社群 ¶
社群¶
此示例展示了如何可视化图的社群或集群。 首先，创建图：为简单起见，我们这里只使用一个著名的图。
import igraph as ig
import matplotlib.pyplot as plt
g = ig.Graph.Famous("Zachary")
其次，定义集群。
# Use edge betweenness to detect communities
communities = g.community_edge_betweenness()
# ... and convert into a VertexClustering for plotting
communities = communities.as_clustering()
第三，为各个社群准备颜色
# Color each vertex and edge based on its community membership
num_communities = len(communities)
palette = ig.RainbowPalette(n=num_communities)
for i, community in enumerate(communities):
g.vs[community]["color"] = i
community_edges = g.es.select(_within=community)
community_edges["color"] = i
最后，绘制图
# Plot with only vertex and edge coloring
fig, ax = plt.subplots()
ig.plot(
communities,
palette=palette,
edge_width=1,
target=ax,
vertex_size=0.3,
)
… 并通过 代理艺术家 添加一个漂亮的图例
legend_handles = []
for i in range(num_communities):
handle = ax.scatter(
[], [],
s=100,
facecolor=palette.get(i),
edgecolor="k",
label=i,
)
legend_handles.append(handle)
ax.legend(
handles=legend_handles,
title='Community:',
bbox_to_anchor=(0, 1.0),
bbox_transform=ax.transAxes,
)
结果图如下所示。
图及其社群通过颜色突出显示。¶
有关如何从顶点集群生成集群图的示例，请查看 生成集群图。