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7c679be0 | 1 | // ************************************************************************** |
2 | // * Copyright(c) 1998-1999, ALICE Experiment at CERN, All rights reserved. * | |
3 | // * * | |
4 | // * Author: The ALICE Off-line Project. * | |
5 | // * Contributors are mentioned in the code where appropriate. * | |
6 | // * * | |
7 | // * Permission to use, copy, modify and distribute this software and its * | |
8 | // * documentation strictly for non-commercial purposes is hereby granted * | |
9 | // * without fee, provided that the above copyright notice appears in all * | |
10 | // * copies and that both the copyright notice and this permission notice * | |
11 | // * appear in the supporting documentation. The authors make no claims * | |
12 | // * about the suitability of this software for any purpose. It is * | |
13 | // * provided "as is" without express or implied warranty. * | |
14 | // ************************************************************************** | |
15 | ||
16 | //----------------------------------------------------------------------------------- | |
17 | // Jet finder based on Deterministic Annealing | |
18 | // For further informations about the DA working features see: | |
19 | // Phys.Lett. B601 (2004) 56-63 (http://arxiv.org/abs/hep-ph/0407214) | |
20 | // Author: Davide Perrino (davide.perrino@ba.infn.it, davide.perrino@cern.ch) | |
21 | //----------------------------------------------------------------------------------- | |
22 | ||
23 | #include <TMath.h> | |
24 | #include <TRandom.h> | |
25 | #include <TClonesArray.h> | |
26 | #include "AliJetReader.h" | |
27 | #include "AliDAJetHeader.h" | |
28 | #include "AliDAJetFinder.h" | |
29 | ||
30 | ||
31 | ClassImp(AliDAJetFinder) | |
32 | ||
33 | ||
34 | //----------------------------------------------------------------------------------- | |
35 | AliDAJetFinder::AliDAJetFinder(): | |
36 | fAlpha(1.01), | |
37 | fDelta(1e-8), | |
38 | fAvDist(1e-6), | |
39 | fEps(1e-4), | |
40 | fEpsMax(1e-2), | |
41 | fNloopMax(100), | |
42 | fBeta(0.1), | |
43 | fNclustMax(0), | |
44 | fPyx(0x0), | |
45 | fY(0x0), | |
46 | fPx(0x0), | |
47 | fPy(0x0), | |
48 | fXEta(0x0), | |
49 | fXPhi(0x0), | |
50 | fNin(0), | |
51 | fHeader(0x0) | |
52 | { | |
53 | // Constructor | |
54 | } | |
55 | ||
56 | //----------------------------------------------------------------------------------- | |
57 | AliDAJetFinder::~AliDAJetFinder() | |
58 | { | |
59 | // Destructor | |
60 | delete fHeader; | |
61 | delete fPyx; | |
62 | delete fY; | |
63 | delete fPx; | |
64 | delete fPy; | |
65 | delete [] fXEta; | |
66 | delete [] fXPhi; | |
67 | } | |
68 | ||
69 | //----------------------------------------------------------------------------------- | |
70 | void AliDAJetFinder::FindJets() | |
71 | { | |
72 | // Find the jets in current event | |
73 | // | |
74 | Float_t betaStop=100.; | |
75 | ||
76 | Double_t dEtSum=0; | |
77 | InitDetAnn(dEtSum); | |
78 | if (!fNin) return; | |
79 | ||
80 | Int_t nc=1,nk; | |
81 | DoubleClusters(nc,nk); | |
82 | do{ //loop over beta | |
