Eigen::SPQR< _MatrixType > Class Template Reference

Sparse QR factorization based on SuiteSparseQR library. More...

#include <SuiteSparseQRSupport.h>

Collaboration diagram for Eigen::SPQR< _MatrixType >:

Public Types
typedef _MatrixType::Scalar	Scalar
typedef _MatrixType::RealScalar	RealScalar
typedef UF_long	Index
typedef SparseMatrix< Scalar, ColMajor, Index >	MatrixType
typedef PermutationMatrix< Dynamic, Dynamic >	PermutationType

Public Member Functions
	SPQR (const _MatrixType &matrix)
void	compute (const _MatrixType &matrix)
Index	rows () const
Index	cols () const
template<typename Rhs >
const internal::solve_retval< SPQR, Rhs >	solve (const MatrixBase< Rhs > &B) const
template<typename Rhs , typename Dest >
void	_solve (const MatrixBase< Rhs > &b, MatrixBase< Dest > &dest) const
const MatrixType	matrixR () const
SPQRMatrixQReturnType< SPQR >	matrixQ () const
	Get an expression of the matrix Q.
PermutationType	colsPermutation () const
	Get the permutation that was applied to columns of A.
Index	rank () const
void	setSPQROrdering (int ord)
	Set the fill-reducing ordering method to be used.
void	setPivotThreshold (const RealScalar &tol)
	Set the tolerance tol to treat columns with 2-norm < =tol as zero.
cholmod_common *	cholmodCommon () const
ComputationInfo	info () const
	Reports whether previous computation was successful. More...

Protected Attributes
bool	m_isInitialized
bool	m_analysisIsOk
bool	m_factorizationIsOk
bool	m_isRUpToDate
ComputationInfo	m_info
int	m_ordering
int	m_allow_tol
RealScalar	m_tolerance
cholmod_sparse *	m_cR
MatrixType	m_R
Index *	m_E
cholmod_sparse *	m_H
Index *	m_HPinv
cholmod_dense *	m_HTau
Index	m_rank
cholmod_common	m_cc

Friends
template<typename , typename >
struct	SPQR_QProduct

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 leasts_square 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 matrixQR() to get it as SparseMatrix. NOTE : The Index type of R is always UF_long. You can get it with SPQR::Index

Template Parameters

_MatrixType

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

Definition at line 15 of file SuiteSparseQRSupport.h.

Member Function Documentation

template<typename _MatrixType >

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

inline

Returns

a pointer to the SPQR workspace

Definition at line 195 of file SuiteSparseQRSupport.h.

{ return &m_cc; }

template<typename _MatrixType >

Index Eigen::SPQR< _MatrixType >::cols ( void  ) const

inline

Get the number of columns of the input matrix.

Definition at line 120 of file SuiteSparseQRSupport.h.

{ return m_cR->ncol; }

template<typename _MatrixType >

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

inline

Reports whether previous computation was successful.

Returns

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

Definition at line 203 of file SuiteSparseQRSupport.h.

    {
      eigen_assert(m_isInitialized && "Decomposition is not initialized.");
      return m_info;
    }

template<typename _MatrixType >

const MatrixType Eigen::SPQR< _MatrixType >::matrixR ( void  ) const

inline

Returns

the sparse triangular factor R. It is a sparse matrix

Definition at line 156 of file SuiteSparseQRSupport.h.

    {
      eigen_assert(m_isInitialized && " The QR factorization should be computed first, call compute()");
      if(!m_isRUpToDate) {
        m_R = viewAsEigen<Scalar,ColMajor, typename MatrixType::Index>(*m_cR);
        m_isRUpToDate = true;
      }
      return m_R;
    }

template<typename _MatrixType >

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

inline

Gets the rank of the matrix. It should be equal to matrixQR().cols if the matrix is full-rank

Definition at line 184 of file SuiteSparseQRSupport.h.

    {
      eigen_assert(m_isInitialized && "Decomposition is not initialized.");
      return m_cc.SPQR_istat[4];
    }

template<typename _MatrixType >

Index Eigen::SPQR< _MatrixType >::rows ( void  ) const

inline

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

Definition at line 115 of file SuiteSparseQRSupport.h.

{return m_H->nrow; }

template<typename _MatrixType >

template<typename Rhs >

const internal::solve_retval<SPQR, Rhs> Eigen::SPQR< _MatrixType >::solve ( const MatrixBase< Rhs > &  B ) const

inline

Returns

the solution X of using the current decomposition of A.

See also

compute()

Definition at line 127 of file SuiteSparseQRSupport.h.

    {
      eigen_assert(m_isInitialized && " The QR factorization should be computed first, call compute()");
      eigen_assert(this->rows()==B.rows()
                    && "SPQR::solve(): invalid number of rows of the right hand side matrix B");
          return internal::solve_retval<SPQR, Rhs>(*this, B.derived());
    }

---

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

• C:/Users/Brig/Documents/ShapeWorksStudio/src/Surfworks/Eigen/src/SPQRSupport/SuiteSparseQRSupport.h