def __init__(self, user_incar_settings,
constrain_total_magmom=False, sort_structure=False,
kpoints_density=1000, sym_prec=0.1):
self.sym_prec = sym_prec
DictVaspInputSet.__init__(
self, "MaterialsProject Static",
loadfn(os.path.join(MODULE_DIR, "MPVaspInputSet.yaml")),
constrain_total_magmom=constrain_total_magmom,
sort_structure=sort_structure)
self.user_incar_settings = user_incar_settings
# impose tetrahedron method
self.incar_settings.update(
{"IBRION": -1, "ISMEAR": -5, "LCHARG": False,
"LORBIT": 11, "LWAVE": False, "NSW": 0, "ISYM": 0, "ICHARG": 11})
# this variable may have been used in the ground state calculation,
# but is not relevant to the tetrahedron DOS calculation; its superfluous
# presence in the INCAR leads to (human) confusion (VASP doesn't care).
self.incar_settings.pop('SIGMA',None)
self.kpoints_settings.update({"kpoints_density": kpoints_density})
# Set dense DOS output
self.incar_settings.update({"NEDOS": 2001})
if "NBANDS" not in user_incar_settings:
raise KeyError("For NonSCF runs, NBANDS value from SC runs is "
"required!")
else:
self.incar_settings.update(user_incar_settings)
def __init__(self, user_incar_settings=None, constrain_total_magmom=False):
module_dir = os.path.dirname(os.path.abspath(__file__))
with open(os.path.join(module_dir, "QiminGWVaspInputSet.json")) as f:
DictVaspInputSet.__init__(
self, "Qimin GW", json.load(f),
constrain_total_magmom=constrain_total_magmom)
if user_incar_settings:
self.incar_settings.update(user_incar_settings)
def __init__(self, structure, spec, functional='PBE', sym_prec=0.01, **kwargs):
"""
Supports the same kwargs as :class:`JSONVaspInputSet`.
"""
with open(GWVaspInputSet) as f:
DictVaspInputSet.__init__(
self, "MP Static Self consistent run for GW", json.load(f), **kwargs)
self.structure = structure
self.tests = self.__class__.get_defaults_tests()
self.convs = self.__class__.get_defaults_convs()
self.functional = functional
self.set_dens(spec)
self.sym_prec = sym_prec
def __init__(self, structure, spec, functional='PBE', sym_prec=0.01, **kwargs):
"""
Supports the same kwargs as :class:`JSONVaspInputSet`.
"""
with open(os.path.join(MODULE_DIR, "GWVaspInputSet.json")) as f:
DictVaspInputSet.__init__(
self, "MP Static Self consistent run for GW", json.load(f), **kwargs)
self.structure = structure
self.tests = self.__class__.get_defaults_tests()
self.convs = self.__class__.get_defaults_convs()
self.functional = functional
self.set_dens(spec)
self.sym_prec = sym_prec
def get_vasp_input_set(self, date_string=None):
"""
Returns the VaspInputSet used by the Materials Project at a
particular date.
Args:
date_string:
A date string in the format of "YYYY-MM-DD". Defaults to
None, which means the VaspInputSet today.
Returns:
DictVaspInputSet
"""
url = "{}/parameters/vasp".format(self.preamble)
payload = {"date": date_string} if date_string else {}
try:
response = self.session.get(url, data=payload)
if response.status_code in [200, 400]:
data = json.loads(response.text, cls=PMGJSONDecoder)
if data["valid_response"]:
if data.get("warning"):
warnings.warn(data["warning"])
return DictVaspInputSet("MPVaspInputSet", data["response"])
else:
raise MPRestError(data["error"])
raise MPRestError(
"REST query returned with error status code {}".format(
response.status_code))
except Exception as ex:
raise MPRestError(str(ex))
def __init__(self, structure, spec, functional='PBE', sym_prec=0.01, **kwargs):
"""
Supports the same kwargs as :class:`JSONVaspInputSet`.
