JTestPoissonLogLikelihoodRatioBeestonBarlow.hh

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#ifndef __JCOMPAREHISTOGRAMS__JTESTPOISSONLOGLIKELIHOODRATIOBEESTONBARLOW__
#define __JCOMPAREHISTOGRAMS__JTESTPOISSONLOGLIKELIHOODRATIOBEESTONBARLOW__

#include <istream>
#include <ostream>

#include "JLang/JException.hh"

#include "JCompareHistograms/JTest_t.hh"

#include "TH1.h"

#include "RooRealVar.h"
#include "RooRealConstant.h"
#include "RooParamHistFunc.h"
#include "RooHistConstraint.h"
#include "RooProdPdf.h"
#include "RooDataSet.h"
#include "RooDataHist.h"
#include "RooHistFunc.h"
#include "RooHistPdf.h"
#include "RooRealSumPdf.h"
#include "RooFitResult.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 JTestPoissonLogLikelihoodRatioBeestonBarlow: 
    public JTest_t
  { 
  public:  

    /**
     * Default constructor.
     */
    JTestPoissonLogLikelihoodRatioBeestonBarlow() :
      JTest_t("Poissonian Log-Likelihood Ratio with Beeston-Barlow Correction", "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);
      }

      RooRealVar x("x", "x", h1->GetBinLowEdge(1), h1->GetBinLowEdge(h1->GetNbinsX()) + h1->GetBinWidth(h1->GetNbinsX()));

      RooDataHist dh1("dh1", h1->GetTitle(), x, h1);
      RooDataHist dh2("dh2", h2->GetTitle(), x, h2);

      RooParamHistFunc  ph1("ph1", "ph1", dh1);
      RooHistConstraint hc1("hc1", "hc1", ph1);

      RooRealSumPdf model_tmp1("model_tmp1", "model_tmp1", ph1, RooRealConstant::value(1.0));
      RooProdPdf    model1    ("model1", "model1", hc1, RooFit::Conditional(model_tmp1,x));
      
      RooFitResult* result1 = (RooFitResult*) model1.fitTo(dh2,
                                                           RooFit::SumW2Error(false),
                                                           RooFit::PrintLevel(-1),
                                                           RooFit::Verbose(false),
                                                           RooFit::Save());
      
      if (result1 == NULL) {
        THROW(JValueOutOfRange, "JTestPoissonLogLikelihoodRatioBeestonBarlow::test(): Unable to retrieve fit results");
      }

      double nll2 = 0.0; // Poissonian negative log-likelihood of Asimov data-set onto itself

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

            const double n = h2->GetBinContent(i,j,k);
            
            if (n > 0.0) {
              nll2 += -n*log(n) + log(tgamma(n+1)) + n;
            } else {
              nll2 -= penalty;
            }
          }
        }
      }
      
      const double nllratio = 2 * (result1->minNll() - nll2);
      const bool   passed   = (nllratio < threshold);

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

      TH2* h3 = result1->correlationHist();
      h3->SetTitle(title.getTitle().c_str());

      const JTestResult r (testName,
                           JRootObjectID(MAKE_STRING(h1->GetDirectory()->GetPath() << h1->GetName())),
                           JRootObjectID(MAKE_STRING(h2->GetDirectory()->GetPath() << h1->GetName())),
                           resultType, nllratio, 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, "JTestPoissonLogLikelihoodRatioBeestonBarlow::read(): Given chi-square threshold " << threshold << " is invalid");
      }
      
      return in;
    }
  
  private:
    
    double threshold;  //!< threshold chi-square to decide if test is passed.
  };
}
  
#endif