how to compute 'nearby' nodes with networkx

Question

What I'm looking for here may well be a built-in function in networkx, and have a mathematical name - if so, I'd like to know what it is! it is very difficult to Google for, it seems.

Given a graph G and a starting node i, I'd like to find the subgraph of all the nodes "within P edges" from i - that is, those that are connected to i by a path of less than P edges.

My draft implementation for this is:

import networkx as nx

N = 30
G = nx.Graph()

# populate the graph...
G.add_cycle(range(N))

# the starting node:
i = 15

# the 'distance' limit:
P = 4

neighborhood = [i]
new_neighbors = [i]
depth = 0

while depth < P:
    new_neighbors = list(set(sum([
        [k for k in G[j].keys() if k not in neighborhood]
    for j in new_neighbors], [])))

    neighborhood.extend(new_neighbors)

    depth += 1

Gneighbors = G.subgraph(neighborhood)

This code works, by the way, so I don't need help with the implementation. I would simply like to know if this has a name, and whether it is provided by the networkx library.

It is very useful when your code is crashing and you want to see why - you can render just the "locality/region" of the graph near the problem node.

Answer 1

Two years late, but I was looking for this same thing and found a built-in that I think will get the subgraph you want: ego_graph. The function signature and documentation:

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.