def nasa_polynomial_task(mdriver_path, spc_locs_dct, thm_paths_dct, spc_dct,
spc_mod_dct, spc_mods, sort_info_lst, ref_scheme):
""" generate the nasa polynomials
"""
ckin_nasa_str_dct = {}
ckin_nasa_str_dct[0] = ''
ckin_path = output_path('CKIN', prefix=mdriver_path)
for spc_name in spc_locs_dct:
for idx, spc_locs in enumerate(spc_locs_dct[spc_name], start=1):
if idx not in ckin_nasa_str_dct:
ckin_nasa_str_dct[idx] = ''
spc_locs = tuple(spc_locs)
ioprinter.nasa('calculate', spc_name)
# for spc_mod in spc_mods:
# ioprinter.message('for: ', spc_locs, spc_mod)
# # Write the header describing the models used in thermo calcs
# ckin_nasa_str += writer.ckin.model_header(
# [spc_mod], spc_mod_dct, refscheme=ref_scheme)
# # Build and write NASA polynomial in CHEMKIN-format string
# # Call dies if you haven't run "write mess" task
# ckin_nasa_str += nasapoly.build_polynomial(
# spc_name, spc_dct,
# thm_paths_dct[spc_name][tuple(spc_locs)][spc_mod][0],
# thm_paths_dct[spc_name][tuple(spc_locs)][spc_mod][1],
# spc_locs=spc_locs, spc_mod=spc_mod)
# ckin_nasa_str += '\n\n'
ioprinter.message('for: ', spc_locs, ' combined models')
ckin_nasa_str_dct[idx] += writer.ckin.model_header(
spc_mods,
spc_mod_dct,
sort_info_lst=sort_info_lst,
refscheme=ref_scheme)
ckin_nasa_str_dct[idx] += nasapoly.build_polynomial(
spc_name,
spc_dct,
thm_paths_dct[spc_name][tuple(spc_locs)]['mod_total'][0],
thm_paths_dct[spc_name][tuple(spc_locs)]['mod_total'][1],
spc_locs_idx=idx - 1,
spc_mod=','.join(spc_mods))
ckin_nasa_str_dct[idx] += '\n\n'
ioprinter.info_message('CKIN NASA STR\n')
ioprinter.info_message(ckin_nasa_str_dct[idx])
ioprinter.message('for combined rid cids:', spc_locs_dct[spc_name])
ckin_nasa_str_dct[0] += writer.ckin.model_header(
spc_mods,
spc_mod_dct,
sort_info_lst=sort_info_lst,
refscheme=ref_scheme)
ckin_nasa_str_dct[0] += nasapoly.build_polynomial(
spc_name,
spc_dct,
thm_paths_dct[spc_name]['spc_total'][0],
thm_paths_dct[spc_name]['spc_total'][1],
spc_locs_idx='final',
spc_mod=','.join(spc_mods))
ckin_nasa_str_dct[0] += '\n\n'
ioprinter.info_message('CKIN NASA STR\n')
ioprinter.info_message(ckin_nasa_str_dct[0])
return ckin_nasa_str_dct, ckin_path
def build_polynomial(spc_name, spc_dct, pf_path, nasa_path):
""" Build a nasa polynomial
"""
# Read the temperatures from the pf.dat file, check if viable
temps = pfrunner.read_messpf_temps(pf_path)
ioprinter.nasa('fit', temps=temps)
ioprinter.generating('NASA polynomials', nasa_path)
# Generate forumula
spc_dct_i = spc_dct[spc_name]
formula_str = automol.inchi.formula_string(spc_dct_i['inchi'])
formula_dct = automol.inchi.formula(spc_dct_i['inchi'])
hform0 = spc_dct_i['Hfs'][0]
thermp_script_str = autorun.SCRIPT_DCT['thermp']
pac99_script_str = autorun.SCRIPT_DCT['pac99'].format(formula_str)
# Copy MESSPF output file to THERMP run dir and rename to pf.dat
pf_str = ioformat.pathtools.read_file(pf_path, 'pf.dat')
print('pf_path test:', pf_path)
print('pf_str test:', pf_str)
hform298, poly_str = autorun.thermo(
thermp_script_str, pac99_script_str, nasa_path,
pf_str, spc_name, formula_dct, hform0,
enthalpyt=0.0, breakt=1000.0, convert=True)
# Write the full CHEMKIN strings
ckin_str = writer.ckin.nasa_polynomial(hform0, hform298, poly_str)
full_ckin_str = '\n' + ckin_str
# Print thermo
return full_ckin_str
def build_polynomial(spc_name,
spc_dct,
pf_path,
nasa_path,
spc_locs_idx=None,
spc_mod=None):
""" For a given species: obtain partition function data read from a
MESSPF output file currently existing in the RUN filesystem as well as
the previously computed 0 K heat-of-formation from the species
dictionary. Then use this to run ThermP and PAC99 in the RUN filesystem
to generate a ChemKin-formatted 7-coefficient NASA polynomial.
