JFIT::JRegressor< JPoint4D, JGandalf > Struct Template Reference

#include <JPoint4DRegressor.hh>

Inheritance diagram for JFIT::JRegressor< JPoint4D, JGandalf >:

Public Types
typedef JGandalf< JPoint4D >	minimiser_type
typedef JRegressor< JPoint4D, JGandalf >	regressor_type
typedef minimiser_type::result_type	result_type
typedef JFIT_LOCAL::JTypedef_t < JPoint4D >::parameter_type	parameter_type
	Data type of fit parameter. More...

Public Member Functions
	JRegressor (double sigma)
	Constructor. More...
template<class JHit_t >
result_type	operator() (const JPoint4D &vx, const JHit_t &hit) const
result_type	operator() (const JPoint4D &value, T __begin, T __end)
	Global fit. More...
result_type	operator() (const JFunction_t &fit, T __begin, T __end, Args...args)
	Multi-dimensional fit of multiple data sets. More...

Public Attributes
JLANG::JSharedPointer < JMEstimator >	estimator
	M-Estimator function. More...
double	sigma
	Time resolution [ns]. More...
std::vector< parameter_type >	parameters
	fit parameters More...
int	numberOfIterations
	number of iterations More...
double	lambda
	control parameter More...
JPoint4D	value
	value More...
JPoint4D	error
	error More...
JMATH::JMatrixNS	V
	Hesse matrix. More...
result_type	result

Static Public Attributes
static int	MAXIMUM_ITERATIONS
	maximal number of iterations More...
static double	EPSILON
	maximal distance to minimum More...
static double	LAMBDA_MIN
	minimal value control parameter More...
static double	LAMBDA_MAX
	maximal value control parameter More...
static double	LAMBDA_UP
	multiplication factor control parameter More...
static double	LAMBDA_DOWN
	multiplication factor control parameter More...
static double	PIVOT
	minimal value diagonal element of Hesse matrix More...
static int	debug = 0
	debug level (default is off). More...

Detailed Description

template<>
struct JFIT::JRegressor< JPoint4D, JGandalf >

Definition at line 67 of file JPoint4DRegressor.hh.

Member Typedef Documentation

typedef JGandalf <JPoint4D > JFIT::JAbstractRegressor< JPoint4D , JGandalf >::minimiser_type

inherited

Definition at line 80 of file JRegressor.hh.

typedef JRegressor<JPoint4D , JGandalf > JFIT::JAbstractRegressor< JPoint4D , JGandalf >::regressor_type

inherited

Definition at line 81 of file JRegressor.hh.

typedef minimiser_type::result_type JFIT::JAbstractRegressor< JPoint4D , JGandalf >::result_type

inherited

Definition at line 82 of file JRegressor.hh.

typedef JFIT_LOCAL::JTypedef_t<JPoint4D >::parameter_type JFIT::JGandalf< JPoint4D >::parameter_type

inherited

Data type of fit parameter.

Definition at line 95 of file JGandalf.hh.

Constructor & Destructor Documentation

JFIT::JRegressor< JPoint4D, JGandalf >::JRegressor ( double  sigma )

inline

Constructor.

Definition at line 75 of file JPoint4DRegressor.hh.

    {
      this->sigma = sigma;
    }

Member Function Documentation

template<class JHit_t >

result_type JFIT::JRegressor< JPoint4D, JGandalf >::operator() ( const JPoint4D &  vx, const JHit_t &  hit  ) const

inline

Definition at line 89 of file JPoint4DRegressor.hh.

    {
      using namespace JPP;

      const double dt = hit.getT() - vx.getT(hit.getPosition());

      const double u  = dt / sigma;
      result_type result;
      result.chi2 = estimator->getRho(u) * hit.getW();

      JVector3D d = hit.getPosition() - vx.getPosition();
      
      double weight = getIndexOfRefraction() * getInverseSpeedOfLight()/(d.getLength() * sigma);
      
      result.gradient = hit.getW() * JPoint4D( d * weight,
                                               -1/sigma);
      result.gradient.mul(0.5 * estimator->getPsi(u));
      
      return result;
    }

result_type JFIT::JAbstractRegressor< JPoint4D , JGandalf >::operator() ( const JPoint4D &  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);
    }

result_type JFIT::JGandalf< JPoint4D >::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)) {

              // normal end

              const result_type result = current.result;

              lambda  = LAMBDA_MIN;

              reset();

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

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

              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

      lambda  = LAMBDA_MIN;

      reset();

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

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

      for (size_t i = 0; i != N; ++i) {
        get(error, parameters[i]) = sqrt(V(i,i));
      }

      return result;
    }

Member Data Documentation

JLANG::JSharedPointer<JMEstimator> JFIT::JRegressor< JPoint4D, JGandalf >::estimator

M-Estimator function.

Definition at line 110 of file JPoint4DRegressor.hh.

double JFIT::JRegressor< JPoint4D, JGandalf >::sigma

Time resolution [ns].

Definition at line 111 of file JPoint4DRegressor.hh.

int JFIT::JGandalf< JPoint4D >::MAXIMUM_ITERATIONS

staticinherited

maximal number of iterations

maximal number of iterations.

Definition at line 335 of file JGandalf.hh.

double JFIT::JGandalf< JPoint4D >::EPSILON

staticinherited

maximal distance to minimum

maximal distance to minimum.

Definition at line 336 of file JGandalf.hh.

double JFIT::JGandalf< JPoint4D >::LAMBDA_MIN

staticinherited

minimal value control parameter

Definition at line 337 of file JGandalf.hh.

double JFIT::JGandalf< JPoint4D >::LAMBDA_MAX

staticinherited

maximal value control parameter

Definition at line 338 of file JGandalf.hh.

double JFIT::JGandalf< JPoint4D >::LAMBDA_UP

staticinherited

multiplication factor control parameter

Definition at line 339 of file JGandalf.hh.

double JFIT::JGandalf< JPoint4D >::LAMBDA_DOWN

staticinherited

multiplication factor control parameter

Definition at line 340 of file JGandalf.hh.

double JFIT::JGandalf< JPoint4D >::PIVOT

staticinherited

minimal value diagonal element of Hesse matrix

minimal value diagonal element of matrix

Definition at line 341 of file JGandalf.hh.

std::vector<parameter_type> JFIT::JGandalf< JPoint4D >::parameters

inherited

fit parameters

Definition at line 343 of file JGandalf.hh.

int JFIT::JGandalf< JPoint4D >::numberOfIterations

inherited

number of iterations

Definition at line 344 of file JGandalf.hh.

double JFIT::JGandalf< JPoint4D >::lambda

inherited

control parameter

Definition at line 345 of file JGandalf.hh.

JPoint4D JFIT::JGandalf< JPoint4D >::value

inherited

value

Definition at line 346 of file JGandalf.hh.

JPoint4D JFIT::JGandalf< JPoint4D >::error

inherited

error

Definition at line 347 of file JGandalf.hh.

JMATH::JMatrixNS JFIT::JGandalf< JPoint4D >::V

inherited

Hesse matrix.

Definition at line 348 of file JGandalf.hh.

result_type JFIT::JGandalf< JPoint4D >::result

inherited

Definition at line 491 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 struct was generated from the following file:

• JPoint4DRegressor.hh