Eigen
3.3.71

Sparse QR factorization based on SuiteSparseQR library.
This class is used to perform a multithreaded and multifrontal rankrevealing 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 columnmajor SparseMatrix<> 
This class follows the sparse solver concept .
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< 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 2norm < =tol as zero.  
void  setSPQROrdering (int ord) 
Set the fillreducing ordering method to be used.  

inline 

inline 
Get the number of columns of the input matrix.

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

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