JFIT::JRegressor< JShower3EZ, JGandalf > Struct Reference

Regressor function object for JShower3EZ fit using JGandalf minimiser. More...

#include <JShower3EZRegressor.hh>

Inheritance diagram for JFIT::JRegressor< JShower3EZ, JGandalf >:

Public Types
typedef JTOOLS::JSplineFunction1S_t	JFunction1D_t
typedef JTOOLS::JMapList< JTOOLS::JPolint0FunctionalMap, JTOOLS::JMapList< JTOOLS::JPolint0FunctionalMap, JTOOLS::JMapList< JTOOLS::JPolint0FunctionalGridMap, JTOOLS::JMapList< JTOOLS::JPolint0FunctionalGridMap > > > >	JPDFMaplist_t
typedef JPHYSICS::JPDFTable< JFunction1D_t, JPDFMaplist_t >	JPDF_t
typedef JTOOLS::JMapList< JTOOLS::JPolint1FunctionalMap, JTOOLS::JMapList< JTOOLS::JPolint1FunctionalMapH, JTOOLS::JMapList< JTOOLS::JPolint1FunctionalGridMap, JTOOLS::JMapList< JTOOLS::JPolint1FunctionalGridMap > > > >	JNPEMaplist_t
typedef JPHYSICS::JNPETable< double, double, JNPEMaplist_t >	JNPE_t
typedef JGandalf< JShower3EZ >	minimiser_type
typedef JRegressor< JShower3EZ, JGandalf >	regressor_type
typedef minimiser_type::result_type	result_type
typedef JFIT_LOCAL::JTypedef_t< JModel_t >::parameter_type	parameter_type
	Data type of fit parameter. More...

Public Member Functions
	JRegressor (const std::string &fileDescriptor)
	Parameterized constructor. More...
result_type	operator() (const JShower3EZ &shower, const JPMTW0 &pmt) const
	Fit function. More...
JNPE_t::result_type	getH0 (const double R_Hz) const
	Get background hypothesis value for time integrated PDF. More...
JNPE_t::result_type	getH1 (const double D, const double cd, const double theta, const double phi, const double E) const
	Get signal hypothesis value for time integrated PDF. More...
result_type	operator() (const JShower3EZ &value, T __begin, T __end)
	Global fit. More...
template<class JFunction_t , class T , class ... Args>
result_type	operator() (const JFunction_t &fit, T __begin, T __end, Args ...args)
	Multi-dimensional fit of multiple data sets. More...

Public Attributes
JNPE_t	npe [NUMBER_OF_PDFS]
	PDF. More...
JLANG::JSharedPointer< JMEstimator >	estimator
	M-Estimator function. More...
std::vector< parameter_type >	parameters
	fit parameters More...
int	numberOfIterations
	number of iterations More...
double	lambda
	control parameter More...
JModel_t	value
	value More...
JModel_t	error
	error More...
JMATH::JMatrixNS	V
	Hesse matrix. More...

Static Public Attributes
static JTimeRange	T_ns
	Time window with respect to Cherenkov hypothesis [ns]. More...
static double	Vmax_npe = std::numeric_limits<double>::max()
	Maximal integral of PDF [npe]. More...
static const int	NUMBER_OF_PDFS = 2
static const JFIT::JPDFType_t	pdf_t [NUMBER_OF_PDFS]
static int	MAXIMUM_ITERATIONS = 1000
	maximal number of iterations More...
static double	EPSILON = 1.0e-3
	maximal distance to minimum More...
static bool	EPSILON_ABSOLUTE = false
	set epsilon to absolute difference instead of relative More...
static double	LAMBDA_MIN = 0.01
	minimal value control parameter More...
static double	LAMBDA_MAX = 100.0
	maximal value control parameter More...
static double	LAMBDA_UP = 10.0
	multiplication factor control parameter More...
static double	LAMBDA_DOWN = 10.0
	multiplication factor control parameter More...
static double	PIVOT = std::numeric_limits<double>::epsilon()
	minimal value diagonal element of Hesse matrix More...
static int	debug = 0
	debug level (default is off). More...

