def test_GetProbability1(self):
discreteDistribution = DiscreteDistribution()
for i in range(1000):
discreteDistribution.addItem(i.__str__())
self.assertEqual(
0.001,
discreteDistribution.getProbability(randrange(1000).__str__()))
def setUp(self):
self.smallDistribution = DiscreteDistribution()
self.smallDistribution.addItem("item1")
self.smallDistribution.addItem("item2")
self.smallDistribution.addItem("item3")
self.smallDistribution.addItem("item1")
self.smallDistribution.addItem("item2")
self.smallDistribution.addItem("item1")
def test_AddDistribution2(self):
discreteDistribution1 = DiscreteDistribution()
for i in range(1000):
discreteDistribution1.addItem(i.__str__())
discreteDistribution2 = DiscreteDistribution()
for i in range(500, 1000):
discreteDistribution2.addItem((1000 + i).__str__())
discreteDistribution1.addDistribution(discreteDistribution2)
self.assertEqual(1500, len(discreteDistribution1))
def predict(self, instance: Instance) -> str:
"""
The predict method takes an Instance as an input and loops through the list of DecisionTrees.
Makes prediction for the items of that ArrayList and returns the maximum item of that ArrayList.
PARAMETERS
----------
instance : Instance
Instance to make prediction.
RETURNS
-------
str
The maximum prediction of a given Instance.
"""
distribution = DiscreteDistribution()
for tree in self.__forest:
distribution.addItem(tree.predict(instance))
return distribution.getMaxItem()
def test_AddItem3(self):
discreteDistribution = DiscreteDistribution()
for i in range(1000):
discreteDistribution.addItem(randrange(1000).__str__())
for i in range(1000000):
discreteDistribution.addItem(randrange(1000000).__str__())
self.assertAlmostEqual(len(discreteDistribution) / 1000000.0, 0.632, 3)
def test_AddItem2(self):
discreteDistribution = DiscreteDistribution()
for i in range(1000):
discreteDistribution.addItem(randrange(1000).__str__())
count = 0
for i in range(1000):
if discreteDistribution.containsItem(i.__str__()):
count += discreteDistribution.getCount(i.__str__())
self.assertEqual(1000, count)
def test_RemoveDistribution(self):
discreteDistribution = DiscreteDistribution()
discreteDistribution.addItem("item1")
discreteDistribution.addItem("item1")
discreteDistribution.addItem("item2")
self.smallDistribution.removeDistribution(discreteDistribution)
self.assertEqual(1, self.smallDistribution.getCount("item1"))
self.assertEqual(1, self.smallDistribution.getCount("item2"))
self.assertEqual(1, self.smallDistribution.getCount("item3"))
self.smallDistribution.addDistribution(discreteDistribution)
def test_GetProbabilityLaplaceSmoothing1(self):
discreteDistribution = DiscreteDistribution()
for i in range(1000):
discreteDistribution.addItem(i.__str__())
self.assertEqual(
2.0 / 2001,
discreteDistribution.getProbabilityLaplaceSmoothing(
randrange(1000).__str__()))
self.assertEqual(
1.0 / 2001,
discreteDistribution.getProbabilityLaplaceSmoothing("item0"))
def predictProbability(self, instance: Instance) -> dict:
distribution = DiscreteDistribution()
for tree in self.__forest:
distribution.addItem(tree.predict(instance))
return distribution.getProbabilityDistribution()
def test_GetSum2(self):
discreteDistribution = DiscreteDistribution()
for i in range(1000):
discreteDistribution.addItem(randrange(1000).__str__())
self.assertEqual(1000, discreteDistribution.getSum(), 0.0)
class DiscreteDistributionTest(unittest.TestCase):
def setUp(self):
self.smallDistribution = DiscreteDistribution()
self.smallDistribution.addItem("item1")
self.smallDistribution.addItem("item2")
self.smallDistribution.addItem("item3")
self.smallDistribution.addItem("item1")
self.smallDistribution.addItem("item2")
self.smallDistribution.addItem("item1")
def test_AddItem1(self):
self.assertEqual(3, self.smallDistribution.getCount("item1"))
self.assertEqual(2, self.smallDistribution.getCount("item2"))
self.assertEqual(1, self.smallDistribution.getCount("item3"))
def test_AddItem2(self):
discreteDistribution = DiscreteDistribution()
for i in range(1000):
discreteDistribution.addItem(randrange(1000).__str__())
count = 0
for i in range(1000):
if discreteDistribution.containsItem(i.__str__()):
count += discreteDistribution.getCount(i.__str__())
self.assertEqual(1000, count)
def test_AddItem3(self):
discreteDistribution = DiscreteDistribution()
for i in range(1000):
discreteDistribution.addItem(randrange(1000).__str__())
for i in range(1000000):
discreteDistribution.addItem(randrange(1000000).__str__())
self.assertAlmostEqual(len(discreteDistribution) / 1000000.0, 0.632, 3)
def test_RemoveItem(self):
self.smallDistribution.removeItem("item1")
self.smallDistribution.removeItem("item2")
