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buchmann |
1.1 |
#include <iostream>
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using namespace std;
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buchmann |
1.17 |
float Get_Met_Z_Prediction(TCut JetCut, float MetCut, int isdata, bool isDYonly);
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buchmann |
1.24 |
namespace MetPlotsSpace {
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buchmann |
1.28 |
float Zprediction_Uncertainty=0.2;
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buchmann |
1.30 |
float Zestimate__data=-1;
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float Zestimate__data_sys=-1;
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float Zestimate__data_stat=-1;
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float Zestimate__mc=-1;
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float Zestimate__mc_sys=-1;
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float Zestimate__mc_stat=-1;
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float Zestimate__dy=-1;
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float Zestimate__dy_sys=-1;
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float Zestimate__dy_stat=-1;
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buchmann |
1.24 |
}
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buchmann |
1.17 |
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buchmann |
1.30 |
void ExperimentalMetPrediction(bool QuickRun);
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void ExtractScaleFactor(TH1F *mllSF,TH1F *mllOF, THStack* mcMllSF, THStack* mcMllOF, TH1F *prediction, TLegend *leg, string saveasSig, TBox *srbox) {
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Int_t minbin = mllSF->FindBin(20.);
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Int_t maxbin = mllSF->FindBin(70.-1);
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// Get yields in OF region
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Float_t iDataOF = mllOF->Integral();
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Float_t iDataOFSR = mllOF->Integral(minbin,maxbin);
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Float_t iMCOF = 0.0;
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Float_t iMCOFSR = 0.0;
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TIter nextOF(mcMllOF->GetHists());
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TH1F* h;
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while ( h = (TH1F*)nextOF() ) {
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iMCOF += h->Integral();
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iMCOFSR += h->Integral(minbin,maxbin);
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}
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Float_t scale = iDataOF/iMCOF;
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// Re-scale OF
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nextOF = TIter(mcMllOF->GetHists());
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while ( h = (TH1F*)nextOF() ) {
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h->Scale(scale);
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}
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nextOF = TIter(mcMllOF->GetHists());
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// Rescale SF and count in signal region
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std::cout << "Integrating from " << mllSF->GetBinLowEdge(minbin) << " to " << mllSF->GetBinLowEdge(maxbin)+mllSF->GetBinWidth(maxbin) << std::endl;
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Float_t iDataSFSR = mllSF->Integral(minbin,maxbin);
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Float_t iMCSFSR = 0.0;
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TIter nextSF = TIter(mcMllSF->GetHists());
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while ( h = (TH1F*)nextSF() ) {
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h->Scale(scale);
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iMCSFSR += h->Integral(minbin,maxbin);
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}
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nextSF = TIter(mcMllSF->GetHists());
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while ( h = (TH1F*)nextSF() ) {
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iMCSFSR += h->Integral(minbin,maxbin);
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}
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mcMllSF->Modified();
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TPad* rcan2 = new TPad("rcan2","rcan2",0,0,1,1);
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rcan2->cd();
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mllSF->Draw();
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mcMllSF->Draw("same");
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prediction->Draw("histo,same");
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mllSF->Draw("same");
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DrawPrelim();
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stringstream leghead;
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leghead << "MC scaled by " << std::setprecision(2) << scale << "";
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cout << "SCALE: " << scale << endl;
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TH1F *histo = new TH1F("histo","histo",1,0,1);histo->SetLineColor(kWhite);
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leg->AddEntry(histo,leghead.str().c_str(),"l");
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leg->Draw();
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srbox->Draw();
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stringstream saveasSig2;
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saveasSig2 << saveasSig << "__mcScaled";
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rcan2->Update();
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save_with_ratio( mllSF, *mcMllSF, rcan2, saveasSig2.str() );
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buchmann |
1.32 |
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// restore original stacks
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nextOF = TIter(mcMllOF->GetHists());
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while ( h = (TH1F*)nextOF() ) {
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h->Scale(1/scale);
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}
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nextSF = TIter(mcMllSF->GetHists());
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while ( h = (TH1F*)nextSF() ) {
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h->Scale(1/scale);
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}
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mcMllSF->Modified();
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mcMllOF->Modified();
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buchmann |
1.30 |
}
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buchmann |
1.1 |
TGraphErrors* MakeErrorGraph(TH1F *histo) {
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float dx[histo->GetNbinsX()];
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float dy[histo->GetNbinsX()];
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float x[histo->GetNbinsX()];
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float y[histo->GetNbinsX()];
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for(int i=1;i<=histo->GetNbinsX();i++) {
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x[i-1]=histo->GetBinCenter(i);
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y[i-1]=histo->GetBinContent(i);
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if(i>1) dx[i-1]=(histo->GetBinCenter(i)-histo->GetBinCenter(i-1))/2.0;
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else dx[i-1]=(histo->GetBinCenter(i+1)-histo->GetBinCenter(i))/2.0;
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dy[i-1]=histo->GetBinError(i);
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}
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TGraphErrors *gr = new TGraphErrors(histo->GetNbinsX(),x,y,dx,dy);
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gr->SetFillColor(TColor::GetColor("#2E9AFE"));
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return gr;
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}
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fronga |
1.22 |
void ProduceMetPlotsWithCut(TCut cut, string name, float cutat, int njets, bool doMC = false, float ymax = 80 ) {
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buchmann |
1.30 |
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bool UseSpecialZprediction=false;
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if(cutat==100 && name=="") {
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UseSpecialZprediction=true;
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bool ReRunEstimate=false;
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//need to check if the results have already been stored; if not, need to get the estimate!
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if(MetPlotsSpace::Zestimate__data<0) ReRunEstimate=true;
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if(MetPlotsSpace::Zestimate__data_stat<0) ReRunEstimate=true;