83 | fBeta*=fAlpha; | |
84 | Annealing(nk); | |
85 | NumCl(nc,nk); | |
86 | }while((fBeta<betaStop || nc<4) && nc<fNclustMax); | |
87 | ||
88 | Int_t *xx=new Int_t[fNin]; | |
89 | EndDetAnn(nk,xx,dEtSum); | |
90 | StoreJets(nk,xx); | |
91 | delete [] xx; | |
92 | ||
93 | } | |
94 | ||
95 | //----------------------------------------------------------------------------------- | |
96 | void AliDAJetFinder::InitDetAnn(Double_t &dEtSum) | |
97 | { | |
98 | //Initialise the variables used by the algorithm | |
99 | fBeta=0.1; | |
100 | TClonesArray *lvArray = fReader->GetMomentumArray(); | |
101 | fNin = lvArray->GetEntries(); | |
102 | fNclustMax= fHeader->GetFixedCl() ? fHeader->GetNclustMax() : TMath::Max((Int_t)TMath::Sqrt(fNin),5); | |
103 | fXEta=new Double_t[fNin]; fXPhi=new Double_t[fNin]; | |
104 | fPx = new TVectorD(fNin); | |
105 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
106 | TLorentzVector *lv=(TLorentzVector*)lvArray->At(iIn); | |
107 | fXEta[iIn] = lv->Eta(); | |
108 | fXPhi[iIn] = lv->Phi()<0 ? lv->Phi() + 2*TMath::Pi() : lv->Phi(); | |
109 | (*fPx)(iIn)=lv->Pt(); | |
110 | dEtSum+=(*fPx)(iIn); | |
111 | } | |
112 | for (Int_t iIn=0; iIn<fNin; iIn++) (*fPx)(iIn)=(*fPx)(iIn)/dEtSum; | |
113 | ||
114 | Int_t njdim=2*fNclustMax+1; | |
115 | fPyx = new TMatrixD(fNin,njdim); | |
116 | fY = new TMatrixD(4,njdim); | |
117 | fPy= new TVectorD(njdim); | |
118 | fY->Zero();fPyx->Zero();fPy->Zero(); | |
119 | (*fPy)(0)=1; | |
120 | TMatrixDColumn(*fPyx,0)=1; | |
121 | Double_t ypos=0,xpos=0; | |
122 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
123 | (*fY)(0,0)+=(*fPx)(iIn)*fXEta[iIn]; | |
124 | ypos+=(*fPx)(iIn)*TMath::Sin(fXPhi[iIn]); | |
125 | xpos+=(*fPx)(iIn)*TMath::Cos(fXPhi[iIn]); | |
126 | } | |
127 | (*fY)(1,0)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2*TMath::Pi(); | |
128 | lvArray->Delete(); | |
129 | } | |
130 | ||
131 | //----------------------------------------------------------------------------------- | |
132 | void AliDAJetFinder::DoubleClusters(Int_t nc,Int_t &nk) | |
133 | { | |
134 | for(Int_t iClust=0; iClust<nc; iClust++){ | |
135 | (*fPy)(iClust)=(*fPy)(iClust)/2; | |
136 | (*fPy)(nc+iClust)=(*fPy)(iClust); | |
137 | for(Int_t iComp=0; iComp<3; iComp++) (*fY)(iComp,nc+iClust)=(*fY)(iComp,iClust); | |
138 | } | |
139 | nk=2*nc; | |
140 | } | |
141 | ||
142 | //----------------------------------------------------------------------------------- | |
143 | void AliDAJetFinder::Annealing(Int_t nk) | |
144 | { | |
145 | // Main part of the algorithm | |
146 | const Double_t pi=TMath::Pi(); | |
147 | TVectorD *py = new TVectorD(nk); | |
148 | TVectorD *p = new TVectorD(nk); | |
149 | TMatrixD *y = new TMatrixD(4,nk); | |
150 | TMatrixD *y1 = new TMatrixD(4,nk); | |
151 | TMatrixD *ry = new TMatrixD(2,nk); | |
152 | Double_t Dist(TVectorD,TVectorD); | |
153 | ||
154 | Double_t df[2]={fHeader->GetEtaCut(),pi}; | |
155 | TVectorD vPart(2); | |
156 | Double_t *m = new Double_t[nk]; | |
157 | Double_t chi,chi1; | |
158 | do{ | |
159 | Int_t nloop=0; | |
160 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
161 | for (Int_t i=0; i<3; i++)(*y1)(i,iClust)=(*fY)(i,iClust); | |
