JETAN/AliDAJetFinder.cxx

   1
   2 //  **************************************************************************
   3 //  * Copyright(c) 1998-1999, ALICE Experiment at CERN, All rights reserved. *
   4 //  *                                                                        *
   5 //  * Author: The ALICE Off-line Project.                                    *
   6 //  * Contributors are mentioned in the code where appropriate.              *
   7 //  *                                                                        *
   8 //  * Permission to use, copy, modify and distribute this software and its   *
   9 //  * documentation strictly for non-commercial purposes is hereby granted   *
  10 //  * without fee, provided that the above copyright notice appears in all   *
  11 //  * copies and that both the copyright notice and this permission notice   *
  12 //  * appear in the supporting documentation. The authors make no claims     *
  13 //  * about the suitability of this software for any purpose. It is          *
  14 //  * provided "as is" without express or implied warranty.                  *
  15 //  **************************************************************************
  16
  17 //-----------------------------------------------------------------------------------
  18 // Jet finder based on Deterministic Annealing
  19 // For further informations about the DA working features see:
  20 // Phys.Lett. B601 (2004) 56-63 (http://arxiv.org/abs/hep-ph/0407214)
  21 // Author: Davide Perrino (davide.perrino@ba.infn.it, davide.perrino@cern.ch)
  22 //-----------------------------------------------------------------------------------
  23
  24 #include <TMath.h>
  25 #include <TRandom2.h>
  26 #include <TClonesArray.h>
  27 #include "AliJetReaderHeader.h"
  28 #include "AliJetReader.h"
  29 #include "AliDAJetHeader.h"
  30 #include "AliDAJetFinder.h"
  31
  32 ClassImp(AliDAJetFinder)
  33
  34
  35 //-----------------------------------------------------------------------------------
  36 AliDAJetFinder::AliDAJetFinder():
  37         AliJetFinder(),
  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),
  46         fNin(0),
  47         fNeff(0)
  48 {
  49         // Constructor
  50 }
  51
  52 //-----------------------------------------------------------------------------------
  53 AliDAJetFinder::~AliDAJetFinder()
  54 {
  55         // Destructor
  56 }
  57
  58 //-----------------------------------------------------------------------------------
  59 void AliDAJetFinder::FindJets()
  60 {
  61 // Find the jets in current event
  62 //
  63         Float_t betaStop=100.;
  64         fDebug = fHeader->GetDebug();
  65
  66         Double_t dEtSum=0;
  67         Double_t *xData[2];
  68         TVectorD *vPx = new TVectorD();
  69         TVectorD *vPy = new TVectorD();
  70         TMatrixD *mPyx= new TMatrixD();
  71         TMatrixD *mY  = new TMatrixD();
  72         InitDetAnn(dEtSum,xData,vPx,vPy,mPyx,mY);
  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         }
  81         Int_t nc=1, nk;
  82         DoubleClusters(nc,nk,vPy,mY);
  83         do{                                     //loop over beta
  84                 fBeta*=fAlpha;
  85                 Annealing(nk,xData,vPx,vPy,mPyx,mY);
  86                 NumCl(nc,nk,vPy,mPyx,mY);
  87         }while((fBeta<betaStop || nc<4) && nc<fNclustMax);
  88
  89         Int_t *xx=new Int_t[fNeff];
  90         EndDetAnn(nk,xData,xx,dEtSum,vPx,vPy,mPyx,mY);
  91         StoreJets(nk,xData,xx,mY);
  92         delete [] xx;
  93
  94         delete [] xData[0], delete [] xData[1];
  95         delete mPyx;
  96         delete mY;
  97         delete vPx;
  98         delete vPy;
  99
 100 }
 101
 102 //-----------------------------------------------------------------------------------
 103 void AliDAJetFinder::InitDetAnn(Double_t &dEtSum,Double_t **xData,TVectorD *vPx,TVectorD *vPy,TMatrixD *mPyx,TMatrixD *mY)
 104 {
 105 //Initialise the variables used by the algorithm
 106         fBeta=0.1;
 107         fNclustMax = ((AliDAJetHeader*)fHeader)->GetFixedCl() ?
