void exampleTMVA_histogram() {


   // fill some histogram from signal and background
   auto hs1 = new TH1D("hs1","signal training histo",1000,-3,3);
   auto hs2 = new TH1D("hs2","signal test histo",1000,-3,3);
   auto hb1 = new TH1D("hb1","background training histo",1000,-3,3);
   auto hb2 = new TH1D("hb2","background test histo",1000,-3,3);

   auto f1 = new TF1("f1","gaus");
   f1->SetParameters(1,1,1);  // signal
   hs1->FillRandom("f1",10000);
   hs2->FillRandom("f1",10000);
   
   f1->SetParameters(1,-1,1);  // signal   
   hb1->FillRandom("f1",10000);
   hb2->FillRandom("f1",10000);

   //now make a classifier

    TMVA::Tools::Instance();
    auto outputFile = TFile::Open("TMVA_BDT_Results_FromHistograms.root", "RECREATE");

    // Create a factory and a DataLoader for handling data
    TMVA::Factory factory("TMVAClassification", outputFile, "!V:!Silent:Color:DrawProgressBar:AnalysisType=Classification");
    TMVA::DataLoader loader("dataset");

    loader.AddVariable("x",'F');
    // add events (assume all histograms have same number of bins, otherwise do in separate loops
    int nevts = hs1->GetNbinsX();
    for (int i = 1; i <= nevts; i++) {
       if (hs1->GetBinContent(i) > 0)
          loader.AddSignalTrainingEvent( {hs1->GetBinCenter(i) }, hs1->GetBinContent(i));
       //if (hs2->GetBinContent(i) > 0)
          //loader.AddSignalTestEvent( {hs2->GetBinCenter(i) }, hs2->GetBinContent(i));
       // background
       if (hb1->GetBinContent(i) > 0)
          loader.AddBackgroundTrainingEvent( {hb1->GetBinCenter(i) }, hb1->GetBinContent(i));
       //if (hb2->GetBinContent(i) > 0)
          //loader.AddBackgroundTestEvent( {hb2->GetBinCenter(i) }, hb2->GetBinContent(i));

    }

    TCut cut;
    loader.PrepareTrainingAndTestTree(cut,"");

    // Setup BDT configuration
    factory.BookMethod(&loader, TMVA::Types::kBDT, "BDT",
                       "!H:!V:NTrees=100:MaxDepth=3:BoostType=AdaBoost:AdaBoostBeta=0.5:SeparationType=GiniIndex:nCuts=20");

    // Train the model
    factory.TrainAllMethods();
    factory.TestAllMethods();
    factory.EvaluateAllMethods();

    // Clean up
    outputFile->Close();

    std::cout << "BDT training completed using histograms!" << std::endl;
    return;
}