Matshow/imshow changes layout in matplotlib >= 3.3

Description

I set up a subplots layout the way I need it for my figure and the subplots look good. But as soon as I start filling the axes with image-data using matshow or imshow, the layout is completely changed. It appears, the axes change their aspect ratio to one, resulting in large margins in the final plot.

Steps to reproduce

import proplot as plot
import numpy as np

f, axes = plot.subplots(nrows=2, ncols=5, aspect=4/3, wspace='3mm', hspace='3mm')
axes[0].matshow(np.random.randn(3,4))

Expected behavior: I expect to see a nicely aligned grid of axes with the given aspect ratio, the first axes should be completely filled with the random data, roughly like this (except for the missing data):

Actual behavior: The matshow command changes the layout:

Equivalent steps in matplotlib

Not sure whether this applies here, but with the matplotlib subplots, the layout is not changed after the first matshow.

import matplotlib.pyplot as plt
import numpy as np

f, axes = plt.subplots(2, 5, figsize=(4*5, 3*2))
axes[0, 0].matshow(np.random.randn(3,4))
f.subplots_adjust(hspace=0.1, wspace=0.1, left=0.02, right=0.98, top=0.98, bottom=0.02)

Proplot version

0.6.4

[matthias-k]

@lukelbd Thanks for fixing this! For the sake of completeness, git bisect is a git feature for efficiently finding the commit that introduced a certain bug. It can save a lot of time 😃. See https://git-scm.com/docs/git-bisect for a nice introduction

[lukelbd]

Eating my words – it was e7f76fa (I have no idea what git bisect is but evidently I should learn). In matplotlib 3.3+ they translate aspect='equal' to aspect=1 (these are synonyms since here “1” is in data units) but I confused matplotlib’s convention of data-units “aspect” with proplot’s convention of physical-units “aspect”. So this otherwise innocuous change caused the whole algorithm to fail.

Now fixed by: 124ea3f