创建一个无标度网络G，随机生成节点：
# -*-coding:utf-8-*-import networkx as nximport matplotlib.pyplot as pltG = nx.random_graphs.barabasi_albert_graph(100, 1) # 生成一个BA无标度网络Gnx.draw(G) # 绘制网络Gplt.savefig("ba.png") # 输出方式1: 将图像存为一个png格式的图片文件plt.show()G = nx.Graph()G.add_node(1) # 添加节点G.add_edge(2, 3) # 添加边G.add_edge(3, 2)PRint G.nodes() # 输出所有的节点print G.edges() # 输出所有的边print G.number_of_edges() # 边的条数，只有一条边，就是（2，3）G.add_weighted_edges_from([(0, 1, 3.0), (1, 2, 7.5)]) # 增加边的权重print G.get_edge_data(1, 2)path = nx.all_pairs_shortest_path(G)print path[0][2] # 计算最短路径print '---------------------------------------------------------'G = nx.random_graphs.barabasi_albert_graph(1000, 3)print G.degree(0)print G.degree() # 返回节点的度print nx.degree_histogram(G) # 返回所有节点的分布序列degree = nx.degree_histogram(G)x = range(len(degree))y = [z/float(sum(degree)) for z in degree]plt.loglog(x, y, color='blue', linewidth=2)plt.show()print 'average clustering coefficient is', nx.average_clustering(G)print "every node's clustering coefficient is ", nx.clustering(G)print 'Diameter of G is ', nx.diameter(G)print "all nodes' average shortest path length is", nx.average_shortest_path_length(G)新闻热点
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