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

	Int_t *xx=new Int_t[fNeff];
	for (Int_t i = 0; i < fNeff; i++) xx[i] = 0;
	
	EndDetAnn(nk,xData,xx,dEtSum,vPx,vPy,mPyx,mY);
	StoreJets(nk,xData,xx,mY);
	delete [] xx;

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

}

//-----------------------------------------------------------------------------------
void AliDAJetFinder::InitDetAnn(Double_t &dEtSum,Double_t **xData,TVectorD *vPx,TVectorD *vPy,TMatrixD *mPyx,TMatrixD *mY)
{
//Initialise the variables used by the algorithm
	fBeta=0.1;
	fNclustMax = ((AliDAJetHeader*)fHeader)->GetFixedCl() ? 
	    ((AliDAJetHeader*)fHeader)->GetNclustMax() : 
	    TMath::Max((Int_t)TMath::Sqrt(fNin),5);
	Float_t etaEff = ((AliDAJetHeader*)fHeader)->GetEtaEff();
	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 (iIn=fNin; iIn<fNeff; iIn++){
		xEta[iIn]=r.Uniform(-1*etaEff,etaEff);
		xPhi[iIn]=r.Uniform(0.,2*TMath::Pi());
		(*vPx)(iIn)=r.Uniform(0.01,0.02);
		dEtSum+=(*vPx)(iIn);
	}
	for (iIn=0; iIn<fNeff; iIn++) (*vPx)(iIn)=(*vPx)(iIn)/dEtSum;

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

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

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

}

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

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

	if (((AliDAJetHeader*)fHeader)->GetSelJets()){
		for (Int_t iClust=0; iClust<nk; iClust++){
			if (!isJet[iClust] && (*mY)(0,iClust)<dFidEtaMax && (*mY)(0,iClust)>dFidEtaMin){
				Double_t etDensMed=0.;
				Double_t etDensSqr=0.;
				Int_t norm=0;
				for (Int_t iClust1=0; iClust1<nk; iClust1++){
					if(iClust1!=iClust && (*mY)(0,iClust)<dFidEtaMax && (*mY)(0,iClust)>dFidEtaMin){
						etDensMed+=etDens[iClust1];
						etDensSqr+=TMath::Power(etDens[iClust1],2);
						norm++;
					}
				}
				etDensMed/=TMath::Max(norm,1);
				etDensSqr/=TMath::Max(norm,1);
				Double_t deltaEtDens=TMath::Sqrt(etDensSqr-TMath::Power(etDensMed,2));
				if ((*mY)(3,iClust) > (etDensMed+deltaEtDens)*surf[iClust]) isJet[iClust]=kTRUE;
				etNoBg[iClust]=(*mY)(3,iClust)-etDensMed*surf[iClust];
			}
		}
		for (Int_t iClust=0; iClust<nk; iClust++){
			if (isJet[iClust]){
				Double_t etDensMed=0;
				Double_t extSurf=2*dFiducialEta*pi;
				for (Int_t iClust1=0; iClust1<nk; iClust1++){
					if (!isJet[iClust1]) etDensMed+=(*mY)(3,iClust1);
					else extSurf-=surf[iClust1];
				}
				etDensMed/=extSurf;
				etNoBg[iClust]=(*mY)(3,iClust)-etDensMed*surf[iClust];
				if (etNoBg[iClust]<((AliDAJetHeader*)fHeader)->GetEtMin()){
					isJet[iClust]=kFALSE;
					iClust=-1;
				}
