//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//
// DY
//
// channel = SF, MuMu, EE
//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
void DY(Double_t &yield,
Double_t &statError,
Double_t &systError,
Double_t &scaleFactor,
Int_t njet,
TString channel,
TString directory,
Bool_t useDataDriven,
Int_t printLevel,
Bool_t drawR = false)
{
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//
// Input files
//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
TString path = Form("%s/%djet/%s/", directory.Data(), njet, channel.Data());
TFile* inputDYSF = new TFile(path + "DY.root");
TFile* inputZZSF = new TFile(path + "ZZ.root");
TFile* inputWZSF = new TFile(path + "WZ.root");
TFile* inputDataSF = new TFile(path + "DataRun2012_Total.root");
TFile* inputDataOF = new TFile(Form("%s/%djet/OF/DataRun2012_Total.root", directory.Data(), njet));
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//
// Input histograms
//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
TH1F* hNinDYSF [numberMetCuts];
TH1F* hNinWZSF [numberMetCuts];
TH1F* hNinZZSF [numberMetCuts];
TH1F* hNinDataSF[numberMetCuts];
TH1F* hNinDataOF[numberMetCuts];
TH1F* hNoutDYSF [numberMetCuts];
TH1F* hNoutWZSF [numberMetCuts];
TH1F* hNoutZZSF [numberMetCuts];
TH1F* hNoutDataSF[numberMetCuts];
TH1F* hNoutDataOF[numberMetCuts];
for (UInt_t nC=0; nC<numberMetCuts; nC++) {
hNinDYSF [nC] = (TH1F*)inputDYSF ->Get(Form("hNinZevents%.2f", MetCuts[nC]));
hNinWZSF [nC] = (TH1F*)inputWZSF ->Get(Form("hNinZevents%.2f", MetCuts[nC]));
hNinZZSF [nC] = (TH1F*)inputZZSF ->Get(Form("hNinZevents%.2f", MetCuts[nC]));
hNinDataSF[nC] = (TH1F*)inputDataSF->Get(Form("hNinZevents%.2f", MetCuts[nC]));
hNinDataOF[nC] = (TH1F*)inputDataOF->Get(Form("hNinZevents%.2f", MetCuts[nC]));
hNoutDYSF [nC] = (TH1F*)inputDYSF ->Get(Form("hNoutZevents%.2f", MetCuts[nC]));
hNoutWZSF [nC] = (TH1F*)inputWZSF ->Get(Form("hNoutZevents%.2f", MetCuts[nC]));
hNoutZZSF [nC] = (TH1F*)inputZZSF ->Get(Form("hNoutZevents%.2f", MetCuts[nC]));
hNoutDataSF[nC] = (TH1F*)inputDataSF->Get(Form("hNoutZevents%.2f", MetCuts[nC]));
hNoutDataOF[nC] = (TH1F*)inputDataOF->Get(Form("hNoutZevents%.2f", MetCuts[nC]));
}
// Histogram at analysis level
//----------------------------------------------------------------------------
TH1F* hExpectedDYSF = (TH1F*)inputDYSF->Get("hWTopTagging");
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//
// k estimation
//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
TFile* inputDYmumu = new TFile(Form("%s/%djet/MuMu/DY.root", directory.Data(), njet));
TFile* inputDYee = new TFile(Form("%s/%djet/EE/DY.root", directory.Data(), njet));
TH1F* hNinDYmumu = (TH1F*)inputDYmumu->Get("hNinLooseZevents20.00");
TH1F* hNinDYee = (TH1F*)inputDYee ->Get("hNinLooseZevents20.00");
Double_t NinDYmumu = hNinDYmumu->GetBinContent(2);
Double_t NinDYee = hNinDYee ->GetBinContent(2);
Double_t k = 0.5 * (sqrt(NinDYmumu / NinDYee) + sqrt(NinDYee / NinDYmumu));
Double_t errk = errkSF(NinDYmumu, NinDYee);
if (channel == "MuMu") {
k = 0.5 * sqrt(NinDYmumu / NinDYee);
errk = errkFunction(NinDYmumu, NinDYee);
}
else if (channel == "EE") {
k = 0.5 * sqrt(NinDYee / NinDYmumu);