 108             ((AliDAJetHeader*)fHeader)->GetNclustMax() :
 109             TMath::Max((Int_t)TMath::Sqrt(fNin),5);
 110         Float_t etaEff = ((AliDAJetHeader*)fHeader)->GetEtaEff();
 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++;
 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];
 120         xData[0]=xEta; xData[1]=xPhi;
 121         vPx->ResizeTo(fNeff);
 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);
 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);
 130                 iIn++;
 131         }
 132         TRandom2 r;
 133         r.SetSeed(0);
 134         for (iIn=fNin; iIn<fNeff; iIn++){
 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;
 141
 142         Int_t njdim=2*fNclustMax+1;
 143         mPyx->ResizeTo(fNeff,njdim);
 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;
 149         Double_t ypos=0,xpos=0;
 150         for (iIn=0; iIn<fNeff; iIn++){
 151                 (*mY)(0,0)+=(*vPx)(iIn)*xEta[iIn];
 152                 ypos+=(*vPx)(iIn)*TMath::Sin(xPhi[iIn]);
 153                 xpos+=(*vPx)(iIn)*TMath::Cos(xPhi[iIn]);
 154         }
 155         (*mY)(1,0)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2*TMath::Pi();
 156 }
 157
 158 //-----------------------------------------------------------------------------------
 159 void AliDAJetFinder::DoubleClusters(Int_t nc,Int_t &nk,  TVectorD *vPy, TMatrixD *mY) const
 160 {
 161 // Return double clusters
 162         for(Int_t iClust=0; iClust<nc; iClust++){
 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);
 166         }
 167         nk=2*nc;
 168 }
 169
 170 //-----------------------------------------------------------------------------------
 171 void AliDAJetFinder::Annealing(Int_t nk,Double_t **xData,  TVectorD *vPx,  TVectorD *vPy,  TMatrixD *mPyx,  TMatrixD *mY)
 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);
 180         Double_t *xEta = xData[0];
 181         Double_t *xPhi = xData[1];
 182         Double_t Dist(TVectorD,TVectorD);
 183
 184         Double_t df[2]={fReader->GetReaderHeader()->GetFiducialEtaMax(),pi};
 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++){
 191                         for (Int_t i=0; i<3; i++)(*y1)(i,iClust)=(*mY)(i,iClust);
 192                         (*py)(iClust)=(*vPy)(iClust);
 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++;
 206                         for (Int_t iIn=0; iIn<fNeff; iIn++){
 207                                 vPart(0)=xEta[iIn]; vPart(1)=xPhi[iIn];
 208                                 for(Int_t iClust=0; iClust<nk; iClust++){
 209                                         (*mPyx)(iIn,iClust)=-log((*py)(iClust))+fBeta*Dist(vPart,TMatrixDColumn(*y1,iClust));
 210                                         m[iClust]=(*mPyx)(iIn,iClust);
 211                                 }
 212                                 Double_t pyxNorm=0;
 213                                 Double_t minPyx=TMath::MinElement(nk,m);
 214                                 for (Int_t iClust=0; iClust<nk; iClust++){
 215                                         (*mPyx)(iIn,iClust)-=minPyx;
 216                                         (*mPyx)(iIn,iClust)=exp(-(*mPyx)(iIn,iClust));
 217                                         pyxNorm+=(*mPyx)(iIn,iClust);
 218                                 }
 219                                 for (Int_t iClust=0; iClust<nk; iClust++) (*mPyx)(iIn,iClust)/=pyxNorm;
 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;
 226                                 for (Int_t iIn=0; iIn<fNeff; iIn++) (*p)(iClust)+=(*vPx)(iIn)*(*mPyx)(iIn,iClust);
 227                                 for (Int_t iIn=0; iIn<fNeff; iIn++){
 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)+=pxy*xEta[iIn];
 232                                 }
 233                                 (*y)(1,iClust)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2*pi;
 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/=(2*TMath::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
 254                 for (Int_t i=0; i<2; i++) (*mY)(i,iClust)=(*y)(i,iClust);
 255                 (*vPy)(iClust)=(*p)(iClust);
 256         }
 257     delete py;
 258     delete p;
 259     delete y;
 260     delete y1;
 261     delete ry;
 262     delete [] m;
 263 }
 264
 265 //-----------------------------------------------------------------------------------
 266 void AliDAJetFinder::NumCl(Int_t &nc,Int_t &nk,TVectorD *vPy,  TMatrixD *mPyx,TMatrixD *mY)
 267 {
 268     // Number of clusters
 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++){
 281                                 Double_t eta  = (*mY)(0,iClust) ; Double_t phi  = (*mY)(1,iClust);