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if(MetPlotsSpace::Zestimate__data_sys<0) ReRunEstimate=true;
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if(MetPlotsSpace::Zestimate__mc<0) ReRunEstimate=true;
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if(MetPlotsSpace::Zestimate__mc_stat<0) ReRunEstimate=true;
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if(MetPlotsSpace::Zestimate__mc_sys<0) ReRunEstimate=true;
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if(MetPlotsSpace::Zestimate__dy<0) ReRunEstimate=true;
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if(MetPlotsSpace::Zestimate__dy_stat<0) ReRunEstimate=true;
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if(MetPlotsSpace::Zestimate__dy_sys<0) ReRunEstimate=true;
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cout << "****************** About to do Z prediction " << endl;
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if(ReRunEstimate) ExperimentalMetPrediction(true);//doing quick run (i.e. only data)
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cout << "****************** Done predicting the Z " << endl;
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}
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fronga |
1.16 |
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buchmann |
1.1 |
TCanvas *tcan = new TCanvas("tcan","tcan");
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cout << "Doing met plots" << endl;
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buchmann |
1.2 |
stringstream MetBaseCuts;
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fronga |
1.7 |
MetBaseCuts << "met[4]>" << cutat << "&&" << cut.GetTitle();
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stringstream snjets;
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snjets << njets;
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buchmann |
1.2 |
TCut MetBaseCut(MetBaseCuts.str().c_str());
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fronga |
1.10 |
TCut nJetsSignal(PlottingSetup::basicqualitycut&&("pfJetGoodNum40>="+snjets.str()).c_str());
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fronga |
1.22 |
TCut nJetsControl(PlottingSetup::basiccut&&("met[4]>100&&met[4]<150&&pfJetGoodID[0]!=0&&pfJetGoodNum40=="+snjets.str()+"-1").c_str()); // Only njets vary
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fronga |
1.16 |
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if ( !PlottingSetup::openBox ) {
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buchmann |
1.34 |
nJetsSignal += TCut("mll>70");
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fronga |
1.16 |
}
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buchmann |
1.1 |
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//compute SF / OF rate in (CR1+CR2), should give 0.941 +/- 0.05
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fronga |
1.7 |
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// Create histograms
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fronga |
1.9 |
//int nbins = 30;
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int nbins = 60;
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buchmann |
1.17 |
float xmin=15., xmax = 315.;
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TH1F *mllsigEE = allsamples.Draw("mllsigEE","mll",nbins,xmin,xmax,"m_{ee} [GeV]", "events",TCut(cutOSSF&&MetBaseCut&&nJetsSignal&&"id1==0"),data,PlottingSetup::luminosity);
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TH1F *mllsigMM = allsamples.Draw("mllsigMM","mll",nbins,xmin,xmax,"m_{#mu#mu} [GeV]","events",TCut(cutOSSF&&MetBaseCut&&nJetsSignal&&"id1==1"),data,PlottingSetup::luminosity);
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fronga |
1.22 |
TH1F *mllscon = allsamples.Draw("mllscon","mll",nbins,xmin,xmax,"m_{ll} [GeV]", "events",TCut(cutOSSF&&cut&&nJetsControl),data,PlottingSetup::luminosity);
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fronga |
1.7 |
TH1F *mllOsig = allsamples.Draw("mllOsig", "mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSOF&&MetBaseCut&&nJetsSignal),data,PlottingSetup::luminosity);
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fronga |
1.22 |
TH1F *mllOscon = allsamples.Draw("mllOscon","mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSOF&&cut&&nJetsControl),data,PlottingSetup::luminosity);
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fronga |
1.7 |
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fronga |
1.8 |
TH1F* mllsig = (TH1F*)mllsigEE->Clone("mllsig");
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mllsig->Add(mllsigMM);
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mllsig->GetXaxis()->SetTitle("m_{ll} [GeV]");
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THStack *mcMllsig, *mcMllsigEE,*mcMllsigMM,*mcMllscon,*mcMllsconEE,*mcMllsconMM, *mcMllOsig, *mcMllOscon;
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fronga |
1.7 |
if ( doMC ) {
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name += "_mc";
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fronga |
1.8 |
mcMllsig = new THStack(allsamples.DrawStack("mcMllsig","mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSSF&&MetBaseCut&&nJetsSignal),mc,PlottingSetup::luminosity));
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mcMllsigEE = new THStack(allsamples.DrawStack("mcMllsigEE","mll",nbins,xmin,xmax,"m_{ee} [GeV]","events",TCut(cutOSSF&&MetBaseCut&&nJetsSignal&&"id1==0"),mc,PlottingSetup::luminosity));
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mcMllsigMM = new THStack(allsamples.DrawStack("mcMllsigMM","mll",nbins,xmin,xmax,"m_{#mu#mu} [GeV]","events",TCut(cutOSSF&&MetBaseCut&&nJetsSignal&&"id1==1"),mc,PlottingSetup::luminosity));
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fronga |
1.22 |
mcMllscon = new THStack(allsamples.DrawStack("mcMllscon","mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSSF&&cut&&nJetsControl),mc,PlottingSetup::luminosity));
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fronga |
1.8 |
mcMllOsig = new THStack(allsamples.DrawStack("mcMllOsig","mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSOF&&MetBaseCut&&nJetsSignal),mc,PlottingSetup::luminosity));
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fronga |
1.22 |
mcMllOscon= new THStack(allsamples.DrawStack("mcMllOscon","mll",nbins,xmin,xmax,"m_{ll} [GeV]","events",TCut(cutOSOF&&cut&&nJetsControl),mc,PlottingSetup::luminosity));
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fronga |
1.8 |
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fronga |
1.7 |
}
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fronga |
1.8 |
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buchmann |
1.1 |
mllOsig->SetLineColor(kRed);
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mllOscon->SetLineColor(kRed);
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buchmann |
1.28 |
TH1F *zlineshape = allsamples.Draw("zlineshape","mll",nbins,xmin,xmax,"m_{ll} (GeV)","events",cutOSSF&&TCut("pfJetGoodNum40==2")&&cut,data,PlottingSetup::luminosity);
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TH1F *Ozlineshape = allsamples.Draw("Ozlineshape","mll",nbins,xmin,xmax,"m_{ll} (GeV)","events",cutOSOF&&TCut("pfJetGoodNum40==2")&&cut,data,PlottingSetup::luminosity);
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zlineshape->Add(Ozlineshape,-1);
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| 197 |
buchmann |
1.13 |
TH1F *zlineshapeControl = (TH1F*)zlineshape->Clone("zlineshapeControl");
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| 198 |
buchmann |
1.21 |
// TH1F *zlineshapeFINE = allsamples.Draw("zlineshapeFINE","mll",50*nbins,xmin,xmax,"m_{ll} (GeV)","events",cutOSSF&&TCut("pfJetGoodNum40==1")&&cut,data,PlottingSetup::luminosity);
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//
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// float scalefactor = Get_Met_Z_Prediction(nJetsSignal,cutat, data, false) / (zlineshapeFINE->Integral(zlineshapeFINE->FindBin(91.1-20),zlineshapeFINE->FindBin(91.1+20)));
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| 201 |
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// float scalefactor_Control = Get_Met_Z_Prediction(nJetsControl,cutat, data, false) / (zlineshapeFINE->Integral(zlineshapeFINE->FindBin(91.1-20),zlineshapeFINE->FindBin(91.1+20)));
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// delete zlineshapeFINE;
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buchmann |
1.30 |
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| 206 |
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buchmann |
1.21 |
Int_t scaleBinLow = mllsig->FindBin(86);
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Int_t scaleBinHigh = mllsig->FindBin(94);
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float scalefactor = (mllsig->Integral(scaleBinLow,scaleBinHigh)-mllOsig->Integral(scaleBinLow,scaleBinHigh));
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scalefactor /= zlineshape->Integral(scaleBinLow,scaleBinHigh);
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| 211 |
buchmann |
1.30 |
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| 212 |
buchmann |
1.21 |
float scalefactor_Control = (mllscon->Integral(scaleBinLow,scaleBinHigh)-mllOscon->Integral(scaleBinLow,scaleBinHigh));
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scalefactor_Control /= zlineshapeControl->Integral(scaleBinLow,scaleBinHigh);
