[u/mrichter/AliRoot.git] / PWGHF / vertexingHF / macros / CombineFeedDownMCSubtractionMethodsUncertainties.C

#include "TFile.h"
#include "TH1.h"
#include "TH1D.h"
#include "TH2.h"
#include "TH2F.h"
#include "TGraphAsymmErrors.h"
#include "TCanvas.h"
#include "TLegend.h"
#include "TMath.h"
#include "TROOT.h"
#include "TStyle.h"

#include "AliHFSystErr.h"

#include <Riostream.h>

//_________________________________________________________________________________________
//
//  Macro to combine the the MonteCarlo B feed-down subtraction uncertainties
//
//   Take as input the output files from the HFPtSpectrum class 
//    from both fc & Nb subtraction methods and combine the uncertainties. 
//   The final central value is set as the one from the Nb-method. 
//   The final uncertainties are defined as the envelope of both fc & Nb
//      uncertainties with respect to the new central-value.
//   The final global uncertainties are also defined and a preliminary drawing done. 
//
//
//   Usage parameters:
//      1. HFPtSpectrum fc subtraction file 
//      2. HFPtSpectrum Nb subtraction file 
//      3. Output file name
//      4. FONLL theoretical predictions file to draw on top
//      5. Decay channel as defined in the AliHFSystErr class
//
//_________________________________________________________________________________________

enum centrality{ kpp7, kpp276, k010, k020, k2040, k4060, k6080, k4080, k80100 };

void CombineFeedDownMCSubtractionMethodsUncertainties(const char *fcfilename="HFPtSpectrum_D0Kpi_method1_221110_newnorm.root",
						      const char *nbfilename="HFPtSpectrum_D0Kpi_method2_221110_newnorm.root",
						      const char *outfilename="HFPtSpectrum_D0Kpi_combinedFD.root",
						      const char *thfilename="D0DplusDstarPredictions_y05.root",
						      Int_t decay=1, Int_t centrality=kpp7)
{
  
  // 
  // Get fc file inputs
  TFile * fcfile = new TFile(fcfilename,"read");
  TH1D * histoSigmaCorrFc = (TH1D*)fcfile->Get("histoSigmaCorr");
  histoSigmaCorrFc->SetNameTitle("histoSigmaCorrFc","histoSigmaCorrFc");
  TGraphAsymmErrors * gSigmaCorrFc = (TGraphAsymmErrors*)fcfile->Get("gSigmaCorr");
  gSigmaCorrFc->SetNameTitle("gSigmaCorrFc","gSigmaCorrFc");
  TGraphAsymmErrors * gSigmaCorrConservativeFc = (TGraphAsymmErrors*)fcfile->Get("gSigmaCorrConservative");
  gSigmaCorrConservativeFc->SetNameTitle("gSigmaCorrConservativeFc","Cross section (fc prompt fraction)");
  TGraphAsymmErrors * gFcConservativeFc = (TGraphAsymmErrors*)fcfile->Get("gFcConservative");
  gFcConservativeFc->SetNameTitle("gFcConservativeFc","fc prompt fraction");

  // 
  // Get Nb file inputs
  TFile * nbfile = new TFile(nbfilename,"read");
  TH1D * histoSigmaCorrNb = (TH1D*)nbfile->Get("histoSigmaCorr");
  histoSigmaCorrNb->SetNameTitle("histoSigmaCorrNb","histoSigmaCorrNb");
  TGraphAsymmErrors * gSigmaCorrNb = (TGraphAsymmErrors*)nbfile->Get("gSigmaCorr");
  gSigmaCorrNb->SetNameTitle("gSigmaCorrNb","gSigmaCorrNb");
  TGraphAsymmErrors * gSigmaCorrConservativeNb = (TGraphAsymmErrors*)nbfile->Get("gSigmaCorrConservative");
  gSigmaCorrConservativeNb->SetNameTitle("gSigmaCorrConservativeNb","Cross section (Nb prompt fraction)");
  TGraphAsymmErrors * gFcConservativeNb = (TGraphAsymmErrors*)nbfile->Get("gFcConservative");
  gFcConservativeNb->SetNameTitle("gFcConservativeNb","Nb prompt fraction");

  //
  // Get the predictions input
  TFile *thfile = new TFile(thfilename,"read");
  TGraphAsymmErrors * thD0KpifromBprediction = (TGraphAsymmErrors*)thfile->Get("D0Kpiprediction");
  TGraphAsymmErrors * thDpluskpipiprediction = (TGraphAsymmErrors*)thfile->Get("Dpluskpipiprediction");
  TGraphAsymmErrors * thDstarD0piprediction = (TGraphAsymmErrors*)thfile->Get("DstarD0piprediction");
  thD0KpifromBprediction->SetLineColor(4);
  thD0KpifromBprediction->SetFillColor(kAzure+9);
  thDpluskpipiprediction->SetLineColor(4);
  thDpluskpipiprediction->SetFillColor(kAzure+9);
  thDstarD0piprediction->SetLineColor(4);
  thDstarD0piprediction->SetFillColor(kAzure+9);

  //
  // Get the spectra bins & limits
  Int_t nbins = histoSigmaCorrFc->GetNbinsX();
  Double_t *limits = new Double_t[nbins+1];
  Double_t xlow=0., binwidth=0.;
  for (Int_t i=1; i<=nbins; i++) {
    binwidth = histoSigmaCorrFc->GetBinWidth(i);
    xlow = histoSigmaCorrFc->GetBinLowEdge(i);
    limits[i-1] = xlow;
  }
  limits[nbins] = xlow + binwidth;