 282                                 Double_t eta1 = (*mY)(0,iClust1); Double_t phi1 = (*mY)(1,iClust1);
 283                                 Double_t distCl=(TMath::CosH(eta-eta1)-TMath::Cos(phi-phi1))/(2*TMath::CosH(eta)*TMath::CosH(eta1));
 284                                 if (distCl < fAvDist) iSame[iClust][iClust1]=iSame[iClust1][iClust]=1;
 285                                 else iSame[iClust][iClust1]=iSame[iClust1][iClust]=0;
 286                         }
 287                 }
 288                 ReduceClusters(iSame,nk,nc,cont,nSame);
 289                 if (nc >= fNclustMax) growcl=false;
 290 //recalculate the nc distinct codevectors
 291                 TMatrixD *pyx = new TMatrixD(fNeff,2*nc);
 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];
 297                                 for (Int_t iIn=0; iIn<fNeff; iIn++) (*pyx)(iIn,iClust)+=(*mPyx)(iIn,iClust1);
 298                                 (*py)(iClust)+=(*vPy)(iClust1);
 299                                 for (Int_t i=0; i<2; i++) (*y1)(i,iClust)+=(*mY)(i,iClust1);
 300                         }
 301                         for (Int_t i=0; i<2; i++) (*y1)(i,iClust)/=nSame[iClust];
 302                 }
 303                 for (Int_t iClust=0; iClust<nk; iClust++) delete [] cont[iClust], delete [] iSame[iClust];
 304                 delete [] iSame;
 305                 delete [] cont;
 306                 delete [] nSame;
 307                 if (nc > nk/2){
 308                         for (Int_t iClust=0; iClust<nc; iClust++){
 309                                 for (Int_t iIn=0; iIn<fNeff; iIn++) (*mPyx)(iIn,iClust)=(*pyx)(iIn,iClust);
 310                                 for (Int_t iComp=0; iComp<2; iComp++) (*mY)(iComp,iClust)=(*y1)(iComp,iClust);
 311                                 (*vPy)(iClust)=(*py)(iClust);
 312                         }
 313                         nk=nc;
 314                         if (growcl) DoubleClusters(nc,nk,vPy,mY);
 315                 }
 316                 delete pyx;
 317                 delete py;
 318                 delete y1;
 319         }
 320
 321 }
 322
 323 //-----------------------------------------------------------------------------------
 324 void AliDAJetFinder::ReduceClusters(Int_t **iSame,Int_t nc,Int_t &ncout,Int_t **cont,Int_t *nSameOut) const
 325 {
 326 // Reduction step
 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;
 332                 for (Int_t jCl=0; jCl<nc; jCl++) nSame[iCl]+=iSame[iCl][jCl], cont[iCl][jCl]=0;
 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 //-----------------------------------------------------------------------------------
 360 void AliDAJetFinder::EndDetAnn(Int_t &nk,Double_t **xData,Int_t *xx,Double_t etx,TVectorD *vPx,TVectorD *vPy,TMatrixD *mPyx,TMatrixD *mY)
 361 {
 362 //now assign each particle to only one cluster
 363         Double_t *clusters=new Double_t[nk];
 364         for (Int_t iIn=0; iIn<fNeff; iIn++){
 365                 for (Int_t iClust=0; iClust<nk; iClust++) clusters[iClust]=(*mPyx)(iIn,iClust);
 366                 xx[iIn]=TMath::LocMax(nk,clusters);
 367         }
 368         delete [] clusters;
 369
 370 //recalculate codevectors, having all p(y|x)=0 or 1
 371         Double_t *xEta = xData[0];
 372         Double_t *xPhi = xData[1];
 373         mY->Zero();
 374         mPyx->Zero();
 375         vPy->Zero();
 376         for (Int_t iIn=0; iIn<fNin; iIn++){
 377                 Int_t iClust=xx[iIn];
 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;
 382         }
 383         Int_t k=0;
 384         for (Int_t iClust=0; iClust<nk; iClust++){
 385                 if ((*vPy)(iClust)>0){
 386                         Double_t xpos=0,ypos=0,pxy;
 387                         for (Int_t iIn=0; iIn<fNin; iIn++){
 388                                 pxy=(*vPx)(iIn)*(*mPyx)(iIn,iClust)/(*vPy)(iClust);
 389                                 ypos+=pxy*TMath::Sin(xPhi[iIn]);
 390                                 xpos+=pxy*TMath::Cos(xPhi[iIn]);
 391                                 if (xx[iIn]==iClust) xx[iIn]=k;
 392                         }
 393                         (*mY)(0,k)=(*mY)(0,iClust)/(*vPy)(iClust);
 394                         (*mY)(1,k)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2*TMath::Pi();
 395                         (*mY)(3,k)=(*mY)(3,iClust);
 396                         k++;
 397                 }
 398         }
 399         nk=k;
 400 }
 401
 402 //-----------------------------------------------------------------------------------
 403 void AliDAJetFinder::StoreJets(Int_t nk, Double_t **xData, Int_t *xx, TMatrixD *mY)
