GradFunc.h

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#ifndef GRADFUNC_H_
#define GRADFUNC_H_

#include "VecMat.h"
#include "GeneralObjective.h"

namespace ublas = boost::numeric::ublas;

//! Calculate the model gradient vector df(m)/dm 
gplib::rvec CalcGradient(GeneralObjective &Objective, const gplib::rvec &Model);
//! Calculate the model sensitivity matrix 
gplib::rmat CalcPartialDerivs(GeneralObjective &Objective,
    const gplib::rvec &Model, const gplib::rvec varfactor);

//! The class ModelAnalysis is used to calculate resolution matrix, nullspace and other parameters for model analyis

/*! We assume that the data characteristics as indicated by the CGeneralObjective object do not change, but we want
 * the possibility to analyse several different models
 */
class ModelAnalysis
  {
private:
  bool haveModel;
  bool haveSVD;
  bool changedThreshold;
  double SVDThreshold;
  GeneralObjective &Objective;
  gplib::rvec Model;
  gplib::rmat OldSensitivityMatrix;
  gplib::rmat SensitivityMatrix;
  gplib::rmat SensitivityInv;
  gplib::rvec s;
  gplib::rmat u, vt;
  gplib::rmat vnull, unull;
  gplib::rmat sinv;
  gplib::rvec varfactor;
  void CalcSensitivityMatrix();
  void CalcSVD();
  void ApplyThreshold();
public:
  void SetVariationFactor(const gplib::rvec varfac)
    {
      varfactor = varfac;
    }
  void SetModel(const gplib::rvec &TheModel);
  void SetRelativeSVDThreshold(const double t)
    {
      changedThreshold = true;
      SVDThreshold = t;
    }
  const gplib::rmat &GetSensitivityMatrix()
    {
      CalcSensitivityMatrix();
      return SensitivityMatrix;
    }
  const gplib::rmat &GetSensitivityInverse() const
    {
      return SensitivityInv;
    }
  gplib::rmat GetModelCorrelation(const gplib::rmat &DataCovar);
  gplib::rmat GetModelResolution();
  gplib::rmat GetDataResolution();
  gplib::rmat GetModelCovariance(const gplib::rmat &DataCovar);
  gplib::rmat GetModelNullspace();
  gplib::rvec GetSingularValues();
  ModelAnalysis(GeneralObjective &TheObjective) :
    haveModel(false), haveSVD(false), changedThreshold(true), Objective(
        TheObjective), SVDThreshold(0.0)
    {
    }
  ;
  ~ModelAnalysis()
    {
    }
  ;
  };
#endif /*GRADFUNC_H_*/