Private Member Functions
void	reset ()
	Reset current parameters. More...
template<class JFunction_t , class T , class ... Args>
void	update (const JFunction_t &fit, T __begin, T __end, Args ...args)
	Recursive method to update current parameters. More...
template<class JFunction_t >
void	update (const JFunction_t &fit)
	Termination method to update current parameters. More...

Static Private Member Functions
static double	get (const JModel_t &model, double JModel_t::*parameter)
	Read/write access to parameter value by data member. More...
static double &	get (JModel_t &model, double JModel_t::*parameter)
	Read/write access to parameter value by data member. More...
static double	get (const JModel_t &model, const size_t index)
	Read/write access to parameter value by index. More...
static double &	get (JModel_t &model, const size_t index)
	Read/write access to parameter value by index. More...
static double	get (const JModel_t &model, const int index)
	Read/write access to parameter value by index. More...
static double &	get (JModel_t &model, const int index)
	Read/write access to parameter value by index. More...

Private Attributes
std::vector< double >	h
JMATH::JVectorND	x
struct {
result_type   result
}	current
struct {
JModel_t   value
result_type   result
}	previous

Detailed Description

Regressor function object for JShower3EZ fit using JGandalf minimiser.

Definition at line 276 of file JShower3EZRegressor.hh.

Member Typedef Documentation

JFunction1D_t

typedef JTOOLS::JSplineFunction1S_t JFIT::JRegressor< JShower3EZ, JGandalf >::JFunction1D_t

Definition at line 281 of file JShower3EZRegressor.hh.

JPDFMaplist_t

typedef JTOOLS::JMapList<JTOOLS::JPolint0FunctionalMap, JTOOLS::JMapList<JTOOLS::JPolint0FunctionalMap, JTOOLS::JMapList<JTOOLS::JPolint0FunctionalGridMap, JTOOLS::JMapList<JTOOLS::JPolint0FunctionalGridMap> > > > JFIT::JRegressor< JShower3EZ, JGandalf >::JPDFMaplist_t

Definition at line 285 of file JShower3EZRegressor.hh.

JPDF_t

typedef JPHYSICS::JPDFTable<JFunction1D_t, JPDFMaplist_t> JFIT::JRegressor< JShower3EZ, JGandalf >::JPDF_t

Definition at line 286 of file JShower3EZRegressor.hh.

JNPEMaplist_t

typedef JTOOLS::JMapList<JTOOLS::JPolint1FunctionalMap, JTOOLS::JMapList<JTOOLS::JPolint1FunctionalMapH, JTOOLS::JMapList<JTOOLS::JPolint1FunctionalGridMap, JTOOLS::JMapList<JTOOLS::JPolint1FunctionalGridMap> > > > JFIT::JRegressor< JShower3EZ, JGandalf >::JNPEMaplist_t

Definition at line 291 of file JShower3EZRegressor.hh.

JNPE_t

typedef JPHYSICS::JNPETable<double, double, JNPEMaplist_t> JFIT::JRegressor< JShower3EZ, JGandalf >::JNPE_t

Definition at line 292 of file JShower3EZRegressor.hh.

minimiser_type

typedef JGandalf <JShower3EZ > JFIT::JAbstractRegressor< JShower3EZ , JGandalf >::minimiser_type

inherited

Definition at line 80 of file JRegressor.hh.

regressor_type

typedef JRegressor<JShower3EZ , JGandalf > JFIT::JAbstractRegressor< JShower3EZ , JGandalf >::regressor_type

inherited

Definition at line 81 of file JRegressor.hh.

result_type

typedef minimiser_type::result_type JFIT::JAbstractRegressor< JShower3EZ , JGandalf >::result_type

inherited

Definition at line 82 of file JRegressor.hh.

parameter_type

template<class JModel_t >

typedef JFIT_LOCAL::JTypedef_t<JModel_t>::parameter_type JFIT::JGandalf< JModel_t >::parameter_type

inherited

Data type of fit parameter.

Definition at line 95 of file JGandalf.hh.

