简化二维网格上的路径

import heapq

def heuristic(a, b):
    return abs(a[0] - b[0]) + abs(a[1] - b[1])

def astar(grid, start, end):
    neighbors = [(0, 1), (0, -1), (1, 0), (-1, 0)]
    close_set = set()
    came_from = {}
    gscore = {start: 0}
    fscore = {start: heuristic(start, end)}
    oheap = []

    heapq.heappush(oheap, (fscore[start], start))

    while oheap:
        current = heapq.heappop(oheap)[1]

        if current == end:
            data = []
            while current in came_from:
                data.append(current)
                current = came_from[current]
            return data[::-1]

        close_set.add(current)
        for i, j in neighbors:
            neighbor = current[0] + i, current[1] + j
            tentative_g_score = gscore[current] + heuristic(current, neighbor)

            if 0 <= neighbor[0] < len(grid) and 0 <= neighbor[1] < len(grid[0]):
                if grid[neighbor[0]][neighbor[1]] == 1:
                    continue
            else:
                continue

            if neighbor in close_set and tentative_g_score >= gscore.get(neighbor, 0):
                continue

            if tentative_g_score < gscore.get(neighbor, 0) or neighbor not in [i[1] for i in oheap]:
                came_from[neighbor] = current
                gscore[neighbor] = tentative_g_score
                fscore[neighbor] = tentative_g_score + heuristic(neighbor, end)
                heapq.heappush(oheap, (fscore[neighbor], neighbor))

    return False

# 示例网格
grid = [
    [0, 0, 0, 0, 1],
    [1, 1, 0, 1, 0],
    [0, 0, 0, 0, 0],
    [0, 1, 1, 1, 0],
    [0, 0, 0, 0, 0]
]

start = (0, 0)
end = (4, 4)

path = astar(grid, start, end)
print(path)