//  **************************************************************************
//  * Copyright(c) 1998-1999, ALICE Experiment at CERN, All rights reserved. *
//  *                                                                        *
//  * Author: The ALICE Off-line Project.                                    *
//  * Contributors are mentioned in the code where appropriate.              *
//  *                                                                        *
//  * Permission to use, copy, modify and distribute this software and its   *
//  * documentation strictly for non-commercial purposes is hereby granted   *
//  * without fee, provided that the above copyright notice appears in all   *
//  * copies and that both the copyright notice and this permission notice   *
//  * appear in the supporting documentation. The authors make no claims     *
//  * about the suitability of this software for any purpose. It is          *
//  * provided "as is" without express or implied warranty.                  *
//  **************************************************************************

/* $Id$ */

//-----------------------------------------------------------------------------------
// Jet finder based on Deterministic Annealing
// For further informations about the DA working features see:
// Phys.Lett. B601 (2004) 56-63 (http://arxiv.org/abs/hep-ph/0407214)
// Author: Davide Perrino (davide.perrino@ba.infn.it, davide.perrino@cern.ch)
//         alexandre.shabetai@cern.ch (Modification of the input object (reader/finder splitting)) 
// ** 2011
// Modified accordingly to reader/finder splitting and new handling of neutral information   
//-----------------------------------------------------------------------------------

#include <TMath.h>
#include <TRandom2.h>

#include "AliAODJet.h"
#include "AliDAJetHeader.h"
#include "AliDAJetFinder.h"

ClassImp(AliDAJetFinder)

///////////////////////////////////////////////////////////////////////

AliDAJetFinder::AliDAJetFinder():
  AliJetFinder(),
  fAlpha(1.01),
  fDelta(1e-8),
  fAvDist(1e-6),
  fEps(1e-4),
  fEpsMax(1e-2),
  fNloopMax(100),
  fBeta(0.1),
  fNclustMax(0),
  fNin(0),
  fNeff(0)
{
  // Constructor
}

//-----------------------------------------------------------------------------------
AliDAJetFinder::~AliDAJetFinder()
{
  // Destructor
}

//-----------------------------------------------------------------------------------
void AliDAJetFinder::FindJets()  
{
  // Find the jets in current event
  //
  Float_t betaStop=100.;
  fDebug = fHeader->GetDebug();

  Double_t dEtSum=0;
  Double_t *xData[2];
  TVectorD *vPx = new TVectorD();
  TVectorD *vPy = new TVectorD();
  TMatrixD *mPyx= new TMatrixD();
  TMatrixD *mY  = new TMatrixD();
  InitDetAnn(dEtSum,xData,vPx,vPy,mPyx,mY);
  if (fNin < fNclustMax){
    delete [] xData[0], delete [] xData[1];
    delete vPx;
    delete vPy;
    delete mPyx;
    delete mY;
    return;
  }
  Int_t nc=1, nk;
  DoubleClusters(nc,nk,vPy,mY);
  do{					//loop over beta
    fBeta*=fAlpha;
    Annealing(nk,xData,vPx,vPy,mPyx,mY);
    NumCl(nc,nk,vPy,mPyx,mY);
  }while((fBeta<betaStop || nc<4) && nc<fNclustMax);

  Int_t *xx=new Int_t[fNeff];
  for (Int_t i = 0; i < fNeff; i++) xx[i] = 0;

  EndDetAnn(nk,xData,xx,dEtSum,vPx,vPy,mPyx,mY);
  StoreJets(nk,xData,xx,mY);
  delete [] xx;

  delete [] xData[0], delete [] xData[1];
  delete mPyx;
  delete mY;
  delete vPx;
  delete vPy;

}

//-----------------------------------------------------------------------------------
void AliDAJetFinder::InitDetAnn(Double_t &dEtSum,Double_t **xData,TVectorD *vPx,TVectorD *vPy,TMatrixD *mPyx,TMatrixD *mY)
{
  //Initialise the variables used by the algorithm
  fBeta=0.1;
  fNclustMax = ((AliDAJetHeader*)fHeader)->GetFixedCl() ?
    ((AliDAJetHeader*)fHeader)->GetNclustMax() :
    TMath::Max((Int_t)TMath::Sqrt(fNin),5);
  Float_t etaEff = ((AliDAJetHeader*)fHeader)->GetEtaEff();

