Remove unused variable variance.
[libav.git] / libavutil / lls.c
1 /*
2 * linear least squares model
3 *
4 * Copyright (c) 2006 Michael Niedermayer <michaelni@gmx.at>
5 *
6 * This file is part of FFmpeg.
7 *
8 * FFmpeg is free software; you can redistribute it and/or
9 * modify it under the terms of the GNU Lesser General Public
10 * License as published by the Free Software Foundation; either
11 * version 2.1 of the License, or (at your option) any later version.
12 *
13 * FFmpeg is distributed in the hope that it will be useful,
14 * but WITHOUT ANY WARRANTY; without even the implied warranty of
15 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
16 * Lesser General Public License for more details.
17 *
18 * You should have received a copy of the GNU Lesser General Public
19 * License along with FFmpeg; if not, write to the Free Software
20 * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
21 */
22
23 /**
24 * @file lls.c
25 * linear least squares model
26 */
27
28 #include <math.h>
29 #include <string.h>
30
31 #include "lls.h"
32
33 #ifdef TEST
34 #define av_log(a,b,...) printf(__VA_ARGS__)
35 #endif
36
37 void av_init_lls(LLSModel *m, int indep_count){
38 memset(m, 0, sizeof(LLSModel));
39
40 m->indep_count= indep_count;
41 }
42
43 void av_update_lls(LLSModel *m, double *var, double decay){
44 int i,j;
45
46 for(i=0; i<=m->indep_count; i++){
47 for(j=i; j<=m->indep_count; j++){
48 m->covariance[i][j] *= decay;
49 m->covariance[i][j] += var[i]*var[j];
50 }
51 }
52 }
53
54 void av_solve_lls(LLSModel *m, double threshold, int min_order){
55 int i,j,k;
56 double (*factor)[MAX_VARS+1]= &m->covariance[1][0];
57 double (*covar )[MAX_VARS+1]= &m->covariance[1][1];
58 double *covar_y = m->covariance[0];
59 int count= m->indep_count;
60
61 for(i=0; i<count; i++){
62 for(j=i; j<count; j++){
63 double sum= covar[i][j];
64
65 for(k=i-1; k>=0; k--)
66 sum -= factor[i][k]*factor[j][k];
67
68 if(i==j){
69 if(sum < threshold)
70 sum= 1.0;
71 factor[i][i]= sqrt(sum);
72 }else
73 factor[j][i]= sum / factor[i][i];
74 }
75 }
76 for(i=0; i<count; i++){
77 double sum= covar_y[i+1];
78 for(k=i-1; k>=0; k--)
79 sum -= factor[i][k]*m->coeff[0][k];
80 m->coeff[0][i]= sum / factor[i][i];
81 }
82
83 for(j=count-1; j>=min_order; j--){
84 for(i=j; i>=0; i--){
85 double sum= m->coeff[0][i];
86 for(k=i+1; k<=j; k++)
87 sum -= factor[k][i]*m->coeff[j][k];
88 m->coeff[j][i]= sum / factor[i][i];
89 }
90
91 m->variance[j]= covar_y[0];
92 for(i=0; i<=j; i++){
93 double sum= m->coeff[j][i]*covar[i][i] - 2*covar_y[i+1];
94 for(k=0; k<i; k++)
95 sum += 2*m->coeff[j][k]*covar[k][i];
96 m->variance[j] += m->coeff[j][i]*sum;
97 }
98 }
99 }
100
101 double av_evaluate_lls(LLSModel *m, double *param, int order){
102 int i;
103 double out= 0;
104
105 for(i=0; i<=order; i++)
106 out+= param[i]*m->coeff[order][i];
107
108 return out;
109 }
110
111 #ifdef TEST
112
113 #include <stdlib.h>
114 #include <stdio.h>
115
116 int main(void){
117 LLSModel m;
118 int i, order;
119
120 av_init_lls(&m, 3);
121
122 for(i=0; i<100; i++){
123 double var[4];
124 double eval;
125 #if 0
126 var[1] = rand() / (double)RAND_MAX;
127 var[2] = rand() / (double)RAND_MAX;
128 var[3] = rand() / (double)RAND_MAX;
129
130 var[2]= var[1] + var[3]/2;
131
132 var[0] = var[1] + var[2] + var[3] + var[1]*var[2]/100;
133 #else
134 var[0] = (rand() / (double)RAND_MAX - 0.5)*2;
135 var[1] = var[0] + rand() / (double)RAND_MAX - 0.5;
136 var[2] = var[1] + rand() / (double)RAND_MAX - 0.5;
137 var[3] = var[2] + rand() / (double)RAND_MAX - 0.5;
138 #endif
139 av_update_lls(&m, var, 0.99);
140 av_solve_lls(&m, 0.001, 0);
141 for(order=0; order<3; order++){
142 eval= av_evaluate_lls(&m, var+1, order);
143 av_log(NULL, AV_LOG_DEBUG, "real:%f order:%d pred:%f var:%f coeffs:%f %f %f\n",
144 var[0], order, eval, sqrt(m.variance[order] / (i+1)),
145 m.coeff[order][0], m.coeff[order][1], m.coeff[order][2]);
146 }
147 }
148 return 0;
149 }
150
151 #endif