def get_models_to_merge(input_model_files):
"""
Reads input file paths and creates a list of ReactionModel
"""
models = []
for chemkin, species_path, transport_path in input_model_files:
print('Loading model #{0:d}...'.format(len(models) + 1))
model = ReactionModel()
model.species, model.reactions = load_chemkin_file(chemkin, species_path, transport_path=transport_path)
models.append(model)
return models
def saveCompareHTML(outputDir,chemkinPath1,speciesDictPath1,chemkinPath2,speciesDictPath2,readComments1=True,readComments2=True):
"""
Saves a model comparison HTML file based on two sets of chemkin and species dictionary
files.
"""
model1 = ReactionModel()
model1.species, model1.reactions = loadChemkinFile(chemkinPath1, speciesDictPath1, readComments = readComments1)
model2 = ReactionModel()
model2.species, model2.reactions = loadChemkinFile(chemkinPath2, speciesDictPath2, readComments = readComments2)
commonReactions, uniqueReactions1, uniqueReactions2 = compareModelReactions(model1, model2)
commonSpecies, uniqueSpecies1, uniqueSpecies2 = compareModelSpecies(model1, model2)
outputPath = outputDir + 'diff.html'
saveDiffHTML(outputPath, commonSpecies, uniqueSpecies1, uniqueSpecies2, commonReactions, uniqueReactions1, uniqueReactions2)
def combine_models(models):
"""
Takes in a list of ReactionModels and and merges them into a single ReactionModel
Reindexes species with the same label and index
"""
final_model = ReactionModel()
for i, model in enumerate(models):
print('Ignoring common species and reactions from model #{0:d}...'.
format(i + 1))
nspec0 = len(final_model.species)
nrxn0 = len(final_model.reactions)
final_model = final_model.merge(model)
nspec = len(final_model.species)
nrxn = len(final_model.reactions)
if len(model.species) > 0:
print(
'Added {1:d} out of {2:d} ({3:.1f}%) unique species from model '
'#{0:d}.'.format(i + 1, nspec - nspec0, len(model.species),
(nspec - nspec0) * 100. / len(model.species)))
else:
print('Added {1:d} out of {2:d} unique species from model '
'#{0:d}.'.format(i + 1, nspec - nspec0, len(model.species)))
if len(model.reactions) > 0:
print(
'Added {1:d} out of {2:d} ({3:.1f}%) unique reactions from model '
'#{0:d}.'.format(i + 1, nrxn - nrxn0, len(model.reactions),
(nrxn - nrxn0) * 100. / len(model.reactions)))
else:
print('Added {1:d} out of {2:d} unique reactions from model '
'#{0:d}.'.format(i + 1, nrxn - nrxn0, len(model.reactions)))
print('The merged model has {0:d} species and {1:d} reactions'
''.format(len(final_model.species), len(final_model.reactions)))
# ensure no species with same name and index
label_index_dict = {}
for s in final_model.species:
if s.label not in label_index_dict:
label_index_dict[s.label] = [s.index]
else:
if s.index in label_index_dict[s.label]:
# obtained a duplicate
s.index = max(label_index_dict[s.label]) + 1
print("Reindexed {0} due to dublicate labels and index".format(
s.label))
label_index_dict[s.label].append(s.index)
return final_model
def test_1(self):
"""
Test basic functionality of /tools/populate_reactions/
"""
from rmgpy.chemkin import loadChemkinFile
from rmgpy.rmg.model import ReactionModel
inputFile = os.path.join(rmgpy.getPath(), 'tools', 'data', 'generate',
'input.py')
with open(inputFile) as fp:
response = self.client.post('/tools/populate_reactions/',
{'InputFile': fp})
self.assertEqual(response.status_code, 200)
folder = os.path.join(settings.MEDIA_ROOT, 'rmg', 'tools',
'populateReactions')
# Check if inputs were correctly uploaded
pyInput = os.path.join(folder, 'input.txt')
self.assertTrue(os.path.isfile(pyInput),
'RMG input file was not uploaded')
# Check if outputs were correctly generated
htmlOutput = os.path.join(folder, 'output.html')
chemOutput = os.path.join(folder, 'chemkin', 'chem.inp')
dictOutput = os.path.join(folder, 'chemkin', 'species_dictionary.txt')
self.assertTrue(os.path.isfile(htmlOutput),
'HTML Output was not generated')
self.assertTrue(os.path.isfile(chemOutput),
'CHEMKIN file was not generated')
self.assertTrue(os.path.isfile(dictOutput),
'Species dictionary was not generated')
# Check that the output is not empty
model = ReactionModel()
model.species, model.reactions = loadChemkinFile(
chemOutput, dictOutput)
self.assertTrue(model.species, 'No species were generated')
self.assertTrue(model.reactions, 'No reactions were generated')
shutil.rmtree(folder)
def execute(inputModelFiles, **kwargs):
try:
wd = kwargs['wd']
except KeyError:
wd = os.getcwd()
transport = kwargs['transport']
outputChemkinFile = os.path.join(wd, 'chem.inp')
outputSpeciesDictionary = os.path.join(wd, 'species_dictionary.txt')
outputTransportFile = os.path.join(wd, 'tran.dat') if transport else None
# Load the models to merge
models = []
for chemkin, speciesPath, transportPath in inputModelFiles:
print 'Loading model #{0:d}...'.format(len(models)+1)
model = ReactionModel()
model.species, model.reactions = loadChemkinFile(chemkin, speciesPath, transportPath=transportPath)
models.append(model)
finalModel = ReactionModel()
for i, model in enumerate(models):
print 'Ignoring common species and reactions from model #{0:d}...'.format(i+1)
Nspec0 = len(finalModel.species)
Nrxn0 = len(finalModel.reactions)
finalModel = finalModel.merge(model)
Nspec = len(finalModel.species)
Nrxn = len(finalModel.reactions)
print 'Added {1:d} out of {2:d} ({3:.1f}%) unique species from model #{0:d}.'.format(i+1, Nspec - Nspec0, len(model.species), (Nspec - Nspec0) * 100. / len(model.species))
print 'Added {1:d} out of {2:d} ({3:.1f}%) unique reactions from model #{0:d}.'.format(i+1, Nrxn - Nrxn0, len(model.reactions), (Nrxn - Nrxn0) * 100. / len(model.reactions))
print 'The merged model has {0:d} species and {1:d} reactions'.format(len(finalModel.species), len(finalModel.reactions))
# Save the merged model to disk
saveChemkinFile(outputChemkinFile, finalModel.species, finalModel.reactions)
saveSpeciesDictionary(outputSpeciesDictionary, finalModel.species)
if transport:
saveTransportFile(outputTransportFile, finalModel.species)
print 'Merged Chemkin file saved to {0}'.format(outputChemkinFile)
print 'Merged species dictionary saved to {0}'.format(outputSpeciesDictionary)
if transport:
print 'Merged transport file saved to {0}'.format(outputTransportFile)
def combine_models(models):
"""
Takes in a list of ReactionModels and and merges them into a single ReactionModel
Reindexes species with the same label and index
"""
final_model = ReactionModel()
for i, model in enumerate(models):
print('Ignoring common species and reactions from model #{0:d}...'.
format(i + 1))
nspec0 = len(final_model.species)
nrxn0 = len(final_model.reactions)
final_model = final_model.merge(model)
nspec = len(final_model.species)
nrxn = len(final_model.reactions)
if len(model.species) > 0:
print(
'Added {1:d} out of {2:d} ({3:.1f}%) unique species from model '
'#{0:d}.'.format(i + 1, nspec - nspec0, len(model.species),
(nspec - nspec0) * 100. / len(model.species)))
else:
print('Added {1:d} out of {2:d} unique species from model '
'#{0:d}.'.format(i + 1, nspec - nspec0, len(model.species)))
if len(model.reactions) > 0:
print(
'Added {1:d} out of {2:d} ({3:.1f}%) unique reactions from model '
'#{0:d}.'.format(i + 1, nrxn - nrxn0, len(model.reactions),
(nrxn - nrxn0) * 100. / len(model.reactions)))
else:
print('Added {1:d} out of {2:d} unique reactions from model '
'#{0:d}.'.format(i + 1, nrxn - nrxn0, len(model.reactions)))
print('The merged model has {0:d} species and {1:d} reactions'
''.format(len(final_model.species), len(final_model.reactions)))
# reindex the unique species (to avoid name conflicts on save)
speciesIndex = 0
for spec in final_model.species:
if spec.label not in ['Ar', 'N2', 'Ne', 'He']:
spec.index = speciesIndex + 1
speciesIndex += 1
return final_model
def saveCompareHTML(outputDir,
chemkinPath1,
speciesDictPath1,
chemkinPath2,
speciesDictPath2,
readComments1=True,
readComments2=True):
"""
Saves a model comparison HTML file based on two sets of chemkin and species dictionary
files.
"""
model1 = ReactionModel()
model1.species, model1.reactions = loadChemkinFile(
chemkinPath1, speciesDictPath1, readComments=readComments1)
model2 = ReactionModel()
model2.species, model2.reactions = loadChemkinFile(
chemkinPath2, speciesDictPath2, readComments=readComments2)
commonReactions, uniqueReactions1, uniqueReactions2 = compareModelReactions(
model1, model2)
commonSpecies, uniqueSpecies1, uniqueSpecies2 = compareModelSpecies(
model1, model2)
outputPath = outputDir + 'diff.html'
saveDiffHTML(outputPath, commonSpecies, uniqueSpecies1, uniqueSpecies2,
commonReactions, uniqueReactions1, uniqueReactions2)
def save_compare_html(outputDir,
chemkin_path1,
species_dict_path1,
chemkin_path2,
species_dict_path2,
read_comments1=True,
read_comments2=True):
"""
Saves a model comparison HTML file based on two sets of chemkin and species dictionary
files.
