New class to extract pt distribution of given particle from pt distribution of a...
[u/mrichter/AliRoot.git] / JETAN / AliDAJetFinder.cxx
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9e4cc50d 1
7c679be0 2// **************************************************************************
3// * Copyright(c) 1998-1999, ALICE Experiment at CERN, All rights reserved. *
4// * *
5// * Author: The ALICE Off-line Project. *
6// * Contributors are mentioned in the code where appropriate. *
7// * *
8// * Permission to use, copy, modify and distribute this software and its *
9// * documentation strictly for non-commercial purposes is hereby granted *
10// * without fee, provided that the above copyright notice appears in all *
11// * copies and that both the copyright notice and this permission notice *
12// * appear in the supporting documentation. The authors make no claims *
13// * about the suitability of this software for any purpose. It is *
14// * provided "as is" without express or implied warranty. *
15// **************************************************************************
16
17//-----------------------------------------------------------------------------------
18// Jet finder based on Deterministic Annealing
19// For further informations about the DA working features see:
20// Phys.Lett. B601 (2004) 56-63 (http://arxiv.org/abs/hep-ph/0407214)
21// Author: Davide Perrino (davide.perrino@ba.infn.it, davide.perrino@cern.ch)
22//-----------------------------------------------------------------------------------
23
24#include <TMath.h>
386b2e2f 25#include <TRandom2.h>
7c679be0 26#include <TClonesArray.h>
36b5cc43 27#include "AliJetReaderHeader.h"
7c679be0 28#include "AliJetReader.h"
29#include "AliDAJetHeader.h"
30#include "AliDAJetFinder.h"
31
7c679be0 32ClassImp(AliDAJetFinder)
33
34
35//-----------------------------------------------------------------------------------
36AliDAJetFinder::AliDAJetFinder():
36b5cc43 37 AliJetFinder(),
7c679be0 38 fAlpha(1.01),
39 fDelta(1e-8),
40 fAvDist(1e-6),
41 fEps(1e-4),
42 fEpsMax(1e-2),
43 fNloopMax(100),
44 fBeta(0.1),
45 fNclustMax(0),
386b2e2f 46 fNin(0),
47 fNeff(0)
7c679be0 48{
49 // Constructor
50}
51
52//-----------------------------------------------------------------------------------
53AliDAJetFinder::~AliDAJetFinder()
54{
55 // Destructor
7c679be0 56}
57
58//-----------------------------------------------------------------------------------
59void AliDAJetFinder::FindJets()
60{
61// Find the jets in current event
62//
63 Float_t betaStop=100.;
386b2e2f 64 fDebug = fHeader->GetDebug();
7c679be0 65
66 Double_t dEtSum=0;
36b5cc43 67 Double_t *xData[2];
386b2e2f 68 TVectorD *vPx = new TVectorD();
69 TVectorD *vPy = new TVectorD();
70 TMatrixD *mPyx= new TMatrixD();
71 TMatrixD *mY = new TMatrixD();
36b5cc43 72 InitDetAnn(dEtSum,xData,vPx,vPy,mPyx,mY);
a9f9d6d5 73 if (fNin < fNclustMax) return;
7c679be0 74
36b5cc43 75 Int_t nc=1, nk;
76 DoubleClusters(nc,nk,vPy,mY);
7c679be0 77 do{ //loop over beta
78 fBeta*=fAlpha;
36b5cc43 79 Annealing(nk,xData,vPx,vPy,mPyx,mY);
80 NumCl(nc,nk,vPy,mPyx,mY);
7c679be0 81 }while((fBeta<betaStop || nc<4) && nc<fNclustMax);
82
386b2e2f 83 Int_t *xx=new Int_t[fNeff];
36b5cc43 84 EndDetAnn(nk,xData,xx,dEtSum,vPx,vPy,mPyx,mY);
85 StoreJets(nk,xData,xx,mY);
7c679be0 86 delete [] xx;
87
36b5cc43 88 delete [] xData[0], delete [] xData[1];
89 delete mPyx;
90 delete mY;
91 delete vPx;
92 delete vPy;
93
7c679be0 94}
95
96//-----------------------------------------------------------------------------------
36b5cc43 97void AliDAJetFinder::InitDetAnn(Double_t &dEtSum,Double_t **xData,TVectorD *vPx,TVectorD *vPy,TMatrixD *mPyx,TMatrixD *mY)
7c679be0 98{
99//Initialise the variables used by the algorithm
100 fBeta=0.1;
386b2e2f 101 fNclustMax = ((AliDAJetHeader*)fHeader)->GetFixedCl() ?