  fNin=0;
  for (Int_t iTr=0; iTr<GetCalTrkEvent()->GetNCalTrkTracks(); iTr++) if (GetCalTrkEvent()->GetCalTrkTrack(iTr)->GetCutFlag()==1) fNin++;

  fNeff = ((AliDAJetHeader*)fHeader)->GetNeff();
  fNeff = TMath::Max(fNeff,fNin);
  Double_t *xEta = new Double_t[fNeff];
  Double_t *xPhi = new Double_t[fNeff];
  xData[0]=xEta; xData[1]=xPhi;
  vPx->ResizeTo(fNeff);
  Int_t iIn=0;

  for (Int_t iTr=0; iTr<GetCalTrkEvent()->GetNCalTrkTracks(); iTr++){
    AliJetCalTrkTrack* ctT = GetCalTrkEvent()->GetCalTrkTrack(iTr);
    if (ctT->GetCutFlag()==0) continue;
    xEta[iIn] = ctT->GetEta();
    xPhi[iIn] = ctT->GetPhi()<0 ? ctT->GetPhi() + 2*TMath::Pi() : ctT->GetPhi();
    (*vPx)(iIn)=ctT->GetPt();
    dEtSum+=(*vPx)(iIn);
    iIn++;
  }

  TRandom2 r;
  r.SetSeed(0);
  for (iIn=fNin; iIn<fNeff; iIn++){
    xEta[iIn]=r.Uniform(-1*etaEff,etaEff);
    xPhi[iIn]=r.Uniform(0.,2*TMath::Pi());
    (*vPx)(iIn)=r.Uniform(0.01,0.02);
    dEtSum+=(*vPx)(iIn);
  }
  for (iIn=0; iIn<fNeff; iIn++) (*vPx)(iIn)=(*vPx)(iIn)/dEtSum;

  Int_t njdim=2*fNclustMax+1;
  mPyx->ResizeTo(fNeff,njdim);
  mY->ResizeTo(4,njdim);
  vPy->ResizeTo(njdim);
  mY->Zero();mPyx->Zero();vPy->Zero();
  (*vPy)(0)=1;
  TMatrixDColumn(*mPyx,0)=1;
  Double_t ypos=0,xpos=0;
  for (iIn=0; iIn<fNeff; iIn++){
    (*mY)(0,0)+=(*vPx)(iIn)*xEta[iIn];
    ypos+=(*vPx)(iIn)*TMath::Sin(xPhi[iIn]);
    xpos+=(*vPx)(iIn)*TMath::Cos(xPhi[iIn]);
  }
  (*mY)(1,0)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2*TMath::Pi();

}

//-----------------------------------------------------------------------------------
void AliDAJetFinder::DoubleClusters(Int_t nc,Int_t &nk, TVectorD *vPy, TMatrixD *mY) const
{
  // Return double clusters
  for(Int_t iClust=0; iClust<nc; iClust++){
    (*vPy)(iClust)=(*vPy)(iClust)/2;
    (*vPy)(nc+iClust)=(*vPy)(iClust);
    for(Int_t iComp=0; iComp<3; iComp++) (*mY)(iComp,nc+iClust)=(*mY)(iComp,iClust);
  }
  nk=2*nc;

}

//-----------------------------------------------------------------------------------
void AliDAJetFinder::Annealing(Int_t nk,Double_t **xData,  const TVectorD *vPx,  TVectorD *vPy,  TMatrixD *mPyx,  TMatrixD *mY)
{
  // Main part of the algorithm
  const Double_t pi=TMath::Pi();
  TVectorD *py = new TVectorD(nk);
  TVectorD *p  = new TVectorD(nk);
  TMatrixD *y  = new TMatrixD(4,nk);
  TMatrixD *y1 = new TMatrixD(4,nk);
  TMatrixD *ry = new TMatrixD(2,nk);
  Double_t *xEta = xData[0];
  Double_t *xPhi = xData[1];
  Double_t Dist(TVectorD,TVectorD);

