def load(self): """ Load the contents of the input file into a PressureDependenceJob object. """ from rmgpy.cantherm.pdep import PressureDependenceJob from rmgpy.cantherm.input import loadInputFile # Seed with a PdepJob object if self.pdep is None: self.pdep = PressureDependenceJob(network=None) if self.inputFileExists(): jobList = loadInputFile(self.getInputFilename()) assert len(jobList) == 1 job = jobList[0] if isinstance(job, PressureDependenceJob) is False: raise Exception( 'Input file given did not provide a pressure dependence network.' ) self.pdep = job self.pdep.initialize() if self.pdep.network is not None: self.title = self.pdep.network.label self.save() return self.pdep.network
def pressureDependence( method, temperatures, pressures, maximumGrainSize=0.0, minimumNumberOfGrains=0, interpolation=None, maximumAtoms=None, ): from rmgpy.cantherm.pdep import PressureDependenceJob # Setting the pressureDependence attribute to non-None enables pressure dependence rmg.pressureDependence = PressureDependenceJob(network=None) # Process method rmg.pressureDependence.method = method # Process interpolation model if isinstance(interpolation, str): interpolation = (interpolation, ) if interpolation[0].lower() not in ("chebyshev", "pdeparrhenius"): raise InputError( "Interpolation model must be set to either 'Chebyshev' or 'PDepArrhenius'." ) rmg.pressureDependence.interpolationModel = interpolation # Process temperatures Tmin, Tmax, Tunits, Tcount = temperatures rmg.pressureDependence.Tmin = Quantity(Tmin, Tunits) rmg.pressureDependence.Tmax = Quantity(Tmax, Tunits) rmg.pressureDependence.Tcount = Tcount rmg.pressureDependence.generateTemperatureList() # Process pressures Pmin, Pmax, Punits, Pcount = pressures rmg.pressureDependence.Pmin = Quantity(Pmin, Punits) rmg.pressureDependence.Pmax = Quantity(Pmax, Punits) rmg.pressureDependence.Pcount = Pcount rmg.pressureDependence.generatePressureList() # Process grain size and count rmg.pressureDependence.maximumGrainSize = Quantity(maximumGrainSize) rmg.pressureDependence.minimumGrainCount = minimumNumberOfGrains # Process maximum atoms rmg.pressureDependence.maximumAtoms = maximumAtoms rmg.pressureDependence.activeJRotor = True rmg.pressureDependence.activeKRotor = True rmg.pressureDependence.rmgmode = True
def pressureDependence( method, temperatures, pressures, maximumGrainSize=0.0, minimumNumberOfGrains=0, interpolation=None, maximumAtoms=None, ): from rmgpy.cantherm.pdep import PressureDependenceJob # Setting the pressureDependence attribute to non-None enables pressure dependence rmg.pressureDependence = PressureDependenceJob(network=None) # Process method rmg.pressureDependence.method = method # Process interpolation model rmg.pressureDependence.interpolationModel = interpolation # Process temperatures Tmin, Tmax, Tunits, Tcount = temperatures rmg.pressureDependence.Tmin = Quantity(Tmin, Tunits) rmg.pressureDependence.Tmax = Quantity(Tmax, Tunits) rmg.pressureDependence.Tcount = Tcount rmg.pressureDependence.generateTemperatureList() # Process pressures Pmin, Pmax, Punits, Pcount = pressures rmg.pressureDependence.Pmin = Quantity(Pmin, Punits) rmg.pressureDependence.Pmax = Quantity(Pmax, Punits) rmg.pressureDependence.Pcount = Pcount rmg.pressureDependence.generatePressureList() # Process grain size and count rmg.pressureDependence.maximumGrainSize = Quantity(maximumGrainSize) rmg.pressureDependence.minimumGrainCount = minimumNumberOfGrains # Process maximum atoms rmg.pressureDependence.maximumAtoms = maximumAtoms rmg.pressureDependence.activeJRotor = True rmg.pressureDependence.activeKRotor = True rmg.pressureDependence.rmgmode = True
