根据节点的属性NetworkX将图划分为太阳图 [英] partition graph into sungraphs based on node's attribute NetworkX

问题描述

我正在使用Networkx计算图形的一些度量，例如直径，聚类系数等.直接对整个图形执行此操作很简单.我感兴趣的是在具有相同属性(例如颜色)的节点之间找到这些度量.我在考虑是否可以将图划分为不同的子图，其中每个子图中的节点具有相同的颜色，那么我可以继续进行并测量该子图中的直径.所以我的问题是:是否可以将一个图划分为包含相同颜色节点的子图?

I'm using Networkx to compute some measures of a graph such as diameter, clustering coefficient, etc. It's straight forward how to do this for graph as a whole. What I'm interested in is finding these measures between nodes that have same attribute(say color). I'm thinking if I could partition the graph into different sub graphs, where nodes in each sub graph are of the same color, then I could accomplish go ahead and measure diameter in this sub graph. So my question is: Is there a way to partition a graph into sub graphs which contain nodes of same color?

我真的很感谢任何见解.

I would really appreciate any insight.

推荐答案

使用演示

import networkx as nx

G = nx.Graph()

G.add_nodes_from([1, 2, 3], color="red")
G.add_nodes_from([4, 5, 6])
G.nodes  # NodeView((1, 2, 3, 4, 5, 6))

# create generator
nodes = (
    node
    for node, data
    in G.nodes(data=True)
    if data.get("color") == "red"
)
subgraph = G.subgraph(nodes)
subgraph.nodes  # NodeView((1, 2, 3))

旧版NetworkX的

遍历( )，然后根据您的条件过滤节点.将该列表传递给 Graph.subgraph() ，它将返回这些节点及其内部边缘的副本.

older NetworkX's

Iterate over (Graph.iter_nodes()) and filter the nodes based on your criteria. Pass that list to Graph.subgraph() and it'll return a copy of those nodes and their internal edges.

例如:

G = nx.Graph()
# ... build or do whatever to the graph
nodes = (n for n, d in G.nodes_iter(data=True)) if d.get('color') == 'red')
subgraph = G.subgraph(nodes)

这篇关于根据节点的属性NetworkX将图划分为太阳图的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！