[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) 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;
	TClonesArray *lvArray = fReader->GetMomentumArray();
	fNin = lvArray->GetEntries();
	fNclustMax= ((AliDAJetHeader*)fHeader)->GetFixedCl() ? 
	    ((AliDAJetHeader*)fHeader)->GetNclustMax() : 
	    TMath::Max((Int_t)TMath::Sqrt(fNin),5);
	Double_t *xEta = new Double_t[fNin];
    Double_t *xPhi = new Double_t[fNin];
	xData[0]=xEta; xData[1]=xPhi;
	vPx->ResizeTo(fNin);
	for (Int_t iIn=0; iIn<fNin; iIn++){
		TLorentzVector *lv=(TLorentzVector*)lvArray->At(iIn);
		xEta[iIn] = lv->Eta();
		xPhi[iIn] = lv->Phi()<0 ? lv->Phi() + 2*TMath::Pi() : lv->Phi();
		(*vPx)(iIn)=lv->Pt();
		dEtSum+=(*vPx)(iIn);
	}
	for (Int_t 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 (Int_t 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();
	lvArray->Delete();
}

//-----------------------------------------------------------------------------------
void AliDAJetFinder::DoubleClusters(Int_t nc,Int_t &nk,TVectorD *vPy,TMatrixD *mY)
{
	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)
{
	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) 
			    for (Int_t iIn=0; iIn<fNin; iIn++) if (xx[iIn]==iClust) jet.AddTrack(refs->At(iIn));
			AddJet(jet);
			printf("jet %d, Eta: %f, Phi: %f, Et: %f\n",iClust,jet.Eta(),jet.Phi(),jet.Pt());
		}
	}
	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);
7c679be0	71	if (!fNin) 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;
	99	TClonesArray *lvArray = fReader->GetMomentumArray();
	100	fNin = lvArray->GetEntries();
9e4cc50d	101	fNclustMax= ((AliDAJetHeader*)fHeader)->GetFixedCl() ?
36b5cc43	102	((AliDAJetHeader*)fHeader)->GetNclustMax() :
9e4cc50d	103	TMath::Max((Int_t)TMath::Sqrt(fNin),5);
36b5cc43	104	Double_t *xEta = new Double_t[fNin];
	105	Double_t *xPhi = new Double_t[fNin];
	106	xData[0]=xEta; xData[1]=xPhi;
	107	vPx->ResizeTo(fNin);
7c679be0	108	for (Int_t iIn=0; iIn<fNin; iIn++){
7c679be0	109	TLorentzVector lv=(TLorentzVector)lvArray->At(iIn);
36b5cc43	110	xEta[iIn] = lv->Eta();
	111	xPhi[iIn] = lv->Phi()<0 ? lv->Phi() + 2*TMath::Pi() : lv->Phi();
	112	(*vPx)(iIn)=lv->Pt();
	113	dEtSum+=(*vPx)(iIn);
7c679be0	114	}
36b5cc43	115	for (Int_t iIn=0; iIn<fNin; iIn++) (vPx)(iIn)=(vPx)(iIn)/dEtSum;
7c679be0	116
7c679be0	117	Int_t njdim=2*fNclustMax+1;
36b5cc43	118	mPyx->ResizeTo(fNin,njdim);
	119	mY->ResizeTo(4,njdim);
	120	vPy->ResizeTo(njdim);
	121	mY->Zero();mPyx->Zero();vPy->Zero();
	122	(*vPy)(0)=1;
	123	TMatrixDColumn(*mPyx,0)=1;
7c679be0	124	Double_t ypos=0,xpos=0;
7c679be0	125	for (Int_t iIn=0; iIn<fNin; iIn++){
36b5cc43	126	(mY)(0,0)+=(vPx)(iIn)*xEta[iIn];
	127	ypos+=(vPx)(iIn)TMath::Sin(xPhi[iIn]);
	128	xpos+=(vPx)(iIn)TMath::Cos(xPhi[iIn]);
7c679be0	129	}
36b5cc43	130	(mY)(1,0)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2TMath::Pi();
7c679be0	131	lvArray->Delete();
	132	}
	133
	134	//-----------------------------------------------------------------------------------
36b5cc43	135	void AliDAJetFinder::DoubleClusters(Int_t nc,Int_t &nk,TVectorD vPy,TMatrixD mY)
7c679be0	136	{
7c679be0	137	for(Int_t iClust=0; iClust<nc; iClust++){
36b5cc43	138	(vPy)(iClust)=(vPy)(iClust)/2;
	139	(vPy)(nc+iClust)=(vPy)(iClust);
	140	for(Int_t iComp=0; iComp<3; iComp++) (mY)(iComp,nc+iClust)=(mY)(iComp,iClust);
7c679be0	141	}
	142	nk=2*nc;
	143	}
	144
	145	//-----------------------------------------------------------------------------------
36b5cc43	146	void AliDAJetFinder::Annealing(Int_t nk,Double_t *xData,TVectorD vPx,TVectorD vPy,TMatrixD mPyx,TMatrixD *mY)
7c679be0	147	{
	148	// Main part of the algorithm
	149	const Double_t pi=TMath::Pi();
	150	TVectorD *py = new TVectorD(nk);
	151	TVectorD *p = new TVectorD(nk);
	152	TMatrixD *y = new TMatrixD(4,nk);
	153	TMatrixD *y1 = new TMatrixD(4,nk);
	154	TMatrixD *ry = new TMatrixD(2,nk);
36b5cc43	155	Double_t *xEta = xData[0];
36b5cc43	156	Double_t *xPhi = xData[1];
7c679be0	157	Double_t Dist(TVectorD,TVectorD);
7c679be0	158
36b5cc43	159	Double_t df[2]={fReader->GetReaderHeader()->GetFiducialEtaMax(),pi};
7c679be0	160	TVectorD vPart(2);
	161	Double_t *m = new Double_t[nk];
	162	Double_t chi,chi1;
	163	do{
	164	Int_t nloop=0;
	165	for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	166	for (Int_t i=0; i<3; i++)(y1)(i,iClust)=(mY)(i,iClust);
36b5cc43	167	(py)(iClust)=(vPy)(iClust);
7c679be0	168	}
	169	//perturbation of codevectors
	170	Double_t seed=1000000*gRandom->Rndm(24);
	171	ry->Randomize(-0.5,0.5,seed);
	172	for (Int_t i=0; i<2; i++){
	173	for (Int_t iClust=0; iClust<nk/2; iClust++)
	174	(y1)(i,iClust)+=((ry)(i,iClust)+TMath::Sign(0.5,(ry)(i,iClust)))fDelta*df[i];
	175	for (Int_t iClust=nk/2; iClust<nk; iClust++)
	176	(y1)(i,iClust)-=((ry)(i,iClust-nk/2)+TMath::Sign(0.5,(ry)(i,iClust-nk/2)))fDelta*df[i];
	177	}
	178	do{
	179	//recalculate conditional probabilities
	180	nloop++;
	181	for (Int_t iIn=0; iIn<fNin; iIn++){
36b5cc43	182	vPart(0)=xEta[iIn]; vPart(1)=xPhi[iIn];
7c679be0	183	for(Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	184	(mPyx)(iIn,iClust)=-log((py)(iClust))+fBetaDist(vPart,TMatrixDColumn(y1,iClust));
36b5cc43	185	m[iClust]=(*mPyx)(iIn,iClust);
7c679be0	186	}
	187	Double_t pyxNorm=0;
	188	Double_t minPyx=TMath::MinElement(nk,m);
	189	for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	190	(*mPyx)(iIn,iClust)-=minPyx;
	191	(mPyx)(iIn,iClust)=exp(-(mPyx)(iIn,iClust));
	192	pyxNorm+=(*mPyx)(iIn,iClust);
7c679be0	193	}
