Indexing [::-1] to Reverse ALL 2D Array Rows, ALL 3D, 4D Array Columns & Rows Python

[Jeremy7]

How do you get indexing [::-1] to reverse ALL 2D array rows and ALL 3D and 4D array columns and rows simultaneously? I can only get indexing [::-1] to reverse 2D array columns. Python

import numpy as np

randomArray = np.round(10*np.random.rand(5,4))
sortedArray = np.sort(randomArray,axis=1)
reversedArray = sortedArray[::-1]
# reversedArray = np.flip(sortedArray,axis=1)

print('Random Array:')
print(randomArray,'\n')
print('Sorted Array:')
print(sortedArray,'\n')
print('Reversed Array:')
print(reversedArray)

[DeaD_EyE]

You should try: https://numpy.org/doc/stable/reference/g...numpy-flip

[Gribouillis]

Not a numpy expert here, but this seems to reverse all the axis simultaneously

import numpy as np
 
random_array = np.round(10 * np.random.rand(5, 4, 4))
sorted_array = np.sort(random_array,axis=1)
 
a = sorted_array.reshape(sorted_array.size)
reversed_array = a[::-1].reshape(sorted_array.shape)

print('Sorted Array:')
print(sorted_array,'\n')
print('Reversed Array:')
print(reversed_array)

[Jeremy7]

You should try: https://numpy.org/doc/stable/reference/g...numpy-flip

Thanks for your help; I'm aware of numpy.flip(). numpy.flip() works great, but I wanted to only use the index. I got the following answers with some help from Stack Overflow and another source:
[:,::-1] reverses 2D array rows, [:,::-1,:] reverses 3D array columns, [:,:,::-1] reverses 3D array rows, [:,:,::-1,:] reverses 4D array columns, [:,:,:,::-1] reverses 4D array rows

[Jeremy7]

Not a numpy expert here, but this seems to reverse all the axis simultaneously

import numpy as np
 
random_array = np.round(10 * np.random.rand(5, 4, 4))
sorted_array = np.sort(random_array,axis=1)
 
a = sorted_array.reshape(sorted_array.size)
reversed_array = a[::-1].reshape(sorted_array.shape)

print('Sorted Array:')
print(sorted_array,'\n')
print('Reversed Array:')
print(reversed_array)

Thanks for your help. I got the following answers with some help from Stack Overflow and another source:
[:,::-1] reverses 2D array rows, [:,::-1,:] reverses 3D array columns, [:,:,::-1] reverses 3D array rows, [:,:,::-1,:] reverses 4D array columns, [:,:,:,::-1] reverses 4D array rows

Gribouillis, I see that you're a Moderator. When I view threads and posts, under my username, Jeremy7, are the words "Programmer named Tim," but my name is not Tim. Respectfully request "Programmer named Tim" be removed. Thanks!

[Gribouillis]

@Jeremy7 User titles are inserted automatically. They are references to Monty Python's Flying Circus which gave its name to the Python language.

[Jeremy7]

@Jeremy7 User titles are inserted automatically. They are references to Monty Python's Flying Circus which gave its name to the Python language.

Ok.

[nilamo]

Thanks for your help. I got the following answers with some help from Stack Overflow and another source:
[:,::-1] reverses 2D array rows, [:,::-1,:] reverses 3D array columns, [:,:,::-1] reverses 3D array rows, [:,:,::-1,:] reverses 4D array columns, [:,:,:,::-1] reverses 4D array rows

I think you can achieve what you're looking for by using raw slice objects.

>>> import numpy as np
>>> randomArray = np.round(10*np.random.rand(5,4))
>>> sortedArray = np.sort(randomArray, axis=1)
>>> sortedArray.shape
(5, 4)
>>> axes = len(sortedArray.shape)
>>> slices = tuple(slice(None, None, -1) for _ in range(axes))
>>> reversedArr = sortedArray[slices]
>>> sortedArray
array([[4., 6., 6., 7.],
       [3., 6., 7., 8.],
       [1., 8., 9., 9.],
       [7., 8., 8., 9.],
       [0., 6., 7., 8.]])
>>> reversedArr
array([[8., 7., 6., 0.],
       [9., 8., 8., 7.],
       [9., 9., 8., 1.],
       [8., 7., 6., 3.],
       [7., 6., 6., 4.]])

[Jeremy7]

Thanks for your help. I got the following answers with some help from Stack Overflow and another source:
[:,::-1] reverses 2D array rows, [:,::-1,:] reverses 3D array columns, [:,:,::-1] reverses 3D array rows, [:,:,::-1,:] reverses 4D array columns, [:,:,:,::-1] reverses 4D array rows

I think you can achieve what you're looking for by using raw slice objects.

>>> import numpy as np
>>> randomArray = np.round(10*np.random.rand(5,4))
>>> sortedArray = np.sort(randomArray, axis=1)
>>> sortedArray.shape
(5, 4)
>>> axes = len(sortedArray.shape)
>>> slices = tuple(slice(None, None, -1) for _ in range(axes))
>>> reversedArr = sortedArray[slices]
>>> sortedArray
array([[4., 6., 6., 7.],
       [3., 6., 7., 8.],
       [1., 8., 9., 9.],
       [7., 8., 8., 9.],
       [0., 6., 7., 8.]])
>>> reversedArr
array([[8., 7., 6., 0.],
       [9., 8., 8., 7.],
       [9., 9., 8., 1.],
       [8., 7., 6., 3.],
       [7., 6., 6., 4.]])

Thanks, nilamo!