Reference Manual

All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Properties Friends Macros Pages

Functions
def	createRatio

def	createRatioFromGraph

def	graphProducer

def	histoProducer

def	savePlots

Variables
string	Banner = "CMS Preliminary"

	batch = False

	doRatio = True

	drawLegend = False

string	drawOption = ""

list	EtaPtBin

string	fileNameRef = "BTagRelVal_TTbar_Startup_612SLHC1_14.root"

string	fileNameVal = "BTagRelVal_TTbar_Startup_14_612SLHC2.root"

list	listFlavors

list	listFromats

list	listHistos

list	listTag

dictionary	mapColor

dictionary	mapLineStyle

dictionary	mapLineWidth

dictionary	mapMarker

string	pathInFile = "/DQMData/Run 1/Btag/Run summary/"

	printBanner = False

string	RefRel = "612SLHC1_14"

string	RefSample = "TTbar_FullSim"

tuple	unity = TF1("unity","1",-1000,1000)

string	ValRel = "612SLHC2_14"

string	ValSample = "TTbar_FullSim"

int	weight = 1

Function Documentation

def histoStyle.createRatio	(	hVal,
		hRef
	)

Definition at line 392 of file histoStyle.py.

 
 def createRatio(hVal,hRef):
     ratio = []
     for h_i in range(0,len(hVal)): 
         if hVal[h_i] is None : continue
         r = TH1F(hVal[h_i].GetName()+"ratio","ratio "+hVal[h_i].GetTitle(),hVal[h_i].GetNbinsX(),hVal[h_i].GetXaxis().GetXmin(),hVal[h_i].GetXaxis().GetXmax())
         r.Add(hVal[h_i])
         r.Divide(hRef[h_i])
         r.GetYaxis().SetRangeUser(0.25,1.75)
         r.SetMarkerColor(hVal[h_i].GetMarkerColor())
         r.SetLineColor(hVal[h_i].GetLineColor())
         r.GetYaxis().SetLabelSize(0.15)
         r.GetXaxis().SetLabelSize(0.15)
         ratio.append(r)
     return ratio
#to create ratio plots from TGraphErrors

histoStyle.createRatio

def createRatio

Definition: histoStyle.py:392

def histoStyle.createRatioFromGraph	(	hVal,
		hRef
	)

Definition at line 407 of file histoStyle.py.

