SampleHandlerFD.cpp

Go to the documentation of this file.

#include "SampleHandlerFD.h"
#include "Manager/MaCh3Exception.h"
#include "Manager/MaCh3Logger.h"
#include <cstddef>
 
#include <algorithm>
#include <memory>
 
// ************************************************
SampleHandlerFD::SampleHandlerFD(std::string ConfigFileName, ParameterHandlerGeneric* xsec_cov,
                                 const std::shared_ptr<OscillationHandler>& OscillatorObj_) : SampleHandlerBase() {
// ************************************************
  MACH3LOG_INFO("-------------------------------------------------------------------");
  MACH3LOG_INFO("Creating SampleHandlerFD object");
 
  //ETA - safety feature so you can't pass a NULL xsec_cov
  if(!xsec_cov){
    MACH3LOG_ERROR("You've passed me a nullptr to a SystematicHandlerGeneric... I need this to setup splines!");
    throw MaCh3Exception(__FILE__, __LINE__);
  }
  ParHandler = xsec_cov;
 
  nSamples = 1;
 
  if (OscillatorObj_ != nullptr) {
    MACH3LOG_WARN("You have passed an Oscillator object through the constructor of a SampleHandlerFD object - this will be used for all oscillation channels");
    Oscillator = OscillatorObj_;
  }
  dathist = nullptr;
  dathist2d = nullptr;
  _hPDF1D = nullptr;
  _hPDF2D = nullptr;
 
  KinematicParameters = nullptr;
  ReversedKinematicParameters = nullptr;
  KinematicVectors = nullptr;
  ReversedKinematicVectors = nullptr;
 
  SampleHandlerFD_array = nullptr;
  SampleHandlerFD_data = nullptr;
  SampleHandlerFD_array_w2 = nullptr;
  SampleName = "";
  SampleManager = std::unique_ptr<manager>(new manager(ConfigFileName.c_str()));
 
  // Variables related to MC stat
  FirstTimeW2 = true;
  UpdateW2 = false;
}
 
SampleHandlerFD::~SampleHandlerFD() {
  MACH3LOG_DEBUG("I'm deleting SampleHandlerFD");
  
  for (unsigned int yBin=0;yBin<(Binning.YBinEdges.size()-1);yBin++) {
    if(SampleHandlerFD_array != nullptr){delete[] SampleHandlerFD_array[yBin];}
    delete[] SampleHandlerFD_array_w2[yBin];
    //ETA - there is a chance that you haven't added any data...
    if(SampleHandlerFD_data != nullptr){delete[] SampleHandlerFD_data[yBin];}
  }
 
  if(SampleHandlerFD_array != nullptr){delete[] SampleHandlerFD_array;}
  delete[] SampleHandlerFD_array_w2;
  //ETA - there is a chance that you haven't added any data...
  if(SampleHandlerFD_data != nullptr){delete[] SampleHandlerFD_data;}
 
  if(THStackLeg != nullptr) delete THStackLeg;
 
  if(dathist != nullptr) delete dathist;
  if(dathist2d != nullptr) delete dathist2d;
  if(_hPDF1D != nullptr) delete _hPDF1D;
  if(_hPDF2D != nullptr) delete _hPDF2D;
}
 
void SampleHandlerFD::ReadSampleConfig() 
{
  auto ModeName = Get<std::string>(SampleManager->raw()["MaCh3ModeConfig"], __FILE__ , __LINE__);
  Modes = std::make_unique<MaCh3Modes>(ModeName);
  //SampleTitle has to be provided in the sample yaml otherwise this will throw an exception
  SampleTitle = Get<std::string>(SampleManager->raw()["SampleTitle"], __FILE__ , __LINE__);
  //SampleName has to be provided in the sample yaml otherwise this will throw an exception
  SampleName = Get<std::string>(SampleManager->raw()["SampleName"], __FILE__ , __LINE__);
 
  fTestStatistic = static_cast<TestStatistic>(SampleManager->GetMCStatLLH());
  if (CheckNodeExists(SampleManager->raw(), "LikelihoodOptions")) {
    UpdateW2 = GetFromManager<bool>(SampleManager->raw()["LikelihoodOptions"]["UpdateW2"], false);
  }
  //Binning
  nDimensions = 0;
  XVarStr = GetFromManager(SampleManager->raw()["Binning"]["XVarStr"], std::string(""));
  Binning.XBinEdges = GetFromManager(SampleManager->raw()["Binning"]["XVarBins"], std::vector<double>());
  const auto& edgesx = Binning.XBinEdges;
  if (!std::is_sorted(edgesx.begin(), edgesx.end())) {
    MACH3LOG_ERROR("XVarBins must be in increasing order in sample config {}\n  XVarBins: [{}]",
                   GetTitle(), fmt::join(edgesx, ", "));
    throw MaCh3Exception(__FILE__, __LINE__);
  }
  if(XVarStr.length() > 0){
    nDimensions++;
  } else{
    MACH3LOG_ERROR("Please specify an X-variable string in sample config {}", SampleManager->GetFileName());
    throw MaCh3Exception(__FILE__, __LINE__);
  }
  
  YVarStr = GetFromManager(SampleManager->raw()["Binning"]["YVarStr"], std::string(""));
  Binning.YBinEdges = GetFromManager(SampleManager->raw()["Binning"]["YVarBins"], std::vector<double>());
  const auto& edgesy = Binning.YBinEdges;
  if (!std::is_sorted(edgesy.begin(), edgesy.end())) {
    MACH3LOG_ERROR("YBinEdges must be in increasing order in sample config {}\n  YBinEdges: [{}]",
                   GetTitle(), fmt::join(edgesy, ", "));
    throw MaCh3Exception(__FILE__, __LINE__);
  }
  if(YVarStr.length() > 0){
    if(XVarStr.length() == 0){
      MACH3LOG_ERROR("Please specify an X-variable string in sample config {}. I won't work only with a Y-variable", SampleManager->GetFileName());
      throw MaCh3Exception(__FILE__, __LINE__);
    }
    nDimensions++;
  }
  
  if(nDimensions == 0){
    MACH3LOG_ERROR("Error setting up the sample binning");
    MACH3LOG_ERROR("Number of dimensions is {}", nDimensions);
    MACH3LOG_ERROR("Check that an XVarStr has been given in the sample config");
    throw MaCh3Exception(__FILE__, __LINE__);
  } else{
    MACH3LOG_INFO("Found {} dimensions for sample binning", nDimensions);
  }
  
  //Sanity check that some binning has been specified
  if(Binning.XBinEdges.size() == 0 && Binning.YBinEdges.size() == 0){
    MACH3LOG_ERROR("No binning specified for either X or Y of sample binning, please add some binning to the sample config {}", SampleManager->GetFileName());
    throw MaCh3Exception(__FILE__, __LINE__);
  }
  
  if (!CheckNodeExists(SampleManager->raw(), "BinningFile")){
    MACH3LOG_ERROR("BinningFile not given in for sample {}, ReturnKinematicParameterBinning will not work", GetTitle());
    throw MaCh3Exception(__FILE__, __LINE__);
  }
 
  auto mtupleprefix  = Get<std::string>(SampleManager->raw()["InputFiles"]["mtupleprefix"], __FILE__, __LINE__);
  auto mtuplesuffix  = Get<std::string>(SampleManager->raw()["InputFiles"]["mtuplesuffix"], __FILE__, __LINE__);
  auto splineprefix  = Get<std::string>(SampleManager->raw()["InputFiles"]["splineprefix"], __FILE__, __LINE__);
  auto splinesuffix  = Get<std::string>(SampleManager->raw()["InputFiles"]["splinesuffix"], __FILE__, __LINE__);
  
  int NChannels = static_cast<M3::int_t>(SampleManager->raw()["SubSamples"].size());
  OscChannels.reserve(NChannels);
 
  for (auto const &osc_channel : SampleManager->raw()["SubSamples"]) {
    std::string MTupleFileName = mtupleprefix+osc_channel["mtuplefile"].as<std::string>()+mtuplesuffix;
    
    OscChannelInfo OscInfo;
    OscInfo.flavourName       = osc_channel["Name"].as<std::string>();
    OscInfo.flavourName_Latex = osc_channel["LatexName"].as<std::string>();
    OscInfo.InitPDG           = static_cast<NuPDG>(osc_channel["nutype"].as<int>());
    OscInfo.FinalPDG          = static_cast<NuPDG>(osc_channel["oscnutype"].as<int>());
    OscInfo.ChannelIndex      = static_cast<int>(OscChannels.size());
 
 
    OscChannels.push_back(std::move(OscInfo));
 
    FileToInitPDGMap[MTupleFileName] = static_cast<NuPDG>(osc_channel["nutype"].as<int>());
    FileToFinalPDGMap[MTupleFileName] = static_cast<NuPDG>(osc_channel["oscnutype"].as<int>());
 
    mc_files.push_back(MTupleFileName);
    spline_files.push_back(splineprefix+osc_channel["splinefile"].as<std::string>()+splinesuffix);
  }
 
  //Now grab the selection cuts from the manager
  for ( auto const &SelectionCuts : SampleManager->raw()["SelectionCuts"]) {
    auto TempBoundsVec = GetBounds(SelectionCuts["Bounds"]);
    KinematicCut CutObj;
    CutObj.LowerBound = TempBoundsVec[0];
    CutObj.UpperBound = TempBoundsVec[1];
    CutObj.ParamToCutOnIt = ReturnKinematicParameterFromString(SelectionCuts["KinematicStr"].as<std::string>());
    MACH3LOG_INFO("Adding cut on {} with bounds {} to {}", SelectionCuts["KinematicStr"].as<std::string>(), TempBoundsVec[0], TempBoundsVec[1]);
    StoredSelection.push_back(CutObj);
  }
 
  // EM: initialise the mode weight map
  for( int iMode=0; iMode < Modes->GetNModes(); iMode++ ) {
    _modeNomWeightMap[Modes->GetMaCh3ModeName(iMode)] = 1.0;
  }
 
  // EM: multiply by the nominal weight specified in the sample config file
  if ( SampleManager->raw()["NominalWeights"] ) {
    for( int iMode=0; iMode<Modes->GetNModes(); iMode++ ) {
      std::string modeStr = Modes->GetMaCh3ModeName(iMode);
      if( SampleManager->raw()["NominalWeights"][modeStr] ) {
        double modeWeight = SampleManager->raw()["NominalWeights"][modeStr].as<double>();
        _modeNomWeightMap[Modes->GetMaCh3ModeName(iMode)] *= modeWeight;
      }
    }
  }
 
  // EM: print em out
  MACH3LOG_INFO("  Nominal mode weights to apply: ");
  for(int iMode=0; iMode<Modes->GetNModes(); iMode++ ) {
    std::string modeStr = Modes->GetMaCh3ModeName(iMode);
    MACH3LOG_INFO("    - {}: {}", modeStr, _modeNomWeightMap.at(modeStr));
  }
}
 
void SampleHandlerFD::Initialise() {
  //First grab all the information from your sample config via your manager
  ReadSampleConfig();
 
  //Now initialise all the variables you will need
  Init();
 
  nEvents = SetupExperimentMC();
 
  InitialiseSingleFDMCObject();
  SetupFDMC();
 
  MACH3LOG_INFO("=============================================");
  MACH3LOG_INFO("Total number of events is: {}", GetNEvents());
 
  auto OscParams = ParHandler->GetOscParsFromSampleName(SampleName);
  if (OscParams.size() > 0) {
    MACH3LOG_INFO("Setting up NuOscillator..");
    if (Oscillator != nullptr) {
      MACH3LOG_INFO("You have passed an OscillatorBase object through the constructor of a SampleHandlerFD object - this will be used for all oscillation channels");
      if(Oscillator->isEqualBinningPerOscChannel() != true) {
        MACH3LOG_ERROR("Trying to run shared NuOscillator without EqualBinningPerOscChannel, this will not work");
        throw MaCh3Exception(__FILE__, __LINE__);
      }
 
      if(OscParams.size() != Oscillator->GetOscParamsSize()){
        MACH3LOG_ERROR("Sample {} with {} has {} osc params, while shared NuOsc has {} osc params", GetTitle(), GetSampleName(),
                       OscParams.size(), Oscillator->GetOscParamsSize());
        MACH3LOG_ERROR("This indicate misconfiguration in your Osc yaml");
        throw MaCh3Exception(__FILE__, __LINE__);
      }
    } else {
      InitialiseNuOscillatorObjects();
    }
    SetupNuOscillatorPointers();
  } else{
    MACH3LOG_WARN("Didn't find any oscillation params, thus will not enable oscillations");
  }
 