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| 214 |
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| 215 |
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cout << "Bins for scaling : " << scaleBinLow << " : " << scaleBinHigh << endl;
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| 216 |
buchmann |
1.30 |
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| 217 |
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if(UseSpecialZprediction) {
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| 218 |
buchmann |
1.33 |
scaleBinLow = mllsig->FindBin(81);
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scaleBinHigh = mllsig->FindBin(101);
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| 220 |
buchmann |
1.30 |
scalefactor = MetPlotsSpace::Zestimate__data/ (zlineshape->Integral(scaleBinLow,scaleBinHigh));
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cout << "Dividing: " << MetPlotsSpace::Zestimate__data << " by " << (zlineshape->Integral(scaleBinLow,scaleBinHigh)) << endl;
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| 222 |
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write_warning(__FUNCTION__,"Not using JZB prediction for control region!");
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}
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| 224 |
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| 225 |
buchmann |
1.21 |
cout << "Scale factors : " << scalefactor << " : " << scalefactor_Control << endl;
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| 226 |
buchmann |
1.30 |
if(UseSpecialZprediction) cout << " NOTE: Used JZB prediction for scaling! (Bins )" << scaleBinLow << " to " << scaleBinHigh << endl;
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| 227 |
buchmann |
1.17 |
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| 228 |
buchmann |
1.3 |
zlineshape->Scale(scalefactor);
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| 229 |
buchmann |
1.30 |
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| 230 |
buchmann |
1.3 |
zlineshape->SetLineColor(kBlue);
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zlineshape->SetLineStyle(2);
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| 233 |
buchmann |
1.30 |
if(UseSpecialZprediction) {
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//need to update each bin with correct stat uncert
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float relDYerr = MetPlotsSpace::Zestimate__data_stat/MetPlotsSpace::Zestimate__data;
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for(int iz=1;iz<=zlineshape->GetNbinsX();iz++) {
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float bincontent=zlineshape->GetBinContent(iz);
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float binerror=zlineshape->GetBinError(iz);
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float finalerr=0;
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if(bincontent>0) finalerr+= (binerror/bincontent) * (binerror/bincontent);
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if(MetPlotsSpace::Zestimate__data>0) finalerr+= relDYerr*relDYerr;
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finalerr=bincontent * TMath::Sqrt(finalerr);
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zlineshape->SetBinError(iz,finalerr);
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}
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}
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buchmann |
1.13 |
zlineshapeControl->Scale(scalefactor_Control);
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zlineshapeControl->SetLineColor(kBlue);
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zlineshapeControl->SetLineStyle(2);
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| 251 |
buchmann |
1.3 |
TH1F *subtracted = (TH1F*)mllsig->Clone("subtracted");
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| 252 |
buchmann |
1.13 |
TH1F *subtractedControl = (TH1F*)mllscon->Clone("subtractedControl");
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| 253 |
buchmann |
1.3 |
TH1F *baseline = (TH1F*)mllOsig->Clone("baseline");
|
| 254 |
buchmann |
1.13 |
TH1F *baselineControl = (TH1F*)mllOscon->Clone("baselineControl");
|
| 255 |
buchmann |
1.3 |
for(int i=1;i<=subtracted->GetNbinsX();i++) {
|
| 256 |
|
|
subtracted->SetBinContent(i,mllsig->GetBinContent(i)-mllOsig->GetBinContent(i));
|
| 257 |
buchmann |
1.13 |
subtractedControl->SetBinContent(i,mllscon->GetBinContent(i)-mllOscon->GetBinContent(i));
|
| 258 |
buchmann |
1.3 |
baseline->SetBinContent(i,0);
|
| 259 |
buchmann |
1.13 |
baselineControl->SetBinContent(i,0);
|
| 260 |
buchmann |
1.3 |
}
|
| 261 |
|
|
|
| 262 |
|
|
TH1F *prediction = (TH1F*)mllOsig->Clone("prediction");
|
| 263 |
|
|
prediction->Add(zlineshape);
|
| 264 |
|
|
prediction->SetLineColor(TColor::GetColor("#CF35CA"));
|
| 265 |
fronga |
1.7 |
|
| 266 |
|
|
TH1F *control_prediction = (TH1F*)mllOscon->Clone("control_prediction");
|
| 267 |
|
|
control_prediction->SetLineColor(TColor::GetColor("#CF35CA"));
|
| 268 |
|
|
|
| 269 |
|
|
// FIX Y RANGE TO EASE COMPARISON
|
| 270 |
fronga |
1.22 |
mllsig->SetMaximum(ymax);
|
| 271 |
buchmann |
1.30 |
float PreviousMinimum=mllsig->GetMinimum();
|
| 272 |
|
|
mllsig->SetMinimum(0);
|
| 273 |
fronga |
1.22 |
mllsigEE->SetMaximum(ymax);
|
| 274 |
|
|
mllsigMM->SetMaximum(ymax);
|
| 275 |
|
|
mllOsig->SetMaximum(ymax);
|
| 276 |
|
|
mllOscon->SetMaximum(ymax);
|
| 277 |
|
|
subtracted->SetMaximum(60);
|
| 278 |
|
|
subtracted->SetMinimum(-30);
|
| 279 |
|
|
subtractedControl->SetMaximum(65);
|
| 280 |
|
|
subtractedControl->SetMinimum(-30);
|
| 281 |
fronga |
1.7 |
|
| 282 |
buchmann |
1.3 |
|
| 283 |
fronga |
1.7 |
// 1.- Signal region comparison
|
| 284 |
buchmann |
1.30 |
TBox *srbox = new TBox(20,0,70,mllsig->GetMaximum());
|
| 285 |
buchmann |
1.1 |
srbox->SetFillStyle(0);
|
| 286 |
|
|
srbox->SetLineColor(TColor::GetColor("#298A08"));
|
| 287 |
|
|
srbox->SetLineWidth(3);
|
| 288 |
buchmann |
1.23 |
|
| 289 |
fronga |
1.10 |
|
| 290 |
buchmann |
1.2 |
stringstream MetHeader;
|
| 291 |
fronga |
1.19 |
MetHeader << "N_{j}#geq" << snjets.str() << ", MET>" << cutat << " GeV";
|
| 292 |
|
|
stringstream MetHeaderCon;
|
| 293 |
fronga |
1.22 |
MetHeaderCon << "N_{j}=" << njets-1 << ", 100<MET<150 GeV";
|
| 294 |
fronga |
1.10 |
stringstream saveasSig;
|
| 295 |
|
|
saveasSig << "MetPlots/mll_sig" << cutat << "__" << name;
|
| 296 |
|
|
|
| 297 |
|
|
TLegend* leg;
|
| 298 |
|
|
if ( !doMC ) {
|
| 299 |
|
|
tcan->cd();
|
| 300 |
|
|
//mllsig->GetYaxis()->SetRangeUser(0,mllsig->GetMaximum()*1.2);
|
| 301 |
|
|
mllsig->Draw();
|
| 302 |
|
|
TGraphErrors *stat3j = MakeErrorGraph(prediction);
|
| 303 |
|
|
stat3j->Draw("2,same");
|
| 304 |
|
|
mllOsig->Draw("histo,same");
|
| 305 |
|
|
zlineshape->Draw("histo,same");
|
| 306 |
|
|
prediction->Draw("histo,same");
|
| 307 |
|
|
mllsig->Draw("same");
|
| 308 |
|
|
DrawPrelim();
|
| 309 |
|
|
leg = make_legend();
|
| 310 |
fronga |
1.19 |
leg->SetX1(0.52);
|
| 311 |
|
|
leg->SetHeader(MetHeader.str().c_str());
|
| 312 |
fronga |
1.10 |
leg->AddEntry(mllsig,"Data","PL");
|
| 313 |
|
|
leg->AddEntry(prediction,"All bg prediction","L");
|
| 314 |
fronga |
1.7 |
leg->AddEntry(mllOsig,"bg without Z","L");
|
| 315 |
buchmann |
1.30 |
if(!UseSpecialZprediction) leg->AddEntry(zlineshape,"Z lineshape","L");
|
| 316 |
|
|
else leg->AddEntry(zlineshape,"bg with Z (JZB)","L");
|
| 317 |
fronga |
1.7 |
leg->AddEntry(stat3j,"stat. uncert.","F");
|
| 318 |
fronga |
1.10 |
leg->AddEntry(srbox,"SR","F");
|
| 319 |
|
|
leg->Draw();
|
| 320 |
|
|
srbox->Draw();
|
| 321 |
|
|
CompleteSave(tcan,saveasSig.str());
|
| 322 |
|
|
} else {
|
| 323 |
fronga |
1.19 |
|
| 324 |
fronga |
1.10 |
TPad* rcan = new TPad("rcan","rcan",0,0,1,1);
|
| 325 |
|
|
rcan->cd();
|
| 326 |
|
|
mllsig->Draw();
|
| 327 |
|
|
mcMllsig->Draw("same");
|
| 328 |
|
|
prediction->Draw("histo,same");
|
| 329 |
|
|
mllsig->Draw("same");
|
| 330 |
|
|
DrawPrelim();
|
| 331 |
|
|
leg = allsamples.allbglegend();
|
| 332 |
fronga |
1.19 |
leg->SetHeader(MetHeader.str().c_str());
|
| 333 |
|
|
leg->SetX1(0.52);
|
| 334 |
fronga |
1.10 |
leg->AddEntry(prediction,"All bg prediction","L");
|
| 335 |
|
|
leg->AddEntry(srbox,"SR","F");
|
| 336 |
|
|
leg->Draw();
|
| 337 |
|
|
srbox->Draw();
|
| 338 |
|
|
save_with_ratio( mllsig, *mcMllsig, rcan, saveasSig.str() );
|
| 339 |
buchmann |
1.30 |
|
| 340 |
|
|
ExtractScaleFactor(mllsig,mllOsig,mcMllsig,mcMllOsig,prediction,leg,saveasSig.str(),srbox);
|
| 341 |
fronga |
1.7 |
}
|
| 342 |
buchmann |
1.1 |
|
| 343 |
fronga |
1.8 |
// 1b. MC: split ee and mumu
|
| 344 |
|
|
if ( doMC ) {
|
| 345 |
fronga |
1.10 |
TPad* rcan = new TPad("rcan","rcan",0,0,1,1);
|
| 346 |
|
|
rcan->cd();
|
| 347 |
fronga |
1.8 |
mllsigEE->Draw();
|
| 348 |
|
|
mcMllsigEE->Draw("same");
|
| 349 |
|
|
mllsigEE->Draw("same");
|
| 350 |
|
|
DrawPrelim();
|
| 351 |
|
|
leg->Draw();
|
| 352 |
|
|
srbox->Draw();
|
| 353 |
fronga |
1.10 |
save_with_ratio( mllsigEE, *mcMllsigEE,rcan->cd(),saveasSig.str()+"_ee" );
|
| 354 |
fronga |
1.8 |
|
| 355 |
fronga |
1.10 |
rcan = new TPad("rcan","rcan",0,0,1,1);
|
| 356 |
|
|
rcan->cd();
|
| 357 |
fronga |
1.8 |
mllsigMM->Draw();
|
| 358 |
|
|
mcMllsigMM->Draw("same");
|
| 359 |
|
|
mllsigMM->Draw("same");
|
| 360 |
|
|
DrawPrelim();
|
| 361 |
|
|
leg->Draw();
|
| 362 |
|
|
srbox->Draw();
|
| 363 |
fronga |
1.10 |
save_with_ratio( mllsigMM, *mcMllsigMM,rcan,saveasSig.str()+"_mm" );
