This sub-wiki gives an AI assistant the scientific context of the
methodological tooling that underpins PyAutoLens, PyAutoFit, and
related codes: Bayesian inference, nested and Hamiltonian sampling,
deep learning for astrophysics, probabilistic programming languages,
linear-algebra primitives (NUFFT, message passing), and the wider
scientific-software ecosystem. Sibling of ../lensing/ under
PyAutoMemory/, same Karpathy "LLM Wiki" pattern.
methods/
├── AGENTS.md # this file — schema + scope
├── index.md # top-level navigation
├── log.md # append-only compilation log
├── concepts/ # Bayes basics, samplers, deep learning, etc.
├── entities/ # PyAutoFit, PolyChord, BlackJAX, jax-finufft, …
├── sources/ # per-topic claim support
└── seed/ # unverified 2026-05 import — never cite from here
Inherits verbatim from ../AGENTS.md.
In-scope folders:
Stats/— Bayesian methods, likelihood-free inference, MCMC, sampler comparisons.GaussianLinearModels/— Gaussian linear models, conjugate priors, closed-form posteriors used in linear inversion.PPLs/— probabilistic programming languages (Stan, PyMC, NumPyro, Pyro, etc.).Deep Learning/— CNNs, BNNs, simulation-based inference applied to astrophysics (cross-references../lensing/sources-deep-learning-lensing.md).Software/— general-purpose scientific software references (samplers, optimisers, JAX ecosystem).Simulation/— Monte Carlo simulation methodology, hierarchical forward modelling.- Root-level
PolyChord.pdf,linearalgebra.pdf,NUFFTPAper.pdf,PYNUFFT.pdf,MessagePassingIsAWayOfLife.pdf,BigData.pdf,PyLops(folder),imfit.pdf,Profit2019.pdf.
Adjacent topics that link out:
- Lens-modelling-specific Bayesian / regularisation methods —
../lensing/concepts/bayesian-inference-lensing.mdand../lensing/concepts/regularization.md. - Mass-model / source-reconstruction software entities —
../lensing/entities/{pyautolens,pyautofit,lenstronomy}.md.
Same protocol as ../AGENTS.md.