225 lines
11 KiB
Python
225 lines
11 KiB
Python
import heapq # dla utrzymania fringe
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from classes import node, minesweeper, system
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class BFS:
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window: system.Window
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agent: minesweeper.Minesweeper
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node: node.Node
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def __init__(self, agent, window):
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self.agent = agent
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self.window = window
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def successor(self, current_position):
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new_nodes = []
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neighbours_list = self.agent.sensor(current_position[0], current_position[1])
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if current_position[2] == 180: # jesli patrzy na polnoc
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if neighbours_list[0][1] not in ['wall', 'cliff_south', 'cliff_east', 'cliff_north', 'cliff_west']:
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if neighbours_list[0][1] == 'slowfloor':
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cost = 3
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elif neighbours_list[0][1] == 'floor':
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cost = 2
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elif neighbours_list[0][1] == 'encounter':
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cost = 0
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tmp = ('forward', [current_position[0], current_position[1] - 1, 180], cost)
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new_nodes.append(tmp)
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if neighbours_list[1][0] not in ['wall', 'cliff_south', 'cliff_east', 'cliff_north', 'cliff_west']:
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# if neighbours_list[1][0] == 'slowfloor':
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# cost = 10
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# elif neighbours_list[1][0] == 'floor':
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# cost = 2
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# elif neighbours_list[1][0] == 'encounter':
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# cost = 0
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tmp = ('left', [current_position[0], current_position[1], 270], 1)
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new_nodes.append(tmp)
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if neighbours_list[1][2] not in ['wall', 'cliff_south', 'cliff_east', 'cliff_north', 'cliff_west']:
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# if neighbours_list[1][2] == 'slowfloor':
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# cost = 10
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# elif neighbours_list[1][2] == 'floor':
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# cost = 2
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# elif neighbours_list[1][2] == 'encounter':
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# cost = 0
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tmp = ('right', [current_position[0], current_position[1], 90], 1)
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new_nodes.append(tmp)
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if current_position[2] == 90: # jesli patrzy na wschod
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if neighbours_list[1][2] not in ['wall', 'cliff_south', 'cliff_east', 'cliff_north', 'cliff_west']:
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if neighbours_list[1][2] == 'slowfloor':
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cost = 3
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elif neighbours_list[1][2] == 'floor':
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cost = 2
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elif neighbours_list[1][2] == 'encounter':
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cost = 0
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tmp = ('forward', [current_position[0] + 1, current_position[1], 90], cost)
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new_nodes.append(tmp)
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if neighbours_list[0][1] not in ['wall', 'cliff_south', 'cliff_east', 'cliff_north', 'cliff_west']:
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# if neighbours_list[0][1] == 'slowfloor':
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# cost = 10
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# elif neighbours_list[0][1] == 'floor':
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# cost = 2
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# elif neighbours_list[0][1] == 'encounter':
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# cost = 0
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tmp = ('left', [current_position[0], current_position[1], 180], 1)
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new_nodes.append(tmp)
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if neighbours_list[2][1] not in ['wall', 'cliff_south', 'cliff_east', 'cliff_north', 'cliff_west']:
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# if neighbours_list[2][1] == 'slowfloor':
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# cost = 10
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# elif neighbours_list[2][1] == 'floor':
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# cost = 2
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# elif neighbours_list[2][1] == 'encounter':
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# cost = 0
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tmp = ('right', [current_position[0], current_position[1], 0], 1)
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new_nodes.append(tmp)
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if current_position[2] == 0: # jesli patczy na poludzie
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if neighbours_list[2][1] not in ['wall', 'cliff_south', 'cliff_east', 'cliff_north', 'cliff_west']:
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if neighbours_list[2][1] == 'slowfloor':
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cost = 3
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elif neighbours_list[2][1] == 'floor':
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cost = 2
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elif neighbours_list[2][1] == 'encounter':
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cost = 0
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tmp = ('forward', [current_position[0], current_position[1] + 1, 0], cost)
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new_nodes.append(tmp)
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if neighbours_list[1][2] not in ['wall', 'cliff_south', 'cliff_east', 'cliff_north', 'cliff_west']:
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# if neighbours_list[1][2] == 'slowfloor':
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# cost = 10
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# elif neighbours_list[1][2] == 'floor':
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# cost = 2
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# elif neighbours_list[1][2] == 'encounter':
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# cost = 0
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tmp = ('left', [current_position[0], current_position[1], 90], 1)
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new_nodes.append(tmp)
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if neighbours_list[1][0] not in ['wall', 'cliff_south', 'cliff_east', 'cliff_north', 'cliff_west']:
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# if neighbours_list[1][0] == 'slowfloor':
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# cost = 10
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# elif neighbours_list[1][0] == 'floor':
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# cost = 2
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# elif neighbours_list[1][0] == 'encounter':
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# cost = 0
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tmp = ('right', [current_position[0], current_position[1], 270], 1)
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new_nodes.append(tmp)
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if current_position[2] == 270: # jesli patczy na wschod
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if neighbours_list[1][0] not in ['wall', 'cliff_south', 'cliff_east', 'cliff_north', 'cliff_west']:
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if neighbours_list[1][0] == 'slowfloor':
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cost = 3