 
 def createRatioFromGraph(hVal,hRef):
     ratio = []
     for g_i in range(0,len(hVal)):
         if hVal[g_i] is None :
             ratio.append(None)
             continue
         tmp = hVal[g_i].GetHistogram()
         histVal = TH1F(hVal[g_i].GetName()+"_ratio",hVal[g_i].GetTitle()+"_ratio",tmp.GetNbinsX(),tmp.GetXaxis().GetXmin(),tmp.GetXaxis().GetXmax())
         histRef = TH1F(hRef[g_i].GetName()+"_ratio",hRef[g_i].GetTitle()+"_ratio",histVal.GetNbinsX(),histVal.GetXaxis().GetXmin(),histVal.GetXaxis().GetXmax())
         #loop over the N points
         for p in range(0,hVal[g_i].GetN()-1):
             #get point p
             x = Double(0)
             y = Double(0)
             hVal[g_i].GetPoint(p,x,y)
             xerr = hVal[g_i].GetErrorX(p)
             yerr = hVal[g_i].GetErrorY(p)
             bin_p = histVal.FindBin(x)
             xHist = histVal.GetBinCenter(bin_p)
             #get the other point as xHist in [x,xbis]
             xbis = Double(0)
             ybis = Double(0)
             #points are odered from high x to low x
             if xHist>x : 
                 if p==0 : continue
                 xbiserr = hVal[g_i].GetErrorX(p-1)
                 ybiserr = hVal[g_i].GetErrorY(p-1)
                 hVal[g_i].GetPoint(p-1,xbis,ybis)
             else :
                 xbiserr = hVal[g_i].GetErrorX(p+1)
                 ybiserr = hVal[g_i].GetErrorY(p+1)
                 hVal[g_i].GetPoint(p+1,xbis,ybis)
             if ybis==y : 
                 #just take y at x
                 bin_p_valContent = y
                 bin_p_valContent_errP = y+yerr
                 bin_p_valContent_errM = y-yerr
             else :
                 #do a linear extrapolation (equivalent to do Eval(xHist))
                 a=(ybis-y)/(xbis-x)
                 b=y-a*x
                 bin_p_valContent = a*xHist+b
                 #extrapolate the error
                 aerrP = ( (ybis+ybiserr)-(y+yerr) ) / (xbis-x)
                 berrP = (y+yerr)-aerrP*x
                 bin_p_valContent_errP = aerrP*xHist+berrP
                 aerrM = ( (ybis-ybiserr)-(y-yerr) ) / (xbis-x)
                 berrM = (y-yerr)-aerrM*x
                 bin_p_valContent_errM = aerrM*xHist+berrM
             #fill val hist
             histVal.SetBinContent(bin_p,bin_p_valContent)
             histVal.SetBinError(bin_p,(bin_p_valContent_errP-bin_p_valContent_errM)/2)
             #loop over the reference TGraph to get the corresponding point
             for pRef in range(0,hRef[g_i].GetN()):
                 #get point pRef
                 xRef = Double(0)
                 yRef = Double(0)
                 hRef[g_i].GetPoint(pRef,xRef,yRef)
                 #take the first point as xRef < xHist
                 if xRef > xHist : continue
                 xReferr = hRef[g_i].GetErrorX(pRef)
                 yReferr = hRef[g_i].GetErrorY(pRef)
                 #get the other point as xHist in [xRef,xRefbis]
                 xRefbis = Double(0)
                 yRefbis = Double(0)
                 xRefbiserr = hRef[g_i].GetErrorX(pRef+1)
                 yRefbiserr = hRef[g_i].GetErrorY(pRef+1)
                 hRef[g_i].GetPoint(pRef+1,xRefbis,yRefbis)
                 if yRefbis==yRef :
                     #just take yRef at xRef
                     bin_p_refContent = yRef
                     bin_p_refContent_errP = yRef+yReferr
                     bin_p_refContent_errM = yRef-yReferr
                 else :
                     #do a linear extrapolation (equivalent to do Eval(xHist))
                     aRef=(ybis-y)/(xbis-x)
                     bRef=yRef-aRef*xRef
                     bin_p_refContent = aRef*xHist+bRef
                     #extrapolate the error
                     aReferrP = ((yRefbis+yRefbiserr)-(yRef+yReferr))/((xRefbis)-(xRef))
                     bReferrP = (yRef+yReferr)-aReferrP*(xRef-xReferr)
                     bin_p_refContent_errP = aReferrP*xHist+bReferrP
                     aReferrM = ((yRefbis-yRefbiserr)-(yRef-yReferr))/((xRefbis)-(xRef))
                     bReferrM = (yRef-yReferr)-aReferrM*(xRef+xReferr)
                     bin_p_refContent_errM = aReferrM*xHist+bReferrM
                 break
             #fill ref hist
             histRef.SetBinContent(bin_p,bin_p_refContent)
             histRef.SetBinError(bin_p,(bin_p_refContent_errP-bin_p_refContent_errM)/2)
         #do the ratio
         histVal.Sumw2()
         histRef.Sumw2()
         histVal.Divide(histRef)
         #ratio style
         histVal.GetXaxis().SetRangeUser(0.,1.)
         #histRef.GetXaxis().SetRangeUser(0.,1.)
         histVal.GetYaxis().SetRangeUser(0.25,1.75)
         histVal.SetMarkerColor(hVal[g_i].GetMarkerColor())
         histVal.SetLineColor(hVal[g_i].GetLineColor())
         histVal.GetYaxis().SetLabelSize(0.15)
         histVal.GetXaxis().SetLabelSize(0.15)
         ratio.append(histVal)
     return ratio

def histoStyle.graphProducer	(	plot,
		histos,
		tagFlav = `"B"`,
		mistagFlav = `["C"`,
		DUSG,
		isVal = `True`
	)

Definition at line 239 of file histoStyle.py.

