void CheckMerge(TH3* h, THnSparse* sparse)
{
// check merging of three THnSparse
TList h3_clones;
h3_clones.SetOwner();
for (int i = 0; i < 4; ++i) {
h3_clones.AddLast(h->Clone());
((TH3*)h3_clones.Last())->Scale(i);
}
TList hs_clones;
hs_clones.SetOwner();
for (int i = 0; i < 4; ++i) {
hs_clones.AddLast(sparse->Clone());
((THnSparse*)hs_clones.Last())->Scale(i);
}
TH3* h3Merge = (TH3*) h->Clone();
THnSparse* hsMerge = (THnSparse*) sparse->Clone();
h3Merge->Merge(&h3_clones);
hsMerge->Merge(&hs_clones);
TH3* proj = hsMerge->Projection(0, 1, 2);
Test(h3Merge, proj, "Merging histograms");
delete proj;
delete h3Merge;
delete hsMerge;
}
//______________________________________________________________________________
void drawsparse()
{
// create a THnSparse and draw it.
#ifdef __CINT__
printf("For performance reasons we advise to run \".x drawsparse.C+\"\n");
#endif
const Int_t ndims = 8;
Int_t bins[ndims] = {10, 10, 5, 30, 10, 4, 18, 12};
Double_t xmin[ndims] = {-5., -10., -1000., -3., 0., 0., 0., 0.};
Double_t xmax[ndims] = {10., 70., 3000., 3., 5., 2., 2., 5.};
THnSparse* hs = new THnSparseD("hs", "Sparse Histogram", ndims, bins, xmin, xmax);
// fill it
Double_t x[ndims];
for (Long_t i = 0; i < 100000; ++i) {
for (Int_t d = 0; d < ndims; ++d) {
switch (d) {
case 0: x[d] = gRandom->Gaus()*2 + 3.; break;
case 1:
case 2:
case 3: x[d] = (x[d-1]*x[d-1] - 1.5)/1.5 + (0.5*gRandom->Rndm()); break;
default: x[d] = sin(gRandom->Gaus()*i/1000.) + 1.;
}
}
hs->Fill(x);
}
TFile* f = new TFile("drawsparse.root","RECREATE");
TCanvas* canv = new TCanvas("hDrawSparse", "Drawing a sparse hist");
canv->Divide(2);
// draw it
canv->cd(1);
drawsparse_draw(hs);
// project it
canv->cd(2);
TH3D* h3proj = hs->Projection(2, 3, 6);
h3proj->SetLineColor(kOrange);
h3proj->SetDirectory(0);
h3proj->Draw("lego1");
// save everything to a file
canv->Write();
hs->Write();
h3proj->Write();
delete f;
}
void CheckClone(TH3* h, THnSparse* sparse)
{
// Check cloning of a THnSparse
if (h) {}
THnSparse* clone = (THnSparse*)sparse->Clone("clone");
TH3* proj = sparse->Projection(0, 1, 2);
TH3* projclone = clone->Projection(0, 1, 2);
Test(proj, projclone, "Cloning of THnSparse");
delete clone;
delete proj;
delete projclone;
}
void CheckSubtract(TH3* h, THnSparse* sparse)
{
// Check subtracting THnSparse from THnSparse
TH3* h42 = (TH3*)h->Clone("h42");
h42->Scale(.42);
THnSparse* clone = (THnSparse*)sparse->Clone("clone");
clone->Scale(1.42);
clone->Add(sparse, -1.);
TH3* proj = clone->Projection(0, 1, 2);
Test(h42, proj, "Subtracting two THnSparse");
delete proj;
delete clone;
delete h42;
}
TH1 *PullHisto(const TList *list, const char *name, Int_t min, Int_t max,
Double_t &mean)
{
THnSparse *hs = list->FindObject(name);
if (!hs) return 0;
TAxis *atmp = hs->GetAxis(1);
atmp->SetRange(min, max);
// !!!!!!!!!!!!!!!!!!!!
hs->GetAxis(2)->SetRangeUser(-0.5, 0.5);
TH1 *hfin = hs->Projection(0);
hfin->SetTitle(Form("p_{t} #in (%4.2f, %4.2f) GeV/c",
atmp->GetBinLowEdge(min),
atmp->GetBinLowEdge(max) + atmp->GetBinWidth(max)));
mean = atmp->GetBinLowEdge(min) +
(atmp->GetBinLowEdge(max) + atmp->GetBinWidth(max) -
atmp->GetBinLowEdge(min))/2.0;
// !!!!!!!!!!!!!!!!!!!!
