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doAnalysis.cpp
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#include <TFile.h>
#include <TString.h>
#include <TGraphErrors.h>
#include <TROOT.h>
#include <TStyle.h>
#include <TMath.h>
#include <TMatrixD.h>
#include <TVectorD.h>
#include <TH2.h>
#include <TF2.h>
#include <TCanvas.h>
#include <TPad.h>
#include <TGaxis.h>
#include <TLegend.h>
#include <fstream>
#include <iostream>
#undef doGaussian
#define rebin 1
using namespace std;
Double_t chiSquare(Double_t* x, Double_t* p) {
return p[0]*TMath::Power(x[0],p[1]/2.-1.)*TMath::Exp(-x[0]/2.);
}
Double_t gaussian2d(Double_t* x, Double_t* p) {
return p[0]*TMath::Exp(-(1./(2.*(1-p[5]))) * ((x[0]-p[1])*(x[0]-p[1])/(p[3]*p[3])+(x[1]-p[2])*(x[1]-p[2])/(p[4]*p[4])-2*p[5]*(x[0]-p[1])*(x[1]-p[2])/(p[3]*p[4])));
}
int main(int argc, char** argv)
{
gROOT->SetStyle("Plain");
gStyle->SetOptStat("MR");
gStyle->SetOptFit(0111);
gStyle->SetTitleBorderSize(0);
gStyle->SetPalette(1, 0);
// The ResBos mass
const Double_t trueMass = 80.419;
// Define what we want
TH1D* mt_dists[300/rebin];
TH1D* pt_dists[200/rebin];
TH1D* met_dists[200/rebin];
TH1D* mt_poisson[300/rebin];
TH1D* pt_poisson[200/rebin];
TH1D* met_poisson[200/rebin];
TH1D* mtUnbiasedPull = new TH1D("mtUnbiasedPull", "", 50, -5., 5.);
TH1D* ptUnbiasedPull = new TH1D("ptUnbiasedPull", "", 50, -5., 5.);
TH1D* metUnbiasedPull = new TH1D("metUnbiasedPull", "", 50, -5., 5.);
TH2D* mtptUnbiasedPull = new TH2D("mtptUnbiasedPull", "", 20, -5., 5., 20, -5., 5.);
TH2D* ptmetUnbiasedPull = new TH2D("ptmetUnbiasedPull", "", 20, -5., 5., 20, -5., 5.);
TH2D* metmtUnbiasedPull = new TH2D("metmtUnbiasedPull", "", 20, -5., 5., 20, -5., 5.);
TH1D* mtPull = new TH1D("mtPull", "", 50, -5., 5.);
TH1D* ptPull = new TH1D("ptPull", "", 50, -5., 5.);
TH1D* metPull = new TH1D("metPull", "", 50, -5., 5.);
TH2D* mtptPull = new TH2D("mtptPull", "", 20, -5., 5., 20, -5., 5.);
TH2D* ptmetPull = new TH2D("ptmetPull", "", 20, -5., 5., 20, -5., 5.);
TH2D* metmtPull = new TH2D("metmtPull", "", 20, -5., 5., 20, -5., 5.);
TH1D* mtJKMean = new TH1D("mtJKMean", "", 50, 80.380, 80.440);
TH1D* ptJKMean = new TH1D("ptJKMean", "", 50, 80.380, 80.440);
TH1D* metJKMean = new TH1D("metJKMean", "", 50, 80.380, 80.440);
TH1D* mtJKSigma = new TH1D("mtJKSigma", "", 50, 0.005, 0.060);
TH1D* ptJKSigma = new TH1D("ptJKSigma", "", 50, 0.005, 0.060);
TH1D* metJKSigma = new TH1D("metJKSigma", "", 50, 0.005, 0.060);
TH1D* mtJKUnbiasedSigma = new TH1D("mtJKUnbiasedSigma", "", 50, 0.005, 0.060);
TH1D* ptJKUnbiasedSigma = new TH1D("ptJKUnbiasedSigma", "", 50, 0.005, 0.060);
TH1D* metJKUnbiasedSigma = new TH1D("metJKUnbiasedSigma", "", 50, 0.005, 0.060);
TH1D* mtptJKCorr = new TH1D("mtptJKCorr", "", 20, 0.0, 1.0);
TH1D* metmtJKCorr = new TH1D("metmtJKCorr", "", 20, 0.0, 1.0);
TH1D* ptmetJKCorr = new TH1D("ptmetJKCorr", "", 20, 0.0, 1.0);
// Storage for the data
TGraph* mtptData = new TGraph();
TGraph* metmtData = new TGraph();
TGraph* ptmetData = new TGraph();
TGraphErrors* mtptScatter = new TGraphErrors();
TGraphErrors* metmtScatter = new TGraphErrors();
TGraphErrors* ptmetScatter = new TGraphErrors();
// Reads the data
cout << "Getting the data" << endl;
TH1D* mt_sum = new TH1D("mt_sum", "", 300/rebin, 50., 200.);
TH1D* mt_sqrtmean = new TH1D("mt_sqrtmean", "", 300/rebin, 50., 200.);
TH1D* mt_mean = new TH1D("mt_mean", "", 300/rebin, 50., 200.);
TH1D* mt_rms = new TH1D("mt_rms", "", 300/rebin, 50., 200.);
TH1D* mt_rms_ratio = new TH1D("mt_rms_ratio", "", 300/rebin, 50., 200.);
TH1D* mt_rmsfrac = new TH1D("mt_rmsfrac", "", 300/rebin, 50., 200.);
TH2D* mt_sum2 = new TH2D("mt_sum2", "", 300/rebin, 50., 200., 300/rebin, 50., 200.);
TH2D* mt_corr = new TH2D("mt_corr", "", 300/rebin, 50., 200., 300/rebin, 50., 200.);
TH1D* elecpt_sum = new TH1D("elecpt_sum", "", 200/rebin, 0., 100.);
TH1D* elecpt_mean = new TH1D("elecpt_mean", "", 200/rebin, 0., 100.);
TH1D* elecpt_sqrtmean = new TH1D("elecpt_sqrtmean", "", 200/rebin, 0., 100.);
TH1D* elecpt_rms = new TH1D("elecpt_rms", "", 200/rebin, 0., 100.);
TH1D* elecpt_rms_ratio = new TH1D("elecpt_rms_ratio", "", 200/rebin, 0., 100.);
TH1D* elecpt_rmsfrac = new TH1D("elecpt_rmsfrac", "", 200/rebin, 0., 100.);
TH2D* elecpt_sum2 = new TH2D("elecpt_sum2", "", 200/rebin, 0., 100., 200/rebin, 0., 100.);
TH2D* elecpt_corr = new TH2D("elecpt_corr", "", 200/rebin, 0., 100., 200/rebin, 0., 100.);
TH1D* met_sum = new TH1D("met_sum", "", 200/rebin, 0., 100.);
TH1D* met_mean = new TH1D("met_mean", "", 200/rebin, 0., 100.);
TH1D* met_sqrtmean = new TH1D("met_sqrtmean", "", 200/rebin, 0., 100.);
TH1D* met_rms = new TH1D("met_rms", "", 200/rebin, 0., 100.);
TH1D* met_rms_ratio = new TH1D("met_rms_ratio", "", 200/rebin, 0., 100.);
TH1D* met_rmsfrac = new TH1D("met_rmsfrac", "", 200/rebin, 0., 100.);
TH2D* met_sum2 = new TH2D("met_sum2", "", 200/rebin, 0., 100., 200/rebin, 0., 100.);
TH2D* met_corr = new TH2D("met_corr", "", 200/rebin, 0., 100., 200/rebin, 0., 100.);
Double_t corr_n = 0;
ifstream _fileList(argv[2]);
TString _reader;
while (!_fileList.eof()) {
_reader.ReadLine(_fileList);
if (_reader.Length() < 5) continue;
TFile* tempFile = TFile::Open(_reader);
if (!tempFile->IsOpen()) continue;
TH1D* tempmt = (TH1D*) tempFile->Get("default/hWcandMt_CC");
