Performs non linear optimization over a non-linear function, using a variant of the Levenberg Marquardt algorithm. More...

#include <LevenbergMarquardt.h>

Inheritance diagram for Eigen::LevenbergMarquardt< _FunctorType >:

Classes
struct	Parameters

Public Types
typedef _FunctorType	FunctorType

typedef FunctorType::QRSolver	QRSolver

typedef FunctorType::JacobianType	JacobianType

typedef JacobianType::Scalar	Scalar

typedef JacobianType::RealScalar	RealScalar

typedef QRSolver::StorageIndex	PermIndex

typedef Matrix< Scalar, Dynamic, 1 >	FVectorType

typedef PermutationMatrix< Dynamic, Dynamic, int >	PermutationType

typedef DenseIndex	Index

typedef Matrix< Scalar, Dynamic, 1 >	FVectorType

typedef Matrix< Scalar, Dynamic, Dynamic >	JacobianType

Public Member Functions
	LevenbergMarquardt (FunctorType &functor)

LevenbergMarquardtSpace::Status	minimize (FVectorType &x)

LevenbergMarquardtSpace::Status	minimizeInit (FVectorType &x)

LevenbergMarquardtSpace::Status	minimizeOneStep (FVectorType &x)

LevenbergMarquardtSpace::Status	lmder1 (FVectorType &x, const Scalar tol=std::sqrt(NumTraits< Scalar >::epsilon()))

void	resetParameters ()

void	setXtol (RealScalar xtol)

void	setFtol (RealScalar ftol)

void	setGtol (RealScalar gtol)

void	setFactor (RealScalar factor)

void	setEpsilon (RealScalar epsfcn)

void	setMaxfev (Index maxfev)

void	setExternalScaling (bool value)

RealScalar	xtol () const

RealScalar	ftol () const

RealScalar	gtol () const

RealScalar	factor () const

RealScalar	epsilon () const

Index	maxfev () const

FVectorType &	diag ()

Index	iterations ()

Index	nfev ()

Index	njev ()

RealScalar	fnorm ()

RealScalar	gnorm ()

RealScalar	lm_param (void)

FVectorType &	fvec ()

JacobianType &	jacobian ()

JacobianType &	matrixR ()

PermutationType	permutation ()

ComputationInfo	info () const
	Reports whether the minimization was successful.

	LevenbergMarquardt (FunctorType &_functor)

LevenbergMarquardtSpace::Status	lmder1 (FVectorType &x, const Scalar tol=sqrt_epsilon())

LevenbergMarquardtSpace::Status	minimize (FVectorType &x)

LevenbergMarquardtSpace::Status	minimizeInit (FVectorType &x)

LevenbergMarquardtSpace::Status	minimizeOneStep (FVectorType &x)

LevenbergMarquardtSpace::Status	lmstr1 (FVectorType &x, const Scalar tol=sqrt_epsilon())

LevenbergMarquardtSpace::Status	minimizeOptimumStorage (FVectorType &x)

LevenbergMarquardtSpace::Status	minimizeOptimumStorageInit (FVectorType &x)

LevenbergMarquardtSpace::Status	minimizeOptimumStorageOneStep (FVectorType &x)

void	resetParameters (void)

Scalar	lm_param (void)

Static Public Member Functions
static LevenbergMarquardtSpace::Status	lmdif1 (FunctorType &functor, FVectorType &x, Index *nfev, const Scalar tol=std::sqrt(NumTraits< Scalar >::epsilon()))

static LevenbergMarquardtSpace::Status	lmdif1 (FunctorType &functor, FVectorType &x, Index *nfev, const Scalar tol=sqrt_epsilon())

Public Attributes
Parameters	parameters

FVectorType	fvec

FVectorType	qtf

FVectorType	diag

JacobianType	fjac

PermutationMatrix< Dynamic, Dynamic >	permutation

Index	nfev

Index	njev

Index	iter

Scalar	fnorm

Scalar	gnorm

bool	useExternalScaling

Detailed Description

template<typename _FunctorType>
class Eigen::LevenbergMarquardt< _FunctorType >

Performs non linear optimization over a non-linear function, using a variant of the Levenberg Marquardt algorithm.

