[u/mrichter/AliRoot.git] / JETAN / AliDAJetFinder.cxx


//  **************************************************************************
//  * 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.                  *
//  **************************************************************************

//-----------------------------------------------------------------------------------
// 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)
//-----------------------------------------------------------------------------------

#include <TMath.h>
#include <TRandom.h>
#include <TClonesArray.h>
#include "AliJetReaderHeader.h"
#include "AliJetReader.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)
{
	// Constructor
}

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

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

	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) 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[fNin];
	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);
	TClonesArray *lvArray = fReader->GetMomentumArray();
	Int_t nEntr = lvArray->GetEntries();
	fNin=0;
	for (Int_t iEn=0; iEn<nEntr; iEn++) if (fReader->GetCutFlag(iEn)==1) fNin++;
	Double_t *xEta = new Double_t[fNin];
	Double_t *xPhi = new Double_t[fNin];
	xData[0]=xEta; xData[1]=xPhi;
	vPx->ResizeTo(fNin);
	Int_t iIn=0;
	for (Int_t iEn=0; iEn<nEntr; iEn++){
		if (fReader->GetCutFlag(iEn)==0) continue;
		TLorentzVector *lv=(TLorentzVector*)lvArray->At(iEn);
		xEta[iIn] = lv->Eta();
		xPhi[iIn] = lv->Phi()<0 ? lv->Phi() + 2*TMath::Pi() : lv->Phi();
		(*vPx)(iIn)=lv->Pt();
		dEtSum+=(*vPx)(iIn);
		iIn++;
	}
	for (iIn=0; iIn<fNin; iIn++) (*vPx)(iIn)=(*vPx)(iIn)/dEtSum;

	Int_t njdim=2*fNclustMax+1;
	mPyx->ResizeTo(fNin,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<fNin; 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
{
	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,  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]={fReader->GetReaderHeader()->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<fNin; 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<fNin; iIn++) (*p)(iClust)+=(*vPx)(iIn)*(*mPyx)(iIn,iClust);
				for (Int_t iIn=0; iIn<fNin; 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)
{
	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(fNin,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<fNin; 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<fNin; 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
{
	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,
                               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<fNin; 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,  Int_t *xx,  TMatrixD *mY)
{
//evaluate significant clusters properties
	const Double_t pi=TMath::Pi();
	AliJetReaderHeader *rHeader=fReader->GetReaderHeader();
	Float_t dFiducialEta=rHeader->GetFiducialEtaMax()-rHeader->GetFiducialEtaMin();
	Double_t dMeanDist=TMath::Sqrt(2*dFiducialEta*pi/fNin);
    Double_t *xEta = xData[0];
    Double_t *xPhi = xData[1];
	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++){									//clusters loop
		isJet[iClust]=false;
		Double_t dEtaMin=10.,dEtaMax=-10.,dPhiMin=10.,dPhiMax=0.;
		for (Int_t iIn=0; iIn<fNin; iIn++){
			if (xx[iIn]!=iClust) 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]){
				Double_t etDensMed=0.;
				Double_t etDensSqr=0.;
				Int_t norm=0;
				for (Int_t iClust1=0; iClust1<nk; iClust1++){
					if(iClust1!=iClust){
						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;
	}
	delete [] etDens;
	delete [] surf;
	
//now add selected jets to the list
	Int_t *inJet = new Int_t[fNin];
	TRefArray *refs = 0;
	Bool_t fromAod = !strcmp(fReader->ClassName(),"AliJetAODReader");
	if (fromAod) refs = fReader->GetReferences();
	for (Int_t iClust=0; iClust<nk; iClust++){									//clusters loop
		if (isJet[iClust]){														//choose cluster
			Float_t px,py,pz,en;
			px = (*mY)(3,iClust)*TMath::Cos((*mY)(1,iClust));
			py = (*mY)(3,iClust)*TMath::Sin((*mY)(1,iClust));
			pz = (*mY)(3,iClust)/TMath::Tan(2.0 * TMath::ATan(TMath::Exp(-(*mY)(0,iClust))));
			en = TMath::Sqrt(px * px + py * py + pz * pz);
			AliAODJet jet(px, py, pz, en);