  //
  // Define a new histogram with the real-data reconstructed spectrum binning 
  //   they will be filled with central value equal to the Nb result
  //   and uncertainties taken from the envelope of the result uncertainties
  //   The systematical unc. (but FD) will also be re-calculated
  //
  TH1D * histoSigmaCorr = new TH1D("histoSigmaCorr","corrected cross-section (combined fc and Nb MC feed-down subtraction)",nbins,limits);
  TGraphAsymmErrors * gSigmaCorr = new TGraphAsymmErrors(nbins+1);
  gSigmaCorr->SetNameTitle("gSigmaCorr","gSigmaCorr (combined fc and Nb MC FD)");
  TGraphAsymmErrors * gFcCorrConservative = new TGraphAsymmErrors(nbins+1);
  gFcCorrConservative->SetNameTitle("gFcCorrConservative","Combined prompt fraction");
  TGraphAsymmErrors * gSigmaCorrConservative = new TGraphAsymmErrors(nbins+1);
  gSigmaCorrConservative->SetNameTitle("gSigmaCorrConservative","Cross section (combined prompt fraction)");
  TGraphAsymmErrors * gSigmaCorrConservativePC = new TGraphAsymmErrors(nbins+1);
  gSigmaCorrConservativePC->SetNameTitle("gSigmaCorrConservativePC","Conservative gSigmaCorr (combined fc and Nb MC FD) in percentages [for drawing with AliHFSystErr]");

  //
  // Call the systematics uncertainty class for a given decay
  //   will help to compute the systematical unc. (but FD) 
  AliHFSystErr systematics;
  if( centrality==kpp276 ) {
    systematics.SetIsLowEnergy(true);
  } else if( centrality!=kpp7 )  {
    systematics.SetCollisionType(1);
    if ( centrality == k020 ) {
      systematics.SetCentrality("020");
    }
    else if ( centrality == k4080 ) {
      systematics.SetCentrality("4080");
    }
    else { 
      cout << " Systematics not yet implemented " << endl;
      return;
    }
  }
  else { systematics.SetCollisionType(0); }
  systematics.Init(decay);

  // 
  // Loop on all the bins to do the calculations
  //
  Double_t pt=0., average = 0., averageStatUnc=0., avErrx=0., avErryl=0., avErryh=0., avErryfdl=0., avErryfdh=0.;
  Double_t avErrylPC=0., avErryhPC=0., avErryfdlPC=0., avErryfdhPC=0.;
  Double_t valFc = 0., valFcErrstat=0., valFcErrx=0., valFcErryl=0., valFcErryh=0., valFcErryfdl=0., valFcErryfdh=0.;
  Double_t valNb = 0., valNbErrstat=0., valNbErrx=0., valNbErryl=0., valNbErryh=0., valNbErryfdl=0., valNbErryfdh=0.;
  Double_t corrfd = 0., corrfdl=0., corrfdh=0.;
  //
  for(Int_t ibin=1; ibin<=nbins; ibin++){

    // Get input values from fc method
    valFc = histoSigmaCorrFc->GetBinContent(ibin);
    pt = histoSigmaCorrFc->GetBinCenter(ibin);
    valFcErrstat = histoSigmaCorrFc->GetBinError(ibin);
    Double_t value =0., ptt=0.;
    gSigmaCorrConservativeFc->GetPoint(ibin,ptt,value);
    if (value<=0.) continue;
    if ( TMath::Abs(valFc-value)>0.1 || TMath::Abs(pt-ptt)>0.1 ) 
      cout << "Hey you ! There might be a problem with the fc input file, please, have a look !" << endl;
    valFcErrx = gSigmaCorrFc->GetErrorXlow(ibin);
    valFcErryl = gSigmaCorrFc->GetErrorYlow(ibin);
    valFcErryh = gSigmaCorrFc->GetErrorYhigh(ibin);
    valFcErryfdl = TMath::Abs( gSigmaCorrConservativeFc->GetErrorYlow(ibin) );
    valFcErryfdh = TMath::Abs( gSigmaCorrConservativeFc->GetErrorYhigh(ibin) );
    Double_t valfdFc = 0., x=0.;
    gFcConservativeFc->GetPoint(ibin,x,valfdFc);
    Double_t valfdFch = gFcConservativeFc->GetErrorYhigh(ibin);
    Double_t valfdFcl = gFcConservativeFc->GetErrorYlow(ibin);

    // Get input values from Nb method
    valNb = histoSigmaCorrNb->GetBinContent(ibin);
    pt = histoSigmaCorrNb->GetBinCenter(ibin);
    valNbErrstat = histoSigmaCorrNb->GetBinError(ibin);
    gSigmaCorrConservativeNb->GetPoint(ibin,ptt,value);
    if ( TMath::Abs(valNb-value)>0.1 || TMath::Abs(pt-ptt)>0.1 ) 
      cout << "Hey you ! There might be a problem with the Nb input file, please, have a look !" << endl;
    valNbErrx = gSigmaCorrNb->GetErrorXlow(ibin);
    valNbErryl = gSigmaCorrNb->GetErrorYlow(ibin);
    valNbErryh = gSigmaCorrNb->GetErrorYhigh(ibin);
    valNbErryfdl = gSigmaCorrConservativeNb->GetErrorYlow(ibin);
    valNbErryfdh = gSigmaCorrConservativeNb->GetErrorYhigh(ibin);
    Double_t valfdNb = 0.;
    gFcConservativeNb->GetPoint(ibin,x,valfdNb);
    Double_t valfdNbh = gFcConservativeNb->GetErrorYhigh(ibin);
    Double_t valfdNbl = gFcConservativeNb->GetErrorYlow(ibin);
    

    // Compute the FD combined value
    //    average = valNb
    average = valNb ;
    corrfd = valfdNb;
    avErrx = valFcErrx;
    if ( TMath::Abs( valFcErrx - valNbErrx ) > 0.1 ) 
      cout << "Hey you ! There might be consistency problem with the fc & Nb input files, please, have a look !" << endl;
    averageStatUnc = valNbErrstat ;
//     cout << " pt=" << pt << ", average="<<average<<endl;
//     cout << "   stat unc (pc)=" << averageStatUnc/average << ", stat-fc (pc)="<<(valFcErrstat/valFc) << ", stat-Nb (pc)="<<(valNbErrstat/valNb)<<endl;
    
