TooN 2.0.0-beta8
|
Classes to perform matrix decompositions, used to solve linear equations and provide information about matrices. More...
Classes | |
class | Cholesky< Size, Precision > |
Decomposes a positive-semidefinite symmetric matrix A (such as a covariance) into L*D*L^T, where L is lower-triangular and D is diagonal. More... | |
class | Lapack_Cholesky< Size, Precision > |
Decomposes a positive-semidefinite symmetric matrix A (such as a covariance) into L*L^T, where L is lower-triangular. More... | |
class | LU< Size, Precision > |
Performs LU decomposition and back substitutes to solve equations. More... | |
class | QR_Lapack< Rows, Cols, Precision > |
Performs QR decomposition. More... | |
struct | SQSVD< Size, Precision > |
version of SVD forced to be square princiapally here to allow use in WLS More... | |
class | SymEigen< Size, Precision > |
Performs eigen decomposition of a matrix. More... | |
class | GR_SVD< M, N, Precision, WANT_U, WANT_V > |
Performs SVD and back substitute to solve equations. More... | |
class | SVD< Rows, Cols, Precision > |
Performs SVD and back substitute to solve equations. More... | |
Functions | |
template<int R, int C, class Precision , class Base > | |
void | gauss_jordan (Matrix< R, C, Precision, Base > &m) |
Classes to perform matrix decompositions, used to solve linear equations and provide information about matrices.
These are wrappers for functionality provided by the LAPACK library.
void TooN::gauss_jordan | ( | Matrix< R, C, Precision, Base > & | m | ) |
Perform Gauss-Jordan reduction on m.
If m is of the form , then after reduction, m will be
. There is no restriction on the input, in that the matrix augmenting A does not need to be I, or square. The reduction is performed using elementary row operations and partial pivoting.
m | The matrix to be reduced. |
References Matrix< Rows, Cols, Precision, Layout >::num_cols(), and Matrix< Rows, Cols, Precision, Layout >::num_rows().