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testPileUp.C
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testPileUp.C
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std::vector<int> fFillColors = {kGray+1, kRed-10, kBlue-9, kGreen-8, kMagenta-9, kOrange-9, kCyan-8, kYellow-7};
std::vector<int> fColors = {kBlack, kRed+1 , kBlue+2, kGreen+3, kMagenta+1, kOrange-1, kCyan+2, kYellow+2};
std::vector<int> fMarkers = {kFullCircle, kFullSquare, kOpenCircle, kOpenSquare, kOpenDiamond, kOpenCross, kFullCross, kFullDiamond, kFullStar, kOpenStar};
// ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
void SetStyle(bool graypalette=false, bool title=false)
{
const int NCont = 255;
gStyle->Reset("Plain");
gStyle->SetNumberContours(NCont);
gStyle->SetOptTitle(title);
gStyle->SetTitleBorderSize(0);
gStyle->SetOptStat(0);
if(graypalette) gStyle->SetPalette(8,0);
else gStyle->SetPalette(1);
gStyle->SetCanvasColor(10);
gStyle->SetCanvasBorderMode(0);
gStyle->SetFrameLineWidth(1);
gStyle->SetFrameFillColor(kWhite);
gStyle->SetPadColor(10);
gStyle->SetPadTickX(1);
gStyle->SetPadTickY(1);
gStyle->SetPadBottomMargin(0.15);
gStyle->SetPadLeftMargin(0.15);
gStyle->SetHistLineWidth(1);
gStyle->SetHistLineColor(kRed);
gStyle->SetFuncWidth(2);
gStyle->SetFuncColor(kGreen);
gStyle->SetLineWidth(2);
gStyle->SetLabelSize(0.045,"xyz");
gStyle->SetLabelOffset(0.01,"y");
gStyle->SetLabelOffset(0.01,"x");
gStyle->SetLabelColor(kBlack,"xyz");
gStyle->SetTitleSize(0.05,"xyz");
gStyle->SetTitleOffset(1.25,"y");
gStyle->SetTitleOffset(1.2,"x");
gStyle->SetTitleFillColor(kWhite);
gStyle->SetTextSizePixels(26);
gStyle->SetTextFont(42);
gStyle->SetLegendBorderSize(0);
gStyle->SetLegendFillColor(kWhite);
gStyle->SetLegendFont(42);
gStyle->SetLegendBorderSize(0);
const int NRGBs = 6;
Double_t stops[NRGBs];
for(int i=0; i<NRGBs; ++i) stops[i] = float(i)/(NRGBs-1);
Double_t red[NRGBs] = { 1., 29./255., 25./255., 27./255., 32./255., 24./255.};
Double_t green[NRGBs] = { 1., 221./255., 160./255., 113./255., 74./255., 37./255.};
Double_t blue[NRGBs] = { 1., 221./255., 184./255., 154./255., 129./255., 98./255.};
TColor::CreateGradientColorTable(NRGBs,stops,red,green,blue,NCont);
}
// ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
void SetStyleHisto(TH1 *histo, int marker, int color)
{
histo->GetXaxis()->SetLabelSize(0.045);
histo->GetXaxis()->SetTitleSize(0.05);
histo->GetXaxis()->SetLabelOffset(0.01);
histo->GetXaxis()->SetTitleOffset(1.2);
histo->GetXaxis()->SetLabelFont(42);
histo->GetYaxis()->SetLabelSize(0.045);
histo->GetYaxis()->SetTitleSize(0.05);
histo->GetYaxis()->SetLabelOffset(0.01);
histo->GetYaxis()->SetTitleOffset(1.25);
histo->SetMarkerStyle(fMarkers[marker]);
histo->SetMarkerColor(fColors[color]);
histo->SetLineColor(fColors[color]);
}
// ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
TH1F* Calculate_CF(TH1F* histRE_relK,TH1F* histME_relK, TString CFname,Double_t normleft,Double_t normright)
{
// histRE_relK->Sumw2();
// histME_relK->Sumw2();
Double_t norm_relK = histRE_relK->Integral(histRE_relK->FindBin(normleft),histRE_relK->FindBin(normright)) / histME_relK->Integral(histME_relK->FindBin(normleft),histME_relK->FindBin(normright));
TH1F* Hist_CF = (TH1F*)histRE_relK->Clone(CFname.Data());
Hist_CF->Divide(histRE_relK,histME_relK,1,norm_relK);
return Hist_CF;
}
// ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
TH1F* add_CF(TH1F* hist_CF1, TH1F* hist_CF2,TString HistName)
{
//Calculate CFs with error weighting
TH1F* hist_CF_sum = (TH1F*)hist_CF1->Clone(HistName.Data());
Int_t NBins = hist_CF_sum->GetNbinsX();
for(Int_t i=0;i<NBins;i++)
{
double CF1_val = hist_CF1->GetBinContent(i+1);
double CF1_err = hist_CF1->GetBinError(i+1);
double CF2_val = hist_CF2->GetBinContent(i+1);
double CF2_err = hist_CF2->GetBinError(i+1);
//average for bin i:
if(CF1_val != 0. && CF2_val != 0.)
