These matrices are built on top of the basic matrices. They perform special operations using the interface defined by the MatrixType concept.
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These matrices are built on top of the basic matrices. They perform special operations using the interface defined by the MatrixType concept.
◆ size_type
template<typename number >
Declare type of container size type.
Definition at line 87 of file householder.h.
◆ Householder() [1/2]
template<typename number >
◆ Householder() [2/2]
template<typename number >
template<typename number2 >
Create an object holding the QR-decomposition of the matrix \(A\).
◆ initialize()
template<typename number >
template<typename number2 >
Compute the QR-decomposition of the given matrix \(A\).
This overwrites any previously computed QR decomposition.
◆ least_squares() [1/2]
template<typename number >
template<typename number2 >
Solve the least-squares problem for the right hand side src
. The returned scalar value is the Euclidean norm of the approximation error.
dst
contains the solution of the least squares problem on return.
src
contains the right hand side b of the least squares problem. It will be changed during the algorithm and is unusable on return.
◆ least_squares() [2/2]
template<typename number >
template<typename number2 >
This function does the same as the previous one, but for BlockVectors.
◆ vmult()
template<typename number >
template<class VectorType >
A wrapper to least_squares(), implementing the standard MatrixType interface.
◆ Tvmult()
template<typename number >
template<class VectorType >
A wrapper to least_squares() that implements multiplication with the transpose matrix.
◆ diagonal
template<typename number >
Storage for the diagonal elements of the orthogonal transformation. See the class documentation for more information.
Definition at line 153 of file householder.h.
◆ storage
template<typename number >