Example script to use Nauty from Python

Nauty can be used to reduce any graph into a normal form. In this notebook, we show how to use the Nauty functionality from Python.

import numpy as np
import oapackage

Define a function to invert a permutation.

def inverse_permutation(perm):
    inverse = [0] * len(perm)
    for i, p in enumerate(perm):
        inverse[p] = i
    return inverse

We define a graph with 5 nodes. The graph is defined by the incidence matrix of size \(5\times 5\) and a coloring with two colors.

graph= np.zeros( (5,5), dtype=int); graph[0,1]=graph[0,2]=graph[0,3]=graph[1,3]=1;
graph = np.maximum(graph, graph.T) # make array symmetric
colors = [0,0,0,1,1]

Reduce the graph to normal form using Nauty.

help(oapackage.reduceGraphNauty)

Help on function reduceGraphNauty in module oalib:

reduceGraphNauty(G, colors=None, verbose=1)
    Return vertex transformation reducing array to normal form

    The reduction is calculated using `Nauty <http://users.cecs.anu.edu.au/~bdm/nauty/>`_

    Args:
        G (numpy array or array_link) :   the graph in incidence matrix form
        colors (list or None): an optional vertex coloring
    Returns:
        v: relabelling of the vertices

tr = oapackage.reduceGraphNauty(graph, colors=colors, verbose=0)
tri = inverse_permutation(tr)

graph_reduced=oapackage.transformGraphMatrix(graph, tri)

print('normal form reduction: %s' % (tr,))
print('input graph: ')
print(graph)

print('reduced graph: ')
print(graph_reduced)

colorsr=[colors[idx] for idx in tri]
print('colors reduced: %s' % (colorsr,))

normal form reduction: (1, 2, 0, 4, 3)
input graph:
[[0 1 1 1 0]
 [1 0 0 1 0]
 [1 0 0 0 0]
 [1 1 0 0 0]
 [0 0 0 0 0]]
reduced graph:
[[0 0 1 0 1]
 [0 0 1 0 0]
 [1 1 0 0 1]
 [0 0 0 0 0]
 [1 0 1 0 0]]
colors reduced: [0, 0, 0, 1, 1]

Apply a random permutation to the graph and reduce the graph again.

perm = np.random.permutation(5); iperm = inverse_permutation(perm)
print('permutation: %s' % (perm,))
graph2 = graph[perm, :][:,perm]
colors2=[colors[idx] for idx in perm]

permutation: [4 3 2 1 0]

Show the transformed matrix and color vector.

print(graph2)
print(colors2)

[[0 0 0 0 0]
 [0 0 0 1 1]
 [0 0 0 0 1]
 [0 1 0 0 1]
 [0 1 1 1 0]]
[1, 1, 0, 0, 0]

tr2 = oapackage.reduceGraphNauty(graph2, colors=colors2, verbose=0)
tr2i = inverse_permutation(tr2)

colors2r=[colors2[idx] for idx in tr2]

graph2reduced=oapackage.transformGraphMatrix(graph2, tr2i)

print('tr2: %s' % (tr2,))
print('input graph: ')
print(graph2)

print('reduced graph: ')
print(graph2reduced)

print('colors2r: %s' % (colors2r,))

tr2: (3, 2, 4, 0, 1)
input graph:
[[0 0 0 0 0]
 [0 0 0 1 1]
 [0 0 0 0 1]
 [0 1 0 0 1]
 [0 1 1 1 0]]
reduced graph:
[[0 0 1 0 1]
 [0 0 1 0 0]
 [1 1 0 0 1]
 [0 0 0 0 0]
 [1 0 1 0 0]]
colors2r: [0, 0, 0, 1, 1]

Check that the two reduced graphs are equal.

if np.all(graph_reduced==graph2reduced):
    print('reduced arrays are equal!')

reduced arrays are equal!