return hfin;//->Rebin();
}
//___________________________________________________________________
Int_t studyBinZero(TString pathData, TString fileNameData, TString listName = "",
Double_t etaLow = -0.9, Double_t etaUp = 0.9,
Double_t lowerCentrality = -2, Double_t upperCentrality = -2)
{
PrintSettingsAxisRangeForMultiplicityAxisForMB();
TString pathNameData = Form("%s/%s", pathData.Data(), fileNameData.Data());
if (listName == "") {
listName = pathNameData;
listName.Replace(0, listName.Last('/') + 1, "");
listName.ReplaceAll(".root", "");
}
TObjArray* histList = 0x0;
TFile* f = TFile::Open(pathNameData.Data());
if (!f) {
std::cout << std::endl;
std::cout << "Failed to open file \"" << pathNameData.Data() << "\"!" << std::endl;
return -1;
}
histList = (TObjArray*)(f->Get(listName.Data()));
if (!histList) {
std::cout << std::endl;
std::cout << "Failed to load list \"" << listName.Data() << "\"!" << std::endl;
return -1;
}
// Extract the data histograms
TH1* hNumEventsTriggerSel = dynamic_cast<TH1*>(histList->FindObject("fhEventsTriggerSel"));
TH1* hNumEventsTriggerSelVtxCut = dynamic_cast<TH1*>(histList->FindObject("fhEventsTriggerSelVtxCut"));
TH1* hNumEventsTriggerSelVtxCutZ= dynamic_cast<TH1*>(histList->FindObject("fhEventsProcessedNoPileUpRejection"));
TH1* hNumEventsTriggerSelVtxCutZPileUpRej= dynamic_cast<TH1*>(histList->FindObject("fhEventsProcessed"));
THnSparse* hDataTriggerSel = dynamic_cast<THnSparse*>(histList->FindObject("fChargedGenPrimariesTriggerSel"));
THnSparse* hDataTriggerSelVtxCut = dynamic_cast<THnSparse*>(histList->FindObject("fChargedGenPrimariesTriggerSelVtxCut"));
THnSparse* hDataTriggerSelVtxCutZ = dynamic_cast<THnSparse*>(histList->FindObject("fChargedGenPrimariesTriggerSelVtxCutZ"));
THnSparse* hDataTriggerSelVtxCutZPileUpRej = dynamic_cast<THnSparse*>(histList->FindObject("fChargedGenPrimariesTriggerSelVtxCutZPileUpRej"));
setSparseErrors(hDataTriggerSel);
setSparseErrors(hDataTriggerSelVtxCut);
setSparseErrors(hDataTriggerSelVtxCutZ);
setSparseErrors(hDataTriggerSelVtxCutZPileUpRej);
// Set multiplicity range, if desired. Note that mult and pT axes are the same for all histos
Int_t lowerCentralityBinLimit = -1;
Int_t upperCentralityBinLimit = -2;
Bool_t restrictCentralityAxis = kFALSE;
Double_t actualLowerCentrality = -1.;
Double_t actualUpperCentrality = -1.;
if (lowerCentrality >= -1 && upperCentrality >= -1) {
// Add subtract a very small number to avoid problems with values right on the border between to bins
lowerCentralityBinLimit = hNumEventsTriggerSel->GetXaxis()->FindFixBin(lowerCentrality + 0.001);
upperCentralityBinLimit = hNumEventsTriggerSel->GetXaxis()->FindFixBin(upperCentrality - 0.001);
// Check if the values look reasonable
if (lowerCentralityBinLimit <= upperCentralityBinLimit && lowerCentralityBinLimit >= 1
&& upperCentralityBinLimit <= hNumEventsTriggerSel->GetXaxis()->GetNbins()) {
actualLowerCentrality = hNumEventsTriggerSel->GetXaxis()->GetBinLowEdge(lowerCentralityBinLimit);
actualUpperCentrality = hNumEventsTriggerSel->GetXaxis()->GetBinUpEdge(upperCentralityBinLimit);
restrictCentralityAxis = kTRUE;
}
else {
std::cout << std::endl;
std::cout << "Requested centrality range out of limits or upper and lower limit are switched!" << std::endl;
return -1;
}
}
if (!restrictCentralityAxis)
GetAxisRangeForMultiplicityAxisForMB(hNumEventsTriggerSel->GetXaxis(), lowerCentralityBinLimit, upperCentralityBinLimit);
hNumEventsTriggerSel->GetXaxis()->SetRange(lowerCentralityBinLimit, upperCentralityBinLimit);
actualLowerCentrality = hNumEventsTriggerSel->GetXaxis()->GetBinLowEdge(hNumEventsTriggerSel->GetXaxis()->GetFirst());
actualUpperCentrality = hNumEventsTriggerSel->GetXaxis()->GetBinUpEdge(hNumEventsTriggerSel->GetXaxis()->GetLast());
std::cout << "centrality: ";
if (restrictCentralityAxis) {
std::cout << actualLowerCentrality << " - " << actualUpperCentrality << std::endl;
std::cout << "WARNING: Does it really make sense to restrict the centrality? Usually, centrality estimators imply centrality >= 0!"
