#ifndef __JCOMPAREHISTOGRAMS__JTESTPOISSONLOGLIKELIHOODRATIO__
#define __JCOMPAREHISTOGRAMS__JTESTPOISSONLOGLIKELIHOODRATIO__

#include <istream>
#include <ostream>

#include "JLang/JException.hh"

#include "JCompareHistograms/JResultTitle.hh"
#include "JCompareHistograms/JTest_t.hh"

#include "TH1.h"


/**
 * \author bjung
 */
namespace JCOMPAREHISTOGRAMS {
  
  /**
   * Implementation of the Poisson log-likelihood ratio test.\n
   * The first histogram is treated as an Asimov dataset corresponding to a given null hypothesis,\n
   * which is compared to an alternative hypothesis given by the second histogram.\n\n
   *
   * This class is derived from the abstract class JTest_t(). For a general description of the implementation of this and other tests derived from JTest_t(), see its documentation.\n
   */
  class JTestPoissonLogLikelihoodRatio: 
    public JTest_t
  { 
  public:  

    /**
     * Default constructor.
     */
    JTestPoissonLogLikelihoodRatio() :
      JTest_t("Poissonian Log-Likelihood Ratio", "NLLR")
    {}

    
    /**
     * Applies a Poissonian log-likelihood ratio test to the two given histograms.\n
     * The first histogram is treated as an Asimov dataset corresponding to a given null hypothesis.\n
     * The second histogram is treated as the expectation for the alternative hypothesis, to which the null hypothesis is compared.
     * 
     * \param o1    First histogram
     * \param o2    Second histogram
     */
    void test(const TObject* o1, const TObject* o2) override
    {
      using namespace std;
      using namespace JPP;
      
      static const double penalty = -1e9; //!< Penalty factor

      const TH1* h1 =  dynamic_cast<const TH1*>(o1);
      const TH1* h2 =  dynamic_cast<const TH1*>(o2);

      if (h1 == NULL || h2 == NULL) {
	THROW(JValueOutOfRange, "JTestPoissonLogLikelihood::test(): Could not cast given TObjects to TH1.");
      }

      if(h1->GetNbinsX() != h2->GetNbinsX() ||
	 h1->GetNbinsY() != h2->GetNbinsY() ||
	 h1->GetNbinsZ() != h2->GetNbinsZ()) {
	THROW(JValueOutOfRange, "JTestPoissonLogLikelihood::test(): Histograms with different binning. The objects: " <<
	      h1->GetName() << " and " << h2->GetName() << " can not be compared." << endl);
      }

      TH1* h3 = (TH1*) h1->Clone(h1->GetName() == h2->GetName() ?
				 MAKE_CSTRING(h1->GetName()                            << "_" << testName) :
				 MAKE_CSTRING(h1->GetName() << "_VS_" << h2->GetName() << "_" << testName));

      h3->Reset();

      double LnLratio = 0.0;

      for (int i=1 ; i <= h1->GetNbinsX() ; ++i){
	for (int j=1 ; j <= h1->GetNbinsY() ; ++j){
	  for (int k=1 ; k <= h1->GetNbinsZ() ; ++k){

	    double contribution;

	    const double n0 = h1->GetBinContent(i,j,k);
	    const double n1 = h2->GetBinContent(i,j,k);

	    if        (n0 > 0.0 && n1 > 0.0) {
	      contribution = 2 * (n0 - n1 - n0 * log(n0/n1));
	    } else if (n0 > 0.0 || n1 > 0.0) {
	      contribution = penalty;
	    } else {
	      contribution = 0.0;
	    }

	    h3->SetBinContent(i,j,k, contribution);

	    LnLratio -= contribution;
	  }
	}
      }

      const bool passed = (LnLratio < threshold);

      const JResultTitle title(testName, resultType, passed, LnLratio);

      h3->SetTitle(title.getTitle().c_str());
      h3->GetYaxis()->SetTitle(resultType.c_str());

      const JTestResult r (testName,
			   JRootObjectID(MAKE_STRING(h1->GetDirectory()->GetPath() << h1->GetName())),
			   JRootObjectID(MAKE_STRING(h2->GetDirectory()->GetPath() << h1->GetName())),
			   resultType, LnLratio, threshold, h3, passed);
      
      this->push_back(r);
    }


    /**
     * Read test parameters from input.
     *
     * \param  in            input stream
     * \return               input stream
     */
    std::istream& read(std::istream& in) override
    {
      using namespace JPP;
      
      in >> threshold;

      if (!(threshold > 0.0)) {
	THROW(JValueOutOfRange, "JTestPoissonLogLikelihoodRatio::read(): Given chi-square threshold " << threshold << " is invalid");
      }
       
      return in;
    }
  
  private:
    
    double threshold;  //!< threshold chi-square to decide if test is passed.
  };
}
  
#endif