM0qelM7yv8Vkx9SZQX6gFWYixttKIIGUnWzQhCP1fve19s63EP924oT25HvhFpnDvGx+ss+7vDbVnVBBPArEYZEtFpaMPtvb6FRMREQqaiaX2RTBmtl0uZVNtDHZNMjH1QfqOmutguZvnm0+5ASVGntwC7ugjbJcwFQVp5llRqHogVuqlNpVJRyWcBaFfmzv0JppSqXQJRgqcue4pxY7BDxm/SASaMLbIHArWyXRYV5eRsUahDVlbuAZ6iTaqkXLvyY6KsPeUHXSI01I5N2V7eGlo05ktyQ09+O0AL5ibrrb4JHSvxKKxcDTCUtUzPZySIgLR8iMGa6zq1o71r917bwZv8w8P/al2a450aRF9igqq6TWQHtMuq2zBCja88c+FBUg0mlUT09P+cR/L/semnyrUqYxCsj/+ebx27KISib0x3m7d7mOFUTsDib+cjypc2NyKHB2d8f0liGzol1rMVezVlujjvrOmnjRq/dwy6Wf85RbNRqH1201F9ohO4sGRfhQ87SEcltbcZoZD8rEJ7/3bY88T10PS+QQsLimUqHMIbDX+MJYOqXYUppZKpbzS+/+9Xe6sNxWQRgtaqKyfdLa2BxJKPF82SUCFOBU3mq0B5vq1rwXjksIA33prnD+1nwlEIHAR5JIxtwCloXyZbDEnJbfPWV6o6NeK+vIsoBpMcRvl/kCd2UsjLI0l5jvp+BNSVwYkzyzLGP24IKW+NaYGznuzfyivdTsCBQwHre66sY1M7OuZ9WKuviYrnt047hU2sEutBWYROuw2zDTZ+ek6L89jbK3y25w8B5Zc+9Ak6FJCiZObbtvdEY7Q63xVWv9Qlgo7I/G42gDVVNCKe8Sl7raCvZEq/3dVsaT+38UhKK5dmTswmYPUdU1c9nsJu+oS520gL3RpK8b5L7/IDc37iu0VMSWXPCQgKfEtn1yCYjbw2VOYuzTv3u1cdytf7DVutSidaynUfbDz29cFk+gyrcoFSoTj/xelgAl8HXimDUABatxMmwt5AeaCKdkvr8mKt0tnZUmAdeEEMlsQluNP0z4VlJskXwTq1l+SRnKhqJvBvq8eCBPJbRhW3+cXgBpXtUFD1VSBZ1P9tzJ9tjmF11lSH0SiUuM4gXzUEK4pzUZB/1SaoBHbcsoewrUL35bu2ev+G0mJa3FG5jKj3SvLFldrQmkAHVCK/p8deOnT2xX4j3sGzLCSpnv7qnR/5mkFeapttP1KifABGqid1zx8UzOGgU3ItAJoO8+qWfpPCarwki9AZv5Q4i9WeRjQeWPBJgJ72r/q6gKJUvXBAyY+XukxqeIQpNeEjJyS5zPcPVisbVwxf9JNg3IJT02kqWQ12mTqAI9gob/cI9R2E8qDM4y5++8YjjjEoX5G5r+BlPGyTPkY1Dr7EXWQZb87xuvjzjTMVeZc4/9dgxYhLESjZ7FaqnEQEWWzDs9eOzKO5lFJr0kSlblmK6hHHyrjJlQVVu7i7fsAIP0DsijGuqC/Ea3aJ880ce1Y5fcHiz0mvM9hCTmsq9gYuSmZ2G8o22woaFtqD3hHPmAGkK6mtXS3tWqjtkLXSmOEyasc8K+jhuJNhee4CLYjE7jkAQwtdNnJ2uSBPgQDO73w/ip2W7TTF9bYrGVgy9wtAUNwuY6jQO1U7oQml+57sy70jfyyVMLWmZGSeejHAZSVKxFWFJmsyCLbJhmwBpisbi1Uyl464CHB6x+s4DKmfQ8vnnKeLLdbZUwqCJJIF+R44sTln55EePuS06NDNG28Uyne6g2n0XKLL/4+s11ZZ61E7ftvsYxoQqwkphltc5KxKwzZ9oTDTP8urme78pgi/8JxpTceoP+WPGYwlzb2tfY0NwPhMTD7dJjJitygzlXPuaCvu5kBOyVelxq72jTrJnLulQe4uYL5TGnyAaDEF9MSCDIOLdOFqUqc4wXskkZVeqqIzohNxBKVOoC3vRyUJ3xPqnXpfUuaZ55usQCc5T1u5lFRr00KjSWmcPmBr6hTqKp2rDsKAlKRAKeqtqgJCaWd1W1hpePOiu9SR6kiDHXS0VsYqw3PQg6hLQfgQq+OkGWITreFODPJ4boKk+HQzHoaSSmZvVYzT1xNS1hkQp8z64t1ROjWgXMLB27SyY8+JFaDM9SjGMqs6XMO1i0gL8WkAx378gTeS/K1aySpkygjDpqIzcEi4RwQ2AF9rKbRU11Kjv6cvSka0EsCB8+A033dBJsJkg/KCkCJwObap6+93kIX138Ik5S66tIL+H4ei/1NRvQuI1IrOVO113TDScyFJFMBvro6KLDslFFcisfavRXUuXhtNCkMunI6ZrwbbzBwcozBJocgiGfNL/jdqBgrGiKtMW2cTQGdInRK578eYit83Q4lEPuRt+oU1UttUyIq2hVVqmA5XlzbbqGEqWo8iFNwnA7GErGrx3ssgIElMGDHnyJs3mgkUAvx7n/ujrjqGzTw1y27rSsejGgndptTepTn4WY2ngaX7HzaJSlLTi+1YSLirR4ThxmQoo9jbJ/mgsO3yIPEzjkHI6I5FfixHmGd2RlmsjtGh9+XvNvv8ZE2Vtkp2CEiN411lvUNnMB5ibCKF/Y/hVFhqNLV62akYfx8AqSgXy5ImatlLaVwfCgkxSSby7HX6QXGe1lZRAD+QfPaC6Ws7AzUTQXyZzockiyA3FuXPsbuR5fD9U8TG8P5VUVeGnj+8ytNLSN/af4TYlfezwTFLd1a3sVrNBgU6htS1XIv7z88dFOQ5ez/GsusEpI1nw9zlHAaF9T6duUskmb61Vmrgm5asjTOH56R9Sy+IOLl4pCHaCszz7giFr4D7kzrbXuFStDPTG3cWR2mspKrtNpSfYZRJUlBPc6VNMmeCO4oxaleomP8vfjl3NwKigAdNBjCeOw0N57/mSBmvblF2q7DRJ3Z0VguSzIEEWYxlluY8FWo8NvFjRWK0FzUi1q1KvSwe0dYUHr7BEXIIrqZD9UTTTcJaqhpZiWBLXN0d9y/bvPmAfNtVBowlZT7+icYIC99Suh0MYzHu9zIOwPDjC3WOfY1MJfs6DvT54pZ2b/7wNGqS2b8nsB7rMyfliGX058Xpz3IX+3Mnhl3Vsqk3GjW0L2sUMN06Nl4hLcqJVtoQXgw3jzu8YSqvhbbAEGkZpl0k+w05HBT8zUyA1c3cR44skjb4guYwVYh/RJLaNTJjzuHZGD15gF3tfvQl9WEfyyAB1mMVebBhk7F+NBUot9ruUNiZkpUB83Vfe6PRxjsd+Fa7AWQ8jK20OkNvvZCOAWxdits7prMYqkEep0YZW12ws0BPEDIjoFtLIlxvErKyw694tqN5haGWa/LPVmrbbj59yWefAzzk4ZQhDkY7P/GFdOKKUGhpv8+cA4Whr+RUfXPEde4M8HH3NOr4mYey1pZ+sdQupcmGkU0TMlzaHn9IMER4bqxdf8JlvQOmvYVZ/KRW089khhY1WcuTVNYGIedi3EX43bKm7Gb4KHLvztq3j3NlC6sMNR7gCKSkrpTag0YcWFhCsU+jsK3xNhiuZeLjAbSnSIuksJECt2hsL91EXfQe6/pSz2l1YehhxE4MNMdXmLLBDnmy0xpTA0LwpvP8hkyb7DNpgaTP1OhuJJewR+UhyMyyz6MF/iL28G0l2WOLcd+6Mw4VRE8Z6CmpzzJHT5jv9Qcsk5IRhGma8SOv1UIOt2CTta1DKbOdiMjxZqsoO3TpEGHtLJ++/LqC/a2Jqkq2h+xQMy/WMUc2N2Ni0FbJgN19V5bKEqU065Dz2iZ+cI4Bk74JZfHqK0Fi7WxVPiViN9my1Rs6+xxmdiDctlkzjsSXLpCLD+Daj2jgWrzL9WUzV+DGFRe6HEhEVXwA62YTfwO/qMCIVRLhKYFYpi/Qw3gP8SekkCk8BU5YTId77qx3nuCfFNOhN7+Nsqpo0y0aDG1uCmEjt0FlUkyVg+SkVwRCZB+KOHZMY4oMxXz1xPRGI0yojzjj6YTOC996AMZckj4yqwP2PzrXmEHzHli9CiGNPvrFEaZZRuvRDXor1FrTBJ3hRij9piifQygO8lrhOtXuuriQYJm1vFm7sH2vQpMZj4YNsRYiBYzlAhvn9uutfoktK/Dv6G/A4x9pESNmmXxynrqLb2EQ2N1S4Np/IFVfbLW2TENpWnONIVDUUmOYoTyxHkkw8k9L/aOJpqT/fZ8pd00iMUvZGakZsxLbOWtSkriz6XgXpIpr8AutSxZNxREtJAhSx2gewUh3tAVsBmQYWaUIkjGQdgZx05x8O5xwHr3rlFrG/yoS3r+2/93Xxz0VXBnIirj7DA5aGuIEEeAsmEHdGpERNUjZ2ud9izjj5M1Lw9NM071+YnNFd+SIJqKlyVzYXStV4Rw8ujob270+KBY2QL3hLuLHxy2Enc8RhPKZ90pcSSsa54Jef1FQymasuezSXMTJCfCpYv4ntKPRjVD8felATVtiOFuDt2LXWjUZU0zioD9grPlc/nQdZxfbrozF0xMtSg4lRJhChocdV3i5xU9EYjW0tal1FqudKEZLMwBJ7Zc0I+yTJ728p3Yl7z3InpSiu5TmszH41w2arULgo0wJ/75S9bHRWqeGukBkH9kd+gtQP1YnlCtP7+kAmFORClkk7icMsivewAAwSdibMZi5vZRLfda2K6z5xx5DMwmZmnrnmZTDLkFhj2m+p6awcTFZZYupjhZ/6srVTtIT+VbuM5Vp3ehi3EACXOAkf+awPAmBJG4STv2sW75zpS6Ao2GPGhVFDQSOqyNhor5dpFy4zcYNTFGtx2bQ5aJrXISNNTfvjGXBArYUbCYqPIwmg44aAASWnXxNY5+Tp7h1kzNQzRO8HQjq1ptu4qPSNhFrIt33yUbZdSo1I93ES98wqlvUiFmRW6KFUz/cQfEBgeWFQj3jF+6hHrLKgfhitwjE4vhFbcdQ8vMp6b8O60LT0KP6Oo1c8HOkgOawPtMGu9f1K5gGf2koUaiEky0tnXlx+xw5Uf5OTsdjMHQ5DPdLIFdBAxnuTJ1pYXO/qrW1yQpUH/NuUM3vxOtqCCMpXJu9M7xWCJNmdmIa2OvG0cKo5DBs56X1mABr7WxMbiGHkwcr5ViYnp1NlGN3oEuB0+3eRUv+DKW74Zp1Ws+uG/xMRe55ObBKmkrbEUns7XPgG/1+EDw6OWynZA6Kx494tkYcCO2hM7l11qK3QixpYiKzZ/WVbo8aCsBcHkF1sgtEjoRL1ze3xh0IZS5gYiRFfNfZYgFL2W1tbysUIUuqxUW0Fg/O2tEAoQqWRShPJszRFJLYPyozNzneWhzYd8BI3Sx1s37BdaVU6sGbUI5X59rVNDjenkMJB6UU3Nv/R7gc+dDR9Tp8pf+P4QEX3nHtKSfVk8YTfX2ffr7LNUGIjxtGBMzPaxSeVfjLz7BCl74UcX5+oa/803yqXy9e4yH53lQbhkICqe4G+H+WhcQ66bIXgoibn4yVS61jrPnV6X6sr6f3KL3FCLAsw8t1otcomG4B8tcYj4uunK78/ttC3Aq0Dx8YWWAhwcjQIIphZU2YP3eMSRq1dH0kaR5+roENgzMhCWeXTnvGBhcYVHVPihyoRaT7dW02G369u7NZCzR6XzQQ59h9csdp6DyoZU4aqAzZoIRANVYWBkbJ/KUTQ6O4AASTmLA9nx2cAePv77/+DEGe/fYB+40BW8Ev1/d+Jt/Q/kGAAa7uaC2xof2EoDLP9bAJtJW80Uo4iCuPeun/ZGy+yAxBoXu9s8oWew1Vwp5sUVBnFt0mukbQOLWR0q3C95AgP8xumgWSmavkeIq/s1IY2nAIJe2aqzE6tvzrVhR9l2N/MnzHy9hzkcapqlSozfXhM/NGTBzTCnejTB9sa42+Sv9Bfa0DT05MuC+4VaDcnIlYqFkSQkEJpE891B/ZSJoNeSYPNsHKHAenyyfObkTVMXTDiQqrmwYMB+aKh3pxJIovfzW4v8DEXPtN0Hb+///Dzu/tVc+/uGUJtcW4ec6VwUnAFCfxyfoaFGdQqYmXpRi3p1hwo36aVRqizb9tE3FrZZyEjoq2xd6Vt34C3tOKKZ0m526Jz8dZoYMInupTHr9u6p/hN7UrPx9x/m2J8Zw91SUzV2wLJ4cEVfwv9BVp3cdpl4DqNHQv9FMCmyxzBzdufa56s8dWRoBzjz0vUR4mzZuRC1a7hvGgMgoAvzP7Qn11haZnPkk30jWYfx+/NiaFO2WUlkPp9d3FqD6mn/cM9QBjcySVm2A69onToxgWfCDNhwviW/NDHs5Zebsu1/cBQ2nGMqwg9eUen48IhH0vwM5QRCS+nLPSsACGi93H+qmgUu/4DG0w6z1TkUj6UzBgQMJ6vkdFeHLIOZRI/zli6ptr3jYBxtBGNNSIXVro2WtfxzkVWKpU3uWsOk5XXzyhqUzrJge7YNcXSZZOKySwRnPCh4P2GgD3CHuWXMQtCKkHKbeF5ZvLDSO1qfSk1pZNrKJ8M3wVyGdCKiclgSrnq89X7+a5rPRBC/bj/07ChWIwlYmntWtVX8xLNsSS3NM6FJskTQIPDYk6u1hrmBlYVTngIzj8MGnRzX0C47pytm+V3c7YpMZTy7XwxfnRIjCHrhOZrVYffXyDRkgdedgwvKG4KFLncJ7cTyHRYYMSenUt5TK9EbA3yGk60bF9FHpcZsMM4C2glacERyl60i4mlExrQDdrcumuoX+LzPd3A5770RF7o00EyT03RmTr7fk6GMyNNzzYFSO7jk682TN9lWLS1+2pthwwoONTWG+C/1E/gQODw5g4BRsePCdkLUmtjrkXyWMyw2JQntsvHNgw11zZO7ArY5a6+TZcYyyTq0/rJfipimSlKtDm9h43o2W+Sz186RTlH3lKs0Oh6RE+Z/puuBR39ceH6ukUMEvJTaawFrMeQwHY1qSUpPJonrRa4UtHreODg+tQze/urqST1B2QTbfnI9+fWGJK3x3SKBd16A714RgWUDgNp4DNOjP4VotuzcBDgnWCjM4R5+nZ2hPl1C4CtufNoKLzPLvnzYqup/Omrtul4pUcVc6skPzMJJgPAlIfeHIItD5NoY6Ry98gbtc9etxtCMJUYNPqF5feMX4EpOTTltE2qTaBVh4fr+dAKGxenfRKcy6vAgB9ez2SqfNbBSNpUkUIv2LOukY0dguTToGzRJ0441MU5fOC8fYLl+m4kfTXOVfLuSy/PFE5F4VZ0Nv2xeKGMOe2D6zG9hnD2CjNfiInmzjDn4cWvfFQmJhAK3i2yXp28KzU1qzqogDPNtpgj5hV+LL3vF25aU+1FJhUmRSfoDOLsgSuzis+y3yzV6m0IJ2mygt8ZvlNfUS/VVT3OwbmUWfvq5RS+R3FZ+ndu9fq+8wySkeGy8lRfKugqwH2DNFiIRMPrDkf+GrTxbhFrWxeMTWlC+jWQVthYnJDdJKjvCwURDraecD2yquRG1A7MVr2u0w+rvJ6RsAXuFLMexs768s2m4v1/3k2xo2oshQZx4cGpfy3BuYpHQ0DnUERiMYrxEXwxz5i2XqyoWCo9vH1+IKfD8mJ6KV/o0NgUrXyi5QXqpIXJFy1wPtEGN3sX4zptAyL+uU11dISuj6yuMxbme2P/JARQJLzd/vKR8XmDrf+W6MKbUbBZqtNG+GwsiFTpuOckEE6F1JiTdyZFVgXVgfcXuH0oiFUrjy3JcVIxQB0plU9kVl9OK2TZBGybl5SLIOvGcbiHX3hHDm1u1ZtZ5kk8SrGuP8h813aoa5y397DBd5pEd4mxGagzaOgqbVTXI3WtibmS6ZONx4p63cDjBEoWAaN3/JZxLVG/jqtQTWXMnMdEuSZYdaS/rKsCcwek4XeD21p8Q95mX8jnSyM/llhFaDDenIC6KlFdzZiZnqQC/8ORdOEJiz26RFHXa2ZlIK/9B6aCYSQ8p7KqGayX5LK9SrTKKsMSN55YQ82wVoKXZVM5IJNuD7HKLphLWsriPmFSMkZ/zlj1QdvhYTXNB5pHvI9uFis0CnGHT7en4PFuF2foZsI1m0tF1COw31wRdUliNQgyuyongSZUxbMl0M1onYKsJQChEFRSK5w7wnbnXWotMRaaMKwp8zx0EDLKJnOWt6iyfBXuk2pEa+OMro42Agmwu9AzeXmLH7izVrm4OMVlauc8rNPs6IeWgG2J2WoI7OoutE6rU9IRNKnC9vjZDSY3K9EXGjDsrsRLlBFZaavkxQcTnR65NdbTESyjhvz2l4Zldk2at04QK+8VTi5v4EWOwrn1LUt9jLCaDG4EOelqxoaL/Kleq8UHZl9mlp1LTEHEo9ZaSondk2mQoovDi1TeSNLyT+n3InEYA92KzrUeP76XznBTGbthnikJtnnSRNaKzIsKWn+mmcY09b5ZyUgCojcP18hfDyYrC0O8HpY45xqKSY0EbDveUJZZdIkLxwG/uSuXjI1HzUL9vKz0J1hZs+r+zkG+M4Q7XjE3W+Zh6N5LAXrsYGqpwTQ79oUYU05lmBoMZBCFXxbpsTvVso+jIEQFAVdbdoK1XhrggW+NHVVpLCP1zx3lAt5D+lYjzMYtv1FT+RbOcX6ivP7+9DvMNoW/Rd/Lws+32NMrDG0rgGzte92wM6srGxUyclUcj2nIPf4mc3Nb2cpQtsKo74+GAhffwJUVvc6pRS/+55lTobREHKD1z8nEu+P17sHJ8ERZ9Bp2VkwFmZVLzhDblyx7yaypjri497ZwYyYQYf80pItifCCfh61pFs4msCLqqYOpJxBoZKDofbkbmFfD3NCPEEby2CaJZm6eVbvdwmD3KBeS3iyaExpf9KUgSiYZAcpmzi5ItO3kuSnMB/m93V39ZzDykOVJ6gh3lew+2hLzpkUvxaUZGRKXJcUpgrYwt7tJweFs1v4c9D/V2/niJh5Dpcu1PlQ5SEc1Ez6CF8J3eZFwYEwp/kBAS6/jOMZeyUexgvfkUZspF1ww4VdM8EKc1+5eYKFtnW9ggb4d0nJqQQpu7Pf2SpE4ZqquEnLWVIZms8SsLTmzGUFsrHBb058n/3wYtn0TG6WS8gNwq9AdaQSlDJM/eelNPRPnWXiSQsUSeWVZwdlmzbTf31oW6C2l9m8Ntwt8gSlrrVpArp5CNziSbecXHN6+9RfwKVnZRXQfBQlJAkNPqt+moL50XYLI30vkoj68g9TWuoouMmUTWYyxtAD7WFF37yd3gspHVRTVzjy9p4zkWzpjGBSN72mX/PjarIgspVcVwgvnQYfScbmYJ+HJ/zvt/BW+9Wf/JoISJmuFsdGkGKXxr/7PQgnEh1MOfv85E3A3MpL3LA09PpFr8VgkTCxf8Qsu2PZVZcnw3XpaXXHz9ZpgQybiVO0DY3WSD2eO4pff1HPbFb2AMqK8a+NySYIXtRbvAPML025uKsAKlRa5iefNKrqkaXe5g8tmdqnyHnkTBvRQhIo1SLtPUgy28icd6hQlDtKElzDUxoFn/rhvW7UeU3VxXtJm11f3l4X1G2q4jz2U5tJ1/m5XChSo5w6ndJim6sITYBwyBXg3g1BcQpn24iYAWKs0yBcuTV3JVlYJknFBAqKDlF08vcAFP77y85g7gEPWm93ADBpO+rkMKKgLURTVGUtRKL/jZps+k7ygyUzvR8RJoUaZlfeagvPZtFfn5/UcEWDreLFb4fpfJoqKv0YvLNQabTUYQYV2UT6Bzb1dGKQRZaAKHS+VcPrNN34NxO0SCl/gpxDRBq4tPjbaZKP1d7zVziq4l7uNau6W+52xvkrCGRaWTB/iu+MWDtYoiwe6X/mj/4aJp2T6JqEng5fSJJv94Qliptasar4aNS61at0hQ8c/B2ytkJ91nxTu+OPN9Baf13znunPuUWOH7Tk4GkYK57M3l3nb8RgK1Pa7iXzoxrMH0V1EQuf99a8Zfgz50lf7vke+fn7Zl5gNVZ4CM7vxuVVc4Y8t97U8izWPgWgHZ5LFIWggQz/dgoAvhT+LpNeAvqjxx1hCCyA3eIoqrTfQXIsrS8L5zTtdQt3u4dwY+x8Z9f7p1sD7Foo9phbtFLUkZEWThoriJl1Sz4zHxB5cD+iGjRdlO9o7QAQY2iUin5vnvE/X1K4R1UYVACnxxq2zZfyGVVq424V/3YmwNvfUAGyjxOxPsy5cfRcCx5n8WlJnl4x6hgIw22tMUdkyZsmt5eJ/iCAjvP39+c8XwZXFVSC5hUFFaACq9N7lbfjhhOcCW3RbFDLhJBpX9n5i5MS2m4ouEbN5/UKUMAWmKTmJinZKsjsSx6ipTGbnp57awxl+xK/LleVGZfPO3dTijppeJ+fGfefiwzUpgL7h88ZEUy46qlk0CPseY6RfZ2czfDx/7ng7VVwNTaK4DZWTHtCdrCOi7/xXfVsCKb+VhH3MF5oqG17gwVFCjsnzx6KKyy6QJinBdAhKWHP70g8+Fmex/DpThktdTRLlFSIzcKMTiGvXhFkg4DdroeVkMIGAOiDL/Gqd2Ixuputwapaq4eykTmIjrwpyTjvexi74+QNd42h3Kozc3c6ndw8x2/3VtmoYa1Uph1l2EfvfG3m30iIf1cYCAISwDmrsEvgL9FlRwDsdkKe/Zpjz8husf82Mys7r6ECKDYeaYbX4L6AjoeQYlolOfsGmUyX4HrX6yLAqhrsTYGI6A3if8RNEsDRg2BqMr51WNITUJS853xki1DFaWy2a4I8c2cnmN5Rban8TSno6cP7dXJUhp6q2mz9ZtoTN4NHE+i7kOKzh/59ESjiboqsl6XjEbFxQU32xlObxho/6V/uEFohRSruK8jbwLiw/qupoGQPi2O6M3NtU2Z4i6fB3SIsvCTy8O3TGp8XpeMh5t5yOx9BHsUkhOC2OKS0rwpUmhcMzcDhcZ0/VRczkVvg5h4SdaadWMmWCYnw28wHnhMoTv+BindTnSSUf8IQts+lMs9qzbLSBKIKUZk7qbb9xDYCJRRCuDZeLT12DkKYNHSA3KyFn2rc7C5flxqo4Zq6YCpSffobr6CNUv9tXF/YJlysqtYmd9PCBjR7V8P8FMk6Y4eOnWLRCrFWpmt03bjiBw+qQUnFEgMt9hijy1qB6Ip6QZS5vBrdJM9hvyD7cpcrfy2B1iBz3hFhMDZyNSjGWgAvt5kCSA3V1wCxNUd0LG5Fiise/+shGGEq3jV1udjbA78MlIqywLP0oMKdnYCIF6Qima+STwr21FHYP1o3BdhZ+cTx+TM39DzpxBPIGPU+uptyYUc1TtZlNEr035RMORCf+9SJQ4lLswoyuzuLFStXP+GUxALUMebiNrUylGe7lwbB7SJj07L7HctiilKGYJJfTXIWF2AcnMDtMT9xeHjLYvS+YmyTIxAP9xbG25Q/x6vc3QinC01nQkxDcHxh9aeJpXjVmIAuI6TKcTvO0kx+dT9rCHO7rDONXVmBi2Mgvz7Y2u6vbeJnNSLkqqIVNqBmaPw8ltA73WwRF78h+oTi6sVOzNp5o4epvvcBVPH7VCVFUvB1i7jrzZxy7p7DJcD/MwJlfIG1uM/TTClk7D2PnB2vYE52EziAQlaaw3JS/vkBWe9QoZEJvNUoHaoIQceA2/A0MC4EywXv31y8c2CTDizUa93F1wInwy0qIYRxwlBs+J8BbWDBJJVaD+yN70TvEBUPW11JheubWSay+RV4iqSr4oR2KrvKlOaZimb3ATjTloySKMcRy7fQBpbYjSYPYyHo3nifTSBJOZw7m6F3qQKnigNDJsclnDq8P1MMJOowvbeKD1upfPKhc8ymqfVRtHyUinyx7OT6WVHEggqJpUCNHsNshYeeQyDrUDQKwp4j38h6K3OjWoGS/OQUoD9YeX4SuUTFkFaPkgHK8hZ7jPzB534Ndad4B4IdWgH9/kYlbq4uEA/z3FZpG449wsfKYS50Edm9KUPFIc85+0elGwjXIspQK6G+TXVPoqXVp6WbVgRHNBdQLhE3xn+tBSJxkWdWwaowbkAXUcCsn2fY2oA9DTsbakmjaMFoLFx9E4rzzLXrxZek7mCu+QpZrnQoZYR3lKgYRod410CavW9Xf8TxCTR13FqhDF/3T9dKE8gjXF2Zt4Xqzb//Z49cd7ovnPA1uGUN/r4U/cIeYk9NKSxyquinMNlFSYwDzqtiIyvezm+n8f2GuuW8TU4kMinHCfWsVxe6ZfVdXZjIak+HcY46MAsDcHldPHBEgbHJmAejur3Ne8QIASKE1SKQ36XxW3Ym1WZX0Rbjr04tDh6o/4WQUjsYvnkV3cQ+n85gvhHkO53hPXDnXfpvhlMRODlRVuESn4wgMnV/nXrKWEkGwn6fRtuHDfd2G4QlP5LqO4PZAivoMYBaf/8gUK28JVDdvvfoJR9qnXIf3/ElASg8rJz4O8uC5WRf1PP4mY8Kg4pwvuyDSWFNP6UnHB+w7EbOg3nhofUAz33jltYYl12a7vCqNWU5Rnzq/O2lKCRNSuKwumsUU2JxHIGl5iv5ZfUe+pjLpUOY5HW8cqaDO5eaUVYRhGBVdzbE4SkKZbQrKVPHtKG2zARgtdBbXYilxye69Y4bYaVD5n9lzcZRL5OBq57eDhQvJOILPldQjMmQ9yhmOiV6IMWHSaiOuuoZZ88SAS1yQwxZygLncSxnFbSDiWfxjLRtbmtZ8si8QYsxvwGI1/jFOsI90HLAq+PfJFJyXRjtpK98VyqBZwGKaWd1pj2BOu7tdfpqrs5E863ERVx5TOeDDiNPHuPyeprRYN0v38OztTSf78hfQKY7Vzp4DHPS5l+2miXCdCY7DI5DaLxeyMu1WaSItg5CtCJpUxqkhLOytCMiPfpslv4s0mvOGo85NeqylsXdK17Cd0u7z8vQtG9JJ+OLXXmJPnC0ImixWU6SJQTbroKvNrTyzfo3+k0hZLEaS7MG3nt+PufgkbL1nDfNrJw5Lu/H57ZxFugTa3YGq+oaYVQIczgL3DFpOJr/C4cURSCVBTUJHWXZE2MasiMDqScWcGuBi/dQRcwbjn+LEahdFfZ8dtnQeuYtwBd/LekZQurdvpKHApzebqHT+2wuHp7ex2TagsXXTDs+iGNujZsd1DJ/v9fnLgSY3V3Tv+i0vzdny5Wj+AtmX1+YPRLEDrAJbcZY48qC1oGW/LX7zYUmjrDUIdDjgwLrkMFyw6HGab2CSIlAbE+fOywuSpwilbovzg0cDRGH9gy8nCwqQLPmUB/lz+8Lr9+m3H7dT2PgQObbRfEUwbAZ9ghhsBhmvw5yAwLGgDla5Do3V0qgFArMB3ISL+8xuAk77+08fP9B4d6Bs4dfxU34l+p/gYLpLTIhHnNuFju0SSXdhoTrNYndeGD24BGiOjrwKsz3sbAk8urIYAYSR06ozVEaL7hSqLQSWDyIeep0KTDHVsRdig5DcEasFVKzLa/MBP0u+hBx+2VAiPj8543+qyRZIOvcSq1sm82JenX3XRDLpGqtarB91xGywjmBuNOTxQcogNdETuiLl8Y9Wftfpad0R+TPsSn+YlZky03Qf+EHVt6c+hkWYkJ1Ttd644KrPATqP8LX4M/MOHqQprJ1+ftPnM7f1SgCnGarEqjplg2GWXKl0acW//4sxVWfLQxIbOgXq7tLNJ64AsjpjPbvVY+FbaIIlPDYMyYH4kdcps/xcW0jBAFLCDbghbp600G6mauFKjcdZTFMp6isaplZuiVvJxm5RtFZkMsVa2fq8RrTbz5G6hVA0qBHT4dvJEfVRj5JusPjzdhjdAUoXHBJyV4knjXJ2iSZMXZ6zKkgX76jsm1ztknc1au6FKrI5hurQf77wXqObZqAvJfEoIlIlAKKpXFzD80FUuav9Zkku4cNY3RF3lbDz6UPzoubf/cP9mQPlkv2m/ce3XOwHRhndg08ARrzq4GCgcRla11UU5M373vUZex+VaSuiPhPnP2whkwUIF01FBxNkaq7CoMZSPSvegnCvnW0Fcs3Qv7rYA+G8vnLFS6AuvIQB63Ngl8eNLvp3NB5qBtAzjBSMArbiA+sTqq3qjWOfSv9Jdq673uwCo8bLmfaMaGsyaWDHthvpyD/ByBQEhgPThBriXwnXqr+l+1rmj4H9Ig9+ZoemyOmtHVsc7m/F9zbsZCgcMp5H4e/O9CBtu0fKe01h83Xrf/A007KbvBrDLKIF1c5VZm3jAnzZi/gQ1txfIL2lIXBFMmww+QQ83At9cIokXXx3pIpE4R/L9pcjPH+sEeL+/5MCB/ftK9h/Ye0B8YN/B/ZJYbwDOCv0DTqtSaAs/HLfM/sj+/LJK97mH4b4ARH32j+wAJvI+ItdBlTS+2vQt94r5sjbr1o9v0Y3mk+Y74GrLJvPGzECyJlTwpALw1ETZ0YV7i3UO49FfuQfcL7ex5YD9APCu9eLoYmBRshQz70LqdljuW2bde1UBgP5xT8rLnuOw/y8r/6RMGwueq+bJL3XWJ1YesEFmDYtp/G0WKd9q0bDIxq/Wjmi9Ksv4ygZqx4YDp+kNjQmTSuV7b+8/IJll0uqL6md+xzAxtbk9OOr+u5gvqlY7Y3GYZM/+AqrduXXvdr88IPdrmTCC5pVPKn4rCkGCb6e3g85Y/POFkmj80mUOlJVUW1MQgW/8YiF6X+Nz1QCALvIBBLTPE+wNa6H5WL/93kv7g34E43X884ZCf2hRNd7E824R1yE5SstGOopgv43QpDh5s2Ep/OtV3iq6kisk6y0L0wrLM6BklqJteIqxshRr2a04GyvxEjmoBFv9SrTZoySzhGTIUqVYryvVRg6axJVu+U2Z5llkQZa+ZgNcmal8G7QKzKMQyn0VWfMphoxRAtmh0plUkSmDPHgtd1KF5RyUAqeKZNprdXuogezRvb1r2zU86l9kVYObgEZkUdnriGQ9Zv6Ta2XG4dVXwPFmxvLiK+BzOeP78Cvg/+AzAp5fE3SbfO2jvyagmPtaf01AMff1nNczIQAUMyEAFDMhABTHQ1AAphDQ1rmVLo2wSe5N/vWIjcEkEFmSe3+GkYAB7F43fPHUqJulBwWmRnPa62BuIpQZiVBmJOLayKM9RgcFskHK6NF7CpsEMK14tPoy1cwjb2qe0dcAc5kXlA2XTyOZc+R23EqmNu0c8mlfVnw3LybNX1mAjBSmCk7G1hE4zvDp19h1DL7TtAe9eInOTqvQc5q6Dqwpc33mpi6nXse6PSryXtw455Pu2C6rfW3X+IH/X2+m9ktHRt9rk6OwJbz7FspHPddTBfP0qjt0X14ac/4PJ59FxtXmp8y+f1Zen+/Tcsg9RVXVHm6cwjiEuMUXbdOKwpn/hC6o8ysVNLkG6oy17gd7bJiDWmxAL3Sn8jOtPVvavqe2Kw+a4JIyLDYD/ajPo3s5pirG90ax69s7TdH0VuMayJeSRvcX7bnGpM/+GtLB87S0Tmcskz1TlFoDp9z7Pfsky/RjkY3D3hbRQtc/lsRWHDrN1/waoNjKzw9ZfVopdy+Bz7N+qWoGcSl0dfYp99raaLt50qY/Tecp60N/m21X3VnbdarHzsUbgY/ut5ZrlL6vBX41MXvHLT8r5vbe83WptqpOxf1eL9l3s2WvQABU5fcLdv16rbV/CTHuGQC7P9/5HAA4eC/eO/L5g3vCb2DLuAIg8If7PZQajOz09svdTq7HkSuuF9MPXDeBv9BH0XaVIj8H2znOR9TVfbXlCcu6a33MzsGvmRYuXcq9f0LpH1COK1z8K9T+nzrf3rthgJJnh0VmUYeHWBZ2dis9VqVzkOvqp84e7pZAeCm116kjx5g49/wGNTM19izWLKVC/+4HZ1LaRhn0/vijrL7P1vzcYzI7BlKlth+wTK7tknPUwtFpW72ezZ6PnEygPMDfNfgn3ZujFaA0T8dLe93I3BM3JvvfMcf7p4CfUx2qzxpWmgK7VjUB/j499DZ23t3HI2zNBVQ/5OLf4eynHTKCT5RzGs9L6vGESa6ljg6+dXaYKwA/H2N+GestzKJqi0ZxLH3A0876u6wWGnZr5+delM+czsDrWbf2Xe7TQVmHKXs2kzQ4u+IH7qW3Je87EcSf6gSlJ/doP8bWNsr8r7blrx0zjckBPOcrylES2a8zqY99g+yhTmc0z6+UgrpeWSiMWjzajhauZ5a21cR919jVu7CX1rWh1/Pj487Y8/lbxDmRKjBmdf+TUV9YX/Ta1+7rzrsNc8quorz/i0iUtkPR57Xjbi25WzpRP2brQepL+L6azW+Rx8qsZYGHnWfzx1ftmm7ZdPx+Y76qDymzgtLGT8XTqcXk3C/v3+aaOhfrM0XrtMMk9Y2n//KLJz0rz6DlwY+1p49NhUATHdDIIyrHQMRroJF4WBokmIFpLUk3vKbMLCoAmmiB8peKIYEIngcG5JErC0LdkQVATVSrxTrLVXp+u3mBPsMZOjP2xqphhh9ysMhLGcB75pdo88yA0xHO2rUcKgeYosTnmg6ygFY6L+vFfv8Yp72sGmdWWBP+5o2c8OOZobZ0fXunx8RvE09bc4U61WMvWebpnaXBCMCfCPD7Y6asdyLyLCfX+e+2mGqP/p2kARwphQFH6ff2YPilPK4xuZR7jqxCi+DJthajBF60BFrwrSXBJnpLRhU1tHQI0lBLjwY60jLAXb+1jGhgYsuEek61zKjlPa1isPlpqziRN/GHKIGgNisEVYzjmcukM/igiJCICGjGoIIGGB+jGHG53KKSNUVZkNXoru/yQFdWhc8pb50hEOhM4fsFJIiMIQTUWLWotFCvqwgRVnzOn01cB9BpE6gXp7P78h8OzbVNqHRB6S91RSBhITFZA0MDdVlbOoVMMGXco3dhsuDsLagt4mbFCRivv5FMc6vC90M+94RCBalp6wSjmc1ssg/H/dzbRsmQfkJ2q88cARhAz25N6QqzMxLYxKwY9+RPBN2DZmYNqFjTvRm1Gqm4rFLsjiXPNpWK7ttotMjEH1e3QvQa/QN2Qqf6Bi2PYJIiIWQj03MvoHQONgJut2gMLIwCtNjzPbZcVbHQxNmTqT3F9ZpBpSqqK/wtdW6qred86J6mDumekXoXOERaWKAtGubvHw/zIXJzeITUSfG4JTFtN5SNucf3ZcAN7Hnk/YE725SjMB6Gtrypz56JoYaeWmzvtVO2sJP/aASAttt2fnVLR8/AyMQMa1jLLHPMswAgwn/o8x1cyL/67/8NmSCM4iTN8qKsbN20XT+MbvLzsm77cV73834/gAgTyriQShvrfIgpF2VVN23XD+OkmzeICfNRKp0XN+njXc3nul/74/Pr++f3DwAhGEExnCApmmE5XhAlWVE13TAt23E9PwijOEmzvCirumm7fhineVm3/Tiv+3m/HydIimZYjhdESVams/liqWq6YVq243rgB2EUJ2mWo9V6s93tD0eImjOyevaeZtB0i9Ww2R1OcZluD4AIE8q4kEqbIIziJM3yoqxs3bRdP4xu8vOybvtxXvfzfj8AQjCCYjhBUjTDcrwgSrJCqVJrtDq9wWgyW6w2u8Ppcnu8Pn+3//tC32CWKfNHLRS6SFBidX4u8ZjhmjnIsZ1cdWcZ+yuJu3W8I/d0Y3uLi+BL90Afpom0aU27hP6PtXowB+iMLtdyK2fSSOut3kv4o3X5t67qTH44VjnfupG3LZQgkrh4lk5r07R7HWdywTRiHWMoNGkjvyexFfiJnNdkAcuH4tBHMerRal8Wt6WfrlUt8jRzG/PSQqvctpprJtCdXetJ9u60o5V0SfUUlhurEzcVlJvbOcFfDxzmw5LuWopAL5tnZkzY952Vi4cf3HsxmuQ8OSvzsyAP8/SsDp8NcxddVF1ukK/SvE9rscbppK22AAZjcpNM1rVvs6LFwCdy8Bzcl1A7njrV03pZr+hVvabXb9M406G/IJihWvz4eDAWM+zLOirYSpc0KPnN52SM6EgVxo6OiRad8I1GF+QlO0Lk8zoetjY5xCqCjckdNZXhdTtukbYkP96Rfs2GUS+iZoNcUCUatZOJUz3ppE49Tjdq9zZCpFt0QSoCgiocmLkO89pr7h551c2pZLF8pRQb05Y6eFanw7wxuP8od6sREWeITrPkQC+8cKJYiOQcjWFsRBt7FOogqsKjZHpVGYxcE6uAFWJBvbUtRj3FBGGQXXa6MdTaGjVnlfUivmB1S62rxO4iHSA9BGs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") 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") 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Emoji", "Noto Color Emoji", "Twitter Color Emoji", "OpenMoji", "EmojiOne Color") +force_autohinter = true + +[sub_resource type="FontFile" id="FontFile_oowaf"] +fallbacks = Array[Font]([SubResource("FontFile_m60m1"), SubResource("FontFile_cti3n"), SubResource("FontFile_7pcud"), SubResource("FontFile_8npy6"), SubResource("FontFile_vgqfe"), SubResource("FontFile_ryy6m"), SubResource("FontFile_nftyr"), SubResource("FontFile_a3ivw"), SubResource("FontFile_hftju"), SubResource("FontFile_x6oay"), SubResource("FontFile_2xrbr"), SubResource("FontFile_g47oi"), SubResource("FontFile_eoofr"), SubResource("SystemFont_7t075")]) +data = 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19.796875) +cache/1/15/0/glyphs/214/offset = Vector2(0, -13) +cache/1/15/0/glyphs/214/size = Vector2(9, 14) +cache/1/15/0/glyphs/214/uv_rect = Rect2(103, 17, 9, 14) +cache/1/15/0/glyphs/214/texture_idx = 0 +cache/1/15/0/glyphs/269/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/269/offset = Vector2(0, -14) +cache/1/15/0/glyphs/269/size = Vector2(8, 18) +cache/1/15/0/glyphs/269/uv_rect = Rect2(114, 17, 8, 18) +cache/1/15/0/glyphs/269/texture_idx = 0 +cache/1/15/0/glyphs/809/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/809/offset = Vector2(2, -4) +cache/1/15/0/glyphs/809/size = Vector2(5, 5) +cache/1/15/0/glyphs/809/uv_rect = Rect2(124, 17, 5, 5) +cache/1/15/0/glyphs/809/texture_idx = 0 +cache/1/15/0/glyphs/244/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/244/offset = Vector2(-1, -13) +cache/1/15/0/glyphs/244/size = Vector2(10, 14) +cache/1/15/0/glyphs/244/uv_rect = Rect2(131, 17, 10, 14) +cache/1/15/0/glyphs/244/texture_idx = 0 +cache/1/15/0/glyphs/319/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/319/offset = Vector2(0, -10) +cache/1/15/0/glyphs/319/size = Vector2(9, 14) +cache/1/15/0/glyphs/319/uv_rect = Rect2(143, 17, 9, 14) +cache/1/15/0/glyphs/319/texture_idx = 0 +cache/1/15/0/glyphs/245/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/245/offset = Vector2(0, -10) +cache/1/15/0/glyphs/245/size = Vector2(9, 14) +cache/1/15/0/glyphs/245/uv_rect = Rect2(154, 17, 9, 14) +cache/1/15/0/glyphs/245/texture_idx = 0 +cache/1/15/0/glyphs/282/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/282/offset = Vector2(-1, -10) +cache/1/15/0/glyphs/282/size = Vector2(11, 11) +cache/1/15/0/glyphs/282/uv_rect = Rect2(165, 17, 11, 11) +cache/1/15/0/glyphs/282/texture_idx = 0 +cache/1/15/0/glyphs/361/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/361/offset = Vector2(-1, -10) +cache/1/15/0/glyphs/361/size = Vector2(11, 11) +cache/1/15/0/glyphs/361/uv_rect = Rect2(178, 17, 11, 11) +cache/1/15/0/glyphs/361/texture_idx = 0 +cache/1/15/0/glyphs/89/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/89/offset = Vector2(0, -13) +cache/1/15/0/glyphs/89/size = Vector2(9, 14) +cache/1/15/0/glyphs/89/uv_rect = Rect2(191, 17, 9, 14) +cache/1/15/0/glyphs/89/texture_idx = 0 +cache/1/15/0/glyphs/122/advance = Vector2(9, 19.796875) +cache/1/15/0/glyphs/122/offset = Vector2(0, -13) +cache/1/15/0/glyphs/122/size = Vector2(10, 14) +cache/1/15/0/glyphs/122/uv_rect = Rect2(202, 17, 10, 14) +cache/1/15/0/glyphs/122/texture_idx = 0 + +[sub_resource type="FontVariation" id="FontVariation_2iyu5"] +base_font = SubResource("FontFile_oowaf") +opentype_features = { +1667329140: 0 +} +spacing_top = -1 +spacing_bottom = -1 + +[sub_resource type="FontVariation" id="FontVariation_wml18"] +base_font = SubResource("FontFile_oowaf") +variation_embolden = 0.8 +opentype_features = { +1667329140: 0 +} +spacing_top = -1 +spacing_bottom = -1 + +[sub_resource type="FontVariation" id="FontVariation_1lm0m"] +base_font = SubResource("FontFile_oowaf") +variation_embolden = 0.8 +variation_transform = Transform2D(1, 0.2, 0, 1, 0, 0) +opentype_features = { +1667329140: 0 +} +spacing_top = -1 +spacing_bottom = -1 + +[sub_resource type="FontVariation" id="FontVariation_qryon"] +base_font = SubResource("FontFile_oowaf") +variation_transform = Transform2D(1, 0.2, 0, 1, 0, 0) +opentype_features = { +1667329140: 0 +} +spacing_top = -1 +spacing_bottom = -1 + +[sub_resource type="FontVariation" id="FontVariation_qc5vd"] +base_font = SubResource("FontFile_oowaf") +variation_embolden = -0.25 +variation_transform = Transform2D(1, 0.1, 0, 1, 0, 0) +opentype_features = { +1667329140: 0 +} +spacing_top = -1 +spacing_bottom = -1 + +[sub_resource type="StyleBoxFlat" id="StyleBoxFlat_hbbq5"] +content_margin_left = 10.0 +content_margin_right = 10.0 +bg_color = Color(0.172549, 0.113725, 0.141176, 1) +border_width_left = 4 +border_width_top = 4 +border_width_right = 4 +border_width_bottom = 4 +border_color = Color(0.87451, 0.0705882, 0.160784, 1) +border_blend = true +corner_radius_top_left = 8 +corner_radius_top_right = 8 +corner_radius_bottom_right = 8 +corner_radius_bottom_left = 8 +shadow_color = Color(0, 0, 0, 0.756863) +shadow_size = 10 +shadow_offset = Vector2(10, 10) + +[node name="GdUnitSettingsDialog" type="Window"] +disable_3d = true +gui_embed_subwindows = true +title = "GdUnit4 Settings" +initial_position = 1 +size = Vector2i(1400, 600) +visible = false +wrap_controls = true +exclusive = true +extend_to_title = true +script = ExtResource("2") + +[node name="property_template" type="Control" parent="."] +visible = false +layout_mode = 3 +anchors_preset = 0 +offset_left = 4.0 +offset_top = 4.0 +offset_right = 4.0 +offset_bottom = 4.0 +size_flags_horizontal = 0 + +[node name="Label" type="Label" parent="property_template"] +layout_mode = 1 +anchors_preset = 4 +anchor_top = 0.5 +anchor_bottom = 0.5 +offset_top = -11.5 +offset_right = 1.0 +offset_bottom = 11.5 +grow_vertical = 2 + +[node name="btn_reset" type="Button" parent="property_template"] +layout_mode = 0 +offset_right = 12.0 +offset_bottom = 40.0 +tooltip_text = "Reset to default value" +clip_text = true + +[node name="info" type="Label" parent="property_template"] +clip_contents = true +layout_mode = 1 +anchors_preset = 4 +anchor_top = 0.5 +anchor_bottom = 0.5 +offset_top = -11.5 +offset_right = 316.0 +offset_bottom = 11.5 +grow_vertical = 2 +size_flags_horizontal = 3 +max_lines_visible = 1 + +[node name="sub_category" type="Panel" parent="property_template"] +layout_mode = 1 +anchors_preset = 10 +anchor_right = 1.0 +offset_right = -220.0 +grow_horizontal = 2 +size_flags_horizontal = 3 + +[node name="Label" type="Label" parent="property_template/sub_category"] +layout_mode = 1 +anchors_preset = 4 +anchor_top = 0.5 +anchor_bottom = 0.5 +offset_left = 4.0 +offset_top = -11.5 +offset_right = 5.0 +offset_bottom = 11.5 +grow_vertical = 2 +theme_override_colors/font_color = Color(0.439216, 0.45098, 1, 1) + +[node name="GdUnitUpdateClient" type="Node" parent="."] +script = ExtResource("8_2ggr0") + +[node name="Panel" type="Panel" parent="."] +use_parent_material = true +clip_contents = true +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="PanelContainer" type="PanelContainer" parent="Panel"] +layout_mode = 1 +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 + +[node name="v" type="VBoxContainer" parent="Panel/PanelContainer"] +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="MarginContainer" type="MarginContainer" parent="Panel/PanelContainer/v"] +use_parent_material = true +layout_mode = 2 +size_flags_vertical = 3 +theme_override_constants/margin_left = 4 +theme_override_constants/margin_top = 4 +theme_override_constants/margin_right = 4 + +[node name="GridContainer" type="HBoxContainer" parent="Panel/PanelContainer/v/MarginContainer"] +use_parent_material = true +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="PanelContainer" type="MarginContainer" parent="Panel/PanelContainer/v/MarginContainer/GridContainer"] +use_parent_material = true +layout_mode = 2 +size_flags_vertical = 3 + +[node name="Panel" type="VBoxContainer" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/PanelContainer"] +use_parent_material = true +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="CenterContainer" type="CenterContainer" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/PanelContainer/Panel"] +use_parent_material = true +layout_mode = 2 +size_flags_horizontal = 3 + +[node name="logo" type="TextureRect" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/PanelContainer/Panel/CenterContainer"] +custom_minimum_size = Vector2(120, 120) +layout_mode = 2 +size_flags_horizontal = 0 +size_flags_vertical = 4 +texture = ExtResource("3_isfyl") +expand_mode = 1 +stretch_mode = 5 + +[node name="CenterContainer2" type="MarginContainer" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/PanelContainer/Panel"] +use_parent_material = true +custom_minimum_size = Vector2(0, 30) +layout_mode = 2 +size_flags_horizontal = 3 + +[node name="version" type="RichTextLabel" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/PanelContainer/Panel/CenterContainer2"] +unique_name_in_owner = true +auto_translate_mode = 2 +use_parent_material = true +clip_contents = false +layout_mode = 2 +size_flags_horizontal = 3 +localize_numeral_system = false +theme_override_fonts/normal_font = SubResource("FontVariation_2iyu5") +theme_override_fonts/bold_font = SubResource("FontVariation_wml18") +theme_override_fonts/bold_italics_font = SubResource("FontVariation_1lm0m") +theme_override_fonts/italics_font = SubResource("FontVariation_qryon") +theme_override_fonts/mono_font = SubResource("FontVariation_qc5vd") +theme_override_font_sizes/normal_font_size = 13 +theme_override_font_sizes/bold_font_size = 13 +theme_override_font_sizes/bold_italics_font_size = 13 +theme_override_font_sizes/italics_font_size = 13 +theme_override_font_sizes/mono_font_size = 13 +bbcode_enabled = true +text = "[center][color=#9887c4]gd[/color][color=#7a57d6]Unit[/color][color=#9887c4]4[/color] [color=#9887c4]6.0.0[/color][/center]" +scroll_active = false +meta_underlined = false + +[node name="VBoxContainer" type="VBoxContainer" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/PanelContainer"] +custom_minimum_size = Vector2(200, 0) +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +alignment = 2 + +[node name="btn_report_bug" type="Button" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/PanelContainer/VBoxContainer"] +layout_mode = 2 +size_flags_horizontal = 3 +tooltip_text = "Press to create a bug report" +text = "Report Bug" + +[node name="btn_request_feature" type="Button" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/PanelContainer/VBoxContainer"] +layout_mode = 2 +size_flags_horizontal = 3 +tooltip_text = "Press to create a feature request" +text = "Request Feature" + +[node name="btn_install_examples" type="Button" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/PanelContainer/VBoxContainer"] +unique_name_in_owner = true +layout_mode = 2 +size_flags_horizontal = 3 +tooltip_text = "Press to install the advanced test examples" +disabled = true +text = "Install Examples" + +[node name="Properties" type="TabContainer" parent="Panel/PanelContainer/v/MarginContainer/GridContainer"] +unique_name_in_owner = true +layout_mode = 2 +size_flags_horizontal = 3 +current_tab = 0 + +[node name="Common" type="ScrollContainer" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/Properties"] +layout_mode = 2 +metadata/_tab_index = 0 + +[node name="common-content" type="VBoxContainer" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/Properties/Common"] +unique_name_in_owner = true +clip_contents = true +custom_minimum_size = Vector2(1026, 0) +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="Hooks" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/Properties" instance=ExtResource("4_nf72w")] +visible = false +layout_mode = 2 + +[node name="UI" type="ScrollContainer" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/Properties"] +visible = false +layout_mode = 2 +metadata/_tab_index = 2 + +[node name="ui-content" type="VBoxContainer" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/Properties/UI"] +unique_name_in_owner = true +clip_contents = true +custom_minimum_size = Vector2(741, 0) +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="Shortcuts" type="ScrollContainer" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/Properties"] +visible = false +layout_mode = 2 +metadata/_tab_index = 3 + +[node name="shortcut-content" type="VBoxContainer" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/Properties/Shortcuts"] +unique_name_in_owner = true +clip_contents = true +custom_minimum_size = Vector2(683, 0) +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="Report" type="ScrollContainer" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/Properties"] +visible = false +layout_mode = 2 +metadata/_tab_index = 4 + +[node name="report-content" type="VBoxContainer" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/Properties/Report"] +unique_name_in_owner = true +clip_contents = true +custom_minimum_size = Vector2(667, 0) +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="Templates" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/Properties" instance=ExtResource("4")] +visible = false +layout_mode = 2 +metadata/_tab_index = 5 + +[node name="Update" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/Properties" instance=ExtResource("5_n1jtv")] +unique_name_in_owner = true +visible = false +layout_mode = 2 +metadata/_tab_index = 6 + +[node name="GdUnitInputCapture" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/Properties" instance=ExtResource("5_xu3j8")] +unique_name_in_owner = true +visible = false +modulate = Color(1.54884e-09, 1.54884e-09, 1.54884e-09, 0.1) +z_index = 1 +z_as_relative = false +layout_mode = 2 +size_flags_horizontal = 1 +size_flags_vertical = 1 + +[node name="propertyError" type="PopupPanel" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/Properties"] +unique_name_in_owner = true +initial_position = 1 +size = Vector2i(400, 100) +theme_override_styles/panel = SubResource("StyleBoxFlat_hbbq5") + +[node name="Label" type="Label" parent="Panel/PanelContainer/v/MarginContainer/GridContainer/Properties/propertyError"] +offset_left = 10.0 +offset_top = 4.0 +offset_right = 390.0 +offset_bottom = 96.0 +theme_override_colors/font_color = Color(0.858824, 0, 0.109804, 1) +horizontal_alignment = 1 +vertical_alignment = 1 + +[node name="MarginContainer2" type="MarginContainer" parent="Panel/PanelContainer/v"] +layout_mode = 2 +size_flags_horizontal = 3 +theme_override_constants/margin_left = 4 +theme_override_constants/margin_right = 4 +theme_override_constants/margin_bottom = 4 + +[node name="HBoxContainer" type="HBoxContainer" parent="Panel/PanelContainer/v/MarginContainer2"] +layout_mode = 2 +size_flags_horizontal = 3 +alignment = 2 + +[node name="ProgressBar" type="ProgressBar" parent="Panel/PanelContainer/v/MarginContainer2/HBoxContainer"] +unique_name_in_owner = true +visible = false +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="progress_lbl" type="Label" parent="Panel/PanelContainer/v/MarginContainer2/HBoxContainer/ProgressBar"] +unique_name_in_owner = true +layout_mode = 1 +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +clip_text = true + +[node name="btn_close" type="Button" parent="Panel/PanelContainer/v/MarginContainer2/HBoxContainer"] +custom_minimum_size = Vector2(200, 0) +layout_mode = 2 +text = "Close" + +[connection signal="close_requested" from="." to="." method="_on_btn_close_pressed"] +[connection signal="pressed" from="Panel/PanelContainer/v/MarginContainer/GridContainer/PanelContainer/VBoxContainer/btn_report_bug" to="." method="_on_btn_report_bug_pressed"] +[connection signal="pressed" from="Panel/PanelContainer/v/MarginContainer/GridContainer/PanelContainer/VBoxContainer/btn_request_feature" to="." method="_on_btn_request_feature_pressed"] +[connection signal="pressed" from="Panel/PanelContainer/v/MarginContainer/GridContainer/PanelContainer/VBoxContainer/btn_install_examples" to="." method="_on_btn_install_examples_pressed"] +[connection signal="pressed" from="Panel/PanelContainer/v/MarginContainer2/HBoxContainer/btn_close" to="." method="_on_btn_close_pressed"] diff --git a/addons/gdUnit4/src/ui/settings/GdUnitSettingsTabHooks.gd b/addons/gdUnit4/src/ui/settings/GdUnitSettingsTabHooks.gd new file mode 100644 index 0000000..3b01f34 --- /dev/null +++ b/addons/gdUnit4/src/ui/settings/GdUnitSettingsTabHooks.gd @@ -0,0 +1,255 @@ +@tool +extends ScrollContainer + + +@onready var _hooks_tree: Tree = %hooks_tree +@onready var _hook_description: RichTextLabel = %hook_description +@onready var _btn_move_up: Button = %hook_actions/btn_move_up +@onready var _btn_move_down: Button = %hook_actions/btn_move_down +@onready var _btn_delete: Button = %hook_actions/btn_delete_hook +@onready var _select_hook_dlg: FileDialog = %select_hook_dlg +@onready var _error_msg_popup :AcceptDialog = %error_msg_popup + +var _selected_hook_item: TreeItem = null +var _root: TreeItem +var _system_box_style: StyleBoxFlat +var _priority_box_style: StyleBoxFlat + +func _ready() -> void: + _setup_styles() + _setup_buttons() + _setup_tree() + _load_registered_hooks() + + +func _setup_styles() -> void: + _system_box_style = StyleBoxFlat.new() + _system_box_style.bg_color = Color(1.0, 0.76, 0.03, 1) + _system_box_style.corner_radius_top_left = 6 + _system_box_style.corner_radius_top_right = 6 + _system_box_style.corner_radius_bottom_left = 6 + _system_box_style.corner_radius_bottom_right = 6 + _priority_box_style = _system_box_style.duplicate() + _priority_box_style.bg_color = Color(0.26, 0.54, 0.89, 1) + + +func _setup_buttons() -> void: + #if Engine.is_editor_hint(): + # _btn_move_up.icon = GdUnitUiTools.get_icon("MoveUp") + # _btn_move_down.icon = GdUnitUiTools.get_icon("MoveDown") + # _btn_add.icon = GdUnitUiTools.get_icon("Add") + # _btn_delete.icon = GdUnitUiTools.get_icon("Remove") + pass + + +func _setup_tree() -> void: + _hooks_tree.clear() + _root = _hooks_tree.create_item() + _hooks_tree.set_columns(2) + _hooks_tree.set_column_custom_minimum_width(1, 32) + _hooks_tree.set_column_expand(1, false) + _hooks_tree.set_hide_root(true) + _hooks_tree.set_hide_folding(true) + _hooks_tree.set_select_mode(Tree.SELECT_SINGLE) + _hooks_tree.item_selected.connect(_on_hook_selected) + _hooks_tree.item_edited.connect(_on_item_edited) + + +func _load_registered_hooks() -> void: + var hook_service := GdUnitTestSessionHookService.instance() + for hook: GdUnitTestSessionHook in hook_service.enigne_hooks: + _create_hook_tree_item(hook) + + # Select first item if any + if _root.get_child_count() > 0: + var first_item: TreeItem = _root.get_first_child() + first_item.select(0) + _on_hook_selected() + + +func _create_hook_tree_item(hook: GdUnitTestSessionHook) -> TreeItem: + var item: TreeItem = _hooks_tree.create_item(_root) + item.set_custom_minimum_height(26) + # Column 0: Hook info with custom drawing + item.set_cell_mode(0, TreeItem.CELL_MODE_CUSTOM) + item.set_custom_draw_callback(0, _draw_hook_item) + item.set_editable(0, false) + item.set_metadata(0, hook) + # Column 1: Checkbox for enable/disable + item.set_cell_mode(1, TreeItem.CELL_MODE_CHECK) + item.set_checked(1, GdUnitTestSessionHookService.is_enabled(hook)) + item.set_editable(1, true) + item.set_custom_bg_color(1, _hook_bg_color(hook)) + item.set_tooltip_text(1, "Enable/Disable the Hook") + item.propagate_check(1) + + if _is_system_hook(hook): + item.set_tooltip_text(0, "System hook - (Read-only)") + else: + item.set_tooltip_text(0, "User hook") + return item + + +func _hook_bg_color(hook: GdUnitTestSessionHook) -> Color: + if _is_system_hook(hook): + return Color(0.133, 0.118, 0.090, 1) # Brownish background for system hooks + return Color(0.176, 0.196, 0.235, 1) # Dark background #2d3142 + + +func _draw_hook_item(item: TreeItem, rect: Rect2) -> void: + var hook := _get_hook(item) + var is_system := _is_system_hook(hook) + var is_selected := item == _selected_hook_item + + # Draw background + var bg_color := _hook_bg_color(hook) # Dark background #2d3142 + if is_selected: + bg_color = bg_color.lerp(Color(0.2, 0.4, 0.6, 0.3), 0.5) # Blue tint for selection + _hooks_tree.draw_rect(rect, bg_color) + + # Draw left border for system hooks + if is_system: + var border_rect := Rect2(rect.position.x, rect.position.y, 3, rect.size.y) + _hooks_tree.draw_rect(border_rect, Color(1.0, 0.76, 0.03, 1)) # Yellow border + + var font := _hooks_tree.get_theme_default_font() + + # Draw hook name + var hook_name := hook.name + var text_pos := Vector2(rect.position.x + ( 15 if is_system else 12), rect.position.y + 18) + var text_color := Color(0.95, 0.95, 0.95, 1) + _hooks_tree.draw_string(font, text_pos, hook_name, HORIZONTAL_ALIGNMENT_LEFT, -1, 14, text_color) + + # Draw system badge if needed + if is_system: + var badge_x := rect.position.x + rect.end.x - 100 + var badge_y := rect.position.y + 14 + var system_badge_rect := Rect2(badge_x, badge_y-8, 48, 16) + _hooks_tree.draw_style_box(_system_box_style, system_badge_rect) + + var system_text_pos := Vector2(badge_x + 4, badge_y + 4) + var system_font_size := 10 + _hooks_tree.draw_string(font, system_text_pos, "SYSTEM", HORIZONTAL_ALIGNMENT_CENTER, -1, system_font_size, Color(0.1, 0.1, 0.1, 1)) + + +func _create_hook_display_text(hook_name: String, priority: int, is_system: bool) -> String: + var text := hook_name + "\n" + text += "Priority: [color=#4299e1][bgcolor=#4299e1] " + str(priority) + " [/bgcolor][/color]" + + if is_system: + text += " [color=#1a202c][bgcolor=#ffc107] SYSTEM [/bgcolor][/color]" + + return text + + +func _update_hook_description() -> void: + if _selected_hook_item == null: + _hook_description.text = "[i]Select a hook to view its description[/i]" + return + _hook_description.text = _get_hook(_selected_hook_item).description + + +func _update_hook_buttons() -> void: + # Is nothing selected disable the move and delete buttons + if _selected_hook_item == null: + _btn_move_up.disabled = true + _btn_move_down.disabled = true + _btn_delete.disabled = true + return + + var hook := _get_hook(_selected_hook_item) + var is_system := _is_system_hook(hook) + + # Disable the move and delete buttons for system hooks by default + if is_system: + _btn_move_up.disabled = true + _btn_move_down.disabled = true + _btn_delete.disabled = true + return + + var prev_item: TreeItem = _selected_hook_item.get_prev() + var next_item: TreeItem = _selected_hook_item.get_next() + + if prev_item != null: + var prev_hook := _get_hook(prev_item) + _btn_move_up.disabled = _is_system_hook(prev_hook) + + _btn_move_down.disabled = next_item == null + _btn_delete.disabled = false + + +static func _get_hook(item: TreeItem) -> GdUnitTestSessionHook: + return item.get_metadata(0) + + +static func _is_system_hook(hook: GdUnitTestSessionHook) -> bool: + if hook == null: + return false + return hook.get_meta("SYSTEM_HOOK") + + +func _on_hook_selected() -> void: + _selected_hook_item = _hooks_tree.get_selected() + _update_hook_buttons() + _update_hook_description() + + +func _on_item_edited() -> void: + var selected_hook_item := _hooks_tree.get_selected() + if selected_hook_item != null: + var hook := _get_hook(selected_hook_item) + var is_enabled := selected_hook_item.is_checked(1) + GdUnitTestSessionHookService.instance().enable_hook(hook, is_enabled) + + +func _on_btn_add_hook_pressed() -> void: + _select_hook_dlg.show() + + +func _on_select_hook_dlg_file_selected(path: String) -> void: + _select_hook_dlg.set_current_path(path) + _on_select_hook_dlg_confirmed() + + +func _on_select_hook_dlg_confirmed() -> void: + _select_hook_dlg.hide() + var result := GdUnitTestSessionHookService.instance().load_hook(_select_hook_dlg.get_current_path()) + if result.is_error(): + _error_msg_popup.dialog_text = result.error_message() + _error_msg_popup.show() + return + + var hook: GdUnitTestSessionHook = result.value() + result = GdUnitTestSessionHookService.instance().register(hook) + if result.is_error(): + _error_msg_popup.dialog_text = result.error_message() + _error_msg_popup.show() + return + + var hook_added := _create_hook_tree_item(hook) + _hooks_tree.set_selected(hook_added, 0) + + +func _on_btn_delete_hook_pressed() -> void: + if _selected_hook_item != null: + _root.remove_child(_selected_hook_item) + GdUnitTestSessionHookService.instance()\ + .unregister(_get_hook(_selected_hook_item)) + _selected_hook_item = null + _update_hook_buttons() + + +func _on_btn_move_up_pressed() -> void: + var prev := _selected_hook_item.get_prev() + _selected_hook_item.move_before(prev) + GdUnitTestSessionHookService.instance()\ + .move_before(_get_hook(_selected_hook_item), _get_hook(prev)) + _update_hook_buttons() + + +func _on_btn_move_down_pressed() -> void: + var next := _selected_hook_item.get_next() + _selected_hook_item.move_after(next) + GdUnitTestSessionHookService.instance()\ + .move_after(_get_hook(_selected_hook_item), _get_hook(next)) + _update_hook_buttons() diff --git 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+unique_name_in_owner = true +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="hooks_tree" type="Tree" parent="HBoxContainer/hooks_content"] +unique_name_in_owner = true +layout_direction = 2 +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +columns = 2 +hide_folding = true +hide_root = true + +[node name="hook_description" type="RichTextLabel" parent="HBoxContainer/hooks_content"] +unique_name_in_owner = true +custom_minimum_size = Vector2(0, 120) +layout_mode = 2 +size_flags_vertical = 2 +bbcode_enabled = true +text = "The Html test reporting hook." +scroll_active = false + +[node name="hook_actions" type="VBoxContainer" parent="HBoxContainer"] +unique_name_in_owner = true +custom_minimum_size = Vector2(80, 0) +layout_mode = 2 +size_flags_horizontal = 0 +theme_override_constants/separation = 5 + +[node name="btn_move_up" type="Button" parent="HBoxContainer/hook_actions"] +layout_mode = 2 +tooltip_text = "Move hook up in priority" +disabled = true +icon = SubResource("ImageTexture_77fm0") +icon_alignment = 1 + +[node name="btn_move_down" type="Button" parent="HBoxContainer/hook_actions"] +layout_mode = 2 +tooltip_text = "Move hook down in priority" +disabled = true +icon = SubResource("ImageTexture_rewru") +icon_alignment = 1 + +[node name="btn_add_hook" type="Button" parent="HBoxContainer/hook_actions"] +layout_mode = 2 +tooltip_text = "Add new hook" +icon = SubResource("ImageTexture_manhx") +icon_alignment = 1 + +[node name="btn_delete_hook" type="Button" parent="HBoxContainer/hook_actions"] +layout_mode = 2 +tooltip_text = "Delete selected hook" +disabled = true +icon = SubResource("ImageTexture_4h4u1") +icon_alignment = 1 + +[node name="select_hook_dlg" type="FileDialog" parent="."] +unique_name_in_owner = true +disable_3d = true +title = "Open a File" +initial_position = 3 +current_screen = 0 +ok_button_text = "Open" +file_mode = 0 +filters = PackedStringArray("*.gd") + +[node name="error_msg_popup" type="AcceptDialog" parent="."] +unique_name_in_owner = true +initial_position = 3 +current_screen = 0 + +[connection signal="pressed" from="HBoxContainer/hook_actions/btn_move_up" to="." method="_on_btn_move_up_pressed"] +[connection signal="pressed" from="HBoxContainer/hook_actions/btn_move_down" to="." method="_on_btn_move_down_pressed"] +[connection signal="pressed" from="HBoxContainer/hook_actions/btn_add_hook" to="." method="_on_btn_add_hook_pressed"] +[connection signal="pressed" from="HBoxContainer/hook_actions/btn_delete_hook" to="." method="_on_btn_delete_hook_pressed"] +[connection signal="confirmed" from="select_hook_dlg" to="." method="_on_select_hook_dlg_confirmed"] +[connection signal="file_selected" from="select_hook_dlg" to="." method="_on_select_hook_dlg_file_selected"] diff --git a/addons/gdUnit4/src/ui/settings/logo.png b/addons/gdUnit4/src/ui/settings/logo.png new file mode 100644 index 0000000..12de79f Binary files /dev/null and b/addons/gdUnit4/src/ui/settings/logo.png differ diff --git a/addons/gdUnit4/src/ui/settings/logo.png.import b/addons/gdUnit4/src/ui/settings/logo.png.import new file mode 100644 index 0000000..66d29a7 --- /dev/null +++ b/addons/gdUnit4/src/ui/settings/logo.png.import @@ -0,0 +1,40 @@ +[remap] + +importer="texture" +type="CompressedTexture2D" +uid="uid://d2ukt7dja0uud" +path="res://.godot/imported/logo.png-deda0e4ba02a0b9e4e4a830029a5817f.ctex" +metadata={ +"vram_texture": false +} + +[deps] + +source_file="res://addons/gdUnit4/src/ui/settings/logo.png" +dest_files=["res://.godot/imported/logo.png-deda0e4ba02a0b9e4e4a830029a5817f.ctex"] + +[params] + +compress/mode=0 +compress/high_quality=false +compress/lossy_quality=0.7 +compress/uastc_level=0 +compress/rdo_quality_loss=0.0 +compress/hdr_compression=1 +compress/normal_map=0 +compress/channel_pack=0 +mipmaps/generate=false +mipmaps/limit=-1 +roughness/mode=0 +roughness/src_normal="" +process/channel_remap/red=0 +process/channel_remap/green=1 +process/channel_remap/blue=2 +process/channel_remap/alpha=3 +process/fix_alpha_border=true +process/premult_alpha=false +process/normal_map_invert_y=false +process/hdr_as_srgb=false +process/hdr_clamp_exposure=false +process/size_limit=0 +detect_3d/compress_to=1 diff --git a/addons/gdUnit4/src/ui/templates/TestSuiteTemplate.gd b/addons/gdUnit4/src/ui/templates/TestSuiteTemplate.gd new file mode 100644 index 0000000..be5c352 --- /dev/null +++ b/addons/gdUnit4/src/ui/templates/TestSuiteTemplate.gd @@ -0,0 +1,129 @@ +@tool +extends MarginContainer + +@onready var _template_editor :CodeEdit = $VBoxContainer/EdiorLayout/Editor +@onready var _tags_editor :CodeEdit = $Tags/MarginContainer/TextEdit +@onready var _title_bar :Panel = $VBoxContainer/sub_category +@onready var _save_button :Button = $VBoxContainer/Panel/HBoxContainer/Save +@onready var _selected_type :OptionButton = $VBoxContainer/EdiorLayout/Editor/MarginContainer/HBoxContainer/SelectType +@onready var _show_tags :PopupPanel = $Tags + + +var gd_key_words :PackedStringArray = ["extends", "class_name", "const", "var", "onready", "func", "void", "pass"] +var gdunit_key_words :PackedStringArray = ["GdUnitTestSuite", "before", "after", "before_test", "after_test"] +var _selected_template :int + + +func _ready() -> void: + setup_editor_colors() + setup_fonts() + setup_supported_types() + load_template(GdUnitTestSuiteTemplate.TEMPLATE_ID_GD) + setup_tags_help() + + +func _notification(what :int) -> void: + if what == EditorSettings.NOTIFICATION_EDITOR_SETTINGS_CHANGED: + setup_fonts() + + +func setup_editor_colors() -> void: + if not Engine.is_editor_hint(): + return + + var background_color := get_editor_color("text_editor/theme/highlighting/background_color", Color(0.1155, 0.132, 0.1595, 1)) + var text_color := get_editor_color("text_editor/theme/highlighting/text_color", Color(0.8025, 0.81, 0.8225, 1)) + var selection_color := get_editor_color("text_editor/theme/highlighting/selection_color", Color(0.44, 0.73, 0.98, 0.4)) + + for e :CodeEdit in [_template_editor, _tags_editor]: + var editor :CodeEdit = e + editor.add_theme_color_override("background_color", background_color) + editor.add_theme_color_override("font_color", text_color) + editor.add_theme_color_override("font_readonly_color", text_color) + editor.add_theme_color_override("font_selected_color", selection_color) + setup_highlighter(editor) + + +func setup_highlighter(editor :CodeEdit) -> void: + var highlighter := CodeHighlighter.new() + editor.set_syntax_highlighter(highlighter) + var number_color := get_editor_color("text_editor/theme/highlighting/number_color", Color(0.63, 1, 0.88, 1)) + var symbol_color := get_editor_color("text_editor/theme/highlighting/symbol_color", Color(0.67, 0.79, 1, 1)) + var function_color := get_editor_color("text_editor/theme/highlighting/function_color", Color(0.34, 0.7, 1, 1)) + var member_variable_color := get_editor_color("text_editor/theme/highlighting/member_variable_color", Color(0.736, 0.88, 1, 1)) + var comment_color := get_editor_color("text_editor/theme/highlighting/comment_color", Color(0.8025, 0.81, 0.8225, 0.5)) + var keyword_color := get_editor_color("text_editor/theme/highlighting/keyword_color", Color(1, 0.44, 0.52, 1)) + var base_type_color := get_editor_color("text_editor/theme/highlighting/base_type_color", Color(0.26, 1, 0.76, 1)) + var annotation_color := get_editor_color("text_editor/theme/highlighting/gdscript/annotation_color", Color(1, 0.7, 0.45, 1)) + + highlighter.clear_color_regions() + highlighter.clear_keyword_colors() + highlighter.add_color_region("#", "", comment_color, true) + highlighter.add_color_region("${", "}", Color.YELLOW) + highlighter.add_color_region("'", "'", Color.YELLOW) + highlighter.add_color_region("\"", "\"", Color.YELLOW) + highlighter.number_color = number_color + highlighter.symbol_color = symbol_color + highlighter.function_color = function_color + highlighter.member_variable_color = member_variable_color + highlighter.add_keyword_color("@", annotation_color) + highlighter.add_keyword_color("warning_ignore", annotation_color) + for word in gd_key_words: + highlighter.add_keyword_color(word, keyword_color) + for word in gdunit_key_words: + highlighter.add_keyword_color(word, base_type_color) + + +## Using this function to avoid null references to colors on inital Godot installations. +## For more details show https://github.com/MikeSchulze/gdUnit4/issues/533 +func get_editor_color(property_name: String, default: Color) -> Color: + var settings := EditorInterface.get_editor_settings() + return settings.get_setting(property_name) if settings.has_setting(property_name) else default + + +func setup_fonts() -> void: + if _template_editor: + @warning_ignore("return_value_discarded") + GdUnitFonts.init_fonts(_template_editor) + var font_size := GdUnitFonts.init_fonts(_tags_editor) + _title_bar.size.y = font_size + 16 + _title_bar.custom_minimum_size.y = font_size + 16 + + +func setup_supported_types() -> void: + _selected_type.clear() + _selected_type.add_item("GD - GDScript", GdUnitTestSuiteTemplate.TEMPLATE_ID_GD) + _selected_type.add_item("C# - CSharpScript", GdUnitTestSuiteTemplate.TEMPLATE_ID_CS) + + +func setup_tags_help() -> void: + _tags_editor.set_text(GdUnitTestSuiteTemplate.load_tags(_selected_template)) + + +func load_template(template_id :int) -> void: + _selected_template = template_id + _template_editor.set_text(GdUnitTestSuiteTemplate.load_template(template_id)) + + +func _on_Restore_pressed() -> void: + _template_editor.set_text(GdUnitTestSuiteTemplate.default_template(_selected_template)) + GdUnitTestSuiteTemplate.reset_to_default(_selected_template) + _save_button.disabled = true + + +func _on_Save_pressed() -> void: + GdUnitTestSuiteTemplate.save_template(_selected_template, _template_editor.get_text()) + _save_button.disabled = true + + +func _on_Tags_pressed() -> void: + _show_tags.popup_centered_ratio(.5) + + +func _on_Editor_text_changed() -> void: + _save_button.disabled = false + + +func _on_SelectType_item_selected(index :int) -> void: + load_template(_selected_type.get_item_id(index)) + setup_tags_help() diff --git a/addons/gdUnit4/src/ui/templates/TestSuiteTemplate.gd.uid b/addons/gdUnit4/src/ui/templates/TestSuiteTemplate.gd.uid new file mode 100644 index 0000000..a09ef6a --- /dev/null +++ b/addons/gdUnit4/src/ui/templates/TestSuiteTemplate.gd.uid @@ -0,0 +1 @@ +uid://b46arvmkmkbrg diff --git a/addons/gdUnit4/src/ui/templates/TestSuiteTemplate.tscn b/addons/gdUnit4/src/ui/templates/TestSuiteTemplate.tscn new file mode 100644 index 0000000..6360a2a --- /dev/null +++ b/addons/gdUnit4/src/ui/templates/TestSuiteTemplate.tscn @@ -0,0 +1,238 @@ +[gd_scene load_steps=4 format=3 uid="uid://dte0m2endcgtu"] + +[ext_resource type="Script" uid="uid://b46arvmkmkbrg" path="res://addons/gdUnit4/src/ui/templates/TestSuiteTemplate.gd" id="1"] + +[sub_resource type="CodeHighlighter" id="CodeHighlighter_6gsdy"] +number_color = Color(0.63, 1, 0.88, 1) +symbol_color = Color(0.67, 0.79, 1, 1) +function_color = Color(0.34, 0.7, 1, 1) +member_variable_color = Color(0.736, 0.88, 1, 1) +keyword_colors = { +"@": Color(1, 0.7, 0.45, 1), +"GdUnitTestSuite": Color(0.26, 1, 0.76, 1), +"after": Color(0.26, 1, 0.76, 1), +"after_test": Color(0.26, 1, 0.76, 1), +"before": Color(0.26, 1, 0.76, 1), +"before_test": Color(0.26, 1, 0.76, 1), +"class_name": Color(1, 0.44, 0.52, 1), +"const": Color(1, 0.44, 0.52, 1), +"extends": Color(1, 0.44, 0.52, 1), +"func": Color(1, 0.44, 0.52, 1), +"onready": Color(1, 0.44, 0.52, 1), +"pass": Color(1, 0.44, 0.52, 1), +"var": Color(1, 0.44, 0.52, 1), +"void": Color(1, 0.44, 0.52, 1), +"warning_ignore": Color(1, 0.7, 0.45, 1) +} +color_regions = { +"\" \"": Color(1, 1, 0, 1), +"#": Color(0.8025, 0.81, 0.8225, 0.5), +"${ }": Color(1, 1, 0, 1), +"' '": Color(1, 1, 0, 1) +} + +[sub_resource type="CodeHighlighter" id="CodeHighlighter_oi772"] +number_color = Color(0.63, 1, 0.88, 1) +symbol_color = Color(0.67, 0.79, 1, 1) +function_color = Color(0.34, 0.7, 1, 1) +member_variable_color = Color(0.736, 0.88, 1, 1) +keyword_colors = { +"@": Color(1, 0.7, 0.45, 1), +"GdUnitTestSuite": Color(0.26, 1, 0.76, 1), +"after": Color(0.26, 1, 0.76, 1), +"after_test": Color(0.26, 1, 0.76, 1), +"before": Color(0.26, 1, 0.76, 1), +"before_test": Color(0.26, 1, 0.76, 1), +"class_name": Color(1, 0.44, 0.52, 1), +"const": Color(1, 0.44, 0.52, 1), +"extends": Color(1, 0.44, 0.52, 1), +"func": Color(1, 0.44, 0.52, 1), +"onready": Color(1, 0.44, 0.52, 1), +"pass": Color(1, 0.44, 0.52, 1), +"var": Color(1, 0.44, 0.52, 1), +"void": Color(1, 0.44, 0.52, 1), +"warning_ignore": Color(1, 0.7, 0.45, 1) +} +color_regions = { +"\" \"": Color(1, 1, 0, 1), +"#": Color(0.8025, 0.81, 0.8225, 0.5), +"${ }": Color(1, 1, 0, 1), +"' '": Color(1, 1, 0, 1) +} + +[node name="TestSuiteTemplate" type="MarginContainer"] +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +script = ExtResource("1") + +[node name="VBoxContainer" type="VBoxContainer" parent="."] +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="sub_category" type="Panel" parent="VBoxContainer"] +custom_minimum_size = Vector2(0, 29) +layout_mode = 2 +size_flags_horizontal = 3 + +[node name="Label" type="Label" parent="VBoxContainer/sub_category"] +layout_mode = 1 +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +offset_left = 4.0 +offset_right = 4.0 +offset_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 +text = "Test Suite Template +" + +[node name="EdiorLayout" type="VBoxContainer" parent="VBoxContainer"] +layout_mode = 2 +size_flags_vertical = 3 + +[node name="Editor" type="CodeEdit" parent="VBoxContainer/EdiorLayout"] +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +theme_override_colors/font_selected_color = Color(0.44, 0.73, 0.98, 0.4) +theme_override_colors/font_color = Color(0.8025, 0.81, 0.8225, 1) +theme_override_colors/font_readonly_color = Color(0.8025, 0.81, 0.8225, 1) +theme_override_colors/background_color = Color(0.115499996, 0.132, 0.15949999, 1) +theme_override_font_sizes/font_size = 13 +text = "# GdUnit generated TestSuite +class_name ${suite_class_name} +extends GdUnitTestSuite +@warning_ignore('unused_parameter') +@warning_ignore('return_value_discarded') + +# TestSuite generated from +const __source: String = '${source_resource_path}' +" +syntax_highlighter = SubResource("CodeHighlighter_6gsdy") + +[node name="MarginContainer" type="MarginContainer" parent="VBoxContainer/EdiorLayout/Editor"] +layout_mode = 1 +anchors_preset = 12 +anchor_top = 1.0 +anchor_right = 1.0 +anchor_bottom = 1.0 +offset_top = -31.0 +grow_horizontal = 2 +grow_vertical = 0 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="HBoxContainer" type="HBoxContainer" parent="VBoxContainer/EdiorLayout/Editor/MarginContainer"] +layout_mode = 2 +size_flags_vertical = 8 +alignment = 2 + +[node name="Tags" type="Button" parent="VBoxContainer/EdiorLayout/Editor/MarginContainer/HBoxContainer"] +layout_mode = 2 +tooltip_text = "Shows supported tags." +text = "Supported Tags" + +[node name="SelectType" type="OptionButton" parent="VBoxContainer/EdiorLayout/Editor/MarginContainer/HBoxContainer"] +layout_mode = 2 +tooltip_text = "Select the script type specific template." +selected = 0 +item_count = 2 +popup/item_0/text = "GD - GDScript" +popup/item_0/id = 1000 +popup/item_1/text = "C# - CSharpScript" +popup/item_1/id = 2000 + +[node name="Panel" type="MarginContainer" parent="VBoxContainer"] +layout_mode = 2 +size_flags_horizontal = 3 + +[node name="HBoxContainer" type="HBoxContainer" parent="VBoxContainer/Panel"] +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +alignment = 2 + +[node name="Restore" type="Button" parent="VBoxContainer/Panel/HBoxContainer"] +layout_mode = 2 +text = "Restore" + +[node name="Save" type="Button" parent="VBoxContainer/Panel/HBoxContainer"] +layout_mode = 2 +disabled = true +text = "Save" + +[node name="Tags" type="PopupPanel" parent="."] +size = Vector2i(300, 100) +unresizable = false +content_scale_aspect = 4 + +[node name="MarginContainer" type="MarginContainer" parent="Tags"] +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +offset_left = 4.0 +offset_top = 4.0 +offset_right = 296.0 +offset_bottom = 96.0 +grow_horizontal = 2 +grow_vertical = 2 + +[node name="TextEdit" type="CodeEdit" parent="Tags/MarginContainer"] +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +theme_override_colors/font_selected_color = Color(0.44, 0.73, 0.98, 0.4) +theme_override_colors/font_color = Color(0.8025, 0.81, 0.8225, 1) +theme_override_colors/font_readonly_color = Color(0.8025, 0.81, 0.8225, 1) +theme_override_colors/background_color = Color(0.115499996, 0.132, 0.15949999, 1) +theme_override_font_sizes/font_size = 13 +text = " + GdScript Tags are replaced when the test-suite is created. + + # The class name of the test-suite, formed from the source script. + ${suite_class_name} + # is used to build the test suite class name + class_name ${suite_class_name} + extends GdUnitTestSuite + + + # The class name in pascal case, formed from the source script. + ${source_class} + # can be used to create the class e.g. for source 'MyClass' + var my_test_class := ${source_class}.new() + # will be result in + var my_test_class := MyClass.new() + + # The class as variable name in snake case, formed from the source script. + ${source_var} + # Can be used to build the variable name e.g. for source 'MyClass' + var ${source_var} := ${source_class}.new() + # will be result in + var my_class := MyClass.new() + + # The full resource path from which the file was created. + ${source_resource_path} + # Can be used to load the script in your test + var my_script := load(${source_resource_path}) + # will be result in + var my_script := load(\"res://folder/my_class.gd\") +" +editable = false +context_menu_enabled = false +shortcut_keys_enabled = false +virtual_keyboard_enabled = false +scroll_vertical = 30.0 +syntax_highlighter = SubResource("CodeHighlighter_oi772") + +[connection signal="text_changed" from="VBoxContainer/EdiorLayout/Editor" to="." method="_on_Editor_text_changed"] +[connection signal="pressed" from="VBoxContainer/EdiorLayout/Editor/MarginContainer/HBoxContainer/Tags" to="." method="_on_Tags_pressed"] +[connection signal="item_selected" from="VBoxContainer/EdiorLayout/Editor/MarginContainer/HBoxContainer/SelectType" to="." method="_on_SelectType_item_selected"] +[connection signal="pressed" from="VBoxContainer/Panel/HBoxContainer/Restore" to="." method="_on_Restore_pressed"] +[connection signal="pressed" from="VBoxContainer/Panel/HBoxContainer/Save" to="." method="_on_Save_pressed"] diff --git a/addons/gdUnit4/src/update/GdMarkDownReader.gd b/addons/gdUnit4/src/update/GdMarkDownReader.gd new file mode 100644 index 0000000..dab19e4 --- /dev/null +++ b/addons/gdUnit4/src/update/GdMarkDownReader.gd @@ -0,0 +1,405 @@ +@tool +extends RefCounted + +const GdUnitUpdateClient = preload("res://addons/gdUnit4/src/update/GdUnitUpdateClient.gd") + +const FONT_H1 := 22 +const FONT_H2 := 20 +const FONT_H3 := 18 +const FONT_H4 := 16 +const FONT_H5 := 14 +const FONT_H6 := 12 + +const HORIZONTAL_RULE := "[img=4000x2]res://addons/gdUnit4/src/update/assets/horizontal-line2.png[/img]" +const HEADER_RULE := "[font_size=%d]$1[/font_size]" +const HEADER_CENTERED_RULE := "[font_size=%d][center]$1[/center][/font_size]" + +const image_download_folder := "res://addons/gdUnit4/tmp-update/" + +const exclude_font_size := "\b(?!(?:(font_size))\b)" + +var md_replace_patterns := [ + # comments + [regex("(?m)^\\n?\\s*\\s*\\n?"), ""], + + # horizontal rules + [regex("(?m)^[ ]{0,3}---$"), HORIZONTAL_RULE], + [regex("(?m)^[ ]{0,3}___$"), HORIZONTAL_RULE], + [regex("(?m)^[ ]{0,3}\\*\\*\\*$"), HORIZONTAL_RULE], + + # headers + [regex("(?m)^###### (.*)"), HEADER_RULE % FONT_H6], + [regex("(?m)^##### (.*)"), HEADER_RULE % FONT_H5], + [regex("(?m)^#### (.*)"), HEADER_RULE % FONT_H4], + [regex("(?m)^### (.*)"), HEADER_RULE % FONT_H3], + [regex("(?m)^## (.*)"), (HEADER_RULE + HORIZONTAL_RULE) % FONT_H2], + [regex("(?m)^# (.*)"), (HEADER_RULE + HORIZONTAL_RULE) % FONT_H1], + [regex("(?m)^(.+)=={2,}$"), HEADER_RULE % FONT_H1], + [regex("(?m)^(.+)--{2,}$"), HEADER_RULE % FONT_H2], + # html headers + [regex("

((.*?\\R?)+)<\\/h1>"), (HEADER_RULE + HORIZONTAL_RULE) % FONT_H1], + [regex("((.*?\\R?)+)<\\/h1>"), (HEADER_CENTERED_RULE + HORIZONTAL_RULE) % FONT_H1], + [regex("

((.*?\\R?)+)<\\/h2>"), (HEADER_RULE + HORIZONTAL_RULE) % FONT_H2], + [regex("((.*?\\R?)+)<\\/h2>"), (HEADER_CENTERED_RULE + HORIZONTAL_RULE) % FONT_H1], + [regex("

((.*?\\R?)+)<\\/h3>"), HEADER_RULE % FONT_H3], + [regex("((.*?\\R?)+)<\\/h3>"), HEADER_CENTERED_RULE % FONT_H3], + [regex("

((.*?\\R?)+)<\\/h4>"), HEADER_RULE % FONT_H4], + [regex("((.*?\\R?)+)<\\/h4>"), HEADER_CENTERED_RULE % FONT_H4], + [regex("
((.*?\\R?)+)<\\/h5>"), HEADER_RULE % FONT_H5], + [regex("((.*?\\R?)+)<\\/h5>"), HEADER_CENTERED_RULE % FONT_H5], + [regex("
((.*?\\R?)+)<\\/h6>"), HEADER_RULE % FONT_H6], + [regex("((.*?\\R?)+)<\\/h6>"), HEADER_CENTERED_RULE % FONT_H6], + + # asterics + #[regex("(\\*)"), "xxx$1xxx"], + + # extract/compile image references + [regex("!\\[(.*?)\\]\\[(.*?)\\]"), process_image_references], + # extract images with path and optional tool tip + [regex("!\\[(.*?)\\]\\((.*?)(( )+(.*?))?\\)"), process_image], + + # links + [regex("([!]|)\\[(.+)\\]\\(([^ ]+?)\\)"), "[url={\"url\":\"$3\"}]$2[/url]"], + # links with tool tip + [regex("([!]|)\\[(.+)\\]\\(([^ ]+?)( \"(.+)\")?\\)"), "[url={\"url\":\"$3\", \"tool_tip\":\"$5\"}]$2[/url]"], + # links to github, as shorted link + [regex("(https://github.*/?/(\\S+))"), '[url={"url":"$1", "tool_tip":"$1"}]#$2[/url]'], + + # embeded text + [regex("(?m)^[ ]{0,3}>(.*?)$"), "[img=50x14]res://addons/gdUnit4/src/update/assets/embedded.png[/img][i]$1[/i]"], + + # italic + bold font + [regex("[_]{3}(.*?)[_]{3}"), "[i][b]$1[/b][/i]"], + [regex("[\\*]{3}(.*?)[\\*]{3}"), "[i][b]$1[/b][/i]"], + # bold font + [regex("(.*?)<\\/b>"), "[b]$1[/b]"], + [regex("[_]{2}(.*?)[_]{2}"), "[b]$1[/b]"], + [regex("[\\*]{2}(.*?)[\\*]{2}"), "[b]$1[/b]"], + # italic font + [regex("(.*?)<\\/i>"), "[i]$1[/i]"], + [regex(exclude_font_size+"_(.*?)_"), "[i]$1[/i]"], + [regex("\\*(.*?)\\*"), "[i]$1[/i]"], + + # strikethrough font + [regex("(.*?)"), "[s]$1[/s]"], + [regex("~~(.*?)~~"), "[s]$1[/s]"], + [regex("~(.*?)~"), "[s]$1[/s]"], + + # handling lists + # using an image for dots + [regex("(?m)^[ ]{0,1}[*\\-+] (.*)$"), list_replace(0)], + [regex("(?m)^[ ]{2,3}[*\\-+] (.*)$"), list_replace(1)], + [regex("(?m)^[ ]{4,5}[*\\-+] (.*)$"), list_replace(2)], + [regex("(?m)^[ ]{6,7}[*\\-+] (.*)$"), list_replace(3)], + [regex("(?m)^[ ]{8,9}[*\\-+] (.*)$"), list_replace(4)], + + # code + [regex("``([\\s\\S]*?)``"), code_block("$1")], + [regex("`([\\s\\S]*?)`{1,2}"), code_block("$1")], +] + +var code_block_patterns := [ + # code blocks, code blocks looks not like code blocks in richtext + [regex("```(javascript|python|shell|gdscript|gd)([\\s\\S]*?\n)```"), code_block("$2", true)], +] + +var _img_replace_regex := RegEx.new() +var _image_urls := PackedStringArray() +var _on_table_tag := false +var _client: GdUnitUpdateClient + + +static func regex(pattern: String) -> RegEx: + var regex_ := RegEx.new() + var err := regex_.compile(pattern) + if err != OK: + push_error("error '%s' checked pattern '%s'" % [err, pattern]) + return null + return regex_ + + +func _init() -> void: + @warning_ignore("return_value_discarded") + _img_replace_regex.compile("\\[img\\]((.*?))\\[/img\\]") + + +func set_http_client(client: GdUnitUpdateClient) -> void: + _client = client + + +@warning_ignore("return_value_discarded") +func _notification(what: int) -> void: + if what == NOTIFICATION_PREDELETE: + # finally remove_at the downloaded images + for image in _image_urls: + DirAccess.remove_absolute(image) + DirAccess.remove_absolute(image + ".import") + + +func list_replace(indent: int) -> String: + var replace_pattern := "[img=12x12]res://addons/gdUnit4/src/update/assets/dot2.png[/img]" if indent %2 else "[img=12x12]res://addons/gdUnit4/src/update/assets/dot1.png[/img]" + replace_pattern += " $1" + + for index in indent: + replace_pattern = replace_pattern.insert(0, " ") + return replace_pattern + + +func code_block(replace: String, border: bool = false) -> String: + if border: + return """ + [img=1400x14]res://addons/gdUnit4/src/update/assets/border_top.png[/img] + [indent][color=GRAY][font_size=16]%s[/font_size][/color][/indent] + [img=1400x14]res://addons/gdUnit4/src/update/assets/border_bottom.png[/img] + """.dedent() % replace + return "[code][bgcolor=DARK_SLATE_GRAY][color=GRAY][font_size=16]%s[/font_size][/color][/bgcolor][/code]" % replace + + +func convert_text(input: String) -> String: + input = process_tables(input) + + for pattern: Array in md_replace_patterns: + var regex_: RegEx = pattern[0] + var bb_replace: Variant = pattern[1] + if bb_replace is Callable: + @warning_ignore("unsafe_method_access") + input = await bb_replace.call(regex_, input) + else: + @warning_ignore("unsafe_cast") + input = regex_.sub(input, bb_replace as String, true) + return input + + +func convert_code_block(input: String) -> String: + for pattern: Array in code_block_patterns: + var regex_: RegEx = pattern[0] + var bb_replace: Variant = pattern[1] + if bb_replace is Callable: + @warning_ignore("unsafe_method_access") + input = await bb_replace.call(regex_, input) + else: + @warning_ignore("unsafe_cast") + input = regex_.sub(input, bb_replace as String, true) + return input + + +func to_bbcode(input: String) -> String: + var re := regex("(?m)```[\\s\\S]*?```") + var current_pos := 0 + var as_bbcode := "" + + # we split by code blocks to handle this blocks customized + for result in re.search_all(input): + # Add text before code block + if result.get_start() > current_pos: + as_bbcode += await convert_text(input.substr(current_pos, result.get_start() - current_pos)) + # Add code block + as_bbcode += await convert_code_block(result.get_string()) + current_pos = result.get_end() + + # Add remaining text after last code block + if current_pos < input.length(): + as_bbcode += await convert_text(input.substr(current_pos)) + return as_bbcode + + +func process_tables(input: String) -> String: + var bbcode := PackedStringArray() + var lines: Array[String] = Array(input.split("\n") as Array, TYPE_STRING, "", null) + while not lines.is_empty(): + if is_table(lines[0]): + bbcode.append_array(parse_table(lines)) + continue + @warning_ignore("return_value_discarded", "unsafe_cast") + bbcode.append(lines.pop_front() as String) + return "\n".join(bbcode) + + +class GdUnitMDReaderTable: + var _columns: int + var _rows: Array[Row] = [] + + class Row: + var _cells := PackedStringArray() + + + func _init(cells: PackedStringArray, columns: int) -> void: + _cells = cells + for i in range(_cells.size(), columns): + @warning_ignore("return_value_discarded") + _cells.append("") + + + func to_bbcode(cell_sizes: PackedInt32Array, bold: bool) -> String: + var cells := PackedStringArray() + for cell_index in _cells.size(): + var cell: String = _cells[cell_index] + if cell.strip_edges() == "--": + cell = create_line(cell_sizes[cell_index]) + if bold: + cell = "[b]%s[/b]" % cell + @warning_ignore("return_value_discarded") + cells.append("[cell]%s[/cell]" % cell) + return "|".join(cells) + + + func create_line(length: int) -> String: + var line := "" + for i in length: + line += "-" + return line + + + func _init(columns: int) -> void: + _columns = columns + + + func parse_row(line :String) -> bool: + # is line containing cells? + if line.find("|") == -1: + return false + _rows.append(Row.new(line.split("|"), _columns)) + return true + + + func calculate_max_cell_sizes() -> PackedInt32Array: + var cells_size := PackedInt32Array() + for column in _columns: + @warning_ignore("return_value_discarded") + cells_size.append(0) + + for row_index in _rows.size(): + var row: Row = _rows[row_index] + for cell_index in row._cells.size(): + var cell_size: int = cells_size[cell_index] + var size := row._cells[cell_index].length() + if size > cell_size: + cells_size[cell_index] = size + return cells_size + + + @warning_ignore("return_value_discarded") + func to_bbcode() -> PackedStringArray: + var cell_sizes := calculate_max_cell_sizes() + var bb_code := PackedStringArray() + + bb_code.append("[table=%d]" % _columns) + for row_index in _rows.size(): + bb_code.append(_rows[row_index].to_bbcode(cell_sizes, row_index==0)) + bb_code.append("[/table]\n") + return bb_code + + +func parse_table(lines: Array) -> PackedStringArray: + var line: String = lines[0] + var table := GdUnitMDReaderTable.new(line.count("|") + 1) + while not lines.is_empty(): + line = lines.pop_front() + if not table.parse_row(line): + break + return table.to_bbcode() + + +func is_table(line: String) -> bool: + return line.find("|") != -1 + + +func open_table(line: String) -> String: + _on_table_tag = true + return "[table=%d]" % (line.count("|") + 1) + + +func close_table() -> String: + _on_table_tag = false + return "[/table]" + + +func extract_cells(line: String, bold := false) -> String: + var cells := "" + for cell in line.split("|"): + if bold: + cell = "[b]%s[/b]" % cell + cells += "[cell]%s[/cell]" % cell + return cells + + +func process_image_references(p_regex: RegEx, p_input: String) -> String: + #return p_input + + # exists references? + var matches := p_regex.search_all(p_input) + if matches.is_empty(): + return p_input + # collect image references and remove_at it + var references := Dictionary() + var link_regex := regex("\\[(\\S+)\\]:(\\S+)([ ]\"(.*)\")?") + # create copy of original source to replace checked it + var input := p_input.replace("\r", "") + var extracted_references := p_input.replace("\r", "") + for reg_match in link_regex.search_all(input): + var line := reg_match.get_string(0) + "\n" + var ref := reg_match.get_string(1) + #var topl_tip = reg_match.get_string(4) + # collect reference and url + references[ref] = reg_match.get_string(2) + extracted_references = extracted_references.replace(line, "") + + # replace image references by collected url's + for reference_key: String in references.keys(): + var regex_key := regex("\\](\\[%s\\])" % reference_key) + for reg_match in regex_key.search_all(extracted_references): + var ref: String = reg_match.get_string(0) + var image_url: String = "](%s)" % references.get(reference_key) + extracted_references = extracted_references.replace(ref, image_url) + return extracted_references + + +@warning_ignore("return_value_discarded") +func process_image(p_regex: RegEx, p_input: String) -> String: + #return p_input + var to_replace := PackedStringArray() + var tool_tips := PackedStringArray() + # find all matches + var matches := p_regex.search_all(p_input) + if matches.is_empty(): + return p_input + for reg_match in matches: + # grap the parts to replace and store temporay because a direct replace will distort the offsets + to_replace.append(p_input.substr(reg_match.get_start(0), reg_match.get_end(0))) + # grap optional tool tips + tool_tips.append(reg_match.get_string(5)) + # finally replace all findings + for replace in to_replace: + var re := p_regex.sub(replace, "[img]$2[/img]") + p_input = p_input.replace(replace, re) + return await _process_external_image_resources(p_input) + + +func _process_external_image_resources(input: String) -> String: + @warning_ignore("return_value_discarded") + DirAccess.make_dir_recursive_absolute(image_download_folder) + # scan all img for external resources and download it + for value in _img_replace_regex.search_all(input): + if value.get_group_count() >= 1: + var image_url: String = value.get_string(1) + # if not a local resource we need to download it + if image_url.begins_with("http"): + if OS.is_stdout_verbose(): + prints("download image:", image_url) + var response := await _client.request_image(image_url) + if response.status() == 200: + var image := Image.new() + var error := image.load_png_from_buffer(response.get_body()) + if error != OK: + prints("Error creating image from response", error) + # replace characters where format characters + var new_url := image_download_folder + image_url.get_file().replace("_", "-") + if new_url.get_extension() != 'png': + new_url = new_url + '.png' + var err := image.save_png(new_url) + if err: + push_error("Can't save image to '%s'. Error: %s" % [new_url, error_string(err)]) + @warning_ignore("return_value_discarded") + _image_urls.append(new_url) + input = input.replace(image_url, new_url) + return input diff --git a/addons/gdUnit4/src/update/GdMarkDownReader.gd.uid b/addons/gdUnit4/src/update/GdMarkDownReader.gd.uid new file mode 100644 index 0000000..0391df7 --- /dev/null +++ b/addons/gdUnit4/src/update/GdMarkDownReader.gd.uid @@ -0,0 +1 @@ +uid://ba4mkwcrm3olg diff --git a/addons/gdUnit4/src/update/GdUnitPatch.gd b/addons/gdUnit4/src/update/GdUnitPatch.gd new file mode 100644 index 0000000..daa20f7 --- /dev/null +++ b/addons/gdUnit4/src/update/GdUnitPatch.gd @@ -0,0 +1,20 @@ +class_name GdUnitPatch +extends RefCounted + +const PATCH_VERSION = "patch_version" + +var _version :GdUnit4Version + + +func _init(version_ :GdUnit4Version) -> void: + _version = version_ + + +func version() -> GdUnit4Version: + return _version + + +# this function needs to be implement +func execute() -> bool: + push_error("The function 'execute()' is not implemented at %s" % self) + return false diff --git a/addons/gdUnit4/src/update/GdUnitPatch.gd.uid b/addons/gdUnit4/src/update/GdUnitPatch.gd.uid new file mode 100644 index 0000000..74d6958 --- /dev/null +++ b/addons/gdUnit4/src/update/GdUnitPatch.gd.uid @@ -0,0 +1 @@ +uid://bbsi3sdmd4bn2 diff --git a/addons/gdUnit4/src/update/GdUnitPatcher.gd b/addons/gdUnit4/src/update/GdUnitPatcher.gd new file mode 100644 index 0000000..73d25c9 --- /dev/null +++ b/addons/gdUnit4/src/update/GdUnitPatcher.gd @@ -0,0 +1,75 @@ +class_name GdUnitPatcher +extends RefCounted + + +const _base_dir := "res://addons/gdUnit4/src/update/patches/" + +var _patches := Dictionary() + + +func scan(current :GdUnit4Version) -> void: + _scan(_base_dir, current) + + +func _scan(scan_path :String, current :GdUnit4Version) -> void: + _patches = Dictionary() + var patch_paths := _collect_patch_versions(scan_path, current) + for path in patch_paths: + prints("scan for patches checked '%s'" % path) + _patches[path] = _scan_patches(path) + + +func patch_count() -> int: + var count := 0 + for key :String in _patches.keys(): + @warning_ignore("unsafe_method_access") + count += _patches[key].size() + return count + + +func execute() -> void: + for key :String in _patches.keys(): + for path :String in _patches[key]: + var patch :GdUnitPatch = (load(key + "/" + path) as GDScript).new() + if patch: + prints("execute patch", patch.version(), patch.get_script().resource_path) + if not patch.execute(): + prints("error checked execution patch %s" % key + "/" + path) + + +func _collect_patch_versions(scan_path :String, current :GdUnit4Version) -> PackedStringArray: + if not DirAccess.dir_exists_absolute(scan_path): + return PackedStringArray() + var patches := Array() + var dir := DirAccess.open(scan_path) + if dir != null: + @warning_ignore("return_value_discarded") + dir.list_dir_begin() # TODO GODOT4 fill missing arguments https://github.com/godotengine/godot/pull/40547 + var next := "." + while next != "": + next = dir.get_next() + if next.is_empty() or next == "." or next == "..": + continue + var version := GdUnit4Version.parse(next) + if version.is_greater(current): + patches.append(scan_path + next) + patches.sort() + return PackedStringArray(patches) + + +func _scan_patches(path :String) -> PackedStringArray: + var patches := Array() + var dir := DirAccess.open(path) + if dir != null: + @warning_ignore("return_value_discarded") + dir.list_dir_begin() # TODOGODOT4 fill missing arguments https://github.com/godotengine/godot/pull/40547 + var next := "." + while next != "": + next = dir.get_next() + # step over directory links and .uid files + if next.is_empty() or next == "." or next == ".." or next.ends_with(".uid"): + continue + patches.append(next) + # make sorted from lowest to high version + patches.sort() + return PackedStringArray(patches) diff --git a/addons/gdUnit4/src/update/GdUnitPatcher.gd.uid b/addons/gdUnit4/src/update/GdUnitPatcher.gd.uid new file mode 100644 index 0000000..30d3b4d --- /dev/null +++ b/addons/gdUnit4/src/update/GdUnitPatcher.gd.uid @@ -0,0 +1 @@ +uid://ccffxqpxxxn0r diff --git a/addons/gdUnit4/src/update/GdUnitUpdate.gd b/addons/gdUnit4/src/update/GdUnitUpdate.gd new file mode 100644 index 0000000..97b7fdd --- /dev/null +++ b/addons/gdUnit4/src/update/GdUnitUpdate.gd @@ -0,0 +1,305 @@ +@tool +extends Container + +const GdUnitTools := preload("res://addons/gdUnit4/src/core/GdUnitTools.gd") +const GdUnitUpdateClient := preload("res://addons/gdUnit4/src/update/GdUnitUpdateClient.gd") +const GDUNIT_TEMP := "user://tmp" + +@onready var _progress_content: RichTextLabel = %message +@onready var _progress_bar: TextureProgressBar = %progress +@onready var _cancel_btn: Button = %cancel +@onready var _update_btn: Button = %update +@onready var _spinner_img := GdUnitUiTools.get_spinner() + + +var _debug_mode := false +var _update_client :GdUnitUpdateClient +var _download_url :String + + +func _ready() -> void: + init_progress(6) + + +func _process(_delta :float) -> void: + if _progress_content != null and _progress_content.is_visible_in_tree(): + _progress_content.queue_redraw() + + +func init_progress(max_value: int) -> void: + _cancel_btn.disabled = false + _update_btn.disabled = false + _progress_bar.max_value = max_value + _progress_bar.value = 1 + message_h4("Press [Update] to start.", Color.GREEN, false) + + +func setup(update_client: GdUnitUpdateClient, download_url: String) -> void: + _update_client = update_client + _download_url = download_url + + +func update_progress(message: String, color := Color.GREEN) -> void: + message_h4(message, color) + _progress_bar.value += 1 + if _debug_mode: + await get_tree().create_timer(3).timeout + await get_tree().create_timer(.2).timeout + + +func _colored(message: String, color: Color) -> String: + return "[color=#%s]%s[/color]" % [color.to_html(), message] + + +func message_h4(message: String, color: Color, show_spinner := true) -> void: + _progress_content.clear() + if show_spinner: + _progress_content.add_image(_spinner_img) + _progress_content.append_text(" [font_size=16]%s[/font_size]" % _colored(message, color)) + if _debug_mode: + prints(message) + + +@warning_ignore("return_value_discarded") +func run_update() -> void: + _cancel_btn.disabled = true + _update_btn.disabled = true + + await update_progress("Downloading the update.") + await download_release() + await update_progress("Extracting") + var zip_file := temp_dir() + "/update.zip" + var tmp_path := create_temp_dir("update") + var result :Variant = extract_zip(zip_file, tmp_path) + if result == null: + await update_progress("Update failed! .. Rollback.", Color.INDIAN_RED) + await get_tree().create_timer(3).timeout + _cancel_btn.disabled = false + _update_btn.disabled = false + init_progress(5) + hide() + return + + await update_progress("Uninstall GdUnit4.") + disable_gdUnit() + if not _debug_mode: + GdUnitFileAccess.delete_directory("res://addons/gdUnit4/") + # give editor time to react on deleted files + await get_tree().create_timer(1).timeout + + await update_progress("Install new GdUnit4 version.") + if _debug_mode: + copy_directory(tmp_path, "res://debug") + else: + copy_directory(tmp_path, "res://") + + await update_progress("Patch invalid UID's") + await patch_uids() + + await rebuild_project() + + await update_progress("New GdUnit version successfully installed, Restarting Godot please wait.") + await get_tree().create_timer(3).timeout + enable_gdUnit() + hide() + GdUnitFileAccess.delete_directory("res://addons/.gdunit_update") + restart_godot() + + +func patch_uids(path := "res://addons/gdUnit4/src/") -> void: + var to_reimport: PackedStringArray + for file in DirAccess.get_files_at(path): + var file_path := path.path_join(file) + var ext := file.get_extension() + + if ext == "tscn" or ext == "scn" or ext == "tres" or ext == "res": + message_h4("Patch GdUnit4 scene: '%s'" % file, Color.WEB_GREEN) + remove_uids_from_file(file_path) + elif FileAccess.file_exists(file_path + ".import"): + to_reimport.append(file_path) + + if not to_reimport.is_empty(): + message_h4("Reimport resources '%s'" % ", ".join(to_reimport), Color.WEB_GREEN) + if Engine.is_editor_hint(): + EditorInterface.get_resource_filesystem().reimport_files(to_reimport) + + for dir in DirAccess.get_directories_at(path): + if not dir.begins_with("."): + patch_uids(path.path_join(dir)) + await get_tree().process_frame + + +func remove_uids_from_file(file_path: String) -> bool: + var file := FileAccess.open(file_path, FileAccess.READ) + if file == null: + print("Failed to open file: ", file_path) + return false + + var original_content := file.get_as_text() + file.close() + + # Remove UIDs using regex + var regex := RegEx.new() + regex.compile("(\\[ext_resource[^\\]]*?)\\s+uid=\"uid://[^\"]*\"") + + var modified_content := regex.sub(original_content, "$1", true) + + # Check if any changes were made + if original_content != modified_content: + prints("Patched invalid uid's out in '%s'" % file_path) + # Write the modified content back + file = FileAccess.open(file_path, FileAccess.WRITE) + if file == null: + print("Failed to write to file: ", file_path) + return false + + file.store_string(modified_content) + file.close() + return true + + return false + + +func restart_godot() -> void: + prints("Force restart Godot") + EditorInterface.restart_editor(true) + + +@warning_ignore("return_value_discarded") +func enable_gdUnit() -> void: + var enabled_plugins := PackedStringArray() + if ProjectSettings.has_setting("editor_plugins/enabled"): + enabled_plugins = ProjectSettings.get_setting("editor_plugins/enabled") + if not enabled_plugins.has("res://addons/gdUnit4/plugin.cfg"): + enabled_plugins.append("res://addons/gdUnit4/plugin.cfg") + ProjectSettings.set_setting("editor_plugins/enabled", enabled_plugins) + ProjectSettings.save() + + +func disable_gdUnit() -> void: + EditorInterface.set_plugin_enabled("gdUnit4", false) + + +func temp_dir() -> String: + if not DirAccess.dir_exists_absolute(GDUNIT_TEMP): + @warning_ignore("return_value_discarded") + DirAccess.make_dir_recursive_absolute(GDUNIT_TEMP) + return GDUNIT_TEMP + + +func create_temp_dir(folder_name :String) -> String: + var new_folder := temp_dir() + "/" + folder_name + GdUnitFileAccess.delete_directory(new_folder) + if not DirAccess.dir_exists_absolute(new_folder): + @warning_ignore("return_value_discarded") + DirAccess.make_dir_recursive_absolute(new_folder) + return new_folder + + +func copy_directory(from_dir: String, to_dir: String) -> bool: + if not DirAccess.dir_exists_absolute(from_dir): + printerr("Source directory not found '%s'" % from_dir) + return false + # check if destination exists + if not DirAccess.dir_exists_absolute(to_dir): + # create it + var err := DirAccess.make_dir_recursive_absolute(to_dir) + if err != OK: + printerr("Can't create directory '%s'. Error: %s" % [to_dir, error_string(err)]) + return false + var source_dir := DirAccess.open(from_dir) + var dest_dir := DirAccess.open(to_dir) + if source_dir != null: + @warning_ignore("return_value_discarded") + source_dir.list_dir_begin() + var next := "." + + while next != "": + next = source_dir.get_next() + if next == "" or next == "." or next == "..": + continue + var source := source_dir.get_current_dir() + "/" + next + var dest := dest_dir.get_current_dir() + "/" + next + if source_dir.current_is_dir(): + @warning_ignore("return_value_discarded") + copy_directory(source + "/", dest) + continue + var err := source_dir.copy(source, dest) + if err != OK: + printerr("Error checked copy file '%s' to '%s'" % [source, dest]) + return false + return true + else: + printerr("Directory not found: " + from_dir) + return false + + +func extract_zip(zip_package: String, dest_path: String) -> Variant: + var zip: ZIPReader = ZIPReader.new() + var err := zip.open(zip_package) + if err != OK: + printerr("Extracting `%s` failed! Please collect the error log and report this. Error Code: %s" % [zip_package, err]) + return null + var zip_entries: PackedStringArray = zip.get_files() + # Get base path and step over archive folder + var archive_path := zip_entries[0] + zip_entries.remove_at(0) + + for zip_entry in zip_entries: + var new_file_path: String = dest_path + "/" + zip_entry.replace(archive_path, "") + if zip_entry.ends_with("/"): + @warning_ignore("return_value_discarded") + DirAccess.make_dir_recursive_absolute(new_file_path) + continue + var file: FileAccess = FileAccess.open(new_file_path, FileAccess.WRITE) + file.store_buffer(zip.read_file(zip_entry)) + @warning_ignore("return_value_discarded") + zip.close() + return dest_path + + +func download_release() -> void: + var zip_file := GdUnitFileAccess.temp_dir() + "/update.zip" + var response :GdUnitUpdateClient.HttpResponse + if _debug_mode: + response = GdUnitUpdateClient.HttpResponse.new(200, PackedByteArray()) + zip_file = "res://update.zip" + return + + response = await _update_client.request_zip_package(_download_url, zip_file) + if response.status() != 200: + push_warning("Update information cannot be retrieved from GitHub! \n Error code: %d : %s" % [response.status(), response.response()]) + message_h4("Download the update failed! Try it later again.", Color.INDIAN_RED) + await get_tree().create_timer(3).timeout + + +func rebuild_project() -> void: + # Check if this is a Godot .NET runtime instance + if not ClassDB.class_exists("CSharpScript"): + return + + update_progress("Rebuild the project ...") + await get_tree().process_frame + + var output := [] + var exit_code := OS.execute("dotnet", ["build"], output) + if exit_code == -1: + message_h4("Rebuild the project failed, check your project dependencies.", Color.INDIAN_RED) + await get_tree().create_timer(3).timeout + return + + for out: String in output: + print_rich("[color=DEEP_SKY_BLUE] %s" % out.strip_edges()) + await get_tree().process_frame + + +func _on_confirmed() -> void: + await run_update() + + +func _on_cancel_pressed() -> void: + hide() + + +func _on_update_pressed() -> void: + await run_update() diff --git a/addons/gdUnit4/src/update/GdUnitUpdate.gd.uid b/addons/gdUnit4/src/update/GdUnitUpdate.gd.uid new file mode 100644 index 0000000..918b627 --- /dev/null +++ b/addons/gdUnit4/src/update/GdUnitUpdate.gd.uid @@ -0,0 +1 @@ +uid://c1nr0ni7ydykg diff --git a/addons/gdUnit4/src/update/GdUnitUpdate.tscn b/addons/gdUnit4/src/update/GdUnitUpdate.tscn new file mode 100644 index 0000000..ae1a3cb --- /dev/null +++ b/addons/gdUnit4/src/update/GdUnitUpdate.tscn @@ -0,0 +1,100 @@ +[gd_scene load_steps=6 format=3 uid="uid://2eahgaw88y6q"] + +[ext_resource type="Script" uid="uid://c1nr0ni7ydykg" path="res://addons/gdUnit4/src/update/GdUnitUpdate.gd" id="1"] + +[sub_resource type="Gradient" id="Gradient_wilsr"] +colors = PackedColorArray(0.151276, 0.151276, 0.151276, 1, 1, 1, 1, 1) + +[sub_resource type="GradientTexture2D" id="GradientTexture2D_45cww"] +gradient = SubResource("Gradient_wilsr") +fill_to = Vector2(0.75641, 0) + +[sub_resource type="Gradient" id="Gradient_i0qp8"] +colors = PackedColorArray(1, 1, 1, 1, 0.20871, 0.20871, 0.20871, 1) + +[sub_resource type="GradientTexture2D" id="GradientTexture2D_wilsr"] +gradient = SubResource("Gradient_i0qp8") +fill_from = Vector2(0.794872, 0) +fill_to = Vector2(0, 0) + +[node name="GdUnitUpdate" type="MarginContainer"] +clip_contents = true +custom_minimum_size = Vector2(0, 80) +anchors_preset = 10 +anchor_right = 1.0 +offset_bottom = 80.0 +grow_horizontal = 2 +size_flags_horizontal = 3 +theme_override_constants/margin_left = 10 +theme_override_constants/margin_right = 10 +script = ExtResource("1") + +[node name="VBoxContainer" type="VBoxContainer" parent="."] +layout_mode = 2 + +[node name="Panel" type="Panel" parent="VBoxContainer"] +layout_mode = 2 +size_flags_vertical = 3 + +[node name="message" type="RichTextLabel" parent="VBoxContainer/Panel"] +unique_name_in_owner = true +layout_mode = 1 +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 +bbcode_enabled = true +text = "aaaaa" +fit_content = true +scroll_active = false +shortcut_keys_enabled = false + +[node name="Panel2" type="Panel" parent="VBoxContainer"] +layout_mode = 2 +size_flags_vertical = 3 + +[node name="progress" type="TextureProgressBar" parent="VBoxContainer/Panel2"] +unique_name_in_owner = true +auto_translate_mode = 2 +clip_contents = true +custom_minimum_size = Vector2(0, 20) +layout_mode = 1 +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 +localize_numeral_system = false +min_value = 1.0 +max_value = 6.0 +value = 1.0 +rounded = true +allow_greater = true +nine_patch_stretch = true +texture_under = SubResource("GradientTexture2D_45cww") +texture_progress = SubResource("GradientTexture2D_wilsr") +tint_under = Color(0.0235294, 0.145098, 0.168627, 1) +tint_progress = Color(0.288912, 0.233442, 0.533772, 1) + +[node name="PanelContainer" type="MarginContainer" parent="VBoxContainer"] +layout_mode = 2 +size_flags_vertical = 3 + +[node name="HBoxContainer" type="HBoxContainer" parent="VBoxContainer/PanelContainer"] +layout_mode = 2 +theme_override_constants/separation = 10 +alignment = 2 + +[node name="update" type="Button" parent="VBoxContainer/PanelContainer/HBoxContainer"] +unique_name_in_owner = true +layout_mode = 2 +text = "Update" + +[node name="cancel" type="Button" parent="VBoxContainer/PanelContainer/HBoxContainer"] +unique_name_in_owner = true +layout_mode = 2 +text = "Cancel" + +[connection signal="pressed" from="VBoxContainer/PanelContainer/HBoxContainer/update" to="." method="_on_update_pressed"] +[connection signal="pressed" from="VBoxContainer/PanelContainer/HBoxContainer/cancel" to="." method="_on_cancel_pressed"] diff --git a/addons/gdUnit4/src/update/GdUnitUpdateClient.gd b/addons/gdUnit4/src/update/GdUnitUpdateClient.gd new file mode 100644 index 0000000..b4f54b7 --- /dev/null +++ b/addons/gdUnit4/src/update/GdUnitUpdateClient.gd @@ -0,0 +1,98 @@ +@tool +extends Node + +signal request_completed(response: HttpResponse) + +class HttpResponse: + var _http_status: int + var _body: PackedByteArray + + + func _init(http_status: int, body: PackedByteArray) -> void: + _http_status = http_status + _body = body + + + func status() -> int: + return _http_status + + + func response() -> Variant: + if _http_status != 200: + return _body.get_string_from_utf8() + + var test_json_conv := JSON.new() + @warning_ignore("return_value_discarded") + var error := test_json_conv.parse(_body.get_string_from_utf8()) + if error != OK: + return "HttpResponse: %s Error: %s" % [error_string(error), _body.get_string_from_utf8()] + return test_json_conv.get_data() + + func get_body() -> PackedByteArray: + return _body + + +var _http_request := HTTPRequest.new() + + +func _ready() -> void: + add_child(_http_request) + @warning_ignore("return_value_discarded") + _http_request.request_completed.connect(_on_request_completed) + + +func _notification(what: int) -> void: + if what == NOTIFICATION_PREDELETE: + if is_instance_valid(_http_request): + _http_request.queue_free() + + +#func list_tags() -> void: +# _http_request.connect("request_completed",Callable(self,"_response_request_tags")) +# var error = _http_request.request("https://api.github.com/repos/MikeSchulze/gdUnit4/tags") +# if error != OK: +# push_error("An error occurred in the HTTP request.") + + +func request_latest_version() -> HttpResponse: + var error := _http_request.request("https://api.github.com/repos/MikeSchulze/gdUnit4/tags") + if error != OK: + var message := "Request latest version failed, %s" % error_string(error) + return HttpResponse.new(error, message.to_utf8_buffer()) + return await self.request_completed + + +func request_releases() -> HttpResponse: + var error := _http_request.request("https://api.github.com/repos/MikeSchulze/gdUnit4/releases") + if error != OK: + var message := "request_releases failed: %d" % error + return HttpResponse.new(error, message.to_utf8_buffer()) + return await self.request_completed + + +func request_image(url: String) -> HttpResponse: + var error := _http_request.request(url) + if error != OK: + var message := "request_image failed: %d" % error + return HttpResponse.new(error, message.to_utf8_buffer()) + return await self.request_completed + + +func request_zip_package(url: String, file: String) -> HttpResponse: + _http_request.set_download_file(file) + var error := _http_request.request(url) + if error != OK: + var message := "request_zip_package failed: %d" % error + return HttpResponse.new(error, message.to_utf8_buffer()) + return await self.request_completed + + +func extract_latest_version(response: HttpResponse) -> GdUnit4Version: + var body: Array = response.response() + return GdUnit4Version.parse(str(body[0]["name"])) + + +func _on_request_completed(_result: int, response_http_status: int, _headers: PackedStringArray, body: PackedByteArray) -> void: + if _http_request.get_http_client_status() != HTTPClient.STATUS_DISCONNECTED: + _http_request.set_download_file("") + request_completed.emit(HttpResponse.new(response_http_status, body)) diff --git a/addons/gdUnit4/src/update/GdUnitUpdateClient.gd.uid b/addons/gdUnit4/src/update/GdUnitUpdateClient.gd.uid new file mode 100644 index 0000000..809bc2e --- /dev/null +++ b/addons/gdUnit4/src/update/GdUnitUpdateClient.gd.uid @@ -0,0 +1 @@ +uid://dsd727gi635oe diff --git a/addons/gdUnit4/src/update/GdUnitUpdateNotify.gd b/addons/gdUnit4/src/update/GdUnitUpdateNotify.gd new file mode 100644 index 0000000..f4ae9ac --- /dev/null +++ b/addons/gdUnit4/src/update/GdUnitUpdateNotify.gd @@ -0,0 +1,206 @@ +@tool +extends MarginContainer + +#signal request_completed(response) + +const GdMarkDownReader = preload("res://addons/gdUnit4/src/update/GdMarkDownReader.gd") +const GdUnitUpdateClient = preload("res://addons/gdUnit4/src/update/GdUnitUpdateClient.gd") +const GdUnitUpdateProgress = preload("res://addons/gdUnit4/src/update/GdUnitUpdate.gd") + +@onready var _md_reader: GdMarkDownReader = GdMarkDownReader.new() +@onready var _update_client: GdUnitUpdateClient = $GdUnitUpdateClient +@onready var _header: Label = $Panel/GridContainer/PanelContainer/header +@onready var _update_button: Button = $Panel/GridContainer/Panel/HBoxContainer/update +@onready var _content: RichTextLabel = $Panel/GridContainer/PanelContainer2/ScrollContainer/MarginContainer/content +@onready var _update_progress :GdUnitUpdateProgress = %update_banner + +var _debug_mode := false +var _patcher := GdUnitPatcher.new() +var _current_version := GdUnit4Version.current() + + +func _ready() -> void: + _update_button.set_disabled(false) + _md_reader.set_http_client(_update_client) + @warning_ignore("return_value_discarded") + #GdUnitFonts.init_fonts(_content) + _update_progress.set_visible(false) + _update_progress.hidden.connect(func() -> void: + _update_button.set_disabled(false) + ) + + +func request_releases() -> bool: + if _debug_mode: + _update_progress._debug_mode = _debug_mode + _header.text = "A new version 'v4.4.4' is available" + _update_button.set_disabled(false) + return true + + var response :GdUnitUpdateClient.HttpResponse = await _update_client.request_latest_version() + if response.status() != 200: + _header.text = "Update information cannot be retrieved from GitHub!" + message_h4("\n\nError: %s" % response.response(), Color.INDIAN_RED) + return false + var latest_version := _update_client.extract_latest_version(response) + # if same version exit here no update need + if latest_version.is_greater(_current_version): + _patcher.scan(_current_version) + _header.text = "A new version '%s' is available" % latest_version + var download_zip_url := extract_zip_url(response) + _update_progress.setup(_update_client, download_zip_url) + _update_button.set_disabled(false) + return true + else: + _header.text = "No update is available." + _update_button.set_disabled(true) + return false + + +func _colored(message_: String, color: Color) -> String: + return "[color=#%s]%s[/color]" % [color.to_html(), message_] + + +func message_h4(message_: String, color: Color, clear := true) -> void: + if clear: + _content.clear() + _content.append_text("[font_size=16]%s[/font_size]" % _colored(message_, color)) + + +func message(message_: String, color: Color) -> void: + _content.clear() + _content.append_text(_colored(message_, color)) + + +func _process(_delta: float) -> void: + if _content != null and _content.is_visible_in_tree(): + _content.queue_redraw() + + +func show_update() -> void: + if not GdUnitSettings.is_update_notification_enabled(): + _header.text = "No update is available." + message_h4("The search for updates is deactivated.", Color.CORNFLOWER_BLUE) + _update_button.set_disabled(true) + return + + if not await request_releases(): + return + _update_button.set_disabled(true) + + prints("Scan for GdUnit4 Update ...") + message_h4("\n\n\nRequest release infos ... ", Color.SNOW) + _content.add_image(GdUnitUiTools.get_spinner(), 32, 32) + + var content: String + if _debug_mode: + await get_tree().create_timer(.2).timeout + var template := FileAccess.open("res://addons/gdUnit4/test/update/resources/http_response_releases.txt", FileAccess.READ).get_as_text() + content = await _md_reader.to_bbcode(template) + else: + var response :GdUnitUpdateClient.HttpResponse = await _update_client.request_releases() + if response.status() == 200: + content = await extract_releases(response, _current_version) + else: + message_h4("\n\n\nError checked request available releases!", Color.INDIAN_RED) + return + + # finally force rescan to import images as textures + if Engine.is_editor_hint(): + await rescan() + message(content, Color.CADET_BLUE) + _update_button.set_disabled(false) + + + +func extract_zip_url(response: GdUnitUpdateClient.HttpResponse) -> String: + var body :Array = response.response() + return body[0]["zipball_url"] + + +func extract_releases(response: GdUnitUpdateClient.HttpResponse, current_version: GdUnit4Version) -> String: + await get_tree().process_frame + var result := "" + for release :Dictionary in response.response(): + var release_version := str(release["tag_name"]) + if GdUnit4Version.parse(release_version).equals(current_version): + break + var release_description := _colored("

GdUnit Release %s

" % release_version, Color.CORNFLOWER_BLUE) + release_description += "\n" + release_description += release["body"] + release_description += "\n\n" + result += await _md_reader.to_bbcode(release_description) + return result + + +func rescan() -> void: + if Engine.is_editor_hint(): + if OS.is_stdout_verbose(): + prints(".. reimport release resources") + var fs := EditorInterface.get_resource_filesystem() + fs.scan() + while fs.is_scanning(): + if OS.is_stdout_verbose(): + progressBar(fs.get_scanning_progress() * 100 as int) + await get_tree().process_frame + await get_tree().process_frame + await get_tree().create_timer(1).timeout + + +func progressBar(p_progress: int) -> void: + if p_progress < 0: + p_progress = 0 + if p_progress > 100: + p_progress = 100 + printraw("scan [%-50s] %-3d%%\r" % ["".lpad(int(p_progress/2.0), "#").rpad(50, "-"), p_progress]) + + +@warning_ignore("return_value_discarded") +func _on_update_pressed() -> void: + _update_button.set_disabled(true) + # close all opend scripts before start the update + if not _debug_mode: + ScriptEditorControls.close_open_editor_scripts() + # copy update source to a temp because the update is deleting the whole gdUnit folder + DirAccess.make_dir_absolute("res://addons/.gdunit_update") + DirAccess.copy_absolute("res://addons/gdUnit4/src/update/GdUnitUpdate.tscn", "res://addons/.gdunit_update/GdUnitUpdate.tscn") + DirAccess.copy_absolute("res://addons/gdUnit4/src/update/GdUnitUpdate.gd", "res://addons/.gdunit_update/GdUnitUpdate.gd") + var source := FileAccess.open("res://addons/gdUnit4/src/update/GdUnitUpdate.tscn", FileAccess.READ) + var content := source.get_as_text().replace("res://addons/gdUnit4/src/update/GdUnitUpdate.gd", "res://addons/.gdunit_update/GdUnitUpdate.gd") + var dest := FileAccess.open("res://addons/.gdunit_update/GdUnitUpdate.tscn", FileAccess.WRITE) + dest.store_string(content) + _update_progress.set_visible(true) + + +func _on_show_next_toggled(enabled: bool) -> void: + GdUnitSettings.set_update_notification(enabled) + + +func _on_cancel_pressed() -> void: + hide() + + +func _on_content_meta_clicked(meta: String) -> void: + var properties: Dictionary = str_to_var(meta) + if properties.has("url"): + @warning_ignore("return_value_discarded") + OS.shell_open(str(properties.get("url"))) + + +func _on_content_meta_hover_started(meta: String) -> void: + var properties: Dictionary = str_to_var(meta) + if properties.has("tool_tip"): + _content.set_tooltip_text(str(properties.get("tool_tip"))) + + +@warning_ignore("unused_parameter") +func _on_content_meta_hover_ended(meta: String) -> void: + _content.set_tooltip_text("") + + +func _on_visibility_changed() -> void: + if not is_visible_in_tree(): + return + if _update_progress != null: + _update_progress.set_visible(false) + await show_update() diff --git a/addons/gdUnit4/src/update/GdUnitUpdateNotify.gd.uid b/addons/gdUnit4/src/update/GdUnitUpdateNotify.gd.uid new file mode 100644 index 0000000..44dc12d --- /dev/null +++ b/addons/gdUnit4/src/update/GdUnitUpdateNotify.gd.uid @@ -0,0 +1 @@ +uid://b2x28v83imlod diff --git a/addons/gdUnit4/src/update/GdUnitUpdateNotify.tscn b/addons/gdUnit4/src/update/GdUnitUpdateNotify.tscn new file mode 100644 index 0000000..f74fb06 --- /dev/null +++ b/addons/gdUnit4/src/update/GdUnitUpdateNotify.tscn @@ -0,0 +1,97 @@ +[gd_scene load_steps=4 format=3 uid="uid://0xyeci1tqebj"] + +[ext_resource type="Script" uid="uid://b2x28v83imlod" path="res://addons/gdUnit4/src/update/GdUnitUpdateNotify.gd" id="1_112wo"] +[ext_resource type="Script" uid="uid://dsd727gi635oe" path="res://addons/gdUnit4/src/update/GdUnitUpdateClient.gd" id="2_18asx"] +[ext_resource type="PackedScene" uid="uid://2eahgaw88y6q" path="res://addons/gdUnit4/src/update/GdUnitUpdate.tscn" id="3_x87h6"] + +[node name="Control" type="MarginContainer"] +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +script = ExtResource("1_112wo") + +[node name="GdUnitUpdateClient" type="Node" parent="."] +script = ExtResource("2_18asx") + +[node name="Panel" type="Panel" parent="."] +layout_mode = 2 + +[node name="GridContainer" type="VBoxContainer" parent="Panel"] +layout_mode = 1 +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +alignment = 1 + +[node name="PanelContainer" type="MarginContainer" parent="Panel/GridContainer"] +layout_mode = 2 +theme_override_constants/margin_left = 4 +theme_override_constants/margin_top = 4 +theme_override_constants/margin_right = 4 +theme_override_constants/margin_bottom = 4 + +[node name="header" type="Label" parent="Panel/GridContainer/PanelContainer"] +unique_name_in_owner = true +layout_mode = 2 +size_flags_horizontal = 9 + +[node name="PanelContainer2" type="PanelContainer" parent="Panel/GridContainer"] +layout_mode = 2 +size_flags_vertical = 3 + +[node name="ScrollContainer" type="ScrollContainer" parent="Panel/GridContainer/PanelContainer2"] +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="MarginContainer" type="MarginContainer" parent="Panel/GridContainer/PanelContainer2/ScrollContainer"] +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="content" type="RichTextLabel" parent="Panel/GridContainer/PanelContainer2/ScrollContainer/MarginContainer"] +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +bbcode_enabled = true + +[node name="update_banner" parent="Panel/GridContainer" instance=ExtResource("3_x87h6")] +unique_name_in_owner = true +visible = false +layout_mode = 2 +size_flags_horizontal = 1 +size_flags_vertical = 8 + +[node name="Panel" type="MarginContainer" parent="Panel/GridContainer"] +layout_mode = 2 +size_flags_vertical = 8 +theme_override_constants/margin_left = 4 +theme_override_constants/margin_top = 4 +theme_override_constants/margin_right = 4 +theme_override_constants/margin_bottom = 4 + +[node name="HBoxContainer" type="HBoxContainer" parent="Panel/GridContainer/Panel"] +use_parent_material = true +layout_mode = 2 +theme_override_constants/separation = 4 + +[node name="update" type="Button" parent="Panel/GridContainer/Panel/HBoxContainer"] +custom_minimum_size = Vector2(100, 40) +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 4 +text = "Update" + +[connection signal="visibility_changed" from="." to="." method="_on_visibility_changed"] +[connection signal="meta_clicked" from="Panel/GridContainer/PanelContainer2/ScrollContainer/MarginContainer/content" to="." method="_on_content_meta_clicked"] +[connection signal="meta_hover_ended" from="Panel/GridContainer/PanelContainer2/ScrollContainer/MarginContainer/content" to="." method="_on_content_meta_hover_ended"] +[connection signal="meta_hover_started" from="Panel/GridContainer/PanelContainer2/ScrollContainer/MarginContainer/content" to="." method="_on_content_meta_hover_started"] +[connection signal="pressed" from="Panel/GridContainer/Panel/HBoxContainer/update" to="." method="_on_update_pressed"] diff --git a/addons/gdUnit4/src/update/assets/border_bottom.png b/addons/gdUnit4/src/update/assets/border_bottom.png new file mode 100644 index 0000000..aa16bb7 Binary files /dev/null and b/addons/gdUnit4/src/update/assets/border_bottom.png differ diff --git a/addons/gdUnit4/src/update/assets/border_bottom.png.import b/addons/gdUnit4/src/update/assets/border_bottom.png.import new file mode 100644 index 0000000..51a951f --- /dev/null +++ b/addons/gdUnit4/src/update/assets/border_bottom.png.import @@ -0,0 +1,40 @@ +[remap] + +importer="texture" +type="CompressedTexture2D" +uid="uid://b80tdniy8pxqu" +path="res://.godot/imported/border_bottom.png-30d66a4c67e3a03ad191e37cdf16549d.ctex" +metadata={ +"vram_texture": false +} + +[deps] + 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Advanced property-based entity filtering + +### 🛠️ Practical Application (30-60 minutes) + +- **[Best Practices](docs/BEST_PRACTICES.md)** - Write maintainable, performant ECS code +- **[Relationships](docs/RELATIONSHIPS.md)** - Link entities together for complex interactions +- **[Observers](docs/OBSERVERS.md)** - Reactive systems that respond to component changes +- **[Serialization](docs/SERIALIZATION.md)** - Save and load game state and entities + +### ⚡ Optimization & Advanced (As needed) + +- **[Debug Viewer](docs/DEBUG_VIEWER.md)** - Real-time debugging and performance monitoring +- **[Performance Optimization](docs/PERFORMANCE_OPTIMIZATION.md)** - Make your games run fast and smooth +- **[Troubleshooting](docs/TROUBLESHOOTING.md)** - Solve common issues quickly + +### 🔬 Framework Development (For contributors) + +- **[Performance Testing](docs/PERFORMANCE_TESTING.md)** - Framework-level performance testing guide + +## 📖 Documentation by Topic + +### Entity Component System Basics + +| Topic | Document | Description | +| ----------------- | ------------------------------------------ | ------------------------------------ | +| **Introduction** | [Getting Started](docs/GETTING_STARTED.md) | First ECS project tutorial | +| **Architecture** | [Core Concepts](docs/CORE_CONCEPTS.md) | Complete ECS architecture overview | +| **Data Patterns** | [Best Practices](docs/BEST_PRACTICES.md) | Component and system design patterns | + +### Advanced Features + +| Topic | Document | Description | +| ---------------------- | ---------------------------------------------- | ----------------------------------- | +| **Entity Linking** | [Relationships](docs/RELATIONSHIPS.md) | Connect entities with relationships | +| **Property Filtering** | [Component Queries](docs/COMPONENT_QUERIES.md) | Query entities by component data | +| **Event Systems** | [Observers](docs/OBSERVERS.md) | React to component changes | +| **Data Persistence** | [Serialization](docs/SERIALIZATION.md) | Save/load entities and game state | + +### Optimization & Debugging + +| Topic | Document | Description | +| ------------------ | ------------------------------------------------------------ | ----------------------------------- | +| **Debug Viewer** | [Debug Viewer](docs/DEBUG_VIEWER.md) | Real-time debugging and inspection | +| **Performance** | [Performance Optimization](docs/PERFORMANCE_OPTIMIZATION.md) | Game performance optimization | +| **Debugging** | [Troubleshooting](docs/TROUBLESHOOTING.md) | Common problems and solutions | +| **Testing** | [Performance Testing](docs/PERFORMANCE_TESTING.md) | Framework performance testing | + +## 🎯 Quick References + +### Naming Conventions + +- **Entities**: `ClassCase` class, `e_entity_name.gd` file +- **Components**: `C_ComponentName` class, `c_component_name.gd` file +- **Systems**: `SystemNameSystem` class, `s_system_name.gd` file +- **Observers**: `ObserverNameObserver` class, `o_observer_name.gd` file + +### Essential Patterns + +```gdscript +# Entity creation +var player = Player.new() +player.add_component(C_Health.new(100)) +player.add_component(C_Position.new(Vector2.ZERO)) +ECS.world.add_entity(player) + +# System queries +func query(): return q.with_all([C_Health, C_Position]) +func process(entities: Array[Entity], components: Array, delta: float): # Unified signature +# Use .iterate([Components]) for batch component array access + +# Relationships +entity.add_relationship(Relationship.new(C_Likes.new(), target_entity)) +var likers = ECS.world.query.with_relationship([Relationship.new(C_Likes.new(), entity)]).execute() + +# Component queries +var low_health = ECS.world.query.with_all([{C_Health: {"current": {"_lt": 20}}}]).execute() + +# Order Independence: with_all/with_any/with_node component order does not affect matching or caching. +# The framework normalizes component sets internally so these yield identical results: +# ECS.world.query.with_all([C_Health, C_Position]) +# ECS.world.query.with_all([C_Position, C_Health]) +# Cache keys and archetype matching are order-insensitive. + +# Serialization +var data = ECS.serialize(ECS.world.query.with_all([C_Persistent])) +ECS.save(data, "user://savegame.tres", true) # Binary format +var entities = ECS.deserialize("user://savegame.tres") +``` + +## 🎮 Example Projects + +Basic examples are included in each guide. For complete game examples, see: + +- **Simple Ball Movement** - [Getting Started Guide](docs/GETTING_STARTED.md) +- **Combat Systems** - [Relationships Guide](docs/RELATIONSHIPS.md) +- **UI Synchronization** - [Observers Guide](docs/OBSERVERS.md) + +## 🆘 Getting Help + +1. **Check documentation** - Most questions are answered in the guides above +2. **Review examples** - Each guide includes working code examples +3. **Try troubleshooting** - [Troubleshooting Guide](docs/TROUBLESHOOTING.md) covers common issues +4. **Community support** - [Join our Discord](https://discord.gg/eB43XU2tmn) for discussions and questions + +## 🔄 Documentation Updates + +This documentation is actively maintained. If you find errors or have suggestions: + +- **Report issues** for bugs or unclear documentation +- **Suggest improvements** for better examples or explanations +- **Contribute examples** showing real-world usage patterns + +--- + +**Ready to start?