<p>在<code>networkx</code>中,我可以想出两种很好的方法来解决这个问题。第一种方法是为每个字段制作单独的标签,并以不同的颜色打印,如下所示:</p>
<pre class="lang-py prettyprint-override"><code>import networkx as nx
import matplotlib.pyplot as plt
# Create the graph from the example edgelist
edges=[(1405394338,
1367797753,
{'Email': 'NJOHNSONJOHNSON34@GMAIL.COM',
'Phone': 5392353776,
'VIN': '1C3CDZBG9DN5907'}),
(1405394338, 1354581834, {'Phone': 5392353776}),
(1405394338,
1334448011,
{'Email': 'NJOHNSONJOHNSON34@GMAIL.COM', 'Phone': 5392353776}),
(1405394338, 1244950426, {'Email': 'NJOHNSONJOHNSON34@GMAIL.COM'}),
(1354581834, 1367797753, {'Phone': 5392353776}),
(1354581834, 1334448011, {'Phone': 5392353776}),
(1334448011,
1367797753,
{'Email': 'NJOHNSONJOHNSON34@GMAIL.COM', 'Phone': 5392353776}),
(1334448011, 1244950426, {'Email': 'NJOHNSONJOHNSON34@GMAIL.COM'}),
(1367797753, 1244950426, {'Email': 'NJOHNSONJOHNSON34@GMAIL.COM'})]
G=nx.DiGraph(edges)
# Grab the labels individually
labels1=nx.get_edge_attributes(G,'Email')
labels2=nx.get_edge_attributes(G,'Phone')
labels3=nx.get_edge_attributes(G,'VIN')
# Setup the figure and plot it
plt.figure(figsize=(15,15))
pos=nx.spring_layout(G)
nx.draw(G,pos)
# Add each label individually
nx.drawing.draw_networkx_edge_labels(G,pos,edge_labels=labels1,font_color='red',label_pos=0.75,rotate=True)
nx.drawing.draw_networkx_edge_labels(G,pos,edge_labels=labels2,font_color='blue',label_pos=0.5,rotate=True)
nx.drawing.draw_networkx_edge_labels(G,pos,edge_labels=labels3,font_color='green',label_pos=0.25,rotate=True)
# display
plt.show()
</code></pre>
<p>本例中的图形如下所示:
<a href="https://i.stack.imgur.com/lwkVB.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/lwkVB.png" alt="enter image description here"/></a></p>
<p>另一个是制作自定义标签,如下所示:</p>
<pre class="lang-py prettyprint-override"><code># Setup the figure and plot it
plt.figure(figsize=(15,15))
pos=nx.spring_layout(G)
nx.draw(G,pos)
custom_labels = {}
for u,v,d in G.edges(data=True):
L=""
for att,val in d.items():
L+=att+":"+str(val)+"\n"
custom_labels[(u,v)]=L
nx.drawing.draw_networkx_edge_labels(G,pos,edge_labels=custom_labels,font_color='red',
rotate=False,horizontalalignment ='left')
</code></pre>
<p>在本例中,该图如下所示:
<a href="https://i.stack.imgur.com/BcQwH.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/BcQwH.png" alt="enter image description here"/></a></p>
<p>当然,您可以使用figsize和font参数使这些更漂亮。此外,我个人建议使用yED(<a href="https://www.yworks.com/products/yed" rel="nofollow noreferrer">https://www.yworks.com/products/yed</a>)或其他图形界面来实现这类功能。您可以使用<code>nx.write_graphml(G, "filename.graphml")</code>导出到可以读入的文件,然后使用它的属性映射器和布局工具进行设置。如果要查看大量绘图,这会很乏味,但如果要制作“最终版本”图形,它确实是一个更好的工具,因为可以轻松微调各个节点、边和标签的位置。(这就是我如何为我的研究论文和会议幻灯片制作99%的网络数据。)</p>
<p><strong>编辑</strong>为完整起见,我将在此处输入导出代码和我为其制作的图形:</p>
<pre class="lang-py prettyprint-override"><code># Make a copy for export
G_ex=G.copy()
# Add the custom labels we made earlier
# to the copy graph as an attribute
for u,v in custom_labels:
G_ex.edges[(u,v)]['label']=custom_labels[(u,v)]
# Convert the attributes to strings to avoid import headaches
for e in G_ex.edges():
for k,v in G_ex.edges[e].items():
G_ex.edges[e][k]=str(v)
# Actually do the exporting
nx.write_graphml(G_ex,"test.graphml")
</code></pre>
<p>我将graphml文件导入到yED中,并对其进行处理,直到得到以下结果:
<a href="https://i.stack.imgur.com/njXXX.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/njXXX.png" alt="enter image description here"/></a></p>