def predict(self):
import input
import model
input = input.load()
model_pred = model.create(input)
model_pred.predict(input)
def goTrain(self):
import input
import model
input = input.load()
model_train = model.create(input)
model_train.fit(input)
if not conf.path_model is None:
model_train.save(conf.path_model)
def main():
args = parseCommandLineArguments()
level = INFO
if args.debug: level = 0
elif args.verbose: level = DEBUG
elif args.quiet: level = WARNING
initializeLog(level)
inputFile, reductionFile, chemkinFile, spcDict = args.requiredFiles[-4:]
for f in [inputFile, reductionFile, chemkinFile, spcDict]:
assert os.path.isfile(f), 'Could not find {}'.format(f)
inputDirectory = os.path.abspath(os.path.dirname(inputFile))
output_directory = inputDirectory
rmg, targets, error = load(inputFile, reductionFile, chemkinFile, spcDict)
logger.info('Allowed error in target observables: {0:.0f}%'.format(error *
100))
reactionModel = rmg.reactionModel
initialize(rmg.outputDirectory, reactionModel.core.reactions)
atol, rtol = rmg.absoluteTolerance, rmg.relativeTolerance
index = 0
reactionSystem = rmg.reactionSystems[index]
#compute original target observables
observables = computeObservables(targets, reactionModel, reactionSystem, \
rmg.absoluteTolerance, rmg.relativeTolerance)
logger.info('Observables of original model:')
for target, observable in zip(targets, observables):
logger.info('{}: {:.2f}%'.format(target, observable * 100))
# optimize reduction tolerance
tol, importantReactions = optimize(targets, reactionModel, rmg, index,
error, observables)
logger.info('Optimized tolerance: {:.0E}'.format(10**tol))
logger.info('Number of reactions in optimized reduced model : {}'.format(
len(importantReactions)))
# plug the important reactions into the RMG object and write:
rmg.reactionModel.core.reactions = importantReactions
writeModel(rmg)
def main():
args = parseCommandLineArguments()
level = INFO
if args.debug: level = 0
elif args.verbose: level = DEBUG
elif args.quiet: level = WARNING
initializeLog(level)
inputFile, reductionFile, chemkinFile, spcDict = args.requiredFiles[-4:]
for f in [inputFile, reductionFile, chemkinFile, spcDict]:
assert os.path.isfile(f), 'Could not find {}'.format(f)
inputDirectory = os.path.abspath(os.path.dirname(inputFile))
output_directory = inputDirectory
rmg, targets, error = load(inputFile, reductionFile, chemkinFile, spcDict)
logger.info('Allowed error in target observables: {0:.0f}%'.format(error * 100))
reactionModel = rmg.reactionModel
initialize(rmg.outputDirectory, reactionModel.core.reactions)
atol, rtol = rmg.absoluteTolerance, rmg.relativeTolerance
index = 0
reactionSystem = rmg.reactionSystems[index]
#compute original target observables
observables = computeObservables(targets, reactionModel, reactionSystem, \
rmg.absoluteTolerance, rmg.relativeTolerance)
logger.info('Observables of original model:')
for target, observable in zip(targets, observables):
logger.info('{}: {:.2f}%'.format(target, observable * 100))
# optimize reduction tolerance
tol, importantReactions = optimize(targets, reactionModel, rmg, index, error, observables)
logger.info('Optimized tolerance: {:.0E}'.format(10**tol))
logger.info('Number of reactions in optimized reduced model : {}'.format(len(importantReactions)))
# plug the important reactions into the RMG object and write:
rmg.reactionModel.core.reactions = importantReactions
writeModel(rmg)
def __parse_input(self, in_file):
from input import load
data = load(in_file)
options = data[input.OPTIONS]
if options.flow_unit in US_UNITS:
self.units = UnitsUS() #TODO make proper units system
else:
self.units = UnitsSI() #TODO implement UnitsSI
#init curves
self.curves = {}
for c in data[input.CURVES]:
self.curves[c.ID] = None
for id in self.curves.keys():
self.curves[id] = Curve(data[input.CURVES], id)
self.__prepare_nodes(data)
self.__prepare_links(data)
def __parse_input(self, in_file):
from input import load
data = load(in_file)
options = data[input.OPTIONS]
if options.flow_unit in US_UNITS:
self.units = UnitsUS() #TODO make proper units system
else:
self.units = UnitsSI() #TODO implement UnitsSI
#init curves
self.curves = {}
for c in data[input.CURVES]:
self.curves[c.ID] = None
for id in self.curves.keys():
self.curves[id] = Curve(data[input.CURVES], id)
self.__prepare_nodes(data)
self.__prepare_links(data)