adding selector that creates histograms needed for systematic uncertainty

[u/mrichter/AliRoot.git] / PWG0 / esdTrackCuts / AliESDtrackCuts.cxx

#include "AliESDtrackCuts.h"


#include <AliESDtrack.h>
#include <AliESD.h>
#include <AliLog.h>

//____________________________________________________________________
ClassImp(AliESDtrackCuts)

// Cut names
const Char_t* AliESDtrackCuts::fgkCutNames[kNCuts] = {
 "require TPC refit",
 "require ITS refit",
 "n clusters TPC",
 "n clusters ITS",
 "#Chi^{2}/clusters TPC",
 "#Chi^{2}/clusters ITS",
 "cov 11",
 "cov 22",
 "cov 33",
 "cov 44",
 "cov 55",
 "trk-to-vtx",
 "trk-to-vtx failed",
 "kink daughters",

 "p",
 "p_{T}",
 "p_{x}",
 "p_{y}",
 "p_{z}",
 "y",
 "eta"
};

//____________________________________________________________________
AliESDtrackCuts::AliESDtrackCuts()
{
  //
  // constructor
  //

  Init();

  //##############################################################################
  // setting default cuts
  SetMinNClustersTPC();
  SetMinNClustersITS();
  SetMaxChi2PerClusterTPC();
  SetMaxChi2PerClusterITS();  				    
  SetMaxCovDiagonalElements();  				    
  SetRequireTPCRefit();
  SetRequireITSRefit();
  SetAcceptKingDaughters();
  SetMinNsigmaToVertex();
  SetRequireSigmaToVertex();
  SetPRange();
  SetPtRange();
  SetPxRange();
  SetPyRange();
  SetPzRange();
  SetEtaRange();
  SetRapRange();

  SetHistogramsOn();
}

//_____________________________________________________________________________
AliESDtrackCuts::AliESDtrackCuts(const AliESDtrackCuts &c) : TObject(c)
{
  //
  // copy constructor
  //

  ((AliESDtrackCuts &) c).Copy(*this);
}

AliESDtrackCuts::~AliESDtrackCuts()
{
  //
  // destructor
  //

  // ## TODO to be implemented
}

void AliESDtrackCuts::Init()
{
  //
  // sets everything to zero
  //

  fCutMinNClusterTPC = 0;
  fCutMinNClusterITS = 0;

  fCutMaxChi2PerClusterTPC = 0;
  fCutMaxChi2PerClusterITS = 0;

  fCutMaxC11 = 0;
  fCutMaxC22 = 0;
  fCutMaxC33 = 0;
  fCutMaxC44 = 0;
  fCutMaxC55 = 0;

  fCutAcceptKinkDaughters = 0;
  fCutRequireTPCRefit = 0;
  fCutRequireITSRefit = 0;

  fCutNsigmaToVertex = 0;
  fCutSigmaToVertexRequired = 0;

  fPMin = 0;
  fPMax = 0;
  fPtMin = 0;
  fPtMax = 0;
  fPxMin = 0;
  fPxMax = 0;
  fPyMin = 0;
  fPyMax = 0;
  fPzMin = 0;
  fPzMax = 0;
  fEtaMin = 0;
  fEtaMax = 0;
  fRapMin = 0;
  fRapMax = 0;

  fHistogramsOn = kFALSE;

  for (Int_t i=0; i<2; ++i)
  {
    fhNClustersITS[i] = 0;
    fhNClustersTPC[i] = 0;

    fhChi2PerClusterITS[i] = 0;
    fhChi2PerClusterTPC[i] = 0;

    fhC11[i] = 0;
    fhC22[i] = 0;
    fhC33[i] = 0;
    fhC44[i] = 0;
    fhC55[i] = 0;

    fhDXY[i] = 0;
    fhDZ[i] = 0;
    fhDXYvsDZ[i] = 0;

    fhDXYNormalized[i] = 0;
    fhDZNormalized[i] = 0;
    fhDXYvsDZNormalized[i] = 0;
  }

  fhCutStatistics = 0;
  fhCutCorrelation = 0;
}

//_____________________________________________________________________________
AliESDtrackCuts &AliESDtrackCuts::operator=(const AliESDtrackCuts &c)
{
  //
  // Assignment operator
  //

  if (this != &c) ((AliESDtrackCuts &) c).Copy(*this);
  return *this;
}

//_____________________________________________________________________________
void AliESDtrackCuts::Copy(TObject &c) const
{
  //
  // Copy function
  //

  AliESDtrackCuts& target = (AliESDtrackCuts &) c;

  target.Init();

  target.fCutMinNClusterTPC = fCutMinNClusterTPC;
  target.fCutMinNClusterITS = fCutMinNClusterITS;

  target.fCutMaxChi2PerClusterTPC = fCutMaxChi2PerClusterTPC;
  target.fCutMaxChi2PerClusterITS = fCutMaxChi2PerClusterITS;

  target.fCutMaxC11 = fCutMaxC11;
  target.fCutMaxC22 = fCutMaxC22;
  target.fCutMaxC33 = fCutMaxC33;
  target.fCutMaxC44 = fCutMaxC44;
  target.fCutMaxC55 = fCutMaxC55;

  target.fCutAcceptKinkDaughters = fCutAcceptKinkDaughters;
  target.fCutRequireTPCRefit = fCutRequireTPCRefit;
  target.fCutRequireITSRefit = fCutRequireITSRefit;

  target.fCutNsigmaToVertex = fCutNsigmaToVertex;
  target.fCutSigmaToVertexRequired = fCutSigmaToVertexRequired;

  target.fPMin = fPMin;
  target.fPMax = fPMax;
  target.fPtMin = fPtMin;
  target.fPtMax = fPtMax;
  target.fPxMin = fPxMin;
  target.fPxMax = fPxMax;
  target.fPyMin = fPyMin;
  target.fPyMax = fPyMax;
  target.fPzMin = fPzMin;
  target.fPzMax = fPzMax;
  target.fEtaMin = fEtaMin;
  target.fEtaMax = fEtaMax;
  target.fRapMin = fRapMin;
  target.fRapMax = fRapMax;

  target.fHistogramsOn = fHistogramsOn;

  for (Int_t i=0; i<2; ++i)
  {
    if (fhNClustersITS[i]) target.fhNClustersITS[i] = (TH1F*) fhNClustersITS[i]->Clone();
    if (fhNClustersTPC[i]) target.fhNClustersTPC[i] = (TH1F*) fhNClustersTPC[i]->Clone();

    if (fhChi2PerClusterITS[i]) target.fhChi2PerClusterITS[i] = (TH1F*) fhChi2PerClusterITS[i]->Clone();
    if (fhChi2PerClusterTPC[i]) target.fhChi2PerClusterTPC[i] = (TH1F*) fhChi2PerClusterTPC[i]->Clone();

    if (fhC11[i]) target.fhC11[i] = (TH1F*) fhC11[i]->Clone();
    if (fhC22[i]) target.fhC22[i] = (TH1F*) fhC22[i]->Clone();
    if (fhC33[i]) target.fhC33[i] = (TH1F*) fhC33[i]->Clone();
    if (fhC44[i]) target.fhC44[i] = (TH1F*) fhC44[i]->Clone();
    if (fhC55[i]) target.fhC55[i] = (TH1F*) fhC55[i]->Clone();

    if (fhDXY[i]) target.fhDXY[i] = (TH1F*) fhDXY[i]->Clone();
    if (fhDZ[i]) target.fhDZ[i] = (TH1F*) fhDZ[i]->Clone();
    if (fhDXYvsDZ[i]) target.fhDXYvsDZ[i] = (TH2F*) fhDXYvsDZ[i]->Clone();

    if (fhDXYNormalized[i]) target.fhDXYNormalized[i] = (TH1F*) fhDXYNormalized[i]->Clone();
    if (fhDZNormalized[i]) target.fhDZNormalized[i] = (TH1F*) fhDZNormalized[i]->Clone();
    if (fhDXYvsDZNormalized[i]) target.fhDXYvsDZNormalized[i] = (TH2F*) fhDXYvsDZNormalized[i]->Clone();
  }

  if (fhCutStatistics) target.fhCutStatistics = (TH1F*) fhCutStatistics->Clone();
  if (fhCutCorrelation) target.fhCutCorrelation = (TH2F*) fhCutCorrelation->Clone();

