Plotting/Modules/MetPlotting.C

#include <iostream>

using namespace std;

TGraphErrors* MakeErrorGraph(TH1F *histo) { 
  
  float dx[histo->GetNbinsX()];
  float dy[histo->GetNbinsX()];
  float x[histo->GetNbinsX()];
  float y[histo->GetNbinsX()];
  for(int i=1;i<=histo->GetNbinsX();i++) {
    x[i-1]=histo->GetBinCenter(i);
    y[i-1]=histo->GetBinContent(i);
    if(i>1) dx[i-1]=(histo->GetBinCenter(i)-histo->GetBinCenter(i-1))/2.0;
    else dx[i-1]=(histo->GetBinCenter(i+1)-histo->GetBinCenter(i))/2.0;
    dy[i-1]=histo->GetBinError(i);
  }
  
  TGraphErrors *gr = new TGraphErrors(histo->GetNbinsX(),x,y,dx,dy);
  gr->SetFillColor(TColor::GetColor("#2E9AFE"));
  return gr;
}
  
void ProduceMetPlotsWithCut(TCut cut, string name, float cutat, int njets, bool doMC = false ) {
  TCanvas *tcan = new TCanvas("tcan","tcan");
  cout << "Doing met plots" << endl;
  stringstream MetBaseCuts;
  MetBaseCuts << "met[4]>" << cutat << "&&" << cut.GetTitle();
  stringstream snjets;
  snjets << njets;
  TCut MetBaseCut(MetBaseCuts.str().c_str());
  TCut nJetsSignal(("pfJetGoodNum40>="+snjets.str()).c_str());
  TCut nJetsControl(("pfJetGoodNum40<"+snjets.str()).c_str());
  
  //compute SF / OF rate in (CR1+CR2), should give 0.941 +/- 0.05

  // Create histograms
  //int nbins = 30;
  int nbins = 60;
  float xmin=20., xmax = 320.;
  TH1F *mllsig   = allsamples.Draw("mllsig",  "mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSSF&&MetBaseCut&&nJetsSignal),data,PlottingSetup::luminosity);
  TH1F *mllscon  = allsamples.Draw("mllscon", "mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSSF&&MetBaseCut&&nJetsControl),data,PlottingSetup::luminosity);
  TH1F *mllOsig  = allsamples.Draw("mllOsig", "mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSOF&&MetBaseCut&&nJetsSignal),data,PlottingSetup::luminosity);
  TH1F *mllOscon = allsamples.Draw("mllOscon","mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSOF&&MetBaseCut&&nJetsControl),data,PlottingSetup::luminosity);

  THStack* mcMllsig;
  THStack* mcMllscon, *mcMllOsig, *mcMllOscon;
  if ( doMC ) {
    name += "_mc";
    mcMllsig  = new THStack(allsamples.DrawStack("mcMllsig",  "mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSSF&&MetBaseCut&&nJetsSignal),mc,PlottingSetup::luminosity));
    mcMllscon = new THStack(allsamples.DrawStack("mcMllscon", "mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSSF&&MetBaseCut&&nJetsControl),mc,PlottingSetup::luminosity));
    mcMllOsig = new THStack(allsamples.DrawStack("mcMllOsig", "mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSOF&&MetBaseCut&&nJetsSignal),mc,PlottingSetup::luminosity));
    mcMllOscon= new THStack(allsamples.DrawStack("mcMllOscon","mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSOF&&MetBaseCut&&nJetsControl),mc,PlottingSetup::luminosity));
  }
  
  mllOsig->SetLineColor(kRed);
  mllOscon->SetLineColor(kRed);
  
  TH1F *zlineshape = allsamples.Draw("zlineshape","mll",nbins,xmin,xmax,"m_{ll} (GeV)","events",cutOSSF&&TCut("pfJetGoodNum40==1")&&cut,data,PlottingSetup::luminosity);
  //float scalefactor=(mllsig->GetBinContent(mllsig->GetMaximumBin()-1)+mllsig->GetBinContent(mllsig->GetMaximumBin())+mllsig->GetBinContent(mllsig->GetMaximumBin()+1)-mllOsig->GetBinContent(mllsig->GetMaximumBin()-1)-mllOsig->GetBinContent(mllsig->GetMaximumBin())-mllOsig->GetBinContent(mllsig->GetMaximumBin())+1);
  //scalefactor/=(zlineshape->GetBinContent(zlineshape->GetMaximumBin()-1)+zlineshape->GetBinContent(zlineshape->GetMaximumBin())+zlineshape->GetBinContent(zlineshape->GetMaximumBin()+1));
  // Alternative scale factor: use 90+-5 GeV
  Int_t scaleBinLow = mllsig->FindBin(86);
  Int_t scaleBinHigh = mllsig->FindBin(94);
  float scalefactor = (mllsig->Integral(scaleBinLow,scaleBinHigh)-mllOsig->Integral(scaleBinLow,scaleBinHigh));
  scalefactor /= zlineshape->Integral(scaleBinLow,scaleBinHigh);
  
  cout << "Bins for scaling : " << scaleBinLow << " : " << scaleBinHigh << endl;
  
  zlineshape->Scale(scalefactor);
  zlineshape->SetLineColor(kBlue);
  zlineshape->SetLineStyle(2);
  
