diff --git a/Validation/RecoB/scripts/histoStyle.py b/Validation/RecoB/scripts/histoStyle.py
new file mode 100644
index 0000000000000..7d3c4dd2922aa
--- /dev/null
+++ b/Validation/RecoB/scripts/histoStyle.py
@@ -0,0 +1,509 @@
+
+####### 
+
+#  automatized plots generator for b-tagging performances
+#  Adrien Caudron, 2013, UCL
+
+#######
+
+#do all import
+import os, sys
+
+try:
+    import ROOT
+except:
+    print "\nCannot load PYROOT, make sure you have setup ROOT in the path"
+    print "and pyroot library is also defined in the variable PYTHONPATH, try:\n"
+    if (os.getenv("PYTHONPATH")):
+        print " setenv PYTHONPATH ${PYTHONPATH}:$ROOTSYS/lib\n"
+    else:
+        print " setenv PYTHONPATH $ROOTSYS/lib\n"
+        sys.exit()
+
+from ROOT import TFile
+from ROOT import TCanvas
+from ROOT import TPad
+from ROOT import TLegend
+from ROOT import TLatex
+from ROOT import TH1F
+from ROOT import TF1
+from ROOT import TVectorD
+from ROOT import TGraphErrors
+from ROOT import Double
+
+import Style
+from listHistos import *
+
+#define the input root files
+#fileVal = TFile("BTagRelVal_TTbar_Startup_14_612SLHC2.root","READ")
+#fileRef = TFile("BTagRelVal_TTbar_Startup_612SLHC1_14.root","READ")
+fileNameVal = "BTagRelVal_TTbar_Startup_14_612SLHC2.root"
+fileNameRef = "BTagRelVal_TTbar_Startup_612SLHC1_14.root"
+#define the val/ref labels
+ValRel = "612SLHC2_14"
+RefRel = "612SLHC1_14"
+#define the sample labels
+ValSample = "TTbar_FullSim"
+RefSample = "TTbar_FullSim"
+#define different settings
+batch = False #run on batch mode ?
+weight = 1. #rescale the histos according to this weight
+drawLegend = False #draw legend ?
+printBanner = False #draw text Banner on top of the histos
+Banner = "CMS Preliminary"
+doRatio = True #plot the ratios
+drawOption = "" # "" or "HIST"
+#path in the file
+pathInFile = "/DQMData/Run 1/Btag/Run summary/"
+#ETA/PT bins, GLOBAL ?
+EtaPtBin =[
+    "GLOBAL",
+    #"ETA_0-1v4",
+    #"ETA_1v4-2v4",
+    #"PT_50-80",
+    #"PT_80-120",
+    ]
+#list of taggers to look at
+listTag = [
+    "CSV",
+    "CSVMVA",
+    "JP",
+    "JBP",
+    "TCHE",
+    "TCHP",
+    "SSVHE",
+    "SSVHP",
+    "SMT",
+    #"SMTIP3d",
+    #"SMTPt",
+    "SET",
+    ]
+#list of flavors to look at
+listFlavors = [
+        #"ALL",
+        "B",
+        "C",
+        #"G",
+        #"DUS",
+        "DUSG",
+        #"NI",
+        ]
+#map for marker color for flav-col and tag-col
+mapColor = {
+    "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
+    }
+#marker style map for Val/Ref
+mapMarker = {
+    "Val" : 22,
+    "Ref" :  8
+    }
+mapLineWidth = {
+    "Val" : 3,
+    "Ref" : 2
+    }
+mapLineStyle = {
+    "Val" : 2,
+    "Ref" : 1
+    }
+#choose the formats to save the plots 
+listFromats = [
+    "gif",
+    ]
+#unity function
+unity = TF1("unity","1",-1000,1000)
+unity.SetLineColor(8)
+unity.SetLineWidth(1)
+unity.SetLineStyle(1)
+#list of histos to plots
+listHistos = [
+    jetPt,
+    jetEta,
+    discr,
+    effVsDiscrCut_discr,
+    FlavEffVsBEff_discr,
+    performance,
+    #performanceC,
+
+    #IP,
+    #IPe,
+    #IPs,
+    #NTracks,
+    #decayLength,
+    #distToJetAxis,
+    #NHits,
+    #NPixelHits,
+    #NormChi2,
+    #trackPt,
+
+
+    #flightDist3Dval,
+    #flightDist3Dsig,
+    #jetNSecondaryVertices,
+    
+    #vertexMass,
+    #vertexNTracks,
+    #vertexJetDeltaR,
+    #vertexEnergyRatio,
+
+    #vertexCategory,
+    #trackSip3dVal,
+    #trackSip3dSig,
+    #trackSip3dSigAboveCharm,
+    #trackDeltaR,
+    #trackEtaRel,
+    #trackDecayLenVal,
+    #trackSumJetDeltaR,
+    #trackJetDist,
+    #trackSumJetEtRatio,
+    #trackPtRel,
+    #trackPtRatio,
+    #trackMomentum,
+    #trackPPar,
+    #trackPParRatio,
+    ]
+
+#methode to do a plot from histos       
+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
+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
+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
+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
+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
diff --git a/Validation/RecoB/scripts/listHistos.py b/Validation/RecoB/scripts/listHistos.py
new file mode 100644
index 0000000000000..a05204bdd92a2
--- /dev/null
+++ b/Validation/RecoB/scripts/listHistos.py
@@ -0,0 +1,237 @@
+
+####### 
+
+#  automatized plots generator for b-tagging performances
+#  Adrien Caudron, 2013, UCL
+
+#######
+
+class plotInfo :
+    def __init__ (self, name, title, #mandatory
+                  legend="", Xlabel="", Ylabel="", logY=False, grid=False,
+                  binning=None, Rebin=None,
+                  doNormalization=False,
+                  listTagger=None,
+                  doPerformance=False, tagFlavor="B", mistagFlavor=["C","DUSG"]):
+        self.name = name #name of the histos without postfix as PT/ETA bin or flavor
+        self.title = title #title of the histograms : better if specific for the histogram
+        self.legend = legend #legend name, if contain 'KEY', it will be replace by the list of keys you provide (as flavor, tagger ...)
