def correct(self):
backup(VASP_BACKUP_FILES)
vi = VaspInput.from_directory(".")
potim = float(vi["INCAR"].get("POTIM", 0.5))
ibrion = int(vi["INCAR"].get("IBRION", 0))
if potim < 0.2 and ibrion != 3:
actions = [{
"dict": "INCAR",
"action": {
"_set": {
"IBRION": 3,
"SMASS": 0.75
}
}
}]
else:
actions = [{
"dict": "INCAR",
"action": {
"_set": {
"POTIM": potim * 0.5
}
}
}]
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["POTIM"], "actions": actions}
def correct(self):
backup("*.nw*")
actions = []
nwi = NwInput.from_file(self.input_file)
for e in self.errors:
if e == "autoz error":
action = {
"_set": {
"geometry_options": ["units", "angstroms", "noautoz"]
}
}
actions.append(action)
elif e == "Bad convergence":
t = nwi.tasks[self.ntasks - 1]
if "cgmin" in t.theory_directives:
nwi.tasks.pop(self.ntasks - 1)
else:
t.theory_directives["cgmin"] = ""
for t in nwi.tasks:
if t.operation.startswith("freq"):
# You cannot calculate hessian with cgmin.
t.theory_directives["nocgmin"] = ""
action = {"_set": {"tasks": [t.as_dict() for t in nwi.tasks]}}
actions.append(action)
else:
# For unimplemented errors, this should just cause the job to
# die.
return {"errors": self.errors, "actions": None}
m = Modder()
for action in actions:
nwi = m.modify_object(action, nwi)
nwi.write_file(self.input_file)
return {"errors": self.errors, "actions": actions}
def correct(self):
backup(VASP_BACKUP_FILES)
actions = []
vi = VaspInput.from_directory(".")
incar = vi["INCAR"]
outcar = Outcar("OUTCAR")
# Move CONTCAR to POSCAR
actions.append({"file": "CONTCAR",
"action": {"_file_copy": {"dest": "POSCAR"}}})
# First try adding ADDGRID
if not incar.get("ADDGRID", False) :
actions.append({"dict": "INCAR",
"action": {"_set": {"ADDGRID": True}}})
# Otherwise set PREC to High so ENAUG can be used to control Augmentation Grid Size
elif incar.get("PREC", "Accurate").lower() != "high":
actions.append({"dict": "INCAR",
"action": {"_set": {"PREC": "High"}}})
actions.append({"dict": "INCAR",
"action": {"_set": {"ENAUG": incar.get("ENCUT", 520) * 2}}})
# PREC is already high and ENAUG set so just increase it
else:
actions.append({"dict": "INCAR",
"action": {"_set": {"ENAUG": int(incar.get("ENAUG", 1040) * self.enaug_multiply)}}})
curr_drift = outcar.data.get("drift", [])[::-1][:self.to_average]
curr_drift = np.average([np.linalg.norm(d) for d in curr_drift])
VaspModder(vi=vi).apply_actions(actions)
return {"errors": "Excessive drift {} > {}".format(curr_drift, self.max_drift), "actions": actions}
def correct(self):
backup("*.nw*")
actions = []
nwi = NwInput.from_file(self.input_file)
for e in self.errors:
if e == "autoz error":
action = {"_set": {"geometry_options": ["units",
"angstroms",
"noautoz"]}}
actions.append(action)
elif e == "Bad convergence":
t = nwi.tasks[self.ntasks - 1]
if "cgmin" in t.theory_directives:
nwi.tasks.pop(self.ntasks - 1)
else:
t.theory_directives["cgmin"] = ""
for t in nwi.tasks:
if t.operation.startswith("freq"):
#You cannot calculate hessian with cgmin.
t.theory_directives["nocgmin"] = ""
action = {"_set": {"tasks": [t.as_dict() for t in nwi.tasks]}}
actions.append(action)
else:
# For unimplemented errors, this should just cause the job to
# die.
return {"errors": self.errors, "actions": None}
m = Modder()
for action in actions:
nwi = m.modify_object(action, nwi)
nwi.write_file(self.input_file)
return {"errors": self.errors, "actions": actions}
def setup(self):
"""
Performs initial setup for VaspJob, including overriding any settings
and backing up.
"""
decompress_dir('.')
if self.backup:
for f in VASP_INPUT_FILES:
shutil.copy(f, "{}.orig".format(f))
if self.auto_npar:
try:
incar = Incar.from_file("INCAR")
# Only optimized NPAR for non-HF and non-RPA calculations.
if not (incar.get("LHFCALC") or incar.get("LRPA") or
incar.get("LEPSILON")):
if incar.get("IBRION") in [5, 6, 7, 8]:
# NPAR should not be set for Hessian matrix
# calculations, whether in DFPT or otherwise.
del incar["NPAR"]
else:
import multiprocessing
# try sge environment variable first
# (since multiprocessing counts cores on the current
# machine only)
ncores = os.environ.get('NSLOTS') or \
multiprocessing.cpu_count()
ncores = int(ncores)
for npar in range(int(math.sqrt(ncores)),
ncores):
if ncores % npar == 0:
incar["NPAR"] = npar
break
incar.write_file("INCAR")
except:
pass
if self.auto_continue:
if os.path.exists("continue.json"):
actions = loadfn("continue.json").get("actions")
logger.info("Continuing previous VaspJob. Actions: {}".format(actions))
backup(VASP_BACKUP_FILES, prefix="prev_run")
VaspModder().apply_actions(actions)
else:
# Default functionality is to copy CONTCAR to POSCAR and set
# ISTART to 1 in the INCAR, but other actions can be specified
if self.auto_continue is True:
actions = [{"file": "CONTCAR",
"action": {"_file_copy": {"dest": "POSCAR"}}},
{"dict": "INCAR",
"action": {"_set": {"ISTART": 1}}}]
else:
actions = self.auto_continue
dumpfn({"actions": actions}, "continue.json")
if self.settings_override is not None:
VaspModder().apply_actions(self.settings_override)
def correct(self):
backup(FEFF_BACKUP_FILES)
feff_input = FEFFDictSet.from_directory(".")
scf_values = feff_input.tags.get("SCF")
nscmt = scf_values[2]
ca = scf_values[3]
nmix = scf_values[4]
actions = []
#Add RESTART card to PARAMETERS
if not "RESTART" in feff_input.tags:
actions.append({"dict": "PARAMETERS",
"action": {"_set": {"RESTART": []}}})
if nscmt < 100 and ca == 0.2:
scf_values[2] = 100
scf_values[4] = 3 # Set nmix = 3
actions.append({"dict": "PARAMETERS",
"action": {"_set": {"SCF": scf_values}}})
FeffModder().apply_actions(actions)
return {"errors": ["Non-converging job"], "actions": actions}
elif nscmt == 100 and nmix == 3 and ca > 0.01:
# Reduce the convergence accelerator factor
scf_values[3] = round(ca / 2, 2)
actions.append({"dict": "PARAMETERS",
"action": {"_set": {"SCF": scf_values}}})
FeffModder().apply_actions(actions)
return {"errors": ["Non-converging job"], "actions": actions}
elif nmix == 3 and ca == 0.01:
# Set ca = 0.05 and set nmix
scf_values[3] = 0.05
scf_values[4] = 5
actions.append({"dict": "PARAMETERS",
"action": {"_set": {"SCF": scf_values}}})
FeffModder().apply_actions(actions)
return {"errors": ["Non-converging job"], "actions": actions}
elif nmix == 5 and ca == 0.05:
# Set ca = 0.05 and set nmix
scf_values[3] = 0.05
scf_values[4] = 10
actions.append({"dict": "PARAMETERS",
"action": {"_set": {"SCF": scf_values}}})
FeffModder().apply_actions(actions)
return {"errors": ["Non-converging job"], "actions": actions}
elif nmix == 10 and ca < 0.2:
# loop through ca with nmix = 10
scf_values[3] = round(ca * 2, 2)
actions.append({"dict": "PARAMETERS",
"action": {"_set": {"SCF": scf_values}}})
FeffModder().apply_actions(actions)
return {"errors": ["Non-converging job"], "actions": actions}
# Unfixable error. Just return None for actions.
else:
return {"errors": ["Non-converging job"], "actions": None}
def setup(self):
"""
Performs initial setup for VaspJob, including overriding any settings
and backing up.