  Double_t df[2]={((AliDAJetHeader*)fHeader)->GetFiducialEtaMax(),pi};
  TVectorD vPart(2);
  Double_t *m = new Double_t[nk];
  Double_t chi,chi1;
  do{
    Int_t nloop=0;
    for (Int_t iClust=0; iClust<nk; iClust++){
      for (Int_t i=0; i<3; i++)(*y1)(i,iClust)=(*mY)(i,iClust);
      (*py)(iClust)=(*vPy)(iClust);
    }
    //perturbation of codevectors
    Double_t seed=1000000*gRandom->Rndm(24);
    ry->Randomize(-0.5,0.5,seed);
    for (Int_t i=0; i<2; i++){
      for (Int_t iClust=0; iClust<nk/2; iClust++)
	(*y1)(i,iClust)+=((*ry)(i,iClust)+TMath::Sign(0.5,(*ry)(i,iClust)))*fDelta*df[i];
      for (Int_t iClust=nk/2; iClust<nk; iClust++)
	(*y1)(i,iClust)-=((*ry)(i,iClust-nk/2)+TMath::Sign(0.5,(*ry)(i,iClust-nk/2)))*fDelta*df[i];
    }
    do{
      //recalculate conditional probabilities
      nloop++;
      for (Int_t iIn=0; iIn<fNeff; iIn++){
	vPart(0)=xEta[iIn]; vPart(1)=xPhi[iIn];
	for(Int_t iClust=0; iClust<nk; iClust++){
	  (*mPyx)(iIn,iClust)=-log((*py)(iClust))+fBeta*Dist(vPart,TMatrixDColumn(*y1,iClust));
	  m[iClust]=(*mPyx)(iIn,iClust);
	}
	Double_t pyxNorm=0;
	Double_t minPyx=TMath::MinElement(nk,m);
	for (Int_t iClust=0; iClust<nk; iClust++){
	  (*mPyx)(iIn,iClust)-=minPyx;
	  (*mPyx)(iIn,iClust)=exp(-(*mPyx)(iIn,iClust));
	  pyxNorm+=(*mPyx)(iIn,iClust);
	}
	for (Int_t iClust=0; iClust<nk; iClust++) (*mPyx)(iIn,iClust)/=pyxNorm;
      }
      p->Zero();
      y->Zero();
      //recalculate codevectors
      for (Int_t iClust=0; iClust<nk; iClust++){
	Double_t xpos=0,ypos=0,pxy;
	for (Int_t iIn=0; iIn<fNeff; iIn++) (*p)(iClust)+=(*vPx)(iIn)*(*mPyx)(iIn,iClust);
	for (Int_t iIn=0; iIn<fNeff; iIn++){
	  pxy=(*vPx)(iIn)*(*mPyx)(iIn,iClust)/(*p)(iClust);
	  ypos+=pxy*TMath::Sin(xPhi[iIn]);
	  xpos+=pxy*TMath::Cos(xPhi[iIn]);
	  (*y)(0,iClust)+=pxy*xEta[iIn];
	}
	(*y)(1,iClust)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2*pi;
      }
      //verify codevectors' stability
      chi=0;
      for (Int_t iClust=0; iClust<nk; iClust++){
	chi1=TMath::CosH((*y1)(0,iClust)-(*y)(0,iClust))-TMath::Cos((*y1)(1,iClust)-(*y)(1,iClust));
	chi1/=(2*TMath::CosH((*y1)(0,iClust))*TMath::CosH((*y)(0,iClust)));
	chi1*=chi1;
	if (chi1>chi) chi=chi1;
      }
      chi=TMath::Sqrt(chi);
      for (Int_t iClust=0; iClust<nk; iClust++){
	for (Int_t i=0; i<2; i++) (*y1)(i,iClust)=(*y)(i,iClust);
	(*py)(iClust)=(*p)(iClust);
      }
      if (nloop>fNloopMax){
	if (chi<fEpsMax || nloop>500) break;
      }
    }while (chi>fEps);
  }while (chi>fEpsMax);
  for (Int_t iClust=0; iClust<nk; iClust++){				//set codevectors and probability equal to those calculated
    for (Int_t i=0; i<2; i++) (*mY)(i,iClust)=(*y)(i,iClust);
    (*vPy)(iClust)=(*p)(iClust);
  }
  delete py;
  delete p;
  delete y;
  delete y1;
  delete ry;
  delete [] m;

