from chainer_chemistry.dataset.preprocessors.common import construct_atomic_number_array # NOQA
from chainer_chemistry.dataset.preprocessors.common import construct_discrete_edge_matrix # NOQA
from chainer_chemistry.dataset.preprocessors.common import MolFeatureExtractionError # NOQA
from chainer_chemistry.dataset.preprocessors.common import type_check_num_atoms
from chainer_chemistry.dataset.preprocessors.mol_preprocessor import MolPreprocessor # NOQA
[docs]class RelGATPreprocessor(MolPreprocessor):
"""RelGAT Preprocessor
Args:
max_atoms (int): Max number of atoms for each molecule, if the
number of atoms is more than this value, this data is simply
ignored.
Setting negative value indicates no limit for max atoms.
out_size (int): It specifies the size of array returned by
`get_input_features`.
If the number of atoms in the molecule is less than this value,
the returned arrays is padded to have fixed size.
Setting negative value indicates do not pad returned array.
"""
[docs] def __init__(self, max_atoms=-1, out_size=-1, add_Hs=False):
super(RelGATPreprocessor, self).__init__(add_Hs=add_Hs)
if max_atoms >= 0 and out_size >= 0 and max_atoms > out_size:
raise ValueError('max_atoms {} must be less or equal to '
'out_size {}'.format(max_atoms, out_size))
self.max_atoms = max_atoms
self.out_size = out_size
def get_input_features(self, mol):
"""get input features
Args:
mol (Mol):
Returns:
"""
type_check_num_atoms(mol, self.max_atoms)
atom_array = construct_atomic_number_array(mol, out_size=self.out_size)
adj_array = construct_discrete_edge_matrix(mol, out_size=self.out_size)
return atom_array, adj_array