PyAutoGalaxy

[Jammy2211]

Submitting Author: (@Jammy2211)
All current maintainers: (@Jammy2211)
Package Name: PyAutoGalaxy
One-Line Description of Package: Astronomy software for analysing the morphologies and structures of galaxies
Repository Link: https://github.com/Jammy2211/PyAutoGalaxy
Version submitted: 2025.1.18.7
EiC: @coatless
Editor: @hamogu
Reviewer 1: @canorve
Reviewer 2: @eteq
Archive: TBD
JOSS DOI: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD

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Description

Nearly a century ago, Edwin Hubble famously classified galaxies into three distinct groups: ellipticals, spirals and irregulars [@Hubble1926]. Today, by analysing millions of galaxies with advanced image processing techniques Astronomers have expanded on this picture and revealed the rich diversity of galaxy morphology in both the nearby and distant Universe [@Kormendy2015a; @Vulcani2014; @VanDerWel2012]. PyAutoGalaxy is an open-source Python 3.8 - 3.11 package for analysing the morphologies and structures of large multiwavelength galaxy samples, with core features including fully automated Bayesian model-fitting of galaxy two-dimensional surface brightness profiles, support for dataset and interferometer datasets and comprehensive tools for simulating galaxy images. The software places a focus on big data analysis, including support for hierarchical models that simultaneously fit thousands of galaxies, massively parallel model-fitting and an SQLite3 database that allows large suites of modeling results to be loaded, queried and analysed.

Scope

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  • Data extraction
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  • Who is the target audience and what are scientific applications of this package?

Astronomers studying the morphology of galaxies, and undergraduates / people interested in learning how to do science with galaxies. The package analyses galaxy images (e.g. from the James Webb Space Telescope) and extracts information on them.

• Are there other Python packages that accomplish the same thing? If so, how does yours differ?

Many: pysersic, GALFIT, ProFit, to name a few.

PyAutoGalaxy supports a more diverse range of ways to analysis galaxy images and has support for Bayesian inference on big data (e.g. sqlite database, graphical modeling) other packages do not.

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This package was first submited to astropy years ago, then was to be moved to PyOpenSci, this PR discussion shows that: astropy/astropy.github.com#491

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Already Published in JOSS: https://joss.theoj.org/papers/10.21105/joss.04475

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[coatless]

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Editor comments

Thanks for submitting PyAutoGalaxy to pyOpenSci! The package is in ship shape to move forward with our review process. The documentation and functionality is excellent! Well done on creating actionable streams to get users immediately able to analyzing morphoologies and structures of galaxies!

The only minor nit is a section in the README.md clearly labeled as "Installation Instructions". That said, this is largely covered by "Installation Guide" link. However, it would be great if you could include a brief separate snippet. Though, I'm going to go ahead and move the process along by assigning to @hamogu.

[hamogu]

Editor response to review:

Hi @Jammy2211! Thanks for submitting your package to PyOpenSci. I'll be your editor - please feel free to reach out to me with any questions you might have. I'll now start to look for reviewers; usually that's the most time-consuming part of the process but I'll keep you updated as that goes along!

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Editor comments

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Please get in touch with any questions or concerns! Your review is due:

Reviewers: @canorve @eteq
Due date: 6-Jule-2025

[hamogu]

Hi @Jammy2211! I just want to let you know that I'm still looking for a second reviewer. I've contacted three people so far, one declined and two never responded. I know with summer approaching it's a busy time for many and I hope I'll find someone soon. I just need to ask for a little more patience; I'm sorry it takes to long and I promise I keep working on it.