|
| 364 |
fronga |
1.8 |
}
|
| 365 |
fronga |
1.14 |
|
| 366 |
|
|
// 1c. MC: compare of and sf
|
| 367 |
|
|
if ( doMC ) {
|
| 368 |
|
|
TH1F* hMcMllsig = CollapseStack( *mcMllsig);
|
| 369 |
fronga |
1.15 |
leg = allsamples.allbglegend("");
|
| 370 |
fronga |
1.19 |
leg->SetHeader(MetHeader.str().c_str());
|
| 371 |
fronga |
1.15 |
// Change "Data" label by hand
|
| 372 |
|
|
((TLegendEntry*)leg->GetListOfPrimitives()->At(0))->SetLabel("Same-flavor (MC)");
|
| 373 |
fronga |
1.14 |
TPad* rcan = new TPad("rcan","rcan",0,0,1,1);
|
| 374 |
|
|
rcan->cd();
|
| 375 |
fronga |
1.22 |
hMcMllsig->SetMaximum(ymax);
|
| 376 |
fronga |
1.14 |
hMcMllsig->Draw("E");
|
| 377 |
|
|
mcMllOsig->Draw("same,hist");
|
| 378 |
|
|
hMcMllsig->Draw("same,E");
|
| 379 |
|
|
DrawMCPrelim();
|
| 380 |
fronga |
1.19 |
leg->SetX1(0.52);
|
| 381 |
fronga |
1.14 |
leg->AddEntry(srbox,"SR","F");
|
| 382 |
|
|
leg->Draw();
|
| 383 |
|
|
srbox->Draw();
|
| 384 |
|
|
save_with_ratio( hMcMllsig, *mcMllOsig, rcan, saveasSig.str()+"_mconly");
|
| 385 |
|
|
|
| 386 |
|
|
}
|
| 387 |
buchmann |
1.1 |
|
| 388 |
fronga |
1.7 |
// 2.- Signal region comparison - LOG scale
|
| 389 |
fronga |
1.10 |
if ( !doMC ) {
|
| 390 |
|
|
tcan->cd();
|
| 391 |
|
|
mllsig->SetMinimum(0.2); // FIX Y RANGE TO EASE COMPARISON
|
| 392 |
|
|
//mllsig->SetMaximum(mllsig->GetMaximum()*4.0);
|
| 393 |
|
|
srbox->SetY2(mllsig->GetMaximum());
|
| 394 |
|
|
tcan->SetLogy(1);
|
| 395 |
|
|
stringstream saveasSig2;
|
| 396 |
|
|
saveasSig2 << "MetPlots/mll_sig_ZLINESHAPE_" << cutat << "__" << name;
|
| 397 |
|
|
|
| 398 |
|
|
CompleteSave(tcan,saveasSig2.str());
|
| 399 |
|
|
tcan->SetLogy(0);
|
| 400 |
|
|
}
|
| 401 |
buchmann |
1.1 |
|
| 402 |
fronga |
1.7 |
|
| 403 |
|
|
// 3.- Signal region, background subtracted
|
| 404 |
fronga |
1.8 |
if ( !doMC ) {
|
| 405 |
fronga |
1.10 |
tcan->cd();
|
| 406 |
buchmann |
1.13 |
for(int i=1;i<=subtracted->GetNbinsX();i++) {
|
| 407 |
fronga |
1.8 |
subtracted->SetBinContent(i,subtracted->GetBinContent(i)-zlineshape->GetBinContent(i));
|
| 408 |
buchmann |
1.13 |
subtractedControl->SetBinContent(i,subtractedControl->GetBinContent(i)-zlineshapeControl->GetBinContent(i));
|
| 409 |
fronga |
1.8 |
}
|
| 410 |
buchmann |
1.3 |
|
| 411 |
fronga |
1.8 |
TGraphErrors *subtrerr = MakeErrorGraph(baseline);
|
| 412 |
|
|
subtracted->Draw();
|
| 413 |
|
|
subtrerr->Draw("2,same");
|
| 414 |
|
|
subtracted->Draw("same");
|
| 415 |
|
|
DrawPrelim();
|
| 416 |
|
|
TLegend *DiffLeg = make_legend();
|
| 417 |
fronga |
1.22 |
DiffLeg->SetX1(0.4);
|
| 418 |
fronga |
1.8 |
DiffLeg->SetFillStyle(0);
|
| 419 |
fronga |
1.19 |
DiffLeg->SetHeader(MetHeader.str().c_str());
|
| 420 |
fronga |
1.8 |
DiffLeg->AddEntry(subtracted,"observed - predicted","PL");
|
| 421 |
fronga |
1.19 |
DiffLeg->AddEntry(subtrerr,"stat. uncert","F");
|
| 422 |
fronga |
1.8 |
DiffLeg->AddEntry((TObject*)0,"","");
|
| 423 |
|
|
DiffLeg->AddEntry((TObject*)0,"","");
|
| 424 |
|
|
DiffLeg->Draw();
|
| 425 |
|
|
|
| 426 |
|
|
stringstream saveasSigSub;
|
| 427 |
|
|
saveasSigSub << "MetPlots/mll_sig_SUBTRACTED_" << cutat << "__" << name;
|
| 428 |
|
|
|
| 429 |
fronga |
1.22 |
//CompleteSave(tcan,saveasSigSub.str());
|
| 430 |
buchmann |
1.13 |
|
| 431 |
|
|
// 3a.- Control region, background subtracted
|
| 432 |
|
|
TGraphErrors *subtrerrControl = MakeErrorGraph(baselineControl);
|
| 433 |
|
|
subtractedControl->Draw();
|
| 434 |
|
|
subtrerrControl->Draw("2,same");
|
| 435 |
|
|
subtractedControl->Draw("same");
|
| 436 |
|
|
DrawPrelim();
|
| 437 |
fronga |
1.19 |
DiffLeg->SetHeader(MetHeaderCon.str().c_str());
|
| 438 |
buchmann |
1.13 |
DiffLeg->Draw();
|
| 439 |
|
|
saveasSigSub.str("");
|
| 440 |
fronga |
1.16 |
saveasSigSub << "MetPlots/mll_con_SUBTRACTED_" << cutat << "__" << name;
|
| 441 |
fronga |
1.22 |
//CompleteSave(tcan,saveasSigSub.str());
|
| 442 |
buchmann |
1.13 |
|
| 443 |
|
|
|
| 444 |
|
|
|
| 445 |
fronga |
1.8 |
// 4.- Signal region, background subtracted, errors added in quadrature
|
| 446 |
|
|
TGraphErrors *subtrerr2 = (TGraphErrors*)subtrerr->Clone("subtrerr2");
|
| 447 |
buchmann |
1.13 |
for(int i=1;i<=subtrerr2->GetN();i++) {
|
| 448 |
|
|
subtrerr2->SetPoint(i-1,subtracted->GetBinCenter(i),subtracted->GetBinContent(i));
|
| 449 |
|
|
subtrerr2->SetPointError(i-1,subtrerr2->GetErrorX(i),TMath::Sqrt(subtrerr2->GetErrorY(i)*subtrerr2->GetErrorY(i)+subtracted->GetBinError(i)*subtracted->GetBinError(i)));
|
| 450 |
fronga |
1.8 |
}
|
| 451 |
|
|
TLine* l = new TLine(subtracted->GetBinLowEdge(1),0.,subtracted->GetBinLowEdge(subtracted->GetNbinsX()-1)+subtracted->GetBinWidth(1),0.);
|
| 452 |
|
|
l->SetLineWidth(subtracted->GetLineWidth());
|
| 453 |
|
|
subtracted->Draw();
|
| 454 |
|
|
subtrerr2->Draw("2,same");
|
| 455 |
|
|
l->Draw("same");
|
| 456 |
|
|
subtracted->Draw("same");
|
| 457 |
|
|
DrawPrelim();
|
| 458 |
|
|
TLegend *DiffLeg2 = make_legend();
|
| 459 |
fronga |
1.22 |
DiffLeg2->SetX1(0.4);
|
| 460 |
fronga |
1.19 |
DiffLeg2->SetHeader(MetHeader.str().c_str());
|
| 461 |
fronga |
1.8 |
DiffLeg2->SetFillStyle(0);
|
| 462 |
|
|
DiffLeg2->AddEntry(subtracted,"observed - predicted","PL");
|
| 463 |
fronga |
1.19 |
DiffLeg2->AddEntry(subtrerr2,"stat. uncert","F");
|
| 464 |
fronga |
1.8 |
DiffLeg2->AddEntry((TObject*)0,"","");
|
| 465 |
|
|
DiffLeg2->AddEntry((TObject*)0,"","");
|
| 466 |
|
|
DiffLeg2->Draw();
|
| 467 |
|
|
|
| 468 |
|
|
stringstream saveasSigSub2;
|
| 469 |
|
|
saveasSigSub2 << "MetPlots/mll_sig_SUBTRACTED_quadr_" << cutat << "__" << name;
|
| 470 |
fronga |
1.5 |
|
| 471 |
fronga |
1.8 |
CompleteSave(tcan,saveasSigSub2.str());
|
| 472 |
fronga |
1.5 |
|
| 473 |
buchmann |
1.13 |
|
| 474 |
|
|
|
| 475 |
|
|
//4a.- Control region, background subtracted, errors added in quadrature
|
| 476 |
|
|
TGraphErrors *subtrerr2Control = (TGraphErrors*)subtrerrControl->Clone("subtrerr2Control");
|
| 477 |
|
|
for(int i=1;i<=subtrerr2Control->GetN();i++) {
|
| 478 |
|
|
subtrerr2Control->SetPoint(i-1,subtractedControl->GetBinCenter(i),subtractedControl->GetBinContent(i));
|
| 479 |
|
|
float width=subtrerr2Control->GetErrorX(i);
|
| 480 |
|
|
if(i==subtrerr2Control->GetN()) width=subtrerr2Control->GetErrorX(i-1);
|
| 481 |
|
|
subtrerr2Control->SetPointError(i-1,width,TMath::Sqrt(subtrerr2Control->GetErrorY(i)*subtrerr2Control->GetErrorY(i)+subtractedControl->GetBinError(i)*subtractedControl->GetBinError(i)));
|
| 482 |
|
|
}
|
| 483 |
|
|
TLine* lControl = new TLine(subtractedControl->GetBinLowEdge(1),0.,subtractedControl->GetBinLowEdge(subtractedControl->GetNbinsX()-1)+subtractedControl->GetBinWidth(1),0.);
|
| 484 |
|
|
lControl->SetLineWidth(subtractedControl->GetLineWidth());
|
| 485 |
|
|
subtractedControl->Draw();
|
| 486 |
|
|
subtrerr2Control->Draw("2,same");
|
| 487 |
|
|
lControl->Draw("same");
|
| 488 |
|
|
subtractedControl->Draw("same");
|
| 489 |
|
|
DrawPrelim();
|
| 490 |
fronga |
1.22 |
DiffLeg2->SetHeader(MetHeaderCon.str().c_str());
|
| 491 |
buchmann |
1.13 |
DiffLeg2->Draw();
|
| 492 |
|
|
|
| 493 |
|
|
saveasSigSub2.str("");
|
| 494 |
fronga |
1.16 |
saveasSigSub2 << "MetPlots/mll_con_SUBTRACTED_quadr_" << cutat << "__" << name;
|
| 495 |
buchmann |
1.13 |
|
| 496 |
|
|
CompleteSave(tcan,saveasSigSub2.str());
|
| 497 |
|
|
|
| 498 |
fronga |
1.8 |
delete DiffLeg;
|
| 499 |
|
|
delete DiffLeg2;
|
| 500 |
buchmann |
1.13 |
|
| 501 |
fronga |
1.8 |
} // !doMC
|
| 502 |
buchmann |
1.3 |
|
| 503 |
|
|
|
| 504 |
fronga |
1.7 |
// 5.- Control region comparison
|
| 505 |
fronga |
1.16 |
// scalefactor = (mllscon->Integral(scaleBinLow,scaleBinHigh)-mllOscon->Integral(scaleBinLow,scaleBinHigh));
|
| 506 |
|
|
// scalefactor /= zlineshape->Integral(scaleBinLow,scaleBinHigh);
|
| 507 |
|
|
// zlineshape->Scale(scalefactor);
|
| 508 |
|
|
control_prediction->Add(zlineshapeControl);
|
| 509 |
|
|
|
| 510 |
fronga |
1.22 |
control_prediction->SetMaximum(ymax); // FIX MAXIMUM TO EASE COMPARISON
|
| 511 |
fronga |
1.7 |
|
| 512 |
fronga |
1.14 |
TBox *cr1box = new TBox(xmin,0,70,control_prediction->GetMaximum());
|
| 513 |
buchmann |
1.1 |
cr1box->SetFillStyle(0);
|
| 514 |
|
|
cr1box->SetLineColor(TColor::GetColor("#0404B4"));
|
| 515 |
|
|
cr1box->SetLineWidth(3);
|
| 516 |
|
|
|
| 517 |
fronga |
1.14 |
TBox *cr2box = new TBox(120,0,xmax,control_prediction->GetMaximum());
|
| 518 |
buchmann |
1.1 |
cr2box->SetFillStyle(0);
|
| 519 |
|
|
cr2box->SetLineColor(TColor::GetColor("#0404B4"));
|
| 520 |
|
|
cr2box->SetLineWidth(3);
|
| 521 |
|
|
cr2box->SetLineStyle(2);
|
| 522 |
|
|
|
| 523 |
fronga |
1.10 |
stringstream saveasCon;
|
| 524 |
|
|
saveasCon << "MetPlots/mll_con" << cutat << "__" << name;
|
| 525 |
|
|
|
| 526 |
fronga |
1.7 |
TLegend *legc;
|
| 527 |
fronga |
1.10 |
//control_prediction->GetYaxis()->SetRangeUser(0,control_prediction->GetMaximum()*1.3);
|
| 528 |
|
|
if ( !doMC ) {
|
| 529 |
|
|
tcan->cd();
|
| 530 |
|
|
control_prediction->Draw("hist");
|
| 531 |
|
|
TGraphErrors *stat2j = MakeErrorGraph(control_prediction);
|
| 532 |
|
|
stat2j->Draw("2,same");
|
| 533 |
|
|
mllOscon->Draw("same,hist");
|
| 534 |
fronga |
1.16 |
zlineshapeControl->Draw("histo,same");
|
| 535 |
fronga |
1.10 |
control_prediction->Draw("histo,same");
|
| 536 |
|
|
mllscon->Draw("same");
|
| 537 |
|
|
DrawPrelim();
|
| 538 |
fronga |
1.7 |
legc = make_legend();
|
| 539 |
fronga |
1.19 |
legc->SetX1(0.52);
|
| 540 |
|
|
legc->SetHeader(MetHeaderCon.str().c_str());
|
| 541 |
fronga |
1.10 |
legc->AddEntry(mllscon,"Data","PL");
|
| 542 |
|
