def run_task(self, fw_spec):
struct = self.get("structure") or fw_spec["structure"]
s = Structure.from_dict(struct.as_dict())
user_incar_settings = fw_spec.get("user_incar_settings", {})
vasp_input_set = MPRelaxSet(s, user_incar_settings=user_incar_settings)
dec = MontyDecoder()
vis = dec.process_decoded(vasp_input_set.as_dict())
output_dir = os.getcwd()
vis.write_input(output_dir=output_dir)
return FWAction()
def wf_thermal_expansion(structure, c=None):
"""
Thermal expansion coefficient workflow from the given structure and config dict.
Args:
structure (Structure): input structure
c (dict): workflow config dict
Returns:
Workflow
"""
c = c or {}
eos = c.get("EOS", "vinet")
vasp_cmd = c.get("VASP_CMD", VASP_CMD)
db_file = c.get("DB_FILE", DB_FILE)
pressure = c.get("PRESSURE", 0.0)
user_kpoints_settings = {"grid_density": 7000}
# 10 deformations
deformations = [(np.identity(3) * (1 + x)).tolist() for x in np.linspace(-0.1, 0.1, 10)]
tag = "thermal_expansion group: >>{}<<".format(str(uuid4()))
# input set for structure optimization
vis_relax = MPRelaxSet(structure, force_gamma=True)
v = vis_relax.as_dict()
v.update({"user_kpoints_settings": user_kpoints_settings})
vis_relax = vis_relax.__class__.from_dict(v)
# optimization only workflow
wf = get_wf(structure, "optimize_only.yaml",
params=[{"vasp_cmd": vasp_cmd, "db_file": db_file,
"name": "{} structure optimization".format(tag)}],
vis=vis_relax)
wf_thermal = get_wf_thermal_expansion(structure, user_kpoints_settings=user_kpoints_settings,
deformations=deformations, vasp_cmd=vasp_cmd, db_file=db_file,
eos=eos, pressure=pressure, tag=tag)
# chain it
wf.append_wf(wf_thermal, wf.leaf_fw_ids)
wf = add_modify_incar(wf, modify_incar_params={"incar_update": {"ENCUT": 600, "EDIFF": 1e-6}})
wf = add_common_powerups(wf, c)
if c.get("ADD_WF_METADATA", ADD_WF_METADATA):
wf = add_wf_metadata(wf, structure)
return wf
def wf_bulk_modulus(structure, c=None):
"""
Bulk modulus workflow from the given structure and config dict.
Args:
structure (Structure): input structure
c (dict): workflow config dict
Returns:
Workflow
"""
c = c or {}
eos = c.get("EOS", "vinet")
vasp_cmd = c.get("VASP_CMD", VASP_CMD)
db_file = c.get("DB_FILE", DB_FILE)
user_kpoints_settings = {"grid_density": 7000}
# 6 deformations
deformations = [(np.identity(3) * (1 + x)).tolist()
for x in np.linspace(-0.05, 0.05, 6)]
tag = "bulk_modulus group: >>{}<<".format(str(uuid4()))
# input set for structure optimization
vis_relax = MPRelaxSet(structure, force_gamma=True)
v = vis_relax.as_dict()
v.update({"user_kpoints_settings": user_kpoints_settings})
vis_relax = vis_relax.__class__.from_dict(v)
# static input set for the transmute firework
uis_static = {"ISIF": 2, "ISTART": 1, "IBRION": 2, "NSW": 99}
# optimization only workflow
wf = get_wf(structure,
"optimize_only.yaml",
params=[{
"vasp_cmd": vasp_cmd,
"db_file": db_file,
"name": "{} structure optimization".format(tag)
}],
vis=vis_relax)
vis_static = MPStaticSet(structure,
force_gamma=True,
lepsilon=False,
user_kpoints_settings=user_kpoints_settings,
user_incar_settings=uis_static)
# get the deformations wflow for bulk modulus calculation
wf_bm = get_wf_bulk_modulus(structure,
eos=eos,
user_kpoints_settings=user_kpoints_settings,
deformations=deformations,
vasp_cmd=vasp_cmd,
db_file=db_file,
tag=tag,
vasp_input_set=vis_static)
# chain it
wf.append_wf(wf_bm, wf.leaf_fw_ids)
wf = add_modify_incar(
wf,
modify_incar_params={"incar_update": {
"ENCUT": 600,
"EDIFF": 1e-6
}})
wf = add_common_powerups(wf, c)
if c.get("ADD_WF_METADATA", ADD_WF_METADATA):
wf = add_wf_metadata(wf, structure)
return wf
def wf_gibbs_free_energy(structure, c=None):
"""
Gibbs free energy workflow from the given structure and config dict.
