def get_yaff_system(self, snapshot=0):
numbers = np.array([
pt[symbol].number
for symbol in self.structure.get_chemical_symbols()
])
if snapshot == 0:
struct = self.structure
else:
struct = self.get_structure(iteration_step=snapshot,
wrap_atoms=False)
pos = struct.positions.reshape(-1, 3) * angstrom
cell = struct.cell
if cell is None:
system = System(numbers,
pos,
ffatypes=self.ffatypes,
ffatype_ids=self.ffatype_ids)
else:
system = System(numbers,
pos,
rvecs=cell * angstrom,
ffatypes=self.ffatypes,
ffatype_ids=self.ffatype_ids)
system.detect_bonds()
system.set_standard_masses()
return system
def detect_ffatypes(self, ffatypes=None, ffatype_rules=None, ffatype_level=None):
'''
Define atom types by explicitely giving them through the
ffatypes keyword, defining atype rules using the ATSELECT
language implemented in Yaff (see the Yaff documentation at
http://molmod.github.io/yaff/ug_atselect.html) or by specifying
the ffatype_level employing the built-in routine in QuickFF.
'''
numbers = np.array([pt[symbol].number for symbol in self.structure.get_chemical_symbols()])
if self.structure.cell is None:
system = System(numbers, self.structure.positions.copy()*angstrom)
else:
system = System(numbers, self.structure.positions.copy()*angstrom, rvecs=self.structure.cell*angstrom)
system.detect_bonds()
if not sum([ffatypes is None, ffatype_rules is None, ffatype_level is None]) == 2:
raise IOError('Exactly one of ffatypes, ffatype_rules and ffatype_level should be defined')
if ffatypes is not None:
assert ffatype_rules is None, 'ffatypes and ffatype_rules cannot be defined both'
system.ffatypes = ffatypes
system.ffatype_ids = None
system._init_derived_ffatypes()
if ffatype_rules is not None:
system.detect_ffatypes(ffatype_rules)
if ffatype_level is not None:
set_ffatypes(system, ffatype_level)
self.ffatypes = system.ffatypes.copy()
self.ffatype_ids = system.ffatype_ids.copy()
def write_chk(input_dict,working_directory='.'):
# collect data and initialize Yaff system
if 'cell' in input_dict.keys() and input_dict['cell'] is not None:
system = System(input_dict['numbers'], input_dict['pos']*angstrom, ffatypes=input_dict['ffatypes'], ffatype_ids=input_dict['ffatype_ids'], rvecs=input_dict['cell']*angstrom)
else:
system = System(input_dict['numbers'], input_dict['pos']*angstrom, ffatypes=input_dict['ffatypes'], ffatype_ids=input_dict['ffatype_ids'])
# determine masses, bonds and ffaypes from ffatype_rules
system.detect_bonds()
system.set_standard_masses()
# write dictionary to MolMod CHK file
system.to_file(posixpath.join(working_directory,'system.chk'))
def __init__(self, system, rules=None, cases=None):
self.system = system
self.cases = cases
# Compile the rules if they are present
if cases is None:
if rules is None:
rules = ['!0'] * self.natom
compiled_rules = []
for rule in rules:
if isinstance(rule, str):
rule = atsel_compile(rule)
compiled_rules.append(rule)
self.rules = compiled_rules
self.cases = list(self._iter_cases())
elif rules is not None:
raise ValueError(
'Either rules are cases must be provided, not both.')
# Construct a fake system, a dlist and an iclist for just one ic
self.fake_system = System(numbers=np.zeros(self.natom, int),
pos=np.zeros((self.natom, 3), float),
rvecs=self.system.cell.rvecs)
self.dlist = DeltaList(self.fake_system)
self.iclist = InternalCoordinateList(self.dlist)
self.tangent = np.zeros((self.natom, 3), float)
def test_uio66zrbrick_crossterms():
with log.section('NOSETEST', 2):
# Load input data for a ficticious system of an isolated
# UiO-66 brick
with path('quickff.data.systems.uio66-zr-brick', 'system.chk') as fn:
data = load_chk(fn)
system = System(data['numbers'],data['pos'],charges=data['charges'],
ffatypes=data['ffatypes'],bonds=data['bonds'],radii=data['radii'])
system.set_standard_masses()
ai = SecondOrderTaylor('ai', coords=system.pos.copy(),
grad=data['gradient'], hess=data['hessian'])
# Run QuickFF
with tmpdir('test_uio66') as dn:
fn_yaff = os.path.join(dn, 'pars_cov.txt')
fn_sys = os.path.join(dn, 'system.chk')
fn_log = os.path.join(dn, 'quickff.log')
program = DeriveFF(system, ai, Settings(consistent_cross_rvs=True,
remove_dysfunctional_cross=True,fn_yaff=fn_yaff,fn_sys=fn_sys,log_file=fn_log))
program.run()
# Check force constants of cross terms and corresponding diagonal terms
print("%50s %15s %15s"%("Basename","Cross FC","Diag FC"))
for term in program.valence.terms:
if not term.is_master(): continue
if term.basename.startswith('Cross'):
fc = program.valence.get_params(term.index, only='fc')
for i in [0,1]:
fc_diag = program.valence.get_params(term.diag_term_indexes[i], only='fc')
print("%50s %15.6f %15.6f %50s" % (term.basename,fc,fc_diag,program.valence.terms[term.diag_term_indexes[i]].basename))
if fc_diag==0.0: assert fc==0.0
def test_detect_bonds_cyclopropene_exceptions():
system = get_system_cyclopropene()
# create system without bonds
system = System(system.numbers, system.pos)
# Add bonds between all hydrogen and carbon atoms (unrealistic but useful for testing)
system.detect_bonds({(1, 6): 8.0 * angstrom})
assert system.nbond == 3 + 4 * 3
def test_detect_bonds_water_exceptions():
system = get_system_water32()
# create system without bonds
system = System(system.numbers, system.pos)
# Add bonds between hydrogen atoms (unrealistic but useful for testing)
system.detect_bonds({(1, 1): 2.0 * angstrom})
assert system.nbond >= 96
def read_system(name):
# Load system data
dn = 'quickff.data.systems'
if '/' in name:
words = name.split('/')
dn += '.%s' % ('.'.join(words[:-1]))
name = words[-1]
with path(dn, name) as fn:
numbers, coords, energy, grad, hess, masses, rvecs, pbc = read_abinitio(
fn)
fns_wpart = glob(os.path.join(os.path.dirname(fn), 'gaussian_mbis.h5'))
# Try to load charges.
charges = None
if len(fns_wpart) > 0:
with h5.File(fns_wpart[0], 'r') as f:
charges = f['charges'][:]
# Create system object.
system = System(numbers, coords, charges=charges)
system.detect_bonds()
system.set_standard_masses()
# Load ab initio data.
ai = SecondOrderTaylor('ai',
coords=system.pos.copy(),
energy=energy,
grad=grad,
hess=hess,
pbc=pbc)
return system, ai
def load_system_cube(fn):
'''Load system from fn in cube format'''
# TODO: this should be moved into Yaff/MolMod
print 'Loading atomic structure from CUBE file.'
with open(fn) as f:
# Skip two header lines.
f.next()
f.next()
# Read number of atoms.
natom = int(f.next().split()[0])
assert natom > 0
# Read real-space vectors
rvecs = np.zeros((3, 3), float)
for irow in xrange(3):
words = f.next().split()
nrep = int(words[0])
rvecs[irow, 0] = nrep * float(words[1])
rvecs[irow, 1] = nrep * float(words[2])
rvecs[irow, 2] = nrep * float(words[3])
print 'Treating system as periodic with the following cell vectors'
print 'in Angstrom. (Cell vectors are displayed as rows.)'
print rvecs / angstrom
# Read atomic numbers and coordinates
numbers = np.zeros(natom, int)
coordinates = np.zeros((natom, 3), float)
for iatom in xrange(natom):
words = f.next().split()
numbers[iatom] = int(words[0])
coordinates[iatom, 0] = float(words[2])
coordinates[iatom, 1] = float(words[3])
coordinates[iatom, 2] = float(words[4])
print
return System(numbers=numbers, pos=coordinates, rvecs=rvecs)
def test_detect_bonds_glycine():
system = get_system_glycine()
check_detect_bonds(system)
system = System(system.numbers, system.pos)
system.detect_bonds()
assert hasattr(system, 'neighs1')
assert hasattr(system, 'neighs2')
assert hasattr(system, 'neighs3')
def read_system(name):
fn = context.get_fn('systems/%s' %name)
numbers, coords, energy, grad, hess, masses, rvecs, pbc = read_abinitio(fn)
system = System(numbers, coords)
system.detect_bonds()
system.set_standard_masses()
ai = SecondOrderTaylor('ai', coords=system.pos.copy(), energy=energy, grad=grad, hess=hess, pbc=pbc)
return system, ai
def test_iter_matches_single_atom():
system = System.from_file(context.get_fn('test/rhodium_complex_nobornane.xyz'))
system.detect_bonds()
system_ref = System(pos=np.zeros((1, 3), float), numbers = np.array([45]))
system_ref.detect_bonds()
selected = set(system.iter_matches(system_ref).next())
reference = set([28])
np.testing.assert_equal(selected, reference)
def test_supercell_nobonds():
cellpar = 2.867 * angstrom
sys111 = System(
numbers=np.array([26, 26]),
pos=np.array([[0.0, 0.0, 0.0], [0.5, 0.5, 0.5]]) * cellpar,
ffatypes=['Fe', 'Fe'],
rvecs=np.identity(3) * cellpar,
)
sys333 = sys111.supercell(3, 3, 3)
def test_iter_matches_single_atom():
system = System.from_file(
pkg_resources.resource_filename(
__name__, '../data/test/rhodium_complex_nobornane.xyz'))
system.detect_bonds()
system_ref = System(pos=np.zeros((1, 3), float), numbers=np.array([45]))
system_ref.detect_bonds()
selected = set(next(system.iter_matches(system_ref)))
reference = set([28])
np.testing.assert_equal(selected, reference)
def test_scopes2():
system = System(numbers=np.array([8, 1, 1, 6, 1, 1, 1, 8, 1]),
pos=np.zeros((9, 3), float),
scopes=['WAT', 'METH'],
scope_ids=np.array([0, 0, 0, 1, 1, 1, 1, 1, 1]),
ffatypes=['O', 'H', 'C', 'H_C', 'O', 'H_O'],
ffatype_ids=np.array([0, 1, 1, 2, 3, 3, 3, 4, 5]))
assert (system.scopes == ['WAT', 'METH']).all()
assert (system.scope_ids == np.array([0, 0, 0, 1, 1, 1, 1, 1, 1])).all()
assert (system.ffatypes == ['O', 'H', 'C', 'H_C', 'O', 'H_O']).all()
assert (system.ffatype_ids == np.array([0, 1, 1, 2, 3, 3, 3, 4, 5])).all()
def write_chk(input_dict, working_directory='.'):
# collect data and initialize Yaff system
if 'cell' in input_dict.keys() and input_dict['cell'] is not None:
system = System(input_dict['numbers'], input_dict['pos']*angstrom, rvecs=input_dict['cell']*angstrom, ffatypes=input_dict['ffatypes_man'], ffatype_ids=input_dict['ffatype_ids_man'])
else:
system = System(input_dict['numbers'], input_dict['pos']*angstrom, ffatypes=input_dict['ffatypes_man'], ffatype_ids=input_dict['ffatype_ids_man'])
# determine masses, bonds and ffaypes from ffatype_rules
system.detect_bonds()
system.set_standard_masses()
# write dictionnairy to MolMod CHK file
system.to_file(posixpath.join(working_directory,'input.chk'))
# Reload input.chk as dictionairy and add AI input data
d = load_chk(posixpath.join(working_directory,'input.chk'))
assert isinstance(input_dict['aiener'], float), "AI energy not defined in input, use job.read_abintio(...)"
assert isinstance(input_dict['aigrad'], np.ndarray), "AI gradient not defined in input, use job.read_abintio(...)"
assert isinstance(input_dict['aihess'], np.ndarray), "AI hessian not defined in input, use job.read_abintio(...)"
d['energy'] = input_dict['aiener']
d['grad'] = input_dict['aigrad']
d['hess'] = input_dict['aihess']
dump_chk(posixpath.join(working_directory,'input.chk'), d)
def test_supercell_charges():
cellpar = 2.867 * angstrom
sys111 = System(
numbers=np.array([26, 26]),
pos=np.array([[0.0, 0.0, 0.0], [0.5, 0.5, 0.5]]) * cellpar,
ffatypes=['Fe', 'Fe'],
charges=np.array([0.1, 1.0]),
radii=np.array([0.0, 2.0]),
rvecs=np.identity(3) * cellpar,
)
sys333 = sys111.supercell(3, 3, 3)
assert (sys333.charges == np.tile(np.array([0.1, 1.0]), 27)).all()
assert (sys333.radii == np.tile(np.array([0.0, 2.0]), 27)).all()
def test_scopes3():
system = System(numbers=np.array([8, 1, 1, 6, 1, 1, 1, 8, 1]),
pos=np.zeros((9, 3), float),
scopes=['WAT', 'METH'],
scope_ids=np.array([0, 0, 0, 1, 1, 1, 1, 1, 1]),
ffatypes=['O', 'H', 'C', 'H_C', 'H_O'],
ffatype_ids=np.array([0, 1, 1, 2, 3, 3, 3, 0, 4]))
assert (system.scopes == ['WAT', 'METH']).all()
assert (system.scope_ids == np.array([0, 0, 0, 1, 1, 1, 1, 1, 1])).all()
assert (system.ffatypes == ['O', 'H', 'C', 'H_C', 'H_O', 'O']).all()
assert (system.ffatype_ids == np.array([0, 1, 1, 2, 3, 3, 3, 5, 4])).all()
assert system.get_scope(0) == 'WAT'
assert system.get_scope(3) == 'METH'
assert system.get_ffatype(0) == 'O'
assert system.get_ffatype(7) == 'O'
assert system.get_ffatype(8) == 'H_O'
def read_system(name):
# Load system data.
fn = context.get_fn(os.path.join('systems', name))
numbers, coords, energy, grad, hess, masses, rvecs, pbc = read_abinitio(fn)
# Try to load charges.
charges = None
fns_wpart = glob(os.path.join(os.path.dirname(fn), 'gaussian_mbis.h5'))
if len(fns_wpart) > 0:
with h5.File(fns_wpart[0], 'r') as f:
charges = f['charges'][:]
# Create system object.
system = System(numbers, coords, charges=charges)
system.detect_bonds()
system.set_standard_masses()
# Load ab initio data.
ai = SecondOrderTaylor('ai', coords=system.pos.copy(), energy=energy, grad=grad, hess=hess, pbc=pbc)
return system, ai
def test_remove_duplicate_dipoles():
cellpar = 2.867 * angstrom
system1 = System(
numbers=np.array([26, 27]),
pos=np.array([[0.0, 0.0, 0.0], [0.5, 0.5, 0.5]]) * cellpar,
ffatypes=['A', 'B'],
dipoles=np.array([[0.1, 1.0, 2.0], [0.5, 0.7, 0.9]]),
radii2=np.array([0.0, 2.0]),
rvecs=np.identity(3) * cellpar,
)
system2 = system1.supercell(1, 2, 1)
system2.cell = system1.cell
system3 = system2.remove_duplicate()
for j, number in enumerate([26, 27]):
#By removing duplicates, atoms might be reordered
i = np.where(system3.numbers == number)[0]
assert system1.radii2[j] == system3.radii2[i]
assert np.all(system1.dipoles[j] == system3.dipoles[i])
self.make_output()
#settings
with log.section('INIT', 2, timer='Initialization'):
settings = Settings(fn_yaff='pars_cov.txt', plot_traj='All', xyz_traj=True)
#load Gaussian Formatted Checkpoint file
fchk = FCHKFile('gaussian.fchk')
numbers = fchk.fields.get('Atomic numbers')
energy = fchk.fields.get('Total Energy')
coords = fchk.fields.get('Current cartesian coordinates').reshape([len(numbers), 3])
grad = fchk.fields.get('Cartesian Gradient').reshape([len(numbers), 3])
hess = fchk.get_hessian().reshape([len(numbers), 3, len(numbers), 3])
#Construct Yaff System file
system = System(numbers, coords)
system.detect_bonds()
system.set_standard_masses()
#Construct a QuickFF SecondOrderTaylor object containing the AI reference
with log.section('INIT', 2, timer='Initialization'):
ai = SecondOrderTaylor('ai', coords=coords, energy=energy, grad=grad, hess=hess)
#define atom types
rules = [
('H', '1 & =1%8'), #hydrogen atom with one oxygen neighbor
('O', '8 & =2%1'), #oxygen atom with two hydrogen neighbors
]
system.detect_ffatypes(rules)
#construct electrostatic force field from HE charges in gaussian_wpart.h5
def write_lammps_table_jelle(ff):
from yaff import NeighborList, PairPotEI, Switch3, ForcePartPair, Scalings,\
PairPotMM3
nffa = ff.system.ffatypes.shape[0]
numbers = []
for i in xrange(nffa):
index0 = np.where(ff.system.ffatype_ids == i)[0][0]
if np.sum(ff.system.ffatype_ids == i) > 1:
index1 = np.where(ff.system.ffatype_ids == i)[0][1]
numbers.append([index0, index1])
for j in xrange(i + 1, nffa):
index1 = np.where(ff.system.ffatype_ids == j)[0][0]
numbers.append([index0, index1])
part_names = [part.name for part in ff.parts]
print part_names
ftab = open('lammps_smoothei2.table', 'w')
ftab.write("# LAMMPS tabulated potential generated by Yaff\n")
ftab.write("# All quantities in atomic units\n")
ftab.write(
"# The names of the tables refer to the ffatypes that have to be used in the Yaff system\n"
)
ftab.write("#%4s %13s %21s %21s\n" % ("i", "d", "V", "F"))
for number in numbers:
pos = np.zeros((2, 3))
pos[1, 2] = 1.0
smallsys = System(system.numbers[number],
pos,
charges=system.charges[number],
radii=system.radii[number])
smallsys_noradii = System(system.numbers[number],
pos,
charges=system.charges[number])
idx_ei = -1
idx_mm3 = -1
for idx, part in enumerate(ff.parts):
if part.name == 'pair_ei': idx_ei = idx
elif part.name == 'pair_mm3': idx_mm3 = idx
tr = ff.parts[idx_ei].pair_pot.get_truncation()
rcut = ff.parts[idx_ei].pair_pot.rcut
alpha = ff.parts[idx_ei].pair_pot.alpha
nlist = NeighborList(smallsys)
pair_pot = PairPotEI(smallsys.charges,
alpha,
rcut,
tr=Switch3(tr.width),
radii=smallsys.radii)
# pair_pot = PairPotEI(smallsys.charges, 0.0, rcut, tr=None, radii=smallsys.radii)
scalings = Scalings(smallsys, scale1=1.0, scale2=1.0, scale3=1.0)
part0 = ForcePartPair(smallsys, nlist, scalings, pair_pot)
ff0 = ForceField(smallsys, [part0], nlist)
ff0.compute()
nlist1 = NeighborList(smallsys_noradii)
# pair_pot = PairPotEI(smallsys_noradii.charges, alpha, rcut, tr=Switch3(tr.width))
pair_pot = PairPotEI(smallsys_noradii.charges, alpha, rcut, tr=None)
scalings = Scalings(smallsys_noradii,
scale1=1.0,
scale2=1.0,
scale3=1.0)
part1 = ForcePartPair(smallsys_noradii, nlist1, scalings, pair_pot)
ff1 = ForceField(smallsys_noradii, [part1], nlist1)
ff1.compute()
tr = ff.parts[idx_mm3].pair_pot.get_truncation()
rcut = ff.parts[idx_mm3].pair_pot.rcut
nlist2 = NeighborList(smallsys)
pair_pot = PairPotMM3(ff.parts[idx_mm3].pair_pot.sigmas[number],
ff.parts[idx_mm3].pair_pot.epsilons[number],
ff.parts[idx_mm3].pair_pot.onlypaulis[number],
rcut, Switch3(tr.width))
scalings = Scalings(smallsys, scale1=1.0, scale2=1.0, scale3=1.0)
part2 = ForcePartPair(smallsys, nlist, scalings, pair_pot)
ff2 = ForceField(smallsys, [part2], nlist)
ff2.nlist.nneigh = 1
ff2.compute()
distances = np.linspace(0.5 * angstrom, rcut, 5000)
energies = []
toplot = []
for d in distances:
gposnn0 = np.zeros(ff0.system.pos.shape, float)
ff0.nlist.neighs[0] = (0, 1, d, 0.0, 0.0, d, 0, 0, 0)
energy0 = ff0.compute(gpos=gposnn0)
gposnn1 = np.zeros(ff1.system.pos.shape, float)
ff1.nlist.neighs[0] = (0, 1, d, 0.0, 0.0, d, 0, 0, 0)
energy1 = ff1.compute(gpos=gposnn1)
gposnn2 = np.zeros(ff2.system.pos.shape, float)
ff2.nlist.neighs[0] = (0, 1, d, 0.0, 0.0, d, 0, 0, 0)
energy2 = ff2.compute(gpos=gposnn2)
toplot.append([d, energy0, energy1, energy2])
row = [
d, energy0 - energy1 + energy2,
gposnn0[0, 2] - gposnn1[0, 2] + gposnn2[0, 2]
]
# row = [d, energy2, gposnn2[0,2]]
energies.append(row)
energies = np.asarray(energies)
toplot = np.asarray(toplot)
ffa0 = ff.system.ffatypes[ff.system.ffatype_ids[number[0]]]
ffa1 = ff.system.ffatypes[ff.system.ffatype_ids[number[1]]]
if ffa0 > ffa1:
name = '%s-%s' % (ffa0, ffa1)
else:
name = '%s-%s' % (ffa1, ffa0)
ftab.write("%s\nN %d R %f %f\n\n" %
(name, energies.shape[0], distances[0], distances[-1]))
for irow, row in enumerate(energies):
ftab.write("%05d %+13.8f %+21.12f %+21.12f\n" %
(irow + 1, row[0], row[1], row[2]))
print name
def test_exclusion():
def random_rotation(pos):
com = np.average(pos, axis=0)
pos -= com
while True:
V1 = np.random.rand()
V2 = np.random.rand()
S = V1**2 + V2**2
if S < 1:
break
theta = np.array([
2 * np.pi * (2 * V1 * np.sqrt(1 - S) - 0.5),
2 * np.pi * (2 * V2 * np.sqrt(1 - S) - 0.5),
np.pi * ((1 - 2 * S) / 2)
])
R_x = np.array([[1, 0, 0], [0, np.cos(theta[0]), -np.sin(theta[0])],
[0, np.sin(theta[0]),
np.cos(theta[0])]])
R_y = np.array([[np.cos(theta[1]), 0,
np.sin(theta[1])], [0, 1, 0],
[-np.sin(theta[1]), 0,
np.cos(theta[1])]])
R_z = np.array([[np.cos(theta[2]), -np.sin(theta[2]), 0],
[np.sin(theta[2]),
np.cos(theta[2]), 0], [0, 0, 1]])
R = np.dot(R_z, np.dot(R_y, R_x))
pos_new = np.zeros((len(pos), len(pos[0])))
for i, p in enumerate(pos):
pos_new[i] = np.dot(R, np.array(p).T)
return pos_new + com
def get_adsorbate_pos(adsorbate, rvecs):
pos = adsorbate.pos
pos = random_rotation(pos)
pos -= np.average(pos, axis=0)
new_com = np.random.rand() * rvecs[0] + np.random.rand(
) * rvecs[1] + np.random.rand() * rvecs[2]
return pos + new_com
# Empty framework
system = System.from_file(
pkg_resources.resource_filename(__name__,
'../../data/test/CAU_13.chk'))
N_system = len(system.pos)
ff_file = pkg_resources.resource_filename(
__name__, '../../data/test/parameters_CAU-13_xylene.txt')
ff = ForceField.generate(system, ff_file)
ff.nlist.update()
E_parts = {part.name: part.compute() for part in ff.parts}
ff_new = ForceField.generate(system,
ff_file,
exclude_frame=True,
n_frame=N_system)
ff_new.nlist.update()
E_parts_new = {part.name: part.compute() for part in ff_new.parts}
# Add 4 adsorbates
adsorbate = System.from_file(
pkg_resources.resource_filename(__name__,
'../../data/test/xylene.chk'))
pos = system.pos
ffatypes = np.append(system.ffatypes, adsorbate.ffatypes)
bonds = system.bonds
numbers = system.numbers
ffatype_ids = system.ffatype_ids
charges = system.charges
masses = system.masses
for i in range(4):
pos = np.append(pos,
get_adsorbate_pos(adsorbate, system.cell.rvecs),
axis=0)
bonds = np.append(bonds,
adsorbate.bonds + N_system + len(adsorbate.pos) * i,
axis=0)
numbers = np.append(numbers, adsorbate.numbers, axis=0)
ffatype_ids = np.append(ffatype_ids,
adsorbate.ffatype_ids +
max(system.ffatype_ids) + 1,
axis=0)
charges = np.append(charges, adsorbate.charges, axis=0)
masses = np.append(masses, adsorbate.masses, axis=0)
# Framework with 4 adsorbates
system = System(numbers, pos, ffatypes=ffatypes, ffatype_ids=ffatype_ids, bonds=bonds,\
rvecs = system.cell.rvecs, charges=charges, masses=masses)
ff = ForceField.generate(system, ff_file)
ff_new = ForceField.generate(system,
ff_file,
exclude_frame=True,
n_frame=N_system)
# Test 100 random configurations
for i in range(100):
new_pos = ff.system.pos
for i in range(4):
new_pos[N_system + i * len(adsorbate.pos):N_system +
(i + 1) * len(adsorbate.pos)] = get_adsorbate_pos(
adsorbate, system.cell.rvecs)
ff.update_pos(new_pos)
ff_new.update_pos(new_pos)
ff.nlist.update()
ff_new.nlist.update()
E_parts_rand = {part.name: part.compute() for part in ff.parts}
E_parts_new_rand = {part.name: part.compute() for part in ff_new.parts}
for key, _ in E_parts.items():
assert (E_parts[key] - E_parts_rand[key]) - (
E_parts_new[key] - E_parts_new_rand[key]) < 10e-12
def main():
args = parse_args()
# Load system file
if args.fn_sys.endswith('.fchk'):
numbers, coords, energy, grad, hess, masses, rvecs, pbc = read_abinitio(
args.fn_sys, do_hess=False)
system = System(numbers,
coords,
rvecs=None,
charges=None,
radii=None,
masses=masses)
system.detect_bonds()
else:
system = System.from_file(args.fn_sys)
# Guess atom types if needed
if args.ffatypes is not None:
guess_ffatypes(system, args.ffatypes)
ffatypes = [system.ffatypes[i] for i in system.ffatype_ids]
# Load atomic charges
fn_charges, _, path = args.charges.partition(':')
if fn_charges.endswith('.h5'):
with h5.File(fn_charges, 'r') as f:
if not path in f:
raise IOError(
'Given HDF5 file %s does not contain a dataset %s' %
(fn_charges, path))
charges = f[path][:]
radii = None
if args.gaussian:
path_radii = os.path.join(os.path.dirname(path), 'radii')
if 'radii' in f[path]:
radii = average(f['%s/radii' % path][:],
ffatypes,
fmt='dict')
else:
radii = average(get_ei_radii(system.numbers),
ffatypes,
fmt='dict')
elif fn_charges.endswith('.chk'):
sample = load_chk(fn_charges)
if path in sample.keys():
charges = sample[path]
else:
raise IOError(
'Given CHK file %s does not contain a dataset with label %s' %
(fn_charges, path))
radii = None
if args.gaussian:
if 'radii' in sample.keys():
radii = average(sample['radii'], ffatypes, fmt='dict')
else:
raise IOError(
'Invalid extension, fn_charges should be a HDF5 or a CHK file.')
# Derive charge parameters
if args.bci:
constraints = {}
if args.bci_constraints is not None:
constraints = read_bci_constraints(args.bci_constraints)
bcis = charges_to_bcis(charges,
ffatypes,
system.bonds,
constraints=constraints,
verbose=args.verbose)
make_yaff_ei(args.fn_out, None, bcis=bcis, radii=radii)
else:
charges = average(charges, ffatypes, fmt='dict', verbose=args.verbose)
make_yaff_ei(args.fn_out, charges, radii=radii)
def qff(args=None):
if args is None:
args = qff_parse_args()
else:
args = qff_parse_args(args)
#define logger
verbosity = None
if args.silent:
verbosity = 'silent'
else:
if args.very_verbose:
verbosity = 'highest'
elif args.verbose:
verbosity = 'high'
#get settings
kwargs = {
'fn_traj': args.fn_traj,
'only_traj': args.only_traj,
'program_mode': args.program_mode,
'plot_traj': args.plot_traj,
'xyz_traj': args.xyz_traj,
'suffix': args.suffix,
'log_level': verbosity,
'log_file': args.logfile,
'ffatypes': args.ffatypes,
'ei': args.ei,
'ei_rcut': args.ei_rcut,
'vdw': args.vdw,
'vdw_rcut': args.vdw_rcut,
'covres': args.covres,
}
settings = Settings(fn=args.config_file, **kwargs)
with log.section('INIT', 1, timer='Initializing'):
log.dump('Initializing system')
#read system and ab initio reference
system = None
energy = 0.0
grad = None
hess = None
pbc = None
rvecs = None
for fn in args.fn:
if fn.endswith('.fchk') or fn.endswith('.xml'):
numbers, coords, energy, grad, hess, masses, rvecs, pbc = read_abinitio(
fn)
if system is None:
system = System(numbers,
coords,
rvecs=rvecs,
charges=None,
radii=None,
masses=masses)
else:
system.pos = coords.copy()
system.cell = Cell(rvecs)
system.numbers = numbers.copy()
if masses is not None: system.masses = masses.copy()
system._init_derived()
elif fn.endswith('.chk'):
sample = load_chk(fn)
if 'energy' in list(sample.keys()): energy = sample['energy']
if 'grad' in list(sample.keys()): grad = sample['grad']
elif 'gradient' in list(sample.keys()):
grad = sample['gradient']
if 'hess' in list(sample.keys()): hess = sample['hess']
elif 'hessian' in list(sample.keys()): hess = sample['hessian']
if 'rvecs' in list(sample.keys()): pbc = [1, 1, 1]
else: pbc = [0, 0, 0]
if system is None:
system = System.from_file(fn)
else:
if 'pos' in list(sample.keys()): system.pos = sample['pos']
elif 'coords' in list(sample.keys()):
system.pos = sample['coords']
if 'rvecs' in list(sample.keys()):
system.cell = Cell(sample['rvecs'])
elif 'cell' in list(sample.keys()):
system.cell = Cell(sample['cell'])
if 'bonds' in list(sample.keys()):
system.bonds = sample['bonds']
if 'ffatypes' in list(sample.keys()):
system.ffatypes = sample['ffatypes']
if 'ffatype_ids' in list(sample.keys()):
system.ffatype_ids = sample['ffatype_ids']
system._init_derived()
else:
raise NotImplementedError('File format for %s not supported' %
fn)
assert system is not None, 'No system could be defined from input'
assert grad is not None, 'No ab initio gradient found in input'
assert hess is not None, 'No ab initio hessian found in input'
#complete the system information
if system.bonds is None: system.detect_bonds()
if system.masses is None: system.set_standard_masses()
if system.ffatypes is None:
if settings.ffatypes is not None:
set_ffatypes(system, settings.ffatypes)
else:
raise AssertionError('No atom types defined')
if settings.do_hess_negfreq_proj:
log.dump(
'Projecting negative frequencies out of the mass-weighted hessian.'
)
with log.section('SYS', 3, 'Initializing'):
hess = project_negative_freqs(hess, system.masses)
#construct ab initio reference
ai = SecondOrderTaylor('ai',
coords=system.pos.copy(),
energy=energy,
grad=grad,
hess=hess,
pbc=pbc)
#detect a priori defined contributions to the force field
refs = []
if settings.ei is not None:
if rvecs is None:
if settings.ei_rcut is None:
rcut = 50 * angstrom
else:
rcut = settings.ei_rcut
ff = ForceField.generate(system, settings.ei, rcut=rcut)
else:
if settings.ei_rcut is None:
rcut = 20 * angstrom
else:
rcut = settings.ei_rcut
ff = ForceField.generate(system,
settings.ei,
rcut=rcut,
alpha_scale=3.2,
gcut_scale=1.5,
smooth_ei=True)
refs.append(YaffForceField('EI', ff))
if settings.vdw is not None:
ff = ForceField.generate(system,
settings.vdw,
rcut=settings.vdw_rcut)
refs.append(YaffForceField('vdW', ff))
if settings.covres is not None:
ff = ForceField.generate(system, settings.covres)
refs.append(YaffForceField('Cov res', ff))
#define quickff program
assert settings.program_mode in allowed_programs, \
'Given program mode %s not allowed. Choose one of %s' %(
settings.program_mode,
', '.join([prog for prog in allowed_programs if not prog=='BaseProgram'])
)
mode = program_modes[settings.program_mode]
program = mode(system, ai, settings, ffrefs=refs)
#run program
program.run()
return program
def main():
options, args = parse()
fn_sys, fn_in, path = args
if fn_sys.endswith('.fchk'):
numbers, coords, energy, grad, hess, masses, rvecs, pbc = read_abinitio(
fn_sys, do_hess=False)
system = System(numbers,
coords,
rvecs=None,
charges=None,
radii=None,
masses=masses)
system.detect_bonds()
else:
system = System.from_file(fn_sys)
if options.ffatypes is not None:
guess_ffatypes(system, options.ffatypes)
ffatypes = [system.ffatypes[i] for i in system.ffatype_ids]
if fn_in.endswith('.h5'):
h5 = h5py.File(fn_in)
if not path in h5 or 'charges' not in h5[path]:
raise IOError(
'Given HDF5 file %s does not contain dataset %s/charges' %
(fn_in, path))
charges = h5['%s/charges' % path][:]
radii = None
if options.gaussian:
if 'radii' in h5[path]:
radii = average(h5['%s/radii' % path][:], ffatypes, fmt='dict')
else:
radii = average(get_ei_radii(system.numbers),
ffatypes,
fmt='dict')
elif fn_in.endswith('.chk'):
sample = load_chk(fn_in)
if path in sample.keys():
charges = sample[path]
else:
raise IOError(
'Given CHK file %s does not contain dataset with label %s' %
(fn_in, path))
radii = None
if options.gaussian:
if 'radii' in sample.keys():
radii = average(sample['radii'], ffatypes, fmt='dict')
else:
raise IOError(
'Invalid extension, fn_in should be a HDF5 or a CHK file.')
if options.output is None:
if path == '.':
fn_out = 'pars_ei.txt'
else:
fn_out = 'pars_ei_%s.txt' % path.replace('/', '_')
else:
fn_out = options.output
if options.bci:
constraints = {}
if options.bci_constraints is not None:
constraints = read_bci_constraints(options.bci_constraints)
bcis = charges_to_bcis(charges,
ffatypes,
system.bonds,
constraints=constraints,
verbose=options.verbose)
make_yaff_ei(fn_out, None, bcis=bcis, radii=radii)
else:
charges = average(charges,
ffatypes,
fmt='dict',
verbose=options.verbose)
make_yaff_ei(fn_out, charges, radii=radii)
def run_GCMC(self, N_iterations, N_sample):
A = Acceptance()
if rank == 0:
if not (os.path.isdir('results')):
try:
os.mkdir('results')
except:pass
if self.write_traj:
ftraj = open('results/traj_%.8f.xyz'%(self.P/bar), 'w')
e = 0
t_it = time()
N_samples = []
E_samples = []
pressures = []
traj = []
q0s = []
if rank == 0:
print('\n Iteration inst. N inst. E inst. V time [s]')
print('--------------------------------------------------------')
for iteration in range(N_iterations+1):
if self.ads_ei:
sfac_init = deepcopy(self.sfac)
pos_init = deepcopy(self.pos)
rvecs_init = deepcopy(self.rvecs)
rvecs_flat_init = deepcopy(self.rvecs_flat)
V_init = self.V
e_el_real_init = self.e_el_real
e_vdw_init = self.e_vdw
switch = np.random.rand()
acc = 0
# Insertion / deletion
if(switch < self.prob[0] and not self.Z_ads == self.fixed_N):
if(switch < self.prob[0]/2):
new_pos = random_ads(self.pos_ads, self.rvecs)
e_new = self.insertion(new_pos)
exp_value = self.beta * (-e_new + e)
if(exp_value > 100):
acc = 1
elif(exp_value < -100):
acc = 0
else:
acc = min(1, self.V*self.beta*self.fugacity/self.Z_ads * np.exp(exp_value))
# Reject monte carlo move
if np.random.rand() > acc:
self.pos = pos_init
if self.ads_ei:
self.sfac = sfac_init
self.e_el_real = e_el_real_init
self.e_vdw = e_vdw_init
self.Z_ads -= 1
else:
e = e_new
elif(self.Z_ads > 0):
deleted_coord, e_new = self.deletion()
exp_value = -self.beta * (e_new - e)
if(exp_value > 100):
acc = 1
else:
acc = min(1, (self.Z_ads+1)/self.V/self.beta/self.fugacity * np.exp(exp_value))
# Reject monte carlo move
if np.random.rand() > acc:
self.pos = pos_init
if self.ads_ei:
self.sfac = sfac_init
self.e_el_real = e_el_real_init
self.e_vdw = e_vdw_init
self.Z_ads += 1
else:
e = e_new
elif(switch < self.prob[1]):