+        self.Xlabel = Xlabel #label of the X axis
+        self.Ylabel = Ylabel #label of the Y axis
+        self.logY = logY #if True : Y axis will be in log scale
+        self.grid = grid #if True : a grid will be drawn
+        self.binning = binning #if you want to change the binning put a list with [nBins,xmin,xmax]
+        self.Rebin = Rebin #if you want to rebin the histos
+        self.doNormalization = doNormalization #if you want to normalize to 1 all the histos 
+        self.doPerformance = doPerformance #if you want to draw the performance as TGraph
+        if self.doPerformance : 
+            #replace TAG by the tag flavor choosen (B, C, UDSG ...)
+            self.title = name.replace("TAG",tagFlavor)
+            self.Xlabel = Xlabel.replace("TAG",tagFlavor)
+            self.Ylabel = Ylabel.replace("TAG",tagFlavor)
+            self.legend = legend.replace("TAG",tagFlavor)
+            self.tagFlavor = tagFlavor
+            self.mistagFlavor = mistagFlavor
+        if listTagger is None :
+            self.listTagger=None #you will take the list of tagger defined centrally
+        else :
+            self.listTagger=listTagger #you take the list passed as argument
+#define here the histograms you interested by
+#by jets
+jetPt = plotInfo(name="jetPt", title="Pt of all jets", legend="isVAL KEY-jets", Xlabel="Pt (GeV/c)", Ylabel="abitrary units",
+                 logY=False, grid=False,
+                 binning=[300,10.,310.], Rebin=20, doNormalization=True,
+                 listTagger=["CSV"]
+                 )
+jetEta = plotInfo(name="jetEta", title="Eta of all jets", legend="isVAL KEY-jets", Xlabel="#eta", Ylabel="abitrary units",
+                  logY=False, grid=False,
+                  binning=[11,90], Rebin=4, doNormalization=True,
+                  listTagger=["CSV"]
+                  )
+discr = plotInfo(name="discr", title="Discriminant of all jets", legend="isVAL KEY-jets", Xlabel="Discriminant", Ylabel="abitrary units",
+                 logY=False, grid=False,
+                 binning=None, Rebin=None, doNormalization=True
+                 )
+effVsDiscrCut_discr = plotInfo(name="effVsDiscrCut_discr", title="Efficiency versus discriminant cut for all jets", legend="isVAL KEY-jets", Xlabel="Discriminant", Ylabel="efficiency",
+                               logY=True, grid=True
+                               )
+#MC only
+FlavEffVsBEff_discr = plotInfo(name="FlavEffVsBEff_B_discr", title="b-tag efficiency versus non b-tag efficiency", 
+                               legend="KEY FLAV-jets versus b-jets", Xlabel="b-tag efficiency", Ylabel="non b-tag efficiency",
+                               logY=True, grid=True
+                               )
+#MC only
+performance = plotInfo(name="effVsDiscrCut_discr", title="TAG-tag efficiency versus non TAG-tag efficiency", 
+                       legend="isVAL KEY-jets versus TAG-jets", Xlabel="TAG-tag efficiency", Ylabel="non TAG-tag efficiency",
+                       logY=True, grid=True, 
+                       doPerformance=True, tagFlavor="B", mistagFlavor=["C","DUSG"]
+                       )
+#MC only, to do C vs B and C vs light
+performanceC = plotInfo(name="effVsDiscrCut_discr", title="TAG-tag efficiency versus non TAG-tag efficiency", 
+                       legend="isVAL KEY-jets versus TAG-jets", Xlabel="TAG-tag efficiency", Ylabel="non TAG-tag efficiency",
+                       logY=True, grid=True, 
+                       doPerformance=True, tagFlavor="C", mistagFlavor=["B","DUSG"]
+                       )
+#by tracks
+IP = plotInfo(name="ip_3D", title="Impact parameter", legend="isVAL KEY-jets", Xlabel="IP [cm]", Ylabel="abitrary units",
+              logY=False, grid=False,
+              binning=None,Rebin=None, doNormalization=True,
+              listTagger=["IPTag"]
+              )
+IPe = plotInfo(name="ipe_3D", title="Impact parameter error", legend="isVAL KEY-jets", Xlabel="IPE [cm]", Ylabel="abitrary units",
+               logY=False, grid=False, 
+               binning=None, Rebin=None, doNormalization=True,
+               listTagger=["IPTag"]
+               )
+IPs = plotInfo(name="ips_3D", title="Impact parameter significance", legend="isVAL KEY-jets", Xlabel="IPS", Ylabel="abitrary units", 
+               logY=False, grid=False, 
+               binning=None, Rebin=None, doNormalization=True,
+               listTagger=["IPTag"]
+               )
+NTracks = plotInfo(name="selTrksNbr_3D", title="number of selected tracks", legend="isVAL KEY-jets", Xlabel="number of selected tracks", Ylabel="abitrary units",
+                   logY=False, grid=False,
+                   binning=None, Rebin=None, doNormalization=True,