  TH1F *subtracted = (TH1F*)mllsig->Clone("subtracted");
  TH1F *baseline = (TH1F*)mllOsig->Clone("baseline");
  for(int i=1;i<=subtracted->GetNbinsX();i++) {
    subtracted->SetBinContent(i,mllsig->GetBinContent(i)-mllOsig->GetBinContent(i));
    baseline->SetBinContent(i,0);
  }
  
  TH1F *prediction = (TH1F*)mllOsig->Clone("prediction");
  prediction->Add(zlineshape);
  prediction->SetLineColor(TColor::GetColor("#CF35CA"));
  
  TH1F *control_prediction = (TH1F*)mllOscon->Clone("control_prediction");
  control_prediction->SetLineColor(TColor::GetColor("#CF35CA"));

  // FIX Y RANGE TO EASE COMPARISON
  mllsig->SetMaximum(120);
  mllOsig->SetMaximum(120);
  mllOscon->SetMaximum(280);
  subtracted->SetMaximum(50);
  subtracted->SetMinimum(-30);


  // 1.- Signal region comparison
  TGraphErrors *stat3j;
  ////mllsig->GetYaxis()->SetRangeUser(0,mllsig->GetMaximum()*1.2);
  mllsig->Draw();
  // Do not draw errors on prediction when overlaying MC.
  if ( doMC ) {
    mcMllsig->Draw("same");
  } else {
    stat3j = MakeErrorGraph(prediction);
    stat3j->Draw("2,same");
    mllOsig->Draw("histo,same");
    zlineshape->Draw("histo,same");
  }
  prediction->Draw("histo,same");
  mllsig->Draw("same");
  DrawPrelim();
  
  TBox *srbox = new TBox(20,0,70,mllsig->GetMaximum());
  srbox->SetFillStyle(0);
  srbox->SetLineColor(TColor::GetColor("#298A08"));
  srbox->SetLineWidth(3);
  
  TLegend *leg;
  if ( doMC ) {
    leg = allsamples.allbglegend();
  } else {
    leg = make_legend();
  }
  leg->SetX1(0.54);
  stringstream MetHeader;
  MetHeader << "MET>" << cutat << " GeV";
  leg->SetHeader(((string)"N_{jets}#geq"+snjets.str()+", "+MetHeader.str()).c_str());
  if (!doMC) leg->AddEntry(mllsig,"Data","PL");
  leg->AddEntry(prediction,"All bg prediction","L");
  if (!doMC) {
    leg->AddEntry(mllOsig,"bg without Z","L");
    leg->AddEntry(zlineshape,"Z lineshape","L");
    leg->AddEntry(stat3j,"stat. uncert.","F");
  }
  leg->AddEntry(srbox,"SR","F");
  leg->Draw();
  
  srbox->Draw();
  
  stringstream saveasSig;
  saveasSig << "MetPlots/mll_sig" << cutat << "__" << name;
  CompleteSave(tcan,saveasSig.str());
  
  // 2.- Signal region comparison - LOG scale
  mllsig->SetMinimum(0.2); // FIX Y RANGE TO EASE COMPARISON
  //mllsig->SetMaximum(mllsig->GetMaximum()*4.0);
  srbox->SetY2(mllsig->GetMaximum());
  
  tcan->SetLogy(1);
  stringstream saveasSig2;
  saveasSig2 << "MetPlots/mll_sig_ZLINESHAPE_" << cutat << "__" << name;
  
  CompleteSave(tcan,saveasSig2.str());
  tcan->SetLogy(0);
  

  // 3.- Signal region, background subtracted
  for(int i=1;i<subtracted->GetNbinsX();i++) {
    subtracted->SetBinContent(i,subtracted->GetBinContent(i)-zlineshape->GetBinContent(i));
  }

  TGraphErrors *subtrerr = MakeErrorGraph(baseline);
  subtracted->Draw();
  subtrerr->Draw("2,same");
  subtracted->Draw("same");
  DrawPrelim();
  TLegend *DiffLeg = make_legend();
  DiffLeg->SetX1(0.3);
  DiffLeg->SetFillStyle(0);
  DiffLeg->AddEntry(subtracted,"observed - predicted","PL");
  DiffLeg->AddEntry(subtrerr,"stat. uncert on prediction","F");
  DiffLeg->AddEntry((TObject*)0,"","");
  DiffLeg->AddEntry((TObject*)0,"","");
  DiffLeg->Draw();
  
  stringstream saveasSigSub;
  saveasSigSub << "MetPlots/mll_sig_SUBTRACTED_" << cutat << "__" << name;
  