"""
model1 = ReactionModel()
model1.species, model1.reactions = load_chemkin_file(
chemkin_path1, species_dict_path1, read_comments=read_comments1)
model2 = ReactionModel()
model2.species, model2.reactions = load_chemkin_file(
chemkin_path2, species_dict_path2, read_comments=read_comments2)
common_reactions, unique_reactions1, unique_reactions2 = compare_model_reactions(
model1, model2)
common_species, unique_species1, unique_species2 = compare_model_species(
model1, model2)
output_path = outputDir + 'diff.html'
save_diff_html(output_path, common_species, unique_species1,
unique_species2, common_reactions, unique_reactions1,
unique_reactions2)
def test_1(self):
"""
Test basic functionality of /tools/populate_reactions/
"""
from rmgpy.chemkin import loadChemkinFile
from rmgpy.rmg.model import ReactionModel
inputFile = os.path.join(rmgpy.getPath(),'tools','data','generate','input.py')
with open(inputFile) as fp:
response = self.client.post('/tools/populate_reactions/', {'InputFile': fp})
self.assertEqual(response.status_code, 200)
folder = os.path.join(settings.MEDIA_ROOT,'rmg','tools','populateReactions')
# Check if inputs were correctly uploaded
pyInput = os.path.join(folder,'input.txt')
self.assertTrue(os.path.isfile(pyInput),'RMG input file was not uploaded')
# Check if outputs were correctly generated
htmlOutput = os.path.join(folder,'output.html')
chemOutput = os.path.join(folder,'chemkin','chem.inp')
dictOutput = os.path.join(folder,'chemkin','species_dictionary.txt')
self.assertTrue(os.path.isfile(htmlOutput),'HTML Output was not generated')
self.assertTrue(os.path.isfile(chemOutput),'CHEMKIN file was not generated')
self.assertTrue(os.path.isfile(dictOutput),'Species dictionary was not generated')
# Check that the output is not empty
model = ReactionModel()
model.species, model.reactions = loadChemkinFile(chemOutput, dictOutput)
self.assertTrue(model.species,'No species were generated')
self.assertTrue(model.reactions, 'No reactions were generated')
shutil.rmtree(folder)
def execute(inputModelFiles, **kwargs):
try:
wd = kwargs['wd']
except KeyError:
wd = os.getcwd()
transport = kwargs['transport']
outputChemkinFile = os.path.join(wd, 'chem.inp')
outputSpeciesDictionary = os.path.join(wd, 'species_dictionary.txt')
outputTransportFile = os.path.join(wd, 'tran.dat') if transport else None
# Load the models to merge
models = []
for chemkin, speciesPath, transportPath in inputModelFiles:
print 'Loading model #{0:d}...'.format(len(models) + 1)
model = ReactionModel()
model.species, model.reactions = loadChemkinFile(
chemkin, speciesPath, transportPath=transportPath)
models.append(model)
finalModel = ReactionModel()
for i, model in enumerate(models):
print 'Ignoring common species and reactions from model #{0:d}...'.format(
i + 1)
Nspec0 = len(finalModel.species)
Nrxn0 = len(finalModel.reactions)
finalModel = finalModel.merge(model)
Nspec = len(finalModel.species)
Nrxn = len(finalModel.reactions)
print 'Added {1:d} out of {2:d} ({3:.1f}%) unique species from model #{0:d}.'.format(
i + 1, Nspec - Nspec0, len(model.species),
(Nspec - Nspec0) * 100. / len(model.species))
print 'Added {1:d} out of {2:d} ({3:.1f}%) unique reactions from model #{0:d}.'.format(
i + 1, Nrxn - Nrxn0, len(model.reactions),
(Nrxn - Nrxn0) * 100. / len(model.reactions))
print 'The merged model has {0:d} species and {1:d} reactions'.format(
len(finalModel.species), len(finalModel.reactions))
# Save the merged model to disk
saveChemkinFile(outputChemkinFile, finalModel.species,
finalModel.reactions)
saveSpeciesDictionary(outputSpeciesDictionary, finalModel.species)
if transport:
saveTransportFile(outputTransportFile, finalModel.species)
print 'Merged Chemkin file saved to {0}'.format(outputChemkinFile)
print 'Merged species dictionary saved to {0}'.format(
outputSpeciesDictionary)
if transport:
print 'Merged transport file saved to {0}'.format(outputTransportFile)
def test_save_output_html(self):
"""
This example is to test if an HTML file can be generated
for the provided chemkin model.
