const int nsig = 5.E4;
const int nbkg = 1.e6;
int nEvents = nsig + nbkg;
int nBins = 1e3;

double signal_mean = 3;
TF1 *f_cb = new TF1("MyCrystalBall", "crystalball", -5., 5.);
TF1 *f_exp = new TF1("MyExponential", "expo", -5., 5.);

f_exp->SetParameters(1., -0.3);
f_cb->SetParameters(1, signal_mean, 0.3, 2, 1.5);

TF1NormSum *fnorm_exp_cb = new TF1NormSum(f_cb, f_exp, nsig, nbkg);

TF1 *f_sum = new TF1("fsum", *fnorm_exp_cb, -5., 5., fnorm_exp_cb->GetNpar());

f_sum->SetParameters(fnorm_exp_cb->GetParameters().data());
f_sum->SetParName(1, "NBackground");
f_sum->SetParName(0, "NSignal");
for (int i = 2; i < f_sum->GetNpar(); ++i)
   f_sum->SetParName(i, fnorm_exp_cb->GetParName(i));

TStopwatch w;
w.Start();
TH1D *h_sum = new TH1D("h_ExpCB", "Exponential Bkg + CrystalBall function", nBins, -5., 5.);
h_sum->FillRandom("fsum", nEvents);
printf("Time to generate %d events:  ", nEvents);
w.Print();

h_sum->Sumw2();
h_sum->Scale(1., "width");

ROOT::Math::MinimizerOptions::SetDefaultMinimizer("Minuit2");
new TCanvas("Fit", "Fit", 800, 1000);

auto result = h_sum->Fit("fsum", "SQ");
result->Print();
h_sum->Draw();
printf("Time to fit using ROOT TF1Normsum: ");
w.Print();

std::vector<double> pref = {nsig, nbkg, signal_mean};
for (unsigned int i = 0; i < pref.size(); ++i) {
   if (!TMath::AreEqualAbs(pref[i], f_sum->GetParameter(i), f_sum->GetParError(i) * 10.))
      Error("testFitNormSum", "Difference found in fitted %s - difference is %g sigma", f_sum->GetParName(i),
            (f_sum->GetParameter(i) - pref[i]) / f_sum->GetParError(i));
}

gStyle->SetOptStat(0);

auto t1 = new TLatex(
   -2.5, 300000, TString::Format("%s = %8.0f #pm %4.0f", "NSignal", f_sum->GetParameter(0), f_sum->GetParError(0)));
auto t2 = new TLatex(
   -2.5, 270000, TString::Format("%s = %8.0f #pm %4.0f", "Nbackgr", f_sum->GetParameter(1), f_sum->GetParError(1)));
t1->Draw();
t2->Draw();

gROOT->GetListOfCanvases()->Draw()