cdlib.viz.plot_community_graph

plot_community_graph(graph: object, partition: cdlib.classes.node_clustering.NodeClustering, figsize: tuple = (8, 8), node_size: int = 200, plot_overlaps: bool = False, plot_labels: bool = False, cmap: object = None, top_k: int = None, min_size: int = None) → object

Plot a algorithms-graph with node color coding for communities.

Parameters:
  • graph – NetworkX/igraph graph
  • partition – NodeClustering object
  • figsize – the figure size; it is a pair of float, default (8, 8)
  • node_size – int, default 200
  • plot_overlaps – bool, default False. Flag to control if multiple algorithms memberships are plotted.
  • plot_labels – bool, default False. Flag to control if node labels are plotted.
  • cmap – str or Matplotlib colormap, Colormap(Matplotlib colormap) for mapping intensities of nodes. If set to None, original colormap is used..
  • top_k – int, Show the top K influential communities. If set to zero or negative value indicates all.
  • min_size – int, Exclude communities below the specified minimum size.

Example:

>>> from cdlib import algorithms, viz
>>> import networkx as nx
>>> g = nx.karate_club_graph()
>>> coms = algorithms.louvain(g)
>>> viz.plot_community_graph(g, coms)