{
double CF1_err_weight = 1./TMath::Power(CF1_err,2.);
double CF2_err_weight = 1./TMath::Power(CF2_err,2.);
double CF_sum_average = (CF1_err_weight*CF1_val + CF2_err_weight*CF2_val)/(CF1_err_weight+CF2_err_weight);
double CF_sum_err = 1./TMath::Sqrt(CF1_err_weight+CF2_err_weight);
hist_CF_sum->SetBinContent(i+1,CF_sum_average);
hist_CF_sum->SetBinError(i+1,CF_sum_err);
}
else if(CF1_val == 0. && CF2_val != 0.)
{
hist_CF_sum->SetBinContent(i+1,CF2_val);
hist_CF_sum->SetBinError(i+1,CF2_err);
}
else if(CF2_val == 0 && CF1_val != 0.)
{
hist_CF_sum->SetBinContent(i+1,CF1_val);
hist_CF_sum->SetBinError(i+1,CF1_err);
}
}
return hist_CF_sum;
}
// ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
TH1F *getSignalHisto(TF1 *function, TH1F *histo, float rangeLow, float rangeHigh, const char *name)
{
const int firstBin = histo->FindBin(rangeLow);
const int lastBin = histo->FindBin(rangeHigh);
TH1F *result = new TH1F(Form("result_%f_%f_%s", rangeLow, rangeHigh, name), "", histo->GetNbinsX(), histo->GetXaxis()->GetXmin(), histo->GetXaxis()->GetXmax());
for(int i = firstBin; i<lastBin; ++i) {
float weight = histo->GetBinContent(i) - function->Eval(histo->GetBinCenter(i));
result->Fill(histo->GetBinCenter(i), weight);
result->SetBinError(i, histo->GetBinError(i));
}
result->SetFillColor(fFillColors[0]);
result->SetLineColor(fFillColors[0]);
// result->Sumw2();
return result;
}
// ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
void FitLambda(TH1F* histo, float &signal, float &signalErr, float &background, float &backgroundErr, float lowerBound, float upperBound)
{
histo->Sumw2();
// Fit Background with second order polynomial, excluding Mlambda +/- 10 MeV
TF1 *fBackground = new TF1("fBackground", [&](double *x, double *p) { if (x[0] > 1.1075 && x[0] < 1.1235) {TF1::RejectPoint(); return (double)0; } return p[0] + p[1]*x[0] + p[2]*x[0]*x[0]; }, 1.095, 1.15, 3);
TFitResultPtr backgroundR = histo->Fit("fBackground", "SRQ0", "", 1.095, 1.15);
// parse then to proper TF1
TF1 *fBackground2 = new TF1("fBackground2","pol2", 0, 1.5);
fBackground2->SetParameter(0, fBackground->GetParameter(0));
fBackground2->SetParameter(1, fBackground->GetParameter(1));
fBackground2->SetParameter(2, fBackground->GetParameter(2));
// remove background from signal
TH1F *signalOnly = getSignalHisto(fBackground2, histo, 1.0, 1.3, Form("%s_signal_only", histo->GetName()));
signalOnly->Sumw2();
signalOnly->Draw("same");
// fit signal only
TF1 *fSignalSingleGauss = new TF1("fSignalSingleGauss", "gaus", 1.095, 1.15);
// fSignalSingleGauss->SetParameter(1, 1.115);
signalOnly->Fit("fSignalSingleGauss", "SRQ0", "", 1.1075, 1.1235);
TF1 *fSignalGauss = new TF1("fSignalGauss", "gaus(0) + gaus(3)", 1.1, 1.3);
fSignalGauss->SetParameter(0, 0.05 * histo->GetMaximum());
fSignalGauss->SetParameter(1, fSignalSingleGauss->GetParameter(1));
fSignalGauss->SetParLimits(1, 1.115-0.01, 1.115+0.01);
fSignalGauss->SetParameter(2, 5.f*fSignalSingleGauss->GetParameter(2));
fSignalGauss->SetParameter(3, 0.95 * histo->GetMaximum());
fSignalGauss->SetParameter(4, fSignalSingleGauss->GetParameter(1));
fSignalGauss->SetParLimits(4, 1.115-0.01, 1.115+0.01);
fSignalGauss->SetParameter(5, fSignalSingleGauss->GetParameter(2));
TFitResultPtr r = signalOnly->Fit("fSignalGauss", "SRQ0", "", 1.1075, 1.1235);
// Extract signal as integral
signal = fSignalGauss->Integral(lowerBound, upperBound) /double(histo->GetBinWidth(1));
signalErr = fSignalGauss->IntegralError(lowerBound, upperBound, r->GetParams(), r->GetCovarianceMatrix().GetMatrixArray()) /double(histo->GetBinWidth(1));
TF1 *fLambda = new TF1("fLambda", "fBackground2 + fSignalGauss", 1.1, 1.13);
fLambda->SetNpx(1000);
