+#include"TF1.h"
+#include"TH1D.h"
+#include"TH2F.h"
+#include"TMath.h"
+#include"TSystem.h"
+#include"TCanvas.h"
+#include"TFile.h"
+#include"TGraphErrors.h"
+#include"AliPIDperfContainer.h"
+
+int LoadLib();
+void doeffKaUser(Int_t pos,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8);
+void doeffKa(Int_t pos=1,Float_t prob=0.1,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8);
+TH2F *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);
+TH2F *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);
+void fit(TH1D *h,Float_t *a=NULL,char *opt="",char *opt2="",Float_t pt=1.5);
+void AddHisto(TH2F *h1,TH2F *h2,Float_t w);
+TH2F *GetHistoUser(Int_t pos=1,Float_t pt=1,Float_t ptM=1.1,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8);
+TH2F *GetHistoPiUser(Int_t pos=1,Float_t pt=1,Float_t ptM=1.1,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8);
+TH2F *GetHistoKaUser(Int_t pos=1,Float_t pt=1,Float_t ptM=1.1,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8);
+TH2F *GetHistoPrUser(Int_t pos=1,Float_t pt=1,Float_t ptM=1.1,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8);
+
TObject* fContPid1;
TObject* fContPid2;
+TObject* fContUser1;
+TObject* fContUser2;
const Int_t nBinPid = 14; // pt,eta, ptPip, ptPin, PPip, PPin, TOF3sigmaPip, TOF3sigmaPin, isPhiTrue, nsigmaPip, nsigmaPin
// 0.985 < mass < 1.045 (60) and 0 < centrality < 100 (10)
Int_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*/};
Float_t fitmin = 0.99;
Float_t fitmax = 1.045;
-Int_t cmin = 4;
-Int_t cmax = 8;
+Int_t cmin = 1;// min 1
+Int_t cmax = 10;// max 10
-Float_t weightS = -1.;
+Float_t weightS = -0.9;
-Int_t rebinsize = 2;
+Int_t rebinsize = 1;
Int_t parplotted = 2;
Bool_t kGoodMatch = kFALSE; // to check good matching
Bool_t kSigma2vs3 = kFALSE; // to check good matching
+Bool_t kSigma2vs3TPC = kFALSE; // to check good matching
Bool_t require5sigma = kFALSE; // don't touch this flag
Bool_t kTOFmatch = kFALSE; // for combined PID requires TOF matching
-Bool_t kOverAll = kTRUE;
+Bool_t kOverAll = kFALSE;
Bool_t kOverAllTOFmatch = kFALSE;
-Bool_t kOverAll2Sigma = kTRUE;
+Bool_t kOverAll2Sigma = kFALSE;
+
+TH2F *hmatched;
+TH2F *htracked;
Bool_t kLoaded=kFALSE;
-LoadLib(){
- weightS = -1.;
+int LoadLib(){
+ weightS = -0.9;
+
+ require5sigma = kFALSE;
if(! kLoaded){
gSystem->Load("libVMC.so");
gSystem->Load("libPWGPPpid.so");
TFile *f = new TFile("AnalysisResults.root");
- f->ls();
TList *l = (TList *) f->Get("contPhiBayes1");
- l->ls();
- fContPid1 = (AliPIDperfContainer *) l->At(0);
- fContPid2 = (AliPIDperfContainer *) l->At(1);
+ TList *l2 = (TList *) f->Get("contPhiBayes2");
