Loading deepchem/data/datasets.py +6 −1 Original line number Diff line number Diff line Loading @@ -623,7 +623,12 @@ class DiskDataset(Dataset): for (X_shard, y_shard, w_shard, ids_shard) in dataset.itershards(): n_samples = X_shard.shape[0] for i in range(n_samples): yield (X_shard[i], y_shard[i], w_shard[i], ids_shard[i]) def sanitize(elem): if elem is None: return None else: return elem[i] yield map(sanitize, [X_shard, y_shard, w_shard, ids_shard]) return iterate(self) def transform(self, fn, **args): Loading deepchem/data/tests/__init__.py +9 −0 Original line number Diff line number Diff line Loading @@ -91,3 +91,12 @@ def load_gaussian_cdf_data(): loader = dc.data.UserCSVLoader( tasks=tasks, featurizer=featurizer, id_field="id") return loader.featurize(input_file) def load_unlabelled_data(): current_dir = os.path.dirname(os.path.abspath(__file__)) featurizer = dc.feat.CircularFingerprint(size=1024) tasks = [] input_file = os.path.join(current_dir, "../../data/tests/no_labels.csv") loader = dc.data.CSVLoader( tasks=tasks, smiles_field="smiles", featurizer=featurizer) return loader.featurize(input_file) No newline at end of file deepchem/trans/tests/test_transformers.py +14 −0 Original line number Diff line number Diff line Loading @@ -49,6 +49,20 @@ class TestTransformers(unittest.TestCase): # Check that untransform does the right thing. np.testing.assert_allclose(log_transformer.untransform(y_t), y) def test_transform_unlabelled(self): ul_dataset = dc.data.tests.load_unlabelled_data() # transforming y should raise an exception with self.assertRaises(ValueError) as context: dc.trans.transformers.Transformer(transform_y=True).transform(ul_dataset) # transforming w should raise an exception with self.assertRaises(ValueError) as context: dc.trans.transformers.Transformer(transform_w=True).transform(ul_dataset) # transforming X should be okay dc.trans.NormalizationTransformer(transform_X=True, dataset=ul_dataset).transform(ul_dataset) def test_X_log_transformer(self): """Tests logarithmic data transformer.""" solubility_dataset = dc.data.tests.load_solubility_data() Loading deepchem/trans/transformers.py +5 −0 Original line number Diff line number Diff line Loading @@ -79,6 +79,11 @@ class Transformer(object): Transforms all internally stored data. Adds X-transform, y-transform columns to metadata. """ _, y_shape, w_shape, _ = dataset.get_shape() if y_shape == tuple() and self.transform_y: raise ValueError("Cannot transform y when y_values are not present") if w_shape == tuple() and self.transform_w: raise ValueError("Cannot transform w when w_values are not present") return dataset.transform(lambda X, y, w: self.transform_array(X, y, w)) def transform_on_array(self, X, y, w): Loading Loading
deepchem/data/datasets.py +6 −1 Original line number Diff line number Diff line Loading @@ -623,7 +623,12 @@ class DiskDataset(Dataset): for (X_shard, y_shard, w_shard, ids_shard) in dataset.itershards(): n_samples = X_shard.shape[0] for i in range(n_samples): yield (X_shard[i], y_shard[i], w_shard[i], ids_shard[i]) def sanitize(elem): if elem is None: return None else: return elem[i] yield map(sanitize, [X_shard, y_shard, w_shard, ids_shard]) return iterate(self) def transform(self, fn, **args): Loading
deepchem/data/tests/__init__.py +9 −0 Original line number Diff line number Diff line Loading @@ -91,3 +91,12 @@ def load_gaussian_cdf_data(): loader = dc.data.UserCSVLoader( tasks=tasks, featurizer=featurizer, id_field="id") return loader.featurize(input_file) def load_unlabelled_data(): current_dir = os.path.dirname(os.path.abspath(__file__)) featurizer = dc.feat.CircularFingerprint(size=1024) tasks = [] input_file = os.path.join(current_dir, "../../data/tests/no_labels.csv") loader = dc.data.CSVLoader( tasks=tasks, smiles_field="smiles", featurizer=featurizer) return loader.featurize(input_file) No newline at end of file
deepchem/trans/tests/test_transformers.py +14 −0 Original line number Diff line number Diff line Loading @@ -49,6 +49,20 @@ class TestTransformers(unittest.TestCase): # Check that untransform does the right thing. np.testing.assert_allclose(log_transformer.untransform(y_t), y) def test_transform_unlabelled(self): ul_dataset = dc.data.tests.load_unlabelled_data() # transforming y should raise an exception with self.assertRaises(ValueError) as context: dc.trans.transformers.Transformer(transform_y=True).transform(ul_dataset) # transforming w should raise an exception with self.assertRaises(ValueError) as context: dc.trans.transformers.Transformer(transform_w=True).transform(ul_dataset) # transforming X should be okay dc.trans.NormalizationTransformer(transform_X=True, dataset=ul_dataset).transform(ul_dataset) def test_X_log_transformer(self): """Tests logarithmic data transformer.""" solubility_dataset = dc.data.tests.load_solubility_data() Loading
deepchem/trans/transformers.py +5 −0 Original line number Diff line number Diff line Loading @@ -79,6 +79,11 @@ class Transformer(object): Transforms all internally stored data. Adds X-transform, y-transform columns to metadata. """ _, y_shape, w_shape, _ = dataset.get_shape() if y_shape == tuple() and self.transform_y: raise ValueError("Cannot transform y when y_values are not present") if w_shape == tuple() and self.transform_w: raise ValueError("Cannot transform w when w_values are not present") return dataset.transform(lambda X, y, w: self.transform_array(X, y, w)) def transform_on_array(self, X, y, w): Loading