errk = errkFunction(NinDYee, NinDYmumu);
}
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//
// Counters
//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Double_t NinDYSF [numberMetCuts];
Double_t NinWZSF [numberMetCuts];
Double_t NinZZSF [numberMetCuts];
Double_t NinDataSF[numberMetCuts];
Double_t NinDataOF[numberMetCuts];
Double_t NoutDYSF [numberMetCuts];
Double_t NoutWZSF [numberMetCuts]; // Not used for now
Double_t NoutZZSF [numberMetCuts]; // Not used for now
Double_t NoutDataSF[numberMetCuts];
Double_t NoutDataOF[numberMetCuts];
for (UInt_t nC=0; nC<numberMetCuts-1; nC++) {
NinDYSF [nC] = hNinDYSF [nC]->GetBinContent(2);
NinWZSF [nC] = hNinWZSF [nC]->GetBinContent(2);
NinZZSF [nC] = hNinZZSF [nC]->GetBinContent(2);
NinDataSF [nC] = hNinDataSF [nC]->GetBinContent(2);
NinDataOF [nC] = hNinDataOF [nC]->GetBinContent(2);
NoutDYSF [nC] = hNoutDYSF [nC]->GetBinContent(2);
NoutWZSF [nC] = hNoutWZSF [nC]->GetBinContent(2);
NoutZZSF [nC] = hNoutZZSF [nC]->GetBinContent(2);
NoutDataSF[nC] = hNoutDataSF[nC]->GetBinContent(2);
NoutDataOF[nC] = hNoutDataOF[nC]->GetBinContent(2);
}
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//
// R estimation
//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Double_t R [numberMetCuts];
Double_t RData [numberMetCuts];
Double_t errR [numberMetCuts];
Double_t errRData[numberMetCuts];
// Loop over the met cuts
//----------------------------------------------------------------------------
for (UInt_t nC=0; nC<numberMetCuts-1; nC++) {
R [nC] = NoutDYSF[nC] / NinDYSF[nC];
errR[nC] = errRFunction(NoutDYSF[nC], NinDYSF[nC]);
RData [nC] = RDataFunction (NoutDataSF[nC], NoutDataOF[nC], NinDataSF[nC], NinDataOF[nC], k);
errRData[nC] = errRDataFunction(NoutDataSF[nC], NoutDataOF[nC], NinDataSF[nC], NinDataOF[nC], k, errk);
if (printLevel > 2) {
printf("\n %.0f < mpmet < %.0f GeV\n", MetCuts[nC], MetCuts[nC+1]);
printf(" -------------------------------------------------\n");
printf(" N^{MC}_{out,SF} = %6.1f\n", NoutDYSF[nC]);
printf(" N^{MC}_{in, SF} = %6.1f\n", NinDYSF[nC]);
printf(" N^{data}_{out,SF} = %4.0f\n", NoutDataSF[nC]);
printf(" N^{data}_{out,OF} = %4.0f\n", NoutDataOF[nC]);
printf(" N^{data}_{in, SF} = %4.0f\n", NinDataSF[nC]);
printf(" N^{data}_{in, OF} = %4.0f\n", NinDataOF[nC]);
printf(" k = % 5.3f +- %5.3f\n", k, errk);
printf(" R^{MC} = % 5.3f +- %5.3f\n", R[nC], errR[nC]);
printf(" R^{data} = % 5.3f +- %5.3f\n", RData[nC], errRData[nC]);
}
}
// Estimate the R systematic as the difference between R[2] and R[3]
//----------------------------------------------------------------------------
Int_t iMaxR = 0;
Int_t iMinR = 0;
for (UInt_t nC=0; nC<numberMetCuts-1; nC++) {
if (R[nC] > 0 && R[nC] > R[iMaxR]) iMaxR = nC;
if (R[nC] > 0 && R[nC] < R[iMinR]) iMinR = nC;
}
Int_t theR = 2;
Int_t sysR = 3;
Double_t RelDiffR = (R[theR] > 0) ? fabs(R[theR] - R[sysR]) / R[theR] : -999;
if (printLevel > 0) {
printf("\n [%s] R systematic uncertainty\n", channel.Data());
printf(" -------------------------------------------------\n");
printf(" min R = %5.3f\n", R[iMinR]);
printf(" max R = %5.3f\n", R[iMaxR]);
printf(" R[%d] = %5.3f\n", theR, R[theR]);
