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: TBD
Editor: TBD
Reviewer 1: TBD
Reviewer 2: TBD
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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  Check out our package scope page to learn more about our
  scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):

  • Data retrieval
  • Data extraction
  • Data processing/munging
  • Data deposition
  • Data validation and testing
  • Data visualization¹
  • Workflow automation
  • Citation management and bibliometrics
  • Scientific software wrappers
  • Database interoperability

Domain Specific

• Geospatial
• Education

Community Partnerships

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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.

• If you made a pre-submission enquiry, please paste the link to the corresponding issue, forum post, or other discussion, or @tag the editor you contacted:

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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• I expect to maintain this package for at least 2 years and can help find a replacement for the maintainer (team) if needed.

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Footnotes

1. Please fill out a pre-submission inquiry before submitting a data visualization package. ↩