engine improvements
This commit is contained in:
parent
4504d0d412
commit
522b29269d
@ -2,6 +2,7 @@ from typing import Tuple, List
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from AgentBase import AgentBase
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from data.enum.Direction import Direction
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from decision.Action import Action
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from decision.ActionType import ActionType
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@ -9,52 +10,52 @@ class ForkliftAgent(AgentBase):
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def __init__(self, model):
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super().__init__(model)
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self.movement_queue = []
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self.action_queue: List[Action] = []
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self.current_position = Tuple[int, int]
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self.current_rotation = Direction.right
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def queue_movement_actions(self, movement_actions: List[ActionType]):
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self.movement_queue.extend(movement_actions)
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def queue_movement_actions(self, movement_actions: List[Action]):
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self.action_queue.extend(movement_actions)
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def move(self):
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if len(self.movement_queue) > 0:
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action = self.movement_queue.pop(0)
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if len(self.action_queue) > 0:
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action = self.action_queue.pop(0)
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action_type = action.action_type
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if action == ActionType.ROTATE_UP:
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print("rotate {} --> {}".format(self.current_rotation, action))
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if action_type == ActionType.ROTATE_UP:
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print("rotate {} --> {}".format(self.current_rotation, action_type))
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self.current_rotation = Direction.top
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elif action == ActionType.ROTATE_RIGHT:
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print("rotate {} --> {}".format(self.current_rotation, action))
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elif action_type == ActionType.ROTATE_RIGHT:
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print("rotate {} --> {}".format(self.current_rotation, action_type))
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self.current_rotation = Direction.right
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elif action == ActionType.ROTATE_DOWN:
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print("rotate {} --> {}".format(self.current_rotation, action))
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elif action_type == ActionType.ROTATE_DOWN:
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print("rotate {} --> {}".format(self.current_rotation, action_type))
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self.current_rotation = Direction.down
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elif action == ActionType.ROTATE_LEFT:
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print("rotate {} --> {}".format(self.current_rotation, action))
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elif action_type == ActionType.ROTATE_LEFT:
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print("rotate {} --> {}".format(self.current_rotation, action_type))
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self.current_rotation = Direction.left
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elif action == ActionType.MOVE:
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elif action_type == ActionType.MOVE:
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if self.current_rotation == Direction.top:
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print("move {} --> {}".format(self.current_position, action))
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print("move {} --> {}".format(self.current_position, action_type))
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self.current_position = (self.current_position[0], self.current_position[1] + 1)
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elif self.current_rotation == Direction.down:
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print("move {} --> {}".format(self.current_position, action))
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print("move {} --> {}".format(self.current_position, action_type))
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self.current_position = (self.current_position[0], self.current_position[1] - 1)
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elif self.current_rotation == Direction.right:
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print("move {} --> {}".format(self.current_position, action))
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print("move {} --> {}".format(self.current_position, action_type))
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self.current_position = (self.current_position[0] + 1, self.current_position[1])
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elif self.current_rotation == Direction.left:
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print("move {} --> {}".format(self.current_position, action))