  TObject::Copy(c);
}

//____________________________________________________________________
Bool_t 
AliESDtrackCuts::AcceptTrack(AliESDtrack* esdTrack) {
  // 
  // figure out if the tracks survives all the track cuts defined
  //
  // the different quality parameter and kinematic values are first
  // retrieved from the track. then it is found out what cuts the
  // track did not survive and finally the cuts are imposed.



  UInt_t status = esdTrack->GetStatus();

  // dummy array
  Int_t  fIdxInt[200];

  // getting quality parameters from the ESD track
  Int_t nClustersITS = esdTrack->GetITSclusters(fIdxInt);
  Int_t nClustersTPC = esdTrack->GetTPCclusters(fIdxInt);
  


  Float_t chi2PerClusterITS = -1;
  Float_t chi2PerClusterTPC = -1;
  if (nClustersITS!=0)
    chi2PerClusterITS = esdTrack->GetITSchi2()/Float_t(nClustersITS);
  if (nClustersTPC!=0)
    chi2PerClusterTPC = esdTrack->GetTPCchi2()/Float_t(nClustersTPC);  

  Double_t extCov[15];
  esdTrack->GetExternalCovariance(extCov);

  // getting the track to vertex parameters
  Float_t b[2];
  Float_t bRes[2];
  Float_t bCov[3];
  esdTrack->GetImpactParameters(b,bCov);    
  if (bCov[0]<=0 || bCov[2]<=0) {
    AliDebug(1, "Estimated b resolution lower or equal zero!");
    bCov[0]=0; bCov[2]=0;
  } 
  bRes[0] = TMath::Sqrt(bCov[0]);
  bRes[1] = TMath::Sqrt(bCov[2]);

  // -----------------------------------
  // How to get to a n-sigma cut?
  //
  // The accumulated statistics from 0 to d is
  //
  // ->  Erf(d/Sqrt(2)) for a 1-dim gauss (d = n_sigma)
  // ->  1 - Exp(-d**2) for a 2-dim gauss (d*d = dx*dx + dy*dy != n_sigma)
  //
  // It means that for a 2-dim gauss: n_sigma(d) = Sqrt(2)*ErfInv(1 - Exp((-x**2)/2)
  // Can this be expressed in a different way?
  //
  //
  // FIX: I don't think this is correct!!! Keeping d as n_sigma for now...

  Float_t nSigmaToVertex = -1;
  if (bRes[0]!=0 && bRes[1]!=0) {
    Float_t d = TMath::Sqrt(TMath::Power(b[0]/bRes[0],2) + TMath::Power(b[1]/bRes[1],2));
    nSigmaToVertex = d;

    // JF solution:
    //nSigmaToVertex = TMath::ErfInverse(TMath::Sqrt(2.0/TMath::Pi()) * TMath::Erf(d / TMath::Sqrt(2))) * TMath::Sqrt(2);
    // Claus solution:
    //nSigmaToVertex = TMath::Sqrt(2)*(TMath::ErfInverse(1 - TMath::Exp(0.5*(-d*d))));
  }

  // getting the kinematic variables of the track 
  // (assuming the mass is known)
  Double_t p[3];
  esdTrack->GetPxPyPz(p);
  Float_t momentum = TMath::Sqrt(TMath::Power(p[0],2) + TMath::Power(p[1],2) + TMath::Power(p[2],2));
  Float_t pt       = TMath::Sqrt(TMath::Power(p[0],2) + TMath::Power(p[1],2));
  Float_t energy   = TMath::Sqrt(TMath::Power(esdTrack->GetMass(),2) + TMath::Power(momentum,2));


  //y-eta related calculations
  Float_t eta = -100.;
  Float_t y   = -100.;
  if((momentum != TMath::Abs(p[2]))&&(momentum != 0))
    eta = 0.5*TMath::Log((momentum + p[2])/(momentum - p[2]));
  if((energy != TMath::Abs(p[2]))&&(momentum != 0))
    y = 0.5*TMath::Log((energy + p[2])/(energy - p[2]));

  
  //########################################################################
  // cut the track?
  
