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The Super Dual Auroral Radar Network (SuperDARN) is an international network of high frequency coherent scatter radars that are used for monitoring the electrodynamics of the Earth’s upper atmosphere at middle, high, and polar latitudes in both hemispheres. pyDARN is an open-source Python-based library developed specifically for visualizing SuperDARN radar data products. It provides various plotting functions of different types of SuperDARN data, including time series plot, range-time parameter plot, fields of view, full scan, and global convection map plots. In this paper, we review the different types of SuperDARN data products, pyDARN’s development history and goals, the current implementation of pyDARN, and various plotting and analysis functionalities. We also discuss applications of pyDARN, how it can be combined with other existing Python software for scientific analysis, challenges for pyDARN development and future plans. Examples showing how to read, visualize, and interpret different SuperDARN data products using pyDARN are provided as a Jupyter notebook.
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Replication Data for: Search for High-Energy Neutrinos From the Sun Using Ten Years of IceCube Data
Data and plotting scripts for reproducing plots from Search for High-Energy Neutrinos From the Sun Using Ten Years of IceCube Data Contents: - paper_plots.h5: Data used to make plots - paper_plots.py: Python script for making plots - paper.mplstyle: Matplotlib style file to set plotting defaults - README.md
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- Award ID(s):
- 2042807
- PAR ID:
- 10668194
- Publisher / Repository:
- Harvard Dataverse
- Date Published:
- Edition / Version:
- 1.0
- Subject(s) / Keyword(s):
- Astronomy and Astrophysics Physics Dark matter Solar neutrinos
- Format(s):
- Medium: X Size: 3822920; 1059; 23783; 695 Other: application/x-h5; application/octet-stream; text/x-python-script; text/markdown
- Size(s):
- 3822920 1059 23783 695
- Sponsoring Org:
- National Science Foundation
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