"""
with open(GWVaspInputSet) as f:
DictVaspInputSet.__init__(
self, "MP Static exact diagonalization", json.load(f), **kwargs)
self.structure = structure
self.tests = self.__class__.get_defaults_tests()
self.convs = self.__class__.get_defaults_convs()
self.functional = functional
self.sym_prec = sym_prec
self.set_dens(spec)
npar = self.get_npar(self.structure)
#single step exact diagonalization, output WAVEDER
self.incar_settings.update({"ALGO": "Exact", "NELM": 1, "LOPTICS": "TRUE"})
# for large systems exact diagonalization consumes too much memory
self.set_gw_bands(15)
self.incar_settings.update({"NPAR": npar})
def __init__(self, structure, spec, functional='PBE', sym_prec=0.01, **kwargs):
"""
Supports the same kwargs as :class:`JSONVaspInputSet`.
"""
with open(os.path.join(MODULE_DIR, "GWVaspInputSet.json")) as f:
DictVaspInputSet.__init__(
self, "MP Static exact diagonalization", json.load(f), **kwargs)
self.structure = structure
self.tests = self.__class__.get_defaults_tests()
self.convs = self.__class__.get_defaults_convs()
self.functional = functional
self.sym_prec = sym_prec
self.set_dens(spec)
npar = self.get_npar(self.structure)
#single step exact diagonalization, output WAVEDER
self.incar_settings.update({"ALGO": "Exact", "NELM": 1, "LOPTICS": "TRUE"})
# for large systems exact diagonalization consumes too much memory
self.set_gw_bands(15)
self.incar_settings.update({"NPAR": npar})
def __init__(self, structure, spec, functional='PBE', sym_prec=0.01, **kwargs):
"""
Supports the same kwargs as :class:`JSONVaspInputSet`.
"""
with open(GWVaspInputSet) as f:
DictVaspInputSet.__init__(
self, "MP Static G0W0", json.load(f), **kwargs)
self.structure = structure
self.tests = self.__class__.get_defaults_tests()
self.convs = self.__class__.get_defaults_convs()
self.functional = functional
self.sym_prec = sym_prec
npar = self.get_npar(structure)
# G0W0 calculation with reduced cutoff for the response function
self.incar_settings.update({"ALGO": "GW0", "ENCUTGW": 250, "LWAVE": "FALSE", "NELM": 1})
self.set_dens(spec)
self.nomega_max = 2 * self.get_kpoints(structure).kpts[0][0]**3
nomega = npar * int(self.nomega_max / npar)
self.set_gw_bands(15)
self.incar_settings.update({"NPAR": npar})
self.incar_settings.update({"NOMEGA": nomega})
self.tests = self.__class__.get_defaults_tests()
def __init__(self, structure, spec, functional='PBE', sym_prec=0.01, **kwargs):
"""
Supports the same kwargs as :class:`JSONVaspInputSet`.
"""
with open(os.path.join(MODULE_DIR, "GWVaspInputSet.json")) as f:
DictVaspInputSet.__init__(
self, "MP Static G0W0", json.load(f), **kwargs)
self.structure = structure
self.tests = self.__class__.get_defaults_tests()
self.convs = self.__class__.get_defaults_convs()
self.functional = functional
self.sym_prec = sym_prec
npar = self.get_npar(structure)
# G0W0 calculation with reduced cutoff for the response function
self.incar_settings.update({"ALGO": "GW0", "ENCUTGW": 250, "LWAVE": "FALSE", "NELM": 1})
self.set_dens(spec)
self.nomega_max = 2 * self.get_kpoints(structure).kpts[0][0]**3
nomega = npar * int(self.nomega_max / npar)
self.set_gw_bands(15)
self.incar_settings.update({"NPAR": npar})
self.incar_settings.update({"NOMEGA": nomega})
self.tests = self.__class__.get_defaults_tests()