  CompleteSave(tcan,saveasSigSub.str());

  // 4.- Signal region, background subtracted, errors added in quadrature
  TGraphErrors *subtrerr2 = (TGraphErrors*)subtrerr->Clone("subtrerr2");
  for(int i=0;i<subtrerr2->GetN();i++) {
     subtrerr2->SetPoint(i,subtracted->GetBinCenter(i),subtracted->GetBinContent(i));
     subtrerr2->SetPointError(i,subtrerr2->GetErrorX(i),TMath::Sqrt(subtrerr2->GetErrorY(i)*subtrerr2->GetErrorY(i)+subtracted->GetBinError(i)*subtracted->GetBinError(i)));
  }
  TLine* l = new TLine(subtracted->GetBinLowEdge(1),0.,subtracted->GetBinLowEdge(subtracted->GetNbinsX()-1)+subtracted->GetBinWidth(1),0.);
  l->SetLineWidth(subtracted->GetLineWidth());
  subtracted->Draw();
  subtrerr2->Draw("2,same");
  l->Draw("same");
  subtracted->Draw("same");
  DrawPrelim();
  TLegend *DiffLeg2 = make_legend();
  DiffLeg2->SetX1(0.3);
  DiffLeg2->SetFillStyle(0);
  DiffLeg2->AddEntry(subtracted,"observed - predicted","PL");
  DiffLeg2->AddEntry(subtrerr2,"stat. uncert on prediction","F");
  DiffLeg2->AddEntry((TObject*)0,"","");
  DiffLeg2->AddEntry((TObject*)0,"","");
  DiffLeg2->Draw();

  stringstream saveasSigSub2;
  saveasSigSub2 << "MetPlots/mll_sig_SUBTRACTED_quadr_" << cutat << "__" << name;

  CompleteSave(tcan,saveasSigSub2.str());

    
  // 5.- Control region comparison
  scalefactor = (mllscon->Integral(scaleBinLow,scaleBinHigh)-mllOscon->Integral(scaleBinLow,scaleBinHigh));
  scalefactor /= zlineshape->Integral(scaleBinLow,scaleBinHigh);
  zlineshape->Scale(scalefactor);
  control_prediction->Add(zlineshape);
  control_prediction->SetMaximum(280); // FIX Y RANGE TO EASE COMPARISON

  //control_prediction->GetYaxis()->SetRangeUser(0,control_prediction->GetMaximum()*1.3);
  TGraphErrors *stat2j;
  control_prediction->Draw("hist");
  if(doMC) {
    mcMllscon->Draw("same");
  } else {
    stat2j = MakeErrorGraph(control_prediction);
    stat2j->Draw("2,same");
    mllOscon->Draw("same,hist");
    zlineshape->Draw("histo,same");
  }
  control_prediction->Draw("histo,same");
  mllscon->Draw("same");
  DrawPrelim();
  
  TBox *cr1box = new TBox(20,0,70,control_prediction->GetMaximum());
  cr1box->SetFillStyle(0);
  cr1box->SetLineColor(TColor::GetColor("#0404B4"));
  cr1box->SetLineWidth(3);
  
  TBox *cr2box = new TBox(150,0,320,control_prediction->GetMaximum());
  cr2box->SetFillStyle(0);
  cr2box->SetLineColor(TColor::GetColor("#0404B4"));
  cr2box->SetLineWidth(3);
  cr2box->SetLineStyle(2);
  
  TLegend *legc;
  if ( doMC ) {
    legc = allsamples.allbglegend();
  } else {
    legc = make_legend();
  }
  legc->SetX1(0.54);
  legc->SetHeader(((string)"N_{jets} < "+snjets.str()+", "+MetHeader.str()).c_str());
  if ( !doMC ) legc->AddEntry(mllscon,"Data","PL");
  legc->AddEntry(control_prediction,"All bg","L");
  if ( !doMC ) {
    legc->AddEntry(zlineshape,"Z lineshape","L");
    legc->AddEntry(mllOscon,"bg without Z","L");
    legc->AddEntry(stat2j,"stat. uncert.","F");
  }
  legc->AddEntry(cr1box,"CR1","F");
  legc->AddEntry(cr2box,"CR2","F");
  legc->Draw();
  
  cr1box->Draw();
  cr2box->Draw();
  
  stringstream saveasCon;
  saveasCon << "MetPlots/mll_con" << cutat << "__" << name;
  CompleteSave(tcan,saveasCon.str());

