def compute_thermo(self,
kinetics_flag: bool = False,
e0_only: bool = False,
) -> None:
"""
Generate thermodynamic data for a species.
Populates the species.thermo attribute.
Args:
kinetics_flag (bool, optional): Whether this call is used for generating species statmech
for a rate coefficient calculation.
e0_only (bool, optional): Whether to only run statmech (w/o thermo) to compute E0.
"""
if not kinetics_flag:
# initialize the Arkane species_dict so that species for which thermo is calculated won't interfere
# with species used for a rate coefficient calculation.
arkane.input.species_dict = dict()
if self.sp_level.to_arkane_level_of_theory(variant='AEC', raise_error=False, warn=False) is None:
raise ValueError(f'Cannot compute thermo without a valid Arkane Level for AEC.')
if self.species is None:
raise InputError('Cannot not compute thermo without a species object.')
arkane_output_path = self.generate_arkane_species_file(species=self.species,
bac_type=self.bac_type)
if arkane_output_path is not None:
try:
arkane_species = arkane_input_species(self.species.label, self.species.arkane_file)
except ValueError:
arkane_species = arkane.input.species_dict[self.species.label]
self.species.rmg_species = Species(molecule=[self.species.mol])
self.species.rmg_species.reactive = True
if self.species.mol_list:
# add resonance structures for thermo determination
arkane_species.molecule = self.species.mol_list
self.species.rmg_species.molecule = self.species.mol_list
statmech_success = self.run_statmech(arkane_species=arkane_species,
arkane_file_path=self.species.arkane_file,
arkane_output_path=arkane_output_path,
bac_type=self.bac_type,
sp_level=self.sp_level,
plot=False)
if statmech_success:
self.species.e0 = arkane_species.conformer.E0.value_si * 0.001 # convert to kJ/mol
logger.debug(f'Assigned E0 to {self.species.label}: {self.species.e0:.2f} kJ/mol')
if not e0_only:
thermo_job = ThermoJob(arkane_species, 'NASA')
thermo_job.execute(output_directory=arkane_output_path, plot=True)
self.species.thermo = arkane_species.get_thermo_data()
if not kinetics_flag:
plotter.log_thermo(self.species.label, path=arkane_output_path)
else:
logger.error(f'Could not run statmech job for species {self.species.label}')
clean_output_directory(species_path=os.path.join(self.output_directory, 'Species', self.species.label))
def thermo(label, thermoClass):
global jobList, speciesDict
try:
spec = speciesDict[label]
except KeyError:
raise ValueError('Unknown species label {0!r} for thermo() job.'.format(label))
job = ThermoJob(species=spec, thermoClass=thermoClass)
jobList.append(job)
def thermo(label, thermoClass):
"""Generate a thermo job"""
global job_list, species_dict
try:
spec = species_dict[label]
except KeyError:
raise ValueError('Unknown species label {0!r} for thermo() job.'.format(label))
job = ThermoJob(species=spec, thermo_class=thermoClass)
job_list.append(job)
def setUp(cls):
"""A method that is run before each unit test in this class"""
spc = Species().fromSMILES('CCO')
log = GaussianLog(os.path.join(os.path.dirname(__file__), 'data', 'ethylene.log'))
spc.conformer = log.loadConformer()[0]
coords, numbers, masses = log.loadGeometry()
spc.conformer.coordinates = coords, 'angstroms'
spc.conformer.number = numbers
spc.conformer.mass = masses, 'amu'
cls.thermo_job = ThermoJob(species=spc, thermoClass='NASA')
def process(self):
"""
Process ARC outputs and generate thermo and kinetics.
