Ndtyjky

I am putting together a website using Blogdown/Hugo. I am 'manually' assembling the code and output rather than dynamically knitting with knitr as I didn't want to upload the dataset.

So, I'm using a css style to put borders around the code, etc.

This is all working as I want it to. But, is there a way to also have the syntax highlighting show in the rendered .html page? For example, if I run this using the code below, the html output is the first screengrab,

and I'd like the code coloured as in the second screengrab.

<style>

div.code pre { 

                font-family: 'Source Code Pro', 'Courier New', monospace;

                font-size: 12px;

                background-color:#F5F8FA;

                padding-top: 10px;

                padding-bottom: 10px;

                padding-left: 10px;

                border: 1px solid lightgrey;

                border-radius: 5px;

}

</style>



<style>

div.output pre { 

                font-family: 'Source Code Pro', 'Courier New', monospace;

                font-size: 12px;

                padding-top: 10px;

                padding-bottom: 10px;

                padding-left: 10px;

                border: 1px solid lightgrey;

                border-radius: 5px;

}

</style>





```{r setup, include=FALSE}

knitr::opts_chunk$set(collapse = T)

```



```{r, echo=FALSE}

library(rmarkdown) #used for syntax highlighting in this document

```





### Descriptives



The basic frequency histogram for Left and Right eye data, constructed with ggplot2.



<div class = "code">

```{r hist, eval=F}

hist_va <-ggplot(data, aes(x = bcva, fill = bcva < -0.1)) +

  geom_histogram(color = "black",  binwidth = 0.05, center = 0.025) +

  scale_x_continuous(limits = c(-0.4, 0.4), breaks = seq(-0.4, 0.4, 0.1)) +

  theme(legend.position = "none") +

  xlab("Best Corrected Visual Acuity (logMAR)") +

  ylab("Frequency ") +

  scale_fill_manual(values = c("white", "red")) +

  facet_grid(. ~ eye)

```

</div>





Then overlaying the classification thresholds for SuperHuman vision.



<div class = "output">

```{r hist2, eval=F}

##  hist_va + 

##  geom_vline(data = data, aes(xintercept = -0.097, color = "red"), linetype = "dashed") +

##  geom_text(aes(-0.25, 420, label = "Superhuman Vision", color = "red"))

```

</div>