帮写游览长隆世界动物园最佳旅游路线的代码

好的，我可以为你提供一个基于 Python 的简单游览长隆世界动物园最佳旅游路线的代码。在这个代码中，我们将使用广度优先搜索算法（BFS）来查找最短路线。

首先，我们需要定义一些变量和数据结构：

# 地图
map = {
    "入口": {"海洋王国", "欢乐世界"},
    "欢乐世界": {"入口", "动物世界", "百鸟园", "熊猫馆"},
    "海洋王国": {"入口", "海狮湾", "海豚湾", "极地海洋馆"},
    "动物世界": {"欢乐世界", "大象馆", "狮虎山"},
    "百鸟园": {"欢乐世界", "孔雀园", "鹦鹉馆"},
    "熊猫馆": {"欢乐世界", "熊猫剧场"},
    "海狮湾": {"海洋王国"},
    "海豚湾": {"海洋王国"},
    "极地海洋馆": {"海洋王国"},
    "大象馆": {"动物世界"},
    "狮虎山": {"动物世界"},
    "孔雀园": {"百鸟园"},
    "鹦鹉馆": {"百鸟园"},
    "熊猫剧场": {"熊猫馆"}
}

# 起点和终点
start = "入口"
end = "海狮湾"

接下来，我们可以定义 BFS 算法来找到最短路线：

from collections import deque

# BFS 算法
def bfs(graph, start, end):
    # 用来记录访问过的节点
    visited = set()
    # 用来存储每个节点的前驱节点，便于最后回溯路径
    predecessor = dict()
    # 用来存储每个节点到起点的距离
    distance = dict()

    # 初始化起点信息
    queue = deque()
    visited.add(start)
    predecessor[start] = None
    distance[start] = 0
    queue.append(start)

    # 开始搜索
    while queue:
        node = queue.popleft()
        for neighbor in graph[node]:
            if neighbor not in visited:
                visited.add(neighbor)
                predecessor[neighbor] = node
                distance[neighbor] = distance[node] + 1
                if neighbor == end:
                    # 找到目标节点，回溯路径
                    path = []
                    while neighbor:
                        path.append(neighbor)
                        neighbor = predecessor[neighbor]
                    path.reverse()
                    return path, distance[end]
                queue.append(neighbor)

    # 没有找到路径
    return None, None

最后，我们可以调用 BFS 函数来查找最短路线：

path, distance = bfs(map, start, end)
if path:
    print("最短路线为：", "->".join(path))
    print("最短距离为：", distance)
else:
    print("没有找到路径。")

完整代码如下所示：

from collections import deque

# 地图
map = {
    "入口": {"海洋王国", "欢乐世界"},
    "欢乐世界": {"入口", "动物世界", "百鸟园", "熊猫馆"},
    "海洋王国": {"入口", "海狮湾", "海豚湾", "极地海洋馆"},
    "动物世界": {"欢乐世界", "大象馆", "狮虎山"},
    "百鸟园": {"欢乐世界", "孔雀园", "鹦鹉馆"},
    "熊猫馆": {"欢乐世界", "熊猫剧场"},
    "海狮湾": {"海洋王国"},
    "海豚湾": {"海洋王国"},
    "极地海洋馆": {"海洋王国"},
    "大象馆": {"动物世界"},
    "狮虎山": {"动物世界"},
    "孔雀园": {"百鸟园"},
    "鹦鹉馆": {"百鸟园"},
    "熊猫剧场": {"熊猫馆"}
}

# 起点和终点
start = "入口"
end = "海狮湾"

# BFS 算法
def bfs(graph, start, end):
    # 用来记录访问过的节点
    visited = set()
    # 用来存储每个节点的前驱节点，便于最后回溯路径
    predecessor = dict()
    # 用来存储每个节点到起点的距离
    distance = dict()

    # 初始化起点信息
    queue = deque()
    visited.add(start)
    predecessor[start] = None
    distance[start] = 0
    queue.append(start)

    # 开始搜索
    while queue:
        node = queue.popleft()
        for neighbor in graph[node]:
            if neighbor not in visited:
                visited.add(neighbor)
                predecessor[neighbor] = node
                distance[neighbor] = distance[node] + 1
                if neighbor == end:
                    # 找到目标节点，回溯路径
                    path = []
                    while neighbor:
                        path.append(neighbor)
                        neighbor = predecessor[neighbor]
                    path.reverse()
                    return path, distance[end]
                queue.append(neighbor)

    # 没有找到路径
    return None, None

# 查找最短路线
path, distance = bfs(map, start, end)
if path:
    print("最短路线为：", "->".join(path))
    print("最短距离为：", distance)
else:
    print("没有找到路径。")

希望这个代码能够帮助你规划游览长隆世界动物园的最佳旅游路线！