** Begin with the [Getting Started Guide](docs/GETTING_STARTED.md) and build your first ECS project in just 5 minutes! + +_GECS makes building scalable, maintainable games easier by separating data from logic and providing powerful query systems for entity management._ diff --git a/addons/gecs/assets/component.svg b/addons/gecs/assets/component.svg new file mode 100644 index 0000000..35ef021 --- /dev/null +++ b/addons/gecs/assets/component.svg @@ -0,0 +1,9 @@ + + + + + + + diff --git a/addons/gecs/assets/component.svg.import b/addons/gecs/assets/component.svg.import new file mode 100644 index 0000000..7e1fc79 --- /dev/null +++ b/addons/gecs/assets/component.svg.import @@ -0,0 +1,43 @@ +[remap] + +importer="texture" 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a/addons/gecs/assets/logo.png.import b/addons/gecs/assets/logo.png.import new file mode 100644 index 0000000..d454ed8 --- /dev/null +++ b/addons/gecs/assets/logo.png.import @@ -0,0 +1,40 @@ +[remap] + +importer="texture" +type="CompressedTexture2D" +uid="uid://dfuhf6eppvmxn" +path="res://.godot/imported/logo.png-8dce28df5ee6c8739ca6b3801cfe878d.ctex" +metadata={ +"vram_texture": false +} + +[deps] + +source_file="res://addons/gecs/assets/logo.png" +dest_files=["res://.godot/imported/logo.png-8dce28df5ee6c8739ca6b3801cfe878d.ctex"] + +[params] + +compress/mode=0 +compress/high_quality=false +compress/lossy_quality=0.7 +compress/uastc_level=0 +compress/rdo_quality_loss=0.0 +compress/hdr_compression=1 +compress/normal_map=0 +compress/channel_pack=0 +mipmaps/generate=false +mipmaps/limit=-1 +roughness/mode=0 +roughness/src_normal="" +process/channel_remap/red=0 +process/channel_remap/green=1 +process/channel_remap/blue=2 +process/channel_remap/alpha=3 +process/fix_alpha_border=true +process/premult_alpha=false +process/normal_map_invert_y=false +process/hdr_as_srgb=false +process/hdr_clamp_exposure=false +process/size_limit=0 +detect_3d/compress_to=1 diff --git a/addons/gecs/assets/observer.svg b/addons/gecs/assets/observer.svg new file mode 100644 index 0000000..61af188 --- /dev/null +++ b/addons/gecs/assets/observer.svg @@ -0,0 +1,5 @@ + + + \ No newline at end of file diff --git a/addons/gecs/assets/observer.svg.import b/addons/gecs/assets/observer.svg.import new file mode 100644 index 0000000..ffd5785 --- /dev/null +++ b/addons/gecs/assets/observer.svg.import @@ -0,0 +1,43 @@ +[remap] + +importer="texture" +type="CompressedTexture2D" +uid="uid://dqhpkkwhk2kcd" +path="res://.godot/imported/observer.svg-4447d1c14fb8407efb95472a8cbe6c0b.ctex" +metadata={ +"vram_texture": false +} + +[deps] + +source_file="res://addons/gecs/assets/observer.svg" +dest_files=["res://.godot/imported/observer.svg-4447d1c14fb8407efb95472a8cbe6c0b.ctex"] + +[params] + +compress/mode=0 +compress/high_quality=false +compress/lossy_quality=0.7 +compress/uastc_level=0 +compress/rdo_quality_loss=0.0 +compress/hdr_compression=1 +compress/normal_map=0 +compress/channel_pack=0 +mipmaps/generate=false +mipmaps/limit=-1 +roughness/mode=0 +roughness/src_normal="" +process/channel_remap/red=0 +process/channel_remap/green=1 +process/channel_remap/blue=2 +process/channel_remap/alpha=3 +process/fix_alpha_border=true +process/premult_alpha=false +process/normal_map_invert_y=false +process/hdr_as_srgb=false +process/hdr_clamp_exposure=false +process/size_limit=0 +detect_3d/compress_to=1 +svg/scale=1.0 +editor/scale_with_editor_scale=false +editor/convert_colors_with_editor_theme=false diff --git a/addons/gecs/assets/system.svg b/addons/gecs/assets/system.svg new file mode 100644 index 0000000..fcf264b --- /dev/null +++ b/addons/gecs/assets/system.svg @@ -0,0 +1,15 @@ + + + + + + + + + + + + + diff --git a/addons/gecs/assets/system.svg.import b/addons/gecs/assets/system.svg.import new file mode 100644 index 0000000..9d86e53 --- /dev/null +++ b/addons/gecs/assets/system.svg.import @@ -0,0 +1,43 @@ +[remap] + +importer="texture" +type="CompressedTexture2D" +uid="uid://d3yy7cagqxvuy" +path="res://.godot/imported/system.svg-3ba90685fdf6d3608f3a7eef4b55f305.ctex" +metadata={ +"vram_texture": false +} + +[deps] + +source_file="res://addons/gecs/assets/system.svg" +dest_files=["res://.godot/imported/system.svg-3ba90685fdf6d3608f3a7eef4b55f305.ctex"] + +[params] + +compress/mode=0 +compress/high_quality=false +compress/lossy_quality=0.7 +compress/uastc_level=0 +compress/rdo_quality_loss=0.0 +compress/hdr_compression=1 +compress/normal_map=0 +compress/channel_pack=0 +mipmaps/generate=false +mipmaps/limit=-1 +roughness/mode=0 +roughness/src_normal="" +process/channel_remap/red=0 +process/channel_remap/green=1 +process/channel_remap/blue=2 +process/channel_remap/alpha=3 +process/fix_alpha_border=true +process/premult_alpha=false +process/normal_map_invert_y=false +process/hdr_as_srgb=false +process/hdr_clamp_exposure=false +process/size_limit=0 +detect_3d/compress_to=1 +svg/scale=1.0 +editor/scale_with_editor_scale=false +editor/convert_colors_with_editor_theme=false diff --git a/addons/gecs/assets/system_folder.svg b/addons/gecs/assets/system_folder.svg new file mode 100644 index 0000000..ed3119d --- /dev/null +++ b/addons/gecs/assets/system_folder.svg @@ -0,0 +1,7 @@ + + + + \ No newline at end of file diff --git a/addons/gecs/assets/system_folder.svg.import b/addons/gecs/assets/system_folder.svg.import new file mode 100644 index 0000000..c27dfb7 --- /dev/null +++ b/addons/gecs/assets/system_folder.svg.import @@ -0,0 +1,43 @@ +[remap] + +importer="texture" +type="CompressedTexture2D" +uid="uid://bebopiehk02k1" +path="res://.godot/imported/system_folder.svg-9f95776b45329abe5c6e0deb4fa1cf7c.ctex" +metadata={ +"vram_texture": false +} + +[deps] + +source_file="res://addons/gecs/assets/system_folder.svg" +dest_files=["res://.godot/imported/system_folder.svg-9f95776b45329abe5c6e0deb4fa1cf7c.ctex"] + +[params] + +compress/mode=0 +compress/high_quality=false +compress/lossy_quality=0.7 +compress/uastc_level=0 +compress/rdo_quality_loss=0.0 +compress/hdr_compression=1 +compress/normal_map=0 +compress/channel_pack=0 +mipmaps/generate=false +mipmaps/limit=-1 +roughness/mode=0 +roughness/src_normal="" +process/channel_remap/red=0 +process/channel_remap/green=1 +process/channel_remap/blue=2 +process/channel_remap/alpha=3 +process/fix_alpha_border=true +process/premult_alpha=false +process/normal_map_invert_y=false +process/hdr_as_srgb=false +process/hdr_clamp_exposure=false +process/size_limit=0 +detect_3d/compress_to=1 +svg/scale=1.0 +editor/scale_with_editor_scale=false +editor/convert_colors_with_editor_theme=false diff --git a/addons/gecs/assets/world.svg b/addons/gecs/assets/world.svg new file mode 100644 index 0000000..d6614fc --- /dev/null +++ b/addons/gecs/assets/world.svg @@ -0,0 +1,17 @@ + + + + + + + + diff --git a/addons/gecs/assets/world.svg.import b/addons/gecs/assets/world.svg.import new file mode 100644 index 0000000..c06ccf7 --- /dev/null +++ b/addons/gecs/assets/world.svg.import @@ -0,0 +1,43 @@ +[remap] + +importer="texture" +type="CompressedTexture2D" +uid="uid://dhu1m3rpx1al3" +path="res://.godot/imported/world.svg-4fb4d15549e6aa583bb2553a24189477.ctex" +metadata={ +"vram_texture": false +} + +[deps] + +source_file="res://addons/gecs/assets/world.svg" +dest_files=["res://.godot/imported/world.svg-4fb4d15549e6aa583bb2553a24189477.ctex"] + +[params] + +compress/mode=0 +compress/high_quality=false +compress/lossy_quality=0.7 +compress/uastc_level=0 +compress/rdo_quality_loss=0.0 +compress/hdr_compression=1 +compress/normal_map=0 +compress/channel_pack=0 +mipmaps/generate=false +mipmaps/limit=-1 +roughness/mode=0 +roughness/src_normal="" +process/channel_remap/red=0 +process/channel_remap/green=1 +process/channel_remap/blue=2 +process/channel_remap/alpha=3 +process/fix_alpha_border=true +process/premult_alpha=false +process/normal_map_invert_y=false +process/hdr_as_srgb=false +process/hdr_clamp_exposure=false +process/size_limit=0 +detect_3d/compress_to=1 +svg/scale=1.0 +editor/scale_with_editor_scale=false +editor/convert_colors_with_editor_theme=false diff --git a/addons/gecs/debug/gecs_editor_debugger.gd b/addons/gecs/debug/gecs_editor_debugger.gd new file mode 100644 index 0000000..eae4d99 --- /dev/null +++ b/addons/gecs/debug/gecs_editor_debugger.gd @@ -0,0 +1,128 @@ +class_name GECSEditorDebugger +extends EditorDebuggerPlugin + +## The Debugger session for the current game +var session: EditorDebuggerSession +## The tab that will be added to the debugger window +var debugger_tab: GECSEditorDebuggerTab = preload("res://addons/gecs/debug/gecs_editor_debugger_tab.tscn").instantiate() + +## The debugger messages that will be sent to the editor debugger +var Msg := GECSEditorDebuggerMessages.Msg +## Reference to editor interface for selecting nodes +var editor_interface: EditorInterface = null + + +func _has_capture(capture): + # Return true if you wish to handle messages with the prefix "gecs:". + return capture == "gecs" + + +func _capture(message: String, data: Array, session_id: int) -> bool: + if message == Msg.WORLD_INIT: + # data: [World.get_path()] + var world = data[0] + var world_path = data[1] + debugger_tab.world_init(data[0], data[1]) + return true + elif message == Msg.SYSTEM_METRIC: + # data: [system, system_name, elapsed_time] + var system = data[0] + var system_name = data[1] + var elapsed_time = data[2] + debugger_tab.system_metric(system, system_name, elapsed_time) + return true + elif message == Msg.SYSTEM_LAST_RUN_DATA: + # data: [system_id, system_name, last_run_data] + var system_id = data[0] + var system_name = data[1] + var last_run_data = data[2] + debugger_tab.system_last_run_data(system_id, system_name, last_run_data) + return true + elif message == Msg.SET_WORLD: + if data.size() == 0: + return true + var world = data[0] + var world_path = data[1] + debugger_tab.set_world(world, world_path) + return true + elif message == Msg.PROCESS_WORLD: + # data: [float, String] + var delta = data[0] + var group_name = data[1] + debugger_tab.process_world(delta, group_name) + return true + elif message == Msg.EXIT_WORLD: + debugger_tab.exit_world() + return true + elif message == Msg.ENTITY_ADDED: + # data: [Entity, NodePath] + debugger_tab.entity_added(data[0], data[1]) + return true + elif message == Msg.ENTITY_REMOVED: + # data: [Entity, NodePath] + debugger_tab.entity_removed(data[0], data[1]) + return true + elif message == Msg.ENTITY_DISABLED: + # data: [Entity, NodePath] + debugger_tab.entity_disabled(data[0], data[1]) + return true + elif message == Msg.ENTITY_ENABLED: + # data: [Entity, NodePath] + debugger_tab.entity_enabled(data[0], data[1]) + return true + elif message == Msg.SYSTEM_ADDED: + # data: [System, group, process_empty, active, paused, NodePath] + debugger_tab.system_added(data[0], data[1], data[2], data[3], data[4], data[5]) + return true + elif message == Msg.SYSTEM_REMOVED: + # data: [System, NodePath] + debugger_tab.system_removed(data[0], data[1]) + return true + elif message == Msg.ENTITY_COMPONENT_ADDED: + # data: [ent.get_instance_id(), comp.get_instance_id(), ClassUtils.get_type_name(comp), comp.serialize()] + debugger_tab.entity_component_added(data[0], data[1], data[2], data[3]) + return true + elif message == Msg.ENTITY_COMPONENT_REMOVED: + # data: [Entity, Variant] + debugger_tab.entity_component_removed(data[0], data[1]) + return true + elif message == Msg.ENTITY_RELATIONSHIP_ADDED: + # data: [ent_id, rel_id, rel_data] + debugger_tab.entity_relationship_added(data[0], data[1], data[2]) + return true + elif message == Msg.ENTITY_RELATIONSHIP_REMOVED: + # data: [Entity, Relationship] + debugger_tab.entity_relationship_removed(data[0], data[1]) + return true + elif message == Msg.COMPONENT_PROPERTY_CHANGED: + # data: [Entity, Component, property_name, old_value, new_value] + debugger_tab.entity_component_property_changed(data[0], data[1], data[2], data[3], data[4]) + return true + return false + + +func _setup_session(session_id): + # Add a new tab in the debugger session UI containing a label. + debugger_tab.name = "GECS" # Will be used as the tab title. + session = get_session(session_id) + # Pass session reference to the tab for sending messages + debugger_tab.set_debugger_session(session) + # Pass editor interface to the tab for selecting nodes + debugger_tab.set_editor_interface(editor_interface) + # Listens to the session started and stopped signals. + if not session.started.is_connected(_on_session_started): + session.started.connect(_on_session_started) + if not session.stopped.is_connected(_on_session_stopped): + session.stopped.connect(_on_session_stopped) + session.add_session_tab(debugger_tab) + + +func _on_session_started(): + print("GECS Debug Session started") + debugger_tab.clear_all_data() + debugger_tab.active = true + + +func _on_session_stopped(): + print("GECS Debug Session stopped") + debugger_tab.active = false diff --git a/addons/gecs/debug/gecs_editor_debugger.gd.uid b/addons/gecs/debug/gecs_editor_debugger.gd.uid new file mode 100644 index 0000000..1516f13 --- /dev/null +++ b/addons/gecs/debug/gecs_editor_debugger.gd.uid @@ -0,0 +1 @@ +uid://fndnnk201xlo diff --git a/addons/gecs/debug/gecs_editor_debugger_messages.gd b/addons/gecs/debug/gecs_editor_debugger_messages.gd new file mode 100644 index 0000000..aefb7e8 --- /dev/null +++ b/addons/gecs/debug/gecs_editor_debugger_messages.gd @@ -0,0 +1,227 @@ +class_name GECSEditorDebuggerMessages + +## A mapping of all the messages sent to the editor debugger. +const Msg = { + "WORLD_INIT": "gecs:world_init", + "SYSTEM_METRIC": "gecs:system_metric", + "SYSTEM_LAST_RUN_DATA": "gecs:system_last_run_data", + "SET_WORLD": "gecs:set_world", + "PROCESS_WORLD": "gecs:process_world", + "EXIT_WORLD": "gecs:exit_world", + "ENTITY_ADDED": "gecs:entity_added", + "ENTITY_REMOVED": "gecs:entity_removed", + "ENTITY_DISABLED": "gecs:entity_disabled", + "ENTITY_ENABLED": "gecs:entity_enabled", + "SYSTEM_ADDED": "gecs:system_added", + "SYSTEM_REMOVED": "gecs:system_removed", + "ENTITY_COMPONENT_ADDED": "gecs:entity_component_added", + "ENTITY_COMPONENT_REMOVED": "gecs:entity_component_removed", + "ENTITY_RELATIONSHIP_ADDED": "gecs:entity_relationship_added", + "ENTITY_RELATIONSHIP_REMOVED": "gecs:entity_relationship_removed", + "COMPONENT_PROPERTY_CHANGED": "gecs:component_property_changed", + "POLL_ENTITY": "gecs:poll_entity", + "SELECT_ENTITY": "gecs:select_entity", +} + + +## Helper function to check if we can send messages to the editor debugger. +static func can_send_message() -> bool: + return not Engine.is_editor_hint() and OS.has_feature("editor") + + +static func world_init(world: World) -> bool: + if can_send_message(): + EngineDebugger.send_message(Msg.WORLD_INIT, [world.get_instance_id(), + world.get_path() + ]) + return true + +static func system_metric(system: System, time: float) -> bool: + if can_send_message(): + EngineDebugger.send_message( + Msg.SYSTEM_METRIC, [system.get_instance_id(), + system.name, + time + ] + ) + return true + +static func system_last_run_data(system: System, last_run_data: Dictionary) -> bool: + if can_send_message(): + # Send trimmed data to avoid excessive payload; include execution time and entity count primarily + EngineDebugger.send_message( + Msg.SYSTEM_LAST_RUN_DATA, + [ + system.get_instance_id(), + system.name, + last_run_data.duplicate() # duplicate so caller's dictionary isn't mutated + ] + ) + return true + +static func set_world(world: World) -> bool: + if can_send_message(): + EngineDebugger.send_message( + Msg.SET_WORLD, + [world.get_instance_id(), + world.get_path() + ] + if world else [] + ) + return true + +static func process_world(delta: float, group_name: String) -> bool: + if can_send_message(): + EngineDebugger.send_message(Msg.PROCESS_WORLD, [delta, group_name]) + return true + + +static func exit_world() -> bool: + if can_send_message(): + EngineDebugger.send_message(Msg.EXIT_WORLD, []) + return true + +static func entity_added(ent: Entity) -> bool: + if can_send_message(): + EngineDebugger.send_message(Msg.ENTITY_ADDED, [ent.get_instance_id(), ent.get_path()]) + return true + +static func entity_removed(ent: Entity) -> bool: + if can_send_message(): + EngineDebugger.send_message(Msg.ENTITY_REMOVED, [ent.get_instance_id(), ent.get_path()]) + return true + +static func entity_disabled(ent: Entity) -> bool: + if can_send_message(): + EngineDebugger.send_message(Msg.ENTITY_DISABLED, [ent.get_instance_id(), ent.get_path()]) + return true + +static func entity_enabled(ent: Entity) -> bool: + if can_send_message(): + EngineDebugger.send_message(Msg.ENTITY_ENABLED, [ent.get_instance_id(), ent.get_path()]) + return true + +static func system_added(sys: System) -> bool: + if can_send_message(): + EngineDebugger.send_message( + Msg.SYSTEM_ADDED, + [ + sys.get_instance_id(), + sys.group, + sys.process_empty, + sys.active, + sys.paused, + sys.get_path() + ] + ) + return true + +static func system_removed(sys: System) -> bool: + if can_send_message(): + EngineDebugger.send_message(Msg.SYSTEM_REMOVED, [sys.get_instance_id(), sys.get_path()]) + return true + +static func _get_type_name_for_debugger(obj) -> String: + if obj == null: + return "null" + if obj is Resource or obj is Node: + var script = obj.get_script() + if script: + # Try to get class_name first + var type_name = script.get_class() + if type_name and type_name != "GDScript": + return type_name + # Otherwise use the resource path (e.g., "res://components/C_Health.gd") + if script.resource_path: + return script.resource_path # Returns "C_Health" + return obj.get_class() + elif obj is Object: + return obj.get_class() + return str(typeof(obj)) + + +static func entity_component_added(ent: Entity, comp: Resource) -> bool: + if can_send_message(): + EngineDebugger.send_message( + Msg.ENTITY_COMPONENT_ADDED, + [ + ent.get_instance_id(), + comp.get_instance_id(), + _get_type_name_for_debugger(comp), + comp.serialize() + ] + ) + return true + +static func entity_component_removed(ent: Entity, comp: Resource) -> bool: + if can_send_message(): + EngineDebugger.send_message( + Msg.ENTITY_COMPONENT_REMOVED, [ent.get_instance_id(), + comp.get_instance_id() + ] + ) + return true + +static func entity_component_property_changed( + ent: Entity, comp: Resource, property_name: String, old_value: Variant, new_value: Variant +) -> bool: + if can_send_message(): + EngineDebugger.send_message( + Msg.COMPONENT_PROPERTY_CHANGED, + [ent.get_instance_id(), + comp.get_instance_id(), + property_name, + old_value, + new_value + ] + ) + return true + +static func entity_relationship_added(ent: Entity, rel: Relationship) -> bool: + if can_send_message(): + # Serialize relationship data for debugger display + var rel_data = { + "relation_type": _get_type_name_for_debugger(rel.relation) if rel.relation else "null", + "relation_data": rel.relation.serialize() if rel.relation else {}, + "target_type": "", + "target_data": {} + } + + # Format target based on type + if rel.target == null: + rel_data["target_type"] = "null" + elif rel.target is Entity: + rel_data["target_type"] = "Entity" + rel_data["target_data"] = { + "id": rel.target.get_instance_id(), + "path": str(rel.target.get_path()) + } + elif rel.target is Component: + rel_data["target_type"] = "Component" + rel_data["target_data"] = { + "type": _get_type_name_for_debugger(rel.target), + "data": rel.target.serialize() + } + elif rel.target is Script: + rel_data["target_type"] = "Archetype" + rel_data["target_data"] = { + "script_path": rel.target.resource_path + } + + EngineDebugger.send_message( + Msg.ENTITY_RELATIONSHIP_ADDED, + [ent.get_instance_id(), + rel.get_instance_id(), + rel_data + ] + ) + return true + +static func entity_relationship_removed(ent: Entity, rel: Relationship) -> bool: + if can_send_message(): + EngineDebugger.send_message( + Msg.ENTITY_RELATIONSHIP_REMOVED, [ent.get_instance_id(), + rel.get_instance_id() + ] + ) + return true diff --git a/addons/gecs/debug/gecs_editor_debugger_messages.gd.uid b/addons/gecs/debug/gecs_editor_debugger_messages.gd.uid new file mode 100644 index 0000000..e640e31 --- /dev/null +++ b/addons/gecs/debug/gecs_editor_debugger_messages.gd.uid @@ -0,0 +1 @@ +uid://d08dvfk13egq7 diff --git a/addons/gecs/debug/gecs_editor_debugger_tab.gd b/addons/gecs/debug/gecs_editor_debugger_tab.gd new file mode 100644 index 0000000..595577e --- /dev/null +++ b/addons/gecs/debug/gecs_editor_debugger_tab.gd @@ -0,0 +1,1501 @@ +@tool +class_name GECSEditorDebuggerTab +extends Control + +@onready var query_builder_check_box: CheckBox = %QueryBuilderCheckBox +@onready var entities_filter_line_edit: LineEdit = %EntitiesQueryLineEdit +@onready var systems_filter_line_edit: LineEdit = %SystemsQueryLineEdit +@onready var collapse_all_btn: Button = %CollapseAllBtn +@onready var expand_all_btn: Button = %ExpandAllBtn +@onready var systems_collapse_all_btn: Button = %SystemsCollapseAllBtn +@onready var systems_expand_all_btn: Button = %SystemsExpandAllBtn +@onready var pop_out_btn: Button = %PopOutBtn + +var ecs_data: Dictionary = {} +var default_system := {"path": "", "active": true, "metrics": {}, "group": ""} +var default_entity := {"path": "", "active": true, "components": {}, "relationships": {}} +var timer = 5 +var active := false +var _pending_components: Dictionary = {} # ent_id -> Array[Dictionary] of pending component data +var _popup_window: Window = null +var _debugger_session: EditorDebuggerSession = null + +@onready var system_tree: Tree = %SystemsTree +@onready var entities_tree: Tree = %EntitiesTree +@onready var entity_status_bar: TextEdit = %EntityStatusBar +@onready var systems_status_bar: TextEdit = %SystemsStatusBar +@onready var debug_mode_overlay: Panel = %DebugModeOverlay + +# Sorting state +var _system_sort_column: int = -1 # -1 means no sorting +var _system_sort_ascending: bool = true +var _entity_sort_column: int = -1 # -1 means no sorting +var _entity_sort_ascending: bool = true + +# Pinned items +var _pinned_entities: Dictionary = {} # entity_id -> bool +var _pinned_systems: Dictionary = {} # system_id -> bool + +# Icon constants (using Unicode characters) +const ICON_ENTITY = "📦" # Entity icon +const ICON_COMPONENT = "🔧" # Component icon +const ICON_FLAG = "🚩" # Flag component (no properties) +const ICON_RELATIONSHIP = "🔗" # Relationship icon +const ICON_PIN = "📌" # Pinned item icon + + +func _ready() -> void: + _update_debug_mode_overlay() + if system_tree: + # Five columns: name, group, execution time, status, and order + system_tree.columns = 5 + system_tree.set_column_expand(0, true) # Name column expands + system_tree.set_column_expand(1, false) # Group column resizable + system_tree.set_column_expand(2, false) # Execution time column resizable + system_tree.set_column_expand(3, false) # Status column resizable + system_tree.set_column_expand(4, false) # Order column resizable + + # Set column widths + system_tree.set_column_custom_minimum_width(1, 100) # Group: 100px min + system_tree.set_column_custom_minimum_width(2, 100) # Execution time: 100px min + system_tree.set_column_custom_minimum_width(3, 100) # Status: 100px min + system_tree.set_column_custom_minimum_width(4, 60) # Order: 60px min + + # Enable column resizing (clip content allows manual resizing) + system_tree.set_column_clip_content(0, true) + system_tree.set_column_clip_content(1, true) + system_tree.set_column_clip_content(2, true) + system_tree.set_column_clip_content(3, true) + system_tree.set_column_clip_content(4, true) + + # Set column titles (clickable for sorting) + system_tree.set_column_title(0, "Name") + system_tree.set_column_title(1, "Group") + system_tree.set_column_title(2, "Time (ms)") + system_tree.set_column_title(3, "Status") + system_tree.set_column_title(4, "Order") + system_tree.set_column_titles_visible(true) + + # Create root item + if system_tree.get_root() == null: + system_tree.create_item() + if entities_tree: + # Four columns: name, components count, relationships count, nodes count + entities_tree.columns = 4 + entities_tree.set_column_expand(0, true) # Name column expands + entities_tree.set_column_expand(1, false) # Components count resizable + entities_tree.set_column_expand(2, false) # Relationships count resizable + entities_tree.set_column_expand(3, false) # Nodes count resizable + + # Set column widths + entities_tree.set_column_custom_minimum_width(1, 80) # Components: 80px min + entities_tree.set_column_custom_minimum_width(2, 80) # Relationships: 80px min + entities_tree.set_column_custom_minimum_width(3, 80) # Nodes: 80px min + + # Enable column resizing (clip content allows manual resizing) + entities_tree.set_column_clip_content(0, true) + entities_tree.set_column_clip_content(1, true) + entities_tree.set_column_clip_content(2, true) + entities_tree.set_column_clip_content(3, true) + + # Set column titles + entities_tree.set_column_title(0, "Entity") + entities_tree.set_column_title(1, "Comps") + entities_tree.set_column_title(2, "Rels") + entities_tree.set_column_title(3, "Nodes") + entities_tree.set_column_titles_visible(true) + + # Create root item + if entities_tree.get_root() == null: + entities_tree.create_item() + # Polling & pinning removed; tree updates only via incoming messages + if entities_filter_line_edit and not entities_filter_line_edit.text_changed.is_connected(_on_entities_filter_changed): + entities_filter_line_edit.text_changed.connect(_on_entities_filter_changed) + if systems_filter_line_edit and not systems_filter_line_edit.text_changed.is_connected(_on_systems_filter_changed): + systems_filter_line_edit.text_changed.connect(_on_systems_filter_changed) + if collapse_all_btn and not collapse_all_btn.pressed.is_connected(_on_collapse_all_pressed): + collapse_all_btn.pressed.connect(_on_collapse_all_pressed) + if expand_all_btn and not expand_all_btn.pressed.is_connected(_on_expand_all_pressed): + expand_all_btn.pressed.connect(_on_expand_all_pressed) + if systems_collapse_all_btn and not systems_collapse_all_btn.pressed.is_connected(_on_systems_collapse_all_pressed): + systems_collapse_all_btn.pressed.connect(_on_systems_collapse_all_pressed) + if systems_expand_all_btn and not systems_expand_all_btn.pressed.is_connected(_on_systems_expand_all_pressed): + systems_expand_all_btn.pressed.connect(_on_systems_expand_all_pressed) + if pop_out_btn and not pop_out_btn.pressed.is_connected(_on_pop_out_pressed): + pop_out_btn.pressed.connect(_on_pop_out_pressed) + # Connect to system tree for clicking (single click to toggle) + if system_tree and not system_tree.item_mouse_selected.is_connected(_on_system_tree_item_mouse_selected): + system_tree.item_mouse_selected.connect(_on_system_tree_item_mouse_selected) + # Connect to system tree for column clicking (for sorting) + if system_tree and not system_tree.column_title_clicked.is_connected(_on_system_tree_column_clicked): + system_tree.column_title_clicked.connect(_on_system_tree_column_clicked) + # Connect to entities tree for column clicking (for sorting) + if entities_tree and not entities_tree.column_title_clicked.is_connected(_on_entities_tree_column_clicked): + entities_tree.column_title_clicked.connect(_on_entities_tree_column_clicked) + # Connect to entities tree for right-click context menu + if entities_tree and not entities_tree.item_mouse_selected.is_connected(_on_entities_tree_item_mouse_selected): + entities_tree.item_mouse_selected.connect(_on_entities_tree_item_mouse_selected) + # Connect to system tree for right-click context menu + if system_tree and not system_tree.button_clicked.is_connected(_on_system_tree_button_clicked): + system_tree.button_clicked.connect(_on_system_tree_button_clicked) + + +func _process(delta: float) -> void: + # No periodic polling; rely on debugger messages only + pass + + +func _update_debug_mode_overlay() -> void: + if not debug_mode_overlay: + return + + # Check if debug mode is enabled in project settings + var debug_enabled = ProjectSettings.get_setting(GecsSettings.SETTINGS_DEBUG_MODE, false) + + # Show overlay if debug mode is disabled, hide if enabled + debug_mode_overlay.visible = not debug_enabled + + +# --- External setters expected by debugger plugin --- +func set_debugger_session(_session): + # Store session reference for sending messages to game + _debugger_session = _session + + +func set_editor_interface(_editor_interface): + # Store editor interface reference for future use (e.g., selecting nodes) + # Currently not used, but expected by the debugger plugin + pass + + +# Send a message from editor to the running game +func send_to_game(message: String, data: Array = []) -> bool: + if _debugger_session == null: + push_warning("GECS Debug: No active debugger session") + return false + _debugger_session.send_message(message, data) + return true + + +func clear_all_data(): + ecs_data.clear() + _pending_components.clear() + + # Clear system tree + if system_tree: + system_tree.clear() + # Recreate root + system_tree.create_item() + + # Clear entities tree + if entities_tree: + entities_tree.clear() + # Recreate root + entities_tree.create_item() + + # Reset status bars + _update_entity_status_bar() + _update_systems_status_bar() + + +# ---- Filters & Refresh Helpers ---- +func _on_entities_filter_changed(new_text: String): + _refresh_entity_tree_filter() + + +func _on_systems_filter_changed(new_text: String): + _refresh_system_tree_filter() + + +# ---- Button Handlers ---- +func _on_collapse_all_pressed(): + collapse_all_entities() + + +func _on_expand_all_pressed(): + expand_all_entities() + + +func _on_systems_collapse_all_pressed(): + collapse_all_systems() + + +func _on_systems_expand_all_pressed(): + expand_all_systems() + + +func _on_pop_out_pressed(): + if _popup_window != null: + # Window already exists, close it and restore content + _on_popup_window_closed() + return + + # Create a new window + _popup_window = Window.new() + _popup_window.title = "GECS Debug Viewer" + _popup_window.size = Vector2i(1200, 800) + _popup_window.initial_position = Window.WINDOW_INITIAL_POSITION_CENTER_SCREEN_WITH_MOUSE_FOCUS + + # Move the main content to the window (not duplicate) + var hsplit = get_node("HSplit") + remove_child(hsplit) + _popup_window.add_child(hsplit) + + # Add window to the scene tree + add_child(_popup_window) + + # Connect close signal + _popup_window.close_requested.connect(_on_popup_window_closed) + + # Show the window + _popup_window.show() + + # Update the button text + pop_out_btn.text = "Pop In" + + +func _on_popup_window_closed(): + if _popup_window != null: + # Move content back to main tab + var hsplit = _popup_window.get_node("HSplit") + _popup_window.remove_child(hsplit) + add_child(hsplit) + move_child(hsplit, 0) # Move to beginning + + # Close and cleanup window + _popup_window.queue_free() + _popup_window = null + pop_out_btn.text = "Pop Out" + + +func _on_system_tree_item_mouse_selected(position: Vector2, mouse_button_index: int): + # When user clicks on a system tree item, check if clicking on status column to toggle or right-click for menu + var selected = system_tree.get_selected() + if not selected: + return + + # Check if has system_id metadata with safe default + var system_id = selected.get_meta("system_id", null) + if system_id == null: + return + + # Only process top-level system items (not child details) + if selected.get_parent() == system_tree.get_root(): + if mouse_button_index == MOUSE_BUTTON_LEFT: + # Get the column that was clicked + var column = system_tree.get_column_at_position(position) + if column == 3: # Status column (now column 3) + _toggle_system_active() + elif mouse_button_index == MOUSE_BUTTON_RIGHT: + _show_system_context_menu(selected, position) + + +func _on_system_tree_button_clicked(item: TreeItem, column: int, id: int, mouse_button_index: int): + # Handle button clicks in tree (currently unused, but keeping for future) + pass + + +func _on_entities_tree_item_mouse_selected(position: Vector2, mouse_button_index: int): + # Handle right-click on entity tree items + if mouse_button_index != MOUSE_BUTTON_RIGHT: + return + + var selected = entities_tree.get_selected() + if not selected: + return + + # Check if has entity_id metadata (top-level entity item) + var entity_id = selected.get_meta("entity_id", null) + if entity_id == null: + return + + # Only show context menu for top-level entity items + if selected.get_parent() == entities_tree.get_root(): + _show_entity_context_menu(selected, position) + + +func _show_entity_context_menu(item: TreeItem, position: Vector2): + var entity_id = item.get_meta("entity_id", null) + if entity_id == null: + return + + var popup = PopupMenu.new() + add_child(popup) + + var is_pinned = _pinned_entities.get(entity_id, false) + if is_pinned: + popup.add_item("Unpin Entity", 0) + else: + popup.add_item("Pin Entity", 0) + + # Position the popup at the mouse position (use get_screen_position for proper screen coords) + var screen_pos = entities_tree.get_screen_position() + position + popup.position = screen_pos + popup.popup() + + # Connect the selection signal + popup.id_pressed.connect(func(id): + if id == 0: + _toggle_entity_pin(entity_id, item) + popup.queue_free() + ) + + # Clean up when popup closes + popup.popup_hide.connect(func(): + if is_instance_valid(popup): + popup.queue_free() + ) + + +func _show_system_context_menu(item: TreeItem, position: Vector2): + var system_id = item.get_meta("system_id", null) + if system_id == null: + return + + var popup = PopupMenu.new() + add_child(popup) + + var is_pinned = _pinned_systems.get(system_id, false) + if is_pinned: + popup.add_item("Unpin System", 0) + else: + popup.add_item("Pin System", 0) + + # Position the popup at the mouse position (use get_screen_position for proper screen coords) + var screen_pos = system_tree.get_screen_position() + position + popup.position = screen_pos + popup.popup() + + # Connect the selection signal + popup.id_pressed.connect(func(id): + if id == 0: + _toggle_system_pin(system_id, item) + popup.queue_free() + ) + + # Clean up when popup closes + popup.popup_hide.connect(func(): + if is_instance_valid(popup): + popup.queue_free() + ) + + +func _toggle_entity_pin(entity_id: int, item: TreeItem): + var is_pinned = _pinned_entities.get(entity_id, false) + _pinned_entities[entity_id] = not is_pinned + _update_entity_pin_display(item, not is_pinned) + # Re-sort to move pinned items to top + if _entity_sort_column != -1 or not is_pinned: + _sort_entity_tree() + + +func _toggle_system_pin(system_id: int, item: TreeItem): + var is_pinned = _pinned_systems.get(system_id, false) + _pinned_systems[system_id] = not is_pinned + _update_system_pin_display(item, not is_pinned) + # Re-sort to move pinned items to top + if _system_sort_column != -1 or not is_pinned: + _sort_system_tree() + + +func _update_entity_pin_display(item: TreeItem, is_pinned: bool): + var current_text = item.get_text(0) + # Remove existing pin icon if present + if current_text.begins_with(ICON_PIN + " "): + current_text = current_text.substr(2) + + if is_pinned: + item.set_text(0, ICON_PIN + " " + current_text) + else: + item.set_text(0, current_text) + + +func _update_system_pin_display(item: TreeItem, is_pinned: bool): + var current_text = item.get_text(0) # Name is in column 0 now + # Remove existing pin icon if present + if current_text.begins_with(ICON_PIN + " "): + current_text = current_text.substr(2) + + if is_pinned: + item.set_text(0, ICON_PIN + " " + current_text) + else: + item.set_text(0, current_text) + + +func _toggle_system_active(): + var selected = system_tree.get_selected() + if not selected: + push_warning("GECS Debug: No system selected") + return + + var system_id = selected.get_meta("system_id", null) + if system_id == null: + push_warning("GECS Debug: No system selected") + return + var systems_data = ecs_data.get("systems", {}) + var system_data = systems_data.get(system_id, {}) + var current_active = system_data.get("active", true) + + # Toggle the state + var new_active = not current_active + + # Send message to game to toggle system active state + send_to_game("gecs:set_system_active", [system_id, new_active]) + + # Optimistically update local state (will be confirmed by game) + system_data["active"] = new_active + _update_system_active_display(selected, new_active) + + +func _update_system_active_display(system_item: TreeItem, is_active: bool): + # Update the visual display of the system in column 3 as a button + if is_active: + system_item.set_text(3, "ACTIVE") + system_item.set_custom_color(3, Color(0.5, 1.0, 0.5)) # Green text + else: + system_item.set_text(3, "INACTIVE") + system_item.set_custom_color(3, Color(1.0, 0.3, 0.3)) # Red text + + # Make the status column a clickable button + system_item.set_cell_mode(3, TreeItem.CELL_MODE_STRING) + system_item.set_selectable(3, true) + system_item.set_editable(3, false) + + +func _on_system_tree_column_clicked(column: int, mouse_button_index: int): + # Only sort on left click + if mouse_button_index != MOUSE_BUTTON_LEFT: + return + + # Cycle through: None -> Asc -> Desc -> None + if _system_sort_column == column: + if _system_sort_ascending: + # Currently ascending, switch to descending + _system_sort_ascending = false + else: + # Currently descending, remove sorting + _system_sort_column = -1 + _system_sort_ascending = true + else: + # New column, start with ascending + _system_sort_column = column + _system_sort_ascending = true + + # Update column title indicators + _update_system_column_indicators() + + # Sort the tree + _sort_system_tree() + + +func _update_system_column_indicators(): + # Clear all column indicators first + for i in range(5): + var title = "" + match i: + 0: title = "Name" + 1: title = "Group" + 2: title = "Time (ms)" + 3: title = "Status" + 4: title = "Order" + + # Add arrow indicator if this is the sort column + if i == _system_sort_column: + if _system_sort_ascending: + title += " ▲" + else: + title += " ▼" + + system_tree.set_column_title(i, title) + + +func _sort_system_tree(): + if not system_tree: + return + + var root = system_tree.get_root() + if not root: + return + + # Collect all system items with their data + var systems: Array = [] + var pinned_systems: Array = [] + var child = root.get_first_child() + while child: + var system_id = child.get_meta("system_id", null) + var system_data = { + "item": child, + "name": child.get_text(0), + "group": child.get_text(1), + "time": 0.0, + "status": child.get_text(3), + "order": int(child.get_text(4)) if child.get_text(4).is_valid_int() else 0, + "system_id": system_id, + "is_pinned": _pinned_systems.get(system_id, false) + } + + # Get execution time from text (remove " ms" suffix if present) + var time_text = child.get_text(2) + if time_text: + system_data["time"] = float(time_text.replace(" ms", "")) + + if system_data["is_pinned"]: + pinned_systems.append(system_data) + else: + systems.append(system_data) + child = child.get_next() + + # Sort based on column (if sorting is active) + if _system_sort_column != -1: + match _system_sort_column: + 0: # Name + if _system_sort_ascending: + systems.sort_custom(func(a, b): return a["name"].nocasecmp_to(b["name"]) < 0) + else: + systems.sort_custom(func(a, b): return a["name"].nocasecmp_to(b["name"]) > 0) + 1: # Group + if _system_sort_ascending: + systems.sort_custom(func(a, b): return a["group"].nocasecmp_to(b["group"]) < 0) + else: + systems.sort_custom(func(a, b): return a["group"].nocasecmp_to(b["group"]) > 0) + 2: # Time + if _system_sort_ascending: + systems.sort_custom(func(a, b): return a["time"] < b["time"]) + else: + systems.sort_custom(func(a, b): return a["time"] > b["time"]) + 3: # Status + if _system_sort_ascending: + systems.sort_custom(func(a, b): return a["status"] < b["status"]) + else: + systems.sort_custom(func(a, b): return a["status"] > b["status"]) + 4: # Order + if _system_sort_ascending: + systems.sort_custom(func(a, b): return a["order"] < b["order"]) + else: + systems.sort_custom(func(a, b): return a["order"] > b["order"]) + + # Rebuild tree: pinned items first, then sorted items + for system_data in pinned_systems: + var item = system_data["item"] + root.remove_child(item) + root.add_child(item) + for system_data in systems: + var item = system_data["item"] + root.remove_child(item) + root.add_child(item) + + +func _on_entities_tree_column_clicked(column: int, mouse_button_index: int): + # Only sort on left click + if mouse_button_index != MOUSE_BUTTON_LEFT: + return + + # Cycle through: None -> Asc -> Desc -> None + if _entity_sort_column == column: + if _entity_sort_ascending: + # Currently ascending, switch to descending + _entity_sort_ascending = false + else: + # Currently descending, remove sorting + _entity_sort_column = -1 + _entity_sort_ascending = true + else: + # New column, start with ascending + _entity_sort_column = column + _entity_sort_ascending = true + + # Update column title indicators + _update_entity_column_indicators() + + # Sort the tree + _sort_entity_tree() + + +func _update_entity_column_indicators(): + # Clear all column indicators first + for i in range(4): + var title = "" + match i: + 0: title = "Entity" + 1: title = "Comps" + 2: title = "Rels" + 3: title = "Nodes" + + # Add arrow indicator if this is the sort column + if i == _entity_sort_column: + if _entity_sort_ascending: + title += " ▲" + else: + title += " ▼" + + entities_tree.set_column_title(i, title) + + +func _sort_entity_tree(): + if not entities_tree: + return + + var root = entities_tree.get_root() + if not root: + return + + # Collect all entity items with their data + var entities: Array = [] + var pinned_entities: Array = [] + var child = root.get_first_child() + while child: + var entity_id = child.get_meta("entity_id", null) + var entity_data = { + "item": child, + "name": child.get_text(0), + "comps": 0, + "rels": 0, + "nodes": 0, + "entity_id": entity_id, + "is_pinned": _pinned_entities.get(entity_id, false) + } + + # Get numeric counts from columns + var comps_text = child.get_text(1) + if comps_text: + entity_data["comps"] = int(comps_text) + + var rels_text = child.get_text(2) + if rels_text: + entity_data["rels"] = int(rels_text) + + var nodes_text = child.get_text(3) + if nodes_text: + entity_data["nodes"] = int(nodes_text) + + if entity_data["is_pinned"]: + pinned_entities.append(entity_data) + else: + entities.append(entity_data) + child = child.get_next() + + # Sort based on column (if sorting is active) + if _entity_sort_column != -1: + match _entity_sort_column: + 0: # Name + if _entity_sort_ascending: + entities.sort_custom(func(a, b): return a["name"].nocasecmp_to(b["name"]) < 0) + else: + entities.sort_custom(func(a, b): return a["name"].nocasecmp_to(b["name"]) > 0) + 1: # Components + if _entity_sort_ascending: + entities.sort_custom(func(a, b): return a["comps"] < b["comps"]) + else: + entities.sort_custom(func(a, b): return a["comps"] > b["comps"]) + 2: # Relationships + if _entity_sort_ascending: + entities.sort_custom(func(a, b): return a["rels"] < b["rels"]) + else: + entities.sort_custom(func(a, b): return a["rels"] > b["rels"]) + 3: # Nodes + if _entity_sort_ascending: + entities.sort_custom(func(a, b): return a["nodes"] < b["nodes"]) + else: + entities.sort_custom(func(a, b): return a["nodes"] > b["nodes"]) + + # Rebuild tree: pinned items first, then sorted items + for entity_data in pinned_entities: + var item = entity_data["item"] + root.remove_child(item) + root.add_child(item) + for entity_data in entities: + var item = entity_data["item"] + root.remove_child(item) + root.add_child(item) + + +# --- Utilities --- +func get_or_create_dict(dict: Dictionary, key, default_val = {}) -> Dictionary: + if not dict.has(key): + dict[key] = default_val + return dict[key] + + +func collapse_all_entities(): + if not entities_tree: + return + var root = entities_tree.get_root() + if root == null: + return + var item = root.get_first_child() + while item: + _collapse_item_recursive(item) + item = item.get_next() + + +func expand_all_entities(): + if not entities_tree: + return + var root = entities_tree.get_root() + if root == null: + return + var item = root.get_first_child() + while item: + _expand_item_recursive(item) + item = item.get_next() + + +func collapse_all_systems(): + if not system_tree: + return + var root = system_tree.get_root() + if root == null: + return + var item = root.get_first_child() + while item: + _collapse_item_recursive(item) + item = item.get_next() + + +func expand_all_systems(): + if not system_tree: + return + var root = system_tree.get_root() + if root == null: + return + var item = root.get_first_child() + while item: + _expand_item_recursive(item) + item = item.get_next() + + +func _collapse_item_recursive(item: TreeItem): + if item == null: + return + item.collapsed = true + var child = item.get_first_child() + while child: + _collapse_item_recursive(child) + child = child.get_next() + + +func _expand_item_recursive(item: TreeItem): + if item == null: + return + item.collapsed = false + var child = item.get_first_child() + while child: + _expand_item_recursive(child) + child = child.get_next() + + +# ---- Filters ---- +func _refresh_system_tree_filter(): + if not system_tree: + return + var root = system_tree.get_root() + if root == null: + return + var filter = systems_filter_line_edit.text.to_lower() if systems_filter_line_edit else "" + var item = root.get_first_child() + while item: + var name = item.get_text(0).to_lower() + item.visible = filter == "" or name.find(filter) != -1 + item = item.get_next() + + +func _refresh_entity_tree_filter(): + if not entities_tree: + return + var root = entities_tree.get_root() + if root == null: + return + var filter = entities_filter_line_edit.text.to_lower() if entities_filter_line_edit else "" + var item = root.get_first_child() + while item: + var label = item.get_text(0).to_lower() + var matches = filter == "" or label.find(filter) != -1 + if not matches: + var comp_child = item.get_first_child() + while comp_child and not matches: + if comp_child.get_text(0).to_lower().find(filter) != -1: + matches = true + break + var prop_row = comp_child.get_first_child() + while prop_row and not matches: + if prop_row.get_text(0).to_lower().find(filter) != -1: + matches = true + break + prop_row = prop_row.get_next() + comp_child = comp_child.get_next() + item.visible = matches + item = item.get_next() + + +func world_init(world_id: int, world_path: NodePath): + # Initialize world tracking + var world_dict := get_or_create_dict(ecs_data, "world") + world_dict["id"] = world_id + world_dict["path"] = world_path + # Update debug mode overlay in case settings changed + _update_debug_mode_overlay() + + +func set_world(world_id: int, world_path: NodePath): + # Set or update current world + var world_dict := get_or_create_dict(ecs_data, "world") + world_dict["id"] = world_id + world_dict["path"] = world_path + + +func process_world(delta: float, group_name: String): + var world_dict := get_or_create_dict(ecs_data, "world") + world_dict["delta"] = delta + world_dict["active_group"] = group_name + + +func exit_world(): + ecs_data["exited"] = true + + +func _update_entity_counts(entity_item: TreeItem, ent_id: int): + # Update the count columns for an entity + if not entity_item: + return + + var entities = ecs_data.get("entities", {}) + var entity_data = entities.get(ent_id, {}) + + # Count components + var components = entity_data.get("components", {}) + entity_item.set_text(1, str(components.size())) + + # Count relationships + var relationships = entity_data.get("relationships", {}) + entity_item.set_text(2, str(relationships.size())) + + # Count child nodes (entities tree doesn't track this from game data) + # We'll count the child TreeItems instead (components + relationships) + var child_count = 0 + var child = entity_item.get_first_child() + while child: + # Count only component and relationship children, not property rows + if child.has_meta("component_id") or child.has_meta("relationship_id"): + child_count += 1 + child = child.get_next() + entity_item.set_text(3, str(child_count)) + + +func _is_flag_component(component_data: Dictionary) -> bool: + # A flag component has no serializable properties + # Check if data is empty or only has the placeholder + if component_data.is_empty(): + return true + if component_data.size() == 1 and component_data.has(""): + return true + return false + + +func entity_added(ent: int, path: NodePath) -> void: + var entities := get_or_create_dict(ecs_data, "entities") + # Merge with any existing (temporary) entry that may already have buffered components/relationships + var existing := entities.get(ent, {}) + var existing_components: Dictionary = existing.get("components", {}) + var existing_relationships: Dictionary = existing.get("relationships", {}) + # Update in place instead of overwrite to avoid losing buffered component data + entities[ent] = { + "path": path, + "active": true, + "components": existing_components, + "relationships": existing_relationships + } + # Add to entities tree + if entities_tree: + var root = entities_tree.get_root() + if root == null: + root = entities_tree.create_item() + var item = entities_tree.create_item(root) + # Column 0: Entity name with icon (and pin icon if pinned) + var display_name = ICON_ENTITY + " " + str(path).get_file() + if _pinned_entities.get(ent, false): + display_name = ICON_PIN + " " + display_name + item.set_text(0, display_name) + item.set_tooltip_text(0, str(ent) + " : " + str(path)) + # Columns 1-3: Counts (will be updated as components/relationships are added) + item.set_text(1, "0") + item.set_text(2, "0") + item.set_text(3, "0") + item.set_meta("entity_id", ent) + item.set_meta("path", path) + item.collapsed = true # Start collapsed + # Flush any pending components that arrived before the entity node was created + if _pending_components.has(ent): + for comp_info in _pending_components[ent]: + _attach_component_to_entity_item(item, ent, comp_info.comp_id, comp_info.comp_path, comp_info.data) + _pending_components.erase(ent) + # Update counts + _update_entity_counts(item, ent) + + # Re-sort if we have an active sort column + if _entity_sort_column != -1: + _sort_entity_tree() + + _update_entity_status_bar() + + +func entity_removed(ent: int, path: NodePath) -> void: + var entities := get_or_create_dict(ecs_data, "entities") + entities.erase(ent) + # Remove from tree + if entities_tree and entities_tree.get_root(): + var root = entities_tree.get_root() + var child = root.get_first_child() + while child: + if child.get_meta("entity_id", null) == ent: + root.remove_child(child) + break + child = child.get_next() + + # Clean up pinned state + _pinned_entities.erase(ent) + + _update_entity_status_bar() + + +func entity_disabled(ent: int, path: NodePath) -> void: + var entities = get_or_create_dict(ecs_data, "entities") + if entities.has(ent): + entities[ent]["active"] = false + if entities_tree and entities_tree.get_root(): + var child = entities_tree.get_root().get_first_child() + while child: + if child.get_meta("entity_id", null) == ent: + child.set_text(0, child.get_text(0) + " (disabled)") + break + child = child.get_next() + + +func entity_enabled(ent: int, path: NodePath) -> void: + var entities = get_or_create_dict(ecs_data, "entities") + if entities.has(ent): + entities[ent]["active"] = true + if entities_tree and entities_tree.get_root(): + var child = entities_tree.get_root().get_first_child() + while child: + if child.get_meta("entity_id", null) == ent: + # Remove any (disabled) suffix + var txt = child.get_text(0) + if txt.ends_with(" (disabled)"): + child.set_text(0, txt.substr(0, txt.length() - 11)) + break + child = child.get_next() + + +func system_added( + sys: int, group: String, process_empty: bool, active: bool, paused: bool, path: NodePath +) -> void: + var systems_data := get_or_create_dict(ecs_data, "systems") + systems_data[sys] = default_system.duplicate() + systems_data[sys]["path"] = path + systems_data[sys]["group"] = group + systems_data[sys]["process_empty"] = process_empty + systems_data[sys]["active"] = active + systems_data[sys]["paused"] = paused + + _update_systems_status_bar() + + +func system_removed(sys: int, path: NodePath) -> void: + var systems_data := get_or_create_dict(ecs_data, "systems") + systems_data.erase(sys) + + # Clean up pinned state + _pinned_systems.erase(sys) + + _update_systems_status_bar() + + +func system_metric(system: int, system_name: String, time: float): + var systems_data := get_or_create_dict(ecs_data, "systems") + var sys_entry := get_or_create_dict(systems_data, system, default_system.duplicate()) + # Track the last run time separately so it's always visible even when aggregation occurs + sys_entry["last_time"] = time + var sys_metrics = ecs_data["systems"][system]["metrics"] + if not sys_metrics: + # Initialize metrics if not present + sys_metrics = {"min_time": time, "max_time": time, "avg_time": time, "count": 1, "last_time": time} + + sys_metrics["min_time"] = min(sys_metrics["min_time"], time) + sys_metrics["max_time"] = max(sys_metrics["max_time"], time) + sys_metrics["count"] += 1 + sys_metrics["avg_time"] = ( + ((sys_metrics["avg_time"] * (sys_metrics["count"] - 1)) + time) / sys_metrics["count"] + ) + sys_metrics["last_time"] = time + ecs_data["systems"][system]["metrics"] = sys_metrics + + _update_systems_status_bar() + + +func system_last_run_data(system_id: int, system_name: String, last_run_data: Dictionary): + var systems_data := get_or_create_dict(ecs_data, "systems") + var sys_entry := get_or_create_dict(systems_data, system_id, default_system.duplicate()) + sys_entry["last_run_data"] = last_run_data + # Update or create tree item + if system_tree: + var root = system_tree.get_root() + if root == null: + root = system_tree.create_item() + # Try to find existing item by metadata matching system_id + var existing: TreeItem = null + var child = root.get_first_child() + while child != null: + if child.get_meta("system_id", null) == system_id: + existing = child + break + child = child.get_next() + if existing == null: + existing = system_tree.create_item(root) + existing.set_meta("system_id", system_id) + existing.collapsed = true # Start collapsed + + # Set main system name in column 0 + var display_name = system_name + # Check if this system is pinned and update display + if _pinned_systems.get(system_id, false): + if not display_name.begins_with(ICON_PIN + " "): + display_name = ICON_PIN + " " + display_name + existing.set_text(0, display_name) + + # Set group in column 1 + var group = sys_entry.get("group", "") + existing.set_text(1, group) + + # Set execution time in column 2 + var exec_ms = last_run_data.get("execution_time_ms", 0.0) + existing.set_text(2, String.num(exec_ms, 3) + " ms") + + # Set active status in column 3 + var is_active = sys_entry.get("active", true) + _update_system_active_display(existing, is_active) + + # Get execution order (index in systems array from last_run_data) - column 4 + var execution_order = last_run_data.get("execution_order", -1) + if execution_order >= 0: + existing.set_text(4, str(execution_order)) + else: + existing.set_text(4, "-") + # Clear previous children to avoid stale data + var prev_child = existing.get_first_child() + while prev_child: + var next_child = prev_child.get_next() + existing.remove_child(prev_child) + prev_child = next_child + # Create nested rows for key info + var ent_count = last_run_data.get("entity_count", null) + var arch_count = last_run_data.get("archetype_count", null) + var parallel = last_run_data.get("parallel", false) + var nested_data := { + "execution_time_ms": String.num(exec_ms, 3), + "entity_count": ent_count, + "archetype_count": arch_count, + "parallel": parallel, + } + for k in nested_data.keys(): + var v = nested_data[k] + if v == null: + continue + var row = system_tree.create_item(existing) + row.set_text(0, str(k) + ": " + str(v)) + # Subsystem details (numeric keys in last_run_data) + for key in last_run_data.keys(): + if typeof(key) == TYPE_INT and last_run_data[key] is Dictionary: + var sub = last_run_data[key] + var sub_row = system_tree.create_item(existing) + sub_row.set_text(0, "subsystem[" + str(key) + "] entity_count: " + str(sub.get("entity_count", 0))) + # Optionally store raw json in metadata for tooltip or future expansion + existing.set_meta("last_run_data", last_run_data.duplicate()) + + # Re-sort if we have an active sort column + if _system_sort_column != -1: + _sort_system_tree() + + # Update status bar with latest system data + _update_systems_status_bar() + + +func entity_component_added(ent: int, comp: int, comp_path: String, data: Dictionary): + var entities := get_or_create_dict(ecs_data, "entities") + var entity := get_or_create_dict(entities, ent) + if not entity.has("components"): + entity["components"] = {} + # Fallback: if serialized data is empty, attempt reflection of exported properties + var final_data = data + if final_data.is_empty(): + final_data = {} + # Try to get the actual Object from instance_id (editor debugger gives us ID only). We can't reliably from here; leave empty. + # As a workaround store a placeholder so UI shows component node. + final_data[""] = true + entity["components"][comp] = final_data + # Update tree with component node and property children + if entities_tree: + var root = entities_tree.get_root() + if root != null: + var entity_item: TreeItem = null + var child = root.get_first_child() + while child: + if child.get_meta("entity_id", null) == ent: + entity_item = child + break + child = child.get_next() + if entity_item: + # Try to find existing component item to update instead of duplicating + var existing_comp_item: TreeItem = null + var comp_child = entity_item.get_first_child() + while comp_child: + if comp_child.has_meta("component_id") and comp_child.get_meta("component_id") == comp: + existing_comp_item = comp_child + break + comp_child = comp_child.get_next() + if existing_comp_item: + # Clear previous property rows + var prev = existing_comp_item.get_first_child() + while prev: + var nxt = prev.get_next() + existing_comp_item.remove_child(prev) + prev = nxt + # Update title/path with icon + var icon = ICON_FLAG if _is_flag_component(final_data) else ICON_COMPONENT + existing_comp_item.set_text(0, icon + " " + comp_path.get_file().get_basename()) + existing_comp_item.set_tooltip_text(0, comp_path) + existing_comp_item.set_meta("component_path", comp_path) + _add_serialized_rows(existing_comp_item, final_data) + else: + _attach_component_to_entity_item(entity_item, ent, comp, comp_path, final_data) + # Update entity counts + _update_entity_counts(entity_item, ent) + else: + # Buffer component until entity_added arrives + if not _pending_components.has(ent): + _pending_components[ent] = [] + _pending_components[ent].append({"comp_id": comp, "comp_path": comp_path, "data": final_data}) + + # Re-sort if we have an active sort column + if _entity_sort_column != -1: + _sort_entity_tree() + + _update_entity_status_bar() + + +func _attach_component_to_entity_item(entity_item: TreeItem, ent: int, comp: int, comp_path: String, final_data: Dictionary) -> void: + var comp_item = entities_tree.create_item(entity_item) + # Use flag icon for components with no properties, otherwise use component icon + var icon = ICON_FLAG if _is_flag_component(final_data) else ICON_COMPONENT + comp_item.set_text(0, icon + " " + comp_path.get_file().get_basename()) + comp_item.set_tooltip_text(0, comp_path) + comp_item.set_meta("component_id", comp) + comp_item.set_meta("component_path", comp_path) + comp_item.collapsed = true # Start collapsed + # Add property rows with recursive serialization + _add_serialized_rows(comp_item, final_data) + # Update entity counts + _update_entity_counts(entity_item, ent) + + +func entity_component_removed(ent: int, comp: int): + var entities = get_or_create_dict(ecs_data, "entities") + if entities.has(ent) and entities[ent].has("components"): + entities[ent]["components"].erase(comp) + if entities_tree and entities_tree.get_root(): + var entity_item: TreeItem = null + var child = entities_tree.get_root().get_first_child() + while child: + if child.get_meta("entity_id", null) == ent: + entity_item = child + break + child = child.get_next() + if entity_item: + var comp_child = entity_item.get_first_child() + while comp_child: + if comp_child.has_meta("component_id") and comp_child.get_meta("component_id") == comp: + entity_item.remove_child(comp_child) + break + comp_child = comp_child.get_next() + # Update entity counts + _update_entity_counts(entity_item, ent) + + _update_entity_status_bar() + + +func entity_component_property_changed( + ent: int, comp: int, property_name: String, old_value: Variant, new_value: Variant +): + var entities = get_or_create_dict(ecs_data, "entities") + if entities.has(ent) and entities[ent].has("components"): + var component = entities[ent]["components"].get(comp) + if component: + component[property_name] = new_value + # Update tree property row + if entities_tree and entities_tree.get_root(): + var entity_item: TreeItem = null + var child = entities_tree.get_root().get_first_child() + while child: + if child.get_meta("entity_id", null) == ent: + entity_item = child + break + child = child.get_next() + if entity_item: + var comp_child = entity_item.get_first_child() + while comp_child: + if comp_child.has_meta("component_id") and comp_child.get_meta("component_id") == comp: + var prop_row = comp_child.get_first_child() + var updated := false + while prop_row: + if prop_row.has_meta("property_name") and prop_row.get_meta("property_name") == property_name: + prop_row.set_text(0, property_name + ": " + str(new_value)) + updated = true + break + prop_row = prop_row.get_next() + # If property row not found (added dynamically), append it + if not updated: + var new_row = entities_tree.create_item(comp_child) + new_row.set_text(0, property_name + ": " + str(new_value)) + new_row.set_meta("property_name", property_name) + # Done updating this component; no need to scan further + break + comp_child = comp_child.get_next() + + +# ---- Recursive Serialization Rendering ---- +func _add_serialized_rows(parent_item: TreeItem, data: Dictionary): + for key in data.keys(): + var value = data[key] + var row = entities_tree.create_item(parent_item) + row.set_text(0, str(key) + ": " + _value_to_string(value)) + row.set_meta("property_name", key) + if value is Dictionary: + _add_serialized_rows(row, value) + elif value is Array: + _add_array_rows(row, value) + + +func _add_array_rows(parent_item: TreeItem, arr: Array): + for i in range(arr.size()): + var value = arr[i] + var row = entities_tree.create_item(parent_item) + row.set_text(0, "[" + str(i) + "] " + _value_to_string(value)) + row.set_meta("property_name", str(i)) + if value is Dictionary: + _add_serialized_rows(row, value) + elif value is Array: + _add_array_rows(row, value) + + +func _value_to_string(v): + match typeof(v): + TYPE_DICTIONARY: + return "{...}" # expanded in children + TYPE_ARRAY: + return "[..." + str(v.size()) + "]" + TYPE_STRING: + return '"' + v + '"' + TYPE_OBJECT: + if v is Resource: + return "Resource(" + v.resource_path.get_file() + ")" + return str(v) + _: + return str(v) + + +func entity_relationship_added(ent: int, rel: int, rel_data: Dictionary): + var entities := get_or_create_dict(ecs_data, "entities") + var entity := get_or_create_dict(entities, ent) + var relationships := get_or_create_dict(entity, "relationships") + relationships[rel] = rel_data + + # Add to tree + if entities_tree: + var root = entities_tree.get_root() + if root != null: + var entity_item: TreeItem = null + var child = root.get_first_child() + while child: + if child.get_meta("entity_id", null) == ent: + entity_item = child + break + child = child.get_next() + + if entity_item: + # Try to find existing relationship item to update + var existing_rel_item: TreeItem = null + var rel_child = entity_item.get_first_child() + while rel_child: + if rel_child.has_meta("relationship_id") and rel_child.get_meta("relationship_id") == rel: + existing_rel_item = rel_child + break + rel_child = rel_child.get_next() + + if existing_rel_item: + # Clear and rebuild + var prev = existing_rel_item.get_first_child() + while prev: + var nxt = prev.get_next() + existing_rel_item.remove_child(prev) + prev = nxt + _update_relationship_item(existing_rel_item, rel_data) + else: + # Create new relationship item + var rel_item = entities_tree.create_item(entity_item) + rel_item.set_meta("relationship_id", rel) + rel_item.collapsed = true # Start collapsed + _update_relationship_item(rel_item, rel_data) + # Update entity counts + _update_entity_counts(entity_item, ent) + + # Re-sort if we have an active sort column + if _entity_sort_column != -1: + _sort_entity_tree() + + _update_entity_status_bar() + + +func _update_relationship_item(rel_item: TreeItem, rel_data: Dictionary): + # Format the relationship display + var relation_type = rel_data.get("relation_type", "Unknown") + var target_type = rel_data.get("target_type", "Unknown") + + # Build the title based on target type with relationship icon + var title = ICON_RELATIONSHIP + " " + relation_type + " -> " + if target_type == "Entity": + var target_data = rel_data.get("target_data", {}) + title += "Entity " + str(target_data.get("path", "Unknown")) + elif target_type == "Component": + var target_data = rel_data.get("target_data", {}) + title += target_data.get("type", "Unknown") + elif target_type == "Archetype": + var target_data = rel_data.get("target_data", {}) + var script_path = target_data.get("script_path", "") + title += "Archetype " + script_path.get_file().get_basename() + elif target_type == "null": + title += "Wildcard" + else: + title += target_type + + rel_item.set_text(0, title) + + # Add relation data as children + var relation_data = rel_data.get("relation_data", {}) + if not relation_data.is_empty(): + var rel_data_item = entities_tree.create_item(rel_item) + rel_data_item.set_text(0, "Relation Properties:") + _add_serialized_rows(rel_data_item, relation_data) + + # Add target data as children (for components with properties) + if target_type == "Component": + var target_data = rel_data.get("target_data", {}) + var target_comp_data = target_data.get("data", {}) + if not target_comp_data.is_empty(): + var target_data_item = entities_tree.create_item(rel_item) + target_data_item.set_text(0, "Target Properties:") + _add_serialized_rows(target_data_item, target_comp_data) + + +func entity_relationship_removed(ent: int, rel: int): + var entities = get_or_create_dict(ecs_data, "entities") + if entities.has(ent) and entities[ent].has("relationships"): + entities[ent]["relationships"].erase(rel) + + # Remove from tree + if entities_tree and entities_tree.get_root(): + var entity_item: TreeItem = null + var child = entities_tree.get_root().get_first_child() + while child: + if child.get_meta("entity_id", null) == ent: + entity_item = child + break + child = child.get_next() + + if entity_item: + var rel_child = entity_item.get_first_child() + while rel_child: + if rel_child.has_meta("relationship_id") and rel_child.get_meta("relationship_id") == rel: + entity_item.remove_child(rel_child) + break + rel_child = rel_child.get_next() + # Update entity counts + _update_entity_counts(entity_item, ent) + + _update_entity_status_bar() + + +# ---- Status Bar Updates ---- + + +## Update the entity status bar with current counts +func _update_entity_status_bar(): + if not entity_status_bar: + return + + var entities = ecs_data.get("entities", {}) + var entity_count = entities.size() + + # Count total components across all entities + var total_components = 0 + for entity_data in entities.values(): + var components = entity_data.get("components", {}) + total_components += components.size() + + # Count total relationships across all entities + var total_relationships = 0 + for entity_data in entities.values(): + var relationships = entity_data.get("relationships", {}) + total_relationships += relationships.size() + + entity_status_bar.text = "Entities: %d | Components: %d | Relationships: %d" % [ + entity_count, + total_components, + total_relationships + ] + + +## Update the systems status bar with execution metrics +func _update_systems_status_bar(): + if not systems_status_bar: + return + + var systems_data = ecs_data.get("systems", {}) + var system_count = systems_data.size() + + # Calculate total execution time and find most expensive system + var total_time_ms = 0.0 + var most_expensive_name = "" + var most_expensive_time = 0.0 + + for system_id in systems_data.keys(): + var system_data = systems_data[system_id] + # Get execution time from last_run_data if available (more accurate than last_time) + var last_run_data = system_data.get("last_run_data", {}) + var exec_time_ms = last_run_data.get("execution_time_ms", 0.0) + + total_time_ms += exec_time_ms + + if exec_time_ms > most_expensive_time: + most_expensive_time = exec_time_ms + # Try to get a readable system name from last_run_data first, then path + var system_name = last_run_data.get("system_name", "") + if not system_name: + var path = system_data.get("path", "") + if path: + system_name = str(path).get_file().get_basename() + else: + system_name = "System_%d" % system_id + most_expensive_name = system_name + + # Format the status bar text + if most_expensive_name: + systems_status_bar.text = "Systems: %d | Total ms: %.1fms | Most Expensive: %s (%.1fms)" % [ + system_count, + total_time_ms, + most_expensive_name, + most_expensive_time + ] + else: + systems_status_bar.text = "Systems: %d | Total ms: %.1fms" % [ + system_count, + total_time_ms + ] diff --git a/addons/gecs/debug/gecs_editor_debugger_tab.gd.uid b/addons/gecs/debug/gecs_editor_debugger_tab.gd.uid new file mode 100644 index 0000000..6067161 --- /dev/null +++ b/addons/gecs/debug/gecs_editor_debugger_tab.gd.uid @@ -0,0 +1 @@ +uid://ca7erogu58fca diff --git a/addons/gecs/debug/gecs_editor_debugger_tab.tscn b/addons/gecs/debug/gecs_editor_debugger_tab.tscn new file mode 100644 index 0000000..754e311 --- /dev/null +++ b/addons/gecs/debug/gecs_editor_debugger_tab.tscn @@ -0,0 +1,169 @@ +[gd_scene load_steps=2 format=3 uid="uid://cbykprebt3jaa"] + +[ext_resource type="Script" uid="uid://ca7erogu58fca" path="res://addons/gecs/debug/gecs_editor_debugger_tab.gd" id="1_8dl00"] + +[node name="GECSEditorDebuggerTab" type="Control"] +layout_mode = 3 +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 +script = ExtResource("1_8dl00") + +[node name="DebugModeOverlay" type="Panel" parent="."] +unique_name_in_owner = true +visible = false +layout_mode = 1 +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 + +[node name="CenterContainer" type="CenterContainer" parent="DebugModeOverlay"] +layout_mode = 1 +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 + +[node name="VBoxContainer" type="VBoxContainer" parent="DebugModeOverlay/CenterContainer"] +layout_mode = 2 + +[node name="Label" type="Label" parent="DebugModeOverlay/CenterContainer/VBoxContainer"] +layout_mode = 2 +theme_type_variation = &"HeaderLarge" +text = "Debug Mode Disabled" +horizontal_alignment = 1 + +[node name="Message" type="Label" parent="DebugModeOverlay/CenterContainer/VBoxContainer"] +layout_mode = 2 +text = "Enable Debug Mode in Project Settings to show Debug Data" +horizontal_alignment = 1 + +[node name="HSpacer" type="Control" parent="DebugModeOverlay/CenterContainer/VBoxContainer"] +custom_minimum_size = Vector2(0, 10) +layout_mode = 2 + +[node name="Instructions" type="Label" parent="DebugModeOverlay/CenterContainer/VBoxContainer"] +layout_mode = 2 +text = "Project Settings > General > GECS > Settings > Debug Mode" +horizontal_alignment = 1 + +[node name="HSplit" type="HSplitContainer" parent="."] +process_mode = 3 +layout_mode = 1 +anchors_preset = 15 +anchor_right = 1.0 +anchor_bottom = 1.0 +grow_horizontal = 2 +grow_vertical = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="HSplitContainer" type="HSplitContainer" parent="HSplit"] +layout_mode = 2 +size_flags_horizontal = 3 + +[node name="EntitiesVBox" type="VBoxContainer" parent="HSplit/HSplitContainer"] +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="HBoxContainer" type="HBoxContainer" parent="HSplit/HSplitContainer/EntitiesVBox"] +layout_mode = 2 + +[node name="EntitiesQueryLineEdit" type="LineEdit" parent="HSplit/HSplitContainer/EntitiesVBox/HBoxContainer"] +unique_name_in_owner = true +layout_mode = 2 +size_flags_horizontal = 3 +placeholder_text = "Entities filter....." + +[node name="CollapseAllBtn" type="Button" parent="HSplit/HSplitContainer/EntitiesVBox/HBoxContainer"] +unique_name_in_owner = true +layout_mode = 2 +text = "Collapse All" + +[node name="ExpandAllBtn" type="Button" parent="HSplit/HSplitContainer/EntitiesVBox/HBoxContainer"] +unique_name_in_owner = true +layout_mode = 2 +text = "Expand All" + +[node name="QueryBuilderCheckBox" type="CheckBox" parent="HSplit/HSplitContainer/EntitiesVBox/HBoxContainer"] +unique_name_in_owner = true +visible = false +layout_mode = 2 +text = "QueryBuilder" + +[node name="EntitiesTree" type="Tree" parent="HSplit/HSplitContainer/EntitiesVBox"] +unique_name_in_owner = true +layout_mode = 2 +size_flags_vertical = 3 +columns = 4 +column_titles_visible = true +allow_rmb_select = true +hide_root = true + +[node name="HBoxContainerEntitiesStatus" type="HBoxContainer" parent="HSplit/HSplitContainer/EntitiesVBox"] +custom_minimum_size = Vector2(0, 33) +layout_mode = 2 + +[node name="EntityStatusBar" type="TextEdit" parent="HSplit/HSplitContainer/EntitiesVBox/HBoxContainerEntitiesStatus"] +unique_name_in_owner = true +layout_mode = 2 +size_flags_horizontal = 3 +text = "Entities: 0 | Components: 0 | Relationships: 0" +editable = false + +[node name="SystemsVBox" type="VBoxContainer" parent="HSplit/HSplitContainer"] +layout_mode = 2 +size_flags_horizontal = 3 +size_flags_vertical = 3 + +[node name="HBoxContainer" type="HBoxContainer" parent="HSplit/HSplitContainer/SystemsVBox"] +layout_mode = 2 + +[node name="SystemsQueryLineEdit" type="LineEdit" parent="HSplit/HSplitContainer/SystemsVBox/HBoxContainer"] +unique_name_in_owner = true +layout_mode = 2 +size_flags_horizontal = 3 +placeholder_text = "Systems filter...." + +[node name="SystemsCollapseAllBtn" type="Button" parent="HSplit/HSplitContainer/SystemsVBox/HBoxContainer"] +unique_name_in_owner = true +layout_mode = 2 +text = "Collapse All" + +[node name="SystemsExpandAllBtn" type="Button" parent="HSplit/HSplitContainer/SystemsVBox/HBoxContainer"] +unique_name_in_owner = true +layout_mode = 2 +text = "Expand All" + +[node name="PopOutBtn" type="Button" parent="HSplit/HSplitContainer/SystemsVBox/HBoxContainer"] +unique_name_in_owner = true +layout_mode = 2 +text = "Pop Out" + +[node name="SystemsTree" type="Tree" parent="HSplit/HSplitContainer/SystemsVBox"] +unique_name_in_owner = true +layout_mode = 2 +size_flags_vertical = 3 +columns = 5 +column_titles_visible = true +hide_root = true +select_mode = 2 + +[node name="HBoxContainerSystemsStatus" type="HBoxContainer" parent="HSplit/HSplitContainer/SystemsVBox"] +custom_minimum_size = Vector2(0, 33) +layout_mode = 2 + +[node name="SystemsStatusBar" type="TextEdit" parent="HSplit/HSplitContainer/SystemsVBox/HBoxContainerSystemsStatus"] +unique_name_in_owner = true +layout_mode = 2 +size_flags_horizontal = 3 +text = "Systems: 0 | Total ms: 0.0ms | Most Expensive: (0.0ms)" +editable = false diff --git a/addons/gecs/docs/BEST_PRACTICES.md b/addons/gecs/docs/BEST_PRACTICES.md new file mode 100644 index 0000000..c4cdb0b --- /dev/null +++ b/addons/gecs/docs/BEST_PRACTICES.md @@ -0,0 +1,724 @@ +# GECS Best Practices Guide + +> **Write maintainable, performant ECS code** + +This guide covers proven patterns and practices for building robust games with GECS. Apply these patterns to keep your code clean, fast, and easy to debug. + +## 📋 Prerequisites + +- Completed [Getting Started Guide](GETTING_STARTED.md) +- Understanding of [Core Concepts](CORE_CONCEPTS.md) + +## 🧱 Component Design Patterns + +### Keep Components Pure Data + +Components should only hold data, never logic or behavior. + +```gdscript +# ✅ Good - Pure data component +class_name C_Health +extends Component + +@export var current: float = 100.0 +@export var maximum: float = 100.0 +@export var regeneration_rate: float = 1.0 + +func _init(max_health: float = 100.0): + maximum = max_health + current = max_health +``` + +```gdscript +# ❌ Avoid - Logic in components +class_name C_Health +extends Component + +@export var current: float = 100.0 +@export var maximum: float = 100.0 + +# This belongs in a system, not a component +func take_damage(amount: float): + current -= amount + if current <= 0: + print("Entity died!") +``` + +### Use Composition Over Inheritance + +Build entities by combining simple components rather than complex inheritance hierarchies. + +```gdscript +# ✅ Good - Composable components via define_components() or scene setup +class_name Player +extends Entity + +func define_components() -> Array: + return [ + C_Health.new(100), + C_Transform.new(), + C_Input.new() + ] + +class_name Enemy +extends Entity + +func define_components() -> Array: + return [ + C_Health.new(50), + C_Transform.new(), + C_AI.new() + ] +``` + +### Design for Configuration + +Make components easily configurable through export properties. + +```gdscript +# ✅ Good - Configurable component +class_name C_Movement +extends Component + +@export var speed: float = 100.0 +@export var acceleration: float = 500.0 +@export var friction: float = 800.0 +@export var max_speed: float = 300.0 +@export var can_fly: bool = false + +func _init(spd: float = 100.0, can_fly_: bool = false): + speed = spd + can_fly = can_fly_ +``` + +## ⚙️ System Design Patterns + +### Single Responsibility Principle + +Each system should handle one specific concern. + +```gdscript +# ✅ Good - Focused systems +class_name MovementSystem extends System +func query(): return q.with_all([C_Position, C_Velocity]) + +class_name RenderSystem extends System +func query(): return q.with_all([C_Position, C_Sprite]) + +class_name HealthSystem extends System +func query(): return q.with_all([C_Health]) +``` + +### Use System Groups for Processing Order + +Organize systems into logical groups using scene-based organization. Systems are grouped in scene nodes and processed in the correct order. + +```gdscript +# main.gd - Process systems in correct order +func _process(delta): + world.process(delta, "run-first") # Initialization systems + world.process(delta, "input") # Input handling + world.process(delta, "gameplay") # Game logic + world.process(delta, "ui") # UI updates + world.process(delta, "run-last") # Cleanup systems + +func _physics_process(delta): + world.process(delta, "physics") # Physics systems + world.process(delta, "debug") # Debug systems +``` + +### Early Exit for Performance + +Return early from system processing when no work is needed. + +```gdscript +# ✅ Good - Early exit patterns +class_name HealthRegenerationSystem extends System + +func query(): + return q.with_all([C_Health]).with_none([C_Dead]) + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var health = entity.get_component(C_Health) + + # Early exit if already at max health + if health.current >= health.maximum: + continue + + # Apply regeneration + health.current = min(health.current + health.regeneration_rate * delta, health.maximum) +``` + +## 🏗️ Code Organization Patterns + +### GECS Naming Conventions + +```gdscript +# ✅ GECS Standard naming patterns: + +# Components: C_ComponentName class, c_component_name.gd file +class_name C_Health extends Component # c_health.gd +class_name C_Position extends Component # c_position.gd + +# Systems: SystemNameSystem class, s_system_name.gd file +class_name MovementSystem extends System # s_movement.gd +class_name RenderSystem extends System # s_render.gd + +# Entities: EntityName class, e_entity_name.gd file +class_name Player extends Entity # e_player.gd +class_name Enemy extends Entity # e_enemy.gd + +# Observers: ObserverNameObserver class, o_observer_name.gd file +class_name HealthUIObserver extends Observer # o_health_ui.gd +``` + +### File Organization + +Organize your ECS files by theme for better scalability: + +``` +project/ +├── components/ +│ ├── ai/ # AI-related components +│ ├── animation/ # Animation components +│ ├── gameplay/ # Core gameplay components +│ ├── gear/ # Equipment/gear components +│ ├── item/ # Item system components +│ ├── multiplayer/ # Multiplayer-specific +│ ├── relationships/ # Relationship components +│ ├── rendering/ # Visual/rendering +│ └── weapon/ # Weapon system +├── entities/ +│ ├── enemies/ # Enemy entities +│ ├── gameplay/ # Core entities +│ ├── items/ # Item entities +│ └── ui/ # UI entities +├── systems/ +│ ├── combat/ # Combat systems +│ ├── core/ # Core ECS systems +│ ├── gameplay/ # Gameplay systems +│ ├── input/ # Input systems +│ ├── interaction/ # Interaction systems +│ ├── physics/ # Physics systems +│ └── ui/ # UI systems +└── observers/ + └── o_transform.gd # Reactive systems +``` + +## 🎮 Common Game Patterns + +### Player Character Pattern + +```gdscript +# e_player.gd +class_name Player +extends Entity + +func on_ready(): + # Common pattern: sync scene transform to component + if has_component(C_Transform): + var transform_comp = get_component(C_Transform) + transform_comp.transform = global_transform + add_to_group("player") +``` + +### Enemy Pattern + +```gdscript +# e_enemy.gd +class_name Enemy +extends Entity + +func on_ready(): + # Sync transform and add to enemy group + if has_component(C_Transform): + var transform_comp = get_component(C_Transform) + transform_comp.transform = global_transform + add_to_group("enemies") +``` + +## 🚀 Performance Best Practices + +### Choose the Right Query Method ⭐ NEW! + +**Query Performance Ranking** (v5.0.0-rc4+): + +```gdscript +# 🏆 FASTEST - Enabled/disabled queries (constant time) +class_name ActiveEntitiesOnly extends System +func query(): + return q.enabled(true) # ~0.05ms for any number of entities + +# 🥈 EXCELLENT - Component queries (heavily optimized) +class_name MovementSystem extends System +func query(): + return q.with_all([C_Position, C_Velocity]) # ~0.6ms for 10K entities + +# 🥉 GOOD - Use with_any strategically +class_name DamageableSystem extends System +func query(): + return q.with_any([C_Player, C_Enemy]).with_all([C_Health]) # ~5.6ms for 10K + +# 🐌 AVOID - Group queries are slowest +class_name PlayerSystem extends System +func query(): + return q.with_group("player") # ~16ms for 10K entities + # Better: q.with_all([C_Player]) +``` + +### Use iterate() for Batch Performance + +```gdscript +# ✅ Good - Batch processing with iterate() +class_name TransformSystem +extends System + +func query(): + # Use iterate() to get component arrays + return q.with_all([C_Transform]).iterate([C_Transform]) + +func process(entities: Array[Entity], components: Array, delta: float): + # Batch access to components for better performance + var transforms = components[0] # C_Transform array from iterate() + for i in range(entities.size()): + entities[i].global_transform = transforms[i].transform +``` + +### Use Specific Queries + +```gdscript +# ✅ BEST - Combine enabled filter with components +class_name ActivePlayerInputSystem extends System +func query(): + return q.with_all([C_Input, C_Movement]).enabled(true) + # Super fast: enabled filtering + component matching + +# ✅ GOOD - Specific component query +class_name ProjectileSystem extends System +func query(): + return q.with_all([C_Projectile, C_Velocity]) # Fast and specific + +# ❌ AVOID - Group-based queries (slow) +class_name PlayerSystem extends System +func query(): + return q.with_group("player") # Use q.with_all([C_Player]) instead + +# ❌ AVOID - Overly broad queries +class_name UniversalMovementSystem extends System +func query(): + return q.with_all([C_Transform]) # Too broad - matches everything +``` + +## 🎭 Entity Prefabs (Scene Files) + +### Using Godot Scenes as Entity Prefabs + +The most powerful pattern in GECS is using Godot's scene system (.tscn files) as entity prefabs. This combines ECS data with Godot's visual editor: + +``` +e_player.tscn Structure: +├── Player (Entity node - extends your e_player.gd class) +│ ├── MeshInstance3D (visual representation) +│ ├── CollisionShape3D (physics collision) +│ ├── AudioStreamPlayer3D (sound effects) +│ └── SkeletonAttachment3D (for equipment) +``` + +**Benefits of Scene-based Prefabs:** + +- **Visual Editing**: Design entities in Godot's 3D editor +- **Component Assignment**: Set up ECS components in the Inspector +- **Godot Integration**: Leverage existing Godot nodes and systems +- **Reusability**: Instantiate the same prefab multiple times +- **Version Control**: Scene files work well with git + +**Setting up Entity Prefabs:** + +1. **Create scene with Entity as root**: `e_player.tscn` with `Player` entity node. + - Another trick here is to add a CharacterBody3d and then extend that CharacterBody3D with the e_player.gd script this way you get Entity class and CharacterBody3D class data +2. **Add visual/physics children**: Add MeshInstance3D, CollisionShape3D, etc. as children +3. **Configure components in Inspector**: Add components to the `component_resources` array +4. **Save as reusable prefab**: Save the .tscn file for instantiation +5. **Set up on_ready()**: Handle any initialization logic + +### Component Assignment in Prefabs + +**Method 1: Inspector Assignment (Recommended)** + +Set up components directly in the Godot Inspector: + +```gdscript +# In e_player.tscn entity root node Inspector: +# Component Resources array: +# - [0] C_Health.new() (max: 100, current: 100) +# - [1] C_Transform.new() (synced with scene transform) +# - [2] C_Input.new() (for player controls) +# - [3] C_LocalPlayer.new() (mark as local player) +``` + +**Method 2: define_components() (Programmatic)** + +```gdscript +# e_player.gd attached to Player.tscn root +class_name Player +extends Entity + +func define_components() -> Array: + return [ + C_Health.new(100), + C_Transform.new(), + C_Input.new(), + C_LocalPlayer.new() + ] + +func on_ready(): + # Initialize after components are ready + if has_component(C_Transform): + var transform_comp = get_component(C_Transform) + transform_comp.transform = global_transform + add_to_group("player") +``` + +**Method 3: Hybrid Approach** + +```gdscript +# Core components via Inspector, dynamic components via script +func on_ready(): + # Sync scene transform to component + if has_component(C_Transform): + var transform_comp = get_component(C_Transform) + transform_comp.transform = global_transform + + # Add conditional components based on game state + if GameState.is_multiplayer: + add_component(C_NetworkSync.new()) + + if GameState.debug_mode: + add_component(C_DebugInfo.new()) +``` + +### Instantiating Entity Prefabs + +**Basic Spawning Pattern:** + +```gdscript +# Spawn system or main scene +@export var player_prefab: PackedScene +@export var enemy_prefab: PackedScene + +func spawn_player(position: Vector3) -> Entity: + var player = player_prefab.instantiate() as Entity + player.global_position = position + get_tree().current_scene.add_child(player) # Add to scene + ECS.world.add_entity(player) # Register with ECS + return player + +func spawn_enemy(position: Vector3) -> Entity: + var enemy = enemy_prefab.instantiate() as Entity + enemy.global_position = position + get_tree().current_scene.add_child(enemy) + ECS.world.add_entity(enemy) + return enemy +``` + +**Advanced Spawning with SpawnSystem:** + +```gdscript +# s_spawner.gd +class_name SpawnerSystem +extends System + +func query(): + return q.with_all([C_SpawnPoint]) + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var spawn_point = entity.get_component(C_SpawnPoint) + + if spawn_point.should_spawn(): + var spawned = spawn_point.prefab.instantiate() as Entity + spawned.global_position = entity.global_position + get_tree().current_scene.add_child(spawned) + ECS.world.add_entity(spawned) + + spawn_point.mark_spawned() +``` + +**Prefab Management Best Practices:** + +```gdscript +# Organize prefabs in preload statements +const PLAYER_PREFAB = preload("res://entities/gameplay/e_player.tscn") +const ENEMY_PREFAB = preload("res://entities/enemies/e_enemy.tscn") +const WEAPON_PREFAB = preload("res://entities/items/e_weapon.tscn") + +# Or use a prefab registry +class_name PrefabRegistry + +static var prefabs = { + "player": preload("res://entities/gameplay/e_player.tscn"), + "enemy": preload("res://entities/enemies/e_enemy.tscn"), + "weapon": preload("res://entities/items/e_weapon.tscn") +} + +static func spawn(prefab_name: String, position: Vector3) -> Entity: + var prefab = prefabs[prefab_name] + var entity = prefab.instantiate() as Entity + entity.global_position = position + get_tree().current_scene.add_child(entity) + ECS.world.add_entity(entity) + return entity +``` + +## 🏗️ Main Scene Architecture + +### Scene Structure Pattern + +Organize your main scene using the proven structure pattern: + +``` +Main.tscn +├── World (World node) +├── DefaultSystems (Node - instantiated from default_systems.tscn) +│ ├── run-first (Node - SystemGroup) +│ │ ├── VictimInitSystem +│ │ └── EcsStorageLoad +│ ├── input (Node - SystemGroup) +│ │ ├── ItemSystem +│ │ ├── WeaponsSystem +│ │ └── PlayerControlsSystem +│ ├── gameplay (Node - SystemGroup) +│ │ ├── GearSystem +│ │ ├── DeathSystem +│ │ └── EventSystem +│ ├── physics (Node - SystemGroup) +│ │ ├── FrictionSystem +│ │ ├── CharacterBody3DSystem +│ │ └── TransformSystem +│ ├── ui (Node - SystemGroup) +│ │ └── UiVisibilitySystem +│ ├── debug (Node - SystemGroup) +│ │ └── DebugLabel3DSystem +│ └── run-last (Node - SystemGroup) +│ ├── ActionsSystem +│ └── PendingDeleteSystem +├── Level (Node3D - for level geometry) +└── Entities (Node3D - spawned entities go here) +``` + +### Systems Setup in Main Scene + +**Scene-based Systems Setup (Recommended)** + +Use scene composition to organize systems. The default_systems.tscn contains all systems organized by execution groups: + +```gdscript +# main.gd - Simple main scene setup +extends Node + +@onready var world: World = $World + +func _ready(): + Bootstrap.bootstrap() # Initialize any game-specific setup + ECS.world = world + # Systems are automatically registered via scene composition +``` + +**Creating a Default Systems Scene:** + +1. Create `default_systems.tscn` with system groups as Node children +2. Add individual system scripts as children of each group +3. Instantiate this scene in your main scene +4. Systems are automatically discovered and registered by the World + +### Processing Systems by Group + +```gdscript +# main.gd - Process systems in correct order +extends Node3D + +func _process(delta): + if ECS.world: + ECS.process(delta, "input") # Handle input first + ECS.process(delta, "core") # Core logic + ECS.process(delta, "gameplay") # Game mechanics + ECS.process(delta, "render") # UI/visual updates last + +func _physics_process(delta): + if ECS.world: + ECS.process(delta, "physics") # Physics systems +``` + +## 🛠️ Common Utility Patterns + +### Transform Synchronization + +Common transform synchronization patterns: + +```gdscript +# Sync entity transform TO component (scene → component) +static func sync_transform_to_component(entity: Entity): + if entity.has_component(C_Transform): + var transform_comp = entity.get_component(C_Transform) + transform_comp.transform = entity.global_transform + +# Sync component transform TO entity (component → scene) +static func sync_component_to_transform(entity: Entity): + if entity.has_component(C_Transform): + var transform_comp = entity.get_component(C_Transform) + entity.global_transform = transform_comp.transform + +# Common usage in entity on_ready() +func on_ready(): + sync_transform_to_component(self) # Sync scene position to C_Transform +``` + +### Component Helpers + +Build helpers for common component operations: + +```gdscript +# Helper functions you can add to your project +static func add_health_to_entity(entity: Entity, max_health: float): + var health = C_Health.new(max_health) + entity.add_component(health) + return health + +static func damage_entity(entity: Entity, amount: float): + if entity.has_component(C_Health): + var health = entity.get_component(C_Health) + health.current = max(0, health.current - amount) + return health.current <= 0 # Return true if entity died + return false +``` + +## 🎛️ Relationship Management Best Practices + +### Limited Removal Patterns + +**Use Descriptive Constants:** + +```gdscript +# ✅ Good - Clear intent with constants +const WEAK_CLEANSE = 1 +const MEDIUM_CLEANSE = 3 +const STRONG_CLEANSE = -1 # All + +# ✅ Good - Stack-based constants +const SINGLE_STACK = 1 +const PARTIAL_STACKS = 3 +const ALL_STACKS = -1 + +func cleanse_debuffs(entity: Entity, power: int): + match power: + 1: entity.remove_relationship(Relations.any_debuff(), WEAK_CLEANSE) + 2: entity.remove_relationship(Relations.any_debuff(), MEDIUM_CLEANSE) + 3: entity.remove_relationship(Relations.any_debuff(), STRONG_CLEANSE) +``` + +**Validate Before Removal:** + +```gdscript +# ✅ Excellent - Safe removal with validation +func safe_partial_heal(entity: Entity, heal_amount: int): + var damage_rels = entity.get_relationships(Relations.any_damage()) + if damage_rels.is_empty(): + print("Entity has no damage to heal") + return + + var to_heal = min(heal_amount, damage_rels.size()) + entity.remove_relationship(Relations.any_damage(), to_heal) + print("Healed ", to_heal, " damage effects") + +# ✅ Good - Helper function with built-in safety +func remove_poison_stacks(entity: Entity, stacks_to_remove: int): + if stacks_to_remove <= 0: + return + entity.remove_relationship(Relations.poison_effect(), stacks_to_remove) +``` + +**System Integration Patterns:** + +```gdscript +# ✅ Excellent - Integration with game systems +class_name StatusEffectSystem extends System + +func process(entities: Array[Entity], components: Array, delta: float): + # Example: process spell casting entities + for entity in entities: + var spell = entity.get_component(C_SpellCaster) + if spell.is_casting_cleanse(): + process_cleanse_spell(entity, spell.target, spell.power) + +func process_cleanse_spell(caster: Entity, target: Entity, spell_power: int): + # Calculate cleanse strength based on spell power and caster stats + var cleanse_strength = calculate_cleanse_strength(caster, spell_power) + + # Apply graduated cleansing based on strength + match cleanse_strength: + 1..3: target.remove_relationship(Relations.any_debuff(), 1) + 4..6: target.remove_relationship(Relations.any_debuff(), 2) + 7..9: target.remove_relationship(Relations.any_debuff(), 3) + _: target.remove_relationship(Relations.any_debuff()) # Remove all + +func process_antidote_item(user: Entity, antidote_strength: int): + # Remove poison based on antidote quality + user.remove_relationship(Relations.poison_effect(), antidote_strength) + + # Remove poison resistance temporarily to prevent immediate repoison + user.add_relationship(Relations.poison_immunity(), 5.0) # 5 second immunity + +class_name InventorySystem extends System + +func consume_item_stack(entity: Entity, item_type: Script, count: int): + # Consume specific number of items from inventory + entity.remove_relationship( + Relationship.new(C_HasItem.new(), item_type), + count + ) + +func use_consumable(entity: Entity, item: Component, quantity: int = 1): + # Use consumable items with quantity + entity.remove_relationship( + Relationship.new(C_HasItem.new(), item), + quantity + ) +``` + +**Performance Optimization:** + +```gdscript +# ✅ Good - Cache relationships for multiple operations +func optimize_bulk_removal(entity: Entity): + # Cache the relationship for reuse + var poison_rel = Relations.poison_effect() + var damage_rel = Relations.any_damage() + + # Multiple targeted removals + entity.remove_relationship(poison_rel, 2) # Remove 2 poison + entity.remove_relationship(damage_rel, 1) # Remove 1 damage + entity.remove_relationship(poison_rel, 1) # Remove 1 more poison + +# ✅ Excellent - Batch removal patterns +func batch_cleanup(entities: Array[Entity]): + var cleanup_rel = Relations.temporary_effect() + + for entity in entities: + # Remove up to 3 temporary effects from each entity + entity.remove_relationship(cleanup_rel, 3) +``` + +## 🎯 Next Steps + +Now that you understand best practices: + +1. **Apply these patterns** in your projects +2. **Learn advanced topics** in [Core Concepts](CORE_CONCEPTS.md) +3. **Optimize performance** with [Performance Guide](PERFORMANCE_OPTIMIZATION.md) + +**Need help?** [Join our Discord](https://discord.gg/eB43XU2tmn) for community discussions and support. + +--- + +_"Good ECS code is like a well-organized toolbox - every component has its place, every system has its purpose, and everything works together smoothly."_ diff --git a/addons/gecs/docs/COMPONENT_QUERIES.md b/addons/gecs/docs/COMPONENT_QUERIES.md new file mode 100644 index 0000000..0d82944 --- /dev/null +++ b/addons/gecs/docs/COMPONENT_QUERIES.md @@ -0,0 +1,182 @@ +# Component Queries in GECS + +> **Advanced property-based entity filtering** + +Component Queries provide a powerful way to filter entities not just based on the presence of components but also on the data within those components. This allows for precise, data-driven entity selection in your game systems. + +## 📋 Prerequisites + +- Understanding of [Core Concepts](CORE_CONCEPTS.md) +- Familiarity with [Basic Queries](CORE_CONCEPTS.md#query-system) + +## 🎯 Introduction + +In standard ECS queries, you filter entities by which components they have or don't have. Component Queries take this further by letting you filter based on the **values** inside those components. + +Instead of just asking "which entities have a HealthComponent?", you can ask "which entities have a HealthComponent with current health less than 20?" + +## Using Component Queries with `QueryBuilder` + +The `QueryBuilder` class allows you to construct queries to retrieve entities that match certain criteria. With component queries, you can specify conditions on component properties within `with_all` and `with_any` methods. + +### Syntax + +A component query is a `Dictionary` that maps a component class to a query `Dictionary` specifying property conditions. + +```gdscript +{ ComponentClass: { property_name: { operator: value } } } +``` + +### Supported Operators + +- `_eq`: Equal to +- `_ne`: Not equal to +- `_gt`: Greater than +- `_lt`: Less than +- `_gte`: Greater than or equal to +- `_lte`: Less than or equal to +- `_in`: Value is in a list +- `_nin`: Value is not in a list + +### Examples + +#### 1. Basic Component Query + +Retrieve entities where `C_TestC.value` is equal to `25`. + +```gdscript +var result = QueryBuilder.new(world).with_all([ + { C_TestC: { "value": { "_eq": 25 } } } +]).execute() +``` + +#### 2. Multiple Conditions on a Single Component + +Retrieve entities where `C_TestC.value` is between `20` and `25`. + +```gdscript +var result = QueryBuilder.new(world).with_all([ + { C_TestC: { "value": { "_gte": 20, "_lte": 25 } } } +]).execute() +``` + +#### 3. Combining Component Queries and Regular Components + +Retrieve entities that have `C_TestD` component and `C_TestC.value` greater than `20`. + +```gdscript +var result = QueryBuilder.new(world).with_all([ + C_TestD, + { C_TestC: { "value": { "_gt": 20 } } } +]).execute() +``` + +#### 4. Using `with_any` with Component Queries + +Retrieve entities where `C_TestC.value` is less than `15` **or** `C_TestD.points` is greater than or equal to `100`. + +```gdscript +var result = QueryBuilder.new(world).with_any([ + { C_TestC: { "value": { "_lt": 15 } } }, + { C_TestD: { "points": { "_gte": 100 } } } +]).execute() +``` + +#### 5. Using `_in` and `_nin` Operators + +Retrieve entities where `C_TestC.value` is either `10` or `25`. + +```gdscript +var result = QueryBuilder.new(world).with_all([ + { C_TestC: { "value": { "_in": [10, 25] } } } +]).execute() +``` + +#### 6. Complex Queries + +Retrieve entities where: + +- `C_TestC.value` is greater than or equal to `25`, and +- `C_TestD.points` is greater than `75` **or** less than `30`, and +- Excludes entities with `C_TestE` component. + +```gdscript +var result = QueryBuilder.new(world).with_all([ + { C_TestC: { "value": { "_gte": 25 } } } +]).with_any([ + { C_TestD: { "points": { "_gt": 75 } } }, + { C_TestD: { "points": { "_lt": 30 } } } +]).with_none([C_TestE]).execute() +``` + +## Important Notes + +- **Component Queries with `with_none`**: Component queries are **not supported** with the `with_none` method. This is because querying properties of components that should not exist on the entity doesn't make logical sense. Use `with_none` to exclude entities that have certain components. + + ```gdscript + # Correct usage of with_none + var result = QueryBuilder.new(world).with_none([C_Inactive]).execute() + ``` + +- **Empty Queries Match All Instances of the Component** + + If you provide an empty query dictionary for a component, it will match all entities that have that component, regardless of its properties. + + ```gdscript + # This will match all entities that have C_TestC component + var result = QueryBuilder.new(world).with_all([ + { C_TestC: {} } + ]).execute() + ``` + +- **Non-existent Properties** + + If you query a property that doesn't exist on the component, it will not match any entities. + + ```gdscript + # Assuming 'non_existent' is not a property of C_TestC + var result = QueryBuilder.new(world).with_all([ + { C_TestC: { "non_existent": { "_eq": 10 } } } + ]).execute() + # result will be empty + ``` + +## Comprehensive Example + +Here's a full example demonstrating several component queries: + +```gdscript +# Setting up entities with components +var entity1 = Entity.new() +entity1.add_component(C_TestC.new(25)) +entity1.add_component(C_TestD.new(100)) + +var entity2 = Entity.new() +entity2.add_component(C_TestC.new(10)) +entity2.add_component(C_TestD.new(50)) + +var entity3 = Entity.new() +entity3.add_component(C_TestC.new(25)) +entity3.add_component(C_TestD.new(25)) + +var entity4 = Entity.new() +entity4.add_component(C_TestC.new(30)) + +world.add_entity(entity1) +world.add_entity(entity2) +world.add_entity(entity3) +world.add_entity(entity4) + +# Query: Entities with C_TestC.value == 25 and C_TestD.points > 50 +var result = QueryBuilder.new(world).with_all([ + { C_TestC: { "value": { "_eq": 25 } } }, + { C_TestD: { "points": { "_gt": 50 } } } +]).execute() +# result will include entity1 +``` + +## Conclusion + +Component Queries extend the querying capabilities of the GECS framework by allowing you to filter entities based on component data. By utilizing the supported operators and combining component queries with traditional component filters, you can precisely target the entities you need for your game's logic. + +For more information on how to use the `QueryBuilder`, refer to the `query_builder.gd` documentation and the test cases in `test_query_builder.gd`. diff --git a/addons/gecs/docs/CORE_CONCEPTS.md b/addons/gecs/docs/CORE_CONCEPTS.md new file mode 100644 index 0000000..0fa1653 --- /dev/null +++ b/addons/gecs/docs/CORE_CONCEPTS.md @@ -0,0 +1,699 @@ +# GECS Core Concepts Guide + +> **Deep understanding of Entity Component System architecture** + +This guide explains the fundamental concepts that make GECS powerful. After reading this, you'll understand how to architect games using ECS principles and leverage GECS's unique features. + +## 📋 Prerequisites + +- Completed [Getting Started Guide](GETTING_STARTED.md) +- Basic GDScript knowledge +- Understanding of Godot's node system + +## 🎯 Why ECS? + +### The Problem with Traditional OOP + +Traditional object-oriented approaches often bundle data and behavior together. Over time, this can become unwieldy and force complicated inheritance structures: + +```gdscript +# ❌ Traditional OOP problems +class BaseCharacter: + # Lots of shared code + +class Player extends BaseCharacter: + # Player-specific code mixed with shared code + +class Enemy extends BaseCharacter: + # Enemy-specific code, some overlap with Player + +class Boss extends Enemy: + # Even more inheritance complexity +``` + +### The ECS Solution + +ECS keeps data (components) separate from logic (systems), providing clear organization around three core concepts: + +1. **Entities** – IDs or "slots" for your game objects +2. **Components** – Pure data objects that define state (e.g., velocity, health) +3. **Systems** – Logic that processes entities with specific components + +This pattern simplifies organization, collaboration, and refactoring. Systems only act upon relevant components. Entities can freely change their makeup without breaking the overall design. + +## 🏗️ GECS Architecture + +GECS extends standard ECS with Godot-specific features: + +- **Integration with Godot nodes** - Entities can be scenes, Components are resources +- **World management** - Central coordination of entities and systems +- **ECS singleton** - Global access point for queries and processing +- **Advanced queries** - Property-based filtering and relationship support +- **Relationship system** - Define complex associations between entities + +## 🎭 Entities + +### Entity Fundamentals + +Entities are the core data containers you work with in GECS. They're Godot nodes extending `Entity.gd` that hold components and relationships. + +**Creating Entities in Code:** + +```gdscript +# Create entity class with components +class_name MyEntity extends Entity + +func define_components() -> Array: + return [C_Transform.new(), C_Velocity.new(Vector3.UP)] + +# Use the entity +var e_my_entity = MyEntity.new() +ECS.world.add_entity(e_my_entity) +``` + +**Entity Prefabs (Recommended):** +Since GECS integrates with Godot, create scenes with Entity root nodes and save as `.tscn` files. These "prefabs" can include child nodes for visualization while maintaining ECS data organization. + +```gdscript +# e_player.gd - Entity prefab +class_name Player +extends Entity + +func on_ready(): + # Sync transform from scene to component + var c_trs = get_component(C_Transform) as C_Transform + if not c_trs: + return + transform_comp.transform = self.global_transform # This works because the TSCN base type is Node3D and we extend Node3D with Entity (Which itself extends from Node) +``` + +### Entity Lifecycle + +Entities have a managed lifecycle: + +1. **Initialization** - Entity added to world, components loaded from `component_resources` +2. **define_components()** - Called to add components via code +3. **on_ready()** - Setup initial states, sync transforms +4. **on_destroy()** - Cleanup before removal +5. **on_disable()/on_enable()** - Handle enable/disable states + +> **Note:** In GECS v5.0+, entity logic should be handled by Systems, not in entity methods. Entities are pure data containers. + +### Entity Naming Conventions + +**GECS follows consistent naming patterns throughout the framework:** + +- **Class names**: `ClassCase` representing the thing they are +- **File names**: `e_entity_name.gd` using snake_case + +**Examples:** + +```gdscript +# e_player.gd +class_name Player extends Entity + +# e_enemy.gd +class_name Enemy extends Entity + +# e_projectile.gd +class_name Projectile extends Entity + +# e_pickup_item.gd +class_name PickupItem extends Entity +``` + +### Entity as Glue Code + +Entities can serve as initialization and connection points: + +```gdscript +class_name Player +extends Entity + +@onready var mesh_instance = $MeshInstance3D +@onready var collision_shape = $CollisionShape3D + +func on_ready(): + # Connect scene nodes to components + var c_sprite = get_component(C_Sprite) + if c_sprite: + sprite_comp.mesh_instance = mesh_instance + + # Sync editor-placed transform to component + var c_trs = get_component(C_Transform) + if c_trs: + transform_comp.transform = self.global_transform +``` + +## 📦 Components + +### Component Fundamentals + +Components are pure data containers - they store state but contain no game logic. They can emit signals for reactive systems. + +```gdscript +# c_health.gd - Example component +class_name C_Health +extends Component + +signal health_changed + +## How much total health this entity has +@export var maximum := 100.0 +## The current health value +@export var current := 100.0 + +func _init(max_health: float = 100.0): + maximum = max_health + current = max_health +``` + +### Component Design Principles + +**Data Only:** + +```gdscript +# ✅ Good - Pure data +class_name C_Health +extends Component + +@export var current: float = 100.0 +@export var maximum: float = 100.0 +@export var regeneration_rate: float = 1.0 +``` + +**No Game Logic:** + +```gdscript +# ❌ Avoid - Logic in components +class_name C_Health +extends Component + +@export var current: float = 100.0 + +func take_damage(amount: float): # This belongs in a system! + current -= amount + if current <= 0: + print("Entity died!") +``` + +### Component Naming Conventions + +**GECS uses a consistent C\_ prefix system:** + +- **Class names**: `C_ComponentName` in ClassCase +- **File names**: `c_component_name.gd` in snake_case +- **Organization**: Group by purpose in folders + +**Examples:** + +```gdscript +# c_health.gd +class_name C_Health extends Component + +# c_transform.gd +class_name C_Transform extends Component + +# c_velocity.gd +class_name C_Velocity extends Component + +# c_user_input.gd +class_name C_UserInput extends Component + +# c_sprite_renderer.gd +class_name C_SpriteRenderer extends Component +``` + +**File Organization:** + +``` +components/ +├── gameplay/ +│ ├── c_health.gd +│ ├── c_damage.gd +│ └── c_inventory.gd +├── physics/ +│ ├── c_transform.gd +│ ├── c_velocity.gd +│ └── c_collision.gd +└── rendering/ + ├── c_sprite.gd + └── c_mesh.gd +``` + +### Adding Components + +**Via Editor (Recommended):** +Add to entity's `component_resources` array in Inspector - these auto-load when entity is added to world. + +**Via define_components():** + +```gdscript +# e_player.gd - Define components programmatically +class_name Player +extends Entity + +func define_components() -> Array: + return [ + C_Health.new(100), + C_Transform.new(), + C_Input.new() + ] + +# Via Inspector: Add to component_resources array +# Components automatically loaded when entity added to world + +# Dynamic addition (less common): +var entity = Player.new() +entity.add_component(C_StatusEffect.new("poison")) +ECS.world.add_entity(entity) +``` + +## ⚙️ Systems + +### System Fundamentals + +Systems contain game logic and process entities based on component queries. They should be small, atomic, and focused on one responsibility. + +Systems have two main parts: + +- **Query** - Defines which entities to process based on components/relationships +- **Process** - The function that runs on entities + +### System Types + +**Entity Processing:** + +```gdscript +class_name LifetimeSystem +extends System + +func query() -> QueryBuilder: + return q.with_all([C_Lifetime]) + +func process(entities: Array[Entity], components: Array, delta: float): + # Process each entity - all systems use the same signature + for entity in entities: + var c_lifetime = entity.get_component(C_Lifetime) as C_Lifetime + c_lifetime.lifetime -= delta + + if c_lifetime.lifetime <= 0: + ECS.world.remove_entity(entity) +``` + +**Optimized Batch Processing with iterate():** + +```gdscript +class_name VelocitySystem +extends System + +func query() -> QueryBuilder: + # Use iterate() to get component arrays for faster access + return q.with_all([C_Velocity]).iterate([C_Velocity]) + +func process(entities: Array[Entity], components: Array, delta: float): + # components[0] contains all C_Velocity components + var velocities = components[0] + + for i in entities.size(): + # Direct array access is faster than get_component() + var position: Vector3 = entities[i].transform.origin + position += velocities[i].velocity * delta + entities[i].transform.origin = position +``` + +### Sub-Systems + +Group related logic into one system file - all subsystems use the unified signature: + +```gdscript +class_name DamageSystem +extends System + +func sub_systems(): + return [ + # [query, callable] - all use same unified process signature + [ + q + .with_all([C_Health, C_Damage]), + damage_entities + ], + [ + q + .with_all([C_Health]) + .with_none([C_Dead]) + .iterate([C_Health]), + regenerate_health + ] + ] + +func damage_entities(entities: Array[Entity], components: Array, delta: float): + # Process entities with damage + for entity in entities: + var c_health = entity.get_component(C_Health) + var c_damage = entity.get_component(C_Damage) + c_health.current -= c_damage.amount + entity.remove_component(c_damage) + + if c_health.current <= 0: + entity.add_component(C_Dead.new()) + +func regenerate_health(entities: Array[Entity], components: Array, delta: float): + # Batch process using component arrays from iterate() + var healths = components[0] + for i in entities.size(): + healths[i].current = min(healths[i].current + 1 * delta, healths[i].maximum) +``` + +### System Dependencies + +Control system execution order with dependencies: + +```gdscript +class_name RenderSystem +extends System + +func deps() -> Dictionary[int, Array]: + return { + Runs.After: [MovementSystem, TransformSystem], # Run after these + Runs.Before: [UISystem] # Run before this + } + +# Special case: run after ALL other systems +class_name TransformSystem +extends System + +func deps() -> Dictionary[int, Array]: + return { + Runs.After: [ECS.wildcard] # Runs after everything else + } +``` + +### System Naming Conventions + +- **Class names**: `SystemNameSystem` in ClassCase (TransformSystem, PhysicsSystem) +- **File names**: `s_system_name.gd` (s_transform.gd, s_physics.gd) + +### System Lifecycle + +Systems follow Godot node lifecycle: + +- `setup()` - Initial setup after system is added to world +- `process(entities, components, delta)` - Unified method called each frame for matching entities +- System groups for organized processing order + +## 🔍 Query System + +### Query Builder + +GECS uses a fluent API for building entity queries: + +```gdscript +ECS.world.query + .with_all([C_Health, C_Position]) # Must have all these components + .with_any([C_Player, C_Enemy]) # Must have at least one of these + .with_none([C_Dead, C_Disabled]) # Must not have any of these + .with_relationship([r_attacking_player]) # Must have these relationships + .without_relationship([r_fleeing]) # Must not have these relationships + .with_reverse_relationship([r_parent_of]) # Must be target of these relationships + .iterate([C_Health]) # Fetch these components and add to components array for quick iteration +``` + +### Query Methods + +**Basic Query Operations:** + +```gdscript +var entities = query.execute() # Get matching entities +var filtered = query.matches(entity_list) # Filter existing list +var combined = query.combine(another_query) # Combine queries +``` + +### Query Types Explained + +**with_all** - Entities must have ALL specified components: + +```gdscript +# Find entities that can move and be damaged +q.with_all([C_Position, C_Velocity, C_Health]) +``` + +**with_any** - Entities must have AT LEAST ONE of the components: + +```gdscript +# Find players or enemies (anything controllable) +q.with_any([C_Player, C_Enemy]) +``` + +**with_none** - Entities must NOT have any of these components: + +```gdscript +# Find living entities (exclude dead/disabled) +q.with_all([C_Health]).with_none([C_Dead, C_Disabled]) +``` + +### Component Property Queries + +Query based on component data values: + +```gdscript +# Find entities with low health +q.with_all([{C_Health: {"current": {"_lt": 20}}}]) + +# Find fast-moving entities +q.with_all([{C_Velocity: {"speed": {"_gt": 100}}}]) + +# Find entities with specific states +q.with_all([{C_State: {"current_state": {"_eq": "attacking"}}}]) +``` + +**Supported Operators:** + +- `_eq` - Equal to +- `_ne` - Not equal to +- `_gt` - Greater than +- `_lt` - Less than +- `_gte` - Greater than or equal +- `_lte` - Less than or equal +- `_in` - Value in list +- `_nin` - Value not in list + +## 🔗 Relationships + +### Relationship Fundamentals + +Relationships link entities together for complex associations. They consist of: + +- **Source** - Entity that has the relationship +- **Relation** - Component defining the relationship type +- **Target** - Entity or type being related to + +```gdscript +# Create relationship components +class_name C_Likes extends Component +class_name C_Loves extends Component +class_name C_Eats extends Component +@export var quantity: int = 1 + +# Create entities +var e_bob = Entity.new() +var e_alice = Entity.new() +var e_heather = Entity.new() +var e_apple = Food.new() + +# Add relationships +e_bob.add_relationship(Relationship.new(C_Likes.new(), e_alice)) # bob likes alice +e_alice.add_relationship(Relationship.new(C_Loves.new(), e_heather)) # alice loves heather +e_heather.add_relationship(Relationship.new(C_Likes.new(), Food)) # heather likes food (type) +e_heather.add_relationship(Relationship.new(C_Eats.new(5), e_apple)) # heather eats 5 apples +``` + +### Relationship Queries + +**Specific Relationships:** + +```gdscript +# Any entity that likes alice +ECS.world.query.with_relationship([Relationship.new(C_Likes.new(), e_alice)]) + +# Any entity that eats 5 apples +ECS.world.query.with_relationship([Relationship.new(C_Eats.new(5), e_apple)]) + +# Any entity that likes the Food type +ECS.world.query.with_relationship([Relationship.new(C_Likes.new(), Food)]) +``` + +**Wildcard Relationships:** + +```gdscript +# Any entity with any relation toward heather +ECS.world.query.with_relationship([Relationship.new(ECS.wildcard, e_heather)]) + +# Any entity that likes anything +ECS.world.query.with_relationship([Relationship.new(C_Likes.new(), ECS.wildcard)]) + +# Any entity with any relation to Enemy type +ECS.world.query.with_relationship([Relationship.new(ECS.wildcard, Enemy)]) +``` + +**Reverse Relationships:** + +```gdscript +# Find entities that are being liked by someone +ECS.world.query.with_reverse_relationship([Relationship.new(C_Likes.new(), ECS.wildcard)]) +``` + +### Relationship Best Practices + +**Reuse Relationship Objects:** + +```gdscript +# Reuse for performance +var r_likes_apples = Relationship.new(C_Likes.new(), e_apple) +var r_attacking_players = Relationship.new(C_IsAttacking.new(), Player) + +# Consider a static relationships class +class_name Relationships + +static func attacking_players(): + return Relationship.new(C_IsAttacking.new(), Player) + +static func chasing_anything(): + return Relationship.new(C_IsChasing.new(), ECS.wildcard) +``` + +## 🌍 World Management + +### World Lifecycle + +The World is the central manager for all entities and systems: + +```gdscript +# main.gd - Simple scene-based setup +extends Node + +@onready var world: World = $World + +func _ready(): + Bootstrap.bootstrap() # Initialize game-specific setup + ECS.world = world + # Systems are automatically registered via scene composition + +# Process systems by groups in order +func _process(delta): + world.process(delta, "run-first") # Initialization + world.process(delta, "input") # Input handling + world.process(delta, "gameplay") # Game logic + world.process(delta, "ui") # UI updates + world.process(delta, "run-last") # Cleanup + +func _physics_process(delta): + world.process(delta, "physics") # Physics systems + world.process(delta, "debug") # Debug systems +``` + +### System Groups and Processing Order + +Organize systems using scene-based composition with execution groups: + +``` +default_systems.tscn Structure: +├── run-first (SystemGroup) +│ ├── VictimInitSystem +│ └── EcsStorageLoad +├── input (SystemGroup) +│ ├── ItemSystem +│ ├── WeaponsSystem +│ └── PlayerControlsSystem +├── gameplay (SystemGroup) +│ ├── GearSystem +│ ├── DeathSystem +│ └── EventSystem +├── physics (SystemGroup) +│ ├── FrictionSystem +│ ├── CharacterBody3DSystem +│ └── TransformSystem +├── ui (SystemGroup) +│ └── UiVisibilitySystem +├── debug (SystemGroup) +│ └── DebugLabel3DSystem +└── run-last (SystemGroup) + ├── ActionsSystem + └── PendingDeleteSystem +``` + +**Scene Setup Benefits:** + +- **Visual Organization**: See system hierarchy in Godot editor +- **Easy Reordering**: Drag systems between groups +- **Inspector Configuration**: Set system properties in editor +- **Reusable Scenes**: Share system configurations between projects + +## 🔄 Data-Driven Architecture + +### Composition Over Inheritance + +Build entities by combining simple components rather than complex inheritance: + +```gdscript +# ✅ Composition approach in entity definition +class_name Player extends Entity + +func define_components() -> Array: + return [ + C_Health.new(100), + C_Movement.new(200.0), + C_Input.new(), + C_Inventory.new() + ] + +# Same components reused for different entity types +enemy.add_component(C_Health.new(50)) +enemy.add_component(C_Movement.new(100.0)) +enemy.add_component(C_AI.new()) +enemy.add_component(C_Sprite.new("enemy.png")) +``` + +### Modular System Design + +Keep systems small and focused: + +```gdscript +# ✅ Focused systems +class_name MovementSystem extends System +# Only handles position updates + +class_name CollisionSystem extends System +# Only handles collision detection + +class_name HealthSystem extends System +# Only handles health changes +``` + +This ensures: + +- **Easier debugging** - Clear separation of concerns +- **Better reusability** - Systems work across different entity types +- **Simplified testing** - Each system can be tested independently +- **Performance optimization** - Systems can be profiled and optimized individually + +## 🎯 Next Steps + +Now that you understand GECS's core concepts: + +1. **Apply these patterns** in your own projects +2. **Experiment with relationships** for complex entity interactions +3. **Design component hierarchies** that support your game's needs +4. **Learn optimization techniques** in [Performance Guide](PERFORMANCE_OPTIMIZATION.md) +5. **Master common patterns** in [Best Practices Guide](BEST_PRACTICES.md) + +## 📚 Related Documentation + +- **[Getting Started](GETTING_STARTED.md)** - Build your first ECS project +- **[Best Practices](BEST_PRACTICES.md)** - Write maintainable ECS code +- **[Performance Optimization](PERFORMANCE_OPTIMIZATION.md)** - Make your games run fast +- **[Troubleshooting](TROUBLESHOOTING.md)** - Solve common issues + +--- + +_"Understanding ECS is about shifting from 'what things are' to 'what things have' and 'what operates on them.' This separation of data and logic is the key to scalable game architecture."_ diff --git a/addons/gecs/docs/DEBUG_VIEWER.md b/addons/gecs/docs/DEBUG_VIEWER.md new file mode 100644 index 0000000..dbb80dd --- /dev/null +++ b/addons/gecs/docs/DEBUG_VIEWER.md @@ -0,0 +1,357 @@ +# Debug Viewer + +> **Real-time debugging and visualization for your ECS projects** + +The GECS Debug Viewer provides live inspection of entities, components, systems, and relationships while your game is running. Perfect for understanding entity behavior, optimizing system performance, and debugging complex interactions. + +## 📋 Prerequisites + +- GECS plugin enabled in your project +- Debug mode enabled: `Project > Project Settings > GECS > Debug Mode` +- Game running from the editor (F5 or F6) + +## 🎯 Quick Start + +### Opening the Debug Viewer + +1. **Run your game** from the Godot editor (F5 for current scene, F6 for main scene) +2. **Open the debugger panel** (bottom of editor, usually appears automatically) +3. **Click the "GECS" tab** next to "Debugger", "Errors", and "Profiler" + +> 💡 **Debug Mode Required**: If you see an overlay saying "Debug mode is disabled", go to `Project > Project Settings > GECS` and enable "Debug Mode" + +## 🔍 Features Overview + +The debug viewer is split into two main panels: + +### Systems Panel (Right) + +Monitor system execution and performance in real-time. + +**Features:** + +- **System execution time** - See how long each system takes to process (milliseconds) +- **Entity count** - Number of entities processed per system +- **Active/Inactive status** - Toggle systems on/off at runtime +- **Sortable columns** - Click column headers to sort by name, time, or status +- **Performance metrics** - Archetype count, parallel processing info + +**Status Bar:** + +- Total system count +- Combined execution time +- Most expensive system highlighted + +### Entities Panel (Left) + +Inspect individual entities and their components. + +**Features:** + +- **Entity hierarchy** - See all entities in your world +- **Component data** - View component properties in real-time (WIP) +- **Relationships** - Visualize entity connections and associations +- **Search/filter** - Find entities or components by name + +## 🎮 Using the Debug Viewer + +### Monitoring System Performance + +**Sort by execution time:** + +1. Click the **"Time (ms)"** column header in the Systems panel +2. Systems are now sorted by performance (slowest first by default) +3. Click again to reverse the sort order + +**Identify bottlenecks:** + +- Look for systems with high execution times (> 5ms) +- Check the entity count - more entities = more processing +- Consider optimization strategies from [Performance Optimization](PERFORMANCE_OPTIMIZATION.md) + +**Example:** + +``` +Name Time (ms) Status +PhysicsSystem 8.234 ms ACTIVE ← Bottleneck! +RenderSystem 2.156 ms ACTIVE +AISystem 0.892 ms ACTIVE +``` + +### Toggling Systems On/Off + +**Disable a system at runtime:** + +1. Locate the system in the Systems panel +2. Click on the **Status** column (shows "ACTIVE" or "INACTIVE") +3. System immediately stops processing entities +4. Click again to re-enable + +**Use cases:** + +- Test game behavior without specific systems +- Isolate bugs by disabling systems one at a time +- Temporarily disable expensive systems during debugging +- Verify system dependencies + +> ⚠️ **Important**: System state resets when you restart the game. This is a debugging tool, not a save/load feature. + +### Inspecting Entities + +**View entity components:** + +1. Expand an entity in the Entities panel +2. See all attached components (e.g., `C_Health`, `C_Transform`) +3. Expand a component to view its properties +4. Values update in real-time as your game runs + +**Example entity structure:** + +``` +Entity #123 : /root/World/Player +├── C_Health +│ ├── current: 87.5 +│ └── maximum: 100.0 +├── C_Transform +│ └── position: (15.2, 0.0, 23.8) +└── C_Velocity + └── velocity: (2.5, 0.0, 1.3) +``` + +### Viewing Relationships + +Relationships show how entities are connected to each other. + +**Relationship types displayed:** + +- **Entity → Entity**: `Relationship: C_ChildOf -> Entity /root/World/Parent` +- **Entity → Component**: `Relationship: C_Damaged -> C_FireDamage` +- **Entity → Archetype**: `Relationship: C_Buff -> Archetype Player` +- **Entity → Wildcard**: `Relationship: C_Damage -> Wildcard` + +**Expand relationships to see:** + +- Relation component properties +- Target component properties (for component relationships) +- Full relationship metadata + +> 💡 **Learn More**: See [Relationships](RELATIONSHIPS.md) for details on creating and querying entity relationships + +### Using Search and Filters + +**Systems panel:** + +- Type in the "Filter Systems" box to find systems by name +- Only matching systems remain visible + +**Entities panel:** + +- Type in the "Filter Entities" box to search +- Searches entity names, component names, and property names +- Useful for finding specific entities in large worlds + +### Multi-Monitor Setup + +**Pop-out window:** + +1. Click **"Pop Out"** button at the top of the debug viewer +2. Debug viewer moves to a separate window +3. Position on second monitor for permanent visibility +4. Click **"Pop In"** to return to the editor tab + +**Benefits:** + +- Keep debug info visible while editing scenes +- Monitor performance during gameplay +- Track entity changes without switching panels + +### Collapse/Expand Controls + +**Quick controls:** + +- **Collapse All** / **Expand All** - Manage all entities at once +- **Systems Collapse All** / **Systems Expand All** - Manage all systems at once +- Individual items can be collapsed/expanded by clicking + +## 🔧 Common Workflows + +### Performance Optimization Workflow + +1. **Sort systems by execution time** (click "Time (ms)" header) +2. **Identify slowest system** (top of sorted list) +3. **Expand system details** to see entity count and archetype count +4. **Review system implementation** for optimization opportunities +5. **Apply optimizations** from [Performance Optimization](PERFORMANCE_OPTIMIZATION.md) +6. **Re-run and compare** execution times + +### Debugging Workflow + +1. **Identify the problematic entity** using search/filter +2. **Expand entity** to view all components +3. **Watch component values** update in real-time +4. **Toggle related systems off/on** to isolate the issue +5. **Check relationships** if entity interactions are involved +6. **Fix the issue** in your code + +### Testing System Dependencies + +1. **Run your game** from the editor +2. **Disable systems one at a time** using the Status column +3. **Observe game behavior** for each disabled system +4. **Document dependencies** you discover +5. **Design systems to be more independent** if needed + +## 📊 Understanding System Metrics + +When you expand a system in the Systems panel, you'll see detailed metrics: + +**Execution Time (ms):** + +- Time spent in the system's `process()` function +- Lower is better (aim for < 1ms for most systems) +- Spikes indicate performance issues + +**Entity Count:** + +- Number of entities that matched the system's query +- High counts + high execution time = optimization needed +- Zero entities may indicate query issues + +**Archetype Count:** + +- Number of unique component combinations processed +- Higher counts can impact performance +- See [Performance Optimization](PERFORMANCE_OPTIMIZATION.md#archetype-optimization) + +**Parallel Processing:** + +- `true` if system uses parallel iteration +- `false` for sequential processing +- Parallel systems can process entities faster + +**Subsystem Info:** + +- For multi-subsystem systems (advanced feature) +- Shows entity count per subsystem + +## ⚠️ Troubleshooting + +### Debug Viewer Shows "Debug mode is disabled" + +**Solution:** + +1. Go to `Project > Project Settings` +2. Navigate to `GECS` category +3. Enable "Debug Mode" checkbox +4. Restart your game + +> 💡 **Performance Note**: Debug mode adds overhead. Disable it for production builds. + +### No Entities/Systems Appearing + +**Possible causes:** + +1. Game isn't running - Press F5 or F6 to run from editor +2. World not created - Verify `ECS.world` exists in your code +3. Entities/Systems not added to world - Check `world.add_child()` calls + +### Component Properties Not Updating + +**Solution:** + +- Component properties update when they change +- Properties without `@export` won't be visible +- Make sure your systems are modifying component properties correctly + +### Systems Not Toggling + +**Possible causes:** + +1. System has `paused` property set - Check system code +2. Debugger connection lost - Restart the game +3. System is critical - Some systems might ignore toggle requests + +## 🎯 Best Practices + +### During Development + +✅ **Do:** + +- Keep debug viewer open while testing gameplay +- Sort systems by time regularly to catch performance regressions +- Use entity search to track specific entities +- Disable systems to test game behavior + +❌ **Don't:** + +- Leave debug mode enabled in production builds +- Rely on system toggling for game logic (use proper activation patterns) +- Expect perfect frame timing (debug mode adds overhead) + +### For Performance Tuning + +1. **Baseline first**: Run game without debug viewer, note FPS +2. **Enable debug viewer**: Identify expensive systems +3. **Focus on top 3**: Optimize the slowest systems first +4. **Measure impact**: Re-check execution times after changes +5. **Disable debug mode**: Always profile final builds without debug overhead + +## 🚀 Advanced Tips + +### Custom Component Serialization + +If your component properties aren't showing up properly: + +```gdscript +# Mark properties with @export for debug visibility +class_name C_CustomData +extends Component + +@export var visible_property: int = 0 # ✅ Shows in debug viewer +var hidden_property: int = 0 # ❌ Won't appear +``` + +### Relationship Debugging + +Use the debug viewer to verify complex relationship queries: + +1. **Create test entities** with relationships +2. **Check relationship display** in Entities panel +3. **Verify relationship properties** are correct +4. **Test relationship queries** in your systems + +### Performance Profiling Workflow + +Combine debug viewer with Godot's profiler: + +1. **Debug Viewer**: Identify slow ECS systems +2. **Godot Profiler**: Deep-dive into specific functions +3. **Fix bottlenecks**: Optimize based on both tools +4. **Verify improvements**: Check both metrics improve + +## 📚 Related Documentation + +- **[Core Concepts](CORE_CONCEPTS.md)** - Understanding entities, components, and systems +- **[Performance Optimization](PERFORMANCE_OPTIMIZATION.md)** - Optimize systems identified as bottlenecks +- **[Relationships](RELATIONSHIPS.md)** - Working with entity relationships +- **[Troubleshooting](TROUBLESHOOTING.md)** - Common issues and solutions + +## 💡 Summary + +The Debug Viewer is your window into the ECS runtime. Use it to: + +- 🔍 Monitor system performance and identify bottlenecks +- 🎮 Inspect entities and components in real-time +- 🔗 Visualize relationships between entities +- ⚡ Toggle systems on/off for debugging +- 📊 Track entity counts and archetype distribution + +> **Pro Tip**: Pop out the debug viewer to a second monitor and leave it visible while developing. You'll catch performance issues and bugs much faster! + +--- + +**Next Steps:** + +- Learn about [Performance Optimization](PERFORMANCE_OPTIMIZATION.md) to fix bottlenecks you discover +- Explore [Relationships](RELATIONSHIPS.md) to understand entity connections better +- Check [Troubleshooting](TROUBLESHOOTING.md) if you encounter issues diff --git a/addons/gecs/docs/GETTING_STARTED.md b/addons/gecs/docs/GETTING_STARTED.md new file mode 100644 index 0000000..cf406f6 --- /dev/null +++ b/addons/gecs/docs/GETTING_STARTED.md @@ -0,0 +1,341 @@ +# Getting Started with GECS + +> **Build your first ECS project in 5 minutes** + +This guide will walk you through creating a simple player entity with health and transform components using GECS. By the end, you'll understand the core concepts and have a working example. + +## 📋 Prerequisites + +- Godot 4.x installed +- Basic GDScript knowledge +- 5 minutes of your time + +## ⚡ Step 1: Setup (1 minute) + +### Install GECS + +1. **Download GECS** and place it in your project's `addons/` folder +2. **Enable the plugin**: Go to `Project > Project Settings > Plugins` and enable "GECS" +3. **Verify setup**: The ECS singleton should be automatically added to AutoLoad + +> 💡 **Quick Check**: If you see errors, make sure `ECS` appears in `Project > Project Settings > AutoLoad` + +## 🎮 Step 2: Your First Entity (2 minutes) + +Entities in GECS extend Godot's `Node` class. You have two options for creating entities: + +### **Option A: Scene-based Entities** (For spatial properties) + +Use this when you need access to `Node3D` or `Node2D` properties like position, rotation, scale, or want to add visual children (sprites, meshes, etc.). + +> ⚠️ **Key Point**: `Entity` extends `Node` (not `Node3D` or `Node2D`), so create a scene with the appropriate spatial node type as the root, then attach your entity script to it. + +**Steps:** + +1. **Create a new scene** in Godot: + - Click `Scene > New Scene` or press `Ctrl+N` + - Select **"Node3D"** as the root node type (for 3D games) or **"Node2D"** (for 2D games) + - Rename the root node to `Player` + +2. **Attach the entity script**: + - With the root node selected, click the "Attach Script" button (📄+ icon) + - Save as `e_player.gd` + +3. **Save the scene**: + - Save as `e_player.tscn` in your scenes folder + +**File: `e_player.gd`** + +```gdscript +# e_player.gd +class_name Player +extends Entity + +func on_ready(): + # Sync the entity's scene position to the Transform component + if has_component(C_Transform): + var c_trs = get_component(C_Transform) as C_Transform + c_trs.position = self.global_position +``` + +> 💡 **Use case**: Players, enemies, projectiles, or anything that needs a position in your game world. + +### **Option B: Code-based Entities** (Pure data containers) + +Use this when you DON'T need spatial properties and just want a pure data container (e.g., game managers, abstract systems, timers). + +```gdscript +# Just extend Entity directly +class_name GameManager +extends Entity + +# No scene needed - instantiate with GameManager.new() +``` + +> 💡 **Use case**: Game state managers, quest trackers, inventory systems, or any non-spatial game logic. + +--- + +**For this tutorial**, we'll use **Option A** (scene-based) since we want our player to move around the screen with a position. + +## 📦 Step 3: Your First Components (1 minute) + +Components hold data. Let's create health and transform components: + +**File: `c_health.gd`** + +```gdscript +# c_health.gd +class_name C_Health +extends Component + +@export var current: float = 100.0 +@export var maximum: float = 100.0 + +func _init(max_health: float = 100.0): + maximum = max_health + current = max_health +``` + +**File: `c_transform.gd`** + +```gdscript +# c_transform.gd +class_name C_Transform +extends Component + +@export var position: Vector3 = Vector3.ZERO + +func _init(pos: Vector3 = Vector3.ZERO): + position = pos +``` + +**File: `c_velocity.gd`** + +```gdscript +# c_velocity.gd +class_name C_Velocity +extends Component + +@export var velocity: Vector3 = Vector3.ZERO + +func _init(vel: Vector3 = Vector3.ZERO): + velocity = vel +``` + +> 💡 **Key Principle**: Components only hold data, never logic. Think of them as data containers. +> ⚠️ **Important Note**: Components `_init` function requires that all arguments have a default value or Godot will crash. + +## ⚙️ Step 4: Your First System (1 minute) + +Systems contain the logic that operates on entities with specific components. This system moves entities across the screen: + +**File: `s_movement.gd`** + +```gdscript +# s_movement.gd +class_name MovementSystem +extends System + +func query(): + # Find all entities that have both transform and velocity + return q.with_all([C_Transform, C_Velocity]) + +func process(entities: Array[Entity], components: Array, delta: float): + # Process each entity in the array + for entity in entities: + var c_trs = entity.get_component(C_Transform) as C_Transform + var c_velocity = entity.get_component(C_Velocity) as C_Velocity + + # Move the entity based on its velocity + c_trs.position += c_velocity.velocity * delta + + # Update the actual entity position in the scene + entity.global_position = c_trs.position + + # Bounce off screen edges (simple example) + if c_trs.position.x > 10 or c_trs.position.x < -10: + c_velocity.velocity.x *= -1 +``` + +> 💡 **System Logic**: Query finds entities with required components, process() runs the movement logic on each entity every frame. + +## 🎬 Step 5: See It Work (1 minute) + +Now let's put it all together in a main scene: + +### Create Main Scene + +1. **Create a new scene** with a `Node` as the root +2. **Add a World node** as a child (Add Child Node > search for "World") +3. **Attach this script** to the root node: + +**File: `main.gd`** + +```gdscript +# main.gd +extends Node + +@onready var world: World = $World + +func _ready(): + ECS.world = world + + # Load and instantiate the player entity scene + var player_scene = preload("res://e_player.tscn") # Adjust path as needed + var e_player = player_scene.instantiate() as Player + + # Add components to the entity + e_player.add_components([ + C_Health.new(100), + C_Transform.new(), + C_Velocity.new(Vector3(2, 0, 0)) # Move right at 2 units/second + ]) + + add_child(e_player) # Add to scene tree + ECS.world.add_entity(e_player) # Add to ECS world + + # Create the movement system + var movement_system = MovementSystem.new() + ECS.world.add_system(movement_system) + +func _process(delta): + # Process all systems + if ECS.world: + ECS.process(delta) +``` + +**Run your project!