advanced patterns with np.roll on multi-dimensional arrays in NumPy 1.23.5
I've tried everything I can think of but I need some guidance on I'm trying to figure out Can someone help me understand I've encountered an unexpected behavior while using `np.roll` on a multi-dimensional NumPy array in version 1.23.5..... I am trying to roll a 2D array along a specific axis, but the results are not what I anticipated. Here's the code snippet I'm using: ```python import numpy as np array_2d = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) rolled_array = np.roll(array_2d, shift=1, axis=0) print(rolled_array) ``` I expected the output to be: ``` [[ 7, 8, 9], [ 1, 2, 3], [ 4, 5, 6]] ``` However, I am getting: ``` [[ 4, 5, 6], [ 7, 8, 9], [ 1, 2, 3]] ``` It seems like the `np.roll` function is not rolling the array correctly along the specified axis. I've also tried using `axis=1`, and it works as expected, but I'm specifically interested in rolling along the first axis. I've double-checked the version of NumPy I'm using and confirmed it's indeed 1.23.5. I looked through the documentation and saw that the `shift` parameter should indeed work for multi-dimensional arrays. I also tried reshaping the array and using different `shift` values, but the results remain inconsistent. Can anyone guide to understand why this behavior is occurring and how I can achieve the expected result? Any ideas how to fix this? This is part of a larger desktop app I'm building. My team is using Python for this CLI tool. What am I doing wrong?