References python.multivaluedict.append(), and bookConverter.max.

 
 def graphProducer(plot,histos,tagFlav="B",mistagFlav=["C","DUSG"],isVal=True):
     if histos is None : return
     if isVal : sample = "Val"
     else : sample = "Ref"
     #define graphs
     g = {}
     g_out = []
     if tagFlav not in listFlavors :
         return
     if plot.tagFlavor and plot.mistagFlavor :
         tagFlav = plot.tagFlavor
         mistagFlav = plot.mistagFlavor
     for f in listFlavors :
         #compute errors, in case not already done
         histos[f].Sumw2()
     #efficiency lists
     Eff = {}
     EffErr = {}
     for f in listFlavors :
         Eff[f] = []
         EffErr[f] = []
     #define mapping points for the histos
     maxnpoints = histos[tagFlav].GetNbinsX()
     for f in listFlavors :
         Eff[f].append(histos[f].GetBinContent(1))
         EffErr[f].append(histos[f].GetBinError(1))
     for bin in range(2,maxnpoints+1) :
         #check if we add the point to the graph for Val sample
         if len(Eff[tagFlav])>0 :
             delta = Eff[tagFlav][-1]-histos[tagFlav].GetBinContent(bin)
             if delta>max(0.005,EffErr[tagFlav][-1]) :
                 #get efficiencies
                 for f in listFlavors :
                     Eff[f].append(histos[f].GetBinContent(bin))
                     EffErr[f].append(histos[f].GetBinError(bin))
     #create TVector
     len_ = len(Eff[tagFlav])
     TVec_Eff = {}
     TVec_EffErr = {}
     for f in listFlavors :
         TVec_Eff[f] = TVectorD(len_)
         TVec_EffErr[f] = TVectorD(len_)
     #Fill the vector
     for j in range(0,len_) :
         for f in listFlavors :
             TVec_Eff[f][j] = Eff[f][j]
             TVec_EffErr[f][j] = EffErr[f][j]
     #fill TGraph
     for mis in mistagFlav :
         g[tagFlav+mis]=TGraphErrors(TVec_Eff[tagFlav],TVec_Eff[mis],TVec_EffErr[tagFlav],TVec_EffErr[mis])
     #style
     for f in listFlavors :
         if f not in mistagFlav : continue
         g[tagFlav+f].SetLineColor(mapColor[f])
         g[tagFlav+f].SetMarkerStyle(mapMarker[sample])
         g[tagFlav+f].SetMarkerColor(mapColor[f])
         g_out.append(g[tagFlav+f])
     index = -1     
     for g_i in g_out :
         index+=1
         if g_i is not None : break
     #Axis
     g_out[index].GetXaxis().SetRangeUser(0,1)
     g_out[index].GetYaxis().SetRangeUser(0.0001,1)
     if plot.Xlabel :
         g_out[index].GetXaxis().SetTitle(plot.Xlabel)
     if plot.Ylabel :
         g_out[index].GetYaxis().SetTitle(plot.Ylabel)
     #add in the list None for element in listFlavors for which no TGraph is computed
     for index,f in enumerate(listFlavors) :
         if f not in mistagFlav : g_out.insert(index,None)
     return g_out   
 
#method to draw the plot and save it

histoStyle.graphProducer

def graphProducer

Definition: histoStyle.py:239

python.multivaluedict.append

def append

Definition: multivaluedict.py:73

bookConverter.max

max

Definition: bookConverter.py:166

def histoStyle.histoProducer	(	plot,
		histos,
		keys,
		isVal = `True`
	)

Definition at line 183 of file histoStyle.py.