** 🎉 You now have a working ECS setup where the player entity moves across the screen and bounces off the edges! The MovementSystem updates entity positions based on their velocity components. + +> 💡 **Scene-based entities**: Notice we load and instantiate the `e_player.tscn` scene instead of calling `Player.new()`. This is required because we need access to spatial properties (position). For entities that don't need spatial properties, `Entity.new()` works fine. + +## 🎯 What You Just Built + +Congratulations! You've created your first ECS project with: + +- **Entity**: Player - a container for components +- **Components**: C_Health, C_Transform, C_Velocity - pure data containers +- **System**: MovementSystem - logic that moves entities based on velocity +- **World**: Container that manages entities and systems + +## 📈 Next Steps + +Now that you have the basics working, here's how to level up: + +### 1. Create Entity Prefabs (Recommended) + +Instead of creating entities in code, use Godot's scene system: + +1. **Create a new scene** with your Entity class as the root node +2. **Add visual children** (MeshInstance3D, Sprite3D, etc.) +3. **Add components via define_components()** or `component_resources` array in Inspector +4. **Save as .tscn file** (e.g., `e_player.tscn`) +5. **Load and instantiate** in your main scene + +```gdscript +# Improved e_player.gd with define_components() +class_name Player +extends Entity + +func define_components() -> Array: + return [ + C_Health.new(100), + C_Transform.new(), + C_Velocity.new(Vector3(1, 0, 0)) # Move right slowly + ] + +func on_ready(): + # Sync scene position to component + if has_component(C_Transform): + var c_trs = get_component(C_Transform) as C_Transform + c_trs.position = self.global_position +``` + +### 2. Organize Your Main Scene + +Structure your main scene using the proven scene-based pattern: + +``` +Main.tscn +├── World (World node) +├── DefaultSystems (instantiated from default_systems.tscn) +│ ├── input (SystemGroup) +│ ├── gameplay (SystemGroup) +│ ├── physics (SystemGroup) +│ └── ui (SystemGroup) +├── Level (Node3D for static environment) +└── Entities (Node3D for spawned entities) +``` + +**Benefits:** +- **Visual organization** in Godot editor +- **Easy system reordering** between groups +- **Reusable system configurations** + +### 3. Learn More Patterns + +### 🧠 Understand the Concepts + +**→ [Core Concepts Guide](CORE_CONCEPTS.md)** - Deep dive into Entities, Components, Systems, and Relationships + +### 🔧 Add More Features + +Try adding these to your moving player: + +- **Input system** - Add C_Input component and system to control movement with arrow keys +- **Multiple entities** - Create more moving objects with different velocities +- **Collision system** - Add C_Collision component and detect when entities hit each other +- **Gravity system** - Add downward velocity to make entities fall + +### 📚 Learn Best Practices + +**→ [Best Practices Guide](BEST_PRACTICES.md)** - Write maintainable ECS code + +### 🔧 Explore Advanced Features + +- **[Component Queries](COMPONENT_QUERIES.md)** - Filter by component property values +- **[Relationships](RELATIONSHIPS.md)** - Link entities together for complex interactions +- **[Observers](OBSERVERS.md)** - Reactive systems that respond to changes +- **[Performance Optimization](PERFORMANCE_OPTIMIZATION.md)** - Make your games run fast + +## ❓ Having Issues? + +### Player not responding? + +- Check that `ECS.process(delta)` is called in `_process()` +- Verify components are added to the entity via `define_components()` or Inspector +- Make sure the system is added to the world +- Ensure transform synchronization is called in entity's `on_ready()` + +### Can't access position/rotation properties? + +- ⚠️ **Entity extends Node, not Node3D**: To access spatial properties, create a scene with `Node3D` (3D) or `Node2D` (2D) as the root node type +- Attach your entity script (that extends `Entity`) to the Node3D/Node2D root +- Load and instantiate the scene file (don't use `.new()` for spatial entities) +- **If you don't need spatial properties**: Using `Entity.new()` is perfectly fine for pure data containers +- See Step 2 for both entity creation approaches + +### Errors in console? + +- Check that all classes extend the correct base class +- Verify file names match class names +- Ensure GECS plugin is enabled + +**Still stuck?** → [Troubleshooting Guide](TROUBLESHOOTING.md) + +## 🏆 What's Next? + +You're now ready to build amazing games with GECS! The Entity-Component-System pattern will help you: + +- **Scale your game** - Add features without breaking existing code +- **Reuse code** - Components and systems work across different entity types +- **Debug easier** - Clear separation between data and logic +- **Optimize performance** - GECS handles efficient querying for you + +**Ready to dive deeper?** Start with [Core Concepts](CORE_CONCEPTS.md) to really understand what makes ECS powerful. + +**Need help?** [Join our Discord community](https://discord.gg/eB43XU2tmn) for support and discussions. + +--- + +_"The best way to learn ECS is to build with it. Start simple, then add complexity as you understand the patterns."_ diff --git a/addons/gecs/docs/OBSERVERS.md b/addons/gecs/docs/OBSERVERS.md new file mode 100644 index 0000000..82e6339 --- /dev/null +++ b/addons/gecs/docs/OBSERVERS.md @@ -0,0 +1,351 @@ +# Observers in GECS + +> **Reactive systems that respond to component changes** + +Observers provide a reactive programming model where systems automatically respond to component changes, additions, and removals. This allows for decoupled, event-driven game logic. + +## 📋 Prerequisites + +- Understanding of [Core Concepts](CORE_CONCEPTS.md) +- Familiarity with [Systems](CORE_CONCEPTS.md#systems) +- Observers must be added to the World to function + +## 🎯 What are Observers? + +Observers are specialized systems that watch for changes to specific components and react immediately when those changes occur. Instead of processing entities every frame, observers only trigger when something actually changes. + +**Benefits:** + +- **Performance** - Only runs when changes occur, not every frame +- **Decoupling** - Components don't need to know what systems depend on them +- **Reactivity** - Immediate response to state changes +- **Clean Logic** - Separate change-handling logic from regular processing + +## 🔧 Observer Structure + +Observers extend the `Observer` class and implement key methods: + +1. **`watch()`** - Specifies which component to monitor for events (**required** - will crash if not overridden) +2. **`match()`** - Defines a query to filter which entities trigger events (optional - defaults to all entities) +3. **Event Handlers** - Handle specific types of changes + +```gdscript +# o_transform.gd +class_name TransformObserver +extends Observer + +func watch() -> Resource: + return C_Transform # Watch for transform component changes (REQUIRED) + +func on_component_added(entity: Entity, component: Resource): + # Sync component transform to entity when added + var transform_comp = component as C_Transform + entity.global_transform = transform_comp.transform + +func on_component_changed(entity: Entity, component: Resource, property: String, new_value: Variant, old_value: Variant): + # Sync component transform to entity when changed + var transform_comp = component as C_Transform + entity.global_transform = transform_comp.transform +``` + +## 🎮 Observer Event Types + +### on_component_added() + +Triggered when a watched component is added to an entity: + +```gdscript +class_name HealthUIObserver +extends Observer + +func watch() -> Resource: + return C_Health + +func match(): + return q.with_all([C_Health]).with_group("player") + +func on_component_added(entity: Entity, component: Resource): + # Create health bar when player gains health component + var health = component as C_Health + # Use call_deferred to avoid timing issues during component changes + call_deferred("create_health_bar", entity, health.maximum) +``` + +### on_component_changed() + +Triggered when a watched component's property changes: + +```gdscript +class_name HealthBarObserver +extends Observer + +func watch() -> Resource: + return C_Health + +func match(): + return q.with_all([C_Health]).with_group("player") + +func on_component_changed(entity: Entity, component: Resource, property: String, new_value: Variant, old_value: Variant): + if property == "current": + var health = component as C_Health + # Update health bar display + call_deferred("update_health_bar", entity, health.current, health.maximum) +``` + +### on_component_removed() + +Triggered when a watched component is removed from an entity: + +```gdscript +class_name HealthUIObserver +extends Observer + +func watch() -> Resource: + return C_Health + +func on_component_removed(entity: Entity, component: Resource): + # Clean up health bar when health component is removed + call_deferred("remove_health_bar", entity) +``` + +## 💡 Common Observer Patterns + +### Transform Synchronization + +Keep entity scene transforms in sync with Transform components: + +```gdscript +# o_transform.gd +class_name TransformObserver +extends Observer + +func watch() -> Resource: + return C_Transform + +func on_component_added(entity: Entity, component: Resource): + var transform_comp = component as C_Transform + entity.global_transform = transform_comp.transform + +func on_component_changed(entity: Entity, component: Resource, property: String, new_value: Variant, old_value: Variant): + var transform_comp = component as C_Transform + entity.global_transform = transform_comp.transform +``` + +### Status Effect Visuals + +Show visual feedback for status effects: + +```gdscript +# o_status_effects.gd +class_name StatusEffectObserver +extends Observer + +func watch() -> Resource: + return C_StatusEffect + +func on_component_added(entity: Entity, component: Resource): + var status = component as C_StatusEffect + call_deferred("add_status_visual", entity, status.effect_type) + +func on_component_removed(entity: Entity, component: Resource): + var status = component as C_StatusEffect + call_deferred("remove_status_visual", entity, status.effect_type) + +func add_status_visual(entity: Entity, effect_type: String): + match effect_type: + "poison": + # Add poison particle effect + pass + "shield": + # Add shield visual overlay + pass + +func remove_status_visual(entity: Entity, effect_type: String): + # Remove corresponding visual effect + pass +``` + +### Audio Feedback + +Trigger sound effects on component changes: + +```gdscript +# o_audio_feedback.gd +class_name AudioFeedbackObserver +extends Observer + +func watch() -> Resource: + return C_Health + +func on_component_changed(entity: Entity, component: Resource, property: String, new_value: Variant, old_value: Variant): + if property == "current": + var health_change = new_value - old_value + + if health_change < 0: + # Health decreased - play damage sound + call_deferred("play_damage_sound", entity.global_position) + elif health_change > 0: + # Health increased - play heal sound + call_deferred("play_heal_sound", entity.global_position) +``` + +## 🏗️ Observer Best Practices + +### Naming Conventions + +**Observer files and classes:** + +- **Class names**: `DescriptiveNameObserver` (TransformObserver, HealthUIObserver) +- **File names**: `o_descriptive_name.gd` (o_transform.gd, o_health_ui.gd) + +### Use Deferred Calls + +Always use `call_deferred()` to defer work and avoid immediate execution during component updates: + +```gdscript +# ✅ Good - Defer work for later execution +func on_component_changed(entity: Entity, component: Resource, property: String, new_value: Variant, old_value: Variant): + call_deferred("update_ui_element", entity, new_value) + +# ❌ Avoid - Immediate execution can cause issues +func on_component_changed(entity: Entity, component: Resource, property: String, new_value: Variant, old_value: Variant): + update_ui_element(entity, new_value) # May cause timing issues +``` + +### Keep Observer Logic Simple + +Focus observers on single responsibilities: + +```gdscript +# ✅ Good - Single purpose observer +class_name HealthUIObserver +extends Observer + +func watch() -> Resource: + return C_Health + +func on_component_changed(entity: Entity, component: Resource, property: String, new_value: Variant, old_value: Variant): + if property == "current": + call_deferred("update_health_display", entity, new_value) + +# ❌ Avoid - Observer doing too much +class_name HealthObserver +extends Observer + +func on_component_changed(entity: Entity, component: Resource, property: String, new_value: Variant, old_value: Variant): + # Too many responsibilities in one observer + update_health_display(entity, new_value) + play_damage_sound(entity) + check_achievements(entity) + save_game_state() +``` + +### Use Specific Queries + +Filter which entities trigger observers with `match()`: + +```gdscript +# ✅ Good - Specific query +func match(): + return q.with_all([C_Health]).with_group("player") # Only player health + +# ❌ Avoid - Too broad +func match(): + return q.with_all([C_Health]) # ALL entities with health +``` + +## 🎯 When to Use Observers + +**Use Observers for:** + +- UI updates based on game state changes +- Audio/visual effects triggered by state changes +- Immediate response to critical state changes (death, level up) +- Synchronization between components and scene nodes +- Event logging and analytics + +**Use Regular Systems for:** + +- Continuous processing (movement, physics) +- Frame-by-frame updates +- Complex logic that depends on multiple entities +- Performance-critical processing loops + +## 🚀 Adding Observers to the World + +Observers must be registered with the World to function. There are several ways to do this: + +### Manual Registration + +```gdscript +# In your scene or main script +func _ready(): + var health_observer = HealthUIObserver.new() + ECS.world.add_observer(health_observer) + + # Or add multiple observers at once + ECS.world.add_observers([health_observer, transform_observer, audio_observer]) +``` + +### Automatic Scene Tree Registration + +Place Observer nodes in your scene under the systems root (default: "Systems" node), and they'll be automatically registered: + +``` +Main +├── World +├── Systems/ # Observers placed here are auto-registered +│ ├── HealthUIObserver +│ ├── TransformObserver +│ └── AudioFeedbackObserver +└── Entities/ + └── Player +``` + +### Important Notes: +- Observers are initialized with their own QueryBuilder (`observer.q`) +- The `watch()` method is called during registration to validate the component +- Observers must return a valid Component class from `watch()` or they'll crash + +## ⚠️ Common Issues & Troubleshooting + +### Observer Not Triggering +**Problem**: Observer events never fire +**Solutions**: +- Ensure the observer is added to the World with `add_observer()` +- Check that `watch()` returns the correct component class +- Verify entities match the `match()` query (if defined) +- Component changes must be on properties, not just internal state + +### Crash: "You must override the watch() method" +**Problem**: Observer crashes on registration +**Solution**: Override `watch()` method and return a Component class: +```gdscript +func watch() -> Resource: + return C_Health # Must return actual component class +``` + +### Events Fire for Wrong Entities +**Problem**: Observer triggers for entities you don't want +**Solution**: Use `match()` to filter entities: +```gdscript +func match(): + return q.with_all([C_Health]).with_group("player") # Only players +``` + +### Property Changes Not Detected +**Problem**: Observer doesn't detect component property changes +**Causes**: +- Direct assignment to properties should work automatically +- Internal object modifications (like Array.append()) may not trigger signals +- Manual signal emission required for complex property changes + +## 📚 Related Documentation + +- **[Core Concepts](CORE_CONCEPTS.md)** - Understanding the ECS fundamentals +- **[Systems](CORE_CONCEPTS.md#systems)** - Regular processing systems +- **[Best Practices](BEST_PRACTICES.md)** - Write maintainable ECS code + +--- + +_"Observers turn your ECS from a polling system into a reactive system, making your game respond intelligently to state changes rather than constantly checking for them."_ \ No newline at end of file diff --git a/addons/gecs/docs/PERFORMANCE_OPTIMIZATION.md b/addons/gecs/docs/PERFORMANCE_OPTIMIZATION.md new file mode 100644 index 0000000..b64e4e0 --- /dev/null +++ b/addons/gecs/docs/PERFORMANCE_OPTIMIZATION.md @@ -0,0 +1,418 @@ +# GECS Performance Optimization Guide + +> **Make your ECS games run fast and smooth** + +This guide shows you how to optimize your GECS-based games for maximum performance. Learn to identify bottlenecks, optimize queries, and design systems that scale. + +## 📋 Prerequisites + +- Understanding of [Core Concepts](CORE_CONCEPTS.md) +- Familiarity with [Best Practices](BEST_PRACTICES.md) +- A working GECS project to optimize + +## 🎯 Performance Fundamentals + +### The ECS Performance Model + +GECS performance depends on three key factors: + +1. **Query Efficiency** - How fast you find entities +2. **Component Access** - How quickly you read/write data +3. **System Design** - How well your logic is organized + +Most performance gains come from optimizing these in order of impact. + +## 🔍 Profiling Your Game + +### Monitor Query Cache Performance + +Always profile before optimizing. GECS provides query cache statistics for performance monitoring: + +```gdscript +# Main.gd +func _process(delta): + ECS.process(delta) + + # Print cache performance stats every second + if Engine.get_process_frames() % 60 == 0: + var cache_stats = ECS.world.get_cache_stats() + print("ECS Performance:") + print(" Query cache hits: ", cache_stats.get("hits", 0)) + print(" Query cache misses: ", cache_stats.get("misses", 0)) + print(" Total entities: ", ECS.world.entities.size()) + + # Reset stats for next measurement period + ECS.world.reset_cache_stats() +``` + +### Use Godot's Built-in Profiler + +Monitor your game's performance in the Godot editor: + +1. **Run your project** in debug mode +2. **Open the Profiler** (Debug → Profiler) +3. **Look for ECS-related spikes** in the frame time +4. **Identify the slowest systems** in your processing groups + +## ⚡ Query Optimization + +### 1. Choose the Right Query Method ⭐ NEW! + +**As of v5.0.0-rc4**, query performance ranking (10,000 entities): + +1. **`.enabled(true/false)` queries**: **~0.05ms** 🏆 **(Fastest - Use when possible!)** +2. **`.with_all([Components])` queries**: **~0.6ms** 🥈 **(Excellent for most use cases)** +3. **`.with_any([Components])` queries**: **~5.6ms** 🥉 **(Good for OR-style queries)** +4. **`.with_group("name")` queries**: **~16ms** 🐌 **(Avoid for performance-critical code)** + +**Performance Recommendations:** + +```gdscript +# 🏆 FASTEST - Use enabled/disabled queries when you only need active entities +class_name ActiveSystemsOnly extends System +func query(): + return q.enabled(true) # Constant-time O(1) performance! + +# 🥈 EXCELLENT - Component-based queries (heavily optimized cache) +class_name MovementSystem extends System +func query(): + return q.with_all([C_Position, C_Velocity]) # ~0.6ms for 10K entities + +# 🥉 GOOD - Use with_any sparingly, split into multiple systems when possible +class_name DamageableSystem extends System +func query(): + return q.with_any([C_Player, C_Enemy]).with_all([C_Health]) + +# 🐌 AVOID - Group queries are the slowest +class_name PlayerSystem extends System +func query(): + return q.with_group("player") # Consider using components instead + # Better: q.with_all([C_Player]) +``` + +### 2. Use Proper System Query Pattern + +GECS automatically handles query optimization when you follow the standard pattern: + +### 2. Use Proper System Query Pattern + +GECS automatically handles query optimization when you follow the standard pattern: + +```gdscript +# ✅ Good - Standard GECS pattern (automatically optimized) +class_name MovementSystem extends System + +func query(): + return q.with_all([C_Position, C_Velocity]).with_none([C_Frozen]) + +func process(entities: Array[Entity], components: Array, delta: float): + # Process each entity + for entity in entities: + var pos = entity.get_component(C_Position) + var vel = entity.get_component(C_Velocity) + pos.value += vel.value * delta +``` + +```gdscript +# ❌ Avoid - Manual query building in process methods +func process(entities: Array[Entity], components: Array, delta: float): + # Don't do this - bypasses automatic query optimization + var custom_entities = ECS.world.query.with_all([C_Position]).execute() + # Process custom_entities... +``` + +### 3. Optimize Query Specificity + +More specific queries run faster: + +```gdscript +# ✅ Fast - Use enabled filter for active entities only +class_name PlayerInputSystem extends System +func query(): + return q.with_all([C_Input, C_Movement]).enabled(true) + # Super fast enabled filtering + component matching + +# ✅ Fast - Specific component query +class_name ProjectileSystem extends System +func query(): + return q.with_all([C_Projectile, C_Velocity]) + # Only matches projectiles - very specific +``` + +```gdscript +# ❌ Slow - Overly broad query +class_name UniversalSystem extends System +func query(): + return q.with_all([C_Position]) + # Matches almost everything in the game! + +func process(entities: Array[Entity], components: Array, delta: float): + # Now we need expensive type checking in a loop + for entity in entities: + if entity.has_component(C_Player): + # Handle player... + elif entity.has_component(C_Enemy): + # Handle enemy... + # This defeats the purpose of ECS! +``` + +### 4. Smart Use of with_any Queries + +`with_any` queries are **much faster than before** but still slower than `with_all`. Use strategically: + +```gdscript +# ✅ Good - with_any for legitimate OR scenarios +class_name DamageSystem extends System +func query(): + return q.with_any([C_Player, C_Enemy, C_NPC]).with_all([C_Health]) + # When you truly need "any of these types with health" + +# ✅ Better - Split when entities have different behavior +class_name PlayerMovementSystem extends System +func query(): return q.with_all([C_Player, C_Movement]) + +class_name EnemyMovementSystem extends System +func query(): return q.with_all([C_Enemy, C_Movement]) +# Split systems = simpler logic + better performance +``` + +### 5. Avoid Group Queries for Performance-Critical Code + +Group queries are now the slowest option. Use component-based queries instead: + +```gdscript +# ❌ Slow - Group-based query (~16ms for 10K entities) +class_name PlayerSystem extends System +func query(): + return q.with_group("player") + +# ✅ Fast - Component-based query (~0.6ms for 10K entities) +class_name PlayerSystem extends System +func query(): + return q.with_all([C_Player]) +``` + +## 🧱 Component Design for Performance + +### Keep Components Lightweight + +Smaller components = faster memory access: + +```gdscript +# ✅ Good - Lightweight components +class_name C_Position extends Component +@export var position: Vector2 + +class_name C_Velocity extends Component +@export var velocity: Vector2 + +class_name C_Health extends Component +@export var current: float +@export var maximum: float +``` + +```gdscript +# ❌ Heavy - Bloated component +class_name MegaComponent extends Component +@export var position: Vector2 +@export var velocity: Vector2 +@export var health: float +@export var mana: float +@export var inventory: Array[Item] = [] +@export var abilities: Array[Ability] = [] +@export var dialogue_history: Array[String] = [] +# Too much data in one place! +``` + +### Minimize Component Additions/Removals + +Adding and removing components requires index updates. Batch component operations when possible: + +```gdscript +# ✅ Good - Batch component operations +func setup_new_enemy(entity: Entity): + # Add multiple components in one batch + entity.add_components([ + C_Health.new(), + C_Position.new(), + C_Velocity.new(), + C_Enemy.new() + ]) + +# ✅ Good - Single component change when needed +func apply_damage(entity: Entity, damage: float): + var health = entity.get_component(C_Health) + health.current = clamp(health.current - damage, 0, health.maximum) + + if health.current <= 0: + entity.add_component(C_Dead.new()) # Single component addition +``` + +### Choose Between Boolean Properties vs Components Based on Usage + +The choice between boolean properties and separate components depends on how frequently states change and how many entities need them. + +#### Use Boolean Properties for Frequently-Changing States + +When states change often, boolean properties avoid expensive index updates: + +```gdscript +# ✅ Good for frequently-changing states (buffs, status effects, etc.) +class_name C_EntityState extends Component +@export var is_stunned: bool = false +@export var is_invisible: bool = false +@export var is_invulnerable: bool = false + +class_name MovementSystem extends System +func query(): + return q.with_all([C_Position, C_Velocity, C_EntityState]) + # All entities that might need states must have this component + +func process(entity: Entity, delta: float): + var state = entity.get_component(C_EntityState) + if state.is_stunned: + return # Just a property check - no index updates + + # Process movement... +``` + +**Tradeoffs:** + +- ✅ Fast state changes (no index rebuilds) +- ✅ Simple property checks in systems +- ❌ All entities need the state component (memory overhead) +- ❌ Less precise queries (can't easily find "only stunned entities") + +#### Use Separate Components for Rare or Permanent States + +When states are long-lasting or infrequent, separate components provide precise queries: + +```gdscript +# ✅ Good for rare/permanent states (player vs enemy, permanent abilities) +class_name MovementSystem extends System +func query(): + return q.with_all([C_Position, C_Velocity]).with_none([C_Paralyzed]) + # Precise query - only entities that can move + +# Separate systems can target specific states precisely +class_name ParalyzedSystem extends System +func query(): + return q.with_all([C_Paralyzed]) # Only paralyzed entities +``` + +**Tradeoffs:** + +- ✅ Memory efficient (only entities with states have components) +- ✅ Precise queries for specific states +- ❌ State changes trigger expensive index updates +- ❌ Complex queries with multiple exclusions + +#### Guidelines: + +- **High-frequency changes** (every few frames): Use boolean properties +- **Low-frequency changes** (minutes apart): Use separate components +- **Related states** (buffs/debuffs): Group into property components +- **Distinct entity types** (player/enemy): Use separate components + +## ⚙️ System Performance Patterns + +### Early Exit Strategies + +Return early when no processing is needed: + +```gdscript +class_name HealthRegenerationSystem extends System + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var health = entity.get_component(C_Health) + + # Early exits for common cases + if health.current >= health.maximum: + continue # Already at full health + + if health.regeneration_rate <= 0: + continue # No regeneration configured + + # Only do expensive work when needed + health.current = min(health.current + health.regeneration_rate * delta, health.maximum) +``` + +### Batch Entity Operations + +Group entity operations together: + +```gdscript +# ✅ Good - Batch creation +func spawn_enemy_wave(): + var enemies: Array[Entity] = [] + + # Create all entities using entity pooling + for i in range(50): + var enemy = ECS.world.create_entity() # Uses entity pool for performance + setup_enemy_components(enemy) + enemies.append(enemy) + + # Add all to world at once + ECS.world.add_entities(enemies) + +# ✅ Good - Individual removal (batch removal not available) +func cleanup_dead_entities(): + var dead_entities = ECS.world.query.with_all([C_Dead]).execute() + for entity in dead_entities: + ECS.world.remove_entity(entity) # Remove individually +``` + +## 📊 Performance Targets + +### Frame Rate Targets + +Aim for these processing times per frame: + +- **60 FPS target**: ECS processing < 16ms per frame +- **30 FPS target**: ECS processing < 33ms per frame +- **Mobile target**: ECS processing < 8ms per frame + +### Entity Scale Guidelines + +GECS handles these entity counts well with proper optimization: + +- **Small games**: 100-500 entities +- **Medium games**: 500-2000 entities +- **Large games**: 2000-10000 entities +- **Massive games**: 10000+ entities (requires advanced optimization) + +## 🎯 Next Steps + +1. **Profile your current game** to establish baseline performance +2. **Apply query optimizations** from this guide +3. **Redesign heavy components** into lighter, focused ones +4. **Implement system improvements** like early exits and batching +5. **Consider advanced techniques** like pooling and spatial partitioning for demanding scenarios + +## 🔍 Additional Performance Features + +### Entity Pooling + +GECS includes built-in entity pooling for optimal performance: + +```gdscript +# Use the entity pool for frequent entity creation/destruction +var new_entity = ECS.world.create_entity() # Gets from pool when available +``` + +### Query Cache Statistics + +Monitor query performance with built-in cache tracking: + +```gdscript +# Get detailed cache performance data +var stats = ECS.world.get_cache_stats() +print("Cache hit rate: ", stats.get("hits", 0) / (stats.get("hits", 0) + stats.get("misses", 1))) +``` + +**Need more help?** Check the [Troubleshooting Guide](TROUBLESHOOTING.md) for specific performance issues. + +--- + +_"Fast ECS code isn't about clever tricks - it's about designing systems that naturally align with how the framework works best."_ diff --git a/addons/gecs/docs/PERFORMANCE_TESTING.md b/addons/gecs/docs/PERFORMANCE_TESTING.md new file mode 100644 index 0000000..3c37894 --- /dev/null +++ b/addons/gecs/docs/PERFORMANCE_TESTING.md @@ -0,0 +1,216 @@ +# GECS Performance Testing Guide + +> **Framework-level performance testing for GECS developers** + +This document explains how to run and interpret the GECS performance tests. This is primarily for framework developers and contributors who need to ensure GECS maintains high performance. + +**For game developers:** See [Performance Optimization Guide](PERFORMANCE_OPTIMIZATION.md) for optimizing your games. + +## 📋 Prerequisites + +- GECS framework development environment +- gdUnit4 testing framework +- Godot 4.x +- Test system dependencies: `s_performance_test.gd` and `s_complex_performance_test.gd` in tests/systems/ + +## 🎯 Overview + +The GECS performance test suite provides comprehensive benchmarking for all critical ECS operations: + +- **Entity Operations**: Creation, destruction, world management +- **Component Operations**: Addition, removal, lookup, indexing +- **Query Performance**: All query types, caching, complex scenarios +- **System Processing**: Single/multiple systems, different scales +- **Array Operations**: Optimized set operations (intersect, union, difference) +- **Integration Tests**: Realistic game scenarios and stress tests + +## 🚀 Running Performance Tests + +### Prerequisites + +Set the `GODOT_BIN` environment variable to your Godot executable: + +```bash +# Windows +setx GODOT_BIN "C:\path\to\godot.exe" + +# Linux/Mac +export GODOT_BIN="/path/to/godot" +``` + +### Running Individual Test Suites + +```bash +# Entity performance tests +addons/gdUnit4/runtest.cmd -a res://addons/gecs/tests/performance/performance_test_entities.gd + +# Component performance tests +addons/gdUnit4/runtest.cmd -a res://addons/gecs/tests/performance/performance_test_components.gd + +# Query performance tests +addons/gdUnit4/runtest.cmd -a res://addons/gecs/tests/performance/performance_test_queries.gd + +# System performance tests +addons/gdUnit4/runtest.cmd -a res://addons/gecs/tests/performance/performance_test_systems.gd + +# Array operations performance tests +addons/gdUnit4/runtest.cmd -a res://addons/gecs/tests/performance/performance_test_arrays.gd + +# Integration performance tests +addons/gdUnit4/runtest.cmd -a res://addons/gecs/tests/performance/performance_test_integration.gd +``` + +### Running Complete Performance Suite + +```bash +# Run all performance tests with comprehensive reporting +addons/gdUnit4/runtest.cmd -a res://addons/gecs/tests/performance/performance_test_master.gd + +# Quick smoke test to verify basic performance +addons/gdUnit4/runtest.cmd -a res://addons/gecs/tests/performance/performance_test_master.gd::test_performance_smoke_test +``` + +## 📊 Test Scales + +The performance tests use three different scales: + +- **SMALL_SCALE**: 100 entities (for fine-grained testing) +- **MEDIUM_SCALE**: 1,000 entities (for typical game scenarios) +- **LARGE_SCALE**: 10,000 entities (for stress testing) + +## ⏱️ Performance Thresholds + +The tests include automatic performance threshold checking: + +### Entity Operations + +- Create 100 entities: < 10ms +- Create 1,000 entities: < 50ms +- Add 1,000 entities to world: < 100ms + +### Component Operations + +- Add components to 100 entities: < 10ms +- Add components to 1,000 entities: < 75ms +- Component lookup in 1,000 entities: < 30ms + +### Query Performance + +- Simple query on 100 entities: < 5ms +- Simple query on 1,000 entities: < 20ms +- Simple query on 10,000 entities: < 100ms +- Complex queries: < 50ms + +### System Processing + +- Process 100 entities: < 5ms +- Process 1,000 entities: < 30ms +- Process 10,000 entities: < 150ms + +### Game Loop Performance + +- Realistic game frame (1,000 entities): < 16ms (60 FPS target) + +## 📈 Understanding Results + +### Performance Metrics + +Each test provides: + +- **Average Time**: Mean execution time across multiple runs +- **Min/Max Time**: Best and worst execution times +- **Standard Deviation**: Consistency of performance +- **Operations/Second**: Throughput measurement +- **Time/Operation**: Per-item processing time + +### Result Files + +Performance results are saved to `res://reports/` with timestamps: + +- `entity_performance_results.json` +- `component_performance_results.json` +- `query_performance_results.json` +- `system_performance_results.json` +- `array_performance_results.json` +- `integration_performance_results.json` +- `complete_performance_results_[timestamp].json` + +### Interpreting Results + +**Good Performance Indicators:** + +- ✅ High operations/second (>10,000 for simple operations) +- ✅ Low standard deviation (consistent performance) +- ✅ Linear scaling with entity count +- ✅ Query cache hit rates >80% + +**Performance Warning Signs:** + +- ⚠️ Tests taking >50ms consistently +- ⚠️ Exponential time scaling with entity count +- ⚠️ High standard deviation (inconsistent performance) +- ⚠️ Cache hit rates <50% + +## 🔄 Regression Testing + +To monitor performance over time: + +1. **Establish Baseline**: Run the complete test suite and save results +2. **Regular Testing**: Run tests after significant changes +3. **Compare Results**: Use the master test suite's regression checking +4. **Set Alerts**: Monitor for >20% performance degradation + +## 🎯 Optimization Areas + +Based on test results, focus optimization efforts on: + +1. **Query Performance**: Most critical for gameplay +2. **Component Operations**: High frequency operations +3. **Array Operations**: Core performance building blocks +4. **System Processing**: Frame-rate critical +5. **Memory Usage**: Large-scale scenarios + +## ⚠️ Common Issues + +### Missing Dependencies +If tests fail with missing class errors, ensure these files exist: +- `addons/gecs/tests/systems/s_performance_test.gd` +- `addons/gecs/tests/systems/s_complex_performance_test.gd` + +### gdUnit4 Setup +Beyond setting `GODOT_BIN`, ensure: +- gdUnit4 plugin is enabled in project settings +- All test component classes are properly defined + +## 🔧 Custom Performance Tests + +To create custom performance tests: + +1. Extend `PerformanceTestBase` +2. Use the `benchmark()` method for timing +3. Set appropriate performance thresholds +4. Include in the master test suite + +Example: + +```gdscript +extends PerformanceTestBase + +func test_my_custom_operation(): + var my_test = func(): + # Your operation here + pass + + benchmark("My_Custom_Test", my_test) + assert_performance_threshold("My_Custom_Test", 10.0, "Custom operation too slow") +``` + +## 📚 Related Documentation + +- **[Performance Optimization](PERFORMANCE_OPTIMIZATION.md)** - User-focused optimization guide +- **[Best Practices](BEST_PRACTICES.md)** - Write performant ECS code +- **[Core Concepts](CORE_CONCEPTS.md)** - Understanding the ECS architecture + +--- + +_This performance testing framework ensures GECS maintains high performance as the codebase evolves. It's a critical tool for framework development and optimization efforts._ diff --git a/addons/gecs/docs/RELATIONSHIPS.md b/addons/gecs/docs/RELATIONSHIPS.md new file mode 100644 index 0000000..24c196b --- /dev/null +++ b/addons/gecs/docs/RELATIONSHIPS.md @@ -0,0 +1,893 @@ +# Relationships in GECS + +> **Link entities together for complex game interactions** + +Relationships allow you to connect entities in meaningful ways, creating dynamic associations that go beyond simple component data. This guide shows you how to use GECS's relationship system to build complex game mechanics. + +## 📋 Prerequisites + +- Understanding of [Core Concepts](CORE_CONCEPTS.md) +- Familiarity with [Query System](CORE_CONCEPTS.md#query-system) + +## 🔗 What are Relationships? + +Think of **components** as the data that makes up an entity's state, and **relationships** as the links that connect entities to other entities, components, or types. Relationships can be simple links or carry data about the connection itself. + +In GECS, relationships consist of three parts: + +- **Source** - Entity that has the relationship (e.g., Bob) +- **Relation** - Component defining the relationship type (e.g., "Likes", "Damaged") +- **Target** - What is being related to: Entity, Component instance, or archetype (e.g., Alice, FireDamage component, Enemy class) + +## 🎯 Relationship Types + +GECS supports three powerful relationship patterns: + +### 1. **Entity Relationships** +Link entities to other entities: +```gdscript +# Bob likes Alice (entity to entity) +e_bob.add_relationship(Relationship.new(C_Likes.new(), e_alice)) +``` + +### 2. **Component Relationships** +Link entities to component instances for type hierarchies: +```gdscript +# Entity has fire damage (entity to component) +entity.add_relationship(Relationship.new(C_Damaged.new(), C_FireDamage.new(50))) +``` + +### 3. **Archetype Relationships** +Link entities to classes/types: +```gdscript +# Heather likes all food (entity to type) +e_heather.add_relationship(Relationship.new(C_Likes.new(), Food)) +``` + +This creates powerful queries like "find all entities that like Alice", "find all entities with fire damage", or "find all entities damaged by anything". + +## 🎯 Core Relationship Concepts + +### Relationship Components + +Relationships use components to define their type and can carry data: + +```gdscript +# c_likes.gd - Simple relationship +class_name C_Likes +extends Component + +# c_loves.gd - Another simple relationship +class_name C_Loves +extends Component + +# c_eats.gd - Relationship with data +class_name C_Eats +extends Component + +@export var quantity: int = 1 + +func _init(qty: int = 1): + quantity = qty +``` + +### Creating Relationships + +```gdscript +# Create entities +var e_bob = Entity.new() +var e_alice = Entity.new() +var e_heather = Entity.new() +var e_apple = Food.new() + +# Add to world +ECS.world.add_entity(e_bob) +ECS.world.add_entity(e_alice) +ECS.world.add_entity(e_heather) +ECS.world.add_entity(e_apple) + +# Create relationships +e_bob.add_relationship(Relationship.new(C_Likes.new(), e_alice)) # bob likes alice +e_alice.add_relationship(Relationship.new(C_Loves.new(), e_heather)) # alice loves heather +e_heather.add_relationship(Relationship.new(C_Likes.new(), Food)) # heather likes food (type) +e_heather.add_relationship(Relationship.new(C_Eats.new(5), e_apple)) # heather eats 5 apples + +# Remove relationships +e_alice.remove_relationship(Relationship.new(C_Loves.new(), e_heather)) # alice no longer loves heather + +# Remove with limits (NEW) +e_player.remove_relationship(Relationship.new(C_Poison.new(), null), 1) # Remove only 1 poison stack +e_enemy.remove_relationship(Relationship.new(C_Buff.new(), null), 3) # Remove up to 3 buffs +e_hero.remove_relationship(Relationship.new(C_Damage.new(), null), -1) # Remove all damage (default) +``` + +## 🔍 Relationship Queries + +### Basic Relationship Queries + +**Query for Specific Relationships:** + +```gdscript +# Any entity that likes alice (type matching) +ECS.world.query.with_relationship([Relationship.new(C_Likes.new(), e_alice)]) + +# Any entity that eats apples (type matching) +ECS.world.query.with_relationship([Relationship.new(C_Eats.new(), e_apple)]) + +# Any entity that eats 5 or more apples (component query) +ECS.world.query.with_relationship([ + Relationship.new({C_Eats: {'quantity': {"_gte": 5}}}, e_apple) +]) + +# Any entity that likes the Food entity type +ECS.world.query.with_relationship([Relationship.new(C_Likes.new(), Food)]) +``` + +**Exclude Relationships:** + +```gdscript +# Entities with any relation toward heather that don't like bob +ECS.world.query + .with_relationship([Relationship.new(ECS.wildcard, e_heather)]) + .without_relationship([Relationship.new(C_Likes.new(), e_bob)]) +``` + +### Wildcard Relationships + +Use `ECS.wildcard` (or `null`) to query for any relation or target: + +```gdscript +# Any entity with any relation toward heather +ECS.world.query.with_relationship([Relationship.new(ECS.wildcard, e_heather)]) + +# Any entity that likes anything +ECS.world.query.with_relationship([Relationship.new(C_Likes.new(), ECS.wildcard)]) +ECS.world.query.with_relationship([Relationship.new(C_Likes.new())]) # Omitting target = wildcard + +# Any entity with any relation to Enemy entity type +ECS.world.query.with_relationship([Relationship.new(ECS.wildcard, Enemy)]) +``` + +### Component-Based Relationships + +Link entities to **component instances** for powerful type hierarchies and data systems: + +```gdscript +# Damage system using component targets +class_name C_Damaged extends Component +class_name C_FireDamage extends Component + @export var amount: int = 0 + func _init(dmg: int = 0): amount = dmg + +class_name C_PoisonDamage extends Component + @export var amount: int = 0 + func _init(dmg: int = 0): amount = dmg + +# Entity has multiple damage types +entity.add_relationship(Relationship.new(C_Damaged.new(), C_FireDamage.new(50))) +entity.add_relationship(Relationship.new(C_Damaged.new(), C_PoisonDamage.new(25))) + +# Query for entities with any damage type (wildcard) +var damaged_entities = ECS.world.query.with_relationship([ + Relationship.new(C_Damaged.new(), null) +]).execute() + +# Query for entities with fire damage >= 50 using component query +var high_fire_damaged = ECS.world.query.with_relationship([ + Relationship.new(C_Damaged.new(), {C_FireDamage: {"amount": {"_gte": 50}}}) +]).execute() + +# Query for entities with any fire damage (type matching) +var any_fire_damaged = ECS.world.query.with_relationship([ + Relationship.new(C_Damaged.new(), C_FireDamage) +]).execute() +``` + +### Matching Modes + +GECS relationships support two matching modes: + +#### Type Matching (Default) +Matches relationships by component type, ignoring property values: + +```gdscript +# Matches any C_Damaged relationship regardless of amount +entity.has_relationship(Relationship.new(C_Damaged.new(), target)) + +# Matches any fire damage effect by type +entity.has_relationship(Relationship.new(C_Damaged.new(), C_FireDamage.new())) + +# Query for any entities with fire damage (type matching) +var any_fire_damaged = ECS.world.query.with_relationship([ + Relationship.new(C_Damaged.new(), C_FireDamage) +]).execute() +``` + +#### Component Query Matching +Match relationships by specific property criteria using dictionaries: + +```gdscript +# Match C_Damaged relationships where amount >= 50 +var high_damage = ECS.world.query.with_relationship([ + Relationship.new({C_Damaged: {'amount': {"_gte": 50}}}, target) +]).execute() + +# Match fire damage with specific duration +var lasting_fire = ECS.world.query.with_relationship([ + Relationship.new( + C_Damaged.new(), + {C_FireDamage: {'duration': {"_gt": 5.0}}} + ) +]).execute() + +# Match both relation AND target with queries +var strong_buffs = ECS.world.query.with_relationship([ + Relationship.new( + {C_Buff: {'duration': {"_gt": 10}}}, + {C_Player: {'level': {"_gte": 5}}} + ) +]).execute() +``` + +**When to Use Each:** +- **Type Matching**: Find entities with "any fire damage", "any buff of this type" +- **Component Queries**: Find entities with exact damage amounts, specific buff durations, or property criteria + +### Component Queries in Relationships + +Query relationships by specific property values using dictionaries: + +```gdscript +# Query by relation property +var heavy_eaters = ECS.world.query.with_relationship([ + Relationship.new({C_Eats: {'amount': {"_gte": 5}}}, e_apple) +]).execute() + +# Query by target component property +var high_hp_targets = ECS.world.query.with_relationship([ + Relationship.new(C_Targeting.new(), {C_Health: {'hp': {"_gte": 100}}}) +]).execute() + +# Query operators: _eq, _ne, _gt, _lt, _gte, _lte, _in, _nin, func +var special_damage = ECS.world.query.with_relationship([ + Relationship.new( + {C_Damage: {'type': {"_in": ["fire", "ice"]}}}, + null + ) +]).execute() + +# Complex multi-property queries +var critical_effects = ECS.world.query.with_relationship([ + Relationship.new( + {C_Effect: { + 'damage': {"_gt": 20}, + 'duration': {"_gte": 10.0}, + 'type': {"_eq": "critical"} + }}, + null + ) +]).execute() +``` + +### Reverse Relationships + +Find entities that are the **target** of relationships: + +```gdscript +# Find entities that are being liked by someone +ECS.world.query.with_reverse_relationship([Relationship.new(C_Likes.new(), ECS.wildcard)]) + +# Find entities being attacked +ECS.world.query.with_reverse_relationship([Relationship.new(C_IsAttacking.new())]) + +# Find food being eaten +ECS.world.query.with_reverse_relationship([Relationship.new(C_Eats.new(), ECS.wildcard)]) +``` + +## 🎛️ Limited Relationship Removal + +> **Control exactly how many relationships to remove for fine-grained management** + +The `remove_relationship()` method now supports a **limit parameter** that allows you to control exactly how many matching relationships to remove. This is essential for stack-based systems, partial healing, inventory management, and fine-grained effect control. + +### Basic Syntax + +```gdscript +entity.remove_relationship(relationship, limit) +``` + +**Limit Values:** +- `limit = -1` (default): Remove **all** matching relationships +- `limit = 0`: Remove **no** relationships (useful for testing/validation) +- `limit = 1`: Remove **one** matching relationship +- `limit > 1`: Remove **up to that many** matching relationships + +### Core Use Cases + +#### 1. **Stack-Based Systems** + +Perfect for buff/debuff stacks, damage over time effects, or any system where effects can stack: + +```gdscript +# Poison stack system +class_name C_PoisonStack extends Component +@export var damage_per_tick: float = 5.0 + +# Apply poison stacks +entity.add_relationship(Relationship.new(C_PoisonStack.new(3.0), null)) +entity.add_relationship(Relationship.new(C_PoisonStack.new(3.0), null)) +entity.add_relationship(Relationship.new(C_PoisonStack.new(3.0), null)) +entity.add_relationship(Relationship.new(C_PoisonStack.new(3.0), null)) # 4 poison stacks + +# Antidote removes 2 poison stacks +entity.remove_relationship(Relationship.new(C_PoisonStack.new(), null), 2) +# Entity now has 2 poison stacks remaining + +# Strong antidote removes all poison +entity.remove_relationship(Relationship.new(C_PoisonStack.new(), null)) # Default: remove all +``` + +#### 2. **Partial Healing Systems** + +Control damage removal for gradual healing or partial repair: + +```gdscript +# Multiple damage sources on entity +entity.add_relationship(Relationship.new(C_Damage.new(), C_FireDamage.new(25))) +entity.add_relationship(Relationship.new(C_Damage.new(), C_FireDamage.new(15))) +entity.add_relationship(Relationship.new(C_Damage.new(), C_SlashDamage.new(30))) +entity.add_relationship(Relationship.new(C_Damage.new(), C_PoisonDamage.new(10))) + +# Healing potion removes one damage source +entity.remove_relationship(Relationship.new(C_Damage.new(), null), 1) + +# Fire resistance removes only fire damage (up to 2 sources) +entity.remove_relationship(Relationship.new(C_Damage.new(), C_FireDamage), 2) + +# Full heal removes all damage +entity.remove_relationship(Relationship.new(C_Damage.new(), null)) # All damage gone +``` + +#### 3. **Inventory and Resource Management** + +Handle item stacks, resource consumption, and crafting materials: + +```gdscript +# Item stack system +class_name C_HasItem extends Component +class_name C_HealthPotion extends Component +@export var healing_amount: int = 50 + +# Player has multiple health potions +entity.add_relationship(Relationship.new(C_HasItem.new(), C_HealthPotion.new(50))) +entity.add_relationship(Relationship.new(C_HasItem.new(), C_HealthPotion.new(50))) +entity.add_relationship(Relationship.new(C_HasItem.new(), C_HealthPotion.new(50))) +entity.add_relationship(Relationship.new(C_HasItem.new(), C_HealthPotion.new(50))) + +# Use one health potion +entity.remove_relationship(Relationship.new(C_HasItem.new(), C_HealthPotion), 1) + +# Vendor buys 2 health potions +entity.remove_relationship(Relationship.new(C_HasItem.new(), C_HealthPotion), 2) + +# Drop all potions +entity.remove_relationship(Relationship.new(C_HasItem.new(), C_HealthPotion)) +``` + +#### 4. **Buff/Debuff Management** + +Fine-grained control over temporary effects: + +```gdscript +# Multiple speed buffs from different sources +entity.add_relationship(Relationship.new(C_Buff.new(), C_SpeedBuff.new(1.2, 10.0))) # Boots +entity.add_relationship(Relationship.new(C_Buff.new(), C_SpeedBuff.new(1.5, 5.0))) # Spell +entity.add_relationship(Relationship.new(C_Buff.new(), C_SpeedBuff.new(1.1, 30.0))) # Passive + +# Dispel magic removes one buff +entity.remove_relationship(Relationship.new(C_Buff.new(), null), 1) + +# Mass dispel removes up to 3 buffs +entity.remove_relationship(Relationship.new(C_Buff.new(), null), 3) + +# Purge removes all buffs +entity.remove_relationship(Relationship.new(C_Buff.new(), null)) +``` + +### Advanced Examples + +#### Component Query + Limit Combination + +Combine component queries with limits for precise control: + +```gdscript +# Remove only high-damage effects (damage > 20), up to 2 of them +entity.remove_relationship( + Relationship.new({C_Damage: {"amount": {"_gt": 20}}}, null), + 2 +) + +# Remove poison effects with duration < 5 seconds, limit to 1 +entity.remove_relationship( + Relationship.new({C_PoisonEffect: {"duration": {"_lt": 5.0}}}, null), + 1 +) + +# Remove fire damage with specific amount range, up to 3 instances +entity.remove_relationship( + Relationship.new( + C_Damage.new(), + {C_FireDamage: {"amount": {"_gte": 10, "_lte": 50}}} + ), + 3 +) + +# Remove all fire damage regardless of amount (no limit, type matching) +entity.remove_relationship( + Relationship.new(C_Damage.new(), C_FireDamage), + -1 +) + +# Remove buffs with specific multiplier, limit to 2 +entity.remove_relationship( + Relationship.new({C_Buff: {"multiplier": {"_gte": 1.5}}}, null), + 2 +) +``` + +#### System Integration + +Integrate limited removal into your game systems: + +```gdscript +class_name HealingSystem extends System + +func heal_entity(entity: Entity, healing_power: int): + """Remove damage based on healing power""" + if healing_power <= 0: + return + + # Partial healing - remove damage effects based on healing power + var damage_to_remove = min(healing_power, get_damage_count(entity)) + entity.remove_relationship(Relationship.new(C_Damage.new(), null), damage_to_remove) + + print("Healed ", damage_to_remove, " damage effects") + +func get_damage_count(entity: Entity) -> int: + return entity.get_relationships(Relationship.new(C_Damage.new(), null)).size() + +class_name CleanseSystem extends System + +func cleanse_entity(entity: Entity, cleanse_strength: int): + """Remove debuffs based on cleanse strength""" + match cleanse_strength: + 1: # Weak cleanse + entity.remove_relationship(Relationship.new(C_Debuff.new(), null), 1) + 2: # Medium cleanse + entity.remove_relationship(Relationship.new(C_Debuff.new(), null), 3) + 3: # Strong cleanse + entity.remove_relationship(Relationship.new(C_Debuff.new(), null)) # All debuffs + +class_name CraftingSystem extends System + +func consume_materials(entity: Entity, recipe: Dictionary): + """Consume specific amounts of crafting materials""" + for material_type in recipe: + var amount_needed = recipe[material_type] + entity.remove_relationship( + Relationship.new(C_HasMaterial.new(), material_type), + amount_needed + ) +``` + +### Error Handling and Validation + +The limit parameter provides built-in safeguards: + +```gdscript +# Safe operations - won't crash if fewer relationships exist than requested +entity.remove_relationship(Relationship.new(C_Buff.new(), null), 100) # Removes all available, won't error + +# Validation operations +entity.remove_relationship(Relationship.new(C_Damage.new(), null), 0) # Removes nothing - useful for testing + +# Check before removal +var damage_count = entity.get_relationships(Relationship.new(C_Damage.new(), null)).size() +if damage_count > 0: + entity.remove_relationship(Relationship.new(C_Damage.new(), null), min(3, damage_count)) +``` + +### Performance Considerations + +Limited removal is optimized for efficiency: + +```gdscript +# ✅ Efficient - stops searching after finding enough matches +entity.remove_relationship(Relationship.new(C_Effect.new(), null), 5) + +# ✅ Still efficient - reuses the same removal logic +entity.remove_relationship(Relationship.new(C_Effect.new(), null), -1) # Remove all + +# ✅ Most efficient for single removals +entity.remove_relationship(Relationship.new(C_SpecificEffect.new(exact_data), target), 1) +``` + +### Integration with Multiple Relationships + +Works seamlessly with `remove_relationships()` for batch operations: + +```gdscript +# Apply limit to multiple relationship types +var relationships_to_remove = [ + Relationship.new(C_Buff.new(), null), + Relationship.new(C_Debuff.new(), null), + Relationship.new(C_TemporaryEffect.new(), null) +] + +# Remove up to 2 of each type +entity.remove_relationships(relationships_to_remove, 2) +``` + +## 🎮 Game Examples + +### Status Effect System with Component Relationships + +This example shows how to build a flexible status effect system using component-based relationships: + +```gdscript +# Status effect marker +class_name C_HasEffect extends Component + +# Damage type components +class_name C_FireDamage extends Component + @export var damage_per_second: float = 10.0 + @export var duration: float = 5.0 + func _init(dps: float = 10.0, dur: float = 5.0): + damage_per_second = dps + duration = dur + +class_name C_PoisonDamage extends Component + @export var damage_per_tick: float = 5.0 + @export var ticks_remaining: int = 10 + func _init(dpt: float = 5.0, ticks: int = 10): + damage_per_tick = dpt + ticks_remaining = ticks + +# Buff type components +class_name C_SpeedBuff extends Component + @export var multiplier: float = 1.5 + @export var duration: float = 10.0 + func _init(mult: float = 1.5, dur: float = 10.0): + multiplier = mult + duration = dur + +class_name C_StrengthBuff extends Component + @export var bonus_damage: float = 25.0 + @export var duration: float = 8.0 + func _init(bonus: float = 25.0, dur: float = 8.0): + bonus_damage = bonus + duration = dur + +# Apply various effects to entities +func apply_status_effects(): + # Player gets fire damage and speed buff + player.add_relationship(Relationship.new(C_HasEffect.new(), C_FireDamage.new(15.0, 8.0))) + player.add_relationship(Relationship.new(C_HasEffect.new(), C_SpeedBuff.new(2.0, 12.0))) + + # Enemy gets poison and strength buff + enemy.add_relationship(Relationship.new(C_HasEffect.new(), C_PoisonDamage.new(8.0, 15))) + enemy.add_relationship(Relationship.new(C_HasEffect.new(), C_StrengthBuff.new(30.0, 10.0))) + +# Status effect processing system +class_name StatusEffectSystem extends System + +func query(): + # Get all entities with any status effects + return ECS.world.query.with_relationship([Relationship.new(C_HasEffect.new(), null)]) + +func process_fire_damage(): + # Find entities with any fire damage effect (type matching) + var fire_damaged = ECS.world.query.with_relationship([ + Relationship.new(C_HasEffect.new(), C_FireDamage) + ]).execute() + + for entity in fire_damaged: + # Get the actual fire damage data using type matching + var fire_rel = entity.get_relationship( + Relationship.new(C_HasEffect.new(), C_FireDamage.new()) + ) + var fire_damage = fire_rel.target as C_FireDamage + + # Apply damage + apply_damage(entity, fire_damage.damage_per_second * delta) + + # Reduce duration + fire_damage.duration -= delta + if fire_damage.duration <= 0: + entity.remove_relationship(fire_rel) + +func process_speed_buffs(): + # Find entities with speed buffs using type matching + var speed_buffed = ECS.world.query.with_relationship([ + Relationship.new(C_HasEffect.new(), C_SpeedBuff) + ]).execute() + + for entity in speed_buffed: + # Get actual speed buff data using type matching + var speed_rel = entity.get_relationship( + Relationship.new(C_HasEffect.new(), C_SpeedBuff.new()) + ) + var speed_buff = speed_rel.target as C_SpeedBuff + + # Apply speed modification + apply_speed_modifier(entity, speed_buff.multiplier) + + # Handle duration + speed_buff.duration -= delta + if speed_buff.duration <= 0: + entity.remove_relationship(speed_rel) + +func remove_all_effects_from_entity(entity: Entity): + # Remove all status effects using wildcard + entity.remove_relationship(Relationship.new(C_HasEffect.new(), null)) + +func remove_some_effects_from_entity(entity: Entity, count: int): + # Remove a specific number of status effects using limit parameter + entity.remove_relationship(Relationship.new(C_HasEffect.new(), null), count) + +func cleanse_one_debuff(entity: Entity): + # Remove just one debuff (useful for cleanse spells) + entity.remove_relationship(Relationship.new(C_Debuff.new(), null), 1) + +func dispel_magic(entity: Entity, power: int): + # Dispel magic spell removes buffs based on power level + match power: + 1: entity.remove_relationship(Relationship.new(C_HasEffect.new(), C_SpeedBuff), 1) # Weak dispel - 1 speed buff + 2: entity.remove_relationship(Relationship.new(C_HasEffect.new(), null), 2) # Medium dispel - 2 any effects + 3: entity.remove_relationship(Relationship.new(C_HasEffect.new(), null)) # Strong dispel - all effects + +func antidote_healing(entity: Entity, antidote_strength: int): + # Antidote removes poison effects based on strength + entity.remove_relationship(Relationship.new(C_HasEffect.new(), C_PoisonDamage), antidote_strength) + +func partial_fire_immunity(entity: Entity): + # Fire immunity spell removes up to 3 fire damage effects + entity.remove_relationship(Relationship.new(C_HasEffect.new(), C_FireDamage), 3) + +func get_entities_with_damage_effects(): + # Get entities with any damage type effect (fire or poison) + var fire_damaged = ECS.world.query.with_relationship([ + Relationship.new(C_HasEffect.new(), C_FireDamage) + ]).execute() + + var poison_damaged = ECS.world.query.with_relationship([ + Relationship.new(C_HasEffect.new(), C_PoisonDamage) + ]).execute() + + # Combine results + var all_damaged = {} + for entity in fire_damaged: + all_damaged[entity] = true + for entity in poison_damaged: + all_damaged[entity] = true + + return all_damaged.keys() +``` + +### Combat System with Relationships + +```gdscript +# Combat relationship components +class_name C_IsAttacking extends Component +@export var damage: float = 10.0 + +class_name C_IsTargeting extends Component +class_name C_IsAlliedWith extends Component + +# Create combat entities +var player = Player.new() +var enemy1 = Enemy.new() +var enemy2 = Enemy.new() +var ally = Ally.new() + +# Setup relationships +enemy1.add_relationship(Relationship.new(C_IsAttacking.new(25.0), player)) +enemy2.add_relationship(Relationship.new(C_IsTargeting.new(), player)) +player.add_relationship(Relationship.new(C_IsAlliedWith.new(), ally)) + +# Combat system queries +class_name CombatSystem extends System + +func get_entities_attacking_player(): + var player = get_player_entity() + return ECS.world.query.with_relationship([ + Relationship.new(C_IsAttacking.new(), player) + ]).execute() + +func get_high_damage_attackers(): + var player = get_player_entity() + # Find entities attacking player with damage >= 20 + return ECS.world.query.with_relationship([ + Relationship.new({C_IsAttacking: {'damage': {"_gte": 20.0}}}, player) + ]).execute() + +func get_player_allies(): + var player = get_player_entity() + return ECS.world.query.with_reverse_relationship([ + Relationship.new(C_IsAlliedWith.new(), player) + ]).execute() +``` + +### Hierarchical Entity System + +```gdscript +# Hierarchy relationship components +class_name C_ParentOf extends Component +class_name C_ChildOf extends Component +class_name C_OwnerOf extends Component + +# Create hierarchy +var parent = Entity.new() +var child1 = Entity.new() +var child2 = Entity.new() +var weapon = Weapon.new() + +# Setup parent-child relationships +parent.add_relationship(Relationship.new(C_ParentOf.new(), child1)) +parent.add_relationship(Relationship.new(C_ParentOf.new(), child2)) +child1.add_relationship(Relationship.new(C_ChildOf.new(), parent)) +child2.add_relationship(Relationship.new(C_ChildOf.new(), parent)) + +# Setup ownership +child1.add_relationship(Relationship.new(C_OwnerOf.new(), weapon)) + +# Hierarchy system queries +class_name HierarchySystem extends System + +func get_children_of_entity(entity: Entity): + return ECS.world.query.with_relationship([ + Relationship.new(C_ParentOf.new(), entity) + ]).execute() + +func get_parent_of_entity(entity: Entity): + return ECS.world.query.with_reverse_relationship([ + Relationship.new(C_ParentOf.new(), entity) + ]).execute() +``` + +## 🏗️ Relationship Best Practices + +### Performance Optimization + +**Reuse Relationship Objects:** + +```gdscript +# ✅ Good - Reuse for performance +var r_likes_apples = Relationship.new(C_Likes.new(), e_apple) +var r_attacking_players = Relationship.new(C_IsAttacking.new(), Player) + +# Use the same relationship object multiple times +entity1.add_relationship(r_attacking_players) +entity2.add_relationship(r_attacking_players) +``` + +**Static Relationship Factory (Recommended):** + +```gdscript +# ✅ Excellent - Organized relationship management +class_name Relationships + +static func attacking_players(): + return Relationship.new(C_IsAttacking.new(), Player) + +static func attacking_anything(): + return Relationship.new(C_IsAttacking.new(), ECS.wildcard) + +static func chasing_players(): + return Relationship.new(C_IsChasing.new(), Player) + +static func interacting_with_anything(): + return Relationship.new(C_Interacting.new(), ECS.wildcard) + +static func equipped_on_anything(): + return Relationship.new(C_EquippedOn.new(), ECS.wildcard) + +static func any_status_effect(): + return Relationship.new(C_HasEffect.new(), null) + +static func any_damage_effect(): + return Relationship.new(C_Damage.new(), null) + +static func any_buff(): + return Relationship.new(C_Buff.new(), null) + +# Usage in systems: +var attackers = ECS.world.query.with_relationship([Relationships.attacking_players()]).execute() +var chasers = ECS.world.query.with_relationship([Relationships.chasing_anything()]).execute() + +# Usage with limits: +entity.remove_relationship(Relationships.any_status_effect(), 1) # Remove one effect +entity.remove_relationship(Relationships.any_damage_effect(), 3) # Remove up to 3 damage effects +entity.remove_relationship(Relationships.any_buff()) # Remove all buffs +``` + +**Limited Removal Best Practices:** + +```gdscript +# ✅ Good - Clear intent with descriptive variables +var WEAK_CLEANSE = 1 +var MEDIUM_CLEANSE = 3 +var STRONG_CLEANSE = -1 # All + +entity.remove_relationship(Relationships.any_debuff(), WEAK_CLEANSE) + +# ✅ Good - Helper functions for common operations +func remove_one_poison(entity: Entity): + entity.remove_relationship(Relationship.new(C_Poison.new(), null), 1) + +func remove_all_fire_damage(entity: Entity): + entity.remove_relationship(Relationship.new(C_Damage.new(), C_FireDamage)) + +func partial_heal(entity: Entity, healing_power: int): + entity.remove_relationship(Relationship.new(C_Damage.new(), null), healing_power) + +# ✅ Excellent - Validation before removal +func safe_remove_effects(entity: Entity, count: int): + var current_effects = entity.get_relationships(Relationship.new(C_Effect.new(), null)).size() + var to_remove = min(count, current_effects) + if to_remove > 0: + entity.remove_relationship(Relationship.new(C_Effect.new(), null), to_remove) + print("Removed ", to_remove, " effects") +``` + +### Naming Conventions + +**Relationship Components:** + +- Use descriptive names that clearly indicate the relationship +- Follow the `C_VerbNoun` pattern when possible +- Examples: `C_Likes`, `C_IsAttacking`, `C_OwnerOf`, `C_MemberOf` + +**Relationship Variables:** + +- Use `r_` prefix for relationship instances +- Examples: `r_likes_alice`, `r_attacking_player`, `r_parent_of_child` + +## 🎯 Next Steps + +Now that you understand relationships, component queries, and limited removal: + +1. **Design relationship schemas** for your game's entities +2. **Experiment with wildcard queries** for dynamic systems +3. **Use component queries** to filter relationships by property criteria +4. **Implement limited removal** for stack-based and graduated systems +5. **Combine type matching with component queries** for flexible filtering +6. **Optimize with static relationship factories** for better performance +7. **Use limit parameters** for fine-grained control in healing, crafting, and effect systems +8. **Learn advanced patterns** in [Best Practices Guide](BEST_PRACTICES.md) + +**Quick Start Checklist for Component Queries:** +- ✅ Try basic component query: `Relationship.new({C_Damage: {'amount': {"_gt": 10}}}, null)` +- ✅ Use query operators: `_eq`, `_ne`, `_gt`, `_lt`, `_gte`, `_lte`, `_in`, `_nin` +- ✅ Query both relation and target properties +- ✅ Combine queries with wildcards for flexible filtering +- ✅ Use type matching for "any component of this type" queries + +**Quick Start Checklist for Limited Removal:** +- ✅ Try basic limit syntax: `entity.remove_relationship(rel, 1)` +- ✅ Build a simple stack system (buffs, debuffs, or damage) +- ✅ Create helper functions for common removal patterns +- ✅ Integrate limits into your game systems (healing, cleansing, etc.) +- ✅ Test edge cases (limit > available relationships) +- ✅ Combine component queries with limits for precise control + +## 📚 Related Documentation + +- **[Core Concepts](CORE_CONCEPTS.md)** - Understanding the ECS fundamentals +- **[Component Queries](COMPONENT_QUERIES.md)** - Advanced property-based filtering +- **[Best Practices](BEST_PRACTICES.md)** - Write maintainable ECS code +- **[Performance Optimization](PERFORMANCE_OPTIMIZATION.md)** - Optimize relationship queries + +--- + +_"Relationships turn a collection of entities into a living, interconnected game world where entities can react to each other in meaningful ways."_ diff --git a/addons/gecs/docs/SERIALIZATION.md b/addons/gecs/docs/SERIALIZATION.md new file mode 100644 index 0000000..72ff4ed --- /dev/null +++ b/addons/gecs/docs/SERIALIZATION.md @@ -0,0 +1,218 @@ +# GECS Serialization + +The GECS framework provides a robust serialization system using Godot's native resource format, enabling persistent game states, save systems, and level data management. + +## Quick Start + +### Basic Save/Load + +```gdscript +# Save entities with persistent components +var query = ECS.world.query.with_all([C_Persistent]) +var data = ECS.serialize(query) +ECS.save(data, "user://savegame.tres") + +# Load entities back +var entities = ECS.deserialize("user://savegame.tres") +for entity in entities: + ECS.world.add_entity(entity) +``` + +### Binary Format + +```gdscript +# Save as binary for production (smaller files) +ECS.save(data, "user://savegame.tres", true) # Creates .res file + +# Load auto-detects format (tries .res first, then .tres) +var entities = ECS.deserialize("user://savegame.tres") +``` + +## API Reference + +### ECS.serialize(query: QueryBuilder) -> GecsData + +Converts entities matching a query into serializable data. + +**Example:** + +```gdscript +# Serialize specific entities +var player_query = ECS.world.query.with_all([C_Player, C_Health]) +var save_data = ECS.serialize(player_query) +``` + +### ECS.save(data: GecsData, filepath: String, binary: bool = false) -> bool + +Saves data to disk. Returns `true` on success. + +**Parameters:** + +- `data`: Serialized entity data +- `filepath`: Save location (use `.tres` extension) +- `binary`: If `true`, saves as `.res` (smaller, faster loading) + +### ECS.deserialize(filepath: String) -> Array[Entity] + +Loads entities from file. Returns empty array if file doesn't exist. + +**Auto-detection:** Tries binary `.res` first, falls back to text `.tres`. + +## Component Serialization + +Only `@export` variables are serialized: + +```gdscript +class_name C_PlayerData +extends Component + +@export var health: float = 100.0 # ✅ Saved +@export var inventory: Array[String] # ✅ Saved +@export var position: Vector2 # ✅ Saved + +var _cache: Dictionary = {} # ❌ Not saved +``` + +**Supported types:** All Godot built-ins (int, float, String, Vector2/3, Color, Array, Dictionary, etc.) + +## Use Cases + +### Save Game System + +```gdscript +func save_game(slot: String): + var query = ECS.world.query.with_all([C_Persistent]) + var data = ECS.serialize(query) + + if ECS.save(data, "user://saves/slot_%s.tres" % slot, true): + print("Game saved!") + +func load_game(slot: String): + ECS.world.purge() # Clear current state + + var entities = ECS.deserialize("user://saves/slot_%s.tres" % slot) + for entity in entities: + ECS.world.add_entity(entity) +``` + +### Level Export/Import + +```gdscript +func export_level(): + var query = ECS.world.query.with_all([C_LevelObject]) + var data = ECS.serialize(query) + ECS.save(data, "res://levels/level_01.tres") + +func load_level(path: String): + var entities = ECS.deserialize(path) + ECS.world.add_entities(entities) +``` + +### Selective Serialization + +```gdscript +# Save only player data +var player_query = ECS.world.query.with_all([C_Player]) + +# Save entities in specific area +var area_query = ECS.world.query.with_group("area_1") + +# Save entities with specific components +var combat_query = ECS.world.query.with_all([C_Health, C_Weapon]) +``` + +## Data Structure + +The system uses two main resource classes: + +### GecsData + +```gdscript +class_name GecsData +extends Resource + +@export var version: String = "0.1" +@export var entities: Array[GecsEntityData] = [] +``` + +### GecsEntityData + +```gdscript +class_name GecsEntityData +extends Resource + +@export var entity_name: String = "" +@export var scene_path: String = "" # For prefab entities +@export var components: Array[Component] = [] +``` + +## Error Handling + +```gdscript +# Serialize never fails (returns empty data if no matches) +var data = ECS.serialize(query) + +# Check save success +if not ECS.save(data, filepath): + print("Save failed - check permissions") + +# Handle missing files +var entities = ECS.deserialize(filepath) +if entities.is_empty(): + print("No data loaded") +``` + +## Performance + +- **Memory:** Creates component copies during serialization +- **Speed:** Binary format ~60% smaller, faster loading than text +- **Scale:** Tested with 100+ entities, sub-second performance + +## Binary vs Text Format + +**Text (.tres):** + +- Human readable +- Editor inspectable +- Version control friendly +- Development debugging + +**Binary (.res):** + +- Smaller file size +- Faster loading +- Production builds +- Auto-detection on load + +## File Structure Example + +```tres +[gd_resource type="GecsData" format=3] + +[sub_resource type="C_Health" id="1"] +current = 85.0 +maximum = 100.0 + +[sub_resource type="GecsEntityData" id="2"] +entity_name = "Player" +components = [SubResource("1")] + +[resource] +version = "0.1" +entities = [SubResource("2")] +``` + +## Best Practices + +1. **Use meaningful filenames:** `player_save.tres`, `level_boss.tres` +2. **Organize by purpose:** `user://saves/`, `res://levels/` +3. **Handle missing components gracefully** +4. **Use binary format for production** +5. **Version your save data for compatibility** +6. **Test with empty query results** + +## Limitations + +- No entity relationships (planned feature) +- Prefab entities need scene files present +- External resource references need manual handling diff --git a/addons/gecs/docs/TROUBLESHOOTING.md b/addons/gecs/docs/TROUBLESHOOTING.md new file mode 100644 index 0000000..a276025 --- /dev/null +++ b/addons/gecs/docs/TROUBLESHOOTING.md @@ -0,0 +1,434 @@ +# GECS Troubleshooting Guide + +> **Quickly solve common GECS issues** + +This guide helps you diagnose and fix the most common problems when working with GECS. Find your issue, apply the solution, and learn how to prevent it. + +## 📋 Quick Diagnosis + +### My Game Isn't Working At All + +**Symptoms**: No entities moving, systems not running, nothing happening + +**Quick Check**: + +```gdscript +# In your _process() method, ensure you have: +func _process(delta): + if ECS.world: + ECS.world.process(delta) # This line is critical! +``` + +**Missing this?** → [Systems Not Running](#systems-not-running) + +### Entities Aren't Moving/Updating + +**Symptoms**: Entities exist but don't respond to systems + +**Quick Check**: + +1. Are your entities added to the world? `ECS.world.add_entity(entity)` +2. Do your entities have the right components? Check system queries +3. Are your systems properly organized in scene hierarchy? Check default_systems.tscn + +**Still broken?** → [Entity Issues](#entity-issues) + +### Performance Is Terrible + +**Symptoms**: Low FPS, stuttering, slow response + +**Quick Check**: + +1. Enable profiling: `ECS.world.enable_profiling = true` +2. Check entity count: `print(ECS.world.entity_count)` +3. Look for expensive queries in your systems + +**Need optimization?** → [Performance Issues](#performance-issues) + +## 🚫 Systems Not Running + +### Problem: Systems Never Execute + +**Error Messages**: + +- No error, but `process()` method never called +- Entities exist but don't change + +**Solution**: + +```gdscript +# ✅ Ensure this exists in your main scene +func _process(delta): + ECS.process(delta) # This processes all systems + +# OR if using system groups: +func _process(delta): + ECS.process(delta, "physics") + ECS.process(delta, "render") +``` + +**Prevention**: Always call `ECS.process()` in your main game loop. + +### Problem: System Query Returns Empty + +**Symptoms**: System exists but `process()` never called + +**Diagnosis**: + +```gdscript +# Add this to your system for debugging +class_name MySystem extends System + +func _ready(): + print("MySystem query result: ", query().execute().size()) + +func query(): + return q.with_all([C_ComponentA, C_ComponentB]) +``` + +**Common Causes**: + +1. **Missing Components**: + + ```gdscript + # ❌ Problem - Entity missing required component + var entity = Entity.new() + entity.add_component(C_ComponentA.new()) + # Missing C_ComponentB! + + # ✅ Solution - Add all required components + entity.add_component(C_ComponentA.new()) + entity.add_component(C_ComponentB.new()) + ``` + +2. **Wrong Component Types**: + + ```gdscript + # ❌ Problem - Using instance instead of class + func query(): + return q.with_all([C_ComponentA.new()]) # Wrong! + + # ✅ Solution - Use class reference + func query(): + return q.with_all([C_ComponentA]) # Correct! + ``` + +3. **Component Not Added to World**: + + ```gdscript + # ❌ Problem - Entity not in world + var entity = Entity.new() + entity.add_component(C_ComponentA.new()) + # Entity never added to world! + + # ✅ Solution - Add entity to world + ECS.world.add_entity(entity) + ``` + +## 🎭 Entity Issues + +### Problem: Entity Components Not Found + +**Error Messages**: + +- `get_component() returned null` +- `Entity does not have component of type...` + +**Diagnosis**: + +```gdscript +# Debug what components an entity actually has +func debug_entity_components(entity: Entity): + print("Entity components:") + for component_path in entity.components.keys(): + print(" ", component_path) +``` + +**Solution**: Ensure components are added correctly: + +```gdscript +# ✅ Correct component addition +var entity = Entity.new() +entity.add_component(C_Health.new(100)) +entity.add_component(C_Position.new(Vector2(50, 50))) + +# Verify component exists before using +if entity.has_component(C_Health): + var health = entity.get_component(C_Health) + health.current -= 10 +``` + +### Problem: Component Properties Not Updating + +**Symptoms**: Setting component properties has no effect + +**Common Causes**: + +1. **Getting Component Reference Once**: + + ```gdscript + # ❌ Problem - Stale component reference + var health = entity.get_component(C_Health) + # ... later in code, component gets replaced ... + health.current = 50 # Updates old component! + + # ✅ Solution - Get fresh reference each time + entity.get_component(C_Health).current = 50 + ``` + +2. **Modifying Wrong Entity**: + + ```gdscript + # ❌ Problem - Variable confusion + var player = get_player_entity() + var enemy = get_enemy_entity() + + # Accidentally modify wrong entity + player.get_component(C_Health).current = 0 # Meant to be enemy! + + # ✅ Solution - Use clear variable names + var player_health = player.get_component(C_Health) + var enemy_health = enemy.get_component(C_Health) + enemy_health.current = 0 + ``` + +## 💥 Common Errors + +### Error: "Cannot access property/method on null instance" + +**Full Error**: + +``` +Invalid get index 'current' (on base: 'null instance') +``` + +**Cause**: Component doesn't exist on entity + +**Solution**: + +```gdscript +# ❌ Causes null error +var health = entity.get_component(C_Health) +health.current -= 10 # health is null! + +# ✅ Safe component access +if entity.has_component(C_Health): + var health = entity.get_component(C_Health) + health.current -= 10 +else: + print("Entity doesn't have C_Health!") +``` + +### Error: "Class not found" + +**Full Error**: + +``` +Identifier 'ComponentName' not found in current scope +``` + +**Causes & Solutions**: + +1. **Missing class_name**: + + ```gdscript + # ❌ Problem - No class_name declaration + extends Component + # Script exists but can't be referenced by name + + # ✅ Solution - Add class_name + class_name C_Health + extends Component + ``` + +2. **File not saved or loaded**: + + - Save your component script files + - Restart Godot if classes still not found + - Check for syntax errors in the component file + +3. **Wrong inheritance**: + + ```gdscript + # ❌ Problem - Wrong base class + class_name C_Health + extends Node # Should be Component! + + # ✅ Solution - Correct inheritance + class_name C_Health + extends Component + ``` + +## 🐌 Performance Issues + +### Problem: Low FPS / Stuttering + +**Diagnosis Steps**: + +1. **Enable profiling**: + + ```gdscript + ECS.world.enable_profiling = true + + # Check processing times + func _process(delta): + ECS.process(delta) + print("Frame time: ", get_process_delta_time() * 1000, "ms") + ``` + +2. **Check entity count**: + ```gdscript + print("Total entities: ", ECS.world.entity_count) + print("System count: ", ECS.world.get_system_count()) + ``` + +**Common Fixes**: + +1. **Too Many Entities in Broad Queries**: + + ```gdscript + # ❌ Problem - Overly broad query + func query(): + return q.with_all([C_Position]) # Matches everything! + + # ✅ Solution - More specific query + func query(): + return q.with_all([C_Position, C_Movable]) + ``` + +2. **Expensive Queries Rebuilt Every Frame**: + + ```gdscript + # ❌ Problem - Rebuilding queries in process + func process(entities: Array[Entity], components: Array, delta: float): + var custom_entities = ECS.world.query.with_all([C_ComponentA]).execute() + + # ✅ Solution - Use the system's query() method (automatically cached) + func query(): + return q.with_all([C_ComponentA]) # Automatically cached by GECS + + func process(entities: Array[Entity], components: Array, delta: float): + # Just process the entities passed in - already filtered by query + for entity in entities: + # Process entity... + ``` + +## 🔧 Integration Issues + +### Problem: GECS Conflicts with Godot Features + +**Issue**: Using GECS entities with Godot nodes causes problems + +**Solution**: Choose your approach consistently: + +```gdscript +# ✅ Approach 1 - Pure ECS (recommended for complex games) +# Entities are not nodes, use ECS for everything +var entity = Entity.new() # Not added to scene tree +entity.add_component(C_Position.new()) +ECS.world.add_entity(entity) + +# ✅ Approach 2 - Hybrid (good for simpler games) +# Entities are nodes, use ECS for specific systems +var entity = Entity.new() +add_child(entity) # Entity is in scene tree +entity.add_component(C_Health.new()) +ECS.world.add_entity(entity) +``` + +**Avoid**: Mixing approaches inconsistently in the same project. + +### Problem: GECS Not Working After Scene Changes + +**Symptoms**: Systems stop working when changing scenes + +**Solution**: Properly reinitialize ECS in new scenes: + +```gdscript +# In each main scene script +func _ready(): + # Create new world for this scene + var world = World.new() + add_child(world) + ECS.world = world + + # Systems are usually managed via scene composition + # See default_systems.tscn for organization + + # Create your entities + setup_entities() +``` + +**Prevention**: Always initialize ECS properly in each scene that uses it. + +## 🛠️ Debugging Tools + +### Enable Debug Logging + +Add to your project settings or main script: + +```gdscript +# Enable GECS debug output +ECS.set_debug_level(ECS.DEBUG_VERBOSE) + +# This will show: +# - Entity creation/destruction +# - Component additions/removals +# - System processing information +# - Query execution details +``` + +### Entity Inspector Tool + +Create a debug tool to inspect entities at runtime: + +```gdscript +# DebugPanel.gd +extends Control + +func _on_inspect_button_pressed(): + var entities = ECS.world.get_all_entities() + print("=== ENTITY INSPECTOR ===") + + for i in range(min(10, entities.size())): # Show first 10 + var entity = entities[i] + print("Entity ", i, ":") + print(" Components: ", entity.components.keys()) + print(" Groups: ", entity.get_groups()) + + # Show component values + for comp_path in entity.components.keys(): + var comp = entity.components[comp_path] + print(" ", comp_path, ": ", comp) +``` + +## 📚 Getting More Help + +### Community Resources + +- **Discord**: [Join our community](https://discord.gg/eB43XU2tmn) for help and discussions +- **GitHub Issues**: [Report bugs](https://github.com/csprance/gecs/issues) +- **Documentation**: [Complete Guide](../DOCUMENTATION.md) + +### Before Asking for Help + +Include this information in your question: + +1. **GECS version** you're using +2. **Godot version** you're using +3. **Minimal code example** that reproduces the issue +4. **Error messages** (full text, not paraphrased) +5. **Expected vs actual behavior** + +### Still Stuck? + +If this guide doesn't solve your problem: + +1. **Check the examples** in [Getting Started](GETTING_STARTED.md) +2. **Review best practices** in [Best Practices](BEST_PRACTICES.md) +3. **Search GitHub issues** for similar problems +4. **Create a minimal reproduction** and ask for help + +--- + +_"Every bug is a learning opportunity. The key is knowing where to look and what questions to ask."_ diff --git a/addons/gecs/ecs/archetype.gd b/addons/gecs/ecs/archetype.gd new file mode 100644 index 0000000..e822559 --- /dev/null +++ b/addons/gecs/ecs/archetype.gd @@ -0,0 +1,299 @@ +## Archetype +## +## Represents a unique combination of component types in the ECS framework. +## Entities with the exact same set of components share an archetype. +## +## Archetypes enable high-performance queries by grouping entities with identical +## component structures together in flat arrays, providing excellent cache locality +## and eliminating the need for set intersections during queries. +## +## [b]Key Concepts:[/b] +## - [b]Signature:[/b] Hash of all component types (determines archetype identity) +## - [b]Entities:[/b] Flat array of entities with this exact component combination +## - [b]Edges:[/b] Fast lookup for when components are added/removed (future optimization) +## +## [b]Example:[/b] +## [codeblock] +## # Archetype for entities with Position + Velocity +## var archetype = Archetype.new(12345, ["Position", "Velocity"]) +## archetype.add_entity(player) +## archetype.add_entity(enemy) +## # Now both entities are stored contiguously for fast iteration +## [/codeblock] +## +## [b]Performance:[/b] +## - Add entity: O(1) amortized (array append) +## - Remove entity: O(1) (swap-remove with index tracking) +## - Query match: O(1) (check if archetype signature matches query) +## - Iterate entities: O(n) with excellent cache locality +class_name Archetype +extends RefCounted + +## Unique hash identifying this component combination +## Generated by QueryCacheKey.build() from sorted component types +var signature: int = 0 + +## Sorted array of component resource paths (e.g., ["res://c_position.gd", "res://c_velocity.gd"]) +## Used for debugging and archetype matching logic +var component_types: Array = [] + +## Flat array of entities with this exact component combination +## Provides excellent cache locality when iterating in systems +var entities: Array[Entity] = [] + +## Fast lookup: Entity -> index in entities array +## Enables O(1) entity removal using swap-remove technique +var entity_to_index: Dictionary = {} # Entity -> int + +## OPTIMIZATION: Bitset for enabled/disabled state instead of archetype splitting +## Uses PackedInt64Array where each bit represents whether entity at that index is enabled +## Reduces archetype count by 2x and enables O(1) enabled/disabled filtering +var enabled_bitset: PackedInt64Array = [] + +## OPTIMIZATION: Structure of Arrays (SoA) column storage for cache-friendly iteration +## Maps component_path -> Array of component instances +## Enables Flecs-style direct array iteration without dictionary lookups +## Example: columns["res://c_velocity.gd"] = [vel1, vel2, vel3, ...] +var columns: Dictionary = {} # String (component_path) -> Array of components + +## Archetype edges for fast component add/remove (future optimization) +## Maps: component_path -> Archetype (the archetype you get by adding/removing that component) +var add_edges: Dictionary = {} # String -> Archetype +var remove_edges: Dictionary = {} # String -> Archetype + + +## Initialize archetype with signature and component types +func _init(p_signature: int, p_component_types: Array): + signature = p_signature + component_types = p_component_types.duplicate() + component_types.sort() # Ensure sorted for consistent matching + + # Initialize column arrays for each component type + for comp_type in component_types: + columns[comp_type] = [] + + +## Add an entity to this archetype +## Uses O(1) append and tracks index for fast removal +## OPTIMIZATION: Also populates column arrays for cache-friendly iteration +func add_entity(entity: Entity) -> void: + var index = entities.size() + entities.append(entity) + entity_to_index[entity] = index + + # OPTIMIZATION: Update enabled bitset + _ensure_bitset_capacity(index + 1) + _set_enabled_bit(index, entity.enabled) + + # OPTIMIZATION: Populate column arrays from entity.components + for comp_path in component_types: + if entity.components.has(comp_path): + (columns[comp_path] + .append(entity.components[comp_path])) + else: + # Entity doesn't have this component yet (might be mid-initialization) + # Push null placeholder, will be fixed when component is added + columns[comp_path].append(null) + + +## Remove an entity from this archetype using swap-remove +## O(1) operation: swaps with last entity and pops +## OPTIMIZATION: Also maintains column arrays in sync +func remove_entity(entity: Entity) -> bool: + if not entity_to_index.has(entity): + return false + + var index = entity_to_index[entity] + var last_index = entities.size() - 1 + + # Swap with last element in entities array + if index != last_index: + var last_entity = entities[last_index] + entities[index] = last_entity + entity_to_index[last_entity] = index + + # OPTIMIZATION: Swap in column arrays too (maintain same ordering) + for comp_path in component_types: + columns[comp_path][index] = columns[comp_path][last_index] + + # OPTIMIZATION: Swap enabled bit + var last_enabled = _get_enabled_bit(last_index) + _set_enabled_bit(index, last_enabled) + + # Remove last element from entities + entities.pop_back() + entity_to_index.erase(entity) + + # OPTIMIZATION: Remove last element from all columns + for comp_path in component_types: + columns[comp_path].pop_back() + + # OPTIMIZATION: Update bitset size (no need to clear the bit, just reduce logical size) + # The bit will be overwritten when a new entity is added + + return true + + +## Check if this archetype has a specific entity +func has_entity(entity: Entity) -> bool: + return entity_to_index.has(entity) + + +## Get entity count in this archetype +func size() -> int: + return entities.size() + + +## Check if archetype is empty +func is_empty() -> bool: + return entities.is_empty() + + +## Clear all entities from this archetype +func clear() -> void: + entities.clear() + entity_to_index.clear() + + # OPTIMIZATION: Clear column arrays + for comp_path in component_types: + columns[comp_path].clear() + + # OPTIMIZATION: Clear bitset + enabled_bitset.clear() + + +## Check if this archetype matches a query with all/any/exclude components +## [param all_comp_types] Component paths that must all be present +## [param any_comp_types] Component paths where at least one must be present +## [param exclude_comp_types] Component paths that must not be present +func matches_query(all_comp_types: Array, any_comp_types: Array, exclude_comp_types: Array) -> bool: + # Check all_components: must have ALL of these + for comp_type in all_comp_types: + if not component_types.has(comp_type): + return false + + # Check any_components: must have AT LEAST ONE of these + if not any_comp_types.is_empty(): + var has_any = false + for comp_type in any_comp_types: + if component_types.has(comp_type): + has_any = true + break + if not has_any: + return false + + # Check exclude_components: must have NONE of these + for comp_type in exclude_comp_types: + if component_types.has(comp_type): + return false + + return true + + +## Get a debug-friendly string representation +func _to_string() -> String: + var comp_names = [] + for comp_type in component_types: + # Extract just the class name from the path + var parts = comp_type.split("/") + var filename = parts[parts.size() - 1].replace(".gd", "") + comp_names.append(filename) + + return "Archetype[sig=%d, comps=%s, entities=%d]" % [ + signature, + str(comp_names), + entities.size() + ] + + +## Set up an edge to another archetype when a component is added +## Enables O(1) archetype transitions when components change +func set_add_edge(component_path: String, target_archetype: Archetype) -> void: + add_edges[component_path] = target_archetype + + +## Set up an edge to another archetype when a component is removed +## Enables O(1) archetype transitions when components change +func set_remove_edge(component_path: String, target_archetype: Archetype) -> void: + remove_edges[component_path] = target_archetype + + +## Get the target archetype when adding a component (if edge exists) +func get_add_edge(component_path: String) -> Archetype: + return add_edges.get(component_path, null) + + +## Get the target archetype when removing a component (if edge exists) +func get_remove_edge(component_path: String) -> Archetype: + return remove_edges.get(component_path, null) + + +## OPTIMIZATION: Get component column array for cache-friendly iteration +## Enables Flecs-style direct array access instead of dictionary lookups per entity +## [param component_path] The resource path of the component type (e.g., C_Velocity.resource_path) +## [returns] Array of component instances in entity index order, or empty array if not found +## +## Example: +## [codeblock] +## var velocities = archetype.get_column(C_Velocity.resource_path) +## for i in range(velocities.size()): +## var velocity = velocities[i] +## var entity = archetype.entities[i] +## # Process with cache-friendly sequential access +## [/codeblock] +func get_column(component_path: String) -> Array: + return columns.get(component_path, []) + + +## OPTIMIZATION: Get entities filtered by enabled state using bitset +## [param enabled_only] If true, return only enabled entities; if false, only disabled +## [returns] Array of entities matching the enabled state +func get_entities_by_enabled_state(enabled_only: bool) -> Array[Entity]: + var result: Array[Entity] = [] + for i in range(entities.size()): + if _get_enabled_bit(i) == enabled_only: + result.append(entities[i]) + return result + + +## OPTIMIZATION: Update entity enabled state in bitset +## [param entity] The entity to update +## [param enabled] The new enabled state +func update_entity_enabled_state(entity: Entity, enabled: bool) -> void: + if entity_to_index.has(entity): + var index = entity_to_index[entity] + _set_enabled_bit(index, enabled) + + +## OPTIMIZATION: Ensure bitset has enough capacity for the given number of entities +func _ensure_bitset_capacity(required_size: int) -> void: + var required_int64s = (required_size + 63) / 64 # Round up to nearest 64-bit boundary + while enabled_bitset.size() < required_int64s: + enabled_bitset.append(0) + + +## OPTIMIZATION: Set enabled bit for entity at index +func _set_enabled_bit(index: int, enabled: bool) -> void: + var int64_index = index / 64 + var bit_index = index % 64 + + _ensure_bitset_capacity(index + 1) + + if enabled: + enabled_bitset[int64_index] |= (1 << bit_index) + else: + enabled_bitset[int64_index] &= ~(1 << bit_index) + + +## OPTIMIZATION: Get enabled bit for entity at index +func _get_enabled_bit(index: int) -> bool: + if index >= entities.size(): + return false + + var int64_index = index / 64 + var bit_index = index % 64 + + if int64_index >= enabled_bitset.size(): + return false + + return (enabled_bitset[int64_index] & (1 << bit_index)) != 0 diff --git a/addons/gecs/ecs/archetype.gd.uid b/addons/gecs/ecs/archetype.gd.uid new file mode 100644 index 0000000..c1978bd --- /dev/null +++ b/addons/gecs/ecs/archetype.gd.uid @@ -0,0 +1 @@ +uid://vrhpkju2aq7q diff --git a/addons/gecs/ecs/component.gd b/addons/gecs/ecs/component.gd new file mode 100644 index 0000000..d393ef7 --- /dev/null +++ b/addons/gecs/ecs/component.gd @@ -0,0 +1,48 @@ +## A Component serves as a data container within the [_ECS] ([Entity] [Component] [System]) framework. +## +## A [Component] holds specific data related to an [Entity] but does not contain any behavior or logic.[br] +## Components are designed to be lightweight and easily attachable to [Entity]s to define their properties.[br] +##[br] +## [b]Example:[/b] +##[codeblock] +## ## Velocity Component. +## ## +## ## Holds the velocity data for an entity. +## class_name VelocityComponent +## extends Node2D +## +## @export var velocity: Vector2 = Vector2.ZERO +##[/codeblock] +##[br] +## [b]Component Queries:[/b][br] +## Use component query dictionaries to match components by specific property criteria in queries and relationships:[br] +##[codeblock] +## # Query entities with health >= 50 +## var entities = ECS.world.query.with_all([{C_Health: {'amount': {"_gte": 50}}}]).execute() +## +## # Query relationships with specific damage values +## var entities = ECS.world.query.with_relationship([ +## Relationship.new({C_Damage: {'amount': {"_eq": 100}}}, target) +## ]).execute() +##[/codeblock] +@icon("res://addons/gecs/assets/component.svg") +class_name Component +extends Resource + +## Emitted when a property of this component changes. This is slightly different from the property_changed signal +signal property_changed(component: Resource, property_name: String, old_value: Variant, new_value: Variant) + +## Reference to the parent entity that owns this component +var parent: Entity + +## Used to serialize the component to a dictionary with only the export variables +## This is used for the debugger to send the data to the editor +func serialize() -> Dictionary: + var data: Dictionary = {} + for prop_info in get_script().get_script_property_list(): + # Only include properties that are exported (@export variables) + if prop_info.usage & PROPERTY_USAGE_EDITOR: + var prop_name: String = prop_info.name + var prop_val = get(prop_name) + data[prop_name] = prop_val + return data diff --git a/addons/gecs/ecs/component.gd.uid b/addons/gecs/ecs/component.gd.uid new file mode 100644 index 0000000..fa8e6df --- /dev/null +++ b/addons/gecs/ecs/component.gd.uid @@ -0,0 +1 @@ +uid://b6k13gc2m4e5s diff --git a/addons/gecs/ecs/ecs.gd b/addons/gecs/ecs/ecs.gd new file mode 100644 index 0000000..43c68a3 --- /dev/null +++ b/addons/gecs/ecs/ecs.gd @@ -0,0 +1,102 @@ +## ECS ([Entity] [Component] [System]) Singleton[br] +## The ECS class acts as the central manager for the entire ECS framework +## +## The [_ECS] class maintains the current active [World] and provides access to [QueryBuilder] for fetching [Entity]s based on their [Component]s. +##[br] +## This singleton allows any part of the game to interact with the ECS system seamlessly. +## [codeblock] +## var entities = ECS.world.query.with_all([Transform, Velocity]).execute() +## for entity in entities: +## entity.get_component(Transform).position += entity.get_component(Velocity).direction * delta +## [/codeblock] +## This is also where you control the setup of the world and process loop of the ECS system. +##[codeblock] +## +## func _read(delta): +## ECS.world = world +## +## func _process(delta): +## ECS.process(delta) +##[/codeblock] +## or in the physics loop +##[codeblock] +## func _physics_process(delta): +## ECS.process(delta) +##[/codeblock] +class_name _ECS +extends Node + +## Emitted when the world is changed with a ref to the new world +signal world_changed(world: World) +## Emitted when the world is exited +signal world_exited + +## The Current active [World] Instance[br] +## Holds a reference to the currently active [World], allowing access to the [member World.query] instance and any [Entity]s and [System]s within it. +var world: World: + get: + return world + set(value): + # Add the new world to the scenes + world = value + if world: + if not world.is_inside_tree(): + # Add the world to the tree if it is not already + get_tree().root.get_node("./Root").add_child(world) + if not world.is_connected("tree_exited", _on_world_exited): + world.connect("tree_exited", _on_world_exited) + world_changed.emit(world) + assert(GECSEditorDebuggerMessages.set_world(world) if debug else true, 'Debug Data') + +## Are we in debug mode? Controlled by project setting gecs/debug_mode +var debug := ProjectSettings.get_setting(GecsSettings.SETTINGS_DEBUG_MODE, false) +## This is an array of functions that get called on the entities when they get added to the world (after they are ready) +var entity_preprocessors: Array[Callable] = [] +## This is an array of functions that get called on the entities right before they get removed from the world +var entity_postprocessors: Array[Callable] = [] +## A Wildcard for use in relatonship queries. Indicates can be any value for a relation +## or a target in a Relationship Pair ECS.wildcard +var wildcard = null + + +## This is called to process the current active [World] instance and the [System]s within it. +## You would call this in _process or _physics_process to update the [_ECS] system.[br] +## If you provide a group name it will run just that group otherwise it runs all groups[br] +## Example: +## [codeblock]ECS.world.process(world, 'my-system-group')[/codeblock] +func process(delta: float, group: String = "") -> void: + world.process(delta, group) + + +## Get all components of a specific type from a list of entities[br] +## If the component does not exist on the entity it will return the default_component if provided or assert +func get_components(entities, component_type, default_component = null) -> Array: + var components = [] + for entity in entities: + var component = entity.components.get(component_type.resource_path, null) + if not component and not default_component: + assert(component, "Entity does not have component: " + str(component_type)) + if not component and default_component: + component = default_component + components.append(component) + + return components + + +## Called when the world is exited +func _on_world_exited() -> void: + world = null + world_exited.emit() + assert(GECSEditorDebuggerMessages.exit_world() if debug else true, 'Debug Data') + + +func serialize(query: QueryBuilder, config: GECSSerializeConfig = null) -> GecsData: + return GECSIO.serialize(query, config) + + +func save(gecs_data: GecsData, filepath: String, binary: bool = false) -> bool: + return GECSIO.save(gecs_data, filepath, binary) + + +func deserialize(gecs_filepath: String) -> Array[Entity]: + return GECSIO.deserialize(gecs_filepath) diff --git a/addons/gecs/ecs/ecs.gd.uid b/addons/gecs/ecs/ecs.gd.uid new file mode 100644 index 0000000..14da933 --- /dev/null +++ b/addons/gecs/ecs/ecs.gd.uid @@ -0,0 +1 @@ +uid://dfqwl5njvdnmq diff --git a/addons/gecs/ecs/entity.gd b/addons/gecs/ecs/entity.gd new file mode 100644 index 0000000..d8551ad --- /dev/null +++ b/addons/gecs/ecs/entity.gd @@ -0,0 +1,509 @@ +## Entity[br] +## +## Represents an entity within the [_ECS] framework.[br] +## An entity is a container that can hold multiple [Component]s. +## +## Entities serve as the fundamental building block for game objects, allowing for flexible and modular design.[br] +##[br] +## Entities can have [Component]s added or removed dynamically, enabling the behavior and properties of game objects to change at runtime.[br] +## Entities can have [Relationship]s added or removed dynamically, allowing for a deep hierarchical query system.[br] +##[br] +## Example: +##[codeblock] +## var entity = Entity.new() +## var transform = Transform.new() +## entity.add_component(transform) +## entity.component_added.connect(_on_component_added) +## +## func _on_component_added(entity: Entity, component_key: String) -> void: +## print("Component added:", component_key) +##[/codeblock] +@icon("res://addons/gecs/assets/entity.svg") +@tool +class_name Entity +extends CharacterBody3D + +#region Signals +## Emitted when a [Component] is added to the entity. +signal component_added(entity: Entity, component: Resource) +## Emitted when a [Component] is removed from the entity. +signal component_removed(entity: Entity, component: Resource) +## Emitted when a [Component] property is changed. +signal component_property_changed( + entity: Entity, + component: Resource, + property_name: String, + old_value: Variant, + new_value: Variant +) +## Emit when a [Relationship] is added to the [Entity] +signal relationship_added(entity: Entity, relationship: Relationship) +## Emit when a [Relationship] is removed from the [Entity] +signal relationship_removed(entity: Entity, relationship: Relationship) + +#endregion Signals + +#region Exported Variables +## The id of the entity either UUID or custom string. +## This must be unique within a [World]. If left blank, a UUID will be generated when the entity is added to a world. +@export var id: String +## Is this entity active? (Will show up in queries) +@export var enabled: bool = true: + set(value): + if enabled != value: + var old_enabled = enabled + enabled = value + # Notify world to move entity between enabled/disabled archetypes + _on_enabled_changed(old_enabled, value) +## [Component]s to be attached to the entity set in the editor. These will be loaded for you and added to the [Entity] +@export var component_resources: Array[Component] = [] +## Serialization config override for this specific entity (optional) +@export var serialize_config: GECSSerializeConfig + +#endregion Exported Variables + +#region Public Variables +## [Component]s attached to the [Entity] in the form of Dict[resource_path:String, Component] +var components: Dictionary = {} + +## Relationships attached to the entity +var relationships: Array[Relationship] = [] + +## Cache for component resource paths to avoid repeated .get_script().resource_path calls +var _component_path_cache: Dictionary = {} + +## Logger for entities to only log to a specific domain +var _entityLogger = GECSLogger.new().domain("Entity") + +## We can store ephemeral state on the entity +var _state = {} + +#endregion Public Variables + +#region Built-in Virtual Methods + + +## Called to initialize the entity and its components. +## This is called automatically by [method World.add_entity][br] +func _initialize(_components: Array = []) -> void: + _entityLogger.trace("Entity Initializing Components: ", self.name) + + # because components can be added before the entity is added to the world + # replay adding components here so signals pick them up and the index is updated + var temp_comps = components.values().duplicate_deep() + components.clear() + for comp in temp_comps: + add_component(comp) + + # Add components defined in code to comp resources + component_resources.append_array(define_components()) + + # remove any component_resources that are already defined in components + # This is useful for when you instantiate an entity from a scene and want to overide components + component_resources = component_resources.filter(func(comp): return not has_component(comp.get_script())) + + # Add components passed in directly to the _initialize method to override everything else + component_resources.append_array(_components) + + # Initialize components + for res in component_resources: + add_component(res.duplicate(true)) + + # Call the lifecycle method on_ready + on_ready() + +#endregion Built-in Virtual Methods + + +## Get the effective serialization config for this entity +## Returns entity-specific config if set, otherwise falls back to world default +func get_effective_serialize_config() -> GECSSerializeConfig: + if serialize_config != null: + return serialize_config + if ECS.world != null and ECS.world.default_serialize_config != null: + return ECS.world.default_serialize_config + # Fallback if no world or no default config + var fallback = GECSSerializeConfig.new() + return fallback + +#region Components + + +## Adds a single component to the entity.[br] +## [param component] The subclass of [Component] to add.[br] +## [b]Example[/b]: +## [codeblock]entity.add_component(HealthComponent)[/codeblock] +func add_component(component: Resource) -> void: + # Cache the resource path to avoid repeated calls + var resource_path = component.get_script().resource_path + + # If a component of this type already exists, remove it first + if components.has(resource_path): + var existing_component = components[resource_path] + remove_component(existing_component) + + _component_path_cache[component] = resource_path + components[resource_path] = component + component.parent = self + if not component.property_changed.is_connected(_on_component_property_changed): + component.property_changed.connect(_on_component_property_changed) + ## Adding components happens through a signal + component_added.emit(self , component) + _entityLogger.trace("Added Component: ", resource_path) + + +func _on_component_property_changed( + component: Resource, property_name: String, old_value: Variant, new_value: Variant +) -> void: + # Pass this signal on to the world + component_property_changed.emit(self , component, property_name, old_value, new_value) + + +## Adds multiple components to the entity.[br] +## [param _components] An [Array] of [Component]s to add.[br] +## [b]Example:[/b] +## [codeblock]entity.add_components([TransformComponent, VelocityComponent])[/codeblock] +func add_components(_components: Array): + # OPTIMIZATION: Batch component additions to avoid multiple archetype transitions + # Instead of moving archetype once per component, calculate the final archetype once + if _components.is_empty(): + return + + # Add all components to local storage first (no signals yet) + var added_components = [] + for component in _components: + if component == null: + continue + var component_path = component.get_script().resource_path + if not components.has(component_path): + components[component_path] = component + added_components.append(component) + + # If no new components were actually added, return early + if added_components.is_empty(): + return + + # OPTIMIZATION: Move to final archetype only once, after all components are added + if ECS.world and ECS.world.entity_to_archetype.has(self ): + var old_archetype = ECS.world.entity_to_archetype[ self ] + var new_signature = ECS.world._calculate_entity_signature(self ) + var comp_types = components.keys() + var new_archetype = ECS.world._get_or_create_archetype(new_signature, comp_types) + + # Only move if we actually need a different archetype + if old_archetype != new_archetype: + # Remove from old archetype + old_archetype.remove_entity(self ) + # Add to new archetype + new_archetype.add_entity(self ) + ECS.world.entity_to_archetype[ self ] = new_archetype + + # Clean up empty old archetype + if old_archetype.is_empty(): + old_archetype.add_edges.clear() + old_archetype.remove_edges.clear() + ECS.world.archetypes.erase(old_archetype.signature) + else: + # Same archetype - just update the column data for new components + for component in added_components: + var comp_path = component.get_script().resource_path + var entity_index = old_archetype.entity_to_index[ self ] + old_archetype.columns[comp_path][entity_index] = component + + # Emit signals for all added components + for component in added_components: + component_added.emit(self , component) + + +## Removes a single component from the entity.[br] +## [param component] The [Component] subclass to remove.[br] +## [b]Example:[/b] +## [codeblock]entity.remove_component(HealthComponent)[/codeblock] +func remove_component(component: Resource) -> void: + # Use cached path if available, otherwise get it from the component class + var resource_path: String + if _component_path_cache.has(component): + resource_path = _component_path_cache[component] + _component_path_cache.erase(component) + else: + # Component parameter should be a class/script, consistent with has_component + resource_path = component.resource_path + + if components.has(resource_path): + var component_instance = components[resource_path] + components.erase(resource_path) + + # Clean up cache entry for the component instance + _component_path_cache.erase(component_instance) + + component_removed.emit(self , component_instance) + # ARCHETYPE: Signal handler (_on_entity_component_removed) handles archetype update + _entityLogger.trace("Removed Component: ", resource_path) + + +func deferred_remove_component(component: Resource) -> void: + call_deferred_thread_group("remove_component", component) + + +## Removes multiple components from the entity.[br] +## [param _components] An array of components to remove.[br] +## +## [b]Example:[/b] +## [codeblock]entity.remove_components([transform_component, velocity_component])[/codeblock] +func remove_components(_components: Array): + # OPTIMIZATION: Batch component removals to avoid multiple archetype transitions + # Instead of moving archetype once per component, calculate the final archetype once + if _components.is_empty(): + return + + # Remove all components from local storage first (no signals yet) + var removed_components = [] + for _component in _components: + if _component == null: + continue + var comp_to_remove: Resource = null + + # Handle both Scripts and Resource instances + # NOTE: Check Script first since Script inherits from Resource + if _component is Script: + comp_to_remove = get_component(_component) + elif _component is Resource: + comp_to_remove = _component + + if comp_to_remove: + var component_path = comp_to_remove.get_script().resource_path + if components.has(component_path): + components.erase(component_path) + removed_components.append(comp_to_remove) + + # If no components were actually removed, return early + if removed_components.is_empty(): + return + + # OPTIMIZATION: Move to final archetype only once, after all components are removed + if ECS.world and ECS.world.entity_to_archetype.has(self ): + var old_archetype = ECS.world.entity_to_archetype[ self ] + var new_signature = ECS.world._calculate_entity_signature(self ) + var comp_types = components.keys() + var new_archetype = ECS.world._get_or_create_archetype(new_signature, comp_types) + + # Only move if we actually need a different archetype + if old_archetype != new_archetype: + # Remove from old archetype + old_archetype.remove_entity(self ) + # Add to new archetype + new_archetype.add_entity(self ) + ECS.world.entity_to_archetype[ self ] = new_archetype + + # Clean up empty old archetype + if old_archetype.is_empty(): + old_archetype.add_edges.clear() + old_archetype.remove_edges.clear() + ECS.world.archetypes.erase(old_archetype.signature) + + # Emit signals for all removed components + for component in removed_components: + component_removed.emit(self , component) + + +## Removes all components from the entity.[br] +## [b]Example:[/b] +## [codeblock]entity.remove_all_components()[/codeblock] +func remove_all_components() -> void: + for component in components.values(): + remove_component(component) + + +## Retrieves a specific [Component] from the entity.[br] +## [param component] The [Component] class to retrieve.[br] +## Returns the requested [Component] if it exists, otherwise `null`.[br] +## [b]Example:[/b] +## [codeblock]var transform = entity.get_component(Transform)[/codeblock] +func get_component(component: Resource) -> Component: + return components.get(component.resource_path, null) + + +## Check to see if an entity has a specific component on it.[br] +## This is useful when you're checking to see if it has a component and not going to use the component itself.[br] +## If you plan on getting and using the component, use [method get_component] instead. +func has_component(component: Resource) -> bool: + return components.has(component.resource_path) + +#endregion Components + +#region Relationships + + +## Adds a relationship to this entity.[br] +## [param relationship] The [Relationship] to add. +func add_relationship(relationship: Relationship) -> void: + assert( + not relationship._is_query_relationship, + "Cannot add query relationships to entities. Query relationships (created with dictionaries) are for matching only, not for storage." + ) + relationship.source = self + relationships.append(relationship) + relationship_added.emit(self , relationship) + + +func add_relationships(_relationships: Array): + for relationship in _relationships: + add_relationship(relationship) + + +## Removes a relationship from the entity.[br] +## [param relationship] The [Relationship] to remove.[br] +## [param limit] Maximum number of relationships to remove. -1 = all (default), 0 = none, >0 = up to that many.[br] +## [br] +## [b]Examples:[/b] +## [codeblock] +## # Remove all matching relationships (default behavior) +## entity.remove_relationship(Relationship.new(C_Damage.new(), target)) +## +## # Remove only one matching relationship +## entity.remove_relationship(Relationship.new(C_Damage.new(), target), 1) +## +## # Remove up to 3 matching relationships +## entity.remove_relationship(Relationship.new(C_Damage.new(), target), 3) +## +## # Remove no relationships (useful for testing/debugging) +## entity.remove_relationship(Relationship.new(C_Damage.new(), target), 0) +## [/codeblock] +func remove_relationship(relationship: Relationship, limit: int = -1) -> void: + if limit == 0: + return + + var to_remove = [] + var removed_count = 0 + + var pattern_remove = true + if relationships.has(relationship): + to_remove.append(relationship) + pattern_remove = false + + if pattern_remove: + for rel in relationships: + if rel.matches(relationship): + to_remove.append(rel) + removed_count += 1 + # If limit is positive and we've reached it, stop collecting + if limit > 0 and removed_count >= limit: + break + + for rel in to_remove: + relationships.erase(rel) + relationship_removed.emit(self , rel) + + +## Removes multiple relationships from the entity.[br] +## [param _relationships] Array of [Relationship]s to remove.[br] +## [param limit] Maximum number of relationships to remove per relationship type. -1 = all (default), 0 = none, >0 = up to that many. +func remove_relationships(_relationships: Array, limit: int = -1): + for relationship in _relationships: + remove_relationship(relationship, limit) + + +## Removes all relationships from the entity. +func remove_all_relationships() -> void: + var to_remove = relationships.duplicate() + for rel in to_remove: + relationships.erase(rel) + relationship_removed.emit(self , rel) + + +## Retrieves a specific [Relationship] from the entity. +## [param relationship] The [Relationship] to retrieve. +## [return] The first matching [Relationship] if it exists, otherwise `null` +func get_relationship(relationship: Relationship) -> Relationship: + var to_remove = [] + for rel in relationships: + # Check if the relationship is valid + if not rel.valid(): + to_remove.append(rel) + continue + if rel.matches(relationship): + # Remove invalid relationships before returning + for invalid_rel in to_remove: + relationships.erase(invalid_rel) + relationship_removed.emit(self , invalid_rel) + return rel + # Remove invalid relationships + for rel in to_remove: + relationships.erase(rel) + relationship_removed.emit(self , rel) + return null + + +## Retrieves [Relationship]s from the entity. +## [param relationship] The [Relationship]s to retrieve. +## [return] Array of all matching [Relationship]s (empty array if none found). +func get_relationships(relationship: Relationship) -> Array[Relationship]: + var results: Array[Relationship] = [] + var to_remove = [] + for rel in relationships: + # Check if the relationship is valid + if not rel.valid(): + to_remove.append(rel) + continue + if rel.matches(relationship): + results.append(rel) + # Remove invalid relationships + for rel in to_remove: + relationships.erase(rel) + relationship_removed.emit(self , rel) + return results + + +## Checks if the entity has a specific relationship.[br] +## [param relationship] The [Relationship] to check for. +func has_relationship(relationship: Relationship) -> bool: + return get_relationship(relationship) != null + +#endregion Relationships + +#region Lifecycle Methods + + +## Called after the entity is fully initialized and ready.[br] +## Override this method to perform additional setup after all components have been added. +func on_ready() -> void: + pass + + +## Called right before the entity is freed from memory.[br] +## Override this method to perform any necessary cleanup before the entity is destroyed. +func on_destroy() -> void: + pass + + +## Called when the entity is disabled.[br] +func on_disable() -> void: + pass + + +## Called when the entity is enabled.[br] +func on_enable() -> void: + pass + + +## Define the default components in code to use (Instead of in the editor)[br] +## This should return a list of components to add by default when the entity is created +func define_components() -> Array: + return [] + + +## INTERNAL: Called when entity.enabled changes to move entity between archetypes +func _on_enabled_changed(old_value: bool, new_value: bool) -> void: + # Only handle if entity is already in a world + if not ECS.world or not ECS.world.entity_to_archetype.has(self ): + return + + # OPTIMIZATION: Update bitset instead of moving between archetypes + # This eliminates the need for separate enabled/disabled archetypes + var archetype = ECS.world.entity_to_archetype[ self ] + archetype.update_entity_enabled_state(self , new_value) + + # Invalidate query cache since archetypes changed + ECS.world.cache_invalidated.emit() + +#endregion Lifecycle Methods diff --git a/addons/gecs/ecs/entity.gd.uid b/addons/gecs/ecs/entity.gd.uid new file mode 100644 index 0000000..59e124d --- /dev/null +++ b/addons/gecs/ecs/entity.gd.uid @@ -0,0 +1 @@ +uid://cl6glf45pcrns diff --git a/addons/gecs/ecs/observer.gd b/addons/gecs/ecs/observer.gd new file mode 100644 index 0000000..2658055 --- /dev/null +++ b/addons/gecs/ecs/observer.gd @@ -0,0 +1,74 @@ +## An Observer is like a system that reacts when specific component events happen +## It has a query that filters which entities are monitored for these events +## Observers can respond to component add/remove/change events on specific sets of entities +## +## [b]Important:[/b] For property changes to trigger [method on_component_changed], you must +## manually emit the [signal Component.property_changed] signal from within your component. +## Simply setting properties does not automatically trigger observers. +## +## [b]Example of triggering property changes:[/b] +## [codeblock] +## # In your component class +## class_name MyComponent +## extends Component +## +## @export var health: int = 100 : set = set_health +## +## func set_health(new_value: int): +## var old_value = health +## health = new_value +## # This is required for observers to detect the change +## property_changed.emit(self, "health", old_value, new_value) +## [/codeblock] +@icon("res://addons/gecs/assets/observer.svg") +class_name Observer +extends Node + +## The [QueryBuilder] object exposed for conveinence to use in the system and to create the query. +var q: QueryBuilder + + +## Override this method and return a [QueryBuilder] to define the required [Component]s the entity[br] +## must match for the observer to trigger. If empty this will match all [Entity]s +func match() -> QueryBuilder: + return q + + +## Override this method and provide a single component to watch for events.[br] +## This means that the observer will only react to events on this component (add/remove/change)[br] +## assuming the entity matches the query defined in the [method match] method +func watch() -> Resource: + assert(false, "You must override the watch() method in your system") + return + + +## Override this method to define the main processing function for the observer when a component is added to an [Entity].[br] +## [param entity] The [Entity] the component was added to.[br] +## [param component] The [Component] that was added. Guaranteed to be the component defined in [method watch].[br] +func on_component_added(entity: Entity, component: Resource) -> void: + pass + + +## Override this method to define the main processing function for the observer when a component is removed from an [Entity].[br] +## [param entity] The [Entity] the component was removed from.[br] +## [param component] The [Component] that was removed. Guaranteed to be the component defined in [method watch].[br] +func on_component_removed(entity: Entity, component: Resource) -> void: + pass + + +## Override this method to define the main processing function for property changes.[br] +## This method is called when a property changes on the watched component.[br] +## [br] +## [b]Note:[/b] This method only triggers when the component explicitly emits its +## [signal Component.property_changed] signal for performance reasons. Setting properties directly will +## [b]not[/b] automatically trigger this method.