Loading deepchem/feat/tests/test_mat_featurizer.py +8 −10 Original line number Diff line number Diff line Loading @@ -23,11 +23,10 @@ class TestMATFeaturizer(unittest.TestCase): featurizer = MATFeaturizer() out = featurizer.featurize(self.mol) assert (type(out) == np.ndarray) assert (out.shape == (1,)) assert (out[0].node_features.shape == (3, 36)) assert (out[0].adjacency_matrix.shape == (3, 3)) assert (out[0].distance_matrix.shape == (3, 3)) expected_node_features = np.array([[[ expected_node_features = np.array([[ 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0. ], [ Loading @@ -36,12 +35,11 @@ class TestMATFeaturizer(unittest.TestCase): ], [ 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0. ]]]) expected_adjacency_matrix = np.array([[[0., 0., 0.], [0., 0., 1.], [0., 1., 0.]]]) expected_distance_matrix = np.array([[[1.e+06, 1.e+06, ]]) expected_adj_matrix = np.array([[0., 0., 0.], [0., 0., 1.], [0., 1., 0.]]) expected_dist_matrix = np.array([[1.e+06, 1.e+06, 1.e+06], [1.e+06, 0.e+00, 1.e+00], [1.e+06, 1.e+00, 0.e+00]]]) [1.e+06, 1.e+00, 0.e+00]]) assert (np.array_equal(out[0].node_features, expected_node_features)) assert (np.array_equal(out[0].adjacency_matrix, expected_adjacency_matrix)) assert (np.array_equal(out[0].distance_matrix, expected_distance_matrix)) assert (np.array_equal(out[0].adjacency_matrix, expected_adj_matrix)) assert (np.array_equal(out[0].distance_matrix, expected_dist_matrix)) Loading
deepchem/feat/tests/test_mat_featurizer.py +8 −10 Original line number Diff line number Diff line Loading @@ -23,11 +23,10 @@ class TestMATFeaturizer(unittest.TestCase): featurizer = MATFeaturizer() out = featurizer.featurize(self.mol) assert (type(out) == np.ndarray) assert (out.shape == (1,)) assert (out[0].node_features.shape == (3, 36)) assert (out[0].adjacency_matrix.shape == (3, 3)) assert (out[0].distance_matrix.shape == (3, 3)) expected_node_features = np.array([[[ expected_node_features = np.array([[ 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0. ], [ Loading @@ -36,12 +35,11 @@ class TestMATFeaturizer(unittest.TestCase): ], [ 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0. ]]]) expected_adjacency_matrix = np.array([[[0., 0., 0.], [0., 0., 1.], [0., 1., 0.]]]) expected_distance_matrix = np.array([[[1.e+06, 1.e+06, ]]) expected_adj_matrix = np.array([[0., 0., 0.], [0., 0., 1.], [0., 1., 0.]]) expected_dist_matrix = np.array([[1.e+06, 1.e+06, 1.e+06], [1.e+06, 0.e+00, 1.e+00], [1.e+06, 1.e+00, 0.e+00]]]) [1.e+06, 1.e+00, 0.e+00]]) assert (np.array_equal(out[0].node_features, expected_node_features)) assert (np.array_equal(out[0].adjacency_matrix, expected_adjacency_matrix)) assert (np.array_equal(out[0].distance_matrix, expected_distance_matrix)) assert (np.array_equal(out[0].adjacency_matrix, expected_adj_matrix)) assert (np.array_equal(out[0].distance_matrix, expected_dist_matrix))
