Eigen::LevenbergMarquardt< FunctorType_ > Class Template Reference

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

Inherits internal::no_assignment_operator.

Public Member Functions
FVectorType &	diag ()
RealScalar	epsilon () const
RealScalar	factor () const
RealScalar	fnorm ()
RealScalar	ftol () const
FVectorType &	fvec ()
RealScalar	gnorm ()
RealScalar	gtol () const
ComputationInfo	info () const
	Reports whether the minimization was successful. More...
Index	iterations ()
JacobianType &	jacobian ()
RealScalar	lm_param (void)
JacobianType &	matrixR ()
Index	maxfev () const
Index	nfev ()
Index	njev ()
PermutationType	permutation ()
void	resetParameters ()
void	setEpsilon (RealScalar epsfcn)
void	setExternalScaling (bool value)
void	setFactor (RealScalar factor)
void	setFtol (RealScalar ftol)
void	setGtol (RealScalar gtol)
void	setMaxfev (Index maxfev)
void	setXtol (RealScalar xtol)
RealScalar	xtol () const

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()

template<typename FunctorType_ >

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

inline

Returns

the LevenbergMarquardt parameter

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

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()

template<typename FunctorType_ >

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

inline

Sets the default parameters

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

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

• LevenbergMarquardt/LevenbergMarquardt.h
• LMonestep.h