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contamination also computed for user PID
[u/mrichter/AliRoot.git] / PWGPP / pid / doeffKa.C
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7484404e 1#include"TF1.h"
2#include"TH1D.h"
3#include"TH2F.h"
4#include"TMath.h"
5#include"TSystem.h"
6#include"TCanvas.h"
7#include"TFile.h"
8#include"TGraphErrors.h"
9#include"AliPIDperfContainer.h"
10
11int LoadLib();
9c5bbe8a 12void doeffKaUser(Int_t pos,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8);
7484404e 13void doeffKa(Int_t pos=1,Float_t prob=0.1,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8);
14TH2F *GetHistoKap(Float_t pt=1,Float_t ptM=1.1,Float_t pMinkp=0,Float_t pMinkn=0.,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8);
15TH2F *GetHistoKan(Float_t pt=1,Float_t ptM=1.1,Float_t pMinkn=0,Float_t pMinkp=0.,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8);
16void fit(TH1D *h,Float_t *a=NULL,char *opt="",char *opt2="",Float_t pt=1.5);
17void AddHisto(TH2F *h1,TH2F *h2,Float_t w);
9c5bbe8a 18TH2F *GetHistoUser(Int_t pos=1,Float_t pt=1,Float_t ptM=1.1,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8);
19TH2F *GetHistoPiUser(Int_t pos=1,Float_t pt=1,Float_t ptM=1.1,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8);
20TH2F *GetHistoKaUser(Int_t pos=1,Float_t pt=1,Float_t ptM=1.1,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8);
21TH2F *GetHistoPrUser(Int_t pos=1,Float_t pt=1,Float_t ptM=1.1,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8);
7484404e 22
a8ad4709 23TObject* fContPid1;
24TObject* fContPid2;
9c5bbe8a 25TObject* fContUser1;
26TObject* fContUser2;
a8ad4709 27const Int_t nBinPid = 14; // pt,eta, ptPip, ptPin, PPip, PPin, TOF3sigmaPip, TOF3sigmaPin, isPhiTrue, nsigmaPip, nsigmaPin
28// 0.985 < mass < 1.045 (60) and 0 < centrality < 100 (10)
29Int_t binPid[nBinPid] = {1/*ptPhi*/,8/*EtaPi*/,20/*pt+*/,20/*pt-*/,5/*P+*/,1/*P-*/,2/*TOFmatch+*/,2/*TOFmatch-*/,2/*istrue*/,4/*Nsigma+*/,4/*Nsigma-*/,1/*DeltaPhi+*/,1/*DeltaPhi-*/,1/*Psi*/};
30Float_t xmin[nBinPid] = {1,-0.8,0.3,0.3,0,0,-0.5,-0.5,-0.5,0,0,-TMath::Pi(),-TMath::Pi(),-TMath::Pi()/2};
31Float_t xmax[nBinPid] = {5,0.8,4.3,4.3,1,1,1.5,1.5,1.5,7.5,7.5,TMath::Pi(),TMath::Pi(),TMath::Pi()/2};
32
33TF1 *fsign;
34TF1 *fall;
35TF1 *fback;
36
37Int_t ifunc=0;
38
39Float_t fitmin = 0.99;
40Float_t fitmax = 1.045;
41
08b5b548 42Int_t cmin = 1;// min 1
43Int_t cmax = 8;// max 10
a8ad4709 44
45Float_t weightS = -1.;
46
bf2e05d5 47Int_t rebinsize = 1;
a8ad4709 48
49Int_t parplotted = 2;
50
51Bool_t isMC = kFALSE; // don't change this (is set automatically)
52Bool_t selectTrue = kTRUE; // put it to true to remove background (only for MC)
53Bool_t keepTrue = kFALSE; // put it to false to fit only background (only for MC)
54
55Bool_t kGoodMatch = kFALSE; // to check good matching
56
57Bool_t kSigma2vs3 = kFALSE; // to check good matching
58
59Bool_t require5sigma = kFALSE; // don't touch this flag
60
61Bool_t bayesVsigma = kFALSE; // only to do checks
62
63Bool_t kTOFmatch = kFALSE; // for combined PID requires TOF matching
64
08b5b548 65Bool_t kOverAll = kFALSE;
