np.meshgrid not producing expected grid shape when using non-integer steps
I've spent hours debugging this and Can someone help me understand I'm using NumPy version 1.21.0, and I'm trying to create a meshgrid from two arrays that contain non-integer values....... My intention is to generate a grid of points for evaluating a function, but I'm finding that the shapes of the output arrays from `np.meshgrid` are not what I expected. Here’s what I'm doing: ```python import numpy as np x = np.arange(0, 1, 0.1) y = np.arange(0, 2, 0.25) X, Y = np.meshgrid(x, y) print(X.shape, Y.shape) ``` I expected `X` to have a shape of `(8, 10)` and `Y` to have the same shape, resulting in a grid of 80 points. However, when I run this code, I get the following output: ``` (8, 10) (8, 10) ``` Both arrays seem to have the correct shape, but the values inside them don’t match how I anticipated the grid should look. The values in `Y` appear to repeat along the rows, which makes sense, but I thought the spacing would be uniform across the grid based on the step sizes I provided. After trying various combinations of input arrays, it seems the issue arises from how `np.arange` handles the step sizes. I've also tried using `np.linspace`, but I still encounter unexpected behavior: ```python x = np.linspace(0, 1, num=10) y = np.linspace(0, 2, num=8) X, Y = np.meshgrid(x, y) ``` Both methods leave me scratching my head about the underlying mechanics of `np.meshgrid`. Can anyone clarify how to properly set up the meshgrid for non-integer values, and what the best practices are for ensuring I'm getting the expected output? I would greatly appreciate any insights or examples that might help clarify this issue. My team is using Python for this web app. Is there a simpler solution I'm overlooking? The stack includes Python and several other technologies. What am I doing wrong? I'm coming from a different tech stack and learning Python. Is there a simpler solution I'm overlooking?