Source code for networkx.algorithms.components.attracting

"""Attracting components."""

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

__all__ = [
    "number_attracting_components",
    "attracting_components",
    "is_attracting_component",
]




@not_implemented_for("undirected")
@nx._dispatchable
def attracting_components(G):
    """Generates the attracting components in `G`.

    An attracting component in a directed graph `G` is a strongly connected
    component with the property that a random walker on the graph will never
    leave the component, once it enters the component.

    The nodes in attracting components can also be thought of as recurrent
    nodes.  If a random walker enters the attractor containing the node, then
    the node will be visited infinitely often.

    To obtain induced subgraphs on each component use:
    ``(G.subgraph(c).copy() for c in attracting_components(G))``

    Parameters
    ----------
    G : DiGraph, MultiDiGraph
        The graph to be analyzed.

    Returns
    -------
    attractors : generator of sets
        A generator of sets of nodes, one for each attracting component of G.

    Raises
    ------
    NetworkXNotImplemented
        If the input graph is undirected.

    See Also
    --------
    number_attracting_components
    is_attracting_component

    """
    scc = list(nx.strongly_connected_components(G))
    cG = nx.condensation(G, scc)
    for n in cG:
        if cG.out_degree(n) == 0:
            yield scc[n]





@not_implemented_for("undirected")
@nx._dispatchable
def number_attracting_components(G):
    """Returns the number of attracting components in `G`.

    Parameters
    ----------
    G : DiGraph, MultiDiGraph
        The graph to be analyzed.

    Returns
    -------
    n : int
        The number of attracting components in G.

    Raises
    ------
    NetworkXNotImplemented
        If the input graph is undirected.

    See Also
    --------
    attracting_components
    is_attracting_component

    """
    return sum(1 for ac in attracting_components(G))





@not_implemented_for("undirected")
@nx._dispatchable
def is_attracting_component(G):
    """Returns True if `G` consists of a single attracting component.

    Parameters
    ----------
    G : DiGraph, MultiDiGraph
        The graph to be analyzed.

    Returns
    -------
    attracting : bool
        True if `G` has a single attracting component. Otherwise, False.

    Raises
    ------
    NetworkXNotImplemented
        If the input graph is undirected.

    See Also
    --------
    attracting_components
    number_attracting_components

    """
    ac = list(attracting_components(G))
    if len(ac) == 1:
        return len(ac[0]) == len(G)
    return False