printf(" R[%d] = %5.3f\n", sysR, R[sysR]);
printf(" |R[%d]-R[%d]| / R[%d] = %.1f%s\n", theR, sysR, theR, 1e2*RelDiffR, "%");
printf("\n");
}
// Estimate Nout
//----------------------------------------------------------------------------
Double_t NinCountedSFWZ = NinWZSF [sysR];
Double_t NinCountedSFZZ = NinZZSF [sysR];
Double_t NinCountedSFData = NinDataSF[sysR];
Double_t NinCountedOFData = NinDataOF[sysR];
Double_t NinEstSFFinal = NinCountedSFData - k*NinCountedOFData;
Double_t errNinEstSFFinal = errNinEstFunction(NinCountedSFData, NinCountedOFData, k, errk);
Double_t NestSFFinal = R[theR] * NinEstSFFinal;
Double_t errNestSFFinal = errNestFunction(NestSFFinal, R[theR], errR[theR], NinEstSFFinal, errNinEstSFFinal);
Double_t NinEstSFNoDibosonFinal = NinEstSFFinal - NinCountedSFWZ - NinCountedSFZZ;
Double_t errNinEstSFNoDibosonFinal = errNinEstNoDibosonFunction(NinCountedSFData, k, errk, NinCountedOFData, NinCountedSFWZ, NinCountedSFZZ);
Double_t NestSFNoDibosonFinal = R[theR] * NinEstSFNoDibosonFinal;
Double_t errNestSFNoDibosonFinal = errNestFunction(NestSFNoDibosonFinal, R[theR], errR[theR], NinEstSFNoDibosonFinal, errNinEstSFNoDibosonFinal);
Double_t totalError = sqrt(errNestSFNoDibosonFinal*errNestSFNoDibosonFinal + (RelDiffR*NestSFNoDibosonFinal)*(RelDiffR*NestSFNoDibosonFinal));
Double_t SFsf = NestSFNoDibosonFinal / hExpectedDYSF->GetBinContent(2);
if (printLevel > 1) {
printf("\n Analysis results\n");
printf(" -------------------------------------------------\n");
printf(" N^{data}_{in,SF} = %4.0f\n", NinCountedSFData);
printf(" N^{data}_{in,OF} = %4.0f\n", NinCountedOFData);
printf(" k = %5.3f +- %5.3f\n", k, errk);
printf(" R[%d] = %5.3f +- %5.3f\n", theR, R[theR], errR[theR]);
printf(" N^{WZ}_{in,SF} = %7.2f +- %6.2f (stat.) +- %6.2f (syst.)\n",
NinCountedSFWZ, sqrt(NinCountedSFWZ), 0.1*NinCountedSFWZ);
printf(" N^{ZZ}_{in,SF} = %7.2f +- %6.2f (stat.) +- %6.2f (syst.)\n",
NinCountedSFZZ, sqrt(NinCountedSFZZ), 0.1*NinCountedSFZZ);
printf(" N^{est}_{in, SF} = %7.2f +- %6.2f\n", NinEstSFFinal, errNinEstSFFinal);
printf(" N^{est}_{out,SF} = %7.2f +- %6.2f (stat.) +- %6.2f (syst.)\n",
NestSFFinal, errNestSFFinal, RelDiffR*NestSFFinal);
printf(" -------------------------------------------------\n");
printf(" [no VZ] N^{est}_{out,SF} = %7.2f +- %6.2f (stat.) +- %6.2f (syst.) = %7.2f +- %6.2f (stat. + syst.)\n",
NestSFNoDibosonFinal, errNestSFNoDibosonFinal, RelDiffR*NestSFNoDibosonFinal,
NestSFNoDibosonFinal, totalError);
printf(" N^{MC}_{out,SF} = %7.2f +- %6.2f\n",
hExpectedDYSF->GetBinContent(2), hExpectedDYSF->GetBinError(2));
printf(" *** scale factor = %.3f\n\n", SFsf);
}
// Save the result
//----------------------------------------------------------------------------
yield = (useDataDriven) ? NestSFNoDibosonFinal : hExpectedDYSF->GetBinContent(2);
statError = errNestSFNoDibosonFinal;
systError = RelDiffR*NestSFNoDibosonFinal;
scaleFactor = yield / hExpectedDYSF->GetBinContent(2);
// For the note
//----------------------------------------------------------------------------
if (printLevel > 0) {
printf("\n [%s] DY values for the note\n", channel.Data());