if self.Z_ads != 0:
trial = np.random.randint(self.Z_ads)
if((switch < self.prob[0] + (self.prob[1]-self.prob[0])/2) or self.nads == 1):
# Calculate translation energy as deletion + insertion of molecule
deleted_coord, e_new = self.deletion()
deleted_coord += self.step * (np.random.rand(3) - 0.5)
e_new = self.insertion(deleted_coord)
else:
# Calculate rotation energy as deletion + insertion of molecule
deleted_coord, e_new = self.deletion()
deleted_coord = random_rot(deleted_coord, circlefrac=0.1)
e_new = self.insertion(deleted_coord)
exp_value = -self.beta * (e_new - e)
if(exp_value > 0):
exp_value = 0
acc = min(1, np.exp(exp_value))
# Reject monte carlo move
if np.random.rand() > acc:
self.pos = pos_init
if self.ads_ei:
self.sfac = sfac_init
self.e_el_real = e_el_real_init
self.e_vdw = e_vdw_init
else:
e = e_new
else:
# Construct system and forcefield class for the MD engine
from yaff import System, ForceField, XYZWriter, VerletScreenLog, MTKBarostat, \
NHCThermostat, TBCombination, VerletIntegrator, HDF5Writer, log
log.set_level(0)
n = np.append(self.data.numbers_MOF, np.tile(self.data.numbers_ads, self.Z_ads))
ffa_MOF = self.data.system.ffatypes[self.data.system.ffatype_ids]
ffa_ads = self.data.system_ads.ffatypes[self.data.system_ads.ffatype_ids]
ffa = np.append(ffa_MOF, np.tile(ffa_ads, self.Z_ads))
assert len(self.pos) == len(ffa)
s = System(n, self.pos, ffatypes = ffa, rvecs=self.rvecs)
s.detect_bonds()
ff = ForceField.generate(s, self.ff_file,
rcut=self.rcut,
alpha_scale=self.alpha_scale,
gcut_scale=self.gcut_scale,
tailcorrections=True)
ff_lammps = swap_noncovalent_lammps(ff, fn_system='system_%.8f.dat'%(self.P/bar),
fn_table='table.dat',
nrows=5000,
kspace='pppm',
kspace_accuracy=1e-7,
scalings_ei = [1.0, 1.0, 1.0],
move_central_cell=False,
fn_log="none",
overwrite_table=False, comm=comm)
# Setup and NPT MD run
if rank == 0:
vsl = VerletScreenLog(step=50)
if self.write_h5s:
if self.fixed_N:
hdf5_writer = HDF5Writer(h5.File('results/temp_%d.h5'%self.fixed_N, mode='w'), step=101)
else:
hdf5_writer = HDF5Writer(h5.File('results/temp_%.8f.h5'%(self.P/bar), mode='w'), step=101)
ensemble_hook = NHCThermostat(temp=self.T, timecon=100*femtosecond, chainlength=3)
if self.barostat:
mtk = MTKBarostat(ff_lammps, temp=self.T, press=self.P, \
timecon=1000*femtosecond, vol_constraint = self.vol_constraint, anisotropic = True)
ensemble_hook = TBCombination(ensemble_hook, mtk)
if self.meta:
cv = CVVolume(ff_lammps.system)
sigma = 1000*angstrom**3
K = 20*kjmol
step = 498
# Run MD
t = time()
if self.write_h5s:
if rank == 0:
verlet = VerletIntegrator(ff_lammps, self.timestep, hooks=[ensemble_hook, vsl, hdf5_writer], temp0=self.T)
else:
verlet = VerletIntegrator(ff_lammps, self.timestep, hooks=[ensemble_hook], temp0=self.T)
else:
if rank == 0:
hooks = [ensemble_hook, vsl]
if self.meta:
meta = MTDHook(ff_lammps, cv, sigma, K, start=step, step=step)
for q0 in q0s:
meta.hills.add_hill(q0, K)
hooks.append(meta)
verlet = VerletIntegrator(ff_lammps, self.timestep, hooks=hooks, temp0=self.T)
else:
hooks = [ensemble_hook]
if self.meta:
meta = MTDHook(ff_lammps, cv, sigma, K, start=step, step=step)
for q0 in q0s:
meta.hills.add_hill(q0, K)
hooks.append(meta)
verlet = VerletIntegrator(ff_lammps, self.timestep, hooks=hooks, temp0=self.T)
e0_tot = verlet._compute_ekin() + ff_lammps.compute()
verlet.run(600)
ef_tot = verlet._compute_ekin() + ff_lammps.compute()
if not self.vol_constraint:
Vn = np.linalg.det(ff_lammps.system.cell.rvecs)
exp_value = -self.beta * (ef_tot - e0_tot + self.P * (Vn - self.V) - len(self.pos)/self.beta * np.log(Vn/self.V))
else:
exp_value = -self.beta * (ef_tot - e0_tot)
if(exp_value > 0):
exp_value = 0
acc = min(1, np.exp(exp_value))
# Accept monte carlo move
if np.random.rand() < acc:
if self.write_h5s:
# Append MD data to previous data
self.append_h5()
# Rebuild data for MC
pos_total = ff_lammps.system.pos
self.pos = pos_total[:self.N_frame]
pos_molecules = pos_total[self.N_frame:]
self.rvecs = ff_lammps.system.cell.rvecs
self.rvecs_flat = self.rvecs.reshape(9)
self.V = np.linalg.det(self.rvecs)
if self.meta:
q0s.append(self.V)
if self.ads_ei:
self.sfac = Sfac(self.pos, self.N_frame, self.rvecs_flat, \
self.charges, self.alpha, self.gcut)
self.e_el_real = 0
self.e_vdw = 0
if self.Z_ads > 0:
for p in np.split(pos_molecules, self.Z_ads):
e_new = self.insertion(p)
self.Z_ads -= 1
e = e_new
else:
e = 0
else:
self.pos = pos_init
self.rvecs = rvecs_init
self.rvecs_flat = rvecs_flat_init
self.V = V_init
if rank == 0:
log.set_level(log.medium)
if(iteration % N_sample == 0 and iteration > 0):
eprint = e
if np.abs(eprint) < 1e-10:
eprint = 0
if rank == 0:
print(' {:7.7} {:7.7} {:7.7} {:7.7} {:7.4}'.format(
str(iteration),str(self.Z_ads),str(eprint/kjmol),str(self.V/angstrom**3),time()-t_it)
)
t_it = time()
N_samples.append(self.Z_ads)
E_samples.append(e)
if self.Z_ads == self.fixed_N:
traj.append(self.pos)
if rank == 0 and self.write_traj:
natom = self.N_frame + self.nads * self.Z_ads
rv = self.rvecs_flat/angstrom
ffa_MOF = self.data.system.ffatypes[self.data.system.ffatype_ids]
ffa_ads = self.data.system_ads.ffatypes[self.data.system_ads.ffatype_ids]
ffa = np.append(ffa_MOF, np.tile(ffa_ads, self.Z_ads))
ftraj.write('%d\n%f %f %f %f %f %f %f %f %f\n'%(natom, rv[0], rv[1], rv[2], rv[3], rv[4], rv[5], rv[6], rv[7], rv[8]))
for s, p in zip(ffa, self.pos/angstrom):
ftraj.write('%s %f %f %f\n'%(s, p[0], p[1], p[2]))
if rank == 0:
print('Average N: %.3f'%np.average(N_samples))
if self.fixed_N:
np.save('results/N_%d.npy'%self.fixed_N, np.array(N_samples))
np.save('results/E_%d.npy'%self.fixed_N, np.array(E_samples))
else:
np.save('results/N_%.8f.npy'%(self.P/bar), np.array(N_samples))
np.save('results/E_%.8f.npy'%(self.P/bar), np.array(E_samples))
if self.fixed_N:
from yaff import System
n = np.append(self.data.numbers_MOF, np.tile(self.data.numbers_ads, self.Z_ads))
s = System(n, self.pos, rvecs=self.rvecs)
s.to_file('results/end_%d.xyz'%self.fixed_N)
mol = Molecule.from_file('results/end_%d.xyz'%self.fixed_N)
symbols = mol.symbols
self.write_traj(traj, symbols)
os.remove('results/end_%d.xyz'%self.fixed_N)
if self.write_traj:
ftraj.close()
def main():
options, fns = parse()
#define logger
if options.silent:
log.set_level('silent')
else:
if options.very_verbose:
log.set_level('highest')
elif options.verbose:
log.set_level('high')
if options.logfile is not None and isinstance(options.logfile, str):
log.write_to_file(options.logfile)
with log.section('QFF', 1, timer='Initializing'):
log.dump('Initializing system')
#read system and ab initio reference
system = None
energy = 0.0
grad = None
hess = None
rvecs = None
for fn in fns:
if fn.endswith('.fchk') or fn.endswith('.xml'):
numbers, coords, energy, grad, hess, masses, rvecs, pbc = read_abinitio(
fn)
if system is None:
system = System(numbers,
coords,
rvecs=rvecs,
charges=None,
radii=None,
masses=masses)
else:
system.pos = coords.copy()
system.cell = Cell(rvecs)
system.numbers = numbers.copy()
if masses is not None: system.masses = masses.copy()
system._init_derived()
elif fn.endswith('.chk'):
sample = load_chk(fn)
if 'energy' in sample.keys(): energy = sample['energy']
if 'grad' in sample.keys(): grad = sample['grad']
elif 'gradient' in sample.keys(): grad = sample['gradient']
if 'hess' in sample.keys(): hess = sample['hess']
elif 'hessian' in sample.keys(): hess = sample['hessian']
if system is None:
system = System.from_file(fn)
else:
if 'pos' in sample.keys(): system.pos = sample['pos']
elif 'coords' in sample.keys():
system.pos = sample['coords']
if 'rvecs' in sample.keys():
system.cell = Cell(sample['rvecs'])
elif 'cell' in sample.keys():
system.cell = Cell(sample['cell'])
if 'bonds' in sample.keys(): system.bonds = sample['bonds']
if 'ffatypes' in sample.keys():
system.ffatypes = sample['ffatypes']
if 'ffatype_ids' in sample.keys():
system.ffatype_ids = sample['ffatype_ids']
system._init_derived()
else:
raise NotImplementedError('File format for %s not supported' %
fn)
assert system is not None, 'No system could be defined from input'
assert grad is not None, 'No ab initio gradient found in input'
assert hess is not None, 'No ab initio hessian found in input'
#complete the system information
if system.bonds is None: system.detect_bonds()
if system.masses is None: system.set_standard_masses()
if system.ffatypes is None:
if options.ffatypes in ['low', 'medium', 'high', 'highest']:
guess_ffatypes(system, options.ffatypes)
elif options.ffatypes is not None:
raise NotImplementedError(
'Guessing atom types from %s not implemented' %
options.ffatypes)
else:
raise AssertionError('No atom types defined')
#construct ab initio reference
ai = SecondOrderTaylor('ai',
coords=system.pos.copy(),
energy=energy,
grad=grad,
hess=hess,
pbc=pbc)
#detect a priori defined contributions to the force field
refs = []
if options.ei is not None:
if rvecs is None:
ff = ForceField.generate(system,
options.ei,
rcut=50 * angstrom)
else:
ff = ForceField.generate(system,
options.ei,
rcut=20 * angstrom,
alpha_scale=3.2,
gcut_scale=1.5,
smooth_ei=True)
refs.append(YaffForceField('EI', ff))
if options.vdw is not None:
ff = ForceField.generate(system, options.vdw, rcut=20 * angstrom)
refs.append(YaffForceField('vdW', ff))
if options.covres is not None:
ff = ForceField.generate(system, options.covres)
refs.append(YaffForceField('Cov res', ff))
#define quickff program
assert options.program_mode in allowed_programs, \
'Given program mode %s not allowed. Choose one of %s' %(
options.program_mode,
', '.join([prog for prog in allowed_programs if not prog=='BaseProgram'])
)
mode = program_modes[options.program_mode]
only_traj = 'PT_ALL'
if options.only_traj is not None: only_traj = options.only_traj.split(',')
program = mode(system,
ai,
ffrefs=refs,
fn_traj=options.fn_traj,
only_traj=only_traj,
plot_traj=options.ener_traj,
xyz_traj=options.xyz_traj,
suffix=options.suffix)
#run program
program.run()