Source code for networkx.algorithms.isolate

"""
Functions for identifying isolate (degree zero) nodes.
"""
import networkx as nx

__all__ = ["is_isolate", "isolates", "number_of_isolates"]


[docs] @nx._dispatch def is_isolate(G, n): """Determines whether a node is an isolate. An *isolate* is a node with no neighbors (that is, with degree zero). For directed graphs, this means no in-neighbors and no out-neighbors. Parameters ---------- G : NetworkX graph n : node A node in `G`. Returns ------- is_isolate : bool True if and only if `n` has no neighbors. Examples -------- >>> G = nx.Graph() >>> G.add_edge(1, 2) >>> G.add_node(3) >>> nx.is_isolate(G, 2) False >>> nx.is_isolate(G, 3) True """ return G.degree(n) == 0
[docs] @nx._dispatch def isolates(G): """Iterator over isolates in the graph. An *isolate* is a node with no neighbors (that is, with degree zero). For directed graphs, this means no in-neighbors and no out-neighbors. Parameters ---------- G : NetworkX graph Returns ------- iterator An iterator over the isolates of `G`. Examples -------- To get a list of all isolates of a graph, use the :class:`list` constructor:: >>> G = nx.Graph() >>> G.add_edge(1, 2) >>> G.add_node(3) >>> list(nx.isolates(G)) [3] To remove all isolates in the graph, first create a list of the isolates, then use :meth:`Graph.remove_nodes_from`:: >>> G.remove_nodes_from(list(nx.isolates(G))) >>> list(G) [1, 2] For digraphs, isolates have zero in-degree and zero out_degre:: >>> G = nx.DiGraph([(0, 1), (1, 2)]) >>> G.add_node(3) >>> list(nx.isolates(G)) [3] """ return (n for n, d in G.degree() if d == 0)
[docs] @nx._dispatch def number_of_isolates(G): """Returns the number of isolates in the graph. An *isolate* is a node with no neighbors (that is, with degree zero). For directed graphs, this means no in-neighbors and no out-neighbors. Parameters ---------- G : NetworkX graph Returns ------- int The number of degree zero nodes in the graph `G`. """ # TODO This can be parallelized. return sum(1 for v in isolates(G))