Omit nans in plotting functions, cast to numpy before plotting, fix axes indexing for 1D

[Matthijspals]

What does this implement/fix? Explain your changes

• gives a warning if NaNs or Infs are detected, removes the entryu
• tries to cast data to numpy arrays, if not already numpy (or torch)
• checks if data is 1D and we should not index matplotlib axes.

Does this close any currently open issues?

Fixes #1184 #1059

Any relevant code examples, logs, error output, etc?

Any other comments?

Checklist

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[codecov]

Codecov Report

Attention: Patch coverage is 72.00000% with 14 lines in your changes missing coverage. Please review.

Project coverage is 75.78%. Comparing base (6f61662) to head (e009fef).

❗ There is a different number of reports uploaded between BASE (6f61662) and HEAD (e009fef). Click for more details.

HEAD has 1 upload more than BASE

| Flag | BASE (6f61662) | HEAD (e009fef) | |------|------|------| |unittests|1|2|

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1185      +/-   ##
==========================================
- Coverage   82.13%   75.78%   -6.36%     
==========================================
  Files          93       93              
  Lines        7458     7476      +18     
==========================================
- Hits         6126     5666     -460     
- Misses       1332     1810     +478     

Flag	Coverage Δ
unittests	75.78% <72.00%> (-6.36%)	⬇️

Flags with carried forward coverage won't be shown. Click here to find out more.

Files	Coverage Δ
sbi/analysis/plot.py	66.15% <72.00%> (+24.36%)	⬆️

... and 23 files with indirect coverage changes

[manuelgloeckler]

Great work :) Thanks for fixing these issues. I found a few typos in the notebook.

You can also add the new notebook to the website/documentation i.e. add it (here)[https://github.com/sbi-dev/sbi/blob/main/docs/mkdocs.yml] to e.g. Analysis.

Additionally, CodeCov does complain that there are no unit tests. As this is purely for visualization (and was like this before), this is fine. But it might also be good to add a few simple tests to avoid errors like this in the future.

• Run plotting one 1d and nd, and assert if an error occurs.
• Run plotting on a list of samples, assert if error occurs
• Run plotting on nan and inf samples, assert if error occurs

[Matthijspals]

I added tests. Not sure about what counts as a slow test. on my Mac, pytest tests/plot_test.py take 14.18s

[manuelgloeckler]

Looks good. Great work.

Tests are sufficiently fast.

I tried to build the docs to check if the new notebook is rendered correctly on the website. But for some reason building the docs locally does not work anymore (i.e. building fails as mkdocs does not find any source). It does not work also on main, @janfb do you have any idea why?

[janfb]

Yes, please see this comment: #1147 (comment)

Please note that we should only build the website locally (mkdocs serve) and not deploy it yet, because we want the docs and API refs on the website to be in sync with the latest release (Dec 2023).