Back to Search Start Over

SunPy - Python for Solar Physics

Authors :
N. Freij
Tomas Meszaros
Russell J. Hewett
Jose Iván Campos-Rozo
John G Evans
David Pérez-Suárez
Samuel Bennett
Florian Mayer
Steven Christe
Jack Ireland
Albert Y. Shih
Michael Malocha
Thomas P. Robitaille
Benjamin Mampaey
Andrew J. Leonard
Keith Hughitt
Stuart Mumford
Ankit Agrawal
Simon Liedtke
Michael S. Kirk
Andrew Inglis
Publication Year :
2015

Abstract

This paper presents SunPy (version 0.5), a community-developed Python package for solar physics. Python, a free, cross-platform, general-purpose, high-level programming language, has seen widespread adoption among the scientific community, resulting in the availability of a large number of software packages, from numerical computation (NumPy, SciPy) and machine learning (scikit-learn) to visualization and plotting (matplotlib). SunPy is a data-analysis environment specializing in providing the software necessary to analyse solar and heliospheric data in Python. SunPy is open-source software (BSD licence) and has an open and transparent development workflow that anyone can contribute to. SunPy provides access to solar data through integration with the Virtual Solar Observatory (VSO), the Heliophysics Event Knowledgebase (HEK), and the HELiophysics Integrated Observatory (HELIO) webservices. It currently supports image data from major solar missions (e.g., SDO, SOHO, STEREO, and IRIS), time-series data from missions such as GOES, SDO/EVE, and PROBA2/LYRA, and radio spectra from e-Callisto and STEREO/SWAVES. We describe SunPyʼs functionality, provide examples of solar data analysis in SunPy, and show how Python-based solar data-analysis can leverage the many existing tools already available in Python. We discuss the future goals of the project and encourage interested users to become involved in the planning and development of SunPy.

Details

Language :
English
ISSN :
17494680
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....a14da1b8281f4b7da73395ff42a5f828