JROOT::JRootfit_t< JFs_t > Class Template Reference

Base class for result of ROOT Fit. More...

#include <JRootfit.hh>

Inheritance diagram for JROOT::JRootfit_t< JFs_t >:

Public Types
typedef JFIT_LOCAL::JTypedef_t < JModel_t >::parameter_type	parameter_type
	Data type of fit parameter. More...

Public Member Functions
const JFs_t &	getFunction () const
	Get function. More...
size_t	getNumberOfParameters () const
	Get number of parameters. More...
size_t	getNumberOfFreeParameters () const
	Get number of free parameters. More...
size_t	getN () const
	Get number of data points. More...
double	getChi2 () const
	Get chi2. More...
int	getNDF () const
	Get number of degrees of freedom. More...
double	getValue (size_t i) const
	Get value of parameter at given index. More...
double	getError (size_t i) const
	Get error of parameter at given index. 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
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 int	MAXIMUM_ITERATIONS = 1000
	maximal number of iterations More...
static double	EPSILON = 1.0e-3
	maximal distance to minimum 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...

Protected Member Functions
	JRootfit_t ()
	Default constructor. More...

Protected Attributes
size_t	npx
	number of data points More...
double	chi2
	chi2 More...

Detailed Description

template<class JFs_t>
class JROOT::JRootfit_t< JFs_t >

Base class for result of ROOT Fit.

Definition at line 827 of file JRootfit.hh.

Member Typedef Documentation

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

template<class JFs_t >

JROOT::JRootfit_t< JFs_t >::JRootfit_t ( )

inlineprotected

Default constructor.

Definition at line 834 of file JRootfit.hh.

                 :
      npx (0),
      chi2(0.0)
    {}

Member Function Documentation

template<class JFs_t >

const JFs_t& JROOT::JRootfit_t< JFs_t >::getFunction ( ) const

inline

Get function.

Returns

function.

Definition at line 849 of file JRootfit.hh.

    {
      return this->value;
    }

template<class JFs_t >

size_t JROOT::JRootfit_t< JFs_t >::getNumberOfParameters ( ) const

inline

Get number of parameters.

Returns

number of parameters

Definition at line 860 of file JRootfit.hh.

    {
      return JFs_t::parameters.size();
    }

template<class JFs_t >

size_t JROOT::JRootfit_t< JFs_t >::getNumberOfFreeParameters ( ) const

inline

Get number of free parameters.

Returns

number of free parameters

Definition at line 871 of file JRootfit.hh.

    {
      return this->parameters.size();
    }

template<class JFs_t >

size_t JROOT::JRootfit_t< JFs_t >::getN ( ) const

inline

Get number of data points.

Returns

number of data points

Definition at line 882 of file JRootfit.hh.

    {
      return npx;
    }

template<class JFs_t >

double JROOT::JRootfit_t< JFs_t >::getChi2 ( ) const

inline

Get chi2.

Returns

chi2

Definition at line 893 of file JRootfit.hh.

    {
      return chi2;
    }

template<class JFs_t >

int JROOT::JRootfit_t< JFs_t >::getNDF ( ) const

inline

Get number of degrees of freedom.

Returns

number of degrees of freedom

Definition at line 904 of file JRootfit.hh.

    {
      return (int) getN() - (int) getNumberOfFreeParameters();
    }

template<class JFs_t >

double JROOT::JRootfit_t< JFs_t >::getValue ( size_t  i ) const

inline

Get value of parameter at given index.

Parameters

i

index

Definition at line 915 of file JRootfit.hh.

    {
      return getParameter(this->value, i);
    }

template<class JFs_t >

double JROOT::JRootfit_t< JFs_t >::getError ( size_t  i ) const

inline

Get error of parameter at given index.

Parameters

i

index

Definition at line 926 of file JRootfit.hh.

    {
      return getParameter(this->error, i);
    }

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) {

            if (fabs(previous.result.chi2 - current.result.chi2) < EPSILON*fabs(previous.result.chi2)) {

              const result_type result = current.result;

              reset();

              update(fit, __begin, __end, args...);

              try {
                V.invert();
              }
              catch (const exception& error) {
                V.reset();
              }

              return result;                                        // normal end
            }

            if (lambda > LAMBDA_MIN) {
              lambda /= LAMBDA_DOWN;
            }
          }
            // store current values

            previous.value  = value;
            previous.error  = error;
            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 and error

        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];
          get(error, parameters[row])  = h[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
      error   = previous.error;                                     // restore error

      reset();

      update(fit, __begin, __end, args...);

      try {
        V.invert();
      }
      catch (const exception& error) {
        V.reset();
      }

      return result;
    }

Member Data Documentation

template<class JFs_t >

size_t JROOT::JRootfit_t< JFs_t >::npx

protected

number of data points

Definition at line 840 of file JRootfit.hh.

template<class JFs_t >

double JROOT::JRootfit_t< JFs_t >::chi2

protected

chi2

Definition at line 841 of file JRootfit.hh.

template<class JModel_t>

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

staticinherited

maximal number of iterations

maximal number of iterations.

Definition at line 322 of file JGandalf.hh.

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 323 of file JGandalf.hh.

template<class JModel_t>

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

staticinherited

minimal value control parameter

Definition at line 324 of file JGandalf.hh.

template<class JModel_t>

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

staticinherited

maximal value control parameter

Definition at line 325 of file JGandalf.hh.

template<class JModel_t>

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

staticinherited

multiplication factor control parameter

Definition at line 326 of file JGandalf.hh.

template<class JModel_t>

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

staticinherited

multiplication factor control parameter

Definition at line 327 of file JGandalf.hh.

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 328 of file JGandalf.hh.

template<class JModel_t>

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

inherited

fit parameters

Definition at line 330 of file JGandalf.hh.

template<class JModel_t>

int JFIT::JGandalf< JModel_t >::numberOfIterations

inherited

number of iterations

Definition at line 331 of file JGandalf.hh.

template<class JModel_t>

double JFIT::JGandalf< JModel_t >::lambda

inherited

control parameter

Definition at line 332 of file JGandalf.hh.

template<class JModel_t>

JModel_t JFIT::JGandalf< JModel_t >::value

inherited

value

Definition at line 333 of file JGandalf.hh.

template<class JModel_t>

JModel_t JFIT::JGandalf< JModel_t >::error

inherited

error

Definition at line 334 of file JGandalf.hh.

template<class JModel_t>

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

inherited

Hesse matrix.

Definition at line 335 of file JGandalf.hh.

template<class JModel_t>

result_type JFIT::JGandalf< JModel_t >::result

inherited

Definition at line 478 of file JGandalf.hh.

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 class was generated from the following file:

• JRootfit.hh