View of /trunk/math/mathcore/inc/Fit/Fitter.h

// @(#)root/mathcore:$Id$
// Author: L. Moneta Wed Aug 30 11:05:19 2006

/**********************************************************************
 *                                                                    *
 * Copyright (c) 2006  LCG ROOT Math Team, CERN/PH-SFT                *
 *                                                                    *
 *                                                                    *
 **********************************************************************/

// Header file for class Fitter

#ifndef ROOT_Fit_Fitter
#define ROOT_Fit_Fitter

/**
@defgroup Fit Fitting and Parameter Estimation

Classes used for fitting (regression analysis) and estimation of parameter values given a data sample. 
*/

#ifndef ROOT_Fit_DataVectorfwd
#include "Fit/DataVectorfwd.h"
#endif

#ifndef ROOT_Fit_FitConfig
#include "Fit/FitConfig.h"
#endif

#ifndef ROOT_Fit_FitResult
#include "Fit/FitResult.h"
#endif

#ifndef ROOT_Math_IParamFunctionfwd
#include "Math/IParamFunctionfwd.h"
#endif



namespace ROOT { 


   namespace Math { 
      class Minimizer;
   } 

   /**
      Namespace for the fitting classes
      @ingroup Fit
    */

   namespace Fit { 

/**
   @defgroup FitMain User Fitting classes

   Main Classes used for fitting a given data set
   @ingroup Fit
*/

//___________________________________________________________________________________
/** 
   Fitter class, entry point for performing all type of fits. 
   Fits are performed using the generic ROOT::Fit::Fitter::Fit method. 
   The inputs are the data points and a model function (using a ROOT::Math::IParamFunction)
   The result of the fit is returned and kept internally in the  ROOT::Fit::FitResult class. 
   The configuration of the fit (parameters, options, etc...) are specified in the 
   ROOT::Math::FitConfig class. 

   @ingroup FitMain
*/ 
class Fitter {

public: 

   typedef ROOT::Math::IParamMultiFunction       IModelFunction; 
   typedef ROOT::Math::IParamMultiGradFunction   IGradModelFunction;
   typedef ROOT::Math::IParamFunction            IModel1DFunction; 
   typedef ROOT::Math::IParamGradFunction        IGradModel1DFunction; 

   typedef ROOT::Math::IMultiGenFunction BaseFunc; 
   typedef ROOT::Math::IMultiGradFunction BaseGradFunc; 


   /** 
      Default constructor
   */ 
   Fitter (); 

   /** 
      Destructor
   */ 
   ~Fitter (); 


   /** 
      Copy constructor
   */ 
   Fitter(const Fitter &);

   /** 
      Assignment operator
   */ 
   Fitter & operator = (const Fitter & rhs);  


public: 

   /** 
       fit a data set using any  generic model  function
       Pre-requisite on the function: 
   */ 
   template < class Data , class Function> 
   bool Fit( const Data & data, const Function & func) { 
      SetFunction(func);
      return Fit(data);
   }

   /** 
       fit a binned data set (default method: use chi2)
       To be implemented option to do likelihood bin fit
   */ 
   bool Fit(const BinData & data) { 
      return DoLeastSquareFit(data); 
   } 
   /** 
       fit an binned data set using loglikelihood method
   */ 
   bool Fit(const UnBinData & data) { 
      return DoLikelihoodFit(data); 
   } 

   /**
      Likelihood fit 
    */
   template <class Data> 
   bool LikelihoodFit(const Data & data) { 
      return DoLikelihoodFit(data);
   }

   /** 
       fit a data set using any  generic model  function
       Pre-requisite on the function: 
   */ 
   template < class Data , class Function> 
   bool LikelihoodFit( const Data & data, const Function & func) { 
      SetFunction(func);
      return DoLikelihoodFit(data);
   }

   /**
      fit using the given FCN function. Give optionally initial parameter values and data size to get  Ndf. If parameters are not given it is assumed that the parameter settings are used 
    */
   bool FitFCN(const ROOT::Math::IMultiGenFunction & fcn, const double * params = 0, unsigned int dataSize = 0 ); 
   /**
      fit using the given gradient FCN function. Give also initial parameter values and data size to get  Ndf
    */
   bool FitFCN(const ROOT::Math::IMultiGradFunction & fcn, const double * params = 0, unsigned int dataSize = 0); 

   /**
      do a linear fit on a set of bin-data
    */
   bool LinearFit(const BinData & data) { return DoLinearFit(data); }

   /** 
       Set the fitted function (model function) from a parametric function interface
   */ 
   void  SetFunction(const IModelFunction & func); 
   /**
      Set the fitted function from a parametric 1D function interface
    */
   void  SetFunction(const IModel1DFunction & func); 

   /** 
       Set the fitted function (model function) from a parametric gradient function interface
   */ 
   void  SetFunction(const IGradModelFunction & func); 
   /**
      Set the fitted function from 1D gradient parametric function interface
    */
   void  SetFunction(const IGradModel1DFunction & func); 


   /**
      get fit result
   */
   const FitResult & Result() const { return fResult; } 

   /**
      access to the fit configuration (const method)
   */
   const FitConfig & Config() const { return fConfig; } 

   /**
      access to the configuration (non const method)
   */
   FitConfig & Config() { return fConfig; } 



protected: 

   /// least square fit 
   bool DoLeastSquareFit(const BinData & data); 
   /// binned likelihood fit
   bool DoLikelihoodFit(const BinData & data); 
   /// un-binned likelihood fit
   bool DoLikelihoodFit(const UnBinData & data); 
   /// linear least square fit 
   bool DoLinearFit(const BinData & data);

   /// do minimization
   template<class ObjFunc> 
   bool DoMinimization(ROOT::Math::Minimizer & min, const ObjFunc & f, unsigned int dataSize, const ROOT::Math::IMultiGenFunction * chifunc = 0); 

private: 

   bool fUseGradient;       // flag to indicate if using gradient or not

   IModelFunction * fFunc;  // copy of the fitted  function containing on output the fit result

   FitResult fResult;       // object containing the result of the fit

   FitConfig fConfig;       // fitter configuration (options and parameter settings)

}; 

   } // end namespace Fit

} // end namespace ROOT


#endif /* ROOT_Fit_Fitter */