36b5cc43 102 ((AliDAJetHeader*)fHeader)->GetNclustMax() :
9e4cc50d 103 TMath::Max((Int_t)TMath::Sqrt(fNin),5);
386b2e2f 104 Float_t etaEff = ((AliDAJetHeader*)fHeader)->GetEtaEff();
e53baffe 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++;
386b2e2f 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];
36b5cc43 114 xData[0]=xEta; xData[1]=xPhi;
386b2e2f 115 vPx->ResizeTo(fNeff);
e53baffe 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);
36b5cc43 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);
e53baffe 124 iIn++;
7c679be0 125 }
386b2e2f 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;
7c679be0 135
136 Int_t njdim=2*fNclustMax+1;
386b2e2f 137 mPyx->ResizeTo(fNeff,njdim);
36b5cc43 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;
7c679be0 143 Double_t ypos=0,xpos=0;
386b2e2f 144 for (iIn=0; iIn<fNeff; iIn++){
36b5cc43 145 (*mY)(0,0)+=(*vPx)(iIn)*xEta[iIn];
146 ypos+=(*vPx)(iIn)*TMath::Sin(xPhi[iIn]);
147 xpos+=(*vPx)(iIn)*TMath::Cos(xPhi[iIn]);
7c679be0 148 }
36b5cc43 149 (*mY)(1,0)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2*TMath::Pi();
7c679be0 150}
151
152//-----------------------------------------------------------------------------------
c0a5117c 153void AliDAJetFinder::DoubleClusters(Int_t nc,Int_t &nk, TVectorD *vPy, TMatrixD *mY) const
7c679be0 154{
155 for(Int_t iClust=0; iClust<nc; iClust++){
36b5cc43 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);
7c679be0 159 }
160 nk=2*nc;
161}
162
163//-----------------------------------------------------------------------------------
c0a5117c 164void AliDAJetFinder::Annealing(Int_t nk,Double_t **xData, TVectorD *vPx, TVectorD *vPy, TMatrixD *mPyx, TMatrixD *mY)
7c679be0 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);
386b2e2f 173 Double_t *xEta = xData[0];
174 Double_t *xPhi = xData[1];
7c679be0 175 Double_t Dist(TVectorD,TVectorD);
176
36b5cc43 177 Double_t df[2]={fReader->GetReaderHeader()->GetFiducialEtaMax(),pi};
7c679be0 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++){
36b5cc43 184 for (Int_t i=0; i<3; i++)(*y1)(i,iClust)=(*mY)(i,iClust);
185 (*py)(iClust)=(*vPy)(iClust);
7c679be0 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++;
386b2e2f 199 for (Int_t iIn=0; iIn<fNeff; iIn++){
36b5cc43 200 vPart(0)=xEta[iIn]; vPart(1)=xPhi[iIn];
7c679be0 201 for(Int_t iClust=0; iClust<nk; iClust++){
36b5cc43 202 (*mPyx)(iIn,iClust)=-log((*py)(iClust))+fBeta*Dist(vPart,TMatrixDColumn(*y1,iClust));
203 m[iClust]=(*mPyx)(iIn,iClust);
7c679be0 204 }
205 Double_t pyxNorm=0;
206 Double_t minPyx=TMath::MinElement(nk,m);
207 for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43 208 (*mPyx)(iIn,iClust)-=minPyx;
209 (*mPyx)(iIn,iClust)=exp(-(*mPyx)(iIn,iClust));
210 pyxNorm+=(*mPyx)(iIn,iClust);
7c679be0 211 }
36b5cc43 212 for (Int_t iClust=0; iClust<nk; iClust++) (*mPyx)(iIn,iClust)/=pyxNorm;
7c679be0 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;
386b2e2f 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++){
36b5cc43 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];
7c679be0 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
36b5cc43 247 for (Int_t i=0; i<2; i++) (*mY)(i,iClust)=(*y)(i,iClust);
248 (*vPy)(iClust)=(*p)(iClust);
7c679be0 249 }
250 delete py;
251 delete p;
252 delete y;
253 delete y1;
254 delete ry;
c0a5117c 255 delete [] m;
7c679be0 256}
257
258//-----------------------------------------------------------------------------------
