首先輸入邊和邊的權重，隨後畫出節點位置。依據權重大小劃分實邊和虛邊

#coding:utf-8
#!/usr/bin/env python
"""
An example using Graph as a weighted network.
"""
__author__ = """Aric Hagberg ([email protected])"""
try:
    import matplotlib.pyplot as plt
except:
    raise

import networkx as nx

G=nx.Graph()
#加入帶權邊
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)
#按權重劃分為重權值得邊和輕權值的邊
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]
#節點位置
pos=nx.spring_layout(G) # positions for all nodes
#首先畫出節點位置
# nodes
nx.draw_networkx_nodes(G,pos,node_size=700)
#依據權重，實線為權值大的邊，虛線為權值小的邊
# 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標簽定義
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

python—networkx：依據圖的權重繪圖