Constructor & Destructor Documentation

JRegressor()

JFIT::JRegressor< JShower3EZ, JGandalf >::JRegressor ( const std::string &  fileDescriptor )

inline

Parameterized constructor.

The PDF file descriptor should contain the wild card character JPHYSICS::WILDCARD which will be replaced by the corresponding PDF types listed in JRegressor<JShower3Z, JGandalf>::pdf_t.

Parameters

fileDescriptor

PDF file descriptor

Definition at line 303 of file JShower3EZRegressor.hh.

                                               :
      estimator(new JMEstimatorNull())
    {
      using namespace std;
      using namespace JPP;
 
      const JPDF_t::JSupervisor supervisor(new JPDF_t::JDefaultResult(JMATH::zero));
      
      for (int i = 0; i != NUMBER_OF_PDFS; ++i) {
        
        try {
            
          JPDF_t pdf;
 
          const string file_name = getFilename(fileDescriptor, pdf_t[i]);
            
          NOTICE("loading PDF from file " << file_name << "... " << flush);
 
          pdf.load(file_name.c_str());
          
          NOTICE("OK" << endl);
 
          pdf.setExceptionHandler(supervisor);
 
          npe[i] = JNPE_t(pdf);
        }
        catch(const JException& error) {
          FATAL(error.what() << endl);
        }
      }
 
      // Add PDFs
      for (int i = 1; i < NUMBER_OF_PDFS; i += 2) {
 
        npe[ i ].add(npe[i-1]);
 
        JNPE_t buffer;
 
        npe[i-1].swap(buffer);
      }    
    }

Member Function Documentation

operator()() [1/3]

result_type JFIT::JRegressor< JShower3EZ, JGandalf >::operator() ( const JShower3EZ &  shower, const JPMTW0 &  pmt  ) const

inline

Fit function.

This method is used to determine the chi2 of given PMT with respect to shower hypothesis.

Parameters

shower	shower
pmt	pmt

Returns

chi2

Definition at line 353 of file JShower3EZRegressor.hh.

    {
      using namespace JPP;
      using namespace std;
 
      JPosition3D  D(pmt.getPosition());
      JDirection3D U(pmt.getDirection());
 
      D.sub(shower.getPosition());
 
      const double x  = D.getX();
      const double y  = D.getY();
      const double d  = D.getLength();  
      const double cd = D.getDot(shower.getDirection())/d;  // cosine angle between shower direction and PMT position
 
      U.rotate(JRotation3Z(-atan2(y,x)));                  // rotate PMT axis to x-z plane
 
      const double theta = getPMTAngle(U.getTheta());
      const double phi   = getPMTAngle(U.getPhi());
 
      JNPE_t::result_type H0 = getH0(pmt.getR());                        // background hypothesis value for time integrated PDF. 
      JNPE_t::result_type H1 = getH1(d, cd, theta, phi, shower.getE());  // signal hypothesis value for time integrated PDF. 
 
      if (get_value(H1) >= Vmax_npe) {
        H1 *= Vmax_npe / get_value(H1);
      }
 
      double signal_npe = get_value(H1);
 
      H1 += H0; // now H1 is signal + background
 
      double expectation = get_value(H1);
 
      const bool hit = pmt.getN() != 0;
      const double u = H1.getChi2(hit) - H0.getChi2(hit);
 
      result_type result;
 
      result.chi2     = estimator->getRho(u);
 
      double energy_gradient = signal_npe/shower.getE(); // dP/dE
      if(hit) energy_gradient *= -exp(-expectation)/(1-exp(-expectation)); //dchi2/d(H1), if !hit is 1
 
      result.gradient = JShower3EZ(JPoint4D(JVector3D(0,       // d(cos_th0)/d(x)
                                                      0,       // d(cos_th0)/d(y)
                                                      0),          // d(cos_th0)/d(z) 
                                            0.0),                                 // d(cos_th0)/d(t) 
                                   JVersor3Z(x/d,                // d(cos_th0)/d(dx)
                                             y/d),               // d(cos_th0)/d(dy)  
                                   energy_gradient);                                          // d(chi2)/d(E)
     
      result.gradient.mul(estimator->getPsi(u));
      static_cast<JShower3Z&>(result.gradient).mul(H1.getDerivativeOfChi2(hit) - H0.getDerivativeOfChi2(hit));                    // x d(chi2)/d(cos_th0)
      
      return result;
    }

getH0()

JNPE_t::result_type JFIT::JRegressor< JShower3EZ, JGandalf >::getH0 ( const double  R_Hz ) const

inline

Get background hypothesis value for time integrated PDF.

