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

Results of the IRLBA-based SVD by compute(). More...

#include <compute.hpp>

Collaboration diagram for irlba::Results< EigenMatrix_, EigenVector_ >:

Public Attributes
EigenMatrix_	U
EigenMatrix_	V
EigenVector_	D
Metrics	metrics

Detailed Description

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

Results of the IRLBA-based SVD by compute().

Template Parameters

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

Member Data Documentation

D

template<class EigenMatrix_ , class EigenVector_ >

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

Vector of the largest singular values, ordered by decreasing value. The number of values is no greater than number.

metrics

template<class EigenMatrix_ , class EigenVector_ >

Metrics irlba::Results< EigenMatrix_, EigenVector_ >::metrics

Metrics for the progress of the algorithm.

U

template<class EigenMatrix_ , class EigenVector_ >

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

Matrix of left singular vectors corresponding to the largest singular values. Each column corresponds to a left singular vector, the number of which is no greater than number. The number of rows is equal to the number of rows in the input matrix.

V

template<class EigenMatrix_ , class EigenVector_ >

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

Matrix of right singular vectors corresponding to the largest singular values. Each column corresponds to a right singular vector, the number of which is no greater than number. The number of rows is equal to the number of columns in the input matrix.

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

• irlba/compute.hpp