printf(" -------------------------------------------------\n");
printf(" final state & R_{MC} & N^{control,data} & N_{DY}^{data} & N_{DY}^{MC} & data/MC\n");
printf(" same flavour & %5.3f $\\pm$ %5.3f & %4.0f & %5.1f $\\pm$ %4.1f & %5.1f $\\pm$ %4.1f & %4.1f\n\n",
R[theR],
errR[theR],
NinCountedSFData,
yield,
statError,
hExpectedDYSF->GetBinContent(2),
hExpectedDYSF->GetBinError(2),
scaleFactor);
printf("\n [%s] DY relative systematic uncertainties\n", channel.Data());
printf(" -------------------------------------------------\n");
printf(" DY normalisation = %.0f (stat.) $\\bigoplus$ %.0f (syst.)\n\n",
1e2*statError/yield, 1e2*systError/yield);
}
// Check
//----------------------------------------------------------------------------
Double_t check = hExpectedDYSF->GetBinContent(2) - NoutDYSF[sysR];
if (check != 0) printf(" WARNING: DY yields do not much by %f\n\n", check);
// Draw histograms
//----------------------------------------------------------------------------
if (drawR) {
Double_t absoluteMin = 999;
TGraphErrors* gR = new TGraphErrors(numberMetCuts-1);
TGraphErrors* gRdata = new TGraphErrors(numberMetCuts-1);
for (UInt_t i=0; i<numberMetCuts-1; i++) {
gR->SetPoint (i, 0.5 * (MetDraw[i+1] + MetDraw[i]), R[i]);
gR->SetPointError(i, 0.5 * (MetDraw[i+1] - MetDraw[i]), errR[i]);
gRdata->SetPoint (i, 0.5 * (MetDraw[i+1] + MetDraw[i]), RData[i]);
gRdata->SetPointError(i, 0.5 * (MetDraw[i+1] - MetDraw[i]), errRData[i]);
if (absoluteMin > (R[i] - errR[i])) absoluteMin = R[i] - errR[i];
if (absoluteMin > (RData[i] - errRData[i])) absoluteMin = RData[i] - errRData[i];
}
if (absoluteMin > 0) absoluteMin = 0;
// Cosmetics
//--------------------------------------------------------------------------
gR->SetMarkerSize (0.9);
gR->SetMarkerStyle(kFullCircle);
gRdata->SetLineColor (kRed+1);
gRdata->SetMarkerColor(kRed+1);
gRdata->SetMarkerSize (0.9);
gRdata->SetMarkerStyle(kFullCircle);
// Draw
//--------------------------------------------------------------------------
canvas = new TCanvas();
TMultiGraph *mgR = new TMultiGraph();
mgR->Add(gRdata);
mgR->Add(gR);
mgR->Draw("ap");
mgR->GetYaxis()->SetTitle("R^{out/in}");
mgR->GetXaxis()->SetTitle("mpmet (GeV)");
mgR->SetMinimum(absoluteMin - 0.1);
mgR->SetMaximum(1.0);
// Legend
//--------------------------------------------------------------------------
TLegend* lmgR = new TLegend(0.72, 0.68, 0.92, 0.88);
lmgR->AddEntry(gR, " DY MC", "lp");
lmgR->AddEntry(gRdata," data", "lp");
lmgR->SetFillColor(0);
lmgR->SetTextAlign(12);
lmgR->SetTextFont (42);
lmgR->SetTextSize (0.04);
if (channel == "SF") lmgR->SetHeader("ee + #mu#mu");
else if (channel == "EE") lmgR->SetHeader("ee");
else if (channel == "MuMu") lmgR->SetHeader("#mu#mu");
lmgR->Draw("same");
// Line at zero
//--------------------------------------------------------------------------
TLine* zeroLine = new TLine(canvas->GetUxmin(), 0.0, canvas->GetUxmax(), 0.0);
zeroLine->SetLineStyle(3);
zeroLine->SetLineWidth(2);
zeroLine->Draw("same");
mgR->Draw("p,same");
// Save
//--------------------------------------------------------------------------
canvas->SaveAs("R_" + channel + ".png");
}
}
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//