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print("move {} --> {}".format(self.current_position, action_type))
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self.current_position = (self.current_position[0] - 1, self.current_position[1])
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def step(self) -> None:
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print("forklift step")
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self.move()
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def creation_log(self):
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207
GameModel.py
207
GameModel.py
@ -1,3 +1,4 @@
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from enum import Enum
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from typing import List
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from mesa import Model
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@ -10,89 +11,229 @@ from InitialStateFactory import InitialStateFactory
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from PatchAgent import PatchAgent
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from PatchType import PatchType
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from data.GameConstants import GameConstants
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from data.Item import Item
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from data.Order import Order
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from data.enum.Direction import Direction
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from data.enum.ItemType import ItemType
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from decision.Action import Action
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from decision.ActionType import ActionType
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from pathfinding.PathfinderOnStates import PathFinderOnStates, PathFinderState
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from util.PathDefinitions import GridLocation, GridWithWeights
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class Phase(Enum):
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INIT = 1
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ITEM_RECOGNITION = 2
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CLIENT_SORTING = 3
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PLAN_MOVEMENT = 4
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EXECUTION = 5
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class GameModel(Model):
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def __init__(self, width, height, graph: GridWithWeights, graph2: GridWithWeights):
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def __init__(self, width, height, graph: GridWithWeights):
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# self.num_agents = 5
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self.first = True
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self.item_recognised = False
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self.running = True
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self.grid = MultiGrid(height, width, True)
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self.schedule = RandomActivation(self)
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self.agents = [AgentBase]
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self.client_delivery: PatchAgent = None
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self.drop_off: PatchAgent = None
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self.agents = [AgentBase]
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self.forklift_agent = ForkliftAgent(self)
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self.schedule.add(self.forklift_agent)
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self.agents.append(self.forklift_agent)
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initial_state_factory = InitialStateFactory()
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self.graph = graph
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self.game_constants = GameConstants(
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width,
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height,
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graph.walls,
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graph2.puddles
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graph.puddles
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)
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# Add the agent to a random grid cell
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x = 5
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y = 5
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self.grid.place_agent(self.forklift_agent, (x, y))
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self.forklift_agent.current_position = (x, y)
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# INITIALIZATION #
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print("############## INITIALIZATION ##############")
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self.phase = Phase.INIT
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self.initialize_grid(graph)
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self.orderList: List[Order] = InitialStateFactory.generate_order_list(3)
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start, goal = (x, y), (1, 3)
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print("############## RECOGNISE ITEMS ##############")
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self.phase = Phase.ITEM_RECOGNITION
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self.provided_items = InitialStateFactory.generate_item_list(3)
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self.recognised_items: List[Item] = []
