# Create and attach InducedField object
frequencies = [1.0, 2.08] # Frequencies of interest in eV
folding = 'Gauss' # Folding function
width = 0.1 # Line width for folding in eV
ind = TDDFTInducedField(paw=td_calc,
frequencies=frequencies,
folding=folding,
width=width,
restart_file='na2_td.ind')
# Propagate as usual
td_calc.propagate(time_step, iterations // 2, 'na2_td_dm.dat', 'na2_td.gpw')
# Save TDDFT and InducedField objects
td_calc.write('na2_td.gpw', mode='all')
ind.write('na2_td.ind')
ind.paw = None
# Restart and continue
td_calc = TDDFT('na2_td.gpw')
# Load and attach InducedField object
ind = TDDFTInducedField(filename='na2_td.ind',
paw=td_calc,
restart_file='na2_td.ind')
# Continue propagation as usual
td_calc.propagate(time_step, iterations // 2, 'na2_td_dm.dat', 'na2_td.gpw')
# Calculate induced electric field
Ekin *= 1 / Hartree
v = np.zeros((proj_idx + 1, 3))
v[proj_idx, 2] = -np.sqrt((2 * Ekin) / Mproj) * Bohr / AUT
tdcalc.atoms.set_velocities(v)
evv = EhrenfestVelocityVerlet(tdcalc)
traj = Trajectory(traj_file, 'w', tdcalc.get_atoms())
trajdiv = 1 # number of timesteps between trajectory images
densdiv = 10 # number of timesteps between saved electron densities
niters = 100 # total number of timesteps to propagate
for i in range(niters):
# Stopping condition when projectile z coordinate passes threshold
if evv.x[proj_idx, 2] < delta_stop:
tdcalc.write(strbody + '_end.gpw', mode='all')
break
# Saving trajectory file every trajdiv timesteps
if i % trajdiv == 0:
F_av = evv.F * Hartree / Bohr # forces converted from atomic units
v_av = evv.v * Bohr / AUT # velocities converted from atomic units
epot = tdcalc.get_td_energy() * Hartree # energy
atoms = tdcalc.get_atoms().copy()
atoms.set_velocities(v_av)
traj.write(atoms, energy=epot, forces=F_av)
# Saving electron density every densdiv timesteps
if (i != 0 and i % densdiv == 0):
tdcalc.write(strbody + '_step' + str(i) + '.gpw')
class UTStaticPropagatorSetup(UTGroundStateSetup):
__doc__ = UTGroundStateSetup.__doc__ + """
Propagate electrons with fixed nuclei and verify results.""" #TODO
duration = 10.0 #24.0
timesteps = None
propagator = None
def setUp(self):
UTGroundStateSetup.setUp(self)
for virtvar in ['timesteps', 'propagator']:
assert getattr(self,virtvar) is not None, 'Virtual "%s"!' % virtvar
self.tdname = 'ut_tddft_td_' + self.propagator.lower()
self.tdcalc = TDDFT(self.gsname + '.gpw', propagator=self.propagator,
txt=self.tdname + '.txt')
def tearDown(self):
del self.tdcalc
# =================================
def _test_timestepping(self, t):
#XXX DEBUG START
if debug and os.path.isfile('%s_%d.gpw' % (self.tdname, t)):
return
#XXX DEBUG END
timestep = self.timesteps[t]
self.assertAlmostEqual(self.duration % timestep, 0.0, 12)
niter = int(self.duration / timestep)
ndiv = 1 #XXX
traj = PickleTrajectory('%s_%d.traj' % (self.tdname, t),
'w', self.tdcalc.get_atoms())
t0 = time.time()
f = paropen('%s_%d.log' % (self.tdname, t), 'w')
