[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 <TRandom2.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),
	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) 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];
	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();
	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++;

	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 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++;
	}
	TRandom2 r;
	r.SetSeed(0);
	for (Int_t 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
{
	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<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)
{
	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
{
	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<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, Int_t *xx, TMatrixD *mY)
{
//evaluate significant clusters properties
	const Double_t pi=TMath::Pi();
	AliJetReaderHeader *rHeader=fReader->GetReaderHeader();
	Float_t dFidEtaMax = rHeader->GetFiducialEtaMax();
	Float_t dFidEtaMin = rHeader->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=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;
	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
		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);
			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]==iCl) jet.AddTrack(refs->At(iEn));
					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;
}
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>
386b2e2f	25	#include <TRandom2.h>
7c679be0	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),
386b2e2f	46	fNin(0),
386b2e2f	47	fNeff(0)
7c679be0	48	{
	49	// Constructor
	50	}
	51
	52	//-----------------------------------------------------------------------------------
	53	AliDAJetFinder::~AliDAJetFinder()
	54	{
	55	// Destructor
7c679be0	56	}
	57
	58	//-----------------------------------------------------------------------------------
	59	void AliDAJetFinder::FindJets()
	60	{
	61	// Find the jets in current event
	62	//
	63	Float_t betaStop=100.;
386b2e2f	64	fDebug = fHeader->GetDebug();
7c679be0	65
7c679be0	66	Double_t dEtSum=0;
36b5cc43	67	Double_t *xData[2];
386b2e2f	68	TVectorD *vPx = new TVectorD();
	69	TVectorD *vPy = new TVectorD();
	70	TMatrixD *mPyx= new TMatrixD();
	71	TMatrixD *mY = new TMatrixD();
36b5cc43	72	InitDetAnn(dEtSum,xData,vPx,vPy,mPyx,mY);
a9f9d6d5	73	if (fNin < fNclustMax) return;
7c679be0	74
36b5cc43	75	Int_t nc=1, nk;
36b5cc43	76	DoubleClusters(nc,nk,vPy,mY);
7c679be0	77	do{ //loop over beta
7c679be0	78	fBeta*=fAlpha;
36b5cc43	79	Annealing(nk,xData,vPx,vPy,mPyx,mY);
36b5cc43	80	NumCl(nc,nk,vPy,mPyx,mY);
7c679be0	81	}while((fBeta<betaStop \|\| nc<4) && nc<fNclustMax);
7c679be0	82
386b2e2f	83	Int_t *xx=new Int_t[fNeff];
36b5cc43	84	EndDetAnn(nk,xData,xx,dEtSum,vPx,vPy,mPyx,mY);
36b5cc43	85	StoreJets(nk,xData,xx,mY);
7c679be0	86	delete [] xx;
7c679be0	87
36b5cc43	88	delete [] xData[0], delete [] xData[1];
	89	delete mPyx;
	90	delete mY;
	91	delete vPx;
	92	delete vPy;
	93
7c679be0	94	}
	95
	96	//-----------------------------------------------------------------------------------
36b5cc43	97	void AliDAJetFinder::InitDetAnn(Double_t &dEtSum,Double_t *xData,TVectorD vPx,TVectorD vPy,TMatrixD mPyx,TMatrixD *mY)
7c679be0	98	{
	99	//Initialise the variables used by the algorithm
	100	fBeta=0.1;
386b2e2f	101	fNclustMax = ((AliDAJetHeader*)fHeader)->GetFixedCl() ?