  Bool_t cuts[kNCuts];
  for (Int_t i=0; i<kNCuts; i++) cuts[i]=kFALSE;
  
  // track quality cuts
  if (fCutRequireTPCRefit && (status&AliESDtrack::kTPCrefit)==0)
    cuts[0]=kTRUE;
  if (fCutRequireITSRefit && (status&AliESDtrack::kITSrefit)==0)
    cuts[1]=kTRUE;
  if (nClustersTPC<fCutMinNClusterTPC) 
    cuts[2]=kTRUE;
  if (nClustersITS<fCutMinNClusterITS) 
    cuts[3]=kTRUE;
  if (chi2PerClusterTPC>fCutMaxChi2PerClusterTPC) 
    cuts[4]=kTRUE; 
  if (chi2PerClusterITS>fCutMaxChi2PerClusterITS) 
    cuts[5]=kTRUE;
  if (extCov[0]  > fCutMaxC11) 
    cuts[6]=kTRUE;  
  if (extCov[2]  > fCutMaxC22) 
    cuts[7]=kTRUE;  
  if (extCov[5]  > fCutMaxC33) 
    cuts[8]=kTRUE;  
  if (extCov[9]  > fCutMaxC44) 
    cuts[9]=kTRUE;  
  if (extCov[14]  > fCutMaxC55) 
    cuts[10]=kTRUE;  
  if (nSigmaToVertex > fCutNsigmaToVertex) 
    cuts[11] = kTRUE;
  // if n sigma could not be calculated
  if (nSigmaToVertex<0 && fCutSigmaToVertexRequired)
    cuts[12]=kTRUE;
  if (!fCutAcceptKinkDaughters && esdTrack->GetKinkIndex(0)>0) 
    cuts[13]=kTRUE;
  // track kinematics cut
  if((momentum < fPMin) || (momentum > fPMax)) 
    cuts[14]=kTRUE;
  if((pt < fPtMin) || (pt > fPtMax)) 
    cuts[15] = kTRUE;
  if((p[0] < fPxMin) || (p[0] > fPxMax)) 
    cuts[16] = kTRUE;
  if((p[1] < fPyMin) || (p[1] > fPyMax)) 
    cuts[17] = kTRUE;
  if((p[2] < fPzMin) || (p[2] > fPzMax)) 
    cuts[18] = kTRUE;
  if((eta < fEtaMin) || (eta > fEtaMax)) 
    cuts[19] = kTRUE;
  if((y < fRapMin) || (y > fRapMax)) 
    cuts[20] = kTRUE;

  Bool_t cut=kFALSE;
  for (Int_t i=0; i<kNCuts; i++) 
    if (cuts[i]) cut = kTRUE;
  
  //########################################################################
  // filling histograms
  if (fHistogramsOn) {
    fhCutStatistics->Fill(fhCutStatistics->GetBinCenter(fhCutStatistics->GetXaxis()->FindBin("n tracks")));
    
    if (cut)
      fhCutStatistics->Fill(fhCutStatistics->GetBinCenter(fhCutStatistics->GetXaxis()->FindBin("n cut tracks")));
    
    for (Int_t i=0; i<kNCuts; i++) {
      if (cuts[i])
 	fhCutStatistics->Fill(fhCutStatistics->GetBinCenter(fhCutStatistics->GetXaxis()->FindBin(fgkCutNames[i])));
      
