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[PWGDQ] add efficiency type for random plane test #16481

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Merged
iarsene merged 3 commits into from
Jun 1, 2026
Merged

[PWGDQ] add efficiency type for random plane test #16481

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850b45a
add efficiency type for random plane test
zjxiongOvO Jun 1, 2026
5525970
Please consider the following formatting changes
alibuild Jun 1, 2026
c9a775f
Merge pull request #23 from alibuild/alibot-cleanup-16481
zjxiongOvO Jun 1, 2026
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20 changes: 20 additions & 0 deletions PWGDQ/Core/VarManager.cxx
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Original file line number Diff line number Diff line change
Expand Up @@ -193,8 +193,8 @@
// TO Do: add more systems

// set the beam 4-momentum vectors
float beamAEnergy = energy / 2.0 * sqrt(NumberOfProtonsA * NumberOfProtonsC / NumberOfProtonsC / NumberOfProtonsA); // GeV

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[std-prefix] 

Use std:: prefix for names from the std namespace.
float beamCEnergy = energy / 2.0 * sqrt(NumberOfProtonsC * NumberOfProtonsA / NumberOfProtonsA / NumberOfProtonsC); // GeV

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float beamAMomentum = std::sqrt(beamAEnergy * beamAEnergy - NumberOfNucleonsA * NumberOfNucleonsA * MassProton * MassProton);
float beamCMomentum = std::sqrt(beamCEnergy * beamCEnergy - NumberOfNucleonsC * NumberOfNucleonsC * MassProton * MassProton);
fgBeamA.SetPxPyPzE(0, 0, beamAMomentum, beamAEnergy);
Expand Down Expand Up @@ -293,7 +293,7 @@
double mean = calibMeanHist->GetBinContent(binTPCncls, binPin, binEta);
double sigma = calibSigmaHist->GetBinContent(binTPCncls, binPin, binEta);
return (nSigmaValue - mean) / sigma; // Return the calibrated nSigma value
} else if (fgCalibrationType == 2) {

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[magic-number] 

Avoid magic numbers in expressions. Assign the value to a clearly named variable or constant.
// get the calibration histograms
CalibObjects calibMean, calibSigma, calibStatus;
switch (species) {
Expand Down Expand Up @@ -427,6 +427,26 @@
// get the efficiency value from the histogram
values[kPairEfficiency] = efficiencyHist->GetBinContent(binPt, binCent, binCosThetaStarFT0c);
values[kPairWeight] = 1.0 / (values[kPairEfficiency] > 0 ? values[kPairEfficiency] : 1.0); // set the weight as the inverse of the efficiency, but avoid division by zero
} else if (fgEfficiencyType == kPairPtCentFT0cCosThetaStarRandom) {
if (!fgEfficiencyHist) {
LOG(fatal) << "efficiency histogram not set";
return;
}
TH3F* efficiencyHist = reinterpret_cast<TH3F*>(fgEfficiencyHist);
// Get the bin indices for the efficiency histogram
int binPt = efficiencyHist->GetXaxis()->FindBin(values[kPt]);
binPt = (binPt == 0 ? 1 : binPt);
binPt = (binPt > efficiencyHist->GetXaxis()->GetNbins() ? efficiencyHist->GetXaxis()->GetNbins() : binPt);
int binCent = efficiencyHist->GetYaxis()->FindBin(values[kCentFT0C]);
binCent = (binCent == 0 ? 1 : binCent);
binCent = (binCent > efficiencyHist->GetYaxis()->GetNbins() ? efficiencyHist->GetYaxis()->GetNbins() : binCent);
int binCosThetaStarRandom = efficiencyHist->GetZaxis()->FindBin(values[kCosThetaStarRandom]);
binCosThetaStarRandom = (binCosThetaStarRandom == 0 ? 1 : binCosThetaStarRandom);
binCosThetaStarRandom = (binCosThetaStarRandom > efficiencyHist->GetZaxis()->GetNbins() ? efficiencyHist->GetZaxis()->GetNbins() : binCosThetaStarRandom);

// get the efficiency value from the histogram
values[kPairEfficiency] = efficiencyHist->GetBinContent(binPt, binCent, binCosThetaStarRandom);
values[kPairWeight] = 1.0 / (values[kPairEfficiency] > 0 ? values[kPairEfficiency] : 1.0); // set the weight as the inverse of the efficiency, but avoid division by zero
} else {
LOG(warning) << "FillEfficiency: unknown efficiency type " << fgEfficiencyType << ", using default efficiency = 1";
values[kPairEfficiency] = 1;
Expand All @@ -440,14 +460,14 @@
// Bimodality coefficient = (skewness^2 + 1) / kurtosis
// return a tuple including the coefficient, mean, RMS, skewness, and kurtosis
size_t n = data.size();
if (n < 3) {

