def test_is_true_for_root_node(self):
root_node = BayesNetNode("Cloudy")
root_node.set_probablity(0.9, [True])
self.assertTrue(root_node.is_true_for(0.4, {}))
self.assertFalse(root_node.is_true_for(0.99, {}))
def test_parents(self):
root1 = BayesNetNode("root1")
root2 = BayesNetNode("root2")
root3 = BayesNetNode("root3")
child = BayesNetNode("child")
child.influenced_by(root1)
child.influenced_by(root2)
child.influenced_by(root3)
self.assertSameElements([root1, root2, root3], child.parents)
def test_probability_of_root_variable(self):
bnn = BayesNetNode("var1")
bnn.set_probablity(0.3, [True])
false_result = bnn.probability_of({"var1": False})
expected_false_result = 0.7
self.assertAlmostEqual(expected_false_result, false_result, places=5)
true_result = bnn.probability_of({"var1": True})
expected_true_result = 0.3
self.assertAlmostEqual(expected_true_result, true_result, places=5)
def test_parents(self):
root1 = BayesNetNode("root1")
root2 = BayesNetNode("root2")
root3 = BayesNetNode("root3")
child = BayesNetNode("child")
child.influenced_by(root1)
child.influenced_by(root2)
child.influenced_by(root3)
self.assertSameElements([root1, root2, root3], child.parents)
def test_childs(self):
root_node = BayesNetNode("root")
child1 = BayesNetNode("child1")
child2 = BayesNetNode("child2")
child3 = BayesNetNode("child3")
child1.influenced_by(root_node)
child2.influenced_by(root_node)
child3.influenced_by(root_node)
self.assertSameElements([child1, child2, child3], root_node.children)
def test_get_variables_with_several_childs(self):
root_node = BayesNetNode("root")
child1 = BayesNetNode("child1")
child2 = BayesNetNode("child2")
child3 = BayesNetNode("child3")
child1.influenced_by(root_node)
child2.influenced_by(root_node)
child3.influenced_by(root_node)
bn = BayesNet([root_node])
vars = bn.get_variables()
self.assertSameElements(["root", "child1", "child2", "child3"], vars)
def test_is_true_for_root_node(self):
root_node = BayesNetNode("Cloudy")
root_node.set_probablity(0.9, [True])
self.assertTrue(root_node.is_true_for(0.4, {}))
self.assertFalse(root_node.is_true_for(0.99, {}))
def test_probability_of_root_variable(self):
bnn = BayesNetNode("var1")
bnn.set_probablity(0.3, [True])
false_result = bnn.probability_of({"var1": False})
expected_false_result = 0.7
self.assertAlmostEqual(expected_false_result, false_result, places=5)
true_result = bnn.probability_of({"var1": True})
expected_true_result = 0.3
self.assertAlmostEqual(expected_true_result, true_result, places=5)
def create_burglary_network():
burglary = BayesNetNode("Burglary")
earthQuake = BayesNetNode("EarthQuake")
alarm = BayesNetNode("Alarm")
johnCalls = BayesNetNode("JohnCalls")
maryCalls = BayesNetNode("MaryCalls")
alarm.influenced_by(burglary, earthQuake)
johnCalls.influenced_by(alarm)
maryCalls.influenced_by(alarm)
burglary.set_probablity(0.001, [True])
earthQuake.set_probablity(0.002, [True])
alarm.set_probablity(0.95, [True, True])
alarm.set_probablity(0.94, [True, False])
alarm.set_probablity(0.29, [False, True])
alarm.set_probablity(0.001, [False, False])
johnCalls.set_probablity(0.9, [True])
johnCalls.set_probablity(0.05, [False])
maryCalls.set_probablity(0.7, [True])
maryCalls.set_probablity(0.01, [False])
return BayesNet((burglary, earthQuake))
def _create_wet_grass_network(self):
cloudy_node = BayesNetNode("Cloudy")
sprinkler_node = BayesNetNode("Sprinkler")
rain_node = BayesNetNode("Rain")
wet_grass_node = BayesNetNode("WetGrass")
sprinkler_node.influenced_by(cloudy_node)
rain_node.influenced_by(cloudy_node)
wet_grass_node.influenced_by(rain_node, sprinkler_node)
cloudy_node.set_probablity(0.5, [True])
sprinkler_node.set_probablity(0.1, [True])
sprinkler_node.set_probablity(0.5, [False])
rain_node.set_probablity(0.8, [True])
rain_node.set_probablity(0.2, [False])
wet_grass_node.set_probablity(0.99, [True, True])
wet_grass_node.set_probablity(0.9, [True, False])
wet_grass_node.set_probablity(0.9, [False, True])
wet_grass_node.set_probablity(0, [False, False])
return BayesNet([cloudy_node])
def create_burglary_network():
burglary = BayesNetNode("Burglary")
earthQuake = BayesNetNode("EarthQuake")
alarm = BayesNetNode("Alarm")
johnCalls = BayesNetNode("JohnCalls")
maryCalls = BayesNetNode("MaryCalls")
alarm.influenced_by(burglary, earthQuake)
johnCalls.influenced_by(alarm)
maryCalls.influenced_by(alarm)
burglary.set_probablity(0.001, [True])
earthQuake.set_probablity(0.002, [True])
alarm.set_probablity(0.95, [True, True])
alarm.set_probablity(0.94, [True, False])
alarm.set_probablity(0.29, [False, True])
alarm.set_probablity(0.001, [False, False])
