def test_fast_mean_iterated_with_values(self):
# Arrange
values1 = np.asarray([0.0, 1.1, 2.2], dtype=np.float64)
values2 = np.asarray([0.0, 1.1, 2.2, 3.3, 4.4], dtype=np.float64)
# Act
result1 = fast_mean_iterated(values1, 0.0, fast_mean(values1), 5)
result2 = fast_mean_iterated(values2, 5.5, np.mean(values2), 5)
# Assert
assert result1 == np.mean([0.0, 1.1, 2.2])
assert result2 == 3.3000000000000003
def test_fast_mean_iterated_with_values(self):
# Arrange
values1 = [0.0, 1.1, 2.2]
values2 = [0.0, 1.1, 2.2, 3.3, 4.4]
# Act
result1 = fast_mean_iterated(values1, 0.0, fast_mean(values1), 5)
result2 = fast_mean_iterated(values2, 5.5, np.mean(values2), 5)
# Assert
self.assertEqual(np.mean([0.0, 1.1, 2.2]), result1)
self.assertAlmostEqual(3.3, result2)
def test_fast_mean_iterated_with_values(self):
# Arrange
values1 = [0.0, 1.1, 2.2]
values2 = [0.0, 1.1, 2.2, 3.3, 4.4]
# Act
result1 = fast_mean_iterated(values1, 0.0, fast_mean(values1), 5)
result2 = fast_mean_iterated(values2, 5.5, np.mean(values2), 5)
# Assert
assert np.mean([0.0, 1.1, 2.2]) == result1
assert 3.3000000000000003 == result2
def test_fast_mean_iterated_with_empty_list_returns_zero(self):
# Arrange
values = np.asarray([], dtype=np.float64)
# Act
result = fast_mean_iterated(values, 0.0, 0.0, 6)
# Assert
assert result == 0
def test_fast_mean_iterated_with_empty_list_returns_zero(self):
# Arrange
values = []
# Act
result = fast_mean_iterated(values, 0.0, 0.0, 6)
# Assert
self.assertEqual(0, result)