    // now estimate the new feed-down combined uncertainties
    Double_t minimum[2] = { (valFc - valFcErryfdl), (valNb - valNbErryfdl) };
    Double_t maximum[2] = { (valFc + valFcErryfdh), (valNb + valNbErryfdh) };
    avErryfdl = average - TMath::MinElement(2,minimum);
    avErryfdh = TMath::MaxElement(2,maximum) - average;
    avErryfdlPC = avErryfdl / average ; // in percentage
    avErryfdhPC = avErryfdh / average ; // in percentage
//     cout << " fc : val " << valFc << " + " << valFcErryfdh <<" - " << valFcErryfdl <<endl;
//     cout << " Nb : val " << valNb << " + " << valNbErryfdh <<" - " << valNbErryfdl <<endl;
//     cout << " fc  & Nb: val " << average << " + " << avErryfdh <<" - " << avErryfdl <<endl;
    Double_t minimumfc[2] = { (valfdNb - valfdNbl), (valfdFc - valfdFcl) };
    Double_t maximumfc[2] = { (valfdNb + valfdNbh), (valfdFc + valfdFch) };
    corrfdl = corrfd - TMath::MinElement(2,minimumfc);
    corrfdh = TMath::MaxElement(2,maximumfc) - corrfd;


    // compute the global systematics
    avErrylPC = systematics.GetTotalSystErr(pt,avErryfdlPC); // in percentage
    avErryhPC = systematics.GetTotalSystErr(pt,avErryfdhPC); // in percentage
    avErryl = avErrylPC * average ;
    avErryh = avErryhPC * average ;
//     cout << "   syst av-l="<<avErryl<<", av-h="<<avErryh<<endl;
//     cout << "     fd-l-pc="<<avErryfdlPC<<", fd-h-pc="<<avErryfdhPC<<", syst err(no fd)-pc="<<systematics.GetTotalSystErr(pt)<<", av-l-pc="<<avErrylPC<<", av-h-pc="<<avErryhPC<<endl;

    // fill in the histos and TGraphs
    //   fill them only when for non empty bins
    if ( average > 0.1 ) {
      histoSigmaCorr->SetBinContent(ibin,average);
      histoSigmaCorr->SetBinError(ibin,averageStatUnc);
      gSigmaCorr->SetPoint(ibin,pt,average);
      gSigmaCorr->SetPointError(ibin,valFcErrx,valFcErrx,avErryl,avErryh);
      gSigmaCorrConservative->SetPoint(ibin,pt,average);
      gSigmaCorrConservative->SetPointError(ibin,valFcErrx,valFcErrx,avErryfdl,avErryfdh);
      gSigmaCorrConservativePC->SetPoint(ibin,pt,0.);
      gSigmaCorrConservativePC->SetPointError(ibin,valFcErrx,valFcErrx,avErryfdlPC,avErryfdhPC);
      gFcCorrConservative->SetPoint(ibin,pt,corrfd);
      gFcCorrConservative->SetPointError(ibin,valFcErrx,valFcErrx,corrfdl,corrfdh);
    }

  }


  gROOT->SetStyle("Plain");
  gStyle->SetOptTitle(0);

  //
  // Plot the results
  TH2F *histo2Draw = new TH2F("histo2Draw","histo2 (for drawing)",100,0,20.,100,1e3,5e7);
  histo2Draw->SetStats(0);
  histo2Draw->GetXaxis()->SetTitle("p_{T}  [GeV]");
  histo2Draw->GetXaxis()->SetTitleSize(0.05);
  histo2Draw->GetXaxis()->SetTitleOffset(0.95);
  histo2Draw->GetYaxis()->SetTitle("#frac{1}{BR} #times #frac{d#sigma}{dp_{T}} |_{|y|<0.5}");
  histo2Draw->GetYaxis()->SetTitleSize(0.05);
  //
  TCanvas *combinefdunc = new TCanvas("combinefdunc","show the FD results combination");
  //
  histo2Draw->Draw();
  //
  histoSigmaCorrFc->SetMarkerStyle(20);
  histoSigmaCorrFc->SetMarkerColor(kGreen+2);
  histoSigmaCorrFc->SetLineColor(kGreen+2);
  histoSigmaCorrFc->Draw("esame");
  gSigmaCorrConservativeFc->SetMarkerStyle(20);
  gSigmaCorrConservativeFc->SetMarkerColor(kGreen+2);
  gSigmaCorrConservativeFc->SetLineColor(kGreen+2);
  gSigmaCorrConservativeFc->SetFillStyle(3004);//2);
  gSigmaCorrConservativeFc->SetFillColor(kGreen);
  gSigmaCorrConservativeFc->Draw("2[]same");
  //
  histoSigmaCorrNb->SetMarkerStyle(25);
  histoSigmaCorrNb->SetMarkerColor(kViolet+5);
  histoSigmaCorrNb->SetLineColor(kViolet+5);
  histoSigmaCorrNb->Draw("esame");
  gSigmaCorrConservativeNb->SetMarkerStyle(25);
  gSigmaCorrConservativeNb->SetMarkerColor(kOrange+7);//kViolet+5);
  gSigmaCorrConservativeNb->SetLineColor(kOrange+7);//kOrange+7);//kViolet+5);
  gSigmaCorrConservativeNb->SetFillStyle(3018);//02);
  gSigmaCorrConservativeNb->SetFillColor(kMagenta);
  gSigmaCorrConservativeNb->Draw("2[]same");
  //
  gSigmaCorrConservative->SetLineColor(kRed);
  gSigmaCorrConservative->SetLineWidth(2);
  gSigmaCorrConservative->SetFillColor(kRed);
  gSigmaCorrConservative->SetFillStyle(0);
  gSigmaCorrConservative->Draw("2");
  histoSigmaCorr->SetMarkerColor(kRed);
  histoSigmaCorr->Draw("esame");
  //
  //
  TLegend* leg=combinefdunc->BuildLegend();
  leg->SetFillStyle(0);
  combinefdunc->SetLogy();
  combinefdunc->Update();