// DY
//
// channel = SF, MuMu, EE
//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
void doDY(char jetbin,
TString channel,
TString ID = "MediumIDTighterIP",
TString bunch = "50ns",
Bool_t useDataDriven = true,
Int_t printLevel = 100,
Bool_t drawR = true)
{
cout<<"nJet = "<<jetbin<<endl;
cout<<"Channel = "<<channel<<endl;
Double_t yield;
Double_t statError;
Double_t systError;
Double_t scaleFactor;
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//
// Input files
//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
TString path = "../rootFiles/" + channel + "/" + ID + "/" + bunch + "/";
TString pathOF = "../rootFiles/OF/" + ID + "/" + bunch + "/";
TFile* inputDYSF = new TFile(path + "DY.root");
TFile* inputVVSF = new TFile(path + "VV.root");
TFile* inputDataSF = new TFile(path + "Data2015.root");
TFile* inputDataOF = new TFile(pathOF + "Data2015.root");
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//
// Input histograms
//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
TH1F* hNinDYSF [numberMetCuts];
TH1F* hNinVVSF [numberMetCuts];
TH1F* hNinDataSF[numberMetCuts];
TH1F* hNinDataOF[numberMetCuts];
TH1F* hNoutDYSF [numberMetCuts];
TH1F* hNoutVVSF [numberMetCuts];
TH1F* hNoutDataSF[numberMetCuts];
TH1F* hNoutDataOF[numberMetCuts];
for (UInt_t nC=0; nC<numberMetCuts; nC++) {
hNinDYSF [nC] = (TH1F*)inputDYSF ->Get(Form("hNinZevents%.i%.c", MetCuts[nC],jetbin));
cout<<Form("hNinZevents%.i%.c", MetCuts[nC],jetbin)<<endl;
hNinVVSF [nC] = (TH1F*)inputVVSF ->Get(Form("hNinZevents%.i%.c", MetCuts[nC],jetbin));
hNinDataSF[nC] = (TH1F*)inputDataSF->Get(Form("hNinZevents%.i%.c", MetCuts[nC],jetbin));
hNinDataOF[nC] = (TH1F*)inputDataOF->Get(Form("hNinZevents%.i%.c", MetCuts[nC],jetbin));
hNoutDYSF [nC] = (TH1F*)inputDYSF ->Get(Form("hNoutZevents%.i%.c", MetCuts[nC],jetbin));
hNoutVVSF [nC] = (TH1F*)inputVVSF ->Get(Form("hNoutZevents%.i%.c", MetCuts[nC],jetbin));
hNoutDataSF[nC] = (TH1F*)inputDataSF->Get(Form("hNoutZevents%.i%.c", MetCuts[nC],jetbin));
hNoutDataOF[nC] = (TH1F*)inputDataOF->Get(Form("hNoutZevents%.i%.c", MetCuts[nC],jetbin));
}
// Histogram at analysis level
//----------------------------------------
TH1F* hExpectedDYSF = (TH1F*)inputDYSF->Get(Form("hPtLepton1WWLevel%.c", jetbin));//("hWTopTagging");
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//
// k estimation
//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
TFile* inputDYmumu = new TFile("../rootFiles/MuMu/" + ID + "/" + bunch + "/DY.root");
TFile* inputDYee = new TFile("../rootFiles/EE/" + ID + "/" + bunch + "/DY.root");
TH1F* hNinDYmumu = (TH1F*)inputDYmumu->Get(Form("hNinLooseZevents20%.c", jetbin));
TH1F* hNinDYee = (TH1F*)inputDYee ->Get(Form("hNinLooseZevents20%.c", jetbin));
Double_t NinDYmumu = hNinDYmumu -> GetBinContent(2);
Double_t NinDYee = hNinDYee -> GetBinContent(2);
Double_t k = 0.5 * (sqrt(NinDYmumu / NinDYee) + sqrt(NinDYee / NinDYmumu));
Double_t errk = errkSF(NinDYmumu, NinDYee);
if (channel == "MuMu") {
k = 0.5 * sqrt(NinDYmumu / NinDYee);
errk = errkFunction(NinDYmumu, NinDYee);
}
else if (channel == "EE") {
k = 0.5 * sqrt(NinDYee / NinDYmumu);
errk = errkFunction(NinDYee, NinDYmumu);
