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loadeR

An R package for climate data access building on the NetCDF-Java API.
https://github.com/SantanderMetGroup/loadeR

Category: Climate Change
Sub Category: Climate Data Access and Visualization

Keywords from Contributors

climate-change-atlas climate4r cmip6 cordex ipcc-regions warming-levels

Last synced: about 10 hours ago
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Repository metadata

A climate4R package for data access

README.md

What is loadeR?

loadeR is an R package for climate data access building on the NetCDF-Java API. It allows user-friendly data access either from local or remote locations (e.g. OPeNDAP servers) and it is fully integrated with the User Data Gateway (UDG), a Climate Data Service deployed and maintained by the Santander Meteorology Group. loadeR has been conceived to work in the framework of both seasonal forecasting and climate change studies. Thus, it considers ensemble members as a basic dimension of its two main data structures (grid and station). Find out more about this package at the loadeR wiki.

This package is part of the climate4R framework, formed by loadeR, transformeR, downscaleR, visualizeR and other packages dealing with climate data analysis and visualization.

The recommended installation procedure (for loader and the companion loadeR.java and climate4R.UDG packages) is to use the install_github command from the devtools R package (see the installation info in the wiki):

devtools::install_github(c("SantanderMetGroup/loadeR.java", "SantanderMetGroup/climate4R.UDG", "SantanderMetGroup/loadeR"))

IMPORTANT: On OS X, be sure to execute this in R started from the Terminal, not the R App! (This is because the R app doesn’t honor $PATH changes in ~/.bash_profile)

IMPORTANT: The package requires Java version 1.7 or higher. Several recommendations for known problems with R and Java are given in the wiki installation info).

NOTE: loadeR is enhanced by loadeR.ECOMS package which allows to remotely access harmonized data from several state-of-the-art seasonal forecasting databases stored at the ECOMS-UDG.


Reference and further information:

[General description of the climate4R framework] Iturbide et al. (2019) The R-based climate4R open framework for reproducible climate data access and post-processing. Environmental Modelling and Software, 111, 42-54. https://doi.org/10.1016/j.envsoft.2018.09.009
Check out the companion notebooks with worked examples.

[Statistical Downscaling] Bedia et al. (2020). Statistical downscaling with the downscaleR package (v3.1.0): contribution to the VALUE intercomparison experiment. Geoscientific Model Development, 13, 1711–1735. https://doi.org/10.5194/gmd-13-1711-2020

[Seasonal forecasting applications] Cofiño et al. (2018) The ECOMS User Data Gateway: Towards seasonal forecast data provision and research reproducibility in the era of Climate Services. Climate Services, 9, 33-43. http://doi.org/10.1016/j.cliser.2017.07.001

[Example of a sectoral application (fire danger)] Bedia et al. (2018) Seasonal predictions of Fire Weather Index: Paving the way for their operational applicability in Mediterranean Europe. Climate Services, 9, 101-110. http://doi.org/10.1016/j.cliser.2017.04.001


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Last synced: 5 days ago

Total Commits: 390
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Avg Commits per committer: 43.333
Development Distribution Score (DDS): 0.554

Commits in past year: 7
Committers in past year: 2
Avg Commits per committer in past year: 3.5
Development Distribution Score (DDS) in past year: 0.286

Name Email Commits
jbedia j****a@g****m 174
Your Name m****e@g****m 127
Sixto Herrera García h****s@u****s 55
Jose M. Gutierrez g****m@u****s 19
Jorge b****a@i****s 6
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Jorge Bano Medina j****a@M****l 3
Etienne Tourigny e****y@b****s 1
jesusff j****f 1

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Last synced: 1 day ago

Total issues: 81
Total pull requests: 5
Average time to close issues: 4 months
Average time to close pull requests: 6 months
Total issue authors: 47
Total pull request authors: 5
Average comments per issue: 2.37
Average comments per pull request: 2.0
Merged pull request: 2
Bot issues: 0
Bot pull requests: 0

Past year issues: 2
Past year pull requests: 0
Past year average time to close issues: N/A
Past year average time to close pull requests: N/A
Past year issue authors: 2
Past year pull request authors: 0
Past year average comments per issue: 0.5
Past year average comments per pull request: 0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0

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Package metadata

proxy.golang.org: github.com/santandermetgroup/loader

conda-forge.org: r-loader

  • Homepage: https://github.com/SantanderMetGroup/climate4R
  • Licenses: GPL-3.0-or-later
  • Latest release: 1.7.1 (published almost 3 years ago)
  • Last Synced: 2025-04-02T02:14:00.345Z (26 days ago)
  • Versions: 2
  • Dependent Packages: 2
  • Dependent Repositories: 2
  • Rankings:
    • Dependent packages count: 19.581%
    • Dependent repos count: 20.06%
    • Average: 33.902%
    • Forks count: 42.521%
    • Stargazers count: 53.446%
conda-forge.org: r-loader.2nc

  • Homepage: https://github.com/SantanderMetGroup/loadeR/wiki
  • Licenses: GPL-3.0-or-later
  • Latest release: 0.1.2 (published almost 3 years ago)
  • Last Synced: 2025-04-26T12:34:22.096Z (1 day ago)
  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 2
  • Rankings:
    • Dependent repos count: 20.06%
    • Average: 41.892%
    • Forks count: 42.521%
    • Dependent packages count: 51.54%
    • Stargazers count: 53.446%

Dependencies

DESCRIPTION cran
  • R >= 3.5.0 depends
  • climate4R.UDG >= 0.2.0 depends
  • loadeR.java * depends
  • rJava * depends
  • RCurl * imports
  • abind * imports
  • utils * imports
  • downscaleR * suggests
  • loadeR.ECOMS * suggests
  • transformeR * suggests
  • visualizeR * suggests

Score: 7.901007051992421