//////////////////////////////////////////////////////////////////////////
//
// 'LIKELIHOOD AND MINIMIZATION' RooFit tutorial macro #605
// 
// Working with the profile likelihood estimator
//
//
//
// 07/2008 - Wouter Verkerke 
// 
/////////////////////////////////////////////////////////////////////////

#ifndef __CINT__
#include "RooGlobalFunc.h"
#endif
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "RooAddPdf.h"
#include "RooNLLVar.h"
#include "RooProfileLL.h"
#include "RooMinuit.h"
#include "TCanvas.h"
#include "RooPlot.h"
using namespace RooFit ;


class TestBasic605 : public RooFitTestUnit
{
public: 
  TestBasic605(TFile* refFile, Bool_t writeRef, Int_t verbose) : RooFitTestUnit("Profile Likelihood operator",refFile,writeRef,verbose) {} ;
  Bool_t testCode() {

  // C r e a t e   m o d e l   a n d   d a t a s e t 
  // -----------------------------------------------

  // Observable
  RooRealVar x("x","x",-20,20) ;

  // Model (intentional strong correlations)
  RooRealVar mean("mean","mean of g1 and g2",0,-10,10) ;
  RooRealVar sigma_g1("sigma_g1","width of g1",3) ;
  RooGaussian g1("g1","g1",x,mean,sigma_g1) ;

  RooRealVar sigma_g2("sigma_g2","width of g2",4,3.0,6.0) ;
  RooGaussian g2("g2","g2",x,mean,sigma_g2) ;

  RooRealVar frac("frac","frac",0.5,0.0,1.0) ;
  RooAddPdf model("model","model",RooArgList(g1,g2),frac) ;

  // Generate 1000 events
  RooDataSet* data = model.generate(x,1000) ;
  


  // C o n s t r u c t   p l a i n   l i k e l i h o o d
  // ---------------------------------------------------

  // Construct unbinned likelihood
  RooNLLVar nll("nll","nll",model,*data) ;

  // Minimize likelihood w.r.t all parameters before making plots
  RooMinuit(nll).migrad() ;

  // Plot likelihood scan frac 
  RooPlot* frame1 = frac.frame(Bins(10),Range(0.01,0.95),Title("LL and profileLL in frac")) ;
  nll.plotOn(frame1,ShiftToZero()) ;

  // Plot likelihood scan in sigma_g2
  RooPlot* frame2 = sigma_g2.frame(Bins(10),Range(3.3,5.0),Title("LL and profileLL in sigma_g2")) ;
  nll.plotOn(frame2,ShiftToZero()) ;



  // C o n s t r u c t   p r o f i l e   l i k e l i h o o d   i n   f r a c
  // -----------------------------------------------------------------------

  // The profile likelihood estimator on nll for frac will minimize nll w.r.t
  // all floating parameters except frac for each evaluation
  RooProfileLL pll_frac("pll_frac","pll_frac",nll,frac) ;

  // Plot the profile likelihood in frac
  pll_frac.plotOn(frame1,LineColor(kRed)) ;

  // Adjust frame maximum for visual clarity
  frame1->SetMinimum(0) ;
  frame1->SetMaximum(3) ;



  // C o n s t r u c t   p r o f i l e   l i k e l i h o o d   i n   s i g m a _ g 2 
  // -------------------------------------------------------------------------------

  // The profile likelihood estimator on nll for sigma_g2 will minimize nll
  // w.r.t all floating parameters except sigma_g2 for each evaluation
  RooProfileLL pll_sigmag2("pll_sigmag2","pll_sigmag2",nll,sigma_g2) ;

  // Plot the profile likelihood in sigma_g2
  pll_sigmag2.plotOn(frame2,LineColor(kRed)) ;

  // Adjust frame maximum for visual clarity
  frame2->SetMinimum(0) ;
  frame2->SetMaximum(3) ;


  regPlot(frame1,"rf605_plot1") ;
  regPlot(frame2,"rf605_plot2") ;

  delete data ;

  return kTRUE ;
  }
} ;

