GSLNLSMinimizer.h

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// @(#)root/mathmore:$Id$
// Author: L. Moneta Wed Dec 20 17:16:32 2006
 
/**********************************************************************
 *                                                                    *
 * Copyright (c) 2006  LCG ROOT Math Team, CERN/PH-SFT                *
 *                                                                    *
 * This library is free software; you can redistribute it and/or      *
 * modify it under the terms of the GNU General Public License        *
 * as published by the Free Software Foundation; either version 2     *
 * of the License, or (at your option) any later version.             *
 *                                                                    *
 * This library is distributed in the hope that it will be useful,    *
 * but WITHOUT ANY WARRANTY; without even the implied warranty of     *
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU   *
 * General Public License for more details.                           *
 *                                                                    *
 * You should have received a copy of the GNU General Public License  *
 * along with this library (see file COPYING); if not, write          *
 * to the Free Software Foundation, Inc., 59 Temple Place, Suite      *
 * 330, Boston, MA 02111-1307 USA, or contact the author.             *
 *                                                                    *
 **********************************************************************/
 
// Header file for class GSLNLSMinimizer
 
#ifndef ROOT_Math_GSLNLSMinimizer
#define ROOT_Math_GSLNLSMinimizer
 
 
 
#include "Math/BasicMinimizer.h"
 
#include "Math/IFunctionfwd.h"
 
#include "Math/IParamFunctionfwd.h"
 
#include "Math/FitMethodFunction.h"
 
#include "Math/MinimTransformVariable.h"
 
#include <vector>
 
namespace ROOT {
 
   namespace Math {
 
      class GSLMultiFit;
 
//_____________________________________________________________________________________________________
/**
   GSLNLSMinimizer class for Non Linear Least Square fitting
   It Uses the Levemberg-Marquardt algorithm from
   <A HREF="http://www.gnu.org/software/gsl/manual/html_node/Nonlinear-Least_002dSquares-Fitting.html">
   GSL Non Linear Least Square fitting</A>.
 
   @ingroup MultiMin
*/
class GSLNLSMinimizer : public  ROOT::Math::BasicMinimizer {
 
public:
 
   /**
      Default constructor
   */
   GSLNLSMinimizer (int type = 0);
 
   /**
      Destructor (no operations)
   */
   ~GSLNLSMinimizer () override;
 
private:
   // usually copying is non trivial, so we make this unaccessible
 
   /**
      Copy constructor
   */
   GSLNLSMinimizer(const GSLNLSMinimizer &) : ROOT::Math::BasicMinimizer() {}
 
   /**
      Assignment operator
   */
   GSLNLSMinimizer & operator = (const GSLNLSMinimizer & rhs)  {
      if (this == &rhs) return *this;  // time saving self-test
      return *this;
   }
 
public:
 
   /// set the function to minimize
   void SetFunction(const ROOT::Math::IMultiGenFunction & func) override;
 
 
   /// method to perform the minimization
    bool Minimize() override;
 
 
   /// return expected distance reached from the minimum
   double Edm() const override { return fEdm; } // not impl. }
 
 
   /// return pointer to gradient values at the minimum
   const double *  MinGradient() const override;
 
   /// number of function calls to reach the minimum
   unsigned int NCalls() const override { return fNCalls; }
 
   /// number of free variables (real dimension of the problem)
   /// this is <= Function().NDim() which is the total
//   virtual unsigned int NFree() const { return fNFree; }
 
   /// minimizer provides error and error matrix
   bool ProvidesError() const override { return true; }
 
   /// return errors at the minimum
   const double * Errors() const override { return (!fErrors.empty()) ? &fErrors.front() : nullptr; }
//  {
//       static std::vector<double> err;
//       err.resize(fDim);
//       return &err.front();
//    }
 
   /** return covariance matrices elements
       if the variable is fixed the matrix is zero
       The ordering of the variables is the same as in errors
   */
   double CovMatrix(unsigned int , unsigned int ) const override;
 
   /// return covariance matrix status
   int CovMatrixStatus() const override;
 
protected:
 
   /// Internal method to perform minimization
   /// template on the type of method function
   template<class Func>
   bool DoMinimize(const Func & f);
 
 
private:
 
   bool fUseGradFunction = false; // flag to indicate if using external gradients
   unsigned int fNFree;      // dimension of the internal function to be minimized
   unsigned int fNCalls;        // number of function calls
 
   ROOT::Math::GSLMultiFit * fGSLMultiFit;        // pointer to GSL multi fit solver
 
   double fEdm;                                   // edm value
   double fLSTolerance;                           // Line Search Tolerance
   std::vector<double> fErrors;
   std::vector<double> fCovMatrix;              //  cov matrix (stored as cov[ i * dim + j]
 
 
 
};
 
   } // end namespace Math
 
} // end namespace ROOT
 
 
#endif /* ROOT_Math_GSLNLSMinimizer */