References bookConverter.max, and MultipleCompare.Rebin().

 
 def histoProducer(plot,histos,keys,isVal=True):
     if histos is None : return
     if isVal : sample = "Val"
     else : sample = "Ref"
     outhistos = []
     minY=9999.
     maxY=0.
     for k in keys :
         #Binning
         if plot.binning and len(plot.binning)==3 :
             histos[k].SetBins(plot.binning[0],plot.binning[1],plot.binning[2])
         elif plot.binning and len(plot.binning)==2 :
             nbins=plot.binning[1]+1-plot.binning[0]
             xmin=histos[k].GetBinLowEdge(plot.binning[0])
             xmax=histos[k].GetBinLowEdge(plot.binning[1]+1)
             valtmp=TH1F(histos[k].GetName(),histos[k].GetTitle(),nbins,xmin,xmax)
             i=1
             for bin in range(plot.binning[0],plot.binning[1]+1) :
                 valtmp.SetBinContent(i,histos[k].GetBinContent(bin))
                 i+=1
             histos[k]=valtmp
         if plot.Rebin and plot.Rebin > 0 :
             histos[k].Rebin(plot.Rebin)
         #Style
         histos[k].SetLineColor(mapColor[k])
         histos[k].SetMarkerColor(mapColor[k])
         histos[k].SetMarkerStyle(mapMarker[sample])
         if drawOption == "HIST" :
             histos[k].SetLineWidth(mapLineWidth[sample])
             histos[k].SetLineStyle(mapLineStyle[sample])
         #compute errors
         histos[k].Sumw2()
         #do the norm
         if plot.doNormalization :
             histos[k].Scale(1./histos[k].Integral())
         elif weight!=1 :
             histos[k].Scale(weight)
         #get Y min
         if histos[k].GetMinimum(0.) < minY :
             minY = histos[k].GetMinimum(0.)
         #get Y max
         if histos[k].GetBinContent(histos[k].GetMaximumBin()) > maxY :
             maxY = histos[k].GetBinContent(histos[k].GetMaximumBin())+histos[k].GetBinError(histos[k].GetMaximumBin())
         #Axis
         if plot.Xlabel :
             histos[k].SetXTitle(plot.Xlabel)
         if plot.Ylabel :
             histos[k].SetYTitle(plot.Ylabel)
         outhistos.append(histos[k])    
     #Range
     if not plot.logY : outhistos[0].GetYaxis().SetRangeUser(0,1.1*maxY)
     #else : outhistos[0].GetYaxis().SetRangeUser(0.0001,1.05)
     else : outhistos[0].GetYaxis().SetRangeUser(max(0.0001,0.5*minY),1.1*maxY)
     return outhistos        
 
#method to do a plot from a graph

MultipleCompare.Rebin

def Rebin

Definition: MultipleCompare.py:174

bookConverter.max

max

Definition: bookConverter.py:166

histoStyle.histoProducer

def histoProducer

Definition: histoStyle.py:183

def histoStyle.savePlots	(	title,
		saveName,
		listFromats,
		plot,
		Histos,
		keyHisto,
		listLegend,
		options,
		ratios = `None`,
		legendName = `""`
	)

Definition at line 313 of file histoStyle.py.

References ecalTPGAnalyzer_cfg.Print.

