BUG: Raise TypeError for non-integer float observed data on discrete distributions#8285
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kimjune01 wants to merge 4 commits into
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BUG: Raise TypeError for non-integer float observed data on discrete distributions#8285kimjune01 wants to merge 4 commits into
kimjune01 wants to merge 4 commits into
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…iscrete distributions Fixes pymc-devs#8282. Discrete distributions (Binomial, Poisson, etc.) silently cast float observed values to integers via .astype(), truncating data without warning. Add a validation check in make_obs_var() that detects when float-to-integer casting would alter values. The check is narrowly scoped: - Only fires for concrete data (not symbolic Variables) - Only fires for float->integer dtype casts - Allows float arrays with exact integer values (e.g. [0.0, 1.0]) - Handles masked arrays via .compressed() - Handles scipy sparse matrices via .data attribute
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Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #8285 +/- ##
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- Coverage 91.94% 91.94% -0.01%
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Files 125 125
Lines 20302 20314 +12
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+ Hits 18667 18678 +11
- Misses 1635 1636 +1
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main refactored scipy.sparse to a lazy module (sparse = lazy_scipy_module("sparse"))
and removed 'import scipy.sparse as sps'. Merging main left our new
make_obs_var check referencing the now-undefined 'sps'. Switch to the
'sparse' alias to match the current convention.
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Description
Model.make_obs_varsilently truncates float observed data to integers when the distribution has an integer dtype (e.g.Binomial,Poisson). This can produce wrong posteriors with no indication that anything went wrong.This PR adds a check in
make_obs_varthat raisesTypeErrorwhen float observed data contains non-integer values that would lose information on cast. Float arrays with exact integer values (e.g.[0.0, 1.0]) are still accepted, since this is a common pattern withfloatXdata.Handles
ndarray,MaskedArray, and sparse matrices.Closes #8282
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