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label_propagation_communities(G)

Finds communities in G using a semi-synchronous label propagation method . This method combines the advantages of both the synchronous and asynchronous models. Not implemented for directed graphs.

Parameters

G : graph

An undirected NetworkX graph.

Raises

NetworkXNotImplemented

If the graph is directed

Returns

communities : iterable

A dict_values object that contains a set of nodes for each community.

Generates community sets determined by label propagation

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

networkx.algorithms.community.modularity_max.greedy_modularity_communities

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


GitHub : /networkx/algorithms/community/label_propagation.py#110
type: <class 'function'>
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