Keep track of missing DCS points in DDL maps (flagged by 'x')
[u/mrichter/AliRoot.git] / JETAN / AliDAJetFinder.cxx
CommitLineData
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];
36b5cc43 90 EndDetAnn(nk,xData,xx,dEtSum,vPx,vPy,mPyx,mY);
91 StoreJets(nk,xData,xx,mY);
7c679be0 92 delete [] xx;
93
36b5cc43 94 delete [] xData[0], delete [] xData[1];
95 delete mPyx;
96 delete mY;
97 delete vPx;
98 delete vPy;
99
7c679be0 100}
101
102//-----------------------------------------------------------------------------------
36b5cc43 103void AliDAJetFinder::InitDetAnn(Double_t &dEtSum,Double_t **xData,TVectorD *vPx,TVectorD *vPy,TMatrixD *mPyx,TMatrixD *mY)
7c679be0 104{
105//Initialise the variables used by the algorithm
106 fBeta=0.1;
386b2e2f 107 fNclustMax = ((AliDAJetHeader*)fHeader)->GetFixedCl() ?
36b5cc43 108 ((AliDAJetHeader*)fHeader)->GetNclustMax() :
9e4cc50d 109 TMath::Max((Int_t)TMath::Sqrt(fNin),5);
386b2e2f 110 Float_t etaEff = ((AliDAJetHeader*)fHeader)->GetEtaEff();
e53baffe 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++;
386b2e2f 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];
36b5cc43 120 xData[0]=xEta; xData[1]=xPhi;
386b2e2f 121 vPx->ResizeTo(fNeff);
e53baffe 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);
36b5cc43 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);
e53baffe 130 iIn++;
7c679be0 131 }
386b2e2f 132 TRandom2 r;
133 r.SetSeed(0);
134 for (Int_t 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;
7c679be0 141
142 Int_t njdim=2*fNclustMax+1;
386b2e2f 143 mPyx->ResizeTo(fNeff,njdim);
36b5cc43 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;
7c679be0 149 Double_t ypos=0,xpos=0;
386b2e2f 150 for (iIn=0; iIn<fNeff; iIn++){
36b5cc43 151 (*mY)(0,0)+=(*vPx)(iIn)*xEta[iIn];
152 ypos+=(*vPx)(iIn)*TMath::Sin(xPhi[iIn]);
153 xpos+=(*vPx)(iIn)*TMath::Cos(xPhi[iIn]);
7c679be0 154 }
36b5cc43 155 (*mY)(1,0)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2*TMath::Pi();
7c679be0 156}
157
158//-----------------------------------------------------------------------------------
c0a5117c 159void AliDAJetFinder::DoubleClusters(Int_t nc,Int_t &nk, TVectorD *vPy, TMatrixD *mY) const
7c679be0 160{
161 for(Int_t iClust=0; iClust<nc; iClust++){
36b5cc43 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);
7c679be0 165 }
166 nk=2*nc;
167}
168
169//-----------------------------------------------------------------------------------
c0a5117c 170void AliDAJetFinder::Annealing(Int_t nk,Double_t **xData, TVectorD *vPx, TVectorD *vPy, TMatrixD *mPyx, TMatrixD *mY)
7c679be0 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);
386b2e2f 179 Double_t *xEta = xData[0];
180 Double_t *xPhi = xData[1];
7c679be0 181 Double_t Dist(TVectorD,TVectorD);
182
36b5cc43 183 Double_t df[2]={fReader->GetReaderHeader()->GetFiducialEtaMax(),pi};
7c679be0 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++){
36b5cc43 190 for (Int_t i=0; i<3; i++)(*y1)(i,iClust)=(*mY)(i,iClust);
191 (*py)(iClust)=(*vPy)(iClust);
7c679be0 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++;
386b2e2f 205 for (Int_t iIn=0; iIn<fNeff; iIn++){
36b5cc43 206 vPart(0)=xEta[iIn]; vPart(1)=xPhi[iIn];
7c679be0 207 for(Int_t iClust=0; iClust<nk; iClust++){
36b5cc43 208 (*mPyx)(iIn,iClust)=-log((*py)(iClust))+fBeta*Dist(vPart,TMatrixDColumn(*y1,iClust));
209 m[iClust]=(*mPyx)(iIn,iClust);
7c679be0 210 }
211 Double_t pyxNorm=0;
212 Double_t minPyx=TMath::MinElement(nk,m);
213 for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43 214 (*mPyx)(iIn,iClust)-=minPyx;
215 (*mPyx)(iIn,iClust)=exp(-(*mPyx)(iIn,iClust));
216 pyxNorm+=(*mPyx)(iIn,iClust);
7c679be0 217 }
36b5cc43 218 for (Int_t iClust=0; iClust<nk; iClust++) (*mPyx)(iIn,iClust)/=pyxNorm;