"""
folder = os.path.join(os.path.dirname(__file__), 'test_data/saveOutputHTML/')
chemkin_path = os.path.join(folder, 'eg6', 'chem_annotated.inp')
dictionary_path = os.path.join(folder, 'eg6', 'species_dictionary.txt')
# load_chemkin_file
species, reactions = load_chemkin_file(chemkin_path, dictionary_path)
# convert it into a reaction model:
core = ReactionModel(species, reactions)
cerm = CoreEdgeReactionModel(core)
out = os.path.join(folder, 'output.html')
save_output_html(out, cerm)
self.assertTrue(os.path.isfile(out))
os.remove(out)
shutil.rmtree(os.path.join(folder, 'species'))
inputModelFiles.append((model[0], model[1], None))
elif len(model) == 3:
transport = True
inputModelFiles.append((model[0], model[1], model[2]))
else:
raise Exception
outputChemkinFile = 'chem.inp'
outputSpeciesDictionary = 'species_dictionary.txt'
outputTransportFile = 'tran.dat' if transport else None
# Load the models to merge
models = []
for chemkin, speciesPath, transportPath in inputModelFiles:
print 'Loading model #{0:d}...'.format(len(models)+1)
model = ReactionModel()
model.species, model.reactions = loadChemkinFile(chemkin, speciesPath, transportPath=transportPath)
models.append(model)
finalModel = ReactionModel()
for i, model in enumerate(models):
print 'Ignoring common species and reactions from model #{0:d}...'.format(i+1)
Nspec0 = len(finalModel.species)
Nrxn0 = len(finalModel.reactions)
finalModel = finalModel.merge(model)
Nspec = len(finalModel.species)
Nrxn = len(finalModel.reactions)
print 'Added {1:d} out of {2:d} ({3:.1f}%) unique species from model #{0:d}.'.format(i+1, Nspec - Nspec0, len(model.species), (Nspec - Nspec0) * 100. / len(model.species))
print 'Added {1:d} out of {2:d} ({3:.1f}%) unique reactions from model #{0:d}.'.format(i+1, Nrxn - Nrxn0, len(model.reactions), (Nrxn - Nrxn0) * 100. / len(model.reactions))
print 'The merged model has {0:d} species and {1:d} reactions'.format(len(finalModel.species), len(finalModel.reactions))
inputModelFiles.append((model[0], model[1], None))
elif len(model) == 3:
transport = True
inputModelFiles.append((model[0], model[1], model[2]))
else:
raise Exception
outputChemkinFile = 'chem.inp'
outputSpeciesDictionary = 'species_dictionary.txt'
outputTransportFile = 'tran.dat' if transport else None
# Load the models to merge
models = []
for chemkin, speciesPath, transportPath in inputModelFiles:
print 'Loading model #{0:d}...'.format(len(models)+1)
model = ReactionModel()
model.species, model.reactions = loadChemkinFile(chemkin, speciesPath, transportPath=transportPath)
models.append(model)
allSpecies = []
speciesIndices = [[] for i in range(len(models))]
for i, model in enumerate(models):
speciesIndices[i] = []
for j, species in enumerate(model.species):
for index, species0 in enumerate(allSpecies):
if species0.isIsomorphic(species):
speciesIndices[i].append(index)
break;
else:
allSpecies.append(species)
speciesIndices[i].append(allSpecies.index(species))
def execute(chemkin1, speciesDict1, thermo1, chemkin2, speciesDict2, thermo2, **kwargs):
model1 = ReactionModel()
model1.species, model1.reactions = loadChemkinFile(chemkin1, speciesDict1, thermoPath = thermo1)
model2 = ReactionModel()
model2.species, model2.reactions = loadChemkinFile(chemkin2, speciesDict2, thermoPath = thermo2)
commonSpecies, uniqueSpecies1, uniqueSpecies2 = compareModelSpecies(model1, model2)
commonReactions, uniqueReactions1, uniqueReactions2 = compareModelReactions(model1, model2)
try:
diffOnly = kwargs['diffOnly']
except KeyError:
diffOnly = False
try:
commonDiffOnly = kwargs['commonDiffOnly']
except KeyError:
commonDiffOnly = False
if diffOnly or commonDiffOnly:
commonSpecies = filter(lambda x: not identicalThermo(x), commonSpecies)
commonReactions = filter(lambda x: not identicalKinetics(x), commonReactions)
if commonDiffOnly:
uniqueSpecies1 = []
uniqueSpecies2 = []
uniqueReactions1 = []
uniqueReactions2 = []
try:
web = kwargs['web']
except KeyError:
web = False
if not web:
logging.info('{0:d} species were found in both models:'.format(len(commonSpecies)))
for spec1, spec2 in commonSpecies:
logging.info(' {0!s}'.format(spec1))
if spec1.thermo and spec2.thermo:
spec1.molecule[0].getSymmetryNumber()
logging.info(' {0:7.2f} {1:7.2f} {2:7.2f} {3:7.2f} {4:7.2f} {5:7.2f} {6:7.2f} {7:7.2f} {8:7.2f}'.format(
spec1.thermo.getEnthalpy(300) / 4184.,
spec1.thermo.getEntropy(300) / 4.184,
spec1.thermo.getHeatCapacity(300) / 4.184,
spec1.thermo.getHeatCapacity(400) / 4.184,
spec1.thermo.getHeatCapacity(500) / 4.184,
spec1.thermo.getHeatCapacity(600) / 4.184,
spec1.thermo.getHeatCapacity(800) / 4.184,
spec1.thermo.getHeatCapacity(1000) / 4.184,
spec1.thermo.getHeatCapacity(1500) / 4.184,
))
logging.info(' {0:7.2f} {1:7.2f} {2:7.2f} {3:7.2f} {4:7.2f} {5:7.2f} {6:7.2f} {7:7.2f} {8:7.2f}'.format(
spec2.thermo.getEnthalpy(300) / 4184.,
spec2.thermo.getEntropy(300) / 4.184,
spec2.thermo.getHeatCapacity(300) / 4.184,
spec2.thermo.getHeatCapacity(400) / 4.184,
spec2.thermo.getHeatCapacity(500) / 4.184,
spec2.thermo.getHeatCapacity(600) / 4.184,
spec2.thermo.getHeatCapacity(800) / 4.184,
spec2.thermo.getHeatCapacity(1000) / 4.184,
spec2.thermo.getHeatCapacity(1500) / 4.184,
))
logging.info('{0:d} species were only found in the first model:'.format(len(uniqueSpecies1)))
for spec in uniqueSpecies1:
logging.info(' {0!s}'.format(spec))
logging.info('{0:d} species were only found in the second model:'.format(len(uniqueSpecies2)))
for spec in uniqueSpecies2:
logging.info(' {0!s}'.format(spec))
logging.info('{0:d} reactions were found in both models:'.format(len(commonReactions)))
for rxn1, rxn2 in commonReactions:
logging.info(' {0!s}'.format(rxn1))
if rxn1.kinetics and rxn2.kinetics:
logging.info(' {0:7.2f} {1:7.2f} {2:7.2f} {3:7.2f} {4:7.2f} {5:7.2f} {6:7.2f} {7:7.2f}'.format(
math.log10(rxn1.kinetics.getRateCoefficient(300, 1e5)),
math.log10(rxn1.kinetics.getRateCoefficient(400, 1e5)),
math.log10(rxn1.kinetics.getRateCoefficient(500, 1e5)),
math.log10(rxn1.kinetics.getRateCoefficient(600, 1e5)),
math.log10(rxn1.kinetics.getRateCoefficient(800, 1e5)),
math.log10(rxn1.kinetics.getRateCoefficient(1000, 1e5)),
math.log10(rxn1.kinetics.getRateCoefficient(1500, 1e5)),
math.log10(rxn1.kinetics.getRateCoefficient(2000, 1e5)),
))
logging.info(' {0:7.2f} {1:7.2f} {2:7.2f} {3:7.2f} {4:7.2f} {5:7.2f} {6:7.2f} {7:7.2f}'.format(
math.log10(rxn2.kinetics.getRateCoefficient(300, 1e5)),
math.log10(rxn2.kinetics.getRateCoefficient(400, 1e5)),
math.log10(rxn2.kinetics.getRateCoefficient(500, 1e5)),
math.log10(rxn2.kinetics.getRateCoefficient(600, 1e5)),
math.log10(rxn2.kinetics.getRateCoefficient(800, 1e5)),
math.log10(rxn2.kinetics.getRateCoefficient(1000, 1e5)),
math.log10(rxn2.kinetics.getRateCoefficient(1500, 1e5)),
math.log10(rxn2.kinetics.getRateCoefficient(2000, 1e5)),
))
logging.info('{0:d} reactions were only found in the first model:'.format(len(uniqueReactions1)))
for rxn in uniqueReactions1:
logging.info(' {0!s}'.format(rxn))
logging.info('{0:d} reactions were only found in the second model:'.format(len(uniqueReactions2)))
for rxn in uniqueReactions2:
logging.info(' {0!s}'.format(rxn))
logging.info("Saving output in diff.html")
try:
wd = kwargs['wd']
except KeyError:
wd = os.getcwd()
outputPath = os.path.join(wd, 'diff.html')
saveDiffHTML(outputPath, commonSpecies, uniqueSpecies1, uniqueSpecies2, commonReactions, uniqueReactions1, uniqueReactions2)
logging.info("Finished!")
return commonSpecies, uniqueSpecies1, uniqueSpecies2, commonReactions, uniqueReactions1, uniqueReactions2
def main():
fuelName = 'test'
chemFile = 'chem_' + fuelName
spcFile = 'spc_' + fuelName + '.txt'
outputChemkinFile = chemFile + '_delete_DupThirdBodyRXNs.inp'
chemFile += '.inp'
model = ReactionModel()
model.species, model.reactions = loadChemkinFile(chemFile, spcFile)
# Delete redundant third body reactions
thirdBodyRXNs = []
deleteRedundantThirdBodyRXNs = []
duplicateEndoRXNs = []
for rxn in model.reactions:
if isinstance(rxn.kinetics, ThirdBody):
thirdBodyRXNs.append(rxn)
for rxnThirdBody in thirdBodyRXNs:
for rxnTest in model.reactions:
if rxnThirdBody.index != rxnTest.index:
if checkSpecificFormThirdBodyRXN(rxnThirdBody, rxnTest):
deleteRedundantThirdBodyRXNs.append(rxnTest)
