Keep scCODA and tascCODA working under numpyro 0.22 - #1104
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numpyro 0.22 turns distribution validation on by default. scCODA replaces zero counts with a pseudocount of 0.5, so `counts` and the derived `n_total` fall outside the discrete DirichletMultinomial support: sampling now raises and NUTS initialization fails with "Cannot find valid initial parameters". The log-prob itself is well defined for fractional counts, so the likelihood site opts out of validation, and the prior predictive rounds the number of trials, which is the only well-defined choice when actually drawing counts. Verified against numpyro 0.22.0 in the pertpy conda env: all 11 tests in tests/tools/_coda pass, where run_nuts and make_arviz failed before.
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #1104 +/- ##
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+ Coverage 79.94% 79.96% +0.02%
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Files 55 55
Lines 7533 7533
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+ Hits 6022 6024 +2
+ Misses 1511 1509 -2
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numpyro 0.22 enables distribution validation by default, which rejects the fractional counts scCODA creates with its 0.5 pseudocount and makes
run_nuts()fail with "Cannot find valid initial parameters".The count likelihood now opts out of validation, since its log-prob is well defined for fractional counts, and the prior predictive rounds the number of trials.