SI_InteligentnyWozekWidlowy/GameModel.py

import copy
from enum import Enum
from typing import List, Tuple

from mesa import Model
from mesa.space import MultiGrid
from mesa.time import RandomActivation

from AgentBase import AgentBase
from ForkliftAgent import ForkliftAgent
from InitialStateFactory import InitialStateFactory
from ItemDisplayAgent import ItemDisplayAgent
from PatchAgent import PatchAgent
from PatchType import PatchType
from PictureVisualizationAgent import PictureVisualizationAgent
from data.GameConstants import GameConstants
from data.Item import Item
from data.Order import Order
from data.enum.ItemType import ItemType
from decision.Action import Action
from decision.ActionType import ActionType
from genetic_order.GeneticOrder import GeneticOrder
from imageClasification.Classificator import image_classification
from pathfinding.PathfinderOnStates import PathFinderOnStates, PathFinderState
from tree.DecisionTree import DecisionTree
from util.PathByEnum import PathByEnum
from util.PathDefinitions import GridLocation, GridWithWeights


class Phase(Enum):
    INIT = 1
    ITEM_RECOGNITION = 2
    CLIENT_SORTING = 3
    PLAN_MOVEMENT = 4
    EXECUTION = 5


class GameModel(Model):

    def __init__(self, width, height, graph: GridWithWeights, items: int, orders: int, classificator,
                 item_display_pos: List[GridLocation]):

        # self.num_agents = 5
        self.first = True
        self.item_recognised = False
        self.running = True
        self.grid = MultiGrid(height, width, True)
        self.schedule = RandomActivation(self)
        self.current_item_recognition = None
        self.current_item = None

        self.client_delivery: PatchAgent = None
        self.drop_off: PatchAgent = None
        self.graph = graph
        self.cut_orders : List[Order] = []

        self.game_constants = GameConstants(
            width,
            height,
            graph.walls,
            graph.puddles
        )

        self.agents = [AgentBase]

        self.forklift_agent = ForkliftAgent(
            self,
            self.game_constants,
            self.client_delivery,
            self.drop_off,
            self.graph
        )

        self.schedule.add(self.forklift_agent)
        self.agents.append(self.forklift_agent)
        self.item_display_agents: List[ItemDisplayAgent] = []

        # INITIALIZATION #
        print("############## INITIALIZATION ##############")
        self.phase = Phase.INIT
        self.initialize_grid(graph, item_display_pos)
        self.orderList: List[Order] = InitialStateFactory.generate_order_list(orders)
        self.fulfilled_orders: List[Order] = []
        self.forklift_agent.fulfilled_orders = self.fulfilled_orders
        self.forklift_agent.set_base(self.drop_off)
        self.classificator = classificator

        print("############## RECOGNISE ITEMS ##############")
        self.phase = Phase.ITEM_RECOGNITION
        self.provided_items = InitialStateFactory.generate_item_list(items)
        self.items_for_recognization = copy.deepcopy(self.provided_items)
        self.recognised_items: List[Item] = []

        self.current_order_delivered_items = self.forklift_agent.current_order_delivered_items

        print("Relocate forklift agent to loading area for item recognition")

        pathFinder = PathFinderOnStates(
            self.game_constants,
            self.drop_off.location,
            PathFinderState(self.forklift_agent.current_position, self.forklift_agent.current_rotation, 0,
                            Action(ActionType.NONE), [])
        )

        actions = pathFinder.get_action_list()
        print("PATHFINDING")
        print(actions)
        self.forklift_agent.queue_movement_actions(actions)
        self.current_order = self.forklift_agent.current_order

    def initialize_grid(self, graph: GridWithWeights, item_display_pos):
        print("INITIALIZING GRID")
        # Add the agent to a random grid cell
        x = 5
        y = 5
        self.grid.place_agent(self.forklift_agent, (x, y))
        self.forklift_agent.current_position = (x, y)

        self.picture_visualization = PictureVisualizationAgent(
            self,
            (1, 11),
        )
        self.schedule.add(self.picture_visualization)
        self.grid.place_agent(self.picture_visualization, self.picture_visualization.location)
        self.agents.append(self.picture_visualization)

        self.place_logistics()
        self.place_dividers()
        self.place_walls_agents(graph.walls)
        self.place_puddles(graph.puddles)
        self.place_packing_stations(graph.packingStations)
        self.place_order_items_display(item_display_pos)

