3 const 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)
5 Int_t binPid[nBinPid] = {1/*ptPhi*/,8/*EtaPr*/,20/*pt+*/,20/*pt-*/,5/*P+*/,1/*P-*/,2/*TOFmatch+*/,2/*TOFmatch-*/,2/*istrue*/,4/*Nsigma+*/,4/*Nsigma-*/,1/*DeltaPhi+*/,1/*DeltaPhi-*/,1/*Psi*/};
6 Float_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};
7 Float_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};
15 Float_t fitmin = 1.08;
16 Float_t fitmax = 1.155;
21 Float_t weightS = -1.;
27 Bool_t isMC = kFALSE; // don't change this (is set automatically)
28 Bool_t selectTrue = kTRUE; // put it to true to remove background (only for MC)
29 Bool_t keepTrue = kFALSE; // put it to false to fit only background (only for MC)
31 Bool_t kGoodMatch = kFALSE; // to check good matching
33 Bool_t kSigma2vs3 = kFALSE; // to check good matching
35 Bool_t require5sigma = kFALSE; // don't touch this flag
37 Bool_t bayesVsigma = kFALSE; // only to do checks
39 Bool_t kTOFmatch = kFALSE; // for combined PID requires TOF matching
41 Bool_t kOverAll = kTRUE;
42 Bool_t kOverAllTOFmatch = kFALSE;
43 Bool_t kOverAll2Sigma = kTRUE;
45 Bool_t kLoaded=kFALSE;
50 gSystem->Load("libVMC.so");
51 gSystem->Load("libPhysics.so");
52 gSystem->Load("libTree.so");
53 gSystem->Load("libMinuit.so");
54 gSystem->Load("libSTEERBase.so");
55 gSystem->Load("libANALYSIS.so");
56 gSystem->Load("libAOD.so");
57 gSystem->Load("libESD.so");
58 gSystem->Load("libANALYSIS.so");
59 gSystem->Load("libANALYSISalice.so");
60 gSystem->Load("libCORRFW.so");
61 gSystem->Load("libNetx.so");
62 gSystem->Load("libPWGPPpid.so");
64 TFile *f = new TFile("AnalysisResults.root");
66 TList *l = (TList *) f->Get("contLambdaBayes1");
68 fContPid1 = (AliPIDperfContainer *) l->At(0);
69 fContPid2 = (AliPIDperfContainer *) l->At(1);
74 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]};
75 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]};
77 AliPIDperfContainer *tmp = fContPid1;
78 TH1D *h = tmp->GetQA(0, x, x2)->ProjectionX("checkMC");
80 if(h->GetEntries()) isMC = kTRUE;
88 printf("MC truth found!!!!!!\nIt is MC!!!!!!");
91 fsign = new TF1("fsign","[0]*TMath::Voigt(x-[1],[3],[2])",fitmin,fitmax);
92 fback = new TF1("fback","pol2",fitmin,fitmax);
93 fall = new TF1("fall","[0]*TMath::Voigt(x-[1],[3],[2]) + pol2(4)",fitmin,fitmax);
95 fsign->SetLineColor(2);
96 fback->SetLineColor(4);
112 doeffPr(Int_t pos=1,Float_t prob=0.1,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8){
115 Int_t nptbin = binPid[2];
116 Float_t minptbin = xmin[2];
117 Float_t maxptbin = xmax[2];
128 if(! kOverAll) require5sigma = kTRUE;
129 if(!isMC) weightS = -0.95;
132 TCanvas *c = new TCanvas();
133 c->Divide((nptbin+1)/2,2);
139 Double_t xx[50],yy[50];
140 Double_t exx[50],eyy[50];
142 for(Int_t i=0;i < nptbin;i++){
143 c->cd(i+1)->SetLogy();
144 Float_t ptmin = minptbin+(maxptbin-minptbin)/nptbin*(i);
145 Float_t ptmax = minptbin+(maxptbin-minptbin)/nptbin*(i+1);
147 xx[i] = (ptmin+ptmax)/2;
148 exx[i] = (-ptmin+ptmax)/2;
151 if(prob < 0.2) pp = 0.;
152 if(pos) hh=GetHistoPip(ptmin,ptmax,pp,0.0,etaminkp,etamaxkp);
153 else hh=GetHistoPin(ptmin,ptmax,pp,0.0);
154 sprintf(name,"TOF matched: %f < p_{T} < %f GeV/#it{c}",ptmin,ptmax);
156 sprintf(name,"hNoPid%i",i);
159 if(prob < 0.2) pp = 0.1;
160 if(pos) hh2=GetHistoPip(ptmin,ptmax,pp,0.0,etaminkp,etamaxkp);
161 else hh2=GetHistoPin(ptmin,ptmax,pp,0.0);
162 AddHisto(hh,hh2,weightS);
