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Validate calibration probability and outcome domains - #342

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uriahf merged 3 commits into
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fix/calibration-input-validation
Aug 20, 2026
Merged

Validate calibration probability and outcome domains#342
uriahf merged 3 commits into
mainfrom
fix/calibration-input-validation

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@uriahf

@uriahf uriahf commented Aug 20, 2026

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Summary

  • reject calibration probabilities outside [0, 1]
  • reject binary calibration outcomes outside {0, 1}
  • reject time-dependent calibration event codes outside {0, 1, 2}
  • preserve existing calibration input shapes, including one concatenated model evaluated across multiple populations
  • add focused regression tests

R parity

The R create_calibration_curve() explicitly calls check_probs_input(). Python calibration used a separate data path and did not inherit the performance-data validation added in #341.

Audit classification

Input-validation / correctness gap. Invalid calibration inputs could reach histogram/smoothing/AJ internals rather than failing at the public API boundary.

No valid-input calibration calculations, smoothing methods, censoring/competing-risk heuristics, plotting behavior, or dependencies change.

@uriahf uriahf closed this Aug 20, 2026
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uriahf force-pushed the fix/calibration-input-validation branch from 7c0d49d to f1936a4 Compare August 20, 2026 12:22
@uriahf uriahf reopened this Aug 20, 2026
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github-actions Bot commented Aug 20, 2026

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PR Preview Action v1.8.1
Preview removed because the pull request was closed.
2026-08-20 12:35 UTC

@uriahf
uriahf marked this pull request as ready for review August 20, 2026 12:35
@uriahf
uriahf merged commit 518435f into main Aug 20, 2026
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