| 1 | /// @ref gtx_matrix_factorisation |
| 2 | /// @file glm/gtx/matrix_factorisation.hpp |
| 3 | /// |
| 4 | /// @see core (dependence) |
| 5 | /// |
| 6 | /// @defgroup gtx_matrix_factorisation GLM_GTX_matrix_factorisation |
| 7 | /// @ingroup gtx |
| 8 | /// |
| 9 | /// Include <glm/gtx/matrix_factorisation.hpp> to use the features of this extension. |
| 10 | /// |
| 11 | /// Functions to factor matrices in various forms |
| 12 | |
| 13 | #pragma once |
| 14 | |
| 15 | // Dependency: |
| 16 | #include "../glm.hpp" |
| 17 | |
| 18 | #ifndef GLM_ENABLE_EXPERIMENTAL |
| 19 | # error "GLM: GLM_GTX_matrix_factorisation is an experimental extension and may change in the future. Use #define GLM_ENABLE_EXPERIMENTAL before including it, if you really want to use it." |
| 20 | #elif GLM_MESSAGES == GLM_ENABLE && !defined(GLM_EXT_INCLUDED) |
| 21 | # pragma message("GLM: GLM_GTX_matrix_factorisation extension included") |
| 22 | #endif |
| 23 | |
| 24 | /* |
| 25 | Suggestions: |
| 26 | - Move helper functions flipud and fliplr to another file: They may be helpful in more general circumstances. |
| 27 | - Implement other types of matrix factorisation, such as: QL and LQ, L(D)U, eigendecompositions, etc... |
| 28 | */ |
| 29 | |
| 30 | namespace glm |
| 31 | { |
| 32 | /// @addtogroup gtx_matrix_factorisation |
| 33 | /// @{ |
| 34 | |
| 35 | /// Flips the matrix rows up and down. |
| 36 | /// |
| 37 | /// From GLM_GTX_matrix_factorisation extension. |
| 38 | template <length_t C, length_t R, typename T, qualifier Q> |
| 39 | GLM_FUNC_DECL mat<C, R, T, Q> flipud(mat<C, R, T, Q> const& in); |
| 40 | |
| 41 | /// Flips the matrix columns right and left. |
| 42 | /// |
| 43 | /// From GLM_GTX_matrix_factorisation extension. |
| 44 | template <length_t C, length_t R, typename T, qualifier Q> |
| 45 | GLM_FUNC_DECL mat<C, R, T, Q> fliplr(mat<C, R, T, Q> const& in); |
| 46 | |
| 47 | /// Performs QR factorisation of a matrix. |
| 48 | /// Returns 2 matrices, q and r, such that the columns of q are orthonormal and span the same subspace than those of the input matrix, r is an upper triangular matrix, and q*r=in. |
| 49 | /// Given an n-by-m input matrix, q has dimensions min(n,m)-by-m, and r has dimensions n-by-min(n,m). |
| 50 | /// |
| 51 | /// From GLM_GTX_matrix_factorisation extension. |
| 52 | template <length_t C, length_t R, typename T, qualifier Q> |
| 53 | GLM_FUNC_DISCARD_DECL void qr_decompose(mat<C, R, T, Q> const& in, mat<(C < R ? C : R), R, T, Q>& q, mat<C, (C < R ? C : R), T, Q>& r); |
| 54 | |
| 55 | /// Performs RQ factorisation of a matrix. |
| 56 | /// Returns 2 matrices, r and q, such that r is an upper triangular matrix, the rows of q are orthonormal and span the same subspace than those of the input matrix, and r*q=in. |
| 57 | /// Note that in the context of RQ factorisation, the diagonal is seen as starting in the lower-right corner of the matrix, instead of the usual upper-left. |
| 58 | /// Given an n-by-m input matrix, r has dimensions min(n,m)-by-m, and q has dimensions n-by-min(n,m). |
| 59 | /// |
| 60 | /// From GLM_GTX_matrix_factorisation extension. |
| 61 | template <length_t C, length_t R, typename T, qualifier Q> |
| 62 | GLM_FUNC_DISCARD_DECL void rq_decompose(mat<C, R, T, Q> const& in, mat<(C < R ? C : R), R, T, Q>& r, mat<C, (C < R ? C : R), T, Q>& q); |
| 63 | |
| 64 | /// @} |
| 65 | } |
| 66 | |
| 67 | #include "matrix_factorisation.inl" |