def drawCommunityGraph(G, zeta, **kwargs):
""" Draws the community graph for a given graph and partition. Passes any additional arguments to networkx.draw(...).
By default, node sizes are scaled between 30 and 500 by community size.
"""
cg = ParallelPartitionCoarsening(G, zeta)
cg.run() # convert communities to nodes
graph = cg.getCoarseGraph()
comGraph = nxadapter.nk2nx(graph)
if not "node_size" in kwargs:
sizes = list(zeta.subsetSizeMap().values())
max_size = max(sizes)
sizes = [elem / max_size for elem in sizes]
kwargs["node_size"] = [30 + 470 * s for s in sizes]
networkx.draw(comGraph, **kwargs)
def communityGraph(G, zeta): """ Create a community graph, i.e. a graph in which one node represents a community and an edge represents the edges between communities, from a given graph and a community detection solution""" cg = ParallelPartitionCoarsening(G, zeta) cg.run() return cg.getCoarseGraph()
def communityGraph(G, zeta): """ Create a community graph, i.e. a graph in which one node represents a community and an edge represents the edges between communities, from a given graph and a community detection solution""" cg = ParallelPartitionCoarsening(G, zeta) cg.run() return cg.getCoarseGraph()