  // 6. - Opposite-flavour data/MC comparison
  if ( doMC ) {
    mllOsig->SetLineColor(kBlack);
    mllOsig->Draw();
    mcMllOsig->Draw("same");
    mllOsig->Draw("same");
    TLegend *legsdm = allsamples.allbglegend();
    legsdm->SetHeader(((string)"N_{jets}#geq"+snjets.str()+", "+MetHeader.str()+", OF").c_str());
    legsdm->SetX1(0.54);
    legsdm->Draw();
    stringstream saveasSigOF;
    saveasSigOF << "MetPlots/mll_sig_of_" << cutat << "__" << name;
    CompleteSave(tcan,saveasSigOF.str());

    mllOscon->SetLineColor(kBlack);
    mllOscon->Draw();
    mcMllOscon->Draw("same");
    mllOscon->Draw("same");
    TLegend *legcdm = allsamples.allbglegend();
    legcdm->SetHeader(((string)"N_{jets}<"+snjets.str()+", "+MetHeader.str()+", OF").c_str());
    legcdm->SetX1(0.54);
    legcdm->Draw();
    stringstream saveasConOF;
    saveasConOF << "MetPlots/mll_con_of_" << cutat << "__" << name;
    CompleteSave(tcan,saveasConOF.str());
    
    delete legsdm;
    delete legcdm;

    delete mcMllscon;
    delete mcMllOscon;
    delete mcMllsig;
    delete mcMllOsig;
  }
  
  delete cr1box;
  delete cr2box;
  delete srbox;
  delete legc;
  delete leg;
  delete DiffLeg;
  delete DiffLeg2;
  
  delete mllscon;
  delete mllOscon;
  delete mllsig;
  delete mllOsig;
  delete zlineshape;
  delete tcan;
}  