			if (fromAod){
				Int_t iIn=0;
				Int_t nEntr = fReader->GetMomentumArray()->GetEntries();
				for (Int_t iEn=0; iEn<nEntr; iEn++){
					if (fReader->GetCutFlag(iEn)==0) continue;
					if (xx[iIn]==iClust) jet.AddTrack(refs->At(iEn));
					iIn++;
				}
			}
			AddJet(jet);
		}
	}
	delete [] dDeltaEta; delete [] dDeltaPhi;
	delete [] etNoBg;
	delete [] isJet;
	delete [] inJet;
}

//-----------------------------------------------------------------------------------
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;
}
Commit	Line	Data
9e4cc50d	1
7c679be0	2	// **************************************************************************
	3	// * Copyright(c) 1998-1999, ALICE Experiment at CERN, All rights reserved. *
	4	// * *
	5	// * Author: The ALICE Off-line Project. *
	6	// * Contributors are mentioned in the code where appropriate. *
	7	// * *
	8	// * Permission to use, copy, modify and distribute this software and its *
	9	// * documentation strictly for non-commercial purposes is hereby granted *
	10	// * without fee, provided that the above copyright notice appears in all *
	11	// * copies and that both the copyright notice and this permission notice *
	12	// * appear in the supporting documentation. The authors make no claims *
	13	// * about the suitability of this software for any purpose. It is *
	14	// * provided "as is" without express or implied warranty. *
	15	// **************************************************************************
	16
	17	//-----------------------------------------------------------------------------------
	18	// Jet finder based on Deterministic Annealing
	19	// For further informations about the DA working features see:
	20	// Phys.Lett. B601 (2004) 56-63 (http://arxiv.org/abs/hep-ph/0407214)
	21	// Author: Davide Perrino (davide.perrino@ba.infn.it, davide.perrino@cern.ch)
	22	//-----------------------------------------------------------------------------------
	23
	24	#include <TMath.h>
	25	#include <TRandom.h>
	26	#include <TClonesArray.h>
36b5cc43	27	#include "AliJetReaderHeader.h"
7c679be0	28	#include "AliJetReader.h"
	29	#include "AliDAJetHeader.h"
	30	#include "AliDAJetFinder.h"
	31
7c679be0	32	ClassImp(AliDAJetFinder)
	33
	34
	35	//-----------------------------------------------------------------------------------
	36	AliDAJetFinder::AliDAJetFinder():
36b5cc43	37	AliJetFinder(),
7c679be0	38	fAlpha(1.01),
	39	fDelta(1e-8),
	40	fAvDist(1e-6),
	41	fEps(1e-4),
	42	fEpsMax(1e-2),
	43	fNloopMax(100),
	44	fBeta(0.1),
	45	fNclustMax(0),
9e4cc50d	46	fNin(0)
7c679be0	47	{
	48	// Constructor
	49	}
	50
	51	//-----------------------------------------------------------------------------------
	52	AliDAJetFinder::~AliDAJetFinder()
	53	{
	54	// Destructor
7c679be0	55	}
	56
	57	//-----------------------------------------------------------------------------------
	58	void AliDAJetFinder::FindJets()
	59	{
	60	// Find the jets in current event
	61	//
	62	Float_t betaStop=100.;
	63
	64	Double_t dEtSum=0;
36b5cc43	65	Double_t *xData[2];
	66	TVectorD *vPx = new TVectorD();
	67	TVectorD *vPy = new TVectorD();
	68	TMatrixD *mPyx= new TMatrixD();
	69	TMatrixD *mY = new TMatrixD();
	70	InitDetAnn(dEtSum,xData,vPx,vPy,mPyx,mY);
a9f9d6d5	71	if (fNin < fNclustMax) return;
7c679be0	72
36b5cc43	73	Int_t nc=1, nk;
36b5cc43	74	DoubleClusters(nc,nk,vPy,mY);
7c679be0	75	do{ //loop over beta
7c679be0	76	fBeta*=fAlpha;
36b5cc43	77	Annealing(nk,xData,vPx,vPy,mPyx,mY);
36b5cc43	78	NumCl(nc,nk,vPy,mPyx,mY);
7c679be0	79	}while((fBeta<betaStop \|\| nc<4) && nc<fNclustMax);
	80
	81	Int_t *xx=new Int_t[fNin];
36b5cc43	82	EndDetAnn(nk,xData,xx,dEtSum,vPx,vPy,mPyx,mY);
36b5cc43	83	StoreJets(nk,xData,xx,mY);
7c679be0	84	delete [] xx;
7c679be0	85
36b5cc43	86	delete [] xData[0], delete [] xData[1];
	87	delete mPyx;
	88	delete mY;
	89	delete vPx;
	90	delete vPy;
	91
7c679be0	92	}
	93
	94	//-----------------------------------------------------------------------------------
36b5cc43	95	void AliDAJetFinder::InitDetAnn(Double_t &dEtSum,Double_t *xData,TVectorD vPx,TVectorD vPy,TMatrixD mPyx,TMatrixD *mY)
7c679be0	96	{
	97	//Initialise the variables used by the algorithm
	98	fBeta=0.1;
9e4cc50d	99	fNclustMax= ((AliDAJetHeader*)fHeader)->GetFixedCl() ?
