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Support non-consecutive n_clusters in ClusterAutoK - #127
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ClusterAutoK compared each K with K+1 by looking up self.labels[k + 1], which raised IndexError when n_clusters was a non-consecutive list such as [5, 10, 15, 20]. n_clusters now always holds the K values to evaluate (a tuple is expanded to the inclusive range). The K-1 and K+1 neighbours of every requested K are fitted as well, filling any gaps, so stability is still computed between adjacent numbers of clusters. Values below 2 are ignored with a warning. Models saved with older versions, whose n_clusters also included the border neighbours, are converted on load. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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Merge Risk: 🔵 Low · up to
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| Check name | Status | Explanation | Resolution |
|---|---|---|---|
| Out of Scope Changes check |  |
The changes in tests/conftest.py, tests/test_fixtures.py, and pyproject.toml add file locking, retry handling, and dependency support for concurrent CODEX fixture loading. These changes do not i… |
Remove the unrelated CODEX fixture locking, retry, and dependency changes from this pull request, or move them to a separate pull request with its own scope. |
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Check name Status Explanation Description Check Check skipped - CodeRabbit’s high-level summary is enabled. Title check The title clearly and concisely describes the primary change: adding support for non-consecutive cluster counts in ClusterAutoK. Linked Issues check Issue #117requiresClusterAutoK.fitto handle non-consecutive lists withoutIndexError. The implementation stores sorted requested K values, fits each K with its K-1 and K+1 neighbors, computes p…Docstring Coverage Docstring coverage is 83.33% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 30 functions across 5 files. (1 skipped: 1 … Full details: Linked Issues check
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Explanation
Issue
#117requiresClusterAutoK.fitto handle non-consecutive lists withoutIndexError. The implementation stores sorted requested K values, fits each K with its K-1 and K+1 neighbors, computes pair stability by fitted K, and maps stability to each requested K. The updatedbest_k,peaks, andpredictlogic uses these results. The reported tests cover non-consecutive input and related tuple/list behavior.
Full details: Docstring Coverage
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Explanation
Docstring coverage is 83.33% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 30 functions across 5 files. (1 skipped: 1 unsupported.)
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Full details: Out of Scope Changes check
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Explanation
The changes in
tests/conftest.py,tests/test_fixtures.py, andpyproject.tomladd file locking, retry handling, and dependency support for concurrent CODEX fixture loading. These changes do not implement or test non-consecutiven_clustershandling for Issue#117.Resolution
Remove the unrelated CODEX fixture locking, retry, and dependency changes from this pull request, or move them to a separate pull request with its own scope.
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…tive-117 # Conflicts: # src/cellcharter/tl/_autok.py
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Review comments at @src/cellcharter/tl/_autok.py:
- Around line 400-401: Update the legacy-layout check in _fit_n_clusters to
detect and convert stored border counts based on the relationship between labels
and n_clusters, regardless of whether stability is None; preserve the existing
conversion for models with stability.
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Additional details and impacted files@@ Coverage Diff @@
## main #127 +/- ##
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+ Coverage 68.48% 70.61% +2.12%
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Files 23 23
Lines 1682 1698 +16
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+ Misses 530 499 -31
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- Line 78: Update the recovery exception handling around `ad.read_h5ad` to catch
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Closes #117
Problem
ClusterAutoK.fitcompared each K with K+1 throughself.labels[k + 1], so a non-consecutiven_clusterslist (e.g.[5, 10, 15, 20]) raisedIndexError. Also, a list was used as given and its first and last values were silently left out of the evaluation, unlike a tuple, which was expanded with its border neighbours.Fix
Instead of comparing adjacent list items (stability between K=5 and K=10 is not comparable with stability between adjacent K), the K-1 and K+1 neighbours are added wherever they are missing, i.e. at every gap and not only at the borders of the range:
n_clustersnow always holds the K values to evaluate. A tuple(min, max)is expanded to the inclusive range, and a list is sorted and deduplicated.{K-1, K, K+1}for every requested K. Stability is computed between adjacent fitted K and then combined per evaluated K, as before.best_k,peaksandcc.pl.autok_stabilityindexn_clustersdirectly instead ofn_clusters[1:-1].ValueErroris raised if nothing is left.predictaccepts any fitted K.n_clustersalso contained the border neighbours, are converted on load.Note: a sparse list costs up to 3× the fits of the list itself, because each K brings in its neighbours.
Tests
[6, 2, 4]): fitted K, stability shape,best_kandpredictmibitofmodel🤖 Generated with Claude Code
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