using namespace TMVA::Experimental;

RSofieReader model("Higgs_trained_model.h5");

std::vector<float> input = {0.1,0.2,0.3,0.4,0.5,0.6,0.7};

auto output = model.Compute(input);

std::cout << "Event prediction = " << output[0] << std::endl;

std::string inputFileName = "Higgs_data.root";
std::string inputFile = "http://root.cern.ch/files/" + inputFileName;


ROOT::RDataFrame df1("sig_tree", inputFile);

auto h1 = df1.Define("DNN_Values", Compute<7, float>(model),
                         {"m_jj", "m_jjj", "m_lv", "m_jlv", "m_bb", "m_wbb", "m_wwbb"})
               .Define("y","DNN_Values[0]")
               .Histo1D({"h_sig", "", 100, 0, 1}, "y");

ROOT::RDataFrame df2("bkg_tree", inputFile);
auto h2 = df2.Define("DNN_Values", Compute<7, float>(model),
                         {"m_jj", "m_jjj", "m_lv", "m_jlv", "m_bb", "m_wbb", "m_wwbb"})
               .Define("y","DNN_Values[0]")
               .Histo1D({"h_bkg", "", 100, 0, 1}, "y");

h1->SetLineColor(kRed);
h2->SetLineColor(kBlue);

auto c1 = new TCanvas();
gStyle->SetOptStat(0);

h2->DrawClone();
h1->DrawClone("SAME");
c1->BuildLegend();