			}
		}
	} else {
		for (Int_t iClust=0; iClust<nk; iClust++){
			isJet[iClust]=true;
			etNoBg[iClust]=(*mY)(3,iClust);
		}
	}
	delete [] etDens;
	delete [] surf;
	
//now add selected jets to the list
	Int_t *iSort = new Int_t[nk];
	TMath::Sort(nk,etNoBg,iSort,true);
	Int_t iCl = 0;
	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);
95345ec0	73	if (fNin < fNclustMax){
	74	delete [] xData[0], delete [] xData[1];
	75	delete vPx;
	76	delete vPy;
	77	delete mPyx;
	78	delete mY;
	79	return;
	80	}
36b5cc43	81	Int_t nc=1, nk;
36b5cc43	82	DoubleClusters(nc,nk,vPy,mY);
7c679be0	83	do{ //loop over beta
7c679be0	84	fBeta*=fAlpha;
36b5cc43	85	Annealing(nk,xData,vPx,vPy,mPyx,mY);
36b5cc43	86	NumCl(nc,nk,vPy,mPyx,mY);
7c679be0	87	}while((fBeta<betaStop \|\| nc<4) && nc<fNclustMax);
7c679be0	88
386b2e2f	89	Int_t *xx=new Int_t[fNeff];
f34058c0	90	for (Int_t i = 0; i < fNeff; i++) xx[i] = 0;
f34058c0	91
36b5cc43	92	EndDetAnn(nk,xData,xx,dEtSum,vPx,vPy,mPyx,mY);
36b5cc43	93	StoreJets(nk,xData,xx,mY);
7c679be0	94	delete [] xx;
7c679be0	95
36b5cc43	96	delete [] xData[0], delete [] xData[1];
	97	delete mPyx;
	98	delete mY;
	99	delete vPx;
	100	delete vPy;
	101
7c679be0	102	}
	103
	104	//-----------------------------------------------------------------------------------
36b5cc43	105	void AliDAJetFinder::InitDetAnn(Double_t &dEtSum,Double_t *xData,TVectorD vPx,TVectorD vPy,TMatrixD mPyx,TMatrixD *mY)
7c679be0	106	{
	107	//Initialise the variables used by the algorithm
	108	fBeta=0.1;
386b2e2f	109	fNclustMax = ((AliDAJetHeader*)fHeader)->GetFixedCl() ?
36b5cc43	110	((AliDAJetHeader*)fHeader)->GetNclustMax() :
9e4cc50d	111	TMath::Max((Int_t)TMath::Sqrt(fNin),5);
386b2e2f	112	Float_t etaEff = ((AliDAJetHeader*)fHeader)->GetEtaEff();
e53baffe	113	TClonesArray *lvArray = fReader->GetMomentumArray();
	114	Int_t nEntr = lvArray->GetEntries();
	115	fNin=0;
	116	for (Int_t iEn=0; iEn<nEntr; iEn++) if (fReader->GetCutFlag(iEn)==1) fNin++;
386b2e2f	117
	118	fNeff = ((AliDAJetHeader*)fHeader)->GetNeff();
	119	fNeff = TMath::Max(fNeff,fNin);
	120	Double_t *xEta = new Double_t[fNeff];
	121	Double_t *xPhi = new Double_t[fNeff];
36b5cc43	122	xData[0]=xEta; xData[1]=xPhi;
386b2e2f	123	vPx->ResizeTo(fNeff);
e53baffe	124	Int_t iIn=0;
	125	for (Int_t iEn=0; iEn<nEntr; iEn++){
	126	if (fReader->GetCutFlag(iEn)==0) continue;
	127	TLorentzVector lv=(TLorentzVector)lvArray->At(iEn);
36b5cc43	128	xEta[iIn] = lv->Eta();
	129	xPhi[iIn] = lv->Phi()<0 ? lv->Phi() + 2*TMath::Pi() : lv->Phi();
	130	(*vPx)(iIn)=lv->Pt();
	131	dEtSum+=(*vPx)(iIn);
e53baffe	132	iIn++;
7c679be0	133	}
386b2e2f	134	TRandom2 r;
