Loading deepchem/splits/__init__.py +31 −0 Original line number Diff line number Diff line Loading @@ -95,6 +95,37 @@ class Splitter(object): """ raise NotImplementedError class MolecularWeightSplitter(Splitter): """ Class for doing data splits by molecular weight. """ def split(self, samples, seed=None, frac_train=.8, frac_valid=.1, frac_test=.1, log_every_n=None): """ Splits internal compounds into train/validation/test using the MW calculated by SMILES string. """ np.testing.assert_almost_equal(frac_train + frac_valid + frac_test, 1.) np.random.seed(seed) df = samples.compounds_df mws = [] for _, row in df.iterrows(): mol = Chem.MolFromSmiles(row['smiles']) mw = Chem.rdMolDescriptors.CalcExactMolWt(mol) mws.append(mw) # Sort by increasing MW mws = np.array(mws) sortidx = np.argsort(mws) train_cutoff = frac_train * len(sortidx) valid_cutoff = (frac_train+frac_valid) * len(sortidx) return (sortidx[:train_cutoff], sortidx[train_cutoff:valid_cutoff], sortidx[valid_cutoff:]) class RandomSplitter(Splitter): """ Class for doing random data splits. Loading Loading
deepchem/splits/__init__.py +31 −0 Original line number Diff line number Diff line Loading @@ -95,6 +95,37 @@ class Splitter(object): """ raise NotImplementedError class MolecularWeightSplitter(Splitter): """ Class for doing data splits by molecular weight. """ def split(self, samples, seed=None, frac_train=.8, frac_valid=.1, frac_test=.1, log_every_n=None): """ Splits internal compounds into train/validation/test using the MW calculated by SMILES string. """ np.testing.assert_almost_equal(frac_train + frac_valid + frac_test, 1.) np.random.seed(seed) df = samples.compounds_df mws = [] for _, row in df.iterrows(): mol = Chem.MolFromSmiles(row['smiles']) mw = Chem.rdMolDescriptors.CalcExactMolWt(mol) mws.append(mw) # Sort by increasing MW mws = np.array(mws) sortidx = np.argsort(mws) train_cutoff = frac_train * len(sortidx) valid_cutoff = (frac_train+frac_valid) * len(sortidx) return (sortidx[:train_cutoff], sortidx[train_cutoff:valid_cutoff], sortidx[valid_cutoff:]) class RandomSplitter(Splitter): """ Class for doing random data splits. Loading
