LeastSquareEngine implementation which uses the GNU Scientific Library. More...

#include <GSLEngine.h>

Inheritance diagram for ModelFitting::GSLEngine:

Collaboration diagram for ModelFitting::GSLEngine:

Public Member Functions
	GSLEngine (int itmax=1000, double xtol=1e-8, double gtol=1e-8, double ftol=1e-8, double delta=1e-4)
	Constructs a new instance of the engine.
virtual	~GSLEngine ()=default
	Destructor.
LeastSquareSummary	solveProblem (EngineParameterManager &parameter_manager, ResidualEstimator &residual_estimator) override
Public Member Functions inherited from ModelFitting::LeastSquareEngine
virtual	~LeastSquareEngine ()=default
	Destructor.

Private Attributes
int	m_itmax
double	m_xtol
double	m_gtol
double	m_ftol
double	m_delta

Detailed Description

LeastSquareEngine implementation which uses the GNU Scientific Library.

See also: https://www.gnu.org/software/gsl/doc/html/nls.html

Definition at line 39 of file GSLEngine.h.

Constructor & Destructor Documentation

◆ GSLEngine()

ModelFitting::GSLEngine::GSLEngine	(	int	itmax = 1000,
		double	xtol = 1e-8,
		double	gtol = 1e-8,
		double	ftol = 1e-8,
		double	delta = 1e-4 )

Constructs a new instance of the engine.

Parameters

itmax	Maximum number of iteratios
xtol	Step tolerance: \f\|\delta_i\| \le xtol(\|x_i\| + xtol)\f
gtol	Gradient tolerance: \f\underset{i}{max}\|g_i \times max(x_i, 1)\| \le gtol \times max(\Phi(x),1)\f
ftol	Tolerance for the change in \f\chi^2\f Some versions of the GSL library ignore this.
delta	Step size for finite difference Jacobian

Definition at line 41 of file GSLEngine.cpp.

References m_delta, m_ftol, m_gtol, m_itmax, and m_xtol.

◆ ~GSLEngine()

virtual ModelFitting::GSLEngine::~GSLEngine ( )

virtualdefault

Destructor.

Member Function Documentation

◆ solveProblem()

LeastSquareSummary ModelFitting::GSLEngine::solveProblem	(	ModelFitting::EngineParameterManager &	parameter_manager,
		ModelFitting::ResidualEstimator &	residual_estimator )

overridevirtual

Solves the minimization problem using the levmar library. The returned summary contains as underlying_framework_info an std::array<double,10>, which keeps the information regarding the minimization as it is provided by levmar (for more info see http://users.ics.forth.gr/~lourakis/levmar).

Implements ModelFitting::LeastSquareEngine.

Definition at line 118 of file GSLEngine.cpp.

References std::vector< T >::begin(), ModelFitting::EngineParameterManager::convertCovarianceMatrixToWorldSpace(), std::chrono::duration::count(), std::vector< T >::data(), ModelFitting::LeastSquareSummary::duration, std::end(), std::vector< T >::end(), ModelFitting::LeastSquareSummary::engine_stop_reason, ModelFitting::EngineParameterManager::getEngineValues(), ModelFitting::getStatusFlag(), ModelFitting::LeastSquareSummary::iteration_no, m_delta, m_ftol, m_gtol, m_itmax, m_xtol, std::chrono::steady_clock::now(), ModelFitting::EngineParameterManager::numberOfParameters(), ModelFitting::ResidualEstimator::numberOfResiduals(), ModelFitting::LeastSquareSummary::parameter_sigmas, ModelFitting::ResidualEstimator::populateResiduals(), std::vector< T >::push_back(), std::vector< T >::size(), std::sqrt(), ModelFitting::LeastSquareSummary::status_flag, std::tie(), ModelFitting::LeastSquareSummary::underlying_framework_info, and ModelFitting::EngineParameterManager::updateEngineValues().