在Python中为无向图建模

Question

我尝试使用networkX绘制一个“网络图”，但是told，这个库并不是出于我想要用它的目的。

总结上面提到的失败问题，我从我想要绘制的数据开始，然后继续讨论实际问题：

graph = {
    '1': ['2', '3', '4'],
    '2': ['5','11','12','13','14','15'],
    '3' : ['6','7','66','77'],
    '5': ['6', '8','66','77'],
    '4': ['7','66','77'],
    '7': ['9', '10']
}

将此数据视为defaultdict（列表），最左边的部分是键，右侧的列表是该键的值列表。我想要实现的是绘制图形，类似于网络图here：边缘越多，节点越大，标记节点等。

然而，不同之处在于我想要连接键，具有相应的值（1表示2,1表示3,1表示4），但不键彼此（不 1与2与3与5与4与7）。

将数据映像为服务器和客户端。密钥是服务器，值是客户端。服务器（密钥）不直接相互连接，它们只共享（有时）相同的客户端。在上面的示例中，服务器3和服务器5都连接到客户端6,66和77.这也是为什么客户端（值）不应该彼此连接的原因。

我希望能够清楚地表达我的问题^^

谢谢！

Answer 1

The problem is you're trying to use the same IDs for your servers and clients. NetworkX has no way to know if 2 refers to a client (that should be connected) or a server (that should not). To do what you're describing here, you just need to create a unique id for the servers. For example:

import networkx

graph = {
    '1': ['2', '3', '4'],
    '2': ['5','11','12','13','14','15'],
    '3': ['6','7','66','77'],
    '5': ['6', '8','66','77'],
    '4': ['7','66','77'],
    '7': ['9', '10']
}

g = networkx.Graph()

for k, vs in graph.items():
    server_id = 'server_%s' % k

    for v in vs:
        g.add_edge(server_id,v)

networkx.draw_spring(g)

This produces the following output:

To change the size of node by the number of edges, you need to calculate the size and pass it to draw_spring. To get the number of edges for a particular node you can call g.edges(node) e.g.

node_sizes = [150*len(g.edges(n)) for n in g.nodes()]
networkx.draw_spring(g, node_size=node_sizes)

Which should give you the following: