def movie_maker():
grad = bohr2angstrom(np.array(get_gradients(), dtype=float))
coordinates = bohr2angstrom(get_coords())
energy = get_energy()
atoms_list = [
c.split()[-1]
for c in open('coord').read().split('$')[1].split('\n')[1:-1]
]
with open('movie.xyz', 'w') as fp:
fp.write("%3d\n" % len(coordinates))
fp.write('original:' + str(energy) + '\n')
for a, c in zip(atoms_list, coordinates):
fp.write("{:<2}{:12.5f}{:12.5f}{:12.5f}\n".format(
a.upper(), c[0], c[1], c[2]))
steps = [
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0, -1 - 2,
-3 - 4 - 5, -6, -7, -8. - 9, -10, -9, -8, -7, -6, -5, -4, -3, -2, -1, 0
]
for i in steps:
with open('movie.xyz', 'a') as fp:
fp.write("%3d\n" % len(coordinates))
fp.write(str(i) + ':' + str(energy) + '\n')
for a, c, g in zip(atoms_list, coordinates, grad):
fp.write("{:<2}{:12.5f}{:12.5f}{:12.5f}\n".format(
a.upper(), c[0] + g[0] * i, c[1] + g[1] * i,
c[2] + g[2] * i))
def optimize(self, options):
max_cycles = options['opt_cycles']
gamma = options['gamma']
convergence = options['opt_threshold']
pyar.interface.turbomole.make_coord(self.atoms_list, self.start_coords, self.coord_file)
pyar.interface.turbomole.prepare_control()
for cycle in range(max_cycles):
xtb_turbo_logger.debug("Optimization Cycle {}".format(cycle))
# Calculate energy and gradient
status, message, energy, gradients = self.calc_engrad
if status is False:
xtb_turbo_logger.critical('Energy/Gradient evaluation failed')
return 'SCFFailed'
# Calculate afir gradient if gamma is greater than zero
afir_energy, afir_gradient = restraints.isotropic(self.atoms_in_fragments, self.atoms_list,
pyar.interface.turbomole.get_coords(), gamma)
pyar.interface.turbomole.rewrite_turbomole_energy_and_gradient_files(self.number_of_atoms, afir_energy,
afir_gradient)
# Update coordinates and check convergence.
status = pyar.interface.turbomole.update_coord()
if status is False:
xtb_turbo_logger.critical('Coordinate update failed in cycle %d' % cycle)
xtb_turbo_logger.critical('Check the job in %s' % os.getcwd())
return 'UpdateFailed'
convergence_status = pyar.interface.turbomole.check_geometry_convergence()
if convergence_status is True:
xtb_turbo_logger.info('converged at {}'.format(cycle))
self.energy = pyar.interface.turbomole.get_energy()
self.optimized_coordinates = bohr2angstrom(pyar.interface.turbomole.get_coords())
interface.write_xyz(self.atoms_list, self.optimized_coordinates,
self.result_xyz_file,
self.job_name,
energy=self.energy)
return True
with open('energy.dat', 'a') as fe:
fe.writelines("{:3d} {:15.8f} {:15.8f}\n".format(cycle, energy, energy + afir_energy))
else:
xtb_turbo_logger.info("cycle exceeded")
status = 'cycle_exceeded'
self.energy = pyar.interface.turbomole.get_energy()
self.optimized_coordinates = bohr2angstrom(pyar.interface.turbomole.get_coords())
return status
def optimize(self, options):
"""This is the python implementation of jobex of turbomole
:returns: Union(True,
'SCFFailed',
'GradFailed',
'UpdateFailed',
'CycleExceeded',
False)
"""
max_cycles = options['opt_cycles']
gamma = options['gamma']
convergence = options['opt_threshold']
if convergence == 'loose':
scf_conv = 6
elif convergence == 'tight':
scf_conv = 8
else:
scf_conv = 7
basis_set = self.basis
functional = 'bp'
if self.method.lower() == 'bp86':
functional = 'bp'
if self.method.lower() == 'b3lyp':
functional = 'b3-lyp'
make_coord(self.atoms_list, self.start_coords)
define_status = prepare_control(scf_conv=scf_conv,
charge=self.charge,
multiplicity=self.multiplicity,
basis=basis_set,
func=functional)
if define_status is False:
turbomole_logger.debug(
'Initial Define failed, converting to cartesian coordinate')
remove('control')
define_status = prepare_control(scf_conv=scf_conv,
coordinates='cartesian',
charge=self.charge,
multiplicity=self.multiplicity)
if define_status is False:
turbomole_logger.debug('Initial Define failed again. Quit')
return 'UpdateFailed'
if gamma is None:
return self.run_turbomole_jobex(max_cycles=max_cycles)
# Test for Turbomole input
if not os.path.isfile('control'):
turbomole_logger.critical("Turbomole control file should exist")
return False
with open('not.converged', 'w') as fp:
fp.write('$convcrit\n')
fp.write(' energy 6\n')
fp.write(' cartesian gradient 3\n')
fp.write(' basis set gradient 3\n')
fp.write(' cycles 1\n')
fp.write('$convergence not reached\n')
fp.write('$end\n')
remove('statistics')
remove('dscf_problem')
turbomole_logger.info("Turbomole Optimization started\n")
turbomole_logger.info(" at %s\n" % datetime.datetime.now())
turbomole_logger.info(" on machine %s\n" % socket.gethostname())
turbomole_logger.info(" by user %s\n" % os.getlogin())
turbomole_logger.info(" in directory %s\n" % os.getcwd())
initial_status, initial_energy = calc_energy()
if initial_status is False:
turbomole_logger.warning('Initial energy evaluation failed.')