<< std::endl;
}
else
std::cout << "MB (" << actualLowerCentrality << " - " << actualUpperCentrality << ")" << std::endl;
if (restrictCentralityAxis) {
hDataTriggerSel->GetAxis(iMult)->SetRange(lowerCentralityBinLimit, upperCentralityBinLimit);
hDataTriggerSelVtxCut->GetAxis(iMult)->SetRange(lowerCentralityBinLimit, upperCentralityBinLimit);
hDataTriggerSelVtxCutZ->GetAxis(iMult)->SetRange(lowerCentralityBinLimit, upperCentralityBinLimit);
hDataTriggerSelVtxCutZPileUpRej->GetAxis(iMult)->SetRange(lowerCentralityBinLimit, upperCentralityBinLimit);
}
// Restrict eta range
const Int_t lowerEtaBinLimit = hDataTriggerSel->GetAxis(iEta)->FindFixBin(etaLow + 0.0001);
const Int_t upperEtaBinLimit = hDataTriggerSel->GetAxis(iEta)->FindFixBin(etaUp - 0.0001);
const Double_t actualLowerEta = hDataTriggerSel->GetAxis(iEta)->GetBinLowEdge(lowerEtaBinLimit);
const Double_t actualUpperEta = hDataTriggerSel->GetAxis(iEta)->GetBinUpEdge(upperEtaBinLimit);
std::cout << "Eta: ";
std::cout << actualLowerEta << " - " << actualUpperEta << std::endl;
Bool_t symmetricInEta = TMath::Abs(TMath::Abs(actualLowerEta) - TMath::Abs(actualUpperEta)) < 1e-6;
TString etaRange = symmetricInEta ? Form("|#it{#eta}| < %.1f", TMath::Abs(actualLowerEta))
: Form("%.1f < #it{#eta} < %.1f", actualLowerEta, actualUpperEta);
hDataTriggerSel->GetAxis(iEta)->SetRange(lowerEtaBinLimit, upperEtaBinLimit);
hDataTriggerSelVtxCut->GetAxis(iEta)->SetRange(lowerEtaBinLimit, upperEtaBinLimit);
hDataTriggerSelVtxCutZ->GetAxis(iEta)->SetRange(lowerEtaBinLimit, upperEtaBinLimit);
hDataTriggerSelVtxCutZPileUpRej->GetAxis(iEta)->SetRange(lowerEtaBinLimit, upperEtaBinLimit);
// Obtain number of events for each class
// Note: Under- and overflow automatically taken into account for unrestricted axis by using -1 and -2 for limits
const Double_t numEvtsTriggerSel = hNumEventsTriggerSel->Integral(lowerCentralityBinLimit, upperCentralityBinLimit);
const Double_t numEvtsTriggerSelVtxCut = hNumEventsTriggerSelVtxCut->Integral(lowerCentralityBinLimit, upperCentralityBinLimit);
const Double_t numEvtsTriggerSelVtxCutZ = hNumEventsTriggerSelVtxCutZ->Integral(lowerCentralityBinLimit, upperCentralityBinLimit);
const Double_t numEvtsTriggerSelVtxCutZPileUpRej = hNumEventsTriggerSelVtxCutZPileUpRej->Integral(lowerCentralityBinLimit,
upperCentralityBinLimit);
// Project pT spectra
TH1D* hSpectraTriggerSel = (TH1D*)hDataTriggerSel->Projection(iPt, "e");
TH1D* hSpectraTriggerSelVtxCut = (TH1D*)hDataTriggerSelVtxCut->Projection(iPt, "e");
TH1D* hSpectraTriggerSelVtxCutZ = (TH1D*)hDataTriggerSelVtxCutZ->Projection(iPt, "e");
TH1D* hSpectraTriggerSelVtxCutZPileUpRej = (TH1D*)hDataTriggerSelVtxCutZPileUpRej->Projection(iPt, "e");
// Normalise histos to 1/Nevt dN/dPt
normaliseHist(hSpectraTriggerSel, numEvtsTriggerSel);
normaliseHist(hSpectraTriggerSelVtxCut, numEvtsTriggerSelVtxCut);
