def bandstructure(workdir, runmode, structure, pseudos, scf_kppa, nscf_nband,
ndivsm, accuracy="normal", spin_mode="polarized",
smearing="fermi_dirac:0.1 eV", charge=0.0, scf_solver=None,
dos_kppa=None):
scf_ksampling = KSampling.automatic_density(structure, scf_kppa,
chksymbreak=0)
scf_strategy = ScfStrategy(structure, pseudos, scf_ksampling,
accuracy=accuracy, spin_mode=spin_mode,
smearing=smearing, charge=charge,
scf_solver=scf_solver)
nscf_ksampling = KSampling.path_from_structure(ndivsm, structure)
nscf_strategy = NscfStrategy(scf_strategy, nscf_ksampling, nscf_nband)
dos_strategy = None
if dos_kppa is not None:
raise NotImplementedError("DOS must be tested")
dos_ksampling = KSampling.automatic_density(structure, kppa,
chksymbreak=0)
dos_strategy = NscfStrategy(scf_strategy, dos_ksampling, nscf_nband,
nscf_solver=None)
return BandStructure(workdir, runmode, scf_strategy, nscf_strategy,
dos_strategy=dos_strategy)
def bandstructure(workdir, runmode, structure, pseudos, scf_kppa, nscf_nband,
ndivsm, accuracy="normal", spin_mode="polarized",
smearing="fermi_dirac:0.1 eV", charge=0.0, scf_solver=None,
dos_kppa=None):
"""
Returns a Work object that computes that bandstructure of the material.
Args:
workdir:
Working directory.
runmode:
`RunMode` instance.
structure:
Pymatgen structure.
pseudos:
List of `Pseudo` objects.
scf_kppa:
Defines the sampling used for the SCF run.
nscf_nband:
Number of bands included in the NSCF run.
ndivs:
Number of divisions used to sample the smallest segment of the k-path.
accuracy:
Accuracy of the calculation.
spin_mode:
Spin polarization.
smearing:
Smearing technique.
charge:
Electronic charge added to the unit cell.
scf_solver:
Algorithm used for solving of the SCF cycle.
dos_kppa
Defines the k-point sampling used for the computation of the DOS
(None if DOS is not wanted).
"""
scf_ksampling = KSampling.automatic_density(structure, scf_kppa,
chksymbreak=0)
scf_strategy = ScfStrategy(structure, pseudos, scf_ksampling,
accuracy=accuracy, spin_mode=spin_mode,
smearing=smearing, charge=charge,
scf_solver=scf_solver)
nscf_ksampling = KSampling.path_from_structure(ndivsm, structure)
nscf_strategy = NscfStrategy(scf_strategy, nscf_ksampling, nscf_nband)
dos_strategy = None
if dos_kppa is not None:
raise NotImplementedError("DOS must be tested")
dos_ksampling = KSampling.automatic_density(structure, kppa,
chksymbreak=0)
dos_strategy = NscfStrategy(scf_strategy, dos_ksampling, nscf_nband,
nscf_solver=None)
return BandStructure(workdir, runmode, scf_strategy, nscf_strategy,
dos_strategy=dos_strategy)
def __init__(self, structure, pseudos, ksampling=1000, relax_algo="atoms_and_cell", accuracy="normal",
spin_mode="polarized", smearing="fermi_dirac:0.1 eV", charge=0.0, scf_algorithm=None,
use_symmetries=True, ksampling_band=8, nscf_bands=None, nscf_algorithm=None, autoparal=False,
folder=None, **extra_abivars):
# workflow to obtain the density
if relax_algo in relaxation_methods.keys():
if relax_algo == "atoms_and_cell":
dens_wf = RelaxFWWorkflow(structure=structure, pseudos=pseudos, ksampling=ksampling, accuracy=accuracy,
spin_mode=spin_mode, smearing=smearing, charge=charge,
scf_algorithm=scf_algorithm, autoparal=autoparal, folder=folder,
**extra_abivars)
last_task = dens_wf.ioncell_task
else:
dens_wf = RelaxAtomsFWWorkflow(structure=structure, pseudos=pseudos, ksampling=ksampling,
accuracy=accuracy, spin_mode=spin_mode, smearing=smearing, charge=charge,
scf_algorithm=scf_algorithm, autoparal=autoparal, folder=folder,
**extra_abivars)
last_task = dens_wf.task
deps = {id(last_task): 'DEN structure'}
else:
