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)
user_kpoints_settings = c.get("user_kpoints_settings", {"grid_density": 7000})
deformations = c.get("deformations", [(np.identity(3)*(1+x)).tolist()
for x in np.linspace(-0.1, 0.1, 10)])
pressure = c.get("pressure", 0.0)
wf = 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)
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 test_modify_incar(self):
my_wf = add_modify_incar(self._copy_wf(self.bs_wf), {"incar_update": {"NCORE": 1}},
fw_name_constraint="structure optimization")
for fw in my_wf.fws:
if "structure optimization" in fw.name:
self.assertTrue("ModifyIncar" in fw.to_dict()["spec"]["_tasks"][1]["_fw_name"])
self.assertEqual(fw.to_dict()["spec"]["_tasks"][1]["incar_update"], {"NCORE": 1})
else:
for t in fw.to_dict()["spec"]["_tasks"]:
self.assertFalse("ModifyIncar" in t["_fw_name"])
def setUp(self):
super(TestElasticWorkflow, self).setUp()
self.tf_loc = os.path.join(ref_dir, 'elastic_wf')
self.struct_si = PymatgenTest.get_structure("Si")
self.struct_si = SpacegroupAnalyzer(self.struct_si).get_conventional_standard_structure()
self.opt_struct = Structure.from_file(os.path.join(self.tf_loc, '1', 'inputs', 'POSCAR'))
# Base WF
self.base_wf = get_wf(self.struct_si, "optimize_only.yaml",
params=[{"db_file": ">>db_file<<"}])
self.base_wf.append_wf(get_wf_elastic_constant(self.struct_si, db_file='>>db_file<<',
stencils=[[0.01]]*3 + [[0.03]]*3,
copy_vasp_outputs=True),
self.base_wf.leaf_fw_ids)
self.base_wf_noopt = get_wf_elastic_constant(self.opt_struct, stencils=[[0.01]]*3 + [[0.03]]*3,
copy_vasp_outputs=False, sym_reduce=False,
db_file='>>db_file<<')
ec_incar_update = {'incar_update': {'EDIFF': 1e-6, 'ENCUT': 700}}
self.base_wf = add_modify_incar(self.base_wf, ec_incar_update)
self.base_wf_noopt = add_modify_incar(self.base_wf_noopt, ec_incar_update)
# Full preset WF
self.preset_wf = wf_elastic_constant(self.struct_si)
# Minimal WF
self.minimal_wf = wf_elastic_constant_minimal(self.opt_struct)
self.minimal_wf = add_modify_incar(self.minimal_wf, ec_incar_update)
# TOEC WF (minimal)
self.toec_wf = wf_elastic_constant_minimal(self.struct_si, order=3)
self.toec_wf = add_modify_incar(self.toec_wf, ec_incar_update)
toec_data = loadfn(os.path.join(self.tf_loc, 'toec_data.json'))
# Rather than run entire workflow, preload the spec to test the analysis
toec_analysis = Firework([ElasticTensorToDb(structure=self.struct_si, order=3,
db_file=">>db_file<<")],
spec={"deformation_tasks": toec_data['deformation_tasks']})
self.toec_analysis = Workflow([toec_analysis])
# Check 4th order to see if constructed correctly
self.foec_wf = wf_elastic_constant_minimal(self.struct_si, order=4)
def wf_piezoelectric_constant(structure, c=None):
c = c or {}
wf = wf_dielectric_constant(structure, c)
wf = add_modify_incar(wf, modify_incar_params={"incar_update": {"ENCUT": 1000,
"ADDGRID": True,
"LREAL": False,
"EDIFF": 1e-7}
},
fw_name_constraint="static dielectric")
for fw in wf.fws:
fw.name = fw.name.replace("dielectric", "piezoelectric")
if c.get("ADD_WF_METADATA", ADD_WF_METADATA):
wf = add_wf_metadata(wf, structure)
return wf
def wf_elastic_constant(structure, c=None):
c = c or {}
vasp_cmd = c.get("VASP_CMD", VASP_CMD)
db_file = c.get("DB_FILE", DB_FILE)
user_kpoints_settings = c.get("user_kpoints_settings", {"grid_density": 7000})
norm_deformations = c.get("norm_deformations", [-0.01, -0.005, 0.005, 0.01])
shear_deformations = c.get("shear_deformations", [-0.06, -0.03, 0.03, 0.06])
wf = get_wf_elastic_constant(structure, vasp_cmd=vasp_cmd,
norm_deformations=norm_deformations,
shear_deformations=shear_deformations,
db_file=db_file, user_kpoints_settings=user_kpoints_settings)
mip = {"incar_update":{"ENCUT": 700, "EDIFF": 1e-6, "LAECHG":False}}
wf = add_modify_incar(wf, modify_incar_params=mip)
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_raman_spectra(structure, c=None):
"""
Raman spectra workflow from the given structure and config dict
Args:
structure (Structure): input structure
c (dict): workflow config dict
Returns:
Workflow
"""
c = c or {}
wf = get_wf_raman_spectra(structure, modes=c.get("modes", None), step_size=c.get("step_size", 0.005),
vasp_cmd=c.get("vasp_cmd", "vasp"), db_file=c.get("db_file", None))
wf = add_modify_incar(wf, modify_incar_params={"incar_update": {"ENCUT": 600, "EDIFF": 1e-6}},
fw_name_constraint="static dielectric")
if c.get("ADD_WF_METADATA", ADD_WF_METADATA):
wf = add_wf_metadata(wf, structure)
return wf
structure.replace_species({'O': 'N', 'N': 'O'})
structure.replace_species({
default_B: composition[1]
}) #this will break if B-site is default_a but that shouldn't happen
structure.replace_species({default_A: composition[0]})
poscar_key = tetra_dict[tilt_count]
opt = OptimizeFW(structure, vasp_cmd='ibrun tacc_affinity vasp_std')
stat = StaticFW(parents=opt, vasp_cmd='ibrun tacc_affinity vasp_std')
wf = Workflow([opt, stat])
wf = add_modify_incar(wf,
modify_incar_params={
'incar_update': {
'KPAR': 2,
'NCORE': 4,
'NSIM': 8,
'EDIFF': 0.000002,
'LMAXMIX': 6,
'LSCALAPACK': '.FALSE.',
'ALGO': 'All'
}
})
wf = add_modify_incar(wf,
modify_incar_params={
'incar_update': {
'AMIX': 0.2,
'AMIX_MAG': 0.8,
'BMIX': 0.00001,
'BMIX_MAG': 0.00001,
'ICHARG': 2,
'EDIFFG': 0.0005 * site_num,
'KPAR': 1
def add_modify_incar_by_FWname(wf, modify_incar_params):
from atomate.vasp.powerups import add_modify_incar
for keyword in modify_incar_params.keys():
add_modify_incar(wf, modify_incar_params = modify_incar_params[keyword], fw_name_constraint = keyword)
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