162 | (*py)(iClust)=(*fPy)(iClust); | |
163 | } | |
164 | //perturbation of codevectors | |
165 | Double_t seed=1000000*gRandom->Rndm(24); | |
166 | ry->Randomize(-0.5,0.5,seed); | |
167 | for (Int_t i=0; i<2; i++){ | |
168 | for (Int_t iClust=0; iClust<nk/2; iClust++) | |
169 | (*y1)(i,iClust)+=((*ry)(i,iClust)+TMath::Sign(0.5,(*ry)(i,iClust)))*fDelta*df[i]; | |
170 | for (Int_t iClust=nk/2; iClust<nk; iClust++) | |
171 | (*y1)(i,iClust)-=((*ry)(i,iClust-nk/2)+TMath::Sign(0.5,(*ry)(i,iClust-nk/2)))*fDelta*df[i]; | |
172 | } | |
173 | do{ | |
174 | //recalculate conditional probabilities | |
175 | nloop++; | |
176 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
177 | vPart(0)=fXEta[iIn]; vPart(1)=fXPhi[iIn]; | |
178 | for(Int_t iClust=0; iClust<nk; iClust++){ | |
179 | (*fPyx)(iIn,iClust)=-log((*py)(iClust))+fBeta*Dist(vPart,TMatrixDColumn(*y1,iClust)); | |
180 | m[iClust]=(*fPyx)(iIn,iClust); | |
181 | } | |
182 | Double_t pyxNorm=0; | |
183 | Double_t minPyx=TMath::MinElement(nk,m); | |
184 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
185 | (*fPyx)(iIn,iClust)-=minPyx; | |
186 | (*fPyx)(iIn,iClust)=exp(-(*fPyx)(iIn,iClust)); | |
187 | pyxNorm+=(*fPyx)(iIn,iClust); | |
188 | } | |
189 | for (Int_t iClust=0; iClust<nk; iClust++) (*fPyx)(iIn,iClust)/=pyxNorm; | |
190 | } | |
191 | p->Zero(); | |
192 | y->Zero(); | |
193 | //recalculate codevectors | |
194 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
195 | Double_t xpos=0,ypos=0,pxy; | |
196 | for (Int_t iIn=0; iIn<fNin; iIn++) (*p)(iClust)+=(*fPx)(iIn)*(*fPyx)(iIn,iClust); | |
197 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
198 | pxy=(*fPx)(iIn)*(*fPyx)(iIn,iClust)/(*p)(iClust); | |
199 | ypos+=pxy*TMath::Sin(fXPhi[iIn]); | |
200 | xpos+=pxy*TMath::Cos(fXPhi[iIn]); | |
201 | (*y)(0,iClust)+=pxy*fXEta[iIn]; | |
202 | } | |
203 | (*y)(1,iClust)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2*pi; | |
204 | } | |
205 | //verify codevectors' stability | |
206 | chi=0; | |
207 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
208 | chi1=TMath::CosH((*y1)(0,iClust)-(*y)(0,iClust))-TMath::Cos((*y1)(1,iClust)-(*y)(1,iClust)); | |
209 | chi1/=(2*TMath::CosH((*y1)(0,iClust))*TMath::CosH((*y)(0,iClust))); | |
210 | chi1*=chi1; | |
211 | if (chi1>chi) chi=chi1; | |
212 | } | |
213 | chi=TMath::Sqrt(chi); | |
214 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
215 | for (Int_t i=0; i<2; i++) (*y1)(i,iClust)=(*y)(i,iClust); | |
216 | (*py)(iClust)=(*p)(iClust); | |
217 | } | |
218 | if (nloop>fNloopMax){ | |
219 | if (chi<fEpsMax || nloop>500) break; | |
220 | } | |
221 | }while (chi>fEps); | |
222 | }while (chi>fEpsMax); | |
223 | for (Int_t iClust=0; iClust<nk; iClust++){ //set codevectors and probability equal to those calculated | |
224 | for (Int_t i=0; i<2; i++) (*fY)(i,iClust)=(*y)(i,iClust); | |
225 | (*fPy)(iClust)=(*p)(iClust); | |
226 | } | |
227 | delete py; | |
228 | delete p; | |
229 | delete y; | |
230 | delete y1; | |
231 | delete ry; | |
232 | delete [] m; | |
233 | } | |
234 | ||
235 | //----------------------------------------------------------------------------------- | |