:param spc_name: mechanism name of species to write MESSPF input for
:type spc_name: str
:param spc_dct:
:type spc_dct:
:param pf_path: path to existing MESSPF file in RUN filesystem
:type pf_path: str
:param nasa_path: path to run ThermP+PAC99 in RUN filesystem
:type nasa_path: str
:rtype: str
"""
# Read the temperatures from the pf.dat file, check if viable
ioprinter.nasa('fit', path=pf_path)
ioprinter.generating('NASA polynomials', nasa_path)
# Generate forumula
spc_dct_i = spc_dct[spc_name]
formula_str = automol.inchi.formula_string(spc_dct_i['inchi'])
formula_dct = automol.inchi.formula(spc_dct_i['inchi'])
if spc_locs_idx == 'final':
hform0 = spc_dct_i['Hfs']['final'][0]
spc_label = spc_name
elif spc_locs_idx is not None:
hform0 = spc_dct_i['Hfs'][spc_locs_idx][spc_mod][0]
spc_label = spc_name # + '_{:g}'.format(spc_locs_idx)
# spc_label = spc_name + '_' + spc_locs[1][:5]
else:
hform0 = spc_dct_i['Hfs'][0]
spc_label = spc_name
thermp_script_str = autorun.SCRIPT_DCT['thermp']
pac99_script_str = autorun.SCRIPT_DCT['pac99'].format(formula_str)
# Copy MESSPF output file to THERMP run dir and rename to pf.dat
pf_str = ioformat.pathtools.read_file(pf_path, 'pf.dat')
hform298, poly_str = autorun.thermo(thermp_script_str,
pac99_script_str,
nasa_path,
pf_str,
spc_label,
formula_dct,
hform0,
enthalpyt=0.0,
breakt=1000.0,
convert=True)
# Write the full CHEMKIN strings
ckin_str = '\n' + writer.ckin.nasa_polynomial(hform0, hform298, poly_str)
return ckin_str
def run(spc_rlst, therm_tsk_lst, pes_mod_dct, spc_mod_dct, spc_dct, run_prefix,
save_prefix):
""" main driver for thermo run
"""
# Print Header fo
ioprinter.info_message('Calculating Thermochem:')
ioprinter.runlst(('SPC', 0, 0), spc_rlst)
# ------------------------------------------------ #
# PREPARE INFORMATION TO PASS TO THERMDRIVER TASKS #
# ------------------------------------------------ #
# Build a list of the species to calculate thermochem for loops below
spc_mods = list(spc_mod_dct.keys()) # hack
split_spc_lst = split_unstable_spc(spc_rlst, spc_dct,
spc_mod_dct[spc_mods[0]], save_prefix)
spc_queue = parser.rlst.spc_queue('spc', tuple(split_spc_lst.values())[0])
# Build the paths [(messpf, nasa)], models and levels for each spc
thm_paths = thermo_paths(spc_dct, spc_queue, spc_mods, run_prefix)
# ----------------------------------- #
# RUN THE REQUESTED THERMDRIVER TASKS #
# ----------------------------------- #
# Write and Run MESSPF inputs to generate the partition functions
write_messpf_tsk = parser.run.extract_task('write_mess', therm_tsk_lst)
if write_messpf_tsk is not None:
ioprinter.messpf('write_header')
spc_mods, pes_mod = parser.models.extract_models(write_messpf_tsk)
for idx, spc_name in enumerate(spc_queue):
print('write test {}'.format(spc_name))
for spc_mod in spc_mods:
messpf_inp_str = thmroutines.qt.make_messpf_str(
pes_mod_dct[pes_mod]['therm_temps'], spc_dct, spc_name,
pes_mod_dct[pes_mod], spc_mod_dct[spc_mod], run_prefix,
save_prefix)
ioprinter.messpf('input_string')
ioprinter.info_message(messpf_inp_str)
autorun.write_input(thm_paths[idx][spc_mod][0],
messpf_inp_str,
input_name='pf.inp')
# Run the MESSPF files that have been written
run_messpf_tsk = parser.run.extract_task('run_mess', therm_tsk_lst)
if run_messpf_tsk is not None:
spc_mod, pes_mod = parser.models.extract_models(run_messpf_tsk)
spc_mods = parser.models.split_model(spc_mod[0])
ioprinter.messpf('run_header')
for idx, spc_name in enumerate(spc_queue):
_spc_mods, coeffs, operators = spc_mods
# Run MESSPF for all requested models, combine the PFS at the end
ioprinter.message('Run MESSPF: {}'.format(spc_name), newline=1)
_pfs = []
for spc_mod in _spc_mods:
autorun.run_script(autorun.SCRIPT_DCT['messpf'],
thm_paths[idx][spc_mod][0])
_pfs.append(
pfrunner.mess.read_messpf(thm_paths[idx][spc_mod][0]))
final_pf = pfrunner.mess.combine_pfs(_pfs, coeffs, operators)
# need to clean thm path build
tot_idx = len(spc_mods)
spc_info = sinfo.from_dct(spc_dct[spc_name])
spc_fml = automol.inchi.formula_string(spc_info[0])
thm_prefix = [spc_fml, automol.inchi.inchi_key(spc_info[0])]
thm_paths[idx]['final'] = (job_path(run_prefix,
'MESS',
'PF',
thm_prefix,
locs_idx=tot_idx),
job_path(run_prefix,
'THERM',
'NASA',
thm_prefix,
locs_idx=tot_idx))
pfrunner.mess.write_mess_output(fstring(
spc_dct[spc_name]['inchi']),
final_pf,
thm_paths[idx]['final'][0],
filename='pf.dat')
# Use MESS partition functions to compute thermo quantities
run_fit_tsk = parser.run.extract_task('run_fits', therm_tsk_lst)
if run_fit_tsk is not None:
spc_mods, pes_mod = parser.models.extract_models(run_fit_tsk)
pes_mod_dct_i = pes_mod_dct[pes_mod]
ioprinter.nasa('header')
chn_basis_ene_dct = {}
for idx, spc_name in enumerate(spc_queue):
# Take species model and add it to the chn_basis_ene dct
spc_mod = spc_mods[0]
spc_mod_dct_i = spc_mod_dct[spc_mod]
if spc_mod not in chn_basis_ene_dct:
chn_basis_ene_dct[spc_mod] = {}
# Get the reference scheme and energies (ref in different place)
ref_scheme = pes_mod_dct_i['therm_fit']['ref_scheme']
ref_enes = pes_mod_dct_i['therm_fit']['ref_enes']
# Determine info about the basis species used in thermochem calcs
basis_dct, uniref_dct = thmroutines.basis.prepare_refs(
ref_scheme, spc_dct, [[spc_name, None]], run_prefix,
save_prefix)
# Get the basis info for the spc of interest
spc_basis, coeff_basis = basis_dct[spc_name]
# Get the energies for the spc and its basis
ene_basis = []
energy_missing = False
for spc_basis_i in spc_basis:
if spc_basis_i in chn_basis_ene_dct[spc_mod]:
ioprinter.message(
'Energy already found for basis species: ' +
spc_basis_i)