fLambda->SetParameter(3, 0.75 * histo->GetMaximum());
fLambda->SetParameter(4, fSignalGauss->GetParameter((1)));
fLambda->SetParameter(5, fSignalGauss->GetParameter((2)));
fLambda->SetParameter(6, 0.2 * histo->GetMaximum());
fLambda->SetParameter(7, fSignalGauss->GetParameter((4)));
fLambda->SetParameter(8, fSignalGauss->GetParameter((5)));
fLambda->SetLineColor(fColors[1]);
histo->Fit("fLambda", "SRQ", "", 1.095, 1.15);
TF1 *fLambda_background = new TF1("fLambda_background", "pol2(0)", 1.05, 1.25);
fLambda_background->SetParameter(0, fLambda->GetParameter(0));
fLambda_background->SetParameter(1, fLambda->GetParameter(1));
fLambda_background->SetParameter(2, fLambda->GetParameter(2));
fLambda_background->SetLineStyle(3);
fLambda_background->SetLineColor(fColors[1]);
background = fLambda_background->Integral(lowerBound, upperBound) /double(histo->GetBinWidth(1));
backgroundErr = fLambda_background->IntegralError(lowerBound, upperBound, backgroundR->GetParams(), backgroundR->GetCovarianceMatrix().GetMatrixArray()) /double(histo->GetBinWidth(1));
histo->GetListOfFunctions()->Add(fLambda_background);
delete signalOnly;
delete fSignalGauss;
delete fSignalSingleGauss;
}
//++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
// second order polynomial + double gaus to Xi peak
void FitXi(TH1F* histo, float &signal, float
&signalErr, float &background, float &backgroundErr, float lowerBound,
float upperBound)
{
// Fit Background with second order polynomial, excluding Mlambda +/- 10 MeV
TF1 *fBackground = new TF1("fBackground", [&](double *x, double *p) {
if (x[0] > 1.31 && x[0] < 1.335) {TF1::RejectPoint(); return
(double)0; } return p[0] + p[1]*x[0] + p[2]*x[0]*x[0]; }, 1.29, 1.35, 3);
TFitResultPtr backgroundR = histo->Fit("fBackground", "SRQ0", "",1.295,1.349);
// parse then to proper TF1
TF1 *fBackground2 = new TF1("fBackground2","pol2", 0, 1.4);
fBackground2->SetParameter(0, fBackground->GetParameter(0));
fBackground2->SetParameter(1, fBackground->GetParameter(1));
fBackground2->SetParameter(2, fBackground->GetParameter(2));
// remove background from signal
TH1F *signalOnly = getSignalHisto(fBackground2, histo, 1.3, 1.34,
Form("%s_signal_only", histo->GetName()));
// fit signal only
TF1 *fSignalSingleGauss = new TF1("fSignalSingleGauss", "gaus(0)",1.31,1.34);
// signalOnly->DrawCopy();
signalOnly->Fit("fSignalSingleGauss", "Q");
TF1 *fSignalGauss = new TF1("fSignalGauss", "gaus(0) + gaus(3)", 1.3,
1.4);
fSignalGauss->SetParameter(0, 0.75 * histo->GetMaximum());
fSignalGauss->SetParameter(1, fSignalSingleGauss->GetParameter(1));
fSignalGauss->SetParameter(2, 2.f*fSignalSingleGauss->GetParameter(2));
fSignalGauss->SetParLimits(2, 0.5*fSignalSingleGauss->GetParameter(2),1e2*2.f*fSignalSingleGauss->GetParameter(2));
fSignalGauss->SetParameter(3, 0.2 * histo->GetMaximum());
fSignalGauss->SetParameter(4, fSignalSingleGauss->GetParameter(1));
fSignalGauss->SetParLimits(4,
fSignalSingleGauss->GetParameter(1)-fSignalSingleGauss->GetParameter(2),
fSignalSingleGauss->GetParameter(1)+fSignalSingleGauss->GetParameter(2));
fSignalGauss->SetParameter(5, 0.5*fSignalSingleGauss->GetParameter(2));
fSignalGauss->SetParLimits(5, 0.5*fSignalSingleGauss->GetParameter(2),1e2*2.f*fSignalSingleGauss->GetParameter(2));
TFitResultPtr r = signalOnly->Fit("fSignalGauss", "SRQ0", "", 1.29,
1.38);
// Extract signal as integral
signal = fSignalGauss->Integral(lowerBound, upperBound)
/double(histo->GetBinWidth(1));
signalErr = fSignalGauss->IntegralError(lowerBound, upperBound,
r->GetParams(), r->GetCovarianceMatrix().GetMatrixArray())
/double(histo->GetBinWidth(1));
TF1 *fLambda = new TF1("fLambda", "fBackground2 + fSignalGauss", 1.25,