36b5cc43	102	((AliDAJetHeader*)fHeader)->GetNclustMax() :
9e4cc50d	103	TMath::Max((Int_t)TMath::Sqrt(fNin),5);
386b2e2f	104	Float_t etaEff = ((AliDAJetHeader*)fHeader)->GetEtaEff();
e53baffe	105	TClonesArray *lvArray = fReader->GetMomentumArray();
	106	Int_t nEntr = lvArray->GetEntries();
	107	fNin=0;
	108	for (Int_t iEn=0; iEn<nEntr; iEn++) if (fReader->GetCutFlag(iEn)==1) fNin++;
386b2e2f	109
	110	fNeff = ((AliDAJetHeader*)fHeader)->GetNeff();
	111	fNeff = TMath::Max(fNeff,fNin);
	112	Double_t *xEta = new Double_t[fNeff];
	113	Double_t *xPhi = new Double_t[fNeff];
36b5cc43	114	xData[0]=xEta; xData[1]=xPhi;
386b2e2f	115	vPx->ResizeTo(fNeff);
e53baffe	116	Int_t iIn=0;
	117	for (Int_t iEn=0; iEn<nEntr; iEn++){
	118	if (fReader->GetCutFlag(iEn)==0) continue;
	119	TLorentzVector lv=(TLorentzVector)lvArray->At(iEn);
36b5cc43	120	xEta[iIn] = lv->Eta();
	121	xPhi[iIn] = lv->Phi()<0 ? lv->Phi() + 2*TMath::Pi() : lv->Phi();
	122	(*vPx)(iIn)=lv->Pt();
	123	dEtSum+=(*vPx)(iIn);
e53baffe	124	iIn++;
7c679be0	125	}
386b2e2f	126	TRandom2 r;
	127	r.SetSeed(0);
	128	for (Int_t iIn=fNin; iIn<fNeff; iIn++){
	129	xEta[iIn]=r.Uniform(-1*etaEff,etaEff);
	130	xPhi[iIn]=r.Uniform(0.,2*TMath::Pi());
	131	(*vPx)(iIn)=r.Uniform(0.01,0.02);
	132	dEtSum+=(*vPx)(iIn);
	133	}
	134	for (iIn=0; iIn<fNeff; iIn++) (vPx)(iIn)=(vPx)(iIn)/dEtSum;
7c679be0	135
7c679be0	136	Int_t njdim=2*fNclustMax+1;
386b2e2f	137	mPyx->ResizeTo(fNeff,njdim);
36b5cc43	138	mY->ResizeTo(4,njdim);
	139	vPy->ResizeTo(njdim);
	140	mY->Zero();mPyx->Zero();vPy->Zero();
	141	(*vPy)(0)=1;
	142	TMatrixDColumn(*mPyx,0)=1;
7c679be0	143	Double_t ypos=0,xpos=0;
386b2e2f	144	for (iIn=0; iIn<fNeff; iIn++){
36b5cc43	145	(mY)(0,0)+=(vPx)(iIn)*xEta[iIn];
	146	ypos+=(vPx)(iIn)TMath::Sin(xPhi[iIn]);
	147	xpos+=(vPx)(iIn)TMath::Cos(xPhi[iIn]);
7c679be0	148	}
36b5cc43	149	(mY)(1,0)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2TMath::Pi();
7c679be0	150	}
	151
	152	//-----------------------------------------------------------------------------------
c0a5117c	153	void AliDAJetFinder::DoubleClusters(Int_t nc,Int_t &nk, TVectorD vPy, TMatrixD mY) const
7c679be0	154	{
7c679be0	155	for(Int_t iClust=0; iClust<nc; iClust++){
36b5cc43	156	(vPy)(iClust)=(vPy)(iClust)/2;
	157	(vPy)(nc+iClust)=(vPy)(iClust);
	158	for(Int_t iComp=0; iComp<3; iComp++) (mY)(iComp,nc+iClust)=(mY)(iComp,iClust);
7c679be0	159	}
	160	nk=2*nc;
	161	}
	162
	163	//-----------------------------------------------------------------------------------
c0a5117c	164	void AliDAJetFinder::Annealing(Int_t nk,Double_t *xData, TVectorD vPx, TVectorD vPy, TMatrixD mPyx, TMatrixD *mY)
7c679be0	165	{
	166	// Main part of the algorithm
	167	const Double_t pi=TMath::Pi();
	168	TVectorD *py = new TVectorD(nk);