Args:
structure (Structure): input structure
c (dict): workflow config dict
Returns:
Workflow
"""
c = c or {}
vasp_cmd = c.get("VASP_CMD", VASP_CMD)
db_file = c.get("DB_FILE", DB_FILE)
eos = c.get("EOS", "vinet")
qha_type = c.get("QHA_TYPE", "debye_model")
# min and max temp in K, default setting is to compute the properties at 300K only
t_min = c.get("T_MIN", 300.0)
t_max = c.get("T_MAX", 300.0)
t_step = c.get("T_STEP", 100.0)
pressure = c.get("PRESSURE", 0.0)
poisson = c.get("POISSON", 0.25)
anharmonic_contribution = c.get("ANHARMONIC_CONTRIBUTION", False)
metadata = c.get("METADATA", None)
# 21 deformed structures: from -10% to +10%
defos = [(np.identity(3) * (1 + x)).tolist()
for x in np.linspace(-0.1, 0.1, 21)]
deformations = c.get("DEFORMATIONS", defos)
user_kpoints_settings = {"grid_density": 7000}
tag = "gibbs group: >>{}<<".format(str(uuid4()))
# input set for structure optimization
vis_relax = MPRelaxSet(structure, force_gamma=True)
v = vis_relax.as_dict()
v.update({"user_kpoints_settings": user_kpoints_settings})
vis_relax = vis_relax.__class__.from_dict(v)
# optimization only workflow
wf = get_wf(structure,
"optimize_only.yaml",
params=[{
"vasp_cmd": vasp_cmd,
"db_file": db_file,
"name": "{} structure optimization".format(tag)
}],
vis=vis_relax)
# static input set for the transmute firework
uis_static = {
"ISIF": 2,
"ISTART": 1,
}
lepsilon = False
if qha_type not in ["debye_model"]:
lepsilon = True
try:
from phonopy import Phonopy
except ImportError:
raise RuntimeError(
"'phonopy' package is NOT installed but is required for the final "
"analysis step; you can alternatively switch to the qha_type to "
"'debye_model' which does not require 'phonopy'.")
vis_static = MPStaticSet(structure,
force_gamma=True,
lepsilon=lepsilon,
user_kpoints_settings=user_kpoints_settings,
user_incar_settings=uis_static)
# get gibbs workflow and chain it to the optimization workflow
wf_gibbs = get_wf_gibbs_free_energy(
structure,
user_kpoints_settings=user_kpoints_settings,
deformations=deformations,
vasp_cmd=vasp_cmd,
db_file=db_file,
eos=eos,
qha_type=qha_type,
pressure=pressure,
poisson=poisson,
t_min=t_min,
t_max=t_max,
t_step=t_step,
metadata=metadata,
anharmonic_contribution=anharmonic_contribution,
tag=tag,
vasp_input_set=vis_static)
# chaining
wf.append_wf(wf_gibbs, wf.leaf_fw_ids)
wf = add_modify_incar(wf,
modify_incar_params={
"incar_update": {
"ENCUT": 600,
"EDIFF": 1e-6,
"LAECHG": False
}
})
wf = add_common_powerups(wf, c)
if c.get("ADD_WF_METADATA", ADD_WF_METADATA):
wf = add_wf_metadata(wf, structure)
return wf
