132 lines
5.2 KiB
Python
132 lines
5.2 KiB
Python
from utilities import movement,check_moves
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from DataModels.House import House
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from DataModels.Container import Container
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from config import GRID_WIDTH, GRID_HEIGHT
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from math import sqrt
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INF = float('Inf')
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def CalculateDistance(gc, object_list):
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min_distance_goal = ['-',INF]
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for h in object_list:
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distance = sqrt(pow(h[1][0]-gc[0],2)+pow(h[1][1]-gc[1],2))
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if(min_distance_goal[1] > distance):
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min_distance_goal = [h[1], distance]
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return min_distance_goal
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def BestFS(grid, gc_moveset, object_list):
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print(gc_moveset)
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x, y = gc_moveset[-1][0], gc_moveset[-1][1]
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available_movement = check_moves(grid, x, y)
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if(len(object_list) == 0):
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return gc_moveset
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decision_stack = []
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constraint = 100
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while(len(object_list) > 0 and constraint > 0):
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print("================")
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print("iteracja: "+str(100-constraint))
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print("GC: "+str([x,y]))
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print(object_list)
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#calculate distance to the nearest object
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min_distance_goal = CalculateDistance([x,y], object_list)
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print(min_distance_goal)
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#check if can pick garbage
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if(min_distance_goal[1] == 1):
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gc_moveset.append("pick_garbage")
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decision_stack = []
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#remove object from goals list
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cell = grid[min_distance_goal[0][0]][min_distance_goal[0][1]]
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print("***"+str([cell,min_distance_goal[0]])+"***")
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object_list.remove([cell,min_distance_goal[0]])
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#if that was the last object, return
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if(len(object_list)==0):
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break
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#look for a new goal
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available_movement = check_moves(grid, x, y)
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min_distance_goal = CalculateDistance([x,y], object_list)
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print(min_distance_goal)
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print(min_distance_goal[0])
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#set preffered directions based on the closest object
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preffered_directions = []
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discouraged_directions = []
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if(min_distance_goal[0][0] > x):
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preffered_directions.append("right")
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if(min_distance_goal[0][0] < x):
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preffered_directions.append("left")
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if(min_distance_goal[0][1] > y):
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preffered_directions.append("down")
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if(min_distance_goal[0][1] < y):
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preffered_directions.append("up")
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if(len(preffered_directions) == 1):
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discouraged_directions.append(movement(grid, x, y)[1][preffered_directions[0]])
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print("Preferred: "+str(preffered_directions))
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print("Discouraged: "+str(discouraged_directions))
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print("Available: "+str(available_movement))
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#if agent finds more than 1 optimal route
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possible_routes = len([i for i in available_movement if i in preffered_directions ])
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print("Preferred to available count: "+str(possible_routes))
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#HOTFIX
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if(possible_routes > 1):
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if(len(decision_stack) > 0):
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if(decision_stack[0] == [x,y]):
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preffered_directions.pop(1)
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else:
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decision_stack = [[x,y]]
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preffered_directions.pop(0)
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print("Decision stack: "+str(decision_stack))
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""" if(possible_routes > 1):
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for move in available_movement:
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if (move in preffered_directions):
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x_next, y_next = movement(grid, x, y)[0][move]
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route = BestFS(grid, [x_next,y_next], houses_list, [[x_next, y_next]], check_moves(grid, x_next, y_next, move), "House", depth + 1)
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print("DIRECTION: "+str(move)+", GIVEN "+str(len(houses_list))+" HOUSES, RECURSION ON DEPTH "+str(depth+1)+" returned "+str(route))
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if (route == None):
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break
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if (route.count("pick_garbage") - 1 == len(houses_list)):
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print(str(route.count("pick_garbage"))+" / "+str(len(houses_list)))
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print("ROUTE ADDED")
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gc_moveset.extend(route)
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break
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break """
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#if got no available moves but still has goals to visit
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if(len(available_movement) == 0):
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available_movement = check_moves(grid, x, y)
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#selecting next move based on preferences (starting with the worst option)
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if(len(available_movement)>0):
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next_move = available_movement[0] #pick any
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for move in available_movement:
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if (move not in discouraged_directions): #pick any not discouraged move if possible
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next_move = move
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break
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for move in preffered_directions:
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if(move in available_movement): #pick any preferred move if possible
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next_move = move
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break
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print("Next move: "+str(next_move))
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x_next, y_next = movement(grid, x, y)[0][next_move]
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print("Next moving to "+str(x_next)+" "+str(y_next))
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gc_moveset.append([x_next,y_next])
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x, y = x_next, y_next
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available_movement = check_moves(grid, x, y, next_move)
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print("------------------------------")
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constraint -= 1
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return gc_moveset, [x,y]
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