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Computational Governance and Model Cards

Python-facing port of computational-governance-and-model-cards.Rmd from the frozen R gp3bayes 0.5.0 reference. The statistical and governance framing below follows the canonical vignette; executable Python workflows use the mapped APIs listed later.

Complexity is audited before Stan

The complexity gate is not a statistical adequacy test. It is a reproducible guard against accidentally requesting models that combine many expensive layers or exact Gaussian processes over very large grids.

Model card

A model card records family, temporal structure, residual scale, autocorrelation, data dimensions, measurement/missingness declarations, predictive target, complexity status, and governance text. It is designed to support methods supplements and audit trails without becoming a validity certificate.

Python API mapping

  • gp3bayespy.audit_pupil_computational_budget
  • gp3bayespy.create_pupil_gp_spec
  • gp3bayespy.plot_pupil_model_complexity
  • gp3bayespy.pupil_model_card
  • gp3bayespy.pupil_model_card_table
  • gp3bayespy.simulate_advanced_pupil_timecourse
  • gp3bayespy.specify_advanced_pupil_timecourse_model

Python usage

import gp3bayespy as gp

# All functions listed above are available from the package root.
# Use help(gp.<function>) or the API reference for the exact Python signature.