36b5cc43	100	((AliDAJetHeader*)fHeader)->GetNclustMax() :
9e4cc50d	101	TMath::Max((Int_t)TMath::Sqrt(fNin),5);
e53baffe	102	TClonesArray *lvArray = fReader->GetMomentumArray();
	103	Int_t nEntr = lvArray->GetEntries();
	104	fNin=0;
	105	for (Int_t iEn=0; iEn<nEntr; iEn++) if (fReader->GetCutFlag(iEn)==1) fNin++;
36b5cc43	106	Double_t *xEta = new Double_t[fNin];
e53baffe	107	Double_t *xPhi = new Double_t[fNin];
36b5cc43	108	xData[0]=xEta; xData[1]=xPhi;
36b5cc43	109	vPx->ResizeTo(fNin);
e53baffe	110	Int_t iIn=0;
	111	for (Int_t iEn=0; iEn<nEntr; iEn++){
	112	if (fReader->GetCutFlag(iEn)==0) continue;
	113	TLorentzVector lv=(TLorentzVector)lvArray->At(iEn);
36b5cc43	114	xEta[iIn] = lv->Eta();
	115	xPhi[iIn] = lv->Phi()<0 ? lv->Phi() + 2*TMath::Pi() : lv->Phi();
	116	(*vPx)(iIn)=lv->Pt();
	117	dEtSum+=(*vPx)(iIn);
e53baffe	118	iIn++;
7c679be0	119	}
19b36dbe	120	for (iIn=0; iIn<fNin; iIn++) (vPx)(iIn)=(vPx)(iIn)/dEtSum;
7c679be0	121
7c679be0	122	Int_t njdim=2*fNclustMax+1;
36b5cc43	123	mPyx->ResizeTo(fNin,njdim);
	124	mY->ResizeTo(4,njdim);
	125	vPy->ResizeTo(njdim);
	126	mY->Zero();mPyx->Zero();vPy->Zero();
	127	(*vPy)(0)=1;
	128	TMatrixDColumn(*mPyx,0)=1;
7c679be0	129	Double_t ypos=0,xpos=0;
19b36dbe	130	for (iIn=0; iIn<fNin; iIn++){
36b5cc43	131	(mY)(0,0)+=(vPx)(iIn)*xEta[iIn];
	132	ypos+=(vPx)(iIn)TMath::Sin(xPhi[iIn]);
	133	xpos+=(vPx)(iIn)TMath::Cos(xPhi[iIn]);
7c679be0	134	}
36b5cc43	135	(mY)(1,0)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2TMath::Pi();
7c679be0	136	}
	137
	138	//-----------------------------------------------------------------------------------
c0a5117c	139	void AliDAJetFinder::DoubleClusters(Int_t nc,Int_t &nk, TVectorD vPy, TMatrixD mY) const
7c679be0	140	{
7c679be0	141	for(Int_t iClust=0; iClust<nc; iClust++){
36b5cc43	142	(vPy)(iClust)=(vPy)(iClust)/2;
	143	(vPy)(nc+iClust)=(vPy)(iClust);
	144	for(Int_t iComp=0; iComp<3; iComp++) (mY)(iComp,nc+iClust)=(mY)(iComp,iClust);
7c679be0	145	}
	146	nk=2*nc;
	147	}
	148
	149	//-----------------------------------------------------------------------------------
c0a5117c	150	void AliDAJetFinder::Annealing(Int_t nk,Double_t *xData, TVectorD vPx, TVectorD vPy, TMatrixD mPyx, TMatrixD *mY)
7c679be0	151	{
	152	// Main part of the algorithm
	153	const Double_t pi=TMath::Pi();
	154	TVectorD *py = new TVectorD(nk);
	155	TVectorD *p = new TVectorD(nk);
	156	TMatrixD *y = new TMatrixD(4,nk);
	157	TMatrixD *y1 = new TMatrixD(4,nk);
	158	TMatrixD *ry = new TMatrixD(2,nk);
36b5cc43	159	Double_t *xEta = xData[0];
