if 'fine_grid' in job_types:
del job_types['fine_grid']
- defaults_to_true = ['conformers', 'fine', 'freq', 'irc', 'opt', 'rotors', 'sp']
- defaults_to_false = ['bde', 'onedmin', 'orbitals']
+ defaults_to_true = ['conf_opt', 'fine', 'freq', 'irc', 'opt', 'rotors', 'sp']
+ defaults_to_false = ['conf_sp', 'bde', 'onedmin', 'orbitals']
if job_types is None:
job_types = default_job_types
logger.info("Job types were not specified, using ARC's defaults")
@@ -920,9 +920,7 @@ Source code for arc.common
Returns: Optional[Union[int, None]]
The entry with the minimal/maximal value.
"""
- if len(lst) == 0:
- return None
- elif all([entry is None for entry in lst]):
+ if lst is None or len(lst) == 0 or all([entry is None for entry in lst]):
return None
elif len(lst) == 1:
return lst[0]
diff --git a/_modules/arc/job/trsh.html b/_modules/arc/job/trsh.html
index 9f4bb365b5..ae48faa117 100644
--- a/_modules/arc/job/trsh.html
+++ b/_modules/arc/job/trsh.html
@@ -168,11 +168,11 @@ Source code for arc.job.trsh
import math
import os
-import re
from typing import List, Optional, Tuple, Union
import numpy as np
import pandas as pd
+import re
from arc.common import (check_torsion_change,
convert_to_hours,
@@ -182,19 +182,18 @@ Source code for arc.job.trsh
get_number_with_ordinal_indicator,
is_same_pivot,
is_same_sequence_sublist,
- is_str_float,
+ is_str_float
)
from arc.exceptions import InputError, SpeciesError, TrshError
from arc.imports import settings
+from arc.level import Level
from arc.job.local import execute_command
from arc.job.ssh import SSHClient
-from arc.level import Level
from arc.species import ARCSpecies
from arc.species.conformers import determine_smallest_atom_index_in_scan
-from arc.species.converter import displace_xyz, ics_to_scan_constraints
+from arc.species.converter import (displace_xyz, ics_to_scan_constraints)
from arc.species.species import determine_rotor_symmetry
from arc.species.vectors import calculate_dihedral_angle, calculate_distance
-
from arc.parser import (parse_1d_scan_coords,
parse_normal_mode_displacement,
parse_scan_args,
@@ -202,6 +201,7 @@ Source code for arc.job.trsh
parse_xyz_from_file,
)
+
logger = get_logger()
@@ -256,14 +256,21 @@ Source code for arc.job.trsh
if 'termination' in line:
if 'l9999.exe' in line or 'link 9999' in line:
cycle_issue = False
+ neg_eigenvalues = False
for j in range(i,len(reverse_lines)):
if 'Number of steps exceeded' in reverse_lines[j]:
- keywords = ['MaxOptCycles', 'GL9999', 'SCF']
+ keywords = ['MaxOptCycles', 'GL9999']
error = 'Maximum optimization cycles reached.'
cycle_issue = True
line = 'Number of steps exceeded'
break
- if not cycle_issue:
+ elif "Wrong number of Negative eigenvalues" in reverse_lines[j]:
+ keywords = ['NegEigenvalues', 'GL9999']
+ error = 'Wrong number of Negative eigenvalues'
+ neg_eigenvalues = True
+ line = 'Wrong number of Negative eigenvalues'
+ break
+ if not cycle_issue and not neg_eigenvalues:
keywords = ['Unconverged', 'GL9999'] # GL stand for Gaussian Link
error = 'Unconverged'
elif 'l101.exe' in line:
@@ -312,6 +319,22 @@ Source code for arc.job.trsh
elif 'l913.exe' in line:
keywords = ['MaxOptCycles', 'GL913']
error = 'Maximum optimization cycles reached.'
+ elif 'l123.exe' in line:
+ delta_x = False
+ gs2_opt = False
+ for j in range(i + 1, len(reverse_lines)):
+ if 'Delta-x Convergence NOT Met' in reverse_lines[j]:
+ delta_x = True
+ keywords = ['DeltaX', 'GL123']
+ error = 'Delta-x Convergence NOT Met'
+ line = 'Delta-x Convergence NOT Met'
+ break
+ elif 'GS2 Optimization Failure' in reverse_lines[j]:
+ gs2_opt = True
+ keywords = ['GS2Opt', 'GL123']
+ error = 'GS2 Optimization Failure'
+ line = 'GS2 Optimization Failure'
+ break
if any([keyword in ['GL301', 'GL401'] for keyword in keywords]):
additional_info = forward_lines[len(forward_lines) - i - 2]
if 'No data on chk file' in additional_info \
@@ -370,7 +393,7 @@ Source code for arc.job.trsh
done = True
# If this is an opt job, we must also check that the max num of cycles hasn't been reached,
# so don't break yet.
- if 'opt' not in job_type and 'conformer' not in job_type and 'ts' not in job_type:
+ if 'opt' not in job_type and 'conf_opt' not in job_type and 'ts' not in job_type:
break
elif 'SCF failed' in line:
keywords = ['SCF']
@@ -386,7 +409,7 @@ Source code for arc.job.trsh
elif 'Invalid charge/multiplicity combination' in line:
raise SpeciesError(f'The multiplicity and charge combination for species '
f'{species_label} are wrong.')
- if 'opt' in job_type or 'conformer' in job_type or 'ts' in job_type:
+ if 'opt' in job_type or 'conf_opt' in job_type or 'ts' in job_type:
if 'MAXIMUM OPTIMIZATION CYCLES REACHED' in line:
keywords = ['MaxOptCycles']
error = 'Maximum optimization cycles reached.'
@@ -1041,7 +1064,6 @@ Source code for arc.job.trsh
logger_phrase = f'Troubleshooting {job_type} job in {software} for {label}'
logger_info = []
couldnt_trsh = True
- fine = False
attempted_ess_trsh_methods = ess_trsh_methods.copy() if ess_trsh_methods else None
# Check if Checkfile removal is in the keywords. Removal occurs when:
# - Basis Set Mismatch
@@ -1061,14 +1083,12 @@ Source code for arc.job.trsh
# Check if SCF is in the keyword
ess_trsh_methods, trsh_keyword, couldnt_trsh = trsh_keyword_scf(job_status, ess_trsh_methods, trsh_keyword, couldnt_trsh)
- if 'scf=(maxcycle=512)' in ess_trsh_methods:
- logger_info.append('using scf=(maxcycle=512)')
- if 'scf=(NDamp=30)' in ess_trsh_methods:
- logger_info.append('using scf=(NDamp=30)')
- if 'scf=(qc)' in ess_trsh_methods:
- logger_info.append('using scf=(qc)')
- if 'scf=(NoDIIS)' in ess_trsh_methods:
- logger_info.append('using scf=(NoDIIS)')
+ scf_list = [i for i in ess_trsh_methods if i.startswith('scf=')]
+ if scf_list:
+ formatted_string = f'using {scf_list[0]}'
+ for i in scf_list[1:]:
+ formatted_string += f', {i}'
+ logger_info.append(formatted_string)
# Check if InaccurateQuadrature in the keyword
ess_trsh_methods, trsh_keyword, couldnt_trsh = trsh_keyword_inaccurate_quadrature(job_status, ess_trsh_methods, trsh_keyword, couldnt_trsh)
@@ -1082,14 +1102,35 @@ Source code for arc.job.trsh
ess_trsh_methods, trsh_keyword, fine, couldnt_trsh = trsh_keyword_unconverged(job_status, ess_trsh_methods, trsh_keyword, couldnt_trsh, fine)
if fine:
logger_info.append('using a fine grid')
+
+ # Check if NegEigenvalues is in the keyword
+ ess_trsh_methods, trsh_keyword, couldnt_trsh = trsh_keyword_neg_eigen(job_status, ess_trsh_methods, trsh_keyword, couldnt_trsh)
# Troubleshoot by increasing opt max cycles
#P opt=(calcfc,maxstep=5,tight,maxcycle=200) guess=mix wb97xd/def2tzvp integral=(grid=ultrafine, Acc2E=14) IOp(2/9=2000) scf=(direct,tight,maxcycle=512) iop(3/33=1)
ess_trsh_methods, trsh_keyword, couldnt_trsh = trsh_keyword_opt_maxcycles(job_status, ess_trsh_methods, trsh_keyword, couldnt_trsh)
- if 'opt=(maxcycle=200)' in ess_trsh_methods:
- logger_info.append('using opt=(maxcycle=200)')
+ # print out any words that beging with 'opt='
+ opt_list = [i for i in ess_trsh_methods if i.startswith('opt=')]
+ if opt_list:
+ formatted_string = f'using {opt_list[0]}'
+ for i in opt_list[1:]:
+ formatted_string += f', {i}'
+ logger_info.append(formatted_string)
+
+ # Check for L123 errors
+ ess_trsh_methods, trsh_keyword, couldnt_trsh = trsh_keyword_l123(job_status, ess_trsh_methods, trsh_keyword, couldnt_trsh)
+ irc_list = [i for i in ess_trsh_methods if i.startswith('irc=')]
+ if irc_list:
+ formatted_string = f'using {irc_list[0]}'
+ for i in irc_list[1:]:
+ formatted_string += f', {i}'
+ logger_info.append(formatted_string)
+
+ # Remove qc from ess_trsh_methods if 'no_qc' is in the keywords
+ ess_trsh_methods, trsh_keyword, couldnt_trsh = trsh_keyword_no_qc(job_status, ess_trsh_methods, trsh_keyword, couldnt_trsh)
+ if 'no_qc' in ess_trsh_methods:
+ logger_info.append('removed QC')
-
# Check if memory is in the keyword
if 'Memory' in job_status['keywords'] and 'too high' not in job_status['error'] and server is not None:
@@ -1105,6 +1146,7 @@ Source code for arc.job.trsh
if attempted_ess_trsh_methods:
if attempted_ess_trsh_methods == ess_trsh_methods:
logger.info(f'{logger_phrase} was not successful. Already attempted all possible troubleshooting methods. Will not troubleshoot again.')
