Статья

Stingray: A Modern Python Library for Spectral Timing

Daniela HuppenkothenDIRAC Institute, Department of Astronomy, University of Washington, 3910 15th Avenue NE, Seattle, WA 98195, USA; [email protected]Matteo BachettiINAF-Osservatorio Astronomico di Cagliari, via della Scienza 5, I-09047 Selargius (CA), ItalyAbigail StevensDepartment of Astronomy, University of Michigan, 1085 South University Avenue, Ann Arbor, MI 48109, USASimone MigliariESAC/ESA, XMM-Newton Science Operations Centre, Camino Bajo del Castillo s/n, Urb. Villafranca del Castillo, SE-28692, Villanueva de la Caada, Madrid, SpainPaul BalmTimelab Technologies Ltd., 20-22 Wenlock Road, London N1 7GU, UKOmar HammadAinShams University, Cairo, EgyptUsman Mahmood KhanDepartment of Computer Science, North Carolina State University, Raleigh, NC, USAHimanshu MishraIndian Institute of Technology, Kharagpur West Bengal 721302, IndiaHaroon RashidNational University of Sciences and Technology (NUST), Islamabad 44000, PakistanSwapnil SharmaIndian Institute of Technology Mandi, Mandi, Himachal Pradesh, IndiaEvandro Martinez RibeiroKapteyn Astronomical Institute, University of Groningen, P.O. Box 800, NL-9700 AV Groningen, The NetherlandsRicardo Valles BlancoTimelab Technologies Ltd., 20-22 Wenlock Road, London N1 7GU, UK

2019en

ABI

Аннотация

Abstract 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.

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Идентификаторы

DOI: 10.3847/1538-4357/ab258d

Цитирования и источники

Цитирований: 2Использованных источников: 0

Показатели — AkademScholar