[br] +## [br] +## [param entity] The [Entity] the component that changed is attached to. +## [param component] The [Component] that changed. Guaranteed to be the component defined in [method watch]. +## [param property] The name of the property that changed on the [Component]. +## [param old_value] The old value of the property. +## [param new_value] The new value of the property. +func on_component_changed( + entity: Entity, component: Resource, property: String, new_value: Variant, old_value: Variant +) -> void: + pass diff --git a/addons/gecs/ecs/observer.gd.uid b/addons/gecs/ecs/observer.gd.uid new file mode 100644 index 0000000..50bb3df --- /dev/null +++ b/addons/gecs/ecs/observer.gd.uid @@ -0,0 +1 @@ +uid://dd3umv3f8qyx5 diff --git a/addons/gecs/ecs/query_builder.gd b/addons/gecs/ecs/query_builder.gd new file mode 100644 index 0000000..8949032 --- /dev/null +++ b/addons/gecs/ecs/query_builder.gd @@ -0,0 +1,571 @@ +## QueryBuilder[br] +## A utility class for constructing and executing queries to retrieve entities based on their components. +## +## The QueryBuilder supports filtering entities that have all, any, or exclude specific components, +## as well as filtering by enabled/disabled status using high-performance group indexing. +## [codeblock] +## var enabled_entities = ECS.world.query +## .with_all([Transform, Velocity]) +## .with_any([Health]) +## .with_none([Inactive]) +## .enabled(true) +## .execute() +## +## var disabled_entities = ECS.world.query.enabled(false).execute() +## var all_entities = ECS.world.query.enabled(null).execute() +##[/codeblock] +## This will efficiently query entities using indexed group lookups rather than +## filtering the entire entity list. +class_name QueryBuilder +extends RefCounted + +# The world instance to query against. +var _world: World +# Components that an entity must have all of. +var _all_components: Array = [] +# Components that an entity must have at least one of. +var _any_components: Array = [] +# Components that an entity must not have. +var _exclude_components: Array = [] +# Relationships that entities must have +var _relationships: Array = [] # (Retained for entity-level filtering only; NOT part of cache key) +var _exclude_relationships: Array = [] +# Components queries that an entity must match +var _all_components_queries: Array = [] +# Components queries that an entity must match for any components +var _any_components_queries: Array = [] +# Groups that an entity must be in +var _groups: Array = [] +# Groups that an entity must not be in +var _exclude_groups: Array = [] +# Enabled/disabled filter: true = enabled only, false = disabled only, null = all +var _enabled_filter = null +# Components to iterate in archetype mode (ordered array of component types) +var _iterate_components: Array = [] + +# Add fields for query result caching +var _cache_valid: bool = false +var _cached_result: Array = [] + +# OPTIMIZATION: Cache the query hash key to avoid recalculating FNV-1a hash every frame +var _cache_key: int = -1 +var _cache_key_valid: bool = false + + +## Initializes the QueryBuilder with the specified [param world] +func _init(world: World = null): + _world = world as World + + +## Allow setting the world after creation for editor time creation +func set_world(world: World): + _world = world + + +## Clears the query criteria, resetting all filters. Mostly used in testing +## [param returns] - The current instance of the QueryBuilder for chaining. +func clear(): + _all_components = [] + _any_components = [] + _exclude_components = [] + _relationships = [] + _exclude_relationships = [] + _all_components_queries = [] + _any_components_queries = [] + _groups = [] + _exclude_groups = [] + _enabled_filter = null + _iterate_components = [] + _cache_valid = false + _cache_key_valid = false + return self + + +## Finds entities with all of the provided components.[br] +## [param components] An [Array] of [Component] classes.[br] +## [param returns]: [QueryBuilder] instance for chaining. +func with_all(components: Array = []) -> QueryBuilder: + var processed = ComponentQueryMatcher.process_component_list(components) + _all_components = processed.components + _all_components_queries = processed.queries + _cache_valid = false + _cache_key_valid = false + return self + + +## Entities must have at least one of the provided components.[br] +## [param components] An [Array] of [Component] classes.[br] +## [param reutrns] [QueryBuilder] instance for chaining. +func with_any(components: Array = []) -> QueryBuilder: + var processed = ComponentQueryMatcher.process_component_list(components) + _any_components = processed.components + _any_components_queries = processed.queries + _cache_valid = false + _cache_key_valid = false + return self + + +## Entities must not have any of the provided components.[br] +## Params: [param components] An [Array] of [Component] classes.[br] +## [param reutrns] [QueryBuilder] instance for chaining. +func with_none(components: Array = []) -> QueryBuilder: + # Don't process queries for with_none, just take the components directly + _exclude_components = components.map( + func(comp): return comp if not comp is Dictionary else comp.keys()[0] + ) + _cache_valid = false + _cache_key_valid = false + return self + + +## Finds entities with specific relationships using weak matching by default (component type and queries). +## [br][b]Weak Matching (default):[/b] Components match by type and component queries are evaluated. +## [br]For strong matching (exact component data), use [method Entity.has_relationship] with [code]weak=false[/code]. +func with_relationship(relationships: Array = []) -> QueryBuilder: + _relationships = relationships + _cache_valid = false + # Cache key unaffected by relationships (structural only) + return self + + +## Entities must not have any of the provided relationships using weak matching by default (component type and queries). +## [br][b]Weak Matching (default):[/b] Components match by type and component queries are evaluated. +## [br]For strong matching (exact component data), use [method Entity.has_relationship] with [code]weak=false[/code]. +func without_relationship(relationships: Array = []) -> QueryBuilder: + _exclude_relationships = relationships + _cache_valid = false + return self + + +## Query for entities that are targets of specific relationships +func with_reverse_relationship(relationships: Array = []) -> QueryBuilder: + for rel in relationships: + if rel.relation != null: + var rev_key = "reverse_" + rel.relation.get_script().resource_path + if _world.reverse_relationship_index.has(rev_key): + return self.with_all(_world.reverse_relationship_index[rev_key]) + _cache_valid = false + return self + + +## Finds entities with specific groups. +func with_group(groups: Array[String] = []) -> QueryBuilder: + _groups.append_array(groups) + _cache_valid = false + _cache_key_valid = false + return self + + +## Entities must not have any of the provided groups. +func without_group(groups: Array[String] = []) -> QueryBuilder: + _exclude_groups.append_array(groups) + _cache_valid = false + _cache_key_valid = false + return self + + +## Filter to only enabled entities using internal arrays for optimal performance.[br] +## [param returns] [QueryBuilder] instance for chaining. +func enabled() -> QueryBuilder: + _enabled_filter = true + _cache_valid = false + _cache_key_valid = false + return self + + +## Filter to only disabled entities using internal arrays for optimal performance.[br] +## [param returns] [QueryBuilder] instance for chaining. +func disabled() -> QueryBuilder: + _enabled_filter = false + _cache_valid = false + _cache_key_valid = false + return self + + +## Specifies the component order for batch processing iteration.[br] +## This determines the order of component arrays passed to System.process_batch()[br] +## [param components] An array of component types in the desired iteration order[br] +## [param returns] [QueryBuilder] instance for chaining.[br][br] +## [b]Example:[/b] +## [codeblock] +## func query() -> QueryBuilder: +## return q.with_all([C_Velocity, C_Timer]).enabled().iterate([C_Velocity, C_Timer]) +## +## func process_batch(entities: Array[Entity], components: Array, delta: float) -> void: +## var velocities = components[0] # C_Velocity (first in iterate) +## var timers = components[1] # C_Timer (second in iterate) +## [/codeblock] +func iterate(components: Array) -> QueryBuilder: + _iterate_components = components + return self + + +func execute_one() -> Entity: + # Execute the query and return the first matching entity + var result = execute() + if result.size() > 0: + return result[0] + return null + + +## Executes the constructed query and retrieves matching entities.[br] +## [param returns] - An [Array] of [Entity] that match the query criteria. +func execute() -> Array: + # For relationship or group filters we need fresh filtering every call (no stale cached filtered result) + var uses_relationship_filters := (not _relationships.is_empty() or not _exclude_relationships.is_empty()) + var uses_group_filters := (not _groups.is_empty() or not _exclude_groups.is_empty()) + + var structural_result: Array + if _cache_valid and not uses_relationship_filters and not uses_group_filters: + # Safe to reuse full cached result only for purely structural component queries + structural_result = _cached_result + else: + # Recompute base structural/group result (without relationship filtering caching) + structural_result = _internal_execute() + # Only cache if no dynamic relationship/group filters are present + if not uses_relationship_filters and not uses_group_filters: + _cached_result = structural_result + _cache_valid = true + else: + _cache_valid = false # force recompute next call + + var result = structural_result + # Apply component property queries (post structural) + if not _all_components_queries.is_empty() and _has_actual_queries(_all_components_queries): + result = _filter_entities_by_queries(result, _all_components, _all_components_queries, true) + if not _any_components_queries.is_empty() and _has_actual_queries(_any_components_queries): + result = _filter_entities_by_queries(result, _any_components, _any_components_queries, false) + + return result + + +func _internal_execute() -> Array: + # If we have groups or exclude groups, gather entities from those groups + if not _groups.is_empty() or not _exclude_groups.is_empty(): + var entities_in_group = [] + + # Use Godot's optimized get_nodes_in_group() instead of filtering + if not _groups.is_empty(): + # For multiple groups, use set operations for efficiency + var group_set: Set + + for i in range(_groups.size()): + var group_name = _groups[i] + var nodes_in_group = _world.get_tree().get_nodes_in_group(group_name) + + # Filter to only Entity nodes + var entities_in_this_group = nodes_in_group.filter(func(n): return n is Entity) + + if i == 0: + # First group - start with these entities + group_set = Set.new(entities_in_this_group) + else: + # Subsequent groups - intersect (entity must be in ALL groups) + group_set = group_set.intersect(Set.new(entities_in_this_group)) + + entities_in_group = group_set.to_array() if group_set else [] + else: + # If no required groups but we have exclude_groups, start with ALL entities from component query + # This handles the case of "without_group" queries + entities_in_group = ( + _world._query(_all_components, _any_components, _exclude_components, _enabled_filter, get_cache_key()) as Array[Entity] + ) + + # Filter out entities in excluded groups + if not _exclude_groups.is_empty(): + var exclude_set = Set.new() + for group_name in _exclude_groups: + var nodes_in_group = _world.get_tree().get_nodes_in_group(group_name) + var entities_in_excluded = nodes_in_group.filter(func(n): return n is Entity) + exclude_set = exclude_set.union(Set.new(entities_in_excluded)) + + # Remove excluded entities + var result_set = Set.new(entities_in_group) + entities_in_group = result_set.difference(exclude_set).to_array() + + # match the entities in the group with the query + return matches(entities_in_group) + + # Otherwise, query the world with enabled filter for optimal performance + # OPTIMIZATION: Pass pre-calculated cache key to avoid rehashing + var result = ( + _world._query(_all_components, _any_components, _exclude_components, _enabled_filter, get_cache_key()) as Array[Entity] + ) + + # Handle relationship filtering + if not _relationships.is_empty() or not _exclude_relationships.is_empty(): + var filtered_entities: Array = [] + for entity in result: + var matches = true + # Required relationships + for relationship in _relationships: + if not entity.has_relationship(relationship): + matches = false + break + # Excluded relationships + if matches: + for ex_relationship in _exclude_relationships: + if entity.has_relationship(ex_relationship): + matches = false + break + if matches: + filtered_entities.append(entity) + result = filtered_entities + + # Return the structural query result (caching handled in execute()) + # Note: enabled/disabled filtering is now handled in World._query for optimal performance + return result + + +## Check if any query in the array has actual property filters (not just empty {}) +func _has_actual_queries(queries: Array) -> bool: + for query in queries: + if not query.is_empty(): + return true + return false + + +## Filter entities based on component queries +func _filter_entities_by_queries( + entities: Array, components: Array, queries: Array, require_all: bool +) -> Array: + var filtered = [] + for entity in entities: + if entity == null: + continue + if require_all: + # Must match all queries + var matches = true + for i in range(components.size()): + var component = entity.get_component(components[i]) + var query = queries[i] + if not ComponentQueryMatcher.matches_query(component, query): + matches = false + break + if matches: + filtered.append(entity) + else: + # Must match any query + for i in range(components.size()): + var component = entity.get_component(components[i]) + var query = queries[i] + if component and ComponentQueryMatcher.matches_query(component, query): + filtered.append(entity) + break + return filtered + + +## Check if entity matches any of the queries +func _entity_matches_any_query(entity: Entity, components: Array, queries: Array) -> bool: + for i in range(components.size()): + var component = entity.get_component(components[i]) + if component and ComponentQueryMatcher.matches_query(component, queries[i]): + return true + return false + + +## Filters a provided list of entities using the current query criteria.[br] +## Unlike execute(), this doesn't query the world but instead filters the provided entities.[br][br] +## [param entities] Array of entities to filter[br] +## [param returns] Array of entities that match the query criteria[br] +func matches(entities: Array) -> Array: + # if the query is empty all entities match + if is_empty(): + return entities + var result = [] + + for entity in entities: + # If it's null skip it + if entity == null: + continue + assert(entity is Entity, "Must be an entity") + var matches = true + + # Check all required components + for component in _all_components: + if not entity.has_component(component): + matches = false + break + + # If still matching and we have any_components, check those + if matches and not _any_components.is_empty(): + matches = false + for component in _any_components: + if entity.has_component(component): + matches = true + break + + # Check excluded components + if matches: + for component in _exclude_components: + if entity.has_component(component): + matches = false + break + + # Check required relationships + if matches and not _relationships.is_empty(): + for relationship in _relationships: + if not entity.has_relationship(relationship): + matches = false + break + + # Check excluded relationships + if matches and not _exclude_relationships.is_empty(): + for relationship in _exclude_relationships: + if entity.has_relationship(relationship): + matches = false + break + + if matches: + result.append(entity) + + return result + + +func combine(other: QueryBuilder) -> QueryBuilder: + _all_components += other._all_components + _all_components_queries += other._all_components_queries + _any_components += other._any_components + _any_components_queries += other._any_components_queries + _exclude_components += other._exclude_components + _relationships += other._relationships + _exclude_relationships += other._exclude_relationships + _groups += other._groups + _exclude_groups += other._exclude_groups + _cache_valid = false + return self + + +func as_array() -> Array: + return [ + _all_components, + _any_components, + _exclude_components, + _relationships, + _exclude_relationships + ] + + +func is_empty() -> bool: + return ( + _all_components.is_empty() + and _any_components.is_empty() + and _exclude_components.is_empty() + and _relationships.is_empty() + and _exclude_relationships.is_empty() + ) + + +func _to_string() -> String: + var parts = [] + + if not _all_components.is_empty(): + parts.append("with_all(" + _format_components(_all_components) + ")") + + if not _any_components.is_empty(): + parts.append("with_any(" + _format_components(_any_components) + ")") + + if not _exclude_components.is_empty(): + parts.append("with_none(" + _format_components(_exclude_components) + ")") + + if not _relationships.is_empty(): + parts.append("with_relationship(" + _format_relationships(_relationships) + ")") + + if not _exclude_relationships.is_empty(): + parts.append("without_relationship(" + _format_relationships(_exclude_relationships) + ")") + + if not _groups.is_empty(): + parts.append("with_group(" + str(_groups) + ")") + + if not _exclude_groups.is_empty(): + parts.append("without_group(" + str(_exclude_groups) + ")") + + if _enabled_filter != null: + if _enabled_filter: + parts.append("enabled()") + else: + parts.append("disabled()") + + if not _all_components_queries.is_empty(): + parts.append("component_queries(" + _format_component_queries(_all_components_queries) + ")") + + if not _any_components_queries.is_empty(): + parts.append("any_component_queries(" + _format_component_queries(_any_components_queries) + ")") + + if parts.is_empty(): + return "ECS.world.query" + + return "ECS.world.query." + ".".join(parts) + + +func _format_components(components: Array) -> String: + var names = [] + for component in components: + if component is Script: + names.append(component.get_global_name()) + else: + names.append(str(component)) + return "[" + ", ".join(names) + "]" + + +func _format_relationships(relationships: Array) -> String: + var names = [] + for relationship in relationships: + if relationship.has_method("to_string"): + names.append(relationship.to_string()) + else: + names.append(str(relationship)) + return "[" + ", ".join(names) + "]" + + +func _format_component_queries(queries: Array) -> String: + var formatted = [] + for query in queries: + if query.has_method("to_string"): + formatted.append(query.to_string()) + else: + formatted.append(str(query)) + return "[" + ", ".join(formatted) + "]" + + +func compile(query: String) -> QueryBuilder: + return QueryBuilder.new(_world) + + +func invalidate_cache(): + _cache_valid = false + _cache_key_valid = false + + +## Called when a relationship is added or removed (only for queries using relationships) +## Relationship changes do NOT affect structural cache key; queries only re-filter at execute time +func _on_relationship_changed(_entity: Entity, _relationship: Relationship): + _cache_valid = false # only result cache + + +## Get the cached query hash key, calculating it only once +## OPTIMIZATION: Avoids recalculating FNV-1a hash every frame in hot path queries +func get_cache_key() -> int: + # Structural cache key excludes relationships/groups (matches 6.0.0 behavior) + if not _cache_key_valid: + if _world: + _cache_key = QueryCacheKey.build(_all_components, _any_components, _exclude_components) + _cache_key_valid = true + else: + return -1 + return _cache_key + + +## Get matching archetypes directly for column-based iteration +## OPTIMIZATION: Skip entity flattening, return archetypes directly for cache-friendly processing +## [br][br] +## [b]Example:[/b] +## [codeblock] +## func process_all(entities: Array, delta: float): +## for archetype in query().archetypes(): +## var transforms = archetype.get_column(transform_path) +## for i in range(transforms.size()): +## # Process transform directly from packed array +## [/codeblock] +func archetypes() -> Array[Archetype]: + return _world.get_matching_archetypes(self ) diff --git a/addons/gecs/ecs/query_builder.gd.uid b/addons/gecs/ecs/query_builder.gd.uid new file mode 100644 index 0000000..9cb15c1 --- /dev/null +++ b/addons/gecs/ecs/query_builder.gd.uid @@ -0,0 +1 @@ +uid://dhyy752meflri diff --git a/addons/gecs/ecs/query_cache_key.gd b/addons/gecs/ecs/query_cache_key.gd new file mode 100644 index 0000000..27ac9d7 --- /dev/null +++ b/addons/gecs/ecs/query_cache_key.gd @@ -0,0 +1,184 @@ +## QueryCacheKey +## ------------------------------------------------------------------------------ +## PURPOSE +## Build a structural query signature (cache key) that is: +## * Order-insensitive inside each domain (with_all / with_any / with_none) +## * Order-sensitive ACROSS domains (the same component in different domains => different key) +## * Extremely fast (single allocation + contiguous integer writes) +## * Stable for the lifetime of loaded component scripts (uses script.instance_id) +## +## WHY NOT JUST MERGE & SORT? +## A naive approach merges all component IDs + domain markers then sorts. That destroys +## domain boundaries and lets these collide: +## with_all([A,B]) vs with_any([A,B]) +## After a full sort both become the same multiset {1,2,3,A,B}. We prevent that by +## emitting DOMAIN MARKER then COUNT then the sorted IDs for that domain – preserving +## domain structure while still being permutation-insensitive within the domain. +## +## LAYOUT (integers in final array): +## [ 1, |count_all|, sorted(all_ids)..., +## 2, |count_any|, sorted(any_ids)..., +## 3, |count_none|, sorted(ex_ids)... ] +## 1/2/3 : domain sentinels (ALL / ANY / NONE) +## count_* : disambiguates empty vs non-empty ( [] vs [X] ) and prevents boundary ambiguity +## sorted(ids) : order-insensitivity; identical sets different order => same run of ints +## +## COMPLEXITY +## Sorting dominates: O(a log a + y log y + n log n). Typical domain sizes are tiny. +## Allocation: exactly one integer array sized to final layout. +## Hash: Godot's native Array.hash() (64-bit) – very fast. +## +## COLLISION PROFILE +## 64-bit space (~1.84e19). Even 1,000,000 distinct structural queries => ~2.7e-8 collision probability. +## Practically zero for real ECS usage. See PERFORMANCE_CACHE_KEY_NOTE.md for math. +## +## EXTENSION POINTS +## * Add a leading VERSION marker if the format evolves. +## * Add extra domains (e.g. relationship structure) by appending new marker + count + IDs. +## * Add enabled-state separation by injecting a synthetic domain marker (kept separate currently). +## +## INLINE COMMENT LEGEND +## all_ids / any_ids / ex_ids : per-domain sorted component script instance IDs +## total : exact integer count used for one-shot allocation (prevents incremental reallocation) +## layout[i] = marker/count/id : sequential write building final signature array +## +class_name QueryCacheKey +extends RefCounted + +static func build( + all_components: Array, + any_components: Array, + exclude_components: Array, + relationships: Array = [], + exclude_relationships: Array = [], + groups: Array = [], + exclude_groups: Array = [] +) -> int: + # Collect & sort per-domain IDs (order-insensitive inside each domain) + var all_ids: Array[int] = [] + for c in all_components: all_ids.append(c.get_instance_id()) + all_ids.sort() + var any_ids: Array[int] = [] + for c in any_components: any_ids.append(c.get_instance_id()) + any_ids.sort() + var ex_ids: Array[int] = [] + for c in exclude_components: ex_ids.append(c.get_instance_id()) + ex_ids.sort() + + # Collect & sort relationship IDs + var rel_ids: Array[int] = [] + for rel in relationships: + # Use Script instance ID for type matching (consistent with component queries) + # Relationship.new(C_TestB.new()) creates component instance, we want the Script's ID + if rel.relation: + rel_ids.append(rel.relation.get_script().get_instance_id()) + else: + rel_ids.append(0) + + # Handle target - use Script instance ID for Components (type matching) + if rel.target is Component: + # Component target: use Script instance ID for type matching + rel_ids.append(rel.target.get_script().get_instance_id()) + elif rel.target is Entity: + # Entity target: use entity instance ID (entities are specific instances) + rel_ids.append(rel.target.get_instance_id()) + elif rel.target is Script: + # Archetype target: use Script instance ID + rel_ids.append(rel.target.get_instance_id()) + elif rel.target != null: + # Other types: use generic hash + rel_ids.append(rel.target.hash()) + else: + rel_ids.append(0) # null target + rel_ids.sort() + + var ex_rel_ids: Array[int] = [] + for rel in exclude_relationships: + # Use Script instance ID for type matching (consistent with component queries) + if rel.relation: + ex_rel_ids.append(rel.relation.get_script().get_instance_id()) + else: + ex_rel_ids.append(0) + + # Handle target - use Script instance ID for Components (type matching) + if rel.target is Component: + ex_rel_ids.append(rel.target.get_script().get_instance_id()) + elif rel.target is Entity: + ex_rel_ids.append(rel.target.get_instance_id()) + elif rel.target is Script: + ex_rel_ids.append(rel.target.get_instance_id()) + elif rel.target != null: + ex_rel_ids.append(rel.target.hash()) + else: + ex_rel_ids.append(0) + ex_rel_ids.sort() + + # Collect & sort group name hashes + var group_ids: Array[int] = [] + for group_name in groups: + group_ids.append(group_name.hash()) + group_ids.sort() + + var ex_group_ids: Array[int] = [] + for group_name in exclude_groups: + ex_group_ids.append(group_name.hash()) + ex_group_ids.sort() + + # Compute exact total length: (marker + count) per domain + IDs + var total = 1 + 1 + all_ids.size() # ALL marker + count + ids + total += 1 + 1 + any_ids.size() # ANY marker + count + ids + total += 1 + 1 + ex_ids.size() # NONE marker + count + ids + total += 1 + 1 + rel_ids.size() # RELATIONSHIPS marker + count + ids + total += 1 + 1 + ex_rel_ids.size() # EXCLUDE_RELATIONSHIPS marker + count + ids + total += 1 + 1 + group_ids.size() # GROUPS marker + count + ids + total += 1 + 1 + ex_group_ids.size() # EXCLUDE_GROUPS marker + count + ids + + # Single allocation for final signature layout + var layout: Array[int] = [] + layout.resize(total) + + var i := 0 + # --- Domain: ALL --- + layout[i] = 1; i += 1 # Marker for ALL domain + layout[i] = all_ids.size(); i += 1 # Count (disambiguates empty vs non-empty) + for id in all_ids: + layout[i] = id; i += 1 # Sorted ALL component IDs + + # --- Domain: ANY --- + layout[i] = 2; i += 1 # Marker for ANY domain + layout[i] = any_ids.size(); i += 1 # Count + for id in any_ids: + layout[i] = id; i += 1 # Sorted ANY component IDs + + # --- Domain: NONE (exclude) --- + layout[i] = 3; i += 1 # Marker for NONE domain + layout[i] = ex_ids.size(); i += 1 # Count + for id in ex_ids: + layout[i] = id; i += 1 # Sorted EXCLUDE component IDs + + # --- Domain: RELATIONSHIPS --- + layout[i] = 4; i += 1 # Marker for RELATIONSHIPS domain + layout[i] = rel_ids.size(); i += 1 # Count + for id in rel_ids: + layout[i] = id; i += 1 # Sorted relationship IDs + + # --- Domain: EXCLUDE_RELATIONSHIPS --- + layout[i] = 5; i += 1 # Marker for EXCLUDE_RELATIONSHIPS domain + layout[i] = ex_rel_ids.size(); i += 1 # Count + for id in ex_rel_ids: + layout[i] = id; i += 1 # Sorted exclude relationship IDs + + # --- Domain: GROUPS --- + layout[i] = 6; i += 1 # Marker for GROUPS domain + layout[i] = group_ids.size(); i += 1 # Count + for id in group_ids: + layout[i] = id; i += 1 # Sorted group name hashes + + # --- Domain: EXCLUDE_GROUPS --- + layout[i] = 7; i += 1 # Marker for EXCLUDE_GROUPS domain + layout[i] = ex_group_ids.size(); i += 1 # Count + for id in ex_group_ids: + layout[i] = id; i += 1 # Sorted exclude group name hashes + + # Hash the structural layout -> 64-bit key + return layout.hash() diff --git a/addons/gecs/ecs/query_cache_key.gd.uid b/addons/gecs/ecs/query_cache_key.gd.uid new file mode 100644 index 0000000..fc08672 --- /dev/null +++ b/addons/gecs/ecs/query_cache_key.gd.uid @@ -0,0 +1 @@ +uid://rjjelegj3npr diff --git a/addons/gecs/ecs/relationship.gd b/addons/gecs/ecs/relationship.gd new file mode 100644 index 0000000..b2ceb60 --- /dev/null +++ b/addons/gecs/ecs/relationship.gd @@ -0,0 +1,294 @@ +## Relationship +## Represents a relationship between entities in the ECS framework. +## A relationship consists of a [Component] relation and a target, which can be an [Entity], a [Component], or an archetype. +## +## Relationships are used to link entities together, allowing for complex queries and interactions. +## They enable entities to have dynamic associations that can be queried and manipulated at runtime. +## The powerful relationship system supports component-based targets for hierarchical type systems. +## +## [b]Relationship Types:[/b] +## [br]• [b]Entity Relationships:[/b] Link entities to other entities +## [br]• [b]Component Relationships:[/b] Link entities to component instances for type hierarchies +## [br]• [b]Archetype Relationships:[/b] Link entities to component/entity classes +## +## [b]Query Features:[/b] +## [br]• [b]Type Matching:[/b] Find entities by relationship component type (default) +## [br]• [b]Query Matching:[/b] Use dictionaries to match by specific property criteria +## [br]• [b]Wildcard Queries:[/b] Use [code]null[/code] targets to find any relationship of a type +## +## [b]Basic Entity Relationship Example:[/b] +## [codeblock] +## # Create a 'likes' relationship where e_bob likes e_alice +## var likes_relationship = Relationship.new(C_Likes.new(), e_alice) +## e_bob.add_relationship(likes_relationship) +## +## # Check if e_bob has a 'likes' relationship with e_alice +## if e_bob.has_relationship(Relationship.new(C_Likes.new(), e_alice)): +## print("Bob likes Alice!") +## [/codeblock] +## +## [b]Component-Based Relationship Example:[/b] +## [codeblock] +## # Create a damage type hierarchy using components as targets +## var fire_damage = C_FireDamage.new(50) +## var poison_damage = C_PoisonDamage.new(25) +## +## # Entity has different types of damage +## entity.add_relationship(Relationship.new(C_Damaged.new(), fire_damage)) +## entity.add_relationship(Relationship.new(C_Damaged.new(), poison_damage)) +## +## # Query for entities with any damage type (wildcard) +## var damaged_entities = ECS.world.query.with_relationship([ +## Relationship.new(C_Damaged.new(), null) +## ]).execute() +## +## # Query for entities with fire damage amount >= 50 using component query +## var fire_damaged = ECS.world.query.with_relationship([ +## Relationship.new(C_Damaged.new(), {C_FireDamage: {'amount': {"_gte": 50}}}) +## ]).execute() +## +## # Check if entity has any fire damage (type matching) +## var has_fire_damage = entity.has_relationship( +## Relationship.new(C_Damaged.new(), C_FireDamage.new()) +## ) +## [/codeblock] +## +## [b]Component Query Examples:[/b] +## [codeblock] +## # Query relation by property value +## var entities = ECS.world.query.with_relationship([ +## Relationship.new({C_Eats: {'value': {"_eq": 8}}}, e_apple) +## ]).execute() +## +## # Query target by property value +## var entities = ECS.world.query.with_relationship([ +## Relationship.new(C_Damage.new(), {C_Health: {'amount': {"_gte": 50}}}) +## ]).execute() +## +## # Query both relation AND target +## var entities = ECS.world.query.with_relationship([ +## Relationship.new( +## {C_Buff: {'duration': {"_gt": 10}}}, +## {C_Player: {'level': {"_gte": 5}}} +## ) +## ]).execute() +## [/codeblock] +class_name Relationship +extends Resource + +## The relation component of the relationship. +## This defines the type of relationship and can contain additional data. +var relation + +## The target of the relationship. +## This can be an [Entity], a [Component], an archetype, or null. +var target + +## The source of the relationship. +var source + +## Component query for relation matching (if relation was created from dictionary) +var relation_query: Dictionary = {} + +## Component query for target matching (if target was created from dictionary) +var target_query: Dictionary = {} + +## Flag to track if this relationship was created from a component query dictionary (private - used for validation) +var _is_query_relationship: bool = false + + +func _init(_relation = null, _target = null): + # Handle component queries (dictionaries) for relation + if _relation is Dictionary: + _is_query_relationship = true + # Extract component type and query from dictionary + for component_type in _relation: + var query = _relation[component_type] + # Store the query and create component instance + relation_query = query + _relation = component_type.new() + break + + # Handle component queries (dictionaries) for target + if _target is Dictionary: + _is_query_relationship = true + # Extract component type and query from dictionary + for component_type in _target: + var query = _target[component_type] + # Store the query and create component instance + target_query = query + _target = component_type.new() + break + + # Assert for class reference vs instance for relation (skip for dictionaries) + if not _relation is Dictionary: + assert( + not (_relation != null and (_relation is GDScript or _relation is Script)), + "Relation must be an instance of Component (did you forget to call .new()?)" + ) + + # Assert for relation type + assert( + _relation == null or _relation is Component, "Relation must be null or a Component instance" + ) + + # Assert for class reference vs instance for target (skip for dictionaries) + if not _target is Dictionary: + assert( + not (_target != null and _target is GDScript and _target is Component), + "Target must be an instance of Component (did you forget to call .new()?)" + ) + + # Assert for target type + assert( + _target == null or _target is Entity or _target is Script or _target is Component, + "Target must be null, an Entity instance, a Script archetype, or a Component instance" + ) + + relation = _relation + target = _target + + +## Checks if this relationship matches another relationship. +## [param other]: The [Relationship] to compare with. +## [return]: `true` if both the relation and target match, `false` otherwise. +## +## [b]Matching Modes:[/b] +## [br]• [b]Type Matching:[/b] Components match by type (default behavior) +## [br]• [b]Query Matching:[/b] If component query dictionary used, evaluates property criteria +## [br]• [b]Wildcard Matching:[/b] [code]null[/code] relations or targets act as wildcards and match anything +func matches(other: Relationship) -> bool: + var rel_match = false + var target_match = false + + # Compare relations + if other.relation == null or relation == null: + # If either relation is null, consider it a match (wildcard) + rel_match = true + else: + # Check if other relation has component query (query relationships) + if not other.relation_query.is_empty(): + # Other has component query, check if this relation matches that query + if relation.get_script() == other.relation.get_script(): + rel_match = ComponentQueryMatcher.matches_query(relation, other.relation_query) + else: + rel_match = false + # Check if this relation has component query (this is query relationship) + elif not relation_query.is_empty(): + # This has component query, check if other relation matches this query + if relation.get_script() == other.relation.get_script(): + rel_match = ComponentQueryMatcher.matches_query(other.relation, relation_query) + else: + rel_match = false + else: + # Standard type matching by script type + rel_match = relation.get_script() == other.relation.get_script() + + # Compare targets + if other.target == null or target == null: + # If either target is null, consider it a match (wildcard) + target_match = true + else: + if target == other.target: + target_match = true + elif target is Entity and other.target is Script: + # target is an entity instance, other.target is an archetype + target_match = target.get_script() == other.target + elif target is Script and other.target is Entity: + # target is an archetype, other.target is an entity instance + target_match = other.target.get_script() == target + elif target is Entity and other.target is Entity: + # Both targets are entities; compare references directly + target_match = target == other.target + elif target is Script and other.target is Script: + # Both targets are archetypes; compare directly + target_match = target == other.target + elif target is Component and other.target is Component: + # Both targets are components; check for query or type matching + # Check if other target has component query + if not other.target_query.is_empty(): + # Other has component query, check if this target matches that query + if target.get_script() == other.target.get_script(): + target_match = ComponentQueryMatcher.matches_query(target, other.target_query) + else: + target_match = false + # Check if this target has component query + elif not target_query.is_empty(): + # This has component query, check if other target matches this query + if target.get_script() == other.target.get_script(): + target_match = ComponentQueryMatcher.matches_query(other.target, target_query) + else: + target_match = false + else: + # Standard type matching by script type + target_match = target.get_script() == other.target.get_script() + elif target is Component and other.target is Script: + # target is component instance, other.target is component archetype + target_match = target.get_script() == other.target + elif target is Script and other.target is Component: + # target is component archetype, other.target is component instance + target_match = other.target.get_script() == target + else: + # Unable to compare targets + target_match = false + + return rel_match and target_match + + +func valid() -> bool: + # make sure the target is valid or null + var target_valid = false + if target == null: + target_valid = true + elif target is Entity: + target_valid = is_instance_valid(target) + elif target is Component: + # Components are Resources, so they're always valid once created + target_valid = true + elif target is Script: + # Script archetypes are always valid + target_valid = true + else: + target_valid = false + + # Ensure the source is a valid Entity instance; it cannot be null + var source_valid = is_instance_valid(source) + + return target_valid and source_valid + + +## Provides a consistent string representation for cache keys and debugging. +## Two relationships with the same relation type and target should produce identical strings. +func _to_string() -> String: + var parts = [] + + # Format relation component + if relation == null: + parts.append("null") + elif not relation_query.is_empty(): + # This is a query relationship - include the query criteria + parts.append(relation.get_script().resource_path + str(relation_query)) + else: + # Standard relation - just the type + parts.append(relation.get_script().resource_path) + + # Format target + if target == null: + parts.append("null") + elif target is Entity: + # Use instance_id for stability - entity ID may not be set yet + parts.append("Entity#" + str(target.get_instance_id())) + elif target is Component: + if not target_query.is_empty(): + # Component with query + parts.append(target.get_script().resource_path + str(target_query)) + else: + # Type matching - use Script instance ID (consistent with query caching) + parts.append(target.get_script().resource_path + "#" + str(target.get_script().get_instance_id())) + elif target is Script: + # Archetype target + parts.append("Archetype:" + target.resource_path) + else: + parts.append(str(target)) + + return "Relationship(" + parts[0] + " -> " + parts[1] + ")" diff --git a/addons/gecs/ecs/relationship.gd.uid b/addons/gecs/ecs/relationship.gd.uid new file mode 100644 index 0000000..a6fdfda --- /dev/null +++ b/addons/gecs/ecs/relationship.gd.uid @@ -0,0 +1 @@ +uid://bsyujqr14xkrv diff --git a/addons/gecs/ecs/system.gd b/addons/gecs/ecs/system.gd new file mode 100644 index 0000000..01c35e8 --- /dev/null +++ b/addons/gecs/ecs/system.gd @@ -0,0 +1,459 @@ +## System[br] +## +## The base class for all systems within the ECS framework.[br] +## +## Systems contain the core logic and behavior, processing [Entity]s that have specific [Component]s.[br] +## Each system overrides the [method System.query] and returns a query using [code]q[/code] or [code]ECS.world.query[/code][br] +## to define the required [Component]s for it to process [Entity]s and implements the [method System.process] method.[br][br] +## [b]Example (Simple):[/b] +##[codeblock] +## class_name MovementSystem +## extends System +## +## func query(): +## return q.with_all([Transform, Velocity]) +## +## func process(entities: Array[Entity], components: Array, delta: float) -> void: +## # Per-entity processing (simple but slower) +## for entity in entities: +## var transform = entity.get_component(Transform) +## var velocity = entity.get_component(Velocity) +## transform.position += velocity.direction * velocity.speed * delta +##[/codeblock] +## [b]Example (Optimized with iterate()):[/b] +##[codeblock] +## func query(): +## return q.with_all([Transform, Velocity]).iterate([Transform, Velocity]) +## +## func process(entities: Array[Entity], components: Array, delta: float) -> void: +## # Batch processing with component arrays (faster) +## var transforms = components[0] +## var velocities = components[1] +## for i in entities.size(): +## transforms[i].position += velocities[i].velocity * delta +##[/codeblock] +@icon("res://addons/gecs/assets/system.svg") +class_name System +extends Node + +#region Enums +## These control when the system should run in relation to other systems. +enum Runs { + ## This system should run before all the systems defined in the array ex: [TransformSystem] means it will run before the [TransformSystem] system runs + Before, + ## This system should run after all the systems defined in the array ex: [TransformSystem] means it will run after the [TransformSystem] system runs + After, +} + +#endregion Enums + +#region Exported Variables +## What group this system belongs to. Systems can be organized and run by group +@export var group: String = "" +## Determines whether the system should run even when there are no [Entity]s to process. +@export var process_empty := false +## Is this system active. (Will be skipped if false) +@export var active := true + +@export_group("Parallel Processing") +## Enable parallel processing for this system's entities (No access to scene tree in process method) +@export var parallel_processing := false +## Minimum entities required to use parallel processing (performance threshold) +@export var parallel_threshold := 50 + +#endregion Exported Variables + +#region Public Variables +## Is this system paused. (Will be skipped if true) +var paused := false + +## Logger for system debugging and tracing +var systemLogger = GECSLogger.new().domain("System") +## Data for debugger and profiling - you can add ANY arbitrary data here when ECS.debug is enabled +## All keys and values will automatically appear in the GECS debugger tab +## Example: +## if ECS.debug: +## lastRunData["my_counter"] = 123 +## lastRunData["player_stats"] = {"health": 100, "mana": 50} +## lastRunData["events"] = ["event1", "event2"] +var lastRunData := {} + +## Reference to the world this system belongs to (set by World.add_system) +var _world: World = null +## Convenience property for accessing query builder (returns _world.query or ECS.world.query) +var q: QueryBuilder: + get: + return _world.query if _world else ECS.world.query +## Cached query to avoid recreating it every frame (lazily initialized) +var _query_cache: QueryBuilder = null +## Cached component paths for iterate() fast path (6.0.0 style) +var _component_paths: Array[String] = [] +## Cached subsystems array (6.0.0 style) +var _subsystems_cache: Array = [] + +#endregion Public Variables + + +#region Public Methods +## Override this method to define the [System]s that this system depends on.[br] +## If not overridden the system will run based on the order of the systems in the [World][br] +## and the order of the systems in the [World] will be based on the order they were added to the [World].[br] +func deps() -> Dictionary[int, Array]: + return { + Runs.After: [], + Runs.Before: [], + } + + +## Override this method and return a [QueryBuilder] to define the required [Component]s for the system.[br] +## If not overridden, the system will run on every update with no entities.[br][br] +## You can use [code]q[/code] or [code]ECS.world.query[/code] - both are equivalent. +func query() -> QueryBuilder: + process_empty = true + return _world.query if _world else ECS.world.query + + +## Override this method to define any sub-systems that should be processed by this system.[br] +## Each subsystem is defined as [QueryBuilder, Callable][br] +## Return empty array if not using subsystems (base implementation)[br][br] +## You can use [code]q[/code] or [code]ECS.world.query[/code] in subsystems - both work.[br][br] +## [b]Example:[/b] +## [codeblock] +## func sub_systems() -> Array[Array]: +## return [ +## [q.with_all([C_Velocity]).iterate([C_Velocity]), process_velocity], +## [q.with_all([C_Health]), process_health] +## ] +## +## func process_velocity(entities: Array[Entity], components: Array, delta: float): +## var velocities = components[0] +## for i in entities.size(): +## entities[i].position += velocities[i].velocity * delta +## +## func process_health(entities: Array[Entity], components: Array, delta: float): +## for entity in entities: +## var health = entity.get_component(C_Health) +## health.regenerate(delta) +## [/codeblock] +func sub_systems() -> Array[Array]: + return [] # Base returns empty - overridden systems return populated Array[Array] + + +## Runs once after the system has been added to the [World] to setup anything on the system one time[br] +func setup(): + pass # Override in subclasses if needed + + +## The main processing function for the system.[br] +## Override this method to define your system's behavior.[br] +## [param entities] Array of entities matching the system's query[br] +## [param components] Array of component arrays (in order from iterate()), or empty if no iterate() call[br] +## [param delta] The time elapsed since the last frame[br][br] +## [b]Simple approach:[/b] Loop through entities and use get_component()[br] +## [b]Fast approach:[/b] Use iterate() in query and access component arrays directly +func process(entities: Array[Entity], components: Array, delta: float) -> void: + pass # Override in subclasses - base implementation does nothing + +#endregion Public Methods + +#region Private Methods + + +## INTERNAL: Called by World.add_system() to initialize the system +## DO NOT CALL OR OVERRIDE - this is framework code +func _internal_setup(): + # Call user setup + setup() + + +## Process entities in parallel using WorkerThreadPool +## Splits entities into batches and processes them concurrently +func _process_parallel(entities: Array[Entity], components: Array, delta: float) -> void: + if entities.is_empty(): + return + + # Use OS thread count as fallback since WorkerThreadPool.get_thread_count() doesn't exist + var worker_count = OS.get_processor_count() + var batch_size = max(1, entities.size() / worker_count) + var tasks = [] + + # Submit tasks for each batch + for batch_start in range(0, entities.size(), batch_size): + var batch_end = min(batch_start + batch_size, entities.size()) + + # Slice entities and components for this batch + var batch_entities = entities.slice(batch_start, batch_end) + var batch_components = [] + for comp_array in components: + batch_components.append(comp_array.slice(batch_start, batch_end)) + + var task_id = WorkerThreadPool.add_task(_process_batch_callable.bind(batch_entities, batch_components, delta)) + tasks.append(task_id) + + # Wait for all tasks to complete + for task_id in tasks: + WorkerThreadPool.wait_for_task_completion(task_id) + + +## Process a batch of entities - called by worker threads +func _process_batch_callable(entities: Array[Entity], components: Array, delta: float) -> void: + process(entities, components, delta) + + +## Called by World.process() each frame - main entry point for system execution +## [param delta] The time elapsed since the last frame +func _handle(delta: float) -> void: + if not active or paused: + return + var start_time_usec := 0 + if ECS.debug: + start_time_usec = Time.get_ticks_usec() + lastRunData = { + "system_name": get_script().resource_path.get_file().get_basename(), + "frame_delta": delta, + } + var subs = sub_systems() + if not subs.is_empty(): + _run_subsystems(delta) + else: + _run_process(delta) + if ECS.debug: + var end_time_usec = Time.get_ticks_usec() + lastRunData["execution_time_ms"] = (end_time_usec - start_time_usec) / 1000.0 + + +## UNIFIED execution function for both main systems and subsystems +## This ensures consistent behavior and entity processing logic +## Subsystems and main systems execute IDENTICALLY - no special behavior +## [param query_builder] The query to execute +## [param callable] The function to call with matched entities +## [param delta] Time delta +## [param subsystem_index] Index for debug tracking (-1 for main system) +func _run_subsystems(delta: float) -> void: + if _subsystems_cache.is_empty(): + _subsystems_cache = sub_systems() + var subsystem_index := 0 + for subsystem_tuple in _subsystems_cache: + var subsystem_query := subsystem_tuple[0] as QueryBuilder + var subsystem_callable := subsystem_tuple[1] as Callable + var uses_non_structural := _query_has_non_structural_filters(subsystem_query) + var iterate_comps = subsystem_query._iterate_components + if uses_non_structural: + # Gather ALL structural entities first then filter once (avoid per-archetype filtering churn) + var all_entities: Array[Entity] = [] + for arch in subsystem_query.archetypes(): + if not arch.entities.is_empty(): + all_entities.append_array(arch.entities) # no snapshot to allow mid-frame changes visible to later subsystems + var filtered = _filter_entities_global(subsystem_query, all_entities) + if filtered.is_empty(): + if ECS.debug: + lastRunData[subsystem_index] = {"subsystem_index": subsystem_index, "entity_count": 0, "fallback_execute": true} + subsystem_index += 1 + continue + var components := [] + if not iterate_comps.is_empty(): + for comp_type in iterate_comps: + components.append(_build_component_column_from_entities(filtered, comp_type)) + subsystem_callable.call(filtered, components, delta) + if ECS.debug: + lastRunData[subsystem_index] = {"subsystem_index": subsystem_index, "entity_count": filtered.size(), "fallback_execute": true} + else: + # Structural fast path archetype iteration + var total_entity_count := 0 + for archetype in subsystem_query.archetypes(): + if archetype.entities.is_empty(): + continue + # Snapshot to avoid losing entities during add/remove component archetype moves mid-iteration + var arch_entities = archetype.entities.duplicate() + total_entity_count += arch_entities.size() + var components = [] + if not iterate_comps.is_empty(): + for comp_type in iterate_comps: + var comp_path = comp_type.resource_path if comp_type is Script else comp_type.get_script().resource_path + components.append(archetype.get_column(comp_path)) + subsystem_callable.call(arch_entities, components, delta) + if ECS.debug: + lastRunData[subsystem_index] = {"subsystem_index": subsystem_index, "entity_count": total_entity_count, "fallback_execute": false} + subsystem_index += 1 + + +func _run_process(delta: float) -> void: + if not _query_cache: + _query_cache = query() + if _component_paths.is_empty(): + var iterate_comps = _query_cache._iterate_components + for comp_type in iterate_comps: + var comp_path = comp_type.resource_path if comp_type is Script else comp_type.get_script().resource_path + _component_paths.append(comp_path) + var uses_non_structural := _query_has_non_structural_filters(_query_cache) + var iterate_comps = _query_cache._iterate_components + if uses_non_structural: + # Gather all entities across structural archetypes and then filter once + var all_entities: Array[Entity] = [] + for arch in _query_cache.archetypes(): + if not arch.entities.is_empty(): + all_entities.append_array(arch.entities) + if all_entities.is_empty(): + if process_empty: + process([], [], delta) + return + var filtered = _filter_entities_global(_query_cache, all_entities) + if filtered.is_empty(): + if process_empty: + process([], [], delta) + return + var components := [] + if not iterate_comps.is_empty(): + for comp_type in iterate_comps: + components.append(_build_component_column_from_entities(filtered, comp_type)) + if parallel_processing and filtered.size() >= parallel_threshold: + _process_parallel(filtered, components, delta) + else: + process(filtered, components, delta) + if ECS.debug: + lastRunData["entity_count"] = filtered.size() + lastRunData["archetype_count" + ] = _query_cache.archetypes().size() + lastRunData["fallback_execute"] = true + lastRunData["parallel"] = parallel_processing and filtered.size() >= parallel_threshold + return + # Structural fast path + var matching_archetypes = _query_cache.archetypes() + var has_entities = false + var total_entity_count := 0 + for arch in matching_archetypes: + if not arch.entities.is_empty(): + has_entities = true + total_entity_count += arch.entities.size() + if ECS.debug: + lastRunData["entity_count"] = total_entity_count + lastRunData["archetype_count"] = matching_archetypes.size() + lastRunData["fallback_execute"] = false + if not has_entities and not process_empty: + return + if not has_entities and process_empty: + process([], [], delta) + return + for arch in matching_archetypes: + var arch_entities = arch.entities + if arch_entities.is_empty(): + continue + # Snapshot structural entities to avoid mutation skipping during component add/remove + var snapshot_entities = arch_entities.duplicate() + var components = [] + if not iterate_comps.is_empty(): + for comp_path in _component_paths: + components.append(arch.get_column(comp_path)) + if parallel_processing and snapshot_entities.size() >= parallel_threshold: + if ECS.debug: + lastRunData["parallel"] = true + lastRunData["threshold"] = parallel_threshold + _process_parallel(snapshot_entities, components, delta) + else: + if ECS.debug: + lastRunData["parallel"] = false + process(snapshot_entities, components, delta) + + +## Determine if a query includes non-structural filters requiring execute() fallback +func _query_has_non_structural_filters(qb: QueryBuilder) -> bool: + if not qb._relationships.is_empty(): + return true + if not qb._exclude_relationships.is_empty(): + return true + if not qb._groups.is_empty(): + return true + if not qb._exclude_groups.is_empty(): + return true + # Component property queries (ensure actual queries, not placeholders) + if not qb._all_components_queries.is_empty(): + for query in qb._all_components_queries: + if not query.is_empty(): + return true + if not qb._any_components_queries.is_empty(): + for query in qb._any_components_queries: + if not query.is_empty(): + return true + return false + + +## Build component arrays for iterate() when falling back to execute() result (no archetype columns) +func _build_component_column_from_entities(entities: Array[Entity], comp_type) -> Array: + var out := [] + for e in entities: + if e == null: + out.append(null) + continue + var comp = e.get_component(comp_type) + out.append(comp) + return out + + +## Filter entities in an archetype for non-structural query criteria (relationships/groups/property queries) +## Filter a flat entity array for non-structural criteria +func _filter_entities_global(qb: QueryBuilder, entities: Array[Entity]) -> Array[Entity]: + var result: Array[Entity] = [] + for e in entities: + if e == null: + continue + var include := true + for rel in qb._relationships: + if not e.has_relationship(rel): + include = false; break + if include: + for ex_rel in qb._exclude_relationships: + if e.has_relationship(ex_rel): + include = false; break + if include and not qb._groups.is_empty(): + for g in qb._groups: + if not e.is_in_group(g): + include = false; break + if include and not qb._exclude_groups.is_empty(): + for g in qb._exclude_groups: + if e.is_in_group(g): + include = false; break + if include and not qb._all_components_queries.is_empty(): + for i in range(qb._all_components.size()): + if i >= qb._all_components_queries.size(): + break + var comp_type = qb._all_components[i] + var query = qb._all_components_queries[i] + if not query.is_empty(): + var comp = e.get_component(comp_type) + if comp == null or not ComponentQueryMatcher.matches_query(comp, query): + include = false; break + if include and not qb._any_components_queries.is_empty(): + var any_match := qb._any_components_queries.is_empty() + for i in range(qb._any_components.size()): + if i >= qb._any_components_queries.size(): + break + var comp_type = qb._any_components[i] + var query = qb._any_components_queries[i] + if not query.is_empty(): + var comp = e.get_component(comp_type) + if comp and ComponentQueryMatcher.matches_query(comp, query): + any_match = true; break + if not any_match and not qb._any_components.is_empty(): + include = false + if include: + result.append(e) + return result + + +## Debug helper - updates lastRunData (compiled out in production) +func _update_debug_data(callable: Callable = func(): return {}) -> bool: + if ECS.debug: + var data = callable.call() + if data: + lastRunData.assign(data) + return true + + +## Debug helper - sets lastRunData (compiled out in production) +func _debug_data(_lrd: Dictionary, callable: Callable = func(): return {}) -> bool: + if ECS.debug: + lastRunData = _lrd + lastRunData.assign(callable.call()) + return true + +#endregion Private Methods diff --git a/addons/gecs/ecs/system.gd.uid b/addons/gecs/ecs/system.gd.uid new file mode 100644 index 0000000..04837ba --- /dev/null +++ b/addons/gecs/ecs/system.gd.uid @@ -0,0 +1 @@ +uid://dyrahdwwpjpri diff --git a/addons/gecs/ecs/world.gd b/addons/gecs/ecs/world.gd new file mode 100644 index 0000000..53f756e --- /dev/null +++ b/addons/gecs/ecs/world.gd @@ -0,0 +1,1341 @@ +## World +## +## Represents the game world in the [_ECS] framework, managing all [Entity]s and [System]s. +## +## The World class handles the addition and removal of [Entity]s and [System]s, and orchestrates the processing of [Entity]s through [System]s each frame. +## The World class also maintains an index mapping of components to entities for efficient querying. +@icon("res://addons/gecs/assets/world.svg") +class_name World +extends Node + +#region Signals +## Emitted when an entity is added +signal entity_added(entity: Entity) +signal entity_enabled(entity: Entity) +## Emitted when an entity is removed +signal entity_removed(entity: Entity) +signal entity_disabled(entity: Entity) +## Emitted when a system is added +signal system_added(system: System) +## Emitted when a system is removed +signal system_removed(system: System) +## Emitted when a component is added to an entity +signal component_added(entity: Entity, component: Variant) +## Emitted when a component is removed from an entity +signal component_removed(entity: Entity, component: Variant) +## Emitted when a component property changes on an entity +signal component_changed( + entity: Entity, component: Variant, property: String, new_value: Variant, old_value: Variant +) +## Emitted when a relationship is added to an entity +signal relationship_added(entity: Entity, relationship: Relationship) +## Emitted when a relationship is removed from an entity +signal relationship_removed(entity: Entity, relationship: Relationship) +## Emitted when the queries are invalidated because of a component change +signal cache_invalidated + +#endregion Signals + +#region Exported Variables +## Where are all the [Entity] nodes placed in the scene tree? +@export var entity_nodes_root: NodePath +## Where are all the [System] nodes placed in the scene tree? +@export var system_nodes_root: NodePath +## Default serialization config for all entities in this world +@export var default_serialize_config: GECSSerializeConfig + +#endregion Exported Variables + +#region Public Variables +## All the [Entity]s in the world. +var entities: Array[Entity] = [] +## All the [Observer]s in the world. +var observers: Array[Observer] = [] +## All the [System]s by group Dictionary[String, Array[System]] +var systems_by_group: Dictionary[String, Array] = {} +## All the [System]s in the world flattened into a single array +var systems: Array[System]: + get: + var all_systems: Array[System] = [] + for group in systems_by_group.keys(): + all_systems.append_array(systems_by_group[group]) + return all_systems +## ID to [Entity] registry - Prevents duplicate IDs and enables fast ID lookups and singleton behavior +var entity_id_registry: Dictionary = {} # String (id) -> Entity +## ARCHETYPE STORAGE - Entity storage by component signature for O(1) queries +## Maps archetype signature (FNV-1a hash) -> Archetype instance +var archetypes: Dictionary = {} # int -> Archetype +## Fast lookup: Entity -> its current Archetype +var entity_to_archetype: Dictionary = {} # Entity -> Archetype +## The [QueryBuilder] instance for this world used to build and execute queries. +## Anytime we request a query we want to connect the cache invalidated signal to the query +## so that all queries are invalidated anytime we emit cache_invalidated. +var query: QueryBuilder: + get: + var q: QueryBuilder = QueryBuilder.new(self) + if not cache_invalidated.is_connected(q.invalidate_cache): + cache_invalidated.connect(q.invalidate_cache) + return q +## Index for relationships to entities (Optional for optimization) +var relationship_entity_index: Dictionary = {} +## Index for reverse relationships (target to source entities) +var reverse_relationship_index: Dictionary = {} +## Logger for the world to only log to a specific domain +var _worldLogger = GECSLogger.new().domain("World") +## Cache for commonly used query results - stores matching archetypes, not entities +## This dramatically reduces cache invalidation since archetypes are stable +var _query_archetype_cache: Dictionary = {} # query_sig -> Array[Archetype] +## Track cache hits for performance monitoring +var _cache_hits: int = 0 +var _cache_misses: int = 0 +## Track cache invalidations for debugging +var _cache_invalidation_count: int = 0 +var _cache_invalidation_reasons: Dictionary = {} # reason -> count +## Global cache: resource_path -> Script (loaded once, reused forever) +var _component_script_cache: Dictionary = {} # String -> Script +## OPTIMIZATION: Flag to control cache invalidation during batch operations +var _should_invalidate_cache: bool = true +## Frame + accumulated performance metrics (debug-only) +var _perf_metrics := { + "frame": {}, # Per-frame aggregated timings + "accum": {} # Long-lived totals (cleared manually) +} + + +## Internal perf helper (debug only) +func perf_mark(key: String, duration_usec: int, extra: Dictionary = {}) -> void: + if not ECS.debug: + return + # Aggregate per frame + var entry = _perf_metrics.frame.get(key, {"count": 0, "time_usec": 0}) + entry.count += 1 + entry.time_usec += duration_usec + for k in extra.keys(): + # Attach/overwrite ancillary data (last value wins) + entry[k] = extra[k] + _perf_metrics.frame[key] = entry + # Accumulate lifetime totals + var accum_entry = _perf_metrics.accum.get(key, {"count": 0, "time_usec": 0}) + accum_entry.count += 1 + accum_entry.time_usec += duration_usec + _perf_metrics.accum[key] = accum_entry + + +## Reset per-frame metrics (called at world.process start) +func perf_reset_frame() -> void: + if ECS.debug: + _perf_metrics.frame.clear() + + +## Get a copy of current frame metrics +func perf_get_frame_metrics() -> Dictionary: + return _perf_metrics.frame.duplicate(true) + + +## Get a copy of accumulated metrics +func perf_get_accum_metrics() -> Dictionary: + return _perf_metrics.accum.duplicate(true) + + +## Reset accumulated metrics +func perf_reset_accum() -> void: + if ECS.debug: + _perf_metrics.accum.clear() + +#endregion Public Variables + + +#region Built-in Virtual Methods +## Called when the World node is ready. +func _ready() -> void: + #_worldLogger.disabled = true + initialize() + + +func _make_nodes_root(name: String) -> Node: + var node = Node.new() + node.name = name + add_child(node) + return node + + +## Adds [Entity]s and [System]s from the scene tree to the [World]. +## Called when the World node is ready or when we should re-initialize the world from the tree. +func initialize(): + # Initialize default serialize config if not set + if default_serialize_config == null: + default_serialize_config = GECSSerializeConfig.new() + + # if no entities/systems root node is set create them and use them. This keeps things tidy for debugging + entity_nodes_root = ( + _make_nodes_root("Entities").get_path() if not entity_nodes_root else entity_nodes_root + ) + system_nodes_root = ( + _make_nodes_root("Systems").get_path() if not system_nodes_root else system_nodes_root + ) + + # Add systems from scene tree + var _systems = get_node(system_nodes_root).find_children("*", "System") as Array[System] + add_systems(_systems, true) # and sort them after they're added + _worldLogger.debug("_initialize Added Systems from Scene Tree and dep sorted: ", _systems) + + # Add observers from scene tree + var _observers = get_node(system_nodes_root).find_children("*", "Observer") as Array[Observer] + add_observers(_observers) + _worldLogger.debug("_initialize Added Observers from Scene Tree: ", _observers) + + # Add entities from the scene tree + var _entities = get_node(entity_nodes_root).find_children("*", "Entity") as Array[Entity] + add_entities(_entities) + _worldLogger.debug("_initialize Added Entities from Scene Tree: ", _entities) + + if ECS.debug: + assert(GECSEditorDebuggerMessages.world_init(self ), '') + # Register debugger message handler for entity polling + if not Engine.is_editor_hint() and OS.has_feature("editor"): + EngineDebugger.register_message_capture("gecs", _handle_debugger_message) + +#endregion Built-in Virtual Methods + + +#region Public Methods +## Called every frame by the [method _ECS.process] to process [System]s. +## [param delta] The time elapsed since the last frame. +## [param group] The string for the group we should run. If empty runs all systems in default "" group. +func process(delta: float, group: String = "") -> void: + # PERF: Reset frame metrics at start of processing step + perf_reset_frame() + if systems_by_group.has(group): + var system_index = 0 + for system in systems_by_group[group]: + if system.active: + system._handle(delta) + if ECS.debug: + # Add execution order to last run data + system.lastRunData["execution_order"] = system_index + assert(GECSEditorDebuggerMessages.system_last_run_data(system, system.lastRunData), '') + system_index += 1 + if ECS.debug: + assert(GECSEditorDebuggerMessages.process_world(delta, group), '') + + +## Updates the pause behavior for all systems based on the provided paused state. +## If paused, only systems with PROCESS_MODE_ALWAYS remain active; all others become inactive. +## If unpaused, systems with PROCESS_MODE_DISABLED stay inactive; all others become active. +func update_pause_state(paused: bool) -> void: + for group_key in systems_by_group.keys(): + for system in systems_by_group[group_key]: + # Check to see if the system is can process based on the process mode and paused state + system.paused = not system.can_process() + + +## Adds a single [Entity] to the world.[br] +## [param entity] The [Entity] to add.[br] +## [param components] The optional list of [Component] to add to the entity.[br] +## [b]Example:[/b] +## [codeblock] +## # add just an entity +## world.add_entity(player_entity) +## # add an entity with some components +## world.add_entity(other_entity, [component_a, component_b]) +## [/codeblock] +func add_entity(entity: Entity, components = null, add_to_tree = true) -> void: + # Check for ID collision - if entity with same ID exists, replace it + var entity_id = GECSIO.uuid() if not entity.id else entity.id + entity.id = entity_id # update entity with it's new id + + if entity_id in entity_id_registry: + var existing_entity = entity_id_registry[entity_id] + _worldLogger.debug("ID collision detected, replacing entity: ", existing_entity.name, " with: ", entity.name) + remove_entity(existing_entity) + + # Register this entity's ID + entity_id_registry[entity_id] = entity + + # ID will auto-generate in _enter_tree if empty, or via property getter on first access + + # Update index + _worldLogger.debug("add_entity Adding Entity to World: ", entity) + + # Connect to entity signals for components so we can track global component state + if not entity.component_added.is_connected(_on_entity_component_added): + entity.component_added.connect(_on_entity_component_added) + if not entity.component_removed.is_connected(_on_entity_component_removed): + entity.component_removed.connect(_on_entity_component_removed) + if not entity.relationship_added.is_connected(_on_entity_relationship_added): + entity.relationship_added.connect(_on_entity_relationship_added) + if not entity.relationship_removed.is_connected(_on_entity_relationship_removed): + entity.relationship_removed.connect(_on_entity_relationship_removed) + + # Add the entity to the tree if it's not already there after hooking up the signals + # This ensures that any _ready methods on the entity or its components are called after setup + if add_to_tree and not entity.is_inside_tree(): + get_node(entity_nodes_root).add_child(entity) + + # add entity to our list + entities.append(entity) + + # ARCHETYPE: Add entity to archetype system BEFORE initialization + # Start with empty archetype, then move as components are added + _add_entity_to_archetype(entity) + + # initialize the entity and its components in game only + # This will trigger component_added signals which move the entity to the right archetype + if not Engine.is_editor_hint(): + entity._initialize(components if components else []) + + entity_added.emit(entity) + + # All the entities are ready so we should run the pre-processors now + for processor in ECS.entity_preprocessors: + processor.call(entity) + + if ECS.debug: + assert(GECSEditorDebuggerMessages.entity_added(entity), '') + + +## Adds multiple entities to the world.[br] +## [param entities] An array of entities to add. +## [param components] The optional list of [Component] to add to the entity.[br] +## [b]Example:[/b] +## [codeblock]world.add_entities([player_entity, enemy_entity], [component_a])[/codeblock] +func add_entities(_entities: Array, components = null): + # OPTIMIZATION: Batch processing to reduce cache invalidations + # Temporarily disable cache invalidation during batch, then invalidate once at the end + var original_invalidate = _should_invalidate_cache + _should_invalidate_cache = false + + var new_archetypes_created = false + var initial_archetype_count = archetypes.size() + + # Process all entities + for _entity in _entities: + add_entity(_entity, components) + + # Check if any new archetypes were created + if archetypes.size() > initial_archetype_count: + new_archetypes_created = true + + # Re-enable cache invalidation and invalidate once if needed + _should_invalidate_cache = original_invalidate + if new_archetypes_created: + _invalidate_cache("batch_add_entities") + + +## Removes an [Entity] from the world.[br] +## [param entity] The [Entity] to remove.[br] +## [b]Example:[/b] +## [codeblock]world.remove_entity(player_entity)[/codeblock] +func remove_entity(entity) -> void: + entity = entity as Entity + + for processor in ECS.entity_postprocessors: + processor.call(entity) + entity_removed.emit(entity) + _worldLogger.debug("remove_entity Removing Entity: ", entity) + entities.erase(entity) # FIXME: This doesn't always work for some reason? + + # Only disconnect signals if they're actually connected + if entity.component_added.is_connected(_on_entity_component_added): + entity.component_added.disconnect(_on_entity_component_added) + if entity.component_removed.is_connected(_on_entity_component_removed): + entity.component_removed.disconnect(_on_entity_component_removed) + if entity.relationship_added.is_connected(_on_entity_relationship_added): + entity.relationship_added.disconnect(_on_entity_relationship_added) + if entity.relationship_removed.is_connected(_on_entity_relationship_removed): + entity.relationship_removed.disconnect(_on_entity_relationship_removed) + + # Remove from ID registry + var entity_id = entity.id + if entity_id != "" and entity_id in entity_id_registry and entity_id_registry[entity_id] == entity: + entity_id_registry.erase(entity_id) + + # ARCHETYPE: Remove entity from archetype system (parallel) + _remove_entity_from_archetype(entity) + + # Destroy entity normally + entity.on_destroy() + entity.queue_free() + + if ECS.debug: + assert(GECSEditorDebuggerMessages.entity_removed(entity), '') + + +## Removes an Array of [Entity] from the world.[br] +## [param entity] The Array of [Entity] to remove.[br] +## [b]Example:[/b] +## [codeblock]world.remove_entities([player_entity, other_entity])[/codeblock] +func remove_entities(_entities: Array) -> void: + # OPTIMIZATION: Batch processing to reduce cache invalidations + # Temporarily disable cache invalidation during batch, then invalidate once at the end + var original_invalidate = _should_invalidate_cache + _should_invalidate_cache = false + + # Process all entities + for _entity in _entities: + remove_entity(_entity) + + # Re-enable cache invalidation and always invalidate when entities are removed + # QueryBuilder caches execute() results, so any entity removal requires cache invalidation + _should_invalidate_cache = original_invalidate + _invalidate_cache("batch_remove_entities") + + +## Disable an [Entity] from the world. Disabled entities don't run process or physics,[br] +## are hidden and removed the entities list and the[br] +## [param entity] The [Entity] to disable.[br] +## [b]Example:[/b] +## [codeblock]world.disable_entity(player_entity)[/codeblock] +func disable_entity(entity) -> Entity: + entity = entity as Entity + entity.enabled = false # This will trigger _on_entity_enabled_changed via setter + entity_disabled.emit(entity) + _worldLogger.debug("disable_entity Disabling Entity: ", entity) + + entity.component_added.disconnect(_on_entity_component_added) + entity.component_removed.disconnect(_on_entity_component_removed) + entity.relationship_added.disconnect(_on_entity_relationship_added) + entity.relationship_removed.disconnect(_on_entity_relationship_removed) + entity.on_disable() + entity.set_process(false) + entity.set_physics_process(false) + if ECS.debug: + assert(GECSEditorDebuggerMessages.entity_disabled(entity), '') + return entity + + +## Disable an Array of [Entity] from the world. Disabled entities don't run process or physics,[br] +## are hidden and removed the entities list[br] +## [param entity] The [Entity] to disable.[br] +## [b]Example:[/b] +## [codeblock]world.disable_entities([player_entity, other_entity])[/codeblock] +func disable_entities(_entities: Array) -> void: + for _entity in _entities: + disable_entity(_entity) + + +## Enables a single [Entity] to the world.[br] +## [param entity] The [Entity] to enable.[br] +## [param components] The optional list of [Component] to add to the entity.[br] +## [b]Example:[/b] +## [codeblock] +## # enable just an entity +## world.enable_entity(player_entity) +## # enable an entity with some components +## world.enable_entity(other_entity, [component_a, component_b]) +## [/codeblock] +func enable_entity(entity: Entity, components = null) -> void: + # Update index + _worldLogger.debug("enable_entity Enabling Entity to World: ", entity) + entity.enabled = true # This will trigger _on_entity_enabled_changed via setter + entity_enabled.emit(entity) + + # Connect to entity signals for components so we can track global component state + if not entity.component_added.is_connected(_on_entity_component_added): + entity.component_added.connect(_on_entity_component_added) + if not entity.component_removed.is_connected(_on_entity_component_removed): + entity.component_removed.connect(_on_entity_component_removed) + if not entity.relationship_added.is_connected(_on_entity_relationship_added): + entity.relationship_added.connect(_on_entity_relationship_added) + if not entity.relationship_removed.is_connected(_on_entity_relationship_removed): + entity.relationship_removed.connect(_on_entity_relationship_removed) + + if components: + entity.add_components(components) + + entity.set_process(true) + entity.set_physics_process(true) + entity.on_enable() + if ECS.debug: + assert(GECSEditorDebuggerMessages.entity_enabled(entity), '') + + +## Find an entity by its persistent ID +## [param id] The id to search for +## [return] The Entity with matching ID, or null if not found +func get_entity_by_id(id: String) -> Entity: + return entity_id_registry.get(id, null) + + +## Check if an entity with the given ID exists in the world +## [param id] The id to check +## [return] true if an entity with this ID exists, false otherwise +func has_entity_with_id(id: String) -> bool: + return id in entity_id_registry + +#region Systems + + +## Adds a single system to the world. +## +## [param system] The system to add. +## +## [b]Example:[/b] +## [codeblock]world.add_system(movement_system)[/codeblock] +func add_system(system: System, topo_sort: bool = false) -> void: + if not system.is_inside_tree(): + get_node(system_nodes_root).add_child(system) + _worldLogger.trace("add_system Adding System: ", system) + + # Give the system a reference to this world + system._world = self + + if not systems_by_group.has(system.group): + systems_by_group[system.group] = [] + systems_by_group[system.group].push_back(system) + system_added.emit(system) + system._internal_setup() # Determines execution method and calls user setup() + if topo_sort: + ArrayExtensions.topological_sort(systems_by_group) + if ECS.debug: + assert(GECSEditorDebuggerMessages.system_added(system), '') + + +## Adds multiple systems to the world. +## +## [param systems] An array of systems to add. +## +## [b]Example:[/b] +## [codeblock]world.add_systems([movement_system, render_system])[/codeblock] +func add_systems(_systems: Array, topo_sort: bool = false): + for _system in _systems: + add_system(_system) + # After we add them all sort them + if topo_sort: + ArrayExtensions.topological_sort(systems_by_group) + + +## Removes a [System] from the world.[br] +## [param system] The [System] to remove.[br] +## [b]Example:[/b] +## [codeblock]world.remove_system(movement_system)[/codeblock] +func remove_system(system, topo_sort: bool = false) -> void: + _worldLogger.debug("remove_system Removing System: ", system) + systems_by_group[system.group].erase(system) + if systems_by_group[system.group].size() == 0: + systems_by_group.erase(system.group) + system_removed.emit(system) + # Update index + system.queue_free() + if topo_sort: + ArrayExtensions.topological_sort(systems_by_group) + if ECS.debug: + assert(GECSEditorDebuggerMessages.system_removed(system), '') + + +## Removes an Array of [System] from the world.[br] +## [param system] The Array of [System] to remove.[br] +## [b]Example:[/b] +## [codeblock]world.remove_systems([movement_system, other_system])[/codeblock] +func remove_systems(_systems: Array, topo_sort: bool = false) -> void: + for _system in _systems: + remove_system(_system) + if topo_sort: + ArrayExtensions.topological_sort(systems_by_group) + + +## Removes all systems in a group from the world.[br] +## [param group] The group name of the systems to remove.[br] +## [b]Example:[/b] +## [codeblock]world.remove_system_group("Gameplay")[/codeblock] +func remove_system_group(group: String, topo_sort: bool = false) -> void: + if systems_by_group.has(group): + for system in systems_by_group[group]: + remove_system(system) + if topo_sort: + ArrayExtensions.topological_sort(systems_by_group) + + +## Removes all [Entity]s and [System]s from the world.[br] +## [param should_free] Optionally frees the world node by default +## [param keep] A list of entities that should be kept in the world +func purge(should_free = true, keep := []) -> void: + # Get rid of all entities + _worldLogger.debug("Purging Entities", entities) + for entity in entities.duplicate().filter(func(x): return not keep.has(x)): + remove_entity(entity) + + # Clear relationship indexes after purging entities + relationship_entity_index.clear() + reverse_relationship_index.clear() + _worldLogger.debug("Cleared relationship indexes after purge") + + # ARCHETYPE: Clear archetype system + # First, break circular references by clearing edges + for archetype in archetypes.values(): + archetype.add_edges.clear() + archetype.remove_edges.clear() + archetypes.clear() + entity_to_archetype.clear() + _worldLogger.debug("Cleared archetype storage after purge") + + # Purge all systems + _worldLogger.debug("Purging All Systems") + for group_key in systems_by_group.keys(): + for system in systems_by_group[group_key].duplicate(): + remove_system(system) + + # Purge all observers + _worldLogger.debug("Purging Observers", observers) + for observer in observers.duplicate(): + remove_observer(observer) + + _invalidate_cache("purge") + + # remove itself + if should_free: + queue_free() + +## Executes a query to retrieve entities based on component criteria.[br] +## [param all_components] [Component]s that [Entity]s must have all of.[br] +## [param any_components] [Component]s that [Entity]s must have at least one of.[br] +## [param exclude_components] [Component]s that [Entity]s must not have.[br] +## [param returns] An [Array] of [Entity]s that match the query.[br] +## [br] +## Performance Optimization:[br] +## When checking for all_components, the system first identifies the component with the smallest[br] +## set of entities and starts with that set. This significantly reduces the number of comparisons needed,[br] +## as we only need to check the smallest possible set of entities against other components. + +#endregion Systems + +#region Signal Callbacks + + +## [signal Entity.component_added] Callback when a component is added to an entity.[br] +## [param entity] The entity that had a component added.[br] +## [param component] The resource path of the added component. +func _on_entity_component_added(entity: Entity, component: Resource) -> void: + # ARCHETYPE: Move entity to new archetype + if entity_to_archetype.has(entity): + var old_archetype = entity_to_archetype[entity] + var comp_path = component.get_script().resource_path + var new_archetype = _move_entity_to_new_archetype_fast(entity, old_archetype, comp_path, true) + # Must invalidate: QueryBuilder caches execute() results, not just archetype matches + _invalidate_cache("entity_component_added") + + # Emit Signal + component_added.emit(entity, component) + _handle_observer_component_added(entity, component) + if not entity.component_property_changed.is_connected(_on_entity_component_property_change): + entity.component_property_changed.connect(_on_entity_component_property_change) + if ECS.debug: + assert(GECSEditorDebuggerMessages.entity_component_added(entity, component), '') + + +## Called when a component property changes through signals called on the components and connected to.[br] +## in the _ready method.[br] +## [param entity] The [Entity] with the component change.[br] +## [param component] The [Component] that changed.[br] +## [param property_name] The name of the property that changed.[br] +## [param old_value] The old value of the property.[br] +## [param new_value] The new value of the property.[br] +func _on_entity_component_property_change( + entity: Entity, + component: Resource, + property_name: String, + old_value: Variant, + new_value: Variant +) -> void: + # Notify the World to trigger observers + _handle_observer_component_changed(entity, component, property_name, new_value, old_value) + # ARCHETYPE: No cache invalidation - property changes don't affect archetype membership + # Send the message to the debugger if we're in debug + if ECS.debug: + assert(GECSEditorDebuggerMessages.entity_component_property_changed( + entity, component, property_name, old_value, new_value + ), '') + + +## [signal Entity.component_removed] Callback when a component is removed from an entity.[br] +## [param entity] The entity that had a component removed.[br] +## [param component] The resource path of the removed component. +func _on_entity_component_removed(entity, component: Resource) -> void: + if entity_to_archetype.has(entity): + var old_archetype = entity_to_archetype[entity] + var comp_path = component.resource_path + var new_archetype = _move_entity_to_new_archetype_fast(entity, old_archetype, comp_path, false) + # Must invalidate: QueryBuilder caches execute() results, not just archetype matches + _invalidate_cache("entity_component_removed") + + component_removed.emit(entity, component) + _handle_observer_component_removed(entity, component) + if ECS.debug: + assert(GECSEditorDebuggerMessages.entity_component_removed(entity, component), '') + + +## (Optional) Update index when a relationship is added. +func _on_entity_relationship_added(entity: Entity, relationship: Relationship) -> void: + var key = relationship.relation.resource_path + if not relationship_entity_index.has(key): + relationship_entity_index[key] = [] + relationship_entity_index[key].append(entity) + + # Index the reverse relationship + if is_instance_valid(relationship.target) and relationship.target is Entity: + var rev_key = "reverse_" + key + if not reverse_relationship_index.has(rev_key): + reverse_relationship_index[rev_key] = [] + reverse_relationship_index[rev_key].append(relationship.target) + + # PERFORMANCE: Do NOT invalidate archetype cache on relationship changes + # Relationships do not alter archetype membership (structural component sets) + # QueryBuilder.execute() performs relationship filtering on entity results. + # Systems use archetypes() + per-entity filtering, so invalidation here only + # increases cache churn without improving correctness. + + # Emit Signal + relationship_added.emit(entity, relationship) + if ECS.debug: + assert(GECSEditorDebuggerMessages.entity_relationship_added(entity, relationship), '') + + +## (Optional) Update index when a relationship is removed. +func _on_entity_relationship_removed(entity: Entity, relationship: Relationship) -> void: + var key = relationship.relation.resource_path + if relationship_entity_index.has(key): + relationship_entity_index[key].erase(entity) + + if is_instance_valid(relationship.target) and relationship.target is Entity: + var rev_key = "reverse_" + key + if reverse_relationship_index.has(rev_key): + reverse_relationship_index[rev_key].erase(relationship.target) + + # PERFORMANCE: No cache invalidation (see comment in _on_entity_relationship_added) + + # Emit Signal + relationship_removed.emit(entity, relationship) + if ECS.debug: + assert(GECSEditorDebuggerMessages.entity_relationship_removed(entity, relationship), '') + + +## Adds a single [Observer] to the [World]. +## [param observer] The [Observer] to add. +## [b]Example:[/b] +## [codeblock]world.add_observer(health_change_system)[/codeblock] +func add_observer(_observer: Observer) -> void: + # Verify the system has a valid watch component + _observer.watch() # Just call to validate it returns a component + if not _observer.is_inside_tree(): + get_node(system_nodes_root).add_child(_observer) + _worldLogger.trace("add_observer Adding Observer: ", _observer) + observers.append(_observer) + + # Initialize the query builder for the observer + _observer.q = QueryBuilder.new(self ) + + # Verify the system has a valid watch component + _observer.watch() # Just call to validate it returns a component + + +## Adds multiple [Observer]s to the [World]. +## [param observers] An array of [Observer]s to add. +## [b]Example:[/b] +## [codeblock]world.add_observers([health_system, damage_system])[/codeblock] +func add_observers(_observers: Array): + for _observer in _observers: + add_observer(_observer) + + +## Removes an [Observer] from the [World]. +## [param observer] The [Observer] to remove. +## [b]Example:[/b] +## [codeblock]world.remove_observer(health_system)[/codeblock] +func remove_observer(observer: Observer) -> void: + _worldLogger.debug("remove_observer Removing Observer: ", observer) + observers.erase(observer) + # if ECS.debug: + # # Don't use system_removed as it expects a System not ReactiveSystem + # GECSEditorDebuggerMessages.exit_world() # Just send a general update + observer.queue_free() + + +## Handle component property changes and notify observers +## [param entity] The entity with the component change +## [param component] The component that changed +## [param property] The property name that changed +## [param new_value] The new value of the property +## [param old_value] The previous value of the property +func handle_component_changed( + entity: Entity, component: Resource, property: String, new_value: Variant, old_value: Variant +) -> void: + # Emit the general signal + component_changed.emit(entity, component, property, new_value, old_value) + + # Find observers watching for this component and notify them + _handle_observer_component_changed(entity, component, property, new_value, old_value) + + +## Notify observers when a component is added +func _handle_observer_component_added(entity: Entity, component: Resource) -> void: + for reactive_system in observers: + # Get the component that this system is watching + var watch_component = reactive_system.watch() + if ( + watch_component + and component and component.get_script() + and watch_component.resource_path == component.get_script().resource_path + ): + # Check if the entity matches the system's query + var query_builder = reactive_system.match() + var matches = true + + if query_builder: + # Use the _query method instead of trying to use query as a function + var entities_matching = _query( + query_builder._all_components, + query_builder._any_components, + query_builder._exclude_components + ) + # Check if our entity is in the result set + matches = entities_matching.has(entity) + + if matches: + reactive_system.on_component_added(entity, component) + + +## Notify observers when a component is removed +func _handle_observer_component_removed(entity: Entity, component: Resource) -> void: + for reactive_system in observers: + # Get the component that this system is watching + var watch_component = reactive_system.watch() + if ( + watch_component + and component and component.get_script() + and watch_component.resource_path == component.get_script().resource_path + ): + # For removal, we don't check the query since the component is already removed + # Just notify the system + reactive_system.on_component_removed(entity, component) + + +## Notify observers when a component property changes +func _handle_observer_component_changed( + entity: Entity, component: Resource, property: String, new_value: Variant, old_value: Variant +) -> void: + for reactive_system in observers: + # Get the component that this system is watching + var watch_component = reactive_system.watch() + if ( + watch_component + and component and component.get_script() + and watch_component.resource_path == component.get_script().resource_path + ): + # Check if the entity matches the system's query + var query_builder = reactive_system.match() + var matches = true + + if query_builder: + # Use the _query method instead of trying to use query as a function + var entities_matching = _query( + query_builder._all_components, + query_builder._any_components, + query_builder._exclude_components + ) + # Check if our entity is in the result set + matches = entities_matching.has(entity) + + if matches: + reactive_system.on_component_changed( + entity, component, property, new_value, old_value + ) + +#endregion Signal Callbacks + +#endregion Public Methods + +#region Utility Methods + + +func _query(all_components = [], any_components = [], exclude_components = [], enabled_filter = null, precalculated_cache_key: int = -1) -> Array: + var _perf_start_total := 0 + if ECS.debug: + _perf_start_total = Time.get_ticks_usec() + # Early return if no components specified - return all entities + if all_components.is_empty() and any_components.is_empty() and exclude_components.is_empty(): + if enabled_filter == null: + if ECS.debug: + perf_mark("query_all_entities", Time.get_ticks_usec() - _perf_start_total, {"returned": entities.size()}) + return entities + else: + # OPTIMIZATION: Use bitset filtering from all archetypes instead of entity.enabled check + var filtered: Array[Entity] = [] + for archetype in archetypes.values(): + filtered.append_array(archetype.get_entities_by_enabled_state(enabled_filter)) + if ECS.debug: + perf_mark("query_all_entities_filtered", Time.get_ticks_usec() - _perf_start_total, {"returned": filtered.size(), "enabled_filter": enabled_filter}) + return filtered + + # OPTIMIZATION: Use pre-calculated cache key if provided (avoids hash recalculation) + var _perf_start_cache_key := 0 + if ECS.debug: + _perf_start_cache_key = Time.get_ticks_usec() + var cache_key = precalculated_cache_key if precalculated_cache_key != -1 else QueryCacheKey.build(all_components, any_components, exclude_components) + if ECS.debug: + perf_mark("query_cache_key", Time.get_ticks_usec() - _perf_start_cache_key) + + # Check if we have cached matching archetypes for this query + var matching_archetypes: Array[Archetype] = [] + if _query_archetype_cache.has(cache_key): + _cache_hits += 1 + matching_archetypes = _query_archetype_cache[cache_key] + if ECS.debug: + perf_mark("query_cache_hit", 0, {"archetypes": matching_archetypes.size()}) + else: + _cache_misses += 1 + var _perf_start_scan := 0 + if ECS.debug: + _perf_start_scan = Time.get_ticks_usec() + # Find all archetypes that match this query + var map_resource_path = func(x): return x.resource_path + var _all := all_components.map(map_resource_path) + var _any := any_components.map(map_resource_path) + var _exclude := exclude_components.map(map_resource_path) + + for archetype in archetypes.values(): + if archetype.matches_query(_all, _any, _exclude): + matching_archetypes.append(archetype) + # Cache the matching archetypes (not the entity arrays!) + _query_archetype_cache[cache_key] = matching_archetypes + if ECS.debug: + perf_mark("query_archetype_scan", Time.get_ticks_usec() - _perf_start_scan, {"archetypes": matching_archetypes.size()}) + + # OPTIMIZATION: If there's only ONE matching archetype with no filtering, return it directly + # This avoids array allocation and copying for the common case + if matching_archetypes.size() == 1 and enabled_filter == null: + if ECS.debug: + perf_mark("query_single_archetype", Time.get_ticks_usec() - _perf_start_total, {"entities": matching_archetypes[0].entities.size()}) + return matching_archetypes[0].entities + + # Collect entities from all matching archetypes with enabled filtering if needed + var _perf_start_flatten := 0 + if ECS.debug: + _perf_start_flatten = Time.get_ticks_usec() + var result: Array[Entity] = [] + for archetype in matching_archetypes: + if enabled_filter == null: + # No filtering - add all entities + result.append_array(archetype.entities) + else: + # OPTIMIZATION: Use bitset filtering instead of per-entity enabled check + result.append_array(archetype.get_entities_by_enabled_state(enabled_filter)) + if ECS.debug: + perf_mark("query_flatten", Time.get_ticks_usec() - _perf_start_flatten, {"returned": result.size(), "archetypes": matching_archetypes.size()}) + perf_mark("query_total", Time.get_ticks_usec() - _perf_start_total, {"returned": result.size()}) + + return result + + +## OPTIMIZATION: Group entities by their archetype for column-based iteration +## Enables systems to use get_column() for cache-friendly array access +## [param entities] Array of entities to group +## [returns] Dictionary mapping Archetype -> Array[Entity] +## +## Example usage in a System: +## [codeblock] +## func process_all(entities: Array, delta: float): +## var grouped = ECS.world.group_entities_by_archetype(entities) +## for archetype in grouped.keys(): +## process_columns(archetype, delta) +## [/codeblock] +func group_entities_by_archetype(entities: Array) -> Dictionary: + var grouped = {} + for entity in entities: + if entity_to_archetype.has(entity): + var archetype = entity_to_archetype[entity] + if not grouped.has(archetype): + grouped[archetype] = [] + grouped[archetype].append(entity) + return grouped + + +## OPTIMIZATION: Get matching archetypes directly from query (no entity array flattening) +## This is MUCH faster than query().execute() + group_entities_by_archetype() +## [param query_builder] The query to execute +## [returns] Array of matching archetypes +## +## Example usage in a System: +## [codeblock] +## func process_all(entities: Array, delta: float): +## # OLD WAY (slow): +## # var grouped = ECS.world.group_entities_by_archetype(entities) +## +## # NEW WAY (fast): +## var archetypes = ECS.world.get_matching_archetypes(q.with_all([C_Velocity])) +## for archetype in archetypes: +## var velocities = archetype.get_column(C_Velocity.resource_path) +## for i in range(velocities.size()): +## # Process with cache-friendly column access +## [/codeblock] +func get_matching_archetypes(query_builder: QueryBuilder) -> Array[Archetype]: + var _perf_start := 0 + if ECS.debug: + _perf_start = Time.get_ticks_usec() + # PERFORMANCE: Archetype matching is based ONLY on structural components. + # Relationship/group filters are evaluated per-entity in System execution. + # This avoids double-scanning entities (World + System) and reduces cache churn. + var all_components = query_builder._all_components + var any_components = query_builder._any_components + var exclude_components = query_builder._exclude_components + + # Use a COMPONENT-ONLY cache key (ignore relationships/groups) + var cache_key = QueryCacheKey.build(all_components, any_components, exclude_components) + + if _query_archetype_cache.has(cache_key): + if ECS.debug: + perf_mark("archetypes_cache_hit", Time.get_ticks_usec() - _perf_start) + return _query_archetype_cache[cache_key] + + var map_resource_path = func(x): return x.resource_path + var _all := all_components.map(map_resource_path) + var _any := any_components.map(map_resource_path) + var _exclude := exclude_components.map(map_resource_path) + + var matching: Array[Archetype] = [] + var _perf_scan_start := 0 + if ECS.debug: + _perf_scan_start = Time.get_ticks_usec() + for archetype in archetypes.values(): + if archetype.matches_query(_all, _any, _exclude): + matching.append(archetype) + if ECS.debug: + perf_mark("archetypes_scan", Time.get_ticks_usec() - _perf_scan_start, {"archetypes": matching.size()}) + + _query_archetype_cache[cache_key] = matching + if ECS.debug: + perf_mark("archetypes_total", Time.get_ticks_usec() - _perf_start, {"archetypes": matching.size()}) + return matching + + +## Get performance statistics for cache usage +func get_cache_stats() -> Dictionary: + var total_requests = _cache_hits + _cache_misses + var hit_rate = 0.0 if total_requests == 0 else float(_cache_hits) / float(total_requests) + return { + "cache_hits": _cache_hits, + "cache_misses": _cache_misses, + "hit_rate": hit_rate, + "cached_queries": _query_archetype_cache.size(), + "total_archetypes": archetypes.size(), + "invalidation_count": _cache_invalidation_count, + "invalidation_reasons": _cache_invalidation_reasons.duplicate() + } + + +## Reset cache statistics +func reset_cache_stats() -> void: + _cache_hits = 0 + _cache_misses = 0 + _cache_invalidation_count = 0 + _cache_invalidation_reasons.clear() + + +## Internal helper to track cache invalidations (debug mode only) +func _invalidate_cache(reason: String) -> void: + # OPTIMIZATION: Skip invalidation during batch operations + if not _should_invalidate_cache: + return + + _query_archetype_cache.clear() + cache_invalidated.emit() + + # Track invalidation stats (debug mode only) + if ECS.debug: + _cache_invalidation_count += 1 + _cache_invalidation_reasons[reason] = _cache_invalidation_reasons.get(reason, 0) + 1 + + +## Calculate archetype signature for an entity based on its components +## Uses the same hash function as queries for consistency +## An entity signature is just a query with all its components (no any/exclude) +func _calculate_entity_signature(entity: Entity) -> int: + # Get component resource paths + var comp_paths = entity.components.keys() + comp_paths.sort() # Sort paths for consistent ordering + + # Convert paths to Script objects using cached scripts (load once, reuse forever) + var comp_scripts = [] + for comp_path in comp_paths: + # Check cache first + if not _component_script_cache.has(comp_path): + # Load once and cache + var component = entity.components[comp_path] + _component_script_cache[comp_path] = component.get_script() + comp_scripts.append(_component_script_cache[comp_path]) + + # Use the SAME hash function as queries - entity is just "all components, no any/exclude" + # OPTIMIZATION: Removed enabled_marker from signature - now handled by bitset in archetype + var signature = QueryCacheKey.build(comp_scripts, [], []) + + return signature + + +## Get or create an archetype for the given signature and component types +func _get_or_create_archetype(signature: int, component_types: Array) -> Archetype: + var is_new = not archetypes.has(signature) + if is_new: + var archetype = Archetype.new(signature, component_types) + archetypes[signature] = archetype + _worldLogger.trace("Created new archetype: ", archetype) + + # ARCHETYPE OPTIMIZATION: Only invalidate cache when NEW archetype is created + # This is rare compared to entities moving between existing archetypes + _invalidate_cache("new_archetype_created") + + return archetypes[signature] + + +## Add entity to appropriate archetype (parallel system) +func _add_entity_to_archetype(entity: Entity) -> void: + # Calculate signature based on entity's components (enabled state now handled by bitset) + var signature = _calculate_entity_signature(entity) + + # Get component type paths for this entity + var comp_types = entity.components.keys() + + # Get or create archetype (no longer needs enabled filter value) + var archetype = _get_or_create_archetype(signature, comp_types) + + # Add entity to archetype + archetype.add_entity(entity) + entity_to_archetype[entity] = archetype + + _worldLogger.trace("Added entity ", entity.name, " to archetype: ", archetype) + + +## Remove entity from its current archetype +func _remove_entity_from_archetype(entity: Entity) -> bool: + if not entity_to_archetype.has(entity): + return false + + var archetype = entity_to_archetype[entity] + var removed = archetype.remove_entity(entity) + entity_to_archetype.erase(entity) + + # Clean up empty archetypes (optional - can keep them for reuse) + if archetype.is_empty(): + # Break circular references before removing + archetype.add_edges.clear() + archetype.remove_edges.clear() + archetypes.erase(archetype.signature) + _worldLogger.trace("Removed empty archetype: ", archetype) + # OPTIMIZATION: Only invalidate when archetype is actually removed from world + _invalidate_cache("empty_archetype_removed") + + return removed + + +## Fast path: Move entity when we already know which component was added/removed +## This avoids expensive set comparisons to find the difference +## Returns the new archetype the entity was moved to +func _move_entity_to_new_archetype_fast(entity: Entity, old_archetype: Archetype, comp_path: String, is_add: bool) -> Archetype: + # Try to use archetype edge for O(1) transition + var new_archetype: Archetype = null + + if is_add: + # Check if we have a cached edge for this component addition + new_archetype = old_archetype.get_add_edge(comp_path) + else: + # Check if we have a cached edge for this component removal + new_archetype = old_archetype.get_remove_edge(comp_path) + + # BUG FIX: If archetype retrieved from edge cache was removed from world.archetypes + # when it became empty, re-add it so queries can find it + if new_archetype != null and not archetypes.has(new_archetype.signature): + archetypes[new_archetype.signature] = new_archetype + _worldLogger.trace("Re-added archetype from edge cache: ", new_archetype) + + # If no cached edge, calculate signature and find/create archetype + if new_archetype == null: + var new_signature = _calculate_entity_signature(entity) + var comp_types = entity.components.keys() + new_archetype = _get_or_create_archetype(new_signature, comp_types) + + # Cache the edge for next time (archetype graph optimization) + if is_add: + old_archetype.set_add_edge(comp_path, new_archetype) + new_archetype.set_remove_edge(comp_path, old_archetype) + else: + old_archetype.set_remove_edge(comp_path, new_archetype) + new_archetype.set_add_edge(comp_path, old_archetype) + + # Remove from old archetype + old_archetype.remove_entity(entity) + + # Add to new archetype + new_archetype.add_entity(entity) + entity_to_archetype[entity] = new_archetype + + _worldLogger.trace("Moved entity ", entity.name, " from ", old_archetype, " to ", new_archetype) + + # Clean up empty old archetype + if old_archetype.is_empty(): + # Break circular references before removing + old_archetype.add_edges.clear() + old_archetype.remove_edges.clear() + archetypes.erase(old_archetype.signature) + + return new_archetype + + +## Move entity from one archetype to another (when components change) +## Uses archetype edges for O(1) transitions when possible +## NOTE: This slow path compares sets - only used when we don't know which component changed +func _move_entity_to_new_archetype(entity: Entity, old_archetype: Archetype) -> void: + # Determine which component was added/removed by comparing old archetype with current entity + var old_comp_set = {} + for comp_path in old_archetype.component_types: + old_comp_set[comp_path] = true + + var new_comp_set = {} + for comp_path in entity.components.keys(): + new_comp_set[comp_path] = true + + # Find the difference (added or removed component) + var added_comp: String = "" + var removed_comp: String = "" + + for comp_path in new_comp_set.keys(): + if not old_comp_set.has(comp_path): + added_comp = comp_path + break + + for comp_path in old_comp_set.keys(): + if not new_comp_set.has(comp_path): + removed_comp = comp_path + break + + # Try to use archetype edge for O(1) transition + var new_archetype: Archetype = null + + if added_comp != "": + # Check if we have a cached edge for this component addition + new_archetype = old_archetype.get_add_edge(added_comp) + elif removed_comp != "": + # Check if we have a cached edge for this component removal + new_archetype = old_archetype.get_remove_edge(removed_comp) + + # If no cached edge, calculate signature and find/create archetype + if new_archetype == null: + var new_signature = _calculate_entity_signature(entity) + var comp_types = entity.components.keys() + new_archetype = _get_or_create_archetype(new_signature, comp_types) + + # Cache the edge for next time (archetype graph optimization) + if added_comp != "": + old_archetype.set_add_edge(added_comp, new_archetype) + new_archetype.set_remove_edge(added_comp, old_archetype) + elif removed_comp != "": + old_archetype.set_remove_edge(removed_comp, new_archetype) + new_archetype.set_add_edge(removed_comp, old_archetype) + + # Remove from old archetype + old_archetype.remove_entity(entity) + + # Add to new archetype + new_archetype.add_entity(entity) + entity_to_archetype[entity] = new_archetype + + _worldLogger.trace("Moved entity ", entity.name, " from ", old_archetype, " to ", new_archetype) + + # Clean up empty old archetype + if old_archetype.is_empty(): + # Break circular references before removing + old_archetype.add_edges.clear() + old_archetype.remove_edges.clear() + archetypes.erase(old_archetype.signature) + +#endregion Utility Methods + +#region Debugger Support + + +## Handle messages from the editor debugger +func _handle_debugger_message(message: String, data: Array) -> bool: + if message == "set_system_active": + # Editor requested to toggle a system's active state + var system_id = data[0] + var new_active = data[1] + + # Find the system by instance ID + for sys in systems: + if sys.get_instance_id() == system_id: + sys.active = new_active + + # Send confirmation back to editor + GECSEditorDebuggerMessages.system_added(sys) + return true + + return false + elif message == "poll_entity": + # Editor requested a component poll for a specific entity + var entity_id = data[0] + _poll_entity_for_debugger(entity_id) + return true + elif message == "select_entity": + # Editor requested to select an entity in the scene tree + var entity_path = data[0] + print("GECS World: Received select_entity request for path: ", entity_path) + # Get the actual node to get its ObjectID + var node = get_node_or_null(entity_path) + if node: + var obj_id = node.get_instance_id() + var _class_name = node.get_class() + # The path needs to be an array of node names from root to target + var path_array = str(entity_path).split("/", false) + print(" Found node, sending inspect message") + print(" ObjectID: ", obj_id) + print(" Class: ", _class_name) + + if GECSEditorDebuggerMessages.can_send_message(): + # The scene:inspect_object format per Godot source code: + # [object_id (uint64), class_name (STRING), properties_array (ARRAY)] + # NO path_array! Just 3 elements total + # properties_array contains arrays of 6 elements each: + # [name (STRING), type (INT), hint (INT), hint_string (STRING), usage (INT), value (VARIANT)] + # Get actual properties from the node + var properties: Array = [] + var prop_list = node.get_property_list() + # Add properties (limit to avoid huge payload) + for i in range(min(20, prop_list.size())): + var prop = prop_list[i] + var prop_name: String = prop.name + var prop_type: int = prop.type + var prop_hint: int = prop.get("hint", 0) + var prop_hint_string: String = prop.get("hint_string", "") + var prop_usage: int = prop.usage + var prop_value = node.get(prop_name) + + var prop_info: Array = [prop_name, prop_type, prop_hint, prop_hint_string, prop_usage, prop_value] + properties.append(prop_info) + + # Message format: [object_id, class_name, properties] - only 3 elements! + var msg_data: Array = [obj_id, _class_name, properties] + print(" Sending scene:inspect_object: [", obj_id, ", ", _class_name, ", ", properties.size(), " props]") + EngineDebugger.send_message("scene:inspect_object", msg_data) + else: + print(" ERROR: Could not find node at path: ", entity_path) + return true + return false + + +## Poll a specific entity's components and send updates to the debugger +func _poll_entity_for_debugger(entity_id: int) -> void: + # Find the entity by instance ID + var entity: Entity = null + for ent in entities: + if ent.get_instance_id() == entity_id: + entity = ent + break + + if entity == null: + return + + # Re-send all component data with fresh serialize() calls + for comp_path in entity.components.keys(): + var comp = entity.components[comp_path] + if comp and comp is Resource: + # Send updated component data + GECSEditorDebuggerMessages.entity_component_added(entity, comp) + +#endregion Debugger Support diff --git a/addons/gecs/ecs/world.gd.uid b/addons/gecs/ecs/world.gd.uid new file mode 100644 index 0000000..3e4cd5a --- /dev/null +++ b/addons/gecs/ecs/world.gd.uid @@ -0,0 +1 @@ +uid://cdu5tlyk72uu4 diff --git a/addons/gecs/io/gecs_data.gd b/addons/gecs/io/gecs_data.gd new file mode 100644 index 0000000..cbbad83 --- /dev/null +++ b/addons/gecs/io/gecs_data.gd @@ -0,0 +1,9 @@ +class_name GecsData +extends Resource + +@export var version: String = "0.2" +@export var entities: Array[GecsEntityData] = [] + + +func _init(_entities: Array[GecsEntityData] = []): + entities = _entities diff --git a/addons/gecs/io/gecs_data.gd.uid b/addons/gecs/io/gecs_data.gd.uid new file mode 100644 index 0000000..37e9c75 --- /dev/null +++ b/addons/gecs/io/gecs_data.gd.uid @@ -0,0 +1 @@ +uid://pagmg5srhrnd diff --git a/addons/gecs/io/gecs_entity_data.gd b/addons/gecs/io/gecs_entity_data.gd new file mode 100644 index 0000000..3ca8fdf --- /dev/null +++ b/addons/gecs/io/gecs_entity_data.gd @@ -0,0 +1,18 @@ +class_name GecsEntityData +extends Resource + +@export var entity_name: String = "" +@export var scene_path: String = "" +@export var components: Array[Component] = [] +@export var relationships: Array[GecsRelationshipData] = [] +@export var auto_included: bool = false +@export var id: String = "" + + +func _init(_name: String = "", _scene_path: String = "", _components: Array[Component] = [], _relationships: Array[GecsRelationshipData] = [], _auto_included: bool = false, _id: String = ""): + entity_name = _name + scene_path = _scene_path + components = _components + relationships = _relationships + auto_included = _auto_included + id = _id diff --git a/addons/gecs/io/gecs_entity_data.gd.uid b/addons/gecs/io/gecs_entity_data.gd.uid new file mode 100644 index 0000000..f319d84 --- /dev/null +++ b/addons/gecs/io/gecs_entity_data.gd.uid @@ -0,0 +1 @@ +uid://cphey3uadg1ai diff --git a/addons/gecs/io/gecs_relationship_data.gd b/addons/gecs/io/gecs_relationship_data.gd new file mode 100644 index 0000000..b56d4f8 --- /dev/null +++ b/addons/gecs/io/gecs_relationship_data.gd @@ -0,0 +1,95 @@ +## GecsRelationshipData +## Resource class for serializing relationship data in GECS +## +## This class stores all the necessary information to recreate a [Relationship] +## during deserialization, including the relation component and target information. +class_name GecsRelationshipData +extends Resource + +## The relation component data (duplicated for serialization) +@export var relation_data: Component + +## The type of target this relationship points to +## Valid values: "Entity", "Component", "Script" +@export var target_type: String = "" + +## The id of the target entity (used when target_type is "Entity") +@export var target_entity_id: String = "" + +## The target component data (used when target_type is "Component") +@export var target_component_data: Component + +## The resource path of the target script (used when target_type is "Script") +@export var target_script_path: String = "" + + +## Constructor to create relationship data from a Relationship instance +func _init( + _relation_data: Component = null, + _target_type: String = "", + _target_entity_id: String = "", + _target_component_data: Component = null, + _target_script_path: String = "" +): + relation_data = _relation_data + target_type = _target_type + target_entity_id = _target_entity_id + target_component_data = _target_component_data + target_script_path = _target_script_path + +## Creates GecsRelationshipData from a Relationship instance +static func from_relationship(relationship: Relationship) -> GecsRelationshipData: + var data = GecsRelationshipData.new() + + # Store relation component (duplicate to avoid reference issues) + if relationship.relation: + data.relation_data = relationship.relation.duplicate(true) + + # Determine target type and store appropriate data + if relationship.target == null: + data.target_type = "null" + elif relationship.target is Entity: + data.target_type = "Entity" + data.target_entity_id = relationship.target.id + elif relationship.target is Component: + data.target_type = "Component" + data.target_component_data = relationship.target.duplicate(true) + elif relationship.target is Script: + data.target_type = "Script" + data.target_script_path = relationship.target.resource_path + else: + push_warning("GecsRelationshipData: Unknown target type: " + str(type_string(typeof(relationship.target)))) + data.target_type = "unknown" + + return data + + +## Recreates a Relationship from this data (requires entity mapping for Entity targets) +func to_relationship(entity_mapping: Dictionary = {}) -> Relationship: + var relationship = Relationship.new() + + # Restore relation component + if relation_data: + relationship.relation = relation_data.duplicate(true) + + # Restore target based on type + match target_type: + "null": + relationship.target = null + "Entity": + if target_entity_id in entity_mapping: + relationship.target = entity_mapping[target_entity_id] + else: + push_warning("GecsRelationshipData: Could not resolve entity with ID: " + target_entity_id) + return null + "Component": + if target_component_data: + relationship.target = target_component_data.duplicate(true) + "Script": + if target_script_path != "": + relationship.target = load(target_script_path) + _: + push_warning("GecsRelationshipData: Unknown target type during deserialization: " + target_type) + return null + + return relationship diff --git a/addons/gecs/io/gecs_relationship_data.gd.uid b/addons/gecs/io/gecs_relationship_data.gd.uid new file mode 100644 index 0000000..8a92e9d --- /dev/null +++ b/addons/gecs/io/gecs_relationship_data.gd.uid @@ -0,0 +1 @@ +uid://bbqc1v8555562 diff --git a/addons/gecs/io/io.gd b/addons/gecs/io/io.gd new file mode 100644 index 0000000..b7b6db1 --- /dev/null +++ b/addons/gecs/io/io.gd @@ -0,0 +1,219 @@ +## GECS IO Utility Class[br] +## +## Provides functions for generating UUIDs, serializing/deserializing [Entity]s to/from [GecsData], +## and saving/loading [GecsData] to/from files. +class_name GECSIO + +## Generates a custom GUID using random bytes.[br] +## The format uses 16 random bytes encoded to hex and formatted with hyphens. +static func uuid() -> String: + const BYTE_MASK: int = 0b11111111 + # 16 random bytes with the bytes on index 6 and 8 modified + var b = [ + randi() & BYTE_MASK, randi() & BYTE_MASK, randi() & BYTE_MASK, randi() & BYTE_MASK, + randi() & BYTE_MASK, randi() & BYTE_MASK, ((randi() & BYTE_MASK) & 0x0f) | 0x40, randi() & BYTE_MASK, + ((randi() & BYTE_MASK) & 0x3f) | 0x80, randi() & BYTE_MASK, randi() & BYTE_MASK, randi() & BYTE_MASK, + randi() & BYTE_MASK, randi() & BYTE_MASK, randi() & BYTE_MASK, randi() & BYTE_MASK, + ] + + return '%02x%02x%02x%02x-%02x%02x-%02x%02x-%02x%02x-%02x%02x%02x%02x%02x%02x' % [ + # low + b[0], b[1], b[2], b[3], + + # mid + b[4], b[5], + + # hi + b[6], b[7], + + # clock + b[8], b[9], + + # clock + b[10], b[11], b[12], b[13], b[14], b[15] + ] + +## Serialize a [QueryBuilder] of [Entity](s) to [GecsData] format.[br] +## Optionally takes a [GECSSerializeConfig] to customize what gets serialized. +static func serialize(query: QueryBuilder, config: GECSSerializeConfig = null) -> GecsData: + return serialize_entities(query.execute() as Array[Entity], config) + +## Serialize a list of [Entity](s) to [GecsData] format.[br] +## Optionally takes a [GECSSerializeConfig] to customize what gets serialized. +static func serialize_entities(entities: Array, config: GECSSerializeConfig = null) -> GecsData: + # Pass 1: Serialize entities from original query + var entity_data_array: Array[GecsEntityData] = [] + var processed_entities: Dictionary = {} # id -> bool + var entity_id_mapping: Dictionary = {} # id -> Entity + for entity in entities: + var effective_config = _resolve_config(entity, config) + var entity_data = _serialize_entity(entity, false, effective_config) + entity_data_array.append(entity_data) + processed_entities[entity.id] = true + entity_id_mapping[entity.id] = entity + + # Pass 2: Scan relationships and auto-include referenced entities (if enabled) + var entities_to_check = entities.duplicate() + var check_index = 0 + + while check_index < entities_to_check.size(): + var entity = entities_to_check[check_index] + var effective_config = _resolve_config(entity, config) + + # Only proceed if config allows including related entities + if effective_config.include_related_entities: + # Check all relationships of this entity + for relationship in entity.relationships: + if relationship.target is Entity: + var target_entity = relationship.target as Entity + var target_id = target_entity.id + + # If this entity hasn't been processed yet, auto-include it + if not processed_entities.has(target_id): + var target_config = _resolve_config(target_entity, config) + var auto_entity_data = _serialize_entity(target_entity, true, target_config) + entity_data_array.append(auto_entity_data) + processed_entities[target_id] = true + entity_id_mapping[target_id] = target_entity + + # Add to list for further relationship checking + entities_to_check.append(target_entity) + + check_index += 1 + + return GecsData.new(entity_data_array) + +## Save [GecsData] to a file at the specified path.[br] +## If binary is true, saves in binary format (.res), otherwise text format (.tres). +static func save(gecs_data: GecsData, filepath: String, binary: bool = false) -> bool: + var final_path = filepath + var flags = 0 + + if binary: + # Convert .tres to .res for binary format + final_path = filepath.replace(".tres", ".res") + flags = ResourceSaver.FLAG_COMPRESS # Binary format uses no flags, .res extension determines format + # else: text format (default flags = 0) + + var result = ResourceSaver.save(gecs_data, final_path, flags) + if result != OK: + push_error("GECS save: Failed to save resource to: " + final_path) + return false + return true + +## Load and deserialize [Entity](s) from a file at the specified path.[br] +## Supports both binary (.res) and text (.tres) formats, tries binary first. +static func deserialize(gecs_filepath: String) -> Array[Entity]: + # Try binary first (.res), then text (.tres) + var binary_path = gecs_filepath.replace(".tres", ".res") + + if ResourceLoader.exists(binary_path): + return _load_from_path(binary_path) + elif ResourceLoader.exists(gecs_filepath): + return _load_from_path(gecs_filepath) + else: + push_error("GECS deserialize: File not found: " + gecs_filepath) + return [] + +## Deserialize [GecsData] into a list of [Entity](s).[br] +## This can be used so you can serialize entities to GECS Data and then Deserailize that [GecsSData] later +static func deserialize_gecs_data(gecs_data: GecsData) -> Array[Entity]: + var entities: Array[Entity] = [] + var id_to_entity: Dictionary = {} # id -> Entity + + # Pass 1: Create all entities and build ID mapping + for entity_data in gecs_data.entities: + var entity = _deserialize_entity(entity_data) + entities.append(entity) + id_to_entity[entity.id] = entity + + # Pass 2: Restore relationships using ID mapping + for i in entities.size(): + var entity = entities[i] + var entity_data = gecs_data.entities[i] + + # Restore relationships + for rel_data in entity_data.relationships: + var relationship = rel_data.to_relationship(id_to_entity) + if relationship != null: + entity.add_relationship(relationship) + # Note: Invalid relationships are skipped with warning logged in to_relationship() + + return entities + +## Helper function to resolve the effective configuration for an entity +## Priority: provided_config > entity.serialize_config > world.default_serialize_config > fallback +static func _resolve_config(entity: Entity, provided_config: GECSSerializeConfig) -> GECSSerializeConfig: + if provided_config != null: + return provided_config + return entity.get_effective_serialize_config() + +## Helper function to serialize a single entity with its components and relationships +static func _serialize_entity(entity: Entity, auto_included: bool, config: GECSSerializeConfig) -> GecsEntityData: + # Serialize components (filtered by config) + var components: Array[Component] = [] + for component in entity.components.values(): + if config.should_include_component(component): + # Duplicate the component to avoid modifying the original + components.append(component.duplicate(true)) + + # Serialize relationships (if enabled by config) + var relationships: Array[GecsRelationshipData] = [] + if config.include_relationships: + for relationship in entity.relationships: + var rel_data = GecsRelationshipData.from_relationship(relationship) + relationships.append(rel_data) + + return GecsEntityData.new( + entity.name, + entity.scene_file_path if entity.scene_file_path != "" else "", + components, + relationships, + auto_included, + entity.id + ) + +## Helper function to load and deserialize entities from a given file path +static func _load_from_path(file_path: String) -> Array[Entity]: + print("GECS _load_from_path: Loading file: ", file_path) + var gecs_data = load(file_path) as GecsData + if not gecs_data: + push_error("GECS deserialize: Could not load GecsData resource: " + file_path) + return [] + + print("GECS _load_from_path: Loaded GecsData with ", gecs_data.entities.size(), " entities") + + return deserialize_gecs_data(gecs_data) + +## Helper function to deserialize a single entity with its components and uuid +static func _deserialize_entity(entity_data: GecsEntityData) -> Entity: + var entity: Entity + + # Check if this entity is a prefab (has scene file) + if entity_data.scene_path != "": + var scene_path = entity_data.scene_path + if ResourceLoader.exists(scene_path): + var packed_scene = load(scene_path) as PackedScene + if packed_scene: + entity = packed_scene.instantiate() as Entity + else: + push_warning("GECS deserialize: Could not load scene: " + scene_path + ", creating new entity") + entity = Entity.new() + else: + push_warning("GECS deserialize: Scene file not found: " + scene_path + ", creating new entity") + entity = Entity.new() + else: + # Create new entity + entity = Entity.new() + + # Set entity name + entity.name = entity_data.entity_name + + # Restore id (important: set this directly) + entity.id = entity_data.id + + # Add components (they're already properly typed as Component resources) + for component in entity_data.components: + entity.add_component(component.duplicate(true)) + + return entity diff --git a/addons/gecs/io/io.gd.uid b/addons/gecs/io/io.gd.uid new file mode 100644 index 0000000..6130d13 --- /dev/null +++ b/addons/gecs/io/io.gd.uid @@ -0,0 +1 @@ +uid://drhirabcyqlvk diff --git a/addons/gecs/io/serialize_config.gd b/addons/gecs/io/serialize_config.gd new file mode 100644 index 0000000..b8c17b3 --- /dev/null +++ b/addons/gecs/io/serialize_config.gd @@ -0,0 +1,33 @@ +## This config defines what to include when serializing +## It can be appled to the world as a whole or to specific entities +## This way you can define project level defaults and override them for specific cases +class_name GECSSerializeConfig +extends Resource + +## Include all components (true) or only specific components (false) +@export var include_all_components: bool = true +## Which component types to include in serialization (only used when include_all_components = false) +@export var components: Array = [] +## Whether to include relationships in serialization +@export var include_relationships: bool = true +## Whether to include related entities in serialization (Related entities are entities referenced by relationships from the serialized entities) +@export var include_related_entities: bool = true + + +## Helper method to determine if a component should be included in serialization +func should_include_component(component: Component) -> bool: + var comp_type = component.get_script() + return include_all_components or components.any(func(type): return comp_type == type) + + +## Merge this config with another config, with the other config taking priority +func merge_with(other: GECSSerializeConfig) -> GECSSerializeConfig: + if other == null: + return self + + var merged = GECSSerializeConfig.new() + merged.include_all_components = other.include_all_components + merged.components = other.components.duplicate() + merged.include_relationships = other.include_relationships + merged.include_related_entities = other.include_related_entities + return merged diff --git a/addons/gecs/io/serialize_config.gd.uid b/addons/gecs/io/serialize_config.gd.uid new file mode 100644 index 0000000..f6197ad --- /dev/null +++ b/addons/gecs/io/serialize_config.gd.uid @@ -0,0 +1 @@ +uid://cf84mkp0nv2mk diff --git a/addons/gecs/lib/array_extensions.gd b/addons/gecs/lib/array_extensions.gd new file mode 100644 index 0000000..e69973b --- /dev/null +++ b/addons/gecs/lib/array_extensions.gd @@ -0,0 +1,191 @@ +class_name ArrayExtensions + +## Intersects two arrays of entities.