236 | void AliDAJetFinder::NumCl(Int_t &nc,Int_t &nk) | |
237 | { | |
238 | static Bool_t growcl=true; | |
239 | ||
240 | if (nk==2) growcl=true; | |
241 | if (growcl){ | |
242 | //verify if two codevectors are equal within fAvDist | |
243 | Int_t *nSame = new Int_t[nk]; | |
244 | Int_t **iSame = new Int_t*[nk]; | |
245 | Int_t **cont = new Int_t*[nk]; | |
246 | for (Int_t iClust=0; iClust<nk; iClust++) cont[iClust]=new Int_t[nk],iSame[iClust]=new Int_t[nk]; | |
247 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
248 | iSame[iClust][iClust]=1; | |
249 | for (Int_t iClust1=iClust+1; iClust1<nk; iClust1++){ | |
250 | Double_t eta = (*fY)(0,iClust) ; Double_t phi = (*fY)(1,iClust); | |
251 | Double_t eta1 = (*fY)(0,iClust1); Double_t phi1 = (*fY)(1,iClust1); | |
252 | Double_t distCl=(TMath::CosH(eta-eta1)-TMath::Cos(phi-phi1))/(2*TMath::CosH(eta)*TMath::CosH(eta1)); | |
253 | if (distCl < fAvDist) iSame[iClust][iClust1]=iSame[iClust1][iClust]=1; | |
254 | } | |
255 | } | |
256 | ReduceClusters(iSame,nk,nc,cont,nSame); | |
257 | if (nc >= fNclustMax) growcl=false; | |
258 | //recalculate the nc distinct codevectors | |
259 | TMatrixD *pyx = new TMatrixD(fNin,2*nc); | |
260 | TVectorD *py = new TVectorD(nk); | |
261 | TMatrixD *y1 = new TMatrixD(3,nk); | |
262 | for (Int_t iClust=0; iClust<nc; iClust++){ | |
263 | for(Int_t j=0; j<nSame[iClust]; j++){ | |
264 | Int_t iClust1 = cont[iClust][j]; | |
265 | for (Int_t iIn=0; iIn<fNin; iIn++) (*pyx)(iIn,iClust)+=(*fPyx)(iIn,iClust1); | |
266 | (*py)(iClust)+=(*fPy)(iClust1); | |
267 | for (Int_t i=0; i<2; i++) (*y1)(i,iClust)+=(*fY)(i,iClust1); | |
268 | } | |
269 | for (Int_t i=0; i<2; i++) (*y1)(i,iClust)/=nSame[iClust]; | |
270 | } | |
271 | if (nc > nk/2){ | |
272 | for (Int_t iClust=0; iClust<nc; iClust++){ | |
273 | for (Int_t iIn=0; iIn<fNin; iIn++) (*fPyx)(iIn,iClust)=(*pyx)(iIn,iClust); | |
274 | for (Int_t iComp=0; iComp<2; iComp++) (*fY)(iComp,iClust)=(*y1)(iComp,iClust); | |
275 | (*fPy)(iClust)=(*py)(iClust); | |
276 | } | |
277 | nk=nc; | |
278 | if (growcl) DoubleClusters(nc,nk); | |
279 | } | |
280 | delete [] nSame; | |
281 | delete [] iSame; | |
282 | delete [] cont; | |
283 | delete pyx; | |
284 | delete py; | |
285 | delete y1; | |
286 | } | |
287 | ||
288 | } | |
289 | ||
290 | //----------------------------------------------------------------------------------- | |
291 | void AliDAJetFinder::ReduceClusters(Int_t **iSame,Int_t nc,Int_t &ncout,Int_t **cont,Int_t *nSameOut) | |
292 | { | |
293 | Int_t *nSame = new Int_t[nc]; | |
294 | Int_t *iperm = new Int_t[nc]; | |
295 | Int_t *go = new Int_t[nc]; | |
296 | for (Int_t iCl=0; iCl<nc; iCl++){ | |
297 | nSame[iCl]=0; | |
298 | for (Int_t jCl=0; jCl<nc; jCl++) nSame[iCl]+=iSame[iCl][jCl]; | |
299 | iperm[iCl]=iCl; | |
300 | go[iCl]=1; | |
301 | } | |
302 | TMath::Sort(nc,nSame,iperm,true); | |
303 | Int_t l=0; | |
304 | for (Int_t iCl=0; iCl<nc; iCl++){ | |
305 | Int_t k=iperm[iCl]; | |
306 | if (go[k] == 1){ | |
307 | Int_t m=0; | |
308 | for (Int_t jCl=0; jCl<nc; jCl++){ | |
309 | if (iSame[k][jCl] == 1){ | |
