def read(self, feature, *args, **kwargs):
if feature == 'molecular orbitals':
n = args[0]
basis_functions = self.data.gbasis
if feature == 'molecule':
# Angstrom to nanometers
# CJS added option to get molecule from steps of optimisation
# or optimisations for PES scans
# TODO error checking
if kwargs.has_key('step'):
return Molecule.from_arrays(
r_array=self.data.atomcoords[kwargs['step']] / 10,
type_array=np.array(
[symbols[a] for a in self.data.atomnos]))
elif kwargs.has_key('scan'):
return Molecule.from_arrays(
r_array=self.data.scancoords[kwargs['scan']] / 10,
type_array=np.array(
[symbols[a] for a in self.data.atomnos]))
else:
return Molecule.from_arrays(
r_array=self.data.atomcoords[-1] / 10,
type_array=np.array(
[symbols[a] for a in self.data.atomnos]))
else:
return getattr(self.data, feature)
def test_residue():
m = Molecule.from_arrays(type_array=['H', 'H', 'H', 'O', 'O'],
residue_name=['VAL', 'ALA'],
maps={('atom', 'residue'): [0, 0, 0, 1, 1]})
assert_npequal(m.sub(residue_index=0).type_array, ['H', 'H', 'H'])
s = System([m, m])
assert_npequal(s.maps['atom', 'residue'].value, [0, 0, 0, 1, 1, 2, 2, 2, 3, 3])
def test_random_lattice():
'''Testing random made box'''
na = Molecule([Atom('Na', [0.0, 0.0, 0.0])])
cl = Molecule([Atom('Cl', [0.0, 0.0, 0.0])])
wat = Molecule.from_arrays(type_array=['O', 'H', 'H'])
s = random_lattice_box([na, cl, wat], [160, 160, 160], [4, 4, 4])
eq_(s.dimensions['molecule'], 160 * 3)
eq_(s.dimensions['atom'], 160 * 5)
def test_random_lattice():
'''Testing random made box'''
na = Molecule([Atom('Na', [0.0, 0.0, 0.0])])
cl = Molecule([Atom('Cl', [0.0, 0.0, 0.0])])
wat = Molecule.from_arrays(type_array=['O', 'H', 'H'])
s = random_lattice_box([na, cl, wat], [160, 160, 160], [4, 4, 4])
eq_(s.dimensions['molecule'], 160 * 3)
eq_(s.dimensions['atom'], 160 * 5)
def test_residue():
m = Molecule.from_arrays(type_array=['H', 'H', 'H', 'O', 'O'],
residue_name=['VAL', 'ALA'],
maps={('atom', 'residue'): [0, 0, 0, 1, 1]})
assert_npequal(m.sub(residue_index=0).type_array, ['H', 'H', 'H'])
s = System([m, m])
assert_npequal(s.maps['atom', 'residue'].value,
[0, 0, 0, 1, 1, 2, 2, 2, 3, 3])
def split_groups(mol):
groups = []
unselected = [x for x in range(mol.n_atoms)]
while len(unselected) > 0:
new_atoms = set()
new_atoms.add(unselected[0])
atoms = []
new_bonds = []
new_bond_orders = []
while len(new_atoms) > 0:
a = list(new_atoms)[0]
atoms.append(a)
new_atoms.remove(a)
for bond_index, bond in enumerate(mol.bonds):
if atoms[-1] == bond[0] and bond[1] not in atoms:
new_atoms.add(bond[1])
if atoms[-1] == bond[1] and bond[0] not in atoms:
new_atoms.add(bond[0])
if a in bond and bond.tolist() not in new_bonds:
new_bonds.append(bond.tolist())
new_bond_orders.append(mol.bond_orders[bond_index])
atoms.sort()
groups.append([atoms, new_bonds, new_bond_orders])
unselected = [x for x in range(mol.n_atoms) if x not in sum([y[0] for y in groups],[])]
molecules = []
for group in groups:
new_bonds_reduced = np.array([[group[0].index(x[0]), group[0].index(x[1])] for x in group[1]])
numpy_vectors = [system.r_array[x] for x in group[0]]
new_molecule = Molecule.from_arrays(r_array=np.array(numpy_vectors),
type_array=system.type_array[a],
bonds=new_bonds_reduced,
bond_orders=group[2]
)
new_molecule.export['vectors'] = numpy_vectors
molecules.append(new_molecule)
return molecules
