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PyAutoGalaxy — Agent Instructions

PyAutoGalaxy is a Bayesian galaxy morphology fitting library. It depends on autoarray (data structures) and autofit (model-fitting framework).

Setup

pip install -e ".[dev]"

Running Tests

python -m pytest test_autogalaxy/
python -m pytest test_autogalaxy/galaxy/test_galaxy.py
python -m pytest test_autogalaxy/galaxy/test_galaxy.py::TestGalaxy::test_name

Sandboxed / Codex runs

NUMBA_CACHE_DIR=/tmp/numba_cache MPLCONFIGDIR=/tmp/matplotlib python -m pytest test_autogalaxy/

Key Architecture

  • Profiles: LightProfile (lp.*), MassProfile (mp.*), LightProfileLinear (lp_linear.*)
  • Galaxy (galaxy/galaxy.py): holds light/mass profiles, pixelizations
  • Fit classes: FitImaging, FitInterferometer, FitQuantity, FitEllipse
  • Analysis classes: AnalysisImaging, AnalysisInterferometer — implement log_likelihood_function
  • Decorator system (from autoarray): @to_array, @to_grid, @to_vector_yx, @transform
  • Operate mixins: OperateImage, OperateDeflections, LensCalc

Key Rules

  • The xp parameter controls NumPy vs JAX: xp=np (default) or xp=jnp
  • Functions inside jax.jit must guard autoarray wrapping with if xp is np:
  • Decorated functions return raw arrays — the decorator wraps them
  • Use grid.array[:, 0] to access grid coordinates (not grid[:, 0])
  • All files must use Unix line endings (LF)
  • Format with black autogalaxy/

Working on Issues

  1. Read the issue description and any linked plan.
  2. Identify affected files and write your changes.
  3. Run the full test suite: python -m pytest test_autogalaxy/
  4. Ensure all tests pass before opening a PR.
  5. If changing public API, note the change in your PR description — downstream packages (PyAutoLens) and workspaces may need updates.