}

//-----------------------------------------------------------------------------------
void AliDAJetFinder::NumCl(Int_t &nc,Int_t &nk,TVectorD *vPy, TMatrixD *mPyx,TMatrixD *mY)
{
  // Number of clusters
  static Bool_t growcl=true;
	
  if (nk==2) growcl=true;
  if (growcl){
    //verify if two codevectors are equal within fAvDist
    Int_t *nSame = new Int_t[nk];
    Int_t **iSame = new Int_t*[nk];
    Int_t **cont = new Int_t*[nk];
    for (Int_t iClust=0; iClust<nk; iClust++) {
      cont[iClust] =new Int_t[nk];
      iSame[iClust]=new Int_t[nk];         
    }

    for (Int_t iClust=0; iClust<nk; iClust++){
      iSame[iClust][iClust]=1;
      for (Int_t iClust1=iClust+1; iClust1<nk; iClust1++){
	Double_t eta  = (*mY)(0,iClust) ; Double_t phi  = (*mY)(1,iClust);
	Double_t eta1 = (*mY)(0,iClust1); Double_t phi1 = (*mY)(1,iClust1);
	Double_t distCl=(TMath::CosH(eta-eta1)-TMath::Cos(phi-phi1))/(2*TMath::CosH(eta)*TMath::CosH(eta1));
	if (distCl < fAvDist) iSame[iClust][iClust1]=iSame[iClust1][iClust]=1;
	else iSame[iClust][iClust1]=iSame[iClust1][iClust]=0;
      }
    }
    ReduceClusters(iSame,nk,nc,cont,nSame);
    if (nc >= fNclustMax) growcl=false;
    //recalculate the nc distinct codevectors
    TMatrixD *pyx = new TMatrixD(fNeff,2*nc);
    TVectorD *py = new TVectorD(nk);
    TMatrixD *y1  = new TMatrixD(3,nk);
    for (Int_t iClust=0; iClust<nc; iClust++){
      for(Int_t j=0; j<nSame[iClust]; j++){
	Int_t iClust1 = cont[iClust][j];
	for (Int_t iIn=0; iIn<fNeff; iIn++) (*pyx)(iIn,iClust)+=(*mPyx)(iIn,iClust1);
	(*py)(iClust)+=(*vPy)(iClust1);
	for (Int_t i=0; i<2; i++) (*y1)(i,iClust)+=(*mY)(i,iClust1);
      }
      for (Int_t i=0; i<2; i++) (*y1)(i,iClust)/=nSame[iClust];
    }
    for (Int_t iClust=0; iClust<nk; iClust++) delete [] cont[iClust], delete [] iSame[iClust];
    delete [] iSame;
    delete [] cont;
    delete [] nSame;
    if (nc > nk/2){
      for (Int_t iClust=0; iClust<nc; iClust++){
	for (Int_t iIn=0; iIn<fNeff; iIn++) (*mPyx)(iIn,iClust)=(*pyx)(iIn,iClust);
	for (Int_t iComp=0; iComp<2; iComp++) (*mY)(iComp,iClust)=(*y1)(iComp,iClust);
	(*vPy)(iClust)=(*py)(iClust);
      }
      nk=nc;
      if (growcl) DoubleClusters(nc,nk,vPy,mY);
    }
    delete pyx;
    delete py;
    delete y1;
  }

}

//-----------------------------------------------------------------------------------
void AliDAJetFinder::ReduceClusters(Int_t **iSame,Int_t nc,Int_t &ncout,Int_t **cont,Int_t *nSameOut) const
{
  // Reduction step
  Int_t *nSame = new Int_t[nc];
  Int_t *iperm = new Int_t[nc];
  Int_t *go = new Int_t[nc];
  for (Int_t iCl=0; iCl<nc; iCl++){
    nSame[iCl]=0;
    for (Int_t jCl=0; jCl<nc; jCl++) nSame[iCl]+=iSame[iCl][jCl], cont[iCl][jCl]=0;
    iperm[iCl]=iCl;
    go[iCl]=1;
  }
  TMath::Sort(nc,nSame,iperm,true);
  Int_t l=0;
  for (Int_t iCl=0; iCl<nc; iCl++){
    Int_t k=iperm[iCl];
    if (go[k] == 1){
      Int_t m=0;
      for (Int_t jCl=0; jCl<nc; jCl++){
	if (iSame[k][jCl] == 1){
	  cont[l][m]=jCl;
	  go[jCl]=0;
	  m++;
	}
      }
      nSameOut[l]=m;
      l++;
    }
  }
  ncout=l;
  delete [] nSame;
  delete [] iperm;
  delete [] go;

