高德地图最短路径规划源代码

以下是一个基于 Dijkstra 算法实现的高德地图最短路径规划的示例代码：

import heapq

class Graph:
    def __init__(self, vertices):
        self.V = vertices
        self.graph = [[] for i in range(vertices)]
    
    def add_edge(self, u, v, w):
        self.graph[u].append((v, w))
        self.graph[v].append((u, w))

def dijkstra(src, graph):
    heap = [(0, src)]
    dist = [float('inf')] * graph.V
    dist[src] = 0

    while heap:
        (d, u) = heapq.heappop(heap)
        if d > dist[u]:
            continue

        for v, w in graph.graph[u]:
            if dist[u] + w < dist[v]:
                dist[v] = dist[u] + w
                heapq.heappush(heap, (dist[v], v))

    return dist

# 定义地图数据
vertices = 5
edges = [(0, 1, 10), (0, 3, 5), (1, 2, 1), (1, 3, 2), (2, 4, 4), (3, 1, 3), (3, 2, 9), (3, 4, 2), (4, 0, 7), (4, 2, 6)]

# 构建地图图结构
graph = Graph(vertices)
for edge in edges:
    graph.add_edge(*edge)

# 进行最短路径规划
src = 0
dist = dijkstra(src, graph)

# 输出最短路径结果
print("最短路径结果：")
for i in range(vertices):
    print(f"从节点 {src} 到节点 {i} 的最短距离为 {dist[i]}")

这是一个简单的示例代码，实际上高德地图的路线规划涉及更多的算法和技术，如 A* 算法、动态规划、机器学习等。