WPILibC++ 2023.4.3
Eigen::SVDBase< Derived > Class Template Reference

Base class of SVD algorithms. More...

#include </home/runner/work/allwpilib/allwpilib/wpimath/src/main/native/thirdparty/eigen/include/Eigen/src/SVD/SVDBase.h>

Inheritance diagram for Eigen::SVDBase< Derived >:
Eigen::SolverBase< SVDBase< Derived > > Eigen::EigenBase< SVDBase< Derived > >

Public Types

enum  {
  RowsAtCompileTime = MatrixType::RowsAtCompileTime , ColsAtCompileTime = MatrixType::ColsAtCompileTime , DiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime,ColsAtCompileTime) , MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime ,
  MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime , MaxDiagSizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_FIXED(MaxRowsAtCompileTime,MaxColsAtCompileTime) , MatrixOptions = MatrixType::Options
}
 
typedef internal::traits< Derived >::MatrixType MatrixType
 
typedef MatrixType::Scalar Scalar
 
typedef NumTraits< typenameMatrixType::Scalar >::Real RealScalar
 
typedef Eigen::internal::traits< SVDBase >::StorageIndex StorageIndex
 
typedef Eigen::Index Index
 
typedef Matrix< Scalar, RowsAtCompileTime, RowsAtCompileTime, MatrixOptions, MaxRowsAtCompileTime, MaxRowsAtCompileTimeMatrixUType
 
typedef Matrix< Scalar, ColsAtCompileTime, ColsAtCompileTime, MatrixOptions, MaxColsAtCompileTime, MaxColsAtCompileTimeMatrixVType
 
typedef internal::plain_diag_type< MatrixType, RealScalar >::type SingularValuesType
 
- Public Types inherited from Eigen::SolverBase< SVDBase< Derived > >
enum  
 
typedef EigenBase< SVDBase< Derived > > Base
 
typedef internal::traits< SVDBase< Derived > >::Scalar Scalar
 
typedef Scalar CoeffReturnType
 
typedef internal::add_const< Transpose< constDerived > >::type ConstTransposeReturnType
 
typedef internal::conditional< NumTraits< Scalar >::IsComplex, CwiseUnaryOp< internal::scalar_conjugate_op< Scalar >, ConstTransposeReturnType >, ConstTransposeReturnType >::type AdjointReturnType
 
- Public Types inherited from Eigen::EigenBase< SVDBase< Derived > >
typedef Eigen::Index Index
 The interface type of indices. More...
 
typedef internal::traits< SVDBase< Derived > >::StorageKind StorageKind
 

Public Member Functions

Derived & derived ()
 
const Derived & derived () const
 
const MatrixUTypematrixU () const
 
const MatrixVTypematrixV () const
 
const SingularValuesTypesingularValues () const
 
Index nonzeroSingularValues () const
 
Index rank () const
 
Derived & setThreshold (const RealScalar &threshold)
 Allows to prescribe a threshold to be used by certain methods, such as rank() and solve(), which need to determine when singular values are to be considered nonzero. More...
 
Derived & setThreshold (Default_t)
 Allows to come back to the default behavior, letting Eigen use its default formula for determining the threshold. More...
 
RealScalar threshold () const
 Returns the threshold that will be used by certain methods such as rank(). More...
 
bool computeU () const
 
bool computeV () const
 
Index rows () const
 
Index cols () const
 
EIGEN_DEVICE_FUNC ComputationInfo info () const
 Reports whether previous computation was successful. More...
 
template<typename RhsType , typename DstType >
void _solve_impl (const RhsType &rhs, DstType &dst) const
 
template<bool Conjugate, typename RhsType , typename DstType >
void _solve_impl_transposed (const RhsType &rhs, DstType &dst) const
 
- Public Member Functions inherited from Eigen::SolverBase< SVDBase< Derived > >
 SolverBase ()
 Default constructor. More...
 
