7.11. Communities¶
Contents
7.11.1. Bipartitions¶
Functions for computing the Kernighan–Lin bipartition algorithm.
kernighan_lin_bisection(G[, partition, ...]) |
Partition a graph into two blocks using the Kernighan–Lin algorithm. |
7.11.2. Generators¶
LFR_benchmark_graph |
7.11.3. K-Clique¶
k_clique_communities(G, k[, cliques]) |
Find k-clique communities in graph using the percolation method. |
7.11.4. Label propagation¶
Asynchronous label propagation algorithms for community detection.
asyn_lpa_communities(G[, weight]) |
Returns communities in G as detected by asynchronous label propagation. |
7.11.5. Measuring partitions¶
Functions for measuring the quality of a partition (into communities).
coverage(*args, **kw) |
Returns the coverage of a partition. |
performance(*args, **kw) |
Returns the performance of a partition. |
7.11.6. Partitions via centrality measures¶
Functions for computing communities based on centrality notions.
girvan_newman(G[, most_valuable_edge]) |
Finds communities in a graph using the Girvan–Newman method. |