386b2e2f	135	r.SetSeed(0);
d072acbe	136	for (iIn=fNin; iIn<fNeff; iIn++){
386b2e2f	137	xEta[iIn]=r.Uniform(-1*etaEff,etaEff);
	138	xPhi[iIn]=r.Uniform(0.,2*TMath::Pi());
	139	(*vPx)(iIn)=r.Uniform(0.01,0.02);
	140	dEtSum+=(*vPx)(iIn);
	141	}
	142	for (iIn=0; iIn<fNeff; iIn++) (vPx)(iIn)=(vPx)(iIn)/dEtSum;
7c679be0	143
7c679be0	144	Int_t njdim=2*fNclustMax+1;
386b2e2f	145	mPyx->ResizeTo(fNeff,njdim);
36b5cc43	146	mY->ResizeTo(4,njdim);
	147	vPy->ResizeTo(njdim);
	148	mY->Zero();mPyx->Zero();vPy->Zero();
	149	(*vPy)(0)=1;
	150	TMatrixDColumn(*mPyx,0)=1;
7c679be0	151	Double_t ypos=0,xpos=0;
386b2e2f	152	for (iIn=0; iIn<fNeff; iIn++){
36b5cc43	153	(mY)(0,0)+=(vPx)(iIn)*xEta[iIn];
	154	ypos+=(vPx)(iIn)TMath::Sin(xPhi[iIn]);
	155	xpos+=(vPx)(iIn)TMath::Cos(xPhi[iIn]);
7c679be0	156	}
36b5cc43	157	(mY)(1,0)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2TMath::Pi();
7c679be0	158	}
	159
	160	//-----------------------------------------------------------------------------------
1240edf5	161	void AliDAJetFinder::DoubleClusters(Int_t nc,Int_t &nk, TVectorD vPy, TMatrixD mY) const
7c679be0	162	{
1240edf5	163	// Return double clusters
7c679be0	164	for(Int_t iClust=0; iClust<nc; iClust++){
36b5cc43	165	(vPy)(iClust)=(vPy)(iClust)/2;
	166	(vPy)(nc+iClust)=(vPy)(iClust);
	167	for(Int_t iComp=0; iComp<3; iComp++) (mY)(iComp,nc+iClust)=(mY)(iComp,iClust);
7c679be0	168	}
	169	nk=2*nc;
	170	}
	171
	172	//-----------------------------------------------------------------------------------
c0a5117c	173	void AliDAJetFinder::Annealing(Int_t nk,Double_t *xData, TVectorD vPx, TVectorD vPy, TMatrixD mPyx, TMatrixD *mY)
7c679be0	174	{
	175	// Main part of the algorithm
	176	const Double_t pi=TMath::Pi();
	177	TVectorD *py = new TVectorD(nk);
	178	TVectorD *p = new TVectorD(nk);
	179	TMatrixD *y = new TMatrixD(4,nk);
	180	TMatrixD *y1 = new TMatrixD(4,nk);
	181	TMatrixD *ry = new TMatrixD(2,nk);
386b2e2f	182	Double_t *xEta = xData[0];
386b2e2f	183	Double_t *xPhi = xData[1];
7c679be0	184	Double_t Dist(TVectorD,TVectorD);
7c679be0	185
36b5cc43	186	Double_t df[2]={fReader->GetReaderHeader()->GetFiducialEtaMax(),pi};
7c679be0	187	TVectorD vPart(2);
	188	Double_t *m = new Double_t[nk];
	189	Double_t chi,chi1;
	190	do{
	191	Int_t nloop=0;
	192	for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	193	for (Int_t i=0; i<3; i++)(y1)(i,iClust)=(mY)(i,iClust);
36b5cc43	194	(py)(iClust)=(vPy)(iClust);
7c679be0	195	}
	196	//perturbation of codevectors
	197	Double_t seed=1000000*gRandom->Rndm(24);
	198	ry->Randomize(-0.5,0.5,seed);
	199	for (Int_t i=0; i<2; i++){
	200	for (Int_t iClust=0; iClust<nk/2; iClust++)
