是否可以使用Networkx和Python获取基于节点属性的度中心值？

Question

我是 Networkx 的新手，我想知道是否有任何方法可以输出以下内容：

Let's say I have a network whose nodes are people's names and their attributes are their gender(M,F). When obtaining the degree centrality degree_cent = nx.degree_centrality(g)

Instead of having something like this:

[('Anna', 1.0),('Ben',0.6), ...

Is it possible to have something like this:

[('Anna', M:0.4, F:0.6),('Ben', M:0.3, F:0.3),... where I can distinguish the number of nodes with M and F attributes that are connected to my nodes of interest?

Thank you.

Answer 1

需要自己写度函数：

import networkx as nx
import random

random.seed(42)

graph = nx.erdos_renyi_graph(20, .1)

classes = ["A", "B", "C"]

for node in graph:
    graph.nodes[node]["attribute"] = random.choice(classes)


def attribute_degree(G, node):
    degree = {}

    for neighbor in G.neighbors(node):
        attribute = G.nodes[neighbor]["attribute"]
        degree[attribute] = degree.get(attribute, 0) + 1

    return degree


print(attribute_degree(graph, 0))
# {'B': 1, 'A': 2, 'C': 1}
print(attribute_degree(graph, 1))
# {'B': 1, 'A': 1, 'C': 1}

是否可以使用Networkx和Python获取基于节点属性的度中心值？

Is it possible to obtain the degree centrality values based on the node attributes using Networkx and Python?

python

attributes

nodes

networkx