Parameters

R_Hz

rate [Hz]

Returns

hypothesis value

Definition at line 416 of file JShower3EZRegressor.hh.

    {
      return JNPE_t::result_type(R_Hz * 1e-9 * T_ns.getLength(), 0.0);
    }

getH1()

JNPE_t::result_type JFIT::JRegressor< JShower3EZ, JGandalf >::getH1 ( const double  D, const double  cd, const double  theta, const double  phi, const double  E  ) const

inline

Get signal hypothesis value for time integrated PDF.

Parameters

D	PMT distance from shower [m]
cd	cosine angle between shower direction and PMT position
theta	PMT zenith angle [deg]
phi	PMT azimuth angle [deg]
E	shower energy [GeV]

Returns

hypothesis value

Definition at line 431 of file JShower3EZRegressor.hh.

    {
      JNPE_t::result_type h1 = JMATH::zero;
        
      for (int i = 0; i != NUMBER_OF_PDFS; ++i) {
 
        if (!npe[i].empty() && D <= npe[i].getXmax()) {
 
          try {
 
            JNPE_t::result_type y1 = E * npe[i](std::max(D, npe[i].getXmin()), cd, theta, phi);
          
            if (get_value(y1) > 0.0) {
              h1 += y1;
            }
          
          }
          catch(JLANG::JException& error) {
            ERROR(error << std::endl);
          }
        }
      }
 
      return h1;
    }

operator()() [2/3]

result_type JFIT::JAbstractRegressor< JShower3EZ , JGandalf >::operator() ( const JShower3EZ &  value, T  __begin, T  __end  )

inlineinherited

Global fit.

Parameters

value	start value
__begin	begin of data set
__end	end of data set

Returns

chi2

Definition at line 94 of file JRegressor.hh.

    {
      static_cast<minimiser_type&>(*this).value = value;
 
      return static_cast<minimiser_type&>(*this)(static_cast<regressor_type&>(*this), __begin, __end);
    }

operator()() [3/3]

template<class JModel_t >

template<class JFunction_t , class T , class ... Args>

result_type JFIT::JGandalf< JModel_t >::operator() ( const JFunction_t &  fit, T  __begin, T  __end, Args ...  args  )

inlineinherited

Multi-dimensional fit of multiple data sets.

The fit function should return the chi2 as well as the partial derivatives for the current value of the model and a given data point.

Parameters

fit	fit function
__begin	begin of data
__end	end of data
args	optional data

Returns

chi2 and gradient

Definition at line 160 of file JGandalf.hh.

    {
      using namespace std;
      using namespace JPP;
 
      // note that all model values should be assigned to the start value of the model before use
      // because the actual list of model parameters can vary from fit to fit
      // (e.g. if model consists of a container).
 
      const size_t N = parameters.size();
 
      V.resize(N);
      h.resize(N);
      x.resize(N);
 
      previous.result.chi2 = numeric_limits<double>::max();
 
      current.result.chi2     = numeric_limits<double>::max();
      current.result.gradient = value;
      current.result.gradient = zero;
 
      error     = value;
      error     = zero;
 
      lambda    = LAMBDA_MIN;
 
      for (numberOfIterations = 0; numberOfIterations != MAXIMUM_ITERATIONS; ++numberOfIterations) {
 
        DEBUG("step:     " << numberOfIterations << endl);
 
        reset();
 
        update(fit, __begin, __end, args...);
 