ene_basis.append(chn_basis_ene_dct[spc_mod][spc_basis_i])
else:
ioprinter.message(
'Energy will be determined for basis species: ' +
spc_basis_i)
energy_missing = True
if not energy_missing:
pf_filesystems = filesys.models.pf_filesys(spc_dct[spc_name],
spc_mod_dct_i,
run_prefix,
save_prefix,
saddle=False)
ene_spc = ene.read_energy(spc_dct[spc_name],
pf_filesystems,
spc_mod_dct_i,
run_prefix,
read_ene=True,
read_zpe=True,
saddle=False)
else:
ene_spc, ene_basis = thmroutines.basis.basis_energy(
spc_name, spc_basis, uniref_dct, spc_dct, spc_mod_dct_i,
run_prefix, save_prefix)
for spc_basis_i, ene_basis_i in zip(spc_basis, ene_basis):
chn_basis_ene_dct[spc_mod][spc_basis_i] = ene_basis_i
# Calculate and store the 0 K Enthalpy
hf0k = thmroutines.heatform.calc_hform_0k(ene_spc,
ene_basis,
spc_basis,
coeff_basis,
ref_set=ref_enes)
spc_dct[spc_name]['Hfs'] = [hf0k]
# Write the NASA polynomials in CHEMKIN format
ckin_nasa_str = ''
ckin_path = output_path('CKIN')
for idx, spc_name in enumerate(spc_queue):
ioprinter.nasa('calculate', spc_name)
# Write the header describing the models used in thermo calcs
ckin_nasa_str += writer.ckin.model_header(spc_mods, spc_mod_dct)
# Build and write the NASA polynomial in CHEMKIN-format string
# Call dies if you haven't run "write mess" task
ckin_nasa_str += thmroutines.nasapoly.build_polynomial(
spc_name, spc_dct, thm_paths[idx]['final'][0],
thm_paths[idx]['final'][1])
ckin_nasa_str += '\n\n'
print(ckin_nasa_str)
nasa7_params_all = chemkin_io.parser.thermo.create_spc_nasa7_dct(
ckin_nasa_str)
# print('ckin_nasa_str test', ckin_nasa_str)
ioprinter.info_message(
'SPECIES H(0 K) H(298 K) S(298 K) Cp(300 K) Cp(500 K) Cp(1000 K) Cp(1500 K)\n'
)
ioprinter.info_message(
' kcal/mol kcal/mol cal/(mol K) ... \n')
for spc_name in nasa7_params_all:
nasa7_params = nasa7_params_all[spc_name]
whitespace = 18 - len(spc_name)
h0 = spc_dct[spc_name]['Hfs'][0]
h298 = mechanalyzer.calculator.thermo.enthalpy(
nasa7_params, 298.15) / 1000.
s298 = mechanalyzer.calculator.thermo.entropy(nasa7_params, 298.15)
cp300 = mechanalyzer.calculator.thermo.heat_capacity(
nasa7_params, 300)
cp500 = mechanalyzer.calculator.thermo.heat_capacity(
nasa7_params, 500)
cp1000 = mechanalyzer.calculator.thermo.heat_capacity(
nasa7_params, 1000)
cp1500 = mechanalyzer.calculator.thermo.heat_capacity(
nasa7_params, 1500)
whitespace = whitespace * ' '
ioprinter.info_message(
'{}{}{:>7.2f}{:>9.2f}{:>9.2f}{:>9.2f}{:>9.2f}{:>9.2f}{:>9.2f}'.
format(spc_name, whitespace, h0, h298, s298, cp300, cp500,
cp1000, cp1500))
# Write all of the NASA polynomial strings
writer.ckin.write_nasa_file(ckin_nasa_str, ckin_path)
def run(pes_rlst, spc_rlst, therm_tsk_lst, pes_mod_dct, spc_mod_dct, spc_dct,
thy_dct, run_prefix, save_prefix, mdriver_path):
""" Executes all thermochemistry tasks.