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[magic-number] 

Avoid magic numbers in expressions. Assign the value to a clearly named variable or constant.
return std::make_tuple(-1.0, -1.0, -1.0, -1.0, -1.0);
}
float mean = std::accumulate(data.begin(), data.end(), 0.0) / n;

float m2 = 0.0, m3 = 0.0, m4 = 0.0;
float diff, diff2;
for (float x : data) {

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diff = x - mean;
diff2 = diff * diff;
m2 += diff2;
Expand Down Expand Up @@ -486,7 +506,7 @@
int nBins = static_cast<int>((max - min) / binWidth);
std::vector<int> counts(nBins, 0.0);

for (float x : data) {

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[const-ref-in-for-loop] 

Use constant references for non-modified iterators in range-based for loops.
if (x < min || x >= max) {
continue; // skip out-of-range values
}
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1 change: 1 addition & 0 deletions PWGDQ/Core/VarManager.h
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Expand Up @@ -1130,6 +1130,7 @@
enum EfficiencyType {
kNone = 0,
kPairPtCentFT0cCosThetaStarFT0c,
kPairPtCentFT0cCosThetaStarRandom,
// Add more efficiency types as needed
kNEfficiencyTypes
};
Expand Down Expand Up @@ -1840,9 +1841,9 @@
}
if constexpr ((fillMap & MuonCov) > 0 || (fillMap & ReducedMuonCov) > 0) {
o2::dataformats::GlobalFwdTrack propmuon = PropagateMuon(muontrack, collision);
double px = propmuon.getP() * sin(M_PI / 2 - atan(mfttrack.tgl())) * cos(mfttrack.phi());

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[std-prefix] 

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double py = propmuon.getP() * sin(M_PI / 2 - atan(mfttrack.tgl())) * sin(mfttrack.phi());

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double pz = propmuon.getP() * cos(M_PI / 2 - atan(mfttrack.tgl()));

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double pt = std::sqrt(std::pow(px, 2) + std::pow(py, 2));
auto mftprop = o2::aod::fwdtrackutils::getTrackParCovFwdShift(mfttrack, fgzShiftFwd);
values[kX] = mftprop.getX();
Expand Down Expand Up @@ -4707,7 +4708,7 @@
values[kVertexingLxyErr] = (KFPV.GetCovariance(0) + KFGeoTwoProng.GetCovariance(0)) * dxPair2PV * dxPair2PV + (KFPV.GetCovariance(2) + KFGeoTwoProng.GetCovariance(2)) * dyPair2PV * dyPair2PV + 2 * ((KFPV.GetCovariance(1) + KFGeoTwoProng.GetCovariance(1)) * dxPair2PV * dyPair2PV);
values[kVertexingLzErr] = (KFPV.GetCovariance(5) + KFGeoTwoProng.GetCovariance(5)) * dzPair2PV * dzPair2PV;
values[kVertexingLxyzErr] = (KFPV.GetCovariance(0) + KFGeoTwoProng.GetCovariance(0)) * dxPair2PV * dxPair2PV + (KFPV.GetCovariance(2) + KFGeoTwoProng.GetCovariance(2)) * dyPair2PV * dyPair2PV + (KFPV.GetCovariance(5) + KFGeoTwoProng.GetCovariance(5)) * dzPair2PV * dzPair2PV + 2 * ((KFPV.GetCovariance(1) + KFGeoTwoProng.GetCovariance(1)) * dxPair2PV * dyPair2PV + (KFPV.GetCovariance(3) + KFGeoTwoProng.GetCovariance(3)) * dxPair2PV * dzPair2PV + (KFPV.GetCovariance(4) + KFGeoTwoProng.GetCovariance(4)) * dyPair2PV * dzPair2PV);
if (fabs(values[kVertexingLxy]) < 1.e-8f)

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values[kVertexingLxy] = 1.e-8f;
values[kVertexingLxyErr] = values[kVertexingLxyErr] < 0. ? 1.e8f : std::sqrt(values[kVertexingLxyErr]) / values[kVertexingLxy];
if (fabs(values[kVertexingLz]) < 1.e-8f)
Expand Down
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