  MACH3LOG_INFO("Setting up Sample Binning..");
  SetupSampleBinning();
  MACH3LOG_INFO("Setting up Splines..");
  SetupSplines();
  MACH3LOG_INFO("Setting up Normalisation Pointers..");
  SetupNormParameters();
  MACH3LOG_INFO("Setting up Functional Pointers..");
  SetupFunctionalParameters();
  MACH3LOG_INFO("Setting up Weight Pointers..");
  SetupWeightPointers();
  MACH3LOG_INFO("Setting up Kinematic Map..");
  SetupKinematicMap();
  MACH3LOG_INFO("=======================================================");
}
 
// ************************************************
void SampleHandlerFD::SetupKinematicMap() {
// ************************************************
  if(KinematicParameters == nullptr || ReversedKinematicParameters == nullptr) {
    MACH3LOG_INFO("Map KinematicParameters or ReversedKinematicParameters hasn't been initialised");
    throw MaCh3Exception(__FILE__, __LINE__);
  }
  // KS: Ensure maps exist correctly
  for (const auto& pair : *KinematicParameters) {
    const auto& key = pair.first;
    const auto& value = pair.second;
 
    auto it = ReversedKinematicParameters->find(value);
    if (it == ReversedKinematicParameters->end() || it->second != key) {
      MACH3LOG_ERROR("Mismatch found: {} -> {} but {} -> {}",
                     key, value, value, (it != ReversedKinematicParameters->end() ? it->second : "NOT FOUND"));
      throw MaCh3Exception(__FILE__, __LINE__);
    }
  }
}
 
void SampleHandlerFD::Fill1DHist()
{
  // DB Commented out by default - Code heading towards GetLikelihood using arrays instead of root objects
  // Wouldn't actually need this for GetLikelihood as TH objects wouldn't be filled
  _hPDF1D->Reset();
  for (unsigned int yBin=0;yBin<(Binning.YBinEdges.size()-1);yBin++) {
    for (unsigned int xBin=0;xBin<(Binning.XBinEdges.size()-1);xBin++) {
      _hPDF1D->AddBinContent(xBin+1,SampleHandlerFD_array[yBin][xBin]);
    }
  }
}
 
void SampleHandlerFD::Fill2DHist()
{
  // DB Commented out by default - Code heading towards GetLikelihood using arrays instead of root objects
  // Wouldn't actually need this for GetLikelihood as TH objects wouldn't be filled
  _hPDF2D->Reset();
  for (unsigned int yBin=0;yBin<(Binning.YBinEdges.size()-1);yBin++) {
    for (unsigned int xBin=0;xBin<(Binning.XBinEdges.size()-1);xBin++) {
      _hPDF2D->SetBinContent(xBin+1,yBin+1,SampleHandlerFD_array[yBin][xBin]);
    }
  }
}
 
// ************************************************
void SampleHandlerFD::SetupSampleBinning(){
// ************************************************
  MACH3LOG_INFO("Setting up Sample Binning");
  TString histname1d = (XVarStr).c_str();
  TString histname2d = (XVarStr+"_"+YVarStr).c_str();
  TString histtitle = GetTitle();
 
  //The binning here is arbitrary, now we get info from cfg so the
  //set1DBinning and set2Dbinning calls below will make the binning
  //to be what we actually want
  _hPDF1D   = new TH1D("h" + histname1d + GetTitle(),histtitle, 1, 0, 1);
  dathist   = new TH1D("d" + histname1d + GetTitle(),histtitle, 1, 0, 1);
  _hPDF2D   = new TH2D("h" + histname2d + GetTitle(),histtitle, 1, 0, 1, 1, 0, 1);
  dathist2d = new TH2D("d" + histname2d + GetTitle(),histtitle, 1, 0, 1, 1, 0, 1);
 
  _hPDF1D->GetXaxis()->SetTitle(XVarStr.c_str());
  dathist->GetXaxis()->SetTitle(XVarStr.c_str());
  _hPDF2D->GetXaxis()->SetTitle(XVarStr.c_str());
  dathist2d->GetXaxis()->SetTitle(XVarStr.c_str());
 
  //A string to store the binning for a nice print out
  std::string XBinEdgesStr = "";
  std::string YBinEdgesStr = "";
 
  for(auto XBinEdge : Binning.XBinEdges){
    XBinEdgesStr += std::to_string(XBinEdge);
    XBinEdgesStr += ", ";
  }
  MACH3LOG_INFO("XBinning:");
  MACH3LOG_INFO("{}", XBinEdgesStr);
  
  //And now the YBin Edges
  for(auto YBinEdge : Binning.YBinEdges){
    YBinEdgesStr += std::to_string(YBinEdge);
    YBinEdgesStr += ", ";
  }
  MACH3LOG_INFO("YBinning:");
  MACH3LOG_INFO("{}", YBinEdgesStr);
  
  //Check whether you are setting up 1D or 2D binning
  if(nDimensions == 1){
    MACH3LOG_INFO("Setting up 1D binning with {}", XVarStr);
    Set1DBinning(Binning.XBinEdges);
  }
  else if(nDimensions == 2){
    MACH3LOG_INFO("Setting up 2D binning with {} and {}", XVarStr, YVarStr);
    Set2DBinning(Binning.XBinEdges, Binning.YBinEdges);
  }
  else{
    MACH3LOG_ERROR("Number of dimensions is not 1 or 2, this is unsupported at the moment");
    throw MaCh3Exception(__FILE__, __LINE__);
  }
}
 
// ************************************************
bool SampleHandlerFD::IsEventSelected(const int iEvent) {
// ************************************************
  const int SelectionSize = static_cast<int>(Selection.size());
  for (int iSelection = 0; iSelection < SelectionSize; ++iSelection) {
    const auto& Cut = Selection[iSelection];
    const double Val = ReturnKinematicParameter(Cut.ParamToCutOnIt, iEvent);
    if ((Val < Cut.LowerBound) || (Val >= Cut.UpperBound)) {
      return false;
    }
  }
  //DB To avoid unnecessary checks, now return false rather than setting bool to true and continuing to check
  return true;
}
 
// === JM Define function to check if sub-event is selected ===
bool SampleHandlerFD::IsSubEventSelected(const std::vector<KinematicCut> &SubEventCuts, const int iEvent, const unsigned int iSubEvent, size_t nsubevents) {
  for (unsigned int iSelection=0;iSelection < SubEventCuts.size() ;iSelection++) {
    std::vector<double> Vec = ReturnKinematicVector(SubEventCuts[iSelection].ParamToCutOnIt, iEvent);
    if (nsubevents != Vec.size()) {
      MACH3LOG_ERROR("Cannot apply kinematic cut on {} as it is of different size to plotting variable");
      throw MaCh3Exception(__FILE__, __LINE__);
    }
    const double Val = Vec[iSubEvent];
    if ((Val < SubEventCuts[iSelection].LowerBound) || (Val >= SubEventCuts[iSelection].UpperBound)) {
      return false;
    }
  }
  //DB To avoid unnecessary checks, now return false rather than setting bool to true and continuing to check
  return true;
}
// ===========================================================
 
//************************************************
// Reweight function
void SampleHandlerFD::Reweight() {
//************************************************
  //KS: Reset the histograms before reweight 
  ResetHistograms();
  
  //You only need to do these things if Oscillator has been initialised
  //if not then you're not considering oscillations
  if (Oscillator) Oscillator->Evaluate();
 
  // Calculate weight coming from all splines if we initialised handler
  if(SplineHandler) SplineHandler->Evaluate();
 
  #ifdef MULTITHREAD
  // Call entirely different routine if we're running with openMP
  FillArray_MP();
  #else
  FillArray();
  #endif
 
  //KS: If you want to not update W2 wights then uncomment this line
  if(!UpdateW2) FirstTimeW2 = false;
}
 
//************************************************
void SampleHandlerFD::FillArray() {
//************************************************
  //DB Reset which cuts to apply
  Selection = StoredSelection;
  
  PrepFunctionalParameters();
 
  for (unsigned int iEvent = 0; iEvent < GetNEvents(); iEvent++) {
    ApplyShifts(iEvent);
 
    if (!IsEventSelected(iEvent)) {
      continue;
    }
 
    FarDetectorCoreInfo* MCEvent = &MCSamples[iEvent];
    M3::float_t splineweight = CalcWeightSpline(MCEvent);
    //DB Catch negative spline weights and skip any event with a negative event. Previously we would set weight to zero and continue but that is inefficient. Do this on a spline-by-spline basis
    if (splineweight <= 0.){
      MCEvent->xsec_w = 0.;
      continue;
    }
 
    //Loop over stored normalisation and function pointers
    M3::float_t normweight = CalcWeightNorm(MCEvent);
 
    // Virtual by default does nothing
    CalcWeightFunc(iEvent);
 
    MCEvent->xsec_w = splineweight*normweight;
 
    //DB Total weight
    M3::float_t totalweight = GetEventWeight(iEvent);
    //DB Catch negative weights and skip any event with a negative event
    if (totalweight <= 0.){
      MCEvent->xsec_w = 0.;
      continue;
    }
    //DB Switch on BinningOpt to allow different binning options to be implemented
    //The alternative would be to have inheritance based on BinningOpt
    const double XVar = *(MCEvent->x_var);
 
    //DB Find the relevant bin in the PDF for each event
    const int XBinToFill = Binning.FindXBin(XVar, MCEvent->NomXBin);
    const int YBinToFill = MCEvent->NomYBin;
 
    //DB Fill relevant part of thread array
    if (XBinToFill != -1 && YBinToFill != -1) {
      SampleHandlerFD_array[YBinToFill][XBinToFill] += totalweight;
      if (FirstTimeW2) SampleHandlerFD_array_w2[YBinToFill][XBinToFill] += totalweight*totalweight;
    }
  }
}
 
#ifdef MULTITHREAD
// ************************************************ 
void SampleHandlerFD::FillArray_MP() {
// ************************************************
  //DB Reset which cuts to apply
  Selection = StoredSelection;
 
  PrepFunctionalParameters();
 
  //This is stored as [y][x] due to shifts only occurring in the x variable (Erec/Lep mom) - I believe this will help reduce cache misses
  double** SampleHandlerFD_array_private = nullptr;
  double** SampleHandlerFD_array_private_w2 = nullptr;
  // Declare the omp parallel region
  // The parallel region needs to stretch beyond the for loop!
  #pragma omp parallel private(SampleHandlerFD_array_private, SampleHandlerFD_array_private_w2)
  {
    // private to each thread
    // ETA - maybe we can use parallel firstprivate to initialise these?
    SampleHandlerFD_array_private = new double*[Binning.nYBins];
    SampleHandlerFD_array_private_w2 = new double*[Binning.nYBins];
    for (size_t yBin=0;yBin<Binning.nYBins; ++yBin) {
      SampleHandlerFD_array_private[yBin] = new double[Binning.nXBins];
      SampleHandlerFD_array_private_w2[yBin] = new double[Binning.nXBins];
 
      std::fill_n(SampleHandlerFD_array_private[yBin], Binning.nXBins, 0.0);
      std::fill_n(SampleHandlerFD_array_private_w2[yBin], Binning.nXBins, 0.0);
    }
    
    //DB - Brain dump of speedup ideas
    //
    //Those relevant to reweighting
    // 1. Don't bother storing and calculating NC signal events - Implemented and saves marginal s/step
    // 2. Loop over spline event weight calculation in the following event loop - Currently done in splineSKBase->calcWeight() where multi-threading won't be optimised - Implemented and saves 0.3s/step
    // 3. Inline getDiscVar or somehow include that calculation inside the multi-threading - Implemented and saves about 0.01s/step
    // 4. Include isCC inside SKMCStruct so don't have to have several 'if' statements determine if oscillation weight needs to be set to 1.0 for NC events - Implemented and saves marginal s/step
    // 5. Do explicit check on adjacent bins when finding event XBin instead of looping over all BinEdge indices - Implemented but doesn't significantly affect s/step
    //
    //Other aspects
    // 1. Order minituples in Y-axis variable as this will *hopefully* reduce cache misses inside SampleHandlerFD_array_class[yBin][xBin]
    //
    // We will hit <0.1 s/step eventually! :D
 
    const unsigned int NumberOfEvents = GetNEvents();
    #pragma omp for
    for (unsigned int iEvent = 0; iEvent < NumberOfEvents; ++iEvent) {
      //ETA - generic functions to apply shifts to kinematic variables
      // Apply this before IsEventSelected is called.
      ApplyShifts(iEvent);
 
      //ETA - generic functions to apply shifts to kinematic variable
      //this is going to be slow right now due to string comps under the hood.
      //Need to implement a more efficient version of event-by-event cut checks
      if(!IsEventSelected(iEvent)){
        continue;
      }
 