36b5cc43	194	for (Int_t iClust=0; iClust<nk; iClust++) (*mPyx)(iIn,iClust)/=pyxNorm;
7c679be0	195	}
	196	p->Zero();
	197	y->Zero();
	198	//recalculate codevectors
	199	for (Int_t iClust=0; iClust<nk; iClust++){
	200	Double_t xpos=0,ypos=0,pxy;
36b5cc43	201	for (Int_t iIn=0; iIn<fNin; iIn++) (p)(iClust)+=(vPx)(iIn)(mPyx)(iIn,iClust);
7c679be0	202	for (Int_t iIn=0; iIn<fNin; iIn++){
36b5cc43	203	pxy=(vPx)(iIn)(mPyx)(iIn,iClust)/(p)(iClust);
	204	ypos+=pxy*TMath::Sin(xPhi[iIn]);
	205	xpos+=pxy*TMath::Cos(xPhi[iIn]);
	206	(y)(0,iClust)+=pxyxEta[iIn];
7c679be0	207	}
	208	(y)(1,iClust)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2pi;
	209	}
	210	//verify codevectors' stability
	211	chi=0;
	212	for (Int_t iClust=0; iClust<nk; iClust++){
	213	chi1=TMath::CosH((y1)(0,iClust)-(y)(0,iClust))-TMath::Cos((y1)(1,iClust)-(y)(1,iClust));
	214	chi1/=(2TMath::CosH((y1)(0,iClust))TMath::CosH((y)(0,iClust)));
	215	chi1*=chi1;
	216	if (chi1>chi) chi=chi1;
	217	}
	218	chi=TMath::Sqrt(chi);
	219	for (Int_t iClust=0; iClust<nk; iClust++){
	220	for (Int_t i=0; i<2; i++) (y1)(i,iClust)=(y)(i,iClust);
	221	(py)(iClust)=(p)(iClust);
	222	}
	223	if (nloop>fNloopMax){
	224	if (chi<fEpsMax \|\| nloop>500) break;
	225	}
	226	}while (chi>fEps);
	227	}while (chi>fEpsMax);
	228	for (Int_t iClust=0; iClust<nk; iClust++){ //set codevectors and probability equal to those calculated
36b5cc43	229	for (Int_t i=0; i<2; i++) (mY)(i,iClust)=(y)(i,iClust);
36b5cc43	230	(vPy)(iClust)=(p)(iClust);
7c679be0	231	}
	232	delete py;
	233	delete p;
	234	delete y;
	235	delete y1;
	236	delete ry;
	237	delete [] m;
	238	}
	239
	240	//-----------------------------------------------------------------------------------
36b5cc43	241	void AliDAJetFinder::NumCl(Int_t &nc,Int_t &nk,TVectorD vPy,TMatrixD mPyx,TMatrixD *mY)
7c679be0	242	{
	243	static Bool_t growcl=true;
	244
	245	if (nk==2) growcl=true;
	246	if (growcl){
	247	//verify if two codevectors are equal within fAvDist
	248	Int_t *nSame = new Int_t[nk];
	249	Int_t *iSame = new Int_t[nk];
	250	Int_t *cont = new Int_t[nk];
	251	for (Int_t iClust=0; iClust<nk; iClust++) cont[iClust]=new Int_t[nk],iSame[iClust]=new Int_t[nk];
	252	for (Int_t iClust=0; iClust<nk; iClust++){
	253	iSame[iClust][iClust]=1;
	254	for (Int_t iClust1=iClust+1; iClust1<nk; iClust1++){
36b5cc43	255	Double_t eta = (mY)(0,iClust) ; Double_t phi = (mY)(1,iClust);
36b5cc43	256	Double_t eta1 = (mY)(0,iClust1); Double_t phi1 = (mY)(1,iClust1);
7c679be0	257	Double_t distCl=(TMath::CosH(eta-eta1)-TMath::Cos(phi-phi1))/(2TMath::CosH(eta)TMath::CosH(eta1));
7c679be0	258	if (distCl < fAvDist) iSame[iClust][iClust1]=iSame[iClust1][iClust]=1;
852db00e	259	else iSame[iClust][iClust1]=iSame[iClust1][iClust]=0;
7c679be0	260	}
	261	}
	262	ReduceClusters(iSame,nk,nc,cont,nSame);