e34b28fe 66Bool_t kOverAllTOFmatch = kFALSE;
08b5b548 67Bool_t kOverAll2Sigma = kFALSE;
68
69TH2F *hmatched;
70TH2F *htracked;
a8ad4709 71
72Bool_t kLoaded=kFALSE;
7484404e 73int LoadLib(){
a8ad4709 74 weightS = -1.;
75
bf2e05d5 76 require5sigma = kFALSE;
77
a8ad4709 78 if(! kLoaded){
79 gSystem->Load("libVMC.so");
80 gSystem->Load("libPhysics.so");
81 gSystem->Load("libTree.so");
82 gSystem->Load("libMinuit.so");
83 gSystem->Load("libSTEERBase.so");
84 gSystem->Load("libANALYSIS.so");
85 gSystem->Load("libAOD.so");
86 gSystem->Load("libESD.so");
87 gSystem->Load("libANALYSIS.so");
88 gSystem->Load("libANALYSISalice.so");
89 gSystem->Load("libCORRFW.so");
90 gSystem->Load("libNetx.so");
91 gSystem->Load("libPWGPPpid.so");
92
93 TFile *f = new TFile("AnalysisResults.root");
a8ad4709 94 TList *l = (TList *) f->Get("contPhiBayes1");
08b5b548 95 TList *l2 = (TList *) f->Get("contPhiBayes2");
7484404e 96
97 if(!(l && l2)) return 0;
98
08b5b548 99 fContPid1 = (AliPIDperfContainer *) l->FindObject("contPID");
100 fContPid2 = (AliPIDperfContainer *) l->FindObject("contPID2");
9c5bbe8a 101 fContUser1 = (AliPIDperfContainer *) l->FindObject("contUserPID");
102 fContUser2 = (AliPIDperfContainer *) l->FindObject("contUserPID2");
08b5b548 103 hmatched = (TH2F *) l2->FindObject("hMatchKa");
104 htracked = (TH2F *) l2->FindObject("hTrackingKa");
a8ad4709 105 }
106 kLoaded = kTRUE;
107
108 // check if MC
109 Float_t x[] = {xmin[0]+0.001,xmin[1]+0.001,xmin[2]+0.001,xmin[3]+0.001,xmin[4]+0.001,xmin[5]+0.001,xmin[6]+0.001,xmin[7]+0.001,1/*trueMC*/,xmin[9],xmin[10]};
110 Float_t x2[] = {xmax[0],xmax[1],xmax[2],xmax[3],xmax[4],xmax[5],xmax[6],xmax[7],xmax[8],xmax[9],xmax[10]};
111
7484404e 112 AliPIDperfContainer *tmp = (AliPIDperfContainer *) fContPid1;
a8ad4709 113 TH1D *h = tmp->GetQA(0, x, x2)->ProjectionX("checkMC");
114
115 if(h->GetEntries()) isMC = kTRUE;
116 else isMC=kFALSE;
117
118 if(!isMC){
119 selectTrue = kFALSE;
120 keepTrue = kTRUE;
121 }
122 else{
123 printf("MC truth found!!!!!!\nIt is MC!!!!!!");
124 }
125
126 fsign = new TF1("fsign","[0]*TMath::Voigt(x-[1],[3],[2])*(x>0.987)*(x > 1.005 && x < 1.035 || [4])",fitmin,fitmax);
127 fback = new TF1("fback","([0]*sqrt(x-0.987) + [1]*(x-0.987) + [2]*sqrt(x-0.987)*(x-0.987) +[3]*(x-0.987)*(x-0.987)+[4]*(x-0.987)*(x-0.987)*sqrt(x-0.987))*(x>0.987)",fitmin,fitmax);
128 fall = new TF1("fall","([0]*TMath::Voigt(x-[1],[3],[2])*(x > 1.005 && x < 1.035 || [9]) + [4]*sqrt(x-0.987) + [5]*(x-0.987) + [6]*sqrt(x-0.987)*(x-0.987) +[7]*(x-0.987)*(x-0.987)+[8]*(x-0.987)*(x-0.987)*sqrt(x-0.987))*(x>0.987)",0.987,1.05);
129
130 if(isMC){
131 fsign->SetParameter(4,0);
132 fall->FixParameter(9,0);
133 }
134 else{
135 fsign->SetParameter(4,1);
136 fall->FixParameter(9,1);
137 }
138
139 fsign->SetLineColor(2);
140 fback->SetLineColor(4);
141
142 if(kSigma2vs3){
143 kGoodMatch=kFALSE;
144 kOverAll = 0;
145 }
146
147 if(bayesVsigma){
148 kOverAll = 0;
149 kGoodMatch=kFALSE;
150 kSigma2vs3=kFALSE;
151 kTOFmatch=kTRUE;
152 weightS = -0.7;
153 }
e34b28fe 154 if(kOverAll){
155 weightS = -0.7;
156 }
7484404e 157
158 return 1;
a8ad4709 159}
9c5bbe8a 160void doeffKaUser(Int_t pos,Float_t etaminkp,Float_t etamaxkp){
