def test_cv_update_batch():
cv1 = ContinuousValue()
cv2 = ContinuousValue()
nums = [random() for i in range(10)]
for n in nums:
cv1.update(n)
cv2.update_batch(nums)
assert cv1.unbiased_mean() == cv2.unbiased_mean()
assert cv1.biased_std() == cv2.biased_std()
def test_cv_combine():
cv1 = ContinuousValue()
with pytest.raises(ValueError):
cv1.combine(3)
cv2 = ContinuousValue()
cv3 = ContinuousValue()
nums = [normalvariate(0, 1) for _ in range(1000)]
cv1.update_batch(nums[:500])
cv2.update_batch(nums[500:])
cv3.update_batch(nums)
cv1.combine(cv2)
assert cv1.num == cv3.num
assert abs(cv1.mean - cv3.mean) <= 1e-6
assert abs(cv1.meanSq - cv3.meanSq) <= 1e-6