63 lines
1.7 KiB
Python
63 lines
1.7 KiB
Python
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import heapq
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class PriorityQueue:
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def __init__(self):
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self.elements = []
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def put(self, item, priority):
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heapq.heappush(self.elements, (priority, item))
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def get(self):
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return heapq.heappop(self.elements)[1]
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def heuristic(xy1, xy2):
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return abs(xy1[0] - xy2[0]) + abs(xy1[1] - xy2[1])
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def neighbors(point):
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x, y = point
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list=((x+1,y), (x,y+1), (x,y-1), (x-1,y))
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return list
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#determining the cost of a specific field in the grid
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def checkCost(grid, xy):
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x, y = xy
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cost = grid[x][y]
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return cost
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def aStar(grid, start, goal):
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openlist = PriorityQueue()
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openlist.put(start, 0)
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fScore = {}
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origin = {start: None}
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fScore[start] = 0
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closedlist=[]
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cost=0
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while openlist!={}:
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current = openlist.get()
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if current == goal:
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path = []
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#following from the succesors to the root our starting point
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while current != start:
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path.append(current)
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current = origin[current]
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path.reverse()
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break
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# succescor function
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for succ in neighbors(current):
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#checking if didn't go out of the maze
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if(succ[0] < 0 or succ[1] < 0 or succ[0] > 19 or succ[1] > 19):
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continue
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gScore = fScore[current[0],current[1]] + checkCost(grid, current)
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if succ not in closedlist or gScore < fScore[succ[0],succ[1]]:
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closedlist.append(succ)
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origin[succ[0],succ[1]] = current
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fScore[succ[0],succ[1]] = gScore
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priority = gScore + heuristic(goal, succ)
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openlist.put(succ, priority)
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return path
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