"""
# Thermo:
species_list_for_thermo_parity = list()
species_for_thermo_lib = list()
species_for_transport_lib = list()
unconverged_species = list()
for species in self.species_dict.values():
if not species.is_ts and 'ALL converged' in self.output[species.label]['status']:
output_path = self._generate_arkane_species_file(species)
unique_arkane_species_label = False
while not unique_arkane_species_label:
try:
arkane_spc = arkane_input_species(str(species.label), species.arkane_file)
except ValueError:
species.label += '_' + str(randint(0, 999))
else:
unique_arkane_species_label = True
species.rmg_species = Species(molecule=[species.mol])
species.rmg_species.reactive = True
if species.mol_list:
arkane_spc.molecule = species.mol_list
species.rmg_species.molecule = species.mol_list # add resonance structures for thermo determination
statmech_success = self._run_statmech(arkane_spc, species.arkane_file, output_path,
use_bac=self.use_bac)
if not statmech_success:
continue
if species.generate_thermo:
thermo_job = ThermoJob(arkane_spc, 'NASA')
thermo_job.execute(output_directory=output_path, plot=False)
species.thermo = arkane_spc.getThermoData()
plotter.log_thermo(species.label, path=output_path)
species_for_thermo_lib.append(species)
if self.use_bac and self.sp_level:
# If BAC was used, save another Arkane YAML file of this species with no BAC, so it can be used
# for further rate calculations if needed (where the conformer.E0 has no BAC)
statmech_success = self._run_statmech(arkane_spc, species.arkane_file, output_path,
use_bac=False)
# if statmech_success:
# arkane_spc.label += str('_no_BAC')
# arkane_spc.thermo = None # otherwise thermo won't be calculated, although we don't really care
# thermo_job = ThermoJob(arkane_spc, 'NASA')
# thermo_job.execute(output_directory=output_path, plot=False)
try:
species.rmg_thermo = self.rmgdb.thermo.getThermoData(species.rmg_species)
except (ValueError, AttributeError) as e:
logger.info('Could not retrieve RMG thermo for species {0}, possibly due to missing 2D structure '
'(bond orders). Not including this species in the parity plots.'
'\nGot: {1}'.format(species.label, e.message))
else:
if species.generate_thermo:
species_list_for_thermo_parity.append(species)
if 'onedmin converged' in self.output[species.label]['status'].lower():
species_for_transport_lib.append(species)
elif 'ALL converged' not in self.output[species.label]['status']:
unconverged_species.append(species)
# Kinetics:
rxn_list_for_kinetics_plots = list()
arkane_spc_dict = dict() # a dictionary with all species and the TSs
for rxn in self.rxn_list:
logger.info('\n\n')
species = self.species_dict[rxn.ts_label] # The TS
if 'ALL converged' in self.output[species.label]['status'] and rxn.check_ts():
self.copy_freq_output_for_ts(species.label)
success = True
rxn_list_for_kinetics_plots.append(rxn)
output_path = self._generate_arkane_species_file(species)
arkane_ts = arkane_transition_state(str(species.label), species.arkane_file)
arkane_spc_dict[species.label] = arkane_ts
self._run_statmech(arkane_ts, species.arkane_file, kinetics=True)
for spc in rxn.r_species + rxn.p_species:
if spc.label not in arkane_spc_dict.keys():
# add an extra character to the arkane_species label to distinguish between species calculated
# for thermo and species calculated for kinetics (where we don't want to use BAC)
arkane_spc = arkane_input_species(str(spc.label + '_'), spc.arkane_file)
self._run_statmech(arkane_spc, spc.arkane_file, kinetics=True)
rxn.dh_rxn298 = sum([product.thermo.getEnthalpy(298) for product in arkane_spc_dict.values()
if product.label in rxn.products])\
- sum([reactant.thermo.getEnthalpy(298) for reactant in arkane_spc_dict.values()
if reactant.label in rxn.reactants])
arkane_rxn = arkane_reaction(label=str(rxn.label),
reactants=[str(label + '_') for label in arkane_spc_dict.keys()
if label in rxn.reactants],
products=[str(label + '_') for label in arkane_spc_dict.keys()
if label in rxn.products],
transitionState=rxn.ts_label, tunneling='Eckart')
kinetics_job = KineticsJob(reaction=arkane_rxn, Tmin=self.t_min, Tmax=self.t_max, Tcount=self.t_count)
logger.info('Calculating rate for reaction {0}'.format(rxn.label))
try:
kinetics_job.execute(output_directory=output_path, plot=False)
except (ValueError, OverflowError) as e:
# ValueError: One or both of the barrier heights of -9.3526 and 62.683 kJ/mol encountered in Eckart
# method are invalid.
#
# File "/home/alongd/Code/RMG-Py/arkane/kinetics.py", line 136, in execute
# self.generateKinetics(self.Tlist.value_si)
# File "/home/alongd/Code/RMG-Py/arkane/kinetics.py", line 179, in generateKinetics
# klist[i] = self.reaction.calculateTSTRateCoefficient(Tlist[i])
# File "rmgpy/reaction.py", line 818, in rmgpy.reaction.Reaction.calculateTSTRateCoefficient
# File "rmgpy/reaction.py", line 844, in rmgpy.reaction.Reaction.calculateTSTRateCoefficient
# OverflowError: math range error
logger.error('Failed to generate kinetics for {0} with message:\n{1}'.format(rxn.label, e))
success = False
if success:
rxn.kinetics = kinetics_job.reaction.kinetics
plotter.log_kinetics(species.label, path=output_path)
rxn.rmg_reactions = rmgdb.determine_rmg_kinetics(rmgdb=self.rmgdb, reaction=rxn.rmg_reaction,
dh_rxn298=rxn.dh_rxn298)
logger.info('\n\n')
output_dir = os.path.join(self.project_directory, 'output')
libraries_path = os.path.join(output_dir, 'RMG libraries')
if species_list_for_thermo_parity:
plotter.draw_thermo_parity_plots(species_list_for_thermo_parity, path=output_dir)
plotter.save_thermo_lib(species_for_thermo_lib, path=libraries_path,
name=self.project, lib_long_desc=self.lib_long_desc)
if species_for_transport_lib:
plotter.save_transport_lib(species_for_thermo_lib, path=libraries_path, name=self.project)
if rxn_list_for_kinetics_plots:
plotter.draw_kinetics_plots(rxn_list_for_kinetics_plots, path=output_dir,
t_min=self.t_min, t_max=self.t_max, t_count=self.t_count)
plotter.save_kinetics_lib(rxn_list=rxn_list_for_kinetics_plots, path=libraries_path,
name=self.project, lib_long_desc=self.lib_long_desc)
self._clean_output_directory()
if unconverged_species:
if not os.path.isdir(output_dir):
os.makedirs(output_dir)
with open(os.path.join(output_dir, 'unconverged_species.log'), 'w') as f:
for spc in unconverged_species:
f.write(spc.label)
if spc.is_ts:
f.write(str(' rxn: {0}'.format(spc.rxn_label)))
elif spc.mol is not None:
f.write(str(' SMILES: {0}'.format(spc.mol.toSMILES())))
f.write(str('\n'))
def process(self):
"""Process ARC outputs and generate thermo and kinetics"""
# Thermo:
species_list_for_thermo_parity = list()
species_for_thermo_lib = list()
for species in self.species_dict.values():
if not species.is_ts and 'ALL converged' in self.output[
species.label]['status']:
species_for_thermo_lib.append(species)
output_file_path = self._generate_arkane_species_file(species)
arkane_spc = arkane_species(str(species.label),
species.arkane_file)
if species.mol_list:
arkane_spc.molecule = species.mol_list
stat_mech_job = StatMechJob(arkane_spc, species.arkane_file)
stat_mech_job.applyBondEnergyCorrections = self.use_bac
stat_mech_job.modelChemistry = self.model_chemistry
stat_mech_job.frequencyScaleFactor = assign_frequency_scale_factor(
self.model_chemistry)
stat_mech_job.execute(outputFile=output_file_path, plot=False)
if species.generate_thermo:
thermo_job = ThermoJob(arkane_spc, 'NASA')
thermo_job.execute(outputFile=output_file_path, plot=False)
species.thermo = arkane_spc.getThermoData()
plotter.log_thermo(species.label, path=output_file_path)
species.rmg_species = Species(molecule=[species.mol])
species.rmg_species.reactive = True
if species.mol_list:
species.rmg_species.molecule = species.mol_list # add resonance structures for thermo determination
try:
species.rmg_thermo = self.rmgdb.thermo.getThermoData(
species.rmg_species)
except ValueError:
logging.info(
'Could not retrieve RMG thermo for species {0}, possibly due to missing 2D structure '
'(bond orders). Not including this species in the parity plots.'