  TCanvas *combinefcunc = new TCanvas("combinefcunc","show the fc FD results combination");
  //
  TH2F *histo3Draw = new TH2F("histo3Draw","histo3 (for drawing)",100,0,20.,10,0.,1.);
  histo3Draw->SetStats(0);
  histo3Draw->GetXaxis()->SetTitle("p_{T}  [GeV]");
  histo3Draw->GetXaxis()->SetTitleSize(0.05);
  histo3Draw->GetXaxis()->SetTitleOffset(0.95);
  histo3Draw->GetYaxis()->SetTitle("Prompt fraction of the raw yields");
  histo3Draw->GetYaxis()->SetTitleSize(0.05);
  histo3Draw->Draw();
  //
  gFcConservativeFc->SetMarkerStyle(20);
  gFcConservativeFc->SetMarkerColor(kGreen+2);
  gFcConservativeFc->SetLineColor(kGreen+2);
  gFcConservativeFc->SetFillStyle(3004);
  gFcConservativeFc->SetFillColor(kGreen);
  gFcConservativeFc->Draw("2P");
  //
  gFcConservativeNb ->SetMarkerStyle(25);
  gFcConservativeNb ->SetMarkerSize(1.3);
  gFcConservativeNb->SetMarkerColor(kOrange+7);//kViolet+5);
  gFcConservativeNb->SetLineColor(kOrange+7);//kViolet+5);
  gFcConservativeNb->SetFillStyle(3018);
  gFcConservativeNb->SetFillColor(kMagenta);
  gFcConservativeNb->Draw("2P");
  //
  gFcCorrConservative->SetMarkerStyle(21);
  gFcCorrConservative->SetLineColor(kRed);
  gFcCorrConservative->SetLineWidth(2);
  gFcCorrConservative->SetFillColor(kRed);
  gFcCorrConservative->SetFillStyle(0);
  gFcCorrConservative->Draw("2P");
  //
  leg=combinefcunc->BuildLegend();
  leg->SetFillStyle(0);
  //
  combinefcunc->Update();

  //
  // Plot the results
  TCanvas *finalresults = new TCanvas("finalresults","show all combined results");
  //
  if ( decay==1 ) {
    thD0KpifromBprediction->SetLineColor(kGreen+2);
    thD0KpifromBprediction->SetLineWidth(3);
    thD0KpifromBprediction->SetFillColor(kGreen-6);
    thD0KpifromBprediction->Draw("3CA");
    thD0KpifromBprediction->Draw("CX");
  }
  else if ( decay==2 ) {
    thDpluskpipiprediction->SetLineColor(kGreen+2);
    thDpluskpipiprediction->SetLineWidth(3);
    thDpluskpipiprediction->SetFillColor(kGreen-6);
    thDpluskpipiprediction->Draw("3CA");
    thDpluskpipiprediction->Draw("CX");
  }
  else if ( decay==3 ) {
    thDstarD0piprediction->SetLineColor(kGreen+2);
    thDstarD0piprediction->SetLineWidth(3);
    thDstarD0piprediction->SetFillColor(kGreen-6);
    thDstarD0piprediction->Draw("3CA");
    thDstarD0piprediction->Draw("CX");
  }
  //
  gSigmaCorr->SetLineColor(kRed);
  gSigmaCorr->SetLineWidth(1);
  gSigmaCorr->SetFillColor(kRed);
  gSigmaCorr->SetFillStyle(0);
  gSigmaCorr->Draw("2");
  histoSigmaCorr->SetMarkerStyle(21);
  histoSigmaCorr->SetMarkerColor(kRed);
  histoSigmaCorr->Draw("esame");
  //
  leg = new TLegend(0.7,0.75,0.87,0.5);
  leg->SetBorderSize(0);
  leg->SetLineColor(0);
  leg->SetFillColor(0);
  leg->SetTextFont(42);
  if ( decay==1 ) leg->AddEntry(thD0KpifromBprediction,"FONLL ","fl");
  else if ( decay==2 ) leg->AddEntry(thDpluskpipiprediction,"FONLL ","fl");
  else if ( decay==3 ) leg->AddEntry(thDstarD0piprediction,"FONLL ","fl");
  leg->AddEntry(histoSigmaCorr,"data stat. unc.","pl");
  leg->AddEntry(gSigmaCorr,"data syst. unc.","f");
  leg->Draw();
  //
  finalresults->SetLogy();
  finalresults->Update();


  //
  // Draw all the systematics independently
  systematics.DrawErrors(gSigmaCorrConservativePC);


  // Write the output to a file
  TFile * out = new TFile(outfilename,"recreate");
  histoSigmaCorr->Write();
  gSigmaCorr->Write();
  gSigmaCorrConservative->Write();
  gSigmaCorrConservativePC->Write();
  gFcCorrConservative->Write();
  out->Write();

