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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> | |
25 | #include <TRandom.h> | |
26 | #include <TClonesArray.h> | |
27 | #include "AliJetReader.h" | |
28 | #include "AliDAJetHeader.h" | |
29 | #include "AliDAJetFinder.h" | |
30 | ||
31 | ||
32 | ClassImp(AliDAJetFinder) | |
33 | ||
34 | ||
35 | //----------------------------------------------------------------------------------- | |
36 | AliDAJetFinder::AliDAJetFinder(): | |
37 | fAlpha(1.01), | |
38 | fDelta(1e-8), | |
39 | fAvDist(1e-6), | |
40 | fEps(1e-4), | |
41 | fEpsMax(1e-2), | |
42 | fNloopMax(100), | |
43 | fBeta(0.1), | |
44 | fNclustMax(0), | |
45 | fPyx(0x0), | |
46 | fY(0x0), | |
47 | fPx(0x0), | |
48 | fPy(0x0), | |
49 | fXEta(0x0), | |
50 | fXPhi(0x0), | |
9e4cc50d | 51 | fNin(0) |
7c679be0 | 52 | { |
53 | // Constructor | |
54 | } | |
55 | ||
56 | //----------------------------------------------------------------------------------- | |
57 | AliDAJetFinder::~AliDAJetFinder() | |
58 | { | |
59 | // Destructor | |
7c679be0 | 60 | delete fPyx; |
61 | delete fY; | |
62 | delete fPx; | |
63 | delete fPy; | |
64 | delete [] fXEta; | |
65 | delete [] fXPhi; | |
66 | } | |
67 | ||
68 | //----------------------------------------------------------------------------------- | |
69 | void AliDAJetFinder::FindJets() | |
70 | { | |
71 | // Find the jets in current event | |
72 | // | |
73 | Float_t betaStop=100.; | |
74 | ||
75 | Double_t dEtSum=0; | |
76 | InitDetAnn(dEtSum); | |
77 | if (!fNin) return; | |
78 | ||
79 | Int_t nc=1,nk; | |
80 | DoubleClusters(nc,nk); | |
81 | do{ //loop over beta | |
82 | fBeta*=fAlpha; | |
83 | Annealing(nk); | |
84 | NumCl(nc,nk); | |
85 | }while((fBeta<betaStop || nc<4) && nc<fNclustMax); | |
86 | ||
87 | Int_t *xx=new Int_t[fNin]; | |
88 | EndDetAnn(nk,xx,dEtSum); | |
89 | StoreJets(nk,xx); | |
90 | delete [] xx; | |
91 | ||
92 | } | |
93 | ||
94 | //----------------------------------------------------------------------------------- | |
95 | void AliDAJetFinder::InitDetAnn(Double_t &dEtSum) | |
96 | { | |
97 | //Initialise the variables used by the algorithm | |
98 | fBeta=0.1; | |
99 | TClonesArray *lvArray = fReader->GetMomentumArray(); | |
100 | fNin = lvArray->GetEntries(); | |
9e4cc50d | 101 | fNclustMax= ((AliDAJetHeader*)fHeader)->GetFixedCl() ? |
102 | ((AliDAJetHeader*)fHeader)->GetNclustMax() | |
103 | : | |
104 | TMath::Max((Int_t)TMath::Sqrt(fNin),5); | |
7c679be0 | 105 | fXEta=new Double_t[fNin]; fXPhi=new Double_t[fNin]; |
106 | fPx = new TVectorD(fNin); | |
107 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
108 | TLorentzVector *lv=(TLorentzVector*)lvArray->At(iIn); | |
109 | fXEta[iIn] = lv->Eta(); | |
110 | fXPhi[iIn] = lv->Phi()<0 ? lv->Phi() + 2*TMath::Pi() : lv->Phi(); | |
111 | (*fPx)(iIn)=lv->Pt(); | |
112 | dEtSum+=(*fPx)(iIn); | |
113 | } | |
114 | for (Int_t iIn=0; iIn<fNin; iIn++) (*fPx)(iIn)=(*fPx)(iIn)/dEtSum; | |
