adding rho dependence on leading track (M. Verweij)
[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);
95345ec0 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 }
36b5cc43 81 Int_t nc=1, nk;
82 DoubleClusters(nc,nk,vPy,mY);
7c679be0 83 do{ //loop over beta
84 fBeta*=fAlpha;
36b5cc43 85 Annealing(nk,xData,vPx,vPy,mPyx,mY);
86 NumCl(nc,nk,vPy,mPyx,mY);
7c679be0 87 }while((fBeta<betaStop || nc<4) && nc<fNclustMax);
88
386b2e2f 89 Int_t *xx=new Int_t[fNeff];
f34058c0 90 for (Int_t i = 0; i < fNeff; i++) xx[i] = 0;
91
36b5cc43 92 EndDetAnn(nk,xData,xx,dEtSum,vPx,vPy,mPyx,mY);
93 StoreJets(nk,xData,xx,mY);
7c679be0 94 delete [] xx;
95
36b5cc43 96 delete [] xData[0], delete [] xData[1];
97 delete mPyx;
98 delete mY;
99 delete vPx;
100 delete vPy;
101
7c679be0 102}
103
104//-----------------------------------------------------------------------------------
36b5cc43 105void AliDAJetFinder::InitDetAnn(Double_t &dEtSum,Double_t **xData,TVectorD *vPx,TVectorD *vPy,TMatrixD *mPyx,TMatrixD *mY)
7c679be0 106{
107//Initialise the variables used by the algorithm
108 fBeta=0.1;
386b2e2f 109 fNclustMax = ((AliDAJetHeader*)fHeader)->GetFixedCl() ?
36b5cc43 110 ((AliDAJetHeader*)fHeader)->GetNclustMax() :
9e4cc50d 111 TMath::Max((Int_t)TMath::Sqrt(fNin),5);
386b2e2f 112 Float_t etaEff = ((AliDAJetHeader*)fHeader)->GetEtaEff();
e53baffe 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++;
386b2e2f 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];
36b5cc43 122 xData[0]=xEta; xData[1]=xPhi;
386b2e2f 123 vPx->ResizeTo(fNeff);
e53baffe 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);
36b5cc43 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);
e53baffe 132 iIn++;
7c679be0 133 }
386b2e2f 134 TRandom2 r;
135 r.SetSeed(0);
d072acbe 136 for (iIn=fNin; iIn<fNeff; iIn++){
386b2e2f 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;
7c679be0 143
144 Int_t njdim=2*fNclustMax+1;
386b2e2f 145 mPyx->ResizeTo(fNeff,njdim);
36b5cc43 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;
7c679be0 151 Double_t ypos=0,xpos=0;
386b2e2f 152 for (iIn=0; iIn<fNeff; iIn++){
36b5cc43 153 (*mY)(0,0)+=(*vPx)(iIn)*xEta[iIn];
154 ypos+=(*vPx)(iIn)*TMath::Sin(xPhi[iIn]);
155 xpos+=(*vPx)(iIn)*TMath::Cos(xPhi[iIn]);
7c679be0 156 }
36b5cc43 157 (*mY)(1,0)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2*TMath::Pi();
7c679be0 158}
159
160//-----------------------------------------------------------------------------------
1240edf5 161void AliDAJetFinder::DoubleClusters(Int_t nc,Int_t &nk, TVectorD *vPy, TMatrixD *mY) const
7c679be0 162{
1240edf5 163// Return double clusters
7c679be0 164 for(Int_t iClust=0; iClust<nc; iClust++){
36b5cc43 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);
7c679be0 168 }
169 nk=2*nc;
170}
171
172//-----------------------------------------------------------------------------------
c0a5117c 173void AliDAJetFinder::Annealing(Int_t nk,Double_t **xData, TVectorD *vPx, TVectorD *vPy, TMatrixD *mPyx, TMatrixD *mY)
