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PyAutoGalaxy: Open-Source Multi Wavelength Galaxy Structure \u0026 Morphology\n\n[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.6.26.642/notebooks/imaging/start_here.ipynb)\n[![Documentation Status](https://readthedocs.org/projects/pyautogalaxy/badge/?version=latest)](https://pyautogalaxy.readthedocs.io/en/latest/?badge=latest)\n[![Tests](https://github.com/PyAutoLabs/PyAutoGalaxy/actions/workflows/main.yml/badge.svg)](https://github.com/PyAutoLabs/PyAutoGalaxy/actions)\n[![Build](https://github.com/Jammy2211/PyAutoBuild/actions/workflows/release.yml/badge.svg)](https://github.com/Jammy2211/PyAutoBuild/actions)\n[![Code Style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n[![JOSS](https://joss.theoj.org/papers/10.21105/joss.04475/status.svg)](https://doi.org/10.21105/joss.04475)\n[![pyOpenSci Peer-Reviewed](https://pyopensci.org/badges/peer-reviewed.svg)](https://github.com/pyOpenSci/software-submission/issues/235)\n[![Zenodo DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.7546914.svg)](https://doi.org/10.5281/zenodo.7546914)\n[![Project Status: Active](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)\n[![Python Versions](https://img.shields.io/pypi/pyversions/autogalaxy)](https://pypi.org/project/autogalaxy/)\n[![PyPI Version](https://img.shields.io/pypi/v/autogalaxy.svg)](https://pypi.org/project/autogalaxy/)\n\n[Installation Guide](https://pyautogalaxy.readthedocs.io/en/latest/installation/overview.html) |\n[readthedocs](https://pyautogalaxy.readthedocs.io/en/latest/index.html) |\n[Introduction on Colab](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.6.26.642/notebooks/imaging/start_here.ipynb) |\n[HowToGalaxy](https://pyautogalaxy.readthedocs.io/en/latest/howtogalaxy/howtogalaxy.html)\n\n**PyAutoGalaxy** is software for analysing the morphologies and structures of galaxies:\n\n[![HST Combined](https://github.com/PyAutoLabs/PyAutoGalaxy/blob/main/paper/hstcombined.png?raw=true)](https://github.com/PyAutoLabs/PyAutoGalaxy/blob/main/paper/hstcombined.png)\n\n**PyAutoGalaxy** also fits interferometer data from observatories such as ALMA:\n\n[![ALMA Combined](https://github.com/PyAutoLabs/PyAutoGalaxy/blob/main/paper/almacombined.png?raw=true)](https://github.com/PyAutoLabs/PyAutoGalaxy/blob/main/paper/almacombined.png)\n\n## Getting Started\n\nThe following links are useful for new starters:\n\n- [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).\n- [The introduction Jupyter Notebook on Google Colab](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.6.26.642/notebooks/imaging/start_here.ipynb), where you can try **PyAutoGalaxy** in a web browser (without installation).\n- [The autogalaxy_workspace GitHub repository](https://github.com/PyAutoLabs/autogalaxy_workspace): example scripts covering every **PyAutoGalaxy** use case.\n- [The HowToGalaxy GitHub repository](https://github.com/PyAutoLabs/HowToGalaxy): a Jupyter notebook lecture series teaching galaxy modeling from the ground up.\n\n## Core Aims\n\n**PyAutoGalaxy** has three core aims:\n\n- **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***.\n- **Model Complexity**: Fitting complex galaxy morphology models (e.g. Multi Gaussian Expansion, Shapelets, Ellipse Fitting, Irregular Meshes) that go beyond just simple Sérsic fitting.\n- **Data Variety**: Support for many data types (e.g. CCD imaging, interferometry, multi-band imaging) which can be fitted independently or simultaneously.\n\nA 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).\n\n## Community \u0026 Support\n\nSupport for **PyAutoGalaxy** is available via our Slack workspace, where the community shares updates, discusses\ngalaxy modeling and analysis, and helps troubleshoot problems.\n\nSlack is invitation-only. If you'd like to join, please send an email requesting an invite.\n\nFor installation issues, bug reports, or feature requests, please raise an issue on the [GitHub issues page](https://github.com/PyAutoLabs/PyAutoGalaxy/issues).\n\n## HowToGalaxy\n\nFor users less familiar with galaxy analysis, Bayesian inference, and scientific analysis, you may wish to read through\nthe **HowToGalaxy** lectures. These introduce the basic principles of galaxy modeling and Bayesian inference, with\nthe material pitched at undergraduate level and above.\n\nA 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.\n\n## Citations\n\nInformation on how to cite **PyAutoGalaxy** in publications can be found [on the citations page](https://github.com/PyAutoLabs/PyAutoGalaxy/blob/main/CITATIONS.md).\n\n## Contributing\n\nInformation on how to contribute to **PyAutoGalaxy** can be found [on the contributing page](https://github.com/PyAutoLabs/PyAutoGalaxy/blob/main/CONTRIBUTING.md).\n\nHands on support for contributions is available via our Slack workspace, again please email to request an invite.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpyautolabs%2Fpyautogalaxy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpyautolabs%2Fpyautogalaxy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpyautolabs%2Fpyautogalaxy/lists"}