.format(species.label))
else:
if species.generate_thermo:
species_list_for_thermo_parity.append(species)
# Kinetics:
rxn_list_for_kinetics_plots = list()
arkane_spc_dict = dict() # a dictionary with all species and the TSs
for rxn in self.rxn_list:
logging.info('\n\n')
species = self.species_dict[rxn.ts_label] # The TS
if 'ALL converged' in self.output[
species.label]['status'] and rxn.check_ts():
self.copy_freq_output_for_ts(species.label)
success = True
rxn_list_for_kinetics_plots.append(rxn)
output_file_path = self._generate_arkane_species_file(species)
arkane_ts = arkane_transition_state(str(species.label),
species.arkane_file)
arkane_spc_dict[species.label] = arkane_ts
stat_mech_job = StatMechJob(arkane_ts, species.arkane_file)
stat_mech_job.applyBondEnergyCorrections = False
if not self.model_chemistry:
stat_mech_job.modelChemistry = self.model_chemistry
else:
stat_mech_job.applyAtomEnergyCorrections = False
stat_mech_job.frequencyScaleFactor = assign_frequency_scale_factor(
self.model_chemistry)
stat_mech_job.execute(outputFile=None, plot=False)
for spc in rxn.r_species + rxn.p_species:
if spc.label not in arkane_spc_dict.keys():
# add an extra character to the arkane_species label to distinguish between species calculated
# for thermo and species calculated for kinetics (where we don't want to use BAC)
arkane_spc = arkane_species(str(spc.label + '_'),
spc.arkane_file)
stat_mech_job = StatMechJob(arkane_spc,
spc.arkane_file)
arkane_spc_dict[spc.label] = arkane_spc
stat_mech_job.applyBondEnergyCorrections = False
if not self.model_chemistry:
stat_mech_job.modelChemistry = self.model_chemistry
else:
stat_mech_job.applyAtomEnergyCorrections = False
stat_mech_job.frequencyScaleFactor = assign_frequency_scale_factor(
self.model_chemistry)
stat_mech_job.execute(outputFile=None, plot=False)
# thermo_job = ThermoJob(arkane_spc, 'NASA')
# thermo_job.execute(outputFile=None, plot=False)
# arkane_spc.thermo = arkane_spc.getThermoData()
rxn.dh_rxn298 = sum([product.thermo.getEnthalpy(298) for product in arkane_spc_dict.values()
if product.label in rxn.products])\
- sum([reactant.thermo.getEnthalpy(298) for reactant in arkane_spc_dict.values()
if reactant.label in rxn.reactants])
arkane_rxn = arkane_reaction(
label=str(rxn.label),
reactants=[
str(label + '_') for label in arkane_spc_dict.keys()
if label in rxn.reactants
],
products=[
str(label + '_') for label in arkane_spc_dict.keys()
if label in rxn.products
],
transitionState=rxn.ts_label,
tunneling='Eckart')
kinetics_job = KineticsJob(reaction=arkane_rxn,
Tmin=self.t_min,
Tmax=self.t_max,
Tcount=self.t_count)
logging.info('Calculating rate for reaction {0}'.format(
rxn.label))
try:
kinetics_job.execute(outputFile=output_file_path,
plot=False)
except ValueError as e:
"""
ValueError: One or both of the barrier heights of -9.35259 and 62.6834 kJ/mol encountered in Eckart
method are invalid.
"""
logging.error(
'Failed to generate kinetics for {0} with message:\n{1}'
.format(rxn.label, e))
success = False
if success:
rxn.kinetics = kinetics_job.reaction.kinetics
plotter.log_kinetics(species.label, path=output_file_path)
rxn.rmg_reactions = rmgdb.determine_rmg_kinetics(
rmgdb=self.rmgdb,
reaction=rxn.rmg_reaction,
dh_rxn298=rxn.dh_rxn298)
logging.info('\n\n')
output_dir = os.path.join(self.project_directory, 'output')
if species_list_for_thermo_parity:
plotter.draw_thermo_parity_plots(species_list_for_thermo_parity,
path=output_dir)
libraries_path = os.path.join(output_dir, 'RMG libraries')
# species_list = [spc for spc in self.species_dict.values()]
plotter.save_thermo_lib(species_for_thermo_lib,
path=libraries_path,
name=self.project,
lib_long_desc=self.lib_long_desc)
if rxn_list_for_kinetics_plots:
plotter.draw_kinetics_plots(rxn_list_for_kinetics_plots,
path=output_dir,
t_min=self.t_min,
t_max=self.t_max,
t_count=self.t_count)
libraries_path = os.path.join(output_dir, 'RMG libraries')
plotter.save_kinetics_lib(rxn_list=rxn_list_for_kinetics_plots,
path=libraries_path,
name=self.project,
lib_long_desc=self.lib_long_desc)
self.clean_output_directory()