pydarnio 2.1

Python data IO library for the Super Dual Auroral Radar Network (SuperDARN).

Changelog

Version 2.1 - Release!

This release includes changes to support darn-dmap up to version 0.8.2 This includes:

• removal of wrapper code deemed unnecessary
• addition of the widetx field
• updates for mode options
• indices option replacing sniff which returns the subset of records you request
• bz2 compression when returning bytes object
• bz2 compression detection rather than relying on file name

Documentation

pyDARNio's documentation can found here

Getting Started

pip install pydarnio

Or read the installation guide.

If wish to get access to SuperDARN data please read the SuperDARN data access documentation. Please make sure to also read the documentation on citing SuperDARN and pydarn.

As a quick tutorial on using pyDARNio to read a non-compressed file:

import pydarnio
fitacf_file = '20180220.C0.rkn.stream.fitacf'
records, _ = pydarnio.read_fitacf(fitacf_file)

or to read a compressed file:

import pydarnio
fitacf_file = '20180220.C0.rkn.stream.fitacf.bz2'  # note the .bz2 compression
records, _ = pydarnio.read_fitacf(fitacf_file)

For more information and tutorials on pyDARNio please see the tutorial section

Getting involved

pyDARNio is always looking for testers and developers keen on learning python, github, and/or SuperDARN data visualizations! Here are some ways to get started:

• Testing Pull Request: to determine which pull requests need to be tested right away, filter them by their milestones.
• Getting involved in projects: if you are looking to help in a specific area, look at pyDARNio's projects tab. The project you are interested in will give you information on what is needed to reach completion. This includes things currently in progress, and those awaiting reviews.
• Answer questions: if you want to try your hand at answering some pyDARNio questions, or adding to the discussion, look at pyDARNio's issues and filter by labels.
• Become a developer: if you want to practice those coding skills and add to the library, look at pyDARNio issues and filter by milestone's to see what needs to get done right away.

Please contact the Data Visualization Working Group, if you would like to become a member of the team!