self.smallDistribution.removeItem("item3")
self.assertEqual(2, self.smallDistribution.getCount("item1"))
self.assertEqual(1, self.smallDistribution.getCount("item2"))
self.smallDistribution.addItem("item1")
self.smallDistribution.addItem("item2")
self.smallDistribution.addItem("item3")
def test_AddDistribution1(self):
discreteDistribution = DiscreteDistribution()
discreteDistribution.addItem("item4")
discreteDistribution.addItem("item5")
discreteDistribution.addItem("item5")
discreteDistribution.addItem("item2")
self.smallDistribution.addDistribution(discreteDistribution)
self.assertEqual(3, self.smallDistribution.getCount("item1"))
self.assertEqual(3, self.smallDistribution.getCount("item2"))
self.assertEqual(1, self.smallDistribution.getCount("item3"))
self.assertEqual(1, self.smallDistribution.getCount("item4"))
self.assertEqual(2, self.smallDistribution.getCount("item5"))
self.smallDistribution.removeDistribution(discreteDistribution)
def test_AddDistribution2(self):
discreteDistribution1 = DiscreteDistribution()
for i in range(1000):
discreteDistribution1.addItem(i.__str__())
discreteDistribution2 = DiscreteDistribution()
for i in range(500, 1000):
discreteDistribution2.addItem((1000 + i).__str__())
discreteDistribution1.addDistribution(discreteDistribution2)
self.assertEqual(1500, len(discreteDistribution1))
def test_RemoveDistribution(self):
discreteDistribution = DiscreteDistribution()
discreteDistribution.addItem("item1")
discreteDistribution.addItem("item1")
discreteDistribution.addItem("item2")
self.smallDistribution.removeDistribution(discreteDistribution)
self.assertEqual(1, self.smallDistribution.getCount("item1"))
self.assertEqual(1, self.smallDistribution.getCount("item2"))
self.assertEqual(1, self.smallDistribution.getCount("item3"))
self.smallDistribution.addDistribution(discreteDistribution)
def test_GetSum1(self):
self.assertEqual(6, self.smallDistribution.getSum(), 0.0)
def test_GetSum2(self):
discreteDistribution = DiscreteDistribution()
for i in range(1000):
discreteDistribution.addItem(randrange(1000).__str__())
self.assertEqual(1000, discreteDistribution.getSum(), 0.0)
def test_GetIndex(self):
self.assertEqual(0, self.smallDistribution.getIndex("item1"))
self.assertEqual(1, self.smallDistribution.getIndex("item2"))
self.assertEqual(2, self.smallDistribution.getIndex("item3"))
def test_ContainsItem(self):
self.assertTrue(self.smallDistribution.containsItem("item1"))
self.assertFalse(self.smallDistribution.containsItem("item4"))
def test_GetItem(self):
self.assertEqual("item1", self.smallDistribution.getItem(0))
self.assertEqual("item2", self.smallDistribution.getItem(1))
self.assertEqual("item3", self.smallDistribution.getItem(2))
def test_GetValue(self):
self.assertEqual(3, self.smallDistribution.getValue(0))
self.assertEqual(2, self.smallDistribution.getValue(1))
self.assertEqual(1, self.smallDistribution.getValue(2))
def test_GetCount(self):
self.assertEqual(3, self.smallDistribution.getCount("item1"))
self.assertEqual(2, self.smallDistribution.getCount("item2"))
self.assertEqual(1, self.smallDistribution.getCount("item3"))
def test_GetMaxItem1(self):
self.assertEqual("item1", self.smallDistribution.getMaxItem())
def test_GetMaxItem2(self):
include = ["item2", "item3"]
self.assertEqual(
"item2",
self.smallDistribution.getMaxItemIncludeTheseOnly(include))
def test_GetProbability1(self):
discreteDistribution = DiscreteDistribution()
for i in range(1000):
discreteDistribution.addItem(i.__str__())
self.assertEqual(
0.001,
discreteDistribution.getProbability(randrange(1000).__str__()))
def test_GetProbability2(self):
self.assertEqual(0.5, self.smallDistribution.getProbability("item1"))
self.assertAlmostEqual(0.333333,
self.smallDistribution.getProbability("item2"),
4)
self.assertAlmostEqual(0.166667,
self.smallDistribution.getProbability("item3"),
4)
def test_GetProbabilityLaplaceSmoothing1(self):
discreteDistribution = DiscreteDistribution()
for i in range(1000):
discreteDistribution.addItem(i.__str__())
self.assertEqual(
2.0 / 2001,
discreteDistribution.getProbabilityLaplaceSmoothing(
randrange(1000).__str__()))
self.assertEqual(
1.0 / 2001,
discreteDistribution.getProbabilityLaplaceSmoothing("item0"))
def test_getProbabilityLaplaceSmoothing2(self):
self.assertEqual(
0.4,
self.smallDistribution.getProbabilityLaplaceSmoothing("item1"))
self.assertEqual(
0.3,
self.smallDistribution.getProbabilityLaplaceSmoothing("item2"))
self.assertEqual(
0.2,
self.smallDistribution.getProbabilityLaplaceSmoothing("item3"))
self.assertEqual(
0.1,
self.smallDistribution.getProbabilityLaplaceSmoothing("item4"))
def test_Entropy(self):
self.assertAlmostEqual(1.4591, self.smallDistribution.entropy(), 4)
