def test_batch_construction(self):
mol_batch = NPMol.create_from_batch(batch_atoms=atoms,
batch_distances=distances)
for i in range(len(distances)):
npt.assert_allclose(mol_batch[i].distances, distances[i])
npt.assert_allclose(mol_batch[i].distance_matrix,
distance_matrix[i])
npt.assert_equal(mol_batch[i].atoms, atom_types[i])
self.assertTrue(isinstance(mol_batch[i].smiles, str))
def test_empty(self):
atoms_empty = np.zeros([batch_size, num_atoms, num_atom_types])
atoms_empty[:, :, -1] = 1
mol_batch = NPMol.create_from_batch(batch_atoms=atoms_empty,
batch_distances=distances)
for mol in mol_batch:
npt.assert_equal(mol.distance_matrix, np.zeros([0, 0]))
npt.assert_equal(mol.coordinates, np.zeros([0, 3]))
npt.assert_equal(mol.smiles, '')
npt.assert_equal(mol.atoms, [])
def test_atom_features(self):
data_dir = os.path.join(os.path.dirname(__file__), 'sample_data')
trainer = VAETrainer(data_dir, 10, 10)
sdf_path = os.path.join(os.path.dirname(__file__), 'sample_mol.sdf')
mol_supplier = Chem.SDMolSupplier(
sdf_path, removeHs=True) # import molecules from sdf file
rdkit_mol = mol_supplier[0]
featurizer = DistanceFeaturizer(9, implicit_hydrogen=True)
feat_mol = featurizer.featurize(rdkit_mol)
coordinates = np.copy(feat_mol.coordinates)
coordinates *= -1 # invert
coordinates[:, 0] *= -1 # mirror
mol = NPMol(atoms=feat_mol.atom_features,
coordinates=feat_mol.coordinates)
rec_mol = NPMol(atoms=feat_mol.atom_features, coordinates=coordinates)
mse, mae = trainer._compute_position_accuracy(mol, rec_mol)
np.testing.assert_allclose([mse, mae], [0, 0], atol=1e-5)
def test_padding_removal(self):
p_coordinates = np.concatenate((coordinates[0], [[0, 0, 0]]))
p_distance_matrix = np.pad(distance_matrix[0], ((0, 1), (0, 1)),
mode='constant')
p_distances = p_distance_matrix[np.triu_indices(4, 1)]
p_atoms = np.concatenate((atoms[0], [[0, 0, 0, 0, 1]]))
mol = NPMol(atoms=p_atoms,
coordinates=p_coordinates,
distance_matrix=p_distance_matrix,
distances=p_distances)
npt.assert_allclose(mol.distances, distances[0])
npt.assert_allclose(mol.distance_matrix, distance_matrix[0])
npt.assert_allclose(mol.coordinates, coordinates[0])
npt.assert_equal(mol.atoms, atom_types[0])
def test_atom_types(self):
mol = NPMol(atoms=atoms[0], coordinates=coordinates[0])
npt.assert_equal(mol.atoms, atom_types[0])
def test_coordinates_provided(self):
mol = NPMol(atoms=atoms[0], coordinates=coordinates[0])
npt.assert_allclose(mol.distances, distances[0])
npt.assert_allclose(mol.distance_matrix, distance_matrix[0])
self.assertTrue(isinstance(mol.smiles, str))
def test_distance_matrix_provided(self):
mol = NPMol(atoms=atoms[0], distance_matrix=distance_matrix[0])
npt.assert_allclose(mol.distances, distances[0])
self.assertTrue(isinstance(mol.smiles, str))
npt.assert_equal(mol.coordinates.shape, coordinates[0].shape)
def test_none_provided(self):
with self.assertRaises(ValueError):
_ = NPMol(atoms=atoms)