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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.22741 |
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| _version_ | 1866913059355754496 |
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| author | Kempton, Dustin Goodwin, Griffin Thippareddy, Tarun Kumar Reddy Gupta, Reet Sadykov, Viacheslav Angryk, Rafal |
| author_facet | Kempton, Dustin Goodwin, Griffin Thippareddy, Tarun Kumar Reddy Gupta, Reet Sadykov, Viacheslav Angryk, Rafal |
| contents | swdatatoolkit is a Python-based scientific software library designed to support the acquisition, preprocessing, and analysis of solar and space weather data. The toolkit consolidates functionality across multiple domains, including data downloading from established heliophysics sources, image preprocessing, edge detection, image texture quantification, magnetic field analysis, and the derivation of higher-level parameters commonly used in solar physics research. Its modular structure reflects the heterogeneous nature of space weather data and enables reproducible, extensible workflows for both exploratory analysis and machine-learning-driven studies. This paper presents an overview of the library's available capabilities, its scientific motivations, and its role in the broader space weather research ecosystem. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_22741 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Describing the swdatatoolkit: A Space Weather Data Analysis Library Kempton, Dustin Goodwin, Griffin Thippareddy, Tarun Kumar Reddy Gupta, Reet Sadykov, Viacheslav Angryk, Rafal Instrumentation and Methods for Astrophysics Solar and Stellar Astrophysics J.2; D.2.13 swdatatoolkit is a Python-based scientific software library designed to support the acquisition, preprocessing, and analysis of solar and space weather data. The toolkit consolidates functionality across multiple domains, including data downloading from established heliophysics sources, image preprocessing, edge detection, image texture quantification, magnetic field analysis, and the derivation of higher-level parameters commonly used in solar physics research. Its modular structure reflects the heterogeneous nature of space weather data and enables reproducible, extensible workflows for both exploratory analysis and machine-learning-driven studies. This paper presents an overview of the library's available capabilities, its scientific motivations, and its role in the broader space weather research ecosystem. |
| title | Describing the swdatatoolkit: A Space Weather Data Analysis Library |
| topic | Instrumentation and Methods for Astrophysics Solar and Stellar Astrophysics J.2; D.2.13 |
| url | https://arxiv.org/abs/2604.22741 |