def optimize(self, state):
mch_mol = mch.Molecule(
atoms=(mch.Atom(
id=atom.get_id(),
element_string=atom.__class__.__name__,
) for atom in state.get_atoms()),
bonds=get_mch_bonds(state),
position_matrix=state.get_position_matrix(),
)
mch_mol, result = self._optimizer.get_result(
mol=mch_mol,
bond_pair_ids=tuple(get_long_bond_ids(state)),
subunits=get_subunits(state),
)
old_pos_mat = state.get_position_matrix()
new_pos_mat = mch_mol.get_position_matrix()
old_extents = (abs(max(old_pos_mat[:, i]) - min(old_pos_mat[:, i]))
for i in range(3))
new_extents = (abs(max(new_pos_mat[:, i]) - min(new_pos_mat[:, i]))
for i in range(3))
ratios = (n / o for n, o in zip(new_extents, old_extents))
old_lattice = state.get_lattice_constants()
new_lattice = tuple(old_lattice[i] * ratio
for i, ratio in enumerate(ratios))
state = state.with_lattice_constants(new_lattice)
return state.with_position_matrix(
position_matrix=mch_mol.get_position_matrix())
def atoms():
return [
mch.Atom(0, 'C'),
mch.Atom(1, 'C'),
mch.Atom(2, 'C'),
mch.Atom(3, 'C'),
mch.Atom(4, 'C'),
mch.Atom(5, 'C'),
]
def optimize(self, state):
# Define MCHammer molecule to optimize.
mch_mol = mch.Molecule(
atoms=(mch.Atom(
id=atom.get_id(),
element_string=atom.__class__.__name__,
) for atom in state.get_atoms()),
bonds=tuple(get_mch_bonds(state)),
position_matrix=state.get_position_matrix(),
)
# Run optimization.
mch_mol, results = self._optimizer.get_result(
mol=mch_mol,
bond_pair_ids=tuple(get_long_bond_ids(state)),
subunits=get_subunits(state),
)
return state.with_position_matrix(
position_matrix=mch_mol.get_position_matrix(), )
import stk
import mchammer as mch
benzene = stk.BuildingBlock.init_from_file('benzene.mol')
benzene_atoms = [(atom.get_id(), atom.__class__.__name__)
for atom in benzene.get_atoms()]
benzene_bonds = []
for i, bond in enumerate(benzene.get_bonds()):
# Must ensure that bond atom ids are ordered by atom id.
b_ids = ((bond.get_atom1().get_id(), bond.get_atom2().get_id())
if bond.get_atom1().get_id() < bond.get_atom2().get_id() else
(bond.get_atom2().get_id(), bond.get_atom1().get_id()))
benzene_bonds.append((i, b_ids))
mch_mol = mch.Molecule(
atoms=(mch.Atom(id=i[0], element_string=i[1]) for i in benzene_atoms),
bonds=(mch.Bond(id=i[0], atom1_id=i[1][0], atom2_id=i[1][1])
for i in benzene_bonds),
position_matrix=benzene.get_position_matrix(),
)
target_bond_length = 1.2
optimizer = mch.Optimizer(
step_size=0.25,
target_bond_length=target_bond_length,
num_steps=100,
)
subunits = mch_mol.get_subunits(bond_pair_ids=((2, 3), (1, 5)), )
# Get all steps.
mch_result = optimizer.get_trajectory(
mol=mch_mol,
# on. You can use ranges to specify the ids.
building_blocks={
bb1: range(2),
bb2: (2, 3),
bb3: 4,
bb4: 5,
bb5: range(6, 10),
},
),
)
cage.write('poc.mol')
stk_long_bond_ids = get_long_bond_ids(cage)
mch_mol = mch.Molecule(
atoms=(
mch.Atom(
id=atom.get_id(),
element_string=atom.__class__.__name__,
) for atom in cage.get_atoms()
),
bonds=(
mch.Bond(
id=i,
atom1_id=bond.get_atom1().get_id(),
atom2_id=bond.get_atom2().get_id()
) for i, bond in enumerate(cage.get_bonds())
),
position_matrix=cage.get_position_matrix(),
)
mch_mol_nci = deepcopy(mch_mol)
optimizer = mch.Optimizer(
step_size=0.25,
import pytest
import numpy as np
import mchammer as mch
@pytest.fixture(
params=(
(mch.Atom(id=0, element_string='N'), 0, 'N'),
(mch.Atom(id=65, element_string='P'), 65, 'P'),
(mch.Atom(id=2, element_string='C'), 2, 'C'),
)
)
def atom_info(request):
return request.param
@pytest.fixture(
params=(
(mch.Bond(id=0, atom_ids=(0, 1)), 0, 0, 1),
(mch.Bond(id=65, atom_ids=(2, 3)), 65, 2, 3),
(mch.Bond(id=2, atom_ids=(3, 4)), 2, 3, 4),
(mch.Bond(id=3, atom_ids=(0, 9)), 3, 0, 9),
)
)
def bond_info(request):
return request.param
@pytest.fixture
def atoms():
return [