Check wikipedia for more information. http://en.wikipedia.org/wiki/Levenberg%E2%80%93Marquardt_algorithm

Member Typedef Documentation

◆ FunctorType

template<typename _FunctorType >

typedef _FunctorType Eigen::LevenbergMarquardt< _FunctorType >::FunctorType

◆ FVectorType [1/2]

template<typename _FunctorType >

typedef Matrix<Scalar,Dynamic,1> Eigen::LevenbergMarquardt< _FunctorType >::FVectorType

◆ FVectorType [2/2]

template<typename _FunctorType >

typedef Matrix< Scalar, Dynamic, 1 > Eigen::LevenbergMarquardt< _FunctorType >::FVectorType

◆ Index

template<typename _FunctorType >

typedef DenseIndex Eigen::LevenbergMarquardt< _FunctorType >::Index

◆ JacobianType [1/2]

template<typename _FunctorType >

typedef FunctorType::JacobianType Eigen::LevenbergMarquardt< _FunctorType >::JacobianType

◆ JacobianType [2/2]

template<typename _FunctorType >

typedef Matrix< Scalar, Dynamic, Dynamic > Eigen::LevenbergMarquardt< _FunctorType >::JacobianType

◆ PermIndex

template<typename _FunctorType >

typedef QRSolver::StorageIndex Eigen::LevenbergMarquardt< _FunctorType >::PermIndex

◆ PermutationType

template<typename _FunctorType >

typedef PermutationMatrix<Dynamic,Dynamic,int> Eigen::LevenbergMarquardt< _FunctorType >::PermutationType

◆ QRSolver

template<typename _FunctorType >

typedef FunctorType::QRSolver Eigen::LevenbergMarquardt< _FunctorType >::QRSolver

◆ RealScalar

template<typename _FunctorType >

typedef JacobianType::RealScalar Eigen::LevenbergMarquardt< _FunctorType >::RealScalar

◆ Scalar

template<typename _FunctorType >

typedef JacobianType::Scalar Eigen::LevenbergMarquardt< _FunctorType >::Scalar

Constructor & Destructor Documentation

◆ LevenbergMarquardt() [1/2]

template<typename _FunctorType >

Eigen::LevenbergMarquardt< _FunctorType >::LevenbergMarquardt ( FunctorType & functor )

inline

◆ LevenbergMarquardt() [2/2]

template<typename _FunctorType >

Eigen::LevenbergMarquardt< _FunctorType >::LevenbergMarquardt ( FunctorType & _functor )

inline

Member Function Documentation

◆ diag()

template<typename _FunctorType >

FVectorType & Eigen::LevenbergMarquardt< _FunctorType >::diag ( )

inline

Returns: a reference to the diagonal of the jacobian

◆ epsilon()

template<typename _FunctorType >

RealScalar Eigen::LevenbergMarquardt< _FunctorType >::epsilon ( ) const

inline

Returns: the error precision

◆ factor()

template<typename _FunctorType >

RealScalar Eigen::LevenbergMarquardt< _FunctorType >::factor ( ) const

inline

Returns: the step bound for the diagonal shift

◆ fnorm()

template<typename _FunctorType >

RealScalar Eigen::LevenbergMarquardt< _FunctorType >::fnorm ( )

inline

Returns: the norm of current vector function

◆ ftol()

template<typename _FunctorType >

RealScalar Eigen::LevenbergMarquardt< _FunctorType >::ftol ( ) const

inline

Returns: the tolerance for the norm of the vector function

◆ fvec()

template<typename _FunctorType >

FVectorType & Eigen::LevenbergMarquardt< _FunctorType >::fvec ( )

inline

Returns: a reference to the current vector function

◆ gnorm()

template<typename _FunctorType >

RealScalar Eigen::LevenbergMarquardt< _FunctorType >::gnorm ( )

inline

Returns: the norm of the gradient of the error

◆ gtol()

template<typename _FunctorType >

RealScalar Eigen::LevenbergMarquardt< _FunctorType >::gtol ( ) const

inline

Returns: the tolerance for the norm of the gradient of the error vector

◆ info()

template<typename _FunctorType >

ComputationInfo Eigen::LevenbergMarquardt< _FunctorType >::info ( ) const

inline

Reports whether the minimization was successful.

