将最小值替换为numpy数组中的另一个 [英] replace min value to another in numpy array

问题描述

让我们说我们有这个数组，我想用数字50代替最小值

Lets say we have this array and I want to replace the minimum value with number 50

import numpy as np
numbers = np.arange(20)
numbers[numbers.min()] = 50

所以输出是[50,1,2,3,....20]

但是现在我对此有疑问:

But now I have problems with this:

numbers = np.arange(20).reshape(5,4)
numbers[numbers.min(axis=1)]=50

获取[[50,1,2,3],[50,5,6,7],....]

但是我收到此错误:

IndexError:索引8超出了轴5的大小5 ....

IndexError: index 8 is out of bounds for axis 0 with size 5 ....

有什么帮助的想法吗?

推荐答案

您需要使用numpy.argmin而不是numpy.min:

In [89]: numbers = np.arange(20).reshape(5,4)

In [90]: numbers[np.arange(len(numbers)), numbers.argmin(axis=1)] = 50
In [91]: numbers
Out[91]: 
array([[50,  1,  2,  3],
       [50,  5,  6,  7],
       [50,  9, 10, 11],
       [50, 13, 14, 15],
       [50, 17, 18, 19]])

In [92]: numbers = np.arange(20).reshape(5,4)

In [93]: numbers[1,3] = -5 # Let's make sure that mins are not on same column

In [94]: numbers[np.arange(len(numbers)), numbers.argmin(axis=1)] = 50

In [95]: numbers
Out[95]: 
array([[50,  1,  2,  3],
       [ 4,  5,  6, 50],
       [50,  9, 10, 11],
       [50, 13, 14, 15],
       [50, 17, 18, 19]])

(我相信我的原始答案不正确，我混淆了行和列，这是正确的)

(I believe my original answer was incorrect, I confused rows and columns, and this is right)

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