161 Int_t nptbin = binPid[2];
162 Float_t minptbin = xmin[2];
163 Float_t maxptbin = xmax[2];
164
165 TCanvas *c1 = new TCanvas();
166 c1->Divide((nptbin+1)/2,2);
167
168 Double_t xx[50],yyPi[50],yyKa[50],yyPr[50];
169 Double_t exx[50],eyyPi[50],eyyKa[50],eyyPr[50];
170
171 TH2F *hh;
172 TH1D *h;
173
174 Float_t b[100][3];
175 Float_t bPi[100][3];
176 Float_t bKa[100][3];
177 Float_t bPr[100][3];
178
179 char name[100];
180
181 for(Int_t i=0;i < nptbin;i++){
182 c1->cd(i+1);
183 Float_t ptmin = minptbin+(maxptbin-minptbin)/nptbin*(i);
184 Float_t ptmax = minptbin+(maxptbin-minptbin)/nptbin*(i+1);
185
186 xx[i] = (ptmin+ptmax)/2;
187 exx[i] = (-ptmin+ptmax)/2;
188
189 hh=GetHistoUser(pos,ptmin,ptmax,etaminkp,etamaxkp);
190 sprintf(name,"all%i",i);
191 h = hh->ProjectionX(name,cmin,cmax);
192 Int_t ntrial = 0;
193 Float_t chi2 = 10000;
194 while(ntrial < 3 && (chi2 > 20 + 1000*selectTrue)){
195 fit(h,b[i],"WW","",xx[i]);
196 fit(h,b[i],"","",xx[i]);
197 ntrial++;
198 chi2 = b[i][2];
199 }
200 printf("%i) %f +/- %f\n",i,b[i][0],b[i][1]);
201
202 hh=GetHistoPiUser(pos,ptmin,ptmax,etaminkp,etamaxkp);
203 sprintf(name,"pi%i",i);
204 h = hh->ProjectionX(name,cmin,cmax);
205 ntrial = 0;
206 chi2 = 10000;
207 while(ntrial < 3 && (chi2 > 20 + 1000*selectTrue)){
208 fit(h,bPi[i],"WW","",xx[i]);
209 fit(h,bPi[i],"","",xx[i]);
210 ntrial++;
211 chi2 = bPi[i][2];
212 }
213 printf("pi) %f +/- %f\n",bPi[i][0],bPi[i][1]);
214
215 hh=GetHistoKaUser(pos,ptmin,ptmax,etaminkp,etamaxkp);
216 sprintf(name,"ka%i",i);
217 h = hh->ProjectionX(name,cmin,cmax);
218 ntrial = 0;
219 chi2 = 10000;
220 while(ntrial < 3 && (chi2 > 20 + 1000*selectTrue)){
221 fit(h,bKa[i],"WW","",xx[i]);
222 fit(h,bKa[i],"","",xx[i]);
223 ntrial++;
224 chi2 = bKa[i][2];
225 }
226 printf("ka) %f +/- %f\n",bKa[i][0],bKa[i][1]);
227
228 hh=GetHistoPrUser(pos,ptmin,ptmax,etaminkp,etamaxkp);
229 sprintf(name,"pr%i",i);
230 h = hh->ProjectionX(name,cmin,cmax);
231 ntrial = 0;
232 chi2 = 10000;
233 while(ntrial < 3 && (chi2 > 20 + 1000*selectTrue)){
234 fit(h,bPr[i],"WW","",xx[i]);
235 fit(h,bPr[i],"","",xx[i]);
236 ntrial++;
237 chi2 = bPr[i][2];
238 }
239 printf("pr) %f +/- %f\n",bPr[i][0],bPr[i][1]);
240
241 yyPi[i] = bPi[i][0] / b[i][0];
242 yyKa[i] = bKa[i][0] / b[i][0];
243 yyPr[i] = bPr[i][0] / b[i][0];
244
245 eyyPi[i] = bPi[i][1]/bPi[i][0]*yyPi[i];
246 eyyKa[i] = bKa[i][1]/bKa[i][0]*yyKa[i];
247 eyyPr[i] = bPr[i][1]/bPr[i][0]*yyPr[i];
248 }
249
250 /*TCanvas *c2 =*/ new TCanvas();
251 TGraphErrors *gKa = new TGraphErrors(nptbin,xx,yyKa,exx,eyyKa);
252 gKa->Draw("AP");
253 gKa->SetLineColor(1);
254 gKa->SetMarkerColor(1);
255 gKa->SetMarkerStyle(21);
256
257 TGraphErrors *gPi = new TGraphErrors(nptbin,xx,yyPi,exx,eyyPi);
258 gPi->Draw("P");
259 gPi->SetLineColor(4);
260 gPi->SetMarkerColor(4);
261 gPi->SetMarkerStyle(20);
262
263 TGraphErrors *gPr = new TGraphErrors(nptbin,xx,yyPr,exx,eyyPr);
264 gPr->Draw("P");
265 gPr->SetLineColor(2);
266 gPr->SetMarkerColor(2);
267 gPr->SetMarkerStyle(22);
268
269 if(pos) sprintf(name,"phiUserAnalPos_%3.1f-%3.1f_%i-%i.root",etaminkp,etamaxkp,cmin,cmax);