+
+ if(!(l && l2)) return 0;
+
+ fContPid1 = (AliPIDperfContainer *) l->FindObject("contPID");
+ fContPid2 = (AliPIDperfContainer *) l->FindObject("contPID2");
+ fContUser1 = (AliPIDperfContainer *) l->FindObject("contUserPID");
+ fContUser2 = (AliPIDperfContainer *) l->FindObject("contUserPID2");
+ hmatched = (TH2F *) l2->FindObject("hMatchKa");
+ htracked = (TH2F *) l2->FindObject("hTrackingKa");
}
kLoaded = kTRUE;
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]};
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]};
- AliPIDperfContainer *tmp = fContPid1;
+ AliPIDperfContainer *tmp = (AliPIDperfContainer *) fContPid1;
TH1D *h = tmp->GetQA(0, x, x2)->ProjectionX("checkMC");
if(h->GetEntries()) isMC = kTRUE;
kOverAll = 0;
}
+ if(kSigma2vs3TPC){
+ kGoodMatch=kFALSE;
+ kOverAll = 0;
+ }
+
if(bayesVsigma){
kOverAll = 0;
kGoodMatch=kFALSE;
kSigma2vs3=kFALSE;
+ kSigma2vs3TPC=kFALSE;
kTOFmatch=kTRUE;
- weightS = -0.7;
+ weightS = -0.5;
}
if(kOverAll){
- weightS = -0.7;
+ weightS = -0.5;
+ }
+
+ return 1;
+}
+void doeffKaUser(Int_t pos,Float_t etaminkp,Float_t etamaxkp){
+ Int_t nptbin = binPid[2];
+ Float_t minptbin = xmin[2];
+ Float_t maxptbin = xmax[2];
+
+ TCanvas *c1 = new TCanvas();
+ c1->Divide((nptbin+1)/2,2);
+
+ Double_t xx[50],yyPi[50],yyKa[50],yyPr[50];
+ Double_t exx[50],eyyPi[50],eyyKa[50],eyyPr[50];
+
+ TH2F *hh;
+ TH1D *h;
+
+ Float_t b[100][3];
+ Float_t bPi[100][3];
+ Float_t bKa[100][3];
+ Float_t bPr[100][3];
+
+ char name[100];
+
+ for(Int_t i=0;i < nptbin;i++){
+ c1->cd(i+1);
+ Float_t ptmin = minptbin+(maxptbin-minptbin)/nptbin*(i);
+ Float_t ptmax = minptbin+(maxptbin-minptbin)/nptbin*(i+1);
+
+ xx[i] = (ptmin+ptmax)/2;
+ exx[i] = (-ptmin+ptmax)/2;
+
+ hh=GetHistoUser(pos,ptmin,ptmax,etaminkp,etamaxkp);
+ sprintf(name,"all%i",i);
+ h = hh->ProjectionX(name,cmin,cmax);
+ Int_t ntrial = 0;
+ Float_t chi2 = 10000;
+ while(ntrial < 3 && (chi2 > 20 + 1000*selectTrue)){
+ fit(h,b[i],"WW","",xx[i]);
+ fit(h,b[i],"","",xx[i]);
+ ntrial++;
+ chi2 = b[i][2];
+ }
+ printf("%i) %f +/- %f\n",i,b[i][0],b[i][1]);
+
+ hh=GetHistoPiUser(pos,ptmin,ptmax,etaminkp,etamaxkp);
+ sprintf(name,"pi%i",i);
+ h = hh->ProjectionX(name,cmin,cmax);
+ ntrial = 0;
+ chi2 = 10000;
+ while(ntrial < 3 && (chi2 > 20 + 1000*selectTrue)){
+ fit(h,bPi[i],"WW","",xx[i]);
+ fit(h,bPi[i],"","",xx[i]);
+ ntrial++;
+ chi2 = bPi[i][2];
+ }
+ printf("pi) %f +/- %f\n",bPi[i][0],bPi[i][1]);
+
+ hh=GetHistoKaUser(pos,ptmin,ptmax,etaminkp,etamaxkp);
+ sprintf(name,"ka%i",i);
+ h = hh->ProjectionX(name,cmin,cmax);
+ ntrial = 0;
+ chi2 = 10000;
+ while(ntrial < 3 && (chi2 > 20 + 1000*selectTrue)){
