advanced patterns with np.meshgrid when using indexing with multi-dimensional arrays in NumPy 1.25
I'm getting frustrated with I'm working with an scenario with `np.meshgrid` in NumPy 1.25 when using it in conjunction with indexing multi-dimensional arrays. I expected to generate coordinate matrices from my input arrays but I'm getting unexpected results when I try to index into the output arrays. Here's a simplified version of what I'm trying to achieve: ```python import numpy as np x = np.array([0, 1, 2]) y = np.array([10, 20]) X, Y = np.meshgrid(x, y) print("X:", X) print("Y:", Y) # Attempting to index into the coordinate matrices index = (1, 0) print("Value at index (1, 0):", X[index], Y[index]) ``` I expected the output for `X[index]` to be `1` and for `Y[index]` to be `10`, but instead, I'm receiving `1` and `20`. It seems that the indexing is not working as I assumed it would. I tried using `X[1, 0]` and `Y[1, 0]` instead, which returned the expected results, but this behavior with tuple indexing is confusing. Is there a reason why using a tuple for indexing like `X[index]` returns unexpected results? Is this a known behavior with NumPy's array indexing that I need to consider? I've also checked the documentation but couldn't find anything that directly addresses this. Any insights would be appreciated! I recently upgraded to Python 3.11. Any ideas what could be causing this? What am I doing wrong? The stack includes Python and several other technologies. Am I approaching this the right way? I'm coming from a different tech stack and learning Python.