def setUpClass(cls):
"""This method is run once before all tests in this class."""
test_dir = rmgpy.settings['test_data.directory']
data_dir = os.path.join(test_dir, 'testing_database')
chem_dir = os.path.join(test_dir, 'parsing_data')
chemkin_file = os.path.join(chem_dir, 'chem_annotated.inp')
spc_dict = os.path.join(chem_dir, 'species_dictionary.txt')
cls.uncertainty = Uncertainty(outputDirectory='chemDir')
cls.uncertainty.loadModel(chemkin_file, spc_dict)
# load database properly
cls.uncertainty.database = RMGDatabase()
cls.uncertainty.database.load(
data_dir,
kineticsFamilies=[
'1,2_shiftC', '6_membered_central_C-C_shift',
'Disproportionation', 'H_Abstraction', 'Intra_ene_reaction',
'intra_H_migration', 'Intra_R_Add_Exo_scission',
'intra_substitutionS_isomerization', 'R_Addition_MultipleBond',
'R_Recombination'
],
kineticsDepositories=['training'],
thermoLibraries=['primaryThermoLibrary'],
reactionLibraries=['GRI-Mech3.0'],
)
# Prepare the database by loading training reactions and averaging the rate rules verbosely
for family in cls.uncertainty.database.kinetics.families.itervalues():
family.addKineticsRulesFromTrainingSet(
thermoDatabase=cls.uncertainty.database.thermo)
family.fillKineticsRulesByAveragingUp(verbose=True)
def setUpClass(cls):
"""This method is run once before all tests in this class."""
test_dir = rmgpy.settings['test_data.directory']
data_dir = os.path.join(test_dir, 'testing_database')
chem_dir = os.path.join(test_dir, 'parsing_data')
chemkin_file = os.path.join(chem_dir, 'chem_annotated.inp')
spc_dict = os.path.join(chem_dir, 'species_dictionary.txt')
cls.uncertainty = Uncertainty(outputDirectory='chemDir')
cls.uncertainty.loadModel(chemkin_file, spc_dict)
# load database properly
cls.uncertainty.database = RMGDatabase()
cls.uncertainty.database.load(
data_dir,
kineticsFamilies='all',
kineticsDepositories=['training'],
thermoLibraries=['primaryThermoLibrary'],
reactionLibraries=['GRI-Mech3.0'],
)
# Prepare the database by loading training reactions and averaging the rate rules verbosely
for family in cls.uncertainty.database.kinetics.families.itervalues():
family.addKineticsRulesFromTrainingSet(
thermoDatabase=cls.uncertainty.database.thermo)
family.fillKineticsRulesByAveragingUp(verbose=True)