    def place_dividers(self):
        for i in range(0, 10):
            for j in range(10, 13):
                agent = PatchAgent(self, (i, j), PatchType.divider)
                self.agents.append(agent)
                self.grid.place_agent(agent, (i, j))

    def place_logistics(self):
        agent = PatchAgent(self, (self.grid.width - 1, int(self.grid.height / 2)), PatchType.pickUp)
        self.schedule.add(agent)
        self.grid.place_agent(agent, agent.location)
        self.agents.append(agent)
        self.client_delivery = agent
        self.forklift_agent.client_delivery = self.client_delivery

        agent = PatchAgent(self, (0, int(self.grid.height / 2)), PatchType.dropOff)
        self.grid.place_agent(agent, agent.location)
        self.agents.append(agent)
        self.drop_off = agent
        self.forklift_agent.drop_off = self.drop_off

    def place_walls_agents(self, walls: List[GridLocation]):
        for w in walls:
            agent = PatchAgent(self, w, PatchType.wall)
            self.agents.append(agent)
            self.grid.place_agent(agent, w)

    def place_puddles(self, puddles: List[GridLocation]):
        for p in puddles:
            agent = PatchAgent(self, p, PatchType.diffTerrain)
            self.agents.append(agent)
            self.grid.place_agent(agent, p)

    def place_packing_stations(self, packing_stations: List[Tuple[PatchType, GridLocation]]):
        for p in packing_stations:
            agent = PatchAgent(self, p[1], p[0])
            self.agents.append(agent)
            self.grid.place_agent(agent, p[1])

    def place_order_items_display(self, item_positions: List[GridLocation]):
        for p in item_positions:
            agent = ItemDisplayAgent(self, p)
            self.item_display_agents.append(agent)
            self.grid.place_agent(agent, p)

    def update_item_display(self):
        self.current_item = self.forklift_agent.current_item
        for i in range(4):
            self.item_display_agents[i].image = None
            if len(self.forklift_agent.current_order_delivered_items) > i:
                self.item_display_agents[i].image = self.forklift_agent.current_order_delivered_items[i].image

    def step(self):
        self.schedule.step()
        self.grid.remove_agent(self.forklift_agent)
        self.grid.place_agent(self.forklift_agent, self.forklift_agent.current_position)
        self.update_item_display()

        if self.phase == Phase.ITEM_RECOGNITION:
            if not self.item_recognised and self.forklift_agent.current_position == self.drop_off.location:

                if len(self.items_for_recognization) == 0:
                    print("FINISHED ITEM RECOGNITION")
                    self.item_recognised = True
                    self.phase = Phase.CLIENT_SORTING
                    self.forklift_agent.ready_for_execution = True
                else:
                    print("BEGIN ITEM RECOGNITION, left: {}".format(len(self.items_for_recognization)))
                    item_to_recognise = self.items_for_recognization.pop()
                    self.picture_visualization.img = PathByEnum.get_random_path(item_to_recognise.real_type)
                    recognised = self.recognise_item(item_to_recognise)
                    self.recognised_items.append(recognised)

        if self.phase == Phase.CLIENT_SORTING:
            orders: [Order] = self.orderList
            tree: DecisionTree = DecisionTree()

            # CLIENT RECOGNITION
            orders_with_prio = tree.get_data_good(orders)

            # print("before:" )
            # for i in range(len(orders_with_prio)):
            #     print("ORDER {}, PRIO: {}".format(orders_with_prio[i].id, orders_with_prio[i].priority))

            # GENERICS SORTING
            genericOrder: GeneticOrder = GeneticOrder(orders_with_prio)
            new_orders = genericOrder.get_orders_sorted(orders)

            # print("after:" )
            # for i in range(len(new_orders)):
            #     print("ORDER {}, PRIO: {}".format(new_orders[i].id, new_orders[i].priority))

            self.orderList = new_orders
            self.forklift_agent.orderList = self.orderList

            print("FINISHED CLIENT ORDER SORTING")
            self.phase = Phase.EXECUTION

        if self.phase == Phase.EXECUTION:
            self.current_order = self.forklift_agent.current_order
            pass
            # print("Execution")

    def recognise_item(self, item: Item):
        val = image_classification(self.picture_visualization.img, self.classificator)
        print("VAL: {}".format(val))

        if val == ItemType.DOOR:
            item.guessed_type = ItemType.DOOR
        elif val == ItemType.REFRIGERATOR:
            item.guessed_type = ItemType.REFRIGERATOR
        elif val == ItemType.SHELF:
            item.guessed_type = ItemType.SHELF

        return item