36b5cc43	160	Double_t *xPhi = xData[1];
7c679be0	161	Double_t Dist(TVectorD,TVectorD);
7c679be0	162
36b5cc43	163	Double_t df[2]={fReader->GetReaderHeader()->GetFiducialEtaMax(),pi};
7c679be0	164	TVectorD vPart(2);
	165	Double_t *m = new Double_t[nk];
	166	Double_t chi,chi1;
	167	do{
	168	Int_t nloop=0;
	169	for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	170	for (Int_t i=0; i<3; i++)(y1)(i,iClust)=(mY)(i,iClust);
36b5cc43	171	(py)(iClust)=(vPy)(iClust);
7c679be0	172	}
	173	//perturbation of codevectors
	174	Double_t seed=1000000*gRandom->Rndm(24);
	175	ry->Randomize(-0.5,0.5,seed);
	176	for (Int_t i=0; i<2; i++){
	177	for (Int_t iClust=0; iClust<nk/2; iClust++)
	178	(y1)(i,iClust)+=((ry)(i,iClust)+TMath::Sign(0.5,(ry)(i,iClust)))fDelta*df[i];
	179	for (Int_t iClust=nk/2; iClust<nk; iClust++)
	180	(y1)(i,iClust)-=((ry)(i,iClust-nk/2)+TMath::Sign(0.5,(ry)(i,iClust-nk/2)))fDelta*df[i];
	181	}
	182	do{
	183	//recalculate conditional probabilities
	184	nloop++;
	185	for (Int_t iIn=0; iIn<fNin; iIn++){
36b5cc43	186	vPart(0)=xEta[iIn]; vPart(1)=xPhi[iIn];
7c679be0	187	for(Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	188	(mPyx)(iIn,iClust)=-log((py)(iClust))+fBetaDist(vPart,TMatrixDColumn(y1,iClust));
36b5cc43	189	m[iClust]=(*mPyx)(iIn,iClust);
7c679be0	190	}
	191	Double_t pyxNorm=0;
	192	Double_t minPyx=TMath::MinElement(nk,m);
	193	for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	194	(*mPyx)(iIn,iClust)-=minPyx;
	195	(mPyx)(iIn,iClust)=exp(-(mPyx)(iIn,iClust));
	196	pyxNorm+=(*mPyx)(iIn,iClust);
7c679be0	197	}
36b5cc43	198	for (Int_t iClust=0; iClust<nk; iClust++) (*mPyx)(iIn,iClust)/=pyxNorm;
7c679be0	199	}
	200	p->Zero();
	201	y->Zero();
	202	//recalculate codevectors
	203	for (Int_t iClust=0; iClust<nk; iClust++){
	204	Double_t xpos=0,ypos=0,pxy;
36b5cc43	205	for (Int_t iIn=0; iIn<fNin; iIn++) (p)(iClust)+=(vPx)(iIn)(mPyx)(iIn,iClust);
7c679be0	206	for (Int_t iIn=0; iIn<fNin; iIn++){
36b5cc43	207	pxy=(vPx)(iIn)(mPyx)(iIn,iClust)/(p)(iClust);
	208	ypos+=pxy*TMath::Sin(xPhi[iIn]);
	209	xpos+=pxy*TMath::Cos(xPhi[iIn]);
	210	(y)(0,iClust)+=pxyxEta[iIn];
7c679be0	211	}
	212	(y)(1,iClust)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2pi;
	213	}
	214	//verify codevectors' stability
	215	chi=0;
	216	for (Int_t iClust=0; iClust<nk; iClust++){
	217	chi1=TMath::CosH((y1)(0,iClust)-(y)(0,iClust))-TMath::Cos((y1)(1,iClust)-(y)(1,iClust));
	218	chi1/=(2TMath::CosH((y1)(0,iClust))TMath::CosH((y)(0,iClust)));
	219	chi1*=chi1;
	220	if (chi1>chi) chi=chi1;
	221	}
	222	chi=TMath::Sqrt(chi);
