compbio
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Sparse QR factorization based on SuiteSparseQR library. More...
#include <SuiteSparseQRSupport.h>
Public Types | |
enum | { ColsAtCompileTime = Dynamic, MaxColsAtCompileTime = Dynamic } |
typedef _MatrixType::Scalar | Scalar |
typedef _MatrixType::RealScalar | RealScalar |
typedef SuiteSparse_long | StorageIndex |
typedef SparseMatrix< Scalar, ColMajor, StorageIndex > | MatrixType |
typedef Map< PermutationMatrix< Dynamic, Dynamic, StorageIndex > > | PermutationType |
Public Member Functions | |
SPQR (const _MatrixType &matrix) | |
void | SPQR_free () |
void | compute (const _MatrixType &matrix) |
Index | rows () const |
Get the number of rows of the input matrix and the Q matrix. | |
Index | cols () const |
Get the number of columns of the input matrix. | |
template<typename Rhs , typename Dest > | |
void | _solve_impl (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 |
Gets the rank of the matrix. More... | |
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... | |
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SparseSolverBase () | |
Default constructor. | |
SPQR< _MatrixType > & | derived () |
const SPQR< _MatrixType > & | derived () const |
const Solve< SPQR< _MatrixType >, Rhs > | solve (const MatrixBase< Rhs > &b) const |
const Solve< SPQR< _MatrixType >, Rhs > | solve (const SparseMatrixBase< Rhs > &b) const |
void | _solve_impl (const SparseMatrixBase< Rhs > &b, SparseMatrixBase< Dest > &dest) const |
Protected Types | |
typedef SparseSolverBase< SPQR< _MatrixType > > | Base |
Protected Attributes | |
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 |
StorageIndex * | m_E |
cholmod_sparse * | m_H |
StorageIndex * | m_HPinv |
cholmod_dense * | m_HTau |
Index | m_rank |
cholmod_common | m_cc |
bool | m_useDefaultThreshold |
Index | m_rows |
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bool | m_isInitialized |
Friends | |
template<typename , typename > | |
struct | SPQR_QProduct |
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 SuiteSparse_long. You can get it with SPQR::Index
_MatrixType | The type of the sparse matrix A, must be a column-major SparseMatrix<> |
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Reports whether previous computation was successful.
Success
if computation was succesful, NumericalIssue
if the sparse QR can not be computed
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Gets the rank of the matrix.
It should be equal to matrixQR().cols if the matrix is full-rank