问题：
数列A为[1, 2, 3, 4, 5, 6, 7, 8, 9]，已知数列A的均值和方差和个数为mean_x，var_x，size_x
数列B为[20, 21, 22, 23, 24, 25, 26, 27, 28, 29]，已知数列B的均值和方差和个数为mean_y，var_y，size_y
现在将数列A与数列B拼合为数列Z，则数列Z为[ 1, 2, 3, 4, 5, 6, 7, 8, 9, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29]
现在要求数列Z的均值和方差
这里的重点是要快速求出数列Z的均值方差，或者可以换一种问法，那就是知道数列A的均值和方差和个数，也知道数列B的均值和方差和个数，但是不知道数列A和数列B的具体值，现在要求拼合后的数列Z的均值和方差。
给出代码：（代码地址：https://github.com/openai/baselines/blob/master/baselines/common/vec_env/vec_normalize.py
）
def update_mean_var_count_from_moments(mean, var, count, batch_mean, batch_var, batch_count):
delta = batch_mean - mean
tot_count = count + batch_count
new_mean = mean + delta * batch_count / tot_count
m_a = var * count
m_b = batch_var * batch_count
M2 = m_a + m_b + torch.pow(delta, 2).double() * count * batch_count / tot_count
new_var = M2 / tot_count
new_count = tot_count
return new_mean, new_var, new_count
注意，上面的mean，var，count为数列A的均值、方差、个数；batch_mean, batch_var, batch_count为数列B的均值、方差、个数；目标数列Z的均值、方差、个数为new_mean, new_var, new_count 。
具体验证：
标签：count,数列,方差,均值,batch,var,mean From： https://www.cnblogs.com/devilmaycry812839668/p/18032081