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print("Relocate forklift agent to loading area for item recognition")
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pathFinder = PathFinderOnStates(
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self.game_constants,
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goal,
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self.drop_off.location,
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PathFinderState(self.forklift_agent.current_position, self.forklift_agent.current_rotation, 0,
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ActionType.NONE, [])
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Action(ActionType.NONE), [])
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)
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self.place_patch_agents()
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self.place_walls_agents(graph.walls)
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self.place_puddles(graph2.puddles)
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actions = pathFinder.get_action_list()
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print("PATHFINDING")
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print(actions)
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self.forklift_agent.queue_movement_actions(actions)
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def place_patch_agents(self):
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agent = PatchAgent(self, PatchType.pickUp)
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def initialize_grid(self, graph: GridWithWeights):
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print("INITIALIZING GRID")
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# Add the agent to a random grid cell
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x = 5
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y = 5
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self.grid.place_agent(self.forklift_agent, (x, y))
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self.forklift_agent.current_position = (x, y)
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self.place_logistics()
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self.place_walls_agents(graph.walls)
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self.place_puddles(graph.puddles)
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self.place_packing_stations(graph.packingStations)
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def place_logistics(self):
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agent = PatchAgent(self, (self.grid.width - 1, int(self.grid.height / 2)), PatchType.pickUp)
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self.schedule.add(agent)
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self.grid.place_agent(agent, (self.grid.width - 1, self.grid.height - 1))
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self.grid.place_agent(agent, agent.location)
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self.agents.append(agent)
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self.client_delivery = agent
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agent = PatchAgent(self, PatchType.dropOff)
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# self.schedule.add(agent)
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self.grid.place_agent(agent, (0, self.grid.height - 1))
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agent = PatchAgent(self, (0, int(self.grid.height / 2)), PatchType.dropOff)
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self.grid.place_agent(agent, agent.location)
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self.agents.append(agent)
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for i in range(3):
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a = PatchAgent(self, PatchType.item)
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self.agents.append(a)
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self.grid.place_agent(a, (i, 0))
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self.drop_off = agent
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def place_walls_agents(self, walls: List[GridLocation]):
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for w in walls:
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agent = PatchAgent(self, PatchType.wall)
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agent = PatchAgent(self, w, PatchType.wall)
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self.agents.append(agent)
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self.grid.place_agent(agent, w)
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def place_puddles(self, puddles: List[GridLocation]):
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for p in puddles:
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agent = PatchAgent(self, PatchType.diffTerrain)
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agent = PatchAgent(self, p, PatchType.diffTerrain)
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self.agents.append(agent)
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self.grid.place_agent(agent, p)
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def place_packing_stations(self, packing_stations: List[tuple[PatchType, GridLocation]]):
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for p in packing_stations:
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agent = PatchAgent(self, p[1], p[0])
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self.agents.append(agent)
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self.grid.place_agent(agent, p[1])
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def step(self):
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self.schedule.step()
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print("update multiGrid")
