Have you ever tried to find a lightweight yet nice theme for the R Markdown documents, just like this page?
With the powerful rmarkdown package, we could easily create nice HTML document by adding some meta information in the header, for example
---
title: Nineteen Years Later
author: Harry Potter
date: July 31, 2016
output:
rmarkdown::html_document:
theme: lumen
---The html_document engine uses the Bootswatch theme library to support different styles of the document. This is a quick and easy way to tune the appearance of your document, yet with the price of a large file size (> 700KB) since the whole Bootstrap library needs to be packed in.
For package vignettes, we can use the html_vignette engine to generate a more lightweight HTML file that is meant to minimize the package size, but the output HTML is less stylish than the html_document ones.
So can we do BOTH, a lightweight yet nice-looking theme for R Markdown?
The answer is YES! (At least towards that direction)
The prettydoc package provides an alternative engine, html_pretty, to knit your R Markdown document into pretty HTML pages. Its usage is extremely easy: simply replace the rmarkdown::html_document or rmarkdown::html_vignette output engine by prettydoc::html_pretty in your R Markdown header, and use one of the built-in themes and syntax highlighters. For example
The options for the html_pretty engine are mostly compatible with the default html_document (see the documentation) with a few exceptions:
theme option can take the following values. More themes will be added in the future.
highlight option takes value from github and vignette.math parameter to choose between mathjax and katex for rendering math expressions. The katex option supports offline display when there is no internet connection.code_folding, code_download and toc_float are not applicable.By default, html_pretty uses MathJax to render math expressions, for example inline math expressions \(x^2 + y^2 = z^2\), and display formulas:
\[ f(x)=\frac{1}{\sqrt{2\pi}\sigma}e^{-\frac{(x-\mu)^2}{2\sigma^2}} \]
However, using MathJax requires an internet connection. If you need to create documents that can show math expressions offline, simply add one line math: katex to the document metadata:
---
title: Nineteen Years Later
author: Harry Potter
date: July 31, 2016
output:
prettydoc::html_pretty:
theme: cayman
highlight: github
math: katex
---This option will enable KaTeX for rendering the math expressions, and all resource files will be included in for offline viewing. The offline document will be ~800k larger.
We demonstrate some commonly used HTML elements here to show the appearance of themes.
| Df | Sum Sq | Mean Sq | F value | Pr(>F) | ||
|---|---|---|---|---|---|---|
| Block | 5 | 343.3 | 68.66 | 4.447 | 0.01594 | * |
| N | 1 | 189.3 | 189.28 | 12.259 | 0.00437 | ** |
| P | 1 | 8.4 | 8.40 | 0.544 | 0.47490 | |
| K | 1 | 95.2 | 95.20 | 6.166 | 0.02880 | * |
| N:P | 1 | 21.3 | 21.28 | 1.378 | 0.26317 | |
| N:K | 1 | 33.1 | 33.14 | 2.146 | 0.16865 | |
| P:K | 1 | 0.5 | 0.48 | 0.031 | 0.86275 | |
| Residuals | 12 | 185.3 | 15.44 |
There are three kinds of lies:
Supported highlighters in prettydoc:
github: Style similar to Githubvignette: Style used by rmarkdown::html_vignetteBold, italic, don’t say this.
Familiar knitr R code and plots:
set.seed(123)
n <- 1000
x1 <- matrix(rnorm(n), ncol = 2)
x2 <- matrix(rnorm(n, mean = 3, sd = 1.5), ncol = 2)
x <- rbind(x1, x2)
smoothScatter(x, xlab = "x1", ylab = "x2")## [,1] [,2]
## [1,] -0.56047565 -0.60189285
## [2,] -0.23017749 -0.99369859
## [3,] 1.55870831 1.02678506
## [4,] 0.07050839 0.75106130
## [5,] 0.12928774 -1.50916654
## [6,] 1.71506499 -0.09514745
Also try some other languages, for example C++.
// [[Rcpp::depends(RcppEigen)]]
// [[Rcpp::depends(RcppNumerical)]]
#include <RcppNumerical.h>
using namespace Numer;
// f = 100 * (x2 - x1^2)^2 + (1 - x1)^2
// True minimum: x1 = x2 = 1
class Rosenbrock: public MFuncGrad
{
public:
double f_grad(Constvec& x, Refvec grad)
{
double t1 = x[1] - x[0] * x[0];
double t2 = 1 - x[0];
grad[0] = -400 * x[0] * t1 - 2 * t2;
grad[1] = 200 * t1;
return 100 * t1 * t1 + t2 * t2;
}
};
// [[Rcpp::export]]
Rcpp::List optim_test()
{
Eigen::VectorXd x(2);
x[0] = -1.2;
x[1] = 1;
double fopt;
Rosenbrock f;
int res = optim_lbfgs(f, x, fopt);
return Rcpp::List::create(
Rcpp::Named("xopt") = x,
Rcpp::Named("fopt") = fopt,
Rcpp::Named("status") = res
);
}