Loading deepchem/feat/base_classes.py +12 −6 Original line number Diff line number Diff line Loading @@ -30,8 +30,10 @@ class Featurizer(object): Parameters ---------- datapoints: object Any blob of data you like. Subclasss should instantiate this. datapoints: iterable A sequence of objects that you'd like to featurize. Subclassses of `Featurizer` should instantiate the `_featurize` method that featurizes objects in the sequence. Returns ------- Loading @@ -40,6 +42,8 @@ class Featurizer(object): datapoints = list(datapoints) features = [] for i, point in enumerate(datapoints): if i % log_every_n == 0: logger.info("Featurizing datapoint %i" % i) if point is not None: features.append(self._featurize(point)) else: Loading Loading @@ -135,14 +139,14 @@ class MolecularFeaturizer(Featurizer): In general, subclasses of this class will require RDKit to be installed. """ def featurize(self, mols, verbose=True, log_every_n=1000): def featurize(self, mols, log_every_n=1000): """Calculate features for molecules. Parameters ---------- mols : iterable RDKit Mol, or SMILES string, or filename for mol2/sdf/pdb/pdbqt file. mols : RDKit Mol / SMILES string /iterable RDKit Mol, or SMILES string or iterable sequence of RDKit mols/SMILES strings. Returns ------- Loading @@ -162,6 +166,8 @@ class MolecularFeaturizer(Featurizer): mols = list(mols) features = [] for i, mol in enumerate(mols): if i % log_every_n == 0: logger.info("Featurizing datapoint %i" % i) if mol is not None: # Process only case of SMILES strings. if isinstance(mol, str): Loading deepchem/feat/basic.py +3 −3 Original line number Diff line number Diff line Loading @@ -46,8 +46,8 @@ class RDKitDescriptors(MolecularFeaturizer): Attributes ---------- descriptors: list List of RDKit descriptor names used in this class. descriptors: np.ndarray 1D array of RDKit descriptor names used in this class. Note ---- Loading Loading @@ -108,7 +108,7 @@ class RDKitDescriptors(MolecularFeaturizer): Returns ------- rval: np.ndarray Vector of RDKit descriptors for `mol` 1D array of RDKit descriptors for `mol` """ rval = [] for desc_name, function in self.descList: Loading deepchem/feat/coulomb_matrices.py +47 −3 Original line number Diff line number Diff line Loading @@ -27,6 +27,14 @@ class BPSymmetryFunctionInput(MolecularFeaturizer): """ def __init__(self, max_atoms): """Initialize this featurizer. Parameters ---------- max_atoms: int The maximum number of atoms expected for molecules this featurizer will process. """ self.max_atoms = max_atoms def _featurize(self, mol): Loading Loading @@ -92,6 +100,24 @@ class CoulombMatrix(MolecularFeaturizer): upper_tri=False, n_samples=1, seed=None): """Initialize this featurizer. Parameters ---------- max_atoms: int The maximum number of atoms expected for molecules this featurizer will process. remove_hydrogens: bool, optional (default False) If True, remove hydrogens before processing them. randomize: bool, optional (default False) If True, use method `randomize_coulomb_matrices` to randomize Coulomb matrices. upper_tri: bool, optional (default False) Generate only upper triangle part of Coulomb matrices. n_samples: int, optional (default 1) If `randomize` is set to True, the number of random samples to draw. seed: int, optional (default None) Random seed to use. """ try: from rdkit import Chem except ModuleNotFoundError: Loading Loading @@ -163,9 +189,7 @@ class CoulombMatrix(MolecularFeaturizer): return rval def randomize_coulomb_matrix(self, m): """ Randomize a Coulomb matrix as decribed in Montavon et al., New Journal of Physics, 15, (2013), 095003: """Randomize a Coulomb matrix as decribed in [1]_: 1. Compute row norms for M in a vector row_norms. 