def test_parallel_hubness_equal_serial_hubness_distance_based(self):
S_k_p, D_k_p, N_k_p = hubness_p(
self.distance, k=5, metric='distance', verbose=True, n_jobs=2)
S_k_s, D_k_s, N_k_s = hubness_s(
self.distance, k=5, metric='distance', verbose=False)
result = np.allclose(S_k_p, S_k_s) & \
np.allclose(D_k_p, D_k_s) & \
np.allclose(N_k_p, N_k_s)
return self.assertTrue(result)
def test_parallel_hubness_equal_serial_hubness_similarity_based(self):
similarity = random_sparse_matrix(size=1000)
S_k_p, D_k_p, N_k_p = hubness_p(
similarity, k=5, metric='similarity', verbose=False, n_jobs=-1)
S_k_s, D_k_s, N_k_s = hubness_s(
similarity, k=5, metric='similarity', verbose=False)
result = np.allclose(S_k_p, S_k_s) & \
np.allclose(D_k_p, D_k_s) & \
np.allclose(N_k_p, N_k_s)
return self.assertTrue(result)