	169	TVectorD *p = new TVectorD(nk);
	170	TMatrixD *y = new TMatrixD(4,nk);
	171	TMatrixD *y1 = new TMatrixD(4,nk);
	172	TMatrixD *ry = new TMatrixD(2,nk);
386b2e2f	173	Double_t *xEta = xData[0];
386b2e2f	174	Double_t *xPhi = xData[1];
7c679be0	175	Double_t Dist(TVectorD,TVectorD);
7c679be0	176
36b5cc43	177	Double_t df[2]={fReader->GetReaderHeader()->GetFiducialEtaMax(),pi};
7c679be0	178	TVectorD vPart(2);
	179	Double_t *m = new Double_t[nk];
	180	Double_t chi,chi1;
	181	do{
	182	Int_t nloop=0;
	183	for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	184	for (Int_t i=0; i<3; i++)(y1)(i,iClust)=(mY)(i,iClust);
36b5cc43	185	(py)(iClust)=(vPy)(iClust);
7c679be0	186	}
	187	//perturbation of codevectors
	188	Double_t seed=1000000*gRandom->Rndm(24);
	189	ry->Randomize(-0.5,0.5,seed);
	190	for (Int_t i=0; i<2; i++){
	191	for (Int_t iClust=0; iClust<nk/2; iClust++)
	192	(y1)(i,iClust)+=((ry)(i,iClust)+TMath::Sign(0.5,(ry)(i,iClust)))fDelta*df[i];
	193	for (Int_t iClust=nk/2; iClust<nk; iClust++)
	194	(y1)(i,iClust)-=((ry)(i,iClust-nk/2)+TMath::Sign(0.5,(ry)(i,iClust-nk/2)))fDelta*df[i];
	195	}
	196	do{
	197	//recalculate conditional probabilities
	198	nloop++;
386b2e2f	199	for (Int_t iIn=0; iIn<fNeff; iIn++){
36b5cc43	200	vPart(0)=xEta[iIn]; vPart(1)=xPhi[iIn];
7c679be0	201	for(Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	202	(mPyx)(iIn,iClust)=-log((py)(iClust))+fBetaDist(vPart,TMatrixDColumn(y1,iClust));
36b5cc43	203	m[iClust]=(*mPyx)(iIn,iClust);
7c679be0	204	}
	205	Double_t pyxNorm=0;
	206	Double_t minPyx=TMath::MinElement(nk,m);
	207	for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	208	(*mPyx)(iIn,iClust)-=minPyx;
	209	(mPyx)(iIn,iClust)=exp(-(mPyx)(iIn,iClust));
	210	pyxNorm+=(*mPyx)(iIn,iClust);
7c679be0	211	}
36b5cc43	212	for (Int_t iClust=0; iClust<nk; iClust++) (*mPyx)(iIn,iClust)/=pyxNorm;
7c679be0	213	}
	214	p->Zero();
	215	y->Zero();
	216	//recalculate codevectors
	217	for (Int_t iClust=0; iClust<nk; iClust++){
	218	Double_t xpos=0,ypos=0,pxy;
386b2e2f	219	for (Int_t iIn=0; iIn<fNeff; iIn++) (p)(iClust)+=(vPx)(iIn)(mPyx)(iIn,iClust);
386b2e2f	220	for (Int_t iIn=0; iIn<fNeff; iIn++){
36b5cc43	221	pxy=(vPx)(iIn)(mPyx)(iIn,iClust)/(p)(iClust);
	222	ypos+=pxy*TMath::Sin(xPhi[iIn]);
	223	xpos+=pxy*TMath::Cos(xPhi[iIn]);
	224	(y)(0,iClust)+=pxyxEta[iIn];
7c679be0	225	}
	226	(y)(1,iClust)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2pi;
	227	}
	228	//verify codevectors' stability
	229	chi=0;
	230	for (Int_t iClust=0; iClust<nk; iClust++){
	231	chi1=TMath::CosH((y1)(0,iClust)-(y)(0,iClust))-TMath::Cos((y1)(1,iClust)-(y)(1,iClust));
	232	chi1/=(2TMath::CosH((y1)(0,iClust))TMath::CosH((y)(0,iClust)));
	233	chi1*=chi1;
	234	if (chi1>chi) chi=chi1;
	235	}
	236	chi=TMath::Sqrt(chi);