print >>f, 'propagator: %s, duration: %6.1f as, timestep: %5.2f as, ' \
'niter: %d' % (self.propagator, self.duration, timestep, niter)
for i in range(1, niter+1):
# XXX bare bones propagation without all the nonsense
self.tdcalc.propagator.propagate(self.tdcalc.time,
timestep * attosec_to_autime)
self.tdcalc.time += timestep * attosec_to_autime
self.tdcalc.niter += 1
if i % ndiv == 0:
rate = 60 * ndiv / (time.time()-t0)
ekin = self.tdcalc.atoms.get_kinetic_energy()
epot = self.tdcalc.get_td_energy() * Hartree
F_av = np.zeros((len(self.tdcalc.atoms), 3))
print >>f, 'i=%06d, time=%6.1f as, rate=%6.2f min^-1, ' \
'ekin=%13.9f eV, epot=%13.9f eV, etot=%13.9f eV' \
% (i, timestep * i, rate, ekin, epot, ekin + epot)
t0 = time.time()
# Hack to prevent calls to GPAW::get_potential_energy when saving
spa = self.tdcalc.get_atoms()
spc = SinglePointCalculator(epot, F_av, None, None, spa)
spa.set_calculator(spc)
traj.write(spa)
f.close()
traj.close()
self.tdcalc.write('%s_%d.gpw' % (self.tdname, t), mode='all')
# Save density and wavefunctions to binary
gd, finegd = self.tdcalc.wfs.gd, self.tdcalc.density.finegd
if world.rank == 0:
big_nt_g = finegd.collect(self.tdcalc.density.nt_g)
np.save('%s_%d_nt.npy' % (self.tdname, t), big_nt_g)
del big_nt_g
big_psit_nG = gd.collect(self.tdcalc.wfs.kpt_u[0].psit_nG)
np.save('%s_%d_psit.npy' % (self.tdname, t), big_psit_nG)
del big_psit_nG
else:
finegd.collect(self.tdcalc.density.nt_g)
gd.collect(self.tdcalc.wfs.kpt_u[0].psit_nG)
world.barrier()
def test_timestepping_ref(self):
# Reference values for density and wavefunctions (assumed stationary)
nt0_g = self.tdcalc.density.nt_g
phases_n = self.tdcalc.wfs.kpt_u[0].eps_n * self.duration * attosec_to_autime
psit0_nG = np.exp(-1j * phases_n) * self.tdcalc.wfs.kpt_u[0].psit_nG
f = paropen('%s_ref.log' % self.tdname, 'w')
niters = np.round(self.duration / self.timesteps).astype(int)
print >>f, 'propagator: %s, duration: %6.1f as, niters: %s, ' \
% (self.propagator, self.duration, niters.tolist())
for t,timestep in enumerate(self.timesteps):
self.assertTrue(os.path.isfile('%s_%d.gpw' % (self.tdname, t)))
# Load density and wavefunctions from binary
gd, finegd = self.tdcalc.wfs.gd, self.tdcalc.density.finegd
nt_g, psit_nG = finegd.empty(), gd.empty(self.nbands, dtype=complex)
if world.rank == 0:
big_nt_g = np.load('%s_%d_nt.npy' % (self.tdname, t))
finegd.distribute(big_nt_g, nt_g)
del big_nt_g
big_psit_nG = np.load('%s_%d_psit.npy' % (self.tdname, t))
gd.distribute(big_psit_nG, psit_nG)
del big_psit_nG
else:
finegd.distribute(None, nt_g)
gd.distribute(None, psit_nG)
# Check loaded density and wavefunctions against reference values
dnt = finegd.comm.max(np.abs(nt_g - nt0_g).max())
dpsit = gd.comm.max(np.abs(psit_nG - psit0_nG).max())
print >>f, 't=%d, timestep: %5.2f as, dnt: %16.13f, ' \
'dpsit: %16.13f' % (t, timestep, dnt, dpsit)
snt, spsit = {'SITE': (5,4)}.get(self.propagator, (7,5))
