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Open-Source Multi Wavelength Galaxy Structure \u0026 Morphology\r\n========================================================================\r\n\r\n.. image:: https://colab.research.google.com/assets/colab-badge.svg\r\n   :target: https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.1.4/start_here.ipynb\r\n\r\n.. image:: https://readthedocs.org/projects/pyautogalaxy/badge/?version=latest\r\n   :target: https://pyautogalaxy.readthedocs.io/en/latest/?badge=latest\r\n   :alt: Documentation Status\r\n\r\n.. image:: https://github.com/Jammy2211/PyAutoGalaxy/actions/workflows/main.yml/badge.svg\r\n   :target: https://github.com/Jammy2211/PyAutoGalaxy/actions\r\n\r\n.. image:: https://github.com/Jammy2211/PyAutoBuild/actions/workflows/release.yml/badge.svg\r\n   :target: https://github.com/Jammy2211/PyAutoBuild/actions\r\n\r\n.. image:: https://img.shields.io/badge/code%20style-black-000000.svg\r\n   :target: https://github.com/psf/black\r\n\r\n.. image:: https://joss.theoj.org/papers/10.21105/joss.04475/status.svg\r\n   :target: https://doi.org/10.21105/joss.04475\r\n\r\n.. image:: https://pyopensci.org/badges/peer-reviewed.svg\r\n   :target: https://github.com/pyOpenSci/software-submission/issues/235\r\n   :alt: pyOpenSci Peer-Reviewed\r\n\r\n.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.7546914.svg\r\n   :target: https://doi.org/10.5281/zenodo.7546914\r\n   :alt: Zenodo DOI\r\n\r\n.. image:: https://www.repostatus.org/badges/latest/active.svg\r\n    :target: https://www.repostatus.org/#active\r\n    :alt: Project Status: Active\r\n\r\n.. image:: https://img.shields.io/pypi/pyversions/autogalaxy\r\n    :target: https://pypi.org/project/autogalaxy/\r\n    :alt: Python Versions\r\n\r\n.. image:: https://img.shields.io/pypi/v/autogalaxy.svg\r\n    :target: https://pypi.org/project/autogalaxy/\r\n    :alt: PyPI Version\r\n\r\n`Installation Guide \u003chttps://pyautogalaxy.readthedocs.io/en/latest/installation/overview.html\u003e`_ |\r\n`readthedocs \u003chttps://pyautogalaxy.readthedocs.io/en/latest/index.html\u003e`_ |\r\n`Introduction on Colab \u003chttps://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.1.4/start_here.ipynb\u003e`_ |\r\n`HowToGalaxy \u003chttps://pyautogalaxy.readthedocs.io/en/latest/howtogalaxy/howtogalaxy.html\u003e`_\r\n\r\n**PyAutoGalaxy** is software for analysing the morphologies and structures of galaxies:\r\n\r\n.. image:: https://github.com/Jammy2211/PyAutoGalaxy/blob/main/paper/hstcombined.png?raw=true\r\n        :target: https://github.com/Jammy2211/PyAutoGalaxy/blob/main/paper/hstcombined.png\r\n\r\n**PyAutoGalaxy** also fits interferometer data from observatories such as ALMA:\r\n\r\n.. image:: https://github.com/Jammy2211/PyAutoGalaxy/blob/main/paper/almacombined.png?raw=true\r\n        :target: https://github.com/Jammy2211/PyAutoGalaxy/blob/main/paper/almacombined.png\r\n\r\nGetting Started\r\n---------------\r\n\r\nThe following links are useful for new starters:\r\n\r\n- `The PyAutoGalaxy readthedocs \u003chttps://pyautogalaxy.readthedocs.io/en/latest\u003e`_, which includes `an overview of PyAutoGalaxy's core features \u003chttps://pyautogalaxy.readthedocs.io/en/latest/overview/overview_1_start_here.html\u003e`_, `a new user starting guide \u003chttps://pyautogalaxy.readthedocs.io/en/latest/overview/overview_2_new_user_guide.html\u003e`_ and `an installation guide \u003chttps://pyautogalaxy.readthedocs.io/en/latest/installation/overview.html\u003e`_.\r\n\r\n- `The introduction Jupyter Notebook on Google Colab \u003chttps://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.5.1.4/start_here.ipynb\u003e`_, where you can try **PyAutoGalaxy** in a web browser (without installation).\r\n\r\n- `The autogalaxy_workspace GitHub repository \u003chttps://github.com/PyAutoLabs/autogalaxy_workspace\u003e`_: example scripts covering every **PyAutoGalaxy** use case.\r\n\r\n- `The HowToGalaxy GitHub repository \u003chttps://github.com/PyAutoLabs/HowToGalaxy\u003e`_: a Jupyter notebook lecture series teaching galaxy modeling from the ground up.\r\n\r\nCore Aims\r\n---------\r\n\r\n**PyAutoGalaxy** has three core aims:\r\n\r\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***.\r\n\r\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.\r\n\r\n- **Data Variety**: Support for many data types (e.g. CCD imaging, interferometry, multi-band imaging) which can be fitted independently or simultaneously.\r\n\r\nA complete overview of the software's aims is provided in our `Journal of Open Source Software paper \u003chttps://joss.theoj.org/papers/10.21105/joss.04475\u003e`_.\r\n\r\nCommunity \u0026 Support\r\n-------------------\r\n\r\nSupport for **PyAutoGalaxy** is available via our Slack workspace, where the community shares updates, discusses\r\ngalaxy modeling and analysis, and helps troubleshoot problems.\r\n\r\nSlack is invitation-only. If you’d like to join, please send an email requesting an invite.\r\n\r\nFor installation issues, bug reports, or feature requests, please raise an issue on the `GitHub issues page \u003chttps://github.com/Jammy2211/PyAutoGalaxy/issues\u003e`_.\r\n\r\nHowToGalaxy\r\n-----------\r\n\r\nFor users less familiar with galaxy analysis, Bayesian inference, and scientific analysis, you may wish to read through\r\nthe **HowToGalaxy** lectures. 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