Latest commit 96f838f Apr 18, 2017 @matteobachetti matteobachetti committed on GitHub Merge pull request #185 from StingraySoftware/lc_baseline
Baseline of light curve improved



Master Build Status Master Readthedocs Slack Coverage Status Master

X-Ray Spectral Timing Made Easy

Stingray is an in-development spectral-timing software package for astrophysical X-ray (and more) 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 is composed of:

  1. a library of time series methods, including power spectra, cross spectra, covariance spectra, lags, and so on;
  2. a set of scripts to load FITS data files from different missions;
  3. a simulator of light curves and event lists, that includes different kinds of variability and more complicated phenomena based on the impulse response of given physical events (e.g. reverberation);
  4. finally, an in-development GUI to ease the learning curve for new users.

There are a number of official software packages for X-ray spectral fitting (Xspec, ISIS, Sherpa, ...). Such a widely used and standard software package does not exist for X-ray timing, that remains for now mostly done with custom software. Stingray aims not only at becoming a standard timing package, but at extending the implementation to 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.

Note to Users

Stingray is currently in development phase. Some of the code is not in its final stage, and might change before our first release. There might also still be bugs we are working on fixing and features that are not finished.

We encourage you to download it and try it out, but please be aware of the caveats of working with in-development code. At the same time, we welcome contributions and we need your help! If you have your own code duplicating any part of the methods implemented in Stingray, please try out Stingray and compare to your own results.

We do welcome any sort of feedback: if something breaks, please report it via the issues page. Similarly, please open an issue if any functionality is missing, the API is not intuitive or if you have suggestions for additional functionality that would be useful to have.

If you have code you might want to contribute, we'd love to hear from you, either via a pull request or via an issue.


  • make a light curve from event data
  • make periodograms in Leahy and rms normalization
  • average periodograms
  • maximum likelihood fitting of periodograms/parametric models
  • cross spectra and lags (time vs energy, time vs frequency)
  • coherence
  • simulate a light curve with a given power spectrum
  • simulate a light curve from another light curve and a 1-d (time) or 2-d (time-energy) impulse response
  • simulate an event list from a given light curve _and_ with a given energy spectrum
  • load event lists from fits files of a few missions (RXTE/PCA, NuSTAR/FPM, XMM-Newton/EPIC)

Future Additions

  • cross correlation functions,
  • bispectra (?)
  • spectral-timing functionality
  • Bayesian QPO searches
  • power colours
  • rms spectra
  • full HEASARC-compatible mission support
  • graphical interface
  • (...) Feel free to propose! Use the Issues page!


  1. Clone our project from github (remember about including --recursive flag due to our submodule(s)):

    $ git clone --recursive
  2. Go to already created directory and install all dependencies:

    $ pip install -r requirements.txt
  3. Go back to stingray project directory and execute:

    $ python install


Is hosted at

And is generated using Sphinx. Try:

$ sphinx-build docs docs/_build

Then open ./docs/_build/index.html in the browser of your choice.

Test suite

Stingray uses py.test for testing. To run the tests, try:

$ python test


All content © 2015 the authors. The code is distributed under the MIT license.

Pull requests are welcome! If you are interested in the further development of this project, please get in touch via the issues!