Regressor function object for JLine3Z fit using JSimplex minimiser. More...

#include <JLine3ZRegressor.hh>

Inheritance diagram for JFIT::JRegressor< JLine3Z, JSimplex >:

Public Types
typedef JSimplex< JLine3Z >	minimiser_type

typedef JRegressor< JLine3Z, JSimplex >	regressor_type

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

template<class JHit_t >
double	operator() (const JLine3Z &track, const JHit_t &hit) const
	Fit function. More...

double	operator() (const JLine3Z &value, T __begin, T __end)
	Global fit. More...

double	operator() (const JLine3Z &value, T1 __begin1, T1 __end1, T2 __begin2, T2 __end2)
	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 JLine3Z &step)
	1D fit. More...

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

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

JLine3Z	value

std::vector< JLine3Z >	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< JLine3Z, JSimplex >

Regressor function object for JLine3Z fit using JSimplex minimiser.

Definition at line 50 of file JLine3ZRegressor.hh.

Member Typedef Documentation

typedef JSimplex <JLine3Z > JFIT::JAbstractRegressor< JLine3Z , JSimplex >::minimiser_type

inherited

Definition at line 76 of file JRegressor.hh.

typedef JRegressor<JLine3Z , JSimplex > JFIT::JAbstractRegressor< JLine3Z , JSimplex >::regressor_type

inherited

Definition at line 77 of file JRegressor.hh.

Constructor & Destructor Documentation

JFIT::JRegressor< JLine3Z, JSimplex >::JRegressor ( double sigma )

inline

Constructor.

Parameters

sigma time resolution of hit [ns]

Definition at line 60 of file JLine3ZRegressor.hh.

                              :
       estimator(new JMEstimatorNormal())
     {
       this->sigma = sigma;
     }

Member Function Documentation

template<class JHit_t >

double JFIT::JRegressor< JLine3Z, JSimplex >::operator()	(	const JLine3Z &	track,
		const JHit_t &	hit
	)		const

inline

Fit function.

This method is used to determine the chi2 of given hit with respect to trajectory of muon.

The template argument JHit_t refers to a data structure which should have the following member methods:

double getX(); // [m]
double getY(); // [m]
double getZ(); // [m]
double getT(); // [ns]

Parameters

track	track
hit	hit

Returns: chi2

Definition at line 82 of file JLine3ZRegressor.hh.

     {
       using namespace JGEOMETRY3D;
       using namespace JTOOLS;
 
       JPosition3D D(hit.getX(), hit.getY(), hit.getZ());
 
       D.sub(track.getPosition());
 
       const double z  = D.getDot(track.getDirection());
       const double R  = sqrt(D.getLengthSquared() - z*z);
 
       const double t1 = track.getT() + (z + R * getKappaC()) * getInverseSpeedOfLight();
 
       const double u  = (t1 - hit.getT()) / sigma;
 
       return estimator->getRho(u) * hit.getW();
     }

double JFIT::JAbstractRegressor< JLine3Z , JSimplex >::operator()	(	const JLine3Z &	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 89 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::JAbstractRegressor< JLine3Z , JSimplex >::operator()	(	const JLine3Z &	value,
		T1	__begin1,
		T1	__end1,
		T2	__begin2,
		T2	__end2
	)

inlineinherited

Global fit.

Parameters

value	start value
__begin1	begin of first data set
__end1	end of first data set
__begin2	begin of second data set
__end2	end of second data set

Returns: chi2

Definition at line 108 of file JRegressor.hh.

     {
       static_cast<minimiser_type&>(*this).value = value;
 
       return static_cast<minimiser_type&>(*this)(static_cast<regressor_type&>(*this), __begin1, __end1, __begin2, __end2);
     }

double JFIT::JSimplex< JLine3Z >::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 69 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) {
 
         double chi2[N];
 
         numberOfIterations = 0;
 
         while (numberOfIterations != MAXIMUM_ITERATIONS) {
 
           DEBUG("old: " << FIXED(12,5) << chi2_old << endl);
 
           const JModel_t 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
 
           JModel_t wall = value - 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 - 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< JLine3Z >::operator()	(	const JFunction_t &	fit,
		T	__begin,
		T	__end,
		const JLine3Z &	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 171 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) {
 
         value += lambda * step;
 
         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) {
 
             value -= lambda * step;                            // undo last step
 
             return chi2_old;
 
           } else {
 
             return chi2_new;
           }
         }
 
         if (chi2_new < chi2_old) {
 
           chi2_old = chi2_new;
 
         } else {
             
           value  -=  lambda * step;                            // step back
           lambda  = -lambda;                                   // change direction
           
           if (i != 0) {
             factor = 0.5;                                      // reduce step size
           }
         }
         
         lambda = factor * lambda;
       }
 
       return chi2_old;
     }