	223	for (Int_t iClust=0; iClust<nk; iClust++){
	224	for (Int_t i=0; i<2; i++) (y1)(i,iClust)=(y)(i,iClust);
	225	(py)(iClust)=(p)(iClust);
	226	}
	227	if (nloop>fNloopMax){
	228	if (chi<fEpsMax \|\| nloop>500) break;
	229	}
	230	}while (chi>fEps);
	231	}while (chi>fEpsMax);
	232	for (Int_t iClust=0; iClust<nk; iClust++){ //set codevectors and probability equal to those calculated
36b5cc43	233	for (Int_t i=0; i<2; i++) (mY)(i,iClust)=(y)(i,iClust);
36b5cc43	234	(vPy)(iClust)=(p)(iClust);
7c679be0	235	}
	236	delete py;
	237	delete p;
	238	delete y;
	239	delete y1;
	240	delete ry;
c0a5117c	241	delete [] m;
7c679be0	242	}
	243
	244	//-----------------------------------------------------------------------------------
c0a5117c	245	void AliDAJetFinder::NumCl(Int_t &nc,Int_t &nk,TVectorD vPy, TMatrixD mPyx,TMatrixD *mY)
7c679be0	246	{
	247	static Bool_t growcl=true;
	248
	249	if (nk==2) growcl=true;
	250	if (growcl){
	251	//verify if two codevectors are equal within fAvDist
	252	Int_t *nSame = new Int_t[nk];
	253	Int_t *iSame = new Int_t[nk];
	254	Int_t *cont = new Int_t[nk];
	255	for (Int_t iClust=0; iClust<nk; iClust++) cont[iClust]=new Int_t[nk],iSame[iClust]=new Int_t[nk];
	256	for (Int_t iClust=0; iClust<nk; iClust++){
	257	iSame[iClust][iClust]=1;
	258	for (Int_t iClust1=iClust+1; iClust1<nk; iClust1++){
36b5cc43	259	Double_t eta = (mY)(0,iClust) ; Double_t phi = (mY)(1,iClust);
36b5cc43	260	Double_t eta1 = (mY)(0,iClust1); Double_t phi1 = (mY)(1,iClust1);
7c679be0	261	Double_t distCl=(TMath::CosH(eta-eta1)-TMath::Cos(phi-phi1))/(2TMath::CosH(eta)TMath::CosH(eta1));
7c679be0	262	if (distCl < fAvDist) iSame[iClust][iClust1]=iSame[iClust1][iClust]=1;
852db00e	263	else iSame[iClust][iClust1]=iSame[iClust1][iClust]=0;
7c679be0	264	}
	265	}
	266	ReduceClusters(iSame,nk,nc,cont,nSame);
	267	if (nc >= fNclustMax) growcl=false;
	268	//recalculate the nc distinct codevectors
	269	TMatrixD pyx = new TMatrixD(fNin,2nc);
	270	TVectorD *py = new TVectorD(nk);
	271	TMatrixD *y1 = new TMatrixD(3,nk);
	272	for (Int_t iClust=0; iClust<nc; iClust++){
	273	for(Int_t j=0; j<nSame[iClust]; j++){
	274	Int_t iClust1 = cont[iClust][j];
36b5cc43	275	for (Int_t iIn=0; iIn<fNin; iIn++) (pyx)(iIn,iClust)+=(mPyx)(iIn,iClust1);
	276	(py)(iClust)+=(vPy)(iClust1);
	277	for (Int_t i=0; i<2; i++) (y1)(i,iClust)+=(mY)(i,iClust1);
7c679be0	278	}
	279	for (Int_t i=0; i<2; i++) (*y1)(i,iClust)/=nSame[iClust];
	280	}
852db00e	281	for (Int_t iClust=0; iClust<nk; iClust++) delete [] cont[iClust], delete [] iSame[iClust];