}
Commit	Line	Data
066998f0	1	#include "TFile.h"
	2	#include "TH1.h"
	3	#include "TH1D.h"
	4	#include "TH2.h"
	5	#include "TH2F.h"
	6	#include "TGraphAsymmErrors.h"
	7	#include "TCanvas.h"
	8	#include "TLegend.h"
	9	#include "TMath.h"
	10	#include "TROOT.h"
	11	#include "TStyle.h"
	12
	13	#include "AliHFSystErr.h"
	14
	15	#include <Riostream.h>
	16
	17	//_________________________________________________________________________________________
	18	//
	19	// Macro to combine the the MonteCarlo B feed-down subtraction uncertainties
	20	//
	21	// Take as input the output files from the HFPtSpectrum class
	22	// from both fc & Nb subtraction methods and combine the uncertainties.
	23	// The final central value is set as the one from the Nb-method.
	24	// The final uncertainties are defined as the envelope of both fc & Nb
	25	// uncertainties with respect to the new central-value.
	26	// The final global uncertainties are also defined and a preliminary drawing done.
	27	//
	28	//
	29	// Usage parameters:
	30	// 1. HFPtSpectrum fc subtraction file
	31	// 2. HFPtSpectrum Nb subtraction file
	32	// 3. Output file name
	33	// 4. FONLL theoretical predictions file to draw on top
	34	// 5. Decay channel as defined in the AliHFSystErr class
	35	//
	36	//_________________________________________________________________________________________
	37
066c6b9b	38	enum centrality{ kpp7, kpp276, k010, k020, k2040, k4060, k6080, k4080, k80100 };
066998f0	39
	40	void CombineFeedDownMCSubtractionMethodsUncertainties(const char *fcfilename="HFPtSpectrum_D0Kpi_method1_221110_newnorm.root",
	41	const char *nbfilename="HFPtSpectrum_D0Kpi_method2_221110_newnorm.root",
	42	const char *outfilename="HFPtSpectrum_D0Kpi_combinedFD.root",
	43	const char *thfilename="D0DplusDstarPredictions_y05.root",
066c6b9b	44	Int_t decay=1, Int_t centrality=kpp7)
066998f0	45	{
	46
	47	//
	48	// Get fc file inputs
	49	TFile * fcfile = new TFile(fcfilename,"read");
	50	TH1D * histoSigmaCorrFc = (TH1D*)fcfile->Get("histoSigmaCorr");
	51	histoSigmaCorrFc->SetNameTitle("histoSigmaCorrFc","histoSigmaCorrFc");
	52	TGraphAsymmErrors * gSigmaCorrFc = (TGraphAsymmErrors*)fcfile->Get("gSigmaCorr");
	53	gSigmaCorrFc->SetNameTitle("gSigmaCorrFc","gSigmaCorrFc");
	54	TGraphAsymmErrors * gSigmaCorrConservativeFc = (TGraphAsymmErrors*)fcfile->Get("gSigmaCorrConservative");
ce4c4d27	55	gSigmaCorrConservativeFc->SetNameTitle("gSigmaCorrConservativeFc","Cross section (fc prompt fraction)");
	56	TGraphAsymmErrors * gFcConservativeFc = (TGraphAsymmErrors*)fcfile->Get("gFcConservative");
	57	gFcConservativeFc->SetNameTitle("gFcConservativeFc","fc prompt fraction");
066998f0	58
	59	//
	60	// Get Nb file inputs
	61	TFile * nbfile = new TFile(nbfilename,"read");
	62	TH1D * histoSigmaCorrNb = (TH1D*)nbfile->Get("histoSigmaCorr");
	63	histoSigmaCorrNb->SetNameTitle("histoSigmaCorrNb","histoSigmaCorrNb");
	64	TGraphAsymmErrors * gSigmaCorrNb = (TGraphAsymmErrors*)nbfile->Get("gSigmaCorr");
	65	gSigmaCorrNb->SetNameTitle("gSigmaCorrNb","gSigmaCorrNb");
	66	TGraphAsymmErrors * gSigmaCorrConservativeNb = (TGraphAsymmErrors*)nbfile->Get("gSigmaCorrConservative");
ce4c4d27	67	gSigmaCorrConservativeNb->SetNameTitle("gSigmaCorrConservativeNb","Cross section (Nb prompt fraction)");
	68	TGraphAsymmErrors * gFcConservativeNb = (TGraphAsymmErrors*)nbfile->Get("gFcConservative");
	69	gFcConservativeNb->SetNameTitle("gFcConservativeNb","Nb prompt fraction");
066998f0	70
	71	//
	72	// Get the predictions input
	73	TFile *thfile = new TFile(thfilename,"read");
	74	TGraphAsymmErrors * thD0KpifromBprediction = (TGraphAsymmErrors*)thfile->Get("D0Kpiprediction");
	75	TGraphAsymmErrors * thDpluskpipiprediction = (TGraphAsymmErrors*)thfile->Get("Dpluskpipiprediction");
	76	TGraphAsymmErrors * thDstarD0piprediction = (TGraphAsymmErrors*)thfile->Get("DstarD0piprediction");
	77	thD0KpifromBprediction->SetLineColor(4);
	78	thD0KpifromBprediction->SetFillColor(kAzure+9);
	79	thDpluskpipiprediction->SetLineColor(4);
	80	thDpluskpipiprediction->SetFillColor(kAzure+9);
	81	thDstarD0piprediction->SetLineColor(4);
	82	thDstarD0piprediction->SetFillColor(kAzure+9);
	83
	84	//
	85	// Get the spectra bins & limits
	86	Int_t nbins = histoSigmaCorrFc->GetNbinsX();
	87	Double_t *limits = new Double_t[nbins+1];
	88	Double_t xlow=0., binwidth=0.;
	89	for (Int_t i=1; i<=nbins; i++) {
	90	binwidth = histoSigmaCorrFc->GetBinWidth(i);
	91	xlow = histoSigmaCorrFc->GetBinLowEdge(i);
	92	limits[i-1] = xlow;
	93	}
	94	limits[nbins] = xlow + binwidth;
	95
	96
	97	//