	263	if (nc >= fNclustMax) growcl=false;
	264	//recalculate the nc distinct codevectors
	265	TMatrixD pyx = new TMatrixD(fNin,2nc);
	266	TVectorD *py = new TVectorD(nk);
	267	TMatrixD *y1 = new TMatrixD(3,nk);
	268	for (Int_t iClust=0; iClust<nc; iClust++){
	269	for(Int_t j=0; j<nSame[iClust]; j++){
	270	Int_t iClust1 = cont[iClust][j];
36b5cc43	271	for (Int_t iIn=0; iIn<fNin; iIn++) (pyx)(iIn,iClust)+=(mPyx)(iIn,iClust1);
	272	(py)(iClust)+=(vPy)(iClust1);
	273	for (Int_t i=0; i<2; i++) (y1)(i,iClust)+=(mY)(i,iClust1);
7c679be0	274	}
	275	for (Int_t i=0; i<2; i++) (*y1)(i,iClust)/=nSame[iClust];
	276	}
852db00e	277	for (Int_t iClust=0; iClust<nk; iClust++) delete [] cont[iClust], delete [] iSame[iClust];
	278	delete [] iSame;
	279	delete [] cont;
	280	delete [] nSame;
7c679be0	281	if (nc > nk/2){
7c679be0	282	for (Int_t iClust=0; iClust<nc; iClust++){
36b5cc43	283	for (Int_t iIn=0; iIn<fNin; iIn++) (mPyx)(iIn,iClust)=(pyx)(iIn,iClust);
	284	for (Int_t iComp=0; iComp<2; iComp++) (mY)(iComp,iClust)=(y1)(iComp,iClust);
	285	(vPy)(iClust)=(py)(iClust);
7c679be0	286	}
7c679be0	287	nk=nc;
36b5cc43	288	if (growcl) DoubleClusters(nc,nk,vPy,mY);
7c679be0	289	}
7c679be0	290	delete pyx;
	291	delete py;
	292	delete y1;
	293	}
	294
	295	}
	296
	297	//-----------------------------------------------------------------------------------
	298	void AliDAJetFinder::ReduceClusters(Int_t iSame,Int_t nc,Int_t &ncout,Int_t cont,Int_t *nSameOut)
	299	{
	300	Int_t *nSame = new Int_t[nc];
	301	Int_t *iperm = new Int_t[nc];
	302	Int_t *go = new Int_t[nc];
	303	for (Int_t iCl=0; iCl<nc; iCl++){
	304	nSame[iCl]=0;
852db00e	305	for (Int_t jCl=0; jCl<nc; jCl++) nSame[iCl]+=iSame[iCl][jCl], cont[iCl][jCl]=0;
7c679be0	306	iperm[iCl]=iCl;
	307	go[iCl]=1;
	308	}
	309	TMath::Sort(nc,nSame,iperm,true);
	310	Int_t l=0;
	311	for (Int_t iCl=0; iCl<nc; iCl++){
	312	Int_t k=iperm[iCl];
	313	if (go[k] == 1){
	314	Int_t m=0;
	315	for (Int_t jCl=0; jCl<nc; jCl++){
	316	if (iSame[k][jCl] == 1){
	317	cont[l][m]=jCl;
	318	go[jCl]=0;
	319	m++;
	320	}
	321	}
	322	nSameOut[l]=m;
	323	l++;
	324	}
	325	}
	326	ncout=l;
	327	delete [] nSame;
	328	delete [] iperm;
	329	delete [] go;
	330	}
	331
	332	//-----------------------------------------------------------------------------------
36b5cc43	333	void AliDAJetFinder::EndDetAnn(Int_t &nk,Double_t *xData,Int_t xx,Double_t etx,
36b5cc43	334	TVectorD vPx,TVectorD vPy,TMatrixD mPyx,TMatrixD mY)
7c679be0	335	{
	336	//now assign each particle to only one cluster
	337	Double_t *clusters=new Double_t[nk];
	338	for (Int_t iIn=0; iIn<fNin; iIn++){
36b5cc43	339	for (Int_t iClust=0; iClust<nk; iClust++) clusters[iClust]=(*mPyx)(iIn,iClust);
7c679be0	340	xx[iIn]=TMath::LocMax(nk,clusters);
