def bond_features(bond: Chem.rdchem.Bond,
distance_path: int = None,
distance_3d: int = None) -> List[Union[bool, int, float]]:
"""
Builds a feature vector for a bond.
:param bond: A RDKit bond.
:param distance_path: The topological (path) distance between the atoms in the bond.
Note: This is always 1 if the atoms are actually bonded and >1 for "virtual" edges between non-bonded atoms.
:param distance_3d: The bin index of the 3D distance in THREE_D_DISTANCE_BINS.
:return: A PyTorch tensor containing the bond features.
"""
if bond is None:
fbond = [1] + [0] * (BOND_FDIM - 1)
else:
bt = bond.GetBondType()
fbond = [
0, # bond is not None
bt == Chem.rdchem.BondType.SINGLE,
bt == Chem.rdchem.BondType.DOUBLE,
bt == Chem.rdchem.BondType.TRIPLE,
bt == Chem.rdchem.BondType.AROMATIC,
(bond.GetIsConjugated() if bt is not None else 0),
(bond.IsInRing() if bt is not None else 0)
]
fbond += onek_encoding_unk(int(bond.GetStereo()), list(range(6)))
if distance_path is not None:
fbond += onek_encoding_unk(distance_path, PATH_DISTANCE_BINS)
if distance_3d is not None:
fbond += onek_encoding_unk(distance_3d, THREE_D_DISTANCE_BINS)
return fbond
def bond_features(bond: Chem.rdchem.Bond,
args) -> List[Union[bool, int, float]]:
"""
Builds a feature vector for a bond.
:param bond: A RDKit bond.
:return: A list containing the bond features.
"""
bond_fdim = get_bond_fdim(args)
if bond is None:
fbond = [1] + [0] * (bond_fdim - 1)
else:
bt = bond.GetBondType()
fbond = [
0, # bond is not None
bt == Chem.rdchem.BondType.SINGLE,
bt == Chem.rdchem.BondType.DOUBLE,
bt == Chem.rdchem.BondType.TRIPLE,
bt == Chem.rdchem.BondType.AROMATIC,
(bond.GetIsConjugated() if bt is not None else 0),
(bond.IsInRing() if bt is not None else 0)
]
# if args.chiral_features:
# fbond += onek_encoding_unk(int(bond.GetStereo()), list(range(6))) # remove global cis/trans tags
return fbond
def getBondFeatures(b: Chem.rdchem.Bond):
return [
b.GetBeginAtomIdx(),
b.GetEndAtomIdx(),
b.GetBondTypeAsDouble(),
int(b.GetIsAromatic()),
int(b.GetIsConjugated())
]
def get_path_bond_feature(bond: Chem.rdchem.Bond):
"""Given a rdkit bond object, returns the bond features for that bond.
When the given input is none, returns a 0-vector"""
if bond is None:
return torch.zeros(N_BOND_FEATS)
else:
bond_type = onek_unk_encoding(bond.GetBondType(), BOND_TYPES)
conj = [int(bond.GetIsConjugated())]
ring = [int(bond.IsInRing())]
return torch.Tensor(bond_type + conj + ring)
def get_bond_features(bond: Chem.rdchem.Bond) -> List[Union[bool, int, float]]:
bond_type = bond.GetBondType()
features = [
0, # bond is not None
bond_type == Chem.rdchem.BondType.SINGLE,
bond_type == Chem.rdchem.BondType.DOUBLE,
bond_type == Chem.rdchem.BondType.TRIPLE,
bond_type == Chem.rdchem.BondType.AROMATIC,
(bond.GetIsConjugated() if bond_type is not None else 0),
(bond.IsInRing() if bond_type is not None else 0)
]
features += one_hot_vector(int(bond.GetStereo()),
list(range(6)),
extra_category=True)
return features
def get_bond_features(bond:Chem.rdchem.Bond) -> np.ndarray:
"Concats all bond features together and returns numpy array of bools"
potential_bond_types_list = [Chem.rdchem.BondType.SINGLE,
Chem.rdchem.BondType.DOUBLE,
Chem.rdchem.BondType.TRIPLE,
Chem.rdchem.BondType.AROMATIC]
encoded_bond_type_list = one_of_k(bond.GetBondType(),
potential_bond_types_list)
feature_vector = np.array(encoded_bond_type_list +
[bond.GetIsConjugated()] +
[bond.IsInRing()])
return feature_vector
def bond_features(bond: Chem.rdchem.Bond) -> List[Union[bool, int, float]]:
if bond is None:
fbond = [1] + [0] * (BOND_FDIM - 1)
else:
bt = bond.GetBondType()
fbond = [
0, # bond is not None
bt == Chem.rdchem.BondType.SINGLE,
bt == Chem.rdchem.BondType.DOUBLE,
bt == Chem.rdchem.BondType.TRIPLE,
bt == Chem.rdchem.BondType.AROMATIC,
(bond.GetIsConjugated() if bt is not None else 0),
(bond.IsInRing() if bt is not None else 0)
]
fbond += onek_encoding_unk(int(bond.GetStereo()), list(range(6)))
return fbond
def bond_features(bond: Chem.rdchem.Bond) -> List[int]:
"""
Builds a feature vector for a bond.
:param bond: A RDKit bond.
:return: A list containing the bond features.
"""
assert bond is not None
bt = bond.GetBondType()
fbond = [
0, # bond is not None
bt == Chem.rdchem.BondType.SINGLE,
bt == Chem.rdchem.BondType.DOUBLE,
bt == Chem.rdchem.BondType.TRIPLE,
bt == Chem.rdchem.BondType.AROMATIC,
(bond.GetIsConjugated() if bt is not None else 0),
(bond.IsInRing() if bt is not None else 0)
]
fbond += onek_encoding_unk(int(bond.GetStereo()), list(range(6)))
return fbond
def get_bond_features(bond: Chem.rdchem.Bond, bt_only: bool = False):
"""Given an bond object, returns a numpy array of features.
bond can be None, in which case returns default features for a non-bond.
"""
# Bond features are bond type, conjugacy, and ring-membership
if bond is None:
bond_type = onek_unk_encoding(None, BOND_TYPES)
conj = [0]
ring = [0]
else:
bond_type = onek_unk_encoding(bond.GetBondType(), BOND_TYPES)
conj = [int(bond.GetIsConjugated())]
ring = [int(bond.IsInRing())]
if bt_only:
feature_array = bond_type
else:
feature_array = bond_type + conj + ring
return torch.Tensor(feature_array)
def bond_features(bond: Chem.rdchem.Bond) -> List[Union[bool, int, float]]:
"""
Builds a feature vector for a bond.
:param bond: An RDKit bond.
:return: A list containing the bond features.
"""
if bond is None:
fbond = [1] + [0] * (BOND_FDIM - 1)
else:
bt = bond.GetBondType()
fbond = [
0, # bond is not None
bt == Chem.rdchem.BondType.SINGLE,
bt == Chem.rdchem.BondType.DOUBLE,
bt == Chem.rdchem.BondType.TRIPLE,
bt == Chem.rdchem.BondType.AROMATIC,
(bond.GetIsConjugated() if bt is not None else 0),
(bond.IsInRing() if bt is not None else 0)
]
fbond += onek_encoding_unk(int(bond.GetStereo()), list(range(6)))
return fbond