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elif neighbours_list[1][0] == 'floor':
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cost = 2
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elif neighbours_list[1][0] == 'encounter':
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cost = 0
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tmp = ('forward', [current_position[0] - 1, current_position[1], 270], cost)
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new_nodes.append(tmp)
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if neighbours_list[2][1] not in ['wall', 'cliff_south', 'cliff_east', 'cliff_north', 'cliff_west']:
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# if neighbours_list[2][1] == 'slowfloor':
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# cost = 10
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# elif neighbours_list[2][1] == 'floor':
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# cost = 2
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# elif neighbours_list[2][1] == 'encounter':
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# cost = 0
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tmp = ('left', [current_position[0], current_position[1], 0], 1)
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new_nodes.append(tmp)
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if neighbours_list[0][1] not in ['wall', 'cliff_south', 'cliff_east', 'cliff_north', 'cliff_west']:
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# if neighbours_list[0][1] == 'slowfloor':
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# cost = 10
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# elif neighbours_list[0][1] == 'floor':
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# cost = 2
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# elif neighbours_list[0][1] == 'encounter':
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# cost = 0
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tmp = ('right', [current_position[0], current_position[1], 180], 1)
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new_nodes.append(tmp)
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return new_nodes
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# fringe = struktura danych przeszowyjąca wierchowki do odwiedzenia
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# explored = lista odwiedzonych stanow
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# position_at_beginning = stan poczatkowy
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# succ = funkcja nastempnika
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# goaltest = test spewnienia celu
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def graphsearch(self, fringe, explored, succ, goaltest):
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def manhattan(state, target_state):
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return abs(state[0] - target_state[0]) + abs(state[1] - target_state[1])
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self.window.pause(True)
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position_at_beginning = [self.agent.position_x, self.agent.position_y,
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self.agent.rotation_degrees] # x, y, gdzie_patczy
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final_action_list = [] # lista co ma robic zeby dojechac do miny
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root = node.Node(None, None, position_at_beginning, 2) # parent, action, position, cost
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heapq.heappush(fringe, (0, root)) # add first node to fringe
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while len(fringe) != 0: # poki sa wezly do odwiedzenia(na fringe)
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if len(fringe) == 0:
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return False
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# get node from fringe
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tmp_node = heapq.heappop(fringe) # tuple(priority, node)
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tmp_node_position = tmp_node[1].get_position() # x, y , gdzie patczy
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# jesli tmp node to goaltest
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if tmp_node_position[:2] == goaltest:
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print('Find\n')
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while tmp_node[1].get_parent() is not None:
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final_action_list.append(tmp_node[1].get_action())
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tmp_node = tmp_node[1].get_parent()
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final_action_list.reverse()
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# print(final_action_list)
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self.window.pause(False)
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return final_action_list
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explored.append(tmp_node[1]) # add node to array of visited nodes
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neighbours_list_of_our_node = self.successor(tmp_node_position) # lista możliwych akcij
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# print(neighbours_list_of_our_node)
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for node_ in neighbours_list_of_our_node:
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# node_ is tuple(action, [x, y, gdzie_patczy], cost)
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notInFringe = True # false if node in fringe
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notInExplored = True # false if node in explored
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p = manhattan(node_[1], goaltest) + node_[2]
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# wyznacza jaki jest priorytet nastempnika
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# manchaten from node_ + cost of way from tmp_ode to node_
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priority_in_fringe = 0
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counter = 0
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index_of_node_in_fringe = 0 # zero if node not in fringe
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for fringeNode in fringe: # isc po wszystkich wezlach ktore juz sa w fringe
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# jesli nasz wezel juz jest w fringe
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if fringeNode[1].get_position()[0] == node_[1][0] and fringeNode[1].get_position()[1] == node_[1][
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1] and fringeNode[1].get_position()[2] == node_[1][2]:
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notInFringe = False
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priority_in_fringe = fringeNode[0]
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# number of element in fringe
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index_of_node_in_fringe = counter
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counter = counter + 1
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for exploredNode in explored: # isc po wszystkich wezlach z listy explored
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# jesli nasz wezel juz jest w explored
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if exploredNode.get_position()[0] == node_[1][0] and exploredNode.get_position()[1] == node_[1][
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1] and exploredNode.get_position()[2] == node_[1][2]:
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notInExplored = False
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# if node not in fringe and not in explored
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if notInFringe and notInExplored:
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x = node.Node(tmp_node, node_[0], node_[1], node_[2]) # parent, action, state_array, cost
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heapq.heappush(fringe, (p, x))
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# if node not in fringe
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elif notInFringe is False and (priority_in_fringe > p):
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x = node.Node(tmp_node, node_[0], node_[1], node_[2]) # parent, action, state_array, cost
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tmp = list(fringe[index_of_node_in_fringe])
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tmp[0] = p
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tmp[1] = x
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fringe[index_of_node_in_fringe] = tuple(tmp)
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self.window.draw_search([self.agent.position_x, self.agent.position_y], [node_[1][0], node_[1][1]],
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self.agent.current_map.tile_size, self.agent.current_map, self.agent)
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