+ ess_trsh_methods.append("all_attempted")
couldnt_trsh = True
else:
if logger_info:
@@ -1929,7 +1971,7 @@ Source code for arc.job.trsh
Check if the job requires change of cartesian coordinate
"""
if 'InternalCoordinateError' in job_status['keywords'] \
- and 'cartesian' not in ess_trsh_methods and job_type == 'opt':
+ and 'cartesian' not in ess_trsh_methods:
ess_trsh_methods.append('cartesian')
trsh_keyword.append('opt=(cartesian)')
couldnt_trsh = False
@@ -1945,7 +1987,7 @@ Source code for arc.job.trsh
Check if the job requires change of scf
"""
scf_pattern = r"scf=\((.*?)\)" # e.g., scf=(xqc,MaxCycle=1000), will match xqc,MaxCycle=1000
- if 'SCF' in job_status['keywords'] and 'scf=(qc)' not in ess_trsh_methods:
+ if 'SCF' in job_status['keywords'] and 'scf=(qc)' not in ess_trsh_methods and 'no_qc' not in ess_trsh_methods:
# try both qc and nosymm
ess_trsh_methods.append('scf=(qc)')
couldnt_trsh = False
@@ -1962,7 +2004,7 @@ Source code for arc.job.trsh
couldnt_trsh = False
trsh_keyword.append('guess=INDO')
# If we have attempted all scf methods above, then we will try last resort methods
- if 'SCF' in job_status['keywords'] and 'scf=(maxcycle=128)' in ess_trsh_methods and 'scf=(qc)' in ess_trsh_methods and 'scf=(NDamp=30)' in ess_trsh_methods and 'scf=(NoDIIS)' in ess_trsh_methods and 'guess=INDO' in ess_trsh_methods \
+ if 'SCF' in job_status['keywords'] and 'scf=(qc)' in ess_trsh_methods and 'scf=(NDamp=30)' in ess_trsh_methods and 'scf=(NoDIIS)' in ess_trsh_methods and 'guess=INDO' in ess_trsh_methods \
and 'scf=(Fermi)' not in ess_trsh_methods and 'scf=(Noincfock)' not in ess_trsh_methods and 'scf=(NoVarAcc)' not in ess_trsh_methods:
# Uses Fermi broadening to help SCF convergence
ess_trsh_methods.append('scf=(Fermi)')
@@ -1970,6 +2012,9 @@ Source code for arc.job.trsh
ess_trsh_methods.append('scf=(Noincfock)')
ess_trsh_methods.append('scf=(NoVarAcc)')
couldnt_trsh = False
+ if 'no_qc' in ess_trsh_methods and 'scf=(qc)' in ess_trsh_methods:
+ ess_trsh_methods.remove('scf=(qc)')
+ couldnt_trsh = False
if any('scf' in keyword for keyword in ess_trsh_methods):
scf_list = [match for element in ess_trsh_methods for match in re.findall(scf_pattern, element)] if any(re.search(scf_pattern, element) for element in ess_trsh_methods) else []
@@ -1986,8 +2031,6 @@ Source code for arc.job.trsh
ess_trsh_methods.append('fine')
fine = True
couldnt_trsh = False
- else:
- fine = False
return ess_trsh_methods, trsh_keyword, fine, couldnt_trsh
@@ -2009,11 +2052,34 @@ Source code for arc.job.trsh
"""
Check if the job requires change of opt(maxcycle=200)
"""
-
- if 'MaxOptCycles' in job_status['keywords'] and 'opt=(maxcycles=200)' not in ess_trsh_methods:
+ opt_pattern = r"opt=\((.*?)\)"
+ if 'MaxOptCycles' in job_status['keywords'] and 'opt=(maxcycle=200)' not in ess_trsh_methods:
ess_trsh_methods.append('opt=(maxcycle=200)')
trsh_keyword.append('opt=(maxcycle=200)')
couldnt_trsh = False
+ elif 'MaxOptCycles' in job_status['keywords'] and 'opt=(RFO)' not in ess_trsh_methods:
+ ess_trsh_methods.append('opt=(RFO)')
+ trsh_keyword.append('opt=(RFO)')
+ couldnt_trsh = False
+ elif 'MaxOptCycles' in job_status['keywords'] and 'opt=(RFO)' in ess_trsh_methods and 'opt=(GDIIS)' not in ess_trsh_methods:
+ ess_trsh_methods.append('opt=(GDIIS)')
+ trsh_keyword.append('opt=(GDIIS)')
+ couldnt_trsh = False
+ elif 'MaxOptCycles' in job_status['keywords'] and 'opt=(RFO)' in ess_trsh_methods and 'opt=(GDIIS)' in ess_trsh_methods and 'opt=(GEDIIS)' not in ess_trsh_methods:
+ ess_trsh_methods.append('opt=(GEDIIS)')
+ trsh_keyword.append('opt=(GEDIIS)')
+ couldnt_trsh = False
+
+ if any('opt' in keyword for keyword in ess_trsh_methods):
+ opt_list = [match for element in ess_trsh_methods for match in re.findall(opt_pattern, element)] if any(re.search(opt_pattern, element) for element in ess_trsh_methods) else []
+
+ if opt_list:
+
+ filtered_methods = prioritize_opt_methods(opt_list)
+
+ new_opt_keyword = 'opt=(' + ','.join(filtered_methods) + ')'
+
+ trsh_keyword = [kw if not kw.startswith('opt') else new_opt_keyword for kw in trsh_keyword]
return ess_trsh_methods, trsh_keyword, couldnt_trsh
@@ -2059,6 +2125,72 @@ Source code for arc.job.trsh
scf_list = [match for element in ess_trsh_methods for match in re.findall(scf_pattern, element)] if any(re.search(scf_pattern, element) for element in ess_trsh_methods) else []
trsh_keyword.append('scf=(' + ','.join(scf_list) + ')')
+ return ess_trsh_methods, trsh_keyword, couldnt_trsh
+
+[docs]def trsh_keyword_l123(job_status, ess_trsh_methods, trsh_keyword, couldnt_trsh) -> Tuple[List, List, bool]:
+ """
+ When a job fails with l123.exe error, there are two possible solutions based upon the error message:
+ 1. If Delta-X issue, will need to adjust the maxcycle of IRC job. If fails, then change algorithm to LQA.
+ 2. GS2 Optimization failed, then try to change the algorithm to LQA.
+ """
+ irc_pattern = r"irc=\((.*?)\)"
+ if 'DeltaX' in job_status['keywords'] and 'irc=(maxcycle=200)' not in ess_trsh_methods:
+ ess_trsh_methods.append('irc=(maxcycle=200)')
+ trsh_keyword.append('irc=(maxcycle=200)')
+ couldnt_trsh = False
+ elif 'DeltaX' in job_status['keywords'] and 'irc=(LQA)' not in ess_trsh_methods:
+ ess_trsh_methods.append('irc=(LQA)')
+ trsh_keyword.append('irc=(LQA)')
+ couldnt_trsh = False
+ elif 'GS2Opt' in job_status['keywords'] and 'irc=(LQA)' not in ess_trsh_methods:
+ ess_trsh_methods.append('irc=(LQA)')
+ trsh_keyword.append('irc=(LQA)')
+ couldnt_trsh = False
+
+ if any('irc' in keyword for keyword in ess_trsh_methods):
+ scf_list = [match for element in ess_trsh_methods for match in re.findall(irc_pattern, element)] if any(re.search(irc_pattern, element) for element in ess_trsh_methods) else []
+ trsh_keyword.append('irc=(' + ','.join(scf_list) + ')')
+
+ return ess_trsh_methods, trsh_keyword, couldnt_trsh
+
+[docs]def trsh_keyword_neg_eigen(job_status, ess_trsh_methods, trsh_keyword, couldnt_trsh) -> Tuple[List, List, bool]:
+ """
+ Gaussian will check the number of negative frequency after finishing the TS optimization.
+ If there is more than one negative frequency, Gaussian will stop the calculation.
+ """
+ if 'NegEigenvalues' in job_status['keywords'] and 'opt=(noeigen)' not in ess_trsh_methods:
+ ess_trsh_methods.append('opt=(noeigen)')
+ trsh_keyword.append('opt=(noeigen)')
+ couldnt_trsh = False
+
+ return ess_trsh_methods, trsh_keyword, couldnt_trsh
+
+def prioritize_opt_methods(opt_methods):
+
+ preferred_order = ['GEDIIS', 'GDIIS', 'RFO']
+ selected_method = None
+
+ for method in preferred_order:
+ if method in opt_methods:
+ selected_method = method
+ break
+
+ filtered_methods = [method for method in opt_methods if method not in preferred_order or method == selected_method]
+
+ return filtered_methods
+
+[docs]def trsh_keyword_no_qc(job_status, ess_trsh_methods, trsh_keyword, couldnt_trsh) -> Tuple[List, List, bool]:
+ """
+ When a job fails with no qc, there are two possible solutions based upon the error message:
+ 1. If SCF fails, then try to change the algorithm to LQA.
+ 2. If SCF fails, then try to change the algorithm to LQA.
+ """
+ if 'no_xqc' in job_status['keywords'] and 'scf=(qc)' in ess_trsh_methods:
+ ess_trsh_methods.remove('scf=(qc)')
+ ess_trsh_methods.append('no_xqc')
+ couldnt_trsh = False
+
+
return ess_trsh_methods, trsh_keyword, couldnt_trsh
diff --git a/_modules/arc/main.html b/_modules/arc/main.html
index 6f2532aa76..871337aaad 100644
--- a/_modules/arc/main.html
+++ b/_modules/arc/main.html
@@ -244,6 +244,8 @@ Source code for arc.main
instead (e.g., ``opt_level``).
composite_method (str, dict, Level, optional): Composite method.
conformer_level (str, dict, Level, optional): Level of theory for conformer searches.
+ conformer_opt_level (str, dict, Level, optional): Level of theory for conformer searches, interchangable with `conformer_level`.
+ conformer_sp_level (str, dict, Level, optional): Level of theory for conformer sp jobs after opt.
opt_level (str, dict, Level, optional): Level of theory for geometry optimization.
freq_level (str, dict, Level, optional): Level of theory for frequency calculations.
sp_level (str, dict, Level, optional): Level of theory for single point calculations.
@@ -331,7 +333,8 @@ Source code for arc.main
reactions (list): A list of :ref:`ARCReaction <reaction>` objects.
level_of_theory (str): A shortcut representing either sp//geometry levels or a composite method.
composite_method (Level): Composite method.
- conformer_level (Level): Level of theory for conformer searches.
+ conformer_opt_level (Level): Level of theory for conformer searches.
+ conformer_sp_level (Level): Level of theory for conformer sp jobs after opt.
opt_level (Level): Level of theory for geometry optimization.
freq_level (Level): Level of theory for frequency calculations.
sp_level (Level): Level of theory for single point calculations.