 ~SolverBase ()
 
const Solve< SVDBase< Derived >, Rhs > solve (const MatrixBase< Rhs > &b) const
 
ConstTransposeReturnType transpose () const
 
AdjointReturnType adjoint () const
 
EIGEN_DEVICE_FUNC SVDBase< Derived > & derived ()
 
EIGEN_DEVICE_FUNC const SVDBase< Derived > & derived () const
 
- Public Member Functions inherited from Eigen::EigenBase< SVDBase< Derived > >
EIGEN_DEVICE_FUNC SVDBase< Derived > & derived ()
 
EIGEN_DEVICE_FUNC const SVDBase< Derived > & derived () const
 
EIGEN_DEVICE_FUNC SVDBase< Derived > & const_cast_derived () const
 
EIGEN_DEVICE_FUNC const SVDBase< Derived > & const_derived () const
 
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index rows () const EIGEN_NOEXCEPT
 
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index cols () const EIGEN_NOEXCEPT
 
EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index size () const EIGEN_NOEXCEPT
 
EIGEN_DEVICE_FUNC void evalTo (Dest &dst) const
 
EIGEN_DEVICE_FUNC void addTo (Dest &dst) const
 
EIGEN_DEVICE_FUNC void subTo (Dest &dst) const
 
EIGEN_DEVICE_FUNC void applyThisOnTheRight (Dest &dst) const
 
EIGEN_DEVICE_FUNC void applyThisOnTheLeft (Dest &dst) const
 

Protected Member Functions

void _check_compute_assertions () const
 
template<bool Transpose_, typename Rhs >
void _check_solve_assertion (const Rhs &b) const
 
bool allocate (Index rows, Index cols, unsigned int computationOptions)
 
 SVDBase ()
 Default Constructor. More...
 
- Protected Member Functions inherited from Eigen::SolverBase< SVDBase< Derived > >
void _check_solve_assertion (const Rhs &b) const
 

Static Protected Member Functions

static void check_template_parameters ()
 

Protected Attributes

MatrixUType m_matrixU
 
MatrixVType m_matrixV
 
SingularValuesType m_singularValues
 
ComputationInfo m_info
 
bool m_isInitialized
 
bool m_isAllocated
 
bool m_usePrescribedThreshold
 
bool m_computeFullU
 
bool m_computeThinU
 
bool m_computeFullV
 
bool m_computeThinV
 
unsigned int m_computationOptions
 
Index m_nonzeroSingularValues
 
Index m_rows
 
Index m_cols
 
Index m_diagSize
 
RealScalar m_prescribedThreshold
 

Friends

template<typename Derived_ >
struct internal::solve_assertion
 

Detailed Description

template<typename Derived>
class Eigen::SVDBase< Derived >

Base class of SVD algorithms.

Template Parameters
Derivedthe type of the actual SVD decomposition

SVD decomposition consists in decomposing any n-by-p matrix A as a product

\[ A = U S V^* \]

where U is a n-by-n unitary, V is a p-by-p unitary, and S is a n-by-p real positive matrix which is zero outside of its main diagonal; the diagonal entries of S are known as the singular values of A and the columns of U and V are known as the left and right singular vectors of A respectively.

Singular values are always sorted in decreasing order.

You can ask for only thin U or V to be computed, meaning the following. In case of a rectangular n-by-p matrix, letting m be the smaller value among n and p, there are only m singular vectors; the remaining columns of U and V do not correspond to actual singular vectors. Asking for thin U or V means asking for only their m first columns to be formed. So U is then a n-by-m matrix, and V is then a p-by-m matrix. Notice that thin U and V are all you need for (least squares) solving.

The status of the computation can be retrived using the info() method. Unless info() returns Success, the results should be not considered well defined.

If the input matrix has inf or nan coefficients, the result of the computation is undefined, and info() will return InvalidInput, but the computation is guaranteed to terminate in finite (and reasonable) time.

See also
class BDCSVD, class JacobiSVD

Member Typedef Documentation

◆ Index

template<typename Derived >
typedef Eigen::Index Eigen::SVDBase< Derived >::Index
Deprecated:
since Eigen 3.3

◆ MatrixType

template<typename Derived >
typedef internal::traits<Derived>::MatrixType Eigen::SVDBase< Derived >::MatrixType

◆ MatrixUType

◆ MatrixVType

◆ RealScalar

template<typename Derived >
typedef NumTraits<typenameMatrixType::Scalar>::Real Eigen::SVDBase< Derived >::RealScalar

◆ Scalar

template<typename Derived >
typedef MatrixType::Scalar Eigen::SVDBase< Derived >::Scalar

◆ SingularValuesType

template<typename Derived >
typedef internal::plain_diag_type<MatrixType,RealScalar>::type Eigen::SVDBase< Derived >::SingularValuesType

