Anesthetic

Overview

Anesthetic is a Python package for visualizing and analyzing posterior samples from Bayesian inference. It creates publication-quality corner plots, 1D/2D marginal distributions, and computes Bayesian statistics (evidence, KL divergence) from nested sampling or MCMC chains.

Key capabilities:

• Load chains from PolyChord, MultiNest, UltraNest, Cobaya, GetDist formats
• Create corner/triangle plots with KDE, histogram, or scatter representations
• Compare prior vs posterior distributions
• Compute log-evidence, KL divergence, model dimensionality
• Built on pandas DataFrames for easy parameter manipulation

Workflow position: This skill provides component (4) Visualization in the physics workflow.

Installation

First, ensure anesthetic is installed in your environment: