Sensitivity Atlases

Python-facing port of sensitivity-atlas.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.

Existing sensitivity workflows now share a publication-oriented table-and-plot layer.

Local stability under a perturbation is not promoted to a universal robustness claim.

Python API mapping

• gp3bayespy.estimand_sensitivity_table
• gp3bayespy.group_deletion_sensitivity_table
• gp3bayespy.plot_estimand_sensitivity_gg
• gp3bayespy.plot_group_deletion_sensitivity
• gp3bayespy.plot_powerscale_sensitivity_gg
• gp3bayespy.plot_prior_sensitivity
• gp3bayespy.plot_random_slope_sensitivity
• gp3bayespy.powerscale_sensitivity_table
• gp3bayespy.prior_sensitivity_table
• gp3bayespy.random_slope_sensitivity_table

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/sensitivity_workflow.py.

Visual companion

These figures complement the canonical ported narrative and are generated from package functions.

Sensitivity suite. Deterministic visual companion generated from the Python package.

Backend parity. Deterministic visual companion generated from the Python package.

The figures remain descriptive evidence and do not create automatic inferential decisions.