}

//-----------------------------------------------------------------------------------
void AliDAJetFinder::EndDetAnn(Int_t &nk,Double_t **xData,Int_t *xx,Double_t etx,const TVectorD *vPx,TVectorD *vPy,TMatrixD *mPyx,TMatrixD *mY)
{
  //now assign each particle to only one cluster
  Double_t *clusters=new Double_t[nk];
  for (Int_t iIn=0; iIn<fNeff; iIn++){
    for (Int_t iClust=0; iClust<nk; iClust++) clusters[iClust]=(*mPyx)(iIn,iClust);
    xx[iIn]=TMath::LocMax(nk,clusters);
  }
  delete [] clusters;
	
  //recalculate codevectors, having all p(y|x)=0 or 1
  Double_t *xEta = xData[0];
  Double_t *xPhi = xData[1];
  mY->Zero();
  mPyx->Zero();
  vPy->Zero();
  for (Int_t iIn=0; iIn<fNin; iIn++){
    Int_t iClust=xx[iIn];
    (*mPyx)(iIn,iClust)=1;
    (*vPy)(iClust)+=(*vPx)(iIn);
    (*mY)(0,iClust)+=(*vPx)(iIn)*xEta[iIn];
    (*mY)(3,iClust)+=(*vPx)(iIn)*etx;
  }
  Int_t k=0;
  for (Int_t iClust=0; iClust<nk; iClust++){
    if ((*vPy)(iClust)>0){
      Double_t xpos=0,ypos=0,pxy;
      for (Int_t iIn=0; iIn<fNin; iIn++){
	pxy=(*vPx)(iIn)*(*mPyx)(iIn,iClust)/(*vPy)(iClust);
	ypos+=pxy*TMath::Sin(xPhi[iIn]);
	xpos+=pxy*TMath::Cos(xPhi[iIn]);
	if (xx[iIn]==iClust) xx[iIn]=k;
      }
      (*mY)(0,k)=(*mY)(0,iClust)/(*vPy)(iClust);
      (*mY)(1,k)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2*TMath::Pi();
      (*mY)(3,k)=(*mY)(3,iClust);
      k++;
    }
  }
  nk=k;

}

//-----------------------------------------------------------------------------------
void AliDAJetFinder::StoreJets(Int_t nk, Double_t **xData, const Int_t *xx, const TMatrixD *mY)
{
  //evaluate significant clusters properties
  const Double_t pi=TMath::Pi();
  Float_t dFidEtaMax = ((AliDAJetHeader*)fHeader)->GetFiducialEtaMax();
  Float_t dFidEtaMin = ((AliDAJetHeader*)fHeader)->GetFiducialEtaMin();
  Float_t dFiducialEta= dFidEtaMax - dFidEtaMin;
  Double_t *xEta = xData[0];
  Double_t *xPhi = xData[1];
  Int_t nEff = 0;
  for (Int_t i=0; i<fNeff; i++) if (xEta[i]<dFidEtaMax && xEta[i]>dFidEtaMin) nEff++;
  Double_t dMeanDist=0.;
  if (nEff > 0)
    dMeanDist=TMath::Sqrt(2*dFiducialEta*pi/nEff);
  Bool_t   *isJet = new Bool_t[nk];
  Double_t *etNoBg= new Double_t[nk];
  Double_t *dDeltaEta=new Double_t[nk];
  Double_t *dDeltaPhi=new Double_t[nk];
  Double_t *surf  = new Double_t[nk];
  Double_t *etDens= new Double_t[nk];
  for (Int_t iClust=0; iClust<nk; iClust++){
    isJet[iClust]=false;
    Double_t dEtaMin=10.,dEtaMax=-10.,dPhiMin=10.,dPhiMax=0.;
    for (Int_t iIn=0; iIn<fNeff; iIn++){
      if (xx[iIn]!=iClust || xEta[iIn]>dFidEtaMax || xEta[iIn]<dFidEtaMin) continue;
      if (xEta[iIn] < dEtaMin) dEtaMin=xEta[iIn];
      if (xEta[iIn] > dEtaMax) dEtaMax=xEta[iIn];
      Double_t dPhi=xPhi[iIn]-(*mY)(1,iClust);
      if      (dPhi > pi     ) dPhi-=2*pi;
      else if (dPhi < (-1)*pi) dPhi+=2*pi;
      if      (dPhi < dPhiMin) dPhiMin=dPhi;
      else if (dPhi > dPhiMax) dPhiMax=dPhi;
    }
    dDeltaEta[iClust]=dEtaMax-dEtaMin+dMeanDist;
    dDeltaPhi[iClust]=dPhiMax-dPhiMin+dMeanDist;
    surf[iClust]=0.25*pi*dDeltaEta[iClust]*dDeltaPhi[iClust];
    etDens[iClust]=(*mY)(3,iClust)/surf[iClust];
  }