+                   listTagger=["IPTag"]
+                   )
+distToJetAxis = plotInfo(name="jetDist_3D", title="track distance to the jet axis", legend="isVAL KEY-jets", Xlabel="distance to the jet axis [cm]", Ylabel="abitrary units",
+                         logY=False, grid=False,
+                         binning=None, Rebin=None, doNormalization=True, 
+                         listTagger=["IPTag"]
+                         )
+decayLength = plotInfo(name="decLen_3D", title="track decay length", legend="isVAL KEY-jets", Xlabel="decay length [cm]", Ylabel="abitrary units",
+                       logY=False, grid=False,
+                       binning=None, Rebin=None, doNormalization=True, listTagger=["IPTag"]
+                       )
+NHits = plotInfo(name="tkNHits_3D", title="Number of Hits / selected tracks", legend="isVAL KEY-jets", Xlabel="Number of Hits", Ylabel="abitrary units",
+                 logY=False, grid=False,
+                 binning=None, Rebin=None, doNormalization=True,
+                 listTagger=["IPTag"]
+                 )
+NPixelHits = plotInfo(name="tkNPixelHits_3D", title="Number of Pixel Hits / selected tracks", legend="isVAL KEY-jets", Xlabel="Number of Pixel Hits", Ylabel="abitrary units",
+                      logY=False, grid=False, 
+                      binning=None, Rebin=None, doNormalization=True,
+                      listTagger=["IPTag"]
+                      )
+NormChi2 = plotInfo(name="tkNChiSqr_3D", title="Normalized Chi2", legend="isVAL KEY-jets", Xlabel="Normilized Chi2", Ylabel="abitrary units",
+                    logY=False, grid=False,
+                    binning=None, Rebin=None, doNormalization=True,
+                    listTagger=["IPTag"]
+                    )
+trackPt = plotInfo(name="tkPt_3D", title="track Pt", legend="isVAL KEY-jets", Xlabel="track Pt", Ylabel="abitrary units",
+                   logY=False, grid=False,
+                   binning=None, Rebin=None, doNormalization=True,
+                   listTagger=["IPTag"]
+                   )
+#by SV and for CSV information
+flightDist3Dval = plotInfo(name="flightDistance3dVal", title="3D flight distance value", legend="isVAL KEY-jets", Xlabel="3D flight distance value [cm]", Ylabel="abitrary units",
+                           logY=False, grid=False,
+                           binning=None, Rebin=None, doNormalization=True,
+                           listTagger=["CSVTag"]
+                           )
+flightDist3Dsig = plotInfo(name="flightDistance3dSig", title="3D flight distance significance", legend="isVAL KEY-jets", Xlabel="3D flight distance significance", Ylabel="abitrary units",
+                           logY=False, grid=False,
+                           binning=None, Rebin=None, doNormalization=True,
+                           listTagger=["CSVTag"]
+                           )
+jetNSecondaryVertices = plotInfo(name="jetNSecondaryVertices", title="Number of SV / jet", legend="isVAL KEY-jets", Xlabel="Number of SV / jet", Ylabel="abitrary units",
+                           logY=False, grid=False,
+                           binning=None, Rebin=None, doNormalization=True,
+                           listTagger=["CSVTag"]
+                           )
+#Reco and pseudo vertex information
+vertexMass = plotInfo(name="vertexMass", title="vertex mass", legend="isVAL KEY-jets", Xlabel="vertex mass GeV/c^2", Ylabel="abitrary units",
+                      logY=False, grid=False,
+                      binning=None, Rebin=None, doNormalization=True,
+                      listTagger=["CSVTag"]
+                      )
+vertexNTracks = plotInfo(name="vertexNTracks", title="number of tracks at SV", legend="isVAL KEY-jets", Xlabel="number of tracks at SV", Ylabel="abitrary units",
+                      logY=False, grid=False,
+                      binning=None, Rebin=None, doNormalization=True,
+                      listTagger=["CSVTag"]
+                      )
+vertexJetDeltaR = plotInfo(name="vertexJetDeltaR", title="Delta R between the SV and the jet axis", legend="isVAL KEY-jets", Xlabel="Delta R between the SV and the jet axis", Ylabel="abitrary units",
+                      logY=False, grid=False,
+                      binning=None, Rebin=None, doNormalization=True,
+                      listTagger=["CSVTag"]
+                      )
+vertexEnergyRatio = plotInfo(name="vertexEnergyRatio", title="Energy Ratio between SV and the jet", legend="isVAL KEY-jets", Xlabel="Energy Ratio between SV and the jet", Ylabel="abitrary units",
+                      logY=False, grid=False,
+                      binning=None, Rebin=None, doNormalization=True,
+                      listTagger=["CSVTag"]
+                      )