	341	}
	342	delete [] clusters;
	343
	344	//recalculate codevectors, having all p(y\|x)=0 or 1
36b5cc43	345	Double_t *xEta = xData[0];
	346	Double_t *xPhi = xData[1];
	347	mY->Zero();
	348	mPyx->Zero();
	349	vPy->Zero();
7c679be0	350	for (Int_t iIn=0; iIn<fNin; iIn++){
7c679be0	351	Int_t iClust=xx[iIn];
36b5cc43	352	(*mPyx)(iIn,iClust)=1;
	353	(vPy)(iClust)+=(vPx)(iIn);
	354	(mY)(0,iClust)+=(vPx)(iIn)*xEta[iIn];
	355	(mY)(3,iClust)+=(vPx)(iIn)*etx;
7c679be0	356	}
	357	Int_t k=0;
	358	for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	359	if ((*vPy)(iClust)>0){
7c679be0	360	Double_t xpos=0,ypos=0,pxy;
7c679be0	361	for (Int_t iIn=0; iIn<fNin; iIn++){
36b5cc43	362	pxy=(vPx)(iIn)(mPyx)(iIn,iClust)/(vPy)(iClust);
	363	ypos+=pxy*TMath::Sin(xPhi[iIn]);
	364	xpos+=pxy*TMath::Cos(xPhi[iIn]);
7c679be0	365	if (xx[iIn]==iClust) xx[iIn]=k;
7c679be0	366	}
36b5cc43	367	(mY)(0,k)=(mY)(0,iClust)/(*vPy)(iClust);
	368	(mY)(1,k)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2TMath::Pi();
	369	(mY)(3,k)=(mY)(3,iClust);
7c679be0	370	k++;
	371	}
	372	}
	373	nk=k;
	374	}
	375
	376	//-----------------------------------------------------------------------------------
36b5cc43	377	void AliDAJetFinder::StoreJets(Int_t nk,Double_t *xData,Int_t xx,TMatrixD *mY)
7c679be0	378	{
	379	//evaluate significant clusters properties
	380	const Double_t pi=TMath::Pi();
36b5cc43	381	AliJetReaderHeader *rHeader=fReader->GetReaderHeader();
	382	Float_t dFiducialEta=rHeader->GetFiducialEtaMax()-rHeader->GetFiducialEtaMin();
	383	Double_t dMeanDist=TMath::Sqrt(2dFiducialEtapi/fNin);
	384	Double_t *xEta = xData[0];
	385	Double_t *xPhi = xData[1];
7c679be0	386	Bool_t *isJet = new Bool_t[nk];
	387	Double_t *etNoBg= new Double_t[nk];
	388	Double_t *dDeltaEta=new Double_t[nk];
	389	Double_t *dDeltaPhi=new Double_t[nk];
	390	Double_t *surf = new Double_t[nk];
	391	Double_t *etDens= new Double_t[nk];
	392	for (Int_t iClust=0; iClust<nk; iClust++){ //clusters loop
	393	isJet[iClust]=false;
	394	Double_t dEtaMin=10.,dEtaMax=-10.,dPhiMin=10.,dPhiMax=0.;
	395	for (Int_t iIn=0; iIn<fNin; iIn++){
	396	if (xx[iIn]!=iClust) continue;
36b5cc43	397	if (xEta[iIn] < dEtaMin) dEtaMin=xEta[iIn];
	398	if (xEta[iIn] > dEtaMax) dEtaMax=xEta[iIn];
	399	Double_t dPhi=xPhi[iIn]-(*mY)(1,iClust);
7c679be0	400	if (dPhi > pi ) dPhi-=2*pi;
	401	else if (dPhi < (-1)pi) dPhi+=2pi;
	402	if (dPhi < dPhiMin) dPhiMin=dPhi;
	403	else if (dPhi > dPhiMax) dPhiMax=dPhi;
	404	}
	405	dDeltaEta[iClust]=dEtaMax-dEtaMin+dMeanDist;
	406	dDeltaPhi[iClust]=dPhiMax-dPhiMin+dMeanDist;
	407	surf[iClust]=0.25pidDeltaEta[iClust]*dDeltaPhi[iClust];
36b5cc43	408	etDens[iClust]=(*mY)(3,iClust)/surf[iClust];
7c679be0	409	}
7c679be0	410
9e4cc50d	411	if (((AliDAJetHeader*)fHeader)->GetSelJets()){
