stats: fit_clmm no longer raises ImportError when statsmodels is absent - #33
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stats: fit_clmm no longer raises ImportError when statsmodels is absent#33ChrisW09 wants to merge 1 commit into
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fit_clmm/fit_logistic are documented to always return a result object with available=False and a reason instead of raising, and the codebase deliberately supports pandas-without-statsmodels environments (fit_effects catches ImportError and falls back to one-way ANOVA). But _design_rank_deficient imported statsmodels outside its try block, so fit_clmm on a >=2-factor study with the default interactions=2 crashed with ImportError in exactly those environments. Fixes #9 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Fixes #9.
_design_rank_deficient(shared byfit_clmmandfit_logisticfor the aliasing check) importedstatsmodels.formula.apioutside itstry, so in a pandas-without-statsmodels environment — whichfit_effectsdeliberately supports via its ownImportErrorfallback —fit_clmmon a ≥2-factor study with the defaultinteractions=2raisedImportErrorinstead of returning its documented gracefulCLMMResult. Single-factor orinteractions=1studies dodged it via the early return, making the crash data-shape dependent.The import is now guarded; without statsmodels the aliasing check is simply skipped (
return False), matching the function's existing "can't determine → False" behavior. Regression test simulates the missing module viasys.modules.Test:
pytest packages/cafe-core/tests/test_stats.py— 19 passed (the one failure is pre-existing #4, fixed in a separate PR).🤖 Generated with Claude Code