def runThermoEstimator(inputFile):
"""
Estimate thermo for a list of species using RMG and the settings chosen inside a thermo input file.
"""
rmg = RMG()
rmg.loadThermoInput(inputFile)
# initialize and load the database as well as any QM settings
rmg.loadDatabase()
if rmg.quantumMechanics:
rmg.quantumMechanics.initialize()
# Generate the thermo for all the species and write them to chemkin format as well as
# ThermoLibrary format with values for H, S, and Cp's.
output = open(os.path.join(rmg.outputDirectory, 'output.txt'),'wb')
library = ThermoLibrary(name='Thermo Estimation Library')
for species in rmg.initialSpecies:
species.generateThermoData(rmg.database, quantumMechanics=rmg.reactionModel.quantumMechanics)
library.loadEntry(
index = len(library.entries) + 1,
label = species.label,
molecule = species.molecule[0].toAdjacencyList(),
thermo = species.thermo.toThermoData(),
shortDesc = species.thermo.comment,
)
output.write(writeThermoEntry(species))
output.write('\n')
output.close()
library.save(os.path.join(rmg.outputDirectory,'ThermoLibrary.py'))
def save_thermo_lib(species_list, path, name, lib_long_desc):
"""
Save an RMG thermo library of all species in `species_list` in the supplied `path`
`name` is the library's name (or project's name)
`long_desc` is a multiline string with level of theory description
"""
if species_list:
lib_path = os.path.join(path, 'thermo', '{0}.py'.format(name))
thermo_library = ThermoLibrary(name=name, longDesc=lib_long_desc)
for i, spc in enumerate(species_list):
if spc.thermo is not None:
spc.long_thermo_description += '\nExternal symmetry: {0}, optical isomers: {1}\n'.format(
spc.external_symmetry, spc.optical_isomers)
spc.long_thermo_description += '\nGeometry:\n{0}'.format(
spc.final_xyz)
thermo_library.loadEntry(
index=i + 1,
label=spc.label,
molecule=spc.mol_list[0].toAdjacencyList(),
thermo=spc.thermo,
shortDesc=spc.thermo.comment,
longDesc=spc.long_thermo_description)
else:
logging.warning(
'Species {0} did not contain any thermo data and was omitted from the thermo'
' library.'.format(str(spc)))
thermo_library.save(lib_path)
def runThermoEstimator(inputFile):
"""
Estimate thermo for a list of species using RMG and the settings chosen inside a thermo input file.
"""
rmg = RMG()
rmg.loadThermoInput(inputFile)
# initialize and load the database as well as any QM settings
rmg.loadDatabase()
if rmg.quantumMechanics:
rmg.quantumMechanics.initialize()
# Generate the thermo for all the species and write them to chemkin format as well as
# ThermoLibrary format with values for H, S, and Cp's.
output = open(os.path.join(rmg.outputDirectory, 'output.txt'), 'wb')
library = ThermoLibrary(name='Thermo Estimation Library')
for species in rmg.initialSpecies:
species.generateThermoData(
rmg.database, quantumMechanics=rmg.reactionModel.quantumMechanics)
library.loadEntry(
index=len(library.entries) + 1,
label=species.label,
molecule=species.molecule[0].toAdjacencyList(),
thermo=species.thermo.toThermoData(),
shortDesc=species.thermo.comment,
)
output.write(writeThermoEntry(species))
output.write('\n')
output.close()
library.save(os.path.join(rmg.outputDirectory, 'ThermoLibrary.py'))
def runThermoEstimator(inputFile, library_flag):
"""
Estimate thermo for a list of species using RMG and the settings chosen inside a thermo input file.
