[sophiamaedler]

Closes #1279.

_get_joined_table_indices and _get_masked_element use NumPy isin to match table instance IDs against spatial element indices. For object or string IDs, this can trigger repeated element-wise comparisons and make bounding_box_query substantially slower. This PR uses Pandas Series.isin() in both helpers while preserving the existing join behavior.

Benchmark

Using the benchmark script and the public Xenium breast cancer dataset linked in the issue, I ran ten crops per ID type on main and this PR branch. The dataset has 167,780 cells; each crop retained 199 cells. For the string-ID case, the sample’s numeric IDs were cast to strings in memory.

Cell ID type	main median	PR median	Change
Numeric	0.0082 s	0.0096 s	Comparable in absolute time
String	0.4126 s	0.0141 s	29× faster

The benchmark script is attached to issue #1279.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 91.42%. Comparing base (9ffe082) to head (e67602a).

Additional details and impacted files

@@           Coverage Diff           @@
##             main    #1280   +/-   ##
=======================================
  Coverage   91.42%   91.42%           
=======================================
  Files          53       53           
  Lines        8381     8381           
=======================================
  Hits         7662     7662           
  Misses        719      719           

Files with missing lines	Coverage Δ
src/spatialdata/_core/query/relational_query.py	93.34% <100.00%> (ø)

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