	98	// Define a new histogram with the real-data reconstructed spectrum binning
	99	// they will be filled with central value equal to the Nb result
	100	// and uncertainties taken from the envelope of the result uncertainties
	101	// The systematical unc. (but FD) will also be re-calculated
	102	//
	103	TH1D * histoSigmaCorr = new TH1D("histoSigmaCorr","corrected cross-section (combined fc and Nb MC feed-down subtraction)",nbins,limits);
	104	TGraphAsymmErrors * gSigmaCorr = new TGraphAsymmErrors(nbins+1);
	105	gSigmaCorr->SetNameTitle("gSigmaCorr","gSigmaCorr (combined fc and Nb MC FD)");
ce4c4d27	106	TGraphAsymmErrors * gFcCorrConservative = new TGraphAsymmErrors(nbins+1);
ce4c4d27	107	gFcCorrConservative->SetNameTitle("gFcCorrConservative","Combined prompt fraction");
066998f0	108	TGraphAsymmErrors * gSigmaCorrConservative = new TGraphAsymmErrors(nbins+1);
ce4c4d27	109	gSigmaCorrConservative->SetNameTitle("gSigmaCorrConservative","Cross section (combined prompt fraction)");
066998f0	110	TGraphAsymmErrors * gSigmaCorrConservativePC = new TGraphAsymmErrors(nbins+1);
	111	gSigmaCorrConservativePC->SetNameTitle("gSigmaCorrConservativePC","Conservative gSigmaCorr (combined fc and Nb MC FD) in percentages [for drawing with AliHFSystErr]");
	112
	113	//
	114	// Call the systematics uncertainty class for a given decay
	115	// will help to compute the systematical unc. (but FD)
6ad825bf	116	AliHFSystErr systematics;
066c6b9b	117	if( centrality==kpp276 ) {
	118	systematics.SetIsLowEnergy(true);
	119	} else if( centrality!=kpp7 ) {
6ad825bf	120	systematics.SetCollisionType(1);
6ad825bf	121	if ( centrality == k020 ) {
066c6b9b	122	systematics.SetCentrality("020");
6ad825bf	123	}
6ad825bf	124	else if ( centrality == k4080 ) {
066c6b9b	125	systematics.SetCentrality("4080");
6ad825bf	126	}
	127	else {
	128	cout << " Systematics not yet implemented " << endl;
	129	return;
	130	}
	131	}
	132	else { systematics.SetCollisionType(0); }
	133	systematics.Init(decay);
066998f0	134
	135	//
	136	// Loop on all the bins to do the calculations
	137	//
	138	Double_t pt=0., average = 0., averageStatUnc=0., avErrx=0., avErryl=0., avErryh=0., avErryfdl=0., avErryfdh=0.;
	139	Double_t avErrylPC=0., avErryhPC=0., avErryfdlPC=0., avErryfdhPC=0.;
	140	Double_t valFc = 0., valFcErrstat=0., valFcErrx=0., valFcErryl=0., valFcErryh=0., valFcErryfdl=0., valFcErryfdh=0.;
	141	Double_t valNb = 0., valNbErrstat=0., valNbErrx=0., valNbErryl=0., valNbErryh=0., valNbErryfdl=0., valNbErryfdh=0.;
ce4c4d27	142	Double_t corrfd = 0., corrfdl=0., corrfdh=0.;
066998f0	143	//
	144	for(Int_t ibin=1; ibin<=nbins; ibin++){
	145
	146	// Get input values from fc method
	147	valFc = histoSigmaCorrFc->GetBinContent(ibin);
	148	pt = histoSigmaCorrFc->GetBinCenter(ibin);
	149	valFcErrstat = histoSigmaCorrFc->GetBinError(ibin);
	150	Double_t value =0., ptt=0.;
	151	gSigmaCorrConservativeFc->GetPoint(ibin,ptt,value);
066c6b9b	152	if (value<=0.) continue;
066998f0	153	if ( TMath::Abs(valFc-value)>0.1 \|\| TMath::Abs(pt-ptt)>0.1 )
	154	cout << "Hey you ! There might be a problem with the fc input file, please, have a look !" << endl;
	155	valFcErrx = gSigmaCorrFc->GetErrorXlow(ibin);
	156	valFcErryl = gSigmaCorrFc->GetErrorYlow(ibin);
	157	valFcErryh = gSigmaCorrFc->GetErrorYhigh(ibin);
	158	valFcErryfdl = TMath::Abs( gSigmaCorrConservativeFc->GetErrorYlow(ibin) );
	159	valFcErryfdh = TMath::Abs( gSigmaCorrConservativeFc->GetErrorYhigh(ibin) );
ce4c4d27	160	Double_t valfdFc = 0., x=0.;
	161	gFcConservativeFc->GetPoint(ibin,x,valfdFc);
	162	Double_t valfdFch = gFcConservativeFc->GetErrorYhigh(ibin);
	163	Double_t valfdFcl = gFcConservativeFc->GetErrorYlow(ibin);
066998f0	164
	165	// Get input values from Nb method
	166	valNb = histoSigmaCorrNb->GetBinContent(ibin);
	167	pt = histoSigmaCorrNb->GetBinCenter(ibin);
	168	valNbErrstat = histoSigmaCorrNb->GetBinError(ibin);
	169	gSigmaCorrConservativeNb->GetPoint(ibin,ptt,value);
	170	if ( TMath::Abs(valNb-value)>0.1 \|\| TMath::Abs(pt-ptt)>0.1 )
	171	cout << "Hey you ! There might be a problem with the Nb input file, please, have a look !" << endl;
	172	valNbErrx = gSigmaCorrNb->GetErrorXlow(ibin);
	173	valNbErryl = gSigmaCorrNb->GetErrorYlow(ibin);
	174	valNbErryh = gSigmaCorrNb->GetErrorYhigh(ibin);
	175	valNbErryfdl = gSigmaCorrConservativeNb->GetErrorYlow(ibin);
	176	valNbErryfdh = gSigmaCorrConservativeNb->GetErrorYhigh(ibin);
ce4c4d27	177	Double_t valfdNb = 0.;
	178	gFcConservativeNb->GetPoint(ibin,x,valfdNb);
	179	Double_t valfdNbh = gFcConservativeNb->GetErrorYhigh(ibin);
