bool CreateTrainDir(AliAnalysisAlien *plugin, const TMap &lookup){
//
// Make train data dir name and JDL, C and sh file names
//
TObjArray infos;
bool found = FindDataSample(lookup, infos);
if(!found){
printf("sample %s not found\n", g_sample.Data());
return false;
}
TString type; GetData(infos, type, 2);
// check whether the train dir is already provided or needs to be specified
if(!g_train_dir.Length()){
// Query number of train runs before
const char *gridhome = gGrid->GetHomeDirectory();
const char gridoutdir[256];
sprintf(gridoutdir, "%sAnalysis_pPb/%s", gridhome, type.Data());
TGridResult *trainruns = gGrid->Ls(gridoutdir);
int nruns = trainruns->GetEntries();
// Get Date and time
TDatime time;
g_train_dir = Form("%d_%d%02d%02d_%02d%02d", nruns, time.GetYear(), time.GetMonth(), time.GetDay(), time.GetHour(), time.GetMinute());
}
plugin->SetGridWorkingDir(Form("Analysis_pPb/%s/%s", type.Data(), g_train_dir.Data()));
plugin->SetJDLName(Form("TPCTOFanalysispPb_%s_%s.jdl", type.Data(), g_train_dir.Data()));
plugin->SetExecutable(Form("TPCTOFanalysispPb_%s_%s.sh", type.Data(), g_train_dir.Data()));
plugin->SetAnalysisMacro(Form("TPCTOFanalysispPb_%s_%s.C", type.Data(), g_train_dir.Data()));
return true;
}
void TExpenser::calculate_balance() {
fBalanceXMLParser -> selectMainNode();
fBalanceXMLParser -> selectNode("entry");
TString balance = fBalanceXMLParser -> getNodeContent("amount");
fBalanceXMLParser -> selectNode("date");
TString balance_year = fBalanceXMLParser -> getNodeContent("year");
TString balance_month = fBalanceXMLParser -> getNodeContent("month");
fLastStatusLabel -> SetText(balance_month+"/"+balance_year+": " + balance + " eur");
// now calculate the current balance (last - expenses since the last)
TDatime time;
fXMLParser->selectMainNode();
fXMLParser->selectNode("expense");
Double_t expenses_since_last_status = 0;
while (fXMLParser->getCurrentNode() != 0) {
XMLNodePointer_t current_node = fXMLParser->getCurrentNode();
fXMLParser -> selectNode("date");
TString year = fXMLParser -> getNodeContent("year");
TString month = fXMLParser -> getNodeContent("month");
fXMLParser -> setCurrentNode(current_node);
bool year_more_recent = (year.Atoi() > balance_year.Atoi());
bool year_same = (year.Atoi() == balance_year.Atoi());
bool month_more_recent = (month.Atoi()>=balance_month.Atoi());
bool expense_more_recent_than_balance = (year_more_recent || (year_same && month_more_recent));
if ( expense_more_recent_than_balance && fXMLParser -> getNodeContent("withdrawn") == "Yes" ) {
expenses_since_last_status += fXMLParser -> getNodeContent("amount").Atof();
}
fXMLParser->selectNextNode("expense");
}
// calculate total income since last balance
fIncomeXMLParser->selectMainNode();
fIncomeXMLParser->selectNode("entry");
Double_t income_since_last_status = 0;
while (fIncomeXMLParser->getCurrentNode() != 0) {
XMLNodePointer_t current_node = fIncomeXMLParser->getCurrentNode();
fIncomeXMLParser -> selectNode("date");
TString year = fIncomeXMLParser -> getNodeContent("year");
TString month = fIncomeXMLParser -> getNodeContent("month");
fIncomeXMLParser -> setCurrentNode(current_node);
if ( ( (month.Atoi()>=balance_month.Atoi()) && (year.Atoi()==balance_year.Atoi()) ) || (year.Atoi()>balance_year.Atoi()) ) {
income_since_last_status += fIncomeXMLParser -> getNodeContent("amount").Atof();
}
fIncomeXMLParser->selectNextNode("entry");
}
Double_t new_balance = balance.Atof() - expenses_since_last_status + income_since_last_status;
fCurrentStatusLabel -> SetText(toStr(time.GetDay())+"/"+toStr(time.GetMonth())+"/"+toStr(time.GetYear())+": " + toStr(new_balance,2) + " eur");
}
void TExpenser::drawStatisticsMonthTab() {
fStatisticsTab = fTab->AddTab("Statistics (Month)");
fStatisticsTab -> SetLayoutManager(new TGHorizontalLayout(fStatisticsTab));
TRootEmbeddedCanvas * fEcanvas = new TRootEmbeddedCanvas("Ecanvas",fStatisticsTab, CANVAS_WIDTH, CANVAS_HEIGHT);
fStatisticsTab -> AddFrame(fEcanvas, new TGLayoutHints(kLHintsCenterX, 10,10,10,1));
fCanvas = fEcanvas->GetCanvas();
fCategoriesHistogram = new TH1F("fCategoriesHistogram", "Expenses for each category for a given month", NCATEGORIES, 0, NCATEGORIES);
fCategoriesHistogram -> SetStats(0);
TGVerticalFrame *vframe = new TGVerticalFrame(fStatisticsTab, 60, 40);
fStatisticsTab -> AddFrame(vframe, new TGLayoutHints(kLHintsCenterX,2,2,2,2));
// month selector
fStatisticsMonth = new TGComboBox(vframe);
for (unsigned i = 0; i < 12; i++) {
fStatisticsMonth->AddEntry(MONTHS[i], i+1);
}
fStatisticsMonth->Resize(DROPDOWN_MENU_WIDTH, DROPDOWN_MENU_HEIGHT);
TDatime time;
fStatisticsMonth->Select(time.GetMonth());
vframe->AddFrame(fStatisticsMonth, new TGLayoutHints(kLHintsLeft,5,10,5,5));
// year selector
fStatisticsYear = new TGComboBox(vframe);
for (unsigned i = FIRST_YEAR; i <= LAST_YEAR; i++) {
fStatisticsYear->AddEntry(toStr(i), i+1-FIRST_YEAR);
}
fStatisticsYear->Resize(DROPDOWN_MENU_WIDTH, DROPDOWN_MENU_HEIGHT);
fStatisticsYear->Select(time.GetYear()-FIRST_YEAR+1);
vframe->AddFrame(fStatisticsYear, new TGLayoutHints(kLHintsLeft,5,10,5,5));
// update-button
TGTextButton * update_button = new TGTextButton(vframe,"&Apply");
update_button -> SetFont("-*-times-bold-r-*-*-28-*-*-*-*-*-*-*");
update_button -> Connect("Clicked()", "TExpenser", this, "calculate_monthly()");
vframe -> AddFrame(update_button, new TGLayoutHints(kLHintsLeft,5,5,3,4));
// monthly sum
TColor *color = gROOT->GetColor(kBlue);
TGFont *font = gClient->GetFont("-*-times-bold-r-*-*-22-*-*-*-*-*-*-*");
fTotalMonthlyExpenses = new TGLabel(vframe, "");
vframe->AddFrame(fTotalMonthlyExpenses, new TGLayoutHints(kLHintsNormal, 5, 5, 3, 4));
fTotalMonthlyExpenses->SetTextColor(color);
fTotalMonthlyExpenses -> SetTextFont(font);
calculate_monthly();
}
//_________________________________________________________________________________________
Int_t checkPullTree(TString pathTree, TString pathNameThetaMap, TString pathNameSigmaMap,
TString mapSuffix, const Int_t collType /*0: pp, 1: pPb, 2: PbPb*/, const Bool_t plotPull = kTRUE,
const Double_t downScaleFactor = 1,
TString pathNameSplinesFile = "", TString prSplinesName = "",
TString fileNameTree = "bhess_PIDetaTree.root", TString treeName = "fTree")
{
const Bool_t isNonPP = collType != 0;
const Double_t massProton = AliPID::ParticleMass(AliPID::kProton);
Bool_t recalculateExpecteddEdx = pathNameSplinesFile != "";
TFile* f = 0x0;
f = TFile::Open(Form("%s/%s", pathTree.Data(), fileNameTree.Data()));
if (!f) {
std::cout << "Failed to open tree file \"" << Form("%s/%s", pathTree.Data(), fileNameTree.Data()) << "\"!" << std::endl;
return -1;
}
// Extract the data Tree
TTree* tree = dynamic_cast<TTree*>(f->Get(treeName.Data()));
if (!tree) {
std::cout << "Failed to load data tree!" << std::endl;
return -1;
}
// Extract the splines, if desired
TSpline3* splPr = 0x0;
if (recalculateExpecteddEdx) {
std::cout << "Loading splines to recalculate expected dEdx!" << std::endl << std::endl;
