def make_spc_mess_str(spc_dct, spc_name,
pes_mod_dct_i, spc_mod_dct_i,
run_prefix, save_prefix):
""" Write the MESS input file strings
"""
# Read the filesystem for the information
inf_dct, _ = build.read_spc_data(
spc_dct, spc_name,
pes_mod_dct_i, spc_mod_dct_i,
run_prefix, save_prefix, {}, calc_chn_ene=False)
# Write the mol block
mess_writer = getattr(BLOCK_MODULE, inf_dct['writer'])
mess_block, dat_str_dct = mess_writer(inf_dct)
if inf_dct['writer'] == 'tau_block':
zero_energy = None
else:
zero_energy = inf_dct['zpe_chnlvl']
# Write the mess string
spc_str = mess_io.writer.species(
spc_label=spc_name,
spc_data=mess_block,
zero_ene=zero_energy
)
return spc_str, dat_str_dct
def get_channel_data(reacs, prods, tsname, spc_dct, model_basis_energy_dct,
pes_model_dct_i, spc_model_dct_i, run_prefix,
save_prefix):
""" For all species and transition state for the channel and
read all required data from the save filesys, then process and
format it to be able to write it into a MESS filesystem.
:param tsname: mechanism name of the transition state
:param reacs: mechanisms name for the reactants of the reaction channel
:type reacs: tuple(str)
:param prods: mechanisms name for the products of the reaction channel
:type prods: tuple(str)
"""
# Initialize the dict
chnl_infs = {}
# Initialize the symm_barrier variable for TS
# symm_barrier = False
# Determine the MESS data for the reactants and products
# Gather data or set fake information for dummy reactants/products
chnl_infs['reacs'], chnl_infs['prods'] = [], []
for rgts, side in zip((reacs, prods), ('reacs', 'prods')):
for rgt in rgts:
chnl_infs_i, model_basis_energy_dct = build.read_spc_data(
spc_dct, rgt, pes_model_dct_i, spc_model_dct_i, run_prefix,
save_prefix, model_basis_energy_dct)
chnl_infs[side].append(chnl_infs_i)
# if side in rxn['dummy']:
# symm_barrier = True
# for _ in range(len(rxn[side])):
# chnl_infs[side].append({'ene_chnlvl': 0.00})
# Set up data for TS
chnl_infs['ts'] = []
tsnames = [name for name in spc_dct.keys() if tsname in name]
for name in tsnames:
inf_dct, model_basis_energy_dct = build.read_ts_data(
spc_dct, name, reacs, prods, pes_model_dct_i, spc_model_dct_i,
run_prefix, save_prefix, model_basis_energy_dct)
chnl_infs['ts'].append(inf_dct)
# turn back on with fixed TSs
# chnl_infs['ts']['symm_barrier'] = symm_barrier
# Set up the info for the wells
rwell_model = spc_model_dct_i['ts']['rwells']
pwell_model = spc_model_dct_i['ts']['pwells']
rxn_class = spc_dct[tsname + '_0']['class']
if need_fake_wells(rxn_class, rwell_model):
chnl_infs['fake_vdwr'] = copy.deepcopy(chnl_infs['reacs'])
# pwell_model = spc_model_dct_i['ts']['pwells']
if need_fake_wells(rxn_class, pwell_model):
chnl_infs['fake_vdwp'] = copy.deepcopy(chnl_infs['prods'])
return chnl_infs, model_basis_energy_dct
def make_messpf_str(temps, spc_dct, spc_name, spc_locs, pes_mod_dct_i,
spc_mod_dct_i, run_prefix, save_prefix):
""" Reads and processes all information in the save filesys for
a given species that are required for MESSPF calculations,
as specified by the model dictionaries built from user input.
:param temps: temperatures to calculate partition functions (in K)
:type temps: tuple(float)
:param spc_dct:
:type spc_dct:
:param spc_name: mechanism name of species to write MESSPF input for
:type spc_name: str
:param pes_mod_dct_i: keyword dict of specific kin model
:type pes_mod_dct_i: dict[]
:param spc_mod_dct_i: keyword dict of specific species model
:type spc_mod_dct_i: 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
:rtype: str
"""
# Read the filesystem for the information
inf_dct, _ = build.read_spc_data(spc_dct,
spc_name,
pes_mod_dct_i,
spc_mod_dct_i,
run_prefix,
save_prefix, {},
calc_chn_ene=False,
spc_locs=spc_locs)
# Write the header string for the MESS input file
globkey_str = mess_io.writer.global_pf_input(temperatures=temps,
rel_temp_inc=0.001,
atom_dist_min=0.6)
# Write the species data block for the MESS input file
mess_writer = getattr(blocks, inf_dct['writer'])
mess_block, dat_str_dct = mess_writer(inf_dct)
if inf_dct['writer'] == 'tau_block':
zero_energy = None
else:
zero_energy = inf_dct['zpe_chnlvl']
spc_str = mess_io.writer.species(spc_label=spc_name,
spc_data=mess_block,
zero_ene=zero_energy)
# Combine the strings together to create full MESS input file string
mess_inp_str = mess_io.writer.messpf_inp_str(globkey_str, spc_str)
return mess_inp_str, dat_str_dct
def set_reference_ene(rxn_lst, spc_dct, tsk_key_dct,
model_basis_energy_dct,
thy_dct, pes_model_dct_i, spc_model_dct_i,
run_prefix, save_prefix, ref_idx=0):
""" Sets the reference species for the PES for which all energies
are scaled relative to.