normaliseHist(hSpectraTriggerSelVtxCutZ, numEvtsTriggerSelVtxCutZ);
normaliseHist(hSpectraTriggerSelVtxCutZPileUpRej, numEvtsTriggerSelVtxCutZPileUpRej);
setupHist(hSpectraTriggerSel, kBlack, "Trigger selection");
setupHist(hSpectraTriggerSelVtxCut, kRed, "& vertex cut");
setupHist(hSpectraTriggerSelVtxCutZ, kBlue, "& vertex #it{z} cut");
setupHist(hSpectraTriggerSelVtxCutZPileUpRej, kGreen, "& pile-up rejection");
TCanvas* canvSpectra = new TCanvas("canvSpectra", "Spectra", 760, 420);
canvSpectra->SetLogx();
canvSpectra->SetLogy();
canvSpectra->SetGrid(0, 0);
SetCanvasMargins(canvSpectra);
TLegend* leg = new TLegend(0.14, 0.26, 0.62, 0.55);
leg->SetHeader(Form("MC pp #sqrt{s}=7 TeV, inclusive, %s", etaRange.Data()));
leg->AddEntry(hSpectraTriggerSel, "", "l");
leg->AddEntry(hSpectraTriggerSelVtxCut, "", "l");
leg->AddEntry(hSpectraTriggerSelVtxCutZ, "", "l");
if (drawPileUp)
leg->AddEntry(hSpectraTriggerSelVtxCutZPileUpRej, "", "l");
SetupLegend(leg);
leg->SetMargin(0.15);
hSpectraTriggerSel->Draw();
hSpectraTriggerSelVtxCut->Draw("same");
hSpectraTriggerSelVtxCutZ->Draw("same");
if (drawPileUp)
hSpectraTriggerSelVtxCutZPileUpRej->Draw("same");
leg->Draw("same");
// Ratios (take binomial errors, since real sub-samples)
TH1D* hRatioVtxCut = new TH1D(*hSpectraTriggerSelVtxCut);
hRatioVtxCut->SetName("hRatioVtxCut");
setupHist(hRatioVtxCut, kBlack, "MB & vtx / MB");
hRatioVtxCut->GetYaxis()->SetTitle("1/#it{N}_{evt} d#it{N}/d#it{p}_{T}^{gen} ratio");
hRatioVtxCut->Divide(hRatioVtxCut, hSpectraTriggerSel, 1., 1., "B");
hRatioVtxCut->GetYaxis()->SetRangeUser(1.08, 1.14);
// Mean ratio of spectra and of Nevt
TF1* funcRatioVtxCut = new TF1("funcRatioVtxCut", "pol0",
0.15, hRatioVtxCut->GetXaxis()->GetBinUpEdge(hSpectraTriggerSelVtxCut->FindLastBinAbove(0)));
funcRatioVtxCut->SetLineWidth(2);
funcRatioVtxCut->SetLineColor(kRed);
hRatioVtxCut->Fit(funcRatioVtxCut, "N");
const Double_t meanRatioVtxCut = funcRatioVtxCut->GetParameter(0);
const Double_t ratioNevtVtxCut = numEvtsTriggerSelVtxCut > 0 ? numEvtsTriggerSel / numEvtsTriggerSelVtxCut : -1.;
const Double_t doubleRatioMinusOne = meanRatioVtxCut > 0 ? (ratioNevtVtxCut / meanRatioVtxCut - 1.) : -999.;
TH1D* hRatioVtxCutZ = new TH1D(*hSpectraTriggerSelVtxCutZ);
hRatioVtxCutZ->SetName("hRatioVtxCutZ");
setupHist(hRatioVtxCutZ, kBlack, "MB & vtx & #it{z} vtx / MB & vtx");
hRatioVtxCutZ->GetYaxis()->SetTitle("1/#it{N}_{evt} d#it{N}/d#it{p}_{T}^{gen} ratio");
hRatioVtxCutZ->Divide(hRatioVtxCutZ, hSpectraTriggerSelVtxCut, 1., 1., "B");
hRatioVtxCutZ->GetYaxis()->SetRangeUser(0.95, 1.05);
// Mean ratio of spectra and of Nevt
TF1* funcRatioVtxCutZ = new TF1("funcRatioVtxCutZ", "pol0",
0.15, hRatioVtxCutZ->GetXaxis()->GetBinUpEdge(hSpectraTriggerSelVtxCutZ->FindLastBinAbove(0)));
hRatioVtxCutZ->Fit(funcRatioVtxCutZ, "N");