:param pes_rlst: species from PESs to run
[(PES formula, PES idx, SUP-PES idx)
(CHANNEL idx, (REACS, PRODS))
:type pes_rlst: tuple(dict[str: dict])
:param spc_rlst: lst of species to run
:type spc_rlst: tuple(dict[str: dict])
:param es_tsk_lst: list of the electronic structure tasks
:type es_tsk_lst: tuple(tuple(str, str, dict))
:param spc_dct: species information
:type spc_dct: dict[str:dict]
:param glob_dct: global information for all species
:type glob_dct: dict[str: dict]
:param thy_dct: all of the theory information
:type thy_dct: dict[str:dict]
:param run_prefix: root-path to the run-filesystem
:type run_prefix: str
:param save_prefix: root-path to the save-filesystem
:type save_prefix: str
:param mdriver_path: path where mechdriver is running
:type mdriver_path: str
"""
# Print Header
ioprinter.info_message('Calculating Thermochem:')
ioprinter.runlst(list(spc_rlst.keys())[0], list(spc_rlst.values())[0])
# ------------------------------------------------ #
# PREPARE INFORMATION TO PASS TO THERMDRIVER TASKS #
# ------------------------------------------------ #
# Parse Tasks
write_messpf_tsk = parser.run.extract_task('write_mess', therm_tsk_lst)
run_messpf_tsk = parser.run.extract_task('run_mess', therm_tsk_lst)
run_fit_tsk = parser.run.extract_task('run_fits', therm_tsk_lst)
# Build a list of the species to calculate thermochem for loops below
# and build the paths [(messpf, nasa)], models and levels for each spc
cnf_range = write_messpf_tsk[-1]['cnf_range']
sort_str = write_messpf_tsk[-1]['sort']
spc_locs_dct, thm_paths_dct, sort_info_lst = _set_spc_queue(
spc_mod_dct, pes_rlst, spc_rlst, spc_dct, thy_dct, save_prefix,
run_prefix, cnf_range, sort_str)
# ----------------------------------- #
# RUN THE REQUESTED THERMDRIVER TASKS #
# ----------------------------------- #
# Write and Run MESSPF inputs to generate the partition functions
if write_messpf_tsk is not None:
thermo_tasks.write_messpf_task(write_messpf_tsk, spc_locs_dct, spc_dct,
pes_mod_dct, spc_mod_dct, run_prefix,
save_prefix, thm_paths_dct)
# Run the MESSPF files that have been written
if run_messpf_tsk is not None:
thermo_tasks.run_messpf_task(run_messpf_tsk, spc_locs_dct, spc_dct,
thm_paths_dct)
# Use MESS partition functions to compute thermo quantities
if run_fit_tsk is not None:
ioprinter.nasa('header')
spc_mods, pes_mod = parser.models.extract_models(run_fit_tsk)
pes_mod_dct_i = pes_mod_dct[pes_mod]
# Get the reference scheme and energies (ref in different place)
ref_scheme = pes_mod_dct_i['therm_fit']['ref_scheme']
ref_enes = pes_mod_dct_i['therm_fit']['ref_enes']
spc_dct = thermo_tasks.get_heats_of_formation(spc_locs_dct, spc_dct,
spc_mods, spc_mod_dct,
ref_scheme, ref_enes,
run_prefix, save_prefix)
# This has to happen down here because the weights rely on
# The heats of formation
print('in run_fit_tsk for thermo_driver boltzmann')
spc_dct = thermo_tasks.produce_boltzmann_weighted_conformers_pf(
run_messpf_tsk, spc_locs_dct, spc_dct, thm_paths_dct)
# Write the NASA polynomials in CHEMKIN format
ckin_nasa_str_dct, ckin_path = thermo_tasks.nasa_polynomial_task(
mdriver_path, spc_locs_dct, thm_paths_dct, spc_dct, spc_mod_dct,
spc_mods, sort_info_lst, ref_scheme)
for idx, nasa_str in ckin_nasa_str_dct.items():
ioprinter.print_thermo(spc_dct, nasa_str, spc_locs_dct, idx,
spc_mods[0])
# Write all of the NASA polynomial strings
writer.ckin.write_nasa_file(nasa_str, ckin_path, idx=idx)
def run(pes_rlst, spc_rlst,
therm_tsk_lst,
pes_mod_dct, spc_mod_dct,
spc_dct,
run_prefix, save_prefix):
""" Executes all thermochemistry tasks.
