Regressor function object for JPoint4D fit using JSimplex minimiser. More...

#include <JPoint4DRegressor.hh>

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

Public Types
typedef JSimplex< JPoint4D >	minimiser_type

typedef JRegressor< JPoint4D, JSimplex >	regressor_type

typedef minimiser_type::result_type	result_type

Public Member Functions
	JRegressor (double sigma)
	Constructor. More...

template<class JHit_t >
double	operator() (const JPoint4D &vx, const JHit_t &hit) const

result_type	operator() (const JPoint4D &value, T __begin, T __end)
	Global fit. More...

double	operator() (const JFunction_t &fit, T __begin, T __end)
	Multi-dimensional fit. More...

double	operator() (const JFunction_t &fit, T __begin, T __end, const JPoint4D &step)
	1D fit. More...

Public Attributes
JLANG::JSharedPointer < JMEstimator >	estimator
	M-Estimator function. More...

double	sigma
	Time resolution [ns]. More...

JPoint4D	value

std::vector< JPoint4D >	step

int	numberOfIterations

Static Public Attributes
static int	MAXIMUM_ITERATIONS
	maximal number of iterations More...

static double	EPSILON
	maximal distance to minimum More...

static int	debug = 0
	debug level (default is off). More...

Detailed Description

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

Regressor function object for JPoint4D fit using JSimplex minimiser.

Definition at line 28 of file JPoint4DRegressor.hh.

Member Typedef Documentation

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

inherited

Definition at line 78 of file JRegressor.hh.

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

inherited

Definition at line 79 of file JRegressor.hh.

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

inherited

Definition at line 80 of file JRegressor.hh.

Constructor & Destructor Documentation

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

inline

Constructor.

Definition at line 36 of file JPoint4DRegressor.hh.

     {
       this->sigma = sigma;
     }

Member Function Documentation

template<class JHit_t >

double JFIT::JRegressor< JPoint4D, JSimplex >::operator()	(	const JPoint4D &	vx,
		const JHit_t &	hit
	)		const

inline

Definition at line 50 of file JPoint4DRegressor.hh.

     {
       using namespace JPP;
       
       const double dt = hit.getT() - vx.getT(hit.getPosition());
       
       const double u  = dt / sigma;
       
       return estimator->getRho(u) * hit.getW();
     }

result_type JFIT::JAbstractRegressor< JPoint4D , JSimplex >::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 92 of file JRegressor.hh.

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

double JFIT::JSimplex< JPoint4D >::operator()	(	const JFunction_t &	fit,
		T	__begin,
		T	__end
	)

inlineinherited

Multi-dimensional fit.

The given fit function should return the equivalent of chi2 for the current value of the given model and a given data point.

Parameters

fit	fit function
__begin	begin of data
__end	end of data

Returns: chi2

Definition at line 71 of file JSimplex.hh.

     {
       using namespace std;
       using namespace JPP;
 
       double chi2_old = evaluate(fit, __begin, __end);
 
       const int N = step.size();
 
       if (N != 0) {
 
         p0   = value;
         p1   = value;
         wall = value;
 
         double chi2[N];
 
         numberOfIterations = 0;
 
         while (numberOfIterations != MAXIMUM_ITERATIONS) {
 
           DEBUG("old: " << FIXED(12,5) << chi2_old << endl);
 
           p0 = value;
 
           for (int i = 0; i != N; ++i) {
 
             DEBUG("step: " << i << ' ' << setw(5) << numberOfIterations << endl);
 
             chi2[i] = (*this)(fit, __begin, __end, step[i]);
           }
 
           // overall step direction of last iteration
 
           wall  = value;
           wall -= p0;
 
           const double chi2_new = (*this)(fit, __begin, __end, wall);
 
           DEBUG("new: " << FIXED(12,5) << chi2_new << endl);
 
 
           if (fabs(chi2_old - chi2_new) < EPSILON*fabs(chi2_old)) {
             return chi2_new;
           }
 
           // double overall step
 
           wall   = value;
           wall  -= p0;
           value += wall;
 
           const double fe = evaluate(fit, __begin, __end);
 
           value -= wall;
 
 
           for (int i = N-1; i != 0; --i) {
             chi2[i] = chi2[i-1] - chi2[i];
           }
 
           chi2[0] = chi2_old - chi2[0];
 
 
           double df = 0.0;
 
           for (int i = 0; i != N; ++i) {
             if (chi2[i] > df) {
               df = chi2[i];
             }
           }
 
           const double fn = chi2_new;
           const double f0 = chi2_old;
           const double ff = f0 - fn - df;
 
           // shift step directions
 
           if (fe < f0 && 2.0*(f0 - 2.0*fn + fe)*ff*ff < (f0-fe)*(f0-fe)*df) {
 
             for (int i = 0; i != N - 1; ++i) {
               step[i] = step[i+1];
             }
 
             step[N-1] = wall;
           }
 
           chi2_old = chi2_new;
         }
       }
 
       return chi2_old;
     }

double JFIT::JSimplex< JPoint4D >::operator()	(	const JFunction_t &	fit,
		T	__begin,
		T	__end,
		const JPoint4D &	step
	)

inlineinherited

1D fit.

The given fit function should return the equivalent of chi2 for the current value of the given model and a given data point.

Parameters

fit	fit function
__begin	begin of data
__end	end of data
step	step direction

Definition at line 178 of file JSimplex.hh.

     {
       using namespace std;
       using namespace JPP;
 
       double lambda = 0.5;                                     // control parameter
       double factor = 1.0;                                     // multiplication factor
 
       double chi2_old = evaluate(fit, __begin, __end);
 
       for (int i = 0; numberOfIterations != MAXIMUM_ITERATIONS; ++numberOfIterations, ++i) {
 
         p1      = step;
         p1     *= lambda;
         value  += p1;
 
         const double chi2_new = evaluate(fit, __begin, __end);
 
         DEBUG("step: " << setw(3) << i << ' ' << FIXED(12,5) << chi2_old << ' ' << FIXED(12,5) << chi2_new << ' ' << FIXED(5,2) << lambda << endl);
 
         if (fabs(chi2_old - chi2_new) < EPSILON*fabs(chi2_old)) {
 
           if (chi2_new > chi2_old) {
 
             p1      = step;
             p1     *= lambda;
             value  -= p1;                                      // undo last step
 
             return chi2_old;
 
           } else {
 
             return chi2_new;
           }
         }
 
         if (chi2_new < chi2_old) {
 
           chi2_old = chi2_new;
 
         } else {
             
           p1      = step;
           p1     *= lambda;
           value  -=  p1;                                       // step back
           lambda  = -lambda;                                   // change direction
           
           if (i != 0) {
             factor = 0.5;                                      // reduce step size
           }
         }
         
         lambda = factor * lambda;
       }
 
       return chi2_old;
     }