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self.grid.remove_agent(self.forklift_agent)
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self.grid.place_agent(self.forklift_agent, self.forklift_agent.current_position)
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if self.phase == Phase.ITEM_RECOGNITION:
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if not self.item_recognised and self.forklift_agent.current_position == self.drop_off.location:
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if len(self.provided_items) == 0:
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print("FINISHED ITEM RECOGNITION")
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self.item_recognised = True
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self.phase = Phase.CLIENT_SORTING
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else:
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print("BEGIN ITEM RECOGNITION, left: {}".format(len(self.provided_items)))
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item_to_recognise = self.provided_items.pop()
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recognised = self.recognise_item(item_to_recognise)
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self.recognised_items.append(recognised)
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if self.phase == Phase.CLIENT_SORTING:
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# TODO GENERICS SORTING
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sorted(self.orderList, key=lambda x: len(x.items))
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print("FINISHED CLIENT ORDER SORTING")
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self.phase = Phase.PLAN_MOVEMENT
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if self.phase == Phase.PLAN_MOVEMENT:
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if len(self.orderList) > 0:
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self.plan_actions()
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self.phase = Phase.EXECUTION
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else:
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print("NO MORE ORDERS")
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if self.phase == Phase.EXECUTION:
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print("Execution")
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if (len(self.forklift_agent.action_queue) == 0):
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self.phase = Phase.PLAN_MOVEMENT
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def plan_actions(self):
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order = self.orderList.pop(0)
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print("PLAN MOVEMENT")
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for i in order.items:
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if self.first:
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# get item
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pathFinder = PathFinderOnStates(
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self.game_constants,
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self.drop_off.location,
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PathFinderState(self.forklift_agent.current_position,
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self.forklift_agent.current_rotation,
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0,
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Action(ActionType.NONE),
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[])
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)
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actions = pathFinder.get_action_list()
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self.forklift_agent.queue_movement_actions(actions)
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self.first = False
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else:
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# get item
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pathFinder = PathFinderOnStates(
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self.game_constants,
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self.drop_off.location,
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PathFinderState(self.client_delivery.location,
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Direction.right,
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0,
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Action(ActionType.NONE),
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[])
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)
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actions = pathFinder.get_action_list()
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self.forklift_agent.queue_movement_actions(actions)
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self.first = False
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# go through station
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packing_station: GridLocation = None
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stations = dict(self.graph.packingStations)
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if i.real_type == ItemType.PASTA:
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packing_station = stations[PatchType.packingA]
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elif i.real_type == ItemType.EGG:
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packing_station = stations[PatchType.packingB]
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elif i.real_type == ItemType.PIZZA:
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packing_station = stations[PatchType.packingC]
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pathFinder = PathFinderOnStates(
