SVD Class Template Reference
[SVD module]

List of all members.

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Detailed Description

template<typename MatrixType>
class Eigen::SVD< MatrixType >

Standard SVD decomposition of a matrix and associated features.

Warning:

This is not considered to be part of the stable public API yet. Changes may happen in future releases. See Experimental parts of Eigen

Parameters:

MatrixType

the type of the matrix of which we are computing the SVD decomposition

This class performs a standard SVD decomposition of a real matrix A of size M x N with M >= N.

See also:

MatrixBase::SVD()

Public Member Functions
void	compute (const MatrixType &matrix)
template<typename PositiveType, typename UnitaryType>
void	computePositiveUnitary (PositiveType *positive, UnitaryType *unitary) const
template<typename RotationType, typename ScalingType>
void	computeRotationScaling (RotationType *unitary, ScalingType *positive) const
template<typename ScalingType, typename RotationType>
void	computeScalingRotation (ScalingType *positive, RotationType *unitary) const
template<typename UnitaryType, typename PositiveType>
void	computeUnitaryPositive (UnitaryType *unitary, PositiveType *positive) const
const MatrixUType &	matrixU () const
const MatrixVType &	matrixV () const
const SingularValuesType &	singularValues () const
template<typename OtherDerived, typename ResultType>
bool	solve (const MatrixBase< OtherDerived > &b, ResultType *result) const
SVD &	sort ()
	SVD (const MatrixType &matrix)
Protected Attributes
MatrixUType	m_matU
MatrixVType	m_matV
SingularValuesType	m_sigma

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Member Function Documentation

void compute

(

const MatrixType &

matrix

)

[inline]

Computes / recomputes the SVD decomposition A = U S V^* of matrix

Note:

this code has been adapted from JAMA (public domain)

void computePositiveUnitary	(	UnitaryType *	positive,
		PositiveType *	unitary
	)			const [inline]

Computes the polar decomposition of the matrix, as a product positive x unitary.

If either pointer is zero, the corresponding computation is skipped.

Only for square matrices.

See also:

computeUnitaryPositive(), computeRotationScaling()

void computeRotationScaling	(	RotationType *	rotation,
		ScalingType *	scaling
	)			const [inline]

decomposes the matrix as a product rotation x scaling, the scaling being not necessarily positive.

If either pointer is zero, the corresponding computation is skipped.

This method requires the Geometry module.

See also:

computeScalingRotation(), computeUnitaryPositive()

void computeScalingRotation	(	ScalingType *	scaling,
		RotationType *	rotation
	)			const [inline]

decomposes the matrix as a product scaling x rotation, the scaling being not necessarily positive.

If either pointer is zero, the corresponding computation is skipped.

This method requires the Geometry module.

See also:

computeRotationScaling(), computeUnitaryPositive()

void computeUnitaryPositive	(	UnitaryType *	unitary,
		PositiveType *	positive
	)			const [inline]

Computes the polar decomposition of the matrix, as a product unitary x positive.

If either pointer is zero, the corresponding computation is skipped.

Only for square matrices.

See also:

computePositiveUnitary(), computeRotationScaling()

bool solve	(	const MatrixBase< OtherDerived > &	b,
		ResultType *	result
	)			const [inline]

Returns:

the solution of using the current SVD decomposition of A. The parts of the solution corresponding to zero singular values are ignored.

See also:

MatrixBase::svd(), LU::solve(), LLT::solve()

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

• SVD