Eigen  3.2.2
SPQR< _MatrixType > Class Template Reference

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

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. More...
 
SPQRMatrixQReturnType< SPQRmatrixQ () 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.
 
template<typename Rhs >
const internal::solve_retval< SPQR, Rhs > solve (const MatrixBase< Rhs > &B) const
 

Member Function Documentation

◆ cholmodCommon()

cholmod_common* cholmodCommon ( ) const
inline
Returns
a pointer to the SPQR workspace

◆ cols()

Index cols ( void  ) const
inline

Get the number of columns of the input matrix.

◆ info()

ComputationInfo info ( ) const
inline

Reports whether previous computation was successful.

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

◆ matrixR()

const MatrixType matrixR ( ) const
inline
Returns
the sparse triangular factor R. It is a sparse matrix

◆ rank()

Index rank ( ) const
inline

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

◆ rows()

Index rows ( void  ) const
inline

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

◆ solve()

const internal::solve_retval<SPQR, Rhs> solve ( const MatrixBase< Rhs > &  B) const
inline
Returns
the solution X of $ A X = B $ using the current decomposition of A.
See also
compute()

References Eigen::Success, and DenseBase< Derived >::topRows().


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