+#Reco, pseudo and no vertex information
+vertexCategory = plotInfo(name="vertexCategory", title="Reco, Pseudo, No vertex", legend="isVAL KEY-jets", Xlabel="Reco, Pseudo, No vertex", Ylabel="abitrary units",
+                          logY=False, grid=False,
+                          binning=None, Rebin=None, doNormalization=True,
+                          listTagger=["CSVTag"]
+                          )
+trackSip3dVal = plotInfo(name="trackSip3dVal", title="track IP 3D", legend="isVAL KEY-jets", Xlabel="track IP 3D [cm]", Ylabel="abitrary units",
+                         logY=False, grid=False,
+                         binning=None, Rebin=None, doNormalization=True,
+                         listTagger=["CSVTag"]
+                         )
+trackSip3dSig = plotInfo(name="trackSip3dSig", title="track IPS 3D", legend="isVAL KEY-jets", Xlabel="track IPS 3D", Ylabel="abitrary units",
+                         logY=False, grid=False,
+                         binning=None, Rebin=None, doNormalization=True,
+                         listTagger=["CSVTag"]
+                         )
+trackSip3dSigAboveCharm = plotInfo(name="trackSip3dSigAboveCharm", title="first track IPS 3D lifting SV mass above charm", legend="isVAL KEY-jets", Xlabel="first track IPS 3D lifting SV mass above charm", Ylabel="abitrary units",
+                                   logY=False, grid=False,
+                                   binning=None, Rebin=None, doNormalization=True,
+                                   listTagger=["CSVTag"]
+                                   )
+trackDeltaR = plotInfo(name="trackDeltaR", title="Delta R between the track and the jet axis", legend="isVAL KEY-jets", Xlabel="DeltaR(track,jet axis)", Ylabel="abitrary units",
+                       logY=False, grid=False,
+                       binning=None, Rebin=None, doNormalization=True,
+                       listTagger=["CSVTag"]
+                       )
+trackEtaRel = plotInfo(name="trackEtaRel", title="track eta relative to the jet axis", legend="isVAL KEY-jets", Xlabel="track eta relative to the jet axis", Ylabel="abitrary units",
+                       logY=False, grid=False,
+                       binning=None, Rebin=None, doNormalization=True,
+                       listTagger=["CSVTag"]
+                       )
+trackDecayLenVal = plotInfo(name="trackDecayLenVal", title="track decay length", legend="isVAL KEY-jets", Xlabel="track decay length", Ylabel="abitrary units",
+                            logY=False, grid=False,
+                            binning=None, Rebin=None, doNormalization=True,
+                            listTagger=["CSVTag"]
+                            )
+trackSumJetDeltaR = plotInfo(name="trackSumJetDeltaR", title="Delta R between track 4-vector sum and jet axis", legend="isVAL KEY-jets", Xlabel="Delta R between track 4-vector sum and jet axis", Ylabel="abitrary units",
+                             logY=False, grid=False,
+                             binning=None, Rebin=None, doNormalization=True,
+                             listTagger=["CSVTag"]
+                             )
+trackJetDist = plotInfo(name="trackJetDist", title="track distance to jet axis", legend="isVAL KEY-jets", Xlabel="track distance to jet axis", Ylabel="abitrary units",
+                        logY=False, grid=False,
+                        binning=None, Rebin=None, doNormalization=True,
+                        listTagger=["CSVTag"]
+                        )
+trackSumJetEtRatio = plotInfo(name="trackSumJetEtRatio", title="track sum Et / jet energy", legend="isVAL KEY-jets", Xlabel="track sum Et / jet energy", Ylabel="abitrary units",
+                              logY=False, grid=False,
+                              binning=None, Rebin=None, doNormalization=True,
+                              listTagger=["CSVTag"]
+                              )
+trackPtRel = plotInfo(name="trackPtRel", title="track Pt relative to jet axis", legend="isVAL KEY-jets", Xlabel="track Pt relative to jet axis", Ylabel="abitrary units",
+                      logY=False, grid=False,
+                      binning=None, Rebin=None, doNormalization=True,
+                      listTagger=["CSVTag"]
+                      )
+trackPtRatio = plotInfo(name="trackPtRatio", title="track Pt relative to jet axis, normalized to its energy", legend="isVAL KEY-jets", Xlabel="track Pt relative to jet axis, normalized to its energy", Ylabel="abitrary units",
+                        logY=False, grid=False,
+                        binning=None, Rebin=None, doNormalization=True,
+                        listTagger=["CSVTag"]
+                        )
+trackMomentum = plotInfo(name="trackMomentum", title="track momentum", legend="isVAL KEY-jets", Xlabel="track momentum [GeV/c]", Ylabel="abitrary units",