	201	(y1)(i,iClust)+=((ry)(i,iClust)+TMath::Sign(0.5,(ry)(i,iClust)))fDelta*df[i];
	202	for (Int_t iClust=nk/2; iClust<nk; iClust++)
	203	(y1)(i,iClust)-=((ry)(i,iClust-nk/2)+TMath::Sign(0.5,(ry)(i,iClust-nk/2)))fDelta*df[i];
	204	}
	205	do{
	206	//recalculate conditional probabilities
	207	nloop++;
386b2e2f	208	for (Int_t iIn=0; iIn<fNeff; iIn++){
36b5cc43	209	vPart(0)=xEta[iIn]; vPart(1)=xPhi[iIn];
7c679be0	210	for(Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	211	(mPyx)(iIn,iClust)=-log((py)(iClust))+fBetaDist(vPart,TMatrixDColumn(y1,iClust));
36b5cc43	212	m[iClust]=(*mPyx)(iIn,iClust);
7c679be0	213	}
	214	Double_t pyxNorm=0;
	215	Double_t minPyx=TMath::MinElement(nk,m);
	216	for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	217	(*mPyx)(iIn,iClust)-=minPyx;
	218	(mPyx)(iIn,iClust)=exp(-(mPyx)(iIn,iClust));
	219	pyxNorm+=(*mPyx)(iIn,iClust);
7c679be0	220	}
36b5cc43	221	for (Int_t iClust=0; iClust<nk; iClust++) (*mPyx)(iIn,iClust)/=pyxNorm;
7c679be0	222	}
	223	p->Zero();
	224	y->Zero();
	225	//recalculate codevectors
	226	for (Int_t iClust=0; iClust<nk; iClust++){
	227	Double_t xpos=0,ypos=0,pxy;
386b2e2f	228	for (Int_t iIn=0; iIn<fNeff; iIn++) (p)(iClust)+=(vPx)(iIn)(mPyx)(iIn,iClust);
386b2e2f	229	for (Int_t iIn=0; iIn<fNeff; iIn++){
36b5cc43	230	pxy=(vPx)(iIn)(mPyx)(iIn,iClust)/(p)(iClust);
	231	ypos+=pxy*TMath::Sin(xPhi[iIn]);
	232	xpos+=pxy*TMath::Cos(xPhi[iIn]);
	233	(y)(0,iClust)+=pxyxEta[iIn];
7c679be0	234	}
	235	(y)(1,iClust)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2pi;
	236	}
	237	//verify codevectors' stability
	238	chi=0;
	239	for (Int_t iClust=0; iClust<nk; iClust++){
	240	chi1=TMath::CosH((y1)(0,iClust)-(y)(0,iClust))-TMath::Cos((y1)(1,iClust)-(y)(1,iClust));
	241	chi1/=(2TMath::CosH((y1)(0,iClust))TMath::CosH((y)(0,iClust)));
	242	chi1*=chi1;
	243	if (chi1>chi) chi=chi1;
	244	}
	245	chi=TMath::Sqrt(chi);
	246	for (Int_t iClust=0; iClust<nk; iClust++){
	247	for (Int_t i=0; i<2; i++) (y1)(i,iClust)=(y)(i,iClust);
	248	(py)(iClust)=(p)(iClust);
	249	}
	250	if (nloop>fNloopMax){
	251	if (chi<fEpsMax \|\| nloop>500) break;
	252	}
	253	}while (chi>fEps);
	254	}while (chi>fEpsMax);
	255	for (Int_t iClust=0; iClust<nk; iClust++){ //set codevectors and probability equal to those calculated
36b5cc43	256	for (Int_t i=0; i<2; i++) (mY)(i,iClust)=(y)(i,iClust);
36b5cc43	257	(vPy)(iClust)=(p)(iClust);
7c679be0	258	}
	259	delete py;
	260	delete p;
	261	delete y;
	262	delete y1;
	263	delete ry;
c0a5117c	264	delete [] m;
7c679be0	265	}
	266
	267	//-----------------------------------------------------------------------------------