7c679be0 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);
386b2e2f 182 Double_t *xEta = xData[0];
183 Double_t *xPhi = xData[1];
7c679be0 184 Double_t Dist(TVectorD,TVectorD);
185
36b5cc43 186 Double_t df[2]={fReader->GetReaderHeader()->GetFiducialEtaMax(),pi};
7c679be0 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++){
36b5cc43 193 for (Int_t i=0; i<3; i++)(*y1)(i,iClust)=(*mY)(i,iClust);
194 (*py)(iClust)=(*vPy)(iClust);
7c679be0 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++;
386b2e2f 208 for (Int_t iIn=0; iIn<fNeff; iIn++){
36b5cc43 209 vPart(0)=xEta[iIn]; vPart(1)=xPhi[iIn];
7c679be0 210 for(Int_t iClust=0; iClust<nk; iClust++){
36b5cc43 211 (*mPyx)(iIn,iClust)=-log((*py)(iClust))+fBeta*Dist(vPart,TMatrixDColumn(*y1,iClust));
212 m[iClust]=(*mPyx)(iIn,iClust);
7c679be0 213 }
214 Double_t pyxNorm=0;
215 Double_t minPyx=TMath::MinElement(nk,m);
216 for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43 217 (*mPyx)(iIn,iClust)-=minPyx;
218 (*mPyx)(iIn,iClust)=exp(-(*mPyx)(iIn,iClust));
219 pyxNorm+=(*mPyx)(iIn,iClust);
7c679be0 220 }
36b5cc43 221 for (Int_t iClust=0; iClust<nk; iClust++) (*mPyx)(iIn,iClust)/=pyxNorm;
7c679be0 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;
386b2e2f 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++){
36b5cc43 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];
7c679be0 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
36b5cc43 256 for (Int_t i=0; i<2; i++) (*mY)(i,iClust)=(*y)(i,iClust);
257 (*vPy)(iClust)=(*p)(iClust);
7c679be0 258 }
259 delete py;
260 delete p;
261 delete y;
262 delete y1;
263 delete ry;
c0a5117c 264 delete [] m;
7c679be0 265}
266
267//-----------------------------------------------------------------------------------
c0a5117c 268void AliDAJetFinder::NumCl(Int_t &nc,Int_t &nk,TVectorD *vPy, TMatrixD *mPyx,TMatrixD *mY)
7c679be0 269{
1240edf5 270 // Number of clusters
7c679be0 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];
f34058c0 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
7c679be0 284 for (Int_t iClust=0; iClust<nk; iClust++){
285 iSame[iClust][iClust]=1;
286 for (Int_t iClust1=iClust+1; iClust1<nk; iClust1++){
36b5cc43 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);
7c679be0 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;
852db00e 291 else iSame[iClust][iClust1]=iSame[iClust1][iClust]=0;
7c679be0 292 }
293 }
294 ReduceClusters(iSame,nk,nc,cont,nSame);
295 if (nc >= fNclustMax) growcl=false;
296//recalculate the nc distinct codevectors
386b2e2f 297 TMatrixD *pyx = new TMatrixD(fNeff,2*nc);
7c679be0 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];
386b2e2f 303 for (Int_t iIn=0; iIn<fNeff; iIn++) (*pyx)(iIn,iClust)+=(*mPyx)(iIn,iClust1);
36b5cc43 304 (*py)(iClust)+=(*vPy)(iClust1);
305 for (Int_t i=0; i<2; i++) (*y1)(i,iClust)+=(*mY)(i,iClust1);
7c679be0 306 }
307 for (Int_t i=0; i<2; i++) (*y1)(i,iClust)/=nSame[iClust];
308 }
852db00e 309 for (Int_t iClust=0; iClust<nk; iClust++) delete [] cont[iClust], delete [] iSame[iClust];