        DEBUG("lambda:   " << FIXED(12,5) << lambda              << endl);
        DEBUG("chi2:     " << FIXED(12,5) << current.result.chi2 << endl);
 
        if (current.result.chi2 < previous.result.chi2) {
 
          if (numberOfIterations != 0) {
 
            const double tolerance = EPSILON * (EPSILON_ABSOLUTE ? 1.0 : fabs(previous.result.chi2)); 
 
            if (fabs(previous.result.chi2 - current.result.chi2) <= tolerance) {
 
              // normal end
 
              const result_type result = current.result;
 
              reset();
 
              update(fit, __begin, __end, args...);
 
              try {
                V.invert();
              }
              catch (const exception& error) {}
 
              for (size_t i = 0; i != N; ++i) {
                get(error, parameters[i]) = sqrt(V(i,i));
              }
 
              return result;
            }
 
            if (lambda > LAMBDA_MIN) {
              lambda /= LAMBDA_DOWN;
            }
          }
 
          // store current values
 
          previous.value  = value;
          previous.result = current.result;
 
        } else {
 
          value   = previous.value;                                 // restore value
 
          lambda *= LAMBDA_UP;
          
          if (lambda > LAMBDA_MAX) {
            break;
          }
 
          reset();
 
          update(fit, __begin, __end, args...);
        }
 
        DEBUG("Hesse matrix:" << endl << V << endl);
 
        // force definite positiveness
 
        for (size_t i = 0; i != N; ++i) {
 
          if (V(i,i) < PIVOT) {
            V(i,i) = PIVOT;
          }
 
          h[i] = 1.0 / sqrt(V(i,i));
        }
 
        // normalisation
        
        for (size_t row = 0; row != N; ++row) {
          for (size_t col = 0; col != row; ++col) {
            V(row,col) *= h[row] * h[col];
            V(col,row)  = V(row,col);
          }
        }
        
        for (size_t i = 0; i != N; ++i) {
          V(i,i) = 1.0 + lambda;
        }
 
        // solve A x = b
 
        for (size_t col = 0; col != N; ++col) {
          x[col] = h[col] * get(current.result.gradient, parameters[col]);
        }
 
        try {
          V.solve(x);
        }
        catch (const exception& error) {
 
          ERROR("JGandalf: " << error.what() << endl << V << endl);
 
          break;
        }
 
        // update value
 
        for (size_t row = 0; row != N; ++row) {
 
          DEBUG("u[" << noshowpos << setw(3) << row << "] = " << showpos << FIXED(15,5) << get(value, parameters[row]));
 
          get(value, parameters[row]) -= h[row] * x[row];
 
          DEBUG(" -> " << FIXED(15,5) << get(value, parameters[row]) << noshowpos << endl);
        }
 
        model(value);
      }
 
      // abnormal end
 
      const result_type result = previous.result;
 
      value   = previous.value;                                     // restore value
 
      reset();
 
      update(fit, __begin, __end, args...);
 
      try {
        V.invert();
      }
      catch (const exception& error) {}
 
      for (size_t i = 0; i != N; ++i) {
        get(error, parameters[i]) = sqrt(V(i,i));
      }
 
      return result;
    }

reset()

template<class JModel_t >

void JFIT::JGandalf< JModel_t >::reset ( )

inlineprivateinherited

Reset current parameters.

Definition at line 349 of file JGandalf.hh.

    {
      using namespace JPP;
 
      current.result.chi2     = 0.0;
      current.result.gradient = zero;
 
      V.reset();          
    }

update() [1/2]

template<class JModel_t >

template<class JFunction_t , class T , class ... Args>

void JFIT::JGandalf< JModel_t >::update ( const JFunction_t &  fit, T  __begin, T  __end, Args ...  args  )

inlineprivateinherited

Recursive method to update current parameters.

Parameters

fit	fit function
__begin	begin of data
__end	end of data
args	optional data

Definition at line 369 of file JGandalf.hh.

    {
      for (T i = __begin; i != __end; ++i) {
 
        const result_type& result = fit(value, *i);
 
        current.result.chi2     += result.chi2;
        current.result.gradient += result.gradient;
 
        for (size_t row = 0; row != parameters.size(); ++row) {
          for (size_t col = row; col != parameters.size(); ++col) {
            V(row,col) += get(result.gradient, parameters[row]) * get(result.gradient, parameters[col]);
          }
        }
      }
 
      update(fit, args...);
    }

update() [2/2]

template<class JModel_t >

template<class JFunction_t >

void JFIT::JGandalf< JModel_t >::update ( const JFunction_t &  fit )

inlineprivateinherited

Termination method to update current parameters.

