Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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61 lines
2.1 KiB
61 lines
2.1 KiB
#!/usr/bin/env python3
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# License: MIT License
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import unittest
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import numpy as np
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from pyctbn.legacy.utility.cache import Cache
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from pyctbn.legacy.structure_graph.set_of_cims import SetOfCims
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class TestCache(unittest.TestCase):
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def test_init(self):
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c1 = Cache()
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self.assertFalse(c1._list_of_sets_of_parents)
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self.assertFalse(c1._actual_cache)
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def test_put(self):
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c1 = Cache()
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pset1 = {'X', 'Y'}
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sofc1 = SetOfCims(node_id = 'Z', parents_states_number = [], node_states_number = 3, p_combs = np.array([]))
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c1.put(pset1, sofc1)
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self.assertEqual(1, len(c1._actual_cache))
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self.assertEqual(1, len(c1._list_of_sets_of_parents))
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self.assertEqual(sofc1, c1._actual_cache[0])
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pset2 = {'X'}
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sofc2 = SetOfCims(node_id = 'Z', parents_states_number = [], node_states_number = 3, p_combs = np.array([]))
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c1.put(pset2, sofc2)
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self.assertEqual(2, len(c1._actual_cache))
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self.assertEqual(2, len(c1._list_of_sets_of_parents))
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self.assertEqual(sofc2, c1._actual_cache[1])
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def test_find(self):
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c1 = Cache()
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pset1 = {'X', 'Y'}
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sofc1 = SetOfCims(node_id = 'Z', parents_states_number = [], node_states_number = 3, p_combs = np.array([]))
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c1.put(pset1, sofc1)
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self.assertEqual(1, len(c1._actual_cache))
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self.assertEqual(1, len(c1._list_of_sets_of_parents))
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self.assertIsInstance(c1.find(pset1), SetOfCims)
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self.assertEqual(sofc1, c1.find(pset1))
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self.assertIsInstance(c1.find({'Y', 'X'}), SetOfCims)
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self.assertEqual(sofc1, c1.find({'Y', 'X'}))
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self.assertIsNone(c1.find({'X'}))
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def test_clear(self):
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c1 = Cache()
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pset1 = {'X', 'Y'}
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sofc1 = SetOfCims('Z', [], 3, np.array([]))
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c1.put(pset1, sofc1)
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self.assertEqual(1, len(c1._actual_cache))
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self.assertEqual(1, len(c1._list_of_sets_of_parents))
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c1.clear()
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self.assertFalse(c1._list_of_sets_of_parents)
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self.assertFalse(c1._actual_cache)
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if __name__ == '__main__':
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unittest.main()
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