7c679be0	412	for (Int_t iClust=0; iClust<nk; iClust++){
	413	if (!isJet[iClust]){
	414	Double_t etDensMed=0.;
	415	Double_t etDensSqr=0.;
	416	Int_t norm=0;
	417	for (Int_t iClust1=0; iClust1<nk; iClust1++){
	418	if(iClust1!=iClust){
	419	etDensMed+=etDens[iClust1];
	420	etDensSqr+=TMath::Power(etDens[iClust1],2);
	421	norm++;
	422	}
	423	}
	424	etDensMed/=TMath::Max(norm,1);
	425	etDensSqr/=TMath::Max(norm,1);
	426	Double_t deltaEtDens=TMath::Sqrt(etDensSqr-TMath::Power(etDensMed,2));
36b5cc43	427	if ((mY)(3,iClust) > (etDensMed+deltaEtDens)surf[iClust]) isJet[iClust]=kTRUE;
36b5cc43	428	etNoBg[iClust]=(mY)(3,iClust)-etDensMedsurf[iClust];
7c679be0	429	}
	430	}
	431	for (Int_t iClust=0; iClust<nk; iClust++){
	432	if (isJet[iClust]){
	433	Double_t etDensMed=0;
36b5cc43	434	Double_t extSurf=2dFiducialEtapi;
7c679be0	435	for (Int_t iClust1=0; iClust1<nk; iClust1++){
36b5cc43	436	if (!isJet[iClust1]) etDensMed+=(*mY)(3,iClust1);
7c679be0	437	else extSurf-=surf[iClust1];
	438	}
	439	etDensMed/=extSurf;
36b5cc43	440	etNoBg[iClust]=(mY)(3,iClust)-etDensMedsurf[iClust];
10bd125d	441	if (etNoBg[iClust]<((AliDAJetHeader*)fHeader)->GetEtMin()){
	442	isJet[iClust]=kFALSE;
	443	iClust=-1;
	444	}
7c679be0	445	}
	446	}
	447	} else {
	448	for (Int_t iClust=0; iClust<nk; iClust++) isJet[iClust]=true;
	449	}
	450	delete [] etDens;
	451	delete [] surf;
	452
	453	//now add selected jets to the list
	454	Int_t *inJet = new Int_t[fNin];
	455	TRefArray *refs = 0;
	456	Bool_t fromAod = !strcmp(fReader->ClassName(),"AliJetAODReader");
	457	if (fromAod) refs = fReader->GetReferences();
	458	for (Int_t iClust=0; iClust<nk; iClust++){ //clusters loop
	459	if (isJet[iClust]){ //choose cluster
	460	Float_t px,py,pz,en;
36b5cc43	461	px = (mY)(3,iClust)TMath::Cos((*mY)(1,iClust));
	462	py = (mY)(3,iClust)TMath::Sin((*mY)(1,iClust));
	463	pz = (mY)(3,iClust)/TMath::Tan(2.0 TMath::ATan(TMath::Exp(-(*mY)(0,iClust))));
7c679be0	464	en = TMath::Sqrt(px * px + py * py + pz * pz);
	465	AliAODJet jet(px, py, pz, en);
	466	if (fromAod)
	467	for (Int_t iIn=0; iIn<fNin; iIn++) if (xx[iIn]==iClust) jet.AddTrack(refs->At(iIn));
	468	AddJet(jet);
	469	printf("jet %d, Eta: %f, Phi: %f, Et: %f\n",iClust,jet.Eta(),jet.Phi(),jet.Pt());
	470	}
	471	}
	472	delete [] dDeltaEta; delete [] dDeltaPhi;
	473	delete [] etNoBg;
	474	delete [] isJet;
	475	delete [] inJet;
	476	}
	477
	478	//-----------------------------------------------------------------------------------
	479	Double_t Dist(TVectorD x,TVectorD y)
	480	{
	481	// Squared distance
	482	const Double_t pi=TMath::Pi();
	483	Double_t dphi=TMath::Abs(x(1)-y(1));
	484	if (dphi > pi) dphi=2*pi-dphi;
	485	Double_t dist=pow(x(0)-y(0),2)+pow(dphi,2);
	486	return dist;
	487	}