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 SuiteSparse_long. You can get it with SPQR::Index
- Template Parameters
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_MatrixType | The type of the sparse matrix A, must be a column-major SparseMatrix<> |
This class follows the sparse solver concept .
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cholmod_common * | cholmodCommon () const |
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Index | cols () const |
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PermutationType | colsPermutation () const |
| Get the permutation that was applied to columns of A.
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ComputationInfo | info () const |
| Reports whether previous computation was successful.
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SPQRMatrixQReturnType< SPQR > | matrixQ () const |
| Get an expression of the matrix Q.
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const MatrixType | matrixR () const |
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Index | rank () const |
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Index | rows () const |
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void | setPivotThreshold (const RealScalar &tol) |
| Set the tolerance tol to treat columns with 2-norm < =tol as zero.
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void | setSPQROrdering (int ord) |
| Set the fill-reducing ordering method to be used.
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const Solve< SPQR< _MatrixType >, Rhs > | solve (const MatrixBase< Rhs > &b) const |
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const Solve< SPQR< _MatrixType >, Rhs > | solve (const SparseMatrixBase< Rhs > &b) const |
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| SparseSolverBase () |
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