+ fit(h,bKa[i],"WW","",xx[i]);
+ fit(h,bKa[i],"","",xx[i]);
+ ntrial++;
+ chi2 = bKa[i][2];
+ }
+ printf("ka) %f +/- %f\n",bKa[i][0],bKa[i][1]);
+
+ hh=GetHistoPrUser(pos,ptmin,ptmax,etaminkp,etamaxkp);
+ sprintf(name,"pr%i",i);
+ h = hh->ProjectionX(name,cmin,cmax);
+ ntrial = 0;
+ chi2 = 10000;
+ while(ntrial < 3 && (chi2 > 20 + 1000*selectTrue)){
+ fit(h,bPr[i],"WW","",xx[i]);
+ fit(h,bPr[i],"","",xx[i]);
+ ntrial++;
+ chi2 = bPr[i][2];
+ }
+ printf("pr) %f +/- %f\n",bPr[i][0],bPr[i][1]);
+
+ yyPi[i] = bPi[i][0] / b[i][0];
+ yyKa[i] = bKa[i][0] / b[i][0];
+ yyPr[i] = bPr[i][0] / b[i][0];
+
+ eyyPi[i] = bPi[i][1]/bPi[i][0]*yyPi[i];
+ eyyKa[i] = bKa[i][1]/bKa[i][0]*yyKa[i];
+ eyyPr[i] = bPr[i][1]/bPr[i][0]*yyPr[i];
}
+
+ /*TCanvas *c2 =*/ new TCanvas();
+ TGraphErrors *gKa = new TGraphErrors(nptbin,xx,yyKa,exx,eyyKa);
+ gKa->Draw("AP");
+ gKa->SetLineColor(1);
+ gKa->SetMarkerColor(1);
+ gKa->SetMarkerStyle(21);
+
+ TGraphErrors *gPi = new TGraphErrors(nptbin,xx,yyPi,exx,eyyPi);
+ gPi->Draw("P");
+ gPi->SetLineColor(4);
+ gPi->SetMarkerColor(4);
+ gPi->SetMarkerStyle(20);
+
+ TGraphErrors *gPr = new TGraphErrors(nptbin,xx,yyPr,exx,eyyPr);
+ gPr->Draw("P");
+ gPr->SetLineColor(2);
+ gPr->SetMarkerColor(2);
+ gPr->SetMarkerStyle(22);
+
+ if(pos) sprintf(name,"phiUserAnalPos_%3.1f-%3.1f_%i-%i.root",etaminkp,etamaxkp,cmin,cmax);
+ else sprintf(name,"phiUserAnalNeg_%3.1f-%3.1f_%i-%i.root",etaminkp,etamaxkp,cmin,cmax);
+
+ gPi->SetName("piSelected");
+ gKa->SetName("kaSelected");
+ gPr->SetName("prSelected");
+
+ TFile *fout = new TFile(name,"RECREATE");
+ gPi->Write();
+ gKa->Write();
+ gPr->Write();
+ fout->Close();
+}
+
+TH2F *GetHistoUser(Int_t pos,Float_t pt,Float_t ptM,Float_t etaminkp,Float_t etamaxkp){
+ // Int_t binUser[nBinUser] = {8/*Eta*/,20/*pt*/,2/*istrue*/,4/*whatSelection*/,1/*DeltaPhi*/,1/*Psi*/};
+ Float_t x[] = {etaminkp+0.0001,pt+0.0001,isMC,0.0001,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
+ Float_t x2[] = {etamaxkp-0.0001,ptM-0.0001,isMC,2.9999,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
+
+ AliPIDperfContainer *tmp = (AliPIDperfContainer *) fContUser1;
+ if(!pos) tmp = (AliPIDperfContainer *) fContUser2;
+
+ TH2F *h = tmp->GetQA(0, x, x2);
+
+ h->GetXaxis()->SetTitle("M_{K^{0}_{s}} (GeV/#it{c}^{2})");
+ h->GetYaxis()->SetTitle("centrality [%]");
+
+ return h;
+
+}
+
+
+TH2F *GetHistoPiUser(Int_t pos,Float_t pt,Float_t ptM,Float_t etaminkp,Float_t etamaxkp){
+ // Int_t binUser[nBinUser] = {8/*Eta*/,20/*pt*/,2/*istrue*/,4/*whatSelection*/,1/*DeltaPhi*/,1/*Psi*/};
+ Float_t x[] = {etaminkp+0.0001,pt+0.0001,isMC,1.0001,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
