Remove non functional setter for event selection.
[u/mrichter/AliRoot.git] / PWGPP / pid / doeffPi.C
CommitLineData
a8ad4709 1TObject* fContPid1;
2TObject* fContPid2;
3const Int_t nBinPid = 14; // pt,eta, ptPip, ptPin, PPip, PPin, TOF3sigmaPip, TOF3sigmaPin, isPhiTrue, nsigmaPip, nsigmaPin
4// 0.985 < mass < 1.045 (60) and 0 < centrality < 100 (10)
5Int_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*/};
6Float_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};
7Float_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};
8
9TF1 *fsign;
10TF1 *fall;
11TF1 *fback;
12
13Int_t ifunc=0;
14
15Float_t fitmin = 0.3;
16Float_t fitmax = 0.7;
17
18Int_t cmin = 1;
19Int_t cmax = 8;
20
21Float_t weightS = -1.;
22
23Int_t rebinsize = 4;
24
25Int_t parplotted = 2;
26
27Bool_t isMC = kFALSE; // don't change this (is set automatically)
28Bool_t selectTrue = kTRUE; // put it to true to remove background (only for MC)
29Bool_t keepTrue = kFALSE; // put it to false to fit only background (only for MC)
30
31Bool_t kGoodMatch = kFALSE; // to check good matching
32
33Bool_t kSigma2vs3 = kFALSE; // to check good matching
34
35Bool_t require5sigma = kFALSE; // don't touch this flag
36
37Bool_t bayesVsigma = kFALSE; // only to do checks
38
39Bool_t kTOFmatch = kFALSE; // for combined PID requires TOF matching
40
41Bool_t kOverAll = kFALSE;
42
43Bool_t kLoaded=kFALSE;
44LoadLib(){
45 weightS = -1.;
46
47 if(! kLoaded){
48 gSystem->Load("libVMC.so");
49 gSystem->Load("libPhysics.so");
50 gSystem->Load("libTree.so");
51 gSystem->Load("libMinuit.so");
52 gSystem->Load("libSTEERBase.so");
53 gSystem->Load("libANALYSIS.so");
54 gSystem->Load("libAOD.so");
55 gSystem->Load("libESD.so");
56 gSystem->Load("libANALYSIS.so");
57 gSystem->Load("libANALYSISalice.so");
58 gSystem->Load("libCORRFW.so");
59 gSystem->Load("libNetx.so");
60 gSystem->Load("libPWGPPpid.so");
61
62 TFile *f = new TFile("AnalysisResults.root");
63 f->ls();
64 TList *l = (TList *) f->Get("contK0sBayes1");
65 l->ls();
66 fContPid1 = (AliPIDperfContainer *) l->At(0);
67 fContPid2 = (AliPIDperfContainer *) l->At(1);
68 }
69 kLoaded = kTRUE;
70
71 // check if MC
72 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]};
73 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]};
74
75 AliPIDperfContainer *tmp = fContPid1;
76 TH1D *h = tmp->GetQA(0, x, x2)->ProjectionX("checkMC");
77
78 if(h->GetEntries()) isMC = kTRUE;
79 else isMC=kFALSE;
80
81 if(!isMC){
82 selectTrue = kFALSE;
83 keepTrue = kTRUE;
84 }
85 else{
86 printf("MC truth found!!!!!!\nIt is MC!!!!!!");
87 }
88
89 fsign = new TF1("fsign","[0]*TMath::Voigt(x-[1],[3],[2])",fitmin,fitmax);
90 fback = new TF1("fback","pol1",fitmin,fitmax);
91 fall = new TF1("fall","[0]*TMath::Voigt(x-[1],[3],[2]) + pol1(4)",fitmin,fitmax);
92
93 fsign->SetLineColor(2);
94 fback->SetLineColor(4);
95
96 if(kSigma2vs3){
97 kGoodMatch=kFALSE;
98 kOverAll = 0;
99 }
100
101 if(bayesVsigma){
102 kOverAll = 0;
103 kGoodMatch=kFALSE;
104 kSigma2vs3=kFALSE;
105 kTOFmatch=kTRUE;
106 weightS = -0.7;
107 }
108}
109
110doeffPi(Int_t pos=1,Float_t prob=0.1,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8){
111 LoadLib();
112
113 Int_t nptbin = binPid[2];