      for (Int_t j=i; j<kNCuts; j++) {
 	if (cuts[i] && cuts[j]) {
 	  Float_t x = fhCutCorrelation->GetXaxis()->GetBinCenter(fhCutCorrelation->GetXaxis()->FindBin(fgkCutNames[i]));
 	  Float_t y = fhCutCorrelation->GetYaxis()->GetBinCenter(fhCutCorrelation->GetYaxis()->FindBin(fgkCutNames[j]));
 	  fhCutCorrelation->Fill(x,y);
 	}
      }
    }
    

    fhNClustersITS[0]->Fill(nClustersITS);        
    fhNClustersTPC[0]->Fill(nClustersTPC);        
    fhChi2PerClusterITS[0]->Fill(chi2PerClusterITS);
    fhChi2PerClusterTPC[0]->Fill(chi2PerClusterTPC);   
    
    fhC11[0]->Fill(extCov[0]);                 
    fhC22[0]->Fill(extCov[2]);                 
    fhC33[0]->Fill(extCov[5]);                 
    fhC44[0]->Fill(extCov[9]);                                  
    fhC55[0]->Fill(extCov[14]);                                  
    
    fhDZ[0]->Fill(b[1]);     
    fhDXY[0]->Fill(b[0]);    
    fhDXYvsDZ[0]->Fill(b[1],b[0]);

    if (bRes[0]!=0 && bRes[1]!=0) {
      fhDZNormalized[0]->Fill(b[1]/bRes[1]);
      fhDXYNormalized[0]->Fill(b[0]/bRes[0]);    
      fhDXYvsDZNormalized[0]->Fill(b[1]/bRes[1], b[0]/bRes[0]);
    }
  }

  //########################################################################  
  // cut the track!
  if (cut) return kFALSE;

  //########################################################################  
  // filling histograms after cut
  if (fHistogramsOn) {
    fhNClustersITS[1]->Fill(nClustersITS);        
    fhNClustersTPC[1]->Fill(nClustersTPC);        
    fhChi2PerClusterITS[1]->Fill(chi2PerClusterITS);
    fhChi2PerClusterTPC[1]->Fill(chi2PerClusterTPC);   
    
    fhC11[1]->Fill(extCov[0]);                 
    fhC22[1]->Fill(extCov[2]);                 
    fhC33[1]->Fill(extCov[5]);
    fhC44[1]->Fill(extCov[9]);                                  
    fhC55[1]->Fill(extCov[14]);                                  
    
    fhDZ[1]->Fill(b[1]);     
    fhDXY[1]->Fill(b[0]);    
    fhDXYvsDZ[1]->Fill(b[1],b[0]);

    if (bRes[0]!=0 && bRes[1]!=0)
    {
      fhDZNormalized[1]->Fill(b[1]/bRes[1]);
      fhDXYNormalized[1]->Fill(b[0]/bRes[0]);
      fhDXYvsDZNormalized[1]->Fill(b[1]/bRes[1], b[0]/bRes[0]);
    }
  }
  
  return kTRUE;
}

//____________________________________________________________________
TObjArray*
AliESDtrackCuts::GetAcceptedTracks(AliESD* esd)
{
  //
  // returns an array of all tracks that pass the cuts
  //

  TObjArray* acceptedTracks = new TObjArray();

  // loop over esd tracks
  for (Int_t iTrack = 0; iTrack < esd->GetNumberOfTracks(); iTrack++) {
    AliESDtrack* track = esd->GetTrack(iTrack);

    if (AcceptTrack(track))
      acceptedTracks->Add(track);
  }

  return acceptedTracks;
}

//____________________________________________________________________
Int_t
AliESDtrackCuts::CountAcceptedTracks(AliESD* esd)
{
  //
  // returns an the number of tracks that pass the cuts
  //

  Int_t count = 0;

  // loop over esd tracks
  for (Int_t iTrack = 0; iTrack < esd->GetNumberOfTracks(); iTrack++) {
    AliESDtrack* track = esd->GetTrack(iTrack);

    if (AcceptTrack(track))
      count++;
  }

  return count;
}

//____________________________________________________________________
 void AliESDtrackCuts::DefineHistograms(Int_t color) {
   // 
   // diagnostics histograms are defined
   // 

   fHistogramsOn=kTRUE;

