利用networkx里面的函数betweenness_centrality(G)来求解节点介数和函数edge_betweenness_centrality(G)来求解边介数

# -*- coding: utf-8 -*-
"""
Created on Sat Sep 14 18:01:27 2019

@author: Administrator
"""

import matplotlib.pyplot as plt
import networkx as nx
import operator

def matrix_to_graph():
    
  G = nx.Graph()
  
  filestr = ""
  
  #需要读入的邻接矩阵
  with open("mlMatrix.txt") as files:
     for line in files:
         filestr += line.strip()
 
  
  #将字符串转换成列表
  matrix = eval(filestr)

  nodes = range(len(matrix))
  G.add_nodes_from(nodes)
 
  for i in range(len(matrix)):
    for j in range(len(matrix)):
      if(matrix[i][j] == 1):
		G.add_edge(i, j)
  
  bc= nx.centrality.betweenness_centrality(G,normalized=False)
  ebc = nx.centrality.edge_betweenness_centrality(G,normalized=False)
  
  print("节点编号及其节点介数最大值为：")
  bc_list = sorted(bc.items(), key=operator.itemgetter(1))
  print(bc_list)
  
  print("-----------------------------------")
  print("节点编号及其边介数最大值为：")
  ebc_list = sorted(ebc.items(), key=operator.itemgetter(1))
  print(ebc_list)
   
matrix_to_graph()

节点介数

边介数