return 'SCFFailed'
turbomole_logger.debug('First step: %s, %f' %
(initial_status, initial_energy))
for cycle in range(max_cycles):
# Calculate Gradients
gradient_status = calc_gradients()
if gradient_status is False:
turbomole_logger.error(
'Gradient evaluation failed in cycle %d' % cycle)
return 'GradFailed'
for line in open('gradient').readlines():
if 'cycle' in line:
turbomole_logger.debug(line.strip())
# Calculate afir gradient if gamma is greater than zero
# if gamma > 0.0:
afir_energy, afir_gradients = restraints.isotropic(
self.atoms_in_fragments, self.atoms_list, get_coords(), gamma)
rewrite_turbomole_energy_and_gradient_files(
self.number_of_atoms, afir_energy, afir_gradients)
turbomole_logger.debug(f'restraint energy = {afir_energy:f}')
# Update coordinates and check convergence.
update_status = update_coord()
if update_status is False:
turbomole_logger.critical(
'Coordinate update failed in cycle %d' % cycle)
turbomole_logger.critical('Check the job in %s' % os.getcwd())
return 'UpdateFailed'
convergence_status = check_geometry_convergence()
if convergence_status is True:
turbomole_logger.info('converged at %d' % cycle)
self.energy = get_energy()
self.optimized_coordinates = bohr2angstrom(get_coords())
interface.write_xyz(self.atoms_list,
self.optimized_coordinates,
self.result_xyz_file,
self.job_name,
energy=self.energy)
return True
# Calculate energy
scf_status, energy = calc_energy()
if scf_status is False:
turbomole_logger.critical(
'Energy evaluation failed in cycle %d' % cycle)
return 'SCFFailed'
with open('energy.dat', 'a') as fe:
# if gamma > 0.0:
fe.writelines("{:3d} {:15.8f} {:15.8f}\n".format(
cycle, energy, energy + afir_energy))
# else:
# fe.writelines("{:3d} {:15.8f}\n".format(cycle, energy))
else:
turbomole_logger.info(
"OPTIMIZATION DID NOT CONVERGE WITHIN "
"%d CYCLES\n Restarting it after checking "
"the gradient norms\n might be a good idea..."
" (grep cycle gradient)" % max_cycles)
self.energy = get_energy()
self.optimized_coordinates = bohr2angstrom(get_coords())
return 'CycleExceeded'
def run_turbomole_jobex(self, max_cycles=350):
"""
Run a turbomole optimisation.
return one of the following:
True: converged
SCFFailed
GradFailed
UpdateFailed
CycleExceeded
False: unknown error or jebex execution error
:rtype: string or boolean
"""
with open('jobex.out', 'w') as fj:
try:
subp.check_call(['jobex', '-ri', '-c',
str(max_cycles)],
stdout=fj,
stderr=fj)
except subp.CalledProcessError as e:
turbomole_logger.debug('jobex failed, check %s/jobex.out' %
os.getcwd())
return False
if os.path.isfile('GEO_OPT_FAILED'):
message = open('GEO_OPT_FAILED').read()
if 'ERROR: Module' in message:
turbomole_logger.debug(
'Error in module!\n chcek %s/GEO_OPT_FAILED' % os.getcwd())
return False
elif 'ERROR in statpt step,' in message:
turbomole_logger.debug(
'Statpt failed!\n chcek %s/GEO_OPT_FAILED' % os.getcwd())
return 'UpdateFailed'
elif 'ERROR in relax step,' in message:
turbomole_logger.debug(
'Relax failed!\n chcek %s/GEO_OPT_FAILED' % os.getcwd())
return 'UpdateFailed'
elif 'ERROR: your energy calculation did not converge !!,' in message:
turbomole_logger.debug(
'SCF failed!\n chcek %s/GEO_OPT_FAILED' % os.getcwd())
return 'SCFFailed'
elif 'ERROR in dscf step' in message:
turbomole_logger.debug(
'SCF failed!\n chcek %s/GEO_OPT_FAILED' % os.getcwd())
return 'SCFFailed'
elif 'ERROR in gradient step' in message:
turbomole_logger.debug(
'Gradient failed!\n chcek %s/GEO_OPT_FAILED' % os.getcwd())
return 'GradientFailed'
elif 'OPTIMIZATION DID NOT CONVERGE' in message:
turbomole_logger.debug(
'Geometry did not converge in %d cycles.\ncheck %s' %
(max_cycles, os.getcwd()))
self.energy = get_energy()
self.optimized_coordinates = bohr2angstrom(get_coords())
return 'CycleExceeded'
else:
turbomole_logger.debug(
'Unknown Error!\n chcek the files in %s' % os.getcwd())
return False
elif os.path.isfile('GEO_OPT_CONVERGED'):
turbomole_logger.debug('jobex done')
self.energy = get_energy()
self.optimized_coordinates = bohr2angstrom(get_coords())
interface.write_xyz(self.atoms_list,
self.optimized_coordinates,
self.result_xyz_file,
self.job_name,
energy=self.energy)
return True