	237	for (Int_t iClust=0; iClust<nk; iClust++){
	238	for (Int_t i=0; i<2; i++) (y1)(i,iClust)=(y)(i,iClust);
	239	(py)(iClust)=(p)(iClust);
	240	}
	241	if (nloop>fNloopMax){
	242	if (chi<fEpsMax \|\| nloop>500) break;
	243	}
	244	}while (chi>fEps);
	245	}while (chi>fEpsMax);
	246	for (Int_t iClust=0; iClust<nk; iClust++){ //set codevectors and probability equal to those calculated
36b5cc43	247	for (Int_t i=0; i<2; i++) (mY)(i,iClust)=(y)(i,iClust);
36b5cc43	248	(vPy)(iClust)=(p)(iClust);
7c679be0	249	}
	250	delete py;
	251	delete p;
	252	delete y;
	253	delete y1;
	254	delete ry;
c0a5117c	255	delete [] m;
7c679be0	256	}
	257
	258	//-----------------------------------------------------------------------------------
c0a5117c	259	void AliDAJetFinder::NumCl(Int_t &nc,Int_t &nk,TVectorD vPy, TMatrixD mPyx,TMatrixD *mY)
7c679be0	260	{
	261	static Bool_t growcl=true;
	262
	263	if (nk==2) growcl=true;
	264	if (growcl){
	265	//verify if two codevectors are equal within fAvDist
	266	Int_t *nSame = new Int_t[nk];
	267	Int_t *iSame = new Int_t[nk];
	268	Int_t *cont = new Int_t[nk];
	269	for (Int_t iClust=0; iClust<nk; iClust++) cont[iClust]=new Int_t[nk],iSame[iClust]=new Int_t[nk];
	270	for (Int_t iClust=0; iClust<nk; iClust++){
	271	iSame[iClust][iClust]=1;
	272	for (Int_t iClust1=iClust+1; iClust1<nk; iClust1++){
36b5cc43	273	Double_t eta = (mY)(0,iClust) ; Double_t phi = (mY)(1,iClust);
36b5cc43	274	Double_t eta1 = (mY)(0,iClust1); Double_t phi1 = (mY)(1,iClust1);
7c679be0	275	Double_t distCl=(TMath::CosH(eta-eta1)-TMath::Cos(phi-phi1))/(2TMath::CosH(eta)TMath::CosH(eta1));
7c679be0	276	if (distCl < fAvDist) iSame[iClust][iClust1]=iSame[iClust1][iClust]=1;
852db00e	277	else iSame[iClust][iClust1]=iSame[iClust1][iClust]=0;
7c679be0	278	}
	279	}
	280	ReduceClusters(iSame,nk,nc,cont,nSame);
	281	if (nc >= fNclustMax) growcl=false;
	282	//recalculate the nc distinct codevectors
386b2e2f	283	TMatrixD pyx = new TMatrixD(fNeff,2nc);
7c679be0	284	TVectorD *py = new TVectorD(nk);
	285	TMatrixD *y1 = new TMatrixD(3,nk);
	286	for (Int_t iClust=0; iClust<nc; iClust++){
	287	for(Int_t j=0; j<nSame[iClust]; j++){
	288	Int_t iClust1 = cont[iClust][j];
386b2e2f	289	for (Int_t iIn=0; iIn<fNeff; iIn++) (pyx)(iIn,iClust)+=(mPyx)(iIn,iClust1);
36b5cc43	290	(py)(iClust)+=(vPy)(iClust1);
36b5cc43	291	for (Int_t i=0; i<2; i++) (y1)(i,iClust)+=(mY)(i,iClust1);
7c679be0	292	}
	293	for (Int_t i=0; i<2; i++) (*y1)(i,iClust)/=nSame[iClust];
	294	}
852db00e	295	for (Int_t iClust=0; iClust<nk; iClust++) delete [] cont[iClust], delete [] iSame[iClust];
	296	delete [] iSame;
	297	delete [] cont;
	298	delete [] nSame;
7c679be0	299	if (nc > nk/2){
7c679be0	300	for (Int_t iClust=0; iClust<nc; iClust++){
