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",
]


[docs] @not_implemented_for("undirected") @nx._dispatch 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]
[docs] @not_implemented_for("undirected") @nx._dispatch 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))
[docs] @not_implemented_for("undirected") @nx._dispatch 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