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网络节点的重要性指标介数中心性的计算，使用python的networkx包
import networkx as nx
G = nx.Graph()
# 从文件@filename中读取网络的adjacentMatrix，通过networkx的add_edges方法向对象G中添加边
def readNetwork(filename):
fin = open(filename, 'r')
# for line in fin:
# for node in line:
# print(node, end="")
# lines = fin.readlines()
# print(len(lines))
rowCount = 1;
colCount = 1;
for line in fin.readlines():
line = line.split(" ")
for node in line:
if node == '1':
G.add_edge(rowCount, colCount)
colCount = colCount + 1
colCount = 1
rowCount += 1
print(G.edges())
# 计算网络中的节点的介数中心性，并进行排序输出
def topNBetweeness():
score = nx.betweenness_centrality(G)
score = sorted(score.items(), key=lambda item:item[1], reverse = True)
print("betweenness_centrality: ", score)
output = []
for node in score:
output.append(node[0])
print(output)
fout = open("betweennessSorted.data", 'w')
for target in output:
fout.write(str(target)+" ")
readNetwork("sf100.data")
topNBetweeness()
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