386b2e2f	301	for (Int_t iIn=0; iIn<fNeff; iIn++) (mPyx)(iIn,iClust)=(pyx)(iIn,iClust);
36b5cc43	302	for (Int_t iComp=0; iComp<2; iComp++) (mY)(iComp,iClust)=(y1)(iComp,iClust);
36b5cc43	303	(vPy)(iClust)=(py)(iClust);
7c679be0	304	}
7c679be0	305	nk=nc;
36b5cc43	306	if (growcl) DoubleClusters(nc,nk,vPy,mY);
7c679be0	307	}
7c679be0	308	delete pyx;
	309	delete py;
	310	delete y1;
	311	}
	312
	313	}
	314
	315	//-----------------------------------------------------------------------------------
c0a5117c	316	void AliDAJetFinder::ReduceClusters(Int_t iSame,Int_t nc,Int_t &ncout,Int_t cont,Int_t *nSameOut) const
7c679be0	317	{
	318	Int_t *nSame = new Int_t[nc];
	319	Int_t *iperm = new Int_t[nc];
	320	Int_t *go = new Int_t[nc];
	321	for (Int_t iCl=0; iCl<nc; iCl++){
	322	nSame[iCl]=0;
852db00e	323	for (Int_t jCl=0; jCl<nc; jCl++) nSame[iCl]+=iSame[iCl][jCl], cont[iCl][jCl]=0;
7c679be0	324	iperm[iCl]=iCl;
	325	go[iCl]=1;
	326	}
	327	TMath::Sort(nc,nSame,iperm,true);
	328	Int_t l=0;
	329	for (Int_t iCl=0; iCl<nc; iCl++){
	330	Int_t k=iperm[iCl];
	331	if (go[k] == 1){
	332	Int_t m=0;
	333	for (Int_t jCl=0; jCl<nc; jCl++){
	334	if (iSame[k][jCl] == 1){
	335	cont[l][m]=jCl;
	336	go[jCl]=0;
	337	m++;
	338	}
	339	}
	340	nSameOut[l]=m;
	341	l++;
	342	}
	343	}
	344	ncout=l;
	345	delete [] nSame;
	346	delete [] iperm;
	347	delete [] go;
	348	}
	349
	350	//-----------------------------------------------------------------------------------
386b2e2f	351	void AliDAJetFinder::EndDetAnn(Int_t &nk,Double_t *xData,Int_t xx,Double_t etx,TVectorD vPx,TVectorD vPy,TMatrixD mPyx,TMatrixD mY)
7c679be0	352	{
	353	//now assign each particle to only one cluster
	354	Double_t *clusters=new Double_t[nk];
386b2e2f	355	for (Int_t iIn=0; iIn<fNeff; iIn++){
36b5cc43	356	for (Int_t iClust=0; iClust<nk; iClust++) clusters[iClust]=(*mPyx)(iIn,iClust);
7c679be0	357	xx[iIn]=TMath::LocMax(nk,clusters);
7c679be0	358	}
386b2e2f	359	delete [] clusters;
7c679be0	360
7c679be0	361	//recalculate codevectors, having all p(y\|x)=0 or 1
386b2e2f	362	Double_t *xEta = xData[0];
386b2e2f	363	Double_t *xPhi = xData[1];
36b5cc43	364	mY->Zero();
	365	mPyx->Zero();
	366	vPy->Zero();
7c679be0	367	for (Int_t iIn=0; iIn<fNin; iIn++){
7c679be0	368	Int_t iClust=xx[iIn];
36b5cc43	369	(*mPyx)(iIn,iClust)=1;
	370	(vPy)(iClust)+=(vPx)(iIn);
	371	(mY)(0,iClust)+=(vPx)(iIn)*xEta[iIn];
	372	(mY)(3,iClust)+=(vPx)(iIn)*etx;
7c679be0	373	}
	374	Int_t k=0;
	375	for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	376	if ((*vPy)(iClust)>0){
7c679be0	377	Double_t xpos=0,ypos=0,pxy;
7c679be0	378	for (Int_t iIn=0; iIn<fNin; iIn++){
36b5cc43	379	pxy=(vPx)(iIn)(mPyx)(iIn,iClust)/(vPy)(iClust);
	380	ypos+=pxy*TMath::Sin(xPhi[iIn]);
	381	xpos+=pxy*TMath::Cos(xPhi[iIn]);
7c679be0	382	if (xx[iIn]==iClust) xx[iIn]=k;