 404 {
 405 //evaluate significant clusters properties
 406         const Double_t pi=TMath::Pi();
 407         AliJetReaderHeader *rHeader=fReader->GetReaderHeader();
 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(2*dFiducialEta*pi/nEff);
 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];
 422         for (Int_t iClust=0; iClust<nk; iClust++){
 423                 isJet[iClust]=false;
 424                 Double_t dEtaMin=10.,dEtaMax=-10.,dPhiMin=10.,dPhiMax=0.;
 425                 for (Int_t iIn=0; iIn<fNeff; iIn++){
 426                         if (xx[iIn]!=iClust || xEta[iIn]>dFidEtaMax || xEta[iIn]<dFidEtaMin) continue;
 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);
 430                         if      (dPhi > pi     ) dPhi-=2*pi;
 431                         else if (dPhi < (-1)*pi) dPhi+=2*pi;
 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]=0.25*pi*dDeltaEta[iClust]*dDeltaPhi[iClust];
 438                 etDens[iClust]=(*mY)(3,iClust)/surf[iClust];
 439         }
 440
 441         if (((AliDAJetHeader*)fHeader)->GetSelJets()){
 442                 for (Int_t iClust=0; iClust<nk; iClust++){
 443                         if (!isJet[iClust] && (*mY)(0,iClust)<dFidEtaMax && (*mY)(0,iClust)>dFidEtaMin){
 444                                 Double_t etDensMed=0.;
 445                                 Double_t etDensSqr=0.;
 446                                 Int_t norm=0;
 447                                 for (Int_t iClust1=0; iClust1<nk; iClust1++){
 448                                         if(iClust1!=iClust && (*mY)(0,iClust)<dFidEtaMax && (*mY)(0,iClust)>dFidEtaMin){
 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));
 457                                 if ((*mY)(3,iClust) > (etDensMed+deltaEtDens)*surf[iClust]) isJet[iClust]=kTRUE;
 458                                 etNoBg[iClust]=(*mY)(3,iClust)-etDensMed*surf[iClust];
 459                         }
 460                 }
 461                 for (Int_t iClust=0; iClust<nk; iClust++){
 462                         if (isJet[iClust]){
 463                                 Double_t etDensMed=0;
 464                                 Double_t extSurf=2*dFiducialEta*pi;
 465                                 for (Int_t iClust1=0; iClust1<nk; iClust1++){
 466                                         if (!isJet[iClust1]) etDensMed+=(*mY)(3,iClust1);
 467                                         else extSurf-=surf[iClust1];
 468                                 }
 469                                 etDensMed/=extSurf;
 470                                 etNoBg[iClust]=(*mY)(3,iClust)-etDensMed*surf[iClust];
 471                                 if (etNoBg[iClust]<((AliDAJetHeader*)fHeader)->GetEtMin()){
 472                                         isJet[iClust]=kFALSE;
 473                                         iClust=-1;
 474                                 }
 475                         }
 476                 }
 477         } else {
 478                 for (Int_t iClust=0; iClust<nk; iClust++){
 479                         isJet[iClust]=true;
 480                         etNoBg[iClust]=(*mY)(3,iClust);
 481                 }
 482         }
 483         delete [] etDens;
 484         delete [] surf;
 485
 486 //now add selected jets to the list
 487         Int_t *iSort = new Int_t[nk];
 488         TMath::Sort(nk,etNoBg,iSort,true);
 489         Int_t iCl = 0;
 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
 494                 iCl=iSort[iClust];
 495                 if (isJet[iCl]){                                                                                                                //choose cluster
 496                         Float_t px,py,pz,en;
 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))));
 500                         en = TMath::Sqrt(px * px + py * py + pz * pz);
 501                         AliAODJet jet(px, py, pz, en);
 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;
 507                                         if (xx[iIn]==iCl) jet.AddTrack(refs->At(iEn));
 508                                         iIn++;
 509                                 }
 510                         }
 511                         AddJet(jet);
 512                         if (fDebug > 0) printf("jet %d, Eta: %f, Phi: %f, Et: %f\n",iCl,jet.Eta(),jet.Phi(),jet.Pt());
 513                 }
 514         }
 515         delete [] dDeltaEta; delete [] dDeltaPhi;
 516         delete [] etNoBg;
 517         delete [] isJet;
 518         delete [] iSort;
 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 }