2. Sample a zero-mean unit-variance noise vector e with dimension Loading @@ -181,6 +205,10 @@ class CoulombMatrix(MolecularFeaturizer): Number of random matrices to generate. seed : int, optional Random seed. References ---------- .. [1] Montavon et al., New Journal of Physics, 15, (2013), 095003 """ rval = [] row_norms = np.asarray([np.linalg.norm(row) for row in m], dtype=float) Loading Loading @@ -263,6 +291,22 @@ class CoulombMatrixEig(CoulombMatrix): randomize=False, n_samples=1, seed=None): """Initialize this featurizer. Parameters ---------- max_atoms: int The maximum number of atoms expected for molecules this featurizer will process. remove_hydrogens: bool, optional (default False) If True, remove hydrogens before processing them. randomize: bool, optional (default False) If True, use method `randomize_coulomb_matrices` to randomize Coulomb matrices. n_samples: int, optional (default 1) If `randomize` is set to True, the number of random samples to draw. seed: int, optional (default None) Random seed to use. """ self.max_atoms = int(max_atoms) self.remove_hydrogens = remove_hydrogens self.randomize = randomize Loading deepchem/feat/graph_features.py +211 −35 Original line number Diff line number Diff line import enum import numpy as np import deepchem as dc from deepchem.feat.base_classes import MolecularFeaturizer Loading @@ -14,21 +15,73 @@ def _featurize_complex(featurizer, mol_pdb_file, protein_pdb_file, log_message): def one_of_k_encoding(x, allowable_set): """Encodes elements of a provided set as integers. Parameters ---------- x: object Must be present in `allowable_set`. allowable_set: list List of allowable quantities. Example ------- >>> import deepchem as dc >>> dc.feat.graph_features.one_of_k_encoding("a", ["a", "b", "c"]) [True, False, False] Raises ------ `ValueError` if `x` is not in `allowable_set`. """ if x not in allowable_set: raise Exception("input {0} not in allowable set{1}:".format( raise ValueError("input {0} not in allowable set{1}:".format( x, allowable_set)) return list(map(lambda s: x == s, allowable_set)) def one_of_k_encoding_unk(x, allowable_set): """Maps inputs not in the allowable set to the last element.""" """Maps inputs not in the allowable set to the last element. Unlike `one_of_k_encoding`, if `x` is not in `allowable_set`, this method pretends that `x` is the last element of `allowable_set`. Parameters ---------- x: object Must be present in `allowable_set`. allowable_set: list List of allowable quantities. Examples -------- >>> dc.feat.graph_features.one_of_k_encoding_unk("s", ["a", "b", "c"]) [False, False, True] """ if x not in allowable_set: x = allowable_set[-1] return list(map(lambda s: x == s, allowable_set)) def get_intervals(l): """For list of lists, gets the cumulative products of the lengths""" """For list of lists, gets the cumulative products of the lengths Note that we add 1 to the lengths of all lists (to avoid an empty list propagating a 0). Parameters ---------- l: list of lists Returns the cumulative product of these lengths. Examples -------- >>> dc.feat.graph_features.get_intervals([[1], [1, 2], [1, 2, 3]]) [1, 3, 12] >>> dc.feat.graph_features.get_intervals([[1], [], [1, 2], [1, 2, 3]]) >>> [1, 1, 3, 12] """ intervals = len(l) * [0] # Initalize with 1 intervals[0] = 1 Loading @@ -39,36 +92,58 @@ def get_intervals(l): def safe_index(l, e): """Gets the index of e in l, providing an index of len(l) if not found""" """Gets the index of e in l, providing an index of len(l) if not found Parameters ---------- l: list List of values e: object Object to check whether `e` is in `l` Examples -------- >>> dc.feat.graph_features.safe_index([1, 2, 3], 1) 0 >>> dc.feat.graph_features.safe_index([1, 2, 3], 7) 3 """ try: return l.index(e) except: return len(l) class GraphConvConstants(enum.Enum): """Allowed Atom Types.""" possible_atom_list = [ 'C', 'N', 'O', 'S', 'F', 'P', 'Cl', 'Mg', 'Na', 'Br', 'Fe', 'Ca', 'Cu', 'Mc', 'Pd', 'Pb', 'K', 'I', 'Al', 'Ni', 'Mn' ] """Allowed Numbers of Hydrogens""" possible_numH_list = [0, 1, 2, 3, 4] """Allowed Valences for Atoms""" possible_valence_list = [0, 1, 2, 3, 4, 5, 6] """Allowed Formal Charges for Atoms""" possible_formal_charge_list = [-3, -2, -1, 0, 1, 2, 3] # To avoid importing rdkit, this is a placeholder list of the correct # length. These will be replaced with rdkit HybridizationType below """This is a placeholder for documentation. These will be replaced with corresponding values of the rdkit HybridizationType""" possible_hybridization_list = ["SP", "SP2", "SP3", "SP3D", "SP3D2"] """Allowed number of radical electrons.""" possible_number_radical_e_list = [0, 1, 2] """Allowed types of Chirality""" possible_chirality_list = ['R', 'S'] """The set of all values allowed.""" reference_lists = [ possible_atom_list, possible_numH_list, possible_valence_list, possible_formal_charge_list, possible_number_radical_e_list, possible_hybridization_list, possible_chirality_list ] """The number of different values that can be taken. See `get_intervals()`""" intervals = get_intervals(reference_lists) # We use E-Z notation for stereochemistry # https://en.wikipedia.org/wiki/E%E2%80%93Z_notation """Possible stereochemistry. We use E-Z notation for stereochemistry https://en.wikipedia.org/wiki/E%E2%80%93Z_notation""" possible_bond_stereo = ["STEREONONE", "STEREOANY", "STEREOZ", "STEREOE"] """Number of different bond types not counting stereochemistry.""" bond_fdim_base = 6 Loading @@ -79,10 +154,39 @@ def get_feature_list(atom): ---------- atom: RDKit.rdchem.Atom Atom to get features for Examples -------- >>> from rdkit import Chem >>> mol = Chem.MolFromSmiles("C") >>> atom = mol.GetAtoms()[0] >>> dc.feat.graph_features.get_feature_list(atom) [0, 4, 4, 3, 0, 2] Note ---- This method requires RDKit to be installed. Returns ------- features: list List of length 6. The i-th value in this list provides the index of the atom in the corresponding feature value list. The 6 feature values lists for this function are `[GraphConvConstants.possible_atom_list, GraphConvConstants.possible_numH_list, GraphConvConstants.possible_valence_list, GraphConvConstants.possible_formal_charge_list, GraphConvConstants.possible_num_radical_e_list]`. """ possible_atom_list = GraphConvConstants.possible_atom_list possible_numH_list = GraphConvConstants.possible_numH_list possible_valence_list = GraphConvConstants.possible_valence_list possible_formal_charge_list = GraphConvConstants.possible_formal_charge_list possible_number_radical_e_list = GraphConvConstants.possible_number_radical_e_list possible_hybridization_list = GraphConvConstants.possible_hybridization_list # Replace the hybridization from rdkit import Chem global possible_hybridization_list #global possible_hybridization_list possible_hybridization_list = [ Chem.rdchem.HybridizationType.SP, Chem.rdchem.HybridizationType.SP2, Chem.rdchem.HybridizationType.SP3, Chem.rdchem.HybridizationType.SP3D, Loading @@ -101,7 +205,20 @@ def get_feature_list(atom): def features_to_id(features, intervals): """Convert list of features into index using spacings provided in intervals""" """Convert list of features into index using spacings provided in intervals Parameters ---------- features: list List of features as returned by `get_feature_list()` intervals: list List of intervals as returned by `get_intervals()` Returns ------- id: int The index in a feature vector given by the given set of features. """ id = 0 for k in range(len(intervals)): id += features[k] * intervals[k] Loading @@ -112,6 +229,20 @@ def features_to_id(features, intervals): def id_to_features(id, intervals): """Given an index in a feature vector, return the original set of features. Parameters ---------- id: int The index in a feature vector given by the given set of features. intervals: list List of intervals as returned by `get_intervals()` Returns ------- features: list List of features as returned by `get_feature_list()` """ features = 6 * [0] # Correct for null Loading @@ -133,6 +264,11 @@ def atom_to_id(atom): ---------- atom: RDKit.rdchem.Atom Atom to convert to ids. Returns ------- id: int The index in a feature vector given by the given set of features. """ features = get_feature_list(atom) return features_to_id(features, intervals) Loading @@ -154,6 +290,10 @@ def atom_features(atom, If true, model hydrogens explicitly use_chirality: bool, optional If true, use chirality information. Returns ------- np.ndarray of per-atom features. """ if bool_id_feat: return np.array([atom_to_id(atom)]) Loading Loading @@ -245,6 +385,12 @@ def bond_features(bond, use_chirality=False): Note ---- This method requires RDKit to be installed. Returns ------- bond_feats: np.ndarray Array of bond features. This is a 1-D array of length 6 if `use_chirality` is `False` else of length 10 with chirality encoded. """ try: from rdkit import Chem Loading Loading @@ -278,16 +424,24 @@ def pair_features(mol, edge_list, canon_adj_list, bt_len=6, Molecule to compute features on. edge_list: list List of edges to consider canon_adj_list: list TODO bt_len: int, optional TODO graph_distance: bool, optional canon_adj_list: list of lists `canon_adj_list[i]` is a list of the atom indices that atom `i` shares a list. This list is symmetrical so if `j in canon_adj_list[i]` then `i in canon_adj_list[j]`. bt_len: int, optional (default 6) The number of different bond types to consider. graph_distance: bool, optional (default True) If true, use graph distance between molecules. Else use euclidean distance. Note ---- This method requires RDKit to be installed. Returns ------- features: np.ndarray Of shape `(N, N, bt_len + max_distance + 1)`. This is the array of pairwise features for all atom pairs. """ if graph_distance: max_distance = 7 Loading Loading @@ -326,6 +480,28 @@ def pair_features(mol, edge_list, canon_adj_list, bt_len=6, def find_distance(a1, num_atoms, canon_adj_list, max_distance=7): """Computes distances from provided atom. Parameters ---------- a1: RDKit atom The source atom to compute distances from. num_atoms: int The total number of atoms. canon_adj_list: list of lists `canon_adj_list[i]` is a list of the atom indices that atom `i` shares a list. This list is symmetrical so if `j in canon_adj_list[i]` then `i in canon_adj_list[j]`. max_distance: int, optional (default 7) The max distance to search. Returns ------- distances: np.ndarray Of shape `(num_atoms, max_distance)`. Provides a one-hot encoding of the distances. That is, `distances[i]` is a one-hot encoding of the distance from `a1` to atom `i`. """ distance = np.zeros((num_atoms, max_distance)) radial = 0 # atoms `radial` bonds away from `a1` Loading deepchem/feat/one_hot.py +4 −4 Original line number Diff line number Diff line Loading @@ -25,10 +25,10 @@ class OneHotFeaturizer(MolecularFeaturizer): Parameters ---------- charset: obj:`list` of obj:`str` Each string is length 1 padlength: int length to pad the smile strings to charset: list of str, optional (default None) A list of strings, where each string is length 1. padlength: int, optional (default 120) length to pad the smile strings to. """ try: from rdkit import Chem Loading Loading
deepchem/feat/base_classes.py +12 −6 Original line number Diff line number Diff line Loading @@ -30,8 +30,10 @@ class Featurizer(object): Parameters ---------- datapoints: object Any blob of data you like. Subclasss should instantiate this. datapoints: iterable A sequence of objects that you'd like to featurize. Subclassses of `Featurizer` should instantiate the `_featurize` method that featurizes objects in the sequence. Returns ------- Loading @@ -40,6 +42,8 @@ class Featurizer(object): datapoints = list(datapoints) features = [] for i, point in enumerate(datapoints): if i % log_every_n == 0: logger.info("Featurizing datapoint %i" % i) if point is not None: features.append(self._featurize(point)) else: Loading Loading @@ -135,14 +139,14 @@ class MolecularFeaturizer(Featurizer): In general, subclasses of this class will require RDKit to be installed. """ def featurize(self, mols, verbose=True, log_every_n=1000): def featurize(self, mols, log_every_n=1000): """Calculate features for molecules. Parameters ---------- mols : iterable RDKit Mol, or SMILES string, or filename for mol2/sdf/pdb/pdbqt file. mols : RDKit Mol / SMILES string /iterable RDKit Mol, or SMILES string or iterable sequence of RDKit mols/SMILES strings. Returns ------- Loading @@ -162,6 +166,8 @@ class MolecularFeaturizer(Featurizer): mols = list(mols) features = [] for i, mol in enumerate(mols): if i % log_every_n == 0: logger.info("Featurizing datapoint %i" % i) if mol is not None: # Process only case of SMILES strings. if isinstance(mol, str): Loading
deepchem/feat/basic.py +3 −3 Original line number Diff line number Diff line Loading @@ -46,8 +46,8 @@ class RDKitDescriptors(MolecularFeaturizer): Attributes ---------- descriptors: list List of RDKit descriptor names used in this class. descriptors: np.ndarray 1D array of RDKit descriptor names used in this class. Note ---- Loading Loading @@ -108,7 +108,7 @@ class RDKitDescriptors(MolecularFeaturizer): Returns ------- rval: np.ndarray Vector of RDKit descriptors for `mol` 1D array of RDKit descriptors for `mol` """ rval = [] for desc_name, function in self.descList: Loading
