dijkstra滑行路径算法的代码

以下是Dijkstra滑行路径算法的示例Python代码：

import heapq

def dijkstra(start, graph):
    queue = [(0, start)]
    visited = set()
    distances = {start: 0}
    while queue:
        (cost, current) = heapq.heappop(queue)
        if current in visited:
            continue
        visited.add(current)
        for neighbor, weight in graph[current].items():
            if neighbor in visited:
                continue
            if neighbor not in distances or cost + weight < distances[neighbor]:
                distances[neighbor] = cost + weight
                heapq.heappush(queue, (distances[neighbor], neighbor))
    return distances

def get_path(start, end, graph):
    distances = dijkstra(start, graph)
    path = [end]
    while path[-1] != start:
        current = path[-1]
        neighbors = graph[current]
        neighbor_distances = [(distances[neighbor], neighbor) for neighbor in neighbors if neighbor in distances]
        if not neighbor_distances:
            return None
        nearest_neighbor_distance, nearest_neighbor = min(neighbor_distances)
        if nearest_neighbor_distance >= distances[current]:
            return None
        path.append(nearest_neighbor)
    path.reverse()
    return path

其中，输入参数`start`表示起点，`end`表示终点，`graph`表示带权图，其格式为字典嵌套字典，例如：

graph = {
    'A': {'B': 10, 'D': 20},
    'B': {'C': 5, 'D': 10},
    'C': {'E': 2},
    'D': {'C': 15, 'E': 10},
    'E': {}
}

该算法使用堆优化的Dijkstra算法实现最短路径的计算，同时也考虑了滑行路径的限制条件，即只能沿着已有的滑行道路行驶。函数`dijkstra`返回每个节点到起点的最短距离，函数`get_path`返回从起点到终点的最短滑行路径。如果无法找到从起点到终点的合法滑行路径，则返回`None`。