Eigen::SPQR< MatrixType_ > Class Template Reference

#include <Eigen/src/SPQRSupport/SuiteSparseQRSupport.h>

Detailed Description

template<typename MatrixType_>
class Eigen::SPQR< MatrixType_ >

Sparse QR factorization based on SuiteSparseQR library.

This class is used to perform a multithreaded and multifrontal rank-revealing QR decomposition of sparse matrices. The result is then used to solve linear least-squares systems. Clearly, a QR factorization is returned such that A*P = Q*R where :

P is the column permutation. Use colsPermutation() to get it.

Q is the orthogonal matrix represented as Householder reflectors. Use matrixQ() to get an expression and matrixQ().transpose() to get the transpose. You can then apply it to a vector.

R is the sparse triangular factor. Use matrixR() to get it as SparseMatrix. NOTE : The storage index type of R is always SuiteSparse_long. You can get it with SPQR::StorageIndex

Template Parameters

MatrixType_

The type of the sparse matrix A, must be a column-major SparseMatrix<>

This class follows the sparse solver concept .

Inheritance diagram for Eigen::SPQR< MatrixType_ >:

Public Member Functions
cholmod_common *	cholmodCommon () const
Index	cols () const
PermutationType	colsPermutation () const
	Get the permutation that was applied to columns of A.
ComputationInfo	info () const
	Reports whether previous computation was successful.
SPQRMatrixQReturnType< SPQR >	matrixQ () const
	Get an expression of the matrix Q.
const MatrixType &	matrixR () const
Index	rank () const
Index	rows () const
void	setPivotThreshold (const RealScalar &tol)
	Set the tolerance tol to treat columns with 2-norm <= tol as zero.
void	setSPQROrdering (int ord)
	Set the fill-reducing ordering method to be used.
Public Member Functions inherited from Eigen::SparseSolverBase< SPQR< MatrixType_ > >
Solve< SPQR< MatrixType_ >, Rhs >	solve (const MatrixBase< Rhs > &b) const
Solve< SPQR< MatrixType_ >, Rhs >	solve (const MatrixBase< Rhs > &b) const
Solve< SPQR< MatrixType_ >, Rhs >	solve (const SparseMatrixBase< Rhs > &b) const
Solve< SPQR< MatrixType_ >, Rhs >	solve (const SparseMatrixBase< Rhs > &b) const
	SparseSolverBase ()=default
	SparseSolverBase ()=default

Member Function Documentation

cholmodCommon()

template<typename MatrixType_>

cholmod_common * Eigen::SPQR< MatrixType_ >::cholmodCommon ( ) const

inline

Returns

a pointer to the SPQR workspace

cols()

template<typename MatrixType_>

Index Eigen::SPQR< MatrixType_ >::cols ( ) const

inline

Get the number of columns of the input matrix.

info()

template<typename MatrixType_>

ComputationInfo Eigen::SPQR< MatrixType_ >::info ( ) const

inline

Reports whether previous computation was successful.

Returns

Success if computation was successful, NumericalIssue if the sparse QR can not be computed

matrixR()

template<typename MatrixType_>

const MatrixType & Eigen::SPQR< MatrixType_ >::matrixR ( ) const

inline

Returns

the sparse triangular factor R. It is a sparse matrix

rank()

template<typename MatrixType_>

Index Eigen::SPQR< MatrixType_ >::rank ( ) const

inline

Gets the rank of the matrix. It should be equal to matrixR().rows() if the matrix is full-rank; matrixR().cols() is always the number of columns of the input matrix.

rows()

template<typename MatrixType_>

Index Eigen::SPQR< MatrixType_ >::rows ( ) const

inline

Get the number of rows of the input matrix and the Q matrix

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

• /builds/libeigen/eigen/Eigen/src/SPQRSupport/SuiteSparseQRSupport.h