	180	Double_t valfdNbl = gFcConservativeNb->GetErrorYlow(ibin);
066998f0	181
	182
	183	// Compute the FD combined value
	184	// average = valNb
	185	average = valNb ;
ce4c4d27	186	corrfd = valfdNb;
066998f0	187	avErrx = valFcErrx;
	188	if ( TMath::Abs( valFcErrx - valNbErrx ) > 0.1 )
	189	cout << "Hey you ! There might be consistency problem with the fc & Nb input files, please, have a look !" << endl;
	190	averageStatUnc = valNbErrstat ;
	191	// cout << " pt=" << pt << ", average="<<average<<endl;
	192	// cout << " stat unc (pc)=" << averageStatUnc/average << ", stat-fc (pc)="<<(valFcErrstat/valFc) << ", stat-Nb (pc)="<<(valNbErrstat/valNb)<<endl;
	193
	194	// now estimate the new feed-down combined uncertainties
	195	Double_t minimum[2] = { (valFc - valFcErryfdl), (valNb - valNbErryfdl) };
	196	Double_t maximum[2] = { (valFc + valFcErryfdh), (valNb + valNbErryfdh) };
	197	avErryfdl = average - TMath::MinElement(2,minimum);
	198	avErryfdh = TMath::MaxElement(2,maximum) - average;
	199	avErryfdlPC = avErryfdl / average ; // in percentage
	200	avErryfdhPC = avErryfdh / average ; // in percentage
	201	// cout << " fc : val " << valFc << " + " << valFcErryfdh <<" - " << valFcErryfdl <<endl;
	202	// cout << " Nb : val " << valNb << " + " << valNbErryfdh <<" - " << valNbErryfdl <<endl;
	203	// cout << " fc & Nb: val " << average << " + " << avErryfdh <<" - " << avErryfdl <<endl;
ce4c4d27	204	Double_t minimumfc[2] = { (valfdNb - valfdNbl), (valfdFc - valfdFcl) };
	205	Double_t maximumfc[2] = { (valfdNb + valfdNbh), (valfdFc + valfdFch) };
	206	corrfdl = corrfd - TMath::MinElement(2,minimumfc);
	207	corrfdh = TMath::MaxElement(2,maximumfc) - corrfd;
066998f0	208
	209
	210	// compute the global systematics
	211	avErrylPC = systematics.GetTotalSystErr(pt,avErryfdlPC); // in percentage
	212	avErryhPC = systematics.GetTotalSystErr(pt,avErryfdhPC); // in percentage
	213	avErryl = avErrylPC * average ;
	214	avErryh = avErryhPC * average ;
	215	// cout << " syst av-l="<<avErryl<<", av-h="<<avErryh<<endl;
	216	// cout << " fd-l-pc="<<avErryfdlPC<<", fd-h-pc="<<avErryfdhPC<<", syst err(no fd)-pc="<<systematics.GetTotalSystErr(pt)<<", av-l-pc="<<avErrylPC<<", av-h-pc="<<avErryhPC<<endl;
	217
	218	// fill in the histos and TGraphs
	219	// fill them only when for non empty bins
	220	if ( average > 0.1 ) {
	221	histoSigmaCorr->SetBinContent(ibin,average);
	222	histoSigmaCorr->SetBinError(ibin,averageStatUnc);
	223	gSigmaCorr->SetPoint(ibin,pt,average);
	224	gSigmaCorr->SetPointError(ibin,valFcErrx,valFcErrx,avErryl,avErryh);
	225	gSigmaCorrConservative->SetPoint(ibin,pt,average);
	226	gSigmaCorrConservative->SetPointError(ibin,valFcErrx,valFcErrx,avErryfdl,avErryfdh);
	227	gSigmaCorrConservativePC->SetPoint(ibin,pt,0.);
	228	gSigmaCorrConservativePC->SetPointError(ibin,valFcErrx,valFcErrx,avErryfdlPC,avErryfdhPC);
ce4c4d27	229	gFcCorrConservative->SetPoint(ibin,pt,corrfd);
ce4c4d27	230	gFcCorrConservative->SetPointError(ibin,valFcErrx,valFcErrx,corrfdl,corrfdh);
066998f0	231	}
	232
	233	}
	234
	235
	236	gROOT->SetStyle("Plain");
	237	gStyle->SetOptTitle(0);
	238
	239	//
	240	// Plot the results
ce4c4d27	241	TH2F *histo2Draw = new TH2F("histo2Draw","histo2 (for drawing)",100,0,20.,100,1e3,5e7);
066998f0	242	histo2Draw->SetStats(0);
	243	histo2Draw->GetXaxis()->SetTitle("p_{T} [GeV]");
	244	histo2Draw->GetXaxis()->SetTitleSize(0.05);
	245	histo2Draw->GetXaxis()->SetTitleOffset(0.95);
	246	histo2Draw->GetYaxis()->SetTitle("#frac{1}{BR} #times #frac{d#sigma}{dp_{T}} \|_{\|y\|<0.5}");
	247	histo2Draw->GetYaxis()->SetTitleSize(0.05);
	248	//
	249	TCanvas *combinefdunc = new TCanvas("combinefdunc","show the FD results combination");
	250	//
	251	histo2Draw->Draw();
	252	//
	253	histoSigmaCorrFc->SetMarkerStyle(20);
	254	histoSigmaCorrFc->SetMarkerColor(kGreen+2);
	255	histoSigmaCorrFc->SetLineColor(kGreen+2);
	256	histoSigmaCorrFc->Draw("esame");
	257	gSigmaCorrConservativeFc->SetMarkerStyle(20);
	258	gSigmaCorrConservativeFc->SetMarkerColor(kGreen+2);
	259	gSigmaCorrConservativeFc->SetLineColor(kGreen+2);
ce4c4d27	260	gSigmaCorrConservativeFc->SetFillStyle(3004);//2);
066998f0	261	gSigmaCorrConservativeFc->SetFillColor(kGreen);
	262	gSigmaCorrConservativeFc->Draw("2[]same");
	263	//
	264	histoSigmaCorrNb->SetMarkerStyle(25);
	265	histoSigmaCorrNb->SetMarkerColor(kViolet+5);
	266	histoSigmaCorrNb->SetLineColor(kViolet+5);
	267	histoSigmaCorrNb->Draw("esame");
	268	gSigmaCorrConservativeNb->SetMarkerStyle(25);
ce4c4d27	269	gSigmaCorrConservativeNb->SetMarkerColor(kOrange+7);//kViolet+5);