c0a5117c	268	void AliDAJetFinder::NumCl(Int_t &nc,Int_t &nk,TVectorD vPy, TMatrixD mPyx,TMatrixD *mY)
7c679be0	269	{
1240edf5	270	// Number of clusters
7c679be0	271	static Bool_t growcl=true;
	272
	273	if (nk==2) growcl=true;
	274	if (growcl){
	275	//verify if two codevectors are equal within fAvDist
	276	Int_t *nSame = new Int_t[nk];
	277	Int_t *iSame = new Int_t[nk];
	278	Int_t *cont = new Int_t[nk];
f34058c0	279	for (Int_t iClust=0; iClust<nk; iClust++) {
	280	cont[iClust] =new Int_t[nk];
	281	iSame[iClust]=new Int_t[nk];
	282	}
	283
7c679be0	284	for (Int_t iClust=0; iClust<nk; iClust++){
	285	iSame[iClust][iClust]=1;
	286	for (Int_t iClust1=iClust+1; iClust1<nk; iClust1++){
36b5cc43	287	Double_t eta = (mY)(0,iClust) ; Double_t phi = (mY)(1,iClust);
36b5cc43	288	Double_t eta1 = (mY)(0,iClust1); Double_t phi1 = (mY)(1,iClust1);
7c679be0	289	Double_t distCl=(TMath::CosH(eta-eta1)-TMath::Cos(phi-phi1))/(2TMath::CosH(eta)TMath::CosH(eta1));
7c679be0	290	if (distCl < fAvDist) iSame[iClust][iClust1]=iSame[iClust1][iClust]=1;
852db00e	291	else iSame[iClust][iClust1]=iSame[iClust1][iClust]=0;
7c679be0	292	}
	293	}
	294	ReduceClusters(iSame,nk,nc,cont,nSame);
	295	if (nc >= fNclustMax) growcl=false;
	296	//recalculate the nc distinct codevectors
386b2e2f	297	TMatrixD pyx = new TMatrixD(fNeff,2nc);
7c679be0	298	TVectorD *py = new TVectorD(nk);
	299	TMatrixD *y1 = new TMatrixD(3,nk);
	300	for (Int_t iClust=0; iClust<nc; iClust++){
	301	for(Int_t j=0; j<nSame[iClust]; j++){
	302	Int_t iClust1 = cont[iClust][j];
386b2e2f	303	for (Int_t iIn=0; iIn<fNeff; iIn++) (pyx)(iIn,iClust)+=(mPyx)(iIn,iClust1);
36b5cc43	304	(py)(iClust)+=(vPy)(iClust1);
36b5cc43	305	for (Int_t i=0; i<2; i++) (y1)(i,iClust)+=(mY)(i,iClust1);
7c679be0	306	}
	307	for (Int_t i=0; i<2; i++) (*y1)(i,iClust)/=nSame[iClust];
	308	}
852db00e	309	for (Int_t iClust=0; iClust<nk; iClust++) delete [] cont[iClust], delete [] iSame[iClust];
	310	delete [] iSame;
	311	delete [] cont;
	312	delete [] nSame;
7c679be0	313	if (nc > nk/2){
7c679be0	314	for (Int_t iClust=0; iClust<nc; iClust++){
386b2e2f	315	for (Int_t iIn=0; iIn<fNeff; iIn++) (mPyx)(iIn,iClust)=(pyx)(iIn,iClust);
36b5cc43	316	for (Int_t iComp=0; iComp<2; iComp++) (mY)(iComp,iClust)=(y1)(iComp,iClust);
36b5cc43	317	(vPy)(iClust)=(py)(iClust);
7c679be0	318	}
7c679be0	319	nk=nc;
36b5cc43	320	if (growcl) DoubleClusters(nc,nk,vPy,mY);
7c679be0	321	}
7c679be0	322	delete pyx;
	323	delete py;
	324	delete y1;
	325	}
	326
	327	}
	328
	329	//-----------------------------------------------------------------------------------
