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78b5479633
* commit '502ab21af0ca68f76d6112722c46d2f35c004053': x86: lpc: simd av_update_lls The versions are bumped due to changes in lls.h which is used across libraries affecting intra library ABI (This version bump also covers changes to lls.h in the immedeatly previous commits) Merged-by: Michael Niedermayer <michaelni@gmx.at>
180 lines
4.7 KiB
C
180 lines
4.7 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 "attributes.h"
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#include "version.h"
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#include "lls.h"
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static void update_lls(LLSModel *m, 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 = 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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static double 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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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_X86)
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ff_init_lls_x86(m);
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}
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#if FF_API_LLS_PRIVATE
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av_cold 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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m->update_lls(m, param);
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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 m->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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LOCAL_ALIGNED(32, 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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m.update_lls(&m, var);
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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 = m.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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