Where to begin…. (#13)

+/- Reworked collection of altimeter related functions into altimeter class
+/- Reworked bno055 class to be imu class with minimal functionality

\- Removed external Kalman filter implementations in favor of own in house version
\- Removed any/unused files
\+ Added buffer logger for when sitting on pad for extended period of time in effort to prevent filling of flash chip
\+ Added heartbeat LED for alive status

1 files changed, 0 insertions, 101 deletions

diff --git a/test/kalmanFilterTest.cpp b/test/kalmanFilterTest.cpp
deleted file mode 100644
index bb0acda..0000000
--- a/test/kalmanFilterTest.cpp
+++ /dev/null
@@ -1,101 +0,0 @@
-#include <iostream>
-#include <gtest/gtest.h>
-#include <Eigen/Dense>
-#include "../include/kalmanfilter.hpp"
-
-using namespace Eigen;
-
-class KalmanFilterTest : public ::testing::Test {
-
-	protected:
-
-		KalmanFilterTest() {
-
-			kf = new KalmanFilter(2, 1, 1, 1);
-		}
-			
-		//~KalmanFilterTest() {}
-
-		KalmanFilter *kf;
-};
-
-
-/**
- *	@brief Test Setting the initial state x & P
- *
- * **/
-TEST_F(KalmanFilterTest, setInitialState) {
-	
-	VectorXf state_vec(2);
-	MatrixXf state_cov(2, 2);
-	state_vec << 1, 2;
-	state_cov << 1, 3, 4, 9;
-	
-	// Success Case
-	EXPECT_TRUE(kf->setInitialState(state_vec, state_cov));
-
-	// Failure Case
-	VectorXf state_vec2(4);
-	state_vec2 << 1, 2, 3, 4;
-	EXPECT_FALSE(kf->setInitialState(state_vec2, state_cov));
-}
-
-/**
- *	@brief Test a single iteration of the Kalman Filter
- *
- * **/
-TEST_F(KalmanFilterTest, run) {
-	
-	VectorXf control(1);
-	VectorXf measurement(1);
-	control << 1;
-	measurement << 1;
-	VectorXf res(1);
-
-	res = kf->run(control, measurement, 1);
-
-	EXPECT_NEAR(0.5454, res(0), 0.0001);
-	EXPECT_NEAR(1, res(1), 0.0001);
-}
-
-
-/**
- * @brief Test run() when the time step value is changed between function calls.
- * 
- */
-TEST_F(KalmanFilterTest, runChange) {
-	
-	VectorXf control(1);
-	VectorXf measurement(1);
-	control << 1;
-	measurement << 1;
-	VectorXf res(1);
-
-	res = kf->run(control, measurement, 0.1);
-	EXPECT_NEAR(0.09545, res(0), 0.00001);
-	EXPECT_NEAR(0.1, res(1), 0.1);
-
-	res = kf->run(control, measurement, 0.15);
-	EXPECT_NEAR(0.2761, res(0), 0.0001);
-	EXPECT_NEAR(0.3585, res(1), 0.0001);
-}
-
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