      //DB SKDet Syst
      //As weights were skdet::fParProp, and we use the non-shifted erec, we might as well cache the corresponding fParProp index for each event and the pointer to it
      FarDetectorCoreInfo* MCEvent = &MCSamples[iEvent];
      const M3::float_t splineweight = CalcWeightSpline(MCEvent);
      //DB Catch negative spline weights and skip any event with a negative event. Previously we would set weight to zero and continue but that is inefficient
      if (splineweight <= 0.){
        MCEvent->xsec_w = 0.;
        continue;
      }
 
      const M3::float_t normweight = CalcWeightNorm(MCEvent);
 
      // Virtual by default does nothing
      CalcWeightFunc(iEvent);
 
      MCEvent->xsec_w = splineweight*normweight;
 
      const M3::float_t totalweight = GetEventWeight(iEvent);
 
      //DB Catch negative weights and skip any event with a negative event
      if (totalweight <= 0.){
        MCEvent->xsec_w = 0.;
        continue;
      }
 
      //DB Switch on BinningOpt to allow different binning options to be implemented
      //The alternative would be to have inheritance based on BinningOpt
      const double XVar = (*(MCEvent->x_var));
 
      //DB Find the relevant bin in the PDF for each event
      const int XBinToFill = Binning.FindXBin(XVar, MCEvent->NomXBin);
      const int YBinToFill = MCEvent->NomYBin;
 
      //ETA - we can probably remove this final if check on the -1?
      //Maybe we can add an overflow bin to the array and assign any events to this bin?
      //Might save us an extra if call?
      //DB Fill relevant part of thread array
      if (XBinToFill != -1 && YBinToFill != -1) {
        SampleHandlerFD_array_private[YBinToFill][XBinToFill] += totalweight;
        SampleHandlerFD_array_private_w2[YBinToFill][XBinToFill] += totalweight*totalweight;
      }
    }
    //End of Calc Weights and fill Array
    //==================================================
    // DB Copy contents of 'SampleHandlerFD_array_private' into 'SampleHandlerFD_array' which can then be used in GetLikelihood
    for (size_t yBin = 0; yBin < Binning.nYBins; ++yBin) {
      for (size_t xBin = 0; xBin < Binning.nXBins; ++xBin) {
        #pragma omp atomic
        SampleHandlerFD_array[yBin][xBin] += SampleHandlerFD_array_private[yBin][xBin];
        if(FirstTimeW2) {
          #pragma omp atomic
          SampleHandlerFD_array_w2[yBin][xBin] += SampleHandlerFD_array_private_w2[yBin][xBin];
        }
      }
    }
    
    for (size_t yBin = 0; yBin < Binning.nYBins; ++yBin) {
      delete[] SampleHandlerFD_array_private[yBin];
      delete[] SampleHandlerFD_array_private_w2[yBin];
    }
    delete[] SampleHandlerFD_array_private;
    delete[] SampleHandlerFD_array_private_w2;
  } //end of parallel region
}
#endif
 
// **************************************************
// Helper function to reset the data and MC histograms
void SampleHandlerFD::ResetHistograms() {
// **************************************************  
  //DB Reset values stored in PDF array to 0.
  // Don't openMP this; no significant gain
  for (size_t yBin = 0; yBin < Binning.nYBins; ++yBin) {
    #ifdef MULTITHREAD
    #pragma omp simd
    #endif
    for (size_t xBin = 0; xBin < Binning.nXBins; ++xBin) {
      SampleHandlerFD_array[yBin][xBin] = 0.;
      if(FirstTimeW2) SampleHandlerFD_array_w2[yBin][xBin] = 0.;
    }
  }
} // end function
 
void SampleHandlerFD::RegisterIndividualFunctionalParameter(const std::string& fpName, int fpEnum, FuncParFuncType fpFunc){
  // Add protections to not add the same functional parameter twice
  if (funcParsNamesMap.find(fpName) != funcParsNamesMap.end()) {
    MACH3LOG_ERROR("Functional parameter {} already registered in funcParsNamesMap with enum {}", fpName, funcParsNamesMap[fpName]);
    throw MaCh3Exception(__FILE__, __LINE__);
  }
  if (std::find(funcParsNamesVec.begin(), funcParsNamesVec.end(), fpName) != funcParsNamesVec.end()) {
    MACH3LOG_ERROR("Functional parameter {} already in funcParsNamesVec", fpName);
    throw MaCh3Exception(__FILE__, __LINE__);
  }
  if (funcParsFuncMap.find(fpEnum) != funcParsFuncMap.end()) {
    MACH3LOG_ERROR("Functional parameter enum {} already registered in funcParsFuncMap", fpEnum);
    throw MaCh3Exception(__FILE__, __LINE__);
  }
  funcParsNamesMap[fpName] = fpEnum;
  funcParsNamesVec.push_back(fpName);
  funcParsFuncMap[fpEnum] = fpFunc;
}
 
void SampleHandlerFD::SetupFunctionalParameters() {
  funcParsVec = ParHandler->GetFunctionalParametersFromSampleName(SampleName);
  // RegisterFunctionalParameters is implemented in experiment-specific code, 
  // which calls RegisterIndividualFuncPar to populate funcParsNamesMap, funcParsNamesVec, and funcParsFuncMap
  RegisterFunctionalParameters();
  funcParsMap.resize(funcParsNamesMap.size());
  funcParsGrid.resize(GetNEvents());
 
  // For every functional parameter in XsecCov that matches the name in funcParsNames, add it to the map
  for (FunctionalParameter & fp : funcParsVec) {
    for (std::string name : funcParsNamesVec) {
      if (fp.name == name) {
        MACH3LOG_INFO("Adding functional parameter: {} to funcParsMap with key: {}", fp.name, funcParsNamesMap[fp.name]);
        fp.funcPtr = &funcParsFuncMap[funcParsNamesMap[fp.name]];
        funcParsMap[static_cast<std::size_t>(funcParsNamesMap[fp.name])] = &fp;
        continue;
      }
    }
    // If we don't find a match, we need to throw an error
    if (funcParsMap[static_cast<std::size_t>(funcParsNamesMap[fp.name])] == nullptr) {
      MACH3LOG_ERROR("Functional parameter {} not found, did you define it in RegisterFunctionalParameters()?", fp.name);
      throw MaCh3Exception(__FILE__, __LINE__);
    }
  }
 
  // Mostly the same as CalcXsecNormsBins
  // For each event, make a vector of pointers to the functional parameters
  for (std::size_t iEvent = 0; iEvent < static_cast<std::size_t>(GetNEvents()); ++iEvent) {
    // Now loop over the functional parameters and get a vector of enums corresponding to the functional parameters
    for (std::vector<FunctionalParameter>::iterator it = funcParsVec.begin(); it != funcParsVec.end(); ++it) {
      // Check whether the interaction modes match
      bool ModeMatch = MatchCondition((*it).modes, static_cast<int>(std::round(*(MCSamples[iEvent].mode))));
      if (!ModeMatch) {
        MACH3LOG_TRACE("Event {}, missed Mode check ({}) for dial {}", iEvent, *(MCSamples[iEvent].mode), (*it).name);
        continue;
      }
      // Now check whether within kinematic bounds
      bool IsSelected = true;
      if ((*it).hasKinBounds) {
        const auto& kinVars = (*it).KinematicVarStr;
        const auto& selection = (*it).Selection;
 
        for (std::size_t iKinPar = 0; iKinPar < kinVars.size(); ++iKinPar) {
          const double kinVal = ReturnKinematicParameter(kinVars[iKinPar], static_cast<int>(iEvent));
 
          bool passedAnyBound = false;
          const auto& boundsList = selection[iKinPar];
 
          for (const auto& bounds : boundsList) {
            if (kinVal > bounds[0] && kinVal <= bounds[1]) {
              passedAnyBound = true;
              break;
            }
          }
 
          if (!passedAnyBound) {
            MACH3LOG_TRACE("Event {}, missed kinematic check ({}) for dial {}",
                           iEvent, kinVars[iKinPar], (*it).name);
            IsSelected = false;
            break;
          }
        }
      }
      // Need to then break the event loop
      if(!IsSelected){
        MACH3LOG_TRACE("Event {}, missed Kinematic var check for dial {}", iEvent, (*it).name);
        continue;
      }
      auto funcparenum = funcParsNamesMap[(*it).name];
      funcParsGrid.at(iEvent).push_back(funcparenum);
    }
  }
  MACH3LOG_INFO("Finished setting up functional parameters");
}
 
void SampleHandlerFD::ApplyShifts(int iEvent) {
  // Given a sample and event, apply the shifts to the event based on the vector of functional parameter enums
  // First reset shifted array back to nominal values
  resetShifts(iEvent);
 
  const std::vector<int>& fpEnums = funcParsGrid[iEvent];
  const std::size_t nShifts = fpEnums.size();
 
  for (std::size_t i = 0; i < nShifts; ++i) {
    const int fpEnum = fpEnums[i];
    FunctionalParameter *fp = funcParsMap[static_cast<std::size_t>(fpEnum)];
    // if (fp->funcPtr) {
    //   (*fp->funcPtr)(fp->valuePtr, iEvent);
    // } else {
    //   MACH3LOG_ERROR("Functional parameter function pointer for {} is null for event {} in sample {}", fp->name, iEvent);
    //   throw MaCh3Exception(__FILE__, __LINE__);
    // }
    (*fp->funcPtr)(fp->valuePtr, iEvent);
  }
}
 
// ***************************************************************************
// Calculate the spline weight for one event
M3::float_t SampleHandlerFD::CalcWeightSpline(const FarDetectorCoreInfo* MCEvent) const {
// ***************************************************************************
  M3::float_t spline_weight = 1.0;
  const int nSplines = static_cast<int>(MCEvent->xsec_spline_pointers.size());
  //DB Xsec syst
  //Loop over stored spline pointers
  #ifdef MULTITHREAD
  #pragma omp simd
  #endif
  for (int iSpline = 0; iSpline < nSplines; ++iSpline) {
    spline_weight *= *(MCEvent->xsec_spline_pointers[iSpline]);
  }
  return spline_weight;
}
 
// ***************************************************************************
// Calculate the normalisation weight for an event
M3::float_t SampleHandlerFD::CalcWeightNorm(const FarDetectorCoreInfo* MCEvent) const {
// ***************************************************************************
  M3::float_t xsecw = 1.0;
  const int nNorms = static_cast<int>(MCEvent->xsec_norm_pointers.size());
  //Loop over stored normalisation and function pointers
  #ifdef MULTITHREAD
  #pragma omp simd
  #endif
  for (int iParam = 0; iParam < nNorms; ++iParam)
  {
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wuseless-cast"
    xsecw *= static_cast<M3::float_t>(*(MCEvent->xsec_norm_pointers[iParam]));
#pragma GCC diagnostic pop
    #ifdef DEBUG
    if (std::isnan(xsecw)) MACH3LOG_WARN("iParam= {} xsecweight=nan from norms", iParam);
    #endif
  }
  return xsecw;
}
 
// ***************************************************************************
// Setup the norm parameters
void SampleHandlerFD::SetupNormParameters() {
// ***************************************************************************
  std::vector< std::vector< int > > xsec_norms_bins(GetNEvents());
 
  std::vector<NormParameter> norm_parameters = ParHandler->GetNormParsFromSampleName(GetSampleName());
 
  if(!ParHandler){
    MACH3LOG_ERROR("ParHandler is not setup!");
    throw MaCh3Exception(__FILE__ , __LINE__ );
  }
 
  // Assign xsec norm bins in MCSamples tree
  CalcNormsBins(norm_parameters, xsec_norms_bins);
 
  //DB Attempt at reducing impact of SystematicHandlerGeneric::calcReweight()
  int counter;
  for (unsigned int iEvent = 0; iEvent < GetNEvents(); ++iEvent) {
    counter = 0;
 
    MCSamples[iEvent].xsec_norm_pointers.resize(xsec_norms_bins[iEvent].size());
    for(auto const & norm_bin: xsec_norms_bins[iEvent]) {
      MCSamples[iEvent].xsec_norm_pointers[counter] = ParHandler->RetPointer(norm_bin);
      counter += 1;
    }
  }
}
 