TH1D* tempelecpt = (TH1D*) tempFile->Get("default/hWcandElecPt_CC");
TH1D* tempmet = (TH1D*) tempFile->Get("default/hWcandMet_CC");
tempmt->Rebin(rebin);
tempelecpt->Rebin(rebin);
tempmet->Rebin(rebin);
for (int ibin=1; ibin<=tempmt->GetNbinsX(); ibin++) {
mt_sum->Fill(tempmt->GetXaxis()->GetBinCenter(ibin), tempmt->GetBinContent(ibin));
for (int jbin=1; jbin<=tempmt->GetNbinsX(); jbin++) {
mt_sum2->Fill(tempmt->GetXaxis()->GetBinCenter(ibin), tempmt->GetXaxis()->GetBinCenter(jbin), tempmt->GetBinContent(ibin)*tempmt->GetBinContent(jbin));
}
}
for (int ibin=1; ibin<=tempelecpt->GetNbinsX(); ibin++) {
elecpt_sum->Fill(tempelecpt->GetXaxis()->GetBinCenter(ibin), tempelecpt->GetBinContent(ibin));
for (int jbin=1; jbin<=tempelecpt->GetNbinsX(); jbin++) {
elecpt_sum2->Fill(tempelecpt->GetXaxis()->GetBinCenter(ibin), tempelecpt->GetXaxis()->GetBinCenter(jbin), tempelecpt->GetBinContent(ibin)*tempelecpt->GetBinContent(jbin));
}
}
for (int ibin=1; ibin<=tempmet->GetNbinsX(); ibin++) {
met_sum->Fill(tempmet->GetXaxis()->GetBinCenter(ibin), tempmet->GetBinContent(ibin));
for (int jbin=1; jbin<=tempmet->GetNbinsX(); jbin++) {
met_sum2->Fill(tempmet->GetXaxis()->GetBinCenter(ibin), tempmet->GetXaxis()->GetBinCenter(jbin), tempmet->GetBinContent(ibin)*tempmet->GetBinContent(jbin));
}
}
corr_n++;
tempFile->Close();
}
_fileList.close();
for (int ibin=1; ibin<=mt_rms->GetNbinsX(); ibin++) {
mt_mean->SetBinContent(ibin, mt_sum->GetBinContent(ibin)/corr_n);
mt_sqrtmean->SetBinContent(ibin, TMath::Sqrt(mt_sum->GetBinContent(ibin)/corr_n));
mt_rms->SetBinContent(ibin, TMath::Sqrt(mt_sum2->GetBinContent(ibin, ibin)/corr_n-mt_sum->GetBinContent(ibin)*mt_sum->GetBinContent(ibin)/(corr_n*corr_n)));
mt_rmsfrac->SetBinContent(ibin, mt_rms->GetBinContent(ibin)/mt_mean->GetBinContent(ibin));
}
mt_rms_ratio->Divide(mt_rms, mt_sqrtmean, 1., 1.);
for (int ibin=1; ibin<=elecpt_rms->GetNbinsX(); ibin++) {
elecpt_mean->SetBinContent(ibin, elecpt_sum->GetBinContent(ibin)/corr_n);
elecpt_sqrtmean->SetBinContent(ibin, TMath::Sqrt(elecpt_sum->GetBinContent(ibin)/corr_n));
elecpt_rms->SetBinContent(ibin, TMath::Sqrt(elecpt_sum2->GetBinContent(ibin, ibin)/corr_n-elecpt_sum->GetBinContent(ibin)*elecpt_sum->GetBinContent(ibin)/(corr_n*corr_n)));
elecpt_rmsfrac->SetBinContent(ibin, elecpt_rms->GetBinContent(ibin)/elecpt_mean->GetBinContent(ibin));
}
elecpt_rms_ratio->Divide(elecpt_rms, elecpt_sqrtmean, 1., 1.);
for (int ibin=1; ibin<=met_rms->GetNbinsX(); ibin++) {
met_mean->SetBinContent(ibin, met_sum->GetBinContent(ibin)/corr_n);
met_sqrtmean->SetBinContent(ibin, TMath::Sqrt(met_sum->GetBinContent(ibin)/corr_n));
met_rms->SetBinContent(ibin, TMath::Sqrt(met_sum2->GetBinContent(ibin, ibin)/corr_n-met_sum->GetBinContent(ibin)*met_sum->GetBinContent(ibin)/(corr_n*corr_n)));
met_rmsfrac->SetBinContent(ibin, met_rms->GetBinContent(ibin)/met_mean->GetBinContent(ibin));
}
met_rms_ratio->Divide(met_rms, met_sqrtmean, 1., 1.);
for (int ibin=1; ibin<=mt_corr->GetNbinsX(); ibin++)
for (int jbin=1; jbin<=mt_corr->GetNbinsY(); jbin++) {
if (ibin == jbin) continue;
mt_corr->SetBinContent(ibin, jbin, (mt_sum2->GetBinContent(ibin,jbin)/corr_n - mt_sum->GetBinContent(ibin)*mt_sum->GetBinContent(jbin)/(corr_n*corr_n))/(mt_rms->GetBinContent(ibin)*mt_rms->GetBinContent(jbin)));
}
for (int ibin=1; ibin<=elecpt_corr->GetNbinsX(); ibin++)
for (int jbin=1; jbin<=elecpt_corr->GetNbinsY(); jbin++) {
if (ibin == jbin) continue;
elecpt_corr->SetBinContent(ibin, jbin, (elecpt_sum2->GetBinContent(ibin,jbin)/corr_n - elecpt_sum->GetBinContent(ibin)*elecpt_sum->GetBinContent(jbin)/(corr_n*corr_n))/(elecpt_rms->GetBinContent(ibin)*elecpt_rms->GetBinContent(jbin)));
}
for (int ibin=1; ibin<=met_corr->GetNbinsX(); ibin++)
for (int jbin=1; jbin<=met_corr->GetNbinsY(); jbin++) {
if (ibin == jbin) continue;
met_corr->SetBinContent(ibin, jbin, (met_sum2->GetBinContent(ibin,jbin)/corr_n - met_sum->GetBinContent(ibin)*met_sum->GetBinContent(jbin)/(corr_n*corr_n))/(met_rms->GetBinContent(ibin)*met_rms->GetBinContent(jbin)));
}
for (int i=0; i<300/rebin; i++) {
mt_dists[i] = new TH1D(TString::Format("mt_dists_%d", i), "", 25, mt_mean->GetBinContent(i)-5*mt_rms->GetBinContent(i), mt_mean->GetBinContent(i)+5*mt_rms->GetBinContent(i));
mt_poisson[i] = new TH1D(TString::Format("mt_poisson_%d", i), "", 25, mt_mean->GetBinContent(i)-5*mt_rms->GetBinContent(i), mt_mean->GetBinContent(i)+5*mt_rms->GetBinContent(i));
}
for (int i=0; i<200/rebin; i++) {
pt_dists[i] = new TH1D(TString::Format("pt_dists_%d", i), "", 25, elecpt_mean->GetBinContent(i)-5*elecpt_rms->GetBinContent(i), elecpt_mean->GetBinContent(i)+5*elecpt_rms->GetBinContent(i));
pt_poisson[i] = new TH1D(TString::Format("pt_poisson_%d", i), "", 25, elecpt_mean->GetBinContent(i)-5*elecpt_rms->GetBinContent(i), elecpt_mean->GetBinContent(i)+5*elecpt_rms->GetBinContent(i));
}
for (int i=0; i<200/rebin; i++) {
met_dists[i] = new TH1D(TString::Format("met_dists_%d", i), "", 25, met_mean->GetBinContent(i)-5*met_rms->GetBinContent(i), met_mean->GetBinContent(i)+5*met_rms->GetBinContent(i));
met_poisson[i] = new TH1D(TString::Format("met_poisson_%d", i), "", 25, met_mean->GetBinContent(i)-5*met_rms->GetBinContent(i), met_mean->GetBinContent(i)+5*met_rms->GetBinContent(i));
}
ifstream _fileList2(argv[2]);
while (!_fileList2.eof()) {
_reader.ReadLine(_fileList2);