	282	delete [] iSame;
	283	delete [] cont;
	284	delete [] nSame;
7c679be0	285	if (nc > nk/2){
7c679be0	286	for (Int_t iClust=0; iClust<nc; iClust++){
36b5cc43	287	for (Int_t iIn=0; iIn<fNin; iIn++) (mPyx)(iIn,iClust)=(pyx)(iIn,iClust);
	288	for (Int_t iComp=0; iComp<2; iComp++) (mY)(iComp,iClust)=(y1)(iComp,iClust);
	289	(vPy)(iClust)=(py)(iClust);
7c679be0	290	}
7c679be0	291	nk=nc;
36b5cc43	292	if (growcl) DoubleClusters(nc,nk,vPy,mY);
7c679be0	293	}
7c679be0	294	delete pyx;
	295	delete py;
	296	delete y1;
	297	}
	298
	299	}
	300
	301	//-----------------------------------------------------------------------------------
c0a5117c	302	void AliDAJetFinder::ReduceClusters(Int_t iSame,Int_t nc,Int_t &ncout,Int_t cont,Int_t *nSameOut) const
7c679be0	303	{
	304	Int_t *nSame = new Int_t[nc];
	305	Int_t *iperm = new Int_t[nc];
	306	Int_t *go = new Int_t[nc];
	307	for (Int_t iCl=0; iCl<nc; iCl++){
	308	nSame[iCl]=0;
852db00e	309	for (Int_t jCl=0; jCl<nc; jCl++) nSame[iCl]+=iSame[iCl][jCl], cont[iCl][jCl]=0;
7c679be0	310	iperm[iCl]=iCl;
	311	go[iCl]=1;
	312	}
	313	TMath::Sort(nc,nSame,iperm,true);
	314	Int_t l=0;
	315	for (Int_t iCl=0; iCl<nc; iCl++){
	316	Int_t k=iperm[iCl];
	317	if (go[k] == 1){
	318	Int_t m=0;
	319	for (Int_t jCl=0; jCl<nc; jCl++){
	320	if (iSame[k][jCl] == 1){
	321	cont[l][m]=jCl;
	322	go[jCl]=0;
	323	m++;
	324	}
	325	}
	326	nSameOut[l]=m;
	327	l++;
	328	}
	329	}
	330	ncout=l;
	331	delete [] nSame;
	332	delete [] iperm;
	333	delete [] go;
	334	}
	335
	336	//-----------------------------------------------------------------------------------
36b5cc43	337	void AliDAJetFinder::EndDetAnn(Int_t &nk,Double_t *xData,Int_t xx,Double_t etx,
36b5cc43	338	TVectorD vPx,TVectorD vPy,TMatrixD mPyx,TMatrixD mY)
7c679be0	339	{
	340	//now assign each particle to only one cluster
	341	Double_t *clusters=new Double_t[nk];
	342	for (Int_t iIn=0; iIn<fNin; iIn++){
36b5cc43	343	for (Int_t iClust=0; iClust<nk; iClust++) clusters[iClust]=(*mPyx)(iIn,iClust);
7c679be0	344	xx[iIn]=TMath::LocMax(nk,clusters);
	345	}
	346	delete [] clusters;
	347
	348	//recalculate codevectors, having all p(y\|x)=0 or 1
36b5cc43	349	Double_t *xEta = xData[0];
	350	Double_t *xPhi = xData[1];
	351	mY->Zero();
	352	mPyx->Zero();
	353	vPy->Zero();
7c679be0	354	for (Int_t iIn=0; iIn<fNin; iIn++){
7c679be0	355	Int_t iClust=xx[iIn];
36b5cc43	356	(*mPyx)(iIn,iClust)=1;
	357	(vPy)(iClust)+=(vPx)(iIn);
	358	(mY)(0,iClust)+=(vPx)(iIn)*xEta[iIn];
	359	(mY)(3,iClust)+=(vPx)(iIn)*etx;
7c679be0	360	}
	361	Int_t k=0;
