Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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58 lines
2.7 KiB
58 lines
2.7 KiB
import unittest
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import random
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from pyctbn.legacy.structure_graph.trajectory import Trajectory
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from pyctbn.legacy.structure_graph.trajectory_generator import TrajectoryGenerator
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from pyctbn.legacy.utility.json_importer import JsonImporter
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class TestTrajectoryGenerator(unittest.TestCase):
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@classmethod
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def setUpClass(cls) -> None:
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cls.j1 = JsonImporter(file_path = "./tests/data/networks_and_trajectories_binary_data_01_3.json", samples_label = "samples",
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structure_label = "dyn.str", variables_label = "variables",
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cims_label = "dyn.cims", time_key = "Time",
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variables_key = "Name")
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cls.j1.import_data(0)
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def test_init(self):
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tg = TrajectoryGenerator(self.j1)
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self.assertEqual(len(tg._vnames), len(self.j1.variables))
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self.assertIsInstance(tg._vnames, list)
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self.assertIsInstance(tg._parents, dict)
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self.assertIsInstance(tg._cims, dict)
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self.assertListEqual(list(tg._parents.keys()), tg._vnames)
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self.assertListEqual(list(tg._cims.keys()), tg._vnames)
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def test_generated_trajectory(self):
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tg = TrajectoryGenerator(self.j1)
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end_time = random.randint(5, 100)
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sigma = tg.CTBN_Sample(end_time)
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traj = Trajectory(self.j1.build_list_of_samples_array(sigma), len(self.j1.sorter) + 1)
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self.assertLessEqual(traj.times[len(traj.times) - 1], end_time)
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for index in range(len(traj.times)):
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if index > 0:
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self.assertLess(traj.times[index - 1], traj.times[index])
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if index < len(traj.times) - 1:
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diff = abs(sum(traj.trajectory[index - 1]) - sum(traj.trajectory[index]))
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self.assertEqual(diff, 1)
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self.assertEqual(sum(traj.trajectory[len(traj.times) - 1]), -1 * len(self.j1.sorter))
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def test_generated_trajectory_max_tr(self):
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tg = TrajectoryGenerator(self.j1)
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n_tr = random.randint(5, 100)
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sigma = tg.CTBN_Sample(max_tr = n_tr)
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traj = Trajectory(self.j1.build_list_of_samples_array(sigma), len(self.j1.sorter) + 1)
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self.assertEqual(len(traj.times), n_tr + 1)
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def test_multi_trajectory(self):
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tg = TrajectoryGenerator(self.j1)
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max_trs = [random.randint(5, 100) for i in range(10)]
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trajectories = tg.multi_trajectory(max_trs = max_trs)
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self.assertEqual(len(trajectories), len(max_trs))
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self.assertTrue({len(trajectory) for trajectory in trajectories} == {max_tr + 1 for max_tr in max_trs})
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t_ends = [random.randint(100, 500) for i in range(10)]
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trajectories = tg.multi_trajectory(t_ends = t_ends)
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self.assertEqual(len(trajectories), len(t_ends))
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if __name__ == '__main__':
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unittest.main() |