Paparazzi UAS  v5.15_devel-164-g81d4ceb
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pprz_matrix_decomp_float.h
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1 /*
2  * Copyright (C) 2014 Gautier Hattenberger
3  *
4  * This file is part of paparazzi.
5  *
6  * paparazzi is free software; you can redistribute it and/or modify
7  * it under the terms of the GNU General Public License as published by
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14  * GNU General Public License for more details.
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20 
27 #ifndef PPRZ_MATRIX_DECOMP_FLOAT_H
28 #define PPRZ_MATRIX_DECOMP_FLOAT_H
29 
30 #ifdef __cplusplus
31 extern "C" {
32 #endif
33 
34 #include "std.h"
35 
44 void pprz_cholesky_float(float **out, float **in, int n);
45 
58 void pprz_qr_float(float **Q, float **R, float **in, int m, int n);
59 
84 int pprz_svd_float(float **a, float *w, float **v, int m, int n);
85 
104 void pprz_svd_solve_float(float **x, float **u, float *w, float **v, float **b, int m, int n, int l);
105 
117 void fit_linear_model(float *targets, int D, float (*samples)[D], uint16_t count, bool use_bias, float *params,
118  float *fit_error);
119 
120 
121 
135 void fit_linear_model_prior(float *targets, int D, float (*samples)[D], uint16_t count, bool use_bias, float *priors, float *params, float *fit_error);
136 
137 
138 #ifdef __cplusplus
139 } /* extern "C" */
140 #endif
141 
142 #endif /* PPRZ_MATRIX_DECOMP_FLOAT_H */
void fit_linear_model_prior(float *targets, int D, float(*samples)[D], uint16_t count, bool use_bias, float *priors, float *params, float *fit_error)
Fit a linear model from samples to target values with a prior.
unsigned short uint16_t
Definition: types.h:16
void pprz_cholesky_float(float **out, float **in, int n)
Cholesky decomposition.
int32_t m[3 *3]
void pprz_qr_float(float **Q, float **R, float **in, int m, int n)
QR decomposition.
static float D
Definition: trilateration.c:35
void pprz_svd_solve_float(float **x, float **u, float *w, float **v, float **b, int m, int n, int l)
SVD based linear solver.
int pprz_svd_float(float **a, float *w, float **v, int m, int n)
SVD decomposition.
void fit_linear_model(float *targets, int D, float(*samples)[D], uint16_t count, bool use_bias, float *params, float *fit_error)
Fit a linear model from samples to target values.