if (_reader.Length() < 5) continue;
TFile* tempFile = TFile::Open(_reader);
if (!tempFile->IsOpen()) continue;
TH1D* tempmt = (TH1D*) tempFile->Get("default/hWcandMt_CC");
TH1D* tempelecpt = (TH1D*) tempFile->Get("default/hWcandElecPt_CC");
TH1D* tempmet = (TH1D*) tempFile->Get("default/hWcandMet_CC");
tempmt->Rebin(rebin);
tempelecpt->Rebin(rebin);
tempmet->Rebin(rebin);
for (int i=0; i<300/rebin; i++)
mt_dists[i]->Fill(tempmt->GetBinContent(i));
for (int i=0; i<200/rebin; i++)
pt_dists[i]->Fill(tempelecpt->GetBinContent(i));
for (int i=0; i<200/rebin; i++)
met_dists[i]->Fill(tempmet->GetBinContent(i));
}
for (int i=0; i<300/rebin; i++) {
Double_t mt_dists_integral = mt_dists[i]->Integral();
if (mt_dists_integral == 0) continue;
mt_dists[i]->Sumw2();
mt_dists[i]->Scale(1/mt_dists_integral);
for (int j=1; j<=mt_poisson[i]->GetNbinsX(); j++) {
#ifdef doGaussian
mt_poisson[i]->SetBinContent(j, TMath::Gaus(mt_poisson[i]->GetXaxis()->GetBinCenter(j), mt_mean->GetBinContent(i), 1.18411*TMath::Sqrt(mt_mean->GetBinContent(i))));
#else
mt_poisson[i]->SetBinContent(j, TMath::PoissonI(mt_poisson[i]->GetXaxis()->GetBinCenter(j), mt_mean->GetBinContent(i)));
#endif
}
}
for (int i=0; i<200/rebin; i++) {
Double_t pt_dists_integral = pt_dists[i]->Integral();
if (pt_dists_integral == 0) continue;
pt_dists[i]->Sumw2();
pt_dists[i]->Scale(1/pt_dists_integral);
for (int j=1; j<=pt_poisson[i]->GetNbinsX(); j++) {
#ifdef doGaussian
pt_poisson[i]->SetBinContent(j, TMath::Gaus(pt_poisson[i]->GetXaxis()->GetBinCenter(j), elecpt_mean->GetBinContent(i), 1.18378*TMath::Sqrt(elecpt_mean->GetBinContent(i))));
#else
pt_poisson[i]->SetBinContent(j, TMath::PoissonI(pt_poisson[i]->GetXaxis()->GetBinCenter(j), elecpt_mean->GetBinContent(i)));
#endif
}
}
for (int i=0; i<200/rebin; i++) {
Double_t met_dists_integral = met_dists[i]->Integral();
if (met_dists_integral == 0) continue;
met_dists[i]->Sumw2();
met_dists[i]->Scale(1/met_dists_integral);
for (int j=1; j<=met_poisson[i]->GetNbinsX(); j++) {
#ifdef doGaussian
met_poisson[i]->SetBinContent(j, TMath::Gaus(met_poisson[i]->GetXaxis()->GetBinCenter(j), met_mean->GetBinContent(i), 1.18663*TMath::Sqrt(met_mean->GetBinContent(i))));
#else
met_poisson[i]->SetBinContent(j, TMath::PoissonI(met_poisson[i]->GetXaxis()->GetBinCenter(j), met_mean->GetBinContent(i)));
#endif
}
}
_fileList2.close();
ifstream fileList(argv[1]);
TString reader;
Int_t pseudoNumber = 0;
while (!fileList.eof()) {
reader.ReadLine(fileList);
if (reader.Length() < 5) continue;
TFile* tempFile = TFile::Open(reader);
if (!tempFile->IsOpen()) continue;
TGraphErrors* mtGraph = (TGraphErrors*) tempFile->Get("wmass_Mt");
TGraphErrors* ptGraph = (TGraphErrors*) tempFile->Get("wmass_Pt");
TGraphErrors* metGraph = (TGraphErrors*) tempFile->Get("wmass_MET");
mtptData->SetPoint(pseudoNumber, mtGraph->GetY()[0], ptGraph->GetY()[0]);
metmtData->SetPoint(pseudoNumber, metGraph->GetY()[0], mtGraph->GetY()[0]);
ptmetData->SetPoint(pseudoNumber, ptGraph->GetY()[0], metGraph->GetY()[0]);
mtptScatter->SetPoint(pseudoNumber, mtGraph->GetY()[0], ptGraph->GetY()[0]);
metmtScatter->SetPoint(pseudoNumber, metGraph->GetY()[0], mtGraph->GetY()[0]);
ptmetScatter->SetPoint(pseudoNumber, ptGraph->GetY()[0], metGraph->GetY()[0]);
mtptScatter->SetPointError(pseudoNumber, mtGraph->GetEY()[0], ptGraph->GetEY()[0]);
metmtScatter->SetPointError(pseudoNumber, metGraph->GetEY()[0], mtGraph->GetEY()[0]);
ptmetScatter->SetPointError(pseudoNumber, ptGraph->GetEY()[0], metGraph->GetEY()[0]);
mtUnbiasedPull->Fill((mtGraph->GetY()[0]-trueMass)/mtGraph->GetEY()[0]);
ptUnbiasedPull->Fill((ptGraph->GetY()[0]-trueMass)/ptGraph->GetEY()[0]);
metUnbiasedPull->Fill((metGraph->GetY()[0]-trueMass)/metGraph->GetEY()[0]);
mtptUnbiasedPull->Fill((mtGraph->GetY()[0]-trueMass)/mtGraph->GetEY()[0], (ptGraph->GetY()[0]-trueMass)/ptGraph->GetEY()[0]);
ptmetUnbiasedPull->Fill((ptGraph->GetY()[0]-trueMass)/ptGraph->GetEY()[0], (metGraph->GetY()[0]-trueMass)/metGraph->GetEY()[0]);
metmtUnbiasedPull->Fill((metGraph->GetY()[0]-trueMass)/metGraph->GetEY()[0], (mtGraph->GetY()[0]-trueMass)/mtGraph->GetEY()[0]);
tempFile->Close();
pseudoNumber++;
}
fileList.close();
ifstream fileList2(argv[1]);
while (!fileList2.eof()) {
reader.ReadLine(fileList2);
if (reader.Length() < 5) continue;
TFile* tempFile = TFile::Open(reader);
if (!tempFile->IsOpen()) continue;
TGraphErrors* mtGraph = (TGraphErrors*) tempFile->Get("wmass_Mt");
TGraphErrors* ptGraph = (TGraphErrors*) tempFile->Get("wmass_Pt");
TGraphErrors* metGraph = (TGraphErrors*) tempFile->Get("wmass_MET");
mtPull->Fill((mtGraph->GetY()[0]-mtptData->GetMean())/mtGraph->GetEY()[0]);
ptPull->Fill((ptGraph->GetY()[0]-ptmetData->GetMean())/ptGraph->GetEY()[0]);
metPull->Fill((metGraph->GetY()[0]-metmtData->GetMean())/metGraph->GetEY()[0]);
mtptPull->Fill((mtGraph->GetY()[0]-mtptData->GetMean())/mtGraph->GetEY()[0], (ptGraph->GetY()[0]-ptmetData->GetMean())/ptGraph->GetEY()[0]);
ptmetPull->Fill((ptGraph->GetY()[0]-ptmetData->GetMean())/ptGraph->GetEY()[0], (metGraph->GetY()[0]-metmtData->GetMean())/metGraph->GetEY()[0]);
metmtPull->Fill((metGraph->GetY()[0]-metmtData->GetMean())/metGraph->GetEY()[0], (mtGraph->GetY()[0]-mtptData->GetMean())/mtGraph->GetEY()[0]);
tempFile->Close();
}
fileList2.close();
cout << mtptData->GetMean() << " " << mtptData->GetRMS() << endl;
