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Presubmission inquiry for Stingray #195

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@matteobachetti

Description

@matteobachetti

Submitting Author: Name @matteobachetti
Package Name: Stingray
One-Line Description of Package: A spectral-timing software package for astrophysical X-ray (and other) data
Repository Link (if existing): github.com/stingraysoftware/stingray


Code of Conduct & Commitment to Maintain Package

Description

  • Include a brief paragraph describing what your package does:

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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Scope

  • Please indicate which category or categories.
    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 visualization
    • Workflow automation
    • Citation management and bibliometrics
    • Scientific software wrappers
    • Database interoperability

Domain Specific

  • Geospatial

  • Education

  • Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:

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).

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

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.

  • Are there other Python packages that accomplish similar things? If so, how does yours differ?

Our package is arguably the most well-known Python package for X-ray spectral timing.

  • Any other questions or issues we should be aware of:

We are alread Astropy-affiliated, and we wish to update the affiliation through the PyOpenSci infrastructure and standards. We have a 2019 JOSS paper, that we would like to update.

P.S. Have feedback/comments about our review process? Leave a comment here

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