def make_supercell(
cell_structure: pmg.Structure,
scaling_matrix: Optional[ScalingMatrix] = None,
scaling_factors: Optional[Tuple[int, int, int]] = None,
) -> pmg.Structure:
"""Transforms a pymatgen ``Structure`` object into a supercell according to the
scaling parameters.
:param cell_structure: A pymatgen ``Structure`` object.
:param scaling_matrix: A matrix of transforming the lattice vectors. Has to be all
integers. e.g., [[2,1,0],[0,3,0],[0,0,1]] generates a new structure with lattice
vectors a" = 2a + b, b" = 3b, c" = c where a, b, and c are the lattice vectors
of the original structure.
:param scaling_factors: A tuple of three numbers used to scale each lattice vector.
Same as: ``scaling_matrix=[[scale_a, 0, 0], [0, scale_b, 0], [0, 0, scale_c]]``
:return: A pymatgen ``Structure`` object.
"""
if scaling_matrix is not None:
cell_transformation: SupercellTransformation = SupercellTransformation(
scaling_matrix=scaling_matrix)
return cell_transformation.apply_transformation(cell_structure)
elif scaling_factors is not None:
cell_transformation = SupercellTransformation.from_scaling_factors(
scale_a=scaling_factors[0],
scale_b=scaling_factors[1],
scale_c=scaling_factors[2],
)
return cell_transformation.apply_transformation(cell_structure)
else:
return cell_structure
def planar_structure_normalization(structure):
'''
This function does the following:
1. check whether the structure is planar using coordniates standard deviation
2. move the planar layer to the center of c-direction
Args:
structure: pymatgen structure
Return:
a boolean whether the structure is planar
tranformed pymatgen structure
'''
tol = 1E-3 # tolerance to check whether the structure is planar
is_planar = True
coords = structure.frac_coords
ts = TransformedStructure(structure, [])
if np.std(coords[:,2]) < tol :
center_translate = 0.5 - coords[:,2].mean()
elif np.std(coords[:,0]) < tol :
ts.append_transformation(SupercellTransformation([[0,0,1],[0,1,0],[1,0,0]]))
ts.append_transformation(RotationTransformation([0,1,0], 90))
center_translate = 0.5 - coords[:,0].mean()
elif np.std(coords[:,1]) < tol :
ts.append_transformation(SupercellTransformation([[1,0,0],[0,0,1],[0,1,0]]))
ts.append_transformation(RotationTransformation([1,0,0], 90))
center_translate = 0.5 - coords[:,1].mean()
else :
is_planar = False
transformed_structure = None
if is_planar:
ts.append_transformation(TranslateSitesTransformation(
list(range(len(structure))), [0,0,center_translate]))
# Use pymatgen 2019.7.2, ts.structures[-1] may change in a newer version
transformed_structure = ts.structures[-1]
return is_planar, transformed_structure
def abi_sanitize(self, symprec=1e-3, primitive=True):
"""
Returns a new structure in which:
* Oxidation states are removed.
* Structure is refined.
* Reduced to primitive settings.
* Lattice vectors are exchanged if the triple product is negative
Args:
symprec: Symmetry precision used to refine the structure.
if `symprec` is None, so structure refinement is peformed.
primitive (bool): Whether to convert to a primitive cell.
"""
from pymatgen.transformations.standard_transformations import OxidationStateRemovalTransformation, \
PrimitiveCellTransformation, SupercellTransformation
# Remove oxidation states.
remove_ox = OxidationStateRemovalTransformation()
structure = remove_ox.apply_transformation(self)
# Refine structure
if symprec is not None:
sym_finder = SpacegroupAnalyzer(structure=structure,
symprec=symprec)
structure = sym_finder.get_refined_structure()
# Convert to primitive structure.
if primitive:
get_prim = PrimitiveCellTransformation()
structure = get_prim.apply_transformation(structure)
# Exchange last two lattice vectors if triple product is negative.
m = structure.lattice.matrix
x_prod = np.dot(np.cross(m[0], m[1]), m[2])
if x_prod < 0:
trans = SupercellTransformation(((1, 0, 0), (0, 0, 1), (0, 1, 0)))
structure = trans.apply_transformation(structure)
m = structure.lattice.matrix
x_prod = np.dot(np.cross(m[0], m[1]), m[2])
if x_prod < 0: raise RuntimeError("x_prod is still negative!")
