James Nightingale james.w.nightingale@durham.ac.uk
Academic Visitor
James Nightingale james.w.nightingale@durham.ac.uk
Academic Visitor
Aristeidis Amvrosiadis aristeidis.amvrosiadis@durham.ac.uk
Post Doctoral Research Associate
Richard G. Hayes
Dr Qiuhan He qiuhan.he@durham.ac.uk
Post Doctoral Research Associate
Amy Etherington amy.etherington@durham.ac.uk
PGR Student Doctor of Philosophy
XiaoYue Cao
Professor Shaun Cole shaun.cole@durham.ac.uk
Director of the Institute for Computational Cosmology
Jonathan Frawley jonathan.frawley@durham.ac.uk
PGR Student Doctor of Philosophy
Professor Carlos Frenk c.s.frenk@durham.ac.uk
Professor
Sam Lange samuel.c.lange@durham.ac.uk
PGR Student Doctor of Philosophy
Ran Li
Professor Richard Massey r.j.massey@durham.ac.uk
Professor
Mattia Negrello
Dr Andrew Robertson andrew.robertson@durham.ac.uk
Academic Visitor
Nearly a century ago, Edwin Hubble famously classified galaxies into three distinct groups: ellipticals, spirals and irregulars (Hubble, 1926). 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 (Kormendy, 2015; Van Der Wel et al., 2012; Vulcani et al., 2014). PyAutoGalaxy is an open-source Python 3.8+ 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 imaging 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. Accompanying PyAutoGalaxy is the autogalaxy workspace, which includes example scripts, datasets and the HowToGalaxy lectures in Jupyter notebook format which introduce non-experts to studies of galaxy morphology using PyAutoGalaxy. Readers can try PyAutoGalaxy right now by going to the introduction Jupyter notebook on Binder or checkout the readthedocs for a complete overview of PyAutoGalaxy’s features.
Nightingale, J. W., Amvrosiadis, A., Hayes, R. G., He, Q., Etherington, A., Cao, X., Cole, S., Frawley, J., Frenk, C. S., Lange, S., Li, R., Massey, R. J., Negrello, M., & Robertson, A. (2023). PyAutoGalaxy: Open-Source Multiwavelength Galaxy Structure & Morphology. The Journal of Open Source Software, 8(81), Article 4475. https://doi.org/10.21105/joss.04475
Journal Article Type | Article |
---|---|
Online Publication Date | Jan 27, 2023 |
Publication Date | 2023 |
Deposit Date | Jun 22, 2023 |
Publicly Available Date | Jun 22, 2023 |
Journal | Journal of Open Source Software |
Publisher | Open Journals |
Peer Reviewed | Peer Reviewed |
Volume | 8 |
Issue | 81 |
Article Number | 4475 |
DOI | https://doi.org/10.21105/joss.04475 |
Public URL | https://durham-repository.worktribe.com/output/1170394 |
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