LogLikelihoodFCN.h

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// @(#)root/mathcore:$Id$
// Author: L. Moneta Fri Aug 17 14:29:24 2007
 
/**********************************************************************
 *                                                                    *
 * Copyright (c) 2007  LCG ROOT Math Team, CERN/PH-SFT                *
 *                                                                    *
 *                                                                    *
 **********************************************************************/
 
// Header file for class LogLikelihoodFCN
 
#ifndef ROOT_Fit_LogLikelihoodFCN
#define ROOT_Fit_LogLikelihoodFCN
 
#include "ROOT/EExecutionPolicy.hxx"
#include "Fit/BasicFCN.h"
#include "Fit/FitUtil.h"
#include "Fit/UnBinData.h"
#include "Math/IParamFunction.h"
 
#include <memory>
#include <vector>
 
namespace ROOT {
 
   namespace Fit {
 
 
//___________________________________________________________________________________
/**
   LogLikelihoodFCN class
   for likelihood fits
 
   it is template to distinguish gradient and non-gradient case
 
   @ingroup  FitMethodFunc
*/
template<class DerivFunType,class ModelFunType = ROOT::Math::IParamMultiFunction>
class LogLikelihoodFCN : public BasicFCN<DerivFunType,ModelFunType,UnBinData>  {
 
public:
 
   typedef typename ModelFunType::BackendType T;
   typedef  BasicFCN<DerivFunType,ModelFunType,UnBinData> BaseFCN;
 
   typedef  ::ROOT::Math::BasicFitMethodFunction<DerivFunType> BaseObjFunction;
   typedef typename  BaseObjFunction::BaseFunction BaseFunction;
 
   typedef  ::ROOT::Math::IParamMultiFunctionTempl<T> IModelFunction;
   typedef typename BaseObjFunction::Type_t Type_t;
 
 
   /**
      Constructor from unbin data set and model function (pdf)
   */
   LogLikelihoodFCN (const std::shared_ptr<UnBinData> & data, const std::shared_ptr<IModelFunction> & func, int weight = 0, bool extended = false, const ::ROOT::EExecutionPolicy &executionPolicy = ::ROOT::EExecutionPolicy::kSequential) :
      BaseFCN( data, func),
      fIsExtended(extended),
      fWeight(weight),
      fNEffPoints(0),
      fGrad ( std::vector<double> ( func->NPar() ) ),
      fExecutionPolicy(executionPolicy)
   {}
 
      /**
      Constructor from unbin data set and model function (pdf) for object managed by users
   */
   LogLikelihoodFCN (const UnBinData & data, const IModelFunction & func, int weight = 0, bool extended = false, const ::ROOT::EExecutionPolicy &executionPolicy = ::ROOT::EExecutionPolicy::kSequential) :
      BaseFCN(std::make_shared<UnBinData>(data), std::shared_ptr<IModelFunction>(dynamic_cast<IModelFunction*>(func.Clone() ) ) ),
      fIsExtended(extended),
      fWeight(weight),
      fNEffPoints(0),
      fGrad ( std::vector<double> ( func.NPar() ) ),
      fExecutionPolicy(executionPolicy)
   {}
 
   /**
      Destructor (no operations)
   */
   virtual ~LogLikelihoodFCN () {}
 
   /**
      Copy constructor
   */
   LogLikelihoodFCN(const LogLikelihoodFCN & f) :
      BaseFCN(f.DataPtr(), f.ModelFunctionPtr() ),
      fIsExtended(f.fIsExtended ),
      fWeight( f.fWeight ),
      fNEffPoints( f.fNEffPoints ),
      fGrad( f.fGrad),
      fExecutionPolicy(f.fExecutionPolicy)
   {  }
 
 
   /**
      Assignment operator
   */
   LogLikelihoodFCN & operator = (const LogLikelihoodFCN & rhs) {
      SetData(rhs.DataPtr() );
      SetModelFunction(rhs.ModelFunctionPtr() );
      fNEffPoints = rhs.fNEffPoints;
      fGrad = rhs.fGrad;
      fIsExtended = rhs.fIsExtended;
      fWeight = rhs.fWeight;
      fExecutionPolicy = rhs.fExecutionPolicy;
      return *this;
   }
 
 
   /// clone the function (need to return Base for Windows)
   BaseFunction * Clone() const override { return  new LogLikelihoodFCN(*this); }
 
 
   //using BaseObjFunction::operator();
 
   // effective points used in the fit
   virtual unsigned int NFitPoints() const { return fNEffPoints; }
 
   /// i-th likelihood contribution and its gradient
   double DataElement(const double * x, unsigned int i, double * g, double *  h = nullptr, bool fullHessian = false) const override {
      if (i==0) this->UpdateNCalls();
      return FitUtil::Evaluate<T>::EvalPdf(BaseFCN::ModelFunction(), BaseFCN::Data(), x, i, g, h, BaseFCN::IsAGradFCN(), fullHessian);
   }
 
   // need to be virtual to be instantiated
   void Gradient(const double *x, double *g) const override {
      // evaluate the chi2 gradient
      FitUtil::Evaluate<typename BaseFCN::T>::EvalLogLGradient(BaseFCN::ModelFunction(), BaseFCN::Data(), x, g,
                                                               fNEffPoints, fExecutionPolicy);
   }
 
   /// get type of fit method function
   typename BaseObjFunction::Type_t Type() const override { return BaseObjFunction::kLogLikelihood; }
 
 
   // Use sum of the weight squared in evaluating the likelihood
   // (this is needed for calculating the errors)
   void UseSumOfWeightSquare(bool on = true) {
      if (fWeight == 0) return; // do nothing if it was not weighted
      if (on) fWeight = 2;
      else fWeight = 1;
   }
 
 
 
protected:
 
 
private:
 
   /**
      Evaluation of the  function (required by interface)
    */
   double DoEval (const double * x) const override {
      this->UpdateNCalls();
      return FitUtil::Evaluate<T>::EvalLogL(BaseFCN::ModelFunction(), BaseFCN::Data(), x, fWeight, fIsExtended, fNEffPoints, fExecutionPolicy);
   }
 
   // for derivatives
   double DoDerivative(const double * x, unsigned int icoord) const override {
      Gradient(x, &fGrad[0]);
      return fGrad[icoord];
   }
 
 
      //data member
   bool fIsExtended;  ///< flag for indicating if likelihood is extended
   int  fWeight;  ///< flag to indicate if needs to evaluate using weight or weight squared (default weight = 0)
 
 
   mutable unsigned int fNEffPoints;  ///< number of effective points used in the fit
 
   mutable std::vector<double> fGrad; ///< for derivatives
 
   ::ROOT::EExecutionPolicy fExecutionPolicy; ///< Execution policy
};
      // define useful typedef's
      // using LogLikelihoodFunction_v = LogLikelihoodFCN<ROOT::Math::IMultiGenFunction, ROOT::Math::IParametricFunctionMultiDimTempl<T>>;
      typedef LogLikelihoodFCN<ROOT::Math::IMultiGenFunction, ROOT::Math::IParamMultiFunction>  LogLikelihoodFunction;
      typedef LogLikelihoodFCN<ROOT::Math::IMultiGradFunction, ROOT::Math::IParamMultiFunction> LogLikelihoodGradFunction;
 
   } // end namespace Fit
 
} // end namespace ROOT
 
 
#endif /* ROOT_Fit_LogLikelihoodFCN */