|
legc->AddEntry(control_prediction,"All bg","L");
|
| 543 |
fronga |
1.16 |
legc->AddEntry(zlineshapeControl,"Z lineshape","L");
|
| 544 |
fronga |
1.7 |
legc->AddEntry(mllOscon,"bg without Z","L");
|
| 545 |
|
|
legc->AddEntry(stat2j,"stat. uncert.","F");
|
| 546 |
fronga |
1.10 |
legc->AddEntry(cr1box,"CR1","F");
|
| 547 |
|
|
legc->AddEntry(cr2box,"CR2","F");
|
| 548 |
|
|
legc->Draw();
|
| 549 |
|
|
cr1box->Draw();
|
| 550 |
|
|
cr2box->Draw();
|
| 551 |
|
|
CompleteSave(tcan,saveasCon.str());
|
| 552 |
|
|
} else {
|
| 553 |
|
|
TPad* rcan = new TPad("rcan","rcan",0,0,1,1);
|
| 554 |
|
|
rcan->cd();
|
| 555 |
|
|
control_prediction->Draw("hist");
|
| 556 |
|
|
mcMllscon->Draw("same");
|
| 557 |
|
|
control_prediction->Draw("histo,same");
|
| 558 |
|
|
mllscon->Draw("same");
|
| 559 |
|
|
DrawPrelim();
|
| 560 |
|
|
legc = allsamples.allbglegend();
|
| 561 |
fronga |
1.19 |
legc->SetX1(0.52);
|
| 562 |
|
|
legc->SetHeader(MetHeaderCon.str().c_str());
|
| 563 |
fronga |
1.10 |
legc->AddEntry(control_prediction,"All bg","L");
|
| 564 |
|
|
legc->AddEntry(cr1box,"CR1","F");
|
| 565 |
|
|
legc->AddEntry(cr2box,"CR2","F");
|
| 566 |
|
|
legc->Draw();
|
| 567 |
|
|
cr1box->Draw();
|
| 568 |
|
|
cr2box->Draw();
|
| 569 |
|
|
save_with_ratio( mllscon, *mcMllscon, rcan, saveasCon.str());
|
| 570 |
|
|
}
|
| 571 |
buchmann |
1.1 |
|
| 572 |
fronga |
1.7 |
// 6. - Opposite-flavour data/MC comparison
|
| 573 |
|
|
if ( doMC ) {
|
| 574 |
fronga |
1.10 |
TPad* rcan = new TPad("rcan","rcan",0,0,1,1);
|
| 575 |
|
|
rcan->cd();
|
| 576 |
fronga |
1.7 |
mllOsig->SetLineColor(kBlack);
|
| 577 |
|
|
mllOsig->Draw();
|
| 578 |
|
|
mcMllOsig->Draw("same");
|
| 579 |
|
|
mllOsig->Draw("same");
|
| 580 |
|
|
TLegend *legsdm = allsamples.allbglegend();
|
| 581 |
fronga |
1.19 |
legsdm->SetHeader((MetHeader.str()+", OF").c_str());
|
| 582 |
|
|
legsdm->SetX1(0.52);
|
| 583 |
fronga |
1.7 |
legsdm->Draw();
|
| 584 |
|
|
stringstream saveasSigOF;
|
| 585 |
|
|
saveasSigOF << "MetPlots/mll_sig_of_" << cutat << "__" << name;
|
| 586 |
fronga |
1.10 |
save_with_ratio( mllOsig, *mcMllOsig, rcan, saveasSigOF.str());
|
| 587 |
fronga |
1.7 |
|
| 588 |
fronga |
1.10 |
rcan = new TPad("rcan","rcan",0,0,1,1);
|
| 589 |
|
|
rcan->cd();
|
| 590 |
fronga |
1.7 |
mllOscon->SetLineColor(kBlack);
|
| 591 |
|
|
mllOscon->Draw();
|
| 592 |
|
|
mcMllOscon->Draw("same");
|
| 593 |
|
|
mllOscon->Draw("same");
|
| 594 |
|
|
TLegend *legcdm = allsamples.allbglegend();
|
| 595 |
fronga |
1.19 |
legcdm->SetHeader((MetHeaderCon.str()+", OF").c_str());
|
| 596 |
|
|
legcdm->SetX1(0.52);
|
| 597 |
fronga |
1.7 |
legcdm->Draw();
|
| 598 |
|
|
stringstream saveasConOF;
|
| 599 |
|
|
saveasConOF << "MetPlots/mll_con_of_" << cutat << "__" << name;
|
| 600 |
fronga |
1.10 |
save_with_ratio( mllOscon, *mcMllOscon, rcan, saveasConOF.str());
|
| 601 |
|
|
|
| 602 |
fronga |
1.7 |
delete legsdm;
|
| 603 |
|
|
delete legcdm;
|
| 604 |
fronga |
1.10 |
}
|
| 605 |
fronga |
1.7 |
|
| 606 |
fronga |
1.10 |
// Memory clean-up
|
| 607 |
|
|
if (doMC) {
|
| 608 |
fronga |
1.7 |
delete mcMllscon;
|
| 609 |
|
|
delete mcMllOscon;
|
| 610 |
|
|
delete mcMllsig;
|
| 611 |
fronga |
1.8 |
delete mcMllsigEE;
|
| 612 |
|
|
delete mcMllsigMM;
|
| 613 |
fronga |
1.7 |
delete mcMllOsig;
|
| 614 |
|
|
}
|
| 615 |
buchmann |
1.1 |
|
| 616 |
|
|
delete cr1box;
|
| 617 |
|
|
delete cr2box;
|
| 618 |
|
|
delete srbox;
|
| 619 |
|
|
delete legc;
|
| 620 |
|
|
delete leg;
|
| 621 |
fronga |
1.7 |
|
| 622 |
buchmann |
1.1 |
delete mllscon;
|
| 623 |
|
|
delete mllOscon;
|
| 624 |
|
|
delete mllsig;
|
| 625 |
fronga |
1.8 |
delete mllsigEE;
|
| 626 |
|
|
delete mllsigMM;
|
| 627 |
buchmann |
1.1 |
delete mllOsig;
|
| 628 |
fronga |
1.7 |
delete zlineshape;
|
| 629 |
fronga |
1.16 |
delete zlineshapeControl;
|
| 630 |
buchmann |
1.6 |
delete tcan;
|
| 631 |
buchmann |
1.1 |
}
|
| 632 |
|
|
|
| 633 |
fronga |
1.14 |
void DoMetPlots(string datajzb, string mcjzb) {
|
| 634 |
buchmann |
1.27 |
switch_overunderflow(true);
|
| 635 |
fronga |
1.7 |
float metCuts[] = { 100., 150. };
|
| 636 |
fronga |
1.22 |
float ymax[] = { 90., 80. };
|
| 637 |
fronga |
1.7 |
int jetCuts[] = { 3, 2 };
|
| 638 |
fronga |
1.11 |
//int jetCuts[] = { 3, 3 };
|
| 639 |
buchmann |
1.35 |
string leptCuts[] = { "pt1>20&&pt2>20", "pt1>20&&pt2>10&&pfTightHT>100" };
|
| 640 |
fronga |
1.7 |
bool nomc(0),domc(1);
|
| 641 |
|
|
for ( int i=0; i<2; ++i ) {
|
| 642 |
buchmann |
1.33 |
// ProduceMetPlotsWithCut(TCut(("mll>15&&"+leptCuts[i]).c_str()),"",metCuts[i],jetCuts[i],nomc,ymax[i]);
|
| 643 |
fronga |
1.22 |
ProduceMetPlotsWithCut(TCut(("mll>15&&"+leptCuts[i]).c_str()),"",metCuts[i],jetCuts[i],domc,ymax[i]);
|
| 644 |
|
|
continue;
|
| 645 |
fronga |
1.19 |
// stringstream jzbcut;
|
| 646 |
|
|
// jzbcut << "((is_data&&("<<datajzb<<")>0)||(!is_data&&("<<mcjzb<<")>0))";
|
| 647 |
|
|
// ProduceMetPlotsWithCut(TCut((jzbcut.str()+"&&mll>20&&"+leptCuts[i]).c_str()),"JZBpos",metCuts[i], jetCuts[i],domc);
|
| 648 |
fronga |
1.11 |
//continue;
|
| 649 |
fronga |
1.7 |
if (!PlottingSetup::is53reco) { // Old 5_2
|
| 650 |
fronga |
1.22 |
ProduceMetPlotsWithCut(TCut(("mll>15&&pfJetGoodNumBtag==0&&"+leptCuts[i]).c_str()),"bTagVeto30",metCuts[i], jetCuts[i], nomc,ymax[i]);
|
| 651 |
|
|
ProduceMetPlotsWithCut(TCut(("mll>15&&pfJetGoodNumBtag>0&&"+leptCuts[i]).c_str()),"AtLeastOneBJet30",metCuts[i],jetCuts[i], nomc,ymax[i]);
|
| 652 |
|
|
ProduceMetPlotsWithCut(TCut(("mll>15&&pfJetGoodNumBtag==0&&"+leptCuts[i]).c_str()),"bTagVeto30",metCuts[i], jetCuts[i], domc,ymax[i]);
|
| 653 |
|
|
ProduceMetPlotsWithCut(TCut(("mll>15&&pfJetGoodNumBtag>0&&"+leptCuts[i]).c_str()),"AtLeastOneBJet30",metCuts[i],jetCuts[i], domc,ymax[i]);
|
| 654 |
fronga |
1.7 |
} else {
|
| 655 |
fronga |
1.22 |
ProduceMetPlotsWithCut(TCut(("mll>15&&pfJetGoodNumBtag30==0&&"+leptCuts[i]).c_str()),"bTagVeto30",metCuts[i], jetCuts[i],nomc,ymax[i]);
|
| 656 |
|
|
ProduceMetPlotsWithCut(TCut(("mll>15&&pfJetGoodNumBtag30>0&&"+leptCuts[i]).c_str()),"AtLeastOneBJet30",metCuts[i],jetCuts[i],nomc,ymax[i]);
|
| 657 |
|
|
ProduceMetPlotsWithCut(TCut(("mll>15&&pfJetGoodNumBtag30==0&&"+leptCuts[i]).c_str()),"bTagVeto30",metCuts[i], jetCuts[i],domc,ymax[i]);
|
| 658 |
|
|
ProduceMetPlotsWithCut(TCut(("mll>15&&pfJetGoodNumBtag30>0&&"+leptCuts[i]).c_str()),"AtLeastOneBJet30",metCuts[i], jetCuts[i],domc,ymax[i]);
|
| 659 |
fronga |
1.7 |
}
|
| 660 |
|
|
}
|
| 661 |
buchmann |
1.27 |
switch_overunderflow(false);
|
| 662 |
buchmann |
1.1 |
}
|
| 663 |
buchmann |
1.12 |
|
| 664 |
buchmann |
1.13 |
void compute_r_in_out() {
|
| 665 |
|
|
int nbins=10;
|
| 666 |
|
|
float xmin=10;
|
| 667 |
|
|
float xmax=10;
|
| 668 |
buchmann |
1.33 |
TCut InCut("mll>81&&mll<101&&pfJetGoodNum40>0");
|
| 669 |
buchmann |
1.13 |
TCut OutCut("mll>20&&mll<70&&pfJetGoodNum40>0");
|
| 670 |
|
|
|
| 671 |
|
|
TH1F *mllIN =allsamples.Draw("mllIN", "mll",nbins,xmin,xmax,"m_{ee} [GeV]", "events",TCut(cutOSSF&&InCut),mc,PlottingSetup::luminosity,allsamples.FindSample("DYJetsToLLNoTau"));
|
| 672 |
|
|
TH1F *mllOUT =allsamples.Draw("mllOUT","mll",nbins,xmin,xmax,"m_{ee} [GeV]", "events",TCut(cutOSSF&&OutCut),mc,PlottingSetup::luminosity,allsamples.FindSample("DYJetsToLLNoTau"));
|
| 673 |
|
|
|
| 674 |
|
|
cout << "IN: " << mllIN->Integral() << endl;
|
| 675 |
|
|
cout << "OUT: " << mllOUT->Integral() << endl;
|
| 676 |
|
|
cout << "r_oi: " <<((float) mllOUT->Integral()) / mllIN->Integral()<< endl;
|
| 677 |
|
|
|
| 678 |
|
|
delete mllIN;
|
| 679 |
|
|
delete mllOUT;
|
| 680 |
|
|
|
| 681 |
|
|
}
|
| 682 |
|
|
|
| 683 |
buchmann |
1.17 |
|
| 684 |
|
|
|
| 685 |
|
|
void LabelHisto(TH1 *MET_ratio,string titlex, string titley) {
|
| 686 |
|
|
MET_ratio->GetXaxis()->SetTitle(titlex.c_str());
|
| 687 |
|
|
MET_ratio->GetXaxis()->CenterTitle();
|
| 688 |
|
|
MET_ratio->GetYaxis()->SetTitle(titley.c_str());
|
| 689 |
|
|
MET_ratio->GetYaxis()->CenterTitle();
|
| 690 |
|
|
}
|
| 691 |
|
|
|
| 692 |
buchmann |
1.23 |
TH1F* GetPredictedAndObservedMetShapes(TCut JetCut, string sPositiveCut,string sNegativeCut,string CorrectedMet,string ObservedMet, string JZBPosvar, string JZBNegvar, float MetCut, int is_data, bool isDYonly, bool isAachen) {
|
| 693 |
buchmann |
1.17 |
|
| 694 |
|
|
//Steps:
|
| 695 |
|
|
// 1) Prepare samples and histo definition (with "optimal" binning for MET cut)
|
| 696 |
|
|
// 2) Fill MET histograms
|
| 697 |
|
|
// 3) Fill JZB histograms
|
| 698 |
|
|
// 4) Draw them and store them
|
| 699 |
|
|
// 5) return predicted MET distribution as is (i.e. not scaled by factor of 2!)
|
| 700 |
|
|
|
| 701 |
buchmann |
1.24 |
cout << "*************************************" << endl;
|
| 702 |
buchmann |
1.26 |
// cout << "** SUMMARY BEFORE STARTING DRAWING **" << endl;
|
| 703 |
|
|
// cout << "MET variable: " << ObservedMet << endl;
|
| 704 |
|
|
// cout << "Corr. MET var:" << CorrectedMet << endl;
|
| 705 |
|
|
// cout << "JZB pos. var: " << JZBPosvar << endl;
|
| 706 |
|
|
// cout << "JZB neg. var: " << JZBNegvar << endl;
|
| 707 |
|
|
// cout << "JZB pos cut : " << sPositiveCut << endl;
|
| 708 |
|
|
// cout << "JZB neg cut : " << sNegativeCut << endl;
|
| 709 |
buchmann |
1.30 |
|
| 710 |
|
|
|
| 711 |
|
|
if(isAachen) MetPlotsSpace::Zprediction_Uncertainty=0.3;
|
| 712 |
buchmann |
1.17 |
//Step 1: Prepare samples and histo definition
|
| 713 |
|
|
vector<int> SelectedSamples;
|
| 714 |
|
|
if(is_data==mc&&isDYonly) {
|
| 715 |
|
|
SelectedSamples=allsamples.FindSample("Z_em_DYJetsToL");
|
| 716 |
|
|
if(SelectedSamples.size()==0) {