johnCalls.set_probablity(0.9, [True])
johnCalls.set_probablity(0.05, [False])
maryCalls.set_probablity(0.7, [True])
maryCalls.set_probablity(0.01, [False])
return BayesNet((burglary, earthQuake))
def test_is_true_for_not_root_node(self):
sprinkler_node = BayesNetNode("Sprinkler")
rain_node = BayesNetNode("Rain")
wet_grass_node = BayesNetNode("WetGrass")
wet_grass_node.influenced_by(sprinkler_node, rain_node)
wet_grass_node.set_probablity(0.99, [True, True])
wet_grass_node.set_probablity(0.90, [True, False])
wet_grass_node.set_probablity(0.90, [False, True])
wet_grass_node.set_probablity(0, [False, False])
self.assertTrue(wet_grass_node.is_true_for(0.5, {"Sprinkler" : True, "Rain" : True}))
self.assertFalse(wet_grass_node.is_true_for(0.99876, {"Sprinkler" : True, "Rain" : True}))
def test_get_root_variable(self):
root_node = BayesNetNode("root")
bn = BayesNet([root_node])
vars = bn.get_variables()
self.assertSameElements(["root"], vars)
def test_is_true_for_not_root_node(self):
sprinkler_node = BayesNetNode("Sprinkler")
rain_node = BayesNetNode("Rain")
wet_grass_node = BayesNetNode("WetGrass")
wet_grass_node.influenced_by(sprinkler_node, rain_node)
wet_grass_node.set_probablity(0.99, [True, True])
wet_grass_node.set_probablity(0.90, [True, False])
wet_grass_node.set_probablity(0.90, [False, True])
wet_grass_node.set_probablity(0, [False, False])
self.assertTrue(
wet_grass_node.is_true_for(0.5, {
"Sprinkler": True,
"Rain": True
}))
self.assertFalse(
wet_grass_node.is_true_for(0.99876, {
"Sprinkler": True,
"Rain": True
}))
def test_get_variables_with_several_roots(self):
root_node1 = BayesNetNode("root1")
root_node2 = BayesNetNode("root2")
child1 = BayesNetNode("child1")
child2 = BayesNetNode("child2")
child3 = BayesNetNode("child3")
child1.influenced_by(root_node1)
child2.influenced_by(root_node1, root_node2)
child3.influenced_by(root_node2)
bn = BayesNet([root_node1, root_node2])
vars = bn.get_variables()
self.assertSameElements(
["root1", "root2", "child1", "child2", "child3"], vars)
def test_childs(self):
root_node = BayesNetNode("root")
child1 = BayesNetNode("child1")
child2 = BayesNetNode("child2")
child3 = BayesNetNode("child3")
child1.influenced_by(root_node)
child2.influenced_by(root_node)
child3.influenced_by(root_node)
self.assertSameElements([child1, child2, child3], root_node.children)
def _create_wet_grass_network(self):
cloudy_node = BayesNetNode("Cloudy")
sprinkler_node = BayesNetNode("Sprinkler")
rain_node = BayesNetNode("Rain")
wet_grass_node = BayesNetNode("WetGrass")
sprinkler_node.influenced_by(cloudy_node)
rain_node.influenced_by(cloudy_node)
wet_grass_node.influenced_by(rain_node, sprinkler_node)
cloudy_node.set_probablity(0.5, [True])
sprinkler_node.set_probablity(0.1, [True])
sprinkler_node.set_probablity(0.5, [False])
rain_node.set_probablity(0.8, [True])
rain_node.set_probablity(0.2, [False])
wet_grass_node.set_probablity(0.99, [True, True])
wet_grass_node.set_probablity(0.9, [True, False])
wet_grass_node.set_probablity(0.9, [False, True])
wet_grass_node.set_probablity(0, [False, False])
return BayesNet([cloudy_node])
def test_probability_of_non_root_var(self):
root_bnn1 = BayesNetNode("root1")
root_bnn2 = BayesNetNode("root2")
root_bnn3 = BayesNetNode("root3")
dependent_bnn = BayesNetNode("dependentNode")
dependent_bnn.influenced_by(root_bnn1, root_bnn2, root_bnn3)
dependent_bnn.influenced_by(root_bnn1, root_bnn2, root_bnn3)
dependent_bnn.set_probablity(0.1, (True, True, True))
dependent_bnn.set_probablity(0.15, (True, False, True))
dependent_bnn.set_probablity(0.2, (True, True, False))
dependent_bnn.set_probablity(0.25, (False, True, True))
dependent_bnn.set_probablity(0.3, (False, False, True))
result = dependent_bnn.probability_of({"root1" : True})
expected_result = 0.1 + 0.15 + 0.2
self.assertAlmostEqual(expected_result, result, places=5)
def test_probability_of_non_root_var(self):
root_bnn1 = BayesNetNode("root1")
root_bnn2 = BayesNetNode("root2")
root_bnn3 = BayesNetNode("root3")
dependent_bnn = BayesNetNode("dependentNode")
dependent_bnn.influenced_by(root_bnn1, root_bnn2, root_bnn3)
dependent_bnn.influenced_by(root_bnn1, root_bnn2, root_bnn3)
dependent_bnn.set_probablity(0.1, (True, True, True))
dependent_bnn.set_probablity(0.15, (True, False, True))
dependent_bnn.set_probablity(0.2, (True, True, False))
dependent_bnn.set_probablity(0.25, (False, True, True))
dependent_bnn.set_probablity(0.3, (False, False, True))
result = dependent_bnn.probability_of({"root1": True})
expected_result = 0.1 + 0.15 + 0.2
self.assertAlmostEqual(expected_result, result, places=5)