return structure
def refine_structure(structure, symprec=1e-3):
remove_ox = OxidationStateRemovalTransformation()
structure = remove_ox.apply_transformation(structure)
sym_finder = SpacegroupAnalyzer(structure=structure, symprec=symprec)
structure = sym_finder.get_refined_structure()
get_prim = PrimitiveCellTransformation()
structure = get_prim.apply_transformation(structure)
m = structure.lattice.matrix
x_prod = np.dot(np.cross(m[0], m[1]), m[2])
if x_prod < 0:
print(x_prod)
trans = SupercellTransformation(((1, 0, 0), (0, 0, 1), (0, 1, 0)))
structure = trans.apply_transformation(structure)
m = structure.lattice.matrix
x_prod = np.dot(np.cross(m[0], m[1]), m[2])
print(x_prod)
if x_prod < 0:
raise RuntimeError
return structure
def correct(self):
backup(VASP_BACKUP_FILES | {self.output_filename})
actions = []
vi = VaspInput.from_directory(".")
if self.errors.intersection(["tet", "dentet"]):
actions.append({"dict": "INCAR",
"action": {"_set": {"ISMEAR": 0}}})
if "inv_rot_mat" in self.errors:
actions.append({"dict": "INCAR",
"action": {"_set": {"SYMPREC": 1e-8}}})
if "brmix" in self.errors:
# If there is not a valid OUTCAR already, increment
# error count to 1 to skip first fix
if self.error_count['brmix'] == 0:
try:
assert (Outcar(zpath(os.path.join(
os.getcwd(), "OUTCAR"))).is_stopped is False)
except:
self.error_count['brmix'] += 1
if self.error_count['brmix'] == 0:
# Valid OUTCAR - simply rerun the job and increment
# error count for next time
actions.append({"dict": "INCAR",
"action": {"_set": {"ISTART": 1}}})
self.error_count['brmix'] += 1
elif self.error_count['brmix'] == 1:
# Use Kerker mixing w/default values for other parameters
actions.append({"dict": "INCAR",
"action": {"_set": {"IMIX": 1}}})
self.error_count['brmix'] += 1
elif self.error_count['brmix'] == 2 and vi["KPOINTS"].style \
== Kpoints.supported_modes.Gamma:
actions.append({"dict": "KPOINTS",
"action": {"_set": {"generation_style":
"Monkhorst"}}})
actions.append({"dict": "INCAR",
"action": {"_unset": {"IMIX": 1}}})
self.error_count['brmix'] += 1
elif self.error_count['brmix'] in [2, 3] and vi["KPOINTS"].style \
== Kpoints.supported_modes.Monkhorst:
actions.append({"dict": "KPOINTS",
"action": {"_set": {"generation_style":
"Gamma"}}})
actions.append({"dict": "INCAR",
"action": {"_unset": {"IMIX": 1}}})
self.error_count['brmix'] += 1
if vi["KPOINTS"].num_kpts < 1:
all_kpts_even = all([
bool(n % 2 == 0) for n in vi["KPOINTS"].kpts[0]
])
print("all_kpts_even = {}".format(all_kpts_even))
if all_kpts_even:
new_kpts = (
tuple(n + 1 for n in vi["KPOINTS"].kpts[0]),)
print("new_kpts = {}".format(new_kpts))
actions.append({"dict": "KPOINTS", "action": {"_set": {
"kpoints": new_kpts
}}})
else:
actions.append({"dict": "INCAR",
"action": {"_set": {"ISYM": 0}}})
if vi["KPOINTS"].style == Kpoints.supported_modes.Monkhorst:
actions.append({"dict": "KPOINTS",
"action": {
"_set": {"generation_style": "Gamma"}}})
# Based on VASP forum's recommendation, you should delete the
# CHGCAR and WAVECAR when dealing with this error.
if vi["INCAR"].get("ICHARG", 0) < 10:
actions.append({"file": "CHGCAR",
"action": {
"_file_delete": {'mode': "actual"}}})
actions.append({"file": "WAVECAR",
"action": {
"_file_delete": {'mode': "actual"}}})
if "zpotrf" in self.errors:
# Usually caused by short bond distances. If on the first step,
# volume needs to be increased. Otherwise, it was due to a step
# being too big and POTIM should be decreased. If a static run
# try turning off symmetry.
try:
oszicar = Oszicar("OSZICAR")
nsteps = len(oszicar.ionic_steps)
except:
nsteps = 0
if nsteps >= 1:
potim = float(vi["INCAR"].get("POTIM", 0.5)) / 2.0
actions.append(
{"dict": "INCAR",
"action": {"_set": {"ISYM": 0, "POTIM": potim}}})
elif vi["INCAR"].get("NSW", 0) == 0 \
or vi["INCAR"].get("ISIF", 0) in range(3):
actions.append(
{"dict": "INCAR", "action": {"_set": {"ISYM": 0}}})
else:
s = vi["POSCAR"].structure
s.apply_strain(0.2)
actions.append({"dict": "POSCAR",
"action": {"_set": {"structure": s.as_dict()}}})
# Based on VASP forum's recommendation, you should delete the
# CHGCAR and WAVECAR when dealing with this error.
if vi["INCAR"].get("ICHARG", 0) < 10:
actions.append({"file": "CHGCAR",
"action": {"_file_delete": {'mode': "actual"}}})
actions.append({"file": "WAVECAR",
"action": {"_file_delete": {'mode': "actual"}}})
if self.errors.intersection(["subspacematrix", "rspher",
"real_optlay", "nicht_konv"]):
s = vi["POSCAR"].structure
if len(s) < self.natoms_large_cell:
actions.append({"dict": "INCAR",
"action": {"_set": {"LREAL": False}}})
else:
# for large supercell, try an in-between option LREAL = True
# prior to LREAL = False
if self.error_count['real_optlay'] == 0:
# use real space projectors generated by pot
actions.append({"dict": "INCAR",
"action": {"_set": {"LREAL": True}}})
self.error_count['real_optlay'] += 1
elif self.error_count['real_optlay'] == 1:
actions.append({"dict": "INCAR",
"action": {"_set": {"LREAL": False}}})
self.error_count['real_optlay'] += 1
if self.errors.intersection(["tetirr", "incorrect_shift"]):
if vi["KPOINTS"].style == Kpoints.supported_modes.Monkhorst:
actions.append({"dict": "KPOINTS",
"action": {
"_set": {"generation_style": "Gamma"}}})
if "rot_matrix" in self.errors:
if vi["KPOINTS"].style == Kpoints.supported_modes.Monkhorst:
actions.append({"dict": "KPOINTS",
"action": {
"_set": {"generation_style": "Gamma"}}})
else:
actions.append({"dict": "INCAR",
"action": {"_set": {"ISYM": 0}}})
if "amin" in self.errors:
actions.append({"dict": "INCAR",
"action": {"_set": {"AMIN": "0.01"}}})
if "triple_product" in self.errors:
s = vi["POSCAR"].structure
trans = SupercellTransformation(((1, 0, 0), (0, 0, 1), (0, 1, 0)))
new_s = trans.apply_transformation(s)
actions.append({"dict": "POSCAR",
"action": {"_set": {"structure": new_s.as_dict()}},
"transformation": trans.as_dict()})
if "pricel" in self.errors:
actions.append({"dict": "INCAR",
"action": {"_set": {"SYMPREC": 1e-8, "ISYM": 0}}})
if "brions" in self.errors:
potim = float(vi["INCAR"].get("POTIM", 0.5)) + 0.1
actions.append({"dict": "INCAR",
"action": {"_set": {"POTIM": potim}}})
if "zbrent" in self.errors:
actions.append({"dict": "INCAR",
"action": {"_set": {"IBRION": 1}}})
actions.append({"file": "CONTCAR",
"action": {"_file_copy": {"dest": "POSCAR"}}})
if "too_few_bands" in self.errors:
if "NBANDS" in vi["INCAR"]:
nbands = int(vi["INCAR"]["NBANDS"])
else:
with open("OUTCAR") as f:
for line in f:
if "NBANDS" in line:
try:
d = line.split("=")
nbands = int(d[-1].strip())