funcRatioVtxCutZ->SetLineWidth(2);
funcRatioVtxCutZ->SetLineColor(kRed);
const Double_t meanRatioVtxCutZ = funcRatioVtxCutZ->GetParameter(0);
const Double_t ratioNevtVtxCutZ = numEvtsTriggerSelVtxCutZ > 0 ? numEvtsTriggerSelVtxCut / numEvtsTriggerSelVtxCutZ : -1.;
TH1D* hRatioPileUp = new TH1D(*hSpectraTriggerSelVtxCutZPileUpRej);
hRatioPileUp->SetName("hRatioPileUp");
setupHist(hRatioPileUp, kBlack, "MB & vtx & #it{z} vtx & pile-up / MB & vtx & #it{z} vtx");
hRatioPileUp->GetYaxis()->SetTitle("1/#it{N}_{evt} d#it{N}/d#it{p}_{T}^{gen} ratio");
hRatioPileUp->Divide(hRatioPileUp, hSpectraTriggerSelVtxCutZ, 1., 1., "B");
/*
TF1* funcRatioPileUp = new TF1("funcRatioPileUp", "pol0",
0.15, hRatioPileUp->GetXaxis()->GetBinUpEdge(hSpectraTriggerSelVtxCutZPileUpRej->FindLastBinAbove(0)));
hRatioPileUp->Fit(funcRatioPileUp, "N");*/
ClearTitleFromHistoInCanvas(canvSpectra);
TCanvas* canvRatioVtx = new TCanvas("canvRatioVtx", "Ratio vertex", 760, 420);
canvRatioVtx->SetLogx();
canvRatioVtx->SetGrid(0, 1);
SetCanvasMargins(canvRatioVtx);
hRatioVtxCut->Draw();
funcRatioVtxCut->Draw("same");
TLegend* leg2 = new TLegend(0.22, 0.7, drawPileUp ? 0.87 : 0.72, 0.9);
leg2->SetHeader(Form("MC pp #sqrt{s}=7 TeV, inclusive, %s", etaRange.Data()));
leg2->AddEntry(hRatioVtxCut, "", "l");
SetupLegend(leg2);
leg2->SetMargin(0.1);
leg2->Draw("same");
ClearTitleFromHistoInCanvas(canvRatioVtx);
TCanvas* canvRatioOther = new TCanvas("canvRatioOther", "Ratio others", 760, 420);
canvRatioOther->SetLogx();
canvRatioOther->SetGrid(0, 1);
SetCanvasMargins(canvRatioOther);
hRatioVtxCutZ->Draw();
if (drawPileUp)
hRatioPileUp->Draw("same");
TLegend* leg3 = new TLegend(0.22, drawPileUp ? 0.63 : 0.7, drawPileUp ? 0.87 : 0.72, 0.9);
leg3->SetHeader(Form("MC pp #sqrt{s}=7 TeV, inclusive, %s", etaRange.Data()));
leg3->AddEntry(hRatioVtxCutZ, "", "l");
if (drawPileUp)
leg3->AddEntry(hRatioPileUp, "", "l");
SetupLegend(leg3);
leg3->SetMargin(0.1);
leg3->Draw("same");
ClearTitleFromHistoInCanvas(canvRatioOther);
printf("meanRatioVtxCut %f <-> ratioNevtVtxCut %f => meanRatioVtxCutZ/ratioNevtVtxCutZ - 1 = %f\nmeanRatioVtxCutZ %f <-> ratioNevtVtxCutZ %f\n",
meanRatioVtxCut, ratioNevtVtxCut, doubleRatioMinusOne, meanRatioVtxCutZ, ratioNevtVtxCutZ);
TNamed* settings = new TNamed(
Form("Settings: Data file \"%s\", lowerEta %.2f, uppEta %.2f, lowerCentrality %.3f, upperCentrality %.3f, doubleRatioMinusOne %.4f\n",
pathNameData.Data(), etaLow, etaUp, lowerCentrality, upperCentrality, doubleRatioMinusOne), "");
// Save results to file
TString saveFileName = pathNameData;
saveFileName = Form("%s_binZeroStudy.root", saveFileName.ReplaceAll(".root", "").Data());
TFile *saveFile = TFile::Open(saveFileName.Data(), "RECREATE");
saveFile->cd();
hSpectraTriggerSel->Write();
hSpectraTriggerSelVtxCut->Write();
hSpectraTriggerSelVtxCutZ->Write();
