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Source code for networkx.generators.stochastic
"""Stocastic graph.""" # Copyright (C) 2010-2013 by # Aric Hagberg <email@example.com> # Dan Schult <firstname.lastname@example.org> # Pieter Swart <email@example.com> # All rights reserved. # BSD license. import networkx as nx from networkx.utils import not_implemented_for __author__ = "Aric Hagberg <firstname.lastname@example.org>" __all__ = ['stochastic_graph'] @not_implemented_for('multigraph') @not_implemented_for('undirected')[docs]def stochastic_graph(G, copy=True, weight='weight'): """Return a right-stochastic representation of G. A right-stochastic graph is a weighted digraph in which all of the node (out) neighbors edge weights sum to 1. Parameters ----------- G : directed graph A NetworkX DiGraph copy : boolean, optional If True make a copy of the graph, otherwise modify the original graph weight : edge attribute key (optional, default='weight') Edge data key used for weight. If no attribute is found for an edge the edge weight is set to 1. Weights must be positive numbers. """ import warnings if copy: W = nx.DiGraph(G) else: W = G # reference original graph, no copy degree = W.out_degree(weight=weight) for (u,v,d) in W.edges(data=True): if degree[u] == 0: warnings.warn('zero out-degree for node %s'%u) d[weight] = 0.0 else: d[weight] = float(d.get(weight,1.0))/degree[u] return W