115 | ||
116 | Int_t njdim=2*fNclustMax+1; | |
117 | fPyx = new TMatrixD(fNin,njdim); | |
118 | fY = new TMatrixD(4,njdim); | |
119 | fPy= new TVectorD(njdim); | |
120 | fY->Zero();fPyx->Zero();fPy->Zero(); | |
121 | (*fPy)(0)=1; | |
122 | TMatrixDColumn(*fPyx,0)=1; | |
123 | Double_t ypos=0,xpos=0; | |
124 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
125 | (*fY)(0,0)+=(*fPx)(iIn)*fXEta[iIn]; | |
126 | ypos+=(*fPx)(iIn)*TMath::Sin(fXPhi[iIn]); | |
127 | xpos+=(*fPx)(iIn)*TMath::Cos(fXPhi[iIn]); | |
128 | } | |
129 | (*fY)(1,0)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2*TMath::Pi(); | |
130 | lvArray->Delete(); | |
131 | } | |
132 | ||
133 | //----------------------------------------------------------------------------------- | |
134 | void AliDAJetFinder::DoubleClusters(Int_t nc,Int_t &nk) | |
135 | { | |
136 | for(Int_t iClust=0; iClust<nc; iClust++){ | |
137 | (*fPy)(iClust)=(*fPy)(iClust)/2; | |
138 | (*fPy)(nc+iClust)=(*fPy)(iClust); | |
139 | for(Int_t iComp=0; iComp<3; iComp++) (*fY)(iComp,nc+iClust)=(*fY)(iComp,iClust); | |
140 | } | |
141 | nk=2*nc; | |
142 | } | |
143 | ||
144 | //----------------------------------------------------------------------------------- | |
145 | void AliDAJetFinder::Annealing(Int_t nk) | |
146 | { | |
147 | // Main part of the algorithm | |
148 | const Double_t pi=TMath::Pi(); | |
149 | TVectorD *py = new TVectorD(nk); | |
150 | TVectorD *p = new TVectorD(nk); | |
151 | TMatrixD *y = new TMatrixD(4,nk); | |
152 | TMatrixD *y1 = new TMatrixD(4,nk); | |
153 | TMatrixD *ry = new TMatrixD(2,nk); | |
154 | Double_t Dist(TVectorD,TVectorD); | |
155 | ||
9e4cc50d | 156 | Double_t df[2]={((AliDAJetHeader*)fHeader)->GetEtaCut(),pi}; |
7c679be0 | 157 | TVectorD vPart(2); |
158 | Double_t *m = new Double_t[nk]; | |
159 | Double_t chi,chi1; | |
160 | do{ | |
161 | Int_t nloop=0; | |
162 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
163 | for (Int_t i=0; i<3; i++)(*y1)(i,iClust)=(*fY)(i,iClust); | |
164 | (*py)(iClust)=(*fPy)(iClust); | |
165 | } | |
166 | //perturbation of codevectors | |
167 | Double_t seed=1000000*gRandom->Rndm(24); | |
168 | ry->Randomize(-0.5,0.5,seed); | |
169 | for (Int_t i=0; i<2; i++){ | |
170 | for (Int_t iClust=0; iClust<nk/2; iClust++) | |
171 | (*y1)(i,iClust)+=((*ry)(i,iClust)+TMath::Sign(0.5,(*ry)(i,iClust)))*fDelta*df[i]; | |
172 | for (Int_t iClust=nk/2; iClust<nk; iClust++) | |
173 | (*y1)(i,iClust)-=((*ry)(i,iClust-nk/2)+TMath::Sign(0.5,(*ry)(i,iClust-nk/2)))*fDelta*df[i]; | |
174 | } | |
175 | do{ | |
176 | //recalculate conditional probabilities | |
177 | nloop++; | |
178 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
179 | vPart(0)=fXEta[iIn]; vPart(1)=fXPhi[iIn]; | |
180 | for(Int_t iClust=0; iClust<nk; iClust++){ | |
181 | (*fPyx)(iIn,iClust)=-log((*py)(iClust))+fBeta*Dist(vPart,TMatrixDColumn(*y1,iClust)); | |
182 | m[iClust]=(*fPyx)(iIn,iClust); | |
183 | } | |
184 | Double_t pyxNorm=0; | |