"""
decompress_dir('.')
if self.backup:
for f in VASP_INPUT_FILES:
shutil.copy(f, "{}.orig".format(f))
if self.auto_npar:
try:
incar = Incar.from_file("INCAR")
# Only optimized NPAR for non-HF and non-RPA calculations.
if not (incar.get("LHFCALC") or incar.get("LRPA") or
incar.get("LEPSILON")):
if incar.get("IBRION") in [5, 6, 7, 8]:
# NPAR should not be set for Hessian matrix
# calculations, whether in DFPT or otherwise.
del incar["NPAR"]
else:
import multiprocessing
# try sge environment variable first
# (since multiprocessing counts cores on the current
# machine only)
ncores = os.environ.get('NSLOTS') or \
multiprocessing.cpu_count()
ncores = int(ncores)
for npar in range(int(math.sqrt(ncores)),
ncores):
if ncores % npar == 0:
incar["NPAR"] = npar
break
incar.write_file("INCAR")
except:
pass
if self.auto_continue:
if os.path.exists("continue.json"):
actions = loadfn("continue.json").get("actions")
logger.info("Continuing previous VaspJob. Actions: {}".format(actions))
backup(VASP_BACKUP_FILES, prefix="prev_run")
VaspModder().apply_actions(actions)
else:
# Default functionality is to copy CONTCAR to POSCAR and set
# ISTART to 1 in the INCAR, but other actions can be specified
if self.auto_continue is True:
actions = [{"file": "CONTCAR",
"action": {"_file_copy": {"dest": "POSCAR"}}},
{"dict": "INCAR",
"action": {"_set": {"ISTART": 1}}}]
else:
actions = self.auto_continue
dumpfn({"actions": actions}, "continue.json")
if self.settings_override is not None:
VaspModder().apply_actions(self.settings_override)
def correct(self):
backup(VASP_BACKUP_FILES | {self.output_filename})
vi = VaspInput.from_directory(".")
m = reduce(operator.mul, vi["KPOINTS"].kpts[0])
m = max(int(round(m ** (1 / 3))), 1)
if vi["KPOINTS"].style.lower().startswith("m"):
m += m % 2
actions = [{"dict": "KPOINTS", "action": {"_set": {"kpoints": [[m] * 3]}}}]
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["mesh_symmetry"], "actions": actions}
def correct(self):
backup(orig_handlers.VASP_BACKUP_FILES)
v = Vasprun(self.output_filename)
actions = [{
"file": "CONTCAR",
"action": {
"_file_copy": {
"dest": "POSCAR"
}
}
}]
if not v.converged_electronic:
# For SCAN try switching to CG for the electronic minimization
if "SCAN" in v.incar.get("METAGGA", "").upper():
new_settings = {"ALGO": "All"}
else:
new_settings = {
"ISTART": 1,
"ALGO": "Normal",
"NELMDL": -6,
"BMIX": 0.001,
"AMIX_MAG": 0.8,
"BMIX_MAG": 0.001
}
if all(
[v.incar.get(k, "") == val
for k, val in new_settings.items()]):
return {"errors": ["Unconverged"], "actions": None}
actions.append({"dict": "INCAR", "action": {"_set": new_settings}})
# Instead of changing the IBRION, we reduce the EDIFF since we usually
# use the constant EDIFF value as default.
elif not v.converged_ionic:
ediff = v.incar["EDIFF"]
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"EDIFF": ediff * 0.5
}
}
})
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ADDGRID": True
}
}
})
ViseVaspModder().apply_actions(actions)
return {"errors": ["Unconverged"], "actions": actions}
def correct(self):
backup(VASP_BACKUP_FILES | {self.output_filename})
vi = VaspInput.from_directory(".")
actions = []
if vi["INCAR"].get("ALGO", "Normal") == "Fast":
actions.append({"dict": "INCAR", "action": {"_set": {"ALGO": "Normal"}}})
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["Frozen job"], "actions": actions}
def correct(self):
backup(VASP_BACKUP_FILES | {self.output_filename})
vi = VaspInput.from_directory(".")
m = reduce(operator.mul, vi["KPOINTS"].kpts[0])
m = max(int(round(m ** (1 / 3))), 1)
if vi["KPOINTS"].style.name.lower().startswith("m"):
m += m % 2
actions = [{"dict": "KPOINTS",
"action": {"_set": {"kpoints": [[m] * 3]}}}]
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["mesh_symmetry"], "actions": actions}
def correct(self):
backup(VASP_BACKUP_FILES | {self.output_filename})
vi = VaspInput.from_directory(".")
ediff = float(vi["INCAR"].get("EDIFF", 1e-4))
ediffg = float(vi["INCAR"].get("EDIFFG", ediff * 10))
actions = [{"file": "CONTCAR",
"action": {"_file_copy": {"dest": "POSCAR"}}},
{"dict": "INCAR",
"action": {"_set": {"EDIFFG": ediffg * 0.5}}}]
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["MaxForce"], "actions": actions}
def correct(self):
# change ALGO = Fast to Normal if ALGO is !Normal
vi = VaspInput.from_directory(".")
algo = vi["INCAR"].get("ALGO", "Normal")
if algo.lower() not in ["normal", "n"]:
backup(VASP_BACKUP_FILES)
actions = [{"dict": "INCAR", "action": {"_set": {"ALGO": "Normal"}}}]
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["Positive energy"], "actions": actions}
# Unfixable error. Just return None for actions.
else:
return {"errors": ["Positive energy"], "actions": None}
def correct(self):
backup(VASP_BACKUP_FILES)
vi = VaspInput.from_directory(".")
potim = float(vi["INCAR"].get("POTIM", 0.5))
ibrion = int(vi["INCAR"].get("IBRION", 0))
if potim < 0.2 and ibrion != 3:
actions = [{"dict": "INCAR", "action": {"_set": {"IBRION": 3, "SMASS": 0.75}}}]
else:
actions = [{"dict": "INCAR", "action": {"_set": {"POTIM": potim * 0.5}}}]
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["POTIM"], "actions": actions}
def correct(self):
backup(VASP_BACKUP_FILES | {self.output_filename})
vi = VaspInput.from_directory('.')
actions = []
if vi["INCAR"].get("ALGO", "Normal") == "Fast":
actions.append({"dict": "INCAR",
"action": {"_set": {"ALGO": "Normal"}}})
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["Frozen job"], "actions": actions}
def correct(self):
backup(["INCAR", "KPOINTS", "POSCAR", "OUTCAR",
self.output_filename, "vasp.out"])
vi = VaspInput.from_directory(".")
ediff = float(vi["INCAR"].get("EDIFF", 1e-4))
actions = [{"file": "CONTCAR",
"action": {"_file_copy": {"dest": "POSCAR"}}},
{"dict": "INCAR",
"action": {"_set": {"EDIFF": ediff*0.75}}}]
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["MaxForce"], "actions": actions}
def correct(self):
backup(VASP_BACKUP_FILES | {self.output_filename})
vi = VaspInput.from_directory(".")
ediff = float(vi["INCAR"].get("EDIFF", 1e-4))
ediffg = float(vi["INCAR"].get("EDIFFG", ediff * 10))
actions = [{"file": "CONTCAR",
"action": {"_file_copy": {"dest": "POSCAR"}}},
{"dict": "INCAR",
"action": {"_set": {"EDIFFG": ediffg*0.5}}}]
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["MaxForce"], "actions": actions}
def correct(self):
backup(VASP_BACKUP_FILES)
actions = [{"file": "CONTCAR",
"action": {"_file_copy": {"dest": "POSCAR"}}},
{"dict": "INCAR",
"action": {"_set": {"ISTART": 1,
"ALGO": "Normal",
"NELMDL": -6,
"BMIX": 0.001,
"AMIX_MAG": 0.8,
"BMIX_MAG": 0.001}}}]
VaspModder().apply_actions(actions)
return {"errors": ["Unconverged"], "actions": actions}
def correct(self):
backup(VASP_BACKUP_FILES)
actions = [{"file": "CONTCAR",
"action": {"_file_copy": {"dest": "POSCAR"}}},
{"dict": "INCAR",
"action": {"_set": {"ISTART": 1,
"ALGO": "Normal",
"NELMDL": -6,
"BMIX": 0.001,
"AMIX_MAG": 0.8,
"BMIX_MAG": 0.001}}}]
VaspModder().apply_actions(actions)
return {"errors": ["Unconverged"], "actions": actions}
def correct(self):
# change ALGO = Fast to Normal if ALGO is !Normal
vi = VaspInput.from_directory(".")
