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Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍 https://github.com/madlabunimib/PyCTBN
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PyCTBN/main_package/tests/structure_graph/test_trajectory.py

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import sys
sys.path.append("../../classes/")
import unittest
import numpy as np
import structure_graph.trajectory as tr
class TestTrajectory(unittest.TestCase):
def test_init(self):
cols_list = [np.array([1.2,1.3,.14]), np.arange(1,4), np.arange(4,7)]
t1 = tr.Trajectory(cols_list, len(cols_list) - 2)
self.assertTrue(np.array_equal(cols_list[0], t1.times))
self.assertTrue(np.array_equal(np.ravel(t1.complete_trajectory[:, : 1]), cols_list[1]))
self.assertTrue(np.array_equal(np.ravel(t1.complete_trajectory[:, 1: 2]), cols_list[2]))
self.assertEqual(len(cols_list) - 1, t1.complete_trajectory.shape[1])
self.assertEqual(t1.size(), t1.times.size)
def test_init_first_array_not_float_type(self):
cols_list = [np.arange(1, 4), np.arange(4, 7), np.array([1.2, 1.3, .14])]
self.assertRaises(TypeError, tr.Trajectory, cols_list, len(cols_list))
def test_complete_trajectory(self):
cols_list = [np.array([1.2, 1.3, .14]), np.arange(1, 4), np.arange(4, 7)]
t1 = tr.Trajectory(cols_list, len(cols_list) - 2)
complete = np.column_stack((cols_list[1], cols_list[2]))
self.assertTrue(np.array_equal(t1.complete_trajectory, complete))
def test_trajectory(self):
cols_list = [np.array([1.2, 1.3, .14]), np.arange(1, 4), np.arange(4, 7)]
t1 = tr.Trajectory(cols_list, len(cols_list) - 2)
self.assertTrue(np.array_equal(cols_list[1], t1.trajectory.ravel()))
def test_times(self):
cols_list = [np.array([1.2, 1.3, .14]), np.arange(1, 4), np.arange(4, 7)]
t1 = tr.Trajectory(cols_list, len(cols_list) - 2)
self.assertTrue(np.array_equal(cols_list[0], t1.times))
def test_repr(self):
cols_list = [np.array([1.2, 1.3, .14]), np.arange(1, 4), np.arange(4, 7)]
t1 = tr.Trajectory(cols_list, len(cols_list) - 2)
print(t1)
if __name__ == '__main__':
unittest.main()