# 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._dispatchable
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._dispatchable
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._dispatchable
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))