/usr/lib/python2.7/dist-packages/networkx/generators/stochastic.py is in python-networkx 1.8.1-0ubuntu3.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | """Stocastic graph."""
# Copyright (C) 2010-2013 by
# Aric Hagberg <hagberg@lanl.gov>
# Dan Schult <dschult@colgate.edu>
# Pieter Swart <swart@lanl.gov>
# All rights reserved.
# BSD license.
import networkx as nx
__author__ = "Aric Hagberg <aric.hagberg@gmail.com>"
__all__ = ['stochastic_graph']
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 : graph
A NetworkX graph
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.
"""
if type(G) == nx.MultiGraph or type(G) == nx.MultiDiGraph:
raise nx.NetworkXError('stochastic_graph not implemented '
'for multigraphs')
if not G.is_directed():
raise nx.NetworkXError('stochastic_graph not implemented '
'for undirected graphs')
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):
d[weight] = float(d.get(weight,1.0))/degree[u]
return W
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