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4349 Serge 1
/*
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 * linear least squares model
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 *
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 * Copyright (c) 2006 Michael Niedermayer 
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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 
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#include 
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#include "attributes.h"
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#include "version.h"
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#include "lls1.h"
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#if FF_API_LLS1
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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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}
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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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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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    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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#endif /* FF_API_LLS1 */
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#ifdef TEST
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#include 
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#include 
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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