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