deepchem/feat/coulomb_matrices.py +47 −3 Original line number Diff line number Diff line Loading @@ -27,6 +27,14 @@ class BPSymmetryFunctionInput(MolecularFeaturizer): """ def __init__(self, max_atoms): """Initialize this featurizer. Parameters ---------- max_atoms: int The maximum number of atoms expected for molecules this featurizer will process. """ self.max_atoms = max_atoms def _featurize(self, mol): Loading Loading @@ -92,6 +100,24 @@ class CoulombMatrix(MolecularFeaturizer): upper_tri=False, n_samples=1, seed=None): """Initialize this featurizer. Parameters ---------- max_atoms: int The maximum number of atoms expected for molecules this featurizer will process. remove_hydrogens: bool, optional (default False) If True, remove hydrogens before processing them. randomize: bool, optional (default False) If True, use method `randomize_coulomb_matrices` to randomize Coulomb matrices. upper_tri: bool, optional (default False) Generate only upper triangle part of Coulomb matrices. n_samples: int, optional (default 1) If `randomize` is set to True, the number of random samples to draw. seed: int, optional (default None) Random seed to use. """ try: from rdkit import Chem except ModuleNotFoundError: Loading Loading @@ -163,9 +189,7 @@ class CoulombMatrix(MolecularFeaturizer): return rval def randomize_coulomb_matrix(self, m): """ Randomize a Coulomb matrix as decribed in Montavon et al., New Journal of Physics, 15, (2013), 095003: """Randomize a Coulomb matrix as decribed in [1]_: 1. Compute row norms for M in a vector row_norms. 2. Sample a zero-mean unit-variance noise vector e with dimension Loading @@ -181,6 +205,10 @@ class CoulombMatrix(MolecularFeaturizer): Number of random matrices to generate. seed : int, optional Random seed. References ---------- .. [1] Montavon et al., New Journal of Physics, 15, (2013), 095003 """ rval = [] row_norms = np.asarray([np.linalg.norm(row) for row in m], dtype=float) Loading Loading @@ -263,6 +291,22 @@ class CoulombMatrixEig(CoulombMatrix): randomize=False, n_samples=1, seed=None): """Initialize this featurizer. Parameters ---------- max_atoms: int The maximum number of atoms expected for molecules this featurizer will process. remove_hydrogens: bool, optional (default False) If True, remove hydrogens before processing them. randomize: bool, optional (default False) If True, use method `randomize_coulomb_matrices` to randomize Coulomb matrices. n_samples: int, optional (default 1) If `randomize` is set to True, the number of random samples to draw. seed: int, optional (default None) Random seed to use. """ self.max_atoms = int(max_atoms) self.remove_hydrogens = remove_hydrogens self.randomize = randomize Loading
deepchem/feat/graph_features.py +211 −35 Original line number Diff line number Diff line import enum import numpy as np import deepchem as dc from deepchem.feat.base_classes import MolecularFeaturizer Loading @@ -14,21 +15,73 @@ def _featurize_complex(featurizer, mol_pdb_file, protein_pdb_file, log_message): def one_of_k_encoding(x, allowable_set): """Encodes elements of a provided set as integers. Parameters ---------- x: object Must be present in `allowable_set`. allowable_set: list List of allowable quantities. Example ------- >>> import deepchem as dc >>> dc.feat.graph_features.one_of_k_encoding("a", ["a", "b", "c"]) [True, False, False] Raises ------ `ValueError` if `x` is not in `allowable_set`. """ if x not in allowable_set: raise Exception("input {0} not in allowable set{1}:".format( raise ValueError("input {0} not in allowable set{1}:".format( x, allowable_set)) return list(map(lambda s: x == s, allowable_set)) def one_of_k_encoding_unk(x, allowable_set): """Maps inputs not in the allowable set to the last element.""" """Maps inputs not in the allowable set to the last element. Unlike `one_of_k_encoding`, if `x` is not in `allowable_set`, this method pretends that `x` is the last element of `allowable_set`. Parameters ---------- x: object Must be present in `allowable_set`. allowable_set: list List of allowable quantities. Examples -------- >>> dc.feat.graph_features.one_of_k_encoding_unk("s", ["a", "b", "c"]) [False, False, True] """ if x not in allowable_set: x = allowable_set[-1] return