cdlib.evaluation.max_odf

max_odf(graph: <Mock id='140619399399888'>, community: object, summary: bool = True) → object

Maximum fraction of edges of a node of a community that point outside the community itself.

\[max_{u \in S} \frac{|\{(u,v)\in E: v \not\in S\}|}{d(u)}\]

where \(E\) is the graph edge set, \(v\) is a node in \(S\) and \(d(u)\) is the degree of \(u\)

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.max_odf(g,communities)
References:
  1. Flake, G.W., Lawrence, S., Giles, C.L., et al.: Efficient identification of web communities. In: KDD, vol. 2000, pp. 150–160 (2000)