algo = vi["INCAR"].get("ALGO", "Normal")
if algo.lower() not in ['normal', 'n']:
backup(["INCAR", "KPOINTS", "POSCAR", "OUTCAR", "vasprun.xml"])
actions = [{"dict": "INCAR",
"action": {"_set": {"ALGO": "Normal"}}}]
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["Positive energy"], "actions": actions}
#Unfixable error. Just return None for actions.
else:
return {"errors": ["Positive energy"], "actions": None}
def correct(self):
backup([self.output_filename, "INCAR", "KPOINTS", "POSCAR", "OUTCAR",
"vasprun.xml"])
vi = VaspInput.from_directory('.')
actions = []
if vi["INCAR"].get("ALGO", "Normal") == "Fast":
actions.append({"dict": "INCAR",
"action": {"_set": {"ALGO": "Normal"}}})
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["Frozen job"], "actions": actions}
def correct(self):
# change ALGO = Fast to Normal if ALGO is !Normal
vi = VaspInput.from_directory(".")
algo = vi["INCAR"].get("ALGO", "Normal")
if algo.lower() not in ['normal', 'n']:
backup(VASP_BACKUP_FILES)
actions = [{"dict": "INCAR",
"action": {"_set": {"ALGO": "Normal"}}}]
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["Positive energy"], "actions": actions}
# Unfixable error. Just return None for actions.
else:
return {"errors": ["Positive energy"], "actions": None}
def correct(self):
backup(AIMS_BACKUP_FILES | {self.output_filename})
actions = []
init_cons = []
if "energy_F_inconsistent" in self.errors:
with open('geometry.in', 'rt') as f:
content = f.readlines()
for i, line in enumerate(content):
if 'atom' in line:
init_cons.append(
self.check_constraints(content,
i + 1,
total_lines=len(content)))
k = 0
content = []
with open('geometry.in.next_step', 'rt') as f:
for line in f:
if 'lattice_vector ' in line:
content.append(line)
if 'atom' in line:
content.append(line)
if init_cons[k][0]:
content.append(' initial_moment {:3.3f}\n'.format(
init_cons[k][0]))
print(init_cons[k][1][0], init_cons[k][1][1],
init_cons[k][1][2])
if init_cons[k][1][0] and init_cons[k][1][
1] and init_cons[k][1][2]:
content.append(' constrain_relaxation .true.\n')
else:
if init_cons[k][1][0]:
content.append(' constrain_relaxation x\n')
if init_cons[k][1][1]:
content.append(' constrain_relaxation y\n')
if init_cons[k][1][2]:
content.append(' constrain_relaxation z\n')
if not os.path.isfile('user_supplied_geometry.in'):
os.rename('geometry.in', 'user_supplied_geometry.in')
with open('geometry.in', 'wt') as f:
for line in content:
f.write(line)
print(content)
actions.append({'fixed': 'geo_step -> geo'})
return {"errors": list(self.errors), "actions": actions}
def correct(self):
backup(VASP_BACKUP_FILES | {self.output_filename})
actions = []
vi = VaspInput.from_directory(".")
if "lrf_comm" in self.errors:
if Outcar(zpath(os.path.join(
os.getcwd(), "OUTCAR"))).is_stopped is False:
if not vi["INCAR"].get("LPEAD"):
actions.append({"dict": "INCAR",
"action": {"_set": {"LPEAD": True}}})
VaspModder(vi=vi).apply_actions(actions)
return {"errors": list(self.errors), "actions": actions}
def correct(self):
backup(["INCAR", "KPOINTS", "POSCAR", "OUTCAR", "vasprun.xml",
"vasp.out"])
actions = [{"file": "CONTCAR",
"action": {"_file_copy": {"dest": "POSCAR"}}},
{"dict": "INCAR",
"action": {"_set": {"ISTART": 1,
"ALGO": "Normal",
"NELMDL": -6,
"BMIX": 0.001,
"AMIX_MAG": 0.8,
"BMIX_MAG": 0.001}}}]
VaspModder().apply_actions(actions)
return {"errors": ["Unconverged"], "actions": actions}
def correct(self):
backup(VASP_BACKUP_FILES | {self.output_filename})
actions = []
vi = VaspInput.from_directory(".")
if "lrf_comm" in self.errors:
if Outcar(zpath(os.path.join(
os.getcwd(), "OUTCAR"))).is_stopped is False:
if not vi["INCAR"].get("LPEAD"):
actions.append({"dict": "INCAR",
"action": {"_set": {"LPEAD": True}}})
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 "subspacematrix" in self.errors:
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ALGO": "All"
}
}
})
VaspModder(vi=vi).apply_actions(actions)
return {"errors": list(self.errors), "actions": actions}
def correct(self):
backup(VASP_BACKUP_FILES)
v = Vasprun(self.output_filename)
actions = [{"file": "CONTCAR",
"action": {"_file_copy": {"dest": "POSCAR"}}}]
if not v.converged_electronic:
actions.append({"dict": "INCAR",
"action": {"_set": {"ISTART": 1,
"ALGO": "Normal",
"NELMDL": -6,
"BMIX": 0.001,
"AMIX_MAG": 0.8,
"BMIX_MAG": 0.001}}})
if not v.converged_ionic:
actions.append({"dict": "INCAR",
"action": {"_set": {"IBRION":1}}})
VaspModder().apply_actions(actions)
return {"errors": ["Unconverged"], "actions": actions}
def correct(self):
backup(VASP_BACKUP_FILES)
v = Vasprun(self.output_filename)
actions = [{"file": "CONTCAR",
"action": {"_file_copy": {"dest": "POSCAR"}}}]
if not v.converged_electronic:
actions.append({"dict": "INCAR",
"action": {"_set": {"ISTART": 1,
"ALGO": "Normal",
"NELMDL": -6,
"BMIX": 0.001,
"AMIX_MAG": 0.8,
"BMIX_MAG": 0.001}}})
if not v.converged_ionic:
actions.append({"dict": "INCAR",
"action": {"_set": {"IBRION": 1}}})
VaspModder().apply_actions(actions)
return {"errors": ["Unconverged"], "actions": actions}
def correct(self):
backup(VASP_BACKUP_FILES | {self.output_filename})
actions = []
vi = VaspInput.from_directory(".")
if "aliasing" in self.errors:
with open("OUTCAR") as f:
grid_adjusted = False
changes_dict = {}
r = re.compile(".+aliasing errors.*(NG.)\s*to\s*(\d+)")
for line in f:
m = r.match(line)
if m:
changes_dict[m.group(1)] = int(m.group(2))
grid_adjusted = True
# Ensure that all NGX, NGY, NGZ have been checked
if grid_adjusted and 'NGZ' in line:
actions.append(
{"dict": "INCAR", "action": {"_set": changes_dict}})
if vi["INCAR"].get("ICHARG", 0) < 10:
actions.extend([{"file": "CHGCAR",
"action": {"_file_delete": {
'mode': "actual"}}},
{"file": "WAVECAR",
"action": {"_file_delete": {
'mode': "actual"}}}])
break
if "aliasing_incar" in self.errors:
# vasp seems to give different warnings depending on whether the
# aliasing error was caused by user supplied inputs
d = {k: 1 for k in ['NGX', 'NGY', 'NGZ'] if k in vi['INCAR'].keys()}
actions.append({"dict": "INCAR", "action": {"_unset": d}})
if vi["INCAR"].get("ICHARG", 0) < 10:
actions.extend([{"file": "CHGCAR",
"action": {
"_file_delete": {'mode': "actual"}}},
{"file": "WAVECAR",
"action": {
"_file_delete": {'mode': "actual"}}}])
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 "aliasing" in self.errors:
with open("OUTCAR") as f:
grid_adjusted = False
changes_dict = {}
r = re.compile(".+aliasing errors.*(NG.)\s*to\s*(\d+)")
for line in f:
m = r.match(line)
if m:
changes_dict[m.group(1)] = int(m.group(2))
grid_adjusted = True
# Ensure that all NGX, NGY, NGZ have been checked
if grid_adjusted and 'NGZ' in line:
actions.append(
{"dict": "INCAR", "action": {"_set": changes_dict}})
if vi["INCAR"].get("ICHARG", 0) < 10:
actions.extend([{"file": "CHGCAR",
"action": {"_file_delete": {
'mode': "actual"}}},
{"file": "WAVECAR",
"action": {"_file_delete": {
'mode': "actual"}}}])
break
if "aliasing_incar" in self.errors:
# vasp seems to give different warnings depending on whether the
# aliasing error was caused by user supplied inputs
d = {k: 1 for k in ['NGX', 'NGY', 'NGZ'] if k in vi['INCAR'].keys()}
actions.append({"dict": "INCAR", "action": {"_unset": d}})
if vi["INCAR"].get("ICHARG", 0) < 10:
actions.extend([{"file": "CHGCAR",
"action": {
"_file_delete": {'mode': "actual"}}},
{"file": "WAVECAR",
"action": {
"_file_delete": {'mode': "actual"}}}])
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 we encounter a DAV Sub-Space-Matrix error
if "subspacematrix" or "edddav" in self.errors:
# Switch to the CG algorithm
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ALGO": "All"
}
}
})
# If we encounter a ZBRENT error
if "zbrent" in self.errors:
# Switch to Quasi-Newton algorithm
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"IBRION": 1
}
}
})
# Move CONTCAR to POSCAR
actions.append({
"file": "CONTCAR",
"action": {
"_file_copy": {
"dest": "POSCAR"
}
}
})
VaspModder(vi=vi).apply_actions(actions)
return {"errors": list(self.errors), "actions": actions}
def correct(self):
# if change_algo is True, change ALGO = Fast to Normal if ALGO is
# Fast. If still not converging, following Kresse's
# recommendation, we will try two iterations of different mixing
# parameters. If this error is caught again, then kil the job
vi = VaspInput.from_directory(".")