}
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//
// Counters
//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Double_t NinDYSF [numberMetCuts];
Double_t NinVVSF [numberMetCuts];
Double_t NinDataSF[numberMetCuts];
Double_t NinDataOF[numberMetCuts];
Double_t NoutDYSF [numberMetCuts];
Double_t NoutVVSF [numberMetCuts]; // Not used for now
Double_t NoutDataSF[numberMetCuts];
Double_t NoutDataOF[numberMetCuts];
for (UInt_t nC=0; nC<numberMetCuts-1; nC++) {
NinDYSF [nC] = hNinDYSF [nC]->GetBinContent(2);
NinVVSF [nC] = hNinVVSF [nC]->GetBinContent(2);
NinDataSF [nC] = hNinDataSF [nC]->GetBinContent(2);
NinDataOF [nC] = hNinDataOF [nC]->GetBinContent(2);
NoutDYSF [nC] = hNoutDYSF [nC]->GetBinContent(2);
NoutVVSF [nC] = hNoutVVSF [nC]->GetBinContent(2);
NoutDataSF[nC] = hNoutDataSF[nC]->GetBinContent(2);
NoutDataOF[nC] = hNoutDataOF[nC]->GetBinContent(2);
}
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//
// R estimation
//
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Double_t R [numberMetCuts];
Double_t RData [numberMetCuts];
Double_t errR [numberMetCuts];
Double_t errRData[numberMetCuts];
// Loop over the met cuts
//----------------------------------------------------------------------------
for (UInt_t nC=0; nC<numberMetCuts-1; nC++) {
R [nC] = NoutDYSF[nC] / NinDYSF[nC];
errR[nC] = errRFunction(NoutDYSF[nC], NinDYSF[nC]);
RData [nC] = RDataFunction (NoutDataSF[nC], NoutDataOF[nC], NinDataSF[nC], NinDataOF[nC], k);
errRData[nC] = errRDataFunction(NoutDataSF[nC], NoutDataOF[nC], NinDataSF[nC], NinDataOF[nC], k, errk);
if (printLevel > 2) {
printf("\n %.0f < mpmet < %.0f GeV\n", MetCuts[nC], MetCuts[nC+1]);
printf(" -------------------------------------------------\n");
printf(" N^{MC}_{out,SF} = %6.1f\n", NoutDYSF[nC]);
printf(" N^{MC}_{in, SF} = %6.1f\n", NinDYSF[nC]);
printf(" N^{data}_{out,SF} = %4.0f\n", NoutDataSF[nC]);
printf(" N^{data}_{out,OF} = %4.0f\n", NoutDataOF[nC]);
printf(" N^{data}_{in, SF} = %4.0f\n", NinDataSF[nC]);
printf(" N^{data}_{in, OF} = %4.0f\n", NinDataOF[nC]);
printf(" k = % 5.3f +- %5.3f\n", k, errk);
printf(" R^{MC} = % 5.3f +- %5.3f\n", R[nC], errR[nC]);
printf(" R^{data} = % 5.3f +- %5.3f\n", RData[nC], errRData[nC]);
}
}
// Estimate the R systematic as the difference between R[2] and R[3]
//----------------------------------------------------------------------------
Int_t iMaxR = 0;
Int_t iMinR = 0;
for (UInt_t nC=0; nC<numberMetCuts-1; nC++) {
if (R[nC] > 0 && R[nC] > R[iMaxR]) iMaxR = nC;
if (R[nC] > 0 && R[nC] < R[iMinR]) iMinR = nC;
}
Int_t theR = 2;
Int_t sysR = 3;
Double_t RelDiffR = (R[theR] > 0) ? fabs(R[theR] - R[sysR]) / R[theR] : -999;
if (printLevel > 0) {
printf("\n [%s] R systematic uncertainty\n", channel.Data());
printf(" -------------------------------------------------\n");
printf(" min R = %5.3f\n", R[iMinR]);
printf(" max R = %5.3f\n", R[iMaxR]);
printf(" R[%d] = %5.3f\n", theR, R[theR]);
printf(" R[%d] = %5.3f\n", sysR, R[sysR]);
printf(" |R[%d]-R[%d]| / R[%d] = %.1f%s\n", theR, sysR, theR, 1e2*RelDiffR, "%");
printf("\n");
}
// Estimate Nout
//----------------------------------------------------------------------------