#self.assertAlmostEqual(dnt, 0, snt, 't=%d, timestep: ' \
# '%5.2f as, dnt: %g, digits: %d' % (t, timestep, dnt, snt))
#self.assertAlmostEqual(dpsit, 0, spsit, 't=%d, timestep: ' \
# '%5.2f as, dpsit=%g, digits: %d' % (t, timestep, dpsit, spsit))
f.close()
class UTStaticPropagatorSetup(UTGroundStateSetup):
__doc__ = UTGroundStateSetup.__doc__ + """
Propagate electrons with fixed nuclei and verify results.""" #TODO
duration = 10.0 #24.0
timesteps = None
propagator = None
def setUp(self):
UTGroundStateSetup.setUp(self)
for virtvar in ['timesteps', 'propagator']:
assert getattr(self,
virtvar) is not None, 'Virtual "%s"!' % virtvar
self.tdname = 'ut_tddft_td_' + self.propagator.lower()
self.tdcalc = TDDFT(self.gsname + '.gpw',
propagator=self.propagator,
txt=self.tdname + '.txt')
def tearDown(self):
del self.tdcalc
# =================================
def _test_timestepping(self, t):
#XXX DEBUG START
if debug and os.path.isfile('%s_%d.gpw' % (self.tdname, t)):
return
#XXX DEBUG END
timestep = self.timesteps[t]
self.assertAlmostEqual(self.duration % timestep, 0.0, 12)
niter = int(self.duration / timestep)
ndiv = 1 #XXX
traj = PickleTrajectory('%s_%d.traj' % (self.tdname, t), 'w',
self.tdcalc.get_atoms())
t0 = time.time()
f = paropen('%s_%d.log' % (self.tdname, t), 'w')
print('propagator: %s, duration: %6.1f as, timestep: %5.2f as, ' \
'niter: %d' % (self.propagator, self.duration, timestep, niter), file=f)
for i in range(1, niter + 1):
# XXX bare bones propagation without all the nonsense
self.tdcalc.propagator.propagate(self.tdcalc.time,
timestep * attosec_to_autime)
self.tdcalc.time += timestep * attosec_to_autime
self.tdcalc.niter += 1
if i % ndiv == 0:
rate = 60 * ndiv / (time.time() - t0)
ekin = self.tdcalc.atoms.get_kinetic_energy()
epot = self.tdcalc.get_td_energy() * Hartree
F_av = np.zeros((len(self.tdcalc.atoms), 3))
print('i=%06d, time=%6.1f as, rate=%6.2f min^-1, ' \
'ekin=%13.9f eV, epot=%13.9f eV, etot=%13.9f eV' \
% (i, timestep * i, rate, ekin, epot, ekin + epot), file=f)
t0 = time.time()
# Hack to prevent calls to GPAW::get_potential_energy when saving
spa = self.tdcalc.get_atoms()
spc = SinglePointCalculator(epot, F_av, None, None, spa)
spa.set_calculator(spc)
traj.write(spa)
f.close()
traj.close()
self.tdcalc.write('%s_%d.gpw' % (self.tdname, t), mode='all')
# Save density and wavefunctions to binary
gd, finegd = self.tdcalc.wfs.gd, self.tdcalc.density.finegd
if world.rank == 0:
big_nt_g = finegd.collect(self.tdcalc.density.nt_g)
np.save('%s_%d_nt.npy' % (self.tdname, t), big_nt_g)
del big_nt_g
big_psit_nG = gd.collect(self.tdcalc.wfs.kpt_u[0].psit_nG)
np.save('%s_%d_psit.npy' % (self.tdname, t), big_psit_nG)
del big_psit_nG
else:
finegd.collect(self.tdcalc.density.nt_g)
gd.collect(self.tdcalc.wfs.kpt_u[0].psit_nG)
world.barrier()
def test_timestepping_ref(self):
# Reference values for density and wavefunctions (assumed stationary)
nt0_g = self.tdcalc.density.nt_g
phases_n = self.tdcalc.wfs.kpt_u[
