def kinetics(label, Tmin=None, Tmax=None, Tlist=None, Tcount=0, sensitivity_conditions=None):
global jobList, reactionDict
try:
rxn = reactionDict[label]
except KeyError:
raise ValueError('Unknown reaction label {0!r} for kinetics() job.'.format(label))
job = KineticsJob(reaction=rxn, Tmin=Tmin, Tmax=Tmax, Tcount=Tcount, Tlist=Tlist,
sensitivity_conditions=sensitivity_conditions)
jobList.append(job)
def test_give_tlist_for_kineticsjob(self):
"""
Ensures that the proper temperature ranges are set when Tlist is specified
"""
rxn = Reaction(transition_state=TransitionState())
t_list = [50.7, 100, 300, 800, 1255]
kjob = KineticsJob(rxn, Tlist=(t_list, 'K'))
self.assertEqual(min(t_list), kjob.Tmin.value_si)
self.assertEqual(max(t_list), kjob.Tmax.value_si)
self.assertEqual(len(t_list), kjob.Tcount)
def test_give_temperature_range_for_kineticsjob(self):
"""
Ensures that Tlist is set when a range of temperatures is specified
"""
rxn = Reaction(transition_state=TransitionState())
kjob = KineticsJob(rxn, Tmin=(50, 'K'), Tmax=(4000, 'K'), Tcount=5)
self.assertEqual(5, len(kjob.Tlist.value_si))
self.assertEqual(50, min(kjob.Tlist.value_si))
self.assertAlmostEqual(4000, max(kjob.Tlist.value_si))
inverse_tlist = 1 / kjob.Tlist.value_si
self.assertAlmostEqual(inverse_tlist[1] - inverse_tlist[0],
inverse_tlist[-1] - inverse_tlist[-2],
msg='The points for fitting do not appear 1/T spaced. '
'Obtained values of {0} and {1}'.format(inverse_tlist[1] - inverse_tlist[0],
inverse_tlist[-1] - inverse_tlist[-2]))
def test_get_tlist_for_kineticsjob(self):
"""
Ensures that Tlist is set when no range is specified
"""
rxn = Reaction(transition_state=TransitionState())
kjob = KineticsJob(rxn)
self.assertAlmostEqual(298, kjob.Tmin.value_si)
self.assertAlmostEqual(2500, kjob.Tmax.value_si)
self.assertEqual(50, kjob.Tcount)
self.assertEqual(50, len(kjob.Tlist.value_si))
self.assertAlmostEqual(298, min(kjob.Tlist.value_si))
self.assertAlmostEqual(2500, max(kjob.Tlist.value_si))
inverse_tlist = 1 / kjob.Tlist.value_si
self.assertAlmostEqual(inverse_tlist[1] - inverse_tlist[0],
inverse_tlist[-1] - inverse_tlist[-2],
msg='The points for fitting do not appear 1/T spaced. '
'Obtained values of {0} and {1}'.format(inverse_tlist[1] - inverse_tlist[0],
inverse_tlist[-1] - inverse_tlist[-2]))
def kinetics(label,
Tmin=None,
Tmax=None,
Tlist=None,
Tcount=0,
sensitivity_conditions=None,
three_params=True):
"""Generate a kinetics job"""
global job_list, reaction_dict
try:
rxn = reaction_dict[label]
except KeyError:
raise ValueError(
'Unknown reaction label {0!r} for kinetics() job.'.format(label))
job = KineticsJob(reaction=rxn,
Tmin=Tmin,
Tmax=Tmax,
Tcount=Tcount,
Tlist=Tlist,
sensitivity_conditions=sensitivity_conditions,
three_params=three_params)
job_list.append(job)
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()
def compute_high_p_rate_coefficient(self) -> None:
"""
Generate a high pressure rate coefficient for a reaction.
Populates the reaction.kinetics attribute.
"""
ts_species = self.species_dict[self.reaction.ts_label]
if self.output_dict[ts_species.label]['convergence']:
success = True
arkane_output_path = self.generate_arkane_species_file(species=ts_species,
bac_type=None)
arkane_ts_species = arkane_transition_state(ts_species.label, ts_species.arkane_file)
statmech_success = self.run_statmech(arkane_species=arkane_ts_species,
arkane_file_path=ts_species.arkane_file,
arkane_output_path=arkane_output_path,
bac_type=None,
sp_level=self.sp_level,
plot=False)
if not statmech_success:
logger.error(f'Could not run statmech job for TS species {ts_species.label} '
f'of reaction {self.reaction.label}')
else:
ts_species.e0 = arkane_ts_species.conformer.E0.value_si * 0.001 # convert to kJ/mol
self.reaction.check_ts()
self.reaction.dh_rxn298 = \
sum([product.thermo.get_enthalpy(298) * self.reaction.get_species_count(product, well=1)
for product in self.reaction.p_species]) \
- sum([reactant.thermo.get_enthalpy(298) * self.reaction.get_species_count(reactant, well=0)
for reactant in self.reaction.r_species])
reactant_labels, product_labels = list(), list()
for reactant in self.reaction.r_species:
reactant_labels.extend([reactant.label] * self.reaction.get_species_count(reactant, well=0))
for product in self.reaction.p_species:
product_labels.extend([product.label] * self.reaction.get_species_count(product, well=1))
arkane_rxn = arkane_reaction(label=self.reaction.label,
reactants=reactant_labels,
products=product_labels,
transitionState=self.reaction.ts_label,
tunneling='Eckart')
kinetics_job = KineticsJob(reaction=arkane_rxn, Tmin=self.T_min, Tmax=self.T_max, Tcount=self.T_count,
three_params=self.three_params)
if self.three_params:
msg = 'using the modified three-parameter Arrhenius equation k = A * (T/T0)^n * exp(-Ea/RT)'
else:
msg = 'using the classical two-parameter Arrhenius equation k = A * exp(-Ea/RT)'
logger.info(f'Calculating rate for reaction {self.reaction.label} {msg}.')
try:
kinetics_job.execute(output_directory=arkane_output_path, plot=True)
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 "RMG-Py/arkane/kinetics.py", line 136, in execute
# generateKinetics(Tlist.value_si)
# File "RMG-Py/arkane/kinetics.py", line 179, in generateKinetics
# klist[i] = 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(f'Failed to generate kinetics for {self.reaction.label}, got:\n{e}')
success = False
if success:
self.reaction.kinetics = kinetics_job.reaction.kinetics
plotter.log_kinetics(ts_species.label, path=arkane_output_path)
# initialize the Arkane species_dict in case another reaction uses the same species
arkane.input.species_dict = dict()
clean_output_directory(species_path=os.path.join(self.output_directory, 'rxns', ts_species.label),
is_ts=True)