114 Float_t minptbin = xmin[2];
115 Float_t maxptbin = xmax[2];
116
117 if(pos == 0){
118 nptbin = binPid[3];
119 minptbin = xmin[3];
120 maxptbin = xmax[3];
121 }
122
123 if(prob > 0.1999){
124 kGoodMatch = kFALSE;
125 kSigma2vs3 = kFALSE;
126 if(! kOverAll) require5sigma = kTRUE;
127 if(!isMC) weightS = -0.95;
128 }
129
130 TCanvas *c = new TCanvas();
131 c->Divide((nptbin+1)/2,2);
132 TH2F *hh.*hh2;
133 TH1D *h,*h2;
134 char name[100];
135 Float_t b[50][3];
136
137 Double_t xx[50],yy[50];
138 Double_t exx[50],eyy[50];
139
140 for(Int_t i=0;i < nptbin;i++){
141 c->cd(i+1)->SetLogy();
142 Float_t ptmin = minptbin+(maxptbin-minptbin)/nptbin*(i);
143 Float_t ptmax = minptbin+(maxptbin-minptbin)/nptbin*(i+1);
144
145 xx[i] = (ptmin+ptmax)/2;
146 exx[i] = (-ptmin+ptmax)/2;
147
148 Float_t pp=0.1;
149 if(prob < 0.2) pp = 0.;
150 if(pos) hh=GetHistoPip(ptmin,ptmax,pp,0.0,etaminkp,etamaxkp);
151 else hh=GetHistoPin(ptmin,ptmax,pp,0.0);
152 sprintf(name,"TOF matched: %f < p_{T} < %f GeV/#it{c}",ptmin,ptmax);
153 hh->SetTitle(name);
154 sprintf(name,"hNoPid%i",i);
155
156 pp=prob;
157 if(prob < 0.2) pp = 0.1;
158 if(pos) hh2=GetHistoPip(ptmin,ptmax,pp,0.0,etaminkp,etamaxkp);
159 else hh2=GetHistoPin(ptmin,ptmax,pp,0.0);
160 AddHisto(hh,hh2,weightS);
161
162 h = hh->ProjectionX(name,cmin,cmax);
163 h->RebinX(rebinsize);
164 h->Draw("ERR");
165 h->SetMarkerStyle(24);
166 b[i][0]=-1;
167 Int_t ntrial = 0;
168 Float_t chi2 = 10000;
169 while(ntrial < 10 && (chi2 > 20 + 1000*selectTrue)){
170 fit(h,b[i],"WW","",xx[i]);
171 c1->Update();
172// getchar();
173 fit(h,b[i],"","",xx[i]);
174 ntrial++;
175 chi2 = b[i][2];
176 printf("chi2 = %f\n",chi2);
177 c1->Update();
178// getchar();
179
180 }
181
182 yy[i] = fall->GetParameter(parplotted);
183 eyy[i] = fall->GetParError(parplotted);
184 }
185
186 TGraphErrors *gpar = new TGraphErrors(nptbin,xx,yy,exx,eyy);
187 c->cd(8);
188 gpar->Draw("AP");
189 gpar->SetMarkerStyle(20);
190
191 TCanvas *c2 = new TCanvas();
192 c2->Divide((nptbin+1)/2,2);
193 Float_t b2[50][3];
194
195 for(Int_t i=0;i < nptbin;i++){
196 c2->cd(i+1);
197 Float_t ptmin = minptbin+(maxptbin-minptbin)/nptbin*(i);
198 Float_t ptmax = minptbin+(maxptbin-minptbin)/nptbin*(i+1);
199
200 Float_t pp=prob;
201 if(prob < 0.2) pp = 0.1;
202 if(pos) hh=GetHistoPip(ptmin,ptmax,pp,0.0,etaminkp,etamaxkp);
203 else hh=GetHistoPin(ptmin,ptmax,pp,0.0);
204 sprintf(name,"P_{TOF} > 0.8: %f < p_{T} < %f GeV/#it{c}",ptmin,ptmax);
205 hh->SetTitle(name);
206 sprintf(name,"hPid60_%i",i);
207 h = hh->ProjectionX(name,cmin,cmax);
208 h->RebinX(rebinsize);
209 h->Draw("ERR");
210 h->SetMarkerStyle(24);
211 b2[i][0]=-1;
212 Int_t ntrial = 0;
213 Float_t chi2 = 10000;
214 while(ntrial < 40 && (chi2 > 20 + 1000*selectTrue)){
215 fit(h,b2[i],"WW","");
216 fit(h,b2[i],"","");
217 ntrial++;
218 chi2 = b2[i][2];
219 printf("chi2 = %f\n",chi2);
220 }
221 yy[i] = fall->GetParameter(parplotted);
222 eyy[i] = fall->GetParError(parplotted);
223
224 }
225
226 TGraphErrors *gpar2 = new TGraphErrors(nptbin,xx,yy,exx,eyy);
227 c2->cd(8);
228 gpar2->Draw("AP");
229 gpar2->SetMarkerStyle(20);
230
231 Double_t xpt[50],expt[50],eff[50],efferr[50];
232 for(Int_t i=0;i<nptbin;i++){
