Optimize the calculation speed and logic of InterRDF_s to ensure that the results are consistent with InterRDF

[gitzhangch]

Refactored bin index calculation in the _single_frame function of InterRDF_s to optimize redundant np.histogram calls. Additionally, divided by N in _conclude to make the computation consistent with InterRDF.

Fixes #5067

Changes made in this Pull Request:

• Refactored bin index calculation in InterRDF_s._single_frame to avoid multiple redundant np.histogram calls, improving performance.
• Updated _conclude to divide by N, ensuring consistency with InterRDF.

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• Tests updated/added?
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• package/CHANGELOG file updated?
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📚 Documentation preview 📚: https://mdanalysis--5073.org.readthedocs.build/en/5073/

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[orbeckst]

Thank you for the contribution! With any code rewrite for performance, the first thing is to make sure that the existing tests still pass. Have a look at the test output (you can run the tests locally, too) and modify your code so that it produces the same results as before.

If you have any reason to belief that the new code produces correct output while the old code is incorrect, please start a discussion.

[codecov]

Codecov Report

Attention: Patch coverage is 83.33333% with 1 line in your changes missing coverage. Please review.

Project coverage is 93.83%. Comparing base (b113fd5) to head (fa271c2).
Report is 4 commits behind head on develop.

Files with missing lines	Patch %	Lines
package/MDAnalysis/analysis/rdf.py	83.33%	0 Missing and 1 partial ⚠️

Additional details and impacted files

@@             Coverage Diff             @@
##           develop    #5073      +/-   ##
===========================================
+ Coverage    93.62%   93.83%   +0.20%     
===========================================
  Files          177      177              
  Lines        22001    22005       +4     
  Branches      3114     3115       +1     
===========================================
+ Hits         20599    20648      +49     
+ Misses         947      901      -46     
- Partials       455      456       +1     

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[gitzhangch]

@orbeckst
During my work with MDAnalysis.analysis.rdf.InterRDF_s, I noticed that processing Gromacs trajectories was much slower compared to InterRDF. Upon investigation, I found that the _single_frame method was repeatedly calling np.histogram inside a loop, causing significant slowdowns. Additionally, after running rdf_calc.run(), plotting with plt.plot(rdf.results.bins, rdf.results.rdf[0][0, 0]) showed that rdf.results.rdf[0][0, 0] was mostly zeros, indicating issues with the calculation logic. I also observed that _conclude did not normalize the arrays as in InterRDF (i.e., dividing by N = nA * nB), and that the distances.capped_distance call in _single_frame lacked the min_cutoff parameter, making it inconsistent with the range setting.

Commits and testing:

• First commit:

  1. Removed repeated np.histogram calls to improve speed
  2. Modified self.results.count[i][0, 0] to fix RDF accuracy
  3. Updated _conclude to normalize by N
  4. Set min_cutoff in distances.capped_distance
     However, these changes caused many test failures.

• Second commit:
  Removed changes 2 and 3. Most tests passed, but two still failed.

• Third commit:
  Reverted change 4. Now, almost all tests pass except for a Codecov/coverage warning.

I don't use tests very often, so I've briefly described the test situation here. I hope to discuss with you how to make reasonable modifications further.