Double_t NinCountedSFVV = NinVVSF [sysR];
Double_t NinCountedSFData = NinDataSF[sysR];
Double_t NinCountedOFData = NinDataOF[sysR];
Double_t NinEstSFFinal = NinCountedSFData - k*NinCountedOFData;
Double_t errNinEstSFFinal = errNinEstFunction(NinCountedSFData, NinCountedOFData, k, errk);
Double_t NestSFFinal = R[theR] * NinEstSFFinal;
Double_t errNestSFFinal = errNestFunction(NestSFFinal, R[theR], errR[theR], NinEstSFFinal, errNinEstSFFinal);
Double_t NinEstSFNoDibosonFinal = NinEstSFFinal - NinCountedSFVV;
Double_t errNinEstSFNoDibosonFinal = errNinEstNoDibosonFunction(NinCountedSFData, k, errk, NinCountedOFData, NinCountedSFVV);
Double_t NestSFNoDibosonFinal = R[theR] * NinEstSFNoDibosonFinal;
Double_t errNestSFNoDibosonFinal = errNestFunction(NestSFNoDibosonFinal, R[theR], errR[theR], NinEstSFNoDibosonFinal, errNinEstSFNoDibosonFinal);
Double_t totalError = sqrt(errNestSFNoDibosonFinal*errNestSFNoDibosonFinal + (RelDiffR*NestSFNoDibosonFinal)*(RelDiffR*NestSFNoDibosonFinal));
Double_t SFsf = NestSFNoDibosonFinal / hExpectedDYSF->Integral();
if (printLevel > 1) {
printf("\n Analysis results\n");
printf(" -------------------------------------------------\n");
printf(" N^{data}_{in,SF} = %4.0f\n", NinCountedSFData);
printf(" N^{data}_{in,OF} = %4.0f\n", NinCountedOFData);
printf(" k = %5.3f +- %5.3f\n", k, errk);
printf(" R[%d] = %5.3f +- %5.3f\n", theR, R[theR], errR[theR]);
printf(" N^{VV}_{in,SF} = %7.2f +- %6.2f (stat.) +- %6.2f (syst.)\n",
NinCountedSFVV, sqrt(NinCountedSFVV), 0.1*NinCountedSFVV);
printf(" N^{est}_{in, SF} = %7.2f +- %6.2f\n", NinEstSFFinal, errNinEstSFFinal);
printf(" N^{est}_{out,SF} = %7.2f +- %6.2f (stat.) +- %6.2f (syst.)\n",
NestSFFinal, errNestSFFinal, RelDiffR*NestSFFinal);
printf(" -------------------------------------------------\n");
printf(" [no VZ] N^{est}_{out,SF} = %7.2f +- %6.2f (stat.) +- %6.2f (syst.) = %7.2f +- %6.2f (stat. + syst.)\n",
NestSFNoDibosonFinal, errNestSFNoDibosonFinal, RelDiffR*NestSFNoDibosonFinal,
NestSFNoDibosonFinal, totalError);
printf(" N^{MC}_{out,SF} = %7.2f +- %6.2f\n",
hExpectedDYSF->Integral(), sqrt(hExpectedDYSF->Integral()));
printf(" *** scale factor = %.3f\n\n", SFsf);
}
// Save the result
//----------------------------------------------------------------------------
yield = (useDataDriven) ? NestSFNoDibosonFinal : hExpectedDYSF->Integral();
statError = errNestSFNoDibosonFinal;
systError = RelDiffR*NestSFNoDibosonFinal;
scaleFactor = yield / hExpectedDYSF->Integral();
// For the note
//----------------------------------------------------------------------------
if (printLevel > 0) {
printf("\n [%s] DY values for the note\n", channel.Data());
printf(" -------------------------------------------------\n");
printf(" final state & R_{MC} & N^{control,data} & N_{DY}^{data} & N_{DY}^{MC} & data/MC\n");
printf(" same flavour & %5.3f $\\pm$ %5.3f & %4.0f & %5.1f $\\pm$ %4.1f & %5.1f $\\pm$ %4.1f & %4.1f\n\n",
R[theR],
errR[theR],
NinCountedSFData,
yield,
statError,
hExpectedDYSF->Integral(),
sqrt(hExpectedDYSF->Integral()),
scaleFactor);
printf("\n [%s] DY relative systematic uncertainties\n", channel.Data());