# Delete duplicate reactions caused by Intra_R_Add_Endocyclic and Intra_R_Add_Exocyclic
# Delete the endo one.
for rxn1 in [
rxn for rxn in model.reactions
if rxn.duplicate == True and rxn.family == 'Intra_R_Add_Exocyclic'
]:
for rxn2 in [
rxn for rxn in model.reactions if rxn.duplicate == True
and rxn.family == 'Intra_R_Add_Endocyclic'
]:
if rxn1.index != rxn2.index and rxn1.isIsomorphic(
rxn2, eitherDirection=True):
duplicateEndoRXNs.append(rxn2)
rxn1.duplicate = False
print '--------------------------------------------'
print 'The following {0} redundant third body reactions will be removed from the original model:'.format(
len(deleteRedundantThirdBodyRXNs))
for rxn in deleteRedundantThirdBodyRXNs:
print rxn
print '--------------------------------------------'
print 'The following {0} duplicated Intra_R_Add_Endocyclic reactions will be removed from the original model:'.format(
len(duplicateEndoRXNs))
for rxn in duplicateEndoRXNs:
print rxn
print '--------------------------------------------'
print 'The original model has {0} rxns'.format(len(model.reactions))
for rxn in deleteRedundantThirdBodyRXNs + duplicateEndoRXNs:
model.reactions.remove(rxn)
print 'The final model has {0} rxns'.format(len(model.reactions))
print 'Save the final model into chemkin file...'
saveChemkinFile(outputChemkinFile, model.species, model.reactions)
inputModelFiles.append((model[0], model[1], None))
elif len(model) == 3:
transport = True
inputModelFiles.append((model[0], model[1], model[2]))
else:
raise Exception
outputChemkinFile = 'chem.inp'
outputSpeciesDictionary = 'species_dictionary.txt'
outputTransportFile = 'tran.dat' if transport else None
# Load the models to merge
models = []
for chemkin, speciesPath, transportPath in inputModelFiles:
print 'Loading model #{0:d}...'.format(len(models)+1)
model = ReactionModel()
model.species, model.reactions = loadChemkinFile(chemkin, speciesPath, transportPath=transportPath)
models.append(model)
allSpecies = []
speciesIndices = [[] for i in range(len(models))]
for i, model in enumerate(models):
speciesIndices[i] = []
for j, species in enumerate(model.species):
for index, species0 in enumerate(allSpecies):
if species0.isIsomorphic(species):
speciesIndices[i].append(index)
break;
else:
allSpecies.append(species)
speciesIndices[i].append(allSpecies.index(species))
def execute(chemkin1, species_dict1, thermo1, chemkin2, species_dict2, thermo2,
**kwargs):
model1 = ReactionModel()
model1.species, model1.reactions = load_chemkin_file(chemkin1,
species_dict1,
thermo_path=thermo1)
model2 = ReactionModel()
model2.species, model2.reactions = load_chemkin_file(chemkin2,
species_dict2,
thermo_path=thermo2)
common_species, unique_species1, unique_species2 = compare_model_species(
model1, model2)
common_reactions, unique_reactions1, unique_reactions2 = compare_model_reactions(
model1, model2)
try:
diff_only = kwargs['diffOnly']
except KeyError:
diff_only = False
try:
common_diff_only = kwargs['commonDiffOnly']
except KeyError:
common_diff_only = False
if diff_only or common_diff_only:
common_species = [x for x in common_species if not identical_thermo(x)]
common_reactions = [
x for x in common_reactions if not identical_kinetics(x)
]
if common_diff_only:
unique_species1 = []
unique_species2 = []
unique_reactions1 = []
unique_reactions2 = []
try:
web = kwargs['web']
except KeyError:
web = False
if not web:
logging.info('{0:d} species were found in both models:'.format(
len(common_species)))
