def ion_ioncell_relax_input(
structure,
pseudos,
kppa=None,
nband=None,
ecut=None,
pawecutdg=None,
accuracy="normal",
spin_mode="polarized",
smearing="fermi_dirac:0.1 eV",
charge=0.0,
scf_algorithm=None,
shift_mode="Monkhorst-pack",
):
"""
Returns a |BasicMultiDataset| for a structural relaxation. The first dataset optmizes the
atomic positions at fixed unit cell. The second datasets optimizes both ions and unit cell parameters.
Args:
structure: |Structure| object.
pseudos: List of filenames or list of |Pseudo| objects or |PseudoTable| object.
kppa: Defines the sampling used for the Brillouin zone.
nband: Number of bands included in the SCF run.
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 the solution of the SCF cycle.
"""
structure = as_structure(structure)
multi = BasicMultiDataset(structure, pseudos, ndtset=2)
# Set the cutoff energies.
multi.set_vars(
_find_ecut_pawecutdg(ecut, pawecutdg, multi.pseudos, accuracy))
kppa = _DEFAULTS.get("kppa") if kppa is None else kppa
shift_mode = ShiftMode.from_object(shift_mode)
shifts = _get_shifts(shift_mode, structure)
ksampling = aobj.KSampling.automatic_density(structure,
kppa,
chksymbreak=0,
shifts=shifts)
electrons = aobj.Electrons(
spin_mode=spin_mode,
smearing=smearing,
algorithm=scf_algorithm,
charge=charge,
nband=nband,
fband=None,
)
if electrons.nband is None:
electrons.nband = _find_scf_nband(structure, multi.pseudos, electrons,
multi[0].get("spinat", None))
ion_relax = aobj.RelaxationMethod.atoms_only(atoms_constraints=None)
ioncell_relax = aobj.RelaxationMethod.atoms_and_cell(
atoms_constraints=None)
multi.set_vars(electrons.to_abivars())
multi.set_vars(ksampling.to_abivars())
multi[0].set_vars(ion_relax.to_abivars())
multi[0].set_vars(_stopping_criterion("relax", accuracy))
multi[1].set_vars(ioncell_relax.to_abivars())
multi[1].set_vars(_stopping_criterion("relax", accuracy))
return multi
def ebands_input(
structure,
pseudos,
kppa=None,
nscf_nband=None,
ndivsm=15,
ecut=None,
pawecutdg=None,
scf_nband=None,
accuracy="normal",
spin_mode="polarized",
smearing="fermi_dirac:0.1 eV",
charge=0.0,
scf_algorithm=None,
dos_kppa=None,
):
"""
Returns a |BasicMultiDataset| object for band structure calculations.
Args:
structure: |Structure| object.
pseudos: List of filenames or list of |Pseudo| objects or |PseudoTable| object.
kppa: Defines the sampling used for the SCF run. Defaults to 1000 if not given.
nscf_nband: Number of bands included in the NSCF run. Set to scf_nband + 10 if None.
ndivsm: Number of divisions used to sample the smallest segment of the k-path.
if 0, only the GS input is returned in multi[0].
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.
dos_kppa: Scalar or List of integers with the number of k-points per atom
to be used for the computation of the DOS (None if DOS is not wanted).
"""
structure = as_structure(structure)
if dos_kppa is not None and not isinstance(dos_kppa, (list, tuple)):
dos_kppa = [dos_kppa]
multi = BasicMultiDataset(structure,
pseudos,
ndtset=2 if dos_kppa is None else 2 +
len(dos_kppa))
# Set the cutoff energies.
multi.set_vars(
_find_ecut_pawecutdg(ecut, pawecutdg, multi.pseudos, accuracy))
# SCF calculation.
kppa = _DEFAULTS.get("kppa") if kppa is None else kppa
scf_ksampling = aobj.KSampling.automatic_density(structure,
kppa,
chksymbreak=0)
scf_electrons = aobj.Electrons(
spin_mode=spin_mode,
smearing=smearing,
algorithm=scf_algorithm,
charge=charge,
nband=scf_nband,
fband=None,
)
if scf_electrons.nband is None:
scf_electrons.nband = _find_scf_nband(structure, multi.pseudos,
scf_electrons,
multi[0].get("spinat", None))
multi[0].set_vars(scf_ksampling.to_abivars())
multi[0].set_vars(scf_electrons.to_abivars())
multi[0].set_vars(_stopping_criterion("scf", accuracy))
if ndivsm == 0:
return multi
# Band structure calculation.
nscf_ksampling = aobj.KSampling.path_from_structure(ndivsm, structure)
nscf_nband = scf_electrons.nband + 10 if nscf_nband is None else nscf_nband
nscf_electrons = aobj.Electrons(
spin_mode=spin_mode,
smearing=smearing,
algorithm={"iscf": -2},
charge=charge,
nband=nscf_nband,
fband=None,
)
multi[1].set_vars(nscf_ksampling.to_abivars())
multi[1].set_vars(nscf_electrons.to_abivars())
multi[1].set_vars(_stopping_criterion("nscf", accuracy))
# DOS calculation with different values of kppa.
if dos_kppa is not None:
for i, kppa_ in enumerate(dos_kppa):
dos_ksampling = aobj.KSampling.automatic_density(structure,
kppa_,
chksymbreak=0)
# dos_ksampling = aobj.KSampling.monkhorst(dos_ngkpt, shiftk=dos_shiftk, chksymbreak=0)
dos_electrons = aobj.Electrons(
spin_mode=spin_mode,
smearing=smearing,
algorithm={"iscf": -2},
charge=charge,
nband=nscf_nband,
)
dt = 2 + i
multi[dt].set_vars(dos_ksampling.to_abivars())
multi[dt].set_vars(dos_electrons.to_abivars())
multi[dt].set_vars(_stopping_criterion("nscf", accuracy))
return multi