TFile* fSpl = TFile::Open(pathNameSplinesFile.Data());
if (!fSpl) {
std::cout << "Failed to open spline file \"" << pathNameSplinesFile.Data() << "\"!" << std::endl;
return 0x0;
}
TObjArray* TPCPIDResponse = (TObjArray*)fSpl->Get("TPCPIDResponse");
if (!TPCPIDResponse) {
splPr = (TSpline3*)fSpl->Get(prSplinesName.Data());
// If splines are in file directly, without TPCPIDResponse object, try to load them
if (!splPr) {
std::cout << "Failed to load object array from spline file \"" << pathNameSplinesFile.Data() << "\"!" << std::endl;
return 0x0;
}
}
else {
splPr = (TSpline3*)TPCPIDResponse->FindObject(prSplinesName.Data());
if (!splPr) {
std::cout << "Failed to load splines from file \"" << pathNameSplinesFile.Data() << "\"!" << std::endl;
return 0x0;
}
}
}
else
std::cout << "Taking dEdxExpected from Tree..." << std::endl << std::endl;
// Extract the correction maps
TFile* fMap = TFile::Open(pathNameThetaMap.Data());
if (!fMap) {
std::cout << "Failed to open thetaMap file \"" << pathNameThetaMap.Data() << "\"! Will not additionally correct data...." << std::endl;
}
TH2D* hMap = 0x0;
if (fMap) {
hMap = dynamic_cast<TH2D*>(fMap->Get(Form("hRefined%s", mapSuffix.Data())));
if (!hMap) {
std::cout << "Failed to load theta map!" << std::endl;
return -1;
}
}
TFile* fSigmaMap = TFile::Open(pathNameSigmaMap.Data());
if (!fSigmaMap) {
std::cout << "Failed to open simgaMap file \"" << pathNameSigmaMap.Data() << "\"!" << std::endl;
return -1;
}
TH2D* hThetaMapSigmaPar1 = dynamic_cast<TH2D*>(fSigmaMap->Get("hThetaMapSigmaPar1"));
if (!hThetaMapSigmaPar1) {
std::cout << "Failed to load sigma map for par 1!" << std::endl;
return -1;
}
Double_t c0 = -1;
TNamed* c0Info = dynamic_cast<TNamed*>(fSigmaMap->Get("c0"));
if (!c0Info) {
std::cout << "Failed to extract c0 from file with sigma map!" << std::endl;
return -1;
}
TString c0String = c0Info->GetTitle();
c0 = c0String.Atof();
printf("Loaded parameter 0 for sigma: %f\n\n", c0);
if (plotPull)
std::cout << "Plotting pull..." << std::endl << std::endl;
else
std::cout << "Plotting delta'..." << std::endl << std::endl;
Long64_t nTreeEntries = tree->GetEntriesFast();
Double_t dEdx = 0.; // Measured dE/dx
Double_t dEdxExpected = 0.; // Expected dE/dx according to parametrisation
Double_t tanTheta = 0.; // Tangens of (local) theta at TPC inner wall
Double_t pTPC = 0.; // Momentum at TPC inner wall
UShort_t tpcSignalN = 0; // Number of clusters used for dEdx
UChar_t pidType = 0;
Int_t fMultiplicity = 0;
//Double_t phiPrime = 0;
// Only activate the branches of interest to save processing time
tree->SetBranchStatus("*", 0); // Disable all branches
tree->SetBranchStatus("pTPC", 1);
tree->SetBranchStatus("dEdx", 1);
tree->SetBranchStatus("dEdxExpected", 1);
tree->SetBranchStatus("tanTheta", 1);
tree->SetBranchStatus("tpcSignalN", 1);
tree->SetBranchStatus("pidType", 1);
//tree->SetBranchStatus("phiPrime", 1);
if (isNonPP)
tree->SetBranchStatus("fMultiplicity", 1);
tree->SetBranchAddress("dEdx", &dEdx);
tree->SetBranchAddress("dEdxExpected", &dEdxExpected);
tree->SetBranchAddress("tanTheta", &tanTheta);
tree->SetBranchAddress("tpcSignalN", &tpcSignalN);
tree->SetBranchAddress("pTPC", &pTPC);
tree->SetBranchAddress("pidType", &pidType);
//tree->SetBranchAddress("phiPrime", &phiPrime);
if (isNonPP)
tree->SetBranchAddress("fMultiplicity", &fMultiplicity);
// Output file
TDatime daTime;
TString savefileName = Form("%s%s_checkPullSigma_%04d_%02d_%02d__%02d_%02d.root", fileNameTree.ReplaceAll(".root", "").Data(),
recalculateExpecteddEdx ? "_recalcdEdx" : "",
daTime.GetYear(), daTime.GetMonth(), daTime.GetDay(), daTime.GetHour(), daTime.GetMinute());
TFile* fSave = TFile::Open(Form("%s/%s", pathTree.Data(), savefileName.Data()), "recreate");
if (!fSave) {
std::cout << "Failed to open save file \"" << Form("%s/%s", pathTree.Data(), savefileName.Data()) << "\"!" << std::endl;
return -1;
}
const Double_t pBoundLow = 0.1;
const Double_t pBoundUp = 5;
const Int_t nBins1 = TMath::Ceil(180 / downScaleFactor);
const Int_t nBins2 = TMath::Ceil(100 / downScaleFactor);
const Int_t nBins3 = TMath::Ceil(60 / downScaleFactor);
const Int_t nPbinsForMap = nBins1 + nBins2 + nBins3;
Double_t binsPforMap[nPbinsForMap + 1];
Double_t binWidth1 = (1.0 - pBoundLow) / nBins1;
Double_t binWidth2 = (2.0 - 1.0 ) / nBins2;
Double_t binWidth3 = (pBoundUp - 2.0) / nBins3;
for (Int_t i = 0; i < nBins1; i++) {
binsPforMap[i] = pBoundLow + i * binWidth1;
}
for (Int_t i = nBins1, j = 0; i < nBins1 + nBins2; i++, j++) {
binsPforMap[i] = 1.0 + j * binWidth2;
}
for (Int_t i = nBins1 + nBins2, j = 0; i < nBins1 + nBins2 + nBins3; i++, j++) {
binsPforMap[i] = 2.0 + j * binWidth3;
}
binsPforMap[nPbinsForMap] = pBoundUp;
TH2D* hPull = new TH2D("hPull", "Pull vs. p_{TPC} integrated over tan(#Theta);p_{TPC} (GeV/c);Pull", nPbinsForMap, binsPforMap,
plotPull ? 120 : 240, plotPull ? -6 : -0.6, plotPull ? 6 : 0.6);
TH2D* hPullAdditionalCorr = (TH2D*)hPull->Clone("hPullAdditionalCorr");
hPullAdditionalCorr->SetTitle("Pull vs. p_{TPC} integrated over tan(#Theta) with additional dEdx correction w.r.t. tan(#Theta)");
/*
const Int_t nThetaHistos = 3;
TH2D* hPullTheta[nThetaHistos];
TH2D* hPullAdditionalCorrTheta[nThetaHistos];
Double_t tThetaLow[nThetaHistos] = { 0.0, 0.4, 0.9 };
Double_t tThetaHigh[nThetaHistos] = { 0.1, 0.5, 1.0 };
*/
const Int_t nThetaHistos = 10;
TH2D* hPullTheta[nThetaHistos];
TH2D* hPullAdditionalCorrTheta[nThetaHistos];
Double_t tThetaLow[nThetaHistos] = { 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 };
Double_t tThetaHigh[nThetaHistos] = { 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0 };
for (Int_t i = 0; i < nThetaHistos; i++) {
hPullTheta[i] = new TH2D(Form("hPullTheta_%d", i),
Form("Pull vs. p_{TPC} for %.2f <= |tan(#Theta)| < %.2f;p_{TPC} (GeV/c);Pull", tThetaLow[i], tThetaHigh[i]),
nPbinsForMap, binsPforMap, plotPull ? 120 : 240, plotPull ? -6 : -0.6, plotPull ? 6 : 0.6);
hPullAdditionalCorrTheta[i] =
new TH2D(Form("hPullAdditionalCorrTheta_%d", i),
Form("Pull vs. p_{TPC} for %.2f <= |tan(#Theta)| < %.2f with additional dEdx correction w.r.t. tan(#Theta);p_{TPC} (GeV/c);Pull",
tThetaLow[i], tThetaHigh[i]),
nPbinsForMap, binsPforMap, plotPull ? 120 : 240, plotPull ? -6 : -0.6, plotPull ? 6 : 0.6);
}
TF1 corrFuncMult("corrFuncMult", "[0] + [1]*TMath::Max([4], TMath::Min(x, [3])) + [2] * TMath::Power(TMath::Max([4], TMath::Min(x, [3])), 2)",
0., 0.2);
TF1 corrFuncMultTanTheta("corrFuncMultTanTheta", "[0] * (x -[2]) + [1] * (x * x - [2] * [2])", -1.5, 1.5);
TF1 corrFuncSigmaMult("corrFuncSigmaMul", "TMath::Max(0, [0] + [1]*TMath::Min(x, [3]) + [2] * TMath::Power(TMath::Min(x, [3]), 2))", 0., 0.2);
// LHC13b.pass2
if (isNonPP)
printf("Using corr Parameters for 13b.pass2\n!");
corrFuncMult.SetParameter(0, -5.906e-06);
corrFuncMult.SetParameter(1, -5.064e-04);
corrFuncMult.SetParameter(2, -3.521e-02);
corrFuncMult.SetParameter(3, 2.469e-02);
corrFuncMult.SetParameter(4, 0);
corrFuncMultTanTheta.SetParameter(0, -5.32e-06);