for spec1, spec2 in common_species:
logging.info(' {0!s}'.format(spec1))
if spec1.thermo and spec2.thermo:
spec1.molecule[0].get_symmetry_number()
logging.info(
' {0:7.2f} {1:7.2f} {2:7.2f} {3:7.2f} {4:7.2f} {5:7.2f} {6:7.2f} {7:7.2f} {8:7.2f}'
.format(
spec1.thermo.get_enthalpy(300) / 4184.,
spec1.thermo.get_entropy(300) / 4.184,
spec1.thermo.get_heat_capacity(300) / 4.184,
spec1.thermo.get_heat_capacity(400) / 4.184,
spec1.thermo.get_heat_capacity(500) / 4.184,
spec1.thermo.get_heat_capacity(600) / 4.184,
spec1.thermo.get_heat_capacity(800) / 4.184,
spec1.thermo.get_heat_capacity(1000) / 4.184,
spec1.thermo.get_heat_capacity(1500) / 4.184,
))
logging.info(
' {0:7.2f} {1:7.2f} {2:7.2f} {3:7.2f} {4:7.2f} {5:7.2f} {6:7.2f} {7:7.2f} {8:7.2f}'
.format(
spec2.thermo.get_enthalpy(300) / 4184.,
spec2.thermo.get_entropy(300) / 4.184,
spec2.thermo.get_heat_capacity(300) / 4.184,
spec2.thermo.get_heat_capacity(400) / 4.184,
spec2.thermo.get_heat_capacity(500) / 4.184,
spec2.thermo.get_heat_capacity(600) / 4.184,
spec2.thermo.get_heat_capacity(800) / 4.184,
spec2.thermo.get_heat_capacity(1000) / 4.184,
spec2.thermo.get_heat_capacity(1500) / 4.184,
))
logging.info(
'{0:d} species were only found in the first model:'.format(
len(unique_species1)))
for spec in unique_species1:
logging.info(' {0!s}'.format(spec))
logging.info(
'{0:d} species were only found in the second model:'.format(
len(unique_species2)))
for spec in unique_species2:
logging.info(' {0!s}'.format(spec))
logging.info('{0:d} reactions were found in both models:'.format(
len(common_reactions)))
for rxn1, rxn2 in common_reactions:
logging.info(' {0!s}'.format(rxn1))
if rxn1.kinetics and rxn2.kinetics:
logging.info(
' {0:7.2f} {1:7.2f} {2:7.2f} {3:7.2f} {4:7.2f} {5:7.2f} {6:7.2f} {7:7.2f}'
.format(
math.log10(rxn1.kinetics.get_rate_coefficient(
300, 1e5)),
math.log10(rxn1.kinetics.get_rate_coefficient(
400, 1e5)),
math.log10(rxn1.kinetics.get_rate_coefficient(
500, 1e5)),
math.log10(rxn1.kinetics.get_rate_coefficient(
600, 1e5)),
math.log10(rxn1.kinetics.get_rate_coefficient(
800, 1e5)),
math.log10(
rxn1.kinetics.get_rate_coefficient(1000, 1e5)),
math.log10(
rxn1.kinetics.get_rate_coefficient(1500, 1e5)),
math.log10(
rxn1.kinetics.get_rate_coefficient(2000, 1e5)),
))
logging.info(
' {0:7.2f} {1:7.2f} {2:7.2f} {3:7.2f} {4:7.2f} {5:7.2f} {6:7.2f} {7:7.2f}'
.format(
math.log10(rxn2.kinetics.get_rate_coefficient(
300, 1e5)),
math.log10(rxn2.kinetics.get_rate_coefficient(
400, 1e5)),
math.log10(rxn2.kinetics.get_rate_coefficient(
500, 1e5)),
math.log10(rxn2.kinetics.get_rate_coefficient(
600, 1e5)),
math.log10(rxn2.kinetics.get_rate_coefficient(
800, 1e5)),
math.log10(
rxn2.kinetics.get_rate_coefficient(1000, 1e5)),
math.log10(
rxn2.kinetics.get_rate_coefficient(1500, 1e5)),
math.log10(
rxn2.kinetics.get_rate_coefficient(2000, 1e5)),
))
logging.info(
'{0:d} reactions were only found in the first model:'.format(
len(unique_reactions1)))
for rxn in unique_reactions1:
logging.info(' {0!s}'.format(rxn))
logging.info(
'{0:d} reactions were only found in the second model:'.format(
len(unique_reactions2)))
for rxn in unique_reactions2:
logging.info(' {0!s}'.format(rxn))
logging.info("Saving output in diff.html")
try:
wd = kwargs['wd']
except KeyError:
wd = os.getcwd()
output_path = os.path.join(wd, 'diff.html')
save_diff_html(output_path, common_species, unique_species1,
unique_species2, common_reactions, unique_reactions1,
unique_reactions2)
logging.info("Finished!")