break
except (IndexError, ValueError):
pass
actions.append({"dict": "INCAR",
"action": {"_set": {"NBANDS": int(1.1 * nbands)}}})
if "pssyevx" in self.errors:
actions.append({"dict": "INCAR", "action":
{"_set": {"ALGO": "Normal"}}})
if "eddrmm" in self.errors:
# RMM algorithm is not stable for this calculation
if vi["INCAR"].get("ALGO", "Normal") in ["Fast", "VeryFast"]:
actions.append({"dict": "INCAR", "action":
{"_set": {"ALGO": "Normal"}}})
else:
potim = float(vi["INCAR"].get("POTIM", 0.5)) / 2.0
actions.append({"dict": "INCAR",
"action": {"_set": {"POTIM": potim}}})
if vi["INCAR"].get("ICHARG", 0) < 10:
actions.append({"file": "CHGCAR",
"action": {"_file_delete": {'mode': "actual"}}})
actions.append({"file": "WAVECAR",
"action": {"_file_delete": {'mode': "actual"}}})
if "edddav" in self.errors:
if vi["INCAR"].get("ICHARG", 0) < 10:
actions.append({"file": "CHGCAR",
"action": {"_file_delete": {'mode': "actual"}}})
actions.append({"dict": "INCAR", "action":
{"_set": {"ALGO": "All"}}})
if "grad_not_orth" in self.errors:
if vi["INCAR"].get("ISMEAR", 1) < 0:
actions.append({"dict": "INCAR",
"action": {"_set": {"ISMEAR": "0"}}})
if "zheev" in self.errors:
if vi["INCAR"].get("ALGO", "Fast").lower() != "exact":
actions.append({"dict": "INCAR",
"action": {"_set": {"ALGO": "Exact"}}})
if "elf_kpar" in self.errors:
actions.append({"dict": "INCAR",
"action": {"_set": {"KPAR": 1}}})
if "rhosyg" in self.errors:
if vi["INCAR"].get("SYMPREC", 1e-4) == 1e-4:
actions.append({"dict": "INCAR",
"action": {"_set": {"ISYM": 0}}})
actions.append({"dict": "INCAR",
"action": {"_set": {"SYMPREC": 1e-4}}})
if "posmap" in self.errors:
actions.append({"dict": "INCAR",
"action": {"_set": {"SYMPREC": 1e-6}}})
VaspModder(vi=vi).apply_actions(actions)
return {"errors": list(self.errors), "actions": actions}
def correct(self):
backup(VASP_BACKUP_FILES | {self.output_filename})
actions = []
vi = VaspInput.from_directory(".")
if self.errors.intersection(["tet", "dentet"]):
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ISMEAR": 0
}
}
})
if "inv_rot_mat" in self.errors:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"SYMPREC": 1e-8
}
}
})
if "brmix" in self.errors:
if self.error_count['brmix'] == 0 and vi[
"KPOINTS"].style == Kpoints.supported_modes.Gamma:
actions.append({
"dict": "KPOINTS",
"action": {
"_set": {
"generation_style": "Monkhorst"
}
}
})
self.error_count['brmix'] += 1
elif self.error_count['brmix'] <= 1 and vi[
"KPOINTS"].style == Kpoints.supported_modes.Monkhorst:
actions.append({
"dict": "KPOINTS",
"action": {
"_set": {
"generation_style": "Gamma"
}
}
})
self.error_count['brmix'] += 1
if vi["KPOINTS"].num_kpts < 1:
all_kpts_even = all(
[bool(n % 2 == 0) for n in vi["KPOINTS"].kpts[0]])
print("all_kpts_even = {}".format(all_kpts_even))
if all_kpts_even:
new_kpts = (tuple(n + 1
for n in vi["KPOINTS"].kpts[0]), )
print("new_kpts = {}".format(new_kpts))
actions.append({
"dict": "KPOINTS",
"action": {
"_set": {
"kpoints": new_kpts
}
}
})
else:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ISYM": 0
}
}
})
if vi["KPOINTS"].style == Kpoints.supported_modes.Monkhorst:
actions.append({
"dict": "KPOINTS",
"action": {
"_set": {
"generation_style": "Gamma"
}
}
})
