Communities¶
Functions for computing and measuring community structure.
The functions in this class are not imported into the top-level
networkx
namespace. You can access these functions by importing
the networkx.algorithms.community
module, then accessing the
functions as attributes of community
. For example:
>>> import networkx as nx
>>> from networkx.algorithms import community
>>> G = nx.barbell_graph(5, 1)
>>> communities_generator = community.girvan_newman(G)
>>> top_level_communities = next(communities_generator)
>>> next_level_communities = next(communities_generator)
>>> sorted(map(sorted, next_level_communities))
[[0, 1, 2, 3, 4], [5], [6, 7, 8, 9, 10]]
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. |
Generators¶
Functions for generating graphs with community structure.
LFR_benchmark_graph (n, tau1, tau2, mu[, …]) |
Returns the LFR benchmark graph for testing community-finding algorithms. |
K-Clique¶
k_clique_communities (G, k[, cliques]) |
Find k-clique communities in graph using the percolation method. |
Label propagation¶
Label propagation community detection algorithms.
asyn_lpa_communities (G[, weight]) |
Returns communities in G as detected by asynchronous label propagation. |
label_propagation_communities (G) |
Generates community sets determined by label propagation |
Fluid Communities¶
Asynchronous Fluid Communities algorithm for community detection.
asyn_fluidc (G, k[, max_iter]) |
Returns communities in G as detected by Fluid Communities algorithm. |
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. |
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. |
Validating partitions¶
Helper functions for community-finding algorithms.
is_partition (G, communities) |
Return True if and only if communities is a partition of the nodes of G . |