Python/NumPy中用于计算均值的元素排列 [英] Elements Arrangement For Calculating Mean In Python/NumPy

问题描述

我的一维列表如下:

data = [1,5,9,13,
        2,6,10,14,
        3,7,11,15,
        4,8,12,16]

我要列出以下元组，并分别计算每个元组的平均值.

I want to make the following list of tuples, and calculate mean of each tuple separately.

[(1,5,2,6), (3,7,4,8), (9,13,10,14), (11,15,12,16)]

预期结果应该是:

[3.5, 5.5, 11.5, 13.5]

最简单的方法是什么?

推荐答案

将数据放入形状为(2，2，2，2，2)的4-d numpy数组中，然后取该数组在轴1和轴上的均值3:

Put the data into a 4-d numpy array with shape (2, 2, 2, 2), then take the mean of that array over axes 1 and 3:

In [25]: data
Out[25]: [1, 5, 9, 13, 2, 6, 10, 14, 3, 7, 11, 15, 4, 8, 12, 16]

In [26]: a = np.array(data).reshape(2, 2, 2, 2)

In [27]: a
Out[27]: 
array([[[[ 1,  5],
         [ 9, 13]],

        [[ 2,  6],
         [10, 14]]],


       [[[ 3,  7],
         [11, 15]],

        [[ 4,  8],
         [12, 16]]]])

In [28]: a.mean(axis=(1, 3))
Out[28]: 
array([[  3.5,  11.5],
       [  5.5,  13.5]])

如果需要最终结果作为一维数组，则可以使用ravel()方法:

You can use the ravel() method if you need the final result as a 1-d array:

In [31]: a.mean(axis=(1, 3)).ravel()
Out[31]: array([  3.5,  11.5,   5.5,  13.5])

请参见如何我可以向量化numpy数组的2x2子数组的平均值吗?有一个类似的问题.

See How can I vectorize the averaging of 2x2 sub-arrays of numpy array? for a similar question.

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