Parameters

fit	fit function

Definition at line 395 of file JGandalf.hh.

    {
      for (size_t row = 0; row != parameters.size(); ++row) {
        for (size_t col = 0; col != row; ++col) {
          V(row,col) = V(col,row);
        }
      }
    }

get() [1/6]

template<class JModel_t >

static double JFIT::JGandalf< JModel_t >::get ( const JModel_t &  model, double JModel_t::*  parameter  )

inlinestaticprivateinherited

Read/write access to parameter value by data member.

Parameters

model	model
parameter	parameter

Returns

value

Definition at line 412 of file JGandalf.hh.

    {
      return model.*parameter;
    }

get() [2/6]

template<class JModel_t >

static double& JFIT::JGandalf< JModel_t >::get ( JModel_t &  model, double JModel_t::*  parameter  )

inlinestaticprivateinherited

Read/write access to parameter value by data member.

Parameters

model	model
parameter	parameter

Returns

value

Definition at line 425 of file JGandalf.hh.

    {
      return model.*parameter;
    }

get() [3/6]

template<class JModel_t >

static double JFIT::JGandalf< JModel_t >::get ( const JModel_t &  model, const size_t  index  )

inlinestaticprivateinherited

Read/write access to parameter value by index.

Parameters

model	model
index	index

Returns

value

Definition at line 438 of file JGandalf.hh.

    {
      return model[index];
    }

get() [4/6]

template<class JModel_t >

static double& JFIT::JGandalf< JModel_t >::get ( JModel_t &  model, const size_t  index  )

inlinestaticprivateinherited

Read/write access to parameter value by index.

Parameters

model	model
index	index

Returns

value

Definition at line 451 of file JGandalf.hh.

    {
      return model[index];
    }

get() [5/6]

template<class JModel_t >

static double JFIT::JGandalf< JModel_t >::get ( const JModel_t &  model, const int  index  )

inlinestaticprivateinherited

Read/write access to parameter value by index.

Parameters

model	model
index	index

Returns

value

Definition at line 464 of file JGandalf.hh.

    {
      return model[index];
    }

get() [6/6]

template<class JModel_t >

static double& JFIT::JGandalf< JModel_t >::get ( JModel_t &  model, const int  index  )

inlinestaticprivateinherited

Read/write access to parameter value by index.

Parameters

model	model
index	index

Returns

value

Definition at line 477 of file JGandalf.hh.

    {
      return model[index];
    }

Member Data Documentation

T_ns

JTimeRange JFIT::JRegressor< JShower3EZ, JGandalf >::T_ns

static

Time window with respect to Cherenkov hypothesis [ns].

Definition at line 462 of file JShower3EZRegressor.hh.

Vmax_npe

double JFIT::JRegressor< JShower3EZ, JGandalf >::Vmax_npe = std::numeric_limits<double>::max()

static

Maximal integral of PDF [npe].

Definition at line 463 of file JShower3EZRegressor.hh.

NUMBER_OF_PDFS

const int JFIT::JRegressor< JShower3EZ, JGandalf >::NUMBER_OF_PDFS = 2

static

Definition at line 465 of file JShower3EZRegressor.hh.

pdf_t

const JPDFType_t JFIT::JRegressor< JShower3EZ, JGandalf >::pdf_t

static

Initial value:

= { DIRECT_LIGHT_FROM_EMSHOWER, 
                                                                 SCATTERED_LIGHT_FROM_EMSHOWER }

Definition at line 467 of file JShower3EZRegressor.hh.

npe

JNPE_t JFIT::JRegressor< JShower3EZ, JGandalf >::npe[NUMBER_OF_PDFS]

PDF.

Definition at line 469 of file JShower3EZRegressor.hh.

estimator

JLANG::JSharedPointer<JMEstimator> JFIT::JRegressor< JShower3EZ, JGandalf >::estimator

M-Estimator function.