hSpectraTriggerSelVtxCutZPileUpRej->Write();
hRatioVtxCut->Write();
hRatioVtxCutZ->Write();
hRatioPileUp->Write();
funcRatioVtxCut->Write();
funcRatioVtxCutZ->Write();
canvSpectra->Write();
canvRatioVtx->Write();
canvRatioOther->Write();
settings->Write();
saveFile->Close();
TString temp = saveFileName;
canvRatioVtx->SaveAs(Form("%s", temp.ReplaceAll(".root", "_ratioVtx.pdf").Data()));
temp = saveFileName;
canvRatioOther->SaveAs(Form("%s", temp.ReplaceAll(".root", "_ratioOther.pdf").Data()));
PrintSettingsAxisRangeForMultiplicityAxisForMB();
return 0;
}
void RebinCFContainer(const char *infile="AnalysisResults.root",Int_t rebinVar=0, Int_t myEff=3, const char * name="Nch"){
gSystem->SetIncludePath("-I. -I$ALICE_ROOT -I$ALICE_ROOT/include -I$ALICE_PHYSICS -I$ALICE_PHYSICS/include -I$ALICE_ROOT/ITS -I$ALICE_ROOT/TPC -I$ALICE_ROOT/RAW -I$ALICE_ROOT/CONTAINERS -I$ALICE_ROOT/STEER/STEER -I$ALICE_ROOT/STEER/STEERBase -I$ALICE_ROOT/STEER/ESD -I$ALICE_ROOT/STEER/AOD -I$ALICE_ROOT/TRD -I$ALICE_ROOT/macros -I$ALICE_ROOT/ANALYSIS -I$ALICE_PHYSICS/PWGPP -g");
// gROOT->LoadMacro("AliSingleTrackEffCuts.cxx++g");
// gROOT->LoadMacro("AliCFSingleTrackEfficiencyTask.cxx++g");
gROOT->SetStyle("Plain");
gStyle->SetPalette(1);
gStyle->SetOptStat(0);
gStyle->SetPalette(1);
gStyle->SetCanvasColor(0);
gStyle->SetFrameFillColor(0);
gStyle->SetOptTitle(0);
TFile* file = TFile::Open(infile,"read");
TDirectoryFile *d = 0;
AliCFContainer *dataIni = 0;
d = (TDirectoryFile*)file->Get(Form("PWGPP_CFSingleTrack"));
if(!d) {
cout<<" no directory "<<endl;
return;
}
dataIni = (AliCFContainer*) (d->Get(Form("container%s",name)));
if(!dataIni){
cout <<" no container"<<endl;
}
//
// Do an slice of the container to make sure to remove outliers
//
const UInt_t ipt = 0;
const UInt_t ieta = 1;
const UInt_t iphi = 2;
const UInt_t itheta = 3;
const UInt_t izvtx = 4;
const UInt_t imult = 5;
const UInt_t icent = 6;
Int_t nvars = 7;
Int_t* ivarSlice = new Int_t[nvars];
ivarSlice[0]= ipt; ivarSlice[1] = ieta; ivarSlice[2] = iphi; ivarSlice[3] = itheta;
ivarSlice[4]= izvtx; ivarSlice[5] = imult; ivarSlice[6] = icent;
Double_t *mins = new Double_t[nvars];
Double_t *maxs = new Double_t[nvars];
mins[ipt] = ptmin; maxs[ipt] = ptmax;
mins[ieta] = etamin; maxs[ieta] = etamax;
mins[iphi] = phimin; maxs[iphi] = phimax;
mins[itheta] = thetamin; maxs[itheta] = thetamax;
mins[izvtx] = zvtxmin; maxs[izvtx] = zvtxmax;
mins[imult] = multmin; maxs[imult] = multmax;
mins[icent] = centmin; maxs[icent] = centmax;
AliCFContainer *data = (AliCFContainer*)dataIni->MakeSlice(nvars,ivarSlice,mins,maxs);
cout<< " ... slice done"<<endl;
cout<< " the new container has "<< data->GetNStep() << " steps"<<endl;
//
// *********** NUMERATOR
//
AliCFGridSparse* gridSparse = 0;
if( myEff == 1 ) gridSparse = (AliCFGridSparse*)data->GetGrid(1); // GenAcc
