def test_match_graphs_shuffled():
L1, A1 = graph2matrices([[0], [1], [2]], [(0, 1), (0, 2)])
L2, A2 = graph2matrices([[1], [0], [2]], [(1, 0), (1, 2)])
P = match_graphs(A1, A2, L1, L2, device_id=-1)
P_expected = np.array([[0, 1, 0],
[1, 0, 0],
[0, 0, 1]])
assert np.allclose(P, P_expected)
def test_match_graphs():
L1, A1 = graph2matrices(4, [(0, 1), (0, 2), (2, 3)])
L2, A2 = graph2matrices(4, [(0, 1), (0, 2)])
P = match_graphs(A1, A2, L1, L2, device_id=-1)
P_expected = np.array([[1, 0, 0],
[0, 1, 0],
[0, 0, 1],
[0, 0, 0]])
assert np.allclose(P, P_expected)
def test_pfp_identity():
L, A = graph2matrices(3, [(0, 1), (0, 2)])
X = pfp(A, A, L, L, device_id=-1)
X_expected = np.array([[1, 0, 0],
[0, 1, 0],
[0, 0, 1]])
assert np.allclose(X, X_expected, atol=0.1)
def test_match_graphs_identity():
L, A = graph2matrices(3, [(0, 1), (0, 2)])
P = match_graphs(A, A, L, L, device_id=-1)
P_expected = np.array([[1, 0, 0],
[0, 1, 0],
[0, 0, 1]])
assert np.allclose(P, P_expected)
def test_num_nodes():
L1, A1 = graph2matrices(4, [(0, 1), (0, 2), (2, 3)])
L2, A2 = graph2matrices(4, [(0, 1), (0, 2)])
n1, n2 = num_nodes(A1, A2)
assert n1 == 4
assert n2 == 3
"""
.. module:: example
:synopsis: A usage example
"""
from __future__ import print_function
from fastpfp.util import graph2matrices
from fastpfp.match import match_graphs
if __name__ == '__main__':
L1, A1 = graph2matrices([[0], [1], [2], [3]], [(0, 1), (0, 2), (2, 3)])
L2, A2 = graph2matrices([[1], [0], [2]], [(1, 0), (1, 2)])
print('first graph -----------------------------------------')
print(L1)
print(A1)
print('second graph ----------------------------------------')
print(L2)
print(A2)
P = match_graphs(A1, A2, L1, L2, lam=1.0, device_id=-1)
print('permutation matrix----------------------------------------')
print(P)