c0a5117c	330	void AliDAJetFinder::ReduceClusters(Int_t iSame,Int_t nc,Int_t &ncout,Int_t cont,Int_t *nSameOut) const
7c679be0	331	{
1240edf5	332	// Reduction step
7c679be0	333	Int_t *nSame = new Int_t[nc];
	334	Int_t *iperm = new Int_t[nc];
	335	Int_t *go = new Int_t[nc];
	336	for (Int_t iCl=0; iCl<nc; iCl++){
	337	nSame[iCl]=0;
852db00e	338	for (Int_t jCl=0; jCl<nc; jCl++) nSame[iCl]+=iSame[iCl][jCl], cont[iCl][jCl]=0;
7c679be0	339	iperm[iCl]=iCl;
	340	go[iCl]=1;
	341	}
	342	TMath::Sort(nc,nSame,iperm,true);
	343	Int_t l=0;
	344	for (Int_t iCl=0; iCl<nc; iCl++){
	345	Int_t k=iperm[iCl];
	346	if (go[k] == 1){
	347	Int_t m=0;
	348	for (Int_t jCl=0; jCl<nc; jCl++){
	349	if (iSame[k][jCl] == 1){
	350	cont[l][m]=jCl;
	351	go[jCl]=0;
	352	m++;
	353	}
	354	}
	355	nSameOut[l]=m;
	356	l++;
	357	}
	358	}
	359	ncout=l;
	360	delete [] nSame;
	361	delete [] iperm;
	362	delete [] go;
	363	}
	364
	365	//-----------------------------------------------------------------------------------
386b2e2f	366	void AliDAJetFinder::EndDetAnn(Int_t &nk,Double_t *xData,Int_t xx,Double_t etx,TVectorD vPx,TVectorD vPy,TMatrixD mPyx,TMatrixD mY)
7c679be0	367	{
	368	//now assign each particle to only one cluster
	369	Double_t *clusters=new Double_t[nk];
386b2e2f	370	for (Int_t iIn=0; iIn<fNeff; iIn++){
36b5cc43	371	for (Int_t iClust=0; iClust<nk; iClust++) clusters[iClust]=(*mPyx)(iIn,iClust);
7c679be0	372	xx[iIn]=TMath::LocMax(nk,clusters);
7c679be0	373	}
386b2e2f	374	delete [] clusters;
7c679be0	375
7c679be0	376	//recalculate codevectors, having all p(y\|x)=0 or 1
386b2e2f	377	Double_t *xEta = xData[0];
386b2e2f	378	Double_t *xPhi = xData[1];
36b5cc43	379	mY->Zero();
	380	mPyx->Zero();
	381	vPy->Zero();
7c679be0	382	for (Int_t iIn=0; iIn<fNin; iIn++){
7c679be0	383	Int_t iClust=xx[iIn];
36b5cc43	384	(*mPyx)(iIn,iClust)=1;
	385	(vPy)(iClust)+=(vPx)(iIn);
	386	(mY)(0,iClust)+=(vPx)(iIn)*xEta[iIn];
	387	(mY)(3,iClust)+=(vPx)(iIn)*etx;
7c679be0	388	}
	389	Int_t k=0;
	390	for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43	391	if ((*vPy)(iClust)>0){
7c679be0	392	Double_t xpos=0,ypos=0,pxy;
7c679be0	393	for (Int_t iIn=0; iIn<fNin; iIn++){
36b5cc43	394	pxy=(vPx)(iIn)(mPyx)(iIn,iClust)/(vPy)(iClust);
	395	ypos+=pxy*TMath::Sin(xPhi[iIn]);
	396	xpos+=pxy*TMath::Cos(xPhi[iIn]);
7c679be0	397	if (xx[iIn]==iClust) xx[iIn]=k;
7c679be0	398	}
36b5cc43	399	(mY)(0,k)=(mY)(0,iClust)/(*vPy)(iClust);
	400	(mY)(1,k)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2TMath::Pi();
	401	(mY)(3,k)=(mY)(3,iClust);
7c679be0	402	k++;
	403	}
	404	}
	405	nk=k;
	406	}
	407
	408	//-----------------------------------------------------------------------------------