270 else sprintf(name,"phiUserAnalNeg_%3.1f-%3.1f_%i-%i.root",etaminkp,etamaxkp,cmin,cmax);
271
272 gPi->SetName("piSelected");
273 gKa->SetName("kaSelected");
274 gPr->SetName("prSelected");
275
276 TFile *fout = new TFile(name,"RECREATE");
277 gPi->Write();
278 gKa->Write();
279 gPr->Write();
280 fout->Close();
281}
282
283TH2F *GetHistoUser(Int_t pos,Float_t pt,Float_t ptM,Float_t etaminkp,Float_t etamaxkp){
284 // Int_t binUser[nBinUser] = {8/*Eta*/,20/*pt*/,2/*istrue*/,4/*whatSelection*/,1/*DeltaPhi*/,1/*Psi*/};
285 Float_t x[] = {etaminkp+0.0001,pt+0.0001,isMC,0.0001,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
286 Float_t x2[] = {etamaxkp-0.0001,ptM-0.0001,isMC,2.9999,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
287
288 AliPIDperfContainer *tmp = (AliPIDperfContainer *) fContUser1;
289 if(!pos) tmp = (AliPIDperfContainer *) fContUser2;
290
291 TH2F *h = tmp->GetQA(0, x, x2);
292
293 h->GetXaxis()->SetTitle("M_{K^{0}_{s}} (GeV/#it{c}^{2})");
294 h->GetYaxis()->SetTitle("centrality [%]");
295
296 return h;
297
298}
299
300
301TH2F *GetHistoPiUser(Int_t pos,Float_t pt,Float_t ptM,Float_t etaminkp,Float_t etamaxkp){
302 // Int_t binUser[nBinUser] = {8/*Eta*/,20/*pt*/,2/*istrue*/,4/*whatSelection*/,1/*DeltaPhi*/,1/*Psi*/};
303 Float_t x[] = {etaminkp+0.0001,pt+0.0001,isMC,1.0001,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
304 Float_t x2[] = {etamaxkp-0.0001,ptM-0.0001,isMC,1.0002,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
305
306 AliPIDperfContainer *tmp = (AliPIDperfContainer *) fContUser1;
307 if(!pos) tmp = (AliPIDperfContainer *) fContUser2;
308
309 TH2F *h = tmp->GetQA(0, x, x2);
310
311 h->GetXaxis()->SetTitle("M_{K^{0}_{s}} (GeV/#it{c}^{2})");
312 h->GetYaxis()->SetTitle("centrality [%]");
313
314 return h;
315
316}
317
318
319TH2F *GetHistoKaUser(Int_t pos,Float_t pt,Float_t ptM,Float_t etaminkp,Float_t etamaxkp){
320 // Int_t binUser[nBinUser] = {8/*Eta*/,20/*pt*/,2/*istrue*/,4/*whatSelection*/,1/*DeltaPhi*/,1/*Psi*/};
321 Float_t x[] = {etaminkp+0.0001,pt+0.0001,isMC,2.0001,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
322 Float_t x2[] = {etamaxkp-0.0001,ptM-0.0001,isMC,2.0002,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
323
324 AliPIDperfContainer *tmp = (AliPIDperfContainer *) fContUser1;
325 if(!pos) tmp = (AliPIDperfContainer *) fContUser2;
326
327 TH2F *h = tmp->GetQA(0, x, x2);
328
329 h->GetXaxis()->SetTitle("M_{K^{0}_{s}} (GeV/#it{c}^{2})");
330 h->GetYaxis()->SetTitle("centrality [%]");
331
332 return h;
333
334}
335
336
337TH2F *GetHistoPrUser(Int_t pos,Float_t pt,Float_t ptM,Float_t etaminkp,Float_t etamaxkp){
338 // Int_t binUser[nBinUser] = {8/*Eta*/,20/*pt*/,2/*istrue*/,4/*whatSelection*/,1/*DeltaPhi*/,1/*Psi*/};
339 Float_t x[] = {etaminkp+0.0001,pt+0.0001,isMC,3.0001,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
340 Float_t x2[] = {etamaxkp-0.0001,ptM-0.0001,isMC,3.0002,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
341
342 AliPIDperfContainer *tmp = (AliPIDperfContainer *) fContUser1;
343 if(!pos) tmp = (AliPIDperfContainer *) fContUser2;
344
345 TH2F *h = tmp->GetQA(0, x, x2);
346