233 printf("%f +/- %f - %f +/- %f\n",b[i][0],b[i][1],b2[i][0],b2[i][1]);
234
235 Float_t ptmin = minptbin+(maxptbin-minptbin)/nptbin*(i);
236 Float_t ptmax = minptbin+(maxptbin-minptbin)/nptbin*(i+1);
237
238 xpt[i] = (ptmin+ptmax)/2;
239 expt[i] = (-ptmin+ptmax)/2;
240 eff[i] = b2[i][0]/(b[i][0]-b2[i][0]*weightS);
241
242 b[i][0] = b[i][0]-b2[i][0]*weightS;
243
244 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]));
245
246 if(TMath::Abs(efferr[i]) > 1)efferr[i]=1;
247 }
248 new TCanvas();
249 TGraphErrors *geff = new TGraphErrors(nptbin,xpt,eff,expt,efferr);
250 geff->Draw("AP");
251
252 char flag[100];
253 sprintf(flag,"");
254
255 if(isMC){
256 if(selectTrue) sprintf(flag,"true");
257 else if(!keepTrue) sprintf(flag,"back");
258 }
259
260 char flag2[100];
261 sprintf(flag2,"");
262
263 char etarange[100];
264 sprintf(etarange,"_%.1f-%.1f_",etaminkp,etamaxkp);
265
266 if(kGoodMatch)
267 sprintf(flag2,"GM");
268
269 if(bayesVsigma)
270 sprintf(flag2,"BayesVsSigma");
271
272 if(kSigma2vs3)
273 sprintf(flag2,"Sigma2vs3");
274
275 if(kOverAll)
276 sprintf(flag2,"OverAll");
277
278 if(pos){
279 if(prob >=0.2) sprintf(name,"pionPos%sP%iEff%i_%i%s%s.root",etarange,Int_t(prob*100),(cmin-1)*10,cmax*10,flag,flag2);
280 else sprintf(name,"pionPos%sMatchEff%i_%i%s%s.root",etarange,(cmin-1)*10,cmax*10,flag,flag2);
281 }
282 else{
283 if(prob >=0.2) sprintf(name,"pionNeg%sP%iEff%i_%i%s%s.root",etarange,Int_t(prob*100),(cmin-1)*10,cmax*10,flag,flag2);
284 else sprintf(name,"pionNeg%sMatchEff%i_%i%s%s.root",etarange,(cmin-1)*10,cmax*10,flag,flag2);
285 }
286
287 TFile *fout = new TFile(name,"RECREATE");
288 geff->Write();
289 fout->Close();
290
291
292 TF1 *ff = new TF1("ff","[0] - [1]*TMath::Exp([2]*x)",0,3);
293 ff->SetParameter(0,0.67);
294 ff->SetParameter(1,1.14383e+00);
295 ff->SetParameter(2,-2.29910);
296 ff->SetLineColor(4);
297 ff->SetLineColor(2);
298 ff->Draw("SAME");
299
300 TF1 *ff2 = new TF1("ff2","[0] - [1]*TMath::Exp([2]*x)",0,3);
301 ff2->SetParameter(0,0.67);
302 ff2->SetParameter(1,9.23126e-01);
303 ff2->SetParameter(2,-1.851);
304 ff2->SetLineColor(4);
305 ff2->Draw("SAME");
306}
307
308TH2F *GetHistoPip(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){
309
310 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]};
311 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]};
312
313 if(kGoodMatch){
314 x[6] = 1.0001;
315 if(pMinkp > 0)
316 x2[9] = 4.9;
317
318 }
319
320 if(kTOFmatch){
321 x[6] = 1.0001;
322 }
323
324 if(kSigma2vs3){
325 x[6] = 1.0001;
326 x2[9] = 3;
327 if(pMinkp > 0)
328 x2[9] = 2;
329 }
330
331 if(bayesVsigma){
332 if(pMinkp > 0){
333 x[4] = 0.2001;
334 x2[9] = 5;
335 }
336 else{
337 x2[9] = 3;
338 }
339
340
341 }
342
343 if(require5sigma) x2[9] = 4.9;
344
345 AliPIDperfContainer *tmp = fContPid1;
346
347 TH2F *h = tmp->GetQA(0, x, x2);
348
349 h->GetXaxis()->SetTitle("M_{K^{0}_{s}} (GeV/#it{c}^{2})");
350 h->GetYaxis()->SetTitle("centrality [%]");
351
352 return h;
353}
354
355TH2F *GetHistoPin(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){
356
357 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]};
358 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]};
359
360 if(kGoodMatch){
