pydarnio

Python Library for read in SuperDARN data

https://github.com/superdarn/pydarnio

Science Score: 59.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 3 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Committers with academic emails
    1 of 17 committers (5.9%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (14.7%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

Python Library for read in SuperDARN data

Basic Info
  • Host: GitHub
  • Owner: SuperDARN
  • License: lgpl-3.0
  • Language: Python
  • Default Branch: develop
  • Size: 2.07 MB
Statistics
  • Stars: 9
  • Watchers: 11
  • Forks: 2
  • Open Issues: 9
  • Releases: 7
Created over 5 years ago · Last pushed 7 months ago
Metadata Files
Readme License Zenodo

README.md

pyDARNio

License: LGPL v3 Python 3.8 GitHub release (latest by date) DOI

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

Changelog

Version 1.3 - Release!

This release includes changes to support Borealis v0.7 files, snd files, and removes the deprecated deepdish dependency.

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: python3 import pydarnio fitacf_file = '20180220.C0.rkn.stream.fitacf' records = pydarnio.read_fitacf(fitacf_file)

or to read a compressed file: python3 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!

Owner

  • Name: SuperDARN
  • Login: SuperDARN
  • Kind: organization

Github for the international Super Dual Auroral Radar Network (SuperDARN) community

GitHub Events

Total
  • Watch event: 1
  • Delete event: 2
  • Issue comment event: 7
  • Push event: 14
  • Pull request event: 3
  • Create event: 2
Last Year
  • Watch event: 1
  • Delete event: 2
  • Issue comment event: 7
  • Push event: 14
  • Pull request event: 3
  • Create event: 2

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 115
  • Total Committers: 17
  • Avg Commits per committer: 6.765
  • Development Distribution Score (DDS): 0.6
Top Committers
Name Email Commits
mts299 m****t@g****m 46
Marina Schmidt m****8@g****m 12
Remington Rohel r****9@u****a 10
Remington Rohel r****l@u****a 8
carleyjmartin c****n@h****m 8
RemingtonRohel 7****l@u****m 7
Kevin Krieger k****r@g****m 6
mardet987 m****r@g****m 4
Emma Bland e****d@u****o 4
carleyjmartin 6****n@u****m 2
Angeline Burrell a****l@u****m 2
Evan Thomas e****s@d****u 1
mardet987 m****r@u****a 1
radar r****r@b****a 1
Keith Kotyk k****k@g****m 1
Marina Schmidt m****t@u****a 1
Devin Huyghebaert d****t@g****m 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 37
  • Total pull requests: 40
  • Average time to close issues: 11 months
  • Average time to close pull requests: about 2 months
  • Total issue authors: 15
  • Total pull request authors: 8
  • Average comments per issue: 2.08
  • Average comments per pull request: 2.15
  • Merged pull requests: 33
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 5
  • Average time to close issues: 16 days
  • Average time to close pull requests: 3 months
  • Issue authors: 2
  • Pull request authors: 2
  • Average comments per issue: 1.5
  • Average comments per pull request: 3.0
  • Merged pull requests: 3
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • carleyjmartin (8)
  • mts299 (6)
  • RemingtonRohel (6)
  • aburrell (3)
  • alexchartier (3)
  • tjk584 (2)
  • ecbland (1)
  • egthomas (1)
  • billetd (1)
  • Cooper10 (1)
  • mardet987 (1)
  • Shirling-VT (1)
  • lkilcommons (1)
  • SamRennie (1)
  • kkotyk (1)
Pull Request Authors
  • RemingtonRohel (25)
  • mts299 (6)
  • aburrell (5)
  • carleyjmartin (4)
  • egthomas (3)
  • mardet987 (1)
  • ecbland (1)
  • kevinkrieger (1)
Top Labels
Issue Labels
bug (5) enhancement (4) help wanted (1) documentation (1)
Pull Request Labels
enhancement (8) bug (3)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 251 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 2
  • Total versions: 6
  • Total maintainers: 4
pypi.org: pydarnio

Python library for reading and writing SuperDARN data

  • Versions: 6
  • Dependent Packages: 1
  • Dependent Repositories: 2
  • Downloads: 251 Last month
  • Docker Downloads: 0
Rankings
Docker downloads count: 4.3%
Dependent packages count: 4.8%
Dependent repos count: 11.5%
Average: 14.6%
Stargazers count: 20.4%
Forks count: 22.7%
Downloads: 23.8%
Last synced: 7 months ago

Dependencies

setup.py pypi
  • deepdish *
  • h5py *
  • numpy *
  • pathlib2 *
  • pyyaml *
pyproject.toml pypi