[br] +## In common terms, use this to find items appearing in both arrays. +## [param array1] The first array to intersect.[br] +## [param array2] The second array to intersect.[br] +## [b]return Array[/b] The intersection of the two arrays. +static func intersect(array1: Array, array2: Array) -> Array: + # Optimize by using the smaller array for lookup + if array1.size() > array2.size(): + return intersect(array2, array1) + + # Use dictionary for O(1) lookup instead of O(n) Array.has() + var lookup := {} + for entity in array2: + lookup[entity] = true + + var result: Array = [] + for entity in array1: + if lookup.has(entity): + result.append(entity) + return result + +## Unions two arrays of entities.[br] +## In common terms, use this to combine items without duplicates.[br] +## [param array1] The first array to union.[br] +## [param array2] The second array to union.[br] +## [b]return Array[/b] The union of the two arrays. +static func union(array1: Array, array2: Array) -> Array: + # Use dictionary to track uniqueness for O(1) lookups + var seen := {} + var result: Array = [] + + # Add all from array1 + for entity in array1: + if not seen.has(entity): + seen[entity] = true + result.append(entity) + + # Add unique items from array2 + for entity in array2: + if not seen.has(entity): + seen[entity] = true + result.append(entity) + + return result + +## Differences two arrays of entities.[br] +## In common terms, use this to find items only in the first array.[br] +## [param array1] The first array to difference.[br] +## [param array2] The second array to difference.[br] +## [b]return Array[/b] The difference of the two arrays (entities in array1 not in array2). +static func difference(array1: Array, array2: Array) -> Array: + # Use dictionary for O(1) lookup instead of O(n) Array.has() + var lookup := {} + for entity in array2: + lookup[entity] = true + + var result: Array = [] + for entity in array1: + if not lookup.has(entity): + result.append(entity) + return result + +## systems_by_group is a dictionary of system groups and their systems +## { "Group1": [SystemA, SystemB], "Group2": [SystemC, SystemD] } +static func topological_sort(systems_by_group: Dictionary) -> void: + # Iterate over each group key in 'systems_by_group' + for group in systems_by_group.keys(): + var systems = systems_by_group[group] + # If the group has 1 or fewer systems, no sorting is needed + if systems.size() <= 1: + continue + + # Create two data structures: + # 1) adjacency: stores, for a given system, which systems must come after it + # 2) indegree: tracks how many "prerequisite" systems each system has + var adjacency = {} + var indegree = {} + var wildcard_front = [] + var wildcard_back = [] + for s in systems: + adjacency[s] = [] + indegree[s] = 0 + + # Build adjacency and indegree counts based on dependencies returned by s.deps() + for s in systems: + var deps_dict = s.deps() + + # Check for Runs.Before array on s + # If present, each item in s.Runs.Before means "s must run before that item" + # So we add the item to adjacency[s], and increment the item's indegree + # If item is null or ECS.wildcard, we treat it as "run before everything" by pushing 's' onto wildcard_front + if deps_dict.has(System.Runs.Before): + for b in deps_dict[System.Runs.Before]: + if b == null: + # ECS.wildcard AKA 'null' means s should run before all systems + wildcard_front.append(s) + else: + # Find system instance that matches the dependency type + var target_system = _find_system_by_type(systems, b) + if target_system: + # Normal dependency within the group + adjacency[s].append(target_system) + indegree[target_system] += 1 + + # Check for Runs.After array on s + # If present, each item in s.Runs.After means "s must run after that item" + # So we add 's' to adjacency[item], and increment s's indegree + # If item is null or ECS.wildcard, we treat it as "run after everything" by pushing 's' onto wildcard_back + if deps_dict.has(System.Runs.After): + for a in deps_dict[System.Runs.After]: + if a == null: + # ECS.wildcard AKA 'null' means s should run after all systems + wildcard_back.append(s) + else: + # Find system instance that matches the dependency type + var dependency_system = _find_system_by_type(systems, a) + if dependency_system: + # Normal dependency within the group + adjacency[dependency_system].append(s) + indegree[s] += 1 + + # Kahn's Algorithm begins: + # 1) Insert all systems with zero indegree into a queue + # 2) Pop from the queue, add to sorted_result + # 3) Decrement indegree for each adjacent system + # 4) Any adjacent system that reaches zero indegree is appended to the queue + var queue = [] + + # Adjust for wildcard_front and wildcard_back: + # wildcard_front: s runs before everything -> point s -> other + for w in wildcard_front: + for other in systems: + if other != w and not adjacency[w].has(other): + adjacency[w].append(other) + indegree[other] += 1 + + # wildcard_back: s runs after everything -> point other -> s + for w in wildcard_back: + for other in systems: + if other != w and not adjacency[other].has(w): + adjacency[other].append(w) + indegree[w] += 1 + + # Collect all systems with zero indegree into the queue as our starting point + for s in systems: + if indegree[s] == 0: + queue.append(s) + + var sorted_result = [] + + # While there are systems with no remaining prerequisites + while queue.size() > 0: + var current = queue.pop_front() + # Add that system to the sorted list + sorted_result.append(current) + # For each system that depends on 'current' + for nxt in adjacency[current]: + # Decrement its indegree because 'current' is now accounted for + indegree[nxt] -= 1 + # If it has no more prerequisites, add it to the queue + if indegree[nxt] == 0: + queue.append(nxt) + + # If we successfully placed all systems, overwrite the original array with sorted_result + if sorted_result.size() == systems.size(): + systems_by_group[group] = sorted_result + else: + assert( + false, + ( + "Topological sort failed for group '%s'. Possible cycle or mismatch in dependencies." + % group + ) + ) + # Otherwise, we found a cycle or mismatch. Fallback to the original unsorted array + systems_by_group[group] = systems + + # The function modifies 'systems_by_group' in-place with a topologically sorted order + +## Helper function to find a system instance by its type/class +static func _find_system_by_type(systems: Array, target_type) -> System: + for system in systems: + # Check if the system is an instance of the target type + if system.get_script() == target_type: + return system + # Also check class name matching for backward compatibility + if system.get_script() and system.get_script().get_global_name() == str(target_type).get_file().get_basename(): + return system + return null diff --git a/addons/gecs/lib/array_extensions.gd.uid b/addons/gecs/lib/array_extensions.gd.uid new file mode 100644 index 0000000..28838c6 --- /dev/null +++ b/addons/gecs/lib/array_extensions.gd.uid @@ -0,0 +1 @@ +uid://h7vbvqjotxmf diff --git a/addons/gecs/lib/component_query_matcher.gd b/addons/gecs/lib/component_query_matcher.gd new file mode 100644 index 0000000..efc0141 --- /dev/null +++ b/addons/gecs/lib/component_query_matcher.gd @@ -0,0 +1,108 @@ +## ComponentQueryMatcher +## Static utility for matching components against query criteria. +## Used by QueryBuilder and Relationship systems for consistent component filtering. +## +## Supports comparison operators (_gt, _lt, _eq), array membership (_in, _nin), +## and custom functions for property-based filtering. +## +## [b]Query Operators:[/b] +## [br]• [b]_eq:[/b] Equal [code]property == value[/code] +## [br]• [b]_ne:[/b] Not equal [code]property != value[/code] +## [br]• [b]_gt:[/b] Greater than [code]property > value[/code] +## [br]• [b]_lt:[/b] Less than [code]property < value[/code] +## [br]• [b]_gte:[/b] Greater or equal [code]property >= value[/code] +## [br]• [b]_lte:[/b] Less or equal [code]property <= value[/code] +## [br]• [b]_in:[/b] In array [code]property in [values][/code] +## [br]• [b]_nin:[/b] Not in array [code]property not in [values][/code] +## [br]• [b]func:[/b] Custom function [code]func(property) -> bool[/code] +## +## [codeblock] +## var component = C_Health.new(75) +## var query = {"health": {"_gte": 50, "_lte": 100}} +## var matches = ComponentQueryMatcher.matches_query(component, query) +## +## # Custom functions +## var func_query = {"level": {"func": func(level): return level >= 40}} +## +## # Array membership +## var type_query = {"type": {"_in": ["fire", "ice"]}} +## [/codeblock] +class_name ComponentQueryMatcher +extends RefCounted + +## Checks if a component matches the given query criteria. +## All query operators must pass for the component to match. +## +## [param component]: The [Component] to evaluate +## [param query]: Dictionary mapping property names to operator dictionaries +## [return]: [code]true[/code] if all criteria match, [code]false[/code] otherwise +## +## Returns [code]true[/code] for empty queries. Returns [code]false[/code] if any +## property doesn't exist or any operator fails. +static func matches_query(component: Component, query: Dictionary) -> bool: + if query.is_empty(): + return true + + for property in query: + # Check if property exists (can't use truthiness check because 0, false, etc. are valid values) + if not property in component: + return false + + var property_value = component.get(property) + var property_query = query[property] + + for operator in property_query: + match operator: + "func": + if not property_query[operator].call(property_value): + return false + "_eq": + if property_value != property_query[operator]: + return false + "_gt": + if property_value <= property_query[operator]: + return false + "_lt": + if property_value >= property_query[operator]: + return false + "_gte": + if property_value < property_query[operator]: + return false + "_lte": + if property_value > property_query[operator]: + return false + "_ne": + if property_value == property_query[operator]: + return false + "_nin": + if property_value in property_query[operator]: + return false + "_in": + if not (property_value in property_query[operator]): + return false + + return true + +## Separates component types from query dictionaries in a mixed array. +## Used by QueryBuilder to process component lists that may contain queries. +## +## [param components]: Array of [Component] classes and/or query dictionaries +## [return]: Dictionary with [code]"components"[/code] and [code]"queries"[/code] arrays +## +## Regular components get empty query dictionaries. Query dictionaries are +## split into their component type and criteria. +static func process_component_list(components: Array) -> Dictionary: + var result := {"components": [], "queries": []} + + for component in components: + if component is Dictionary: + # Handle component query case + for component_type in component: + result.components.append(component_type) + result.queries.append(component[component_type]) + else: + # Handle regular component case + result.components.append(component) + result.queries.append({}) # Empty query for regular components (matches all) + + return result diff --git a/addons/gecs/lib/component_query_matcher.gd.uid b/addons/gecs/lib/component_query_matcher.gd.uid new file mode 100644 index 0000000..2199f57 --- /dev/null +++ b/addons/gecs/lib/component_query_matcher.gd.uid @@ -0,0 +1 @@ +uid://beqw44pppbpl diff --git a/addons/gecs/lib/gecs_settings.gd b/addons/gecs/lib/gecs_settings.gd new file mode 100644 index 0000000..4355013 --- /dev/null +++ b/addons/gecs/lib/gecs_settings.gd @@ -0,0 +1,26 @@ +class_name GecsSettings +extends Node + +const SETTINGS_LOG_LEVEL = "gecs/settings/log_level" +const SETTINGS_DEBUG_MODE = "gecs/settings/debug_mode" + +const project_settings = { + "log_level": + { + "path": SETTINGS_LOG_LEVEL, + "default_value": GECSLogger.LogLevel.ERROR, + "type": TYPE_INT, + "hint": PROPERTY_HINT_ENUM, + "hint_string": "TRACE,DEBUG,INFO,WARNING,ERROR", + "doc": "What log level GECS should log at.", + }, + "debug_mode": + { + "path": SETTINGS_DEBUG_MODE, + "default_value": false, + "type": TYPE_BOOL, + "hint": PROPERTY_HINT_NONE, + "hint_string": "", + "doc": "Enable debug mode for GECS operations. Enables editor debugger integration but impacts performance significantly.", + } +} diff --git a/addons/gecs/lib/gecs_settings.gd.uid b/addons/gecs/lib/gecs_settings.gd.uid new file mode 100644 index 0000000..6acd9aa --- /dev/null +++ b/addons/gecs/lib/gecs_settings.gd.uid @@ -0,0 +1 @@ +uid://buvg6dnpqcnys diff --git a/addons/gecs/lib/logger.gd b/addons/gecs/lib/logger.gd new file mode 100644 index 0000000..c17c395 --- /dev/null +++ b/addons/gecs/lib/logger.gd @@ -0,0 +1,90 @@ +## Simplified Logger for GECS +class_name GECSLogger +extends RefCounted + +const disabled := true + +enum LogLevel {TRACE, DEBUG, INFO, WARNING, ERROR} + +var current_level: LogLevel = ProjectSettings.get_setting(GecsSettings.SETTINGS_LOG_LEVEL, LogLevel.ERROR) +var current_domain: String = "" + + +func set_level(level: LogLevel): + current_level = level + + +func domain(domain_name: String) -> GECSLogger: + current_domain = domain_name + return self + + +func log(level: LogLevel, msg = ""): + if disabled: + return + var level_name: String + if level >= current_level: + match level: + LogLevel.TRACE: + level_name = "TRACE" + LogLevel.DEBUG: + level_name = "DEBUG" + LogLevel.INFO: + level_name = "INFO" + LogLevel.WARNING: + level_name = "WARNING" + LogLevel.ERROR: + level_name = "ERROR" + _: + level_name = "UNKNOWN" + print("%s [%s]: %s" % [current_domain, level_name, msg]) + + +func trace(msg = "", arg1 = null, arg2 = null, arg3 = null, arg4 = null, arg5 = null): + self.log(LogLevel.TRACE, concatenate_msg_and_args(msg, arg1, arg2, arg3, arg4, arg5)) + + +func debug(msg = "", arg1 = null, arg2 = null, arg3 = null, arg4 = null, arg5 = null): + self.log(LogLevel.DEBUG, concatenate_msg_and_args(msg, arg1, arg2, arg3, arg4, arg5)) + + +func info(msg = "", arg1 = null, arg2 = null, arg3 = null, arg4 = null, arg5 = null): + self.log(LogLevel.INFO, concatenate_msg_and_args(msg, arg1, arg2, arg3, arg4, arg5)) + + +func warning(msg = "", arg1 = null, arg2 = null, arg3 = null, arg4 = null, arg5 = null): + self.log(LogLevel.WARNING, concatenate_msg_and_args(msg, arg1, arg2, arg3, arg4, arg5)) + + +func error(msg = "", arg1 = null, arg2 = null, arg3 = null, arg4 = null, arg5 = null): + self.log(LogLevel.ERROR, concatenate_msg_and_args(msg, arg1, arg2, arg3, arg4, arg5)) + +## Concatenates all given args into one single string, in consecutive order starting with 'msg'.[br] +## Stolen from Loggie +static func concatenate_msg_and_args( + msg: Variant, + arg1: Variant = null, + arg2: Variant = null, + arg3: Variant = null, + arg4: Variant = null, + arg5: Variant = null, + arg6: Variant = null +) -> String: + var final_msg = convert_to_string(msg) + var arguments = [arg1, arg2, arg3, arg4, arg5, arg6] + for arg in arguments: + if arg != null: + final_msg += (" " + convert_to_string(arg)) + return final_msg + +## Converts [param something] into a string.[br] +## If [param something] is a Dictionary, uses a special way to convert it into a string.[br] +## You can add more exceptions and rules for how different things are converted to strings here.[br] +## Stolen from Loggie +static func convert_to_string(something: Variant) -> String: + var result: String + if something is Dictionary: + result = JSON.new().stringify(something, " ", false, true) + else: + result = str(something) + return result diff --git a/addons/gecs/lib/logger.gd.uid b/addons/gecs/lib/logger.gd.uid new file mode 100644 index 0000000..7f9e974 --- /dev/null +++ b/addons/gecs/lib/logger.gd.uid @@ -0,0 +1 @@ +uid://betmoqpwcq0wc diff --git a/addons/gecs/lib/set.gd b/addons/gecs/lib/set.gd new file mode 100644 index 0000000..fc9756d --- /dev/null +++ b/addons/gecs/lib/set.gd @@ -0,0 +1,321 @@ +## Set is Mathematical set data structure for collections of unique values.[br] +## +## Built on Dictionary for O(1) membership testing. Used throughout GECS for +## entity filtering and component indexing. +## +## Supports standard set operations like union, intersection, and difference. +## No inherent ordering - elements are stored by hash. +## +## [codeblock] +## var numbers = Set.new([1, 2, 3, 4, 5]) +## numbers.add(6) +## print(numbers.has(3)) # true +## +## var set_a = Set.new([1, 2, 3, 4]) +## var set_b = Set.new([3, 4, 5, 6]) +## var intersection = set_a.intersect(set_b) # [3, 4] +## [/codeblock] +class_name Set +extends RefCounted + +## Internal storage using Dictionary keys for O(1) average-case operations. +## Values in the dictionary are always [code]true[/code] and ignored. +var _data: Dictionary = {} + + +## Initializes a new Set from Array, Dictionary keys, or another Set. +## [param data]: Optional initial data. Duplicates are automatically removed. +func _init(data = null) -> void: + if data: + if data is Array: + # Add array elements, automatically deduplicating + for value in data: + _data[value] = true + elif data is Set: + # Copy from another set + for value in data._data.keys(): + _data[value] = true + elif data is Dictionary: + # Use dictionary keys as set elements + for key in data.keys(): + _data[key] = true + +#region Basic Set Operations + + +## Adds a value to the set. Has no effect if the value is already present. +## [param value]: The value to add to the set. Can be any hashable type. +## +## [b]Time Complexity:[/b] O(1) average case +## [codeblock] +## var my_set = Set.new([1, 2, 3]) +## my_set.add(4) # Set now contains [1, 2, 3, 4] +## my_set.add(2) # No change, 2 already exists +## [/codeblock] +func add(value) -> void: + _data[value] = true + + +## Removes a value from the set. Has no effect if the value is not present. +## [param value]: The value to remove from the set +## +## [b]Time Complexity:[/b] O(1) average case +## [codeblock] +## var my_set = Set.new([1, 2, 3, 4]) +## my_set.erase(3) # Set now contains [1, 2, 4] +## my_set.erase(5) # No change, 5 doesn't exist +## [/codeblock] +func erase(value) -> void: + _data.erase(value) + + +## Tests whether a value exists in the set. +## [param value]: The value to test for membership +## [return]: [code]true[/code] if the value exists in the set, [code]false[/code] otherwise +## +## [b]Time Complexity:[/b] O(1) average case +## [codeblock] +## var my_set = Set.new(["apple", "banana", "cherry"]) +## print(my_set.has("banana")) # true +## print(my_set.has("grape")) # false +## [/codeblock] +func has(value) -> bool: + return _data.has(value) + + +## Removes all elements from the set, making it empty. +## [b]Time Complexity:[/b] O(1) +## [codeblock] +## var my_set = Set.new([1, 2, 3, 4, 5]) +## my_set.clear() +## print(my_set.is_empty()) # true +## [/codeblock] +func clear() -> void: + _data.clear() + + +## Returns the number of elements in the set. +## [return]: Integer count of unique elements in the set +## +## [b]Time Complexity:[/b] O(1) +## [codeblock] +## var my_set = Set.new(["a", "b", "c", "a", "b"]) # Duplicates ignored +## print(my_set.size()) # 3 +## [/codeblock] +func size() -> int: + return _data.size() + + +## Tests whether the set contains no elements. +## [return]: [code]true[/code] if the set is empty, [code]false[/code] otherwise +## +## [b]Time Complexity:[/b] O(1) +## [codeblock] +## var empty_set = Set.new() +## var filled_set = Set.new([1, 2, 3]) +## print(empty_set.is_empty()) # true +## print(filled_set.is_empty()) # false +## [/codeblock] +func is_empty() -> bool: + return _data.is_empty() + + +## Returns all elements in the set as an Array. +## The order of elements is not guaranteed and may vary between calls. +## [return]: Array containing all set elements +## +## [b]Time Complexity:[/b] O(n) where n is the number of elements +## [codeblock] +## var my_set = Set.new([3, 1, 4, 1, 5]) +## var elements = my_set.values() # [1, 3, 4, 5] (order may vary) +## [/codeblock] +func values() -> Array: + return _data.keys() + +#endregion + +#region Set Algebra Operations + + +## Returns the union of this set with another set (A ∪ B). +## Creates a new set containing all elements that exist in either set. +## [param other]: The other set to union with +## [return]: New [Set] containing all elements from both sets +## +## [b]Time Complexity:[/b] O(|A| + |B|) where |A| and |B| are set sizes +## [codeblock] +## var set_a = Set.new([1, 2, 3]) +## var set_b = Set.new([3, 4, 5]) +## var union_set = set_a.union(set_b) # Contains [1, 2, 3, 4, 5] +## [/codeblock] +func union(other: Set) -> Set: + var result = Set.new() + result._data = _data.duplicate() + for key in other._data.keys(): + result._data[key] = true + return result + + +## Returns the intersection of this set with another set (A ∩ B). +## Creates a new set containing only elements that exist in both sets. +## Automatically optimizes by iterating over the smaller set. +## [param other]: The other set to intersect with +## [return]: New [Set] containing elements common to both sets +## +## [b]Time Complexity:[/b] O(min(|A|, |B|)) - optimized for smaller set +## [codeblock] +## var set_a = Set.new([1, 2, 3, 4]) +## var set_b = Set.new([3, 4, 5, 6]) +## var intersection = set_a.intersect(set_b) # Contains [3, 4] +## [/codeblock] +func intersect(other: Set) -> Set: + # Optimization: iterate over smaller set for better performance + if other.size() < _data.size(): + return other.intersect(self ) + + var result = Set.new() + for key in _data.keys(): + if other._data.has(key): + result._data[key] = true + return result + + +## Returns the difference of this set minus another set (A - B). +## Creates a new set containing elements in this set but not in the other. +## [param other]: The set whose elements to exclude +## [return]: New [Set] containing elements only in this set +## +## [b]Time Complexity:[/b] O(|A|) where |A| is the size of this set +## [codeblock] +## var set_a = Set.new([1, 2, 3, 4]) +## var set_b = Set.new([3, 4, 5, 6]) +## var difference = set_a.difference(set_b) # Contains [1, 2] +## [/codeblock] +func difference(other: Set) -> Set: + var result = Set.new() + for key in _data.keys(): + if not other._data.has(key): + result._data[key] = true + return result + + +## Returns the symmetric difference of this set with another set (A ⊕ B). +## Creates a new set containing elements in either set, but not in both. +## Equivalent to (A - B) ∪ (B - A). +## [param other]: The other set for symmetric difference +## [return]: New [Set] containing elements in exactly one of the two sets +## +## [b]Time Complexity:[/b] O(|A| + |B|) +## [codeblock] +## var set_a = Set.new([1, 2, 3, 4]) +## var set_b = Set.new([3, 4, 5, 6]) +## var sym_diff = set_a.symmetric_difference(set_b) # Contains [1, 2, 5, 6] +## [/codeblock] +func symmetric_difference(other: Set) -> Set: + var result = Set.new() + # Add elements from this set that aren't in other + for key in _data.keys(): + if not other._data.has(key): + result._data[key] = true + # Add elements from other set that aren't in this set + for key in other._data.keys(): + if not _data.has(key): + result._data[key] = true + return result + +#endregion + +#region Set Relationship Testing + + +## Tests whether this set is a subset of another set (A ⊆ B). +## Returns [code]true[/code] if every element in this set also exists in the other set. +## [param other]: The potential superset to test against +## [return]: [code]true[/code] if this set is a subset of other, [code]false[/code] otherwise +## +## [b]Time Complexity:[/b] O(|A|) where |A| is the size of this set +## [codeblock] +## var small_set = Set.new([1, 2]) +## var large_set = Set.new([1, 2, 3, 4, 5]) +## print(small_set.is_subset(large_set)) # true +## print(large_set.is_subset(small_set)) # false +## [/codeblock] +func is_subset(other: Set) -> bool: + for key in _data.keys(): + if not other._data.has(key): + return false + return true + + +## Tests whether this set is a superset of another set (A ⊇ B). +## Returns [code]true[/code] if this set contains every element from the other set. +## [param other]: The potential subset to test +## [return]: [code]true[/code] if this set is a superset of other, [code]false[/code] otherwise +## +## [b]Time Complexity:[/b] O(|B|) where |B| is the size of the other set +## [codeblock] +## var large_set = Set.new([1, 2, 3, 4, 5]) +## var small_set = Set.new([2, 4]) +## print(large_set.is_superset(small_set)) # true +## [/codeblock] +func is_superset(other: Set) -> bool: + return other.is_subset(self ) + + +## Tests whether this set contains exactly the same elements as another set (A = B). +## Two sets are equal if they have the same size and this set is a subset of the other. +## [param other]: The set to compare for equality +## [return]: [code]true[/code] if sets contain identical elements, [code]false[/code] otherwise +## +## [b]Time Complexity:[/b] O(min(|A|, |B|)) - fails fast on size mismatch +## [codeblock] +## var set_a = Set.new([1, 2, 3]) +## var set_b = Set.new([3, 1, 2]) # Order doesn't matter +## var set_c = Set.new([1, 2, 3, 4]) +## print(set_a.is_equal(set_b)) # true +## print(set_a.is_equal(set_c)) # false +## [/codeblock] +func is_equal(other) -> bool: + # Quick size check for early exit + if _data.size() != other._data.size(): + return false + return self.is_subset(other) + +#endregion + +#region Utility Methods + + +## Creates a shallow copy of this set. +## The returned set is independent - modifications to either set won't affect the other. +## However, if the set contains reference types, the references are shared. +## [return]: New [Set] containing the same elements +## +## [b]Time Complexity:[/b] O(n) where n is the number of elements +## [codeblock] +## var original = Set.new([1, 2, 3]) +## var copy = original.duplicate() +## copy.add(4) # Only affects copy +## print(original.size()) # 3 +## print(copy.size()) # 4 +## [/codeblock] +func duplicate() -> Set: + var result = Set.new() + result._data = _data.duplicate() + return result + + +## Converts the set to an Array containing all elements. +## This is an alias for [method values] provided for API consistency. +## The order of elements is not guaranteed. +## [return]: Array containing all set elements +## +## [b]Time Complexity:[/b] O(n) where n is the number of elements +## [codeblock] +## var my_set = Set.new(["x", "y", "z"]) +## var array = my_set.to_array() # ["x", "y", "z"] (order may vary) +## [/codeblock] +func to_array() -> Array: + return _data.keys() + +#endregion diff --git a/addons/gecs/lib/set.gd.uid b/addons/gecs/lib/set.gd.uid new file mode 100644 index 0000000..3aad0a6 --- /dev/null +++ b/addons/gecs/lib/set.gd.uid @@ -0,0 +1 @@ +uid://oqdcekkxyt52 diff --git a/addons/gecs/lib/system_group.gd b/addons/gecs/lib/system_group.gd new file mode 100644 index 0000000..3098be0 --- /dev/null +++ b/addons/gecs/lib/system_group.gd @@ -0,0 +1,34 @@ +## This is a node that automatically fills in the [member System.group] property +## of any [System] that is a child of this node. +## Allowing you to visually organize your systems in the scene tree +## without having to manually set the group property on each [System]. +## Add this node to your scene tree and make [System]s children of it. +## The name of the SystemGroup node will be set to [member System.group] for +## all child [System]s. +@tool +@icon('res://addons/gecs/assets/system_folder.svg') +class_name SystemGroup +extends Node + +## Put the [System]s in the group based on the [member Node.name] of the [SystemGroup] +@export var auto_group := true + + +## called when the node enters the scene tree for the first time. +func _enter_tree() -> void: + # Connect signals + if not child_entered_tree.is_connected(_on_child_entered_tree): + child_entered_tree.connect(_on_child_entered_tree) + + # Set the group for all child systems + if auto_group: + for child in get_children(): + if child is System: + child.group = name + + +## Anytime a child enters the tree, set its group if it's a System +func _on_child_entered_tree(node: Node) -> void: + if auto_group: + if node is System: + node.group = name diff --git a/addons/gecs/lib/system_group.gd.uid b/addons/gecs/lib/system_group.gd.uid new file mode 100644 index 0000000..d9b3f04 --- /dev/null +++ b/addons/gecs/lib/system_group.gd.uid @@ -0,0 +1 @@ +uid://b3vi2ingux88g diff --git a/addons/gecs/plugin.cfg b/addons/gecs/plugin.cfg new file mode 100644 index 0000000..dbf7260 --- /dev/null +++ b/addons/gecs/plugin.cfg @@ -0,0 +1,6 @@ +[plugin] +name="GECS" +description="GECS - Godot Entity Component System" +author="Quantum Tangent Games" +version="6.7.2" +script="plugin.gd" diff --git a/addons/gecs/plugin.gd b/addons/gecs/plugin.gd new file mode 100644 index 0000000..d18663d --- /dev/null +++ b/addons/gecs/plugin.gd @@ -0,0 +1,72 @@ +@tool +extends EditorPlugin + +var gecs_editor_debugger = preload("res://addons/gecs/debug/gecs_editor_debugger.gd").new() + + +func _enter_tree(): + add_autoload_singleton("ECS", "res://addons/gecs/ecs/ecs.gd") + # Pass editor interface to debugger so it can select nodes + gecs_editor_debugger.editor_interface = get_editor_interface() + add_debugger_plugin(gecs_editor_debugger) + add_gecs_project_settings() + + +func _exit_tree(): + remove_autoload_singleton("ECS") + remove_debugger_plugin(gecs_editor_debugger) + # remove_gecs_project_setings() + + +func _on_settings_changed(): + pass + + +## Adds a new project setting to Godot. +## TODO: Figure out how to also add the documentation to the ProjectSetting so that it shows up +## in the Godot Editor tooltip when the setting is hovered over. +func add_project_setting( + setting_name: String, + default_value: Variant, + value_type: int, + type_hint: int = PROPERTY_HINT_NONE, + hint_string: String = "", + documentation: String = "" +): + if !ProjectSettings.has_setting(setting_name): + ProjectSettings.set_setting(setting_name, default_value) + + ProjectSettings.set_initial_value(setting_name, default_value) + ProjectSettings.add_property_info( + {"name": setting_name, "type": value_type, "hint": type_hint, "hint_string": hint_string} + ) + ProjectSettings.set_as_basic(setting_name, true) + + var error: int = ProjectSettings.save() + if error: + push_error("GECS - Encountered error %d while saving project settings." % error) + + +## Adds new GECS related ProjectSettings to Godot. +func add_gecs_project_settings(): + ProjectSettings.settings_changed.connect(_on_settings_changed) + for setting in GecsSettings.project_settings.values(): + add_project_setting( + setting["path"], + setting["default_value"], + setting["type"], + setting["hint"], + setting["hint_string"], + setting["doc"] + ) + + +## Removes GECS related ProjectSettings from Godot. +func remove_gecs_project_setings(): + ProjectSettings.settings_changed.disconnect(_on_settings_changed) + for setting in GecsSettings.project_settings.values(): + ProjectSettings.set_setting(setting["path"], null) + + var error: int = ProjectSettings.save() + if error != OK: + push_error("GECS - Encountered error %d while saving project settings." % error) diff --git a/addons/gecs/plugin.gd.uid b/addons/gecs/plugin.gd.uid new file mode 100644 index 0000000..acc5715 --- /dev/null +++ b/addons/gecs/plugin.gd.uid @@ -0,0 +1 @@ +uid://ddl20uqtqukbm diff --git a/addons/gecs/tests/components/c_complex_serialization_test.gd b/addons/gecs/tests/components/c_complex_serialization_test.gd new file mode 100644 index 0000000..9820ecc --- /dev/null +++ b/addons/gecs/tests/components/c_complex_serialization_test.gd @@ -0,0 +1,21 @@ +class_name C_ComplexSerializationTest +extends Component + +@export var array_value: Array[int] = [1, 2, 3, 4, 5] +@export var string_array: Array[String] = ["hello", "world", "test"] +@export var dict_value: Dictionary = {"key1": "value1", "key2": 123, "key3": true} +@export var empty_array: Array = [] +@export var empty_dict: Dictionary = {} + +func _init( + _array_value: Array[int] = [1, 2, 3, 4, 5], + _string_array: Array[String] = ["hello", "world", "test"], + _dict_value: Dictionary = {"key1": "value1", "key2": 123, "key3": true}, + _empty_array: Array = [], + _empty_dict: Dictionary = {} +): + array_value = _array_value + string_array = _string_array + dict_value = _dict_value + empty_array = _empty_array + empty_dict = _empty_dict diff --git a/addons/gecs/tests/components/c_complex_serialization_test.gd.uid b/addons/gecs/tests/components/c_complex_serialization_test.gd.uid new file mode 100644 index 0000000..ef49f71 --- /dev/null +++ b/addons/gecs/tests/components/c_complex_serialization_test.gd.uid @@ -0,0 +1 @@ +uid://cpvr163gwyx2d diff --git a/addons/gecs/tests/components/c_debug_tracking_test_a.gd b/addons/gecs/tests/components/c_debug_tracking_test_a.gd new file mode 100644 index 0000000..ac53aa1 --- /dev/null +++ b/addons/gecs/tests/components/c_debug_tracking_test_a.gd @@ -0,0 +1,4 @@ +class_name C_DebugTrackingTestA +extends Component + +@export var value: float = 0.0 diff --git a/addons/gecs/tests/components/c_debug_tracking_test_a.gd.uid b/addons/gecs/tests/components/c_debug_tracking_test_a.gd.uid new file mode 100644 index 0000000..06c1813 --- /dev/null +++ b/addons/gecs/tests/components/c_debug_tracking_test_a.gd.uid @@ -0,0 +1 @@ +uid://d0vhjx22wswv5 diff --git a/addons/gecs/tests/components/c_debug_tracking_test_b.gd b/addons/gecs/tests/components/c_debug_tracking_test_b.gd new file mode 100644 index 0000000..eb811f3 --- /dev/null +++ b/addons/gecs/tests/components/c_debug_tracking_test_b.gd @@ -0,0 +1,4 @@ +class_name C_DebugTrackingTestB +extends Component + +@export var count: int = 0 diff --git a/addons/gecs/tests/components/c_debug_tracking_test_b.gd.uid b/addons/gecs/tests/components/c_debug_tracking_test_b.gd.uid new file mode 100644 index 0000000..603ff92 --- /dev/null +++ b/addons/gecs/tests/components/c_debug_tracking_test_b.gd.uid @@ -0,0 +1 @@ +uid://bijx0kal4npp diff --git a/addons/gecs/tests/components/c_domain_test_a.gd b/addons/gecs/tests/components/c_domain_test_a.gd new file mode 100644 index 0000000..2fd43cf --- /dev/null +++ b/addons/gecs/tests/components/c_domain_test_a.gd @@ -0,0 +1,3 @@ +class_name C_DomainTestA +extends Component +@export var v_a: int = 1 diff --git a/addons/gecs/tests/components/c_domain_test_a.gd.uid b/addons/gecs/tests/components/c_domain_test_a.gd.uid new file mode 100644 index 0000000..496f0ce --- /dev/null +++ b/addons/gecs/tests/components/c_domain_test_a.gd.uid @@ -0,0 +1 @@ +uid://cqsmow0liv20e diff --git a/addons/gecs/tests/components/c_domain_test_b.gd b/addons/gecs/tests/components/c_domain_test_b.gd new file mode 100644 index 0000000..30aa92c --- /dev/null +++ b/addons/gecs/tests/components/c_domain_test_b.gd @@ -0,0 +1,3 @@ +class_name C_DomainTestB +extends Component +@export var v_b: int = 2 diff --git a/addons/gecs/tests/components/c_domain_test_b.gd.uid b/addons/gecs/tests/components/c_domain_test_b.gd.uid new file mode 100644 index 0000000..8353280 --- /dev/null +++ b/addons/gecs/tests/components/c_domain_test_b.gd.uid @@ -0,0 +1 @@ +uid://bjodoqd54f6pq diff --git a/addons/gecs/tests/components/c_observer_health.gd b/addons/gecs/tests/components/c_observer_health.gd new file mode 100644 index 0000000..7aaa36e --- /dev/null +++ b/addons/gecs/tests/components/c_observer_health.gd @@ -0,0 +1,22 @@ +## Test health component for observer tests with proper property_changed signal emission +class_name C_ObserverHealth +extends Component + +@export var health: int = 100 : set = set_health +@export var max_health: int = 100 : set = set_max_health + +func set_health(new_health: int): + var old_health = health + health = new_health + # Emit signal for observers to detect the change + property_changed.emit(self, "health", old_health, new_health) + +func set_max_health(new_max: int): + var old_max = max_health + max_health = new_max + # Emit signal for observers to detect the change + property_changed.emit(self, "max_health", old_max, new_max) + +func _init(_health: int = 100, _max_health: int = 100): + health = _health + max_health = _max_health diff --git a/addons/gecs/tests/components/c_observer_health.gd.uid b/addons/gecs/tests/components/c_observer_health.gd.uid new file mode 100644 index 0000000..8512692 --- /dev/null +++ b/addons/gecs/tests/components/c_observer_health.gd.uid @@ -0,0 +1 @@ +uid://c0o4jh5t35hqw diff --git a/addons/gecs/tests/components/c_observer_test.gd b/addons/gecs/tests/components/c_observer_test.gd new file mode 100644 index 0000000..0d18b24 --- /dev/null +++ b/addons/gecs/tests/components/c_observer_test.gd @@ -0,0 +1,22 @@ +## Test component for observer tests with proper property_changed signal emission +class_name C_ObserverTest +extends Component + +@export var value: int = 0 : set = set_value +@export var name_prop: String = "" : set = set_name_prop + +func set_value(new_value: int): + var old_value = value + value = new_value + # Emit signal for observers to detect the change + property_changed.emit(self, "value", old_value, new_value) + +func set_name_prop(new_name: String): + var old_name = name_prop + name_prop = new_name + # Emit signal for observers to detect the change + property_changed.emit(self, "name_prop", old_name, new_name) + +func _init(_value: int = 0, _name: String = ""): + value = _value + name_prop = _name diff --git a/addons/gecs/tests/components/c_observer_test.gd.uid b/addons/gecs/tests/components/c_observer_test.gd.uid new file mode 100644 index 0000000..075f010 --- /dev/null +++ b/addons/gecs/tests/components/c_observer_test.gd.uid @@ -0,0 +1 @@ +uid://cmxcdgnk537l diff --git a/addons/gecs/tests/components/c_order_test_a.gd b/addons/gecs/tests/components/c_order_test_a.gd new file mode 100644 index 0000000..f13ed94 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_a.gd @@ -0,0 +1,3 @@ +class_name C_OrderTestA +extends Component +@export var value_a: int = 1 diff --git a/addons/gecs/tests/components/c_order_test_a.gd.uid b/addons/gecs/tests/components/c_order_test_a.gd.uid new file mode 100644 index 0000000..af0086e --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_a.gd.uid @@ -0,0 +1 @@ +uid://12rys1s4dqub diff --git a/addons/gecs/tests/components/c_order_test_b.gd b/addons/gecs/tests/components/c_order_test_b.gd new file mode 100644 index 0000000..a514815 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_b.gd @@ -0,0 +1,3 @@ +class_name C_OrderTestB +extends Component +@export var value_b: int = 2 diff --git a/addons/gecs/tests/components/c_order_test_b.gd.uid b/addons/gecs/tests/components/c_order_test_b.gd.uid new file mode 100644 index 0000000..3d22174 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_b.gd.uid @@ -0,0 +1 @@ +uid://brsnu840dpdnw diff --git a/addons/gecs/tests/components/c_order_test_c.gd b/addons/gecs/tests/components/c_order_test_c.gd new file mode 100644 index 0000000..5c82aa4 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_c.gd @@ -0,0 +1,3 @@ +class_name C_OrderTestC +extends Component +@export var value_c: int = 3 diff --git a/addons/gecs/tests/components/c_order_test_c.gd.uid b/addons/gecs/tests/components/c_order_test_c.gd.uid new file mode 100644 index 0000000..67db405 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_c.gd.uid @@ -0,0 +1 @@ +uid://bkx8tgtgdngvs diff --git a/addons/gecs/tests/components/c_order_test_d.gd b/addons/gecs/tests/components/c_order_test_d.gd new file mode 100644 index 0000000..065a3a5 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_d.gd @@ -0,0 +1,3 @@ +class_name C_OrderTestD +extends Component +@export var value_d: int = 4 diff --git a/addons/gecs/tests/components/c_order_test_d.gd.uid b/addons/gecs/tests/components/c_order_test_d.gd.uid new file mode 100644 index 0000000..dc57e93 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_d.gd.uid @@ -0,0 +1 @@ +uid://cdih4o87okurl diff --git a/addons/gecs/tests/components/c_order_test_e.gd b/addons/gecs/tests/components/c_order_test_e.gd new file mode 100644 index 0000000..55de0c2 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_e.gd @@ -0,0 +1,3 @@ +class_name C_OrderTestE +extends Component +@export var value_e: int = 5 diff --git a/addons/gecs/tests/components/c_order_test_e.gd.uid b/addons/gecs/tests/components/c_order_test_e.gd.uid new file mode 100644 index 0000000..14cd04f --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_e.gd.uid @@ -0,0 +1 @@ +uid://djobbcytnokef diff --git a/addons/gecs/tests/components/c_order_test_f.gd b/addons/gecs/tests/components/c_order_test_f.gd new file mode 100644 index 0000000..fe76cbf --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_f.gd @@ -0,0 +1,3 @@ +class_name C_OrderTestF +extends Component +@export var value_f: int = 6 diff --git a/addons/gecs/tests/components/c_order_test_f.gd.uid b/addons/gecs/tests/components/c_order_test_f.gd.uid new file mode 100644 index 0000000..4f28973 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_f.gd.uid @@ -0,0 +1 @@ +uid://be0tga28sdlof diff --git a/addons/gecs/tests/components/c_order_test_g.gd b/addons/gecs/tests/components/c_order_test_g.gd new file mode 100644 index 0000000..d16d648 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_g.gd @@ -0,0 +1,3 @@ +class_name C_OrderTestG +extends Component +@export var value_g: int = 7 diff --git a/addons/gecs/tests/components/c_order_test_g.gd.uid b/addons/gecs/tests/components/c_order_test_g.gd.uid new file mode 100644 index 0000000..49cf632 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_g.gd.uid @@ -0,0 +1 @@ +uid://ctgvxw7pi4wro diff --git a/addons/gecs/tests/components/c_order_test_h.gd b/addons/gecs/tests/components/c_order_test_h.gd new file mode 100644 index 0000000..7d54586 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_h.gd @@ -0,0 +1,3 @@ +class_name C_OrderTestH +extends Component +@export var value_h: int = 8 diff --git a/addons/gecs/tests/components/c_order_test_h.gd.uid b/addons/gecs/tests/components/c_order_test_h.gd.uid new file mode 100644 index 0000000..abb385a --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_h.gd.uid @@ -0,0 +1 @@ +uid://hyqseyaigq4o diff --git a/addons/gecs/tests/components/c_order_test_i.gd b/addons/gecs/tests/components/c_order_test_i.gd new file mode 100644 index 0000000..38a42b9 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_i.gd @@ -0,0 +1,3 @@ +class_name C_OrderTestI +extends Component +@export var value_i: int = 9 diff --git a/addons/gecs/tests/components/c_order_test_i.gd.uid b/addons/gecs/tests/components/c_order_test_i.gd.uid new file mode 100644 index 0000000..a02eb6f --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_i.gd.uid @@ -0,0 +1 @@ +uid://c25bhc3kbc4e8 diff --git a/addons/gecs/tests/components/c_order_test_j.gd b/addons/gecs/tests/components/c_order_test_j.gd new file mode 100644 index 0000000..cf715db --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_j.gd @@ -0,0 +1,3 @@ +class_name C_OrderTestJ +extends Component +@export var value_j: int = 10 diff --git a/addons/gecs/tests/components/c_order_test_j.gd.uid b/addons/gecs/tests/components/c_order_test_j.gd.uid new file mode 100644 index 0000000..630ac8b --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_j.gd.uid @@ -0,0 +1 @@ +uid://d1igiif6mkikj diff --git a/addons/gecs/tests/components/c_order_test_k.gd b/addons/gecs/tests/components/c_order_test_k.gd new file mode 100644 index 0000000..034e8c4 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_k.gd @@ -0,0 +1,3 @@ +class_name C_OrderTestK +extends Component +@export var value_k: int = 11 diff --git a/addons/gecs/tests/components/c_order_test_k.gd.uid b/addons/gecs/tests/components/c_order_test_k.gd.uid new file mode 100644 index 0000000..93199cc --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_k.gd.uid @@ -0,0 +1 @@ +uid://jcoxghymmvmh diff --git a/addons/gecs/tests/components/c_order_test_l.gd b/addons/gecs/tests/components/c_order_test_l.gd new file mode 100644 index 0000000..8544249 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_l.gd @@ -0,0 +1,3 @@ +class_name C_OrderTestL +extends Component +@export var value_l: int = 12 diff --git a/addons/gecs/tests/components/c_order_test_l.gd.uid b/addons/gecs/tests/components/c_order_test_l.gd.uid new file mode 100644 index 0000000..c73b8bf --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_l.gd.uid @@ -0,0 +1 @@ +uid://bce7cd48nf8e7 diff --git a/addons/gecs/tests/components/c_order_test_m.gd b/addons/gecs/tests/components/c_order_test_m.gd new file mode 100644 index 0000000..c8dabe6 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_m.gd @@ -0,0 +1,3 @@ +class_name C_OrderTestM +extends Component +@export var value_m: int = 13 diff --git a/addons/gecs/tests/components/c_order_test_m.gd.uid b/addons/gecs/tests/components/c_order_test_m.gd.uid new file mode 100644 index 0000000..bdb4d5d --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_m.gd.uid @@ -0,0 +1 @@ +uid://df0af054av56n diff --git a/addons/gecs/tests/components/c_order_test_n.gd b/addons/gecs/tests/components/c_order_test_n.gd new file mode 100644 index 0000000..fcccc6c --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_n.gd @@ -0,0 +1,3 @@ +class_name C_OrderTestN +extends Component +@export var value_n: int = 14 diff --git a/addons/gecs/tests/components/c_order_test_n.gd.uid b/addons/gecs/tests/components/c_order_test_n.gd.uid new file mode 100644 index 0000000..5a50694 --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_n.gd.uid @@ -0,0 +1 @@ +uid://dkbwhig77q1j8 diff --git a/addons/gecs/tests/components/c_order_test_o.gd b/addons/gecs/tests/components/c_order_test_o.gd new file mode 100644 index 0000000..97e4cfc --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_o.gd @@ -0,0 +1,3 @@ +class_name C_OrderTestO +extends Component +@export var value_o: int = 15 diff --git a/addons/gecs/tests/components/c_order_test_o.gd.uid b/addons/gecs/tests/components/c_order_test_o.gd.uid new file mode 100644 index 0000000..50e01bc --- /dev/null +++ b/addons/gecs/tests/components/c_order_test_o.gd.uid @@ -0,0 +1 @@ +uid://bgsirllg7wil0 diff --git a/addons/gecs/tests/components/c_perm_a.gd b/addons/gecs/tests/components/c_perm_a.gd new file mode 100644 index 0000000..36f117a --- /dev/null +++ b/addons/gecs/tests/components/c_perm_a.gd @@ -0,0 +1,3 @@ +class_name C_PermA +extends Component +@export var v: int = 1 diff --git a/addons/gecs/tests/components/c_perm_a.gd.uid b/addons/gecs/tests/components/c_perm_a.gd.uid new file mode 100644 index 0000000..67dd655 --- /dev/null +++ b/addons/gecs/tests/components/c_perm_a.gd.uid @@ -0,0 +1 @@ +uid://bi4vscfom0st2 diff --git a/addons/gecs/tests/components/c_perm_b.gd b/addons/gecs/tests/components/c_perm_b.gd new file mode 100644 index 0000000..79fbfea --- /dev/null +++ b/addons/gecs/tests/components/c_perm_b.gd @@ -0,0 +1,3 @@ +class_name C_PermB +extends Component +@export var v: int = 2 diff --git a/addons/gecs/tests/components/c_perm_b.gd.uid b/addons/gecs/tests/components/c_perm_b.gd.uid new file mode 100644 index 0000000..4a34c95 --- /dev/null +++ b/addons/gecs/tests/components/c_perm_b.gd.uid @@ -0,0 +1 @@ +uid://c1svfcwyi2oie diff --git a/addons/gecs/tests/components/c_perm_c.gd b/addons/gecs/tests/components/c_perm_c.gd new file mode 100644 index 0000000..bb5cfd7 --- /dev/null +++ b/addons/gecs/tests/components/c_perm_c.gd @@ -0,0 +1,3 @@ +class_name C_PermC +extends Component +@export var v: int = 3 diff --git a/addons/gecs/tests/components/c_perm_c.gd.uid b/addons/gecs/tests/components/c_perm_c.gd.uid new file mode 100644 index 0000000..2fd675c --- /dev/null +++ b/addons/gecs/tests/components/c_perm_c.gd.uid @@ -0,0 +1 @@ +uid://0ynnafo2v1it diff --git a/addons/gecs/tests/components/c_perm_d.gd b/addons/gecs/tests/components/c_perm_d.gd new file mode 100644 index 0000000..94eb349 --- /dev/null +++ b/addons/gecs/tests/components/c_perm_d.gd @@ -0,0 +1,3 @@ +class_name C_PermD +extends Component +@export var v: int = 4 diff --git a/addons/gecs/tests/components/c_perm_d.gd.uid b/addons/gecs/tests/components/c_perm_d.gd.uid new file mode 100644 index 0000000..89acbe4 --- /dev/null +++ b/addons/gecs/tests/components/c_perm_d.gd.uid @@ -0,0 +1 @@ +uid://cts7f306wa0fa diff --git a/addons/gecs/tests/components/c_perm_e.gd b/addons/gecs/tests/components/c_perm_e.gd new file mode 100644 index 0000000..1f4b44f --- /dev/null +++ b/addons/gecs/tests/components/c_perm_e.gd @@ -0,0 +1,3 @@ +class_name C_PermE +extends Component +@export var v: int = 5 diff --git a/addons/gecs/tests/components/c_perm_e.gd.uid b/addons/gecs/tests/components/c_perm_e.gd.uid new file mode 100644 index 0000000..b17bb95 --- /dev/null +++ b/addons/gecs/tests/components/c_perm_e.gd.uid @@ -0,0 +1 @@ +uid://c720mkd00xchu diff --git a/addons/gecs/tests/components/c_perm_f.gd b/addons/gecs/tests/components/c_perm_f.gd new file mode 100644 index 0000000..dfa88a7 --- /dev/null +++ b/addons/gecs/tests/components/c_perm_f.gd @@ -0,0 +1,3 @@ +class_name C_PermF +extends Component +@export var v: int = 6 diff --git a/addons/gecs/tests/components/c_perm_f.gd.uid b/addons/gecs/tests/components/c_perm_f.gd.uid new file mode 100644 index 0000000..57c2bd1 --- /dev/null +++ b/addons/gecs/tests/components/c_perm_f.gd.uid @@ -0,0 +1 @@ +uid://ccws6g7g0j6w8 diff --git a/addons/gecs/tests/components/c_persistent.gd b/addons/gecs/tests/components/c_persistent.gd new file mode 100644 index 0000000..483ccab --- /dev/null +++ b/addons/gecs/tests/components/c_persistent.gd @@ -0,0 +1,21 @@ +extends Component +class_name C_Persistent + +@export var player_name: String = "Player1" +@export var level: int = 1 +@export var health: float = 100.0 +@export var position: Vector2 = Vector2.ZERO +@export var inventory: Array[String] = [] + +func _init( + _player_name: String = "Player1", + _level: int = 1, + _health: float = 100.0, + _position: Vector2 = Vector2.ZERO, + _inventory: Array[String] = [] +): + player_name = _player_name + level = _level + health = _health + position = _position + inventory = _inventory diff --git a/addons/gecs/tests/components/c_persistent.gd.uid b/addons/gecs/tests/components/c_persistent.gd.uid new file mode 100644 index 0000000..27145c7 --- /dev/null +++ b/addons/gecs/tests/components/c_persistent.gd.uid @@ -0,0 +1 @@ +uid://bikywcisu1fsu diff --git a/addons/gecs/tests/components/c_position.gd b/addons/gecs/tests/components/c_position.gd new file mode 100644 index 0000000..868fb57 --- /dev/null +++ b/addons/gecs/tests/components/c_position.gd @@ -0,0 +1,14 @@ +## Test position component for observer performance tests +class_name C_TestPosition +extends Component + +@export var position: Vector3 = Vector3.ZERO : set = set_position + +func set_position(new_pos: Vector3): + var old_pos = position + position = new_pos + # Emit signal for observers to detect the change + property_changed.emit(self, "position", old_pos, new_pos) + +func _init(_position: Vector3 = Vector3.ZERO): + position = _position diff --git a/addons/gecs/tests/components/c_position.gd.uid b/addons/gecs/tests/components/c_position.gd.uid new file mode 100644 index 0000000..7df39ab --- /dev/null +++ b/addons/gecs/tests/components/c_position.gd.uid @@ -0,0 +1 @@ +uid://33n1ne8tuyja diff --git a/addons/gecs/tests/components/c_serialization_test.gd b/addons/gecs/tests/components/c_serialization_test.gd new file mode 100644 index 0000000..8399b38 --- /dev/null +++ b/addons/gecs/tests/components/c_serialization_test.gd @@ -0,0 +1,27 @@ +extends Component +class_name C_SerializationTest + +@export var int_value: int = 42 +@export var float_value: float = 3.14 +@export var string_value: String = "test_string" +@export var bool_value: bool = true +@export var vector2_value: Vector2 = Vector2(1.0, 2.0) +@export var vector3_value: Vector3 = Vector3(1.0, 2.0, 3.0) +@export var color_value: Color = Color.RED + +func _init( + _int_value: int = 42, + _float_value: float = 3.14, + _string_value: String = "test_string", + _bool_value: bool = true, + _vector2_value: Vector2 = Vector2(1.0, 2.0), + _vector3_value: Vector3 = Vector3(1.0, 2.0, 3.0), + _color_value: Color = Color.RED +): + int_value = _int_value + float_value = _float_value + string_value = _string_value + bool_value = _bool_value + vector2_value = _vector2_value + vector3_value = _vector3_value + color_value = _color_value diff --git a/addons/gecs/tests/components/c_serialization_test.gd.uid b/addons/gecs/tests/components/c_serialization_test.gd.uid new file mode 100644 index 0000000..cec6fa6 --- /dev/null +++ b/addons/gecs/tests/components/c_serialization_test.gd.uid @@ -0,0 +1 @@ +uid://3w2r1fop8e52 diff --git a/addons/gecs/tests/components/c_test_a.gd b/addons/gecs/tests/components/c_test_a.gd new file mode 100644 index 0000000..6f9fff7 --- /dev/null +++ b/addons/gecs/tests/components/c_test_a.gd @@ -0,0 +1,8 @@ +class_name C_TestA +extends Component + +@export var value: int = 0 + + +func _init(_value: int = 0): + value = _value diff --git a/addons/gecs/tests/components/c_test_a.gd.uid b/addons/gecs/tests/components/c_test_a.gd.uid new file mode 100644 index 0000000..4edb8a5 --- /dev/null +++ b/addons/gecs/tests/components/c_test_a.gd.uid @@ -0,0 +1 @@ +uid://5antadqj7v84 diff --git a/addons/gecs/tests/components/c_test_b.gd b/addons/gecs/tests/components/c_test_b.gd new file mode 100644 index 0000000..154933a --- /dev/null +++ b/addons/gecs/tests/components/c_test_b.gd @@ -0,0 +1,8 @@ +class_name C_TestB +extends Component + +@export var value: int = 0 + + +func _init(_value: int = 0): + value = _value diff --git a/addons/gecs/tests/components/c_test_b.gd.uid b/addons/gecs/tests/components/c_test_b.gd.uid new file mode 100644 index 0000000..6cbbebf --- /dev/null +++ b/addons/gecs/tests/components/c_test_b.gd.uid @@ -0,0 +1 @@ +uid://c6lvbdptfldrg diff --git a/addons/gecs/tests/components/c_test_c.gd b/addons/gecs/tests/components/c_test_c.gd new file mode 100644 index 0000000..92891c2 --- /dev/null +++ b/addons/gecs/tests/components/c_test_c.gd @@ -0,0 +1,8 @@ +class_name C_TestC +extends Component + +@export var value: int + + +func _init(_value: int = 0): + value = _value diff --git a/addons/gecs/tests/components/c_test_c.gd.uid b/addons/gecs/tests/components/c_test_c.gd.uid new file mode 100644 index 0000000..c7920d0 --- /dev/null +++ b/addons/gecs/tests/components/c_test_c.gd.uid @@ -0,0 +1 @@ +uid://3lo6r4xvicxp diff --git a/addons/gecs/tests/components/c_test_d.gd b/addons/gecs/tests/components/c_test_d.gd new file mode 100644 index 0000000..47cd42c --- /dev/null +++ b/addons/gecs/tests/components/c_test_d.gd @@ -0,0 +1,8 @@ +class_name C_TestD +extends Component + +@export var points: int = 0 + + +func _init(_points: int = 0): + points = _points diff --git a/addons/gecs/tests/components/c_test_d.gd.uid b/addons/gecs/tests/components/c_test_d.gd.uid new file mode 100644 index 0000000..8082870 --- /dev/null +++ b/addons/gecs/tests/components/c_test_d.gd.uid @@ -0,0 +1 @@ +uid://cd2ml5rtb3c8g diff --git a/addons/gecs/tests/components/c_test_e.gd b/addons/gecs/tests/components/c_test_e.gd new file mode 100644 index 0000000..d116e88 --- /dev/null +++ b/addons/gecs/tests/components/c_test_e.gd @@ -0,0 +1,4 @@ +class_name C_TestE +extends Component + +@export var value: int = 0 diff --git a/addons/gecs/tests/components/c_test_e.gd.uid b/addons/gecs/tests/components/c_test_e.gd.uid new file mode 100644 index 0000000..38ca48c --- /dev/null +++ b/addons/gecs/tests/components/c_test_e.gd.uid @@ -0,0 +1 @@ +uid://cp6siju1aijj2 diff --git a/addons/gecs/tests/components/c_test_f.gd b/addons/gecs/tests/components/c_test_f.gd new file mode 100644 index 0000000..27496db --- /dev/null +++ b/addons/gecs/tests/components/c_test_f.gd @@ -0,0 +1,11 @@ +class_name C_TestF +extends Component + +var value: int = 0 # properties with no export annotation + +static var init_count: int = 0 + +func _init(_value: int = 0): + value = _value + init_count += 1 + print("Component c_test_f init, value=%d" % value) diff --git a/addons/gecs/tests/components/c_test_f.gd.uid b/addons/gecs/tests/components/c_test_f.gd.uid new file mode 100644 index 0000000..9eb9e0b --- /dev/null +++ b/addons/gecs/tests/components/c_test_f.gd.uid @@ -0,0 +1 @@ +uid://py2qgdkhiy30 diff --git a/addons/gecs/tests/components/c_test_g.gd b/addons/gecs/tests/components/c_test_g.gd new file mode 100644 index 0000000..189bb54 --- /dev/null +++ b/addons/gecs/tests/components/c_test_g.gd @@ -0,0 +1,12 @@ +class_name C_TestG +extends Component + +@export var value: int = 0 + +static var init_count: int = 0 + +func _init(_value: int = 0): + value = _value + init_count += 1 + # to test _init() calling problem + print("Component c_test_g init, value=%d" % value) diff --git a/addons/gecs/tests/components/c_test_g.gd.uid b/addons/gecs/tests/components/c_test_g.gd.uid new file mode 100644 index 0000000..c443b77 --- /dev/null +++ b/addons/gecs/tests/components/c_test_g.gd.uid @@ -0,0 +1 @@ +uid://4ud215bve6ap diff --git a/addons/gecs/tests/components/c_test_h.gd b/addons/gecs/tests/components/c_test_h.gd new file mode 100644 index 0000000..6ef62cf --- /dev/null +++ b/addons/gecs/tests/components/c_test_h.gd @@ -0,0 +1,8 @@ +class_name C_TestH +extends Component + +@export var value: int = 0 + +# Simulates parameters with no default values +func _init(_value: int): + value = _value diff --git a/addons/gecs/tests/components/c_test_h.gd.uid b/addons/gecs/tests/components/c_test_h.gd.uid new file mode 100644 index 0000000..a24e531 --- /dev/null +++ b/addons/gecs/tests/components/c_test_h.gd.uid @@ -0,0 +1 @@ +uid://b8ptu8k8rp1sb diff --git a/addons/gecs/tests/components/c_velocity.gd b/addons/gecs/tests/components/c_velocity.gd new file mode 100644 index 0000000..f4e4b15 --- /dev/null +++ b/addons/gecs/tests/components/c_velocity.gd @@ -0,0 +1,14 @@ +## Test velocity component for observer performance tests +class_name C_TestVelocity +extends Component + +@export var velocity: Vector3 = Vector3.ZERO : set = set_velocity + +func set_velocity(new_vel: Vector3): + var old_vel = velocity + velocity = new_vel + # Emit signal for observers to detect the change + property_changed.emit(self, "velocity", old_vel, new_vel) + +func _init(_velocity: Vector3 = Vector3.ZERO): + velocity = _velocity diff --git a/addons/gecs/tests/components/c_velocity.gd.uid b/addons/gecs/tests/components/c_velocity.gd.uid new file mode 100644 index 0000000..107d0de --- /dev/null +++ b/addons/gecs/tests/components/c_velocity.gd.uid @@ -0,0 +1 @@ +uid://ckhr8q3glmacs diff --git a/addons/gecs/tests/core/test_archetype_edge_cache.gd b/addons/gecs/tests/core/test_archetype_edge_cache.gd new file mode 100644 index 0000000..fc23316 --- /dev/null +++ b/addons/gecs/tests/core/test_archetype_edge_cache.gd @@ -0,0 +1,147 @@ +class_name TestArchetypeEdgeCacheBug +extends GdUnitTestSuite +## Test suite for archetype edge cache bug +## +## Tests that archetypes retrieved from edge cache are properly re-registered +## with the world when they were previously removed due to being empty. +## +## Bug sequence: +## 1. Entity A gets component added -> creates archetype X, cached edge +## 2. Entity A removed -> archetype X becomes empty, gets removed from world.archetypes +## 3. Entity B gets same component -> uses cached edge to archetype X +## 4. BUG: archetype X not in world.archetypes, so queries can't find Entity B + + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + if world: + world.purge(false) + + +## Test that archetypes retrieved from edge cache are re-registered with world +func test_archetype_reregistered_after_edge_cache_retrieval(): + # ARRANGE: Create two entities with same initial components + var entity1 = Entity.new() + entity1.add_component(C_TestA.new()) + world.add_entities([entity1]) + + var entity2 = Entity.new() + entity2.add_component(C_TestA.new()) + world.add_entities([entity2]) + + # ACT 1: Add ComponentB to entity1 (creates new archetype + edge cache) + var comp_b1 = C_TestB.new() + entity1.add_component(comp_b1) + + # Get the archetype signature for A+B combination + var archetype_with_b = world.entity_to_archetype[entity1] + var signature_with_b = archetype_with_b.signature + + # Verify archetype is in world.archetypes + assert_bool(world.archetypes.has(signature_with_b)).is_true() + + # ACT 2: Remove entity1 to make archetype empty (triggers cleanup) + world.remove_entity(entity1) + + # Verify archetype was removed from world.archetypes when empty + assert_bool(world.archetypes.has(signature_with_b)).is_false() + + # ACT 3: Add ComponentB to entity2 (should use edge cache) + # This is where the bug would occur - archetype retrieved from cache + # but not re-registered with world + var comp_b2 = C_TestB.new() + entity2.add_component(comp_b2) + + # ASSERT: Archetype should be back in world.archetypes + assert_bool(world.archetypes.has(signature_with_b)).is_true() + + # ASSERT: Query should find entity2 + var query = QueryBuilder.new(world).with_all([C_TestA, C_TestB]) + var results = query.execute() + assert_int(results.size()).is_equal(1) + assert_object(results[0]).is_same(entity2) + + +## Test that queries find entities in edge-cached archetypes +func test_query_finds_entities_in_edge_cached_archetype(): + # This reproduces the exact projectile bug scenario + # ARRANGE: Create 3 projectiles + var projectile1 = Entity.new() + projectile1.add_component(C_TestA.new()) # Simulates C_Projectile + world.add_entities([projectile1]) + + var projectile2 = Entity.new() + projectile2.add_component(C_TestA.new()) + world.add_entities([projectile2]) + + var projectile3 = Entity.new() + projectile3.add_component(C_TestA.new()) + world.add_entities([projectile3]) + + # ACT 1: First projectile collides (adds ComponentB = C_Collision) + projectile1.add_component(C_TestB.new()) + + # Verify query finds it + var collision_query = QueryBuilder.new(world).with_all([C_TestA, C_TestB]) + assert_int(collision_query.execute().size()).is_equal(1) + + # ACT 2: First projectile processed and removed (empties collision archetype) + world.remove_entity(projectile1) + + # ACT 3: Second projectile collides (edge cache used) + projectile2.add_component(C_TestB.new()) + + # ASSERT: Query should find second projectile (BUG: it wouldn't before fix) + var results = collision_query.execute() + assert_int(results.size()).is_equal(1) + assert_object(results[0]).is_same(projectile2) + + # ACT 4: Third projectile also collides while second still exists + projectile3.add_component(C_TestB.new()) + + # ASSERT: Query should find both projectiles + results = collision_query.execute() + assert_int(results.size()).is_equal(2) + + +## Test rapid add/remove cycles don't lose archetypes +func test_rapid_archetype_cycling(): + # Tests the exact pattern: create -> empty -> reuse via cache + var entities = [] + for i in range(5): + var e = Entity.new() + e.add_component(C_TestA.new()) + world.add_entities([e]) + entities.append(e) + + # Cycle through adding/removing ComponentB + for cycle in range(3): + # Add ComponentB to first entity (creates/reuses archetype) + entities[0].add_component(C_TestB.new()) + + # Query should find it + var query = QueryBuilder.new(world).with_all([C_TestA, C_TestB]) + var results = query.execute() + assert_int(results.size()).is_equal(1) + + # Remove entity (empties archetype) + world.remove_entity(entities[0]) + + # Create new entity for next cycle + entities[0] = Entity.new() + entities[0].add_component(C_TestA.new()) + world.add_entities([entities[0]]) + + # Final cycle - should still work + entities[0].add_component(C_TestB.new()) + var final_query = QueryBuilder.new(world).with_all([C_TestA, C_TestB]) + assert_int(final_query.execute().size()).is_equal(1) diff --git a/addons/gecs/tests/core/test_archetype_edge_cache.gd.uid b/addons/gecs/tests/core/test_archetype_edge_cache.gd.uid new file mode 100644 index 0000000..125bba6 --- /dev/null +++ b/addons/gecs/tests/core/test_archetype_edge_cache.gd.uid @@ -0,0 +1 @@ +uid://hphmrhtswrjq diff --git a/addons/gecs/tests/core/test_archetype_systems.gd b/addons/gecs/tests/core/test_archetype_systems.gd new file mode 100644 index 0000000..a00b24e --- /dev/null +++ b/addons/gecs/tests/core/test_archetype_systems.gd @@ -0,0 +1,156 @@ +extends GdUnitTestSuite + +## Test archetype-based system execution + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + if world: + world.purge(false) + + +func test_archetype_system_processes_entities(): + # Create test system that uses archetype mode + var test_system = ArchetypeTestSystem.new() + world.add_system(test_system) + + # Create entities with components + var entity1 = Entity.new() + entity1.name = "Entity1" + world.add_entity(entity1, [C_TestA.new()]) + + var entity2 = Entity.new() + entity2.name = "Entity2" + world.add_entity(entity2, [C_TestA.new()]) + + # Process the system + world.process(0.1) + + # Verify archetype method was called + assert_int(test_system.archetype_call_count).is_equal(1) + assert_int(test_system.entities_processed).is_equal(2) + + +func test_archetype_iteration_order_matches_iterate(): + # System that checks component order + var test_system = ArchetypeOrderTestSystem.new() + world.add_system(test_system) + + # Create entity with multiple components + var entity = Entity.new() + entity.name = "TestEntity" + world.add_entity(entity, [C_TestB.new(), C_TestA.new()]) + + # Process + world.process(0.1) + + # Verify components were in correct order (as specified in iterate()) + assert_bool(test_system.order_correct).is_true() + + +func test_archetype_processes_entities_with_extra_components(): + # Query for A and B, but entity has A, B, and C + var test_system = ArchetypeSubsetTestSystem.new() + world.add_system(test_system) + + # Entity has MORE components than query asks for + var entity = Entity.new() + entity.name = "ExtraComponents" + world.add_entity(entity, [C_TestA.new(), C_TestB.new(), C_TestC.new()]) + + # Should still match and process + world.process(0.1) + + assert_int(test_system.entities_processed).is_equal(1) + + +func test_archetype_processes_multiple_archetypes(): + # System that tracks archetype calls + var test_system = ArchetypeMultipleArchetypesTestSystem.new() + world.add_system(test_system) + + # Create entities with different component combinations + # Archetype 1: [A, B] + var entity1 = Entity.new() + world.add_entity(entity1, [C_TestA.new(), C_TestB.new()]) + + var entity2 = Entity.new() + world.add_entity(entity2, [C_TestA.new(), C_TestB.new()]) + + # Archetype 2: [A, B, C] + var entity3 = Entity.new() + world.add_entity(entity3, [C_TestA.new(), C_TestB.new(), C_TestC.new()]) + + # Process + world.process(0.1) + + # Should be called once per archetype + assert_int(test_system.archetype_call_count).is_equal(2) + assert_int(test_system.total_entities_processed).is_equal(3) + + +func test_archetype_column_data_is_correct(): + # System that verifies column data + var test_system = ArchetypeColumnDataTestSystem.new() + world.add_system(test_system) + + # Create entities with specific values + var entity1 = Entity.new() + var comp_a1 = C_TestA.new() + comp_a1.value = 10 + world.add_entity(entity1, [comp_a1]) + + var entity2 = Entity.new() + var comp_a2 = C_TestA.new() + comp_a2.value = 20 + world.add_entity(entity2, [comp_a2]) + + # Process + world.process(0.1) + + # Verify column had correct values + assert_array(test_system.values_seen).contains_exactly([10, 20]) + + +func test_archetype_modifies_components(): + # System that modifies component values + var test_system = ArchetypeModifyTestSystem.new() + world.add_system(test_system) + + var entity = Entity.new() + var comp = C_TestA.new() + comp.value = 5 + world.add_entity(entity, [comp]) + + # Process multiple times + world.process(0.1) + world.process(0.1) + world.process(0.1) + + # Value should have been incremented each time + # Get the component from the entity (not the local reference) + var updated_comp = entity.get_component(C_TestA) + assert_int(updated_comp.value).is_equal(8) + + +func test_archetype_works_without_iterate_call(): + # System that doesn't call iterate() still works, just gets empty components array + var test_system = ArchetypeNoIterateSystem.new() + world.add_system(test_system) + + var entity = Entity.new() + world.add_entity(entity, [C_TestA.new()]) + + # Should work fine - system can use get_component() instead + world.process(0.1) + + # System should have processed the entity + assert_int(test_system.processed).is_equal(1) diff --git a/addons/gecs/tests/core/test_archetype_systems.gd.uid b/addons/gecs/tests/core/test_archetype_systems.gd.uid new file mode 100644 index 0000000..d07203c --- /dev/null +++ b/addons/gecs/tests/core/test_archetype_systems.gd.uid @@ -0,0 +1 @@ +uid://cem3jyvifqys diff --git a/addons/gecs/tests/core/test_complex_relationship_serialization.gd b/addons/gecs/tests/core/test_complex_relationship_serialization.gd new file mode 100644 index 0000000..feaf64e --- /dev/null +++ b/addons/gecs/tests/core/test_complex_relationship_serialization.gd @@ -0,0 +1,371 @@ +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + +func after_test(): + if world: + world.purge(false) + +func test_complex_nested_relationships_serialization(): + # Create a complex hierarchy: Player -> Weapon -> Attachment + # This tests multi-level relationship auto-inclusion + # 1. Create Player entity + var player = Entity.new() + player.name = "Player" + player.add_component(C_TestA.new()) # Player-specific component + + # 2. Create Weapon entity with weapon-specific components + var weapon = Entity.new() + weapon.name = "AssaultRifle" + weapon.add_component(C_TestB.new()) # Weapon component + weapon.add_component(C_TestC.new()) # Damage component + + # 3. Create Attachment entity + var attachment = Entity.new() + attachment.name = "RedDotSight" + attachment.add_component(C_TestD.new()) # Attachment component + attachment.add_component(C_TestE.new()) # Accuracy modifier component + + # 4. Create another attachment for testing multiple relationships + var attachment2 = Entity.new() + attachment2.name = "Silencer" + attachment2.add_component(C_TestF.new()) # Another attachment component + + # 5. Set up relationships: Player -> Weapon -> Attachments + var player_weapon_rel = Relationship.new(C_TestA.new(), weapon) # Player equipped with weapon + player.add_relationship(player_weapon_rel) + + var weapon_sight_rel = Relationship.new(C_TestB.new(), attachment) # Weapon has sight + weapon.add_relationship(weapon_sight_rel) + + var weapon_silencer_rel = Relationship.new(C_TestC.new(), attachment2) # Weapon has silencer + weapon.add_relationship(weapon_silencer_rel) + + # 6. Add entities to world (don't add to scene tree to preserve names) + world.add_entity(player) + world.add_entity(weapon) + world.add_entity(attachment) + world.add_entity(attachment2) + + # Store original UUIDs for verification + var player_id = player.id + var weapon_id = weapon.id + var attachment_id = attachment.id + var attachment2_id = attachment2.id + + print("=== BEFORE SERIALIZATION ===") + print("Player UUID: ", player_id) + print("Weapon UUID: ", weapon_id) + print("Attachment UUID: ", attachment_id) + print("Attachment2 UUID: ", attachment2_id) + print("Player relationships: ", player.relationships.size()) + print("Weapon relationships: ", weapon.relationships.size()) + + # 7. Serialize ONLY the player (should auto-include weapon and attachments) + var query = world.query.with_all([C_TestA]) # Only matches player + var serialized_data = ECS.serialize(query) + + print("=== SERIALIZATION RESULTS ===") + print("Total entities serialized: ", serialized_data.entities.size()) + + # 8. Verify serialization results + assert_that(serialized_data.entities).has_size(4) # All 4 entities should be included + + # Count auto-included vs original entities + var auto_included_count = 0 + var original_count = 0 + var player_data = null + var weapon_data = null + var attachment_data = null + var attachment2_data = null + + for entity_data in serialized_data.entities: + print("Entity: ", entity_data.entity_name, " - Auto-included: ", entity_data.auto_included, " - id: ", entity_data.id) + + if entity_data.auto_included: + auto_included_count += 1 + else: + original_count += 1 + + # Find specific entities for detailed verification + match entity_data.entity_name: + "Player": + player_data = entity_data + "AssaultRifle": + weapon_data = entity_data + "RedDotSight": + attachment_data = entity_data + "Silencer": + attachment2_data = entity_data + + # Verify auto-inclusion flags + assert_that(original_count).is_equal(1) # Only player from original query + assert_that(auto_included_count).is_equal(3) # Weapon and both attachments auto-included + + # Verify specific entity data + assert_that(player_data).is_not_null() + assert_that(player_data.auto_included).is_false() # Player was in original query + assert_that(player_data.relationships).has_size(1) # Player -> Weapon relationship + + assert_that(weapon_data).is_not_null() + assert_that(weapon_data.auto_included).is_true() # Weapon was auto-included + assert_that(weapon_data.relationships).has_size(2) # Weapon -> Attachments relationships + + assert_that(attachment_data).is_not_null() + assert_that(attachment_data.auto_included).is_true() # Attachment was auto-included + + assert_that(attachment2_data).is_not_null() + assert_that(attachment2_data.auto_included).is_true() # Attachment2 was auto-included + + # 9. Save and load the serialized data + var file_path = "res://reports/test_complex_relationships.tres" + ECS.save(serialized_data, file_path) + + # 10. Clear the world to simulate fresh start + world.purge(false) + assert_that(world.entities).has_size(0) + assert_that(world.entity_id_registry).has_size(0) + + # 11. Deserialize and add back to world + var deserialized_entities = ECS.deserialize(file_path) + + print("=== DESERIALIZATION RESULTS ===") + print("Deserialized entities: ", deserialized_entities.size()) + + assert_that(deserialized_entities).has_size(4) + + # Add all entities back to world (don't add to scene tree to avoid naming conflicts) + for entity in deserialized_entities: + world.add_entity(entity, null, false) + + # 12. Verify world state after deserialization + assert_that(world.entities).has_size(4) + assert_that(world.entity_id_registry).has_size(4) + + # Find entities by UUID to verify they're properly restored + var restored_player = world.get_entity_by_id(player_id) + var restored_weapon = world.get_entity_by_id(weapon_id) + var restored_attachment = world.get_entity_by_id(attachment_id) + var restored_attachment2 = world.get_entity_by_id(attachment2_id) + + print("=== RESTORED ENTITIES ===") + print("Player found: ", restored_player != null, " - Name: ", restored_player.name if restored_player else "null") + print("Weapon found: ", restored_weapon != null, " - Name: ", restored_weapon.name if restored_weapon else "null") + print("Attachment found: ", restored_attachment != null, " - Name: ", restored_attachment.name if restored_attachment else "null") + print("Attachment2 found: ", restored_attachment2 != null, " - Name: ", restored_attachment2.name if restored_attachment2 else "null") + + # Verify all entities were found + assert_that(restored_player).is_not_null() + assert_that(restored_weapon).is_not_null() + assert_that(restored_attachment).is_not_null() + assert_that(restored_attachment2).is_not_null() + + # Verify entity names are preserved + assert_that(restored_player.name).is_equal("Player") + assert_that(restored_weapon.name).is_equal("AssaultRifle") + assert_that(restored_attachment.name).is_equal("RedDotSight") + assert_that(restored_attachment2.name).is_equal("Silencer") + + # 13. Verify relationships are intact + print("=== RELATIONSHIP VERIFICATION ===") + print("Player relationships: ", restored_player.relationships.size()) + print("Weapon relationships: ", restored_weapon.relationships.size()) + + # Player should have 1 relationship to weapon + assert_that(restored_player.relationships).has_size(1) + var player_rel = restored_player.relationships[0] + assert_that(player_rel.target).is_equal(restored_weapon) + print("Player -> Weapon relationship intact: ", player_rel.target.name) + + # Weapon should have 2 relationships to attachments + assert_that(restored_weapon.relationships).has_size(2) + + var weapon_targets = [] + var weapon_target_entities = [] + for rel in restored_weapon.relationships: + weapon_target_entities.append(rel.target) + weapon_targets.append(rel.target.name) + print("Weapon -> ", rel.target.name, " relationship intact") + + # Verify weapon is connected to both attachments + assert_that(weapon_target_entities).contains(restored_attachment) + assert_that(weapon_target_entities).contains(restored_attachment2) + assert_that(weapon_targets).contains("RedDotSight") + assert_that(weapon_targets).contains("Silencer") + + # 14. Verify components are preserved + assert_that(restored_player.has_component(C_TestA)).is_true() + assert_that(restored_weapon.has_component(C_TestB)).is_true() + assert_that(restored_weapon.has_component(C_TestC)).is_true() + assert_that(restored_attachment.has_component(C_TestD)).is_true() + assert_that(restored_attachment.has_component(C_TestE)).is_true() + assert_that(restored_attachment2.has_component(C_TestF)).is_true() + + print("=== TEST PASSED: Complex nested relationships preserved! ===") + world.remove_entities(deserialized_entities) + + +func test_relationship_replacement_with_id_collision(): + # Test that when entities with relationships are replaced via UUID collision, + # the relationships update correctly to point to the new entities + # 1. Create initial setup: Player -> Weapon + var player = Entity.new() + player.name = "Player" + player.add_component(C_TestA.new()) + player.set("id", "player-id-123") + + var old_weapon = Entity.new() + old_weapon.name = "OldWeapon" + old_weapon.add_component(C_TestB.new()) + old_weapon.set("id", "weapon-id-456") + + var player_weapon_rel = Relationship.new(C_TestA.new(), old_weapon) + player.add_relationship(player_weapon_rel) + + world.add_entity(player) + world.add_entity(old_weapon) + + # Verify initial relationship + assert_that(player.relationships).has_size(1) + assert_that(player.relationships[0].target).is_equal(old_weapon) + assert_that(player.relationships[0].target.name).is_equal("OldWeapon") + + # 2. Serialize the current state + var query = world.query.with_all([C_TestA]) + var serialized_data = ECS.serialize(query) + var file_path = "res://reports/test_replacement_relationships.tres" + ECS.save(serialized_data, file_path) + + # 3. Create "updated" entities with same UUIDs but different data + var new_weapon = Entity.new() + new_weapon.name = "NewUpgradedWeapon" + new_weapon.add_component(C_TestB.new()) + new_weapon.add_component(C_TestC.new()) # Added component + new_weapon.set("id", "weapon-id-456") # Same UUID! + + # 4. Add new weapon (should replace old weapon) + world.add_entity(new_weapon) + + # Verify replacement occurred + assert_that(world.entities).has_size(2) # Still only 2 entities + var current_weapon = world.get_entity_by_id("weapon-id-456") + assert_that(current_weapon).is_equal(new_weapon) + assert_that(current_weapon.name).is_equal("NewUpgradedWeapon") + assert_that(current_weapon.has_component(C_TestC)).is_true() + + # 5. NOTE: When we replace an entity, existing relationships still point to the old entity object + # This is expected behavior - the relationship contains a direct Entity reference + # To update relationships, we would need to re-serialize/deserialize or manually update them + print("Current relationship target: ", player.relationships[0].target.name) + print("Expected: Relationship still points to old entity until re-serialized") + + print("=== Relationship correctly updated after entity replacement ===") + + # 6. Now test loading the old save file (should replace with old state) + var loaded_entities = ECS.deserialize(file_path) + + for entity in loaded_entities: + world.add_entity(entity) # Should trigger replacements + + # Verify entities were replaced with old state + var final_weapon = world.get_entity_by_id("weapon-id-456") + print("Final weapon name: ", final_weapon.name) + assert_that(final_weapon.has_component(C_TestC)).is_false() # Lost the added component + + # Verify relationship points to restored weapon + var final_player = world.get_entity_by_id("player-id-123") + assert_that(final_player.relationships).has_size(1) + assert_that(final_player.relationships[0].target).is_equal(final_weapon) + print("Final relationship target name: ", final_player.relationships[0].target.name) + + print("=== Save/Load replacement cycle completed successfully ===") + + +func test_partial_serialization_auto_inclusion(): + # Test that we can serialize a subset of entities and auto-include dependencies + # while excluding unrelated entities + # Create multiple independent entity groups + # Group 1: Player -> Weapon -> Attachment (should be included) + var player = Entity.new() + player.name = "Player" + player.add_component(C_TestA.new()) + + var weapon = Entity.new() + weapon.name = "Weapon" + weapon.add_component(C_TestB.new()) + + var attachment = Entity.new() + attachment.name = "Attachment" + attachment.add_component(C_TestC.new()) + + player.add_relationship(Relationship.new(C_TestA.new(), weapon)) + weapon.add_relationship(Relationship.new(C_TestB.new(), attachment)) + + # Group 2: Enemy -> EnemyWeapon (should NOT be included) + var enemy = Entity.new() + enemy.name = "Enemy" + enemy.add_component(C_TestD.new()) # Different component type + + var enemy_weapon = Entity.new() + enemy_weapon.name = "EnemyWeapon" + enemy_weapon.add_component(C_TestE.new()) + + enemy.add_relationship(Relationship.new(C_TestD.new(), enemy_weapon)) + + # Group 3: Standalone entity (should NOT be included) + var standalone = Entity.new() + standalone.name = "Standalone" + standalone.add_component(C_TestF.new()) + + # Add all entities to world (don't add to scene tree) + world.add_entity(player) + world.add_entity(weapon) + world.add_entity(attachment) + world.add_entity(enemy) + world.add_entity(enemy_weapon) + world.add_entity(standalone) + + assert_that(world.entities).has_size(6) + + # Serialize ONLY entities with C_TestA (just the player) + var query = world.query.with_all([C_TestA]) + var serialized_data = ECS.serialize(query) + + print("=== PARTIAL SERIALIZATION RESULTS ===") + print("Total entities in world: ", world.entities.size()) + print("Entities serialized: ", serialized_data.entities.size()) + + # Should include Player + Weapon + Attachment (3 total) but NOT Enemy group or Standalone + assert_that(serialized_data.entities).has_size(3) + + var serialized_names = [] + for entity_data in serialized_data.entities: + serialized_names.append(entity_data.entity_name) + print("Serialized: ", entity_data.entity_name, " (auto-included: ", entity_data.auto_included, ")") + + # Verify correct entities were included + assert_that(serialized_names).contains("Player") + assert_that(serialized_names).contains("Weapon") + assert_that(serialized_names).contains("Attachment") + + # Verify incorrect entities were excluded + assert_that(serialized_names.has("Enemy")).is_false() + assert_that(serialized_names.has("EnemyWeapon")).is_false() + assert_that(serialized_names.has("Standalone")).is_false() + + # Verify auto-inclusion flags + var player_data = serialized_data.entities.filter(func(e): return e.entity_name == "Player")[0] + var weapon_data = serialized_data.entities.filter(func(e): return e.entity_name == "Weapon")[0] + var attachment_data = serialized_data.entities.filter(func(e): return e.entity_name == "Attachment")[0] + + assert_that(player_data.auto_included).is_false() # Original query + assert_that(weapon_data.auto_included).is_true() # Auto-included via Player relationship + assert_that(attachment_data.auto_included).is_true() # Auto-included via Weapon relationship + + print("=== Partial serialization with auto-inclusion working correctly ===") diff --git a/addons/gecs/tests/core/test_complex_relationship_serialization.gd.uid b/addons/gecs/tests/core/test_complex_relationship_serialization.gd.uid new file mode 100644 index 0000000..a4eed3f --- /dev/null +++ b/addons/gecs/tests/core/test_complex_relationship_serialization.gd.uid @@ -0,0 +1 @@ +uid://bdpuk46wqnhuw diff --git a/addons/gecs/tests/core/test_component.gd b/addons/gecs/tests/core/test_component.gd new file mode 100644 index 0000000..69f03b8 --- /dev/null +++ b/addons/gecs/tests/core/test_component.gd @@ -0,0 +1,163 @@ +extends GdUnitTestSuite + + + +func test_component_key_is_set_correctly(): + # Create an instance of a concrete Component subclass + var component = C_TestA.new() + # The key should be set to the resource path of the component's script + var expected_key = component.get_script().resource_path + assert_str("res://addons/gecs/tests/components/c_test_a.gd").is_equal(expected_key) + + +func test_component_query_matcher_equality(): + # Test _eq operator + var component = C_TestA.new(42) + + # Should match exact value + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_eq": 42}})).is_true() + # Should not match different value + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_eq": 10}})).is_false() + + +func test_component_query_matcher_inequality(): + # Test _ne operator + var component = C_TestA.new(42) + + # Should match different value + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_ne": 10}})).is_true() + # Should not match same value + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_ne": 42}})).is_false() + + +func test_component_query_matcher_greater_than(): + # Test _gt and _gte operators + var component = C_TestA.new(50) + + # _gt tests + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_gt": 49}})).is_true() + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_gt": 50}})).is_false() + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_gt": 51}})).is_false() + + # _gte tests + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_gte": 49}})).is_true() + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_gte": 50}})).is_true() + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_gte": 51}})).is_false() + + +func test_component_query_matcher_less_than(): + # Test _lt and _lte operators + var component = C_TestA.new(50) + + # _lt tests + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_lt": 51}})).is_true() + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_lt": 50}})).is_false() + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_lt": 49}})).is_false() + + # _lte tests + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_lte": 51}})).is_true() + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_lte": 50}})).is_true() + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_lte": 49}})).is_false() + + +func test_component_query_matcher_array_membership(): + # Test _in and _nin operators + var component = C_TestA.new(42) + + # _in tests + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_in": [40, 41, 42]}})).is_true() + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_in": [1, 2, 3]}})).is_false() + + # _nin tests + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_nin": [1, 2, 3]}})).is_true() + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_nin": [40, 41, 42]}})).is_false() + + +func test_component_query_matcher_custom_function(): + # Test func operator + var component = C_TestA.new(42) + + # Custom function that checks if value is even + var is_even = func(val): return val % 2 == 0 + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"func": is_even}})).is_true() + + # Custom function that checks if value is odd + var is_odd = func(val): return val % 2 == 1 + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"func": is_odd}})).is_false() + + # Custom function with complex logic + var in_range = func(val): return val >= 40 and val <= 50 + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"func": in_range}})).is_true() + + +func test_component_query_matcher_multiple_operators(): + # Test combining multiple operators (all must pass) + var component = C_TestA.new(50) + + # Should match: value >= 40 AND value <= 60 + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_gte": 40, "_lte": 60}})).is_true() + + # Should not match: value >= 40 AND value <= 45 + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_gte": 40, "_lte": 45}})).is_false() + + # Should match: value != 0 AND value > 30 + assert_bool(ComponentQueryMatcher.matches_query(component, {"value": {"_ne": 0, "_gt": 30}})).is_true() + + +func test_component_query_matcher_falsy_values(): + # Test that falsy values (0, false, null) are handled correctly + var component_zero = C_TestA.new(0) + + # Should match 0 exactly + assert_bool(ComponentQueryMatcher.matches_query(component_zero, {"value": {"_eq": 0}})).is_true() + assert_bool(ComponentQueryMatcher.matches_query(component_zero, {"value": {"_eq": 1}})).is_false() + + # Should handle 0 in ranges + assert_bool(ComponentQueryMatcher.matches_query(component_zero, {"value": {"_gte": 0}})).is_true() + assert_bool(ComponentQueryMatcher.matches_query(component_zero, {"value": {"_lte": 0}})).is_true() + assert_bool(ComponentQueryMatcher.matches_query(component_zero, {"value": {"_gt": 0}})).is_false() + + # Should handle negative numbers + var component_negative = C_TestA.new(-5) + assert_bool(ComponentQueryMatcher.matches_query(component_negative, {"value": {"_eq": -5}})).is_true() + assert_bool(ComponentQueryMatcher.matches_query(component_negative, {"value": {"_lt": 0}})).is_true() + + +func test_component_query_matcher_empty_query(): + # Empty query should match any component + var component = C_TestA.new(42) + assert_bool(ComponentQueryMatcher.matches_query(component, {})).is_true() + + +func test_component_query_matcher_nonexistent_property(): + # Should return false if property doesn't exist + var component = C_TestA.new(42) + assert_bool(ComponentQueryMatcher.matches_query(component, {"nonexistent": {"_eq": 10}})).is_false() + + +func test_component_query_matcher_multiple_properties(): + # Test querying multiple properties at once + var component = C_TestD.new(5) # Has 'points' property + + # Both properties must match + assert_bool(ComponentQueryMatcher.matches_query(component, { + "points": {"_eq": 5} + })).is_true() + + assert_bool(ComponentQueryMatcher.matches_query(component, { + "points": {"_eq": 10} + })).is_false() + + +func test_component_serialization(): + # Create an instance of a concrete Component subclass + var component_a = C_TestA.new(42) + var component_b = C_TestD.new(1) + + # Serialize the component + var serialized_data_a = component_a.serialize() + var serialized_data_b = component_b.serialize() + + # Check if the serialized data matches the expected values + assert_int(serialized_data_a["value"]).is_equal(42) + assert_int(serialized_data_b["points"]).is_equal(1) diff --git a/addons/gecs/tests/core/test_component.gd.uid b/addons/gecs/tests/core/test_component.gd.uid new file mode 100644 index 0000000..509d275 --- /dev/null +++ b/addons/gecs/tests/core/test_component.gd.uid @@ -0,0 +1 @@ +uid://4nqun3t8nb18 diff --git a/addons/gecs/tests/core/test_debug_tracking.gd b/addons/gecs/tests/core/test_debug_tracking.gd new file mode 100644 index 0000000..b21b1a9 --- /dev/null +++ b/addons/gecs/tests/core/test_debug_tracking.gd @@ -0,0 +1,178 @@ +extends GdUnitTestSuite + +# Test suite for System debug tracking (lastRunData) + +var world: World + +func before_test(): + world = World.new() + world.name = "TestWorld" + Engine.get_main_loop().root.add_child(world) + ECS.world = world + +func after_test(): + ECS.world = null + if is_instance_valid(world): + world.queue_free() + +func test_debug_tracking_process_mode(): + # Enable debug mode for these tests + ECS.debug = true + # Create entities + for i in range(10): + var entity = Entity.new() + entity.add_component(C_DebugTrackingTestA.new()) + world.add_entity(entity) + + # Create system with PROCESS execution method + var system = ProcessSystem.new() + world.add_system(system) + + # Process once + world.process(0.016) + + # Debug: Print what's in lastRunData + print("DEBUG: ECS.debug = ", ECS.debug) + print("DEBUG: lastRunData = ", system.lastRunData) + print("DEBUG: lastRunData keys = ", system.lastRunData.keys()) + + # Verify debug data + assert_that(system.lastRunData.has("system_name")).is_true() + assert_that(system.lastRunData.has("frame_delta")).is_true() + assert_that(system.lastRunData.has("entity_count")).is_true() + assert_that(system.lastRunData.has("execution_time_ms")).is_true() + + # Verify values + assert_that(system.lastRunData["frame_delta"]).is_equal(0.016) + assert_that(system.lastRunData["entity_count"]).is_equal(10) + assert_that(system.lastRunData["execution_time_ms"]).is_greater(0.0) + assert_that(system.lastRunData["parallel"]).is_equal(false) + + # Store first execution time + var first_exec_time = system.lastRunData["execution_time_ms"] + + # Process again + world.process(0.032) + + # Verify time is different (not accumulating) + var second_exec_time = system.lastRunData["execution_time_ms"] + assert_that(system.lastRunData["frame_delta"]).is_equal(0.032) + + # Times should be similar but not identical (and definitely not accumulated) + # If accumulating, second would be ~2x first + assert_that(second_exec_time).is_less(first_exec_time * 1.5) + print("First exec: %.3f ms, Second exec: %.3f ms" % [first_exec_time, second_exec_time]) + + +func test_debug_tracking_subsystems(): + # Enable debug mode for these tests + ECS.debug = true + # Create entities + for i in range(10): + var entity = Entity.new() + entity.add_component(C_DebugTrackingTestA.new()) + entity.add_component(C_DebugTrackingTestB.new()) + world.add_entity(entity) + + # Create system with SUBSYSTEMS execution method + var system = SubsystemsTestSystem.new() + world.add_system(system) + + # Process once + world.process(0.016) + + # Verify debug data + assert_that(system.lastRunData["execution_time_ms"]).is_greater(0.0) + + # Verify subsystem data + assert_that(system.lastRunData.has(0)).is_true() + assert_that(system.lastRunData.has(1)).is_true() + + # First subsystem + assert_that(system.lastRunData[0]["entity_count"]).is_equal(10) + + # Second subsystem + assert_that(system.lastRunData[1]["entity_count"]).is_equal(10) + + print("Subsystem 0: %s" % [system.lastRunData[0]]) + print("Subsystem 1: %s" % [system.lastRunData[1]]) + + +func test_debug_disabled_has_no_data(): + # Disable debug mode + ECS.debug = false + + # Create entities + for i in range(5): + var entity = Entity.new() + entity.add_component(C_DebugTrackingTestA.new()) + world.add_entity(entity) + + # Create system + var system = ProcessSystem.new() + world.add_system(system) + + # Process + world.process(0.016) + + # lastRunData should be empty or not updated when debug is off + # (It might still exist from a previous run, but shouldn't be updated) + var initial_data = system.lastRunData.duplicate() + + # Process again + world.process(0.016) + + # Data should not change (because ECS.debug = false) + assert_that(system.lastRunData).is_equal(initial_data) + + print("With ECS.debug=false, lastRunData remains unchanged: %s" % [system.lastRunData]) + + +# Test system - PROCESS mode +class ProcessSystem extends System: + func query() -> QueryBuilder: + return ECS.world.query.with_all([C_DebugTrackingTestA]) + + func process(entities: Array[Entity], components: Array, delta: float) -> void: + for entity in entities: + var comp = entity.get_component(C_DebugTrackingTestA) + comp.value += delta + +# Test system - unified process +class ProcessAllSystem extends System: + func query() -> QueryBuilder: + return ECS.world.query.with_all([C_DebugTrackingTestB]) + + func process(entities: Array[Entity], components: Array, delta: float) -> void: + for entity in entities: + var comp = entity.get_component(C_DebugTrackingTestB) + comp.count += 1 + +# Test system - batch processing with iterate +class ProcessBatchSystem extends System: + func query() -> QueryBuilder: + return ECS.world.query.with_all([C_DebugTrackingTestA]).iterate([C_DebugTrackingTestA]) + + func process(entities: Array[Entity], components: Array, delta: float) -> void: + var test_a_components = components[0] + for i in range(entities.size()): + test_a_components[i].value += delta + +# Test system - SUBSYSTEMS mode +class SubsystemsTestSystem extends System: + func sub_systems() -> Array[Array]: + return [ + [ECS.world.query.with_all([C_DebugTrackingTestA]), process_sub], + [ECS.world.query.with_all([C_DebugTrackingTestB]).iterate([C_DebugTrackingTestB]), batch_sub] + ] + + func process_sub(entities: Array[Entity], components: Array, delta: float) -> void: + for entity in entities: + var comp = entity.get_component(C_DebugTrackingTestA) + comp.value += delta + + func batch_sub(entities: Array[Entity], components: Array, delta: float) -> void: + if components.size() > 0 and components[0].size() > 0: + var test_b_components = components[0] + for i in range(entities.size()): + test_b_components[i].count += 1 diff --git a/addons/gecs/tests/core/test_debug_tracking.gd.uid b/addons/gecs/tests/core/test_debug_tracking.gd.uid new file mode 100644 index 0000000..3453e91 --- /dev/null +++ b/addons/gecs/tests/core/test_debug_tracking.gd.uid @@ -0,0 +1 @@ +uid://bk45ditcdxhih diff --git a/addons/gecs/tests/core/test_entity.gd b/addons/gecs/tests/core/test_entity.gd new file mode 100644 index 0000000..2a3e65e --- /dev/null +++ b/addons/gecs/tests/core/test_entity.gd @@ -0,0 +1,164 @@ +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + + + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + if world: + world.purge(false) + + +# TODO: We need to add the world here becuase remove fails because we don't have access to world + + +func test_add_and_get_component(): + var entity = auto_free(TestA.new()) + var comp = C_TestA.new() + entity.add_component(comp) + # Test that the component was added + assert_bool(entity.has_component(C_TestA)).is_true() + # Test retrieving the component + var retrieved_component = entity.get_component(C_TestA) + assert_str(type_string(typeof(retrieved_component))).is_equal(type_string(typeof(comp))) + +# Components need default values on init or they will error +# FIXME: How can we catch this in the code? +func test_add_entity_with_component_with_no_defaults_in_init(): + var entity = auto_free(Entity.new()) + # this line will lead to crash (the _init parameters has no default value) + assert_error(func(): entity.add_component(C_TestH.new(57))) + +func test_add_multiple_components_and_has(): + var entity = auto_free(TestB.new()) + var comp1 = C_TestA.new() + var comp2 = C_TestB.new() + entity.add_components([comp1, comp2]) + # Test that the components were added + assert_bool(entity.has_component(C_TestA)).is_true() + assert_bool(entity.has_component(C_TestB)).is_true() + assert_bool(entity.has_component(C_TestC)).is_false() + + +func test_remove_component(): + var entity = auto_free(TestB.new()) + var comp = C_TestB.new() + entity.add_component(comp) + entity.remove_component(C_TestB) + # Test that the component was removed + assert_bool(entity.has_component(C_TestB)).is_false() + + +func test_add_get_has_relationship(): + var entitya = auto_free(TestC.new()) + var entityb = auto_free(TestC.new()) + var r_testa_entitya = Relationship.new(C_TestA.new(), entitya) + # Add the relationship + entityb.add_relationship(r_testa_entitya) + # Test that the relationship was added + # With the actual relationship + assert_bool(entityb.has_relationship(r_testa_entitya)).is_true() + # with a matching relationship + assert_bool(entityb.has_relationship(Relationship.new(C_TestA.new(), entitya))).is_true() + # Test retrieving the relationship + # with the actual relationship + var inst_retrieved_relationship = entityb.get_relationship(r_testa_entitya) + assert_str(type_string(typeof(inst_retrieved_relationship))).is_equal( + type_string(typeof(r_testa_entitya)) + ) + # with a matching relationship + var class_retrieved_relationship = entityb.get_relationship( + Relationship.new(C_TestA.new(), entitya) + ) + assert_str(type_string(typeof(class_retrieved_relationship))).is_equal( + type_string(typeof(r_testa_entitya)) + ) + assert_str(type_string(typeof(class_retrieved_relationship))).is_equal( + type_string(typeof(Relationship.new(C_TestA.new(), entitya))) + ) + +func test_add_and_remove_component(): + var entity = auto_free(TestB.new()) + for i in range(99): + var comp = C_TestB.new() + entity.add_component(comp) + entity.remove_component(C_TestB) + print('_component_path_cache size=', entity._component_path_cache.size()) + + # Test memory leak + assert_int(entity._component_path_cache.size()).is_equal(0) + + +func test_remove_components_with_scripts(): + var entity = auto_free(TestB.new()) + var comp1 = C_TestA.new() + var comp2 = C_TestB.new() + var comp3 = C_TestC.new() + + # Add multiple components + entity.add_components([comp1, comp2, comp3]) + + # Verify all were added + assert_bool(entity.has_component(C_TestA)).is_true() + assert_bool(entity.has_component(C_TestB)).is_true() + assert_bool(entity.has_component(C_TestC)).is_true() + + # Remove multiple components by Script class + entity.remove_components([C_TestA, C_TestB]) + + # Test that the components were removed + assert_bool(entity.has_component(C_TestA)).is_false() + assert_bool(entity.has_component(C_TestB)).is_false() + # Test that C_TestC is still there + assert_bool(entity.has_component(C_TestC)).is_true() + + +func test_remove_components_with_instances(): + var entity = auto_free(TestB.new()) + var comp1 = C_TestA.new() + var comp2 = C_TestB.new() + var comp3 = C_TestC.new() + + # Add multiple components + entity.add_components([comp1, comp2, comp3]) + + # Verify all were added + assert_bool(entity.has_component(C_TestA)).is_true() + assert_bool(entity.has_component(C_TestB)).is_true() + assert_bool(entity.has_component(C_TestC)).is_true() + + # Remove multiple components by instance + entity.remove_components([comp1, comp2]) + + # Test that the components were removed + assert_bool(entity.has_component(C_TestA)).is_false() + assert_bool(entity.has_component(C_TestB)).is_false() + # Test that C_TestC is still there + assert_bool(entity.has_component(C_TestC)).is_true() + + +func test_remove_components_mixed(): + var entity = auto_free(TestB.new()) + var comp1 = C_TestA.new() + var comp2 = C_TestB.new() + var comp3 = C_TestC.new() + + # Add multiple components + entity.add_components([comp1, comp2, comp3]) + + # Remove with mixed Script and instance + entity.remove_components([C_TestA, comp2]) + + # Test that the components were removed + assert_bool(entity.has_component(C_TestA)).is_false() + assert_bool(entity.has_component(C_TestB)).is_false() + # Test that C_TestC is still there + assert_bool(entity.has_component(C_TestC)).is_true() diff --git a/addons/gecs/tests/core/test_entity.gd.uid b/addons/gecs/tests/core/test_entity.gd.uid new file mode 100644 index 0000000..b4d1b13 --- /dev/null +++ b/addons/gecs/tests/core/test_entity.gd.uid @@ -0,0 +1 @@ +uid://dh1uujht5xew7 diff --git a/addons/gecs/tests/core/test_entity_id_system.gd b/addons/gecs/tests/core/test_entity_id_system.gd new file mode 100644 index 0000000..2e18f7d --- /dev/null +++ b/addons/gecs/tests/core/test_entity_id_system.gd @@ -0,0 +1,246 @@ +extends GdUnitTestSuite + +## Test suite for the Entity ID system functionality +## Tests auto-generation, custom IDs, singleton behavior, and world-level enforcement + +var world: World + +func before_test(): + world = World.new() + world.name = "TestWorld" + add_child(world) + ECS.world = world + +func after_test(): + if is_instance_valid(world): + world.queue_free() + await await_idle_frame() + +func test_entity_id_auto_generation(): + # Test that entities auto-generate IDs in _enter_tree + var entity = Entity.new() + entity.name = "TestEntity" + + # ID should be empty before entering tree + assert_str(entity.id).is_empty() + + # Add to tree - triggers _enter_tree and ID generation + world.add_entity(entity) + + # ID should now be auto-generated + assert_str(entity.id).is_not_empty() + assert_bool(entity.id.length() > 0).is_true() + + # Should not change ID on subsequent checks + var first_id = entity.id + var second_id = entity.id + assert_str(second_id).is_equal(first_id) + +func test_entity_custom_id(): + # Test custom ID functionality for singleton entities + var entity = Entity.new() + entity.name = "SingletonEntity" + + # Set custom ID before adding to world + entity.id = "singleton_player" + assert_str(entity.id).is_equal("singleton_player") + + # Add to world - should preserve custom ID + world.add_entity(entity) + assert_str(entity.id).is_equal("singleton_player") + + # Custom ID should not change on subsequent access + var same_id = entity.id + assert_str(same_id).is_equal("singleton_player") + +func test_world_id_tracking(): + # Test that World tracks IDs and provides lookup functionality + var entity1 = Entity.new() + entity1.name = "Entity1" + entity1.id = "test_id_1" + + var entity2 = Entity.new() + entity2.name = "Entity2" + entity2.id = "test_id_2" + + # Add entities to world + world.add_entity(entity1) + world.add_entity(entity2) + + # Test lookup by ID + assert_object(world.get_entity_by_id("test_id_1")).is_same(entity1) + assert_object(world.get_entity_by_id("test_id_2")).is_same(entity2) + assert_object(world.get_entity_by_id("nonexistent")).is_null() + + # Test has_entity_with_id + assert_bool(world.has_entity_with_id("test_id_1")).is_true() + assert_bool(world.has_entity_with_id("test_id_2")).is_true() + assert_bool(world.has_entity_with_id("nonexistent")).is_false() + +func test_world_id_replacement(): + # Test singleton behavior - entities with same ID replace existing ones + # Create first entity with custom ID + var entity1 = Entity.new() + entity1.name = "FirstEntity" + entity1.id = "singleton_player" + var comp1 = C_TestA.new() + comp1.value = 100 + entity1.add_component(comp1) + world.add_entity(entity1) + + # Verify it's in the world + assert_int(world.entities.size()).is_equal(1) + assert_object(world.get_entity_by_id("singleton_player")).is_same(entity1) + + # Create second entity with same ID + var entity2 = Entity.new() + entity2.name = "ReplacementEntity" + entity2.id = "singleton_player" + var comp2 = C_TestA.new() + comp2.value = 200 + entity2.add_component(comp2) + + # Add to world - should replace first entity + world.add_entity(entity2) + + # Should still have only one entity + assert_int(world.entities.size()).is_equal(1) + # Should be the new entity + var found_entity = world.get_entity_by_id("singleton_player") + assert_object(found_entity).is_same(entity2) + assert_str(found_entity.name).is_equal("ReplacementEntity") + + # Verify component value is from new entity + var comp = found_entity.get_component(C_TestA) as C_TestA + assert_int(comp.value).is_equal(200) + +func test_auto_generated_id_tracking(): + # Test that auto-generated IDs are also tracked by the world + var entity = Entity.new() + entity.name = "AutoIDEntity" + # Don't set custom ID - let it auto-generate + + world.add_entity(entity) + + # Should have auto-generated ID + assert_str(entity.id).is_not_empty() + + # Should be trackable by ID + assert_object(world.get_entity_by_id(entity.id)).is_same(entity) + assert_bool(world.has_entity_with_id(entity.id)).is_true() + +func test_id_generation_format(): + # Test that generated IDs follow expected GUID format + var entity = Entity.new() + + # Add to tree to trigger ID generation + world.add_entity(entity) + + var id = entity.id + assert_str(id).is_not_empty() + assert_bool(id.contains("-")).is_true() + + var parts = id.split("-") + assert_int(parts.size()).is_equal(5) + + # All parts should be valid hex strings + for part in parts: + assert_bool(part.is_valid_hex_number()).is_true() + +func test_id_uniqueness(): + # Test that multiple entities get unique IDs + var ids = {} + var entities = [] + + # Generate 100 entities with auto IDs + for i in range(100): + var entity = Entity.new() + entity.name = "Entity%d" % i + world.add_entity(entity) + entities.append(entity) + + # Should not have seen this ID before + assert_bool(ids.has(entity.id)).is_false() + ids[entity.id] = true + + # All IDs should be unique + assert_int(ids.size()).is_equal(100) + +func test_remove_entity_clears_id_registry(): + # Test that removing entities clears them from ID registry + var entity = Entity.new() + entity.name = "TestEntity" + entity.id = "test_remove_id" + + world.add_entity(entity) + assert_bool(world.has_entity_with_id("test_remove_id")).is_true() + + world.remove_entity(entity) + assert_bool(world.has_entity_with_id("test_remove_id")).is_false() + assert_object(world.get_entity_by_id("test_remove_id")).is_null() + +func test_id_system_comprehensive_demo(): + # Comprehensive test demonstrating all ID system features + # Test 1: Auto ID generation + var auto_entity = Entity.new() + auto_entity.name = "AutoIDEntity" + world.add_entity(auto_entity) + + var generated_id = auto_entity.id + assert_str(generated_id).is_not_empty() # Should auto-generate + assert_bool(generated_id.contains("-")).is_true() # Should have correct GUID format + + # Should still have the same ID + assert_str(auto_entity.id).is_equal(generated_id) + + # Test 2: Custom ID singleton behavior + var player1 = Entity.new() + player1.name = "Player1" + player1.id = "singleton_player" + var comp1 = C_TestA.new() + comp1.value = 100 + player1.add_component(comp1) + world.add_entity(player1) + + assert_int(world.entities.size()).is_equal(2) # auto_entity + player1 + assert_object(world.get_entity_by_id("singleton_player")).is_same(player1) + + # Add second entity with same ID - should replace first + var player2 = Entity.new() + player2.name = "Player2" + player2.id = "singleton_player" + var comp2 = C_TestA.new() + comp2.value = 200 + player2.add_component(comp2) + world.add_entity(player2) + + assert_int(world.entities.size()).is_equal(2) # Should still be 2 (replacement occurred) + var found_entity = world.get_entity_by_id("singleton_player") + assert_object(found_entity).is_same(player2) # Should be the new entity + assert_str(found_entity.name).is_equal("Player2") + + var found_comp = found_entity.get_component(C_TestA) as C_TestA + assert_int(found_comp.value).is_equal(200) # Should have new entity's data + + # Test 3: Multiple entity tracking + var tracked_entities = [] + for i in range(3): + var entity = Entity.new() + entity.name = "TrackedEntity%d" % i + entity.id = "tracked_%d" % i + tracked_entities.append(entity) + world.add_entity(entity) + + # Verify all are tracked + for i in range(3): + var id = "tracked_%d" % i + assert_bool(world.has_entity_with_id(id)).is_true() + assert_object(world.get_entity_by_id(id)).is_same(tracked_entities[i]) + + # Test 4: ID registry cleanup on removal + world.remove_entity(tracked_entities[1]) + assert_bool(world.has_entity_with_id("tracked_1")).is_false() + assert_object(world.get_entity_by_id("tracked_1")).is_null() + # Others should still exist + assert_bool(world.has_entity_with_id("tracked_0")).is_true() + assert_bool(world.has_entity_with_id("tracked_2")).is_true() diff --git a/addons/gecs/tests/core/test_entity_id_system.gd.uid b/addons/gecs/tests/core/test_entity_id_system.gd.uid new file mode 100644 index 0000000..7c86ada --- /dev/null +++ b/addons/gecs/tests/core/test_entity_id_system.gd.uid @@ -0,0 +1 @@ +uid://d3n5subrpobw3 diff --git a/addons/gecs/tests/core/test_observers.gd b/addons/gecs/tests/core/test_observers.gd new file mode 100644 index 0000000..1684877 --- /dev/null +++ b/addons/gecs/tests/core/test_observers.gd @@ -0,0 +1,392 @@ +extends GdUnitTestSuite + + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + world.purge(false) + +func test_observer_receive_component_changed(): + world.add_system(TestASystem.new()) + var test_a_observer = TestAObserver.new() + world.add_observer(test_a_observer) + + # Create entities with the required components + var entity_a = TestA.new() + entity_a.name = "a" + entity_a.add_component(C_TestA.new()) + + var entity_b = TestB.new() + entity_b.name = "b" + entity_b.add_component(C_TestA.new()) + entity_b.add_component(C_TestB.new()) + + # issue #43 + var entity_a2 = TestA.new() + entity_a2.name = "a" + entity_a2.add_component(C_TestA.new()) + world.get_node(world.entity_nodes_root).add_child(entity_a2) + world.add_entity(entity_a2, null, false) + assert_int(test_a_observer.added_count).is_equal(1) + + + # Add some entities before systems + world.add_entities([entity_a, entity_b]) + assert_int(test_a_observer.added_count).is_equal(3) + + + # Run the systems once + print('process 1st') + world.process(0.1) + + # Check the event_count + assert_int(test_a_observer.event_count).is_equal(2) + + # Run the systems again + print('process 2nd') + world.process(0.1) + + # Check the event_count + assert_int(test_a_observer.event_count).is_equal(4) + + +## Test that observers detect when a component is added to an entity +func test_observer_on_component_added(): + var observer = O_ObserverTest.new() + world.add_observer(observer) + + # Create an entity without the component + var entity = Entity.new() + world.add_entity(entity) + + # Verify observer hasn't fired yet + assert_int(observer.added_count).is_equal(0) + + # Add the watched component + var component = C_ObserverTest.new() + entity.add_component(component) + + # Verify observer detected the addition + assert_int(observer.added_count).is_equal(1) + assert_object(observer.last_added_entity).is_equal(entity) + + +## Test that observers detect when a component is removed from an entity +func test_observer_on_component_removed(): + var observer = O_ObserverTest.new() + world.add_observer(observer) + + # Create an entity with the component + var entity = Entity.new() + var component = C_ObserverTest.new() + entity.add_component(component) + world.add_entity(entity) + + # Verify observer detected the addition + assert_int(observer.added_count).is_equal(1) + + # Reset and remove the component + observer.reset() + entity.remove_component(C_ObserverTest) + + # Verify observer detected the removal + assert_int(observer.removed_count).is_equal(1) + assert_object(observer.last_removed_entity).is_equal(entity) + assert_int(observer.added_count).is_equal(0) # Should remain 0 after reset + + +## Test that observers detect property changes on watched components +func test_observer_on_component_changed(): + var observer = O_ObserverTest.new() + world.add_observer(observer) + + # Create an entity with the component + var entity = Entity.new() + var component = C_ObserverTest.new(0, "initial") + entity.add_component(component) + world.add_entity(entity) + + # Reset the observer (it may have fired on add) + observer.reset() + + # Change the value property (this will emit property_changed signal) + component.value = 42 + + # Verify observer detected the change + assert_int(observer.changed_count).is_equal(1) + assert_object(observer.last_changed_entity).is_equal(entity) + assert_str(observer.last_changed_property).is_equal("value") + assert_int(observer.last_old_value).is_equal(0) + assert_int(observer.last_new_value).is_equal(42) + + # Change another property + component.name_prop = "changed" + + # Verify observer detected the second change + assert_int(observer.changed_count).is_equal(2) + assert_str(observer.last_changed_property).is_equal("name_prop") + assert_str(observer.last_old_value).is_equal("initial") + assert_str(observer.last_new_value).is_equal("changed") + + +## Test that observers respect query filters (only match entities that pass the query) +func test_observer_respects_query_filter(): + var health_observer = O_HealthObserver.new() + world.add_observer(health_observer) + + # Create entity with only health component (should NOT match - needs both components) + var entity_only_health = Entity.new() + entity_only_health.add_component(C_ObserverHealth.new()) + world.add_entity(entity_only_health) + + # Observer should NOT have fired (doesn't match query) + assert_int(health_observer.health_added_count).is_equal(0) + + # Create entity with both components (should match) + var entity_both = Entity.new() + entity_both.add_component(C_ObserverTest.new()) + entity_both.add_component(C_ObserverHealth.new()) + world.add_entity(entity_both) + + # Observer should have fired now (matches query) + assert_int(health_observer.health_added_count).is_equal(1) + + +## Test that multiple observers can watch the same component +func test_multiple_observers_same_component(): + var observer1 = O_ObserverTest.new() + var observer2 = O_ObserverTest.new() + world.add_observer(observer1) + world.add_observer(observer2) + + # Create an entity with the component + var entity = Entity.new() + var component = C_ObserverTest.new() + entity.add_component(component) + world.add_entity(entity) + + # Both observers should have detected the addition + assert_int(observer1.added_count).is_equal(1) + assert_int(observer2.added_count).is_equal(1) + + # Change the component + observer1.reset() + observer2.reset() + component.value = 100 + + # Both observers should have detected the change + assert_int(observer1.changed_count).is_equal(1) + assert_int(observer2.changed_count).is_equal(1) + + +## Test that observers can track multiple property changes +func test_observer_tracks_multiple_changes(): + var observer = O_ObserverTest.new() + world.add_observer(observer) + + # Create an entity with the component + var entity = Entity.new() + var component = C_ObserverTest.new(0, "start") + entity.add_component(component) + world.add_entity(entity) + + observer.reset() + + # Make multiple changes + component.value = 10 + component.value = 20 + component.name_prop = "middle" + component.value = 30 + + # Should have detected all 4 changes + assert_int(observer.changed_count).is_equal(4) + + +## Test observer with health component and query matching +func test_observer_health_low_health_alert(): + var health_observer = O_HealthObserver.new() + world.add_observer(health_observer) + + # Create entity with both components + var entity = Entity.new() + entity.add_component(C_ObserverTest.new()) + var health = C_ObserverHealth.new(100) + entity.add_component(health) + world.add_entity(entity) + + health_observer.reset() + + # Reduce health gradually + health.health = 50 + assert_int(health_observer.health_changed_count).is_equal(1) + assert_int(health_observer.low_health_alerts.size()).is_equal(0) + + health.health = 25 # Below threshold + assert_int(health_observer.health_changed_count).is_equal(2) + assert_int(health_observer.low_health_alerts.size()).is_equal(1) + assert_object(health_observer.low_health_alerts[0]).is_equal(entity) + + +## Test that observer doesn't fire when entity doesn't match query +func test_observer_ignores_non_matching_entities(): + var health_observer = O_HealthObserver.new() + world.add_observer(health_observer) + + # Create entity with only C_ObserverTest (not both components) + var entity = Entity.new() + entity.add_component(C_ObserverTest.new()) + world.add_entity(entity) + + # Try to add C_ObserverHealth to a different entity that doesn't have C_ObserverTest + var entity2 = Entity.new() + entity2.add_component(C_ObserverHealth.new()) + world.add_entity(entity2) + + # Observer should not have fired (entity2 doesn't match query) + assert_int(health_observer.health_added_count).is_equal(0) + + +## Test observer detects component addition before entity is added to world +func test_observer_component_added_before_entity_added(): + var observer = O_ObserverTest.new() + world.add_observer(observer) + + # Create entity and add component BEFORE adding to world + var entity = Entity.new() + var component = C_ObserverTest.new() + entity.add_component(component) + + # Observer shouldn't have fired yet + assert_int(observer.added_count).is_equal(0) + + # Now add to world + world.add_entity(entity) + + # Observer should fire now + assert_int(observer.added_count).is_equal(1) + + +## Test observer with component replacement +func test_observer_component_replacement(): + var observer = O_ObserverTest.new() + world.add_observer(observer) + + # Create entity with component + var entity = Entity.new() + var component1 = C_ObserverTest.new(10, "first") + entity.add_component(component1) + world.add_entity(entity) + + assert_int(observer.added_count).is_equal(1) + + # Replace the component (add_component on same type replaces) + var component2 = C_ObserverTest.new(20, "second") + entity.add_component(component2) + + # Should trigger both removed and added + assert_int(observer.removed_count).is_equal(1) + assert_int(observer.added_count).is_equal(2) + + +## Test that property changes without signal emission don't trigger observer +func test_observer_ignores_direct_property_changes(): + var observer = O_ObserverTest.new() + world.add_observer(observer) + + # Create entity with component + var entity = Entity.new() + var component = C_ObserverTest.new() + entity.add_component(component) + world.add_entity(entity) + + observer.reset() + + # Directly set the property WITHOUT using the setter + # This bypasses the property_changed signal + # Note: In GDScript, using the property name always calls the setter, + # so we need to access the internal variable directly + # For this test, we're verifying that ONLY setters that emit signals work + + # Using the setter (should trigger) + component.value = 42 + assert_int(observer.changed_count).is_equal(1) + + # The framework correctly requires explicit signal emission in setters + + +## Test observer with entity that starts matching query after component addition +func test_observer_entity_becomes_matching(): + var health_observer = O_HealthObserver.new() + world.add_observer(health_observer) + + # Create entity with only one component + var entity = Entity.new() + entity.add_component(C_ObserverTest.new()) + world.add_entity(entity) + + # Health observer shouldn't fire (needs both components) + assert_int(health_observer.health_added_count).is_equal(0) + + # Add the second component + entity.add_component(C_ObserverHealth.new()) + + # Now health observer should fire + assert_int(health_observer.health_added_count).is_equal(1) + + +## Test removing observer from world +func test_remove_observer(): + var observer = O_ObserverTest.new() + world.add_observer(observer) + + # Create entity with component + var entity = Entity.new() + entity.add_component(C_ObserverTest.new()) + world.add_entity(entity) + + assert_int(observer.added_count).is_equal(1) + + # Remove the observer + world.remove_observer(observer) + + # Add another entity - observer should not fire + var entity2 = Entity.new() + entity2.add_component(C_ObserverTest.new()) + world.add_entity(entity2) + + # Count should still be 1 (not 2) + assert_int(observer.added_count).is_equal(1) + + +## Test observer with multiple entities +func test_observer_with_multiple_entities(): + var observer = O_ObserverTest.new() + world.add_observer(observer) + + # Create multiple entities + for i in range(5): + var entity = Entity.new() + entity.add_component(C_ObserverTest.new(i)) + world.add_entity(entity) + + # Should have detected all 5 additions + assert_int(observer.added_count).is_equal(5) + + observer.reset() + + # Get all entities and modify their components + var entities = world.query.with_all([C_ObserverTest]).execute() + for entity in entities: + var comp = entity.get_component(C_ObserverTest) + comp.value = comp.value + 100 + + # Should have detected all 5 changes + assert_int(observer.changed_count).is_equal(5) diff --git a/addons/gecs/tests/core/test_observers.gd.uid b/addons/gecs/tests/core/test_observers.gd.uid new file mode 100644 index 0000000..e9c2bfd --- /dev/null +++ b/addons/gecs/tests/core/test_observers.gd.uid @@ -0,0 +1 @@ +uid://jr1qceldoims diff --git a/addons/gecs/tests/core/test_query_builder.gd b/addons/gecs/tests/core/test_query_builder.gd new file mode 100644 index 0000000..876899c --- /dev/null +++ b/addons/gecs/tests/core/test_query_builder.gd @@ -0,0 +1,1249 @@ +extends GdUnitTestSuite + + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + world.purge(false) + + +func test_query_entities_with_all_components(): + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + + var test_a = C_TestA.new() + var test_b = C_TestB.new() + var test_c = C_TestC.new() + + # Entity1 has TestA and TestB + entity1.add_component(test_a) + entity1.add_component(test_b) + # Entity2 has TestA only + entity2.add_component(test_a.duplicate()) + # Entity3 has all three components + entity3.add_component(test_a.duplicate()) + entity3.add_component(test_b.duplicate()) + entity3.add_component(test_c.duplicate()) + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + + # Query entities with TestA + var result = QueryBuilder.new(world).with_all([C_TestA]).execute() + assert_array(result).has_size(3) + + result = QueryBuilder.new(world).with_all([C_TestA, C_TestB]).execute() + assert_array(result).has_size(2) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity3)).is_true() + assert_bool(result.has(entity2)).is_false() + + +func test_query_entities_with_any_components(): + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + + var test_a = C_TestA.new() + var test_b = C_TestB.new() + var test_c = C_TestC.new() + + # Entity1 has TestA + entity1.add_component(test_a) + # Entity2 has TestB + entity2.add_component(test_b) + # Entity3 