self.assertRaises(ValueError, random.gammavariate, 2, 0)
self.assertRaises(ValueError, random.gammavariate, 1, -3)
+ # There are three different possibilities in the current implementation
+ # of random.gammavariate(), depending on the value of 'alpha'. What we
+ # are going to do here is to fix the values returned by random() to
+ # generate test cases that provide 100% line coverage of the method.
@unittest.mock.patch('random.Random.random')
- def test_gammavariate_full_code_coverage(self, random_mock):
- # There are three different possibilities in the current implementation
- # of random.gammavariate(), depending on the value of 'alpha'. What we
- # are going to do here is to fix the values returned by random() to
- # generate test cases that provide 100% line coverage of the method.
+ def test_gammavariate_alpha_greater_one(self, random_mock):
- # #1: alpha > 1.0: we want the first random number to be outside the
+ # #1: alpha > 1.0.
+ # We want the first random number to be outside the
# [1e-7, .9999999] range, so that the continue statement executes
# once. The values of u1 and u2 will be 0.5 and 0.3, respectively.
random_mock.side_effect = [1e-8, 0.5, 0.3]
returned_value = random.gammavariate(1.1, 2.3)
self.assertAlmostEqual(returned_value, 2.53)
- # #2: alpha == 1: first random number less than 1e-7 to that the body
- # of the while loop executes once. Then random.random() returns 0.45,
+ @unittest.mock.patch('random.Random.random')
+ def test_gammavariate_alpha_equal_one(self, random_mock):
+
+ # #2.a: alpha == 1.
+ # The execution body of the while loop executes once.
+ # Then random.random() returns 0.45,
# which causes while to stop looping and the algorithm to terminate.
- random_mock.side_effect = [1e-8, 0.45]
+ random_mock.side_effect = [0.45]
returned_value = random.gammavariate(1.0, 3.14)
- self.assertAlmostEqual(returned_value, 2.507314166123803)
+ self.assertAlmostEqual(returned_value, 1.877208182372648)
+
+ @unittest.mock.patch('random.Random.random')
+ def test_gammavariate_alpha_equal_one_equals_expovariate(self, random_mock):
+
+ # #2.b: alpha == 1.
+ # It must be equivalent of calling expovariate(1.0 / beta).
+ beta = 3.14
+ random_mock.side_effect = [1e-8, 1e-8]
+ gammavariate_returned_value = random.gammavariate(1.0, beta)
+ expovariate_returned_value = random.expovariate(1.0 / beta)
+ self.assertAlmostEqual(gammavariate_returned_value, expovariate_returned_value)
+
+ @unittest.mock.patch('random.Random.random')
+ def test_gammavariate_alpha_between_zero_and_one(self, random_mock):
- # #3: 0 < alpha < 1. This is the most complex region of code to cover,
+ # #3: 0 < alpha < 1.
+ # This is the most complex region of code to cover,
# as there are multiple if-else statements. Let's take a look at the
# source code, and determine the values that we need accordingly:
#