:param pes_rlst: species from PESs to run
[(PES formula, PES idx, SUP-PES idx)
(CHANNEL idx, (REACS, PRODS))
:type pes_rlst: tuple(dict[str: dict])
:param spc_rlst: lst of species to run
:type spc_rlst: tuple(dict[str: dict])
:param es_tsk_lst: list of the electronic structure tasks
tuple(tuple(obj, tsk, keyword_dict))
:type es_tsk_lst: tuple(tuple(str, str, dict))
:param spc_dct: species information
dict[spc_name: spc_information]
:type spc_dct: dict[str:dict]
:param glob_dct: global information for all species
dict[spc_name: spc_information]
:type glob_dct: dict[str: dict]
:param thy_dct: all of the theory information
dict[thy name: inf]
:type thy_dct: dict[str:dict]
:param run_prefix: root-path to the run-filesystem
:type run_prefix: str
:param save_prefix: root-path to the save-filesystem
:type save_prefix: str
"""
# Print Header
ioprinter.info_message('Calculating Thermochem:')
ioprinter.runlst(('SPC', 0, 0), spc_rlst)
# ------------------------------------------------ #
# PREPARE INFORMATION TO PASS TO THERMDRIVER TASKS #
# ------------------------------------------------ #
# Build a list of the species to calculate thermochem for loops below
spc_mods = list(spc_mod_dct.keys()) # hack
spc_mod_dct_i = spc_mod_dct[spc_mods[0]]
split_rlst = split_unstable_full(
pes_rlst, spc_rlst, spc_dct, spc_mod_dct_i, save_prefix)
spc_queue = parser.rlst.spc_queue(
tuple(split_rlst.values())[0], 'SPC')
# Build the paths [(messpf, nasa)], models and levels for each spc
thm_paths = thermo_paths(spc_dct, spc_queue, spc_mods, run_prefix)
# ----------------------------------- #
# RUN THE REQUESTED THERMDRIVER TASKS #
# ----------------------------------- #
# Write and Run MESSPF inputs to generate the partition functions
write_messpf_tsk = parser.run.extract_task('write_mess', therm_tsk_lst)
if write_messpf_tsk is not None:
ioprinter.messpf('write_header')
spc_mods, pes_mod = parser.models.extract_models(write_messpf_tsk)
for idx, spc_name in enumerate(spc_queue):
print('write test {}'.format(spc_name))
for spc_mod in spc_mods:
messpf_inp_str = thmroutines.qt.make_messpf_str(
pes_mod_dct[pes_mod]['therm_temps'],
spc_dct, spc_name,
pes_mod_dct[pes_mod], spc_mod_dct[spc_mod],
run_prefix, save_prefix)
ioprinter.messpf('input_string')
ioprinter.info_message(messpf_inp_str)
autorun.write_input(
thm_paths[idx][spc_mod][0], messpf_inp_str,
input_name='pf.inp')
# Run the MESSPF files that have been written
run_messpf_tsk = parser.run.extract_task('run_mess', therm_tsk_lst)
if run_messpf_tsk is not None:
spc_mod, pes_mod = parser.models.extract_models(run_messpf_tsk)
spc_mods = parser.models.split_model(spc_mod[0])
ioprinter.messpf('run_header')
for idx, spc_name in enumerate(spc_queue):
_spc_mods, coeffs, operators = spc_mods
# Run MESSPF for all requested models, combine the PFS at the end
ioprinter.message('Run MESSPF: {}'.format(spc_name), newline=1)
_pfs = []
for spc_mod in _spc_mods:
autorun.run_script(
autorun.SCRIPT_DCT['messpf'],
thm_paths[idx][spc_mod][0])
_pfs.append(
reader.mess.messpf(thm_paths[idx][spc_mod][0]))
final_pf = thermfit.pf.combine(_pfs, coeffs, operators)
# need to clean thm path build
tdx = len(spc_mods)
spc_info = sinfo.from_dct(spc_dct[spc_name])
spc_fml = automol.inchi.formula_string(spc_info[0])
thm_prefix = [spc_fml, automol.inchi.inchi_key(spc_info[0])]
thm_paths[idx]['final'] = (
job_path(run_prefix, 'MESS', 'PF', thm_prefix, locs_idx=tdx),
