cdlib.evaluation.avg_distance

avg_distance(graph: <Mock id='140619399398416'>, communities: object, **kwargs) → object

Average distance.

The average distance of a community is defined average path length across all possible pair of nodes composing it.

Parameters:
  • graph – a networkx/igraph object
  • communities – 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)
>>> scd = evaluation.avg_distance(g,communities)