void DoMetPlots() {
  float metCuts[] = { 100., 150. };
  int jetCuts[] = { 3, 2 };
  string leptCuts[] = { "pt1>20&&pt2>20&&abs(eta1)<1.4&&abs(eta2)<1.4", 
                        "pt1>20&&pt2>10" 
                      };
  bool nomc(0),domc(1);
  for ( int i=0; i<2; ++i ) {
    ProduceMetPlotsWithCut(TCut(("mll>20&&"+leptCuts[i]).c_str()),"",metCuts[i], jetCuts[i],nomc);
    ProduceMetPlotsWithCut(TCut(("mll>20&&"+leptCuts[i]).c_str()),"",metCuts[i], jetCuts[i],domc);
    if (!PlottingSetup::is53reco) { // Old 5_2
      ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag==0&&"+leptCuts[i]).c_str()),"bTagVeto30",metCuts[i], jetCuts[i]);
      ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag>0&&"+leptCuts[i]).c_str()),"AtLeastOneBJet30",metCuts[i], jetCuts[i]);
    } else {
      ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag30==0&&"+leptCuts[i]).c_str()),"bTagVeto30",metCuts[i], jetCuts[i],nomc);
      ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag30>0&&"+leptCuts[i]).c_str()),"AtLeastOneBJet30",metCuts[i], jetCuts[i],nomc);
      ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag30==0&&"+leptCuts[i]).c_str()),"bTagVeto30",metCuts[i], jetCuts[i],domc);
      ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag30>0&&"+leptCuts[i]).c_str()),"AtLeastOneBJet30",metCuts[i], jetCuts[i],domc);
      ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag40==0&&"+leptCuts[i]).c_str()),"bTagVeto40",metCuts[i], jetCuts[i]);
      ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag40>0&&"+leptCuts[i]).c_str()),"AtLeastOneBJet40",metCuts[i], jetCuts[i]);
    }
  }
}
Revision:	1.7
Committed:	Thu Aug 23 16:31:31 2012 UTC (12 years, 8 months ago) by fronga
Content type:	text/plain
Branch:	MAIN
Changes since 1.6:	+162 -58 lines
Log Message:	Significantly pimped up the MET plots. Now includes data/MC comparison (TODO: ratio plots!?). Also includes MET150 region. Marco-Andrea: please check for memory abuse ;)
#	User	Rev	Content
1	buchmann	1.1	#include <iostream>
2
3			using namespace std;
4
5			TGraphErrors* MakeErrorGraph(TH1F *histo) {
6
7			float dx[histo->GetNbinsX()];
8			float dy[histo->GetNbinsX()];
9			float x[histo->GetNbinsX()];
10			float y[histo->GetNbinsX()];
11			for(int i=1;i<=histo->GetNbinsX();i++) {
12			x[i-1]=histo->GetBinCenter(i);
13			y[i-1]=histo->GetBinContent(i);
14			if(i>1) dx[i-1]=(histo->GetBinCenter(i)-histo->GetBinCenter(i-1))/2.0;
15			else dx[i-1]=(histo->GetBinCenter(i+1)-histo->GetBinCenter(i))/2.0;
16			dy[i-1]=histo->GetBinError(i);
17			}
18
19			TGraphErrors *gr = new TGraphErrors(histo->GetNbinsX(),x,y,dx,dy);
20			gr->SetFillColor(TColor::GetColor("#2E9AFE"));
21			return gr;
22			}
23
24	fronga	1.7	void ProduceMetPlotsWithCut(TCut cut, string name, float cutat, int njets, bool doMC = false ) {
25	buchmann	1.1	TCanvas *tcan = new TCanvas("tcan","tcan");
26			cout << "Doing met plots" << endl;
27	buchmann	1.2	stringstream MetBaseCuts;
28	fronga	1.7	MetBaseCuts << "met[4]>" << cutat << "&&" << cut.GetTitle();
29			stringstream snjets;
30			snjets << njets;
31	buchmann	1.2	TCut MetBaseCut(MetBaseCuts.str().c_str());
32	fronga	1.7	TCut nJetsSignal(("pfJetGoodNum40>="+snjets.str()).c_str());
33			TCut nJetsControl(("pfJetGoodNum40<"+snjets.str()).c_str());
34	buchmann	1.1
35			//compute SF / OF rate in (CR1+CR2), should give 0.941 +/- 0.05
36	fronga	1.7
37			// Create histograms
38			//int nbins = 30;
39			int nbins = 60;
40			float xmin=20., xmax = 320.;
41			TH1F *mllsig = allsamples.Draw("mllsig", "mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSSF&&MetBaseCut&&nJetsSignal),data,PlottingSetup::luminosity);
42			TH1F *mllscon = allsamples.Draw("mllscon", "mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSSF&&MetBaseCut&&nJetsControl),data,PlottingSetup::luminosity);
43			TH1F *mllOsig = allsamples.Draw("mllOsig", "mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSOF&&MetBaseCut&&nJetsSignal),data,PlottingSetup::luminosity);
44			TH1F *mllOscon = allsamples.Draw("mllOscon","mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSOF&&MetBaseCut&&nJetsControl),data,PlottingSetup::luminosity);
45
46			THStack* mcMllsig;
47			THStack* mcMllscon, mcMllOsig, mcMllOscon;
48			if ( doMC ) {
49			name += "_mc";
