Last updated: 2021-06-14

Checks: 7 0

Knit directory: globalIRmap/

This reproducible R Markdown analysis was created with workflowr (version 1.6.2). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

R Markdown file: up-to-date

Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

Environment: empty

Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.

Seed: set.seed(20200414)

The command set.seed(20200414) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.

Session information: recorded

Great job! Recording the operating system, R version, and package versions is critical for reproducibility.

Cache: none

Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.

File paths: relative

Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.

Repository version: 5e433c3

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.

The results in this page were generated with repository version 5e433c3. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:


Ignored files:
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    R/.Rhistory
    Ignored:    analysis/.Rhistory
    Ignored:    renv/library/
    Ignored:    renv/staging/

Untracked files:
    Untracked:  .Rbuildignore
    Untracked:  .drake/
    Untracked:  .gitignore
    Untracked:  Compare_models_20201026.Rmd
    Untracked:  Rplots.pdf
    Untracked:  assets/
    Untracked:  figtabres.docx
    Untracked:  figtabres_20201220_1.docx
    Untracked:  figtabres_20210216.docx
    Untracked:  log/
    Untracked:  schema.ini
    Untracked:  tabs_quick.Rmd
    Untracked:  tabs_quick.docx
    Untracked:  tabs_quick.html
    Untracked:  test.html

Unstaged changes:
    Modified:   .Rprofile
    Modified:   R/IRmapping_plan.R
    Modified:   analysis/_site.yml
    Deleted:    analysis/results_diagnostics.Rmd
    Modified:   figtabres.Rmd
    Modified:   interactive.R
    Modified:   workflowr_commands.R

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/methods_gettingstarted.Rmd) and HTML (docs/methods_gettingstarted.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File	Version	Author	Date	Message
Rmd	5e433c3	messamat	2021-06-14	Publish new pages

Install the R package

This repository is organized as an R package, providing documented functions to reproduce and extend the analysis reported in the publication. Note that this package has been written explicitly for this project and may not be suitable for general use.

This project is setup with a drake workflow, ensuring reproducibility. Intermediate targets/objects will be stored in a hidden .drake directory.

The R library of this project is managed by renv. This makes sure that the exact same package versions are used when recreating the project. When calling renv::restore(), all required packages will be installed with their specific version.

Please note that this project was built with R version 4.0.3 on a Windows 10 operating system. The renv packages from this project are not compatible with R versions prior to version 3.6.0.

To copy (i.e., clone) this repository to your local machine (for Windows only, please contact author for guidance on other platforms).
In Git Bash, the following commands illustrate the procedure to make a local copy of the Github repository in a newly created directory at C://test_globalIRmap :

Mathis@DESKTOP MINGW64 /c/temp
$ cd /c/
Mathis@DESKTOP MINGW64 /c
$ mkdir test_globalIRmap
Mathis@DESKTOP MINGW64 /c
$ cd /c/test_globalIRmap
Mathis@DESKTOP MINGW64 /c/test_globalIRmap
$ git clone https://github.com/messamat/globalIRmap.git
Cloning into 'globalIRmap'...
remote: Enumerating objects: 116, done.
remote: Counting objects: 100% (116/116), done.
remote: Compressing objects: 100% (89/89), done.
remote: Total 7363 (delta 48), reused 75 (delta 19), pack-reused 7247
Receiving objects: 100% (7363/7363), 1.91 GiB | 3.78 MiB/s, done.
Resolving deltas: 100% (925/925), done.

In R Studio for Windows, the following procedure can be used:

Click on “File” in the menu ribbon
Select “New project…”
Choose the “Version control” option in the New Project Wizard window.
Then, select “Git” in the next window.
In the next window, fill the fields as follows:
- Repository URL: https://github.com/messamat/globalIRmap
- Project directory name: [will autofill as “globalIRmap”]
- Create project as subdirectory of: [choose the directory, e.g., C://test_globalIRmap]
Tick “Open in new session” and then click “Create project”.

Then open this project in R and run:

renv::restore() # restores all R packages with their specific version
r_make() # recreates the analysis

Structure of the analysis

In the drake philosophy, every R object is a “target” with dependencies. This repository contains more targets than actually needed to replicate the associated publication. Future task: create a simplified workflow to strictly reproduce main results

If you want to replicate the publication, you need to build the following targets: - - - -

Other practical notes

Notes and resources

The issues tracker is the place to report problems or ask questions
See the repository history for a fine-grained view of progress and changes.

sessionInfo()

R version 4.0.2 (2020-06-22)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19042)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252 
[2] LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] workflowr_1.6.2

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.4.6    rprojroot_1.3-2 digest_0.6.27   later_1.0.0    
 [5] R6_2.5.0        backports_1.2.1 git2r_0.27.1    magrittr_1.5   
 [9] evaluate_0.14   stringi_1.4.6   rlang_0.4.5     fs_1.4.1       
[13] promises_1.1.0  whisker_0.4     rmarkdown_2.3   tools_4.0.2    
[17] stringr_1.4.0   glue_1.4.0      httpuv_1.5.2    xfun_0.13      
[21] yaml_2.2.1      compiler_4.0.2  htmltools_0.4.0 knitr_1.28

Getting started

Install the R package

Structure of the analysis

Other practical notes

Notes and resources