0].eps_n * self.duration * attosec_to_autime
psit0_nG = np.exp(-1j * phases_n) * self.tdcalc.wfs.kpt_u[0].psit_nG
f = paropen('%s_ref.log' % self.tdname, 'w')
niters = np.round(self.duration / self.timesteps).astype(int)
print('propagator: %s, duration: %6.1f as, niters: %s, ' \
% (self.propagator, self.duration, niters.tolist()), file=f)
for t, timestep in enumerate(self.timesteps):
self.assertTrue(os.path.isfile('%s_%d.gpw' % (self.tdname, t)))
# Load density and wavefunctions from binary
gd, finegd = self.tdcalc.wfs.gd, self.tdcalc.density.finegd
nt_g, psit_nG = finegd.empty(), gd.empty(self.nbands,
dtype=complex)
if world.rank == 0:
big_nt_g = np.load('%s_%d_nt.npy' % (self.tdname, t))
finegd.distribute(big_nt_g, nt_g)
del big_nt_g
big_psit_nG = np.load('%s_%d_psit.npy' % (self.tdname, t))
gd.distribute(big_psit_nG, psit_nG)
del big_psit_nG
else:
finegd.distribute(None, nt_g)
gd.distribute(None, psit_nG)
# Check loaded density and wavefunctions against reference values
dnt = finegd.comm.max(np.abs(nt_g - nt0_g).max())
dpsit = gd.comm.max(np.abs(psit_nG - psit0_nG).max())
print('t=%d, timestep: %5.2f as, dnt: %16.13f, ' \
'dpsit: %16.13f' % (t, timestep, dnt, dpsit), file=f)
snt, spsit = {'SITE': (5, 4)}.get(self.propagator, (7, 5))
#self.assertAlmostEqual(dnt, 0, snt, 't=%d, timestep: ' \
# '%5.2f as, dnt: %g, digits: %d' % (t, timestep, dnt, snt))
#self.assertAlmostEqual(dpsit, 0, spsit, 't=%d, timestep: ' \
# '%5.2f as, dpsit=%g, digits: %d' % (t, timestep, dpsit, spsit))
f.close()
time_step = 10.0
iterations = 10
td_calc = TDDFT('gs.gpw')
td_calc.absorption_kick(kick_strength=kick)
td_calc.hamiltonian.poisson.set_kick(kick)
# Attach InducedFields to the calculation
frequencies = [2.05, 4.0]
width = 0.15
cl_ind = FDTDInducedField(paw=td_calc, frequencies=frequencies, width=width)
qm_ind = TDDFTInducedField(paw=td_calc, frequencies=frequencies, width=width)
# Propagate TDDFT and FDTD
td_calc.propagate(time_step, iterations // 2, 'dm.dat', 'td.gpw')
td_calc.write('td.gpw', 'all')
cl_ind.write('cl.ind')
qm_ind.write('qm.ind')
td_calc = None
cl_ind.paw = None
qm_ind.paw = None
cl_ind = None
qm_ind = None
# Restart
td_calc = TDDFT('td.gpw')
cl_ind = FDTDInducedField(filename='cl.ind', paw=td_calc)
qm_ind = TDDFTInducedField(filename='qm.ind', paw=td_calc)
td_calc.propagate(time_step, iterations // 2, 'dm.dat', 'td.gpw')
td_calc.write('td.gpw', 'all')
cl_ind.write('cl.ind')
from gpaw.tddft import TDDFT
from gpaw.inducedfield.inducedfield_tddft import TDDFTInducedField
# Load TDDFT object
td_calc = TDDFT('na2_td.gpw')
# Load and attach InducedField object
ind = TDDFTInducedField(filename='na2_td.ind',
paw=td_calc,
restart_file='na2_td.ind')
# Continue propagation as usual
time_step = 20.0
iterations = 250
td_calc.propagate(time_step, iterations, 'na2_td_dm.dat', 'na2_td.gpw')
# Save TDDFT and InducedField objects
td_calc.write('na2_td.gpw', mode='all')
ind.write('na2_td.ind')