cout << ptmetData->GetMean() << " " << ptmetData->GetRMS() << endl;
cout << metmtData->GetMean() << " " << metmtData->GetRMS() << endl;
cout << mtptData->GetCorrelationFactor() << " " << ptmetData->GetCorrelationFactor() << " " << metmtData->GetCorrelationFactor() << endl;
cout << "Data saved! " << pseudoNumber << endl;
mtUnbiasedPull->Fit("gaus");
ptUnbiasedPull->Fit("gaus");
metUnbiasedPull->Fit("gaus");
mtPull->Fit("gaus");
ptPull->Fit("gaus");
metPull->Fit("gaus");
TF2* mtptUnbiasedGaussian2d = new TF2("mtptUnbiasedGaussian2d", gaussian2d, -5., 5., -5., 5., 6);
TF2* ptmetUnbiasedGaussian2d = new TF2("ptmetUnbiasedGaussian2d", gaussian2d, -5., 5., -5., 5., 6);
TF2* metmtUnbiasedGaussian2d = new TF2("metmtUnbiasedGaussian2d", gaussian2d, -5., 5., -5., 5., 6);
mtptUnbiasedGaussian2d->SetParameter(0, 10.);
mtptUnbiasedGaussian2d->SetParameter(3, 1.);
mtptUnbiasedGaussian2d->SetParameter(4, 1.);
mtptUnbiasedGaussian2d->SetParameter(5, 0.5);
ptmetUnbiasedGaussian2d->SetParameter(0, 10.);
ptmetUnbiasedGaussian2d->SetParameter(3, 1.);
ptmetUnbiasedGaussian2d->SetParameter(4, 1.);
ptmetUnbiasedGaussian2d->SetParameter(5, 0.5);
metmtUnbiasedGaussian2d->SetParameter(0, 10.);
metmtUnbiasedGaussian2d->SetParameter(3, 1.);
metmtUnbiasedGaussian2d->SetParameter(4, 1.);
metmtUnbiasedGaussian2d->SetParameter(5, 0.5);
mtptUnbiasedPull->Fit(mtptUnbiasedGaussian2d, "R");
ptmetUnbiasedPull->Fit(ptmetUnbiasedGaussian2d, "R");
metmtUnbiasedPull->Fit(metmtUnbiasedGaussian2d, "R");
((TF2*) mtptUnbiasedPull->GetListOfFunctions()->At(0))->SetContour(4);
((TF2*) mtptUnbiasedPull->GetListOfFunctions()->At(0))->SetLineColor(kRed);
((TF2*) mtptUnbiasedPull->GetListOfFunctions()->At(0))->SetNpx(100);
((TF2*) mtptUnbiasedPull->GetListOfFunctions()->At(0))->SetNpy(100);
((TF2*) ptmetUnbiasedPull->GetListOfFunctions()->At(0))->SetContour(4);
((TF2*) ptmetUnbiasedPull->GetListOfFunctions()->At(0))->SetLineColor(kRed);
((TF2*) ptmetUnbiasedPull->GetListOfFunctions()->At(0))->SetNpx(100);
((TF2*) ptmetUnbiasedPull->GetListOfFunctions()->At(0))->SetNpy(100);
((TF2*) metmtUnbiasedPull->GetListOfFunctions()->At(0))->SetContour(4);
((TF2*) metmtUnbiasedPull->GetListOfFunctions()->At(0))->SetLineColor(kRed);
((TF2*) metmtUnbiasedPull->GetListOfFunctions()->At(0))->SetNpx(100);
((TF2*) metmtUnbiasedPull->GetListOfFunctions()->At(0))->SetNpy(100);
mtptUnbiasedPull->SetLineWidth(2);
ptmetUnbiasedPull->SetLineWidth(2);
metmtUnbiasedPull->SetLineWidth(2);
mtptUnbiasedPull->SetLineColor(kBlue);
ptmetUnbiasedPull->SetLineColor(kBlue);
metmtUnbiasedPull->SetLineColor(kBlue);
((TF1*) mtUnbiasedPull->GetListOfFunctions()->At(0))->SetLineColor(kRed);
((TF1*) ptUnbiasedPull->GetListOfFunctions()->At(0))->SetLineColor(kRed);
((TF1*) metUnbiasedPull->GetListOfFunctions()->At(0))->SetLineColor(kRed);
TF2* mtptGaussian2d = new TF2("mtptGaussian2d", gaussian2d, -5., 5., -5., 5., 6);
TF2* ptmetGaussian2d = new TF2("ptmetGaussian2d", gaussian2d, -5., 5., -5., 5., 6);
TF2* metmtGaussian2d = new TF2("metmtGaussian2d", gaussian2d, -5., 5., -5., 5., 6);
mtptGaussian2d->SetParameter(0, 10.);
mtptGaussian2d->SetParameter(3, 1.);
mtptGaussian2d->SetParameter(4, 1.);
mtptGaussian2d->SetParameter(5, 0.5);
ptmetGaussian2d->SetParameter(0, 10.);
ptmetGaussian2d->SetParameter(3, 1.);
ptmetGaussian2d->SetParameter(4, 1.);
ptmetGaussian2d->SetParameter(5, 0.5);
metmtGaussian2d->SetParameter(0, 10.);
metmtGaussian2d->SetParameter(3, 1.);
metmtGaussian2d->SetParameter(4, 1.);
metmtGaussian2d->SetParameter(5, 0.5);
mtptPull->Fit(mtptGaussian2d, "R");
ptmetPull->Fit(ptmetGaussian2d, "R");
metmtPull->Fit(metmtGaussian2d, "R");
((TF2*) mtptPull->GetListOfFunctions()->At(0))->SetContour(4);
((TF2*) mtptPull->GetListOfFunctions()->At(0))->SetLineColor(kRed);
((TF2*) mtptPull->GetListOfFunctions()->At(0))->SetNpx(100);
((TF2*) mtptPull->GetListOfFunctions()->At(0))->SetNpy(100);
((TF2*) ptmetPull->GetListOfFunctions()->At(0))->SetContour(4);
((TF2*) ptmetPull->GetListOfFunctions()->At(0))->SetLineColor(kRed);
((TF2*) ptmetPull->GetListOfFunctions()->At(0))->SetNpx(100);
((TF2*) ptmetPull->GetListOfFunctions()->At(0))->SetNpy(100);
((TF2*) metmtPull->GetListOfFunctions()->At(0))->SetContour(4);
((TF2*) metmtPull->GetListOfFunctions()->At(0))->SetLineColor(kRed);
((TF2*) metmtPull->GetListOfFunctions()->At(0))->SetNpx(100);
((TF2*) metmtPull->GetListOfFunctions()->At(0))->SetNpy(100);
mtptPull->SetLineWidth(2);
ptmetPull->SetLineWidth(2);
metmtPull->SetLineWidth(2);
mtptPull->SetLineColor(kBlue);
ptmetPull->SetLineColor(kBlue);
metmtPull->SetLineColor(kBlue);
((TF1*) mtPull->GetListOfFunctions()->At(0))->SetLineColor(kRed);
((TF1*) ptPull->GetListOfFunctions()->At(0))->SetLineColor(kRed);
((TF1*) metPull->GetListOfFunctions()->At(0))->SetLineColor(kRed);
Double_t biasFactor = TMath::Sqrt(pseudoNumber/(pseudoNumber-1));
Double_t biasFactor2 = TMath::Sqrt((pseudoNumber-1)/(pseudoNumber-2));
// Do the JackKnife analysis
cout << "Doing the jackknife analysis" << endl;
for (Int_t i=0; i<pseudoNumber; i++) {
TGraph* mtptTemp = (TGraph*) mtptData->Clone();
TGraph* metmtTemp = (TGraph*) metmtData->Clone();
TGraph* ptmetTemp = (TGraph*) ptmetData->Clone();
mtptTemp->RemovePoint(i);
metmtTemp->RemovePoint(i);
ptmetTemp->RemovePoint(i);
mtJKMean->Fill(mtptTemp->GetMean());
