cdlib.evaluation.expansion¶
-
expansion
(graph: <Mock id='139632780070544'>, community: object, summary: bool = True) → object¶ Number of edges per community node that point outside the cluster.
\[f(S) = \frac{c_S}{n_S}\]where \(n_S\) is the number of edges on the community boundary, \(c_S\) is the number of community nodes.
Parameters: - 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.
Returns: If summary==True a FitnessResult object, otherwise a list of floats.
Example:
>>> from cdlib.algorithms import louvain >>> from cdlib import evaluation >>> g = nx.karate_club_graph() >>> communities = louvain(g) >>> mod = evaluation.expansion(g,communities)
References: - 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.