  if (((AliDAJetHeader*)fHeader)->GetSelJets()){
    for (Int_t iClust=0; iClust<nk; iClust++){
      if (!isJet[iClust] && (*mY)(0,iClust)<dFidEtaMax && (*mY)(0,iClust)>dFidEtaMin){
	Double_t etDensMed=0.;
	Double_t etDensSqr=0.;
	Int_t norm=0;
	for (Int_t iClust1=0; iClust1<nk; iClust1++){
	  if(iClust1!=iClust && (*mY)(0,iClust)<dFidEtaMax && (*mY)(0,iClust)>dFidEtaMin){
	    etDensMed+=etDens[iClust1];
	    etDensSqr+=TMath::Power(etDens[iClust1],2);
	    norm++;
	  }
	}
	etDensMed/=TMath::Max(norm,1);
	etDensSqr/=TMath::Max(norm,1);
	Double_t deltaEtDens=TMath::Sqrt(etDensSqr-TMath::Power(etDensMed,2));
	if ((*mY)(3,iClust) > (etDensMed+deltaEtDens)*surf[iClust]) isJet[iClust]=kTRUE;
	etNoBg[iClust]=(*mY)(3,iClust)-etDensMed*surf[iClust];
      }
    }
    for (Int_t iClust=0; iClust<nk; iClust++){
      if (isJet[iClust]){
	Double_t etDensMed=0;
	Double_t extSurf=2*dFiducialEta*pi;
	for (Int_t iClust1=0; iClust1<nk; iClust1++){
	  if (!isJet[iClust1]) etDensMed+=(*mY)(3,iClust1);
	  else extSurf-=surf[iClust1];
	}
	etDensMed/=extSurf;
	etNoBg[iClust]=(*mY)(3,iClust)-etDensMed*surf[iClust];
	if (etNoBg[iClust]<((AliDAJetHeader*)fHeader)->GetEtMin()){
	  isJet[iClust]=kFALSE;
	  iClust=-1;
	}
      }
    }
  } else {
    for (Int_t iClust=0; iClust<nk; iClust++){
      isJet[iClust]=true;
      etNoBg[iClust]=(*mY)(3,iClust);
    }
  }
  delete [] etDens;
  delete [] surf;
	
  //now add selected jets to the list
  Int_t *iSort = new Int_t[nk];
  TMath::Sort(nk,etNoBg,iSort,true);
  Int_t iCl = 0;

  for (Int_t iClust=0; iClust<nk; iClust++){ //clusters loop
    iCl=iSort[iClust];
    if (isJet[iCl]){ //choose cluster
      Float_t px,py,pz,en;
      px = (*mY)(3,iCl)*TMath::Cos((*mY)(1,iCl));
      py = (*mY)(3,iCl)*TMath::Sin((*mY)(1,iCl));
      pz = (*mY)(3,iCl)/TMath::Tan(2.0 * TMath::ATan(TMath::Exp(-(*mY)(0,iCl))));
      en = TMath::Sqrt(px * px + py * py + pz * pz);
      AliAODJet jet(px, py, pz, en);
      Int_t iIn=0;
      Int_t nTr = GetCalTrkEvent()->GetNCalTrkTracks();
      for (Int_t iTr=0; iTr<nTr; iTr++){
	AliJetCalTrkTrack* ctT = GetCalTrkEvent()->GetCalTrkTrack(iTr);
	if (ctT->GetCutFlag()==0) continue;
	if (xx[iIn]==iCl) jet.AddTrack(ctT->GetTrackObject());
	iIn++;
      }
      AddJet(jet);
      if (fDebug > 0) printf("jet %d, Eta: %f, Phi: %f, Et: %f\n",iCl,jet.Eta(),jet.Phi(),jet.Pt());
    }
  }
  delete [] dDeltaEta; delete [] dDeltaPhi;
  delete [] etNoBg;
  delete [] isJet;
  delete [] iSort;

}

//-----------------------------------------------------------------------------------
Double_t Dist(TVectorD x,TVectorD y)
{
  // Squared distance
  const Double_t pi=TMath::Pi();
  Double_t dphi=TMath::Abs(x(1)-y(1));
  if (dphi > pi) dphi=2*pi-dphi;
  Double_t dist=pow(x(0)-y(0),2)+pow(dphi,2);
  return dist;

}