@@ -409,6 +412,8 @@ Source code for arc.main
compute_thermo: bool = True,
compute_transport: bool = False,
conformer_level: Optional[Union[str, dict, Level]] = None,
+ conformer_opt_level: Optional[Union[str, dict, Level]] = None,
+ conformer_sp_level: Optional[Union[str, dict, Level]] = None,
dont_gen_confs: List[str] = None,
e_confs: float = 5.0,
ess_settings: Dict[str, Union[str, List[str]]] = None,
@@ -510,7 +515,8 @@ Source code for arc.main
# attributes related to level of theory specifications
self.level_of_theory = level_of_theory
self.composite_method = composite_method or None
- self.conformer_level = conformer_level or None
+ self.conformer_opt_level = conformer_level or conformer_opt_level or None
+ self.conformer_sp_level = conformer_sp_level or None
self.opt_level = opt_level or None
self.freq_level = freq_level or None
self.sp_level = sp_level or None
@@ -653,8 +659,10 @@ Source code for arc.main
restart_dict['compute_thermo'] = self.compute_thermo
if self.compute_transport:
restart_dict['compute_transport'] = self.compute_transport
- if self.conformer_level is not None and str(self.conformer_level).split()[0] != default_levels_of_theory['conformer']:
- restart_dict['conformer_level'] = self.conformer_level.as_dict()
+ if self.conformer_opt_level is not None:
+ restart_dict['conformer_opt_level'] = self.conformer_opt_level.as_dict()
+ if self.conformer_sp_level is not None:
+ restart_dict['conformer_sp_level'] = self.conformer_sp_level.as_dict()
if self.dont_gen_confs:
restart_dict['dont_gen_confs'] = self.dont_gen_confs
if self.ts_adapters is not None:
@@ -772,7 +780,8 @@ Source code for arc.main
species_list=self.species,
rxn_list=self.reactions,
composite_method=self.composite_method,
- conformer_level=self.conformer_level,
+ conformer_opt_level=self.conformer_opt_level,
+ conformer_sp_level=self.conformer_sp_level,
opt_level=self.opt_level,
freq_level=self.freq_level,
sp_level=self.sp_level,
@@ -853,7 +862,8 @@ Source code for arc.main
txt = ''
txt += f'ARC v{self.__version__}\n'
txt += f'ARC project {self.project}\n\nLevels of theory used:\n\n'
- txt += f'Conformers: {self.conformer_level}\n'
+ txt += f'Conformer optimization: {self.conformer_opt_level}\n'
+ txt += f'Conformer single point: {self.conformer_sp_level}\n'
txt += f'TS guesses: {self.ts_guess_level}\n'
if self.composite_method is not None:
txt += f'Composite method: {self.composite_method} {fine_txt}\n'
@@ -1139,13 +1149,17 @@ Source code for arc.main
logger.info('\n\nUsing the following levels of theory:\n')
- if self.conformer_level is None:
- self.conformer_level = default_levels_of_theory['conformer']
+ if self.conformer_opt_level is None:
+ self.conformer_opt_level = default_levels_of_theory['conformer']
default_flag = ' (default)'
else:
default_flag = ''
- self.conformer_level = Level(repr=self.conformer_level)
- logger.info(f'Conformers:{default_flag} {self.conformer_level}')
+ self.conformer_opt_level = Level(repr=self.conformer_opt_level)
+ logger.info(f'Conformers opt:{default_flag} {self.conformer_opt_level}')
+
+ if self.conformer_sp_level is not None:
+ self.conformer_sp_level = Level(repr=self.conformer_sp_level)
+ logger.info(f'Conformers sp: {self.conformer_sp_level}')
if self.reactions or any([spc.is_ts for spc in self.species]):
if not self.ts_guess_level:
diff --git a/_modules/arc/plotter.html b/_modules/arc/plotter.html
index 98fb573cb8..0b438533c0 100644
--- a/_modules/arc/plotter.html
+++ b/_modules/arc/plotter.html
@@ -1064,6 +1064,8 @@ Source code for arc.plotter
ts_methods: Optional[List[str]] = None,
im_freqs: Optional[List[List[float]]] = None,
log_content: bool = False,
+ before_optimization: bool = True,
+ sp_flag = False,
):
"""
Save the conformers before or after optimization.
@@ -1082,23 +1084,28 @@ Source code for arc.plotter
ts_methods (list, optional): Entries are method names used to generate the TS guess.
im_freqs (list, optional): Entries lists of imaginary frequencies.
log_content (bool): Whether to log the content of the conformers file. ``True`` to log, default is ``False``.
+ before_optimization (bool): Whether the conformers are before DFT optimization. ``True`` for before, default is ``True``.
+ sp_flag (bool): Whether the conformers are single point calculations. ``True`` for single point, default is ``False``.
"""
spc_dir = 'rxns' if is_ts else 'Species'
geo_dir = os.path.join(project_directory, 'output', spc_dir, label, 'geometry', 'conformers')
if not os.path.exists(geo_dir):
os.makedirs(geo_dir)
- if energies is not None and any(e is not None for e in energies):
- optimized = True
- min_e = extremum_list(energies, return_min=True)
- conf_path = os.path.join(geo_dir, 'conformers_after_optimization.txt')
- else:
- optimized = False
+ if before_optimization:
conf_path = os.path.join(geo_dir, 'conformers_before_optimization.txt')
+ else:
+ conf_path = os.path.join(geo_dir, 'conformers_after_optimization.txt')
+ min_e = extremum_list(energies, return_min=True)
with open(conf_path, 'w') as f:
content = ''
- if optimized:
+ if before_optimization:
+ content += f'Conformers for {label}, computed using a force field:\n\n'
+ else:
level_of_theory = level_of_theory.simple() if isinstance(level_of_theory, Level) else level_of_theory
- content += f'Conformers for {label}, optimized at the {level_of_theory} level:\n\n'
+ if not sp_flag:
+ content += f'Conformers for {label}, optimized at the {level_of_theory} level:\n\n'
+ else:
+ content += f'Conformers for {label}, single point calculation at the {level_of_theory} level:\n\n'
for i, xyz in enumerate(xyzs):
content += f'conformer {i}:\n'
if xyz is not None:
@@ -1114,7 +1121,7 @@ Source code for arc.plotter
content += f'TS guess method: {ts_methods[i]}\n'
if im_freqs is not None and im_freqs[i] is not None:
content += f'Imaginary frequencies: {im_freqs[i]}\n'
- if optimized:
+ if min_e is not None:
if energies[i] == min_e:
content += 'Relative Energy: 0 kJ/mol (lowest)'
elif energies[i] is not None:
diff --git a/_modules/arc/scheduler.html b/_modules/arc/scheduler.html
index 478197c1d7..2756801e4e 100644
--- a/_modules/arc/scheduler.html
+++ b/_modules/arc/scheduler.html
@@ -243,7 +243,9 @@ Source code for arc.scheduler
Dictionary structures::
- job_dict = {label_1: {'conformers': {0: Job1,
+ job_dict = {label_1: {'conf_opt': {0: Job1,
+ 1: Job2, ...},
+ 'conf_sp': {0: Job1,
1: Job2, ...},
'tsg': {0: Job1,
1: Job2, ...}, # TS guesses
@@ -294,7 +296,8 @@ Source code for arc.scheduler
rxn_list (list): Contains input :ref:`ARCReaction <reaction>` objects.
project_directory (str): Folder path for the project: the input file path or ARC/Projects/project-name.
composite_method (str, optional): A composite method to use.
- conformer_level (Union[str, dict], optional): The level of theory to use for conformer comparisons.
+ conformer_opt_level (Union[str, dict], optional): The level of theory to use for conformer comparisons.
+ conformer_sp_level (Union[str, dict], optional): The level of theory to use for conformer sp jobs.
opt_level (Union[str, dict], optional): The level of theory to use for geometry optimizations.
freq_level (Union[str, dict], optional): The level of theory to use for frequency calculations.
sp_level (Union[str, dict], optional): The level of theory to use for single point energy calculations.
@@ -366,7 +369,8 @@ Source code for arc.scheduler
bath_gas (str): A bath gas. Currently used in OneDMin to calc L-J parameters.
Allowed values are He, Ne, Ar, Kr, H2, N2, O2.
composite_method (str): A composite method to use.
- conformer_level (dict): The level of theory to use for conformer comparisons.
+ conformer_opt_level (dict): The level of theory to use for conformer comparisons.
+ conformer_sp_level (dict): The level of theory to use for conformer sp jobs.
opt_level (dict): The level of theory to use for geometry optimizations.
freq_level (dict): The level of theory to use for frequency calculations.
sp_level (dict): The level of theory to use for single point energy calculations.
@@ -394,7 +398,8 @@ Source code for arc.scheduler
species_list: list,
project_directory: str,
composite_method: Optional[Level] = None,
- conformer_level: Optional[Level] = None,
+ conformer_opt_level: Optional[Level] = None,
+ conformer_sp_level: Optional[Level] = None,
opt_level: Optional[Level] = None,
freq_level: Optional[Level] = None,
sp_level: Optional[Level] = None,
@@ -474,7 +479,8 @@ Source code for arc.scheduler
self.report_time = time.time() # init time for reporting status every 1 hr
self.servers = list()
self.composite_method = composite_method
- self.conformer_level = conformer_level
+ self.conformer_opt_level = conformer_opt_level
+ self.conformer_sp_level = conformer_sp_level
self.ts_guess_level = ts_guess_level
self.opt_level = opt_level
self.freq_level = freq_level
@@ -588,8 +594,8 @@ Source code for arc.scheduler
if not self.job_types['opt'] and species.final_xyz is not None:
# opt wasn't asked for, and it's not needed, declare it as converged
self.output[species.label]['job_types']['opt'] = True
- if not self.job_types['conformers'] and len(species.conformers) == 1:
- # conformers weren't asked for, assign initial_xyz
+ if not self.job_types['conf_opt'] and len(species.conformers) == 1:
+ # conformers opt weren't asked for, assign initial_xyz
species.initial_xyz = species.conformers[0]
if species.label not in self.running_jobs:
self.running_jobs[species.label if not species.multi_species else species.multi_species] = list()
@@ -607,7 +613,7 @@ Source code for arc.scheduler
self.run_sp_job(label=species.label)
if self.job_types['onedmin']:
self.run_onedmin_job(species.label)
- elif species.get_xyz(generate=False) and not self.job_types['conformers'] and not self.job_types['opt'] \
+ elif species.get_xyz(generate=False) and not self.job_types['conf_opt'] and not self.job_types['opt'] \
and species.irc_label is None:
if self.job_types['freq']:
self.run_freq_job(species.label)
@@ -707,20 +713,25 @@ Source code for arc.scheduler
continue
job_list = self.running_jobs[label]
for job_name in job_list:
- if 'conformer' in job_name:
+ if 'conf' in job_name:
i = get_i_from_job_name(job_name)
- job = self.job_dict[label]['conformers'][i]
+ job = self.job_dict[label]['conf_opt'][i] if 'conf_opt' in job_name \
+ else self.job_dict[label]['conf_sp'][i]
if not (job.job_id in self.server_job_ids and job.job_id not in self.completed_incore_jobs):
# this is a completed conformer job
successful_server_termination = self.end_job(job=job, label=label, job_name=job_name)
if successful_server_termination:
troubleshooting_conformer = self.parse_conformer(job=job, label=label, i=i)
+ if 'conf_opt' in job_name and self.job_types['conf_sp'] and not troubleshooting_conformer:
+ self.run_sp_job(label=label,
+ level=self.conformer_sp_level,
+ conformer=i)
if troubleshooting_conformer:
break
# Just terminated a conformer job.
# Are there additional conformer jobs currently running for this species?
for spec_jobs in job_list:
- if 'conformer' in spec_jobs and spec_jobs != job_name:
+ if ('conf_opt' in spec_jobs or 'conf_sp' in spec_jobs) and spec_jobs != job_name:
break
else:
# All conformer jobs terminated.
@@ -729,7 +740,7 @@ Source code for arc.scheduler
if self.species_dict[label].is_ts:
self.determine_most_likely_ts_conformer(label)
else:
- self.determine_most_stable_conformer(label) # also checks isomorphism
+ self.determine_most_stable_conformer(label, sp_flag=True if self.job_types['conf_sp'] else False) # also checks isomorphism
if self.species_dict[label].initial_xyz is not None:
# if initial_xyz is None, then we're probably troubleshooting conformers, don't opt
if not self.composite_method:
@@ -757,7 +768,7 @@ Source code for arc.scheduler
self.run_conformer_jobs(labels=[label])
self.timer = False
break
- elif 'opt' in job_name:
+ elif 'opt' in job_name and 'conf_opt' not in job_name:
# val is 'opt1', 'opt2', etc., or 'optfreq1', optfreq2', etc.
job = self.job_dict[label]['opt'][job_name]
if not (job.job_id in self.server_job_ids and job.job_id not in self.completed_incore_jobs):
@@ -789,7 +800,7 @@ Source code for arc.scheduler
self.check_freq_job(label=label, job=job)
self.timer = False
break
- elif 'sp' in job_name:
+ elif 'sp' in job_name and 'conf_sp' not in job_name:
job = self.job_dict[label]['sp'][job_name]
if not (job.job_id in self.server_job_ids and job.job_id not in self.completed_incore_jobs):
successful_server_termination = self.end_job(job=job, label=label, job_name=job_name)
@@ -1043,10 +1054,12 @@ Source code for arc.scheduler
elif conformer is not None:
# Running a conformer DFT job. Append differently to job_dict.
self.running_jobs[label] = list() if label not in self.running_jobs else self.running_jobs[label]
- self.running_jobs[label].append(f'conformer{conformer}') # mark as a running job
- if 'conformers' not in self.job_dict[label]:
- self.job_dict[label]['conformers'] = dict()
- self.job_dict[label]['conformers'][conformer] = job # save job object
+ self.running_jobs[label].append(f'{job_type}_{conformer}') # mark as a running job
+ if 'conf_opt' not in self.job_dict[label]:
+ self.job_dict[label]['conf_opt'] = dict()
+ if 'conf_sp' not in self.job_dict[label] and job_type == 'conf_sp':
+ self.job_dict[label]['conf_sp'] = dict()
+ self.job_dict[label][job_type][conformer] = job # save job object
elif tsg is not None:
# Running a TS guess job. Append differently to job_dict.
self.running_jobs[label] = list() if label not in self.running_jobs else self.running_jobs[label]
@@ -1248,10 +1261,10 @@ Source code for arc.scheduler
and all([e is None for e in self.species_dict[label].conformer_energies]) \
and self.species_dict[label].number_of_atoms > 1 and not self.output[label]['paths']['geo'] \
and self.species_dict[label].yml_path is None and not self.output[label]['convergence'] \
- and (self.job_types['conformers'] and label not in self.dont_gen_confs
+ and (self.job_types['conf_opt'] and label not in self.dont_gen_confs
or self.species_dict[label].get_xyz(generate=False) is None):
# This is not a TS, opt (/composite) did not converge nor is it running, and conformer energies were
- # not set. Also, either 'conformers' are set to True in job_types (and it's not in dont_gen_confs),
+ # not set. Also, either 'conf_opt' are set to True in job_types (and it's not in dont_gen_confs),
# or they are set to False (or it's in dont_gen_confs), but the species has no 3D information.
# Generate conformers.
if not log_info_printed:
@@ -1309,15 +1322,16 @@ Source code for arc.scheduler
f'{tsg.method_direction if tsg.method_direction is not None else ""} '
f'{tsg.method_index if tsg.method_index is not None else ""} '
for tsg in self.species_dict[label].ts_guesses],
+ before_optimization=True,
)
successful_tsgs = [tsg for tsg in self.species_dict[label].ts_guesses if tsg.success]
if len(successful_tsgs) > 1:
- self.job_dict[label]['conformers'] = dict()
+ self.job_dict[label]['conf_opt'] = dict()
for i, tsg in enumerate(successful_tsgs):
self.run_job(label=label,
xyz=tsg.initial_xyz,
level_of_theory=self.ts_guess_level,
- job_type='conformers',
+ job_type='conf_opt',
conformer=i,
)
tsg.conformer_index = i # Store the conformer index in the TSGuess object to match them later.
@@ -1417,6 +1431,7 @@ Source code for arc.scheduler
[docs] def run_sp_job(self,
label: str,
level: Optional[Level] = None,
+ conformer: Optional[int] = None,
):
"""
Spawn a single point job using 'final_xyz' for species ot TS 'label'.
@@ -1425,9 +1440,17 @@ Source code for arc.scheduler
Args:
label (str): The species label.
level (Level): An alternative level of theory to run at. If ``None``, self.sp_level will be used.
+ conformer (int): The conformer number.
"""
level = level or self.sp_level
+ if self.job_types['conf_sp'] and conformer is not None and self.conformer_sp_level != self.conformer_opt_level:
+ self.run_job(label=label,
+ xyz=self.species_dict[label].conformers[conformer],
+ level_of_theory=self.conformer_sp_level,
+ job_type='conf_sp',
+ conformer=conformer)
+ return
# determine_occ(xyz=self.xyz, charge=self.charge)
if level == self.opt_level and not self.composite_method \
and not (level.software == 'xtb' and self.species_dict[label].is_ts) \
@@ -2003,8 +2026,8 @@ Source code for arc.scheduler
[docs] def process_conformers(self, label):
"""
- Process the generated conformers and spawn DFT jobs at the conformer_level.
- If more than one conformer is available, they will be optimized at the DFT conformer_level.
+ Process the generated conformers and spawn DFT jobs at the conformer_opt_level.
+ If more than one conformer is available, they will be optimized at the DFT conformer_opt_level.
Args:
label (str): The species label.
@@ -2012,21 +2035,23 @@ Source code for arc.scheduler
plotter.save_conformers_file(project_directory=self.project_directory,
label=label,
xyzs=self.species_dict[label].conformers,
- level_of_theory=self.conformer_level,
+ level_of_theory=self.conformer_opt_level,
multiplicity=self.species_dict[label].multiplicity,
charge=self.species_dict[label].charge,
is_ts=False,
+ energies=self.species_dict[label].conformer_energies,
+ before_optimization=True,
) # before optimization
self.species_dict[label].conformers_before_opt = tuple(self.species_dict[label].conformers)
if self.species_dict[label].initial_xyz is None and self.species_dict[label].final_xyz is None \
and not self.testing:
if len(self.species_dict[label].conformers) > 1:
- self.job_dict[label]['conformers'] = dict()
+ self.job_dict[label]['conf_opt'] = dict()
for i, xyz in enumerate(self.species_dict[label].conformers):
self.run_job(label=label,
xyz=xyz,
- level_of_theory=self.conformer_level,
- job_type='conformers',
+ job_type='conf_opt',
+ level_of_theory=self.conformer_opt_level,
conformer=i,
)
elif len(self.species_dict[label].conformers) == 1:
@@ -2049,7 +2074,7 @@ Source code for arc.scheduler
if self.species_dict[label].charge:
logger.warning(f'Isomorphism check cannot be done for charged species {label}')
self.output[label]['conformers'] += 'Single conformer could not be checked for isomorphism; '
- self.output[label]['job_types']['conformers'] = True
+ self.output[label]['job_types']['conf_opt'] = True
self.species_dict[label].conf_is_isomorphic, spawn_jobs = True, True
else:
logger.error(f'The only conformer for species {label} could not be checked for isomorphism '
@@ -2058,7 +2083,7 @@ Source code for arc.scheduler
f'this species. To change this behaviour, pass `allow_nonisomorphic_2d = True`.')
self.species_dict[label].conf_is_isomorphic, spawn_jobs = False, False
if b_mol is None and (self.allow_nonisomorphic_2d or self.species_dict[label].charge):
- self.output[label]['job_types']['conformers'] = True
+ self.output[label]['job_types']['conf_opt'] = True
if b_mol is not None:
try:
is_isomorphic = check_isomorphism(self.species_dict[label].mol, b_mol)
@@ -2074,7 +2099,7 @@ Source code for arc.scheduler
logger.info(f'The only conformer for species {label} was found to be isomorphic '
f'with the 2D graph representation {b_mol.copy(deep=True).to_smiles()}\n')
self.output[label]['conformers'] += 'single conformer passed isomorphism check; '
- self.output[label]['job_types']['conformers'] = True
+ self.output[label]['job_types']['conf_opt'] = True
self.species_dict[label].conf_is_isomorphic = True
else:
logger.error(f'The only conformer for species {label} is not isomorphic '
@@ -2159,7 +2184,7 @@ Source code for arc.scheduler
return True
return False
-[docs] def determine_most_stable_conformer(self, label):
+[docs] def determine_most_stable_conformer(self, label, sp_flag=False):
"""
Determine the most stable conformer for a species (which is not a TS).
Also run an isomorphism check.