corrFuncMultTanTheta.SetParameter(1, 1.177e-05);
corrFuncMultTanTheta.SetParameter(2, -0.5);
corrFuncSigmaMult.SetParameter(0, 0.);
corrFuncSigmaMult.SetParameter(1, 0.);
corrFuncSigmaMult.SetParameter(2, 0.);
corrFuncSigmaMult.SetParameter(3, 0.);
/* OK, but PID task was not very satisfying
corrFuncMult.SetParameter(0, -6.27187e-06);
corrFuncMult.SetParameter(1, -4.60649e-04);
corrFuncMult.SetParameter(2, -4.26450e-02);
corrFuncMult.SetParameter(3, 2.40590e-02);
corrFuncMult.SetParameter(4, 0);
corrFuncMultTanTheta.SetParameter(0, -5.338e-06);
corrFuncMultTanTheta.SetParameter(1, 1.220e-05);
corrFuncMultTanTheta.SetParameter(2, -0.5);
corrFuncSigmaMult.SetParameter(0, 7.89237e-05);
corrFuncSigmaMult.SetParameter(1, -1.30662e-02);
corrFuncSigmaMult.SetParameter(2, 8.91548e-01);
corrFuncSigmaMult.SetParameter(3, 1.47931e-02);
*/
/*
// LHC11a10a
if (isNonPP)
printf("Using corr Parameters for 11a10a\n!");
corrFuncMult.SetParameter(0, 6.90133e-06);
corrFuncMult.SetParameter(1, -1.22123e-03);
corrFuncMult.SetParameter(2, 1.80220e-02);
corrFuncMult.SetParameter(3, 0.1);
corrFuncMult.SetParameter(4, 6.45306e-03);
corrFuncMultTanTheta.SetParameter(0, -2.85505e-07);
corrFuncMultTanTheta.SetParameter(1, -1.31911e-06);
corrFuncMultTanTheta.SetParameter(2, -0.5);
corrFuncSigmaMult.SetParameter(0, -4.29665e-05);
corrFuncSigmaMult.SetParameter(1, 1.37023e-02);
corrFuncSigmaMult.SetParameter(2, -6.36337e-01);
corrFuncSigmaMult.SetParameter(3, 1.13479e-02);
*/
/* OLD without saturation and large error for negative slopes
corrFuncSigmaMult.SetParameter(0, -4.79684e-05);
corrFuncSigmaMult.SetParameter(1, 1.49938e-02);
corrFuncSigmaMult.SetParameter(2, -7.15269e-01);
corrFuncSigmaMult.SetParameter(3, 1.06855e-02);
*/
/* OLD very good try, but with fewer pBins for the fitting
corrFuncMult.SetParameter(0, 6.88365e-06);
corrFuncMult.SetParameter(1, -1.22324e-03);
corrFuncMult.SetParameter(2, 1.81625e-02);
corrFuncMult.SetParameter(3, 0.1);
corrFuncMult.SetParameter(4, 6.36890e-03);
corrFuncMultTanTheta.SetParameter(0, -2.85505e-07);
corrFuncMultTanTheta.SetParameter(1, -1.31911e-06);
corrFuncMultTanTheta.SetParameter(2, -0.5);
corrFuncSigmaMult.SetParameter(0, -4.28401e-05);
corrFuncSigmaMult.SetParameter(1, 1.24812e-02);
corrFuncSigmaMult.SetParameter(2, -5.28531e-01);
corrFuncSigmaMult.SetParameter(3, 1.25147e-02);
*/
/*OLD good try
corrFuncMult.SetParameter(0, 7.50321e-06);
corrFuncMult.SetParameter(1, -1.25250e-03);
corrFuncMult.SetParameter(2, 1.85437e-02);
corrFuncMult.SetParameter(3, 0.1);
corrFuncMult.SetParameter(4, 6.21192e-03);
corrFuncMultTanTheta.SetParameter(0, -1.43112e-07);
corrFuncMultTanTheta.SetParameter(1, -1.53e-06);
corrFuncMultTanTheta.SetParameter(2, 0.3);
corrFuncSigmaMult.SetParameter(0, -2.54019e-05);
corrFuncSigmaMult.SetParameter(1, 8.68883e-03);
corrFuncSigmaMult.SetParameter(2, -3.36176e-01);
corrFuncSigmaMult.SetParameter(3, 1.29230e-02);
*/
/*
// LHC10h.pass2
if (isNonPP)
printf("Using corr Parameters for 10h.pass2\n!");
corrFuncMult.SetParameter(0, 3.21636e-07);
corrFuncMult.SetParameter(1, -6.65876e-04);
corrFuncMult.SetParameter(2, 1.28786e-03);
corrFuncMult.SetParameter(3, 1.47677e-02);
corrFuncMult.SetParameter(4, 0.);
corrFuncMultTanTheta.SetParameter(0, 7.23591e-08);
corrFuncMultTanTheta.SetParameter(1, 2.7469e-06);
corrFuncMultTanTheta.SetParameter(2, -0.5);
corrFuncSigmaMult.SetParameter(0, -1.22590e-05);
corrFuncSigmaMult.SetParameter(1, 6.88888e-03);
corrFuncSigmaMult.SetParameter(2, -3.20788e-01);
corrFuncSigmaMult.SetParameter(3, 1.07345e-02);
*/
/*OLD bad try
corrFuncMult.SetParameter(0, 2.71514e-07);
corrFuncMult.SetParameter(1, -6.92031e-04);
corrFuncMult.SetParameter(2, 3.56042e-03);
corrFuncMult.SetParameter(3, 1.47497e-02);
corrFuncMult.SetParameter(4, 0.);
corrFuncMultTanTheta.SetParameter(0, 8.53204e-08);
corrFuncMultTanTheta.SetParameter(1, 2.85591e-06);
corrFuncMultTanTheta.SetParameter(2, -0.5);
corrFuncSigmaMult.SetParameter(0, -6.82477e-06);
corrFuncSigmaMult.SetParameter(1, 4.97051e-03);
corrFuncSigmaMult.SetParameter(2, -1.64954e-01);
corrFuncSigmaMult.SetParameter(3, 9.21061e-03);
*/
//TODO NOW
TF1* fShapeSmallP = new TF1("fShapeSmallP", "pol5", -0.4, 0.4);
fShapeSmallP->SetParameters(1.01712, -0.0202725, -0.260692, 0.261623, 0.671854, -1.14014);
for (Long64_t i = 0; i < nTreeEntries; i++) {
tree->GetEntry(i);
if (dEdx <= 0 || dEdxExpected <= 0 || tpcSignalN <= 10)
continue;
/*
Double_t pT = pTPC*TMath::Sin(-TMath::ATan(tanTheta)+TMath::Pi()/2.0);
if ((phiPrime > 0.072/pT+TMath::Pi()/18.0-0.035 && phiPrime < 0.07/pT/pT+0.1/pT+TMath::Pi()/18.0+0.035))
continue;
*/
if (pidType != kMCid) {
if (pidType == kTPCid && pTPC > 0.6)
continue;
if (pidType == kTPCandTOFid && (pTPC < 0.6 || pTPC > 2.0))
continue;
if ((collType == 2) && pidType == kTPCandTOFid && pTPC > 1.0)
continue;// Only V0's in case of PbPb above 1.0 GeV/c
if (pidType == kV0idPlusTOFrejected) //TODO NOW NEW
continue;
}
if (recalculateExpecteddEdx) {
dEdxExpected = 50. * splPr->Eval(pTPC / massProton); //WARNING: What, if MIP is different from 50.? Seems not to be used (tested for pp, MC_pp, PbPb and MC_PbPb), but can in principle happen
}
//TODO NOW
/*
if (TMath::Abs(tanTheta) <= 0.4) {
Double_t p0 = fShapeSmallP->Eval(tanTheta) - 1.0; // Strength of the correction
Double_t p1 = -9.0; // How fast the correction is turned off
Double_t p2 = -0.209; // Turn off correction around 0.2 GeV/c
Double_t p3 = 1.0; // Delta' for large p should be 1
Double_t corrFactor = TMath::Erf((pTPC + p2) * p1) * p0 + p3 + p0; // Add p0 to have 1 for p3 = 1 and large pTPC
dEdxExpected *= corrFactor;
}*/
/*TODO old unsuccessful try
Double_t thetaGlobalTPC = -TMath::ATan(tanTheta) + TMath::Pi() / 2.;
Double_t pTtpc = pTPC * TMath::Sin(thetaGlobalTPC);
Double_t pTtpcInv = (pTtpc > 0) ? 1. / pTtpc : 0;
Double_t p0 = 1.0;
Double_t p1 = 1./ 0.5;//TODO 2.0;
Double_t p2 = -0.2;//TODO 0.1
Double_t pTcorrFactor = p0 + (pTtpcInv > p1) * p2 * (pTtpcInv - p1);
dEdxExpected *= pTcorrFactor;
*/
// From the momentum (via dEdxExpected) and the tanTheta of the track, the expected dEdx can be calculated (correctedDeDxExpected).
// If the splines are correct, this should give in average the same value as dEdx.
// Now valid: Maps created from corrected data with splines adopted to corrected data, so lookup should be for dEdxExpected=dEdxSplines (no further
// eta correction) or the corrected dEdx from the track (which should ideally be = dEdxSplines)
// Tested with corrected data for LHC10d.pass2: using dEdx for the lookup (which is the corrected value and should ideally be = dEdxSplines):
// Results almost the same. Maybe slightly better for dEdxExpected.
// No longer valid: Note that the maps take always the uncorrected dEdx w.r.t.
// tanTheta, so that correctedDeDxExpected is needed here normally. However, the information for the correction will be lost at some point.
// Therefore, dEdxExpected can be used instead and should provide a good approximation.
