Loading deepchem/feat/base_classes.py +17 −1 Original line number Diff line number Diff line Loading @@ -428,7 +428,23 @@ class DummyFeaturizer(Featurizer): This is useful when the raw dataset has to be used without featurizing the examples. Examples -------- >>> import deepchem as dc >>> smi_map = [[ "N#C[S-].O=C(CBr)c1ccc(C(F)(F)F)cc1>CCO.[K+]", "N#CSCC(=O)c1ccc(C(F)(F)F)cc1" ], [ "C1COCCN1.FCC(Br)c1cccc(Br)n1>CCN(C(C)C)C(C)C.CN(C)C=O.O", "FCC(c1cccc(Br)n1)N1CCOCC1" ]] >>> Featurizer = dc.feat.DummyFeaturizer() >>> smi_feat = Featurizer.featurize(smi_map) >>> smi_feat array([['N#C[S-].O=C(CBr)c1ccc(C(F)(F)F)cc1>CCO.[K+]', 'N#CSCC(=O)c1ccc(C(F)(F)F)cc1'], ['C1COCCN1.FCC(Br)c1cccc(Br)n1>CCN(C(C)C)C(C)C.CN(C)C=O.O', 'FCC(c1cccc(Br)n1)N1CCOCC1']], dtype='<U55') """ def featurize(self, datapoints: Iterable[Any], Loading Loading
deepchem/feat/base_classes.py +17 −1 Original line number Diff line number Diff line Loading @@ -428,7 +428,23 @@ class DummyFeaturizer(Featurizer): This is useful when the raw dataset has to be used without featurizing the examples. Examples -------- >>> import deepchem as dc >>> smi_map = [[ "N#C[S-].O=C(CBr)c1ccc(C(F)(F)F)cc1>CCO.[K+]", "N#CSCC(=O)c1ccc(C(F)(F)F)cc1" ], [ "C1COCCN1.FCC(Br)c1cccc(Br)n1>CCN(C(C)C)C(C)C.CN(C)C=O.O", "FCC(c1cccc(Br)n1)N1CCOCC1" ]] >>> Featurizer = dc.feat.DummyFeaturizer() >>> smi_feat = Featurizer.featurize(smi_map) >>> smi_feat array([['N#C[S-].O=C(CBr)c1ccc(C(F)(F)F)cc1>CCO.[K+]', 'N#CSCC(=O)c1ccc(C(F)(F)F)cc1'], ['C1COCCN1.FCC(Br)c1cccc(Br)n1>CCN(C(C)C)C(C)C.CN(C)C=O.O', 'FCC(c1cccc(Br)n1)N1CCOCC1']], dtype='<U55') """ def featurize(self, datapoints: Iterable[Any], Loading
