def test_mds_params(self): np.random.seed(14) X = np.random.random((10, 2)) y = np.random.randint(0, 2, 10) X_cand = np.random.random((15, 2)) alce = ALCE(self.classes, self.regressor, self.cost_matrix, random_state=14, mds_params={ 'n_jobs': 1, 'verbose': 2 }) cand1 = alce.query(X_cand, X, y) alce = ALCE(self.classes, self.regressor, self.cost_matrix, random_state=14, mds_params={'n_jobs': 2}) cand2 = alce.query(X_cand, X, y) np.testing.assert_array_equal(cand1, cand2) alce = ALCE(self.classes, self.regressor, self.cost_matrix, mds_params={'dissimilarity': 'wrong'}) self.assertRaises(ValueError, alce.query, X_cand, X, y) alce = ALCE(base_regressor=self.regressor, classes=[0, 1], mds_params={'dissimilarity': 'precomputed'}) query_indices = alce.query([[0], [100], [200]], [[0], [200]], [0, 1]) np.testing.assert_array_equal(query_indices, [1])
def test_query_param_X(self): alce = ALCE(self.classes, self.regressor, self.cost_matrix) self.assertRaises(ValueError, alce.query, X_cand=self.X_cand, X=np.ones((5, 3)), y=self.y) _, result = alce.query(self.X_cand, X=self.X, y=[MISSING_LABEL] * len(self.X), return_utilities=True) np.testing.assert_array_equal(result, np.ones((1, len(self.X_cand))))
def test_query(self): alce = ALCE(base_regressor=self.regressor, classes=[0, 1]) query_indices = alce.query([[0], [100], [200]], [[0], [200]], [0, 1]) np.testing.assert_array_equal(query_indices, [1])