👀 Views: 68 💬 Answers: 1 📅 Created: 2025-07-31

numpy reshape array-manipulation python

I can't seem to get I'm writing unit tests and I need some guidance on I'm relatively new to this, so bear with me... I'm working with an scenario when trying to reshape a 1D NumPy array into a 2D array. The array I'm working with is generated using `np.arange(12)`, resulting in a shape of (12,). When I attempt to reshape it into a 2D array with shape (3, 5), I expect it to throw an behavior because the total number of elements does not match. However, I am seeing unexpected behavior. Here's the code snippet I used: ```python import numpy as np a = np.arange(12) print('Original array shape:', a.shape) # Output: (12,) # Attempting to reshape to an incompatible dimension try: b = a.reshape(3, 5) print('Reshaped array:', b) except ValueError as e: print('behavior:', e) ``` When I run this code, I expect it to raise a `ValueError`, but instead, it throws a different behavior. In fact, the reshape operation is not throwing an behavior at all and I see the output as: ``` Reshaped array: [[ 0 1 2 3 4] [ 5 6 7 8 9] [10 11]] ``` The last row appears to be truncated, but I didn't anticipate this behavior. Why is this happening? Is there something wrong with how I'm trying to reshape the array? I would expect that reshaping should maintain the total number of elements. I double-checked the dimensions, and it seems correct, so I'm puzzled. I would appreciate any insights into how to properly handle this situation or if this behavior is expected with NumPy. I'm using NumPy version 1.21.0. I'm working on a web app that needs to handle this. I'd really appreciate any guidance on this. Thanks for any help you can provide! I'm working with Python in a Docker container on Linux. I'm open to any suggestions. I'm developing on Debian with Python. This is my first time working with Python 3.10. Cheers for any assistance! For reference, this is a production application. Cheers for any assistance!