Definition at line 471 of file JShower3EZRegressor.hh.

MAXIMUM_ITERATIONS

template<class JModel_t >

int JFIT::JGandalf< JModel_t >::MAXIMUM_ITERATIONS = 1000

staticinherited

maximal number of iterations

maximal number of iterations.

Definition at line 329 of file JGandalf.hh.

EPSILON

template<class JModel_t >

double JFIT::JGandalf< JModel_t >::EPSILON = 1.0e-3

staticinherited

maximal distance to minimum

maximal distance to minimum.

Definition at line 330 of file JGandalf.hh.

EPSILON_ABSOLUTE

template<class JModel_t >

bool JFIT::JGandalf< JModel_t >::EPSILON_ABSOLUTE = false

staticinherited

set epsilon to absolute difference instead of relative

set epsilon to absolute difference instead of relative.

Definition at line 331 of file JGandalf.hh.

LAMBDA_MIN

template<class JModel_t >

double JFIT::JGandalf< JModel_t >::LAMBDA_MIN = 0.01

staticinherited

minimal value control parameter

Definition at line 332 of file JGandalf.hh.

LAMBDA_MAX

template<class JModel_t >

double JFIT::JGandalf< JModel_t >::LAMBDA_MAX = 100.0

staticinherited

maximal value control parameter

Definition at line 333 of file JGandalf.hh.

LAMBDA_UP

template<class JModel_t >

double JFIT::JGandalf< JModel_t >::LAMBDA_UP = 10.0

staticinherited

multiplication factor control parameter

Definition at line 334 of file JGandalf.hh.

LAMBDA_DOWN

template<class JModel_t >

double JFIT::JGandalf< JModel_t >::LAMBDA_DOWN = 10.0

staticinherited

multiplication factor control parameter

Definition at line 335 of file JGandalf.hh.

PIVOT

template<class JModel_t >

double JFIT::JGandalf< JModel_t >::PIVOT = std::numeric_limits<double>::epsilon()

staticinherited

minimal value diagonal element of Hesse matrix

minimal value diagonal element of matrix

Definition at line 336 of file JGandalf.hh.

parameters

template<class JModel_t >

std::vector<parameter_type> JFIT::JGandalf< JModel_t >::parameters

inherited

fit parameters

Definition at line 338 of file JGandalf.hh.

numberOfIterations

template<class JModel_t >

int JFIT::JGandalf< JModel_t >::numberOfIterations

inherited

number of iterations

Definition at line 339 of file JGandalf.hh.

lambda

template<class JModel_t >

double JFIT::JGandalf< JModel_t >::lambda

inherited

control parameter

Definition at line 340 of file JGandalf.hh.

value

template<class JModel_t >

JModel_t JFIT::JGandalf< JModel_t >::value

inherited

value

Definition at line 341 of file JGandalf.hh.

error

template<class JModel_t >

JModel_t JFIT::JGandalf< JModel_t >::error

inherited

error

Definition at line 342 of file JGandalf.hh.

V

template<class JModel_t >

JMATH::JMatrixNS JFIT::JGandalf< JModel_t >::V

inherited

Hesse matrix.

Definition at line 343 of file JGandalf.hh.

h

template<class JModel_t >

std::vector<double> JFIT::JGandalf< JModel_t >::h

privateinherited

Definition at line 482 of file JGandalf.hh.

x

template<class JModel_t >

JMATH::JVectorND JFIT::JGandalf< JModel_t >::x

privateinherited

Definition at line 483 of file JGandalf.hh.

result

template<class JModel_t >

result_type JFIT::JGandalf< JModel_t >::result

inherited

Definition at line 486 of file JGandalf.hh.

struct { ... } JFIT::JGandalf< JModel_t >::current

struct { ... } JFIT::JGandalf< JModel_t >::previous

debug

template<class T >

int JEEP::JMessage< T >::debug = 0

staticinherited

debug level (default is off).

Definition at line 45 of file JMessage.hh.

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The documentation for this struct was generated from the following file:

• JShower3EZRegressor.hh