def test_copy(self):
model = MC(['a', 'b'], [2, 2], [State('a', 0), State('b', 1)])
model.add_transition_model('a', {0: {0: 0.1, 1: 0.9}, 1: {0: 0.2, 1: 0.8}})
model.add_transition_model('b', {0: {0: 0.3, 1: 0.7}, 1: {0: 0.4, 1: 0.6}})
copy = model.copy()
self.assertIsInstance(copy, MC)
self.assertEqual(sorted(model.variables), sorted(copy.variables))
self.assertEqual(model.cardinalities, copy.cardinalities)
self.assertEqual(model.transition_models, copy.transition_models)
self.assertEqual(model.state, copy.state)
model.add_variable('p', 1)
model.set_start_state([State('a', 0), State('b', 1), State('p', 0)])
model.add_transition_model('p', {0: {0: 1}})
self.assertNotEqual(sorted(model.variables), sorted(copy.variables))
self.assertEqual(sorted(['a', 'b']), sorted(copy.variables))
self.assertNotEqual(model.cardinalities, copy.cardinalities)
self.assertEqual({'a': 2, 'b': 2}, copy.cardinalities)
self.assertNotEqual(model.state, copy.state)
self.assertEqual([State('a', 0), State('b', 1)], copy.state)
self.assertNotEqual(model.transition_models, copy.transition_models)
self.assertEqual(len(copy.transition_models), 2)
self.assertEqual(copy.transition_models['a'], {0: {0: 0.1, 1: 0.9}, 1: {0: 0.2, 1: 0.8}})
self.assertEqual(copy.transition_models['b'], {0: {0: 0.3, 1: 0.7}, 1: {0: 0.4, 1: 0.6}})
def test_is_stationarity_failure(self):
model = MC(['intel', 'diff'], [2, 3])
model.set_start_state([State('intel', 0), State('diff', 2)])
intel_tm = {0: {0: 0.25, 1: 0.75}, 1: {0: 0.5, 1: 0.5}}
model.add_transition_model('intel', intel_tm)
diff_tm = {0: {0: 0.1, 1: 0.5, 2: 0.4}, 1: {0: 0.2, 1: 0.2, 2: 0.6}, 2: {0: 0.7, 1: 0.15, 2: 0.15}}
model.add_transition_model('diff', diff_tm)
self.assertFalse(model.is_stationarity(0.002, None))
def test_is_stationarity_failure(self):
model = MC(['intel', 'diff'], [2, 3])
model.set_start_state([State('intel', 0), State('diff', 2)])
intel_tm = {0: {0: 0.25, 1: 0.75}, 1: {0: 0.5, 1: 0.5}}
model.add_transition_model('intel', intel_tm)
diff_tm = {
0: {
0: 0.1,
1: 0.5,
2: 0.4
},
1: {
0: 0.2,
1: 0.2,
2: 0.6
},
2: {
0: 0.7,
1: 0.15,
2: 0.15
}
}
model.add_transition_model('diff', diff_tm)
self.assertFalse(model.is_stationarity(0.002, None))
def test_transition_model_dict_to_matrix(self):
model = MC(['var'], [2])
transition_model = {0: {0: 0.3, 1: 0.7}, 1: {0: 0.5, 1: 0.5}}
transition_model_matrix = np.array([[0.3, 0.7], [0.5, 0.5]])
model.add_transition_model('var', transition_model_matrix)
self.assertDictEqual(model.transition_models['var'], transition_model)
def test_add_transition_model_success(self):
model = MC(['var'], [2])
transition_model = {0: {0: 0.3, 1: 0.7}, 1: {0: 0.5, 1: 0.5}}
model.add_transition_model('var', transition_model)
self.assertDictEqual(model.transition_models['var'], transition_model)
def test_copy(self):
model = MC(['a', 'b'], [2, 2], [State('a', 0), State('b', 1)])
model.add_transition_model('a', {
0: {
0: 0.1,
1: 0.9
},
1: {
0: 0.2,
1: 0.8
}
})
model.add_transition_model('b', {
0: {
0: 0.3,
1: 0.7
},
1: {
0: 0.4,
1: 0.6
}
})
copy = model.copy()
self.assertIsInstance(copy, MC)
self.assertEqual(sorted(model.variables), sorted(copy.variables))
self.assertEqual(model.cardinalities, copy.cardinalities)
self.assertEqual(model.transition_models, copy.transition_models)
self.assertEqual(model.state, copy.state)
model.add_variable('p', 1)
model.set_start_state([State('a', 0), State('b', 1), State('p', 0)])
model.add_transition_model('p', {0: {0: 1}})
self.assertNotEqual(sorted(model.variables), sorted(copy.variables))
self.assertEqual(sorted(['a', 'b']), sorted(copy.variables))
self.assertNotEqual(model.cardinalities, copy.cardinalities)
self.assertEqual({'a': 2, 'b': 2}, copy.cardinalities)
self.assertNotEqual(model.state, copy.state)
self.assertEqual([State('a', 0), State('b', 1)], copy.state)
self.assertNotEqual(model.transition_models, copy.transition_models)
self.assertEqual(len(copy.transition_models), 2)
self.assertEqual(copy.transition_models['a'], {
0: {
0: 0.1,
1: 0.9
},
1: {
0: 0.2,
1: 0.8
}
})
self.assertEqual(copy.transition_models['b'], {
0: {
0: 0.3,
1: 0.7
},
1: {
0: 0.4,
1: 0.6
}
})
def test_transition_model_dict_to_matrix(self):
model = MC(['var'], [2])
transition_model = {0: {0: 0.3, 1: 0.7}, 1: {0: 0.5, 1: 0.5}}
transition_model_matrix = np.array([[0.3, 0.7], [0.5, 0.5]])
model.add_transition_model('var', transition_model_matrix)
self.assertDictEqual(model.transition_models['var'], transition_model)
def test_add_transition_model_success(self):
model = MC(['var'], [2])
transition_model = {0: {0: 0.3, 1: 0.7}, 1: {0: 0.5, 1: 0.5}}
model.add_transition_model('var', transition_model)
self.assertDictEqual(model.transition_models['var'], transition_model)