 
 def savePlots(title,saveName,listFromats,plot,Histos,keyHisto,listLegend,options,ratios=None,legendName="") :
     #create canvas
     c = {}
     pads = {}
     if options.doRatio :
         c[keyHisto] = TCanvas(saveName,keyHisto+plot.title,700,700+24*len(listFlavors))
         pads["hist"] = TPad("hist", saveName+plot.title,0,0.11*len(listFlavors),1.0,1.0)    
     else :
         c[keyHisto] = TCanvas(keyHisto,saveName+plot.title,700,700)
         pads["hist"] = TPad("hist", saveName+plot.title,0,0.,1.0,1.0)
     pads["hist"].Draw()
     if ratios :
         for r in range(0,len(ratios)) :
             pads["ratio_"+str(r)] = TPad("ratio_"+str(r), saveName+plot.title+str(r),0,0.11*r,1.0,0.11*(r+1))
             pads["ratio_"+str(r)].Draw()
     pads["hist"].cd()
     #canvas style                                                                                                                                                                          
     if plot.logY : pads["hist"].SetLogy()
     if plot.grid : pads["hist"].SetGrid()
     #legend                                                                                                                                                                                
     leg = TLegend(0.6,0.4,0.8,0.6)
     leg.SetMargin(0.12)
     leg.SetTextSize(0.035)
     leg.SetFillColor(10)
     leg.SetBorderSize(0)
     #draw histos                                                                                                                                                                           
     first = True
     option = drawOption
     optionSame = drawOption+"same"
     if plot.doPerformance :
         option = "AP"
         optionSame = "sameP"
     for i in range(0,len(Histos)) :
         if Histos[i] is None : continue
         if first :
             if not plot.doPerformance : Histos[i].GetPainter().PaintStat(ROOT.gStyle.GetOptStat(),0)
             Histos[i].SetTitle(title)
             Histos[i].Draw(option)
             first = False
         else : Histos[i].Draw(optionSame)
         #Fill legend                                                                                                                                                                       
         if plot.legend and len(Histos)%len(listLegend)==0:
             r=len(Histos)/len(listLegend)
             index=i-r*len(listLegend)
             while(index<0):
                 index+=len(listLegend)
             legName = legendName.replace("KEY",listLegend[index])
             if i<len(listLegend) : legName = legName.replace("isVAL",options.ValRel)
             else : legName = legName.replace("isVAL",options.RefRel)
             if drawOption=="HIST" :
                 leg.AddEntry(Histos[i],legName,"L")
             else :
                 leg.AddEntry(Histos[i],legName,"P")
     #Draw legend                                                                                                                                                                           
     if plot.legend and options.drawLegend : leg.Draw("same")
     tex = None
     if options.printBanner :
         print type(options.printBanner)
         tex = TLatex(0.55,0.75,options.Banner)
         tex.SetNDC()
         tex.SetTextSize(0.05)
         tex.Draw()
     #save canvas
     if ratios :
         for r in range(0,len(ratios)) :
             pads["ratio_"+str(r)].cd()
             if ratios[r] is None : continue
             pads["ratio_"+str(r)].SetGrid()
             ratios[r].GetYaxis().SetTitle(listLegend[r]+"-jets")
             ratios[r].GetYaxis().SetTitleSize(0.15)
             ratios[r].GetYaxis().SetTitleOffset(0.2)
             ratios[r].GetYaxis().SetNdivisions(3,3,2)
             ratios[r].Draw("")
             unity.Draw("same")
     for format in listFromats :
         save = saveName+"."+format
         c[keyHisto].Print(save)
     return [c,leg,tex,pads]    
#to create ratio plots from histograms

histoStyle.savePlots

def savePlots

Definition: histoStyle.py:313

ecalTPGAnalyzer_cfg.Print

tuple Print

Definition: ecalTPGAnalyzer_cfg.py:144

Variable Documentation

string histoStyle.Banner = "CMS Preliminary"

Definition at line 53 of file histoStyle.py.

histoStyle.batch = False

Definition at line 49 of file histoStyle.py.

histoStyle.doRatio = True

Definition at line 54 of file histoStyle.py.

histoStyle.drawLegend = False

Definition at line 51 of file histoStyle.py.

string histoStyle.drawOption = ""

Definition at line 55 of file histoStyle.py.

Referenced by drawHistograms(), and TauDQMHistPlotter.endRun().

list histoStyle.EtaPtBin

Initial value:

 = [
     "GLOBAL",
     #"ETA_0-1v4",
     #"ETA_1v4-2v4",
     #"PT_50-80",
     #"PT_80-120",
     ]

Definition at line 59 of file histoStyle.py.

Referenced by BTagPerformanceHarvester.getEtaPtBin(), BTagPerformanceAnalyzerOnData.getEtaPtBin(), and BTagPerformanceAnalyzerMC.getEtaPtBin().

string histoStyle.fileNameRef = "BTagRelVal_TTbar_Startup_612SLHC1_14.root"

Definition at line 41 of file histoStyle.py.

string histoStyle.fileNameVal = "BTagRelVal_TTbar_Startup_14_612SLHC2.root"

Definition at line 40 of file histoStyle.py.

list histoStyle.listFlavors

Initial value:

 = [
         #"ALL",
         "B",
         "C",
         #"G",
         #"DUS",
         "DUSG",
         #"NI",
         ]

Definition at line 82 of file histoStyle.py.

list histoStyle.listFromats

Initial value:

 = [
     "gif",
     ]

Definition at line 126 of file histoStyle.py.

