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					86 lines
				
				2.2 KiB
			
		
		
			
		
	
	
					86 lines
				
				2.2 KiB
			| 
											6 years ago
										 | 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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|  | 
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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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|  | 
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|  | 
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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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|  | 
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|  |     self.kf_old = KF1D_old(x0=np.matrix([[x0_0], [x1_0]]),
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|  |                            A=np.matrix([[A0_0, A0_1], [A1_0, A1_1]]),
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|  |                            C=np.matrix([C0_0, C0_1]),
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|  |                            K=np.matrix([[K0_0], [K1_0]]))
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|  | 
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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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|  | 
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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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|  | 
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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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|  | 
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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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|  | 
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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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|  | 
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|  |       # Compare the output x, verify that the error is less than 1e-4
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|  |       self.assertAlmostEqual(x_old[0], x[0])
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|  |       self.assertAlmostEqual(x_old[1], x[1])
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|  | 
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|  | 
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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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|  | 
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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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|  | 
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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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|  | 
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|  | kf_old = KF1D_old(x0=np.matrix([[x0_0], [x1_0]]),
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|  |                   A=np.matrix([[A0_0, A0_1], [A1_0, A1_1]]),
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|  |                   C=np.matrix([C0_0, C0_1]),
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|  |                   K=np.matrix([[K0_0], [K1_0]]))
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|  | 
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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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