edge_betweenness_partition

edge_betweenness_partition(G, number_of_sets, *, weight=None)

由迭代移除具有最高边介数的边创建的分区。

该算法通过计算所有边的边介数并移除具有最高值的边来工作。然后确定图是否已被分解为至少 number_of_sets 个连通分量。如果没有，则重复该过程。

Parameters:

GNetworkX 图、有向图或多图

要分区的图

number_of_setsint

图的期望分区中的集合数量

weight键, 可选, 默认=None

如果使用边介数计算的权重，则使用的键

Returns:

C集合列表

G的节点分区

Raises:

NetworkXError

如果number_of_sets <= 0或number_of_sets > len(G)

See also

edge_current_flow_betweenness_partition

Notes

该算法相当慢，因为连通分量和边介数的计算都依赖于所有对最短路径算法。它们有可能被结合起来以减少总体计算时间。

References

[1]

Santo Fortunato ‘Community Detection in Graphs’ Physical Reports Volume 486, Issue 3-5 p. 75-174 http://arxiv.org/abs/0906.0612

Examples

>>> G = nx.karate_club_graph()
>>> part = nx.community.edge_betweenness_partition(G, 2)
>>> {0, 1, 3, 4, 5, 6, 7, 10, 11, 12, 13, 16, 17, 19, 21} in part
True
>>> {
...     2,
...     8,
...     9,
...     14,
...     15,
...     18,
...     20,
...     22,
...     23,
...     24,
...     25,
...     26,
...     27,
...     28,
...     29,
...     30,
...     31,
...     32,
...     33,
... } in part
True