https://github.com/pyautolabs/pyautoarray
Array and grid manipulation for the PyAuto ecosystem
https://github.com/pyautolabs/pyautoarray
astronomy numpy python scientific-computing
Last synced: 3 days ago
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Array and grid manipulation for the PyAuto ecosystem
- Host: GitHub
- URL: https://github.com/pyautolabs/pyautoarray
- Owner: PyAutoLabs
- License: mit
- Created: 2019-09-26T02:18:10.000Z (almost 7 years ago)
- Default Branch: main
- Last Pushed: 2026-07-02T05:59:39.000Z (3 days ago)
- Last Synced: 2026-07-02T07:26:15.258Z (3 days ago)
- Topics: astronomy, numpy, python, scientific-computing
- Language: Python
- Size: 12.6 MB
- Stars: 10
- Watchers: 3
- Forks: 7
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Agents: AGENTS.md
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README
# PyAutoArray
**PyAutoArray** (package `autoarray`) is the low-level data-structure and
numerical-utility layer of the [PyAuto](https://github.com/PyAutoLabs)
ecosystem. It provides masks, arrays, (y,x) coordinate grids,
imaging/interferometer datasets, inversions/pixelizations for source
reconstruction, and convolution/over-sampling operators.
`PyAutoGalaxy` and `PyAutoLens` build directly on autoarray: every grid a
profile consumes, every masked image a fit operates on, and the linear-algebra
inversions behind pixelized source reconstruction are autoarray objects. The
package supports both a NumPy and an opt-in JAX (`xp=jnp`) backend.
## Install
```bash
pip install autoarray
```
## Examples
A masked 2D array tied to a pixel scale:
```python
import autoarray as aa
arr = aa.Array2D.no_mask(values=[[1.0, 2.0], [3.0, 4.0]], pixel_scales=0.1)
arr.shape_native # (2, 2)
arr.native[0, 0] # 1.0
```
A circular mask and the (y,x) coordinate grid of its unmasked pixels:
```python
mask = aa.Mask2D.circular(shape_native=(50, 50), pixel_scales=0.1, radius=2.0)
mask.pixels_in_mask # 1264
grid = aa.Grid2D.from_mask(mask=mask) # shape (1264, 2)
uniform = aa.Grid2D.uniform(shape_native=(10, 10), pixel_scales=0.1)
```
A normalized Gaussian PSF convolver:
```python
convolver = aa.Convolver.from_gaussian(
shape_native=(11, 11), pixel_scales=0.1, sigma=1.0, normalize=True
)
convolver.kernel.shape_native # (11, 11)
convolver.kernel.array.sum() # 1.0
```
## Links
- Source & tests: [`autoarray/`](autoarray), [`test_autoarray/`](test_autoarray)
- Decorators & JAX deep dive: [`docs/agents/jax_and_decorators.md`](docs/agents/jax_and_decorators.md)
- Agent/contributor instructions: [`AGENTS.md`](AGENTS.md)
- Ecosystem: [PyAutoLabs on GitHub](https://github.com/PyAutoLabs)