ptJKMean->Fill(ptmetTemp->GetMean());
metJKMean->Fill(metmtTemp->GetMean());
mtJKSigma->Fill(biasFactor*pseudoNumber*mtptData->GetRMS()-biasFactor2*(pseudoNumber-1)*mtptTemp->GetRMS());
ptJKSigma->Fill(biasFactor*pseudoNumber*ptmetData->GetRMS()-biasFactor2*(pseudoNumber-1)*ptmetTemp->GetRMS());
metJKSigma->Fill(biasFactor*pseudoNumber*metmtData->GetRMS()-biasFactor2*(pseudoNumber-1)*metmtTemp->GetRMS());
mtJKUnbiasedSigma->Fill(pseudoNumber*TMath::Sqrt(mtptData->GetRMS()*mtptData->GetRMS()+mtptData->GetMean()*mtptData->GetMean()-2*trueMass*mtptData->GetMean()+trueMass*trueMass)
-(pseudoNumber-1)*TMath::Sqrt(mtptTemp->GetRMS()*mtptTemp->GetRMS()+mtptTemp->GetMean()*mtptTemp->GetMean()-2*trueMass*mtptTemp->GetMean()+trueMass*trueMass));
ptJKUnbiasedSigma->Fill(pseudoNumber*TMath::Sqrt(ptmetData->GetRMS()*ptmetData->GetRMS()+ptmetData->GetMean()*ptmetData->GetMean()-2*trueMass*ptmetData->GetMean()+trueMass*trueMass)
-(pseudoNumber-1)*TMath::Sqrt(ptmetTemp->GetRMS()*ptmetTemp->GetRMS()+ptmetTemp->GetMean()*ptmetTemp->GetMean()-2*trueMass*ptmetTemp->GetMean()+trueMass*trueMass));
metJKUnbiasedSigma->Fill(pseudoNumber*TMath::Sqrt(metmtData->GetRMS()*metmtData->GetRMS()+metmtData->GetMean()*metmtData->GetMean()-2*trueMass*metmtData->GetMean()+trueMass*trueMass)
-(pseudoNumber-1)*TMath::Sqrt(metmtTemp->GetRMS()*metmtTemp->GetRMS()+metmtTemp->GetMean()*metmtTemp->GetMean()-2*trueMass*metmtTemp->GetMean()+trueMass*trueMass));
mtptJKCorr->Fill(pseudoNumber*mtptData->GetCorrelationFactor()-(pseudoNumber-1)*mtptTemp->GetCorrelationFactor());
metmtJKCorr->Fill(pseudoNumber*metmtData->GetCorrelationFactor()-(pseudoNumber-1)*metmtTemp->GetCorrelationFactor());
ptmetJKCorr->Fill(pseudoNumber*ptmetData->GetCorrelationFactor()-(pseudoNumber-1)*ptmetTemp->GetCorrelationFactor());
}
// The values we are measuring
TMatrixD correlationValue(3,3);
TMatrixD correlationError(3,3);
TVectorD uncertaintyValue(3);
TVectorD uncertaintyError(3);
TVectorD unbiasedUncertaintyValue(3);
TVectorD unbiasedUncertaintyError(3);
correlationValue[0][1] = mtptJKCorr->GetMean(); correlationError[0][1] = mtptJKCorr->GetRMS()/TMath::Sqrt(pseudoNumber-1.);
correlationValue[0][2] = metmtJKCorr->GetMean(); correlationError[0][2] = metmtJKCorr->GetRMS()/TMath::Sqrt(pseudoNumber-1.);
correlationValue[1][2] = ptmetJKCorr->GetMean(); correlationError[1][2] = ptmetJKCorr->GetRMS()/TMath::Sqrt(pseudoNumber-1.);
correlationValue[1][0] = correlationValue[0][1]; correlationError[1][0] = correlationError[0][1];
correlationValue[2][0] = correlationValue[0][2]; correlationError[2][0] = correlationError[0][2];
correlationValue[2][1] = correlationValue[1][2]; correlationError[2][1] = correlationError[1][2];
correlationValue[0][0] = 1.0; correlationError[0][0] = 0.0;
correlationValue[1][1] = 1.0; correlationError[1][1] = 0.0;
correlationValue[2][2] = 1.0; correlationError[2][2] = 0.0;
uncertaintyValue[0] = mtJKSigma->GetMean(); uncertaintyError[0] = mtJKSigma->GetRMS()/TMath::Sqrt(pseudoNumber-1.);
uncertaintyValue[1] = ptJKSigma->GetMean(); uncertaintyError[1] = ptJKSigma->GetRMS()/TMath::Sqrt(pseudoNumber-1.);
uncertaintyValue[2] = metJKSigma->GetMean(); uncertaintyError[2] = metJKSigma->GetRMS()/TMath::Sqrt(pseudoNumber-1.);
unbiasedUncertaintyValue[0] = mtJKUnbiasedSigma->GetMean(); unbiasedUncertaintyError[0] = mtJKUnbiasedSigma->GetRMS()/TMath::Sqrt(pseudoNumber-1.);
unbiasedUncertaintyValue[1] = ptJKUnbiasedSigma->GetMean(); unbiasedUncertaintyError[1] = ptJKUnbiasedSigma->GetRMS()/TMath::Sqrt(pseudoNumber-1.);
unbiasedUncertaintyValue[2] = metJKUnbiasedSigma->GetMean(); unbiasedUncertaintyError[2] = metJKUnbiasedSigma->GetRMS()/TMath::Sqrt(pseudoNumber-1.);
cout << "The order is mT, pT, MET" << endl;
cout << "The correlation matrix" << endl;
correlationValue.Print();
cout << "The uncertainty in the correlation matrix" << endl;
correlationError.Print();
cout << "The uncertainty values" << endl;
uncertaintyValue.Print();
cout << "The uncertainty in the uncertainty values" << endl;
uncertaintyError.Print();
cout << "The unbiased uncertainty values" << endl;
unbiasedUncertaintyValue.Print();
cout << "The uncertainty in the unbiased uncertainty values" << endl;
unbiasedUncertaintyError.Print();
cout << "Jackknife bias" << endl;
cout << (pseudoNumber-1)*(mtJKMean->GetMean()-mtptData->GetMean()) << endl;
cout << (pseudoNumber-1)*(ptJKMean->GetMean()-ptmetData->GetMean()) << endl;
cout << (pseudoNumber-1)*(metJKMean->GetMean()-metmtData->GetMean()) << endl << endl;
cout << "Unbiased Pull information" << endl;
cout << " mT) Mean: " << mtUnbiasedPull->GetMean() << " +/- " << mtUnbiasedPull->GetMeanError() << " RMS: " << mtUnbiasedPull->GetRMS() << " +/- " << mtUnbiasedPull->GetRMSError() << endl;
cout << " pT) Mean: " << ptUnbiasedPull->GetMean() << " +/- " << ptUnbiasedPull->GetMeanError() << " RMS: " << ptUnbiasedPull->GetRMS() << " +/- " << ptUnbiasedPull->GetRMSError() << endl;
cout << "MET) Mean: " << metUnbiasedPull->GetMean() << " +/- " << metUnbiasedPull->GetMeanError() << " RMS: " << metUnbiasedPull->GetRMS() << " +/- " << metUnbiasedPull->GetRMSError() << endl;
cout << "Pull information" << endl;
cout << " mT) Mean: " << mtPull->GetMean() << " +/- " << mtPull->GetMeanError() << " RMS: " << mtPull->GetRMS() << " +/- " << mtPull->GetRMSError() << endl;