	362	for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	363	if ((*vPy)(iClust)>0){
7c679be0	364	Double_t xpos=0,ypos=0,pxy;
7c679be0	365	for (Int_t iIn=0; iIn<fNin; iIn++){
36b5cc43	366	pxy=(vPx)(iIn)(mPyx)(iIn,iClust)/(vPy)(iClust);
	367	ypos+=pxy*TMath::Sin(xPhi[iIn]);
	368	xpos+=pxy*TMath::Cos(xPhi[iIn]);
7c679be0	369	if (xx[iIn]==iClust) xx[iIn]=k;
7c679be0	370	}
36b5cc43	371	(mY)(0,k)=(mY)(0,iClust)/(*vPy)(iClust);
	372	(mY)(1,k)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2TMath::Pi();
	373	(mY)(3,k)=(mY)(3,iClust);
7c679be0	374	k++;
	375	}
	376	}
	377	nk=k;
	378	}
	379
	380	//-----------------------------------------------------------------------------------
c0a5117c	381	void AliDAJetFinder::StoreJets(Int_t nk,Double_t *xData, Int_t xx, TMatrixD *mY)
7c679be0	382	{
	383	//evaluate significant clusters properties
	384	const Double_t pi=TMath::Pi();
36b5cc43	385	AliJetReaderHeader *rHeader=fReader->GetReaderHeader();
	386	Float_t dFiducialEta=rHeader->GetFiducialEtaMax()-rHeader->GetFiducialEtaMin();
	387	Double_t dMeanDist=TMath::Sqrt(2dFiducialEtapi/fNin);
	388	Double_t *xEta = xData[0];
	389	Double_t *xPhi = xData[1];
7c679be0	390	Bool_t *isJet = new Bool_t[nk];
	391	Double_t *etNoBg= new Double_t[nk];
	392	Double_t *dDeltaEta=new Double_t[nk];
	393	Double_t *dDeltaPhi=new Double_t[nk];
	394	Double_t *surf = new Double_t[nk];
	395	Double_t *etDens= new Double_t[nk];
	396	for (Int_t iClust=0; iClust<nk; iClust++){ //clusters loop
	397	isJet[iClust]=false;
	398	Double_t dEtaMin=10.,dEtaMax=-10.,dPhiMin=10.,dPhiMax=0.;
	399	for (Int_t iIn=0; iIn<fNin; iIn++){
	400	if (xx[iIn]!=iClust) continue;
36b5cc43	401	if (xEta[iIn] < dEtaMin) dEtaMin=xEta[iIn];
	402	if (xEta[iIn] > dEtaMax) dEtaMax=xEta[iIn];
	403	Double_t dPhi=xPhi[iIn]-(*mY)(1,iClust);
7c679be0	404	if (dPhi > pi ) dPhi-=2*pi;
	405	else if (dPhi < (-1)pi) dPhi+=2pi;
	406	if (dPhi < dPhiMin) dPhiMin=dPhi;
	407	else if (dPhi > dPhiMax) dPhiMax=dPhi;
	408	}
	409	dDeltaEta[iClust]=dEtaMax-dEtaMin+dMeanDist;
	410	dDeltaPhi[iClust]=dPhiMax-dPhiMin+dMeanDist;
	411	surf[iClust]=0.25pidDeltaEta[iClust]*dDeltaPhi[iClust];
36b5cc43	412	etDens[iClust]=(*mY)(3,iClust)/surf[iClust];
7c679be0	413	}
7c679be0	414
9e4cc50d	415	if (((AliDAJetHeader*)fHeader)->GetSelJets()){
7c679be0	416	for (Int_t iClust=0; iClust<nk; iClust++){
	417	if (!isJet[iClust]){
	418	Double_t etDensMed=0.;
	419	Double_t etDensSqr=0.;
	420	Int_t norm=0;
	421	for (Int_t iClust1=0; iClust1<nk; iClust1++){
	422	if(iClust1!=iClust){
	423	etDensMed+=etDens[iClust1];
	424	etDensSqr+=TMath::Power(etDens[iClust1],2);
