Stingray: A Modern Python Library for Spectral Timing

This paper describes the design and implementation of stingray, a library in Python built to perform time series analysis and related tasks on astronomical light curves. Its core functionality comprises a range of Fourier analysis techniques commonly used in spectral-timing analysis, as well as exte...

Full description

Saved in:
Bibliographic Details
Published in:The Astrophysical journal Vol. 881; no. 1; pp. 39 - 52
Main Authors: Huppenkothen, Daniela, Bachetti, Matteo, Stevens, Abigail L., Migliari, Simone, Balm, Paul, Hammad, Omar, Khan, Usman Mahmood, Mishra, Himanshu, Rashid, Haroon, Sharma, Swapnil, Ribeiro, Evandro Martinez, Blanco, Ricardo Valles
Format: Journal Article
Language:English
Published: Philadelphia The American Astronomical Society 10.08.2019
IOP Publishing
Subjects:
ISSN:0004-637X, 1538-4357
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper describes the design and implementation of stingray, a library in Python built to perform time series analysis and related tasks on astronomical light curves. Its core functionality comprises a range of Fourier analysis techniques commonly used in spectral-timing analysis, as well as extensions for analyzing pulsar data, simulating data sets, and statistical modeling. Its modular build allows for easy extensions and incorporation of its methods into data analysis workflows and pipelines. We aim for the library to be a platform for the implementation of future spectral-timing techniques. We describe the overall vision and framework, core functionality, extensions, and connections to high-level command-line and graphical interfaces. The code is well tested, with a test coverage of currently 95%, and is accompanied by extensive Application Program Interface (API) documentation and a set of step-by-step tutorials.
Bibliography:AAS15712
Instrumentation, Software, Laboratory Astrophysics, and Data
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0004-637X
1538-4357
DOI:10.3847/1538-4357/ab258d