@@ -2167,13 +2192,14 @@ Source code for arc.scheduler
Args:
label (str): The species label.
+ sp_flag (bool): Whether this is a single point calculation job.
"""
if self.species_dict[label].is_ts:
raise SchedulerError('The determine_most_stable_conformer() method does not deal with transition '
'state guesses.')
- if 'conformers' in self.job_dict[label].keys() and all(e is None for e in self.species_dict[label].conformer_energies):
+ if 'conf_opt' in self.job_dict[label].keys() and all(e is None for e in self.species_dict[label].conformer_energies):
logger.error(f'No conformer converged for species {label}! Trying to troubleshoot conformer jobs...')
- for i, job in self.job_dict[label]['conformers'].items():
+ for i, job in self.job_dict[label]['conf_opt'].items():
self.troubleshoot_ess(label, job, level_of_theory=job.level, conformer=job.conformer)
else:
conformer_xyz = None
@@ -2181,19 +2207,21 @@ Source code for arc.scheduler
if self.species_dict[label].conformer_energies:
xyzs = self.species_dict[label].conformers
else:
- for job in self.job_dict[label]['conformers'].values():
+ for job in self.job_dict[label]['conf_opt'].values():
xyzs.append(parser.parse_xyz_from_file(path=job.local_path_to_output_file))
xyzs_in_original_order = xyzs
energies, xyzs = sort_two_lists_by_the_first(self.species_dict[label].conformer_energies, xyzs)
plotter.save_conformers_file(project_directory=self.project_directory,
label=label,
xyzs=self.species_dict[label].conformers,
- level_of_theory=self.conformer_level,
+ level_of_theory=self.conformer_opt_level if not sp_flag else self.conformer_sp_level,
multiplicity=self.species_dict[label].multiplicity,
charge=self.species_dict[label].charge,
is_ts=False,
- energies=self.species_dict[label].conformer_energies, # after optimization
- )
+ energies=self.species_dict[label].conformer_energies,
+ before_optimization=False,
+ sp_flag=sp_flag,
+ ) # after optimization
# Run isomorphism checks if a 2D representation is available
if self.species_dict[label].mol is not None:
for i, xyz in enumerate(xyzs):
@@ -2248,7 +2276,7 @@ Source code for arc.scheduler
conformer_xyz = xyz
if 'Conformers optimized and compared' not in self.output[label]['conformers']:
self.output[label]['conformers'] += \
- f'Conformers optimized and compared at {self.conformer_level.simple()}; '
+ f'Conformers optimized and compared at {self.conformer_opt_level.simple()}; '
break
else:
if i == 0:
@@ -2287,11 +2315,11 @@ Source code for arc.scheduler
else:
# troubleshoot when all conformers of a species failed isomorphic test
logger.warning(f'Isomorphism check for all conformers of species {label} failed at '
- f'{self.conformer_level.simple()}. '
+ f'{self.conformer_opt_level.simple()}. '
f'Attempting to troubleshoot using a different level.')
self.output[label]['conformers'] += \
f'Error: No conformer was found to be isomorphic with the 2D graph representation at ' \
- f'{self.conformer_level.simple()}; '
+ f'{self.conformer_opt_level.simple()}; '
self.troubleshoot_conformer_isomorphism(label=label)
else:
logger.warning(f'Could not run isomorphism check for species {label} due to missing 2D graph '
@@ -2302,7 +2330,9 @@ Source code for arc.scheduler
self.species_dict[label].most_stable_conformer = xyzs_in_original_order.index(conformer_xyz)
logger.info(f'Conformer number {xyzs_in_original_order.index(conformer_xyz)} for species {label} is '
f'used for geometry optimization.')
- self.output[label]['job_types']['conformers'] = True
+ self.output[label]['job_types']['conf_opt'] = True
+ if sp_flag:
+ self.output[label]['job_types']['conf_sp'] = True
[docs] def determine_most_likely_ts_conformer(self, label: str):
"""
@@ -2408,6 +2438,7 @@ Source code for arc.scheduler
for tsg in self.species_dict[label].ts_guesses],
im_freqs=[tsg.imaginary_freqs for tsg in self.species_dict[label].ts_guesses]
if any(tsg.imaginary_freqs is not None for tsg in self.species_dict[label].ts_guesses) else None,
+ before_optimization=False,
)
[docs] def parse_composite_geo(self,
@@ -2743,6 +2774,7 @@ Source code for arc.scheduler
for tsg in self.species_dict[label].ts_guesses],
im_freqs=[tsg.imaginary_freqs for tsg in self.species_dict[label].ts_guesses]
if any(tsg.imaginary_freqs is not None for tsg in self.species_dict[label].ts_guesses) else None,
+ before_optimization=False,
)
if not self.testing:
# Update restart dictionary and save the yaml restart file:
@@ -3204,11 +3236,11 @@ Source code for arc.scheduler
if label in self.output and not self.output[label]['convergence']:
for job_type, spawn_job_type in self.job_types.items():
if spawn_job_type and not self.output[label]['job_types'][job_type] \
- and not ((self.species_dict[label].is_ts and job_type in ['scan', 'conformers'])
+ and not ((self.species_dict[label].is_ts and job_type in ['scan', 'conf_opt'])
or (self.species_dict[label].number_of_atoms == 1
- and job_type in ['conformers', 'opt', 'fine', 'freq', 'rotors', 'bde'])
+ and job_type in ['conf_opt', 'opt', 'fine', 'freq', 'rotors', 'bde'])
or job_type == 'bde' and self.species_dict[label].bdes is None
- or job_type == 'conformers'
+ or job_type == 'conf_opt'
or job_type == 'irc'
or job_type == 'tsg'):
logger.debug(f'Species {label} did not converge.')
@@ -3220,9 +3252,12 @@ Source code for arc.scheduler
self.species_dict[label].make_ts_report()
logger.info(self.species_dict[label].ts_report + '\n')
zero_delta = datetime.timedelta(0)
- conf_time = extremum_list([job.run_time for job in self.job_dict[label]['conformers'].values()],
+ conf_time = extremum_list([job.run_time for job in self.job_dict[label]['conf_opt'].values()],
+ return_min=False) \
+ if 'conf_opt' in self.job_dict[label].keys() else zero_delta
+ conf_time = conf_time + extremum_list([job.run_time for job in self.job_dict[label]['conf_sp'].values()],
return_min=False) \
- if 'conformers' in self.job_dict[label].keys() else zero_delta
+ if 'conf_sp' in self.job_dict[label].keys() else zero_delta
tsg_time = extremum_list([job.run_time for job in self.job_dict[label]['tsg'].values()], return_min=False) \
if 'tsg' in self.job_dict[label].keys() else zero_delta
opt_time = sum_time_delta([job.run_time for job in self.job_dict[label]['opt'].values()]) \
@@ -3231,8 +3266,8 @@ Source code for arc.scheduler
if 'composite' in self.job_dict[label].keys() else zero_delta
other_time = extremum_list([sum_time_delta([job.run_time for job in job_dictionary.values()])
for job_type, job_dictionary in self.job_dict[label].items()
- if job_type not in ['conformers', 'opt', 'composite']], return_min=False) \
- if any([job_type not in ['conformers', 'opt', 'composite']
+ if job_type not in ['conf_opt', 'conf_sp', 'opt', 'composite']], return_min=False) \
+ if any([job_type not in ['conf_opt', 'conf_sp', 'opt', 'composite']
for job_type in self.job_dict[label].keys()]) else zero_delta
self.species_dict[label].run_time = self.species_dict[label].run_time \
or (conf_time or zero_delta) + \
@@ -3280,8 +3315,10 @@ Source code for arc.scheduler
if i is None:
job_type = '_'.join(job_name.split('_')[:-1]) # Consider job types such as 'directed_scan'.
job = self.job_dict[label][job_type][job_name]
- elif 'conformer' in job_name:
- job = self.job_dict[label]['conformers'][i]
+ elif 'conf_opt' in job_name:
+ job = self.job_dict[label]['conf_opt'][i]
+ elif 'conf_sp' in job_name:
+ job = self.job_dict[label]['conf_sp'][i]
elif 'tsg' in job_name:
job = self.job_dict[label]['tsg'][i]
else:
@@ -3325,12 +3362,12 @@ Source code for arc.scheduler
self.delete_all_species_jobs(label)
self.species_dict[label].conformers = confs
self.species_dict[label].conformer_energies = [None] * len(confs)
- self.job_dict[label]['conformers'] = dict() # initialize the conformer job dictionary
+ self.job_dict[label]['conf_opt'] = dict() # initialize the conformer job dictionary
for i, xyz in enumerate(self.species_dict[label].conformers):
self.run_job(label=label,
xyz=xyz,
- level_of_theory=self.conformer_level,
- job_type='conformers',
+ level_of_theory=self.conformer_opt_level,
+ job_type='conf_opt',
conformer=i,
)
@@ -3519,12 +3556,13 @@ Source code for arc.scheduler
if previous_job_num >= 0 and job.fine:
previous_job = self.job_dict[label]['opt']['opt_a' + str(previous_job_num)]
if not previous_job.fine and previous_job.job_status[0] == 'done' \
- and previous_job.job_status[1]['status'] == 'done':
+ and previous_job.job_status[1]['status'] == 'done' \
+ and 'all_attempted' in job.ess_trsh_methods:
# The present job with a fine grid failed in the ESS calculation.
# A *previous* job without a fine grid terminated successfully on the server and ESS.
# So use the xyz determined w/o the fine grid, and output an error message to alert users.
logger.error(f'Optimization job for {label} with a fine grid terminated successfully '
- f'on the server, but crashed during calculation. NOT running with fine '
+ f'on the server, but crashed during calculation after troubleshooting. NOT running with fine '
f'grid again.')
self.parse_opt_geo(label=label, job=previous_job)
trsh_opt = False
@@ -3656,7 +3694,7 @@ Source code for arc.scheduler
raise SchedulerError('The troubleshoot_conformer_isomorphism() method got zero conformers.')
# use the first conformer of a species to determine applicable troubleshooting method
- job = self.job_dict[label]['conformers'][0]
+ job = self.job_dict[label]['conf_opt'][0]
level_of_theory = trsh_conformer_isomorphism(software=job.job_adapter, ess_trsh_methods=job.ess_trsh_methods)
@@ -3677,15 +3715,15 @@ Source code for arc.scheduler
# initial xyz before troubleshooting
xyz = self.species_dict[label].conformers_before_opt[conformer]
- job = self.job_dict[label]['conformers'][conformer]
- if 'Conformers: ' + level_of_theory not in job.ess_trsh_methods:
- job.ess_trsh_methods.append('Conformers: ' + level_of_theory)
+ job = self.job_dict[label]['conf_opt'][conformer]
+ if 'conf_opt: ' + level_of_theory not in job.ess_trsh_methods:
+ job.ess_trsh_methods.append('conf_opt: ' + level_of_theory)
self.run_job(label=label,
xyz=xyz,
level_of_theory=level_of_theory,
job_adapter=job.job_adapter,
- job_type='conformers',
+ job_type='conf_opt',
ess_trsh_methods=job.ess_trsh_methods,
conformer=conformer,
)
@@ -3699,7 +3737,7 @@ Source code for arc.scheduler
"""
logger.debug(f'Deleting all jobs for species {label}')
for value in self.job_dict[label].values():
- if value in ['conformers', 'tsg']:
+ if value in ['conf_opt', 'tsg']:
for job_name, job in self.job_dict[label][value].items():
if label in self.running_jobs.keys() and job_name in self.running_jobs[label] \
and job.execution_type != 'incore':
@@ -3756,17 +3794,17 @@ Source code for arc.scheduler
if ('conformer' not in job_description or job_description['conformer'] is None) \
and ('tsg' not in job_description or job_description['tsg'] is None):
self.job_dict[spc_label][job_description['job_type']] = dict()
- elif 'conformers' not in self.job_dict[spc_label].keys():
- self.job_dict[spc_label]['conformers'] = dict()
+ elif 'conf_opt' not in self.job_dict[spc_label].keys():
+ self.job_dict[spc_label]['conf_opt'] = dict()
elif 'tsg' not in self.job_dict[spc_label].keys():
self.job_dict[spc_label]['tsg'] = dict()
if ('conformer' not in job_description or job_description['conformer'] is None) \
and ('tsg' not in job_description or job_description['tsg'] is None):
self.job_dict[spc_label][job_description['job_type']][job_description['job_name']] = job
elif 'conformer' in job_description and job_description['conformer'] is not None:
- if 'conformers' not in self.job_dict[spc_label].keys():
- self.job_dict[spc_label]['conformers'] = dict()
- self.job_dict[spc_label]['conformers'][int(job_description['conformer'])] = job
+ if 'conf_opt' not in self.job_dict[spc_label].keys():
+ self.job_dict[spc_label]['conf_opt'] = dict()
+ self.job_dict[spc_label]['conf_opt'][int(job_description['conformer'])] = job
# don't generate additional conformers for this species
self.dont_gen_confs.append(spc_label)
elif 'tsg' in job_description and job_description['tsg'] is not None:
@@ -3780,9 +3818,9 @@ Source code for arc.scheduler
content += f'\n{spc_label}: '
for job_type in self.job_dict[spc_label].keys():
for job_name in self.job_dict[spc_label][job_type].keys():
- if job_type not in ['conformers', 'tsg']:
+ if job_type not in ['conf_opt', 'conf_sp', 'tsg']:
content += job_name + ', '
- elif job_type == 'conformers':
+ elif 'conf_' in job_type:
content += self.job_dict[spc_label][job_type][job_name].job_name \
+ f' (conformer{job_name}), '
elif job_type == 'tsg':
@@ -3806,9 +3844,11 @@ Source code for arc.scheduler
self.restart_dict['running_jobs'][spc.label] = \
[self.job_dict[spc.label][job_name.rsplit('_', 1)[0]][job_name].as_dict()
for job_name in self.running_jobs[spc.label]
- if 'conformer' not in job_name and 'tsg' not in job_name] \
- + [self.job_dict[spc.label]['conformers'][get_i_from_job_name(job_name)].as_dict()
- for job_name in self.running_jobs[spc.label] if 'conformer' in job_name] \
+ if all(x not in job_name for x in ['conf_opt', 'conf_sp', 'tsg'])] \
+ + [self.job_dict[spc.label]['conf_opt'][get_i_from_job_name(job_name)].as_dict()
+ for job_name in self.running_jobs[spc.label] if 'conf_opt' in job_name] \
+ + [self.job_dict[spc.label]['conf_sp'][get_i_from_job_name(job_name)].as_dict()
+ for job_name in self.running_jobs[spc.label] if 'conf_sp' in job_name] \
+ [self.job_dict[spc.label]['tsg'][get_i_from_job_name(job_name)].as_dict()
for job_name in self.running_jobs[spc.label] if 'tsg' in job_name]
logger.debug(f'Dumping restart dictionary:\n{self.restart_dict}')
diff --git a/_modules/arc/species/species.html b/_modules/arc/species/species.html
index 1113e778e9..1fc9b06b87 100644
--- a/_modules/arc/species/species.html
+++ b/_modules/arc/species/species.html
@@ -1283,7 +1283,7 @@ Source code for arc.species.species
)
if len(lowest_confs):
self.conformers.extend([conf['xyz'] for conf in lowest_confs])
- self.conformer_energies.extend([None] * len(lowest_confs))
+ self.conformer_energies.extend([conf['FF energy'] for conf in lowest_confs])
else:
xyz = self.get_xyz(generate=False)
if xyz is None or not xyz:
diff --git a/_sources/advanced.rst.txt b/_sources/advanced.rst.txt
index 37c94e1a7a..86953f9b98 100644
--- a/_sources/advanced.rst.txt
+++ b/_sources/advanced.rst.txt
@@ -566,12 +566,13 @@ which could be read as an input in ARC::
input_dict['project'] = 'Demo_project_input_file_from_API'
- input_dict['job_types'] = {'conformers': True,
+ input_dict['job_types'] = {'conf_opt': True,
'opt': True,
'fine': True,
'freq': True,
'sp': True,
'rotors': True,
+ 'conf_sp': False,
'orbitals': False,
'lennard_jones': False,
}
diff --git a/_sources/examples.rst.txt b/_sources/examples.rst.txt
index 5e9538dccf..86899a99cb 100644
--- a/_sources/examples.rst.txt
+++ b/_sources/examples.rst.txt
@@ -126,7 +126,7 @@ The same example as above ran via the API (e.g., in `Jupyter notebooks`__) would
arc = ARC(project='arc_demo_1',
ess_settings={'gaussian': ['local', 'server1'], 'molpro': 'server1', 'qchem': 'server2'},
- job_types={'rotors': True, 'conformers': True, 'fine': True, 'freq': True, 'opt': True, sp: True},
+ job_types={'rotors': True, 'conf_opt': True, 'conf_sp': True, 'fine': True, 'freq': True, 'opt': True, sp: True},
max_job_time=24,
level_of_theory='CCSD(T)-F12/cc-pVTZ-F12//wb97xd/def2tzvp',
scan_level='wb97xd/def2tzvp',
diff --git a/advanced.html b/advanced.html
index aba928201a..93b93984a5 100644
--- a/advanced.html
+++ b/advanced.html
@@ -702,12 +702,13 @@ Writing an ARC input file using the APIinput_dict['project'] = 'Demo_project_input_file_from_API'
-input_dict['job_types'] = {'conformers': True,
+input_dict['job_types'] = {'conf_opt': True,
'opt': True,
'fine': True,
'freq': True,
'sp': True,
'rotors': True,
+ 'conf_sp': False,
'orbitals': False,
'lennard_jones': False,
}
diff --git a/api/main.html b/api/main.html
index 8f0031247c..71ee84e2b1 100644
--- a/api/main.html
+++ b/api/main.html
@@ -200,7 +200,7 @@
Where spc0, spc1, and spc2 in the above example are ARCSpecies objects.
-
-class arc.main.ARC(adaptive_levels: Optional[dict] = None, allow_nonisomorphic_2d: bool = False, arkane_level_of_theory: Optional[Union[str, dict, Level]] = None, bac_type: Optional[str] = 'p', bath_gas: Optional[str] = None, calc_freq_factor: bool = True, compare_to_rmg: bool = True, composite_method: Optional[Union[str, dict, Level]] = None, compute_rates: bool = True, compute_thermo: bool = True, compute_transport: bool = False, conformer_level: Optional[Union[str, dict, Level]] = None, dont_gen_confs: Optional[List[str]] = None, e_confs: float = 5.0, ess_settings: Optional[Dict[str, Union[str, List[str]]]] = None, freq_level: Optional[Union[str, dict, Level]] = None, freq_scale_factor: Optional[float] = None, irc_level: Optional[Union[str, dict, Level]] = None, keep_checks: bool = False, kinetics_adapter: str = 'Arkane', job_memory: Optional[int] = None, job_types: Optional[Dict[str, bool]] = None, level_of_theory: str = '', max_job_time: Optional[float] = None, n_confs: int = 10, opt_level: Optional[Union[str, dict, Level]] = None, orbitals_level: Optional[Union[str, dict, Level]] = None, output: Optional[dict] = None, output_multi_spc: Optional[dict] = None, project: Optional[str] = None, project_directory: Optional[str] = None, reactions: Optional[List[Union[ARCReaction, Reaction]]] = None, running_jobs: Optional[dict] = None, scan_level: Optional[Union[str, dict, Level]] = None, sp_level: Optional[Union[str, dict, Level]] = None, species: Optional[List[Union[ARCSpecies, Species]]] = None, specific_job_type: str = '', T_min: Optional[Tuple[float, str]] = None, T_max: Optional[Tuple[float, str]] = None, T_count: int = 50, thermo_adapter: str = 'Arkane', three_params: bool = True, trsh_ess_jobs: bool = True, ts_adapters: Optional[List[str]] = None, ts_guess_level: Optional[Union[str, dict, Level]] = None, verbose=20, report_e_elect: Optional[bool] = False, skip_nmd: Optional[bool] = False)[source]¶
+class arc.main.ARC(adaptive_levels: Optional[dict] = None, allow_nonisomorphic_2d: bool = False, arkane_level_of_theory: Optional[Union[str, dict, Level]] = None, bac_type: Optional[str] = 'p', bath_gas: Optional[str] = None, calc_freq_factor: bool = True, compare_to_rmg: bool = True, composite_method: Optional[Union[str, dict, Level]] = None, compute_rates: bool = True, compute_thermo: bool = True, compute_transport: bool = False, conformer_level: Optional[Union[str, dict, Level]] = None, conformer_opt_level: Optional[Union[str, dict, Level]] = None, conformer_sp_level: Optional[Union[str, dict, Level]] = None, dont_gen_confs: Optional[List[str]] = None, e_confs: float = 5.0, ess_settings: Optional[Dict[str, Union[str, List[str]]]] = None, freq_level: Optional[Union[str, dict, Level]] = None, freq_scale_factor: Optional[float] = None, irc_level: Optional[Union[str, dict, Level]] = None, keep_checks: bool = False, kinetics_adapter: str = 'Arkane', job_memory: Optional[int] = None, job_types: Optional[Dict[str, bool]] = None, level_of_theory: str = '', max_job_time: Optional[float] = None, n_confs: int = 10, opt_level: Optional[Union[str, dict, Level]] = None, orbitals_level: Optional[Union[str, dict, Level]] = None, output: Optional[dict] = None, output_multi_spc: Optional[dict] = None, project: Optional[str] = None, project_directory: Optional[str] = None, reactions: Optional[List[Union[ARCReaction, Reaction]]] = None, running_jobs: Optional[dict] = None, scan_level: Optional[Union[str, dict, Level]] = None, sp_level: Optional[Union[str, dict, Level]] = None, species: Optional[List[Union[ARCSpecies, Species]]] = None, specific_job_type: str = '', T_min: Optional[Tuple[float, str]] = None, T_max: Optional[Tuple[float, str]] = None, T_count: int = 50, thermo_adapter: str = 'Arkane', three_params: bool = True, trsh_ess_jobs: bool = True, ts_adapters: Optional[List[str]] = None, ts_guess_level: Optional[Union[str, dict, Level]] = None, verbose=20, report_e_elect: Optional[bool] = False, skip_nmd: Optional[bool] = False)[source]¶
The main ARC class.
