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Synthetic Advanced Pupillometry Gallery

Python-facing port of synthetic-advanced-pupillometry-gallery.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.

Observed trajectories

Stored latent mean

Temporal dependence

Missingness

Computational audit

Binocular example

The gallery is intentionally backend-free so it can be built during package checks without compiling Stan. Full posterior plot examples are shown in the modelling vignettes with fitting code disabled by default.

Python API mapping

  • gp3bayespy.audit_binocular_pupil_readiness
  • gp3bayespy.audit_pupil_measurement_model
  • gp3bayespy.audit_pupil_missingness
  • gp3bayespy.audit_pupil_temporal_dependence
  • gp3bayespy.create_pupil_measurement_model
  • gp3bayespy.create_pupil_missingness_spec
  • gp3bayespy.plot_advanced_pupil_simulation
  • gp3bayespy.plot_pupil_measurement_uncertainty
  • gp3bayespy.plot_pupil_missingness
  • gp3bayespy.plot_pupil_model_complexity
  • gp3bayespy.plot_pupil_temporal_dependence
  • gp3bayespy.prepare_binocular_pupil_timecourse
  • gp3bayespy.simulate_advanced_pupil_timecourse
  • gp3bayespy.simulate_binocular_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.

An executable workflow for this family is included in ../../examples/pupil_workflow.py.