if __name__ == '__main__':
elements = ['Pd', 'O']
rcuts = None
powers = {'O-Pd': range(2, 7), 'O-O': range(2, 7), 'Pd-Pd': range(2, 7)}
kptdensity = 3.0
calc = TANGO(
elements,
DftCalc=CP2KCalculator,
DftbPlusCalc=DftbPlusCalculator,
kptdensity=kptdensity,
initial_training='random_vc_relax',
generator=generator,
maximum_angular_momenta={
'Pd': 2,
'O': 1
},
rcuts=rcuts,
powers=powers,
update_rcuts=False,
kBT=1.,
comparator=comparator,
max_select=20,
)
os.environ['ASE_CP2K_COMMAND'] = 'mpirun -np 20 cp2k_shell.popt'
N = 1
for i in range(5):
calc.run(steps=1,
go_steps=0,
dbfiles = ['training.db']
force_scaling = 0.0 # how the forces should be weighted w.r.t. the forces;
# this does not matter here because the forces are zero by symmetry
rcov = covalent_radii[atomic_numbers['Si']]
rcuts = {
'Si-Si': 1.5 * 2 * rcov
} # 'outer' cutoff as approximately 1.5 times the NN distance
rmins = {
'Si-Si': 0.8 * 2 * rcov
} # 'inner' cutoff below which we switch to exponential repulsion
powers = {
'Si-Si': range(2, 7)
} # standard (rcut-r)**2 + ... + (rcut-r)**6 polynomial
calc = TANGO(
elements,
DftbPlusCalc=DftbPlusCalculator,
kptdensity=kptdensity,
rmins=rmins,
rcuts=rcuts,
powers=powers,
fit_constant=fit_constant,
kBT=kBT,
mode=mode,
force_scaling=force_scaling,
maximum_angular_momenta=mam,
)
residual = calc.fit_repulsion(dbfiles, run_checks=True)
print('Residual:', residual)
dimersdbfile = 'dimers.' + dbext
atomicfile = 'atomic_energies.json'
generate_training_data(dbext)
with open(atomicfile, 'r') as f:
atomic_energies = json.load(f)
for mode in ['poly', 'exp_poly', 'exp_spline']:
rmins = {pair: 0.7 * 2 * rcov} if mode == 'exp_poly' else None
powers = {pair: range(2, 7) if 'poly' in mode else range(4)}
calc = TANGO([element],
DftCalc=None,
DftbPlusCalc=DftbPlusCalc,
mode=mode,
kptdensity=None,
maximum_angular_momenta=mam,
fit_constant='element',
kBT=2.0,
force_scaling=0.,
rcuts=rcuts,
rmins=rmins,
powers=powers)
residual = calc.fit_repulsion([dbfile],
run_checks=False,
atomic_energies=atomic_energies,
dimersdb=dimersdbfile)
suffix = '%s_%s' % (dbext, mode)
assert residual < 0.02, (suffix, residual)
os.system('mv %s.pdf %s_%s.pdf' % (pair, pair, suffix))
if __name__=='__main__':
elements = ['Xx']
rcov = covalent_radii[atomic_numbers['Xx']]
rcuts = {'Xx-Xx': 1.5 * 2 * rcov}
rmins = {'Xx-Xx': 0.6 * 2 * rcov}
powers = {'Xx-Xx': range(2, 4)}
kptdensity = 1.5
calc = TANGO(elements,
DftCalc=CP2KCalculator,
DftbPlusCalc=DftbPlusCalc,
kptdensity=kptdensity,
initial_training='random_vc_relax',
generator=generator,
maximum_angular_momenta={'Xx': MAM},
mode='exp_poly',
rcuts=rcuts,
rmins=rmins,
powers=powers,
kBT=10.,
comparator=comparator,
max_select=20,
)
N = 1
calc.run(steps=1, go_steps=0, recalculate_dftb=True,
run_go=run, number_of_go_runs=2, restart_go=True)
N = 4
calc.run(steps=1, go_steps=10, recalculate_dftb=True,
run_go=run, number_of_go_runs=2, restart_go=True)
mam = {'C': 1, 'N': 1}
dbfile = 'training.json'
if os.path.exists(dbfile):
os.remove(dbfile)
generate_database(dbfile, rc)
for mode in ['poly', 'exp_poly', 'exp_spline']:
powers = {pair: range(2, 7) if 'poly' in mode else range(4)}
rmins = {pair: rmin} if 'exp' in mode else None
calc = TANGO(
elements,
DftCalc=None,
DftbPlusCalc=DftbPlusCalc,
mode=mode,
kptdensity=None,
maximum_angular_momenta=mam,
fit_constant=None,
kBT=2.,
force_scaling=1.,
rcuts=rcuts,
rmins=rmins,
powers=powers,
referencing=[range(18), [18, 19]],
)
residual = calc.fit_repulsion([dbfile], run_checks=False)
eps = 1e-6 if 'poly' in mode else 1e-2
assert residual < eps, (mode, residual, eps)
os.system('mv %s.pdf %s_%s.pdf' % (pair, pair, mode))