def pressureDependence(label, Tmin=None, Tmax=None, Tcount=0, Tlist=None, Pmin=None, Pmax=None, Pcount=0, Plist=None, maximumGrainSize=None, minimumGrainCount=0, method=None, interpolationModel=None, activeKRotor=True, activeJRotor=True, rmgmode=False): global jobList, networkDict if isinstance(interpolationModel, str): interpolationModel = (interpolationModel, ) job = PressureDependenceJob( network=networkDict[label], Tmin=Tmin, Tmax=Tmax, Tcount=Tcount, Tlist=Tlist, Pmin=Pmin, Pmax=Pmax, Pcount=Pcount, Plist=Plist, maximumGrainSize=maximumGrainSize, minimumGrainCount=minimumGrainCount, method=method, interpolationModel=interpolationModel, activeKRotor=activeKRotor, activeJRotor=activeJRotor, rmgmode=rmgmode, ) jobList.append(job)
def loadFAMEInput(path, moleculeDict=None): """ Load the contents of a FAME input file into the MEASURE object. FAME is an early version of MEASURE written in Fortran and used by RMG-Java. This script enables importing FAME input files into MEASURE so we can use the additional functionality that MEASURE provides. Note that it is mostly designed to load the FAME input files generated automatically by RMG-Java, and may not load hand-crafted FAME input files. If you specify a `moleculeDict`, then this script will use it to associate the species with their structures. """ def readMeaningfulLine(f): line = f.readline() while line != '': line = line.strip() if len(line) > 0 and line[0] != '#': return line else: line = f.readline() return '' moleculeDict = moleculeDict or {} logging.info('Loading file "{0}"...'.format(path)) f = open(path) job = PressureDependenceJob(network=None) # Read method method = readMeaningfulLine(f).lower() if method == 'modifiedstrongcollision': job.method = 'modified strong collision' elif method == 'reservoirstate': job.method = 'reservoir state' # Read temperatures Tcount, Tunits, Tmin, Tmax = readMeaningfulLine(f).split() job.Tmin = Quantity(float(Tmin), Tunits) job.Tmax = Quantity(float(Tmax), Tunits) job.Tcount = int(Tcount) Tlist = [] for i in range(int(Tcount)): Tlist.append(float(readMeaningfulLine(f))) job.Tlist = Quantity(Tlist, Tunits) # Read pressures Pcount, Punits, Pmin, Pmax = readMeaningfulLine(f).split() job.Pmin = Quantity(float(Pmin), Punits) job.Pmax = Quantity(float(Pmax), Punits) job.Pcount = int(Pcount) Plist = [] for i in range(int(Pcount)): Plist.append(float(readMeaningfulLine(f))) job.Plist = Quantity(Plist, Punits) # Read interpolation model model = readMeaningfulLine(f).split() if model[0].lower() == 'chebyshev': job.interpolationModel = ('chebyshev', int(model[1]), int(model[2])) elif model[0].lower() == 'pdeparrhenius': job.interpolationModel = ('pdeparrhenius',) # Read grain size or number of grains job.minimumGrainCount = 0 job.maximumGrainSize = None for i in range(2): data = readMeaningfulLine(f).split() if data[0].lower() == 'numgrains': job.minimumGrainCount = int(data[1]) elif data[0].lower() == 'grainsize': job.maximumGrainSize = (float(data[2]), data[1]) # A FAME file is almost certainly created during an RMG job, so use RMG mode job.rmgmode = True # Create the Network job.network = Network() # Read collision model data = readMeaningfulLine(f) assert data.lower() == 'singleexpdown' alpha0units, alpha0 = readMeaningfulLine(f).split() T0units, T0 = readMeaningfulLine(f).split() n = readMeaningfulLine(f) energyTransferModel = SingleExponentialDown( alpha0 = Quantity(float(alpha0), alpha0units), T0 = Quantity(float(T0), T0units), n = float(n), ) speciesDict = {} # Read bath gas parameters bathGas = Species(label='bath_gas', energyTransferModel=energyTransferModel) molWtunits, molWt = readMeaningfulLine(f).split() if molWtunits == 'u': molWtunits = 'amu' bathGas.molecularWeight = Quantity(float(molWt), molWtunits) sigmaLJunits, sigmaLJ = readMeaningfulLine(f).split() epsilonLJunits, epsilonLJ = readMeaningfulLine(f).split() assert epsilonLJunits == 'J' bathGas.transportData = TransportData( sigma = Quantity(float(sigmaLJ), sigmaLJunits), epsilon = Quantity(float(epsilonLJ) / constants.kB, 'K'), ) job.network.bathGas = {bathGas: 1.0} # Read species data Nspec = int(readMeaningfulLine(f)) for i in range(Nspec): species = Species() species.conformer = Conformer() species.energyTransferModel = energyTransferModel # Read species label species.label = readMeaningfulLine(f) speciesDict[species.label] = species if species.label in moleculeDict: species.molecule = [moleculeDict[species.label]] # Read species E0 E0units, E0 = readMeaningfulLine(f).split() species.conformer.E0 = Quantity(float(E0), E0units) species.conformer.E0.units = 'kJ/mol' # Read species thermo data H298units, H298 = readMeaningfulLine(f).split() S298units, S298 = readMeaningfulLine(f).split() Cpcount, Cpunits = readMeaningfulLine(f).split() Cpdata = [] for i in range(int(Cpcount)): Cpdata.append(float(readMeaningfulLine(f))) if S298units == 'J/mol*K': S298units = 'J/(mol*K)' if Cpunits == 'J/mol*K': Cpunits = 'J/(mol*K)' species.thermo = ThermoData( H298 = Quantity(float(H298), H298units), S298 = Quantity(float(S298), S298units), Tdata = Quantity([300,400,500,600,800,1000,1500], "K"), Cpdata = Quantity(Cpdata, Cpunits), Cp0 = (Cpdata[0], Cpunits), CpInf = (Cpdata[-1], Cpunits), ) # Read species collision parameters molWtunits, molWt = readMeaningfulLine(f).split() if molWtunits == 'u': molWtunits = 'amu' species.molecularWeight = Quantity(float(molWt), molWtunits) sigmaLJunits, sigmaLJ = readMeaningfulLine(f).split() epsilonLJunits, epsilonLJ = readMeaningfulLine(f).split() assert epsilonLJunits == 'J' species.transportData = TransportData( sigma = Quantity(float(sigmaLJ), sigmaLJunits), epsilon = Quantity(float(epsilonLJ) / constants.kB, 'K'), ) # Read species vibrational frequencies freqCount, freqUnits = readMeaningfulLine(f).split() frequencies = [] for j in range(int(freqCount)): frequencies.append(float(readMeaningfulLine(f))) species.conformer.modes.append(HarmonicOscillator( frequencies = Quantity(frequencies, freqUnits), )) # Read species external rotors rotCount, rotUnits = readMeaningfulLine(f).split() if int(rotCount) > 0: raise NotImplementedError('Cannot handle external rotational modes in FAME input.') # Read species internal rotors freqCount, freqUnits = readMeaningfulLine(f).split() frequencies = [] for j in range(int(freqCount)): frequencies.append(float(readMeaningfulLine(f))) barrCount, barrUnits = readMeaningfulLine(f).split() barriers = [] for j in range(int(barrCount)): barriers.append(float(readMeaningfulLine(f))) if barrUnits == 'cm^-1': barrUnits = 'J/mol' barriers = [barr * constants.h * constants.c * constants.Na * 100. for barr in barriers] elif barrUnits in ['Hz', 's^-1']: barrUnits = 'J/mol' barriers = [barr * constants.h * constants.Na for barr in barriers] elif barrUnits != 'J/mol': raise Exception('Unexpected units "{0}" for hindered rotor barrier height.'