has TestC + entity3.add_component(test_c) + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + + # Query entities with any of TestA or TestB + var result = QueryBuilder.new(world).with_any([C_TestA, C_TestB]).execute() + assert_array(result).has_size(2) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity2)).is_true() + assert_bool(result.has(entity3)).is_false() + + +func test_query_entities_excluding_components(): + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + + var test_a = C_TestA.new() + var test_b = C_TestB.new() + + # Entity1 has TestA + entity1.add_component(test_a) + # Entity2 has TestA and TestB + entity2.add_component(test_a.duplicate()) + entity2.add_component(test_b) + # Entity3 has no components + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + + # Query entities with TestA but excluding those with TestB + var result = QueryBuilder.new(world).with_all([C_TestA]).with_none([C_TestB]).execute() + assert_array(result).has_size(1) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity2)).is_false() + assert_bool(result.has(entity3)).is_false() + + +func test_query_entities_with_all_and_any_components(): + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + var entity4 = Entity.new() + + var test_a = C_TestA.new() + var test_b = C_TestB.new() + var test_c = C_TestC.new() + var test_d = C_TestD.new() + + # Entity1 has TestA and TestB + entity1.add_component(test_a) + entity1.add_component(test_b) + # Entity2 has TestA, TestB, and TestC + entity2.add_component(test_a.duplicate()) + entity2.add_component(test_b.duplicate()) + entity2.add_component(test_c) + # Entity3 has TestA, TestB, and TestD + entity3.add_component(test_a.duplicate()) + entity3.add_component(test_b.duplicate()) + entity3.add_component(test_d) + # Entity4 has TestA only + entity4.add_component(test_a.duplicate()) + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + world.add_entity(entity4) + + # Query entities with TestA and TestB, and any of TestC or TestD + var result = ( + QueryBuilder.new(world).with_all([C_TestA, C_TestB]).with_any([C_TestC, C_TestD]).execute() + ) + assert_array(result).has_size(2) + assert_bool(result.has(entity2)).is_true() + assert_bool(result.has(entity3)).is_true() + assert_bool(result.has(entity1)).is_false() + assert_bool(result.has(entity4)).is_false() + + +func test_query_entities_with_any_and_exclude_components(): + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + var entity4 = Entity.new() + + var test_a = C_TestA.new() + var test_b = C_TestB.new() + var test_c = C_TestC.new() + + # Entity1 has TestA + entity1.add_component(test_a) + # Entity2 has TestB + entity2.add_component(test_b) + # Entity3 has TestC + entity3.add_component(test_c) + # Entity4 has TestA and TestB + entity4.add_component(test_a.duplicate()) + entity4.add_component(test_b.duplicate()) + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + world.add_entity(entity4) + + # Query entities with any of TestA or TestB, excluding TestC + var result = QueryBuilder.new(world).with_any([C_TestA, C_TestB]).with_none([C_TestC]).execute() + assert_array(result).has_size(3) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity2)).is_true() + assert_bool(result.has(entity4)).is_true() + assert_bool(result.has(entity3)).is_false() + + +func test_query_entities_with_all_any_and_exclude_components(): + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + var entity4 = Entity.new() + var entity5 = Entity.new() + + var test_a = C_TestA.new() + var test_b = C_TestB.new() + var test_c = C_TestC.new() + var test_d = C_TestD.new() + var test_e = C_TestE.new() + + # Entity1 has TestA, TestB, TestD + entity1.add_component(test_a) + entity1.add_component(test_b) + entity1.add_component(test_d) + # Entity2 has TestA, TestB, TestC + entity2.add_component(test_a.duplicate()) + entity2.add_component(test_b.duplicate()) + entity2.add_component(test_c) + # Entity3 has TestA, TestB, TestE + entity3.add_component(test_a.duplicate()) + entity3.add_component(test_b.duplicate()) + entity3.add_component(test_e) + # Entity4 has TestB, TestC + entity4.add_component(test_b.duplicate()) + entity4.add_component(test_c.duplicate()) + # Entity5 has TestA, TestB, TestC, TestD + entity5.add_component(test_a.duplicate()) + entity5.add_component(test_b.duplicate()) + entity5.add_component(test_c.duplicate()) + entity5.add_component(test_d.duplicate()) + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + world.add_entity(entity4) + world.add_entity(entity5) + + # Query entities with TestA and TestB, any of TestC or TestE, excluding TestD + var result = ( + QueryBuilder + .new(world) + .with_all([C_TestA, C_TestB]) + .with_any([C_TestC, C_TestE]) + .with_none([C_TestD]) + .execute() + ) + + assert_array(result).has_size(2) + assert_bool(result.has(entity1)).is_false() + assert_bool(result.has(entity2)).is_true() + assert_bool(result.has(entity3)).is_true() + assert_bool(result.has(entity4)).is_false() + assert_bool(result.has(entity5)).is_false() + + +func test_query_entities_with_nothing(): + var entity1 = Entity.new() + var entity2 = Entity.new() + world.add_entity(entity1) + world.add_entity(entity2) + + # Query with no components specified should return all entities + var result = QueryBuilder.new(world).execute() + assert_array(result).has_size(2) + + +func test_query_entities_excluding_only(): + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + + var test_c = C_TestC.new() + + # Entity1 has TestC + entity1.add_component(test_c) + # Entity2 and Entity3 have no components + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + + # Query excluding entities with TestC + var result = QueryBuilder.new(world).with_none([C_TestC]).execute() + assert_array(result).has_size(2) + assert_bool(result.has(entity2)).is_true() + assert_bool(result.has(entity3)).is_true() + assert_bool(result.has(entity1)).is_false() + + +func test_query_with_no_matching_entities(): + var entity1 = Entity.new() + var entity2 = Entity.new() + + var test_a = C_TestA.new() + var test_b = C_TestB.new() + + # Entity1 has TestA + entity1.add_component(test_a) + # Entity2 has TestB + entity2.add_component(test_b) + + world.add_entity(entity1) + world.add_entity(entity2) + + # Query entities with both TestA and TestB (no entity has both) + var result = QueryBuilder.new(world).with_all([C_TestA, C_TestB]).execute() + assert_array(result).has_size(0) + + # Edge case: Entity with duplicate components + var entity = Entity.new() + var test_a1 = C_TestA.new() + var test_a2 = C_TestA.new() + + # Add two TestA components to the same entity + entity.add_component(test_a1) + entity.add_component(test_a2) + + world.add_entity(entity) + + # Query entities with TestA + result = QueryBuilder.new(world).with_all([C_TestA]).execute() + assert_array(result).has_size(2) + assert_bool(result.has(entity)).is_true() + assert_bool(result.has(entity1)).is_true() + + +func test_query_entities_with_multiple_excludes(): + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + var entity4 = Entity.new() + + var test_c = C_TestC.new() + var test_a = C_TestA.new() + var test_d = C_TestD.new() + + # Entity1 has TestC + entity1.add_component(test_c) + # Entity2 has TestA and TestD + entity2.add_component(test_a) + entity2.add_component(test_d) + # Entity3 has TestD only + entity3.add_component(test_d.duplicate()) + # Entity4 has no components + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + world.add_entity(entity4) + + # Query excluding entities with TestC or TestD + var result = QueryBuilder.new(world).with_none([C_TestC, C_TestD]).execute() + assert_array(result).has_size(1) + assert_bool(result.has(entity4)).is_true() + assert_bool(result.has(entity1)).is_false() + assert_bool(result.has(entity2)).is_false() + assert_bool(result.has(entity3)).is_false() + + +func test_query_matches(): + var entitya = auto_free(Entity.new()) + var entityb = auto_free(Entity.new()) + var entityc = auto_free(Entity.new()) + var entityd = auto_free(Entity.new()) + var entitye = auto_free(Entity.new()) + + var test_a = C_TestA.new() + var test_b = C_TestB.new() + var test_c = C_TestC.new() + var test_d = C_TestD.new() + + # Entitya has TestA + entitya.add_component(test_a) + # Entityb has TestA and TestD + entityb.add_component(test_a.duplicate()) + entityb.add_component(test_d) + # Entityc has TestD only + entityc.add_component(test_d.duplicate()) + # Entityd has no components + # Entitye has TestA, TestB, TestC + entitye.add_component(test_a.duplicate()) + entitye.add_component(test_b) + entitye.add_component(test_c) + + var q = QueryBuilder.new(world) + + # test with no query (should match all entities) + assert_array(q.matches([entitya, entityb, entityc, entityd, entitye])).has_size(5) + q.clear() + # Test with_all + ( + assert_array(q.with_all([C_TestA]).matches([entitya, entityb, entityc, entityd, entitye])) + .has_size(3) + ) + ( + assert_bool( + q.with_all([C_TestA]).matches([entitya, entityb, entityc, entityd, entitye]).has( + entitya + ) + ) + .is_true() + ) + ( + assert_bool( + q.with_all([C_TestA]).matches([entitya, entityb, entityc, entityd, entitye]).has( + entityb + ) + ) + .is_true() + ) + ( + assert_bool( + q.with_all([C_TestA]).matches([entitya, entityb, entityc, entityd, entitye]).has( + entitye + ) + ) + .is_true() + ) + q.clear() + + # Test multiple with_all + ( + assert_array( + q.with_all([C_TestA, C_TestD]).matches([entitya, entityb, entityc, entityd, entitye]) + ) + .has_size(1) + ) + ( + assert_bool( + ( + q + .with_all([C_TestA, C_TestD]) + .matches([entitya, entityb, entityc, entityd, entitye]) + .has(entityb) + ) + ) + .is_true() + ) + q.clear() + + # Test with_none + assert_array(q.with_none([C_TestB]).matches([entitya, entityb, entityc, entityd])).has_size(4) + assert_array(q.with_none([C_TestB]).matches([entitya, entityb])).has_size(2) + q.clear() + + # Test with_any + ( + assert_array( + q.with_any([C_TestA, C_TestD]).matches([entitya, entityb, entityc, entityd, entitye]) + ) + .has_size(4) + ) + ( + assert_bool( + ( + q + .with_any([C_TestA, C_TestD]) + .matches([entitya, entityb, entityc, entityd, entitye]) + .has(entityc) + ) + ) + .is_true() + ) + ( + assert_bool( + ( + q + .with_any([C_TestA, C_TestD]) + .matches([entitya, entityb, entityc, entityd, entitye]) + .has(entityd) + ) + ) + .is_false() + ) + q.clear() + + # Test combination of with_all and with_any + ( + assert_array( + q.with_all([C_TestA]).with_any([C_TestB, C_TestC]).matches( + [entitya, entityb, entityc, entityd, entitye] + ) + ) + .has_size(1) + ) + ( + assert_bool( + ( + q + .with_all([C_TestA]) + .with_any([C_TestB, C_TestC]) + .matches([entitya, entityb, entityc, entityd, entitye]) + .has(entitye) + ) + ) + .is_true() + ) + q.clear() + + # Test combination of with_all and with_none + ( + assert_array( + q.with_all([C_TestA]).with_none([C_TestD]).matches( + [entitya, entityb, entityc, entityd, entitye] + ) + ) + .has_size(2) + ) + ( + assert_bool( + ( + q + .with_all([C_TestA]) + .with_none([C_TestD]) + .matches([entitya, entityb, entityc, entityd, entitye]) + .has(entitya) + ) + ) + .is_true() + ) + ( + assert_bool( + ( + q + .with_all([C_TestA]) + .with_none([C_TestD]) + .matches([entitya, entityb, entityc, entityd, entitye]) + .has(entitye) + ) + ) + .is_true() + ) + q.clear() + + # Test combination of all three query types + ( + assert_array( + q.with_all([C_TestA]).with_any([C_TestB, C_TestC]).with_none([C_TestD]).matches( + [entitya, entityb, entityc, entityd, entitye] + ) + ) + .has_size(1) + ) + ( + assert_bool( + ( + q + .with_all([C_TestA]) + .with_any([C_TestB, C_TestC]) + .with_none([C_TestD]) + .matches([entitya, entityb, entityc, entityd, entitye]) + .has(entitye) + ) + ) + .is_true() + ) + q.clear() + + +func test_query_matches_with_relationships(): + var entitya = auto_free(Entity.new()) + var entityb = auto_free(Entity.new()) + var entityc = auto_free(Entity.new()) + + var test_a = C_TestA.new() + var test_b = C_TestB.new() + var rel_a = Relationship.new(test_a, entityb) + var rel_b = Relationship.new(test_b, entityc) + + # EntityA has relationship with EntityB using TestA + entitya.add_relationship(rel_a) + # EntityB has relationship with EntityC using TestB + entityb.add_relationship(rel_b) + + var q = QueryBuilder.new(world) + + # Test with_relationship + var result = q.with_relationship([Relationship.new(C_TestA.new(), ECS.wildcard)]).matches( + [entitya, entityb, entityc] + ) + assert_array(result).has_size(1) + assert_bool(result.has(entitya)).is_true() + q.clear() + + # Test without_relationship + result = q.without_relationship([Relationship.new(C_TestA.new(), Entity)]).matches( + [entitya, entityb, entityc] + ) + assert_array(result).has_size(2) + assert_bool(result.has(entityb)).is_true() + assert_bool(result.has(entityc)).is_true() + q.clear() + + # Test combination of relationships and components + entitya.add_component(test_a.duplicate()) + result = q.with_all([C_TestA]).with_relationship([Relationship.new(C_TestA.new())]).matches( + [entitya, entityb, entityc] + ) + assert_array(result).has_size(1) + assert_bool(result.has(entitya)).is_true() + q.clear() + + +func test_query_with_component_query(): + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + var entity4 = Entity.new() + + var test_a = C_TestA.new() + var test_d = C_TestD.new() + + # Entity1 has TestC value 25 and TestA + entity1.add_component(C_TestC.new(25)) + entity1.add_component(test_a) + # Entity2 has TestA and TestC but value 10 + entity2.add_component(test_a) + entity2.add_component(C_TestC.new(10)) + # Entity3 has TestD only + entity3.add_component(test_d.duplicate()) + # Entity4 has no components + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + world.add_entity(entity4) + + # Query excluding entities with TestC or TestD + var result = ( + QueryBuilder.new(world).with_all([ {C_TestC: {"value": {"_eq": 25}}}, C_TestA]).execute() + ) + assert_array(result).has_size(1) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity2)).is_false() + assert_bool(result.has(entity3)).is_false() + assert_bool(result.has(entity4)).is_false() + + +func test_query_with_component_queries(): + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + var entity4 = Entity.new() + + # Entity1: TestC(value=25), TestD(points=100) + entity1.add_component(C_TestC.new(25)) + entity1.add_component(C_TestD.new(100)) + + # Entity2: TestC(value=10), TestD(points=50) + entity2.add_component(C_TestC.new(10)) + entity2.add_component(C_TestD.new(50)) + + # Entity3: TestC(value=25), TestD(points=25) + entity3.add_component(C_TestC.new(25)) + entity3.add_component(C_TestD.new(25)) + + # Entity4: TestC(value=30) + entity4.add_component(C_TestC.new(30)) + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + world.add_entity(entity4) + + # Test with_all with multiple component queries + var result = ( + QueryBuilder + .new(world) + .with_all([ {C_TestC: {"value": {"_eq": 25}}}, {C_TestD: {"points": {"_gt": 50}}}]) + .execute() + ) + assert_array(result).has_size(1) + assert_bool(result.has(entity1)).is_true() + + # Test with_any with component queries + result = ( + QueryBuilder + .new(world) + .with_any([ {C_TestC: {"value": {"_lt": 15}}}, {C_TestD: {"points": {"_gte": 100}}}]) + .execute() + ) + assert_array(result).has_size(2) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity2)).is_true() + + # Remove the with_none component query test and replace with regular component tests + result = QueryBuilder.new(world).with_none([C_TestD]).execute() + assert_array(result).has_size(1) + assert_bool(result.has(entity4)).is_true() + + # Test multiple operators in same query + result = ( + QueryBuilder.new(world).with_all([ {C_TestC: {"value": {"_gte": 20, "_lte": 25}}}]).execute() + ) + assert_array(result).has_size(2) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity3)).is_true() + + # Test combination of regular components and component queries + result = ( + QueryBuilder.new(world).with_all([C_TestD, {C_TestC: {"value": {"_gt": 20}}}]).execute() + ) + assert_array(result).has_size(2) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity3)).is_true() + + # Test _in and _nin operators + result = QueryBuilder.new(world).with_all([ {C_TestC: {"value": {"_in": [10, 25]}}}]).execute() + assert_array(result).has_size(3) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity2)).is_true() + assert_bool(result.has(entity3)).is_true() + + # Test complex combination of queries without with_none queries + result = ( + QueryBuilder + .new(world) + .with_all([ {C_TestC: {"value": {"_gte": 25}}}]) + .with_any([ {C_TestD: {"points": {"_gt": 75}}}, {C_TestD: {"points": {"_lt": 30}}}]) + .with_none([C_TestE]) + .execute() + ) # Only use simple component exclusion + assert_array(result).has_size(2) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity3)).is_true() + + # Test empty value matching + result = QueryBuilder.new(world).with_all([ {C_TestC: {}}]).execute() + assert_array(result).has_size(4) # Should match all entities with TestC + + # Test non-existent property + result = QueryBuilder.new(world).with_all([ {C_TestC: {"non_existent": {"_eq": 10}}}]).execute() + assert_array(result).has_size(0) # Should match no entities + + # Test empty world query with component query property + result = ( + QueryBuilder + .new(world) + .with_all([ {C_TestC: {"non_existent": {"_eq": 10}}}, C_TestD, C_TestE, C_TestA]) + .execute() + ) + assert_array(result).has_size(0) # Should match no entities + + +func test_query_entities_groups(): + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + + entity1.add_component(C_TestA.new()) + entity2.add_component(C_TestB.new()) + entity3.add_component(C_TestC.new()) + + # Add entities to groups + entity1.add_to_group("Player") + entity2.add_to_group("Enemy") + entity3.add_to_group("Enemy") + entity3.add_to_group("NPC") + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + + # Test with_group for "Player" + var result = QueryBuilder.new(world).with_group(["Player"]).execute() + assert_array(result).has_size(1) + assert_bool(result.has(entity1)).is_true() + + # Verify entity1 with C_TestA in "Player" + var check_player_a = ( + QueryBuilder.new(world).with_all([C_TestA]).with_group(["Player"]).execute() + ) + assert_array(check_player_a).has_size(1) + assert_bool(check_player_a.has(entity1)).is_true() + + # Test with_group for "Enemy" + result = QueryBuilder.new(world).with_group(["Enemy"]).execute() + assert_array(result).has_size(2) + assert_bool(result.has(entity2)).is_true() + assert_bool(result.has(entity3)).is_true() + + # Verify entity2 with C_TestB in "Enemy" + var check_enemy_b = QueryBuilder.new(world).with_all([C_TestB]).with_group(["Enemy"]).execute() + assert_array(check_enemy_b).has_size(1) + assert_bool(check_enemy_b.has(entity2)).is_true() + + # Verify entity3 with C_TestC in "Enemy" + var check_enemy_c = QueryBuilder.new(world).with_all([C_TestC]).with_group(["Enemy"]).execute() + assert_array(check_enemy_c).has_size(1) + assert_bool(check_enemy_c.has(entity3)).is_true() + + # Test without_group excluding "NPC" + result = QueryBuilder.new(world).with_group(["Enemy"]).without_group(["NPC"]).execute() + assert_array(result).has_size(1) + assert_bool(result.has(entity2)).is_true() + assert_bool(result.has(entity3)).is_false() + + # Verify excluding "NPC" removes entity3 + var check_enemy_c_no_npc = ( + QueryBuilder + .new(world) + .with_all([C_TestC]) + .with_group(["Enemy"]) + .without_group(["NPC"]) + .execute() + ) + assert_array(check_enemy_c_no_npc).has_size(0) + + +#func test_query_caching(): + ## Setup test entities + #var entities = [] + #for i in range(1000): # Create a large number of entities for performance testing + #var entity = Entity.new() + #if i % 2 == 0: + #entity.add_component(C_TestA.new()) + #if i % 3 == 0: + #entity.add_component(C_TestB.new()) + #if i % 4 == 0: + #entity.add_component(C_TestC.new()) + #entities.append(entity) + #world.add_entities(entities) +# + #var query = QueryBuilder.new(world) + #query.with_all([C_TestA, C_TestB]) +# + ## First execution - uncached + #var time_start = Time.get_ticks_usec() + #var result1 = query.execute() + #var uncached_time = Time.get_ticks_usec() - time_start +# + ## Second execution - should use cache + #time_start = Time.get_ticks_usec() + #var result2 = query.execute() + #var cached_time = Time.get_ticks_usec() - time_start +# + ## Verify results are identical + #assert_array(result1).is_equal(result2) +# + ## Verify cache is faster (should be significantly faster) + #assert_bool(cached_time < uncached_time).is_true() + #print("Uncached query time: %d ns" % uncached_time) + #print("Cached query time: %d ns" % cached_time) + #print("Cache speedup: %.2fx" % (float(uncached_time) / max(cached_time, 1))) +# + ## Test cache invalidation + #var new_entity = Entity.new() + #new_entity.add_component(C_TestA.new()) + #new_entity.add_component(C_TestB.new()) + #world.add_entity(new_entity) +# + #query.invalidate_cache() + #var result3 = query.execute() + ## Verify new entity is included after cache invalidation + #assert_bool(result3.has(new_entity)).is_true() + #assert_int(result3.size()).is_equal(result2.size() + 1) +# + ## Test that modifying an entity's components invalidates relevant queries + #var test_entity = result2[0] + #test_entity.remove_component(C_TestA) +# + #query.invalidate_cache() + #var result4 = query.execute() + #assert_bool(result4.has(test_entity)).is_false() + #assert_int(result4.size()).is_equal(result3.size() - 1) +# + +func test_query_cache_with_component_queries(): + # Setup test entities with varying component values + var entities = [] + for i in range(100): + var entity = Entity.new() + entity.add_component(C_TestC.new(i)) # Each entity has unique TestC value + world.add_entity(entity) + entities.append(entity) + + var query = QueryBuilder.new(world) + query.with_all([ {C_TestC: {"value": {"_gt": 50}}}]) + + # First execution - uncached + var time_start = Time.get_ticks_usec() + var result1 = query.execute() + var uncached_time = Time.get_ticks_usec() - time_start + + # Second execution - should use cache + time_start = Time.get_ticks_usec() + var result2 = query.execute() + var cached_time = Time.get_ticks_usec() - time_start + + # Verify results + assert_array(result1).is_equal(result2) + assert_int(result1.size()).is_equal(49) # Should have entities with values 51-99 + + # Verify cache is faster + assert_bool(cached_time < uncached_time).is_true() + print("Component query uncached time: %d ns" % uncached_time) + print("Component query cached time: %d ns" % cached_time) + print("Component query cache speedup: %.2fx" % (float(uncached_time) / max(cached_time, 1))) + + # Test cache invalidation with component value changes + var target_entity = result1[0] + var comp = target_entity.get_component(C_TestC) + comp.value = 25 # Change to value that shouldn't match query + + query.invalidate_cache() + var result3 = query.execute() + assert_bool(result3.has(target_entity)).is_false() + assert_int(result3.size()).is_equal(result2.size() - 1) + + +# Tests for relationship querying bug where with_relationship and without_relationship return same results +func test_with_relationship_vs_without_relationship_basic(): + # Create entities with and without relationships + var entity_with_rel = Entity.new() + var entity_without_rel = Entity.new() + var target = Entity.new() + + # Only entity_with_rel has a relationship + entity_with_rel.add_relationship(Relationship.new(C_TestA.new(), target)) + + world.add_entity(entity_with_rel) + world.add_entity(entity_without_rel) + world.add_entity(target) + + # Test with_relationship - should only return entity_with_rel + var with_result = QueryBuilder.new(world).with_relationship([Relationship.new(C_TestA.new(), null)]).execute() + assert_array(with_result).has_size(1) + assert_bool(with_result.has(entity_with_rel)).is_true() + assert_bool(with_result.has(entity_without_rel)).is_false() + + # Test without_relationship - should only return entity_without_rel (and target) + var without_result = QueryBuilder.new(world).without_relationship([Relationship.new(C_TestA.new(), null)]).execute() + assert_bool(without_result.has(entity_with_rel)).is_false() + assert_bool(without_result.has(entity_without_rel)).is_true() + + # These should NOT be equal! + assert_bool(with_result.size() == without_result.size()).is_false() + + +func test_with_relationship_null_target(): + # Test the exact case from the bug report + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + var target = Entity.new() + + # Add relationship to only entity1 and entity2 + entity1.add_relationship(Relationship.new(C_TestA.new(), target)) + entity2.add_relationship(Relationship.new(C_TestA.new(), target)) + # entity3 has NO relationships + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + world.add_entity(target) + + # Query with null target (wildcard) should find entities with ANY target for this relationship + var result = QueryBuilder.new(world).with_relationship([Relationship.new(C_TestA.new(), null)]).execute() + + # Should only find entity1 and entity2 + assert_array(result).has_size(2) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity2)).is_true() + assert_bool(result.has(entity3)).is_false() + assert_bool(result.has(target)).is_false() + + +func test_without_relationship_null_target(): + # Test without_relationship with null target + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + var target = Entity.new() + + # Add relationship to only entity1 and entity2 + entity1.add_relationship(Relationship.new(C_TestA.new(), target)) + entity2.add_relationship(Relationship.new(C_TestA.new(), target)) + # entity3 has NO relationships + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + world.add_entity(target) + + # Query WITHOUT this relationship should find only entity3 and target + var result = QueryBuilder.new(world).without_relationship([Relationship.new(C_TestA.new(), null)]).execute() + + # Should NOT find entity1 or entity2 + assert_bool(result.has(entity1)).is_false() + assert_bool(result.has(entity2)).is_false() + # Should find entity3 and target + assert_bool(result.has(entity3)).is_true() + assert_bool(result.has(target)).is_true() + + +func test_with_relationship_wildcard_target(): + # Test with ECS.wildcard explicitly + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + var target = Entity.new() + + entity1.add_relationship(Relationship.new(C_TestA.new(), target)) + entity2.add_relationship(Relationship.new(C_TestA.new(), target)) + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + world.add_entity(target) + + # Use ECS.wildcard explicitly + var result = QueryBuilder.new(world).with_relationship([Relationship.new(C_TestA.new(), ECS.wildcard)]).execute() + + assert_array(result).has_size(2) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity2)).is_true() + assert_bool(result.has(entity3)).is_false() + + +func test_with_relationship_specific_entity_target(): + # Test with a specific entity as target + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + var target_a = Entity.new() + var target_b = Entity.new() + + entity1.add_relationship(Relationship.new(C_TestA.new(), target_a)) + entity2.add_relationship(Relationship.new(C_TestA.new(), target_b)) + # entity3 has no relationships + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + world.add_entity(target_a) + world.add_entity(target_b) + + # Query for entities with relationship to target_a specifically + var result = QueryBuilder.new(world).with_relationship([Relationship.new(C_TestA.new(), target_a)]).execute() + + assert_array(result).has_size(1) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity2)).is_false() + assert_bool(result.has(entity3)).is_false() + + +func test_with_relationship_entity_archetype_target(): + # Test with entity archetype as target + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + var target = Entity.new() # Generic Entity type + + entity1.add_relationship(Relationship.new(C_TestA.new(), Entity)) + entity2.add_relationship(Relationship.new(C_TestA.new(), target)) + # entity3 has no relationships + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + world.add_entity(target) + + # Query for entities with relationship to Entity archetype + var result = QueryBuilder.new(world).with_relationship([Relationship.new(C_TestA.new(), Entity)]).execute() + + # Should find both entity1 and entity2 (entity2's target is an Entity instance) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity2)).is_true() + assert_bool(result.has(entity3)).is_false() + + +# Tests for with_group bug where nonexistent groups return all entities +func test_with_group_basic(): + # Create entities with and without groups + var entity_in_group = Entity.new() + var entity_not_in_group = Entity.new() + + entity_in_group.add_to_group("TestGroup") + # entity_not_in_group is not in any group + + world.add_entity(entity_in_group) + world.add_entity(entity_not_in_group) + + # Query for entities in "TestGroup" + var result = QueryBuilder.new(world).with_group(["TestGroup"]).execute() + + assert_array(result).has_size(1) + assert_bool(result.has(entity_in_group)).is_true() + assert_bool(result.has(entity_not_in_group)).is_false() + + +func test_with_group_nonexistent_group(): + # Test the exact bug: querying for a nonexistent group should return NO entities + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + + entity1.add_to_group("GroupA") + entity2.add_to_group("GroupB") + # entity3 has no groups + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + + # Query for a group that DOES NOT EXIST + var result = QueryBuilder.new(world).with_group(["NonexistentGroup"]).execute() + + # Should return ZERO entities, not all entities! + assert_array(result).has_size(0) + assert_bool(result.has(entity1)).is_false() + assert_bool(result.has(entity2)).is_false() + assert_bool(result.has(entity3)).is_false() + + +func test_with_group_vs_without_group(): + # Test that with_group and without_group return different results + var entity_in_group = Entity.new() + var entity_not_in_group = Entity.new() + + entity_in_group.add_to_group("TestGroup") + + world.add_entity(entity_in_group) + world.add_entity(entity_not_in_group) + + # with_group should find only entity_in_group + var with_result = QueryBuilder.new(world).with_group(["TestGroup"]).execute() + assert_array(with_result).has_size(1) + assert_bool(with_result.has(entity_in_group)).is_true() + + # without_group should find only entity_not_in_group + var without_result = QueryBuilder.new(world).without_group(["TestGroup"]).execute() + assert_array(without_result).has_size(1) + assert_bool(without_result.has(entity_not_in_group)).is_true() + + # These should be DIFFERENT! + assert_bool(with_result.size() == without_result.size()).is_true() # Both have 1 entity + assert_bool(with_result.has(entity_in_group)).is_true() + assert_bool(without_result.has(entity_not_in_group)).is_true() + # But they should not contain the same entities + assert_bool(with_result.has(entity_not_in_group)).is_false() + assert_bool(without_result.has(entity_in_group)).is_false() + + +func test_with_all_and_with_relationship_combination(): + # Test combining component and relationship queries + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + var target = Entity.new() + + # entity1 has component A and relationship + entity1.add_component(C_TestA.new()) + entity1.add_relationship(Relationship.new(C_TestB.new(), target)) + + # entity2 has only component A + entity2.add_component(C_TestA.new()) + + # entity3 has only relationship + entity3.add_relationship(Relationship.new(C_TestB.new(), target)) + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + world.add_entity(target) + + # Query for entities with both component A and the relationship + var result = ( + QueryBuilder.new(world) + .with_all([C_TestA]) + .with_relationship([Relationship.new(C_TestB.new(), null)]) + .execute() + ) + + # Should only find entity1 + assert_array(result).has_size(1) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity2)).is_false() + assert_bool(result.has(entity3)).is_false() + + +func test_with_all_and_with_group_combination(): + # Test combining component and group queries + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + + # entity1 has component A and is in group + entity1.add_component(C_TestA.new()) + entity1.add_to_group("TestGroup") + + # entity2 has only component A + entity2.add_component(C_TestA.new()) + + # entity3 is only in group + entity3.add_to_group("TestGroup") + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + + # Query for entities with both component A and in the group + var result = QueryBuilder.new(world).with_all([C_TestA]).with_group(["TestGroup"]).execute() + + # Should only find entity1 + assert_array(result).has_size(1) + assert_bool(result.has(entity1)).is_true() + assert_bool(result.has(entity2)).is_false() + assert_bool(result.has(entity3)).is_false() + + +func test_with_any_filters_instead_of_broadening(): + # This test documents current semantics of with_any(): it REQUIRES at least one of the listed + # components to be present (logical OR constraint) in addition to with_all()/relationships, + # instead of broadening the result set. Users sometimes expect with_any() to behave like + # "optionally include these components" (i.e. a union of baseline results plus entities that + # have the optional components). That is NOT the implemented behavior. + # + # Setup: + # - Two entities (e1, e2) both have C_TestA (acting like C_Health) and a damage relationship + # - Only e2 has C_TestC (acting like C_Breakable) + # Baseline query (with_all + relationship) returns BOTH entities. + # Adding with_any([C_TestC]) returns ONLY e2 (entities must now also have at least one of the any-list) + # If no entity had C_TestC then result would become empty + var e1 = Entity.new() + var e2 = Entity.new() + var target = Entity.new() # Relationship target entity + + # Components analogous to C_Health and C_Breakable + e1.add_component(C_TestA.new()) + e2.add_component(C_TestA.new()) + e2.add_component(C_TestC.new()) # Only e2 is "breakable" + + # Relationship marker analogous to R_Damaged_Any (using C_TestB as marker) + e1.add_relationship(Relationship.new(C_TestB.new(), target)) + e2.add_relationship(Relationship.new(C_TestB.new(), target)) + + world.add_entity(e1) + world.add_entity(e2) + world.add_entity(target) + + # Baseline query: both entities match (have C_TestA + damage relationship) + var baseline = ( + QueryBuilder + .new(world) + .with_all([C_TestA]) + .with_relationship([Relationship.new(C_TestB.new(), null)]) + .execute() + ) as Array[Entity] + assert_int(baseline.size()).is_equal(2) + assert_bool(baseline.has(e1)).is_true() + assert_bool(baseline.has(e2)).is_true() + + # Adding with_any([C_TestC]) NARROWS results to just e2 (must have at least one any-component) + var narrowed = ( + QueryBuilder + .new(world) + .with_all([C_TestA]) + .with_relationship([Relationship.new(C_TestB.new(), null)]) + .with_any([C_TestC]) + .execute() + ) as Array[Entity] + assert_int(narrowed.size()).is_equal(1) + assert_bool(narrowed.has(e2)).is_true() + assert_bool(narrowed.has(e1)).is_false() \ No newline at end of file diff --git a/addons/gecs/tests/core/test_query_builder.gd.uid b/addons/gecs/tests/core/test_query_builder.gd.uid new file mode 100644 index 0000000..94199a5 --- /dev/null +++ b/addons/gecs/tests/core/test_query_builder.gd.uid @@ -0,0 +1 @@ +uid://b06t0s7ajwlme diff --git a/addons/gecs/tests/core/test_query_cache_key_domains.gd b/addons/gecs/tests/core/test_query_cache_key_domains.gd new file mode 100644 index 0000000..1a12690 --- /dev/null +++ b/addons/gecs/tests/core/test_query_cache_key_domains.gd @@ -0,0 +1,30 @@ +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + +func after_test(): + if world: + world.purge(false) + +func test_all_vs_any_distinct_cache_key(): + var qb_all = world.query.with_all([C_DomainTestA, C_DomainTestB]) + var key_all = qb_all.get_cache_key() + var qb_any = world.query.with_any([C_DomainTestA, C_DomainTestB]) + var key_any = qb_any.get_cache_key() + assert_int(key_all).is_not_equal(key_any) + +func test_all_vs_mixed_not_colliding(): + var qb1 = world.query.with_all([C_DomainTestA]).with_any([C_DomainTestB]) + var qb2 = world.query.with_all([C_DomainTestA, C_DomainTestB]) + assert_int(qb1.get_cache_key()).is_not_equal(qb2.get_cache_key()) + +func test_any_vs_exclude_not_colliding(): + var qb3 = world.query.with_any([C_DomainTestA]) + var qb4 = world.query.with_none([C_DomainTestA]) + assert_int(qb3.get_cache_key()).is_not_equal(qb4.get_cache_key()) diff --git a/addons/gecs/tests/core/test_query_cache_key_domains.gd.uid b/addons/gecs/tests/core/test_query_cache_key_domains.gd.uid new file mode 100644 index 0000000..92b83c6 --- /dev/null +++ b/addons/gecs/tests/core/test_query_cache_key_domains.gd.uid @@ -0,0 +1 @@ +uid://dw542afdb7ydt diff --git a/addons/gecs/tests/core/test_query_domain_permutations.gd b/addons/gecs/tests/core/test_query_domain_permutations.gd new file mode 100644 index 0000000..e769524 --- /dev/null +++ b/addons/gecs/tests/core/test_query_domain_permutations.gd @@ -0,0 +1,81 @@ +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + +# Preload component scripts to ensure availability +const C_PermA = preload("res://addons/gecs/tests/components/c_perm_a.gd") +const C_PermB = preload("res://addons/gecs/tests/components/c_perm_b.gd") +const C_PermC = preload("res://addons/gecs/tests/components/c_perm_c.gd") +const C_PermD = preload("res://addons/gecs/tests/components/c_perm_d.gd") +const C_PermE = preload("res://addons/gecs/tests/components/c_perm_e.gd") +const C_PermF = preload("res://addons/gecs/tests/components/c_perm_f.gd") + +const ALL = [C_PermA, C_PermB] +const ANY = [C_PermC, C_PermD] +const NONE = [C_PermE, C_PermF] + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + +func after_test(): + if world: + world.purge(false) + +func _both_orders(arr: Array) -> Array: + if arr.size() < 2: + return [arr] + var rev = arr.duplicate(); rev.reverse() + return [arr, rev] + +func _cache_key(all: Array, any: Array, none: Array) -> int: + return world.query.with_all(all).with_any(any).with_none(none).get_cache_key() + +func test_permutation_invariance_all_any_none(): + var keys = [] + for all_var in _both_orders(ALL): + for any_var in _both_orders(ANY): + for none_var in _both_orders(NONE): + keys.append(_cache_key(all_var, any_var, none_var)) + var first = keys[0] + for k in keys: + assert_int(k).is_equal(first) + +func test_cross_domain_differentiation(): + var k1 = _cache_key([C_PermA, C_PermB], [C_PermC, C_PermD], [C_PermE, C_PermF]) + # Move C_PermB to ANY domain should change key + var k2 = _cache_key([C_PermA], [C_PermB, C_PermC, C_PermD], [C_PermE, C_PermF]) + assert_int(k1).is_not_equal(k2) + +func test_empty_domain_variants_unique(): + var k_all_only = world.query.with_all([C_PermA, C_PermB]).get_cache_key() + var k_any_only = world.query.with_any([C_PermA, C_PermB]).get_cache_key() + var k_none_only = world.query.with_none([C_PermA, C_PermB]).get_cache_key() + assert_int(k_all_only).is_not_equal(k_any_only) + assert_int(k_all_only).is_not_equal(k_none_only) + assert_int(k_any_only).is_not_equal(k_none_only) + +func test_domain_swaps_stability(): + # Swapping order inside a single domain should not change key + var k_orig = _cache_key(ALL, ANY, NONE) + var all_rev = ALL.duplicate(); all_rev.reverse() + var any_rev = ANY.duplicate(); any_rev.reverse() + var none_rev = NONE.duplicate(); none_rev.reverse() + var k_rev_combo = _cache_key(all_rev, any_rev, none_rev) + assert_int(k_orig).is_equal(k_rev_combo) + +func test_single_component_domains_invariance(): + # Reduce domains to single components, permutations collapse + var k1 = _cache_key([C_PermA], [C_PermC], [C_PermE]) + var k2 = _cache_key([C_PermA], [C_PermC], [C_PermE]) + assert_int(k1).is_equal(k2) + +func test_mixed_add_remove_domain_changes(): + # Adding a component to ANY changes key; removing restores original + var base = _cache_key(ALL, [C_PermC], NONE) + var added = _cache_key(ALL, [C_PermC, C_PermD], NONE) + assert_int(base).is_not_equal(added) + var restored = _cache_key(ALL, [C_PermC], NONE) + assert_int(restored).is_equal(base) diff --git a/addons/gecs/tests/core/test_query_domain_permutations.gd.uid b/addons/gecs/tests/core/test_query_domain_permutations.gd.uid new file mode 100644 index 0000000..715e5bb --- /dev/null +++ b/addons/gecs/tests/core/test_query_domain_permutations.gd.uid @@ -0,0 +1 @@ +uid://bl360eyrl22in diff --git a/addons/gecs/tests/core/test_query_order_insensitivity.gd b/addons/gecs/tests/core/test_query_order_insensitivity.gd new file mode 100644 index 0000000..1a467da --- /dev/null +++ b/addons/gecs/tests/core/test_query_order_insensitivity.gd @@ -0,0 +1,78 @@ +extends GdUnitTestSuite + +# Verifies that with_all([...]) matches entities regardless of component order both in +# entity component-add order and query component array order. Uses 15 distinct component types. + +var runner: GdUnitSceneRunner +var world: World + +var ALL_COMPONENT_TYPES = [ + C_OrderTestA, C_OrderTestB, C_OrderTestC, C_OrderTestD, C_OrderTestE, + C_OrderTestF, C_OrderTestG, C_OrderTestH, C_OrderTestI, C_OrderTestJ, + C_OrderTestK, C_OrderTestL, C_OrderTestM, C_OrderTestN, C_OrderTestO +] + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + +func after_test(): + if world: + world.purge(false) + +func _make_entity_with_components(order: Array) -> Entity: + var e = Entity.new() + for comp_type in order: + var comp = comp_type.new() + e.add_component(comp) + return e + +func test_with_all_order_independent(): + # Create entities with different component insertion orders + var shuffled1 = ALL_COMPONENT_TYPES.duplicate() + shuffled1.shuffle() + var shuffled2 = ALL_COMPONENT_TYPES.duplicate() + shuffled2.shuffle() + var shuffled3 = ALL_COMPONENT_TYPES.duplicate() + shuffled3.shuffle() + + var e1 = _make_entity_with_components(shuffled1) + var e2 = _make_entity_with_components(shuffled2) + var e3 = _make_entity_with_components(shuffled3) + world.add_entities([e1, e2, e3]) + + # Build multiple queries with different ordering of with_all component arrays + var q_base = world.query.with_all(ALL_COMPONENT_TYPES).execute() + var rev = ALL_COMPONENT_TYPES.duplicate() + rev.reverse() + var q_rev = world.query.with_all(rev).execute() + var alt = ALL_COMPONENT_TYPES.duplicate(); alt.shuffle() + var q_alt = world.query.with_all(alt).execute() + + # All queries should match all entities + assert_int(q_base.size()).is_equal(3) + assert_int(q_rev.size()).is_equal(3) + assert_int(q_alt.size()).is_equal(3) + + # Ensure same entity set (order may differ). Convert to Set of instance IDs. + var set_base = q_base.map(func(e): return e.get_instance_id()) + var set_rev = q_rev.map(func(e): return e.get_instance_id()) + var set_alt = q_alt.map(func(e): return e.get_instance_id()) + set_base.sort(); set_rev.sort(); set_alt.sort() + assert_array(set_base).is_equal(set_rev) + assert_array(set_base).is_equal(set_alt) + +func test_cache_key_consistency(): + # Verify cache key identical for different ordering + var qb1 = QueryBuilder.new(world).with_all(ALL_COMPONENT_TYPES.duplicate()) + var key1 = qb1.get_cache_key() + var rev2 = ALL_COMPONENT_TYPES.duplicate() + rev2.reverse() + var qb2 = QueryBuilder.new(world).with_all(rev2) + var key2 = qb2.get_cache_key() + var shuffled = ALL_COMPONENT_TYPES.duplicate(); shuffled.shuffle() + var qb3 = QueryBuilder.new(world).with_all(shuffled) + var key3 = qb3.get_cache_key() + assert_int(key1).is_equal(key2) + assert_int(key1).is_equal(key3) diff --git a/addons/gecs/tests/core/test_query_order_insensitivity.gd.uid b/addons/gecs/tests/core/test_query_order_insensitivity.gd.uid new file mode 100644 index 0000000..7522a94 --- /dev/null +++ b/addons/gecs/tests/core/test_query_order_insensitivity.gd.uid @@ -0,0 +1 @@ +uid://c8hseirwjt6oi diff --git a/addons/gecs/tests/core/test_relationship_hash.gd b/addons/gecs/tests/core/test_relationship_hash.gd new file mode 100644 index 0000000..10d609a --- /dev/null +++ b/addons/gecs/tests/core/test_relationship_hash.gd @@ -0,0 +1,165 @@ +extends GdUnitTestSuite + +const C_TestA = preload("res://addons/gecs/tests/components/c_test_a.gd") +const C_TestB = preload("res://addons/gecs/tests/components/c_test_b.gd") + +var runner: GdUnitSceneRunner +var world: World + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + +func after_test(): + world.purge(false) + +func test_relationship_string_representation(): + # Test that two semantically identical relationships produce the same string + var rel1 = Relationship.new(C_TestA.new(10), null) + var rel2 = Relationship.new(C_TestA.new(10), null) + + # These should produce the same string representation for cache keys + var str1 = str(rel1) + var str2 = str(rel2) + + print("rel1 string: ", str1) + print("rel2 string: ", str2) + + # They won't be equal as objects (different instances) + assert_bool(rel1 == rel2).is_false() + + # But they should match semantically + assert_bool(rel1.matches(rel2)).is_true() + + # The problem: their string representations are different! + # This breaks query caching + print("Strings equal? ", str1 == str2) + +func test_relationship_with_entity_targets(): + var entity1 = Entity.new() + var entity2 = Entity.new() + entity1.name = "entity1" + entity2.name = "entity2" + world.add_entity(entity1) + world.add_entity(entity2) + + var rel1 = Relationship.new(C_TestA.new(), entity1) + var rel2 = Relationship.new(C_TestA.new(), entity1) + var rel3 = Relationship.new(C_TestA.new(), entity2) + + print("rel1 with entity1: ", str(rel1)) + print("rel2 with entity1: ", str(rel2)) + print("rel3 with entity2: ", str(rel3)) + + # Should match same entity + assert_bool(rel1.matches(rel2)).is_true() + # Should not match different entity + assert_bool(rel1.matches(rel3)).is_false() + +func test_query_cache_key_with_relationships(): + # This test shows the actual problem with query caching + var entity = Entity.new() + world.add_entity(entity) + entity.add_component(C_TestA.new(5)) + entity.add_relationship(Relationship.new(C_TestB.new(), null)) + + # These two queries are semantically identical + var query1 = world.query.with_relationship([Relationship.new(C_TestB.new(), null)]) + var query2 = world.query.with_relationship([Relationship.new(C_TestB.new(), null)]) + + var key1 = query1.to_string() + var key2 = query2.to_string() + + print("Query1 cache key: ", key1) + print("Query2 cache key: ", key2) + + # These SHOULD be the same for proper caching + # But they're probably not because Relationship lacks to_string() + print("Cache keys equal? ", key1 == key2) + +func test_relationship_matching_with_multiple_relationships(): + # Test that relationship matching works regardless of order in relationships list + var target_entity = Entity.new() + target_entity.name = "target" + world.add_entity(target_entity) + + var entity = Entity.new() + entity.name = "test_entity" + world.add_entity(entity) + + # Add multiple relationships in specific order + entity.add_relationship(Relationship.new(C_TestA.new(1), target_entity)) + entity.add_relationship(Relationship.new(C_TestA.new(2), target_entity)) + entity.add_relationship(Relationship.new(C_TestB.new(99), target_entity)) + + print("Entity relationships count: ", entity.relationships.size()) + + # Try to find the C_TestB relationship - it's at index 2 + var has_testb = entity.has_relationship(Relationship.new(C_TestB.new(), target_entity)) + print("Has C_TestB relationship (at end of list): ", has_testb) + assert_bool(has_testb).is_true() + + # Now try when C_TestB is first + var entity2 = Entity.new() + entity2.name = "test_entity2" + world.add_entity(entity2) + + entity2.add_relationship(Relationship.new(C_TestB.new(99), target_entity)) + entity2.add_relationship(Relationship.new(C_TestA.new(1), target_entity)) + entity2.add_relationship(Relationship.new(C_TestA.new(2), target_entity)) + + var has_testb2 = entity2.has_relationship(Relationship.new(C_TestB.new(), target_entity)) + print("Has C_TestB relationship (at start of list): ", has_testb2) + assert_bool(has_testb2).is_true() + + # Test the actual relationship objects match + for i in range(entity.relationships.size()): + var rel = entity.relationships[i] + var test_rel = Relationship.new(C_TestB.new(), target_entity) + print("Relationship[", i, "] matches test_rel: ", rel.matches(test_rel)) + print(" - Relation types: ", rel.relation.get_script().resource_path, " vs ", test_rel.relation.get_script().resource_path) + print(" - Target IDs: ", rel.target.id if rel.target else "null", " vs ", test_rel.target.id if test_rel.target else "null") + print(" - Targets same instance: ", rel.target == test_rel.target) + +func test_query_with_multiple_relationships(): + # Test that queries find entities even when they have multiple relationships + var target_entity = Entity.new() + target_entity.name = "target" + world.add_entity(target_entity) + + var entity1 = Entity.new() + entity1.name = "entity1_single_rel" + world.add_entity(entity1) + entity1.add_relationship(Relationship.new(C_TestB.new(1), target_entity)) + + var entity2 = Entity.new() + entity2.name = "entity2_multi_rel" + world.add_entity(entity2) + entity2.add_relationship(Relationship.new(C_TestA.new(1), target_entity)) + entity2.add_relationship(Relationship.new(C_TestA.new(2), target_entity)) + entity2.add_relationship(Relationship.new(C_TestB.new(99), target_entity)) + + var entity3 = Entity.new() + entity3.name = "entity3_no_testb" + world.add_entity(entity3) + entity3.add_relationship(Relationship.new(C_TestA.new(5), target_entity)) + + print("\n=== Query Test ===") + print("entity1 relationships: ", entity1.relationships.size()) + print("entity2 relationships: ", entity2.relationships.size()) + print("entity3 relationships: ", entity3.relationships.size()) + + # Query for entities with C_TestB relationship + var query = world.query.with_relationship([Relationship.new(C_TestB.new(), target_entity)]) + var results = Array(query.execute()) + + print("\nQuery results count: ", results.size()) + for ent in results: + print(" - Found: ", ent.name) + + # Both entity1 and entity2 should be found + assert_bool(results.has(entity1)).is_true() + assert_bool(results.has(entity2)).is_true() + assert_bool(results.has(entity3)).is_false() + assert_int(results.size()).is_equal(2) diff --git a/addons/gecs/tests/core/test_relationship_hash.gd.uid b/addons/gecs/tests/core/test_relationship_hash.gd.uid new file mode 100644 index 0000000..73bf86a --- /dev/null +++ b/addons/gecs/tests/core/test_relationship_hash.gd.uid @@ -0,0 +1 @@ +uid://bpc0k3us7q6cd diff --git a/addons/gecs/tests/core/test_relationship_serialization.gd b/addons/gecs/tests/core/test_relationship_serialization.gd new file mode 100644 index 0000000..07859db --- /dev/null +++ b/addons/gecs/tests/core/test_relationship_serialization.gd @@ -0,0 +1,302 @@ +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + +func after_test(): + if world: + world.purge(false) + +func test_serialize_entity_with_basic_relationship(): + # Create two entities with a basic relationship + var entity_a = Entity.new() + entity_a.name = "EntityA" + entity_a.add_component(C_TestA.new()) + + var entity_b = Entity.new() + entity_b.name = "EntityB" + entity_b.add_component(C_TestB.new()) + + # Create relationship: A -> B + var relationship = Relationship.new(C_TestC.new(), entity_b) + entity_a.add_relationship(relationship) + + world.add_entity(entity_a) + world.add_entity(entity_b) + + # Serialize only entity A (entity B should be auto-included) + var query = world.query.with_all([C_TestA]) + var serialized_data = ECS.serialize(query) + + # Validate serialization + assert_that(serialized_data).is_not_null() + assert_that(serialized_data.entities).has_size(2) # Both A and B should be included + + # Check that entity B is marked as auto-included + var entity_a_data = serialized_data.entities.filter(func(e): return e.entity_name == "EntityA")[0] + var entity_b_data = serialized_data.entities.filter(func(e): return e.entity_name == "EntityB")[0] + + assert_that(entity_a_data.auto_included).is_false() # Original query entity + assert_that(entity_b_data.auto_included).is_true() # Auto-included dependency + + # Check relationship data + assert_that(entity_a_data.relationships).has_size(1) + var rel_data = entity_a_data.relationships[0] + assert_that(rel_data.target_type).is_equal("Entity") + assert_that(rel_data.target_entity_id).is_equal(entity_b.id) + +func test_deserialize_entity_with_basic_relationship(): + # Create and serialize entities with relationship + var entity_a = Entity.new() + entity_a.name = "EntityA" + entity_a.add_component(C_TestA.new()) + + var entity_b = Entity.new() + entity_b.name = "EntityB" + entity_b.add_component(C_TestB.new()) + + var relationship = Relationship.new(C_TestC.new(), entity_b) + entity_a.add_relationship(relationship) + + world.add_entity(entity_a) + world.add_entity(entity_b) + + # Serialize + var query = world.query.with_all([C_TestA]) + var serialized_data = ECS.serialize(query) + + # Save and load + var file_path = "res://reports/test_relationship_basic.tres" + ECS.save(serialized_data, file_path) + var deserialized_entities = ECS.deserialize(file_path) + + # Validate deserialization + assert_that(deserialized_entities).has_size(2) + + var des_entity_a = deserialized_entities.filter(func(e): return e.name == "EntityA")[0] + var des_entity_b = deserialized_entities.filter(func(e): return e.name == "EntityB")[0] + + # Check that relationships are restored + assert_that(des_entity_a.relationships).has_size(1) + var des_relationship = des_entity_a.relationships[0] + assert_that(des_relationship.target).is_equal(des_entity_b) + + # Cleanup + for entity in deserialized_entities: + auto_free(entity) + +func test_circular_relationships(): + # Create entities with circular relationships: A -> B -> A + var entity_a = Entity.new() + entity_a.name = "EntityA" + entity_a.add_component(C_TestA.new()) + + var entity_b = Entity.new() + entity_b.name = "EntityB" + entity_b.add_component(C_TestB.new()) + + # Create circular relationships + var rel_a_to_b = Relationship.new(C_TestC.new(), entity_b) + var rel_b_to_a = Relationship.new(C_TestD.new(), entity_a) + + entity_a.add_relationship(rel_a_to_b) + entity_b.add_relationship(rel_b_to_a) + + world.add_entity(entity_a) + world.add_entity(entity_b) + + # Serialize starting from entity A + var query = world.query.with_all([C_TestA]) + var serialized_data = ECS.serialize(query) + + # Should include both entities (no infinite loop) + assert_that(serialized_data.entities).has_size(2) + + # Deserialize and validate + var file_path = "res://reports/test_relationship_circular.tres" + ECS.save(serialized_data, file_path) + var deserialized_entities = ECS.deserialize(file_path) + + assert_that(deserialized_entities).has_size(2) + + var des_a = deserialized_entities.filter(func(e): return e.name == "EntityA")[0] + var des_b = deserialized_entities.filter(func(e): return e.name == "EntityB")[0] + + # Validate circular relationships are restored + assert_that(des_a.relationships).has_size(1) + assert_that(des_b.relationships).has_size(1) + assert_that(des_a.relationships[0].target).is_equal(des_b) + assert_that(des_b.relationships[0].target).is_equal(des_a) + + # Cleanup + for entity in deserialized_entities: + auto_free(entity) + +func test_component_target_relationship(): + # Create entity with component-based relationship + var entity = Entity.new() + entity.name = "EntityWithComponentRel" + entity.add_component(C_TestA.new()) + + # Create relationship with Component target + var target_component = C_TestB.new() + # Note: Components don't have a 'name' property, so we don't set it + var relationship = Relationship.new(C_TestC.new(), target_component) + entity.add_relationship(relationship) + + world.add_entity(entity) + + # Serialize and deserialize + var query = world.query.with_all([C_TestA]) + var serialized_data = ECS.serialize(query) + + var file_path = "res://reports/test_relationship_component.tres" + ECS.save(serialized_data, file_path) + var deserialized_entities = ECS.deserialize(file_path) + + # Validate + assert_that(deserialized_entities).has_size(1) + var des_entity = deserialized_entities[0] + assert_that(des_entity.relationships).has_size(1) + + var des_relationship = des_entity.relationships[0] + assert_that(des_relationship.target is C_TestB).is_true() + + # Cleanup + auto_free(des_entity) + +func test_script_target_relationship(): + # Create entity with script archetype relationship + var entity = Entity.new() + entity.name = "EntityWithScriptRel" + entity.add_component(C_TestA.new()) + + # Create relationship with Script target + var relationship = Relationship.new(C_TestC.new(), C_TestB) + entity.add_relationship(relationship) + + world.add_entity(entity) + + # Serialize and deserialize + var query = world.query.with_all([C_TestA]) + var serialized_data = ECS.serialize(query) + + var file_path = "res://reports/test_relationship_script.tres" + ECS.save(serialized_data, file_path) + var deserialized_entities = ECS.deserialize(file_path) + + # Validate + assert_that(deserialized_entities).has_size(1) + var des_entity = deserialized_entities[0] + assert_that(des_entity.relationships).has_size(1) + + var des_relationship = des_entity.relationships[0] + assert_that(des_relationship.target).is_equal(C_TestB) + + # Cleanup + auto_free(des_entity) + +func test_id_persistence_across_save_load_cycles(): + # Create entity and save its UUID + var entity = Entity.new() + entity.name = "UUIDTestEntity" + entity.add_component(C_TestA.new()) + + world.add_entity(entity) + var original_id = entity.id + + # Serialize, save, and load multiple times + var query = world.query.with_all([C_TestA]) + + for cycle in range(3): + var serialized_data = ECS.serialize(query) + var file_path = "res://reports/test_id_cycle_" + str(cycle) + ".tres" + ECS.save(serialized_data, file_path) + + var deserialized_entities = ECS.deserialize(file_path) + assert_that(deserialized_entities).has_size(1) + + var des_entity = deserialized_entities[0] + assert_that(des_entity.id).is_equal(original_id) + + # Cleanup + auto_free(des_entity) + +func test_deep_relationship_chain(): + # Create a chain: A -> B -> C -> D + var entities = [] + for i in range(4): + var entity = Entity.new() + entity.name = "Entity" + String.num(i) + entity.add_component(C_TestA.new()) + entities.append(entity) + world.add_entity(entity) + + # Create chain relationships + for i in range(3): + var relationship = Relationship.new(C_TestC.new(), entities[i + 1]) + entities[i].add_relationship(relationship) + + # Serialize starting from first entity only - create a query that matches just the first entity + # We'll use a unique component for the first entity + entities[0].add_component(C_TestE.new()) # Add unique component to first entity + var query = world.query.with_all([C_TestE]) + var serialized_data = ECS.serialize(query) + + # Should auto-include entire chain + assert_that(serialized_data.entities).has_size(4) + + # Verify auto-inclusion flags + var auto_included_count = 0 + var original_entity_count = 0 + + for entity_data in serialized_data.entities: + if entity_data.auto_included: + auto_included_count += 1 + else: + original_entity_count += 1 + + assert_that(original_entity_count).is_equal(1) # Only one entity from original query + assert_that(auto_included_count).is_equal(3) # Three entities auto-included + + # Test deserialization + var file_path = "res://reports/test_relationship_chain.tres" + ECS.save(serialized_data, file_path) + var deserialized_entities = ECS.deserialize(file_path) + + assert_that(deserialized_entities).has_size(4) + + # Cleanup + for entity in deserialized_entities: + auto_free(entity) + +func test_backward_compatibility_no_relationships(): + # Test that entities without relationships still work + var entity = Entity.new() + entity.name = "NoRelationshipEntity" + entity.add_component(C_TestA.new()) + + world.add_entity(entity) + + # Serialize and deserialize + var query = world.query.with_all([C_TestA]) + var serialized_data = ECS.serialize(query) + + var file_path = "res://reports/test_no_relationships.tres" + ECS.save(serialized_data, file_path) + var deserialized_entities = ECS.deserialize(file_path) + + # Should work normally + assert_that(deserialized_entities).has_size(1) + var des_entity = deserialized_entities[0] + assert_that(des_entity.name).is_equal("NoRelationshipEntity") + assert_that(des_entity.relationships).has_size(0) + assert_that(des_entity.id).is_not_equal("") + + # Cleanup + auto_free(des_entity) diff --git a/addons/gecs/tests/core/test_relationship_serialization.gd.uid b/addons/gecs/tests/core/test_relationship_serialization.gd.uid new file mode 100644 index 0000000..af7daaf --- /dev/null +++ b/addons/gecs/tests/core/test_relationship_serialization.gd.uid @@ -0,0 +1 @@ +uid://d1xbolxpx2n81 diff --git a/addons/gecs/tests/core/test_relationships.gd b/addons/gecs/tests/core/test_relationships.gd new file mode 100644 index 0000000..d6d9d7a --- /dev/null +++ b/addons/gecs/tests/core/test_relationships.gd @@ -0,0 +1,1017 @@ +extends GdUnitTestSuite + +const C_Likes = preload("res://addons/gecs/tests/components/c_test_a.gd") +const C_Loves = preload("res://addons/gecs/tests/components/c_test_b.gd") +const C_Eats = preload("res://addons/gecs/tests/components/c_test_c.gd") +const C_IsCryingInFrontOf = preload("res://addons/gecs/tests/components/c_test_d.gd") +const C_IsAttacking = preload("res://addons/gecs/tests/components/c_test_e.gd") +const Person = preload("res://addons/gecs/tests/entities/e_test_a.gd") +const TestB = preload("res://addons/gecs/tests/entities/e_test_b.gd") +const TestC = preload("res://addons/gecs/tests/entities/e_test_c.gd") + +var runner: GdUnitSceneRunner +var world: World + +var e_bob: Person +var e_alice: Person +var e_heather: Person +var e_apple: GecsFood +var e_pizza: GecsFood + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + world.purge(false) + + +func before_test(): + e_bob = Person.new() + e_bob.name = "e_bob" + e_alice = Person.new() + e_alice.name = "e_alice" + e_heather = Person.new() + e_heather.name = "e_heather" + e_apple = GecsFood.new() + e_apple.name = "e_apple" + e_pizza = GecsFood.new() + e_pizza.name = "e_pizza" + + world.add_entity(e_bob) + world.add_entity(e_alice) + world.add_entity(e_heather) + world.add_entity(e_apple) + world.add_entity(e_pizza) + + # Create our relationships + # bob likes alice + e_bob.add_relationship(Relationship.new(C_Likes.new(), e_alice)) + # alice loves heather + e_alice.add_relationship(Relationship.new(C_Loves.new(), e_heather)) + # heather likes ALL food both apples and pizza + e_heather.add_relationship(Relationship.new(C_Likes.new(), GecsFood)) + # heather eats 5 apples + e_heather.add_relationship(Relationship.new(C_Eats.new(5), e_apple)) + # Alice attacks all food + e_alice.add_relationship(Relationship.new(C_IsAttacking.new(), GecsFood)) + # bob cries in front of everyone + e_bob.add_relationship(Relationship.new(C_IsCryingInFrontOf.new(), Person)) + # Bob likes ONLY pizza even though there are other foods so he doesn't care for apples + e_bob.add_relationship(Relationship.new(C_Likes.new(), e_pizza)) + + +func test_with_relationships(): + # Any entity that likes alice + var ents_that_likes_alice = Array( + ECS.world.query.with_relationship([Relationship.new(C_Likes.new(), e_alice)]).execute() + ) + assert_bool(ents_that_likes_alice.has(e_bob)).is_true() # bob likes alice + assert_bool(ents_that_likes_alice.size() == 1).is_true() # just bob likes alice + + +func test_with_relationships_entity_wildcard_target_remove_relationship(): + # Any entity with any relations toward heather + var ents_with_rel_to_heather = ( + ECS.world.query.with_relationship([Relationship.new(null, e_heather)]).execute() + ) + assert_bool(Array(ents_with_rel_to_heather).has(e_alice)).is_true() # alice loves heather + assert_bool(Array(ents_with_rel_to_heather).has(e_bob)).is_true() # bob is crying in front of people so he has a relation to heather because she's a person allegedly + assert_bool(Array(ents_with_rel_to_heather).size() == 2).is_true() # 2 entities have relations to heather + + # alice no longer loves heather + e_alice.remove_relationship(Relationship.new(C_Loves.new(), e_heather)) + # bob stops crying in front of people + e_bob.remove_relationship(Relationship.new(C_IsCryingInFrontOf.new(), Person)) + ents_with_rel_to_heather = ( + ECS.world.query.with_relationship([Relationship.new(null, e_heather)]).execute() + ) + assert_bool(Array(ents_with_rel_to_heather).size() == 0).is_true() # nobody has any relations with heather now :( + + +func test_with_relationships_entity_target(): + # Any entity that eats 5 apples + ( + assert_bool( + ( + Array( + ( + ECS + .world + .query + .with_relationship([Relationship.new(C_Eats.new(5), e_apple)]) + .execute() + ) + ) + .has(e_heather) + ) + ) + .is_true() + ) # heather eats 5 apples + + +func test_with_relationships_archetype_target(): + # any entity that likes the food entity archetype + ( + assert_bool( + ( + Array( + ( + ECS + .world + .query + .with_relationship([Relationship.new(C_Eats.new(5), e_apple)]) + .execute() + ) + ) + .has(e_heather) + ) + ) + .is_true() + ) # heather likes food + + +func test_with_relationships_wildcard_target(): + # Any entity that likes anything + var ents_that_like_things = ( + ECS.world.query.with_relationship([Relationship.new(C_Likes.new(), null)]).execute() + ) + assert_bool(Array(ents_that_like_things).has(e_bob)).is_true() # bob likes alice + assert_bool(Array(ents_that_like_things).has(e_heather)).is_true() # heather likes food + + # Any entity that likes anything also (Just a different way to write the query) + var ents_that_like_things_also = ( + ECS.world.query.with_relationship([Relationship.new(C_Likes.new())]).execute() + ) + assert_bool(Array(ents_that_like_things_also).has(e_bob)).is_true() # bob likes alice + assert_bool(Array(ents_that_like_things_also).has(e_heather)).is_true() # heather likes food + + +func test_with_relationships_wildcard_relation(): + # Any entity with any relation to the Food archetype + var any_relation_to_food = ( + ECS.world.query.with_relationship([Relationship.new(ECS.wildcard, GecsFood)]).execute() + ) + assert_bool(Array(any_relation_to_food).has(e_heather)).is_true() # heather likes food. but i mean cmon we all do + + +func test_archetype_and_entity(): + # we should be able to assign a specific entity as a target, and then match that by using the archetype class + # we know that heather likes food, so we can use the archetype class to match that. She should like pizza and apples because they're both food and she likes food + var entities_that_like_food = ( + ECS + .world + .query + .with_relationship([Relationship.new(C_Likes.new(), GecsFood)]) + .execute() + ) + assert_bool(entities_that_like_food.has(e_heather)).is_true() # heather likes food + assert_bool(entities_that_like_food.has(e_bob)).is_true() # bob likes a specific food but still a food + assert_bool(Array(entities_that_like_food).size() == 2).is_true() # only one entity likes all food + + # Because heather likes food of course she likes apples + var entities_that_like_apples = ( + ECS.world.query.with_relationship([Relationship.new(C_Likes.new(), e_apple)]).execute() + ) + assert_bool(entities_that_like_apples.has(e_heather)).is_true() + + # we also know that bob likes pizza which is also food but it's an entity so we can't use the archetype class to match that but we can match with the entitiy pizza + var entities_that_like_pizza = ( + ECS.world.query.with_relationship([Relationship.new(C_Likes.new(), e_pizza)]).execute() + ) + assert_bool(entities_that_like_pizza.has(e_bob)).is_true() # bob only likes pizza + assert_bool(entities_that_like_pizza.has(e_heather)).is_true() # heather likes food so of course she likes pizza + +func test_weak_relationship_matching(): + var heather_eats_apples = e_heather.get_relationship(Relationship.new(C_Eats.new(), e_apple)) + var heather_has_eats_apples = e_heather.has_relationship(Relationship.new(C_Eats.new(), e_apple)) + var bob_doesnt_eat_apples = e_bob.get_relationship(Relationship.new(C_Eats.new(), e_apple)) + var bob_has_eats_apples = e_bob.has_relationship(Relationship.new(C_Eats.new(), e_apple)) + assert_bool(heather_eats_apples != null).is_true() # heather eats apples + assert_bool(heather_has_eats_apples).is_true() # heather eats apples + assert_bool(bob_doesnt_eat_apples == null).is_true() # bob doesn't eat apples + assert_bool(bob_has_eats_apples).is_false() # bob doesn't eat apples + + +func test_weak_vs_strong_component_matching(): + # Test that type matching only cares about component type, not data + # Component queries care about both type and data + # Add relationships with different C_Eats values + e_bob.add_relationship(Relationship.new(C_Eats.new(3), e_apple)) # bob eats 3 apples + e_alice.add_relationship(Relationship.new(C_Eats.new(7), e_apple)) # alice eats 7 apples + + # Component queries should only find exact matches + var strong_match_3_apples = e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 3}}}, e_apple)) + var strong_match_5_apples = e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 5}}}, e_apple)) + var strong_match_7_apples = e_alice.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 7}}}, e_apple)) + + assert_bool(strong_match_3_apples).is_true() # bob eats exactly 3 apples + assert_bool(strong_match_5_apples).is_false() # bob doesn't eat exactly 5 apples + assert_bool(strong_match_7_apples).is_true() # alice eats exactly 7 apples + + # Type matching should find any C_Eats relationship regardless of value + var weak_match_any_eats_bob = e_bob.has_relationship(Relationship.new(C_Eats.new(), e_apple)) + var weak_match_any_eats_alice = e_alice.has_relationship(Relationship.new(C_Eats.new(), e_apple)) + + assert_bool(weak_match_any_eats_bob).is_true() # bob eats apples (any amount) + assert_bool(weak_match_any_eats_alice).is_true() # alice eats apples (any amount) + + +func test_multiple_relationships_same_component_type(): + # Test having multiple relationships with the same component type but different targets + # Bob likes multiple entities + e_bob.add_relationship(Relationship.new(C_Likes.new(), e_heather)) # bob also likes heather + + # Now bob likes both alice and heather + var bob_likes_alice = e_bob.has_relationship(Relationship.new(C_Likes.new(), e_alice)) + var bob_likes_heather = e_bob.has_relationship(Relationship.new(C_Likes.new(), e_heather)) + var bob_likes_pizza = e_bob.has_relationship(Relationship.new(C_Likes.new(), e_pizza)) + + assert_bool(bob_likes_alice).is_true() # bob likes alice + assert_bool(bob_likes_heather).is_true() # bob also likes heather + assert_bool(bob_likes_pizza).is_true() # bob also likes pizza + + # Query should find bob for any of these likes relationships + var entities_that_like_alice = Array(ECS.world.query.with_relationship([Relationship.new(C_Likes.new(), e_alice)]).execute()) + var entities_that_like_heather = Array(ECS.world.query.with_relationship([Relationship.new(C_Likes.new(), e_heather)]).execute()) + + assert_bool(entities_that_like_alice.has(e_bob)).is_true() + assert_bool(entities_that_like_heather.has(e_bob)).is_true() + + +func test_component_data_preservation_in_weak_matching(): + # Test that when using type matching on entities directly, we can still retrieve the actual component data + # Note: We need to be careful about existing relationships from setup + # First, remove any existing C_Eats relationships to avoid conflicts + var existing_bob_eats = e_bob.get_relationships(Relationship.new(C_Eats.new(), null)) + for rel in existing_bob_eats: + e_bob.remove_relationship(rel) + var existing_alice_eats = e_alice.get_relationships(Relationship.new(C_Eats.new(), null)) + for rel in existing_alice_eats: + e_alice.remove_relationship(rel) + + # Add eating relationships with different amounts + e_bob.add_relationship(Relationship.new(C_Eats.new(10), e_pizza)) # bob eats 10 pizza slices + e_alice.add_relationship(Relationship.new(C_Eats.new(2), e_pizza)) # alice eats 2 pizza slices + + # Use type matching to find the relationships, but verify we get the correct data + var bob_eats_pizza_rel = e_bob.get_relationship(Relationship.new(C_Eats.new(), e_pizza)) # type match + var alice_eats_pizza_rel = e_alice.get_relationship(Relationship.new(C_Eats.new(), e_pizza)) # type match + + assert_bool(bob_eats_pizza_rel != null).is_true() + assert_bool(alice_eats_pizza_rel != null).is_true() + + # The actual component data should be preserved + assert_int(bob_eats_pizza_rel.relation.value).is_equal(10) # bob's actual eating amount + assert_int(alice_eats_pizza_rel.relation.value).is_equal(2) # alice's actual eating amount + + +func test_query_with_strong_relationship_matching(): + # Test query system with component query matching + # Add multiple eating relationships with different amounts + e_bob.add_relationship(Relationship.new(C_Eats.new(15), e_pizza)) + e_alice.add_relationship(Relationship.new(C_Eats.new(8), e_apple)) + + # Query for entities that eat exactly 15 pizza - should find bob + var pizza_eaters_15 = Array(ECS.world.query.with_relationship([Relationship.new({C_Eats: {'value': {"_eq": 15}}}, e_pizza)]).execute()) + assert_bool(pizza_eaters_15.has(e_bob)).is_true() # bob eats exactly 15 pizza + assert_bool(pizza_eaters_15.has(e_heather)).is_false() # heather doesn't eat pizza + + # Query for entities that eat exactly 8 apples - should find alice + var apple_eaters_8 = Array(ECS.world.query.with_relationship([Relationship.new({C_Eats: {'value': {"_eq": 8}}}, e_apple)]).execute()) + assert_bool(apple_eaters_8.has(e_alice)).is_true() # alice eats exactly 8 apples + assert_bool(apple_eaters_8.has(e_heather)).is_false() # heather eats 5 apples, not 8 + + # Query for entities that eat exactly 5 apples - should find heather (from setup) + var apple_eaters_5 = Array(ECS.world.query.with_relationship([Relationship.new({C_Eats: {'value': {"_eq": 5}}}, e_apple)]).execute()) + assert_bool(apple_eaters_5.has(e_heather)).is_true() # heather eats exactly 5 apples + assert_bool(apple_eaters_5.has(e_alice)).is_false() # alice eats 8 apples, not 5 + + +func test_relationship_removal_with_data_specificity(): + # Test that relationship removal works correctly with specific component data + # Add multiple eating relationships for the same entity-target pair with different amounts + e_bob.add_relationship(Relationship.new(C_Eats.new(5), e_apple)) + e_bob.add_relationship(Relationship.new(C_Eats.new(10), e_apple)) + + # Verify both relationships exist + var has_5_apples = e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 5}}}, e_apple)) + var has_10_apples = e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 10}}}, e_apple)) + + assert_bool(has_5_apples).is_true() + assert_bool(has_10_apples).is_true() + + # Remove only the specific relationship (5 apples) + e_bob.remove_relationship(Relationship.new({C_Eats: {'value': {"_eq": 5}}}, e_apple)) + + # Verify only the correct relationship was removed + var still_has_5_apples = e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 5}}}, e_apple)) + var still_has_10_apples = e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 10}}}, e_apple)) + + assert_bool(still_has_5_apples).is_false() # removed + assert_bool(still_has_10_apples).is_true() # should still exist + + +func test_edge_case_null_component_data(): + # Test relationships with components that have null/default values + # Create components with default values + var default_likes = C_Likes.new() # value = 0 (default) + var zero_likes = C_Likes.new(0) # value = 0 (explicit) + + e_bob.add_relationship(Relationship.new(default_likes, e_alice)) + + # Both should match with component query since they have the same data + var matches_default = e_bob.has_relationship(Relationship.new({C_Likes: {'value': {"_eq": 0}}}, e_alice)) + var matches_zero = e_bob.has_relationship(Relationship.new({C_Likes: {'value': {"_eq": 0}}}, e_alice)) + + assert_bool(matches_default).is_true() + assert_bool(matches_zero).is_true() + + # Different value should not match with component query + var matches_different = e_bob.has_relationship(Relationship.new({C_Likes: {'value': {"_eq": 1}}}, e_alice)) + assert_bool(matches_different).is_false() + + # But should match with type matching + var weak_matches_different = e_bob.has_relationship(Relationship.new(C_Likes.new(), e_alice)) + assert_bool(weak_matches_different).is_true() + + +func test_wildcard_and_null_targets_with_weak_matching(): + # Test wildcard (ECS.wildcard) and null targets work correctly with type matching + # Add some relationships for testing + e_bob.add_relationship(Relationship.new(C_Eats.new(5), e_apple)) + e_alice.add_relationship(Relationship.new(C_Eats.new(3), e_pizza)) + e_heather.add_relationship(Relationship.new(C_Likes.new(7), e_bob)) + + # Test null target (wildcard) with type matching - should match any target + var bob_eats_anything_weak = e_bob.has_relationship(Relationship.new(C_Eats.new(), null)) + var alice_eats_anything_weak = e_alice.has_relationship(Relationship.new(C_Eats.new(), null)) + var heather_eats_anything_weak = e_heather.has_relationship(Relationship.new(C_Eats.new(), null)) + + assert_bool(bob_eats_anything_weak).is_true() # bob eats apples (any amount, any target) + assert_bool(alice_eats_anything_weak).is_true() # alice eats pizza (any amount, any target) + assert_bool(heather_eats_anything_weak).is_true() # heather eats 5 apples from setup (any amount, any target) + + # Test null target with component query - should also work the same way + var bob_eats_anything_strong = e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 5}}}, null)) + var alice_eats_anything_strong = e_alice.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 3}}}, null)) + var wrong_amount_strong = e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 999}}}, null)) + + assert_bool(bob_eats_anything_strong).is_true() # bob eats exactly 5 of something + assert_bool(alice_eats_anything_strong).is_true() # alice eats exactly 3 of something + assert_bool(wrong_amount_strong).is_false() # bob doesn't eat exactly 999 of anything + + # Test ECS.wildcard as target with type matching + var bob_eats_wildcard_weak = e_bob.has_relationship(Relationship.new(C_Eats.new(), ECS.wildcard)) + var alice_eats_wildcard_weak = e_alice.has_relationship(Relationship.new(C_Eats.new(), ECS.wildcard)) + + assert_bool(bob_eats_wildcard_weak).is_true() # bob eats something (any amount) + assert_bool(alice_eats_wildcard_weak).is_true() # alice eats something (any amount) + + +func test_wildcard_relation_with_weak_matching(): + # Test using null or ECS.wildcard as the relation component + # Add different types of relationships + e_bob.add_relationship(Relationship.new(C_Eats.new(5), e_apple)) + e_bob.add_relationship(Relationship.new(C_Likes.new(3), e_alice)) + e_alice.add_relationship(Relationship.new(C_Loves.new(2), e_heather)) + + # Test null relation (any relationship type) with specific target + var any_rel_to_apple_bob = e_bob.has_relationship(Relationship.new(null, e_apple)) + var any_rel_to_apple_alice = e_alice.has_relationship(Relationship.new(null, e_apple)) + var any_rel_to_alice_bob = e_bob.has_relationship(Relationship.new(null, e_alice)) + + assert_bool(any_rel_to_apple_bob).is_true() # bob has some relationship with apple (eats it) + assert_bool(any_rel_to_apple_alice).is_true() # alice DOES have a relationship with apple from setup - she attacks food, and apple is food + assert_bool(any_rel_to_alice_bob).is_true() # bob has some relationship with alice (likes her) + + # Test ECS.wildcard as relation + var wildcard_rel_to_heather = e_alice.has_relationship(Relationship.new(ECS.wildcard, e_heather)) + assert_bool(wildcard_rel_to_heather).is_true() # alice has some relationship with heather (loves her) + + +func test_query_with_wildcards_and_strong_matching(): + # Test query system behavior with wildcards + # Add test relationships + e_bob.add_relationship(Relationship.new(C_Eats.new(8), e_apple)) + e_alice.add_relationship(Relationship.new(C_Eats.new(12), e_pizza)) + e_heather.add_relationship(Relationship.new(C_Likes.new(6), e_bob)) + + # Query for entities that eat exact amounts + var entities_that_eat_8_anything = Array(ECS.world.query.with_relationship([Relationship.new({C_Eats: {'value': {"_eq": 8}}}, null)]).execute()) + assert_bool(entities_that_eat_8_anything.has(e_bob)).is_true() # bob eats exactly 8 of something (apple) + assert_bool(entities_that_eat_8_anything.has(e_alice)).is_false() # alice eats 12, not 8 + + # Query for entities that eat 12 of anything + var entities_that_eat_12_anything = Array(ECS.world.query.with_relationship([Relationship.new({C_Eats: {'value': {"_eq": 12}}}, null)]).execute()) + assert_bool(entities_that_eat_12_anything.has(e_alice)).is_true() # alice eats exactly 12 of something (pizza) + assert_bool(entities_that_eat_12_anything.has(e_bob)).is_false() # bob eats 8, not 12 + + # Query for any entity with any relationship to a specific target + var entities_with_rel_to_bob = Array(ECS.world.query.with_relationship([Relationship.new(null, e_bob)]).execute()) + + assert_bool(entities_with_rel_to_bob.has(e_heather)).is_true() # heather likes bob + assert_bool(entities_with_rel_to_bob.has(e_bob)).is_true() # bob cries in front of people (from setup) + + # Query for any entity with any relationship to anything (double wildcard) + var entities_with_any_rel = Array(ECS.world.query.with_relationship([Relationship.new(null, null)]).execute()) + + # Should find all entities that have any relationships + assert_bool(entities_with_any_rel.has(e_bob)).is_true() + assert_bool(entities_with_any_rel.has(e_alice)).is_true() + assert_bool(entities_with_any_rel.has(e_heather)).is_true() + + +func test_empty_relationship_constructor_with_weak_matching(): + # Test using Relationship.new() with no parameters (both relation and target are null) + e_bob.add_relationship(Relationship.new(C_Eats.new(10), e_apple)) + e_alice.add_relationship(Relationship.new(C_Likes.new(5), e_heather)) + + # Empty relationship should match any relationship + var bob_has_any_rel = e_bob.has_relationship(Relationship.new()) + var alice_has_any_rel = e_alice.has_relationship(Relationship.new()) + + assert_bool(bob_has_any_rel).is_true() # bob has some relationship + assert_bool(alice_has_any_rel).is_true() # alice has some relationship + + +func test_mixed_wildcard_scenarios_with_strong_matching(): + # Test complex scenarios mixing wildcards with component queries + # Setup complex relationship scenario + e_bob.add_relationship(Relationship.new(C_Eats.new(15), e_apple)) + e_bob.add_relationship(Relationship.new(C_Likes.new(20), e_pizza)) + e_alice.add_relationship(Relationship.new(C_Eats.new(25), e_pizza)) + e_alice.add_relationship(Relationship.new(C_Loves.new(30), e_heather)) + + # Test: Find entities that have C_Eats relationship with any target for specific amounts + var eats_15_anything = Array(ECS.world.query.with_relationship([Relationship.new({C_Eats: {'value': {"_eq": 15}}}, null)]).execute()) + var eats_25_anything = Array(ECS.world.query.with_relationship([Relationship.new({C_Eats: {'value': {"_eq": 25}}}, null)]).execute()) + + assert_bool(eats_15_anything.has(e_bob)).is_true() # bob eats exactly 15 of something (apples) + assert_bool(eats_15_anything.has(e_alice)).is_false() # alice eats 25, not 15 + assert_bool(eats_25_anything.has(e_alice)).is_true() # alice eats exactly 25 of something (pizza) + assert_bool(eats_25_anything.has(e_bob)).is_false() # bob eats 15, not 25 + + # Test: Find entities with any relationship to pizza + var any_rel_to_pizza = Array(ECS.world.query.with_relationship([Relationship.new(null, e_pizza)]).execute()) + + assert_bool(any_rel_to_pizza.has(e_bob)).is_true() # bob likes pizza + assert_bool(any_rel_to_pizza.has(e_alice)).is_true() # alice eats pizza + assert_bool(any_rel_to_pizza.has(e_heather)).is_true() # heather likes food, and pizza is food (from setup) + + # Test: Verify type matching on entities directly still retrieves correct component data + # Note: Need to account for existing relationships from setup + + # Bob should have the new C_Likes(20) relationship we just added + var bob_pizza_rel = e_bob.get_relationship(Relationship.new(C_Likes.new(), e_pizza)) + assert_bool(bob_pizza_rel != null).is_true() + # Bob already has a C_Likes relationship with pizza from setup with value=0, so type matching finds that one first + # We should test with the actual value from setup instead + assert_int(bob_pizza_rel.relation.value).is_equal(0) # bob's relationship from setup has value=0 + + # Alice should have the new C_Eats(25) relationship we just added, but type matching finds the FIRST + # C_Eats relationship with pizza, which could be from an earlier test + var alice_pizza_rel = e_alice.get_relationship(Relationship.new(C_Eats.new(), e_pizza)) + assert_bool(alice_pizza_rel != null).is_true() + # Alice has had multiple C_Eats relationships with pizza added in previous tests + # Type matching finds the first one, which could be C_Eats.new(3) from test_wildcard_and_null_targets_with_weak_matching + # We need to check what the actual first relationship is, not assume it's the most recent + # Since we can't control test execution order easily, let's just verify a relationship exists + # and has some valid value >= 0 + assert_bool(alice_pizza_rel.relation.value >= 0).is_true() # alice has some valid eats relationship with pizza + + +func test_component_based_relationships(): + # Test using components as targets for relationships to enable damage type hierarchies + # Create damage type components - simulating C_Damaged -> C_HeavyDamage, C_LightDamage patterns + # Using existing test components to represent damage types + var c_damage_base = C_Likes.new(1) # Base damage marker + var c_heavy_damage = C_Eats.new(10) # Heavy damage type + var c_light_damage = C_Loves.new(2) # Light damage type + + # Bob has been damaged and specifically has heavy damage + e_bob.add_relationship(Relationship.new(c_damage_base, c_heavy_damage)) + + # Alice has been damaged and specifically has light damage + e_alice.add_relationship(Relationship.new(c_damage_base, c_light_damage)) + + # Heather has been damaged with both types + e_heather.add_relationship(Relationship.new(c_damage_base, c_heavy_damage)) + e_heather.add_relationship(Relationship.new(c_damage_base, c_light_damage)) + + # Test exact component matching (strong matching) + var heavy_damaged_entities = Array(ECS.world.query.with_relationship([Relationship.new(c_damage_base, c_heavy_damage)]).execute()) + var light_damaged_entities = Array(ECS.world.query.with_relationship([Relationship.new(c_damage_base, c_light_damage)]).execute()) + + assert_bool(heavy_damaged_entities.has(e_bob)).is_true() # bob has heavy damage + assert_bool(heavy_damaged_entities.has(e_heather)).is_true() # heather has heavy damage + assert_bool(heavy_damaged_entities.has(e_alice)).is_false() # alice doesn't have heavy damage + + assert_bool(light_damaged_entities.has(e_alice)).is_true() # alice has light damage + assert_bool(light_damaged_entities.has(e_heather)).is_true() # heather has light damage + assert_bool(light_damaged_entities.has(e_bob)).is_false() # bob doesn't have light damage + + # Test wildcard queries - find all entities with any damage type + var any_damaged_entities = Array(ECS.world.query.with_relationship([Relationship.new(c_damage_base, null)]).execute()) + + assert_bool(any_damaged_entities.has(e_bob)).is_true() # bob is damaged + assert_bool(any_damaged_entities.has(e_alice)).is_true() # alice is damaged + assert_bool(any_damaged_entities.has(e_heather)).is_true() # heather is damaged + assert_int(any_damaged_entities.size()).is_equal(3) # all three are damaged + + +func test_component_target_with_weak_matching(): + # Test type matching with component targets - should match by component type regardless of data + # Create different instances of the same component type with different values + var status_effect_marker = C_IsCryingInFrontOf.new() # Status effect marker + var poison_level_1 = C_Eats.new(1) # Poison level 1 + var poison_level_5 = C_Eats.new(5) # Poison level 5 + var poison_level_10 = C_Eats.new(10) # Poison level 10 + + # Apply different poison levels + e_bob.add_relationship(Relationship.new(status_effect_marker, poison_level_1)) + e_alice.add_relationship(Relationship.new(status_effect_marker, poison_level_5)) + e_heather.add_relationship(Relationship.new(status_effect_marker, poison_level_10)) + + # Component queries should find exact poison levels only + var poison_1_entities = Array(ECS.world.query.with_relationship([Relationship.new(status_effect_marker, {C_Eats: {'value': {"_eq": 1}}})]).execute()) + var poison_5_entities = Array(ECS.world.query.with_relationship([Relationship.new(status_effect_marker,{C_Eats: {'value': {"_eq": 5}}})]).execute()) + + assert_bool(poison_1_entities.has(e_bob)).is_true() + assert_bool(poison_1_entities.has(e_alice)).is_false() + assert_bool(poison_5_entities.has(e_alice)).is_true() + assert_bool(poison_5_entities.has(e_bob)).is_false() + + # Test type matching on individual entities - should find any poison level of same type + var bob_has_any_poison = e_bob.has_relationship(Relationship.new(status_effect_marker, C_Eats.new())) + var alice_has_any_poison = e_alice.has_relationship(Relationship.new(status_effect_marker, C_Eats.new())) + var heather_has_any_poison = e_heather.has_relationship(Relationship.new(status_effect_marker, C_Eats.new())) + + assert_bool(bob_has_any_poison).is_true() # bob has some level of poison + assert_bool(alice_has_any_poison).is_true() # alice has some level of poison + assert_bool(heather_has_any_poison).is_true() # heather has some level of poison + + # Verify we can retrieve the actual poison levels using type matching + var bob_poison_rel = e_bob.get_relationship(Relationship.new(status_effect_marker, C_Eats.new())) + var alice_poison_rel = e_alice.get_relationship(Relationship.new(status_effect_marker, C_Eats.new())) + var heather_poison_rel = e_heather.get_relationship(Relationship.new(status_effect_marker, C_Eats.new())) + + assert_int(bob_poison_rel.target.value).is_equal(1) # bob's actual poison level + assert_int(alice_poison_rel.target.value).is_equal(5) # alice's actual poison level + assert_int(heather_poison_rel.target.value).is_equal(10) # heather's actual poison level + + +func test_component_archetype_target_matching(): + # Test matching component instances against component archetypes + # Create a buff system - entities can have buffs that are component instances + var has_buff_marker = C_IsAttacking.new() + var strength_buff = C_Likes.new(25) # +25 strength buff + var speed_buff = C_Loves.new(15) # +15 speed buff + + # Apply buffs to entities + e_bob.add_relationship(Relationship.new(has_buff_marker, strength_buff)) + e_alice.add_relationship(Relationship.new(has_buff_marker, speed_buff)) + e_heather.add_relationship(Relationship.new(has_buff_marker, strength_buff)) + e_heather.add_relationship(Relationship.new(has_buff_marker, speed_buff)) + + # Query for entities with any strength buff (using archetype) + var entities_with_strength_buff = Array(ECS.world.query.with_relationship([Relationship.new(has_buff_marker, C_Likes)]).execute()) + + assert_bool(entities_with_strength_buff.has(e_bob)).is_true() # bob has strength buff + assert_bool(entities_with_strength_buff.has(e_heather)).is_true() # heather has strength buff + assert_bool(entities_with_strength_buff.has(e_alice)).is_false() # alice doesn't have strength buff + + # Query for entities with any speed buff (using archetype) + var entities_with_speed_buff = Array(ECS.world.query.with_relationship([Relationship.new(has_buff_marker, C_Loves)]).execute()) + + assert_bool(entities_with_speed_buff.has(e_alice)).is_true() # alice has speed buff + assert_bool(entities_with_speed_buff.has(e_heather)).is_true() # heather has speed buff + assert_bool(entities_with_speed_buff.has(e_bob)).is_false() # bob doesn't have speed buff + + # Test that archetype query matches instances correctly + # Verify that when we query with archetype, it finds the specific instance + var bob_strength_rel = e_bob.get_relationship(Relationship.new(has_buff_marker, C_Likes.new())) + var heather_strength_rel = e_heather.get_relationship(Relationship.new(has_buff_marker, C_Likes.new())) + + assert_int(bob_strength_rel.target.value).is_equal(25) # bob's strength buff value + assert_int(heather_strength_rel.target.value).is_equal(25) # heather's strength buff value + + +func test_multiple_component_targets_same_relationship(): + # Test having multiple relationships with same relation but different component targets + # Clear any existing C_IsAttacking relationships to avoid conflicts with setup + var existing_alice_attacking = e_alice.get_relationships(Relationship.new(C_IsAttacking.new(), null)) + for rel in existing_alice_attacking: + e_alice.remove_relationship(rel) + + # Create a resistance system - entities can be resistant to different damage types + # Use C_IsAttacking as marker to avoid conflicts with existing C_IsCryingInFrontOf relationships + var has_resistance_marker = C_IsAttacking.new() + var fire_resistance = C_Eats.new(50) # 50% fire resistance + var ice_resistance = C_Loves.new(30) # 30% ice resistance + var poison_resistance = C_Likes.new(75) # 75% poison resistance + + # Bob is resistant to fire and poison + e_bob.add_relationship(Relationship.new(has_resistance_marker, fire_resistance)) + e_bob.add_relationship(Relationship.new(has_resistance_marker, poison_resistance)) + + # Alice is resistant to ice and poison + e_alice.add_relationship(Relationship.new(has_resistance_marker, ice_resistance)) + e_alice.add_relationship(Relationship.new(has_resistance_marker, poison_resistance)) + + # Heather is resistant to all three + e_heather.add_relationship(Relationship.new(has_resistance_marker, fire_resistance)) + e_heather.add_relationship(Relationship.new(has_resistance_marker, ice_resistance)) + e_heather.add_relationship(Relationship.new(has_resistance_marker, poison_resistance)) + + # Test queries for specific resistance types + var fire_resistant_entities = Array(ECS.world.query.with_relationship([Relationship.new(has_resistance_marker, fire_resistance)]).execute()) + var ice_resistant_entities = Array(ECS.world.query.with_relationship([Relationship.new(has_resistance_marker, ice_resistance)]).execute()) + var poison_resistant_entities = Array(ECS.world.query.with_relationship([Relationship.new(has_resistance_marker, poison_resistance)]).execute()) + + assert_bool(fire_resistant_entities.has(e_bob)).is_true() + assert_bool(fire_resistant_entities.has(e_heather)).is_true() + assert_bool(fire_resistant_entities.has(e_alice)).is_false() + + assert_bool(ice_resistant_entities.has(e_alice)).is_true() + assert_bool(ice_resistant_entities.has(e_heather)).is_true() + assert_bool(ice_resistant_entities.has(e_bob)).is_false() + + assert_bool(poison_resistant_entities.has(e_bob)).is_true() + assert_bool(poison_resistant_entities.has(e_alice)).is_true() + assert_bool(poison_resistant_entities.has(e_heather)).is_true() + + # Test getting all resistance relationships for an entity + var bob_resistances = e_bob.get_relationships(Relationship.new(has_resistance_marker, null)) + var alice_resistances = e_alice.get_relationships(Relationship.new(has_resistance_marker, null)) + var heather_resistances = e_heather.get_relationships(Relationship.new(has_resistance_marker, null)) + + assert_int(bob_resistances.size()).is_equal(2) # bob has 2 resistances + assert_int(alice_resistances.size()).is_equal(2) # alice has 2 resistances + assert_int(heather_resistances.size()).is_equal(3) # heather has 3 resistances + + # Test wildcard query by component archetype + var entities_with_fire_resistance_type = Array(ECS.world.query.with_relationship([Relationship.new(has_resistance_marker, C_Eats)]).execute()) + var entities_with_ice_resistance_type = Array(ECS.world.query.with_relationship([Relationship.new(has_resistance_marker, C_Loves)]).execute()) + + assert_bool(entities_with_fire_resistance_type.has(e_bob)).is_true() # bob has C_Eats resistance (fire) + assert_bool(entities_with_fire_resistance_type.has(e_heather)).is_true() # heather has C_Eats resistance (fire) + assert_bool(entities_with_fire_resistance_type.has(e_alice)).is_false() # alice doesn't have C_Eats resistance + + assert_bool(entities_with_ice_resistance_type.has(e_alice)).is_true() # alice has C_Loves resistance (ice) + assert_bool(entities_with_ice_resistance_type.has(e_heather)).is_true() # heather has C_Loves resistance (ice) + assert_bool(entities_with_ice_resistance_type.has(e_bob)).is_false() # bob doesn't have C_Loves resistance +# +# +#func test_component_queries_in_relationships(): + ## Test if we can use component queries to filter relationships by target component properties + ## Create damage relationships with different amounts + #var damage_marker = C_IsCryingInFrontOf.new() + #var light_damage = C_Eats.new(25) # 25 damage + #var heavy_damage = C_Eats.new(75) # 75 damage + #var massive_damage = C_Eats.new(150) # 150 damage + # + ## Apply different damage amounts to entities + #e_bob.add_relationship(Relationship.new(damage_marker, light_damage)) + #e_alice.add_relationship(Relationship.new(damage_marker, heavy_damage)) + #e_heather.add_relationship(Relationship.new(damage_marker, massive_damage)) + # + ## Try to use component queries within relationships - test if this works + ## This would be: entities with damage relationships where target component value > 50 + # + ## Test 1: Try direct component query in relationship (might not work) + ## This syntax probably doesn't exist yet but let's see what happens + #var high_damage_query = Relationship.new(damage_marker, {C_Eats: {"value": {"_gt": 50}}}) + # + #var high_damage_entities = ECS.world.query.with_relationship([high_damage_query]).execute() + #print("Component queries in relationships work! Found: ", high_damage_entities.size()) + + +func test_broad_query_with_drill_down_filtering(): + # Test the pattern: broad query -> drill down with entity.has_relationship() + # This is the recommended pattern for complex relationship filtering + # Purge and recreate entities for a clean slate + world.purge(false) + + e_bob = Person.new() + e_bob.name = "e_bob" + e_alice = Person.new() + e_alice.name = "e_alice" + e_heather = Person.new() + e_heather.name = "e_heather" + + world.add_entity(e_bob) + world.add_entity(e_alice) + world.add_entity(e_heather) + + # Create clear component aliases for this test + var C_Damaged = C_IsCryingInFrontOf # Damage marker component + var C_FireDamage = C_Eats # Fire damage type + var C_PoisonDamage = C_Loves # Poison damage type + + # Create a damage system with various damage types and amounts + # Each entity gets unique component instances as per typical workflow + + # Bob has fire damage (low amount) + e_bob.add_relationship(Relationship.new(C_Damaged.new(), C_FireDamage.new(25))) + + # Alice has fire damage (high amount) and poison damage + e_alice.add_relationship(Relationship.new(C_Damaged.new(), C_FireDamage.new(85))) + e_alice.add_relationship(Relationship.new(C_Damaged.new(), C_PoisonDamage.new(40))) + + # Heather has only poison damage + e_heather.add_relationship(Relationship.new(C_Damaged.new(), C_PoisonDamage.new(60))) + + # Step 1: Broad query - get ALL entities with any damage + var all_damaged_entities = ECS.world.query.with_relationship([ + Relationship.new(C_Damaged.new(), null) + ]).execute() as Array[Entity] + + # Verify we found all damaged entities + assert_bool(all_damaged_entities.has(e_bob)).is_true() + assert_bool(all_damaged_entities.has(e_alice)).is_true() + assert_bool(all_damaged_entities.has(e_heather)).is_true() + assert_int(all_damaged_entities.size()).is_equal(3) + + # Step 2: Drill down - find entities with ANY fire damage (type matching) + var fire_damaged_entities = [] + for entity in all_damaged_entities: + # Use type matching to find any fire damage type regardless of amount + if entity.has_relationship(Relationship.new(C_Damaged.new(), C_FireDamage.new())): + fire_damaged_entities.append(entity) + + assert_bool(fire_damaged_entities.has(e_bob)).is_true() # bob has fire damage (25) + assert_bool(fire_damaged_entities.has(e_alice)).is_true() # alice has fire damage (85) + assert_bool(fire_damaged_entities.has(e_heather)).is_false() # heather has no fire damage + assert_int(fire_damaged_entities.size()).is_equal(2) + + # Step 3: Drill down further - find entities with HIGH fire damage (type matching + manual filter) + var high_fire_damage_entities = [] + for entity in fire_damaged_entities: + # Get the actual fire damage relationship using type matching + var fire_rel = entity.get_relationship(Relationship.new(C_Damaged.new(), C_FireDamage.new())) + if fire_rel and fire_rel.target.value > 50: + high_fire_damage_entities.append(entity) + + assert_bool(high_fire_damage_entities.has(e_alice)).is_true() # alice has 85 fire damage + assert_bool(high_fire_damage_entities.has(e_bob)).is_false() # bob has only 25 fire damage + assert_int(high_fire_damage_entities.size()).is_equal(1) + + # Step 4: Drill down - find entities with MULTIPLE damage types + var multi_damage_entities = [] + for entity in all_damaged_entities: + var damage_rels = entity.get_relationships(Relationship.new(C_Damaged.new(), null)) + if damage_rels.size() > 1: + multi_damage_entities.append(entity) + + assert_bool(multi_damage_entities.has(e_alice)).is_true() # alice has fire + poison + assert_bool(multi_damage_entities.has(e_bob)).is_false() # bob has only fire + assert_bool(multi_damage_entities.has(e_heather)).is_false() # heather has only poison + assert_int(multi_damage_entities.size()).is_equal(1) + + # Step 5: Drill down - find entities with specific damage combinations + var fire_and_poison_entities = [] + for entity in all_damaged_entities: + var has_fire = entity.has_relationship(Relationship.new(C_Damaged.new(), C_FireDamage.new())) + var has_poison = entity.has_relationship(Relationship.new(C_Damaged.new(), C_PoisonDamage.new())) + if has_fire and has_poison: + fire_and_poison_entities.append(entity) + + assert_bool(fire_and_poison_entities.has(e_alice)).is_true() # alice has both + assert_bool(fire_and_poison_entities.has(e_bob)).is_false() # bob has only fire + assert_bool(fire_and_poison_entities.has(e_heather)).is_false() # heather has only poison + assert_int(fire_and_poison_entities.size()).is_equal(1) + + +func test_component_query_based_removal(): + # Test removal logic with component queries and instances + # Add multiple eating relationships with different amounts + e_bob.add_relationship(Relationship.new(C_Eats.new(5), e_apple)) + e_bob.add_relationship(Relationship.new(C_Eats.new(10), e_apple)) + e_bob.add_relationship(Relationship.new(C_Eats.new(15), e_apple)) + e_bob.add_relationship(Relationship.new(C_Likes.new(100), e_apple)) # Different component type + + # Verify all relationships exist + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 5}}}, e_apple))).is_true() + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 10}}}, e_apple))).is_true() + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 15}}}, e_apple))).is_true() + assert_bool(e_bob.has_relationship(Relationship.new({C_Likes: {'value': {"_eq": 100}}}, e_apple))).is_true() + + # Test 1: Removal with component query (should remove only exact match) + e_bob.remove_relationship(Relationship.new({C_Eats: {'value': {"_eq": 10}}}, e_apple)) + + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 5}}}, e_apple))).is_true() # still exists + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 10}}}, e_apple))).is_false() # removed + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 15}}}, e_apple))).is_true() # still exists + assert_bool(e_bob.has_relationship(Relationship.new({C_Likes: {'value': {"_eq": 100}}}, e_apple))).is_true() # different type, still exists + + # Test 2: Type-based removal with empty component query (should remove all of that type) + e_bob.remove_relationship(Relationship.new({C_Eats: {}}, e_apple)) + + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 5}}}, e_apple))).is_false() # removed by type matching + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 15}}}, e_apple))).is_false() # removed by type matching + assert_bool(e_bob.has_relationship(Relationship.new({C_Likes: {'value': {"_eq": 100}}}, e_apple))).is_true() # different type, still exists + + # Test 3: Query-based removal with specific criteria + # Add more relationships to test query operators + e_bob.add_relationship(Relationship.new(C_Eats.new(25), e_apple)) + e_bob.add_relationship(Relationship.new(C_Eats.new(35), e_apple)) + e_bob.add_relationship(Relationship.new(C_Eats.new(45), e_apple)) + + # Remove all eating relationships where value > 30 + e_bob.remove_relationship(Relationship.new({C_Eats: {"value": {"_gt": 30}}}, e_apple)) + + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 25}}}, e_apple))).is_true() # 25 <= 30, still exists + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 35}}}, e_apple))).is_false() # 35 > 30, removed + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 45}}}, e_apple))).is_false() # 45 > 30, removed + assert_bool(e_bob.has_relationship(Relationship.new({C_Likes: {'value': {"_eq": 100}}}, e_apple))).is_true() # different type, still exists + + # Test 4: Query-based removal with range criteria + e_bob.add_relationship(Relationship.new(C_Eats.new(50), e_apple)) + e_bob.add_relationship(Relationship.new(C_Eats.new(75), e_apple)) + e_bob.add_relationship(Relationship.new(C_Eats.new(100), e_apple)) + + # Remove eating relationships in range 40-80 + e_bob.remove_relationship(Relationship.new({C_Eats: {"value": {"_gte": 40, "_lte": 80}}}, e_apple)) + + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 25}}}, e_apple))).is_true() # 25 < 40, still exists + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 50}}}, e_apple))).is_false() # 40 <= 50 <= 80, removed + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 75}}}, e_apple))).is_false() # 40 <= 75 <= 80, removed + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 100}}}, e_apple))).is_true() # 100 > 80, still exists + + # Test 5: Wildcard target with component query (remove from any target) + e_bob.add_relationship(Relationship.new(C_Eats.new(25), e_pizza)) + e_bob.add_relationship(Relationship.new(C_Eats.new(25), e_alice)) + + # Remove all eating relationships with value exactly 25, regardless of target + e_bob.remove_relationship(Relationship.new({C_Eats: {"value": {"_eq": 25}}}, null)) + + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 25}}}, e_apple))).is_false() # removed + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 25}}}, e_pizza))).is_false() # removed + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 25}}}, e_alice))).is_false() # removed + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 100}}}, e_apple))).is_true() # different value, still exists + + +func test_limited_relationship_removal(): + # Test the new limit parameter for relationship removal + # Clear existing relationships first to have a clean slate + e_bob.relationships.clear() + + # Add multiple relationships of the same type + e_bob.add_relationship(Relationship.new(C_Eats.new(10), e_apple)) + e_bob.add_relationship(Relationship.new(C_Eats.new(20), e_apple)) + e_bob.add_relationship(Relationship.new(C_Eats.new(30), e_apple)) + e_bob.add_relationship(Relationship.new(C_Eats.new(40), e_apple)) + e_bob.add_relationship(Relationship.new(C_Likes.new(5), e_apple)) # Different component type + + # Verify all relationships were added + assert_int(e_bob.relationships.size()).is_equal(5) + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 10}}}, e_apple))).is_true() + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 20}}}, e_apple))).is_true() + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 30}}}, e_apple))).is_true() + assert_bool(e_bob.has_relationship(Relationship.new({C_Eats: {'value': {"_eq": 40}}}, e_apple))).is_true() + assert_bool(e_bob.has_relationship(Relationship.new({C_Likes: {'value': {"_eq": 5}}}, e_apple))).is_true() + + # Test 1: Remove with limit 0 (should remove nothing) + e_bob.remove_relationship(Relationship.new({C_Eats: {}}, e_apple), 0) + assert_int(e_bob.relationships.size()).is_equal(5) # All should still exist + + # Test 2: Remove with limit 1 (should remove only one) + e_bob.remove_relationship(Relationship.new({C_Eats: {}}, e_apple), 1) + assert_int(e_bob.relationships.size()).is_equal(4) # One C_Eats should be removed + + # Count remaining C_Eats relationships + var eats_count = 0 + for rel in e_bob.relationships: + if rel.relation is C_Eats and rel.target == e_apple: + eats_count += 1 + assert_int(eats_count).is_equal(3) # Should have 3 C_Eats relationships left + + # Test 3: Remove with limit 2 (should remove two more) + e_bob.remove_relationship(Relationship.new({C_Eats: {}}, e_apple), 2) + assert_int(e_bob.relationships.size()).is_equal(2) # Two more C_Eats should be removed + + # Count remaining C_Eats relationships + eats_count = 0 + for rel in e_bob.relationships: + if rel.relation is C_Eats and rel.target == e_apple: + eats_count += 1 + assert_int(eats_count).is_equal(1) # Should have 1 C_Eats relationship left + + # Verify C_Likes relationship is still there (different component type) + assert_bool(e_bob.has_relationship(Relationship.new({C_Likes: {'value': {"_eq": 5}}}, e_apple))).is_true() + + # Test 4: Remove with limit -1 (should remove all remaining) + e_bob.remove_relationship(Relationship.new({C_Eats: {}}, e_apple), -1) + assert_int(e_bob.relationships.size()).is_equal(1) # Only C_Likes should remain + + # Count remaining C_Eats relationships + eats_count = 0 + for rel in e_bob.relationships: + if rel.relation is C_Eats and rel.target == e_apple: + eats_count += 1 + assert_int(eats_count).is_equal(0) # Should have no C_Eats relationships left + + # Verify C_Likes relationship is still there + assert_bool(e_bob.has_relationship(Relationship.new({C_Likes: {'value': {"_eq": 5}}}, e_apple))).is_true() + + # Test 5: Remove with limit higher than available relationships + e_bob.add_relationship(Relationship.new(C_Eats.new(50), e_apple)) + e_bob.add_relationship(Relationship.new(C_Eats.new(60), e_apple)) + e_bob.remove_relationship(Relationship.new({C_Eats: {}}, e_apple), 10) # Try to remove 10, but only 2 exist + + # Count remaining C_Eats relationships + eats_count = 0 + for rel in e_bob.relationships: + if rel.relation is C_Eats and rel.target == e_apple: + eats_count += 1 + assert_int(eats_count).is_equal(0) # Should have removed both (all available) + + +func test_limited_relationship_removal_with_strong_matching(): + # Test limit parameter with component queries + e_alice.relationships.clear() + + # Add multiple relationships with the same exact component data + e_alice.add_relationship(Relationship.new(C_Eats.new(25), e_pizza)) + e_alice.add_relationship(Relationship.new(C_Eats.new(25), e_pizza)) + e_alice.add_relationship(Relationship.new(C_Eats.new(25), e_pizza)) + e_alice.add_relationship(Relationship.new(C_Eats.new(30), e_pizza)) # Different value + + assert_int(e_alice.relationships.size()).is_equal(4) + + # Remove with limit 2 using component query + e_alice.remove_relationship(Relationship.new({C_Eats: {'value': {"_eq": 25}}}, e_pizza), 2) + + # Should have removed 2 of the 3 matching relationships + assert_int(e_alice.relationships.size()).is_equal(2) + + # Check that one C_Eats(25) and one C_Eats(30) relationship remain + var count_25 = 0 + var count_30 = 0 + for rel in e_alice.relationships: + if rel.relation is C_Eats and rel.target == e_pizza: + if rel.relation.value == 25: + count_25 += 1 + elif rel.relation.value == 30: + count_30 += 1 + + assert_int(count_25).is_equal(1) # One C_Eats(25) should remain + assert_int(count_30).is_equal(1) # One C_Eats(30) should remain + +func test_component_target_relationship_by_component_query(): + e_bob.add_relationship(Relationship.new(C_TestA.new(10), C_TestC.new())) + e_alice.add_relationship(Relationship.new(C_TestA.new(20), C_TestC.new())) + e_heather.add_relationship(Relationship.new(C_TestA.new(10), C_TestD.new())) + e_heather.add_relationship(Relationship.new(C_TestB.new(10), C_TestC.new())) + + var entities_with_strength_buff = Array(ECS.world.query.with_relationship([Relationship.new({C_TestA: {}}, C_TestC.new())]).execute()) + + assert_bool(entities_with_strength_buff.has(e_bob)).is_true() + assert_bool(entities_with_strength_buff.has(e_alice)).is_true() + assert_bool(entities_with_strength_buff.has(e_heather)).is_false() + + var rel_love_attack = e_bob.get_relationship(Relationship.new({C_TestA: {}}, C_TestC.new())) + assert_int(rel_love_attack.relation.value).is_equal(10) + + +func test_remove_specific_relationship(): + e_bob = Person.new() + world.add_entity(e_bob) + + e_bob.add_relationship(Relationship.new(C_Likes.new(1), e_alice)) + e_bob.add_relationship(Relationship.new(C_Likes.new(2), e_alice)) + e_bob.add_relationship(Relationship.new(C_Likes.new(1), e_alice)) + + var all_rels = e_bob.get_relationships(Relationship.new({C_Likes:{}}, null)) + assert_array(all_rels).has_size(3) + + assert_int(all_rels[1].relation.value).is_equal(2) + e_bob.remove_relationship(all_rels[1]) + + var like1_rels = e_bob.get_relationships(Relationship.new({C_Likes:{}}, null)) + assert_array(like1_rels).has_size(2) + assert_int(like1_rels[0].relation.value).is_equal(1) + assert_int(like1_rels[1].relation.value).is_equal(1) + + +# # FIXME: This is not working +# func test_reverse_relationships_a(): + +# # Here I want to get the reverse of this relationship I want to get all the food being attacked. +# var food_being_attacked = ECS.world.query.with_reverse_relationship([Relationship.new(C_IsAttacking.new(), ECS.wildcard)]).execute() +# assert_bool(food_being_attacked.has(e_apple)).is_true() # The Apple is being attacked by alice because she's attacking all food +# assert_bool(food_being_attacked.has(e_pizza)).is_true() # The pizza is being attacked by alice because she's attacking all food +# assert_bool(Array(food_being_attacked).size() == 2).is_true() # pizza and apples are UNDER ATTACK + +# # FIXME: This is not working +# func test_reverse_relationships_b(): +# # Query 2: Find all entities that are the target of any relationship with Person archetype +# var entities_with_relations_to_people = ECS.world.query.with_reverse_relationship([Relationship.new(ECS.wildcard, Person)]).execute() +# # This returns any entity that is the TARGET of any relationship where Person is specified +# assert_bool(Array(entities_with_relations_to_people).has(e_heather)).is_true() # heather is loved by alice +# assert_bool(Array(entities_with_relations_to_people).has(e_alice)).is_true() # alice is liked by bob +# assert_bool(Array(entities_with_relations_to_people).size() == 2).is_true() # only two people are the targets of relations with other persons diff --git a/addons/gecs/tests/core/test_relationships.gd.uid b/addons/gecs/tests/core/test_relationships.gd.uid new file mode 100644 index 0000000..72fb7d9 --- /dev/null +++ b/addons/gecs/tests/core/test_relationships.gd.uid @@ -0,0 +1 @@ +uid://ddcusum4gp5im diff --git a/addons/gecs/tests/core/test_simple_serialization.gd b/addons/gecs/tests/core/test_simple_serialization.gd new file mode 100644 index 0000000..073debe --- /dev/null +++ b/addons/gecs/tests/core/test_simple_serialization.gd @@ -0,0 +1,62 @@ +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + +func after_test(): + if world: + world.purge(false) + +func test_serialize_basic_entity(): + # Create a simple entity with one component + var entity = Entity.new() + entity.name = "TestEntity" + entity.add_component(C_SerializationTest.new()) + + world.add_entity(entity) + + # Serialize the entity + var query = world.query.with_all([C_SerializationTest]) + var serialized_data = ECS.serialize(query) + + # Basic validation + assert_that(serialized_data).is_not_null() + assert_that(serialized_data.version).is_equal("0.2") + assert_that(serialized_data.entities).has_size(1) + + print("Serialized data: ", JSON.stringify(serialized_data, "\t")) + +func test_save_and_load_simple(): + # Create a simple entity + var entity = Entity.new() + entity.name = "SaveLoadTest" + entity.add_component(C_SerializationTest.new(123, 4.56, "save_load_test", false)) + + world.add_entity(entity) + + # Serialize and save + var query = world.query.with_all([C_SerializationTest]) + var serialized_data = ECS.serialize(query) + + var file_path = "res://reports/test_simple.tres" + ECS.save(serialized_data, file_path) + + # Load and deserialize + var deserialized_entities = ECS.deserialize(file_path) + + # Validate + assert_that(deserialized_entities).has_size(1) + var des_entity = deserialized_entities[0] + assert_that(des_entity.name).is_equal("SaveLoadTest") + + # Use auto_free for cleanup + for _entity in deserialized_entities: + auto_free(_entity) + + # Keep file for inspection in reports directory diff --git a/addons/gecs/tests/core/test_simple_serialization.gd.uid b/addons/gecs/tests/core/test_simple_serialization.gd.uid new file mode 100644 index 0000000..fae86a2 --- /dev/null +++ b/addons/gecs/tests/core/test_simple_serialization.gd.uid @@ -0,0 +1 @@ +uid://2coo3k0qawx diff --git a/addons/gecs/tests/core/test_subsystem_component_propagation.gd b/addons/gecs/tests/core/test_subsystem_component_propagation.gd new file mode 100644 index 0000000..d4fe5f3 --- /dev/null +++ b/addons/gecs/tests/core/test_subsystem_component_propagation.gd @@ -0,0 +1,358 @@ +extends GdUnitTestSuite + +## Test suite for subsystem component modification propagation +## Tests that when subsystem A modifies entity components (causing archetype moves), +## subsystem B can see those changes in the same frame + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + if world: + world.purge(false) + + +## =============================== +## COMPONENT ADDITION PROPAGATION +## =============================== + +## Test that components added by subsystem A are visible to subsystem B in the same frame +func test_subsystem_component_addition_propagation(): + # Create entities with only component A + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + entity1.add_component(C_OrderTestA.new()) + entity2.add_component(C_OrderTestA.new()) + entity3.add_component(C_OrderTestA.new()) + world.add_entities([entity1, entity2, entity3]) + + # Create system with two subsystems: + # Subsystem 1: Find entities with A, add B + # Subsystem 2: Find entities with B, increment counter + var system = ComponentAdditionPropagationSystem.new() + world.add_system(system) + + # Process system once + world.process(0.016) + + # Verify: Subsystem 1 processed 3 entities (added B to all of them) + assert_int(system.subsystem1_count).is_equal(3) + + # Verify: Subsystem 2 processed 3 entities (saw all B components added by subsystem 1) + assert_int(system.subsystem2_count).is_equal(3) + + # Verify: All entities now have both A and B + assert_bool(entity1.has_component(C_OrderTestA)).is_true() + assert_bool(entity1.has_component(C_OrderTestB)).is_true() + assert_bool(entity2.has_component(C_OrderTestA)).is_true() + assert_bool(entity2.has_component(C_OrderTestB)).is_true() + assert_bool(entity3.has_component(C_OrderTestA)).is_true() + assert_bool(entity3.has_component(C_OrderTestB)).is_true() + + +## Test that components removed by subsystem A are not visible to subsystem B in the same frame +func test_subsystem_component_removal_propagation(): + # Create entities with both A and B + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + entity1.add_component(C_OrderTestA.new()) + entity1.add_component(C_OrderTestB.new()) + entity2.add_component(C_OrderTestA.new()) + entity2.add_component(C_OrderTestB.new()) + entity3.add_component(C_OrderTestA.new()) + entity3.add_component(C_OrderTestB.new()) + world.add_entities([entity1, entity2, entity3]) + + # Create system with two subsystems: + # Subsystem 1: Find entities with A, remove A + # Subsystem 2: Find entities with A, increment counter (should see none) + var system = ComponentRemovalPropagationSystem.new() + world.add_system(system) + + # Process system once + world.process(0.016) + + # Verify: Subsystem 1 processed 3 entities (removed A from all of them) + assert_int(system.subsystem1_count).is_equal(3) + + # Verify: Subsystem 2 processed 0 entities (no entities have A anymore) + assert_int(system.subsystem2_count).is_equal(0) + + # Verify: All entities still have B but not A + assert_bool(entity1.has_component(C_OrderTestA)).is_false() + assert_bool(entity1.has_component(C_OrderTestB)).is_true() + assert_bool(entity2.has_component(C_OrderTestA)).is_false() + assert_bool(entity2.has_component(C_OrderTestB)).is_true() + assert_bool(entity3.has_component(C_OrderTestA)).is_false() + assert_bool(entity3.has_component(C_OrderTestB)).is_true() + + +## Test that component modifications causing archetype moves are handled correctly +func test_subsystem_archetype_move_propagation(): + # Create entities with different starting components + var entity1 = Entity.new() # Has A + var entity2 = Entity.new() # Has A + var entity3 = Entity.new() # Has B + var entity4 = Entity.new() # Has B + entity1.add_component(C_OrderTestA.new()) + entity2.add_component(C_OrderTestA.new()) + entity3.add_component(C_OrderTestB.new()) + entity4.add_component(C_OrderTestB.new()) + world.add_entities([entity1, entity2, entity3, entity4]) + + # Create system with three subsystems: + # Subsystem 1: Find entities with A, add B (archetype move from A to A+B) + # Subsystem 2: Find entities with B but not A, add A (archetype move from B to A+B) + # Subsystem 3: Find entities with A+B, increment counter (should see all 4) + var system = ArchetypeMovePropagationSystem.new() + world.add_system(system) + + # Process system once + world.process(0.016) + + # Verify: Subsystem 1 processed 2 entities (entity1, entity2) + assert_int(system.subsystem1_count).is_equal(2) + + # Verify: Subsystem 2 processed 2 entities (entity3, entity4) + assert_int(system.subsystem2_count).is_equal(2) + + # Verify: Subsystem 3 processed 4 entities (all entities now have A+B) + assert_int(system.subsystem3_count).is_equal(4) + + # Verify: All entities now have both A and B + assert_bool(entity1.has_component(C_OrderTestA)).is_true() + assert_bool(entity1.has_component(C_OrderTestB)).is_true() + assert_bool(entity2.has_component(C_OrderTestA)).is_true() + assert_bool(entity2.has_component(C_OrderTestB)).is_true() + assert_bool(entity3.has_component(C_OrderTestA)).is_true() + assert_bool(entity3.has_component(C_OrderTestB)).is_true() + assert_bool(entity4.has_component(C_OrderTestA)).is_true() + assert_bool(entity4.has_component(C_OrderTestB)).is_true() + + +## Test that entities are not double-processed when moving between archetypes +func test_subsystem_no_double_processing(): + # Create entities with A + var entity1 = Entity.new() + var entity2 = Entity.new() + entity1.add_component(C_OrderTestA.new()) + entity2.add_component(C_OrderTestA.new()) + world.add_entities([entity1, entity2]) + + # Create system with one subsystem that adds B to entities with A + # This causes archetype move from A to A+B + # System should NOT process the same entity twice + var system = NoDoubleProcessingSystem.new() + world.add_system(system) + + # Process system once + world.process(0.016) + + # Verify: Each entity processed exactly once + assert_int(system.entity1_process_count).is_equal(1) + assert_int(system.entity2_process_count).is_equal(1) + + +## Test that multiple archetype moves in sequence are handled correctly +func test_subsystem_multiple_archetype_moves(): + # Create entity with A + var entity = Entity.new() + entity.add_component(C_OrderTestA.new()) + world.add_entity(entity) + + # Create system with subsystems that progressively add components: + # Subsystem 1: A -> add B (A+B) + # Subsystem 2: A+B -> add C (A+B+C) + # Subsystem 3: A+B+C -> increment counter + var system = MultipleArchetypeMovesSystem.new() + world.add_system(system) + + # Process system once + world.process(0.016) + + # Verify: Each subsystem processed the entity + assert_int(system.subsystem1_count).is_equal(1) + assert_int(system.subsystem2_count).is_equal(1) + assert_int(system.subsystem3_count).is_equal(1) + + # Verify: Entity has all three components + assert_bool(entity.has_component(C_OrderTestA)).is_true() + assert_bool(entity.has_component(C_OrderTestB)).is_true() + assert_bool(entity.has_component(C_OrderTestC)).is_true() + + +## Test with many entities to ensure archetype moves scale correctly +func test_subsystem_archetype_move_at_scale(): + # Create 100 entities with A + var entities = [] + for i in 100: + var entity = Entity.new() + entity.add_component(C_OrderTestA.new()) + entities.append(entity) + world.add_entities(entities) + + # Create system that adds B to all entities with A + var system = ComponentAdditionPropagationSystem.new() + world.add_system(system) + + # Process system once + world.process(0.016) + + # Verify: Subsystem 1 processed 100 entities + assert_int(system.subsystem1_count).is_equal(100) + + # Verify: Subsystem 2 processed 100 entities (saw all B components) + assert_int(system.subsystem2_count).is_equal(100) + + # Verify: All entities have both A and B + for entity in entities: + assert_bool(entity.has_component(C_OrderTestA)).is_true() + assert_bool(entity.has_component(C_OrderTestB)).is_true() + + +## =============================== +## TEST HELPER SYSTEMS +## =============================== + +## System that adds components in subsystem 1 and checks them in subsystem 2 +class ComponentAdditionPropagationSystem extends System: + var subsystem1_count = 0 + var subsystem2_count = 0 + + func sub_systems() -> Array[Array]: + return [ + [ECS.world.query.with_all([C_OrderTestA]), add_component_b], + [ECS.world.query.with_all([C_OrderTestB]), count_component_b] + ] + + func add_component_b(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + entity.add_component(C_OrderTestB.new()) + subsystem1_count += 1 + + func count_component_b(entities: Array[Entity], components: Array, delta: float): + # Subsystems work like regular systems - called once per archetype + # So we need to accumulate the count across all archetype calls + subsystem2_count += entities.size() + + +## System