145 lines
3.7 KiB
C
145 lines
3.7 KiB
C
/*
|
|
* linear least squares model
|
|
*
|
|
* Copyright (c) 2006 Michael Niedermayer <michaelni@gmx.at>
|
|
*
|
|
* This library 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 of the License, or (at your option) any later version.
|
|
*
|
|
* This library 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 this library; if not, write to the Free Software
|
|
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
|
|
*/
|
|
|
|
/**
|
|
* @file lls.c
|
|
* linear least squares model
|
|
*/
|
|
|
|
#include <math.h>
|
|
#include <string.h>
|
|
|
|
#include "lls.h"
|
|
|
|
#undef NDEBUG // allways check asserts, the speed effect is far too small to disable them
|
|
#include <assert.h>
|
|
|
|
#ifdef TEST
|
|
#define av_log(a,b,...) printf(__VA_ARGS__)
|
|
#endif
|
|
|
|
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];
|
|
}
|
|
}
|
|
}
|
|
|
|
double av_solve_lls(LLSModel *m, double threshold){
|
|
int i,j,k;
|
|
double (*factor)[MAX_VARS+1]= &m->covariance[1][0];
|
|
double (*covar )[MAX_VARS+1]= &m->covariance[1][1];
|
|
double *covar_y = m->covariance[0];
|
|
double variance;
|
|
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[k];
|
|
m->coeff[i]= sum / factor[i][i];
|
|
}
|
|
|
|
for(i=count-1; i>=0; i--){
|
|
double sum= m->coeff[i];
|
|
for(k=i+1; k<count; k++)
|
|
sum -= factor[k][i]*m->coeff[k];
|
|
m->coeff[i]= sum / factor[i][i];
|
|
}
|
|
|
|
variance= covar_y[0];
|
|
for(i=0; i<count; i++){
|
|
double sum= m->coeff[i]*covar[i][i] - 2*covar_y[i+1];
|
|
for(j=0; j<i; j++)
|
|
sum += 2*m->coeff[j]*covar[j][i];
|
|
variance += m->coeff[i]*sum;
|
|
}
|
|
return variance;
|
|
}
|
|
|
|
double av_evaluate_lls(LLSModel *m, double *param){
|
|
int i;
|
|
double out= 0;
|
|
|
|
for(i=0; i<m->indep_count; i++)
|
|
out+= param[i]*m->coeff[i];
|
|
|
|
return out;
|
|
}
|
|
|
|
#ifdef TEST
|
|
|
|
#include <stdlib.h>
|
|
#include <stdio.h>
|
|
|
|
int main(){
|
|
LLSModel m;
|
|
int i;
|
|
|
|
av_init_lls(&m, 3);
|
|
|
|
for(i=0; i<100; i++){
|
|
double var[4];
|
|
double eval, variance;
|
|
var[1] = rand() / (double)RAND_MAX;
|
|
var[2] = rand() / (double)RAND_MAX;
|
|
var[3] = rand() / (double)RAND_MAX;
|
|
|
|
var[2]= var[1] + var[3];
|
|
|
|
var[0] = var[1] + var[2] + var[3] + var[1]*var[2]/100;
|
|
|
|
eval= av_evaluate_lls(&m, var+1);
|
|
av_update_lls(&m, var, 0.99);
|
|
variance= av_solve_lls(&m, 0.001);
|
|
av_log(NULL, AV_LOG_DEBUG, "real:%f pred:%f var:%f coeffs:%f %f %f\n",
|
|
var[0], eval, sqrt(variance / (i+1)),
|
|
m.coeff[0], m.coeff[1], m.coeff[2]);
|
|
}
|
|
return 0;
|
|
}
|
|
|
|
#endif
|