python—networkx：依据图的权重绘图

首先输入边和边的权重，随后画出节点位置。依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 plt

except:

    raise

import networkx as nx

G=nx.Graph()

#加入带权边

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

# nodes

nx.draw_networkx_nodes(G,pos,node_size=700)

#依据权重，实线为权值大的边，虚线为权值小的边

# edges

nx.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 png

plt.show() # display