50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
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from collections import deque
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import heapq
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class AStar:
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def __init__(self, cells):
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self.cells = cells
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def heuristic(self, current, target):
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# Euclidean distance heuristic
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dx = abs(current[0] - target[0])
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dy = abs(current[1] - target[1])
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return dx + dy
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def get_neighbors(self, cell):
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neighbors = []
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x, y = cell[0], cell[1]
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if x > 0 and not self.cells[x - 1][y].blocking_movement:
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neighbors.append((x - 1, y))
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if x < len(self.cells) - 1 and not self.cells[x + 1][y].blocking_movement:
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neighbors.append((x + 1, y))
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if y > 0 and not self.cells[x][y - 1].blocking_movement:
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neighbors.append((x, y - 1))
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if y < len(self.cells[x]) - 1 and not self.cells[x][y + 1].blocking_movement:
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neighbors.append((x, y + 1))
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return neighbors
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def astar(self, start, target):
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open_list = [(0, start)]
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came_from = {}
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g_score = {start: 0}
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while open_list:
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_, current = heapq.heappop(open_list)
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if current == target:
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path = []
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while current in came_from:
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path.append(current)
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current = came_from[current]
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return path[::-1]
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for neighbor in self.get_neighbors(current):
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tentative_g_score = g_score[current] + 1
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if tentative_g_score < g_score.get(neighbor, float('inf')):
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came_from[neighbor] = current
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g_score[neighbor] = tentative_g_score
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f_score = tentative_g_score + self.heuristic(neighbor, target)
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heapq.heappush(open_list, (f_score, neighbor))
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return []
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