"""
rmg = RMG()
rmg.loadThermoInput(inputFile)
rmg.database = RMGDatabase()
path = os.path.join(settings['database.directory'])
# forbidden structure loading
rmg.database.loadThermo(os.path.join(path, 'thermo'),
rmg.thermoLibraries,
depository=False)
if rmg.solvent:
rmg.database.loadSolvation(os.path.join(path, 'solvation'))
Species.solventData = rmg.database.solvation.getSolventData(
rmg.solvent)
Species.solventName = rmg.solvent
for species in rmg.initialSpecies:
submit(species)
if library_flag:
library = ThermoLibrary(name='Thermo Estimation Library')
for species in rmg.initialSpecies:
library.loadEntry(
index=len(library.entries) + 1,
label=species.label,
molecule=species.molecule[0].toAdjacencyList(),
thermo=species.getThermoData().toThermoData(),
shortDesc=species.getThermoData().comment,
)
library.save(os.path.join(rmg.outputDirectory, 'ThermoLibrary.py'))
# Save the thermo data to chemkin format output files and dictionary, with no reactions
saveChemkinFile(os.path.join(rmg.outputDirectory, 'chem_annotated.inp'),
species=rmg.initialSpecies,
reactions=[])
saveSpeciesDictionary(os.path.join(rmg.outputDirectory,
'species_dictionary.txt'),
species=rmg.initialSpecies)
def runThermoEstimator(inputFile):
"""
Estimate thermo for a list of species using RMG and the settings chosen inside a thermo input file.
"""
rmg = RMG()
rmg.loadThermoInput(inputFile)
rmg.database = RMGDatabase()
path = os.path.join(settings['database.directory'])
# forbidden structure loading
rmg.database.loadThermo(os.path.join(path, 'thermo'), rmg.thermoLibraries, depository=False)
if rmg.solvent:
rmg.database.loadSolvation(os.path.join(path, 'solvation'))
Species.solventData = rmg.database.solvation.getSolventData(rmg.solvent)
Species.solventName = rmg.solvent
# Generate the thermo for all the species and write them to chemkin format as well as
# ThermoLibrary format with values for H, S, and Cp's.
output = open(os.path.join(rmg.outputDirectory, 'output.txt'),'wb')
library = ThermoLibrary(name='Thermo Estimation Library')
for species in rmg.initialSpecies:
species.getThermoData(rmg.database)
library.loadEntry(
index = len(library.entries) + 1,
label = species.label,
molecule = species.molecule[0].toAdjacencyList(),
thermo = species.thermo.toThermoData(),
shortDesc = species.thermo.comment,
)
output.write(writeThermoEntry(species))
output.write('\n')
output.close()
library.save(os.path.join(rmg.outputDirectory,'ThermoLibrary.py'))
print removeH
speciesList, reactionList = loadChemkinFile(chemkinPath, dictionaryPath)
# load thermo library entries
thermoLibrary = ThermoLibrary()
for i in range(len(speciesList)):
species = speciesList[i]
rdkitmol = species.molecule[0].toRDKitMol(removeHs=False)
species.molecule = [Molecule().fromRDKitMol(rdkitmol)]#[0].toAdjacencyList(removeH=False)
print species.molecule[0].toAdjacencyList(removeH = removeH)
if species.thermo:
thermoLibrary.loadEntry(index = i + 1,
label = species.label,
molecule = species.molecule[0].toAdjacencyList(removeH = removeH),
thermo = species.thermo,
shortDesc = species.thermo.comment
)
else:
logging.warning('Species {0} did not contain any thermo data and was omitted from the thermo library.'.format(str(species)))
# load kinetics library entries
kineticsLibrary = KineticsLibrary()
kineticsLibrary.entries = {}
for i in range(len(reactionList)):
reaction = reactionList[i]
entry = Entry(
index = i+1,
item = reaction,
data = reaction.kinetics,
)
def getLibraries(self):
name = 'kineticsjobs'
speciesList = self.speciesDict.values()
reactionList = self.reactionDict.values()
# remove duplicate species
for rxn in reactionList:
for i, rspc in enumerate(rxn.reactants):
for spc in speciesList:
if spc.isIsomorphic(rspc):
rxn.reactants[i] = spc
break
for i, rspc in enumerate(rxn.products):
for spc in speciesList:
if spc.isIsomorphic(rspc):
rxn.products[i] = spc
break
del_inds = []
for i, spc1 in enumerate(speciesList):
for j, spc2 in enumerate(speciesList):
if j > i and spc1.isIsomorphic(spc2):
del_inds.append(j)
for j in sorted(del_inds)[::-1]:
del speciesList[j]
thermoLibrary = ThermoLibrary(name=name)
for i, species in enumerate(speciesList):
if species.thermo:
thermoLibrary.loadEntry(
index=i + 1,
label=species.label,
molecule=species.molecule[0].toAdjacencyList(),
thermo=species.thermo,
shortDesc=species.thermo.comment)
else:
logging.warning(
'Species {0} did not contain any thermo data and was omitted from the thermo library.'