if relax_algo not in (None, 'scf', 'scf_only', 'no_relax'):
logger.warning('relax_algo value "%s" not recognized. Perorming a scf calculation.' % relax_algo)
dens_wf = ScfFWWorkflow(structure=structure, pseudos=pseudos, ksampling=ksampling, accuracy=accuracy,
spin_mode=spin_mode, smearing=smearing, charge=charge, scf_algorithm=scf_algorithm,
use_symmetries=use_symmetries, autoparal=autoparal, folder=folder, **extra_abivars)
last_task = dens_wf.task
deps = {id(last_task): 'DEN'}
# Create the ksampling based on high symmetry lines of the structure
if isinstance(ksampling_band, int):
# ksampling_band = KSampling.automatic_density(structure, 100)
ksampling_band = KSampling.path_from_structure(ksampling_band, structure)
# Create the nscf FW
nscf_task = NscfStrategyFireTask(scf_task=last_task, ksampling=ksampling_band, nscf_bands=nscf_bands,
nscf_algorithm=nscf_algorithm, deps=deps, **extra_abivars)
spec = {'create_file': 'band_structure'}
if folder:
spec['_launch_dir'] = os.path.join(folder, 'band_structure')
nscf_fw = Firework(nscf_task, spec=spec)
# Expand the first part to get the proper list of FWs and links
fws, links = parse_workflow([dens_wf.wf, nscf_fw], {dens_wf.wf: [nscf_fw]})
self.wf = Workflow(fws, links)
def bandstructure(structure, pseudos, scf_kppa, nscf_nband,
ndivsm, accuracy="normal", spin_mode="polarized",
smearing="fermi_dirac:0.1 eV", charge=0.0, scf_algorithm=None,
dos_kppa=None, workdir=None, manager=None, **extra_abivars):
"""
Returns a Work object that computes that bandstructure of the material.
Args:
structure:
Pymatgen structure.
pseudos:
List of `Pseudo` objects.
scf_kppa:
Defines the sampling used for the SCF run.
nscf_nband:
Number of bands included in the NSCF run.
ndivs:
Number of divisions used to sample the smallest segment of the
k-path.
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:
Defines the k-point sampling used for the computation of the DOS
(None if DOS is not wanted).
workdir:
Working directory.
manager:
`TaskManager` instance.
extra_abivars:
Dictionary with extra variables passed to ABINIT.
"""
# SCF calculation.
scf_ksampling = KSampling.automatic_density(structure, scf_kppa, chksymbreak=0)
scf_strategy = ScfStrategy(structure, pseudos, scf_ksampling,
accuracy=accuracy, spin_mode=spin_mode,
smearing=smearing, charge=charge,
scf_algorithm=scf_algorithm, **extra_abivars)
# Band structure calculation.
nscf_ksampling = KSampling.path_from_structure(ndivsm, structure)
nscf_strategy = NscfStrategy(scf_strategy, nscf_ksampling, nscf_nband, **extra_abivars)
# DOS calculation.
dos_strategy = None
if dos_kppa is not None:
raise NotImplementedError("DOS must be tested")
dos_ksampling = KSampling.automatic_density(structure, dos_kppa, chksymbreak=0)
#dos_ksampling = KSampling.monkhorst(dos_ngkpt, shiftk=dos_shiftk, chksymbreak=0)
dos_strategy = NscfStrategy(scf_strategy, dos_ksampling, nscf_nband, nscf_solver=None, **extra_abivars)
return BandStructureWorkflow(scf_strategy, nscf_strategy, dos_inputs=dos_strategy,
workdir=workdir, manager=manager)
def bandstructure(structure, pseudos, scf_kppa, nscf_nband,
ndivsm, accuracy="normal", spin_mode="polarized",
smearing="fermi_dirac:0.1 eV", charge=0.0, scf_algorithm=None,
dos_kppa=None, workdir=None, manager=None, **extra_abivars):
"""
Returns a Work object that computes that bandstructure of the material.
Args:
structure:
Pymatgen structure.
pseudos:
List of `Pseudo` objects.
scf_kppa:
Defines the sampling used for the SCF run.
nscf_nband:
Number of bands included in the NSCF run.
ndivs:
Number of divisions used to sample the smallest segment of the
k-path.