	270	gSigmaCorrConservativeNb->SetLineColor(kOrange+7);//kOrange+7);//kViolet+5);
	271	gSigmaCorrConservativeNb->SetFillStyle(3018);//02);
066998f0	272	gSigmaCorrConservativeNb->SetFillColor(kMagenta);
	273	gSigmaCorrConservativeNb->Draw("2[]same");
	274	//
	275	gSigmaCorrConservative->SetLineColor(kRed);
ce4c4d27	276	gSigmaCorrConservative->SetLineWidth(2);
066998f0	277	gSigmaCorrConservative->SetFillColor(kRed);
	278	gSigmaCorrConservative->SetFillStyle(0);
	279	gSigmaCorrConservative->Draw("2");
	280	histoSigmaCorr->SetMarkerColor(kRed);
	281	histoSigmaCorr->Draw("esame");
	282	//
ce4c4d27	283	//
	284	TLegend* leg=combinefdunc->BuildLegend();
	285	leg->SetFillStyle(0);
066998f0	286	combinefdunc->SetLogy();
	287	combinefdunc->Update();
	288
ce4c4d27	289	TCanvas *combinefcunc = new TCanvas("combinefcunc","show the fc FD results combination");
	290	//
	291	TH2F *histo3Draw = new TH2F("histo3Draw","histo3 (for drawing)",100,0,20.,10,0.,1.);
	292	histo3Draw->SetStats(0);
	293	histo3Draw->GetXaxis()->SetTitle("p_{T} [GeV]");
	294	histo3Draw->GetXaxis()->SetTitleSize(0.05);
	295	histo3Draw->GetXaxis()->SetTitleOffset(0.95);
	296	histo3Draw->GetYaxis()->SetTitle("Prompt fraction of the raw yields");
	297	histo3Draw->GetYaxis()->SetTitleSize(0.05);
	298	histo3Draw->Draw();
	299	//
	300	gFcConservativeFc->SetMarkerStyle(20);
	301	gFcConservativeFc->SetMarkerColor(kGreen+2);
	302	gFcConservativeFc->SetLineColor(kGreen+2);
	303	gFcConservativeFc->SetFillStyle(3004);
	304	gFcConservativeFc->SetFillColor(kGreen);
	305	gFcConservativeFc->Draw("2P");
	306	//
	307	gFcConservativeNb ->SetMarkerStyle(25);
	308	gFcConservativeNb ->SetMarkerSize(1.3);
	309	gFcConservativeNb->SetMarkerColor(kOrange+7);//kViolet+5);
	310	gFcConservativeNb->SetLineColor(kOrange+7);//kViolet+5);
	311	gFcConservativeNb->SetFillStyle(3018);
	312	gFcConservativeNb->SetFillColor(kMagenta);
	313	gFcConservativeNb->Draw("2P");
	314	//
	315	gFcCorrConservative->SetMarkerStyle(21);
	316	gFcCorrConservative->SetLineColor(kRed);
	317	gFcCorrConservative->SetLineWidth(2);
	318	gFcCorrConservative->SetFillColor(kRed);
	319	gFcCorrConservative->SetFillStyle(0);
	320	gFcCorrConservative->Draw("2P");
	321	//
	322	leg=combinefcunc->BuildLegend();
	323	leg->SetFillStyle(0);
	324	//
	325	combinefcunc->Update();
	326
066998f0	327	//
	328	// Plot the results
	329	TCanvas *finalresults = new TCanvas("finalresults","show all combined results");
	330	//
	331	if ( decay==1 ) {
	332	thD0KpifromBprediction->SetLineColor(kGreen+2);
	333	thD0KpifromBprediction->SetLineWidth(3);
	334	thD0KpifromBprediction->SetFillColor(kGreen-6);
	335	thD0KpifromBprediction->Draw("3CA");
	336	thD0KpifromBprediction->Draw("CX");
	337	}
	338	else if ( decay==2 ) {
	339	thDpluskpipiprediction->SetLineColor(kGreen+2);
	340	thDpluskpipiprediction->SetLineWidth(3);
	341	thDpluskpipiprediction->SetFillColor(kGreen-6);
	342	thDpluskpipiprediction->Draw("3CA");
	343	thDpluskpipiprediction->Draw("CX");
	344	}
	345	else if ( decay==3 ) {
	346	thDstarD0piprediction->SetLineColor(kGreen+2);
	347	thDstarD0piprediction->SetLineWidth(3);
	348	thDstarD0piprediction->SetFillColor(kGreen-6);
	349	thDstarD0piprediction->Draw("3CA");
	350	thDstarD0piprediction->Draw("CX");
	351	}
	352	//
	353	gSigmaCorr->SetLineColor(kRed);
	354	gSigmaCorr->SetLineWidth(1);
	355	gSigmaCorr->SetFillColor(kRed);
	356	gSigmaCorr->SetFillStyle(0);
	357	gSigmaCorr->Draw("2");
	358	histoSigmaCorr->SetMarkerStyle(21);
	359	histoSigmaCorr->SetMarkerColor(kRed);
	360	histoSigmaCorr->Draw("esame");
	361	//
ce4c4d27	362	leg = new TLegend(0.7,0.75,0.87,0.5);
066998f0	363	leg->SetBorderSize(0);
	364	leg->SetLineColor(0);
	365	leg->SetFillColor(0);
	366	leg->SetTextFont(42);
	367	if ( decay==1 ) leg->AddEntry(thD0KpifromBprediction,"FONLL ","fl");
	368	else if ( decay==2 ) leg->AddEntry(thDpluskpipiprediction,"FONLL ","fl");
	369	else if ( decay==3 ) leg->AddEntry(thDstarD0piprediction,"FONLL ","fl");
	370	leg->AddEntry(histoSigmaCorr,"data stat. unc.","pl");
	371	leg->AddEntry(gSigmaCorr,"data syst. unc.","f");
	372	leg->Draw();
	373	//
	374	finalresults->SetLogy();
	375	finalresults->Update();
	376
	377
	378	//
	379	// Draw all the systematics independently
	380	systematics.DrawErrors(gSigmaCorrConservativePC);
	381
	382
	383	// Write the output to a file
	384	TFile * out = new TFile(outfilename,"recreate");
	385	histoSigmaCorr->Write();
	386	gSigmaCorr->Write();
	387	gSigmaCorrConservative->Write();
	388	gSigmaCorrConservativePC->Write();
ce4c4d27	389	gFcCorrConservative->Write();
066998f0	390	out->Write();
	391
	392	}