185 | Double_t minPyx=TMath::MinElement(nk,m); | |
186 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
187 | (*fPyx)(iIn,iClust)-=minPyx; | |
188 | (*fPyx)(iIn,iClust)=exp(-(*fPyx)(iIn,iClust)); | |
189 | pyxNorm+=(*fPyx)(iIn,iClust); | |
190 | } | |
191 | for (Int_t iClust=0; iClust<nk; iClust++) (*fPyx)(iIn,iClust)/=pyxNorm; | |
192 | } | |
193 | p->Zero(); | |
194 | y->Zero(); | |
195 | //recalculate codevectors | |
196 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
197 | Double_t xpos=0,ypos=0,pxy; | |
198 | for (Int_t iIn=0; iIn<fNin; iIn++) (*p)(iClust)+=(*fPx)(iIn)*(*fPyx)(iIn,iClust); | |
199 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
200 | pxy=(*fPx)(iIn)*(*fPyx)(iIn,iClust)/(*p)(iClust); | |
201 | ypos+=pxy*TMath::Sin(fXPhi[iIn]); | |
202 | xpos+=pxy*TMath::Cos(fXPhi[iIn]); | |
203 | (*y)(0,iClust)+=pxy*fXEta[iIn]; | |
204 | } | |
205 | (*y)(1,iClust)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2*pi; | |
206 | } | |
207 | //verify codevectors' stability | |
208 | chi=0; | |
209 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
210 | chi1=TMath::CosH((*y1)(0,iClust)-(*y)(0,iClust))-TMath::Cos((*y1)(1,iClust)-(*y)(1,iClust)); | |
211 | chi1/=(2*TMath::CosH((*y1)(0,iClust))*TMath::CosH((*y)(0,iClust))); | |
212 | chi1*=chi1; | |
213 | if (chi1>chi) chi=chi1; | |
214 | } | |
215 | chi=TMath::Sqrt(chi); | |
216 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
217 | for (Int_t i=0; i<2; i++) (*y1)(i,iClust)=(*y)(i,iClust); | |
218 | (*py)(iClust)=(*p)(iClust); | |
219 | } | |
220 | if (nloop>fNloopMax){ | |
221 | if (chi<fEpsMax || nloop>500) break; | |
222 | } | |
223 | }while (chi>fEps); | |
224 | }while (chi>fEpsMax); | |
225 | for (Int_t iClust=0; iClust<nk; iClust++){ //set codevectors and probability equal to those calculated | |
226 | for (Int_t i=0; i<2; i++) (*fY)(i,iClust)=(*y)(i,iClust); | |
227 | (*fPy)(iClust)=(*p)(iClust); | |
228 | } | |
229 | delete py; | |
230 | delete p; | |
231 | delete y; | |
232 | delete y1; | |
233 | delete ry; | |
234 | delete [] m; | |
235 | } | |
236 | ||
237 | //----------------------------------------------------------------------------------- | |
238 | void AliDAJetFinder::NumCl(Int_t &nc,Int_t &nk) | |
239 | { | |
240 | static Bool_t growcl=true; | |
241 | ||
242 | if (nk==2) growcl=true; | |
243 | if (growcl){ | |
244 | //verify if two codevectors are equal within fAvDist | |
245 | Int_t *nSame = new Int_t[nk]; | |
246 | Int_t **iSame = new Int_t*[nk]; | |
247 | Int_t **cont = new Int_t*[nk]; | |
248 | for (Int_t iClust=0; iClust<nk; iClust++) cont[iClust]=new Int_t[nk],iSame[iClust]=new Int_t[nk]; | |
249 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
250 | iSame[iClust][iClust]=1; | |
251 | for (Int_t iClust1=iClust+1; iClust1<nk; iClust1++){ | |
252 | Double_t eta = (*fY)(0,iClust) ; Double_t phi = (*fY)(1,iClust); | |
253 | Double_t eta1 = (*fY)(0,iClust1); Double_t phi1 = (*fY)(1,iClust1); | |