|
| 717 |
|
|
write_error(__FUNCTION__,"Cannot continue, there seems to be no DY sample without Taus - goodbye!");
|
| 718 |
|
|
assert(SelectedSamples.size()>0);
|
| 719 |
|
|
}
|
| 720 |
|
|
}
|
| 721 |
|
|
|
| 722 |
|
|
float DisplayedBinSize=10.0; // this is the bin size that we use for plotting
|
| 723 |
|
|
|
| 724 |
buchmann |
1.21 |
float BinWidth=1.0;
|
| 725 |
buchmann |
1.17 |
float xmin=0;
|
| 726 |
buchmann |
1.23 |
float xmax=110;
|
| 727 |
|
|
if(isAachen) xmax=160;
|
| 728 |
buchmann |
1.21 |
if(MetCut>=xmax) xmax=MetCut+10;
|
| 729 |
buchmann |
1.17 |
int nbins=int((xmax-xmin)/BinWidth);
|
| 730 |
buchmann |
1.23 |
|
| 731 |
|
|
float pt2cut=20;
|
| 732 |
|
|
if(isAachen)pt2cut=10;
|
| 733 |
|
|
|
| 734 |
buchmann |
1.17 |
stringstream basiccut;
|
| 735 |
buchmann |
1.23 |
basiccut << (const char*) JetCut << "&&" << (const char*) Restrmasscut << "&&" << (const char*) leptoncut << "&&pt1>20&&pt2>" << pt2cut;
|
| 736 |
buchmann |
1.17 |
|
| 737 |
|
|
|
| 738 |
|
|
stringstream cMET_observed;
|
| 739 |
|
|
cMET_observed << "(" << basiccut.str() << "&&(" << sPositiveCut << ")&&" << (const char*) cutOSSF << ")";
|
| 740 |
|
|
stringstream cMET_ttbar_pred;
|
| 741 |
|
|
cMET_ttbar_pred << "(" << basiccut.str() << "&&(" << sPositiveCut << ")&&" << (const char*) cutOSOF << ")";
|
| 742 |
|
|
stringstream cMET_osof_pred;
|
| 743 |
|
|
cMET_osof_pred << "(" << basiccut.str() << "&&(" << sNegativeCut << ")&&" << (const char*) cutOSOF << ")";
|
| 744 |
|
|
stringstream cMET_ossf_pred;
|
| 745 |
|
|
cMET_ossf_pred << "(" << basiccut.str() << "&&(" << sNegativeCut << ")&&" << (const char*) cutOSSF << ")";
|
| 746 |
|
|
|
| 747 |
|
|
write_warning(__FUNCTION__,"Once the rush is over you might want to define the potential sidebands ... ");
|
| 748 |
buchmann |
1.28 |
|
| 749 |
buchmann |
1.17 |
//Step 2: Fill Met histograms
|
| 750 |
buchmann |
1.28 |
float bottommargin=gStyle->GetPadBottomMargin();
|
| 751 |
|
|
float canvas_height=gStyle->GetCanvasDefH();
|
| 752 |
|
|
float canvas_width=gStyle->GetCanvasDefW();
|
| 753 |
|
|
float ratiospace=0.25;// space the ratio should take up (relative to original pad)
|
| 754 |
|
|
|
| 755 |
|
|
float ratiobottommargin=0.3;
|
| 756 |
|
|
float ratiotopmargin=0.1;
|
| 757 |
|
|
|
| 758 |
|
|
float xstretchfactor=((1-ratiospace)*(1-gStyle->GetPadTopMargin()))/((1)*ratiospace);
|
| 759 |
|
|
|
| 760 |
|
|
TCanvas *main_canvas = new TCanvas("main_canvas","main_canvas",(Int_t)canvas_width,(Int_t)(canvas_height*(1+ratiospace)));
|
| 761 |
|
|
TPad *mainpad = new TPad("mainpad","mainpad",0,1-(1.0/(1+ratiospace)),1,1);//top (main) pad
|
| 762 |
|
|
TPad *coverpad = new TPad("coverpad","coverpad",gStyle->GetPadLeftMargin()-0.008,1-(1.0/(1+ratiospace))-0.04,1,1-(1.0/(1+ratiospace))+0.103);//pad covering up the x scale
|
| 763 |
|
|
TPad *bottompad = new TPad("bottompad", "Ratio Pad",0,0,1,(1-(1-bottommargin)/(1+ratiospace))-0.015); //bottom pad
|
| 764 |
|
|
|
| 765 |
|
|
main_canvas->Range(0,0,1,1);
|
| 766 |
|
|
main_canvas->SetBorderSize(0);
|
| 767 |
|
|
main_canvas->SetFrameFillColor(0);
|
| 768 |
|
|
|
| 769 |
|
|
mainpad->Draw();
|
| 770 |
|
|
mainpad->cd();
|
| 771 |
|
|
mainpad->SetLogy(1);
|
| 772 |
|
|
mainpad->Range(0,0,1,1);
|
| 773 |
|
|
mainpad->SetFillColor(kWhite);
|
| 774 |
|
|
mainpad->SetBorderSize(0);
|
| 775 |
|
|
mainpad->SetFrameFillColor(0);
|
| 776 |
|
|
|
| 777 |
|
|
|
| 778 |
|
|
|
| 779 |
|
|
|
| 780 |
buchmann |
1.17 |
TH1F *MET_observed = allsamples.Draw("MET_observed",ObservedMet,nbins,xmin,xmax,"MET [GeV]","events",
|
| 781 |
buchmann |
1.26 |
TCut(cMET_observed.str().c_str()),is_data,PlottingSetup::luminosity,SelectedSamples);
|
| 782 |
buchmann |
1.17 |
TH1F *MET_ossf_pred = allsamples.Draw("MET_ossf_pred",CorrectedMet,nbins,xmin,xmax,"MET [GeV]","events",
|
| 783 |
buchmann |
1.26 |
TCut(cMET_ossf_pred.str().c_str()),is_data,PlottingSetup::luminosity,SelectedSamples);
|
| 784 |
buchmann |
1.17 |
TH1F *MET_osof_pred = allsamples.Draw("MET_osof_pred",CorrectedMet,nbins,xmin,xmax,"MET [GeV]","events",
|
| 785 |
buchmann |
1.26 |
TCut(cMET_osof_pred.str().c_str()),is_data,PlottingSetup::luminosity,SelectedSamples);
|
| 786 |
buchmann |
1.17 |
TH1F *MET_ttbar_pred= allsamples.Draw("MET_ttbar_pred",ObservedMet,nbins,xmin,xmax,"MET [GeV]","events",
|
| 787 |
buchmann |
1.26 |
TCut(cMET_ttbar_pred.str().c_str()),is_data,PlottingSetup::luminosity,SelectedSamples);
|
| 788 |
buchmann |
1.17 |
|
| 789 |
buchmann |
1.25 |
|
| 790 |
|
|
if(isDYonly && is_data==mc) {
|
| 791 |
|
|
TH1F *MET_truth = allsamples.Draw("MET_truth",ObservedMet,1,MetCut,10000,"MET [GeV]","events",TCut(((string)"met[4]>"+any2string(MetCut)).c_str())&&cutOSSF&&TCut(basiccut.str().c_str()),is_data,PlottingSetup::luminosity,SelectedSamples);
|
| 792 |
|
|
write_info(__FUNCTION__,"DY Truth is : "+any2string(MET_truth->Integral()));
|
| 793 |
|
|
delete MET_truth;
|
| 794 |
|
|
}
|
| 795 |
|
|
|
| 796 |
|
|
|
| 797 |
buchmann |
1.17 |
TH1F *MET_predicted=(TH1F*)MET_ossf_pred->Clone("MET_predicted");
|
| 798 |
|
|
MET_predicted->Add(MET_osof_pred,-1);
|
| 799 |
|
|
MET_predicted->Add(MET_ttbar_pred);
|
| 800 |
|
|
MET_predicted->SetLineColor(kRed);
|
| 801 |
|
|
MET_observed->SetLineColor(kBlack);
|
| 802 |
|
|
|
| 803 |
|
|
TH1F *MET_Z_prediction=(TH1F*)MET_ossf_pred->Clone("MET_Z_prediction");
|
| 804 |
|
|
MET_Z_prediction->Add(MET_osof_pred,-1);
|
| 805 |
|
|
MET_Z_prediction->SetLineColor(kBlue);
|
| 806 |
|
|
|
| 807 |
|
|
LabelHisto(MET_observed,"MET (GeV)","events");
|
| 808 |
|
|
|
| 809 |
|
|
//Step 3: Fill JZB histograms
|
| 810 |
buchmann |
1.25 |
|
| 811 |
buchmann |
1.17 |
TH1F *JZB_observed = allsamples.Draw("JZB_observed",JZBPosvar,nbins,xmin,xmax,"JZB [GeV]","events",
|
| 812 |
|
|
TCut(cMET_observed.str().c_str()),is_data,PlottingSetup::luminosity,SelectedSamples);
|
| 813 |
|
|
TH1F *JZB_ossf_pred = allsamples.Draw("JZB_ossf_pred",JZBNegvar,nbins,xmin,xmax,"JZB [GeV]","events",
|
| 814 |
|
|
TCut(cMET_ossf_pred.str().c_str()),is_data,PlottingSetup::luminosity,SelectedSamples);
|
| 815 |
|
|
TH1F *JZB_osof_pred = allsamples.Draw("JZB_osof_pred",JZBNegvar,nbins,xmin,xmax,"JZB [GeV]","events",
|
| 816 |
|
|
TCut(cMET_osof_pred.str().c_str()),is_data,PlottingSetup::luminosity,SelectedSamples);
|
| 817 |
|
|
TH1F *JZB_ttbar_pred= allsamples.Draw("JZB_ttbar_pred",JZBPosvar,nbins,xmin,xmax,"JZB [GeV]","events",
|
| 818 |
|
|
TCut(cMET_ttbar_pred.str().c_str()),is_data,PlottingSetup::luminosity,SelectedSamples);
|
| 819 |
|
|
|
| 820 |
|
|
TH1F *JZB_predicted=(TH1F*)JZB_ossf_pred->Clone("JZB_predicted");
|
| 821 |
|
|
JZB_predicted->Add(JZB_osof_pred,-1);
|
| 822 |
|
|
JZB_predicted->Add(JZB_ttbar_pred);
|
| 823 |
|
|
JZB_predicted->SetLineColor(kRed);
|
| 824 |
|
|
JZB_observed->SetLineColor(kBlack);
|
| 825 |
|
|
|
| 826 |
|
|
TH1F *JZB_Z_prediction=(TH1F*)JZB_ossf_pred->Clone("JZB_Z_prediction");
|
| 827 |
|
|
JZB_Z_prediction->Add(JZB_osof_pred,-1);
|
| 828 |
|
|
MET_Z_prediction->SetLineColor(kBlue);
|
| 829 |
|
|
|
| 830 |
|
|
LabelHisto(JZB_observed,"JZB (GeV)","events");
|
| 831 |
|
|
|
| 832 |
|
|
// Step 4: Draw them and store them
|
| 833 |
|
|
|
| 834 |
|
|
TLegend *legend = new TLegend(0.6,0.6,0.89,0.89);
|
| 835 |
|
|
|
| 836 |
|
|
MET_ttbar_pred->SetLineColor(TColor::GetColor("#005C00"));
|
| 837 |
|
|
JZB_ttbar_pred->SetLineColor(TColor::GetColor("#005C00"));
|
| 838 |
|
|
|
| 839 |
|
|
legend->SetFillColor(kWhite);
|
| 840 |
|
|
legend->SetBorderSize(0);
|
| 841 |
|
|
legend->AddEntry(MET_predicted,"prediction","l");
|
| 842 |
|
|
legend->AddEntry(MET_observed,"observed","p");
|
| 843 |
|
|
legend->AddEntry(MET_Z_prediction,"predicted Z","l");
|
| 844 |
|
|
legend->AddEntry(MET_ttbar_pred,"OF-based prediction","l");
|
| 845 |
|
|
|
| 846 |
|
|
if(is_data==mc) legend->SetHeader("Simulation:");
|
| 847 |
|
|
if(is_data==mc&&isDYonly) legend->SetHeader("DY #rightarrow ee,#mu#mu only:");
|
| 848 |
|
|
if(is_data==data) legend->SetHeader("Data:");
|
| 849 |
|
|
|
| 850 |
|
|
stringstream SaveJZBname;
|
| 851 |
|
|
stringstream SaveMETname;
|
| 852 |
|
|
if(is_data==data) {
|
| 853 |
|
|
SaveJZBname << "MetPrediction/JZBdistribution_Data_METCutAt" << MetCut;
|
| 854 |
|
|
SaveMETname << "MetPrediction/METdistribution_Data_METCutAt" << MetCut;
|
| 855 |
|
|
}
|
| 856 |
|
|
if(is_data==mc&&!isDYonly) {
|
| 857 |
|
|
SaveJZBname << "MetPrediction/JZBdistribution_FullMC_METCutAt" << MetCut;
|
| 858 |
|
|
SaveMETname << "MetPrediction/METdistribution_FullMC_METCutAt" << MetCut;
|
| 859 |
|
|
}
|
| 860 |
|
|
if(is_data==mc&&isDYonly) {
|
| 861 |
|
|
SaveJZBname << "MetPrediction/JZBdistribution_DYMC_METCutAt" << MetCut;
|
| 862 |
|
|
SaveMETname << "MetPrediction/METdistribution_DYMC_METCutAt" << MetCut;
|
| 863 |
|
|
}
|
| 864 |
|
|
|
| 865 |
buchmann |
1.26 |
dout << "Shape summary (MET>50) for ";
|
| 866 |
|
|
if(is_data==data) cout << "data";
|
| 867 |
|
|
if(is_data==mc&&isDYonly) cout<< "DY ";
|
| 868 |
|
|
if(is_data==mc&&!isDYonly) cout << " Full MC";
|
| 869 |
|
|
cout << " : " << endl;
|
| 870 |
|
|
|
| 871 |
buchmann |
1.24 |
dout << " observed : " << MET_observed->Integral(MET_observed->FindBin(50),MET_observed->FindBin(xmax)) << endl;
|
| 872 |
|
|
dout << " predicted : " << MET_predicted->Integral(MET_predicted->FindBin(50),MET_predicted->FindBin(xmax)) << endl;
|
| 873 |
|
|
dout << " Z pred : " << MET_Z_prediction->Integral(MET_Z_prediction->FindBin(50),MET_Z_prediction->FindBin(xmax)) << endl;
|
| 874 |
|
|