310 delete [] iSame;
311 delete [] cont;
312 delete [] nSame;
7c679be0 313 if (nc > nk/2){
314 for (Int_t iClust=0; iClust<nc; iClust++){
386b2e2f 315 for (Int_t iIn=0; iIn<fNeff; iIn++) (*mPyx)(iIn,iClust)=(*pyx)(iIn,iClust);
36b5cc43 316 for (Int_t iComp=0; iComp<2; iComp++) (*mY)(iComp,iClust)=(*y1)(iComp,iClust);
317 (*vPy)(iClust)=(*py)(iClust);
7c679be0 318 }
319 nk=nc;
36b5cc43 320 if (growcl) DoubleClusters(nc,nk,vPy,mY);
7c679be0 321 }
7c679be0 322 delete pyx;
323 delete py;
324 delete y1;
325 }
326
327}
328
329//-----------------------------------------------------------------------------------
c0a5117c 330void AliDAJetFinder::ReduceClusters(Int_t **iSame,Int_t nc,Int_t &ncout,Int_t **cont,Int_t *nSameOut) const
7c679be0 331{
1240edf5 332// Reduction step
7c679be0 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;
852db00e 338 for (Int_t jCl=0; jCl<nc; jCl++) nSame[iCl]+=iSame[iCl][jCl], cont[iCl][jCl]=0;
7c679be0 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//-----------------------------------------------------------------------------------
386b2e2f 366void AliDAJetFinder::EndDetAnn(Int_t &nk,Double_t **xData,Int_t *xx,Double_t etx,TVectorD *vPx,TVectorD *vPy,TMatrixD *mPyx,TMatrixD *mY)
7c679be0 367{
368//now assign each particle to only one cluster
369 Double_t *clusters=new Double_t[nk];
386b2e2f 370 for (Int_t iIn=0; iIn<fNeff; iIn++){
36b5cc43 371 for (Int_t iClust=0; iClust<nk; iClust++) clusters[iClust]=(*mPyx)(iIn,iClust);
7c679be0 372 xx[iIn]=TMath::LocMax(nk,clusters);
373 }
386b2e2f 374 delete [] clusters;
7c679be0 375
376//recalculate codevectors, having all p(y|x)=0 or 1
386b2e2f 377 Double_t *xEta = xData[0];
378 Double_t *xPhi = xData[1];
36b5cc43 379 mY->Zero();
380 mPyx->Zero();
381 vPy->Zero();
7c679be0 382 for (Int_t iIn=0; iIn<fNin; iIn++){
383 Int_t iClust=xx[iIn];
36b5cc43 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;
7c679be0 388 }
389 Int_t k=0;
390 for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43 391 if ((*vPy)(iClust)>0){
7c679be0 392 Double_t xpos=0,ypos=0,pxy;
393 for (Int_t iIn=0; iIn<fNin; iIn++){
36b5cc43 394 pxy=(*vPx)(iIn)*(*mPyx)(iIn,iClust)/(*vPy)(iClust);
395 ypos+=pxy*TMath::Sin(xPhi[iIn]);
396 xpos+=pxy*TMath::Cos(xPhi[iIn]);
7c679be0 397 if (xx[iIn]==iClust) xx[iIn]=k;
398 }
36b5cc43 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);
7c679be0 402 k++;
403 }
404 }
405 nk=k;
406}
407
408//-----------------------------------------------------------------------------------
386b2e2f 409void AliDAJetFinder::StoreJets(Int_t nk, Double_t **xData, Int_t *xx, TMatrixD *mY)
7c679be0 410{
411//evaluate significant clusters properties
412 const Double_t pi=TMath::Pi();
36b5cc43 413 AliJetReaderHeader *rHeader=fReader->GetReaderHeader();
386b2e2f 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++;
f8ec9e37 421 Double_t dMeanDist=0.;
422 if (nEff > 0)
423 dMeanDist=TMath::Sqrt(2*dFiducialEta*pi/nEff);
7c679be0 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];
