首先输入边和边的权重，随后画出节点位置，根据权重大小划分实边和虚边

#coding:utf-8#!/usr/bin/env python"""An example using Graph as a weighted network."""__author__ = """Aric Hagberg (hagberg@lanl.gov)"""try: import matplotlib.pyplot as pltexcept: raise import networkx as nx G=nx.Graph()#添加带权边G.add_edge('a','b',weight=0.6)G.add_edge('a','c',weight=0.2)G.add_edge('c','d',weight=0.1)G.add_edge('c','e',weight=0.7)G.add_edge('c','f',weight=0.9)G.add_edge('a','d',weight=0.3)#按权重划分为重权值得边和轻权值的边elarge=[(u,v) for (u,v,d) in G.edges(data=True) if d['weight'] >0.5]esmall=[(u,v) for (u,v,d) in G.edges(data=True) if d['weight'] <=0.5]#节点位置pos=nx.spring_layout(G) # positions for all nodes#首先画出节点位置# nodesnx.draw_networkx_nodes(G,pos,node_size=700)#根据权重，实线为权值大的边，虚线为权值小的边# edgesnx.draw_networkx_edges(G,pos,edgelist=elarge, width=6)nx.draw_networkx_edges(G,pos,edgelist=esmall, width=6,alpha=0.5,edge_color='b',style='dashed') # labels标签定义nx.draw_networkx_labels(G,pos,font_size=20,font_family='sans-serif') plt.axis('off')plt.savefig("weighted_graph.png") # save as pngplt.show() # display

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