7c679be0 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;
386b2e2f 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++){
36b5cc43 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];
7c679be0 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
36b5cc43 253 for (Int_t i=0; i<2; i++) (*mY)(i,iClust)=(*y)(i,iClust);
254 (*vPy)(iClust)=(*p)(iClust);
7c679be0 255 }
256 delete py;
257 delete p;
258 delete y;
259 delete y1;
260 delete ry;
c0a5117c 261 delete [] m;
7c679be0 262}
263
264//-----------------------------------------------------------------------------------
c0a5117c 265void AliDAJetFinder::NumCl(Int_t &nc,Int_t &nk,TVectorD *vPy, TMatrixD *mPyx,TMatrixD *mY)
7c679be0 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++){
36b5cc43 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);
7c679be0 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;
852db00e 283 else iSame[iClust][iClust1]=iSame[iClust1][iClust]=0;
7c679be0 284 }
285 }
286 ReduceClusters(iSame,nk,nc,cont,nSame);
287 if (nc >= fNclustMax) growcl=false;
288//recalculate the nc distinct codevectors
386b2e2f 289 TMatrixD *pyx = new TMatrixD(fNeff,2*nc);
7c679be0 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];
386b2e2f 295 for (Int_t iIn=0; iIn<fNeff; iIn++) (*pyx)(iIn,iClust)+=(*mPyx)(iIn,iClust1);
36b5cc43 296 (*py)(iClust)+=(*vPy)(iClust1);
297 for (Int_t i=0; i<2; i++) (*y1)(i,iClust)+=(*mY)(i,iClust1);
7c679be0 298 }
299 for (Int_t i=0; i<2; i++) (*y1)(i,iClust)/=nSame[iClust];
300 }
852db00e 301 for (Int_t iClust=0; iClust<nk; iClust++) delete [] cont[iClust], delete [] iSame[iClust];
302 delete [] iSame;
303 delete [] cont;
304 delete [] nSame;
7c679be0 305 if (nc > nk/2){
306 for (Int_t iClust=0; iClust<nc; iClust++){
386b2e2f 307 for (Int_t iIn=0; iIn<fNeff; iIn++) (*mPyx)(iIn,iClust)=(*pyx)(iIn,iClust);
36b5cc43 308 for (Int_t iComp=0; iComp<2; iComp++) (*mY)(iComp,iClust)=(*y1)(iComp,iClust);
309 (*vPy)(iClust)=(*py)(iClust);
7c679be0 310 }
311 nk=nc;
36b5cc43 312 if (growcl) DoubleClusters(nc,nk,vPy,mY);
7c679be0 313 }
7c679be0 314 delete pyx;
315 delete py;
316 delete y1;
317 }
318
319}
320
321//-----------------------------------------------------------------------------------
c0a5117c 322void AliDAJetFinder::ReduceClusters(Int_t **iSame,Int_t nc,Int_t &ncout,Int_t **cont,Int_t *nSameOut) const
7c679be0 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;
852db00e 329 for (Int_t jCl=0; jCl<nc; jCl++) nSame[iCl]+=iSame[iCl][jCl], cont[iCl][jCl]=0;
7c679be0 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//-----------------------------------------------------------------------------------
386b2e2f 357void AliDAJetFinder::EndDetAnn(Int_t &nk,Double_t **xData,Int_t *xx,Double_t etx,TVectorD *vPx,TVectorD *vPy,TMatrixD *mPyx,TMatrixD *mY)
7c679be0 358{
359//now assign each particle to only one cluster
360 Double_t *clusters=new Double_t[nk];
386b2e2f 361 for (Int_t iIn=0; iIn<fNeff; iIn++){
36b5cc43 362 for (Int_t iClust=0; iClust<nk; iClust++) clusters[iClust]=(*mPyx)(iIn,iClust);
7c679be0 363 xx[iIn]=TMath::LocMax(nk,clusters);
364 }
386b2e2f 365 delete [] clusters;
7c679be0 366
367//recalculate codevectors, having all p(y|x)=0 or 1
386b2e2f 368 Double_t *xEta = xData[0];
369 Double_t *xPhi = xData[1];
36b5cc43 370 mY->Zero();
371 mPyx->Zero();
372 vPy->Zero();
7c679be0 373 for (Int_t iIn=0; iIn<fNin; iIn++){
374 Int_t iClust=xx[iIn];
36b5cc43 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;
7c679be0 379 }
380 Int_t k=0;
381 for (Int_t iClust=0; iClust<nk; iClust++){
36b5cc43 382 if ((*vPy)(iClust)>0){
7c679be0 383 Double_t xpos=0,ypos=0,pxy;
384 for (Int_t iIn=0; iIn<fNin; iIn++){
36b5cc43 385 pxy=(*vPx)(iIn)*(*mPyx)(iIn,iClust)/(*vPy)(iClust);
