Int_t testMT( Bool_t mt )
{
    TCanvas cv;

    if( mt ) ROOT::EnableImplicitMT();
    ROOT::RDataFrame df("AnalysisTree", "AnalysisTree10M.root");

    Int_t* bins = new Int_t[3];
    Double_t* xmin = new Double_t[3];
    Double_t* xmax = new Double_t[3];

    for (size_t n = 0; n < 2; n++) {
        bins[n] = 80;
        xmin[n] = -20;
        xmax[n] = 20;
    }
    bins[2] = 100;
    xmin[2] = 0;
    xmax[2] = 10;

    THnD* sparse = new THnD("sparse", "sparse", 3, bins, xmin, xmax);

    std::vector<std::vector<double> > data;
    auto parValues1 = df.Take<double>("final_posX");
    data.push_back(*parValues1);
    auto parValues2 = df.Take<double>("final_posY");
    data.push_back(*parValues2);
    auto parValues3 = df.Take<double>("final_energy");
    data.push_back(*parValues3);

    Double_t* values = new Double_t[3];
    std::cout << "N-values filled: " << data[0].size() << std::endl;
    if (!data.empty())
        for (size_t m = 0; m < data[0].size(); m++)
        {
            for (size_t v = 0; v < 3; v++) {
                values[v] = data[v][m];
            }

            sparse->Fill(values);
        }

    std::vector <Double_t> test = {-0.250000 ,  2.750000 ,   2.150000};
    Double_t content = sparse->GetBinContent(sparse->GetBin(test.data()));
    std::cout << "Content " << content << std::endl;


    std::cout << "Nbins : " << sparse->GetNbins() << std::endl;

    return 0;
}