Loading deepchem/featurizers/coulomb_matrices.py +57 −0 Original line number Diff line number Diff line Loading @@ -155,3 +155,60 @@ class CoulombMatrix(Featurizer): else: continue return d class CoulombMatrixEig(CoulombMatrix): """ Calculate the eigenvales of Coulomb matrices for molecules. Parameters ---------- max_atoms : int Maximum number of atoms for any molecule in the dataset. Used to pad the Coulomb matrix. remove_hydrogens : bool, optional (default False) Whether to remove hydrogens before constructing Coulomb matrix. randomize : bool, optional (default False) Whether to randomize Coulomb matrices to remove dependence on atom index order. n_samples : int, optional (default 1) Number of random Coulomb matrices to generate if randomize is True. seed : int, optional Random seed. """ conformers = True name = 'coulomb_matrix' def __init__(self, max_atoms, remove_hydrogens=False, randomize=False, n_samples=1, seed=None): self.max_atoms = int(max_atoms) self.remove_hydrogens = remove_hydrogens self.randomize = randomize self.n_samples = n_samples if seed is not None: seed = int(seed) self.seed = seed def _featurize(self, mol): """ Calculate eigenvalues of Coulomb matrix for molecules. Eigenvalues are returned sorted by absolute value in descending order and padded by max_atoms. Parameters ---------- mol : RDKit Mol Molecule. """ cmat = self.coulomb_matrix(mol) features = [] for f in cmat: w, v = np.linalg.eig(f) w_abs = np.abs(w) sortidx = np.argsort(w_abs) sortidx = sortidx[::-1] w = w[sortidx] f = pad_array(w, self.max_atoms) features.append(f) features = np.asarray(features) return features deepchem/featurizers/tests/test_coulomb_matrices.py +32 −0 Original line number Diff line number Diff line Loading @@ -63,3 +63,35 @@ class TestCoulombMatrix(unittest.TestCase): rval = f([self.mol]) size = np.triu_indices(self.mol.GetNumAtoms())[0].size assert rval.shape == (1, self.mol.GetNumConformers(), size) class TestCoulombMatrixEig(unittest.TestCase): """ Tests for CoulombMatrixEig. """ def setUp(self): """ Set up tests. """ smiles = '[H]C([H])([H])[H]' mol = Chem.MolFromSmiles(smiles) mol = Chem.AddHs(mol) engine = conformers.ConformerGenerator(max_conformers=1) self.mol = engine.generate_conformers(mol) assert self.mol.GetNumConformers() > 0 def test_coulomb_matrix_eig(self): """ Test CoulombMatrixEig. """ f = cm.CoulombMatrixEig(self.mol.GetNumAtoms()) rval = f([self.mol]) assert rval.shape == (1, self.mol.GetNumConformers(), self.mol.GetNumAtoms()) def test_coulomb_matrix_eig_padding(self): """ Test padding of CoulombMatixEig """ self.max_atoms = 29 f = cm.CoulombMatrixEig(self.max_atoms) rval = f([self.mol]) assert rval.shape == (1, self.mol.GetNumConformers(), self.max_atoms) Loading
deepchem/featurizers/coulomb_matrices.py +57 −0 Original line number Diff line number Diff line Loading @@ -155,3 +155,60 @@ class CoulombMatrix(Featurizer): else: continue return d class CoulombMatrixEig(CoulombMatrix): """ Calculate the eigenvales of Coulomb matrices for molecules. Parameters ---------- max_atoms : int Maximum number of atoms for any molecule in the dataset. Used to pad the Coulomb matrix. remove_hydrogens : bool, optional (default False) Whether to remove hydrogens before constructing Coulomb matrix. randomize : bool, optional (default False) Whether to randomize Coulomb matrices to remove dependence on atom index order. n_samples : int, optional (default 1) Number of random Coulomb matrices to generate if randomize is True. seed : int, optional Random seed. """ conformers = True name = 'coulomb_matrix' def __init__(self, max_atoms, remove_hydrogens=False, randomize=False, n_samples=1, seed=None): self.max_atoms = int(max_atoms) self.remove_hydrogens = remove_hydrogens self.randomize = randomize self.n_samples = n_samples if seed is not None: seed = int(seed) self.seed = seed def _featurize(self, mol): """ Calculate eigenvalues of Coulomb matrix for molecules. Eigenvalues are returned sorted by absolute value in descending order and padded by max_atoms. Parameters ---------- mol : RDKit Mol Molecule. """ cmat = self.coulomb_matrix(mol) features = [] for f in cmat: w, v = np.linalg.eig(f) w_abs = np.abs(w) sortidx = np.argsort(w_abs) sortidx = sortidx[::-1] w = w[sortidx] f = pad_array(w, self.max_atoms) features.append(f) features = np.asarray(features) return features
deepchem/featurizers/tests/test_coulomb_matrices.py +32 −0 Original line number Diff line number Diff line Loading @@ -63,3 +63,35 @@ class TestCoulombMatrix(unittest.TestCase): rval = f([self.mol]) size = np.triu_indices(self.mol.GetNumAtoms())[0].size assert rval.shape == (1, self.mol.GetNumConformers(), size) class TestCoulombMatrixEig(unittest.TestCase): """ Tests for CoulombMatrixEig. """ def setUp(self): """ Set up tests. """ smiles = '[H]C([H])([H])[H]' mol = Chem.MolFromSmiles(smiles) mol = Chem.AddHs(mol) engine = conformers.ConformerGenerator(max_conformers=1) self.mol = engine.generate_conformers(mol) assert self.mol.GetNumConformers() > 0 def test_coulomb_matrix_eig(self): """ Test CoulombMatrixEig. """ f = cm.CoulombMatrixEig(self.mol.GetNumAtoms()) rval = f([self.mol]) assert rval.shape == (1, self.mol.GetNumConformers(), self.mol.GetNumAtoms()) def test_coulomb_matrix_eig_padding(self): """ Test padding of CoulombMatixEig """ self.max_atoms = 29 f = cm.CoulombMatrixEig(self.max_atoms) rval = f([self.mol]) assert rval.shape == (1, self.mol.GetNumConformers(), self.max_atoms)
