numpy.argmax的使用

Question

I'm here to inquire about the use of numpy.argmax

For instance, consider this array:

import numpy as np

a = np.arange(6).reshape(2,3)
b = np.argmax(a, axis = 0)
c = np.argmax(a, axis = 1)

print(a)
print(b)
print(c)

Here's the output:

[[0 1 2]
 [3 4 5]]
5
[1 1 1]
[2 2]

I'm confused about the use of the parameter axis for numpy.argmax. What does it do? Why does it return [1 1 1] if axis = 0 and [2 2] if the value of axis = 1?

Answer 1

numpy.argmax() returns the position of the largest element in an array, optionally by row or column (the axis argument). So in the first case, [1 1 1] , you get the position of the largest element column-wise. Since the elements in row 1 are all larger that the elements in row 0, you get your array of three ones. Analogously for axis=1 , where you get the column of the largest element in each row.

Answer 2

argmax returns to you the index of the max value along the axis you specified.

The exact comparisons it did to get there:

3 > 0, 4 > 1, 5 > 2 : [1 1 1]

2 is the largest of set [0 1 2] 5 is the largest of set [3 4 5] :

[2 2]