254 | Double_t distCl=(TMath::CosH(eta-eta1)-TMath::Cos(phi-phi1))/(2*TMath::CosH(eta)*TMath::CosH(eta1)); | |
255 | if (distCl < fAvDist) iSame[iClust][iClust1]=iSame[iClust1][iClust]=1; | |
256 | } | |
257 | } | |
258 | ReduceClusters(iSame,nk,nc,cont,nSame); | |
259 | if (nc >= fNclustMax) growcl=false; | |
260 | //recalculate the nc distinct codevectors | |
261 | TMatrixD *pyx = new TMatrixD(fNin,2*nc); | |
262 | TVectorD *py = new TVectorD(nk); | |
263 | TMatrixD *y1 = new TMatrixD(3,nk); | |
264 | for (Int_t iClust=0; iClust<nc; iClust++){ | |
265 | for(Int_t j=0; j<nSame[iClust]; j++){ | |
266 | Int_t iClust1 = cont[iClust][j]; | |
267 | for (Int_t iIn=0; iIn<fNin; iIn++) (*pyx)(iIn,iClust)+=(*fPyx)(iIn,iClust1); | |
268 | (*py)(iClust)+=(*fPy)(iClust1); | |
269 | for (Int_t i=0; i<2; i++) (*y1)(i,iClust)+=(*fY)(i,iClust1); | |
270 | } | |
271 | for (Int_t i=0; i<2; i++) (*y1)(i,iClust)/=nSame[iClust]; | |
272 | } | |
273 | if (nc > nk/2){ | |
274 | for (Int_t iClust=0; iClust<nc; iClust++){ | |
275 | for (Int_t iIn=0; iIn<fNin; iIn++) (*fPyx)(iIn,iClust)=(*pyx)(iIn,iClust); | |
276 | for (Int_t iComp=0; iComp<2; iComp++) (*fY)(iComp,iClust)=(*y1)(iComp,iClust); | |
277 | (*fPy)(iClust)=(*py)(iClust); | |
278 | } | |
279 | nk=nc; | |
280 | if (growcl) DoubleClusters(nc,nk); | |
281 | } | |
282 | delete [] nSame; | |
283 | delete [] iSame; | |
284 | delete [] cont; | |
285 | delete pyx; | |
286 | delete py; | |
287 | delete y1; | |
288 | } | |
289 | ||
290 | } | |
291 | ||
292 | //----------------------------------------------------------------------------------- | |
293 | void AliDAJetFinder::ReduceClusters(Int_t **iSame,Int_t nc,Int_t &ncout,Int_t **cont,Int_t *nSameOut) | |
294 | { | |
295 | Int_t *nSame = new Int_t[nc]; | |
296 | Int_t *iperm = new Int_t[nc]; | |
297 | Int_t *go = new Int_t[nc]; | |
298 | for (Int_t iCl=0; iCl<nc; iCl++){ | |
299 | nSame[iCl]=0; | |
300 | for (Int_t jCl=0; jCl<nc; jCl++) nSame[iCl]+=iSame[iCl][jCl]; | |
301 | iperm[iCl]=iCl; | |
302 | go[iCl]=1; | |
303 | } | |
304 | TMath::Sort(nc,nSame,iperm,true); | |
305 | Int_t l=0; | |
306 | for (Int_t iCl=0; iCl<nc; iCl++){ | |
307 | Int_t k=iperm[iCl]; | |
308 | if (go[k] == 1){ | |
309 | Int_t m=0; | |
310 | for (Int_t jCl=0; jCl<nc; jCl++){ | |
311 | if (iSame[k][jCl] == 1){ | |
312 | cont[l][m]=jCl; | |
313 | go[jCl]=0; | |
314 | m++; | |
315 | } | |
316 | } | |
317 | nSameOut[l]=m; | |
318 | l++; | |
319 | } | |
320 | } | |
321 | ncout=l; | |
322 | delete [] nSame; | |
323 | delete [] iperm; | |
324 | delete [] go; | |
325 | } | |
326 | ||
327 | //----------------------------------------------------------------------------------- | |
328 | void AliDAJetFinder::EndDetAnn(Int_t &nk,Int_t *xx,Double_t etx) | |
329 | { | |
330 | //now assign each particle to only one cluster | |
331 | Double_t *clusters=new Double_t[nk]; | |
332 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