c0a5117c 259void AliDAJetFinder::NumCl(Int_t &nc,Int_t &nk,TVectorD *vPy, TMatrixD *mPyx,TMatrixD *mY)
7c679be0 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++){
36b5cc43 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);
7c679be0 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;
852db00e 277 else iSame[iClust][iClust1]=iSame[iClust1][iClust]=0;
7c679be0 278 }
279 }
280 ReduceClusters(iSame,nk,nc,cont,nSame);
281 if (nc >= fNclustMax) growcl=false;
282//recalculate the nc distinct codevectors
386b2e2f 283 TMatrixD *pyx = new TMatrixD(fNeff,2*nc);
7c679be0 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];
386b2e2f 289 for (Int_t iIn=0; iIn<fNeff; iIn++) (*pyx)(iIn,iClust)+=(*mPyx)(iIn,iClust1);
36b5cc43 290 (*py)(iClust)+=(*vPy)(iClust1);
291 for (Int_t i=0; i<2; i++) (*y1)(i,iClust)+=(*mY)(i,iClust1);
7c679be0 292 }
293 for (Int_t i=0; i<2; i++) (*y1)(i,iClust)/=nSame[iClust];
294 }
852db00e 295 for (Int_t iClust=0; iClust<nk; iClust++) delete [] cont[iClust], delete [] iSame[iClust];
296 delete [] iSame;
297 delete [] cont;
298 delete [] nSame;
7c679be0 299 if (nc > nk/2){
300 for (Int_t iClust=0; iClust<nc; iClust++){
386b2e2f 301 for (Int_t iIn=0; iIn<fNeff; iIn++) (*mPyx)(iIn,iClust)=(*pyx)(iIn,iClust);
36b5cc43 302 for (Int_t iComp=0; iComp<2; iComp++) (*mY)(iComp,iClust)=(*y1)(iComp,iClust);
303 (*vPy)(iClust)=(*py)(iClust);
7c679be0 304 }
305 nk=nc;
36b5cc43 306 if (growcl) DoubleClusters(nc,nk,vPy,mY);
7c679be0 307 }
7c679be0 308 delete pyx;
309 delete py;
310 delete y1;
311 }
312
313}
314
315//-----------------------------------------------------------------------------------
c0a5117c 316void AliDAJetFinder::ReduceClusters(Int_t **iSame,Int_t nc,Int_t &ncout,Int_t **cont,Int_t *nSameOut) const
7c679be0 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;
852db00e 323 for (Int_t jCl=0; jCl<nc; jCl++) nSame[iCl]+=iSame[iCl][jCl], cont[iCl][jCl]=0;
7c679be0 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//-----------------------------------------------------------------------------------
386b2e2f 351void AliDAJetFinder::EndDetAnn(Int_t &nk,Double_t **xData,Int_t *xx,Double_t etx,TVectorD *vPx,TVectorD *vPy,TMatrixD *mPyx,TMatrixD *mY)
7c679be0 352{
353//now assign each particle to only one cluster
354 Double_t *clusters=new Double_t[nk];
386b2e2f 355 for (Int_t iIn=0; iIn<fNeff; iIn++){
36b5cc43 356 for (Int_t iClust=0; iClust<nk; iClust++) clusters[iClust]=(*mPyx)(iIn,iClust);
7c679be0 357 xx[iIn]=TMath::LocMax(nk,clusters);
358 }
386b2e2f 359 delete [] clusters;
7c679be0 360
361//recalculate codevectors, having all p(y|x)=0 or 1
386b2e2f 362 Double_t *xEta = xData[0];
363 Double_t *xPhi = xData[1];
36b5cc43 364 mY->Zero();
365 mPyx->Zero();
366 vPy->Zero();
7c679be0 367 for (Int_t iIn=0; iIn<fNin; iIn++){
368 Int_t iClust=xx[iIn];
36b5cc43 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;
7c679be0 373 }
374 Int_t k=0;
375 for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43 376 if ((*vPy)(iClust)>0){
7c679be0 377 Double_t xpos=0,ypos=0,pxy;
378 for (Int_t iIn=0; iIn<fNin; iIn++){
36b5cc43 379 pxy=(*vPx)(iIn)*(*mPyx)(iIn,iClust)/(*vPy)(iClust);
380 ypos+=pxy*TMath::Sin(xPhi[iIn]);
381 xpos+=pxy*TMath::Cos(xPhi[iIn]);
7c679be0 382 if (xx[iIn]==iClust) xx[iIn]=k;
383 }
36b5cc43 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);
7c679be0 387 k++;
388 }
389 }
390 nk=k;
391}
392