1.4);
fLambda->SetNpx(1000);
fLambda->SetParameter(3, 0.75 * histo->GetMaximum());
fLambda->SetParameter(4, fSignalGauss->GetParameter((1)));
fLambda->SetParameter(5, fSignalGauss->GetParameter((2)));
fLambda->SetParameter(6, 0.2 * histo->GetMaximum());
fLambda->SetParameter(7, fSignalGauss->GetParameter((4)));
fLambda->SetParameter(8, fSignalGauss->GetParameter((5)));
fLambda->SetLineColor(fColors[1]);
histo->Fit("fLambda", "SRQ", "", 1.28, 1.4);
TF1 *fLambda_background = new TF1("fLambda_background", "pol2(0)",
1.28, 1.45);
fLambda_background->SetParameter(0, fLambda->GetParameter(0));
fLambda_background->SetParameter(1, fLambda->GetParameter(1));
fLambda_background->SetParameter(2, fLambda->GetParameter(2));
fLambda_background->SetLineStyle(3);
fLambda_background->SetLineColor(fColors[1]);
background = fLambda_background->Integral(lowerBound, upperBound)
/double(histo->GetBinWidth(1));
backgroundErr = fLambda_background->IntegralError(lowerBound,
upperBound, backgroundR->GetParams(),
backgroundR->GetCovarianceMatrix().GetMatrixArray())
/double(histo->GetBinWidth(1));
histo->GetListOfFunctions()->Add(fLambda_background);
delete signalOnly;
delete fSignalGauss;
delete fSignalSingleGauss;
}
// ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
// a and c are the weighting entities, i.e. wMean = (weightA*A + weightB*d) / (a+weightB)
float weightedMean(float weightA, float A, float weightB, float B)
{
return (weightA*A + weightB*B)/(weightA+weightB);
}
// ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
// a and weightB are the weighting entities, i.e. wMean = (weightA*A + weightB*B) / (a+weightB)
float weightedMeanError(float weightA, float A, float weightB, float B, float weightAErr, float AErr, float weightBErr, float BErr)
{
return std::sqrt(weightAErr*weightAErr*std::pow(((weightB*(A - B))/((weightA + weightB)*(weightA + weightB))), 2) + AErr*AErr* std::pow(weightA/(weightA + weightB), 2) + weightBErr*weightBErr*std::pow((weightA* (-A + B))/((weightA + weightB)*(weightA + weightB)) , 2) + BErr*BErr* std::pow(weightB/(weightA + weightB), 2));
}
// ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
void testPileUp(const char *expfile = "~/Downloads/AnalysisResults.root", const char* prefix ="MB", const char* folder = "0") {
SetStyle();
TFile* _file0=TFile::Open(expfile);
// Mixed event normalisation
const float normleft = 0.2;
const float normright = 0.4;
const float right = 0.025;
const float top = 0.025;
TDirectoryFile *dirResults=(TDirectoryFile*)(_file0->FindObjectAny(Form("%sResults%s", prefix, folder)));
TList *Results;
dirResults->GetObject(Form("%sResults%s", prefix, folder), Results);
TList* tmpFolder=(TList*)Results->FindObject("Particle0_Particle0");
TH1F* histRE_relK_pp = (TH1F*)tmpFolder->FindObject("SEDist_Particle0_Particle0");
TH1F* histME_relK_pp = (TH1F*)tmpFolder->FindObject("MEDist_Particle0_Particle0");
tmpFolder=(TList*)Results->FindObject("Particle1_Particle1");
TH1F* histRE_relK_ApAp = (TH1F*)tmpFolder->FindObject("SEDist_Particle1_Particle1");
TH1F* histME_relK_ApAp = (TH1F*)tmpFolder->FindObject("MEDist_Particle1_Particle1");
tmpFolder=(TList*)Results->FindObject("Particle0_Particle2");
TH1F* histRE_relK_Lp = (TH1F*)tmpFolder->FindObject("SEDist_Particle0_Particle2");
TH1F* histME_relK_Lp = (TH1F*)tmpFolder->FindObject("MEDist_Particle0_Particle2");
tmpFolder=(TList*)Results->FindObject("Particle1_Particle3");
TH1F* histRE_relK_ALAp = (TH1F*)tmpFolder->FindObject("SEDist_Particle1_Particle3");
TH1F* histME_relK_ALAp = (TH1F*)tmpFolder->FindObject("MEDist_Particle1_Particle3");
tmpFolder=(TList*)Results->FindObject("Particle2_Particle2");
TH1F* histRE_relK_LL = (TH1F*)tmpFolder->FindObject("SEDist_Particle2_Particle2");
TH1F* histME_relK_LL = (TH1F*)tmpFolder->FindObject("MEDist_Particle2_Particle2");
tmpFolder=(TList*)Results->FindObject("Particle3_Particle3");
TH1F* histRE_relK_ALAL = (TH1F*)tmpFolder->FindObject("SEDist_Particle3_Particle3");
TH1F* histME_relK_ALAL = (TH1F*)tmpFolder->FindObject("MEDist_Particle3_Particle3");
tmpFolder=(TList*)Results->FindObject("Particle0_Particle4");
TH1F* histRE_relK_Xip = (TH1F*)tmpFolder->FindObject("SEDist_Particle0_Particle4");
TH1F* histME_relK_Xip = (TH1F*)tmpFolder->FindObject("MEDist_Particle0_Particle4");
tmpFolder=(TList*)Results->FindObject("Particle1_Particle5");
TH1F* histRE_relK_AXiAp = (TH1F*)tmpFolder->FindObject("SEDist_Particle1_Particle5");
TH1F* histME_relK_AXiAp = (TH1F*)tmpFolder->FindObject("MEDist_Particle1_Particle5");
const float marginLambda = 0.004;
const float massLambda = 1.115;
TDirectoryFile *dirv0Cuts=(TDirectoryFile*)(_file0->FindObjectAny(Form("%sv0Cuts%s", prefix, folder)));
TList *tmp=dirv0Cuts->GetListOfKeys();
TString name=tmp->At(0)->GetName();
TList *v0CutList;
dirv0Cuts->GetObject(name,v0CutList);
TList *v0Cuts = (TList*)v0CutList->FindObject("MinimalBooking");
if(!v0Cuts) v0Cuts = (TList*)v0CutList->FindObject("v0Cuts");
TH1F *InvMassPtLambda= (TH1F*)((TH2F*)v0Cuts->FindObject("InvMassPt"))->ProjectionY();
SetStyleHisto(InvMassPtLambda, 0,1);
float lambdaSignalAll, lambdaSignalAllErr, lambdaBackgroundAll, lambdaBackgroundAllErr;
FitLambda(InvMassPtLambda, lambdaSignalAll, lambdaSignalAllErr, lambdaBackgroundAll, lambdaBackgroundAllErr, massLambda-marginLambda, massLambda+marginLambda);
const int LambdaSignal = lambdaSignalAll;
const int LambdaBackground = lambdaBackgroundAll;
const float LambdaPurity = lambdaSignalAll/(lambdaSignalAll+lambdaBackgroundAll)*100.f;
std::cout << "Lambda \n";
std::cout << "Signal " << lambdaSignalAll << " Background " << lambdaBackgroundAll << " S/B " << lambdaSignalAll/lambdaBackgroundAll << " Purity " << lambdaSignalAll/(lambdaSignalAll+lambdaBackgroundAll)*100.f << "\n";
TDirectoryFile *dirAv0Cuts=(TDirectoryFile*)(_file0->FindObjectAny(Form("%sAntiv0Cuts%s", prefix, folder)));
tmp=dirAv0Cuts->GetListOfKeys();
name=tmp->At(0)->GetName();
TList *Av0CutList;
dirAv0Cuts->GetObject(name,Av0CutList);
TList *Av0Cuts = (TList*)Av0CutList->FindObject("MinimalBooking");
if(!Av0Cuts) Av0Cuts = (TList*)Av0CutList->FindObject("v0Cuts");
TH1F *InvMassPtAntiLambda= (TH1F*)((TH2F*)Av0Cuts->FindObject("InvMassPt"))->ProjectionY();
SetStyleHisto(InvMassPtAntiLambda, 0,1);
FitLambda(InvMassPtAntiLambda, lambdaSignalAll, lambdaSignalAllErr, lambdaBackgroundAll, lambdaBackgroundAllErr, massLambda-marginLambda, massLambda+marginLambda);
std::cout << "Anti-Lambda \n";
std::cout << "Signal " << lambdaSignalAll << " Background " << lambdaBackgroundAll << " S/B " << lambdaSignalAll/lambdaBackgroundAll << " Purity " << lambdaSignalAll/(lambdaSignalAll+lambdaBackgroundAll)*100.f << "\n";
const int AntiLambdaSignal = lambdaSignalAll;
const int AntiLambdaBackground = lambdaBackgroundAll;
const float AntiLambdaPurity = lambdaSignalAll/(lambdaSignalAll+lambdaBackgroundAll)*100.f;
TH2F* xiMass2D;
TH1F* xiMass;
TH2F* AntiXiMass2D;
TH1F* AntiXiMass;
TDirectoryFile *dirExp=(TDirectoryFile*)(_file0->FindObjectAny(Form("%sCascadeCuts%s", prefix, folder)));
tmp=dirExp->GetListOfKeys();
name=tmp->At(0)->GetName();
TList *output;
dirExp->GetObject(name,output);
TList *Cascade=(TList*)output->FindObject("MinimalBooking");
if(!Cascade) Cascade=(TList*)output->FindObject("Cascade");
xiMass2D=(TH2F*)Cascade->FindObject("InvMassXiPt");
