PLearn 0.1
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#include <plearn/math/Cholesky_utils.h>
#include <plearn/math/TMat_maths.h>
#include <plearn/math/random.h>
Go to the source code of this file.
Namespaces | |
namespace | PLearn |
< for swap | |
Functions | |
void | PLearn::choleskyAppendDimension (Mat &L, const Vec &new_row) |
Update the Cholesky decomposition of A = L L' when a new row is appended to the matrix A. | |
void | PLearn::choleskyRemoveDimension (Mat &L, int i) |
Update the Cholesky decomposition of A = L L' when dimension i is removed (i.e. | |
void | PLearn::choleskyInsertBasis (Mat &L, Mat active_bases_outputs, Vec new_basis_outputs, real lambda, real min_Lii) |
void | PLearn::choleskyUpgrade (Mat &L, Vec v) |
void | PLearn::chol_dxch (Mat &R, int l, int m) |
From 'Matrix Algorithms, Vol1' by G. W. Stewart, p.272, 273, 335, 338. | |
void | PLearn::chol_dxch_tr (Mat &R_t, int l, int m) |
These two functions are variants of the above functions, where the R matrix is given as its transpose (which is the case in the Cholesky decomposition). | |
void | PLearn::chol_rotapp (real c, real s, const Vec &x, const Vec &y) |
void | PLearn::chol_rotapp_tr (real c, real s, const Mat &x, const Mat &y) |
void | PLearn::chol_rotapp_tr_opt (real c, real s, const Mat &R, int i, int j, int k, int m) |
Optimized version of 'chol_rotapp_tr' that directly call BLAS functions. | |
void | PLearn::chol_rotgen (real &a, real &b, real &c, real &s) |
void | PLearn::testCholeskyRoutines () |
Definition in file Cholesky_utils.cc.