algo = vi["INCAR"].get("ALGO", "Normal")
amix = vi["INCAR"].get("AMIX", 0.4)
bmix = vi["INCAR"].get("BMIX", 1.0)
amin = vi["INCAR"].get("AMIN", 0.1)
actions = []
if self.change_algo:
if algo == "Fast":
backup(VASP_BACKUP_FILES)
actions.append({"dict": "INCAR", "action": {"_set": {"ALGO": "Normal"}}})
elif amix > 0.1 and bmix > 0.01:
# try linear mixing
backup(VASP_BACKUP_FILES)
actions.append({"dict": "INCAR", "action": {"_set": {"AMIX": 0.1, "BMIX": 0.01, "ICHARG": 2}}})
elif bmix < 3.0 and amin > 0.01:
# Try increasing bmix
backup(VASP_BACKUP_FILES)
actions.append({"dict": "INCAR", "action": {"_set": {"AMIN": 0.01, "BMIX": 3.0, "ICHARG": 2}}})
if actions:
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["Non-converging job"], "actions": actions}
# Unfixable error. Just return None for actions.
else:
return {"errors": ["Non-converging job"], "actions": None}
def correct(self):
backup(VASP_BACKUP_FILES | {self.output_filename})
actions = []
vi = VaspInput.from_directory(".")
if "kpoints_trans" in self.errors:
if self.error_count["kpoints_trans"] == 0:
m = reduce(operator.mul, vi["KPOINTS"].kpts[0])
m = max(int(round(m ** (1 / 3))), 1)
if vi["KPOINTS"].style.name.lower().startswith("m"):
m += m % 2
actions.append({"dict": "KPOINTS", "action": {"_set": {"kpoints": [[m] * 3]}}})
self.error_count['kpoints_trans'] += 1
if "out_of_memory" in self.errors:
if vi["INCAR"].get("KPAR", 1) > 1:
reduced_kpar = max(vi["INCAR"].get("KPAR", 1) // 2, 1)
actions.append({"dict": "INCAR",
"action": {"_set": {"KPAR": reduced_kpar}}})
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 "lrf_comm" in self.errors:
if self.error_count['lrf_comm'] == 0:
if Outcar(zpath(os.path.join(os.getcwd(),
"OUTCAR"))).is_stopped is False:
# simply rerun the job and increment
# error count for next time
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ISTART": 1
}
}
})
self.error_count['lrf_comm'] += 1
if "kpoints_trans" in self.errors:
if self.error_count["kpoints_trans"] == 0:
m = reduce(operator.mul, vi["KPOINTS"].kpts[0])
m = max(int(round(m**(1 / 3))), 1)
if vi["KPOINTS"].style.name.lower().startswith("m"):
m += m % 2
actions.append({
"dict": "KPOINTS",
"action": {
"_set": {
"kpoints": [[m] * 3]
}
}
})
self.error_count['kpoints_trans'] += 1
VaspModder(vi=vi).apply_actions(actions)
return {"errors": list(self.errors), "actions": actions}
def correct(self):
# if change_algo is True, change ALGO = Fast to Normal if ALGO is
# Fast. If still not converging, following Kresse's
# recommendation, we will try two iterations of different mixing
# parameters. If this error is caught again, then kil the job
vi = VaspInput.from_directory(".")
algo = vi["INCAR"].get("ALGO", "Normal")
amix = vi["INCAR"].get("AMIX", 0.4)
bmix = vi["INCAR"].get("BMIX", 1.0)
amin = vi["INCAR"].get("AMIN", 0.1)
actions = []
if self.change_algo:
if algo == "Fast":
backup(VASP_BACKUP_FILES)
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ALGO": "Normal"
}
}
})
elif amix > 0.1 and bmix > 0.01:
#try linear mixing
backup(VASP_BACKUP_FILES)
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"AMIX": 0.1,
"BMIX": 0.01,
"ICHARG": 2
}
}
})
elif bmix < 3.0 and amin > 0.01:
#Try increasing bmix
backup(VASP_BACKUP_FILES)
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"AMIN": 0.01,
"BMIX": 3.0,
"ICHARG": 2
}
}
})
if actions:
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["Non-converging job"], "actions": actions}
#Unfixable error. Just return None for actions.
else:
return {"errors": ["Non-converging job"], "actions": None}
def correct(self):
backup(VASP_BACKUP_FILES | {self.output_filename})
actions = []
vi = VaspInput.from_directory(".")
if "kpoints_trans" in self.errors:
if self.error_count["kpoints_trans"] == 0:
m = reduce(operator.mul, vi["KPOINTS"].kpts[0])
m = max(int(round(m ** (1 / 3))), 1)
if vi["KPOINTS"].style.name.lower().startswith("m"):
m += m % 2
actions.append({"dict": "KPOINTS",
"action": {"_set": {"kpoints": [[m] * 3]}}})
self.error_count['kpoints_trans'] += 1
if "out_of_memory" in self.errors:
if vi["INCAR"].get("KPAR", 1) > 1:
reduced_kpar = max(vi["INCAR"].get("KPAR", 1) // 2, 1)
actions.append({"dict": "INCAR",
"action": {"_set": {"KPAR": reduced_kpar}}})
VaspModder(vi=vi).apply_actions(actions)
return {"errors": list(self.errors), "actions": actions}
def correct(self):
backup(VASP_BACKUP_FILES)
v = Vasprun(self.output_filename)
actions = [{"file": "CONTCAR",
"action": {"_file_copy": {"dest": "POSCAR"}}}]
if not v.converged_electronic:
new_settings = {"ISTART": 1,
"ALGO": "Normal",
"NELMDL": -6,
"BMIX": 0.001,
"AMIX_MAG": 0.8,
"BMIX_MAG": 0.001}
if all([v.incar.get(k,"") == val for k,val in new_settings.items()]):
return {"errors": ["Unconverged"], "actions": None}
actions.append({"dict": "INCAR",
"action": {"_set": new_settings}})
if not v.converged_ionic:
actions.append({"dict": "INCAR",
"action": {"_set": {"IBRION": 1}}})
VaspModder().apply_actions(actions)
return {"errors": ["Unconverged"], "actions": actions}
def correct(self):
vi = VaspInput.from_directory(".")