// ************************************************
//A way to check whether a normalisation parameter applies to an event or not
void SampleHandlerFD::CalcNormsBins(std::vector<NormParameter>& norm_parameters, std::vector< std::vector< int > >& xsec_norms_bins) {
// ************************************************
  #ifdef DEBUG
  std::vector<int> VerboseCounter(norm_parameters.size(), 0);
  #endif
  for(unsigned int iEvent = 0; iEvent < GetNEvents(); ++iEvent){
    std::vector< int > NormBins = {};
    if (ParHandler) {
      // Skip oscillated NC events
      // Not strictly needed, but these events don't get included in oscillated predictions, so
      // no need to waste our time calculating and storing information about xsec parameters
      // that will never be used.
      if (MCSamples[iEvent].isNC && (*MCSamples[iEvent].nupdg != *MCSamples[iEvent].nupdgUnosc) ) {
        MACH3LOG_TRACE("Event {}, missed NC/signal check", iEvent);
        continue;
      } //DB Abstract check on MaCh3Modes to determine which apply to neutral current
      for (std::vector<NormParameter>::iterator it = norm_parameters.begin(); it != norm_parameters.end(); ++it) {
        //Now check that the target of an interaction matches with the normalisation parameters
        bool TargetMatch = MatchCondition((*it).targets, *(MCSamples[iEvent].Target));
        if (!TargetMatch) {
          MACH3LOG_TRACE("Event {}, missed target check ({}) for dial {}", iEvent, *(MCSamples[iEvent].Target), (*it).name);
          continue;
        }
 
        //Now check that the neutrino flavour in an interaction matches with the normalisation parameters
        bool FlavourMatch = MatchCondition((*it).pdgs, *(MCSamples[iEvent].nupdg));
        if (!FlavourMatch) {
          MACH3LOG_TRACE("Event {}, missed PDG check ({}) for dial {}", iEvent,(*MCSamples[iEvent].nupdg), (*it).name);
          continue;
        }
 
        //Now check that the unoscillated neutrino flavour in an interaction matches with the normalisation parameters
        bool FlavourUnoscMatch = MatchCondition((*it).preoscpdgs, *(MCSamples[iEvent].nupdgUnosc));
        if (!FlavourUnoscMatch){
          MACH3LOG_TRACE("Event {}, missed FlavourUnosc check ({}) for dial {}", iEvent,(*MCSamples[iEvent].nupdgUnosc), (*it).name);
          continue;
        }
 
        //Now check that the mode of an interaction matches with the normalisation parameters
        bool ModeMatch = MatchCondition((*it).modes, static_cast<int>(std::round(*(MCSamples[iEvent].mode))));
        if (!ModeMatch) {
          MACH3LOG_TRACE("Event {}, missed Mode check ({}) for dial {}", iEvent, *(MCSamples[iEvent].mode), (*it).name);
          continue;
        }
 
        //Now check whether the norm has kinematic bounds
        //i.e. does it only apply to events in a particular kinematic region?
        // Now check whether within kinematic bounds
        bool IsSelected = true;
        if ((*it).hasKinBounds) {
          const auto& kinVars = (*it).KinematicVarStr;
          const auto& selection = (*it).Selection;
 
          for (std::size_t iKinPar = 0; iKinPar < kinVars.size(); ++iKinPar) {
            const double kinVal = ReturnKinematicParameter(kinVars[iKinPar], static_cast<int>(iEvent));
 
            bool passedAnyBound = false;
            const auto& boundsList = selection[iKinPar];
 
            for (const auto& bounds : boundsList) {
              if (kinVal > bounds[0] && kinVal <= bounds[1]) {
                passedAnyBound = true;
                break;
              }
            }
 
            if (!passedAnyBound) {
              MACH3LOG_TRACE("Event {}, missed kinematic check ({}) for dial {}",
                             iEvent, kinVars[iKinPar], (*it).name);
              IsSelected = false;
              break;
            }
          }
        }
        // Need to then break the event loop
        if(!IsSelected){
          MACH3LOG_TRACE("Event {}, missed Kinematic var check for dial {}", iEvent, (*it).name);
          continue;
        }
        // Now set 'index bin' for each normalisation parameter
        // All normalisations are just 1 bin for 2015, so bin = index (where index is just the bin for that normalisation)
        int bin = (*it).index;
 
        NormBins.push_back(bin);
        MACH3LOG_TRACE("Event {}, will be affected by dial {}", iEvent, (*it).name);
        #ifdef DEBUG
        VerboseCounter[std::distance(norm_parameters.begin(), it)]++;
        #endif
        //}
      } // end iteration over norm_parameters
    } // end if (ParHandler)
    xsec_norms_bins[iEvent] = NormBins;
  }//end loop over events
  #ifdef DEBUG
  MACH3LOG_DEBUG("┌──────────────────────────────────────────────────────────┐");
  for (std::size_t i = 0; i < norm_parameters.size(); ++i) {
    const auto& norm = norm_parameters[i];
    double eventRatio = static_cast<double>(VerboseCounter[i]) / static_cast<double>(GetNEvents());
 
    MACH3LOG_DEBUG("│ Param {:<15}, affects {:<8} events ({:>6.2f}%) │",
                  ParHandler->GetParFancyName(norm.index), VerboseCounter[i], eventRatio);
  }
  MACH3LOG_DEBUG("└──────────────────────────────────────────────────────────┘");
  #endif
}
 
// ************************************************
void SampleHandlerFD::SetupReweightArrays(const size_t numberXBins, const size_t numberYBins) {
// ************************************************
  //Set the number of X and Y bins now
  Binning.nXBins = numberXBins;
  Binning.nYBins = numberYBins;
 
  SampleHandlerFD_array = new double*[Binning.nYBins];
  SampleHandlerFD_array_w2 = new double*[Binning.nYBins];
  SampleHandlerFD_data = new double*[Binning.nYBins];
  for (size_t yBin=0;yBin<Binning.nYBins;yBin++) {
    SampleHandlerFD_array[yBin] = new double[Binning.nXBins];
    SampleHandlerFD_array_w2[yBin] = new double[Binning.nXBins];
    SampleHandlerFD_data[yBin] = new double[Binning.nXBins];
    for (size_t xBin=0;xBin<Binning.nXBins;xBin++) {
      SampleHandlerFD_array[yBin][xBin] = 0.;
      SampleHandlerFD_array_w2[yBin][xBin] = 0.;
      SampleHandlerFD_data[yBin][xBin] = 0.;
    }
  }
}
 
//ETA
//New versions of set binning functions is SampleHandlerBase
//so that we can set the values of the bin and lower/upper
//edges in the skmc_base. Hopefully we can use this to make
//fill1Dhist and fill2Dhist quicker
void SampleHandlerFD::Set1DBinning(size_t nbins, double* boundaries)
{
  _hPDF1D->Reset();
  _hPDF1D->SetBins(static_cast<int>(nbins),boundaries);
  dathist->SetBins(static_cast<int>(nbins),boundaries);
 
  Binning.YBinEdges = std::vector<double>(2);
  Binning.YBinEdges[0] = -1e8;
  Binning.YBinEdges[1] = 1e8;
 
  double YBinEdges_Arr[2];
  YBinEdges_Arr[0] = Binning.YBinEdges[0];
  YBinEdges_Arr[1] = Binning.YBinEdges[1];
 
  _hPDF2D->Reset();
  _hPDF2D->SetBins(static_cast<int>(nbins),boundaries,1,YBinEdges_Arr);
  dathist2d->SetBins(static_cast<int>(nbins),boundaries,1,YBinEdges_Arr);
 
  //Set the number of X and Y bins now
  SetupReweightArrays(Binning.XBinEdges.size() - 1, Binning.YBinEdges.size() - 1);
 
  FindNominalBinAndEdges1D();
}
 
void SampleHandlerFD::FindNominalBinAndEdges1D() {
  for(unsigned int event_i = 0; event_i < GetNEvents(); event_i++){
    //Set x_var and y_var values based on XVarStr and YVarStr
    MCSamples[event_i].x_var = GetPointerToKinematicParameter(XVarStr, event_i);
    if (std::isnan(*MCSamples[event_i].x_var) || std::isinf(*MCSamples[event_i].x_var)) {
      MACH3LOG_ERROR("X var for event {} is ill-defined and equal to {}", event_i, *MCSamples[event_i].x_var);
      throw MaCh3Exception(__FILE__, __LINE__);
    }
 
    //Give y_var M3::_BAD_DOUBLE_ value for the 1D case since this won't be used
    MCSamples[event_i].y_var = &(M3::_BAD_DOUBLE_);
    int bin = _hPDF1D->FindBin(*(MCSamples[event_i].x_var));
 
    if ((bin-1) >= 0 && (bin-1) < int(Binning.XBinEdges.size()-1)) {
      MCSamples[event_i].NomXBin = bin-1;
    } else {
      MCSamples[event_i].NomXBin = -1;
    }
    MCSamples[event_i].NomYBin = 0;
  }
 
  Binning.rw_lower_xbinedge.resize(Binning.nXBins);
  Binning.rw_lower_lower_xbinedge.resize(Binning.nXBins);
  Binning.rw_upper_xbinedge.resize(Binning.nXBins);
  Binning.rw_upper_upper_xbinedge.resize(Binning.nXBins);
  //Set rw_pdf_bin and rw_upper_xbinedge and rw_lower_xbinedge for each skmc_base
  for(size_t bin_x = 0; bin_x < Binning.nXBins; bin_x++){
    double low_lower_edge = M3::_DEFAULT_RETURN_VAL_;
    double low_edge = Binning.XBinEdges[bin_x];
    double upper_edge = Binning.XBinEdges[bin_x+1];
    double upper_upper_edge = M3::_DEFAULT_RETURN_VAL_;
 
    if (bin_x == 0) {
      low_lower_edge = Binning.XBinEdges[0];
    } else {
      low_lower_edge = Binning.XBinEdges[bin_x-1];
    }
 
    if (bin_x + 2 < Binning.nXBins) {
      upper_upper_edge = Binning.XBinEdges[bin_x + 2];
    } else if (bin_x + 1 < Binning.nXBins) {
      upper_upper_edge = Binning.XBinEdges[bin_x + 1];
    }
 
    Binning.rw_lower_xbinedge[bin_x] = low_edge;
    Binning.rw_upper_xbinedge[bin_x] = upper_edge;
    Binning.rw_lower_lower_xbinedge[bin_x] = low_lower_edge;
    Binning.rw_upper_upper_xbinedge[bin_x] = upper_upper_edge;
  }
}
 
void SampleHandlerFD::Set2DBinning(size_t nbins1, double* boundaries1, size_t nbins2, double* boundaries2)
{
  _hPDF1D->Reset();
  _hPDF1D->SetBins(static_cast<int>(nbins1),boundaries1);
  dathist->SetBins(static_cast<int>(nbins1),boundaries1);
 
  _hPDF2D->Reset();
  _hPDF2D->SetBins(static_cast<int>(nbins1),boundaries1,static_cast<int>(nbins2),boundaries2);
  dathist2d->SetBins(static_cast<int>(nbins1),boundaries1,static_cast<int>(nbins2),boundaries2);
  
  //Set the number of X and Y bins now
  SetupReweightArrays(Binning.XBinEdges.size() - 1, Binning.YBinEdges.size() - 1);
 
  FindNominalBinAndEdges2D();
}
 
// ************************************************
void SampleHandlerFD::FindNominalBinAndEdges2D() {
// ************************************************
  for(unsigned int event_i = 0 ; event_i < GetNEvents(); event_i++) {
    //Set x_var and y_var values based on XVarStr and YVarStr
    MCSamples[event_i].x_var = GetPointerToKinematicParameter(XVarStr, event_i);
    MCSamples[event_i].y_var = GetPointerToKinematicParameter(YVarStr, event_i);
 
    if (std::isnan(*MCSamples[event_i].x_var) || std::isinf(*MCSamples[event_i].x_var)) {
      MACH3LOG_ERROR("X var for event {} is ill-defined and equal to {}", event_i, *MCSamples[event_i].x_var);
      throw MaCh3Exception(__FILE__, __LINE__);
    }
    if (std::isnan(*MCSamples[event_i].y_var) || std::isinf(*MCSamples[event_i].y_var)) {
      MACH3LOG_ERROR("Y var for event {} is ill-defined and equal to {}", event_i, *MCSamples[event_i].y_var);
      throw MaCh3Exception(__FILE__, __LINE__);
    }
    //Global bin number
    int bin = _hPDF2D->FindBin(*(MCSamples[event_i].x_var), *(MCSamples[event_i].y_var));
 
    int bin_x = M3::_BAD_INT_;
    int bin_y = M3::_BAD_INT_;
    int bin_z = M3::_BAD_INT_;
    _hPDF2D->GetBinXYZ(bin, bin_x, bin_y, bin_z);
 
    if ((bin_x-1) >= 0 && (bin_x-1) < int(Binning.XBinEdges.size()-1)) {
      MCSamples[event_i].NomXBin = bin_x-1;
    }
    MCSamples[event_i].NomYBin = bin_y-1;
    if(MCSamples[event_i].NomYBin < 0){
      MACH3LOG_WARN("Nominal YBin PROBLEM, y-bin is {}", MCSamples[event_i].NomYBin);
    }
  }
 
