Plots generated from `.plot` methods look odd in jupyter notebooks and regular matplotlib

Start by reproducing the documented SpectrogramCube.plot() example in JupyterLab and IPython with the listed dependency versions. Trace the .plot() entry point and determine why plot elements overlap and widgets fail; done means the generated plots render correctly in both environments.

Describe the bug

When I run the plotting examples from the documentation, e.g. from here, in jupyter lab the generated plots have multiple overlapping elements, including widgets that don't work.

EDIT: The plots look about the same in matplotlib run from ipython. Screenshot added.

To Reproduce

This code is from https://docs.sunpy.org/projects/sunraster/en/latest/data_types/spectrogram.html#plotting:

import numpy as np
data = np.ones((3, 4, 5))
import astropy.wcs
wcs_input_dict = {
    'CTYPE1': 'WAVE    ', 'CUNIT1': 'Angstrom', 'CDELT1': 0.2, 'CRPIX1': 0, 'CRVAL1': 10, 'NAXIS1': 5,
    'CTYPE2': 'HPLT-TAN', 'CUNIT2': 'deg', 'CDELT2': 0.5, 'CRPIX2': 2, 'CRVAL2': 0.5, 'NAXIS2': 4,
    'CTYPE3': 'HPLN-TAN', 'CUNIT3': 'deg', 'CDELT3': 0.4, 'CRPIX3': 2, 'CRVAL3': 1, 'NAXIS3': 3}
input_wcs = astropy.wcs.WCS(wcs_input_dict)

from sunraster import SpectrogramCube
my_spectrograms = SpectrogramCube(data, input_wcs)

import astropy.units as u
from astropy.nddata import StdDevUncertainty

uncertainties = StdDevUncertainty(np.sqrt(data))
# Create a mask where all pixels are unmasked, i.e. all mask values are False.
mask = np.zeros_like(data, dtype=bool)
my_spectrograms = SpectrogramCube(data, input_wcs, uncertainty=uncertainties, mask=mask)

my_spectrograms.plot() 

See next section for screenshot.

Screenshots

In Jupyter Lab notebook

In matplotlib MacOSX backend from ipython

System Details

sunpy Installation Information

General

OS: Mac OS 13.3.1
Arch: 64bit, (arm)
sunpy: 4.1.6
Installation path: /Users/mattcraig/mambaforge/envs/sunraster-dev/lib/python3.11/site-packages/sunpy-4.1.6.dist-info
python: 3.11.3

Required Dependencies

astropy: 5.2.2
numpy: 1.24.3
packaging: 23.1
parfive: 2.0.2

Optional Dependencies

asdf: 2.15.0
asdf-astropy: 0.4.0
beautifulsoup4: 4.12.2
cdflib: Missing cdflib!=0.4.0,>=0.3.19; extra == "timeseries"
dask: Missing dask[array]>=2.0.0; extra == "dask"
drms: Missing drms>=0.6.1; extra == "net"
glymur: Missing glymur!=0.9.0,!=0.9.5,>=0.8.18; extra == "jpeg2000"
h5netcdf: Missing h5netcdf>=0.8.1; extra == "timeseries"
h5py: Missing h5py>=3.1.0; extra == "timeseries"
lxml: Missing lxml>=4.8.0; extra == "jpeg2000"
matplotlib: 3.7.1
mpl-animators: 1.1.0
pandas: Missing pandas>=1.0.0; extra == "timeseries"
python-dateutil: 2.8.2
reproject: Missing reproject; extra == "docs" or "map"
scikit-image: Missing scikit-image>=0.16.0; extra == "image"
scipy: 1.10.1
sqlalchemy: Missing sqlalchemy>=1.3.4; extra == "database"
tqdm: 4.65.0
zeep: Missing zeep>=3.4.0; extra == "net"

Other

ndcube: 2.1.1

Installation method

git checkout