Double_t c1FromSigmaMap = hThetaMapSigmaPar1->GetBinContent(getBinX(hThetaMapSigmaPar1, tanTheta), getBinY(hThetaMapSigmaPar1, 1./dEdxExpected));
Double_t expectedSigma = dEdxExpected * TMath::Sqrt( c0 * c0 + (c1FromSigmaMap * c1FromSigmaMap) / tpcSignalN);
Double_t pull = (dEdx - dEdxExpected) / (plotPull ? expectedSigma: dEdxExpected);
// Fill pull histo
hPull->Fill(pTPC, pull);
Double_t tanThetaAbs = TMath::Abs(tanTheta);
for (Int_t j = 0; j < nThetaHistos; j++) {
if (tanThetaAbs >= tThetaLow[j] && tanThetaAbs < tThetaHigh[j]) {
hPullTheta[j]->Fill(pTPC, pull);
}
}
if (!hMap)
continue;
Double_t correctionFactor = 1.;
if (isNonPP) {
// 1. Correct eta dependence
correctionFactor = hMap->GetBinContent(getBinX(hMap, tanTheta), getBinY(hMap, 1./dEdxExpected));
// 2. Correct for multiplicity dependence:
Double_t multCorrectionFactor = 1.;
if (fMultiplicity > 0) {
Double_t relSlope = corrFuncMult.Eval(1. / (dEdxExpected * correctionFactor));
relSlope += corrFuncMultTanTheta.Eval(tanTheta);
multCorrectionFactor = 1. + relSlope * fMultiplicity;
}
c1FromSigmaMap = hThetaMapSigmaPar1->GetBinContent(getBinX(hThetaMapSigmaPar1, tanTheta), getBinY(hThetaMapSigmaPar1, 1./dEdxExpected));
// Multiplicity dependence of sigma depends on the real dEdx at zero multiplicity, i.e. the eta (only) corrected dEdxExpected value has to be used
// since all maps etc. have been created for ~zero multiplicity
Double_t relSigmaSlope = corrFuncSigmaMult.Eval(1. / (dEdxExpected * correctionFactor));
Double_t multSigmaCorrectionFactor = 1. + relSigmaSlope * fMultiplicity;
dEdxExpected *= correctionFactor * multCorrectionFactor;
expectedSigma = dEdxExpected * TMath::Sqrt( c0 * c0 + (c1FromSigmaMap * c1FromSigmaMap) / tpcSignalN);
expectedSigma *= multSigmaCorrectionFactor;
pull = (dEdx - dEdxExpected) / (plotPull ? expectedSigma: dEdxExpected);
}
else {
correctionFactor = hMap->GetBinContent(getBinX(hMap, tanTheta), getBinY(hMap, 1./dEdxExpected));
c1FromSigmaMap = hThetaMapSigmaPar1->GetBinContent(getBinX(hThetaMapSigmaPar1, tanTheta), getBinY(hThetaMapSigmaPar1, 1./dEdxExpected));
dEdxExpected *= correctionFactor; // If data is not corrected, but the sigma map is for corrected data, re-do analysis with corrected dEdx
expectedSigma = dEdxExpected * TMath::Sqrt( c0 * c0 + (c1FromSigmaMap * c1FromSigmaMap) / tpcSignalN);
pull = (dEdx - dEdxExpected) / (plotPull ? expectedSigma: dEdxExpected);
}
pull = (dEdx - dEdxExpected) / (plotPull ? expectedSigma: dEdxExpected);
hPullAdditionalCorr->Fill(pTPC, pull);
for (Int_t j = 0; j < nThetaHistos; j++) {
if (tanThetaAbs >= tThetaLow[j] && tanThetaAbs < tThetaHigh[j]) {
hPullAdditionalCorrTheta[j]->Fill(pTPC, pull);
}
}
}
/*
// Mean, Sigma, chi^2/NDF of pull of different theta bins and all in one plot
TCanvas* canvPullMean = new TCanvas("canvPullMean", "canvPullMean", 100,10,1380,800);
canvPullMean->SetLogx(kTRUE);
canvPullMean->SetGridx(kTRUE);
canvPullMean->SetGridy(kTRUE);
TCanvas* canvPullSigma = new TCanvas("canvPullSigma", "canvPullSigma", 100,10,1380,800);
canvPullSigma->SetLogx(kTRUE);
canvPullSigma->SetGridx(kTRUE);
canvPullSigma->SetGridy(kTRUE);
TCanvas* canvPullChi2 = new TCanvas("canvPullChi2", "canvPullChi2", 100,10,1380,800);
canvPullChi2->SetLogx(kTRUE);
canvPullChi2->SetGridx(kTRUE);
canvPullChi2->SetGridy(kTRUE);
TCanvas* canvPull[nThetaHistos + 1];
for (Int_t i = 0, j = nThetaHistos; i < nThetaHistos + 1; i++, j--) {
canvPull[i] = new TCanvas(Form("canvPull_%d", i), "canvPull", 100,10,1380,800);
canvPull[i]->cd();
canvPull[i]->SetLogx(kTRUE);
canvPull[i]->SetLogz(kTRUE);
canvPull[i]->SetGrid(kTRUE, kTRUE);
TH2D* hTemp = 0x0;
TString thetaString = "";
if (i == nThetaHistos) {
hTemp = hPull;
thetaString = "tan(#Theta) integrated";
}
else {
hTemp = hPullTheta[i];
thetaString = Form("%.2f #leq |tan(#Theta)| < %.2f", tThetaLow[i], tThetaHigh[i]);
}
normaliseHisto(hTemp);
hTemp->FitSlicesY();
hTemp->GetYaxis()->SetNdivisions(12);
hTemp->GetXaxis()->SetMoreLogLabels(kTRUE);
TH1D* hTempMean = (TH1D*)gDirectory->Get(Form("%s_1", hTemp->GetName()));
hTempMean->SetTitle(Form("mean(pull), %s", thetaString.Data()));
hTempMean->GetXaxis()->SetMoreLogLabels(kTRUE);
hTempMean->SetLineWidth(2);
hTempMean->SetMarkerStyle(20);
TH1D* hTempSigma = (TH1D*)gDirectory->Get(Form("%s_2", hTemp->GetName()));
hTempSigma->SetTitle(Form("#sigma(pull), %s", thetaString.Data()));
hTempSigma->GetXaxis()->SetMoreLogLabels(kTRUE);
hTempSigma->SetLineColor(kMagenta);
hTempSigma->SetMarkerStyle(20);
hTempSigma->SetMarkerColor(kMagenta);
hTempSigma->SetLineWidth(2);
TH1D* hTempChi2 = (TH1D*)gDirectory->Get(Form("%s_chi2", hTemp->GetName()));
hTempChi2->SetTitle(Form("#chi^{2} / NDF (pull), %s", thetaString.Data()));
hTempChi2->GetXaxis()->SetMoreLogLabels(kTRUE);
hTempChi2->SetLineColor(kMagenta + 2);
hTempChi2->SetMarkerStyle(20);
hTempChi2->SetMarkerColor(kMagenta + 2);
hTempChi2->SetLineWidth(2);
hTemp->DrawCopy("colz");
hTempMean->DrawCopy("same");
hTempSigma->DrawCopy("same");
hTempChi2->Scale(-1./10.);
hTempChi2->DrawCopy("same");
hTempChi2->Scale(-10.);
canvPullMean->cd();
hTempMean->SetLineColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempMean->SetMarkerColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempMean->DrawCopy((i == 0 ? "" : "same"));
canvPullSigma->cd();
hTempSigma->SetLineColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempSigma->SetMarkerColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempSigma->DrawCopy((i == 0 ? "" : "same"));
canvPullChi2->cd();
hTempChi2->SetLineColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempChi2->SetMarkerColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempChi2->DrawCopy((i == 0 ? "" : "same"));
}
canvPullMean->BuildLegend();
canvPullSigma->BuildLegend();
canvPullChi2->BuildLegend();
*/
// Histograms with additional correction
TCanvas* canvPullMeanCorr = 0x0;
TCanvas* canvPullSigmaCorr = 0x0;
TCanvas* canvPullChi2Corr = 0x0;
TCanvas* canvPullCorr[nThetaHistos + 1];
for (Int_t i = 0; i < nThetaHistos + 1; i++)
canvPullCorr[i] = 0x0;
if (hMap) {
// Mean, Sigma, chi^2/NDF of pull of different theta bins and all in one plot
canvPullMeanCorr = new TCanvas("canvPullMeanCorr", "canvPullMeanCorr", 100,10,1380,800);
canvPullMeanCorr->SetLogx(kTRUE);
canvPullMeanCorr->SetGridx(kTRUE);
canvPullMeanCorr->SetGridy(kTRUE);
canvPullSigmaCorr = new TCanvas("canvPullSigmaCorr", "canvPullSigmaCorr", 100,10,1380,800);
canvPullSigmaCorr->SetLogx(kTRUE);
canvPullSigmaCorr->SetGridx(kTRUE);
canvPullSigmaCorr->SetGridy(kTRUE);
canvPullChi2Corr = new TCanvas("canvPullChi2Corr", "canvPullChi2Corr", 100,10,1380,800);
canvPullChi2Corr->SetLogx(kTRUE);
canvPullChi2Corr->SetGridx(kTRUE);
canvPullChi2Corr->SetGridy(kTRUE);
for (Int_t i = 0, j = nThetaHistos; i < nThetaHistos + 1; i++, j--) {
canvPullCorr[i] = new TCanvas(Form("canvPullCorr_%d", i), "canvPullCorr", 100,10,1380,800);
canvPullCorr[i]->cd();
canvPullCorr[i]->SetLogx(kTRUE);
canvPullCorr[i]->SetLogz(kTRUE);
canvPullCorr[i]->SetGrid(kTRUE, kTRUE);
TH2D* hTemp = 0x0;
TString thetaString = "";
if (i == nThetaHistos) {
hTemp = hPullAdditionalCorr;
thetaString = "tan(#Theta) integrated";
}
else {
hTemp = hPullAdditionalCorrTheta[i];
