aboutsummaryrefslogtreecommitdiffstats
path: root/libavutil/lls.h
blob: 0709275822192bf3b301f260786d4baee0b3b2ee (plain) (blame)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
/*
 * 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
 */

#ifndef AVUTIL_LLS_H
#define AVUTIL_LLS_H

#include "macros.h"
#include "mem_internal.h"

#define MAX_VARS 32
#define MAX_VARS_ALIGN FFALIGN(MAX_VARS+1,4)

//FIXME avoid direct access to LLSModel from outside

/**
 * Linear least squares model.
 */
typedef struct LLSModel {
    DECLARE_ALIGNED(32, double, covariance[MAX_VARS_ALIGN][MAX_VARS_ALIGN]);
    DECLARE_ALIGNED(32, double, coeff[MAX_VARS][MAX_VARS]);
    double variance[MAX_VARS];
    int indep_count;
    /**
     * Take the outer-product of var[] with itself, and add to the covariance matrix.
     * @param m this context
     * @param var training samples, starting with the value to be predicted
     *            32-byte aligned, and any padding elements must be initialized
     *            (i.e not denormal/nan).
     */
    void (*update_lls)(struct LLSModel *m, const double *var);
    /**
     * Inner product of var[] and the LPC coefs.
     * @param m this context
     * @param var training samples, excluding the value to be predicted. unaligned.
     * @param order lpc order
     */
    double (*evaluate_lls)(struct LLSModel *m, const double *var, int order);
} LLSModel;

void avpriv_init_lls(LLSModel *m, int indep_count);
void ff_init_lls_x86(LLSModel *m);
void avpriv_solve_lls(LLSModel *m, double threshold, unsigned short min_order);

#endif /* AVUTIL_LLS_H */