50			mcMllsig = new THStack(allsamples.DrawStack("mcMllsig", "mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSSF&&MetBaseCut&&nJetsSignal),mc,PlottingSetup::luminosity));
51			mcMllscon = new THStack(allsamples.DrawStack("mcMllscon", "mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSSF&&MetBaseCut&&nJetsControl),mc,PlottingSetup::luminosity));
52			mcMllOsig = new THStack(allsamples.DrawStack("mcMllOsig", "mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSOF&&MetBaseCut&&nJetsSignal),mc,PlottingSetup::luminosity));
53			mcMllOscon= new THStack(allsamples.DrawStack("mcMllOscon","mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSOF&&MetBaseCut&&nJetsControl),mc,PlottingSetup::luminosity));
54			}
55	buchmann	1.1
56			mllOsig->SetLineColor(kRed);
57			mllOscon->SetLineColor(kRed);
58
59	fronga	1.7	TH1F *zlineshape = allsamples.Draw("zlineshape","mll",nbins,xmin,xmax,"m_{ll} (GeV)","events",cutOSSF&&TCut("pfJetGoodNum40==1")&&cut,data,PlottingSetup::luminosity);
60	fronga	1.4	//float scalefactor=(mllsig->GetBinContent(mllsig->GetMaximumBin()-1)+mllsig->GetBinContent(mllsig->GetMaximumBin())+mllsig->GetBinContent(mllsig->GetMaximumBin()+1)-mllOsig->GetBinContent(mllsig->GetMaximumBin()-1)-mllOsig->GetBinContent(mllsig->GetMaximumBin())-mllOsig->GetBinContent(mllsig->GetMaximumBin())+1);
61			//scalefactor/=(zlineshape->GetBinContent(zlineshape->GetMaximumBin()-1)+zlineshape->GetBinContent(zlineshape->GetMaximumBin())+zlineshape->GetBinContent(zlineshape->GetMaximumBin()+1));
62			// Alternative scale factor: use 90+-5 GeV
63	buchmann	1.6	Int_t scaleBinLow = mllsig->FindBin(86);
64			Int_t scaleBinHigh = mllsig->FindBin(94);
65	fronga	1.4	float scalefactor = (mllsig->Integral(scaleBinLow,scaleBinHigh)-mllOsig->Integral(scaleBinLow,scaleBinHigh));
66			scalefactor /= zlineshape->Integral(scaleBinLow,scaleBinHigh);
67	buchmann	1.6
68			cout << "Bins for scaling : " << scaleBinLow << " : " << scaleBinHigh << endl;
69
70	buchmann	1.3	zlineshape->Scale(scalefactor);
71			zlineshape->SetLineColor(kBlue);
72			zlineshape->SetLineStyle(2);
73
74			TH1F subtracted = (TH1F)mllsig->Clone("subtracted");
75			TH1F baseline = (TH1F)mllOsig->Clone("baseline");
76			for(int i=1;i<=subtracted->GetNbinsX();i++) {
77			subtracted->SetBinContent(i,mllsig->GetBinContent(i)-mllOsig->GetBinContent(i));
78			baseline->SetBinContent(i,0);
79			}
80
81			TH1F prediction = (TH1F)mllOsig->Clone("prediction");
82			prediction->Add(zlineshape);
83			prediction->SetLineColor(TColor::GetColor("#CF35CA"));
84	fronga	1.7
85			TH1F control_prediction = (TH1F)mllOscon->Clone("control_prediction");
86			control_prediction->SetLineColor(TColor::GetColor("#CF35CA"));
87
88			// FIX Y RANGE TO EASE COMPARISON
89			mllsig->SetMaximum(120);
90			mllOsig->SetMaximum(120);
91			mllOscon->SetMaximum(280);
92			subtracted->SetMaximum(50);
93			subtracted->SetMinimum(-30);
94
95	buchmann	1.3
96	fronga	1.7	// 1.- Signal region comparison
97			TGraphErrors *stat3j;
98			////mllsig->GetYaxis()->SetRangeUser(0,mllsig->GetMaximum()*1.2);
99	buchmann	1.1	mllsig->Draw();
100	fronga	1.7	// Do not draw errors on prediction when overlaying MC.
101			if ( doMC ) {
102			mcMllsig->Draw("same");
103			} else {
104			stat3j = MakeErrorGraph(prediction);
105			stat3j->Draw("2,same");
106			mllOsig->Draw("histo,same");
107			zlineshape->Draw("histo,same");
108			}
109	buchmann	1.3	prediction->Draw("histo,same");
110	buchmann	1.1	mllsig->Draw("same");
111			DrawPrelim();
112
113			TBox *srbox = new TBox(20,0,70,mllsig->GetMaximum());
114			srbox->SetFillStyle(0);
115			srbox->SetLineColor(TColor::GetColor("#298A08"));
116			srbox->SetLineWidth(3);
117
118	fronga	1.7	TLegend *leg;
119			if ( doMC ) {
120			leg = allsamples.allbglegend();
121			} else {
122			leg = make_legend();
123			}
124	buchmann	1.1	leg->SetX1(0.54);
125	buchmann	1.2	stringstream MetHeader;
126			MetHeader << "MET>" << cutat << " GeV";
127	fronga	1.7	leg->SetHeader(((string)"N_{jets}#geq"+snjets.str()+", "+MetHeader.str()).c_str());
128			if (!doMC) leg->AddEntry(mllsig,"Data","PL");
129			leg->AddEntry(prediction,"All bg prediction","L");
130			if (!doMC) {
131			leg->AddEntry(mllOsig,"bg without Z","L");
132			leg->AddEntry(zlineshape,"Z lineshape","L");
133			leg->AddEntry(stat3j,"stat. uncert.","F");
134			}