cout << " pT) Mean: " << ptPull->GetMean() << " +/- " << ptPull->GetMeanError() << " RMS: " << ptPull->GetRMS() << " +/- " << ptPull->GetRMSError() << endl;
cout << "MET) Mean: " << metPull->GetMean() << " +/- " << metPull->GetMeanError() << " RMS: " << metPull->GetRMS() << " +/- " << metPull->GetRMSError() << endl;
TMatrixD mtptcov(2,2);
mtptcov[0][0] = mtptGaussian2d->GetParameter(3)*mtptGaussian2d->GetParameter(3);
mtptcov[0][1] = mtptGaussian2d->GetParameter(3)*mtptGaussian2d->GetParameter(4)*mtptGaussian2d->GetParameter(5);
mtptcov[1][0] = mtptGaussian2d->GetParameter(3)*mtptGaussian2d->GetParameter(4)*mtptGaussian2d->GetParameter(5);
mtptcov[1][1] = mtptGaussian2d->GetParameter(4)*mtptGaussian2d->GetParameter(4);
TMatrixD mtptEigenVectors(2,2);
TVectorD mtptEigenValues(2);
mtptEigenVectors = mtptcov.EigenVectors(mtptEigenValues);
cout << "---- mT-pT ----" << endl;
cout << " " << mtptGaussian2d->GetParameter(1) << " +/- " << mtptGaussian2d->GetParError(1) << endl;
cout << " " << mtptGaussian2d->GetParameter(2) << " +/- " << mtptGaussian2d->GetParError(2) << endl;
cout << " " << mtptGaussian2d->GetParameter(3) << " +/- " << mtptGaussian2d->GetParError(3) << endl;
cout << " " << mtptGaussian2d->GetParameter(4) << " +/- " << mtptGaussian2d->GetParError(4) << endl;
cout << " " << mtptGaussian2d->GetParameter(5) << " +/- " << mtptGaussian2d->GetParError(5) << endl;
mtptEigenVectors.Print();
mtptEigenValues.Print();
TMatrixD ptmetcov(2,2);
ptmetcov[0][0] = ptmetGaussian2d->GetParameter(3)*ptmetGaussian2d->GetParameter(3);
ptmetcov[0][1] = ptmetGaussian2d->GetParameter(3)*ptmetGaussian2d->GetParameter(4)*ptmetGaussian2d->GetParameter(5);
ptmetcov[1][0] = ptmetGaussian2d->GetParameter(3)*ptmetGaussian2d->GetParameter(4)*ptmetGaussian2d->GetParameter(5);
ptmetcov[1][1] = ptmetGaussian2d->GetParameter(4)*ptmetGaussian2d->GetParameter(4);
TMatrixD ptmetEigenVectors(2,2);
TVectorD ptmetEigenValues(2);
ptmetEigenVectors = ptmetcov.EigenVectors(ptmetEigenValues);
cout << "---- pT-MET ----" << endl;
cout << " " << ptmetGaussian2d->GetParameter(1) << " +/- " << ptmetGaussian2d->GetParError(1) << endl;
cout << " " << ptmetGaussian2d->GetParameter(2) << " +/- " << ptmetGaussian2d->GetParError(2) << endl;
cout << " " << ptmetGaussian2d->GetParameter(3) << " +/- " << ptmetGaussian2d->GetParError(3) << endl;
cout << " " << ptmetGaussian2d->GetParameter(4) << " +/- " << ptmetGaussian2d->GetParError(4) << endl;
cout << " " << ptmetGaussian2d->GetParameter(5) << " +/- " << ptmetGaussian2d->GetParError(5) << endl;
ptmetEigenVectors.Print();
ptmetEigenValues.Print();
TMatrixD metmtcov(2,2);
metmtcov[0][0] = metmtGaussian2d->GetParameter(3)*metmtGaussian2d->GetParameter(3);
metmtcov[0][1] = metmtGaussian2d->GetParameter(3)*metmtGaussian2d->GetParameter(4)*metmtGaussian2d->GetParameter(5);
metmtcov[1][0] = metmtGaussian2d->GetParameter(3)*metmtGaussian2d->GetParameter(4)*metmtGaussian2d->GetParameter(5);
metmtcov[1][1] = metmtGaussian2d->GetParameter(4)*metmtGaussian2d->GetParameter(4);
TMatrixD metmtEigenVectors(2,2);
TVectorD metmtEigenValues(2);
metmtEigenVectors = metmtcov.EigenVectors(metmtEigenValues);
cout << "---- MET-mT ----" << endl;
cout << " " << metmtGaussian2d->GetParameter(1) << " +/- " << metmtGaussian2d->GetParError(1) << endl;
cout << " " << metmtGaussian2d->GetParameter(2) << " +/- " << metmtGaussian2d->GetParError(2) << endl;
cout << " " << metmtGaussian2d->GetParameter(3) << " +/- " << metmtGaussian2d->GetParError(3) << endl;
cout << " " << metmtGaussian2d->GetParameter(4) << " +/- " << metmtGaussian2d->GetParError(4) << endl;
cout << " " << metmtGaussian2d->GetParameter(5) << " +/- " << metmtGaussian2d->GetParError(5) << endl;
metmtEigenVectors.Print();
metmtEigenValues.Print();
TFile* outputFile = TFile::Open("StatUnc.root", "recreate");
mt_mean->Write();
elecpt_mean->Write();
met_mean->Write();
mt_rms->Write();
elecpt_rms->Write();
met_rms->Write();
mt_rms_ratio->Write();
elecpt_rms_ratio->Write();
met_rms_ratio->Write();
mt_rmsfrac->Write();
elecpt_rmsfrac->Write();
met_rmsfrac->Write();
mt_corr->Write();
elecpt_corr->Write();
met_corr->Write();
mtPull->Write();
ptPull->Write();
metPull->Write();
mtptPull->Write();
ptmetPull->Write();
metmtPull->Write();
mtUnbiasedPull->Write();
ptUnbiasedPull->Write();
metUnbiasedPull->Write();
mtptUnbiasedPull->Write();
ptmetUnbiasedPull->Write();
metmtUnbiasedPull->Write();
mtJKMean->Write();
ptJKMean->Write();
metJKMean->Write();
mtJKSigma->Write();
ptJKSigma->Write();
metJKSigma->Write();
mtJKUnbiasedSigma->Write();
ptJKUnbiasedSigma->Write();
metJKUnbiasedSigma->Write();
mtptJKCorr->Write();
metmtJKCorr->Write();
ptmetJKCorr->Write();
for (int i=0; i<300/rebin; i++)
mt_dists[i]->Write();
for (int i=0; i<200/rebin; i++)
pt_dists[i]->Write();
for (int i=0; i<200/rebin; i++)
met_dists[i]->Write();
outputFile->Close();
TCanvas* c1 = new TCanvas();
c1->Print("StatUnc.ps[");
{
for (int i=1; i<=mt_mean->GetNbinsX(); i++) {
Double_t expectedUncertainty = mt_mean->GetBinContent(i);
expectedUncertainty = TMath::Sqrt(expectedUncertainty);
mt_mean->SetBinContent(i, expectedUncertainty);
mt_mean->SetBinError(i, TMath::Sqrt(expectedUncertainty));
}
mt_mean->SetLineColor(kBlue);
mt_rms->SetLineColor(kRed);
mt_rms->Sumw2();
mt_mean->Sumw2();
double __sum = 0;
double __n = 0;
