def getFluxModel(self,configFileName,modelNames):
gconfigParser = GeneralMultiConfigParser()
gconfigs = gconfigParser.parse(configFileName)
modelParser = FluxModelFlatFileParser()
modelParser.setWrapper("\'")
fluxModel = None
pName = ''
iFluxModel = LinearModel()
for mName in modelNames:
if mName != '':
gconfig = gconfigs[mName]
iFluxModel = modelParser.parseGenConfig(gconfig, mName)
if fluxModel == None:
fluxModel = iFluxModel
pName = fluxModel.objectives.keys()[0]
else:
fluxModel.extend(pName,mName,iFluxModel)
#---------------------------
# Parse Linear Model
#---------------------------
modelName = modelNames[0]
modelMaker = CreateLinearModel()
modelMaker.setScale(1)
modelMatrix = modelMaker.fromFluxModel(fluxModel, modelName)
#-------------------------
#Set Filter Target List
#------------------------
nonTargets = []
targetList = fluxModel.getMetabolicNetwork().getAnnotation("ValidTarget")
for name in targetList.keys():
value = targetList[name]
if value =="FALSE":
nonTargets.append(name)
return (fluxModel,modelMatrix,nonTargets)
def parseModel(self,modelNames):
'''
Generate linear optimization model object
using names from configuration set in ModelFactory
@var modelNames: list of the names of the metabolic models
@type modelNames: [String]
'''
modelConfig = ReflectionConfig()
modelConfig.readfp(open(self.modelConfigFile))
fluxModel = None
#fluxModel = FluxModel()
pName = ''
annotation = {}
for mName in modelNames:
if mName != '':
lmParser = MetabolicNetworkParser()
modelConfig.reflect(mName,lmParser)
#xFluxModel = lmParser.generateModel(mName)
modelParser = FluxModelFlatFileParser()
modelParser.setWrapper("\'")
modelConfig.reflect(mName, modelParser)
jFluxModel = modelParser.generateModel(mName)
if fluxModel == None:
fluxModel = jFluxModel
pName = fluxModel.objectives.keys()[0]
else:
fluxModel.extend(pName,mName,jFluxModel)
pass
if modelConfig.has_option(mName, "annotationFiles"):
annotationFiles = modelConfig.get(mName,"annotationfiles")
annotationFiles = eval(annotationFiles)
iAnnotation = self.parseAnnotationFiles(annotationFiles)
annotation = self.joinAnnotation(annotation, iAnnotation)
#---------------------------
# Parse Linear Model
#---------------------------
modelName = modelNames[0]
modelMaker = CreateLinearModel()
model = modelMaker.fromFluxModel(fluxModel, modelName)
model.annotation = annotation
model.modelName = ",".join(modelNames)
#---------------------------
# Select subsections
#---------------------------
if self.subSections != '':
subSections = self.subSections.split(',')
subValues= fluxModel.getMetabolicNetwork().getAnnotation("Section")
for (name,subValue) in subValues.items():
if subValue != None and subValue not in subSections:
if self.verbose: print "removing %s" % (name)
model.removeColumn(name)
validColumns = model.getColumnNames()
#-------------------------
#Set Filter Target List
#------------------------
targets = []
nonTargets = []
targetTags = fluxModel.getMetabolicNetwork().getAnnotation("ValidTarget")
for (name,value) in targetTags.items():
if value == "TRUE":
targets.append(name)
if value =="FALSE":
nonTargets.append(name)
targets = set(validColumns).intersection(targets)
model.targets = targets
return (fluxModel,model)
