def generateLongNameReport(self,fluxModel):
report = Report()
for name in fluxModel.getMetabolicNetwork().getOrderedReactionNames():
reaction = fluxModel.getMetabolicNetwork().getReaction(name)
longName = reaction.getName()
equation = reaction.getEquation()
report.addElement(name,"LongName",longName)
report.addElement(name,"Equation",equation)
return report
def writeReport(self,ltReport,fluxModel, oPredVal,sPredVal,s2PredVal,neighborhood,iterations,fObjective,resultDir):
if self.verbose: print "Preparing report ..."
report = Report()
reactionNames = fluxModel.network.getOrderedReactionNames()
reactionMap = fluxModel.network.getReactionMap()
for reactionName in reactionNames:
reaction = reactionMap[reactionName]
equation = reaction.getEquation()
pathway = reaction.getAnnotation("Subsystem")
name = reaction.getName()#Currently sensitivity values can be too large for control factors.
report.addElement(reactionName,"name",name)
report.addElement(reactionName,"equation", equation)
report.addElement(reactionName,"Subsystem", pathway)
#--------------------
#Analysis in report
#--------------------
report.addColumnHash("Original", oPredVal)
report.addColumnHash("Synthetic", sPredVal)
report.addColumnHash("Synthetic mBio", s2PredVal)
report.extend(ltReport)
report.addColumnHash("Final Objective", fObjective)
#--------------------
#Write Report
#--------------------
if self.verbose: print "Writing report ..."
outputFileName = resultDir + "RD_" + self.resultTag + "_" + self.modelName + "_" + self.syntheticObjectiveName + "_" + str(neighborhood) + "_" + str(iterations) + "_" + strftime('%Y%m%dT%H%M%S') + ".txt"
writer = ReportWriter()
writer.setFile(outputFileName)
writer.write(report)
writer.closeFile()
if self.verbose: print "Report Written [%s]" % (outputFileName)
return report
