lls: whitespace cosmetics
[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 Libav.
7 *
8 * Libav 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 * Libav 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 Libav; 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
25 * linear least squares model
26 */
27
28 #include <math.h>
29 #include <string.h>
30
31 #include "lls.h"
32
33 void av_init_lls(LLSModel *m, int indep_count)
34 {
35 memset(m, 0, sizeof(LLSModel));
36 m->indep_count = indep_count;
37 }
38
39 void av_update_lls(LLSModel *m, double *var, double decay)
40 {
41 int i, j;
42
43 for (i = 0; i <= m->indep_count; i++) {
44 for (j = i; j <= m->indep_count; j++) {
45 m->covariance[i][j] *= decay;
46 m->covariance[i][j] += var[i] * var[j];
47 }
48 }
49 }
50
51 void av_solve_lls(LLSModel *m, double threshold, int min_order)
52 {
53 int i, j, k;
54 double (*factor)[MAX_VARS + 1] = (void *) &m->covariance[1][0];
55 double (*covar) [MAX_VARS + 1] = (void *) &m->covariance[1][1];
56 double *covar_y = m->covariance[0];
57 int count = m->indep_count;
58
59 for (i = 0; i < count; i++) {
60 for (j = i; j < count; j++) {
61 double sum = covar[i][j];
62
63 for (k = i - 1; k >= 0; k--)
64 sum -= factor[i][k] * factor[j][k];
65
66 if (i == j) {
67 if (sum < threshold)
68 sum = 1.0;
69 factor[i][i] = sqrt(sum);
70 } else {
71 factor[j][i] = sum / factor[i][i];
72 }
73 }
74 }
75
76 for (i = 0; i < count; i++) {
77 double sum = covar_y[i + 1];
78
79 for (k = i - 1; k >= 0; k--)
80 sum -= factor[i][k] * m->coeff[0][k];
81
82 m->coeff[0][i] = sum / factor[i][i];
83 }
84
85 for (j = count - 1; j >= min_order; j--) {
86 for (i = j; i >= 0; i--) {
87 double sum = m->coeff[0][i];
88
89 for (k = i + 1; k <= j; k++)
90 sum -= factor[k][i] * m->coeff[j][k];
91
92 m->coeff[j][i] = sum / factor[i][i];
93 }
94
95 m->variance[j] = covar_y[0];
96
97 for (i = 0; i <= j; i++) {
98 double sum = m->coeff[j][i] * covar[i][i] - 2 * covar_y[i + 1];
99
100 for (k = 0; k < i; k++)
101 sum += 2 * m->coeff[j][k] * covar[k][i];
102
103 m->variance[j] += m->coeff[j][i] * sum;
104 }
105 }
106 }
107
108 double av_evaluate_lls(LLSModel *m, double *param, int order)
109 {
110 int i;
111 double out = 0;
112
113 for (i = 0; i <= order; i++)
114 out += param[i] * m->coeff[order][i];
115
116 return out;
117 }
118
119 #ifdef TEST
120
121 #include <stdlib.h>
122 #include <stdio.h>
123
124 int main(void)
125 {
126 LLSModel m;
127 int i, order;
128
129 av_init_lls(&m, 3);
130
131 for (i = 0; i < 100; i++) {
132 double var[4];
133 double eval;
134
135 var[0] = (rand() / (double) RAND_MAX - 0.5) * 2;
136 var[1] = var[0] + rand() / (double) RAND_MAX - 0.5;
137 var[2] = var[1] + rand() / (double) RAND_MAX - 0.5;
138 var[3] = var[2] + rand() / (double) RAND_MAX - 0.5;
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 printf("real:%9f order:%d pred:%9f var:%f coeffs:%f %9f %9f\n",
144 var[0], order, eval, sqrt(m.variance[order] / (i + 1)),
145 m.coeff[order][0], m.coeff[order][1],
146 m.coeff[order][2]);
147 }
148 }
149 return 0;
150 }
151
152 #endif