irlba::Results< EigenMatrix_, EigenVector_ > Struct Template Reference

Result of the IRLBA-based decomposition. More...

#include <compute.hpp>

Public Attributes
EigenMatrix_	U
EigenMatrix_	V
EigenVector_	D
int	iterations
bool	converged

Detailed Description

template<class EigenMatrix_, class EigenVector_>
struct irlba::Results< EigenMatrix_, EigenVector_ >

Result of the IRLBA-based decomposition.

Template Parameters

EigenMatrix_	A floating-point Eigen::Matrix class.
EigenVector_	A floating-point Eigen::Vector class, typically of the same scalar type as EigenMatrix_.

Member Data Documentation

converged

template<class EigenMatrix_ , class EigenVector_ >

bool irlba::Results< EigenMatrix_, EigenVector_ >::converged

Whether the algorithm converged.

D

template<class EigenMatrix_ , class EigenVector_ >

EigenVector_ irlba::Results< EigenMatrix_, EigenVector_ >::D

The requested number of singular values, ordered by decreasing value. These correspond to the vectors in U and V.

iterations

template<class EigenMatrix_ , class EigenVector_ >

int irlba::Results< EigenMatrix_, EigenVector_ >::iterations

The number of restart iterations performed.

U

template<class EigenMatrix_ , class EigenVector_ >

EigenMatrix_ irlba::Results< EigenMatrix_, EigenVector_ >::U

The left singular vectors, stored as columns of U. The number of rows in U is equal to the number of rows in the input matrix, and the number of columns is equal to the number of requested vectors.

V

template<class EigenMatrix_ , class EigenVector_ >

EigenMatrix_ irlba::Results< EigenMatrix_, EigenVector_ >::V

The right singular vectors, stored as columns of U. The number of rows in U is equal to the number of columns in the input matrix, and the number of columns is equal to the number of requested vectors.

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

• irlba/compute.hpp