   //###################################################################################
   // defining histograms

   fhCutStatistics = new TH1F("cut_statistics","cut statistics",kNCuts+4,-0.5,kNCuts+3.5);

   fhCutStatistics->GetXaxis()->SetBinLabel(1,"n tracks");
   fhCutStatistics->GetXaxis()->SetBinLabel(2,"n cut tracks");

   fhCutCorrelation = new TH2F("cut_correlation","cut correlation",kNCuts,-0.5,kNCuts-0.5,kNCuts,-0.5,kNCuts-0.5);;
  
   for (Int_t i=0; i<kNCuts; i++) {
     fhCutStatistics->GetXaxis()->SetBinLabel(i+4,fgkCutNames[i]);
     fhCutCorrelation->GetXaxis()->SetBinLabel(i+1,fgkCutNames[i]);
     fhCutCorrelation->GetYaxis()->SetBinLabel(i+1,fgkCutNames[i]);
   } 

  fhCutStatistics  ->SetLineColor(color);
  fhCutCorrelation ->SetLineColor(color);
  fhCutStatistics  ->SetLineWidth(2);
  fhCutCorrelation ->SetLineWidth(2);

  Char_t str[256];
  for (Int_t i=0; i<2; i++) {
    if (i==0) sprintf(str," ");
    else sprintf(str,"_cut");

    fhNClustersITS[i]        = new TH1F(Form("nClustersITS%s",str),"",8,-0.5,7.5);
    fhNClustersTPC[i]        = new TH1F(Form("nClustersTPC%s",str),"",165,-0.5,164.5);
    fhChi2PerClusterITS[i]   = new TH1F(Form("chi2PerClusterITS%s",str),"",500,0,10);
    fhChi2PerClusterTPC[i]   = new TH1F(Form("chi2PerClusterTPC%s",str),"",500,0,10);

    fhC11[i]                 = new TH1F(Form("covMatrixDiagonal11%s",str),"",1000,0,5);
    fhC22[i]                 = new  TH1F(Form("covMatrixDiagonal22%s",str),"",1000,0,5);
    fhC33[i]                 = new  TH1F(Form("covMatrixDiagonal33%s",str),"",1000,0,0.5);
    fhC44[i]                 = new  TH1F(Form("covMatrixDiagonal44%s",str),"",1000,0,5);
    fhC55[i]                 = new  TH1F(Form("covMatrixDiagonal55%s",str),"",1000,0,5);

    fhDXY[i]                 = new  TH1F(Form("dXY%s",str),"",500,-10,10);
    fhDZ[i]                  = new  TH1F(Form("dZ%s",str),"",500,-10,10);
    fhDXYvsDZ[i]             = new  TH2F(Form("dXYvsDZ%s",str),"",200,-10,10,200,-10,10);

    fhDXYNormalized[i]       = new  TH1F(Form("dXYNormalized%s",str),"",500,-10,10);
    fhDZNormalized[i]        = new  TH1F(Form("dZNormalized%s",str),"",500,-10,10);
    fhDXYvsDZNormalized[i]   = new  TH2F(Form("dXYvsDZNormalized%s",str),"",200,-10,10,200,-10,10);


    fhNClustersITS[i]->SetXTitle("n ITS clusters");
    fhNClustersTPC[i]->SetXTitle("n TPC clusters");
    fhChi2PerClusterITS[i]->SetXTitle("#Chi^{2} per ITS cluster");
    fhChi2PerClusterTPC[i]->SetXTitle("#Chi^{2} per TPC cluster");

    fhC11[i]->SetXTitle("cov 11 : #sigma_{y}^{2} [cm^{2}]");
    fhC22[i]->SetXTitle("cov 22 : #sigma_{z}^{2} [cm^{2}]");
    fhC33[i]->SetXTitle("cov 33 : #sigma_{sin(#phi)}^{2}");
    fhC44[i]->SetXTitle("cov 44 : #sigma_{tan(#theta_{dip})}^{2}");
    fhC55[i]->SetXTitle("cov 55 : #sigma_{1/p_{T}}^{2} [(c/GeV)^2]");