for (int i=1; i<=mt_rms_ratio->GetNbinsX(); i++) {
if (mt_rms_ratio->GetBinContent(i) > 0) {
__sum += mt_rms_ratio->GetBinContent(i);
__n += 1;
}
}
cout << "Mt correction " << __sum/__n << endl;
TPad *pad1 = new TPad("pad1","pad1",0,0.3,1,1);
pad1->SetBottomMargin(0);
pad1->Draw();
pad1->cd();
mt_rms->SetStats(0);
mt_mean->SetStats(0);
mt_rms->SetMarkerStyle(20);
mt_mean->SetMarkerStyle(21);
mt_rms->SetMinimum(-10);
mt_rms->GetXaxis()->SetRangeUser(0, 120);
mt_rms->Draw();
mt_mean->Draw("same");
TLegend* leg = new TLegend(0.6, 0.6, 0.8, 0.8);
leg->AddEntry(mt_rms, "RMS", "lp");
leg->AddEntry(mt_mean, "#sqrt{mean}", "lp");
leg->SetFillColor(0);
leg->SetBorderSize(0);
leg->Draw();
c1->cd();
TPad *pad2 = new TPad("pad2","pad2",0,0.,1,0.35);
pad2->SetTopMargin(0);
pad2->SetBottomMargin(0.5);
pad2->Draw();
pad2->cd();
mt_rms_ratio->SetTitle(" ;m_{T} (GeV); ");
mt_rms_ratio->SetLineColor(kBlack);
mt_rms_ratio->SetMarkerColor(kBlue);
mt_rms_ratio->SetMarkerStyle(20);
mt_rms_ratio->SetStats(0);
mt_rms_ratio->GetXaxis()->SetLabelFont(63);
mt_rms_ratio->GetXaxis()->SetLabelSize(16);
mt_rms_ratio->GetYaxis()->SetLabelFont(63);
mt_rms_ratio->GetYaxis()->SetLabelSize(12);
mt_rms_ratio->GetYaxis()->SetRangeUser(0.45, 1.55);
mt_rms_ratio->GetYaxis()->SetNdivisions(5);
mt_rms_ratio->GetXaxis()->SetRangeUser(0, 120);
mt_rms_ratio->GetXaxis()->SetTitleFont(63);
mt_rms_ratio->GetXaxis()->SetTitleSize(16);
mt_rms_ratio->GetXaxis()->SetTitleOffset(2.5);
mt_rms_ratio->Draw("e0");
}
c1->Print("StatUnc.ps");
c1->Clear();
c1->cd();
{
for (int i=1; i<=met_mean->GetNbinsX(); i++) {
Double_t expectedUncertainty = met_mean->GetBinContent(i);
expectedUncertainty = TMath::Sqrt(expectedUncertainty);
met_mean->SetBinContent(i, expectedUncertainty);
met_mean->SetBinError(i, TMath::Sqrt(expectedUncertainty));
}
met_mean->SetLineColor(kBlue);
met_rms->SetLineColor(kRed);
met_rms->Sumw2();
met_mean->Sumw2();
double __sum = 0;
double __n = 0;
for (int i=1; i<=met_rms_ratio->GetNbinsX(); i++) {
if (met_rms_ratio->GetBinContent(i) > 0) {
__sum += met_rms_ratio->GetBinContent(i);
__n += 1;
}
}
cout << "Met correction " << __sum/__n << endl;
TPad *pad1 = new TPad("pad1","pad1",0,0.3,1,1);
pad1->SetBottomMargin(0);
pad1->Draw();
pad1->cd();
met_rms->SetStats(0);
met_mean->SetStats(0);
met_rms->SetMarkerStyle(20);
met_mean->SetMarkerStyle(21);
met_rms->SetMinimum(-10);
met_rms->GetXaxis()->SetRangeUser(25, 60);
met_rms->Draw();
met_mean->Draw("same");
TLegend* leg = new TLegend(0.6, 0.6, 0.8, 0.8);
leg->AddEntry(met_rms, "RMS", "lp");
leg->AddEntry(met_mean, "#sqrt{mean}", "lp");
leg->SetFillColor(0);
leg->SetBorderSize(0);
leg->Draw();
c1->cd();
TPad *pad2 = new TPad("pad2","pad2",0,0,1,0.3);
pad2->SetTopMargin(0);
pad2->SetBottomMargin(0.5);
pad2->Draw();
pad2->cd();
met_rms_ratio->SetTitle(" ;MET (GeV); ");
met_rms_ratio->SetLineColor(kBlack);
met_rms_ratio->SetMarkerColor(kBlue);
met_rms_ratio->SetMarkerStyle(20);
met_rms_ratio->SetStats(0);
met_rms_ratio->GetXaxis()->SetLabelFont(63);
met_rms_ratio->GetXaxis()->SetLabelSize(16);
met_rms_ratio->GetYaxis()->SetLabelFont(63);
met_rms_ratio->GetYaxis()->SetLabelSize(12);
met_rms_ratio->GetYaxis()->SetRangeUser(0.45, 1.55);
met_rms_ratio->GetYaxis()->SetNdivisions(5);
met_rms_ratio->GetXaxis()->SetRangeUser(25, 60);
met_rms_ratio->GetXaxis()->SetTitleFont(63);
met_rms_ratio->GetXaxis()->SetTitleSize(16);
met_rms_ratio->GetXaxis()->SetTitleOffset(2.5);
met_rms_ratio->Draw("e0");
}
c1->Print("StatUnc.ps");
c1->Clear();
c1->cd();
{
for (int i=1; i<=elecpt_mean->GetNbinsX(); i++) {
Double_t expectedUncertainty = elecpt_mean->GetBinContent(i);
expectedUncertainty = TMath::Sqrt(expectedUncertainty);
elecpt_mean->SetBinContent(i, expectedUncertainty);
elecpt_mean->SetBinError(i, TMath::Sqrt(expectedUncertainty));
}
elecpt_mean->SetLineColor(kBlue);
elecpt_rms->SetLineColor(kRed);
elecpt_rms->Sumw2();
elecpt_mean->Sumw2();
double __sum = 0;
double __n = 0;
for (int i=1; i<=elecpt_rms_ratio->GetNbinsX(); i++) {
if (elecpt_rms_ratio->GetBinContent(i) > 0) {
__sum += elecpt_rms_ratio->GetBinContent(i);
__n += 1;
}
}
cout << "Elecpt correction " << __sum/__n << endl;
TPad *pad1 = new TPad("pad1","pad1",0,0.3,1,1);
pad1->SetBottomMargin(0);
pad1->Draw();
pad1->cd();
elecpt_rms->SetStats(0);
elecpt_mean->SetStats(0);
elecpt_rms->SetMarkerStyle(20);
elecpt_mean->SetMarkerStyle(21);
elecpt_rms->SetMinimum(-10);
elecpt_rms->GetXaxis()->SetRangeUser(25, 60);
elecpt_rms->Draw();
elecpt_mean->Draw("same");
TLegend* leg = new TLegend(0.6, 0.6, 0.8, 0.8);
leg->AddEntry(elecpt_rms, "RMS", "lp");
leg->AddEntry(elecpt_mean, "#sqrt{mean}", "lp");
leg->SetFillColor(0);
leg->SetBorderSize(0);
leg->Draw();
c1->cd();
TPad *pad2 = new TPad("pad2","pad2",0,0,1,0.3);
pad2->SetTopMargin(0);
pad2->SetBottomMargin(0.5);
pad2->Draw();
pad2->cd();
elecpt_rms_ratio->SetTitle(" ; Electron p_{T} (GeV); ");
elecpt_rms_ratio->SetLineColor(kBlack);
elecpt_rms_ratio->SetMarkerColor(kBlue);
elecpt_rms_ratio->SetMarkerStyle(20);
elecpt_rms_ratio->SetStats(0);
elecpt_rms_ratio->GetXaxis()->SetLabelFont(63);
elecpt_rms_ratio->GetXaxis()->SetLabelSize(16);
elecpt_rms_ratio->GetYaxis()->SetLabelFont(63);
elecpt_rms_ratio->GetYaxis()->SetLabelSize(12);
elecpt_rms_ratio->GetYaxis()->SetRangeUser(0.45, 1.55);
elecpt_rms_ratio->GetYaxis()->SetNdivisions(5);