  Binning.rw_lower_xbinedge.resize(Binning.nXBins);
  Binning.rw_lower_lower_xbinedge.resize(Binning.nXBins);
  Binning.rw_upper_xbinedge.resize(Binning.nXBins);
  Binning.rw_upper_upper_xbinedge.resize(Binning.nXBins);
  //Set rw_pdf_bin and rw_upper_xbinedge and rw_lower_xbinedge for each skmc_base
  for(size_t bin_x = 0; bin_x < Binning.nXBins; bin_x++){
    double low_lower_edge = M3::_DEFAULT_RETURN_VAL_;
    double low_edge = Binning.XBinEdges[bin_x];
    double upper_edge = Binning.XBinEdges[bin_x+1];
    double upper_upper_edge = M3::_DEFAULT_RETURN_VAL_;
 
    if (bin_x == 0) {
      low_lower_edge = Binning.XBinEdges[0];
    } else {
      low_lower_edge = Binning.XBinEdges[bin_x-1];
    }
 
    if (bin_x + 2 < Binning.nXBins) {
      upper_upper_edge = Binning.XBinEdges[bin_x + 2];
    } else if (bin_x + 1 < Binning.nXBins) {
      upper_upper_edge = Binning.XBinEdges[bin_x + 1];
    }
 
    Binning.rw_lower_xbinedge[bin_x] = low_edge;
    Binning.rw_upper_xbinedge[bin_x] = upper_edge;
    Binning.rw_lower_lower_xbinedge[bin_x] = low_lower_edge;
    Binning.rw_upper_upper_xbinedge[bin_x] = upper_upper_edge;
  }
}
 
// ************************************************
TH1* SampleHandlerFD::GetW2Hist(const int Dimension) {
// ************************************************
  if(Dimension == 1) {
    TH1D* W2Hist = dynamic_cast<TH1D*>(_hPDF1D->Clone((_hPDF1D->GetName() + std::string("_W2")).c_str()));
    W2Hist->Reset();
    for (unsigned int yBin = 0; yBin < (Binning.YBinEdges.size()-1); yBin++) {
      for (unsigned int xBin = 0; xBin < (Binning.XBinEdges.size()-1); xBin++) {
        W2Hist->AddBinContent(xBin+1, SampleHandlerFD_array_w2[yBin][xBin]);
      }
    }
    return W2Hist;
  } else if(Dimension == 2) {
    TH2D* W2Hist = dynamic_cast<TH2D*>(_hPDF2D->Clone((_hPDF2D->GetName() + std::string("_W2")).c_str()));
    W2Hist->Reset();
    for (unsigned int yBin = 0; yBin < (Binning.YBinEdges.size()-1); yBin++) {
      for (unsigned int xBin = 0; xBin < (Binning.XBinEdges.size()-1); xBin++) {
        W2Hist->SetBinContent(xBin+1, yBin+1, SampleHandlerFD_array_w2[yBin][xBin]);
      }
    }
    return W2Hist;
  } else{
    MACH3LOG_ERROR("Asking for {} with N Dimension = {}. This is not implemented", __func__, Dimension);
    throw MaCh3Exception(__FILE__, __LINE__);
  }
}
 
// ************************************************
TH1* SampleHandlerFD::GetMCHist(const int Dimension) {
// ************************************************
  if(Dimension == 1) {
    Fill1DHist();
    return _hPDF1D;
  } else if(Dimension == 2) {
    Fill2DHist();
    return _hPDF2D;
  } else{
    MACH3LOG_ERROR("Asdking for {} with N Dimension = {}. This is not implemented", __func__, Dimension);
    throw MaCh3Exception(__FILE__, __LINE__);
  }
}
 
// ************************************************
TH1* SampleHandlerFD::GetDataHist(const int Dimension) {
// ************************************************
  if(Dimension == 1) {
    return dathist;
  } else if(Dimension == 2) {
    return dathist2d;
  } else{
    MACH3LOG_ERROR("Asdking for {} with N Dimension = {}. This is not implemented", __func__, Dimension);
    throw MaCh3Exception(__FILE__, __LINE__);
  }
}
 
void SampleHandlerFD::AddData(std::vector<double> &data) {
  dathist2d = nullptr;
  dathist->Reset();
 
  if (GetNDim()!=1) {
    MACH3LOG_ERROR("Trying to set a 1D 'data' histogram when the number of dimensions for this sample is {}", GetNDim());
    MACH3LOG_ERROR("This won't work, please specify the correct dimensions in your sample config with the X and Y variables");
    throw MaCh3Exception(__FILE__, __LINE__);
  }
 
  for (auto const& data_point : data){
    dathist->Fill(data_point);
  }
 
  if(SampleHandlerFD_data == nullptr) {
    MACH3LOG_ERROR("SampleHandlerFD_data haven't been initialised yet");
    throw MaCh3Exception(__FILE__, __LINE__);
  }
  for (size_t yBin=0;yBin<Binning.nYBins;yBin++) {
    for (size_t xBin=0;xBin<Binning.nXBins;xBin++) {
      SampleHandlerFD_data[yBin][xBin] = dathist->GetBinContent(static_cast<int>(xBin+1));
    }
  }
}
 
void SampleHandlerFD::AddData(std::vector< std::vector <double> > &data) {
  dathist = nullptr;
  dathist2d->Reset();
 
  if (GetNDim()!=2) {
    MACH3LOG_ERROR("Trying to set a 2D 'data' histogram when the number of dimensions for this sample is {}", GetNDim());
    MACH3LOG_ERROR("This won't work, please specify the correct dimensions in your sample config with the X and Y variables");
    throw MaCh3Exception(__FILE__, __LINE__);
  }
 
  //TODO: this assumes that std::vector is of length 2 and then both data.at(0) and data
  //ETA: I think this might just be wrong? We should probably just make this AddData(std::vector<double> data_x, std::vector<double> data_y)
  // or maybe something like AddData(std::vector<std::pair<double, double>> data)?
  for (int i = 0; i < int(data.size()); i++) {
    dathist2d->Fill(data.at(0)[i],data.at(1)[i]);
  }
 
  if(SampleHandlerFD_data == nullptr) {
    MACH3LOG_ERROR("SampleHandlerFD_data haven't been initialised yet");
    throw MaCh3Exception(__FILE__, __LINE__);
  }
  for (size_t yBin=0;yBin<Binning.nYBins;yBin++) {
    for (size_t xBin=0;xBin<Binning.nXBins;xBin++) {
      //Need to cast to an int (Int_t) for ROOT
      //Need to do +1 for the bin, this is to be consistent with ROOTs binning scheme
      SampleHandlerFD_data[yBin][xBin] = dathist2d->GetBinContent(static_cast<int>(xBin+1),static_cast<int>(yBin+1));
    }
  }
}
 
void SampleHandlerFD::AddData(TH1D* Data) {
  MACH3LOG_INFO("Adding 1D data histogram: {} with {:.2f} events", Data->GetTitle(), Data->Integral());
  dathist2d = nullptr;
  dathist = static_cast<TH1D*>(Data->Clone());
 
  if (GetNDim() != 1) {
    MACH3LOG_ERROR("Trying to set a 1D 'data' histogram in a 2D sample - Quitting"); 
    MACH3LOG_ERROR("The number of dimensions for this sample is {}", GetNDim());
    throw MaCh3Exception(__FILE__ , __LINE__ );
  }
    
  if(SampleHandlerFD_data == nullptr) {
    MACH3LOG_ERROR("SampleHandlerFD_data haven't been initialised yet");
    throw MaCh3Exception(__FILE__, __LINE__);
  }
  for (size_t yBin=0;yBin<Binning.nYBins;yBin++) {
    for (size_t xBin=0;xBin<Binning.nXBins;xBin++) {
      //Need to cast to an int (Int_t) for ROOT
      //Need to do +1 for the bin, this is to be consistent with ROOTs binning scheme
      SampleHandlerFD_data[yBin][xBin] = Data->GetBinContent(static_cast<int>(xBin+1));
    }
  }
}
 
void SampleHandlerFD::AddData(TH2D* Data) {
  MACH3LOG_INFO("Adding 2D data histogram: {} with {:.2f} events", Data->GetTitle(), Data->Integral());
  dathist2d = static_cast<TH2D*>(Data->Clone());
  dathist = nullptr;
 
  if (GetNDim() != 2) {
    MACH3LOG_ERROR("Trying to set a 2D 'data' histogram in a 1D sample - Quitting"); 
    throw MaCh3Exception(__FILE__ , __LINE__ );}
   
  if(SampleHandlerFD_data == nullptr) {
    MACH3LOG_ERROR("SampleHandlerFD_data haven't been initialised yet");
    throw MaCh3Exception(__FILE__, __LINE__);
  }
  for (size_t yBin=0;yBin<Binning.nYBins;yBin++) {
    for (size_t xBin=0;xBin<Binning.nXBins;xBin++) {
      //Need to cast to an int (Int_t) for ROOT
      //Need to do +1 for the bin, this is to be consistent with ROOTs binning scheme
      SampleHandlerFD_data[yBin][xBin] = dathist2d->GetBinContent(static_cast<int>(xBin+1),static_cast<int>(yBin+1));
    }
  }
}
 
// ************************************************
void SampleHandlerFD::InitialiseNuOscillatorObjects() {
// ************************************************
  auto NuOscillatorConfigFile = Get<std::string>(SampleManager->raw()["NuOsc"]["NuOscConfigFile"], __FILE__ , __LINE__);
  auto EqualBinningPerOscChannel = Get<bool>(SampleManager->raw()["NuOsc"]["EqualBinningPerOscChannel"], __FILE__ , __LINE__);
 
  // TN override the sample setting if not using binned oscillation
  if (EqualBinningPerOscChannel) {
    if (YAML::LoadFile(NuOscillatorConfigFile)["General"]["CalculationType"].as<std::string>() == "Unbinned") {
      MACH3LOG_WARN("Tried using EqualBinningPerOscChannel while using Unbinned oscillation calculation, changing EqualBinningPerOscChannel to false");
      EqualBinningPerOscChannel = false;
    }
  }
  std::vector<const double*> OscParams = ParHandler->GetOscParsFromSampleName(SampleName);
  if (OscParams.empty()) {
    MACH3LOG_ERROR("OscParams is empty for sample '{}'.", GetTitle());
    MACH3LOG_ERROR("This likely indicates an error in your oscillation YAML configuration.");
    throw MaCh3Exception(__FILE__, __LINE__);
  }
  Oscillator = std::make_shared<OscillationHandler>(NuOscillatorConfigFile, EqualBinningPerOscChannel, OscParams, static_cast<int>(OscChannels.size()));
 
  if (!EqualBinningPerOscChannel) {
    for(int iChannel = 0; iChannel < static_cast<int>(OscChannels.size()); iChannel++) {
      std::vector<M3::float_t> EnergyArray;
      std::vector<M3::float_t> CosineZArray;
 
      for (unsigned int iEvent = 0; iEvent < GetNEvents(); iEvent++) {
        // KS: This is bit weird but we basically loop over all events and push to vector only these which are part of a given OscChannel
        const int Channel = GetOscChannel(OscChannels, (*MCSamples[iEvent].nupdgUnosc), (*MCSamples[iEvent].nupdg));
        //DB Remove NC events from the arrays which are handed to the NuOscillator objects
        if (!MCSamples[iEvent].isNC && Channel == iChannel) {
          EnergyArray.push_back(M3::float_t(*(MCSamples[iEvent].rw_etru)));
        }
      }
      std::sort(EnergyArray.begin(),EnergyArray.end());
 
      //============================================================================
      //DB Atmospheric only part, can only happen if truecz has been initialised within the experiment specific code
      if (*(MCSamples[0].rw_truecz) != M3::_BAD_DOUBLE_) {
        for (unsigned int iEvent = 0; iEvent < GetNEvents(); iEvent++) {
          // KS: This is bit weird but we basically loop over all events and push to vector only these which are part of a given OscChannel
          const int Channel = GetOscChannel(OscChannels, (*MCSamples[iEvent].nupdgUnosc), (*MCSamples[iEvent].nupdg));
          //DB Remove NC events from the arrays which are handed to the NuOscillator objects
          if (!MCSamples[iEvent].isNC && Channel == iChannel) {
            CosineZArray.push_back(M3::float_t(*(MCSamples[iEvent].rw_truecz)));
          }
        }
        std::sort(CosineZArray.begin(),CosineZArray.end());
      }
      Oscillator->SetOscillatorBinning(iChannel, EnergyArray, CosineZArray);
    } // end loop over channels
  }
}
 
void SampleHandlerFD::SetupNuOscillatorPointers() {
  for (unsigned int iEvent=0;iEvent<GetNEvents();iEvent++) {
    MCSamples[iEvent].osc_w_pointer = &M3::Unity;
    if (MCSamples[iEvent].isNC) {
      if (*MCSamples[iEvent].nupdg != *MCSamples[iEvent].nupdgUnosc) {
        MCSamples[iEvent].osc_w_pointer = &M3::Zero;
      } else {
        MCSamples[iEvent].osc_w_pointer = &M3::Unity;
      }
    } else {
      int InitFlav = M3::_BAD_INT_;
      int FinalFlav = M3::_BAD_INT_;
 