- Parameters:
@@ -216,6 +216,8 @@
instead (e.g., opt_level).
composite_method (str, dict, Level, optional) – Composite method.
conformer_level (str, dict, Level, optional) – Level of theory for conformer searches.
conformer_opt_level (str, dict, Level, optional) – Level of theory for conformer searches, interchangable with conformer_level.
conformer_sp_level (str, dict, Level, optional) – Level of theory for conformer sp jobs after opt.
opt_level (str, dict, Level, optional) – Level of theory for geometry optimization.
freq_level (str, dict, Level, optional) – Level of theory for frequency calculations.
sp_level (str, dict, Level, optional) – Level of theory for single point calculations.
--
-conformer_level¶
+-
+conformer_opt_level¶
Level of theory for conformer searches.
- Type:
@@ -376,6 +378,17 @@
+
+
-
opt_level¶
diff --git a/api/plotter.html b/api/plotter.html
index d22d37039f..59bdef01d8 100644
--- a/api/plotter.html
+++ b/api/plotter.html
@@ -621,7 +621,7 @@
-
-arc.plotter.save_conformers_file(project_directory: str, label: str, xyzs: List[dict], level_of_theory: Union[Level, str], multiplicity: Optional[int] = None, charge: Optional[int] = None, is_ts: bool = False, energies: Optional[List[float]] = None, ts_methods: Optional[List[str]] = None, im_freqs: Optional[List[List[float]]] = None, log_content: bool = False)[source]¶
+arc.plotter.save_conformers_file(project_directory: str, label: str, xyzs: List[dict], level_of_theory: Union[Level, str], multiplicity: Optional[int] = None, charge: Optional[int] = None, is_ts: bool = False, energies: Optional[List[float]] = None, ts_methods: Optional[List[str]] = None, im_freqs: Optional[List[List[float]]] = None, log_content: bool = False, before_optimization: bool = True, sp_flag=False)[source]¶
Save the conformers before or after optimization.
If energies are given, the conformers are considered to be optimized.
@@ -639,6 +639,8 @@
ts_methods (list, optional) – Entries are method names used to generate the TS guess.
im_freqs (list, optional) – Entries lists of imaginary frequencies.
log_content (bool) – Whether to log the content of the conformers file. True to log, default is False.
before_optimization (bool) – Whether the conformers are before DFT optimization. True for before, default is True.
sp_flag (bool) – Whether the conformers are single point calculations. True for single point, default is False.
diff --git a/api/scheduler.html b/api/scheduler.html
index 2b9df45ca7..ef8946f43d 100644
--- a/api/scheduler.html
+++ b/api/scheduler.html
@@ -195,11 +195,13 @@
Includes spawning, terminating, checking, and troubleshooting various jobs
-
-class arc.scheduler.Scheduler(project: str, ess_settings: dict, species_list: list, project_directory: str, composite_method: Optional[Level] = None, conformer_level: Optional[Level] = None, opt_level: Optional[Level] = None, freq_level: Optional[Level] = None, sp_level: Optional[Level] = None, scan_level: Optional[Level] = None, ts_guess_level: Optional[Level] = None, irc_level: Optional[Level] = None, orbitals_level: Optional[Level] = None, adaptive_levels: Optional[dict] = None, rmg_database: Optional = None, job_types: Optional[dict] = None, rxn_list: Optional[list] = None, bath_gas: Optional[str] = None, restart_dict: Optional[dict] = None, max_job_time: Optional[float] = None, allow_nonisomorphic_2d: Optional[bool] = False, memory: Optional[float] = None, testing: Optional[bool] = False, dont_gen_confs: Optional[list] = None, n_confs: Optional[int] = 10, e_confs: Optional[float] = 5, fine_only: Optional[bool] = False, trsh_ess_jobs: Optional[bool] = True, kinetics_adapter: str = 'arkane', freq_scale_factor: float = 1.0, ts_adapters: List[str] = None, report_e_elect: Optional[bool] = False, skip_nmd: Optional[bool] = False, output: Optional[dict] = None)[source]¶
+class arc.scheduler.Scheduler(project: str, ess_settings: dict, species_list: list, project_directory: str, composite_method: Optional[Level] = None, conformer_opt_level: Optional[Level] = None, conformer_sp_level: Optional[Level] = None, opt_level: Optional[Level] = None, freq_level: Optional[Level] = None, sp_level: Optional[Level] = None, scan_level: Optional[Level] = None, ts_guess_level: Optional[Level] = None, irc_level: Optional[Level] = None, orbitals_level: Optional[Level] = None, adaptive_levels: Optional[dict] = None, rmg_database: Optional = None, job_types: Optional[dict] = None, rxn_list: Optional[list] = None, bath_gas: Optional[str] = None, restart_dict: Optional[dict] = None, max_job_time: Optional[float] = None, allow_nonisomorphic_2d: Optional[bool] = False, memory: Optional[float] = None, testing: Optional[bool] = False, dont_gen_confs: Optional[list] = None, n_confs: Optional[int] = 10, e_confs: Optional[float] = 5, fine_only: Optional[bool] = False, trsh_ess_jobs: Optional[bool] = True, kinetics_adapter: str = 'arkane', freq_scale_factor: float = 1.0, ts_adapters: List[str] = None, report_e_elect: Optional[bool] = False, skip_nmd: Optional[bool] = False, output: Optional[dict] = None)[source]¶
ARC’s Scheduler class. Creates jobs, submits, checks status, troubleshoots.
Each species in species_list has to have a unique label.
Dictionary structures:
-job_dict = {label_1: {'conformers': {0: Job1,
+job_dict = {label_1: {'conf_opt': {0: Job1,
+ 1: Job2, ...},
+ 'conf_sp': {0: Job1,
1: Job2, ...},
'tsg': {0: Job1,
1: Job2, ...}, # TS guesses
@@ -254,7 +256,8 @@
rxn_list (list) – Contains input ARCReaction objects.
project_directory (str) – Folder path for the project: the input file path or ARC/Projects/project-name.
composite_method (str, optional) – A composite method to use.
conformer_level (Union[str, dict], optional) – The level of theory to use for conformer comparisons.
conformer_opt_level (Union[str, dict], optional) – The level of theory to use for conformer comparisons.
conformer_sp_level (Union[str, dict], optional) – The level of theory to use for conformer sp jobs.
opt_level (Union[str, dict], optional) – The level of theory to use for geometry optimizations.
freq_level (Union[str, dict], optional) – The level of theory to use for frequency calculations.
sp_level (Union[str, dict], optional) – The level of theory to use for single point energy calculations.
--
-conformer_level¶
+-
+conformer_opt_level¶
The level of theory to use for conformer comparisons.
- Type:
@@ -608,6 +611,17 @@
+
+-
+conformer_sp_level¶
+The level of theory to use for conformer sp jobs.
+
+- Type:
+dict
+
+
+
-
opt_level¶
@@ -1005,13 +1019,16 @@
-
-determine_most_stable_conformer(label)[source]¶
+determine_most_stable_conformer(label, sp_flag=False)[source]¶
Determine the most stable conformer for a species (which is not a TS).
Also run an isomorphism check.
Save the resulting xyz as initial_xyz.
- Parameters:
-label (str) – The species label.
+
+label (str) – The species label.
sp_flag (bool) – Whether this is a single point calculation job.
@@ -1196,8 +1213,8 @@
-
process_conformers(label)[source]¶
-Process the generated conformers and spawn DFT jobs at the conformer_level.
-If more than one conformer is available, they will be optimized at the DFT conformer_level.
+Process the generated conformers and spawn DFT jobs at the conformer_opt_level.
+If more than one conformer is available, they will be optimized at the DFT conformer_opt_level.
- Parameters:
label (str) – The species label.
@@ -1362,7 +1379,7 @@
-
-run_sp_job(label: str, level: Optional[Level] = None)[source]¶
+run_sp_job(label: str, level: Optional[Level] = None, conformer: Optional[int] = None)[source]¶
Spawn a single point job using ‘final_xyz’ for species ot TS ‘label’.
If the method is MRCI, first spawn a simple CCSD job, and use orbital determination to run the MRCI job.
@@ -1370,6 +1387,7 @@
label (str) – The species label.
level (Level) – An alternative level of theory to run at. If None, self.sp_level will be used.
conformer (int) – The conformer number.
diff --git a/api/trsh.html b/api/trsh.html
index 5a1d38563b..2bd9e29df2 100644
--- a/api/trsh.html
+++ b/api/trsh.html
@@ -449,6 +449,29 @@
Check if the job requires change of 2 electron integral accuracy
+
+-
+arc.job.trsh.trsh_keyword_l123(job_status, ess_trsh_methods, trsh_keyword, couldnt_trsh) Tuple[List, List, bool][source]¶
+When a job fails with l123.exe error, there are two possible solutions based upon the error message:
+1. If Delta-X issue, will need to adjust the maxcycle of IRC job. If fails, then change algorithm to LQA.
+2. GS2 Optimization failed, then try to change the algorithm to LQA.
