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::JPolint1FunctionalMapH, JTOOLS::JMapList < JTOOLS::JPolint1FunctionalMap, 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 JShower3EZ::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 cosDelta, const double theta, const double phi, const double E) const
	Get signal hypothesis value for time integrated PDF. More...

double	getRmax () const
	Get maximal road width of PDF. More...

result_type	operator() (const JShower3EZ &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 two data sets. More...

Public Attributes
JNPE_t	npe [NUMBER_OF_PDFS]
	PDF. More...

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

double	lambda

JShower3EZ	value

JShower3EZ	error

std::vector< parameter_type >	parameters

int	numberOfIterations

JMATH::JMatrixNS	H

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
	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 matrix More...

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

Detailed Description

template<>
struct JFIT::JRegressor< JShower3EZ, JGandalf >

Regressor function object for JShower3EZ fit using JGandalf minimiser.

Definition at line 253 of file JShower3EZRegressor.hh.

Member Typedef Documentation

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

Definition at line 258 of file JShower3EZRegressor.hh.

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 262 of file JShower3EZRegressor.hh.

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

Definition at line 263 of file JShower3EZRegressor.hh.

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

Definition at line 268 of file JShower3EZRegressor.hh.

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

Definition at line 269 of file JShower3EZRegressor.hh.

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

inherited

Definition at line 78 of file JRegressor.hh.

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

inherited

Definition at line 79 of file JRegressor.hh.

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

inherited

Definition at line 80 of file JRegressor.hh.

typedef JShower3EZ ::parameter_type JFIT::JGandalf< JShower3EZ >::parameter_type

inherited

Data type of fit parameter.

Definition at line 63 of file JGandalf.hh.

Constructor & Destructor Documentation

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

inline

Parameterized constructor.

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

Parameters

fileDescriptor PDF file descriptor

Definition at line 280 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

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 330 of file JShower3EZRegressor.hh.

     {
       using namespace JPP;
       using namespace std;
       
       JPosition3D D(pmt.getPosition());
       JDirection3D U(pmt.getDirection());
 
       D.sub(shower.getPosition());
 
       JVersor3D shower_dir(shower.getDirection());
 
       const double z  = D.getDot(shower_dir);
       const double x  = D.getX()  -  z * shower.getDX();
       const double y  = D.getY()  -  z * shower.getDY();
       const double R2 = D.getLengthSquared() - z*z;
       const double R = sqrt(R2);
       const double d = D.getLength();  
       const double cos_th0 = z/d;  // theta0 = angle between shower direction and PMT position
  
       U.rotate(JRotation3Z(-atan2(y,x)));                  // rotate PMT axis to x-z plane
 
       const double theta = U.getTheta();
       const double phi   = fabs(U.getPhi());
 
       JNPE_t::result_type H0 = getH0(pmt.getR());  // getH0 = Get background hypothesis value for time integrated PDF. 
       JNPE_t::result_type H1 = getH1(d, cos_th0, theta, phi, shower.getE());  // getH1 = Get signal hypothesis value for time integrated PDF. 
 
       if (get_value(H1) >= Vmax_npe) {
         H1 *= Vmax_npe / get_value(H1);
       }
 
       H1 += H0; // now H1 is signal + background
 
       const bool hit = pmt.getN() != 0;
       const double u = H1.getChi2(hit);
 
       result_type result;      
 
       result.chi2     = estimator->getRho(u);
 
       result.gradient = JShower3EZ(JPoint4D(JVector3D(x*z / (d*d*d),       // d(cos_th0)/d(x)
                                                       y*z / (d*d*d),       // d(cos_th0)/d(y)
                                                       -(R*R) / (d*d*d)),          // d(cos_th0)/d(z) 
                                             0.0),                                 // d(cos_th0)/d(t) 
                                    JVersor3Z(x*z*z / (d*R),                // d(cos_th0)/d(dx)
                                              y*z*z / (d*R)),               // d(cos_th0)/d(dy)  
                                    0.0);                                          // d(cos_th0)/d(E)
       
       result.gradient.mul(estimator->getPsi(u));
       result.gradient.mul(H1.getDerivativeOfChi2(hit));                    // x d(chi2)/d(cos_th0)
        
       return result;
     }

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 391 of file JShower3EZRegressor.hh.

