Skip to content

Prediction Profiles, Surfaces, and Contrast Profiles

Python-facing port of prediction-profiles-surfaces-and-contrasts.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.

Governed prediction grids can be explored as one-dimensional profiles, finite-difference predictive gradients, two-dimensional surfaces, and two-level contrast profiles.

These are fitted predictive descriptions, not causal response curves or automatic interaction tests.

Python API mapping

  • gp3bayespy.create_prediction_contrast_profile
  • gp3bayespy.create_prediction_profile
  • gp3bayespy.create_prediction_surface
  • gp3bayespy.plot_prediction_contrast_profile
  • gp3bayespy.plot_prediction_gradient
  • gp3bayespy.plot_prediction_profile
  • gp3bayespy.plot_prediction_surface
  • gp3bayespy.plot_prediction_surface_uncertainty
  • gp3bayespy.prediction_gradient_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/predictive_diagnostics.py.