def generate_reactions_from_library(self,
library,
reactants,
products=None):
"""
Find all reactions from the specified kinetics library involving the
provided `reactants`, which can be either :class:`Molecule` objects or
:class:`Species` objects.
"""
ensure_species(reactants)
reaction_list = []
for entry in library.entries.values():
if entry.item.matchesSpecies(reactants, products=products):
reaction = LibraryReaction(
reactants=entry.item.reactants[:],
products=entry.item.products[:],
specificCollider=entry.item.specificCollider,
degeneracy=entry.item.degeneracy,
reversible=entry.item.reversible,
duplicate=entry.item.duplicate,
kinetics=deepcopy(entry.data),
library=library,
entry=entry,
)
reaction_list.append(reaction)
return reaction_list
def generateReactionsFromLibrary(self, reactants, products, library):
"""
Generate all reactions between the provided list of one or two
`reactants`, which should be :class:`Molecule` objects. This method
searches the depository.
"""
reactionList = []
for entry in library.entries.values():
if entry.item.matchesMolecules(reactants):
reaction = LibraryReaction(
reactants = entry.item.reactants[:],
products = entry.item.products[:],
degeneracy = entry.item.degeneracy,
reversible = entry.item.reversible,
duplicate = entry.item.duplicate,
kinetics = deepcopy(entry.data),
library = library,
entry = entry,
)
reactionList.append(reaction)
if products:
reactionList = filterReactions(reactants, products, reactionList)
return reactionList
print('Loading RMG-Py database...')
database = RMGDatabase()
database.load(settings['database.directory'],
kinetics_families='all',
kinetics_depositories='all')
print('Loading {0} library'.format(library_name))
kinetic_library = database.kinetics.libraries[library_name]
reaction_list = []
for index, entry in kinetic_library.entries.items():
reaction = entry.item
reaction.kinetics = entry.data
library_reaction = LibraryReaction(index=reaction.index,
reactants=reaction.reactants,
products=reaction.products,
reversible=reaction.reversible,
kinetics=reaction.kinetics,
library=library_name)
reaction_list.append(library_reaction)
species_list = []
index = 0
species_dict = kinetic_library.get_species(
os.path.join(settings['database.directory'], 'kinetics', 'libraries',
library_name, 'dictionary.txt'))
for spec in list(species_dict.values()):
index = index + 1
species = Species(molecule=spec.molecule)
species.get_thermo_data()
species.index = index
species_list.append(species)