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self.game_constants,
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packing_station,
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PathFinderState(self.drop_off.location,
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Direction.left,
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0,
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Action(
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desired_item=i,
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action_type=ActionType.PICK_ITEM
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),
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[])
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)
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actions = pathFinder.get_action_list()
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self.forklift_agent.queue_movement_actions(actions)
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# go to client delivery area
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pathFinder = PathFinderOnStates(
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self.game_constants,
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self.client_delivery.location,
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PathFinderState(packing_station,
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Direction.right,
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0,
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Action(ActionType.NONE),
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[])
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)
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actions = pathFinder.get_action_list()
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self.forklift_agent.queue_movement_actions(actions)
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self.forklift_agent.queue_movement_actions(
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[Action(ActionType.DROP_ITEM)]
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)
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def recognise_item(self, item: Item):
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# TODO IMAGE PROCESSING
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item.guessed_type = item.real_type
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return item
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@ -1,38 +1,47 @@
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import random
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from data.Item import Item
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from data.enum.ItemType import ItemType
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from data.Order import Order
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from data.enum.ItemType import ItemType
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from util.ClientParamsFactory import ClientParamsFactory
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class InitialStateFactory:
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@staticmethod
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def generate_order_list(self, output_order_list_size: int):
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order_list = [Order]
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for i in range(0, output_order_list_size):
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order_list.append(self.__generate_order())
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def generate_item_list(output_list_size: int):
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item_list : [Item] = []
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for i in range(output_list_size):
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item_list.append(InitialStateFactory.__generate_item())
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return item_list
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@staticmethod
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def generate_order_list(output_order_list_size: int):
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order_list: [Order] = []
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for i in range(output_order_list_size):
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order_list.append(InitialStateFactory.__generate_order())
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return order_list
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@staticmethod
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def __generate_order(self) -> Order:
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def __generate_order() -> Order:
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order_size = random.randint(1, 4)
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items = [Item]
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items: [Item] = []
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for i in range(order_size):
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items.append(self.generate_item())
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items.append(InitialStateFactory.__generate_item())
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time_base = random.randint(8, 20)
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final_time = time_base * order_size
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value = sum(i.price for i in items)
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client_params = ClientParamsFactory.get_client_params()
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return Order(final_time, items, value)
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return Order(final_time, items, None, client_params)
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@staticmethod