      InitFlav =  MaCh3Utils::PDGToNuOscillatorFlavour((*MCSamples[iEvent].nupdgUnosc));
      FinalFlav = MaCh3Utils::PDGToNuOscillatorFlavour((*MCSamples[iEvent].nupdg));
 
      if (InitFlav == M3::_BAD_INT_ || FinalFlav == M3::_BAD_INT_) {
        MACH3LOG_ERROR("Something has gone wrong in the mapping between MCSamples.nutype and the enum used within NuOscillator");
        MACH3LOG_ERROR("MCSamples.nupdgUnosc: {}", (*MCSamples[iEvent].nupdgUnosc));
        MACH3LOG_ERROR("InitFlav: {}", InitFlav);
        MACH3LOG_ERROR("MCSamples.nupdg: {}", (*MCSamples[iEvent].nupdg));
        MACH3LOG_ERROR("FinalFlav: {}", FinalFlav);
        throw MaCh3Exception(__FILE__, __LINE__);
      }
 
      const int OscIndex = GetOscChannel(OscChannels, (*MCSamples[iEvent].nupdgUnosc), (*MCSamples[iEvent].nupdg));
      //Can only happen if truecz has been initialised within the experiment specific code
      if (*(MCSamples[iEvent].rw_truecz) != M3::_BAD_DOUBLE_) {
        //Atmospherics
        MCSamples[iEvent].osc_w_pointer = Oscillator->GetNuOscillatorPointers(OscIndex, InitFlav, FinalFlav, FLOAT_T(*(MCSamples[iEvent].rw_etru)), FLOAT_T(*(MCSamples[iEvent].rw_truecz)));
      } else {
        //Beam
        MCSamples[iEvent].osc_w_pointer = Oscillator->GetNuOscillatorPointers(OscIndex, InitFlav, FinalFlav, FLOAT_T(*(MCSamples[iEvent].rw_etru)));
      }
    } // end if NC
  } // end loop over events
}
 
std::string SampleHandlerFD::GetSampleName(int iSample) const {
  //ETA - this is just to suppress a warning for an unused variable
  (void)iSample;
 
  //ETA - extra safety to make sure SampleName is actually set
  // probably unnecessary due to the requirement for it to be in the yaml config
  if(SampleName.length() == 0){
    MACH3LOG_ERROR("No sample name provided");
    MACH3LOG_ERROR("Please provide a SampleName in your configuration file: {}", SampleManager->GetFileName());
    throw MaCh3Exception(__FILE__, __LINE__);
  }
  return SampleName;
}
 
M3::float_t SampleHandlerFD::GetEventWeight(const int iEntry) const {
  M3::float_t totalweight = 1.0;
  const int nParams = static_cast<int>(MCSamples[iEntry].total_weight_pointers.size());
  #ifdef MULTITHREAD
  #pragma omp simd
  #endif
  for (int iParam = 0; iParam < nParams; ++iParam) {
    totalweight *= *(MCSamples[iEntry].total_weight_pointers[iParam]);
  }
 
  return totalweight;
}
 
void SampleHandlerFD::FillSplineBins() {
  //Now loop over events and get the spline bin for each event
  for (unsigned int j = 0; j < GetNEvents(); ++j) {
    const int OscIndex = GetOscChannel(OscChannels, (*MCSamples[j].nupdgUnosc), (*MCSamples[j].nupdg));
 
    std::vector< std::vector<int> > EventSplines;
    switch(nDimensions){
      case 1:
        EventSplines = SplineHandler->GetEventSplines(GetSampleName(), OscIndex, int(*(MCSamples[j].mode)), *(MCSamples[j].rw_etru), *(MCSamples[j].x_var), 0.);
        break;
      case 2:
        EventSplines = SplineHandler->GetEventSplines(GetSampleName(), OscIndex, int(*(MCSamples[j].mode)), *(MCSamples[j].rw_etru), *(MCSamples[j].x_var), *(MCSamples[j].y_var));
        break;
      default:
        MACH3LOG_ERROR("Error in assigning spline bins because nDimensions = {}", nDimensions);
        MACH3LOG_ERROR("MaCh3 only supports splines binned in Etrue + the sample binning");
        MACH3LOG_ERROR("Please check the sample binning you specified in your sample config ");
        throw MaCh3Exception(__FILE__, __LINE__);
        break;
    }
    int NSplines = int(EventSplines.size());
    if(NSplines < 0){
      throw MaCh3Exception(__FILE__, __LINE__);
    }
    MCSamples[j].xsec_spline_pointers.resize(NSplines);
    for(size_t spline = 0; spline < MCSamples[j].xsec_spline_pointers.size(); spline++) {
      //Event Splines indexed as: sample name, oscillation channel, syst, mode, etrue, var1, var2 (var2 is a dummy 0 for 1D splines)
      MCSamples[j].xsec_spline_pointers[spline] = SplineHandler->retPointer(EventSplines[spline][0], EventSplines[spline][1],
                                                                                EventSplines[spline][2], EventSplines[spline][3],
                                                                                EventSplines[spline][4], EventSplines[spline][5],
                                                                                EventSplines[spline][6]);
    }
  }
}
 
// ************************************************
double SampleHandlerFD::GetLikelihood() {
// ************************************************
  if (SampleHandlerFD_data == nullptr) {
    MACH3LOG_ERROR("Data sample is empty! Can't calculate a likelihood!");
    throw MaCh3Exception(__FILE__, __LINE__);
  }
    
  double negLogL = 0.;
  #ifdef MULTITHREAD
  #pragma omp parallel for collapse(2) reduction(+:negLogL)
  #endif
  for (size_t yBin = 0; yBin < Binning.nYBins; ++yBin)
  {
    for (size_t xBin = 0; xBin < Binning.nXBins; ++xBin)
    {
      const double DataVal = SampleHandlerFD_data[yBin][xBin];
      const double MCPred = SampleHandlerFD_array[yBin][xBin];
      const double w2 = SampleHandlerFD_array_w2[yBin][xBin];
      
      //KS: Calculate likelihood using Barlow-Beeston Poisson or even IceCube
      negLogL += GetTestStatLLH(DataVal, MCPred, w2);
    }
  }
  return negLogL;
}
 
void SampleHandlerFD::InitialiseSingleFDMCObject() {
  MCSamples.resize(nEvents);
}
 
 
// ************************************************
void SampleHandlerFD::SaveAdditionalInfo(TDirectory* Dir) {
// ************************************************
  Dir->cd();
 
  YAML::Node Config = SampleManager->raw();
  TMacro ConfigSave = YAMLtoTMacro(Config, (std::string("Config_") + GetTitle()));
  ConfigSave.Write();
 
  std::unique_ptr<TH1> data_hist;
 
  if (GetNDim() == 1) {
    data_hist = M3::Clone<TH1D>(dynamic_cast<TH1D*>(GetDataHist(1)), "data_" + GetTitle());
    data_hist->GetXaxis()->SetTitle(XVarStr.c_str());
    data_hist->GetYaxis()->SetTitle("Number of Events");
  } else if (GetNDim() == 2) {
    data_hist = M3::Clone<TH2D>(dynamic_cast<TH2D*>(GetDataHist(2)), "data_" + GetTitle());
    data_hist->GetXaxis()->SetTitle(XVarStr.c_str());
    data_hist->GetYaxis()->SetTitle(YVarStr.c_str());
    data_hist->GetZaxis()->SetTitle("Number of Events");
  } else {
    MACH3LOG_ERROR("Not implemented");
    throw MaCh3Exception(__FILE__, __LINE__);
  }
 
  if (!data_hist) {
    MACH3LOG_ERROR("nullptr data hist :(");
    throw MaCh3Exception(__FILE__, __LINE__);
  }
 
  data_hist->SetTitle(("data_" + GetTitle()).c_str());
  data_hist->Write();
}
 
void SampleHandlerFD::InitialiseSplineObject() {
  std::vector<std::string> spline_filepaths;
  for(unsigned iChannel = 0 ; iChannel < OscChannels.size() ; iChannel++){
    spline_filepaths.push_back(spline_files[iChannel]);
  }
 
  //Keep a track of the spline variables
  std::vector<std::string> SplineVarNames = {"TrueNeutrinoEnergy"};
  if(XVarStr.length() > 0){
    SplineVarNames.push_back(XVarStr);
  }
  if(YVarStr.length() > 0){
    SplineVarNames.push_back(YVarStr);
  }
  
  SplineHandler->AddSample(SampleName, spline_filepaths, SplineVarNames);
  SplineHandler->CountNumberOfLoadedSplines(false, 1);
  SplineHandler->TransferToMonolith();
 
  MACH3LOG_INFO("--------------------------------");
  MACH3LOG_INFO("Setup Far Detector splines");
 
  FillSplineBins();
 
  SplineHandler->cleanUpMemory();
}
 
// === JM adjust GetNDVarHist functions to allow for subevent-level plotting ===
TH1* SampleHandlerFD::Get1DVarHist(const std::string& ProjectionVar_Str, const std::vector< KinematicCut >& EventSelectionVec, 
    int WeightStyle, TAxis* Axis, const std::vector< KinematicCut >& SubEventSelectionVec) {
  //DB Need to overwrite the Selection member variable so that IsEventSelected function operates correctly.
  //   Consequently, store the selection cuts already saved in the sample, overwrite the Selection variable, then reset
  std::vector< KinematicCut > tmp_Selection = Selection;
  std::vector< KinematicCut > SelectionVecToApply;
 
  //DB Add all the predefined selections to the selection vector which will be applied
  for (size_t iSelec=0;iSelec<Selection.size();iSelec++) {
    SelectionVecToApply.emplace_back(Selection[iSelec]);
  }
 
  //DB Add all requested cuts from the argument to the selection vector which will be applied
  for (size_t iSelec=0;iSelec<EventSelectionVec.size();iSelec++) {
    SelectionVecToApply.emplace_back(EventSelectionVec[iSelec]);
  }
 
  //DB Set the member variable to be the cuts to apply
  Selection = SelectionVecToApply;
 
  //DB Define the histogram which will be returned
  TH1D* _h1DVar;
  if (Axis) {
    _h1DVar = new TH1D("","",Axis->GetNbins(),Axis->GetXbins()->GetArray());
  } else {
    std::vector<double> xBinEdges = ReturnKinematicParameterBinning(ProjectionVar_Str);
    _h1DVar = new TH1D("", "", int(xBinEdges.size())-1, xBinEdges.data());
  }
  
  if (IsSubEventVarString(ProjectionVar_Str)) {
    Fill1DSubEventHist(_h1DVar, ProjectionVar_Str, SubEventSelectionVec, WeightStyle);
  } else {
    //DB Grab the associated enum with the argument string
    int ProjectionVar_Int = ReturnKinematicParameterFromString(ProjectionVar_Str);
 
    //DB Loop over all events
    for (unsigned int iEvent = 0; iEvent < GetNEvents(); iEvent++) {
      if (IsEventSelected(iEvent)) {
        double Weight = GetEventWeight(iEvent);
        if (WeightStyle == 1) {
          Weight = 1.;
        }
        double Var = ReturnKinematicParameter(ProjectionVar_Int,iEvent);
        _h1DVar->Fill(Var,Weight);
      }
    }
  }
  //DB Reset the saved selection
  Selection = tmp_Selection;
 
  return _h1DVar;
}
 
void SampleHandlerFD::Fill1DSubEventHist(TH1D* _h1DVar, const std::string& ProjectionVar_Str, const std::vector< KinematicCut >& SubEventSelectionVec, int WeightStyle) {
  int ProjectionVar_Int = ReturnKinematicVectorFromString(ProjectionVar_Str);
 
  //JM Loop over all events
  for (unsigned int iEvent = 0; iEvent < GetNEvents(); iEvent++) {
    if (IsEventSelected(iEvent)) {
      double Weight = GetEventWeight(iEvent);
      if (WeightStyle == 1) {
        Weight = 1.;
      }
      std::vector<double> Vec = ReturnKinematicVector(ProjectionVar_Int,iEvent);
      size_t nsubevents = Vec.size();
      //JM Loop over all subevents in event
      for (unsigned int iSubEvent = 0; iSubEvent < nsubevents; iSubEvent++) {
        if (IsSubEventSelected(SubEventSelectionVec, iEvent, iSubEvent, nsubevents)) {
          double Var = Vec[iSubEvent];
          _h1DVar->Fill(Var,Weight);
        }
      }
    }
  }
}
 