elecpt_rms_ratio->GetXaxis()->SetRangeUser(25, 60);
elecpt_rms_ratio->GetXaxis()->SetTitleFont(63);
elecpt_rms_ratio->GetXaxis()->SetTitleSize(16);
elecpt_rms_ratio->GetXaxis()->SetTitleOffset(2.5);
elecpt_rms_ratio->Draw("e0");
}
c1->Print("StatUnc.ps");
c1->Clear();
c1->cd();
mt_corr->SetTitle("Bin-by-bin correlation m_{T}; m_{T} (GeV); m_{T} (GeV)");
mt_corr->GetXaxis()->SetRangeUser(65, 90);
mt_corr->GetYaxis()->SetRangeUser(65, 90);
mt_corr->GetZaxis()->SetRangeUser(-0.4, 0.4);
mt_corr->SetStats(0);
mt_corr->Draw("colz");
c1->Print("StatUnc.ps");
elecpt_corr->SetTitle("Bin-by-bin correlation Electron p_{T}; Electron p_{T} (GeV); Electron p_{T} (GeV)");
elecpt_corr->GetXaxis()->SetRangeUser(32, 48);
elecpt_corr->GetYaxis()->SetRangeUser(32, 48);
elecpt_corr->GetZaxis()->SetRangeUser(-0.4, 0.4);
elecpt_corr->SetStats(0);
elecpt_corr->Draw("colz");
c1->Print("StatUnc.ps");
met_corr->SetTitle("Bin-by-bin correlation MET; MET (GeV); MET (GeV)");
met_corr->GetXaxis()->SetRangeUser(32, 48);
met_corr->GetYaxis()->SetRangeUser(32, 48);
met_corr->GetZaxis()->SetRangeUser(-0.4, 0.4);
met_corr->SetStats(0);
met_corr->Draw("colz");
c1->Print("StatUnc.ps");
mtUnbiasedPull->SetTitle("m_{T} unbiased pull; Unbiased pull; Pseudo-experiments");
mtUnbiasedPull->Draw();
c1->Print("StatUnc.ps");
ptUnbiasedPull->SetTitle("p_{T} unbiased pull; Unbiased pull; Pseudo-experiments");
ptUnbiasedPull->Draw();
c1->Print("StatUnc.ps");
metUnbiasedPull->SetTitle("MET unbiased pull; Unbiased pull; Pseudo-experiments");
metUnbiasedPull->Draw();
c1->Print("StatUnc.ps");
mtptUnbiasedPull->SetTitle("m_{T} - p_{T} unbiased pull; m_{T} pull; p_{T} pull");
mtptUnbiasedPull->Draw("box");
c1->Print("StatUnc.ps");
ptmetUnbiasedPull->SetTitle("p_{T} - MET unbiased pull; p_{T} pull; MET pull");
ptmetUnbiasedPull->Draw("box");
c1->Print("StatUnc.ps");
metmtUnbiasedPull->SetTitle("MET - m_{T} unbiased pull; MET pull; m_{T} pull");
metmtUnbiasedPull->Draw("box");
c1->Print("StatUnc.ps");
mtPull->SetTitle("m_{T} pull; pull; Pseudo-experiments");
mtPull->Draw();
c1->Print("StatUnc.ps");
ptPull->SetTitle("p_{T} pull; pull; Pseudo-experiments");
ptPull->Draw();
c1->Print("StatUnc.ps");
metPull->SetTitle("MET pull; pull; Pseudo-experiments");
metPull->Draw();
c1->Print("StatUnc.ps");
mtptPull->SetTitle("m_{T} - p_{T} pull; m_{T} pull; p_{T} pull");
mtptPull->Draw("box");
c1->Print("StatUnc.ps");
ptmetPull->SetTitle("p_{T} - MET pull; p_{T} pull; MET pull");
ptmetPull->Draw("box");
c1->Print("StatUnc.ps");
metmtPull->SetTitle("MET - m_{T} pull; MET pull; m_{T} pull");
metmtPull->Draw("box");
c1->Print("StatUnc.ps");
mtJKSigma->SetTitle("m_{T} Standard Deviation Jackknife Estimator; Psuedo-value (GeV); Pseudo-experiment");
mtJKSigma->Draw();
c1->Print("StatUnc.ps");
ptJKSigma->SetTitle("p_{T} Standard Deviation Jackknife Estimator; Psuedo-value (GeV); Pseudo-experiment");
ptJKSigma->Draw();
c1->Print("StatUnc.ps");
metJKSigma->SetTitle("MET Standard Deviation Jackknife Estimator; Psuedo-value (GeV); Pseudo-experiment");
metJKSigma->Draw();
c1->Print("StatUnc.ps");
mtJKUnbiasedSigma->SetTitle("m_{T} Unbiased Standard Deviation Jackknife Estimator; Psuedo-value (GeV); Pseudo-experiment");
mtJKUnbiasedSigma->Draw();
c1->Print("StatUnc.ps");
ptJKUnbiasedSigma->SetTitle("p_{T} Unbiased Standard Deviation Jackknife Estimator; Psuedo-value (GeV); Pseudo-experiment");
ptJKUnbiasedSigma->Draw();
c1->Print("StatUnc.ps");
metJKUnbiasedSigma->SetTitle("MET Unbiased Standard Deviation Jackknife Estimator; Psuedo-value (GeV); Pseudo-experiment");
metJKUnbiasedSigma->Draw();
c1->Print("StatUnc.ps");
mtptJKCorr->SetTitle("m_{T} - p_{T} Correlation Jackknife Estimator; Pseudo-value; Pseudo-experiment");
mtptJKCorr->Draw();
c1->Print("StatUnc.ps");
ptmetJKCorr->SetTitle("p_{T} - MET Correlation Jackknife Estimator; Pseudo-value; Pseudo-experiment");
ptmetJKCorr->Draw();
c1->Print("StatUnc.ps");
metmtJKCorr->SetTitle("MET - m_{T} Correlation Jackknife Estimator; Pseudo-value; Pseudo-experiment");
metmtJKCorr->Draw();
c1->Print("StatUnc.ps");
mtptScatter->Draw("A");
mtptScatter->SetLineColor(kRed);
mtptScatter->SetTitle("m_{T} - p_{T} Fitted W mass; m_{T} fitted W mass (GeV); p_{T} fitted W mass (GeV)");
mtptScatter->Draw("AP");
c1->Print("StatUnc.ps");
ptmetScatter->Draw("A");
ptmetScatter->SetLineColor(kRed);
ptmetScatter->SetTitle("p_{T} - MET Fitted W mass; p_{T} fitted W mass (GeV); MET fitted W mass (GeV)");
ptmetScatter->Draw("AP");
c1->Print("StatUnc.ps");
metmtScatter->Draw("A");
metmtScatter->SetLineColor(kRed);
metmtScatter->SetTitle("MET - m_{T} Fitted W mass; MET fitted W mass (GeV); m_{T} fitted W mass (GeV)");
metmtScatter->Draw("AP");
c1->Print("StatUnc.ps");
c1->Clear();
c1->Divide(2,2);
Int_t __i = 1;
for (int i=0; i<300/rebin; i++) {
c1->cd(__i);
Double_t mt_poisson_integral = mt_poisson[i]->Integral();
mt_poisson[i]->Sumw2();
mt_poisson[i]->Scale(1/mt_poisson_integral);
mt_poisson[i]->SetLineColor(kRed);
mt_poisson[i]->SetTitle(TString::Format("m_{T} bin [%.1f, %.1f]", mt_mean->GetXaxis()->GetBinLowEdge(i+1), mt_mean->GetXaxis()->GetBinUpEdge(i+1)));
mt_poisson[i]->SetStats(0);
mt_poisson[i]->Draw("hist");
mt_dists[i]->SetLineColor(kBlue);
mt_dists[i]->Draw("same, hist");
__i++;
if (__i == 5) {
c1->Print("StatUnc.ps");
__i = 1;
}
}