def nudged_elastic_band(images,
fmax=0.01,
algo='BFGS',
trajectory='path-neb.traj',
final='neb.traj'):
calc = cline.gen_active_calc()
load1 = calc.size[0]
master = calc.rank == 0
for image in images:
image.calc = calc
# calculate for the first and last images
# (for more efficient ML)
images[0].get_potential_energy()
images[-1].get_potential_energy()
# define and run NEB
neb = NEB(images, allow_shared_calculator=True)
Min = getattr(optimize, algo)
dyn = Min(neb, trajectory=trajectory, master=master)
dyn.run(fmax)
load2 = calc.size[0]
if master:
print(f'\tTotal number of Ab initio calculations: {load2-load1}\n')
# output
if master:
out = Trajectory(final, 'w')
for image in images:
image.get_potential_energy()
if master:
out.write(image)
def test(*args, r='::', o='test.traj'):
if 'calculator' in cline.ARGS and cline.ARGS['calculator'] is not None:
raise RuntimeError('set calculator = None in ARGS!')
traj = Trajectory(o, 'w')
calc = cline.gen_active_calc()
for arg in args:
data = [read(arg)] if (r is None or ':' not in r) else read(arg, r)
for atoms in data:
atoms.set_calculator(calc)
atoms.get_forces()
if calc.rank == 0:
traj.write(atoms)
def init_model(atoms, samples=5, rattle=0.05, trajectory='init.traj'):
"""
atoms: ASE atoms
samples: number of samples
rattle: stdev for random displacements
trajectory: traj file name
"""
calc = cline.gen_active_calc()
master = calc.rank == 0
if master:
traj = Trajectory(trajectory, 'w')
for _ in range(samples):
tmp = atoms.copy()
tmp.rattle(rattle, rng=np.random)
tmp.set_calculator(calc)
tmp.get_potential_energy()
if master:
traj.write(tmp)
def relax(atoms,
fmax=0.01,
cell=False,
mask=None,
algo='BFGS',
trajectory='relax.traj',
rattle=0.02,
clear_hist=True,
confirm=True):
"""
atoms: ASE atoms
fmax: maximum forces
cell: if True, minimize stress
mask: stress components for relaxation
algo: algo from ase.optimize
trajectory: traj file name
rattle: rattle atoms at initial step
clear_hist: clear optimizer histtory if ML model is updated
confirm: if True, do ab initio for the last step
"""
calc = cline.gen_active_calc()
load1 = calc.size[0]
master = calc.rank == 0
atoms.rattle(rattle, rng=np.random)
atoms.set_calculator(calc)
# define and run relaxation dynamics
if cell:
filtered = UnitCellFilter(atoms, mask=mask)
else:
filtered = atoms
Min = getattr(optimize, algo)
dyn = Min(filtered, trajectory=trajectory, master=master)
for _ in dyn.irun(fmax):
if calc.updated and clear_hist:
dyn.initialize()
load2 = calc.size[0]
# confirm:
if calc.active and confirm:
while True:
load2 += 1
if calc.update_data(try_fake=False):
calc.update(data=False)
calc.results.clear()
dyn.initialize()
dyn.run(fmax=fmax)
else:
break
ML = ('ML', calc.results['energy'], calc.results['forces'])
Ab = ('Ab initio', *calc._test())
for method, energy, forces in [ML, Ab]:
f_rms = np.sqrt(np.mean(forces**2))
f_max = abs(forces).max()
report = f"""
relaxation result ({method}):
energy: {energy}
force (rms): {f_rms}
force (max): {f_max}
"""
if master:
print(report)
if master:
print(f'\tTotal number of Ab initio calculations: {load2-load1}\n')
def md(atoms,
dynamics='NPT',
dt=None,
tem=300.,
picos=100,
bulk_modulus=None,
stress=0.,
mask=None,
iso=False,
trajectory='md.traj',
loginterval=1,
append=False,
rattle=0.0,
tdamp=25,
pdamp=100,
friction=1e-3,
ml_filter=0.8):
"""
atoms: ASE atoms
dynamics: 'NPT'
dt: time-step in fs
tem: temperature in Kelvin
picos: pico-seconds for md
bulk_modulus: bulk_modulus for NPT simulations. if None, NVT is performed
stress: external stress (GPa) for NPT
mask: see ase.npt.NPT
iso: if True, keep the shape constant
trajectory: traj file name
loginterval: for traj file
append: append to traj file
rattle: rattle atoms at initial step (recommended ~0.05)
tdamp: temperature damping time (fs)
pdamp: pressure damping time (fs)
friction: for Langevin dynamics
ml_filter: filters force discontinuities due to ML updates range(0, 1)
"""
calc = cline.gen_active_calc()
atoms.rattle(rattle, rng=np.random)
atoms.set_calculator(calc)
atoms.get_potential_energy()
init_velocities(atoms, tem)
if dt is None:
if (atoms.numbers == 1).any():
dt = 0.25
else:
dt = 1.
if ml_filter:
md_atoms = FilterDeltas(atoms, shrink=ml_filter)
else:
md_atoms = atoms
if dynamics.upper() == 'NPT':
dyn = npt_dynamics(md_atoms, dt, tem, bulk_modulus, stress, mask, iso,
trajectory, loginterval, append, tdamp, pdamp)
elif dynamics.upper() == 'LANGEVIN':
dyn = langevin_dynamics(md_atoms, dt, tem, friction, trajectory,
loginterval, append)
if calc.meta is not None:
dyn.attach(calc.meta.update)
steps = int(picos * 1000 / dt) if picos > 0 else -picos
dyn.run(steps)