dout << " ttbar : " << MET_ttbar_pred->Integral(MET_ttbar_pred->FindBin(50),MET_ttbar_pred->FindBin(xmax)) << endl;
|
| 875 |
|
|
|
| 876 |
|
|
|
| 877 |
buchmann |
1.17 |
TH1F *ZpredClone = (TH1F*)MET_Z_prediction->Clone("ZpredClone");
|
| 878 |
|
|
ZpredClone->SetLineColor(kBlue);
|
| 879 |
|
|
MET_observed->Rebin(int(DisplayedBinSize/BinWidth));
|
| 880 |
|
|
ZpredClone->Rebin(int(DisplayedBinSize/BinWidth));
|
| 881 |
|
|
MET_predicted->Rebin(int(DisplayedBinSize/BinWidth));
|
| 882 |
|
|
MET_ttbar_pred->Rebin(int(DisplayedBinSize/BinWidth));
|
| 883 |
|
|
|
| 884 |
|
|
TH1F *JZBZpredClone = (TH1F*)JZB_Z_prediction->Clone("ZpredClone");
|
| 885 |
|
|
JZBZpredClone->SetLineColor(kBlue);
|
| 886 |
|
|
JZB_observed->Rebin(int(DisplayedBinSize/BinWidth));
|
| 887 |
|
|
JZBZpredClone->Rebin(int(DisplayedBinSize/BinWidth));
|
| 888 |
|
|
JZB_predicted->Rebin(int(DisplayedBinSize/BinWidth));
|
| 889 |
|
|
JZB_ttbar_pred->Rebin(int(DisplayedBinSize/BinWidth));
|
| 890 |
|
|
|
| 891 |
|
|
TH1F *JZB_ratio = (TH1F*)JZB_observed->Clone("JZB_ratio");
|
| 892 |
|
|
JZB_ratio->Divide(JZB_predicted);
|
| 893 |
|
|
LabelHisto(JZB_ratio,"JZB (GeV)","obs/pred");
|
| 894 |
|
|
TH1F *MET_ratio = (TH1F*)MET_observed->Clone("MET_ratio");
|
| 895 |
|
|
MET_ratio->Divide(MET_predicted);
|
| 896 |
buchmann |
1.28 |
MET_observed->SetMaximum(5*MET_observed->GetMaximum());
|
| 897 |
|
|
JZB_observed->SetMaximum(5*JZB_observed->GetMaximum());
|
| 898 |
|
|
MET_observed->SetMinimum(0.5);
|
| 899 |
|
|
JZB_observed->SetMinimum(0.5);
|
| 900 |
buchmann |
1.17 |
LabelHisto(MET_ratio,"MET (GeV)","obs/pred");
|
| 901 |
buchmann |
1.24 |
TBox *sysenvelope = new TBox(xmin,1.0-MetPlotsSpace::Zprediction_Uncertainty,xmax,1.0+MetPlotsSpace::Zprediction_Uncertainty);
|
| 902 |
buchmann |
1.17 |
sysenvelope->SetFillColor(TColor::GetColor("#82FA58")); // light green
|
| 903 |
|
|
sysenvelope->SetLineWidth(0);
|
| 904 |
buchmann |
1.24 |
TBox *dsysenvelope = new TBox(xmin,1.0-2*MetPlotsSpace::Zprediction_Uncertainty,xmax,1.0+2*MetPlotsSpace::Zprediction_Uncertainty);
|
| 905 |
|
|
dsysenvelope->SetFillColor(TColor::GetColor("#F3F781")); // light yellow
|
| 906 |
|
|
dsysenvelope->SetLineWidth(0);
|
| 907 |
buchmann |
1.28 |
|
| 908 |
|
|
MET_ratio->GetYaxis()->SetNdivisions(502,false);
|
| 909 |
|
|
JZB_ratio->GetYaxis()->SetNdivisions(502,false);
|
| 910 |
|
|
|
| 911 |
buchmann |
1.17 |
|
| 912 |
|
|
MET_observed->Draw("e1");
|
| 913 |
|
|
MET_ttbar_pred->Draw("histo,same");
|
| 914 |
|
|
ZpredClone->Draw("histo,same");
|
| 915 |
|
|
MET_predicted->Draw("histo,same");
|
| 916 |
|
|
MET_observed->Draw("e1,same");
|
| 917 |
|
|
legend->Draw();
|
| 918 |
|
|
if(is_data==data) DrawPrelim();
|
| 919 |
|
|
else DrawMCPrelim();
|
| 920 |
|
|
|
| 921 |
buchmann |
1.28 |
mainpad->Modified();
|
| 922 |
|
|
main_canvas->cd();
|
| 923 |
|
|
coverpad->Draw();
|
| 924 |
|
|
coverpad->cd();
|
| 925 |
|
|
coverpad->Range(0,0,1,1);
|
| 926 |
|
|
coverpad->SetFillColor(kWhite);
|
| 927 |
|
|
coverpad->SetBorderSize(0);
|
| 928 |
|
|
coverpad->SetFrameFillColor(0);
|
| 929 |
|
|
coverpad->Modified();
|
| 930 |
|
|
main_canvas->cd();
|
| 931 |
|
|
bottompad->SetTopMargin(ratiotopmargin);
|
| 932 |
|
|
bottompad->SetBottomMargin(ratiobottommargin);
|
| 933 |
|
|
bottompad->Draw();
|
| 934 |
buchmann |
1.17 |
bottompad->cd();
|
| 935 |
buchmann |
1.28 |
bottompad->Range(0,0,1,1);
|
| 936 |
|
|
bottompad->SetFillColor(kWhite);
|
| 937 |
|
|
|
| 938 |
buchmann |
1.17 |
MET_ratio->GetYaxis()->SetRangeUser(0,2);
|
| 939 |
buchmann |
1.28 |
MET_ratio->GetXaxis()->SetLabelSize(xstretchfactor*MET_ratio->GetXaxis()->GetLabelSize());
|
| 940 |
|
|
MET_ratio->GetYaxis()->SetLabelSize(xstretchfactor*MET_ratio->GetYaxis()->GetLabelSize());
|
| 941 |
|
|
MET_ratio->GetXaxis()->SetTitleSize(xstretchfactor*gStyle->GetTitleSize());
|
| 942 |
|
|
MET_ratio->GetYaxis()->SetTitleSize(xstretchfactor*gStyle->GetTitleSize());
|
| 943 |
|
|
|
| 944 |
buchmann |
1.17 |
MET_ratio->Draw("e1");
|
| 945 |
buchmann |
1.28 |
// dsysenvelope->Draw();
|
| 946 |
buchmann |
1.17 |
sysenvelope->Draw();
|
| 947 |
|
|
MET_ratio->Draw("AXIS,same");
|
| 948 |
|
|
MET_ratio->Draw("e1,same");
|
| 949 |
|
|
TLine *metl = new TLine(xmin,1.0,xmax,1.0);
|
| 950 |
|
|
metl->SetLineColor(kBlue);
|
| 951 |
|
|
metl->Draw();
|
| 952 |
buchmann |
1.28 |
CompleteSave(main_canvas,SaveMETname.str());
|
| 953 |
|
|
|
| 954 |
|
|
mainpad->cd();
|
| 955 |
buchmann |
1.17 |
|
| 956 |
|
|
JZB_observed->Draw("e1");
|
| 957 |
|
|
JZB_ttbar_pred->Draw("histo,same");
|
| 958 |
|
|
JZBZpredClone->Draw("histo,same");
|
| 959 |
|
|
JZB_predicted->Draw("histo,same");
|
| 960 |
|
|
JZB_observed->Draw("e1,same");
|
| 961 |
|
|
legend->Draw();
|
| 962 |
|
|
if(is_data==data) DrawPrelim();
|
| 963 |
|
|
else DrawMCPrelim();
|
| 964 |
|
|
|
| 965 |
buchmann |
1.28 |
main_canvas->cd();
|
| 966 |
|
|
coverpad->Draw();
|
| 967 |
|
|
main_canvas->cd();
|
| 968 |
|
|
bottompad->Draw();
|
| 969 |
buchmann |
1.17 |
bottompad->cd();
|
| 970 |
|
|
JZB_ratio->GetYaxis()->SetRangeUser(0,2);
|
| 971 |
buchmann |
1.28 |
|
| 972 |
|
|
JZB_ratio->GetXaxis()->SetLabelSize(xstretchfactor*JZB_ratio->GetXaxis()->GetLabelSize());
|
| 973 |
|
|
JZB_ratio->GetYaxis()->SetLabelSize(xstretchfactor*JZB_ratio->GetYaxis()->GetLabelSize());
|
| 974 |
|
|
JZB_ratio->GetXaxis()->SetTitleSize(xstretchfactor*gStyle->GetTitleSize());
|
| 975 |
|
|
JZB_ratio->GetYaxis()->SetTitleSize(xstretchfactor*gStyle->GetTitleSize());
|
| 976 |
|
|
|
| 977 |
buchmann |
1.17 |
JZB_ratio->Draw("e1");
|
| 978 |
buchmann |
1.28 |
// dsysenvelope->Draw();
|
| 979 |
buchmann |
1.17 |
sysenvelope->Draw();
|
| 980 |
|
|
JZB_ratio->Draw("AXIS,same");
|
| 981 |
|
|
JZB_ratio->Draw("e1,same");
|
| 982 |
|
|
metl->Draw();
|
| 983 |
|
|
|
| 984 |
buchmann |
1.28 |
CompleteSave(main_canvas,SaveJZBname.str());
|
| 985 |
buchmann |
1.17 |
|
| 986 |
buchmann |
1.28 |
delete main_canvas;
|
| 987 |
buchmann |
1.17 |
delete MET_observed;
|
| 988 |
|
|
delete MET_predicted;
|
| 989 |
|
|
//do NOT delete MET_Z_prediction (it's the return value)
|
| 990 |
|
|
delete MET_osof_pred;
|
| 991 |
|
|
delete MET_ossf_pred;
|
| 992 |
|
|
delete MET_ttbar_pred;
|
| 993 |
|
|
|
| 994 |
|
|
delete JZB_observed;
|
| 995 |
|
|
delete JZB_predicted;
|
| 996 |
|
|
delete JZB_osof_pred;
|
| 997 |
|
|
delete JZB_ossf_pred;
|
| 998 |
|
|
delete JZB_Z_prediction;
|
| 999 |
|
|
delete JZB_ttbar_pred;
|
| 1000 |
|
|
|
| 1001 |
|
|
return MET_Z_prediction;
|
| 1002 |
|
|
}
|
| 1003 |
|
|
|
| 1004 |
buchmann |
1.25 |
float extract_correction(string jzbvariable) {
|
| 1005 |
|
|
int position = (int)jzbvariable.find("[1]");
|
| 1006 |
|
|
if(position==-1) return 0.0;
|
| 1007 |
|
|
string correction=jzbvariable.substr(position+3,jzbvariable.length()-position-3);
|
| 1008 |
|
|
position = (int)correction.find("*");
|
| 1009 |
|
|
if(position==-1) return 0.0;
|
| 1010 |
|
|
correction=correction.substr(0,position);
|
| 1011 |
|
|
float correctionvalue=atof(correction.c_str());
|
| 1012 |
|
|
assert(correctionvalue<1&&correctionvalue>0);
|
| 1013 |
|
|
return correctionvalue;
|
| 1014 |
|
|
}
|
| 1015 |
|
|
|
| 1016 |
buchmann |
1.23 |
float Get_Met_Z_Prediction(TCut JetCut, float MetCut, int isdata, bool isDYonly, bool isAachen=false) {
|
| 1017 |
buchmann |
1.17 |
dout << "Going to compute Z region prediction for a MET cut at " << MetCut << " GeV" << endl;
|
| 1018 |
|
|
// Steps:
|
| 1019 |
buchmann |
1.25 |
// 1) Get peak
|
| 1020 |
|
|
// 2) use the peak and pt correction for sample splitting
|
| 1021 |
|
|
// and for MET distribution shifting
|
| 1022 |
buchmann |
1.17 |
// 3) compute the estimate for MET>MetCut
|
| 1023 |
|
|
|
| 1024 |
|
|
// do this for data if isdata==data, otherwise for MC (full closure if isDYonly==false, otherwise use only DY sample)
|
| 1025 |
|
|
|
| 1026 |
buchmann |
1.28 |
// Step 0 : If we're dealing with DY, we need to make sure PURW is off!
|
| 1027 |
|
|
// string bkpcutweight = (const char*) cutWeight;
|
| 1028 |
|
|
// if(isdata==mc && isDYonly) cutWeight=TCut("1.0");
|
| 1029 |
|
|
|
| 1030 |
|
|
|
| 1031 |
buchmann |
1.25 |
// Step 1) Get peak
|
| 1032 |
buchmann |
1.17 |
float MCPeakNoPtCorr=0,MCPeakErrorNoPtCorr=0,DataPeakNoPtCorr=0,DataPeakErrorNoPtCorr=0,MCSigma=0,DataSigma=0;
|
| 1033 |
|
|
stringstream resultsNoPtCorr;
|
| 1034 |
|
|
stringstream NoPtCorrdatajzb;
|
| 1035 |
|
|
stringstream NoPtCorrmcjzb;
|
| 1036 |
|
|
|
| 1037 |
buchmann |
1.24 |
if(isAachen) {
|
| 1038 |
|
|
//need to make sure that none of the typical basic cuts contain problematic selections!
|
| 1039 |
|
|
string Sleptoncut = (const char*) leptoncut;
|
| 1040 |
|
|
if((int)Sleptoncut.find("pt2>20")>-1) {
|
| 1041 |
|
|
write_error(__FUNCTION__,"You're trying to compute the Aachen estimate but are requiring pt2>20 ... please check your config.");
|
| 1042 |
|
|
assert((int)Sleptoncut.find("pt2>20")==-1);
|
| 1043 |
|
|
}
|
| 1044 |
|
|
} else {
|
| 1045 |
|
|
string Sleptoncut = (const char*) leptoncut;
|
| 1046 |
|
|
if((int)Sleptoncut.find("pt2>10")>-1) {
|
| 1047 |
|
|
write_error(__FUNCTION__,"You're trying to compute the ETH estimate but are requiring pt2>10 ... please check your config.");
|
| 1048 |
|
|
assert((int)Sleptoncut.find("pt2>10")==-1);
|
| 1049 |
|
|
}
|
| 1050 |
|
|
}
|
| 1051 |
|
|
|
| 1052 |
|
|
|
| 1053 |
buchmann |
1.25 |
float Ptcorrection=0.0;
|
| 1054 |
buchmann |
1.24 |
|
| 1055 |
buchmann |
1.25 |
if(isdata==data) Ptcorrection=extract_correction(PlottingSetup::jzbvariabledata);
|
| 1056 |
|
|
else Ptcorrection=extract_correction(PlottingSetup::jzbvariablemc);
