def test_simrank_numpy_no_source_no_target(self):
G = nx.cycle_graph(5)
expected = numpy.array([[
1.0, 0.3947180735764555, 0.570482097206368, 0.570482097206368,
0.3947180735764555
],
[
0.3947180735764555, 1.0,
0.3947180735764555, 0.570482097206368,
0.570482097206368
],
[
0.570482097206368, 0.3947180735764555, 1.0,
0.3947180735764555, 0.570482097206368
],
[
0.570482097206368, 0.570482097206368,
0.3947180735764555, 1.0, 0.3947180735764555
],
[
0.3947180735764555, 0.570482097206368,
0.570482097206368, 0.3947180735764555, 1.0
]])
actual = nx.simrank_similarity_numpy(G)
numpy.testing.assert_allclose(expected, actual, atol=1e-7)
def test_simrank_numpy_source_no_target(self):
G = nx.cycle_graph(5)
expected = numpy.array(
[1.0, 0.3947180735764555, 0.570482097206368, 0.570482097206368, 0.3947180735764555],
)
actual = nx.simrank_similarity_numpy(G, source=0)
numpy.testing.assert_allclose(expected, actual, atol=1e-7)
def CoSimRankNumpy(G,
src=0,
ngh=1,
importance_factor=0.85,
max_iterations=100,
tolerance=0.0001):
print("Start SimRankNumpy")
t0 = time.time()
similarity = nx.simrank_similarity_numpy(
G,
source=src,
target=ngh,
importance_factor=importance_factor,
max_iterations=max_iterations,
tolerance=tolerance)
t1 = time.time()
print("Time: ", t1 - t0)
print("Similarity: ", similarity)
def test_simrank_numpy_source_and_target(self):
G = nx.cycle_graph(5)
expected = 1.0
actual = nx.simrank_similarity_numpy(G, source=0, target=0)
numpy.testing.assert_allclose(expected, actual, atol=1e-7)
def test_simrank_numpy_source_and_target(self):
G = nx.cycle_graph(5)
expected = 1.0
actual = nx.simrank_similarity_numpy(G, source=0, target=0)
numpy.testing.assert_allclose(expected, actual, atol=1e-7)