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def generate_input_sequence(self, input_sequence_size):
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sequence = [Item]
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sequence : [Item] = []
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for i in range(0, input_sequence_size):
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sequence.append(self.__generate_item())
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@ -1,12 +1,12 @@
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from mesa import Agent, Model
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from AgentBase import AgentBase
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from PatchType import PatchType
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from util.PathDefinitions import GridLocation
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class PatchAgent(AgentBase):
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def __init__(self, model, patch_type: PatchType):
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def __init__(self, model, location: GridLocation, patch_type: PatchType):
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self.location = location
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self.patch_type = patch_type
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super().__init__(model)
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@ -7,3 +7,6 @@ class PatchType(enum.Enum):
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item = 3
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wall = 4
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diffTerrain = 5
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packingA = 6
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packingB = 7
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packingC = 8
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|
11
data/Item.py
11
data/Item.py
@ -6,11 +6,10 @@ from data.enum.ItemType import ItemType
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class Item:
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id_counter = count(start=0)
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def __init__(self, type: ItemType):
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def __init__(self, item_type: ItemType):
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self.id = next(self.id_counter)
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self.category = type
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self.price = self.price_factory(type)
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self.real_type = item_type
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self.guessed_type = None
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@staticmethod
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def price_factory(self, type: ItemType):
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return 1
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def __repr__(self) -> str:
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return "|real: {} -- guessed: {}| \n".format(self.real_type, self.guessed_type)
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@ -1,4 +1,5 @@
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from itertools import count
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from typing import List
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from data.ClientParams import ClientParams
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from data.Item import Item
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@ -8,9 +9,12 @@ from data.enum.Priority import Priority
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class Order:
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id_counter = count(start=0)
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def __init__(self, time: int, items: [Item], value: int, priority: Priority, client_params: ClientParams):
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def __init__(self, time: int, items: [Item], priority: Priority, client_params: ClientParams):
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self.id = next(self.id_counter)
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self.time = time
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self.items = items
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self.value = value
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self.items: List[Item] = items
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self.client_params = client_params
|
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self.priority = priority
|
||||
|
||||
def __repr__(self) -> str:
|
||||
return "items: {} priority: {}".format(self.items, self.priority)
|
||||
|
@ -5,4 +5,3 @@ class ItemType(Enum):
|
||||
PIZZA = 1
|
||||
PASTA = 2
|
||||
EGG = 3
|
||||
UNKNOWN = 4
|
9
decision/Action.py
Normal file
9
decision/Action.py
Normal file
@ -0,0 +1,9 @@
|
||||
from data.Item import Item
|
||||
from decision.ActionType import ActionType
|
||||
|
||||
|
||||
class Action:
|
||||
|
||||
def __init__(self, action_type: ActionType, desired_item: Item = None):
|
||||
self.desired_item = desired_item
|
||||
self.action_type = action_type
|
@ -1,25 +0,0 @@
|
||||
from typing import List
|
||||
|
||||
from InitialStateFactory import InitialStateFactory
|
||||
from data.GameConstants import GameConstants
|
||||
from decision.ActionType import ActionType
|
||||
from decision.State import State
|
||||
from util.PathDefinitions import GridLocation
|
||||
|
||||
|
||||
class StateTree:
|
||||
|
||||
def __init__(self, initial_state_factory: InitialStateFactory, game_constants: GameConstants,
|
||||
initial_forklift_position: GridLocation):
|
||||
self.game_constants = game_constants
|
||||
|
||||
parent = State(
|
||||
action_taken=ActionType.NONE,