|
| 1057 |
buchmann |
1.24 |
|
| 1058 |
buchmann |
1.29 |
bool OverFlowStatus=addoverunderflowbins;
|
| 1059 |
|
|
|
| 1060 |
buchmann |
1.25 |
find_peaks(MCPeakNoPtCorr,MCPeakErrorNoPtCorr, DataPeakNoPtCorr,DataPeakErrorNoPtCorr,resultsNoPtCorr,true,NoPtCorrdatajzb,NoPtCorrmcjzb,(const char*) JetCut, true);
|
| 1061 |
buchmann |
1.17 |
|
| 1062 |
buchmann |
1.29 |
switch_overunderflow(OverFlowStatus);
|
| 1063 |
buchmann |
1.28 |
|
| 1064 |
buchmann |
1.25 |
float PeakPosition=0.0;
|
| 1065 |
|
|
string jzbvariable;
|
| 1066 |
buchmann |
1.17 |
if(isdata==data) {
|
| 1067 |
|
|
PeakPosition=DataPeakNoPtCorr;
|
| 1068 |
buchmann |
1.25 |
jzbvariable=jzbvariabledata;
|
| 1069 |
buchmann |
1.17 |
dout << "Found peak in data at " << DataPeakNoPtCorr << " +/- " << DataPeakErrorNoPtCorr << " ; will use this result (" << PeakPosition << ")" << endl;
|
| 1070 |
|
|
} else {
|
| 1071 |
|
|
PeakPosition=MCPeakNoPtCorr;
|
| 1072 |
buchmann |
1.25 |
jzbvariable=jzbvariablemc;
|
| 1073 |
buchmann |
1.17 |
dout << "Found peak in mc at " << MCPeakNoPtCorr << " +/- " << MCPeakErrorNoPtCorr << " ; will use this result (" << PeakPosition << ")" << endl;
|
| 1074 |
|
|
}
|
| 1075 |
|
|
|
| 1076 |
|
|
// Step 2: Use peak for sample splitting and MET shifting
|
| 1077 |
buchmann |
1.25 |
string CorrectedMet="met[4]-"+any2string(Ptcorrection)+"*pt +"+any2string(abs(1.0*(PeakPosition)));
|
| 1078 |
|
|
if(2*(PeakPosition)<0) CorrectedMet="met[4]-"+any2string(Ptcorrection)+"*pt -"+any2string(abs(1.0*(PeakPosition)));
|
| 1079 |
buchmann |
1.17 |
|
| 1080 |
|
|
stringstream sPositiveCut;
|
| 1081 |
buchmann |
1.25 |
if(PeakPosition>0) sPositiveCut << "((" << jzbvariable << "-" << PeakPosition << ")>0)";
|
| 1082 |
|
|
else sPositiveCut << "( " << jzbvariable << "+" << abs(PeakPosition) << ")>0)";
|
| 1083 |
buchmann |
1.17 |
|
| 1084 |
|
|
stringstream sNegativeCut;
|
| 1085 |
buchmann |
1.25 |
if(PeakPosition<0) sNegativeCut << "((" << jzbvariable << "+" << abs(PeakPosition) << ")<0)";
|
| 1086 |
|
|
else sNegativeCut << "(( " << jzbvariable << "-" << abs(PeakPosition) << ")<0)";
|
| 1087 |
buchmann |
1.17 |
|
| 1088 |
|
|
string ObservedMet="met[4]";
|
| 1089 |
|
|
|
| 1090 |
|
|
stringstream JZBPosvar;
|
| 1091 |
buchmann |
1.25 |
JZBPosvar<<jzbvariable;
|
| 1092 |
|
|
if(PeakPosition>0) JZBPosvar << "-" << PeakPosition;
|
| 1093 |
|
|
else JZBPosvar << "+" << abs(PeakPosition);
|
| 1094 |
|
|
|
| 1095 |
buchmann |
1.17 |
stringstream JZBNegvar;
|
| 1096 |
buchmann |
1.25 |
JZBNegvar<<"-(" << jzbvariable;
|
| 1097 |
|
|
if(PeakPosition>0) JZBNegvar << "-" << PeakPosition << ")";
|
| 1098 |
|
|
else JZBNegvar << "+" << abs(PeakPosition) << ")";
|
| 1099 |
|
|
|
| 1100 |
buchmann |
1.17 |
|
| 1101 |
|
|
// Step 3: Compute estimate
|
| 1102 |
buchmann |
1.23 |
TH1F *predicted = GetPredictedAndObservedMetShapes(JetCut, sPositiveCut.str(),sNegativeCut.str(),CorrectedMet,ObservedMet,JZBPosvar.str(),JZBNegvar.str(), MetCut, isdata, isDYonly, isAachen);
|
| 1103 |
buchmann |
1.17 |
float ZregionZestimate=0;
|
| 1104 |
|
|
for(int ibin=1;ibin<=(int)predicted->GetNbinsX();ibin++) {
|
| 1105 |
|
|
if(predicted->GetBinLowEdge(ibin)+predicted->GetBinWidth(ibin)>MetCut) {
|
| 1106 |
|
|
ZregionZestimate+=2*(predicted->GetBinContent(ibin));
|
| 1107 |
|
|
}
|
| 1108 |
|
|
}
|
| 1109 |
|
|
|
| 1110 |
buchmann |
1.25 |
cout << " Z region estimate in MET>" << MetCut << " for this sample: " << ZregionZestimate << endl;
|
| 1111 |
buchmann |
1.30 |
if(isdata==data) {
|
| 1112 |
|
|
MetPlotsSpace::Zestimate__data=ZregionZestimate;
|
| 1113 |
|
|
MetPlotsSpace::Zestimate__data_stat=2*TMath::Sqrt(ZregionZestimate/2);
|
| 1114 |
|
|
MetPlotsSpace::Zestimate__data_sys=ZregionZestimate*MetPlotsSpace::Zprediction_Uncertainty;
|
| 1115 |
|
|
}
|
| 1116 |
|
|
if(isdata==mc && isDYonly) {
|
| 1117 |
|
|
MetPlotsSpace::Zestimate__dy=ZregionZestimate;
|
| 1118 |
|
|
MetPlotsSpace::Zestimate__dy_stat=2*TMath::Sqrt(ZregionZestimate/2);
|
| 1119 |
|
|
MetPlotsSpace::Zestimate__dy_sys=ZregionZestimate*MetPlotsSpace::Zprediction_Uncertainty;
|
| 1120 |
|
|
}
|
| 1121 |
|
|
if(isdata==mc && !isDYonly) {
|
| 1122 |
|
|
MetPlotsSpace::Zestimate__mc=ZregionZestimate;
|
| 1123 |
|
|
MetPlotsSpace::Zestimate__mc_stat=2*TMath::Sqrt(ZregionZestimate/2);
|
| 1124 |
|
|
MetPlotsSpace::Zestimate__mc_sys=ZregionZestimate*MetPlotsSpace::Zprediction_Uncertainty;
|
| 1125 |
|
|
}
|
| 1126 |
|
|
|
| 1127 |
|
|
|
| 1128 |
buchmann |
1.25 |
|
| 1129 |
buchmann |
1.28 |
// if(isdata==mc && isDYonly) cutWeight=TCut(bkpcutweight.c_str());
|
| 1130 |
|
|
|
| 1131 |
buchmann |
1.17 |
return ZregionZestimate;
|
| 1132 |
|
|
}
|
| 1133 |
|
|
|
| 1134 |
buchmann |
1.30 |
void ExperimentalMetPrediction(bool QuickRun=false) {
|
| 1135 |
buchmann |
1.17 |
|
| 1136 |
buchmann |
1.28 |
switch_overunderflow(true);
|
| 1137 |
buchmann |
1.23 |
bool isAachen=false;
|
| 1138 |
buchmann |
1.24 |
|
| 1139 |
buchmann |
1.35 |
bool HighPurityMode=false; // High Purity = |mll-91|<10 GeV , else <20
|
| 1140 |
buchmann |
1.24 |
|
| 1141 |
buchmann |
1.30 |
if(QuickRun) {
|
| 1142 |
|
|
isAachen=false;
|
| 1143 |
buchmann |
1.32 |
HighPurityMode=true;
|
| 1144 |
buchmann |
1.30 |
}
|
| 1145 |
|
|
|
| 1146 |
buchmann |
1.24 |
string restrmasscutbkp=(const char*) PlottingSetup::Restrmasscut;
|
| 1147 |
|
|
|
| 1148 |
buchmann |
1.32 |
if(HighPurityMode) PlottingSetup::Restrmasscut=TCut("abs(mll-91)<10");
|
| 1149 |
|
|
else PlottingSetup::Restrmasscut= TCut("abs(mll-91)<20");
|
| 1150 |
buchmann |
1.24 |
|
| 1151 |
|
|
|
| 1152 |
|
|
|
| 1153 |
buchmann |
1.23 |
cout << "Aachen mode (20/10, 2 jets) ? " << isAachen << endl;
|
| 1154 |
buchmann |
1.24 |
cout << "High Purity mode? " << HighPurityMode << endl;
|
| 1155 |
|
|
|
| 1156 |
buchmann |
1.23 |
|
| 1157 |
|
|
if(isAachen) write_warning(__FUNCTION__,"Please don't forget to adapt the global lepton cut (to 20/10) for Aachen!");
|
| 1158 |
buchmann |
1.24 |
stringstream snjets;
|
| 1159 |
|
|
if(isAachen) snjets << 2;
|
| 1160 |
|
|
else snjets << 3;
|
| 1161 |
|
|
float maxMET=100;
|
| 1162 |
|
|
if(isAachen) maxMET=150;
|
| 1163 |
buchmann |
1.12 |
|
| 1164 |
buchmann |
1.17 |
TCut nJetsSignal(PlottingSetup::basicqualitycut&&("pfJetGoodNum40>="+snjets.str()).c_str());
|
| 1165 |
buchmann |
1.35 |
/*
|
| 1166 |
buchmann |
1.17 |
cout << " ***** TESTING Z PREDICTION ***** " << endl;
|
| 1167 |
|
|
cout << "Notation (you can copy & paste this to evaluate it further)" << endl;
|
| 1168 |
|
|
cout << "Cut;Data;MC;DY;" << endl;
|
| 1169 |
buchmann |
1.30 |
float DataEstimate = Get_Met_Z_Prediction(Restrmasscut&&nJetsSignal,maxMET, data, false, isAachen);
|
| 1170 |
|
|
float DYEstimate;
|
| 1171 |
|
|
if(!QuickRun) DYEstimate = Get_Met_Z_Prediction(Restrmasscut&&nJetsSignal,maxMET, mc, true, isAachen);
|
| 1172 |
|
|
float MCEstimate;
|
| 1173 |
|
|
if(!QuickRun) MCEstimate = Get_Met_Z_Prediction(Restrmasscut&&nJetsSignal,maxMET, mc, false, isAachen);
|
| 1174 |
|
|
|
| 1175 |
|
|
if(QuickRun) return;
|
| 1176 |
|
|
cout << maxMET << ";" << DataEstimate << ";" << MCEstimate << ";" << DYEstimate << endl;
|
| 1177 |
|
|
dout << "Found estimate in data of " << DataEstimate << endl;
|
| 1178 |
buchmann |
1.35 |
*/
|
| 1179 |
buchmann |
1.24 |
float Diff=20.0;
|
| 1180 |
|
|
if(HighPurityMode) Diff=10;
|
| 1181 |
|
|
TCut cut("mll>20&&pt1>20&&pt2>20");
|
| 1182 |
buchmann |
1.35 |
if (isAachen) cut = TCut("mll>20&&pt1>20&&pt2>10&&pfTightHT>100");
|
| 1183 |
buchmann |
1.28 |
|
| 1184 |
|
|
TCanvas *qcan = new TCanvas("qcan","qcan");
|
| 1185 |
buchmann |
1.35 |
TH1F *zlineshape = allsamples.Draw("zlineshape","mll",int((91+25-18)*5),18,91+25,"m_{ll} (GeV)","events",cutOSSF&&TCut("pfJetGoodNum40==2")&&cut,data,PlottingSetup::luminosity); // bins of 0.2 GeV
|
| 1186 |
|
|
TH1F *Ozlineshape = allsamples.Draw("Ozlineshape","mll",int((91+25-18)*5),18,91+25,"m_{ll} (GeV)","events",cutOSOF&&TCut("pfJetGoodNum40==2")&&cut,data,PlottingSetup::luminosity); // bins of 0.2 GeV
|
| 1187 |
buchmann |
1.28 |
zlineshape->Add(Ozlineshape,-1);
|
| 1188 |
|
|
delete qcan;
|
| 1189 |
buchmann |
1.24 |
float a = (zlineshape->Integral(zlineshape->FindBin(20),zlineshape->FindBin(70)));
|
| 1190 |
buchmann |
1.32 |
float b = (zlineshape->Integral(zlineshape->FindBin(91-Diff),zlineshape->FindBin(91+Diff)));
|
| 1191 |
buchmann |
1.24 |
float r = a/b;
|
| 1192 |
|
|
float dr= (a/b)*TMath::Sqrt(1/a+1/b);
|
| 1193 |
buchmann |
1.35 |
/*
|
| 1194 |
buchmann |
1.24 |
float SysUncertainty = TMath::Sqrt(DataEstimate*DataEstimate*dr*dr + r*r*(DataEstimate*MetPlotsSpace::Zprediction_Uncertainty*DataEstimate*MetPlotsSpace::Zprediction_Uncertainty));
|
| 1195 |
|
|
float StatUncertainty = TMath::Sqrt(DataEstimate);
|
| 1196 |
|
|
|
| 1197 |
|
|
cout << "Z estimate in peak : " << DataEstimate << " +/- " << DataEstimate*MetPlotsSpace::Zprediction_Uncertainty << " (sys) +/- " << TMath::Sqrt(2*DataEstimate) << " (stat) " << endl;
|
| 1198 |
|
|
cout << "Z ESTIMATE IN SR : " << DataEstimate*r << " +/- " << SysUncertainty << " (sys) +/- " << StatUncertainty << " (stat) " << endl;
|
| 1199 |
buchmann |
1.35 |
// cout << endl;*/
|
| 1200 |
buchmann |
1.24 |
cout << "r = " << r << " +/- " << dr << endl;
|
| 1201 |
|
|
|
| 1202 |
|
|
|
| 1203 |
|
|
|
| 1204 |
|
|
delete zlineshape;
|
| 1205 |
|
|
|
| 1206 |
|
|
PlottingSetup::Restrmasscut=TCut(restrmasscutbkp.c_str());
|
| 1207 |
buchmann |
1.28 |
switch_overunderflow(false);
|
| 1208 |
buchmann |
1.24 |
|
| 1209 |
buchmann |
1.12 |
}
|
| 1210 |
buchmann |
1.17 |
|
