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)
def setUp(self):
np.random.seed(626)
self.matrix_n = 500
self.density = 0.02
self.similarity = random_sparse_matrix(
size=self.matrix_n, density=self.density)