thetaString = Form("%.2f #leq |tan(#Theta)| < %.2f", tThetaLow[i], tThetaHigh[i]);
}
normaliseHisto(hTemp);
hTemp->FitSlicesY();
hTemp->GetYaxis()->SetNdivisions(12);
hTemp->GetXaxis()->SetMoreLogLabels(kTRUE);
TH1D* hTempMean = (TH1D*)gDirectory->Get(Form("%s_1", hTemp->GetName()));
hTempMean->SetTitle(Form("mean(pull), %s", thetaString.Data()));
hTempMean->GetXaxis()->SetMoreLogLabels(kTRUE);
hTempMean->SetLineWidth(2);
hTempMean->SetMarkerStyle(20);
TH1D* hTempSigma = (TH1D*)gDirectory->Get(Form("%s_2", hTemp->GetName()));
hTempSigma->SetTitle(Form("#sigma(pull), %s", thetaString.Data()));
hTempSigma->GetXaxis()->SetMoreLogLabels(kTRUE);
hTempSigma->SetLineColor(kMagenta);
hTempSigma->SetMarkerStyle(20);
hTempSigma->SetMarkerColor(kMagenta);
hTempSigma->SetLineWidth(2);
TH1D* hTempChi2 = (TH1D*)gDirectory->Get(Form("%s_chi2", hTemp->GetName()));
hTempChi2->SetTitle(Form("#chi^{2} / NDF (pull), %s", thetaString.Data()));
hTempChi2->GetXaxis()->SetMoreLogLabels(kTRUE);
hTempChi2->SetLineColor(kMagenta + 2);
hTempChi2->SetMarkerStyle(20);
hTempChi2->SetMarkerColor(kMagenta + 2);
hTempChi2->SetLineWidth(2);
hTemp->DrawCopy("colz");
hTempMean->DrawCopy("same");
hTempSigma->DrawCopy("same");
hTempChi2->Scale(-1./10.);
hTempChi2->DrawCopy("same");
hTempChi2->Scale(-10.);
canvPullMeanCorr->cd();
hTempMean->SetLineColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempMean->SetMarkerColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempMean->DrawCopy((i == 0 ? "" : "same"));
canvPullSigmaCorr->cd();
hTempSigma->SetLineColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempSigma->SetMarkerColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempSigma->DrawCopy((i == 0 ? "" : "same"));
canvPullChi2Corr->cd();
hTempChi2->SetLineColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempChi2->SetMarkerColor(1 + ((j >= 9) ? (39 + 2 * (j - 9)) : j));
hTempChi2->DrawCopy((i == 0 ? "" : "same"));
}
canvPullMeanCorr->BuildLegend();
canvPullSigmaCorr->BuildLegend();
canvPullChi2Corr->BuildLegend();
}
fSave->cd();
/*canvPullMean->Write();
canvPullSigma->Write();
canvPullChi2->Write();
for (Int_t i = 0; i < nThetaHistos + 1; i++) {
canvPull[i]->Write();
}*/
canvPullMeanCorr->Write();
canvPullSigmaCorr->Write();
canvPullChi2Corr->Write();
for (Int_t i = 0; i < nThetaHistos + 1; i++) {
canvPullCorr[i]->Write();
}
TNamed* info = new TNamed(Form("Theta map: %s\n\nSigma map: %s\n\nSplines file: %s\n\nSplines name: %s", pathNameThetaMap.Data(),
pathNameSigmaMap.Data(), pathNameSplinesFile.Data(), prSplinesName.Data()),
"info");
info->Write();
fSave->Close();
return 0;
}
//____________________________________________________________
void AverageDmesonRaa( const char* fD0Raa="", const char* fD0ppRef="",
const char* fDplusRaa="", const char* fDplusppRef="",
const char* fDstarRaa="", const char* fDstarppRef="",
const char* outfile="", Int_t averageOption=kRelativeStatUnc, Int_t cc=kpPb0100, Int_t ccestimator=kV0M,
Bool_t isReadAllPPUnc=false, Bool_t isPPRefExtrapD0=false, Bool_t isPPRefExtrapDplus=false, Bool_t isPPRefExtrapDstar=false)
{
FILE *resultFile;
TString foutname = "Average";
if(fD0Raa) foutname += "Dzero";
if(fDplusRaa) foutname += "Dplus";
if(fDstarRaa) foutname += "Dstar";
if(averageOption==kRelativeStatUnc) foutname+= "_RelStatUncWeight";
else if(averageOption==kAbsoluteStatUnc) foutname+= "_AbsStatUncWeight";
else if(averageOption==kRelativeStatUncorrWoPidSyst) foutname+= "_RelStatUncorrWeight";
else if(averageOption==kRelativeStatRawYieldSyst) foutname+= "_RelStatRawYieldSystWeight";
if(!useExtrapPPref) foutname+= "_NoExtrapBins";
TDatime d;
TString ndate = Form("%02d%02d%04d",d.GetDay(),d.GetMonth(),d.GetYear());
resultFile = fopen( Form("%s_result_%s.txt",foutname.Data(),ndate.Data()),"w");
fprintf(resultFile,"Ptmin (GeV/c) Ptmax (GeV/c) Raa(Daverage) +-(stat) +(syst) - (syst) \n\n");
// Define here all needed histograms/graphs to be retrieved
TH1D *hDmesonRaa[3];
TH1I *hCombinedReferenceFlag[3];
TGraphAsymmErrors *gDataSystematicsPP[3], *gDataSystematicsAB[3];
TGraphAsymmErrors *gScalingUncPP[3];
TGraphAsymmErrors *gRABFeedDownSystematicsElossHypothesis[3];
TGraphAsymmErrors *gRAB_GlobalSystematics[3];
TH1D *hDmesonPPRef[3], *hDmesonPPYieldExtrUnc[3], *hDmesonPPCutVarUnc[3], *hDmesonPPIDPUnc[3], *hDmesonPPMCPtUnc[3];
// Define here all output histograms/graphs
TH1D *hDmesonAverageRAB = new TH1D("hDmesonAverageRAB","D meson average Raa ; p_{T} (GeV/c)",nbins,ptbinlimits);
TGraphAsymmErrors *gRABNorm;
TGraphAsymmErrors *gRAB_DmesonAverage_GlobalSystematics = new TGraphAsymmErrors(0);
TGraphAsymmErrors *gRAB_DmesonAverage_FeedDownSystematicsElossHypothesis = new TGraphAsymmErrors(0);
TGraphAsymmErrors *gRAB_DmesonAverage_ScalingSystematicsPP = new TGraphAsymmErrors(0);
TGraphAsymmErrors *gRAB_DmesonAverage_DataSystematicsPP = new TGraphAsymmErrors(0);
TGraphAsymmErrors *gRAB_DmesonAverage_DataSystematicsAB = new TGraphAsymmErrors(0);
TGraphAsymmErrors *gRAB_DmesonAverage_TrackingSystematicsPP = new TGraphAsymmErrors(0);
TGraphAsymmErrors *gRAB_DmesonAverage_TrackingSystematicsAB = new TGraphAsymmErrors(0);
gRAB_DmesonAverage_GlobalSystematics->SetNameTitle("gRAB_DmesonAverage_GlobalSystematics","DmesonAverage GlobalSystematics");
gRAB_DmesonAverage_FeedDownSystematicsElossHypothesis->SetNameTitle("gRAB_DmesonAverage_FeedDownSystematicsElossHypothesis","DmesonAverage FeedDownSystematicsElossHypothesis");
gRAB_DmesonAverage_ScalingSystematicsPP->SetNameTitle("gRAB_DmesonAverage_ScalingSystematicsPP","DmesonAverage Scaling uncertainty PP");
gRAB_DmesonAverage_DataSystematicsPP->SetNameTitle("gRAB_DmesonAverage_DataSystematicsPP","DmesonRaaAverage DataSystematicsPP - tracking uncertainty PP");
gRAB_DmesonAverage_DataSystematicsAB->SetNameTitle("gRAB_DmesonAverage_DataSystematicsAB","DmesonRaaAverage DataSystematicsAB - tracking uncertainty AB");
gRAB_DmesonAverage_TrackingSystematicsPP->SetNameTitle("gRAB_DmesonAverage_TrackingSystematicsPP","DmesonRaaAverage tracking uncertainty PP");
gRAB_DmesonAverage_TrackingSystematicsAB->SetNameTitle("gRAB_DmesonAverage_TrackingSystematicsAB","DmesonRaaAverage tracking uncertainty AB");
const char *filenamesRaa[3] = { fD0Raa, fDplusRaa, fDstarRaa };
const char *filenamesReference[3] = { fD0ppRef, fDplusppRef, fDstarppRef };
const char *filenamesSuffixes[3] = { "Dzero", "Dplus", "Dstar" };
Bool_t isDmeson[3] = { true, true, true };
if(strcmp(filenamesRaa[0],"")==0) { cout<<" Dzero not set, error"<<endl; return; }
//
// Get Raa file histos and graphs
//
AliHFSystErr *ppSyst[3];
AliHFSystErr *ABSyst[3];
Double_t ppTracking[3][nbins], ppSystRawYield[3][nbins], ppSystCutVar[3][nbins], ppSystPid[3][nbins];
Double_t ABTracking[3][nbins], ABSystRawYield[3][nbins], ABSystCutVar[3][nbins], ABSystPid[3][nbins];
for(Int_t j=0; j<3; j++) {
if(strcmp(filenamesRaa[j],"")==0) { isDmeson[j]=false; continue; }
cout<<" Reading file "<<filenamesRaa[j]<<"..."<<endl;
TFile *fDRaa = TFile::Open(filenamesRaa[j],"read");
if(!fDRaa){ cout<<" Error on file !!!!!"<<filenamesRaa[j]<<endl; return; }
hDmesonRaa[j] = (TH1D*)fDRaa->Get("hRABvsPt");
hDmesonRaa[j]->SetName(Form("%s_%s",hDmesonRaa[j]->GetName(),filenamesSuffixes[j]));