.format(barrUnits)) inertia = [V0 / 2.0 / (nu * constants.c * 100.)**2 / constants.Na for nu, V0 in zip(frequencies, barriers)] for I, V0 in zip(inertia, barriers): species.conformer.modes.append(HinderedRotor( inertia = Quantity(I,"kg*m^2"), barrier = Quantity(V0,barrUnits), symmetry = 1, semiclassical = False, )) # Read overall symmetry number species.conformer.spinMultiplicity = int(readMeaningfulLine(f)) # Read isomer, reactant channel, and product channel data Nisom = int(readMeaningfulLine(f)) Nreac = int(readMeaningfulLine(f)) Nprod = int(readMeaningfulLine(f)) for i in range(Nisom): data = readMeaningfulLine(f).split() assert data[0] == '1' job.network.isomers.append(speciesDict[data[1]]) for i in range(Nreac): data = readMeaningfulLine(f).split() assert data[0] == '2' job.network.reactants.append([speciesDict[data[1]], speciesDict[data[2]]]) for i in range(Nprod): data = readMeaningfulLine(f).split() if data[0] == '1': job.network.products.append([speciesDict[data[1]]]) elif data[0] == '2': job.network.products.append([speciesDict[data[1]], speciesDict[data[2]]]) # Read path reactions Nrxn = int(readMeaningfulLine(f)) for i in range(Nrxn): # Read and ignore reaction equation equation = readMeaningfulLine(f) reaction = Reaction(transitionState=TransitionState(), reversible=True) job.network.pathReactions.append(reaction) reaction.transitionState.conformer = Conformer() # Read reactant and product indices data = readMeaningfulLine(f).split() reac = int(data[0]) - 1 prod = int(data[1]) - 1 if reac < Nisom: reaction.reactants = [job.network.isomers[reac]] elif reac < Nisom+Nreac: reaction.reactants = job.network.reactants[reac-Nisom] else: reaction.reactants = job.network.products[reac-Nisom-Nreac] if prod < Nisom: reaction.products = [job.network.isomers[prod]] elif prod < Nisom+Nreac: reaction.products = job.network.reactants[prod-Nisom] else: reaction.products = job.network.products[prod-Nisom-Nreac] # Read reaction E0 E0units, E0 = readMeaningfulLine(f).split() reaction.transitionState.conformer.E0 = Quantity(float(E0), E0units) reaction.transitionState.conformer.E0.units = 'kJ/mol' # Read high-pressure limit kinetics data = readMeaningfulLine(f) assert data.lower() == 'arrhenius' Aunits, A = readMeaningfulLine(f).split() if '/' in Aunits: index = Aunits.find('/') Aunits = '{0}/({1})'.format(Aunits[0:index], Aunits[index+1:]) Eaunits, Ea = readMeaningfulLine(f).split() n = readMeaningfulLine(f) reaction.kinetics = Arrhenius( A = Quantity(float(A), Aunits), Ea = Quantity(float(Ea), Eaunits), n = Quantity(float(n)), ) reaction.kinetics.Ea.units = 'kJ/mol' f.close() job.network.isomers = [Configuration(isomer) for isomer in job.network.isomers] job.network.reactants = [Configuration(*reactants) for reactants in job.network.reactants] job.network.products = [Configuration(*products) for products in job.network.products] return job
