def scf_phonons_inputs(structure, pseudos, kppa,
ecut=None, pawecutdg=None, scf_nband=None, accuracy="normal", spin_mode="polarized",
smearing="fermi_dirac:0.1 eV", charge=0.0, scf_algorithm=None):
"""
Returns a :class:`AbinitInput` for performing phonon calculations.
GS input + the input files for the phonon calculation.
Args:
structure: :class:`Structure` object.
pseudos: List of filenames or list of :class:`Pseudo` objects or :class:`PseudoTable` object.
kppa: Defines the sampling used for the SCF run.
ecut: cutoff energy in Ha (if None, ecut is initialized from the pseudos according to accuracy)
pawecutdg: cutoff energy in Ha for PAW double-grid (if None, pawecutdg is initialized from the
pseudos according to accuracy)
scf_nband: Number of bands for SCF run. If scf_nband is None, nband is automatically initialized from the list of
pseudos, the structure and the smearing option.
accuracy: Accuracy of the calculation.
spin_mode: Spin polarization.
smearing: Smearing technique.
charge: Electronic charge added to the unit cell.
scf_algorithm: Algorithm used for solving of the SCF cycle.
"""
# Build the input file for the GS run.
gs_inp = AbinitInput(structure=structure, pseudos=pseudos)
# Set the cutoff energies.
gs_inp.set_vars(_find_ecut_pawecutdg(ecut, pawecutdg, gs_inp.pseudos))
ksampling = aobj.KSampling.automatic_density(gs_inp.structure, kppa, chksymbreak=0)
gs_inp.set_vars(ksampling.to_abivars())
gs_inp.set_vars(tolvrs=1.0e-18)
# Get the qpoints in the IBZ. Note that here we use a q-mesh with ngkpt=(4,4,4) and shiftk=(0,0,0)
# i.e. the same parameters used for the k-mesh in gs_inp.
qpoints = gs_inp.abiget_ibz(ngkpt=(4,4,4), shiftk=(0,0,0), kptopt=1).points
#print("get_ibz qpoints:", qpoints)
# Build the input files for the q-points in the IBZ.
ph_inputs = MultiDataset(gs_inp.structure, pseudos=gs_inp.pseudos, ndtset=len(qpoints))
for ph_inp, qpt in zip(ph_inputs, qpoints):
# Response-function calculation for phonons.
ph_inp.set_vars(
rfphon=1, # Will consider phonon-type perturbation
nqpt=1, # One wavevector is to be considered
qpt=qpt, # This wavevector is q=0 (Gamma)
tolwfr=1.0e-20,
kptopt=3, # One could used symmetries for Gamma.
)
#rfatpol 1 1 # Only the first atom is displaced
#rfdir 1 0 0 # Along the first reduced coordinate axis
#kptopt 2 # Automatic generation of k points, taking
irred_perts = ph_inp.abiget_irred_phperts()
#for pert in irred_perts:
# #print(pert)
# # TODO this will work for phonons, but not for the other types of perturbations.
# ph_inp = q_inp.deepcopy()
# rfdir = 3 * [0]
# rfdir[pert.idir -1] = 1
# ph_inp.set_vars(
# rfdir=rfdir,
# rfatpol=[pert.ipert, pert.ipert]
# )
# ph_inputs.append(ph_inp)
# Split input into gs_inp and ph_inputs
all_inps = [gs_inp]
all_inps.extend(ph_inputs.split_datasets())
return all_inps
def scf_phonons_inputs(structure,
pseudos,
kppa,
ecut=None,
pawecutdg=None,
scf_nband=None,
accuracy="normal",
spin_mode="polarized",
smearing="fermi_dirac:0.1 eV",
charge=0.0,
scf_algorithm=None):
"""
Returns a :class:`AbinitInput` for performing phonon calculations.
GS input + the input files for the phonon calculation.
Args:
structure: :class:`Structure` object.
pseudos: List of filenames or list of :class:`Pseudo` objects or :class:`PseudoTable` object.
kppa: Defines the sampling used for the SCF run.
ecut: cutoff energy in Ha (if None, ecut is initialized from the pseudos according to accuracy)
pawecutdg: cutoff energy in Ha for PAW double-grid (if None, pawecutdg is initialized from the
pseudos according to accuracy)
scf_nband: Number of bands for SCF run. If scf_nband is None, nband is automatically initialized from the list of
pseudos, the structure and the smearing option.
accuracy: Accuracy of the calculation.
spin_mode: Spin polarization.
smearing: Smearing technique.
charge: Electronic charge added to the unit cell.
scf_algorithm: Algorithm used for solving of the SCF cycle.
"""
# Build the input file for the GS run.
gs_inp = AbinitInput(structure=structure, pseudos=pseudos)
# Set the cutoff energies.
gs_inp.set_vars(_find_ecut_pawecutdg(ecut, pawecutdg, gs_inp.pseudos))
ksampling = aobj.KSampling.automatic_density(gs_inp.structure,
kppa,
chksymbreak=0)
gs_inp.set_vars(ksampling.to_abivars())
gs_inp.set_vars(tolvrs=1.0e-18)
# Get the qpoints in the IBZ. Note that here we use a q-mesh with ngkpt=(4,4,4) and shiftk=(0,0,0)
# i.e. the same parameters used for the k-mesh in gs_inp.
qpoints = gs_inp.abiget_ibz(ngkpt=(4, 4, 4), shiftk=(0, 0, 0),
kptopt=1).points
#print("get_ibz qpoints:", qpoints)
# Build the input files for the q-points in the IBZ.
ph_inputs = MultiDataset(gs_inp.structure,
pseudos=gs_inp.pseudos,
ndtset=len(qpoints))
for ph_inp, qpt in zip(ph_inputs, qpoints):
# Response-function calculation for phonons.
ph_inp.set_vars(
rfphon=1, # Will consider phonon-type perturbation
nqpt=1, # One wavevector is to be considered
qpt=qpt, # This wavevector is q=0 (Gamma)
tolwfr=1.0e-20,
kptopt=3, # One could used symmetries for Gamma.
)
#rfatpol 1 1 # Only the first atom is displaced
#rfdir 1 0 0 # Along the first reduced coordinate axis
#kptopt 2 # Automatic generation of k points, taking
irred_perts = ph_inp.abiget_irred_phperts()
#for pert in irred_perts:
# #print(pert)
# # TODO this will work for phonons, but not for the other types of perturbations.
# ph_inp = q_inp.deepcopy()
# rfdir = 3 * [0]
# rfdir[pert.idir -1] = 1
# ph_inp.set_vars(
# rfdir=rfdir,
# rfatpol=[pert.ipert, pert.ipert]
# )
# ph_inputs.append(ph_inp)
# Split input into gs_inp and ph_inputs
all_inps = [gs_inp]
all_inps.extend(ph_inputs.split_datasets())
return all_inps