# Based on VASP forum's recommendation, you should delete the
# CHGCAR and WAVECAR when dealing with this error.
actions.append({
"file": "CHGCAR",
"action": {
"_file_delete": {
'mode': "actual"
}
}
})
actions.append({
"file": "WAVECAR",
"action": {
"_file_delete": {
'mode': "actual"
}
}
})
if "zpotrf" in self.errors:
# Usually caused by short bond distances. If on the first step,
# volume needs to be increased. Otherwise, it was due to a step
# being too big and POTIM should be decreased.
try:
oszicar = Oszicar("OSZICAR")
nsteps = len(oszicar.ionic_steps)
except:
nsteps = 0
if nsteps >= 1:
potim = float(vi["INCAR"].get("POTIM", 0.5)) / 2.0
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ISYM": 0,
"POTIM": potim
}
}
})
else:
s = vi["POSCAR"].structure
s.apply_strain(0.2)
actions.append({
"dict": "POSCAR",
"action": {
"_set": {
"structure": s.as_dict()
}
}
})
# Based on VASP forum's recommendation, you should delete the
# CHGCAR and WAVECAR when dealing with this error.
actions.append({
"file": "CHGCAR",
"action": {
"_file_delete": {
'mode': "actual"
}
}
})
actions.append({
"file": "WAVECAR",
"action": {
"_file_delete": {
'mode': "actual"
}
}
})
if self.errors.intersection(
["subspacematrix", "rspher", "real_optlay"]):
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"LREAL": False
}
}
})
if self.errors.intersection(["tetirr", "incorrect_shift"]):
if vi["KPOINTS"].style == Kpoints.supported_modes.Monkhorst:
actions.append({
"dict": "KPOINTS",
"action": {
"_set": {
"generation_style": "Gamma"
}
}
})
if "rot_matrix" in self.errors:
if vi["KPOINTS"].style == Kpoints.supported_modes.Monkhorst:
actions.append({
"dict": "KPOINTS",
"action": {
"_set": {
"generation_style": "Gamma"
}
}
})
else:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ISYM": 0
}
}
})
if "amin" in self.errors:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"AMIN": "0.01"
}
}
})
if "triple_product" in self.errors:
s = vi["POSCAR"].structure
trans = SupercellTransformation(((1, 0, 0), (0, 0, 1), (0, 1, 0)))
new_s = trans.apply_transformation(s)
actions.append({
"dict": "POSCAR",
"action": {
"_set": {
"structure": new_s.as_dict()
}
},
"transformation": trans.as_dict()
})
if "pricel" in self.errors:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"SYMPREC": 1e-8,
"ISYM": 0
}
}
})
if "brions" in self.errors:
potim = float(vi["INCAR"].get("POTIM", 0.5)) + 0.1
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"POTIM": potim
}
}
})
if "zbrent" in self.errors:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"IBRION": 1
}
}
})
if "too_few_bands" in self.errors:
if "NBANDS" in vi["INCAR"]:
nbands = int(vi["INCAR"]["NBANDS"])
else:
with open("OUTCAR") as f:
for line in f:
if "NBANDS" in line:
try:
d = line.split("=")
nbands = int(d[-1].strip())
break
except (IndexError, ValueError):
pass
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"NBANDS": int(1.1 * nbands)
}
}
})
if "pssyevx" in self.errors:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ALGO": "Normal"
}
}
})
if "eddrmm" in self.errors:
#RMM algorithm is not stable for this calculation
if vi["INCAR"].get("ALGO", "Normal") in ["Fast", "VeryFast"]:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ALGO": "Normal"
}
}
})
else:
potim = float(vi["INCAR"].get("POTIM", 0.5)) / 2.0
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"POTIM": potim
}
}
})
actions.append({
"file": "CHGCAR",
"action": {
"_file_delete": {
'mode': "actual"
}
}
})
actions.append({
"file": "WAVECAR",
"action": {
"_file_delete": {
'mode': "actual"
}
}
})
if "edddav" in self.errors:
actions.append({
"file": "CHGCAR",
"action": {
"_file_delete": {
'mode': "actual"
}
}
})
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ALGO": "All"
}
}
})
VaspModder(vi=vi).apply_actions(actions)
return {"errors": list(self.errors), "actions": actions}
def test_apply_transformation(self):
t = SupercellTransformation([[2, 1, 0], [0, 2, 0], [1, 0, 2]])
s = t.apply_transformation(self.struct)
self.assertEqual(s.composition.formula, "Li16 O16")
def correct(self):
backup(orig_handlers.VASP_BACKUP_FILES | {self.output_filename})
actions = []
vi = VaspInput.from_directory(".")
