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 Eigen  3.3.9
Eigen::BDCSVD< _MatrixType > Class Template Reference

Detailed Description

template<typename _MatrixType> class Eigen::BDCSVD< _MatrixType >

class Bidiagonal Divide and Conquer SVD

Template Parameters
 _MatrixType the type of the matrix of which we are computing the SVD decomposition

This class first reduces the input matrix to bi-diagonal form using class UpperBidiagonalization, and then performs a divide-and-conquer diagonalization. Small blocks are diagonalized using class JacobiSVD. You can control the switching size with the setSwitchSize() method, default is 16. For small matrice (<16), it is thus preferable to directly use JacobiSVD. For larger ones, BDCSVD is highly recommended and can several order of magnitude faster.

Warning
this algorithm is unlikely to provide accurate result when compiled with unsafe math optimizations. For instance, this concerns Intel's compiler (ICC), which perfroms such optimization by default unless you compile with the -fp-model precise option. Likewise, the -ffast-math option of GCC or clang will significantly degrade the accuracy.
class JacobiSVD

Public Member Functions

BDCSVD ()
Default Constructor. More...

BDCSVD (const MatrixType &matrix, unsigned int computationOptions=0)
Constructor performing the decomposition of given matrix. More...

BDCSVD (Index rows, Index cols, unsigned int computationOptions=0)
Default Constructor with memory preallocation. More...

BDCSVDcompute (const MatrixType &matrix)
Method performing the decomposition of given matrix using current options. More...

BDCSVDcompute (const MatrixType &matrix, unsigned int computationOptions)
Method performing the decomposition of given matrix using custom options. More...

bool computeU () const

bool computeV () const

◆ BDCSVD() [1/3]

template<typename _MatrixType >
 Eigen::BDCSVD< _MatrixType >::BDCSVD ( )
inline

Default Constructor.

The default constructor is useful in cases in which the user intends to perform decompositions via BDCSVD::compute(const MatrixType&).

◆ BDCSVD() [2/3]

template<typename _MatrixType >
 Eigen::BDCSVD< _MatrixType >::BDCSVD ( Index rows, Index cols, unsigned int computationOptions = 0 )
inline

Default Constructor with memory preallocation.

Like the default constructor but with preallocation of the internal data according to the specified problem size.

BDCSVD()

◆ BDCSVD() [3/3]

template<typename _MatrixType >
 Eigen::BDCSVD< _MatrixType >::BDCSVD ( const MatrixType & matrix, unsigned int computationOptions = 0 )
inline

Constructor performing the decomposition of given matrix.

Parameters
 matrix the matrix to decompose computationOptions optional parameter allowing to specify if you want full or thin U or V unitaries to be computed. By default, none is computed. This is a bit - field, the possible bits are ComputeFullU, ComputeThinU, ComputeFullV, ComputeThinV.

Thin unitaries are only available if your matrix type has a Dynamic number of columns (for example MatrixXf). They also are not available with the (non - default) FullPivHouseholderQR preconditioner.

◆ compute() [1/2]

template<typename _MatrixType >
 BDCSVD& Eigen::BDCSVD< _MatrixType >::compute ( const MatrixType & matrix )
inline

Method performing the decomposition of given matrix using current options.

Parameters
 matrix the matrix to decompose

This method uses the current computationOptions, as already passed to the constructor or to compute(const MatrixType&, unsigned int).

◆ compute() [2/2]

template<typename MatrixType >
 BDCSVD< MatrixType > & Eigen::BDCSVD< MatrixType >::compute ( const MatrixType & matrix, unsigned int computationOptions )

Method performing the decomposition of given matrix using custom options.

Parameters
 matrix the matrix to decompose computationOptions optional parameter allowing to specify if you want full or thin U or V unitaries to be computed. By default, none is computed. This is a bit - field, the possible bits are ComputeFullU, ComputeThinU, ComputeFullV, ComputeThinV.

Thin unitaries are only available if your matrix type has a Dynamic number of columns (for example MatrixXf). They also are not available with the (non - default) FullPivHouseholderQR preconditioner.

◆ computeU()

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

◆ computeV()

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

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