--- title: "Advanced R Markdown" subtitle: "Day 2: Customization and Extensions" author: "[Yihui Xie](https://yihui.org) and [Hao Zhu](https://haozhu233.github.io)" date: "2019/01/16 @ rstudio::conf, Austin, TX" output: xaringan::moon_reader: lib_dir: libs chakra: remark/0.14.1.min.js nature: highlightStyle: github highlightLines: true countIncrementalSlides: false beforeInit: js/macro.js --- ```{r setup, include=FALSE} options(htmltools.dir.version = FALSE, width = 50) knitr::opts_chunk$set(tidy = FALSE) ``` .center[![:image 80%, How to wake up a student](gif/sleep-clap.gif)] --- class: middle, center # Slides: http://bit.ly/arm-xie # Examples: http://bit.ly/arm-exm --- # Outline - Welcome to the command-line world - Parameterized reports - How R Markdown works: knitr + Pandoc - Pandoc's Markdown - knitr: Things you may not know - R Markdown output formats - Custom templates and formats - [**rticles**](https://github.com/rstudio/rticles): LaTeX journal articles - [**memor**](https://cran.rstudio.com/package=memor): LaTeX customization - Shiny and HTML widgets - (Optional) knitr hooks and language engines --- class: inverse, center, middle # Using R Markdown via command line --- # rmarkdown::render() - Under the hood, it calls `knitr::knit()` (`.Rmd -> .md`) and Pandoc (`.md` to other formats) - **knitr** processes code chunks and inline R expressions - Pandoc converts Markdown to other output formats - Click the Knit button (in RStudio), and get one output document - [If you run a loop](https://stackoverflow.com/q/8519128/559676), you can easily get a thousand reports ```r for (year in 1001:2000) { rmarkdown::render('input.Rmd', 'pdf_document', output_file = paste0('report-', year, '.pdf')) } ``` ```md # Report for Year `r '\x60r year\x60'` More content of input.Rmd ``` --- # Understanding the `envir` argument - `rmarkdown::render()` has an `envir` argument for the environment in which the R code in the R Markdown document is evaluated - The default is `parent.frame()`, which is usually the global environment of your workspace, unless you are calling this function inside other functions --- # A quick example A custom render function: ```r my_render = function(x) { rmarkdown::render('input.Rmd') } ``` The source of `input.Rmd`: ````md # A simple report `r ''````{r} head(x) ``` ```` Call the custom render function: ```r my_render(iris) # x will be `iris` in input.Rmd my_render(mtcars) # use `mtcars` as x now ``` --- # Parameterized reports via `params` - The `envir` argument is extremely flexible, but it may be too technical (it is not trivially easy to understand R's environments) - R Markdown introduced a special object to help you parameterize your reports - You can use either the `params` argument of `render()`, or define `params` in YAML, e.g., ```yaml title: "My Report" params: year: 2001 ``` or command line: ```r rmarkdown::render('input.Rmd', params = list(year = 2001)) ``` Command-line `params` will override `params` in YAML; `params` may contain multiple parameters. --- # Using `params` inside R Markdown Typically `params` is a list, so you can extract its elements via `$` (or `[[]]`). ```md # Report for Year `r '\x60r params$year\x60'` More content of input.Rmd ``` Render reports by a changing parameter through a loop: ```r for (year in 1001:2000) { rmarkdown::render('input.Rmd', params = list(year = year)) } ``` --- # Input parameters interactively ![Parameters via a Shiny widget](https://bookdown.org/yihui/rmarkdown/images/params-input.png) `Knit with Parameters` in RStudio. [Section 15.3.3](https://bookdown.org/yihui/rmarkdown/params-knit.html) of the R Markdown book. --- # More input controls ![Input controls](https://bookdown.org/yihui/rmarkdown/images/params-controls.png) Example: 01-params-controls.Rmd --- # Parameterized reports on RStudio Connect - https://www.rstudio.com/products/connect/ - Input parameters through the web interface of RStudio Connect - View reports built previously - Automated emails - Example [ ](https://rsc.radixu.com/connect/#/apps/3316) --- # Render & download a report in a Shiny app - Example: http://shiny.rstudio.com/gallery/download-knitr-reports.html - Source: https://github.com/rstudio/shiny-examples/tree/master/016-knitr-pdf --- # Debugging R Markdown documents - For non-trivial debugging tasks (e.g., debugging complicated functions), you have to call `rmarkdown::render()` interactively. - Inside the R Markdown document, you may use usual debugging techniques such as `debug()` or inserting `browser()` in functions. - To debug the Pandoc conversion, try `rmarkdown::render(..., clean = FALSE)`. Then intermediate files (such as `.md`) will be preserved, so you can check what's possibly wrong there. --- class: center, middle, inverse # How R Markdown works --- class: middle > Good morning, #rstats friends! I mentioned in class how learning R is a lifelong process, there isn't always a "right" answer, & our community is kind & supportive of beginners. In the spirit of being vulnerable, what's one thing in R you don't yet quite understand? > --- [Jesse Mostipak (@kierisi)](https://twitter.com/kierisi/status/1070318868609019905) -- > Anything about the inner workings of rmarkdown/knitr/pandoc. I press knit, a document appears, and I believe that anything happening in between could be actual magic. > --- [Allison Horst (@allison_horst)](https://twitter.com/allison_horst/status/1070323369600442368) --- background-image: url(https://pbs.twimg.com/media/DwKpN8RUcAAcqwm.jpg) background-size: contain class: bottom --- # The Knit button - It calls `rmarkdown::render()` - R Markdown ≈ knitr (R) + Pandoc (Markdown) - `rmarkdown::render()` ≈ `knitr::knit()` + a `system()` call to `pandoc` - R Markdown (`.Rmd`) -> `knit()` -> Markdown (`.md`) -> `pandoc` -> - `.html` - `.pdf` (LaTeX) - `.docx` - `.epub` - `.rtf` - ... --- # A minimal R Markdown document ```yaml --- title: "A Simple Regression" #---- author: "Yihui Xie" # |--> Pandoc variables date: "2019-01-02" #---- output: #---- html_document: # |--> Passed to rmarkdown toc: true #---- --- ``` ````md We built a linear regression model. `r ''````{r} fit <- lm(dist ~ speed, data = cars) b <- coef(fit) plot(fit) `r ''```` The slope of the regression is `r '\x60r b[1]\x60'`. ```` --- # Markdown output after knitting ```yaml --- title: "A Simple Regression" #---- author: "Yihui Xie" # |--> Pandoc variables date: "2019-01-02" #---- output: #---- html_document: # |--> Passed to rmarkdown toc: true #---- --- ``` ````md We built a linear regression model. ```r fit <- lm(dist ~ speed, data = cars) b <- coef(fit) plot(fit) ``` ![a plot](input_files/figure-html/unnamed-chunk-1.png) The slope of the regression is -17.57909. ```` --- # After Pandoc conversion (HTML output) ```html A Simple Regression

We built a linear regression model.

fit <- lm(dist ~ speed, data = cars)
    b   <- coef(fit)
a plot

The slope of the regression is -17.57909.

``` --- # After Pandoc conversion (LaTeX output) ```latex \documentclass{article} \title{A Simple Regression} \author{Yihui Xie} \date{2019-01-02} \begin{document} \maketitle We built a linear regression model. \begin{verbatim} fit <- lm(dist ~ speed, data = cars) b <- coef(fit) plot(fit) \end{verbatim} \begin{figure} \includegraphics{input_files/figure-html/unnamed-chunk-1.png} \caption{a plot} \end{figure} The slope of the regression is -17.57909. \end{document} ``` --- class: center # Same ducks, different masks ![dog masks of ducks](gif/duck-dog-mask.gif) --- class: center, middle, inverse ## The (R) Markdown philosophy ### Similar to KISS # Keep the Duck Simple and Stupid ### and wear a mask as fancy as you want --- # Pandoc's Markdown - You should read the Pandoc Manual at least once to learn the possibilities of Pandoc's Markdown: https://pandoc.org/MANUAL.html#pandocs-markdown - Original Markdown ([John Gruber](https://daringfireball.net/projects/markdown/)) - primarily for HTML - paragraphs, `# headers`, `> blockquotes` - `**bold**`, `_italic_` - `- lists` - `[text](url)` - `![text](image)` - code blocks (indent by four spaces) --- # Pandoc's Markdown - Markdown extensions - YAML metadata - LaTeX math `$\sum_{i=1}^n \alpha_i$` = $\sum_{i=1}^n \alpha_i$ - syntax highlighting of code blocks (three backticks followed by the language name, e.g. ```` ```r ````) - tables - footnotes `^[A footnote here.]` - citations `[@joe2014]` (database can be BibTeX or in YAML) - raw HTML/LaTeX --- # Pandoc's Markdown - Types of output documents - LaTeX/PDF, HTML, Word (MS Word, OpenOffice) - beamer, ioslides, Slidy, reveal.js - E-books - ... --- class: center, middle background-image: url(https://pandoc.org/diagram.jpg) background-size: cover # https://pandoc.org --- # Command-line usage of Pandoc Some examples: ```sh pandoc test.md -o test.html pandoc test.md -s --mathjax -o test.html pandoc test.md -o test.odt pandoc test.md -o test.rtf pandoc test.md -o test.docx pandoc test.md -o test.pdf pandoc test.md --pdf-engine=xelatex -o test.pdf pandoc test.md -o test.epub ``` To run system commands in R, use functions `system()` or `system2()`. The **rmarkdown** package provides a helper function `rmarkdown::pandoc_convert()` to convert Markdown documents to other formats using Pandoc. When you click the Knit button in RStudio, you will see the actual (usually very long) command that is executed. ??? You can use `rmarkdown::render(clean = FALSE)` to keep the intermediate .md, and run the `pandoc` command for debugging purposes. --- # Example: Markdown in the eyes of Pandoc ## The Pandoc abstract syntax tree (AST) Let's explore a Markdown file with R: ```{r} f1 = tempfile() # pandoc -f markdown -t json ... rmarkdown::pandoc_convert( "2019-rstudio-arm/02-markdown-data.md", to = "json", from = "markdown", output = f1, wd = "." ) # read JSON into R x = jsonlite::fromJSON(f1, simplifyVector = FALSE) ``` --- ```{r, comment='', highlight.output=c(4,6)} str(x) # original Markdown data ``` --- [How to change `##` to `#`?](https://stackoverflow.com/q/54204380/559676) Or in general, level-N headers to level-(N-1) headers? ```{r} # a recursion into the list to modify header levels raise_header = function(x) { lapply(x, function(el) { if (!is.list(el)) return(el) if (identical(el[["t"]], "Header")) { lvl = el[["c"]][[1]] if (lvl <= 1) stop("I don't know how to raise the level of h1") el[["c"]][[1]] = as.integer(lvl - 1) #<< } raise_header(el) }) } x = raise_header(x) ``` --- ```{r, comment='', highlight.output=c(4,6)} str(x) # modified Markdown data ``` --- ```{r, comment=''} f2 = tempfile() # to write out (the modified) JSON f3 = tempfile() # to write out Markdown xfun::write_utf8(jsonlite::toJSON(x, auto_unbox = TRUE), f2) rmarkdown::pandoc_convert( f2, to = "markdown", from = "json", output = f3, options = "--atx-headers", wd = "." ) xfun::file_string(f3) unlink(c(f1, f2, f3)) ``` --- # More power (and speed) with Lua filters Rewrite the previous R function with a Lua filter `raise-header.lua`: ```lua `r xfun::file_string("2019-rstudio-arm/raise-header.lua")` ``` Run it: ```sh pandoc -t markdown --lua-filter=raise-header.lua 02-markdown-data.md ``` More about Lua filters: https://pandoc.org/lua-filters.html --- # The Pandoc version - RStudio has bundled a version of Pandoc, so you don't need to install Pandoc separately if you use RStudio - If you install Pandoc by yourself, **rmarkdown** will use the highest version of Pandoc that it can find - Check `rmarkdown::pandoc_version()` - RStudio 1.1.x included Pandoc 1.19.x; RStudio 1.2.x will include Pandoc 2.x - Pandoc 2.x is not fully compatible with 1.x, but we have solved these issues in the **rmarkdown** package and other R packages we maintain (e.g., `--latex-engine` was renamed to `--pdf-engine`) --- class: middle, center, inverse # knitr ## the other cornerstone of R Markdown --- class: center [![the knitr book](https://db.yihui.org/imgur/yYw46aF.jpg)](https://amzn.com/1498716962) The **knitr** book is a comprehensive guide, but is unfortunately [not free](https://amzn.com/1498716962). Stay tuned for a free book this year. --- # knitr is not only for R - It contains many, many other language engines: https://bookdown.org/yihui/rmarkdown/language-engines.html - For example, Shell/Bash scripts, SQL, Python, C, C++, Fortran, Stan, ... - Demo of two engines: `python` and `asis`. ````markdown `r ''````{python} x = 42 print(x) ``` ```` ````markdown `r ''````{asis, echo=identical(knitr:::pandoc_to(), 'html')} Here is _some text_ that you want to display only when the output format of R Markdown is **HTML**. You can write arbitrary Markdown content in this chunk. ``` ```` --- # knitr is not only for Markdown, either R Markdown may be the most popular document format, but you could also use other authoring languages such as LaTeX, HTML, AsciiDoc, and reStructuredText. Demo: `*.Rnw`, `*.Rhtml` --- # knitr works on R scripts, too - Most of time you may be using `knitr::knit()`, but sometimes you may want `knitr::spin()`. - `knitr::spin()` first converts an R script to R Markdown (or other document formats that `knitr::knit()` supports, such as `*.Rnw`). - If you use RStudio, you can click the button "Compile Report" on the toolbar. - Demo: https://github.com/yihui/knitr/blob/master/inst/examples/knitr-spin.R --- # The chunk option include=FALSE Have you ever used these chunk options? ````markdown `r ''````{r, echo=FALSE, results='hide'} ``` ```` or ````markdown `r ''````{r, echo=FALSE, results='hide', message=FALSE, warning=FALSE} ``` ```` or even ````markdown `r ''````{r, echo=FALSE, results='hide', message=FALSE, warning=FALSE, fig.show='hide'} ``` ```` You probably only need a single chunk option `include=FALSE`: https://yihui.org/en/2017/11/knitr-include-false/. --- # Conditional evaluation/inclusion Include a chunk in the output only if the output format is `html`: ````markdown `r ''````{r, include=identical(knitr:::pandoc_to(), 'html')} # blabla ``` ```` Helper functions `knitr::is_latex_output()` (`latex` or `beamer`) and `knitr::is_html_output()` (`html`, `ioslides`, `slidy`, ...). Evaluate a code chunk only if the output format is LaTeX: ````markdown `r ''````{r, eval=knitr::is_latex_output()} # blabla ``` ```` BTW, the [**tufte**](https://github.com/rstudio/tufte) package makes heavy use of these functions so that its functions work for both HTML and LaTeX output, e.g., `tufte::newthought()`. --- # Live-preview HTML output documents - Tired of clicking the Knit button to view your results? - Just use `xaringan::inf_mr('your.Rmd')`. - `install.packages('xaringan')` - You can also use the RStudio addin "Infinite Moon Reader". - Demo - For more info, see - https://bookdown.org/yihui/rmarkdown/compile.html - https://bookdown.org/yihui/rmarkdown/xaringan-preview.html - https://yihui.org/en/2017/08/why-xaringan-remark-js/ --- class: center ![:image 300px, sit back and relax](gif/dog-motor.gif) --- # knitr::knit_watch() Watch an input file continuously, and knit it when it is updated, e.g., ```r library(knitr) knit_watch('foo.Rnw', knitr::knit2pdf) knit_watch('foo.Rmd', rmarkdown::render) ``` This function works for any documents with any output formats, but unlike `xaringan::inf_mr()`, it does not automatically refresh the output page. However, if the output format is PDF, your PDF viewer might be able to automatically refresh the page when the PDF has been updated. --- # Caching - The chunk option `cache=TRUE` - Basic idea: if nothing has changed from the previous run, just load the results instead of executing the code chunk again. ````markdown `r ''````{r cache=TRUE} Sys.sleep(10) # pretend this is a time-consuming code chunk ``` ```` - Further reading (why caching is one of the two hard things in computer science): https://yihui.org/en/2018/06/cache-invalidation/ --- class: center ![:image 70%, caching can make your code fast](gif/get-into-the-car.gif) --- # You can generate animations from R plots - Requires `install.packages('gifski')` - Demo ````markdown `r ''````{r, animation.hook='gifski'} for (i in 0:1) { pie(c(i, 6), col = c('red', 'yellow'), labels = NA) } ``` ```` -- .center[![:image 50%, Pacman](https://user-images.githubusercontent.com/163582/44246516-30c93000-a1a4-11e8-8aa5-8876e51a227f.gif)] ??? The only valid use case of pie charts. --- - You may also use FFmpeg (https://ffmpeg.org) (easy to install for macOS users using Homebrew: `brew install ffmpeg`) ````markdown `r ''````{r, animation.hook='ffmpeg', ffmpeg.format='gif', dev='jpeg'} for (i in 0:1) { pie(c(i, 6), col = c('red', 'yellow'), labels = NA) } ``` ```` The animation format is specified by the chunk option `ffmpeg.format`. It could be `gif`, `mp4`, `webm`, or any other formats that FFmpeg supports. - You may use `cache=TRUE` when the animation takes long time to generate. - The [**gganimate**](https://cran.r-project.org/package=gganimate) package works out of the box with **knitr** (`ggplot(...) + transition_*(...)` in a code chunk). --- class: center ![:image 70%, enjoy your own animations](gif/pixar.gif) --- # Reuse a code chunk - If you want to reuse the code from a chunk, don't copy and paste. - Three ways: 1. Use the same label, but leave the chunk empty. Useful when you want to run the same code twice with different chunk options. 1. Use the `ref.label` option, and leave the chunk empty; `ref.label` can be a vector of chunk labels. 1. Use the `<>` syntax to embed one chunk in another. - Demo - More info: https://yihui.org/knitr/demo/reference/ --- # Child documents Don't want to write everything in a single document? You can use child documents, and include them in the main document via the `child` option, e.g., ````markdown `r ''````{r, child=c('one.Rmd', 'another.Rmd')} ``` ```` You can also be creative, e.g., conditionally include child documents: ````markdown `r ''````{r, child = if (p.value < 0.05) 'one.Rmd' else 'another.Rmd'} ``` ```` Remember: **knitr**'s chunk options can be arbitrary valid R code, so feel free to use `if`-statements. --- # knitr::knit_expand() ```r library(knitr) knit_expand(text = "The value of pi is {{pi}}.") knit_expand( text = "The value of a is {{a}}, so a + 1 is {{a+1}}.", a = rnorm(1) ) ``` More info: https://cran.rstudio.com/web/packages/knitr/vignettes/knit_expand.html --- # knitr::knit_expand() with file templates A (child) template document `template.Rmd`: ````markdown # Regression on {{i}} `r ''````{r lm-{{i}}} lm(mpg ~ {{i}}, data = mtcars) ``` ```` Build linear regression models using all variables against `mpg` in the `mtcars` dataset: ````markdown Below are ten regression models: `r ''````{r, echo=FALSE, results='asis'} src = lapply(names(mtcars)[-1], function(i) { knitr::knit_expand('template.Rmd') }) res = knitr::knit_child(text = unlist(src)) # knit the source cat(res, sep = '\n') ``` ```` --- # knitr::fig_chunk() - When you draw a plot in a code chunk, but want to show it elsewhere (not in the code chunk), `knitr::fig_chunk()` gives you the path to the plot file. ````markdown `r ''````{r cars-plot, fig.show='hide'} plot(cars) ``` Bla bla... ![a figure moved here](`r "\x60r knitr::fig_chunk('cars-plot', 'png')\x60"`) ```` - More info: https://yihui.org/en/2017/09/knitr-fig-chunk/ --- # knitr::write_bib() ```{r warning=FALSE, comment='', class.output='bibtex'} knitr::write_bib(c('knitr', 'shiny')) ``` --- Normally you want to write citation entries to a file (the default is to write to the R console), e.g., `write_bib(..., file = 'references.bib')`. What I often do: ````markdown --- title: "My Report" bibliography: references.bib --- Cite @R-knitr or [@R-shiny]. `r ''````{r, include=FALSE} knitr::write_bib(c(.packages(), 'shiny'), file = 'references.bib') ``` ```` --- # knitr::knit_print() - Visible objects in code chunks are printed through this S3 generic function - You can register custom printing methods - See the vignette for details: https://cran.rstudio.com/web/packages/knitr/vignettes/knit_print.html - The [**printr**](https://github.com/yihui/printr) package - Example `03-knit_print.Rmd` --- class: center, middle, inverse # R Markdown output formats --- # R Markdown output formats - An output format is an abstraction in **rmarkdown** as a uniform (programming) interface to deal with - **knitr** options (chunk options, hooks, package options, ...) - pandoc options (`--from`, `--to`, `--bibliography`, ...) - pre/post-processors - and other options (e.g., whether to keep the intermediate .md) - Can be created via `rmarkdown::output_format()` - Note the `base_format` argument: output formats are _extensible_. If you only want to modify a few options of an existing format, you can use it as the base, e.g., you can add a custom post-processor on top of the existing one. --- # Built-in formats `r knitr::combine_words(grep('^[^_]+_(document|presentation)$', ls(asNamespace('rmarkdown')), value = TRUE), sep = '\n\n', and = '', before = '- \x60', after = '\x60')` --- # YAML options for output formats The YAML metadata ```yaml --- output: html_document: toc: true theme: "united" fig_height: 6 --- ``` will be translated to ```r rmarkdown::render( 'input.Rmd', * html_document( * toc = TRUE, * theme = "united", * fig_height = 6 * ) ) ``` --- # Example: html_document() ```{r comment=''} str(rmarkdown::html_document()) ``` --- # Example: html_document() Some options: - `theme`: you can set it to `NULL` to reduce the HTML file size significantly (because of Bootstrap) - `css`: tweak the styles of certain elements - `template`: a custom Pandoc template --- # Pandoc templates - Official Pandoc templates: https://github.com/jgm/pandoc-templates - **rmarkdown**'s templates: https://github.com/rstudio/rmarkdown/tree/master/inst/rmd --- # A minimal HTML template ```html * $title$ $for(css)$ $endfor$ * $body$ ``` --- # A minimal LaTeX example ```latex \documentclass{article} \begin{document} *$body$ \end{document} ``` --- # Simple customization There are many options you can set in YAML. Two types of options: - Options for Pandoc: make sure you read the Pandoc manual to know the possible options (e.g., for LaTeX output: https://pandoc.org/MANUAL.html#variables-for-latex). ```yaml fontsize: 12pt documentclass: book monofont: "Source Code Pro" # for XeLaTeX output ``` - Options for an R Markdown output format in the `output` field in YAML: consult the specific R help page. You can certainly create your own template, but it may not be necessary to do so if your problem can be solved by setting a few options in YAML. --- # A crash course on HTML/CSS/JavaScript? ```yaml output: html_document: css: ["style.css", "another.css"] ``` or ````markdown `r ''````{css, echo=FALSE} p { color: red; } ``` ```` Learn to use the Developer Tools of your web browser. They are very powerful! --- # Custom Word/PPT templates Idea: generate an arbitrary document with Pandoc first, customize the style of this document, and use it as the "reference document". ```yaml output: word_document: reference_docx: "word-template.docx" powerpoint_presentation: reference_doc: "powerpoint-template.pptx" ``` PowerPoint output requires Pandoc 2.x, which has been bundled in RStudio 1.2.x (currently a [preview version](https://www.rstudio.com/products/rstudio/download/preview/)). --- # Deeper customization A common use case: inject a snippet of code to the HTML `` (e.g., JS/CSS code), or the LaTeX preamble (e.g., load some LaTeX packages before `\begin{document}`). ```yaml output: html_document: includes: in_header: "header.html" before_body: "before.html" after_body: "after.html" pdf_document: includes: in_header: "preamble.tex" ``` Even deeper customization? Sure, write a package with custom output formats! Let's study a few relatively simple examples in **rmarkdown** first. --- background-image: url(gif/jump-off.gif) background-size: contain class: bottom, center ## Take a deep breath and read some source code! --- # Example: latex_fragment ```{r, comment=''} rmarkdown::latex_fragment ``` - https://github.com/rstudio/rmarkdown/blob/b209cdc/R/pdf_document.R#L252-L256 - The key: use a custom template https://github.com/rstudio/rmarkdown/blob/master/inst/rmd/fragment/default.tex - Similarly: https://github.com/rstudio/rmarkdown/blob/master/R/html_fragment.R and https://github.com/rstudio/rmarkdown/blob/master/inst/rmd/fragment/default.html --- # Example: powerpoint_presentation A minimal example of the PowerPoint output format (not really `rmarkdown::powerpoint_presentation`): ```{r, eval=FALSE} powerpoint_presentation = function(pandoc_args = NULL) { rmarkdown::output_format( knitr = list(), pandoc = rmarkdown::pandoc_options( to = 'pptx', #<< args = pandoc_args ) ) } ``` --- # Example: rtf_document - https://github.com/rstudio/rmarkdown/blob/master/R/rtf_document.R - pre-processor (protect raw RTF content) - post-processor (restore raw RTF content) - raw RTF looks like this ```rtf {\rtf1\ansi{\fonttbl\f0\fswiss Helvetica;}\f0\pard This is some {\b bold} text.\par } ``` --- class: inverse, center, middle # Custom Templates and Formats --- # Hao Zhu's session https://arm.rbind.io/days/day2/ --- class: center, middle, inverse # Shiny documents --- # Shiny documents vs Shiny apps - R Markdown + `runtime: shiny` in YAML - In a Shiny document, you render output wherever you need it in the document. No need to write a UI. A Shiny app requires both a UI and the server logic (`shiny::shinyApp(ui = ..., server = ...)`). - In other words, the R Markdown document itself is the _implicit_ UI. --- # Render output inline - I assume most people are familiar with using `shiny::renderXXX()` in code blocks. - You can also `renderXXX()` in an inline R expression in R Markdown. - https://shiny.rstudio.com/gallery/inline-output.html - Source: https://github.com/rstudio/shiny-examples/blob/master/026-shiny-inline/index.Rmd -- - Potential application: a recipe website? I really need this for making moon cakes. --- # Delayed rendering - Wrap your `renderXXX()` in `rmarkdown::render_delayed()` to delay rendering output until the document has been compiled. - Useful when the Shiny output takes long time to render. - Demo ````markdown `r ''````{r, echo = FALSE} numericInput("rows", "How many cars?", 5) rmarkdown::render_delayed({ # Sys.sleep(6) renderTable({ head(cars, input$rows) }) }) ``` ```` --- class: center, middle, inverse # HTML widgets --- # HTML widgets - (Often interactive) JavaScript applications created from R and displayed on HTML pages - Can be viewed (1) as a standalone page when printed in the R console (2) in R Markdown output documents (HTML) (3) in Shiny apps - You can pretty much think them like normal R plots - See [Chapter 16](https://bookdown.org/yihui/rmarkdown/html-widgets.html) of the R Markdown book --- # The three components - R binding: pass data and options from R to JS - JS binding: receive data from R and create the widget - A YAML configuration file to specify HTML/JS/CSS dependencies --- # A self-contained minimal example ```r blink = function(text, interval = 1) { htmlwidgets::createWidget( 'blink', * x = list(text = text, interval = interval), dependencies = htmltools::htmlDependency( 'blink', '0.1', src = c(href = ''), head = ''))} ``` --- # Example: the sigma package - Source: https://github.com/jjallaire/sigma - sigma.js: http://sigmajs.org - Basic file structure: ```md R/ | sigma.R inst/ |-- htmlwidgets/ | |-- sigma.js | |-- sigma.yaml | |-- lib/ | | |-- sigma-1.0.3/ | | | |-- sigma.min.js | | | |-- plugins/ | | | | |-- sigma.parsers.gexf.min.js ``` --- # sigma.yaml ```yaml dependencies: - name: sigma version: 1.0.3 src: htmlwidgets/lib/sigma-1.0.3 script: - sigma.min.js - plugins/sigma.parsers.gexf.min.js ``` --- # sigma.R ```r sigma = function(gexf, drawEdges = TRUE, drawNodes = TRUE, width = NULL, height = NULL) { # read the gexf file data = paste(readLines(gexf), collapse = "\n") # create a list that contains the settings settings = list(drawEdges = drawEdges, drawNodes = drawNodes) # pass the data and settings using 'x' x = list(data = data, settings = settings) # create the widget htmlwidgets::createWidget( "sigma", x, width = width, height = height ) } ``` --- # sigma.js ```js HTMLWidgets.widget({ name: "sigma", factory: function(el, width, height) { // create our sigma object and bind it to the element var sig = new sigma(el.id); return { renderValue: function(x) { // apply settings for (var name in x.settings) sig.settings(name, x.settings[name]); // update the sigma object sigma.parsers.gexf( x.data, sig, ... ``` --- # Demo ```r remotes::install_github("jjallaire/sigma") sigma::sigma( system.file("examples/ediaspora.gexf.xml", package = "sigma") ) ``` --- # Shiny output wrappers ```r # UI wrapper sigmaOutput = function(outputId, width = "100%", height = "400px") { htmlwidgets::shinyWidgetOutput( outputId, "sigma", width, height, package = "sigma" ) } # use in the server logic renderSigma = function(expr, env = parent.frame(), quoted = FALSE) { if (!quoted) { expr = substitute(expr) } # force quoted htmlwidgets::shinyRenderWidget( expr, sigmaOutput, env, quoted = TRUE ) } ``` --- # HTML widgets for non-HTML output - HTML widgets are for HTML output formats (of course!). What if we embed a widget in a PDF document? In this case, **knitr** will take a screenshot of the widget automatically if you have installed **webshot** and PhantomJS: ```r install.packages("webshot") webshot::install_phantomjs() ``` - Demo ````markdown `r ''````{r} DT::datatable(iris) ``` ```` --- class: center, middle, inverse # Misc topics (time permitting) --- # knitr hooks - Chunk hooks: you can run extra code before/after each code chunk - Output hooks: you have control over every single piece of the output (text, plots, messages) - https://yihui.org/knitr/hooks/ --- # Chunk hooks A chunk hook is a function with three arguments (the latter two are optional). Register the hook function via `knitr::knit_hooks$set()`: ```r knitr::knit_hooks$set(HOOK_NAME = function(before, options, envir) { if (before) { # code to run before a chunk } else { # code to run after a chunk } }) ``` --- Chunk hooks are triggered when the corresponding chunk option is not `NULL`, e.g., ````markdown `r ''````{r include=FALSE} knitr::knit_hooks$set(small_mar = function(before, options, envir) { if (before) par(mar = c(4, 4, .1, .1)) }) ``` `r ''````{r small_mar=TRUE} plot(cars) ``` ```` Of course, you can set the option globally so that the hook is executed for all chunks: ```r knitr::opts_chunk$set(small_mar = TRUE) ``` --- Use your imagination. ```r knitr::knit_hooks$set(tweet = function(before, options, envir) { if (before) { rtweet::post_message("I have started the computation, my lord.") } else { rtweet::post_message("The MCMC has converged!") } }) ``` --- # Output hooks Hook names preserved for output: ```{r} names(knitr::knit_hooks$get()) knitr::knit_hooks$get('inline') ``` --- # Example: truncate long text output [Example 052](https://github.com/yihui/knitr-examples/blob/master/052-suppress-output.Rmd): https://github.com/yihui/knitr-examples/ ```{r} knitr::knit_hooks$set(output = local({ # the default output hook hook_output = knitr::knit_hooks$get('output') function(x, options) { if (!is.null(n <- options$out.lines)) { x = knitr:::split_lines(x) if (length(x) > n) { # truncate the output x = c(head(x, n), '....\n') #<< } x = paste(x, collapse = '\n') # paste first n lines together } hook_output(x, options) } })) ``` --- ```{r, comment=''} 1:100 # normal and full output ``` ````markdown `r ''````{r out.lines=3} 1:100 # truncated output ``` ```` ````{r out.lines=3,echo=FALSE, comment=''} 1:100 ``` --- # knitr's language engines See [Section 2.7](https://bookdown.org/yihui/rmarkdown/language-engines.html) of the R Markdown book for some examples. ```{r} names(knitr::knit_engines$get()) ``` For curious hackers: https://github.com/yihui/knitr/blob/master/R/engine.R --- # A minimal Python engine You can execute Python code via the command line `python -c 'YOUR CODE'`. ```{r} knitr::knit_engines$set(py = function(options) { code = paste(options$code, collapse = '\n') out = system2('python', c('-c', shQuote(code)), stdout = TRUE) knitr::engine_output(options, code, out) }) ``` Now you can use the new engine `py`, e.g., ````markdown `r ''````{py} print(1 + 1) ``` ```` --- Use your imagination. Language engines don't have to involve command-line tools. I give you the code and chunk options. You do whatever you like. ```{r} knitr::knit_engines$set(upper = function(options) { if (!options$eval) return() # don't run this chunk code = paste(options$code, collapse = '\n') toupper(code) }) ``` ````markdown `r ''````{upper} Hello, knitr engines! ``` ```` ```{upper} Hello, knitr engines! ``` --- class: center, middle # Thank you! ## All materials can be found at https://arm.rbind.io You will receive an email request to fill out a workshop feedback survey at the end of the day. We will truly appreciate it if you could fill it out to help us improve our workshops in the future. ![:image 20%, RStudio logo](gif/logo.png)