if self.errors.intersection(["tet", "dentet"]):
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ISMEAR": 0
}
}
})
if "inv_rot_mat" in self.errors:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"SYMPREC": 1e-8
}
}
})
# ----- added ---------------------------------------------------
if "plane_wave_coeff" in self.errors:
actions.append({
"file": "WAVECAR",
"action": {
"_file_delete": {
'mode': "actual"
}
}
})
actions.append({
"file": "CHGCAR",
"action": {
"_file_delete": {
'mode': "actual"
}
}
})
# ---------------------------------------------------------------
if "zpotrf" in self.errors:
# Usually caused by short bond distances. If on the first step,
# volume needs to be increased. Otherwise, it was due to a step
# being too big and POTIM should be decreased. If a static run
# try turning off symmetry.
try:
oszicar = Oszicar("OSZICAR")
nsteps = len(oszicar.ionic_steps)
except:
nsteps = 0
if nsteps >= 1:
potim = float(vi["INCAR"].get("POTIM", 0.5)) / 2.0
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ISYM": 0,
"POTIM": potim
}
}
})
elif vi["INCAR"].get("NSW", 0) == 0 \
or vi["INCAR"].get("ISIF", 0) in range(3):
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ISYM": 0
}
}
})
else:
s = vi["POSCAR"].structure
s.apply_strain(0.2)
actions.append({
"dict": "POSCAR",
"action": {
"_set": {
"structure": s.as_dict()
}
}
})
# Based on VASP forum's recommendation, you should delete the
# CHGCAR and WAVECAR when dealing with this error.
if vi["INCAR"].get("ICHARG", 0) < 10:
actions.append({
"file": "CHGCAR",
"action": {
"_file_delete": {
'mode': "actual"
}
}
})
actions.append({
"file": "WAVECAR",
"action": {
"_file_delete": {
'mode': "actual"
}
}
})
if self.errors.intersection(["subspacematrix"]):
if self.error_count["subspacematrix"] == 0:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"LREAL": False
}
}
})
else:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"PREC": "Accurate"
}
}
})
self.error_count["subspacematrix"] += 1
if self.errors.intersection(["rspher", "real_optlay", "nicht_konv"]):
s = vi["POSCAR"].structure
if len(s) < self.natoms_large_cell:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"LREAL": False
}
}
})
else:
# for large supercell, try an in-between option LREAL = True
# prior to LREAL = False
if self.error_count['real_optlay'] == 0:
# use real space projectors generated by pot
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"LREAL": True
}
}
})
elif self.error_count['real_optlay'] == 1:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"LREAL": False
}
}
})
self.error_count['real_optlay'] += 1
if self.errors.intersection(["tetirr", "incorrect_shift"]):
# --Modified------------------------------------------------------
if vi["KPOINTS"].style == Kpoints.supported_modes.Monkhorst or \
vi["KPOINTS"].kpts_shift != [0.0, 0.0, 0.0]:
actions.append({
"dict": "KPOINTS",
"action": {
"_set": {
"generation_style": "Gamma",
"usershift": [0.0, 0.0, 0.0]
}
}
})
# -----------------------------------------------------------
if "rot_matrix" in self.errors:
# --Modified------------------------------------------------------
if vi["KPOINTS"].style == Kpoints.supported_modes.Monkhorst or \
vi["KPOINTS"].kpts_shift != [0.0, 0.0, 0.0]:
actions.append({
"dict": "KPOINTS",
"action": {
"_set": {
"generation_style": "Gamma",
"usershift": [0.0, 0.0, 0.0]
}
}
})
# -----------------------------------------------------------
else:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ISYM": 0
}
}
})
if "amin" in self.errors:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"AMIN": "0.01"
}
}
})
if "triple_product" in self.errors:
s = vi["POSCAR"].structure
trans = SupercellTransformation(((1, 0, 0), (0, 0, 1), (0, 1, 0)))