386 ypos+=pxy*TMath::Sin(xPhi[iIn]);
387 xpos+=pxy*TMath::Cos(xPhi[iIn]);
7c679be0 388 if (xx[iIn]==iClust) xx[iIn]=k;
389 }
36b5cc43 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);
7c679be0 393 k++;
394 }
395 }
396 nk=k;
397}
398
399//-----------------------------------------------------------------------------------
386b2e2f 400void AliDAJetFinder::StoreJets(Int_t nk, Double_t **xData, Int_t *xx, TMatrixD *mY)
7c679be0 401{
402//evaluate significant clusters properties
403 const Double_t pi=TMath::Pi();
36b5cc43 404 AliJetReaderHeader *rHeader=fReader->GetReaderHeader();
386b2e2f 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);
7c679be0 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];
386b2e2f 419 for (Int_t iClust=0; iClust<nk; iClust++){
7c679be0 420 isJet[iClust]=false;
421 Double_t dEtaMin=10.,dEtaMax=-10.,dPhiMin=10.,dPhiMax=0.;
386b2e2f 422 for (Int_t iIn=0; iIn<fNeff; iIn++){
423 if (xx[iIn]!=iClust || xEta[iIn]>dFidEtaMax || xEta[iIn]<dFidEtaMin) continue;
36b5cc43 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);
7c679be0 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];
36b5cc43 435 etDens[iClust]=(*mY)(3,iClust)/surf[iClust];
7c679be0 436 }
437
9e4cc50d 438 if (((AliDAJetHeader*)fHeader)->GetSelJets()){
7c679be0 439 for (Int_t iClust=0; iClust<nk; iClust++){
386b2e2f 440 if (!isJet[iClust] && (*mY)(0,iClust)<dFidEtaMax && (*mY)(0,iClust)>dFidEtaMin){
7c679be0 441 Double_t etDensMed=0.;
442 Double_t etDensSqr=0.;
443 Int_t norm=0;
444 for (Int_t iClust1=0; iClust1<nk; iClust1++){
386b2e2f 445 if(iClust1!=iClust && (*mY)(0,iClust)<dFidEtaMax && (*mY)(0,iClust)>dFidEtaMin){
7c679be0 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));
36b5cc43 454 if ((*mY)(3,iClust) > (etDensMed+deltaEtDens)*surf[iClust]) isJet[iClust]=kTRUE;
455 etNoBg[iClust]=(*mY)(3,iClust)-etDensMed*surf[iClust];
7c679be0 456 }
457 }
458 for (Int_t iClust=0; iClust<nk; iClust++){
459 if (isJet[iClust]){
460 Double_t etDensMed=0;
36b5cc43 461 Double_t extSurf=2*dFiducialEta*pi;
7c679be0 462 for (Int_t iClust1=0; iClust1<nk; iClust1++){
36b5cc43 463 if (!isJet[iClust1]) etDensMed+=(*mY)(3,iClust1);
7c679be0 464 else extSurf-=surf[iClust1];
465 }
466 etDensMed/=extSurf;
36b5cc43 467 etNoBg[iClust]=(*mY)(3,iClust)-etDensMed*surf[iClust];
10bd125d 468 if (etNoBg[iClust]<((AliDAJetHeader*)fHeader)->GetEtMin()){
469 isJet[iClust]=kFALSE;
470 iClust=-1;
471 }
7c679be0 472 }
473 }
474 } else {
386b2e2f 475 for (Int_t iClust=0; iClust<nk; iClust++){
476 isJet[iClust]=true;
477 etNoBg[iClust]=(*mY)(3,iClust);
478 }
7c679be0 479 }
480 delete [] etDens;
481 delete [] surf;
482
483//now add selected jets to the list
af816924 484 Int_t *iSort = new Int_t[nk];
386b2e2f 485 TMath::Sort(nk,etNoBg,iSort,true);
486 Int_t iCl = 0;
7c679be0 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
af816924 491 iCl=iSort[iClust];
492 if (isJet[iCl]){ //choose cluster
7c679be0 493 Float_t px,py,pz,en;
af816924 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))));
7c679be0 497 en = TMath::Sqrt(px * px + py * py + pz * pz);
498 AliAODJet jet(px, py, pz, en);
e53baffe 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;
af816924 504 if (xx[iIn]==iCl) jet.AddTrack(refs->At(iEn));
e53baffe 505 iIn++;
506 }
507 }
7c679be0 508 AddJet(jet);
dd677561 509 if (fDebug > 0) printf("jet %d, Eta: %f, Phi: %f, Et: %f\n",iCl,jet.Eta(),jet.Phi(),jet.Pt());
7c679be0 510 }
511 }
512 delete [] dDeltaEta; delete [] dDeltaPhi;
513 delete [] etNoBg;
514 delete [] isJet;
af816924 515 delete [] iSort;
7c679be0 516}
517
518//-----------------------------------------------------------------------------------
519Double_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}