Source code for networkx.algorithms.mis

# -*- coding: utf-8 -*-
# $Id: maximalIndependentSet.py 576 2011-03-01 05:50:34Z lleeoo $
"""
Algorithm to find a maximal (not maximum) independent set.

"""
#    Leo Lopes <leo.lopes@monash.edu>
#    Aric Hagberg <hagberg@lanl.gov>
#    Dan Schult <dschult@colgate.edu>
#    Pieter Swart <swart@lanl.gov>
#    All rights reserved.
#    BSD license.

__author__ = "\n".join(["Leo Lopes <leo.lopes@monash.edu>",
                        "Loïc Séguin-C. <loicseguin@gmail.com>"])

__all__ = ['maximal_independent_set']

import random
import networkx as nx

[docs]def maximal_independent_set(G, nodes=None):
    """Return a random maximal independent set guaranteed to contain
    a given set of nodes.

    An independent set is a set of nodes such that the subgraph
    of G induced by these nodes contains no edges. A maximal
    independent set is an independent set such that it is not possible
    to add a new node and still get an independent set.
    
    Parameters
    ----------
    G : NetworkX graph 

    nodes : list or iterable
       Nodes that must be part of the independent set. This set of nodes
       must be independent.

    Returns
    -------
    indep_nodes : list 
       List of nodes that are part of a maximal independent set.

    Raises
    ------
    NetworkXUnfeasible
       If the nodes in the provided list are not part of the graph or
       do not form an independent set, an exception is raised.

    Examples
    --------
    >>> G = nx.path_graph(5)
    >>> nx.maximal_independent_set(G) # doctest: +SKIP
    [4, 0, 2]
    >>> nx.maximal_independent_set(G, [1]) # doctest: +SKIP
    [1, 3]
    
    Notes
    ------
    This algorithm does not solve the maximum independent set problem.

    """
    if not nodes:
        nodes = set([random.choice(G.nodes())])
    else:
        nodes = set(nodes)
    if not nodes.issubset(G):
        raise nx.NetworkXUnfeasible(
                "%s is not a subset of the nodes of G" % nodes)
    neighbors = set.union(*[set(G.neighbors(v)) for v in nodes])
    if set.intersection(neighbors, nodes):
        raise nx.NetworkXUnfeasible(
                "%s is not an independent set of G" % nodes)
    indep_nodes = list(nodes)
    available_nodes = set(G.nodes()).difference(neighbors.union(nodes))
    while available_nodes:
        node = random.choice(list(available_nodes))
        indep_nodes.append(node)
        available_nodes.difference_update(G.neighbors(node) + [node])
    return indep_nodes