+ Float_t x2[] = {etamaxkp-0.0001,ptM-0.0001,isMC,1.0002,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
+
+ AliPIDperfContainer *tmp = (AliPIDperfContainer *) fContUser1;
+ if(!pos) tmp = (AliPIDperfContainer *) fContUser2;
+
+ TH2F *h = tmp->GetQA(0, x, x2);
+
+ h->GetXaxis()->SetTitle("M_{K^{0}_{s}} (GeV/#it{c}^{2})");
+ h->GetYaxis()->SetTitle("centrality [%]");
+
+ return h;
+
+}
+
+
+TH2F *GetHistoKaUser(Int_t pos,Float_t pt,Float_t ptM,Float_t etaminkp,Float_t etamaxkp){
+ // Int_t binUser[nBinUser] = {8/*Eta*/,20/*pt*/,2/*istrue*/,4/*whatSelection*/,1/*DeltaPhi*/,1/*Psi*/};
+ Float_t x[] = {etaminkp+0.0001,pt+0.0001,isMC,2.0001,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
+ Float_t x2[] = {etamaxkp-0.0001,ptM-0.0001,isMC,2.0002,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
+
+ AliPIDperfContainer *tmp = (AliPIDperfContainer *) fContUser1;
+ if(!pos) tmp = (AliPIDperfContainer *) fContUser2;
+
+ TH2F *h = tmp->GetQA(0, x, x2);
+
+ h->GetXaxis()->SetTitle("M_{K^{0}_{s}} (GeV/#it{c}^{2})");
+ h->GetYaxis()->SetTitle("centrality [%]");
+
+ return h;
+
+}
+
+
+TH2F *GetHistoPrUser(Int_t pos,Float_t pt,Float_t ptM,Float_t etaminkp,Float_t etamaxkp){
+ // Int_t binUser[nBinUser] = {8/*Eta*/,20/*pt*/,2/*istrue*/,4/*whatSelection*/,1/*DeltaPhi*/,1/*Psi*/};
+ Float_t x[] = {etaminkp+0.0001,pt+0.0001,isMC,3.0001,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
+ Float_t x2[] = {etamaxkp-0.0001,ptM-0.0001,isMC,3.0002,-TMath::Pi(),TMath::Pi(),-TMath::Pi()/2,TMath::Pi()/2};
+
+ AliPIDperfContainer *tmp = (AliPIDperfContainer *) fContUser1;
+ if(!pos) tmp = (AliPIDperfContainer *) fContUser2;
+
+ TH2F *h = tmp->GetQA(0, x, x2);
+
+ h->GetXaxis()->SetTitle("M_{K^{0}_{s}} (GeV/#it{c}^{2})");
+ h->GetYaxis()->SetTitle("centrality [%]");
+
+ return h;
+
}
-doeffKa(Int_t pos=1,Float_t prob=0.1,Float_t etaminkp=-0.8,Float_t etamaxkp=0.8){
+
+void doeffKa(Int_t pos,Float_t prob,Float_t etaminkp,Float_t etamaxkp){
LoadLib();
+ TH1D *hm = hmatched->ProjectionX("matchingKaEff",cmin,cmax);
+ TH1D *ht = htracked->ProjectionX("tracking",cmin,cmax);
+
+ hm->GetYaxis()->SetTitle("TOF matching eff.");
+ hm->SetTitle("Using probability as weights");
+ hm->Sumw2();
+ ht->Sumw2();
+
+ hm->Divide(hm,ht,1,1,"B");
+
+
Int_t nptbin = binPid[2];
Float_t minptbin = xmin[2];
Float_t maxptbin = xmax[2];
if(prob > 0.1999){
kGoodMatch = kFALSE;
kSigma2vs3 = kFALSE;
+ kSigma2vs3TPC=kFALSE;
if(! kOverAll) require5sigma = kTRUE;
- if(!isMC && !kOverAll) weightS = -0.95;
+ if(!isMC && !kOverAll) weightS = -0.9;
}
- TCanvas *c = new TCanvas();
- c->Divide((nptbin+1)/2,2);