"""
# Set the index for the reference species, right now defualt to 1st spc
ref_rxn = rxn_lst[ref_idx]
_, (ref_rgts, _) = ref_rxn
ioprinter.info_message(
'Determining the reference energy for PES...', newline=1)
ioprinter.info_message(
' - Reference species assumed to be the',
f' first set of reactants on PES: {"+".join(ref_rgts)}')
# Get the model for the first reference species
cnf_range = tsk_key_dct['cnf_range']
sort_info_lst = filesys.mincnf.sort_info_lst(tsk_key_dct['sort'], thy_dct)
print('sort info list in ref ene', sort_info_lst)
# Get the elec+zpe energy for the reference species
ioprinter.info_message('')
hf0k = 0.0
for rgt in ref_rgts:
spc_locs_lst = filesys.models.get_spc_locs_lst(
spc_dct[rgt], spc_model_dct_i,
run_prefix, save_prefix, saddle=False,
cnf_range=cnf_range, sort_info_lst=sort_info_lst,
name=rgt)
chnl_infs_i, model_basis_energy_dct = build.read_spc_data(
spc_dct, rgt,
pes_model_dct_i, spc_model_dct_i,
run_prefix, save_prefix, model_basis_energy_dct,
spc_locs=spc_locs_lst[0])
hf0k += chnl_infs_i['ene_chnlvl']
# hf0k += chnl_infs_i['ene_tsref']
return hf0k, model_basis_energy_dct
def get_channel_data(reacs, prods, tsname_allconfigs, spc_dct, tsk_key_dct,
model_basis_energy_dct, thy_dct, pes_model_dct_i,
spc_model_dct_i, run_prefix, save_prefix):
""" For all species and transition state for the channel and
read all required data from the save filesys, then process and
format it to be able to write it into a MESS filesystem.
:param tsname: mechanism name of the transition state
:param reacs: mechanisms name for the reactants of the reaction channel
:type reacs: tuple(str)
:param prods: mechanisms name for the products of the reaction channel
:type prods: tuple(str)
"""
# Initialize the dict
chnl_infs = {}
# Get the data for conformer sorting for reading the filesystem
cnf_range = tsk_key_dct['cnf_range']
sort_info_lst = filesys.mincnf.sort_info_lst(tsk_key_dct['sort'], thy_dct)
# Determine the MESS data for the reactants and products
# Gather data or set fake information for dummy reactants/products
chnl_infs['reacs'], chnl_infs['prods'] = [], []
for rgts, side in zip((reacs, prods), ('reacs', 'prods')):
for rgt in rgts:
spc_locs_lst = filesys.models.get_spc_locs_lst(
spc_dct[rgt],
spc_model_dct_i,
run_prefix,
save_prefix,
saddle=False,
cnf_range=cnf_range,
sort_info_lst=sort_info_lst,
name=rgt)
chnl_infs_i, model_basis_energy_dct = build.read_spc_data(
spc_dct,
rgt,
pes_model_dct_i,
spc_model_dct_i,
run_prefix,
save_prefix,
model_basis_energy_dct,
spc_locs=spc_locs_lst[0])
chnl_infs[side].append(chnl_infs_i)
# Get data for all configurations for a TS
chnl_infs['ts'] = []
for name in tsname_allconfigs:
spc_locs_lst = filesys.models.get_spc_locs_lst(
spc_dct[name],
spc_model_dct_i,
run_prefix,
save_prefix,
saddle=True,
cnf_range=cnf_range,
sort_info_lst=sort_info_lst,
name=name)
spc_locs = spc_locs_lst[0] if spc_locs_lst else None
inf_dct, model_basis_energy_dct = build.read_ts_data(
spc_dct,
name,
reacs,
prods,
pes_model_dct_i,
spc_model_dct_i,
run_prefix,
save_prefix,
model_basis_energy_dct,
spc_locs=spc_locs)
chnl_infs['ts'].append(inf_dct)
# Set up the info for the wells
rwell_model = spc_model_dct_i['ts']['rwells']
pwell_model = spc_model_dct_i['ts']['pwells']
rxn_class = spc_dct[tsname_allconfigs[0]]['class']
if need_fake_wells(rxn_class, rwell_model):
chnl_infs['fake_vdwr'] = copy.deepcopy(chnl_infs['reacs'])
if need_fake_wells(rxn_class, pwell_model):
chnl_infs['fake_vdwp'] = copy.deepcopy(chnl_infs['prods'])
return chnl_infs, model_basis_energy_dct