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