+
+
+
+-
+arc.job.trsh.trsh_keyword_neg_eigen(job_status, ess_trsh_methods, trsh_keyword, couldnt_trsh) Tuple[List, List, bool][source]¶
+Gaussian will check the number of negative frequency after finishing the TS optimization.
+If there is more than one negative frequency, Gaussian will stop the calculation.
+
+
+
+-
+arc.job.trsh.trsh_keyword_no_qc(job_status, ess_trsh_methods, trsh_keyword, couldnt_trsh) Tuple[List, List, bool][source]¶
+When a job fails with no qc, there are two possible solutions based upon the error message:
+1. If SCF fails, then try to change the algorithm to LQA.
+2. If SCF fails, then try to change the algorithm to LQA.
+
+
-
arc.job.trsh.trsh_keyword_nosymm(job_status, ess_trsh_methods, trsh_keyword, couldnt_trsh) Tuple[List, List, bool][source]¶
diff --git a/examples.html b/examples.html
index 7919f982c6..c01f705b1f 100644
--- a/examples.html
+++ b/examples.html
@@ -286,7 +286,7 @@ Calculating thermodynamic propertiesarc = ARC(project='arc_demo_1',
ess_settings={'gaussian': ['local', 'server1'], 'molpro': 'server1', 'qchem': 'server2'},
- job_types={'rotors': True, 'conformers': True, 'fine': True, 'freq': True, 'opt': True, sp: True},
+ job_types={'rotors': True, 'conf_opt': True, 'conf_sp': True, 'fine': True, 'freq': True, 'opt': True, sp: True},
max_job_time=24,
level_of_theory='CCSD(T)-F12/cc-pVTZ-F12//wb97xd/def2tzvp',
scan_level='wb97xd/def2tzvp',
diff --git a/genindex.html b/genindex.html
index 05e4855a0b..520e9cb3d3 100644
--- a/genindex.html
+++ b/genindex.html
@@ -556,10 +556,10 @@ C
- check_xyz() (in module arc.species.species)
-
-
- check_xyz_isomorphism() (arc.species.species.ARCSpecies method)
- check_xyz_species_for_drawing() (in module arc.plotter)
@@ -628,10 +628,16 @@
C
- conformer_index (arc.species.species.TSGuess attribute)
- - conformer_level (arc.main.ARC attribute)
+
- conformer_opt_level (arc.main.ARC attribute)
+
+
+ - conformer_sp_level (arc.main.ARC attribute)
- conformers (arc.species.species.ARCSpecies attribute)
@@ -1937,10 +1943,10 @@
T
- trsh_conformer_isomorphism() (in module arc.job.trsh)
-
- trsh_ess_jobs (arc.main.ARC attribute)
@@ -1958,6 +1964,12 @@ T
- trsh_keyword_inaccurate_quadrature() (in module arc.job.trsh)
- trsh_keyword_intaccuracy() (in module arc.job.trsh)
+
+ - trsh_keyword_l123() (in module arc.job.trsh)
+
+ - trsh_keyword_neg_eigen() (in module arc.job.trsh)
+
+ - trsh_keyword_no_qc() (in module arc.job.trsh)
- trsh_keyword_nosymm() (in module arc.job.trsh)
diff --git a/objects.inv b/objects.inv
index c22f105770..f788fe0563 100644
Binary files a/objects.inv and b/objects.inv differ
diff --git a/searchindex.js b/searchindex.js
index 6e28d97db5..fcdb1bbf30 100644
--- a/searchindex.js
+++ b/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"docnames": ["advanced", "api/common", "api/conformers", "api/converter", "api/index", "api/job", "api/level", "api/local", "api/main", "api/parser", "api/plotter", "api/processor", "api/reaction", "api/rmgdb", "api/scale", "api/scheduler", "api/species", "api/ssh", "api/trsh", "api/vectors", "api/zmat", "cite", "contribute", "credits", "examples", "index", "installation", "licence", "media", "output", "release", "running", "tools"], "filenames": ["advanced.rst", "api/common.rst", "api/conformers.rst", "api/converter.rst", "api/index.rst", "api/job.rst", "api/level.rst", "api/local.rst", "api/main.rst", "api/parser.rst", "api/plotter.rst", "api/processor.rst", "api/reaction.rst", "api/rmgdb.rst", "api/scale.rst", "api/scheduler.rst", "api/species.rst", "api/ssh.rst", "api/trsh.rst", "api/vectors.rst", "api/zmat.rst", "cite.rst", "contribute.rst", "credits.rst", "examples.rst", "index.rst", "installation.rst", "licence.rst", "media.rst", "output.rst", "release.rst", "running.rst", "tools.rst"], "titles": ["Advanced Features", "arc.common", "arc.species.conformers", "arc.species.converter", "ARC\u2019s API", "arc.job", "arc.level", "arc.job.local", "arc.main", "arc.parser", "arc.plotter", "arc.processor", "arc.reaction", "arc.rmgdb", "arc.utils.scale", "arc.scheduler", "arc.species.species", "arc.job.ssh", "arc.job.trsh", "arc.species.vectors", "arc.species.zmat", "How to cite ARC", "Contribute", "Credits", "Examples", "ARC - Automated Rate Calculator v1.1.0", "Installation instructions", "Licence", "Media", "Output", "Release notes", "Running ARC", "Standalone tools"], "terms": {"The": [0, 1, 2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 24, 25, 26, 27, 29, 32], "attribut": [0, 1, 2, 3, 6, 8, 10, 12, 13, 15, 16], "arcspeci": [0, 3, 8, 10, 11, 12, 15, 16, 18, 24, 30, 31], "object": [0, 1, 2, 3, 6, 8, 9, 10, 11, 12, 13, 15, 16, 20, 31], "whether": [0, 1, 2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 27], "ts": [0, 1, 2, 3, 8, 10, 12, 15, 16, 18, 20, 24, 26, 29, 30, 31], "extrem": [0, 10, 16], "It": [0, 15, 17, 22, 26, 28, 29, 30], "could": [0, 1, 2, 3, 6, 8, 9, 12, 15, 16, 17, 18, 20, 24, 26, 31], "multilin": [0, 1, 3, 8, 10, 11], "string": [0, 1, 2, 3, 6, 7, 8, 9, 10, 12, 14, 15, 16, 17, 20, 26], "contain": [0, 1, 2, 3, 9, 10, 12, 15, 16, 17, 20, 24, 29, 31], "list": [0, 1, 2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 24, 25, 26, 29, 30, 31], "sever": [0, 16, 18, 24, 26], "also": [0, 1, 2, 3, 15, 16, 17, 20, 24, 26, 29, 31, 32], "valid": [0, 2, 3, 8, 15, 20, 30, 31], "path": [0, 1, 2, 3, 7, 8, 9, 10, 11, 14, 15, 16, 17, 18, 25, 29, 31], "output": [0, 1, 3, 6, 7, 8, 9, 10, 11, 12, 15, 16, 17, 18, 24, 25, 30, 31], "format": [0, 1, 2, 3, 7, 8, 9, 10, 11, 12, 14, 15, 16, 19, 26, 29, 31], "s": [0, 1, 2, 3, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 24, 25, 26, 29, 30, 31, 32], "befor": [0, 2, 10, 16, 17, 26, 30, 32], "after": [0, 1, 3, 10, 15, 16, 20, 24, 26, 29], "see": [0, 2, 3, 6, 10, 11, 22, 24, 26, 29, 30, 31], "exampl": [0, 1, 2, 3, 8, 16, 18, 19, 20, 25, 26, 30, 31], "To": [0, 8, 24, 26, 31], "run": [0, 1, 2, 3, 7, 8, 9, 15, 16, 17, 18, 25, 26, 29, 30, 32], "particular": [0, 27], "onli": [0, 1, 2, 3, 8, 9, 10, 12, 15, 16, 18, 20, 26, 30], "specific_job_typ": [0, 1, 8], "you": [0, 7, 17, 22, 24, 26, 29, 31, 32], "want": 0, "current": [0, 1, 2, 3, 8, 15, 16, 18, 26, 32], "support": [0, 1, 2, 3, 8, 9, 10, 15, 16, 18, 26, 30], "follow": [0, 1, 2, 9, 10, 15, 18, 20, 24, 25, 26, 27, 29], "opt": [0, 8, 9, 15, 16, 18, 24, 30], "freq": [0, 6, 8, 9, 14, 15, 18, 24, 29, 30], "sp": [0, 8, 9, 15, 16, 18, 24, 30], "onedmin": [0, 8, 15, 16, 25], "irc": [0, 8, 10, 15, 16], "note": [0, 2, 3, 7, 16, 20, 24, 25, 26, 29], "take": [0, 1, 2, 3, 10, 16, 18], "higher": [0, 26, 30], "preced": [0, 10], "than": [0, 1, 3, 6, 8, 9, 13, 15, 16, 18, 19, 20, 24, 26, 30, 31], "job_typ": [0, 1, 6, 8, 15, 18, 24, 30], "If": [0, 1, 2, 3, 7, 8, 9, 10, 11, 12, 14, 15, 16, 17, 18, 19, 20, 26, 29, 30, 31], "both": [0, 2, 3, 10, 13, 15, 16, 17, 26], "dismiss": 0, "given": [0, 1, 2, 3, 6, 8, 10, 12, 13, 14, 15, 16, 18, 19, 20, 26, 28, 32], "popul": [0, 2, 6, 8, 12, 13, 16], "dictionari": [0, 1, 2, 3, 6, 8, 9, 10, 11, 12, 14, 15, 16, 18, 20, 26, 29, 30], "For": [0, 2, 8, 15, 16, 18, 24, 26], "two": [0, 1, 2, 3, 8, 11, 12, 15, 16, 19, 20, 26, 32], "ar": [0, 1, 2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 22, 23, 24, 25, 26, 30, 31, 32], "equival": [0, 3, 16], "1": [0, 1, 2, 3, 7, 8, 9, 10, 11, 12, 14, 15, 16, 18, 19, 20, 21, 24, 26, 29, 31, 32], "fals": [0, 1, 2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 24], "true": [0, 1, 2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 24, 30], "2": [0, 1, 2, 3, 7, 8, 12, 14, 15, 16, 18, 19, 20, 24, 26, 32], "class": [0, 1, 6, 8, 12, 15, 16, 17, 31], "meant": 0, "allow": [0, 3, 6, 8, 15, 16, 20, 26, 30, 31], "detail": [0, 24, 26, 29, 31], "comprehens": [0, 1, 6], "user": [0, 2, 3, 7, 8, 12, 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