// cout<< hDmesonRaa[j]<< " bins="<< hDmesonRaa[j]->GetNbinsX()<<", value bin 1 ="<<hDmesonRaa[j]->GetBinContent(1)<<endl;
if(j==0) gRABNorm = (TGraphAsymmErrors*)fDRaa->Get("gRAB_Norm");
//
gDataSystematicsPP[j] = (TGraphAsymmErrors*)fDRaa->Get("gRAB_DataSystematicsPP");
gDataSystematicsPP[j]->SetName(Form("%s_%s",gDataSystematicsPP[j]->GetName(),filenamesSuffixes[j]));
gDataSystematicsAB[j] = (TGraphAsymmErrors*)fDRaa->Get("gRAB_DataSystematicsAB");
gDataSystematicsAB[j]->SetName(Form("%s_%s",gDataSystematicsAB[j]->GetName(),filenamesSuffixes[j]));
gRABFeedDownSystematicsElossHypothesis[j] = (TGraphAsymmErrors*)fDRaa->Get("gRAB_FeedDownSystematicsElossHypothesis");
gRABFeedDownSystematicsElossHypothesis[j]->SetName(Form("%s_%s",gRABFeedDownSystematicsElossHypothesis[j]->GetName(),filenamesSuffixes[j]));
gRAB_GlobalSystematics[j] = (TGraphAsymmErrors*)fDRaa->Get("gRAB_GlobalSystematics");
gRAB_GlobalSystematics[j]->SetName(Form("%s_%s",gRAB_GlobalSystematics[j]->GetName(),filenamesSuffixes[j]));
Bool_t shouldDelete=kFALSE;
if(fDRaa->Get("AliHFSystErrPP")){
ppSyst[j]=(AliHFSystErr*)fDRaa->Get("AliHFSystErrPP");
printf("AliHFSystErr object for meson %d in pp (%s) read from HFPtSpectrumRaa output file\n",j,ppSyst[j]->GetTitle());
}else{
printf("Create instance of AliHFSystErr for meson %d in pp \n",j);
ppSyst[j] = new AliHFSystErr(Form("ppSyst_%d",j),Form("ppSyst_%d",j));
ppSyst[j]->SetIsPass4Analysis(kTRUE);
ppSyst[j]->Init(j+1);
shouldDelete=kTRUE;
}
for(Int_t ipt=0; ipt<nbins; ipt++) {
Double_t ptval = ptbinlimits[ipt] + (ptbinlimits[ipt+1]-ptbinlimits[ipt])/2.;
ppTracking[j][ipt]=0.; ppSystRawYield[j][ipt]=0; ppSystCutVar[j][ipt]=0; ppSystPid[j][ipt]=0.;
ppTracking[j][ipt] =ppSyst[j]->GetTrackingEffErr(ptval);
ppSystRawYield[j][ipt]=ppSyst[j]->GetRawYieldErr(ptval);
ppSystCutVar[j][ipt] =ppSyst[j]->GetCutsEffErr(ptval);
ppSystPid[j][ipt] =ppSyst[j]->GetPIDEffErr(ptval);
}
if(shouldDelete) delete ppSyst[j];
shouldDelete=kFALSE;
if(fDRaa->Get("AliHFSystErrAA")){
ABSyst[j]=(AliHFSystErr*)fDRaa->Get("AliHFSystErrAA");
printf("AliHFSystErr object for meson %d in AA (%s) read from HFPtSpectrumRaa output file\n",j,ppSyst[j]->GetTitle());
}else{
printf("Create instance of AliHFSystErr for meson %d in AA \n",j);
ABSyst[j] = new AliHFSystErr(Form("ABSyst_%d",j),Form("ABSyst_%d",j));
ABSyst[j]->SetCollisionType(1); // PbPb by default
if ( cc == k010 ) ABSyst[j]->SetCentrality("010");
else if ( cc == k1020 ) ABSyst[j]->SetCentrality("1020");
else if ( cc == k2040 || cc == k2030 || cc == k3040 ) {
ABSyst[j]->SetCentrality("2040");
ABSyst[j]->SetIsPbPb2010EnergyScan(true);
}
else if ( cc == k3050 ) ABSyst[j]->SetCentrality("3050");
else if ( cc == k4060 || cc == k4050 || cc == k5060 ) ABSyst[j]->SetCentrality("4060");
else if ( cc == k6080 || cc == k5080 ) ABSyst[j]->SetCentrality("6080");
else if ( cc == k4080 ) ABSyst[j]->SetCentrality("4080");
// Going to pPb systematics
else if ( cc == kpPb0100 || cc == kpPb020 || cc == kpPb2040 || cc == kpPb4060 || cc == kpPb60100 ) {
ABSyst[j]->SetCollisionType(2);
ABSyst[j]->SetRunNumber(16);
if(ccestimator==kV0A) {
if(cc == kpPb020) ABSyst[j]->SetCentrality("020V0A");
else if(cc == kpPb2040) ABSyst[j]->SetCentrality("2040V0A");
else if(cc == kpPb4060) ABSyst[j]->SetCentrality("4060V0A");
else if(cc == kpPb60100) ABSyst[j]->SetCentrality("60100V0A");
} else if (ccestimator==kZNA) {
if(cc == kpPb020) ABSyst[j]->SetCentrality("020ZNA");
else if(cc == kpPb2040) ABSyst[j]->SetCentrality("2040ZNA");
else if(cc == kpPb4060) ABSyst[j]->SetCentrality("4060ZNA");
else if(cc == kpPb60100) ABSyst[j]->SetCentrality("60100ZNA");
} else if (ccestimator==kCL1) {
if(cc == kpPb020) ABSyst[j]->SetCentrality("020CL1");
else if(cc == kpPb2040) ABSyst[j]->SetCentrality("2040CL1");
else if(cc == kpPb4060) ABSyst[j]->SetCentrality("4060CL1");
else if(cc == kpPb60100) ABSyst[j]->SetCentrality("60100CL1");
} else {
if(!(cc == kpPb0100)) {
cout <<" Error on the pPb options"<<endl;
return;
}
}
}
ABSyst[j]->Init(j+1);
shouldDelete=kTRUE;
}
for(Int_t ipt=0; ipt<nbins; ipt++) {
Double_t ptval = ptbinlimits[ipt] + (ptbinlimits[ipt+1]-ptbinlimits[ipt])/2.;
ABTracking[j][ipt]=0.; ABSystRawYield[j][ipt]=0; ABSystCutVar[j][ipt]=0; ABSystPid[j][ipt]=0.;
ABTracking[j][ipt] =ABSyst[j]->GetTrackingEffErr(ptval);
ABSystRawYield[j][ipt]=ABSyst[j]->GetRawYieldErr(ptval);
ABSystCutVar[j][ipt] =ABSyst[j]->GetCutsEffErr(ptval);
ABSystPid[j][ipt] =ABSyst[j]->GetPIDEffErr(ptval);
}
if(shouldDelete) delete ABSyst[j];
}
//
// Get pp-reference file histos and graphs
//
const char *pprefhgnames[6] = { "fhScaledData","gScaledDataSystExtrap",
"fhScaledSystRebinYieldExtraction","fhScaledSystRebinCutVariation","fhScaledSystRebinPIDUnc","fhScaledSystRebinMCPt"};
Bool_t isPPRefExtrap[3] = { isPPRefExtrapD0, isPPRefExtrapDplus, isPPRefExtrapDstar };
for(Int_t j=0; j<3; j++) {
if(strcmp(filenamesReference[j],"")==0) { isDmeson[j]=false; continue; }
cout<<" Reading file "<<filenamesReference[j]<<"..."<<endl;
TFile *fRef = TFile::Open(filenamesReference[j],"read");
gScalingUncPP[j] = (TGraphAsymmErrors*)fRef->Get(pprefhgnames[1]);
gScalingUncPP[j]->SetName(Form("%s_%s",gScalingUncPP[j]->GetName(),filenamesSuffixes[j]));
if(isPPRefExtrap[j]) {
hCombinedReferenceFlag[j] = (TH1I*)fRef->Get("hCombinedReferenceFlag");
hCombinedReferenceFlag[j]->SetName(Form("%s_%s",hCombinedReferenceFlag[j]->GetName(),filenamesSuffixes[j]));
}
if(isReadAllPPUnc){
const char*hname="fhScaledData";
if(isPPRefExtrap[j]) hname="hReference";
hDmesonPPRef[j] = (TH1D*)fRef->Get(hname);
hDmesonPPRef[j]->SetName(Form("%s_%s",hDmesonPPRef[j]->GetName(),filenamesSuffixes[j]));
hDmesonPPYieldExtrUnc[j] = (TH1D*)fRef->Get(pprefhgnames[2]);
hDmesonPPYieldExtrUnc[j]->SetName(Form("%s_%s",hDmesonPPYieldExtrUnc[j]->GetName(),filenamesSuffixes[j]));
hDmesonPPCutVarUnc[j] = (TH1D*)fRef->Get(pprefhgnames[3]);
hDmesonPPCutVarUnc[j]->SetName(Form("%s_%s",hDmesonPPCutVarUnc[j]->GetName(),filenamesSuffixes[j]));
hDmesonPPIDPUnc[j] = (TH1D*)fRef->Get(pprefhgnames[4]);
hDmesonPPIDPUnc[j]->SetName(Form("%s_%s",hDmesonPPIDPUnc[j]->GetName(),filenamesSuffixes[j]));
hDmesonPPMCPtUnc[j] = (TH1D*)fRef->Get(pprefhgnames[5]);
hDmesonPPMCPtUnc[j]->SetName(Form("%s_%s",hDmesonPPMCPtUnc[j]->GetName(),filenamesSuffixes[j]));
}
}
//
// Loop per pt bin
//
for(Int_t ipt=0; ipt<nbins; ipt++) {
cout<<" Calculation for pt bin ("<<ptbinlimits[ipt]<<","<<ptbinlimits[ipt+1]<<")"<<endl;
Double_t ptval = ptbinlimits[ipt] + (ptbinlimits[ipt+1]-ptbinlimits[ipt])/2.;
Double_t RaaDmeson[3]={0.,0.,0.};
Double_t RaaDmesonStat[3]={0.,0.,0.};
Double_t RaaDmesonSystLow[3]={0.,0.,0.};
Double_t RaaDmesonSystHigh[3]={0.,0.,0.};
Double_t weight[3]={0.,0.,0.};
Double_t ppSystLow[3]={0.,0.,0.};
Double_t ppSystHigh[3]={0.,0.,0.};
Double_t ppSystUncorrLow[3]={0.,0.,0.};
Double_t ppSystUncorrHigh[3]={0.,0.,0.};
// Double_t ppTracking[3]={0.,0.,0.};
Double_t ScalingLow[3]={0.,0.,0.};
Double_t ScalingHigh[3]={0.,0.,0.};
Double_t ppSystRawYieldOnly[3]={0.,0.,0.};
Double_t ppSystRawYieldCutVar[3]={0.,0.,0.};
Double_t ppSystRawYieldCutVarPid[3]={0.,0.,0.};
Double_t ABSystLow[3]={0.,0.,0.};
Double_t ABSystHigh[3]={0.,0.,0.};
Double_t ABSystUncorrLow[3]={0.,0.,0.};