new_s = trans.apply_transformation(s)
actions.append({
"dict": "POSCAR",
"action": {
"_set": {
"structure": new_s.as_dict()
}
},
"transformation": trans.as_dict()
})
if "pricel" in self.errors:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"SYMPREC": 1e-8,
"ISYM": 0
}
}
})
if "brions" in self.errors:
potim = float(vi["INCAR"].get("POTIM", 0.5)) + 0.1
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"POTIM": potim
}
}
})
if "zbrent" in self.errors:
# Modified so as not to use IBRION=1 as it does not show the
# eigenvalues in vasprun.xml >>>>>>>>>>>>
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ADDGRID": True
}
}
})
actions.append({
"file": "CONTCAR",
"action": {
"_file_copy": {
"dest": "POSCAR"
}
}
})
# actions.append({"dict": "INCAR",
# "action": {"_set": {"IBRION": 1}}})
# actions.append({"file": "CONTCAR",
# "action": {"_file_copy": {"dest": "POSCAR"}}})
# <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<
if "too_few_bands" in self.errors:
if "NBANDS" in vi["INCAR"]:
nbands = int(vi["INCAR"]["NBANDS"])
else:
with open("OUTCAR") as f:
for line in f:
if "NBANDS" in line:
try:
d = line.split("=")
nbands = int(d[-1].strip())
break
except (IndexError, ValueError):
pass
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"NBANDS": int(1.1 * nbands)
}
}
})
if "pssyevx" in self.errors:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ALGO": "Normal"
}
}
})
if "eddrmm" in self.errors:
# RMM algorithm is not stable for this calculation
if vi["INCAR"].get("ALGO", "Normal") in ["Fast", "VeryFast"]:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ALGO": "Normal"
}
}
})
else:
potim = float(vi["INCAR"].get("POTIM", 0.5)) / 2.0
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"POTIM": potim
}
}
})
if vi["INCAR"].get("ICHARG", 0) < 10:
actions.append({
"file": "CHGCAR",
"action": {
"_file_delete": {
'mode': "actual"
}
}
})
actions.append({
"file": "WAVECAR",
"action": {
"_file_delete": {
'mode': "actual"
}
}
})
if "edddav" in self.errors:
if vi["INCAR"].get("ICHARG", 0) < 10:
actions.append({
"file": "CHGCAR",
"action": {
"_file_delete": {
'mode': "actual"
}
}
})
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ALGO": "All"
}
}
})
if "grad_not_orth" in self.errors:
if vi["INCAR"].get("ISMEAR", 1) < 0:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ISMEAR": "0"
}
}
})
if "zheev" in self.errors:
if vi["INCAR"].get("ALGO", "Fast").lower() != "exact":
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ALGO": "Exact"
}
}
})
if "elf_kpar" in self.errors:
actions.append({"dict": "INCAR", "action": {"_set": {"KPAR": 1}}})
if "rhosyg" in self.errors:
if vi["INCAR"].get("SYMPREC", 1e-4) == 1e-4:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ISYM": 0
}
}
})
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"SYMPREC": 1e-4
}
}
})
if "posmap" in self.errors:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"SYMPREC": 1e-6
}
}
})
if "point_group" in self.errors:
actions.append({"dict": "INCAR", "action": {"_set": {"ISYM": 0}}})
ViseVaspModder(vi=vi).apply_actions(actions)
return {"errors": list(self.errors), "actions": actions}
def create_SNL(dirbase, molecules, atoms, spc_present, num_each_spc, struct,
s):
layers = len(molecules)
with MPRester("sm5RbuEp83T9Wo7P") as m:
first_mol = struct[0]
mono_or_homo = 0
#if system is a monolayer or homogeneous use its proper .cif file, else use generic WTe2 for heterostructures
if (layers == 1) or all(x == first_mol for x in struct):
mono_or_homo = 1
if (first_mol == molec[0]):
structure = m.get_structure_by_material_id("mp-2815") #MoS2
ref = m.get_materials_id_references("mp-2815")
r1 = np.array([0, 2, 4])
elif (first_mol == molec[1]):