printf(" -------------------------------------------------\n");
printf(" DY normalisation = %.0f (stat.) $\\bigoplus$ %.0f (syst.)\n\n",
1e2*statError/yield, 1e2*systError/yield);
}
// Check
//----------------------------------------------------------------------------
Double_t check = hExpectedDYSF->Integral() - NoutDYSF[sysR];
if (check != 0) printf(" WARNING: DY yields do not much by %f\n\n", check);
// Draw histograms
//----------------------------------------------------------------------------
if (drawR) {
Double_t absoluteMin = 999;
TGraphErrors* gR = new TGraphErrors(numberMetCuts-1);
TGraphErrors* gRdata = new TGraphErrors(numberMetCuts-1);
for (UInt_t i=0; i<numberMetCuts-1; i++) {
gR->SetPoint (i, 0.5 * (MetDraw[i+1] + MetDraw[i]), R[i]);
gR->SetPointError(i, 0.5 * (MetDraw[i+1] - MetDraw[i]), errR[i]);
gRdata->SetPoint (i, 0.5 * (MetDraw[i+1] + MetDraw[i]), RData[i]);
gRdata->SetPointError(i, 0.5 * (MetDraw[i+1] - MetDraw[i]), errRData[i]);
if (absoluteMin > (R[i] - errR[i])) absoluteMin = R[i] - errR[i];
if (absoluteMin > (RData[i] - errRData[i])) absoluteMin = RData[i] - errRData[i];
}
if (absoluteMin > 0) absoluteMin = 0;
// Cosmetics
//--------------------------------------------------------------------------
gR->SetMarkerSize (0.9);
gR->SetMarkerStyle(kFullCircle);
gRdata->SetLineColor (kRed+1);
gRdata->SetMarkerColor(kRed+1);
gRdata->SetMarkerSize (0.9);
gRdata->SetMarkerStyle(kFullCircle);
// Draw
//--------------------------------------------------------------------------
canvas = new TCanvas();
TMultiGraph *mgR = new TMultiGraph();
mgR->Add(gRdata);
mgR->Add(gR);
mgR->Draw("ap");
mgR->GetYaxis()->SetTitle("R^{out/in}");
mgR->GetXaxis()->SetTitle("mpmet (GeV)");
mgR->SetMinimum(absoluteMin - 0.1);
mgR->SetMaximum(1.0);
// Legend
//--------------------------------------------------------------------------
TLegend* lmgR = new TLegend(0.62, 0.68, 0.86, 0.88);
lmgR->AddEntry(gR, " DY MC", "lp");
lmgR->AddEntry(gRdata," data", "lp");
lmgR->SetFillColor(0);
lmgR->SetLineColor(kWhite);
lmgR->SetTextAlign(12);
lmgR->SetTextFont (42);
lmgR->SetTextSize (0.04);
if (channel == "SF") lmgR->SetHeader("ee + #mu#mu");
else if (channel == "EE") lmgR->SetHeader("ee");
else if (channel == "MuMu") lmgR->SetHeader("#mu#mu");
lmgR->Draw();
// Line at zero
//--------------------------------------------------------------------------
TLine* zeroLine = new TLine(canvas->GetUxmin(), 0.0, canvas->GetUxmax(), 0.0);
zeroLine->SetLineStyle(3);
zeroLine->SetLineWidth(2);
zeroLine->Draw("same");
mgR->Draw("p,same");
// Save
//--------------------------------------------------------------------------
lmgR->Draw("same");
if (jetbin == '3'){
DrawTLatex(0.725, 0.65, 0.04, "Inclusive");
canvas->SaveAs("R_" + channel + "_Inclusive.png");
canvas->SaveAs("R_" + channel + "_Inclusive.pdf");
}
else{ //Inclusive
if (jetbin == '0') DrawTLatex(0.725, 0.65, 0.04, "0 Jet ");
else if (jetbin == '1') DrawTLatex(0.725, 0.65, 0.04, "1 Jet ");
else if (jetbin == '2') DrawTLatex(0.725, 0.65, 0.04, "2+ Jets ");
canvas->SaveAs("R_" + channel + "_" + jetbin + "jet.png");
canvas->SaveAs("R_" + channel + "_" + jetbin + "jet.pdf");
}
}
}
