Find the maximum value of numpy array and its indexing method in python

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In the list list, max(list) can get the maximum value of the list, and list.index(max(list)) can get the index corresponding to the maximum value

But There is no index method for array in numpy. Instead, it is where, which is not found in list.

First of all, we can get the maximum value of the array globally and in each row and column (the same is true for the minimum value)

>>> a = np.arange(9).reshape((3,3))
>>> a
array([[0, 1, 2],
  [9, 4, 5],
  [6, 7, 8]])
>>> print(np.max(a))  #全局最大
8
>>> print(np.max(a,axis=0)) #每列最大
[6 7 8]
>>> print(np.max(a,axis=1)) #每行最大
[2 5 8]

Then use where to get the index of the maximum value. In the return value, the former array corresponds to the number of rows, and the latter corresponds to the number of columns

>>> print(np.where(a==np.max(a)))
(array([2], dtype=int64), array([2], dtype=int64))
>>> print(np.where(a==np.max(a,axis=0)))
(array([2, 2, 2], dtype=int64), array([0, 1, 2], dtype=int64))

If there are the same maximum values ​​in the array, where will give all their positions

>>> a[1,0]=8
>>> a
array([[0, 1, 2],
  [8, 4, 5],
  [6, 7, 8]])
>>> print(np.where(a==np.max(a)))
(array([1, 2], dtype=int64), array([0, 2], dtype=int64))

Related recommendations:

How to get the specified row and column of numpy array

How to use numpy to find the maximum and minimum value in the array

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