def saveForm(self, posted, form): """ Save form data into input.py file specified by the path. """ # Clean past history self.rmg = RMG() # Databases #self.rmg.databaseDirectory = settings['database.directory'] self.rmg.thermoLibraries = [] if posted.thermo_libraries.all(): self.rmg.thermoLibraries = [ item.thermolib.encode() for item in posted.thermo_libraries.all() ] self.rmg.reactionLibraries = [] self.rmg.seedMechanisms = [] if posted.reaction_libraries.all(): for item in posted.reaction_libraries.all(): if not item.seedmech and not item.edge: self.rmg.reactionLibraries.append( (item.reactionlib.encode(), False)) elif not item.seedmech: self.rmg.reactionLibraries.append( (item.reactionlib.encode(), True)) else: self.rmg.seedMechanisms.append(item.reactionlib.encode()) self.rmg.statmechLibraries = [] self.rmg.kineticsDepositories = 'default' self.rmg.kineticsFamilies = 'default' self.rmg.kineticsEstimator = 'rate rules' # Species self.rmg.initialSpecies = [] speciesDict = {} initialMoleFractions = {} self.rmg.reactionModel = CoreEdgeReactionModel() for item in posted.reactor_species.all(): structure = Molecule().fromAdjacencyList(item.adjlist.encode()) spec, isNew = self.rmg.reactionModel.makeNewSpecies( structure, label=item.name.encode(), reactive=False if item.inert else True) self.rmg.initialSpecies.append(spec) speciesDict[item.name.encode()] = spec initialMoleFractions[spec] = item.molefrac # Reactor systems self.rmg.reactionSystems = [] for item in posted.reactor_systems.all(): T = Quantity(item.temperature, item.temperature_units.encode()) P = Quantity(item.pressure, item.pressure_units.encode()) termination = [] if item.conversion: termination.append( TerminationConversion(speciesDict[item.species.encode()], item.conversion)) termination.append( TerminationTime( Quantity(item.terminationtime, item.time_units.encode()))) # Sensitivity Analysis sensitiveSpecies = [] if item.sensitivity: if isinstance(item.sensitivity.encode(), str): sensitivity = item.sensitivity.encode().split(',').strip() for spec in sensitivity: sensitiveSpecies.append(speciesDict[spec]) system = SimpleReactor(T, P, initialMoleFractions, termination, sensitiveSpecies, item.sensitivityThreshold) self.rmg.reactionSystems.append(system) # Simulator tolerances self.rmg.absoluteTolerance = form.cleaned_data['simulator_atol'] self.rmg.relativeTolerance = form.cleaned_data['simulator_rtol'] self.rmg.sensitivityAbsoluteTolerance = form.cleaned_data[ 'simulator_sens_atol'] self.rmg.sensitivityRelativeTolerance = form.cleaned_data[ 'simulator_sens_rtol'] self.rmg.fluxToleranceKeepInEdge = form.cleaned_data[ 'toleranceKeepInEdge'] self.rmg.fluxToleranceMoveToCore = form.cleaned_data[ 'toleranceMoveToCore'] self.rmg.fluxToleranceInterrupt = form.cleaned_data[ 'toleranceInterruptSimulation'] self.rmg.maximumEdgeSpecies = form.cleaned_data['maximumEdgeSpecies'] self.rmg.minCoreSizeForPrune = form.cleaned_data['minCoreSizeForPrune'] self.rmg.minSpeciesExistIterationsForPrune = form.cleaned_data[ 'minSpeciesExistIterationsForPrune'] # Pressure Dependence pdep = form.cleaned_data['pdep'].encode() if pdep != 'off': self.rmg.pressureDependence = PressureDependenceJob(network=None) self.rmg.pressureDependence.method = pdep # Process interpolation model if form.cleaned_data['interpolation'].encode() == 'chebyshev': self.rmg.pressureDependence.interpolationModel = ( form.cleaned_data['interpolation'].encode(), form.cleaned_data['temp_basis'], form.cleaned_data['p_basis']) else: self.rmg.pressureDependence.interpolationModel = ( form.cleaned_data['interpolation'].encode(), ) # Temperature and pressure range self.rmg.pressureDependence.Tmin = Quantity( form.cleaned_data['temp_low'], form.cleaned_data['temprange_units'].encode()) self.rmg.pressureDependence.Tmax = Quantity( form.cleaned_data['temp_high'], form.cleaned_data['temprange_units'].encode()) self.rmg.pressureDependence.Tcount = form.cleaned_data[ 'temp_interp'] self.rmg.pressureDependence.generateTemperatureList() self.rmg.pressureDependence.Pmin = Quantity( form.cleaned_data['p_low'], form.cleaned_data['prange_units'].encode()) self.rmg.pressureDependence.Pmax = Quantity( form.cleaned_data['p_high'], form.cleaned_data['prange_units'].encode()) self.rmg.pressureDependence.Pcount = form.cleaned_data['p_interp'] self.rmg.pressureDependence.generatePressureList() # Process grain size and count self.rmg.pressureDependence.grainSize = Quantity( form.cleaned_data['maximumGrainSize'], form.cleaned_data['grainsize_units'].encode()) self.rmg.pressureDependence.grainCount = form.cleaned_data[ 'minimumNumberOfGrains'] self.rmg.pressureDependence.maximumAtoms = form.cleaned_data[ 'maximumAtoms'] # Additional Options self.rmg.units = 'si' self.rmg.saveRestartPeriod = Quantity( form.cleaned_data['saveRestartPeriod'], form.cleaned_data['saveRestartPeriodUnits'].encode( )) if form.cleaned_data['saveRestartPeriod'] else None self.rmg.generateOutputHTML = form.cleaned_data['generateOutputHTML'] self.rmg.generatePlots = form.cleaned_data['generatePlots'] self.rmg.saveSimulationProfiles = form.cleaned_data[ 'saveSimulationProfiles'] self.rmg.saveEdgeSpecies = form.cleaned_data['saveEdgeSpecies'] self.rmg.verboseComments = form.cleaned_data['verboseComments'] # Species Constraints speciesConstraints = form.cleaned_data['speciesConstraints'] if speciesConstraints == 'on': allowed = [] if form.cleaned_data['allowed_inputSpecies']: allowed.append('input species') if form.cleaned_data['allowed_seedMechanisms']: allowed.append('seed mechanisms') if form.cleaned_data['allowed_reactionLibraries']: allowed.append('reaction libraries') self.rmg.speciesConstraints['allowed'] = allowed self.rmg.speciesConstraints[ 'maximumCarbonAtoms'] = form.cleaned_data['maximumCarbonAtoms'] self.rmg.speciesConstraints[ 'maximumHydrogenAtoms'] = form.cleaned_data[ 'maximumHydrogenAtoms'] self.rmg.speciesConstraints[ 'maximumOxygenAtoms'] = form.cleaned_data['maximumOxygenAtoms'] self.rmg.speciesConstraints[ 'maximumNitrogenAtoms'] = form.cleaned_data[ 'maximumNitrogenAtoms'] self.rmg.speciesConstraints[ 'maximumSiliconAtoms'] = form.cleaned_data[ 'maximumSiliconAtoms'] self.rmg.speciesConstraints[ 'maximumSulfurAtoms'] = form.cleaned_data['maximumSulfurAtoms'] self.rmg.speciesConstraints[ 'maximumHeavyAtoms'] = form.cleaned_data['maximumHeavyAtoms'] self.rmg.speciesConstraints[ 'maximumRadicalElectrons'] = form.cleaned_data[ 'maximumRadicalElectrons'] self.rmg.speciesConstraints['allowSingletO2'] = form.cleaned_data[ 'allowSingletO2'] # Quantum Calculations quantumCalc = form.cleaned_data['quantumCalc'] if quantumCalc == 'on': from rmgpy.qm.main import QMCalculator self.rmg.quantumMechanics = QMCalculator( software=form.cleaned_data['software'].encode(), method=form.cleaned_data['method'].encode(), fileStore=form.cleaned_data['fileStore'].encode(), scratchDirectory=form.cleaned_data['scratchDirectory'].encode( ), onlyCyclics=form.cleaned_data['onlyCyclics'], maxRadicalNumber=form.cleaned_data['maxRadicalNumber'], ) # Save the input.py file self.rmg.saveInput(self.savepath)