347 h->GetXaxis()->SetTitle("M_{K^{0}_{s}} (GeV/#it{c}^{2})");
348 h->GetYaxis()->SetTitle("centrality [%]");
349
350 return h;
351
352}
353
a8ad4709 354
7484404e 355void doeffKa(Int_t pos,Float_t prob,Float_t etaminkp,Float_t etamaxkp){
a8ad4709 356 LoadLib();
08b5b548 357 TH1D *hm = hmatched->ProjectionX("matchingKaEff",cmin,cmax);
358 TH1D *ht = htracked->ProjectionX("tracking",cmin,cmax);
359
360 hm->GetYaxis()->SetTitle("TOF matching eff.");
361 hm->SetTitle("Using probability as weights");
362
363 hm->Sumw2();
364 ht->Sumw2();
365
366 hm->Divide(hm,ht,1,1,"B");
a8ad4709 367
08b5b548 368
a8ad4709 369 Int_t nptbin = binPid[2];
370 Float_t minptbin = xmin[2];
371 Float_t maxptbin = xmax[2];
372
373 if(pos == 0){
374 nptbin = binPid[3];
375 minptbin = xmin[3];
376 maxptbin = xmax[3];
377 }
378
379 if(prob > 0.1999){
380 kGoodMatch = kFALSE;
381 kSigma2vs3 = kFALSE;
382 if(! kOverAll) require5sigma = kTRUE;
e34b28fe 383 if(!isMC && !kOverAll) weightS = -0.95;
a8ad4709 384 }
385
7484404e 386 TCanvas *c1 = new TCanvas();
387 c1->Divide((nptbin+1)/2,2);
388 TH2F *hh,*hh2;
389 TH1D *h;
a8ad4709 390 char name[100];
391 Float_t b[50][3];
392
393 Double_t xx[50],yy[50];
394 Double_t exx[50],eyy[50];
395
396 for(Int_t i=0;i < nptbin;i++){
7484404e 397 c1->cd(i+1);//->SetLogy();
a8ad4709 398 Float_t ptmin = minptbin+(maxptbin-minptbin)/nptbin*(i);
399 Float_t ptmax = minptbin+(maxptbin-minptbin)/nptbin*(i+1);
400
401 xx[i] = (ptmin+ptmax)/2;
402 exx[i] = (-ptmin+ptmax)/2;
403
404 Float_t pp=0.1;
405 if(prob < 0.2) pp = 0.;
406 if(pos) hh=GetHistoKap(ptmin,ptmax,pp,0.0,etaminkp,etamaxkp);
407 else hh=GetHistoKan(ptmin,ptmax,pp,0.0);
408 sprintf(name,"TOF matched: %f < p_{T} < %f GeV/#it{c}",ptmin,ptmax);
409 hh->SetTitle(name);
410 sprintf(name,"hNoPid%i",i);
411
412 pp=prob;
413 if(prob < 0.2) pp = 0.1;
414 if(pos) hh2=GetHistoKap(ptmin,ptmax,pp,0.0,etaminkp,etamaxkp);
415 else hh2=GetHistoKan(ptmin,ptmax,pp,0.0);
416 AddHisto(hh,hh2,weightS);
417
418 h = hh->ProjectionX(name,cmin,cmax);
419 h->RebinX(rebinsize);
420 h->Draw("ERR");
421 h->SetMarkerStyle(24);
422 b[i][0]=-1;
423 Int_t ntrial = 0;
424 Float_t chi2 = 10000;
08b5b548 425 while(ntrial < 3 && (chi2 > 20 + 1000*selectTrue)){
a8ad4709 426 fit(h,b[i],"WW","",xx[i]);
427 c1->Update();
428// getchar();
429 fit(h,b[i],"","",xx[i]);
430 ntrial++;
431 chi2 = b[i][2];
432 printf("chi2 = %f\n",chi2);
433 c1->Update();
434// getchar();
435
436 }
437
438 yy[i] = fall->GetParameter(parplotted);
439 eyy[i] = fall->GetParError(parplotted);
440 }
441
442 TGraphErrors *gpar = new TGraphErrors(nptbin,xx,yy,exx,eyy);
7484404e 443 c1->cd(8);
08b5b548 444// gpar->Draw("AP");
a8ad4709 445 gpar->SetMarkerStyle(20);
446
447 TCanvas *c2 = new TCanvas();
448 c2->Divide((nptbin+1)/2,2);
449 Float_t b2[50][3];
450
451 for(Int_t i=0;i < nptbin;i++){
452 c2->cd(i+1);
453 Float_t ptmin = minptbin+(maxptbin-minptbin)/nptbin*(i);
454 Float_t ptmax = minptbin+(maxptbin-minptbin)/nptbin*(i+1);
455
456 Float_t pp=prob;
457 if(prob < 0.2) pp = 0.1;
458 if(pos) hh=GetHistoKap(ptmin,ptmax,pp,0.0,etaminkp,etamaxkp);
459 else hh=GetHistoKan(ptmin,ptmax,pp,0.0);