|
||||
forklift_position=initial_forklift_position,
|
||||
pending_orders=initial_state_factory.generate_order_list(5),
|
||||
filled_orders=[],
|
||||
input_items=initial_state_factory.generate_input_sequence(20)
|
||||
)
|
||||
|
||||
def expansion(self, from_state: State) -> List[State]:
|
||||
return []
|
31
main.py
31
main.py
@ -1,25 +1,15 @@
|
||||
import csv
|
||||
import random
|
||||
|
||||
import pandas
|
||||
import sklearn.tree
|
||||
|
||||
from mesa.visualization.ModularVisualization import ModularServer
|
||||
from mesa.visualization.modules import CanvasGrid
|
||||
from sklearn import metrics, preprocessing
|
||||
from sklearn.model_selection import train_test_split
|
||||
from sklearn.tree import DecisionTreeClassifier
|
||||
|
||||
from ClientParamsFactory import ClientParamsFactory
|
||||
from ForkliftAgent import ForkliftAgent
|
||||
from GameModel import GameModel
|
||||
from PatchAgent import PatchAgent
|
||||
from PatchType import PatchType
|
||||
from data.enum.CompanySize import CompanySize
|
||||
from data.enum.Direction import Direction
|
||||
from data.enum.Priority import Priority
|
||||
from tree.DecisionTree import DecisionTree
|
||||
from util.PathDefinitions import GridWithWeights
|
||||
from visualization.DisplayAttributeElement import DisplayAttributeElement
|
||||
|
||||
colors = [
|
||||
'blue', 'cyan', 'orange', 'yellow', 'magenta', 'purple', '#103d3e', '#9fc86c',
|
||||
@ -63,24 +53,27 @@ def agent_portrayal(agent):
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
|
||||
base = 512
|
||||
gridWidth = 10
|
||||
gridHeight = 10
|
||||
scale = base / gridWidth
|
||||
|
||||
diagram4 = GridWithWeights(gridWidth, gridHeight)
|
||||
diagram4.walls = [(6, 5), (6, 6), (6, 7), (6, 8), (2, 3), (2, 4), (3, 4), (4, 4), (6, 4)]
|
||||
|
||||
diagram5 = GridWithWeights(gridWidth, gridHeight)
|
||||
diagram5.puddles = [(2, 2), (2, 5), (2, 6), (5, 4)]
|
||||
diagram = GridWithWeights(gridWidth, gridHeight)
|
||||
diagram.walls = [(6, 5), (6, 6), (6, 7), (6, 8), (2, 3), (2, 4), (3, 4), (4, 4), (6, 4)]
|
||||
diagram.puddles = [(2, 2), (2, 5), (2, 6), (5, 4)]
|
||||
diagram.packingStations = [(PatchType.packingA, (4, 8)), (PatchType.packingB, (4, 6)), (PatchType.packingC, (4, 2))]
|
||||
|
||||
grid = CanvasGrid(agent_portrayal, gridWidth, gridHeight, scale * gridWidth, scale * gridHeight)
|
||||
|
||||
readyText = DisplayAttributeElement("phase")
|
||||
provided_itesm = DisplayAttributeElement("provided_items")
|
||||
recognised_items = DisplayAttributeElement("recognised_items")
|
||||
ordersText = DisplayAttributeElement("orderList")
|
||||
|
||||
server = ModularServer(GameModel,
|
||||
[grid],
|
||||
[grid, readyText, provided_itesm, recognised_items],
|
||||
"Automatyczny Wózek Widłowy",
|
||||
{"width": gridHeight, "height": gridWidth, "graph": diagram4, "graph2": diagram5},)
|
||||
{"width": gridHeight, "height": gridWidth, "graph": diagram}, )
|
||||
|
||||
server.port = 8888
|
||||
server.launch()
|
||||
|
@ -1,17 +1,23 @@
|
||||
from typing import List
|
||||
|
||||
from data.enum.Direction import Direction
|
||||
from decision.ActionType import ActionType
|
||||
from decision.Action import Action
|
||||
from util.PathDefinitions import GridLocation
|
||||
|
||||
|
||||
class PathFinderState:
|
||||
|
||||
def __init__(self, agent_position: GridLocation, agent_direction: Direction, cost: float,
|
||||
last_action: ActionType, action_taken: List[ActionType]):
|
||||
def __init__(self,
|
||||
agent_position: GridLocation,
|
||||
agent_direction: Direction,
|
||||
cost: float,
|
||||
last_action: Action,
|
||||
action_taken: List[Action],
|
||||
desired_item=None):
|
||||
super().__init__()
|
||||
self.agent_position = agent_position
|
||||
self.agent_direction = agent_direction
|
||||
self.cost = cost
|
||||
self.last_action = last_action
|
||||
self.action_taken = action_taken
|
||||
self.desired_item = desired_item
|
||||
|
@ -1,9 +1,9 @@
|
||||
from typing import List
|
||||
from typing import Tuple
|
||||
|
||||
|
||||
from data.GameConstants import GameConstants
|
||||
from data.enum.Direction import Direction
|
||||
from decision.Action import Action
|
||||
from decision.ActionType import ActionType
|
||||
from pathfinding.PathFinderState import PathFinderState
|
||||
from pathfinding.PrioritizedItem import PrioritizedItem
|
||||
@ -53,9 +53,9 @@ class PathFinderOnStates:
|
||||
else:
|
||||
return True
|
||||
|
||||
def create_state(self, curr_state: PathFinderState, action: ActionType) -> PathFinderState:
|
||||
def create_state(self, curr_state: PathFinderState, action: Action) -> PathFinderState:
|
||||
|
||||
if action == action.MOVE:
|
||||
if action == action.action_type.MOVE:
|
||||
if curr_state.agent_position in self.game_constants.diffTerrain:
|
||||
cost = curr_state.cost + 20
|
||||
# tutaj koszt kaluzy
|
||||
@ -66,21 +66,21 @@ class PathFinderOnStates:
|
||||
cost = curr_state.cost + 10
|
||||
|
||||
last_action = action
|
||||
action_taken: List[ActionType] = []
|
||||
action_taken: List[Action] = []
|
||||
action_taken.extend(curr_state.action_taken)
|
||||
action_taken.append(last_action)
|
||||
agent_position = curr_state.agent_position
|
||||
agent_direction = curr_state.agent_direction
|
||||
|
||||
if action == ActionType.ROTATE_UP:
|
||||
if action.action_type == ActionType.ROTATE_UP:
|
||||
agent_direction = Direction.top
|
||||
elif action == ActionType.ROTATE_DOWN:
|
||||
elif action.action_type == ActionType.ROTATE_DOWN:
|
||||
agent_direction = Direction.down
|
||||
elif action == ActionType.ROTATE_LEFT:
|
||||
elif action.action_type == ActionType.ROTATE_LEFT:
|
||||
agent_direction = Direction.left
|
||||
elif action == ActionType.ROTATE_RIGHT:
|
||||
elif action.action_type == ActionType.ROTATE_RIGHT:
|
||||
agent_direction = Direction.right
|
||||
elif action == ActionType.MOVE:
|
||||
elif action.action_type == ActionType.MOVE:
|
||||
agent_position = self.get_position_after_move(curr_state)
|
||||
|
||||
return PathFinderState(agent_position, agent_direction, cost, last_action, action_taken)
|
||||
@ -93,31 +93,31 @@ class PathFinderOnStates:
|
||||
# sprawdz w ktorym kierunku obrocony
|
||||
possible_next_states: List[PathFinderState] = []
|
||||
if self.is_move_possible(curr_state):
|
||||
possible_next_states.append(self.create_state(curr_state, ActionType.MOVE))
|
||||
possible_next_states.append(self.create_state(curr_state, Action(ActionType.MOVE)))
|
||||
|
||||
if curr_state.agent_direction == Direction.top:
|
||||
possible_next_states.append(self.create_state(curr_state, ActionType.ROTATE_RIGHT))
|
||||
possible_next_states.append(self.create_state(curr_state, ActionType.ROTATE_LEFT))
|
||||
possible_next_states.append(self.create_state(curr_state, ActionType.ROTATE_DOWN))
|
||||
possible_next_states.append(self.create_state(curr_state, Action(ActionType.ROTATE_RIGHT)))
|
||||
possible_next_states.append(self.create_state(curr_state, Action(ActionType.ROTATE_LEFT)))
|
||||
possible_next_states.append(self.create_state(curr_state, Action(ActionType.ROTATE_DOWN)))
|
||||
|
||||
elif curr_state.agent_direction == Direction.down:
|
||||
possible_next_states.append(self.create_state(curr_state, ActionType.ROTATE_RIGHT))
|
||||
possible_next_states.append(self.create_state(curr_state, ActionType.ROTATE_LEFT))
|
||||
possible_next_states.append(self.create_state(curr_state, ActionType.ROTATE_UP))
|
||||
possible_next_states.append(self.create_state(curr_state, Action(ActionType.ROTATE_RIGHT)))
|
||||
possible_next_states.append(self.create_state(curr_state, Action(ActionType.ROTATE_LEFT)))
|
||||
possible_next_states.append(self.create_state(curr_state, Action(ActionType.ROTATE_UP)))
|
||||
|
||||
elif curr_state.agent_direction == Direction.left:
|
||||
possible_next_states.append(self.create_state(curr_state, ActionType.ROTATE_RIGHT))
|
||||
possible_next_states.append(self.create_state(curr_state, ActionType.ROTATE_UP))
|
||||
possible_next_states.append(self.create_state(curr_state, ActionType.ROTATE_DOWN))
|
||||
possible_next_states.append(self.create_state(curr_state, Action(ActionType.ROTATE_RIGHT)))
|
||||
possible_next_states.append(self.create_state(curr_state, Action(ActionType.ROTATE_UP)))
|
||||
possible_next_states.append(self.create_state(curr_state, Action(ActionType.ROTATE_DOWN)))
|
||||
|
||||
elif curr_state.agent_direction == Direction.right:
|
||||
possible_next_states.append(self.create_state(curr_state, ActionType.ROTATE_UP))
|
||||
possible_next_states.append(self.create_state(curr_state, ActionType.ROTATE_LEFT))
|
||||
possible_next_states.append(self.create_state(curr_state, ActionType.ROTATE_DOWN))
|
||||
possible_next_states.append(self.create_state(curr_state, Action(ActionType.ROTATE_UP)))
|
||||
possible_next_states.append(self.create_state(curr_state, Action(ActionType.ROTATE_LEFT)))
|
||||
possible_next_states.append(self.create_state(curr_state, Action(ActionType.ROTATE_DOWN)))
|
||||
|
||||
return possible_next_states
|
||||
|
||||
def get_action_list(self) -> List[ActionType]:
|
||||
def get_action_list(self) -> List[Action]:
|
||||
already_visited = {}
|
||||
|
||||
while not self.queue.empty():
|
||||
|
@ -6,7 +6,7 @@ from sklearn import metrics, preprocessing
|
||||
from sklearn.model_selection import train_test_split
|
||||
from sklearn.tree import DecisionTreeClassifier
|
||||
|
||||
from ClientParamsFactory import ClientParamsFactory
|
||||
from util.ClientParamsFactory import ClientParamsFactory
|
||||
|
||||
|
||||
class DecisionTree:
|
||||
|
@ -3,21 +3,21 @@ import random
|
||||
from data.ClientParams import ClientParams
|
||||
from data.enum.CompanySize import CompanySize
|
||||
|
||||
|
||||
class ClientParamsFactory:
|
||||
|
||||
def __init__(self) -> None:
|
||||
super().__init__()
|
||||
|
||||
def getTrueMore(self, perOfTrue: int) -> bool:
|
||||
custom = random.randint(0, perOfTrue)
|
||||
@staticmethod
|
||||
def getTrueMore(per_of_true: int) -> bool:
|
||||
custom = random.randint(0, per_of_true)
|
||||
|
||||
return custom > 0
|
||||
|
||||
def get_client_params(self) -> ClientParams:
|
||||
@staticmethod
|
||||
def get_client_params() -> ClientParams:
|
||||
payment_delay = random.randint(0, 14)
|
||||
payed = self.getTrueMore(5)
|
||||
payed = ClientParamsFactory.getTrueMore(5)
|
||||
net_worth = random.randint(0, 100)
|
||||
is_skarbowka = not self.getTrueMore(5)
|
||||
is_skarbowka = not ClientParamsFactory.getTrueMore(5)
|
||||
membership = random.getrandbits(1)
|
||||
infuelnce_rate = random.randint(0, 100)
|
||||
is_hat = random.getrandbits(1)
|
@ -1,5 +1,7 @@
|
||||
from typing import Iterator, Protocol, List, TypeVar, Tuple, Dict
|
||||
|
||||
from PatchType import PatchType
|
||||
|
||||
GridLocation = Tuple[int, int]
|
||||
Location = TypeVar('Location')
|
||||
|
||||
@ -14,6 +16,7 @@ class SquareGrid:
|
||||
self.height = height
|
||||
self.walls: List[GridLocation] = []
|
||||
self.puddles: List[GridLocation] = []
|
||||
self.packingStations: List[tuple[PatchType, GridLocation]] = []
|
||||
|
||||
def in_bounds(self, id: GridLocation) -> bool:
|
||||
(x, y) = id
|
||||
|
18
visualization/DisplayAttributeElement.py
Normal file
18
visualization/DisplayAttributeElement.py
Normal file
@ -0,0 +1,18 @@
|
||||
from mesa.visualization.modules import TextElement
|
||||
|
||||
|
||||
class DisplayAttributeElement(TextElement):
|
||||
def __init__(self, attr_name):
|
||||
'''
|
||||
Create a new text attribute element.
|
||||
|
||||
Args:
|
||||
attr_name: The name of the attribute to extract from the model.
|
||||
|
||||
Example return: "happy: 10"
|
||||
'''
|
||||
self.attr_name = attr_name
|
||||
|
||||
def render(self, model):
|
||||
val = getattr(model, self.attr_name)
|
||||
return self.attr_name + ": " + str(val)
|
Loading…
Reference in New Issue
Block a user