Exemplo n.º 1
0
    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()
Exemplo n.º 2
0
    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'))
Exemplo n.º 3
0
    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)