edges_inside(graph: <Mock id='139911972696400'>, community: object, summary: bool = True) → object¶
Number of edges internal to the community.
- graph – a networkx/igraph object
- community – NodeClustering object
- summary – boolean. If True it is returned an aggregated score for the partition is returned, otherwise individual-community ones. Default True.
If summary==True a FitnessResult object, otherwise a list of floats.
>>> from cdlib.algorithms import louvain >>> from cdlib import evaluation >>> g = nx.karate_club_graph() >>> communities = louvain(g) >>> mod = evaluation.edges_inside(g,communities)
- Radicchi, F., Castellano, C., Cecconi, F., Loreto, V., & Parisi, D. (2004). Defining and identifying communities in networks. Proceedings of the National Academy of Sciences, 101(9), 2658-2663.