386b2e2f	409	void AliDAJetFinder::StoreJets(Int_t nk, Double_t *xData, Int_t xx, TMatrixD *mY)
7c679be0	410	{
	411	//evaluate significant clusters properties
	412	const Double_t pi=TMath::Pi();
36b5cc43	413	AliJetReaderHeader *rHeader=fReader->GetReaderHeader();
386b2e2f	414	Float_t dFidEtaMax = rHeader->GetFiducialEtaMax();
	415	Float_t dFidEtaMin = rHeader->GetFiducialEtaMin();
	416	Float_t dFiducialEta= dFidEtaMax - dFidEtaMin;
	417	Double_t *xEta = xData[0];
	418	Double_t *xPhi = xData[1];
	419	Int_t nEff = 0;
	420	for (Int_t i=0; i<fNeff; i++) if (xEta[i]<dFidEtaMax && xEta[i]>dFidEtaMin) nEff++;
f8ec9e37	421	Double_t dMeanDist=0.;
	422	if (nEff > 0)
	423	dMeanDist=TMath::Sqrt(2dFiducialEtapi/nEff);
7c679be0	424	Bool_t *isJet = new Bool_t[nk];
	425	Double_t *etNoBg= new Double_t[nk];
	426	Double_t *dDeltaEta=new Double_t[nk];
	427	Double_t *dDeltaPhi=new Double_t[nk];
	428	Double_t *surf = new Double_t[nk];
	429	Double_t *etDens= new Double_t[nk];
386b2e2f	430	for (Int_t iClust=0; iClust<nk; iClust++){
7c679be0	431	isJet[iClust]=false;
7c679be0	432	Double_t dEtaMin=10.,dEtaMax=-10.,dPhiMin=10.,dPhiMax=0.;
386b2e2f	433	for (Int_t iIn=0; iIn<fNeff; iIn++){
386b2e2f	434	if (xx[iIn]!=iClust \|\| xEta[iIn]>dFidEtaMax \|\| xEta[iIn]<dFidEtaMin) continue;
36b5cc43	435	if (xEta[iIn] < dEtaMin) dEtaMin=xEta[iIn];
	436	if (xEta[iIn] > dEtaMax) dEtaMax=xEta[iIn];
	437	Double_t dPhi=xPhi[iIn]-(*mY)(1,iClust);
7c679be0	438	if (dPhi > pi ) dPhi-=2*pi;
	439	else if (dPhi < (-1)pi) dPhi+=2pi;
	440	if (dPhi < dPhiMin) dPhiMin=dPhi;
	441	else if (dPhi > dPhiMax) dPhiMax=dPhi;
	442	}
	443	dDeltaEta[iClust]=dEtaMax-dEtaMin+dMeanDist;
	444	dDeltaPhi[iClust]=dPhiMax-dPhiMin+dMeanDist;
	445	surf[iClust]=0.25pidDeltaEta[iClust]*dDeltaPhi[iClust];
36b5cc43	446	etDens[iClust]=(*mY)(3,iClust)/surf[iClust];
7c679be0	447	}
7c679be0	448
9e4cc50d	449	if (((AliDAJetHeader*)fHeader)->GetSelJets()){
7c679be0	450	for (Int_t iClust=0; iClust<nk; iClust++){
386b2e2f	451	if (!isJet[iClust] && (mY)(0,iClust)<dFidEtaMax && (mY)(0,iClust)>dFidEtaMin){
7c679be0	452	Double_t etDensMed=0.;
	453	Double_t etDensSqr=0.;
	454	Int_t norm=0;
	455	for (Int_t iClust1=0; iClust1<nk; iClust1++){
386b2e2f	456	if(iClust1!=iClust && (mY)(0,iClust)<dFidEtaMax && (mY)(0,iClust)>dFidEtaMin){
7c679be0	457	etDensMed+=etDens[iClust1];
	458	etDensSqr+=TMath::Power(etDens[iClust1],2);
	459	norm++;
	460	}
	461	}
	462	etDensMed/=TMath::Max(norm,1);
	463	etDensSqr/=TMath::Max(norm,1);
	464	Double_t deltaEtDens=TMath::Sqrt(etDensSqr-TMath::Power(etDensMed,2));
36b5cc43	465	if ((mY)(3,iClust) > (etDensMed+deltaEtDens)surf[iClust]) isJet[iClust]=kTRUE;
