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update_lls_8_c: 7.5 update_lls_8_rvv_f64: 4.2 update_lls_12_c: 14.5 update_lls_12_rvv_f64: 5.7
121 lines
3.2 KiB
C
121 lines
3.2 KiB
C
/*
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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 FFmpeg.
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*
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* FFmpeg 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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* FFmpeg 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 FFmpeg; 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 "config.h"
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#include "attributes.h"
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#include "float_dsp.h"
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#include "lls.h"
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static void update_lls(LLSModel *m, const double *var)
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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] += 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_ALIGN] = (void *) &m->covariance[1][0];
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double (*covar) [MAX_VARS_ALIGN] = (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 = 0; k <= i-1; 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 = 0; k <= i-1; 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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static double evaluate_lls(LLSModel *m, const double *param, int order)
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{
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return ff_scalarproduct_double_c(m->coeff[order], param, order + 1);
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}
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av_cold 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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m->update_lls = update_lls;
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m->evaluate_lls = evaluate_lls;
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#if ARCH_RISCV
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ff_init_lls_riscv(m);
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#elif ARCH_X86
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ff_init_lls_x86(m);
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#endif
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}
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