- TH2F *hh.*hh2;
- TH1D *h,*h2;
+ TCanvas *c1 = new TCanvas();
+ c1->Divide((nptbin+1)/2,2);
+ TH2F *hh,*hh2;
+ TH1D *h;
char name[100];
Float_t b[50][3];
Double_t exx[50],eyy[50];
for(Int_t i=0;i < nptbin;i++){
- c->cd(i+1)->SetLogy();
+ c1->cd(i+1);//->SetLogy();
Float_t ptmin = minptbin+(maxptbin-minptbin)/nptbin*(i);
Float_t ptmax = minptbin+(maxptbin-minptbin)/nptbin*(i+1);
b[i][0]=-1;
Int_t ntrial = 0;
Float_t chi2 = 10000;
- while(ntrial < 10 && (chi2 > 20 + 1000*selectTrue)){
+ while(ntrial < 3 && (chi2 > 20 + 1000*selectTrue)){
fit(h,b[i],"WW","",xx[i]);
c1->Update();
// getchar();
}
TGraphErrors *gpar = new TGraphErrors(nptbin,xx,yy,exx,eyy);
- c->cd(8);
- gpar->Draw("AP");
+ c1->cd(8);
+// gpar->Draw("AP");
gpar->SetMarkerStyle(20);
TCanvas *c2 = new TCanvas();
b2[i][0]=-1;
Int_t ntrial = 0;
Float_t chi2 = 10000;
- while(ntrial < 40 && (chi2 > 20 + 1000*selectTrue)){
+ while(ntrial < 3 && (chi2 > 20 + 1000*selectTrue)){
fit(h,b2[i],"WW","");
fit(h,b2[i],"","");
ntrial++;
TGraphErrors *gpar2 = new TGraphErrors(nptbin,xx,yy,exx,eyy);
c2->cd(8);
- gpar2->Draw("AP");
+// gpar2->Draw("AP");
gpar2->SetMarkerStyle(20);
Double_t xpt[50],expt[50],eff[50],efferr[50];
geff->Draw("AP");
char flag[100];
- sprintf(flag,"");
+ flag[0] = '\0';
if(isMC){
if(selectTrue) sprintf(flag,"true");
}
char flag2[100];
- sprintf(flag2,"");
+ flag2[0] = '\0';
+
+ Bool_t kWriteME = kFALSE;
char etarange[100];
sprintf(etarange,"_%.1f-%.1f_",etaminkp,etamaxkp);
if(kSigma2vs3)
sprintf(flag2,"Sigma2vs3");
+ if(kSigma2vs3TPC)
+ sprintf(flag2,"Sigma2vs3TPC");
+
if(kOverAll)
sprintf(flag2,"OverAll");
if(kOverAllTOFmatch)
if(pos){
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);
- else sprintf(name,"kaonPos%sMatchEff%i_%i%s%s.root",etarange,(cmin-1)*10,cmax*10,flag,flag2);
+ else{
+ sprintf(name,"kaonPos%sMatchEff%i_%i%s%s.root",etarange,(cmin-1)*10,cmax*10,flag,flag2);
+ if(!(kOverAll || bayesVsigma || kGoodMatch || kSigma2vs3 || kSigma2vs3TPC)) kWriteME = kTRUE;
+ }
}
else{
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);
else sprintf(name,"kaonNeg%sMatchEff%i_%i%s%s.root",etarange,(cmin-1)*10,cmax*10,flag,flag2);
}
+ geff->SetTitle("K efficiency (from #phi);p_{T} (GeV/#it{c};efficiency");
TFile *fout = new TFile(name,"RECREATE");
geff->Write();
+ if(kWriteME) hm->Write();
fout->Close();
-
- TF1 *ff = new TF1("ff","[0] - [1]*TMath::Exp([2]*x)",0,3);
- ff->SetParameter(0,0.67);
- ff->SetParameter(1,1.14383e+00);
- ff->SetParameter(2,-2.29910);
- ff->SetLineColor(4);
- ff->SetLineColor(2);
- ff->Draw("SAME");
-
- TF1 *ff2 = new TF1("ff2","[0] - [1]*TMath::Exp([2]*x)",0,3);
