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Source code for networkx.algorithms.moral

# -*- coding: utf-8 -*-
#   Copyright (C) 2011-2019 by
#   Julien Klaus <julien.klaus@uni-jena.de>
#   All rights reserved.
#   BSD license.
#   Copyright 2016-2019 NetworkX developers.
#   NetworkX is distributed under a BSD license
# Authors: Julien Klaus <julien.klaus@uni-jena.de>
r"""Function for computing the moral graph of a directed graph."""

import networkx as nx
from networkx.utils import not_implemented_for
import itertools

__all__ = ['moral_graph']

[docs]@not_implemented_for('undirected') def moral_graph(G): r"""Return the Moral Graph Returns the moralized graph of a given directed graph. Parameters ---------- G : NetworkX graph Directed graph Returns ------- H : NetworkX graph The undirected moralized graph of G Notes ------ A moral graph is an undirected graph H = (V, E) generated from a directed Graph, where if a node has more than one parent node, edges between these parent nodes are inserted and all directed edges become undirected. https://en.wikipedia.org/wiki/Moral_graph References ---------- .. [1] Wray L. Buntine. 1995. Chain graphs for learning. In Proceedings of the Eleventh conference on Uncertainty in artificial intelligence (UAI'95) """ if G is None: raise ValueError("Expected NetworkX graph!") H = G.to_undirected() for preds in G.pred.values(): predecessors_combinations = itertools.combinations(preds, r=2) H.add_edges_from(predecessors_combinations) return H