mirror of
https://github.com/dragonpilot/dragonpilot.git
synced 2026-02-22 06:04:00 +08:00
9529764549
* complie boardd without python * not good, but don't want to lose the file, because it works * clean a bit * update dbc * should build on CI * not good, but don't want to lose the file, because it works * clean a bit * should build on CI * remove unneeded path * reorder paths * reduce diff * and now it works?! * ... should work in CI * add kj, 30% chance to fix macos * pydebug * new way to find path * fix :) * tested * sanity check * repl. MacOS flags * hope it works * need more logs * need more logs2 * test if it works * should work on CI * correct python file * should not work * cleanup * real cleanup * more removals * 50% of file * transformations * fixed a hardcoded variable * more logs * simpl. * kalman * all donw if it passes tests * cleanup * reduce code by 20 lines if this works * fix bugs * cleanup * SharedLibrary * cleanup * ... * remove unused * CI fix maybe? * add more valid path * more logs * ...: * fix webcam CI * remove WError flag * deprecated is not an error * more Wno things * reduce diff, add Wno to env * don't import nonexistent stuff * SharedLibrary v2 * less custom env * renaming, remove SharedLibs * pack libs in envCython * experiment * better docker caching * whitespace * more docker caching * improvement * improvements Co-authored-by: Adeeb Shihadeh <adeebshihadeh@gmail.com>
88 lines
2.2 KiB
Python
88 lines
2.2 KiB
Python
import unittest
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import random
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import timeit
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import numpy as np
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from common.kalman.simple_kalman import KF1D
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from common.kalman.simple_kalman_old import KF1D as KF1D_old
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class TestSimpleKalman(unittest.TestCase):
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def setUp(self):
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dt = 0.01
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x0_0 = 0.0
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x1_0 = 0.0
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A0_0 = 1.0
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A0_1 = dt
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A1_0 = 0.0
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A1_1 = 1.0
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C0_0 = 1.0
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C0_1 = 0.0
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K0_0 = 0.12287673
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K1_0 = 0.29666309
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self.kf_old = KF1D_old(x0=np.array([[x0_0], [x1_0]]),
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A=np.array([[A0_0, A0_1], [A1_0, A1_1]]),
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C=np.array([C0_0, C0_1]),
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K=np.array([[K0_0], [K1_0]]))
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self.kf = KF1D(x0=[[x0_0], [x1_0]],
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A=[[A0_0, A0_1], [A1_0, A1_1]],
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C=[C0_0, C0_1],
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K=[[K0_0], [K1_0]])
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def test_getter_setter(self):
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self.kf.x = [[1.0], [1.0]]
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self.assertEqual(self.kf.x, [[1.0], [1.0]])
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def update_returns_state(self):
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x = self.kf.update(100)
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self.assertEqual(x, self.kf.x)
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def test_old_equal_new(self):
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for _ in range(1000):
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v_wheel = random.uniform(0, 200)
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x_old = self.kf_old.update(v_wheel)
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x = self.kf.update(v_wheel)
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# Compare the output x, verify that the error is less than 1e-4
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np.testing.assert_almost_equal(x_old[0], x[0])
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np.testing.assert_almost_equal(x_old[1], x[1])
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def test_new_is_faster(self):
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setup = """
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import numpy as np
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from common.kalman.simple_kalman import KF1D
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from common.kalman.simple_kalman_old import KF1D as KF1D_old
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dt = 0.01
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x0_0 = 0.0
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x1_0 = 0.0
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A0_0 = 1.0
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A0_1 = dt
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A1_0 = 0.0
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A1_1 = 1.0
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C0_0 = 1.0
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C0_1 = 0.0
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K0_0 = 0.12287673
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K1_0 = 0.29666309
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kf_old = KF1D_old(x0=np.array([[x0_0], [x1_0]]),
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A=np.array([[A0_0, A0_1], [A1_0, A1_1]]),
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C=np.array([C0_0, C0_1]),
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K=np.array([[K0_0], [K1_0]]))
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kf = KF1D(x0=[[x0_0], [x1_0]],
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A=[[A0_0, A0_1], [A1_0, A1_1]],
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C=[C0_0, C0_1],
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K=[[K0_0], [K1_0]])
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"""
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kf_speed = timeit.timeit("kf.update(1234)", setup=setup, number=10000)
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kf_old_speed = timeit.timeit("kf_old.update(1234)", setup=setup, number=10000)
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self.assertTrue(kf_speed < kf_old_speed / 4)
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if __name__ == "__main__":
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unittest.main()
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