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

Source code for networkx.generators.expanders

# -*- coding: utf-8 -*-
# Copyright 2014 "cheebee7i".
# Copyright 2014 "alexbrc".
# Copyright 2014 Jeffrey Finkelstein <jeffrey.finkelstein@gmail.com>.
"""Provides explicit constructions of expander graphs.

"""
import itertools
import networkx as nx

__all__ = ['margulis_gabber_galil_graph', 'chordal_cycle_graph']

# Other discrete torus expanders can be constructed by using the following edge
# sets. For more information, see Chapter 4, "Expander Graphs", in
# "Pseudorandomness", by Salil Vadhan.
#
# For a directed expander, add edges from (x, y) to:
#
#     (x, y),
#     ((x + 1) % n, y),
#     (x, (y + 1) % n),
#     (x, (x + y) % n),
#     (-y % n, x)
#
# For an undirected expander, add the reverse edges.
#
# Also appearing in the paper of Gabber and Galil:
#
#     (x, y),
#     (x, (x + y) % n),
#     (x, (x + y + 1) % n),
#     ((x + y) % n, y),
#     ((x + y + 1) % n, y)
#
# and:
#
#     (x, y),
#     ((x + 2*y) % n, y),
#     ((x + (2*y + 1)) % n, y),
#     ((x + (2*y + 2)) % n, y),
#     (x, (y + 2*x) % n),
#     (x, (y + (2*x + 1)) % n),
#     (x, (y + (2*x + 2)) % n),
#
[docs]def margulis_gabber_galil_graph(n, create_using=None):
r"""Returns the Margulis-Gabber-Galil undirected MultiGraph on n^2 nodes.

The undirected MultiGraph is regular with degree 8. Nodes are integer
pairs. The second-largest eigenvalue of the adjacency matrix of the graph
is at most 5 \sqrt{2}, regardless of n.

Parameters
----------
n : int
Determines the number of nodes in the graph: n^2.
create_using : NetworkX graph constructor, optional (default MultiGraph)
Graph type to create. If graph instance, then cleared before populated.

Returns
-------
G : graph
The constructed undirected multigraph.

Raises
------
NetworkXError
If the graph is directed or not a multigraph.

"""
G = nx.empty_graph(0, create_using, default=nx.MultiGraph)
if G.is_directed() or not G.is_multigraph():
msg = "create_using must be an undirected multigraph."
raise nx.NetworkXError(msg)

for (x, y) in itertools.product(range(n), repeat=2):
for (u, v) in (((x + 2 * y) % n, y), ((x + (2 * y + 1)) % n, y),
(x, (y + 2 * x) % n), (x, (y + (2 * x + 1)) % n)):
G.add_edge((x, y), (u, v))
G.graph['name'] = "margulis_gabber_galil_graph({0})".format(n)
return G

[docs]def chordal_cycle_graph(p, create_using=None):
"""Returns the chordal cycle graph on p nodes.

The returned graph is a cycle graph on p nodes with chords joining each
vertex x to its inverse modulo p. This graph is a (mildly explicit)
3-regular expander [1]_.

p *must* be a prime number.

Parameters
----------
p : a prime number

The number of vertices in the graph. This also indicates where the
chordal edges in the cycle will be created.

create_using : NetworkX graph constructor, optional (default=nx.Graph)
Graph type to create. If graph instance, then cleared before populated.

Returns
-------
G : graph
The constructed undirected multigraph.

Raises
------
NetworkXError

If create_using indicates directed or not a multigraph.

References
----------

.. [1] Theorem 4.4.2 in A. Lubotzky. "Discrete groups, expanding graphs and
invariant measures", volume 125 of Progress in Mathematics.
Birkhäuser Verlag, Basel, 1994.

"""
G = nx.empty_graph(0, create_using, default=nx.MultiGraph)
if G.is_directed() or not G.is_multigraph():
msg = "create_using must be an undirected multigraph."
raise nx.NetworkXError(msg)

for x in range(p):
left = (x - 1) % p
right = (x + 1) % p
# Here we apply Fermat's Little Theorem to compute the multiplicative
# inverse of x in Z/pZ. By Fermat's Little Theorem,
#
#     x^p = x (mod p)
#
# Therefore,
#
#     x * x^(p - 2) = 1 (mod p)
#
# The number 0 is a special case: we just let its inverse be itself.
chord = pow(x, p - 2, p) if x > 0 else 0
for y in (left, right, chord):