structure = m.get_structure_by_material_id("mp-1634") #MoSe2
ref = m.get_materials_id_references("mp-1634")
r1 = np.array([0, 2, 4])
elif (first_mol == molec[2]):
structure = m.get_structure_by_material_id("mp-602") #MoTe2
ref = m.get_materials_id_references("mp-602")
r1 = np.array([1, 2, 5])
elif (first_mol == molec[3]):
structure = m.get_structure_by_material_id("mp-224") #WS2
ref = m.get_materials_id_references("mp-224")
r1 = np.array([0, 3, 5])
elif (first_mol == molec[4]):
structure = m.get_structure_by_material_id("mp-1821") #WSe2
ref = m.get_materials_id_references("mp-1821")
r1 = np.array([0, 2, 4])
elif (first_mol == molec[5]):
structure = m.get_structure_by_material_id("mp-1019322") #WTe2
ref = m.get_materials_id_references("mp-1019322")
r1 = np.array([0, 3, 5])
else:
structure = m.get_structure_by_material_id("mp-1019322") #WTe2
ref = m.get_materials_id_references("mp-1019322")
r1 = np.array([0, 3, 5])
# initialize history
history = []
#half the height of original unit cell...to be used for vacuum length calculation later
halfz = (structure.lattice.c) / 2
#make supercell if necessary
levels = layers
if (levels % 2 == 1): levels = levels + 1
tsuper = SupercellTransformation([[1, 0, 0], [0, 1, 0],
[0, 0, (levels) / 2]])
history.append(history_node(tsuper))
supercell = tsuper.apply_transformation(structure)
#make species replacements for heterostructures with more than one layer
levels = layers
if (levels % 2 == 1): levels = levels + 1
#if heterostructure has more than one layer:
if (mono_or_homo == 0):
for i in range(0, len(molecules)):
if (molecules[i] == 5):
continue
else:
TMspc = elems[atoms[2 * i]]
TMloc = (levels * 2) + (i % 2) * (levels / 2) + int(
np.floor((i) / 2))
DCspc = elems[atoms[2 * i + 1]]
DCloc1 = (levels -
(levels / 2)) - i % 2 * (levels / 2) + int(
np.floor((i) / 2))
DCloc2 = levels + i % 2 * (levels / 2) + int(
np.floor((i) / 2))
t1 = ReplaceSiteSpeciesTransformation({TMloc: TMspc})
t2 = ReplaceSiteSpeciesTransformation({DCloc1: DCspc})
t3 = ReplaceSiteSpeciesTransformation({DCloc2: DCspc})
history.append(history_node(t1))
history.append(history_node(t2))
history.append(history_node(t3))
supercell = t1.apply_transformation(supercell)
supercell = t2.apply_transformation(supercell)
supercell = t3.apply_transformation(supercell)
#remove top layer of atom if necessary
mult_factor = (layers + 1) / 2 - 1
r = r1 + (r1 + 1) * mult_factor
tremove = RemoveSitesTransformation(r)
if (layers % 2 == 1):
supercell = tremove.apply_transformation(supercell)
history.append(history_node(tremove))
#sort structure
supercell = supercell.get_sorted_structure()
#extend z-axis cell vector to add vaccuum to supercell
vacuum = 10.0
old_lattice = supercell.lattice
if (layers % 2 == 1):
new_c = old_lattice.c - halfz + vacuum
else:
new_c = old_lattice.c + vacuum
new_lattice = Lattice.from_parameters(old_lattice.a, old_lattice.b,
new_c, old_lattice.alpha,
old_lattice.beta,
old_lattice.gamma)
final_structure = Structure(
new_lattice,
supercell.species,
supercell.frac_coords *
np.array([1., 1., (old_lattice.c / new_lattice.c)]),
coords_are_cartesian=False)
hnode = {
'name': 'add vaccuum',
'url': '',
'description': 'increase z-direction cell vector by 10 angstroms'
}
history.append(hnode)
#creat final SNL
authors = [{"name": "Lindsay Bassman", "email": "*****@*****.**"}]
projects = ["TMDC-Heterostructures"]
remarks = [
"MAGICS calculation of band structures of 2D TMDC stacked heterostructures"
]
final_snl = StructureNL(final_structure,
authors,
projects=projects,
remarks=remarks,
references=ref,
history=history)
#optionally write POSCAR file
poscar = Poscar(final_structure, s)
poscar.write_file(dirbase + "POSCAR", direct=False)