310 | cont[l][m]=jCl; | |
311 | go[jCl]=0; | |
312 | m++; | |
313 | } | |
314 | } | |
315 | nSameOut[l]=m; | |
316 | l++; | |
317 | } | |
318 | } | |
319 | ncout=l; | |
320 | delete [] nSame; | |
321 | delete [] iperm; | |
322 | delete [] go; | |
323 | } | |
324 | ||
325 | //----------------------------------------------------------------------------------- | |
326 | void AliDAJetFinder::EndDetAnn(Int_t &nk,Int_t *xx,Double_t etx) | |
327 | { | |
328 | //now assign each particle to only one cluster | |
329 | Double_t *clusters=new Double_t[nk]; | |
330 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
331 | for (Int_t iClust=0; iClust<nk; iClust++) clusters[iClust]=(*fPyx)(iIn,iClust); | |
332 | xx[iIn]=TMath::LocMax(nk,clusters); | |
333 | } | |
334 | delete [] clusters; | |
335 | ||
336 | //recalculate codevectors, having all p(y|x)=0 or 1 | |
337 | fY->Zero(); | |
338 | fPyx->Zero(); | |
339 | fPy->Zero(); | |
340 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
341 | Int_t iClust=xx[iIn]; | |
342 | (*fPyx)(iIn,iClust)=1; | |
343 | (*fPy)(iClust)+=(*fPx)(iIn); | |
344 | (*fY)(0,iClust)+=(*fPx)(iIn)*fXEta[iIn]; | |
345 | (*fY)(3,iClust)+=(*fPx)(iIn)*etx; | |
346 | } | |
347 | Int_t k=0; | |
348 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
349 | if ((*fPy)(iClust)>0){ | |
350 | Double_t xpos=0,ypos=0,pxy; | |
351 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
352 | pxy=(*fPx)(iIn)*(*fPyx)(iIn,iClust)/(*fPy)(iClust); | |
353 | ypos+=pxy*TMath::Sin(fXPhi[iIn]); | |
354 | xpos+=pxy*TMath::Cos(fXPhi[iIn]); | |
355 | if (xx[iIn]==iClust) xx[iIn]=k; | |
356 | } | |
357 | (*fY)(0,k)=(*fY)(0,iClust)/(*fPy)(iClust); | |
358 | (*fY)(1,k)=(atan2(ypos,xpos)>0) ? atan2(ypos,xpos) : atan2(ypos,xpos)+2*TMath::Pi(); | |
359 | (*fY)(3,k)=(*fY)(3,iClust); | |
360 | k++; | |
361 | } | |
362 | } | |
363 | nk=k; | |
364 | } | |
365 | ||
366 | //----------------------------------------------------------------------------------- | |
367 | void AliDAJetFinder::StoreJets(Int_t nk,Int_t *xx) | |
368 | { | |
369 | //evaluate significant clusters properties | |
370 | const Double_t pi=TMath::Pi(); | |
371 | Double_t dMeanDist=TMath::Sqrt(4*fHeader->GetEtaCut()*pi/fNin); | |
372 | Bool_t *isJet = new Bool_t[nk]; | |
373 | Double_t *etNoBg= new Double_t[nk]; | |
374 | Double_t *dDeltaEta=new Double_t[nk]; | |
375 | Double_t *dDeltaPhi=new Double_t[nk]; | |
376 | Double_t *surf = new Double_t[nk]; | |
377 | Double_t *etDens= new Double_t[nk]; | |
378 | for (Int_t iClust=0; iClust<nk; iClust++){ //clusters loop | |
379 | isJet[iClust]=false; | |
380 | Double_t dEtaMin=10.,dEtaMax=-10.,dPhiMin=10.,dPhiMax=0.; | |
381 | for (Int_t iIn=0; iIn<fNin; iIn++){ | |
382 | if (xx[iIn]!=iClust) continue; | |
383 | if (fXEta[iIn] < dEtaMin) dEtaMin=fXEta[iIn]; | |
384 | if (fXEta[iIn] > dEtaMax) dEtaMax=fXEta[iIn]; | |
385 | Double_t dPhi=fXPhi[iIn]-(*fY)(1,iClust); | |
386 | if (dPhi > pi ) dPhi-=2*pi; | |
387 | else if (dPhi < (-1)*pi) dPhi+=2*pi; | |
388 | if (dPhi < dPhiMin) dPhiMin=dPhi; | |
389 | else if (dPhi > dPhiMax) dPhiMax=dPhi; | |
390 | } | |
391 | dDeltaEta[iClust]=dEtaMax-dEtaMin+dMeanDist; | |
