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 // Author: Krzysztof Danielowski, Kamil Kraszewski, Maciej Kruk, Jan Therhaag
 
 /**********************************************************************************
  * Project: TMVA - a Root-integrated toolkit for multivariate data analysis       *
  * Package: TMVA                                                                  *
  * Class  : MethodLD                                                              *
  *                                             *
  *                                                                                *
  * Description:                                                                   *
  *      Linear Discriminant (Simple Linear Regression)                            *
  *                                                                                *
  * Authors (alphabetical):                                                        *
  *      Krzysztof Danielowski <danielow@cern.ch> - IFJ PAN & AGH, Poland          *
  *      Kamil Kraszewski      <kalq@cern.ch>     - IFJ PAN & UJ, Poland           *
  *      Maciej Kruk           <mkruk@cern.ch>    - IFJ PAN & AGH, Poland          *
  *      Peter Speckmayer      <peter.speckmayer@cern.ch>  - CERN, Switzerland     *
  *      Jan Therhaag          <therhaag@physik.uni-bonn.de> - Uni Bonn, Germany   *
  *                                                                                *
  * Copyright (c) 2008-2011:                                                       *
  *      CERN, Switzerland                                                         *
  *      PAN, Poland                                                               *
  *      U. of Bonn, Germany                                                       *
  *                                                                                *
  * Redistribution and use in source and binary forms, with or without             *
  * modification, are permitted according to the terms listed in LICENSE           *
  * (see tmva/doc/LICENSE)                                          *
  *                                                                                *
  **********************************************************************************/
 
 #ifndef ROOT_TMVA_MethodLD
 #define ROOT_TMVA_MethodLD
 
 //////////////////////////////////////////////////////////////////////////
 //                                                                      //
 // MethodLD                                                             //
 //                                                                      //
 // Linear Discriminant                                                  //
 // Can compute multidimensional output for regression                   //
 // (although it computes every dimension separately)                    //
 //                                                                      //
 //////////////////////////////////////////////////////////////////////////
 
 #include <vector>
 
 #include "TMVA/MethodBase.h"
 #include "TMatrixDfwd.h"
 
 namespace TMVA {
 
    class MethodLD : public MethodBase {
 
    public:
 
       // constructor
       MethodLD( const TString& jobName,
                 const TString& methodTitle,
                 DataSetInfo& dsi,
                 const TString& theOption = "LD");
 
       // constructor
       MethodLD( DataSetInfo& dsi,
                 const TString& theWeightFile);
 
       // destructor
       virtual ~MethodLD( void );
 
       Bool_t HasAnalysisType( Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets ) override;
 
       // training method
       void Train( void ) override;
 
       // calculate the MVA value
       Double_t GetMvaValue( Double_t* err = nullptr, Double_t* errUpper = nullptr ) override;
 
       // calculate the Regression value
       const std::vector<Float_t>& GetRegressionValues() override;
 
       using MethodBase::ReadWeightsFromStream;
 
       void AddWeightsXMLTo      ( void* parent ) const override;
 
       void ReadWeightsFromStream( std::istream & i ) override;
       void ReadWeightsFromXML   ( void* wghtnode ) override;
 
       const Ranking* CreateRanking() override;
       void DeclareOptions() override;
       void ProcessOptions() override;
 
    protected:
 
       void MakeClassSpecific( std::ostream&, const TString& ) const override;
       void GetHelpMessage() const override;
 
    private:
 
       Int_t fNRegOut; ///< size of the output
 
       TMatrixD *fSumMatx;              ///< Sum of coordinates product matrix
       TMatrixD *fSumValMatx;           ///< Sum of values multiplied by coordinates
       TMatrixD *fCoeffMatx;            ///< Matrix of coefficients
       std::vector< std::vector<Double_t>* > *fLDCoeff; ///< LD coefficients
 
       // default initialisation called by all constructors
       void Init( void ) override;
 
       // Initialization and allocation of matrices
       void InitMatrices( void );
 
       // Compute fSumMatx
       void GetSum( void );
 
       // Compute fSumValMatx
       void GetSumVal( void );
 
       // get LD coefficients
       void GetLDCoeff( void );
 
       // nice output
       void PrintCoefficients( void );
 
       ClassDefOverride(MethodLD,0); //Linear discriminant analysis
    };
 } // namespace TMVA
 
 #endif // MethodLD_H

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