Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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46 lines
1.9 KiB
46 lines
1.9 KiB
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import unittest
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import numpy as np
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from ..PyCTBN.trajectory import Trajectory
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class TestTrajectory(unittest.TestCase):
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def test_init(self):
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cols_list = [np.array([1.2,1.3,.14]), np.arange(1,4), np.arange(4,7)]
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t1 = Trajectory(cols_list, len(cols_list) - 2)
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self.assertTrue(np.array_equal(cols_list[0], t1.times))
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self.assertTrue(np.array_equal(np.ravel(t1.complete_trajectory[:, : 1]), cols_list[1]))
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self.assertTrue(np.array_equal(np.ravel(t1.complete_trajectory[:, 1: 2]), cols_list[2]))
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self.assertEqual(len(cols_list) - 1, t1.complete_trajectory.shape[1])
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self.assertEqual(t1.size(), t1.times.size)
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def test_init_first_array_not_float_type(self):
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cols_list = [np.arange(1, 4), np.arange(4, 7), np.array([1.2, 1.3, .14])]
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self.assertRaises(TypeError, Trajectory, cols_list, len(cols_list))
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def test_complete_trajectory(self):
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cols_list = [np.array([1.2, 1.3, .14]), np.arange(1, 4), np.arange(4, 7)]
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t1 = Trajectory(cols_list, len(cols_list) - 2)
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complete = np.column_stack((cols_list[1], cols_list[2]))
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self.assertTrue(np.array_equal(t1.complete_trajectory, complete))
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def test_trajectory(self):
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cols_list = [np.array([1.2, 1.3, .14]), np.arange(1, 4), np.arange(4, 7)]
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t1 = Trajectory(cols_list, len(cols_list) - 2)
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self.assertTrue(np.array_equal(cols_list[1], t1.trajectory.ravel()))
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def test_times(self):
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cols_list = [np.array([1.2, 1.3, .14]), np.arange(1, 4), np.arange(4, 7)]
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t1 = Trajectory(cols_list, len(cols_list) - 2)
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self.assertTrue(np.array_equal(cols_list[0], t1.times))
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def test_repr(self):
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cols_list = [np.array([1.2, 1.3, .14]), np.arange(1, 4), np.arange(4, 7)]
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t1 = Trajectory(cols_list, len(cols_list) - 2)
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print(t1)
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if __name__ == '__main__':
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unittest.main()
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