def test_simple_distinguish_table(self):
input_matrix = np.array([[1, 2, 3], [4, 5, 6]])
res = DistinguishTable.compute_distinguish_matrix(input_matrix)
frequency_of_attributes = (
DistinguishTable.compute_frequency_of_attribute(res))
expected_output = [[set(), {0, 1}], [{0, 1}, set()]]
self.assertEqual(frequency_of_attributes, ([(0.0, 2), (1.0, 2)]))
self.assertEqual(res, expected_output)
def test_two_objects(self):
input_data = np.array([[0, 1, 0, 1], [1, 1, 0, 0]])
expected_output = [[set(), {0}], [{0}, set()]]
actual_output = DistinguishTable.compute_distinguish_matrix(input_data)
frequency_of_attribute = (
DistinguishTable.compute_frequency_of_attribute(actual_output))
self.assertEqual(actual_output, expected_output)
self.assertEqual(frequency_of_attribute, ([(0, 2)]))
def test_simple_distinguish_table(self):
input_matrix = np.array([[1, 2, 3], [4, 5, 6]])
res = DistinguishTable.compute_distinguish_matrix(input_matrix)
frequency_of_attributes = (
DistinguishTable.compute_frequency_of_attribute(res))
expected_output = [[set(), {0, 1}], [{0, 1}, set()]]
self.assertEqual(frequency_of_attributes, ([(0.0, 2), (1.0, 2)]))
self.assertEqual(res, expected_output)
def test_two_objects(self):
input_data = np.array([[0, 1, 0, 1], [1, 1, 0, 0]])
expected_output = [[set(), {0}], [{0}, set()]]
actual_output = DistinguishTable.compute_distinguish_matrix(input_data)
frequency_of_attribute = (
DistinguishTable.compute_frequency_of_attribute(actual_output))
self.assertEqual(actual_output,
expected_output)
self.assertEqual(frequency_of_attribute, ([(0, 2)]))
def test_all_object_with_the_same_decision(self):
input_data = np.array([[1, 0, 1, 2, 1], [1, 1, 1, 1, 1],
[0, 0, 0, 0, 1], [9, 9, 9, 2, 1]])
actual_output = DistinguishTable.compute_distinguish_matrix(input_data)
frequency_of_attributes = (
DistinguishTable.compute_frequency_of_attribute(actual_output))
expected_output = [[set() for _ in range(4)] for _ in range(4)]
self.assertEqual(frequency_of_attributes, [])
self.assertEqual(actual_output, expected_output)
def test_all_object_with_the_same_decision(self):
input_data = np.array([[1, 0, 1, 2, 1], [1, 1, 1, 1, 1],
[0, 0, 0, 0, 1], [9, 9, 9, 2, 1]])
actual_output = DistinguishTable.compute_distinguish_matrix(input_data)
frequency_of_attributes = (
DistinguishTable.compute_frequency_of_attribute(actual_output))
expected_output = [[set() for _ in range(4)] for _ in range(4)]
self.assertEqual(frequency_of_attributes, [])
self.assertEqual(actual_output, expected_output)
def test_four_objects(self):
input_data = np.array([[1, 1, 0, 1, 1], [0, 1, 0, 1, 0],
[1, 1, 1, 0, 1], [1, 0, 0, 1, 0]])
actual_output = DistinguishTable.compute_distinguish_matrix(input_data)
frequency_of_attributes = (
DistinguishTable.compute_frequency_of_attribute(actual_output))
expected_output = [[set() for _ in range(4)] for _ in range(4)]
expected_output[0][1] = {0}
expected_output[1][0] = {0}
expected_output[0][3] = {1}
expected_output[3][0] = {1}
expected_output[1][2] = {0, 2, 3}
expected_output[2][1] = {0, 2, 3}
expected_output[2][3] = {1, 2, 3}
expected_output[3][2] = {1, 2, 3}
self.assertEqual(frequency_of_attributes, ([(0.0, 4), (1.0, 4),
(2.0, 4), (3.0, 4)]))
self.assertEqual(expected_output, actual_output)
def test_four_objects(self):
input_data = np.array([[1, 1, 0, 1, 1], [0, 1, 0, 1, 0],
[1, 1, 1, 0, 1], [1, 0, 0, 1, 0]])
actual_output = DistinguishTable.compute_distinguish_matrix(input_data)
frequency_of_attributes = (
DistinguishTable.compute_frequency_of_attribute(actual_output))
expected_output = [[set() for _ in range(4)] for _ in range(4)]
expected_output[0][1] = {0}
expected_output[1][0] = {0}
expected_output[0][3] = {1}
expected_output[3][0] = {1}
expected_output[1][2] = {0, 2, 3}
expected_output[2][1] = {0, 2, 3}
expected_output[2][3] = {1, 2, 3}
expected_output[3][2] = {1, 2, 3}
self.assertEqual(frequency_of_attributes,
([(0.0, 4), (1.0, 4), (2.0, 4), (3.0, 4)]))
self.assertEqual(expected_output, actual_output)
def test_empty_decision_table(self):
input_data = np.array([])
with self.assertRaises(ValueError):
DistinguishTable.compute_distinguish_matrix(input_data)
def test_empty_decision_table(self):
input_data = np.array([])
with self.assertRaises(ValueError):
DistinguishTable.compute_distinguish_matrix(input_data)