xiMass=(TH1F*)xiMass2D->ProjectionY("InvMassXi");
SetStyleHisto(xiMass,0,1);
xiMass->GetXaxis()->SetRangeUser(1.285,1.345);
xiMass->GetXaxis()->SetTitle("M_{#pi#Lambda} (GeV/#it{c}^{2})");
float signalXi, signalErrXi, backgroundXi, backgroundErrXi;
float lowerBound=1.322-0.005;
float upperBound=1.322+0.005;
FitXi(xiMass, signalXi, signalErrXi, backgroundXi, backgroundErrXi, lowerBound,upperBound);
std::cout << "Xi\n";
std::cout << "Signal " << signalXi << " Background " << backgroundXi << " S/B " << signalXi/backgroundXi << " Purity " << signalXi/(signalXi+backgroundXi)*100.f << "\n";
const int XiSignal = signalXi;
const int XiBackground = backgroundXi;
const float XiPurity = signalXi/(signalXi+backgroundXi)*100.f;
dirExp=(TDirectoryFile*)(_file0->FindObjectAny(Form("%sAntiCascadeCuts%s", prefix, folder)));
tmp=dirExp->GetListOfKeys();
name=tmp->At(0)->GetName();
dirExp->GetObject(name,output);
TList *AntiCascade=(TList*)output->FindObject("MinimalBooking");
if(!AntiCascade) AntiCascade=(TList*)output->FindObject("Cascade");
AntiXiMass2D=(TH2F*)AntiCascade->FindObject("InvMassXiPt");
AntiXiMass=(TH1F*)AntiXiMass2D->ProjectionY("InvMassXi");
SetStyleHisto(AntiXiMass,0,1);
AntiXiMass->GetXaxis()->SetRangeUser(1.285,1.345);
AntiXiMass->GetXaxis()->SetTitle("M_{#pi#Lambda} (GeV/#it{c}^{2})");
float signalAntiXi, signalErrAntiXi, backgroundAntiXi, backgroundErrAntiXi;
FitXi(AntiXiMass, signalAntiXi, signalErrAntiXi, backgroundAntiXi, backgroundErrAntiXi, lowerBound,upperBound);
std::cout << "Anti-Xi\n";
std::cout << "Signal " << signalAntiXi << " Background " << backgroundAntiXi << " S/B " << signalAntiXi/backgroundAntiXi << " Purity " << signalAntiXi/(signalAntiXi+backgroundAntiXi)*100.f << "\n";
const int AntiXiSignal = signalAntiXi;
const int AntiXiBackground = backgroundAntiXi;
const float AntiXiPurity = signalAntiXi/(signalAntiXi+backgroundAntiXi)*100.f;
TH1F *hist_CF_Lp_ALAp_exp[3];
TH1F *hist_CF_LL_ALAL_exp[3];
TH1F *hist_CF_pp_ApAp_exp[3];
TH1F *hist_CF_pXi_ApAXi_exp[3];
hist_CF_Lp_ALAp_exp[0] = Calculate_CF(histRE_relK_Lp,histME_relK_Lp,"hist_CF_Lp_exp",normleft,normright);
hist_CF_Lp_ALAp_exp[1] = Calculate_CF(histRE_relK_ALAp,histME_relK_ALAp,"hist_CF_ALAp_exp",normleft,normright);
hist_CF_Lp_ALAp_exp[2] = add_CF(hist_CF_Lp_ALAp_exp[0],hist_CF_Lp_ALAp_exp[1],"hist_CF_Lp_ALAp_exp_sum");
hist_CF_LL_ALAL_exp[0] = Calculate_CF(histRE_relK_LL,histME_relK_LL,"hist_CF_LL_exp",normleft,normright);
hist_CF_LL_ALAL_exp[1] = Calculate_CF(histRE_relK_ALAL,histME_relK_ALAL,"hist_CF_LL_exp",normleft,normright);
hist_CF_LL_ALAL_exp[2] = add_CF(hist_CF_LL_ALAL_exp[0],hist_CF_LL_ALAL_exp[1],"hist_CF_LL_ALAL_exp_sum");
hist_CF_pp_ApAp_exp[0] = Calculate_CF(histRE_relK_pp,histME_relK_pp,"hist_CF_pp",normleft,normright);
hist_CF_pp_ApAp_exp[1] = Calculate_CF(histRE_relK_ApAp,histME_relK_ApAp,"hist_CF_ApAp",normleft,normright);
hist_CF_pp_ApAp_exp[2] = add_CF(hist_CF_pp_ApAp_exp[0],hist_CF_pp_ApAp_exp[1],"hist_CF_pp_ApAp_exp_sum");
hist_CF_pXi_ApAXi_exp[0] = Calculate_CF(histRE_relK_Xip,histME_relK_Xip,"hist_CF_pXi",normleft,normright);
hist_CF_pXi_ApAXi_exp[1] = Calculate_CF(histRE_relK_AXiAp,histME_relK_AXiAp,"hist_CF_ApAXi",normleft,normright);
hist_CF_pXi_ApAXi_exp[2] = add_CF(hist_CF_pXi_ApAXi_exp[0],hist_CF_pXi_ApAXi_exp[1],"hist_CF_pXi_ApAXi_exp_sum");
SetStyleHisto(hist_CF_pp_ApAp_exp[0], 1,1);
SetStyleHisto(hist_CF_Lp_ALAp_exp[0], 1,1);
SetStyleHisto(hist_CF_LL_ALAL_exp[0], 1,1);
SetStyleHisto(hist_CF_pXi_ApAXi_exp[0], 1,1);
SetStyleHisto(hist_CF_pp_ApAp_exp[1], 0,2);
SetStyleHisto(hist_CF_Lp_ALAp_exp[1], 0,2);
SetStyleHisto(hist_CF_LL_ALAL_exp[1], 0,2);
SetStyleHisto(hist_CF_pXi_ApAXi_exp[1], 0,2);
