numpy:将每行的max更改为1，将所有其他数字更改为0 [英] Numpy: change max in each row to 1, all other numbers to 0

问题描述

我正在尝试实现一个numpy函数，该函数将2D数组的每一行中的max替换为1，并将所有其他数字替换为零:

I'm trying to implement a numpy function that replaces the max in each row of a 2D array with 1, and all other numbers with zero:

>>> a = np.array([[0, 1],
...               [2, 3],
...               [4, 5],
...               [6, 7],
...               [9, 8]])
>>> b = some_function(a)
>>> b
[[0. 1.]
 [0. 1.]
 [0. 1.]
 [0. 1.]
 [1. 0.]]

到目前为止我尝试过的事情

def some_function(x):
    a = np.zeros(x.shape)
    a[:,np.argmax(x, axis=1)] = 1
    return a

>>> b = some_function(a)
>>> b
[[1. 1.]
 [1. 1.]
 [1. 1.]
 [1. 1.]
 [1. 1.]]

推荐答案

方法1，调整您的方法:

Method #1, tweaking yours:

>>> a = np.array([[0, 1], [2, 3], [4, 5], [6, 7], [9, 8]])
>>> b = np.zeros_like(a)
>>> b[np.arange(len(a)), a.argmax(1)] = 1
>>> b
array([[0, 1],
       [0, 1],
       [0, 1],
       [0, 1],
       [1, 0]])

[实际上，range可以正常工作；我出于习惯写了arange.

[Actually, range will work just fine; I wrote arange out of habit.]

方法2，使用max而不是argmax处理多个元素达到最大值的情况:

Method #2, using max instead of argmax to handle the case where multiple elements reach the maximum value:

>>> a = np.array([[0, 1], [2, 2], [4, 3]])
>>> (a == a.max(axis=1)[:,None]).astype(int)
array([[0, 1],
       [1, 1],
       [1, 0]])

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