/// \file
/// \ingroup tutorial_fit
/// \notebook
/// Tutorial for creating a Vectorized TF1 function using a formula expression and
/// use it for fitting an histogram
///
/// To create a vectorized function (if ROOT has been compiled with support for vectorization)
/// is very easy. One needs to create the TF1 object with the option "VEC" or call the method
/// TF1::SetVectorized
///
/// \macro_image
/// \macro_output
/// \macro_code
///
/// \author Lorenzo Moneta

#include <Math/MinimizerOptions.h>
#include <TCanvas.h>
#include <TF1.h>
#include <TH1D.h>
#include <TStopwatch.h>
#include <TStyle.h>

#include <iostream>

void vectorizedFit() {

   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");
   // alternatively you can also use the TF1::SetVectorized function
   //f2->SetVectorized(true); 
   w.Start();
   h1->Fit(f2);
   h1->Fit(f2,"L+");
   w.Print();
   // rebin histograms and scale it back to the function
   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(1)->BuildLegend();

   /// Do a polynomial fit now
   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);
   // generate the events
   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();

   // rebin histograms and scale it back to the function
   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);
   //c1->cd(2)->BuildLegend();

}