SetStyleHisto(hist_CF_pp_ApAp_exp[2], 0,0);
SetStyleHisto(hist_CF_Lp_ALAp_exp[2], 0,0);
SetStyleHisto(hist_CF_LL_ALAL_exp[2], 0,0);
SetStyleHisto(hist_CF_pXi_ApAXi_exp[2], 0,0);
// PLOTTING
TCanvas *Can_CF = new TCanvas("Can_CF","Can_CF",0,0,2000,1100);
Can_CF->Divide(4,2);
Can_CF->cd(1);
Can_CF->cd(1)->SetRightMargin(right);
Can_CF->cd(1)->SetTopMargin(top);
hist_CF_pp_ApAp_exp[0]->Draw("pe");
hist_CF_pp_ApAp_exp[1]->Draw("pe same");
hist_CF_pp_ApAp_exp[0]->SetTitle("; k* (GeV/#it{c}); #it{C}(k*)");
hist_CF_pp_ApAp_exp[0]->GetXaxis()->SetRangeUser(0, 0.4);
hist_CF_pp_ApAp_exp[0]->GetYaxis()->SetRangeUser(0, 4);
auto* leg= new TLegend(0.25, 0.7, 0.95, 0.95);
leg->AddEntry(hist_CF_pp_ApAp_exp[0], "Particle-particle CF", "pe");
leg->AddEntry(hist_CF_pp_ApAp_exp[1], "Antiparticle-antiparticle CF", "pe");
leg->Draw("same");
Can_CF->cd(2);
Can_CF->cd(2)->SetRightMargin(right);
Can_CF->cd(2)->SetTopMargin(top);
hist_CF_Lp_ALAp_exp[0]->Draw("pe");
hist_CF_Lp_ALAp_exp[1]->Draw("pe same");
hist_CF_Lp_ALAp_exp[0]->SetTitle("; k* (GeV/#it{c}); #it{C}(k*)");
hist_CF_Lp_ALAp_exp[0]->GetXaxis()->SetRangeUser(0, 0.4);
hist_CF_Lp_ALAp_exp[0]->GetXaxis()->SetNdivisions(505);
hist_CF_Lp_ALAp_exp[0]->GetYaxis()->SetRangeUser(0.8, 2.5);
Can_CF->cd(3);
Can_CF->cd(3)->SetRightMargin(right);
Can_CF->cd(3)->SetTopMargin(top);
hist_CF_LL_ALAL_exp[0]->Draw("pe");
hist_CF_LL_ALAL_exp[1]->Draw("pe same");
hist_CF_LL_ALAL_exp[0]->SetTitle("; k* (GeV/#it{c}); #it{C}(k*)");
hist_CF_LL_ALAL_exp[0]->GetXaxis()->SetRangeUser(0, 0.4);
hist_CF_LL_ALAL_exp[0]->GetXaxis()->SetNdivisions(505);
hist_CF_LL_ALAL_exp[0]->GetYaxis()->SetRangeUser(0.25, 3);
Can_CF->cd(4);
Can_CF->cd(4)->SetRightMargin(right);
Can_CF->cd(4)->SetTopMargin(top);
hist_CF_pXi_ApAXi_exp[0]->Draw("pe");
hist_CF_pXi_ApAXi_exp[1]->Draw("pe same");
hist_CF_pXi_ApAXi_exp[0]->SetTitle("; k* (GeV/#it{c}); #it{C}(k*)");
hist_CF_pXi_ApAXi_exp[0]->GetXaxis()->SetRangeUser(0, 0.4);
hist_CF_pXi_ApAXi_exp[0]->GetXaxis()->SetNdivisions(505);
hist_CF_pXi_ApAXi_exp[0]->GetYaxis()->SetRangeUser(0.5, 7.5);
Can_CF->cd(5);
Can_CF->cd(5)->SetRightMargin(right);
Can_CF->cd(5)->SetTopMargin(top);
TH1F *ppRatio = (TH1F*)hist_CF_pp_ApAp_exp[0]->Clone();
auto* line = new TLine(0,1,0.4,1);
line->SetLineColor(kGray+3);
line->SetLineWidth(2);
line->SetLineStyle(2);
ppRatio->Divide(hist_CF_pp_ApAp_exp[1]);
ppRatio->GetYaxis()->SetRangeUser(0,2);
ppRatio->SetTitle("; k* (GeV/#it{c}); #it{C}(k*)_{pp}/#it{C}(k*)_{#bar{pp}}");
ppRatio->SetMarkerStyle(fMarkers[2]);
ppRatio->Draw("pe");
line->Draw("same");
Can_CF->cd(6);
Can_CF->cd(6)->SetRightMargin(right);
Can_CF->cd(6)->SetTopMargin(top);
TH1F *pLRatio = (TH1F*)hist_CF_Lp_ALAp_exp[0]->Clone();
pLRatio->Divide(hist_CF_Lp_ALAp_exp[1]);
pLRatio->SetTitle("; k* (GeV/#it{c}); #it{C}(k*)_{p#Lambda}/#it{C}(k*)_{#bar{p}#bar{#Lambda}}");
pLRatio->GetYaxis()->SetRangeUser(0,2);
pLRatio->SetMarkerStyle(fMarkers[2]);
pLRatio->Draw("pe");
line->Draw("same");
Can_CF->cd(7);
Can_CF->cd(7)->SetRightMargin(right);
Can_CF->cd(7)->SetTopMargin(top);
TH1F *LLRatio = (TH1F*)hist_CF_LL_ALAL_exp[0]->Clone();
LLRatio->Divide(hist_CF_LL_ALAL_exp[1]);
LLRatio->SetTitle("; k* (GeV/#it{c}); #it{C}(k*)_{#Lambda#Lambda}/#it{C}(k*)_{#bar{#Lambda}#bar{#Lambda}}");
LLRatio->GetYaxis()->SetRangeUser(0,2);
LLRatio->SetMarkerStyle(fMarkers[2]);
LLRatio->Draw("pe");
line->Draw("same");
Can_CF->cd(8);
Can_CF->cd(8)->SetRightMargin(right);
Can_CF->cd(8)->SetTopMargin(top);
TH1F *pXiRatio = (TH1F*)hist_CF_pXi_ApAXi_exp[0]->Clone();
pXiRatio->Divide(hist_CF_pXi_ApAXi_exp[1]);
pXiRatio->SetTitle("; k* (GeV/#it{c}); #it{C}(k*)_{p#Xi^{-}}/#it{C}(k*)_{#bar{p}#Xi^{+}}");
pXiRatio->GetYaxis()->SetRangeUser(0,2);
