avoiding casts would be even less readable, but other suggestions are welcome. lls.c:56: warning: initialization from incompatible pointer type lls.c:57: warning: initialization from incompatible pointer type Originally committed as revision 11697 to svn://svn.ffmpeg.org/ffmpeg/trunk
		
			
				
	
	
		
			152 lines
		
	
	
		
			4.1 KiB
		
	
	
	
		
			C
		
	
	
	
	
	
			
		
		
	
	
			152 lines
		
	
	
		
			4.1 KiB
		
	
	
	
		
			C
		
	
	
	
	
	
/*
 | 
						|
 * 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 lls.c
 | 
						|
 * linear least squares model
 | 
						|
 */
 | 
						|
 | 
						|
#include <math.h>
 | 
						|
#include <string.h>
 | 
						|
 | 
						|
#include "lls.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];
 | 
						|
        }
 | 
						|
    }
 | 
						|
}
 | 
						|
 | 
						|
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);
 | 
						|
            av_log(NULL, AV_LOG_DEBUG, "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
 |