Skip to main content

Time Series Methods For Astronomical X-ray Data

Project description

Usage

Release

Development

Community

Python Version from PEP 621 TOML

GitHub release

Build Status Master

Slack

Docs

joss

Project Status: Active – The project has reached a stable, usable state and is being actively developed.

pyOpenSci Peer-Reviewed

License

doi

Coverage Status Master

X-Ray Spectral Timing Made Easy

Stingray is a spectral-timing software package for astrophysical X-ray (and other) data. Stingray merges existing efforts for a (spectral-)timing package in Python, and is structured with the best guidelines for modern open-source programming, following the example of Astropy.

It provides:

  • a library of time series methods, including power spectra, cross spectra, covariance spectra, lags, and so on;

  • a set of scripts to load FITS data files from different missions;

  • a light curve and event list simulator, with the ability to simulate different kinds of variability and more complicated phenomena based on the impulse response of given physical events (e.g. reverberation).

There are a number of official software packages for X-ray spectral fitting (Xspec, ISIS, Sherpa, …). However, an equivalent widely-used package does not exist for X-ray timing: to date, that has generally been done with custom software. Stingray aims not only to fill that gap, but also to provide implementations of the most advanced spectral timing techniques available in the literature. The ultimate goal of this project is to provide the community with a package that eases the learning curve for the advanced spectral timing techniques with a correct statistical framework.

More details of current and planned capabilities are available in the Stingray documentation.

Installation and Testing

Stingray can be installed via conda, pip, or directly from the source repository itself. Our documentation provides comprehensive installation instructions.

After installation, it’s a good idea to run the test suite. We use py.test and tox for testing, and, again, our documentation provides step-by-step instructions.

Documentation

Stingray’s documentation can be found at https://docs.stingray.science/.

Getting In Touch, and Getting Involved

We welcome contributions and feedback, and we need your help! The best way to get in touch is via the issues_ page. We’re especially interested in hearing from you:

  • If something breaks;

  • If you spot missing functionality, find the API unintuitive, or have suggestions for future development;

  • If you have your own code implementing any of the methods provided Stingray and it produces different answers.

Even better: if you have code you’d be willing to contribute, please send a pull request or open an issue.

Citing Stingray

If you find this package useful in your research, please provide appropriate acknowledgement and citation. Our documentation gives further guidance, including links to appropriate papers and convenient BibTeX entries.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

stingray-2.2.tar.gz (71.8 MB view details)

Uploaded Source

Built Distribution

stingray-2.2-py3-none-any.whl (55.4 MB view details)

Uploaded Python 3

File details

Details for the file stingray-2.2.tar.gz.

File metadata

  • Download URL: stingray-2.2.tar.gz
  • Upload date:
  • Size: 71.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.8

File hashes

Hashes for stingray-2.2.tar.gz
Algorithm Hash digest
SHA256 a57d79c55e05a6970b88c3c3c7b24750d41f71becbddc1a4a64ebcef78cfc847
MD5 71046b69462a069e5ea3ed215b4844b6
BLAKE2b-256 35e603d990ebc57c5c07984069b31d21334597a066b3488c2dd86e8a66961801

See more details on using hashes here.

File details

Details for the file stingray-2.2-py3-none-any.whl.

File metadata

  • Download URL: stingray-2.2-py3-none-any.whl
  • Upload date:
  • Size: 55.4 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.8

File hashes

Hashes for stingray-2.2-py3-none-any.whl
Algorithm Hash digest
SHA256 12106c5e01ffbefd088f523f4f6c1a84f39a0754b379f12bb1a392dd844a5194
MD5 b9c1b2e272069bbf5fd7cd506d484468
BLAKE2b-256 24254228495701c6d384dd061d79a7c0696a1302df07745fbf47a025df481a4c

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page