36b5cc43	466	etNoBg[iClust]=(mY)(3,iClust)-etDensMedsurf[iClust];
7c679be0	467	}
	468	}
	469	for (Int_t iClust=0; iClust<nk; iClust++){
	470	if (isJet[iClust]){
	471	Double_t etDensMed=0;
36b5cc43	472	Double_t extSurf=2dFiducialEtapi;
7c679be0	473	for (Int_t iClust1=0; iClust1<nk; iClust1++){
36b5cc43	474	if (!isJet[iClust1]) etDensMed+=(*mY)(3,iClust1);
7c679be0	475	else extSurf-=surf[iClust1];
	476	}
	477	etDensMed/=extSurf;
36b5cc43	478	etNoBg[iClust]=(mY)(3,iClust)-etDensMedsurf[iClust];
10bd125d	479	if (etNoBg[iClust]<((AliDAJetHeader*)fHeader)->GetEtMin()){
	480	isJet[iClust]=kFALSE;
	481	iClust=-1;
	482	}
7c679be0	483	}
	484	}
	485	} else {
386b2e2f	486	for (Int_t iClust=0; iClust<nk; iClust++){
	487	isJet[iClust]=true;
	488	etNoBg[iClust]=(*mY)(3,iClust);
	489	}
7c679be0	490	}
	491	delete [] etDens;
	492	delete [] surf;
	493
	494	//now add selected jets to the list
af816924	495	Int_t *iSort = new Int_t[nk];
386b2e2f	496	TMath::Sort(nk,etNoBg,iSort,true);
386b2e2f	497	Int_t iCl = 0;
7c679be0	498	TRefArray *refs = 0;
	499	Bool_t fromAod = !strcmp(fReader->ClassName(),"AliJetAODReader");
	500	if (fromAod) refs = fReader->GetReferences();
	501	for (Int_t iClust=0; iClust<nk; iClust++){ //clusters loop
af816924	502	iCl=iSort[iClust];
af816924	503	if (isJet[iCl]){ //choose cluster
7c679be0	504	Float_t px,py,pz,en;
af816924	505	px = (mY)(3,iCl)TMath::Cos((*mY)(1,iCl));
	506	py = (mY)(3,iCl)TMath::Sin((*mY)(1,iCl));
	507	pz = (mY)(3,iCl)/TMath::Tan(2.0 TMath::ATan(TMath::Exp(-(*mY)(0,iCl))));
7c679be0	508	en = TMath::Sqrt(px * px + py * py + pz * pz);
7c679be0	509	AliAODJet jet(px, py, pz, en);
e53baffe	510	if (fromAod){
	511	Int_t iIn=0;
	512	Int_t nEntr = fReader->GetMomentumArray()->GetEntries();
	513	for (Int_t iEn=0; iEn<nEntr; iEn++){
	514	if (fReader->GetCutFlag(iEn)==0) continue;
af816924	515	if (xx[iIn]==iCl) jet.AddTrack(refs->At(iEn));
e53baffe	516	iIn++;
	517	}
	518	}
7c679be0	519	AddJet(jet);
dd677561	520	if (fDebug > 0) printf("jet %d, Eta: %f, Phi: %f, Et: %f\n",iCl,jet.Eta(),jet.Phi(),jet.Pt());
7c679be0	521	}
	522	}
	523	delete [] dDeltaEta; delete [] dDeltaPhi;
	524	delete [] etNoBg;
	525	delete [] isJet;
af816924	526	delete [] iSort;
7c679be0	527	}
	528
	529	//-----------------------------------------------------------------------------------
	530	Double_t Dist(TVectorD x,TVectorD y)
	531	{
	532	// Squared distance
	533	const Double_t pi=TMath::Pi();
	534	Double_t dphi=TMath::Abs(x(1)-y(1));
	535	if (dphi > pi) dphi=2*pi-dphi;
	536	Double_t dist=pow(x(0)-y(0),2)+pow(dphi,2);
	537	return dist;
	538	}