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PyAutoArray — Agent Instructions

PyAutoArray is the low-level data structures and numerical utilities package for the PyAuto ecosystem. It provides grids, masks, arrays, datasets, inversions, and the decorator system used throughout PyAutoGalaxy and PyAutoLens.

Setup

pip install -e ".[dev]"

Running Tests

python -m pytest test_autoarray/
python -m pytest test_autoarray/structures/test_arrays.py
python -m pytest test_autoarray/structures/test_arrays.py -s

Sandboxed / Codex runs

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

Key Architecture

  • Data structures: Array2D, Grid2D, Grid2DIrregular, VectorYX2D — all inherit from AbstractNDArray
  • Decorator system (structures/decorators/): @to_array, @to_grid, @to_vector_yx, @transform — ensures output type matches input grid type
  • Datasets: Imaging, Interferometer — containers for observational data
  • Inversions (inversion/): sparse linear algebra for source reconstruction via pixelizations
  • Operators: Convolver (PSF convolution), over-sampling utilities

Key Rules

  • The xp parameter pattern controls NumPy vs JAX: xp=np (default) or xp=jnp
  • Autoarray types are not JAX pytrees — they cannot be returned from jax.jit functions
  • Decorated functions must return raw arrays, not autoarray wrappers
  • All files must use Unix line endings (LF)
  • Format with black autoarray/

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_autoarray/
  4. Ensure all tests pass before opening a PR.
  5. If changing public API, note the change in your PR description — downstream packages (PyAutoGalaxy, PyAutoLens) and workspaces may need updates.