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