Double_t ABSystUncorrHigh[3]={0.,0.,0.};
Double_t ABSystRawYieldOnly[3]={0.,0.,0.};
Double_t ABSystRawYieldCutVar[3]={0.,0.,0.};
Double_t ABSystRawYieldCutVarPid[3]={0.,0.,0.};
// Double_t ABTracking[3]={0.,0.,0.};
Double_t RabFdElossLow[3]={0.,0.,0.};
Double_t RabFdElossHigh[3]={0.,0.,0.};
Double_t RabGlobalLow[3]={0.,0.,0.};
Double_t RabGlobalHigh[3]={0.,0.,0.};
Double_t average=0., averageStat=0.;
Double_t weightTot=0.;
Double_t ppTrackingAv=0., ABTrackingAv=0.;
Double_t ppDataSystAvLow=0., ppDataSystAvHigh=0.;
Double_t ABDataSystAvLow=0., ABDataSystAvHigh=0.;
Double_t scalingLowAv=0., scalingHighAv=0.;
Double_t raaSystUncorrLow=0., raaSystUncorrHigh=0.;
Double_t raabeautyLow=0., raabeautyHigh=0.;
Int_t histoBin=-1;
// Get tracking uncertainties and raw yield and cut-variation and pid-systematics
if(isDebug) cout<<" Retrieving tracking + rawyield systematics"<<endl;
for(Int_t j=0; j<3; j++) {
if(!isDmeson[j]) continue;
ppSystRawYieldOnly[j] = ppSystRawYield[j][ipt];
ppSystRawYieldCutVar[j] = TMath::Sqrt( ppSystRawYield[j][ipt]*ppSystRawYield[j][ipt]
+ ppSystCutVar[j][ipt]*ppSystCutVar[j][ipt] );
ppSystRawYieldCutVarPid[j] = TMath::Sqrt( ppSystRawYield[j][ipt]*ppSystRawYield[j][ipt]
+ ppSystCutVar[j][ipt]*ppSystCutVar[j][ipt]
+ ppSystPid[j][ipt]*ppSystPid[j][ipt] );
ABSystRawYieldOnly[j] = ABSystRawYield[j][ipt];
ABSystRawYieldCutVar[j] = TMath::Sqrt( ABSystRawYield[j][ipt]*ABSystRawYield[j][ipt]
+ ABSystCutVar[j][ipt]*ABSystCutVar[j][ipt] );
ABSystRawYieldCutVarPid[j] = TMath::Sqrt( ABSystRawYield[j][ipt]*ABSystRawYield[j][ipt]
+ ABSystCutVar[j][ipt]*ABSystCutVar[j][ipt]
+ ABSystPid[j][ipt]*ABSystPid[j][ipt] );
if(isDebug) cout<<" j="<<j<<" pt="<< ptval<<" ppref unc RY+CV="<<ppSystRawYieldCutVar[j]<<" RY+CV+PID="<<ppSystRawYieldCutVarPid[j]<<endl;
if(isDebug) cout<<" j="<<j<<" pt="<< ptval<<" AB unc RY+CV="<<ABSystRawYieldCutVar[j]<<" RY+CV+PID="<<ABSystRawYieldCutVarPid[j]<<endl;
}
if(isReadAllPPUnc){
if(isDebug) cout<<" Retrieving all pp reference systematics from the rebinned file"<<endl;
for(Int_t j=0; j<3; j++) {
if(!isDmeson[j]) continue;
Int_t ibin = hDmesonPPRef[j]->FindBin(ptval);
Double_t ppval = hDmesonPPRef[j]->GetBinContent(ibin);
Double_t rawyield = hDmesonPPYieldExtrUnc[j]->GetBinContent( hDmesonPPYieldExtrUnc[j]->FindBin(ptval) )/ppval;
Double_t cutvar = hDmesonPPCutVarUnc[j]->GetBinContent( hDmesonPPCutVarUnc[j]->FindBin(ptval) )/ppval;
Double_t pid = hDmesonPPIDPUnc[j]->GetBinContent( hDmesonPPIDPUnc[j]->FindBin(ptval) )/ppval;
ppSystRawYieldCutVar[j] = TMath::Sqrt( rawyield*rawyield + cutvar*cutvar );
ppSystRawYieldCutVarPid[j] = TMath::Sqrt( rawyield*rawyield + cutvar*cutvar + pid*pid );
if(isDebug) cout<<"redo j="<<j<<" pt="<< ptval<<" ppref unc RY+CV="<<ppSystRawYieldCutVar[j]<<" RY+CV+PID="<<ppSystRawYieldCutVarPid[j]<<endl;
}
}
// Check for the pp reference systematics for extrapolated pt bins
for(Int_t j=0; j<3; j++) {
if(isPPRefExtrap[j]){
// if(ptval>ptmaxPPRefData[j]) {
Int_t ippbin = hCombinedReferenceFlag[j]->FindBin(ptval);
Bool_t flag = hCombinedReferenceFlag[j]->GetBinContent(ippbin);
if(!flag) continue;
// cout<<" pp ref flag="<<flag<<" >>> ";
// Get pp reference relative systematics
Double_t ppSystTotLow=0., ppSystTotHigh=0.;
FindGraphRelativeUnc(gDataSystematicsPP[j],ptval,ppSystTotLow,ppSystTotHigh);
ppSystRawYieldCutVar[j] = ppSystTotLow > ppSystTotHigh ? ppSystTotLow : ppSystTotHigh ;
ppSystRawYieldCutVarPid[j] = ppSystRawYieldCutVar[j];
ppSystRawYieldOnly[j] = ppSystRawYieldCutVar[j];
}
}
//
// Loop per meson to get the Raa values and uncertainties for the given pt bin
//
if(isDebug) cout<<" Retrieving all Raa values and uncertainties"<<endl;
for(Int_t j=0; j<3; j++) {
// Get value, stat unc and weight
if(!isDmeson[j]) continue;
if(!hDmesonRaa[j]) continue;
histoBin = hDmesonRaa[j]->FindBin(ptval);
RaaDmeson[j] = hDmesonRaa[j]->GetBinContent( histoBin );
if (RaaDmeson[j]<=0) continue;
RaaDmesonStat[j] = hDmesonRaa[j]->GetBinError( histoBin );
// Get global systematics
FindGraphRelativeUnc(gRAB_GlobalSystematics[j],ptval,RaaDmesonSystLow[j],RaaDmesonSystHigh[j]);
// Evaluate the weight
weight[j] = GetWeight(averageOption,ptval,hDmesonRaa[j],
RaaDmesonSystLow[j],RaaDmesonSystHigh[j],
ppSystRawYieldOnly[j],ppSystRawYieldCutVar[j],ppSystRawYieldCutVarPid[j],
ABSystRawYieldOnly[j],ABSystRawYieldCutVar[j],ABSystRawYieldCutVarPid[j]);
cout<<" raa "<<filenamesSuffixes[j]<<" meson = "<<RaaDmeson[j]<<" +-"<<RaaDmesonStat[j]<<"(stat) -> (weight="<<weight[j]<<") ,";
// Get pp reference relative systematics
FindGraphRelativeUnc(gDataSystematicsPP[j],ptval,ppSystLow[j],ppSystHigh[j]);
// Get pp-extrapolation relative uncertainty
FindGraphRelativeUnc(gScalingUncPP[j],ptval,ScalingHigh[j],ScalingLow[j]); // exchanging low-high bc has oposite influence on Raa
if(isPPRefExtrap[j]){
Int_t ippbin = hCombinedReferenceFlag[j]->FindBin(ptval);
Bool_t flag = hCombinedReferenceFlag[j]->GetBinContent(ippbin);
if(isDebug) cout<< " bin="<<j<<" pp ref flag on? "<<flag;
if(flag){ ScalingHigh[j]=0.; ScalingLow[j]=0.; ppTracking[j][ipt]=0.; }
if(flag && !useExtrapPPref){
weight[j] =0;
cout<<"weight set to 0";
}
}
// Get pp reference systematics minus tracking systematics minus extrapolation uncertainties
ppSystUncorrLow[j] = TMath::Sqrt( ppSystLow[j]*ppSystLow[j]
- ScalingLow[j]*ScalingLow[j]
- ppTracking[j][ipt]*ppTracking[j][ipt] );
ppSystUncorrHigh[j] = TMath::Sqrt( ppSystHigh[j]*ppSystHigh[j]
- ScalingHigh[j]*ScalingHigh[j]
- ppTracking[j][ipt]*ppTracking[j][ipt] );
// Get AB relative systematics
FindGraphRelativeUnc(gDataSystematicsAB[j],ptval,ABSystLow[j],ABSystHigh[j]);
// Get AB relative systematics minus tracking systematics
ABSystUncorrLow[j] = TMath::Sqrt( ABSystLow[j]*ABSystLow[j]
- ABTracking[j][ipt]*ABTracking[j][ipt] );
ABSystUncorrHigh[j] = TMath::Sqrt( ABSystHigh[j]*ABSystHigh[j]
- ABTracking[j][ipt]*ABTracking[j][ipt] );
// Get Feed-Down and Eloss relative uncertainties on the Raa
FindGraphRelativeUnc(gRABFeedDownSystematicsElossHypothesis[j],ptval,RabFdElossLow[j],RabFdElossHigh[j]);
//
// Check with global Raa uncertainties
FindGraphRelativeUnc(gRAB_GlobalSystematics[j],ptval,RabGlobalLow[j],RabGlobalHigh[j]);
Double_t testLow = TMath::Sqrt( RabFdElossLow[j]*RabFdElossLow[j] + ABSystLow[j]*ABSystLow[j]
+ ppSystLow[j]*ppSystLow[j] + ScalingLow[j]*ScalingLow[j] );
Double_t testHigh = TMath::Sqrt( RabFdElossHigh[j]*RabFdElossHigh[j] + ABSystHigh[j]*ABSystHigh[j]
+ ppSystHigh[j]*ppSystHigh[j] + ScalingHigh[j]*ScalingHigh[j] );
if (TMath::Abs( testLow - RabGlobalLow[j] ) > 0.015) {
cout << endl<<" >>>> Error on the global Raa uncertainties low : test-sum = "<< testLow<<", global = "<< RabGlobalLow[j]<<" ppref="<<ppSystLow[j]<<endl;
}
if (TMath::Abs( testHigh - RabGlobalHigh[j] ) > 0.015) {
cout << endl<<" >>>> Error on the global Raa uncertainties high : test-sum = "<< testHigh<<", global = "<< RabGlobalHigh[j]<<" ppref="<<ppSystHigh[j]<<endl<<endl;
}
//
histoBin = -1;
cout<<endl;
}
cout<<endl;
//
// Evaluate Dmeson average
//
if(isDebug) cout<<" Evaluating the average"<<endl;
for(Int_t j=0; j<3; j++){
if(!isDmeson[j]) continue;
if( !(RaaDmeson[j]>0.) ) continue;
weightTot += weight[j];
// weighted average
