25752045982
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Ran 12 May 2026 05:49PM UTC

Jobs 4

Files 25

Run time 1min

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Committed 12 May 2026 05:48PM UTC coverage: 70.838% (+0.06%) from 70.775%

Build # 25752045982

Build Type

push

github

Committed by

web-flow

Commit Message

Batch marker densification in _extract_tcell_markers (#35 finding #2) (#36)

* Batch marker densification in _extract_tcell_markers (closes #35 finding #2)

Replaces the per-marker `adata[:, col].X.toarray().flatten()` loop with
a single column slice that densifies all present markers at once. One
anndata view creation and one sparse-to-dense conversion instead of N.

For TCELL_MARKERS (6 markers), peak memory is unchanged — the dense
values land in the same DataFrame either way. The win is in:

  - Avoiding 6 anndata-view objects per call
  - One contiguous (n_cells, n_present) allocation vs 6 fragmented
    (n_cells, 1) allocations
  - One toarray() call instead of N (each has overhead per scipy)

Behavior is preserved: missing markers still emit a warning and a
0-valued column. Existing test_extract_markers_missing_genes covers
this path; 710 tests pass.

Findings #3 and #4 from #30 (sequential outer merges in unify.py and
til_select.py) are deliberately left as-is — the audit notes them as
speculative since clonotype tables are MB-scale, and re-shaping to
pd.concat doesn't materially change peak. Issue #35 captures them for
the next time someone profiles memory in unify/til-select.

* Bump version to 0.8.4

Coverage Stats

4642 of 6553 relevant lines covered (70.84%)

2.83 hits per line

Coverage Regressions

Lines	Coverage	∆	File
16	88.93	0.55%	loader.py

Jobs

ID	Job ID	Ran	Files	Coverage
1	python-3.10 - 25752045982.1	12 May 2026 05:49PM UTC	25	70.83	GitHub Action Run
2	python-3.9 - 25752045982.2	12 May 2026 05:49PM UTC	25	70.8	GitHub Action Run
3	python-3.11 - 25752045982.3	12 May 2026 05:49PM UTC	25	70.83	GitHub Action Run
4	python-3.12 - 25752045982.4	12 May 2026 05:49PM UTC	25	70.83	GitHub Action Run

pirl-unc / tcrsift / 25752045982
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