// ************************************************
TH2* SampleHandlerFD::Get2DVarHist(const std::string& ProjectionVar_StrX, const std::string& ProjectionVar_StrY,
    const std::vector< KinematicCut >& EventSelectionVec, int WeightStyle, TAxis* AxisX, TAxis* AxisY, const std::vector< KinematicCut >& SubEventSelectionVec) {
// ************************************************
  //DB Need to overwrite the Selection member variable so that IsEventSelected function operates correctly.
  //   Consequently, store the selection cuts already saved in the sample, overwrite the Selection variable, then reset
  std::vector< KinematicCut > tmp_Selection = Selection;
  std::vector< KinematicCut > SelectionVecToApply;
 
  //DB Add all the predefined selections to the selection vector which will be applied
  for (size_t iSelec=0;iSelec<Selection.size();iSelec++) {
    SelectionVecToApply.emplace_back(Selection[iSelec]);
  }
 
  //DB Add all requested cuts from the argument to the selection vector which will be applied
  for (size_t iSelec=0;iSelec<EventSelectionVec.size();iSelec++) {
    SelectionVecToApply.emplace_back(EventSelectionVec[iSelec]);
  }
 
  //DB Set the member variable to be the cuts to apply
  Selection = SelectionVecToApply;
 
  //DB Define the histogram which will be returned
  TH2D* _h2DVar;
  if (AxisX && AxisY) {
    _h2DVar = new TH2D("","",AxisX->GetNbins(),AxisX->GetXbins()->GetArray(),AxisY->GetNbins(),AxisY->GetXbins()->GetArray());
  } else {
    std::vector<double> xBinEdges = ReturnKinematicParameterBinning(ProjectionVar_StrX);
    std::vector<double> yBinEdges = ReturnKinematicParameterBinning(ProjectionVar_StrY);
    _h2DVar = new TH2D("", "", int(xBinEdges.size())-1, xBinEdges.data(), int(yBinEdges.size())-1, yBinEdges.data());
  }
 
  bool IsSubEventHist = IsSubEventVarString(ProjectionVar_StrX) || IsSubEventVarString(ProjectionVar_StrY);
  if (IsSubEventHist) Fill2DSubEventHist(_h2DVar, ProjectionVar_StrX, ProjectionVar_StrY, SubEventSelectionVec, WeightStyle);
  else {
    //DB Grab the associated enum with the argument string
    int ProjectionVar_IntX = ReturnKinematicParameterFromString(ProjectionVar_StrX);
    int ProjectionVar_IntY = ReturnKinematicParameterFromString(ProjectionVar_StrY);
 
    //DB Loop over all events
    for (unsigned int iEvent = 0; iEvent < GetNEvents(); iEvent++) {
      if (IsEventSelected(iEvent)) {
        double Weight = GetEventWeight(iEvent);
        if (WeightStyle == 1) {
          Weight = 1.;
        }
        double VarX = ReturnKinematicParameter(ProjectionVar_IntX, iEvent);
        double VarY = ReturnKinematicParameter(ProjectionVar_IntY, iEvent);
        _h2DVar->Fill(VarX,VarY,Weight);
      }
    }
  }
  //DB Reset the saved selection
  Selection = tmp_Selection;
 
  return _h2DVar;
}
 
void SampleHandlerFD::Fill2DSubEventHist(TH2D* _h2DVar, const std::string& ProjectionVar_StrX, const std::string& ProjectionVar_StrY,
    const std::vector< KinematicCut >& SubEventSelectionVec, int WeightStyle) {
  bool IsSubEventVarX = IsSubEventVarString(ProjectionVar_StrX);
  bool IsSubEventVarY = IsSubEventVarString(ProjectionVar_StrY);   
 
  int ProjectionVar_IntX, ProjectionVar_IntY;
  if (IsSubEventVarX) ProjectionVar_IntX = ReturnKinematicVectorFromString(ProjectionVar_StrX);
  else ProjectionVar_IntX = ReturnKinematicParameterFromString(ProjectionVar_StrX);
  if (IsSubEventVarY) ProjectionVar_IntY = ReturnKinematicVectorFromString(ProjectionVar_StrY);
  else ProjectionVar_IntY = ReturnKinematicParameterFromString(ProjectionVar_StrY); 
 
  //JM Loop over all events
  for (unsigned int iEvent = 0; iEvent < GetNEvents(); iEvent++) {
    if (IsEventSelected(iEvent)) {
      double Weight = GetEventWeight(iEvent);
      if (WeightStyle == 1) {
        Weight = 1.;
      }
      std::vector<double> VecX = {}, VecY = {};
      double VarX = M3::_BAD_DOUBLE_, VarY = M3::_BAD_DOUBLE_;
      size_t nsubevents = 0;
      // JM Three cases: subeventX vs eventY || eventX vs subeventY || subeventX vs subeventY
      if (IsSubEventVarX && !IsSubEventVarY) {
        VecX = ReturnKinematicVector(ProjectionVar_IntX, iEvent);
        VarY = ReturnKinematicParameter(ProjectionVar_IntY, iEvent);
        nsubevents = VecX.size();
      }
      else if (!IsSubEventVarX && IsSubEventVarY) {
        VecY = ReturnKinematicVector(ProjectionVar_IntY, iEvent);
        VarX = ReturnKinematicParameter(ProjectionVar_IntX, iEvent);
        nsubevents = VecY.size();
      }
      else {
        VecX = ReturnKinematicVector(ProjectionVar_IntX, iEvent);
        VecY = ReturnKinematicVector(ProjectionVar_IntY, iEvent);
        if (VecX.size() != VecY.size()) {
          MACH3LOG_ERROR("Cannot plot {} of size {} against {} of size {}", ProjectionVar_StrX, VecX.size(), ProjectionVar_StrY, VecY.size());
          throw MaCh3Exception(__FILE__, __LINE__);
        }
        nsubevents = VecX.size();
      }
      //JM Loop over all subevents in event
      for (unsigned int iSubEvent = 0; iSubEvent < nsubevents; iSubEvent++) {
        if (IsSubEventSelected(SubEventSelectionVec, iEvent, iSubEvent, nsubevents)) {
          if (IsSubEventVarX) VarX = VecX[iSubEvent];
          if (IsSubEventVarY) VarY = VecY[iSubEvent];
          _h2DVar->Fill(VarX,VarY,Weight);
        }
      } 
    }
  }
}
// ================================================
 
// ************************************************
int SampleHandlerFD::ReturnKinematicParameterFromString(const std::string& KinematicParameterStr) const {
// ************************************************
  auto it = KinematicParameters->find(KinematicParameterStr);
  if (it != KinematicParameters->end()) return it->second;
 
  MACH3LOG_ERROR("Did not recognise Kinematic Parameter type: {}", KinematicParameterStr);
  throw MaCh3Exception(__FILE__, __LINE__);
 
  return M3::_BAD_INT_;
}
 
// ************************************************
std::string SampleHandlerFD::ReturnStringFromKinematicParameter(const int KinematicParameter) const {
// ************************************************
  auto it = ReversedKinematicParameters->find(KinematicParameter);
  if (it != ReversedKinematicParameters->end()) {
    return it->second;
  }
 
  MACH3LOG_ERROR("Did not recognise Kinematic Parameter type: {}", KinematicParameter);
  throw MaCh3Exception(__FILE__, __LINE__);
 
  return "";
}
 
// === JM define KinematicVector-to-string mapping functions  ===
// ************************************************
int SampleHandlerFD::ReturnKinematicVectorFromString(const std::string& KinematicVectorStr) const {
// ************************************************
  auto it = KinematicVectors->find(KinematicVectorStr);
  if (it != KinematicVectors->end()) return it->second;
 
  MACH3LOG_ERROR("Did not recognise Kinematic Vector: {}", KinematicVectorStr);
  throw MaCh3Exception(__FILE__, __LINE__);
 
  return M3::_BAD_INT_;
}
 
// ************************************************
std::string SampleHandlerFD::ReturnStringFromKinematicVector(const int KinematicVector) const {
// ************************************************
  auto it = ReversedKinematicVectors->find(KinematicVector);
  if (it != ReversedKinematicVectors->end()) {
    return it->second;
  }
 
  MACH3LOG_ERROR("Did not recognise Kinematic Vector: {}", KinematicVector);
  throw MaCh3Exception(__FILE__, __LINE__);
 
  return "";
}
 
// ************************************************
std::vector<double> SampleHandlerFD::ReturnKinematicParameterBinning(const std::string& KinematicParameter) {
// ************************************************
  // If x or y variable return used binning
  if(KinematicParameter == XVarStr) {
    return Binning.XBinEdges;
  } else if (KinematicParameter == YVarStr) {
    return Binning.YBinEdges;
  }
 
  auto MakeBins = [](int nBins) {
    std::vector<double> bins(nBins + 1);
    for (int i = 0; i <= nBins; ++i)
      bins[i] = static_cast<double>(i) - 0.5;
    return bins;
  };
 
  if (KinematicParameter == "OscillationChannel") {
    return MakeBins(GetNOscChannels());
  } else if (KinematicParameter == "Mode") {
    return MakeBins(Modes->GetNModes());
  }
 
  // We first check if binning for a sample has been specified
  auto BinningConfig = M3OpenConfig(SampleManager->raw()["BinningFile"].as<std::string>());
  if(BinningConfig[GetTitle()] && BinningConfig[GetTitle()][KinematicParameter]){
    auto BinningVect = Get<std::vector<double>>(BinningConfig[GetTitle()][KinematicParameter], __FILE__, __LINE__);
    return BinningVect;
  } else {
    auto BinningVect = Get<std::vector<double>>(BinningConfig[KinematicParameter], __FILE__, __LINE__);
    return BinningVect;
  }
}
 
 
bool SampleHandlerFD::IsSubEventVarString(const std::string& VarStr) {
  if (KinematicVectors == nullptr) return false;
 
  if (KinematicVectors->count(VarStr)) {
    if (!KinematicParameters->count(VarStr)) return true;
    else {
      MACH3LOG_ERROR("Attempted to plot kinematic variable {}, but it appears in both KinematicVectors and KinematicParameters", VarStr);
      throw MaCh3Exception(__FILE__,__LINE__);
    }
  }
  return false;
}
// ===============================================================
 
TH1* SampleHandlerFD::Get1DVarHistByModeAndChannel(const std::string& ProjectionVar_Str, 
    int kModeToFill, int kChannelToFill, int WeightStyle, TAxis* Axis) {
  bool fChannel;
  bool fMode;
 
  if (kChannelToFill != -1) {
    if (kChannelToFill > GetNOscChannels()) {
      MACH3LOG_ERROR("Required channel is not available. kChannelToFill should be between 0 and {}", GetNOscChannels());
      MACH3LOG_ERROR("kChannelToFill given:{}", kChannelToFill);
      MACH3LOG_ERROR("Exiting.");
      throw MaCh3Exception(__FILE__, __LINE__);
    }
    fChannel = true;
  } else {
    fChannel = false;
  }
 
  if (kModeToFill!=-1) {
    if (!(kModeToFill >= 0) && (kModeToFill < Modes->GetNModes())) {
      MACH3LOG_ERROR("Required mode is not available. kModeToFill should be between 0 and {}", Modes->GetNModes());
      MACH3LOG_ERROR("kModeToFill given:{}", kModeToFill);
      MACH3LOG_ERROR("Exiting..");
      throw MaCh3Exception(__FILE__, __LINE__);
    }
    fMode = true;
  } else {
    fMode = false;
  }
 
  std::vector< KinematicCut > SelectionVec;
 
  if (fMode) {
    KinematicCut SelecMode;
    SelecMode.ParamToCutOnIt = ReturnKinematicParameterFromString("Mode");
    SelecMode.LowerBound = kModeToFill;
    SelecMode.UpperBound = kModeToFill+1;
    SelectionVec.push_back(SelecMode);
  }
 
  if (fChannel) {
    KinematicCut SelecChannel;
    SelecChannel.ParamToCutOnIt = ReturnKinematicParameterFromString("OscillationChannel");
    SelecChannel.LowerBound = kChannelToFill;
    SelecChannel.UpperBound = kChannelToFill+1;
    SelectionVec.push_back(SelecChannel);
  }
 
