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