460 sprintf(name,"P_{TOF} > 0.8: %f < p_{T} < %f GeV/#it{c}",ptmin,ptmax);
461 hh->SetTitle(name);
462 sprintf(name,"hPid60_%i",i);
463 h = hh->ProjectionX(name,cmin,cmax);
464 h->RebinX(rebinsize);
465 h->Draw("ERR");
466 h->SetMarkerStyle(24);
467 b2[i][0]=-1;
468 Int_t ntrial = 0;
469 Float_t chi2 = 10000;
08b5b548 470 while(ntrial < 3 && (chi2 > 20 + 1000*selectTrue)){
a8ad4709 471 fit(h,b2[i],"WW","");
472 fit(h,b2[i],"","");
473 ntrial++;
474 chi2 = b2[i][2];
475 printf("chi2 = %f\n",chi2);
476 }
477 yy[i] = fall->GetParameter(parplotted);
478 eyy[i] = fall->GetParError(parplotted);
479
480 }
481
482 TGraphErrors *gpar2 = new TGraphErrors(nptbin,xx,yy,exx,eyy);
483 c2->cd(8);
08b5b548 484// gpar2->Draw("AP");
a8ad4709 485 gpar2->SetMarkerStyle(20);
486
487 Double_t xpt[50],expt[50],eff[50],efferr[50];
488 for(Int_t i=0;i<nptbin;i++){
489 printf("%f +/- %f - %f +/- %f\n",b[i][0],b[i][1],b2[i][0],b2[i][1]);
490
491 Float_t ptmin = minptbin+(maxptbin-minptbin)/nptbin*(i);
492 Float_t ptmax = minptbin+(maxptbin-minptbin)/nptbin*(i+1);
493
494 xpt[i] = (ptmin+ptmax)/2;
495 expt[i] = (-ptmin+ptmax)/2;
496 eff[i] = b2[i][0]/(b[i][0]-b2[i][0]*weightS);
497
498 b[i][0] = b[i][0]-b2[i][0]*weightS;
499
500 efferr[i] = TMath::Sqrt(b[i][1]*b[i][1]/b[i][0]/b[i][0] + b2[i][1]*b2[i][1]/b2[i][0]/b2[i][0])*(b2[i][0]+b2[i][1])*(1+weightS*(b2[i][0]-b2[i][1])/b[i][0])/b[i][0];//*(1-eff[i]);//der2*der2*(b[i][1]*b[i][1] - b2[i][1]*b2[i][1]));
501
502 if(TMath::Abs(efferr[i]) > 1)efferr[i]=1;
503 }
504 new TCanvas();
505 TGraphErrors *geff = new TGraphErrors(nptbin,xpt,eff,expt,efferr);
506 geff->Draw("AP");
507
508 char flag[100];
7484404e 509 flag[0] = '\0';
a8ad4709 510
511 if(isMC){
512 if(selectTrue) sprintf(flag,"true");
513 else if(!keepTrue) sprintf(flag,"back");
514 }
515
516 char flag2[100];
7484404e 517 flag2[0] = '\0';
a8ad4709 518
08b5b548 519 Bool_t kWriteME = kFALSE;
520
a8ad4709 521 char etarange[100];
522 sprintf(etarange,"_%.1f-%.1f_",etaminkp,etamaxkp);
523
524 if(kGoodMatch)
525 sprintf(flag2,"GM");
526
527 if(bayesVsigma)
528 sprintf(flag2,"BayesVsSigma");
529
530 if(kSigma2vs3)
531 sprintf(flag2,"Sigma2vs3");
532
533 if(kOverAll)
534 sprintf(flag2,"OverAll");
e34b28fe 535 if(kOverAllTOFmatch)
536 sprintf(flag2,"OverAllTOF");
537 if(kOverAll2Sigma)
538 sprintf(flag2,"OverAll2sigma");
a8ad4709 539
540 if(pos){
541 if(prob >=0.2) sprintf(name,"kaonPos%sP%iEff%i_%i%s%s.root",etarange,Int_t(prob*100),(cmin-1)*10,cmax*10,flag,flag2);
08b5b548 542 else{
543 sprintf(name,"kaonPos%sMatchEff%i_%i%s%s.root",etarange,(cmin-1)*10,cmax*10,flag,flag2);
544 if(!(kOverAll || bayesVsigma || kGoodMatch || kSigma2vs3)) kWriteME = kTRUE;
545 }
a8ad4709 546 }
547 else{
548 if(prob >=0.2) sprintf(name,"kaonNeg%sP%iEff%i_%i%s%s.root",etarange,Int_t(prob*100),(cmin-1)*10,cmax*10,flag,flag2);
549 else sprintf(name,"kaonNeg%sMatchEff%i_%i%s%s.root",etarange,(cmin-1)*10,cmax*10,flag,flag2);
550 }
551
08b5b548 552 geff->SetTitle("K efficiency (from #phi);p_{T} (GeV/#it{c};efficiency");
a8ad4709 553 TFile *fout = new TFile(name,"RECREATE");
554 geff->Write();
08b5b548 555 if(kWriteME) hm->Write();
a8ad4709 556 fout->Close();
557