164 h = hh->ProjectionX(name,cmin,cmax);
165 h->RebinX(rebinsize);
167 h->SetMarkerStyle(24);
170 Float_t chi2 = 10000;
171 while(ntrial < 10 && (chi2 > 20 + 1000*selectTrue)){
172 fit(h,b[i],"WW","",xx[i]);
175 fit(h,b[i],"","",xx[i]);
178 printf("chi2 = %f\n",chi2);
184 yy[i] = fall->GetParameter(parplotted);
185 eyy[i] = fall->GetParError(parplotted);
188 TGraphErrors *gpar = new TGraphErrors(nptbin,xx,yy,exx,eyy);
191 gpar->SetMarkerStyle(20);
193 TCanvas *c2 = new TCanvas();
194 c2->Divide((nptbin+1)/2,2);
197 for(Int_t i=0;i < nptbin;i++){
199 Float_t ptmin = minptbin+(maxptbin-minptbin)/nptbin*(i);
200 Float_t ptmax = minptbin+(maxptbin-minptbin)/nptbin*(i+1);
203 if(prob < 0.2) pp = 0.1;
204 if(pos) hh=GetHistoPip(ptmin,ptmax,pp,0.0,etaminkp,etamaxkp);
205 else hh=GetHistoPin(ptmin,ptmax,pp,0.0);
206 sprintf(name,"P_{TOF} > 0.8: %f < p_{T} < %f GeV/#it{c}",ptmin,ptmax);
208 sprintf(name,"hPid60_%i",i);
209 h = hh->ProjectionX(name,cmin,cmax);
210 h->RebinX(rebinsize);
212 h->SetMarkerStyle(24);
215 Float_t chi2 = 10000;
216 while(ntrial < 40 && (chi2 > 20 + 1000*selectTrue)){
217 fit(h,b2[i],"WW","");
221 printf("chi2 = %f\n",chi2);
223 yy[i] = fall->GetParameter(parplotted);
224 eyy[i] = fall->GetParError(parplotted);
228 TGraphErrors *gpar2 = new TGraphErrors(nptbin,xx,yy,exx,eyy);
231 gpar2->SetMarkerStyle(20);
233 Double_t xpt[50],expt[50],eff[50],efferr[50];
234 for(Int_t i=0;i<nptbin;i++){
235 printf("%f +/- %f - %f +/- %f\n",b[i][0],b[i][1],b2[i][0],b2[i][1]);
237 Float_t ptmin = minptbin+(maxptbin-minptbin)/nptbin*(i);
238 Float_t ptmax = minptbin+(maxptbin-minptbin)/nptbin*(i+1);
240 xpt[i] = (ptmin+ptmax)/2;
241 expt[i] = (-ptmin+ptmax)/2;
242 eff[i] = b2[i][0]/(b[i][0]-b2[i][0]*weightS);
244 b[i][0] = b[i][0]-b2[i][0]*weightS;
246 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]));
248 if(TMath::Abs(efferr[i]) > 1)efferr[i]=1;
251 TGraphErrors *geff = new TGraphErrors(nptbin,xpt,eff,expt,efferr);
258 if(selectTrue) sprintf(flag,"true");
259 else if(!keepTrue) sprintf(flag,"back");
266 sprintf(etarange,"_%.1f-%.1f_",etaminkp,etamaxkp);
272 sprintf(flag2,"BayesVsSigma");
275 sprintf(flag2,"Sigma2vs3");
278 sprintf(flag2,"OverAll");
280 sprintf(flag2,"OverAllTOF");
282 sprintf(flag2,"OverAll2sigma");
285 if(prob >=0.2) sprintf(name,"protonPos%sP%iEff%i_%i%s%s.root",etarange,Int_t(prob*100),(cmin-1)*10,cmax*10,flag,flag2);
286 else sprintf(name,"protonPos%sMatchEff%i_%i%s%s.root",etarange,(cmin-1)*10,cmax*10,flag,flag2);
289 if(prob >=0.2) sprintf(name,"protonNeg%sP%iEff%i_%i%s%s.root",etarange,Int_t(prob*100),(cmin-1)*10,cmax*10,flag,flag2);
290 else sprintf(name,"protonNeg%sMatchEff%i_%i%s%s.root",etarange,(cmin-1)*10,cmax*10,flag,flag2);
293 TFile *fout = new TFile(name,"RECREATE");
298 TF1 *ff = new TF1("ff","[0] - [1]*TMath::Exp([2]*x)",0,3);
299 ff->SetParameter(0,0.67);
300 ff->SetParameter(1,1.14383e+00);
301 ff->SetParameter(2,-2.29910);
306 TF1 *ff2 = new TF1("ff2","[0] - [1]*TMath::Exp([2]*x)",0,3);
307 ff2->SetParameter(0,0.67);
308 ff2->SetParameter(1,9.23126e-01);
309 ff2->SetParameter(2,-1.851);
310 ff2->SetLineColor(4);
314 TH2F *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){
316 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]};
317 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]};
322 if(pMinkp > 0.19) x2[9] = 4.9;
325 if(kOverAllTOFmatch && pMinkp > 0.19){
