使用numpy提取每行的最小值 [英] Extracting minimum values per row using numpy

问题描述

我有一个问题，无法在互联网上或在此网站上找到答案.我相信这很容易.假设我有一组20个数字，并且它们以5x4矩阵的形式存在:

I have a question and I could not find the answer on the internet nor on this website. I am sure it is very easy though. Let's say I have a set of 20 numbers and I have them in a 5x4 matrix:

numbers = np.arange(20).reshape(5,4) 

这将产生以下矩阵:

[ 0,  1,  2,  3]
[ 4,  5,  6,  7]
[ 8,  9, 10, 11]
[12, 13, 14, 15]
[16, 17, 18, 19]

现在，我希望每行的最小值为0,4,8,12,16.但是，我想补充一点，对于我的问题，最小值并不总是在第一列中，它可以在矩阵中的任意位置(即每一行的第一，第二，第三或第四列).如果有人可以对此有所了解，将不胜感激.

Now I would like to have the minimum value of each row, in this case amounting to 0,4,8,12,16. However, I would like to add that for my problem the minimum value is NOT always in the first column, it can be at a random place in the matrix (i.e. first, second, third or fourth column for each row). If someone could shed some light on this it would be greatly appreciated.

推荐答案

您只需要指定要采用最小值的轴即可.要在每一行中找到最小值，您需要指定轴1:

You just need to specify the axis across which you want to take the minimum. To find the minimum value in each row, you need to specify axis 1:

>>> numbers.min(axis=1)
array([ 0,  4,  8, 12, 16])

对于2D数组，numbers.min()在数组中找到单个最小值，numbers.min(axis=0)返回每一列的最小值，numbers.min(axis=1)返回每一行的最小值.

For a 2D array, numbers.min() finds the single minimum value in the array, numbers.min(axis=0) returns the minimum value for each column and numbers.min(axis=1) returns the minimum value for each row.

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