This documents an unmaintained version of NetworkX. Please upgrade to a maintained version and see the current NetworkX documentation.

Source code for networkx.generators.ego

Ego graph.
#    Copyright (C) 2010 by 
#    Aric Hagberg <hagberg@lanl.gov>
#    Dan Schult <dschult@colgate.edu>
#    Pieter Swart <swart@lanl.gov>
#    All rights reserved.
#    BSD license.
__author__ = """\n""".join(['Drew Conway <drew.conway@nyu.edu>',
                            'Aric Hagberg <hagberg@lanl.gov>'])
__all__ = ['ego_graph']

import networkx as nx

[docs]def ego_graph(G,n,radius=1,center=True,undirected=False,distance=None): """Returns induced subgraph of neighbors centered at node n within a given radius. Parameters ---------- G : graph A NetworkX Graph or DiGraph n : node A single node radius : number, optional Include all neighbors of distance<=radius from n. center : bool, optional If False, do not include center node in graph undirected : bool, optional If True use both in- and out-neighbors of directed graphs. distance : key, optional Use specified edge data key as distance. For example, setting distance='weight' will use the edge weight to measure the distance from the node n. Notes ----- For directed graphs D this produces the "out" neighborhood or successors. If you want the neighborhood of predecessors first reverse the graph with D.reverse(). If you want both directions use the keyword argument undirected=True. Node, edge, and graph attributes are copied to the returned subgraph. """ if undirected: if distance is not None: sp,_=nx.single_source_dijkstra(G.to_undirected(), n,cutoff=radius, weight=distance) else: sp=nx.single_source_shortest_path_length(G.to_undirected(), n,cutoff=radius) else: if distance is not None: sp,_=nx.single_source_dijkstra(G, n,cutoff=radius, weight=distance) else: sp=nx.single_source_shortest_path_length(G,n,cutoff=radius) H=G.subgraph(sp).copy() if not center: H.remove_node(n) return H