def link_modularity(graph: nx.Graph, communities: object,
**kwargs: dict) -> object:
"""
Quality function designed for directed graphs with overlapping communities.
:param graph: a networkx/igraph object
:param communities: NodeClustering object
:return: FitnessResult object
Example:
>>> from cdlib.algorithms import louvain
>>> from cdlib import evaluation
>>> g = nx.karate_club_graph()
>>> communities = louvain(g)
>>> mod = evaluation.link_modularity(g,communities)
:References:
1. Nicosia, V., Mangioni, G., Carchiolo, V., Malgeri, M.: Extending the definition of modularity to directed graphs with overlapping communities. Journal of Statistical Mechanics: Theory and Experiment 2009(03), 03024 (2009)
"""
graph = convert_graph_formats(graph, nx.Graph)
return FitnessResult(score=cal_modularity(graph, communities.communities))
def link_modularity(graph, communities):
"""
Quality function designed for directed graphs with overlapping communities.
:param graph: a networkx/igraph object
:param communities: NodeClustering object
:return: the link modularity score
Example:
>>> from cdlib.algorithms import louvain
>>> from cdlib import evaluation
>>> g = nx.karate_club_graph()
>>> communities = louvain(g)
>>> mod = evaluation.link_modularity(g,communities)
"""
graph = convert_graph_formats(graph, nx.Graph)
return cal_modularity(graph, communities.communities)