333 | for (Int_t iClust=0; iClust<nk; iClust++) clusters[iClust]=(*fPyx)(iIn,iClust); | |
334 | xx[iIn]=TMath::LocMax(nk,clusters); | |
335 | } | |
336 | delete [] clusters; | |
337 | ||
338 | //recalculate codevectors, having all p(y|x)=0 or 1 | |
339 | fY->Zero(); | |
340 | fPyx->Zero(); | |
341 | fPy->Zero(); | |
342 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
343 | Int_t iClust=xx[iIn]; | |
344 | (*fPyx)(iIn,iClust)=1; | |
345 | (*fPy)(iClust)+=(*fPx)(iIn); | |
346 | (*fY)(0,iClust)+=(*fPx)(iIn)*fXEta[iIn]; | |
347 | (*fY)(3,iClust)+=(*fPx)(iIn)*etx; | |
348 | } | |
349 | Int_t k=0; | |
350 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
351 | if ((*fPy)(iClust)>0){ | |
352 | Double_t xpos=0,ypos=0,pxy; | |
353 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
354 | pxy=(*fPx)(iIn)*(*fPyx)(iIn,iClust)/(*fPy)(iClust); | |
355 | ypos+=pxy*TMath::Sin(fXPhi[iIn]); | |
356 | xpos+=pxy*TMath::Cos(fXPhi[iIn]); | |
357 | if (xx[iIn]==iClust) xx[iIn]=k; | |
358 | } | |
359 | (*fY)(0,k)=(*fY)(0,iClust)/(*fPy)(iClust); | |
360 | (*fY)(1,k)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2*TMath::Pi(); | |
361 | (*fY)(3,k)=(*fY)(3,iClust); | |
362 | k++; | |
363 | } | |
364 | } | |
365 | nk=k; | |
366 | } | |
367 | ||
368 | //----------------------------------------------------------------------------------- | |
369 | void AliDAJetFinder::StoreJets(Int_t nk,Int_t *xx) | |
370 | { | |
371 | //evaluate significant clusters properties | |
372 | const Double_t pi=TMath::Pi(); | |
9e4cc50d | 373 | Double_t dMeanDist=TMath::Sqrt(4*((AliDAJetHeader*)fHeader)->GetEtaCut()*pi/fNin); |
7c679be0 | 374 | Bool_t *isJet = new Bool_t[nk]; |
375 | Double_t *etNoBg= new Double_t[nk]; | |
376 | Double_t *dDeltaEta=new Double_t[nk]; | |
377 | Double_t *dDeltaPhi=new Double_t[nk]; | |
378 | Double_t *surf = new Double_t[nk]; | |
379 | Double_t *etDens= new Double_t[nk]; | |
380 | for (Int_t iClust=0; iClust<nk; iClust++){ //clusters loop | |
381 | isJet[iClust]=false; | |
382 | Double_t dEtaMin=10.,dEtaMax=-10.,dPhiMin=10.,dPhiMax=0.; | |
383 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
384 | if (xx[iIn]!=iClust) continue; | |
385 | if (fXEta[iIn] < dEtaMin) dEtaMin=fXEta[iIn]; | |
386 | if (fXEta[iIn] > dEtaMax) dEtaMax=fXEta[iIn]; | |
387 | Double_t dPhi=fXPhi[iIn]-(*fY)(1,iClust); | |
388 | if (dPhi > pi ) dPhi-=2*pi; | |
389 | else if (dPhi < (-1)*pi) dPhi+=2*pi; | |
390 | if (dPhi < dPhiMin) dPhiMin=dPhi; | |
391 | else if (dPhi > dPhiMax) dPhiMax=dPhi; | |
392 | } | |
393 | dDeltaEta[iClust]=dEtaMax-dEtaMin+dMeanDist; | |
394 | dDeltaPhi[iClust]=dPhiMax-dPhiMin+dMeanDist; | |
395 | surf[iClust]=0.25*pi*dDeltaEta[iClust]*dDeltaPhi[iClust]; | |
396 | etDens[iClust]=(*fY)(3,iClust)/surf[iClust]; | |
397 | } | |
398 | ||
9e4cc50d | 399 | if (((AliDAJetHeader*)fHeader)->GetSelJets()){ |
7c679be0 | 400 | for (Int_t iClust=0; iClust<nk; iClust++){ |
401 | if (!isJet[iClust]){ | |
402 | Double_t etDensMed=0.; | |
