| """Functions for generating stochastic graphs from a given weighted directed |
| graph. |
| |
| """ |
|
|
| import networkx as nx |
| from networkx.classes import DiGraph, MultiDiGraph |
| from networkx.utils import not_implemented_for |
|
|
| __all__ = ["stochastic_graph"] |
|
|
|
|
| @not_implemented_for("undirected") |
| @nx._dispatchable( |
| edge_attrs="weight", mutates_input={"not copy": 1}, returns_graph=True |
| ) |
| 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 positive number. |
| |
| """ |
| if copy: |
| G = MultiDiGraph(G) if G.is_multigraph() else DiGraph(G) |
| |
| |
| |
| 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] |
| nx._clear_cache(G) |
| return G |
|
|