  return Get1DVarHist(ProjectionVar_Str,SelectionVec,WeightStyle,Axis);
}
 
TH2* SampleHandlerFD::Get2DVarHistByModeAndChannel(const std::string& ProjectionVar_StrX, const std::string& ProjectionVar_StrY, 
    int kModeToFill, int kChannelToFill, int WeightStyle, TAxis* AxisX, TAxis* AxisY) {
  bool fChannel;
  bool fMode;
 
  if (kChannelToFill!=-1) {
    if (kChannelToFill > GetNOscChannels()) {
      MACH3LOG_ERROR("Required channel is not available. kChannelToFill should be between 0 and {}", GetNOscChannels());
      MACH3LOG_ERROR("kChannelToFill given:{}", kChannelToFill);
      MACH3LOG_ERROR("Exiting.");
      throw MaCh3Exception(__FILE__, __LINE__);
    }
    fChannel = true;
  } else {
    fChannel = false;
  }
 
  if (kModeToFill!=-1) {
    if (!(kModeToFill >= 0) && (kModeToFill < Modes->GetNModes())) {
      MACH3LOG_ERROR("Required mode is not available. kModeToFill should be between 0 and {}", Modes->GetNModes());
      MACH3LOG_ERROR("kModeToFill given:{}", kModeToFill);
      MACH3LOG_ERROR("Exiting..");
      throw MaCh3Exception(__FILE__, __LINE__);
    }
    fMode = true;
  } else {
    fMode = false;
  }
 
  std::vector< KinematicCut > SelectionVec;
 
  if (fMode) {
    KinematicCut SelecMode;
    SelecMode.ParamToCutOnIt = ReturnKinematicParameterFromString("Mode");
    SelecMode.LowerBound = kModeToFill;
    SelecMode.UpperBound = kModeToFill+1;
    SelectionVec.push_back(SelecMode);
  }
 
  if (fChannel) {
    KinematicCut SelecChannel;
    SelecChannel.ParamToCutOnIt = ReturnKinematicParameterFromString("OscillationChannel");
    SelecChannel.LowerBound = kChannelToFill;
    SelecChannel.UpperBound = kChannelToFill+1;
    SelectionVec.push_back(SelecChannel);
  }
 
  return Get2DVarHist(ProjectionVar_StrX,ProjectionVar_StrY,SelectionVec,WeightStyle,AxisX,AxisY);
}
 
void SampleHandlerFD::PrintIntegral(TString OutputFileName, int WeightStyle, TString OutputCSVFileName) {
  int space = 14;
 
  bool printToFile=false;
  if (OutputFileName.CompareTo("/dev/null")) {printToFile = true;}
 
  bool printToCSV=false;
  if(OutputCSVFileName.CompareTo("/dev/null")) printToCSV=true;
 
  std::ofstream outfile;
  if (printToFile) {
    outfile.open(OutputFileName.Data(), std::ios_base::app);
    outfile.precision(7);
  }
 
  std::ofstream outcsv;
  if(printToCSV){
    outcsv.open(OutputCSVFileName, std::ios_base::app); // Appened to CSV
    outcsv.precision(7);
  }
 
  double PDFIntegral = 0.;
 
  std::vector< std::vector< TH1* > > IntegralList;
  IntegralList.resize(Modes->GetNModes());
 
  std::vector<double> ChannelIntegral;
  ChannelIntegral.resize(GetNOscChannels());
  for (unsigned int i=0;i<ChannelIntegral.size();i++) {ChannelIntegral[i] = 0.;}
 
  for (int i=0;i<Modes->GetNModes();i++) {
    if (GetNDim()==1) {
      IntegralList[i] = ReturnHistsBySelection1D(XVarStr,1,i,WeightStyle);
    } else {
      IntegralList[i] = CastVector<TH2, TH1>(ReturnHistsBySelection2D(XVarStr,YVarStr,1,i,WeightStyle));
    }
  }
 
  MACH3LOG_INFO("-------------------------------------------------");
 
  if (printToFile) {
    outfile << "\\begin{table}[ht]" << std::endl;
    outfile << "\\begin{center}" << std::endl;
    outfile << "\\caption{Integral breakdown for sample: " << GetTitle() << "}" << std::endl;
    outfile << "\\label{" << GetTitle() << "-EventRate}" << std::endl;
 
    TString nColumns;
    for (int i=0;i<GetNOscChannels();i++) {nColumns+="|c";}
    nColumns += "|c|";
    outfile << "\\begin{tabular}{|l" << nColumns.Data() << "}" << std::endl;
    outfile << "\\hline" << std::endl;
  }
 
  if(printToCSV){
    // HW Probably a better way but oh well, here I go making MaCh3 messy again
    outcsv<<"Integral Breakdown for sample :"<<GetTitle()<<"\n";
  }
 
  MACH3LOG_INFO("Integral breakdown for sample: {}", GetTitle());
  MACH3LOG_INFO("");
 
  if (printToFile) {outfile << std::setw(space) << "Mode:";}
  if(printToCSV) {outcsv<<"Mode,";}
 
  std::string table_headings = fmt::format("| {:<8} |", "Mode");
  std::string table_footline = "------------"; //Scalable table horizontal line
  for (size_t i = 0;i < OscChannels.size(); i++) {
    table_headings += fmt::format(" {:<17} |", OscChannels[i].flavourName);
    table_footline += "--------------------";
    if (printToFile) {outfile << "&" << std::setw(space) << OscChannels[i].flavourName_Latex << " ";}
    if (printToCSV)  {outcsv << OscChannels[i].flavourName << ",";}
  }
  if (printToFile) {outfile << "&" << std::setw(space) << "Total:" << "\\\\ \\hline" << std::endl;}
  if (printToCSV)  {outcsv <<"Total\n";}
  table_headings += fmt::format(" {:<10} |", "Total");
  table_footline += "-------------";
 
  MACH3LOG_INFO("{}", table_headings);
  MACH3LOG_INFO("{}", table_footline);
 
  for (unsigned int i=0;i<IntegralList.size();i++) {
    double ModeIntegral = 0;
    if (printToFile) {outfile << std::setw(space) << Modes->GetMaCh3ModeName(i);}
    if(printToCSV)   {outcsv << Modes->GetMaCh3ModeName(i) << ",";}
 
    table_headings = fmt::format("| {:<8} |", Modes->GetMaCh3ModeName(i)); //Start string with mode name
 
    for (unsigned int j=0;j<IntegralList[i].size();j++) {
      double Integral = IntegralList[i][j]->Integral();
 
      if (Integral<1e-100) {Integral=0;}
 
      ModeIntegral += Integral;
      ChannelIntegral[j] += Integral;
      PDFIntegral += Integral;
 
      if (printToFile) {outfile << "&" << std::setw(space) << Form("%4.5f",Integral) << " ";}
      if (printToCSV)  {outcsv << Form("%4.5f", Integral) << ",";}
 
      table_headings += fmt::format(" {:<17.4f} |", Integral);
    }
    if (printToFile) {outfile << "&" << std::setw(space) << Form("%4.5f",ModeIntegral) <<  " \\\\ \\hline" << std::endl;}
    if (printToCSV)  {outcsv << Form("%4.5f", ModeIntegral) << "\n";}
 
    table_headings += fmt::format(" {:<10.4f} |", ModeIntegral);
 
    MACH3LOG_INFO("{}", table_headings);
  }
 
  if (printToFile) {outfile << std::setw(space) << "Total:";}
  if (printToCSV)  {outcsv << "Total,";}
 
  //Clear the table_headings to print last row of totals
  table_headings = fmt::format("| {:<8} |", "Total");
  for (unsigned int i=0;i<ChannelIntegral.size();i++) {
    if (printToFile) {outfile << "&" << std::setw(space) << Form("%4.5f",ChannelIntegral[i]) << " ";}
    if (printToCSV)  {outcsv << Form("%4.5f", ChannelIntegral[i]) << ",";}
    table_headings += fmt::format(" {:<17.4f} |", ChannelIntegral[i]);
  }
  if (printToFile) {outfile << "&" << std::setw(space) << Form("%4.5f",PDFIntegral) << " \\\\ \\hline" << std::endl;}
  if (printToCSV)  {outcsv << Form("%4.5f", PDFIntegral) << "\n\n\n\n";} // Let's have a few new lines!
 
  table_headings += fmt::format(" {:<10.4f} |", PDFIntegral);
  MACH3LOG_INFO("{}", table_headings);
  MACH3LOG_INFO("{}", table_footline);
 
  if (printToFile) {
    outfile << "\\end{tabular}" << std::endl;
    outfile << "\\end{center}" << std::endl;
    outfile << "\\end{table}" << std::endl;
  }
 
  MACH3LOG_INFO("");
 
  if (printToFile) {
    outfile << std::endl;
    outfile.close();
  }
}
 
std::vector<TH1*> SampleHandlerFD::ReturnHistsBySelection1D(std::string KinematicProjection, int Selection1, int Selection2, int WeightStyle, TAxis* XAxis) {
  std::vector<TH1*> hHistList;
  std::string legendEntry;
 
  if (THStackLeg != nullptr) {delete THStackLeg;}
  THStackLeg = new TLegend(0.1,0.1,0.9,0.9);
 
  int iMax = -1;
  if (Selection1 == 0) {
    iMax = Modes->GetNModes();
  }
  if (Selection1 == 1) {
    iMax = GetNOscChannels();
  }
  if (iMax == -1) {
    MACH3LOG_ERROR("You've passed me a Selection1 which was not implemented in ReturnHistsBySelection1D. Selection1 and Selection2 are counters for different indexable quantities");
    throw MaCh3Exception(__FILE__, __LINE__);
  }
 
  for (int i=0;i<iMax;i++) {
    if (Selection1==0) {
      hHistList.push_back(Get1DVarHistByModeAndChannel(KinematicProjection,i,Selection2,WeightStyle,XAxis));
      THStackLeg->AddEntry(hHistList[i],(Modes->GetMaCh3ModeName(i)+Form(" : (%4.2f)",hHistList[i]->Integral())).c_str(),"f");
 
      hHistList[i]->SetFillColor(static_cast<Color_t>(Modes->GetMaCh3ModePlotColor(i)));
      hHistList[i]->SetLineColor(static_cast<Color_t>(Modes->GetMaCh3ModePlotColor(i)));
    }
    if (Selection1==1) {
      hHistList.push_back(Get1DVarHistByModeAndChannel(KinematicProjection,Selection2,i,WeightStyle,XAxis));
      THStackLeg->AddEntry(hHistList[i],(OscChannels[i].flavourName+Form(" | %4.2f",hHistList[i]->Integral())).c_str(),"f");
    }
  }
 
  return hHistList;
}
 
std::vector<TH2*> SampleHandlerFD::ReturnHistsBySelection2D(std::string KinematicProjectionX, std::string KinematicProjectionY,
    int Selection1, int Selection2, int WeightStyle, 
    TAxis* XAxis, TAxis* YAxis) {
  std::vector<TH2*> hHistList;
 
  int iMax = -1;
  if (Selection1 == 0) {
    iMax = Modes->GetNModes();
  }
  if (Selection1 == 1) {
    iMax = GetNOscChannels();
  }
  if (iMax == -1) {
    MACH3LOG_ERROR("You've passed me a Selection1 which was not implemented in ReturnHistsBySelection1D. Selection1 and Selection2 are counters for different indexable quantities");
    throw MaCh3Exception(__FILE__, __LINE__);
  }
 
  for (int i=0;i<iMax;i++) {
    if (Selection1==0) {
      hHistList.push_back(Get2DVarHistByModeAndChannel(KinematicProjectionX,KinematicProjectionY,i,Selection2,WeightStyle,XAxis,YAxis));
    }
    if (Selection1==1) {
      hHistList.push_back(Get2DVarHistByModeAndChannel(KinematicProjectionX,KinematicProjectionY,Selection2,i,WeightStyle,XAxis,YAxis));
    }
  }
 
  return hHistList;
}
 
THStack* SampleHandlerFD::ReturnStackedHistBySelection1D(std::string KinematicProjection, int Selection1, int Selection2, int WeightStyle, TAxis* XAxis) {
  std::vector<TH1*> HistList = ReturnHistsBySelection1D(KinematicProjection, Selection1, Selection2, WeightStyle, XAxis);
  THStack* StackHist = new THStack((GetTitle()+"_"+KinematicProjection+"_Stack").c_str(),"");
  for (unsigned int i=0;i<HistList.size();i++) {
    StackHist->Add(HistList[i]);
  }
  return StackHist;
}
 
 
// ************************************************
const double* SampleHandlerFD::GetPointerToOscChannel(int iEvent) const {
// ************************************************
  const int Channel = GetOscChannel(OscChannels, (*MCSamples[iEvent].nupdgUnosc), (*MCSamples[iEvent].nupdg));
 
  return &(OscChannels[Channel].ChannelIndex);
}