403 | Double_t etDensSqr=0.; | |
404 | Int_t norm=0; | |
405 | for (Int_t iClust1=0; iClust1<nk; iClust1++){ | |
406 | if(iClust1!=iClust){ | |
407 | etDensMed+=etDens[iClust1]; | |
408 | etDensSqr+=TMath::Power(etDens[iClust1],2); | |
409 | norm++; | |
410 | } | |
411 | } | |
412 | etDensMed/=TMath::Max(norm,1); | |
413 | etDensSqr/=TMath::Max(norm,1); | |
414 | Double_t deltaEtDens=TMath::Sqrt(etDensSqr-TMath::Power(etDensMed,2)); | |
415 | if ((*fY)(3,iClust) > (etDensMed+deltaEtDens)*surf[iClust]) isJet[iClust]=kTRUE; | |
416 | etNoBg[iClust]=(*fY)(3,iClust)-etDensMed*surf[iClust]; | |
417 | } | |
418 | } | |
419 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
420 | if (isJet[iClust]){ | |
421 | Double_t etDensMed=0; | |
9e4cc50d | 422 | Double_t extSurf=4*((AliDAJetHeader*)fHeader)->GetEtaCut()*pi; |
7c679be0 | 423 | for (Int_t iClust1=0; iClust1<nk; iClust1++){ |
424 | if (!isJet[iClust1]) etDensMed+=(*fY)(3,iClust1); | |
425 | else extSurf-=surf[iClust1]; | |
426 | } | |
427 | etDensMed/=extSurf; | |
428 | etNoBg[iClust]=(*fY)(3,iClust)-etDensMed*surf[iClust]; | |
10bd125d | 429 | if (etNoBg[iClust]<((AliDAJetHeader*)fHeader)->GetEtMin()){ |
430 | isJet[iClust]=kFALSE; | |
431 | iClust=-1; | |
432 | } | |
7c679be0 | 433 | } |
434 | } | |
435 | } else { | |
436 | for (Int_t iClust=0; iClust<nk; iClust++) isJet[iClust]=true; | |
437 | } | |
438 | delete [] etDens; | |
439 | delete [] surf; | |
440 | ||
441 | //now add selected jets to the list | |
442 | Int_t *inJet = new Int_t[fNin]; | |
443 | TRefArray *refs = 0; | |
444 | Bool_t fromAod = !strcmp(fReader->ClassName(),"AliJetAODReader"); | |
445 | if (fromAod) refs = fReader->GetReferences(); | |
446 | for (Int_t iClust=0; iClust<nk; iClust++){ //clusters loop | |
447 | if (isJet[iClust]){ //choose cluster | |
448 | Float_t px,py,pz,en; | |
449 | px = (*fY)(3,iClust)*TMath::Cos((*fY)(1,iClust)); | |
450 | py = (*fY)(3,iClust)*TMath::Sin((*fY)(1,iClust)); | |
451 | pz = (*fY)(3,iClust)/TMath::Tan(2.0 * TMath::ATan(TMath::Exp(-(*fY)(0,iClust)))); | |
452 | en = TMath::Sqrt(px * px + py * py + pz * pz); | |
453 | AliAODJet jet(px, py, pz, en); | |
454 | if (fromAod) | |
455 | for (Int_t iIn=0; iIn<fNin; iIn++) if (xx[iIn]==iClust) jet.AddTrack(refs->At(iIn)); | |
456 | AddJet(jet); | |
457 | printf("jet %d, Eta: %f, Phi: %f, Et: %f\n",iClust,jet.Eta(),jet.Phi(),jet.Pt()); | |
458 | } | |
459 | } | |
460 | delete [] dDeltaEta; delete [] dDeltaPhi; | |
461 | delete [] etNoBg; | |
462 | delete [] isJet; | |
463 | delete [] inJet; | |
464 | } | |
465 | ||
466 | //----------------------------------------------------------------------------------- | |
467 | Double_t Dist(TVectorD x,TVectorD y) | |
468 | { | |
469 | // Squared distance | |
470 | const Double_t pi=TMath::Pi(); | |
471 | Double_t dphi=TMath::Abs(x(1)-y(1)); | |
472 | if (dphi > pi) dphi=2*pi-dphi; | |
473 | Double_t dist=pow(x(0)-y(0),2)+pow(dphi,2); | |
474 | return dist; | |
475 | } |