else if( myEff == 2 ) gridSparse = (AliCFGridSparse*)data->GetGrid(6); // Rec (acc + cuts) draw reco properties
else if( myEff == 3 ) gridSparse = (AliCFGridSparse*)data->GetGrid(7); // RecPID
else if( myEff == 4 ) gridSparse = (AliCFGridSparse*)data->GetGrid(3); // Rec (no cuts)
else if( myEff == 5 ) gridSparse = (AliCFGridSparse*)data->GetGrid(4); // RecAcc
else if( myEff == 6 ) gridSparse = (AliCFGridSparse*)data->GetGrid(5); // Rec (acc + cuts) draw kine properties
THnSparse* numData = (THnSparse*)gridSparse->GetGrid();
// method 2: defining a new THnSparse changing only the axis of interest
Printf("Method 2 ");
THnSparse* newnumData = (THnSparse*)numData->Clone("numNew");
newnumData->Reset();
Int_t nLimits=0;
Double_t* newLimits =0;
TString varname="";
if(rebinVar==0) {
varname="pt";
nLimits = 17;
newLimits = new Double_t[nLimits+1];
newLimits[0]=0;
newLimits[1]=0.25;
newLimits[2]=0.5;
newLimits[3]=0.75;
newLimits[4]=1;
newLimits[5]=1.5;
newLimits[6]=2;
newLimits[7]=2.5;
newLimits[8]=3;
newLimits[9]=4;
newLimits[10]=5;
newLimits[11]=6;
newLimits[12]=7;
newLimits[13]=8;
newLimits[14]=10;
newLimits[15]=12;
newLimits[16]=14;
newLimits[17]=16;
} else if (rebinVar==1) {
varname="eta";
nLimits = 9;
newLimits = new Double_t[nLimits+1];
newLimits[0]=-0.9;
newLimits[1]=-0.7;
newLimits[2]=-0.5;
newLimits[3]=-0.3;
newLimits[4]=-0.1;
newLimits[5]=0.1;
newLimits[6]=0.3;
newLimits[7]=0.5;
newLimits[8]=0.7;
newLimits[9]=0.9;
} else if (rebinVar==2) {
varname="phi";
nLimits = 9;
newLimits = new Double_t[nLimits+1];
for(Int_t i=0; i<=nLimits; i++) newLimits[i]=(Double_t)phimin + (phimax-phimin)/nLimits*(Double_t)i ;
}
const Int_t nnewLimits = nLimits;
TAxis* axis = (TAxis*)newnumData->GetAxis(rebinVar);
axis->Set(nnewLimits,newLimits);
newnumData->SetBinEdges(rebinVar,newLimits);
newnumData->RebinnedAdd(numData, 1);
// checking the bin contents
TH1D* h1 = (TH1D*)numData->Projection(rebinVar);
Float_t sum = 0;
Float_t sumnew = 0;
Printf("Original THnSparse");
for (Int_t ibin = 1; ibin<=h1->GetNbinsX(); ibin++){
Printf("ibin = %d, low edge = %f, content = %f",ibin,h1->GetBinLowEdge(ibin),h1->GetBinContent(ibin));
sum+=h1->GetBinContent(ibin);
}
Printf("THnSparse changing only one axis");
TH1D* h2num = (TH1D*)newnumData->Projection(rebinVar);
for (Int_t ibin = 1; ibin<=h2num->GetNbinsX(); ibin++){
Printf("ibin = %d, low edge = %f, content = %f",ibin,h2num->GetBinLowEdge(ibin),h2num->GetBinContent(ibin));
sumnew+=h2num->GetBinContent(ibin);
}
Printf("sum = %f, sumnew = %f",sum, sumnew);
//
// *********** DENOMINATOR RECPID
//
Printf("DENOMINATOR");
AliCFGridSparse* gridSparse2 = 0;
if( myEff == 1 ) gridSparse2 = (AliCFGridSparse*)data->GetGrid(0); // LimAcc
else gridSparse2 = (AliCFGridSparse*)data->GetGrid(1); // GenAcc
THnSparse* denData = (THnSparse*)gridSparse2->GetGrid();
// method 2: defining a new THnSparse changing only the axis of interest