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

JNPE_t::result_type JFIT::JRegressor< JShower3EZ, JGandalf >::getH1	(	const double	D,
		const double	cosDelta,
		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]
cosDelta	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 406 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()), cosDelta, theta, phi);
           
             if (get_value(y1) > 0.0) {
               h1 += y1;
             }
           
           }
           catch(JLANG::JException& error) {
             ERROR(error << std::endl);
           }
         }
       }
 
       return h1;
     }

double JFIT::JRegressor< JShower3EZ, JGandalf >::getRmax ( ) const

inline

Get maximal road width of PDF.

Returns: road width [m]

Definition at line 442 of file JShower3EZRegressor.hh.

     {
       double xmax = 0.0;
 
       for (int i = 0; i != NUMBER_OF_PDFS; ++i) {
 
         if (!npe[i].empty() && npe[i].getXmax() > xmax) {
           xmax = npe[i].getXmax();
         }
         
       }
 
       return xmax;
     }

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 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);
     }

result_type JFIT::JGandalf< JShower3EZ >::operator()	(	const JFunction_t &	fit,
		T	__begin,
		T	__end,
		Args...	args
	)

inlineinherited

Multi-dimensional fit of two data sets.

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

Parameters

fit	fit function
__begin	begin of data
__end	end of data

Returns: chi2

Definition at line 127 of file JGandalf.hh.

     {
       using namespace std;
       using namespace JPP;
 
       const int N = parameters.size();
 
       H.resize(N);
       h.resize(N);
 
       previous  = value;
 
       successor.gradient = value;
       successor.gradient = zero;
 
       error     = value;
       error     = zero;
 
       lambda    = LAMBDA_MIN;
 
       result_type precessor = result_type(numeric_limits<double>::max(), value);
 
       for (numberOfIterations = 0; numberOfIterations != MAXIMUM_ITERATIONS; ++numberOfIterations) {
 
         DEBUG("step:     " << numberOfIterations << endl);
 
         reset();
 
         __evaluate__(fit, __begin, __end, args...);
 
         DEBUG("lambda:   " << SCIENTIFIC(12,5) << lambda         << endl);
         DEBUG("chi2:     " << FIXED     (12,5) << successor.chi2 << endl);
 
         if (successor.chi2 < precessor.chi2) {
 
           if (numberOfIterations != 0) {
 
             if (fabs(precessor.chi2 - successor.chi2) < EPSILON*fabs(precessor.chi2)) {
               return successor;
             }
 
             if (lambda > LAMBDA_MIN) {
               lambda /= LAMBDA_DOWN;
             }
           }
 
           precessor = successor;
           previous  = value;
 
         } else {
           
           value   = previous;
           lambda *= LAMBDA_UP;
           
           if (lambda > LAMBDA_MAX) {
             return precessor;                                   // no improvement found
           }
 
           reset();
           
           __evaluate__(fit, __begin, __end, args...);
         }
 
         DEBUG("Hesse matrix:" << endl);
         DEBUG(H << endl);
 
 
         // force definite positiveness
 
         for (int i = 0; i != N; ++i) {
 
           if (H(i,i) < PIVOT) {
             H(i,i) = PIVOT;
           }
 
           h[i] = 1.0 / sqrt(H(i,i));
         }
 
 
         // normalisation
         
         for (int i = 0; i != N; ++i) {
           for (int j = 0; j != i; ++j) {
             H(j,i) *= h[i] * h[j];
             H(i,j)  = H(j,i);
           }
         }
         
         for (int i = 0; i != N; ++i) {
           H(i,i) = 1.0 + lambda;
         }
 
         
         try {
           H.invert();
         }
         catch (const JException& error) {
           ERROR("JGandalf: " << error.what() << endl);
           return precessor;
         }
         
         
         for (int i = 0; i != N; ++i) {
 
           DEBUG("u[" << noshowpos << i << "] = " << showpos << FIXED(15,5) << alias(value, parameters[i]));
 
           for (int j = 0; j != N; ++j) {
             alias(value, parameters[i]) -= H(i,j) * alias(successor.gradient, parameters[j]) * h[i] * h[j];
           }
           
           DEBUG(' ' << FIXED(15,5) << alias(value, parameters[i]) << noshowpos << endl);
 
           alias(error, parameters[i]) = h[i];
         }
       }
 
       return precessor;
     }