361 x[7] = 1.0001;
362 if(pMinkn > 0)
363 x2[10] = 4.9;
364
365 }
366
367 if(kTOFmatch){
368 x[7] = 1.0001;
369 }
370
371 if(kSigma2vs3){
372 x[7] = 1.0001;
373 x2[10] = 3;
374 if(pMinkn > 0)
375 x2[10] = 2;
376 }
377
378 if(bayesVsigma){
379 if(pMinkn > 0){
380 x[5] = 0.2001;
381 x2[10] = 5;
382 }
383 else{
384 x2[10] = 3;
385 }
386 }
387
388 if(require5sigma) x2[10] = 4.9;
389
390 AliPIDperfContainer *tmp = fContPid2;
391
392 TH2F *h = tmp->GetQA(0, x, x2);
393
394 h->GetXaxis()->SetTitle("M_{K^{0}_{s}} (GeV/#it{c}^{2})");
395 h->GetYaxis()->SetTitle("centrality [%]");
396
397 return h;
398}
399
400
401fit(TH1D *h,Float_t *a=NULL,char *opt="",char *opt2="",Float_t pt=1.5){
402 if(h->Integral(1,h->GetNbinsX()) < 1){
403 if(a){
404 a[0]=0.001;
405 a[1]=1;
406 }
407 return;
408 }
409
410
411 fall->SetParameter(0,100);
412 fall->SetParameter(1,0.4971);
413 fall->SetParameter(2,0.00006);
414 fall->SetParameter(3,0.0035);
415
416 fall->SetParLimits(0,0.00001,10000);
417 fall->SetParLimits(1,0.4965,0.4985);
418 fall->SetParLimits(2,0.00005,0.001);
419 fall->SetParLimits(3,0.002,0.01);
420
421 fall->ReleaseParameter(4);
422 fall->ReleaseParameter(5);
423
424 if(selectTrue){
425 fall->FixParameter(4,0);
426 fall->FixParameter(5,0);
427 }
428
429 char name[100];
430 TF1 *ftmp=fall;
431
432 TF1 *ftmp2=new TF1(*fsign);
433 sprintf(name,"fsign%i",ifunc);
434 ftmp2->SetName(name);
435
436 TF1 *ftmp3=new TF1(*fback);
437 sprintf(name,"ftmp3%i",ifunc);
438 ftmp3->SetName(name);
439
440 ifunc++;
441
442 h->Fit(ftmp,opt,opt2,fitmin,fitmax);
443 h->Draw("ERR");
444
445 ftmp2->SetParameter(0,ftmp->GetParameter(0));
446 ftmp2->SetParameter(1,ftmp->GetParameter(1));
447 ftmp2->SetParameter(2,ftmp->GetParameter(2));
448 ftmp2->SetParameter(3,ftmp->GetParameter(3));
449 ftmp2->Draw("SAME");
450 ftmp3->SetParameter(0,ftmp->GetParameter(4));
451 ftmp3->SetParameter(1,ftmp->GetParameter(5));
452 ftmp3->Draw("SAME");
453
454 Float_t mean = ftmp->GetParameter(1);
455 Float_t sigma = 0.0044;
456
457 Float_t signI = ftmp2->Integral(mean-10*sigma,mean+10*sigma)/h->GetBinWidth(1);
458 Float_t backI = ftmp3->Integral(mean-3*sigma,mean+3*sigma)/h->GetBinWidth(1);
459
460 Float_t errI = TMath::Sqrt(ftmp->GetParError(0)*ftmp->GetParError(0)/(0.001+ftmp->GetParameter(0))/(0.001+ftmp->GetParameter(0)));
461
462 printf("signal(5 sigma) = %f +/- %f(fit) +/- %f(stat)\n",signI,errI*signI,TMath::Sqrt(signI));
463 printf("backgr(3sigma) = %f\n",backI);
464 printf("significance(3 sigma) = %f\n",signI/sqrt(signI+backI));
465
466 if(a){
467 a[0]=signI;
468 a[1]=signI*errI*signI*errI + signI;
469 a[1] = TMath::Sqrt(a[1]);
470 if(ftmp->GetNDF()) a[2] = ftmp->GetChisquare()/ftmp->GetNDF();
471
472
473 if(selectTrue){
474 a[0] = h->Integral(1,h->GetNbinsX());
475 a[1] = TMath::Sqrt(a[0]);
476 }
477 }
478}
479
480AddHisto(TH2F *h1,TH2F *h2,Float_t w){
481 Int_t nbinx = h1->GetNbinsX();
482 Int_t nbiny = h1->GetNbinsY();
483
484 for(Int_t i=1;i<=nbinx;i++){
485 for(Int_t j=1;j<=nbiny;j++){
486 Float_t val = h1->GetBinContent(i,j) + h2->GetBinContent(i,j)*w;
487 Float_t err = TMath::Min(TMath::Sqrt(val),val);
488 h1->SetBinContent(i,j,val);
489 h1->SetBinError(i,j,err);
490 }
491 }
492}