7c679be0	383	}
36b5cc43	384	(mY)(0,k)=(mY)(0,iClust)/(*vPy)(iClust);
	385	(mY)(1,k)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2TMath::Pi();
	386	(mY)(3,k)=(mY)(3,iClust);
7c679be0	387	k++;
	388	}
	389	}
	390	nk=k;
	391	}
	392
	393	//-----------------------------------------------------------------------------------
386b2e2f	394	void AliDAJetFinder::StoreJets(Int_t nk, Double_t *xData, Int_t xx, TMatrixD *mY)
7c679be0	395	{
	396	//evaluate significant clusters properties
	397	const Double_t pi=TMath::Pi();
36b5cc43	398	AliJetReaderHeader *rHeader=fReader->GetReaderHeader();
386b2e2f	399	Float_t dFidEtaMax = rHeader->GetFiducialEtaMax();
	400	Float_t dFidEtaMin = rHeader->GetFiducialEtaMin();
	401	Float_t dFiducialEta= dFidEtaMax - dFidEtaMin;
	402	Double_t *xEta = xData[0];
	403	Double_t *xPhi = xData[1];
	404	Int_t nEff = 0;
	405	for (Int_t i=0; i<fNeff; i++) if (xEta[i]<dFidEtaMax && xEta[i]>dFidEtaMin) nEff++;
	406	Double_t dMeanDist=TMath::Sqrt(2dFiducialEtapi/nEff);
7c679be0	407	Bool_t *isJet = new Bool_t[nk];
	408	Double_t *etNoBg= new Double_t[nk];
	409	Double_t *dDeltaEta=new Double_t[nk];
	410	Double_t *dDeltaPhi=new Double_t[nk];
	411	Double_t *surf = new Double_t[nk];
	412	Double_t *etDens= new Double_t[nk];
386b2e2f	413	for (Int_t iClust=0; iClust<nk; iClust++){
7c679be0	414	isJet[iClust]=false;
7c679be0	415	Double_t dEtaMin=10.,dEtaMax=-10.,dPhiMin=10.,dPhiMax=0.;
386b2e2f	416	for (Int_t iIn=0; iIn<fNeff; iIn++){
386b2e2f	417	if (xx[iIn]!=iClust \|\| xEta[iIn]>dFidEtaMax \|\| xEta[iIn]<dFidEtaMin) continue;
36b5cc43	418	if (xEta[iIn] < dEtaMin) dEtaMin=xEta[iIn];
	419	if (xEta[iIn] > dEtaMax) dEtaMax=xEta[iIn];
	420	Double_t dPhi=xPhi[iIn]-(*mY)(1,iClust);
7c679be0	421	if (dPhi > pi ) dPhi-=2*pi;
	422	else if (dPhi < (-1)pi) dPhi+=2pi;
	423	if (dPhi < dPhiMin) dPhiMin=dPhi;
	424	else if (dPhi > dPhiMax) dPhiMax=dPhi;
	425	}
	426	dDeltaEta[iClust]=dEtaMax-dEtaMin+dMeanDist;
	427	dDeltaPhi[iClust]=dPhiMax-dPhiMin+dMeanDist;
	428	surf[iClust]=0.25pidDeltaEta[iClust]*dDeltaPhi[iClust];
36b5cc43	429	etDens[iClust]=(*mY)(3,iClust)/surf[iClust];
7c679be0	430	}
7c679be0	431
9e4cc50d	432	if (((AliDAJetHeader*)fHeader)->GetSelJets()){
7c679be0	433	for (Int_t iClust=0; iClust<nk; iClust++){
386b2e2f	434	if (!isJet[iClust] && (mY)(0,iClust)<dFidEtaMax && (mY)(0,iClust)>dFidEtaMin){
7c679be0	435	Double_t etDensMed=0.;
	436	Double_t etDensSqr=0.;
	437	Int_t norm=0;
	438	for (Int_t iClust1=0; iClust1<nk; iClust1++){
386b2e2f	439	if(iClust1!=iClust && (mY)(0,iClust)<dFidEtaMax && (mY)(0,iClust)>dFidEtaMin){
7c679be0	440	etDensMed+=etDens[iClust1];
	441	etDensSqr+=TMath::Power(etDens[iClust1],2);
	442	norm++;
	443	}
	444	}
	445	etDensMed/=TMath::Max(norm,1);
	446	etDensSqr/=TMath::Max(norm,1);