    fhDXY[i]->SetXTitle("transverse impact parameter");
    fhDZ[i]->SetXTitle("longitudinal impact parameter");
    fhDXYvsDZ[i]->SetXTitle("longitudinal impact parameter");
    fhDXYvsDZ[i]->SetYTitle("transverse impact parameter");

    fhDXYNormalized[i]->SetXTitle("normalized trans impact par");
    fhDZNormalized[i]->SetXTitle("normalized long impact par");
    fhDXYvsDZNormalized[i]->SetXTitle("normalized long impact par"); 
    fhDXYvsDZNormalized[i]->SetYTitle("normalized trans impact par");

    fhNClustersITS[i]->SetLineColor(color);   fhNClustersITS[i]->SetLineWidth(2);
    fhNClustersTPC[i]->SetLineColor(color);   fhNClustersTPC[i]->SetLineWidth(2);
    fhChi2PerClusterITS[i]->SetLineColor(color);   fhChi2PerClusterITS[i]->SetLineWidth(2);
    fhChi2PerClusterTPC[i]->SetLineColor(color);   fhChi2PerClusterTPC[i]->SetLineWidth(2);

    fhC11[i]->SetLineColor(color);   fhC11[i]->SetLineWidth(2);
    fhC22[i]->SetLineColor(color);   fhC22[i]->SetLineWidth(2);
    fhC33[i]->SetLineColor(color);   fhC33[i]->SetLineWidth(2);
    fhC44[i]->SetLineColor(color);   fhC44[i]->SetLineWidth(2);
    fhC55[i]->SetLineColor(color);   fhC55[i]->SetLineWidth(2);

    fhDXY[i]->SetLineColor(color);   fhDXY[i]->SetLineWidth(2);
    fhDZ[i]->SetLineColor(color);   fhDZ[i]->SetLineWidth(2);

    fhDXYNormalized[i]->SetLineColor(color);   fhDXYNormalized[i]->SetLineWidth(2);
    fhDZNormalized[i]->SetLineColor(color);   fhDZNormalized[i]->SetLineWidth(2);
  }
}

//____________________________________________________________________
void 
AliESDtrackCuts::Print(const Option_t*) const {
  //
  // print method - still to be implemented
  //

  AliInfo("AliESDtrackCuts...");
}


//____________________________________________________________________
void AliESDtrackCuts::SaveHistograms(Char_t* dir) {
  // 
  // saves the histograms in a directory (dir)
  // 

  
  if (!fHistogramsOn) {
    AliDebug(0, "Histograms not on - cannot save histograms!!!");
    return;
  }

  gDirectory->mkdir(dir);
  gDirectory->cd(dir);

  gDirectory->mkdir("before_cuts");
  gDirectory->mkdir("after_cuts");
 
  fhCutStatistics->Write();
  fhCutCorrelation->Write();

  for (Int_t i=0; i<2; i++) {
    if (i==0)
      gDirectory->cd("before_cuts");
    else
      gDirectory->cd("after_cuts");
    
    fhNClustersITS[i]        ->Write();
    fhNClustersTPC[i]        ->Write();
    fhChi2PerClusterITS[i]   ->Write();
    fhChi2PerClusterTPC[i]   ->Write();
    
    fhC11[i]                 ->Write();
    fhC22[i]                 ->Write();
    fhC33[i]                 ->Write();
    fhC44[i]                 ->Write();
    fhC55[i]                 ->Write();

    fhDXY[i]                 ->Write();
    fhDZ[i]                  ->Write();
    fhDXYvsDZ[i]             ->Write();
    
    fhDXYNormalized[i]       ->Write();
    fhDZNormalized[i]        ->Write();
    fhDXYvsDZNormalized[i]   ->Write();

    gDirectory->cd("../");
  }

  gDirectory->cd("../");
}