gStyle->SetOptFit(111111);


ROOT::Math::MinimizerOptions::SetDefaultMinimizer("Minuit2");

int nbins = 40000;
auto h1 = new TH1D("h1","h1",nbins,-3,3);
h1->FillRandom("gaus",nbins*50);
auto c1 = new TCanvas("Fit","Fit",800,1000);
c1->Divide(1,2);
c1->cd(1);
TStopwatch w;

std::cout << "Doing Serial Gaussian Fit " << std::endl;
auto f1 = new TF1("f1","gaus");
f1->SetNpx(nbins*10);
w.Start();
h1->Fit(f1);
h1->Fit(f1,"L+");
w.Print();

std::cout << "Doing Vectorized Gaussian Fit " << std::endl;
auto f2 = new TF1("f2","gaus",-3,3,"VEC");

w.Start();
h1->Fit(f2);
h1->Fit(f2,"L+");
w.Print();

h1->Rebin(nbins/100);
h1->Scale(100./nbins);
((TF1 *)h1->GetListOfFunctions()->At(0))->SetTitle("Chi2 Fit");
((TF1 *)h1->GetListOfFunctions()->At(1))->SetTitle("Likelihood Fit");
((TF1 *)h1->GetListOfFunctions()->At(1))->SetLineColor(kBlue);

c1->cd(2);
auto f3 = new TF1("f3","[A]*x^2+[B]*x+[C]",0,10);
f3->SetParameters(0.5,3,2);
f3->SetNpx(nbins*10);

auto h2 = new TH1D("h2","h2",nbins,0,10);
h2->FillRandom("f3",10*nbins);
std::cout << "Doing Serial Polynomial Fit " << std::endl;
f3->SetParameters(2,2,2);
w.Start();
h2->Fit(f3);
h2->Fit(f3,"L+");
w.Print();

std::cout << "Doing Vectorized Polynomial Fit " << std::endl;
auto f4 = new TF1("f4","[A]*x*x+[B]*x+[C]",0,10);
f4->SetVectorized(true);
f4->SetParameters(2,2,2);
w.Start();
h2->Fit(f4);
h2->Fit(f4,"L+");
w.Print();

h2->Rebin(nbins/100);
h2->Scale(100./nbins);
((TF1 *)h2->GetListOfFunctions()->At(0))->SetTitle("Chi2 Fit");
((TF1 *)h2->GetListOfFunctions()->At(1))->SetTitle("Likelihood Fit");
((TF1 *)h2->GetListOfFunctions()->At(1))->SetLineColor(kBlue);

gROOT->GetListOfCanvases()->Draw()