algo = vi["INCAR"].get("ALGO", "Normal")
amix = vi["INCAR"].get("AMIX", 0.4)
bmix = vi["INCAR"].get("BMIX", 1.0)
amin = vi["INCAR"].get("AMIN", 0.1)
actions = []
# Ladder from VeryFast to Fast to Fast to All
# These progressively switches to more stable but more
# expensive algorithms
if algo == "VeryFast":
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ALGO": "Fast"
}
}
})
elif algo == "Fast":
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ALGO": "Normal"
}
}
})
elif algo == "Normal":
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"ALGO": "All"
}
}
})
elif amix > 0.1 and bmix > 0.01:
# Try linear mixing
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"AMIX": 0.1,
"BMIX": 0.01,
"ICHARG": 2
}
}
})
elif bmix < 3.0 and amin > 0.01:
# Try increasing bmix
actions.append({
"dict": "INCAR",
"action": {
"_set": {
"AMIN": 0.01,
"BMIX": 3.0,
"ICHARG": 2
}
}
})
if actions:
backup(VASP_BACKUP_FILES)
VaspModder(vi=vi).apply_actions(actions)
return {"errors": ["Non-converging job"], "actions": actions}
# Unfixable error. Just return None for actions.
else:
return {"errors": ["Non-converging job"], "actions": None}
def correct(self):
backup({self.input_file, self.output_file})
actions = []
if "SCF_failed_to_converge" in self.errors:
# Check number of SCF cycles. If not set or less than scf_max_cycles,
# increase to that value and rerun. If already set, check if
# scf_algorithm is unset or set to DIIS, in which case set to RCA-DIIS.
# Otherwise, tell user to call SCF error handler and do nothing.
if self.qcinp.rem.get("max_scf_cycles") != str(
self.scf_max_cycles):
self.qcinp.rem["max_scf_cycles"] = self.scf_max_cycles
actions.append({"max_scf_cycles": self.scf_max_cycles})
elif self.qcinp.rem.get("scf_algorithm", "diis").lower() == "diis":
self.qcinp.rem["scf_algorithm"] = "rca_diis"
actions.append({"scf_algorithm": "rca_diis"})
if self.qcinp.rem.get("gen_scfman"):
self.qcinp.rem["gen_scfman"] = False
actions.append({"gen_scfman": False})
else:
print(
"More advanced changes may impact the SCF result. Use the SCF error handler"
)
elif "out_of_opt_cycles" in self.errors:
# Check number of opt cycles. If less than geom_max_cycles, increase
# to that value, set last geom as new starting geom and rerun.
if self.qcinp.rem.get(
"geom_opt_max_cycles") != self.geom_max_cycles:
self.qcinp.rem["geom_opt_max_cycles"] = self.geom_max_cycles
actions.append({"geom_max_cycles:": self.scf_max_cycles})
if len(self.outdata.get("energy_trajectory")) > 1:
if self.qcinp.molecule.spin_multiplicity != self.outdata.get(
"molecule_from_last_geometry").spin_multiplicity:
raise AssertionError('Multiplicities should match!')
if self.qcinp.molecule.charge != self.outdata.get(
"molecule_from_last_geometry").charge:
raise AssertionError('Charges should match!')
self.qcinp.molecule = self.outdata.get(
"molecule_from_last_geometry")
actions.append({"molecule": "molecule_from_last_geometry"})
else:
print(
"How do I get the geometry optimization converged when already at the maximum number of cycles?"
)
elif "unable_to_determine_lamda" in self.errors:
# Set last geom as new starting geom and rerun. If no opt cycles,
# use diff SCF strat? Diff initial guess? Change basis?
if len(self.outdata.get("energy_trajectory")) > 1:
if self.qcinp.molecule.spin_multiplicity != self.outdata.get(
"molecule_from_last_geometry").spin_multiplicity:
raise AssertionError('Multiplicities should match!')
if self.qcinp.molecule.charge != self.outdata.get(
"molecule_from_last_geometry").charge:
raise AssertionError('Charges should match!')
self.qcinp.molecule = self.outdata.get(
"molecule_from_last_geometry")
actions.append({"molecule": "molecule_from_last_geometry"})
elif self.qcinp.rem.get("scf_algorithm", "diis").lower() == "diis":
self.qcinp.rem["scf_algorithm"] = "rca_diis"
actions.append({"scf_algorithm": "rca_diis"})
if self.qcinp.rem.get("gen_scfman"):
self.qcinp.rem["gen_scfman"] = False
actions.append({"gen_scfman": False})
else:
print(
"Use a different initial guess? Perhaps a different basis?"
)
elif "linear_dependent_basis" in self.errors:
# DIIS -> RCA_DIIS. If already RCA_DIIS, change basis?
if self.qcinp.rem.get("scf_algorithm", "diis").lower() == "diis":
self.qcinp.rem["scf_algorithm"] = "rca_diis"
actions.append({"scf_algorithm": "rca_diis"})
if self.qcinp.rem.get("gen_scfman"):
self.qcinp.rem["gen_scfman"] = False
actions.append({"gen_scfman": False})
else:
print("Perhaps use a better basis?")
elif "failed_to_transform_coords" in self.errors:
# Check for symmetry flag in rem. If not False, set to False and rerun.
# If already False, increase threshold?
if not self.qcinp.rem.get("sym_ignore") or self.qcinp.rem.get(
"symmetry"):
self.qcinp.rem["sym_ignore"] = True
self.qcinp.rem["symmetry"] = False
actions.append({"sym_ignore": True})
actions.append({"symmetry": False})
else:
print("Perhaps increase the threshold?")
elif "input_file_error" in self.errors:
print(
"Something is wrong with the input file. Examine error message by hand."
)
return {"errors": self.errors, "actions": None}
elif "failed_to_read_input" in self.errors:
# Almost certainly just a temporary problem that will not be encountered again. Rerun job as-is.
actions.append({"rerun job as-is"})
elif "IO_error" in self.errors:
# Almost certainly just a temporary problem that will not be encountered again. Rerun job as-is.
actions.append({"rerun job as-is"})
elif "unknown_error" in self.errors:
print("Examine error message by hand.")
return {"errors": self.errors, "actions": None}
else:
# You should never get here. If correct is being called then errors should have at least one entry,
# in which case it should have been caught by the if/elifs above.
print(
"If you get this message, something has gone terribly wrong!")
return {"errors": self.errors, "actions": None}
os.rename(self.input_file, self.input_file + ".last")
self.qcinp.write_file(self.input_file)
return {"errors": self.errors, "actions": actions}
def correct(self): #pylint: disable=R0915,R0912,R0914
"""
"brmix"にてINCARにADDGRIDを追加する
"""
backup([self.output_filename, "INCAR", "KPOINTS", "POSCAR", "OUTCAR",
"vasprun.xml"])
actions = []
vi = VaspInput.from_directory(".")
if "tet" in self.errors or "dentet" in self.errors:
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 and "NELECT" in vi["INCAR"]:
#brmix error always shows up after DAV steps if NELECT is specified
self.errors.remove("brmix")
if "brmix" in self.errors or "zpotrf" in self.errors:
actions.append({"dict": "INCAR",
"action": {"_set": {"ISYM": 0}}})
#140814 add
actions.append({"dict": "INCAR",
"action": {"_set": {"ADDGRID": True}}})
