def checkSolverScip(self,modelMatrix,predVal,delta=1e-3):
lp = LPSolver()
lp.setModel(modelMatrix)
lp.runIntOpt()
scipPredVal = lp.getMipPredictionMap()
(testRows,badRows) = self.checkValues(modelMatrix.data,scipPredVal,modelMatrix.getRowLimits())
if self.verbose: print "--Debug: number of failed rows %s" % (len(badRows))
lp.clear()
solverDiff = self.debugCompareFluxes(predVal,scipPredVal)
if self.verbose: print "--Debug: difference in glpk / scip %s" % (len(solverDiff))
return (testRows,badRows,solverDiff)
def productionLevels(originalModel,options,minBio=0.20,verbose=False):
naturalObjectiveName = options.bioObj
syntheticObjectiveName = options.synthObj
cellularObjective = {naturalObjectiveName:-1.0}
syntheticObjective = {syntheticObjectiveName:-1.0}
lo = LPSolver()
lo.setModel(originalModel)
oPredVal = lo.run(objective = cellularObjective)
oBioVal = oPredVal[naturalObjectiveName]
oSynthVal = oPredVal[syntheticObjectiveName]
if verbose: print "Max cellular: Biological [%s] Synthetic: [%s]" % (oBioVal, oSynthVal)
#---------------------------------------
# Values for Max Synthetic Objective
#---------------------------------------
sPredVal = lo.run(objective = syntheticObjective)
sBioVal = sPredVal[naturalObjectiveName]
sSynthVal = sPredVal[syntheticObjectiveName]
lo.clear()
if verbose: print "Max synthetic: Biological [%s] Synthetic: [%s]" % (sBioVal, sSynthVal)
#-----------------------------------
# Values for minimum Natural objective
#-----------------------------------
minObjVal = oBioVal*0.20
originalModel.addColumnLimit(naturalObjectiveName,(minObjVal,None))
lo = LPSolver()
s2PredVal = lo.run(model=originalModel,objective = syntheticObjective)
s2BioVal = s2PredVal[naturalObjectiveName]
s2SynthVal = s2PredVal[syntheticObjectiveName]
lo.clear()
return (oPredVal,sPredVal,s2PredVal)
