--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/planemo/lib/python3.7/site-packages/networkx/generators/stochastic.py	Fri Jul 31 00:32:28 2020 -0400
@@ -0,0 +1,57 @@
+#    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.
+"""Functions for generating stochastic graphs from a given weighted directed
+graph.
+
+"""
+
+from networkx.classes import DiGraph
+from networkx.classes import MultiDiGraph
+from networkx.utils import not_implemented_for
+
+__author__ = "Aric Hagberg <aric.hagberg@gmail.com>"
+__all__ = ['stochastic_graph']
+
+
+@not_implemented_for('undirected')
+def stochastic_graph(G, copy=True, weight='weight'):
+    """Returns a right-stochastic representation of directed graph `G`.
+
+    A right-stochastic graph is a weighted digraph in which for each
+    node, the sum of the weights of all the out-edges of that node is
+    1. If the graph is already weighted (for example, via a 'weight'
+    edge attribute), the reweighting takes that into account.
+
+    Parameters
+    ----------
+    G : directed graph
+        A :class:`~networkx.DiGraph` or :class:`~networkx.MultiDiGraph`.
+
+    copy : boolean, optional
+        If this is True, then this function returns a new graph with
+        the stochastic reweighting. Otherwise, the original graph is
+        modified in-place (and also returned, for convenience).
+
+    weight : edge attribute key (optional, default='weight')
+        Edge attribute key used for reading the existing weight and
+        setting the new weight.  If no attribute with this key is found
+        for an edge, then the edge weight is assumed to be 1. If an edge
+        has a weight, it must be a a positive number.
+
+    """
+    if copy:
+        G = MultiDiGraph(G) if G.is_multigraph() else DiGraph(G)
+    # There is a tradeoff here: the dictionary of node degrees may
+    # require a lot of memory, whereas making a call to `G.out_degree`
+    # inside the loop may be costly in computation time.
+    degree = dict(G.out_degree(weight=weight))
+    for u, v, d in G.edges(data=True):
+        if degree[u] == 0:
+            d[weight] = 0
+        else:
+            d[weight] = d.get(weight, 1) / degree[u]
+    return G