Loading deepchem/data/data_loader.py +2 −3 Original line number Diff line number Diff line Loading @@ -77,7 +77,7 @@ def featurize_smiles_df(df, featurizer, field, log_every_N=1000, verbose=True): valid_inds = np.array( [1 if elt.size > 0 else 0 for elt in features], dtype=bool) features = [elt for (is_valid, elt) in zip(valid_inds, features) if is_valid] return np.squeeze(np.array(features)), valid_inds return np.reshape(np.array(features), newshape=(-1)), valid_inds def featurize_smiles_np(arr, featurizer, log_every_N=1000, verbose=True): Loading @@ -101,8 +101,7 @@ def featurize_smiles_np(arr, featurizer, log_every_N=1000, verbose=True): [1 if elt.size > 0 else 0 for elt in features], dtype=bool) features = [elt for (is_valid, elt) in zip(valid_inds, features) if is_valid] features = np.squeeze(np.array(features)) return features.reshape( -1,) return features.reshape(-1,) def get_user_specified_features(df, featurizer, verbose=True): Loading Loading
deepchem/data/data_loader.py +2 −3 Original line number Diff line number Diff line Loading @@ -77,7 +77,7 @@ def featurize_smiles_df(df, featurizer, field, log_every_N=1000, verbose=True): valid_inds = np.array( [1 if elt.size > 0 else 0 for elt in features], dtype=bool) features = [elt for (is_valid, elt) in zip(valid_inds, features) if is_valid] return np.squeeze(np.array(features)), valid_inds return np.reshape(np.array(features), newshape=(-1)), valid_inds def featurize_smiles_np(arr, featurizer, log_every_N=1000, verbose=True): Loading @@ -101,8 +101,7 @@ def featurize_smiles_np(arr, featurizer, log_every_N=1000, verbose=True): [1 if elt.size > 0 else 0 for elt in features], dtype=bool) features = [elt for (is_valid, elt) in zip(valid_inds, features) if is_valid] features = np.squeeze(np.array(features)) return features.reshape( -1,) return features.reshape(-1,) def get_user_specified_features(df, featurizer, verbose=True): Loading