+                         logY=False, grid=False,
+                         binning=None, Rebin=None, doNormalization=True,
+                         listTagger=["CSVTag"]
+                         )
+trackPPar = plotInfo(name="trackPPar", title="track parallel momentum along the jet axis", legend="isVAL KEY-jets", Xlabel="track parallel momentum along the jet axis", Ylabel="abitrary units",
+                     logY=False, grid=False,
+                     binning=None, Rebin=None, doNormalization=True,
+                     listTagger=["CSVTag"]
+                     )
+trackPParRatio = plotInfo(name="trackPParRatio", title="track parallel momentum along the jet axis, normalized to its energy", legend="isVAL KEY-jets", Xlabel="track parallel momentum along the jet axis, normalized to its energy", Ylabel="abitrary units",
+                          logY=False, grid=False,
+                          binning=None, Rebin=None, doNormalization=True,
+                          listTagger=["CSVTag"]
+                          )
diff --git a/Validation/RecoB/scripts/plotFactory.py b/Validation/RecoB/scripts/plotFactory.py
new file mode 100755
index 0000000000000..835db3ab1699d
--- /dev/null
+++ b/Validation/RecoB/scripts/plotFactory.py
@@ -0,0 +1,145 @@
+#!/usr/bin/env python
+
+#######
+
+#  automatized plots generator for b-tagging performances
+#  Adrien Caudron, 2013, UCL
+
+#######
+
+#import all what is needed
+from histoStyle import *
+#parser options
+from optparse import OptionParser
+usage="""%prog [options]"""
+description="""A simple script to generate validation plots"""
+epilog="""Example:
+plotFactory.py -f BTagRelVal_TTbar_Startup_600.root -F BTagRelVal_TTbar_Startup_600gspre3.root -r 600 -R 600gspre3 -s TTbar_Startup -S TTbar_Startup 
+"""
+parser = OptionParser(usage=usage,add_help_option=True,description=description,epilog=epilog)
+parser.add_option("-f", "--valInputFile", dest="valPath", default=fileNameVal,
+                  help="Read input file for sample to validated", metavar="VALFILE")
+parser.add_option("-F", "--refInputFile", dest="refPath", default=fileNameRef,
+                  help="Read input file for reference sample", metavar="RAFFILE")
+parser.add_option("-r", "--valReleaseName", dest="ValRel", default=ValRel,
+                  help="Name to refer to the release/conditions to validate, ex: 600, GTV18 ...", metavar="VALREL")
+parser.add_option("-R", "--refReleaseName", dest="RefRel", default=RefRel,
+                  help="Name to refer to the reference release/conditions, ex: 600pre11, GTV16 ...", metavar="REFREL")
+parser.add_option("-s", "--valSampleName", dest="ValSample", default=ValSample,
+                  help="Name to refer to the sample name to validate, ex: TTbar_FullSim, 2012C ...", metavar="VALSAMPLE")
+parser.add_option("-S", "--refSampleName", dest="RefSample", default=RefSample,
+                  help="Name to refer to the reference sample name, ex: TTbar_FullSim, 2012C ...", metavar="REFSAMPLE")
+parser.add_option("-b", "--batch", dest="batch", default=batch,
+                  action="store_true", help="if False, the script will run in batch mode")
+parser.add_option("-l", "--drawLegend", dest="drawLegend", default=drawLegend,
+                  action="store_true", help="if True the legend will be drawn on top of the plots")
+parser.add_option("-p", "--printBanner", dest="printBanner", default=printBanner,
+                  action="store_true", help="if True, a banner will be print on top of the plots")
+parser.add_option("-B", "--Banner", dest="Banner", default=Banner,
+                  help="String to write as banner on top of the plots, option -B should be used")
+parser.add_option("-n", "--noRatio", dest="doRatio", default=doRatio,
+                  action="store_false", help="if True, ratios plots will be created")
+(options, args) = parser.parse_args()
+print "file for validation", options.valPath, "file for reference", options.refPath
+print "Validation release:", options.ValRel, "Reference release:", options.RefRel
+print "Validation sample:", options.ValSample, "Reference sample:", options.RefSample
+print "Options : batch mode ?", options.batch, "draw legend ?", options.drawLegend, "print banner ?", options.printBanner, "banner is ", options.Banner, "make ratio plots ?", options.doRatio
+#define the input root files                                                                                                                                                                              
+if options.valPath and options.refPath :
+    fileVal = TFile(options.valPath,"READ")
+    fileRef = TFile(options.refPath,"READ") 
+#batch mode ?