135	buchmann	1.1	leg->AddEntry(srbox,"SR","F");
136			leg->Draw();
137
138			srbox->Draw();
139
140			stringstream saveasSig;
141	buchmann	1.3	saveasSig << "MetPlots/mll_sig" << cutat << "__" << name;
142	buchmann	1.1	CompleteSave(tcan,saveasSig.str());
143
144	fronga	1.7	// 2.- Signal region comparison - LOG scale
145			mllsig->SetMinimum(0.2); // FIX Y RANGE TO EASE COMPARISON
146			//mllsig->SetMaximum(mllsig->GetMaximum()*4.0);
147	fronga	1.4	srbox->SetY2(mllsig->GetMaximum());
148	buchmann	1.6
149	buchmann	1.1	tcan->SetLogy(1);
150			stringstream saveasSig2;
151	buchmann	1.3	saveasSig2 << "MetPlots/mll_sig_ZLINESHAPE_" << cutat << "__" << name;
152
153	buchmann	1.1	CompleteSave(tcan,saveasSig2.str());
154			tcan->SetLogy(0);
155
156	fronga	1.7
157			// 3.- Signal region, background subtracted
158	buchmann	1.3	for(int i=1;i<subtracted->GetNbinsX();i++) {
159			subtracted->SetBinContent(i,subtracted->GetBinContent(i)-zlineshape->GetBinContent(i));
160			}
161
162			TGraphErrors *subtrerr = MakeErrorGraph(baseline);
163			subtracted->Draw();
164			subtrerr->Draw("2,same");
165			subtracted->Draw("same");
166			DrawPrelim();
167			TLegend *DiffLeg = make_legend();
168	fronga	1.5	DiffLeg->SetX1(0.3);
169	fronga	1.7	DiffLeg->SetFillStyle(0);
170	buchmann	1.3	DiffLeg->AddEntry(subtracted,"observed - predicted","PL");
171			DiffLeg->AddEntry(subtrerr,"stat. uncert on prediction","F");
172	fronga	1.7	DiffLeg->AddEntry((TObject*)0,"","");
173			DiffLeg->AddEntry((TObject*)0,"","");
174	buchmann	1.3	DiffLeg->Draw();
175
176			stringstream saveasSigSub;
177			saveasSigSub << "MetPlots/mll_sig_SUBTRACTED_" << cutat << "__" << name;
178
179			CompleteSave(tcan,saveasSigSub.str());
180	fronga	1.5
181	fronga	1.7	// 4.- Signal region, background subtracted, errors added in quadrature
182	fronga	1.5	TGraphErrors subtrerr2 = (TGraphErrors)subtrerr->Clone("subtrerr2");
183			for(int i=0;i<subtrerr2->GetN();i++) {
184			subtrerr2->SetPoint(i,subtracted->GetBinCenter(i),subtracted->GetBinContent(i));
185			subtrerr2->SetPointError(i,subtrerr2->GetErrorX(i),TMath::Sqrt(subtrerr2->GetErrorY(i)subtrerr2->GetErrorY(i)+subtracted->GetBinError(i)subtracted->GetBinError(i)));
186			}
187			TLine* l = new TLine(subtracted->GetBinLowEdge(1),0.,subtracted->GetBinLowEdge(subtracted->GetNbinsX()-1)+subtracted->GetBinWidth(1),0.);
188			l->SetLineWidth(subtracted->GetLineWidth());
189			subtracted->Draw();
190			subtrerr2->Draw("2,same");
191			l->Draw("same");
192			subtracted->Draw("same");
193			DrawPrelim();
194			TLegend *DiffLeg2 = make_legend();
195			DiffLeg2->SetX1(0.3);
196	fronga	1.7	DiffLeg2->SetFillStyle(0);
197	fronga	1.5	DiffLeg2->AddEntry(subtracted,"observed - predicted","PL");
198			DiffLeg2->AddEntry(subtrerr2,"stat. uncert on prediction","F");
199	fronga	1.7	DiffLeg2->AddEntry((TObject*)0,"","");
200			DiffLeg2->AddEntry((TObject*)0,"","");
201	fronga	1.5	DiffLeg2->Draw();
202
203			stringstream saveasSigSub2;
204			saveasSigSub2 << "MetPlots/mll_sig_SUBTRACTED_quadr_" << cutat << "__" << name;
205
206			CompleteSave(tcan,saveasSigSub2.str());
207
208	buchmann	1.3
209
210	fronga	1.7	// 5.- Control region comparison
211	buchmann	1.6	scalefactor = (mllscon->Integral(scaleBinLow,scaleBinHigh)-mllOscon->Integral(scaleBinLow,scaleBinHigh));
212			scalefactor /= zlineshape->Integral(scaleBinLow,scaleBinHigh);
213			zlineshape->Scale(scalefactor);
214			control_prediction->Add(zlineshape);
215	fronga	1.7	control_prediction->SetMaximum(280); // FIX Y RANGE TO EASE COMPARISON
216
217			//control_prediction->GetYaxis()->SetRangeUser(0,control_prediction->GetMaximum()*1.3);
218			TGraphErrors *stat2j;
219			control_prediction->Draw("hist");
220			if(doMC) {
221			mcMllscon->Draw("same");
222			} else {
223			stat2j = MakeErrorGraph(control_prediction);
224			stat2j->Draw("2,same");
225			mllOscon->Draw("same,hist");
226			zlineshape->Draw("histo,same");
227			}
228	buchmann	1.6	control_prediction->Draw("histo,same");
229	buchmann	1.1	mllscon->Draw("same");
230			DrawPrelim();
231
232	buchmann	1.6	TBox *cr1box = new TBox(20,0,70,control_prediction->GetMaximum());
233	buchmann	1.1	cr1box->SetFillStyle(0);
234			cr1box->SetLineColor(TColor::GetColor("#0404B4"));
235			cr1box->SetLineWidth(3);
236
237	buchmann	1.6	TBox *cr2box = new TBox(150,0,320,control_prediction->GetMaximum());