list histoStyle.listHistos

Definition at line 135 of file histoStyle.py.

list histoStyle.listTag

Initial value:

 = [
     "CSV",
     "CSVMVA",
     "JP",
     "JBP",
     "TCHE",
     "TCHP",
     "SSVHE",
     "SSVHP",
     "SMT",
     #"SMTIP3d",
     #"SMTPt",
     "SET",
     ]

Definition at line 67 of file histoStyle.py.

dictionary histoStyle.mapColor

Initial value:

 = {
     "ALL"  : 4 ,
     "B"    : 3 ,
     "C"    : 1 ,
     "G"    : 2 ,
     "DUS"  : 2 ,
     "DUSG" : 2 ,
     "NI"   : 5 ,
     "CSV"       : 5 ,
     "CSVMVA"   : 6 ,
     "JP"        : 3 ,
     "JBP"       : 9 ,
     "TCHE"      : 1,
     "TCHP"      : 2,
     "SSVHE"     : 4,
     "SSVHP"     : 7,
     "SMT"       : 8 ,
     "SMTIP3d" : 11 ,
     "SMTPt"   : 12
     }

Definition at line 92 of file histoStyle.py.

dictionary histoStyle.mapLineStyle

Initial value:

 = {
     "Val" : 2,
     "Ref" : 1
     }

Definition at line 121 of file histoStyle.py.

dictionary histoStyle.mapLineWidth

Initial value:

 = {
     "Val" : 3,
     "Ref" : 2
     }

Definition at line 117 of file histoStyle.py.

dictionary histoStyle.mapMarker

Initial value:

 = {
     "Val" : 22,
     "Ref" :  8
     }

Definition at line 113 of file histoStyle.py.

string histoStyle.pathInFile = "/DQMData/Run 1/Btag/Run summary/"

Definition at line 57 of file histoStyle.py.

histoStyle.printBanner = False

Definition at line 52 of file histoStyle.py.

string histoStyle.RefRel = "612SLHC1_14"

Definition at line 44 of file histoStyle.py.

string histoStyle.RefSample = "TTbar_FullSim"

Definition at line 47 of file histoStyle.py.

tuple histoStyle.unity = TF1("unity","1",-1000,1000)

Definition at line 130 of file histoStyle.py.

string histoStyle.ValRel = "612SLHC2_14"

Definition at line 43 of file histoStyle.py.

string histoStyle.ValSample = "TTbar_FullSim"

Definition at line 46 of file histoStyle.py.

int histoStyle.weight = 1

Definition at line 50 of file histoStyle.py.