average += RaaDmeson[j]*weight[j];
// stat absolute uncertainty (uncorrelated) : sum in quadrature
averageStat += (RaaDmesonStat[j]*weight[j])*(RaaDmesonStat[j]*weight[j]);
// pp tracking relative uncertainty (correlated) : linear sum
ppTrackingAv += ppTracking[j][ipt]*RaaDmeson[j]*weight[j];
// AB tracking relative uncertainty (correlated) : linear sum
ABTrackingAv += ABTracking[j][ipt]*RaaDmeson[j]*weight[j];
// pp scaling relative uncertainty (correlated) : linear sum
scalingLowAv += ScalingLow[j]*RaaDmeson[j]*weight[j];
scalingHighAv += ScalingHigh[j]*RaaDmeson[j]*weight[j];
// Get pp and AB relative uncorrelated systematics : sum in quadrature
raaSystUncorrLow += (ppSystUncorrLow[j]*RaaDmeson[j]*weight[j])*(ppSystUncorrLow[j]*RaaDmeson[j]*weight[j])
+ (ABSystUncorrLow[j]*RaaDmeson[j]*weight[j])*(ABSystUncorrLow[j]*RaaDmeson[j]*weight[j]);
raaSystUncorrHigh += (ppSystUncorrHigh[j]*RaaDmeson[j]*weight[j])*(ppSystUncorrHigh[j]*RaaDmeson[j]*weight[j])
+ (ABSystUncorrHigh[j]*RaaDmeson[j]*weight[j])*(ABSystUncorrHigh[j]*RaaDmeson[j]*weight[j]);
ppDataSystAvLow += (ppSystUncorrLow[j]*RaaDmeson[j]*weight[j])*(ppSystUncorrLow[j]*RaaDmeson[j]*weight[j]);
ABDataSystAvLow += (ABSystUncorrLow[j]*RaaDmeson[j]*weight[j])*(ABSystUncorrLow[j]*RaaDmeson[j]*weight[j]);
ppDataSystAvHigh += (ppSystUncorrHigh[j]*RaaDmeson[j]*weight[j])*(ppSystUncorrHigh[j]*RaaDmeson[j]*weight[j]);
ABDataSystAvHigh += (ABSystUncorrHigh[j]*RaaDmeson[j]*weight[j])*(ABSystUncorrHigh[j]*RaaDmeson[j]*weight[j]);
// Beauty uncertainties: evaluate Raa average for the upper / lower bands
raabeautyLow += (1-RabFdElossLow[j])*RaaDmeson[j]*weight[j];
raabeautyHigh += (1+RabFdElossHigh[j])*RaaDmeson[j]*weight[j];
}
average /= weightTot;
averageStat = TMath::Sqrt(averageStat)/weightTot;
ppTrackingAv /= weightTot;
ABTrackingAv /= weightTot;
scalingLowAv /= weightTot;
scalingHighAv /= weightTot;
raaSystUncorrLow = TMath::Sqrt(raaSystUncorrLow)/weightTot;
raaSystUncorrHigh = TMath::Sqrt(raaSystUncorrHigh)/weightTot;
ppDataSystAvLow = TMath::Sqrt(ppDataSystAvLow)/weightTot;
ppDataSystAvHigh = TMath::Sqrt(ppDataSystAvHigh)/weightTot;
ABDataSystAvLow = TMath::Sqrt(ABDataSystAvLow)/weightTot;
ABDataSystAvHigh = TMath::Sqrt(ABDataSystAvHigh)/weightTot;
// finalization beauty uncertainties
raabeautyLow /= weightTot;
raabeautyHigh /= weightTot;
Double_t RaaBeauty[3] = { average, raabeautyLow, raabeautyHigh };
Double_t beautyUncLow = average-TMath::MinElement(3,RaaBeauty);
Double_t beautyUncHigh = TMath::MaxElement(3,RaaBeauty)-average;
// finalization global uncertainties
Double_t totalUncLow = TMath::Sqrt( raaSystUncorrLow*raaSystUncorrLow
+ ppTrackingAv*ppTrackingAv + ABTrackingAv*ABTrackingAv
+ scalingLowAv*scalingLowAv
+ beautyUncLow*beautyUncLow );
Double_t totalUncHigh = TMath::Sqrt( raaSystUncorrHigh*raaSystUncorrHigh
+ ppTrackingAv*ppTrackingAv + ABTrackingAv*ABTrackingAv
+ scalingHighAv*scalingHighAv
+ beautyUncHigh*beautyUncHigh );
if(isDebug) cout<<" Raa="<<average<<" +-"<<averageStat<<"(stat) +"<<ppDataSystAvHigh<<" -"<<ppDataSystAvLow<<" (pp-data) +-"<<ppTrackingAv<<" (pp-track) +"<<ABDataSystAvHigh<<" -"<<ABDataSystAvLow<<" (ab-data) +-"<<ABTrackingAv<<" (ab-track) +"<<scalingHighAv<<" -"<<scalingLowAv<<" (scal) +"<<beautyUncHigh<<" -"<<beautyUncLow<<" (fd)"<<endl;
//
// Fill output histos/graphs
//
histoBin = hDmesonAverageRAB->FindBin(ptval);
hDmesonAverageRAB->SetBinContent(histoBin,average);
hDmesonAverageRAB->SetBinError(histoBin,averageStat);
Double_t ept = hDmesonAverageRAB->GetBinWidth(histoBin)/2.;
ept=0.3;
gRAB_DmesonAverage_GlobalSystematics->SetPoint(ipt,ptval,average);
gRAB_DmesonAverage_GlobalSystematics->SetPointError(ipt,ept,ept,totalUncLow,totalUncHigh);
ept=0.2;
gRAB_DmesonAverage_FeedDownSystematicsElossHypothesis->SetPoint(ipt,ptval,average);
gRAB_DmesonAverage_FeedDownSystematicsElossHypothesis->SetPointError(ipt,ept,ept,beautyUncLow,beautyUncHigh);
//
ept=0.1;
gRAB_DmesonAverage_TrackingSystematicsPP->SetPoint(ipt,ptval,average);
gRAB_DmesonAverage_TrackingSystematicsPP->SetPointError(ipt,ept,ept,ppTrackingAv,ppTrackingAv);
gRAB_DmesonAverage_TrackingSystematicsAB->SetPoint(ipt,ptval,average);
gRAB_DmesonAverage_TrackingSystematicsAB->SetPointError(ipt,ept,ept,ABTrackingAv,ABTrackingAv);
gRAB_DmesonAverage_ScalingSystematicsPP->SetPoint(ipt,ptval,average);
gRAB_DmesonAverage_ScalingSystematicsPP->SetPointError(ipt,ept,ept,scalingLowAv,scalingHighAv);
gRAB_DmesonAverage_DataSystematicsPP->SetPoint(ipt,ptval,average);
gRAB_DmesonAverage_DataSystematicsPP->SetPointError(ipt,ept,ept,ppDataSystAvLow,ppDataSystAvHigh);
gRAB_DmesonAverage_DataSystematicsAB->SetPoint(ipt,ptval,average);
gRAB_DmesonAverage_DataSystematicsAB->SetPointError(ipt,ept,ept,ABDataSystAvLow,ABDataSystAvHigh);
histoBin = -1;
//
// Printout
cout<< " pt min (GeV/c), pt max (GeV/c), Raa(Daverage), +- (stat), + (syst) , - (syst) "<<endl;
cout<< ptbinlimits[ipt] <<" "<< ptbinlimits[ipt+1]<< " "<< average<< " "<< averageStat<< " "<< totalUncHigh<<" "<<totalUncLow<<endl;
fprintf(resultFile,"%02.0f %02.0f %5.3f %5.3f %5.3f %5.3f\n",ptbinlimits[ipt],ptbinlimits[ipt+1],average,averageStat,totalUncHigh,totalUncLow);
} // end loop on pt bins
fclose(resultFile);
//
// Now can start drawing
//
TH2F* hempty=new TH2F("hempty"," ; p_{T} (GeV/c} ; Nucl. modif. fact.",100,0.,ptbinlimits[nbins],100,0.,2.);
hempty->SetStats(0);
TCanvas *cAvCheck = new TCanvas("cAvCheck","Average Dmeson check");
hempty->Draw();
hDmesonAverageRAB->SetLineColor(kBlack);
hDmesonAverageRAB->SetMarkerStyle(20);
hDmesonAverageRAB->SetMarkerColor(kBlack);
hDmesonAverageRAB->Draw("esame");
for(Int_t j=0; j<3; j++) {
if(!isDmeson[j]) continue;
hDmesonRaa[j]->SetLineColor(kBlack);
hDmesonRaa[j]->SetMarkerColor(2+j);
hDmesonRaa[j]->SetMarkerStyle(21+j);
gRAB_GlobalSystematics[j]->SetFillStyle(0);
gRAB_GlobalSystematics[j]->SetLineColor(2+j);
gRAB_GlobalSystematics[j]->Draw("2");
hDmesonRaa[j]->Draw("esame");
}
gRAB_DmesonAverage_GlobalSystematics->SetFillStyle(0);
gRAB_DmesonAverage_GlobalSystematics->SetLineColor(kBlack);
gRAB_DmesonAverage_GlobalSystematics->Draw("2");
hDmesonAverageRAB->Draw("esame");
cAvCheck->Update();
cAvCheck->SaveAs(Form("%s_result_%s.gif",foutname.Data(),ndate.Data()));
TCanvas *cAv = new TCanvas("cAv","Average Dmeson");
hDmesonAverageRAB->Draw("e");
gRAB_DmesonAverage_FeedDownSystematicsElossHypothesis->SetFillStyle(1001);
gRAB_DmesonAverage_FeedDownSystematicsElossHypothesis->SetFillColor(kMagenta-7);
gRAB_DmesonAverage_FeedDownSystematicsElossHypothesis->Draw("2");
gRAB_DmesonAverage_GlobalSystematics->Draw("2");
hDmesonAverageRAB->Draw("esame");
cAv->Update();
//
// Now can start saving the output
//
TFile *fout = new TFile(Form("HFPtSpectrumRaa_%s_%s.root",foutname.Data(),ndate.Data()),"recreate");
hDmesonAverageRAB->Write();
gRABNorm->Write();
gRAB_DmesonAverage_GlobalSystematics->Write();
gRAB_DmesonAverage_FeedDownSystematicsElossHypothesis->Write();
gRAB_DmesonAverage_TrackingSystematicsPP->Write();
gRAB_DmesonAverage_TrackingSystematicsAB->Write();
gRAB_DmesonAverage_ScalingSystematicsPP->Write();
gRAB_DmesonAverage_DataSystematicsPP->Write();
gRAB_DmesonAverage_DataSystematicsAB->Write();
fout->Write();
}