	425	norm++;
	426	}
	427	}
	428	etDensMed/=TMath::Max(norm,1);
	429	etDensSqr/=TMath::Max(norm,1);
	430	Double_t deltaEtDens=TMath::Sqrt(etDensSqr-TMath::Power(etDensMed,2));
36b5cc43	431	if ((mY)(3,iClust) > (etDensMed+deltaEtDens)surf[iClust]) isJet[iClust]=kTRUE;
36b5cc43	432	etNoBg[iClust]=(mY)(3,iClust)-etDensMedsurf[iClust];
7c679be0	433	}
	434	}
	435	for (Int_t iClust=0; iClust<nk; iClust++){
	436	if (isJet[iClust]){
	437	Double_t etDensMed=0;
36b5cc43	438	Double_t extSurf=2dFiducialEtapi;
7c679be0	439	for (Int_t iClust1=0; iClust1<nk; iClust1++){
36b5cc43	440	if (!isJet[iClust1]) etDensMed+=(*mY)(3,iClust1);
7c679be0	441	else extSurf-=surf[iClust1];
	442	}
	443	etDensMed/=extSurf;
36b5cc43	444	etNoBg[iClust]=(mY)(3,iClust)-etDensMedsurf[iClust];
10bd125d	445	if (etNoBg[iClust]<((AliDAJetHeader*)fHeader)->GetEtMin()){
	446	isJet[iClust]=kFALSE;
	447	iClust=-1;
	448	}
7c679be0	449	}
	450	}
	451	} else {
	452	for (Int_t iClust=0; iClust<nk; iClust++) isJet[iClust]=true;
	453	}
	454	delete [] etDens;
	455	delete [] surf;
	456
	457	//now add selected jets to the list
	458	Int_t *inJet = new Int_t[fNin];
	459	TRefArray *refs = 0;
	460	Bool_t fromAod = !strcmp(fReader->ClassName(),"AliJetAODReader");
	461	if (fromAod) refs = fReader->GetReferences();
	462	for (Int_t iClust=0; iClust<nk; iClust++){ //clusters loop
	463	if (isJet[iClust]){ //choose cluster
	464	Float_t px,py,pz,en;
36b5cc43	465	px = (mY)(3,iClust)TMath::Cos((*mY)(1,iClust));
	466	py = (mY)(3,iClust)TMath::Sin((*mY)(1,iClust));
	467	pz = (mY)(3,iClust)/TMath::Tan(2.0 TMath::ATan(TMath::Exp(-(*mY)(0,iClust))));
7c679be0	468	en = TMath::Sqrt(px * px + py * py + pz * pz);
7c679be0	469	AliAODJet jet(px, py, pz, en);
e53baffe	470	if (fromAod){
	471	Int_t iIn=0;
	472	Int_t nEntr = fReader->GetMomentumArray()->GetEntries();
	473	for (Int_t iEn=0; iEn<nEntr; iEn++){
	474	if (fReader->GetCutFlag(iEn)==0) continue;
	475	if (xx[iIn]==iClust) jet.AddTrack(refs->At(iEn));
	476	iIn++;
	477	}
	478	}
7c679be0	479	AddJet(jet);
7c679be0	480	}
	481	}
	482	delete [] dDeltaEta; delete [] dDeltaPhi;
	483	delete [] etNoBg;
	484	delete [] isJet;
	485	delete [] inJet;
	486	}
	487
	488	//-----------------------------------------------------------------------------------
	489	Double_t Dist(TVectorD x,TVectorD y)
	490	{
	491	// Squared distance
	492	const Double_t pi=TMath::Pi();
	493	Double_t dphi=TMath::Abs(x(1)-y(1));
	494	if (dphi > pi) dphi=2*pi-dphi;
	495	Double_t dist=pow(x(0)-y(0),2)+pow(dphi,2);
	496	return dist;
	497	}