Strange behavior when using np.where with a masked array in NumPy 1.24.0
I've been researching this but I'm trying to implement I'm attempting to set up I've been researching this but I've been struggling with this for a few days now and could really use some help. I've been struggling with this for a few days now and could really use some help. I'm working with an unexpected scenario when using `np.where` with a masked array in NumPy 1.24.0. When I attempt to apply `np.where` on a masked array, it seems to ignore the mask entirely, and I'm not sure why this is happening. For instance, I have the following code: ```python import numpy as np # Creating a masked array data = np.ma.array([1, 2, 3, 4, 5], mask=[0, 1, 0, 1, 0]) # Trying to use np.where on the masked array result = np.where(data > 2, data, -1) print(result) ``` I expected `result` to give me an array where the masked values are either replaced with `-1` or the original value if it meets the condition. However, the output is: ``` [ -1 -1 3 -1 5] ``` The masked values are still being processed, but they should not be evaluated since they are masked. This behavior seems counterintuitive because I thought `np.where` would respect the mask of the array. I've also tried calling `data.compressed()` before using `np.where`, but this leads to different behavior that isn't what I need for my application. Is there a recommended way to handle this situation or a workaround to ensure the mask is respected when using `np.where`? Is this a known behavior or a bug in version 1.24.0? Thanks for any insights you can provide! This is part of a larger service I'm building. I appreciate any insights! The stack includes Python and several other technologies. I'd love to hear your thoughts on this. My development environment is Linux. Am I missing something obvious?