+if options.batch : ROOT.gROOT.SetBatch()
+# style
+_style = Style.Style()
+_style.SetStyle()
+#title
+if options.ValSample==options.RefSample : title=options.ValRel+"vs"+options.RefRel+" "+options.ValSample+" "
+elif options.ValRel==options.RefRel : title=options.ValRel+" "+options.ValSample+"_vs_"+options.RefSample+" "
+else : title=options.ValRel+"vs"+options.RefRel+" "+options.ValSample+"_vs_"+options.RefSample+" "
+#declaration
+c = {}
+perfAll_Val = {}
+perfAll_Ref = {}
+perfAll_keys = []
+valHistos = {}
+refHistos ={}
+Histos = {}
+ratios = {} 
+#loop over eta an pt bins
+for b in EtaPtBin :
+    #loop over the histos
+    for h in listHistos :
+        for f in listFlavors :
+            perfAll_Val[f] = {}
+            perfAll_Ref[f] = {}
+        #loop over the list of taggers
+        if h.listTagger is None : h.listTagger=listTag
+        for tag in h.listTagger :
+            keyHisto = tag+"_"+h.name+"_"+b
+            if h.doPerformance :
+                keyHisto = tag+"_performance_vs_"+h.tagFlavor
+            #loop over the flavours
+            h_Val = {}
+            h_Ref = {}
+            passH = False
+            for f in listFlavors :
+                path = pathInFile+tag+"_"+b+"/"+h.name+"_"+tag+"_"+b+f
+                if "_B_" in path : 
+                    path=path.replace("_B_","_"+f+"_")
+                    path=path.replace(b+f,b)
+                print path
+                #get histos
+                h_Val[f] = fileVal.Get(path)
+                h_Ref[f] = fileRef.Get(path)
+                if not h_Val[f] :
+                    print "ERROR :", path, "not found in the roofiles, please check the spelling or check if this histogram is present in the rootdile"
+                    passH = True
+            if passH : continue
+            #stop if FlavEffVsBEff_?_discr plot for all the taggers
+            if h.name=="FlavEffVsBEff_B_discr" :
+                for f in listFlavors :
+                    perfAll_Val[f][tag]=h_Val[f]
+                    perfAll_Ref[f][tag]=h_Ref[f]
+                perfAll_keys.append(tag)
+                continue
+            #create final histos   
+            if h.doPerformance :
+                valHistos[keyHisto]=graphProducer(plot=h,histos=h_Val,isVal=True)
+                refHistos[keyHisto]=graphProducer(plot=h,histos=h_Ref,isVal=False)
+            else :    
+                valHistos[keyHisto]=histoProducer(plot=h,histos=h_Val,keys=listFlavors,isVal=True)
+                refHistos[keyHisto]=histoProducer(plot=h,histos=h_Ref,keys=listFlavors,isVal=False)
+            if valHistos[keyHisto] is None or refHistos[keyHisto] is None : continue
+            if len(valHistos[keyHisto])!=len(refHistos[keyHisto]) : print "ERROR"
+            #compute ratios 
+            if options.doRatio :
+                if h.doPerformance:
+                    ratiosList = createRatioFromGraph(valHistos[keyHisto],refHistos[keyHisto])
+                else :
+                    ratiosList = createRatio(valHistos[keyHisto],refHistos[keyHisto])
+                ratios[keyHisto] = ratiosList
+            else :
+                ratiosList = None
+            #set name file
+            if options.ValSample == options.RefSample : saveName=options.ValRel+"vs"+options.RefRel+"_"+options.ValSample+"_Val_"+keyHisto+"_all"
+            elif options.ValRel==options.RefRel : saveName=options.ValRel+"_"+options.ValSample+"_vs_"+options.RefSample+"_Val_"+keyHisto+"_all"
+            else : saveName=options.ValRel+"vs"+options.RefRel+"_"+options.ValSample+"_vs_"+options.RefSample+"_Val_"+keyHisto+"_all"
+            #save canvas
+            c[keyHisto] = savePlots(title=title+tag,saveName=saveName,listFromats=listFromats,plot=h,Histos=valHistos[keyHisto]+refHistos[keyHisto],options=options,ratios=ratiosList,keyHisto=keyHisto,listLegend=listFlavors,legendName=h.legend)