Returns: Success if the minimization was successful, NumericalIssue if a numerical problem arises during the minimization process, for example during the QR factorization NoConvergence if the minimization did not converge after the maximum number of function evaluation allowed InvalidInput if the input matrix is invalid

◆ iterations()

template<typename _FunctorType >

Index Eigen::LevenbergMarquardt< _FunctorType >::iterations ( )

inline

Returns: the number of iterations performed

◆ jacobian()

template<typename _FunctorType >

JacobianType & Eigen::LevenbergMarquardt< _FunctorType >::jacobian ( )

inline

Returns: a reference to the matrix where the current Jacobian matrix is stored

◆ lm_param() [1/2]

template<typename _FunctorType >

RealScalar Eigen::LevenbergMarquardt< _FunctorType >::lm_param ( void )

inline

Returns: the LevenbergMarquardt parameter

◆ lm_param() [2/2]

template<typename _FunctorType >

Scalar Eigen::LevenbergMarquardt< _FunctorType >::lm_param ( void )

inline

◆ lmder1() [1/2]

template<typename _FunctorType >

LevenbergMarquardtSpace::Status Eigen::LevenbergMarquardt< _FunctorType >::lmder1	(	FVectorType &	x,
		const Scalar	tol = `sqrt_epsilon()`
	)

◆ lmder1() [2/2]

template<typename FunctorType , typename Scalar >

LevenbergMarquardtSpace::Status Eigen::LevenbergMarquardt< FunctorType, Scalar >::lmder1	(	FVectorType &	x,
		const Scalar	tol = `std::sqrt(NumTraits<Scalar>::epsilon())`
	)

◆ lmdif1() [1/2]

template<typename _FunctorType >

static LevenbergMarquardtSpace::Status Eigen::LevenbergMarquardt< _FunctorType >::lmdif1	(	FunctorType &	functor,
		FVectorType &	x,
		Index *	nfev,
		const Scalar	tol = `sqrt_epsilon()`
	)

static

◆ lmdif1() [2/2]

template<typename FunctorType , typename Scalar >

LevenbergMarquardtSpace::Status Eigen::LevenbergMarquardt< FunctorType, Scalar >::lmdif1	(	FunctorType &	functor,
		FVectorType &	x,
		Index *	nfev,
		const Scalar	tol = `std::sqrt(NumTraits<Scalar>::epsilon())`
	)

static

◆ lmstr1()

template<typename FunctorType , typename Scalar >

LevenbergMarquardtSpace::Status Eigen::LevenbergMarquardt< FunctorType, Scalar >::lmstr1	(	FVectorType &	x,
		const Scalar	tol = `sqrt_epsilon()`
	)

◆ matrixR()

template<typename _FunctorType >

JacobianType & Eigen::LevenbergMarquardt< _FunctorType >::matrixR ( )

inline

Returns: a reference to the triangular matrix R from the QR of the jacobian matrix.

See also: jacobian()

◆ maxfev()

template<typename _FunctorType >

Index Eigen::LevenbergMarquardt< _FunctorType >::maxfev ( ) const

inline

Returns: the maximum number of function evaluation

◆ minimize() [1/2]

template<typename FunctorType , typename Scalar >

LevenbergMarquardtSpace::Status Eigen::LevenbergMarquardt< FunctorType, Scalar >::minimize ( FVectorType & x )

◆ minimize() [2/2]

template<typename _FunctorType >

LevenbergMarquardtSpace::Status Eigen::LevenbergMarquardt< _FunctorType >::minimize ( FVectorType & x )

◆ minimizeInit() [1/2]

template<typename FunctorType , typename Scalar >

LevenbergMarquardtSpace::Status Eigen::LevenbergMarquardt< FunctorType, Scalar >::minimizeInit ( FVectorType & x )

