| /* |
| * Copyright (c) 2017, Alliance for Open Media. All rights reserved |
| * |
| * This source code is subject to the terms of the BSD 2 Clause License and |
| * the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License |
| * was not distributed with this source code in the LICENSE file, you can |
| * obtain it at www.aomedia.org/license/software. If the Alliance for Open |
| * Media Patent License 1.0 was not distributed with this source code in the |
| * PATENTS file, you can obtain it at www.aomedia.org/license/patent. |
| */ |
| |
| #ifndef AOM_AOM_DSP_MATHUTILS_H_ |
| #define AOM_AOM_DSP_MATHUTILS_H_ |
| |
| #include <assert.h> |
| #include <math.h> |
| #include <string.h> |
| |
| #include "aom_dsp/aom_dsp_common.h" |
| #include "aom_mem/aom_mem.h" |
| |
| static const double TINY_NEAR_ZERO = 1.0E-16; |
| |
| // Solves Ax = b, where x and b are column vectors of size nx1 and A is nxn |
| static INLINE int linsolve(int n, double *A, int stride, double *b, double *x) { |
| int i, j, k; |
| double c; |
| // Forward elimination |
| for (k = 0; k < n - 1; k++) { |
| // Bring the largest magnitude to the diagonal position |
| for (i = n - 1; i > k; i--) { |
| if (fabs(A[(i - 1) * stride + k]) < fabs(A[i * stride + k])) { |
| for (j = 0; j < n; j++) { |
| c = A[i * stride + j]; |
| A[i * stride + j] = A[(i - 1) * stride + j]; |
| A[(i - 1) * stride + j] = c; |
| } |
| c = b[i]; |
| b[i] = b[i - 1]; |
| b[i - 1] = c; |
| } |
| } |
| for (i = k; i < n - 1; i++) { |
| if (fabs(A[k * stride + k]) < TINY_NEAR_ZERO) return 0; |
| c = A[(i + 1) * stride + k] / A[k * stride + k]; |
| for (j = 0; j < n; j++) A[(i + 1) * stride + j] -= c * A[k * stride + j]; |
| b[i + 1] -= c * b[k]; |
| } |
| } |
| // Backward substitution |
| for (i = n - 1; i >= 0; i--) { |
| if (fabs(A[i * stride + i]) < TINY_NEAR_ZERO) return 0; |
| c = 0; |
| for (j = i + 1; j <= n - 1; j++) c += A[i * stride + j] * x[j]; |
| x[i] = (b[i] - c) / A[i * stride + i]; |
| } |
| |
| return 1; |
| } |
| |
| //////////////////////////////////////////////////////////////////////////////// |
| // Least-squares |
| // Solves for n-dim x in a least squares sense to minimize |Ax - b|^2 |
| // The solution is simply x = (A'A)^-1 A'b or simply the solution for |
| // the system: A'A x = A'b |
| static INLINE int least_squares(int n, double *A, int rows, int stride, |
| double *b, double *scratch, double *x) { |
| int i, j, k; |
| double *scratch_ = NULL; |
| double *AtA, *Atb; |
| if (!scratch) { |
| scratch_ = (double *)aom_malloc(sizeof(*scratch) * n * (n + 1)); |
| if (!scratch_) return 0; |
| scratch = scratch_; |
| } |
| AtA = scratch; |
| Atb = scratch + n * n; |
| |
| for (i = 0; i < n; ++i) { |
| for (j = i; j < n; ++j) { |
| AtA[i * n + j] = 0.0; |
| for (k = 0; k < rows; ++k) |
| AtA[i * n + j] += A[k * stride + i] * A[k * stride + j]; |
| AtA[j * n + i] = AtA[i * n + j]; |
| } |
| Atb[i] = 0; |
| for (k = 0; k < rows; ++k) Atb[i] += A[k * stride + i] * b[k]; |
| } |
| int ret = linsolve(n, AtA, n, Atb, x); |
| aom_free(scratch_); |
| return ret; |
| } |
| |
| // Matrix multiply |
| static INLINE void multiply_mat(const double *m1, const double *m2, double *res, |
| const int m1_rows, const int inner_dim, |
| const int m2_cols) { |
| double sum; |
| |
| int row, col, inner; |
| for (row = 0; row < m1_rows; ++row) { |
| for (col = 0; col < m2_cols; ++col) { |
| sum = 0; |
| for (inner = 0; inner < inner_dim; ++inner) |
| sum += m1[row * inner_dim + inner] * m2[inner * m2_cols + col]; |
| *(res++) = sum; |
| } |
| } |
| } |
| |
| #endif // AOM_AOM_DSP_MATHUTILS_H_ |