- ff2->SetParameter(0,0.67);
- ff2->SetParameter(1,9.23126e-01);
- ff2->SetParameter(2,-1.851);
- ff2->SetLineColor(4);
- ff2->Draw("SAME");
+ if(kWriteME) hm->Draw("SAME");
}
-TH2F *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){
+TH2F *GetHistoKap(Float_t pt,Float_t ptM,Float_t pMinkp,Float_t pMinkn,Float_t etaminkp,Float_t etamaxkp){
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]};
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]};
if(kOverAll){
x[6] = 0.0001;
- x2[9] = 5.9;
- if(pMinkp > 0.19) x2[9] = 4.9;
+ x2[9] = 4.9;
}
if(kOverAllTOFmatch && pMinkp > 0.19){
x[6] = 1.0001;
- x2[9] = 4.9;
}
if(kOverAll2Sigma && pMinkp > 0.09){
x2[9] = 2;
}
+ if(kSigma2vs3TPC){
+ x[6] = 0.0001;
+ x2[6] = 0.0002;
+ x2[9] = 3;
+ if(pMinkp > 0)
+ x2[9] = 2;
+ }
+
if(bayesVsigma){
if(pMinkp > 0){
x[4] = 0.2001;
if(require5sigma) x2[9] = 4.9;
- AliPIDperfContainer *tmp = fContPid1;
+ AliPIDperfContainer *tmp = (AliPIDperfContainer *) fContPid1;
TH2F *h = tmp->GetQA(0, x, x2);
return h;
}
-TH2F *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){
+TH2F *GetHistoKan(Float_t pt,Float_t ptM,Float_t pMinkn,Float_t pMinkp,Float_t etaminkp,Float_t etamaxkp){
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]};
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]};
if(kOverAll){
x[7] = 0.0001;
- x2[10] = 5.9;
- if(pMinkn > 0.19) x2[10] = 4.9;
+ x2[10] = 4.9;
}
if(kOverAllTOFmatch && pMinkn > 0.19){
x[7] = 1.0001;
- x2[10] = 4.9;
}
if(kOverAll2Sigma && pMinkn > 0.09){
if(pMinkn > 0)
x2[10] = 2;
}
+
+ if(kSigma2vs3TPC){
+ x[7] = 0.0001;
+ x2[7] = 0.0002;
+ x2[10] = 3;
+ if(pMinkn > 0)
+ x2[10] = 2;
+ }
if(bayesVsigma){
if(pMinkn > 0){
if(require5sigma) x2[10] = 4.9;
- AliPIDperfContainer *tmp = fContPid2;
+ AliPIDperfContainer *tmp = (AliPIDperfContainer *) fContPid2;
TH2F *h = tmp->GetQA(0, x, x2);
}
-fit(TH1D *h,Float_t *a=NULL,char *opt="",char *opt2="",Float_t pt=1.5){
+void fit(TH1D *h,Float_t *a,char *opt,char *opt2,Float_t pt){
if(h->GetEntries() < 1){
if(a){
a[0]=0.01;
if(selectTrue){
- a[0] = h->GetEntries();
+ a[0] = h->Integral(1,h->GetNbinsX());
a[1] = TMath::Sqrt(a[0]);
}
}
}
-AddHisto(TH2F *h1,TH2F *h2,Float_t w){
+void AddHisto(TH2F *h1,TH2F *h2,Float_t w){
Int_t nbinx = h1->GetNbinsX();
Int_t nbiny = h1->GetNbinsY();
for(Int_t i=1;i<=nbinx;i++){
for(Int_t j=1;j<=nbiny;j++){
- Float_t val = h1->GetBinContent(i,j) + h2->GetBinContent(i,j)*w;
+ Double_t val = h1->GetBinContent(i,j) + h2->GetBinContent(i,j)*w;
Float_t err = TMath::Min(TMath::Sqrt(val),val);
h1->SetBinContent(i,j,val);
h1->SetBinError(i,j,err);
git://git.uio.no / u / mrichter / AliRoot.git / blobdiff