that removes components in subsystem 1 and checks them in subsystem 2 +class ComponentRemovalPropagationSystem extends System: + var subsystem1_count = 0 + var subsystem2_count = 0 + + func sub_systems() -> Array[Array]: + return [ + [ECS.world.query.with_all([C_OrderTestA]), remove_component_a], + [ECS.world.query.with_all([C_OrderTestA]), count_component_a] + ] + + func remove_component_a(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + entity.remove_component(C_OrderTestA) + subsystem1_count += 1 + + func count_component_a(entities: Array[Entity], components: Array, delta: float): + subsystem2_count += entities.size() + + +## System that moves entities between archetypes +class ArchetypeMovePropagationSystem extends System: + var subsystem1_count = 0 + var subsystem2_count = 0 + var subsystem3_count = 0 + + func sub_systems() -> Array[Array]: + return [ + [ECS.world.query.with_all([C_OrderTestA]).with_none([C_OrderTestB]), add_b_to_a], + [ECS.world.query.with_all([C_OrderTestB]).with_none([C_OrderTestA]), add_a_to_b], + [ECS.world.query.with_all([C_OrderTestA, C_OrderTestB]), count_both] + ] + + func add_b_to_a(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + entity.add_component(C_OrderTestB.new()) + subsystem1_count += 1 + + func add_a_to_b(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + entity.add_component(C_OrderTestA.new()) + subsystem2_count += 1 + + func count_both(entities: Array[Entity], components: Array, delta: float): + subsystem3_count += entities.size() + + +## System that tracks individual entity processing to detect double-processing +class NoDoubleProcessingSystem extends System: + var entity1_process_count = 0 + var entity2_process_count = 0 + var tracked_entities = {} + + func sub_systems() -> Array[Array]: + return [ + [ECS.world.query.with_all([C_OrderTestA]), process_entities] + ] + + func process_entities(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + # Track which entity is being processed + if not tracked_entities.has(entity): + tracked_entities[entity] = 0 + tracked_entities[entity] += 1 + + # Count for first two entities + var keys = tracked_entities.keys() + if entity == keys[0]: + entity1_process_count = tracked_entities[entity] + elif keys.size() > 1 and entity == keys[1]: + entity2_process_count = tracked_entities[entity] + + # Add B to trigger archetype move + if not entity.has_component(C_OrderTestB): + entity.add_component(C_OrderTestB.new()) + + +## System that performs multiple sequential archetype moves +class MultipleArchetypeMovesSystem extends System: + var subsystem1_count = 0 + var subsystem2_count = 0 + var subsystem3_count = 0 + + func sub_systems() -> Array[Array]: + return [ + [ECS.world.query.with_all([C_OrderTestA]).with_none([C_OrderTestB]), add_b], + [ECS.world.query.with_all([C_OrderTestA, C_OrderTestB]).with_none([C_OrderTestC]), add_c], + [ECS.world.query.with_all([C_OrderTestA, C_OrderTestB, C_OrderTestC]), count_all] + ] + + func add_b(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + entity.add_component(C_OrderTestB.new()) + subsystem1_count += 1 + + func add_c(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + entity.add_component(C_OrderTestC.new()) + subsystem2_count += 1 + + func count_all(entities: Array[Entity], components: Array, delta: float): + subsystem3_count += entities.size() + + +## =============================== +## TEST HELPER COMPONENTS +## =============================== +## Using existing component classes from addons/gecs/tests/components/ +## - C_OrderTestA +## - C_OrderTestB +## - C_OrderTestC diff --git a/addons/gecs/tests/core/test_subsystem_component_propagation.gd.uid b/addons/gecs/tests/core/test_subsystem_component_propagation.gd.uid new file mode 100644 index 0000000..52e77be --- /dev/null +++ b/addons/gecs/tests/core/test_subsystem_component_propagation.gd.uid @@ -0,0 +1 @@ +uid://dbnfyv4w0xa14 diff --git a/addons/gecs/tests/core/test_subsystem_multi_entity_propagation.gd b/addons/gecs/tests/core/test_subsystem_multi_entity_propagation.gd new file mode 100644 index 0000000..51d7cc6 --- /dev/null +++ b/addons/gecs/tests/core/test_subsystem_multi_entity_propagation.gd @@ -0,0 +1,447 @@ +extends GdUnitTestSuite + +## Test suite for multi-entity subsystem propagation (projectile scenario) +## Tests that when subsystem A adds components to MULTIPLE entities, +## subsystem B sees ALL of them in the same frame + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + if world: + world.purge(false) + + +## Test the exact projectile scenario: travelling entities that collide get C_Collision added, +## then collision subsystem processes all entities with C_Collision +func test_projectile_collision_propagation(): + # Create 3 "projectiles" with base components (simulating travelling projectiles) + var projectile1 = Entity.new() + var projectile2 = Entity.new() + var projectile3 = Entity.new() + + projectile1.add_component(C_OrderTestA.new()) # Represents C_Projectile + projectile1.add_component(C_OrderTestB.new()) # Represents C_Velocity + projectile2.add_component(C_OrderTestA.new()) + projectile2.add_component(C_OrderTestB.new()) + projectile3.add_component(C_OrderTestA.new()) + projectile3.add_component(C_OrderTestB.new()) + + world.add_entities([projectile1, projectile2, projectile3]) + + # System simulates: travelling_subsys adds collision, then collision_subsys processes them + var system = ProjectileCollisionSystem.new() + world.add_system(system) + + # Process system once + world.process(0.016) + + # Verify: travelling_subsys saw 3 entities + assert_int(system.travelling_count).is_equal(3) + + # Verify: travelling_subsys added collision to all 3 + assert_int(system.collisions_added).is_equal(3) + + # CRITICAL: collision_subsys should see ALL 3 entities with collision + assert_int(system.collision_count).is_equal(3) + + # Verify: All entities have the collision component + assert_bool(projectile1.has_component(C_OrderTestC)).is_true() + assert_bool(projectile2.has_component(C_OrderTestC)).is_true() + assert_bool(projectile3.has_component(C_OrderTestC)).is_true() + + +## Test with many entities (10 projectiles) to ensure it scales +func test_projectile_collision_propagation_at_scale(): + var projectiles = [] + + # Create 10 projectiles + for i in 10: + var projectile = Entity.new() + projectile.add_component(C_OrderTestA.new()) + projectile.add_component(C_OrderTestB.new()) + projectiles.append(projectile) + + world.add_entities(projectiles) + + var system = ProjectileCollisionSystem.new() + world.add_system(system) + + # Process system once + world.process(0.016) + + # Verify: travelling_subsys saw 10 entities + assert_int(system.travelling_count).is_equal(10) + + # Verify: travelling_subsys added collision to all 10 + assert_int(system.collisions_added).is_equal(10) + + # CRITICAL: collision_subsys should see ALL 10 entities + assert_int(system.collision_count).is_equal(10) + + # Verify: All entities have collision + for projectile in projectiles: + assert_bool(projectile.has_component(C_OrderTestC)).is_true() + + +## Test when only SOME entities collide (partial propagation) +func test_projectile_partial_collision_propagation(): + var projectile1 = Entity.new() + var projectile2 = Entity.new() + var projectile3 = Entity.new() + var projectile4 = Entity.new() + + # All start with A+B + projectile1.add_component(C_OrderTestA.new()) + projectile1.add_component(C_OrderTestB.new()) + projectile2.add_component(C_OrderTestA.new()) + projectile2.add_component(C_OrderTestB.new()) + projectile3.add_component(C_OrderTestA.new()) + projectile3.add_component(C_OrderTestB.new()) + projectile4.add_component(C_OrderTestA.new()) + projectile4.add_component(C_OrderTestB.new()) + + world.add_entities([projectile1, projectile2, projectile3, projectile4]) + + # System that only adds collision to SOME entities + var system = ProjectilePartialCollisionSystem.new() + world.add_system(system) + + # Process system once + world.process(0.016) + + # Verify: travelling_subsys saw 4 entities + assert_int(system.travelling_count).is_equal(4) + + # Verify: only 2 collisions added (system logic adds every other) + assert_int(system.collisions_added).is_equal(2) + + # CRITICAL: collision_subsys should see exactly 2 entities + assert_int(system.collision_count).is_equal(2) + + +## Test entities that add collision and then get removed in collision handler +func test_projectile_collision_then_removal(): + var projectiles = [] + + # Create 5 projectiles + for i in 5: + var projectile = Entity.new() + projectile.add_component(C_OrderTestA.new()) + projectile.add_component(C_OrderTestB.new()) + projectiles.append(projectile) + + world.add_entities(projectiles) + + var system = ProjectileCollisionRemovalSystem.new() + world.add_system(system) + + # Process system once + world.process(0.016) + + # Verify: travelling_subsys saw 5 entities + assert_int(system.travelling_count).is_equal(5) + + # Verify: collision_subsys saw 5 entities + assert_int(system.collision_count).is_equal(5) + + # Verify: All 5 entities were removed + assert_int(system.entities_removed.size()).is_equal(5) + + # Verify: Entities are no longer in the world + var remaining = world.query.with_all([C_OrderTestA]).execute() + assert_int(remaining.size()).is_equal(0) + + +## Test EXACT projectile scenario: travelling adds collision, collision subsys processes and removes +## This tests with multiple entities being processed together and removed in batch +func test_exact_projectile_scenario_with_batch_removal(): + var projectiles = [] + + # Create 5 projectiles (simulating multiple projectiles fired) + for i in 5: + var projectile = Entity.new() + projectile.name = "Projectile_%d" % i + projectile.add_component(C_OrderTestA.new()) # C_Projectile + projectile.add_component(C_OrderTestB.new()) # C_Velocity + projectiles.append(projectile) + + world.add_entities(projectiles) + + # System that mimics your exact code structure + var system = ExactProjectileSystem.new() + world.add_system(system) + + # Process system once + world.process(0.016) + + # Verify: All projectiles were seen in travelling + assert_int(system.travelling_count).is_equal(5) + + # CRITICAL: All projectiles should be seen in collision subsystem + assert_int(system.collision_count).is_equal(5) + + # Verify: All projectiles were removed + var remaining_projectiles = world.query.with_all([C_OrderTestA]).execute() + assert_int(remaining_projectiles.size()).is_equal(0) + + # Verify: No projectiles with collision component remain either + var remaining_with_collision = world.query.with_all([C_OrderTestA, C_OrderTestC]).execute() + assert_int(remaining_with_collision.size()).is_equal(0) + + +## Test multiple frames to see if entities accumulate (your actual bug) +func test_multiple_frames_with_projectiles(): + # Frame 1: Fire 3 projectiles + var frame1_projectiles = [] + for i in 3: + var p = Entity.new() + p.name = "Frame1_Projectile_%d" % i + p.add_component(C_OrderTestA.new()) + p.add_component(C_OrderTestB.new()) + frame1_projectiles.append(p) + world.add_entities(frame1_projectiles) + + var system = ExactProjectileSystem.new() + world.add_system(system) + + # Process frame 1 + world.process(0.016) + assert_int(world.query.with_all([C_OrderTestA]).execute().size()).is_equal(0) + + # Frame 2: Fire 4 more projectiles + var frame2_projectiles = [] + for i in 4: + var p = Entity.new() + p.name = "Frame2_Projectile_%d" % i + p.add_component(C_OrderTestA.new()) + p.add_component(C_OrderTestB.new()) + frame2_projectiles.append(p) + world.add_entities(frame2_projectiles) + + # Process frame 2 + world.process(0.016) + assert_int(world.query.with_all([C_OrderTestA]).execute().size()).is_equal(0) + + # Frame 3: Fire 5 more projectiles (this is where it might break) + var frame3_projectiles = [] + for i in 5: + var p = Entity.new() + p.name = "Frame3_Projectile_%d" % i + p.add_component(C_OrderTestA.new()) + p.add_component(C_OrderTestB.new()) + frame3_projectiles.append(p) + world.add_entities(frame3_projectiles) + + # Process frame 3 + world.process(0.016) + + # CRITICAL: All projectiles should be removed, none should accumulate + var remaining = world.query.with_all([C_OrderTestA]).execute() + assert_int(remaining.size()).is_equal(0) + + +## REGRESSION TEST: Cache invalidation when removing entities +## This test ensures that _remove_entity_from_archetype() invalidates the query cache. +## Without cache invalidation, queries in subsequent frames would return stale archetype references. +## +## BUG: If _remove_entity_from_archetype() doesn't call _invalidate_cache(), then: +## 1. Frame N: Entities removed, cache still points to old archetype state +## 2. Frame N+1: Query uses stale cache, processes wrong/deleted entities +func test_cache_invalidation_on_entity_removal(): + # Frame 1: Create and remove entities + var frame1_entities = [] + for i in 3: + var e = Entity.new() + e.name = "Frame1_Entity_%d" % i + e.add_component(C_OrderTestA.new()) + frame1_entities.append(e) + world.add_entities(frame1_entities) + + # Verify entities exist + var query_result = world.query.with_all([C_OrderTestA]).execute() + assert_int(query_result.size()).is_equal(3) + + # Remove all entities - this MUST invalidate the cache + world.remove_entities(frame1_entities) + + # Verify entities are gone + query_result = world.query.with_all([C_OrderTestA]).execute() + assert_int(query_result.size()).is_equal(0) + + # Frame 2: Create NEW entities with same components + var frame2_entities = [] + for i in 5: + var e = Entity.new() + e.name = "Frame2_Entity_%d" % i + e.add_component(C_OrderTestA.new()) + frame2_entities.append(e) + world.add_entities(frame2_entities) + + # CRITICAL: Query should return ONLY the 5 new entities, not stale references + query_result = world.query.with_all([C_OrderTestA]).execute() + assert_int(query_result.size()).is_equal(5) + + # Verify the entities in the result are the NEW ones, not deleted ones + for entity in query_result: + assert_bool(frame2_entities.has(entity)).is_true() + assert_str(entity.name).starts_with("Frame2_Entity_") + + +## Test with entities in different starting archetypes (some have extra components) +func test_projectile_mixed_archetypes(): + # 2 basic projectiles (A+B) + var projectile1 = Entity.new() + var projectile2 = Entity.new() + projectile1.add_component(C_OrderTestA.new()) + projectile1.add_component(C_OrderTestB.new()) + projectile2.add_component(C_OrderTestA.new()) + projectile2.add_component(C_OrderTestB.new()) + + # 2 "special" projectiles with extra component (different archetype) + var projectile3 = Entity.new() + var projectile4 = Entity.new() + var extra_comp1 = C_DomainTestA.new() + var extra_comp2 = C_DomainTestA.new() + projectile3.add_component(C_OrderTestA.new()) + projectile3.add_component(C_OrderTestB.new()) + projectile3.add_component(extra_comp1) + projectile4.add_component(C_OrderTestA.new()) + projectile4.add_component(C_OrderTestB.new()) + projectile4.add_component(extra_comp2) + + world.add_entities([projectile1, projectile2, projectile3, projectile4]) + + var system = ProjectileCollisionSystem.new() + world.add_system(system) + + # Process system once + world.process(0.016) + + # Verify: ALL 4 entities were processed despite different starting archetypes + assert_int(system.travelling_count).is_equal(4) + assert_int(system.collisions_added).is_equal(4) + assert_int(system.collision_count).is_equal(4) + + +## =============================== +## TEST HELPER SYSTEMS +## =============================== + +## Simulates the ProjectileSystem: travelling_subsys adds collision, collision_subsys processes +class ProjectileCollisionSystem extends System: + var travelling_count = 0 + var collisions_added = 0 + var collision_count = 0 + + func sub_systems() -> Array[Array]: + return [ + # Travelling subsystem: entities with A+B (no C yet) + [ECS.world.query.with_all([C_OrderTestA, C_OrderTestB]), travelling_subsys], + # Collision subsystem: entities with A+B+C + [ECS.world.query.with_all([C_OrderTestA, C_OrderTestB, C_OrderTestC]), collision_subsys] + ] + + func travelling_subsys(entities: Array[Entity], components: Array, delta: float): + # Subsystems work like regular systems - called once per archetype + # Accumulate count across all archetype calls + travelling_count += entities.size() + # Simulate all entities colliding and getting C_Collision (OrderTestC) + for entity in entities: + entity.add_component(C_OrderTestC.new()) + collisions_added += 1 + + func collision_subsys(entities: Array[Entity], components: Array, delta: float): + # Subsystems work like regular systems - called once per archetype + # Accumulate count across all archetype calls + collision_count += entities.size() + # Just count how many we see + + +## System where only SOME entities collide +class ProjectilePartialCollisionSystem extends System: + var travelling_count = 0 + var collisions_added = 0 + var collision_count = 0 + + func sub_systems() -> Array[Array]: + return [ + [ECS.world.query.with_all([C_OrderTestA, C_OrderTestB]), travelling_subsys], + [ECS.world.query.with_all([C_OrderTestA, C_OrderTestB, C_OrderTestC]), collision_subsys] + ] + + func travelling_subsys(entities: Array[Entity], components: Array, delta: float): + # Subsystems work like regular systems - accumulate across archetype calls + travelling_count += entities.size() + # Only add collision to every other entity + var collide = true + for entity in entities: + if collide: + entity.add_component(C_OrderTestC.new()) + collisions_added += 1 + collide = !collide + + func collision_subsys(entities: Array[Entity], components: Array, delta: float): + # Subsystems work like regular systems - accumulate across archetype calls + collision_count += entities.size() + + +## System that removes entities after collision handling +class ProjectileCollisionRemovalSystem extends System: + var travelling_count = 0 + var collision_count = 0 + var entities_removed = [] + + func sub_systems() -> Array[Array]: + return [ + [ECS.world.query.with_all([C_OrderTestA, C_OrderTestB]), travelling_subsys], + [ECS.world.query.with_all([C_OrderTestA, C_OrderTestB, C_OrderTestC]), collision_subsys] + ] + + func travelling_subsys(entities: Array[Entity], components: Array, delta: float): + # Subsystems work like regular systems - accumulate across archetype calls + travelling_count += entities.size() + for entity in entities: + entity.add_component(C_OrderTestC.new()) + + func collision_subsys(entities: Array[Entity], components: Array, delta: float): + # Subsystems work like regular systems - accumulate across archetype calls + collision_count += entities.size() + # Track entities and remove them (simulating projectile destruction) + for entity in entities: + entities_removed.append(entity) + # Remove all at once (like your real code does) + ECS.world.remove_entities(entities) + + +## System that exactly mirrors your ProjectileSystem structure +class ExactProjectileSystem extends System: + var travelling_count = 0 + var collision_count = 0 + + func sub_systems() -> Array[Array]: + return [ + # IMPORTANT: Travelling MUST run first to add collision component + # Then collision handler can see all entities with collision + [ECS.world.query.with_all([C_OrderTestA, C_OrderTestB]), travelling_subsys], + [ECS.world.query.with_all([C_OrderTestA, C_OrderTestB, C_OrderTestC]), projectile_collision_subsys] + ] + + func travelling_subsys(entities: Array[Entity], components: Array, delta: float): + travelling_count = entities.size() + # Simulate all projectiles colliding + for e_projectile in entities: + # Add collision component (simulating move_and_slide collision) + e_projectile.add_component(C_OrderTestC.new()) + + func projectile_collision_subsys(entities: Array[Entity], components: Array, delta: float): + collision_count = entities.size() + # Remove all projectiles that collided (matching your exact code) + ECS.world.remove_entities(entities) diff --git a/addons/gecs/tests/core/test_subsystem_multi_entity_propagation.gd.uid b/addons/gecs/tests/core/test_subsystem_multi_entity_propagation.gd.uid new file mode 100644 index 0000000..f9c3411 --- /dev/null +++ b/addons/gecs/tests/core/test_subsystem_multi_entity_propagation.gd.uid @@ -0,0 +1 @@ +uid://6yo4w3eupvbq diff --git a/addons/gecs/tests/core/test_subsystem_relationship_bug.gd b/addons/gecs/tests/core/test_subsystem_relationship_bug.gd new file mode 100644 index 0000000..12579c6 --- /dev/null +++ b/addons/gecs/tests/core/test_subsystem_relationship_bug.gd @@ -0,0 +1,133 @@ +extends GdUnitTestSuite + +const C_TestA = preload("res://addons/gecs/tests/components/c_test_a.gd") +const C_TestB = preload("res://addons/gecs/tests/components/c_test_b.gd") +const C_Interacting = preload("res://addons/gecs/tests/components/c_test_c.gd") +const C_HasActiveItem = preload("res://addons/gecs/tests/components/c_test_d.gd") + +var runner: GdUnitSceneRunner +var world: World +var test_system: TestSubsystemRelationships + +# Track what was found in each subsystem for assertions +var subsystem1_found = [] +var subsystem2_found = [] + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + +func after_test(): + subsystem1_found.clear() + subsystem2_found.clear() + world.purge(false) + +# Test system that uses subsystems (like InteractionsSystem) +class TestSubsystemRelationships extends System: + var test_suite + + func sub_systems(): + return [ + # Subsystem 1: Check for entities with C_TestB and NO C_Interacting + [ECS.world.query.with_relationship([Relationship.new(C_TestB.new())]).with_none([C_Interacting]), process_can_interact], + # Subsystem 2: Check for entities with C_TestA (any) + [ECS.world.query.with_relationship([Relationship.new(C_TestA.new())]), process_being_interacted], + ] + + func process_can_interact(entities: Array[Entity], components: Array, delta: float): + print("Subsystem 1 processing: ", entities.size(), " entities") + for entity in entities: + print(" - Subsystem 1 found: ", entity.name) + test_suite.subsystem1_found.append(entity) + + func process_being_interacted(entities: Array[Entity], components: Array, delta: float): + print("Subsystem 2 processing: ", entities.size(), " entities") + for entity in entities: + print(" - Subsystem 2 found: ", entity.name) + test_suite.subsystem2_found.append(entity) + +func test_subsystem_with_existing_relationship_blocks_new_relationship_query(): + # Exact scenario: Player has C_HasActiveItem, walks into area getting C_CanInteractWith + # Subsystem queries for C_CanInteractWith but doesn't find player! + + # Create and add our test system with subsystems + test_system = TestSubsystemRelationships.new() + test_system.test_suite = self + world.add_system(test_system) + + var target = Entity.new() + target.name = "interactable" + world.add_entity(target) + + var player = Entity.new() + player.name = "player" + world.add_entity(player) + + print("\n=== Phase 1: Player has C_HasActiveItem (simulating equipped weapon) ===") + # Player already has a relationship (simulating C_HasActiveItem from equipped weapon) + player.add_relationship(Relationship.new(C_HasActiveItem.new(1), target)) + print("Player relationships: ", player.relationships.size()) + + # Process subsystems - should find nothing yet + subsystem1_found.clear() + subsystem2_found.clear() + world.process(0.016) + + print("\nAfter first process:") + print("Subsystem1 found (C_TestB): ", subsystem1_found.size()) + print("Subsystem2 found (C_TestA): ", subsystem2_found.size()) + + print("\n=== Phase 2: Player walks into area, gets C_CanInteractWith (C_TestB) ===") + # Player walks into interaction area and gets C_CanInteractWith relationship + player.add_relationship(Relationship.new(C_TestB.new(99), target)) + print("Player relationships: ", player.relationships.size()) + print("Player has C_TestB: ", player.has_relationship(Relationship.new(C_TestB.new()))) + + # Process subsystems again - BUG: might not find player in subsystem1! + subsystem1_found.clear() + subsystem2_found.clear() + world.process(0.016) + + print("\nAfter second process:") + print("Subsystem1 found (C_TestB): ", subsystem1_found.size()) + for ent in subsystem1_found: + print(" - ", ent.name) + print("Subsystem2 found (C_TestA): ", subsystem2_found.size()) + + # CRITICAL: Subsystem1 should have found the player! + assert_bool(subsystem1_found.has(player)).is_true() + +func test_subsystem_without_existing_relationship_works(): + # Control test: Same scenario but WITHOUT the C_HasActiveItem first + # This should work fine + # Create and add our test system with subsystems + test_system = TestSubsystemRelationships.new() + test_system.test_suite = self + world.add_system(test_system) + var target = Entity.new() + target.name = "interactable" + world.add_entity(target) + + var player = Entity.new() + player.name = "player" + world.add_entity(player) + + print("\n=== Control: Player gets C_TestB WITHOUT existing C_HasActiveItem ===") + # Player walks into interaction area and gets C_CanInteractWith relationship + player.add_relationship(Relationship.new(C_TestB.new(99), target)) + print("Player relationships: ", player.relationships.size()) + print("Player has C_TestB: ", player.has_relationship(Relationship.new(C_TestB.new()))) + + # Process subsystems - should find player! + subsystem1_found.clear() + subsystem2_found.clear() + world.process(0.016) + + print("\nAfter process:") + print("Subsystem1 found (C_TestB): ", subsystem1_found.size()) + for ent in subsystem1_found: + print(" - ", ent.name) + + # This should work + assert_bool(subsystem1_found.has(player)).is_true() diff --git a/addons/gecs/tests/core/test_subsystem_relationship_bug.gd.uid b/addons/gecs/tests/core/test_subsystem_relationship_bug.gd.uid new file mode 100644 index 0000000..ac36d17 --- /dev/null +++ b/addons/gecs/tests/core/test_subsystem_relationship_bug.gd.uid @@ -0,0 +1 @@ +uid://fo54moeskub diff --git a/addons/gecs/tests/core/test_subsystems.gd b/addons/gecs/tests/core/test_subsystems.gd new file mode 100644 index 0000000..165eed3 --- /dev/null +++ b/addons/gecs/tests/core/test_subsystems.gd @@ -0,0 +1,524 @@ +extends GdUnitTestSuite + +## Comprehensive test suite for System.sub_systems() functionality +## Tests execution methods, callable signatures, caching, error handling, and execution order + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + if world: + world.purge(false) + + +## =============================== +## SUBSYSTEM EXECUTION WITH DIFFERENT EXECUTION METHODS +## =============================== + +## Test subsystem with PROCESS execution method +func test_subsystem_process_execution(): + # Create entities + var entity1 = Entity.new() + var entity2 = Entity.new() + entity1.add_component(C_SubsystemTestA.new()) + entity2.add_component(C_SubsystemTestA.new()) + world.add_entities([entity1, entity2]) + + # Create system with PROCESS subsystem + var system = SubsystemProcessTest.new() + world.add_system(system) + + # Process system + world.process(0.016) + + # Verify: process_subsystem called once per entity + assert_int(system.call_count).is_equal(2) + assert_array(system.entities_processed).contains_exactly([entity1, entity2]) + + +## Test subsystem with PROCESS_ALL execution method +func test_subsystem_process_all_execution(): + # Create entities + var entity1 = Entity.new() + var entity2 = Entity.new() + entity1.add_component(C_SubsystemTestA.new()) + entity2.add_component(C_SubsystemTestA.new()) + world.add_entities([entity1, entity2]) + + # Create system with PROCESS_ALL subsystem + var system = SubsystemProcessAllTest.new() + world.add_system(system) + + # Process system + world.process(0.016) + + # Verify: process_all_subsystem called once with all entities + assert_int(system.call_count).is_equal(1) + assert_array(system.all_entities).contains_exactly([entity1, entity2]) + + +## Test subsystem with ARCHETYPE execution method +func test_subsystem_archetype_execution(): + # Create entities + var entity1 = Entity.new() + var entity2 = Entity.new() + entity1.add_component(C_SubsystemTestA.new()) + entity2.add_component(C_SubsystemTestA.new()) + world.add_entities([entity1, entity2]) + + # Create system with ARCHETYPE subsystem + var system = SubsystemArchetypeTest.new() + world.add_system(system) + + # Process system + world.process(0.016) + + # Verify: process_batch_subsystem called with component arrays + assert_int(system.call_count).is_greater_equal(1) # At least once per archetype + assert_int(system.total_entities_processed).is_equal(2) + assert_bool(system.received_component_arrays).is_true() + + +## Test mixed execution methods in same system +func test_subsystem_mixed_execution_methods(): + # Create entities with different components + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + entity1.add_component(C_SubsystemTestA.new()) + entity2.add_component(C_SubsystemTestB.new()) + entity3.add_component(C_SubsystemTestA.new()) + entity3.add_component(C_SubsystemTestB.new()) + world.add_entities([entity1, entity2, entity3]) + + # Create system with mixed subsystems + var system = SubsystemMixedTest.new() + world.add_system(system) + + # Process system + world.process(0.016) + + # Verify: Each subsystem ran with correct execution method + # Note: entity2 (C_SubsystemTestB only) also somehow matches, investigating why + assert_int(system.process_count).is_greater_equal(2) # entity1, entity3 have C_SubsystemTestA (expecting 2, getting 3) + assert_int(system.process_all_count).is_equal(1) # Called once with all C_SubsystemTestB entities + assert_int(system.archetype_count).is_greater_equal(1) # At least once for C_SubsystemTestA archetypes + + +## =============================== +## CALLABLE SIGNATURES MATCH EXECUTION METHOD +## =============================== + +## Test PROCESS subsystem receives correct parameters +func test_subsystem_process_signature(): + var entity = Entity.new() + entity.add_component(C_SubsystemTestA.new()) + world.add_entity(entity) + + var system = SubsystemSignatureTest.new() + world.add_system(system) + world.process(0.016) + + # Verify PROCESS signature: (entity, delta) + assert_bool(system.process_signature_correct).is_true() + assert_that(system.process_entity).is_not_null() + assert_float(system.process_delta).is_between(0.0, 1.0) + + +## Test PROCESS_ALL subsystem receives correct parameters +func test_subsystem_process_all_signature(): + var entity = Entity.new() + entity.add_component(C_SubsystemTestB.new()) + world.add_entity(entity) + + var system = SubsystemSignatureTest.new() + world.add_system(system) + world.process(0.016) + + # Verify PROCESS_ALL signature: (entities, delta) + assert_bool(system.process_all_signature_correct).is_true() + assert_that(system.process_all_entities).is_not_null() + assert_bool(system.process_all_entities is Array).is_true() + assert_float(system.process_all_delta).is_between(0.0, 1.0) + + +## Test ARCHETYPE subsystem receives correct parameters +func test_subsystem_archetype_signature(): + var entity = Entity.new() + entity.add_component(C_SubsystemTestC.new()) + world.add_entity(entity) + + var system = SubsystemSignatureTest.new() + world.add_system(system) + world.process(0.016) + + # Verify ARCHETYPE signature: (entities, components, delta) + assert_bool(system.archetype_signature_correct).is_true() + assert_that(system.archetype_entities).is_not_null() + assert_that(system.archetype_components).is_not_null() + assert_bool(system.archetype_entities is Array).is_true() + assert_bool(system.archetype_components is Array).is_true() + assert_float(system.archetype_delta).is_between(0.0, 1.0) + + +## =============================== +## SUBSYSTEM QUERY CACHING +## =============================== + +## Test that subsystem queries are cached and reused +func test_subsystem_query_caching(): + # Create entities + for i in 100: + var entity = Entity.new() + entity.add_component(C_SubsystemTestA.new()) + world.add_entity(entity) + + var system = SubsystemProcessTest.new() + world.add_system(system) + + # Process multiple times + for i in 10: + world.process(0.016) + + # Verify: System ran 10 times * 100 entities = 1000 calls + assert_int(system.call_count).is_equal(1000) + + +## Test that subsystem cache invalidates on component changes +func test_subsystem_cache_invalidation(): + var entity1 = Entity.new() + entity1.add_component(C_SubsystemTestA.new()) + world.add_entity(entity1) + + var system = SubsystemProcessTest.new() + world.add_system(system) + + # First process + world.process(0.016) + assert_int(system.call_count).is_equal(1) + + # Add another entity mid-frame + var entity2 = Entity.new() + entity2.add_component(C_SubsystemTestA.new()) + world.add_entity(entity2) + + # Second process should see new entity + world.process(0.016) + assert_int(system.call_count).is_equal(3) # 1 + 2 + + +## =============================== +## ERROR HANDLING FOR ARCHETYPE MODE +## =============================== + +## Test subsystem without .iterate() - now works fine with unified signature +func test_subsystem_archetype_missing_iterate_error(): + var entity = Entity.new() + entity.add_component(C_SubsystemTestA.new()) + world.add_entity(entity) + + # Create system without .iterate() - this is now valid + var system = SubsystemArchetypeMissingIterateTest.new() + world.add_system(system) + + # Process system - should work fine without iterate() + world.process(0.016) + + # Verify: Subsystem DOES execute (no error with unified signature) + # Without iterate(), components array will be empty but execution proceeds + assert_int(system.call_count).is_equal(1) + + +## Test ARCHETYPE subsystem works correctly with .iterate() +func test_subsystem_archetype_with_iterate(): + var entity = Entity.new() + var comp = C_SubsystemTestA.new() + comp.value = 42 + entity.add_component(comp) + world.add_entity(entity) + + var system = SubsystemArchetypeTest.new() + world.add_system(system) + world.process(0.016) + + # Verify: Component arrays received + assert_bool(system.received_component_arrays).is_true() + assert_int(system.total_entities_processed).is_equal(1) + + +## =============================== +## SUBSYSTEM EXECUTION ORDER +## =============================== + +## Test multiple subsystems execute in defined order +func test_subsystem_execution_order(): + var entity = Entity.new() + entity.add_component(C_SubsystemTestA.new()) + entity.add_component(C_SubsystemTestB.new()) + entity.add_component(C_SubsystemTestC.new()) + world.add_entity(entity) + + var system = SubsystemOrderTest.new() + world.add_system(system) + world.process(0.016) + + # Verify: Subsystems executed in order (1, 2, 3) + assert_array(system.execution_order).is_equal([1, 2, 3]) + + +## Test subsystem order is consistent across frames +func test_subsystem_order_consistency(): + var entity = Entity.new() + entity.add_component(C_SubsystemTestA.new()) + entity.add_component(C_SubsystemTestB.new()) + entity.add_component(C_SubsystemTestC.new()) + world.add_entity(entity) + + var system = SubsystemOrderTest.new() + world.add_system(system) + + # Process multiple frames + for i in 5: + system.execution_order.clear() + world.process(0.016) + assert_array(system.execution_order).is_equal([1, 2, 3]) + + +## =============================== +## EDGE CASES +## =============================== + +## Test empty subsystems array (should fallback to regular system execution) +func test_empty_subsystems(): + var entity = Entity.new() + entity.add_component(C_SubsystemTestA.new()) + world.add_entity(entity) + + var system = SubsystemEmptyTest.new() + world.add_system(system) + world.process(0.016) + + # Verify: Should not use subsystem execution (falls back to process/archetype/process_all) + # In this case, system does nothing (no process() override) + assert_int(system.call_count).is_equal(0) + + +## Test subsystem with no matching entities +func test_subsystem_no_matches(): + # No entities added + + var system = SubsystemProcessTest.new() + world.add_system(system) + world.process(0.016) + + # Verify: Subsystem not called + assert_int(system.call_count).is_equal(0) + + +## Test subsystem performance vs regular system +func test_subsystem_performance(): + # Create many entities + for i in 1000: + var entity = Entity.new() + entity.add_component(C_SubsystemTestA.new()) + world.add_entity(entity) + + var system = SubsystemArchetypeTest.new() + world.add_system(system) + + var time_start = Time.get_ticks_usec() + world.process(0.016) + var time_taken = Time.get_ticks_usec() - time_start + + # Verify: Processed all entities efficiently + assert_int(system.total_entities_processed).is_equal(1000) + print("Subsystem archetype processed 1000 entities in %d us" % time_taken) + + +## =============================== +## TEST HELPER SYSTEMS +## =============================== + +## System with PROCESS subsystem +class SubsystemProcessTest extends System: + var call_count = 0 + var entities_processed = [] + + func sub_systems() -> Array[Array]: + return [ + [ECS.world.query.with_all([C_SubsystemTestA]), process_subsystem] + ] + + func process_subsystem(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + call_count += 1 + entities_processed.append(entity) + + +## System with PROCESS_ALL subsystem +class SubsystemProcessAllTest extends System: + var call_count = 0 + var all_entities = [] + + func sub_systems() -> Array[Array]: + return [ + [ECS.world.query.with_all([C_SubsystemTestA]), process_all_subsystem] + ] + + func process_all_subsystem(entities: Array[Entity], components: Array, delta: float): + call_count += 1 + for entity in entities: + all_entities.append(entity) + + +## System with ARCHETYPE subsystem +class SubsystemArchetypeTest extends System: + var call_count = 0 + var total_entities_processed = 0 + var received_component_arrays = false + + func sub_systems() -> Array[Array]: + return [ + [ECS.world.query.with_all([C_SubsystemTestA]).iterate([C_SubsystemTestA]), process_batch_subsystem] + ] + + func process_batch_subsystem(entities: Array[Entity], components: Array, delta: float): + call_count += 1 + total_entities_processed += entities.size() + if components.size() > 0 and components[0] is Array: + received_component_arrays = true + + +## System with mixed execution methods +class SubsystemMixedTest extends System: + var process_count = 0 + var process_all_count = 0 + var archetype_count = 0 + + func sub_systems() -> Array[Array]: + return [ + [ECS.world.query.with_all([C_SubsystemTestA]), process_sub], + [ECS.world.query.with_all([C_SubsystemTestB]), process_all_sub], + [ECS.world.query.with_all([C_SubsystemTestA]).iterate([C_SubsystemTestA]), process_batch_sub] + ] + + func process_sub(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + process_count += 1 + + func process_all_sub(entities: Array[Entity], components: Array, delta: float): + process_all_count += 1 + + func process_batch_sub(entities: Array[Entity], components: Array, delta: float): + archetype_count += 1 + + +## System to test callable signatures +class SubsystemSignatureTest extends System: + var process_signature_correct = false + var process_entity = null + var process_delta = 0.0 + + var process_all_signature_correct = false + var process_all_entities = null + var process_all_delta = 0.0 + + var archetype_signature_correct = false + var archetype_entities = null + var archetype_components = null + var archetype_delta = 0.0 + + func sub_systems() -> Array[Array]: + return [ + [ECS.world.query.with_all([C_SubsystemTestA]), test_process], + [ECS.world.query.with_all([C_SubsystemTestB]), test_process_all], + [ECS.world.query.with_all([C_SubsystemTestC]).iterate([C_SubsystemTestC]), test_archetype] + ] + + func test_process(entities: Array[Entity], components: Array, delta: float): + # All subsystems now receive the unified signature + if entities.size() > 0: + process_entity = entities[0] + process_delta = delta + process_signature_correct = entities is Array and typeof(delta) == TYPE_FLOAT + + func test_process_all(entities: Array[Entity], components: Array, delta: float): + process_all_entities = entities + process_all_delta = delta + process_all_signature_correct = entities is Array and typeof(delta) == TYPE_FLOAT + + func test_archetype(entities: Array[Entity], components: Array, delta: float): + archetype_entities = entities + archetype_components = components + archetype_delta = delta + archetype_signature_correct = entities is Array and components is Array and typeof(delta) == TYPE_FLOAT + + +## System with ARCHETYPE but missing .iterate() +class SubsystemArchetypeMissingIterateTest extends System: + var call_count = 0 + + func sub_systems() -> Array[Array]: + return [ + # Missing .iterate() - should error + [ECS.world.query.with_all([C_SubsystemTestA]), process_batch_subsystem] + ] + + func process_batch_subsystem(entities: Array[Entity], components: Array, delta: float): + call_count += 1 + + +## System to test execution order +class SubsystemOrderTest extends System: + var execution_order = [] + + func sub_systems() -> Array[Array]: + return [ + [ECS.world.query.with_all([C_SubsystemTestA]), subsystem1], + [ECS.world.query.with_all([C_SubsystemTestB]), subsystem2], + [ECS.world.query.with_all([C_SubsystemTestC]), subsystem3] + ] + + func subsystem1(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + execution_order.append(1) + + func subsystem2(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + execution_order.append(2) + + func subsystem3(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + execution_order.append(3) + + +## System with empty subsystems (fallback behavior) +class SubsystemEmptyTest extends System: + var call_count = 0 + + func sub_systems() -> Array[Array]: + return [] # Empty - should not use subsystem execution + + # No process(), archetype(), or process_all() override + # System should do nothing + + +## =============================== +## TEST HELPER COMPONENTS +## =============================== + +class C_SubsystemTestA extends Component: + @export var value: float = 0.0 + +class C_SubsystemTestB extends Component: + @export var count: int = 0 + +class C_SubsystemTestC extends Component: + @export var data: String = "" diff --git a/addons/gecs/tests/core/test_subsystems.gd.uid b/addons/gecs/tests/core/test_subsystems.gd.uid new file mode 100644 index 0000000..e3e4be6 --- /dev/null +++ b/addons/gecs/tests/core/test_subsystems.gd.uid @@ -0,0 +1 @@ +uid://daxlfiewqgeo5 diff --git a/addons/gecs/tests/core/test_system.gd b/addons/gecs/tests/core/test_system.gd new file mode 100644 index 0000000..ef3d40a --- /dev/null +++ b/addons/gecs/tests/core/test_system.gd @@ -0,0 +1,275 @@ +extends GdUnitTestSuite + +const TestSystemWithRelationship = preload("res://addons/gecs/tests/systems/s_test_with_relationship.gd") +const TestSystemWithoutRelationship = preload("res://addons/gecs/tests/systems/s_test_without_relationship.gd") +const TestSystemWithGroup = preload("res://addons/gecs/tests/systems/s_test_with_group.gd") +const TestSystemWithoutGroup = preload("res://addons/gecs/tests/systems/s_test_without_group.gd") +const TestSystemNonexistentGroup = preload("res://addons/gecs/tests/systems/s_test_nonexistent_group.gd") + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + world.purge(false) + + +func test_system_processes_entities_with_required_components(): + # Create entities with the required components + var entity_a = TestA.new() + entity_a.add_component(C_TestA.new()) + + var entity_b = TestB.new() + entity_b.add_component(C_TestB.new()) + + var entity_c = TestC.new() + entity_c.add_component(C_TestC.new()) + + var entity_d = Entity.new() + entity_d.add_component(C_TestD.new()) + + # Add some entities before systems + world.add_entities([entity_a, entity_b]) + + world.add_system(TestASystem.new()) + world.add_system(TestBSystem.new()) + world.add_system(TestCSystem.new()) + + # add some entities after systems + world.add_entities([entity_c, entity_d]) + + # Run the systems once + world.process(0.1) + + # Check the values of the components + assert_int(entity_a.get_component(C_TestA).value).is_equal(1) + assert_int(entity_b.get_component(C_TestB).value).is_equal(1) + assert_int(entity_c.get_component(C_TestC).value).is_equal(1) + + # Doesn't get incremented because no systems picked it up + assert_int(entity_d.get_component(C_TestD).points).is_equal(0) + + # override the component with a new one + entity_a.add_component(C_TestA.new()) + # Run the systems again + world.process(0.1) + + # Check the values of the components + assert_int(entity_a.get_component(C_TestA).value).is_equal(1) # This is one because we added a new component which replaced the old one + assert_int(entity_b.get_component(C_TestB).value).is_equal(2) + assert_int(entity_c.get_component(C_TestC).value).is_equal(2) + + # Doesn't get incremented because no systems picked it up (still) + assert_int(entity_d.get_component(C_TestD).points).is_equal(0) + + +# FIXME: This test is failing system groups are not being set correctly (or they're being overidden somewhere) +func test_system_group_processes_entities_with_required_components(): + # Create entities with the required components + var entity_a = TestA.new() + entity_a.add_component(C_TestA.new()) + + var entity_b = TestB.new() + entity_b.add_component(C_TestB.new()) + + var entity_c = TestC.new() + entity_c.add_component(C_TestC.new()) + + var entity_d = Entity.new() + entity_d.add_component(C_TestD.new()) + + # Add some entities before systems + world.add_entities([entity_a, entity_b]) + + var sys_a = TestASystem.new() + sys_a.group = "group1" + var sys_b = TestBSystem.new() + sys_b.group = "group1" + var sys_c = TestCSystem.new() + sys_c.group = "group2" + + world.add_systems([sys_a, sys_b, sys_c]) + + # add some entities after systems + world.add_entities([entity_c, entity_d]) + + # Run the systems once by group + world.process(0.1, "group1") + world.process(0.1, "group2") + + # Check the values of the components + assert_int(entity_a.get_component(C_TestA).value).is_equal(1) + assert_int(entity_b.get_component(C_TestB).value).is_equal(1) + assert_int(entity_c.get_component(C_TestC).value).is_equal(1) + + # Doesn't get incremented because no systems picked it up + assert_int(entity_d.get_component(C_TestD).points).is_equal(0) + + # override the component with a new one + entity_a.add_component(C_TestA.new()) + # Run ALL the systems again (omitting the group means run the default group) + world.process(0.1) + + # Check the values of the components + assert_int(entity_a.get_component(C_TestA).value).is_equal(0) # This is one because we added a new component which replaced the old one + assert_int(entity_b.get_component(C_TestB).value).is_equal(1) + assert_int(entity_c.get_component(C_TestC).value).is_equal(1) + + # Doesn't get incremented because no systems picked it up (still) + assert_int(entity_d.get_component(C_TestD).points).is_equal(0) + + +func test_system_with_relationship_query(): + # Test the bug: with_relationship and without_relationship returning same results in system query + var entity_with_rel = Entity.new() + var entity_without_rel = Entity.new() + var target = Entity.new() + + # Only entity_with_rel has a relationship + entity_with_rel.add_relationship(Relationship.new(C_TestA.new(), target)) + + world.add_entity(entity_with_rel) + world.add_entity(entity_without_rel) + world.add_entity(target) + + var system_with = TestSystemWithRelationship.new() + world.add_system(system_with) + + # Process the system + world.process(0.1) + + # System should only find entity_with_rel + assert_array(system_with.entities_found).has_size(1) + assert_bool(system_with.entities_found.has(entity_with_rel)).is_true() + assert_bool(system_with.entities_found.has(entity_without_rel)).is_false() + assert_bool(system_with.entities_found.has(target)).is_false() + + +func test_system_without_relationship_query(): + # Test without_relationship in system context + var entity_with_rel = Entity.new() + var entity_without_rel = Entity.new() + var target = Entity.new() + + # Only entity_with_rel has a relationship + entity_with_rel.add_relationship(Relationship.new(C_TestA.new(), target)) + + world.add_entity(entity_with_rel) + world.add_entity(entity_without_rel) + world.add_entity(target) + + var system_without = TestSystemWithoutRelationship.new() + world.add_system(system_without) + + # Process the system + world.process(0.1) + + # System should find entity_without_rel and target (not entity_with_rel) + assert_bool(system_without.entities_found.has(entity_with_rel)).is_false() + assert_bool(system_without.entities_found.has(entity_without_rel)).is_true() + assert_bool(system_without.entities_found.has(target)).is_true() + + +func test_system_with_vs_without_relationship_different_results(): + # Verify that with_relationship and without_relationship return DIFFERENT results + var entity_with_rel = Entity.new() + var entity_without_rel = Entity.new() + var target = Entity.new() + + entity_with_rel.add_relationship(Relationship.new(C_TestA.new(), target)) + + world.add_entity(entity_with_rel) + world.add_entity(entity_without_rel) + world.add_entity(target) + + var system_with = TestSystemWithRelationship.new() + var system_without = TestSystemWithoutRelationship.new() + world.add_system(system_with) + world.add_system(system_without) + + # Process both systems + world.process(0.1) + + # The two systems should find DIFFERENT entities + assert_bool(system_with.entities_found.has(entity_with_rel)).is_true() + assert_bool(system_without.entities_found.has(entity_with_rel)).is_false() + + assert_bool(system_with.entities_found.has(entity_without_rel)).is_false() + assert_bool(system_without.entities_found.has(entity_without_rel)).is_true() + + +func test_system_with_group_query(): + # Test with_group in system context + var entity_in_group = Entity.new() + var entity_not_in_group = Entity.new() + + entity_in_group.add_to_group("TestGroup") + + world.add_entity(entity_in_group) + world.add_entity(entity_not_in_group) + + var system = TestSystemWithGroup.new() + world.add_system(system) + + # Process the system + world.process(0.1) + + # System should only find entity_in_group + assert_array(system.entities_found).has_size(1) + assert_bool(system.entities_found.has(entity_in_group)).is_true() + assert_bool(system.entities_found.has(entity_not_in_group)).is_false() + + +func test_system_without_group_query(): + # Test without_group in system context + var entity_in_group = Entity.new() + var entity_not_in_group = Entity.new() + + entity_in_group.add_to_group("TestGroup") + + world.add_entity(entity_in_group) + world.add_entity(entity_not_in_group) + + var system = TestSystemWithoutGroup.new() + world.add_system(system) + + # Process the system + world.process(0.1) + + # System should only find entity_not_in_group + assert_array(system.entities_found).has_size(1) + assert_bool(system.entities_found.has(entity_not_in_group)).is_true() + assert_bool(system.entities_found.has(entity_in_group)).is_false() + + +func test_system_nonexistent_group_query(): + # Test the bug: querying for nonexistent group should return ZERO entities, not all + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + + entity1.add_to_group("GroupA") + entity2.add_to_group("GroupB") + # entity3 has no groups + + world.add_entity(entity1) + world.add_entity(entity2) + world.add_entity(entity3) + + var system = TestSystemNonexistentGroup.new() + world.add_system(system) + + # Process the system + world.process(0.1) + + # System should find ZERO entities (not all of them!) + assert_array(system.entities_found).has_size(0) + assert_bool(system.entities_found.has(entity1)).is_false() + assert_bool(system.entities_found.has(entity2)).is_false() + assert_bool(system.entities_found.has(entity3)).is_false() diff --git a/addons/gecs/tests/core/test_system.gd.uid b/addons/gecs/tests/core/test_system.gd.uid new file mode 100644 index 0000000..47cdd0a --- /dev/null +++ b/addons/gecs/tests/core/test_system.gd.uid @@ -0,0 +1 @@ +uid://c38fxp8uh6w20 diff --git a/addons/gecs/tests/core/test_topological_sort_execution_order.gd b/addons/gecs/tests/core/test_topological_sort_execution_order.gd new file mode 100644 index 0000000..ce0ebaf --- /dev/null +++ b/addons/gecs/tests/core/test_topological_sort_execution_order.gd @@ -0,0 +1,440 @@ +extends GdUnitTestSuite + +## Test suite for verifying topological sorting of systems and their execution order in the World. +## This test demonstrates how system dependencies (Runs.Before and Runs.After) affect the order +## in which systems are executed during World.process(). +## +## NOTE: Inner classes prevent GdUnit from discovering tests, so all test components/systems +## have been extracted to separate files in addons/gecs/tests/systems/ + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + world.purge(false) + + +func test_topological_sort_basic_execution_order(): + # Create entity with component + var entity = Entity.new() + entity.name = "TestEntity" + entity.add_component(C_TestOrderComponent.new()) + world.add_entity(entity) + + # Add systems in random order (NOT dependency order) + var sys_d = S_TestOrderD.new() + var sys_b = S_TestOrderB.new() + var sys_c = S_TestOrderC.new() + var sys_a = S_TestOrderA.new() + + # Add in intentionally wrong order but topo sort enabled + world.add_systems([sys_d, sys_b, sys_c, sys_a], true) + + # Verify the systems are now sorted correctly + var sorted_systems = world.systems_by_group[""] + assert_int(sorted_systems.size()).is_equal(4) + assert_object(sorted_systems[0]).is_same(sys_a) # A runs first + assert_object(sorted_systems[1]).is_same(sys_b) # B runs after A + assert_object(sorted_systems[2]).is_same(sys_c) # C runs after B + assert_object(sorted_systems[3]).is_same(sys_d) # D runs last + + # Process the world - systems should execute in dependency order + world.process(0.016) + + var comp := entity.get_component(C_TestOrderComponent) as C_TestOrderComponent + + # Verify execution order in the log + assert_array(comp.execution_log).is_equal(["A", "B", "C", "D"]) + + # Verify value accumulation happened in correct order + # A adds 1, B adds 10, C adds 100, D adds 1000 = 1111 + assert_int(comp.value).is_equal(1111) + + +func test_topological_sort_multiple_groups(): + # Create entity with component + var entity = Entity.new() + entity.name = "TestEntity" + entity.add_component(C_TestOrderComponent.new()) + world.add_entity(entity) + + # Create systems for different groups + var sys_a_physics = S_TestOrderA.new() + sys_a_physics.group = "physics" + + var sys_b_physics = S_TestOrderB.new() + sys_b_physics.group = "physics" + + var sys_a_render = S_TestOrderA.new() + sys_a_render.group = "render" + + var sys_c_render = S_TestOrderC.new() + sys_c_render.group = "render" + + # Add in wrong order + world.add_systems([sys_b_physics, sys_a_physics, sys_c_render, sys_a_render], true) + + # Verify physics group is sorted + var physics_systems = world.systems_by_group["physics"] + assert_int(physics_systems.size()).is_equal(2) + assert_object(physics_systems[0]).is_same(sys_a_physics) + assert_object(physics_systems[1]).is_same(sys_b_physics) + + # Verify render group is sorted + var render_systems = world.systems_by_group["render"] + assert_int(render_systems.size()).is_equal(2) + assert_object(render_systems[0]).is_same(sys_a_render) + assert_object(render_systems[1]).is_same(sys_c_render) + + var comp := entity.get_component(C_TestOrderComponent) as C_TestOrderComponent + # Process only physics group + comp.execution_log.clear() + world.process(0.016, "physics") + assert_array(comp.execution_log).is_equal(["A", "B"]) + + # Process only render group + comp.execution_log.clear() + world.process(0.016, "render") + assert_array(comp.execution_log).is_equal(["A", "C"]) + + +func test_topological_sort_no_dependencies(): + # Systems with no dependencies should maintain their addition order + var entity = Entity.new() + entity.name = "TestEntity" + entity.add_component(C_TestOrderComponent.new()) + world.add_entity(entity) + + var sys_x = S_TestOrderX.new() + var sys_y = S_TestOrderY.new() + var sys_z = S_TestOrderZ.new() + + # Add in specific order + world.add_systems([sys_x, sys_y, sys_z], true) + + # When systems have no dependencies, they maintain addition order + var sorted_systems = world.systems_by_group[""] + assert_int(sorted_systems.size()).is_equal(3) + # Order should be preserved since no dependencies exist + assert_object(sorted_systems[0]).is_same(sys_x) + assert_object(sorted_systems[1]).is_same(sys_y) + assert_object(sorted_systems[2]).is_same(sys_z) + + world.process(0.016) + var comp := entity.get_component(C_TestOrderComponent) as C_TestOrderComponent + assert_array(comp.execution_log).is_equal(["X", "Y", "Z"]) + + +func test_topological_sort_with_add_system_flag(): + # Test that add_system with topo_sort=true automatically sorts + var entity = Entity.new() + entity.name = "TestEntity" + entity.add_component(C_TestOrderComponent.new()) + world.add_entity(entity) + + # Add systems in wrong order but with topo_sort enabled + world.add_system(S_TestOrderD.new(), true) + world.add_system(S_TestOrderB.new(), true) + world.add_system(S_TestOrderC.new(), true) + world.add_system(S_TestOrderA.new(), true) + + # Systems should already be sorted + var sorted_systems = world.systems_by_group[""] + assert_bool(sorted_systems[0] is S_TestOrderA).is_true() + assert_bool(sorted_systems[1] is S_TestOrderB).is_true() + assert_bool(sorted_systems[2] is S_TestOrderC).is_true() + assert_bool(sorted_systems[3] is S_TestOrderD).is_true() + + # Verify execution order + world.process(0.016) + var comp := entity.get_component(C_TestOrderComponent) as C_TestOrderComponent + assert_array(comp.execution_log).is_equal(["A", "B", "C", "D"]) + + +func test_topological_sort_complex_dependencies(): + # Test more complex dependency graph + var entity = Entity.new() + entity.name = "TestEntity" + entity.add_component(C_TestOrderComponent.new()) + world.add_entity(entity) + + # Create systems and check their dependencies before adding + var sys_e = S_TestOrderE.new() + var sys_f = S_TestOrderF.new() + var sys_g = S_TestOrderG.new() + var sys_h = S_TestOrderH.new() + + # Debug: Check if systems have dependency metadata + print("System E dependencies: ", sys_e.deps()) + print("System F dependencies: ", sys_f.deps()) + print("System G dependencies: ", sys_g.deps()) + print("System H dependencies: ", sys_h.deps()) + + # Check if systems have the proper class names for dependency resolution + print("System E class: ", sys_e.get_script().get_global_name()) + print("System F class: ", sys_f.get_script().get_global_name()) + print("System G class: ", sys_g.get_script().get_global_name()) + print("System H class: ", sys_h.get_script().get_global_name()) + + print("Adding systems with topo_sort=true...") + # Add in random order + world.add_systems([sys_f, sys_h, sys_g, sys_e], true) + + # Debug: Check system order after sorting + var sorted_systems = world.systems_by_group[""] + print("Systems after sorting (count: ", sorted_systems.size(), "):") + for i in range(sorted_systems.size()): + var sys = sorted_systems[i] + print(" [", i, "]: ", sys.get_script().get_global_name(), " (same as original? E:", sys == sys_e, " F:", sys == sys_f, " G:", sys == sys_g, " H:", sys == sys_h, ")") + + # Verify if the sort actually happened by checking if order changed + var original_order = [sys_f, sys_h, sys_g, sys_e] + var order_changed = false + for i in range(sorted_systems.size()): + if sorted_systems[i] != original_order[i]: + order_changed = true + break + print("Order changed after sorting: ", order_changed) + + world.process(0.016) + + # E must run first, F and G must run after E, H must run after both F and G + var comp := entity.get_component(C_TestOrderComponent) as C_TestOrderComponent + var log = comp.execution_log + + # Debug: Check execution + print("Raw execution log: ", log) + print("Log size: ", log.size()) + + if log.is_empty(): + print("ERROR: No systems executed! Log is empty.") + print("Entity has component: ", entity.has_component(C_TestOrderComponent)) + print("Component value: ", comp.value) + assert_bool(false).is_true() # Force test failure with debug info + return + + # Simple verification without processing - just check the raw log + print("Expected order should be: E first, H last, F and G in middle") + + # Verify the correct execution order + assert_int(log.size()).is_equal(4) + + # E must run first (no dependencies) + assert_str(log[0]).is_equal("E") + + # H must run last (depends on both F and G) + assert_str(log[3]).is_equal("H") + + # F and G must run after E but before H (they can be in any order) + var middle_systems = [log[1], log[2]] + assert_bool(middle_systems.has("F")).is_true() + assert_bool(middle_systems.has("G")).is_true() + + print("Topological sort is working correctly!") + + +func test_topological_sort_partial_dependencies(): + """Test with only some systems having dependencies (E, F, G only)""" + # Create entity with component + var entity = Entity.new() + entity.name = "TestEntity_Partial" + entity.add_component(C_TestOrderComponent.new()) + world.add_entity(entity) + + # Add systems: E (no deps), F (depends on E), G (depends on E) + world.add_system(S_TestOrderE.new(), true) # Enable topo_sort + world.add_system(S_TestOrderF.new(), true) + world.add_system(S_TestOrderG.new(), true) + + world.process(0.016) + + var comp := entity.get_component(C_TestOrderComponent) as C_TestOrderComponent + var log = comp.execution_log + + print("Partial dependencies test - Log: ", log) + + # Should be: E first, then F and G (in any order) + assert_int(log.size()).is_equal(3) + assert_str(log[0]).is_equal("E") + + var middle_systems = [log[1], log[2]] + assert_bool(middle_systems.has("F")).is_true() + assert_bool(middle_systems.has("G")).is_true() + + +func test_topological_sort_linear_chain(): + """Test a linear dependency chain: A->B, B->C, C->D""" + # Create entity with component + var entity = Entity.new() + entity.name = "TestEntity_Linear" + entity.add_component(C_TestOrderComponent.new()) + world.add_entity(entity) + + # Add systems in reverse order to test sorting + world.add_system(S_TestOrderD.new(), true) # D depends on C - Enable topo_sort + world.add_system(S_TestOrderC.new(), true) # C depends on B + world.add_system(S_TestOrderB.new(), true) # B depends on A + world.add_system(S_TestOrderA.new(), true) # A has no deps + + world.process(0.016) + + var comp := entity.get_component(C_TestOrderComponent) as C_TestOrderComponent + var log = comp.execution_log + + print("Linear chain test - Log: ", log) + + # Should be exactly: A, B, C, D + assert_int(log.size()).is_equal(4) + assert_str(log[0]).is_equal("A") + assert_str(log[1]).is_equal("B") + assert_str(log[2]).is_equal("C") + assert_str(log[3]).is_equal("D") + + +func test_topological_sort_no_dependencies_order_preserved(): + """Test systems with wildcard dependencies - A should run before E""" + # Create entity with component + var entity = Entity.new() + entity.name = "TestEntity_NoDeps" + entity.add_component(C_TestOrderComponent.new()) + world.add_entity(entity) + + # Add systems with no dependencies + world.add_system(S_TestOrderE.new(), true) # No deps - Enable topo_sort + world.add_system(S_TestOrderA.new(), true) # No deps + + world.process(0.016) + + var comp := entity.get_component(C_TestOrderComponent) as C_TestOrderComponent + var log = comp.execution_log + + print("No dependencies test - Log: ", log) + + # Should execute in dependency order: A runs before all (wildcard), then E + assert_int(log.size()).is_equal(2) + assert_str(log[0]).is_equal("A") # A runs first (has Runs.Before: [ECS.wildcard]) + assert_str(log[1]).is_equal("E") # E runs after A + + +func test_topological_sort_mixed_scenarios(): + """Test all systems together with complex interdependencies""" + # Create entity with component + var entity = Entity.new() + entity.name = "TestEntity_Mixed" + entity.add_component(C_TestOrderComponent.new()) + world.add_entity(entity) + + # Add all systems in random order to test sorting + world.add_system(S_TestOrderH.new(), true) # H depends on F,G - Enable topo_sort + world.add_system(S_TestOrderB.new(), true) # B depends on A + world.add_system(S_TestOrderF.new(), true) # F depends on E + world.add_system(S_TestOrderD.new(), true) # D depends on C + world.add_system(S_TestOrderE.new(), true) # E has no deps + world.add_system(S_TestOrderA.new(), true) # A has no deps + world.add_system(S_TestOrderG.new(), true) # G depends on E + world.add_system(S_TestOrderC.new(), true) # C depends on B + + world.process(0.016) + + var comp := entity.get_component(C_TestOrderComponent) as C_TestOrderComponent + var log = comp.execution_log + + print("Mixed scenarios test - Log: ", log) + print("Expected constraints:") + print(" - Chain A->B->C->D must be in order") + print(" - Chain E->F,G->H must be in order") + print(" - A and E can be in any order (both have no deps)") + + assert_int(log.size()).is_equal(8) + + # Find positions of each system + var positions = {} + for i in range(log.size()): + positions[log[i]] = i + + # Verify chain A->B->C->D + assert_bool(positions["A"] < positions["B"]).is_true() + assert_bool(positions["B"] < positions["C"]).is_true() + assert_bool(positions["C"] < positions["D"]).is_true() + + # Verify chain E->F,G->H + assert_bool(positions["E"] < positions["F"]).is_true() + assert_bool(positions["E"] < positions["G"]).is_true() + assert_bool(positions["F"] < positions["H"]).is_true() + assert_bool(positions["G"] < positions["H"]).is_true() + + print("All dependency constraints satisfied!") + + +func test_no_topological_sort_preserves_order(): + """Test that when topo_sort=false (default), systems execute in add order""" + # Create entity with component + var entity = Entity.new() + entity.name = "TestEntity_NoTopoSort" + entity.add_component(C_TestOrderComponent.new()) + world.add_entity(entity) + + # Add systems with dependencies but WITHOUT topo_sort enabled + # This should execute in the order they were added, not dependency order + world.add_system(S_TestOrderH.new()) # H depends on F,G (topo_sort=false by default) + world.add_system(S_TestOrderF.new()) # F depends on E + world.add_system(S_TestOrderE.new()) # E has no deps + world.add_system(S_TestOrderG.new()) # G depends on E + + world.process(0.016) + + var comp := entity.get_component(C_TestOrderComponent) as C_TestOrderComponent + var log = comp.execution_log + + print("No topo sort test - Log: ", log) + print("Systems should execute in add order: H, F, E, G") + + # Should execute in the exact order they were added, ignoring dependencies + assert_int(log.size()).is_equal(4) + assert_str(log[0]).is_equal("H") # First added + assert_str(log[1]).is_equal("F") # Second added + assert_str(log[2]).is_equal("E") # Third added + assert_str(log[3]).is_equal("G") # Fourth added + + print("✓ Systems executed in add order, ignoring dependencies (as expected)") + + +func test_mixed_topological_sort_flags(): + """Test mixing systems with and without topo_sort enabled""" + # Create entity with component + var entity = Entity.new() + entity.name = "TestEntity_MixedFlags" + entity.add_component(C_TestOrderComponent.new()) + world.add_entity(entity) + + # Add some systems with topo_sort=true, others with false + world.add_system(S_TestOrderE.new(), true) # E: topo_sort=true + world.add_system(S_TestOrderH.new(), false) # H: topo_sort=false + world.add_system(S_TestOrderF.new(), true) # F: topo_sort=true + world.add_system(S_TestOrderG.new(), false) # G: topo_sort=false + + world.process(0.016) + + var comp := entity.get_component(C_TestOrderComponent) as C_TestOrderComponent + var log = comp.execution_log + + print("Mixed topo sort flags test - Log: ", log) + + # This test documents the current behavior - exact order may depend on implementation + # The main point is that it should execute without errors + assert_int(log.size()).is_equal(4) + + # All systems should have executed + assert_bool(log.has("E")).is_true() + assert_bool(log.has("F")).is_true() + assert_bool(log.has("G")).is_true() + assert_bool(log.has("H")).is_true() + + print("✓ Mixed topo_sort flags handled without errors") diff --git a/addons/gecs/tests/core/test_topological_sort_execution_order.gd.uid b/addons/gecs/tests/core/test_topological_sort_execution_order.gd.uid new file mode 100644 index 0000000..e6b5bfb --- /dev/null +++ b/addons/gecs/tests/core/test_topological_sort_execution_order.gd.uid @@ -0,0 +1 @@ +uid://jksjkvw83bmv diff --git a/addons/gecs/tests/core/test_world.gd b/addons/gecs/tests/core/test_world.gd new file mode 100644 index 0000000..978670f --- /dev/null +++ b/addons/gecs/tests/core/test_world.gd @@ -0,0 +1,55 @@ +extends GdUnitTestSuite # Assuming GutTest is the correct base class in your setup + +var runner: GdUnitSceneRunner +var world: World + + + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + if world: + world.purge(false) + + +func test_add_and_remove_entity(): + var entity = Entity.new() + # Test adding + world.add_entities([entity]) + assert_bool(world.entities.has(entity)).is_true() + # Test removing + world.remove_entity(entity) + assert_bool(world.entities.has(entity)).is_false() + + +func test_add_and_remove_system(): + var system = System.new() + # Test adding + world.add_systems([system]) + assert_bool(world.systems.has(system)).is_true() + # Test removing + world.remove_system(system) + assert_bool(world.systems.has(system)).is_false() + + +func test_purge(): + # Add an entity and a system + var entity1 = Entity.new() + var entity2 = Entity.new() + world.add_entities([entity2, entity1]) + + var system1 = System.new() + var system2 = System.new() + world.add_systems([system1, system2]) + + # PURGE!!! + world.purge(false) + # Should be no entities and systems now + assert_int(world.entities.size()).is_equal(0) + assert_int(world.systems.size()).is_equal(0) + diff --git a/addons/gecs/tests/core/test_world.gd.uid b/addons/gecs/tests/core/test_world.gd.uid new file mode 100644 index 0000000..65b34fd --- /dev/null +++ b/addons/gecs/tests/core/test_world.gd.uid @@ -0,0 +1 @@ +uid://b13q8t5827lf8 diff --git a/addons/gecs/tests/core/test_world_cache_invalidation.gd b/addons/gecs/tests/core/test_world_cache_invalidation.gd new file mode 100644 index 0000000..5ac151f --- /dev/null +++ b/addons/gecs/tests/core/test_world_cache_invalidation.gd @@ -0,0 +1,408 @@ +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + +func after_test(): + if world: + world.purge(false) + +## Test that component addition invalidates cached query results +func test_component_addition_invalidates_cache(): + # Setup entities and initial query + var entity1 = Entity.new() + var entity2 = Entity.new() + world.add_entities([entity1, entity2]) + + # Add component to entity1 AFTER adding to world + entity1.add_component(C_TestA.new()) + + # Execute query and cache result + var query = world.query.with_all([C_TestA]) + var initial_result = query.execute() + assert_array(initial_result).has_size(1) + assert_bool(initial_result.has(entity1)).is_true() + + # Add component to entity2 mid-frame + entity2.add_component(C_TestA.new()) + + # Execute same query again - should see fresh results + var updated_result = query.execute() + assert_array(updated_result).has_size(2) + assert_bool(updated_result.has(entity1)).is_true() + assert_bool(updated_result.has(entity2)).is_true() + +## Test that component removal invalidates cached query results +func test_component_removal_invalidates_cache(): + # Setup entities with components + var entity1 = Entity.new() + var entity2 = Entity.new() + entity1.add_component(C_TestA.new()) + entity2.add_component(C_TestA.new()) + world.add_entities([entity1, entity2]) + + # Execute query and cache result + var query = world.query.with_all([C_TestA]) + var initial_result = query.execute() + assert_array(initial_result).has_size(2) + + # Remove component from entity1 mid-frame + entity1.remove_component(C_TestA) + + # Execute same query again - should see fresh results + var updated_result = query.execute() + assert_array(updated_result).has_size(1) + assert_bool(updated_result.has(entity2)).is_true() + assert_bool(updated_result.has(entity1)).is_false() + +## Test that multiple component changes in same frame all invalidate cache +func test_multiple_component_changes_invalidate_cache(): + # Setup entities + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + entity1.add_component(C_TestA.new()) + world.add_entities([entity1, entity2, entity3]) + + # Execute query and cache result + var query = world.query.with_all([C_TestA]) + var initial_result = query.execute() + assert_array(initial_result).has_size(1) + + # Make multiple changes in same frame + entity2.add_component(C_TestA.new()) # Add to entity2 + entity3.add_component(C_TestA.new()) # Add to entity3 + entity1.remove_component(C_TestA) # Remove from entity1 + + # Execute query - should reflect all changes + var final_result = query.execute() + assert_array(final_result).has_size(2) + assert_bool(final_result.has(entity2)).is_true() + assert_bool(final_result.has(entity3)).is_true() + assert_bool(final_result.has(entity1)).is_false() + +## Test cache invalidation works with complex queries +func test_complex_query_cache_invalidation(): + # Setup entities with multiple components + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + + entity1.add_component(C_TestA.new()) + entity1.add_component(C_TestB.new()) + + entity2.add_component(C_TestA.new()) + entity2.add_component(C_TestC.new()) + + entity3.add_component(C_TestB.new()) + entity3.add_component(C_TestC.new()) + + world.add_entities([entity1, entity2, entity3]) + + # Complex query: has TestA AND (TestB OR TestC) but NOT TestD + var query = world.query.with_all([C_TestA]).with_any([C_TestB, C_TestC]).with_none([C_TestD]) + var initial_result = query.execute() + assert_array(initial_result).has_size(2) # entity1 and entity2 + + # Add TestD to entity1 - should remove it from results + entity1.add_component(C_TestD.new()) + + var updated_result = query.execute() + assert_array(updated_result).has_size(1) # only entity2 + assert_bool(updated_result.has(entity2)).is_true() + assert_bool(updated_result.has(entity1)).is_false() + +## Test that cache invalidation signal is properly emitted +func test_cache_invalidation_signal_emission(): + var signal_count = [0] # Use array to avoid closure issues + + # Connect to cache invalidation signal + world.cache_invalidated.connect(func(): + signal_count[0] += 1 + print("[TEST] Signal count incremented to: ", signal_count[0]) + ) + + var entity = Entity.new() + # Adding entity should emit cache_invalidated once + print("[TEST] About to add entity, current signal_count: ", signal_count[0]) + world.add_entity(entity) + print("[TEST] After add entity, signal_count: ", signal_count[0]) + assert_int(signal_count[0]).is_greater_equal(1) # At least one for adding entity + + var initial_count = signal_count[0] + + # Test if signals are properly connected + assert_bool(entity.component_added.is_connected(world._on_entity_component_added)).is_true() + assert_bool(entity.component_removed.is_connected(world._on_entity_component_removed)).is_true() + + # Each component operation should emit signal (may be multiple due to archetype creation) + entity.add_component(C_TestA.new()) + var count_after_add_a = signal_count[0] + assert_int(count_after_add_a).is_greater(initial_count) + + entity.add_component(C_TestB.new()) + var count_after_add_b = signal_count[0] + assert_int(count_after_add_b).is_greater(count_after_add_a) + + entity.remove_component(C_TestA) + var count_after_remove_a = signal_count[0] + assert_int(count_after_remove_a).is_greater(count_after_add_b) + + entity.remove_component(C_TestB) + var count_after_remove_b = signal_count[0] + assert_int(count_after_remove_b).is_greater(count_after_remove_a) + +## Test performance: verify cache actually provides speedup when valid +func test_cache_performance_benefit(): + # Create many entities for meaningful performance test + var entities = [] + for i in range(500): + var entity = Entity.new() + if i % 2 == 0: + entity.add_component(C_TestA.new()) + if i % 3 == 0: + entity.add_component(C_TestB.new()) + entities.append(entity) + world.add_entities(entities) + + var query = world.query.with_all([C_TestA, C_TestB]) + + # First execution - uncached + var time_start = Time.get_ticks_usec() + var result1 = query.execute() + var uncached_time = Time.get_ticks_usec() - time_start + + # Second execution - should use cache + time_start = Time.get_ticks_usec() + var result2 = query.execute() + var cached_time = Time.get_ticks_usec() - time_start + + # Results should be identical + assert_array(result1).is_equal(result2) + + # Cache should be significantly faster + assert_bool(cached_time < uncached_time).is_true() + print("Cache performance test - Uncached: %d us, Cached: %d us, Speedup: %.2fx" % + [uncached_time, cached_time, float(uncached_time) / max(cached_time, 1)]) + +## Test that world cache clearing works correctly +func test_manual_cache_clearing(): + var entity = Entity.new() + entity.add_component(C_TestA.new()) + world.add_entity(entity) + + var query = world.query.with_all([C_TestA]) + var result1 = query.execute() # Cache the result + + # Manually clear cache (now using archetype cache) + world._query_archetype_cache.clear() + + # Should not affect correctness + var result2 = query.execute() + assert_array(result1).is_equal(result2) + +## =============================== +## RELATIONSHIP QUERY TESTS +## =============================== +## NOTE: Relationship changes do NOT invalidate cache (performance optimization) +## Instead, queries work because relationship_entity_index is updated in real-time +## These tests verify that queries still return correct results without cache invalidation + +## Test that relationship queries work correctly with real-time index updates +func test_relationship_addition_queries_correctly(): + var entity1 = Entity.new() + var entity2 = Entity.new() + var target_entity = Entity.new() + world.add_entities([entity1, entity2, target_entity]) + + # Create relationship type + var rel_component = C_TestA.new() + + # Add relationship to entity1 + entity1.add_relationship(Relationship.new(rel_component, target_entity)) + + # Execute query for entities with this relationship type + var query = world.query.with_relationship([Relationship.new(C_TestA.new(), ECS.wildcard)]) + var initial_result = query.execute() + assert_array(initial_result).has_size(1) + assert_bool(initial_result.has(entity1)).is_true() + + # Add same relationship type to entity2 mid-frame + entity2.add_relationship(Relationship.new(rel_component.duplicate(), target_entity)) + + # Execute same query again - should see fresh results + var updated_result = query.execute() + assert_array(updated_result).has_size(2) + assert_bool(updated_result.has(entity1)).is_true() + assert_bool(updated_result.has(entity2)).is_true() + +## Test that relationship removal queries work correctly with real-time index +func test_relationship_removal_queries_correctly(): + var entity1 = Entity.new() + var entity2 = Entity.new() + var target_entity = Entity.new() + world.add_entities([entity1, entity2, target_entity]) + + # Create relationships + var rel1 = Relationship.new(C_TestA.new(), target_entity) + var rel2 = Relationship.new(C_TestA.new(), target_entity) + entity1.add_relationship(rel1) + entity2.add_relationship(rel2) + + # Execute query and cache result + var query = world.query.with_relationship([Relationship.new(C_TestA.new(), ECS.wildcard)]) + var initial_result = query.execute() + assert_array(initial_result).has_size(2) + + # Remove relationship from entity1 mid-frame + entity1.remove_relationship(rel1) + + # Execute same query again - should see fresh results + var updated_result = query.execute() + assert_array(updated_result).has_size(1) + assert_bool(updated_result.has(entity2)).is_true() + assert_bool(updated_result.has(entity1)).is_false() + +## Test the exact bug scenario that was fixed +func test_relationship_removal_stale_cache_bug(): + # Simulate the exact scenario from the bug report + var entity1 = Entity.new() + var entity2 = Entity.new() + var interactable_entity = Entity.new() + world.add_entities([entity1, entity2, interactable_entity]) + + # Create relationships representing "can interact with anything" + var interact_rel1 = Relationship.new(C_TestA.new(), ECS.wildcard) # Using TestA as interaction relation + var interact_rel2 = Relationship.new(C_TestA.new(), ECS.wildcard) + entity1.add_relationship(interact_rel1) + entity2.add_relationship(interact_rel2) + + # First subsystem queries for entities that can interact + var interaction_query = world.query.with_relationship([Relationship.new(C_TestA.new(), ECS.wildcard)]) + var interaction_entities = interaction_query.execute() + assert_array(interaction_entities).has_size(2) + + # Simulate first entity processing: removes its interaction capability + assert_bool(interaction_entities.has(entity1)).is_true() + var first_entity = interaction_entities[0] # Could be entity1 or entity2 + + # Remove relationship (simulating "used up" interaction) + if first_entity == entity1: + first_entity.remove_relationship(interact_rel1) + else: + first_entity.remove_relationship(interact_rel2) + + # Second subsystem queries again in same frame - should NOT see the removed entity + var second_query_result = interaction_query.execute() + assert_array(second_query_result).has_size(1) + assert_bool(second_query_result.has(first_entity)).is_false() + + # Verify the remaining entity still works + var remaining_entity = second_query_result[0] + assert_that(remaining_entity).is_not_null() + # assert_bool(remaining_entity.has_relationship_of_type(C_TestA)).is_true() + +## Test multiple relationship changes in same frame query correctly +func test_multiple_relationship_changes_query_correctly(): + var entity1 = Entity.new() + var entity2 = Entity.new() + var entity3 = Entity.new() + var target_entity = Entity.new() + world.add_entities([entity1, entity2, entity3, target_entity]) + + # Setup initial relationships + var rel1 = Relationship.new(C_TestA.new(), target_entity) + entity1.add_relationship(rel1) + + # Execute query and cache result + var query = world.query.with_relationship([Relationship.new(C_TestA.new(), ECS.wildcard)]) + var initial_result = query.execute() + assert_array(initial_result).has_size(1) + + # Make multiple relationship changes in same frame + var rel2 = Relationship.new(C_TestA.new(), target_entity) + var rel3 = Relationship.new(C_TestA.new(), target_entity) + entity2.add_relationship(rel2) # Add to entity2 + entity3.add_relationship(rel3) # Add to entity3 + entity1.remove_relationship(rel1) # Remove from entity1 + + # Execute query - should reflect all changes + var final_result = query.execute() + assert_array(final_result).has_size(2) + assert_bool(final_result.has(entity2)).is_true() + assert_bool(final_result.has(entity3)).is_true() + assert_bool(final_result.has(entity1)).is_false() + +## Test that relationship changes DO NOT invalidate cache (performance optimization) +func test_relationship_no_cache_invalidation(): + var signal_count = [0] + + # Connect to cache invalidation signal + world.cache_invalidated.connect(func(): signal_count[0] += 1) + + var entity = Entity.new() + var target_entity = Entity.new() + world.add_entities([entity, target_entity]) + + var initial_count = signal_count[0] + + # IMPORTANT: Relationship changes should NOT emit cache_invalidated signal + # This is a performance optimization - relationships use relationship_entity_index + # which is updated in real-time, so cache invalidation is unnecessary + + var rel1 = Relationship.new(C_TestA.new(), target_entity) + entity.add_relationship(rel1) + assert_int(signal_count[0]).is_equal(initial_count) # No invalidation! + + var rel2 = Relationship.new(C_TestB.new(), target_entity) + entity.add_relationship(rel2) + assert_int(signal_count[0]).is_equal(initial_count) # No invalidation! + + entity.remove_relationship(rel1) + assert_int(signal_count[0]).is_equal(initial_count) # No invalidation! + + entity.remove_relationship(rel2) + assert_int(signal_count[0]).is_equal(initial_count) # No invalidation! + +## Test mixed component and relationship cache invalidation +func test_mixed_component_relationship_cache_invalidation(): + var entity1 = Entity.new() + var entity2 = Entity.new() + var target_entity = Entity.new() + world.add_entities([entity1, entity2, target_entity]) + + # Setup entity1 with component and relationship + entity1.add_component(C_TestA.new()) + entity1.add_relationship(Relationship.new(C_TestB.new(), target_entity)) + + # Complex query: has component AND relationship + var component_query = world.query.with_all([C_TestA]) + var relationship_query = world.query.with_relationship([Relationship.new(C_TestB.new(), ECS.wildcard)]) + + # Cache both queries + var comp_result1 = component_query.execute() + var rel_result1 = relationship_query.execute() + assert_array(comp_result1).has_size(1) + assert_array(rel_result1).has_size(1) + + # Add component to entity2 - should invalidate component query only + entity2.add_component(C_TestA.new()) + + var comp_result2 = component_query.execute() + var rel_result2 = relationship_query.execute() + assert_array(comp_result2).has_size(2) # Component query sees change + assert_array(rel_result2).has_size(1) # Relationship query unchanged + + # Add relationship to entity2 - should invalidate relationship query + entity2.add_relationship(Relationship.new(C_TestB.new(), target_entity)) + + var comp_result3 = component_query.execute() + var rel_result3 = relationship_query.execute() + assert_array(comp_result3).has_size(2) # Component query unchanged + assert_array(rel_result3).has_size(2) # Relationship query sees change diff --git a/addons/gecs/tests/core/test_world_cache_invalidation.gd.uid b/addons/gecs/tests/core/test_world_cache_invalidation.gd.uid new file mode 100644 index 0000000..234ed0b --- /dev/null +++ b/addons/gecs/tests/core/test_world_cache_invalidation.gd.uid @@ -0,0 +1 @@ +uid://cn47km7u0kbu6 diff --git a/addons/gecs/tests/core/test_world_serialization.gd b/addons/gecs/tests/core/test_world_serialization.gd new file mode 100644 index 0000000..c82bfa4 --- /dev/null +++ b/addons/gecs/tests/core/test_world_serialization.gd @@ -0,0 +1,645 @@ +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + +func after_test(): + if world: + world.purge(false) + # Clean up any test files + _cleanup_test_files() + +func _cleanup_test_files(): + # Skip cleanup to allow inspection of .tres files in reports directory + return + +func test_basic_entity_serialization(): + # Create entity with basic components + var entity = Entity.new() + entity.name = "TestEntity" + entity.add_component(C_SerializationTest.new(100, 9.99, "serialized", true, Vector2(3.0, 4.0), Vector3(5.0, 6.0, 7.0), Color.GREEN)) + entity.add_component(C_Persistent.new("Hero", 10, 85.5, Vector2(50.0, 100.0), ["shield", "bow"])) + + world.add_entity(entity) + + # Serialize the entity + var query = world.query.with_all([C_SerializationTest]) + var serialized_data = ECS.serialize(query) + + # Validate serialized structure + assert_that(serialized_data).is_not_null() + assert_that(serialized_data.version).is_equal("0.2") + assert_that(serialized_data.entities).has_size(1) + + var entity_data = serialized_data.entities[0] + assert_that(entity_data.entity_name).is_equal("TestEntity") + assert_that(entity_data.components).has_size(2) + + # Find components by type + var serialization_component: C_SerializationTest + var persistent_component: C_Persistent + + for component in entity_data.components: + if component is C_SerializationTest: + serialization_component = component + elif component is C_Persistent: + persistent_component = component + + # Validate component data + assert_that(serialization_component).is_not_null() + assert_that(serialization_component.int_value).is_equal(100) + assert_that(serialization_component.float_value).is_equal(9.99) + assert_that(serialization_component.string_value).is_equal("serialized") + assert_that(serialization_component.bool_value).is_equal(true) + + assert_that(persistent_component).is_not_null() + +func test_complex_data_serialization(): + # Create entity with complex data types + var entity = E_ComplexSerializationTest.new() + entity.name = "ComplexEntity" + + world.add_entity(entity) + + # Serialize the entity + var query = world.query.with_all([C_ComplexSerializationTest]) + var serialized_data = ECS.serialize(query) + + # Validate complex data preservation + var entity_data = serialized_data.entities[0] + var complex_component: C_ComplexSerializationTest + + # Find the complex component + for component in entity_data.components: + if component is C_ComplexSerializationTest: + complex_component = component + break + + assert_that(complex_component).is_not_null() + assert_that(complex_component.array_value).is_equal([10, 20, 30]) + assert_that(complex_component.string_array).is_equal(["alpha", "beta", "gamma"]) + assert_that(complex_component.dict_value).is_equal({"hp": 100, "mp": 50, "items": 3}) + assert_that(complex_component.empty_array).is_equal([]) + assert_that(complex_component.empty_dict).is_equal({}) + +func test_serialization_deserialization_round_trip(): + # Create multiple entities with different components + var entity1 = E_SerializationTest.new() + entity1.name = "Entity1" + + var entity2 = E_ComplexSerializationTest.new() + entity2.name = "Entity2" + + world.add_entities([entity1, entity2]) + + # Serialize entities with C_SerializationTest component + var query = world.query.with_all([C_SerializationTest]) + var serialized_data = ECS.serialize(query) + + # Save to file using resource system + var file_path = "res://reports/test_round_trip.tres" + ECS.save(serialized_data, file_path) + + # Deserialize from file + var deserialized_entities = ECS.deserialize(file_path) + + # Validate deserialized entities + assert_that(deserialized_entities).has_size(2) + + # Check first entity + var des_entity1 = deserialized_entities[0] + assert_that(des_entity1.name).is_equal("Entity1") + assert_that(des_entity1.has_component(C_SerializationTest)).is_true() + assert_that(des_entity1.has_component(C_Persistent)).is_true() + + var des_comp1 = des_entity1.get_component(C_SerializationTest) + assert_that(des_comp1.int_value).is_equal(42) + assert_that(des_comp1.string_value).is_equal("test_string") + + var des_persistent1 = des_entity1.get_component(C_Persistent) + assert_that(des_persistent1.player_name).is_equal("TestPlayer") + assert_that(des_persistent1.level).is_equal(5) + assert_that(des_persistent1.health).is_equal(75.0) + + # Check second entity + var des_entity2 = deserialized_entities[1] + assert_that(des_entity2.name).is_equal("Entity2") + assert_that(des_entity2.has_component(C_ComplexSerializationTest)).is_true() + assert_that(des_entity2.has_component(C_SerializationTest)).is_true() + + var des_complex = des_entity2.get_component(C_ComplexSerializationTest) + assert_that(des_complex.array_value).is_equal([10, 20, 30]) + assert_that(des_complex.dict_value).is_equal({"hp": 100, "mp": 50, "items": 3}) + + # Use auto_free for proper cleanup + for entity in deserialized_entities: + auto_free(entity) + + +func test_empty_query_serialization(): + # Add entities but query for non-existent component + var entity = Entity.new() + entity.add_component(C_SerializationTest.new()) + world.add_entity(entity) + + # Query for component that doesn't exist + var query = world.query.with_all([C_ComplexSerializationTest]) + var serialized_data = ECS.serialize(query) + + # Should return empty entities array + assert_that(serialized_data.entities).has_size(0) + +func test_deserialize_nonexistent_file(): + var entities = ECS.deserialize("res://reports/nonexistent_file.tres") + assert_that(entities).has_size(0) + +func test_deserialize_invalid_resource(): + # Create file with invalid resource content + var file_path = "res://reports/test_invalid.tres" + var file = FileAccess.open(file_path, FileAccess.WRITE) + file.store_string("invalid resource content") + file.close() + + var entities = ECS.deserialize(file_path) + assert_that(entities).has_size(0) + +func test_deserialize_empty_resource(): + # Create a GecsData resource with empty entities array + var empty_data = GecsData.new([]) + var file_path = "res://reports/test_empty_resource.tres" + ECS.save(empty_data, file_path) + + var entities = ECS.deserialize(file_path) + assert_that(entities).has_size(0) + +func test_multiple_entities_with_persistent_components(): + # Create multiple entities with persistent components + var entities_to_create = [] + for i in range(5): + var entity = Entity.new() + entity.name = "PersistentEntity_" + str(i) + entity.add_component(C_Persistent.new("Player" + str(i), i + 1, 100.0 - i * 5, Vector2(i * 10, i * 20), ["item" + str(i)])) + entities_to_create.append(entity) + + world.add_entities(entities_to_create) + + # Serialize all persistent entities + var query = world.query.with_all([C_Persistent]) + var serialized_data = ECS.serialize(query) + + # Save and reload + var file_path = "res://reports/test_multiple_persistent.tres" + ECS.save(serialized_data, file_path) + + var deserialized_entities = ECS.deserialize(file_path) + assert_that(deserialized_entities).has_size(5) + + # Validate each entity + for i in range(5): + var entity = deserialized_entities[i] + assert_that(entity.name).is_equal("PersistentEntity_" + str(i)) + assert_that(entity.has_component(C_Persistent)).is_true() + + var persistent_comp = entity.get_component(C_Persistent) + assert_that(persistent_comp.player_name).is_equal("Player" + str(i)) + assert_that(persistent_comp.level).is_equal(i + 1) + assert_that(persistent_comp.health).is_equal(100.0 - i * 5) + assert_that(persistent_comp.position).is_equal(Vector2(i * 10, i * 20)) + assert_that(persistent_comp.inventory).is_equal(["item" + str(i)]) + + # Use auto_free for cleanup + for entity in deserialized_entities: + auto_free(entity) + +func test_performance_serialization_large_dataset(): + # Create many entities for performance testing + var start_time = Time.get_ticks_msec() + var entities_to_create = [] + + for i in range(100): + var entity = Entity.new() + entity.name = "PerfEntity_" + str(i) + entity.add_component(C_SerializationTest.new(i, i * 1.1, "entity_" + str(i), i % 2 == 0)) + entity.add_component(C_Persistent.new("Player" + str(i), i, 100.0, Vector2(i, i))) + entities_to_create.append(entity) + + world.add_entities(entities_to_create) + + var creation_time = Time.get_ticks_msec() - start_time + + # Serialize all entities + var serialize_start = Time.get_ticks_msec() + var query = world.query.with_all([C_SerializationTest]) + var serialized_data = ECS.serialize(query) + var serialize_time = Time.get_ticks_msec() - serialize_start + + # Validate serialization completed + assert_that(serialized_data.entities).has_size(100) + + # Save to file + var save_start = Time.get_ticks_msec() + var file_path = "res://reports/test_performance.tres" + ECS.save(serialized_data, file_path) + var save_time = Time.get_ticks_msec() - save_start + + # Deserialize + var deserialize_start = Time.get_ticks_msec() + var deserialized_entities = ECS.deserialize(file_path) + var deserialize_time = Time.get_ticks_msec() - deserialize_start + + # Validate deserialization + assert_that(deserialized_entities).has_size(100) + + # Performance assertions (should complete in reasonable time) + print("Performance Test Results:") + print(" Entity Creation: ", creation_time, "ms") + print(" Serialization: ", serialize_time, "ms") + print(" File Save: ", save_time, "ms") + print(" Deserialization: ", deserialize_time, "ms") + + # These are reasonable expectations for 100 entities + assert_that(serialize_time).is_less(1000) # < 1 second + assert_that(deserialize_time).is_less(1000) # < 1 second + + # Use auto_free for cleanup + for entity in deserialized_entities: + auto_free(entity) + +func test_binary_format_and_auto_detection(): + # Create test entity with various component types + var entity = Entity.new() + entity.name = "BinaryTestEntity" + entity.add_component(C_SerializationTest.new(777, 3.14159, "binary_test", true, Vector2(10.0, 20.0), Vector3(1.0, 2.0, 3.0), Color.RED)) + entity.add_component(C_Persistent.new("BinaryPlayer", 99, 88.8, Vector2(100.0, 200.0), ["sword", "shield", "potion"])) + + world.add_entity(entity) + + # Serialize the entity + var query = world.query.with_all([C_SerializationTest]) + var serialized_data = ECS.serialize(query) + + # Save in both formats + var text_path = "res://reports/test_binary_format.tres" + var binary_test_path = "res://reports/test_binary_format.tres" # Same path for both + + # Save as text format + ECS.save(serialized_data, text_path, false) + + # Save as binary format (should create .res file) + ECS.save(serialized_data, binary_test_path, true) + + # Verify both files exist + assert_that(ResourceLoader.exists("res://reports/test_binary_format.tres")).is_true() + assert_that(ResourceLoader.exists("res://reports/test_binary_format.res")).is_true() + + # Test auto-detection: should load binary (.res) first + print("Deserializing from: ", binary_test_path) + print("Binary file exists: ", ResourceLoader.exists("res://reports/test_binary_format.res")) + print("Text file exists: ", ResourceLoader.exists("res://reports/test_binary_format.tres")) + + var entities_auto = ECS.deserialize(binary_test_path) + print("Deserialized entities count: ", entities_auto.size()) + assert_that(entities_auto).has_size(1) + + # Verify loaded data is correct + var loaded_entity = entities_auto[0] + assert_that(loaded_entity.name).is_equal("BinaryTestEntity") + + var loaded_serialization = loaded_entity.get_component(C_SerializationTest) + assert_that(loaded_serialization.int_value).is_equal(777) + assert_that(loaded_serialization.string_value).is_equal("binary_test") + + var loaded_persistent = loaded_entity.get_component(C_Persistent) + assert_that(loaded_persistent.player_name).is_equal("BinaryPlayer") + assert_that(loaded_persistent.level).is_equal(99) + assert_that(loaded_persistent.inventory).is_equal(["sword", "shield", "potion"]) + + # Use auto_free for cleanup + for _entity in entities_auto: + auto_free(_entity) + + print("Binary format test completed successfully!") + + # Compare file sizes (for information) + var text_file = FileAccess.open("res://reports/test_binary_format.tres", FileAccess.READ) + var binary_file = FileAccess.open("res://reports/test_binary_format.res", FileAccess.READ) + + if text_file and binary_file: + var text_size = text_file.get_length() + var binary_size = binary_file.get_length() + text_file.close() + binary_file.close() + + print("File size comparison:") + print(" Text (.tres): ", text_size, " bytes") + print(" Binary (.res): ", binary_size, " bytes") + print(" Compression: ", "%.1f" % ((1.0 - float(binary_size) / float(text_size)) * 100), "% smaller") + +func test_prefab_entity_serialization(): + # Load a prefab entity from scene + var packed_scene = load("res://addons/gecs/tests/entities/e_prefab_test.tscn") as PackedScene + var prefab_entity = packed_scene.instantiate() as Entity + prefab_entity.name = "LoadedPrefab" + + world.add_entity(prefab_entity) + # Add C_Test_C back in + prefab_entity.add_component(C_TestC.new(99)) + + # Get component values before serialization for comparison + var original_test_a = prefab_entity.get_component(C_TestA) + var original_test_b = prefab_entity.get_component(C_TestB) + var original_test_c = prefab_entity.get_component(C_TestC) + + + assert_that(original_test_a).is_not_null() + assert_that(original_test_b).is_not_null() + assert_that(original_test_c).is_not_null() + + + var original_a_value = original_test_a.value + var original_b_value = original_test_b.value + var original_c_value = original_test_c.value + + + # Serialize entities with test components + var query = world.query.with_all([C_TestA]) + var serialized_data = ECS.serialize(query) + + # Validate the prefab was serialized with scene path + assert_that(serialized_data.entities).has_size(1) + var entity_data = serialized_data.entities[0] + assert_that(entity_data.entity_name).is_equal("LoadedPrefab") + assert_that(entity_data.scene_path).is_equal("res://addons/gecs/tests/entities/e_prefab_test.tscn") + assert_that(entity_data.components).has_size(3) # Should have C_TestA, C_TestB, C_TestC + + # Save and reload + var file_path = "res://reports/test_prefab_serialization.tres" + ECS.save(serialized_data, file_path) + + # Remove original entity from world + world.remove_entity(prefab_entity) + + # Deserialize and validate prefab is properly reconstructed + var deserialized_entities = ECS.deserialize(file_path) + assert_that(deserialized_entities).has_size(1) + + var des_entity = deserialized_entities[0] + assert_that(des_entity.name).is_equal("LoadedPrefab") + assert_that(des_entity.has_component(C_TestA)).is_true() + assert_that(des_entity.has_component(C_TestB)).is_true() + assert_that(des_entity.has_component(C_TestC)).is_true() + + # Validate component values are preserved + var test_a = des_entity.get_component(C_TestA) + var test_b = des_entity.get_component(C_TestB) + var test_c = des_entity.get_component(C_TestC) + + assert_that(test_a.value).is_equal(original_a_value) + assert_that(test_b.value).is_equal(original_b_value) + + # NOW THE CRITICAL TEST: Add deserialized entity back to world + world.add_entity(des_entity) + + # Verify components still work after being added to world + assert_that(des_entity.has_component(C_TestA)).is_true() + assert_that(des_entity.has_component(C_TestB)).is_true() + assert_that(des_entity.has_component(C_TestC)).is_true() + + # Verify we can still get components after world operations + var world_test_a = des_entity.get_component(C_TestA) + var world_test_b = des_entity.get_component(C_TestB) + var world_test_c = des_entity.get_component(C_TestC) + + assert_that(world_test_a).is_not_null() + assert_that(world_test_b).is_not_null() + assert_that(world_test_c).is_not_null() + + # Verify values are still correct after world operations + assert_that(world_test_a.value).is_equal(original_a_value) + assert_that(world_test_b.value).is_equal(original_b_value) + + # Test that queries still work with the deserialized entity + var world_query = world.query.with_all([C_TestA]) + var found_entities = world_query.execute() + assert_that(found_entities).has_size(1) + assert_that(found_entities[0]).is_equal(des_entity) + + print("Prefab entity serialization with world round-trip test completed successfully!") + + +func test_serialize_config_include_all_components(): + # Create entity with multiple components + var entity = Entity.new() + entity.name = "ConfigTestEntity" + entity.add_component(C_SerializationTest.new(100, 5.5, "test", true)) + entity.add_component(C_Persistent.new("Player", 10, 75.0, Vector2(10, 20), ["item1"])) + + world.add_entity(entity) + + # Test default config (include all) + var config = GECSSerializeConfig.new() + assert_that(config.include_all_components).is_true() + + var query = world.query.with_all([C_SerializationTest]) + var serialized_data = ECS.serialize(query, config) + + # Should include both components + assert_that(serialized_data.entities).has_size(1) + var entity_data = serialized_data.entities[0] + assert_that(entity_data.components).has_size(2) + + +func test_serialize_config_specific_components_only(): + # Create entity with multiple components + var entity = Entity.new() + entity.name = "SpecificConfigTestEntity" + entity.add_component(C_SerializationTest.new(200, 10.5, "specific", false)) + entity.add_component(C_Persistent.new("SpecificPlayer", 20, 90.0, Vector2(30, 40), ["item2"])) + + world.add_entity(entity) + + # Configure to include only C_SerializationTest + var config = GECSSerializeConfig.new() + config.include_all_components = false + config.components = [C_SerializationTest] + + var query = world.query.with_all([C_SerializationTest]) + var serialized_data = ECS.serialize(query, config) + + # Should only include C_SerializationTest component + assert_that(serialized_data.entities).has_size(1) + var entity_data = serialized_data.entities[0] + assert_that(entity_data.components).has_size(1) + + # Verify it's the correct component type + var component = entity_data.components[0] + assert_that(component is C_SerializationTest).is_true() + assert_that(component.int_value).is_equal(200) + + +func test_serialize_config_exclude_relationships(): + # Create entities with relationships + var parent = Entity.new() + parent.name = "ParentEntity" + parent.add_component(C_SerializationTest.new(300, 15.5, "parent", true)) + + var child = Entity.new() + child.name = "ChildEntity" + child.add_component(C_SerializationTest.new(400, 20.5, "child", false)) + + world.add_entities([parent, child]) + + # Add relationship + var relationship = Relationship.new(C_TestA.new(), parent) + child.add_relationship(relationship) + + # Configure to exclude relationships + var config = GECSSerializeConfig.new() + config.include_relationships = false + + var query = world.query.with_all([C_SerializationTest]) + var serialized_data = ECS.serialize(query, config) + + # Should have entities but no relationships + assert_that(serialized_data.entities).has_size(2) + for entity_data in serialized_data.entities: + assert_that(entity_data.relationships).has_size(0) + + +func test_serialize_config_exclude_related_entities(): + # Create entities with relationships + var parent = Entity.new() + parent.name = "ParentForExclusion" + parent.add_component(C_SerializationTest.new(500, 25.5, "parent_exclude", true)) + + var child = Entity.new() + child.name = "ChildForExclusion" + child.add_component(C_Persistent.new("ChildPlayer", 30, 80.0, Vector2(50, 60), ["child_item"])) + + world.add_entities([parent, child]) + + # Add relationship from parent to child + var relationship = Relationship.new(C_TestA.new(), child) + parent.add_relationship(relationship) + + # Configure to exclude related entities + var config = GECSSerializeConfig.new() + config.include_related_entities = false + + # Query only for parent (which has C_SerializationTest) + var query = world.query.with_all([C_SerializationTest]) + var serialized_data = ECS.serialize(query, config) + + # Should only include the parent, not the related child + assert_that(serialized_data.entities).has_size(1) + var entity_data = serialized_data.entities[0] + assert_that(entity_data.entity_name).is_equal("ParentForExclusion") + + +func test_world_default_serialize_config(): + # Test that world has a default config + assert_that(world.default_serialize_config).is_not_null() + assert_that(world.default_serialize_config.include_all_components).is_true() + assert_that(world.default_serialize_config.include_relationships).is_true() + assert_that(world.default_serialize_config.include_related_entities).is_true() + + # Modify world default to exclude relationships and related entities + world.default_serialize_config.include_relationships = false + world.default_serialize_config.include_related_entities = false + + # Create entity with relationship + var parent = Entity.new() + parent.name = "WorldConfigParent" + parent.add_component(C_SerializationTest.new(600, 30.5, "world_config", true)) + + var child = Entity.new() + child.name = "WorldConfigChild" + child.add_component(C_Persistent.new("WorldChild", 40, 70.0, Vector2(70, 80), ["world_item"])) + + world.add_entities([parent, child]) + + var relationship = Relationship.new(C_TestA.new(), child) + parent.add_relationship(relationship) + + # Serialize without explicit config (should use world default) + var query = world.query.with_all([C_SerializationTest]) + var serialized_data = ECS.serialize(query) + + # Should exclude relationships and related entities due to world config + assert_that(serialized_data.entities).has_size(1) # Only parent, no related entities included + var entity_data = serialized_data.entities[0] + assert_that(entity_data.entity_name).is_equal("WorldConfigParent") + assert_that(entity_data.relationships).has_size(0) # No relationships included + + +func test_entity_level_serialize_config_override(): + # Create entity with custom serialize config + var entity = Entity.new() + entity.name = "EntityConfigOverride" + entity.add_component(C_SerializationTest.new(700, 35.5, "entity_override", false)) + entity.add_component(C_Persistent.new("EntityPlayer", 50, 60.0, Vector2(90, 100), ["entity_item"])) + + # Set entity-specific config to include only C_Persistent + entity.serialize_config = GECSSerializeConfig.new() + entity.serialize_config.include_all_components = false + entity.serialize_config.components = [C_Persistent] + + world.add_entity(entity) + + # Serialize without explicit config (should use entity override) + var query = world.query.with_all([C_SerializationTest]) + var serialized_data = ECS.serialize(query) + + # Should only include C_Persistent component due to entity config + assert_that(serialized_data.entities).has_size(1) + var entity_data = serialized_data.entities[0] + assert_that(entity_data.components).has_size(1) + + var component = entity_data.components[0] + assert_that(component is C_Persistent).is_true() + + +func test_config_hierarchy_priority(): + # Set world default to exclude relationships + world.default_serialize_config.include_relationships = false + + # Create entity with entity-level config that includes relationships + var entity = Entity.new() + entity.name = "HierarchyTestEntity" + entity.add_component(C_SerializationTest.new(800, 40.5, "hierarchy", true)) + entity.serialize_config = GECSSerializeConfig.new() + entity.serialize_config.include_relationships = true + + world.add_entity(entity) + + # Add relationship + var other_entity = Entity.new() + other_entity.name = "OtherEntity" + other_entity.add_component(C_Persistent.new("Other", 60, 50.0, Vector2(110, 120), ["other_item"])) + world.add_entity(other_entity) + + var relationship = Relationship.new(C_TestA.new(), other_entity) + entity.add_relationship(relationship) + + # Test 1: No explicit config should use entity config (include relationships) + var query = world.query.with_all([C_SerializationTest]) + var serialized_data = ECS.serialize(query) + + var entity_data = serialized_data.entities[0] + assert_that(entity_data.relationships).has_size(1) # Entity config overrides world default + + # Test 2: Explicit config should override everything + var explicit_config = GECSSerializeConfig.new() + explicit_config.include_relationships = false + explicit_config.include_related_entities = false + + var serialized_data_explicit = ECS.serialize(query, explicit_config) + assert_that(serialized_data_explicit.entities).has_size(1) # No related entities + var entity_data_explicit = serialized_data_explicit.entities[0] + assert_that(entity_data_explicit.relationships).has_size(0) # Explicit config overrides entity config diff --git a/addons/gecs/tests/core/test_world_serialization.gd.uid b/addons/gecs/tests/core/test_world_serialization.gd.uid new file mode 100644 index 0000000..3881509 --- /dev/null +++ b/addons/gecs/tests/core/test_world_serialization.gd.uid @@ -0,0 +1 @@ +uid://duykas5yc8gn3 diff --git a/addons/gecs/tests/core/tests_array_extensions.gd b/addons/gecs/tests/core/tests_array_extensions.gd new file mode 100644 index 0000000..2819fde --- /dev/null +++ b/addons/gecs/tests/core/tests_array_extensions.gd @@ -0,0 +1,51 @@ +extends GdUnitTestSuite + + +var testSystemA = TestASystem.new() +var testSystemB = TestBSystem.new() +var testSystemC = TestCSystem.new() +var testSystemD = TestDSystem.new() + + +func test_topological_sort(): + # Create a dictionary of systems by group + var systems_by_group = { + "Group1": + [ + testSystemD, + testSystemB, + testSystemC, + testSystemA, + ], + "Group2": + [ + testSystemB, + testSystemD, + testSystemA, + testSystemC, + ] + } + + var expected_sorted_systems = { + "Group1": + [ + testSystemA, + testSystemB, + testSystemC, + testSystemD, + ], + "Group2": + [ + testSystemA, + testSystemB, + testSystemC, + testSystemD, + ] + } + + # Sorts the dict in place + ArrayExtensions.topological_sort(systems_by_group) + + # Check if the systems are sorted correctly + for group in systems_by_group.keys(): + assert_array(systems_by_group[group]).is_equal(expected_sorted_systems[group]) diff --git a/addons/gecs/tests/core/tests_array_extensions.gd.uid b/addons/gecs/tests/core/tests_array_extensions.gd.uid new file mode 100644 index 0000000..b06008c --- /dev/null +++ b/addons/gecs/tests/core/tests_array_extensions.gd.uid @@ -0,0 +1 @@ +uid://bydpef6khpc53 diff --git a/addons/gecs/tests/debug/test_editor_debugger_tab_metrics.gd b/addons/gecs/tests/debug/test_editor_debugger_tab_metrics.gd new file mode 100644 index 0000000..b6d68b1 --- /dev/null +++ b/addons/gecs/tests/debug/test_editor_debugger_tab_metrics.gd @@ -0,0 +1,20 @@ +extends GdUnitTestSuite + +func test_system_metric_last_time_is_recorded() -> void: + var tab := preload("res://addons/gecs/debug/gecs_editor_debugger_tab.gd").new() + # Simulate three metric events for same system id + tab.system_metric(1, "TestSystem", 0.5) + tab.system_metric(1, "TestSystem", 0.25) + tab.system_metric(1, "TestSystem", 0.75) + var systems = tab.ecs_data.get("systems") + assert_object(systems).is_not_null() + var sys_entry = systems.get(1) + assert_object(sys_entry).is_not_null() + # last_time should match the last recorded (0.75) + assert_float(sys_entry["last_time"]).is_equal(0.75) + # metrics should also have last_time + var metrics = sys_entry["metrics"] + assert_object(metrics).is_not_null() + assert_float(metrics["last_time"]).is_equal(0.75) + # avg_time should be (0.5+0.25+0.75)/3 = 0.5 + assert_float(metrics["avg_time"]).is_equal(0.5) \ No newline at end of file diff --git a/addons/gecs/tests/debug/test_editor_debugger_tab_metrics.gd.uid b/addons/gecs/tests/debug/test_editor_debugger_tab_metrics.gd.uid new file mode 100644 index 0000000..c295656 --- /dev/null +++ b/addons/gecs/tests/debug/test_editor_debugger_tab_metrics.gd.uid @@ -0,0 +1 @@ +uid://bsxfshtmg8tfh diff --git a/addons/gecs/tests/entities/e_complex_serialization_test.gd b/addons/gecs/tests/entities/e_complex_serialization_test.gd new file mode 100644 index 0000000..a9eeba0 --- /dev/null +++ b/addons/gecs/tests/entities/e_complex_serialization_test.gd @@ -0,0 +1,15 @@ +class_name E_ComplexSerializationTest +extends Entity + + +func define_components() -> Array: + return [ + C_ComplexSerializationTest.new( + [10, 20, 30], + ["alpha", "beta", "gamma"], + {"hp": 100, "mp": 50, "items": 3}, + [], + {} + ), + C_SerializationTest.new(999, 2.718, "complex_entity", false, Vector2(5.0, 10.0), Vector3(1.0, 2.0, 3.0), Color.BLUE) + ] \ No newline at end of file diff --git a/addons/gecs/tests/entities/e_complex_serialization_test.gd.uid b/addons/gecs/tests/entities/e_complex_serialization_test.gd.uid new file mode 100644 index 0000000..803bc71 --- /dev/null +++ b/addons/gecs/tests/entities/e_complex_serialization_test.gd.uid @@ -0,0 +1 @@ +uid://dlq154oe8rmkg diff --git a/addons/gecs/tests/entities/e_gecs_food.gd b/addons/gecs/tests/entities/e_gecs_food.gd new file mode 100644 index 0000000..4ad38b0 --- /dev/null +++ b/addons/gecs/tests/entities/e_gecs_food.gd @@ -0,0 +1,2 @@ +class_name GecsFood +extends Entity diff --git a/addons/gecs/tests/entities/e_gecs_food.gd.uid b/addons/gecs/tests/entities/e_gecs_food.gd.uid new file mode 100644 index 0000000..58fa17a --- /dev/null +++ b/addons/gecs/tests/entities/e_gecs_food.gd.uid @@ -0,0 +1 @@ +uid://b58vonkhloaow diff --git a/addons/gecs/tests/entities/e_prefab_test.gd b/addons/gecs/tests/entities/e_prefab_test.gd new file mode 100644 index 0000000..3afe99f --- /dev/null +++ b/addons/gecs/tests/entities/e_prefab_test.gd @@ -0,0 +1,2 @@ +class_name PrefabTest +extends Entity diff --git a/addons/gecs/tests/entities/e_prefab_test.gd.uid b/addons/gecs/tests/entities/e_prefab_test.gd.uid new file mode 100644 index 0000000..6e57368 --- /dev/null +++ b/addons/gecs/tests/entities/e_prefab_test.gd.uid @@ -0,0 +1 @@ +uid://dmjuo67pvwh3d diff --git a/addons/gecs/tests/entities/e_prefab_test.tscn b/addons/gecs/tests/entities/e_prefab_test.tscn new file mode 100644 index 0000000..ed59a6b --- /dev/null +++ b/addons/gecs/tests/entities/e_prefab_test.tscn @@ -0,0 +1,250 @@ +[gd_scene load_steps=11 format=3 uid="uid://tpqdridb86dk"] + +[ext_resource type="Script" uid="uid://dmjuo67pvwh3d" path="res://addons/gecs/tests/entities/e_prefab_test.gd" id="1_7nbii"] +[ext_resource type="Script" uid="uid://b6k13gc2m4e5s" path="res://addons/gecs/ecs/component.gd" id="2_ju2ix"] +[ext_resource type="Script" uid="uid://5antadqj7v84" path="res://addons/gecs/tests/components/c_test_a.gd" id="3_8o2uq"] +[ext_resource type="Script" uid="uid://c6lvbdptfldrg" path="res://addons/gecs/tests/components/c_test_b.gd" id="4_t4812"] + +[sub_resource type="Resource" id="Resource_5ke2p"] +script = ExtResource("3_8o2uq") +value = 1 +metadata/_custom_type_script = "uid://5antadqj7v84" + +[sub_resource type="Resource" id="Resource_11y2y"] +script = ExtResource("4_t4812") +value = 2 +metadata/_custom_type_script = "uid://c6lvbdptfldrg" + +[sub_resource type="BoxMesh" id="BoxMesh_7nbii"] + +[sub_resource type="Animation" id="Animation_l1aji"] +length = 0.001 +tracks/0/type = "bezier" +tracks/0/imported = false +tracks/0/enabled = true +tracks/0/path = NodePath("MeshInstance3D:position:x") +tracks/0/interp = 1 +tracks/0/loop_wrap = true +tracks/0/keys = { +"handle_modes": PackedInt32Array(0), +"points": PackedFloat32Array(0, -0.25, 0, 0.25, 0), +"times": PackedFloat32Array(0) +} +tracks/1/type = "bezier" +tracks/1/imported = false +tracks/1/enabled = true +tracks/1/path = NodePath("MeshInstance3D:position:y") +tracks/1/interp = 1 +tracks/1/loop_wrap = true +tracks/1/keys = { +"handle_modes": PackedInt32Array(0), +"points": PackedFloat32Array(0, -0.25, 0, 0.25, 0), +"times": PackedFloat32Array(0) +} +tracks/2/type = "bezier" +tracks/2/imported = false +tracks/2/enabled = true +tracks/2/path = NodePath("MeshInstance3D:position:z") +tracks/2/interp = 1 +tracks/2/loop_wrap = true +tracks/2/keys = { +"handle_modes": PackedInt32Array(0), +"points": PackedFloat32Array(0, -0.25, 0, 0.25, 0), +"times": PackedFloat32Array(0) +} +tracks/3/type = "bezier" +tracks/3/imported = false +tracks/3/enabled = true +tracks/3/path = NodePath("MeshInstance3D2:position:x") +tracks/3/interp = 1 +tracks/3/loop_wrap = true +tracks/3/keys = { +"handle_modes": PackedInt32Array(0), +"points": PackedFloat32Array(-3.0227113, -0.25, 0, 0.25, 0), +"times": PackedFloat32Array(0) +} +tracks/4/type = "bezier" +tracks/4/imported = false +tracks/4/enabled = true +tracks/4/path = NodePath("MeshInstance3D2:position:y") +tracks/4/interp = 1 +tracks/4/loop_wrap = true +tracks/4/keys = { +"handle_modes": PackedInt32Array(0), +"points": PackedFloat32Array(0, -0.25, 0, 0.25, 0), +"times": PackedFloat32Array(0) +} +tracks/5/type = "bezier" +tracks/5/imported = false +tracks/5/enabled = true +tracks/5/path = NodePath("MeshInstance3D2:position:z") +tracks/5/interp = 1 +tracks/5/loop_wrap = true +tracks/5/keys = { +"handle_modes": PackedInt32Array(0), +"points": PackedFloat32Array(1.194534, -0.25, 0, 0.25, 0), +"times": PackedFloat32Array(0) +} +tracks/6/type = "bezier" +tracks/6/imported = false +tracks/6/enabled = true +tracks/6/path = NodePath("MeshInstance3D3:position:x") +tracks/6/interp = 1 +tracks/6/loop_wrap = true +tracks/6/keys = { +"handle_modes": PackedInt32Array(0), +"points": PackedFloat32Array(2.3212543, -0.25, 0, 0.25, 0), +"times": PackedFloat32Array(0) +} +tracks/7/type = "bezier" +tracks/7/imported = false +tracks/7/enabled = true +tracks/7/path = NodePath("MeshInstance3D3:position:y") +tracks/7/interp = 1 +tracks/7/loop_wrap = true +tracks/7/keys = { +"handle_modes": PackedInt32Array(0), +"points": PackedFloat32Array(0, -0.25, 0, 0.25, 0), +"times": PackedFloat32Array(0) +} +tracks/8/type = "bezier" +tracks/8/imported = false +tracks/8/enabled = true +tracks/8/path = NodePath("MeshInstance3D3:position:z") +tracks/8/interp = 1 +tracks/8/loop_wrap = true +tracks/8/keys = { +"handle_modes": PackedInt32Array(0), +"points": PackedFloat32Array(-3.3574667, -0.25, 0, 0.25, 0), +"times": PackedFloat32Array(0) +} + +[sub_resource type="Animation" id="Animation_7nbii"] +resource_name = "test" +loop_mode = 1 +tracks/0/type = "bezier" +tracks/0/imported = false +tracks/0/enabled = true +tracks/0/path = NodePath("MeshInstance3D:position:x") +tracks/0/interp = 1 +tracks/0/loop_wrap = true +tracks/0/keys = { +"handle_modes": PackedInt32Array(0, 2, 2), +"points": PackedFloat32Array(0, -0.25, 0, 0.25, 0, 0, -0.086666666, 0, 0, 0, 0.15021324, -0.07500001, -0.025035542, 0, 0), +"times": PackedFloat32Array(0, 0.52, 0.97) +} +tracks/1/type = "bezier" +tracks/1/imported = false +tracks/1/enabled = true +tracks/1/path = NodePath("MeshInstance3D:position:y") +tracks/1/interp = 1 +tracks/1/loop_wrap = true +tracks/1/keys = { +"handle_modes": PackedInt32Array(0, 2, 2), +"points": PackedFloat32Array(0, -0.25, 0, 0.25, 0, -2.424733, -0.086666666, 0.40412217, 0, 0, -0.0065529346, -0.07500001, -0.40303, 0, 0), +"times": PackedFloat32Array(0, 0.52, 0.97) +} +tracks/2/type = "bezier" +tracks/2/imported = false +tracks/2/enabled = true +tracks/2/path = NodePath("MeshInstance3D:position:z") +tracks/2/interp = 1 +tracks/2/loop_wrap = true +tracks/2/keys = { +"handle_modes": PackedInt32Array(0, 2, 2), +"points": PackedFloat32Array(0, -0.25, 0, 0.25, 0, 0, -0.086666666, 0, 0, 0, 1.1204721, -0.07500001, -0.18674536, 0, 0), +"times": PackedFloat32Array(0, 0.52, 0.97) +} +tracks/3/type = "bezier" +tracks/3/imported = false +tracks/3/enabled = true +tracks/3/path = NodePath("MeshInstance3D2:position:x") +tracks/3/interp = 1 +tracks/3/loop_wrap = true +tracks/3/keys = { +"handle_modes": PackedInt32Array(0, 2, 2), +"points": PackedFloat32Array(-3.0227113, -0.25, 0, 0.25, 0, -3.0227113, -0.086666666, 0, 0, 0, -2.872498, -0.07500001, -0.025035542, 0, 0), +"times": PackedFloat32Array(0, 0.52, 0.97) +} +tracks/4/type = "bezier" +tracks/4/imported = false +tracks/4/enabled = true +tracks/4/path = NodePath("MeshInstance3D2:position:y") +tracks/4/interp = 1 +tracks/4/loop_wrap = true +tracks/4/keys = { +"handle_modes": PackedInt32Array(0, 2, 2), +"points": PackedFloat32Array(0, -0.25, 0, 0.25, 0, -2.424733, -0.086666666, 0.40412217, 0, 0, -0.0065529346, -0.07500001, -0.40303, 0, 0), +"times": PackedFloat32Array(0, 0.52, 0.97) +} +tracks/5/type = "bezier" +tracks/5/imported = false +tracks/5/enabled = true +tracks/5/path = NodePath("MeshInstance3D2:position:z") +tracks/5/interp = 1 +tracks/5/loop_wrap = true +tracks/5/keys = { +"handle_modes": PackedInt32Array(0, 2, 2), +"points": PackedFloat32Array(1.194534, -0.25, 0, 0.25, 0, 1.194534, -0.086666666, 0, 0, 0, 2.315006, -0.07500001, -0.18674536, 0, 0), +"times": PackedFloat32Array(0, 0.52, 0.97) +} +tracks/6/type = "bezier" +tracks/6/imported = false +tracks/6/enabled = true +tracks/6/path = NodePath("MeshInstance3D3:position:x") +tracks/6/interp = 1 +tracks/6/loop_wrap = true +tracks/6/keys = { +"handle_modes": PackedInt32Array(0, 2, 2), +"points": PackedFloat32Array(2.3212543, -0.25, 0, 0.25, 0, 2.3212543, -0.086666666, 0, 0, 0, 2.4714675, -0.07500001, -0.025035542, 0, 0), +"times": PackedFloat32Array(0, 0.52, 0.97) +} +tracks/7/type = "bezier" +tracks/7/imported = false +tracks/7/enabled = true +tracks/7/path = NodePath("MeshInstance3D3:position:y") +tracks/7/interp = 1 +tracks/7/loop_wrap = true +tracks/7/keys = { +"handle_modes": PackedInt32Array(0, 2, 2), +"points": PackedFloat32Array(0, -0.25, 0, 0.25, 0, -2.424733, -0.086666666, 0.40412217, 0, 0, -0.0065529346, -0.07500001, -0.40303, 0, 0), +"times": PackedFloat32Array(0, 0.52, 0.97) +} +tracks/8/type = "bezier" +tracks/8/imported = false +tracks/8/enabled = true +tracks/8/path = NodePath("MeshInstance3D3:position:z") +tracks/8/interp = 1 +tracks/8/loop_wrap = true +tracks/8/keys = { +"handle_modes": PackedInt32Array(0, 2, 2), +"points": PackedFloat32Array(-3.3574667, -0.25, 0, 0.25, 0, -3.3574667, -0.086666666, 0, 0, 0, -2.2369947, -0.07500001, -0.18674533, 0, 0), +"times": PackedFloat32Array(0, 0.52, 0.97) +} + +[sub_resource type="AnimationLibrary" id="AnimationLibrary_twal5"] +_data = { +&"RESET": SubResource("Animation_l1aji"), +&"test": SubResource("Animation_7nbii") +} + +[node name="Node3D" type="Node3D"] +script = ExtResource("1_7nbii") +component_resources = Array[ExtResource("2_ju2ix")]([SubResource("Resource_5ke2p"), SubResource("Resource_11y2y")]) + +[node name="MeshInstance3D" type="MeshInstance3D" parent="."] +mesh = SubResource("BoxMesh_7nbii") + +[node name="MeshInstance3D2" type="MeshInstance3D" parent="."] +transform = Transform3D(0.30630922, 0.54854774, 0.777991, -0.8731008, 0.48753974, 0, -0.37930152, -0.67926455, 0.6282754, -3.0227113, 0, 1.194534) +mesh = SubResource("BoxMesh_7nbii") + +[node name="MeshInstance3D3" type="MeshInstance3D" parent="."] +transform = Transform3D(0.30630922, 0.54854774, 0.777991, -0.8731008, 0.48753974, 0, -0.37930152, -0.67926455, 0.6282754, 2.3212543, 0, -3.3574667) +mesh = SubResource("BoxMesh_7nbii") + +[node name="AnimationPlayer" type="AnimationPlayer" parent="."] +libraries = { +&"": SubResource("AnimationLibrary_twal5") +} +autoplay = "test" diff --git a/addons/gecs/tests/entities/e_serialization_test.gd b/addons/gecs/tests/entities/e_serialization_test.gd new file mode 100644 index 0000000..64d63ea --- /dev/null +++ b/addons/gecs/tests/entities/e_serialization_test.gd @@ -0,0 +1,9 @@ +class_name E_SerializationTest +extends Entity + + +func define_components() -> Array: + return [ + C_SerializationTest.new(), + C_Persistent.new("TestPlayer", 5, 75.0, Vector2(10.0, 20.0), ["sword", "potion"]) + ] \ No newline at end of file diff --git a/addons/gecs/tests/entities/e_serialization_test.gd.uid b/addons/gecs/tests/entities/e_serialization_test.gd.uid new file mode 100644 index 0000000..e7ef722 --- /dev/null +++ b/addons/gecs/tests/entities/e_serialization_test.gd.uid @@ -0,0 +1 @@ +uid://ccx2x5qv04wys diff --git a/addons/gecs/tests/entities/e_test_a.gd b/addons/gecs/tests/entities/e_test_a.gd new file mode 100644 index 0000000..964e06e --- /dev/null +++ b/addons/gecs/tests/entities/e_test_a.gd @@ -0,0 +1,2 @@ +class_name TestA +extends Entity diff --git a/addons/gecs/tests/entities/e_test_a.gd.uid b/addons/gecs/tests/entities/e_test_a.gd.uid new file mode 100644 index 0000000..f81005e --- /dev/null +++ b/addons/gecs/tests/entities/e_test_a.gd.uid @@ -0,0 +1 @@ +uid://ggn111owj1e4 diff --git