dgllife.utils.ConcatFeaturizer

class dgllife.utils.ConcatFeaturizer(func_list)

Concatenate the evaluation results of multiple functions as a single feature.

Parameters

func_list (list) – List of functions for computing molecular descriptors from objects of a same particular data type, e.g. rdkit.Chem.rdchem.Atom. Each function is of signature func(data_type) -> list of float or bool or int. The resulting order of the features will follow that of the functions in the list.

Examples

Setup for demo.

>>> from dgllife.utils import ConcatFeaturizer
>>> from rdkit import Chem
>>> smi = 'CCO'
>>> mol = Chem.MolFromSmiles(smi)

Concatenate multiple atom descriptors as a single node feature.

>>> from dgllife.utils import atom_degree, atomic_number, BaseAtomFeaturizer
>>> # Construct a featurizer for featurizing one atom a time
>>> atom_concat_featurizer = ConcatFeaturizer([atom_degree, atomic_number])
>>> # Construct a featurizer for featurizing all atoms in a molecule
>>> mol_atom_featurizer = BaseAtomFeaturizer({'h': atom_concat_featurizer})
>>> mol_atom_featurizer(mol)
{'h': tensor([[1., 6.],
              [2., 6.],
              [1., 8.]])}

Conctenate multiple bond descriptors as a single edge feature.

>>> from dgllife.utils import bond_type_one_hot, bond_is_in_ring, BaseBondFeaturizer
>>> # Construct a featurizer for featurizing one bond a time
>>> bond_concat_featurizer = ConcatFeaturizer([bond_type_one_hot, bond_is_in_ring])
>>> # Construct a featurizer for featurizing all bonds in a molecule
>>> mol_bond_featurizer = BaseBondFeaturizer({'h': bond_concat_featurizer})
>>> mol_bond_featurizer(mol)
{'h': tensor([[1., 0., 0., 0., 0.],
              [1., 0., 0., 0., 0.],
              [1., 0., 0., 0., 0.],
              [1., 0., 0., 0., 0.]])}

__init__(func_list)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(func_list)

Initialize self.