pXiRatio->SetMarkerStyle(fMarkers[2]);
pXiRatio->Draw("pe");
line->Draw("same");
Can_CF->Print(Form("PileUp/CF_pp-apap_%s.pdf", folder));
TCanvas *Can_CF_comb = new TCanvas("Can_CF_comb","Can_CF_comb",0,0,1000,550);
Can_CF_comb->Divide(4,1);
Can_CF_comb->cd(1);
Can_CF_comb->cd(1)->SetRightMargin(right);
Can_CF_comb->cd(1)->SetTopMargin(top);
hist_CF_pp_ApAp_exp[2]->Draw("pe");
hist_CF_pp_ApAp_exp[2]->SetTitle("; k* (GeV/#it{c}); #it{C}(k*)");
hist_CF_pp_ApAp_exp[2]->GetXaxis()->SetRangeUser(0, 0.4);
hist_CF_pp_ApAp_exp[2]->GetYaxis()->SetRangeUser(0, 4);
Can_CF_comb->cd(2);
Can_CF_comb->cd(2)->SetRightMargin(right);
Can_CF_comb->cd(2)->SetTopMargin(top);
hist_CF_Lp_ALAp_exp[2]->Draw("pe");
hist_CF_Lp_ALAp_exp[2]->SetTitle("; k* (GeV/#it{c}); #it{C}(k*)");
hist_CF_Lp_ALAp_exp[2]->GetXaxis()->SetRangeUser(0, 0.4);
hist_CF_Lp_ALAp_exp[2]->GetXaxis()->SetNdivisions(505);
hist_CF_Lp_ALAp_exp[2]->GetYaxis()->SetRangeUser(0.8, 2.5);
Can_CF_comb->cd(3);
Can_CF_comb->cd(3)->SetRightMargin(right);
Can_CF_comb->cd(3)->SetTopMargin(top);
hist_CF_LL_ALAL_exp[2]->Draw("pe");
hist_CF_LL_ALAL_exp[2]->SetTitle("; k* (GeV/#it{c}); #it{C}(k*)");
hist_CF_LL_ALAL_exp[2]->GetXaxis()->SetRangeUser(0, 0.4);
hist_CF_LL_ALAL_exp[2]->GetXaxis()->SetNdivisions(505);
hist_CF_LL_ALAL_exp[2]->GetYaxis()->SetRangeUser(0.25, 3);
Can_CF_comb->cd(4);
Can_CF_comb->cd(4)->SetRightMargin(right);
Can_CF_comb->cd(4)->SetTopMargin(top);
hist_CF_pXi_ApAXi_exp[2]->Draw("pe");
hist_CF_pXi_ApAXi_exp[2]->SetTitle("; k* (GeV/#it{c}); #it{C}(k*)");
hist_CF_pXi_ApAXi_exp[2]->GetXaxis()->SetRangeUser(0, 0.4);
hist_CF_pXi_ApAXi_exp[2]->GetXaxis()->SetNdivisions(505);
hist_CF_pXi_ApAXi_exp[2]->GetYaxis()->SetRangeUser(0.5, 7.5);
Can_CF_comb->Print(Form("PileUp/CF_%s.pdf", folder));
TCanvas *cLambda = new TCanvas("cLambda","cLambda",0,0,1000,550);
cLambda->Divide(2,1);
cLambda->cd(1);
InvMassPtLambda->Draw();
InvMassPtLambda->GetXaxis()->SetRangeUser(1.1, 1.13);
TLatex LambdaLabel;
LambdaLabel.SetNDC(kTRUE);
LambdaLabel.SetTextSize(gStyle->GetTextSize()*0.8);
LambdaLabel.DrawLatex(0.2, 0.8, Form("Purity: %.1f %%", LambdaPurity));
LambdaLabel.DrawLatex(0.2, 0.75, Form("Signal: %.2f #times 10^{6}", float(LambdaSignal)/1000000.f));
LambdaLabel.DrawLatex(0.2, 0.7, Form("Background: %.2f #times 10^{6}",float(LambdaBackground)/1000000.f));
cLambda->cd(2);
InvMassPtAntiLambda->Draw();
InvMassPtAntiLambda->GetXaxis()->SetRangeUser(1.1, 1.13);
LambdaLabel.DrawLatex(0.2, 0.8, Form("Purity: %.1f %%", AntiLambdaPurity));
LambdaLabel.DrawLatex(0.2, 0.75, Form("Signal: %.2f #times 10^{6}", float(AntiLambdaSignal)/1000000.f));
LambdaLabel.DrawLatex(0.2, 0.7, Form("Background: %.2f #times 10^{6}",float(AntiLambdaBackground)/1000000.f));
cLambda->Print(Form("PileUp/Lambda_%s.pdf", folder));
TCanvas *Xi= new TCanvas("cXi","cXi",0,0,1000,550);
Xi->Divide(2,1);
Xi->cd(1);
xiMass->Draw();
LambdaLabel.SetNDC(kTRUE);
LambdaLabel.SetTextSize(gStyle->GetTextSize()*0.8);
LambdaLabel.DrawLatex(0.2, 0.8, Form("Purity: %.1f %%", XiPurity));
LambdaLabel.DrawLatex(0.2, 0.75, Form("Signal: %.2f #times 10^{3}", float(XiSignal)/1000.f));
LambdaLabel.DrawLatex(0.2, 0.7, Form("Background: %.2f #times 10^{3}",float(XiBackground)/1000.f));
Xi->cd(2);
AntiXiMass->Draw();
LambdaLabel.SetNDC(kTRUE);
LambdaLabel.SetTextSize(gStyle->GetTextSize()*0.8);
LambdaLabel.DrawLatex(0.2, 0.8, Form("Purity: %.1f %%", AntiXiPurity));
LambdaLabel.DrawLatex(0.2, 0.75, Form("Signal: %.2f #times 10^{3}", float(AntiXiSignal)/1000.f));
LambdaLabel.DrawLatex(0.2, 0.7, Form("Background: %.2f #times 10^{3}",float(AntiXiBackground)/1000.f));
Xi->Print(Form("PileUp/Xi_%s.pdf", folder));
}