+        #for FlavEffVsBEff_B_discr
+        if h.name=="FlavEffVsBEff_B_discr" :
+            for f in ["C","DUSG"] :
+                for isVal in [True,False] :
+                    keyHisto=f+str(isVal)
+                    #setup the histos
+                    if isVal : Histos[keyHisto]=histoProducer(plot=h,histos=perfAll_Val[f],keys=perfAll_keys,isVal=isVal)
+                    else : Histos[keyHisto]=histoProducer(plot=h,histos=perfAll_Ref[f],keys=perfAll_keys,isVal=isVal)
+                    #set name file    
+                    if isVal : saveName=options.ValRel+"_"+options.ValSample+"_performance_Bvs"+f+"_allTaggers"
+                    else : saveName=options.RefRel+"_"+options.RefSample+"_performance_Bvs"+f+"_allTaggers"
+                    #set title
+                    if isVal : titleFlav = options.ValRel+"_"+options.ValSample+"_performance_Bvs"+f+"_allTaggers"
+                    else : titleFlav = options.RefRel+"_"+options.RefSample+"_performanceBvs"+f+"_allTaggers"
+                    #save canvas
+                    c[keyHisto] = savePlots(title=titleFlav,saveName=saveName,listFromats=listFromats,plot=h,Histos=Histos[keyHisto],keyHisto=keyHisto,listLegend=h.listTagger,options=options,legendName=h.legend.replace("FLAV",f))
diff --git a/Validation/RecoB/test/RelValnewFinal.csh b/Validation/RecoB/test/RelValnewFinal.csh
new file mode 100755
index 0000000000000..6712b5ad41b22
--- /dev/null
+++ b/Validation/RecoB/test/RelValnewFinal.csh
@@ -0,0 +1,86 @@
+#!/bin/tcsh
+
+#change release version : $1=release to validate, $2=reference release, $3=working directory (where is lacated yours CMSSW instances), $4=release name for DQM inputs to validate, $5=the same for reference DQM inputs
+valrel=$1
+refrel=$2
+workdir=$3
+valdir=$4
+refdir=$5
+
+mkdir TTbar_${valrel}_vs_${refrel}_Startup
+mkdir TTbar_${valrel}_vs_${refrel}_Startup_PU
+mkdir TTbar_${valrel}_vs_${refrel}_FastSim
+mkdir QCD_${valrel}_vs_${refrel}_Startup
+mkdir FastSim_TTbar_${valrel}_vs_TTbar_${valrel}
+
+cd TTbar_${valrel}_vs_${refrel}_Startup
+plotFactory.py -b -f ${workdir}/CMSSW_${valdir}/src/Validation/RecoB/test/BTagRelVal_TTbar_Startup_${valrel}.root -F ${workdir}/CMSSW_${refdir}/src/Validation/RecoB/test/BTagRelVal_TTbar_Startup_${refrel}.root -r ${valrel} -R ${refrel} -s TTbar_Startup -S TTbar_Startup
+cp /afs/cern.ch/cms/btag/www/validation/img/0_leg*.gif .
+mv 0_leg1.gif 0_leg4.gif
+for File in `ls ${valrel}_*_allTaggers*.gif`; do mv ${File} 1_${File}; done
+for File in `ls ${valrel}*jetPt*.gif`; do mv ${File} 2_${File}; done
+for File in `ls ${refrel}_*_allTaggers*.gif`; do mv ${File} 3_${File}; done
+for File in `ls ${valrel}*jetEta*.gif`; do mv ${File} 4_${File}; done
+cd ..
+
+cd TTbar_${valrel}_vs_${refrel}_Startup_PU
+plotFactory.py -b -f ${workdir}/CMSSW_${valdir}/src/Validation/RecoB/test/BTagRelVal_TTbar_Startup_PU_${valrel}.root -F ${workdir}/CMSSW_${refdir}/src/Validation/RecoB/test/BTagRelVal_TTbar_Startup_PU_${refrel}.root -r ${valrel} -R ${refrel} -s TTbar_Startup_PU -S TTbar_Startup_PU
+cp /afs/cern.ch/cms/btag/www/validation/img/0_leg*.gif .
+mv 0_leg1.gif 0_leg4.gif
+for File in `ls ${valrel}_*_allTaggers*.gif`; do mv ${File} 1_${File}; done
+for File in `ls ${valrel}*jetPt*.gif`; do mv ${File} 2_${File}; done
+for File in `ls ${refrel}_*_allTaggers*.gif`; do mv ${File} 3_${File}; done
+for File in `ls ${valrel}*jetEta*.gif`; do mv ${File} 4_${File}; done
+cd ..
+
+cd TTbar_${valrel}_vs_${refrel}_FastSim
+plotFactory.py -b -f ${workdir}/CMSSW_${valdir}/src/Validation/RecoB/test/BTagRelVal_TTbar_FastSim_${valrel}.root -F ${workdir}/CMSSW_${refdir}/src/Validation/RecoB/test/BTagRelVal_TTbar_FastSim_${refrel}.root -r ${valrel} -R ${refrel} -s TTbar_FastSim -S TTbar_FastSim
+cp /afs/cern.ch/cms/btag/www/validation/img/0_leg*.gif .
