naive_greedy_modularity_communities#

naive_greedy_modularity_communities(G, resolution=1, weight=None)[source]#

Find communities in G using greedy modularity maximization.

This implementation is O(n^4), much slower than alternatives, but it is provided as an easy-to-understand reference implementation.

Greedy modularity maximization begins with each node in its own community and joins the pair of communities that most increases modularity until no such pair exists.

This function maximizes the generalized modularity, where resolution is the resolution parameter, often expressed as \(\gamma\). See modularity().

Parameters:

GNetworkX graph
resolutionfloat (default=1): If resolution is less than 1, modularity favors larger communities. Greater than 1 favors smaller communities.
weightstring or None, optional (default=None): The name of an edge attribute that holds the numerical value used as a weight. If None, then each edge has weight 1. The degree is the sum of the edge weights adjacent to the node.

Returns:

list: A list of sets of nodes, one for each community. Sorted by length with largest communities first.

See also

greedy_modularity_communities
modularity

Examples

>>> from networkx.algorithms.community import \
... naive_greedy_modularity_communities
>>> G = nx.karate_club_graph()
>>> c = naive_greedy_modularity_communities(G)
>>> sorted(c[0])
[8, 14, 15, 18, 20, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33]