cdlib.evaluation.avg_odf¶
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avg_odf
(graph: <Mock id='139632780168336'>, community: object, summary: bool = True) → object¶ Average fraction of edges of a node of a community that point outside the community itself.
\[\frac{1}{n_S} \sum_{u \in S} \frac{|\{(u,v)\in E: v \not\in S\}|}{d(u)}\]where \(E\) is the graph edge set, \(v\) is a node in \(S\), \(d(u)\) is the degree of \(u\) and \(n_S\) 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.avg_odf(g,communities)
References: - Flake, G.W., Lawrence, S., Giles, C.L., et al.: Efficient identification of web communities. In: KDD, vol. 2000, pp. 150–160 (2000)