cdlib.evaluation.triangle_participation_ratio¶
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triangle_participation_ratio
(graph: <Mock id='139632780168528'>, community: object, summary: bool = True) → object¶ Fraction of community nodes that belong to a triad.
\[f(S) = \frac{ | \{ u: u \in S,\{(v,w):v, w \in S,(u,v) \in E,(u,w) \in E,(v,w) \in E \} \not = \emptyset \} |}{n_S}\]where \(n_S\) is the set 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.triangle_participation_ratio(g,communities)
References: - Yang, J., Leskovec, J.: Defining and evaluating network communities based on ground-truth. Knowledge and Information Systems 42(1), 181–213 (2015)