330 if(kOverAll2Sigma && pMinkp > 0.09){
365 if(require5sigma) x2[9] = 4.9;
367 AliPIDperfContainer *tmp = fContPid1;
369 TH2F *h = tmp->GetQA(0, x, x2);
371 h->GetXaxis()->SetTitle("M_{#Lambda} (GeV/#it{c}^{2})");
372 h->GetYaxis()->SetTitle("centrality [%]");
377 TH2F *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){
379 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]};
380 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]};
385 if(pMinkn > 0.19) x2[10] = 4.9;
388 if(kOverAllTOFmatch && pMinkn > 0.19){
393 if(kOverAll2Sigma && pMinkn > 0.09){
426 if(require5sigma) x2[10] = 4.9;
428 AliPIDperfContainer *tmp = fContPid2;
430 TH2F *h = tmp->GetQA(0, x, x2);
432 h->GetXaxis()->SetTitle("M_{#Lambda} (GeV/#it{c}^{2})");
433 h->GetYaxis()->SetTitle("centrality [%]");
438 fit(TH1D *h,Float_t *a=NULL,char *opt="",char *opt2="",Float_t pt=1.5){
439 if(h->Integral(1,h->GetNbinsX()) < 1){
448 fall->SetParameter(0,100);
449 fall->SetParameter(1,1.115);
450 fall->SetParameter(2,0.0003);
451 fall->SetParameter(3,0.001);
453 fall->SetParLimits(0,0.00001,10000);
454 fall->SetParLimits(1,1.105,1.125);//1.01898 + 2.4e-04*pt-1e-03,1.01898 + 2.4e-04*pt+1e-03);
455 fall->SetParLimits(2,0.00001,0.001);
456 fall->SetParLimits(3,0.0005,0.01);
458 // fall->FixParameter(2,5E-4);
460 // fall->FixParameter(1,1.01884 + 2.9891e-04*pt);
461 // fall->FixParameter(2,0.0044);
462 // fall->FixParameter(3,7.57574e-04 + 3.85408e-04*pt);
464 fall->ReleaseParameter(4);
465 fall->ReleaseParameter(5);
466 fall->ReleaseParameter(6);
469 fall->FixParameter(4,0);
470 fall->FixParameter(5,0);
471 fall->FixParameter(6,0);
477 TF1 *ftmp2=new TF1(*fsign);
478 sprintf(name,"fsign%i",ifunc);
479 ftmp2->SetName(name);
481 TF1 *ftmp3=new TF1(*fback);
482 sprintf(name,"ftmp3%i",ifunc);
483 ftmp3->SetName(name);
487 h->Fit(ftmp,opt,opt2,fitmin,fitmax);
490 ftmp2->SetParameter(0,ftmp->GetParameter(0));
491 ftmp2->SetParameter(1,ftmp->GetParameter(1));
492 ftmp2->SetParameter(2,ftmp->GetParameter(2));
493 ftmp2->SetParameter(3,ftmp->GetParameter(3));
495 ftmp3->SetParameter(0,ftmp->GetParameter(4));
496 ftmp3->SetParameter(1,ftmp->GetParameter(5));
497 ftmp3->SetParameter(2,ftmp->GetParameter(6));
500 Float_t mean = ftmp->GetParameter(1);
501 Float_t sigma = TMath::Abs(ftmp->GetParameter(3)) + TMath::Abs(ftmp->GetParameter(2));
503 Float_t signI = ftmp2->Integral(mean-10*sigma,mean+10*sigma)/h->GetBinWidth(1);
504 Float_t backI = ftmp3->Integral(mean-3*sigma,mean+3*sigma)/h->GetBinWidth(1);
506 Float_t errI = TMath::Sqrt(ftmp->GetParError(0)*ftmp->GetParError(0)/(0.001+ftmp->GetParameter(0))/(0.001+ftmp->GetParameter(0)));
508 printf("signal(5 sigma) = %f +/- %f(fit) +/- %f(stat)\n",signI,errI*signI,TMath::Sqrt(signI));
509 printf("backgr(3sigma) = %f\n",backI);
510 printf("significance(3 sigma) = %f\n",signI/sqrt(signI+backI));
514 a[1]=signI*errI*signI*errI + signI;
515 a[1] = TMath::Sqrt(a[1]);
516 if(ftmp->GetNDF()) a[2] = ftmp->GetChisquare()/ftmp->GetNDF();
520 a[0] = h->Integral(1,h->GetNbinsX());
521 a[1] = TMath::Sqrt(a[0]);
526 AddHisto(TH2F *h1,TH2F *h2,Float_t w){
527 Int_t nbinx = h1->GetNbinsX();
528 Int_t nbiny = h1->GetNbinsY();
530 for(Int_t i=1;i<=nbinx;i++){
531 for(Int_t j=1;j<=nbiny;j++){
532 Float_t val = h1->GetBinContent(i,j) + h2->GetBinContent(i,j)*w;
533 Float_t err = TMath::Min(TMath::Sqrt(val),val);
534 h1->SetBinContent(i,j,val);
535 h1->SetBinError(i,j,err);