cdlib.algorithms.infomap_bipartite¶
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infomap_bipartite
(g_original: object, flags: str = '') → cdlib.classes.bipartite_node_clustering.BiNodeClustering¶ Infomap is based on ideas of information theory. The algorithm uses the probability flow of random walks on a bipartite network as a proxy for information flows in the real system and it decomposes the network into modules by compressing a description of the probability flow.
Supported Graph Types
Undirected Directed Weighted Bipartite Yes Yes Yes Yes Parameters: - g_original – a networkx/igraph object
- flags – str flags for Infomap
Returns: BiNodeClustering object
Example: >>> from cdlib import algorithms >>> import networkx as nx >>> G = nx.karate_club_graph() >>> coms = algorithms.infomap_bipartite(G)
References: Rosvall M, Bergstrom CT (2008) Maps of random walks on complex networks reveal community structure. Proc Natl Acad SciUSA 105(4):1118–1123
Note
Reference implementation: https://pypi.org/project/infomap/
Note
Infomap Python API documentation: https://mapequation.github.io/infomap/python/