Metadata-Version: 2.4
Name: autogalaxy
Version: 2026.9.19.1
Summary: Open-Source Multi Wavelength Galaxy Structure & Morphology
Author-email: James Nightingale <James.Nightingale@newcastle.ac.uk>, Richard Hayes <richard@rghsoftware.co.uk>
License: MIT
Project-URL: Homepage, https://github.com/PyAutoLabs/PyAutoGalaxy
Keywords: cli
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Requires-Python: >=3.12
Description-Content-Type: text/markdown
License-File: LICENSE
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Dynamic: license-file

# PyAutoGalaxy: Open-Source Multi Wavelength Galaxy Structure & Morphology

[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.9.15.1/start_here.ipynb)
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[Installation Guide](https://pyautogalaxy.readthedocs.io/en/latest/installation/overview.html) |
[readthedocs](https://pyautogalaxy.readthedocs.io/en/latest/index.html) |
[Introduction on Colab](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.9.15.1/start_here.ipynb) |
[HowToGalaxy](https://pyautogalaxy.readthedocs.io/en/latest/howtogalaxy/howtogalaxy.html)

**PyAutoGalaxy** is software for analysing the morphologies and structures of galaxies:

[![HST Combined](https://github.com/PyAutoLabs/PyAutoGalaxy/blob/main/paper/hstcombined.png?raw=true)](https://github.com/PyAutoLabs/PyAutoGalaxy/blob/main/paper/hstcombined.png)

**PyAutoGalaxy** also fits interferometer data from observatories such as ALMA:

[![ALMA Combined](https://github.com/PyAutoLabs/PyAutoGalaxy/blob/main/paper/almacombined.png?raw=true)](https://github.com/PyAutoLabs/PyAutoGalaxy/blob/main/paper/almacombined.png)

## Getting Started

### Human-Readable Documentation and Examples

The following human-readable documentation and examples are useful for new starters:

- [The PyAutoGalaxy readthedocs](https://pyautogalaxy.readthedocs.io/en/latest), which includes [an overview of PyAutoGalaxy's core features](https://pyautogalaxy.readthedocs.io/en/latest/overview/overview_1_start_here.html), [a new user starting guide](https://pyautogalaxy.readthedocs.io/en/latest/overview/overview_2_new_user_guide.html) and [an installation guide](https://pyautogalaxy.readthedocs.io/en/latest/installation/overview.html).
- [The introduction Jupyter Notebook on Google Colab](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.9.15.1/start_here.ipynb), where you can try **PyAutoGalaxy** in a web browser (without installation).
- [The autogalaxy_workspace GitHub repository](https://github.com/PyAutoLabs/autogalaxy_workspace): example scripts covering every **PyAutoGalaxy** use case.
- [The HowToGalaxy GitHub repository](https://github.com/PyAutoLabs/HowToGalaxy): a Jupyter notebook lecture series teaching galaxy modeling from the ground up.

### PyAutoGalaxy AI Assistant

The [**PyAutoGalaxy AI Assistant**](https://github.com/PyAutoLabs/autogalaxy_assistant) lets you do galaxy structure and morphology science in natural language from inside an AI coding agent. You can get started simply by asking it a question about galaxy structure or describing the task you would like to perform with **PyAutoGalaxy**. See the assistant for its full scope and instructions.

**The assistant runs inside an AI coding agent: Claude Code or Codex are recommended. Sustained scientific use normally needs paid access to one of them (a personal subscription, institutional access or API billing). OpenCode is an experimental alternative whose client is free but whose model access, cost and capability depend on the provider. Browser chat routes (ChatGPT or Claude with a GitHub connector) are no longer supported.**

## Core Aims

**PyAutoGalaxy** has three core aims:

- **Big Data**: Scaling automated Sérsic fitting to extremely large datasets, *accelerated with JAX on GPUs and using tools like an SQL database to **build a scalable scientific workflow***.
- **Model Complexity**: Fitting complex galaxy morphology models (e.g. Multi Gaussian Expansion, Shapelets, Ellipse Fitting, Irregular Meshes) that go beyond just simple Sérsic fitting.
- **Data Variety**: Support for many data types (e.g. CCD imaging, interferometry, multi-band imaging) which can be fitted independently or simultaneously.

A complete overview of the software's aims is provided in our [Journal of Open Source Software paper](https://joss.theoj.org/papers/10.21105/joss.04475).

## Community & Support

Support for **PyAutoGalaxy** is available via our Slack workspace, where the community shares updates, discusses
galaxy modeling and analysis, and helps troubleshoot problems.

Slack is invitation-only. If you'd like to join, please send an email requesting an invite.

For installation issues, bug reports, or feature requests, please raise an issue on the [GitHub issues page](https://github.com/PyAutoLabs/PyAutoGalaxy/issues).

## HowToGalaxy

For users less familiar with galaxy analysis, Bayesian inference, and scientific analysis, you may wish to read through
the **HowToGalaxy** lectures. These introduce the basic principles of galaxy modeling and Bayesian inference, with
the material pitched at undergraduate level and above.

A complete overview of the lectures [is provided on the HowToGalaxy readthedocs page](https://pyautogalaxy.readthedocs.io/en/latest/howtogalaxy/howtogalaxy.html), and the notebooks themselves live in the [PyAutoLabs/HowToGalaxy](https://github.com/PyAutoLabs/HowToGalaxy) repository.

## Citations

Information on how to cite **PyAutoGalaxy** in publications can be found [on the citations page](https://github.com/PyAutoLabs/PyAutoGalaxy/blob/main/CITATIONS.md).

## Contributing

Information on how to contribute to **PyAutoGalaxy** can be found [on the contributing page](https://github.com/PyAutoLabs/PyAutoGalaxy/blob/main/CONTRIBUTING.md).

Hands on support for contributions is available via our Slack workspace, again please email to request an invite.

<sub><i><a href="https://open.spotify.com/track/3i9QKRl5Ql3pgUfNdYBVTc">glow</a></i></sub>