Printf("Method 2 ");
THnSparse* newdenData = (THnSparse*)denData->Clone("denNew");
newdenData->Reset();
TAxis* axis2 = (TAxis*)newdenData->GetAxis(rebinVar);
axis2->Set(nnewLimits,newLimits);
newdenData->SetBinEdges(rebinVar,newLimits);
newdenData->RebinnedAdd(denData, 1);
// checking the bin contents
TH1D* h1d = (TH1D*)denData->Projection(rebinVar);
sum = 0;
sumnew = 0;
Printf("Original THnSparse");
for (Int_t ibin = 1; ibin<=h1d->GetNbinsX(); ibin++){
Printf("ibin = %d, low edge = %f, content = %f",ibin,h1d->GetBinLowEdge(ibin),h1d->GetBinContent(ibin));
sum+=h1d->GetBinContent(ibin);
}
Printf("THnSparse changing only one axis");
TH1D* h2 = (TH1D*)newdenData->Projection(rebinVar);
for (Int_t ibin = 1; ibin<=h2->GetNbinsX(); ibin++){
Printf("ibin = %d, low edge = %f, content = %f",ibin,h2->GetBinLowEdge(ibin),h2->GetBinContent(ibin));
sumnew+=h2->GetBinContent(ibin);
}
Printf("sum = %f, sumnew = %f",sum, sumnew);
TH1D* heff = (TH1D*)h2num->Clone("heff");
heff->Divide(h2num, h2,1,1,"B");
// heff->GetXaxis()->SetRangeUser(0,23.5);
TFile* fout = NULL;
if( myEff == 1 ) {
fout = new TFile(Form("efficiency_STE_GenAcc_over_LimAcc_rebinned_%d_%s.root",rebinVar,name),"RECREATE");
heff->Write(Form("h_%s_effCFLimAccGenAcc",varname.Data()));
h2num->Write(Form("h_%s_LimAcc",varname.Data()));
h2->Write(Form("h_%s_GenAcc",varname.Data()));
}
else if( myEff == 2 ) {
fout = new TFile(Form("efficiency_STE_RecPPR_over_GenAcc_rebinned_%d_%s.root",rebinVar,name),"RECREATE");
heff->Write(Form("h_%s_effCFRecPPRGenAcc",varname.Data()));
h2num->Write(Form("h_%s_RecPPR",varname.Data()));
h2->Write(Form("h_%s_GenAcc",varname.Data()));
}
else if( myEff == 3 ) {
fout = new TFile(Form("efficiency_STE_RecPID_over_GenAcc_rebinned_%d_%s.root",rebinVar,name),"RECREATE");
heff->Write(Form("h_%s_effCFRecPIDGenAcc",varname.Data()));
h2num->Write(Form("h_%s_RecPID",varname.Data()));
h2->Write(Form("h_%s_GenAcc",varname.Data()));
}
else if( myEff == 4 ) {
fout = new TFile(Form("efficiency_STE_Rec_over_GenAcc_rebinned_%d_%s.root",rebinVar,name),"RECREATE");
heff->Write(Form("h_%s_effCFRecGenAcc",varname.Data()));
h2num->Write(Form("h_%s_Rec",varname.Data()));
h2->Write(Form("h_%s_GenAcc",varname.Data()));
}
else if( myEff == 5 ) {
fout = new TFile(Form("efficiency_STE_RecAcc_over_GenAcc_rebinned_%d_%s.root",rebinVar,name),"RECREATE");
heff->Write(Form("h_%s_effCFRecAccGenAcc",varname.Data()));
h2num->Write(Form("h_%s_RecAcc",varname.Data()));
h2->Write(Form("h_%s_GenAcc",varname.Data()));
}
else if( myEff == 6 ) {
fout = new TFile(Form("efficiency_STE_RecPPRKine_over_GenAcc_rebinned_%d_%s.root",rebinVar,name),"RECREATE");
heff->Write(Form("h_%s_effCFRecPPRKineGenAcc",varname.Data()));
h2num->Write(Form("h_%s_RecPPRKine",varname.Data()));
h2->Write(Form("h_%s_GenAcc",varname.Data()));
}
fout->Close();
}