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:
Defines the k-point sampling used for the computation of the DOS
(None if DOS is not wanted).
workdir:
Working directory.
manager:
`TaskManager` instance.
extra_abivars:
Dictionary with extra variables passed to ABINIT.
"""
# SCF calculation.
scf_ksampling = KSampling.automatic_density(structure, scf_kppa, chksymbreak=0)
scf_strategy = ScfStrategy(structure, pseudos, scf_ksampling,
accuracy=accuracy, spin_mode=spin_mode,
smearing=smearing, charge=charge,
scf_algorithm=scf_algorithm, **extra_abivars)
# Band structure calculation.
nscf_ksampling = KSampling.path_from_structure(ndivsm, structure)
nscf_strategy = NscfStrategy(scf_strategy, nscf_ksampling, nscf_nband, **extra_abivars)
# DOS calculation.
dos_strategy = None
if dos_kppa is not None:
raise NotImplementedError("DOS must be tested")
dos_ksampling = KSampling.automatic_density(structure, dos_kppa, chksymbreak=0)
#dos_ksampling = KSampling.monkhorst(dos_ngkpt, shiftk=dos_shiftk, chksymbreak=0)
dos_strategy = NscfStrategy(scf_strategy, dos_ksampling, nscf_nband, nscf_solver=None, **extra_abivars)
return BandStructureWorkflow(scf_strategy, nscf_strategy, dos_inputs=dos_strategy,
workdir=workdir, manager=manager)
def __init__(self,
structure,
pseudos,
ksampling=1000,
relax_algo="atoms_and_cell",
accuracy="normal",
spin_mode="polarized",
smearing="fermi_dirac:0.1 eV",
charge=0.0,
scf_algorithm=None,
use_symmetries=True,
ksampling_band=8,
nscf_bands=None,
nscf_algorithm=None,
autoparal=False,
folder=None,
**extra_abivars):
# workflow to obtain the density
if relax_algo in relaxation_methods.keys():
if relax_algo == "atoms_and_cell":
dens_wf = RelaxFWWorkflow(structure=structure,
pseudos=pseudos,
ksampling=ksampling,
accuracy=accuracy,
spin_mode=spin_mode,
smearing=smearing,
charge=charge,
scf_algorithm=scf_algorithm,
autoparal=autoparal,
folder=folder,
**extra_abivars)
last_task = dens_wf.ioncell_task
else:
dens_wf = RelaxAtomsFWWorkflow(structure=structure,
pseudos=pseudos,
ksampling=ksampling,
accuracy=accuracy,
spin_mode=spin_mode,
smearing=smearing,
charge=charge,
scf_algorithm=scf_algorithm,
autoparal=autoparal,
folder=folder,
**extra_abivars)
last_task = dens_wf.task
deps = {id(last_task): 'DEN structure'}
else:
if relax_algo not in (None, 'scf', 'scf_only', 'no_relax'):
logger.warning(
'relax_algo value "%s" not recognized. Perorming a scf calculation.'
% relax_algo)
dens_wf = ScfFWWorkflow(structure=structure,
pseudos=pseudos,
ksampling=ksampling,
accuracy=accuracy,
spin_mode=spin_mode,
smearing=smearing,
charge=charge,
scf_algorithm=scf_algorithm,
use_symmetries=use_symmetries,
autoparal=autoparal,
folder=folder,
**extra_abivars)
last_task = dens_wf.task
deps = {id(last_task): 'DEN'}
# Create the ksampling based on high symmetry lines of the structure
if isinstance(ksampling_band, int):
# ksampling_band = KSampling.automatic_density(structure, 100)
ksampling_band = KSampling.path_from_structure(
ksampling_band, structure)
# Create the nscf FW
nscf_task = NscfStrategyFireTask(scf_task=last_task,
ksampling=ksampling_band,
nscf_bands=nscf_bands,
nscf_algorithm=nscf_algorithm,
deps=deps,
**extra_abivars)
spec = {'create_file': 'band_structure'}
if folder:
spec['_launch_dir'] = os.path.join(folder, 'band_structure')
nscf_fw = Firework(nscf_task, spec=spec)
# Expand the first part to get the proper list of FWs and links
fws, links = parse_workflow([dens_wf.wf, nscf_fw],
{dens_wf.wf: [nscf_fw]})
self.wf = Workflow(fws, links)
