18166700002

Committed 01 Oct 2025 03:09PM UTC coverage: 71.132% (-0.04%) from 71.174%

Build # 18166700002

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push

github

Committed by

paulmthompson

Commit Message

clang format

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20 existing lines in 3 files now uncovered.

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80.85

/src/StateEstimation/Kalman/kalman.cpp

/**
 * 
 * 
 * The MIT License (MIT)

Copyright (c) 2014 Hayk Martirosyan

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
* Kalman filter implementation using Eigen. Based on the following
* introductory paper:
*
*     http://www.cs.unc.edu/~welch/media/pdf/kalman_intro.pdf
*
* @author: Hayk Martirosyan
* @date: 2014.11.15
*/

#include "kalman.hpp"

#include <iostream>
#include <stdexcept>

KalmanFilter::KalmanFilter(
        double dt,
        Eigen::MatrixXd const & A,
        Eigen::MatrixXd const & C,
        Eigen::MatrixXd const & Q,
        Eigen::MatrixXd const & R,
        Eigen::MatrixXd const & P)
    : A(A),
      C(C),
      Q(Q),
      R(R),
      P0(P),
      m(C.rows()),
      n(A.rows()),
      dt(dt),
      initialized(false),
      I(n, n),
      x_hat(n),
      x_hat_new(n) {
    I.setIdentity();
}

KalmanFilter::KalmanFilter() {}

void KalmanFilter::init(double t0, Eigen::VectorXd const & x0) {
    x_hat = x0;
    P = P0;
    this->t0 = t0;
    t = t0;
    initialized = true;
}

void KalmanFilter::init() {
    x_hat.setZero();
    P = P0;
    t0 = 0;
    t = t0;
    initialized = true;
}

void KalmanFilter::update(Eigen::VectorXd const & y) {

    if (!initialized)
        throw std::runtime_error("Filter is not initialized!");

    x_hat_new = A * x_hat;
    P = A * P * A.transpose() + Q;
    K = P * C.transpose() * (C * P * C.transpose() + R).inverse();
    x_hat_new += K * (y - C * x_hat_new);
    P = (I - K * C) * P;
    x_hat = x_hat_new;

    t += dt;
}

void KalmanFilter::update(Eigen::VectorXd const & y, double dt, Eigen::MatrixXd const A) {

    this->A = A;
    this->dt = dt;
    update(y);
}

1	/**
2	*
3	*
4	* The MIT License (MIT)
5
6	Copyright (c) 2014 Hayk Martirosyan
7
8	Permission is hereby granted, free of charge, to any person obtaining a copy
9	of this software and associated documentation files (the "Software"), to deal
10	in the Software without restriction, including without limitation the rights
11	to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
12	copies of the Software, and to permit persons to whom the Software is
13	furnished to do so, subject to the following conditions:
14
15	The above copyright notice and this permission notice shall be included in all
16	copies or substantial portions of the Software.
17
18	THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
19	IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
20	FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
21	AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
22	LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
23	OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
24	SOFTWARE.
25	* Kalman filter implementation using Eigen. Based on the following
26	* introductory paper:
27	*
28	* http://www.cs.unc.edu/~welch/media/pdf/kalman_intro.pdf
29	*
30	* @author: Hayk Martirosyan
31	* @date: 2014.11.15
32	*/
33
34	#include "kalman.hpp"
35
36	#include <iostream>
37	#include <stdexcept>
38
39	KalmanFilter::KalmanFilter(	15✔
40	double dt,
41	Eigen::MatrixXd const & A,
42	Eigen::MatrixXd const & C,
43	Eigen::MatrixXd const & Q,
44	Eigen::MatrixXd const & R,
45	Eigen::MatrixXd const & P)	15✔
46	: A(A),	15✔
47	C(C),	15✔
48	Q(Q),	15✔
49	R(R),	15✔
50	P0(P),	15✔
51	m(C.rows()),	15✔
52	n(A.rows()),	15✔
53	dt(dt),	15✔
54	initialized(false),	15✔
55	I(n, n),	15✔
56	x_hat(n),	15✔
57	x_hat_new(n) {	30✔
58	I.setIdentity();	15✔
59	}	15✔
60
UNCOV 61	KalmanFilter::KalmanFilter() {}	×
62
63	void KalmanFilter::init(double t0, Eigen::VectorXd const & x0) {	15✔
64	x_hat = x0;	15✔
65	P = P0;	15✔
66	this->t0 = t0;	15✔
67	t = t0;	15✔
68	initialized = true;	15✔
69	}	15✔
70
71	void KalmanFilter::init() {	×
72	x_hat.setZero();	×
73	P = P0;	×
74	t0 = 0;	×
75	t = t0;	×
76	initialized = true;	×
77	}	×
78
79	void KalmanFilter::update(Eigen::VectorXd const & y) {	13✔
80
81	if (!initialized)	13✔
82	throw std::runtime_error("Filter is not initialized!");	×
83
84	x_hat_new = A * x_hat;	13✔
85	P = A * P * A.transpose() + Q;	13✔
86	K = P * C.transpose() * (C * P * C.transpose() + R).inverse();	13✔
87	x_hat_new += K * (y - C * x_hat_new);	13✔
88	P = (I - K * C) * P;	13✔
89	x_hat = x_hat_new;	13✔
90
91	t += dt;	13✔
92	}	13✔
93
94	void KalmanFilter::update(Eigen::VectorXd const & y, double dt, Eigen::MatrixXd const A) {	2✔
95
96	this->A = A;	2✔
97	this->dt = dt;	2✔
98	update(y);	2✔
99	}	2✔

paulmthompson / WhiskerToolbox / 18166700002

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