238	buchmann	1.1	cr2box->SetFillStyle(0);
239			cr2box->SetLineColor(TColor::GetColor("#0404B4"));
240			cr2box->SetLineWidth(3);
241			cr2box->SetLineStyle(2);
242
243	fronga	1.7	TLegend *legc;
244			if ( doMC ) {
245			legc = allsamples.allbglegend();
246			} else {
247			legc = make_legend();
248			}
249	buchmann	1.1	legc->SetX1(0.54);
250	fronga	1.7	legc->SetHeader(((string)"N_{jets} < "+snjets.str()+", "+MetHeader.str()).c_str());
251			if ( !doMC ) legc->AddEntry(mllscon,"Data","PL");
252	buchmann	1.6	legc->AddEntry(control_prediction,"All bg","L");
253	fronga	1.7	if ( !doMC ) {
254			legc->AddEntry(zlineshape,"Z lineshape","L");
255			legc->AddEntry(mllOscon,"bg without Z","L");
256			legc->AddEntry(stat2j,"stat. uncert.","F");
257			}
258	buchmann	1.1	legc->AddEntry(cr1box,"CR1","F");
259			legc->AddEntry(cr2box,"CR2","F");
260			legc->Draw();
261
262			cr1box->Draw();
263			cr2box->Draw();
264
265			stringstream saveasCon;
266	buchmann	1.3	saveasCon << "MetPlots/mll_con" << cutat << "__" << name;
267	buchmann	1.1	CompleteSave(tcan,saveasCon.str());
268	fronga	1.7
269			// 6. - Opposite-flavour data/MC comparison
270			if ( doMC ) {
271			mllOsig->SetLineColor(kBlack);
272			mllOsig->Draw();
273			mcMllOsig->Draw("same");
274			mllOsig->Draw("same");
275			TLegend *legsdm = allsamples.allbglegend();
276			legsdm->SetHeader(((string)"N_{jets}#geq"+snjets.str()+", "+MetHeader.str()+", OF").c_str());
277			legsdm->SetX1(0.54);
278			legsdm->Draw();
279			stringstream saveasSigOF;
280			saveasSigOF << "MetPlots/mll_sig_of_" << cutat << "__" << name;
281			CompleteSave(tcan,saveasSigOF.str());
282
283			mllOscon->SetLineColor(kBlack);
284			mllOscon->Draw();
285			mcMllOscon->Draw("same");
286			mllOscon->Draw("same");
287			TLegend *legcdm = allsamples.allbglegend();
288			legcdm->SetHeader(((string)"N_{jets}<"+snjets.str()+", "+MetHeader.str()+", OF").c_str());
289			legcdm->SetX1(0.54);
290			legcdm->Draw();
291			stringstream saveasConOF;
292			saveasConOF << "MetPlots/mll_con_of_" << cutat << "__" << name;
293			CompleteSave(tcan,saveasConOF.str());
294
295			delete legsdm;
296			delete legcdm;
297
298			delete mcMllscon;
299			delete mcMllOscon;
300			delete mcMllsig;
301			delete mcMllOsig;
302			}
303	buchmann	1.1
304			delete cr1box;
305			delete cr2box;
306			delete srbox;
307			delete legc;
308			delete leg;
309	fronga	1.7	delete DiffLeg;
310			delete DiffLeg2;
311
312	buchmann	1.1	delete mllscon;
313			delete mllOscon;
314			delete mllsig;
315			delete mllOsig;
316	fronga	1.7	delete zlineshape;
317	buchmann	1.6	delete tcan;
318	buchmann	1.1	}
319
320			void DoMetPlots() {
321	fronga	1.7	float metCuts[] = { 100., 150. };
322			int jetCuts[] = { 3, 2 };
323			string leptCuts[] = { "pt1>20&&pt2>20&&abs(eta1)<1.4&&abs(eta2)<1.4",
324			"pt1>20&&pt2>10"
325			};
326			bool nomc(0),domc(1);
327			for ( int i=0; i<2; ++i ) {
328			ProduceMetPlotsWithCut(TCut(("mll>20&&"+leptCuts[i]).c_str()),"",metCuts[i], jetCuts[i],nomc);
329			ProduceMetPlotsWithCut(TCut(("mll>20&&"+leptCuts[i]).c_str()),"",metCuts[i], jetCuts[i],domc);
330			if (!PlottingSetup::is53reco) { // Old 5_2
331			ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag==0&&"+leptCuts[i]).c_str()),"bTagVeto30",metCuts[i], jetCuts[i]);
332			ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag>0&&"+leptCuts[i]).c_str()),"AtLeastOneBJet30",metCuts[i], jetCuts[i]);
333			} else {
334			ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag30==0&&"+leptCuts[i]).c_str()),"bTagVeto30",metCuts[i], jetCuts[i],nomc);
335			ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag30>0&&"+leptCuts[i]).c_str()),"AtLeastOneBJet30",metCuts[i], jetCuts[i],nomc);
336			ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag30==0&&"+leptCuts[i]).c_str()),"bTagVeto30",metCuts[i], jetCuts[i],domc);
337			ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag30>0&&"+leptCuts[i]).c_str()),"AtLeastOneBJet30",metCuts[i], jetCuts[i],domc);
338			ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag40==0&&"+leptCuts[i]).c_str()),"bTagVeto40",metCuts[i], jetCuts[i]);
339			ProduceMetPlotsWithCut(TCut(("mll>20&&pfJetGoodNumBtag40>0&&"+leptCuts[i]).c_str()),"AtLeastOneBJet40",metCuts[i], jetCuts[i]);
340			}
341			}
342	buchmann	1.1	}