# Based on VASP forum's recommendation, you should delete the
# CHGCAR and WAVECAR when dealing with these errors.
actions.append({"file": "CHGCAR",
"action": {"_file_delete": {'mode': "actual"}}})
actions.append({"file": "WAVECAR",
"action": {"_file_delete": {'mode': "actual"}}})
if "subspacematrix" in self.errors or "rspher" in self.errors or \
"real_optlay" in self.errors:
actions.append({"dict": "INCAR",
"action": {"_set": {"LREAL": False}}})
if "tetirr" in self.errors or "incorrect_shift" in self.errors or \
"rot_matrix" in self.errors:
actions.append({"dict": "KPOINTS",
"action": {"_set": {"generation_style": "Gamma"}}})
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.to_dict}},
"transformation": trans.to_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 "aliasing" in self.errors:
with open("OUTCAR") as f:
grid_adjusted = False
changes_dict = {}
for line in f:
if "aliasing errors" in line:
try:
grid_vector = line.split(" NG", 1)[1]
value = [int(s) for s in grid_vector.split(" ")
if s.isdigit()][0]
changes_dict["NG" + grid_vector[0]] = value
grid_adjusted = True
except (IndexError, ValueError):
pass
#Ensure that all NGX, NGY, NGZ have been checked
if grid_adjusted and 'NGZ' in line:
actions.append({"dict": "INCAR",
"action": {"_set": changes_dict}})
break
m = Modder(actions=[DictActions, FileActions])
modified = []
for a in actions:
if "dict" in a:
modified.append(a["dict"])
vi[a["dict"]] = m.modify_object(a["action"], vi[a["dict"]])
elif "file" in a:
m.modify(a["action"], a["file"])
for f in modified:
vi[f].write_file(f)
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 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([self.output_filename, "INCAR", "KPOINTS", "POSCAR", "OUTCAR",
"OSZICAR", "vasprun.xml"])
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:
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 "aliasing" in self.errors:
with open("OUTCAR") as f:
grid_adjusted = False
changes_dict = {}
r = re.compile(".+aliasing errors.*(NG.)\s*to\s*(\d+)")
for line in f:
m = r.match(line)
if m:
changes_dict[m.group(1)] = int(m.group(2))
grid_adjusted = True
#Ensure that all NGX, NGY, NGZ have been checked
if grid_adjusted and 'NGZ' in line:
actions.extend(
[{"dict": "INCAR",
"action": {"_set": changes_dict}},
{"file": "CHGCAR",
"action": {"_file_delete": {'mode': "actual"}}},
{"file": "WAVECAR",
"action": {"_file_delete": {'mode': "actual"}}}])
break
if "aliasing_incar" in self.errors:
#vasp seems to give different warnings depending on whether the
#aliasing error was caused by user supplied inputs
d = {k: 1 for k in ['NGX', 'NGY', 'NGZ'] if k in vi['INCAR'].keys()}
actions.extend([{"dict": "INCAR", "action": {"_unset": d}},
{"file": "CHGCAR",
"action": {"_file_delete": {'mode': "actual"}}},
{"file": "WAVECAR",
"action": {"_file_delete": {'mode': "actual"}}}])
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"}}})
VaspModder(vi=vi).apply_actions(actions)
return {"errors": list(self.errors), "actions": actions}
def postprocess(self):
"""
Renaming or gzipping all the output as needed
"""
if self.gzipped:
backup("*", prefix=self.gzipped_prefix)
def correct(self):
backup({self.input_file, self.output_file})
actions = []
self.qcinp = QCInput.from_file(self.input_file)
if "SCF_failed_to_converge" in self.errors:
# Check number of SCF cycles. If not set or less than scf_max_cycles,
# increase to that value and rerun. If already set, check if
# scf_algorithm is unset or set to DIIS, in which case set to GDM.
# Otherwise, tell user to call SCF error handler and do nothing.
if str(self.qcinp.rem.get("max_scf_cycles")) != str(
self.scf_max_cycles):
self.qcinp.rem["max_scf_cycles"] = self.scf_max_cycles
actions.append({"max_scf_cycles": self.scf_max_cycles})
elif self.qcinp.rem.get("scf_algorithm", "diis").lower() == "diis":
self.qcinp.rem["scf_algorithm"] = "gdm"
actions.append({"scf_algorithm": "gdm"})
elif self.qcinp.rem.get("scf_algorithm", "gdm").lower() == "gdm":
self.qcinp.rem["scf_algorithm"] = "diis_gdm"
actions.append({"scf_algorithm": "diis_gdm"})
else:
print(
"More advanced changes may impact the SCF result. Use the SCF error handler"
)
elif "out_of_opt_cycles" in self.errors:
# Check number of opt cycles. If less than geom_max_cycles, increase
# to that value, set last geom as new starting geom and rerun.
if str(self.qcinp.rem.get(
"geom_opt_max_cycles")) != str(self.geom_max_cycles):
self.qcinp.rem["geom_opt_max_cycles"] = self.geom_max_cycles
actions.append({"geom_max_cycles:": self.scf_max_cycles})
if len(self.outdata.get("energy_trajectory")) > 1:
self.qcinp.molecule = self.outdata.get(
"molecule_from_last_geometry")
actions.append({"molecule": "molecule_from_last_geometry"})
# If already at geom_max_cycles, often can just get convergence by restarting
# from the geometry of the last cycle. But we'll also save any structural
# changes that happened along the way.
else:
self.opt_error_history += [self.outdata["structure_change"]]
if len(self.opt_error_history) > 1:
if self.opt_error_history[-1] == "no_change":
# If no structural changes occured in two consecutive optimizations,
# and we still haven't converged, then just exit.
return {"errors": self.errors, "actions": None, "opt_error_history": self.opt_error_history}
self.qcinp.molecule = self.outdata.get("molecule_from_last_geometry")
actions.append({"molecule": "molecule_from_last_geometry"})
elif "unable_to_determine_lamda" in self.errors:
# Set last geom as new starting geom and rerun. If no opt cycles,
# use diff SCF strat? Diff initial guess? Change basis?
if len(self.outdata.get("energy_trajectory")) > 1:
self.qcinp.molecule = self.outdata.get(
"molecule_from_last_geometry")
actions.append({"molecule": "molecule_from_last_geometry"})
elif self.qcinp.rem.get("scf_algorithm", "diis").lower() == "diis":
self.qcinp.rem["scf_algorithm"] = "rca_diis"
actions.append({"scf_algorithm": "rca_diis"})
if self.qcinp.rem.get("gen_scfman"):
self.qcinp.rem["gen_scfman"] = False
actions.append({"gen_scfman": False})
else:
print(
"Use a different initial guess? Perhaps a different basis?"
)
elif "linear_dependent_basis" in self.errors:
# DIIS -> RCA_DIIS. If already RCA_DIIS, change basis?
if self.qcinp.rem.get("scf_algorithm", "diis").lower() == "diis":
self.qcinp.rem["scf_algorithm"] = "rca_diis"
actions.append({"scf_algorithm": "rca_diis"})
if self.qcinp.rem.get("gen_scfman"):
self.qcinp.rem["gen_scfman"] = False
actions.append({"gen_scfman": False})
else:
print("Perhaps use a better basis?")
elif "failed_to_transform_coords" in self.errors:
# Check for symmetry flag in rem. If not False, set to False and rerun.
# If already False, increase threshold?
if not self.qcinp.rem.get("sym_ignore") or self.qcinp.rem.get(
"symmetry"):
self.qcinp.rem["sym_ignore"] = True
self.qcinp.rem["symmetry"] = False
actions.append({"sym_ignore": True})
actions.append({"symmetry": False})
else:
print("Perhaps increase the threshold?")
elif "input_file_error" in self.errors:
print(
"Something is wrong with the input file. Examine error message by hand."
)
return {"errors": self.errors, "actions": None}
elif "failed_to_read_input" in self.errors:
# Almost certainly just a temporary problem that will not be encountered again. Rerun job as-is.
actions.append({"rerun job as-is"})
elif "IO_error" in self.errors:
# Almost certainly just a temporary problem that will not be encountered again. Rerun job as-is.
actions.append({"rerun job as-is"})
elif "read_molecule_error" in self.errors:
# Almost certainly just a temporary problem that will not be encountered again. Rerun job as-is.
actions.append({"rerun job as-is"})
elif "never_called_qchem" in self.errors:
# Almost certainly just a temporary problem that will not be encountered again. Rerun job as-is.
actions.append({"rerun job as-is"})
elif "unknown_error" in self.errors:
print("Examine error message by hand.")
return {"errors": self.errors, "actions": None}
else:
# You should never get here. If correct is being called then errors should have at least one entry,
# in which case it should have been caught by the if/elifs above.
print(
"If you get this message, something has gone terribly wrong!")