	447	Double_t deltaEtDens=TMath::Sqrt(etDensSqr-TMath::Power(etDensMed,2));
36b5cc43	448	if ((mY)(3,iClust) > (etDensMed+deltaEtDens)surf[iClust]) isJet[iClust]=kTRUE;
36b5cc43	449	etNoBg[iClust]=(mY)(3,iClust)-etDensMedsurf[iClust];
7c679be0	450	}
	451	}
	452	for (Int_t iClust=0; iClust<nk; iClust++){
	453	if (isJet[iClust]){
	454	Double_t etDensMed=0;
36b5cc43	455	Double_t extSurf=2dFiducialEtapi;
7c679be0	456	for (Int_t iClust1=0; iClust1<nk; iClust1++){
36b5cc43	457	if (!isJet[iClust1]) etDensMed+=(*mY)(3,iClust1);
7c679be0	458	else extSurf-=surf[iClust1];
	459	}
	460	etDensMed/=extSurf;
36b5cc43	461	etNoBg[iClust]=(mY)(3,iClust)-etDensMedsurf[iClust];
10bd125d	462	if (etNoBg[iClust]<((AliDAJetHeader*)fHeader)->GetEtMin()){
	463	isJet[iClust]=kFALSE;
	464	iClust=-1;
	465	}
7c679be0	466	}
	467	}
	468	} else {
386b2e2f	469	for (Int_t iClust=0; iClust<nk; iClust++){
	470	isJet[iClust]=true;
	471	etNoBg[iClust]=(*mY)(3,iClust);
	472	}
7c679be0	473	}
	474	delete [] etDens;
	475	delete [] surf;
	476
	477	//now add selected jets to the list
af816924	478	Int_t *iSort = new Int_t[nk];
386b2e2f	479	TMath::Sort(nk,etNoBg,iSort,true);
386b2e2f	480	Int_t iCl = 0;
7c679be0	481	TRefArray *refs = 0;
	482	Bool_t fromAod = !strcmp(fReader->ClassName(),"AliJetAODReader");
	483	if (fromAod) refs = fReader->GetReferences();
	484	for (Int_t iClust=0; iClust<nk; iClust++){ //clusters loop
af816924	485	iCl=iSort[iClust];
af816924	486	if (isJet[iCl]){ //choose cluster
7c679be0	487	Float_t px,py,pz,en;
af816924	488	px = (mY)(3,iCl)TMath::Cos((*mY)(1,iCl));
	489	py = (mY)(3,iCl)TMath::Sin((*mY)(1,iCl));
	490	pz = (mY)(3,iCl)/TMath::Tan(2.0 TMath::ATan(TMath::Exp(-(*mY)(0,iCl))));
7c679be0	491	en = TMath::Sqrt(px * px + py * py + pz * pz);
7c679be0	492	AliAODJet jet(px, py, pz, en);
e53baffe	493	if (fromAod){
	494	Int_t iIn=0;
	495	Int_t nEntr = fReader->GetMomentumArray()->GetEntries();
	496	for (Int_t iEn=0; iEn<nEntr; iEn++){
	497	if (fReader->GetCutFlag(iEn)==0) continue;
af816924	498	if (xx[iIn]==iCl) jet.AddTrack(refs->At(iEn));
e53baffe	499	iIn++;
	500	}
	501	}
7c679be0	502	AddJet(jet);
dd677561	503	if (fDebug > 0) printf("jet %d, Eta: %f, Phi: %f, Et: %f\n",iCl,jet.Eta(),jet.Phi(),jet.Pt());
7c679be0	504	}
	505	}
	506	delete [] dDeltaEta; delete [] dDeltaPhi;
	507	delete [] etNoBg;
	508	delete [] isJet;
af816924	509	delete [] iSort;
7c679be0	510	}
	511
	512	//-----------------------------------------------------------------------------------
	513	Double_t Dist(TVectorD x,TVectorD y)
	514	{
	515	// Squared distance
	516	const Double_t pi=TMath::Pi();
	517	Double_t dphi=TMath::Abs(x(1)-y(1));
	518	if (dphi > pi) dphi=2*pi-dphi;
	519	Double_t dist=pow(x(0)-y(0),2)+pow(dphi,2);
	520	return dist;
	521	}