Please consider the following formatting changes

Author: alibuild

PWGHF/Core/HfMlResponseXicToXiPikf.h

@@ -80,7 +80,7 @@ class HfMlResponseXicToXiPikf : public HfMlResponse<TypeOutputScore>
   /// \param candidate is the Xic candidate
   /// \return inputFeatures vector
   template <typename T1, typename T2, typename T3>
-  //std::vector<float> getInputFeatures(T1 const& candidate)
+  // std::vector<float> getInputFeatures(T1 const& candidate)
   std::vector<float> getInputFeatures(T1 const& candidate, T2 const& lamProngPi, T2 const& cascProngPi, T3 const& charmBaryonProngPi)
   {
     std::vector<float> inputFeatures;

PWGHF/TableProducer/candidateSelectorXic0ToXiPiKf.cxx

@@ -123,26 +123,26 @@ struct HfCandidateSelectorXic0ToXiPiKf {
   Configurable<int> nClustersItsMin{"nClustersItsMin", 3, "Minimum number of ITS clusters requirement for pi <- charm baryon"};
   Configurable<int> nClustersItsInnBarrMin{"nClustersItsInnBarrMin", 1, "Minimum number of ITS clusters in inner barrel requirement for pi <- charm baryon"};
   Configurable<float> itsChi2PerClusterMax{"itsChi2PerClusterMax", 36, "Maximum value of chi2 fit over ITS clusters for pi <- charm baryon"};
-                                     
+
   // ML inference
   Configurable<bool> applyMl{"applyMl", true, "Flag to apply ML selections"};
   Configurable<std::vector<double>> binsPtMl{"binsPtMl", std::vector<double>{hf_cuts_ml::vecBinsPt}, "pT bin limits for ML application"};
   Configurable<std::vector<int>> cutDirMl{"cutDirMl", std::vector<int>{hf_cuts_ml::vecCutDir}, "Whether to reject score values greater or smaller than the threshold"};
   Configurable<LabeledArray<double>> cutsMl{"cutsMl", {hf_cuts_ml::Cuts[0], hf_cuts_ml::NBinsPt, hf_cuts_ml::NCutScores, hf_cuts_ml::labelsPt, hf_cuts_ml::labelsCutScore}, "ML selections per pT bin"};
-  Configurable<int> nClassesMl{"nClassesMl", static_cast<int>(hf_cuts_ml::NCutScores), "Number of classes in ML model"}; 
+  Configurable<int> nClassesMl{"nClassesMl", static_cast<int>(hf_cuts_ml::NCutScores), "Number of classes in ML model"};
   Configurable<std::vector<std::string>> namesInputFeatures{"namesInputFeatures", std::vector<std::string>{"feature1", "feature2"}, "Names of ML model input features"};
-                                     
+
   // CCDB configuration
   Configurable<std::string> ccdbUrl{"ccdbUrl", "http://alice-ccdb.cern.ch", "url of the ccdb repository"};
   Configurable<std::vector<std::string>> modelPathsCCDB{"modelPathsCCDB", std::vector<std::string>{"EventFiltering/PWGHF/BDTXic"}, "Paths of models on CCDB"};
   Configurable<std::vector<std::string>> onnxFileNames{"onnxFileNames", std::vector<std::string>{"ModelHandler_onnx_XicToXipikf.onnx"}, "ONNX file names for each pT bin (if not from CCDB full path)"};
   Configurable<int64_t> timestampCCDB{"timestampCCDB", -1, "timestamp of the ONNX file for ML model used to query in CCDB"};
   Configurable<bool> loadModelsFromCCDB{"loadModelsFromCCDB", false, "Flag to enable or disable the loading of models from CCDB"};
-                                     
+
   o2::analysis::HfMlResponseXicToXiPikf<float> hfMlResponse;
   std::vector<float> outputMlXicToXiPi = {};
   o2::ccdb::CcdbApi ccdbApi;
-                                     
+
   TrackSelectorPr selectorProton;
   TrackSelectorPi selectorPion;
 
@@ -203,7 +203,7 @@ struct HfCandidateSelectorXic0ToXiPiKf {
     registry.add("hSelMassCharmBaryon", "hSelMassCharmBaryon;status;entries", {HistType::kTH1D, {axisSel}});
     registry.add("hSelDcaXYToPvV0Daughters", "hSelDcaXYToPvV0Daughters;status;entries", {HistType::kTH1D, {axisSel}});
     registry.add("hSelDcaXYToPvPiFromCasc", "hSelDcaXYToPvPiFromCasc;status;entries", {HistType::kTH1D, {axisSel}});
-    
+
     if (applyMl) {
       hfMlResponse.configure(binsPtMl, cutsMl, cutDirMl, nClassesMl);
       if (loadModelsFromCCDB) {
@@ -215,7 +215,6 @@ struct HfCandidateSelectorXic0ToXiPiKf {
       hfMlResponse.cacheInputFeaturesIndices(namesInputFeatures);
       hfMlResponse.init();
     }
-
   }
 
   void process(aod::HfCandToXiPiKf const& candidates,
@@ -225,7 +224,7 @@ struct HfCandidateSelectorXic0ToXiPiKf {
 
     // looping over charm baryon candidates
     for (const auto& candidate : candidates) {
-      
+
       auto ptCand = RecoDecay::sqrtSumOfSquares(candidate.pxCharmBaryon(), candidate.pyCharmBaryon());
 
       bool resultSelections = true; // True if the candidate passes all the selections, False otherwise
@@ -556,7 +555,7 @@ struct HfCandidateSelectorXic0ToXiPiKf {
           continue;
         }
       }
-      
+
       hfSelToXiPi(statusPidCharmBaryon, statusPidCascade, statusPidLambda, statusInvMassCharmBaryon, statusInvMassCascade, statusInvMassLambda, resultSelections, infoTpcStored, infoTofStored,
                   trackPiFromCharm.tpcNSigmaPi(), trackPiFromCasc.tpcNSigmaPi(), trackPiFromLam.tpcNSigmaPi(), trackPrFromLam.tpcNSigmaPr(),
                   trackPiFromCharm.tofNSigmaPi(), trackPiFromCasc.tofNSigmaPi(), trackPiFromLam.tofNSigmaPi(), trackPrFromLam.tofNSigmaPr());