08b5b548 558 if(kWriteME) hm->Draw("SAME");
a8ad4709 559}
560
7484404e 561TH2F *GetHistoKap(Float_t pt,Float_t ptM,Float_t pMinkp,Float_t pMinkn,Float_t etaminkp,Float_t etamaxkp){
a8ad4709 562
563 Float_t x[] = {xmin[0]+0.001,etaminkp+0.001,pt+0.001,xmin[3]+0.001,pMinkp+0.001,pMinkn+0.001,(pMinkp>0.09)+0.001,kTOFmatch+0.001,selectTrue,xmin[9],xmin[10],xmin[11],xmin[12],xmin[13]};
564 Float_t x2[] = {xmax[0],etamaxkp-0.001,ptM-0.001,xmax[3],xmax[4],xmax[5],xmax[6],xmax[7],keepTrue,xmax[9],xmax[10],xmax[11],xmax[12],xmax[13]};
565
e34b28fe 566 if(kOverAll){
567 x[6] = 0.0001;
568 x2[9] = 5.9;
569 if(pMinkp > 0.19) x2[9] = 4.9;
570 }
571
572 if(kOverAllTOFmatch && pMinkp > 0.19){
573 x[6] = 1.0001;
574 x2[9] = 4.9;
575 }
576
577 if(kOverAll2Sigma && pMinkp > 0.09){
578 x2[9] = 2;
579 x[6] = 1.0001;
580 }
581
a8ad4709 582 if(kGoodMatch){
583 x[6] = 1.0001;
584 if(pMinkp > 0)
585 x2[9] = 4.9;
586
587 }
588
589 if(kTOFmatch){
590 x[6] = 1.0001;
591 }
592
593 if(kSigma2vs3){
594 x[6] = 1.0001;
595 x2[9] = 3;
596 if(pMinkp > 0)
597 x2[9] = 2;
598 }
599
600 if(bayesVsigma){
601 if(pMinkp > 0){
602 x[4] = 0.2001;
603 x2[9] = 5;
604 }
605 else{
606 x2[9] = 3;
607 }
608
609
610 }
611
612 if(require5sigma) x2[9] = 4.9;
613
7484404e 614 AliPIDperfContainer *tmp = (AliPIDperfContainer *) fContPid1;
a8ad4709 615
616 TH2F *h = tmp->GetQA(0, x, x2);
617
618 h->GetXaxis()->SetTitle("M_{#phi} (GeV/#it{c}^{2})");
619 h->GetYaxis()->SetTitle("centrality [%]");
620
621 return h;
622}
623
7484404e 624TH2F *GetHistoKan(Float_t pt,Float_t ptM,Float_t pMinkn,Float_t pMinkp,Float_t etaminkp,Float_t etamaxkp){
a8ad4709 625
626 Float_t x[] = {xmin[0]+0.001,etaminkp+0.001,xmin[2]+0.001,pt+0.001,pMinkp+0.001,pMinkn+0.001,kTOFmatch+0.001,(pMinkn>0.09)+0.001,selectTrue,xmin[9],xmin[10],xmin[11],xmin[12],xmin[13]};
627 Float_t x2[] = {xmax[0],etamaxkp-0.001,xmax[2],ptM-0.001,xmax[4],xmax[5],xmax[6],xmax[7],keepTrue,xmax[9],xmax[10],xmax[11],xmax[12],xmax[13]};
628
e34b28fe 629 if(kOverAll){
630 x[7] = 0.0001;
631 x2[10] = 5.9;
632 if(pMinkn > 0.19) x2[10] = 4.9;
633 }
634
635 if(kOverAllTOFmatch && pMinkn > 0.19){
636 x[7] = 1.0001;
637 x2[10] = 4.9;
638 }
639
640 if(kOverAll2Sigma && pMinkn > 0.09){
641 x2[10] = 2;
642 x[7] = 1.0001;
643 }
644
a8ad4709 645 if(kGoodMatch){
646 x[7] = 1.0001;
647 if(pMinkn > 0)
648 x2[10] = 4.9;
649
650 }
651
652 if(kTOFmatch){
653 x[7] = 1.0001;
654 }
655
656 if(kSigma2vs3){
657 x[7] = 1.0001;
658 x2[10] = 3;
659 if(pMinkn > 0)
660 x2[10] = 2;
661 }
662
663 if(bayesVsigma){
664 if(pMinkn > 0){
665 x[5] = 0.2001;
666 x2[10] = 5;
667 }
668 else{
669 x2[10] = 3;
670 }
671 }
672
673 if(require5sigma) x2[10] = 4.9;
674
7484404e 675 AliPIDperfContainer *tmp = (AliPIDperfContainer *) fContPid2;
a8ad4709 676
677 TH2F *h = tmp->GetQA(0, x, x2);
678
679 h->GetXaxis()->SetTitle("M_{#phi} (GeV/#it{c}^{2})");
680 h->GetYaxis()->SetTitle("centrality [%]");
681
682 return h;
683}
684
685
7484404e 686void fit(TH1D *h,Float_t *a,char *opt,char *opt2,Float_t pt){
a8ad4709 687 if(h->GetEntries() < 1){
688 if(a){
689 a[0]=0.01;
690 a[1]=1;
691 }
692 return;
693 }
694
695
696 fall->SetParameter(0,100);