393//-----------------------------------------------------------------------------------
386b2e2f 394void AliDAJetFinder::StoreJets(Int_t nk, Double_t **xData, Int_t *xx, TMatrixD *mY)
7c679be0 395{
396//evaluate significant clusters properties
397 const Double_t pi=TMath::Pi();
36b5cc43 398 AliJetReaderHeader *rHeader=fReader->GetReaderHeader();
386b2e2f 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);
7c679be0 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];
386b2e2f 413 for (Int_t iClust=0; iClust<nk; iClust++){
7c679be0 414 isJet[iClust]=false;
415 Double_t dEtaMin=10.,dEtaMax=-10.,dPhiMin=10.,dPhiMax=0.;
386b2e2f 416 for (Int_t iIn=0; iIn<fNeff; iIn++){
417 if (xx[iIn]!=iClust || xEta[iIn]>dFidEtaMax || xEta[iIn]<dFidEtaMin) continue;
36b5cc43 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);
7c679be0 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];
36b5cc43 429 etDens[iClust]=(*mY)(3,iClust)/surf[iClust];
7c679be0 430 }
431
9e4cc50d 432 if (((AliDAJetHeader*)fHeader)->GetSelJets()){
7c679be0 433 for (Int_t iClust=0; iClust<nk; iClust++){
386b2e2f 434 if (!isJet[iClust] && (*mY)(0,iClust)<dFidEtaMax && (*mY)(0,iClust)>dFidEtaMin){
7c679be0 435 Double_t etDensMed=0.;
436 Double_t etDensSqr=0.;
437 Int_t norm=0;
438 for (Int_t iClust1=0; iClust1<nk; iClust1++){
386b2e2f 439 if(iClust1!=iClust && (*mY)(0,iClust)<dFidEtaMax && (*mY)(0,iClust)>dFidEtaMin){
7c679be0 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));
36b5cc43 448 if ((*mY)(3,iClust) > (etDensMed+deltaEtDens)*surf[iClust]) isJet[iClust]=kTRUE;
449 etNoBg[iClust]=(*mY)(3,iClust)-etDensMed*surf[iClust];
7c679be0 450 }
451 }
452 for (Int_t iClust=0; iClust<nk; iClust++){
453 if (isJet[iClust]){
454 Double_t etDensMed=0;
36b5cc43 455 Double_t extSurf=2*dFiducialEta*pi;
7c679be0 456 for (Int_t iClust1=0; iClust1<nk; iClust1++){
36b5cc43 457 if (!isJet[iClust1]) etDensMed+=(*mY)(3,iClust1);
7c679be0 458 else extSurf-=surf[iClust1];
459 }
460 etDensMed/=extSurf;
36b5cc43 461 etNoBg[iClust]=(*mY)(3,iClust)-etDensMed*surf[iClust];
10bd125d 462 if (etNoBg[iClust]<((AliDAJetHeader*)fHeader)->GetEtMin()){
463 isJet[iClust]=kFALSE;
464 iClust=-1;
465 }
7c679be0 466 }
467 }
468 } else {
386b2e2f 469 for (Int_t iClust=0; iClust<nk; iClust++){
470 isJet[iClust]=true;
471 etNoBg[iClust]=(*mY)(3,iClust);
472 }
7c679be0 473 }
474 delete [] etDens;
475 delete [] surf;
476
477//now add selected jets to the list
af816924 478 Int_t *iSort = new Int_t[nk];
386b2e2f 479 TMath::Sort(nk,etNoBg,iSort,true);
480 Int_t iCl = 0;
7c679be0 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
af816924 485 iCl=iSort[iClust];
486 if (isJet[iCl]){ //choose cluster
7c679be0 487 Float_t px,py,pz,en;
af816924 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))));
7c679be0 491 en = TMath::Sqrt(px * px + py * py + pz * pz);
492 AliAODJet jet(px, py, pz, en);
e53baffe 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;
af816924 498 if (xx[iIn]==iCl) jet.AddTrack(refs->At(iEn));
e53baffe 499 iIn++;
500 }
501 }
7c679be0 502 AddJet(jet);
dd677561 503 if (fDebug > 0) printf("jet %d, Eta: %f, Phi: %f, Et: %f\n",iCl,jet.Eta(),jet.Phi(),jet.Pt());
7c679be0 504 }
505 }
506 delete [] dDeltaEta; delete [] dDeltaPhi;
507 delete [] etNoBg;
508 delete [] isJet;
af816924 509 delete [] iSort;
7c679be0 510}
511
512//-----------------------------------------------------------------------------------
513Double_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}