{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/stingray-a-modern-python-library-for-spectral","title":"Stingray: A Modern Python Library For Spectral Timing","arxiv_id":"1901.07681","date":"2019-01-23","proceeding":null,"authors":["D. Huppenkothen","M. Bachetti","A. L. Stevens","S. Migliari","P. Balm","O. Hammad","U. M. Khan","H. Mishra","H. Rashid","S. Sharma","R. V. Blanco","E. M. Ribeiro"],"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. Here, 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 API documentation and a set of step-by-step tutorials.","url_abs":"https://arxiv.org/abs/1901.07681v1","url_pdf":"https://arxiv.org/pdf/1901.07681v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"stingray-a-modern-python-library-for-spectral","repo_url":"https://github.com/StingraySoftware/stingraypaper","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"stingray-a-modern-python-library-for-spectral","repo_url":"https://github.com/StingraySoftware/stingray","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}