386b2e2f 430 for (Int_t iClust=0; iClust<nk; iClust++){
7c679be0 431 isJet[iClust]=false;
432 Double_t dEtaMin=10.,dEtaMax=-10.,dPhiMin=10.,dPhiMax=0.;
386b2e2f 433 for (Int_t iIn=0; iIn<fNeff; iIn++){
434 if (xx[iIn]!=iClust || xEta[iIn]>dFidEtaMax || xEta[iIn]<dFidEtaMin) continue;
36b5cc43 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);
7c679be0 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];
36b5cc43 446 etDens[iClust]=(*mY)(3,iClust)/surf[iClust];
7c679be0 447 }
448
9e4cc50d 449 if (((AliDAJetHeader*)fHeader)->GetSelJets()){
7c679be0 450 for (Int_t iClust=0; iClust<nk; iClust++){
386b2e2f 451 if (!isJet[iClust] && (*mY)(0,iClust)<dFidEtaMax && (*mY)(0,iClust)>dFidEtaMin){
7c679be0 452 Double_t etDensMed=0.;
453 Double_t etDensSqr=0.;
454 Int_t norm=0;
455 for (Int_t iClust1=0; iClust1<nk; iClust1++){
386b2e2f 456 if(iClust1!=iClust && (*mY)(0,iClust)<dFidEtaMax && (*mY)(0,iClust)>dFidEtaMin){
7c679be0 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));
36b5cc43 465 if ((*mY)(3,iClust) > (etDensMed+deltaEtDens)*surf[iClust]) isJet[iClust]=kTRUE;
466 etNoBg[iClust]=(*mY)(3,iClust)-etDensMed*surf[iClust];
7c679be0 467 }
468 }
469 for (Int_t iClust=0; iClust<nk; iClust++){
470 if (isJet[iClust]){
471 Double_t etDensMed=0;
36b5cc43 472 Double_t extSurf=2*dFiducialEta*pi;
7c679be0 473 for (Int_t iClust1=0; iClust1<nk; iClust1++){
36b5cc43 474 if (!isJet[iClust1]) etDensMed+=(*mY)(3,iClust1);
7c679be0 475 else extSurf-=surf[iClust1];
476 }
477 etDensMed/=extSurf;
36b5cc43 478 etNoBg[iClust]=(*mY)(3,iClust)-etDensMed*surf[iClust];
10bd125d 479 if (etNoBg[iClust]<((AliDAJetHeader*)fHeader)->GetEtMin()){
480 isJet[iClust]=kFALSE;
481 iClust=-1;
482 }
7c679be0 483 }
484 }
485 } else {
386b2e2f 486 for (Int_t iClust=0; iClust<nk; iClust++){
487 isJet[iClust]=true;
488 etNoBg[iClust]=(*mY)(3,iClust);
489 }
7c679be0 490 }
491 delete [] etDens;
492 delete [] surf;
493
494//now add selected jets to the list
af816924 495 Int_t *iSort = new Int_t[nk];
386b2e2f 496 TMath::Sort(nk,etNoBg,iSort,true);
497 Int_t iCl = 0;
7c679be0 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
af816924 502 iCl=iSort[iClust];
503 if (isJet[iCl]){ //choose cluster
7c679be0 504 Float_t px,py,pz,en;
af816924 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))));
7c679be0 508 en = TMath::Sqrt(px * px + py * py + pz * pz);
509 AliAODJet jet(px, py, pz, en);
e53baffe 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;
af816924 515 if (xx[iIn]==iCl) jet.AddTrack(refs->At(iEn));
e53baffe 516 iIn++;
517 }
518 }
7c679be0 519 AddJet(jet);
dd677561 520 if (fDebug > 0) printf("jet %d, Eta: %f, Phi: %f, Et: %f\n",iCl,jet.Eta(),jet.Phi(),jet.Pt());
7c679be0 521 }
522 }
523 delete [] dDeltaEta; delete [] dDeltaPhi;
524 delete [] etNoBg;
525 delete [] isJet;
af816924 526 delete [] iSort;
7c679be0 527}
528
529//-----------------------------------------------------------------------------------
530Double_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}