RSP: A Brief Introduction

# RSP: A Brief Introduction

by Henrik Bengtsson, 2020-07-09

Available on <a href="https://cran.r-project.org/package=R.rsp">CRAN</a> since 2005 (first version ~2002):

```r
install.packages("R.rsp")
```

```r
> library("R.rsp")

> rcat("A random number: <%= sample(1:10, size = 1) %>")
A random number: 7
```

---
# Objectives
* Dynamically generate documents and reports (and web/help pages).
* Quickly turn your favorite static report template into a dynamic one.
* Support _all_ formats, e.g. LaTeX, Markdown, HTML, ...
* Supplement and/or complement Sweave, knitr, ...
* Mix and match code and text however you want.
* Simplify sharing of template and output documents.
* Use for R package vignettes.

## Some usage
* PSCBS: PDF reports of copy-number segmentation results
* aroma-project.org: Interactive [Chromosome Explorer](http://aroma-project.org/data/reports/GSE8605/ACC,-XY,BPN,-XY,AVG,FLN,-XY,paired/ChromosomeExplorer.html) and [Array Explorer](http://www.aroma-project.org/data/reports/GSE8605/raw/ArrayExplorer.html)

---
# Compiling RSP document into PDF, HTML, ...
```r
> rfile("http://example.org/vignette.tex.rsp")
RspFileProduct:
Pathname: vignette.pdf
File size: 258.71 kB (264925 bytes)
Content type: application/pdf
Metadata 'title': 'Dynamic document creation using RSP'
Metadata 'keywords': 'Literate programming, HTML, PDF'
Metadata 'author': 'Henrik Bengtsson'
```

---
# Very simple idea: Translate RSP to R and evaluate
## 1. RSP document
```
Title: Example
Counting:<% for (i in 1:3) { %>
 <%= i %>
<% } %>
```
## 2. R script
```r
cat("Title: Example\nCounting:")
for (i in 1:3) {
  cat(" ")
  cat(i)
}
```
## 3. RSP output
```
Title: Example
Counting: 1 2 3
```

---
# RSP Markup Language
## 1. RSP comments (`<%-- ... --%>`)
## 2. RSP preprocessing directives (`<%@ ... %>`)
## 3. RSP code expressions (`<% ... %>`)

---
# RSP Markup Language
## 1. RSP comments (`<%-- ... --%>`)
```
<%-----------------------------
  Compile to PDF:
  R.rsp::rfile("report.tex.rsp")
  ------------------------------%>
\documentclass{report}
...
```
RSP comments drop anything within, e.g. private notes, other RSP constructor (nested comments too) and will never be part of the output.

---
# RSP Markup Language
## 2. RSP preprocessing directives (`<%@ ... %>`)
### Including local and online files
```
<%@include file="http://example.org/QC.tex.rsp"%>
```

### Conditional inclusion
```
<%@ifeq version="devel"%>
  <%@include file="templates/QA-devel.tex.rsp"%>
<%@else%>
  Quality assessment is still under development.
<%@endif%>
```

### Meta data
```
<%@meta title="Example"%>
\hypersetup{pdftitle=<%@meta name="title"%>}
\title{<%@meta name="title"%>}
```

RSP preprocessing directives are independent of R, i.e. they would look the same with RSP for Python.

---
# RSP Markup Language
## 3. RSP code expressions (`<% ... %>`)
### Insert value of evaluated R expressions
```
<%= sample(1:100, size = 1) %>
```

<br>

### Code snippets - mixture of RSP and text 
```
<% for (i in 1:3) { %>
 Step <%= i %>.
<% } %>
```

---
# Looping over mixtures of code and text
```
<% fit <- segmentByPairedPSCBS(data) %>

\section{Segmentation results}

<% for (chr in 1:23) { %>
  \subsection{Chromosome <%= chr %>}

<% fitT <- extractChromosome(fit, chr) %>
  PSCBS identified <%= nbrOfSegments(fitT) %> segments
  on Chr. <%= chr %>.

...
<% } # for (chr ...) %>
```

<br>

To achieve the same using noweb-style markup (e.g. Sweave and knitr) is tedious.

---
# RSP template functions
```
<%-- RSP TEMPLATES --%>
<% chromosomeSummary <- function(chr) { %>
  <% fitT <- extractChromosome(fit, chr) %>
  PSCBS identified <%= nbrOfSegments(fitT) %> segments
  on Chr. <%= chr %>.
  ...
<% } %>

<%-- DOCUMENT --%>
...
<% for (chr in 1:23) { %>
  \subsection{Chromosome <%= chr %>}
  <% chromosomeSummary(chr) %>
<% } # for (chr ...) %>
```

---
# R.rsp package - RSP engine for R
## rcat() - RSP version of cat()
```r
> rcat("A random integer in [1,100]:
        <%=sample(1:100, size = 1)%>\n")
A random integer in [1,100]: 77
```

<br>

## rsource() - RSP version of source()
Consider RSP file 'count.rsp' (think 'count.R'):

```
Counting:<% for (i in 1:10) { %>
  <% Sys.sleep(0.3) %><%= i %>
<% } %>.
```
Running this RSP script gives:

```r
> rsource("count.rsp")
Counting: 1 2 3 4 5 6 7 8 9 10.
```

---
# rfile() - end-to-end compilation
```r
> rfile("report.md.rsp", args = list(n = 50, model = "L1"))
RspFileProduct:
Pathname: report.html
File size: 42.54 kB (43564 bytes)
Content type: text/html
```

<br>

```r
> rfile("http://example.org/vignette.tex.rsp")
RspFileProduct:
Pathname: vignette.pdf
File size: 258.71 kB (264925 bytes)
Content type: application/pdf
Metadata 'title': 'Dynamic document creation using RSP'
Metadata 'keywords': 'Literate programming, HTML, PDF'
Metadata 'author': 'Henrik Bengtsson'
```

---
# Including graphics (R.devices package)
RSP-embedded LaTeX

```
\includegraphics{<%= toPDF("MyFigure,yeah,cool", {
  curve(dnorm, from = -5, to = +5)
}) %>}
```

generates the image file and outputs

```
\includegraphics{MyFigure,yeah,cool}
```

which appears as

---
# Appendix
Session info:

```
R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu Jammy Jellyfish (development branch)

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

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 utils     datasets  methods   base

other attached packages:
[1] R.devices_2.17.0  R.rsp_0.44.0      R.oo_1.24.0       R.methodsS3_1.8.1

loaded via a namespace (and not attached):
[1] compiler_4.1.2  markdown_1.1    tools_4.1.2     base64enc_0.1-3
[5] xfun_0.28       digest_0.6.29   R.cache_0.15.0  R.utils_2.11.0 
```

These slides were generated using `R.rsp::rfile()` in 0.11 secs.