◆ StorageIndex

template<typename Derived >
typedef Eigen::internal::traits<SVDBase>::StorageIndex Eigen::SVDBase< Derived >::StorageIndex

Member Enumeration Documentation

◆ anonymous enum

template<typename Derived >
anonymous enum
Enumerator
RowsAtCompileTime 
ColsAtCompileTime 
DiagSizeAtCompileTime 
MaxRowsAtCompileTime 
MaxColsAtCompileTime 
MaxDiagSizeAtCompileTime 
MatrixOptions 

Constructor & Destructor Documentation

◆ SVDBase()

template<typename Derived >
Eigen::SVDBase< Derived >::SVDBase ( )
inlineprotected

Default Constructor.

Default constructor of SVDBase

Member Function Documentation

◆ _check_compute_assertions()

template<typename Derived >
void Eigen::SVDBase< Derived >::_check_compute_assertions ( ) const
inlineprotected

◆ _check_solve_assertion()

template<typename Derived >
template<bool Transpose_, typename Rhs >
void Eigen::SVDBase< Derived >::_check_solve_assertion ( const Rhs &  b) const
inlineprotected

◆ _solve_impl()

template<typename Derived >
template<typename RhsType , typename DstType >
void Eigen::SVDBase< Derived >::_solve_impl ( const RhsType &  rhs,
DstType &  dst 
) const

◆ _solve_impl_transposed()

template<typename Derived >
template<bool Conjugate, typename RhsType , typename DstType >
void Eigen::SVDBase< Derived >::_solve_impl_transposed ( const RhsType &  rhs,
DstType &  dst 
) const

◆ allocate()

template<typename MatrixType >
bool Eigen::SVDBase< MatrixType >::allocate ( Index  rows,
Index  cols,
unsigned int  computationOptions 
)
protected

◆ check_template_parameters()

template<typename Derived >
static void Eigen::SVDBase< Derived >::check_template_parameters ( )
inlinestaticprotected

◆ cols()

template<typename Derived >
Index Eigen::SVDBase< Derived >::cols ( void  ) const
inline

◆ computeU()

template<typename Derived >
bool Eigen::SVDBase< Derived >::computeU ( ) const
inline
Returns
true if U (full or thin) is asked for in this SVD decomposition

◆ computeV()

template<typename Derived >
bool Eigen::SVDBase< Derived >::computeV ( ) const
inline
Returns
true if V (full or thin) is asked for in this SVD decomposition

◆ derived() [1/2]

template<typename Derived >
Derived & Eigen::SVDBase< Derived >::derived ( )
inline

◆ derived() [2/2]

template<typename Derived >
const Derived & Eigen::SVDBase< Derived >::derived ( ) const
inline

◆ info()

template<typename Derived >
EIGEN_DEVICE_FUNC ComputationInfo Eigen::SVDBase< Derived >::info ( ) const
inline

Reports whether previous computation was successful.

Returns
Success if computation was successful.

◆ matrixU()

template<typename Derived >
const MatrixUType & Eigen::SVDBase< Derived >::matrixU ( ) const
inline
Returns
the U matrix.

For the SVD decomposition of a n-by-p matrix, letting m be the minimum of n and p, the U matrix is n-by-n if you asked for ComputeFullU , and is n-by-m if you asked for ComputeThinU .

The m first columns of U are the left singular vectors of the matrix being decomposed.

This method asserts that you asked for U to be computed.

◆ matrixV()

template<typename Derived >
const MatrixVType & Eigen::SVDBase< Derived >::matrixV ( ) const
inline
Returns
the V matrix.

For the SVD decomposition of a n-by-p matrix, letting m be the minimum of n and p, the V matrix is p-by-p if you asked for ComputeFullV , and is p-by-m if you asked for ComputeThinV .

The m first columns of V are the right singular vectors of the matrix being decomposed.

This method asserts that you asked for V to be computed.

◆ nonzeroSingularValues()

template<typename Derived >
Index Eigen::SVDBase< Derived >::nonzeroSingularValues ( ) const
inline
Returns
the number of singular values that are not exactly 0

◆ rank()

template<typename Derived >
Index Eigen::SVDBase< Derived >::rank ( ) const
inline
Returns
the rank of the matrix of which *this is the SVD.
Note
This method has to determine which singular values should be considered nonzero. For that, it uses the threshold value that you can control by calling setThreshold(const RealScalar&).