job_path(run_prefix, 'THERM', 'NASA', thm_prefix, locs_idx=tdx)
)
writer.mess.output(
fstring(spc_dct[spc_name]['inchi']),
final_pf, thm_paths[idx]['final'][0],
filename='pf.dat')
# Use MESS partition functions to compute thermo quantities
run_fit_tsk = parser.run.extract_task('run_fits', therm_tsk_lst)
if run_fit_tsk is not None:
spc_mods, pes_mod = parser.models.extract_models(run_fit_tsk)
pes_mod_dct_i = pes_mod_dct[pes_mod]
ioprinter.nasa('header')
chn_basis_ene_dct = {}
for idx, spc_name in enumerate(spc_queue):
# Take species model and add it to the chn_basis_ene dct
spc_mod = spc_mods[0]
spc_mod_dct_i = spc_mod_dct[spc_mod]
if spc_mod not in chn_basis_ene_dct:
chn_basis_ene_dct[spc_mod] = {}
# Get the reference scheme and energies (ref in different place)
ref_scheme = pes_mod_dct_i['therm_fit']['ref_scheme']
ref_enes = pes_mod_dct_i['therm_fit']['ref_enes']
# Determine info about the basis species used in thermochem calcs
basis_dct, uniref_dct = thermfit.prepare_refs(
ref_scheme, spc_dct, (spc_name,))
# Get the basis info for the spc of interest
spc_basis, coeff_basis = basis_dct[spc_name]
# Get the energies for the spc and its basis
ene_basis = []
energy_missing = False
for spc_basis_i in spc_basis:
if spc_basis_i in chn_basis_ene_dct[spc_mod]:
ioprinter.message(
'Energy already found for basis species: '
+ spc_basis_i)
ene_basis.append(chn_basis_ene_dct[spc_mod][spc_basis_i])
else:
ioprinter.message(
'Energy will be determined for basis species: '
+ spc_basis_i)
energy_missing = True
if not energy_missing:
pf_filesystems = filesys.models.pf_filesys(
spc_dct[spc_name], spc_mod_dct_i,
run_prefix, save_prefix, saddle=False)
ene_spc = ene.read_energy(
spc_dct[spc_name], pf_filesystems, spc_mod_dct_i,
run_prefix, read_ene=True, read_zpe=True, saddle=False)
else:
ene_spc, ene_basis = thmroutines.basis.basis_energy(
spc_name, spc_basis, uniref_dct, spc_dct,
spc_mod_dct_i,
run_prefix, save_prefix)
for spc_basis_i, ene_basis_i in zip(spc_basis, ene_basis):
chn_basis_ene_dct[spc_mod][spc_basis_i] = ene_basis_i
# Calculate and store the 0 K Enthalpy
hf0k = thermfit.heatform.calc_hform_0k(
ene_spc, ene_basis, spc_basis, coeff_basis, ref_set=ref_enes)
spc_dct[spc_name]['Hfs'] = [hf0k]
# Write the NASA polynomials in CHEMKIN format
ckin_nasa_str = ''
ckin_path = output_path('CKIN')
for idx, spc_name in enumerate(spc_queue):
ioprinter.nasa('calculate', spc_name)
# Write the header describing the models used in thermo calcs
ckin_nasa_str += writer.ckin.model_header(spc_mods, spc_mod_dct)
# Build and write the NASA polynomial in CHEMKIN-format string
# Call dies if you haven't run "write mess" task
ckin_nasa_str += thmroutines.nasapoly.build_polynomial(
spc_name, spc_dct,
thm_paths[idx]['final'][0], thm_paths[idx]['final'][1])
ckin_nasa_str += '\n\n'
print('CKIN NASA STR\n')
print(ckin_nasa_str)
nasa7_params_all = chemkin_io.parser.thermo.create_spc_nasa7_dct(
ckin_nasa_str)
ioprinter.info_message(
'SPECIES\t\tH(0 K)[kcal/mol]\tH(298 K)[kcal/mol]\t' +
'S(298 K)[cal/mol K]\n')
for spc_name in nasa7_params_all:
nasa7_params = nasa7_params_all[spc_name]
ht0 = spc_dct[spc_name]['Hfs'][0]
ht298 = mechanalyzer.calculator.thermo.enthalpy(
nasa7_params, 298.15)
st298 = mechanalyzer.calculator.thermo.entropy(
nasa7_params, 298.15)
ioprinter.info_message(
'{}\t{:3.2f}\t{:3.2f}\t{:3.2f}'.format(
spc_name, ht0, ht298/1000., st298))
# Write all of the NASA polynomial strings
writer.ckin.write_nasa_file(ckin_nasa_str, ckin_path)