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175 lines
4.6 KiB
175 lines
4.6 KiB
/* |
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* linear least squares model |
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* |
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* Copyright (c) 2006 Michael Niedermayer <michaelni@gmx.at> |
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* |
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* This file is part of Libav. |
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* |
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* Libav is free software; you can redistribute it and/or |
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* modify it under the terms of the GNU Lesser General Public |
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* License as published by the Free Software Foundation; either |
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* version 2.1 of the License, or (at your option) any later version. |
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* |
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* Libav is distributed in the hope that it will be useful, |
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* but WITHOUT ANY WARRANTY; without even the implied warranty of |
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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* Lesser General Public License for more details. |
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* |
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* You should have received a copy of the GNU Lesser General Public |
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* License along with Libav; if not, write to the Free Software |
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* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA |
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*/ |
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/** |
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* @file |
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* linear least squares model |
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*/ |
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#include <math.h> |
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#include <string.h> |
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#include "version.h" |
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#include "lls.h" |
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void avpriv_init_lls(LLSModel *m, int indep_count) |
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{ |
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memset(m, 0, sizeof(LLSModel)); |
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m->indep_count = indep_count; |
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} |
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void avpriv_update_lls(LLSModel *m, double *var, double decay) |
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{ |
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int i, j; |
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for (i = 0; i <= m->indep_count; i++) { |
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for (j = i; j <= m->indep_count; j++) { |
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m->covariance[i][j] *= decay; |
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m->covariance[i][j] += var[i] * var[j]; |
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} |
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} |
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} |
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void avpriv_solve_lls(LLSModel *m, double threshold, unsigned short min_order) |
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{ |
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int i, j, k; |
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double (*factor)[MAX_VARS + 1] = (void *) &m->covariance[1][0]; |
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double (*covar) [MAX_VARS + 1] = (void *) &m->covariance[1][1]; |
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double *covar_y = m->covariance[0]; |
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int count = m->indep_count; |
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for (i = 0; i < count; i++) { |
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for (j = i; j < count; j++) { |
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double sum = covar[i][j]; |
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for (k = i - 1; k >= 0; k--) |
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sum -= factor[i][k] * factor[j][k]; |
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if (i == j) { |
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if (sum < threshold) |
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sum = 1.0; |
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factor[i][i] = sqrt(sum); |
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} else { |
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factor[j][i] = sum / factor[i][i]; |
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} |
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} |
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} |
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for (i = 0; i < count; i++) { |
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double sum = covar_y[i + 1]; |
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for (k = i - 1; k >= 0; k--) |
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sum -= factor[i][k] * m->coeff[0][k]; |
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m->coeff[0][i] = sum / factor[i][i]; |
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} |
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for (j = count - 1; j >= min_order; j--) { |
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for (i = j; i >= 0; i--) { |
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double sum = m->coeff[0][i]; |
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for (k = i + 1; k <= j; k++) |
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sum -= factor[k][i] * m->coeff[j][k]; |
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m->coeff[j][i] = sum / factor[i][i]; |
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} |
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m->variance[j] = covar_y[0]; |
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for (i = 0; i <= j; i++) { |
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double sum = m->coeff[j][i] * covar[i][i] - 2 * covar_y[i + 1]; |
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for (k = 0; k < i; k++) |
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sum += 2 * m->coeff[j][k] * covar[k][i]; |
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m->variance[j] += m->coeff[j][i] * sum; |
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} |
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} |
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} |
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double avpriv_evaluate_lls(LLSModel *m, double *param, int order) |
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{ |
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int i; |
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double out = 0; |
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for (i = 0; i <= order; i++) |
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out += param[i] * m->coeff[order][i]; |
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return out; |
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} |
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#if FF_API_LLS_PRIVATE |
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void av_init_lls(LLSModel *m, int indep_count) |
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{ |
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avpriv_init_lls(m, indep_count); |
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} |
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void av_update_lls(LLSModel *m, double *param, double decay) |
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{ |
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avpriv_update_lls(m, param, decay); |
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} |
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void av_solve_lls(LLSModel *m, double threshold, int min_order) |
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{ |
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avpriv_solve_lls(m, threshold, min_order); |
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} |
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double av_evaluate_lls(LLSModel *m, double *param, int order) |
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{ |
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return avpriv_evaluate_lls(m, param, order); |
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} |
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#endif /* FF_API_LLS_PRIVATE */ |
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#ifdef TEST |
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#include <stdio.h> |
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#include <limits.h> |
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#include "lfg.h" |
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int main(void) |
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{ |
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LLSModel m; |
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int i, order; |
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AVLFG lfg; |
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av_lfg_init(&lfg, 1); |
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avpriv_init_lls(&m, 3); |
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for (i = 0; i < 100; i++) { |
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double var[4]; |
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double eval; |
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var[0] = (av_lfg_get(&lfg) / (double) UINT_MAX - 0.5) * 2; |
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var[1] = var[0] + av_lfg_get(&lfg) / (double) UINT_MAX - 0.5; |
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var[2] = var[1] + av_lfg_get(&lfg) / (double) UINT_MAX - 0.5; |
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var[3] = var[2] + av_lfg_get(&lfg) / (double) UINT_MAX - 0.5; |
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avpriv_update_lls(&m, var, 0.99); |
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avpriv_solve_lls(&m, 0.001, 0); |
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for (order = 0; order < 3; order++) { |
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eval = avpriv_evaluate_lls(&m, var + 1, order); |
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printf("real:%9f order:%d pred:%9f var:%f coeffs:%f %9f %9f\n", |
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var[0], order, eval, sqrt(m.variance[order] / (i + 1)), |
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m.coeff[order][0], m.coeff[order][1], |
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m.coeff[order][2]); |
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} |
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} |
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return 0; |
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} |
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#endif
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