Skip to content

CLAUDE.md

Latest commit

 

History

History
72 lines (54 loc) · 2.53 KB

CLAUDE.md

File metadata and controls

72 lines (54 loc) · 2.53 KB

PyAutoFit

PyAutoFit is a Python probabilistic programming language for model fitting and Bayesian inference.

  • Authors: James Nightingale, Richard Hayes
  • Requires Python >= 3.9
  • Package name: autofit

Dependency Graph

PyAutoFit depends on autoconf (shared configuration and utilities). PyAutoFit does NOT depend on PyAutoArray, PyAutoGalaxy, or PyAutoLens. Never import from autoarray, autogalaxy, or autolens in this repo. Shared utilities (e.g. test_mode, jax_wrapper) belong in autoconf.

Repository Structure

  • autofit/ - Main package
    • non_linear/ - Non-linear search algorithms
      • search/mcmc/ - MCMC (emcee, zeus)
      • search/mle/ - Maximum likelihood (LBFGS, BFGS, drawer)
      • search/nest/ - Nested sampling (dynesty, nautilus)
      • samples/ - Posterior samples handling
      • paths/ - Output path management
      • analysis/ - Analysis base classes
    • mapper/ - Model and prior machinery
      • prior/ - Prior distributions
      • prior_model/ - Prior model composition
      • model.py - Core model class
    • graphical/ - Graphical models and expectation propagation
    • aggregator/ - Results aggregation across runs
    • database/ - SQLAlchemy-based results database
    • interpolator/ - Model interpolation
    • config/ - Default config files packaged with library
  • test_autofit/ - Test suite (pytest)
  • docs/ - Sphinx documentation

Key Dependencies

  • dynesty==2.1.5 - Nested sampling
  • emcee>=3.1.6 - MCMC
  • scipy<=1.14.0 - Optimisation
  • SQLAlchemy==2.0.32 - Database backend
  • anesthetic==2.8.14 - Posterior analysis/plotting
  • Optional: nautilus-sampler, zeus-mcmc, getdist

Running Tests

pytest test_autofit
pytest test_autofit/non_linear
pytest test_autofit/mapper

Codex / sandboxed runs

When running Python from Codex or any restricted environment, set writable cache directories so numba and matplotlib do not fail on unwritable home or source-tree paths:

NUMBA_CACHE_DIR=/tmp/numba_cache MPLCONFIGDIR=/tmp/matplotlib pytest test_autofit

This workspace is often imported from /mnt/c/... and Codex may not be able to write to module __pycache__ directories or /home/jammy/.cache, which can cause import-time numba caching failures without this override.

Shell Commands

  • Prefer simple shell commands
  • Avoid chaining with && or pipes; run commands separately

Related Repos

  • autofit_workspace (tutorials/examples): ../autofit_workspace