Code
x <- rnorm(10)1 Introduction
1.1 About this document
This document, accompanied with the hopefully finely tuned git repos, provides a template for writing contributions to Computo (Computo Team 2020). We show how R code (R Core Team 2020) can be included and how the repository can be set up for triggering github actions for rendering the document, with dependencies handled by renv.
1.2 Setup a github repository for preparing your submission
You can start by clicking the “use this template” button, on the top of the page of the github repository associated to this document. Of course, you can set your repository private during the preparation of your manuscript.
1.3 Quarto
Quarto is a versatile formatting system for authoring documents integrating markdown, LaTeX and code blocks interpreted either via Jupyter or Knitr (thus supporting Python, R and Julia). It relies on the Pandoc document converter.
1.4 Requirements
You need quarto installed on your system and the Computo extension to prepare your document. For the latter, once quarto is installed, run the following to install the extension in the current directory (it creates a _extension directory which is ignored by git thanks to .gitignore by default):
quarto add computorg/computo-quarto-extensionR and the following R packages must be installed on your computer: knitr, markdown.
1.5 Link with your usual tools
Quarto is expecting a .qmd markdown file, but will also works with a standard Rmarkdown (.Rmd) file. In addition, especially if you are not comfortable with the command line interface, quarto is fully integrated inside the Rstudio IDE so that you can write and build your quarto document inside Rstudio.
Quarto can also process a Jupyter notebook file if you are used to it (it will just require to add the proper YAML metadata1).
Note: More advanced Jupyter-related functionality like Myst/Jupyter book are not supported in this Quarto setup. The markdown syntax inside the Jupyter notebook should follow the Quarto syntax (c.f. below). If you are more comfortable with using Myst/Jupyter book, we provide a specific template but it will requires more formatting work for Computo editorial team, thus highly encourage authors to use the Quarto templates.
2 Formatting
This section covers basic formatting guidelines for quarto documents.
To render a document, run quarto render. By default, both PDF and HTML documents are generated:
quarto render template-computo-R.qmd # will render both to html and PDF
Note
To check the syntax of the formatting below, you can use the </> source button at the top left of this document.
2.1 Basic markdown formatting
Bold text or italic
- This is a list
- With more elements
- It isn’t numbered.
But we can also do a numbered list
- This is my first item
- This is my second item
- This is my third item
2.2 Mathematics
2.2.1 Mathematical formulae
LaTeX code is natively supported2, which makes it possible to use mathematical formulae:
f(x_1, \dots, x_n; \mu, \sigma^2) = \frac{1}{\sigma \sqrt{2\pi}} \exp{\left(- \frac{1}{2\sigma^2}\sum_{i=1}^n(x_i - \mu)^2\right)}
It is also posible to cross-reference an equation, see Equation 1:
\begin{aligned} D_{x_N} & = \frac12 \left[\begin{array}{cc} x_L^\top & x_N^\top \end{array}\right] \, \left[\begin{array}{cc} L_L & B \\ B^\top & L_N \end{array}\right] \, \left[\begin{array}{c} x_L \\ x_N \end{array}\right] \\ & = \frac12 (x_L^\top L_L x_L + 2 x_N^\top B^\top x_L + x_N^\top L_N x_N), \end{aligned} \tag{1}
2.2.2 Theorems and other amsthem-like environments
Quarto includes a nice support for theorems, with predefined prefix labels for theorems, lemmas, proposition, etc. see this page. Here is a simple example:
Theorem 1 (Strong law of large numbers) The sample average converges almost surely to the expected value:
\overline{X}_n\ \xrightarrow{\text{a.s.}}\ \mu \qquad\textrm{when}\ n \to \infty.
See Theorem 1.
2.3 R Code
Quarto uses either Jupyter or knitr to render code chunks. This can be triggered in the yaml header. In this tutorial, we use knitr (R and packages knitr, markdown must be installed on your computer).
---
title: "My Document"
author "Jane Doe"
---R code (R Core Team 2020) chunks may be embedded as follows:
2.4 Figures
Plots can be generated as follows:
Code
library("ggplot2")
p <- ggplot(mpg, aes(displ, hwy)) +
geom_point() +
geom_smooth()
p
It is also possible to create figures from static images:
Note: Until Quarto version 1.3+ is released, including a remote image (from a web URL) in a document (like the image above) will work in the rendered HTML document but will generate an error when building the PDF document (c.f. related bug report).
2.5 Tables
Tables (with label: @tbl-mylabel renders Table 1) can be generated with markdown as follows
| Tables | Are | Cool |
|---|---|---|
| col 1 is | left-aligned | $1600 |
| col 2 is | centered | $12 |
| col 3 is | right-aligned | $1 |
Table can also be generated by some code, for instance with knitr here:
Code
knitr::kable(summary(cars), caption = "Table caption.")| speed | dist | |
|---|---|---|
| Min. : 4.0 | Min. : 2.00 | |
| 1st Qu.:12.0 | 1st Qu.: 26.00 | |
| Median :15.0 | Median : 36.00 | |
| Mean :15.4 | Mean : 42.98 | |
| 3rd Qu.:19.0 | 3rd Qu.: 56.00 | |
| Max. :25.0 | Max. :120.00 |
2.6 Handling references
2.6.1 Bibliographic references
References are displayed as footnotes using BibTeX, e.g. [@computo] will be displayed as (Computo Team 2020), where computo is the bibtex key for this specific entry. The bibliographic information is automatically retrieved from the .bib file specified in the header of this document (here: references.bib).
2.6.2 Other cross-references
As already (partially) seen, Quarto includes a mechanism similar to the bibliographic references for sections, equations, theorems, figures, lists, etc. Have a look at this page.
2.7 Advanced formatting
Advanced formatting features are possible and documented (including interactive plots, pseudo-code, (Tikz) diagrams, Lua filters, mixing R + Python in the same document), but are beyond the scope of this simple introduction. We point several entries in this direction.
More information
The Quarto web site for comprehensive documentation, including:
The template distributed with the Computo Quarto extension, which uses such advanced features.
Our mock version of the t-SNE paper, a full and advanced example using Python and the Jupyter kernel.
The previously published papers in Computo can be used as references.
3 Finalize your submission
3.1 Handle R dependencies with renv
To make your work reproducible, you need to fix the packages and environment used to run your analysis. For the R system, the renv package is one of the possible reliable method, supported by the community. You basically need a couple of commands to setup your environment on your local machine. First,
Code
renv::init()will initialize your repository. Then you just need to install the dependencies required to run your contribution, for instance,
Code
renv::install("ggplot2") # or equivalently install.packages("ggplot2")Non-CRAN packages (e.g. Github packages) can be used. Once you are done, you can fix everything with the command
Code
renv::snapshot()
Important
The only file that needs to be versioned by git is renv.lock. By default, the rest is ignored thanks to .gitignore.
More details for using renv can be found either
- on the
renvpackge webpage, or - on the quarto page dedicated to environments
3.2 Continuous integration
The repository associated with this template is pre-configure to trigger an action on push that performs the following:
- Check out repository on the
ubuntu-latestmachine - Install quarto and dependencies, including the Computo extension
- Install R and dependencies with
renv, using yourrenv.lockfile - Render your .qmd file and Publish the results on a gh-page (both HTML and PDF)
The file .github/workflows/build.yml is largely inspired from this file.
Once this is successful, you are ready to submit your manuscript to the Computo submission platform.
Warning
The first time, you possibly need to create the branch for the action to work. This can be done by running the following command from your computer, in your git repository:
quarto publish gh-pagesThen, set the branch gh-page as the source of your github page, and trigger the action to check that everything works fine.
3.3 Data and large files
If your submission materials contain files larger than 50MB, especially data files, they won’t fit on a git repository as is. For this reason, we encourage you to put your data or any materials you deem necessary on an external “open data” centered repository hub such a Zenodo or OSF.
References
Computo Team. 2020. “Computo: Reproducible Computational/Algorithmic Contributions in Statistics and Machine Learning.”
R Core Team. 2020. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.
Session information
Code
sessionInfo()R version 4.2.2 (2022-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.3 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so
locale:
[1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
[4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8
[7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices datasets utils methods base
other attached packages:
[1] ggplot2_3.4.0
loaded via a namespace (and not attached):
[1] knitr_1.42 magrittr_2.0.3 splines_4.2.2 munsell_0.5.0
[5] lattice_0.20-45 colorspace_2.1-0 R6_2.5.1 rlang_1.0.6
[9] fastmap_1.1.0 fansi_1.0.4 tools_4.2.2 grid_4.2.2
[13] nlme_3.1-162 gtable_0.3.1 mgcv_1.8-41 xfun_0.37
[17] utf8_1.2.3 cli_3.6.0 withr_2.5.0 htmltools_0.5.4
[21] yaml_2.3.7 digest_0.6.31 tibble_3.1.8 lifecycle_1.0.3
[25] Matrix_1.5-3 farver_2.1.1 vctrs_0.5.2 glue_1.6.2
[29] evaluate_0.20 rmarkdown_2.20 labeling_0.4.2 compiler_4.2.2
[33] pillar_1.8.1 scales_1.2.1 jsonlite_1.8.4 renv_0.16.0
[37] pkgconfig_2.0.3 Reuse
Citation
BibTeX citation:
@article{doe2023,
author = {Doe, Jane and Doe, John},
publisher = {Société Française de Statistique},
title = {Template for Contribution to {Computo}},
journal = {Computo},
pages = {undefined},
date = {2023-11-16},
url = {https://computo.sfds.asso.fr/template-computo-quarto},
doi = {xxxx},
issn = {2824-7795},
langid = {en},
abstract = {Lorem ipsum dolor sit amet, consectetur adipiscing elit.
Curabitur posuere vestibulum facilisis. Aenean pretium orci augue,
quis lobortis libero accumsan eu. Nam mollis lorem sit amet
pellentesque ullamcorper. Curabitur lobortis libero eget malesuada
vestibulum. Nam nec nibh massa. Pellentesque porttitor cursus
tellus. Mauris urna erat, rhoncus sed faucibus sit amet, venenatis
eu ipsum.}
}
For attribution, please cite this work as:
Doe, Jane, and John Doe. 2023. “Template for Contribution to
Computo.” Computo, November, undefined. https://doi.org/xxxx.