◆ minimizeInit() [2/2]

template<typename _FunctorType >

LevenbergMarquardtSpace::Status Eigen::LevenbergMarquardt< _FunctorType >::minimizeInit ( FVectorType & x )

◆ minimizeOneStep() [1/2]

template<typename FunctorType , typename Scalar >

LevenbergMarquardtSpace::Status Eigen::LevenbergMarquardt< FunctorType, Scalar >::minimizeOneStep ( FVectorType & x )

◆ minimizeOneStep() [2/2]

template<typename _FunctorType >

LevenbergMarquardtSpace::Status Eigen::LevenbergMarquardt< _FunctorType >::minimizeOneStep ( FVectorType & x )

◆ minimizeOptimumStorage()

template<typename FunctorType , typename Scalar >

LevenbergMarquardtSpace::Status Eigen::LevenbergMarquardt< FunctorType, Scalar >::minimizeOptimumStorage ( FVectorType & x )

◆ minimizeOptimumStorageInit()

template<typename FunctorType , typename Scalar >

LevenbergMarquardtSpace::Status Eigen::LevenbergMarquardt< FunctorType, Scalar >::minimizeOptimumStorageInit ( FVectorType & x )

◆ minimizeOptimumStorageOneStep()

template<typename FunctorType , typename Scalar >

LevenbergMarquardtSpace::Status Eigen::LevenbergMarquardt< FunctorType, Scalar >::minimizeOptimumStorageOneStep ( FVectorType & x )

◆ nfev()

template<typename _FunctorType >

Index Eigen::LevenbergMarquardt< _FunctorType >::nfev ( )

inline

Returns: the number of functions evaluation

◆ njev()

template<typename _FunctorType >

Index Eigen::LevenbergMarquardt< _FunctorType >::njev ( )

inline

Returns: the number of jacobian evaluation

◆ permutation()

template<typename _FunctorType >

PermutationType Eigen::LevenbergMarquardt< _FunctorType >::permutation ( )

inline

the permutation used in the QR factorization

◆ resetParameters() [1/2]

template<typename _FunctorType >

void Eigen::LevenbergMarquardt< _FunctorType >::resetParameters ( )

inline

Sets the default parameters

◆ resetParameters() [2/2]

template<typename _FunctorType >

void Eigen::LevenbergMarquardt< _FunctorType >::resetParameters ( void )

inline

◆ setEpsilon()

template<typename _FunctorType >

void Eigen::LevenbergMarquardt< _FunctorType >::setEpsilon ( RealScalar epsfcn )

inline

Sets the error precision

◆ setExternalScaling()

template<typename _FunctorType >

void Eigen::LevenbergMarquardt< _FunctorType >::setExternalScaling ( bool value )

inline

Use an external Scaling. If set to true, pass a nonzero diagonal to diag()

◆ setFactor()

template<typename _FunctorType >

void Eigen::LevenbergMarquardt< _FunctorType >::setFactor ( RealScalar factor )

inline

Sets the step bound for the diagonal shift

◆ setFtol()

template<typename _FunctorType >

void Eigen::LevenbergMarquardt< _FunctorType >::setFtol ( RealScalar ftol )

inline

Sets the tolerance for the norm of the vector function

◆ setGtol()

template<typename _FunctorType >

void Eigen::LevenbergMarquardt< _FunctorType >::setGtol ( RealScalar gtol )

inline

Sets the tolerance for the norm of the gradient of the error vector

◆ setMaxfev()

template<typename _FunctorType >

void Eigen::LevenbergMarquardt< _FunctorType >::setMaxfev ( Index maxfev )

inline

Sets the maximum number of function evaluation

◆ setXtol()

template<typename _FunctorType >

void Eigen::LevenbergMarquardt< _FunctorType >::setXtol ( RealScalar xtol )

inline

Sets the tolerance for the norm of the solution vector

◆ xtol()