697 fall->SetParameter(0,1.01898 + 2.4e-04*pt);
698 fall->SetParameter(2,0.0044);
699 fall->SetParameter(3,0.0015);
700
701 fall->SetParLimits(0,-100,100000);
702 fall->SetParLimits(1,1.01898 + 2.4e-04*pt-1e-03,1.01898 + 2.4e-04*pt+1e-03);
703 fall->SetParLimits(2,0.0005,0.006);
704 fall->SetParLimits(3,0.001,0.0017);
705
706 fall->FixParameter(1,1.01884 + 2.9891e-04*pt);
707 fall->FixParameter(2,0.0044);
708 fall->FixParameter(3,7.57574e-04 + 3.85408e-04*pt);
709
710 fall->ReleaseParameter(4);
711 fall->ReleaseParameter(5);
712 fall->ReleaseParameter(6);
713 fall->ReleaseParameter(7);
714 fall->ReleaseParameter(8);
715
716
717 if(!kGoodMatch && !kSigma2vs3){
718 if(pt > 1.5){
719 fall->FixParameter(7,0);
720 fall->FixParameter(8,0);
721 }
722 if(pt > 1.7){
723 fall->FixParameter(6,0);
724 }
725 }
726
727 if(selectTrue){
728 fall->FixParameter(4,0);
729 fall->FixParameter(5,0);
730 fall->FixParameter(6,0);
731 fall->FixParameter(7,0);
732 fall->FixParameter(8,0);
733 }
734
735 char name[100];
736 TF1 *ftmp=fall;
737
738 TF1 *ftmp2=new TF1(*fsign);
739 sprintf(name,"fsign%i",ifunc);
740 ftmp2->SetName(name);
741
742 TF1 *ftmp3=new TF1(*fback);
743 sprintf(name,"ftmp3%i",ifunc);
744 ftmp3->SetName(name);
745
746 ifunc++;
747
748 h->Fit(ftmp,opt,opt2,fitmin,fitmax);
749 h->Draw("ERR");
750
751 ftmp2->SetParameter(0,ftmp->GetParameter(0));
752 ftmp2->SetParameter(1,ftmp->GetParameter(1));
753 ftmp2->SetParameter(2,ftmp->GetParameter(2));
754 ftmp2->SetParameter(3,ftmp->GetParameter(3));
755 ftmp2->Draw("SAME");
756 ftmp3->SetParameter(0,ftmp->GetParameter(4));
757 ftmp3->SetParameter(1,ftmp->GetParameter(5));
758 ftmp3->SetParameter(2,ftmp->GetParameter(6));
759 ftmp3->SetParameter(3,ftmp->GetParameter(7));
760 ftmp3->SetParameter(4,ftmp->GetParameter(8));
761 ftmp3->Draw("SAME");
762
763 Float_t mean = ftmp->GetParameter(1);
764 Float_t sigma = 0.0044;//TMath::Abs(ftmp->GetParameter(2));
765
766 Float_t signI = ftmp2->Integral(mean-10*sigma,mean+10*sigma)/h->GetBinWidth(1);
767 Float_t backI = ftmp3->Integral(mean-3*sigma,mean+3*sigma)/h->GetBinWidth(1);
768
769 Float_t errI = TMath::Sqrt(ftmp->GetParError(0)*ftmp->GetParError(0)/(0.001+ftmp->GetParameter(0))/(0.001+ftmp->GetParameter(0)));
770
771 printf("signal(5 sigma) = %f +/- %f(fit) +/- %f(stat)\n",signI,errI*signI,TMath::Sqrt(signI));
772 printf("backgr(3sigma) = %f\n",backI);
773 printf("significance(3 sigma) = %f\n",signI/sqrt(signI+backI));
774
775 if(a){
776 a[0]=signI;
777 a[1]=signI*errI*signI*errI + signI;
778 a[1] = TMath::Sqrt(a[1]);
779 if(ftmp->GetNDF()) a[2] = ftmp->GetChisquare()/ftmp->GetNDF();
780
781
782 if(selectTrue){
783 a[0] = h->GetEntries();
784 a[1] = TMath::Sqrt(a[0]);
785 }
786 }
787}
788
7484404e 789void AddHisto(TH2F *h1,TH2F *h2,Float_t w){
a8ad4709 790 Int_t nbinx = h1->GetNbinsX();
791 Int_t nbiny = h1->GetNbinsY();
792
793 for(Int_t i=1;i<=nbinx;i++){
794 for(Int_t j=1;j<=nbiny;j++){
7484404e 795 Double_t val = h1->GetBinContent(i,j) + h2->GetBinContent(i,j)*w;
a8ad4709 796 Float_t err = TMath::Min(TMath::Sqrt(val),val);
797 h1->SetBinContent(i,j,val);
798 h1->SetBinError(i,j,err);
799 }
800 }
801}