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