◆ rows()

template<typename Derived >
Index Eigen::SVDBase< Derived >::rows ( void  ) const
inline

◆ setThreshold() [1/2]

template<typename Derived >
Derived & Eigen::SVDBase< Derived >::setThreshold ( const RealScalar threshold)
inline

Allows to prescribe a threshold to be used by certain methods, such as rank() and solve(), which need to determine when singular values are to be considered nonzero.

This is not used for the SVD decomposition itself.

When it needs to get the threshold value, Eigen calls threshold(). The default is NumTraits<Scalar>::epsilon()

Parameters
thresholdThe new value to use as the threshold.

A singular value will be considered nonzero if its value is strictly greater than \( \vert singular value \vert \leqslant threshold \times \vert max singular value \vert \).

If you want to come back to the default behavior, call setThreshold(Default_t)

◆ setThreshold() [2/2]

template<typename Derived >
Derived & Eigen::SVDBase< Derived >::setThreshold ( Default_t  )
inline

Allows to come back to the default behavior, letting Eigen use its default formula for determining the threshold.

You should pass the special object Eigen::Default as parameter here.

svd.setThreshold(Eigen::Default);
@ Default
Definition: Constants.h:362

See the documentation of setThreshold(const RealScalar&).

◆ singularValues()

template<typename Derived >
const SingularValuesType & Eigen::SVDBase< Derived >::singularValues ( ) const
inline
Returns
the vector of singular values.

For the SVD decomposition of a n-by-p matrix, letting m be the minimum of n and p, the returned vector has size m. Singular values are always sorted in decreasing order.

◆ threshold()

template<typename Derived >
RealScalar Eigen::SVDBase< Derived >::threshold ( ) const
inline

Returns the threshold that will be used by certain methods such as rank().

See the documentation of setThreshold(const RealScalar&).

Friends And Related Function Documentation

◆ internal::solve_assertion

template<typename Derived >
template<typename Derived_ >
friend struct internal::solve_assertion
friend

Member Data Documentation

◆ m_cols

template<typename Derived >
Index Eigen::SVDBase< Derived >::m_cols
protected

◆ m_computationOptions

template<typename Derived >
unsigned int Eigen::SVDBase< Derived >::m_computationOptions
protected

◆ m_computeFullU

template<typename Derived >
bool Eigen::SVDBase< Derived >::m_computeFullU
protected

◆ m_computeFullV

template<typename Derived >
bool Eigen::SVDBase< Derived >::m_computeFullV
protected

◆ m_computeThinU

template<typename Derived >
bool Eigen::SVDBase< Derived >::m_computeThinU
protected

◆ m_computeThinV

template<typename Derived >
bool Eigen::SVDBase< Derived >::m_computeThinV
protected

◆ m_diagSize

template<typename Derived >
Index Eigen::SVDBase< Derived >::m_diagSize
protected

◆ m_info

template<typename Derived >
ComputationInfo Eigen::SVDBase< Derived >::m_info
protected

◆ m_isAllocated

template<typename Derived >
bool Eigen::SVDBase< Derived >::m_isAllocated
protected

◆ m_isInitialized

template<typename Derived >
bool Eigen::SVDBase< Derived >::m_isInitialized
protected

◆ m_matrixU

template<typename Derived >
MatrixUType Eigen::SVDBase< Derived >::m_matrixU
protected

◆ m_matrixV

template<typename Derived >
MatrixVType Eigen::SVDBase< Derived >::m_matrixV
protected

◆ m_nonzeroSingularValues

template<typename Derived >
Index Eigen::SVDBase< Derived >::m_nonzeroSingularValues
protected

◆ m_prescribedThreshold

template<typename Derived >
RealScalar Eigen::SVDBase< Derived >::m_prescribedThreshold
protected

◆ m_rows

template<typename Derived >
Index Eigen::SVDBase< Derived >::m_rows
protected

◆ m_singularValues

template<typename Derived >
SingularValuesType Eigen::SVDBase< Derived >::m_singularValues
protected

◆ m_usePrescribedThreshold

template<typename Derived >
bool Eigen::SVDBase< Derived >::m_usePrescribedThreshold
protected

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