Referenced by PhysicsTools::LeastSquares.add(), KalmanVertexUpdator< N >.add(), reco::TrackKinematics.add(), lhef::LHERunInfo::Counter.add(), MuonTruth.addChannel(), RPCRawDataCounts.addDccRecord(), Accumulator.addEntry(), CaloValidationStatistics.addEntry(), MultiTrajectoryStateAssembler.addInvalidState(), TtFullLepKinSolver.addKinSolInfo(), addMeas(), MuonDT13ChamberResidual.addResidual(), MuonCSCChamberResidual.addResidual(), MuonDT2ChamberResidual.addResidual(), CSCPairResidualsConstraint.addTrack(), FedCablingAlgorithm.analyse(), EWKSystUnc.analyze(), ZLONLOHistogrammer.analyze(), zPdfUnc.analyze(), ZMCHistogrammer.analyze(), JetAnaPythia< Jet >.analyze(), GenMuonRadCorrAnalyzer.analyze(), HistoAnalyzer< C >.analyze(), BTagPerformanceAnalyzerMC.analyze(), MuonTruth.analyze(), TtSemiLepSignalSelMVATrainer.analyze(), EmbeddingKineReweightNtupleProducer.analyze(), WValidation.analyze(), BasicHepMCHeavyIonValidation.analyze(), BasicHepMCValidation.analyze(), DrellYanValidation.analyze(), BasicGenParticleValidation.analyze(), MBUEandQCDValidation.analyze(), HiggsValidation.analyze(), DuplicationChecker.analyze(), AnotherPrimaryVertexAnalyzer.analyze(), TauValidation.analyze(), MCVerticesAnalyzer.analyze(), Rivet::CMS_2013_I1224539_DIJET.analyze(), FSQDiJetAve.analyze(), MCvsRecoVerticesAnalyzer.analyze(), EgHLTOfflineSource.analyze(), IsolatedTracksNxN.analyze(), MCEmbeddingValidationAnalyzer.analyze(), RegressionHelper.applyCombinationRegression(), areaInfo.areaInfo(), GsfVertexUpdator.assembleVertexComponents(), CaloTowersCreationAlgo.assignHitEcal(), CaloTowersCreationAlgo.assignHitHcal(), reco::tau::RecoTauVertexAssociator.associatedVertex(), JetAnaPythia< Jet >.beginJob(), BremsstrahlungSimulator.brem(), GsfVertexWeightCalculator.calculate(), ClusterShapeAlgo.Calculate_EnergyDepTopology(), PositionCalc.Calculate_Location(), ECAL2DPositionCalcWithDepthCorr.calculateAndSetPositionActual(), TBPositionCalc.CalculateCMSPos(), QGTagger.calcVariables(), XHistogram.check_weight(), DAFTrackProducerAlgorithm.checkHits(), MultiGaussianStateCombiner1D.combine(), EpCombinationTool.combine(), PairProductionSimulator.compute(), CandIsolatorFromDeposits::SingleDeposit.compute(), PFCandIsolatorFromDeposits::SingleDeposit.compute(), MuScleFitUtils.computeWeight(), EcalTPGParamBuilder.computeWeights(), MassWindow.count(), FSQ::HandlerTemplate< TInputCandidateType, TOutputCandidateType, filter >.count(), BackgroundHandler.countEventsInAllWindows(), MultiVertexFitter.createSeed(), DreamSD.curve_LY(), HcalTB02SD.curve_LY(), ECalSD.curve_LY(), SignedImpactParameter3D.distanceWithJetAxis(), HWWFunctions.doCutFlow(), CSCOfflineMonitor.doEfficiencies(), CSCValidation.doEfficiencies(), PhysicsTools::TrainProcessor.doTrainData(), DTCertificationSummary.dqmEndJob(), DTResolutionAnalysisTest.dqmEndJob(), DTRunConditionVarClient.dqmEndJob(), MuScleFit.duringFastLoop(), CalorimetryManager.EMShowerSimulation(), CaloTowersCreationAlgo.emShwrLogWeightPos(), lhef::LHEReader::XMLHandler.endElement(), AdaptiveVertexReconstructor.erase(), evaluateTtFullHadSignalSel(), evaluateTtSemiLepSignalSel(), VertexHistogramMaker.fill(), ConfigurableHisto.fill(), HParticle.Fill(), HPartVSEta.Fill(), HPartVSPhi.Fill(), HPartVSPt.Fill(), HMassVSPart.Fill(), HMassVSPartProfile.Fill(), HcalDigisClient.fill1D(), HcalDigisClient.fill2D(), SiPixelDataQuality.fillGlobalQualityPlot(), HLXMonitor.FillHistograms(), MCEmbeddingValidationAnalyzer::plotEntryTypeEvtWeight.fillHistograms(), SVTagInfoValidationAnalyzer.fillRecoToSim(), recoBSVTagInfoValidationAnalyzer.fillRecoToSim(), recoBSVTagInfoValidationAnalyzer.fillSimToReco(), SVTagInfoValidationAnalyzer.fillSimToReco(), HepMCFilterDriver.filter(), TauSpinnerFilter.filter(), MCVerticesWeight.filter(), reco::PositiveSideGhostTrackFitter.fit(), MuonResiduals1DOFFitter.fit(), PFDisplacedVertexFinder.fitVertexFromSeed(), gen::Hydjet2Hadronizer.generatePartonsAndHadronize(), CaloSD.getAttenuation(), ECalSD.getBirkL3(), EcalTBH4BeamSD.getEnergyDeposit(), HcalTB06BeamSD.getEnergyDeposit(), ECalSD.getEnergyDeposit(), HcalTB02SD.getEnergyDeposit(), HCalSD.getEnergyDeposit(), EcalClusterToolsT< noZS >.getEnergyDepTopology(), FSQ::HandlerTemplate< TInputCandidateType, TOutputCandidateType, filter >.getFilteredCands(), HFShowerParam.getHits(), GsfBetheHeitlerUpdator.getMixtureParameters(), Qjets.GetNextDistance(), TtFullLepKinSolver.getNuSolution(), DreamSD.getStepInfo(), CaloMeanResponse.getWeight(), AdaptiveVertexFitter.getWeight(), tnp::BaseTreeFiller.init(), reco::GhostTrack.initStates(), CSCPairResidualsConstraint.isFiducial(), IPTools.jetTrackDistance(), likelihood(), VoronoiAlgorithm.lp_populate(), reco::PFDisplacedVertexSeed.mergeWith(), EGExtraInfoModifierFromDB.modifyObject(), MuonResiduals1DOFFitter_FCN(), MuonResiduals5DOFFitter_FCN(), MuonResiduals6DOFFitter_FCN(), MuonResiduals6DOFrphiFitter_FCN(), SmsModeFinder3d.operator()(), MtvClusterizer1D< T >.operator()(), FsmwClusterizer1D< T >.operator()(), FsmwModeFinder3d.operator()(), npstat::LinInterpolatedTableND< Numeric, Axis >.operator()(), DTSegmentAnalysisTest.performClientDiagnostic(), TauValidation.photons(), MuonResiduals1DOFFitter.plot(), MuonResiduals5DOFFitter.plot(), MuonResiduals6DOFFitter.plot(), MuonResiduals6DOFrphiFitter.plot(), MuonResidualsFitter.plotweighted(), RandArrayFunction.PrepareTable(), PrescaleWeightProvider.prescaleWeight(), PrintMaterialBudgetInfo.printInfo(), HCalSD.ProcessHits(), WeakEffectsWeightProducer.produce(), ISRGammaWeightProducer.produce(), FSRWeightProducer.produce(), ISRWeightProducer.produce(), LHECOMWeightProducer.produce(), ZmumuEvtSelEffCorrWeightProducer.produce(), edm::BeamHaloProducer.produce(), EmbeddingKineReweightProducer.produce(), MuonRadiationCorrWeightProducer.produce(), GenFilterEfficiencyProducer.produce(), FastPrimaryVertexWithWeightsProducer.produce(), EcalTBWeightsXMLTranslator.readWeightSet(), EcalWeightSetXMLTranslator.readXML(), FastHFShowerLibrary.recoHFShowerLibrary(), KalmanVertexUpdator< N >.remove(), CaloTowersCreationAlgo.rescale(), CaloTowersCreationAlgo.rescaleTowers(), BtoCharmDecayVertexMerger.resolveBtoDchain(), AdaptiveVertexFitter.reWeightTracks(), EcalClusterToolsT< noZS >.roundnessSelectedBarrelRecHits(), PhysicsTools::MLP.set(), UpdateTProfile.setBinContent(), FWGUIManager.setFrom(), tauImpactParameter::LagrangeMultipliersFitter.setWeight(), Histograms.SetWeight(), PFCandIsolatorFromDeposits::SingleDeposit.SingleDeposit(), CandIsolatorFromDeposits::SingleDeposit.SingleDeposit(), TauValidation.spinEffectsWHpm(), TauValidation.spinEffectsZH(), sistrip::MeasureLA.summarize_module_muH_byLayer(), TBposition(), hcalCalib.Terminate(), PF_PU_AssoMapAlgos.TrackWeightAssociation(), EcalTPGParamBuilder.uncodeWeight(), KalmanVertexUpdator< N >.update(), CommissioningTask.updateHistoSet(), reco::PFDisplacedVertexSeed.updateSeedPoint(), GsfMaterialEffectsUpdator.updateState(), MultiVertexFitter.updateWeights(), VertexTrackFactory< 6 >.vertexTrack(), vtxMean(), TtFullLepKinSolver.WeightSolfromMC(), AdaptiveVertexFitter.weightTracks(), and MuonResidualsTwoBin.wmean().