template<typename _FunctorType >

RealScalar Eigen::LevenbergMarquardt< _FunctorType >::xtol ( ) const

inline

Returns: the tolerance for the norm of the solution vector

Member Data Documentation

◆ diag

template<typename _FunctorType >

FVectorType Eigen::LevenbergMarquardt< _FunctorType >::diag

◆ fjac

template<typename _FunctorType >

JacobianType Eigen::LevenbergMarquardt< _FunctorType >::fjac

◆ fnorm

template<typename _FunctorType >

Scalar Eigen::LevenbergMarquardt< _FunctorType >::fnorm

◆ fvec

template<typename _FunctorType >

FVectorType Eigen::LevenbergMarquardt< _FunctorType >::fvec

◆ gnorm

template<typename _FunctorType >

Scalar Eigen::LevenbergMarquardt< _FunctorType >::gnorm

◆ iter

template<typename _FunctorType >

Index Eigen::LevenbergMarquardt< _FunctorType >::iter

◆ nfev

template<typename _FunctorType >

Index Eigen::LevenbergMarquardt< _FunctorType >::nfev

◆ njev

template<typename _FunctorType >

Index Eigen::LevenbergMarquardt< _FunctorType >::njev

◆ parameters

template<typename _FunctorType >

Parameters Eigen::LevenbergMarquardt< _FunctorType >::parameters

◆ permutation

template<typename _FunctorType >

PermutationMatrix<Dynamic,Dynamic> Eigen::LevenbergMarquardt< _FunctorType >::permutation

◆ qtf

template<typename _FunctorType >

FVectorType Eigen::LevenbergMarquardt< _FunctorType >::qtf

◆ useExternalScaling

template<typename _FunctorType >

bool Eigen::LevenbergMarquardt< _FunctorType >::useExternalScaling

The documentation for this class was generated from the following files:

core/util/algorithms/eigen-3.4.0/unsupported/Eigen/src/LevenbergMarquardt/LevenbergMarquardt.h
core/util/algorithms/eigen-3.4.0/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h
core/util/algorithms/eigen-3.4.0/unsupported/Eigen/src/LevenbergMarquardt/LMonestep.h

Classes

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes

Detailed Description

Member Typedef Documentation

◆ FunctorType

◆ FVectorType [1/2]

◆ FVectorType [2/2]

◆ Index

◆ JacobianType [1/2]

◆ JacobianType [2/2]

◆ PermIndex

◆ PermutationType

◆ QRSolver

◆ RealScalar

◆ Scalar

Constructor & Destructor Documentation

◆ LevenbergMarquardt() [1/2]

◆ LevenbergMarquardt() [2/2]

Member Function Documentation

◆ diag()

◆ epsilon()

◆ factor()

◆ fnorm()

◆ ftol()

◆ fvec()

◆ gnorm()

◆ gtol()

◆ info()

◆ iterations()

◆ jacobian()

◆ lm_param() [1/2]

◆ lm_param() [2/2]

◆ lmder1() [1/2]

◆ lmder1() [2/2]

◆ lmdif1() [1/2]

◆ lmdif1() [2/2]

◆ lmstr1()

◆ matrixR()

◆ maxfev()

◆ minimize() [1/2]

◆ minimize() [2/2]

◆ minimizeInit() [1/2]

◆ minimizeInit() [2/2]

◆ minimizeOneStep() [1/2]

◆ minimizeOneStep() [2/2]

◆ minimizeOptimumStorage()

◆ minimizeOptimumStorageInit()

◆ minimizeOptimumStorageOneStep()

◆ nfev()

◆ njev()

◆ permutation()

◆ resetParameters() [1/2]

◆ resetParameters() [2/2]

◆ setEpsilon()

◆ setExternalScaling()

◆ setFactor()

◆ setFtol()

◆ setGtol()

◆ setMaxfev()

◆ setXtol()

◆ xtol()

Member Data Documentation

◆ diag

◆ fjac

◆ fnorm

◆ fvec

◆ gnorm

◆ iter

◆ nfev

◆ njev

◆ parameters

◆ permutation

◆ qtf

◆ useExternalScaling