根据这个，结合数据结构有向图的相关知识，写出这个程序的代码

好的，以下是一个简单的Python程序，用于实现您所要求的全国交通咨询模拟系统。该程序基于有向图的相关知识，使用Dijkstra算法计算两个城市之间的最短路径和最短时间，并使用贪心算法计算最小花费路径。程序中使用了Python的面向对象编程思想，将城市、铁路和路径等信息封装为对象，使程序的结构更加清晰。

import heapq

class City:
    def __init__(self, name, intro):
        self.name = name
        self.intro = intro
        self.railways = []

    def add_railway(self, railway):
        self.railways.append(railway)

class Railway:
    def __init__(self, start_city, end_city, distance, speed, cost):
        self.start_city = start_city
        self.end_city = end_city
        self.distance = distance
        self.speed = speed
        self.cost = cost

class Path:
    def __init__(self, start_city, end_city, distance, time, cost, route):
        self.start_city = start_city
        self.end_city = end_city
        self.distance = distance
        self.time = time
        self.cost = cost
        self.route = route

class Graph:
    def __init__(self):
        self.cities = {}

    def add_city(self, city):
        self.cities[city.name] = city

    def add_railway(self, start_city_name, end_city_name, distance, speed, cost):
        start_city = self.cities[start_city_name]
        end_city = self.cities[end_city_name]
        railway = Railway(start_city, end_city, distance, speed, cost)
        start_city.add_railway(railway)

    def dijkstra_shortest_path(self, start_city_name, end_city_name, mode="distance"):
        start_city = self.cities[start_city_name]
        end_city = self.cities[end_city_name]
        visited = {}
        distance = {}
        previous = {}

        for city_name in self.cities:
            distance[city_name] = float("inf")
            visited[city_name] = False
            previous[city_name] = None

        distance[start_city_name] = 0
        heap = [(0, start_city_name)]

        while heap:
            (d, current_city_name) = heapq.heappop(heap)
            if visited[current_city_name]:
                continue
            visited[current_city_name] = True
            if current_city_name == end_city_name:
                break
            current_city = self.cities[current_city_name]
            for railway in current_city.railways:
                if mode == "distance":
                    weight = railway.distance
                elif mode == "time":
                    weight = railway.distance / railway.speed
                elif mode == "cost":
                    weight = railway.distance * railway.cost
                neighbor_city_name = railway.end_city.name
                tentative_distance = distance[current_city_name] + weight
                if tentative_distance < distance[neighbor_city_name]:
                    distance[neighbor_city_name] = tentative_distance
                    previous[neighbor_city_name] = current_city_name
                    heapq.heappush(heap, (distance[neighbor_city_name], neighbor_city_name))

        path = []
        current_city_name = end_city_name
        while current_city_name != start_city_name:
            previous_city_name = previous[current_city_name]
            current_city = self.cities[current_city_name]
            previous_city = self.cities[previous_city_name]
            for railway in current_city.railways:
                if railway.start_city == previous_city and railway.end_city == current_city:
                    path.insert(0, railway)
                    break
            current_city_name = previous_city_name

        if mode == "distance":
            return Path(start_city, end_city, distance[end_city_name], None, None, path)
        elif mode == "time":
            time = distance[end_city_name] / path[-1].speed
            return Path(start_city, end_city, distance[end_city_name], time, None, path)
        elif mode == "cost":
            cost = distance[end_city_name] * path[-1].cost
            return Path(start_city, end_city, distance[end_city_name], None, cost, path)

def display_menu():
    print("请选择要进行的操作：")
    print("1. 显示城市信息")
    print("2. 查询最短路程")
    print("3. 查询最短时间")
    print("4. 查询最小花费")
    print("5. 增加新的城市")
    print("6. 退出程序")

def display_city_info(city):
    print(city.intro)

def display_path(path):
    print("最短路程：", path.distance, "km")
    if path.time is not None:
        print("最短时间：", path.time, "h")
    if path.cost is not None:
        print("最小花费：", path.cost, "元")
    print("路线规划：")
    for railway in path.route:
        print(railway.start_city.name, "->", railway.end_city.name, "(", railway.distance, "km)")

def main():
    graph = Graph()

    # 添加城市
    beijing = City("北京", "北京是中国的首都。")
    shanghai = City("上海", "上海是中国的经济中心。")
    guangzhou = City("广州", "广州是中国的南方大城市。")
    shenzhen = City("深圳", "深圳是中国的特别行政区之一。")
    chengdu = City("成都", "成都是中国的西南大城市。")
    graph.add_city(beijing)
    graph.add_city(shanghai)
    graph.add_city(guangzhou)
    graph.add_city(shenzhen)
    graph.add_city(chengdu)

    # 添加铁路
    graph.add_railway("北京", "上海", 1318, 300, 0.5)
    graph.add_railway("北京", "广州", 2319, 250, 0.4)
    graph.add_railway("北京", "深圳", 2320, 250, 0.4)
    graph.add_railway("北京", "成都", 1444, 200, 0.3)
    graph.add_railway("上海", "广州", 1210, 300, 0.5)
    graph.add_railway("上海", "深圳", 1462, 300, 0.5)
    graph.add_railway("上海", "成都", 1942, 250, 0.4)
    graph.add_railway("广州", "深圳", 147, 200, 0.3)
    graph.add_railway("广州", "成都", 1430, 200, 0.3)
    graph.add_railway("深圳", "成都", 1426, 200, 0.3)

    while True:
        display_menu()
        choice = input("请输入要进行的操作编号：")
        if choice == "1":
            city_name = input("请输入要查询的城市名称：")
            city = graph.cities[city_name]
            display_city_info(city)
        elif choice == "2":
            start_city_name = input("请输入出发城市名称：")
            end_city_name = input("请输入到达城市名称：")
            path = graph.dijkstra_shortest_path(start_city_name, end_city_name, "distance")
            display_path(path)
        elif choice == "3":
            start_city_name = input("请输入出发城市名称：")
            end_city_name = input("请输入到达城市名称：")
            path = graph.dijkstra_shortest_path(start_city_name, end_city_name, "time")
            display_path(path)
        elif choice == "4":
            start_city_name = input("请输入出发城市名称：")
            end_city_name = input("请输入到达城市名称：")
            path = graph.dijkstra_shortest_path(start_city_name, end_city_name, "cost")
            display_path(path)
        elif choice == "5":
            city_name = input("请输入要添加的城市名称：")
            city_intro = input("请输入要添加的城市介绍：")
            city = City(city_name, city_intro)
            graph.add_city(city)
            print("城市添加成功。")
        elif choice == "6":
            break
        else:
            print("无效的操作编号，请重新输入。")

if __name__ == "__main__":
    main()

以上是一个简单的Python程序，用于实现您所要求的全国交通咨询模拟系统。由于程序的实现方式和您的具体要求可能存在差异，如有需要可以进行适当的修改。