392 | dDeltaPhi[iClust]=dPhiMax-dPhiMin+dMeanDist; | |
393 | surf[iClust]=0.25*pi*dDeltaEta[iClust]*dDeltaPhi[iClust]; | |
394 | etDens[iClust]=(*fY)(3,iClust)/surf[iClust]; | |
395 | } | |
396 | ||
397 | if (fHeader->GetSelJets()){ | |
398 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
399 | if (!isJet[iClust]){ | |
400 | Double_t etDensMed=0.; | |
401 | Double_t etDensSqr=0.; | |
402 | Int_t norm=0; | |
403 | for (Int_t iClust1=0; iClust1<nk; iClust1++){ | |
404 | if(iClust1!=iClust){ | |
405 | etDensMed+=etDens[iClust1]; | |
406 | etDensSqr+=TMath::Power(etDens[iClust1],2); | |
407 | norm++; | |
408 | } | |
409 | } | |
410 | etDensMed/=TMath::Max(norm,1); | |
411 | etDensSqr/=TMath::Max(norm,1); | |
412 | Double_t deltaEtDens=TMath::Sqrt(etDensSqr-TMath::Power(etDensMed,2)); | |
413 | if ((*fY)(3,iClust) > (etDensMed+deltaEtDens)*surf[iClust]) isJet[iClust]=kTRUE; | |
414 | etNoBg[iClust]=(*fY)(3,iClust)-etDensMed*surf[iClust]; | |
415 | } | |
416 | } | |
417 | for (Int_t iClust=0; iClust<nk; iClust++){ | |
418 | if (isJet[iClust]){ | |
419 | Double_t etDensMed=0; | |
420 | Double_t extSurf=4*fHeader->GetEtaCut()*pi; | |
421 | for (Int_t iClust1=0; iClust1<nk; iClust1++){ | |
422 | if (!isJet[iClust1]) etDensMed+=(*fY)(3,iClust1); | |
423 | else extSurf-=surf[iClust1]; | |
424 | } | |
425 | etDensMed/=extSurf; | |
426 | etNoBg[iClust]=(*fY)(3,iClust)-etDensMed*surf[iClust]; | |
427 | } | |
428 | } | |
429 | } else { | |
430 | for (Int_t iClust=0; iClust<nk; iClust++) isJet[iClust]=true; | |
431 | } | |
432 | delete [] etDens; | |
433 | delete [] surf; | |
434 | ||
435 | //now add selected jets to the list | |
436 | Int_t *inJet = new Int_t[fNin]; | |
437 | TRefArray *refs = 0; | |
438 | Bool_t fromAod = !strcmp(fReader->ClassName(),"AliJetAODReader"); | |
439 | if (fromAod) refs = fReader->GetReferences(); | |
440 | for (Int_t iClust=0; iClust<nk; iClust++){ //clusters loop | |
441 | if (isJet[iClust]){ //choose cluster | |
442 | Float_t px,py,pz,en; | |
443 | px = (*fY)(3,iClust)*TMath::Cos((*fY)(1,iClust)); | |
444 | py = (*fY)(3,iClust)*TMath::Sin((*fY)(1,iClust)); | |
445 | pz = (*fY)(3,iClust)/TMath::Tan(2.0 * TMath::ATan(TMath::Exp(-(*fY)(0,iClust)))); | |
446 | en = TMath::Sqrt(px * px + py * py + pz * pz); | |
447 | AliAODJet jet(px, py, pz, en); | |
448 | if (fromAod) | |
449 | for (Int_t iIn=0; iIn<fNin; iIn++) if (xx[iIn]==iClust) jet.AddTrack(refs->At(iIn)); | |
450 | AddJet(jet); | |
451 | printf("jet %d, Eta: %f, Phi: %f, Et: %f\n",iClust,jet.Eta(),jet.Phi(),jet.Pt()); | |
452 | } | |
453 | } | |
454 | delete [] dDeltaEta; delete [] dDeltaPhi; | |
455 | delete [] etNoBg; | |
456 | delete [] isJet; | |
457 | delete [] inJet; | |
458 | } | |
459 | ||
460 | //----------------------------------------------------------------------------------- | |
461 | Double_t Dist(TVectorD x,TVectorD y) | |
462 | { | |
463 | // Squared distance | |
464 | const Double_t pi=TMath::Pi(); | |
465 | Double_t dphi=TMath::Abs(x(1)-y(1)); | |
466 | if (dphi > pi) dphi=2*pi-dphi; | |
467 | Double_t dist=pow(x(0)-y(0),2)+pow(dphi,2); | |
468 | return dist; | |
469 | } |