.format(str(species)))
# load kinetics library entries
kineticsLibrary = KineticsLibrary(name=name, autoGenerated=True)
kineticsLibrary.entries = {}
for i, reaction in enumerate(reactionList):
entry = Entry(
index=i + 1,
label=reaction.toLabeledStr(),
item=reaction,
data=reaction.kinetics,
)
if reaction.kinetics is not None:
if hasattr(reaction, 'library') and reaction.library:
entry.longDesc = 'Originally from reaction library: ' +\
reaction.library + "\n" + reaction.kinetics.comment
else:
entry.longDesc = reaction.kinetics.comment
kineticsLibrary.entries[i + 1] = entry
kineticsLibrary.label = name
return thermoLibrary, kineticsLibrary, speciesList
def getLibraries(self):
name = 'kineticsjobs'
speciesList = self.speciesDict.values()
reactionList = self.reactionDict.values()
# remove duplicate species
for rxn in reactionList:
for i,rspc in enumerate(rxn.reactants):
for spc in speciesList:
if spc.isIsomorphic(rspc):
rxn.reactants[i] = spc
break
for i,rspc in enumerate(rxn.products):
for spc in speciesList:
if spc.isIsomorphic(rspc):
rxn.products[i] = spc
break
del_inds = []
for i,spc1 in enumerate(speciesList):
for j,spc2 in enumerate(speciesList):
if j>i and spc1.isIsomorphic(spc2):
del_inds.append(j)
for j in sorted(del_inds)[::-1]:
del speciesList[j]
thermoLibrary = ThermoLibrary(name=name)
for i,species in enumerate(speciesList):
if species.thermo:
thermoLibrary.loadEntry(index = i + 1,
label = species.label,
molecule = species.molecule[0].toAdjacencyList(),
thermo = species.thermo,
shortDesc = species.thermo.comment
)
else:
logging.warning('Species {0} did not contain any thermo data and was omitted from the thermo library.'.format(str(species)))
# load kinetics library entries
kineticsLibrary = KineticsLibrary(name=name,autoGenerated=True)
kineticsLibrary.entries = {}
for i,reaction in enumerate(reactionList):
entry = Entry(
index = i+1,
label = reaction.toLabeledStr(),
item = reaction,
data = reaction.kinetics,
)
if reaction.kinetics is not None:
if hasattr(reaction,'library') and reaction.library:
entry.longDesc = 'Originally from reaction library: ' +\
reaction.library + "\n" + reaction.kinetics.comment
else:
entry.longDesc = reaction.kinetics.comment
kineticsLibrary.entries[i+1] = entry
kineticsLibrary.label = name
return thermoLibrary,kineticsLibrary,speciesList
name = args.name[0]
speciesList, reactionList = loadChemkinFile(chemkinPath, dictionaryPath)
# Make full species identifier the species labels
for species in speciesList:
species.label = getSpeciesIdentifier(species)
species.index = -1
# load thermo library entries
thermoLibrary = ThermoLibrary(name=name)
for i in range(len(speciesList)):
species = speciesList[i]
if species.thermo:
thermoLibrary.loadEntry(index = i + 1,
label = species.label,
molecule = species.molecule[0].toAdjacencyList(),
thermo = species.thermo,
shortDesc = species.thermo.comment
)
else:
logging.warning('Species {0} did not contain any thermo data and was omitted from the thermo library.'.format(str(species)))
# load kinetics library entries
kineticsLibrary = KineticsLibrary(name=name)
kineticsLibrary.entries = {}
for i in range(len(reactionList)):
reaction = reactionList[i]
entry = Entry(
index = i+1,
label = str(reaction),
item = reaction,
data = reaction.kinetics,