list(map(lambda s: x == s, allowable_set)) def get_intervals(l): """For list of lists, gets the cumulative products of the lengths""" """For list of lists, gets the cumulative products of the lengths Note that we add 1 to the lengths of all lists (to avoid an empty list propagating a 0). Parameters ---------- l: list of lists Returns the cumulative product of these lengths. Examples -------- >>> dc.feat.graph_features.get_intervals([[1], [1, 2], [1, 2, 3]]) [1, 3, 12] >>> dc.feat.graph_features.get_intervals([[1], [], [1, 2], [1, 2, 3]]) >>> [1, 1, 3, 12] """ intervals = len(l) * [0] # Initalize with 1 intervals[0] = 1 Loading @@ -39,36 +92,58 @@ def get_intervals(l): def safe_index(l, e): """Gets the index of e in l, providing an index of len(l) if not found""" """Gets the index of e in l, providing an index of len(l) if not found Parameters ---------- l: list List of values e: object Object to check whether `e` is in `l` Examples -------- >>> dc.feat.graph_features.safe_index([1, 2, 3], 1) 0 >>> dc.feat.graph_features.safe_index([1, 2, 3], 7) 3 """ try: return l.index(e) except: return len(l) class GraphConvConstants(enum.Enum): """Allowed Atom Types.""" possible_atom_list = [ 'C', 'N', 'O', 'S', 'F', 'P', 'Cl', 'Mg', 'Na', 'Br', 'Fe', 'Ca', 'Cu', 'Mc', 'Pd', 'Pb', 'K', 'I', 'Al', 'Ni', 'Mn' ] """Allowed Numbers of Hydrogens""" possible_numH_list = [0, 1, 2, 3, 4] """Allowed Valences for Atoms""" possible_valence_list = [0, 1, 2, 3, 4, 5, 6] """Allowed Formal Charges for Atoms""" possible_formal_charge_list = [-3, -2, -1, 0, 1, 2, 3] # To avoid importing rdkit, this is a placeholder list of the correct # length. These will be replaced with rdkit HybridizationType below """This is a placeholder for documentation. These will be replaced with corresponding values of the rdkit HybridizationType""" possible_hybridization_list = ["SP", "SP2", "SP3", "SP3D", "SP3D2"] """Allowed number of radical electrons.""" possible_number_radical_e_list = [0, 1, 2] """Allowed types of Chirality""" possible_chirality_list = ['R', 'S'] """The set of all values allowed.""" reference_lists = [ possible_atom_list, possible_numH_list, possible_valence_list, possible_formal_charge_list, possible_number_radical_e_list, possible_hybridization_list, possible_chirality_list ] """The number of different values that can be taken. See `get_intervals()`""" intervals = get_intervals(reference_lists) # We use E-Z notation for stereochemistry # https://en.wikipedia.org/wiki/E%E2%80%93Z_notation """Possible stereochemistry. We use E-Z notation for stereochemistry https://en.wikipedia.org/wiki/E%E2%80%93Z_notation""" possible_bond_stereo = ["STEREONONE", "STEREOANY", "STEREOZ", "STEREOE"] """Number of different bond types not counting stereochemistry.""" bond_fdim_base = 6 Loading @@ -79,10 +154,39 @@ def get_feature_list(atom): ---------- atom: RDKit.rdchem.Atom Atom to get features for Examples -------- >>> from rdkit import Chem >>> mol = Chem.MolFromSmiles("C") >>> atom = mol.GetAtoms()[0] >>> dc.feat.graph_features.get_feature_list(atom) [0, 4, 4, 3, 0, 2] Note ---- This method requires RDKit to be installed. Returns ------- features: list List of length 6. The i-th value in this list provides the index of the atom in the corresponding feature value list. The 6 feature values lists for this function are `[GraphConvConstants.possible_atom_list, GraphConvConstants.possible_numH_list, GraphConvConstants.possible_valence_list, GraphConvConstants.possible_formal_charge_list, GraphConvConstants.possible_num_radical_e_list]`. """ possible_atom_list = GraphConvConstants.possible_atom_list possible_numH_list = GraphConvConstants.possible_numH_list possible_valence_list = GraphConvConstants.possible_valence_list possible_formal_charge_list = GraphConvConstants.possible_formal_charge_list possible_number_radical_e_list = GraphConvConstants.possible_number_radical_e_list possible_hybridization_list = GraphConvConstants.possible_hybridization_list # Replace the hybridization from rdkit import Chem global possible_hybridization_list #global possible_hybridization_list possible_hybridization_list = [ Chem.rdchem.HybridizationType.SP, Chem.rdchem.HybridizationType.SP2, Chem.rdchem.HybridizationType.SP3, Chem.rdchem.HybridizationType.SP3D, Loading @@ -101,7 +205,20 @@ def get_feature_list(atom): def features_to_id(features, intervals): """Convert list of features into index using spacings provided in intervals""" """Convert list of features into index using spacings provided in intervals Parameters ---------- features: list List of features as returned by `get_feature_list()` intervals: list List of intervals as returned by `get_intervals()` Returns ------- id: int The index in a feature vector given by the given set of features. """ id = 0 for k in range(len(intervals)): id += features[k] * intervals[k] Loading @@ -112,6 +229,20 @@ def features_to_id(features, intervals): def id_to_features(id, intervals): """Given an index in a feature vector, return the original set of features. Parameters ---------- id: int The index in a feature vector given by the given set of features. intervals: list List of intervals as returned by `get_intervals()` Returns ------- features: list List of features as returned by `get_feature_list()` """ features = 6 * [0] # Correct for null Loading @@ -133,6 +264,11 @@ def atom_to_id(atom): ---------- atom: RDKit.rdchem.Atom Atom to convert to ids. Returns ------- id: int The index in a feature vector given by the given set of features. """ features = get_feature_list(atom) return features_to_id(features, intervals) Loading @@ -154,6 +290,10 @@ def atom_features(atom, If true, model hydrogens explicitly use_chirality: bool, optional If true, use chirality information. Returns ------- np.ndarray of per-atom features. """ if bool_id_feat: return np.array([atom_to_id(atom)]) Loading Loading @@ -245,6 +385,12 @@ def bond_features(bond, use_chirality=False): Note ---- This method requires RDKit to be installed. Returns ------- bond_feats: np.ndarray Array of bond features. This is a 1-D array of length 6 if `use_chirality` is `False` else of length 10 with chirality encoded. """ try: from rdkit import Chem Loading Loading @@ -278,16 +424,24 @@ def pair_features(mol, edge_list, canon_adj_list, bt_len=6, Molecule to compute features on. edge_list: list List of edges to consider canon_adj_list: list TODO bt_len: int, optional TODO graph_distance: bool, optional canon_adj_list: list of lists `canon_adj_list[i]` is a list of the atom indices that atom `i` shares a list. This list is symmetrical so if `j in canon_adj_list[i]` then `i in canon_adj_list[j]`. bt_len: int, optional (default 6) The number of different bond types to consider. graph_distance: bool, optional (default True) If true, use graph distance between molecules. Else use euclidean distance. Note ---- This method requires RDKit to be installed. Returns ------- features: np.ndarray Of shape `(N, N, bt_len + max_distance + 1)`. This is the array of pairwise features for all atom pairs. """ if graph_distance: max_distance = 7 Loading Loading @@ -326,6 +480,28 @@ def pair_features(mol, edge_list, canon_adj_list, bt_len=6, def find_distance(a1, num_atoms, canon_adj_list, max_distance=7): """Computes distances from provided atom. Parameters ---------- a1: RDKit atom The source atom to compute distances from. num_atoms: int The total number of atoms. canon_adj_list: list of lists `canon_adj_list[i]` is a list of the atom indices that atom `i` shares a list. This list is symmetrical so if `j in canon_adj_list[i]` then `i in canon_adj_list[j]`. max_distance: int, optional (default 7) The max distance to search. Returns ------- distances: np.ndarray Of shape `(num_atoms, max_distance)`. Provides a one-hot encoding of the distances. That is, `distances[i]` is a one-hot encoding of the distance from `a1` to atom `i`. """ distance = np.zeros((num_atoms, max_distance)) radial = 0 # atoms `radial` bonds away from `a1` Loading
deepchem/feat/one_hot.py +4 −4 Original line number Diff line number Diff line Loading @@ -25,10 +25,10 @@ class OneHotFeaturizer(MolecularFeaturizer): Parameters ---------- charset: obj:`list` of obj:`str` Each string is length 1 padlength: int length to pad the smile strings to charset: list of str, optional (default None) A list of strings, where each string is length 1. padlength: int, optional (default 120) length to pad the smile strings to. """ try: from rdkit import Chem Loading
