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[PWGHF] Bugfix taskLc: check mlProb vector size for correct PKPi/PiKP hypothesis #13808

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Merged
fgrosa merged 1 commit into from
Nov 14, 2025
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[PWGHF] Bugfix taskLc: check mlProb vector size for correct PKPi/PiKP hypothesis #13808

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24 changes: 12 additions & 12 deletions PWGHF/D2H/Tasks/taskLc.cxx
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Original file line number Diff line number Diff line change
Expand Up @@ -462,18 +462,18 @@ struct HfTaskLc {
if (storeOccupancy && occEstimator != o2::hf_occupancy::OccupancyEstimator::None) {
occ = o2::hf_occupancy::getOccupancyColl(collision, occEstimator);
}
double massLc(-1);
double outputBkg(-1), outputPrompt(-1), outputFD(-1);
const float properLifetime = HfHelper::ctLc(candidate) * CtToProperLifetimePs;

auto fillTHnRecSig = [&](bool isPKPi) {
massLc = isPKPi ? HfHelper::invMassLcToPKPi(candidate) : HfHelper::invMassLcToPiKP(candidate);
const auto massLc = isPKPi ? HfHelper::invMassLcToPKPi(candidate) : HfHelper::invMassLcToPiKP(candidate);

if constexpr (FillMl) {
if (candidate.mlProbLcToPKPi().size() == NumberOfMlClasses) {
outputBkg = isPKPi ? candidate.mlProbLcToPKPi()[MlClassBackground] : candidate.mlProbLcToPiKP()[MlClassBackground]; /// bkg score
outputPrompt = isPKPi ? candidate.mlProbLcToPKPi()[MlClassPrompt] : candidate.mlProbLcToPiKP()[MlClassPrompt]; /// prompt score
outputFD = isPKPi ? candidate.mlProbLcToPKPi()[MlClassNonPrompt] : candidate.mlProbLcToPiKP()[MlClassNonPrompt]; /// non-prompt score
const auto& mlProb = isPKPi ? candidate.mlProbLcToPKPi() : candidate.mlProbLcToPiKP();
if (mlProb.size() == NumberOfMlClasses) {
outputBkg = mlProb[MlClassBackground]; /// bkg score
outputPrompt = mlProb[MlClassPrompt]; /// prompt score
outputFD = mlProb[MlClassNonPrompt]; /// non-prompt score
}
/// Fill the ML outputScores and variables of candidate
std::vector<double> valuesToFill{massLc, pt, cent, outputBkg, outputPrompt, outputFD, static_cast<double>(numPvContributors), ptRecB, static_cast<double>(originType)};
Expand Down Expand Up @@ -655,18 +655,18 @@ struct HfTaskLc {
if (storeOccupancy && occEstimator != o2::hf_occupancy::OccupancyEstimator::None) {
occ = o2::hf_occupancy::getOccupancyColl(collision, occEstimator);
}
double massLc(-1);
double outputBkg(-1), outputPrompt(-1), outputFD(-1);
const float properLifetime = HfHelper::ctLc(candidate) * CtToProperLifetimePs;

auto fillTHnData = [&](bool isPKPi) {
massLc = isPKPi ? HfHelper::invMassLcToPKPi(candidate) : HfHelper::invMassLcToPiKP(candidate);
const auto massLc = isPKPi ? HfHelper::invMassLcToPKPi(candidate) : HfHelper::invMassLcToPiKP(candidate);

if constexpr (FillMl) {
if (candidate.mlProbLcToPKPi().size() == NumberOfMlClasses) {
outputBkg = isPKPi ? candidate.mlProbLcToPKPi()[MlClassBackground] : candidate.mlProbLcToPiKP()[MlClassBackground]; /// bkg score
outputPrompt = isPKPi ? candidate.mlProbLcToPKPi()[MlClassPrompt] : candidate.mlProbLcToPiKP()[MlClassPrompt]; /// prompt score
outputFD = isPKPi ? candidate.mlProbLcToPKPi()[MlClassNonPrompt] : candidate.mlProbLcToPiKP()[MlClassNonPrompt]; /// non-prompt score
const auto& mlProb = isPKPi ? candidate.mlProbLcToPKPi() : candidate.mlProbLcToPiKP();
if (mlProb.size() == NumberOfMlClasses) {
outputBkg = mlProb[MlClassBackground]; /// bkg score
outputPrompt = mlProb[MlClassPrompt]; /// prompt score
outputFD = mlProb[MlClassNonPrompt]; /// non-prompt score
}
/// Fill the ML outputScores and variables of candidate
std::vector<double> valuesToFill{massLc, pt, cent, outputBkg, outputPrompt, outputFD, static_cast<double>(numPvContributors)};
Expand Down
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