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998 abc methods for trial based data using statistical distances#1104

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theogruner
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@theogrunertheogruner commentedMar 22, 2024•
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What does this implement/fix? Explain your changes

Adding an approximation of the squared 2-Wasserstein distance based on Sinkhorn iterations as an additional statistical distance to the available metrics. Furthermore, extending MCABC and SMCABC to allow conditioning on multiple observations using statistical distances.

Does this close any currently open issues?

Fixes#998

Checklist

  • I have read and understood thecontribution
    guidelines
  • I agree with re-licensing my contribution from AGPLv3 to Apache-2.0.
  • I have commented my code, particularly in hard-to-understand areas
  • I have added tests that prove my fix is effective or that my feature works
  • I have reported how long the new tests run and potentially marked them
    withpytest.mark.slow.
  • New and existing unit tests pass locally with my changes
  • I performed linting and formatting as described in thecontribution
    guidelines
  • I rebased onmain (or there are no conflicts withmain)

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Thanks a lot, this is great!
Added a couple of comments.

@theogrunertheogruner requested a review fromjanfbMarch 29, 2024 17:37
…hods-for-trial-based-data-using-statistical-distances
@theogrunertheogruner marked this pull request as ready for reviewApril 2, 2024 19:40
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Great, thanks for the edits!

I added some last comments, once those addressed, the PR can be merged 🎉

@janfbjanfb self-assigned thisApr 4, 2024
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Ping@theogruner 🙂 We are so close to merging here.

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janfb commentedApr 24, 2024•
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Ping@theogruner will you have time to finish this soon?
Please let me know if not, so that we can go ahead for the release - thanks 🙏

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codecovbot commentedMay 28, 2024•
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Codecov Report

Attention: Patch coverage is17.41935% with128 lines in your changes are missing coverage. Please review.

Project coverage is 72.94%. Comparing base(1b268b8) to head(ea43224).

Additional details and impacted files
@@             Coverage Diff             @@##             main    #1104       +/-   ##===========================================- Coverage   83.08%   72.94%   -10.14%===========================================  Files          92       93        +1       Lines        7259     7371      +112     ===========================================- Hits         6031     5377      -654- Misses       1228     1994      +766
FlagCoverage Δ
unittests72.94% <17.41%> (-10.14%)⬇️

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

FilesCoverage Δ
sbi/inference/abc/abc_base.py34.14% <66.66%> (-59.41%)⬇️
sbi/inference/abc/mcabc.py14.51% <0.00%> (-67.63%)⬇️
sbi/inference/abc/smcabc.py11.30% <4.76%> (-69.81%)⬇️
sbi/inference/abc/distances.py28.33% <28.33%> (ø)
sbi/utils/metrics.py38.98% <11.29%> (-17.12%)⬇️

... and19 files with indirect coverage changes

@theogruner
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Hi,
I'm really sorry for the huge delay in my response and for prolonging the release, especially given the minimal changes required.
I have now made the necessary updates and hope everything can be merged now :)
Best, Theo

@theogrunertheogruner requested a review fromjanfbMay 28, 2024 19:57
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Great, looks good now! Thanks a lot for adding these features 👏

@janfbjanfb changed the title998 improving abc methods for trial based data using statistical distances998 abc methods for trial based data using statistical distancesJun 3, 2024
@janfbjanfb merged commit7900af0 intomainJun 3, 2024
5 of 7 checks passed
@janfbjanfb deleted the 998-improving-abc-methods-for-trial-based-data-using-statistical-distances branchJune 3, 2024 13:49
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@janfbjanfbjanfb approved these changes

@gmoss13gmoss13Awaiting requested review from gmoss13

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Improving ABC methods for trial-based data using statistical distances
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