return {"errors": self.errors, "actions": None}
os.rename(self.input_file, self.input_file + ".last")
self.qcinp.write_file(self.input_file)
return {"errors": self.errors, "actions": actions}
def correct(self):
backup({self.input_file, self.output_file})
actions = []
self.qcinp = QCInput.from_file(self.input_file)
if "SCF_failed_to_converge" in self.errors:
# Check number of SCF cycles. If not set or less than scf_max_cycles,
# increase to that value and rerun. If already set, check if
# scf_algorithm is unset or set to DIIS, in which case set to GDM.
# Otherwise, tell user to call SCF error handler and do nothing.
if str(self.qcinp.rem.get("max_scf_cycles")) != str(
self.scf_max_cycles):
self.qcinp.rem["max_scf_cycles"] = self.scf_max_cycles
actions.append({"max_scf_cycles": self.scf_max_cycles})
elif self.qcinp.rem.get("scf_algorithm", "diis").lower() == "diis":
self.qcinp.rem["scf_algorithm"] = "gdm"
actions.append({"scf_algorithm": "gdm"})
elif self.qcinp.rem.get("scf_algorithm", "gdm").lower() == "gdm":
self.qcinp.rem["scf_algorithm"] = "diis_gdm"
actions.append({"scf_algorithm": "diis_gdm"})
else:
print(
"More advanced changes may impact the SCF result. Use the SCF error handler"
)
elif "out_of_opt_cycles" in self.errors:
# Check number of opt cycles. If less than geom_max_cycles, increase
# to that value, set last geom as new starting geom and rerun.
if str(self.qcinp.rem.get("geom_opt_max_cycles")) != str(
self.geom_max_cycles):
self.qcinp.rem["geom_opt_max_cycles"] = self.geom_max_cycles
actions.append({"geom_max_cycles:": self.scf_max_cycles})
if len(self.outdata.get("energy_trajectory")) > 1:
self.qcinp.molecule = self.outdata.get(
"molecule_from_last_geometry")
actions.append({"molecule": "molecule_from_last_geometry"})
# If already at geom_max_cycles, often can just get convergence by restarting
# from the geometry of the last cycle. But we'll also save any structural
# changes that happened along the way.
else:
self.opt_error_history += [self.outdata["structure_change"]]
if len(self.opt_error_history) > 1:
if self.opt_error_history[-1] == "no_change":
# If no structural changes occured in two consecutive optimizations,
# and we still haven't converged, then just exit.
return {
"errors": self.errors,
"actions": None,
"opt_error_history": self.opt_error_history
}
self.qcinp.molecule = self.outdata.get(
"molecule_from_last_geometry")
actions.append({"molecule": "molecule_from_last_geometry"})
elif "unable_to_determine_lamda" in self.errors:
# Set last geom as new starting geom and rerun. If no opt cycles,
# use diff SCF strat? Diff initial guess? Change basis?
if len(self.outdata.get("energy_trajectory")) > 1:
self.qcinp.molecule = self.outdata.get(
"molecule_from_last_geometry")
actions.append({"molecule": "molecule_from_last_geometry"})
elif self.qcinp.rem.get("scf_algorithm", "diis").lower() == "diis":
self.qcinp.rem["scf_algorithm"] = "rca_diis"
actions.append({"scf_algorithm": "rca_diis"})
if self.qcinp.rem.get("gen_scfman"):
self.qcinp.rem["gen_scfman"] = False
actions.append({"gen_scfman": False})
else:
print(
"Use a different initial guess? Perhaps a different basis?"
)
elif "linear_dependent_basis" in self.errors:
# DIIS -> RCA_DIIS. If already RCA_DIIS, change basis?
if self.qcinp.rem.get("scf_algorithm", "diis").lower() == "diis":
self.qcinp.rem["scf_algorithm"] = "rca_diis"
actions.append({"scf_algorithm": "rca_diis"})
if self.qcinp.rem.get("gen_scfman"):
self.qcinp.rem["gen_scfman"] = False
actions.append({"gen_scfman": False})
else:
print("Perhaps use a better basis?")
elif "failed_to_transform_coords" in self.errors:
# Check for symmetry flag in rem. If not False, set to False and rerun.
# If already False, increase threshold?
if not self.qcinp.rem.get("sym_ignore") or self.qcinp.rem.get(
"symmetry"):
self.qcinp.rem["sym_ignore"] = True
self.qcinp.rem["symmetry"] = False
actions.append({"sym_ignore": True})
actions.append({"symmetry": False})
else:
print("Perhaps increase the threshold?")
elif "input_file_error" in self.errors:
print(
"Something is wrong with the input file. Examine error message by hand."
)
return {"errors": self.errors, "actions": None}
elif "failed_to_read_input" in self.errors:
# Almost certainly just a temporary problem that will not be encountered again. Rerun job as-is.
actions.append({"rerun job as-is"})
elif "IO_error" in self.errors:
# Almost certainly just a temporary problem that will not be encountered again. Rerun job as-is.
actions.append({"rerun job as-is"})
elif "read_molecule_error" in self.errors:
# Almost certainly just a temporary problem that will not be encountered again. Rerun job as-is.
actions.append({"rerun job as-is"})
elif "never_called_qchem" in self.errors:
# Almost certainly just a temporary problem that will not be encountered again. Rerun job as-is.
actions.append({"rerun job as-is"})
elif "unknown_error" in self.errors:
print("Examine error message by hand.")
return {"errors": self.errors, "actions": None}
else:
# You should never get here. If correct is being called then errors should have at least one entry,
# in which case it should have been caught by the if/elifs above.
print(
"If you get this message, something has gone terribly wrong!")
return {"errors": self.errors, "actions": None}
os.rename(self.input_file, self.input_file + ".last")
self.qcinp.write_file(self.input_file)
return {"errors": self.errors, "actions": actions}
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 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 correct(self):
"""
Perform corrections
"""
backup({self.input_file, self.output_file})
actions = []
self.qcinp = QCInput.from_file(self.input_file)
if "SCF_failed_to_converge" in self.errors:
# Check number of SCF cycles. If not set or less than scf_max_cycles,
# increase to that value and rerun. If already set, check if
# scf_algorithm is unset or set to DIIS, in which case set to GDM.
# Otherwise, tell user to call SCF error handler and do nothing.
if str(self.qcinp.rem.get("max_scf_cycles")) != str(
self.scf_max_cycles):
self.qcinp.rem["max_scf_cycles"] = self.scf_max_cycles
actions.append({"max_scf_cycles": self.scf_max_cycles})
elif self.qcinp.rem.get("thresh", "10") != "14":
self.qcinp.rem["thresh"] = "14"
actions.append({"thresh": "14"})
elif self.qcinp.rem.get("scf_algorithm", "diis").lower() == "diis":
self.qcinp.rem["scf_algorithm"] = "diis_gdm"
actions.append({"scf_algorithm": "diis_gdm"})
elif self.qcinp.rem.get("scf_algorithm",
"diis").lower() == "diis_gdm":
self.qcinp.rem["scf_algorithm"] = "gdm"
actions.append({"scf_algorithm": "gdm"})
elif self.qcinp.rem.get("scf_guess_always",
"none").lower() != "true":
self.qcinp.rem["scf_guess_always"] = True
actions.append({"scf_guess_always": True})
else:
print(
"More advanced changes may impact the SCF result. Use the SCF error handler"
)
elif "out_of_opt_cycles" in self.errors:
# Check number of opt cycles. If less than geom_max_cycles, increase
# to that value, set last geom as new starting geom and rerun.
if str(self.qcinp.rem.get("geom_opt_max_cycles")) != str(
self.geom_max_cycles):
self.qcinp.rem["geom_opt_max_cycles"] = self.geom_max_cycles
actions.append({"geom_max_cycles:": self.scf_max_cycles})
if len(self.outdata.get("energy_trajectory")) > 1:
self.qcinp.molecule = self.outdata.get(
"molecule_from_last_geometry")
actions.append({"molecule": "molecule_from_last_geometry"})
elif self.qcinp.rem.get("thresh", "10") != "14":
self.qcinp.rem["thresh"] = "14"
actions.append({"thresh": "14"})
# Will need to try and implement this dmax handler below when I have more time
# to fix the tests and the general handling procedure.
# elif self.qcinp.rem.get("geom_opt_dmax",300) != 150:
# self.qcinp.rem["geom_opt_dmax"] = 150
# actions.append({"geom_opt_dmax": "150"})
# If already at geom_max_cycles, thresh 14, and dmax 150, often can just get convergence
# by restarting from the geometry of the last cycle. But we'll also save any structural
# changes that happened along the way.
else:
self.opt_error_history += [self.outdata["structure_change"]]
if len(self.opt_error_history) > 1:
if self.opt_error_history[-1] == "no_change":
# If no structural changes occurred in two consecutive optimizations,
# and we still haven't converged, then just exit.
return {
"errors": self.errors,
"actions": None,
"opt_error_history": self.opt_error_history,
}
self.qcinp.molecule = self.outdata.get(
"molecule_from_last_geometry")
actions.append({"molecule": "molecule_from_last_geometry"})
elif "unable_to_determine_lamda" in self.errors:
# Set last geom as new starting geom and rerun. If no opt cycles,
# use diff SCF start? Diff initial guess? Change basis? Unclear.
if len(self.outdata.get("energy_trajectory")) > 1:
self.qcinp.molecule = self.outdata.get(
"molecule_from_last_geometry")
actions.append({"molecule": "molecule_from_last_geometry"})
elif self.qcinp.rem.get("thresh", "10") != "14":
self.qcinp.rem["thresh"] = "14"
actions.append({"thresh": "14"})
else:
print(
"Use a different initial guess? Perhaps a different basis?"