a/addons/gecs/tests/entities/e_test_b.gd b/addons/gecs/tests/entities/e_test_b.gd new file mode 100644 index 0000000..3cf9741 --- /dev/null +++ b/addons/gecs/tests/entities/e_test_b.gd @@ -0,0 +1,2 @@ +class_name TestB +extends Entity diff --git a/addons/gecs/tests/entities/e_test_b.gd.uid b/addons/gecs/tests/entities/e_test_b.gd.uid new file mode 100644 index 0000000..057d132 --- /dev/null +++ b/addons/gecs/tests/entities/e_test_b.gd.uid @@ -0,0 +1 @@ +uid://b8yk2aa5xng8a diff --git a/addons/gecs/tests/entities/e_test_c.gd b/addons/gecs/tests/entities/e_test_c.gd new file mode 100644 index 0000000..3d742d7 --- /dev/null +++ b/addons/gecs/tests/entities/e_test_c.gd @@ -0,0 +1,2 @@ +class_name TestC +extends Entity diff --git a/addons/gecs/tests/entities/e_test_c.gd.uid b/addons/gecs/tests/entities/e_test_c.gd.uid new file mode 100644 index 0000000..1347080 --- /dev/null +++ b/addons/gecs/tests/entities/e_test_c.gd.uid @@ -0,0 +1 @@ +uid://dkd6h4yf03c2t diff --git a/addons/gecs/tests/entities/e_test_d.gd b/addons/gecs/tests/entities/e_test_d.gd new file mode 100644 index 0000000..1ca1a0a --- /dev/null +++ b/addons/gecs/tests/entities/e_test_d.gd @@ -0,0 +1,2 @@ +class_name TestD +extends Entity diff --git a/addons/gecs/tests/entities/e_test_d.gd.uid b/addons/gecs/tests/entities/e_test_d.gd.uid new file mode 100644 index 0000000..57250fe --- /dev/null +++ b/addons/gecs/tests/entities/e_test_d.gd.uid @@ -0,0 +1 @@ +uid://dpdk51tkdnj8r diff --git a/addons/gecs/tests/performance/perf_helpers.gd b/addons/gecs/tests/performance/perf_helpers.gd new file mode 100644 index 0000000..62e0075 --- /dev/null +++ b/addons/gecs/tests/performance/perf_helpers.gd @@ -0,0 +1,56 @@ +## Simple performance timing helpers for GECS +## Records results to JSONL files (one JSON per line, one file per test) +class_name PerfHelpers + + +## Time a callable and return milliseconds +static func time_it(callable: Callable) -> float: + var start_time = Time.get_ticks_usec() + callable.call() + var end_time = Time.get_ticks_usec() + return (end_time - start_time) / 1000.0 # Return milliseconds + + +## Record performance result to test-specific JSONL file +static func record_result(test_name: String, scale: int, time_ms: float) -> void: + var result = { + "timestamp": Time.get_datetime_string_from_system(), + "test": test_name, + "scale": scale, + "time_ms": time_ms, + "godot_version": Engine.get_version_info().string + } + + # Ensure perf directory exists + var dir = DirAccess.open("res://") + if dir: + if not dir.dir_exists("reports"): + dir.make_dir("reports") + if not dir.dir_exists("reports/perf"): + dir.make_dir("reports/perf") + + # Append to test-specific JSONL file (one JSON per line) + var filepath = "res://reports/perf/%s.jsonl" % test_name + # Check if file exists, if not create it with WRITE, otherwise open with READ_WRITE + var file_exists = FileAccess.file_exists(filepath) + var file = FileAccess.open(filepath, FileAccess.READ_WRITE if file_exists else FileAccess.WRITE) + + if file: + if file_exists: + file.seek_end() + file.store_line(JSON.stringify(result)) + file.close() + else: + push_error("Failed to open performance log file: %s (Error: %s)" % [filepath, error_string(FileAccess.get_open_error())]) + + # Print result for console visibility + prints("📊 %s (scale=%d): %.2f ms" % [test_name, scale, time_ms]) + + +## Optional: Assert performance threshold (simple version) +static func assert_threshold(time_ms: float, max_ms: float, message: String = "") -> void: + if time_ms > max_ms: + var error = "Performance threshold exceeded: %.2f ms > %.2f ms" % [time_ms, max_ms] + if not message.is_empty(): + error = "%s - %s" % [message, error] + assert(false, error) diff --git a/addons/gecs/tests/performance/perf_helpers.gd.uid b/addons/gecs/tests/performance/perf_helpers.gd.uid new file mode 100644 index 0000000..bf318b4 --- /dev/null +++ b/addons/gecs/tests/performance/perf_helpers.gd.uid @@ -0,0 +1 @@ +uid://bw7545nfp8er2 diff --git a/addons/gecs/tests/performance/performance_regression_detector.gd.uid b/addons/gecs/tests/performance/performance_regression_detector.gd.uid new file mode 100644 index 0000000..de495c9 --- /dev/null +++ b/addons/gecs/tests/performance/performance_regression_detector.gd.uid @@ -0,0 +1 @@ +uid://5hhcxik6cv30 diff --git a/addons/gecs/tests/performance/performance_test_arrays.gd.uid b/addons/gecs/tests/performance/performance_test_arrays.gd.uid new file mode 100644 index 0000000..5d19639 --- /dev/null +++ b/addons/gecs/tests/performance/performance_test_arrays.gd.uid @@ -0,0 +1 @@ +uid://cfa7qhlpk01qk diff --git a/addons/gecs/tests/performance/performance_test_base.gd.uid b/addons/gecs/tests/performance/performance_test_base.gd.uid new file mode 100644 index 0000000..71d9ac3 --- /dev/null +++ b/addons/gecs/tests/performance/performance_test_base.gd.uid @@ -0,0 +1 @@ +uid://p46sqv2vhhyj diff --git a/addons/gecs/tests/performance/performance_test_components.gd.uid b/addons/gecs/tests/performance/performance_test_components.gd.uid new file mode 100644 index 0000000..4aa24cb --- /dev/null +++ b/addons/gecs/tests/performance/performance_test_components.gd.uid @@ -0,0 +1 @@ +uid://bxoj2kyydasxw diff --git a/addons/gecs/tests/performance/performance_test_entities.gd.uid b/addons/gecs/tests/performance/performance_test_entities.gd.uid new file mode 100644 index 0000000..412c0f5 --- /dev/null +++ b/addons/gecs/tests/performance/performance_test_entities.gd.uid @@ -0,0 +1 @@ +uid://2l6fp4kfjsc0 diff --git a/addons/gecs/tests/performance/performance_test_integration.gd.uid b/addons/gecs/tests/performance/performance_test_integration.gd.uid new file mode 100644 index 0000000..5b7d076 --- /dev/null +++ b/addons/gecs/tests/performance/performance_test_integration.gd.uid @@ -0,0 +1 @@ +uid://8l8i83qy6ng7 diff --git a/addons/gecs/tests/performance/performance_test_queries.gd.uid b/addons/gecs/tests/performance/performance_test_queries.gd.uid new file mode 100644 index 0000000..9a3d7e0 --- /dev/null +++ b/addons/gecs/tests/performance/performance_test_queries.gd.uid @@ -0,0 +1 @@ +uid://b2d37fkunmia3 diff --git a/addons/gecs/tests/performance/performance_test_sets.gd.uid b/addons/gecs/tests/performance/performance_test_sets.gd.uid new file mode 100644 index 0000000..4b9d47f --- /dev/null +++ b/addons/gecs/tests/performance/performance_test_sets.gd.uid @@ -0,0 +1 @@ +uid://cxpn28q0c7wr diff --git a/addons/gecs/tests/performance/performance_test_system_process.gd.uid b/addons/gecs/tests/performance/performance_test_system_process.gd.uid new file mode 100644 index 0000000..a94cf18 --- /dev/null +++ b/addons/gecs/tests/performance/performance_test_system_process.gd.uid @@ -0,0 +1 @@ +uid://ik4sfttwvm74 diff --git a/addons/gecs/tests/performance/performance_test_systems.gd.uid b/addons/gecs/tests/performance/performance_test_systems.gd.uid new file mode 100644 index 0000000..c9d848e --- /dev/null +++ b/addons/gecs/tests/performance/performance_test_systems.gd.uid @@ -0,0 +1 @@ +uid://x2vtacyhjyp7 diff --git a/addons/gecs/tests/performance/test_cache_debug.gd b/addons/gecs/tests/performance/test_cache_debug.gd new file mode 100644 index 0000000..4efd9dc --- /dev/null +++ b/addons/gecs/tests/performance/test_cache_debug.gd @@ -0,0 +1,36 @@ +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + +func after_test(): + if world: + world.purge(false) + +## Test to debug cache behavior +func test_cache_hits_with_repeated_queries(): + # Add 100 entities with various components + for i in 100: + var entity = Entity.new() + entity.name = "Entity_%d" % i + if i % 2 == 0: + entity.add_component(C_TestA.new()) + if i % 3 == 0: + entity.add_component(C_TestB.new()) + world.add_entity(entity) + + # Execute same query 10 times and print cache stats each time + for i in 10: + var entities = world.query.with_all([C_TestA, C_TestB]).execute() + var stats = world.get_cache_stats() + print("Query %d: found %d entities | Cache hits=%d misses=%d" % [ + i + 1, + entities.size(), + stats.cache_hits, + stats.cache_misses + ]) diff --git a/addons/gecs/tests/performance/test_cache_debug.gd.uid b/addons/gecs/tests/performance/test_cache_debug.gd.uid new file mode 100644 index 0000000..effdd5d --- /dev/null +++ b/addons/gecs/tests/performance/test_cache_debug.gd.uid @@ -0,0 +1 @@ +uid://bdh450526m2jk diff --git a/addons/gecs/tests/performance/test_cache_key_perf.gd b/addons/gecs/tests/performance/test_cache_key_perf.gd new file mode 100644 index 0000000..63ec45e --- /dev/null +++ b/addons/gecs/tests/performance/test_cache_key_perf.gd @@ -0,0 +1,172 @@ +## Cache Key Generation Performance Tests +## Tests the performance of cache key generation with different query complexities +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + if world: + world.purge(false) + + +## Test cache key generation with varying numbers of components +## This tests the raw cache key generation performance +func test_cache_key_generation(num_components: int, test_parameters := [[1], [5], [10], [20]]): + # Build arrays of component types for the test + var all_components = [] + var any_components = [] + var exclude_components = [] + + # Use available test components + var available_components = [C_TestA, C_TestB, C_TestC, C_TestD, C_TestE, C_TestF, C_TestG, C_TestH] + + # Distribute components across all/any/exclude + for i in num_components: + var comp = available_components[i % available_components.size()] + if i % 3 == 0: + all_components.append(comp) + elif i % 3 == 1: + any_components.append(comp) + else: + exclude_components.append(comp) + + # Time generating cache keys 10000 times + var time_ms = PerfHelpers.time_it(func(): + for i in 10000: + var key = QueryCacheKey.build(all_components, any_components, exclude_components) + ) + + PerfHelpers.record_result("cache_key_generation", num_components, time_ms) + + +## Test cache hit performance with varying world sizes +## This measures the complete cached query execution time +func test_cache_hit_performance(scale: int, test_parameters := [[100], [1000], [10000]]): + # Setup entities + for i in scale: + var entity = Entity.new() + entity.name = "Entity_%d" % i + if i % 2 == 0: + entity.add_component(C_TestA.new()) + if i % 3 == 0: + entity.add_component(C_TestB.new()) + world.add_entity(entity, null, false) + + # Execute query once to populate cache + var __ = world.query.with_all([C_TestA, C_TestB]).execute() + + # Time 1000 cache hit queries + var time_ms = PerfHelpers.time_it(func(): + for i in 1000: + var entities = world.query.with_all([C_TestA, C_TestB]).execute() + ) + + PerfHelpers.record_result("cache_hit_performance", scale, time_ms) + + +## Test cache miss vs cache hit comparison +## This shows the performance difference between cache miss and hit +func test_cache_miss_vs_hit(scale: int, test_parameters := [[100], [1000], [10000]]): + # Setup entities + for i in scale: + var entity = Entity.new() + entity.name = "Entity_%d" % i + if i % 2 == 0: + entity.add_component(C_TestA.new()) + if i % 3 == 0: + entity.add_component(C_TestB.new()) + world.add_entity(entity, null, false) + + # Measure cache miss (first query) + var miss_time_ms = PerfHelpers.time_it(func(): + var entities = world.query.with_all([C_TestA, C_TestB]).execute() + ) + + # Measure cache hit (subsequent query) + var hit_time_ms = PerfHelpers.time_it(func(): + var entities = world.query.with_all([C_TestA, C_TestB]).execute() + ) + + PerfHelpers.record_result("cache_miss", scale, miss_time_ms) + PerfHelpers.record_result("cache_hit", scale, hit_time_ms) + + # Print comparison + var speedup = miss_time_ms / hit_time_ms if hit_time_ms > 0 else 0 + print(" Cache speedup at scale %d: %.1fx (miss=%.3fms, hit=%.3fms)" % [ + scale, speedup, miss_time_ms, hit_time_ms + ]) + + +## Test cache key stability across query builder instances +## Ensures the same query produces the same cache key +func test_cache_key_stability(): + # Setup some entities + for i in 100: + var entity = Entity.new() + entity.name = "Entity_%d" % i + if i % 2 == 0: + entity.add_component(C_TestA.new()) + if i % 3 == 0: + entity.add_component(C_TestB.new()) + world.add_entity(entity, null, false) + + # Execute same query 100 times and collect cache stats + var initial_stats = world.get_cache_stats() + + for i in 100: + var entities = world.query.with_all([C_TestA, C_TestB]).execute() + + var final_stats = world.get_cache_stats() + var hits = final_stats.cache_hits - initial_stats.cache_hits + var misses = final_stats.cache_misses - initial_stats.cache_misses + + print(" Cache key stability: %d hits, %d misses (%.1f%% hit rate)" % [ + hits, misses, (hits * 100.0 / (hits + misses)) if (hits + misses) > 0 else 0 + ]) + + # We expect 1 miss (first query) and 99 hits (all subsequent queries) + assert_int(misses).is_equal(1) + assert_int(hits).is_equal(99) + + +## Test cache invalidation frequency impact +## Measures performance when cache is frequently invalidated +func test_cache_invalidation_impact(scale: int, test_parameters := [[100], [1000], [10000]]): + # Setup entities + for i in scale: + var entity = Entity.new() + entity.name = "Entity_%d" % i + if i % 2 == 0: + entity.add_component(C_TestA.new()) + if i % 3 == 0: + entity.add_component(C_TestB.new()) + world.add_entity(entity, null, false) + + # Time queries with cache invalidation after each query + var with_invalidation_ms = PerfHelpers.time_it(func(): + for i in 100: + var entities = world.query.with_all([C_TestA, C_TestB]).execute() + world._query_archetype_cache.clear() # Force cache miss on next query + ) + + # Time queries without invalidation (all cache hits after first) + var without_invalidation_ms = PerfHelpers.time_it(func(): + for i in 100: + var entities = world.query.with_all([C_TestA, C_TestB]).execute() + ) + + PerfHelpers.record_result("cache_invalidation_impact_with", scale, with_invalidation_ms) + PerfHelpers.record_result("cache_invalidation_impact_without", scale, without_invalidation_ms) + + var overhead = (with_invalidation_ms - without_invalidation_ms) / without_invalidation_ms * 100 + print(" Cache invalidation overhead at scale %d: %.1f%% (with=%.2fms, without=%.2fms)" % [ + scale, overhead, with_invalidation_ms, without_invalidation_ms + ]) diff --git a/addons/gecs/tests/performance/test_cache_key_perf.gd.uid b/addons/gecs/tests/performance/test_cache_key_perf.gd.uid new file mode 100644 index 0000000..7de05e6 --- /dev/null +++ b/addons/gecs/tests/performance/test_cache_key_perf.gd.uid @@ -0,0 +1 @@ +uid://dm6141dihwven diff --git a/addons/gecs/tests/performance/test_component_perf.gd b/addons/gecs/tests/performance/test_component_perf.gd new file mode 100644 index 0000000..dd3c615 --- /dev/null +++ b/addons/gecs/tests/performance/test_component_perf.gd @@ -0,0 +1,120 @@ +## Component Performance Tests +## Tests component addition, removal, and lookup operations +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +## Test adding components to entities +func test_component_addition(scale: int, test_parameters := [[100], [1000], [10000]]): + var entities = [] + + # Pre-create entities + for i in scale: + var entity = Entity.new() + entities.append(entity) + world.add_entity(entity, null, false) + + # Time component addition + var time_ms = PerfHelpers.time_it(func(): + for entity in entities: + entity.add_component(C_TestA.new()) + ) + + PerfHelpers.record_result("component_addition", scale, time_ms) + world.purge(false) + + +## Test adding multiple components to entities +func test_multiple_component_addition(scale: int, test_parameters := [[100], [1000]]): + var entities = [] + + # Pre-create entities + for i in scale: + var entity = Entity.new() + entities.append(entity) + world.add_entity(entity, null, false) + + # Time adding multiple components + var time_ms = PerfHelpers.time_it(func(): + for entity in entities: + entity.add_component(C_TestA.new()) + entity.add_component(C_TestB.new()) + entity.add_component(C_TestC.new()) + ) + + PerfHelpers.record_result("multiple_component_addition", scale, time_ms) + world.purge(false) + +## Test removing components from entities +func test_component_removal(scale: int, test_parameters := [[100], [1000]]): + var entities = [] + + # Setup: create entities with components + for i in scale: + var entity = Entity.new() + entity.add_component(C_TestA.new()) + entity.add_component(C_TestB.new()) + entities.append(entity) + world.add_entity(entity, null, false) + + # Time component removal + var time_ms = PerfHelpers.time_it(func(): + for entity in entities: + entity.remove_component(C_TestA) + ) + + PerfHelpers.record_result("component_removal", scale, time_ms) + world.purge(false) + +## Test component lookup (has_component) +func test_component_lookup(scale: int, test_parameters := [[100], [1000], [10000]]): + var entities = [] + + # Setup: create entities with components + for i in scale: + var entity = Entity.new() + if i % 2 == 0: + entity.add_component(C_TestA.new()) + entity.add_component(C_TestB.new()) + entities.append(entity) + world.add_entity(entity, null, false) + + # Time component lookups + var time_ms = PerfHelpers.time_it(func(): + for entity in entities: + var has_a = entity.has_component(C_TestA) + var has_b = entity.has_component(C_TestB) + ) + + PerfHelpers.record_result("component_lookup", scale, time_ms) + world.purge(false) + +## Test getting component from entity +func test_component_get(scale: int, test_parameters := [[100], [1000]]): + var entities = [] + + # Setup: create entities with components + for i in scale: + var entity = Entity.new() + entity.add_component(C_TestA.new()) + entity.add_component(C_TestB.new()) + entities.append(entity) + world.add_entity(entity, null, false) + + # Time component retrieval + var time_ms = PerfHelpers.time_it(func(): + for entity in entities: + var comp_a = entity.get_component(C_TestA) + var comp_b = entity.get_component(C_TestB) + ) + + PerfHelpers.record_result("component_get", scale, time_ms) + world.purge(false) diff --git a/addons/gecs/tests/performance/test_component_perf.gd.uid b/addons/gecs/tests/performance/test_component_perf.gd.uid new file mode 100644 index 0000000..2bf9c4f --- /dev/null +++ b/addons/gecs/tests/performance/test_component_perf.gd.uid @@ -0,0 +1 @@ +uid://bsuu6ftcww6gy diff --git a/addons/gecs/tests/performance/test_entity_perf.gd b/addons/gecs/tests/performance/test_entity_perf.gd new file mode 100644 index 0000000..19f25af --- /dev/null +++ b/addons/gecs/tests/performance/test_entity_perf.gd @@ -0,0 +1,103 @@ +## Entity Performance Tests +## Tests entity creation, addition, removal, and operations +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +## Test entity creation performance at different scales +func test_entity_creation(scale: int, test_parameters := [[100], [1000], [10000]]): + var entities = [] + + var time_ms = PerfHelpers.time_it(func(): + for i in scale: + var entity = auto_free(Entity.new()) + entity.name = "PerfEntity_%d" % i + entities.append(entity) + ) + + PerfHelpers.record_result("entity_creation", scale, time_ms) + + +## Test entity creation with multiple components +func test_entity_with_components(scale: int, test_parameters := [[100], [1000], [10000]]): + var entities = [] + + var time_ms = PerfHelpers.time_it(func(): + for i in scale: + var entity = auto_free(Entity.new()) + entity.name = "PerfEntity_%d" % i + entity.add_component(C_TestA.new()) + entity.add_component(C_TestB.new()) + if i % 2 == 0: + entity.add_component(C_TestC.new()) + entities.append(entity) + ) + + PerfHelpers.record_result("entity_with_components", scale, time_ms) + world.purge(false) + +## Test adding entities to world +func test_entity_world_addition(scale: int, test_parameters := [[100], [1000], [10000]]): + var entities = [] + + # Pre-create entities + for i in scale: + var entity = Entity.new() + entity.name = "PerfEntity_%d" % i + entities.append(entity) + + # Time just the world addition + var time_ms = PerfHelpers.time_it(func(): + for entity in entities: + world.add_entity(entity, null, false) + ) + + PerfHelpers.record_result("entity_world_addition", scale, time_ms) + world.purge(false) + +## Test removing entities from world +func test_entity_removal(scale: int, test_parameters := [[100], [1000], [10000]]): + var entities = [] + + # Setup: create and add entities + for i in scale: + var entity = Entity.new() + entity.name = "PerfEntity_%d" % i + entities.append(entity) + world.add_entity(entity, null, false) + + # Time removal of half the entities + var time_ms = PerfHelpers.time_it(func(): + var to_remove = entities.slice(0, scale / 2) + for entity in to_remove: + world.remove_entity(entity) + ) + + PerfHelpers.record_result("entity_removal", scale, time_ms) + world.purge(false) + +## Test bulk entity operations +func test_bulk_entity_operations(scale: int, test_parameters := [[100], [1000], [10000]]): + var entities = [] + + # Create batch + for i in scale: + var entity = Entity.new() + entity.name = "BatchEntity_%d" % i + entities.append(entity) + + # Time bulk addition to world + var time_ms = PerfHelpers.time_it(func(): + world.add_entities(entities) + ) + + PerfHelpers.record_result("bulk_entity_operations", scale, time_ms) + world.purge(false) diff --git a/addons/gecs/tests/performance/test_entity_perf.gd.uid b/addons/gecs/tests/performance/test_entity_perf.gd.uid new file mode 100644 index 0000000..7591294 --- /dev/null +++ b/addons/gecs/tests/performance/test_entity_perf.gd.uid @@ -0,0 +1 @@ +uid://dytkj0pp6t3sk diff --git a/addons/gecs/tests/performance/test_hotpath_breakdown.gd b/addons/gecs/tests/performance/test_hotpath_breakdown.gd new file mode 100644 index 0000000..30fcd17 --- /dev/null +++ b/addons/gecs/tests/performance/test_hotpath_breakdown.gd @@ -0,0 +1,157 @@ +## System Processing Hotpath Breakdown Tests +## Detailed profiling of where time is spent during system processing +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + if world: + world.purge(false) + + +## Setup entities with velocity components (like real example) +func setup_velocity_entities(count: int) -> void: + for i in count: + var entity = Entity.new() + entity.name = "Entity_%d" % i + entity.add_component(C_Velocity.new(Vector3(randf(), randf(), randf()))) + world.add_entity(entity, null, false) + + +## Test 1: Pure query execution (no processing) +func test_query_execution_only(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_velocity_entities(scale) + + var time_ms = PerfHelpers.time_it(func(): + var _result = world.query.with_all([C_Velocity]).execute() + ) + + PerfHelpers.record_result("hotpath_query_execution", scale, time_ms) + world.purge(false) + + +## Test 2: Query + component access (no actual work) +func test_component_access(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_velocity_entities(scale) + + var entities = world.query.with_all([C_Velocity]).execute() + var c_velocity_path = C_Velocity.resource_path + + var time_ms = PerfHelpers.time_it(func(): + for entity in entities: + var _component = entity.components.get(c_velocity_path, null) as C_Velocity + ) + + PerfHelpers.record_result("hotpath_component_access", scale, time_ms) + world.purge(false) + + +## Test 3: Query + component access + data read +func test_component_data_read(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_velocity_entities(scale) + + var entities = world.query.with_all([C_Velocity]).execute() + var c_velocity_path = C_Velocity.resource_path + + var time_ms = PerfHelpers.time_it(func(): + for entity in entities: + var component = entity.components.get(c_velocity_path, null) as C_Velocity + if component: + # Read the velocity data + var _vel = component.velocity + ) + + PerfHelpers.record_result("hotpath_data_read", scale, time_ms) + world.purge(false) + + +## Test 4: Simulate full system processing loop (manual) +func test_simulated_system_loop(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_velocity_entities(scale) + + var c_velocity_path = C_Velocity.resource_path + var delta = 0.016 + + var time_ms = PerfHelpers.time_it(func(): + # Simulate what a system does: query + iterate + component access + work + var entities = world.query.with_all([C_Velocity]).execute() + for entity in entities: + var component = entity.components.get(c_velocity_path, null) as C_Velocity + if component: + # Simulate typical work (reading velocity, calculating new position) + var _new_pos = component.velocity * delta + ) + + PerfHelpers.record_result("hotpath_simulated_system", scale, time_ms) + world.purge(false) + + +## Test 5: Using actual PerformanceTestSystem (available in tests) +func test_actual_system_processing(scale: int, test_parameters := [[100], [1000], [10000]]): + # Use C_TestA instead since PerformanceTestSystem uses it + for i in scale: + var entity = Entity.new() + entity.name = "Entity_%d" % i + entity.add_component(C_TestA.new()) + world.add_entity(entity, null, false) + + var test_system = PerformanceTestSystem.new() + world.add_system(test_system) + + var time_ms = PerfHelpers.time_it(func(): + world.process(0.016) + ) + + PerfHelpers.record_result("hotpath_actual_system", scale, time_ms) + world.purge(false) + + +## Test 6: Multiple query executions per frame (simulating multiple systems) +func test_multiple_queries_per_frame(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_velocity_entities(scale) + + # Add multiple components to entities + for entity in world.entities: + entity.add_component(C_TestA.new()) + entity.add_component(C_TestB.new()) + + var time_ms = PerfHelpers.time_it(func(): + var _r1 = world.query.with_all([C_Velocity]).execute() + var _r2 = world.query.with_all([C_TestA]).execute() + var _r3 = world.query.with_all([C_TestB]).execute() + ) + + PerfHelpers.record_result("hotpath_multiple_queries", scale, time_ms) + world.purge(false) + + +## Test 7: Component access patterns - dictionary vs cached path +func test_component_access_patterns(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_velocity_entities(scale) + + var entities = world.query.with_all([C_Velocity]).execute() + + # Test with cached path (current best practice) + var c_velocity_path = C_Velocity.resource_path + var time_cached = PerfHelpers.time_it(func(): + for entity in entities: + var _component = entity.components.get(c_velocity_path, null) as C_Velocity + ) + + # Test with get_component() helper + var time_helper = PerfHelpers.time_it(func(): + for entity in entities: + var _component = entity.get_component(C_Velocity) + ) + + PerfHelpers.record_result("hotpath_component_access_cached", scale, time_cached) + PerfHelpers.record_result("hotpath_component_access_helper", scale, time_helper) + world.purge(false) diff --git a/addons/gecs/tests/performance/test_hotpath_breakdown.gd.uid b/addons/gecs/tests/performance/test_hotpath_breakdown.gd.uid new file mode 100644 index 0000000..7a4ffdd --- /dev/null +++ b/addons/gecs/tests/performance/test_hotpath_breakdown.gd.uid @@ -0,0 +1 @@ +uid://cj5f3xbcsymot diff --git a/addons/gecs/tests/performance/test_indexing_perf.gd b/addons/gecs/tests/performance/test_indexing_perf.gd new file mode 100644 index 0000000..93ac222 --- /dev/null +++ b/addons/gecs/tests/performance/test_indexing_perf.gd @@ -0,0 +1,179 @@ +## Component Indexing Performance Tests +## Compares performance of using Script objects vs String paths as dictionary keys +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + if world: + world.purge(false) + + +## Test dictionary lookup performance with String keys (current implementation) +func test_string_key_lookup(scale: int, test_parameters := [[1000], [10000], [100000]]): + # Create string-based dictionary + var string_dict: Dictionary = {} + + # Populate with component paths + var component_types = [C_TestA, C_TestB, C_TestC, C_TestD] + for comp_type in component_types: + var path = comp_type.resource_path + string_dict[path] = [] + for i in scale / 4: + string_dict[path].append(i) + + # Time lookups + var time_ms = PerfHelpers.time_it(func(): + for i in 10000: # Many lookups + var comp_type = component_types[i % 4] + var _result = string_dict.get(comp_type.resource_path, []) + ) + + PerfHelpers.record_result("string_key_lookup", scale, time_ms) + + +## Test dictionary lookup performance with Script object keys +func test_script_key_lookup(scale: int, test_parameters := [[1000], [10000], [100000]]): + # Create script-based dictionary + var script_dict: Dictionary = {} + + # Populate with component scripts directly + var component_types = [C_TestA, C_TestB, C_TestC, C_TestD] + for comp_type in component_types: + script_dict[comp_type] = [] + for i in scale / 4: + script_dict[comp_type].append(i) + + # Time lookups + var time_ms = PerfHelpers.time_it(func(): + for i in 10000: # Many lookups + var comp_type = component_types[i % 4] + var _result = script_dict.get(comp_type, []) + ) + + PerfHelpers.record_result("script_key_lookup", scale, time_ms) + + +## Test dictionary insertion performance with String keys +func test_string_key_insertion(scale: int, test_parameters := [[1000], [10000], [100000]]): + var component_types = [C_TestA, C_TestB, C_TestC, C_TestD] + + var time_ms = PerfHelpers.time_it(func(): + var string_dict: Dictionary = {} + for i in scale: + var comp_type = component_types[i % 4] + var path = comp_type.resource_path + if not string_dict.has(path): + string_dict[path] = [] + string_dict[path].append(i) + ) + + PerfHelpers.record_result("string_key_insertion", scale, time_ms) + + +## Test dictionary insertion performance with Script object keys +func test_script_key_insertion(scale: int, test_parameters := [[1000], [10000], [100000]]): + var component_types = [C_TestA, C_TestB, C_TestC, C_TestD] + + var time_ms = PerfHelpers.time_it(func(): + var script_dict: Dictionary = {} + for i in scale: + var comp_type = component_types[i % 4] + if not script_dict.has(comp_type): + script_dict[comp_type] = [] + script_dict[comp_type].append(i) + ) + + PerfHelpers.record_result("script_key_insertion", scale, time_ms) + + +## Test hash computation overhead - String path generation +func test_get_resource_path_overhead(scale: int, test_parameters := [[10000], [100000], [1000000]]): + var component_types = [C_TestA, C_TestB, C_TestC, C_TestD] + + var time_ms = PerfHelpers.time_it(func(): + for i in scale: + var comp_type = component_types[i % 4] + var _path = comp_type.resource_path + ) + + PerfHelpers.record_result("get_resource_path_overhead", scale, time_ms) + + +## Test dictionary lookup performance with Integer keys +func test_integer_key_lookup(scale: int, test_parameters := [[1000], [10000], [100000]]): + # Create integer-based dictionary + var int_dict: Dictionary = {} + + # Populate with integer keys (simulating instance IDs or hashes) + var component_types = [C_TestA, C_TestB, C_TestC, C_TestD] + for i in range(4): + int_dict[i] = [] + for j in scale / 4: + int_dict[i].append(j) + + # Time lookups + var time_ms = PerfHelpers.time_it(func(): + for i in 10000: # Many lookups + var key = i % 4 + var _result = int_dict.get(key, []) + ) + + PerfHelpers.record_result("integer_key_lookup", scale, time_ms) + + +## Test dictionary insertion performance with Integer keys +func test_integer_key_insertion(scale: int, test_parameters := [[1000], [10000], [100000]]): + var time_ms = PerfHelpers.time_it(func(): + var int_dict: Dictionary = {} + for i in scale: + var key = i % 4 + if not int_dict.has(key): + int_dict[key] = [] + int_dict[key].append(i) + ) + + PerfHelpers.record_result("integer_key_insertion", scale, time_ms) + + +## Test Script.get_instance_id() overhead +func test_get_instance_id_overhead(scale: int, test_parameters := [[10000], [100000], [1000000]]): + var component_types = [C_TestA, C_TestB, C_TestC, C_TestD] + + var time_ms = PerfHelpers.time_it(func(): + for i in scale: + var comp_type = component_types[i % 4] + var _id = comp_type.get_instance_id() + ) + + PerfHelpers.record_result("get_instance_id_overhead", scale, time_ms) + + +## Test realistic query performance with String keys (current implementation) +func test_realistic_query_with_strings(scale: int, test_parameters := [[100], [1000], [10000]]): + # Setup entities + for i in scale: + var entity = Entity.new() + entity.name = "Entity_%d" % i + if i % 2 == 0: + entity.add_component(C_TestA.new()) + if i % 3 == 0: + entity.add_component(C_TestB.new()) + world.add_entity(entity, null, false) + + # Time queries (current string-based approach) + var time_ms = PerfHelpers.time_it(func(): + for i in 100: # Execute query 100 times + var _entities = world.query.with_all([C_TestA]).execute() + ) + + PerfHelpers.record_result("realistic_query_with_strings", scale, time_ms) + world.purge(false) diff --git a/addons/gecs/tests/performance/test_indexing_perf.gd.uid b/addons/gecs/tests/performance/test_indexing_perf.gd.uid new file mode 100644 index 0000000..a1f5629 --- /dev/null +++ b/addons/gecs/tests/performance/test_indexing_perf.gd.uid @@ -0,0 +1 @@ +uid://5218hr3x4ron diff --git a/addons/gecs/tests/performance/test_observer_perf.gd b/addons/gecs/tests/performance/test_observer_perf.gd new file mode 100644 index 0000000..31677c0 --- /dev/null +++ b/addons/gecs/tests/performance/test_observer_perf.gd @@ -0,0 +1,328 @@ +## Observer Performance Tests +## Compares observers vs traditional systems for different use cases +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + if world: + world.purge(false) + + +## Setup entities with position and velocity for movement tests +func setup_velocity_entities(count: int) -> void: + for i in count: + var entity = Entity.new() + entity.name = "VelocityEntity_%d" % i + entity.add_component(C_TestPosition.new(Vector3(i, 0, 0))) + entity.add_component(C_TestVelocity.new(Vector3(randf() * 10, randf() * 10, randf() * 10))) + world.add_entity(entity, null, false) + + +## Setup entities for observer add/remove tests +func setup_observer_test_entities(count: int) -> void: + for i in count: + var entity = Entity.new() + entity.name = "ObserverTestEntity_%d" % i + entity.add_component(C_ObserverTest.new(i)) + world.add_entity(entity, null, false) + + +## Test traditional system approach for continuous processing (like velocity) +## This is the IDEAL use case for systems - they excel at continuous per-frame processing +func test_system_continuous_processing(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_velocity_entities(scale) + + var system = S_VelocitySystem.new() + world.add_system(system) + + var time_ms = PerfHelpers.time_it(func(): + # Simulate 60 frames of processing + for i in range(60): + world.process(0.016) + ) + + PerfHelpers.record_result("system_continuous_velocity", scale, time_ms) + prints("System processed %d entities across 60 frames" % system.process_count) + world.purge(false) + + +## Test observer detecting component additions +## This is an IDEAL use case for observers - they excel at reacting to state changes +func test_observer_component_additions(scale: int, test_parameters := [[100], [1000], [10000]]): + var observer = O_PerformanceTest.new() + world.add_observer(observer) + + var time_ms = PerfHelpers.time_it(func(): + # Add components to entities (observers react to additions) + for i in range(scale): + var entity = Entity.new() + entity.add_component(C_ObserverTest.new(i)) + world.add_entity(entity, null, false) + ) + + PerfHelpers.record_result("observer_component_additions", scale, time_ms) + prints("Observer detected %d additions" % observer.added_count) + assert_int(observer.added_count).is_equal(scale) + world.purge(false) + + +## Test observer detecting component removals +## Another IDEAL use case for observers - reacting to cleanup/removal events +func test_observer_component_removals(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_observer_test_entities(scale) + + var observer = O_PerformanceTest.new() + world.add_observer(observer) + + var entities = world.query.with_all([C_ObserverTest]).execute() + + var time_ms = PerfHelpers.time_it(func(): + # Remove components (observers react to removals) + for entity in entities: + entity.remove_component(C_ObserverTest) + ) + + PerfHelpers.record_result("observer_component_removals", scale, time_ms) + prints("Observer detected %d removals" % observer.removed_count) + assert_int(observer.removed_count).is_equal(scale) + world.purge(false) + + +## Test observer detecting property changes +## Good use case for observers - reacting to specific property changes +func test_observer_property_changes(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_observer_test_entities(scale) + + var observer = O_PerformanceTest.new() + world.add_observer(observer) + observer.reset_counts() + + var entities = world.query.with_all([C_ObserverTest]).execute() + + var time_ms = PerfHelpers.time_it(func(): + # Change properties (observers react to changes) + for entity in entities: + var comp = entity.get_component(C_ObserverTest) + comp.value = comp.value + 1 # Triggers property_changed signal + ) + + PerfHelpers.record_result("observer_property_changes", scale, time_ms) + prints("Observer detected %d property changes" % observer.changed_count) + assert_int(observer.changed_count).is_equal(scale) + world.purge(false) + + +## Test system approach for batch property reads +## Systems are better for batch operations without individual reactions +func test_system_batch_property_reads(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_observer_test_entities(scale) + + var system = PerformanceTestSystem.new() + world.add_system(system) + + var time_ms = PerfHelpers.time_it(func(): + # Single process call reads all entities + world.process(0.016) + ) + + PerfHelpers.record_result("system_batch_property_reads", scale, time_ms) + prints("System processed %d entities in batch" % system.process_count) + world.purge(false) + + +## Test observer overhead with multiple property changes per entity +## Shows cost of observers when entities change frequently +func test_observer_frequent_changes(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_observer_test_entities(scale) + + var observer = O_PerformanceTest.new() + world.add_observer(observer) + observer.reset_counts() + + var entities = world.query.with_all([C_ObserverTest]).execute() + + var time_ms = PerfHelpers.time_it(func(): + # Each entity changes multiple times + for entity in entities: + var comp = entity.get_component(C_ObserverTest) + for j in range(10): # 10 changes per entity + comp.value = comp.value + 1 + ) + + PerfHelpers.record_result("observer_frequent_changes", scale, time_ms) + prints("Observer detected %d property changes (%d entities × 10 changes)" % [observer.changed_count, scale]) + assert_int(observer.changed_count).is_equal(scale * 10) + world.purge(false) + + +## Test system processing the same frequent changes scenario +## Compares continuous polling vs reactive observation +func test_system_simulating_frequent_changes(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_observer_test_entities(scale) + + var system = PerformanceTestSystem.new() + world.add_system(system) + + var entities = world.query.with_all([C_ObserverTest]).execute() + + var time_ms = PerfHelpers.time_it(func(): + # Make the changes + for entity in entities: + var comp = entity.get_component(C_ObserverTest) + for j in range(10): + # Direct property change without signal + comp.value = comp.value + 1 + + # System processes once (doesn't know about individual changes) + world.process(0.016) + ) + + PerfHelpers.record_result("system_simulating_frequent_changes", scale, time_ms) + prints("System processed %d entities once after changes" % system.process_count) + world.purge(false) + + +## Test multiple observers watching the same component +## Shows overhead of multiple reactive systems +func test_multiple_observers_same_component(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_observer_test_entities(scale) + + var observer1 = O_PerformanceTest.new() + var observer2 = O_PerformanceTest.new() + var observer3 = O_PerformanceTest.new() + world.add_observers([observer1, observer2, observer3]) + + observer1.reset_counts() + observer2.reset_counts() + observer3.reset_counts() + + var entities = world.query.with_all([C_ObserverTest]).execute() + + var time_ms = PerfHelpers.time_it(func(): + # Change properties (all 3 observers react) + for entity in entities: + var comp = entity.get_component(C_ObserverTest) + comp.value = comp.value + 1 + ) + + PerfHelpers.record_result("multiple_observers_same_component", scale, time_ms) + prints("3 observers each detected %d changes" % observer1.changed_count) + assert_int(observer1.changed_count).is_equal(scale) + assert_int(observer2.changed_count).is_equal(scale) + assert_int(observer3.changed_count).is_equal(scale) + world.purge(false) + + +## Test observer query filtering performance +## Shows cost of query evaluation for observers +func test_observer_with_complex_query(scale: int, test_parameters := [[100], [1000], [10000]]): + # Create entities with varying component combinations + for i in range(scale): + var entity = Entity.new() + entity.add_component(C_ObserverTest.new(i)) + if i % 2 == 0: + entity.add_component(C_ObserverHealth.new()) + world.add_entity(entity, null, false) + + # Observer with complex query (needs both components) + var observer = O_HealthObserver.new() + world.add_observer(observer) + observer.reset() + + var entities_matching = world.query.with_all([C_ObserverTest, C_ObserverHealth]).execute() + + var time_ms = PerfHelpers.time_it(func(): + # Change health on matching entities + for entity in entities_matching: + var health = entity.get_component(C_ObserverHealth) + health.health = health.health - 1 + ) + + PerfHelpers.record_result("observer_complex_query", scale, time_ms) + prints("Observer with complex query detected %d changes (out of %d total entities)" % [observer.health_changed_count, scale]) + world.purge(false) + + +## Test baseline: Empty observer overhead +## Measures the cost of just having observers in the system +func test_observer_baseline_overhead(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_observer_test_entities(scale) + + # Add observer but don't trigger it + var observer = O_PerformanceTest.new() + world.add_observer(observer) + + var entities = world.query.with_all([C_ObserverTest]).execute() + + var time_ms = PerfHelpers.time_it(func(): + # Make changes WITHOUT triggering property_changed signals + for entity in entities: + var comp = entity.get_component(C_ObserverTest) + # Direct property access without signal emission + comp.value = comp.value + 1 + ) + + PerfHelpers.record_result("observer_baseline_overhead", scale, time_ms) + prints("Made %d changes without triggering observer" % scale) + assert_int(observer.changed_count).is_equal(scale) # Observer should have triggered + world.purge(false) + + +## Test comparison: Observer vs System for sporadic changes +## Real-world scenario: only 10% of entities change per frame +func test_observer_vs_system_sporadic_changes(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_observer_test_entities(scale) + + var observer = O_PerformanceTest.new() + world.add_observer(observer) + observer.reset_counts() + + var entities = world.query.with_all([C_ObserverTest]).execute() + var changes_per_frame = max(1, scale / 10) # 10% of entities change + + var time_ms_observer = PerfHelpers.time_it(func(): + # Simulate 60 frames where only 10% of entities change per frame + for frame in range(60): + for i in range(changes_per_frame): + var entity = entities[i % scale] + var comp = entity.get_component(C_ObserverTest) + comp.value = comp.value + 1 # Triggers observer + ) + + PerfHelpers.record_result("observer_sporadic_changes", scale, time_ms_observer) + prints("Observer detected %d sporadic changes over 60 frames" % observer.changed_count) + + # Now test with system approach + world.purge(false) + setup_observer_test_entities(scale) + + var system = PerformanceTestSystem.new() + world.add_system(system) + + entities = world.query.with_all([C_ObserverTest]).execute() + + var time_ms_system = PerfHelpers.time_it(func(): + # Same scenario but system processes ALL entities every frame + for frame in range(60): + # Make the same changes + for i in range(changes_per_frame): + var entity = entities[i % scale] + var comp = entity.get_component(C_ObserverTest) + comp.value = comp.value + 1 + + # System processes ALL entities every frame + world.process(0.016) + ) + + PerfHelpers.record_result("system_sporadic_changes", scale, time_ms_system) + prints("System processed %d total entities over 60 frames (even though only 10%% changed)" % system.process_count) + world.purge(false) diff --git a/addons/gecs/tests/performance/test_observer_perf.gd.uid b/addons/gecs/tests/performance/test_observer_perf.gd.uid new file mode 100644 index 0000000..a99668a --- /dev/null +++ b/addons/gecs/tests/performance/test_observer_perf.gd.uid @@ -0,0 +1 @@ +uid://bmhys5pytv1x8 diff --git a/addons/gecs/tests/performance/test_query_perf.gd b/addons/gecs/tests/performance/test_query_perf.gd new file mode 100644 index 0000000..31f5a65 --- /dev/null +++ b/addons/gecs/tests/performance/test_query_perf.gd @@ -0,0 +1,225 @@ +## Query Performance Tests +## Tests query building and execution performance +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + if world: + world.purge(false) + + +## Setup diverse entities with various component combinations +func setup_diverse_entities(count: int) -> void: + for i in count: + var entity = Entity.new() + entity.name = "QueryEntity_%d" % i + + # Create diverse component combinations + if i % 2 == 0: + entity.add_component(C_TestA.new()) + if i % 3 == 0: + entity.add_component(C_TestB.new()) + if i % 5 == 0: + entity.add_component(C_TestC.new()) + if i % 7 == 0: + entity.add_component(C_TestD.new()) + + world.add_entity(entity, null, false) + + +## Test simple query with_all performance +func test_query_with_all(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_diverse_entities(scale) + + var time_ms = PerfHelpers.time_it(func(): + var entities = world.query.with_all([C_TestA]).execute() + ) + + PerfHelpers.record_result("query_with_all", scale, time_ms) + world.purge(false) + +## Test query with_any performance +func test_query_with_any(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_diverse_entities(scale) + + var time_ms = PerfHelpers.time_it(func(): + var entities = world.query.with_any([C_TestA, C_TestB, C_TestC]).execute() + ) + + PerfHelpers.record_result("query_with_any", scale, time_ms) + world.purge(false) + +## Test query with_none performance +func test_query_with_none(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_diverse_entities(scale) + + var time_ms = PerfHelpers.time_it(func(): + var entities = world.query.with_none([C_TestD]).execute() + ) + + PerfHelpers.record_result("query_with_none", scale, time_ms) + world.purge(false) + +## Test complex combined query +func test_query_complex(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_diverse_entities(scale) + + var time_ms = PerfHelpers.time_it(func(): + var entities = world.query\ + .with_all([C_TestA])\ + .with_any([C_TestB, C_TestC])\ + .with_none([C_TestD])\ + .execute() + ) + + PerfHelpers.record_result("query_complex", scale, time_ms) + world.purge(false) + +## Test query with component query (property filtering) +func test_query_with_component_query(scale: int, test_parameters := [[100], [1000], [10000]]): + # Setup entities with varying property values + for i in scale: + var entity = Entity.new() + var comp = C_TestA.new() + comp.value = i + entity.add_component(comp) + world.add_entity(entity, null, false) + + var time_ms = PerfHelpers.time_it(func(): + var entities = world.query\ + .with_all([{C_TestA: {'value': {"_gte": scale / 2}}}])\ + .execute() + ) + + PerfHelpers.record_result("query_with_component_query", scale, time_ms) + world.purge(false) + +## Test query caching performance +func test_query_caching(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_diverse_entities(scale) + + # Execute same query multiple times to test cache + var time_ms = PerfHelpers.time_it(func(): + for i in 100: + var entities = world.query.with_all([C_TestA, C_TestB]).execute() + ) + + PerfHelpers.record_result("query_caching", scale, time_ms) + world.purge(false) + +## Test query on empty world +func test_query_empty_world(scale: int, test_parameters := [[100], [1000], [10000]]): + # Don't setup any entities - testing empty world query + + var time_ms = PerfHelpers.time_it(func(): + for i in scale: + var entities = world.query.with_all([C_TestA]).execute() + ) + + PerfHelpers.record_result("query_empty_world", scale, time_ms) + world.purge(false) + +## Test that disabled entities don't contribute to query time +## Creates many disabled entities with only a few enabled ones +## Query time should be similar to querying with only the enabled count +func test_query_disabled_entities_no_impact(scale: int, test_parameters := [[100], [1000], [10000]]): + # Create mostly disabled entities + var enabled_count = 10 # Always use 10 enabled entities regardless of scale + + # First, create disabled entities (scale - enabled_count) + for i in (scale - enabled_count): + var entity = Entity.new() + entity.name = "DisabledEntity_%d" % i + entity.enabled = false + entity.add_component(C_TestA.new()) + world.add_entity(entity, null, false) + + # Then create the few enabled entities + for i in enabled_count: + var entity = Entity.new() + entity.name = "EnabledEntity_%d" % i + entity.enabled = true + entity.add_component(C_TestA.new()) + world.add_entity(entity, null, false) + + # Time querying only enabled entities + var time_ms = PerfHelpers.time_it(func(): + var entities = world.query.with_all([C_TestA]).enabled().execute() + ) + + PerfHelpers.record_result("query_disabled_entities_no_impact", scale, time_ms) + world.purge(false) + +## Baseline test: query with only enabled entities (no disabled ones) +## This should have similar performance to test_query_disabled_entities_no_impact +func test_query_only_enabled_baseline(scale: int, test_parameters := [[100], [1000], [10000]]): + var enabled_count = 10 # Same as test_query_disabled_entities_no_impact + + # Create only enabled entities + for i in enabled_count: + var entity = Entity.new() + entity.name = "EnabledEntity_%d" % i + entity.enabled = true + entity.add_component(C_TestA.new()) + world.add_entity(entity, null, false) + + # Time querying enabled entities + var time_ms = PerfHelpers.time_it(func(): + var entities = world.query.with_all([C_TestA]).enabled().execute() + ) + + PerfHelpers.record_result("query_only_enabled_baseline", scale, time_ms) + world.purge(false) + +## Test group query performance using Godot's optimized get_nodes_in_group() +## This should be very fast since it uses Godot's native group indexing +func test_query_with_group(scale: int, test_parameters := [[100], [1000], [10000]]): + # Create entities and add them to a group + for i in scale: + var entity = Entity.new() + entity.name = "GroupEntity_%d" % i + entity.add_component(C_TestA.new()) + world.add_entity(entity, null, true) # Must be in tree for groups + entity.add_to_group("test_group") + + # Time querying by group + var time_ms = PerfHelpers.time_it(func(): + var entities = world.query.with_group(["test_group"]).execute() + ) + + PerfHelpers.record_result("query_with_group", scale, time_ms) + world.purge(false) + +## Test group query combined with component filtering +## This tests the common case of filtering entities by both group and components +func test_query_group_with_components(scale: int, test_parameters := [[100], [1000], [10000]]): + # Create diverse entities in a group + for i in scale: + var entity = Entity.new() + entity.name = "GroupEntity_%d" % i + + # Add various components + if i % 2 == 0: + entity.add_component(C_TestA.new()) + if i % 3 == 0: + entity.add_component(C_TestB.new()) + + world.add_entity(entity, null, true) # Must be in tree for groups + entity.add_to_group("test_group") + + # Time querying by group + components + var time_ms = PerfHelpers.time_it(func(): + var entities = world.query.with_group(["test_group"]).with_all([C_TestA]).execute() + ) + + PerfHelpers.record_result("query_group_with_components", scale, time_ms) + world.purge(false) diff --git a/addons/gecs/tests/performance/test_query_perf.gd.uid b/addons/gecs/tests/performance/test_query_perf.gd.uid new file mode 100644 index 0000000..6e476cd --- /dev/null +++ b/addons/gecs/tests/performance/test_query_perf.gd.uid @@ -0,0 +1 @@ +uid://dq82hrc6evh3t diff --git a/addons/gecs/tests/performance/test_set_perf.gd b/addons/gecs/tests/performance/test_set_perf.gd new file mode 100644 index 0000000..8d31151 --- /dev/null +++ b/addons/gecs/tests/performance/test_set_perf.gd @@ -0,0 +1,181 @@ +## Set and Array Performance Tests +## Tests Set operations and ArrayExtensions performance +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + if world: + world.purge(false) + + +## Helper to create test arrays with specified overlap +func create_test_arrays(size1: int, size2: int, overlap_percent: float = 0.5) -> Array: + var array1: Array = [] + var array2: Array = [] + + # Create first array + for i in size1: + array1.append("Entity_%d" % i) + + # Create second array with specified overlap + var overlap_count = int(size2 * overlap_percent) + var unique_count = size2 - overlap_count + + # Add overlapping elements + for i in overlap_count: + if i < size1: + array2.append(array1[i]) + + # Add unique elements + for i in unique_count: + array2.append("Entity_%d" % (size1 + i)) + + return [array1, array2] + + +## Test Set.intersect() performance +func test_set_intersect(scale: int, test_parameters := [[100], [1000], [10000]]): + var arrays = create_test_arrays(scale, scale, 0.5) + var set1 = Set.new(arrays[0]) + var set2 = Set.new(arrays[1]) + + var time_ms = PerfHelpers.time_it(func(): + var result = set1.intersect(set2) + ) + + PerfHelpers.record_result("set_intersect", scale, time_ms) + + +## Test Set.union() performance +func test_set_union(scale: int, test_parameters := [[100], [1000], [10000]]): + var arrays = create_test_arrays(scale, scale, 0.5) + var set1 = Set.new(arrays[0]) + var set2 = Set.new(arrays[1]) + + var time_ms = PerfHelpers.time_it(func(): + var result = set1.union(set2) + ) + + PerfHelpers.record_result("set_union", scale, time_ms) + + +## Test Set.difference() performance +func test_set_difference(scale: int, test_parameters := [[100], [1000], [10000]]): + var arrays = create_test_arrays(scale, scale, 0.5) + var set1 = Set.new(arrays[0]) + var set2 = Set.new(arrays[1]) + + var time_ms = PerfHelpers.time_it(func(): + var result = set1.difference(set2) + ) + + PerfHelpers.record_result("set_difference", scale, time_ms) + + +## Test ArrayExtensions.intersect() performance +func test_array_intersect(scale: int, test_parameters := [[100], [1000], [10000]]): + var arrays = create_test_arrays(scale, scale, 0.5) + var array1 = arrays[0] + var array2 = arrays[1] + + var time_ms = PerfHelpers.time_it(func(): + var result = ArrayExtensions.intersect(array1, array2) + ) + + PerfHelpers.record_result("array_intersect", scale, time_ms) + + +## Test ArrayExtensions.union() performance +func test_array_union(scale: int, test_parameters := [[100], [1000], [10000]]): + var arrays = create_test_arrays(scale, scale, 0.5) + var array1 = arrays[0] + var array2 = arrays[1] + + var time_ms = PerfHelpers.time_it(func(): + var result = ArrayExtensions.union(array1, array2) + ) + + PerfHelpers.record_result("array_union", scale, time_ms) + + +## Test ArrayExtensions.difference() performance +func test_array_difference(scale: int, test_parameters := [[100], [1000], [10000]]): + var arrays = create_test_arrays(scale, scale, 0.5) + var array1 = arrays[0] + var array2 = arrays[1] + + var time_ms = PerfHelpers.time_it(func(): + var result = ArrayExtensions.difference(array1, array2) + ) + + PerfHelpers.record_result("array_difference", scale, time_ms) + + +## Test Set.erase() performance +func test_set_erase(scale: int, test_parameters := [[100], [1000], [10000]]): + var array1: Array = [] + for i in scale: + array1.append("Entity_%d" % i) + + var test_set := Set.new(array1) + + var time_ms = PerfHelpers.time_it(func(): + # erase half the elements + for i in scale / 2: + test_set.erase("Entity_%d" % i) + ) + + PerfHelpers.record_result("set_erase", scale, time_ms) + + +## Test Set vs Array operations with no overlap +func test_set_vs_array_no_overlap(scale: int, test_parameters := [[100], [1000]]): + var arrays = create_test_arrays(scale, scale, 0.0) # No overlap + var array1 = arrays[0] + var array2 = arrays[1] + var set1 = Set.new(array1) + var set2 = Set.new(array2) + + # Test array intersect + var array_time = PerfHelpers.time_it(func(): + var result = ArrayExtensions.intersect(array1, array2) + ) + + # Test set intersect + var set_time = PerfHelpers.time_it(func(): + var result = set1.intersect(set2) + ) + + PerfHelpers.record_result("array_intersect_no_overlap", scale, array_time) + PerfHelpers.record_result("set_intersect_no_overlap", scale, set_time) + + +## Test Set vs Array operations with complete overlap +func test_set_vs_array_complete_overlap(scale: int, test_parameters := [[100], [1000]]): + var arrays = create_test_arrays(scale, scale, 1.0) # Complete overlap + var array1 = arrays[0] + var array2 = arrays[1] + var set1 = Set.new(array1) + var set2 = Set.new(array2) + + # Test array intersect + var array_time = PerfHelpers.time_it(func(): + var result = ArrayExtensions.intersect(array1, array2) + ) + + # Test set intersect + var set_time = PerfHelpers.time_it(func(): + var result = set1.intersect(set2) + ) + + PerfHelpers.record_result("array_intersect_complete_overlap", scale, array_time) + PerfHelpers.record_result("set_intersect_complete_overlap", scale, set_time) diff --git a/addons/gecs/tests/performance/test_set_perf.gd.uid b/addons/gecs/tests/performance/test_set_perf.gd.uid new file mode 100644 index 0000000..ebaa167 --- /dev/null +++ b/addons/gecs/tests/performance/test_set_perf.gd.uid @@ -0,0 +1 @@ +uid://brjw81pwtpsml diff --git a/addons/gecs/tests/performance/test_system_perf.gd b/addons/gecs/tests/performance/test_system_perf.gd new file mode 100644 index 0000000..301e92b --- /dev/null +++ b/addons/gecs/tests/performance/test_system_perf.gd @@ -0,0 +1,123 @@ +## System Performance Tests +## Tests system processing and entity iteration performance +extends GdUnitTestSuite + +var runner: GdUnitSceneRunner +var world: World + + +func before(): + runner = scene_runner("res://addons/gecs/tests/test_scene.tscn") + world = runner.get_property("world") + ECS.world = world + + +func after_test(): + if world: + world.purge(false) + + +## Setup entities for system testing +func setup_entities_for_systems(count: int) -> void: + for i in count: + var entity = Entity.new() + entity.name = "SystemEntity_%d" % i + entity.add_component(C_TestA.new()) + if i % 2 == 0: + entity.add_component(C_TestB.new()) + if i % 4 == 0: + entity.add_component(C_TestC.new()) + world.add_entity(entity, null, false) + + +## Test simple system processing +func test_system_processing(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_entities_for_systems(scale) + + var test_system = PerformanceTestSystem.new() + world.add_system(test_system) + + var time_ms = PerfHelpers.time_it(func(): + world.process(0.016) # 60 FPS delta + ) + + PerfHelpers.record_result("system_processing", scale, time_ms) + world.purge(false) + +## Test multiple systems processing +func test_multiple_systems(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_entities_for_systems(scale) + + var system_a = PerformanceTestSystem.new() + var system_b = ComplexPerformanceTestSystem.new() + world.add_systems([system_a, system_b]) + + var time_ms = PerfHelpers.time_it(func(): + world.process(0.016) + ) + + PerfHelpers.record_result("multiple_systems", scale, time_ms) + world.purge(false) + +## Test system processing with no matches +func test_system_no_matches(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_entities_for_systems(scale) + + # Create system that won't match any entities + var test_system = PerformanceTestSystem.new() + world.add_system(test_system) + + # Remove all C_TestA components so system doesn't match + for entity in world.entities: + entity.remove_component(C_TestA) + + var time_ms = PerfHelpers.time_it(func(): + world.process(0.016) + ) + + PerfHelpers.record_result("system_no_matches", scale, time_ms) + world.purge(false) + +## Test system processing with different groups +func test_system_groups(scale: int, test_parameters := [[100], [1000], [10000]]): + setup_entities_for_systems(scale) + + var physics_system = PerformanceTestSystem.new() + physics_system.group = "physics" + var render_system = PerformanceTestSystem.new() + render_system.group = "render" + + world.add_systems([physics_system, render_system]) + + var time_ms = PerfHelpers.time_it(func(): + world.process(0.016, "physics") + world.process(0.016, "render") + ) + + PerfHelpers.record_result("system_groups", scale, time_ms) + world.purge(false) + +## Test system processing with entity changes mid-frame +func test_system_dynamic_entities(scale: int, test_parameters := [[100], [1000], [10000]]): + # Start with half the entities + setup_entities_for_systems(scale / 2) + + var test_system = PerformanceTestSystem.new() + world.add_system(test_system) + + var time_ms = PerfHelpers.time_it(func(): + # Process + world.process(0.016) + + # Add more entities mid-frame + for i in range(scale / 2, scale): + var entity = Entity.new() + entity.add_component(C_TestA.new()) + world.add_entity(entity, null, false) + + # Process again with more entities + world.process(0.016) + ) + + PerfHelpers.record_result("system_dynamic_entities", scale, time_ms) + world.purge(false) diff --git a/addons/gecs/tests/performance/test_system_perf.gd.uid b/addons/gecs/tests/performance/test_system_perf.gd.uid new file mode 100644 index 0000000..390d2f2 --- /dev/null +++ b/addons/gecs/tests/performance/test_system_perf.gd.uid @@ -0,0 +1 @@ +uid://d1md8ied574c0 diff --git a/addons/gecs/tests/systems/c_test_order_component.gd b/addons/gecs/tests/systems/c_test_order_component.gd new file mode 100644 index 0000000..c0a94cf --- /dev/null +++ b/addons/gecs/tests/systems/c_test_order_component.gd @@ -0,0 +1,5 @@ +class_name C_TestOrderComponent +extends Component + +@export var execution_log: Array = [] +@export var value: int = 0 diff --git a/addons/gecs/tests/systems/c_test_order_component.gd.uid b/addons/gecs/tests/systems/c_test_order_component.gd.uid new file mode 100644 index 0000000..d264545 --- /dev/null +++ b/addons/gecs/tests/systems/c_test_order_component.gd.uid @@ -0,0 +1 @@ +uid://botsbhmpawg2q diff --git a/addons/gecs/tests/systems/o_health_observer.gd b/addons/gecs/tests/systems/o_health_observer.gd new file mode 100644 index 0000000..77534af --- /dev/null +++ b/addons/gecs/tests/systems/o_health_observer.gd @@ -0,0 +1,37 @@ +## Observer that watches C_ObserverHealth component with a query filter +class_name O_HealthObserver +extends Observer + +var health_changed_count: int = 0 +var health_added_count: int = 0 +var health_removed_count: int = 0 +var low_health_alerts: Array[Entity] = [] + +func watch() -> Resource: + return C_ObserverHealth + +func match() -> QueryBuilder: + # Only watch entities that have both C_ObserverHealth and C_ObserverTest + return q.with_all([C_ObserverHealth, C_ObserverTest]) + +func on_component_added(entity: Entity, component: Resource) -> void: + health_added_count += 1 + +func on_component_removed(entity: Entity, component: Resource) -> void: + health_removed_count += 1 + +func on_component_changed( + entity: Entity, component: Resource, property: String, new_value: Variant, old_value: Variant +) -> void: + if property == "health": + health_changed_count += 1 + # Track entities with low health + if new_value < 30: + if not low_health_alerts.has(entity): + low_health_alerts.append(entity) + +func reset() -> void: + health_changed_count = 0 + health_added_count = 0 + health_removed_count = 0 + low_health_alerts.clear() diff --git a/addons/gecs/tests/systems/o_health_observer.gd.uid b/addons/gecs/tests/systems/o_health_observer.gd.uid new file mode 100644 index 0000000..2bf3592 --- /dev/null +++ b/addons/gecs/tests/systems/o_health_observer.gd.uid @@ -0,0 +1 @@ +uid://grwgxjngteim diff --git a/addons/gecs/tests/systems/o_observer_test.gd b/addons/gecs/tests/systems/o_observer_test.gd new file mode 100644 index 0000000..22f3346 --- /dev/null +++ b/addons/gecs/tests/systems/o_observer_test.gd @@ -0,0 +1,48 @@ +## Observer that watches C_ObserverTest component for add/remove/change events +class_name O_ObserverTest +extends Observer + +var added_count: int = 0 +var removed_count: int = 0 +var changed_count: int = 0 +var last_added_entity: Entity = null +var last_removed_entity: Entity = null +var last_changed_entity: Entity = null +var last_changed_property: String = "" +var last_old_value: Variant = null +var last_new_value: Variant = null + +func watch() -> Resource: + return C_ObserverTest + +func match() -> QueryBuilder: + # Match all entities with C_ObserverTest + return q.with_all([C_ObserverTest]) + +func on_component_added(entity: Entity, component: Resource) -> void: + added_count += 1 + last_added_entity = entity + +func on_component_removed(entity: Entity, component: Resource) -> void: + removed_count += 1 + last_removed_entity = entity + +func on_component_changed( + entity: Entity, component: Resource, property: String, new_value: Variant, old_value: Variant +) -> void: + changed_count += 1 + last_changed_entity = entity + last_changed_property = property + last_old_value = old_value + last_new_value = new_value + +func reset() -> void: + added_count = 0 + removed_count = 0 + changed_count = 0 + last_added_entity = null + last_removed_entity = null + last_changed_entity = null + last_changed_property = "" + last_old_value = null + last_new_value = null diff --git a/addons/gecs/tests/systems/o_observer_test.gd.uid b/addons/gecs/tests/systems/o_observer_test.gd.uid new file mode 100644 index 0000000..9111f8e --- /dev/null +++ b/addons/gecs/tests/systems/o_observer_test.gd.uid @@ -0,0 +1 @@ +uid://cux6842x440ef diff --git a/addons/gecs/tests/systems/o_performance_test.gd b/addons/gecs/tests/systems/o_performance_test.gd new file mode 100644 index 0000000..4c9ed48 --- /dev/null +++ b/addons/gecs/tests/systems/o_performance_test.gd @@ -0,0 +1,31 @@ +## Simple observer for performance benchmarking +class_name O_PerformanceTest +extends Observer + +var added_count: int = 0 +var removed_count: int = 0 +var changed_count: int = 0 + +func watch() -> Resource: + return C_ObserverTest + +func match() -> QueryBuilder: + return q.with_all([C_ObserverTest]) + +func on_component_added(entity: Entity, component: Resource) -> void: + added_count += 1 + +func on_component_removed(entity: Entity, component: Resource) -> void: + removed_count += 1 + +func on_component_changed( + entity: Entity, component: Resource, property: String, old_value: Variant, new_value: Variant +) -> void: + changed_count += 1 + # Simulate some processing + var _val = component.get("value") + +func reset_counts(): + added_count = 0 + removed_count = 0 + changed_count = 0 diff --git a/addons/gecs/tests/systems/o_performance_test.gd.uid b/addons/gecs/tests/systems/o_performance_test.gd.uid new file mode 100644 index 0000000..0135328 --- /dev/null +++ b/addons/gecs/tests/systems/o_performance_test.gd.uid @@ -0,0 +1 @@ +uid://cm7nijht4sro diff --git a/addons/gecs/tests/systems/o_relationship_observer.gd b/addons/gecs/tests/systems/o_relationship_observer.gd new file mode 100644 index 0000000..5e57c3b --- /dev/null +++ b/addons/gecs/tests/systems/o_relationship_observer.gd @@ -0,0 +1,16 @@ +## Observer that watches relationships +class_name O_RelationshipObserver +extends Observer + +# Note: Observers don't currently have relationship_added/removed callbacks +# This is a placeholder for when relationship observing is implemented +var relationship_events: Array = [] + +func watch() -> Resource: + return C_ObserverTest + +func match() -> QueryBuilder: + return q.with_all([C_ObserverTest]) + +func reset() -> void: + relationship_events.clear() diff --git a/addons/gecs/tests/systems/o_relationship_observer.gd.uid b/addons/gecs/tests/systems/o_relationship_observer.gd.uid new file mode 100644 index 0000000..3133cf2 --- /dev/null +++ b/addons/gecs/tests/systems/o_relationship_observer.gd.uid @@ -0,0 +1 @@ +uid://b0cjecwfpdl1u diff --git a/addons/gecs/tests/systems/o_test_a.gd b/addons/gecs/tests/systems/o_test_a.gd new file mode 100644 index 0000000..220ef2d --- /dev/null +++ b/addons/gecs/tests/systems/o_test_a.gd @@ -0,0 +1,31 @@ +## This system runs when an entity that is not dead and has it's transform component changed +## This is a simple example of a reactive system that updates the entity's transform ONLY when the transform component changes if it's not dead +class_name TestAObserver +extends Observer + + +var event_count := 0 +var added_count := 0 + + +## The component to watch for changes +func watch() -> Resource: + return C_TestA + + +# What the entity needs to match for the system to run +func match() -> QueryBuilder: + # The query the entity needs to match + return ECS.world.query.with_none([C_TestB]) + + +# What to do when a property on C_Transform just changed on an entity that matches the query +func on_component_changed( + entity: Entity, component: Resource, property: String, old_value: Variant, new_value: Variant +) -> void: + # Set the transfrom from the component to the entity + print("We changed!", entity.name, component.value) + event_count += 1 + +func on_component_added(entity: Entity, component: Resource) -> void: + added_count += 1 diff --git a/addons/gecs/tests/systems/o_test_a.gd.uid b/addons/gecs/tests/systems/o_test_a.gd.uid new file mode 100644 index 0000000..a6d61ba --- /dev/null +++ b/addons/gecs/tests/systems/o_test_a.gd.uid @@ -0,0 +1 @@ +uid://dhr3ptijatg7y diff --git a/addons/gecs/tests/systems/o_velocity_observer.gd b/addons/gecs/tests/systems/o_velocity_observer.gd new file mode 100644 index 0000000..2ad5b37 --- /dev/null +++ b/addons/gecs/tests/systems/o_velocity_observer.gd @@ -0,0 +1,29 @@ +## Observer approach for velocity-based movement (reactive) +class_name O_VelocityObserver +extends Observer + +var process_count: int = 0 + +func watch() -> Resource: + return C_TestVelocity + +func match() -> QueryBuilder: + return q.with_all([C_TestPosition, C_TestVelocity]) + +func on_component_changed( + entity: Entity, component: Resource, property: String, old_value: Variant, new_value: Variant +) -> void: + if property == "velocity": + process_count += 1 + # React to velocity changes by updating position + var pos = entity.get_component(C_TestPosition) + if pos: + # Example: Could apply immediate velocity change + # In reality, observers are better for reactions than continuous updates + pass + +func on_component_added(entity: Entity, component: Resource) -> void: + process_count += 1 + +func reset_count(): + process_count = 0 diff --git a/addons/gecs/tests/systems/o_velocity_observer.gd.uid b/addons/gecs/tests/systems/o_velocity_observer.gd.uid new file mode 100644 index 0000000..6176448 --- /dev/null +++ b/addons/gecs/tests/systems/o_velocity_observer.gd.uid @@ -0,0 +1 @@ +uid://b2q8xge0b6r37 diff --git a/addons/gecs/tests/systems/r_s_test_a.gd.uid b/addons/gecs/tests/systems/r_s_test_a.gd.uid new file mode 100644 index 0000000..dd1d839 --- /dev/null +++ b/addons/gecs/tests/systems/r_s_test_a.gd.uid @@ -0,0 +1 @@ +uid://csrumrsjajut4 diff --git a/addons/gecs/tests/systems/s_archetype_column_data_test.gd b/addons/gecs/tests/systems/s_archetype_column_data_test.gd new file mode 100644 index 0000000..f96348c --- /dev/null +++ b/addons/gecs/tests/systems/s_archetype_column_data_test.gd @@ -0,0 +1,16 @@ +## Test system that verifies column data +class_name ArchetypeColumnDataTestSystem +extends System + +var values_seen = [] + + +func query() -> QueryBuilder: + return ECS.world.query.with_all([C_TestA]).iterate([C_TestA]) + + +func process(entities: Array[Entity], components: Array, delta: float) -> void: + var test_a_components = components[0] + for comp in test_a_components: + if comp: + values_seen.append(comp.value) diff --git a/addons/gecs/tests/systems/s_archetype_column_data_test.gd.uid b/addons/gecs/tests/systems/s_archetype_column_data_test.gd.uid new file mode 100644 index 0000000..e0f77ca --- /dev/null +++ b/addons/gecs/tests/systems/s_archetype_column_data_test.gd.uid @@ -0,0 +1 @@ +uid://ctia33u4i24xw diff --git a/addons/gecs/tests/systems/s_archetype_modify_test.gd b/addons/gecs/tests/systems/s_archetype_modify_test.gd new file mode 100644 index 0000000..a543276 --- /dev/null +++ b/addons/gecs/tests/systems/s_archetype_modify_test.gd @@ -0,0 +1,14 @@ +## Test system that modifies components +class_name ArchetypeModifyTestSystem +extends System + + +func query() -> QueryBuilder: + return ECS.world.query.with_all([C_TestA]).iterate([C_TestA]) + + +func process(entities: Array[Entity], components: Array, delta: float) -> void: + var test_a_components = components[0] + for comp in test_a_components: + if comp: + comp.value += 1 diff --git a/addons/gecs/tests/systems/s_archetype_modify_test.gd.uid b/addons/gecs/tests/systems/s_archetype_modify_test.gd.uid new file mode 100644 index 0000000..a5eff64 --- /dev/null +++ b/addons/gecs/tests/systems/s_archetype_modify_test.gd.uid @@ -0,0 +1 @@ +uid://cyfyyfy5pe0qx diff --git a/addons/gecs/tests/systems/s_archetype_multiple_archetypes_test.gd b/addons/gecs/tests/systems/s_archetype_multiple_archetypes_test.gd new file mode 100644 index 0000000..6ce41fd --- /dev/null +++ b/addons/gecs/tests/systems/s_archetype_multiple_archetypes_test.gd @@ -0,0 +1,15 @@ +## Test system that tracks multiple archetype calls +class_name ArchetypeMultipleArchetypesTestSystem +extends System + +var archetype_call_count = 0 +var total_entities_processed = 0 + + +func query() -> QueryBuilder: + return ECS.world.query.with_all([C_TestA, C_TestB]).iterate([C_TestA, C_TestB]) + + +func process(entities: Array[Entity], components: Array, delta: float) -> void: + archetype_call_count += 1 + total_entities_processed += entities.size() diff --git a/addons/gecs/tests/systems/s_archetype_multiple_archetypes_test.gd.uid b/addons/gecs/tests/systems/s_archetype_multiple_archetypes_test.gd.uid new file mode 100644 index 0000000..1c66d20 --- /dev/null +++ b/addons/gecs/tests/systems/s_archetype_multiple_archetypes_test.gd.uid @@ -0,0 +1 @@ +uid://crwuhtu227238 diff --git a/addons/gecs/tests/systems/s_archetype_no_iterate.gd b/addons/gecs/tests/systems/s_archetype_no_iterate.gd new file mode 100644 index 0000000..e39bfcd --- /dev/null +++ b/addons/gecs/tests/systems/s_archetype_no_iterate.gd @@ -0,0 +1,13 @@ +## Test system that doesn't call iterate() (should error) +class_name ArchetypeNoIterateSystem +extends System + +var processed = 0 + + +func query() -> QueryBuilder: + return ECS.world.query.with_all([C_TestA]) # Missing .iterate()! + + +func process(entities: Array[Entity], components: Array, delta: float) -> void: + processed += 1 diff --git a/addons/gecs/tests/systems/s_archetype_no_iterate.gd.uid b/addons/gecs/tests/systems/s_archetype_no_iterate.gd.uid new file mode 100644 index 0000000..8135ad7 --- /dev/null +++ b/addons/gecs/tests/systems/s_archetype_no_iterate.gd.uid @@ -0,0 +1 @@ +uid://dsgb6ogulr0ui diff --git a/addons/gecs/tests/systems/s_archetype_order_test.gd b/addons/gecs/tests/systems/s_archetype_order_test.gd new file mode 100644 index 0000000..d752fda --- /dev/null +++ b/addons/gecs/tests/systems/s_archetype_order_test.gd @@ -0,0 +1,20 @@ +## Test system that verifies component order +class_name ArchetypeOrderTestSystem +extends System + +var order_correct = false + + +func query() -> QueryBuilder: + # Intentionally reverse order from with_all to test iterate() controls order + return ECS.world.query.with_all([C_TestA, C_TestB]).iterate([C_TestB, C_TestA]) + + +func process(entities: Array[Entity], components: Array, delta: float) -> void: + if components.size() == 2: + # First should be C_TestB, second should be C_TestA + var first = components[0][0] if components[0].size() > 0 else null + var second = components[1][0] if components[1].size() > 0 else null + + if first is C_TestB and second is C_TestA: + order_correct = true diff --git a/addons/gecs/tests/systems/s_archetype_order_test.gd.uid b/addons/gecs/tests/systems/s_archetype_order_test.gd.uid new file mode 100644 index 0000000..016ffb4 --- /dev/null +++ b/addons/gecs/tests/systems/s_archetype_order_test.gd.uid @@ -0,0 +1 @@ +uid://drq50t10hcpe6 diff --git a/addons/gecs/tests/systems/s_archetype_subset_test.gd b/addons/gecs/tests/systems/s_archetype_subset_test.gd new file mode 100644 index 0000000..cbbce7d --- /dev/null +++ b/addons/gecs/tests/systems/s_archetype_subset_test.gd @@ -0,0 +1,14 @@ +## Test system that queries for subset of entity components +class_name ArchetypeSubsetTestSystem +extends System + +var entities_processed = 0 + + +func query() -> QueryBuilder: + # Query for A and B, even though entity has A, B, C + return ECS.world.query.with_all([C_TestA, C_TestB]).iterate([C_TestA, C_TestB]) + + +func process(entities: Array[Entity], components: Array, delta: float) -> void: + entities_processed += entities.size() diff --git a/addons/gecs/tests/systems/s_archetype_subset_test.gd.uid b/addons/gecs/tests/systems/s_archetype_subset_test.gd.uid new file mode 100644 index 0000000..4080300 --- /dev/null +++ b/addons/gecs/tests/systems/s_archetype_subset_test.gd.uid @@ -0,0 +1 @@ +uid://c3e54vjnv3eqx diff --git a/addons/gecs/tests/systems/s_archetype_test.gd b/addons/gecs/tests/systems/s_archetype_test.gd new file mode 100644 index 0000000..8ab0645 --- /dev/null +++ b/addons/gecs/tests/systems/s_archetype_test.gd @@ -0,0 +1,15 @@ +## Basic archetype test system +class_name ArchetypeTestSystem +extends System + +var archetype_call_count = 0 +var entities_processed = 0 + + +func query() -> QueryBuilder: + return ECS.world.query.with_all([C_TestA]).iterate([C_TestA]) + + +func process(entities: Array[Entity], components: Array, delta: float) -> void: + archetype_call_count += 1 + entities_processed += entities.size() diff --git a/addons/gecs/tests/systems/s_archetype_test.gd.uid b/addons/gecs/tests/systems/s_archetype_test.gd.uid new file mode 100644 index 0000000..4e3d5f5 --- /dev/null +++ b/addons/gecs/tests/systems/s_archetype_test.gd.uid @@ -0,0 +1 @@ +uid://bvrm33mibdifu diff --git a/addons/gecs/tests/systems/s_complex_performance_test.gd b/addons/gecs/tests/systems/s_complex_performance_test.gd new file mode 100644 index 0000000..5af65dd --- /dev/null +++ b/addons/gecs/tests/systems/s_complex_performance_test.gd @@ -0,0 +1,33 @@ +## Complex test system for performance benchmarking +class_name ComplexPerformanceTestSystem +extends System + + +var process_count: int = 0 + + +func query(): + return ECS.world.query.with_all([C_TestA, C_TestB]) + + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + process_count += 1 + # Simulate more complex processing + var comp_a = entity.get_component(C_TestA) + var comp_b = entity.get_component(C_TestB) + + if comp_a and comp_b: + # Simulate some computation + var _result = comp_a.serialize() + var _result2 = comp_b.serialize() + + # Simulate conditional logic + if process_count % 10 == 0: + # Occasionally add a component + if not entity.has_component(C_TestC): + entity.add_component(C_TestC.new()) + + +func reset_count(): + process_count = 0 diff --git a/addons/gecs/tests/systems/s_complex_performance_test.gd.uid b/addons/gecs/tests/systems/s_complex_performance_test.gd.uid new file mode 100644 index 0000000..5739d8c --- /dev/null +++ b/addons/gecs/tests/systems/s_complex_performance_test.gd.uid @@ -0,0 +1 @@ +uid://d1g2tv3n6uipx diff --git a/addons/gecs/tests/systems/s_noop.gd b/addons/gecs/tests/systems/s_noop.gd new file mode 100644 index 0000000..d659cfd --- /dev/null +++ b/addons/gecs/tests/systems/s_noop.gd @@ -0,0 +1,12 @@ +## No-op system for measuring overhead +class_name NoOpSystem +extends System + + +func query(): + return ECS.world.query.with_all([C_Velocity]) + + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + pass # Do nothing - used for measuring pure framework overhead diff --git a/addons/gecs/tests/systems/s_noop.gd.uid b/addons/gecs/tests/systems/s_noop.gd.uid new file mode 100644 index 0000000..aee6711 --- /dev/null +++ b/addons/gecs/tests/systems/s_noop.gd.uid @@ -0,0 +1 @@ +uid://by11uhl2ifkc7 diff --git a/addons/gecs/tests/systems/s_performance_test.gd b/addons/gecs/tests/systems/s_performance_test.gd new file mode 100644 index 0000000..eec0b1f --- /dev/null +++ b/addons/gecs/tests/systems/s_performance_test.gd @@ -0,0 +1,24 @@ +## Simple test system for performance benchmarking +class_name PerformanceTestSystem +extends System + + +var process_count: int = 0 + + +func query(): + return ECS.world.query.with_all([C_TestA]) + + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + process_count += 1 + # Simulate some light processing + var component = entity.get_component(C_TestA) + if component: + # Access component data (simulates typical system work) + var _value = component.value # Read property directly, not via reflection + + +func reset_count(): + process_count = 0 diff --git a/addons/gecs/tests/systems/s_performance_test.gd.uid b/addons/gecs/tests/systems/s_performance_test.gd.uid new file mode 100644 index 0000000..f36c60c --- /dev/null +++ b/addons/gecs/tests/systems/s_performance_test.gd.uid @@ -0,0 +1 @@ +uid://cgccpsm0e01fb diff --git a/addons/gecs/tests/systems/s_process_test_a.gd b/addons/gecs/tests/systems/s_process_test_a.gd new file mode 100644 index 0000000..3a3a5e0 --- /dev/null +++ b/addons/gecs/tests/systems/s_process_test_a.gd @@ -0,0 +1,33 @@ +## Simple test system for performance benchmarking +# test batch processing +class_name ProcessTestSystem_A +extends System + + +var process_count: int = 0 + +func _init(_process_empty: bool = false): + process_empty = _process_empty + + +func query(): + return ECS.world.query.with_all([C_TestA]) + + +# Unified process function for batch processing +func process(entities: Array[Entity], components: Array, delta: float): + process_count += 1 + var c_test_a_components = ECS.get_components(entities, C_TestA) + for i in range(entities.size()): + # Simulate some light processing + var component = c_test_a_components[i] + if component: + # Access component data (simulates typical system work) + var _data = component.serialize() + # Simulates a task/action execution system, it clears some task-specific + # components after completing the task for better performance. + entities[i].remove_component(C_TestA) + return true + +func reset_count(): + process_count = 0 diff --git a/addons/gecs/tests/systems/s_process_test_a.gd.uid b/addons/gecs/tests/systems/s_process_test_a.gd.uid new file mode 100644 index 0000000..d883f0a --- /dev/null +++ b/addons/gecs/tests/systems/s_process_test_a.gd.uid @@ -0,0 +1 @@ +uid://5dt3o04qd5pq diff --git a/addons/gecs/tests/systems/s_process_test_b.gd b/addons/gecs/tests/systems/s_process_test_b.gd new file mode 100644 index 0000000..bf2adf9 --- /dev/null +++ b/addons/gecs/tests/systems/s_process_test_b.gd @@ -0,0 +1,30 @@ +# test overriding process() +class_name ProcessTestSystem_B +extends System + + +var process_count: int = 0 + +func _init(_process_empty: bool = false): + process_empty = _process_empty + + +func query(): + return ECS.world.query.with_all([C_TestB]) + + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + if entity: + process_count += 1 + # Simulate some light processing + var component = entity.get_component(C_TestB) + if component: + # Access component data (simulates typical system work) + var _data = component.serialize() + # Simulates a task/action execution system, it clears some task-specific + # components after completing the task for better performance. + entity.remove_component(C_TestB) + +func reset_count(): + process_count = 0 diff --git a/addons/gecs/tests/systems/s_process_test_b.gd.uid b/addons/gecs/tests/systems/s_process_test_b.gd.uid new file mode 100644 index 0000000..8df82d2 --- /dev/null +++ b/addons/gecs/tests/systems/s_process_test_b.gd.uid @@ -0,0 +1 @@ +uid://ba3lvvufdygps diff --git a/addons/gecs/tests/systems/s_test_a.gd b/addons/gecs/tests/systems/s_test_a.gd new file mode 100644 index 0000000..bf47a1c --- /dev/null +++ b/addons/gecs/tests/systems/s_test_a.gd @@ -0,0 +1,21 @@ +class_name TestASystem +extends System + + +func deps(): + return { + Runs.After: [], # Doesn't run after any other system + Runs.Before: [ECS.wildcard], # This system runs before all other systems + } + + +func query(): + return ECS.world.query.with_all([C_TestA]) + + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var a = entity.get_component(C_TestA) as C_TestA + a.value += 1 + a.property_changed.emit(a, 'value', null, null) + print("TestASystem: ", entity.name, a.value) \ No newline at end of file diff --git a/addons/gecs/tests/systems/s_test_a.gd.uid b/addons/gecs/tests/systems/s_test_a.gd.uid new file mode 100644 index 0000000..0384173 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_a.gd.uid @@ -0,0 +1 @@ +uid://cwtjamm4iqado diff --git a/addons/gecs/tests/systems/s_test_b.gd b/addons/gecs/tests/systems/s_test_b.gd new file mode 100644 index 0000000..956b49c --- /dev/null +++ b/addons/gecs/tests/systems/s_test_b.gd @@ -0,0 +1,20 @@ +class_name TestBSystem +extends System + + +func deps(): + return { + Runs.After: [TestASystem], # Runs after SystemA + Runs.Before: [TestCSystem], # This system rubs before SystemC + } + + +func query(): + return ECS.world.query.with_all([C_TestB]) + + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var a = entity.get_component(C_TestB) + a.value += 1 + print("TestBSystem: ", a.value) diff --git a/addons/gecs/tests/systems/s_test_b.gd.uid b/addons/gecs/tests/systems/s_test_b.gd.uid new file mode 100644 index 0000000..c350af1 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_b.gd.uid @@ -0,0 +1 @@ +uid://d0qrblp21kurk diff --git a/addons/gecs/tests/systems/s_test_c.gd b/addons/gecs/tests/systems/s_test_c.gd new file mode 100644 index 0000000..bc660b7 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_c.gd @@ -0,0 +1,20 @@ +class_name TestCSystem +extends System + + +func deps(): + return { + Runs.After: [TestBSystem], # Runs after SystemA + Runs.Before: [TestDSystem], # This system rubs before SystemC + } + + +func query(): + return ECS.world.query.with_all([C_TestC]) + + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var a = entity.get_component(C_TestC) + a.value += 1 + print("TestASystem: ", a.value) diff --git a/addons/gecs/tests/systems/s_test_c.gd.uid b/addons/gecs/tests/systems/s_test_c.gd.uid new file mode 100644 index 0000000..4e4b68e --- /dev/null +++ b/addons/gecs/tests/systems/s_test_c.gd.uid @@ -0,0 +1 @@ +uid://chohwnsy3i4s0 diff --git a/addons/gecs/tests/systems/s_test_d.gd b/addons/gecs/tests/systems/s_test_d.gd new file mode 100644 index 0000000..74a86a8 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_d.gd @@ -0,0 +1,21 @@ +class_name TestDSystem +extends System + + +func deps(): + return { + Runs.After: [ECS.wildcard], # Runs after all other systems + # If we exclude Rubs.Before it will be ignored + # Runs.Before: [], # We could also set it to an empty array + } + + +func query(): + return ECS.world.query.with_all([C_TestC]) + + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var a = entity.get_component(C_TestC) + a.value += 1 + print("TestASystem: ", a.value) diff --git a/addons/gecs/tests/systems/s_test_d.gd.uid b/addons/gecs/tests/systems/s_test_d.gd.uid new file mode 100644 index 0000000..7a45ea3 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_d.gd.uid @@ -0,0 +1 @@ +uid://cj0qhir58bt6k diff --git a/addons/gecs/tests/systems/s_test_nonexistent_group.gd b/addons/gecs/tests/systems/s_test_nonexistent_group.gd new file mode 100644 index 0000000..79fca5b --- /dev/null +++ b/addons/gecs/tests/systems/s_test_nonexistent_group.gd @@ -0,0 +1,12 @@ +class_name TestSystemNonexistentGroup +extends System + +var entities_found := [] + + +func query(): + return q.with_group(["NonexistentGroup"]) + + +func process(entities: Array[Entity], components: Array, delta: float) -> void: + entities_found = entities.duplicate() diff --git a/addons/gecs/tests/systems/s_test_nonexistent_group.gd.uid b/addons/gecs/tests/systems/s_test_nonexistent_group.gd.uid new file mode 100644 index 0000000..16bc6c2 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_nonexistent_group.gd.uid @@ -0,0 +1 @@ +uid://bktsskx8mcole diff --git a/addons/gecs/tests/systems/s_test_order_a.gd b/addons/gecs/tests/systems/s_test_order_a.gd new file mode 100644 index 0000000..0b44ee4 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_a.gd @@ -0,0 +1,17 @@ +class_name S_TestOrderA +extends System +const NAME = 'S_TestOrderA' +func deps(): + return { + Runs.Before: [ECS.wildcard], # Run before all other systems + Runs.After: [], + } + +func query(): + return ECS.world.query.with_all([C_TestOrderComponent]) + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var comp = entity.get_component(C_TestOrderComponent) + comp.execution_log.append("A") + comp.value += 1 diff --git a/addons/gecs/tests/systems/s_test_order_a.gd.uid b/addons/gecs/tests/systems/s_test_order_a.gd.uid new file mode 100644 index 0000000..a356055 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_a.gd.uid @@ -0,0 +1 @@ +uid://buariuvsnvjb2 diff --git a/addons/gecs/tests/systems/s_test_order_b.gd b/addons/gecs/tests/systems/s_test_order_b.gd new file mode 100644 index 0000000..4f82d34 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_b.gd @@ -0,0 +1,17 @@ +class_name S_TestOrderB +extends System +const NAME = 'S_TestOrderB' +func deps(): + return { + Runs.After: [S_TestOrderA], + Runs.Before: [S_TestOrderC], + } + +func query(): + return ECS.world.query.with_all([C_TestOrderComponent]) + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var comp = entity.get_component(C_TestOrderComponent) + comp.execution_log.append("B") + comp.value += 10 diff --git a/addons/gecs/tests/systems/s_test_order_b.gd.uid b/addons/gecs/tests/systems/s_test_order_b.gd.uid new file mode 100644 index 0000000..22d5ae5 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_b.gd.uid @@ -0,0 +1 @@ +uid://bkenjhqhoausd diff --git a/addons/gecs/tests/systems/s_test_order_c.gd b/addons/gecs/tests/systems/s_test_order_c.gd new file mode 100644 index 0000000..d6a35b3 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_c.gd @@ -0,0 +1,17 @@ +class_name S_TestOrderC +extends System +const NAME = 'S_TestOrderC' +func deps(): + return { + Runs.After: [S_TestOrderB], + Runs.Before: [S_TestOrderD], + } + +func query(): + return ECS.world.query.with_all([C_TestOrderComponent]) + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var comp = entity.get_component(C_TestOrderComponent) + comp.execution_log.append("C") + comp.value += 100 diff --git a/addons/gecs/tests/systems/s_test_order_c.gd.uid b/addons/gecs/tests/systems/s_test_order_c.gd.uid new file mode 100644 index 0000000..0ade290 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_c.gd.uid @@ -0,0 +1 @@ +uid://cqaxiyxffk4q3 diff --git a/addons/gecs/tests/systems/s_test_order_d.gd b/addons/gecs/tests/systems/s_test_order_d.gd new file mode 100644 index 0000000..75d1e49 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_d.gd @@ -0,0 +1,19 @@ +class_name S_TestOrderD +extends System + +const NAME = 'S_TestOrderD' + +func deps(): + return { + Runs.After: [ECS.wildcard], # Run after all other systems + Runs.Before: [], + } + +func query(): + return ECS.world.query.with_all([C_TestOrderComponent]) + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var comp = entity.get_component(C_TestOrderComponent) + comp.execution_log.append("D") + comp.value += 1000 diff --git a/addons/gecs/tests/systems/s_test_order_d.gd.uid b/addons/gecs/tests/systems/s_test_order_d.gd.uid new file mode 100644 index 0000000..4313dc6 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_d.gd.uid @@ -0,0 +1 @@ +uid://ccy8n3p1rf4fp diff --git a/addons/gecs/tests/systems/s_test_order_e.gd b/addons/gecs/tests/systems/s_test_order_e.gd new file mode 100644 index 0000000..fb122f2 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_e.gd @@ -0,0 +1,13 @@ +class_name S_TestOrderE +extends System + +func deps(): + return {Runs.After: [], Runs.Before: []} + +func query(): + return ECS.world.query.with_all([C_TestOrderComponent]) + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var c = entity.get_component(C_TestOrderComponent) + c.execution_log.append("E") diff --git a/addons/gecs/tests/systems/s_test_order_e.gd.uid b/addons/gecs/tests/systems/s_test_order_e.gd.uid new file mode 100644 index 0000000..e62ac05 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_e.gd.uid @@ -0,0 +1 @@ +uid://cpkgwgw1i378e diff --git a/addons/gecs/tests/systems/s_test_order_f.gd b/addons/gecs/tests/systems/s_test_order_f.gd new file mode 100644 index 0000000..8e5d03b --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_f.gd @@ -0,0 +1,13 @@ +class_name S_TestOrderF +extends System + +func deps(): + return {Runs.After: [S_TestOrderE], Runs.Before: []} + +func query(): + return ECS.world.query.with_all([C_TestOrderComponent]) + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var c = entity.get_component(C_TestOrderComponent) + c.execution_log.append("F") diff --git a/addons/gecs/tests/systems/s_test_order_f.gd.uid b/addons/gecs/tests/systems/s_test_order_f.gd.uid new file mode 100644 index 0000000..47ca272 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_f.gd.uid @@ -0,0 +1 @@ +uid://dnwk2tuyggk6g diff --git a/addons/gecs/tests/systems/s_test_order_g.gd b/addons/gecs/tests/systems/s_test_order_g.gd new file mode 100644 index 0000000..8deb565 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_g.gd @@ -0,0 +1,13 @@ +class_name S_TestOrderG +extends System + +func deps(): + return {Runs.After: [S_TestOrderE], Runs.Before: []} + +func query(): + return ECS.world.query.with_all([C_TestOrderComponent]) + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var c = entity.get_component(C_TestOrderComponent) + c.execution_log.append("G") diff --git a/addons/gecs/tests/systems/s_test_order_g.gd.uid b/addons/gecs/tests/systems/s_test_order_g.gd.uid new file mode 100644 index 0000000..6c87ced --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_g.gd.uid @@ -0,0 +1 @@ +uid://t8yllp42u864 diff --git a/addons/gecs/tests/systems/s_test_order_h.gd b/addons/gecs/tests/systems/s_test_order_h.gd new file mode 100644 index 0000000..ef75c63 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_h.gd @@ -0,0 +1,13 @@ +class_name S_TestOrderH +extends System + +func deps(): + return {Runs.After: [S_TestOrderF, S_TestOrderG], Runs.Before: []} + +func query(): + return ECS.world.query.with_all([C_TestOrderComponent]) + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var c = entity.get_component(C_TestOrderComponent) + c.execution_log.append("H") diff --git a/addons/gecs/tests/systems/s_test_order_h.gd.uid b/addons/gecs/tests/systems/s_test_order_h.gd.uid new file mode 100644 index 0000000..62f49a9 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_h.gd.uid @@ -0,0 +1 @@ +uid://cdpmy2ltl88jr diff --git a/addons/gecs/tests/systems/s_test_order_x.gd b/addons/gecs/tests/systems/s_test_order_x.gd new file mode 100644 index 0000000..12f1df7 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_x.gd @@ -0,0 +1,13 @@ +class_name S_TestOrderX +extends System + +func deps(): + return {Runs.After: [], Runs.Before: []} + +func query(): + return ECS.world.query.with_all([C_TestOrderComponent]) + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var comp = entity.get_component(C_TestOrderComponent) + comp.execution_log.append("X") diff --git a/addons/gecs/tests/systems/s_test_order_x.gd.uid b/addons/gecs/tests/systems/s_test_order_x.gd.uid new file mode 100644 index 0000000..a77dc11 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_x.gd.uid @@ -0,0 +1 @@ +uid://cuslkawfgeyiq diff --git a/addons/gecs/tests/systems/s_test_order_y.gd b/addons/gecs/tests/systems/s_test_order_y.gd new file mode 100644 index 0000000..a905123 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_y.gd @@ -0,0 +1,13 @@ +class_name S_TestOrderY +extends System + +func deps(): + return {Runs.After: [], Runs.Before: []} + +func query(): + return ECS.world.query.with_all([C_TestOrderComponent]) + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var comp = entity.get_component(C_TestOrderComponent) + comp.execution_log.append("Y") diff --git a/addons/gecs/tests/systems/s_test_order_y.gd.uid b/addons/gecs/tests/systems/s_test_order_y.gd.uid new file mode 100644 index 0000000..1848783 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_y.gd.uid @@ -0,0 +1 @@ +uid://b844sl3oew2vc diff --git a/addons/gecs/tests/systems/s_test_order_z.gd b/addons/gecs/tests/systems/s_test_order_z.gd new file mode 100644 index 0000000..eadfd2f --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_z.gd @@ -0,0 +1,13 @@ +class_name S_TestOrderZ +extends System + +func deps(): + return {Runs.After: [], Runs.Before: []} + +func query(): + return ECS.world.query.with_all([C_TestOrderComponent]) + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + var comp = entity.get_component(C_TestOrderComponent) + comp.execution_log.append("Z") diff --git a/addons/gecs/tests/systems/s_test_order_z.gd.uid b/addons/gecs/tests/systems/s_test_order_z.gd.uid new file mode 100644 index 0000000..b21939e --- /dev/null +++ b/addons/gecs/tests/systems/s_test_order_z.gd.uid @@ -0,0 +1 @@ +uid://cbucoavgh1vky diff --git a/addons/gecs/tests/systems/s_test_with_group.gd b/addons/gecs/tests/systems/s_test_with_group.gd new file mode 100644 index 0000000..0ab6fe8 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_with_group.gd @@ -0,0 +1,12 @@ +class_name TestSystemWithGroup +extends System + +var entities_found := [] + + +func query(): + return q.with_group(["TestGroup"]) + + +func process(entities: Array[Entity], components: Array, delta: float) -> void: + entities_found = entities.duplicate() diff --git a/addons/gecs/tests/systems/s_test_with_group.gd.uid b/addons/gecs/tests/systems/s_test_with_group.gd.uid new file mode 100644 index 0000000..004f36e --- /dev/null +++ b/addons/gecs/tests/systems/s_test_with_group.gd.uid @@ -0,0 +1 @@ +uid://balljjtww1lc1 diff --git a/addons/gecs/tests/systems/s_test_with_relationship.gd b/addons/gecs/tests/systems/s_test_with_relationship.gd new file mode 100644 index 0000000..d186d20 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_with_relationship.gd @@ -0,0 +1,12 @@ +class_name TestSystemWithRelationship +extends System + +var entities_found := [] + + +func query(): + return q.with_relationship([Relationship.new(C_TestA.new(), null)]) + + +func process(entities: Array[Entity], components: Array, delta: float) -> void: + entities_found = entities.duplicate() diff --git a/addons/gecs/tests/systems/s_test_with_relationship.gd.uid b/addons/gecs/tests/systems/s_test_with_relationship.gd.uid new file mode 100644 index 0000000..ab7857c --- /dev/null +++ b/addons/gecs/tests/systems/s_test_with_relationship.gd.uid @@ -0,0 +1 @@ +uid://duoso032fxxt2 diff --git a/addons/gecs/tests/systems/s_test_without_group.gd b/addons/gecs/tests/systems/s_test_without_group.gd new file mode 100644 index 0000000..6b3ca3a --- /dev/null +++ b/addons/gecs/tests/systems/s_test_without_group.gd @@ -0,0 +1,12 @@ +class_name TestSystemWithoutGroup +extends System + +var entities_found := [] + + +func query(): + return q.without_group(["TestGroup"]) + + +func process(entities: Array[Entity], components: Array, delta: float) -> void: + entities_found = entities.duplicate() diff --git a/addons/gecs/tests/systems/s_test_without_group.gd.uid b/addons/gecs/tests/systems/s_test_without_group.gd.uid new file mode 100644 index 0000000..2c4b963 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_without_group.gd.uid @@ -0,0 +1 @@ +uid://bjm8r3h0frnlr diff --git a/addons/gecs/tests/systems/s_test_without_relationship.gd b/addons/gecs/tests/systems/s_test_without_relationship.gd new file mode 100644 index 0000000..14bb2a3 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_without_relationship.gd @@ -0,0 +1,12 @@ +class_name TestSystemWithoutRelationship +extends System + +var entities_found := [] + + +func query(): + return q.without_relationship([Relationship.new(C_TestA.new(), null)]) + + +func process(entities: Array[Entity], components: Array, delta: float) -> void: + entities_found = entities.duplicate() diff --git a/addons/gecs/tests/systems/s_test_without_relationship.gd.uid b/addons/gecs/tests/systems/s_test_without_relationship.gd.uid new file mode 100644 index 0000000..7a2c7d0 --- /dev/null +++ b/addons/gecs/tests/systems/s_test_without_relationship.gd.uid @@ -0,0 +1 @@ +uid://d1u7ie74wc3kn diff --git a/addons/gecs/tests/systems/s_velocity_system.gd b/addons/gecs/tests/systems/s_velocity_system.gd new file mode 100644 index 0000000..5e5a0d3 --- /dev/null +++ b/addons/gecs/tests/systems/s_velocity_system.gd @@ -0,0 +1,21 @@ +## Traditional system approach for velocity-based movement +class_name S_VelocitySystem +extends System + +var process_count: int = 0 + +func query(): + return ECS.world.query.with_all([C_TestPosition, C_TestVelocity]) + +func process(entities: Array[Entity], components: Array, delta: float): + for entity in entities: + process_count += 1 + var pos = entity.get_component(C_TestPosition) + var vel = entity.get_component(C_TestVelocity) + + # Update position based on velocity + # Note: Direct assignment without using setter to avoid triggering observers + pos.position = pos.position + vel.velocity * delta + +func reset_count(): + process_count = 0 diff --git a/addons/gecs/tests/systems/s_velocity_system.gd.uid b/addons/gecs/tests/systems/s_velocity_system.gd.uid new file mode 100644 index 0000000..de53e0e --- /dev/null +++ b/addons/gecs/tests/systems/s_velocity_system.gd.uid @@ -0,0 +1 @@ +uid://c1r6ewwcgy8fq diff --git a/addons/gecs/tests/test_component.gd.uid b/addons/gecs/tests/test_component.gd.uid new file mode 100644 index 0000000..947d5a9 --- /dev/null +++ b/addons/gecs/tests/test_component.gd.uid @@ -0,0 +1 @@ +uid://bsw2bhs2js1vt diff --git a/addons/gecs/tests/test_entity.gd.uid b/addons/gecs/tests/test_entity.gd.uid new file mode 100644 index 0000000..a102739 --- /dev/null +++ b/addons/gecs/tests/test_entity.gd.uid @@ -0,0 +1 @@ +uid://cahxu8hd86g diff --git a/addons/gecs/tests/test_observers.gd.uid b/addons/gecs/tests/test_observers.gd.uid new file mode 100644 index 0000000..96cde71 --- /dev/null +++ b/addons/gecs/tests/test_observers.gd.uid @@ -0,0 +1 @@ +uid://b0mh7ox643wtm diff --git a/addons/gecs/tests/test_queries.gd.uid b/addons/gecs/tests/test_queries.gd.uid new file mode 100644 index 0000000..19628d1 --- /dev/null +++ b/addons/gecs/tests/test_queries.gd.uid @@ -0,0 +1 @@ +uid://cn3kv6q24itoj diff --git a/addons/gecs/tests/test_query_builder.gd.uid b/addons/gecs/tests/test_query_builder.gd.uid new file mode 100644 index 0000000..c54ffac --- /dev/null +++ b/addons/gecs/tests/test_query_builder.gd.uid @@ -0,0 +1 @@ +uid://c3mqoma4f6fwq diff --git a/addons/gecs/tests/test_relationships.gd.uid b/addons/gecs/tests/test_relationships.gd.uid new file mode 100644 index 0000000..6dcdcd1 --- /dev/null +++ b/addons/gecs/tests/test_relationships.gd.uid @@ -0,0 +1 @@ +uid://ctgunlbeb57iq diff --git a/addons/gecs/tests/test_scene.gd b/addons/gecs/tests/test_scene.gd new file mode 100644 index 0000000..fee0ef6 --- /dev/null +++ b/addons/gecs/tests/test_scene.gd @@ -0,0 +1,3 @@ +extends Node3D + +@onready var world = %World diff --git a/addons/gecs/tests/test_scene.gd.uid b/addons/gecs/tests/test_scene.gd.uid new file mode 100644 index 0000000..6d9d123 --- /dev/null +++ b/addons/gecs/tests/test_scene.gd.uid @@ -0,0 +1 @@ +uid://bcfll27sdfcpw diff --git a/addons/gecs/tests/test_scene.tscn b/addons/gecs/tests/test_scene.tscn new file mode 100644 index 0000000..110ad67 --- /dev/null +++ b/addons/gecs/tests/test_scene.tscn @@ -0,0 +1,17 @@ +[gd_scene load_steps=3 format=3 uid="uid://ngouye3it3qy"] + +[ext_resource type="Script" uid="uid://cdu5tlyk72uu4" path="res://addons/gecs/ecs/world.gd" id="1_o1k8h"] +[ext_resource type="Script" uid="uid://bcfll27sdfcpw" path="res://addons/gecs/tests/test_scene.gd" id="1_vo5ju"] + +[node name="Node3D" type="Node3D"] +script = ExtResource("1_vo5ju") + +[node name="World" type="Node" parent="."] +unique_name_in_owner = true +script = ExtResource("1_o1k8h") +entity_nodes_root = NodePath("Entities") +system_nodes_root = NodePath("Systems") + +[node name="Entities" type="Node" parent="World"] + +[node name="Systems" type="Node" parent="World"] diff --git a/addons/gecs/tests/test_system.gd.uid b/addons/gecs/tests/test_system.gd.uid new file mode 100644 index 0000000..768dd91 --- /dev/null +++ b/addons/gecs/tests/test_system.gd.uid @@ -0,0 +1 @@ +uid://dy7e70dh6jj01 diff --git a/addons/gecs/tests/test_world.gd.uid b/addons/gecs/tests/test_world.gd.uid new file mode 100644 index 0000000..638dd3f --- /dev/null +++ b/addons/gecs/tests/test_world.gd.uid @@ -0,0 +1 @@ +uid://bystws838yewp diff --git a/addons/gecs/tests/tests_array_extensions.gd.uid b/addons/gecs/tests/tests_array_extensions.gd.uid new file mode 100644 index 0000000..5764d7f --- /dev/null +++ b/addons/gecs/tests/tests_array_extensions.gd.uid @@ -0,0 +1 @@ +uid://uimudkk37xss diff --git a/addons/godot-plugin-refresher/LICENSE b/addons/godot-plugin-refresher/LICENSE new file mode 100644 index 0000000..282a89e --- /dev/null +++ b/addons/godot-plugin-refresher/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2018-2021 Will Nations + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/addons/godot-plugin-refresher/plugin.cfg b/addons/godot-plugin-refresher/plugin.cfg new file mode 100644 index 0000000..90a8572 --- /dev/null +++ b/addons/godot-plugin-refresher/plugin.cfg @@ -0,0 +1,7 @@ +[plugin] + +name="Godot Plugin Refresher" +description="A toolbar addition to facilitate toggling off/on a selected plugin. Updated for Godot 4.3" +author="willnationsdev" +version="1.2" +script="plugin_refresher_plugin.gd" diff --git a/addons/godot-plugin-refresher/plugin_refresher.gd b/addons/godot-plugin-refresher/plugin_refresher.gd new file mode 100644 index 0000000..210cfa0 --- /dev/null +++ b/addons/godot-plugin-refresher/plugin_refresher.gd @@ -0,0 +1,73 @@ +@tool +extends HBoxContainer + +signal request_refresh_plugin(p_name: String) +signal confirm_refresh_plugin(p_name: String) + +@onready var options: OptionButton = $OptionButton + + +func _ready() -> void: + if get_tree().edited_scene_root == self: + return # This is the scene opened in the editor! + $RefreshButton.icon = EditorInterface.get_editor_theme().get_icon("Reload", "EditorIcons") + + +func update_items(p_plugins_info: Array) -> void: + if not options: + return + options.clear() + + var plugins := p_plugins_info[0] as Dictionary + var display_names_map := p_plugins_info[1] as Dictionary + + var plugin_dirs: Array[String] = [] + plugin_dirs.assign(plugins.keys()) + for idx in plugin_dirs.size(): + var plugin_dirname := plugin_dirs[idx] + var plugin_data = plugins[plugin_dirname] # Array[String] used as a Tuple. + var plugin_name := plugin_data[0] as String + var plugin_path := plugin_data[1] as String + var display_name := display_names_map[plugin_path] as String + + options.add_item(display_name, idx) + options.set_item_metadata(idx, plugin_path) + + +# Note: For whatever reason, statically typing `p_name` inexplicably causes +# an error about converting from Nil to String, even if the value is converted. +func select_plugin(p_name) -> void: + if not options or not p_name: + return + + for idx in options.get_item_count(): + var plugin := str(options.get_item_metadata(idx)) + if plugin == str(p_name): + options.selected = options.get_item_id(idx) + break + + +func _on_RefreshButton_pressed() -> void: + if options.selected == -1: + return # nothing selected + + var plugin := str(options.get_item_metadata(options.selected)) + if not plugin: + return + emit_signal("request_refresh_plugin", plugin) + + +func show_warning(p_name: String) -> void: + $ConfirmationDialog.dialog_text = ( + """ + Plugin `%s` is currently disabled.\n + Do you want to enable it now? + """ + % [p_name] + ) + $ConfirmationDialog.popup_centered() + + +func _on_ConfirmationDialog_confirmed() -> void: + var plugin := options.get_item_metadata(options.selected) as String + emit_signal("confirm_refresh_plugin", plugin) diff --git a/addons/godot-plugin-refresher/plugin_refresher.gd.uid b/addons/godot-plugin-refresher/plugin_refresher.gd.uid new file mode 100644 index 0000000..d4e91b3 --- /dev/null +++ b/addons/godot-plugin-refresher/plugin_refresher.gd.uid @@ -0,0 +1 @@ +uid://bf4gdvb18b3od diff --git a/addons/godot-plugin-refresher/plugin_refresher.tscn b/addons/godot-plugin-refresher/plugin_refresher.tscn new file mode 100644 index 0000000..63c77bb --- /dev/null +++ b/addons/godot-plugin-refresher/plugin_refresher.tscn @@ -0,0 +1,21 @@ +[gd_scene load_steps=2 format=3 uid="uid://dnladpgp5dwts"] + +[ext_resource type="Script" uid="uid://bf4gdvb18b3od" path="res://addons/godot-plugin-refresher/plugin_refresher.gd" id="1"] + +[node name="HBoxContainer" type="HBoxContainer"] +script = ExtResource("1") + +[node name="VSeparator" type="VSeparator" parent="."] +layout_mode = 2 + +[node name="OptionButton" type="OptionButton" parent="."] +layout_mode = 2 + +[node name="RefreshButton" type="Button" parent="."] +layout_mode = 2 + +[node name="ConfirmationDialog" type="ConfirmationDialog" parent="."] +dialog_autowrap = true + +[connection signal="pressed" from="RefreshButton" to="." method="_on_RefreshButton_pressed"] +[connection signal="confirmed" from="ConfirmationDialog" to="." method="_on_ConfirmationDialog_confirmed"] diff --git a/addons/godot-plugin-refresher/plugin_refresher_plugin.gd b/addons/godot-plugin-refresher/plugin_refresher_plugin.gd new file mode 100644 index 0000000..99089a9 --- /dev/null +++ b/addons/godot-plugin-refresher/plugin_refresher_plugin.gd @@ -0,0 +1,156 @@ +@tool +extends EditorPlugin + +const ADDONS_PATH := "res://addons/" +const PLUGIN_CONFIG_DIR := "plugins/plugin_refresher" +const PLUGIN_CONFIG := "settings.cfg" +const PLUGIN_NAME := "Godot Plugin Refresher" +const SETTINGS := "settings" +const SETTING_RECENT := "recently_used" +const Refresher := preload("plugin_refresher.gd") + +var plugin_config := ConfigFile.new() +var refresher: Refresher = null + + +func _enter_tree() -> void: + refresher = preload("plugin_refresher.tscn").instantiate() as Refresher + add_control_to_container(CONTAINER_TOOLBAR, refresher) + + # Watch whether any plugin is changed, added or removed on the filesystem + var efs := EditorInterface.get_resource_filesystem() + efs.filesystem_changed.connect(_on_filesystem_changed) + + refresher.request_refresh_plugin.connect(_on_request_refresh_plugin) + refresher.confirm_refresh_plugin.connect(_on_confirm_refresh_plugin) + + _reload_plugins_list() + _load_settings() + + +func _exit_tree() -> void: + remove_control_from_container(CONTAINER_TOOLBAR, refresher) + refresher.free() + + +func _reload_plugins_list() -> void: + var cfg_paths: Array[String] = [] + var plugins := {} + var display_names_map := {} # full path to display name + + find_cfgs(ADDONS_PATH, cfg_paths) + + for cfg_path in cfg_paths: + var plugin_cfg := ConfigFile.new() + var err := plugin_cfg.load(cfg_path) + if err: + push_error("ERROR LOADING PLUGIN FILE: %s" % err) + else: + var plugin_name := plugin_cfg.get_value("plugin", "name") + if plugin_name != PLUGIN_NAME: + var addon_dir_name = cfg_path.split("addons/")[-1].split("/plugin.cfg")[0] + plugins[addon_dir_name] = [plugin_name, cfg_path] + + # This will be an array of the addon/* directory names. + var plugin_dirs: Array[String] = [] + plugin_dirs.assign(plugins.keys()) # typed array "casting" + + var plugin_names: Array[String] = [] + plugin_names.assign(plugin_dirs.map(func(k): return plugins[k][0])) + + for plugin_dirname in plugin_dirs: + var plugin_name = plugins[plugin_dirname][0] + var display_name = plugin_name if plugin_names.count(plugin_name) == 1 else "%s (%s)" % [plugin_name, plugin_dirname] + display_names_map[plugins[plugin_dirname][1]] = display_name + + refresher.update_items([plugins, display_names_map]) + + +func find_cfgs(dir_path: String, cfgs: Array): + var dir := DirAccess.open(dir_path) + var cfg_path := dir_path.path_join("plugin.cfg") + + if dir.file_exists(cfg_path): + cfgs.append(cfg_path) + return + + if dir: + dir.list_dir_begin() + var file_name := dir.get_next() + while file_name != "": + if dir.current_is_dir(): + find_cfgs(dir_path.path_join(file_name), cfgs) + file_name = dir.get_next() + + +func _load_settings() -> void: + var path := get_settings_path() + + if not FileAccess.file_exists(path): + # Create new if running for the first time + var config := ConfigFile.new() + DirAccess.make_dir_recursive_absolute(path.get_base_dir()) + config.save(path) + else: + plugin_config.load(path) + + +func _save_settings() -> void: + plugin_config.save(get_settings_path()) + + +func get_settings_path() -> String: + var editor_paths := EditorInterface.get_editor_paths() + var dir := editor_paths.get_project_settings_dir() + + var home := dir.path_join(PLUGIN_CONFIG_DIR) + var path := home.path_join(PLUGIN_CONFIG) + + return path + + +func _on_filesystem_changed() -> void: + if refresher: + _reload_plugins_list() + var recent = get_recent_plugin() + if recent: + refresher.select_plugin(recent) + + +func get_recent_plugin() -> String: + if not plugin_config.has_section_key(SETTINGS, SETTING_RECENT): + return "" # not saved yet + + var recent = str(plugin_config.get_value(SETTINGS, SETTING_RECENT)) + return recent + + +func _on_request_refresh_plugin(p_path: String) -> void: + assert(not p_path.is_empty()) + + var disabled := not EditorInterface.is_plugin_enabled(p_path) + if disabled: + refresher.show_warning(p_path) + else: + refresh_plugin(p_path) + + +func _on_confirm_refresh_plugin(p_path: String) -> void: + refresh_plugin(p_path) + + +func get_plugin_path() -> String: + return get_script().resource_path.get_base_dir() + + +func refresh_plugin(p_path: String) -> void: + print("Refreshing plugin: ", p_path) + + var enabled := EditorInterface.is_plugin_enabled(p_path) + if enabled: # can only disable an active plugin + EditorInterface.set_plugin_enabled(p_path, false) + + EditorInterface.set_plugin_enabled(p_path, true) + + plugin_config.set_value(SETTINGS, SETTING_RECENT, p_path) + _save_settings() diff --git a/addons/godot-plugin-refresher/plugin_refresher_plugin.gd.uid b/addons/godot-plugin-refresher/plugin_refresher_plugin.gd.uid new file mode 100644 index 0000000..71916ce --- /dev/null +++ b/addons/godot-plugin-refresher/plugin_refresher_plugin.gd.uid @@ -0,0 +1 @@ +uid://dg1pimj67d104 diff --git a/maps/camera.gd b/maps/camera.gd deleted file mode 100644 index 645f4f2..0000000 --- a/maps/camera.gd +++ /dev/null @@ -1,28 +0,0 @@ -extends "res://addons/Free fly camera/Src/free_fly_startup.gd" - - -const SPEED = 5.0 -const JUMP_VELOCITY = 4.5 - - -func _physics_process(delta: float) -> void: - # Add the gravity. - if not is_on_floor(): - velocity += get_gravity() * delta - - # Handle jump. - if Input.is_action_just_pressed("ui_accept") and is_on_floor(): - velocity.y = JUMP_VELOCITY - - # Get the input direction and handle the movement/deceleration. - # As good practice, you should replace UI actions with custom gameplay actions. - var input_dir := Input.get_vector("ui_left", "ui_right", "ui_up", "ui_down") - var direction := (transform.basis * Vector3(input_dir.x, 0, input_dir.y)).normalized() - if direction: - velocity.x = direction.x * SPEED - velocity.z = direction.z * SPEED - else: - velocity.x = move_toward(velocity.x, 0, SPEED) - velocity.z = move_toward(velocity.z, 0, SPEED) - - move_and_slide() diff --git a/maps/camera.gd.uid b/maps/camera.gd.uid deleted file mode 100644 index 49097d8..0000000 --- a/maps/camera.gd.uid +++ /dev/null @@ -1 +0,0 @@ -uid://e6ihddcgve8c diff --git a/maps/enemies.tscn b/maps/enemies.tscn index fb73fbd..b45cc5f 100644 --- a/maps/enemies.tscn +++ b/maps/enemies.tscn @@ -1,6 +1,10 @@ -[gd_scene load_steps=5 format=3 uid="uid://cohmqsk3s70yp"] +[gd_scene load_steps=10 format=3 uid="uid://cohmqsk3s70yp"] +[ext_resource type="Script" uid="uid://cg0xoblykx4w6" path="res://maps/world.gd" id="1_3cfne"] [ext_resource type="Script" uid="uid://cte4jalives85" path="res://addons/sk_fly_camera/src/fly_camera.gd" id="1_aj441"] +[ext_resource type="Script" uid="uid://cdu5tlyk72uu4" path="res://addons/gecs/ecs/world.gd" id="1_i46j0"] +[ext_resource type="PackedScene" uid="uid://b2v1bngfh5te" path="res://GECS/systems/default_systems.tscn" id="4_3cfne"] +[ext_resource type="PackedScene" uid="uid://d0075ch03hfri" path="res://GECS/entities/Spawner/SpawnPoint.tscn" id="5_qsrji"] [sub_resource type="PhysicalSkyMaterial" id="PhysicalSkyMaterial_aj441"] @@ -17,7 +21,17 @@ ssao_enabled = true ssao_radius = 2.0 fog_light_color = Color(1, 1, 1, 1) +[sub_resource type="SphereShape3D" id="SphereShape3D_qsrji"] + [node name="Enemies" type="Node3D"] +script = ExtResource("1_3cfne") + +[node name="World" type="Node" parent="."] +script = ExtResource("1_i46j0") +system_nodes_root = NodePath("../Systems") +metadata/_custom_type_script = "uid://cdu5tlyk72uu4" + +[node name="Systems" parent="." instance=ExtResource("4_3cfne")] [node name="WorldEnvironment" type="WorldEnvironment" parent="."] environment = SubResource("Environment_i46j0") @@ -30,10 +44,24 @@ transform = Transform3D(0.098757595, -0.94823945, -0.30180964, 0.25508866, -0.26 light_energy = 0.2 [node name="CharacterBody3D" type="CharacterBody3D" parent="."] -transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, -13.231003, 12.216311, 0) +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 1.7689972, 2.2163115, 6) +collision_layer = 0 +collision_mask = 0 +motion_mode = 1 script = ExtResource("1_aj441") +[node name="CollisionShape3D" type="CollisionShape3D" parent="CharacterBody3D"] +shape = SubResource("SphereShape3D_qsrji") + +[node name="SpawnPoint" parent="." instance=ExtResource("5_qsrji")] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 4, 2, 1) +spawn_frequency = 2.0 + +[node name="SpawnPoint2" parent="." instance=ExtResource("5_qsrji")] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 7, 2, -21) + [node name="CSGCombiner3D" type="CSGCombiner3D" parent="."] +use_collision = true [node name="CSGBox3D" type="CSGBox3D" parent="CSGCombiner3D"] size = Vector3(100, 1, 100) @@ -87,7 +115,7 @@ transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 10.025868, -9.536743e-07, 8.9 size = Vector3(10, 8, 10) [node name="CSGBox3D14" type="CSGBox3D" parent="CSGCombiner3D"] -transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 13.727036, -9.536743e-07, 0.6610918) +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 12.7270355, -9.536743e-07, 0.6610918) size = Vector3(10, 9, 10) [node name="CSGBox3D15" type="CSGBox3D" parent="CSGCombiner3D"] diff --git a/maps/enemies.tscn101497640.tmp b/maps/enemies.tscn101497640.tmp new file mode 100644 index 0000000..1352d96 --- /dev/null +++ b/maps/enemies.tscn101497640.tmp @@ -0,0 +1,124 @@ +[gd_scene load_steps=10 format=3 uid="uid://cohmqsk3s70yp"] + +[ext_resource type="Script" uid="uid://cg0xoblykx4w6" path="res://maps/world.gd" id="1_3cfne"] +[ext_resource type="Script" uid="uid://cte4jalives85" path="res://addons/sk_fly_camera/src/fly_camera.gd" id="1_aj441"] +[ext_resource type="Script" uid="uid://cdu5tlyk72uu4" path="res://addons/gecs/ecs/world.gd" id="1_i46j0"] +[ext_resource type="PackedScene" uid="uid://b2v1bngfh5te" path="res://GECS/systems/default_systems.tscn" id="4_3cfne"] +[ext_resource type="PackedScene" uid="uid://d0075ch03hfri" path="res://GECS/entities/Spawner/SpawnPoint.tscn" id="5_qsrji"] + +[sub_resource type="PhysicalSkyMaterial" id="PhysicalSkyMaterial_aj441"] + +[sub_resource type="Sky" id="Sky_o2inx"] +sky_material = SubResource("PhysicalSkyMaterial_aj441") + +[sub_resource type="Environment" id="Environment_i46j0"] +background_mode = 2 +sky = SubResource("Sky_o2inx") +ambient_light_source = 2 +ambient_light_color = Color(0.77807873, 0.8451813, 0.8615737, 1) +ambient_light_energy = 0.5 +ssao_enabled = true +ssao_radius = 2.0 +fog_light_color = Color(1, 1, 1, 1) + +[sub_resource type="SphereShape3D" id="SphereShape3D_qsrji"] + +[node name="Enemies" type="Node3D"] +script = ExtResource("1_3cfne") + +[node name="World" type="Node" parent="."] +script = ExtResource("1_i46j0") +system_nodes_root = NodePath("../Systems") +metadata/_custom_type_script = "uid://cdu5tlyk72uu4" + +[node name="Systems" parent="." instance=ExtResource("4_3cfne")] + +[node name="WorldEnvironment" type="WorldEnvironment" parent="."] +environment = SubResource("Environment_i46j0") + +[node name="DirectionalLight3D" type="DirectionalLight3D" parent="."] +transform = Transform3D(0.6725735, -0.5947325, 0.44038418, -0.74003035, -0.5405202, 0.40024132, 0, -0.5950894, -0.8036596, 0, 0, 0) + +[node name="DirectionalLight3D2" type="DirectionalLight3D" parent="."] +transform = Transform3D(0.098757595, -0.94823945, -0.30180964, 0.25508866, -0.26903492, 0.92873573, -0.96186113, -0.16870806, 0.21531586, 0, 0, 0) +light_energy = 0.2 + +[node name="CharacterBody3D" type="CharacterBody3D" parent="."] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 1.7689972, 2.2163115, 6) +collision_layer = 0 +collision_mask = 0 +motion_mode = 1 +script = ExtResource("1_aj441") + +[node name="CollisionShape3D" type="CollisionShape3D" parent="CharacterBody3D"] +shape = SubResource("SphereShape3D_qsrji") + +[node name="SpawnPoint" parent="." instance=ExtResource("5_qsrji")] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 4, 2, 1) +spawn_frequency = 0.2 + +[node name="SpawnPoint2" parent="." instance=ExtResource("5_qsrji")] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 7, 2, -21) +spawn_frequency = -1.0 + +[node name="CSGCombiner3D" type="CSGCombiner3D" parent="."] +use_collision = true + +[node name="CSGBox3D" type="CSGBox3D" parent="CSGCombiner3D"] +size = Vector3(100, 1, 100) + +[node name="CSGBox3D2" type="CSGBox3D" parent="CSGCombiner3D"] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 3.389802, -9.536743e-07, -17.424805) +size = Vector3(2, 10, 2) + +[node name="CSGBox3D3" type="CSGBox3D" parent="CSGCombiner3D"] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 10.554723, 0, -14.582476) +size = Vector3(2, 10, 2) + +[node name="CSGBox3D4" type="CSGBox3D" parent="CSGCombiner3D"] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 10.554723, 0, 8.672777) +size = Vector3(2, 10, 2) + +[node name="CSGBox3D5" type="CSGBox3D" parent="CSGCombiner3D"] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, -3.4320955, 0, 8.672777) +size = Vector3(2, 10, 2) + +[node name="CSGBox3D6" type="CSGBox3D" parent="CSGCombiner3D"] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, -7.400285, 0, -3.0115404) +size = Vector3(2, 10, 2) + +[node name="CSGBox3D7" type="CSGBox3D" parent="CSGCombiner3D"] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 1.3954687, -9.536743e-07, -8.965862) +size = Vector3(10, 2, 10) + +[node name="CSGBox3D8" type="CSGBox3D" parent="CSGCombiner3D"] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, -4.063101, -9.536743e-07, -6.855488) +size = Vector3(10, 3, 10) + +[node name="CSGBox3D9" type="CSGBox3D" parent="CSGCombiner3D"] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, -7.932084, 0, -3.5338726) +size = Vector3(10, 4, 10) + +[node name="CSGBox3D10" type="CSGBox3D" parent="CSGCombiner3D"] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, -7.932084, 0, 1.561698) +size = Vector3(10, 5, 10) + +[node name="CSGBox3D11" type="CSGBox3D" parent="CSGCombiner3D"] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, -5.3916206, -1.9073486e-06, 9.662505) +size = Vector3(10, 6, 10) + +[node name="CSGBox3D12" type="CSGBox3D" parent="CSGCombiner3D"] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 1.696065, -9.536743e-07, 12.753594) +size = Vector3(10, 7, 10) + +[node name="CSGBox3D13" type="CSGBox3D" parent="CSGCombiner3D"] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 10.025868, -9.536743e-07, 8.954356) +size = Vector3(10, 8, 10) + +[node name="CSGBox3D14" type="CSGBox3D" parent="CSGCombiner3D"] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 12.7270355, -9.536743e-07, 0.6610918) +size = Vector3(10, 9, 10) + +[node name="CSGBox3D15" type="CSGBox3D" parent="CSGCombiner3D"] +transform = Transform3D(1, 0, 0, 0, 1, 0, 0, 0, 1, 17.384857, -9.536743e-07, -3.8720686) +size = Vector3(10, 10, 10) diff --git a/main.tscn b/maps/main.tscn similarity index 100% rename from main.tscn rename to maps/main.tscn diff --git a/maps/world.gd b/maps/world.gd new file mode 100644 index 0000000..c8f8d4f --- /dev/null +++ b/maps/world.gd @@ -0,0 +1,24 @@ +extends Node3D + +@onready var world: World = $World + +@onready var spawn_point: E_SpawnPoint = $SpawnPoint +@onready var spawn_point_2: E_SpawnPoint = $SpawnPoint2 + +func _ready(): + ECS.world = world + + #var player_scene = preload("res://GECS/entities/BasicEnemy/BasicEnemy.tscn") # Adjust path as needed + #var basic_enemy = player_scene.instantiate() as BasicEnemy +# + #add_child(basic_enemy) # Add to scene tree + ECS.world.add_entity(spawn_point) + ECS.world.add_entity(spawn_point_2) + +func _process(delta: float) -> void: + if ECS.world: + ECS.process(delta, "gameplay") + +func _physics_process(delta): + if ECS.world: + ECS.process(delta, "physics") diff --git a/maps/world.gd.uid b/maps/world.gd.uid new file mode 100644 index 0000000..1a4a626 --- /dev/null +++ b/maps/world.gd.uid @@ -0,0 +1 @@ +uid://cg0xoblykx4w6 diff --git a/project.godot b/project.godot index a9eb249..15c2d40 100644 --- a/project.godot +++ b/project.godot @@ -11,9 +11,19 @@ config_version=5 [application] config/name="ShaderTests" +run/main_scene="uid://cohmqsk3s70yp" config/features=PackedStringArray("4.5", "Forward Plus") config/icon="res://icon.svg" +[autoload] + +ECS="*res://addons/gecs/ecs/ecs.gd" +DebugMenu="*res://addons/debug_menu/debug_menu.tscn" + [dotnet] project/assembly_name="ShaderTests" + +[editor_plugins] + +enabled=PackedStringArray("res://addons/debug_menu/plugin.cfg", "res://addons/gdUnit4/plugin.cfg", "res://addons/gecs/plugin.cfg", "res://addons/godot-plugin-refresher/plugin.cfg")