+mv 0_leg1.gif 0_leg4.gif
+for File in `ls ${valrel}_*_allTaggers*.gif`; do mv ${File} 1_${File}; done
+for File in `ls ${valrel}*jetPt*.gif`; do mv ${File} 2_${File}; done
+for File in `ls ${refrel}_*_allTaggers*.gif`; do mv ${File} 3_${File}; done
+for File in `ls ${valrel}*jetEta*.gif`; do mv ${File} 4_${File}; done
+cd ..
+ 
+
+cd QCD_${valrel}_vs_${refrel}_Startup
+plotFactory.py -b -f ${workdir}/CMSSW_${valdir}/src/Validation/RecoB/test/BTagRelVal_QCD_Startup_${valrel}.root -F ${workdir}/CMSSW_${refdir}/src/Validation/RecoB/test/BTagRelVal_QCD_Startup_${refrel}.root -r ${valrel} -R ${refrel} -s QCD_Startup -S QCD_Startup
+cp /afs/cern.ch/cms/btag/www/validation/img/0_leg*.gif .
+mv 0_leg1.gif 0_leg4.gif
+for File in `ls ${valrel}_*_allTaggers*.gif`; do mv ${File} 1_${File}; done
+for File in `ls ${valrel}*jetPt*.gif`; do mv ${File} 2_${File}; done
+for File in `ls ${refrel}_*_allTaggers*.gif`; do mv ${File} 3_${File}; done
+for File in `ls ${valrel}*jetEta*.gif`; do mv ${File} 4_${File}; done
+cd ..
+
+cd FastSim_TTbar_${valrel}_vs_TTbar_${valrel}
+plotFactory.py -b -f ${workdir}/CMSSW_${valdir}/src/Validation/RecoB/test/BTagRelVal_TTbar_FastSim_${valrel}.root -F ${workdir}/CMSSW_${valdir}/src/Validation/RecoB/test/BTagRelVal_TTbar_Startup_${valrel}.root -r ${valrel} -R ${valrel} -s TTbar_FastSim -S TTbar_Startup
+cp /afs/cern.ch/cms/btag/www/validation/img/0_leg*.gif .
+mv 0_leg1.gif 0_leg4.gif
+for File in `ls ${valrel}*FastSim*_allTaggers*.gif`; do mv ${File} 1_${File}; done
+for File in `ls ${valrel}*jetPt*.gif`; do mv ${File} 2_${File}; done
+for File in `ls ${valrel}*Startup*_allTaggers*.gif`; do mv ${File} 3_${File}; done
+for File in `ls ${valrel}*jetEta*.gif`; do mv ${File} 4_${File}; done
+cd ..
+
+mkdir CMSSW_${valdir}
+mv *_${valrel}_vs_${refrel}_*                 CMSSW_${valdir}/
+mv FastSim_TTbar_${valrel}_vs_TTbar_${valrel} CMSSW_${valdir}/
+
+echo '<a href="https://cms-btag-validation.web.cern.ch/cms-btag-validation/validation/index_RecoB_'CMSSW_${valdir}_TTbar_${valrel}_vs_${refrel}_Startup.html'">'TTbar_${valrel}_vs_${refrel}_Startup'</a><br>' >> index.html
+
+echo '<a href="https://cms-btag-validation.web.cern.ch/cms-btag-validation/validation/index_RecoB_'CMSSW_${valdir}_TTbar_${valrel}_vs_${refrel}_Startup_PU.html'">'TTbar_${valrel}_vs_${refrel}_Startup_PU'</a><br>' >> index.html
+
+echo '<a href="https://cms-btag-validation.web.cern.ch/cms-btag-validation/validation/index_RecoB_'CMSSW_${valdir}_TTbar_${valrel}_vs_${refrel}_FastSim.html'">'TTbar_${valrel}_vs_${refrel}_FastSim'</a><br>' >> index.html
+
+echo '<a href="https://cms-btag-validation.web.cern.ch/cms-btag-validation/validation/index_RecoB_'CMSSW_${valdir}_QCD_${valrel}_vs_${refrel}_Startup.html'">'QCD_${valrel}_vs_${refrel}_Startup'</a><br>' >> index.html
+
+echo '<a href="https://cms-btag-validation.web.cern.ch/cms-btag-validation/validation/index_RecoB_'CMSSW_${valdir}_FastSim_TTbar_${valrel}_vs_TTbar_${valrel}.html'">'FastSim_TTbar_${valrel}_vs_TTbar_${valrel}'</a><br>' >> index.html
+
+
+
+#mv index.html /afs/cern.ch/cms/btag/www/validation/CMSSW_${valdir}_topdir.html
+
+
+echo "https://cms-btag-validation.web.cern.ch/cms-btag-validation/validation/CMSSW_${valdir}_topdir.html" >& webpage.txt