return common_species, unique_species1, unique_species2, common_reactions, unique_reactions1, unique_reactions2
def execute(chemkin1, speciesDict1, thermo1, chemkin2, speciesDict2, thermo2,
**kwargs):
model1 = ReactionModel()
model1.species, model1.reactions = loadChemkinFile(chemkin1,
speciesDict1,
thermoPath=thermo1)
model2 = ReactionModel()
model2.species, model2.reactions = loadChemkinFile(chemkin2,
speciesDict2,
thermoPath=thermo2)
commonSpecies, uniqueSpecies1, uniqueSpecies2 = compareModelSpecies(
model1, model2)
commonReactions, uniqueReactions1, uniqueReactions2 = compareModelReactions(
model1, model2)
try:
diffOnly = kwargs['diffOnly']
except KeyError:
diffOnly = False
try:
commonDiffOnly = kwargs['commonDiffOnly']
except KeyError:
commonDiffOnly = False
if diffOnly or commonDiffOnly:
commonSpecies = filter(lambda x: not identicalThermo(x), commonSpecies)
commonReactions = filter(lambda x: not identicalKinetics(x),
commonReactions)
if commonDiffOnly:
uniqueSpecies1 = []
uniqueSpecies2 = []
uniqueReactions1 = []
uniqueReactions2 = []
try:
web = kwargs['web']
except KeyError:
web = False
if not web:
logging.info('{0:d} species were found in both models:'.format(
len(commonSpecies)))
for spec1, spec2 in commonSpecies:
logging.info(' {0!s}'.format(spec1))
if spec1.thermo and spec2.thermo:
spec1.molecule[0].getSymmetryNumber()
logging.info(
' {0:7.2f} {1:7.2f} {2:7.2f} {3:7.2f} {4:7.2f} {5:7.2f} {6:7.2f} {7:7.2f} {8:7.2f}'
.format(
spec1.thermo.getEnthalpy(300) / 4184.,
spec1.thermo.getEntropy(300) / 4.184,
spec1.thermo.getHeatCapacity(300) / 4.184,
spec1.thermo.getHeatCapacity(400) / 4.184,
spec1.thermo.getHeatCapacity(500) / 4.184,
spec1.thermo.getHeatCapacity(600) / 4.184,
spec1.thermo.getHeatCapacity(800) / 4.184,
spec1.thermo.getHeatCapacity(1000) / 4.184,
spec1.thermo.getHeatCapacity(1500) / 4.184,
))
logging.info(
' {0:7.2f} {1:7.2f} {2:7.2f} {3:7.2f} {4:7.2f} {5:7.2f} {6:7.2f} {7:7.2f} {8:7.2f}'
.format(
spec2.thermo.getEnthalpy(300) / 4184.,
spec2.thermo.getEntropy(300) / 4.184,
spec2.thermo.getHeatCapacity(300) / 4.184,
spec2.thermo.getHeatCapacity(400) / 4.184,
spec2.thermo.getHeatCapacity(500) / 4.184,
spec2.thermo.getHeatCapacity(600) / 4.184,
spec2.thermo.getHeatCapacity(800) / 4.184,
spec2.thermo.getHeatCapacity(1000) / 4.184,
spec2.thermo.getHeatCapacity(1500) / 4.184,
))
logging.info(
'{0:d} species were only found in the first model:'.format(
len(uniqueSpecies1)))
for spec in uniqueSpecies1:
logging.info(' {0!s}'.format(spec))
logging.info(
'{0:d} species were only found in the second model:'.format(
len(uniqueSpecies2)))
for spec in uniqueSpecies2:
logging.info(' {0!s}'.format(spec))
logging.info('{0:d} reactions were found in both models:'.format(
len(commonReactions)))
for rxn1, rxn2 in commonReactions:
logging.info(' {0!s}'.format(rxn1))
if rxn1.kinetics and rxn2.kinetics:
logging.info(
' {0:7.2f} {1:7.2f} {2:7.2f} {3:7.2f} {4:7.2f} {5:7.2f} {6:7.2f} {7:7.2f}'
.format(
math.log10(rxn1.kinetics.getRateCoefficient(300, 1e5)),
math.log10(rxn1.kinetics.getRateCoefficient(400, 1e5)),
math.log10(rxn1.kinetics.getRateCoefficient(500, 1e5)),
math.log10(rxn1.kinetics.getRateCoefficient(600, 1e5)),
math.log10(rxn1.kinetics.getRateCoefficient(800, 1e5)),
math.log10(rxn1.kinetics.getRateCoefficient(1000,
1e5)),
math.log10(rxn1.kinetics.getRateCoefficient(1500,
1e5)),
math.log10(rxn1.kinetics.getRateCoefficient(2000,
1e5)),
))
logging.info(
' {0:7.2f} {1:7.2f} {2:7.2f} {3:7.2f} {4:7.2f} {5:7.2f} {6:7.2f} {7:7.2f}'
.format(
math.log10(rxn2.kinetics.getRateCoefficient(300, 1e5)),
math.log10(rxn2.kinetics.getRateCoefficient(400, 1e5)),
math.log10(rxn2.kinetics.getRateCoefficient(500, 1e5)),
math.log10(rxn2.kinetics.getRateCoefficient(600, 1e5)),
math.log10(rxn2.kinetics.getRateCoefficient(800, 1e5)),
math.log10(rxn2.kinetics.getRateCoefficient(1000,
1e5)),
math.log10(rxn2.kinetics.getRateCoefficient(1500,
1e5)),
math.log10(rxn2.kinetics.getRateCoefficient(2000,
1e5)),
))
logging.info(
'{0:d} reactions were only found in the first model:'.format(
len(uniqueReactions1)))
for rxn in uniqueReactions1:
logging.info(' {0!s}'.format(rxn))
logging.info(
'{0:d} reactions were only found in the second model:'.format(
len(uniqueReactions2)))
for rxn in uniqueReactions2:
logging.info(' {0!s}'.format(rxn))
logging.info("Saving output in diff.html")
try:
wd = kwargs['wd']
except KeyError:
wd = os.getcwd()
outputPath = os.path.join(wd, 'diff.html')
saveDiffHTML(outputPath, commonSpecies, uniqueSpecies1, uniqueSpecies2,
commonReactions, uniqueReactions1, uniqueReactions2)
logging.info("Finished!")
return commonSpecies, uniqueSpecies1, uniqueSpecies2, commonReactions, uniqueReactions1, uniqueReactions2