)
elif "premature_end_FileMan_error" in self.errors:
if self.qcinp.rem.get("thresh", "10") != "14":
self.qcinp.rem["thresh"] = "14"
actions.append({"thresh": "14"})
elif self.qcinp.rem.get("scf_guess_always",
"none").lower() != "true":
self.qcinp.rem["scf_guess_always"] = True
actions.append({"scf_guess_always": True})
else:
print(
"We're in a bad spot if we get a FileMan error while always generating a new SCF guess..."
)
elif "hessian_eigenvalue_error" in self.errors:
if self.qcinp.rem.get("thresh", "10") != "14":
self.qcinp.rem["thresh"] = "14"
actions.append({"thresh": "14"})
else:
print(
"Not sure how to fix hessian_eigenvalue_error if thresh is already 14!"
)
elif "NLebdevPts" in self.errors:
# this error should only be possible if resp_charges or esp_charges is set
if self.qcinp.rem.get("resp_charges") or self.qcinp.rem.get(
"esp_charges"):
# This error is caused by insufficient no. of Lebedev points on
# the grid used to compute RESP charges
# Increase the density of points on the Lebedev grid using the
# esp_surface_density argument (see manual >= v5.4)
# the default value is 500 (=0.001 Angstrom)
# or disable RESP charges as a last resort
if int(self.qcinp.rem.get("esp_surface_density", 500)) >= 500:
self.qcinp.rem["esp_surface_density"] = "250"
actions.append({"esp_surface_density": "250"})
elif int(self.qcinp.rem.get("esp_surface_density",
250)) >= 250:
self.qcinp.rem["esp_surface_density"] = "125"
actions.append({"esp_surface_density": "125"})
elif int(self.qcinp.rem.get("esp_surface_density",
125)) >= 125:
# switch from Lebedev mode to spherical harmonics mode
if self.qcinp.rem.get("resp_charges"):
self.qcinp.rem["resp_charges"] = "2"
actions.append({"resp_charges": "2"})
if self.qcinp.rem.get("esp_charges"):
self.qcinp.rem["esp_charges"] = "2"
actions.append({"esp_charges": "2"})
else:
if self.qcinp.rem.get("resp_charges"):
self.qcinp.rem["resp_charges"] = "false"
actions.append({"resp_charges": "false"})
if self.qcinp.rem.get("esp_charges"):
self.qcinp.rem["esp_charges"] = "false"
actions.append({"esp_charges": "false"})
else:
print(
"Not sure how to fix NLebdevPts error if resp_charges is disabled!"
)
elif "failed_to_transform_coords" in self.errors:
# Check for symmetry flag in rem. If not False, set to False and rerun.
# If already False, increase threshold?
if not self.qcinp.rem.get("sym_ignore") or self.qcinp.rem.get(
"symmetry"):
self.qcinp.rem["sym_ignore"] = True
self.qcinp.rem["symmetry"] = False
actions.append({"sym_ignore": True})
actions.append({"symmetry": False})
else:
print("Perhaps increase the threshold?")
elif "basis_not_supported" in self.errors:
print(
"Specify a different basis set. At least one of the atoms is not supported."
)
return {"errors": self.errors, "actions": None}
elif "input_file_error" in self.errors:
print(
"Something is wrong with the input file. Examine error message by hand."
)
return {"errors": self.errors, "actions": None}
elif "failed_to_read_input" in self.errors:
# Almost certainly just a temporary problem that will not be encountered again. Rerun job as-is.
actions.append({"rerun_job_no_changes": True})
elif "read_molecule_error" in self.errors:
# Almost certainly just a temporary problem that will not be encountered again. Rerun job as-is.
actions.append({"rerun_job_no_changes": True})
elif "never_called_qchem" in self.errors:
# Almost certainly just a temporary problem that will not be encountered again. Rerun job as-is.
actions.append({"rerun_job_no_changes": True})
elif "licensing_error" in self.errors:
# Almost certainly just a temporary problem that will not be encountered again. Rerun job as-is.
actions.append({"rerun_job_no_changes": True})
elif "unknown_error" in self.errors:
if self.qcinp.rem.get("scf_guess", "none").lower() == "read":
del self.qcinp.rem["scf_guess"]
actions.append({"scf_guess": "deleted"})
elif self.qcinp.rem.get("thresh", "10") != "14":
self.qcinp.rem["thresh"] = "14"
actions.append({"thresh": "14"})
else:
print("Unknown error. Examine output and log files by hand.")
return {"errors": self.errors, "actions": None}
else:
# You should never get here. If correct is being called then errors should have at least one entry,
# in which case it should have been caught by the if/elifs above.
print("Errors:", self.errors)
print(
"Must have gotten an error which is correctly parsed but not included in the handler. FIX!!!"
)
return {"errors": self.errors, "actions": None}
if {
"molecule": "molecule_from_last_geometry"
} in actions and str(
self.qcinp.rem.get("geom_opt_hessian")).lower() == "read":
del self.qcinp.rem["geom_opt_hessian"]
actions.append({"geom_opt_hessian": "deleted"})
os.rename(self.input_file, self.input_file + ".last")
self.qcinp.write_file(self.input_file)
return {
"errors": self.errors,
"warnings": self.warnings,
"actions": actions
}
def correct(self):
backup(FEFF_BACKUP_FILES)
feff_input = FEFFDictSet.from_directory(".")
scf_values = feff_input.tags.get("SCF")
nscmt = scf_values[2]
ca = scf_values[3]
nmix = scf_values[4]
actions = []
if nscmt < 100 and ca == 0.2:
scf_values[2] = 100
scf_values[4] = 3 # Set nmix = 3
actions.append({
"dict": "PARAMETERS",
"action": {
"_set": {
"SCF": scf_values
}
}
})
FeffModder().apply_actions(actions)
return {"errors": ["Non-converging job"], "actions": actions}
elif nscmt == 100 and nmix == 3 and ca > 0.01:
# Reduce the convergence accelerator factor
scf_values[3] = round(ca / 2, 2)
actions.append({
"dict": "PARAMETERS",
"action": {
"_set": {
"SCF": scf_values
}
}
})
FeffModder().apply_actions(actions)
return {"errors": ["Non-converging job"], "actions": actions}
elif nmix == 3 and ca == 0.01:
# Set ca = 0.05 and set nmix
scf_values[3] = 0.05
scf_values[4] = 5
actions.append({
"dict": "PARAMETERS",
"action": {
"_set": {
"SCF": scf_values
}
}
})
FeffModder().apply_actions(actions)
return {"errors": ["Non-converging job"], "actions": actions}
elif nmix == 5 and ca == 0.05:
# Set ca = 0.05 and set nmix
scf_values[3] = 0.05
scf_values[4] = 10
actions.append({
"dict": "PARAMETERS",
"action": {
"_set": {
"SCF": scf_values
}
}
})
FeffModder().apply_actions(actions)
return {"errors": ["Non-converging job"], "actions": actions}
elif nmix == 10 and ca < 0.2:
# loop through ca with nmix = 10
scf_values[3] = round(ca * 2, 2)
actions.append({
"dict": "PARAMETERS",
"action": {
"_set": {
"SCF": scf_values
}
}
})
FeffModder().apply_actions(actions)
return {"errors": ["Non-converging job"], "actions": actions}
# Unfixable error. Just return None for actions.
else:
return {"errors": ["Non-converging job"], "actions": None}
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.
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.
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"]):
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}}})
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"}}})
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:
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 correct(self):
backup(AIMS_BACKUP_FILES | {self.output_filename})
actions = []
return {"errors": ["Non-convergent"], "actions": actions}
def postprocess(self):
"""
Renaming or gzipping all the output as needed
"""
if self.gzipped:
backup("*", prefix=self.gzipped_prefix)
