In adamhsparks/glint: Global ('GSOD') Interpolated Temperatures

Research compendium for a report on interpolating GSOD weather data

Compendium DOI:

http://dx.doi.org/xxxxxxx

The files at the URL above will generate the results as found in the publication. The files hosted at https://github.com/adamhsparks/glint are the development versions and may have changed since the report was published

Authors of this repository:

Adam H Sparks ([e-mail])

Published in:

Overview of contents

This repository is our research compendium that details our methodology for interpolating GSOD weather data to create a global surface of daily weather data for maximum, minimum and mean daily temperature and relative humidity. The compendium contains all data, code, and text associated with the publication. The Rmd files in the inst/paper/ directory contain details of how all the analyses reported in the paper were conducted. Instructions on how to rerun the analysis to reproduce the results are found in the vignette, in the vingettes/ directory.

The supplementary files

The inst/ directory contains:

• the manuscript as submitted (in MS Word format) and its Rmd source file (in the paper/ directory)

• supplementary information source files (in R markdown format) and executed versions

• all the figures that are included in the paper (in the figures/ directory)

The R package

This repository is organized as an R package. There are no actual R functions in this package - all the R code is in the Rmd file. I simply used the R package structure to help manage dependencies, to take advantage of continuous integration for automated code testing, and so I didn't have to think too much about how to organise the files.

To download the package source as you see it on GitHub, for off-line browsing, use this line at the shell prompt (assuming you have Git installed on your computer):

git clone https://github.com/adamhsparks/glint.git

Once the download is complete, open the glint.Rproj in RStudio to begin working with the package and compendium files.

The package has a number of dependencies on other R packages, and programs outside of R. These are listed at the bottom of this README. Installing these can be time-consuming and complicated, so we've done two things to simplify access to the compendium. First is that we have used checkpoint, which will install packages as they existed on CRAN at a specific date as a part of your local library. If all works well, these will be installed on your computer when you open glint.Rproj in RStudio. Second is our Docker image that includes all the necessary software, code and data to run our analysis. The Docker image may give a quicker entry point to the project, and is more self-contained, so might save some fiddling with installing things.

The Docker image

A Docker image is a lightweight GNU/Linux virtual computer that can be run as a piece of software on Windows and OSX (and other Linux systems). To capture the complete computational environment used for this project we have a Dockerfile that specifies how to make the Docker image that we developed this project in. The Docker image includes all of the software dependencies needed to run the code in this project, as well as the R package and other compendium files. To launch the Docker image for this project, first, install Docker on your computer. At the Docker prompt, enter:

$ docker run -dp 8787:8787 adamhsparks/glint

This will start a server instance of RStudio. Then open your web browser at localhost:8787 or or run docker-machine ip default in the shell to find the correct IP address, and log in with rstudio/rstudio.

Once logged in, use the Files pane (bottom right) to navigate to / (the root directory), then open the folder for this project, and open the .Rproj file for this project. Once that's open, you'll see the analysis/paper directory in the Files pane where you can find the R markdown document, and knit them to produce the results in the paper. More information about using RStudio in Docker is available at the Rocker wiki pages.

We developed and tested the package on this Docker container, so this is the only platform that We're confident it works on, and so recommend to anyone wanting to use this package to generate the vignette, etc.

Licenses

Manuscript: CC-BY-4.0

Code: MIT year: r format(Sys.Date(), "%Y"), copyright holder: Adam H Sparks

Data: CC-0 attribution requested in reuse

Dependencies

We used RStudio on MacOS and Ubuntu 16.04 LTS.

Contact

Adam H. Sparks, Senior Research Scientist DPIRD Perth, Western Australia 6000

p. (+61) (8) 9368 3689 e. [e-mail] w. https://adamhsparks.netlify.app

Credits

This research compendium was based on https://github.com/benmarwick/researchcompendium but not forked from because it was already under development when I found Ben's.

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

adamhsparks/glint documentation built on Jan. 31, 2023, 3:21 p.m.