cmarmo
commented
5 months ago Editor in Chief checks
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Editor comments
Stingray is in excellent form! 💪 Congratulations! I am going to check the availability of our Astropy editors and we will be back to you shortly.
hamogu
matteobachetti
masonng-astro
taldcroft
Submitting Author: @matteobachetti All current maintainers: @dhuppenkothen, @mgullik, @jdswinbank, @matteolucchini1 Package Name: Stingray One-Line Description of Package: A spectral-timing software package for astrophysical X-ray (and other) data Repository Link: https://github.com/stingraysoftware/stingray
Version submitted: 2.1 EiC: @cmarmo Editor: @hamogu
JOSS DOI: 10.21105/joss.07389
Version accepted: 2.1
Date accepted (month/day/year): 10/01/2024
Reviewer 1: @taldcroft Reviewer 2: @masonng-astro Archive:
Code of Conduct & Commitment to Maintain Package
Description
Stingray is a Python library for "spectral timing", i.e. time-series analysis techniques that can be used to study how variability changes or correlates between different energy bands/wavelengths. It is Astropy-affiliated, and with an ever growing user base now comprising hundreds of researchers around the globe.
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This package is mostly focused on the analysis of new data from high-energy missions. We added data validation and testing because it can be used as a quick look tool to point out possible anomalies in observations (e.g. solar or other background flares).
The target audience is principally researchers and students of X-ray and multi-wavelength astronomy. This package fills a void for a free and open source (spectral-)timing package for X-ray astronomy. XRONOS, formerly maintained by HEASARC, is currently unmaintained, and the analysis of high-energy timeseries is done mostly with proprietary software or mission-specific packages. We provide a Python package that eases the learning curve for newcomers, also thanks to extensive tutorials based on Jupyter notebooks, and provides experts with a powerful, robust library for their analysis. We provide software to analyze astronomical time series and do a number of things, including periodicity searches, time lag calculations, covariance spectra, power spectral modeling.
Our package is arguably the most well-known Python package for X-ray spectral timing.
@tagthe editor you contacted:https://github.com/pyOpenSci/software-submission/issues/195
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